A primary human T-cell spectral library to facilitate large scale quantitative T-cell proteomics

Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples

Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of "false positives" as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced "false positive" identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of "true positive" identifications across each biological replicate by <6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.

Integrative temporal multi-omics reveals uncoupling of transcriptome and proteome during human T cell activation

Engagement of the T cell receptor (TCR) triggers molecular reprogramming leading to the acquisition of specialized effector functions by CD4 helper and CD8 cytotoxic T cells. While transcription factors, chemokines, and cytokines are known drivers in this process, the temporal proteomic and transcriptomic changes that regulate different stages of human primary T cell activation remain to be elucidated. Here, we report an integrative temporal proteomic and transcriptomic analysis of primary human CD4 and CD8 T cells following ex vivo stimulation with anti-CD3/CD28 beads, which revealed major transcriptome-proteome uncoupling. The early activation phase in both CD4 and CD8 T cells was associated with transient downregulation of the mRNA transcripts and protein of the central glucose transport GLUT1. In the proliferation phase, CD4 and CD8 T cells became transcriptionally more divergent while their proteome became more similar. In addition to the kinetics of proteome-transcriptome correlation, this study unveils selective transcriptional and translational metabolic reprogramming governing CD4 and CD8 T cell responses to TCR stimulation. This temporal transcriptome/proteome map of human T cell activation provides a reference map exploitable for future discovery of biomarkers and candidates targeting T cell responses.

Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape

The data-independent acquisition mass spectrometry (DIA-MS) has rapidly evolved as a powerful alternative for highly reproducible proteome profiling with a unique strength of generating permanent digital maps for retrospective analysis of biological systems. Recent advancements in data analysis software tools for the complex DIA-MS/MS spectra coupled to fast MS scanning speed and high mass accuracy have greatly expanded the sensitivity and coverage of DIA-based proteomics profiling. Here, we review the evolution of the DIA-MS techniques, from earlier proof-of-principle of parallel fragmentation of all-ions or ions in selected m/z range, the sequential window acquisition of all theoretical mass spectra (SWATH-MS) to latest innovations, recent development in computation algorithms for data informatics, and auxiliary tools and advanced instrumentation to enhance the performance of DIA-MS. We further summarize recent applications of DIA-MS and experimentally-derived as well as in silico spectra library resources for large-scale profiling to facilitate biomarker discovery and drug development in human diseases with emphasis on the proteomic profiling coverage. Toward next-generation DIA-MS for clinical proteomics, we outline the challenges in processing multi-dimensional DIA data set and large-scale clinical proteomics, and continuing need in higher profiling coverage and sensitivity.

Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas

The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available and reproducible. To demonstrate its utility, we reanalysed 10 public DIA datasets from the PRIDE database, comprising 1,278 SWATH-MS runs. The robustness of the analysis was evaluated, and the results compared to those obtained in the original publications. The final expression values were integrated into Expression Atlas, making SWATH-MS experiments more widely available and combining them with expression data originating from other proteomics and transcriptomics datasets.

Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research

Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.

A high-resolution mass spectrometry based proteomic dataset of human regulatory T cells

Regulatory T cells (Tregs) play a core role in maintaining immune tolerance, homeostasis, and host health. High-resolution analysis of the Treg proteome is required to identify enriched biological processes and pathways distinct to this important immune cell lineage. We present a comprehensive proteomic dataset of Tregs paired with conventional CD4⁺ (Conv CD4⁺) T cells in healthy individuals. Tregs and Conv CD4⁺ T cells were sorted to high purity using dual magnetic bead-based and flow cytometry-based methodologies. Proteins were trypsin-digested and analysed using label-free data-dependent acquisition mass spectrometry (DDA-MS) followed by label free quantitation (LFQ) proteomics analysis using MaxQuant software. Approximately 4,000 T cell proteins were identified with a 1% false discovery rate, of which approximately 2,800 proteins were consistently identified and quantified in all the samples. Finally, flow cytometry with a monoclonal antibody was used to validate the elevated abundance of the protein phosphatase CD148 in Tregs. This proteomic dataset serves as a reference point for future mechanistic and clinical T cell immunology and identifies receptors, processes, and pathways distinct to Tregs. Collectively, these data will lead to a better understanding of Treg immunophysiology and potentially reveal novel leads for therapeutics seeking Treg regulation.

Expression of CD49f defines subsets of human regulatory T cells with divergent transcriptional landscape and function that correlate with ulcerative colitis disease activity

Objective

Adoptive regulatory T cell (Treg) therapy is being trialled for the treatment of different autoimmune disorders, including inflammatory bowel diseases (IBD). In‐depth understanding of the biological variability of Treg in the human blood may be required to improve IBD immune monitoring and treatment strategies.

Methods

Through a combination of quantitative proteomic, multiparametric flow cytometry, RNA‐sequencing data analysis and functional assays on Treg enriched from the blood of ulcerative colitis (UC) patients and healthy controls, we investigated the association between CD49f expression, Treg phenotype and function, and UC disease activity.

Results

High‐dimensional analysis and filtering defined two distinct subsets of human Treg based on the presence or absence of CD49f with divergent transcriptional landscape and functional activities. CD49f negative (CD49f⁻) Treg are enriched for functional Treg markers and present significantly increased suppressive capacity. In contrast, CD49f^high Treg display a pro‐inflammatory Th17‐like phenotype and accumulate in the blood of patients with UC. Dysregulation on CD49f Treg subsets in patients with UC correlate with disease activity.

Conclusion

Overall, our findings uncover the importance of CD49f expression on Treg in physiological immunity and in pathological autoimmunity.