Computing Metabolic Routes in the Human Microbiome

Abstract

ObjectiveDevelop a computational tool for computing metabolic transformations across multiple organisms within the human microbiome.BackgroundThe complexity of microbiomes and their metabolic networks makes it hard to understand their collective biochemical capabilities. We are enabling computational insights in the context of BioCyc.org, an extensive web portal for microbial genomics and metabolic pathways. BioCyc contains 11,000 microbial genomes including 929 organisms from the Human Microbiome Project. Two BioCyc databases are noteworthy as bacterial references: the EcoCyc database for Escherichia coli has been curated from 33,000 publications, and the BsubCyc database for Bacillus subtilis has been curated from 4,000 publications. BioCyc contains an extensive set of bioinformatics tools. Genome‐related tools include a genome browser, sequence searching and alignment, and extraction of sequence regions. Pathway‐related tools include a tool for navigating zoomable organism‐specific metabolic map diagrams that can be painted with metabolomics and gene‐expression data.Results ObtainedThe new BioCyc Multi‐Organism (metabolic) Route Search (MORS) tool enables the user to explore biochemical conversions among metabolites that are accomplished by multiple microbiome organisms. To specify a route search problem the user provides a starting and an ending metabolite of interest, and a set of organisms that provides the reactions.As the endpoint for one example route, we picked indoxyl sulfate, because it is implicated in toxicity among patients with kidney disease. We selected L‐tryptophan as a starting point because it is the known source of a microbial route to indoxyl sulfate. MORS found a known [1] route of 3 reaction steps, retaining 9 atoms from start to end. The first reaction can be catalyzed by 164 different microbes, whereas the last two reactions are catalyzed by Homo sapiens only. A second route of 9 reactions is also found, retaining 7 atoms. Although this route appears biochemically possible, it looks less plausible because the the required reactions are contributed from a larger set of organisms.For another example route, we wanted to see how microbes might be linked by autoinducers, which are compounds involved in quorum sensing. The start was S‐adenosyl‐L‐methionine, the known source for some autoinducers. As the end, we picked L‐homoserine lactone, which is a degradation product common to a class of autoinducers. We find several related routes, which all have two reactions, retaining 7 atoms. The differences between the routes are that the actual autoinducers are different, which are the products of the first reaction.MethodsThe MORS tool computes a set of optimal routes connecting the starting and ending compounds. Each route is a linear sequence of reactions that converts the starting compound to the ending compound. An optimal route minimizes the number of reactions used while maximizing the number of atoms from the starting compound that are incorporated into the ending compound. The set of reactions from which the routes are computed is the union of all reactions in the metabolic networks of the selected organisms ‐‐ all reactions in those organisms are assumed to be accessible, independent of transport considerations.ConclusionsThe MORS tool will be available in the Spring 2018 release of the BioCyc website.Support or Funding InformationThis work was funded by the National Institute of General Medical Sciences of the National Institutes of Health under Award Number GM080746 to P.D.K. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.