MetaboLights

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Feature Detection: Use XCMS for peak detection, alignment, and quantification to obtain a feature table. MS/MS Acquisition & Pre-processing: Acquire MS/MS data (DDA or DIA). The MS/MS spectra can be merged using tools like MetaboliteSpectralMatcher or libraries like mineMS2 can pre-process them into fragmentation graphs . Annotation: Search libraries with software like metID or Compound Discoverer . Use MS-Net for network-based propagation when no direct match is found . Consider advanced methods like longitudinal profiling for challenging isomers . Identifier Standardization: Use tools like metLinkR to standardize and cross-reference metabolite identifiers (e.g., HMDB, KEGG, PubChem) across studies for meta-analysis or validation . Functional Analysis: Use MetaProViz or MarVis for pathway enrichment and biological interpretationMetaboLightsPublicLiquid Chromatography MS - positive - hilicLiquid Chromatography MS - negative - hilicThe LC analysis was performed on a Vanquish UHPLC System (Thermo Fisher Scientific, USA). Chromatography was carried out with an ACQUITY UPLC HSS T3 (2.1x100 mm, 1.8 µm) (Waters, Milford, MA, USA). The column maintained at 40. The flow rate and injection volume were set at 0.3 mL/min and 2 µL, respectively. For LC-ESI (+)-MS analysis, the mobile phases consisted of (B2) 0.1% formic acid in acetonitrile (v/v) and (A2) 0.1% formic acid in water (v/v). Separation was conducted under the following gradient: 0~1 min, 8% B2; 1~8 min, 8%~98% B2; 8~10 min, 98% B2; 10~10.1 min, 98%~8% B2; 10.1~12 min, 8% B2. For LC-ESI (-)-MS analysis, the analytes was carried out with (B3) acetonitrile and (A3) ammonium formate (5mM). Separation was conducted under the following gradient: 0~1 min, 8% B3; 1~8 min, 8%~98% B3; 8~10 min, 98% B3; 10~10.1 min, 98%~8% B3; 10.1~12 min, 8% B3. Integrative multi-omics, HPLC fingerprinting and machine learning reveal distinct differences among three Dendrobium species from the Dabie Mountains.Peking UniversityDuo Keaistem,leafmass spectrometry assay1. Accurately weigh an appropriate amount of sample into a 2 mL centrifuge tube, add 600 µL MeOH (Containing 2-Amino-3-(2-chloro-phenyl)-propionic acid(4 ppm), vortex for 30 s;2. Add steel balls, placed in a tissue grinder for 60 s at 55 Hz;3. Room temperature ultrasound for 15 min;4. Centrifuge for 10 min at 12,000 rpm and 4, filter the supernatant by 0.22 μm membrane and transfer into the detection bottle for LC-MS detection.Dendrobium officinaleDendrobium moniliformeDendrobium huoshanensehttps://www.ebi.ac.uk/metabolights/MTBLS14876Zenggen Liu. Hubei University of Chinese Medicine. 3370@hbucm.edu.cn.Weiquan Ruan. Hubei University of Chinese Medicine. 649187269@qq.com.Using the MSConvert tool from the ProteoWizard software package (v3.0.8789) [1], the raw mass spectrometry data files were converted into mzXML file format. Peak detection, peak filtering, and peak alignment were performed using the R XCMS package [2], with parameters set as follows: bw = 2, ppm = 15, peakwidth = c(5, 30), mzwid = 0.015, mzdiff = 0.01, method = 'centWave', resulting in a quantitative feature listGroupkeaiduoduo998@126.comLC-MS grade methanol (MeOH) was purchased from Fisher Scientific (Loughborough, UK). 2-Amino-3-(2-chloro-phenyl)-propionic acid was obtained from Aladdin (Shanghai, China).MetabolomicsMetabolomicsNutritional compositionThermo Vanquishuntargeted analysisHPLC fingerprintDendrobium officinaleDendrobium huoshanenseQuality evaluationMulti-omicsSecondary metabolitesDendrobiumDendrobium moniliformeThermo Scientific Q Exactive Focusstem,leaffresh sampleMetabolomicsNutritional compositionThermo Vanquishuntargeted analysisHPLC fingerprintDendrobium officinaleDendrobium huoshanenseQuality evaluationMulti-omicsSecondary metabolitesDendrobiumThermo Scientific Q Exactive FocusDendrobium moniliformestem,leaffresh sampleMass spectrometric detection of metabolites was performed on Q Exactive Focus (Thermo Fisher Scientific, USA) with ESI ion source. Simultaneous MS1 and MS/MS (Full MS-ddMS2 mode, data-dependent MS/MS) acquisition was used. The parameters were as follows: sheath gas pressure, 40 arb; aux gas flow, 10 arb; spray voltage, 3.50 kV and -2.50 kV for ESI(+) and ESI(-), respectively; capillary temperature, 325 ; MS1 range, m/z 100-1000; MS1 resolving power, 70000 FWHM; number of data dependant scans per cycle, 3; MS/MS resolving power, 17500 FWHM; normalized collision energy, 30 eV; dynamic exclusion time,utomaticfalseIntegrative multi-omics, HPLC fingerprinting and machine learning reveal distinct differences among three Dendrobium species from the Dabie MountainsDendrobium species are widely used in traditional Chinese medicine owing to their medicinal and nutritional value, yet the phytochemical diversity and molecular mechanisms underlying theirbioactivities remain poorly understood. To elucidate these traits, we performed an integrative multi-omics study combining metabolomics and transcriptomics on three species, D. huoshanense, D. officinale, and D. moniliforme from the Dabie Mountains in Central China, with emphasis on flavonoid metabolism, particularly apigenin derivatives. Among 470 shared metabolites, quantitative profiling revealed distinct accumulation patterns between stems and leaves. Transcriptomic analysis uncovered species- and tissue-specific regulatory networks governing flavonoid biosynthesis. Complementary HPLC-DAD fingerprinting of stems, leaves, roots, and flowers was established and rigorously validated, with 18 common peaks annotated. VIP analysis identified tissue-specific chemical markers for quality assessment. Apigenin-6-C-α-L-arabinoside-8-C-β-D-xyloside and apigenin-6-C-α-L-rhamnosyl-(12)-β-D- glucoside-8-C-α-L-arabinoside were predominant in D. huoshanense stems, while flowers accumulated high levels of flavonoids such as rutin and vicenin-1 and displayed superior anti-inflammatory activity. Comprehensive nutritional profiling quantified total carbohydrates, polysaccharides, monosaccharides, fatty acids, amino acids, minerals, and vitamins across plant organs. Machine learning integration of multi-omics data delineated key molecular signatures distinguishing the three Dendrobium species from the Dabie Mountains. Together, this work provides a multidimensional resource that advances the biochemical understanding of Dendrobium, supports species and tissue discrimination, and informs quality control and utilization of both medicinal and edible plant parts.2026-06-282026-06-28MTBLS14876