An ensemble approach to the structure-function problem in microbial communities

Gopalakrishnappa, Chandana; Gowda, Karna; Prabhakara,; Kuehn, Seppe

doi:10.1016/j.isci.2022.103761

Cited by 19 publications

(14 citation statements)

References 235 publications

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“…Here, we study the success of the heuristic search by simulating a range of realistic and widely-used consumer-resource models of microbial communities, which have reproduced many features of natural and experimental communities [22][23][24]. Compared to the commonly-used Lotka-Volterra models, our approach is more realistic and makes a closer connection to the metabolic interactions that underpin many optimization problems in biotechnology [25][26][27][28][29]. Furthermore, it is much easier to make educated guesses about the production and consumption of resources than interaction coefficients.…”

Section: Introductionmentioning

confidence: 99%

Ecological landscapes guide the assembly of optimal microbial communities

George

Korolev

2023

PLoS Comput Biol

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Assembling optimal microbial communities is key for various applications in biofuel production, agriculture, and human health. Finding the optimal community is challenging because the number of possible communities grows exponentially with the number of species, and so an exhaustive search cannot be performed even for a dozen species. A heuristic search that improves community function by adding or removing one species at a time is more practical, but it is unknown whether this strategy can discover an optimal or nearly optimal community. Using consumer-resource models with and without cross-feeding, we investigate how the efficacy of search depends on the distribution of resources, niche overlap, cross-feeding, and other aspects of community ecology. We show that search efficacy is determined by the ruggedness of the appropriately-defined ecological landscape. We identify specific ruggedness measures that are both predictive of search performance and robust to noise and low sampling density. The feasibility of our approach is demonstrated using experimental data from a soil microbial community. Overall, our results establish the conditions necessary for the success of the heuristic search and provide concrete design principles for building high-performing microbial consortia.

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Section: Introductionmentioning

confidence: 99%

Ecological landscapes guide the assembly of optimal microbial communities

George

Korolev

2023

PLoS Comput Biol

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“…Ecological communities possess emergent community-level properties, i.e., properties that depend on but cannot be reduced to the properties of individual members of the community [37][38][39][40][41]. For example, whereas beak morphology is a trait of an individual finch, the distribution of beak morphologies in a community of finches on an island is a property of the community.…”

Section: Defining Community Evolution and Its Repeatabilitymentioning

confidence: 99%

“…This question can be broken down into two more basic problems. How do species traits map onto community-level properties [40,42]? And how does evolution explore the trait space?…”

Section: How Is the Repeatability Of Evolution At The Community Level...mentioning

confidence: 99%

“…However, most species belong to ecological communities where they interact with one another by competing for resources, parasitizing, cooperating, etc. These interactions endow communities with emergent properties, such as diversity, productivity, function, etc., that depend on but cannot be reduced to individual-level properties [37][38][39][40][41][42][43]. Such community-level properties are part of the environment in which community-member species evolve and to which they adapt.…”

Section: Introductionmentioning

confidence: 99%

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Evolutionary repeatability of emergent properties of ecological communities

Venkataram¹,

Kryazhimskiy²

2022

Preprint

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Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (1) Is the observed degree of repeatability surprising? (2) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (3) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics.

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“…These and other studies (Bittleston et al, 2020;Clark et al, 2021;Eble et al, 2021;George and Korolev, 2021;Gopalakrishnappa et al, 2022;Gould et al, 2018;Sanchez-Gorostiaga et al, 2019;Senay et al, 2019;Xie and Shou, 2021;Xie et al, 2019) have formally defined the structure-function (or composition-function, or community-function) landscape as the empirical map between community composition and function in a given habitat and set of conditions. The structure of a microbial consortium is given by the list of all it genotypes g = {g1,g2,...,gn} and their respective abundances xg = {x1,x2,...,xn}.…”

Section: Introductionmentioning

confidence: 99%

The community-function landscape of microbial consortia

Sánchez¹,

Bajić²,

Díaz-Colunga³

et al. 2022

Preprint

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Quantitatively and predictively linking the composition and function of microbial communities is a major aspiration of microbial ecology. It is also a critical step in the path toward engineering synthetic consortia and manipulating natural microbiomes. The functions of microbial communities are collective properties that emerge from a complex web of molecular interactions between individual cells, which in turn lead to population-level interactions among strains and species. Incorporating this complexity into predictive models has been highly challenging. A similar problem of predicting phenotype from genotype has been addressed for decades in the field of quantitative genetics, leading to advances in the fields of protein and molecular engineering. By analogy to the genotype-phenotype landscape, an ecological community-function (or structure-function) landscape could be defined that maps community composition and function. In this piece, we present an overview of our current understanding of these community landscapes, their uses, limitations, and open questions. We argue that exploiting the parallels between both landscapes could bring powerful predictive methodologies from evolution and genetics into ecology, providing a boost to our ability to engineer and optimize microbial consortia.

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An ensemble approach to the structure-function problem in microbial communities

Cited by 19 publications

References 235 publications

Ecological landscapes guide the assembly of optimal microbial communities

Ecological landscapes guide the assembly of optimal microbial communities

Evolutionary repeatability of emergent properties of ecological communities

The community-function landscape of microbial consortia

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