Proteomics Analysis

Workflow Overview

Input: MS Proteomics Data
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Phase 1: Data Import & QC
Phase 2: Preprocessing (filter, impute, normalize)
Phase 3: Differential Expression Analysis
Phase 4: PTM Analysis (if applicable)
Phase 5: Functional Enrichment (GO, KEGG, Reactome)
Phase 6: Protein-Protein Interactions (STRING networks)
Phase 7: Multi-Omics Integration (optional, protein-RNA correlation)
Phase 8: Generate Report

See PHASE_DETAILS.md for detailed procedures per phase.

Integration with ToolUniverse

Quantified Minimums

• At least 500 proteins quantified (human: 3,000+ is reasonable; 10,000+ is deep coverage)
• At least 3 biological replicates per condition (non-negotiable for reliable statistics)
• Filter to proteins with 2+ unique peptides (single-peptide IDs are not reported as DE)
• Statistical test: limma or t-test with Benjamini-Hochberg multiple testing correction
• Pathway enrichment: at least one method (GO, KEGG, or Reactome)
• Report must include: QC summary, DE results with volcano plot, pathway analysis, visualizations

Interpretation Framework

Starting Point: Experimental Design

Quantitative proteomics compares protein abundance. LOOK UP DON'T GUESS — always verify the experimental method, platform, and replicate count before choosing an analysis strategy.

Quantification strategy decision tree:

• Cell culture, high accuracy needed → SILAC (ratios within same MS run, most accurate, but culture-only)
• Multiple conditions, multiplexing needed → TMT/iTRAQ (up to 18-plex in one run; TMM/VSN normalization; beware ratio compression artifact that reduces observed fold-changes)
• Discovery study, flexible design → Label-free (LFQ) (intensity-based; median/quantile normalization; more missing values; wider dynamic range)
• Replicates: n < 3 = unreliable fold changes (variance cannot be estimated). Minimum n = 3 biological replicates; n >= 4 preferred for clinical samples. Never report significance from duplicates.
• FDR cutoff: Benjamini-Hochberg correction mandatory. FDR < 0.05 standard; FDR < 0.01 stringent. Never report unadjusted p-values alone.

Protein Identification Reasoning

Protein identification from MS data follows a logical chain. LOOK UP DON'T GUESS — search UniProt and STRING for protein annotation rather than inferring function from name alone.

1. Peptide mass fingerprinting (PMF): Intact protein digested → measured peptide masses compared against theoretical digest of all database proteins. A match requires >=4 peptides covering >=15% of the protein sequence. Single-peptide hits are unreliable (could match multiple proteins).
2. Tandem MS (MS/MS): Fragment ion spectra matched to peptide sequences via search engines (Andromeda, SEQUEST, X!Tandem). Each peptide-spectrum match (PSM) scored; only PSMs above FDR threshold count. Unique peptides (mapping to one protein) are essential — shared peptides cannot distinguish between protein isoforms.
3. Protein inference: Multiple peptides → protein groups. When peptides are shared between homologs, report the protein group (not individual proteins). Use proteins_api_search or uniprot_search_proteins to resolve ambiguous protein groups.
4. Coverage matters: 2+ unique peptides is the minimum for a confident protein ID. Proteins identified by a single unique peptide should be flagged as tentative.

Post-Translational Modification (PTM) Analysis Reasoning

PTMs (phosphorylation, ubiquitination, acetylation, glycosylation) add biological complexity beyond protein abundance.

1. Site localization: A phospho-site is confidently localized only if the localization probability > 0.75 (MaxQuant) or ptmRS score > 75 (Proteome Discoverer). Ambiguous sites should not be reported as specific residue modifications.
2. Enrichment is required: Without phospho-enrichment (TiO2, IMAC), only the most abundant phosphopeptides are detected (~1% of phosphoproteome). An absence of a phospho-site in non-enriched data does not mean it is absent biologically.
3. Kinase prediction: If phospho-sites are identified, predict upstream kinases using motif analysis. Cross-reference with OpenTargets_get_target_safety_profile_by_ensemblID for kinase-disease associations. LOOK UP kinase-substrate relationships in PhosphoSitePlus rather than guessing from sequence motif alone.
4. Stoichiometry: A protein can be 5% or 95% phosphorylated at a given site — this matters enormously for function but is hard to measure. Report whether data supports stoichiometry estimation or only site identification.

Differential Expression Thresholds

• Strong: padj < 0.01, FC > 2.0, ≥5 unique peptides, <20% missing
• Moderate: padj 0.01-0.05, FC 1.5-2.0, 2-5 peptides, 20-50% missing
• Weak/unreliable: padj 0.05-0.1, FC 1.2-1.5, 1-2 peptides (single-peptide proteins are unreliable), >50% missing (imputation needed)

Evidence Grading

• T1: Validated by orthogonal method (Western blot, PRM) + functional study
• T2: Significant DE (padj < 0.05, FC > 1.5) in 2+ biological replicates
• T3: Significant DE in 1 experiment, or significant but low FC
• T4: Identified but not quantified, or single peptide identification

Synthesis Questions

1. How many proteins are differentially expressed? (>500 DE proteins suggests global perturbation; <50 suggests targeted effect)
2. Are key pathway proteins concordantly regulated? (all subunits of a complex changing = high confidence)
3. Do proteomics results correlate with transcriptomics? (low correlation is common — post-translational regulation)
4. Are PTM changes driving the phenotype? (check phosphoproteomics if available)
5. What is the coverage relative to the expected proteome? (human: ~10K quantified is good; <3K is limited)

Limitations

• Platform-specific: Optimized for MS-based proteomics (not Western blot quantification)
• Missing values: High missing rate (>50% per protein) limits statistical power
• PTM analysis: Requires enrichment protocols for comprehensive PTM profiling
• Absolute quantification: Relative abundance only (unless TMT/SILAC used)
• Protein isoforms: Typically collapsed to gene level
• Dynamic range: MS has limited dynamic range vs mRNA sequencing

References

Methods: MaxQuant (doi:10.1038/nbt.1511), Limma for proteomics (doi:10.1093/nar/gkv007), DEP workflow (doi:10.1038/nprot.2018.107)

Databases: STRING, PhosphoSitePlus, CORUM

Reference Files

• PHASE_DETAILS.md - Detailed procedures for each analysis phase, including report template