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Kolosenko, I.

Publications and source records attributed to Kolosenko, I..

3 recordsLinked to original sources

Characterization of HLA-DR immunopeptidome of bronchoalveolar lavage cells in patients with newly diagnosed rheumatoid arthritis and healthy current-smoker controls

Evidence suggests that self-tolerance is breached in the lung prior to the clinical onset of rheumatoid arthritis (RA) in the joints. The human leukocyte antigen DR (HLA-DR) shared epitope (SE) represents the strongest genetic risk factor for sero-positive RA. However, to our knowledge, the HLA-DR immunopeptidome of the RA lung and its link to HLA-DR genotype has not been investigated to date. The objective of this study was to optimize the methods for characterizing the HLA-DR immunopeptidome of lung immune cells and apply it to newly diagnosed RA patients versus current-smoker healthy controls, as well as to investigate the connection with the HLA-DR genotype. The HLA-DR immunopeptidome method was improved to facilitate characterization from as few as 6 million bronchoalveolar lavage (BAL) cells per subject, consisting primarily of alveolar macrophages. This method was applied to newly diagnosed RA patients naive to treatment (n=9, LURA cohort), as well as healthy current-smoker controls (n=10, COSMIC cohort). For five of the RA patients, a 6-month follow-up after initiation of the standard-of-care treatment regime was also included. After isolation and purification, peptide samples were separated by nano-flow liquid chromatography coupled to an Orbitrap mass spectrometer equipped with ion mobility device (FAIMS). Mass spectra acquired in data dependent acquisition mode were then searched against a human proteome database. Subsequently, the identified peptides were deconvoluted to their predicted binding HLA-DR allele using MHCMotifDecon based on the sequenced genotype of the individual. An optimized sample preparation and analytic method enabled the detection of over 23,000 peptides from over 3,000 source proteins with between 1,000 and 5,000 peptides identified per sample. Notably, the application of FAIMS with three compensation voltages allowed for efficient transfer of 2+, 3+, and 4+ peptide ions while removing singly charged background ions. Hierarchical clustering revealed that the immunopeptidome was more driven by the HLA-DR genotype than by RA disease or sex. However, since the HLA-DR genotype is a strong risk factor for RA, these results are convoluted. When deconvoluting the peptides to their predicted binding allele, the HLA-DRB1 alleles *01:01, *04:01, *04:04, *04:05, *04:07, and *10:01 were consistently assigned more peptides than other alleles. Except for *04:07 these alleles belong to the SE risk factor alleles, providing a potential explanation between HLA-SE and RA pathogenesis. Native peptides from known citrullinated and non-modified RA autoantigens (such as -enolase and calreticulin) were detected and validated as binders in prediction algorithms. No significant differences were found between base line and follow-up (post-treatment) samples from RA patients. Taken together, this data characterizes the HLA-DR immunopeptidome in the lung of early RA in an unprecedented manner, which together with future immunogenicity studies will help our understanding of the connection between the lung and the pathogenesis of RA. Finally, more peptides predicted to bind to SE alleles and *04:07 compared to other alleles demands further study on the relative expression of HLA-DR alleles and presentation mechanisms to understand the implications for RA.

immunology↗

microRNA and non-targeted proteome analysis of liquid biopsies from the distal lung collected by Particles in Exhaled Air (PExA) reveals presence from extracellular vesicles

Background. Early detection and longitudinal follow-up are essential for timely diagnosis and treatment for lung diseases. Currently, invasive methods are often required to examine the distal parts of the lungs. The growing need to explore the bio-molecular mechanisms in various lung diseases highlights the importance of non-invasive methods. The use of particles in exhaled air (PExA), a non-invasive technique for sampling of epithelial lining fluid from distal airways, is gaining attention. MicroRNAs (miRNAs) are crucial in modulating protein expression both intracellularly and intercellularly, often transported via extracellular vesicles. Dysregulated miRNAs have been linked to many pulmonary diseases, and their relative stability, especially when encapsulated in EVs, makes them promising biomarkers. Here we report for the first time multi-modal analysis of miRNAs and proteins in PExA, offering an opportunity to study the role of miRNAs in the pathophysiology of respiratory diseases in a non-invasive manner. Methods. Exhaled particles were collected from healthy subjects using the PExA 2.0 instrument utilizing the optimized PExA breathing maneuver. PExA samples collected on different types of impaction membranes were analyzed using a non-targeted mass spectrometry-based proteomics workflow optimized for single-cell detection, and a miRNAseq workflow optimized for low input starting material. Technical validation of a subset of the detected miRNAs was performed using custom-designed miRCURY LNA miRNA PCR assays. Pathway enrichment analyses for the detected proteins were performed using STRING. Results. Proteomic analysis consistently identified over 50 proteins across multiple types of impaction membranes, sample dilution series, and individuals down to a single PEx sPOT (24ng starting material). We observed a significant enrichment of proteins associated with extracellular vesicles, including blood microparticles, and secretory granules. miRNA-seq revealed 39 mature miRNAs, the majority of which have been previously reported to be detected in the airways. Some were also reported to be secreted by primary human airway epithelial cells via extracellular vesicles. miRNA-125b and the members of the let-7 family were among the most abundant miRNAs detected. Fluorometric assays showed significant RNase activity in both PExA and other lung-related samples, such as bronchoalveolar lavage fluid, suggesting that this activity originates from the airways and is independent of the sampling techniques used. The workflow for extraction and processing of the PExA collection membrane, tested with abundant synthetic miRNAs and analyzed using the miRCURY LNA miRNA PCR assay, yielded results comparable to control samples, indicating that the membrane material does not interfere with the assay. Conclusions. Using PExA, we identified several miRNAs reported to be dysregulated in pulmonary disorders. The enrichment of extracellular secretory components in the core protein list, along with the elevated RNAse activity in the respiratory tract, suggest that the detected miRNAs may be encapsulated within extracellular vesicles. These miRNAs are of particular interest due to their potential role in intercellular communication. Our findings suggest that PExA holds a potential as a non-invasive tool for studying extracellular vesicle-mediated miRNA cargo in the small airways.

physiology↗

CORACLE (COVID-19 liteRAture CompiLEr): A platform for efficient tracking and extraction of SARS-CoV-2 and COVID-19 literature, with examples from post-COVID with respiratory involvement

BackgroundDuring the COVID-19 pandemic there emerged a need to efficiently monitor and process large volumes of scientific literature on the subject. Currently, as the pandemic is winding down, the clinicians encountered a novel syndrome - Post-acute Sequelae of COVID- 19 (PASC) - that affects over 10% of those who contract SARS-CoV-2 and presents a significant and growing challenge in the medical field. The continuous influx of new research publications underscores a critical need for efficient tools for navigating the literature. ObjectivesWe aimed to develop an application which will allow monitoring and categorizing COVID-19-related literature through building publication networks and medical subject headings (MeSH) maps to be able to quickly identify key publications and publication networks. MethodsWe introduce CORACLE (COVID-19 liteRAture CompiLEr), an innovative web application designed for the analysis of COVID-19-related scientific articles and the identification of research trends. CORACLE features three primary interfaces: The "Search" interface, which displays research trends and citation links; the "Citation Map" interface, allowing users to create tailored citation networks from PubMed Identifiers (PMIDs) to uncover common references among selected articles; and the "MeSH" interface, highlighting current MeSH trends and associations between MeSH terms. ResultsOur web application, CORACLE, leverages regularly updated PubMed data to aggregate and categorize the extensive literature on COVID-19 and PASC, aiding in the identification of relevant research publication hubs. Using lung function in PASC patients as a search example, we demonstrate how to identify and visualize the interactions between the relevant publications. ConclusionCORACLE proves to be an effective tool for the extraction and analysis of literature. Its functionalities, including the MeSH trends and customizable citation mapping, facilitate the discovery of relevant information and emerging trends in COVID-19 and PASC research.

bioinformatics↗