Recent Developments along the Analytical Process for Metabolomics Workflows

González-Riaño, Carolina; Dudzik, Danuta; García, Aitana Martos; Gil-de-la-Fuente, Alberto; Gradillas, Ana; Godzień, Joanna; López‐Gonzálvez, Ángeles; Rey-Stolle, Fernanda; Rojo, David; Ruperez, Francisco J.; Sáiz, Jorge; Barbas, Coral

doi:10.1021/acs.analchem.9b04553

Cited by 84 publications

(63 citation statements)

References 257 publications

(335 reference statements)

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“…Due to the rapid development of omics techniques such as high-throughput sequencing and data-mining tools, cultivation-independent studies have generated massive data and powerful predictions to advance the pro ling and understanding of GM features [6,[43][44][45][46]. Still, researchers encounter challenges in interpretation of omics data, as considerable amounts of bacterial taxa and genetic elements are "dark matters" [9,11].…”

Section: Discussionmentioning

confidence: 99%

Enlightening the Taxonomy Darkness of Human Gut Microbiomes With Cultured Biobank

Liu

Abuduaini

et al. 2020

Preprint

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Background The cultivated gut microbial resource plays essential role in gut microbiome studies such as gut microbial function and their interactions with host. Though several major studies had been performed to understand the cultured human gut microbiota, up to 70% of the Unified Human Gastrointestinal Genome species remain uncultivated and their taxonomy is not clear. Large-scale gut microbial isolation and identification and their access to pubic are imperative for gut microbial studies and for understanding of the human gut microbial functions.Results Here, we report the construction of an human Gut Microbial Biobank (hGMB) (homepage: hgmb.nmdc.cn) by large-scale cultivation of 10,558 isolates from 239 feces of healthy Chinese volunteers, and deposited 1,170 strains representing 404 different species in International Depository Authority for long-term preservation and public access worldwidely. We discovered and denominated 107 new species, and proposed 28 new genera and 3 new families. The new species and their newly sequenced genomes uncovered 16 “most-wanted” or “medium priority” taxa proposed by the Human Microbiome Project and 42 previously-uncultured MAGs in IGGdb, respectively. The hGMB represented over 80% of the common and dominant human gut microbial genera or species of global human gut 16S rRNA gene amplicon data (n=11,647), and covered 70% of the known genes (KEGG Orthologys) and 10% of the functionally-unknown genes in the global human gut gene catalogs. Conclusions A publically accessible human Gut Microbial Biobank (hGMB) that contains 1,170 strains and represents 404 human gut microbial speces is estabolished. The hGMB expands the currently known, taxonomically-characterized gut microbial resources and genomic repository by adding 107 new species and 115 new genomes of human gut microbes. Based on the newly discovered species in this study, 28 new genera and 3 new families of human gut microbes were identified and proposed.

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Section: Discussionmentioning

confidence: 99%

Enlightening the Taxonomy Darkness of Human Gut Microbiomes With Cultured Biobank

Liu

Abuduaini

et al. 2020

Preprint

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“…Criteria for filtering are correlating with the specific aims and management of the study and should be fixed in advance, e.g., to exclude signals (= lipid species) with a S/N ratio < 10. Outliers should be defined and removed, and missing values can be carefully imputed (191). Quality samples (see above) will help to identify and to correct either drifts of the instrument (retention time, resolution of peaks, sensitivity) and/or batch effects.…”

Section: Data Interpretation and Visualizationmentioning

confidence: 99%

Sphingolipidomics in Translational Sepsis Research–Biomedical Considerations and Perspectives

Claus

Graeler

2021

Front. Med.

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Scientific Background: Sphingolipids are a highly diverse group of lipids with respect to physicochemical properties controlling either structure, distribution, or function, all of them regulating cellular response in health and disease. Mass spectrometry, on the other hand, is an analytical technique characterizing ionized molecules or fragments thereof by mass-to-charge ratios, which has been prosperingly developed for rapid and reliable qualitative and quantitative identification of lipid species. Parallel to best performance of in-depth chromatographical separation of lipid classes, preconditions of precise quantitation of unique molecular species by preprocessing of biological samples have to be fulfilled. As a consequence, “lipid profiles” across model systems and human individuals, esp. complex (clinical) samples, have become eminent over the last couple of years due to sensitivity, specificity, and discriminatory capability. Therefore, it is significance to consider the entire experimental strategy from sample collection and preparation, data acquisition, analysis, and interpretation.Areas Covered: In this review, we outline considerations with clinical (i.e., human) samples with special emphasis on sample handling, specific physicochemical properties, target measurements, and resulting profiling of sphingolipids in biomedicine and translational research to maximize sensitivity and specificity as well as to provide robust and reproducible results. A brief commentary is also provided regarding new insights of “clinical sphingolipidomics” in translational sepsis research.Expert Opinion: The role of mass spectrometry of sphingolipids and related species (“sphingolipidomics”) to investigate cellular and compartment-specific response to stress, e.g., in generalized infection and sepsis, is on the rise and the ability to integrate multiple datasets from diverse classes of biomolecules by mass spectrometry measurements and metabolomics will be crucial to fostering our understanding of human health as well as response to disease and treatment.

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“…Recently, there has been an increasing awareness in the international metabolomics community about the need for implementing quality assurance (QA) and quality control (QC) processes to ensure data quality and reproducibility [ 1 , 2 , 3 , 4 , 5 , 6 ]. Challenges in untargeted metabolomics workflows are associated with pre-analytical, analytical, and post-analytical steps [ 1 , 2 , 3 , 4 , 5 , 7 , 8 , 9 , 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows

et al. 2020

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Preprocessing data in a reproducible and robust way is one of the current challenges in untargeted metabolomics workflows. Data curation in liquid chromatography–mass spectrometry (LC–MS) involves the removal of biologically non-relevant features (retention time, m/z pairs) to retain only high-quality data for subsequent analysis and interpretation. The present work introduces TidyMS, a package for the Python programming language for preprocessing LC–MS data for quality control (QC) procedures in untargeted metabolomics workflows. It is a versatile strategy that can be customized or fit for purpose according to the specific metabolomics application. It allows performing quality control procedures to ensure accuracy and reliability in LC–MS measurements, and it allows preprocessing metabolomics data to obtain cleaned matrices for subsequent statistical analysis. The capabilities of the package are shown with pipelines for an LC–MS system suitability check, system conditioning, signal drift evaluation, and data curation. These applications were implemented to preprocess data corresponding to a new suite of candidate plasma reference materials developed by the National Institute of Standards and Technology (NIST; hypertriglyceridemic, diabetic, and African-American plasma pools) to be used in untargeted metabolomics studies in addition to NIST SRM 1950 Metabolites in Frozen Human Plasma. The package offers a rapid and reproducible workflow that can be used in an automated or semi-automated fashion, and it is an open and free tool available to all users.

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Recent Developments along the Analytical Process for Metabolomics Workflows

Cited by 84 publications

References 257 publications

Enlightening the Taxonomy Darkness of Human Gut Microbiomes With Cultured Biobank

Enlightening the Taxonomy Darkness of Human Gut Microbiomes With Cultured Biobank

Sphingolipidomics in Translational Sepsis Research–Biomedical Considerations and Perspectives

A Python-Based Pipeline for Preprocessing LC–MS Data for Untargeted Metabolomics Workflows

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