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

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 signif...

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Autores principales: Andrighetti, Tahila, Bohar, Balazs, Lemke, Ney, Sudhakar, Padhmanand, Korcsmaros, Tamas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291277/
https://www.ncbi.nlm.nih.gov/pubmed/32455748
http://dx.doi.org/10.3390/cells9051278
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author Andrighetti, Tahila
Bohar, Balazs
Lemke, Ney
Sudhakar, Padhmanand
Korcsmaros, Tamas
author_facet Andrighetti, Tahila
Bohar, Balazs
Lemke, Ney
Sudhakar, Padhmanand
Korcsmaros, Tamas
author_sort Andrighetti, Tahila
collection PubMed
description 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.
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spelling pubmed-72912772020-06-17 MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions Andrighetti, Tahila Bohar, Balazs Lemke, Ney Sudhakar, Padhmanand Korcsmaros, Tamas Cells Article 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. MDPI 2020-05-21 /pmc/articles/PMC7291277/ /pubmed/32455748 http://dx.doi.org/10.3390/cells9051278 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Andrighetti, Tahila
Bohar, Balazs
Lemke, Ney
Sudhakar, Padhmanand
Korcsmaros, Tamas
MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title_full MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title_fullStr MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title_full_unstemmed MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title_short MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions
title_sort microbiolink: an integrated computational pipeline to infer functional effects of microbiome–host interactions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7291277/
https://www.ncbi.nlm.nih.gov/pubmed/32455748
http://dx.doi.org/10.3390/cells9051278
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