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Ecological Dynamics Imposes Fundamental Challenges in Microbial Source Tracking

Xu-Wen Wang, Lu Wu, View ORCID ProfileLei Dai, Xiaole Yin, Tong Zhang, Scott T. Weiss, View ORCID ProfileYang-Yu Liu
doi: https://doi.org/10.1101/2022.05.21.492809
Xu-Wen Wang
1Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA
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Lu Wu
2CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen 518055, China
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Lei Dai
2CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen 518055, China
3University of Chinese Academy of Sciences, Beijing 100049, China
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Xiaole Yin
4Environmental Microbiome Engineering and Biotechnology Laboratory, Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
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Tong Zhang
4Environmental Microbiome Engineering and Biotechnology Laboratory, Department of Civil Engineering, The University of Hong Kong, Hong Kong, China
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Scott T. Weiss
1Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA
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Yang-Yu Liu
1Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, 02115, USA
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  • For correspondence: yyl@channing.harvard.edu
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ABSTRACT

Quantifying 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. Numerous computational methods, referred to as MST solvers hereafter, have been developed in the past 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 any MST solver. 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 solving the MST problem using computational approaches.

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. All rights reserved. No reuse allowed without permission.
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Posted May 21, 2022.
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Ecological Dynamics Imposes Fundamental Challenges in Microbial Source Tracking
Xu-Wen Wang, Lu Wu, Lei Dai, Xiaole Yin, Tong Zhang, Scott T. Weiss, Yang-Yu Liu
bioRxiv 2022.05.21.492809; doi: https://doi.org/10.1101/2022.05.21.492809
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Ecological Dynamics Imposes Fundamental Challenges in Microbial Source Tracking
Xu-Wen Wang, Lu Wu, Lei Dai, Xiaole Yin, Tong Zhang, Scott T. Weiss, Yang-Yu Liu
bioRxiv 2022.05.21.492809; doi: https://doi.org/10.1101/2022.05.21.492809

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