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Integrated chicken and fish farming systems, common in Bangladesh, present significant public health risks due to the spread of antimicrobial resistance genes (ARGs) and virulence factors (VFGs) through mobile genetic elements (MGEs). This study employs metagenomic sequencing to explore the diversity and abundance of ARGs, VFGs, and MGEs in various environmental samples from these farming systems. A total of 384 ARGs were detected, with tetracycline resistance genes such as tetM and tetX being the most abundant, alongside macrolide-lincosamide-streptogramin and aminoglycoside resistance genes. Droppings harbored the highest proportion of ARGs (62.2%), whereas sediment served as a reservoir for multi-metal resistance genes. Virulence factors associated with immune modulation, such as pvdL and tssH , and biofilm formation genes like algC were particularly prevalent in sediment and droppings. Among MGEs, plasmids and transposons like Tn6072 and Tn4001 were the most abundant, playing a critical role in horizontal gene transfer. Bacterial genera including Bacteroides , Clostridium , and Escherichia were strongly associated with MGEs, indicating their role in the dissemination of resistance and virulence traits. Statistical analyses revealed significant differences in the abundance of ARGs, VFGs, and MGEs across sample types, with sediment and droppings identified as hotspots for gene exchange. These findings underscore the urgent need for improved antibiotic stewardship and waste management practices to limit the spread of antimicrobial resistance and pathogenic bacteria within integrated farming environments.

The integrated chicken and fish farming system in Bangladesh is widely practiced for its resource efficiency, yet its microbial structure, functional potential, and associated antimicrobial resistance risks remain poorly understood. This study investigated microbial communities, metabolic functions, and antimicrobial resistance profiles across multiple components of integrated farming systems, including chicken gut, chicken droppings, feed, fish intestine, and pond sediment. Microbial profiling was performed using 16S ribosomal ribonucleic acid (rRNA) gene sequencing, functional metagenomic prediction, and culture-based isolation, complemented by antimicrobial susceptibility testing. A total of 2,838 operational taxonomic units were identified, with bacteria constituting the vast majority of detected microorganisms. Microbial community composition was strongly shaped by sample type, reflecting distinct ecological niches within the farming system. Chicken gut samples were dominated by Firmicutes, feed samples by Cyanobacteria, and sediment samples exhibited the highest microbial diversity, including taxa involved in biogeochemical cycling. Functional analysis revealed that pathways related to amino acid and carbohydrate metabolism were most abundant across all samples, while sediment and feed were enriched in pathways associated with xenobiotic degradation, suggesting a role in environmental detoxification. Culture-based methods isolated clinically relevant bacteria, including Escherichia coli and Proteus mirabilis , although metagenomic analysis indicated that these organisms represented only a minor fraction of the overall microbial community. Antimicrobial susceptibility testing demonstrated notable resistance, particularly to tetracyclines and fluoroquinolones. Metagenomic analysis further identified multiple antimicrobial resistance genes, with several showing strong associations with specific bacterial genera. This study provides the first comprehensive characterization of microbial diversity, functional capacity, and antimicrobial resistance within integrated chicken and fish farming systems in Bangladesh, highlighting potential environmental reservoirs of resistance and underscoring the need for improved management strategies to enhance sustainability and reduce public health risks.

Coronavirus disease 2019 (COVID-19) remains a major global health concern, with emerging evidence highlighting the role of the human microbiome in influencing disease severity. While extensive research has been conducted on COVID-19, studies examining host-pathogen interactions at the transcriptomic level remain limited. In this study, we investigated the metatranscriptomic profiles of forty nasopharyngeal samples collected from COVID-19 patients across different Bangladeshi cohorts. Sequencing data were processed to analyze taxonomic composition, microbial diversity, and antimicrobial resistance gene (ARG) patterns using multiple bioinformatic pipelines. COVID-19 positive and asymptomatic patients exhibited a higher abundance of pathogenic and multidrug-resistant bacteria, whereas COVID-19 negative individuals showed increased fungal diversity. Differential gene expression analysis revealed significant upregulation of immune response related genes, including pro-inflammatory cytokines, in COVID-19 positive cases. Notably, asymptomatic patients demonstrated reduced TLR4 expression, suggesting a potential reducing of innate immune activation, which may contribute to asymptomatic clinical outcomes. Additionally, functional enrichment highlighted active ARG expression in positive cases, indicating potential links between the respiratory microbiome and host immune modulation. These findings provide insights into the host-microbiome interplay underlying COVID-19 severity and highlight the need for further validation in larger, ethnically diverse cohorts with comprehensive clinical metadata.

Bangladeshi yogurt is a creamy, tangy dairy product with culinary significance in Bangladesh, often consumed alone or as a complement to spicy dishes. This study investigates the microbial diversity and nutritional composition in 38 samples, spanning commercial and locally produced varieties from eight districts. Through 16S rRNA amplicon sequencing, 650 Operational Taxonomic Units (OTUs) were identified: sour yogurt contained 493 OTUs, and sweet yogurt 441 OTUs. Firmicutes were predominant across both yogurt types, with unique appearances of Gracilibacteria, Gemmatimonadetes, and Spirochaetes in sour yogurt, while Euryarchaeota and Lentisphaerae were found only in sweet yogurt. Streptococcus and Lactobacillus emerged as the most abundant genera, with local sour samples presenting lower Firmicutes levels (84.98%) compared to commercial types (> 99.27%). Among the samples, those from Cox's Bazar exhibited the greatest bacterial diversity. Nutritional assessments revealed that branded yogurts were denser in nutrients, especially solids-not-fat (SNF), total solids, and essential minerals like iron and zinc. In contrast, local yogurts contained higher fat and lower sodium, appealing to consumers favoring richer textures with less salt. Increased acidity in local varieties also matched preferences for tangier flavors. Physicochemical analysis identified a negative association between Lactobacillus levels and pH, while higher fat content reduced overall bacterial diversity except for Lactobacillus , which further decreased mineral bioavailability. Carbohydrate metabolism was dominant in both types, with increased amino acid metabolism (11.72%) and xenobiotics biodegradation (3.94%) in sour yogurt. This study underscores the health-promoting properties of Bangladeshi yogurt, highlighting its unique regional microbiological and biochemical characteristics.

Purpose Identifying the factors influencing the preventive practices of the healthcare workers (HCWs) is crucial during the ongoing coronavirus disease 2019 (COVID‐19) because the HCWs are exposed to unparalleled levels of risks. Such concern is starting to be explored worldwide although there is only a single study available in Bangladesh with a limited scope of explorations of the domain. Therefore, this study aimed to identify the factors determining better preventive practices of HCWs toward COVID‐19. Materials and methods A cross‐sectional one‐to‐one survey was carried out using a validated questionnaire from December 15, 2020 to March 15, 2021 among a sample of 640 HCWs from Khulna, a southwestern division of Bangladesh, consisting of ten districts. The measures included socio‐demographics, knowledge, attitude, and preventive practices related information. A binary logistic regression analysis was conducted to identify factors determining preventive practices of HCWs toward COVID‐19. Results More than half of the respondents (62%) were following better preventive practices. Besides, around 70% of them had better knowledge and attitudes toward the disease. Regression analysis showed a number of major determining factors of the HCWs' better preventive practices including being a nurse or other professionals (ie, radiologists and pathologists), being graduates, working in coronavirus isolation units, managing COVID‐19 patients, having previous training, and having better attitudes toward COVID‐19. Conclusion The findings confirmed that the HCWs were generally practicing preventive manners although these trends followed were not at the standard level. So, providing guidance and information from authentic sources and organizing proper training could possibly enhance the preventive behavior in managing COVID‐19 patients.

Medical report of the male patient Blood group ABO B Rh Positive Hematological report HGB (Hemoglobin) (cyanomethanoglobin method) 13.0 g/dL ESR (westergren) 35 mm Differential count WBC Total count of WBC 5300/cmm Neutrophils 43% Lymphocytes 48% Eosinophils 3% Monocytes 6% Basophils 0% Total count of platelet 210 000/cmm Biochemical analysis report Random plasma glucose 5.8 mmol/L S. Creatinine 0.9 mg/dL SGPT (ALT) 32 U/L Immunology report D-Dimer 0.21 Case 2: Medical report of the female patient Hematological report HGB (hemoglobin) (cyanomethanoglobin method) 11.5 g/dL ESR (westergren) 20 mm Differential count WBC Total count of WBC 8200/cmm Neutrophils 57% Lymphocytes 35% Eosinophils 6% Monocytes 2% Basophils 0% Total count of platelet 1,86 000/cmm Biochemical analysis report S. Bilirubin 0.8 mg/dL SGPT (ALT) 32 U/L SGOT (AST) 45 Immunology report D-Dimer Not done Partial sequencing of the RBD portion of the spike protein revealed two featured mutations (L452R and T478K) of the B.1.617.2 PANGO lineage for both samples. 14 Whole-genome sequences revealed 38 mutations and 29 aa substitutions for the sample JUST1 (Collected from the female patient, GISAID accession ID—EPI_ISL_ 2 036 272) and 33 mutations and 26 aa substitutions for sample JUST2 (Collected from the male patient, GISAID accession ID—EPI_ISL_1942249). [...]the Nextstrain server (https://nextstrain.org/sars-cov-2/) for SARS-CoV-2 phylodynamics also bolstered our interpretation based on the mutation pattern of the strains. The Delta variants were 50% more transmissible and 60% more lethal (For every one death 1.6 death in ratio compared with the previous version of the virus) with reduced affinity for neutralizing antibody (The L452R mutation confers a reduction of the recognition capability of the immune system) as demonstrated by other studies. 15,16 Transmission of these new variants may cause a similar impact among Bangladeshi population, which introduced the Oxford-Astrazeneca vaccine.

Microbial inoculants that integrate plant growth promotion, pathogen suppression, and pollutant degradation are central to sustainable agriculture. Here, we report the genomic and phenotypic characterization of Lysinibacillus capsici BCSIR-Raj-01, an endophyte isolated from citrus leaves in Bangladesh. The 4.62 Mb genome encodes 4,699 coding sequences and displays an open pangenome with loci linked to stress adaptation, xenobiotic degradation, and secondary metabolite biosynthesis. Genome mining revealed complete pathways for indole-3-acetic acid (IAA) production, siderophore biosynthesis, and phosphate metabolism, alongside gene clusters for bacteriocins, lantibiotics, terpenes, and polyketides. Nitrogen cycling genes indicated diazotrophic growth potential and a truncated denitrification pathway. Phenotypic assays validated these predictions: L. capsici BCSIR-Raj-01 solubilized phosphate, produced IAA and siderophores, grew on hydrocarbons, and exhibited diazotrophic activity. Notably, the strain showed potent larvicidal activity against Culex and Anopheles larvae, suggesting ecological roles beyond plant association. Together, these results establish L. capsici BCSIR-Raj-01 as a multifunctional bacterium with potential applications in crop improvement, bioremediation, and biological vector control. The challenges of modern agriculture and environmental sustainability demand microbial solutions that deliver multiple functions. Lysinibacillus species are increasingly recognized for such versatility, but their genomic basis remains poorly resolved. Our study provides the first genome-enabled framework for understanding multifunctionality in L. capsici. By combining whole-genome sequencing with phenotypic validation, we show that BCSIR-Raj-01 harbors biosynthetic clusters, stress adaptation loci, and xenobiotic degradation genes while also expressing experimentally confirmed traits, including phosphate solubilization, IAA and siderophore production, nitrogen fixation, hydrocarbon utilization, and larvicidal activity. This integration of plant growth promotion, biocontrol potential, and pollutant degradation positions L. capsici BCSIR-Raj-01 as a next-generation bioinoculant. Beyond broadening the functional scope of Lysinibacillus, our findings highlight how genome-guided approaches can identify microbes with cross-sectoral applications in agriculture, bioremediation, and vector management.

In recent years, the research on Coronavirus disease 2019 (COVID-19) has surged rapidly due to its infectious nature and epidemiological importance as a pandemic. Association of other pathogenic microbes or different human microbiomes with COVID-19 severity is well established. While much is known about COVID-19, studies exploring how host-pathogen interactions at the transcriptomic level influence disease severity are still limited. This research focuses on metatranscriptomic perspective of COVID-19 patients from different Bangladeshi cohorts. Metatranscriptomic sequencing was performed using the extracted RNA of forty different nasopharyngeal samples. After preprocessing and assembly of the genome sequence data, taxonomic identification and diversity along with antibiotic resistance pattern was analyzed using different bioinformatic pipelines. COVID-19 positive and asymptomatic positive patients had a higher abundance of pathogenic and multidrug resistant bacteria whereas the Healthy or recovered patients had higher fungal population. Differential gene expression analysis was also performed to identify the upregulated and downregulated genes responsible for different biological and immunological pathways of humans. Here, immunological response related genes were mostly upregulated in positive cases which was also evident in the proinflammatory cytokines upregulation. Moreover, asymptomatic positive cases showed low TLR-4 expression, which is key to recognizing pathogen-associated molecular patterns (PAMPs) and triggering pro-inflammatory immune responses. This study can clarify the gene expression and signaling pattern of COVID-19 patients with different severity. This may also suggest that some populations exhibit reduced basal expression of TLR-4, which may suppress innate immune activation following infection and contribute to asymptomatic clinical outcomes; however, this hypothesis requires further investigation. Future studies should aim to validate these associations using larger, ethnically diverse cohorts with comprehensive clinical and demographic data.