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Hami, I.

Publications and source records attributed to Hami, I..

2 recordsLinked to original sources

Unveiling multi-drug resistant (MDR) gram negative pathogenic bacteria from poultry chickens in the Noakhali region of Bangladesh

Rapidly increasing antibiotic-resistant bacterial strains in Bangladeshs food and farm animals stem from the excessive and inappropriate use of antibiotics. To assess the prevalence of multi drug resistant (MDR) gram-negative bacteria in poultry chicks, we sought to isolate and identify strains carrying antimicrobial resistance genes. Isolation and identification involved biochemical tests, 16S rRNA sequencing, and PCR screening of species-specific genes. MDR patterns were evaluated using CLSI guidelines with seventeen antibiotics across twelve classes. Targeted gene sequences were amplified for detection of ESBL, carbapenem, tetracycline, sulfonamide, and colistin resistance genes. Common isolates, such as Escherichia coli, Klebsiella pneumoniae, Proteus penneri, and Enterobacter hormaechei, exhibited average Multiple Antimicrobial Resistance (MAR) indices of 0.66, 0.76, 0.8, 0.84, and 0.81, 0.76, 0.84, 0.41 for broiler and layer chicken, respectively. Providencia stuartii and Salmonella enterica, exclusive to broiler samples, had MAR indices of 0.82 and 0.84, respectively. Additional isolates Morganella morganii, Aeromonas spp., and Wohlfahrtiimonas chitiniclastica were found in layers (Average MAR indices: 0.73, 0.71, and 0.91). Notably, M. morganii, E. hormaechei and W. chitiniclastica were identified for the first time in Bangladeshi poultry chicken, although their evolution is yet to understand. In this study, Pan-drug resistance was observed in one P. stuartii (broiler) and one Aeromonas spp. (layer) with a MAR index 1, while all isolates exhibited MAR indices >0.2, indicating MDR. Antimicrobial resistance (AMR) gene screening identified blaTEM, blaSHV, tetA, and sul1 in a majority of the MDR strains. Interestingly, E. coli (lactose positive and negative) and E. hormaechei were exclusively found to possess the tetB gene. In addition, E. coli (lactose negative), Klebsiella pneumoniae, Enterobacter hormaechei, M. morganii, and P. stuartii were observed to carry the colistin-resistant mcr1 gene, whereas sul2 was detected in E. coli (lactose positive and negative), E. hormaechei, P. stuartii, and P. penneri. These findings emphasize the health risk of our consumers of both broiler and layer chickens as they have turned to a potent reservoir of various AMR gene carrying MDR and Pan-drug resistant bacteria.

microbiology↗

Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores -9.1, -7.4, and -7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.

bioinformatics↗