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...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Cells |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4409/9/5/1278 |
| _version_ | 1797567351649992704 |
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| author | Tahila Andrighetti Balazs Bohar Ney Lemke Padhmanand Sudhakar Tamas Korcsmaros |
| author_facet | Tahila Andrighetti Balazs Bohar Ney Lemke Padhmanand Sudhakar Tamas Korcsmaros |
| author_sort | Tahila Andrighetti |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-10T19:40:30Z |
| format | Article |
| id | doaj.art-36daaf2be5454ca79b086a531116a10e |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-10T19:40:30Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-36daaf2be5454ca79b086a531116a10e2023-11-20T01:17:25ZengMDPI AGCells2073-44092020-05-0195127810.3390/cells9051278MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host InteractionsTahila Andrighetti0Balazs Bohar1Ney Lemke2Padhmanand Sudhakar3Tamas Korcsmaros4Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UKEarlham Institute, Norwich Research Park, Norwich NR4 7UZ, UKInstitute of Biosciences, São Paulo University (UNESP), Botucatu 18618-689, SP, BrazilEarlham Institute, Norwich Research Park, Norwich NR4 7UZ, UKEarlham Institute, Norwich Research Park, Norwich NR4 7UZ, UKMicrobiome–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.https://www.mdpi.com/2073-4409/9/5/1278microbiota–host interactionsprotein–protein interactionssystems biologynetworksnetwork diffusioncomputational pipeline |
| spellingShingle | Tahila Andrighetti Balazs Bohar Ney Lemke Padhmanand Sudhakar Tamas Korcsmaros MicrobioLink: An Integrated Computational Pipeline to Infer Functional Effects of Microbiome–Host Interactions Cells microbiota–host interactions protein–protein interactions systems biology networks network diffusion computational pipeline |
| 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 | microbiota–host interactions protein–protein interactions systems biology networks network diffusion computational pipeline |
| url | https://www.mdpi.com/2073-4409/9/5/1278 |
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