Microbial Genes Involved in the Aromatic Compound Degradation Deciphered Through Metagenomics Analysis of Industrial Wastewater.

Abstract Background: Understanding microbial and functional diversity from different stages of common effluent treatment plant (CETP) plays an important role to enhance the treatment performs of wastewater systems. However, unraveling microbial interactions as well as utilization of substrate involved in complex microbial communities is a challenging task. Hence, we demonstrate an integrated approach of shotgun metagenomics and whole genome sequencing to identify the microbial diversity and genes involved in degradation of benzoate, 1,2-dichloroethane and phenylalanine metabolism and degradation pathways from CETP microbiome.Results: The taxonomy profile was annotated using the Ribosomal Database Project (RDP) database in the MG-RAST server. The results showed that, bacteria accounted for 98.46% was the most abundant domain, followed by Eukaryota (0.10%) and Archea 0.02%. At Phylum level, Proteobacteria (28.8%) were dominant, followed by Bacteroidetes (16.1%), Firmicutes (11.7%) and Fusobacteria (6.9%). The most dominated species were Klebsiella pneumoniae, Wolinella succinogenes, Pseudomonas stutzeri, Desulfovibris vulgaris, Clostridium sticklandii, and Escherichia coli. The Clusters of Orthologous Groups (COGs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, revealed the presence of the genes responsible for the metabolism and degradation of aromatic compounds. This information was validated with the whole genome analysis of the bacteria isolated from the CETP.Conclusion: The two type of integrated meta omics analyses revealed that the metabolic and degradation capability at both community wide and individual bacterial levels. In addition, we demonstrated that microbial diversity changes with the treatment process in which inlet of CETP effluent shows higher dominancy of Proteobacteria whereas in textile industry outlet the high abundance of Firmicutes was observed. We foresee this approach would contribute in designing the bioremediation strategies for the industrial treatment process.</jats:p

Genomic Variations in SARS-CoV-2 Genomes From Gujarat: Underlying Role of Variants in Disease Epidemiology

Humanity has seen numerous pandemics during its course of evolution. The list includes several incidents from the past, such as measles, Ebola, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS), etc. The latest edition to this is coronavirus disease 2019 (COVID-19), caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of August 18, 2020, COVID-19 has affected over 21 million people from 180 + countries with 0.7 million deaths across the globe. Genomic technologies have enabled us to understand the genomic constitution of pathogens, their virulence, evolution, and rate of mutation, etc. To date, more than 83,000 viral genomes have been deposited in public repositories, such as GISAID and NCBI. While we are writing this, India is the third most affected country by COVID-19, with 2.7 million cases and &amp;gt; 53,000 deaths. Gujarat is the 11th highest affected state with a 3.48% death rate compared to the national average of 1.91%. In this study, a total of 502 SARS-CoV-2 genomes from Gujarat were sequenced and analyzed to understand its phylogenetic distribution and variants against global and national sequences. Further variants were analyzed from diseased and recovered patients from Gujarat and the world to understand its role in pathogenesis. Among the missense mutations present in the Gujarat SARS-CoV-2 genomes, C28854T (Ser194Leu) had an allele frequency of 47.62 and 7.25% in deceased patients from the Gujarat and global datasets, respectively. In contrast, the allele frequency of 35.16 and 3.20% was observed in recovered patients from the Gujarat and global datasets, respectively. It is a deleterious mutation present in the nucleocapsid (N) gene and is significantly associated with mortality in Gujarat patients with a p-value of 0.067 and in the global dataset with a p-value of 0.000924. The other deleterious variant identified in deceased patients from Gujarat (p-value of 0.355) and the world (p-value of 2.43E-06) is G25563T, which is located in Orf3a and plays a potential role in viral pathogenesis. SARS-CoV-2 genomes from Gujarat are forming distinct clusters under the GH clade of GISAID. This study will shed light on the viral haplotype in SARS-CoV-2 samples from Gujarat, India.</jats:p

Genomic variations in SARS-CoV-2 genomes from Gujarat: Underlying role of variants in disease epidemiology

AbstractHumanity has seen numerous pandemics during its course of evolution. The list includes many such as measles, Ebola, SARS, MERS, etc. Latest edition to this pandemic list is COVID-19, caused by the novel coronavirus, SARS-CoV-2. As of 4th July 2020, COVID-19 has affected over 10 million people from 170+ countries, and 5,28,364 deaths. Genomic technologies have enabled us to understand the genomic constitution of the pathogens, their virulence, evolution, rate of mutations, etc. To date, more than 60,000 virus genomes have been deposited in the public depositories like GISAID and NCBI. While we are writing this, India is the 3rd most-affected country with COVID-19 with 0.6 million cases, and &gt;18000 deaths. Gujarat is the fourth highest affected state with 5.44 percent death rate compared to national average of 2.8 percent.Here, 361 SARS-CoV-2 genomes from across Gujarat have been sequenced and analyzed in order to understand its phylogenetic distribution and variants against global and national sequences. Further, variants were analyzed from diseased and recovered patients from Gujarat and the World to understand its role in pathogenesis. From missense mutations, found from Gujarat SARS-CoV-2 genomes, C28854T, deleterious mutation in nucleocapsid (N) gene was found to be significantly associated with mortality in patients. The other significant deleterious variant found in diseased patients from Gujarat and the world is G25563T, which is located in Orf3a and has a potential role in viral pathogenesis. SARS-CoV-2 genomes from Gujarat are forming distinct cluster under GH clade of GISAID.</jats:p