June 10, 2021
Research Highlight

Using Computation to Design Better Microbes

New quantum chemistry pipeline can help predict the effects of bioengineering

ACS Omega Cover Art

CompMol_Thermo can be used to predict changes in cell metabolism for engineered systems.

(Illustration by Nathan Johnson | Pacific Northwest National Laboratory)

The Science                                

A bacterial cell contains over a thousand different enzymes, each catalyzing a biochemical reaction, such as converting food into energy or synthesizing amino acids. Each reaction requires or produces a certain amount of energy, which can be quantified by thermodynamics. When scientists engineer bacteria to contain new enzymes and catalyze new reactions, the thermodynamics of other reaction pathways may be affected. A new computational pipeline, developed by a multi-institutional team, can help accelerate bioengineering by predicting how changes introduced into microbes could influence the energy balances in cell metabolism.

The Impact

Microbial engineering, whether to produce next-generation biofuels or increase crop yields, typically requires many trial-and-error steps in the laboratory. Researchers could use this user-friendly pipeline to design a microbe in silico and calculate the effects of their intended engineering. The results could be used to identify which changes are most likely to yield a successful outcome, essentially reducing months of laboratory benchwork into hours of computation.


A team of researchers from Pacific Northwest National Laboratory, Argonne National Laboratory, and Lawrence Berkeley National Laboratory built an automated software pipeline capable of calculating the energetics of biochemical reactions. This marks the first time a computational system has been able to replicate experimental thermodynamic values within the experimental error range.

The pipeline, called CompMol_Thermo, unites software developed over several decades at the three national laboratories. It makes doing thermodynamic calculations more user-friendly by providing an automated system that connects the various platforms.

First, CompMol_Thermo takes inputs from the ModelSEED database, a biochemistry and modeling database spearheaded by scientists at Argonne National Laboratory. Then, it processes the information with quantum chemical and molecular dynamics calculations using NWChem, an ab initio computational chemistry software developed at the Environmental Molecular Sciences Laboratory, a U.S. Department of Energy (DOE) Office of Science user facility at the Pacific Northwest National Laboratory. Finally, the output from NWChem feeds back into ModelSEED to build a quantum biochemistry reaction database for metabolic modeling and microbial engineering. The entire CompMol_Thermo pipeline and user narrative are available online through KBase, the DOE Systems Biology Knowledgebase. KBase is a multi-institutional team led by scientists at Lawrence Berkeley National Laboratory.


Neeraj Kumar
Pacific Northwest National Laboratory

Lee Ann McCue
Pacific Northwest National Laboratory


The work reported here was supported by the Intramural program at the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program. Additional support was provided by the Laboratory Directed Research and Development Program at Pacific Northwest National Laboratory.

Published: June 10, 2021

R.P. Joshi, et al., “Quantum Mechanical Methods Predict Accurate Thermodynamics of Biochemical Reactions,” ACS Omega 6, 9948-9959 (2021). [DOI: 10.1021/acsomega.1c00997]