1. Microbiology and Infectious Disease
  2. Physics of Living Systems
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Gut bacterial aggregates as living gels

  1. Brandon H Schlomann
  2. Raghuveer Parthasarathy  Is a corresponding author
  1. University of Oregon, United States
Research Article
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Cite this article as: eLife 2021;10:e71105 doi: 10.7554/eLife.71105

Abstract

The spatial organization of gut microbiota influences both microbial abundances and host-microbe interactions, but the underlying rules relating bacterial dynamics to large-scale structure remain unclear. To this end we studied experimentally and theoretically the formation of three-dimensional bacterial clusters, a key parameter controlling susceptibility to intestinal transport and access to the epithelium. Inspired by models of structure formation in soft materials, we sought to understand how the distribution of gut bacterial cluster sizes emerges from bacterial-scale kinetics. Analyzing imaging-derived data on cluster sizes for eight different bacterial strains in the larval zebrafish gut, we find a common family of size distributions that decay approximately as power laws with exponents close to -2, becoming shallower for large clusters in a strain-dependent manner. We show that this type of distribution arises naturally from a Yule-Simons-type process in which bacteria grow within clusters and can escape from them, coupled to an aggregation process that tends to condense the system toward a single massive cluster, reminiscent of gel formation. Together, these results point to the existence of general, biophysical principles governing the spatial organization of the gut microbiome that may be useful for inferring fast-timescale dynamics that are experimentally inaccessible.

Data availability

A table of all bacterial cluster sizes analysed in this study is included in the Supplementary Data File. MATLAB code for simulating the models described in the study is available at https://github.com/rplab/cluster_kinetics

The following previously published data sets were used

Article and author information

Author details

  1. Brandon H Schlomann

    University of Oregon, Eugene, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Raghuveer Parthasarathy

    University of Oregon, Eugene, United States
    For correspondence
    raghu@uoregon.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6006-4749

Funding

National Institutes of Health (P50GM09891)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

National Institutes of Health (P01GM125576)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

National Institutes of Health (F32AI112094)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

National Institutes of Health (T32GM007759)

  • Raghuveer Parthasarathy

National Science Foundation (1427957)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

James S. McDonnell Foundation

  • Brandon H Schlomann

Kavli Foundation (Kavli Microbiome Ideas Challenge)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

National Institutes of Health (P01HD22486)

  • Brandon H Schlomann
  • Raghuveer Parthasarathy

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: The studies that generated the data analyzed in this paper (see cited references) were done in strict accordance with protocols approved by the University of Oregon Institutional Animal Care and Use Committee and following standard protocols.

Reviewing Editor

  1. Kevin B Wood, University of Michigan, United States

Publication history

  1. Preprint posted: June 8, 2021 (view preprint)
  2. Received: June 9, 2021
  3. Accepted: September 6, 2021
  4. Accepted Manuscript published: September 7, 2021 (version 1)
  5. Version of Record published: October 13, 2021 (version 2)

Copyright

© 2021, Schlomann & Parthasarathy

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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Further reading

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    Background:

    Early identification of severe dengue patients is important regarding patient management and resource allocation. We investigated the association of 10 biomarkers (VCAM-1, SDC-1, Ang-2, IL-8, IP-10, IL-1RA, sCD163, sTREM-1, ferritin, CRP) with the development of severe/moderate dengue (S/MD).

    Methods:

    We performed a nested case-control study from a multi-country study. A total of 281 S/MD and 556 uncomplicated dengue cases were included.

    Results:

    On days 1–3 from symptom onset, higher levels of any biomarker increased the risk of developing S/MD. When assessing together, SDC-1 and IL-1RA were stable, while IP-10 changed the association from positive to negative; others showed weaker associations. The best combinations associated with S/MD comprised IL-1RA, Ang-2, IL-8, ferritin, IP-10, and SDC-1 for children, and SDC-1, IL-8, ferritin, sTREM-1, IL-1RA, IP-10, and sCD163 for adults.

    Conclusions:

    Our findings assist the development of biomarker panels for clinical use and could improve triage and risk prediction in dengue patients.

    Funding:

    This study was supported by the EU's Seventh Framework Programme (FP7-281803 IDAMS), the WHO, and the Bill and Melinda Gates Foundation.

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