Biology subjects

Palkopoulou, E.

Publications and source records attributed to Palkopoulou, E..

8 recordsLinked to original sources

bioRxiv2025

Uncovering the Genomic Landscape of Mycobacterium bovis in Wales

Bovine tuberculosis (bTB), caused by the bacterium Mycobacterium bovis, is one of the most pressing animal health issues in Wales today. It negatively impacts cattle health, affects profitability and trade, and can decimate years of genetic improvement towards desirable production traits. It also places a significant burden on the health and well-being of affected farming families. Eradication of bTB requires the understanding of local transmission pathways to target effective disease control interventions. Traditional genotyping methods, such as spoligotyping and VNTR analysis, which have previously been used in Wales to understand the epidemiology of M. bovis, have lacked the discriminatory power to accurately identify local transmission pathways. Recently, whole-genome sequencing has replaced traditional genotyping methods for all M. bovis strains isolated from infected animals in Wales. In this study, we characterised the genomic diversity of M. bovis across Wales by analysing the genome sequence of all 379 M. bovis isolates obtained from culture-positive animals in Wales in 2021. Analyses uncovered three main clusters that are geographically distinct. A further three clusters containing fewer isolates were also geographically separated, two of which had particularly large SNP distances compared to the majority of other Welsh isolates, suggesting independent introductions of M. bovis strains that are not endemic to Wales. Fine-scale and epidemiologically relevant genetic structuring was identified within the six main clusters, indicating region-specific evolution, which can drive local disease dynamics. Finally, A number of SNPs in coding genes were identified that have the potential for important advantageous physiological consequences that may impact host-pathogen interactions and necessitate further investigation.

microbiology↗

bioRxiv2024

The utility of whole-genome sequencing to identify likely transmission pairs for pathogens with slow and variable evolution

Pathogen whole-genome sequencing (WGS) has been used to track the transmission of infectious diseases in extraordinary detail, especially for pathogens that undergo fast and steady evolution, as is the case with many RNA viruses. However, for other pathogens evolution is less predictable, making interpretation of these data to inform our understanding of their epidemiology more challenging and the value of densely collected pathogen genome data uncertain. Here, we assess the utility of WGS for one such pathogen, in the "who-infected-whom" identification problem. We study samples from hosts (130 cattle, 111 badgers) with confirmed infection of M. bovis (causing bovine Tuberculosis), which has an estimated clock rate as slow as [~]0.1-1 variations per year. For each potential pathway between hosts, we calculate the relative likelihood that such a transmission event occurred. This is informed by an epidemiological model of transmission, and host life history data. By including WGS data, we shrink the number of plausible pathways significantly, relative to those deemed likely on the basis of life history data alone. Despite our uncertainty relating to the evolution of M. bovis, the WGS data are therefore a valuable adjunct to epidemiological investigations, especially for wildlife species whose life history data are sparse.

ecology↗

bioRxiv2021

Inferring Mycobacterium bovis transmission between cattle and badgers using isolates from the Randomised Badger Culling Trial

Mycobacterium bovis (M. bovis) is a causative agent of bovine tuberculosis, a significant source of morbidity and mortality in the global cattle industry. The Randomised Badger Culling Trial was a field experiment carried out between 1998 and 2005 in the South West of England. As part of this trial, M. bovis isolates were collected from contemporaneous and overlapping populations of badgers and cattle within ten defined trial areas. We combined whole genome sequences from 1,442 isolates with location and cattle movement data, identifying transmission clusters and inferred rates and routes of transmission of M. bovis. Most trial areas contained a single transmission cluster that had been established shortly before sampling, often contemporaneous with the expansion of bovine tuberculosis in the 1980s. The estimated rate of transmission from badger to cattle was approximately two times higher than from cattle to badger, and the rate of within-species transmission considerably exceeded these for both species. We identified long distance transmission events linked to cattle movement, recurrence of herd breakdown by infection within the same transmission clusters and superspreader events driven by cattle but not badgers. Overall, our data suggests that the transmission clusters in different parts of South West England that are still evident today were established by long-distance seeding events involving cattle movement, not by recrudescence from a long-established wildlife reservoir. Clusters are maintained primarily by within-species transmission, with less frequent spill-over both from badger to cattle and cattle to badger.

genomics↗

bioRxiv2020

Population structure and transmission of Mycobacterium bovis in Ethiopia

Bovine tuberculosis (bTB) is endemic in cattle in Ethiopia, a country that hosts the largest national cattle herd in Africa. The intensive dairy sector, most of which is peri-urban, has the highest prevalence of disease. Previous studies in Ethiopia have demonstrated that the main cause is Mycobacterium bovis (M. bovis), which has been investigated using conventional molecular tools including deletion typing, spoligotyping and Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR). Here we use whole genome sequencing (WGS) to examine the population structure of M. bovis in Ethiopia. A total of 134 M. bovis isolates were sequenced including 128 genomes from 85 mainly dairy cattle and six genomes isolated from humans, originating from 12 study sites across Ethiopia. These genomes provided a good representation of the previously described population structure of M. bovis, based on spoligotyping and demonstrated that the population is dominated by the clonal complexes African 2 (Af2) and European 3 (Eu3). A range of within-host diversity was observed amongst the isolates and evidence was found for both short- and long-distance transmission. Detailed analysis of available genomes from the Eu3 clonal complex combined with previously published genomes revealed two distinct introductions of this clonal complex into Ethiopia between 1950 and 1987, likely from Europe. This work is important to help better understand bTB transmission in cattle in Ethiopia and can potentially inform national strategies for bTB control in Ethiopia and beyond.

genomics↗

bioRxiv2020

Phylodynamic analysis of an emergent Mycobacterium bovis outbreak in an area with no previously known wildlife infections

Understanding how an emergent pathogen successfully establishes itself and persists in a previously unaffected population is a crucial problem in disease ecology. In multi-host pathogen systems this problem is particularly difficult, as the importance of each host species to transmission is often poorly characterised, and the epidemiology of the disease is complex. Opportunities to observe and analyse such emergent scenarios are few. Here, we exploit a unique dataset combining densely-collected data on the epidemiological and evolutionary characteristics of an outbreak of Mycobacterium bovis (M. bovis, the causative agent of bovine tuberculosis, bTB) in a population of cattle and badgers in an area considered low-risk for bTB, that has no previous record of either persistent infection in cattle, or of any infection in wildlife. We analyse the outbreak dynamics using a combination of mathematical modelling, machine learning and Bayesian evolutionary analyses. Comparison to M. bovis whole-genome sequences from Northern Ireland confirmed this to be a single introduction of the pathogen from the latter region, with evolutionary analysis supporting an introduction directly into the local cattle population at least six years prior to its first discovery in badgers. Once introduced, the evidence supports M. bovis epidemiological dynamics passing through two phases, the first dominated by cattle-to-cattle transmission before becoming established in the local badger population. These findings emphasise the importance of disease surveillance for early containment of outbreaks, in particular for pathogens not causing immediately evident symptoms in the infected host, and highlight the utility of combining dynamic modelling and phylogenetic analyses for understanding the often complex infection dynamics associated with emergent outbreaks.

ecology↗

bioRxiv2020

Competitive mapping allows to identify and exclude human DNA contamination in ancient faunal genomic datasets

BackgroundAfter over a decade of developments in field collection, laboratory methods and advances in high-throughput sequencing, contamination remains a key issue in ancient DNA research. Currently, human and microbial contaminant DNA still impose challenges on cost-effective sequencing and accurate interpretation of ancient DNA data. ResultsHere we investigate whether human contaminating DNA can be found in ancient faunal sequencing datasets. We identify variable levels of human contamination, which persists even after the sequence reads have been mapped to the faunal reference genomes. This contamination has the potential to affect a range of downstream analyses. ConclusionsWe propose a fast and simple method, based on competitive mapping, which allows identifying and removing human contamination from ancient faunal DNA datasets with limited losses of true ancient data. This method could represent an important tool for the ancient DNA field.

genomics↗

bioRxiv2018

Early Pleistocene enamel proteome sequences from Dmanisi resolve Stephanorhinus phylogeny.

Ancient DNA (aDNA) sequencing has enabled unprecedented reconstruction of speciation, migration, and admixture events for extinct taxa1. Outside the permafrost, however, irreversible aDNA post-mortem degradation2 has so far limited aDNA recovery within the {small tilde}0.5 million years (Ma) time range3. Tandem mass spectrometry (MS)-based collagen type I (COL1) sequencing provides direct access to older biomolecular information4, though with limited phylogenetic use. In the absence of molecular evidence, the speciation of several Early and Middle Pleistocene extinct species remain contentious. In this study, we address the phylogenetic relationships of the Eurasian Pleistocene Rhinocerotidae5-7 using {small tilde}1.77 million years (Ma) old dental enamel proteome sequences of a Stephanorhinus specimen from the Dmanisi archaeological site in Georgia (South Caucasus)8. Molecular phylogenetic analyses place the Dmanisi Stephanorhinus as a sister group to the woolly (Coelodonta antiquitatis) and Mercks rhinoceros (S. kirchbergensis) clade. We show that Coelodonta evolved from an early Stephanorhinus lineage and that this genus includes at least two distinct evolutionary lines. As such, the genus Stephanorhinus is currently paraphyletic and its systematic revision is therefore needed. We demonstrate that Early Pleistocene dental enamel proteome sequencing overcomes the limits of ancient collagen- and aDNA-based phylogenetic inference, and also provides additional information about the sex and taxonomic assignment of the specimens analysed. Dental enamel, the hardest tissue in vertebrates, is highly abundant in the fossil record. Our findings reveal that palaeoproteomic investigation of this material can push biomolecular investigation further back into the Early Pleistocene.

evolutionary biology↗

bioRxiv2018

Comparative Genomics and Genome Evolution in Birds-of-paradise

BackgroundThe diverse array of phenotypes and lekking behaviors in birds-of-paradise have long excited scientists and laymen alike. Remarkably, almost nothing is known about the genomics underlying this iconic radiation. Currently, there are 41 recognized species of birds-of-paradise, most of which live on the islands of New Guinea. In this study we sequenced genomes of representatives from all five major clades recognized within the birds-of-paradise family (Paradisaeidae). Our aim was to characterize genomic changes that may have been important for the evolution of the groups extensive phenotypic diversity.\n\nResultsWe sequenced three de novo genomes and re-sequenced two additional genomes representing all major clades within the birds-of-paradise. We found genes important for coloration, morphology and feather development to be under positive selection. GO enrichment of positively selected genes on the branch leading to the birds-of-paradise shows an enrichment for collagen, glycogen synthesis and regulation, eye development and other categories. In the core birds-of-paradise, we found GO categories for startle response (response to predators) and olfactory receptor activity to be enriched among the gene families expanding significantly faster compared to the other birds in our study. Furthermore, we found novel families of retrovirus-like retrotransposons active in all three de novo genomes since the early diversification of the birds-of-paradise group, which could have potentially played a role in the evolution of this fascinating group of birds.\n\nConclusionHere we provide a first glimpse into the genomic changes underlying the evolution of birds-of-paradise. Our aim was to use comparative genomics to study to what degree the genomic landscape of birds-of-paradise deviates from other closely related passerine birds. Given the extreme phenotypic diversity in this family, our prediction was that genomes should be able to reveal features important for the evolution of this amazing radiation. Overall, we found a strong signal for evolution on mechanisms important for coloration, morphology, sensory systems, as well as genome structure.

genomics↗