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Functional Anabolic Network Analysis of Human-associated Lactobacillus Strains

Thomas J. Moutinho Jr., Benjamin C. Neubert, Matthew L. Jenior, Maureen A. Carey, Gregory L. Medlock, Glynis L. Kolling, View ORCID ProfileJason A. Papin
doi: https://doi.org/10.1101/746420
Thomas J. Moutinho Jr.
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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Benjamin C. Neubert
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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Matthew L. Jenior
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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Maureen A. Carey
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
bDivision of Infectious Disease and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA
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Gregory L. Medlock
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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Glynis L. Kolling
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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Jason A. Papin
aDepartment of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA
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  • ORCID record for Jason A. Papin
  • For correspondence: papin@virginia.edu
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Abstract

Members of the Lactobacillus genus are frequently utilized in the probiotic industry with many species conferring demonstrated health benefits; however, these effects are largely strain-dependent. We designed a method called PROTEAN (Probabilistic Reconstruction Of constituent Anabolic Networks) to computationally analyze the genomic annotations and predicted metabolic production capabilities of 144 strains across 16 species of Lactobacillus isolated from human intestinal, oral, and vaginal body sites. Using PROTEAN we conducted a genome-scale metabolic network comparison between strains, revealing that metabolic capabilities differ by isolation site. Notably, PROTEAN does not require a well-curated genome-scale metabolic network reconstruction to provide biological insights. We found that predicted metabolic capabilities of lactobacilli isolated from the vaginal microbiota cluster separately from intestinal and oral isolates, and we also uncovered an overlap in the predicted metabolic production capabilities of intestinal and oral isolates. Using machine learning, we determined the most informative metabolic products driving the difference between predicted metabolic capabilities of intestinal, oral, and vaginal isolates. Notably, intestinal and oral isolates were predicted to have a higher likelihood of producing D-alanine, D/L-serine, and L-proline, while the vaginal isolates were distinguished by a higher predicted likelihood of producing L-arginine, citrulline, and D/L-lactate. We found the distinguishing products to be consistent with published experimental literature. This study showcases a systematic technique, PROTEAN, for comparing the predicted functional metabolic output of microbes using genome-scale metabolic network analysis and computational modeling and provides unique insight into human-associated Lactobacillus biology.

Importance The Lactobacillus genus has been shown to be important for human health. Lactobacilli have been isolated from human intestinal, oral, and vaginal sites. Members of the genus contribute significantly to the maintenance of vaginal health by providing colonization resistance to invading pathogens. A wide variety of clinical studies have indicated that Lactobacillus-based probiotics confer health benefits for several gut- and immune-associated diseases. Microbes interact with the human body in several ways, including the production of metabolites that influence physiology or other surrounding microbes. We have conducted a strain-level genome-scale metabolic network reconstruction analysis of human-associated Lactobacillus strains, revealing that predicted metabolic capabilities differ when comparing intestinal/oral isolate to vaginal isolates. The technique we present here allows for direct interpretation of discriminating features between the experimental groups.

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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-ND 4.0 International license.
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Posted August 24, 2019.
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Functional Anabolic Network Analysis of Human-associated Lactobacillus Strains
Thomas J. Moutinho Jr., Benjamin C. Neubert, Matthew L. Jenior, Maureen A. Carey, Gregory L. Medlock, Glynis L. Kolling, Jason A. Papin
bioRxiv 746420; doi: https://doi.org/10.1101/746420
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Functional Anabolic Network Analysis of Human-associated Lactobacillus Strains
Thomas J. Moutinho Jr., Benjamin C. Neubert, Matthew L. Jenior, Maureen A. Carey, Gregory L. Medlock, Glynis L. Kolling, Jason A. Papin
bioRxiv 746420; doi: https://doi.org/10.1101/746420

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