RESUMO
Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.
RESUMO
BACKGROUND: Early in the pandemic, we designed a SARS-CoV-2 peptide vaccine containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation. The rationale for this design was to drive both humoral and cellular immunity with high specificity while avoiding undesired effects such as antibody-dependent enhancement (ADE). METHODS: We explored the set of computationally predicted SARS-CoV-2 HLA-I and HLA-II ligands, examining protein source, concurrent human/murine coverage, and population coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, sequence conservation, source protein abundance, and coverage of high frequency HLA alleles. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering for surface accessibility, sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. RESULTS: From 58 initial candidates, three B cell epitope regions were identified. From 3730 (MHC-I) and 5045 (MHC-II) candidate ligands, 292 CD8+ and 284 CD4+ T cell epitopes were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we proposed a set of 22 SARS-CoV-2 vaccine peptides for use in subsequent murine studies. We curated a dataset of ~ 1000 observed T cell epitopes from convalescent COVID-19 patients across eight studies, showing 8/15 recurrent epitope regions to overlap with at least one of our candidate peptides. Of the 22 candidate vaccine peptides, 16 (n = 10 T cell epitope optimized; n = 6 B cell epitope optimized) were manually selected to decrease their degree of sequence overlap and then synthesized. The immunogenicity of the synthesized vaccine peptides was validated using ELISpot and ELISA following murine vaccination. Strong T cell responses were observed in 7/10 T cell epitope optimized peptides following vaccination. Humoral responses were deficient, likely due to the unrestricted conformational space inhabited by linear vaccine peptides. CONCLUSIONS: Overall, we find our selection process and vaccine formulation to be appropriate for identifying T cell epitopes and eliciting T cell responses against those epitopes. Further studies are needed to optimize prediction and induction of B cell responses, as well as study the protective capacity of predicted T and B cell epitopes.
Assuntos
Vacinas contra COVID-19/administração & dosagem , COVID-19/prevenção & controle , Biologia Computacional/métodos , Epitopos de Linfócito B/química , Epitopos de Linfócito T/química , Sequência de Aminoácidos , Animais , COVID-19/virologia , Vacinas contra COVID-19/química , Epitopos de Linfócito B/imunologia , Epitopos de Linfócito T/imunologia , Feminino , Antígenos de Histocompatibilidade Classe I/química , Antígenos de Histocompatibilidade Classe I/metabolismo , Antígenos de Histocompatibilidade Classe II/química , Antígenos de Histocompatibilidade Classe II/metabolismo , Humanos , Masculino , Camundongos , Camundongos Endogâmicos BALB C , Peptídeos/química , Peptídeos/imunologia , SARS-CoV-2/isolamento & purificação , SARS-CoV-2/metabolismo , Glicoproteína da Espícula de Coronavírus/química , Glicoproteína da Espícula de Coronavírus/imunologiaRESUMO
There is an urgent need for a vaccine with efficacy against SARS-CoV-2. We hypothesize that peptide vaccines containing epitope regions optimized for concurrent B cell, CD4+ T cell, and CD8+ T cell stimulation would drive both humoral and cellular immunity with high specificity, potentially avoiding undesired effects such as antibody-dependent enhancement (ADE). Additionally, such vaccines can be rapidly manufactured in a distributed manner. In this study, we combine computational prediction of T cell epitopes, recently published B cell epitope mapping studies, and epitope accessibility to select candidate peptide vaccines for SARS-CoV-2. We begin with an exploration of the space of possible T cell epitopes in SARS-CoV-2 with interrogation of predicted HLA-I and HLA-II ligands, overlap between predicted ligands, protein source, as well as concurrent human/murine coverage. Beyond MHC affinity, T cell vaccine candidates were further refined by predicted immunogenicity, viral source protein abundance, sequence conservation, coverage of high frequency HLA alleles and co-localization of CD4+ and CD8+ T cell epitopes. B cell epitope regions were chosen from linear epitope mapping studies of convalescent patient serum, followed by filtering to select regions with surface accessibility, high sequence conservation, spatial localization near functional domains of the spike glycoprotein, and avoidance of glycosylation sites. From 58 initial candidates, three B cell epitope regions were identified. By combining these B cell and T cell analyses, as well as a manufacturability heuristic, we propose a set of SARS-CoV-2 vaccine peptides for use in subsequent murine studies and clinical trials.
RESUMO
A system for accurate low-volume delivery of liquids in the micro- to nanoliter range makes use of an integrated miniature flow sensor as part of an intelligent feedback control loop driving a micro-solenoid valve. The flow sensor is hydraulically connected with the pressurized system liquid in the dispensing channel and located downstream from the pressure source, above the solenoid valve. The sensor operates in a differential mode and responds in real-time to the internal flow-pulse resulting from the brief opening interval of the solenoid valve leading to a rapid ejection of a fluid droplet. The integral of the flow-pulse delivered by the sensor is directly proportional to the volume of the ejected droplet from the nozzle. The quantitative information is utilized to provide active control of the effectively dispensed or aspirated volume by adjusting the solenoid valve accordingly. This process significantly enhances the precision of the fluid delivery. The system furthermore compensates automatically for any changes in the viscosity of the dispensed liquid. The data delivered by the flow sensor can be saved and backtracked in order to confirm and validate the aspiration and dispensing process in its entirety. The collected dispense information can be used for quality control assessments and automatically be made part of an electronic record.