Noisy metabolism can promote microbial cross-feeding

  1. Jaime G Lopez
  2. Ned S Wingreen

  • Curated by eLife

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    Evaluation Summary:

    This paper will be of broad interest to microbiologists interested in gene expression noise and/or metabolic interactions in microbial communities. It provides a novel hypothesis that complements existing theoretical frameworks. The hypothesis is well supported by data from a mathematical model, and it its predictions could be tested experimentally in future work.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

Cross-feeding, the exchange of nutrients between organisms, is ubiquitous in microbial communities. Despite its importance in natural and engineered microbial systems, our understanding of how inter-species cross-feeding arises is incomplete, with existing theories limited to specific scenarios. Here, we introduce a novel theory for the emergence of such cross-feeding, which we term noise-averaging cooperation (NAC). NAC is based on the idea that, due to their small size, bacteria are prone to noisy regulation of metabolism which limits their growth rate. To compensate, related bacteria can share metabolites with each other to ‘average out’ noise and improve their collective growth. According to the Black Queen Hypothesis, this metabolite sharing among kin, a form of ‘leakage’, then allows for the evolution of metabolic interdependencies among species including de novo speciation via gene deletions. We first characterize NAC in a simple ecological model of cell metabolism, showing that metabolite leakage can in principle substantially increase growth rate in a community context. Next, we develop a generalized framework for estimating the potential benefits of NAC among real bacteria. Using single-cell protein abundance data, we predict that bacteria suffer from substantial noise-driven growth inefficiencies, and may therefore benefit from NAC. We then discuss potential evolutionary pathways for the emergence of NAC. Finally, we review existing evidence for NAC and outline potential experimental approaches to detect NAC in microbial communities.

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  1. Version published to 10.7554/elife.70694 on eLife
  2. eLife

    Author Response

    Reviewer #1 (Public Review):

    Lopez and Wingreen proposes the idea of noise-averaging cooperation (NAC), or within-population cross-feeding driven by noisy metabolism in microbes. The authors reasoned that since microbes are small, they are prone to noisy metabolism which limits growth rate. If related bacteria can share metabolites to average out noise (e.g in biofilm), then population growth rate can be improved and sometimes, the irreversible growth arrest of individuals can be prevented in theory. The authors predict substantial noise-driven growth inefficiencies from single-cell protein abundance data, review evidence for NAC, and propose how to detect NAC in microbial populations.

    Although this paper would be greatly strengthened by experimental tests (some of which may not be too difficult to do), I did enjoy reading it, and the writing is clear and thoughtful. The problem of "cheaters" (cells that take metabolites but do not leak any) will naturally arise, although the problem is mitigated in biofilms. Discussions on that will be useful.

    We agree that the issue of “cheaters” deserves additional attention in the manuscript. To this end, we have augmented our discussion of NAC’s evolutionary stability to include a discussion of the existing literature on the evolution of cooperation. We now situate NAC and the results of our biofilm model in this larger context. We note that our spatial model results show that the benefits of NAC can be “privatized” among cooperators, a key requirement for the evolution of cooperation.

  3. eLife

    Evaluation Summary:

    This paper will be of broad interest to microbiologists interested in gene expression noise and/or metabolic interactions in microbial communities. It provides a novel hypothesis that complements existing theoretical frameworks. The hypothesis is well supported by data from a mathematical model, and it its predictions could be tested experimentally in future work.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    Lopez and Wingreen proposes the idea of noise-averaging cooperation (NAC), or within-population cross-feeding driven by noisy metabolism in microbes. The authors reasoned that since microbes are small, they are prone to noisy metabolism which limits growth rate. If related bacteria can share metabolites to average out noise (e.g in biofilm), then population growth rate can be improved and sometimes, the irreversible growth arrest of individuals can be prevented in theory. The authors predict substantial noise-driven growth inefficiencies from single-cell protein abundance data, review evidence for NAC, and propose how to detect NAC in microbial populations.

    Although this paper would be greatly strengthened by experimental tests (some of which may not be too difficult to do), I did enjoy reading it, and the writing is clear and thoughtful. The problem of "cheaters" (cells that take metabolites but do not leak any) will naturally arise, although the problem is mitigated in biofilms. Discussions on that will be useful.

  5. eLife

    Reviewer #2 (Public Review):

    The authors introduce the noise averaging cooperation (NAC) concept. When microbes' growth rates are limited due to the noise in vivo metabolite concentrations, sharing metabolites between microbes improves the growth rate of the whole community as the noise is averaged out. The NAC shows that metabolite leakage can be optimal for a group, suggesting a novel scenario to explain how microbial cross-feeding can evolve: first, the cells evolve to share their metabolites via leakage, and then gene deletion may occur, driving the evolution of microbial cross-feeding.

    The model is simple that is easy to understand, and provides intuitive results. Also, biologically feasible conditions where the benefit of metabolite sharing can arise are clearly addressed. Cells should be in a crowded space such as a biofilm to share the metabolites. If a huge free space isolates cells, they cannot get the advantage. An experimental design to confirm the existence of NAC in nature is well discussed as well. Overall, the NAC is a novel approach and provides clear predictions on the evolution of metabolite leakage under the assumptions.

    However, the model has the limitation that the obtained results strongly rely on the bursty behavior of enzyme production. Moreover, the model cannot explicitly show the evolution step on cross-feeding while it clearly shows that metabolite leakage is optimal. Thus, the current model can play a role as a stepping-stone, remaining a future investigation of the evolution of cross-feeding.

  6. eLife

    Reviewer #3 (Public Review):

    Summary:

    The authors present a novel hypothesis of how cross-feeding could evolve in microbial communities. Their central idea is that the growth rate of isolated cells is reduced by fluctuations in essential metabolite concentrations which result from noise in enzyme expression. They hypothesize that the effect of these fluctuations could be reduced if cells share metabolites with each other, as this would average out the fluctuations. The authors term this process noise-averaging cooperation (NAC) and they present a mathematical model to formally analyze their hypotheses.

    The authors first present a simple model for cells whose growth is limited by two essential metabolites. They show that fluctuations in enzyme levels decrease growth rates in isolated cells; the stronger the fluctuations (i.e., the larger the burst size of enzyme production) the more growth is reduced. Next, they show that it is beneficial for cells to share metabolites when enzyme levels fluctuate strongly. The optimal level of leakiness (i.e. cell permeability) depends on both cell density and the degree of enzyme fluctuations: high levels of leakiness are beneficial when cells grow in dense groups and face strong fluctuations, while low levels of leakiness are beneficial when cells grow in isolation and/or face weak fluctuations.

    The authors subsequently generalize their model to an arbitrary number of metabolites and show that the growth reducing effect of metabolite fluctuations increases with the number of essential metabolites. They use previously published experimental data to suggest that E. coli suffers from noise induce growth inhibition and they suggest several experiments that could be done to test predictions from their NAC model. Finally, they show that their results are robust with regards to chosen growth function.

    Strengths:

    Cross-feeding plays an essential role in microbial communities and understanding its ecological consequences and evolutionary history is essential to understand natural communities (including ones affecting human health and disease) and improve the functionality of engineered ones. This question has been the focus of numerous theoretical and experimental studies, however the NAC framework presented by the authors provides a novel and alternative mechanism of why cross-feeding can be beneficial and as such it provides an important addition to these previous studies.

    The NAC framework bridges two important subfields in microbiology: recent studies have focused on understanding how gene expression noise affects the physiology of cells and on how metabolic interactions affect the growth of microbial communities. The authors show that these two questions are related to each other, creating interesting opportunities for further investigations at the interplay between these two fields.

    The model presented by the authors is both simple and realistic. It has relatively few parameters, which all have clear biological meaning, and which could potentially be estimated from data. Most assumptions can be justified (though see below) and the framework could easily be extended in future work to address additional questions about the interplay between metabolic noise and metabolic interactions. A particular strength of the framework is that it creates testable predictions, and the authors discuss some possible experiments to test these predictions in detail.

    Weaknesses:

    The conclusions are generally well supported by the model, however in my opinion the authors somewhat overstate the significance of their results, especially when it comes to comparing them to previous theories on cross-feeding.

    Specifically, the authors suggest that the NAC framework is a generalization of the Black Queen Hypothesis (BQH), as it can provide an evolutionary explanation of why leakiness evolves. I think this misrepresents the relation between NAC and BQC for two reasons. First, although the authors give a plausible explanation of how leakiness could evolve, these conclusions are based on a purely ecological model and no actual evolutionary dynamics where investigated. NAC suggest that higher leakiness could be favored by selection because it buffers metabolic noise and increases cell growth rate, however it is not guaranteed to do so, as there is a potential for a conflict of interest between the individual and the group. E.g., consider a scenario where uptake rates of metabolites are fixed, but leakage rates can evolve. Higher leakage rates would increase the average growth in the population as it allows for cooperative noise buffering, however a mutant cell with a lower leakage rate would have a selective advantage as it does not pay the cost of losing metabolites, but still benefits from the noise buffering by taking up metabolites produced by the other cells. Whether leakiness can evolve under the NAC framework will thus critically depends on details of the evolutionary dynamics. In future work it would thus be essential to develop an evolutionary model to test if and when NAC allows for the evolution of higher levels leakiness. In the absence of such an evolutionary model it is not yet possible to determine whether NAC offers a more general theory than BQH.

    Second, the authors argue that the main limitation of BQH is that it assumes leakiness without providing an evolutionary explanation for it. Although experiments have shown that many metabolites are leaky, the authors argue that cells potentially could have evolved low leakiness levels, and BQH does not explain this fact. The authors thus imply that BQH is an incomplete theory, and they suggest that NAC offers a (more) complete alternative as it could potentially explain why leakiness evolved. I do not agree with this last statement, as in my opinion a similar argument can be made against NAC. NAC is fully contingent on the assumption that metabolism is inherently noisy, and this is not necessarily the case. The degree of gene expression noise is an evolvable trait: under the right conditions, cells could potentially have evolved a largely noise free metabolism, and NAC does not offer an evolutionary explanation for the level of noise we observe now. It is not clear to me why the limitation of BQH (leaving leakiness unexplained) is any worse (or better) than the limitation of NAC (leaving metabolic noise unexplained). In my opinion neither limitation is an issue: the levels of leakiness and metabolic noise we observe in present days microbes are likely the result of complex evolutionary trade-offs that involve many processes in addition to cross-feeding. I thus do not see clear grounds to call NAC more general than BQH, instead I see these two theories as complimentary frameworks that both offer important insight into the question of how cross-feeding could have evolved.

    Moreover, the authors neglect to discuss a third alternative explanation of how metabolite cross-feeding could have evolved. Recent experimental and theoretical work (see for example the work by the group of Christian Kost) has shown that some metabolic pathways display economies of scales: the marginal cost of producing additional metabolite goes down with the total amount of metabolites that is produced. In these cases, a division of labor based on cross-feeding becomes beneficial, as it reduces the overall production costs of metabolites and allows for faster growth of the community. This economy of scales model is complementary to NAC and BQH and a full explanation of cross-feeding will likely require apectes of all three models.

    None of these issues decreases the overall value of the presented framework: NAC is an interesting and novel hypothesis that can help understand cross-feeding communities. However, in my opinion NAC should be seen as complimentary to existing theories and not as a replacement.

    Finally, some of the model assumptions made by the authors have a debatable biological justification. For example, the authors assume that metabolites are degraded both in the cell and external environment, however I expect that most cross-fed metabolites are stable on the relevant time scales. Likewise, the authors assume that enzyme production is proportional to cell growth rate, while for many enzymes the transcription rate mostly depends on metabolite concentrations. Both these assumptions appear to strongly affect some of the authors conclusions: e.g., the decrease in the growth rate of isolated cells as function of permeability (Fig 1E) appears to depend strongly on the degradation rate, while the result that cells experience irreversible metabolic arrest depends critically on the fact that cells are unable to produce new enzymes when their growth halts. Care should thus be taken when comparing NAC predictions with experimental data and modifications of the relevant assumptions might be needed for such future work, however, the framework is flexible enough to allow for this, so this is not a major limitation.

  7. Version published to 10.1101/2021.06.02.446805v1 on bioRxiv