Ecological dynamics imposes fundamental challenges in community‐based microbial source tracking

Author:

Wang Xu‐Wen1ORCID,Wu Lu2,Dai Lei23ORCID,Yin Xiaole4,Zhang Tong4,Weiss Scott T.1,Liu Yang‐Yu15ORCID

Affiliation:

1. Channing Division of Network Medicine, Department of Medicine Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA

2. CAS Key Laboratory of Quantitative Engineering Biology Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen China

3. University of Chinese Academy of Sciences Beijing China

4. Environmental Microbiome Engineering and Biotechnology Laboratory, Department of Civil Engineering The University of Hong Kong Hong Kong China

5. Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology University of Illinois at Urbana‐Champaign Urbana Illinois USA

Abstract

AbstractQuantifying the contributions of possible environmental sources (“sources”) to a specific microbial community (“sink”) is a classical problem in microbiology known as microbial source tracking (MST). Solving the MST problem will not only help us understand how microbial communities were formed, but also have far‐reaching applications in pollution control, public health, and forensics. MST methods generally fall into two categories: target‐based methods (focusing on the detection of source‐specific indicator species or chemicals); and community‐based methods (using community structure to measure similarity between sink samples and potential source environments). As next‐generation sequencing becomes a standard community‐assessment method in microbiology, numerous community‐based computational methods, referred to as MST solvers hereafter have been developed and applied to various real datasets to demonstrate their utility across different contexts. Yet, those MST solvers do not consider microbial interactions and priority effects in microbial communities. Here, we revisit the performance of several representative MST solvers. We show compelling evidence that solving the MST problem using existing MST solvers is impractical when ecological dynamics plays a role in community assembly. In particular, we clearly demonstrate that the presence of either microbial interactions or priority effects will render the MST problem mathematically unsolvable for MST solvers. We further analyze data from fecal microbiota transplantation studies, finding that the state‐of‐the‐art MST solvers fail to identify donors for most of the recipients. Finally, we perform community coalescence experiments to demonstrate that the state‐of‐the‐art MST solvers fail to identify the sources for most of the sinks. Our findings suggest that ecological dynamics imposes fundamental challenges in MST. Interpretation of results of existing MST solvers should be done cautiously.

Publisher

Wiley

Subject

Microbiology,Biotechnology

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