SUMMARY: Mass spectrometry (MS) is widely used for isotopic studies of metabolism and other (bio)chemical processes. Quantitative applications in systems and synthetic biology require to correct the raw MS data for the contribution of naturally occurring isotopes. Several tools are available to correct low-resolution MS data, and recent developments made substantial improvements by introducing resolution-dependent correction methods, hence opening the way to the correction of high-resolution MS (HRMS) data. Nevertheless, current HRMS correction methods partly fail to determine which isotopic species are resolved from the tracer isotopologues and should thus be corrected. We present an updated version of our isotope correction software (IsoCor) with a novel correction algorithm which ensures to accurately exploit any chemical species with any isotopic tracer, at any MS resolution. IsoCor v2 also includes a novel graphical user interface for intuitive use by end-users and a command-line interface to streamline integration into existing pipelines. AVAILABILITY AND IMPLEMENTATION: IsoCor v2 is implemented in Python 3 and was tested on Windows, Unix and MacOS platforms. The source code and the documentation are freely distributed under GPL3 license at https://github.com/MetaSys-LISBP/IsoCor/ and https://isocor.readthedocs.io/.

Abstract Summary: We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography–mass spectrometry-based metabolome annotation. The inference engine core is based on a Bayesian model implemented to (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and (ii) allow sensitive selection of biologically meaningful biochemical reaction databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand-alone versions. Availability and implementation: ProbMetab was implemented in a modular manner to fit together with established upstream (xcms, CAMERA, AStream, mzMatch.R, etc) and downstream R package tools (GeneNet, RCytoscape, DiffCorr, etc). ProbMetab, along with extensive documentation and case studies, is freely available under GNU license at: http://labpib.fmrp.usp.br/methods/probmetab/. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

UNLABELLED: Mass spectrometry (MS) is widely used for isotopic labeling studies of metabolism and other biological processes. Quantitative applications-e.g. metabolic flux analysis-require tools to correct the raw MS data for the contribution of all naturally abundant isotopes. IsoCor is a software that allows such correction to be applied to any chemical species. Hence it can be used to exploit any isotopic tracer, from well-known ((13)C, (15)N, (18)O, etc) to unusual ((57)Fe, (77)Se, etc) isotopes. It also provides new features-e.g. correction for the isotopic purity of the tracer-to improve the accuracy of quantitative isotopic studies, and implements an efficient algorithm to process large datasets. Its user-friendly interface makes isotope labeling experiments more accessible to a wider biological community. AVAILABILITY: IsoCor is distributed under OpenSource license at http://metasys.insa-toulouse.fr/software/isocor/