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Alam, A. S. M. R. U.

Publications and source records attributed to Alam, A. S. M. R. U..

4 recordsLinked to original sources
bioRxiv2021

Metagenomic diagnosis and pathogenic network profile of SARS-CoV-2 in patients co-morbidly affected by type 2 diabetes

BackgroundThe mortality of COVID-19 disease is very high among males or elderly or individuals having comorbidities with obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes SARS-CoV-2 infected patients metagenomic features with or without type 2 diabetes to identify the microbial interactions associated with its fatal consequences. MethodThis study compared the baseline nasopharyngeal microbiome of SARS-CoV-2 infected diabetic and non-diabetic patients with controls adjusted with age and gender. The mNGS were performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. ResultsAll three groups possessed significant bacterial diversity and dissimilarity indexes (p<0.05). Spearmans correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r=0.6-1.0, p<0.05), and 109 positive correlations among normal-flora and probiotic bacteria (r>0.6, p<0.05). The SARS-CoV-2 diabetic group exhibited a significant increase of pathogens (p<0.05) and opportunistic pathogens (p<0.05) with a simultaneous decrease of normal-flora (p<0.05). The molecular docking analysis of Salivaricin, KLD4 (alpha), and enterocin produced by several enriched probiotic strains presented strong binding affinity with Shiga toxin, outer membrane proteins (ompA, omp33) or hemolysin. ConclusionThe dysbiosis of the bacterial community might be linked with severe consequences of COVID-19 infected diabetic patients, although few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal-flora and probiotics through dietary changes and reduction of excessive pro-inflammatory states by preventing pathogenic environment might lead to a better outcome for those co-morbid patients.

genomics↗
bioRxiv2020

Comprehensive annotations of the mutational spectra of SARS-CoV-2 spike protein: a fast and accurate pipeline

In order to explore nonsynonymous mutations and deletions in the spike (S) protein of SARS-CoV-2, we comprehensively analyzed 35,750 complete S protein gene sequences from across six continents and five climate zones around the world, as documented in the GISAID database as of June 24th, 2020. Through a custom Python-based pipeline for analyzing mutations, we identified 27,801 (77.77 % of spike sequences) mutated strains compared to Wuhan-Hu-1 strain. 84.40% of these strains had only single amino-acid (aa) substitution mutations, but an outlier strain from Bosnia and Herzegovina (EPI_ISL_463893) was found to possess six aa substitutions. The D614G variant of the major G clade was found to be predominant across circulating strains in all climates. We also identified 988 unique aa substitution mutations distributed across 660 positions within the spike protein, with eleven sites showing high variability - these sites had four types of aa variations at each position. Besides, 17 in-frame deletions at four major regions (three in N-terminal domain and one just downstream of the RBD) may have possible impact on attenuation. Moreover, the mutational frequency differed significantly (p= 0.003, Kruskal-Wallis test) among the SARS-CoV-2 strains worldwide. This study presents a fast and accurate pipeline for identifying nonsynonymous mutations and deletions from large dataset for any particular protein coding sequence and presents this S protein data as representative analysis. By using separate multi-sequence alignment with MAFFT, removing ambiguous sequences and in-frame stop codons, and utilizing pairwise alignment, this method can derive nonsynonymus mutations (Reference:Position:Strain). We believe this will aid in the surveillance of any proteins encoded by SARS-CoV-2, and will prove to be crucial in tracking the ever-increasing variation of many other divergent RNA viruses in the future.

evolutionary biology↗
bioRxiv2019

First Complete Genome Sequence of the Novel Lineage G-IX (BD-18) of FMDV Serotype Asia1

Foot-and-Mouth Disease (FMD) has been a major threat to livestock worldwide, and is caused by FMD Virus (FMDV) existing as seven serotypes (A, O, C, Asia1 and SAT 1-3), each having variability into topotypes, genetic lineages, sublineages, and strains. Three serotypes are circulating in Indian subcontinent with the widespread distribution of serotype O, whereas serotype A and Asia1 are restricted to certain geographical regions. During 2017-2018, the Sindh-08 lineages of Asia1 serotype was reported from Pakistan, however, in 2018, a novel circulatory foot-and-mouth disease virus serotype Asia1 BD-18 (G-IX) lineage containing a unique mutation has emerged in Bangladesh. The first complete genome of the Asia1/ASIA/G-IX novel lineage strain, isolated from Bangladesh, is reported here. Amino acid substitutions at critical antigenic sites of capsid were identified compared to genome of existing vaccine strain (IND/63/72), and contemporary FMDV serotype A isolate of Bangladesh.

molecular biology↗