SnapShot: Clinical Proteomics – Key Vocabulary

Clinical Specimen Types for MS-Based Proteomics

• Liquid biopsies (most used)

  • Plasma / Serum

  • Proteome dynamic range > 10^{10}; major analytical challenge.

  • High-abundance proteins (e.g., ALB, IgG) often depleted before MS.

  • Circulating extracellular vesicles (EVs)

  • Enriched from blood; provide concentrated, cell-type-specific cargo.

  • Urine, cerebrospinal fluid (CSF), saliva, tears, ascites, feces-derived microbiome.

• Solid & semi-solid specimens

  • FFPE (formalin-fixed paraffin-embedded) tissues

  • Most common archival clinical material; require de-waxing (xylene/heat) and de-crosslinking (≥60 °C, SDS, sonication).

  • Fresh-frozen (FF) tissues

  • Bone (demineralization step).

  • Hair & nails (alkalinization before extraction).

  • Tumor sections, single tumor cells, immune cells, RBCs, WBCs.

  • LCM (laser-capture microdissected) regions → preserve spatial context.

  • Flow-sorted cells → minute populations (10–1,000 cells).

Specimen Preparation Workflow (Generalized)

• Mechanical / chemical disruption

  • Grinding, sonication, PCT (pressure cycling: 45 s cycles @ 0.014 kpsi).

  • Centrifugation to clear debris.

• Protein extraction & clean-up

  • Cold acetone precipitation or SDS lysis → remove lipids, salts.

  • Depletion of high-abundance plasma proteins.

  • SEC to separate complexes & enrich low-molecular-weight species.

  • Ultracentrifugation under alkaline pH for IMPs enrichment.

  • Immunoprecipitation (IP) for specific targets / complexes.

• Protein processing

  • Denaturation (urea, SDS, heat) → unfolds protein.

  • Reduction (DTT/TCEP) breaks \text{–S–S–} bonds → \text{–SH}.

  • Alkylation (IAA) caps \text{–SH} to prevent re-oxidation.

  • Enzymatic digestion

  • Trypsin (K/R cleavage), Lys-C, or multi-enzyme cocktails.

  • Formats: in-solution, in-gel, FASP, SP3, iST, PCT-assisted.

• Optional peptide-level steps

  • PTM enrichment (phospho-TiO$_2$, glyco-HILIC, etc.).

  • Isobaric labeling (TMT = tandem mass tags) for multiplex DDA.

  • Chromatographic fractionation: basic RP (bRP), SCX, high-pH RP.

  • Desalting on C18 cartridges / StageTips.

Streamlined / Automated Preparation Platforms

• FASP (Filter-Aided Sample Preparation): membrane-based cleanup & digestion.

• SP3 (Single-Pot, Solid-Phase-Enhanced Sample Prep): paramagnetic beads bind proteins → minimal loss; ideal for low input.

• iST (in-StageTip) automated liquid-handling system; optimized for plasma.

• PCT workflow: semi-automated, high-yield, <2 h for mg- to µg-level tissue.

Liquid Chromatography (LC) Front-Ends

• Nano-flow LC: \approx 0.3 µL/min; highest sensitivity; lower throughput.

• Evosep One: 0.1{-}3 µL/min; pre-formed gradients; hundreds of runs/day.

• Micro-flow LC: 1{-}50 µL/min → balance between robustness & sensitivity.

• High-flow LC: \approx 0.8 mL/min; supports ultra-fast gradients (e.g., <5 min).

• Short gradients (as low as 5{-}15 min) feasible with modern columns (id 0.75 µm–1 mm) and fast MS duty cycles.

Mass Spectrometry Acquisition Modes

• Data-Dependent Acquisition (DDA)

  • Top-N or intensity-based precursor selection; coupled with TMT for multiplexing.

  • Orbitrap or TOF detectors record MS1 + targeted MS2 spectra.

• Targeted MS

  • SRM/MRM (triple quadrupole Q1\to Q2\to Q3), PRM (high-res full-scan MS2 in Orbitrap).

  • Absolute quantification using AQUA peptides; linear ranges \sim 10^4–10^5.

• Data-Independent Acquisition (DIA)

  • Systematically fragments all ions in sequential m/z windows (e.g., SWATH).

  • Generates 4-D data cubes: m/z (precursor) × m/z (fragment) × RT × Intensity.

  • diaPASEF (parallel accumulation-serial fragmentation with trapped ion mobility) adds a drift-time dimension → boosts sensitivity & selectivity.

  • Scanning SWATH further accelerates duty cycle for ultra-fast acquisitions.

Ion-Mobility Enhancements

• Drift gas-based separation prior to MS2.

• Reduces spectral congestion; improves PTM localization & low-abundance detection.

Data Processing & Interpretation

• Search engines (DDA): MaxQuant, MSFragger, pFind.

• Targeted data analysis: Skyline (SRM/PRM), Spectronaut (DIA), OpenSWATH, DIA-NN.

• Quality control → retention-time (RT) alignment, intensity normalization.

• Downstream analytics

  • Statistical testing (ANOVA, LIMMA), false-discovery rate (FDR <1\%).

  • Network analysis (protein–protein interactions, pathway enrichment).

  • Machine learning for biomarker discovery; deep learning to demultiplex DIA spectra.

Precision Medicine Applications

• Correlating protein abundance, PTM status, complex composition with clinical phenotypes (disease stage, drug response).

• Robustness

  • FFPE, plasma, and body-fluid proteomes show high technical reproducibility.

  • Single-cell proteomics now attainable (hundreds–thousands of proteins/cell).

• Comprehensive views

  • Access to proteoforms, PTMs, structural states, and complex stoichiometries.

Key Numerical & Technical Highlights

• Dynamic range challenge: >10 orders (plasma).

• LC flow-rate options: 0.1 µL/min – 0.8 mL/min.

• Sample throughput: hundreds of proteomes/day/instrument with modern setups.

• PCT pressure: 0.014 kpsi cycling; digestion <1 h possible.

• diaPASEF adds ion mobility resolution \sim 1/K$_0$ dimension.

Ethical & Commercial Notes

• Authors hold equity in Westlake Omics, Biognosys AG, Evosep Biosystems.

• Proteomics datasets inform diagnostics but must respect patient privacy & regulatory frameworks.

Representative Abbreviations

• FFPE, FF, PCT, FASP, SP3, iST, PTM, SEC, SCX, bRP, SRM/MRM, PRM, DIA/SWATH, AQUA, PASEF.

Reference Landmarks

• Gillet et al. 2012: conceptualized DIA.

• Bache et al. 2018: Evosep LC innovation.

• Bian et al. 2020; Messner et al. 2021: high-throughput, micro/high-flow proteomics.

• Hughes et al. 2019: SP3 protocol.

• Meier et al. 2020: diaPASEF.

• Guo et al. 2015: PCT tissue pipeline.