Examining the healthy human microbiome concept

Nature Reviews Microbiology, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 23, 2024

Language: Английский

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Harmonized quality assurance/quality control provisions to assess completeness and robustness of MS1 data preprocessing for LC-HRMS-based suspect screening and non-targeted analysis

TrAC Trends in Analytical Chemistry, Journal Year: 2024, Volume and Issue: 174, P. 117674 - 117674

Published: March 27, 2024

Language: Английский

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The marriage between stable isotope ecology and plant metabolomics – new perspectives for metabolic flux analysis and the interpretation of ecological archives

New Phytologist, Journal Year: 2024, Volume and Issue: 244(1), P. 21 - 31

Published: July 17, 2024

Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high-resolution bioanalytical spectrometers are now not only offering high-throughput metabolite identification but also suitable for compound- intramolecular position-specific analysis in the natural abundance range. In metabolomics, label-free metabolic pathway flux might become possible when applying this new technology. This is because changes commitment of substrates particular pathways activation or deactivation others alter enzyme-specific effects. leads differences compound-specific compositions. ecology, archives informed by could be used reconstruct environmental impacts on complex processes. A technology-driven linkage between two disciplines allow us extract information environment-metabolism interaction from such as tree rings within ecosystems. would contribute a holistic understanding how plants react drivers, thus providing helpful trajectories vegetation under conditions come.

Language: Английский

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Ecological and metabolic implications of the nurse effect of Maihueniopsis camachoi in the Atacama Desert

New Phytologist, Journal Year: 2023, Volume and Issue: 241(3), P. 1074 - 1087

Published: Nov. 20, 2023

Summary Plant–plant positive interactions are key drivers of community structure. Yet, the underlying molecular mechanisms facilitation processes remain unexplored. We investigated ‘nursing’ effect Maihueniopsis camachoi , a cactus that thrives in Atacama Desert between c . 2800 and 3800 m above sea level. hypothesised an important protective factor is thermal amelioration less cold‐tolerant species with corresponding impact on phenotypes. To test this hypothesis, we compared plant cover temperatures within foliage open areas modelled distribution. combined eco‐metabolomics machine learning to consequences association. Multiple benefited from interaction M. A conspicuous example was extended distribution Atriplex imbricata colder elevations association (400 higher as plants areas). Metabolomics identified 93 biochemical markers predicting status A. 79% accuracy, independently year. These findings place communities, driving local biodiversity phenotypes nursed species. Our results support stress‐gradient hypothesis provide pioneer insights into metabolic facilitation.

Language: Английский

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A GC-MS Metabolic Study on Lipophilic Compounds in the Leaves of Common Wheat Triticum aestivum L.

Metabolites, Journal Year: 2024, Volume and Issue: 14(8), P. 426 - 426

Published: Aug. 1, 2024

Common wheat (Triticum aestivum L.) is one of the most valuable cereal crops worldwide. This study examined leaf extracts 30 accessions T. and its subspecies using 48 h maceration with methanol by GC-MS GCxGC-MS. The plants were grown from seeds genetics collection Wheat Genetics Sector Institute Cytology Genetics, SB RAS. analysis revealed 263 components epicuticular waxes, including linear branched alkanes, aliphatic alcohols, aldehydes, ketones, β-diketones, carboxylic acids their derivatives, mono- diterpenes, phytosterols, tocopherols. Hierarchical cluster principal component used to identify visualize differences between different cultivars. Three clusters identified, leading being (1) octacosan-1-ol, (2) esters saturated unsaturated (3) fatty acid alkylamides, which found for first time in plant extracts. results highlight importance metabolic studies understanding adaptive mechanisms increasing resistance stress factors. These are crucial breeding new-generation cultivars improved traits.

Language: Английский

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Characterizing Families of Spectral Similarity Scores and Their Use Cases for Gas Chromatography–Mass Spectrometry Small Molecule Identification

Metabolites, Journal Year: 2023, Volume and Issue: 13(10), P. 1101 - 1101

Published: Oct. 21, 2023

Metabolomics provides a unique snapshot into the world of small molecules and complex biological processes that govern human, animal, plant, environmental ecosystems encapsulated by One Health modeling framework. However, this “molecular snapshot” is only as informative number metabolites confidently identified within it. The spectral similarity (SS) score traditionally used to identify compound(s) in mass spectrometry approaches metabolomics, where spectra are matched reference libraries candidate spectra. Unfortunately, there little consensus on which dozens available SS metrics should be used. This lack standard creates analytic uncertainty potentially leads issues reproducibility, especially these data integrated across other domains. In work, we use metabolomic case study showcase challenges consistency just one piece framework must addressed enable science for problems. Here, using large cohort datasets comprising both with expert-verified truth annotations, evaluated effectiveness 66 delineate between correct matches (true positives) incorrect negatives). We additionally characterize families make informed recommendations their use. Our results indicate specific (the Inner Product, Correlative, Intersection scores) tend perform better than others, no single metric performing optimally all queried work its findings provide an empirically-based resource researchers selection GC-MS identification, increasing scientific reproducibility through taking steps towards standardizing identification workflows.

Language: Английский

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Metabolomic profiling of health‐benefit compounds in fresh and preserved mustard greens

International Journal of Food Science & Technology, Journal Year: 2023, Volume and Issue: 59(6), P. 4290 - 4299

Published: Dec. 12, 2023

Summary In today's consumer landscape, the health benefits of preserved foods, particularly pickled and salted mustard greens, are gaining recognition on a global scale. To compare health‐promoting compounds between fresh comprehensive assessment using proximate composition analysis untargeted metabolomics was conducted. The sub‐metabolome data revealed distinct profiles for each type clearly seen in their separation through principal component analysis. metabolite profiling identified 37 metabolites with significant differences ( P ‐value < 0.05, −log10 > 4). Fresh greens were found to be rich 16 metabolites, including sulfonic acids, purines, oxepanes, monosaccharides, fatty amino acids tripeptides, offering antioxidants, gut enhancers immune boosters. contrast, exhibited an abundance 20 classes flavonoids, dipeptides, providing antioxidant properties. Salted other hand, primarily showcased high level uridine diphosphate glucose (a pyrimidine class metabolite), supporting glycoconjugate synthesis among all samples. This study highlights prominent presence various associated health‐benefit greens. These insights contribute evaluation food industry when choosing preservation methods.

Language: Английский

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Predictive metabolomics of pearl millet phenotypic traits using a germplasm panel of genetic diversity

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: May 31, 2024

Introduction Pearl millet, dubbed a “Nutri-cereal”, has high content of protein, starch, fiber, mineral and fatty acids. Its resilience in adverse agro-climatic conditions sets it apart from major cereals. Despite this, understanding how its genetic diversity affects physiological traits metabolic responses remains limited. Predictive metabolomics, merging metabolomics with artificial intelligence, allows for the comprehensive top-down modelling —from phenotype to mechanism— various phenotypic traits.Objectives To discover predictive biomarkers Brazilian germplasm core collection 203 genotypes pearl millet through combination machine learning.Methods Untargeted was conducted using UHPLC-LTQ-Orbitrap-HRMS obtain metabolite profiles, central specialised metabolism collection. Generalised linear penalisation (GLMNET) applied explore correlation between traits.Results Our model successfully predicted eight qualitative collection, accuracy ranging 74% 87%. From, 834 potential unique (575 annotated-ion features 259 unknowns) have been annotated as top predictors. It is noteworthy that majority predictors were carbohydrate, amino acid, flavonoid, terpene subclasses.Conclusions This first report on leveraging bank metabolome characterisation subsequent important agronomic traits. These outcomes hint at robustness employing GLMNET predicting crucial selecting future breeding programmes.

Language: Английский

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Une recherche dé-coïncidente

éditions Quae eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: June 10, 2024

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Metabolomics and Lipidomics for Studying Metabolic Syndrome: Insights into Cardiovascular Diseases, Type 1 & 2 Diabetes, and Metabolic Dysfunction-Associated Steatotic Liver Disease

Physiological Research, Journal Year: 2024, Volume and Issue: Suppl 1, P. S165 - S183

Published: Aug. 27, 2024

Metabolomics and lipidomics have emerged as tools in understanding the connections of metabolic syndrome (MetS) with cardiovascular diseases (CVD), type 1 2 diabetes (T1D, T2D), dysfunction-associated steatotic liver disease (MASLD). This review highlights applications these omics approaches large-scale cohort studies, emphasizing their role biomarker discovery prediction. Integrating metabolomics has significantly advanced our MetS pathology by identifying unique signatures associated progression. However, challenges such standardizing analytical workflows, data interpretation, validation remain critical for translating research findings into clinical practice. Future should focus on optimizing methodologies to enhance utility address global burden MetS-related diseases.

Language: Английский

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