Biology subjects

Buckley, P.

Publications and source records attributed to Buckley, P..

6 recordsLinked to original sources

bioRxiv2023

Sequence independent activity of a predicted long disordered segment of the human papillomavirus L2 capsid protein during virus entry

The papillomavirus L2 capsid protein protrudes through the endosome membrane into the cytoplasm during virus entry to bind cellular factors required for intracellular virus trafficking. Cytoplasmic protrusion of HPV16 L2, virus trafficking, and infectivity are inhibited by large deletions in an [~]110 amino acid segment of L2 that is predicted to be disordered. The activity of these mutants can be restored by inserting protein segments with diverse compositions and chemical properties into this region, including scrambled sequences, a tandem array of a short sequence, and the intrinsically disordered region of a cellular protein. The infectivity of mutants with small in-frame insertions and deletions in this segment directly correlates with the size of the segment. These results indicate that the length of the disordered segment, not its sequence or its composition, determines its activity during virus entry. Sequence independent but length dependent activity has important implications for protein function and evolution.

biochemistry↗

bioRxiv2021

HLA-dependent variation in SARS-CoV-2 CD8+ T cell cross-reactivity with human coronaviruses

Pre-existing T cell immunity to SARS-CoV-2 in individuals without prior exposure to SARS-CoV-2 has been reported in several studies. While emerging evidence hints toward prior exposure to common-cold human coronaviruses (HCoV), the extent of- and conditions for-cross-protective immunity between SARS-CoV-2 and HCoVs remain open. Here, by leveraging a comprehensive pool of publicly available functionally evaluated SARS-CoV-2 peptides, we report 126 immunogenic SARS-CoV-2 peptides with high sequence similarity to 285 MHC-presented target peptides from at least one of four HCoV, thus providing a map describing the landscape of SARS-CoV-2 shared and private immunogenic peptides with functionally validated T cell responses. Using this map, we show that while SARS-CoV-2 immunogenic peptides in general exhibit higher level of dissimilarity to both self-proteome and -microbiomes, there exist several SARS-CoV-2 immunogenic peptides with high similarity to various human protein coding genes, some of which have been reported to have elevated expression in severe COVID-19 patients. We then combine our map with a SARS-CoV-2-specific TCR repertoire data from COVID-19 patients and healthy controls and show that whereas the public repertoire for the majority of convalescent patients are dominated by TCRs cognate to private SARS-CoV-2 peptides, for a subset of patients, more than 50% of their public repertoires that show reactivity to SARS-CoV-2, consist of TCRs cognate to shared SARS-CoV-2-HCoV peptides. Further analyses suggest that the skewed distribution of TCRs cognate to shared and private peptides in COVID-19 patients is likely to be HLA-dependent. Finally, by utilising the global prevalence of HLA alleles, we provide 10 peptides with known cognate TCRs that are conserved across SARS-CoV-2 and multiple human coronaviruses and are predicted to be recognised by a high proportion of the global population. Overall, our work indicates the potential for HCoV-SARS-CoV-2 reactive CD8+ T cells, which is likely dependent on differences in HLA-coding genes among individuals. These findings may have important implications for COVID-19 heterogeneity and vaccine-induced immune responses as well as robustness of immunity to SARS-CoV-2 and its variants.

immunology↗

bioRxiv2020

Evaluating performance of existing computational models in predicting CD8+ T cell pathogenic epitopes and cancer neoantigens

T cell recognition of a cognate peptide-MHC complex (pMHC) presented on the surface of infected or malignant cells, is of utmost importance for mediating robust and long-term immune responses. Accurate predictions of cognate pMHC targets for T Cell Receptors (TCR) would greatly facilitate identification of vaccine targets for both pathogenic diseases as well as personalized cancer immunotherapies. Predicting immunogenic peptides therefore has been at the centre of intensive research for the past decades but has proven challenging. Although numerous models have been proposed, performance of these models has not been systematically evaluated and their success rate in predicting epitopes in the context of human pathology, has not been measured and compared. In this study, we evaluated the performance of several publicly available models, in identifying immunogenic CD8+ T cell targets in the context of pathogens and cancers. We found that for predicting immunogenic peptides from an emerging virus such as SARS-CoV-2, none of the models perform substantially better than random or offer considerable improvement beyond HLA ligand prediction. We also observed suboptimal performance for predicting cancer neoantigens. Through investigation of potential factors associated with ill performance of models, we highlight several data- and model-associated issues. In particular, we observed that cross-HLA variation in the distribution of immunogenic and non-immunogenic peptides in training data of the models seem to substantially confound the predictions. We additionally compared key parameters associated with immunogenicity between pathogenic peptides and cancer neoantigens and observed evidence for differences in the thresholds of binding affinity and stability, which suggested the need to modulate different features in identifying immunogenic pathogen vs. cancer peptides. Overall, we demonstrate that accurate and reliable prediction of immunogenic CD8+ T cell targets remains unsolved, thus we hope our work will guide users and model developers regarding potential pitfalls and unsettled questions in existing immunogenicity predictors.

immunology↗

bioRxiv2020

CD8+ T cell cross-reactivity against SARS-CoV-2 conferred by other coronavirus strains and influenza virus

While individuals infected with coronavirus disease 2019 (COVID-19) manifested a broad range in susceptibility and severity to the disease, the pre-existing immune memory of related pathogens can influence the disease outcome. Here, we investigated the potential extent of T cell cross-reactivity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that can be conferred by other coronaviruses and influenza virus, and generated a map of public and private predicted CD8+ T cell epitopes between coronaviruses. Moreover, to assess the potential risk of self-reactivity and/or diminished T cell response for peptides identical or highly similar to the host, we identified predicted epitopes with high sequence similarity with human proteome. Lastly, we compared predicted epitopes from coronaviruses with epitopes from influenza virus deposited in IEDB to support vaccine development against different virus strains. We believe the comprehensive in silico profile of private and public predicted epitopes across coronaviruses and influenza viruses will facilitate design of vaccines capable of protecting against various viral infections.

immunology↗

bioRxiv2020

TRM Integrins CD103 and CD49a Differentially Support Adherence and Motility After Resolution of Influenza Virus Infection

Tissue resident memory CD8 T (TRM) cells are a unique immune memory subset that develops and remains in peripheral tissues at the site of infection, providing future host resistance upon re-exposure to that pathogen. In the pulmonary system, TRM are identified through S1P antagonist CD69 and expression of integrins CD103/{beta}7 and CD49a/CD29({beta}1). Contrary to the established role of CD69 on CD8 T cells, the functions of CD103 and CD49a on this population are not well defined. This study examines the expression patterns and functions of CD103 and CD49a with a specific focus on their impact on T cell motility during influenza virus infection. We show that the TRM cell surface phenotype develops by two-weeks post-infection and that each integrin contributes a distinct function regulating CD8 T cell motility both in vitro and in vivo, with CD49a facilitating migration and CD103 limiting motility through tethering. These results demonstrate for the first time how CD103 and CD49a differentially impact adherence and migration in the tissue, likely affecting overall retention, maintenance of TRM, and host protection. Significance StatementCurrent influenza vaccination strategies require annual immunizations, with fairly low efficacy rates. One technique to improve protection against a greater breadth of influenza viruses is to elicit broadly cross-reactive cell-mediated immunity and generate a local population of cytotoxic T cells to respond to conserved regions of circulating viruses. However, this approach requires improved understanding of how these cells migrate within and attach to the tissue, in order to persist and offer long-term immunity. This study investigates how receptors on the T cell surface impact the cells ability to interact with the tissue and provide evidence for which of these receptors are essential for protection. Furthermore, these studies reveal functional in vivo mechanisms of cellular markers used to characterize TRM.

immunology↗

bioRxiv2017

Common variants of NRXN1, LRP1B and RORA are associated with increased ventricular volumes in psychosis - GWAS findings from the B-SNIP deep phenotyping study

Schizophrenia, Schizoaffective, and Bipolar Disorders share common illness traits, intermediate phenotypes and a partially overlapping polygenic basis. We performed GWAS on deep phenotyping data, including structural MRI and DTI, clinical, and behavioral scales from 1,115 cases and controls. Significant associations were observed with two cerebrospinal fluid volumes: the temporal horn of left lateral ventricle was associated with NRXN1, and the volume of the cavum septum pellucidum was associated with LRP1B and RORA. Both volumes were associated with illness. Suggestive associations were observed with local gyrification indices, fractional anisotropy and age at onset. The deep phenotyping approach allowed unexpected genetic sharing to be found between phenotypes, including temporal horn of left lateral ventricle and age at onset.

genetics↗