- Open Access
WUFlux: an open-source platform for 13C metabolic flux analysis of bacterial metabolism
© The Author(s). 2016
- Received: 10 January 2016
- Accepted: 26 October 2016
- Published: 4 November 2016
Flux analyses, including flux balance analysis (FBA) and 13C-metabolic flux analysis (13C-MFA), offer direct insights into cell metabolism, and have been widely used to characterize model and non-model microbial species. Nonetheless, constructing the 13C-MFA model and performing flux calculation are demanding for new learners, because they require knowledge of metabolic networks, carbon transitions, and computer programming. To facilitate and standardize the 13C-MFA modeling work, we set out to publish a user-friendly and programming-free platform (WUFlux) for flux calculations in MATLAB®.
We constructed an open-source platform for steady-state 13C-MFA. Using GUIDE (graphical user interface design environment) in MATLAB, we built a user interface that allows users to modify models based on their own experimental conditions. WUFlux is capable of directly correcting mass spectrum data of TBDMS (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide)-derivatized proteinogenic amino acids by removing background noise. To simplify 13C-MFA of different prokaryotic species, the software provides several metabolic network templates, including those for chemoheterotrophic bacteria and mixotrophic cyanobacteria. Users can modify the network and constraints, and then analyze the microbial carbon and energy metabolisms of various carbon substrates (e.g., glucose, pyruvate/lactate, acetate, xylose, and glycerol). WUFlux also offers several ways of visualizing the flux results with respect to the constructed network. To validate our model’s applicability, we have compared and discussed the flux results obtained from WUFlux and other MFA software. We have also illustrated how model constraints of cofactor and ATP balances influence fluxome results.
Open-source software for 13C-MFA, WUFlux, with a user-friendly interface and easy-to-modify templates, is now available at http://www.13cmfa.org/or (http://tang.eece.wustl.edu/ToolDevelopment.htm). We will continue documenting curated models of non-model microbial species and improving WUFlux performance.
- 13C metabolic flux analysis
- Energy metabolism
Metabolic flux analyses, including flux balance analysis (FBA) and 13C metabolic flux analysis (MFA), are widely used to predict or measure in vivo enzyme reaction rates in microbes. FBA can unravel microbial metabolism based on the stoichiometry of the metabolic reactions as well as measurements of the inflow (substrate uptake) and outflow fluxes (biomass and product synthesis). To facilitate the development of genome scale models, much software has been developed . Our research group built a web-based platform named MicrobesFlux (http://www.microbesflux.org/) . This platform can automatically draft a metabolic model from the annotated microbial genome in the KEGG database. Based on users’ feedback, we have re-built our system on a commercial server to improve its functionality, stability, and robustness. The new MicrobesFlux has been updated with both AMPL optimization software and metabolic network information from the latest version of the KEGG database. This platform now includes 3192 species compared to 1304 species in the previous version. Nevertheless, the MicrobesFlux platform still performs only FBA to estimate the flux values. A more rigorous flux analysis requires 13C-MFA, which combines FBA with 13C isotopic tracing. To complement the current platform, we sought to build an open-source MATLAB-based package (WUFlux) for metabolic flux analysis.
To reduce modeling challenges, mass spectrum (MS) data correction tools and 13C-MFA software have been developed, including FiatFlux , iMS2Flux , INCA , METRAN , OpenFLUX , OpenMebius , 13CFLUX  and 13CFLUX2 . Using these tools and software, researchers can decipher metabolisms of bacterial, plant, and mammalian cells. Our laboratory has also been using 13C-MFA extensively to study both model and non-model bacterial species. Based on our experiences, we set out to build an open-source 13C-MFA platform (WUFlux) to facilitate analysis of metabolisms in diverse microbes. To reduce the work of constructing flux models, we provide several model templates with predefined metabolic network and carbon atom mappings. As a result, WUFlux can minimize the work done by users and facilitate straightforward flux analysis. Using this platform, we can also standardize and disseminate our MFA work by depositing curated models and flux results into the WUFlux database, which will further benefit the development of fluxomic databases for investigating diverse microbial species [13, 14].
We chose MATLAB as the programming environment, because it is broadly used by engineers and scientists in both industry and academia. We began with designing a graphical user interface by using GUIDE in MATLAB, and subsequently we created functions directly linked to tables, buttons, pop-up menus, and figures on the user interface.
Constructing a 13C MFA model in WUFlux starts with defining the metabolic reactions in the ‘Metabolic Reactions’ section. Instead of asking users to design the metabolic network and carbon transitions from scratch, we have included multiple templates which are suitable for studying chemoheterotrophic (e.g., E. coli, Shewanella oneidensis, and Bacillus subtilis), photomixotrophic cyanobacteria (e.g., Synechocystissp. PCC6803), and vanillin-degrading bacteria (e.g., Sphingobium SYK-6) [15–17]. Users can select an appropriate template, and easily make modifications to fine-tune the metabolic network, for example, by knocking out reactions, changing boundary conditions, and adding outflow fluxes.
The ‘Settings’ section allows users to customize the optimization parameters (e.g., the number of initial guesses and maximum iteration number). Thereafter, the flux calculation is ready to start. To determine the fluxome, we used the element metabolite unit algorithm  to simulate the MIDs of proteinogenic amino acids or free metabolites. This method largely reduces the number of variables compared to the traditional isotopomer mapping matrices approach . The built-in MATLAB function ‘fmincon’ is employed for non-linear optimization, i.e., using ‘interior-point’ as the default algorithm, fmincon minimizes the differences between experimentally and computationally determined data weighted by measured variances. To avoid local solutions, users need to run different initial guesses of fluxes, so that fmincon can find the global optimal solution with the least SSR (sum of squared residuals) (Fig. 2).
The Monte Carlo method is used in the model to determine the confidence intervals of central metabolic fluxes. Briefly speaking, MID data are randomly perturbed with normally distributed noises (within the average range of measurement errors), and the flux profile is then recalculated multiple times, which is customizable in WUFlux. The 95 % confidence intervals, for example, are consequently determined by the upper and lower 2.5 % data via the bootstrap method. Additionally, the χ 2 test is applied to determine the goodness of fit, which users can use as the reference to determine whether the fitting is statistically acceptable.
Finally, all the flux values and confidence intervals are presented in the ‘Results’ panel, which can be exported to an Excel file. To better present the results, we have included functions that provide direct ways of visualizing the computed fluxes with respect to the constructed metabolic network and visualizing the comparisons between simulated and experimental MID data (see Additional file 1).
Figure 2 shows the general procedures for performing 13C-MFA with WUFlux: 1) Choose a suitable template, 2) Modify the metabolic network and constraints, 3) Import the experimental data, 4) Customize the optimization parameters, 5) Estimate the flux distribution and determine the confidence intervals, and 6) Visualize the fluxes. More detailed information is provided in Additional file 1.
13C-MFA is a powerful tool for metabolism analysis, but the overall process of performing 13C-MFA is usually not fast enough for biologists to characterize novel microbial species or to provide timely insights into engineered strains in the design-build-test-learn cycle. To overcome this problem, we have designed an open-source MATLAB-based platform, WUFlux, which provides programming-free and straightforward ways of performing 13C-MFA. By testing WUFlux against the other software, we showed that WUFlux can correct raw MS data and reproduce the flux estimation of previously published flux analysis studies. Because the MATLAB codes of all function files in WUFlux are open to researchers, users can extend or enhance its capabilities. By using this platform, we can standardize and document the details of 13C-MFA studies. We will continue to update the software package by including more flux models of non-model microbial species.
Project name: WUFlux
Project homepage: www.13cmfa.org
Operating systems: Preferably Windows OS 7 or higher
Programming language: MATLAB
Other requirements: MATLAB 2012b or higher with optimization toolbox, symbolic math toolbox, and statistic toolbox.
License: WUFlux is freely available.
Any restrictions to use by non-academics: none
We thank Prof. James Ballard for editorial advice on our manuscript.
The project was funded by NSF (DBI 1356669 and MCB 1616619).
YJT and LH initiated the project. LH, YJT and SGW built the original user interface and programmed WUFlux. MZ and YC improved the computational algorithm, user interface, and visualization of flux distributions. LH and SGW prepared the first draft of manuscript and user manual. LH, SGW, MZ, YC, and YJT read, edited, and approved the manuscript.
The authors declare that they have no competing interests.
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