Capturing the dynamics of microbial interactions through individual-specific networks

Frontiers in Microbiology, vol. 14, pp. 1170391

Abstract

Longitudinal analysis of multivariate individual-specific microbiome profiles over time or across conditions remains dauntin. Most statistical tools and methods that are available to study microbiomes are based on cross-sectional data. Over the past few years, several attempts have been made to model the dynamics of bacterial species over time or across conditions. However, the field needs novel views on handling microbial interactions in temporal analyses. This study proposes a novel data analysis framework, MNDA, that combines representation learning and individual-specific microbial co-occurrence networks to uncover taxon neighborhood dynamics. As a use case, we consider a cohort of newborns with microbiomes available at 6 and 9 months after birth, and extraneous data available on the mode of delivery and diet changes between the considered time points. Our results show that prediction models for these extraneous outcomes based on an MNDA measure of local neighborhood dynamics for each taxon outperform traditional prediction models solely based on individual-specific microbial abundances. Furthermore, our results show that unsupervised similarity analysis of newborns in the study, again using the notion of a taxon's dynamic neighborhood derived from time-matched individual-specific microbial networks, can reveal different subpopulations of individuals, compared to standard microbiome-based clustering, with potential relevance to clinical practice. This study highlights the complementarity of microbial interactions and abundances in downstream analyses and opens new avenues to personalized prediction or stratified medicine with temporal microbiome data.

Authors 8

1. Behnam Yousefi

   Institut Pasteur · Sorbonne Université · KU Leuven

   Affiliation as printed

   BIO3-Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium

   Computational Systems Biomedicine Lab, Institut Pasteur, University Paris City, Paris, France

   École Doctorale Complexite du vivant, Sorbonne University, Paris, France

   BIO3—Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium

2. Federico Melograna

   KU Leuven

   Affiliation as printed

   BIO3-Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium

   BIO3—Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium

3. Gianluca Galazzo

   Maastricht University Medical Centre · Maastricht University

   Affiliation as printed

   Department of Medical Microbiology, Infectious Diseases and Infection Prevention, School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, Netherlands

4. Niels van Best Aachen Institute of Medical Microbiology

   Maastricht University Medical Centre · Maastricht University · RWTH Aachen University

   Affiliation as printed

   Department of Medical Microbiology, Infectious Diseases and Infection Prevention, School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, Netherlands

   Institute of Medical Microbiology, Rhine-Westphalia Technical University of Aachen, RWTH University, Aachen, Germany

5. Monique Mommers

   Maastricht University · Care and Public Health Research Institute

   Affiliation as printed

   Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, Netherlands

6. John Penders

   Maastricht University Medical Centre · Maastricht University · Care and Public Health Research Institute

   Affiliation as printed

   Department of Medical Microbiology, Infectious Diseases and Infection Prevention, Care and Public Health Research Institute (CAPHRI), Maastricht University Medical Center+, Maastricht, Netherlands

   Department of Medical Microbiology, Infectious Diseases and Infection Prevention, School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center+, Maastricht, Netherlands

7. Benno Schwikowski

   Institut Pasteur

   Affiliation as printed

   Computational Systems Biomedicine Lab, Institut Pasteur, University Paris City, Paris, France

8. Kristel Van Steen corresponding

   University of Liège · KU Leuven

   Affiliation as printed

   BIO3-Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Lièvzge, Liège, Belgium

   BIO3-Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium

   BIO3—Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Lièvzge, Liège, Belgium

   BIO3—Laboratory for Systems Medicine, Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium