Metabolomic differential analysis of gene-mutated Drosophila using LC/MS and GC/MS
Applications | 2023 | ShimadzuInstrumentation
Genetic mutations can alter metabolic pathways and lead to disease, making their study essential for understanding biological mechanisms and for applications in genetics, drug discovery, and quality control in biotechnology. Integrating LC/MS and GC/MS data provides a comprehensive metabolomic profile, enhancing the detection of subtle biochemical changes.
This study aimed to compare metabolite profiles between wild-type and genetically mutated Drosophila yellow strains. By employing both liquid chromatography–mass spectrometry (LC/MS) and gas chromatography–mass spectrometry (GC/MS), researchers sought to identify mutation-associated metabolic changes and visualize them through advanced statistical analysis and metabolic mapping.
Sample Preparation and Analysis:
Instrumental Platforms:
Principal Component Analysis (PCA):
Loading Plot Insights:
Volcano Plot Findings:
Box Plot Verification:
Integrated LC/MS and GC/MS Analysis:
The combined use of LCMS-8060NX and GCMS-TQ™8040 NX with the Multi-omics Analysis Package effectively distinguished metabolic differences between wild-type and genetically mutated Drosophila. Advanced statistical analyses and integrated metabolic mapping enabled clear visualization of mutation-driven alterations, demonstrating a robust workflow for metabolomic research and potential applications in genetics and biomedical studies.
GC/MSD, GC/MS/MS, GC/QQQ, LC/MS, LC/MS/MS, LC/QQQ
IndustriesMetabolomics
ManufacturerShimadzu
Summary
Significance of the Topic
Genetic mutations can alter metabolic pathways and lead to disease, making their study essential for understanding biological mechanisms and for applications in genetics, drug discovery, and quality control in biotechnology. Integrating LC/MS and GC/MS data provides a comprehensive metabolomic profile, enhancing the detection of subtle biochemical changes.
Objectives and Study Overview
This study aimed to compare metabolite profiles between wild-type and genetically mutated Drosophila yellow strains. By employing both liquid chromatography–mass spectrometry (LC/MS) and gas chromatography–mass spectrometry (GC/MS), researchers sought to identify mutation-associated metabolic changes and visualize them through advanced statistical analysis and metabolic mapping.
Methodology and Instrumentation
Sample Preparation and Analysis:
- 100 adult Drosophila (50 wild type, 50 genetically mutated)
- 20 samples, each comprising 5 flies (10 wild-type samples, 10 mutant samples)
- Metabolite extraction and derivatization followed the Metabolomics Pretreatment Handbook protocols
Instrumental Platforms:
- LC/MS analysis: Shimadzu LCMS-8060NX with primary metabolite method package
- GC/MS analysis: Shimadzu GCMS-TQ™8040 NX for volatile primary metabolites (5 samples per genotype)
Main Results and Discussion
Principal Component Analysis (PCA):
- 89 metabolites detected by LC/MS were subjected to PCA
- PC1 and PC2 captured 29.3% and 18.0% of variance (47.3% cumulative)
- Clear separation between wild-type and mutant groups
Loading Plot Insights:
- Wild-type enrichment: Kynurenic acid, Vitamin B12, Methionine sulfoxide
- Mutant enrichment: Citrulline, Proline, Carnitine; subsets high in Malic acid and Aspartic acid
Volcano Plot Findings:
- Significantly elevated in wild type: Kynurenic acid, Kynurenine, Vitamin B12
- Uniquely elevated in mutants: Citrulline
- Most metabolites showed similar abundance across genotypes
Box Plot Verification:
- Kynurenine levels confirmed to be high exclusively in wild-type samples
Integrated LC/MS and GC/MS Analysis:
- Metabolic maps overlaid LC/MS data on GC/MS pathways for representative samples
- Detailed mapping of the kynurenine pathway showed coordinated elevation of all detected intermediates in wild type
Benefits and Practical Applications
- Comprehensive metabolic profiling through combined LC/MS and GC/MS enhances coverage
- Multi-omics Analysis Package offers user-friendly visualization: PCA, volcano plots, box plots, and metabolic maps
- Objective statistical workflows support reproducible biomarker discovery and quality control
Future Trends and Potential Applications
- Expansion to additional omics layers (proteomics, transcriptomics) for systems-level insights
- Automation and AI-driven pattern recognition to accelerate data interpretation
- High-throughput screening of genetic variants in model organisms and human cell lines
- Integration with clinical diagnostics for personalized medicine research
Conclusion
The combined use of LCMS-8060NX and GCMS-TQ™8040 NX with the Multi-omics Analysis Package effectively distinguished metabolic differences between wild-type and genetically mutated Drosophila. Advanced statistical analyses and integrated metabolic mapping enabled clear visualization of mutation-driven alterations, demonstrating a robust workflow for metabolomic research and potential applications in genetics and biomedical studies.
Reference
- What is genetic disease plus, genetic mutation? How does it happen? accessed 20th June 2022
- Shimadzu Corporation, Metabolomics Pretreatment Handbook, accessed 9th June 2022
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