Biology subjects

Kovaleva, V. A.

Publications and source records attributed to Kovaleva, V. A..

3 recordsLinked to original sources

bioRxiv2025

Pathogenic Fusarium verticillioides and Ophiostoma clavatum Associated with Ips acuminatus in Ukraine

Over the past two decades, dieback of Pinus sylvestris L. stands has increased across Europe, largely due to mass outbreaks of the bark beetle, in particular, Ips acuminatus Gyll. (Coleoptera: Curculionidae). This beetle causes mechanical damage and vectors pathogenic fungi, including ophiostomatoid species that induce blue-stain. Ophiostoma clavatum Math.-Kaarik is the most frequently reported fungal associate, yet its occurrence had not been documented in Ukraine. While ophiostomatoid fungi are well studied in pine pathogenesis, the role of fast-growing associates such as Fusarium spp., remains poorly understood. This study aimed to identify the dominant Ophiostoma and Fusarium species associated with I. acuminatus in western Ukraine and to evaluate their pathogenicity on pine seedlings. Isolates from beetle abdomens and blue-stained wood were identified as O. clavatum based on morphology and molecular markers (ITS, TUB, TEF1-). Pathogenicity tests showed that O. clavatum acts as a weak phytopathogen. The dominant Fusarium morphotype from blue-stained wood was identified as Fusarium verticillioides (Sac) Nirenberg, which induced necrosis and tissue maceration on pine seedlings. In dual culture, F. verticillioides displayed strong competitive dominance over O. clavatum. This study provides the first record of O. clavatum associated with I. acuminatus in Ukraine, extending its known European distribution. The observed pathogenicity and competitive ability of F. verticillioides suggest it may contribute to Scots pine decline, warranting further investigation.

plant biology↗

bioRxiv2023

Abundance of human T-cell epitopes in microbial proteomes

Molecular mimicry, the structural similarity between self and foreign antigens, is considered as a key factor in post-infectious autoimmunity. While certain examples of molecular mimicry are well studied, a comprehensive analysis of its prevalence and impact on the type of T cell response to such self is absent. In this work, we comprehensively studied the frequency of molecular mimicry between human and microbial T-cell epitopes. We performed an in silico analysis of the occurrence of T-cell epitopes originating from different sets of proteins: normal self epitopes, proteins involved in autoimmunity, and cancer neoantigens, in the proteomes of commensal and pathogenic microbiota. We show a significant overlap between repertoires of human T-cell epitopes and predicted epitopes from proteins of both commensal and pathogenic microbiota: the counterparts for over 90% of human HLA-I and 5% of HLA-II ligands were found in the microbial proteomes. HLA-II epitopes derived from the proteins involved in autoimmunity were more frequent in microbiota compared to normal self, suggesting a potential deleterious effect of molecular mimicry, while we did not observe this effect for HLA-I epitopes. Cancer epitopes were less frequent in microbiota compared to normal self of epitopes, implicating potential cancer escape from cross-reactive T cells specific to microbial antigens. Together, our results show that molecular mimicry might have a general pro-inflammatory effect on similar self epitopes, though much in this field remains to be explored.

immunology↗

bioRxiv2023

copepodTCR: Identification of Antigen-Specific T Cell Receptors with combinatorial peptide pooling

T cell receptor (TCR) repertoire diversity enables the antigen-specific immune responses against the vast space of possible pathogens. Identifying TCR-antigen binding pairs from the large TCR repertoire and antigen space is crucial for biomedical research. Here, we introduce copepodTCR, an open-access tool to design and interpret high-throughput experimental TCR specificity assays. copepodTCR implements a combinatorial peptide pooling scheme for efficient experimental testing of T cell responses against large overlapping peptide libraries, that can be used to identify the specificity of (or "deorphanize") TCRs. The scheme detects experimental errors and, coupled with a hierarchical Bayesian model for unbiased interpretation, identifies the response-eliciting peptide sequence for a TCR of interest out of hundreds of peptides tested using a simple experimental set-up. Using in silico simulations, we demonstrate the varied experimental settings in which copepodTCR yields efficient and interpretable TCR specificity results. We validated our approach on a library of 253 overlapping peptides covering the SARS-CoV-2 spike protein, split across 12 pools. A single stimulation with combinatorial pools identified the correct epitope of two TCRs with known specificity and then deorphanized two SARS-CoV-2 associated TCRs shared among a large cohort of COVID-19 patients. We provide experimental guides to efficiently design larger screens covering thousands of peptides which will be crucial to identify antigen-specific T cells and their targets from limited clinical material.

immunology↗