The metaRbolomics Toolbox in Bioconductor and beyond

Metabolomics aims to measure and characterise the complex composition of metabolites in a biological system. Metabolomics studies involve sophisticated analytical techniques such as mass spectrometry and nuclear magnetic resonance spectroscopy, and generate large amounts of high-dimensional and complex experimental data. Open source processing and analysis tools are of major interest in light of innovative, open and reproducible science. The scientific community has developed a wide range of open source software, providing freely available advanced processing and analysis approaches. The programming and statistics environment R has emerged as one of the most popular environments to process and analyse Metabolomics datasets. A major benefit of such an environment is the possibility of connecting different tools into more complex workflows. Combining reusable data processing R scripts with the experimental data thus allows for open, reproducible research. This review provides an extensive overview of existing packages in R for different steps in a typical computational metabolomics workflow, including data processing, biostatistics, metabolite annotation and identification, and biochemical network and pathway analysis. Multifunctional workflows, possible user interfaces and integration into workflow management systems are also reviewed. In total, this review summarises more than two hundred metabolomics specific packages primarily available on CRAN, Bioconductor and GitHub

ptairMS: real-time processing and analysis of PTR-TOF-MS data for biomarker discovery in exhaled breath

International audienceMotivation: Analysis of volatile organic compounds (VOCs) in exhaled breath by proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is of increasing interest for real-time, non-invasive diagnosis, phenotyping and therapeutic drug monitoring in the clinics. However, there is currently a lack of methods and software tools for the processing of PTR-TOF-MS data from cohorts and suited for biomarker discovery studies. Results: We developed a comprehensive suite of algorithms that process raw data from patient acquisitions and generate the table of feature intensities. Notably, we included an innovative two-dimensional peak deconvolution model based on penalized splines signal regression for accurate estimation of the temporal profile and feature quantification, as well as a method to specifically select the VOCs from exhaled breath. The workflow was implemented as the ptairMS software, which contains a graphical interface to facilitate cohort management and data analysis. The approach was validated on both simulated and experimental datasets, and we showed that the sensitivity and specificity of the VOC detection reached 99% and 98.4%, respectively, and that the error of quantification was below 8.1% for concentrations down to 19 ppb. Availability and implementation: The ptairMS software is publicly available as an R package on Bioconductor (doi: 10.18129/B9.bioc.ptairMS), as well as its companion experiment package ptairData (doi: 10.18129/B9.bioc.ptairData

Sacurine toy dataset - 6 samples / 3 QC / 3 Blanks

Objective: Influence of age, body mass index, and gender on the urine metabolome Cohort: 183 employees from CEA LC-HRMS: LTQ-Orbitrap (negative ionization mode

Development and characterization of electronic noses for the rapid detection of COVID-19 in exhaled breath

International audienceNon-invasive and rapid approach is potentially needed for diagnosis of COVID-19. In this work, exhaled breath analysis using e-Nose, is presented as an innovative technique to identify the COVID-19 specific VOCs. The analytical performances of Cyranose®, a commercial e-Nose device, were investigated under controlled conditions. Sensitivity, limit of detection and reproducibility of standardized VOCs existing in the breath was assessed. In addition, the effect of various experimental conditions on sensor response was evaluated, including temperature, relative humidity, flow and sampling time, aiming to select the optimal parameters and to validate it in clinical trials to detect the COVID-19 biomarkers. Cyranose® exhibits high sensitivity and reproducible response towards acetone and nonanal, with a limit of detection of 63 ppb and 20 ppb respectively. Furthermore, results show that the variability of relative humidity, temperature and flow sampling, induced a significant sensors response variation, whereas, varying the sampling time does not affect significantly the sensor response

Development and characterization of electronic noses for the rapid detection of COVID-19 in exhaled breath

International audienceNon-invasive and rapid approach is potentially needed for diagnosis of COVID-19. In this work, exhaled breath analysis using e-Nose, is presented as an innovative technique to identify the COVID-19 specific VOCs. The analytical performances of Cyranose®, a commercial e-Nose device, were investigated under controlled conditions. Sensitivity, limit of detection and reproducibility of standardized VOCs existing in the breath was assessed. In addition, the effect of various experimental conditions on sensor response was evaluated, including temperature, relative humidity, flow and sampling time, aiming to select the optimal parameters and to validate it in clinical trials to detect the COVID-19 biomarkers. Cyranose® exhibits high sensitivity and reproducible response towards acetone and nonanal, with a limit of detection of 63 ppb and 20 ppb respectively. Furthermore, results show that the variability of relative humidity, temperature and flow sampling, induced a significant sensors response variation, whereas, varying the sampling time does not affect significantly the sensor response

Optimized selection process to identify a metabolic syndrome metabolomic/lipidomic signature in older adults of the NuAge cohort

National audienceIntroduction: Metabolic syndrome (MetS) is characterized by a cluster of risk factors including obesity, metabolic dysregulations such as insulin resistance, hypertension, and dyslipidemia, raising the risk for type 2 diabetes development and its complications. It involves multifaceted processes at multiple levels that are still far from being understood. New tools are therefore necessary to bring new knowledge about MetS, better stratify populations and customise strategies for its prevention and/or reversal. Methods: The Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge) regroups 853 men and 940 women, aged 68–82 at recruitment in 2003–2005 (T1) and followed up annually for three years (T2-T4). In the present study, a nested case-control study on MetS was designed to identify a metabolomic/lipidomic signature of MetS in older men, reflecting its phenotypic spectrum. An optimized participant selection strategy was developed based on presence and number of MetS criteria, including medication, their stability over 3 years, as well as the identification of outliers. Results: The final selection included 123 men, 61 cases and 62 controls, with similar age and partial overlap of values defining MetS. This design is necessary to precisely detect and estimate the amplitude of metabolic deviations among the massive data sets, at an individual metabolite level as well as for a multivariate description. Conclusion: This selection process, optimized to limit cofounding effects, will allow identifying specific metabolomic/lipidomic signatures along with significant features for sample classification. Thus, one complex molecular phenotyping will provide a new approach/tool for a better MetS stratification in elderl

Differential effects of post-weaning diet and maternal obesity on mouse liver and brain metabolomes

International audienceNutritional changes during developmental windows are of particular concern in offspring metabolic disease. Questions are emerging concerning the role of maternal weight changes before conception, particularly for weight loss, in the development of diet-related disorders. Understanding the physiological pathways affected by the maternal trajectories in the offspring is therefore essential, but a broad overview is still lacking. We recently reported both metabolic and behavioral negative outcomes in offspring born to obese or weight-loss mothers and fed a control of high-fat diet, suggesting long-term modeling of metabolic pathways needing to be further characterized. Using non-targeted LC–HRMS, we investigated the impact of maternal and post-weaning metabolic status on the adult male offspring’s metabolome in three tissues involved in energy homeostasis: liver, hypothalamus and olfactory bulb. We showed that post-weaning diet interfered with the abundance of several metabolites, including 1,5-anhydroglucitol, saccharopine and β-hydroxybutyrate, differential in the three tissues. Moreover, maternal diet had a unique impact on the abundance of two metabolites in the liver. Particularly, anserine abundance, lowered by maternal obesity, was normalized by a preconceptional weight loss, whatever the post-weaning diet. This study is the first to identify a programming long-term effect of maternal preconception obesity on the offspring metabolome

Mass Spectrometry Imaging visualization tools developed during the Computis European project

International audienceThe Computis European project (2006-2009) was aimed at developing innovative experimental mass spectrometry imaging (MSI) techniques and software tools for data treatment and visualization, and at validating them in key biological applications (neurobiology, pharmaceutical drug development). The project succeeded in defining a specific standard format for MSI, imzML, in collaboration with the HUPO consortium. The four main MSI software tools developed by the project all handle the imzML format.Data Cube Explorer provides an easy spectral and spatial exploration of MS images: spectrum zooming, scrolling through the dataset masses with a manual contrast tuning for images, selection of Regions Of Interest with the display of the associated spectra. The self-organizing map functionality classifies images according to the intensity of all pixel places and automatically selects images as different as possible. Mirion is a simple visualization module displaying spectra by pixel and for the total image, with zooming and scrolling functions. Histogram of the total ion count of each pixel can be calculated, using different input parameters. Images are displayed for each peak of the total spectrum, with a manual intensity tuning and a comparison of the intensity distributions by pixel between several images.EasyMSI enables spatial and spectral visualization of mass spectrometry imaging datasets (spectrum and image display, peak and pixel picking, zooming on spectra and images, ROI selection), as well as an assistance for the interpretation of data: This assistance includes indicators (relative variance, Moran index, m/z correlation) to highlight peaks that bring interesting information, peak list for molecule identification, spectrum denoising or structure analysis by clustering methods (K-means, fuzzy, hierarchical clustering, diffusion map). EasyMSI offers the advantage of processing and displaying the original data (i.e. without binning).BioMap is an image analysis platform for MSI and Magnetic Resonance Imaging. It includes viewing functions (spectrum and image display, intensity adjustment, zoom, treatment of multiple ROIs, geometrical transformations and operations), and spectrum treatment (spatial or temporal filtering, baseline correction, detrending). More elaborated functions enable a simultaneous view of all dataset images, creation of a movie, statistical and histogram analysis, co-registration of images of one or two dataset(s), and realignment of images. The use and capacities of these tools are presented through a comparative analysis of a rodent urinary bladder dataset in imzML format

sj-docx-1-ems-10.1177_14690667231218912 - Supplemental material for Evaluation of SP3 for antibody-free quantification of tau in CSF mimic and brain by mass spectrometry

Supplemental material, sj-docx-1-ems-10.1177_14690667231218912 for Evaluation of SP3 for antibody-free quantification of tau in CSF mimic and brain by mass spectrometry by Chloé Jacquemin, Nicolas Villain, Rita Azevedo, Susana Boluda, Etienne A. Thévenot, François Fenaille, Foudil Lamari and François Becher in European Journal of Mass Spectrometry</p

Automatic search for chemical exposure markers in LC-HRMS metabolomic data

International audienc