4.6 Article

New Insights into the Co-Occurrences of Glycoside Hydrolase Genes among Prokaryotic Genomes through Network Analysis

Journal

MICROORGANISMS
Volume 9, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/microorganisms9020427

Keywords

glycoside hydrolases; prokaryotes; co-occurrence; network; Gephi

Categories

Funding

  1. National Key R&D Program of China [2018YFE0107100]
  2. Priority Academic Program Development of Jiangsu Higher Education Institution
  3. National Natural Science Foundation of China [31900367]

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The study found that glycoside hydrolase families are more common in bacteria and showed strong or moderate-strong correlations among certain microbial collections. Additionally, particular GHFs were progressively enriched in certain types of microbes.
Glycoside hydrolase (GH) represents a crucial category of enzymes for carbohydrate utilization in most organisms. A series of glycoside hydrolase families (GHFs) have been classified, with relevant information deposited in the CAZy database. Statistical analysis indicated that most GHFs (134 out of 154) were prone to exist in bacteria rather than archaea, in terms of both occurrence frequencies and average gene numbers. Co-occurrence analysis suggested the existence of strong or moderate-strong correlations among 63 GHFs. A combination of network analysis by Gephi and functional classification among these GHFs demonstrated the presence of 12 functional categories (from group A to L), with which the corresponding microbial collections were subsequently labeled, respectively. Interestingly, a progressive enrichment of particular GHFs was found among several types of microbes, and type-L as well as type-E microbes were deemed as functional intensified species which formed during the microbial evolution process toward efficient decomposition of lignocellulose as well as pectin, respectively. Overall, integrating network analysis and enzymatic functional classification, we were able to provide a new angle of view for GHs from known prokaryotic genomes, and thus this study is likely to guide the selection of GHs and microbes for efficient biomass utilization.

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