MDPbiome: Microbiome Engineering through Prescriptive Perturbations

García Jiménez, Beatriz and Rosa, Tomás de la and Wilkinson, Mark Denis (2018). MDPbiome: Microbiome Engineering through Prescriptive Perturbations. "Bioinformatics", v. 34 (n. 17); pp.. ISSN 1367-4803. https://doi.org/10.1093/bioinformatics/bty562.

Description

Title: MDPbiome: Microbiome Engineering through Prescriptive Perturbations
Author/s:
  • García Jiménez, Beatriz
  • Rosa, Tomás de la
  • Wilkinson, Mark Denis
Item Type: Article
Título de Revista/Publicación: Bioinformatics
Date: September 2018
ISSN: 1367-4803
Volume: 34
Subjects:
Faculty: Centro de Investigación en Biotecnología y Genómica de Plantas (CBGP) (UPM)
Department: Biotecnología - Biología Vegetal
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

MDPbiome statistically models longitudinal metagenomics samples undergoing perturbations as a Markov Decision Process (MDP). Given a starting microbial composition, our MDPbiome system suggests the sequence of external perturbation(s) that will engineer that microbiome to a goal state, for example, a healthier or more performant composition. It also estimates intermediate microbiome states along the path, thus making it possible to avoid particularly undesirable/unhealthy states. We demonstrate MDPbiome performance over three real and distinct datasets, proving its flexibility, and the reliability and universality of its output ?optimal perturbation policy?. For example, an MDP created using a vaginal microbiome time series, with a goal of recovering from bacterial vaginosis, suggested avoidance of perturbations such as lubricants or sex toys; while another MDP provided a quantitative explanation for why salmonella vaccine accelerates gut microbiome maturation in chicks. This novel analytical approach has clear applications in medicine, where it could suggest low-impact clinical interventions that will lead to achievement or maintenance of a healthy microbial population, or alternately, the sequence of interventions necessary to avoid strongly negative microbiome states.

More information

Item ID: 54821
DC Identifier: http://oa.upm.es/54821/
OAI Identifier: oai:oa.upm.es:54821
DOI: 10.1093/bioinformatics/bty562
Official URL: https://academic.oup.com/bioinformatics/article/34/17/i838/5093255
Deposited by: Memoria Investigacion
Deposited on: 12 Jul 2019 11:24
Last Modified: 01 Oct 2019 22:30
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