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Open AccessArticle

MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions

1
Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK
2
Institute of Biosciences, São Paulo University (UNESP), Botucatu 18618-689, SP, Brazil
3
Department of Genetics, Eötvös Loránd University, Budapest 1117, Hungary
4
Quadram Institute Bioscience, Norwich Research Park, Norwich NR4 7UQ, UK
5
Department of Chronic Diseases, Metabolism and Ageing, KU Leuven BE-3000, Leuven, Belgium
*
Authors to whom correspondence should be addressed.
Current address: Laboratory of Structural Bioinformatics and Computational Biology (SBCB), Institute of Informatics, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre 91501-970, RS, Brazil.
Cells 2020, 9(5), 1278; https://doi.org/10.3390/cells9051278
Received: 23 April 2020 / Revised: 15 May 2020 / Accepted: 19 May 2020 / Published: 21 May 2020
(This article belongs to the Special Issue Quantitative Models of Autoimmunity)
Microbiome–host interactions play significant roles in health and in various diseases including autoimmune disorders. Uncovering these inter-kingdom cross-talks propels our understanding of disease pathogenesis and provides useful leads on potential therapeutic targets. Despite the biological significance of microbe–host interactions, there is a big gap in understanding the downstream effects of these interactions on host processes. Computational methods are expected to fill this gap by generating, integrating, and prioritizing predictions—as experimental detection remains challenging due to feasibility issues. Here, we present MicrobioLink, a computational pipeline to integrate predicted interactions between microbial and host proteins together with host molecular networks. Using the concept of network diffusion, MicrobioLink can analyse how microbial proteins in a certain context are influencing cellular processes by modulating gene or protein expression. We demonstrated the applicability of the pipeline using a case study. We used gut metaproteomic data from Crohn’s disease patients and healthy controls to uncover the mechanisms by which the microbial proteins can modulate host genes which belong to biological processes implicated in disease pathogenesis. MicrobioLink, which is agnostic of the microbial protein sources (bacterial, viral, etc.), is freely available on GitHub. View Full-Text
Keywords: microbiota–host interactions; protein–protein interactions; systems biology; networks; network diffusion; computational pipeline microbiota–host interactions; protein–protein interactions; systems biology; networks; network diffusion; computational pipeline
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MDPI and ACS Style

Andrighetti, T.; Bohar, B.; Lemke, N.; Sudhakar, P.; Korcsmaros, T. MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions. Cells 2020, 9, 1278.

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