GCMS
More information
WebinarsAbout usContact usTerms of use
LabRulez s.r.o. All rights reserved. Content available under a CC BY-SA 4.0 Attribution-ShareAlike

Multicomponent Analysis of Metabolites in Chinese caterpillar fungus using gas chromatography-triple quadrupole mass spectrometry

Posters | 2019 | ShimadzuInstrumentation
GC/MSD, GC/MS/MS, GC/QQQ
Industries
Food & Agriculture, Metabolomics
Manufacturer
Shimadzu

Summary

Importance of the topic


Chinese caterpillar fungus (Cordyceps sinensis) is a prized traditional medicine and functional food, renowned for a diverse array of bioactive metabolites. Detailed profiling of these small molecules enhances understanding of its therapeutic effects, fosters quality assurance and streamlines modern research on this valuable natural product.

Objectives and study overview


The study aimed to develop a high-throughput method for simultaneous detection of up to 475 metabolites in C. sinensis using gas chromatography coupled with triple quadrupole mass spectrometry (GC-MS/MS). An MRM-based approach from the Smart Metabolites Database was applied to achieve broad coverage without requiring individual standards for each analyte.

Methodology and instrumentation


Sample Preparation:
  • 30 mg dried fungus extracted in methanol/water/chloroform (2.5:1:1, v/v/v).
  • Ribitol added as a substitute internal reference; 2-isopropylmalic acid introduced post-extraction for semi-quantitation.
  • Extract dried under vacuum, followed by methyloximation and trimethylsilylation.

MRM Method Development:
  • Retention times predicted using a C9–C33 n-alkane standard run under database parameters.
  • Smart Metabolites Database provided MRM transitions for 475 targets, refined with experimental retention data.

Used instrumentation


GC-MS/MS System:
  • Instrument: Shimadzu GCMS-TQ8050 triple quadrupole mass spectrometer
  • Injection: Split mode (10:1), DB-5 column (30 m×0.25 mm×1.0 µm)
  • Oven: 100 °C (4 min) → 4 °C/min → 320 °C (8 min)
  • Carrier gas: Helium; Collision gas: Argon; Ionization: EI; Interface 280 °C; Ion source 200 °C

Main results and discussion


From the optimized MRM method, 141 metabolites spanning amino acids, organic acids, sugars, nucleosides and related compounds were detected in C. sinensis. Semi-quantitative data were obtained by comparing peak areas to the 2-isopropylmalic acid internal standard. Typical MRM traces illustrated clear separation of key analytes such as glycine-TMS, valine-TMS, adenosine-TMS and dopamine-TMS. The absence of individual standards did not compromise identification, owing to the comprehensive transition library.

Benefits and practical applications


The workflow offers:
  • Rapid screening of hundreds of metabolites in a single run.
  • Robust semi-quantitation using a single internal standard.
  • Enhanced quality control for herbal products and nutraceutical research.

Future trends and potential applications


Further developments may include expansion of the metabolite library, integration of absolute quantitation using isotope-labeled standards, and application of this platform to other botanicals and complex biological matrices. Automation of data processing and incorporation of chemometric tools will advance comprehensive metabolomics studies.

Conclusion


An MRM-based GC-MS/MS approach leveraging the Smart Metabolites Database enables efficient semi-quantitative profiling of over 140 metabolites in Cordyceps sinensis without individual standards, offering a valuable tool for research and quality assessment of this important medicinal fungus.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

Downloadable PDF for viewing
 

Similar PDF

Toggle
Application for Plant Metabolome Analysis Using the GC/MS/MS Smart Metabolites Database
C146-E315 Application for Plant Metabolome Analysis Using the GC/MS/MS Smart Metabolites Database Technical Report Mami Okamoto1, Junko Takanobu1, Muneo Sato1, Satoshi Yamaki2, Yuji Sawada1, Masami Yokota Hirai1 A b s tra c t: The GC/MS/MS Smart Metabolites Database contains analytical…
Key words
tms, tmsacid, acidaric, aricsucci, succisucc, succnyl, nylmetabolites, metabolitessmart, smartmrm, mrmpyruvic, pyruviccoa, coafumar, fumarisoci, isociociitric, ociitricogluttaric
Multicomponent Analysis of Metabolites in Human Plasma using GC-MS/MS
LAAN-J-MS-E104 GC-MS Gas Chromatograph Mass Spectrometer Multicomponent Analysis of Metabolites in Human Plasma using GC-MS/MS 104 The analysis of metabolomes, such as when searching for disease biomarkers, is performed in many areas in the medical field, whether it be for…
Key words
tms, tmsacid, acidmeto, metovalproic, valproicisovalerylglycine, isovalerylglycinentms, ntmsdihydrouracil, dihydrouraciloctadecanol, octadecanolacetylglycine, acetylglycinecystamine, cystaminephenylacetic, phenylaceticoleamide, oleamideparaxanthine, paraxanthinemargaric, margaricglyoxylic
Analysis of Glycolysis Metabolites in Human Embryonic Stem Cells using GC-MS/MS
LAAN-J-MS-E102A GC-MS Gas Chromatograph Mass Spectrometer Analysis of Glycolysis Metabolites in Human Embryonic Stem Cells using GC-MS/MS 102 The analysis of metabolomes, such as when searching for disease biomarkers, is performed in many areas in the medical field, whether it…
Key words
pyruvic, pyruvicname, namemeto, metoglycolysis, glycolysiscompound, compoundacid, acidtms, tmsmrm, mrmdetected, detectedmetabolite, metaboliteglyceraldehyde, glyceraldehydephosphoenolpyruvic, phosphoenolpyruvicdihydroxyacetone, dihydroxyacetonemetabolites, metabolitesembryonic
Comparison of Metabolites in Rice from Different Production Areas Using GC-MS/MS
GC-MS GCMS-TQ 8040 NX Statistical Analysis Software eMSTAT Solution Application News Comparison of Metabolites in Rice from Different Production Areas Using GC-MS/MS Hitomi Tsujihata, Yutaka Umakoshi, and Nanami Sakashita User Benefits  eMSTAT Solution enables multivariate analysis of chromatogram data…
Key words
tms, tmskagawa, kagawaacid, aciddiscriminant, discriminantchiba, chibaemstat, emstatshiga, shigaibaraki, ibarakianalysis, analysismetabolites, metabolitesinquiry, inquirystatistical, statisticalcaproic, caproicmultivariate, multivariateoctanoic
Other projects
LCMS
ICPMS
Follow us
More information
WebinarsAbout usContact usTerms of use
LabRulez s.r.o. All rights reserved. Content available under a CC BY-SA 4.0 Attribution-ShareAlike