Troubleshooting in Large-Scale LC-ToF-MS Metabolomics Analysis: Solving Complex Issues in Big Cohorts

Abstract

Metabolomics, understood as the science that manages the study of compounds from the metabolism, is an essential tool for deciphering metabolic changes in disease. The experiments rely on the use of high-throughput analytical techniques such as liquid chromatography coupled to mass spectrometry (LC-ToF MS). This hyphenation has brought positive aspects such as higher sensitivity, specificity and the extension of the metabolome coverage in a single run. The analysis of a high number of samples in a single batch is currently not always feasible due to technical and practical issues (i.e., a drop of the MS signal) which result in the MS stopping during the experiment obtaining more than a single sample batch. In this situation, careful data treatment is required to enable an accurate joint analysis of multi-batch data sets. This paper summarizes the analytical strategies in large-scale metabolomic experiments; special attention has been given to QC preparation troubleshooting and data treatment. Moreover, labeled internal standards analysis and their aim in data treatment, and data normalization procedures (intra-and inter-batch) are described. These concepts are exemplified using a cohort of 165 patients from a study in asthma.

Integration of metagenomics‐metabolomics reveals specific signatures and functions of airway microbiota in mite‐sensitized childhood asthma

“…Since samples were collected while the cases were diagnosed with mite‐sensitized asthma for the first time at outpatient clinics, data concerning asthma exacerbations and therapies were not obtainable. Also unavailable is information regarding the body mass index and diet, as these factors may perturb airway microbiome 54,55 and circulating metabolome 56,57 in asthma. Another issue is that in spite of a global and unbiased view of the samples, our untargeted metabolomics approach had low analytical sensitivity to metabolites with low abundance (<100 nmol/L, eg histamine) and failed to conduct the absolute quantification of the samples.…”

Food Phenotyping: Recording and Processing of Non-Targeted Liquid Chromatography Mass Spectrometry Data for Verifying Food Authenticity

“… Internal standards: Alternatively, internally added standards can be used, which are at best isotopically labelled. However, it must be taken into account that these can lead to changes in the samples and to co-elutions [ 160 , 161 ]. …”

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“…Together with the high cost of analysis and the massive amount of data obtained per sample, small numbers of patients are chosen, such as twenty per group. However, it is not always possible to select a limited number of subject with a perfect clinical stratification, and thus tremendous work has been put in order to succeed in the analysis of large-scale cohorts with lower classification accuracy [22]. Later on, for “analytical validation” stage, targeted analysis is generally used.…”

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