Background: Lumpy skin disease (LSD) is an important viral disease causing significant economic losses in commercial livestock production. In mid‐2019, an outbreak of LSD has been reported in cattle population from different parts of Bangladesh including Chattogram division. A cross‐sectional surveillance study was undertaken from August 2019 to December 2019 to investigate the prevalence and associated risk factors of LSD in cattle in Chattogram district.Methods: A total of 3,327 cattle from 19 commercial farms were examined for the LSD specific skin lesions and associated risk factors. A total of 120 skin biopsies were collected from the suspected animal for the confirmation of the disease using molecular detection and histopathological examination. Partial genome sequencing and phylogenetic analyses were performed on selected viral isolates.Results: The overall clinical prevalence of LSD in the study population was 10% (95% confidence interval [CI]: 9.4%–11%) where the highest farm level outbreak frequency was 63.33% (95% CI: 45.51%–78.13%) and the lowest 4.22% (95% CI: 3.39%–5.25%). Crossbred and female cattle showed a significantly higher prevalence of the disease compared to their counterparts. Introduction of new animals in farms was found to be one of the most significant risk factors in the transmission of the disease. All suspected skin biopsies were positive for LSD virus (LSDV) infection with granulomatous and pyogranulomatous dermatitis was revealed on histopathology. Phylogenetic analysis based on the inverted terminal repeat region of the LSDV gene suggested that the locally circulating strain was closely related to the strains isolated from the Middle East and North African countries.Conclusions: The data generated in this study would be beneficial to the field veterinarians and animal health decision makers in the country as well as it will aid in taking appropriate measures to prevent further relapse or outbreak of this disease in future.

Goat plays a crucial role in human livelihoods, being a major source of meat, milk, fiber, and hides, particularly under adverse climatic conditions. The goat genomics related to the candidate gene approach is now being used to recognize molecular mechanisms that have different expressions of growth, reproductive, milk, wool, and disease resistance. The appropriate literature on this topic has been reviewed in this article. Several genetic characterization attempts of different goats have reported the existence of genotypic and morphological variations between different goat populations. As a result, different whole-genome sequences along with annotated gene sequences, gene function, and other genomic information of different goats are available in different databases. The main objective of this review is to search the genes associated with economic traits in goats. More than 271 candidate genes have been discovered in goats. Candidate genes influence the physiological pathway, metabolism, and expression of phenotypes. These genes have different functions on economically important traits. Some genes have pleiotropic effect for expression of phenotypic traits. Hence, recognizing candidate genes and their mutations that cause variations in gene expression and phenotype of an economic trait can help breeders look for genetic markers for specific economic traits. The availability of reference whole-genome assembly of goats, annotated genes, and transcriptomics makes comparative genomics a useful tool for systemic genetic upgradation. Identification and characterization of trait-associated sequence variations and gene will provide powerful means to give positive influences for future goat breeding program.

Black Bengal goat (Capra hircus), a member of the Bovidae family with the unique traits of high prolificacy, skin quality and low demand for food is the most socioeconomically significant goat breed in Bangladesh. Furthermore, the aptitude of adaptation and disease resistance capacity of it is highly notable which makes its whole genome information an area of research interest. The genomic DNA of a local (Chattogram, Bangladesh) healthy male Black Bengal goat (Capra hircus) was extracted and then sequenced. Sequencing was completed using the Illumina HiSeq 2500 sequencing platform and the draft assembly was generated using the “ARS1” genome as the reference. MAKER gene annotation pipeline was utilized to annotate 26,458 gene models. Genome completeness was assessed using BUSCO (Benchmarking Universal Single-Copy Orthologs) which showed 82.5% completeness of the assembled genome.

The emergence of colistin resistance in Escherichia coli is a global public health concern. Contaminated food can accelerate the spread of colistin-resistant E. coli to humans. This study aimed to detect and characterize colistin-resistant E. coli from broiler meat in Bangladesh. We analyzed 136 pooled broiler meat samples from 240 carcasses collected from 40 live bird markets in urban and rural areas and 8 metropolitan supermarkets. The mean count of E. coli in broiler meat samples collected from rural retail shops, metropolitan supermarkets, and urban retail shops was 5.3 ± 1.1, 4.1 ± 1.4, and 3.9 ± 0.8 log ₁₀ colony-forming unit per gram, respectively. Colistin-resistant E. coli (minimum inhibitory concentration >2 mg/L) was found in 78% (95% confidence interval 70.2–84.1%) of the samples. All colistin-resistant isolates harbored the mcr - 1 gene, while the rest of the mcr genes ( mcr - 2 to mcr - 9 ) were not detected. Most colistin-resistant E. coli isolates (98%) showed coresistance to tetracycline, sulfamethoxazole/trimethoprim followed by ciprofloxacin (95%). Alarmingly, all of the colistin-resistant isolates were found to be multidrug resistant. Phylogenetic analysis showed close similarities of the mcr - 1 gene sequences of this study with many strains of Enterobacterales isolated from humans, animals, and the environment. This study detected colistin-resistant E. coli contamination in broiler meat, which can pose a serious public health threat.

Background and Aim: Coronavirus disease (COVID-19) has been announced as a life-threatening, highly transmissible infectious novel emerging disease worldwide. Rapid detection and epidemiological information are desperately needed to overcome the existing pandemic situation and alleviate national and international crises. Still, to date, there is no significant epidemiological study of COVID-19 available in Bangladesh, especially in the Chattogram division. However, the current study focuses on molecular detection, prevalence, and risk factors associated with COVID-19 in Southern Bangladesh. Materials and Methods: Standard diagnostic protocols through real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) were performed for molecular confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Different patient demographics were analyzed for exploring the relationship of four factors – region, sex, age, and symptoms with the accumulated number of COVID-19 cases in the Southern Bangladesh during the period of May 13, 2020, to June 12, 2020. Results: A total of 2954 samples were tested where the cumulative prevalence of circulating SARS-CoV-2 was 29.76% (n=879; 95% CI: 28.11-31.44) in the selected study region. Among the risk factors, the present study revealed that flatland people (35.62%, 95% CI 33.61-37.67, OR=3.13) were more vulnerable to getting infected by SARS-CoV-2 than the people living in hill tracts (13.04%, 95% CI 10.73-15.63). People older than 50 years (34.68%, 95% CI 30.38-39.18) were designated the highest risk than other different age groups. A higher number of COVID-19 cases were confirmed in patients (36.0%, 95% CI 33.77-38.29, OR=1.76) with typical symptoms, but interestingly a significant number of asymptomatic carriers (20.39%, 95% CI 18.13-22.80) also positive for SARS-CoV-2. Conclusion: To the best of our knowledge, this is the first epidemiological report in the Southern Bangladesh for COVID- 19. The study's findings will contribute to health professionals and the policy-makers to take preventive measures against the next outbreak emergency for Bangladesh.