MOB rules: Antibiotic Exposure Reprograms Metabolism to Mobilize Bacillus subtilis in Competitive Interactions

  1. Biochemistry and Biophysics Department, Texas A&M University, AgriLife Research, College Station, Texas, USA
  2. Interdisciplinary Program in Genetics and Genomics,Texas A&M University, College Station, Texas, USA
  3. Department of Visualization, Institute for Applied Creativity, Texas A&M University, College Station, Texas, USA
  4. Maple Flavored Solutions, LLC, Indianapolis, Indiana, USA

Peer review process

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, and public reviews.

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Editors

  • Reviewing Editor
    Michael Laub
    Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, United States of America
  • Senior Editor
    Bavesh Kana
    University of the Witwatersrand, Johannesburg, South Africa

Reviewer #1 (Public Review):

Summary:

In this study, Liu et al. investigate the signaling pathway that triggers sliding motility in the bacterium B. subtilis in response to subinhibitory concentrations of the antibiotic chloramphenicol. The authors used a genetic approach to identify the master regulator CodY playing a regulatory role in this behavior. They used transcriptional and metabolomic profiling to delineate the spatiotemporal separation of the regulatory networks that define distinct metabolic states related to purine metabolism and pyruvate utilization, which are ultimately responsible for the induction of sliding in response to chloramphenicol. Many readers would be interested to read this work showing how extracellular signals modulate microbial physiology and metabolism.

Strengths:

This work presents numerous technical and conceptual strengths. In the opinion of this referee, the most significant conceptual strength of this work is to (once again) provide evidence that antibiotics are not merely produced by bacteria to eliminate competitors. Bacteria have evolved to respond to their presence and activate a range of physiological responses, which are poorly understood. Understanding these responses is critical to fully understand the evolutionary consequences associated with the use of antibiotics. From a technical standpoint, perhaps the most relevant aspect is the robust phenotypic assay developed by the authors to study sliding motility in the presence of chloramphenicol. This robustness enables genetic work using mutants and performing omics assays to characterize the response to chloramphenicol in detail. Additionally, two sets of results stood out and provided important value to this work. One is the comparison established between the sliding induced by chloramphenicol and the sliding generated in the ΔcodY mutant, to determine the genes and the metabolites (using transcriptomics and metabolomics) specifically associated with the response to chloramphenicol without being part of the general Cody-mediated induction of sliding. The second set of results led the authors to identify precise genes of bacterial metabolism (pdhA) responsible for the sliding phenotype in response to chloramphenicol, and conducted genetic experiments to demonstrate that the pdhA mutant does not respond to the presence of chloramphenicol.

Weaknesses:

This work has three main weaknesses, all related to transcriptomic and metabolomic analyses. Firstly, there is the challenge of understanding the essence of the omics results. This section presents an overwhelming array of genes involved in different metabolic pathways, without an obvious thread to tie these hits together. It is easy to get lost in this section. For instance, one cannot be certain if the hits from one particular metabolic pathway are significant enough to figure out to which degree is this pathway responsible for the sliding phenotype. This section contains a huge diversity of genes and pathways and needs to be streamlined. Related to this, the message of the omics experiments highlights a very close relationship between purine and pyruvate metabolism in sliding motility. However, it is unclear how these metabolic pathways may influence sliding or any other specific bacterial behavior. I do not mean to say that it is not possible, just that the connection/mechanism is missing. The third weakness concerns the omics results that sometimes are in conflict. The authors proposed that this may stem from a division of labor and the coexistence of different subpopulations with different metabolisms within the microbial community. While plausible, other possibilities are equally plausible and should be tested in a revised version of the work.

Reviewer #2 (Public Review):

Summary:

Liu and colleagues describe the transcriptional changes observed during chloramphenicol-induced surface mobility of Bacillus subtilis. Practically, they describe that numerous transcriptional regulatory pathways are influenced by the subinhibitory concentration of a translational inhibitor and some of these regulatory changes might contribute to the induction of sliding. Nevertheless, how such translational stress is translated to induction of sliding remains undetermined. The authors clearly describe their aim (line 457): "Our goal for this study was to gain insight into how B. subtilis mobilizes a colony in response to subinhibitory exposure to translation inhibitors.", this is unfortunately not solved here, only the authors characterize the transcriptional landscape differences.

Strengths:

The very thorough analysis of transcriptional changes in the wild type and codY mutant strains is appreciated, and there are definitely a plethora of changes observed related to several global transcriptional regulators in B. subtilis. I compliment the authors for this very detailed and thorough description of transcriptional changes.

Weaknesses:

While the transcriptional changes are well and carefully described, the discussion practically interprets the correlations as causations. I am not disputing that the authors are not on the correct path with their assumptions, but their conclusions are not supported by direct experimental data, especially on (1) translational stress directly inducing mobility and (2) division of labor.

Major 1:

The authors conclude that their results point towards a putative mechanism, e.g. line 460 "which suggests translation stress is a trigger for colony mobilization"; however, no experiment demonstrates this aspect. The authors do not test ppGpp-related stress (mutants in ppGpp-related genes, or mutating the functional domain of CodY), nor do they directly connect ppGpp levels dynamics with induction of subsequent pathways. Again, I understand that the authors are on the right path to connect these pathways and identify what is causing mobility induction, but no direct data is represented, solely the transcriptional changes, therefore remains slightly descriptive.

The statement in the chapter title (line 474) is not demonstrated directly and should be revised. Similarly, in line 476, the authors claim that their "data supports a model", but "support" would require direct experimental data on this aspect.

The authors even clearly indicate in lines 504-506 that they do not reveal the direct mechanism, but the rest of the discussion delivers statements that do not consider the lack of direct data.

Major 2:

Line 427: "The results are consistent with a division of metabolic labor among cells in the expanding population" - the data shows heterogeneity, but the direct division of labor is not demonstrated.

Line 442: So in this case, the proposed division of labor is disrupted in the codY mutant (no inner localisation), and hence expansion appears, suggesting a lack of a putative division of labor is not necessary for induced mobility. On the contrary, there could be heterogeneous gene expression, division of labor requires demonstration of fitness benefit from such interaction.

Division of labor assumes that a mixture of mutants would complement full sliding dynamics, and this could be easily demonstrated by fluorescent labeled cells that should be organized in a similar fashion to those observed with luciferase reporters (pucA mutant on the outer ring, while pdhA mutant interior colony part). Without such experimental demonstration, the authors can only conclude spatially heterogeneous gene expresstion without clear functional contribution to subinhibitory chrolamphenociol-induced surface mobility.

Again, the authors' statement in line 472 "reveal a regulated, spatiotemporal division of metabolism" is not demonstrated by experiment, but spatial heterogeneity is revealed here.
The statement in the Discussion chapter (line 499) is also not demonstrated by experimental data: "Metabolic coordination enables surface expansion of mobilitzed B. subtilis"

Line 550: while I agree with the authors' statement that these functions work cooperatively as demonstrated by van Gestel and colleagues (2015 PloS Biol), the exploitation of these shared goods is not quantitatively equivalent, see Jautzus et al 2022 ISME J (DOI: 10.1038/s41396-022-01279-8).

In summary: the two major conclusions of the manuscript are unfortunately not demonstrated, the presented transcriptional data delivers suggestions, supported with specific mutants displaying certain phenotypes (lack of mobility induction or constitutive mobility without inducer), but it remains unclear how translational stress induces mobility and whether the transcriptional heterogeneity detected directly contributes to metabolic division of labor.

The authors should present direct evidence on the major concerns: how translational stress induces surface mobility (using ppGpp synthesis and turnover mutants and specific CdoY mutant lacking ppGpp sensing) and whether the metabolic division of labor contributes to induced surface mobility (mixing mutants and following their distribution).

  1. Howard Hughes Medical Institute
  2. Wellcome Trust
  3. Max-Planck-Gesellschaft
  4. Knut and Alice Wallenberg Foundation