Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Causal inference on microbiome-metabolome relations via in silico in vivo association pattern analyses

View ORCID ProfileJohannes Hertel, View ORCID ProfileAlmut Heinken, View ORCID ProfileInes Thiele
doi: https://doi.org/10.1101/2021.03.15.435397
Johannes Hertel
1School of Medicine, National University of Galway, Galway, Ireland
2Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Johannes Hertel
Almut Heinken
1School of Medicine, National University of Galway, Galway, Ireland
3Ryan Institute, National University of Galway, Galway, Ireland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Almut Heinken
Ines Thiele
1School of Medicine, National University of Galway, Galway, Ireland
3Ryan Institute, National University of Galway, Galway, Ireland
4Discipline of Microbiology, National University of Galway, Galway, Ireland
5APC Microbiome Ireland, University College Cork, Cork, Ireland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ines Thiele
  • For correspondence: ines.thiele@nuigalway.ie
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

The effects of the microbiome on the host’s metabolism are core to understanding the role of the microbiome in health and disease. Herein, we develop the paradigm of in silico in vivo association pattern analyses, entailing a methodology to combine microbiome metabolome association studies with in silico constraint-based microbial community modelling. By dissecting confounding and causal paths, we show that in silico in vivo association pattern analyses allows for causal inference on microbiome-metabolome relations in observational data. Then, we demonstrate the feasibility and validity of our approach on a published multi-omics dataset (n=346), demonstrating causal microbiome-metabolite relations for 43 out of 53 metabolites from faeces. Finally, we utilise the identified in silico in vivo association pattern to estimate the microbial component of the faecal metabolome, revealing that the retrieved metabolite prediction scores correlate with the measured metabolite concentrations, and they also reflect the multivariate structure of the faecal metabolome. Concluding, we integrate with hypothesis free screening association studies and knowledge-based in silico modelling two major paradigms of systems biology, generating a promising new paradigm for causal inference in metabolic host-microbe interactions.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted March 16, 2021.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Causal inference on microbiome-metabolome relations via in silico in vivo association pattern analyses
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Causal inference on microbiome-metabolome relations via in silico in vivo association pattern analyses
Johannes Hertel, Almut Heinken, Ines Thiele
bioRxiv 2021.03.15.435397; doi: https://doi.org/10.1101/2021.03.15.435397
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Causal inference on microbiome-metabolome relations via in silico in vivo association pattern analyses
Johannes Hertel, Almut Heinken, Ines Thiele
bioRxiv 2021.03.15.435397; doi: https://doi.org/10.1101/2021.03.15.435397

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3514)
  • Biochemistry (7365)
  • Bioengineering (5341)
  • Bioinformatics (20317)
  • Biophysics (10041)
  • Cancer Biology (7771)
  • Cell Biology (11346)
  • Clinical Trials (138)
  • Developmental Biology (6447)
  • Ecology (9979)
  • Epidemiology (2065)
  • Evolutionary Biology (13353)
  • Genetics (9370)
  • Genomics (12605)
  • Immunology (7724)
  • Microbiology (19086)
  • Molecular Biology (7459)
  • Neuroscience (41128)
  • Paleontology (300)
  • Pathology (1235)
  • Pharmacology and Toxicology (2142)
  • Physiology (3174)
  • Plant Biology (6878)
  • Scientific Communication and Education (1276)
  • Synthetic Biology (1900)
  • Systems Biology (5327)
  • Zoology (1091)