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Abstract
Across many environments microbial glycoside hydrolases support the enzymatic processing of carbohydrates, a critical function in many ecosystems. Little is known about how the microbial composition of a community and the potential for carbohydrate processing relate to each other. Here, using 1,934 metagenomic datasets, we linked changes in community composition to variation of potential for carbohydrate processing across environments. We were able to show that each ecosystem-type displays a specific potential for carbohydrate utilization. Most of this potential was associated with just 77 bacterial genera. The GH content in bacterial genera is best described by their taxonomic affiliation. Across metagenomes, fluctuations of the microbial community structure and GH potential for carbohydrate utilization were correlated. Our analysis reveals that both deterministic and stochastic processes contribute to the assembly of complex microbial communities.
Highlights
The complete enzymatic deconstruction of polysaccharides involves many carbohydrate active enzymes (CAZymes) including glycoside hydrolases (GH), polysaccharide lyases, carbohydrate esterases, accessory activities (e.g., LPMO), and many accessory domains (e.g., CBM)[1,2,3,4]
The identification of specific GH domains in sequenced genomes [6] and metagenomes [7] allows for the prediction of the potential for starch, cellulose, xylan, fructan, chitin, and dextran deconstruction[2,6,8,9]
In order to test how the environment affected the potential for carbohydrate utilization across ecosystems, we identified 130.2×106 sequences encoding putative glycoside hydrolases (GH, ~0.5% of analyzed sequences) in 1,934 annotated metagenomes from 13 broadly defined ecosystems (S1 Table) [35]
Summary
The complete enzymatic deconstruction of polysaccharides (e.g., cellulose, chitin) involves many carbohydrate active enzymes (CAZymes) including glycoside hydrolases (GH), polysaccharide lyases, carbohydrate esterases, accessory activities (e.g., LPMO), and many accessory domains (e.g., CBM)[1,2,3,4]. The identification of specific GH domains in sequenced genomes [6] and metagenomes [7] allows for the prediction of the potential for starch, cellulose, xylan, fructan, chitin, and dextran deconstruction (i.e., the potential to target carbohydrates according to functional annotation of genes)[2,6,8,9]. Environments with expected abundant and diverse supply of carbohydrates (e.g., human gut, animal, phyllosphere, soil) were associated with sequences for GH targeting many different substrates.
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