short-lived access tokens and long-lived refresh tokens

https://clickamericana.com/topics/science-technology/vintage-portable-manual-typewriters

The Smith-Coronas were offered in 4 different colors.

The Remington Quiet-Riter was eventually offered in white sand, desert sage, mist green, and French gray,

The Royal HH was offered in 6 colors including green, pink, and blue. Brown was the most ubiquitous.

Why bother with dozens of big standards in your office when you can have a portable or two that you can move and which are always in demand?

100% The Practical Magazine of Efficient Management, November 1916, Volume 7, No. 45, p49. https://www.google.com/books/edition/Management/hqj2SD6khL4C?hl=en&gbpv=1&dq=corona&pg=RA4-PA49&printsec=frontcover

Origin of Royal's Vogue by [[x over it]]

Remington Quie- Riter Typewriter 1955

"students who use typewriters get up to 38% better grades."

"gives book reports and themes a professional look"

gendered sales technique - "girls particularly appreciate" the easy change ribbon system...

VINTAGE 1958 COMMERCIAL - REMINGTON RAND - QUIET WRITER TYPEWRITER w/FABULOUS FOUR

VINTAGE 1958 COMMERCIAL - REMINGTON RAND - OFFICE-RITER TYPEWRITER

Up to 10 carbons!<br /> Cuts clear, clean stencils 149.50 plus carrying case additional<br /> $1.50 a week payable monthly

Successful Secretary Presented by Royal Office Typewriters. A Thomas Craven Film Corporation Production, 1966. https://www.youtube.com/watch?v=If5b2FiDaLk.

Script: Lee Thuna<br /> Educational Consultant: Catharine Stevens<br /> Assistant Director: Willis F. Briley<br /> Design: Francisco Reynders<br /> Director & Producer: Carl A. Carbone<br /> A Thomas Craven Film Corporation Production

"Mother the mail"

gendered subservience

"coding boobytraps"

"I think you'll like the half sheet better. It is faster." —Mr. Typewriter, timestamp

A little bit of the tone of "HAL" from 2001: A Space Odyssey (1968). This is particularly suggestive as H.A.L. was a one letter increment from I.B.M. and the 1966 Royal 660 was designed to compete with IBM's Selectric

This calm voice makes suggestions to a secretary while H.A.L. does it for a male astronaut (a heroic figure of the time period). Suddenly the populace feels the computer might be a bad actor.

"We're living in an electric world, more speed and less effort."—Mr. Typewriter<br /> (techno-utopianism)

interesting, we jump back to ww1 versus 1800s, tragedy of great power politics vibes

Very interesting manuscript. The combination of yeast display data with AF3 structure prediction makes a compelling case for using in silico methods (AF3 and CamSol) to rapidly and conservatively identify promiscuous VHH binders across multiple targets. A couple of suggestions that might improve readability and deepen the interpretation:

Figure 2 and beyond: The clustering and FACS plots use three shades of blue to distinguish mono- and polyspecific VHHs, and the shades are close enough that they're hard to tell apart at a glance. Increasing the contrast in brightness (or switching to a more distinguishable palette) would make these figures easier to read.

Figure 3C: The 0.8 ipTM cutoff is used to separate binders from nonbinders, but it would help to see how ipTM tracks with the FACS fluorescence signal directly — e.g., a secondary axis or a simple correlation plot. That would let readers judge whether 0.8 is the right cutoff for this specific interaction, or just the field-standard benchmark being applied by convention.

Detection systems: I was surprised to see two such different detection systems used (AF-488 and PE) rather than, say, two AlexaFluor variants — different fluorophores and detection modes can have very different dynamic ranges, and AF-488 in particular has a smaller dynamic range than PE. It would help to know why these specific systems were chosen, since more comparable fluorophores might have made the results across conditions easier to compare directly.

I have not yet followed up with this trend on social media. Personally, I find the hashtag as a pound sign symbol.

Title: Family / Memory

Significance: This is the highpoint of the poem. It represents the thesis of what is the legacy. In this section the author reveals that the legacy which is inherited is not a recipe for baking, but than manner in which the two protagonists express their deep caring and protectiveness of one another by not expressing these openly.

Topic: Identity / Belonging

Significance: On the surface, this quotation highlights a classic generational clash. The child's defensive stance ("lips poked out") shows her trying to assert an independence from grandmother's attempt to impose traditional expectations.

Topic - Cultural heritage / family

Why it matters: Baking the rolls is not just a cooking instruction but the grandmother expressing her domestic heritage and ensuring its survival with pride and identity she wants it to pass on because it is apart of her identity.

Label: Characterization / Dialogue

Explanation: Giovanni used “African American Vernacular English” and behavioral description also hence “lips poked out” to create a realistic and cultural interaction between the characters. The switch from polite 'yes, madam' shows a transition of attitude which suggests an emotional fear of eventual loss that the child is covering up using acts of independence.

Question: Is the grandmother's understanding to the girls actual motives highlighted by the reaction she gives? Is she angered by her stubbornness or secretly understood the emotional attachment and fear the girl has?

Question: What do you understand by the word 'dependent'? What is being criticised, dependence of the childhood on the other or a beauty expression of spiritual relation that the child does not want to get damaged?

Pattern 2: Repetition of Unspoken Thoughts ("say/said/meant")

Passage: even if she couldn’t say it, so she said, never said what they meant

Significance: Repeatedly used is a form of the word say that emphasizes the key irony of the poem: language is uttered, but there is no communication. Love is felt and acted on, yet it is never said.

Label: Speaker / Tone

Explanation: The speaker is an omniscient, reflective observer, emerging only at the end and changes from a seemingly nostalgic memory of a distant past recounting to a slightly cynic but empathetic commentary on human loneliness and failure to communicate.

Module 2: Who gets to belong, speak, and succeed in society and who decides?

The text addresses the dialogue that happens when some people " speak" about themselves, others " listen" to them; with the tools they possess, either through the "African American Vernacular English" adopted by the grandmother or in the childhood expression of the daughter through " lips poked out" when society on hand dictates that certain speech must conform to formalized rules of diction. Not only are the terms of their conversation in their own little household their own choices and they are still left with broken conversation where they cannot express what they mean; true " belonging" becomes complicated where there is this gap; love, depending on the few terms society give, cannot be said.

Pattern 1: Lowercase Structure and Lack of Punctuation

Passage: He entire poem uses lowercase letters (even for "I") and avoids periods or commas until the final implied pause.

Significance: The conversational, stream-of-consciousness layout resembles the movement of memory as well as oration. The grandmother and granddaughter are depicted with no obvious lines or barriers which conveys how entangled are their, lives as well as their spirits, together their memories and legacies together.

Prediction: Given the title "legacies", it is likely that the text deals with traditions, memories or emotional habits that continue to exist within a family throughout different generations, in spite of tensions or unwillingness among family members.

Question: Why did the author entirely lowercase the title and the text? What does this suggest about the tone/format of the memory?Bold

eLife Assessment

This valuable study investigates the neural basis for recovery of complex wheel running behaviour following a unilateral spinal cord injury in mice. By combining behavioural analyses, whole-brain mapping, and tracing techniques, the authors provide incomplete evidence that new cortico-medullary connections can drive effective motor recovery. The paper could be strengthened with manipulations to establish causality, a more fine-grained analysis of the behaviour, and some reorganisation of how the data are presented and discussed.

Reviewer #1 (Public review):

Summary:

The authors seek to understand and identify the neural plasticity that underlies recovery from precise unilateral hemi-pyramidotomy. The corticospinal tract is severed on one side in the pyramids below the exit of corticoreticular projections. Recovery from the injury is achieved with an intensive wheel running rehabilitation regime. The anatomical sites of plasticity, the importance of plasticity in different reticular areas<br /> to recovery, and the impact of the degree of plasticity observed on recovery as correlated predictors, are shown.

Strengths:

Refined anatomical analysis using mouse line and genetic and viral intersectional tracing identifies specific reticular targets of likely enhanced cortical control that correlate with recovery of locomotor skill.

Weaknesses:

(1) The study is correlational at this time. This does not undercut the value of the data and the identification of targets of plasticity achieved in the work.

(2) Generalization of motor gains beyond locomotion was not tested. Reach-to-grasp tasks for feeding were not tested.

(3) Some discussions and use of the terms fine motor and skilled motor are fuzzy, and the limitations of the study are not sufficiently clearly stated.

Reviewer #2 (Public review):

Summary:

Bonanno and colleagues combine unilateral pyramidotomy, continuous voluntary complex-wheel running, whole-brain intersectional CSN tracing, and c-Fos mapping to ask whether rehabilitation reorganizes the supraspinal collaterals of the intact corticospinal tract neurons. The study is technically ambitious and competent, the uPyX + complex-wheel + intersectional-tracing + BrainJ combination is smart and interesting, the behavioral effect is convincing, and the blinding and exclusion criteria are explicit. The central anatomical finding - a CSN-specific, whole-brain projectome comparison with subregional LPGi/GiA/MdV granularity - is a legitimate contribution that builds on Asboth 2018. However, the strength of evidence does not support the strongest causal wording in the current abstract, significance statement, and parts of the discussion: the results remain correlational, the MdV-behavior correlation is modest, and its significance is sensitive to the unit of analysis. A major revision is recommended, primarily of framing and quantitative robustness, rather than because the central dataset is unconvincing.

Strengths:

(1) Technically ambitious and technically competent study addressing a relevant gap: brain-wide mapping of intact-CSN reorganization under continuous voluntary rehabilitation.

(2) The combination of uPyX, complex-wheel running, intersectional tracing, and BrainJ whole-brain projection analysis is novel and well integrated.

(3) Behavioral effect is convincing, blinding, and exclusion criteria are explicit.

(4) The central anatomical finding (CSN-specific whole-brain projectome under rehab, with LPGi/GiA/MdV subregional resolution) is a legitimate contribution that builds on Asboth 2018. The closest recent works (Lemieux et al. 2024, Jeleva et al. 2026) study reticulospinal rather than CSN plasticity and are complementary rather than competing.

Weaknesses:

(1) Causal framing extends beyond what the current evidence supports.

The abstract and significance statement present MdV as a potential mediator, or even a central locus, through which rehabilitation re-establishes descending control of the impaired limb. This is stronger than the evidence. What the paper shows is that CSN collateral projection density in MdV has a mild-to-medium correlation with behavioral recovery, and that this region is already known from prior work (Esposito 2014) to be relevant for skilled forelimb function. That is an interesting anatomical correlation, not a demonstration of mediation. No manipulation of MdV or of MdV-projecting CST terminals is performed; there is no silencing, no pathway-specific perturbation during rehabilitation, and no test showing that the identified sprouting is necessary for recovery. The limitations section acknowledges this, but the prominent claims do not.

(2) The behavioral caveat on what is actually novel.

The cleanest way to state what is genuinely new, clearer than the abstract itself, is this: when a CSN population loses part of its spinal target domain (via contralateral uPyX denervating the opposite cord), some CSNs from the opposite cortex appear to redirect growth into brainstem collaterals (LPGi, GiA, MdV). The compensation is plausibly sufficient to restore gross descending drive to the impaired forelimb, but most probably inadequate for the fractionated, cortico-motoneuronal fine-grain control that the direct CST normally provides. That distinction - recovery of drive and even skilled locomotor control vs. recovery of fine precision - is consistent with the ladder-rung improvements the paper reports (footfall counts are an integrated gross-placement metric) and with the skilled-reaching literature (Esposito 2014 and similar), which suggests precision grip and digit individuation would not be fully recovered by an MdV-centered detour. This note is also translationally important when we ask what humans consider fine motor control, which is mostly object manipulation. Relatedly, the ladder task is "skilled" in the operational sense that it requires cortical control, but the motor output measured (gross paw placement, overreach) is not fine motor function in the sense of digit individuation, grip force modulation, or pellet manipulation. "Skilled" here does not even mean *acquired* skill: classical skilled reaching in rodents involves explicit training to acquire a novel motor program, whereas here mice are only habituated. The brainstem-compensation hypothesis is more comfortable with restoring cortex-dependent gross placement than with restoring acquired fine-motor skills.

(3) The anatomy sample is modest for the precision of the claims.

Projection analysis rests on n = 9 pooled controls, n = 5 uPyX−Rehab, and n = 5 uPyX+Rehab. For a whole-brain subregion analysis, this is not a large dataset, even with the sensible restriction to the Wang et al. spinally-projecting set. The three medullary hits are plausible, but some of the most specific conclusions rely on a relatively small number of animals for its most specific claims. This matters especially for the MdV-behavior correlation.

(4) Normalization enforces a zero-sum structure.

Projection density is normalized to the total CST tract signal. This is a reasonable way to control for tracing variability, but it imposes a relative structure on the data: an apparent increase in one region may partly force an apparent decrease elsewhere. This may matter and has to be looked into by the authors, because the manuscript interprets decreased density in some other targets as meaningful redistribution.

(5) The decision to merge PMn and MdV under a single "MdV" label needs more justification.

Since the discussion relies on prior literature assigning skilled forelimb function to MdV proper, the reader needs to know whether the signal truly localizes there or whether it may partly reflect a neighboring region grouped under the same atlas label. Related to this, laterality would be very informative: since the proposed compensatory route is anatomically directional, showing whether the increased signal is preferentially located on the expected side of the medulla would strengthen the interpretation.

(6) The c-Fos / Fig. 3 section goes beyond what the data directly support.

The section "Complex-wheel running recruits intact corticospinal neurons" and the figure title "Rehabilitation functionally recruits intact CSNs" go beyond the actual observation, which is that a higher fraction of CSNs in M1 and M2 are c-Fos+ in runners than in non-runners. "Functionally" is not supported: c-Fos is a transcriptional marker of recent activity, not a functional readout; it does not show that the CSN's output is used to drive behavior. "Rehabilitation" is not supported either: the contrast is runners vs non-runners, applied uniformly across Sham and uPyX groups - healthy Sham+Rehab animals are on wheels for leisure, and the c-Fos effect is present in them too. The finding is difficult to interpret without thinking of the simpler framing ("moving mice have more motor cortex activity than resting mice"), with no control for generic arousal or ambulation. This section is the softest link in the causal chain running - CSN activity - medullary sprouting - recovery.

(7) MdV-recovery correlation: unstated multiple-comparison correction and possible pseudoreplication.

The correlation (R² ≈ 0.33, p ≈ 0.01) is the backbone of the paper's "causal" claim. Panels L/M/N test three correlations (LPGi, GiA, MdV vs forelimb footfall recovery); only MdV is reported as significant. The Figure 5 legend applies Tukey adjustment to the t-tests in A-C but makes no analogous statement for the correlations in L-N. A 3-test Bonferroni (α = 0.017) would not flip the MdV result, but disclosure is warranted, and the three tested regions were pre-selected from the significant group contrasts in A-C, which, to a statistician, would further shrink effective α. More importantly, the figure legend states that closed and open circles represent CFA- and RFA-traced values, respectively, which suggests the correlation treats the two tracer channels per mouse as independent datapoints - doubling the apparent n (≈ 20 from 10 uPyX mice), with the result of a higher significance than one would have at the mouse level.

(8) Reporting issues.

The reader would benefit from judging statistical choices such as those above directly from a data table rather than interpreting the authors' choices. The SciScore rightfully flags multiple missing components of transparent reporting: missing RRIDs, no code availability, limited data availability, and no power calculation, among others.

Almost all these weaknesses can be addressed with a revision of the manuscript, especially in the framing of results.

Conclusion:

The core message - that rehabilitation is associated with a selective pattern of CSN collateral remodeling in the motor medulla, and that MdV projection density covaries with behavioral recovery - is defensible from the data and already a useful result. The current wording in parts of the abstract, significance statement, and discussion goes beyond this and implies a mechanistic conclusion (mediation, central locus, re-establishment of descending control) that the data do not yet establish. The manuscript would better match its evidence with "associated with", "correlates with", or "candidate locus" framing, unless a causal experiment is added.

Reviewer #3 (Public review):

Summary:

In this study, Bonanno et al. show that after a lesion of the corticospinal tract (CST), rehabilitation running in a complex wheel drives improvement in skilled forelimb performance in mice. Mice with unilateral CST injury can perform gross motor tasks (locomotion) at the same level as the non-injured mice, but injured mice still have deficits in another task involving fine motor control. Thus, it is well-suited to test the efficacy of locomotion-based rehabilitation in fine motor control. Mice that voluntarily engaged in the rehabilitation protocol improved in the fine motor control task more than those mice that did not perform any rehabilitation. Highlighting the role of rehabilitation in the recovery of motor function after the lesion.

The authors aimed to study rehabilitation-driven intact CST sprouting to supraspinal areas. They identified one area in the motor medulla where rehabilitation significantly changes the projection density from the intact cortical spinal neurons. Interestingly, this area has ipsilateral connections and thus could be a pathway to convey motor commands from the intact corticospinal tract to the denervated area. However, as the authors acknowledge in the discussion, they only found a correlation between the change in the synaptic projections from intact CST to the medulla and the recovery. Future work should study if indeed the area of the motor medulla identified here increases its ipsilateral projections to the denervated area, confirming the re-routing of motor commands from the intact cortico spinal tract to the denervated area. The paper is strong and, in general, claims are supported by the data.

Strengths:

In this study, Bonanno et al. show that after a unilateral corticospinal tract lesion (CST), locomotion rehabilitation can improve motor function and improvements generalized to tasks that require fine motor control. Moreover, it identifies a potential pathway that could be used for the intact corticospinal tract to convey motor commands to the denervated area. The pathway identified here could become a target for rehabilitation therapies.

Weaknesses:

As the authors acknowledge in the discussion of the study, the main limitation of this study is that the reorganization observed at the motor medulla is only correlational. Thus, it is possible that the adaptation to running with an injured limb of the intact CST to adapt to an injured limb rather than a re-routing of the intact CST inputs to the denervated area underlies the synaptic changes observed in the motor medulla.

The statistical analysis could be better described.

The generalization of skilled movement is limited to only locomotion tasks.

eLife Assessment

The worldwide decline in the health of coral reefs is well documented, and overgrowth by microbial consortia can be a contributing factor. Kelman and colleagues used metagenomic analysis to interrogate potential changes in phage-associated genes predicted to be involved in central carbon metabolism. The study addresses the hypothesis that metabolic genes associated with carbon metabolism that are encoded by viruses reflect the health of the corals. The study contributes a valuable perspective on the potential role of phages in coral health, although limitations of the data and analyses offer an exploratory examination rather than a definitive result. Overall, the evidence supporting the major findings is incomplete, in part because the conceptual model relies on qualitative assumptions rather than empirical data.

Reviewer #1 (Public review):

Summary:

Microbialization (bacterial overgrowth) is a recognized component of degraded, eutrophied coral reefs where there is a shift from coral to algal dominance on the benthos. In addition, previous work has demonstrated that virus communities shift from a lytic strategy dominated (kill-the-winner) to a temperate (lysogenic) strategy dominated with reef microbialization. Kelman et al. sought to leverage previously published virus metagenomes produced from the water column of healthy and degraded coral reefs to assess virus community metabolic shifts. The authors also produce a conceptual model to demonstrate the potential impact of the observed metabolism shifts on reef fates.

Strengths:

The main strength of the manuscript is the findings from their metagenomic analyses and results. The virus metagenomes were produced using established approaches in the field and yield sufficient data per sample for their analyses. Interesting results regarding the shift in the types of genes from anaplerotic to cataplerotic provide the foundation for testable hypotheses to determine the magnitude of impact virus strategies have on reef health. The introduction is also well written and sets up the scene very well.

Weaknesses:

(1) The methods text currently omits important information related to the sampling design. It is not clear how many metagenomes are from healthy and degraded communities. This impacts the interpretability and robustness of the statistical results. Furthermore, it is unclear if analyses are based on assembled contigs or read-based alignments. Improving the clarity and organization of the Methods is essential for reproducibility.

(2) Regarding the bioinformatics approach, normalization using the "percent known" approach within samples may not fully account for discovery bias related to sequencing depth. While Supplementary Table 1 shows variability in read counts, the lack of community-level metadata makes it difficult to determine if sequencing depth covaries with community type (healthy vs. degraded). The study would benefit from a rarefaction analysis or subsampling to ensure that gene frequency trends and Spearman correlations are biological signals rather than artifacts of sequencing effort.

(3) The qualitative model in Figure 5 is positioned as evidence for the role of viruses in reef health, but it does not provide independent support for the authors' hypotheses. Since the model is parameterized using "arbitrary units" to reflect the authors' assumptions rather than being derived from the empirical metagenomic data, it serves as a helpful illustration of a hypothesis but not as a validation of the findings.

(4) Results and discussion require revisions to improve readability and connectivity across sections. Ensuring a clear distinction between empirical data and model-based speculation would help the audience better appreciate the science.

Reviewer #2 (Public review):

Summary:

The manuscript by Kelman and coauthors investigates how viral communities differ in the genes they encode in healthy and degraded coral reef ecosystems. Across 19 viral metagenomes from Central Pacific reefs, the authors assess the frequency of integration/excision genes as a proxy for viral community temperateness and ask whether genes associated with central carbon metabolism covary with signatures of temperateness. The main finding is that viral communities with more temperate-related genes encode more genes from the Entner-Doudoroff pathway and other reactions interpreted as anaplerotic, whereas more lytic-associated viral communities show greater representation of some pentose phosphate pathway, TCA, and redox-associated genes interpreted as cataplerotic. The authors propose a model based on these patterns in which lytic viral metabolism helps suppress bacterial overgrowth on healthy reefs, while temperate viral metabolism may promote microbialization on degraded reefs. The study addresses an interesting and potentially important concept - that viral auxiliary metabolic genes are important components of microbial communities and can affect ecosystem functioning. Linking viral metabolism to coral reef microbialization is a creative conceptual advance. The manuscript is clearly written, and the reported enrichment of anaplerotic genes in temperate-associated viromes is an interesting pattern that could motivate future work on how viral metabolic potential varies across reef states.

Strengths:

(1) The study connects viral lifestyle, central carbon metabolism, bacterial overgrowth, and reef degradation in a framework that could be useful for future studies of coral reef ecosystems and viral ecology. This is an interesting synthesis that links viral auxiliary metabolism to broader questions about microbialization and reef state.

(2) The manuscript is generally clearly organized around a testable prediction: viral metabolic gene content should vary along a lytic-to-temperate viral community gradient. The reported enrichment of anaplerotic genes in viromes with a larger fraction of temperate viruses is a compelling result.

(3) The authors highlight several virus-encoded metabolic genes that may not have been previously reported in viral datasets or genomes. If supported by further validation, these observations could expand the known repertoire of viral metabolic potential.

(4) The modeling helps clarify the feedbacks the authors propose may connect viral lifestyle, bacterial metabolism, and coral reef degradation. It provides a foundation for generating hypotheses about how viral metabolic genes could influence reef microbial dynamics.

Weaknesses:

(1) The main limitation is that the evidence for several key claims remains indirect. The core analysis is based on correlations between metabolic gene frequencies and integration/excision-related genes. This does not demonstrate that the metabolic genes occur in temperate viral genomes, are physically linked to lysogeny genes, are expressed during infection, or alter host metabolism. Thus, the data support an association between VLP-associated metabolic annotations and a community-level temperateness proxy, but not a direct link between temperate phages and these metabolic functions.

(2) It is important not to equate community-level gene frequencies with genome-level or infection-level metabolic programs. A virome may contain more anaplerotic genes overall, but that does not demonstrate that individual viruses reprogram their hosts in an anaplerotic manner nor that infection produces a net anaplerotic effect. Individual viruses may encode both anaplerotic and cataplerotic genes, and a smaller number of cataplerotic genes could have stronger metabolic consequences depending on expression, enzyme efficiency, pathway position, and host context. This is an important limitation that should be acknowledged and, if possible, addressed with contig- or genome-level analyses.

(3) The ecological interpretation assumes that viral infection is strong enough to influence reef-scale bacterial population dynamics. However, the study does not directly measure infection frequency, lysis rates, viral production, burst size, lysogeny frequency, prophage induction, gene expression, or bacterial mortality. If viral mortality or lysogenic conversion were rare in these systems, the observed gene-frequency patterns could have limited ecosystem-level consequences. This makes claims about viral metabolism suppressing bacterial overgrowth, accelerating microbialization, or acting as a conservation lever more speculative than suggested.

(4) There are statistical limitations related to the use of relative gene frequencies. Because genes are normalized as percentages of known genes, the data are compositional. Apparent increases in some categories may partly reflect decreases in others. Bootstrapped Spearman correlations are useful for assessing the robustness of these associations, but they do not address compositionality or multiple testing.

(5) The anaplerotic/cataplerotic classification is central to the manuscript's conclusions and would benefit from more support. The framework is useful, but it depends on both annotation confidence and biochemical context. Sequence-similarity annotations alone may be vulnerable to misannotation, especially for central metabolic enzymes that share conserved domains across functionally distinct proteins. Stronger evidence that key genes contain key functional domains and/or are phylogenetically related to characterized enzymes would help support the proposed functions. In addition, many central carbon enzymes are reversible or context-dependent, so a clearer rationale for each classification would strengthen the interpretation.

Overall, the manuscript presents a valuable hypothesis and highlights new ecological patterns in coral reef viral metagenomes, but falls short of the evidence needed for the strongest claims. The work would be strengthened by analyses that directly link metabolic genes to viral genomes or lysogeny markers, address compositional effects, validate key annotations, and more clearly distinguish observed gene-frequency associations from hypothesized effects on infection, host metabolism, and reef state.

Settler apocalypticism projects the problem to a "fantasy" due to the nature of looking at it as post-apocylptic, therefore unable to be saved

Climate crisis is not a future problem, it is a problem we need to deal with now

an argument from the paper

the branch of philosophy concerned with the nature, origin, and limits of human knowledge

The point of the photograph

I need to notice setting because place and time shape the mood, conflict, and choices.

I need to follow the plot closely because event order explains the conflict and turning points.

I need to study character because actions, speech, and choices show who a person really is.

I need to watch tone because it shows the writer's attitude and changes how a scene feels.

Notation here is incredibly confusing. x is used as a 4D full dimensional state vector in the form of [x, theta, x_dot, theta_dot] while x_1 and x_2 are the position vectors for the cart and pendulum in [x, y]. This isn't explained anywhere and is left to the reader to figure out.

This reminds me that reading should be open-minded, trying to understand the writer before judging the story.

Explore why a SIM-based telecalling CRM outperforms VoIP dialers in India. Learn how it improves call quality, reliability, compliance & sales team productivity.

Know More: https://callyzer.co/blog/why-sim-based-telecalling-crm-is-better-than-voip-dialer-india/

Need to have a meeting to discuss on the SecEng SecAd process

stolen pictures

Figure 5a shows the results of this analysis, with the locations of the transcriptomic crests observed by Shen et al. (24) indicated. While the null results do not perfectly recapitulate the reported iPOP transcriptomic waves, it is notable that despite the lack of any true signal, two clear crests are apparent in our null study, one in the early 40s and one in the early 60s. Also notable is the correlation between the sample size in the sliding window and the number of changing molecules that are reported (Figure 5B); this phenomenon applies to both LOESS+DE-SWAN and DE-SWAN alone and is discussed further in Section 4. The appearance of two crests at these time points based on random noise calls into question the validity of the conclusion that they represent true biological trends.

There is a recent comment on pubpeer showing that the original Shen et al., paper replaces the real participant ages with fabricated ages during the LOESS step which is responsible for the "waves" https://pubpeer.com/publications/D2C91E5E2E55CE7452B12E44EBE844#2

Was this analysis done using the corrected code or the same code from the original paper. The authors may want to look into this and address it.

test

对于Mount-VHD有可能你会遇到CommandNotFound错误，这种情况下可以从【磁盘管理】中看到这个磁盘的编号，或者用wmic diskdrive list brief （来自 https://is.gd/yrMw8K )查到——当然，都得先在磁盘管理中把这个vhdx给attach上去

• Core Principle:

  • Shift focus from yourself to the reader's perspective; all good communication is grounded in understanding the mind of the person you are asking.

• Establish You Are Worth Helping (People Before Projects):

  • Demonstrate that you are a serious person by showing "proof of work" (e.g., a trained model, an insightful blog post, or training logs) rather than just stating intentions.
  • Use personal connections warmly but cautiously, as you are borrowing credibility from the person who referred you.
  • Use institutional credibility (e.g., university or corporate names) sparingly, as it only proves you cleared a filter once and can come across as status signaling.

• Keep Context Concise and Connected:

  • Keep background explanations incredibly short to respect the recipient's limited attention.
  • Connect your context directly to things they already know or care about (e.g., how you implemented their specific research paper) rather than sharing generic background stories.

• Make the Request Easy to Accept:

  • Reduce the cost of acceptance by keeping the magnitude small (e.g., asking for 20 minutes of time instead of reviewing a massive manuscript).
  • Make the ask highly specific and low-friction (e.g., providing a forwardable bio blurb for introductions, or asking questions in writing instead of insisting on a call).
  • Keep the obligation strictly bounded rather than asking for long-term or recurring commitments upfront.

• Make it Easy to Say No:

  • Avoid creating emotional guilt or pestering the recipient, as a pressured, begrudging "yes" is the worst outcome and poisons future relationships.
  • Accept a rejection gracefully by thanking them for their time and moving on.

• Ultimate Boundary Condition:

  • Never lie or misrepresent yourself; any hint of dishonesty immediately invalidates the request regardless of how well-crafted it is.

• Project Overview:
  • Named webernetes, it is a highly experimental, browser-based partial port of Kubernetes written in TypeScript, running entirely client-side without backend server components.
  • Developed at ngrok to provide a long-term, low-maintenance simulator for creating interactive and visual educational content about Kubernetes.
• Architecture & Features:
  • Includes ports of core Kubernetes controllers (deployment, ReplicaSet, pod scheduler, and namespace) along with a partial port of the kubelet binary.
  • Features a simulated browser-based container network interface (CNI) for pod-to-pod communication over DNS/IP and a browser container runtime interface (CRI).
  • Avoids pulling massive images from registries like Docker Hub by utilizing a custom browser-based registry defined via a TypeScript API.
• Why WebAssembly (Wasm) Was Not Used:
  • A simple "hello, world!" Go binary compiled to Wasm is ~540KiB gzipped, whereas the entire webernetes project is much lighter at ~140KiB gzipped.
  • Compiling the real Kubernetes codebase to Wasm failed due to compile-time errors from missing system-level APIs in the browser.
• Development & LLM Challenges:
  • Around 90% of the code was translated line-for-line from the original Kubernetes Go source using LLMs, though the author had to strictly review every line.
  • LLMs consistently introduced errors such as cutting corners (e.g., replacing complex caches with a simple JavaScript Map), adding unrequested helper functions, and omitting cases in table tests.
• Testing & Behavioral Parity:
  • To ensure lexical similarity translated to correct execution, hundreds of differential tests were written.
  • These tests validate behavioral parity by running the exact same client code against both webernetes and a real k3s cluster using the official kubernetes-client/javascript library.

• Overview of the AI Audio/Note-Taker Category

  • Tested a wide range of devices categorized as AI pins, note-takers, second brains, or lifelongers [00:00:06].
  • Distinct from previous failures like the Rabbit R1 or Humane AI Pin because they do not aim to replace smartphones [00:00:23].
  • Big tech is moving heavily into the space, with Amazon and Meta recently acquiring key startups in the audio sector [00:00:39].
  • Devices share the same core workflow: record audio, transfer it to a phone, transcribe it via a mobile app, and process it with an AI model for summaries and action items [00:01:14].

• Two Key Product Dimensions

  • Trigger Recording vs. Always Listening: Devices either record only when manually prompted or constantly listen to collect continuous ambient context [00:01:41].
  • Summarization vs. Proactive Interpretation: Products focus strictly on summarizing audio or aim to actively interpret and guide the user [00:01:41].

• Triggered Recording Tools (The Currently Practical Category)

  • Evaluation Criteria: Transcripts and speaker detection are very similar across brands because they outsource to the same providers [00:02:42]. Differentiation comes from:
    • File Transfer: Speed and reliability of moving audio files to a phone [00:03:02].
    • App Quality & Ecosystem: Stability of the mobile app and existence of a desktop app [00:03:13].
    • Trust & Longevity: Manufacturer data privacy practices and financial stability to avoid hardware bricking [00:03:19].
    • Data Lock-in: The ease of exporting notes to external personal knowledge management systems [00:03:30].
    • Cost Structure: Upfront hardware price combined with ongoing subscription costs for server-side AI processing [00:03:35].
  • Top Recommendation — Plaud: The clear winner for file transfer speed/reliability, background Bluetooth/Wi-Fi syncing, cloud upload capabilities, and a functional template ecosystem [00:03:58]. Offers a robust desktop companion app that records virtual meetings via system audio without utilizing an intrusive bot [00:04:59]. It maintains SOC 2 and HIPAA compliance for data privacy [00:05:42]. Data lock-in is mitigated via Zapier integrations, automatic email delivery, and a developer community [00:07:01].
  • Cost-Saving Alternative: The open-source "AudioBridge" project allows users to bypass expensive Plaud subscription costs by utilizing their own direct AI API keys [00:08:41].
  • Other Notable Contenders:
    • Soundcore: Excellent hardware with a built-in magnetic charging case, but restricted by a basic headphone app that lacks AI search or customization [00:08:58].
    • Pocket: Refined premium metal hardware and strong export features (MCP server), but held back by inconsistent phone transfer reliability and sudden changes to their subscription plans [00:09:37].
    • Haidoc P1 / P1 Mini: Connects directly via Bluetooth headphones to a computer or phone to save files locally on internal memory without requiring software installations—ideal for highly locked-down enterprise computers [00:10:36].

• Always-Listening Devices (The "Second Brain" Category)

  • Focused on building an all-knowing memory backup with perfect recall, daily recaps, and automated task generation [00:11:29].
  • Tested Options:
    • Friend & Lookie: Non-recommended. Friend is invasive/sassy; Lookie includes a camera but looks like a conspicuous police body camera and performs poorly [00:11:41].
    • Limitless Pendant: Off the market following Meta's acquisition of the company [00:12:06].
    • OMI: Open-source and ambitious (working on screen recording and AI glasses), but currently buggy and lacks product focus [00:12:44].
    • B: Highly polished initially, but customer support and software stability degraded heavily after Amazon's acquisition [00:13:29].
    • Fieldly: The best of the group due to its focused approach, clean transcriptions, reliable hardware, multi-day battery life, and strong desktop app integration [00:14:13].
  • Fatal Flaws ("Context Rot"): Current models fail at accurate diarization (figuring out who said what), often attributing dialogue heard from nearby strangers or media to the user [00:15:05]. The user faces a heavy administrative burden to clean up flawed AI data, making the absolute "always-on second brain" promise currently non-viable [00:15:34].

• Legal, Ethical, and Social Boundaries

  • Roughly 40% of the US population lives in two-party consent states, creating legal friction for recording private interactions [00:16:33].
  • Socially, requesting recording consent in private contexts remains awkward, frequently altering normal human behavior [00:16:48].

• Future Market Trends

  • Form Factors: Sharp rise in ring-based options (Sandbar, Pebble, Fable) and a shift toward self-improvement pendants focused on emotion-tracking and self-awareness (Nerva, Nuna) [00:17:24].
  • Glasses & Visuals: Shift toward smart glasses (Meta Ray-Ban integrations, Pickle, Rokid) and pendant cameras [00:18:01].
  • Industry Heavyweights: Big tech is aggressively entering the market; OpenAI is working on an audio device, and Apple recently acquired QAI for $1.5B to decipher silent speech via jaw/facial micro-movements [00:18:29].
  • Mainstream Adoption Outlook: Unlike the failure of Google Glass, modern audio-only devices feature virtually invisible microphones, bypassing public visibility backlash [00:19:28]. Adoption may mirror a competitive sports dynamic (like the NBA three-point revolution): if the tools offer an undeniable cognitive or professional advantage, adoption will become mandatory to avoid falling behind [00:19:40].

The examples are solid. these groups barely show up in the data to begin with, and then the filters go and strip out what little they did post.

Gender-job stat's a solid example. nobody coded that bias in, the model just picked it up from the training text. Bringing in Stochastic Parrots is a nice touch since it ties this to a real scandal, not just theory. Also looking back to the Gramsci point, train on existing culture, you inherit its biases.

it's a fascinating analogy, taking a theory from nearly a century ago and applying it to LLMs feels genuinely fresh. The author invited us to look at what "cultural hegemony" might look like in the age of AI.

I agree that culture plays an important role in keeping social systems in place. Schools, the media, and other institutions shape the way people think about society and what they see as "common sense." As a result, people may accept the existing system without even realizing how much these cultural influences affect their views.

I agree that Europe had a rich cultural tradition, but I think the author's description of Russia may be an oversimplification. Even though many people were illiterate and had limited access to mass media, they were still influenced by local culture, religion, and community networks. Culture is broader than formal education or the media.

Internet is already a non-stop mass "advertisement" that is already so entangled into our every day lives. Think about the number times an elementary classroom might use YouTube and expose students to ads. They suggest to young students who haven't clearly developed their sense of self how they should live, value, buy, eat, exercise, and so on. The focus on consumerism is something we may never get away from and have long term serious consequences to the world.

To be able to quantify someone's contribution to the LLM is a scary thought! And because LLM is using such vast number of texts to train AI without any checks and balances we will never truly understand the influence of all these views and values on people as we move forward.

How should we define view of "average human"? Who gets to make that decision of "average human"? What is "average"? Traditionally, the word average often referred to the largest number. So do we go by largest population number or largest religious beliefs or largest popular beliefs. If so, what happens to everyone else's views?

We are already living in a world where it is not clear where the information we are reading about many of the political topics are coming from and who is behind the information. There's been a lot of speculations about the information manipulations related to elections and politics. AI will only add to that mass entanglement of information and misinformation.

Many young students (who grew up with the internet and constant devices around them) are consumers of the internet where they don't always think about what they are reading and the influence on them. AI based web searches further encourages this by providing only a "snippet" summary of information.

Not only is English the more dominant language in AI models, but AI platforms tend to be built by newcomers. Forbes estimated that approximately 65% of AI companies in the US were founded by newcomers in 2023, but English was still the language the models were trained in. Language is such an important part of someone's culture and identity, and it is becoming a popular translation tool, but as it has been discussed there are limitations and biases towards "smaller languages."

I find the term "superhuman intelligence" interesting because is it "superhuman" if it is artificially made?

AI as a conformity tool to try and align everyone with the cis, white, European/American, male perspective. I wonder/fear how this may impact newcomers to Canada and the US? From my Masters thesis, different academic cultures use AI differently. Some are more over-reliant on AI, some it is not usable. When someone comes to a new country that encourages the use of AI in some ways, plus the impacts on enculturation, the pressures of assimilation, etc., the biases that AI have towards marginalized group could be internalized or exacerbated? I'm curious to know other peoples thoughts on this!

Piggy backing off the other comment on this section! We must ask what is the definition of "fairness" and "justice" but also in the larger scale (when it comes to policy/procedures/laws/etc.) who is creating that definition? Are there multiple perspectives at the table from diverse backgrounds? Or are these definitions being created by the ruling class and ultimately maintaining the existing inequitable structures/systems?

Several of you have added commentary to this, which I agree with them all! I would like to add that it's also important to ask who developed and implemented these "interlocking structures." To me, this sentence reads as these are separate structures that got caught up in cultural hegemony, but I think that it's important to note that these structures were also created by the ruling class (white, European, male).

The author argues that LLMs mainly reproduce dominant cultural values because they are trained on existing texts. Using Gramsci's concept of the historic bloc, the author explains that these values become embedded in AI models and are difficult to change. However, I wonder if this is always the case, if LLMs will continue to evolve through updated data, and user interactions, if so, they seem to be shaped not only by the past but also by continuous social and technological change.

I think this is an example of how AI can be used positively by supporting cultural survival when it is built with consent, local institutions, and linguistic diversity in mind.

This quote is incredibly telling. Nothing challenges hegemony more than diversity of thought.

This attack on diversity of thought is paralleled by the political climate we are witnessing in the united states under this administration.

It seems that there is a mounting war on knowledge (and diversity in all of its manifestations; race, nationality, gender, sexual orientation, and diversity of thought**). Both covertly and overtly attempting to silence and defund post-secondary institutions while also threatening our public's opportunity for development and access to objective and subjective information. Completely erasing all progress in EDI(ID) going as far as DOGE deleting archival photographs and records of aircrafts with the word gay in it's name.

This same sentiment seems to be echoing across boarders. Alberta and Ontario are also under attack in a multitude of ways. Ontario is now moving toward a one year program for training teachers, while the standard for the professional certification in other jurisdictions remains a 60 credit hour program including 24 weeks of practicum. Alberta teachers are experiencing unprecedented working conditions with enrollment outpacing new teaching positions, resulting in ballooning class sizes and the teacher strike in 2025

I wonder if Mahelona explained the damage to the environment that is also caused by these learning models. I feel mentioning the repercussions on the planet would have made convincing the elders a little more difficult. Its a wonderful thing that the Maori language will survive this culling of minority human languages but something about the whole ordeal feels unfair. Like the Maori community is forced to participate in this multi-facetted situation (technological advancement, degradation of environment, commodification of human knowledge wherein the profits are given to those who didn't produce it) or become forgotten/irrelevant in the world being created by a careless few.

I find this fragility to be true for many of the social constructs we live with in society today. Whether it be gender norms, capitalism, or nationalism all are concepts that are held in place through institutional and social pressures. I often think about this when I have to make students stand for the national anthem each morning, why must I also participate in the enforcement of nationalism in my students, creating invisible boarders between "us" and "them"? But I also see resistance against other constructs like the "give-and-take" philosophy of capitalism, when students inherently come to their peer's aid or give away their snacks without expecting anything in return to ensure their friend doesn't go hungry for the day.

Timnit Gebru was a co-lead researcher in Ethical AI at Google who was fired in 2020 for raising issues of discrimination in the workplace. I am connecting to Kimberly Krenshaw's views on intersectionality in that prior to this year, I did not recognize her name; despite Timnit being named as Nature’s Ten people who helped shape science and one of TIME 100’s most influential people.

I am reminded of the importance of seeking out diverse perspectives and scholars of colour is more important than ever, in the age of AI and the distillation of information.

• Time of Consumption & Cardiovascular Health

  • Drinking coffee between 4:00 AM and 12:00 PM reduces the risk of premature death from cardiovascular disease by up to 31% [00:01:04].
  • This window aligns with the body's circadian rhythm; anti-inflammatory properties in coffee effectively neutralize peak morning spikes of pro-inflammatory molecules [00:01:31].
  • Consumption later in the day does not yield the same cardiovascular protective benefits [00:01:24].

• Temperature-Related Cancer Risks

  • Drinking very hot beverages frequently and in large volumes increases the risk of stomach cancer by 54% to 69% [00:03:00]. Consuming over eight cups of scalding liquids daily more than doubles this risk [00:03:19].
  • Chronic exposure of the delicate gastric mucosa to high temperatures triggers micro-injuries that can turn neoplastic over time [00:03:29].
  • Hot beverages above 60°C also elevate the risk of esophageal cancer by up to 97% [00:03:55]. The optimal, safe serving temperature range is between 50°C and 55°C [00:04:14].

• Impact on Sleep Quality

  • Caffeine intake affects sleep metrics even if the individual does not consciously experience issues falling asleep [00:05:41].
  • Effects include an average reduction of total sleep duration by 45 minutes [00:05:06], a 7% drop in sleep efficiency [00:05:16], a 9-minute delay in sleep onset [00:05:24], and an extra 12 minutes spent waking up or tossing during the night [00:05:24].
  • The ideal cutoff time for a standard individual to stop drinking coffee is at least 9 hours before bed [00:05:56].

• Individual Variations & Metabolic Factors

  • Caffeine clearance speed is heavily governed by variations in the CYP1A2 gene [00:06:22].
  • The clearance window stretches depending on specific physiological factors:
    • Oral Contraceptives: Extend caffeine's half-life by roughly 4 hours, shifting the required pre-sleep cutoff time to 12–13 hours [00:10:47].
    • Alcohol Intake: Heavy consumption dampens the liver enzymes responsible for breaking down caffeine, prolonged action by up to 70% [00:11:13].
    • Pregnancy: Caffeine processing can slow down by more than three times, particularly in the third trimester [00:11:51]. Daily caffeine allowance should be limited to 200 mg (about 1–2 cups) [00:12:16].

• Empty Stomach Consumption (Fasting)

  • Coffee stimulates gastric hydrochloric acid secretion, but this is entirely safe for healthy individuals with intact mucous linings [00:07:27].
  • Fasting intake can accelerate intestinal motility, causing immediate bathroom urgency or transient heartburn in susceptible individuals [00:08:00].
  • Drinking coffee on an empty stomach after poor sleep disrupts carbohydrate metabolism, causing abnormally sharp blood glucose spikes during the subsequent meal [00:09:30].

• Blood Pressure Concerns

  • Standard regular coffee intake does not increase the risk of developing hypertension in the general healthy population [00:14:28].
  • Individuals with pre-existing hypertension must be cautious: drinking two or more cups daily doubles the risk of premature cardiovascular mortality, whereas limiting consumption to exactly one cup a day acts protectively [00:14:45].
  • "Slow metabolizers" face a 72% higher risk of sustained hypertension when drinking 1–3 cups daily, soaring to a 200% risk increase at 4+ cups [00:16:17]. Combining coffee with smoking exacerbates blood vessel constriction [00:18:09].

• Brewing Methods & Cholesterol Levels

  • Unfiltered coffee contains diterpenes (cafestol and kahveol) that block liver receptors responsible for clearing LDL cholesterol [00:18:41]. Unfiltered methods can elevate LDL cholesterol by 20 to 30 mg/dL [00:21:28].
  • Paper filters (used in drip coffee or AeroPress) trap these oily diterpenes almost completely [00:19:16].
  • Modern automated office machines and advanced home espresso units equipped only with permanent steel or nylon mesh screens fail to block these micro-droplets, resulting in up to 15 times higher diterpene content than paper-filtered options [00:19:26]. French Press brews should ideally be passed through a paper filter before drinking to eliminate the oils [00:20:56].

• Źródło i zakres raportu: Podsumowanie przygotowano na podstawie raportu płacowego firmy Sedlak & Sedlak („Puls Biznesu”), obejmującego dane z ponad 1300 przedsiębiorstw i ponad 408 tysięcy pracowników na 1264 stanowiskach.
• Wpływ awansu na zarobki: Rynek bardzo silnie premiuje unikalne kompetencje i odpowiedzialność strategiczną. Największy przyrost całkowitego wynagrodzenia (aż o 86%) odnotowuje się przy awansie ze stanowiska eksperta (SE) na starszego eksperta (SSE).
• Ogólne rozpiętości płacowe (UoP vs B2B):
  • Mediana całkowitego wynagrodzenia rośnie od 7 180 zł dla młodszego specjalisty do 25 700 zł dla starszego eksperta.
  • W przypadku kontraktów B2B stawki są wyższe i kształtują się w przedziale od 9 437 zł do 29 139 zł.
• Najlepiej opłacane stanowiska w IT i nowych technologiach (dla Starszych Ekspertów - SSE i Ekspertów - SE):
  • Architekt systemowy (SSE) – 29 000 zł
  • Specjalista ds. bezpieczeństwa IT (SSE) – 28 069 zł
  • Konsultant SAP (SSE) – 28 000 zł
  • Programista embedded (SSE) – 27 500 zł
  • Programista back-end (SE) – 27 129 zł
  • Inżynier cloud (SE) – 26 500 zł
  • Product Owner (SSE) – 25 750 zł
• Sektor poza IT: Najwyższymi zarobkami poza technologiami wyróżniają się prawnicy, gdzie np. radca prawny na poziomie starszego eksperta (SSE) osiąga zarobki rzędu 25 100 zł.
• Kluczowy wniosek: Wysokość wynagrodzenia na współczesnym rynku pracy zależy przede wszystkim od realnego wpływu na organizację i ponoszonej odpowiedzialności biznesowej, a nie od samego stażu pracy.

(nil) es el valor que representa null o nada en el lenguaje de programación Ruby.

Normalmente, el sistema espera que un paquete de telemetría tenga una estructura exacta definida en el archivo tlm.txt. Esto incluye una longitud específica de datos y una lista específica de elementos (ID_ITEM) que se extraerán de esos datos. Si los datos que llegan del hardware tienen una longitud diferente o un formato no esperado, el sistema normalmente rechazaría el paquete o fallaría al intentar leerlo.

La Solución del "Catch-All" (Red de Seguridad): Si defines un paquete en tu configuración sin incluir ningún ID_ITEM (es decir, no dices qué campos específicos extraer), COSMOS trata ese paquete como un "recipiente genérico" o catch-all.

Un blob (abreviatura de Binary Large Object u objeto binario grande) es un conjunto de datos almacenados como un único elemento binario, sin que el sistema tenga que interpretar su contenido interno

Everyone should have the freedom to make their own choices about their body.

People made wrong ideas about Arab women because of stereotypes.

Students of color have knowledge and strengths that schools often do not value.

 Treating people like they are less than human is wrong. Everyone deserves respect.

Another book I am reminded of from this reading is Ralph Ellison’s The Invisible Man. In it Ellison has this passage: “ these white folks have newspapers, magazines, radios, spokesman to get their ideas across. If they want to tell the world, a lie, they can tell it so well that it becomes the truth; And if I tell them that you’re lying, they’ll tell the world, even if you prove you’re telling the truth. Because it’s the kind of lie they want to hear.” I think this quote is fitting for how racism in its many forms persists. They tell themselves lies and disguise them as facts. Such as with the case of segregation and taking away a vote. They tell themselves that it is “fairer” to both white and black folk, and people believe it because they want to believe it. Believing a pretty lie is much easier than accepting the ugly truth.

I believe gerrymandering is racially charged to this day. If districts are formed around the poorest of poor and richest of rich, the poorer districts receive less funding than the more wealthy districts. Take the case of Texas unlawful gerrymandering of 2025 in which the “Texas’s GOP-controlled legislature aggressively redrew its congressional map to target the political power of communities of color and try to create 5 more Republican seats in time for the 2026 midterms.” Not only does this affect voting but it affects education. It effects education funding but also how those votes are now distributed to silence people of colors voice on educational decisions in our government.

As I continue reading about the once (mostly) unsegregated states shifted to segregation I am somewhat bewildered by how much racism is exacerbated by outside contexts like the war or economy. Richard Wright wrote in 1945 in his book Black Boy, “ watching the white people eat would make my stomach churn and I would grow vaguely angry. Why could I not eat when I was hungry? Why did I always have to wait until others were through? I could not understand why some people had enough food and others did not.” Wrights question fits with the circumstances of why and how racism is intensified by things like the economy. It comes down to greed, and fairly obviously power. White supremacy elevates the needs of white people and their hunger above black peoples. It is a system that tells them to “wait their turn” and that serves white people first in every way (whether that be educationally, economically, or industrially).

About a year ago I read a book called 12 Million Black Voices by Richard Wright. The book went into heavy detail about the Great Migration and the different Key “personae” that impacted the black community as well as overlapped in terms of economic context as Black people did. In the book there is the Black community, the lords of the land (descendants of the slave owning class who still make the formerly enslaved work as sharecroppers on their plantation), bosses of the business (business owners/apartment complex owners), as well as the poor white. The poor whites were the ones situational context overlapped the most to the black community. They held power due to their whiteness, yet like black folk (to a degree) lacked economic power. This lack of economic power and inability to grow wealth made the poor whites fear and segregate the Black community. The bosses of the building liked it this way, because, rather than the poor whites blaming them it made Black people the “enemy.” This affected education too, because White people knew that education was a primary way to get into industry.

On-prem servers (abreviatura de on-premises servers o servidores locales)

lol

Trust is important and I believe that part of that trust is that they know that you'll have good intentions and not evaluate their performance in a disciplinary way.

I tried to highlight this whole sentence!

What is our responsible/respectful/productive action when we face supervisors in this way? I'm growing in a way that focuses on controlling myself and nothing more and this is making me think about supervisors I've had who don't want to change and I can't make them. I can't force someone to show me respect, so I think to would be interesting to read more about what we can do to manage through some of these challenges. Of course I'm happy to do this reading to continue to work on myself as a supervisor as well.

Et donc, quel programme ?

Qu'est-ce que ça signifie ?

ça j'aime moins...

Comment techniquement le faire, et partout ? Même en outre-mer ?

Personnellement, je trouve ça courageux, et ça, je respecte.

Make sure Figures refer to figure and sub figure letter

Also specify NoIR so that recordings can occur in low light conditions (under read light)

Add a figure showing key points on the body (pose estimation skeleton)

Body weight was measured before the first, fourth, and seventh sessions

Two water bottles were initially put into the cages after EPM so that mice could acclimate before drinking. EtOH bottles were put on around 1pm everyday

Rephrase to something not Monday Wednesday and Friday because it started on Tuesday and there was no weekend break like we usually do

Define CFW

Should be 1 for resilient/susceptible and 2 for ctrl/sds

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.

We thank the reviewer for this comment. The figure legends have been updated to include more details of all the statistical tests used.

1. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.

We agree with the reviewer and indeed, in previous studies on HIV-1 infection of human macrophages performed in the lab, we observed via immunofluorescence that the proportion of infected cells ranged from 20 to 40 %. At the time of submission, we did not have the possibility to label the native SNAT7 protein by immunofluorescence, as the commercial antibody used only works for western blotting.

In the meantime, we have been validating a new antibody (Proteintech) targeting SNAT7 for immunofluorescence. If this is confirmed, we will be able to detect and quantify HIV-1 p24 by immunofluorescence in SNAT7-depleted human macrophages and control cells, thus confirming our results in single-cell analysis.

Flow cytometry analyses are difficult to perform on primary human macrophages because these cells are highly adherent and must be detached first. The process induces significant cell death and damage. This is why we would prefer to carry out these analyses using immunofluorescence and microscopy on adhered cells. This option will be undoubtedly pursued.

1. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.

We apologize for this omission. The figures showing the increase in SNAT7 protein expression following HIV-1 infection at MOIs ranging from 0.05 to 0.5 were added to the new version of the manuscript (Supp. Fig. 1 C-F).

1. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3

We thank the reviewer for this comment. Circulating T lymphocytes isolated from the blood of healthy donors are now referred to resting lymphocytes in the new version of the manuscript, as opposed to activated T lymphocytes stimulated with IL2 and PHA-P for several days (Fig. 1 A-C).

The expression levels of SNAT7, both at the gene and protein levels, are lower in resting or IL2/PHA-P-activated T cells than in macrophages from the same donors. As suggested, we will perform a kinetic of T-cell activation upon HIV-1 infection to investigate how SNAT7 expression varies in these conditions.

1. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).

We thank the reviewer for this comment. Fig. 2B indeed shows one of the different donors analyzed. However, protein quantification across six different donors shows that SNAT7 is more depleted with siRNA #2 (Fig. 2C), and that Gag Pr55 protein levels are consequently more reduced, than with siRNA #1 (Fig. 2D).

We use GraphPad Prism software to perform statistical analysis. Depending on the test used, the software automatically plots the comparison bar and displays the p-value above it. We changed the representation of statistics as suggested.

Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.

The reviewer is right in pointing that we observed a stronger effect during the later stages of the viral cycle, from transcription of viral RNAs (Fig. 2I and Supp. Fig. 2G) to the production of viral particles in the supernatant (Fig. 2D-G), than during the earlier stage of reverse transcription (Fig. 3F, G). Also, it is also possible that we might have missed the peak in ERT/LRT production, which is transient.

It should be noted that SAMHD1 exhibits both dNTPase (Goldstone et al., 2011) and nuclease (Beloglazova et al., 2013) activities. The ability of SAMHD1 to restrict the virus, through dephosphorylation at T592, is mediated by its RNase activity (Ryoo et al., 2014), and not by the dNTPase activity (Welbourn et al., 2013; White et al., 2013).This could explain why SNAT7 exhibit a stronger impact on viral transcription than on reverse transcription.

Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF?

We thank the reviewer for this suggestion. As mentioned under comment #2, flow cytometry analyses are difficult to perform on strongly adherent primary human macrophages.

With regard to immunofluorescence, there is a technical limitation based on the species in which the antibodies are produced. The antibody that targets the native SNAT7 protein, which is currently being validated in our laboratory, is produced in rabbits. An anti-CAp24 antibody produced in goats can be used. It will then be necessary to co-label the cells with anti SAMHD1 and phospho-SAMHD1produced in mouse. We will try to find options to co-label the cells.

The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.

We respectfully disagree with the reviewer.

Figure 4D shows a representative blot of the six donors analysed. As mentioned, the depletion of SNAT7 in the absence of SAMHD1 reduces the production of the viral proteins GagPr55 and CAp24 (see Fig. 4D). This is illustrated by the quantifications (Fig. 4G–I). Following treatment with Vpx, GagPr55 protein expression in SNAT7 KD macrophages is reduced by a factor of 2.6 for siRNA #1 (mean = 1.48, light grey bar) and by a factor of 1.83 for siRNA #2 (mean = 2.13, orange bar), compared to the control (mean = 3.9, pink bar) (Fig. 4G). Similarly, CAp24 protein expression was reduced by a factor of 2.2 for siRNA #1 (mean = 2.05, light grey bar) and by a factor of 1.36 for siRNA #2 (mean = 3.34, orange bar), compared to the control (mean = 4.52, pink bar) (Fig. 4H).

These differences are therefore consistent between the Western blot and the quantifications. However, they are not significantly different to those observed in cells treated with Vpx and depleted with control siRNA, suggesting that the viral restriction observed in SNAT7 KD cells is primarily due to SAMHD1.

Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.

We thank the reviewer for this comment, we will perform the suggested experiment.

1. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions.

We thank the reviewer for this comment. The discussion will be modified further accordingly.

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics. We respectfully disagree with the reviewer.

The cells used here imply greater variability than a cell line, but are also more relevant.

Indeed, the effects observed in the late stages of HIV-1 production are:

• ~80 % decrease in viral transcription compared to the control (Fig. 2I),

• ~85 % decrease in CAp24 protein expression compared to the control, as quantified by western blot (Fig. 2E), or ~90 % by ELISA measurement (Fig. 2F),

• a reduction of more than 90 % in the release of infectious particles (Fig. 2G).

These results were all significant across donors, while SNAT7 depletion was always partial (Fig. 2C, between 31 to 62 % of depletion compared to the control in infected cells).

Therefore, the data were obtained from a mixture of depleted and non-depleted macrophages. This means that the results may be underestimated.

Together, our results show that SNAT7 is necessary for HIV-1 production.

However, reading the comments, we realized that our conclusions regarding reverse transcription were too strong. SNAT7 depletion does not affect viral fusion and reverse transcription. The manuscript was modified accordingly.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future.

For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes? We thank the reviewer for these questions.

To address the role of accessory viral proteins, we have already performed one experiment infecting hMDM with HIV-1 strains deleted for genes such as Nef, Vpr, Vpu and Vif, and have found no clear effect on SNAT7 protein expression compared to WT strains. As an alternative experiment, we could overexpress individual viral genes, such as Nef or Vpr, in HeLa cells and analyze their impact on SNAT7 expression by Western blot.

It is also possible that SNAT7 expression and recycling of lysosomal glutamine are modulated by the macrophage intrinsic immunity in response to HIV-1 infection.

The Thr592 motif of the SAMHD1 protein is phosphorylated by Cyclin A2/CDK1 and type 1 IFN in non-cycling cells, such as MDMs (Cribier et al., 2013). For now, the relationship between SNAT7 and SAMHD1 remains unclear. However, (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This has been added to the discussion to explain the relationship between the 3 partners.

**Referees cross-commenting** I think the comments from the other referees are reasonable and consistent with my assessment

Reviewer #1 (Significance (Required)):

Strength and limitations see above;

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.

We thank the reviewer for this comment. Indeed, there is a modest, but statistically significant increase in SNAT7 protein expression upon HIV-1 infection over time (Fig. 1G, H), without any modulation of SNAT7 gene expression (Fig. 1E). This indicates that the regulation of SNAT7 expression in this context is only at the translation level (i.e. increase of translation or stabilization of the SNAT7 protein).

As mentioned, Fig. 1H aggregates between 3 to 7 independent experiments on different donors depending on the infection time point. SNAT7 protein expression is increased already at 1 day post-infection and until 8 days. The statistical test used here, i.e. 2 way-ANOVA, compared Mock-infected and HIV-1-infected condition for each time point with the same number of donors. In this figure, the comparison is statistically different only at day 6 of the time course (7 donors). We agree that increasing the number of donors of the other time points could help to improve the statistical difference between control and infection condition.

We thank the reviewer for the suggestion mentioning the use of replication inhibitors in this experiment. We plan to use inhibitors of reverse transcription (Nevirapin) and integration (Dolutegravir).

The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.

We respectfully disagree with the reviewer for this question. Indeed, to evaluate the effects of SNAT7 on HIV-1 replication, we measured Gag Pr55 and Cap24 using a Western blot approach (Fig. 2B, D and E), but also assessed the quantity of Cap24 in the supernatants and lysates using an ELISA measurement, the quantity of infectious particles using TZM reporter cells, and total viral transcription or more specifically Gag Pr55 transcription using qPCR (Fig. 2F, G and I and Supp. Fig. 2G).

Regarding the quantification of CAp24 at the cell single level, please refer to comment #2 under Reviewer #1.

Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).

We thank the reviewer for this comment. Our samples are indeed a mixture of SNAT7-depleted and non-depleted macrophages and RNA interference in these cells often leads to a decrease of 50 % of the protein expression.

To determine whether SNAT7 is involved in the release of particles, we quantified Cap24 in cell lysates and in the cell culture medium separately, and normalized the results to the total protein content. The absence of SNAT7 reduced the amount of Cap24 measured by ELISA in both samples to the same extent, showing that there is no storage of Cap24-positive viral particles inside the infected macrophages. These data were initially pooled in one graph (Fig. 2F), but separate graphs are now provided in new Supp. Fig. 2 E, F.

Regarding the western blot shown in Fig. 2B, please refer to comment #5 under Reviewer #1.

In the new version of the manuscript, we arranged the figures and placed the later stages of the viral cycle in Fig. 2 and the earlier stages, such as fusion, reverse transcription and transcription, in Fig. 3.

Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.

We thank the reviewer for this suggestion to include inhibitors of viral replication as controls. In our experiments, cells were Mock-infected in parallel as a negative control of viral detection. We provide the results in the new version of the manuscript to show that (i) there is no detection of viral or Gag RNA in the absence of the virus, (ii) the expression of viral genes measured in HIV-1-infected SNAT7-depleted cells is not different from Mock-infected cells, indicating almost complete inhibition of viral transcription (Fig. 3H and Supp. Fig. 3B), also confirmed at the protein level (Fig. 2B, D-F).

Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.

We thank the reviewer for this comment. LRT concentrations are very low in human macrophages and more challenging to detect than ERT concentrations. This might explain why the differences observed between the SNAT7-depleted and control conditions appear less pronounced for LRT than for ERT.

Furthermore, we cannot rule out the possibility that SNAT7 has a cumulative effect throughout the viral cycle. While reverse transcription remains statistically unaltered, and despite the reduced levels of ERT and LRT in SNAT7-depleted macrophages (Fig. 3 F, G), there is a significant impact on the transcription of viral RNAs (Fig. 2I) and Gag (Supp. Fig. 2G). This step may also be altered by the ribonuclease activity of SAMHD1 (Beloglazova et al., 2013; Ryoo et al., 2014).

Finally, with the help of Dr Baek Kim in Atlanta, we attempted to quantify dNTP concentrations in our human macrophages. Unfortunately, it was not possible to draw any conclusions, as the concentrations of dNTPs extracted from our cells were far too low.

Furthermore, it should be noted that SAMHD1 viral restriction through its phosphorylation at T592 is not correlated with its dNTPase activity (Welbourn et al., 2013; White et al., 2013), but with its ribonuclease activity (Beloglazova et al., 2013; Ryoo et al., 2014). This is supporting why SNAT7, by modulating the ribonuclease activity of SAMHD1, could have a greater effect on viral transcription than on reverse transcription.

There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.

We thank the reviewer for this comment, but believe that Figure 2E rather than Figure 2G is to be mentioned regarding the quantification of CAp24 by Western blot and to be compared with Figure 4H.

In Fig. 2E, we observed an average reduction of 85 % in CAp24 expression normalized to Clathrin HC expression across different donors for both siRNAs targeting SNAT7. For Fig. 4H, there was a 73 % reduction in CAp24 levels for siRNA #1 and a 56 % reduction for siRNA #2. In addition, it should be noted that the reduction in Gag levels is greater in Fig. 4G (between 77 % and 83 %) than in Fig. 2D (between 55 % and 72 %).

Therefore, there is some variation in the results obtained with the different donors, which could be explained by variations in Gag cleavage among donors, but this does not impact the conclusions for both figures.

SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.

We thank the reviewer for this comment. As suggested, we will perform experiments to assess the impact of Vpx-mediated SAMHD1 degradation on viral transcription.

Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

We thank the reviewer for this comment. We will perform the suggested experiments to assess the impact of glutamine supplementation on viral transcription.

Reviewer #2 (Significance (Required)):

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn. Major Concerns： 1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.

We thank the reviewer for this comment. It is worth noting that (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity using drugs decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This is now further discussed in the discussion section of the manuscript.

The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.

We thank the reviewer for this comment. Please, refer to comment #5 under Reviewer #2.

Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.

We thank the reviewer for this comment. The discussion has been modified accordingly.

It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.

We thank the reviewer for this suggestion but don’t really understand why this would strengthen our conclusions. Indeed, despite the known variability between donors and technical limitations to transduce cells, we chose human blood monocyte-derived macrophages as a relevant non-transformed model for HIV-1 infection of macrophages. They also represent to some extent the human diversity.

The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

We thank the reviewer for this comment. The discussion points to some elements of potential translation and limitations of the study.

Reviewer #3 (Significance (Required)):

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience:This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.

We thank the reviewer for this comment. The figure legends have been updated to include more details of all the statistical tests used.

1. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.

We agree with the reviewer and indeed, in previous studies on HIV-1 infection of human macrophages performed in the lab, we observed via immunofluorescence that the proportion of infected cells ranged from 20 to 40 %. At the time of submission, we did not have the possibility to label the native SNAT7 protein by immunofluorescence, as the commercial antibody used only works for western blotting.

In the meantime, we have been validating a new antibody (Proteintech) targeting SNAT7 for immunofluorescence. If this is confirmed, we will be able to detect and quantify HIV-1 p24 by immunofluorescence in SNAT7-depleted human macrophages and control cells, thus confirming our results in single-cell analysis.

Flow cytometry analyses are difficult to perform on primary human macrophages because these cells are highly adherent and must be detached first. The process induces significant cell death and damage. This is why we would prefer to carry out these analyses using immunofluorescence and microscopy on adhered cells. This option will be undoubtedly pursued.

1. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.

We apologize for this omission. The figures showing the increase in SNAT7 protein expression following HIV-1 infection at MOIs ranging from 0.05 to 0.5 were added to the new version of the manuscript (Supp. Fig. 1 C-F).

1. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3

We thank the reviewer for this comment. Circulating T lymphocytes isolated from the blood of healthy donors are now referred to resting lymphocytes in the new version of the manuscript, as opposed to activated T lymphocytes stimulated with IL2 and PHA-P for several days (Fig. 1 A-C).

The expression levels of SNAT7, both at the gene and protein levels, are lower in resting or IL2/PHA-P-activated T cells than in macrophages from the same donors. As suggested, we will perform a kinetic of T-cell activation upon HIV-1 infection to investigate how SNAT7 expression varies in these conditions.

1. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).

We thank the reviewer for this comment. Fig. 2B indeed shows one of the different donors analyzed. However, protein quantification across six different donors shows that SNAT7 is more depleted with siRNA #2 (Fig. 2C), and that Gag Pr55 protein levels are consequently more reduced, than with siRNA #1 (Fig. 2D).

We use GraphPad Prism software to perform statistical analysis. Depending on the test used, the software automatically plots the comparison bar and displays the p-value above it. We changed the representation of statistics as suggested.

Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.

The reviewer is right in pointing that we observed a stronger effect during the later stages of the viral cycle, from transcription of viral RNAs (Fig. 2I and Supp. Fig. 2G) to the production of viral particles in the supernatant (Fig. 2D-G), than during the earlier stage of reverse transcription (Fig. 3F, G). Also, it is also possible that we might have missed the peak in ERT/LRT production, which is transient.

It should be noted that SAMHD1 exhibits both dNTPase (Goldstone et al., 2011) and nuclease (Beloglazova et al., 2013) activities. The ability of SAMHD1 to restrict the virus, through dephosphorylation at T592, is mediated by its RNase activity (Ryoo et al., 2014), and not by the dNTPase activity (Welbourn et al., 2013; White et al., 2013).This could explain why SNAT7 exhibit a stronger impact on viral transcription than on reverse transcription.

Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF?

We thank the reviewer for this suggestion. As mentioned under comment #2, flow cytometry analyses are difficult to perform on strongly adherent primary human macrophages.

With regard to immunofluorescence, there is a technical limitation based on the species in which the antibodies are produced. The antibody that targets the native SNAT7 protein, which is currently being validated in our laboratory, is produced in rabbits. An anti-CAp24 antibody produced in goats can be used. It will then be necessary to co-label the cells with anti SAMHD1 and phospho-SAMHD1produced in mouse. We will try to find options to co-label the cells.

The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.

We respectfully disagree with the reviewer.

Figure 4D shows a representative blot of the six donors analysed. As mentioned, the depletion of SNAT7 in the absence of SAMHD1 reduces the production of the viral proteins GagPr55 and CAp24 (see Fig. 4D). This is illustrated by the quantifications (Fig. 4G–I). Following treatment with Vpx, GagPr55 protein expression in SNAT7 KD macrophages is reduced by a factor of 2.6 for siRNA #1 (mean = 1.48, light grey bar) and by a factor of 1.83 for siRNA #2 (mean = 2.13, orange bar), compared to the control (mean = 3.9, pink bar) (Fig. 4G). Similarly, CAp24 protein expression was reduced by a factor of 2.2 for siRNA #1 (mean = 2.05, light grey bar) and by a factor of 1.36 for siRNA #2 (mean = 3.34, orange bar), compared to the control (mean = 4.52, pink bar) (Fig. 4H).

These differences are therefore consistent between the Western blot and the quantifications. However, they are not significantly different to those observed in cells treated with Vpx and depleted with control siRNA, suggesting that the viral restriction observed in SNAT7 KD cells is primarily due to SAMHD1.

Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.

We thank the reviewer for this comment, we will perform the suggested experiment.

1. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions.

We thank the reviewer for this comment. The discussion will be modified further accordingly.

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics. We respectfully disagree with the reviewer.

The cells used here imply greater variability than a cell line, but are also more relevant.

Indeed, the effects observed in the late stages of HIV-1 production are:

• ~80 % decrease in viral transcription compared to the control (Fig. 2I),

• ~85 % decrease in CAp24 protein expression compared to the control, as quantified by western blot (Fig. 2E), or ~90 % by ELISA measurement (Fig. 2F),

• a reduction of more than 90 % in the release of infectious particles (Fig. 2G).

These results were all significant across donors, while SNAT7 depletion was always partial (Fig. 2C, between 31 to 62 % of depletion compared to the control in infected cells).

Therefore, the data were obtained from a mixture of depleted and non-depleted macrophages. This means that the results may be underestimated.

Together, our results show that SNAT7 is necessary for HIV-1 production.

However, reading the comments, we realized that our conclusions regarding reverse transcription were too strong. SNAT7 depletion does not affect viral fusion and reverse transcription. The manuscript was modified accordingly.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future.

For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes? We thank the reviewer for these questions.

To address the role of accessory viral proteins, we have already performed one experiment infecting hMDM with HIV-1 strains deleted for genes such as Nef, Vpr, Vpu and Vif, and have found no clear effect on SNAT7 protein expression compared to WT strains. As an alternative experiment, we could overexpress individual viral genes, such as Nef or Vpr, in HeLa cells and analyze their impact on SNAT7 expression by Western blot.

It is also possible that SNAT7 expression and recycling of lysosomal glutamine are modulated by the macrophage intrinsic immunity in response to HIV-1 infection.

The Thr592 motif of the SAMHD1 protein is phosphorylated by Cyclin A2/CDK1 and type 1 IFN in non-cycling cells, such as MDMs (Cribier et al., 2013). For now, the relationship between SNAT7 and SAMHD1 remains unclear. However, (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This has been added to the discussion to explain the relationship between the 3 partners.

**Referees cross-commenting** I think the comments from the other referees are reasonable and consistent with my assessment

Reviewer #1 (Significance (Required)):

Strength and limitations see above;

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.

We thank the reviewer for this comment. Indeed, there is a modest, but statistically significant increase in SNAT7 protein expression upon HIV-1 infection over time (Fig. 1G, H), without any modulation of SNAT7 gene expression (Fig. 1E). This indicates that the regulation of SNAT7 expression in this context is only at the translation level (i.e. increase of translation or stabilization of the SNAT7 protein).

As mentioned, Fig. 1H aggregates between 3 to 7 independent experiments on different donors depending on the infection time point. SNAT7 protein expression is increased already at 1 day post-infection and until 8 days. The statistical test used here, i.e. 2 way-ANOVA, compared Mock-infected and HIV-1-infected condition for each time point with the same number of donors. In this figure, the comparison is statistically different only at day 6 of the time course (7 donors). We agree that increasing the number of donors of the other time points could help to improve the statistical difference between control and infection condition.

We thank the reviewer for the suggestion mentioning the use of replication inhibitors in this experiment. We plan to use inhibitors of reverse transcription (Nevirapin) and integration (Dolutegravir).

The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.

We respectfully disagree with the reviewer for this question. Indeed, to evaluate the effects of SNAT7 on HIV-1 replication, we measured Gag Pr55 and Cap24 using a Western blot approach (Fig. 2B, D and E), but also assessed the quantity of Cap24 in the supernatants and lysates using an ELISA measurement, the quantity of infectious particles using TZM reporter cells, and total viral transcription or more specifically Gag Pr55 transcription using qPCR (Fig. 2F, G and I and Supp. Fig. 2G).

Regarding the quantification of CAp24 at the cell single level, please refer to comment #2 under Reviewer #1.

Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).

We thank the reviewer for this comment. Our samples are indeed a mixture of SNAT7-depleted and non-depleted macrophages and RNA interference in these cells often leads to a decrease of 50 % of the protein expression.

To determine whether SNAT7 is involved in the release of particles, we quantified Cap24 in cell lysates and in the cell culture medium separately, and normalized the results to the total protein content. The absence of SNAT7 reduced the amount of Cap24 measured by ELISA in both samples to the same extent, showing that there is no storage of Cap24-positive viral particles inside the infected macrophages. These data were initially pooled in one graph (Fig. 2F), but separate graphs are now provided in new Supp. Fig. 2 E, F.

Regarding the western blot shown in Fig. 2B, please refer to comment #5 under Reviewer #1.

In the new version of the manuscript, we arranged the figures and placed the later stages of the viral cycle in Fig. 2 and the earlier stages, such as fusion, reverse transcription and transcription, in Fig. 3.

Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.

We thank the reviewer for this suggestion to include inhibitors of viral replication as controls. In our experiments, cells were Mock-infected in parallel as a negative control of viral detection. We provide the results in the new version of the manuscript to show that (i) there is no detection of viral or Gag RNA in the absence of the virus, (ii) the expression of viral genes measured in HIV-1-infected SNAT7-depleted cells is not different from Mock-infected cells, indicating almost complete inhibition of viral transcription (Fig. 3H and Supp. Fig. 3B), also confirmed at the protein level (Fig. 2B, D-F).

Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.

We thank the reviewer for this comment. LRT concentrations are very low in human macrophages and more challenging to detect than ERT concentrations. This might explain why the differences observed between the SNAT7-depleted and control conditions appear less pronounced for LRT than for ERT.

Furthermore, we cannot rule out the possibility that SNAT7 has a cumulative effect throughout the viral cycle. While reverse transcription remains statistically unaltered, and despite the reduced levels of ERT and LRT in SNAT7-depleted macrophages (Fig. 3 F, G), there is a significant impact on the transcription of viral RNAs (Fig. 2I) and Gag (Supp. Fig. 2G). This step may also be altered by the ribonuclease activity of SAMHD1 (Beloglazova et al., 2013; Ryoo et al., 2014).

Finally, with the help of Dr Baek Kim in Atlanta, we attempted to quantify dNTP concentrations in our human macrophages. Unfortunately, it was not possible to draw any conclusions, as the concentrations of dNTPs extracted from our cells were far too low.

Furthermore, it should be noted that SAMHD1 viral restriction through its phosphorylation at T592 is not correlated with its dNTPase activity (Welbourn et al., 2013; White et al., 2013), but with its ribonuclease activity (Beloglazova et al., 2013; Ryoo et al., 2014). This is supporting why SNAT7, by modulating the ribonuclease activity of SAMHD1, could have a greater effect on viral transcription than on reverse transcription.

There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.

We thank the reviewer for this comment, but believe that Figure 2E rather than Figure 2G is to be mentioned regarding the quantification of CAp24 by Western blot and to be compared with Figure 4H.

In Fig. 2E, we observed an average reduction of 85 % in CAp24 expression normalized to Clathrin HC expression across different donors for both siRNAs targeting SNAT7. For Fig. 4H, there was a 73 % reduction in CAp24 levels for siRNA #1 and a 56 % reduction for siRNA #2. In addition, it should be noted that the reduction in Gag levels is greater in Fig. 4G (between 77 % and 83 %) than in Fig. 2D (between 55 % and 72 %).

Therefore, there is some variation in the results obtained with the different donors, which could be explained by variations in Gag cleavage among donors, but this does not impact the conclusions for both figures.

SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.

We thank the reviewer for this comment. As suggested, we will perform experiments to assess the impact of Vpx-mediated SAMHD1 degradation on viral transcription.

Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

We thank the reviewer for this comment. We will perform the suggested experiments to assess the impact of glutamine supplementation on viral transcription.

Reviewer #2 (Significance (Required)):

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn. Major Concerns： 1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.

We thank the reviewer for this comment. It is worth noting that (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity using drugs decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This is now further discussed in the discussion section of the manuscript.

The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.

We thank the reviewer for this comment. Please, refer to comment #5 under Reviewer #2.

Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.

We thank the reviewer for this comment. The discussion has been modified accordingly.

It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.

We thank the reviewer for this suggestion but don’t really understand why this would strengthen our conclusions. Indeed, despite the known variability between donors and technical limitations to transduce cells, we chose human blood monocyte-derived macrophages as a relevant non-transformed model for HIV-1 infection of macrophages. They also represent to some extent the human diversity.

The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

We thank the reviewer for this comment. The discussion points to some elements of potential translation and limitations of the study.

Reviewer #3 (Significance (Required)):

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience:This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.

We thank the reviewer for this comment. The figure legends have been updated to include more details of all the statistical tests used.

1. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.

We agree with the reviewer and indeed, in previous studies on HIV-1 infection of human macrophages performed in the lab, we observed via immunofluorescence that the proportion of infected cells ranged from 20 to 40 %. At the time of submission, we did not have the possibility to label the native SNAT7 protein by immunofluorescence, as the commercial antibody used only works for western blotting.

In the meantime, we have been validating a new antibody (Proteintech) targeting SNAT7 for immunofluorescence. If this is confirmed, we will be able to detect and quantify HIV-1 p24 by immunofluorescence in SNAT7-depleted human macrophages and control cells, thus confirming our results in single-cell analysis.

Flow cytometry analyses are difficult to perform on primary human macrophages because these cells are highly adherent and must be detached first. The process induces significant cell death and damage. This is why we would prefer to carry out these analyses using immunofluorescence and microscopy on adhered cells. This option will be undoubtedly pursued.

1. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.

We apologize for this omission. The figures showing the increase in SNAT7 protein expression following HIV-1 infection at MOIs ranging from 0.05 to 0.5 were added to the new version of the manuscript (Supp. Fig. 1 C-F).

1. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3

We thank the reviewer for this comment. Circulating T lymphocytes isolated from the blood of healthy donors are now referred to resting lymphocytes in the new version of the manuscript, as opposed to activated T lymphocytes stimulated with IL2 and PHA-P for several days (Fig. 1 A-C).

The expression levels of SNAT7, both at the gene and protein levels, are lower in resting or IL2/PHA-P-activated T cells than in macrophages from the same donors. As suggested, we will perform a kinetic of T-cell activation upon HIV-1 infection to investigate how SNAT7 expression varies in these conditions.

1. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).

We thank the reviewer for this comment. Fig. 2B indeed shows one of the different donors analyzed. However, protein quantification across six different donors shows that SNAT7 is more depleted with siRNA #2 (Fig. 2C), and that Gag Pr55 protein levels are consequently more reduced, than with siRNA #1 (Fig. 2D).

We use GraphPad Prism software to perform statistical analysis. Depending on the test used, the software automatically plots the comparison bar and displays the p-value above it. We changed the representation of statistics as suggested.

Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.

The reviewer is right in pointing that we observed a stronger effect during the later stages of the viral cycle, from transcription of viral RNAs (Fig. 2I and Supp. Fig. 2G) to the production of viral particles in the supernatant (Fig. 2D-G), than during the earlier stage of reverse transcription (Fig. 3F, G). Also, it is also possible that we might have missed the peak in ERT/LRT production, which is transient.

It should be noted that SAMHD1 exhibits both dNTPase (Goldstone et al., 2011) and nuclease (Beloglazova et al., 2013) activities. The ability of SAMHD1 to restrict the virus, through dephosphorylation at T592, is mediated by its RNase activity (Ryoo et al., 2014), and not by the dNTPase activity (Welbourn et al., 2013; White et al., 2013).This could explain why SNAT7 exhibit a stronger impact on viral transcription than on reverse transcription.

Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF?

We thank the reviewer for this suggestion. As mentioned under comment #2, flow cytometry analyses are difficult to perform on strongly adherent primary human macrophages.

With regard to immunofluorescence, there is a technical limitation based on the species in which the antibodies are produced. The antibody that targets the native SNAT7 protein, which is currently being validated in our laboratory, is produced in rabbits. An anti-CAp24 antibody produced in goats can be used. It will then be necessary to co-label the cells with anti SAMHD1 and phospho-SAMHD1produced in mouse. We will try to find options to co-label the cells.

The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.

We respectfully disagree with the reviewer.

Figure 4D shows a representative blot of the six donors analysed. As mentioned, the depletion of SNAT7 in the absence of SAMHD1 reduces the production of the viral proteins GagPr55 and CAp24 (see Fig. 4D). This is illustrated by the quantifications (Fig. 4G–I). Following treatment with Vpx, GagPr55 protein expression in SNAT7 KD macrophages is reduced by a factor of 2.6 for siRNA #1 (mean = 1.48, light grey bar) and by a factor of 1.83 for siRNA #2 (mean = 2.13, orange bar), compared to the control (mean = 3.9, pink bar) (Fig. 4G). Similarly, CAp24 protein expression was reduced by a factor of 2.2 for siRNA #1 (mean = 2.05, light grey bar) and by a factor of 1.36 for siRNA #2 (mean = 3.34, orange bar), compared to the control (mean = 4.52, pink bar) (Fig. 4H).

These differences are therefore consistent between the Western blot and the quantifications. However, they are not significantly different to those observed in cells treated with Vpx and depleted with control siRNA, suggesting that the viral restriction observed in SNAT7 KD cells is primarily due to SAMHD1.

Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.

We thank the reviewer for this comment, we will perform the suggested experiment.

1. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions.

We thank the reviewer for this comment. The discussion will be modified further accordingly.

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics. We respectfully disagree with the reviewer.

The cells used here imply greater variability than a cell line, but are also more relevant.

Indeed, the effects observed in the late stages of HIV-1 production are:

• ~80 % decrease in viral transcription compared to the control (Fig. 2I),

• ~85 % decrease in CAp24 protein expression compared to the control, as quantified by western blot (Fig. 2E), or ~90 % by ELISA measurement (Fig. 2F),

• a reduction of more than 90 % in the release of infectious particles (Fig. 2G).

These results were all significant across donors, while SNAT7 depletion was always partial (Fig. 2C, between 31 to 62 % of depletion compared to the control in infected cells).

Therefore, the data were obtained from a mixture of depleted and non-depleted macrophages. This means that the results may be underestimated.

Together, our results show that SNAT7 is necessary for HIV-1 production.

However, reading the comments, we realized that our conclusions regarding reverse transcription were too strong. SNAT7 depletion does not affect viral fusion and reverse transcription. The manuscript was modified accordingly.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future.

For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes? We thank the reviewer for these questions.

To address the role of accessory viral proteins, we have already performed one experiment infecting hMDM with HIV-1 strains deleted for genes such as Nef, Vpr, Vpu and Vif, and have found no clear effect on SNAT7 protein expression compared to WT strains. As an alternative experiment, we could overexpress individual viral genes, such as Nef or Vpr, in HeLa cells and analyze their impact on SNAT7 expression by Western blot.

It is also possible that SNAT7 expression and recycling of lysosomal glutamine are modulated by the macrophage intrinsic immunity in response to HIV-1 infection.

The Thr592 motif of the SAMHD1 protein is phosphorylated by Cyclin A2/CDK1 and type 1 IFN in non-cycling cells, such as MDMs (Cribier et al., 2013). For now, the relationship between SNAT7 and SAMHD1 remains unclear. However, (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This has been added to the discussion to explain the relationship between the 3 partners.

**Referees cross-commenting** I think the comments from the other referees are reasonable and consistent with my assessment

Reviewer #1 (Significance (Required)):

Strength and limitations see above;

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.

We thank the reviewer for this comment. Indeed, there is a modest, but statistically significant increase in SNAT7 protein expression upon HIV-1 infection over time (Fig. 1G, H), without any modulation of SNAT7 gene expression (Fig. 1E). This indicates that the regulation of SNAT7 expression in this context is only at the translation level (i.e. increase of translation or stabilization of the SNAT7 protein).

As mentioned, Fig. 1H aggregates between 3 to 7 independent experiments on different donors depending on the infection time point. SNAT7 protein expression is increased already at 1 day post-infection and until 8 days. The statistical test used here, i.e. 2 way-ANOVA, compared Mock-infected and HIV-1-infected condition for each time point with the same number of donors. In this figure, the comparison is statistically different only at day 6 of the time course (7 donors). We agree that increasing the number of donors of the other time points could help to improve the statistical difference between control and infection condition.

We thank the reviewer for the suggestion mentioning the use of replication inhibitors in this experiment. We plan to use inhibitors of reverse transcription (Nevirapin) and integration (Dolutegravir).

The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.

We respectfully disagree with the reviewer for this question. Indeed, to evaluate the effects of SNAT7 on HIV-1 replication, we measured Gag Pr55 and Cap24 using a Western blot approach (Fig. 2B, D and E), but also assessed the quantity of Cap24 in the supernatants and lysates using an ELISA measurement, the quantity of infectious particles using TZM reporter cells, and total viral transcription or more specifically Gag Pr55 transcription using qPCR (Fig. 2F, G and I and Supp. Fig. 2G).

Regarding the quantification of CAp24 at the cell single level, please refer to comment #2 under Reviewer #1.

Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).

We thank the reviewer for this comment. Our samples are indeed a mixture of SNAT7-depleted and non-depleted macrophages and RNA interference in these cells often leads to a decrease of 50 % of the protein expression.

To determine whether SNAT7 is involved in the release of particles, we quantified Cap24 in cell lysates and in the cell culture medium separately, and normalized the results to the total protein content. The absence of SNAT7 reduced the amount of Cap24 measured by ELISA in both samples to the same extent, showing that there is no storage of Cap24-positive viral particles inside the infected macrophages. These data were initially pooled in one graph (Fig. 2F), but separate graphs are now provided in new Supp. Fig. 2 E, F.

Regarding the western blot shown in Fig. 2B, please refer to comment #5 under Reviewer #1.

In the new version of the manuscript, we arranged the figures and placed the later stages of the viral cycle in Fig. 2 and the earlier stages, such as fusion, reverse transcription and transcription, in Fig. 3.

Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.

We thank the reviewer for this suggestion to include inhibitors of viral replication as controls. In our experiments, cells were Mock-infected in parallel as a negative control of viral detection. We provide the results in the new version of the manuscript to show that (i) there is no detection of viral or Gag RNA in the absence of the virus, (ii) the expression of viral genes measured in HIV-1-infected SNAT7-depleted cells is not different from Mock-infected cells, indicating almost complete inhibition of viral transcription (Fig. 3H and Supp. Fig. 3B), also confirmed at the protein level (Fig. 2B, D-F).

Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.

We thank the reviewer for this comment. LRT concentrations are very low in human macrophages and more challenging to detect than ERT concentrations. This might explain why the differences observed between the SNAT7-depleted and control conditions appear less pronounced for LRT than for ERT.

Furthermore, we cannot rule out the possibility that SNAT7 has a cumulative effect throughout the viral cycle. While reverse transcription remains statistically unaltered, and despite the reduced levels of ERT and LRT in SNAT7-depleted macrophages (Fig. 3 F, G), there is a significant impact on the transcription of viral RNAs (Fig. 2I) and Gag (Supp. Fig. 2G). This step may also be altered by the ribonuclease activity of SAMHD1 (Beloglazova et al., 2013; Ryoo et al., 2014).

Finally, with the help of Dr Baek Kim in Atlanta, we attempted to quantify dNTP concentrations in our human macrophages. Unfortunately, it was not possible to draw any conclusions, as the concentrations of dNTPs extracted from our cells were far too low.

Furthermore, it should be noted that SAMHD1 viral restriction through its phosphorylation at T592 is not correlated with its dNTPase activity (Welbourn et al., 2013; White et al., 2013), but with its ribonuclease activity (Beloglazova et al., 2013; Ryoo et al., 2014). This is supporting why SNAT7, by modulating the ribonuclease activity of SAMHD1, could have a greater effect on viral transcription than on reverse transcription.

There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.

We thank the reviewer for this comment, but believe that Figure 2E rather than Figure 2G is to be mentioned regarding the quantification of CAp24 by Western blot and to be compared with Figure 4H.

In Fig. 2E, we observed an average reduction of 85 % in CAp24 expression normalized to Clathrin HC expression across different donors for both siRNAs targeting SNAT7. For Fig. 4H, there was a 73 % reduction in CAp24 levels for siRNA #1 and a 56 % reduction for siRNA #2. In addition, it should be noted that the reduction in Gag levels is greater in Fig. 4G (between 77 % and 83 %) than in Fig. 2D (between 55 % and 72 %).

Therefore, there is some variation in the results obtained with the different donors, which could be explained by variations in Gag cleavage among donors, but this does not impact the conclusions for both figures.

SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.

We thank the reviewer for this comment. As suggested, we will perform experiments to assess the impact of Vpx-mediated SAMHD1 degradation on viral transcription.

Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

We thank the reviewer for this comment. We will perform the suggested experiments to assess the impact of glutamine supplementation on viral transcription.

Reviewer #2 (Significance (Required)):

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn. Major Concerns： 1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.

We thank the reviewer for this comment. It is worth noting that (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity using drugs decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This is now further discussed in the discussion section of the manuscript.

The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.

We thank the reviewer for this comment. Please, refer to comment #5 under Reviewer #2.

Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.

We thank the reviewer for this comment. The discussion has been modified accordingly.

It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.

We thank the reviewer for this suggestion but don’t really understand why this would strengthen our conclusions. Indeed, despite the known variability between donors and technical limitations to transduce cells, we chose human blood monocyte-derived macrophages as a relevant non-transformed model for HIV-1 infection of macrophages. They also represent to some extent the human diversity.

The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

We thank the reviewer for this comment. The discussion points to some elements of potential translation and limitations of the study.

Reviewer #3 (Significance (Required)):

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience:This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.

We thank the reviewer for this comment. The figure legends have been updated to include more details of all the statistical tests used.

1. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.

We agree with the reviewer and indeed, in previous studies on HIV-1 infection of human macrophages performed in the lab, we observed via immunofluorescence that the proportion of infected cells ranged from 20 to 40 %. At the time of submission, we did not have the possibility to label the native SNAT7 protein by immunofluorescence, as the commercial antibody used only works for western blotting.

In the meantime, we have been validating a new antibody (Proteintech) targeting SNAT7 for immunofluorescence. If this is confirmed, we will be able to detect and quantify HIV-1 p24 by immunofluorescence in SNAT7-depleted human macrophages and control cells, thus confirming our results in single-cell analysis.

Flow cytometry analyses are difficult to perform on primary human macrophages because these cells are highly adherent and must be detached first. The process induces significant cell death and damage. This is why we would prefer to carry out these analyses using immunofluorescence and microscopy on adhered cells. This option will be undoubtedly pursued.

1. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.

We apologize for this omission. The figures showing the increase in SNAT7 protein expression following HIV-1 infection at MOIs ranging from 0.05 to 0.5 were added to the new version of the manuscript (Supp. Fig. 1 C-F).

1. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3

We thank the reviewer for this comment. Circulating T lymphocytes isolated from the blood of healthy donors are now referred to resting lymphocytes in the new version of the manuscript, as opposed to activated T lymphocytes stimulated with IL2 and PHA-P for several days (Fig. 1 A-C).

The expression levels of SNAT7, both at the gene and protein levels, are lower in resting or IL2/PHA-P-activated T cells than in macrophages from the same donors. As suggested, we will perform a kinetic of T-cell activation upon HIV-1 infection to investigate how SNAT7 expression varies in these conditions.

1. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).

We thank the reviewer for this comment. Fig. 2B indeed shows one of the different donors analyzed. However, protein quantification across six different donors shows that SNAT7 is more depleted with siRNA #2 (Fig. 2C), and that Gag Pr55 protein levels are consequently more reduced, than with siRNA #1 (Fig. 2D).

We use GraphPad Prism software to perform statistical analysis. Depending on the test used, the software automatically plots the comparison bar and displays the p-value above it. We changed the representation of statistics as suggested.

Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.

The reviewer is right in pointing that we observed a stronger effect during the later stages of the viral cycle, from transcription of viral RNAs (Fig. 2I and Supp. Fig. 2G) to the production of viral particles in the supernatant (Fig. 2D-G), than during the earlier stage of reverse transcription (Fig. 3F, G). Also, it is also possible that we might have missed the peak in ERT/LRT production, which is transient.

It should be noted that SAMHD1 exhibits both dNTPase (Goldstone et al., 2011) and nuclease (Beloglazova et al., 2013) activities. The ability of SAMHD1 to restrict the virus, through dephosphorylation at T592, is mediated by its RNase activity (Ryoo et al., 2014), and not by the dNTPase activity (Welbourn et al., 2013; White et al., 2013).This could explain why SNAT7 exhibit a stronger impact on viral transcription than on reverse transcription.

Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF?

We thank the reviewer for this suggestion. As mentioned under comment #2, flow cytometry analyses are difficult to perform on strongly adherent primary human macrophages.

With regard to immunofluorescence, there is a technical limitation based on the species in which the antibodies are produced. The antibody that targets the native SNAT7 protein, which is currently being validated in our laboratory, is produced in rabbits. An anti-CAp24 antibody produced in goats can be used. It will then be necessary to co-label the cells with anti SAMHD1 and phospho-SAMHD1produced in mouse. We will try to find options to co-label the cells.

The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.

We respectfully disagree with the reviewer.

Figure 4D shows a representative blot of the six donors analysed. As mentioned, the depletion of SNAT7 in the absence of SAMHD1 reduces the production of the viral proteins GagPr55 and CAp24 (see Fig. 4D). This is illustrated by the quantifications (Fig. 4G–I). Following treatment with Vpx, GagPr55 protein expression in SNAT7 KD macrophages is reduced by a factor of 2.6 for siRNA #1 (mean = 1.48, light grey bar) and by a factor of 1.83 for siRNA #2 (mean = 2.13, orange bar), compared to the control (mean = 3.9, pink bar) (Fig. 4G). Similarly, CAp24 protein expression was reduced by a factor of 2.2 for siRNA #1 (mean = 2.05, light grey bar) and by a factor of 1.36 for siRNA #2 (mean = 3.34, orange bar), compared to the control (mean = 4.52, pink bar) (Fig. 4H).

These differences are therefore consistent between the Western blot and the quantifications. However, they are not significantly different to those observed in cells treated with Vpx and depleted with control siRNA, suggesting that the viral restriction observed in SNAT7 KD cells is primarily due to SAMHD1.

Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.

We thank the reviewer for this comment, we will perform the suggested experiment.

1. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions.

We thank the reviewer for this comment. The discussion will be modified further accordingly.

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics. We respectfully disagree with the reviewer.

The cells used here imply greater variability than a cell line, but are also more relevant.

Indeed, the effects observed in the late stages of HIV-1 production are:

• ~80 % decrease in viral transcription compared to the control (Fig. 2I),

• ~85 % decrease in CAp24 protein expression compared to the control, as quantified by western blot (Fig. 2E), or ~90 % by ELISA measurement (Fig. 2F),

• a reduction of more than 90 % in the release of infectious particles (Fig. 2G).

These results were all significant across donors, while SNAT7 depletion was always partial (Fig. 2C, between 31 to 62 % of depletion compared to the control in infected cells).

Therefore, the data were obtained from a mixture of depleted and non-depleted macrophages. This means that the results may be underestimated.

Together, our results show that SNAT7 is necessary for HIV-1 production.

However, reading the comments, we realized that our conclusions regarding reverse transcription were too strong. SNAT7 depletion does not affect viral fusion and reverse transcription. The manuscript was modified accordingly.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future.

For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes? We thank the reviewer for these questions.

To address the role of accessory viral proteins, we have already performed one experiment infecting hMDM with HIV-1 strains deleted for genes such as Nef, Vpr, Vpu and Vif, and have found no clear effect on SNAT7 protein expression compared to WT strains. As an alternative experiment, we could overexpress individual viral genes, such as Nef or Vpr, in HeLa cells and analyze their impact on SNAT7 expression by Western blot.

It is also possible that SNAT7 expression and recycling of lysosomal glutamine are modulated by the macrophage intrinsic immunity in response to HIV-1 infection.

The Thr592 motif of the SAMHD1 protein is phosphorylated by Cyclin A2/CDK1 and type 1 IFN in non-cycling cells, such as MDMs (Cribier et al., 2013). For now, the relationship between SNAT7 and SAMHD1 remains unclear. However, (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This has been added to the discussion to explain the relationship between the 3 partners.

**Referees cross-commenting** I think the comments from the other referees are reasonable and consistent with my assessment

Reviewer #1 (Significance (Required)):

Strength and limitations see above;

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.

We thank the reviewer for this comment. Indeed, there is a modest, but statistically significant increase in SNAT7 protein expression upon HIV-1 infection over time (Fig. 1G, H), without any modulation of SNAT7 gene expression (Fig. 1E). This indicates that the regulation of SNAT7 expression in this context is only at the translation level (i.e. increase of translation or stabilization of the SNAT7 protein).

As mentioned, Fig. 1H aggregates between 3 to 7 independent experiments on different donors depending on the infection time point. SNAT7 protein expression is increased already at 1 day post-infection and until 8 days. The statistical test used here, i.e. 2 way-ANOVA, compared Mock-infected and HIV-1-infected condition for each time point with the same number of donors. In this figure, the comparison is statistically different only at day 6 of the time course (7 donors). We agree that increasing the number of donors of the other time points could help to improve the statistical difference between control and infection condition.

We thank the reviewer for the suggestion mentioning the use of replication inhibitors in this experiment. We plan to use inhibitors of reverse transcription (Nevirapin) and integration (Dolutegravir).

The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.

We respectfully disagree with the reviewer for this question. Indeed, to evaluate the effects of SNAT7 on HIV-1 replication, we measured Gag Pr55 and Cap24 using a Western blot approach (Fig. 2B, D and E), but also assessed the quantity of Cap24 in the supernatants and lysates using an ELISA measurement, the quantity of infectious particles using TZM reporter cells, and total viral transcription or more specifically Gag Pr55 transcription using qPCR (Fig. 2F, G and I and Supp. Fig. 2G).

Regarding the quantification of CAp24 at the cell single level, please refer to comment #2 under Reviewer #1.

Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).

We thank the reviewer for this comment. Our samples are indeed a mixture of SNAT7-depleted and non-depleted macrophages and RNA interference in these cells often leads to a decrease of 50 % of the protein expression.

To determine whether SNAT7 is involved in the release of particles, we quantified Cap24 in cell lysates and in the cell culture medium separately, and normalized the results to the total protein content. The absence of SNAT7 reduced the amount of Cap24 measured by ELISA in both samples to the same extent, showing that there is no storage of Cap24-positive viral particles inside the infected macrophages. These data were initially pooled in one graph (Fig. 2F), but separate graphs are now provided in new Supp. Fig. 2 E, F.

Regarding the western blot shown in Fig. 2B, please refer to comment #5 under Reviewer #1.

In the new version of the manuscript, we arranged the figures and placed the later stages of the viral cycle in Fig. 2 and the earlier stages, such as fusion, reverse transcription and transcription, in Fig. 3.

Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.

We thank the reviewer for this suggestion to include inhibitors of viral replication as controls. In our experiments, cells were Mock-infected in parallel as a negative control of viral detection. We provide the results in the new version of the manuscript to show that (i) there is no detection of viral or Gag RNA in the absence of the virus, (ii) the expression of viral genes measured in HIV-1-infected SNAT7-depleted cells is not different from Mock-infected cells, indicating almost complete inhibition of viral transcription (Fig. 3H and Supp. Fig. 3B), also confirmed at the protein level (Fig. 2B, D-F).

Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.

We thank the reviewer for this comment. LRT concentrations are very low in human macrophages and more challenging to detect than ERT concentrations. This might explain why the differences observed between the SNAT7-depleted and control conditions appear less pronounced for LRT than for ERT.

Furthermore, we cannot rule out the possibility that SNAT7 has a cumulative effect throughout the viral cycle. While reverse transcription remains statistically unaltered, and despite the reduced levels of ERT and LRT in SNAT7-depleted macrophages (Fig. 3 F, G), there is a significant impact on the transcription of viral RNAs (Fig. 2I) and Gag (Supp. Fig. 2G). This step may also be altered by the ribonuclease activity of SAMHD1 (Beloglazova et al., 2013; Ryoo et al., 2014).

Finally, with the help of Dr Baek Kim in Atlanta, we attempted to quantify dNTP concentrations in our human macrophages. Unfortunately, it was not possible to draw any conclusions, as the concentrations of dNTPs extracted from our cells were far too low.

Furthermore, it should be noted that SAMHD1 viral restriction through its phosphorylation at T592 is not correlated with its dNTPase activity (Welbourn et al., 2013; White et al., 2013), but with its ribonuclease activity (Beloglazova et al., 2013; Ryoo et al., 2014). This is supporting why SNAT7, by modulating the ribonuclease activity of SAMHD1, could have a greater effect on viral transcription than on reverse transcription.

There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.

We thank the reviewer for this comment, but believe that Figure 2E rather than Figure 2G is to be mentioned regarding the quantification of CAp24 by Western blot and to be compared with Figure 4H.

In Fig. 2E, we observed an average reduction of 85 % in CAp24 expression normalized to Clathrin HC expression across different donors for both siRNAs targeting SNAT7. For Fig. 4H, there was a 73 % reduction in CAp24 levels for siRNA #1 and a 56 % reduction for siRNA #2. In addition, it should be noted that the reduction in Gag levels is greater in Fig. 4G (between 77 % and 83 %) than in Fig. 2D (between 55 % and 72 %).

Therefore, there is some variation in the results obtained with the different donors, which could be explained by variations in Gag cleavage among donors, but this does not impact the conclusions for both figures.

SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.

We thank the reviewer for this comment. As suggested, we will perform experiments to assess the impact of Vpx-mediated SAMHD1 degradation on viral transcription.

Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

We thank the reviewer for this comment. We will perform the suggested experiments to assess the impact of glutamine supplementation on viral transcription.

Reviewer #2 (Significance (Required)):

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn. Major Concerns： 1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.

We thank the reviewer for this comment. It is worth noting that (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity using drugs decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This is now further discussed in the discussion section of the manuscript.

The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.

We thank the reviewer for this comment. Please, refer to comment #5 under Reviewer #2.

Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.

We thank the reviewer for this comment. The discussion has been modified accordingly.

It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.

We thank the reviewer for this suggestion but don’t really understand why this would strengthen our conclusions. Indeed, despite the known variability between donors and technical limitations to transduce cells, we chose human blood monocyte-derived macrophages as a relevant non-transformed model for HIV-1 infection of macrophages. They also represent to some extent the human diversity.

The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

We thank the reviewer for this comment. The discussion points to some elements of potential translation and limitations of the study.

Reviewer #3 (Significance (Required)):

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience:This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

2.15.1.0 Reviewer #1 (Evidence, reproducibility and clarity (Required)):

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.

We thank the reviewer for this comment. The figure legends have been updated to include more details of all the statistical tests used.

1. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.

We agree with the reviewer and indeed, in previous studies on HIV-1 infection of human macrophages performed in the lab, we observed via immunofluorescence that the proportion of infected cells ranged from 20 to 40 %. At the time of submission, we did not have the possibility to label the native SNAT7 protein by immunofluorescence, as the commercial antibody used only works for western blotting.

In the meantime, we have been validating a new antibody (Proteintech) targeting SNAT7 for immunofluorescence. If this is confirmed, we will be able to detect and quantify HIV-1 p24 by immunofluorescence in SNAT7-depleted human macrophages and control cells, thus confirming our results in single-cell analysis.

Flow cytometry analyses are difficult to perform on primary human macrophages because these cells are highly adherent and must be detached first. The process induces significant cell death and damage. This is why we would prefer to carry out these analyses using immunofluorescence and microscopy on adhered cells. This option will be undoubtedly pursued.

1. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.

We apologize for this omission. The figures showing the increase in SNAT7 protein expression following HIV-1 infection at MOIs ranging from 0.05 to 0.5 were added to the new version of the manuscript (Supp. Fig. 1 C-F).

1. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3

We thank the reviewer for this comment. Circulating T lymphocytes isolated from the blood of healthy donors are now referred to resting lymphocytes in the new version of the manuscript, as opposed to activated T lymphocytes stimulated with IL2 and PHA-P for several days (Fig. 1 A-C).

The expression levels of SNAT7, both at the gene and protein levels, are lower in resting or IL2/PHA-P-activated T cells than in macrophages from the same donors. As suggested, we will perform a kinetic of T-cell activation upon HIV-1 infection to investigate how SNAT7 expression varies in these conditions.

1. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).

We thank the reviewer for this comment. Fig. 2B indeed shows one of the different donors analyzed. However, protein quantification across six different donors shows that SNAT7 is more depleted with siRNA #2 (Fig. 2C), and that Gag Pr55 protein levels are consequently more reduced, than with siRNA #1 (Fig. 2D).

We use GraphPad Prism software to perform statistical analysis. Depending on the test used, the software automatically plots the comparison bar and displays the p-value above it. We changed the representation of statistics as suggested.

Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.

The reviewer is right in pointing that we observed a stronger effect during the later stages of the viral cycle, from transcription of viral RNAs (Fig. 2I and Supp. Fig. 2G) to the production of viral particles in the supernatant (Fig. 2D-G), than during the earlier stage of reverse transcription (Fig. 3F, G). Also, it is also possible that we might have missed the peak in ERT/LRT production, which is transient.

It should be noted that SAMHD1 exhibits both dNTPase (Goldstone et al., 2011) and nuclease (Beloglazova et al., 2013) activities. The ability of SAMHD1 to restrict the virus, through dephosphorylation at T592, is mediated by its RNase activity (Ryoo et al., 2014), and not by the dNTPase activity (Welbourn et al., 2013; White et al., 2013).This could explain why SNAT7 exhibit a stronger impact on viral transcription than on reverse transcription.

Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF?

We thank the reviewer for this suggestion. As mentioned under comment #2, flow cytometry analyses are difficult to perform on strongly adherent primary human macrophages.

With regard to immunofluorescence, there is a technical limitation based on the species in which the antibodies are produced. The antibody that targets the native SNAT7 protein, which is currently being validated in our laboratory, is produced in rabbits. An anti-CAp24 antibody produced in goats can be used. It will then be necessary to co-label the cells with anti SAMHD1 and phospho-SAMHD1produced in mouse. We will try to find options to co-label the cells.

The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.

We respectfully disagree with the reviewer.

Figure 4D shows a representative blot of the six donors analysed. As mentioned, the depletion of SNAT7 in the absence of SAMHD1 reduces the production of the viral proteins GagPr55 and CAp24 (see Fig. 4D). This is illustrated by the quantifications (Fig. 4G–I). Following treatment with Vpx, GagPr55 protein expression in SNAT7 KD macrophages is reduced by a factor of 2.6 for siRNA #1 (mean = 1.48, light grey bar) and by a factor of 1.83 for siRNA #2 (mean = 2.13, orange bar), compared to the control (mean = 3.9, pink bar) (Fig. 4G). Similarly, CAp24 protein expression was reduced by a factor of 2.2 for siRNA #1 (mean = 2.05, light grey bar) and by a factor of 1.36 for siRNA #2 (mean = 3.34, orange bar), compared to the control (mean = 4.52, pink bar) (Fig. 4H).

These differences are therefore consistent between the Western blot and the quantifications. However, they are not significantly different to those observed in cells treated with Vpx and depleted with control siRNA, suggesting that the viral restriction observed in SNAT7 KD cells is primarily due to SAMHD1.

1. Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.

We thank the reviewer for this comment, we will perform the suggested experiment.

1. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions.

We thank the reviewer for this comment. The discussion will be modified further accordingly.

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics. We respectfully disagree with the reviewer.

The cells used here imply greater variability than a cell line, but are also more relevant.

Indeed, the effects observed in the late stages of HIV-1 production are:

• ~80 % decrease in viral transcription compared to the control (Fig. 2I),

• ~85 % decrease in CAp24 protein expression compared to the control, as quantified by western blot (Fig. 2E), or ~90 % by ELISA measurement (Fig. 2F),

• a reduction of more than 90 % in the release of infectious particles (Fig. 2G).

These results were all significant across donors, while SNAT7 depletion was always partial (Fig. 2C, between 31 to 62 % of depletion compared to the control in infected cells).

Therefore, the data were obtained from a mixture of depleted and non-depleted macrophages. This means that the results may be underestimated.

Together, our results show that SNAT7 is necessary for HIV-1 production.

However, reading the comments, we realized that our conclusions regarding reverse transcription were too strong. SNAT7 depletion does not affect viral fusion and reverse transcription. The manuscript was modified accordingly.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future.

For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes? We thank the reviewer for these questions.

To address the role of accessory viral proteins, we have already performed one experiment infecting hMDM with HIV-1 strains deleted for genes such as Nef, Vpr, Vpu and Vif, and have found no clear effect on SNAT7 protein expression compared to WT strains. As an alternative experiment, we could overexpress individual viral genes, such as Nef or Vpr, in HeLa cells and analyze their impact on SNAT7 expression by Western blot.

It is also possible that SNAT7 expression and recycling of lysosomal glutamine are modulated by the macrophage intrinsic immunity in response to HIV-1 infection.

The Thr592 motif of the SAMHD1 protein is phosphorylated by Cyclin A2/CDK1 and type 1 IFN in non-cycling cells, such as MDMs (Cribier et al., 2013). For now, the relationship between SNAT7 and SAMHD1 remains unclear. However, (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This has been added to the discussion to explain the relationship between the 3 partners.

**Referees cross-commenting** I think the comments from the other referees are reasonable and consistent with my assessment

Reviewer #1 (Significance (Required)):

Strength and limitations see above;

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.

We thank the reviewer for this comment. Indeed, there is a modest, but statistically significant increase in SNAT7 protein expression upon HIV-1 infection over time (Fig. 1G, H), without any modulation of SNAT7 gene expression (Fig. 1E). This indicates that the regulation of SNAT7 expression in this context is only at the translation level (i.e. increase of translation or stabilization of the SNAT7 protein).

As mentioned, Fig. 1H aggregates between 3 to 7 independent experiments on different donors depending on the infection time point. SNAT7 protein expression is increased already at 1 day post-infection and until 8 days. The statistical test used here, i.e. 2 way-ANOVA, compared Mock-infected and HIV-1-infected condition for each time point with the same number of donors. In this figure, the comparison is statistically different only at day 6 of the time course (7 donors). We agree that increasing the number of donors of the other time points could help to improve the statistical difference between control and infection condition.

We thank the reviewer for the suggestion mentioning the use of replication inhibitors in this experiment. We plan to use inhibitors of reverse transcription (Nevirapin) and integration (Dolutegravir).

The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.

We respectfully disagree with the reviewer for this question. Indeed, to evaluate the effects of SNAT7 on HIV-1 replication, we measured Gag Pr55 and Cap24 using a Western blot approach (Fig. 2B, D and E), but also assessed the quantity of Cap24 in the supernatants and lysates using an ELISA measurement, the quantity of infectious particles using TZM reporter cells, and total viral transcription or more specifically Gag Pr55 transcription using qPCR (Fig. 2F, G and I and Supp. Fig. 2G).

Regarding the quantification of CAp24 at the cell single level, please refer to comment #2 under Reviewer #1.

Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).

We thank the reviewer for this comment. Our samples are indeed a mixture of SNAT7-depleted and non-depleted macrophages and RNA interference in these cells often leads to a decrease of 50 % of the protein expression.

To determine whether SNAT7 is involved in the release of particles, we quantified Cap24 in cell lysates and in the cell culture medium separately, and normalized the results to the total protein content. The absence of SNAT7 reduced the amount of Cap24 measured by ELISA in both samples to the same extent, showing that there is no storage of Cap24-positive viral particles inside the infected macrophages. These data were initially pooled in one graph (Fig. 2F), but separate graphs are now provided in new Supp. Fig. 2 E, F.

Regarding the western blot shown in Fig. 2B, please refer to comment #5 under Reviewer #1.

In the new version of the manuscript, we arranged the figures and placed the later stages of the viral cycle in Fig. 2 and the earlier stages, such as fusion, reverse transcription and transcription, in Fig. 3.

Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.

We thank the reviewer for this suggestion to include inhibitors of viral replication as controls. In our experiments, cells were Mock-infected in parallel as a negative control of viral detection. We provide the results in the new version of the manuscript to show that (i) there is no detection of viral or Gag RNA in the absence of the virus, (ii) the expression of viral genes measured in HIV-1-infected SNAT7-depleted cells is not different from Mock-infected cells, indicating almost complete inhibition of viral transcription (Fig. 3H and Supp. Fig. 3B), also confirmed at the protein level (Fig. 2B, D-F).

Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.

We thank the reviewer for this comment. LRT concentrations are very low in human macrophages and more challenging to detect than ERT concentrations. This might explain why the differences observed between the SNAT7-depleted and control conditions appear less pronounced for LRT than for ERT.

Furthermore, we cannot rule out the possibility that SNAT7 has a cumulative effect throughout the viral cycle. While reverse transcription remains statistically unaltered, and despite the reduced levels of ERT and LRT in SNAT7-depleted macrophages (Fig. 3 F, G), there is a significant impact on the transcription of viral RNAs (Fig. 2I) and Gag (Supp. Fig. 2G). This step may also be altered by the ribonuclease activity of SAMHD1 (Beloglazova et al., 2013; Ryoo et al., 2014).

Finally, with the help of Dr Baek Kim in Atlanta, we attempted to quantify dNTP concentrations in our human macrophages. Unfortunately, it was not possible to draw any conclusions, as the concentrations of dNTPs extracted from our cells were far too low.

Furthermore, it should be noted that SAMHD1 viral restriction through its phosphorylation at T592 is not correlated with its dNTPase activity (Welbourn et al., 2013; White et al., 2013), but with its ribonuclease activity (Beloglazova et al., 2013; Ryoo et al., 2014). This is supporting why SNAT7, by modulating the ribonuclease activity of SAMHD1, could have a greater effect on viral transcription than on reverse transcription.

There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.

We thank the reviewer for this comment, but believe that Figure 2E rather than Figure 2G is to be mentioned regarding the quantification of CAp24 by Western blot and to be compared with Figure 4H.

In Fig. 2E, we observed an average reduction of 85 % in CAp24 expression normalized to Clathrin HC expression across different donors for both siRNAs targeting SNAT7. For Fig. 4H, there was a 73 % reduction in CAp24 levels for siRNA #1 and a 56 % reduction for siRNA #2. In addition, it should be noted that the reduction in Gag levels is greater in Fig. 4G (between 77 % and 83 %) than in Fig. 2D (between 55 % and 72 %).

Therefore, there is some variation in the results obtained with the different donors, which could be explained by variations in Gag cleavage among donors, but this does not impact the conclusions for both figures.

SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.

We thank the reviewer for this comment. As suggested, we will perform experiments to assess the impact of Vpx-mediated SAMHD1 degradation on viral transcription.

Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

We thank the reviewer for this comment. We will perform the suggested experiments to assess the impact of glutamine supplementation on viral transcription.

Reviewer #2 (Significance (Required)):

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn. Major Concerns： 1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.

We thank the reviewer for this comment. It is worth noting that (Meng et al., 2022) demonstrated that SNAT7 positively regulates mTORC1 activity at the lysosomal membrane through release of lysosomal glutamine, and (Dias et al., 2024) showed that inhibiting mTORC1 activity using drugs decreases SAMHD1 Thr592 phosphorylation in hMDM. Therefore, we could speculate that the absence of SNAT7 down-regulates mTORC1 activity, which then leads to decreased SAMHD1 phosphorylation. This is now further discussed in the discussion section of the manuscript.

The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.

We thank the reviewer for this comment. Please, refer to comment #5 under Reviewer #2.

Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.

We thank the reviewer for this comment. The discussion has been modified accordingly.

It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.

We thank the reviewer for this suggestion but don’t really understand why this would strengthen our conclusions. Indeed, despite the known variability between donors and technical limitations to transduce cells, we chose human blood monocyte-derived macrophages as a relevant non-transformed model for HIV-1 infection of macrophages. They also represent to some extent the human diversity.

The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

We thank the reviewer for this comment. The discussion points to some elements of potential translation and limitations of the study.

Reviewer #3 (Significance (Required)):

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience:This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

2.15.1.0

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

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Referee #3

Evidence, reproducibility and clarity

This study investigates the role of the lysosomal glutamine transporter SLC38A7/SNAT7 in HIV‑1 replication in primary human macrophages. The authors demonstrate that SNAT7 is highly expressed in macrophages and upregulated upon HIV‑1 infection. They show that SNAT7 depletion inhibits HIV‑1 production at the reverse transcription step without affecting viral fusion or global cellular translation/transcription. Mechanistically, SNAT7 knockdown reduces the inhibitory phosphorylation of SAMHD1 at T592, and degradation of SAMHD1 by Vpx fully rescues viral replication. Extracellular glutamine supplementation partially restores HIV‑1 production in SNAT7‑deficient cells. Overall, the authors report interesting observations; however, the mechanistic investigation remains preliminary, raising concerns about whether the data fully support all the conclusions drawn.

Major Concerns

1. The mechanistic depth is insufficient. The authors do not elucidate how glutamine regulates SAMHD1 T592 phosphorylation, whether through metabolite‑mediated control of kinases/phosphatases or via indirect effects.
2. The authors do not measure intracellular dNTP levels upon SNAT7 knockdown, which is the key functional substrate of SAMHD1. They also do not directly demonstrate that glutamine supplementation restores dNTP pools.
3. Extracellular glutamine only partially rescues viral production, implying the existence of transport‑independent functions of SNAT7 or additional pathways. This important observation is not discussed.
4. It is suggested that the key findings be validated in immortalized THP‑1 cells differentiated into macrophage‑like cells by PMA.
5. The Discussion section should be expanded to include the potential translational implications and limitations of the present study.

Significance

General assessment: This study identifies the lysosomal glutamine transporter SLC38A7/SNAT7 as a novel host dependency factor for HIV‑1 replication in primary human macrophages. The major strengths include the use of physiologically relevant primary macrophage models, a well-organized experimental pipeline from expression profiling to functional validation, and the establishment of a link between SNAT7, glutamine metabolism, and the HIV restriction factor SAMHD1.

Advance: It extends current understanding of HIV‑1 host dependency factors and immunometabolism by revealing a compartment‑specific metabolic pathway that supports viral reverse transcription.

Audience: This work will primarily interest specialized researchers in HIV‑1 biology, host-virus interactions, restriction factors, and antiviral innate immunity.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #2

Evidence, reproducibility and clarity

In this report, Herit and colleagues describe the role of a HIV-1 dependency factor that promotes virus replication in macrophages. The authors suggest that the lysosomal membrane-associated SNAT7 glutamine transporter is a HIV dependency factor, that promotes virus replication by enhancing reverse transcription and Gag synthesis. The authors use transient knock-down approaches in primary macrophages to identify that SNAT7 depletion does not impact viral entry but inhibits early reverse transcription which was reversed by exogenous glutamine addition. While reverse transcription enhancement was likely due to selective increase in phosho-SAMHD1 expression, mechanisms by which SNAT7 enhanced viral gene expression were not clearly defined. These are well-controlled studies that pinpoint the role of SNAT7 in the early steps of viral life cycle and highlight the intricate interplay between macrophage metabolism and HIV-1 replication. While the question that is addressed is important, and the hypothesis overall sound, the data presented needs to be strengthened to support the conclusions. There are numerous weaknesses in data interpretation as well.

1. Figure 1: SNAT7 expression was selectively enhanced upon differentiation of monocytes into macrophages but absent in CD4+ T cells. Though there is a claim of enhancement of SNAT7 expression upon HIV-1 infection of macrophages, RT-qPCR analysis shows the opposite trend (Fig 1E) and SNAT7 protein expression changes are modest. Statistical analysis in Fig. 1H needs to be revisited. The number of replicates vary for the lysates harvested at different day post infection, which might have an impact on the statistical test. To determine if SNAT7 expression enhancement is dependent on establishment of virus infection, as the authors imply, control lysates of virus infections in presence of replication inhibitors should be included.
2. The authors rely exclusively on western blot analysis for HIV-1 Gag expression in cell lysates as a measure of effects of SNAT7 on virus replication. Single cell analysis such as intracellular p24gag analysis by FACS should be included; this will provide a better measure of effects of SNAT7 onHIV-1 infection establishment.
3. Knockdown of SNAT7 in MDMs was partial at best; only 30-50% decrease in expression (Fig 2C), but the effects on viral gene expression (Fig. 2I), p24 release and infectious particle production is dramatic (Fig. 2F and G). This discrepancy is not addressed. Does SNAT7 knock-down negatively impact virus particle release? Please note that the representative WB in Fig 2B does not correlate with the quantification in Fig. 2D. There are no p55gag or p24gag bands in SNAT7#1 siRNA condition (Fig. 2B)? Data could also be rearranged to follow the logical sequence of virus replication cycle (viral RNa expression followed by Gag expression, and then release).
4. Data interpretation would be greatly improved by including infection controls (RT or integrase inhibitors) to confirm that measurements of viral RNA and Gag are indeed modulated by SNAT7 expression.
5. Figure 3: Decrease in SNAT7 expression in macrophages resulted in lower levels of early reverse transcripts. But surprisingly, LRT levels were not as affected by decreases in SNAT7 expression. The authors go on to suggest that decreases in early RT are due to loss of phospho-SAMHD1 and increases in catalytically active form of SAMHD1. Mechanistically this does not make sense: LRT should be similarly affected by increase in catalytically active SAMHD1. dNTP concentrations should be measured to determine if the rescue of RT is dependent on SAMHD1 dNTPase activity.
6. There is lack of consistency in the data: p24 release upon SNAT7 depletion is highly variable. While there is a dramatic >90-95% decrease in p24 release (Fig. 2G), the effects are much more moderate in Fig. 4H (50-60% attenuation), even though siRNA-mediated depletion was similar across the data sets. The authors should comment on the variability in their findings.
7. SNAT7 is postulated to affect 2 steps in the virus life cycle: reverse transcription and viral transcription. But Vpx-mediated SAMHD1 degradation reversed both. Its not clear to me as to how SAMHD1 degradation impacts the role of SNAT7 in viral transcription. No explanation is provided.
8. Exogenous addition of glutamine only partially restored Gag synthesis and p24 release, which could be attributed to increased cytoplasmic levels and viral protein synthesis. What about effects on reverse transcription and viral gene expression?

Significance

This is a novel finding, as there are limited number of studies on amino acid transporters and HIV-1 replication enhancement in macrophages. Most of the previous work has focused on CD4 T cells. These studies on SNAT7 and HIV-1 infection establishment in macrophages might better inform the influences of macrophage metabolism on HIV-1 persistence and inflammatory responses.

Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.

Learn more at Review Commons

Referee #1

Evidence, reproducibility and clarity

This study from the Niedergang lab establishes SNAT7 as a host-dependency factor in human macrophages that supports HIV-1 replication. They show a modest increase in SNAT7 levels HIV-1 infected macrophages and suggest that SNAT7 levels are transiently increased. Employing siRNA against SNAT7 they show reduction in HIV-1 protein levels and viral RNAs and claim that there is a block of reverse transcription in SNAT7 KD cells. Focusing on a known HIV-1 restriction factor in macrophages, SAMHD1, they interconnect the SNAT7 depletion with a reduction in phosphorylated, i.e. catalytical inactive SAMHD1 arguing that SNAT7 regulates the phosphorylation and thereby antiviral activity of SAMHD1. Since SNAT7 is a glutamine transporter that provides this AA from lysosomes, they lastly supplement glutamine and this somehow rescues the reduction of HIV-1 production in SNAT7 KD cells.

Major comments:

The strength of this manuscript is the clear focus on primary human macrophages that are HIV-1 infected and the interconnection of HIV-1 replication to the SNAT7 siRNA KD experiments in combination with SAMHD1 depletion and lastly glutamine supplementation. This establishes a stringent and coherent story line. The effects reported are modest; high variability is not a problem since using primary hMDM this is expected and can be addressed by testing several donors and applying stringent statistics.

1. Having said so, I realize that while they give information on the statistical test used, i.e. one-way ANOVA they miss to explain the post-test used to assess significance (i.e. Bonferroni, Fishers LSD, whatsoever). Please add this information.
2. Another issue that might underestimate the effects of HIV-1 infection on SNAT7 levels and vice versa of SNAT7 KD on HIV-1 replication is the non-single cell approach employed, i.e. WBlots. I assume that HIV-1 infection rates in macrophages are not super high, usually not exceeding 20-30%. So indeed the effects the authors observe could be much higher, when checking at the single cell level. I do not know about the SNAT7 ab, but all the other reagents should work via flow cytometry and could hence improve the readout a lot.
3. Furthermore the authors never commented about a dose-response effect in terms of HIV-1 infection levels. There is a MOI dependency described for Suppl.Fig.1 C-F, unfortunately the data is missing in the manuscript.
4. Figure1: specify circulating T lymphocytes. I would expect to see levels of SNAT7 in PHA or CD3/CD28 activated lymphocytes versus resting T cells and a time course of SNAT7 levels upon activation. I think even though SNAT7 levels in T cells might be low, they could also be increased by HIV-1 infection and it is essential that the authors test for this. If not, the result is a valid negative control. For this they should employ HIV-1 primary strains with a tropism for T cells, or at least lab-adapted HIV-1 NL4-3
5. Figure 2 again single cell measurements could reveal much more pronounced effects; it is a bit counterintuitive that siRNA #2 is more efficient in SNAT7 KD but has higher levels of HIV-1 replication in terms of Gag levels. I assume when looking at the stats it is always a comparison to the Ctl treated cells (C-G), but this is not entirely clear. Unify labeling as compared to the stats in Fig.2 I (this also applies for all the other figs).
6. Figure 3: It is a bit odd that they finally conclude on RT as essential step that is reduced in the absence of SNAT7 and then they fail to provide statistical significance for this (Fig.3 panels F and G). One would expect that RT is much more affected given the huge effects on HIV-1 capsid and particle production shown in Fig.2 F, G and I.
7. Figure 4; again single cell flow measurements of SAMHD1, pSAMHD1 and p24 /SNAT7 might help to more clearly discriminate effects that are specifically induced upon infection or happen in virally infected cells. Maybe alternatively IF? The wblot shown in panel D does not really reflect the point the authors want to make by the quantification in panels G-I. Primary data (D) suggests that SNAT7 KD reduces HIV-1 production even in the absence of SAMHD1. The quantification rather indicates that SNAT7 KD does not affect HIV-1 production in the absence of SAMHD1. This needs clarification/corroboration by orthogonal approaches.
8. Figure 5: show SAMHD1 and pSAMHD1 levels upon glutamine supplementation.
9. I think the discussion is very thin, mainly summarizing the results; but fails to give broader context or critically discuss the limitations and further directions

Looking at the data as a whole, I think the results support a modest functional importance of SNAT7 for HIV-1 production in macrophages. I acknowledge that the experiments in primary macrophages are prone to high variability in different donors and the authors transparently depicted their data. However clearly, I would advice the authors to tune down the extend in which they claim SNAT7-dependency given this huge variability and the sometimes-borderline statistics.

On top, there are a lot of optional experiments I am sure the authors are aware of that should be done at least in the future. For instance, how does HIV-1 upregulate SNAT7, is a viral accessory protein involved? What is the mechanism of SNAT7 dependent SAMHD1 phosphorylation? Does SNAT7 (or glutamine) regulate the activity of the SAMHD1 associated kinase / phosphatase) If so, does this impact on other targets of these enzymes?

Referees cross-commenting

I think the comments from the other referees are reasonable and consistent with my assessment

Significance

Strength and limitations see above

Significance: I think this work is of high interest for virologists working in the field of HIV-1 and infection of myeloid cells. In case SNAT7 (and hence glutamine) indeed regulates the phosphorylation of SAMHD1, there could potentially be broad relevance of this work. However unfortunately, this aspect remains underdeveloped and is also not discussed

Field of expertise: HIV-1, immunology, cell biology

Speaks volumes about the significance of the experiments objective

powerful wording and description of how much food took over their lives.

The next 4 paragraphs truly visualizes starvation syndrome, how your body goes into survival mode and the psychological effects that can occur.

RIP KevinNetwork

add 2026 no?

no way this is accessible. too small

is this accessible? to read and see. ? is the font the issue or the size?

fourth

put her third

Identify the figure that should be compared, then base your recommendation on that figure. If the options come in different sizes, compare their price per unit before deciding.

someone should tell bill gates that the optimal human nutrition is the carnivore diet ("a pound beef a day keeps the doctor away"), with the smallest ecological footprint, because ruminant animals (cows, sheep, goats) only need grass and water.

source: shawn baker - the carnivore diet (2019)

but apparently, bill gates is too busy expanding hell on earth, trying to preserve human overpopulation and hightech at all cost... i just hope that he fails as soon as possible, to minimize the side-effects of his stupid experiment (war on nature, luciferianism)

After calculating the total cost from each supplier, how many pesos will Herminia save by choosing the lower-cost supplier?

Do not sign, approve, pay, or forward the document until the discrepancy has been resolved. Recheck your calculations once, then report the difference to the person who prepared the document. Clearly state both figures, for example: "The receipt shows PHP 2,320, but the line items total PHP 2,220."

Summary:

• Steve Yegge introduces Gas Town as an orchestrator for running many Claude Code-style coding agents at once.

"Gas Town helps you with the tedium of running lots of Claude Code instances."

• His thesis: coding agents are no longer the whole product, they are the worker units. The next layer is orchestration.

"Claude Code is just a building block, and it’s going to be all about AI workflows and 'Kubernetes for agents'."

• Gas Town is intentionally for advanced users already juggling many agents, not casual AI coding users.

"If you’re not at least Stage 7, or maybe Stage 6 and very brave, then you will not be able to use Gas Town."

• The human role shifts from coder to Overseer / PM: feed work, shape direction, resolve ambiguity, keep throughput high.

"You are a Product Manager, and Gas Town is an Idea Compiler."

• Core architecture: Town is the HQ, Rigs are project repos, Mayor is the main concierge agent, Polecats do swarm implementation, Refinery manages merges, Witness monitors workers, Deacon coordinates patrols, Dogs help with maintenance, and Crew are long-lived agents for direct collaboration.

"The town (Go binary gt) manages and orchestrates all the workers across all your rigs."

• Beads are the Git-backed unit of work and identity. They power tasks, mail, events, hooks, workflows, and orchestration state.

"Beads are the atomic unit of work in Gas Town."

• The key propulsion rule is GUPP: if work is on an agent’s hook, the agent must run it.

"If there is work on your hook, YOU MUST RUN IT."

• Gas Town treats sessions as disposable and agent identities as persistent.

"Sessions are ephemeral; they are the 'cattle' in the Kubernetes 'pets vs cattle' metaphor."

• The MEOW stack models work as workflows: Beads, Epics, Molecules, Protomolecules, Formulas, Wisps, and guzzoline.

"Molecules are workflows, chained with Beads."

• Its durability idea is Nondeterministic Idempotence: execution may vary, but persistent workflow state lets new sessions resume and eventually finish.

"Even though the path is fully nondeterministic, the outcome — the workflow you wanted to run — eventually finishes."

• Work rolls up into Convoys, which are the tracked delivery units for swarms of tasks.

"Everything in Gas Town, all work, rolls up into a Convoy."

• The big warning: Gas Town is young, chaotic, expensive, tmux-based, and optimized for throughput over neatness.

"The focus is throughput: creation and correction at the speed of thought."

Concepts & Tools:

• Gas Town: agent orchestration system for managing many coding agents.
• Beads: Git-backed issue/work database and control plane.
• GUPP: rule that agents must execute hooked work.
• MEOW: workflow abstraction stack for molecularized work.
• Convoys: tracked units of work delivery.
• tmux: current primary UI.
• Commands mentioned: gt, gt sling, gt nudge, gt seance, gt handoff, bd create, bd show.

References:

• Gas Town
• Beads
• Revenge of the Junior Developer
• MAKER paper

💻/thinkpad/🧊/me/📓/2026/7/0/5/%3D/lindy.learn/🌐/to/One.Shot~Critically.Exploring.Reimagining-%20the.Instruction%20Model

💻/thinkpad/🧊/me/📓/2026/7/0/5/=/lindy.learn

=lindy.learn~search@Brave

This article has been published in Scientific Reports on 04 May 2026 (https://doi.org/10.1038/s41598-026-51310-7). (from Siqi Xia)

ここまで書いて大丈夫かな?全部をやっているわけではないし保証できないと思うので、本記事と関係が薄い内容なので、以下の様な表現でも良いかなって思いました。 「OSSはリリース後、多くの人たちによって検証されてたり、セキュリティベンダーなどのより検証してくれています。リリース後しばらく時間をおくことでマルウェアなどが仕込まれている可能性が低くなり、安全性を高めることができます。」くらいでどうかな?

これは、 pre-commitにない機能?　prekの特徴であればその事を書いておくと良いかも

そうなんだー。これは注目ですね。

対象外とは？？　コミットできない?　コミットしない?　そもそも .git/ 配下だからpullしても共有されないって意味? Gitフックを使っていないのでこの部分の意図がわからなかったです。

https://bafybeiedbtomg2udebl5sgoc7eyraxduotlphicybbffvbkuwz7bttu7zm.ipfs.inbrowser.link/?filename=%3Dmetadesigners.network.outlining.metadesign.html#Paradigm_Design

Paradigms are - complex, self-perpetuating systems

that are co-sustained by habitual processes

that are part of the prevailing social, cultural, economic, aesthetic, psychological, technological and linguistic milieu.

As these factors reinforce one another, they - fiercely resist change - unless they can be addressed in a comprehensive and joined-up way.

humans are form givers

combine that with time binding capacity

affordances.work.effective.pleasing

need radical reform of - the existing economic and - political system

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