Introduction

Rheumatoid arthritis is an autoimmune disease with a 0.5-1% prevalence in developed countries. Currently, there is no cure and only treatment available, resulting in reduced life expectancy and quality of life. The disease mainly affects the joints, which makes it important to analyse those inflamed tissues for possible auto-antigens. Here, we focus on the characterization of the immunopeptidome, particularly on self-peptides presented on MHC class I or II that elicit an auto-immune response against synovial tissues.

However, synovial tissue is very elastic and thus difficult to dissociate, posing a challenge for efficiently isolating MHC-peptide complexes.

By combining efficient tissue digestion, high recovery, and multi-level sample preparation protocols with optimized methods for acquisition and data analysis of liquid chromatography mass spectrometry, we present a workflow enabling in-depth characterization of synovial tissue on both the immunopeptidome and proteome levels.

Methods

70-160 mg of synovial tissue was mechanically disintegrated and lysed by physical forces and a mild detergent. 1/10 of the lysate was digested by FASP for whole proteomics analysis. The remainder of the sample was used for sequential immunoprecipitation, including a blank, an HLA-DR, and a pan-MHC class I immunoaffinity enrichment. Peptides were eluted under acidic conditions, cleaned with a 10 kD MWCO filter, and desalted on an Oasis HLB plate. The MWCO filter retentate (enriched MHC proteins) and an aliquot of the unbound fraction depleted of MHC proteins were subjected to FASP digestion. This resulted in four different sample types derived from each tissue sample.

Immunopeptides were analyzed using a previously optimized ion mobility enhanced data-dependent acquisition (Thunder-DDA-PASEF) with adjusted fragmentation isolation polygons respective to each MHC class. Peptide search was performed in PEAKS.

Proteome samples were measured on an Orbitrap Exploris 480 in data-independent mode for high reproducibility and processed in DIANN.

Preliminary results

Our optimized sample preparation and LC-MS workflow allows the identification of more than 1,000 MHC-bound peptides from 100 mg synovial tissue, increasing sensitivity by approximately 100-fold compared to previous studies requiring 10 g of synovial tissue.to reach a similar coverage. Using the established multi-level workflow, we can additionally infer knowledge from the tissue to the identified immunopeptides and vice versa. We can also assess the quality of the immunoprecipitation due to the filter retained fraction, and the relative composition of HLA proteins which can be used to evaluate differences on their expression. This workflow enables the identification of auto-immunopeptides that can be either targeted for therapy or provide information on the development and onset of rheumatoid arthritis.