Predicting Microbiome Metabolism and Interactions through Integrating Multidisciplinary Principles

Caleb M Schmidt; Parsa Ghadermazi; Siu Hung Joshua Chan

doi:10.1128/mSystems.00768-21

Predicting Microbiome Metabolism and Interactions through Integrating Multidisciplinary Principles

mSystems. 2021 Oct 26;6(5):e0076821. doi: 10.1128/mSystems.00768-21. Epub 2021 Oct 5.

Authors

Caleb M Schmidt^{1

2}, Parsa Ghadermazi³, Siu Hung Joshua Chan³

Affiliations

¹ Advanced Pattern Analysis & Countermeasures Group, Boulder, Colorado, USA.
² Department of Systems Engineering, Colorado State University, Fort Collins, Colorado, USA.
³ Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, Colorado, USA.

Abstract

In this Commentary, we will discuss some of the current trends and challenges in modeling microbiome metabolism. A focus will be the state of the art in the integration of metabolic networks, ecological and evolutionary principles, and spatiotemporal considerations, followed by envisioning integrated frameworks incorporating different principles and data to generate predictive models in the future.

Keywords: metabolic modeling; microbial communities; microbiome.