Defining Coarse-Grainability in a Model of Structured Microbial Ecosystems

Moran, Jacob; Tikhonov, Mikhail

doi:10.1103/physrevx.12.021038

Cited by 10 publications

(14 citation statements)

References 62 publications

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“…This substrate diversity gives rise to a huge number of potential metabolic niches, about 10 30 for just 100 metabolites. Therefore, solving the challenge of understanding metabolic processes in heterotrophic microbial communities requires not only experimental characterizations and the development of phenotype-genotype mappings, but also a way to conceptually simplify, i.e., to “coarse-grain”, metabolic niche space into a few easily interpretable metabolic strategies (7, 8).…”

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confidence: 99%

Fundamental metabolic strategies of heterotrophic bacteria

Gralka

Pollak

Cordero

2022

Preprint

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Through their metabolism, heterotrophic microbes drive carbon cycling in many environments. These microbes consume (and produce) hundreds to thousands of different metabolic substrates, begging the question of what level of description is required to understand the metabolic processes structuring their communities: do we need to account for the detailed metabolic capabilities of each organism, or can these capabilities be understood in terms of a few well-conserved carbon utilization strategies that could be more easily interpreted and more robustly predicted? Based on the high-throughput phenotyping of a diverse collection of marine bacteria, we showed that the fundamental metabolic strategy of heterotrophic microbes can be understood in terms of a single axis of variation, representing their preference for either glycolytic (sugars) or gluconeogenic (amino and organic acids) carbon sources. Moreover, an organism's position on this axis is imprinted in its genome, allowing us to successfully predict metabolic strategy across the bacterial tree of life. Our analysis also unveils a novel and general association between metabolic strategy and genomic GC content, which we hypothesize results from the difference in C:N supply associated with typical sugar and acid substrates. Thus, our work reveals a fundamental constraint on microbial evolution that structures bacterial genomes and communities and can be leveraged to understand diversity in functional terms, beyond catalogs of genes and taxa.

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confidence: 99%

Fundamental metabolic strategies of heterotrophic bacteria

Gralka

Pollak

Cordero

2022

Preprint

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“…What makes the inference possible is that the special structures in the connectivity matrix are constrained by the metapopulation dynamics. This property is known as coarse-grainability in physics [38]. Specifically, the inherent linear structure of metapopulation capacity and conserved structure of patch importance (figure 2).…”

Section: Discussionmentioning

confidence: 99%

Metapopulation persistence can be inferred from incomplete surveys

2022

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Habitat destruction and fragmentation are principal causes of species loss. While a local population might go extinct, a metapopulation—populations inhabiting habitat patches connected by dispersal—can persist regionally by recolonizing empty patches. To assess metapopulation persistence, two widely adopted indicators in conservation management are metapopulation capacity and patch importance. However, we face a fundamental limitation in that assessing metapopulation persistence requires that we survey or sample all the patches in a landscape: often these surveys are logistically challenging to conduct and repeat, which raises the question whether we can learn enough about the metapopulation persistence from an incomplete survey. Here, we provide a robust statistical approach to infer metapopulation capacity and patch importance by sampling a portion of all patches. We provided analytic arguments on why the metapopulation capacity and patch importance can be well predicted from sub-samples of habitat patches. Full-factorial simulations with more complex models corroborate our analytic predictions. We applied our model to an empirical metapopulation of mangrove hummingbirds ( Amazilia boucardi ). On the basis of our statistical framework, we provide some sampling suggestion for monitoring metapopulation persistence. Our approach allows for rapid and effective inference of metapopulation persistence from incomplete patch surveys.

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“…To tackle this complexity, a key goal in ecology has been to derive methods of coarsening, e.g., functional groups or guilds [5, 16]. Such coarsened representations can be more reproducible than the microscopic characterization while still being predictive of properties of interest [6, 10, 14–16, 20, 21]. Earlier, some network-based methods were proposed for identifying such biologically meaningful groups of organisms [1,23].…”

Section: Introductionmentioning

confidence: 99%

Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function

Zhao,

Cordero,

Tikhonov

2024

Preprint

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Microbial communities play key roles across diverse environments. Predicting their function and dynamics is a key goal of microbial ecology, but detailed microscopic descriptions of these systems can be prohibitively complex. One approach to deal with this complexity is to resort to coarser representations. Several approaches have sought to identify useful groupings of microbial species in a data-driven way. Of these, recent work has claimed some empirical success at de novo discovery of coarse representations predictive of a given function using methods as simple as a linear regression, against multiple groups of species or even a single such group (the EQO approach of Shan et al., 2023). This success seems puzzling, since modeling community function as a linear combination of contributions of individual species appears simplistic. However, the task of identifying a predictive coarsening of an ecosystem is distinct from the task of predicting the function well, and it is conceivable that the former could be accomplished by a simpler methodology than the latter. Here, we use the resource competition framework to design a model where the "correct" grouping to be discovered is well-defined, and use synthetic data to evaluate and compare three regression-based methods, namely, two proposed previously and one we introduce. We find that regression-based methods can recover the groupings even when the function is manifestly nonlinear; that multi-group methods offer an advantage over a single-group EQO; and crucially, that simpler (linear) methods can outperform more complex ones.

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Defining Coarse-Grainability in a Model of Structured Microbial Ecosystems

Cited by 10 publications

References 62 publications

Fundamental metabolic strategies of heterotrophic bacteria

Fundamental metabolic strategies of heterotrophic bacteria

Metapopulation persistence can be inferred from incomplete surveys

Linear-regression-based algorithms can succeed at identifying microbial functional groups despite the nonlinearity of ecological function

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