Biology subjects

Pleydell, D. R. J.

Publications and source records attributed to Pleydell, D. R. J..

3 recordsLinked to original sources

bioRxiv2023

A Bayesian analysis of birth pulse effects on the probability of detecting Ebola virus in fruit bats

Since 1976 various species of Ebolavirus have caused a series of zoonotic outbreaks and public health crises in Africa. Bats have long been hypothesised to function as important hosts for ebolavirus maintenance, however the transmission ecology for these viruses remains poorly understood. Several studies have demon-strated rapid seroconversion for ebolavirus antibodies in young bats, yet paradoxically few PCR studies have confirmed the identity of the circulating viral species causing these seroconversions. The current study presents an age-structured epidemiological model that characterises the effects of seasonal birth pulses on ebolavirus transmission within a colony of African straw-coloured fruit bats (Eidolon helvum). Bayesian calibration is performed using previously published serological data collected from Cameroon, and age-structure data from Ghana. The model predicts that annual birth pulses most likely give rise to annual outbreaks, although more complex dynamic patterns - including skip years, multi-annual cycles and chaos - may be possible. Weeks 30 to 31 of each year were estimated to be the most likely period for isolating the circulating virus in Cameroon. The probability that a previous PCR campaign failed to detect Ebola virus, assuming that it was circulating, was estimated to be one in two thousand. This raises questions such as (1) what can we actually learn from ebolavirus serology tests performed without positive controls? (2) are current PCR tests sufficiently sensitive? (3) are swab samples really appropriate for ebolavirus detection? The current results provide important insights for the design of future field studies aiming to detect Ebola viruses from sylvatic hosts, and can contribute to risk assessments concerning the timing of zoonotic outbreaks.

ecology↗

bioRxiv2020

Characterization of a sex-determining region and its genomic context via statistical estimates of haplotype frequencies in daughters and sons sequenced in pools

Sex chromosomes are generally derived from a pair of autosomes that have acquired a locus controlling sex. Sex chromosomes usually evolve reduced recombination around this locus and undergo a long process of molecular divergence. Although sex chromosomes have been intensively studied in several model taxa, the actual loci controlling sex are difficult to identify in highly diverged sex chromosomes, hence they are known in relatively few species. Taxa with evolutionarily young sex chromosomes can help fill this gap in knowledge. Here we aimed at pinpointing the sex-determining region (SDR) of Armadillidium vulgare, a terrestrial isopod with female heterogamety (ZW females and ZZ males) and which presumably presents evolutionarily young sex chromosomes. To locate the SDR, we assessed SNP allele frequencies in F1 daughters and sons sequenced in pools (pool-seq) in several families. We developed a Bayesian method that uses the SNP genotypes of individually sequenced parents and poolseq data from F1 siblings to estimate the genetic distance between a given genomic region (contig) and the SDR. This allowed us to assign more than 43 Megabases of contigs to sex chromosomes. By taking advantage of the several F1 families, we delineated a very short genomic region (~65 kilobases) that did not show evidence for recombination with the SDR. In this region, the comparison of sequencing depths between sexes outlined female-specific genes that may be involved in sex determination. Overall, our results provide strong evidence for an extremely low divergence of sex chromosomes in A. vulgare.

evolutionary biology↗

bioRxiv2017

Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease, and from the computationally intractable number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a fragmented landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years over 600 orchards, we obtain the first estimate of the distribution of the flight distances of infectious aphids at the landscape scale. Most infectious aphids leaving a tree land beyond the bounds of a 1-ha orchard (50% of flights terminate within about 90 m). Moreover, long-distance flights are not rare (10% of flights exceed 1 km). By their impact on our quantitative understanding of winged aphids dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne.\n\nAuthor SummaryIn spatial epidemiology, dispersal kernels quantify how the probability of pathogen dissemination varies with distance. Spatial models of pathogen spread are sensitive to kernel parameters; yet these parameters have rarely been estimated using field data gathered at relevant scales. Robust estimation is rendered difficult by practical constraints limiting the number of surveyed individuals, and uncertainties concerning their disease status. Here, we present a framework that overcomes these barriers and permits inference for a between-patch transmission model. Extensive simulations show that dispersal kernels can be estimated from epidemiological surveillance data. When applied to such data collected from more than 600 orchards during 15 years of a plant virus epidemic our approach enables the estimation of the dispersal kernel of infectious winged aphids. This kernel is long-tailed, as 50% of the infectious aphids leaving a tree terminate their infectious flight within 90 m and 10% beyond 1 km. This first estimate of flight distances at the landscape scale for aphids-a group of vectors transmitting numerous viruses-is crucial for the science-based design of control strategies targeting plant virus epidemics.

epidemiology↗