Sensitive Immunopeptidomics by Leveraging Available Large-Scale Multi-HLA Spectral Libraries, Data-Independent Acquisition, and MS/MS Prediction

Autor: Brian Stevenson, Michal Bassani-Sternberg, George Coukos, Florian Huber, Chloe Chong, Markus Müller, HuiSong Pak, Justine Michaux
Jazyk: angličtina
Rok vydání: 2021
Předmět:
False discovery rate
RT
retention time
Proteomics
FDR
false discovery rate
Computer science
DIA
data-independent acquisition
Peptide Fingerprints
Human leukocyte antigen
Computational biology
Computer Simulation
Histocompatibility Antigens
Peptide Library
Peptides
Proteomics/methods
Tandem Mass Spectrometry
DDA
DIA
HLA
HLA binding prediction
LC-MS
antigen discovery
immunopeptidomics
in silico MS/MS spectra predictions
Biochemistry
Analytical Chemistry
03 medical and health sciences
Special Issue: Immunopeptidomics
PRM
parallel reaction monitoring
MS/MS
tandem MS
Data-independent acquisition
Molecular Biology
030304 developmental biology
0303 health sciences
AGC
automatic gain control
HLA
human leukocyte antigen
030302 biochemistry & molecular biology
Technological Innovation and Resources
iRT
index retention time
Tumor associated antigen
DDA
data-dependent MS/MS acquisition
TAAs
tumor-associated antigens
Scale (map)
Retention time
PSM
peptide spectrum match
Zdroj: Molecular & cellular proteomics, vol. 20, pp. 100080
Molecular & Cellular Proteomics : MCP
Popis: Mass spectrometry (MS) is the state-of-the-art methodology for capturing the breadth and depth of the immunopeptidome across human leukocyte antigen (HLA) allotypes and cell types. The majority of studies in the immunopeptidomics field are discovery driven. Hence, data-dependent tandem MS (MS/MS) acquisition (DDA) is widely used, as it generates high-quality references of peptide fingerprints. However, DDA suffers from the stochastic selection of abundant ions that impairs sensitivity and reproducibility. In contrast, in data-independent acquisition (DIA), the systematic fragmentation and acquisition of all fragment ions within given isolation m/z windows yield a comprehensive map for a given sample. However, many DIA approaches commonly require generating comprehensive DDA-based spectrum libraries, which can become impractical for studying noncanonical and personalized neoantigens. Because the amount of HLA peptides eluted from biological samples such as small tissue biopsies is typically not sufficient for acquiring both meaningful DDA data necessary for generating comprehensive spectral libraries and DIA MS measurements, the implementation of DIA in the immunopeptidomics translational research domain has remained limited. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy by matching DIA data against libraries with growing complexity—from sample-specific libraries to libraries combining 2 to 40 different immunopeptidomics samples. Analyzing DIA immunopeptidomics data against a complex multi-HLA spectral library resulted in a two-fold increase in peptide identification compared with sample-specific library and in a three-fold increase compared with DDA measurements, yet with no detrimental effect on the specificity. Furthermore, we demonstrated the implementation of DIA for sensitive personalized neoantigen discovery through the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands. We conclude that a comprehensive multi-HLA library for DIA approach in combination with MS/MS prediction is highly advantageous for clinical immunopeptidomics, especially when low amounts of biological samples are available.
Graphical Abstract
Highlights • So far, DIA in the immunopeptidomics translational research has been limited. • DIA immunopeptidomics data were analyzed against a complex multi-HLA spectral library. • This resulted in improved sensitivity with no detrimental effect on the specificity. • We implemented DIA for clinical antigen discovery combined with predicted MS/MS spectra.
In Brief The implementation of DIA in the immunopeptidomics translational research domain has remained limited because the amount of HLA peptides eluted from clinical samples is typically not sufficient for acquiring both meaningful DDA data for generating comprehensive spectral libraries and DIA MS measurements. We implemented a DIA immunopeptidomics workflow and assessed its sensitivity and accuracy with libraries of growing complexity and multi-HLA libraries. In addition, we demonstrated the analysis of DIA data with predicted MS/MS spectra of clinically relevant HLA ligands.
Databáze: OpenAIRE
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