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Deciphering Mycobacterium tuberculosis glycan epitopes through clustering of human polyclonal and isolating novel monoclonal antibodies I

ABSTRACT: The immunomodulatory mycobacterial surface antigen lipoarabinomannan (LAM) with its immunogenic glycan component arabinomannan (AM) facilitates Mycobacterium tuberculosis’ (Mtb) escape from the host’s immune response. Some but not all antibodies against AM can protect against TB. To better understand which of AM’s structures to target, we must first identify the spectrum of its epitopes. We here used synthetic AM oligosaccharide motifs to deplete sera from subjects along the spectrum of Mtb infection. Performing cluster analysis, we were able to predict AM’s immunogenic structures and delineate how antibody reactivity to them is influenced by Mtb infection states.

ORGANISM(S): synthetic construct Homo sapiens

PROVIDER: GSE263496 | GEO | 2024/06/01

REPOSITORIES: GEO

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Project description:Infection or reactivation with human cytomegalovirus (HCMV) is still a major cause of morbidity and mortality in patients undergoing solid organ transplantation or allogeneic stem cell transplantation (alloSCT). Recent studies have shown that protection against latent HCMV infection relies on a much broader antigen spectrum than previously expected. The identification of novel immunogenic HCMV-derived peptides that facilitate HCMV control is therefore essential to improve immune monitoring of HCMV-specific T cells and HCMV vaccine development. In particular, only a few HCMV-derived peptides have been described for less common HLA alleles, such as HLA-A*03:01 and HLA-B*15:01, limiting the implementation of these techniques for a substantial number of patients. Here, we identified novel HCMV-derived HLA-A*03:01- and HLA-B*15:01-restricted immunogenic peptides by an innovative combined in vitro and in silico approach. We utilized the computational tools Peptide-PRISM (1) and PRICE (2) to analyze mass spectrometric (MS) and ribosome sequencing (ribo-seq) datasets, respectively. To refine our in silico approach, we utilized machine learning to rate the identified peptide candidates based on their translational activity, binding affinity and positioning within the small open reading frames (sORFs), with the goal of assessing their likelihood to be presented on HLA-A*03:01 and HLA-B*15:01 molecules. After identifying the highest-scoring 49 canonical and 49 cryptic potentially immunogenic peptides for each HLA allele, we assessed their immunogenicity by screening HCMV-seropositive and -seronegative healthy donors, as well as alloSCT patients for their peptide-specific T-cell responses. We used a stimulation procedure in two consecutive steps: peripheral blood cells (PBMCs) were stimulated starting with peptide pools and subsequently with potentially reactive single peptides. In vitro T-cell stimulation resulted in the direct identification of three canonical and one cryptic HLA-A*03-restricted immunogenic peptides as well as five canonical and one cryptic HLA-B*15-restricted immunogenic peptide, with a specific IFNγ+/CD8+ T cell response of ≥ 0.02%. Highest T-cell responses were identified against two HLA-A*03-restricted and three HLA-B*15-restricted canonical peptides with up to 3.42% of IFNγ+/CD8+ T cells in patients 180 days post alloSCT. In conclusion, we identified specific T-cell responses against eight canonical and two cryptic HLA-A*03:01- and HLA-B*15:01-restricted peptides in healthy individuals and post-transplanted patients and which were classified as immunogenic. Of these, six peptides are novel HCMV-derived, immunogenic peptides according to the UniProt database, broadening the spectrum of immunogenic HCMV-derived peptides for personalized immune monitoring and vaccine development.

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Deciphering Mycobacterium tuberculosis glycan epitopes through clustering of human polyclonal and isolating novel monoclonal antibodies I

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