Modern mass spectrometers used in proteomics and metabolomics are hybrid instruments that incorporate multiple mass spectrometry (MS) units. Typically, these include two quadrupoles (Q1 and Q2) followed by a final mass detector, which can be another quadrupole, an Orbitrap, or a time-of-flight (TOF) detector. The configuration allows for the selection of specific masses for fragmentation before detection.
Precursor Ion Scan (MS1):
Q1 is set to select a broad mass range (e.g., 400 m/z for peptides).
Q2 has gas off, allowing detection of intact peptides.
Fragment Ion Scan (MS2):
Q1 selects a narrower mass range.
Q2 collides selected peptides with inert gas to induce fragmentation before detection.
Data Dependent Acquisition (DDA):
The scan sequence adapts based on detected data, leading to variability in scans across runs.
Targeted DDA uses an inclusion list to monitor specific peptides, while untargeted DDA collects data based on the most abundant precursor ions.
Data Independent Acquisition (DIA):
The scan sequence remains constant regardless of detected data.
Targeted DIA methods include Selected Reaction Monitoring (SRM) and Parallel Reaction Monitoring (PRM), focusing on predefined masses.
Untargeted DIA (SWATH) fragments larger mass ranges to capture all peptides of interest.
Initial Scan: Q1 is set to a wide mass range to capture all peptides.
Comparison: The mass spectrometer compares detected ions to the inclusion list.
Fragmentation: Matches are selected for fragmentation in Q2, and the process is repeated for all identified precursors.
Similar to targeted DDA but focuses on the most abundant precursor signals without a predefined list, leading to a stochastic identification process.
Repeated analyses of the same sample yield different protein identifications, with diminishing returns in unique identifications over multiple runs.
This overview highlights the operational principles and methodologies of hybrid mass spectrometers in proteomics and metabolomics, emphasizing the differences between DDA and DIA approaches
DDA (Data-Dependent Acquisition): Analyzing mass spectrometry (MS/MS) data to identify peptides.
Peptide Spectral Matching: Identifying peptides from MS/MS spectra.
Database Search: Compare experimental spectra to theoretical spectra from a genomic database.
Spectral Library Search: Compare to a library of previously identified spectra.
De Novo: Analyze fragment spectra to deduce amino acid sequences.
Statistical Validation:
Target-Decoy Approach:
Search for real peptides and shuffled (decoy) sequences.
Determine False Discovery Rate (FDR) using distributions of target and decoy hits.
Protein Inference:
Compute protein and peptide FDR separately.
Tools: Protein Prophet, Mayu.
Quantification:
Quantify identified peptides and proteins.
MaxQuant: Comprehensive tool for all analysis steps.
Various academic and commercial software available for each step.
A 1% peptide FDR typically corresponds to a higher protein FDR.