Biology subjects

Norris, D. E.

Publications and source records attributed to Norris, D. E..

7 recordsLinked to original sources

bioRxiv2025

Invasive Aedes vittatus mosquitoes in Jamaica: A looming public health concern

Aedes vittatus, an emerging invasive mosquito of significant public health concern has slowly made its way onto the global radar. With a known geographical range in Africa and Asia, where it is a competent vector for several arboviruses, this mosquito has now been reported in the Americas. As the spread of this mosquito has been partly linked to transcontinental trade and travel, Jamaica, the largest English-speaking country in the Caribbean, which serves as a central hub for trade and transport throughout the region has been on alert since its identification in neighbouring Dominican Republic and Cuba. Through ongoing surveillance efforts from January 2023 to October 2024, we report the detection of Ae. vittatus across six locations in four parishes in Jamaica. Both larvae and adults were collected from rural and urban areas in the country. Additionally, we present the first complete annotated mitochondrial genomes of two specimens of this invasive mosquito species. Phylogenetic analysis based on a 539 bp fragment of the cytochrome c oxidase subunit I gene extracted from the derived mitochondrial genomes of Jamaican Ae. vittatus, revealed clustering with specimens from Cuba, India and Nepal. This study highlights the benefits of routine surveillance and the power of molecular approaches to identify invasive species and their potential origins. Author summaryIncreased global movement is facilitating the spread of invasive mosquito species and the pathogens they carry, posing significant public health risks. Jamaica, a popular tourist destination with rising visitor numbers and extensive trade connections, is particularly vulnerable. The invasive Asian tiger mosquito Aedes albopictus, a vector of numerous viruses to humans, was reported in Jamaica in 2019, highlighting this issue. Another invasive species of concern, Ae. vittatus, primarily found in Asia and Africa, has been detected in nearby Cuba and the Dominican Republic. This raises alarms about the potential for disease outbreaks as Ae. vittatus can also transmit viruses such a dengue and chikungunya. We report the detection of Ae. vittatus in Jamaica in samples collected from January 2023 to October 2024. Its presence in multiple widely distributed locations suggests it may have been in Jamaica undetected for some time. This adaptability of this mosquito to human-inhabited areas increases the risk of pathogen transmission to persons, underscoring the urgent need for enhanced surveillance by the Vector Control program at the Ministry of Health and Wellness. Given its potential to transmit viruses, Ae. vittatus is emerging as a serious public health concern that requires immediate attention and action.

ecology↗

bioRxiv2022

A Bayesian Hierarchical Model for Signal Extraction from Protein Microarrays

SO_SCPLOWUMMARYC_SCPLOWProtein microarrays are a promising technology that measure protein levels in serum or plasma samples. Due to the high technical variability of these assays and high variation in protein levels across serum samples in any population, directly answering biological questions of interest using protein microarray measurements is challenging. Using within-array ranks of protein levels for analysis can mitigate the impact of between-sample variation on downstream analysis. Although ranks are sensitive to pre-processing steps, ranking methods that accommodate uncertainty provide robust and loss-function optimal ranks. Such ranking methods require Bayesian modeling that produces full posterior distributions for parameters of interest. Bayesian models that produce such outputs have been developed for other assays, for example DNA microarrays, but those modeling assumptions are not appropriate for protein microarrays. We develop and evaluate a Bayesian model to extract a full posterior distribution of normalized fluorescent signals and associated ranks for protein microarrays, and show that it fits well to data from two studies that use protein microrarrays from different manufacturing processes. We validate the model via simulation and demonstrate the downstream impact of using estimates from this model to obtain optimal ranks.

bioinformatics↗

bioRxiv2022

A Random Forest Classifier Uses Antibody Responses to Plasmodium Antigens to Reveal Candidate Biomarkers of the Intensity and Timing of Past Exposure to Plasmodium falciparum

1Important goals of malaria surveillance efforts include accurately quantifying the burden of malaria over time, which can be useful to target and evaluate interventions. The majority of malaria surveillance methods capture active or recent infections which poses several challenges to achieving malaria surveillance goals. In high transmission settings, asymptomatic infections are common and therefore accurate measurement of malaria burden often demands active surveillance; in low transmission regions where infections are rare accurate surveillance requires sampling a large subset of the population; and in any context monitoring malaria burden over time necessitates serial sampling. Antibody responses to Plasmodium falciparum parasites persist after infection and therefore measuring antibodies has the potential to overcome several of the current difficulties associated with malaria surveillance. However, identifying which antibody responses are markers of the timing and intensity of past exposure to P. falciparum is challenging, particularly among adults who tend to be re-exposed multiple times over the course of their lifetime and therefore have similarly high antibody responses to many P. falciparum antigens. A previous analysis of 479 serum samples from individuals in three regions in southern Africa with different historical levels of P. falciparum malaria transmission (high, intermediate, and low) revealed regional differences in antibody responses to P. falciparum antigens among children under 5 years of age. Using a novel bioinformatic pipeline optimized for protein microarrays that minimizes between-sample technical variation, we used antibody responses to P. falciparum and P. vivax antigens as predictors in random forest models to classify adult samples into these three regions of differing historical malaria transmission with high accuracy. Many of the antigens that were most important for classification in these models do not overlap with previously published results and are therefore novel candidate markers for the timing and intensity of past exposure to P. falciparum. Measuring antibody responses to these antigens could potentially lead to improved malaria serosurveillance that captures the timing and intensity of past exposure.

immunology↗

bioRxiv2021

A Pre-Processing Pipeline to Quantify, Visualize andReduce Technical Variation in Protein Microarray

Technical variation, or variation from non-biological sources, is present in most laboratory assays. Correcting for this variation enables analysts to extract a biological signal that informs questions of interest. However, each assay has different sources and levels of technical variation and the choice of correction methods can impact downstream analyses. Compared to similar assays such as DNA microarrays, relatively few methods have been developed and evaluated for protein microarrays, a versatile tool for measuring levels of various proteins in serum samples. Here, we propose a pre-processing pipeline to correct for some common sources of technical variation in protein microarrays. The pipeline builds upon an existing normalization method by using controls to reduce technical variation. We evaluate our method using data from two protein microarray studies, and by simulation. We demonstrate that pre-processing choices impact the fluorescent-intensity based ranks of proteins, which in turn, impact downstream analysis. 1 Impact StatementProtein microarrays are in wide use in cancer research, infectious disease diagnostics and biomarker identification. To inform research and practice in these and other fields, technical variation must be corrected using normalization and pre-processing. Current protein microarray studies use a variety of normalization methods, many of which were developed for DNA microarrays, and therefore are based on assumptions and data that are not ideal for protein microarrays. To address this issue, we develop, evaluate, and implement a pre-processing pipeline that corrects for technical variation in protein microarrays. We show that pre-processing and normalization directly impact the validity of downstream analysis, and protein-specific approaches are essential.

bioinformatics↗

bioRxiv2020

Genetic diversity of Anopheles coustani in high malaria transmission foci in southern and central Africa

Despite ongoing malaria control efforts implemented throughout sub-Saharan Africa, malaria remains an enormous public health concern. Current interventions such as indoor residual spraying with insecticides and use of insecticide-treated bed nets are aimed at targeting the key malaria vectors that are primarily endophagic and endophilic. While these control measures have resulted in a substantial decline in malaria cases and continue to impact indoor transmission, the importance of alternative vectors for malaria transmission has been largely neglected. Anopheles coustani, an understudied vector of malaria, is a species previously thought to exhibit mostly zoophilic behavior. However, recent studies from across Africa bring to light the contribution of this and ecologically similar anopheline species to human malaria transmission. Like many of these understudied species, An. coustani has greater anthropophilic tendencies than previously appreciated, is often both endophagic and exophagic, and carries Plasmodium falciparum sporozoites. These recent developments highlight the need for more studies throughout the geographic range of this species and the potential need to control this vector. The aim of this study was to explore the genetic variation of An. coustani mosquitoes and the potential of this Anopheles species to contribute to malaria parasite transmission in high transmission settings in Nchelenge District, Zambia, and the Kashobwe and Kilwa Health Zones in Haut-Katanga Province, the Democratic Republic of the Congo (DRC). Morphologically identified An. coustani specimens that were trapped outdoors in these study sites were analyzed by PCR and sequencing for species identification and blood meal sources, and malaria parasite infection was determined by ELISA and qPCR. Fifty specimens were confirmed to be An. coustani by the analysis of mitochondrial DNA cytochrome c oxidase subunit I (COI) and ribosomal internal transcribed spacer region 2 (ITS2). Further, maximum likelihood phylogenetic analysis of COI and ITS2 sequences revealed two distinct phylogenetic groups within this relatively small regional collection. Our findings indicate that both An. coustani groups have anthropophilic and exophagic habits and come into frequent contact with P. falciparum, suggesting that this potential alternative malaria vector might elude current vector controls in Northern Zambia and Southern DRC. This study sets the groundwork for more thorough investigations of bionomic characteristics and genetic diversity of An. coustani and its contribution to malaria transmission in these regions.

evolutionary biology↗

bioRxiv2020

Stability and detection of nucleic acid from viruses and hosts in mosquito blood meals

Monitoring the presence and spread of pathogens in the environment is of critical importance. Rapid detection of infectious disease outbreaks and prediction of their spread can facilitate early responses of health agencies and reduce the severity of outbreaks. Current sampling methods are sorely limited by available personnel and throughput. For instance, xenosurveillance utilizes captured arthropod vectors, such as mosquitoes, as sampling tools to access blood from a wide variety of vertebrate hosts. Next generation sequencing (NGS) of nucleic acid from individual blooded mosquitoes can be used to identify mosquito and host species, and microorganisms including pathogens circulating within either host. However, there are practical challenges to collecting and processing mosquitoes for xenosurveillance, such as the rapid metabolization or decay of microorganisms within the mosquito midgut. This particularly affects pathogens that do not replicate in mosquitoes, preventing their detection by NGS or other methods. Accordingly, we performed a series of experiments to establish the windows of detection for DNA or RNA from human blood and/or viruses present in mosquito blood meals. Our results will contribute to trap design for mosquito-based xenosurveillance, including sample stabilization and ideal time spent from collection to NGS processing.

microbiology↗

bioRxiv2019

The Impact of Antimalarial Resistance on the Genetic Structure of Plasmodium falciparum in the DRC

The Democratic Republic of the Congo (DRC) harbors 11% of global malaria cases, yet little is known about the spatial and genetic structure of the parasite population in that country. We sequenced 2537 Plasmodium falciparum infections, including a nationally representative population sample from DRC and samples from surrounding countries, using molecular inversion probes - a novel high-throughput genotyping tool. We identified an east-west divide in haplotypes known to confer resistance to chloroquine and sulfadoxine-pyrimethamine. Furthermore, we identified highly related parasites over large geographic distances, indicative of gene flow and migration. Our results were consistent with a background of isolation by distance combined with the effects of selection for antimalarial drug resistance. This study provides a high-resolution view of parasite genetic structure across a large country in Africa and provides a baseline to study how implementation programs may impact parasite populations.

genomics↗