Microbial interaction-driven community differences as revealed by network analysis

Abstract

Diversity and compositional analysis are the most common approaches in deciphering microbial community differences. However, these approaches neglect microbial structural differences driven by microbial interactions. In this study, the microbiota data were generated from 12 rectal digesta samples collected from steers in which the Shiga toxin 2 gene (stx2) was not expressed (defined as Stx2− group) in the bacteria, and those with stx2 expressed (defined as Stx2+ group) and used to explore whether microbial networks affect gut microbiota and foodborne pathogen virulence in cattle. Although the Shannon and Chao1 indices of rectal digesta microbial communities did not differ between the two groups (P > 0.05), 24 and 13 taxa were identified to be group-specific genera for Stx2− and Stx2+ microbial communities, respectively. The network analysis indicated 12 and 14 generalists (microbes that were densely connected with other taxa) in microbial communities for Stx2− and Stx2+ groups, and 8 out of 12 generalists and 6 out of 14 generalists were designated to Stx2− and Stx2+ group-specific genera, respectively. However, the 66 core genera were not classified as network generalists. Natural connectivity measurements revealed that the higher stability of the Stx2− microbial network in comparison to the Stx2+ network, suggesting that the structure of each microbial community was inherently different even when their diversity and composition were comparable. Group-specific genera intensely interacted with other taxa in the co-occurrence network, indicating that characterizing microbial networks together with group-specific genera could be an alternative approach to identify variation in microbial communities.

Keywords

• Shiga toxin
• Microbial interactions
• Co-occurrence network
• Group-specific taxa