Using metabolic networks to resolve ecological properties of microbiomes

Modeling microbial communities from atrazine contaminated soils promotes the development of biostimulation solutions

“…Especially, the "in situ microbiome engineering" could be a new paradigm of community-scale microbial engineering [57]. Microbiome's activities and capacities are to a large extent determined by complex networks of metabolic interactions and exchanges [59][60][61][62]. Traditionally, the study of bacterial interactions required the use of laboratory experiments such as growth and co-culture assays [59,63].…”

“…Although multi-technique strategies have been successfully applied for some model systems such as enrichment cultures and synthetic communities [3,65], their application for the study of natural communities is far from trivial [63]. Mathematical models of bacterial community expand the toolbox for detecting metabolic dependencies in natural bacterial consortia [14,17,62].…”

“…3 (NY15, N8 and AT5, respectively). Bars represent the standard errors of the three replicates and more feasible and can hence provide a realistic bridge between microbial ecology and system biology and allow to study ecosystem-level function and dynamics [14,17,62]. Here, all approximations require at least 97% identity in the 16S rRNA between OTUs and representative species, following the common practice in the large majority of ecological surveys of co-clustering sequences above this degree of similarity into a common taxonomic unit.…”

Evidence for a multi-level trophic organization of the human gut microbiome

“…Quantitatively connecting these levels with 21 each other, requires knowledge of the relationships between microbes and metabolites in their 22 shared environment: who produces what, and who consumes what? [9,10] In recent studies, 23 information about these relationships for all of the common species and metabolites in the human 24 gut has been gathered using both manual curation from published studies [6] and automated 25 genome reconstruction methods [3]. This has laid the foundation for mechanistic models which 26 would allow one to relate metabolome composition to microbiome composition [11,12].…”

The signal and the noise - characteristics of antisense RNA in complex microbial communities

“…Much of the current knowledge about asRNA is indeed based on pure cultures (Bashiardes, Zilberman-Schapira, and Elinav 2016), which may not be representative of the intricate interactions that potentially occur in coexistence with other organisms in complex communities, where single cells within a population may be in different states of growth and dormancy simultaneously (Shank 2018). Regardless, profiling microbial communities by high-throughput omics techniques remains a powerful tool to build metabolic networks and infer interactions between different organisms (Mallick et al 2017; Franzosa et al 2018; Muller et al 2018) and we believe asRNA expression should be integrated into such analysis. From our literature search we found three approaches to handle asRNA (Table 1), of which ignoring asRNA or quantifying only the sense RNA are by far the most common.…”