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We, the students of MICI5029/5049, a Graduate Level Molecular Pathogenesis Journal Club at Dalhousie University in Halifax, NS, Canada, hereby submit a review of the following BioRxiv preprint:Souvik Bhattacharyya, David M. Walker, Rasika M. Harshey. Necrosignaling: Cell death triggers antibiotic survival pathways in bacterial swarms. BioRxiv 2020.02.26.966986; doi: https://doi.org/10.1101/2020.02.26.966986 We adhered to the Universal Principled (UP) Review guidelines proposed in:Universal Principled Review: A Community-Driven Method to Improve Peer Review. Krummel M, Blish C, Kuhns M, Cadwell K, Oberst A, Goldrath A, Ansel KM, Chi H, O'Connell R, Wherry EJ, Pepper M; Future Immunology Consortium. Cell. 2019 Dec 12;179(7):1441-1445. https://doi.org/10.1016/j.cell.2019.11.029 SUMMARY: In this manuscript, Bhattacharyya, et al. investigated the mechanism of how the death of a sub-population of swarming bacterial cells increased survival of the remaining cells. They called this phenomenon STRIVE (swarming with temporary resistance in various environments). Using E. coli and several other bacteria, the authors identified a candidate STRIVE factor called AcrA that was released by dead cells. They also demonstrated that the outer membrane protein TolC on the live cells is involved in the STRIVE response, possibly interacting with AcrA released from dead cells. Microscopy studies of mutant bacteria suggested that AcrA binds to TolC on the exterior of live cells and triggers STRIVE. Finally, the authors investigated the gene expression profile of the swarming cells and proposed that increased AcrA-dependent efflux and ROS catabolism, and reduced cell permeability, are potential mechanisms of STRIVE. In summary, this work reveals that AcrA is an enhancing factor of STRIVE that interacts with TolC to stimulate the reprogramming of live cells. OVERALL ASSESSMENT: STRENGTHS: · The work provides a new insight of how the dead subpopulation contributes to swarming cell resistance. The findings are novel and impactful and merit further exploration.· The authors thoroughly investigated the mechanisms of necrosignaling/STRIVE using a suite of complementary approaches. WEAKNESSES: · The reader needs more thorough Introduction and Discussion sections to put these new discoveries (necrosignaling/STRIVE) in proper context in the field. These sections are quite underdeveloped. · Modifications in a few figures and more detailed methodology will help the reader interpret the data.· Statistical analyses are not well described for most data. DETAILED U.P. ASSESSMENT ("1" represents the highest quality) OBJECTIVE CRITERIA (QUALITY): 1. Quality: Experiments (1-3 scale) SCORE = 1.5 Figure by Figure, do experiments, as performed, have the proper controls? · Fig 1: This figure is properly controlled, but the readability of this section of the Results is poor, because the reader must flip back-and-forth between the Supplemental figures and Figure 1 to properly understand the experimental approach and the results. The authors should consider including parts of Figs S1 and S3, as well as a smaller version of the cartoon in Figure S2, to help the reader understand method and important findings. The current compressed format that relegates important data to the supplement, does not serve the reader well.· Fig 2: The findings displayed in Fig. 2C would be stronger if a wild-type control was included. Are specific analyses performed using methods that are consistent with answering the specific question? Is there the appropriate technical expertise in the collection and analysis of data presented?· Yes Is there the appropriate technical expertise in the collection and analysis of data presented? · Fig S1: We think that the relative susceptibility of swarm cells at early times and low doses of antibiotic is quite subtle, and unless the reader consults the supplemental data, they might misunderstand this subtle finding. The description of this finding in the Results text should acknowledge the modest difference in susceptibility. Moreover, we wonder whether this small difference could be an artefact resulting from the collection method rather than true antibiotic susceptibility. However, this experiment was incompletely described in the methods, which makes it difficult to interpret. Appropriate statistical tests should be performed on the data in Fig. S1 to determine whether these modest differences are significant or not. Do analyses use the best possible (most unambiguous) available methods, quantified via appropriate statistical comparisons?· Fig 3c & 3d: The slopes of these curves are shown, but statistical analyses would be helpful in determining whether true significant differences are achieved. · When error bars and p values are presented, the type of error (SD or SEM) and statistical method used should be described. Are controls or experimental foundations consistent with established findings in the field? A review that raises concerns regarding inconsistency with widely reproduced observations should list at least 2 examples in the literature of such results. To address this question may occasionally require a supplemental figure that, for example, re-graphs multi-axis data from the primary figure using established axes or gating strategies to demonstrate how results in this paper line up with established understandings. It should not be necessary to defend exactly why these may be different from established truths, although doing so may increase the impact of the study. · The experiments are consistent with previous findings that swarming cells develop adaptive antibiotic resistance. 2. Quality: Completeness (1-3 scale) SCORE = 1.5Does the collection of experiments and associated analysis of data support the proposed title/abstract-level conclusions? Typically, the major (title or abstract level) conclusions are expected to be supported by at least two experimental systems.· Most of the major conclusions are supported by the experimental results. The only egregious unsupported statement is on line 38: "...our findings may also be relevant to chemotherapy-resistant cancers". The link to cancer chemotherapy resistance is not made clear in the manuscript and is not directly addressed by any of the data. It should be removed. Are there experiments or analyses that have not been performed, but if "true" would disprove the conclusion (sometimes considered a fatal flaw in the study)? In some cases, a reviewer may propose an alternative conclusion/abstract that is clearly defensible with the experiments as presented, and one solution to 'completeness' here should always be to temper an abstract or remove a conclusion and to discuss this alternative in the discussion section.· We think that further description of the RNA-seq analysis is needed to clarify whether functional categories were significantly different overall or if other non-related categories were also significantly different. It is especially important that the authors reveal how they identified the gene families shown: were all gene families of porins/ROS metabolism/efflux pumps shown, or were the families shown selected from a group?· Despite the attempt to identify critical residues for AcrA-TolC interaction, it is unclear how this extracellular interaction contributes to increased efflux and regulation of other signaling pathways, since AcrA usually acts as a periplasmic protein. As a major conclusion of this manuscript, the authors should at least discuss what they think is the most likely mechanism in the Discussion, or state that it is still unclear how this mechanism works.· It would be nice to have a piece of data like an SDS-PAGE of the purified AcrA (could be placed in the Data Supplement) to show the quality of their purification, as any other residual E. coli proteins could influence the results.· The authors should explain how they chose the antibiotics used in the study. In addition, it is unclear why Kan50 was used in Fig 1b and Kan70 in Fig 1d. 3. Quality: Reproducibility (1-3 scale) SCORE = 2 Figure by Figure, were experiments repeated per a standard of 3x repeats or 5 mice/cohort etc.?· Except for the RNA-Seq analysis, most figures and methods do not indicate how many repeats were performed, especially for those that had error bars and p values like Fig 1a, 3b, & 3d. Is there sufficient "raw data" presented to assess rigor of the analysis? · Yes. Are methods for experimentation and analysis adequately outlined to permit reproducibility?· Methods for the Kanamycin survival curves and MIC determination (Fig S1) were not described.· More details are needed on how the RNA-seq data was analyzed. We also suggest that the authors deposit the code that was used to create the simulations and do the RNA-seq analysis in public repository such as github. 4. Quality: Scholarship (1-3 scale), generally not the basis for acceptance/rejection: SCORE = 3Has the author cited and discussed the merits of the relevant data that would argue against their conclusion?· Yes. In the Discussion the authors mention how their finding is different from previous studies that reported other functions of cell lysis. Has the author cited and/or discussed the important works that are consistent with their conclusion and which a reader should be especially familiar when considering the work?· The Introduction and Discussion should be expanded to help readers appreciate previous findings in the field and to put the current work in proper context of larger themes like chemotaxis and quo

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