Biology subjects

Luksza, M.

Publications and source records attributed to Luksza, M..

7 recordsLinked to original sources

bioRxiv2024

T cell epitope mapping reveals immunodominance of evolutionarily conserved regions within SARS-CoV-2 proteome.

As SARS-CoV-2 variants continue to emerge capable of evading neutralizing antibodies, it has become increasingly important to fully understand the breadth and functional profile of T cell responses to determine their impact on the immune surveillance of variant strains. Here, sampling healthy individuals, we profiled the kinetics and polyfunctionality of T cell immunity elicited by mRNA vaccination. Modeling of anti-spike T cell responses against ancestral and variant strains of SARS-CoV-2 suggested that epitope immunodominance and cross-reactivity are major predictive determinants of T cell immunity. To identify immunodominant epitopes across the viral proteome, we generated a comprehensive map of CD4+ and CD8+ T cell epitopes within non-spike proteins that induced polyfunctional T cell responses in convalescent patients. We found that immunodominant epitopes mainly resided within regions that were minimally disrupted by mutations in emerging variants. Conservation analysis across historical human coronaviruses combined with in silico alanine scanning mutagenesis of non-spike proteins underscored the functional importance of mutationally-constrained immunodominant regions. Collectively, these findings identify immunodominant T cell epitopes across the mutationally-constrained SARS-CoV-2 proteome, potentially providing immune surveillance against emerging variants, and inform the design of next-generation vaccines targeting antigens throughout SARS-CoV-2 proteome for broader and more durable protection. One Sentence SummaryPolyfunctional CD8+ and CD4+ T cells directed against SARS-CoV-2 target mutationally constrained regions of the viral proteome.

immunology↗

bioRxiv2024

Energy landscapes of peptide-MHC binding

Molecules of the Major Histocompatibility Complex (MHC) present short protein fragments peptides on the cell surface, an important step in T cell immune recognition. MHC-I molecules process peptides from intracellular proteins; MHC-II molecules act in antigen-presenting cells and present peptides derived from extracellular proteins. Here we show that the sequence-dependent energy landscapes of MHC-peptide binding encode class-specific nonlinearities (epistasis). MHC-I has a smooth landscape with global epistasis; the binding energy is a simple deformation of an underlying linear trait. This form of epistasis enhances the discrimination between strong-binding peptides. In contrast, MHC-II has a rugged landscape with idiosyncratic epistasis: binding depends on detailed amino acid combinations at multiple positions of the peptide sequence. The form of epistasis affects the learning of energy landscapes from training data. For MHC-I, a low-complexity problem, we derive a simple matrix model of binding energies that outperforms current models trained by machine learning. For MHC-II, higher complexity prevents learning by simple regression methods. Epistasis also affects the energy and fitness effects of mutations in antigen-derived peptides (epitopes). In MHC-I, large-effect mutations occur predominantly in anchor positions of strong-binding epitopes. In MHC-II, large effects depend on the background epitope sequence but are broadly distributed over the epitope, generating a bigger target for escape mutations from T cell immunity than for MHC-I. Author SummaryT cell immunity involves the binding of short peptides to the intracellular MHC recognition machinery. Understanding how the binding energy depends on the peptide sequence is key to computationally predict immune recognition and immune escape evolution, for example, of pathogens and cancer cells. We find nonlinear energy landscapes that depend on the recognition pathway: smooth and easy to learn for MHC class I, rugged and difficult to learn for class II. Together, this work establishes links between biophysical origin, nonlinear structure, learnability from data, and biological implications for protein interaction landscapes.

biophysics↗

bioRxiv2022

Vaccination shapes evolutionary trajectories of SARS-CoV-2

The large-scale evolution of the SARS-CoV-2 virus has been marked by rapid turnover of genetic clades. New variants show intrinsic changes, notably increased transmissibility, as well as anti-genic changes that reduce the cross-immunity induced by previous infections or vaccinations1-4. How this functional variation shapes the global evolutionary dynamics has remained unclear. Here we show that selection induced by vaccination impacts on the recent antigenic evolution of SARS-CoV-2; other relevant forces include intrinsic selection and antigenic selection induced by previous infections. We obtain these results from a fitness model with intrinsic and antigenic fitness components. To infer model parameters, we combine time-resolved sequence data5, epidemiological records6,7, and cross-neutralisation assays8-10. This model accurately captures the large-scale evolutionary dynamics of SARS-CoV-2 in multiple geographical regions. In particular, it quantifies how recent vaccinations and infections affect the speed of frequency shifts between viral variants. Our results show that timely neutralisation data can be harvested to identify hotspots of antigenic selection and to predict the impact of vaccination on viral evolution.

biophysics↗

bioRxiv2022

Integrative Analysis of Checkpoint Blockade Response in Advanced Non-Small Cell Lung Cancer

Anti-PD-1/PD-L1 agents have transformed the treatment landscape of advanced non-small cell lung cancer (NSCLC). While our understanding of the biology underlying immune checkpoint blockade in NSCLC is still incomplete, studies to date have established predictive roles for PD-L1 tumor expression and tumor mutational burden (TMB). To expand our understanding of the molecular features underlying response to checkpoint inhibitors in NSCLC, we describe here the first joint analysis of the Stand Up 2 Cancer - Mark Foundation (SU2C-MARK) Cohort, a resource of whole exome and/or RNA sequencing from 393 patients with NSCLC treated with anti-PD-(L)1 therapy, along with matched clinical response annotation. We identify a number of associations between molecular features and outcome, including: 1) favorable (e.g., ATM altered), and unfavorable (e.g., TERT amplified) genomic subgroups, 2) distinct immune infiltration signatures associated with wound healing (unfavorable) and immune activation (favorable), and 3) a novel de-differentiated tumor-intrinsic subtype characterized by expression of endodermal lineage genes, immune activation, and enhanced response rate. Taken together, results from this cohort extend our understanding of NSCLC-specific predictors, providing a rich set of molecular and immunologic hypotheses with which to further our understanding of the biology of checkpoint blockade in NSCLC.

genomics↗

bioRxiv2021

Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer

Although cancer immunotherapy with PD-(L)1 blockade is now routine treatment for patients with lung cancer, remarkably little is known about acquired resistance. We examined 1,201 patients with NSCLC treated with PD-(L)1 blockade to clinically characterize acquired resistance, finding it to be common (occurring in more than 60% of initial responders), with persistent but diminishing risk over time, and with distinct metastatic and survival patterns compared to primary resistance. To examine the molecular phenotype and potential mechanisms of acquired resistance, we performed whole transcriptome and exome tumor profiling in a subset of NSCLC patients (n=29) with acquired resistance. Systematic immunogenomic analysis revealed that tumors with acquired resistance generally had enriched signals of inflammation (including IFN{gamma} signaling and inferred CD8+ T cells) and could be separated into IFN{gamma} upregulated and stable subsets. IFN{gamma} upregulated tumors had putative routes of resistance with signatures of dysfunctional interferon signaling and mutations in antigen presentation genes. Transcriptomic profiling of cancer cells from a murine model of acquired resistance to PD-(L)1 blockade also showed evidence of dysfunctional interferon signaling and acquired insensitivity to in vitro interferon gamma treatment. In summary, we characterized clinical and molecular features of acquired resistance to PD-(L)1 blockade in NSCLC and found evidence of ongoing but dysfunctional IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance informs therapeutic strategies to effectively reprogram and reverse acquired resistance.

cancer biology↗

bioRxiv2021

Diversity and selection of SARS-CoV-2 minority variants in the early New York City outbreak

High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCEWhen viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.

microbiology↗

bioRxiv2018

Clonal competition in B-cell repertoires during chronic HIV-1 infection

During chronic infection, HIV-1 engages in a rapid coevolutionary arms race with the hosts adaptive immune system. While it is clear that HIV exerts strong selection on the adaptive immune system, the characteristics of the somatic evolution that shape the immune response are still unknown. Traditional population genetics methods fail to distinguish chronic immune response from healthy repertoire evolution. Here, we infer the evolutionary modes of B-cell repertoires and identify complex dynamics with a constant production of better B-cell receptor mutants that compete, maintaining large clonal diversity and potentially slowing down adaptation. A substantial fraction of mutations that rise to high frequencies in pathogen engaging CDRs of B-cell receptors (BCRs) are beneficial, in contrast to many such changes in structurally relevant frameworks that are deleterious and circulate by hitchhiking. We identify a pattern where BCRs in patients who experience larger viral expansions undergo stronger selection with a rapid turnover of beneficial mutations due to clonal interference in their CDR3 regions. Using population genetics modeling, we show that the extinction of these beneficial mutations can be attributed to the rise of competing beneficial alleles and clonal interference. The picture is of a dynamic repertoire, where better clones may be outcompeted by new mutants before they fix.

immunology↗