The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

Abstract

13 C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. 13 C MFA, however, stands out from other “-omics sciences,” in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying 13 C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of 13 C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an “all-around carefree package” for 13 C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of 13 C MFA.

Intracellular Mycobacterium tuberculosis Exploits Multiple Host Nitrogen Sources during Growth in Human Macrophages

“…In total, the model has 98 independent fluxes, from which 50 are intracellular (40 net, 10 exchange) and 48 nuisance fluxes for modeling the deconvolution of the substrate species. This nitrogen transition template model was then duplicated per dataset to give rise to a sextuple model (Beyß et al., 2019), where each sub-model shared flux values, biomass requirements, and growth rate. Eventually, the sextuple model had 338 free fluxes (50 intracellular and 288 nuisance fluxes) that had to be inferred from 264 independent labeling measurements (15 measurement groups for Mtb and the host, respectively (Data S2; Figure S4).…”

mfapy: An open-source Python package for 13C-based metabolic flux analysis

“…mfapy has been continuously developed to enrich functions, such as loading various model definition formats and data visualization ( Beyss et al, 2019 ). New versions will be available to the public from the Github repository.…”

Revisiting the Growth Modulon of Corynebacterium glutamicum Under Glucose Limited Chemostat Conditions

“…The metabolic network model of C. glutamicum WT was taken from Kappelmann et al (2016) and slightly modified for experimental design and flux fitting (see Supplementary Material section “ 13 C-MFA”). The models were composed according to the workflow described in Nöh et al (2015) and formulated in FluxML format ( Beyß et al, 2019 ). The models contain the major pathways of central carbon metabolism such as glycolysis, pentose phosphate pathway (PPP), anaplerotic reactions, tricarboxylic acid (TCA) cycle, and all pathways for amino acid synthesis.…”