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Metabolomics to Network Mapping Pipeline

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About This MicroSim

This MicroSim walks through the metabolomics analysis pipeline, from biological sample preparation through mass spectrometry analysis, computational feature extraction, statistical testing, and pathway enrichment mapping. Each stage includes an icon and description panel.

Pipeline Stages

  1. Sample Preparation — Biological samples (blood, tissue, cell lysate) are processed to extract metabolites
  2. LC-MS/MS — Liquid chromatography coupled with tandem mass spectrometry separates and identifies metabolites by mass-to-charge ratio
  3. Feature Extraction — Raw spectral data is processed into a feature table (metabolite x sample matrix of peak intensities)
  4. Statistical Testing — Differential abundance analysis identifies metabolites that differ significantly between conditions
  5. Pathway Enrichment — Significant metabolites are mapped onto known metabolic pathways to identify dysregulated pathways

How to Use

  1. Step button — Advance through each pipeline stage
  2. Read descriptions — Each stage explains what happens, what tools are used, and what the output is
  3. Follow the data transformation — Watch how raw biological samples become pathway-level insights

Iframe Embed Code

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<iframe src="https://dmccreary.github.io/bioinformatics/sims/metabolomics-pipeline/main.html"
        height="502"
        width="100%"
        scrolling="no"></iframe>

Lesson Plan

Grade Level

College introductory bioinformatics

Duration

15-20 minutes

Prerequisites

  • Basic understanding of metabolites and metabolic pathways
  • Concept of mass spectrometry
  • Familiarity with statistical hypothesis testing

Activities

  1. Exploration (5 min): Step through all stages. At each, note what the input and output are.
  2. Method Comparison (5 min): How is the metabolomics pipeline similar to and different from an RNA-seq pipeline? Both start with biological samples and end with pathway-level insights.
  3. Discussion (5 min): Metabolite identification is a major bottleneck — many detected features cannot be matched to known metabolites. How does this affect downstream analysis?
  4. Assessment (3 min): Answer the reflection questions below.

Assessment

  1. What instrument is used for metabolite detection, and what does it measure?
  2. What is a feature table in metabolomics, and what does each cell represent?
  3. How does pathway enrichment analysis help interpret a list of significant metabolites?
  4. Why is metabolomics considered complementary to genomics and proteomics?

References

  1. Metabolomics — Wikipedia
  2. Mass spectrometry — Wikipedia
  3. Liquid chromatography-mass spectrometry — Wikipedia
  4. Metabolic pathway — Wikipedia