Biology subjects

Barrett, D.

Publications and source records attributed to Barrett, D..

3 recordsLinked to original sources

bioRxiv2025

Molecular characterisation of common Culicoides Biting Midges (Diptera: Ceratopogonidae) in Ireland

BackgroundBiting midges in the genus Culicoides (Diptera: Ceratopogonidae) act as vectors for several arboviruses, including Bluetongue virus (BTV) and Schmallenberg virus (SBV), which affect livestock health and productivity. In Ireland, limited genetic data are available regarding the diversity of Culicoides species. This study represents the first attempt to characterise Culicoides in this region using molecular techniques. MethodsAdult Culicoides samples were captured using Onderstepoort Veterinary Institute (OVI) traps across six locations in Ireland. Subsequent molecular analyses involved polymerase chain reaction (PCR) and sequencing of the cytochrome oxidase subunit 1 (CO1) and the internal transcriber spacer (ITS) barcoding regions to obtain species identities. Additionally, using both markers, we inferred the population genetic structure and potential colonisation pathways of Culicoides obsoletus sensu stricto (s. str.), the major vector species in Ireland. ResultsDNA barcoding facilitated identification of 177 specimens. Eight common Culicoides species were identified through DNA barcoding of CO1 and ITS gene regions. The presence of putative vectors of Bluetongue virus (BTV) and Schmallenberg virus (SBV) were also confirmed, including species in the subgenus Avaritia (C. obsoletus s. str., C. scoticus, C. chiopterus, and C. dewulfi) and subgenus Culicoides s. str. (C. pulicaris and C. punctatus). Phylogenetic analysis confirmed the relationship between these vector species and facilitated the placement of Culicoides sp. which could not be identified to species level through DNA barcoding. Haplotype network analysis of C. obsoletus showed that some haplotypes of these species are shared between Continental Europe, the UK, and Ireland, suggesting a possible incursion pathway for this vector. ConclusionDNA barcoding employing a combination of two barcodes, CO1 and ITS, proved effective in identifying Culicoides, especially species within the obsoletus complex, which are difficult to morphologically distinguish. Our findings also suggest that investigation of the population genetic structure of Culicoides spp. could be used to model the potential introduction routes of midge-borne pathogens into the country.

molecular biology↗

bioRxiv2023

DiscoGen: Learning to Discover Gene Regulatory Networks

Accurately inferring Gene Regulatory Networks (GRNs) is a critical and challenging task in biology. GRNs model the activatory and inhibitory interactions between genes and are inherently causal in nature. To accurately identify GRNs, perturbational data is required. However, most GRN discovery methods only operate on observational data. Recent advances in neural network-based causal discovery methods have significantly improved causal discovery, including handling interventional data, improvements in performance and scalability. However, applying state-of-the-art (SOTA) causal discovery methods in biology poses challenges, such as noisy data and a large number of samples. Thus, adapting the causal discovery methods is necessary to handle these challenges. In this paper, we introduce DiscoGen, a neural network-based GRN discovery method that can denoise gene expression measurements and handle interventional data. We demonstrate that our model outperforms SOTA neural network-based causal discovery methods.

genomics↗

bioRxiv2019

Sub-species niche specialization in the oral microbiome is associated with nasopharyngeal carcinoma risk in an endemic area of southern China

Oral health and changes in the oral microbiome have been associated with both local and systemic cancer. Poor oral hygiene is a known risk factor for Nasopharyngeal Carcinoma (NPC), a virally-associated head and neck cancer endemic to southern China. We explored the relationship between NPC and the oral microbiome using 16s rRNA sequencing in a study of 499 NPC patients and 495 population-based age and sex frequency-matched controls from an endemic area of Southern China. We found a significant reduction in community richness in cases compared to controls. Differences in the overall microbial community structure between cases and controls could not be explained by other potential confounders; disease status explained 5 times more variation in the Unweighted UniFrac distance than the next most explanatory variable. In feature-based analyses, we identified a pair of co-excluding Granulicatella adiacens (G. adicans) amplicon sequence variants (ASVs) which were strongly associated with NPC status and differed by a single nucleotide. The G. adicans variant an individual carried was also associated with the overall microbial community based on beta diversity. Co-occurrence analysis suggested the two G. adicans ASVs sit at the center of two co-excluding clusters of closely related organisms. Our results suggest there are differences in the oral microbiome between NPC patients and healthy controls and these may be associated with both a loss of microbial diversity and niche specialization among closely related commensals. Importance The relationship between oral health and the risk of Nasopharyngeal Carcinoma has been previously established. However, the role of oral microbiome has not been evaluated in the disease in a large epidemiological study. This paper clearly establishes a difference in the oral microbiome between NPC patients and healthy controls which cannot be explained by other confounding factors. It furthermore identifies a pair of closely related co-excluding organisms associated with the disease, highlighting the importance of modern methods for single nucleotide resolution in 16s rRNA sequence characterization. To the best of our knowledge, this is one of the first examples of cancer-associated niche-specialization of the oral microbiome.

microbiology↗