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Published March 3, 2020 | Submitted + Supplemental Material
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Metabolic multi-stability and hysteresis in a model aerobe-anaerobe microbiome community

Abstract

Changes in the composition of the human microbiome are associated with health and disease. Some microbiome states persist in seemingly unfavorable conditions, e.g., the proliferation of aerobe-anaerobe communities in oxygen-exposed environments in wounds or small intestinal bacterial overgrowth. However, it remains unclear how different stable microbiome states can exist under the same conditions, or why some states persist under seemingly unfavorable conditions. Here, using two microbes relevant to the human microbiome, we combine genome-scale mathematical modeling, bioreactor experiments, transcriptomics, and dynamical systems theory, to show that multi-stability and hysteresis (MSH) is a mechanism that can describe the shift from an aerobe-dominated state to a resilient, paradoxically persistent aerobe-anaerobe state. We examine the impact of changing oxygen and nutrient regimes and identify factors, including changes in metabolism and gene expression, that lead to MSH. When analyzing the transitions between the two states in this system, the familiar conceptual connection between causation and correlation is broken and MSH must be used to interpret the dynamics. Using MSH to analyze microbiome dynamics will improve our conceptual understanding of the stability of microbiome states and the transitions among microbiome states.

Additional Information

The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Posted February 29, 2020. We thank Jens Nielsen (Chalmers University of Technology), Richard Murray (Caltech), Jared Leadbetter (Caltech), and Elaine Hsiao (UCLA) for helpful discussions. We thank Roberta Poceviciute (Caltech) for imaging samples, Kevin Winzey (Caltech) for performing digital PCR analysis of samples, and Natasha Shelby for contributions to writing and editing this manuscript. This work was supported in part by Army Research Office (ARO) MURI contract #W911NF-17-1-0402, NSF Emerging Frontiers in Research and Innovation (EFRI) Grant 1137089A, NSERC fellowship PGSD3-438474-2013 [to T.K.], and the Center for Environmental Microbial Interactions (CEMI). This work was also supported by the Millard & Muriel Jacobs Genetics and Genomics Laboratory at Caltech and we thank director Igor Antoshechkin for his assistance. Author contributions: T.K., S.R.B., J.C.D. C.S.H., and R.F.I conceptualized the study. T.K., C.S.H. and R.F.I. contributed to the computational investigation. T.K., R.L.W., and R.F.I. contributed to the experimental investigation. T.K. wrote the manuscript and all authors contributed to the final submission of the manuscript. Authors declare no competing interest. Data and materials availability: All associated raw sequencing data have been deposited in the Sequence Read Archive (Bio-Project Accession Number PRJNA580293). All other data will be made publicly available upon publication at CaltechDATA.

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Submitted - 2020.02.28.968941v1.full.pdf

Supplemental Material - media-1.pdf

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Created:
August 19, 2023
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