Biology subjects

Poran, A.

Publications and source records attributed to Poran, A..

6 recordsLinked to original sources

bioRxiv2026

Comprehensive Profiling of Monkeypox Virus Antigens Identifies Potent Targets for Next-Generation mRNA Vaccine Development

The 2022 Monkeypox virus (MPXV) outbreak renewed interest in vaccines for orthopoxviruses. Initial development efforts focused on well-established antigen targets, especially A35, B6, and M1. However, orthopoxvirus surfaces are complex, displaying many antigens across two infectious forms, mature virions (MV) and extracellular virions (EV) and targets relevant to protection remain to be comprehensively defined. We leveraged advances in orthopoxvirus protein biology and mRNA vaccine technology to compare immunity to all feasible targets. Mice were immunized with mRNAs encoding each antigen, or antigen complex, and neutralizing antibody responses were measured prior to heterologous challenge with vaccinia virus. Among MV antigens, A28 induced potent complement-mediated neutralizing antibodies, and the A17:G10 complex induced neutralizing antibodies and protected from challenge. For EV antigens, A36 induced neutralizing antibodies and protected from challenge. Our results affirm the consensus strategy focusing on key antigens while highlighting additional targets that could enhance updated MPXV mRNA vaccines. SIGNIFICANCEMonkeypox virus, a member of the Orthopoxvirus genus along with variola virus, has been associated with two recent outbreaks of mpox disease leading to a renewed focus on orthopoxvirus vaccine development. We report an agnostic screen of all monkeypox virus surface antigens where we combined recent advances in structural biology and mRNA technology to evaluate these potential new vaccine targets. We confirmed that historically prioritized antigens M1, A35 and B6 were protective but also discovered new antigens of interest including A28, the A17:G10 complex and A36 that can be the targets of protective immune responses. These findings are critical to inform next-generation vaccine designs should novel orthopoxviruses emerge as human pathogens.

microbiology↗

bioRxiv2022

Progressive loss of conserved spike protein neutralizing antibody sites in Omicron sublineages is balanced by preserved T-cell recognition epitopes

The continued evolution of the SARS-CoV-2 Omicron variant has led to the emergence of numerous sublineages with different patterns of evasion from neutralizing antibodies. We investigated neutralizing activity in immune sera from individuals vaccinated with SARS-CoV-2 wild-type spike (S) glycoprotein-based COVID-19 mRNA vaccines after subsequent breakthrough infection with Omicron BA.1, BA.2, or BA.4/BA.5 to study antibody responses against sublineages of high relevance. We report that exposure of vaccinated individuals to infections with Omicron sublineages, and especially with BA.4/BA.5, results in a boost of Omicron BA.4.6, BF.7, BQ.1.1, and BA.2.75 neutralization, but does not efficiently boost neutralization of sublineages BA.2.75.2 and XBB. Accordingly, we found in in silico analyses that with occurrence of the Omicron lineage a large portion of neutralizing B-cell epitopes were lost, and that in Omicron BA.2.75.2 and XBB less than 12% of the wild-type strain epitopes are conserved. In contrast, HLA class I and class II presented T-cell epitopes in the S glycoprotein were highly conserved across the entire evolution of SARS-CoV-2 including Alpha, Beta, and Delta and Omicron sublineages, suggesting that CD8+ and CD4+ T-cell recognition of Omicron BQ.1.1, BA.2.75.2, and XBB may be largely intact. Our study suggests that while some Omicron sublineages effectively evade B-cell immunity by altering neutralizing antibody epitopes, S protein-specific T-cell immunity, due to the very nature of the polymorphic cell-mediated immune, response is likely to remain unimpacted and may continue to contribute to prevention or limitation of severe COVID-19 manifestation.

immunology↗

bioRxiv2021

Early Computational Detection of Potential High Risk SARS-CoV-2 Variants

The ongoing COVID-19 pandemic is leading to the discovery of hundreds of novel SARS-CoV-2 variants on a daily basis. While most variants do not impact the course of the pandemic, some variants pose a significantly increased risk when the acquired mutations allow better evasion of antibody neutralisation in previously infected or vaccinated subjects or increased transmissibility. Early detection of such high risk variants (HRVs) is paramount for the proper management of the pandemic. However, experimental assays to determine immune evasion and transmissibility characteristics of new variants are resource-intensive and time-consuming, potentially leading to delays in appropriate responses by decision makers. Here we present a novel in silico approach combining spike (S) protein structure modelling and large protein transformer language models on S protein sequences to accurately rank SARS-CoV-2 variants for immune escape and fitness potential. These metrics can be combined into an automated Early Warning System (EWS) capable of evaluating new variants in minutes and risk-monitoring variant lineages in near real-time. The system accurately pinpoints the putatively dangerous variants by selecting on average less than 0.3% of the novel variants each week. With only the S protein nucleotide sequence as input, the EWS detects HRVs earlier and with better precision than baseline metrics such as the growth metric (which requires real-world observations) or random sampling. Notably, Omicron BA.1 was flagged by the EWS on the day its sequence was made available. Additionally, our immune escape and fitness metrics were experimentally validated using in vitro pseudovirus-based virus neutralisation test (pVNT) assays and binding assays. The EWS flagged as potentially dangerous all 16 variants (Alpha-Omicron BA.1/2/4/5) designated by the World Health Organisation (WHO) with an average lead time of more than one and a half months ahead of them being designated as such. One-Sentence SummaryA COVID-19 Early Warning System combining structural modelling with machine learning to detect and monitor high risk SARS-CoV-2 variants, identifying all 16 WHO designated variants on average more than one and a half months in advance by selecting on average less than 0.3% of the weekly novel variants.

bioinformatics↗

bioRxiv2020

High resolution mouse subventricular zone stem cell niche transcriptomereveals features of lineage, anatomy, and aging

Adult neural stem cells (NSC) serve as a reservoir for brain plasticity and origin for certain gliomas. Lineage tracing and genomic approaches have portrayed complex underlying heterogeneity within the major anatomical location for NSC, the subventricular zone (SVZ). To gain a comprehensive profile of NSC heterogeneity, we utilized a well validated stem/progenitor specific reporter transgene in concert with single cell RNA sequencing to achieve unbiased analysis of SVZ cells from infancy to advanced age. The magnitude and high specificity of the resulting transcriptional data sets allow precise identification of the varied cell types embedded in the SVZ including specialized parenchymal cells (neurons, glia, microglia), and non-central nervous system cells (endothelial, immune). Initial mining of the data delineates four quiescent NSC and three progenitor cell subpopulations formed in a linear progression. Further evidence indicates that distinct stem and progenitor populations reside in different regions of the SVZ. As stem/progenitor populations progress from neonatal to advanced age, they acquire a deficiency in transition from quiescence to proliferation. Further data mining identifies stage specific biological processes, transcription factor networks, and cell surface markers for investigation of cellular identities, lineage relationships, and key regulatory pathways in adult NSC maintenance and neurogenesis. Significance StatementAdult neural stem cells (NSC) are closely related to multiple neurological disorders and brain tumors. Comprehensive investigation of their composition, lineage, and aging will provide new insights that may lead to enhanced patient treatment. This study applies a novel transgene to label and manipulate neural stem/progenitor cells, and monitor their evolution during aging. Together with high-throughput single cell RNA sequencing, we are able to analyze the subventricular zone (SVZ) cells from infancy to advanced age with unprecedented granularity. Diverse new cell states are identified in the stem cell niche, and an aging related NSC deficiency in transition from quiescence to proliferation is identified. The related biological features provide rich resources to inspect adult NSC maintenance and neurogenesis.

neuroscience↗

bioRxiv2020

Sequence-based prediction of vaccine targets for inducing T cell responses to SARS-CoV-2 utilizing the bioinformatics predictor RECON

BackgroundThe ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Consistent with observations for SARS-CoV, a closely related coronavirus responsible for the 2003 SARS outbreak, early reports identify a protective role for both humoral and cell-mediated immunity for SARS CoV-2. MethodsIn this study, we leveraged HLA-I and HLA-II T cell epitope prediction tools from RECON(R) (Real-time Epitope Computation for ONcology), our bioinformatic pipeline that was developed using proteomic profiling of individual HLA-I and HLA-II alleles to predict rules for peptide binding to a diverse set of such alleles. We applied these binding predictors to viral genomes from the Coronaviridae family, and specifically to identify SARS-CoV-2 T cell epitopes. ResultsTo test the suitability of these tools to identify viral T cell epitopes, we first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then use our HLA-I and HLA-II predictors to identify 11,776 HLA-I and 7,991 HLA-II candidate binding peptides across all 12 open reading frames (ORFs) of SARS-CoV-2. This extensive list of identified candidate peptides is driven by the length of the ORFs and the significant number of HLA-I and HLA-II alleles that we are able to predict (74 and 83, respectively), providing over 99% coverage for the US, European and Asian populations, for both HLA-I and HLA-II. From our SARS-CoV-2 predicted peptide-HLA-I allele pairs, 368 pairs identically matched previously reported pairs in the ViPR database, originating from other forms of coronaviruses. 320 of these pairs (89.1%) had a positive MHC-binding assay result. This analysis reinforces the validity our predictions. ConclusionsUsing this bioinformatic platform, we identify multiple putative epitopes for CD4+ and CD8+ T cells whose HLA binding properties cover nearly the entire population and thus may be effective when included in prophylactic vaccines against SARS-CoV-2 to induce broad cellular immunity.

bioinformatics↗

bioRxiv2018

Generation of pulmonary neuro-endocrine cells and tumors resembling small cell lung cancers from human embryonic stem cells

SUMMARYBy blocking an important signaling pathway (called NOTCH) and interfering with expression of two tumor suppressor genes in cells derived from human embryonic stem cells, the authors have developed a model for studying highly lethal small cell lung cancers.\n\nABSTRACTCell culture models based on directed differentiation of human embryonic stem cells (hESCs) may reveal why certain constellations of genetic changes drive carcinogenesis in specialized human cell lineages. Here we demonstrate that up to 10 percent of lung progenitor cells derived from hESCs can be induced to form pulmonary neuroendocrine cells (PNECs), the putative normal precursors to small cell lung cancers (SCLCs), by inhibition of NOTCH signaling. By using small inhibitory RNAs in these cultures to reduce levels of retinoblastoma (RB) protein, the product of a gene commonly mutated in SCLCs, we can significantly expand the number of PNECs. Similarly reducing levels of TP53 protein, the product of another tumor suppressor gene commonly mutated in SCLCs, or expressing mutant KRAS or EGFR genes, did not induce or expand PNECs, consistent with lineage-specific sensitivity to loss of RB function. Tumors resembling early stage SCLC grew in immunodeficient mice after subcutaneous injection of PNEC-containing cultures in which expression of both RB and TP53 was blocked. Single-cell RNA profiles of PNECs are heterogeneous; when RB levels are reduced, the profiles show similarities to RNA profiles from early stage SCLC; when both RB and TP53 levels are reduced, the transcriptome is enriched with cell cycle-specific RNAs. Taken together, these findings suggest that genetic manipulation of hESC-derived pulmonary cells will enable studies of the initiation, progression, and treatment of this recalcitrant cancer.

cancer biology↗