title: The JBEI quantitative metabolic modeling library (jQMM): a python library for modeling microbial metabolism.
abstract: BACKGROUND
  Modeling of microbial metabolism is a topic of growing importance in biotechnology. Mathematical modeling helps provide a mechanistic understanding for the studied process, separating the main drivers from the circumstantial ones, bounding the outcomes of experiments and guiding engineering approaches. Among different modeling schemes, the quantification of intracellular metabolic fluxes (i.e. the rate of each reaction in cellular metabolism) is of particular interest for metabolic engineering because it describes how carbon and energy flow throughout the cell. In addition to flux analysis, new methods for the effective use of the ever more readily available and abundant -omics data (i.e. transcriptomics, proteomics and metabolomics) are urgently needed.
  
  
  RESULTS
  The jQMM library presented here provides an open-source, Python-based framework for modeling internal metabolic fluxes and leveraging other -omics data for the scientific study of cellular metabolism and bioengineering purposes. Firstly, it presents a complete toolbox for simultaneously performing two different types of flux analysis that are typically disjoint: Flux Balance Analysis and13C Metabolic Flux Analysis. Moreover, it introduces the capability to use13C labeling experimental data to constrain comprehensive genome-scale models through a technique called two-scale13C Metabolic Flux Analysis (2S-13C MFA). In addition, the library includes a demonstration of a method that uses proteomics data to produce actionable insights to increase biofuel production. Finally, the use of the jQMM library is illustrated through the addition of several Jupyter notebook demonstration files that enhance reproducibility and provide the capability to be adapted to the user's specific needs.
  
  
  CONCLUSIONS
  jQMM will facilitate the design and metabolic engineering of organisms for biofuels and other chemicals, as well as investigations of cellular metabolism and leveraging -omics data. As an open source software project, we hope it will attract additions from the community and grow with the rapidly changing field of metabolic engineering.
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.|DOE Agile BioFoundry, Emeryville, CA, USA.
authors.forename: Garrett W
authors.initials: GW
authors.lastname: Birkel
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.|School of Energy Science and Engineering, Indian Institute of Technology (IIT), Kharagpur, India.
authors.forename: Amit
authors.initials: A
authors.lastname: Ghosh
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.
authors.forename: Vinay S
authors.initials: VS
authors.lastname: Kumar
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Weaver
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.
authors.forename: David
authors.initials: D
authors.lastname: Ando
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.|DOE Agile BioFoundry, Emeryville, CA, USA.
authors.forename: Tyler W H
authors.initials: TWH
authors.lastname: Backman
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Department of Bioengineering, University of California, Berkeley, CA, USA.|Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
authors.forename: Adam P
authors.initials: AP
authors.lastname: Arkin
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.|Joint BioEnergy Institute, Emeryville, CA, USA.|Department of Chemical and Biomolecular Engineering, University of California, Berkeley, CA, USA.|Department of Bioengineering, University of California, Berkeley, CA, USA.|Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, DK2970, Denmark.
authors.forename: Jay D
authors.initials: JD
authors.lastname: Keasling
authors.affiliation: Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. hgmartin@lbl.gov.|Joint BioEnergy Institute, Emeryville, CA, USA. hgmartin@lbl.gov.|DOE Agile BioFoundry, Emeryville, CA, USA. hgmartin@lbl.gov.|BCAM, Basque Center for Applied Mathematics, Bilbao, Spain. hgmartin@lbl.gov.
authors.forename: Héctor García
authors.identifier: http://orcid.org/0000-0002-4556-9685
authors.initials: HG
authors.lastname: Martín
mesh_terms: D056804:Biofuels; D002247:Carbon Isotopes / Q000737:chemistry; D004926:Escherichia coli / Q000378:metabolism; D020407:Internet; D064688:Metabolic Flux Analysis / Q000379:methods; D055432:Metabolomics; D008954:Models, Biological; D025341:Principal Component Analysis; D040901:Proteomics; D014584:User-Computer Interface
chemical_list: D056804:Biofuels; D002247:Carbon Isotopes
keywords: -omics data; 13 C Metabolic Flux Analysis; Flux analysis; Predictive biology