High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

Environmental Science & Technology, Journal Year: 2024, Volume and Issue: 58(29), P. 12784 - 12822

Published: July 10, 2024

In the modern "omics" era, measurement of human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics metabolomics, has emerged as leading technology to broadly profile chemical exposure agents related biomolecules for accurate measurement, high sensitivity, rapid data acquisition, increased resolution space. Non-targeted approaches are increasingly accessible, supporting shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical computational infrastructures needed expand analysis coverage through streamlined, scalable, harmonized workflows pipelines that permit longitudinal tracking, retrospective validation, multi-omics integration meaningful health-oriented inferences. this article, we survey literature on state-of-the-art technologies, review current informatic pipelines, provide an up-to-date reference exposomic chemists, toxicologists, epidemiologists, care providers, stakeholders health sciences medicine. We propose efforts benchmark fit-for-purpose platforms expanding space, including gas/liquid chromatography-HRMS (GC-HRMS LC-HRMS), discuss opportunities, challenges, strategies advance burgeoning field exposome.

Language: Английский

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AllCCS2: Curation of Ion Mobility Collision Cross-Section Atlas for Small Molecules Using Comprehensive Molecular Representations

Analytical Chemistry, Journal Year: 2023, Volume and Issue: 95(37), P. 13913 - 13921

Published: Sept. 4, 2023

The development of ion mobility-mass spectrometry (IM-MS) has revolutionized the analysis small molecules, such as metabolomics, lipidomics, and exposome studies. curation comprehensive reference collision cross-section (CCS) databases plays a pivotal role in successful application IM-MS for small-molecule analysis. In this study, we presented AllCCS2, an enhanced version AllCCS, designed universal prediction mobility CCS values molecules. AllCCS2 incorporated newly available experimental data, including 10,384 records 7713 unified values, training data. By leveraging neural network trained on diverse molecular representations encompassing mass features, descriptors, graph features extracted using convolutional network, achieved exceptional accuracy. median relative error (MedRE) 0.31, 0.72, 1.64% training, validation, testing sets, respectively, surpassing existing tools terms accuracy coverage. Furthermore, exhibited excellent compatibility with different instrument platforms (DTIMS, TWIMS, TIMS). uncertainties from data model were comprehensively investigated by representative structure similarity variation. Notably, molecules high structural similarities to set lower variation improved errors. summary, serves valuable resource support applications technologies. database are freely accessible at http://allccs.zhulab.cn/.

Language: Английский

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Stony coral tissue loss disease: a review of emergence, impacts, etiology, diagnostics, and intervention

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 25, 2024

Stony coral tissue loss disease (SCTLD) is destructive and poses a significant threat to Caribbean reef ecosystems. Characterized by the acute of tissue, SCTLD has impacted over 22 stony species across region, leading visible declines in health. Based on duration, lethality, host range, spread this disease, considered most devastating outbreak ever recorded. Researchers are actively investigating cause transmission SCTLD, but exact mechanisms, triggers, etiological agent(s) remain elusive. If left unchecked, could have profound implications for health resilience reefs worldwide. To summarize what known about identify potential knowledge gaps, review provides holistic overview research, including susceptibility, transmission, ecological impacts, etiology, diagnostic tools, defense treatments. Additionally, future research avenues highlighted, which also relevant other diseases. As continues spread, collaborative efforts necessary develop effective strategies mitigating its impacts critical These need include researchers from diverse backgrounds underrepresented groups provide additional perspectives that requires creative urgent solutions.

Language: Английский

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Transcriptomic and metabolomic analysis of recalcitrant phosphorus solubilization mechanisms in Trametes gibbosa

Frontiers in Microbiology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 4, 2025

Introduction Phosphorus (P) is a crucial growth-limiting nutrient in soil, much of which remains challenging for plants to absorb and use. Unlike chemical phosphate fertilizers, phosphate-solubilizing microorganisms (PSMs) offer means address available phosphorus deficiency without causing environmental harm. PSMs possess multiple mechanisms solubilization. Although the phosphorus-solubilizing bacteria (PSB) have been well characterized, utilized by fungi (PSF) remain largely unexplored. Methods This study isolated PSF strain, Trametes gibbosa T-41, from soil evaluated its solubilizing capacity with organic (calcium phytin; Phytin-P) inorganic (tricalcium phosphate; Ca-P) sources. The solubilization, enzyme activity, acid production T-41 were measured. And P-solubilizing mechanism conducted transcriptomic metabolomic analyses. Results discussion exhibited varying when grown sources (109.80 ± 8.9 mg/L vs. 57.5 7.9 mg/L, p < 0.05). Compared Ca-P treatment, demonstrated stronger alkaline phosphatase (ALP) under Phytin-P treatment (34.5 1.2 μmol/L/h 19.8 0.8 μmol/L/h, Meanwhile, oxalic acid, maleic succinic was higher ( Transcriptomic analysis revealed that different altered metabolic pathways such as galactose metabolism, glyoxylate dicarboxylic ascorbate aldolate metabolism. Key metabolites like myo-inositol, 2-oxoglutarate, pyruvate found impact performance T. differently two P Notably, synthesis Pytin-P, upregulated genes involved myo-inositol synthesis, potentially enhancing ability. These results provide new insights into molecular at levels, laying theoretical foundation broader application bio-phosphorus fertilizers future.

Language: Английский

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Metabolite fingerprinting of the ripening process in Pixian douban using a feature-based molecular network and metabolomics analysis

Food Chemistry, Journal Year: 2023, Volume and Issue: 418, P. 135940 - 135940

Published: March 20, 2023

Language: Английский

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Tips and tricks for LC–MS-based metabolomics and lipidomics analysis

TrAC Trends in Analytical Chemistry, Journal Year: 2024, Volume and Issue: 180, P. 117940 - 117940

Published: Aug. 29, 2024

Metabolomics and lipidomics are rapidly growing fields, leading to novel discoveries advancing the understanding of biological processes at molecular level. However, designing a proper workflow choosing from countless options can be challenging, especially for beginners in field. To address this challenge, we provide comprehensive overview metabolomics tools step-by-step guide that includes "tips tricks" based on current analysis approaches. We include power analysis, sample collection preparation, separation detection metabolites using primarily liquid chromatography–mass spectrometry (LC–MS), processing raw instrumental files, quality control, statistical data sharing. This offers practical insights applicable diverse research areas, covering all essential steps metabolomic lipidomic profiling.

Language: Английский

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Scaling-up metabolomics: Current state and perspectives

TrAC Trends in Analytical Chemistry, Journal Year: 2023, Volume and Issue: 167, P. 117225 - 117225

Published: Aug. 12, 2023

Metabolomics is now a mature phenotyping tool that provides substantial results within various scientific communities. Its application at large-scale, i.e. on large populations and/or samples, has shown its power for research activities from plant science to human epidemiology and medicine, but it still needs key methodological developments routine application. Here, we review the current state of large-scale metabolomics applications, providing recent examples cohort studies in plant/environment research, present remaining challenges both fields. Then, address common issues, analytics data science, fulfil these objectives go towards more comprehensive interoperable metabolomics, making new actor frame One-Health future research.

Language: Английский

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Computational methods for processing and interpreting mass spectrometry-based metabolomics

Essays in Biochemistry, Journal Year: 2023, Volume and Issue: 68(1), P. 5 - 13

Published: Nov. 24, 2023

Abstract Metabolomics has emerged as an indispensable tool for exploring complex biological questions, providing the ability to investigate a substantial portion of metabolome. However, vast complexity and structural diversity intrinsic metabolites imposes great challenge data analysis interpretation. Liquid chromatography mass spectrometry (LC-MS) stands out versatile technique offering extensive metabolite coverage. In this mini-review, we address some hurdles posed by nature LC-MS data, brief overview computational tools designed help tackling these challenges. Our focus centers on two major steps that are essential most metabolomics investigations: translation raw into quantifiable features, extraction insights from spectra facilitate identification. By current solutions, aim at critical capabilities constraints spectrometry-based metabolomics, while introduce recent trends in processing within field.

Language: Английский

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Hydrophilic Interaction Liquid Chromatography–Hydrogen/Deuterium Exchange–Mass Spectrometry (HILIC-HDX-MS) for Untargeted Metabolomics

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(5), P. 2899 - 2899

Published: March 1, 2024

Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time–m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, 90% signals classified as unknowns. To enhance rates, researchers employ tandem spectral libraries and challenging silico fragmentation software. Hydrogen/deuterium exchange (HDX-MS) may offer an additional layer structural information untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate potential hydrophilic interaction liquid (HILIC)-HDX-MS metabolomics. Specifically, evaluate effectiveness two approaches using hypothetical targets: post-column addition deuterium oxide (D2O) on-column HILIC-HDX-MS method. illustrate practical application HILIC-HDX-MS, apply this methodology software MS-FINDER unknown compound detected various samples, including plasma, serum, tissues, feces during HILIC-MS profiling, subsequently identified N1-acetylspermidine.

Language: Английский

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Critical review on in silico methods for structural annotation of chemicals detected with LC/HRMS non-targeted screening

Analytical and Bioanalytical Chemistry, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 14, 2024

Abstract Non-targeted screening with liquid chromatography coupled to high-resolution mass spectrometry (LC/HRMS) is increasingly leveraging in silico methods, including machine learning, obtain candidate structures for structural annotation of LC/HRMS features and their further prioritization. Candidate are commonly retrieved based on the tandem spectral information either from or databases; however, vast majority detected remain unannotated, constituting what we refer as a part unknown chemical space. Recently, exploration this space has become accessible through generative models. Furthermore, evaluation benefits complementary empirical analytical such retention time, collision cross section values, ionization type. In critical review, provide an overview current approaches retrieving prioritizing structures. These come own set advantages limitations, showcase example ten known features. We emphasize that these limitations stem both experimental computational considerations. Finally, highlight three key considerations future development silico methods. Graphical

Language: Английский

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