Proteomics and MALDI Bioinformatics

One-Sentence Definition

Proteomics and MALDI bioinformatics analyze mass-spectrometry signals to identify microorganisms and quantify their proteins.

Simple Explanation

Mass spectrometry weighs molecules; software turns those weights into “this is Staphylococcus aureus” or “this protein went up threefold.”

Detailed Scientific Explanation

Two related worlds:

  1. MALDI-TOF species ID (clinical routine) — whole-cell spectra of abundant ribosomal proteins matched against a reference spectral library; score thresholds decide genus/species confidence. Limits: closely related species (e.g., Shigella/E. coli, some streptococci), database coverage, extraction method.
  2. Shotgun proteomics (research) — protein digest → LC-MS/MS → spectra matched to a predicted proteome from Genome Annotation → FDR control via target-decoy → quantification (label-free, TMT).

Emerging: machine learning on raw spectra for resistance detection (e.g., carbapenemase-related peaks, MRSA-related profiles) — see AI Diagnostics in Microbiology.

Mechanism

Peak picking and alignment → similarity scoring against reference spectra or in silico peptide fragmentation matching.

Clinical Importance

  • MALDI-TOF collapsed identification time from ~24 h to minutes; a major driver of faster targeted therapy and stewardship

Research Importance

  • Post-transcriptional regulation, PTMs, secretomes, host–pathogen interfaces

Diagnostic Relevance

AMR Relevance

  • Spectral ML for resistance prediction; direct detection of hydrolysis products for β-lactamase activity assays

Active Recall Questions

  1. Which proteins dominate MALDI-TOF species spectra?
  2. Name two species pairs MALDI struggles to separate.
  3. What is target-decoy FDR in proteomics?

Connections