BioinformaticsBioinformaticsPeer-reviewed journal article
ORT: A workflow linking genome-scale metabolic models with reactive transport codes
Rebecca L. RubinsteiniD, Mikayla BortoniD, Haiyan ZhouiD, Michael ShafferiD, David W HoytiD, James StegeniD, Christopher S. HenryiD, Kelly C. WrightoniD, Roelof Jan VersteegiD
Abstract
MotivationNutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. ResultsWe propose a workflow ( Omics to Reactive Transport - ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBASE and PFLOTRAN. Availability and ImplementationInteractive models available at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available at https://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available at https://narrative.kbase.us/narrative/71260 or static narrative (no login required) at https://kbase.us/n/71260/258 Contactrebecca.rubinstein@subsurfaceinsights.com or roelof.versteeg@subsurfaceinsights.com Supplementary informationSupplementary data are available online.
- assay: metagenomics
- research focus: benchmarking
- research focus: database / resource
- research focus: software / tool
- approach: experimental assay
- Citations
- 5
- FWCI
- 0.16
- Field percentile
- 43th percentile
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- METABOLIC: High-throughput profiling of microbial genomes for functional traits, biogeochemistry, and community-scale metabolic networks
Zhichao Zhou, Patricia Q. Tran, … Karthik Anantharaman·MicrobiomePeer-reviewed·Feb 16, 2022
- Planetary-scale heterotrophic microbial community modeling assesses metabolic synergy and viral impacts
Antoine Régimbeau, Funing Tian, … Damien Eveillard·bioRxiv·Feb 13, 2025
- Comparative Analysis of Denitrification and Other Nitrogen Cycle Genes in Diverse Environmental Microbiomes
Andrew M. Pilat, Rachael E. Tomasko, … Joan L. Slonczewski·bioRxiv·Aug 10, 2025
- Global pattern of nitrogen metabolism in marine prokaryotes
Alexandre Schickele, Hadrien Savioz, … Meike Vogt·bioRxiv·Oct 28, 2025
- MICOMWeb: a website for microbial community metabolic modeling of the human gut
Cristóbal Fresno, Juan José Oropeza-Valdez, … Osbaldo Reséndis-Antonio·Gut MicrobesPeer-reviewed·Dec 2, 2025
- Genome-scale metabolic models reveal phylogenetic conservation of amino acid fermentation-linked metabolic traits in soil bacteria
Young C Song, Christian O Ayala-Ortiz, … Emily B. Graham·bioRxiv·Nov 4, 2026