bioRxiv Science⌕ Search

Biology subjects

Osei-Tutu, A.

Publications and source records attributed to Osei-Tutu, A..

2 recordsLinked to original sources

Laboratory-Based Surveillance of Animal Rabies in the Bono East Region of Ghana: A Six-Year Retrospective Study (2020 - 2025).

BackgroundDog-mediated rabies remains a major neglected tropical disease and an important cause of preventable human mortality in sub-Saharan Africa. Despite ongoing control efforts, limited laboratory-confirmed surveillance data hinder accurate assessment of the disease burden and the development of evidence-based interventions in Ghana. This study investigated the epidemiological characteristics of laboratory-confirmed rabies cases among suspected animal submissions and evaluated the contribution of routine diagnostic surveillance to rabies control. Methodology/Principal FindingsA retrospective analysis was conducted using laboratory surveillance records of suspected rabies cases submitted to a regional veterinary laboratory in Ghana between 2020 and 2025. Brain tissue samples were examined using Sellers staining, the direct fluorescent antibody test (FAT), and polymerase chain reaction (PCR). Epidemiological information, including animal species, vaccination history, ownership status, bite history, and diagnostic outcomes, was extracted and analysed descriptively. Of the 51 suspected cases examined, 46 (90.2%) were laboratory confirmed as rabies. Domestic dogs accounted for 96.1% of submissions, while cats represented 3.9%. Most suspected animals were either unvaccinated (64.7%) or had unknown vaccination status (33.3%), and 90.2% had reportedly bitten humans before submission. Confirmed cases were detected throughout the study period, indicating sustained viral circulation and continued zoonotic risk within the study area. Conclusions/SignificanceThe consistently high proportion of laboratory-confirmed rabies cases demonstrates persistent transmission of rabies virus among domestic animals and highlights substantial risks to human health. The integration of conventional and advanced laboratory diagnostic methods strengthened surveillance and improved case confirmation. These findings underscore the urgent need to expand dog vaccination coverage, strengthen laboratory-based surveillance, improve bite reporting systems, and enhance collaboration between veterinary and public health sectors. Reinforcing integrated One Health strategies will be essential to accelerate progress towards the global goal of eliminating dog-mediated human rabies by 2030. Author SummaryRabies remains one of the worlds oldest and most devastating zoonotic diseases, which is fatal yet preventable, causing thousands of human deaths each year, particularly in Africa and Asia. In Ghana, domestic dogs are the principal reservoir of the rabies virus, but information on the epidemiology of animal rabies from routine laboratory surveillance is limited in many regions. We reviewed six years (2020 - 2025) of laboratory records from the Regional Veterinary Laboratory in Techiman, Bono East Region, to describe the epidemiological characteristics of suspected animal rabies cases and laboratory-confirmed infections. Of the 51 brain samples submitted for diagnosis, 46 (90.2%) were confirmed positive for rabies. Domestic dogs accounted for almost all submissions, and most confirmed cases involved animals that were either unvaccinated or had an unknown vaccination history. Furthermore, most suspected animals had reportedly bitten humans before laboratory investigation, highlighting the continuing public health risk posed by canine rabies. The study also documents how regional diagnostic capacity was strengthened through collaboration with national reference laboratories, enabling the routine use of internationally recommended diagnostic methods such as the fluorescent antibody test and polymerase chain reaction. These findings provide valuable evidence to support enhanced rabies surveillance, increased mass dog vaccination, improved public awareness, and strengthened One Health collaboration. Such measures are essential for reducing human rabies deaths and supporting Ghanas contribution to the global goal of eliminating dog-mediated human rabies by 2030.

microbiology↗

A Methylation Density Binary Classifier for Predicting and Optimizing the Performance of Methylation Biomarkers in Clinical Samples

BackgroundVariation in intercellular methylation patterns can complicate the use of methylation biomarkers for clinical diagnostic applications such as blood-based cancer testing. Here, we describe development and validation of a methylation density binary classification method called EpiClass (available for download at https://github.com/Elnitskilab/EpiClass), that can be used to predict and optimize the performance of methylation biomarkers, particularly in challenging, heterogeneous samples such as liquid biopsies. This approach is based upon leveraging statistical differences in single-molecule sample methylation density distributions to identify ideal thresholds for sample classification. ResultsWe developed and tested the classifier using reduced representation bisulfite sequencing (RRBS) data derived from ovarian carcinoma tissue DNA and controls. We used these data to perform in silico simulations using methylation density profiles from individual epiallelic copies of ZNF154, a genomic locus known to be recurrently methylated in numerous cancer types. From these profiles, we predicted the performance of the classifier in liquid biopsies for the detection of epithelial ovarian carcinomas (EOC). In silico analysis indicated that EpiClass could be leveraged to better identify cancer-positive liquid biopsy samples by implementing precise thresholds with respect to methylation density profiles derived from circulating cell-free DNA (cfDNA) analysis. These predictions were confirmed experimentally using DREAMing to perform digital methylation density analysis on a cohort of low volume (1-mL) plasma samples obtained from 26 EOC-positive and 41 cancer-free women. EpiClass performance was then validated in an independent cohort of 24 plasma specimens, derived from a longitudinal study of 8 EOC-positive women, and 12 plasma specimens derived from 12 healthy women, respectively, attaining a sensitivity/specificity of 91.7%/100.0%. Direct comparison of CA-125 measurements with EpiClass demonstrated that EpiClass was able to better identify EOC-positive women than standard CA-125 assessment. Finally, we used independent whole genome bisulfite sequencing (WGBS) datasets to demonstrate that EpiClass can also identify other cancer types as well or better than alternative methylation-based classifiers. ConclusionsOur results indicate that assessment of intramolecular methylation density distributions calculated from cfDNA facilitate the use of methylation biomarkers for diagnostic applications. Furthermore, we demonstrated that EpiClass analysis of ZNF154 methylation was able to outperform CA-125 in the detection of etiologically-diverse ovarian carcinomas, indicating the broad utility of ZNF154 for use as a biomarker of ovarian cancer.

bioinformatics↗