Metabolic Overlap in Environmentally Diverse Microbial Communities

Abstract

The majority of microbial communities consist of hundreds to thousands of species, creating a massive network of organisms competing for available resources within an ecosystem. In natural microbial communities, it appears that many microbial species have highly redundant metabolisms and seemingly are capable of utilizing the same substrates. This is paradoxical, as theory indicates that species requiring a common resource should outcompete one another. To better understand why microbial species can coexist, we developed metabolic overlap (MO) as a new metric to survey the functional redundancy of microbial communities at the genome scale across a wide variety of ecosystems. Using metagenome-assembled genomes, we surveyed nearly 1,000 studies across nine ecosystem types. We found the highest MO in extreme (i.e., low pH/high temperature) and aquatic environments, while the lowest MO was observed in communities associated with animal hosts, the built/engineered environment, and soil. In addition, different metabolism subcategories were explored for their degree of MO. For instance, overlap in nitrogen metabolism was among the lowest in animal and engineered ecosystems, while species from the built environment had the highest overlap. Together, we present a metric that utilizes whole genome information to explore overlapping niches of microbes. This provides a detailed picture of potential metabolic competition and cooperation between species present in an ecosystem, indicates the main substrate types sustaining the community, and serves as a valuable tool to generate hypotheses for future research.

Model-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

“…In contrast, we see in Fig 2B there is a negative relationship between metabolic competition of bacterial species and phylogenetic distance. Our results are consistent with other previous studies of functional and metabolic relationships with phylogenetic distances [ 24 , 26 , 38 ]. And they support the theory of niche differentiation, which states that phylogenetically close species are more likely to compete with each other due to their shared traits and resource overlap, leading to less probability of their co-existence.…”

“…Our analysis shows that metabolic cooperation exhibits a positive relationship with phylogenetic distance, whereas metabolic competition exhibits a negative relationship. These findings support the results from previous work that studied the relationship between phylogenetic relatedness and gene content, functional distance, and metabolic interactions [ 24 , 26 , 38 ]. Together these observed relationships seem to support the theory of niche differentiation, where functional overlap discourages phylogenetically related species from co-existing.…”

Contribution Evenness: A functional redundancy metric sensitive to trait stability in microbial communities

“…Several metrics for functional redundancy exist in the literature. Functional redundancy has been taken as the ratio of community richness and the theoretical maximum number of functional entities (Mouillot et al, 2014), median metabolic overlap of genomic traits (Hester, Jetten, Welte, & Lücker, 2019), expected variability in trait space among community members (Ricotta et al, 2016), the degree of covariance in functional diversity and biodiversity (e.g., Galand et al, 2018; Micheli & Halpern, 2005; Miki, Yokokawa, & Matsui, 2013), and the simple fraction of a community with a given trait (Trivedi et al, 2020; Tully, Wheat, Glazer, & Huber, 2018; Wohl, Arora, & Gladstone, 2004). Notably, these different metrics treat community structure differently.…”

“…Notably, these different metrics treat community structure differently. For instance, some metrics are sensitive to species abundances (Galand et al, 2018; Ricotta et al, 2016), richness (Micheli & Halpern, 2005; Mouillot et al, 2014), or neither (Hester et al, 2019). The diversity of metrics reflects the diverse sources of data used to calculate functional redundancy and the diverse research purposes for how this concept is applied in research.…”

Pathway-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

“…Together, these studies have explored the relationship between functional 29 distances/metabolic overlap with phylogenetic relatedness, and they have given rise to 30 competing theories of 'habitat-filtering' and 'niche differentiation': habitat filtering 31 suggests that dominant species exhibit similar functional traits, whereas niche 32 differentiation says that phylogenetically similar species are unable to co-exist due to 33 similar traits and resource overlap (3). Nevertheless, methods have been developed for 34 inference of bacterial interaction network based on the assumption that phylogenetically 35 related species tend to co-exists. For example, Lo et al (15) developed phylogenetic 36 graphical lasso approach for bacterial community detection, based on the assumption 37 that phylogenetically correlated microbial species are more likely to interact to each 38 other.…”