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Published on: March 5, 2022
Application of a maximal-clique based community detection algorithm to gut microbiome data reveals driver microbes
Anirban Bhar1, Laurin Christopher Gierse2, Alexander Meene2
1Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany.
Abstract:
Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.
Insights
Influenza A Virus (IAV) infection disrupts the gut microbiome. This study introduces a new algorithm to analyze gut microbial communities, identifying key bacterial families involved in host immune response and recovery from IAV infection.
Area of Science:
- Microbiology and Virology
- Bioinformatics and Computational Biology
- Immunology
Background:
- Influenza A Virus (IAV) infection, often followed by bacterial pneumonia, poses significant health risks, particularly for high-risk populations.
- IAV infection disrupts the gut microbial community, impacting the host's colonization resistance, a crucial protective mechanism.
- The intricate mechanisms by which gut microbiota modulate host immune responses post-IAV infection remain incompletely understood.
Purpose of the Study:
- To develop and validate a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN).
- To apply the MCCD-WN algorithm to analyze gut microbiome dynamics in pigs following Influenza A Virus infection.
- To identify microbial biomarkers and elucidate their functional roles in host protection and recovery from IAV infection.
Main Methods:
- Development of a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN).
- Performance evaluation of MCCD-WN against existing algorithms using benchmark networks.
- Application of MCCD-WN to gut microbiome and metaproteomic data from IAV-infected pigs over time.
Main Results:
- The MCCD-WN algorithm demonstrated effective performance in network analysis.
- Analysis of IAV-infected pig data revealed the involvement of microbial families such as Ruminococcaceae, Lachnospiraceae, Spirochaetaceae, and Prevotellaceae.
- Metaproteomic data integration identified microbial biomarkers and their functional roles, highlighting Desulfovibrionaceae and Lactobacillaceae in combating IAV infection and facilitating recovery.
Conclusions:
- The study presents a novel computational tool (MCCD-WN) for analyzing complex microbial network data.
- Key gut microbial families were identified as critical players in the host's response to Influenza A Virus infection.
- The findings provide insights into the gut microbiota's role in host defense and recovery, with potential implications for therapeutic strategies.
