Biology subjects

Castro Dopico, X.

Publications and source records attributed to Castro Dopico, X..

5 recordsLinked to original sources

bioRxiv2025

Isolation of genetically diverse influenza antibodies highlights the role of IG germline gene variation and informs the design of population-comprehensive vaccine strategies

The regular emergence of influenza strains with pandemic potential creates a strong incentive to develop vaccines that stimulate protective responses across all human populations. A critical consideration is how variation in the human immunoglobulin (IG) loci influences B cell recognition of viral epitopes and elicitation of neutralizing antibodies. Here, we applied personalized IG germline genotyping and high-throughput sequencing of paired antibody chains from influenza A virus hemagglutinin (HA)-binding B cells to demonstrate that the response to HA is highly individual. We show that a germline-encoded polymorphism in IGHV2-70 alters the functionality of the LPAF-a class of neutralizing antibodies, and we describe HA stem-targeting broadly neutralizing antibodies (bNAbs) that use germline IGHV genes other than the population-restricted IGHV genes used by many previously known stem bNAbs. Our results demonstrate that the approach used here can be used to discover and avert population vulnerabilities arising from IG gene variation when designing HA-based influenza vaccines aimed for the global human population.

immunology↗

bioRxiv2024

Antigen affinity and site of immunization dictate B cell recall responses

Protective antibodies against HIV-1 require unusually high levels of somatic hypermutations (SHMs) introduced in germinal centers (GCs). To achieve this, a sequential vaccination approach was proposed. Using HIV-1 antibody knock-in mice with fate-mapping genes, we examined if antigen affinity affects the outcome of the B cell recall response. Compared to high affinity boost, low affinity boost resulted in decreased numbers of memory-derived B cells in secondary GCs, but with higher average SHM, indicating an affinity threshold for memory B cells to enter secondary GCs. Upon boosting local LNs, numbers of residual GC B cells increased independent on antigen affinity, while average SHM decreased. Our results demonstrate that antigen affinity and location of the boost affect the outcome of the B cell recall response. These results can help guide the design of vaccine immunogens aiming to selectively engage specific B cell clones for further SHM diversification.

immunology↗

bioRxiv2022

A semi-supervised Bayesian mixture modelling approach for joint batch correction and classification

AO_SCPLOWBSTRACTC_SCPLOWSystematic differences between batches of samples present significant challenges when analysing biological data. Such batch effects are well-studied and are liable to occur in any setting where multiple batches are assayed. Many existing methods for accounting for these have focused on high-dimensional data such as RNA-seq and have assumptions that reflect this. Here we focus on batch-correction in low-dimensional classification problems. We propose a semi-supervised Bayesian generative classifier based on mixture models that jointly predicts class labels and models batch effects. Our model allows observations to be probabilistically assigned to classes in a way that incorporates uncertainty arising from batch effects. By simultaneously inferring the classification and the batch-correction our method is more robust to dependence between batch and class than pre-processing steps such as ComBat. We explore two choices for the within-class densities: the multivariate normal and the multivariate t. A simulation study demonstrates that our method performs well compared to popular off-the-shelf machine learning methods and is also quick; performing 15,000 iterations on a dataset of 750 samples with 2 measurements each in 11.7 seconds for the MVN mixture model and 14.7 seconds for the MVT mixture model. We further validate our model on gene expression data where cell type (class) is known and simulate batch effects. We apply our model to two datasets generated using the enzyme-linked immunosorbent assay (ELISA), a spectrophotometric assay often used to screen for antibodies. The examples we consider were collected in 2020 and measure seropositivity for SARS-CoV-2. We use our model to estimate seroprevalence in the populations studied. We implement the models in C++ using a Metropolis-within-Gibbs algorithm, available in the R package batchmix. Scripts to recreate our analysis are at https://github.com/stcolema/BatchClassifierPaper.

bioinformatics↗

bioRxiv2021

Variable loss of antibody potency against SARS-CoV-2 B.1.1.529 (Omicron)

The recently-emerged SARS-CoV-2 B.1.1.529 variant (Omicron) is spreading rapidly in many countries, with a spike that is highly diverged from the pandemic founder, raising fears that it may evade neutralizing antibody responses. We cloned the Omicron spike from a diagnostic sample which allowed us to rapidly establish an Omicron pseudotyped virus neutralization assay, sharing initial neutralization results only 13 days after the variant was first reported to the WHO, 8 days after receiving the sample. Here we show that Omicron is substantially resistant to neutralization by several monoclonal antibodies that form part of clinical cocktails. Further, we find neutralizing antibody responses in pooled reference sera sampled shortly after infection or vaccination are substantially less potent against Omicron, with neutralizing antibody titers reduced by up to 45 fold compared to those for the pandemic founder. Similarly, in a cohort of convalescent sera prior to vaccination, neutralization of Omicron was low to undetectable. However, in recent samples from two cohorts from Stockholm, Sweden, antibody responses capable of cross-neutralizing Omicron were prevalent. Sera from infected-then-vaccinated healthcare workers exhibited robust cross-neutralization of Omicron, with an average potency reduction of only 5-fold relative to the pandemic founder variant, and some donors showing no loss at all. A similar pattern was observed in randomly sampled recent blood donors, with an average 7-fold loss of potency. Both cohorts showed substantial between-donor heterogeneity in their ability to neutralize Omicron. Together, these data highlight the extensive but incomplete evasion of neutralizing antibody responses by the Omicron variant, and suggest that increasing the magnitude of neutralizing antibody responses by boosting with unmodified vaccines may suffice to raise titers to levels that are protective.

immunology↗

bioRxiv2020

SARS-CoV-2 protein subunit vaccination elicits potent neutralizing antibody responses

The outbreak and spread of SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2), the cause of coronavirus disease 2019 (COVID-19), is a current global health emergency and a prophylactic vaccine is needed urgently. The spike glycoprotein of SARS-CoV-2 mediates entry into host cells, and thus is a target for neutralizing antibodies and vaccine design. Here we show that adjuvanted protein immunization with SARS-CoV-2 spike trimers, stabilized in prefusion conformation 1, results in potent antibody responses in mice and rhesus macaques with neutralizing antibody titers orders of magnitude greater than those typically measured in serum from SARS-CoV-2 seropositive humans. Neutralizing antibody responses were observed after a single dose, with exceptionally high titers achieved after boosting. Furthermore, neutralizing antibody titers elicited by a dose-sparing regimen in mice were similar to those obtained from a high dose regimen. Taken together, these data strongly support the development of adjuvanted SARS-CoV-2 prefusion-stabilized spike protein subunit vaccines.

immunology↗