Evidence map›Paper›PMID 38868341›Full record

ArticleiMeta2023

Ecological dynamics imposes fundamental challenges in community-based microbial source tracking.

Xu-Wen Wang, Lu Wu, Lei Dai, Xiaole Yin, Tong Zhang, Scott T Weiss, Yang-Yu Liu

Erratum issuedAbstract read
In one paragraph

Article in iMeta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Trial
  2. Article
  3. Microbial community assembly in the fermentation of cigar tobacco leaves.Frontiers in bioengineering and biotechnology · 2026
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Xu-Wen WangChanning Division of Network Medicine, Department of Medicine Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA.ORCID 0000-0001-7670-3544
Lu WuCAS Key Laboratory of Quantitative Engineering Biology Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen China.
Lei DaiCAS Key Laboratory of Quantitative Engineering Biology Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen China.ORCID 0000-0002-5598-5308
Xiaole YinEnvironmental Microbiome Engineering and Biotechnology Laboratory, Department of Civil Engineering The University of Hong Kong Hong Kong China.
Tong ZhangEnvironmental Microbiome Engineering and Biotechnology Laboratory, Department of Civil Engineering The University of Hong Kong Hong Kong China.
Scott T WeissChanning Division of Network Medicine, Department of Medicine Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA.
Yang-Yu LiuChanning Division of Network Medicine, Department of Medicine Brigham and Women's Hospital and Harvard Medical School Boston Massachusetts USA.ORCID 0000-0003-2728-4907

Funding

Therapeutic Control of Aspirin-Exacerbated Respiratory DiseaseU19AI095219 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI Nora Amanda Barrett · 2011 to 2026
$29.1M
Genetic Epidemiology of COPDU01HL089856 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI SILVERMAN, EDWIN K · 2007 to 2021
$20.7M
Multi-omic approaches to mechanisms of vitamin D, environmental influences, and the microbiome on asthmaUH3OD023268 · OD · BRIGHAM AND WOMEN'S HOSPITAL · PI LITONJUA, AUGUSTO A, WEISS, SCOTT T · 2018 to 2022
$13.5M
Prospective Study of the Gut Microbiome in AgingRF1AG067744 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI CHAN, ANDREW T · 2020 to 2020
$11.7M
Functional Redundancy of Human Microbiome and its Implication in Fecal Microbiota TransplantationR01AI141529 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI LIU, YANG-YU · 2019 to 2023
$4.5M
Long-term health consequences of birth by cesarean sectionR01HD093761 · NICHD · HARVARD SCHOOL OF PUBLIC HEALTH · PI CHAVARRO, JORGE EDUARDO · 2018 to 2022
$3.3M
NHLBI NIH HHS U01 HL089856NIAID NIH HHS R01 AI141529NIAID NIH HHS U19 AI095219NIA NIH HHS RF1 AG067744NICHD NIH HHS R01 HD093761NIH HHS UH3 OD023268
6 · The paper itself

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. 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.

Indexed as

microbial interactionsmicrobial source trackingpriority effects

Identifiers

PMID38868341
PMCPMC10989786

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.