Wavelet clustering analysis as a tool for characterizing community structure in the human microbiome

Scientific Reports, vol. 13, pp. 8042

Abstract

Human microbiome research is helped by the characterization of microbial networks, as these may reveal key microbes that can be targeted for beneficial health effects. Prevailing methods of microbial network characterization are based on measures of association, often applied to limited sampling points in time. Here, we demonstrate the potential of wavelet clustering, a technique that clusters time series based on similarities in their spectral characteristics. We illustrate this technique with synthetic time series and apply wavelet clustering to densely sampled human gut microbiome time series. We compare our results with hierarchical clustering based on temporal correlations in abundance, within and across individuals, and show that the cluster trees obtained by using either method are significantly different in terms of elements clustered together, branching structure and total branch length. By capitalizing on the dynamic nature of the human microbiome, wavelet clustering reveals community structures that remain obscured in correlation-based methods.

Authors 6

1. Elisa Benincà corresponding

   National Institute for Public Health and the Environment

   Affiliation as printed

   Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. elisa.beninca@rivm.nl

   Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands

2. Susanne Pinto Aachen Biomedical Data Sciences

   Leiden University Medical Center

   Affiliation as printed

   Biomedical Data Sciences, Leiden UMC, Leiden, The Netherlands

3. Bernard Cazelles

   Centre National de la Recherche Scientifique · École Normale Supérieure - PSL · Sorbonne Université · Institut de Biologie de l'École Normale Supérieure · Unité de Modélisation Mathématique et Informatique des Systèmes Complexes

   Affiliation as printed

   CNRS UMR-8197, IBENS, Ecole Normale Supérieure, Paris, France

   Sorbonne Université, UMMISCO, Paris, France

4. Susana Fuentes

   National Institute for Public Health and the Environment

   Affiliation as printed

   Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands

5. Sudarshan Anand Shetty

   University Medical Center Groningen · University of Groningen · National Institute for Public Health and the Environment

   Affiliation as printed

   Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands

   Department of Medical Microbiology and Infection Prevention, UMC Groningen, Groningen, The Netherlands

6. Johannes A. Bogaards

   Amsterdam University Medical Centers · Amsterdam UMC Location Vrije Universiteit Amsterdam

   Affiliation as printed

   Amsterdam Institute for Infection and Immunity, Amsterdam UMC, Amsterdam, The Netherlands

   Department of Epidemiology & Data Science, Amsterdam UMC location VUMC, Amsterdam, The Netherlands