Unlabelled: Current tools for liquid chromatography and mass spectrometry for metabolomic data cover a limited number of processing steps, whereas online tools are hard to use in a programmable fashion. This article introduces the Metabolite Automatic Identification Toolkit (MAIT) package, which makes it possible for users to perform metabolomic end-to-end liquid chromatography and mass spectrometry data analysis. MAIT is focused on improving the peak annotation stage and provides essential tools to validate statistical analysis results. MAIT generates output files with the statistical results, peak annotation and metabolite identification.
Availability And Implementation: http://b2slab.upc.edu/software-and-downloads/metabolite-automatic-identification-toolkit/.
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http://dx.doi.org/10.1093/bioinformatics/btu136 | DOI Listing |
BMC Plant Biol
December 2024
College of Agronomy and Biotechnology, Key Laboratory for Crop Production and Smart Agriculture of Yunnan Province, Yunnan Agricultural University, Kunming, 650201, China.
Background: Yellow nutsedge (Cyperus esculentus, known as 'YouShaDou' in China, YSD) and purple nutsedge (Cyperus rotundus, known as 'XiangFuZi' in China, XFZ), closely related Cyperaceae species, exhibit significant differences in triacylglycerol (TAG) accumulation within their tubers, a key factor in carbon flux repartitioning that highly impact the total lipid, carbohydrate and protein metabolisms. Previous studies have attempted to elucidate the carbon anabolic discrepancies between these two species, however, a lack of comprehensive genome-wide annotation has hindered a detailed understanding of the underlying molecular mechanisms.
Results: This study utilizes transcriptomic analyses, supported by a comprehensive YSD reference genome, and metabolomic profiling to uncover the mechanisms underlying the major carbon perturbations between the developing tubers of YSD and XFZ germplasms harvested in Yunnan province, China, where the plant biodiveristy is renowned worldwide and may contain more genetic variations relative to their counterparts in other places.
Sci Rep
December 2024
Metanotitia Inc, Building C4, Science and Technology Innovation Headquarters, Shenzhen (Harbin) Industrial Park, 288 Zhigu Street, Songbei District, Harbin, 150029, China.
Dried blood spot (DBS) sampling offers significant advantages over conventional blood collection methods, such as reduced sample volume, minimal invasiveness, suitability for home-based sampling, and ease of transport. However, understanding the effects of variable storage temperatures and times on metabolite stability is crucial due to varying intervals and delivery conditions between sample collection and metabolomics analysis. To minimize biological variances, all samples were collected from the same individual simultaneously and stored at three different temperatures (4 °C, 25 °C, and 40 °C) for diverse time points (3, 7, 14, and 21 days).
View Article and Find Full Text PDFMicrob Pathog
December 2024
Guangzhou Key Laboratory of Aquatic Animal Diseases and Waterfowl Breeding, College of Animal Sciences and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, Guangdong, China. Electronic address:
Aeromonas schubertii infections has caused severe economic losses in aquaculture in China. In this study, we first induced enrofloxacin (ENR) resistance in A. schubertii strains and then analyzed the mechanisms of drug resistance using transcriptomics and metabolomics.
View Article and Find Full Text PDFAnal Chem
December 2024
Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1, Canada.
Mass spectrometry (MS)-based metabolomics often rely on separation techniques when analyzing complex biological specimens to improve method resolution, metabolome coverage, quantitative performance, and/or unknown identification. However, low sample throughput and complicated data preprocessing procedures remain major barriers to affordable metabolomic studies that are scalable to large populations. Herein, we introduce PeakMeister as a new software tool in the R statistical environment to enable standardized processing of serum metabolomic data acquired by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), a high-throughput separation platform (<4 min/sample) which takes advantage of a serial injection format of 13 samples within a single analytical run.
View Article and Find Full Text PDFMetabolomics
December 2024
School of Biosciences and the Birmingham Institute of Forest Research, University of Birmingham, Birmingham, B15 2TT, UK.
Introduction: Tree bacterial diseases are a threat in forestry due to their increasing incidence and severity. Understanding tree defence mechanisms requires evaluating metabolic changes arising during infection. Metabolite extraction affects the chemical diversity of the samples and, therefore, the biological relevance of the data.
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