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Chapter 13: Proteomics and Metabolomics

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13.1 Beyond the Genome

Genomics tells us what could happen (the blueprint). Transcriptomics tells us what appears to be happening (the instructions). But Proteomics and Metabolomics tell us what is actually happening.

Proteins are the functional units, and metabolites are the fuel and building blocks. Studying them gives us the closest view of the organism's phenotype.

13.2 Proteomics: The Mass Spec Revolution

Illustration of Mass Spectrometry

12.6 Modern Proteomics: DDA vs DIA and Quantification

Proteomics has matured with better instruments and computational workflows. Two dominant acquisition strategies exist:

  • DDA (Data-Dependent Acquisition): The instrument selects the most intense precursor ions for fragmentation. Historically common and supported by tools like MaxQuant.
  • DIA (Data-Independent Acquisition): Fragments all ions in predefined windows, improving reproducibility and depth of quantification. Tools: OpenSWATH, DIA-NN.

Key points for quantitative proteomics:

  • Spectral libraries vs library-free: DIA benefits from spectral libraries but modern tools (DIA-NN) can operate in library-free or predicted-library modes.
  • Label-free vs labeling approaches: TMT/iTRAQ allow multiplexing; label-free workflows scale more simply but require careful normalization.
  • Quality control: Monitor peptide identification rates, retention time stability, and coefficient of variation across replicates.

Recommended tools and pipelines:

  • MaxQuant for DDA identification and quantification.
  • DIA-NN, OpenSWATH for DIA analyses.
  • Use Perseus or MSstats for downstream statistical analysis and differential protein expression.

Practical advice:

  • Store raw files and spectral libraries in a structured archive and deposit them in PRIDE or MassIVE when publishing.
  • Include a clear description of search parameters, enzyme specificity, and false discovery rate (FDR) thresholds.

Unlike DNA, we cannot "sequence" proteins easily. Instead, we weigh them.

Mass Spectrometry (Mass Spec) is the workhorse of proteomics. 1. Digestion: Proteins are chopped into small peptides using enzymes like Trypsin. 2. Ionization: Peptides are given an electric charge and turned into gas. 3. Detection: The machine measures the Mass-to-Charge Ratio (m/z) of these peptides.

Bioinformatics software then takes these lists of masses and compares them against a database of known protein masses to identify which proteins are present.

13.3 Metabolomics: The Chemical Fingerprint

Metabolomics studies small molecules (sugars, lipids, amino acids, vitamins).

  • Targeted Metabolomics: Looking for a specific set of known compounds (e.g., "How much glucose is in this blood sample?").
  • Untargeted Metabolomics: Measuring everything to find new patterns (e.g., "What molecules are different in cancer patients vs healthy people?").

13.4 Bioinformatics in Action: Protein Analysis

While analyzing raw Mass Spec data requires specialized tools (like MaxQuant), we can use Biopython to analyze the properties of the proteins we identify.

Let's calculate the molecular weight and instability index of a protein sequence.

from Bio.SeqUtils.ProtParam import ProteinAnalysis

# A sample protein sequence (p53 partial)
protein_seq = "MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGP"

# Create an analysis object
analysed_seq = ProteinAnalysis(protein_seq)

# 1. Calculate Molecular Weight (in Daltons)
mw = analysed_seq.molecular_weight()

# 2. Calculate Isoelectric Point (pH where charge is 0)
pi = analysed_seq.isoelectric_point()

# 3. Calculate Amino Acid Percentages
aa_count = analysed_seq.get_amino_acids_percent()

print(f"Sequence Length: {len(protein_seq)}")
print(f"Molecular Weight: {mw:.2f} Da")
print(f"Isoelectric Point: {pi:.2f}")
print(f"Percent Leucine (L): {aa_count['L']:.1%}")

Output: 

Sequence Length: 60
Molecular Weight: 6793.46 Da
Isoelectric Point: 3.77
Percent Leucine (L): 13.3%

12.5 Pathway Analysis

Once we have a list of changed proteins or metabolites, we map them to Pathways.

  • KEGG (Kyoto Encyclopedia of Genes and Genomes): A database of metabolic pathways.
  • Reactome: A database of biological reactions.

If you find that "Glucose", "Pyruvate", and "ATP" are all elevated, pathway analysis will tell you that "Glycolysis" is upregulated.

Summary

Proteomics and Metabolomics use Mass Spectrometry to identify and quantify the functional molecules of the cell. Bioinformatics is used to identify these molecules from their mass fingerprints and map them to biological pathways to understand the cell's metabolic state.