Thank you very much for your work! Antibiotic resistance is a very real threat our society is facing today. We need more efforts to identify novel antibiotic treatments, such as the one you have described here. I studied a T6SS endolysin/effector (Tae1 encoded by Pseudomonas aeruginosa PAO1) in my postdoc so I really enjoy learning about other enzymes in this class. I was wondering if I could ask something about your bioinformatic analysis. You did a great job organizing the Streptomyces phage proteins into different classes based on sequence and catalytic/binding/SAR domains. And I understand that you used Alphafold2 Colab to predict some of the protein structures! This is really exciting! Have you considered using any tools that may let you compare endolysins based on their structures? This type of comparison could allow a more granular understanding of the different classes of endolysins, going beyond a classification based on domains. I would be curious to see how the 250 proteins in your analysis cluster based on their predicted structures! We (Arcadia Science) have recently developed an open-source software, called ProteinCartography, that could let you cluster a set of predicted protein structures based on their structural homology. If this is something that might be of interest to you, check out the link to the GitHub repository with ProteinCartography (https://github.com/Arcadia-Science/ProteinCartography). Please let us know if you have any questions/comments about the software! Thank you again for all of your hard work on this paper!

Thank for all of your work on this paper! We have learned so much about the bacterial cell wall yet there is so much that remains unknown. I particularly enjoyed your use of Pseudomonas fluorescens in your studies, which is still well-studied but definitely not as much as E. coli or B. subtilis. Even for “closely” related species, there is so much easily-accessible novelty that we could discover. I’m glad scientists are taking advantage of this treasure trove. I was curious about something you mentioned in your discussion: “The prevalence of pbp1A mutations in the work reported here likely reflects the fact that loss-of-function mutations in pbp1A are more readily achieved compared to gain-of-function mutations in ftsZ.” Generally, there are more mutations for any gene that are likely to lead to a loss-of-function phenotype relative to the number of mutations that could lead to a gain-of-function phenotype. Do you know if there is anything intrinsically different about the gene locus of pbp1a? Is there anything that suggests it may be a hotspot for mutations? Is there any knowledge on the wild-type strain regarding the rate of mutation across the genome under normal growth conditions? Thank you so much for your hard work and your time!

Thank you for this super cool paper! I was wondering if I could ask some questions about your enzyme activity assays conducted with MltE and MltG. Is there any deeper biochemical knowledge, from structural biology or based on known chemistry mechanisms, that could explain why one enzyme has higher activity at acidic pH but the other has higher activity at neutral pH? Additionally, did you test the activity of MltC under acidic conditions? I understand that its in vivo expression levels increase at acidic pH but I’m curious if its activity is also different. Lastly, I couldn’t find you supplementary materials on biorxiv. Thank you for all of your hard work!

Thank you so much for your study on the important bacterial pathogen Staphylococcus aureus. I get very excited about D-amino acids so thank you also for contributing to the field of chiral chemistry and to our understanding of the enzymes that mediate these types of reactions. I was wondering if I could ask you a few questions about the findings in your paper. First, I was wondering if you have more information on the function of the Alr2 enzyme? Is there any information about its expression levels? Or information about its activity towards different amino acids? I wonder if this enzyme may be a broad racemase with activity towards amino acids such as D-Arg and D-Lys? In my PhD studies, I characterized just such a broad racemase enzyme found in Pseudomonas putida, and that enzyme was also annotated as an Alanine racemase! Second, do you know if the cell wall of the wild-type S. aureus becomes weaker upon acetate intoxication? I see that you describe there is less cross-linking but I’m wondering if you have considered challenging the wild-type strain with an osmotic shock, after exposing to acetate? Third, do you think an acetate treatment could be combined with an antibiotic to act as an adjuvant? I was wondering if a treatment with acetate may allow us to use some antibiotics that S. aureus is typically resistant against. Thank you once more for your hard work and your excellent paper!

This is a very cool paper! Thank you so much for developing this sensor and for studying the important topic of antibiotic resistance. I did not know about this disulfide bond sensor prior to reading your paper and what an amazing tool this is! I'm so glad that we have this technology at our disposal and there are people working on this. I was wondering if I could ask a question about this statement: "E. coli dsb mutants are viable aerobically but not anaerobically. Overall, disulfide bond formation is required for virulence but not for in vitro growth of gram-negative bacteria,". I think I understand the reason that disulfide bonds would be critical for virulence. But I don't think I understand why aren't disulfide bonds also critical for normal in vitro growth? While developing this sensor, have people looked at cytoplasmic proteins using mass spectrometry to confirm that they actually lack disulfide bonds? And if cytoplasmic proteins do indeed lack disulfide bonds, then may be one possibility cytoplasmic proteins can function without disulfide bonds is that they don't need to be as stable as periplasmic or secreted proteins? Thanks again for your hard work on this crucial topic! And thank you for your time!

Thank you for this thorough and cool story! I love bacterial effectors so this really resonated with me. And I commend you on working in a challenging system and developing new empirical techniques! This is a significant advance in our understanding of Rickettsia biology! Thank you! My hope is that many people will follow suit and apply techniques such as BONCAT to their particular areas of biology. That would be amazing!

I was wondering if I could some questions about SrfA. I find this protein really interesting because its annotation suggests that it acts on bacterial peptidoglycan or peptidoglycan precursors. However it appears to be secreted into the eukaryotic host cell cytoplasm and nucleus. Why do you think it's secreted there if it's acting on a bacteria-specific substrate? I have three ideas so just wanted to list them here (1) it's lysing Rickettsia cells, or a subpopulation of Rickettsia cells, (2) it's lysing other non-Rickettsia intracellular bacteria, (3) it's involved in the degradation of released peptidoglycan. Regarding idea (3), is it known if Rickettsia shed (or release) peptidoglycan components as they grow and divide? It may be helpful to have a secreted enzyme that degrades these peptidoglycan components. The peptidoglycan components could act as activators for eukaryotic antibacterial programs which would be undesired from the perspective of a Rickettsia cell. Thanks!

Thank you for your thorough work on the important bacterial pathogen Acinetobacter baumannii! It's absolutely essential to identify new targets, using modern approaches, that could aid us with better drug design. Regarding the essential protein you have identified (Aeg1), I was wondering if it may be a target for any Type VI Secretion effectors, or other types of injected effectors? Are you familiar with any known effectors that target proteins similar to Aeg1, or proteins performing a similar role in the divisome, either in Acinetobacter baumannii or in other bacteria? My thought is that any effectors targeting Aeg1 could help us understand a potentially viable way to inhibit this protein, or its function, with a drug. I know Acinetobacter baumannii does secrete/inject multiple different effectors and it may not be too surprising if one of these effectors targets Aeg1, considering the essential role of this protein in cell division. Thank you so much for this important work!

Overall super cool work! A super fascinating system with so much amazing biology! I truly loved the variety of techniques you have used to make your points. I’m a huge fan of clever and unique assays so i really enjoyed everything, from the native gels and turbity readings to the FRAP assays. Thank you for uncovering this novel biology for the rest of us to learn from! I have a few questions/comments. Please check them out below.

Regarding this statement "Although both carboxysome lineages contain scaffolding proteins, these proteins are related in function alone; they have no sequence or structural similarity.", what do you mean by “no sequence or structural similarity”? do you mean low? may be 50%? or lower?

Regarding CsoS2A and CsoS2B in H. neapolitanus, would these be considered isoforms? Are proteins with isoforms common in this species (or among species in this particular proteobacteria clade)?

Regarding this statement "(1) (V/I)(T/S)G triplets spaced ~8-11 amino acids apart (hereafter VTG repeats), (2) cysteine pairs, (3) a highly conserved lysine, and (4) a highly conserved tyrosine", are these motifs conserved across alpha and beta carboxysome lineages?

Regarding this statement "CsoS2, like most IDPs, stymies AI structure prediction programs - AlphaFold yields a disordered coil and low confidence scores", what about the AlphaFold prediction for the complex between the shell protein and CsoS2?

Really cool paper! Thank you so much for contributing to our scientific knowledge on snake venoms. It's such an important and interesting problem. Based on your preprint, I understand that venom proteins remain poorly annotated, which presents a significant challenge if one is trying to understand the properties of snake venom. I was wondering if you have thought about using a protein structure-based approach to try to assign annotations to some of the uncharacterized proteins found in snake venom? Protein structures tend to be more broadly conserved so they may point you at least in the right direction regarding function assignment. There are several approaches out there for using protein structures to infer function but I wanted to make a plug for a pipeline that we have been developed at Arcadia Science called Protein Cartography. We have a detailed repository on GitHub (https://github.com/Arcadia-Science/ProteinCartography) if you would like to check it out. Also feel free to send us a message if you have any questions on running the pipeline or thinking about the data outputs. Thank you again for the awesome work!

Thank you for your hard work on this publication! Your work has contributed to our understanding of propeptides on enzyme activity in general, and specifically on the activity of the important class of transglutaminase enzymes. Your strategy, keeping the propeptide sequence to help with protein folding and solubility while modifying propeptide residues to improve catalytic activity, could be applied across many similar cases. I hope the broader scientific field adopts and further tests this approach. I was wondering if I could ask a few questions about your expression/induction strategy. Have you considered using a different E. coli strain such as the Origami 2 (DE3) or Rosetta-gami 2 (DE3)? Were all of your different variants induced overnight at 17-18C? In some of the cases, that information is missing in your text. I also noticed the expression of some of your variants was induced by growing them in an Auto Induction Medium (without adding IPTG). What was your rationale to go that route? Thank you once more for your contribution to our understanding of propeptides and their impact on enzymatic activity!

Thank you for this amazing publication! I loved your paper! It's so cool how deeply you went to understand the function of a linker sequence using a variety of biophysical and computational techniques. Big kudos! I personally find it fascinating how a short amino acid sequence, that's technically not part of the core enzyme, could have such a profound impact on the main function of said protein! Specifically in your case, it seems the linker impacts catalytic activity as well as thermal stability of the enzyme. Also it seems that the linker may be impacting substrate binding. You speculate on this in the discussion but I was wondering if I could probe a little further. First, how much is known about the interaction of this enzyme with a complex substrate such as cellulose? For example, is this LPMO, or this class in general, a processive enzyme? Does the enzyme always remain bound to the substrate throughout catalysis? Or does it detach, and then re-attach? Second, is it known how LPMOs locate the scissile bond within the complex cellulose substrate? For example, do they attach at a random place on the substrate and then begin searching for the scissile bond (search in 2-D space)? Or do they search for the bond by attaching and detaching numerous times across the substrate (search in 3-D space)? Thank you so much for the cool paper! And thank you for your time!

Thank you so much for this cool paper! I commend you on being so thorough in the your sacculi and peptidoglycan isolation and characterization. The field of bacterial cell wall biochemistry will greatly benefit from your findings! There is one question that I wanted to ask you. I was wondering if there is a way to estimate what proportion of the total sacculi in a fecal sample you are capturing? Would it be possible to repeat your sacculi isolation procedure on one fecal sample? Or could you use a sacculi label on a fecal sample that has already been treated for sacculi isolation, then try to visualize any remaining sacculi using microscopy or some light detection technique? Thank you very much for your time!

Thank you for this awesome paper! I really enjoy learning about peculiar proteins such as the one that you have described here. I have a few thoughts/comments that I wanted to share. First, would it be possible to test if there are any immune response differences induced by the presence of the Rv1987 protein? I think the answer here may give you some clues about what Rv1987 may be specifically binding. Second, what do you think about using Rv1987 as a bait in a pull-down assay? Perhaps mix it with a macrophage extract or something similar, then apply mass-spectrometry to elucidate potential binding partners? Third, have you thought about the origin of this protein? Perhaps by using a phylogenetic analysis? I'm wondering how it appeared in its current form in M. tuberculosis? Was it a fully functional chitinase/cellulase that was adapted over time (lost its catalytic capacity)? Or was it obtained through a different route already as a carbohydrate binding-protein only? Thank you once more for the cool paper! And thank you for your time!

Thank you so much for your thorough paper on endolysins! I enjoyed reading your work. I think your approach to identify endolysins using single-amplified genomes is very promising! I was wondering if you have considered testing the lytic activity of the identified EADs without fusing them to any CBD? There are likely many EADs that would exhibit potent cell lysis even without a CBD. Although the CBD may help with substrate specificity of the endolysin, EADs themselves also have a cell wall recognition capacity. That would be also interesting to test - is there a big change in the substrate specificity when an EAD alone is compared to an EAD-CBD fusion? Thank you so much for your time!

Thank you for a very well done paper! I did my postdoc on Tae1, a P. aeruginosa T6S toxin with a peptidoglycan endopeptidase activity. I really enjoy thinking about the balance between peptidoglycan synthesis and degradation! There were many really cool ideas in your paper! I found this statement really intriguing: "locally reduced EP activity might create expansive stretches of PG with pentapeptide-rich second layers". Have you thought about how the EP activity could be reduced locally? Do you think it's possible that some of the endogenous EP enzymes recognize a specific PG topology or architecture, like the areas that have two-layers or perhaps densely cross-linked areas? It's super interesting to think how PG enzymes recognize different topological features of the cell wall and your paper really spurred my imagination. Thank you so much!

Thank you for a very well done paper! I did my postdoc on Tae1, a P. aeruginosa T6S toxin with a peptidoglycan endopeptidase activity. I really enjoy thinking about the balance between peptidoglycan synthesis and degradation! There were many really cool ideas in your paper! I found this statement really intriguing: "locally reduced EP activity might create expansive stretches of PG with pentapeptide-rich second layers". Have you thought about how the EP activity could be reduced locally? Do you think it's possible that some of the endogenous EP enzymes recognize a specific PG topology or architecture, like the areas that have two-layers or perhaps densely cross-linked areas? It's super interesting to think how PG enzymes recognize different topological features of the cell wall and your paper really spurred my imagination. Thank you so much!

Thank you for a really cool paper! I commend you on publishing a negative result! It's awesome to see people doing that and I hope more people are encouraged to do the same in the future. I was interested in your finding that the reduced and oxidized 2C-DBD structure appear the same in the circular dichroism experiment. Do you think this result would change if you compare the CD spectra of reduced and oxidized full-length Gd-NifA? Have you also tried modeling reduced and oxidized Gd-NifA with AlphaFold? I'm curious if AlphaFold would predict any structural differences! At the end of your paper, you mention that you are working on experiments with the full length Gc-NifA; I'm excited to see your results! Thank you!

Thank you for your hard work and for making it available to anyone by publishing a pre-print paper! I was wondering if your empirical diffraction datasets could be used to inform better structure prediction? My understanding of structure prediction algorithms is that they capture the global structure but cannot model well the impact of individual residue changes. Have you tried any structure modeling software to see if their predictions would match what you have found empirically? Thank you for your time!

Thank you for this cool paper! You have presented solid evidence to characterize an interesting enzyme! I was really intrigued by your crystal structure and the highly restricted active site of the N-carbamoyl-beta-alanine amidohydrolase. It seems that this active site topology has made the enzyme very specific towards a small group of substrates. What do you think the impact has been on the enzyme kinetics? Do you anticipate this enzyme has maintained a high specificity as well as a high turnover number? Thank you for your time!

Thank you for this cool paper! You have presented solid evidence to characterize an interesting enzyme! I was really intrigued by your crystal structure and the highly restricted active site of the N-carbamoyl-beta-alanine amidohydrolase. It seems that this active site topology has made the enzyme very specific towards a small group of substrates. What do you think the impact has been on the enzyme kinetics? Do you anticipate this enzyme has maintained a high specificity as well as a high turnover number? Thank you for your time!

Thank you for your hard work and for making it available to anyone by publishing a pre-print paper! I was wondering if your empirical diffraction datasets could be used to inform better structure prediction? My understanding of structure prediction algorithms is that they capture the global structure but cannot model well the impact of individual residue changes. Have you tried any structure modeling software to see if their predictions would match what you have found empirically? Thank you for your time!

Thank you so much for this great work! I really enjoyed your paper. I can tell how much work and effort you have put into it. Kudos for producing really high quality science! I was fascinated by the FacZ protein and the modeling and biochemistry you have done. First it's really cool that you were able to show the predicted binding between the FacZ motif and a part of GpsB. It's a fantastic example of combining our modern tools, such as AlphaFold, and also empirically demonstrating the validity of the predictions. I do have a couple of questions about FacZ. It's not a very big protein at 18 kDa but it seems that it may have lots of functions. 1) Do you have any hypotheses about the role of the FacZ exoplasm extension? What could it be doing there? 2) The portion of the FacZ that interacts with GpsB is very small (6 residues). What do you think the rest of the cytoplasmic portion does? Do you think there are other binding partners? Or may be it's necessary for membrane interactions? (it would be super cool to identify a membrane association motif!!!) Or perhaps most of the cytoplasmic portion is involved in the oligomerization of FacZ? Really excited about FacZ! Thank you for your time!

Thank you so much for your paper! Metabolism of amino acids is extremely important to study but also very complex. It's also a really vast field so I really appreciate it when scientists decide to take a deep dive and uncover the existing metabolic pathways. Kudos for that! As excited as I am about L-amino acids, I'm even more excited to understand the metabolism of D-amino acids. I was wondering if you have considered applying your experimental approach to understand the metabolic pathway for D-arginine? May be also other D-amino acids? I think we know little about the metabolism of D-amino acids in B. subtilis and about the regulation of the metabolic enzymes. Thank you for your time!

General comments:

1-Overall a really important paper! Thank you! We need to protect our current antibiotic arsenal as well as develop new antibiotics - this paper provides insight into how to do both!

2-Specifically, beta-lactams are such an important class of antibiotics and we should strive to do our best to preserve their potency and also find new determinants that could help us re-sensitize already resistant bacteria.

3-The authors have done a lot of work in this paper! Really great job! First constructing the transposon library, testing it across many different antibiotics, then validating many of the identified genes and pathways.

4-I love that the authors focused on the cell envelope! It’s an orthogonal cell structure to human cells, it’s easily accessible, and I really think there is still so much we don’t know about how antibiotics target the cell envelope and lead to lysis or stasis!

5-I also love the barcoded transposon approach! It provides a wealth of information and it can be applied across different species but the utility got so much higher once the barcodes were introduced! Kudos for doing that!

6-Overall, I think this paper also shines light on the large differences in cell wall physiology even in the more closely-related Gram-negative bacteria. I hope people branch out more and venture frequently outside of the E. coli world.

Specific comments:

1-Is there biochemical evidence indicating that beta-lactam antibiotics have the same targets in B. cenocepacia as they do in other bacteria (E. coli)?

1-Do you think it’s worth conducting your screen in other conditions besides LB media? I am wondering how much of the findings in LB media translate to antibiotic resistance in the real world?

2-Is there any way to adjust your barcoded transposon approach so that it can be used to probe the role of essential genes in antibiotic resistance? Or do you think you would need a completely different strategy for that? Perhaps a high-throughput CRISPRi approach that would produce only a knockdown in gene expression?

3-Your finding that cycloserine could have an effect on D-glutamate synthesizing enzymes is really exciting! I encourage you or somebody to follow up on that! It would be cool if this leads to developing cycloserine analogs that inhibit D-glutamate production.

4-Similarly to point 3, I was really intrigued by the differences in UndP metabolism in B. cenocepacia compared to E. coli. More specifically, is it known how many UndPP phosphatases there are in B. cenocepacia? I also love your discussion on this point! It’s so cool when people venture outside of the established model organisms and find that conserved physiological processes actually show tremendous variability!

Questions:

1-Is it known if the outer membrane in Burkholderia is responsible for handling any of the turgor pressure? Typically the assumption is that peptidoglycan is the major structure that bears the pressure but we know now that membranes play a role as well (at least in some bacteria). I am wondering if people have studied that in Burkholderia because their outer membrane has distinct properties from other Gram-negatives.

2-Out in nature, do you know if Burkholderia is antagonized by any contact-dependent mechanisms? I’m thinking any bacteria with a Type VI secretion system like Pseudomonas aeruginosa for example. I think it could be cool to use your barcoded transposon approach to look for susceptibility determinants towards Type VI secreted toxins that target the cell wall!

3-I wonder if there is a way to summarize your findings in a database or a resources website? Is there a Burkholderia database that harbors antibiotic resistance information? I think having a publication is great but the utility of your work would skyrocket if the general public, policy makers, and medical doctors could access your findings more quickly and directly.

4-Do you think some of the phenotypes you have measured could be due to polar effects caused by an overall operon disruption? It could be worth following up with some of your knockout strains for genes in operons and measuring the expression of neighboring genes in that same operon.

General comments:

This is an interesting manuscript describing the effect of mechanical stress on the relationship between bacteria and phages. The findings in this paper are valuable and improve our broad understanding of mechanobiology. Specifically, I want to compliment the authors on developing a unique experimental setup which would allow scientists to monitor continuously the effect of mechanical stress on bacteria over tens of hours. I also agree with the authors that there could be potential translational value of their findings that may allow us as a society to address antimicrobial resistance more effectively. I believe the paper is well-written and the conclusions are substantiated by the experiments presented here.

Specific comments:

1. You make the following statement on page 8 of the paper PDF “The frequency at which this occurs depends on the flow rate used to load the cells into the chamber, allowing us to deliberately wedge cells into very narrow areas of the chamber.” I was wondering if it would be possible to include the data you used to determine this?

2. Would it be possible to include statistical significance for panels C and D in Figure 2? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness. This could be a supplementary figure.

3. In Figure 3 panel C, you refer to “persisters” and “non-persisters”. I was wondering if you are referring to the strain that is a “capsule k.o.” and the strain that is “capsule o.e.”? Could you please clarify this?

4. Would it be possible to include statistical significance for panel E in Figure 3? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness.

5. Would it be possible to include statistical significance for panel C in Figure 4? And how about for panels D and E in the same figure (perhaps just for the last time points)? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness.

Questions:

1. Would it be possible to prepare the compression setup with different materials or resins? It could provide broader utility if scientists could 3D-print their own compression devices of different sizes and different materials.

2. Additionally, the compression setups made from different materials may be able to help you understand better the damage inflicted on the bacterial membrane. This could let you get at the question of what mechanoreceptors might be involved here? I understand this is beyond the scope of this paper but, as you have indicated in your discussion, it is relevant to mechanosensing more broadly.

3. Regarding your compression setup, would it possible to determine if the bacteria are in a biofilm? This may help you determine what percentage of the persistence is due to biofilm versus the mechanical compression. I completely realize this is beyond the scope of this study but may be in a future study you could include a strain that cannot form biofilms and test it using the same compression setup.

4. I was wondering if the compression setup you developed could be applied to other bacteria, specifically non-rod-shaped bacteria like Borrelia burgdorferi? And how about to other cell types altogether? I wonder if this type of mechanosensing could trigger protective responses in other unicellular organisms, may be protists or algae!

5. Do you think there may be other persistence mechanisms triggered by mechanosensing? Specifically, do you think the cell wall may be undergoing some restructuring as well as the capsule? It would be interesting if the cell wall does but equally interesting if it does not!

General comments:

This study carefully delineates the role of magnesium in cell division versus cell elongation. The results are really important specifically for rod-shaped bacteria and also an important contribution to the broader field of understanding cell shape. Specifically, I love that they are distinguishing between labile and non-labile intracellular magnesium pools, as well as extracellular magnesium! These three pools are really challenging to separate but I commend them on engaging with this topic and using it to provide alternative explanations for their observations!

A major contribution to prior findings on the effects of magnesium is the author’s ability to visualize the number of septa in the elongating cells in the absence of magnesium. This is novel information and I think the field will benefit from the microscopy data shown here.

I completely agree with the authors that we need to be more careful when using rich media such as LB. It is particularly sad that we may be missing really interesting biology because of that! It’s worth moving away from such media or at least being more careful about batch to batch variability. Batch to batch variability is not as well appreciated in microbiology as it is for growing other cell types (for example, mammalian cells and insect cells).

For me, the most exciting finding was that a large part of the cell length changes within the first 10min after adding magnesium. The authors do speculate in the discussion that this is likely happening because of biophysical or enzymatic effects, and I hope they explore this further in the future!

I love how the paper reads like a novel! Congratulations on a very well-written paper!

Kudos to the authors for providing many alternative explanations for their results. It demonstrates critical thinking and an open-mind to finding the truth.

Specific comments:

Figure 2C → please include indication of statistical significance

Figure 3C → please include indication of statistical significance

Figure 6A → please include indication of statistical significance

Figure 8B → please include indication of statistical significance

Figure S1B → please include indication of statistical significance

Figure S3B → please include indication of statistical significance

For your overexpression experiments, do the overexpressed proteins have a tag? It would be helpful to have Western blot data showing that the particular proteins are actually being overexpressed. I think the phenotypes that you observe are very compelling so I don’t doubt the conclusions. Western blot data would just provide some additional confirmation that you are actually achieving overexpression of UppS, MraY, and BcrC.

Questions:

Based on your data, there are definitely differences in gene expression when you compare cells grown in media with and without magnesium. Because the majority in cell length increase occurs in such a short time though (the first 10min), I was wondering if you think that some or most of it is not due to gene expression? Do you have any hypotheses what is most likely to be affected by magnesium? Do you think if the membrane may be affected?

Why do you think less magnesium activates this program of less division and more elongation? Additionally why is abundant magnesium activating a program of increased cell division and less elongation? Do you think there is some evolutionary advantage, especially considering how important magnesium is for ATP production?

Related to this previous question, I also wonder if this magnesium-dependent phenotype would extend to other unicellular organisms, may be protists or algae? That would be a really exciting direction to explore!

Regarding the zinc and manganese experiments, why do you think they lead to additional phenotypes compared to magnesium? Do you have any hypotheses?

Regarding your results that Lipid I availability may be a major a problem for the cell division in the absence of magnesium, do you think that is due to effects magnesium has on the enzymes directly, or do you think magnesium affects the substrate availability/conformation by coordinating the phosphate groups? Or something else, may be membrane conformation?

General comments: 1-This is a really important work because in this day and age, transforming DNA into an organism or a cell is an essential tool for any molecular biologist

2-And we still don’t understand how to transform the vast majority of organisms on Earth!

3-I applaud this effort for developing robust and accessible transformation tools for the amoeba Acanthamoeba castellanii. I believe this is an important organism to study but equally important are the general trends/approaches about what works to transform an organism

4-accumulating more and more of this knowledge on transformation across different organisms is essential if we want to access the biology of many more organisms

5-Also kudos for the detailed and meticulous transfection optimization! I really enjoyed your use of the N/P ratio and the combinatorial approach over a range of DNA and PEI concentrations. This is solid science!

Specific comments: 1-Figure 2 → Is it possible to include cell counts, in addition to the RFU signal? This is not a major comment. It’s just that there are cell counts in your other figures so it might be good to include for this figure as well. No need to repeat this experiment if you don’t have cell counts though!

2-Figure 4 → Would it be possible to include arrows or something to indicate which parts of the figure you would like the reader to focus on? It’s great having all of the data included but it may help your narrative if you point in the figure itself to certain key differences or features of the data. Or you might consider including a table to summarize all the data from the figure? May be the table could contain standard deviation around the average for each treatment (or something to show the distribution of the signal but with a single number)?

3-Figure 6 → Would it be possible to include indication of statistical significance?

Questions: 1-How long are plasmids maintained in the transformed cells?

2-Is there a robust selection that could enable you to produce stably transformed lines?

3-And related to Q2, is it possible to produce stable mutant lines (gene deletions or gene introductions), perhaps by transiently transforming CRISPR genes?

4-Does Acanthamoeba castellanii easily undergo transfection in nature? Is there any evidence for that based on its genome?

5-Related to Q4, are there known viruses that infect Acanthamoeba castellanii? Knowledge about these viruses may inform alternative methods of gene delivery and also serve as evidence for the transfection rate in nature.

6-I was wondering if you have tried transfecting Acanthamoeba castellanii with one big plasmid containing two fluorescent genes? Does that work? If yes, is the gene expression worse or better compared to having the genes on two plasmids and transfecting the plasmids together?

Thank you for this great work! I enjoyed reading your article and I'm happy there are people working on developing and improving protein expression systems. If I understand correctly from your methods, the culture volumes you used for protein expression are large (250ml, 2L or 5L). Have you tried your expression optimization approach in a 96-well plate or a 96-deep-well block? I understand this would affect the final protein titers but it may be great for quick screening of conditions. Thank you for your time!

Thank you for this great work! I enjoyed reading your article and I'm happy there are people working on developing and improving protein expression systems. If I understand correctly from your methods, the culture volumes you used for protein expression are large (250ml, 2L or 5L). Have you tried your expression optimization approach in a 96-well plate or a 96-deep-well block? I understand this would affect the final protein titers but it may be great for quick screening of conditions. Thank you for your time!

Thank you for this great work! Your article will be very helpful for anyone interested in the ecological significance of amino acid metabolism by bacteria. You have done an outstanding job compiling information on biochemical pathways involved in the metabolism of the 20 canonical amino acids, as well as metabolic pathways for many other compounds (bile acids, carboxylic acids, etc.). Using your methodology, I was wondering if it would be possible to explore the prevalence of D-amino acid metabolism in human gut bacteria? I suspect there is a dearth of metabolic knowledge for most D-amino acids which may not allow running your pipeline. However it may be possible to use your experimental approach to look into the metabolism of well-studied D-amino acids such as D-alanine, D-glutamate, may be also D-serine. Thank you for your time!

Thank you for this great work! Your article will be very helpful for anyone interested in the ecological significance of amino acid metabolism by bacteria. You have done an outstanding job compiling information on biochemical pathways involved in the metabolism of the 20 canonical amino acids, as well as metabolic pathways for many other compounds (bile acids, carboxylic acids, etc.). Using your methodology, I was wondering if it would be possible to explore the prevalence of D-amino acid metabolism in human gut bacteria? I suspect there is a dearth of metabolic knowledge for most D-amino acids which may not allow running your pipeline. However it may be possible to use your experimental approach to look into the metabolism of well-studied D-amino acids such as D-alanine, D-glutamate, may be also D-serine. Thank you for your time!

Thank you for the great publication! It's really important to understand how to improve feed digestibility and you have listed several great reasons. Based on this article and your previous work, it seems that it's possible to improve the secretion levels of xylanase and cellulase enzymes. I'm an enzymologist by training so I was wondering how difficult would it be to improve the actual activity of such hydrolytic enzymes? It could be even more helpful to increase not only the enzyme amount secreted by B. subtilis but also the degradative activity of each enzyme molecule. Could these enzymes be expressed in E. coli to perform a high-throughput mutagenesis screen? Or perhaps such a screen could also be conducted in B. subtilis? Thank you so much for your time!

Thank you for the great publication! It's really important to understand how to improve feed digestibility and you have listed several great reasons. Based on this article and your previous work, it seems that it's possible to improve the secretion levels of xylanase and cellulase enzymes. I'm an enzymologist by training so I was wondering how difficult would it be to improve the actual activity of such hydrolytic enzymes? It could be even more helpful to increase not only the enzyme amount secreted by B. subtilis but also the degradative activity of each enzyme molecule. Could these enzymes be expressed in E. coli to perform a high-throughput mutagenesis screen? Or perhaps such a screen could also be conducted in B. subtilis? Thank you so much for your time!

General comments: 1-This is a really important work because in this day and age, transforming DNA into an organism or a cell is an essential tool for any molecular biologist

2-And we still don’t understand how to transform the vast majority of organisms on Earth!

3-I applaud this effort for developing robust and accessible transformation tools for the amoeba Acanthamoeba castellanii. I believe this is an important organism to study but equally important are the general trends/approaches about what works to transform an organism

4-accumulating more and more of this knowledge on transformation across different organisms is essential if we want to access the biology of many more organisms

5-Also kudos for the detailed and meticulous transfection optimization! I really enjoyed your use of the N/P ratio and the combinatorial approach over a range of DNA and PEI concentrations. This is solid science!

Specific comments: 1-Figure 2 → Is it possible to include cell counts, in addition to the RFU signal? This is not a major comment. It’s just that there are cell counts in your other figures so it might be good to include for this figure as well. No need to repeat this experiment if you don’t have cell counts though!

2-Figure 4 → Would it be possible to include arrows or something to indicate which parts of the figure you would like the reader to focus on? It’s great having all of the data included but it may help your narrative if you point in the figure itself to certain key differences or features of the data. Or you might consider including a table to summarize all the data from the figure? May be the table could contain standard deviation around the average for each treatment (or something to show the distribution of the signal but with a single number)?

3-Figure 6 → Would it be possible to include indication of statistical significance?

Questions: 1-How long are plasmids maintained in the transformed cells?

2-Is there a robust selection that could enable you to produce stably transformed lines?

3-And related to Q2, is it possible to produce stable mutant lines (gene deletions or gene introductions), perhaps by transiently transforming CRISPR genes?

4-Does Acanthamoeba castellanii easily undergo transfection in nature? Is there any evidence for that based on its genome?

5-Related to Q4, are there known viruses that infect Acanthamoeba castellanii? Knowledge about these viruses may inform alternative methods of gene delivery and also serve as evidence for the transfection rate in nature.

6-I was wondering if you have tried transfecting Acanthamoeba castellanii with one big plasmid containing two fluorescent genes? Does that work? If yes, is the gene expression worse or better compared to having the genes on two plasmids and transfecting the plasmids together?

General comments:

1-Overall a really important paper! Thank you! We need to protect our current antibiotic arsenal as well as develop new antibiotics - this paper provides insight into how to do both!

2-Specifically, beta-lactams are such an important class of antibiotics and we should strive to do our best to preserve their potency and also find new determinants that could help us re-sensitize already resistant bacteria.

3-The authors have done a lot of work in this paper! Really great job! First constructing the transposon library, testing it across many different antibiotics, then validating many of the identified genes and pathways.

4-I love that the authors focused on the cell envelope! It’s an orthogonal cell structure to human cells, it’s easily accessible, and I really think there is still so much we don’t know about how antibiotics target the cell envelope and lead to lysis or stasis!

5-I also love the barcoded transposon approach! It provides a wealth of information and it can be applied across different species but the utility got so much higher once the barcodes were introduced! Kudos for doing that!

6-Overall, I think this paper also shines light on the large differences in cell wall physiology even in the more closely-related Gram-negative bacteria. I hope people branch out more and venture frequently outside of the E. coli world.

Specific comments:

1-Is there biochemical evidence indicating that beta-lactam antibiotics have the same targets in B. cenocepacia as they do in other bacteria (E. coli)?

1-Do you think it’s worth conducting your screen in other conditions besides LB media? I am wondering how much of the findings in LB media translate to antibiotic resistance in the real world?

2-Is there any way to adjust your barcoded transposon approach so that it can be used to probe the role of essential genes in antibiotic resistance? Or do you think you would need a completely different strategy for that? Perhaps a high-throughput CRISPRi approach that would produce only a knockdown in gene expression?

3-Your finding that cycloserine could have an effect on D-glutamate synthesizing enzymes is really exciting! I encourage you or somebody to follow up on that! It would be cool if this leads to developing cycloserine analogs that inhibit D-glutamate production.

4-Similarly to point 3, I was really intrigued by the differences in UndP metabolism in B. cenocepacia compared to E. coli. More specifically, is it known how many UndPP phosphatases there are in B. cenocepacia? I also love your discussion on this point! It’s so cool when people venture outside of the established model organisms and find that conserved physiological processes actually show tremendous variability!

Questions:

1-Is it known if the outer membrane in Burkholderia is responsible for handling any of the turgor pressure? Typically the assumption is that peptidoglycan is the major structure that bears the pressure but we know now that membranes play a role as well (at least in some bacteria). I am wondering if people have studied that in Burkholderia because their outer membrane has distinct properties from other Gram-negatives.

2-Out in nature, do you know if Burkholderia is antagonized by any contact-dependent mechanisms? I’m thinking any bacteria with a Type VI secretion system like Pseudomonas aeruginosa for example. I think it could be cool to use your barcoded transposon approach to look for susceptibility determinants towards Type VI secreted toxins that target the cell wall!

3-I wonder if there is a way to summarize your findings in a database or a resources website? Is there a Burkholderia database that harbors antibiotic resistance information? I think having a publication is great but the utility of your work would skyrocket if the general public, policy makers, and medical doctors could access your findings more quickly and directly.

4-Do you think some of the phenotypes you have measured could be due to polar effects caused by an overall operon disruption? It could be worth following up with some of your knockout strains for genes in operons and measuring the expression of neighboring genes in that same operon.

General comments:

This study carefully delineates the role of magnesium in cell division versus cell elongation. The results are really important specifically for rod-shaped bacteria and also an important contribution to the broader field of understanding cell shape. Specifically, I love that they are distinguishing between labile and non-labile intracellular magnesium pools, as well as extracellular magnesium! These three pools are really challenging to separate but I commend them on engaging with this topic and using it to provide alternative explanations for their observations!

A major contribution to prior findings on the effects of magnesium is the author’s ability to visualize the number of septa in the elongating cells in the absence of magnesium. This is novel information and I think the field will benefit from the microscopy data shown here.

I completely agree with the authors that we need to be more careful when using rich media such as LB. It is particularly sad that we may be missing really interesting biology because of that! It’s worth moving away from such media or at least being more careful about batch to batch variability. Batch to batch variability is not as well appreciated in microbiology as it is for growing other cell types (for example, mammalian cells and insect cells).

For me, the most exciting finding was that a large part of the cell length changes within the first 10min after adding magnesium. The authors do speculate in the discussion that this is likely happening because of biophysical or enzymatic effects, and I hope they explore this further in the future!

I love how the paper reads like a novel! Congratulations on a very well-written paper!

Kudos to the authors for providing many alternative explanations for their results. It demonstrates critical thinking and an open-mind to finding the truth.

Specific comments:

Figure 2C → please include indication of statistical significance

Figure 3C → please include indication of statistical significance

Figure 6A → please include indication of statistical significance

Figure 8B → please include indication of statistical significance

Figure S1B → please include indication of statistical significance

Figure S3B → please include indication of statistical significance

For your overexpression experiments, do the overexpressed proteins have a tag? It would be helpful to have Western blot data showing that the particular proteins are actually being overexpressed. I think the phenotypes that you observe are very compelling so I don’t doubt the conclusions. Western blot data would just provide some additional confirmation that you are actually achieving overexpression of UppS, MraY, and BcrC.

Questions:

Based on your data, there are definitely differences in gene expression when you compare cells grown in media with and without magnesium. Because the majority in cell length increase occurs in such a short time though (the first 10min), I was wondering if you think that some or most of it is not due to gene expression? Do you have any hypotheses what is most likely to be affected by magnesium? Do you think if the membrane may be affected?

Why do you think less magnesium activates this program of less division and more elongation? Additionally why is abundant magnesium activating a program of increased cell division and less elongation? Do you think there is some evolutionary advantage, especially considering how important magnesium is for ATP production?

Related to this previous question, I also wonder if this magnesium-dependent phenotype would extend to other unicellular organisms, may be protists or algae? That would be a really exciting direction to explore!

Regarding the zinc and manganese experiments, why do you think they lead to additional phenotypes compared to magnesium? Do you have any hypotheses?

Regarding your results that Lipid I availability may be a major a problem for the cell division in the absence of magnesium, do you think that is due to effects magnesium has on the enzymes directly, or do you think magnesium affects the substrate availability/conformation by coordinating the phosphate groups? Or something else, may be membrane conformation?

General comments:

This is an interesting manuscript describing the effect of mechanical stress on the relationship between bacteria and phages. The findings in this paper are valuable and improve our broad understanding of mechanobiology. Specifically, I want to compliment the authors on developing a unique experimental setup which would allow scientists to monitor continuously the effect of mechanical stress on bacteria over tens of hours. I also agree with the authors that there could be potential translational value of their findings that may allow us as a society to address antimicrobial resistance more effectively. I believe the paper is well-written and the conclusions are substantiated by the experiments presented here.

Specific comments:

1. You make the following statement on page 8 of the paper PDF “The frequency at which this occurs depends on the flow rate used to load the cells into the chamber, allowing us to deliberately wedge cells into very narrow areas of the chamber.” I was wondering if it would be possible to include the data you used to determine this?

2. Would it be possible to include statistical significance for panels C and D in Figure 2? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness. This could be a supplementary figure.

3. In Figure 3 panel C, you refer to “persisters” and “non-persisters”. I was wondering if you are referring to the strain that is a “capsule k.o.” and the strain that is “capsule o.e.”? Could you please clarify this?

4. Would it be possible to include statistical significance for panel E in Figure 3? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness.

5. Would it be possible to include statistical significance for panel C in Figure 4? And how about for panels D and E in the same figure (perhaps just for the last time points)? The data look sufficiently tight and I don’t doubt the results but this would be nice to have for completeness.

Questions:

1. Would it be possible to prepare the compression setup with different materials or resins? It could provide broader utility if scientists could 3D-print their own compression devices of different sizes and different materials.

2. Additionally, the compression setups made from different materials may be able to help you understand better the damage inflicted on the bacterial membrane. This could let you get at the question of what mechanoreceptors might be involved here? I understand this is beyond the scope of this paper but, as you have indicated in your discussion, it is relevant to mechanosensing more broadly.

3. Regarding your compression setup, would it possible to determine if the bacteria are in a biofilm? This may help you determine what percentage of the persistence is due to biofilm versus the mechanical compression. I completely realize this is beyond the scope of this study but may be in a future study you could include a strain that cannot form biofilms and test it using the same compression setup.

4. I was wondering if the compression setup you developed could be applied to other bacteria, specifically non-rod-shaped bacteria like Borrelia burgdorferi? And how about to other cell types altogether? I wonder if this type of mechanosensing could trigger protective responses in other unicellular organisms, may be protists or algae!

5. Do you think there may be other persistence mechanisms triggered by mechanosensing? Specifically, do you think the cell wall may be undergoing some restructuring as well as the capsule? It would be interesting if the cell wall does but equally interesting if it does not!