This study reports the coding-complete genome sequence, with variant identifications and phylogenetic analysis, of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) P.1 variant (20J/501Y.V3), obtained from an oropharyngeal swab specimen from a female Bangladeshi patient diagnosed with coronavirus disease 2019 (COVID-19) with no travel history.

Rationale The global public health is in serious crisis due to emergence of SARS-CoV-2 virus. Studies are ongoing to reveal the genomic variants of the virus circulating in various parts of the world. However, data generated from low- and middle-income countries are scarce due to resource limitation. This study was focused to perform whole genome sequencing of 151 SARS-CoV-2 isolates from COVID-19 positive Bangladeshi patients. The goal of this study was to identify the genomic variants among the SARS-CoV-2 virus isolates in Bangladesh, to determine the molecular epidemiology and to develop a relationship between host clinical trait with the virus genomic variants. Method Suspected patients were tested for COVID-19 using one step commercial qPCR kit for SARS-CoV-2 Virus. Viral RNA was extracted from positive patients, converted to cDNA which was amplified using Ion AmpliSeq™ SARS-CoV-2 Research Panel. Massive parallel sequencing was carried out using Ion AmpliSeq™ Library Kit Plus. Assembly of raw data is done by aligning the reads to a pre-defined reference genome (NC_045512.2) while retaining the unique variations of the input raw data by creating a consensus genome. A random forest-based association analysis was carried out to correlate the viral genomic variants with the clinical traits present in the host. Result Among the 151 viral isolates, we observed the 413 unique variants. Among these 8 variants occurred in more than 80 % of cases which include 241C to T, 1163A to T, 3037C to T,14408C to T, 23403A to G, 28881G to A, 28882 G to A, and finally the 28883G to C. Phylogenetic analysis revealed a predominance of variants belonging to GR clade, which have a strong geographical presence in Europe, indicating possible introduction of the SARS-CoV-2 virus into Bangladesh through a European channel. However, other possibilities like a route of entry from China cannot be ruled out as viral isolate belonging to L clade with a close relationship to Wuhan reference genome was also detected. We observed a total of 37 genomic variants to be strongly associated with clinical symptoms such as fever, sore throat, overall symptomatic status, etc. (Fisher’s Exact Test p-value<0.05). The most mention-worthy among those were the 3916CtoT (associated with causing sore throat, p-value 0.0005), the 14408C to T (associated with protection from developing cough, p-value= 0.027), and the 28881G to A, 28882G to A, and 28883G to C variant (associated with causing chest pain, p-value 0.025). Conclusion To our knowledge, this study is the first large scale phylogenomic studies of SARS-CoV-2 virus circulating in Bangladesh. The observed epidemiological and genomic features may inform future research platform for disease management, vaccine development and epidemiological study.

The global distribution and frequency of maturity onset diabetes of the young (MODY) vary, necessitating investigation across diverse ethnic groups. This study aimed to investigate MODY gene variants and phenotypic characteristics among young Bangladeshi individuals with nonobese, nonautoimmune youth-onset diabetes. Fifty participants with diabetes (onset < 35 years, BMI < 25 kg/m², negative for islet autoantibodies, detectable C-peptide, and a family history of DM) and 50 young individuals with normoglycemia were enrolled. Targeted next-generation sequencing (NGS) was performed on a panel of 14 known MODY genes. Candidate MODY-gene variants were identified in 20% (10/50) of the diabetes cohort. There were 11 heterozygous missense variants across eight genes: HNF1A, PDX1, NEUROD1, KLF11, PAX4 (three variants), BLK, ABCC8 (two variants), and KCNJ11. No variants met the ACMG/AMP criteria for ‘Pathogenic’ or ‘Likely Pathogenic’ classification; all identified variants were categorized as variants of uncertain significance (VUS). No significant phenotypic differences were observed between individuals with diabetes who carried identified variants and those who did not. In conclusion, this study identified candidate MODY variants (all classified as VUS) in one-fifth of the Bangladeshi nonobese, nonautoimmune youth-onset diabetes cohort. These findings provide a preliminary indication of a distinct genetic pattern characterized by a low frequency of common variants and a relative abundance of variants in rare MODY-associated genes. These findings are hypothesis-generating and highlight potential genetic targets for future functional validation to confirm pathogenicity and to support definitive MODY diagnoses.

In this study, we evaluated the performance of the in-house developed rRT-PCR assay for SARS-CoV-2 RNA targeting the envelope (E) and nucleocapsid (N) genes with internal control as human RNase P. A total of 50 positive samples and 50 negative samples of SARS-CoV-2 were tested by a reference kit at site 1 and a subset (30 positives and 16 negatives) of these samples are tested blindly at site 2. The limit of detection (LoD) was calculated by using a replication-deficient complete SARS-CoV-2 genome and known copy numbers, where Pseudo-virus samples were used to evaluate accuracy. On site 1, among the 50 SARS-CoV-2 positive samples 24, 18, and eight samples showed high (Ct < 26), moderate (26 < Ct ≤ 32), and low (32 < Ct ≤ 38) viral load, respectively, whereas in site 2, out of 30 SARS-CoV-2 positive samples, high, moderate, and low viral loads were found in each of the 10 samples. However, SARS-CoV-2 was not detected in the negative sample. So, in-house assays at both sites showed 100% sensitivity and specificity with no difference observed between RT PCR machines. The Ct values of the in-house kit had a very good correlation with the reference kits. LoD was determined as 100 copies/mL. It also displayed 100% accuracy in mutant and wild-type SARS-CoV-2 virus. This Bangasure™ RT-PCR kit shows excellent performance in detecting SARS-CoV-2 viral RNA compared to commercially imported CE-IVD marked FDA authorized kits.

This study determined five coding-complete genome sequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains isolated from oropharyngeal swab specimens of Bangladeshi patients who were diagnosed with coronavirus disease 2019 (COVID-19) and had no travel history.

Soil salinity is an increasing threat to agriculture in coastal regions, where climate change and sea-level rise intensify salt intrusion. Coastal agriculture in Bangladesh faces increasing salinity stress, yet its effects on soil microbial assembly and nutrient cycling remain poorly understood. This study examined how salinity affects soil microbial communities in agricultural soils from Kuakata, Bangladesh, using near-full-length 16 S rRNA amplicon sequencing. Soil samples were collected from 10 saline and 6 non-saline croplands, with saline fields showing visible signs of crop stress. Saline soils had substantially higher electrical conductivity (4.82 vs. 0.5 dS/m), exchangeable sodium percentage (33.78% vs. 11.37%), sodium adsorption ratio (2.38 vs. 0.41), pH (6.83 vs. 5.40), and sulfur content (288.9 vs. 120.62 mg/kg) than non-saline soils. Microbial communities differed significantly between soil groups and saline soils showed reduced microbial evenness. Although Proteobacteria and Chloroflexi dominated both soil types, saline soils were enriched in anaerobic and sulfur-associated-taxa, including Desulfobacterota, Deferrisomatota, Pseudomonas, and Thioalkalispira-Sulfurivermis, whereas non-saline soils showed higher abundance of taxa linked to more diverse soil ecological functions. Predicted phenotype analysis indicated a higher relative abundance of anaerobic-associated microorganisms in saline soils (36.4%) than in non-saline soils (29.3%). Together, these findings indicate that salinity strongly restructures soil microbial communities and may contribute to reduced soil health and agricultural productivity in coastal farming systems.