Biology subjects

Rodriguez-Barraquer, I.

Publications and source records attributed to Rodriguez-Barraquer, I..

10 recordsLinked to original sources

bioRxiv2025

CXCR6⁺ CD127- Tr1 Cells Balance Immunity and Persistence in Plasmodium falciparum Infection

Plasmodium falciparum (Pf) induces the clonal expansion of antigen-specific type 1 regulatory T (Tr1) cells with a capacity for long-term memory. Tr1 cells comprise nearly 90% of the Pf blood stage antigen-specific CD4+ T cell pool in children. Though, whether Tr1 cells contribute to protection from malaria remains undetermined. To address this critical gap in knowledge, we first performed scRNAseq on gated cell populations to validate CXCR6+ CD127- as new phenotypic markers to enrich for bona-fide Tr1 cells. Importantly, these Tr1 cells potently suppressed the proliferation of other CD4+ T cells in vitro via IL-10 secretion. Among children living in malaria-endemic Uganda, CXCR6+ CD127- Tr1 cells were the dominant responding subset to Pf-infected red blood cell stimulation in vitro. They also rapidly expanded following malaria and expressed IL-10 and IFNg during infection in vivo. Tr1 abundance correlated with plasma concentrations of granzyme A, IFNg, IL-10, and LAG3, suggesting that these cells act systemically. Higher CXCR6+ CD127- Tr1 cell frequencies correlated with a lower probability of symptoms given parasitemia but were also associated with delayed parasite clearance among untreated, asymptomatic children. These data suggest that Tr1 cells help mediate clinical immunity to malaria but may also facilitate parasite persistence through mechanisms of immune regulation.

immunology↗

bioRxiv2022

Proteome-wide antigenic profiling in Ugandan cohorts identifies associations between age, exposure intensity, and responses to repeat-containing antigens in Plasmodium falciparum

Protection against Plasmodium falciparum, which is primarily antibody-mediated, requires recurrent exposure to develop. The study of both naturally acquired limited immunity and vaccine induced protection against malaria remains critical for ongoing eradication efforts. Towards this goal, we deployed a customized P. falciparum PhIP-seq T7 phage display library containing 238,068 tiled 62-amino acid peptides, covering all known coding regions, including antigenic variants, to systematically profile antibody targets in 198 Ugandan children and adults from high and moderate transmission settings. Repeat elements - short amino acid sequences repeated within a protein - were significantly enriched in antibody targets. While breadth of responses to repeat-containing peptides was twofold higher in children living in the high versus moderate exposure setting, no such differences were observed for peptides without repeats, suggesting that antibody responses to repeat-containing regions may be more exposure dependent and/or less durable in children than responses to regions without repeats. Additionally, short motifs associated with seroreactivity were extensively shared among hundreds of antigens, potentially representing cross- reactive epitopes. PfEMP1 shared motifs with the greatest number of other antigens, partly driven by the diversity of PfEMP1 sequences. These data suggest that the large number of repeat elements and potential cross-reactive epitopes found within antigenic regions of P. falciparum could contribute to the inefficient nature of malaria immunity.

immunology↗

bioRxiv2022

Dcifer: an IBD-based method to calculate genetic distance between polyclonal infections

An essential step toward reconstructing pathogen transmission and answering epidemiologically relevant questions from genomic data is obtaining pairwise genetic distance between infections. For recombining organisms such as malaria parasites, relatedness measures quantifying recent shared ancestry would provide a meaningful distance, suggesting methods based on identity by descent (IBD). While the concept of relatedness and consequently an IBD approach is fairly straightforward for individual parasites, the distance between polyclonal infections, which are prevalent in malaria, presents specific challenges and awaits a general solution that could be applied to infections of any clonality and accommodate multiallelic (e.g. microsatellite or microhaplotype) and biallelic (SNP) data. Filling this methodological gap, we present Dcifer (Distance for complex infections: fast estimation of relatedness), a method for calculating genetic distance between polyclonal infections, which is designed for unphased data, explicitly accounts for population allele frequencies and complexity of infection, and provides reliable inference. Dcifers IBD-based framework allows us to define model parameters that represent interhost relatedness and to propose corresponding estimators with attractive statistical properties. By using combinatorics to account for unobserved phased haplotypes, Dcifer is able to quickly process large datasets and estimate pairwise relatedness along with measures of uncertainty. We show that Dcifer delivers accurate and interpretable results and detects related infections with statistical power that is 2-4 times greater than that of approaches based on identity by state. Applications to real data indicate that relatedness structure aligns with geographic locations. Dcifer is implemented in a comprehensive publicly available software package.

genetics↗

bioRxiv2019

Dengue after Zika: characterizing impacts of Zika emergence on endemic dengue transmission

In 2015 and 2016, Zika virus (ZIKV) swept through many Latin American countries where dengue virus (DENV) is endemic. Dengue and Zika viruses are of the same family, share a vector and may interact competitively or synergistically through human immune responses. We examine dengue incidence data from Brazil and Colombia from before, during, and after the Zika epidemic. We find evidence that dengue incidence was atypically low in 2017 in both Brazil and Colombia. We investigate whether Zika incidence at the state or department level is associated with changes in dengue incidence and find mixed results. We use simulations to investigate expected impact of cross-protection or enhancement between dengue and Zika. Our simulations show that regardless of the mechanism, low periods of dengue incidence are followed by a resurgence in dengue cases. It is therefore likely that countries currently experiencing low levels of dengue incidence will experience large dengue seasons in the near future. By considering multiple combinations of DENV and ZIKV reproduction numbers, we demonstrate that the mixed results of our statistical models are not entirely unexpected. Correlations in DENV and ZIKV reproduction number could contribute to complicating or masking an association between their case counts.

epidemiology↗

bioRxiv2019

Opportunities for improved surveillance and control of infectious diseases from age-specific case data

One of the challenges faced by global disease surveillance efforts is the lack of comparability across systems. Reporting commonly focuses on overall incidence, despite differences in surveillance quality between and within countries. For most immunizing infections, the age-distribution of incident cases provides a more robust picture of trends in transmission. We present a framework to estimate transmission intensity for dengue virus from age-specific incidence data, and apply it to 363 administrative units in Thailand, Colombia, Brazil and Mexico. Our estimates correlate well with those derived from seroprevalence data (the gold-standard), capture the expected spatial heterogeneity in risk, and correlate with known environmental drivers of transmission. We show how this approach could be used to guide the implementation of control strategies such as vaccination. Since age-specific counts are routinely collected by many surveillance systems, they represent a unique opportunity to further our understanding of disease burden and risk for many diseases.

epidemiology↗

bioRxiv2018

Taking sharper pictures of malaria with CAMERAs: Combined Antibodies to Measure Exposure Recency Assays

Antibodies directed against malaria parasites are easy and inexpensive to measure but remain an underutilized surveillance tool due to a lack of consensus on what to measure and how to interpret results. High throughput screening of antibodies from well-characterized cohorts offers a means to substantially improve existing assays by rationally choosing the most informative sets of responses and analytical methods. Recent data suggest that high-resolution data on malaria exposure can be obtained from a small number of samples by measuring a handful of properly chosen antibody responses. In this review, we will discuss how standardized multi-antibody assays can be developed and efficiently integrated into existing surveillance activities, with great potential to greatly augment the breadth and quality of information available to direct and monitor malaria control and elimination efforts.

epidemiology↗

bioRxiv2018

Heterogeneous exposure and hotspots for malaria vectors at three study sites in Uganda

Heterogeneity in malaria transmission has household, temporal, and spatial components. These factors are relevant for improving the efficiency of malaria control by targeting heterogeneity. To quantify variation, we analyzed mosquito counts from entomological surveillance conducted at three study sites in Uganda that varied in malaria transmission intensity. Using a Bayesian zero-inflated negative binomial model, validated via a comprehensive simulation study, we quantified household differences in malaria exposure and examined its spatial distribution. We found that housing quality explained large variation among households in mosquito counts. In each site, there was evidence for hot and cold spots, spatial patterns associated with urbanicity, elevation, or other environmental covariates. We also found some differences in the hotspots in rainy vs. dry seasons or before vs. after control. This work identified methods for quantifying heterogeneity in malaria exposure and offered a critical evaluation of spatially targeting interventions at malaria hotspots.

ecology↗

bioRxiv2018

What lies beneath: a spatial mosaic of Zika virus transmission in the 2015-2016 epidemic in Colombia

Time series data provide a crucial window into infectious disease dynamics, yet their utility is often limited by the spatially aggregated form in which they are presented. When working with time series data, violating the implicit assumption of homogeneous dynamics below the scale of spatial aggregation could bias inferences about underlying processes. We tested this assumption in the context of the 2015-2016 Zika epidemic in Colombia, where time series of weekly case reports were available at national, departmental, and municipal scales. First, we performed a descriptive analysis, which showed that the timing of departmental-level epidemic peaks varied by three months and that departmental-level estimates of the time-varying reproduction number, R(t), showed patterns that were distinct from a national-level estimate. Second, we applied a classification algorithm to six features of proportional cumulative incidence curves, which showed that variability in epidemic duration, the length of the epidemic tail, and consistency with a cumulative normal density curve made the greatest contributions to distinguishing groups. Third, we applied this classification algorithm to data simulated with a stochastic transmission model, which showed that group assignments were consistent with simulated differences in the basic reproduction number, R0. This result, along with associations between spatial drivers of transmission and group assignments based on observed data, suggests that the classification algorithm is capable of detecting differences in temporal patterns that are associated with differences in underlying drivers of incidence patterns. Overall, this diversity of temporal patterns at local scales underscores the value of spatially disaggregated time series data.

epidemiology↗

bioRxiv2017

Quantification of anti-parasite and anti-disease immunity to malaria as a function of age and exposure

Malaria immunity is complex and multi-faceted, and fundamental gaps remain in our understanding of how it develops. Here, we use detailed clinical and entomological data from three parallel cohort studies conducted across the malaria transmission spectrum in Uganda to quantify the development of immunity against symptomatic Plasmodium falciparum as a function of age and transmission intensity. We focus on: anti-parasite immunity (i.e; ability to control parasite densities) and anti-disease immunity (i.e; ability to tolerate higher parasite densities without fever). Our findings suggest a strong effect of age on both types of immunity, that remains significant after adjusting for cumulative exposure. They also show a non-linear effect of transmission intensity, where children experiencing the lowest transmission appear to develop immunity faster than those experiencing higher transmission. These findings illustrate how anti-parasite and anti-disease immunity develop in parallel, reducing the probability of experiencing symptomatic malaria upon each subsequent P. falciparum infection.

epidemiology↗

bioRxiv2017

Preliminary results of models to predict areas in the Americas with increased likelihood of Zika virus transmission in 2017.

Numerous Zika virus vaccines are being developed. However, identifying sites to evaluate the efficacy of a Zika virus vaccine is challenging due to the general decrease in Zika virus activity. We compare results from three different modeling approaches to estimate areas that may have increased relative risk of Zika virus transmission during 2017. The analysis focused on eight priority countries (i.e., Brazil, Colombia, Costa Rica, Dominican Republic, Ecuador, Mexico, Panama, and Peru). The models projected low incidence rates during 2017 for all locations in the priority countries but identified several subnational areas that may have increased relative risk of Zika virus transmission in 2017. Given the projected low incidence of disease, the total number of participants, number of study sites, or duration of study follow-up may need to be increased to meet the efficacy study endpoints.

epidemiology↗