Genome-wide study of globally distributed respiratory syncytial virus (RSV) strains implicates diversification utilizing phylodynamics and mutational analysis.

Respiratory syncytial virus (RSV) is a common respiratory pathogen that causes mild cold-like symptoms and severe lower respiratory tract infections, causing hospitalizations in children, the elderly and immunocompromised individuals. Due to genetic variability, this virus causes life-threatening pneumonia and bronchiolitis in young infants. Thus, we examined 3600 whole genome sequences submitted to GISAID by 31 December 2022 to examine the genetic variability of RSV. While RSVA and RSVB coexist throughout RSV seasons, RSVA is more prevalent, fatal, and epidemic-prone in several countries, including the United States, the United Kingdom, Australia, and China. Additionally, the virus's attachment glycoprotein and fusion protein were highly mutated, with RSVA having higher Shannon entropy than RSVB. The genetic makeup of these viruses contributes significantly to their prevalence and epidemic potential. Several strain-specific SNPs co-occurred with specific haplotypes of RSVA and RSVB, followed by different haplotypes of the viruses. RSVA and RSVB have the highest linkage probability at loci T12844A/T3483C and G13959T/C2198T, respectively. The results indicate that specific haplotypes and SNPs may significantly affect their spread. Overall, this analysis presents a promising strategy for tracking the evolving epidemic situation and genetic variants of RSV, which could aid in developing effective control, prophylactic, and treatment strategies.

In Silico Functional Characterization of a Hypothetical Protein From Pasteurella Multocida Reveals a Novel S-Adenosylmethionine-Dependent Methyltransferase Activity.

Genomes may now be sequenced in a matter of weeks, leading to an influx of "hypothetical" proteins (HP) whose activities remain a mystery in GenBank. The information included inside these genes has quickly grown in prominence. Thus, we selected to look closely at the structure and function of an HP (AFF25514.1; 246 residues) from Pasteurella multocida (PM) subsp. multocida str. HN06. Possible insights into bacterial adaptation to new environments and metabolic changes might be gained by studying the functions of this protein. The PM HN06 2293 gene encodes an alkaline cytoplasmic protein with a molecular weight of 28352.60 Da, an isoelectric point (pI) of 9.18, and an overall average hydropathicity of around -0.565. One of its functional domains, tRNA (adenine (37)-N6)-methyltransferase TrmO, is a S-adenosylmethionine (SAM)-dependent methyltransferase (MTase), suggesting that it belongs to the Class VIII SAM-dependent MTase family. The tertiary structures represented by HHpred and I-TASSER models were found to be flawless. We predicted the model's active site using the Computed Atlas of Surface Topography of Proteins (CASTp) and FTSite servers, and then displayed it in 3 dimensional (3D) using PyMOL and BIOVIA Discovery Studio. Based on molecular docking (MD) results, we know that HP interacts with SAM and S-adenosylhomocysteine (SAH), 2 crucial metabolites in the tRNA methylation process, with binding affinities of 7.4 and 7.5 kcal/mol, respectively. Molecular dynamic simulations (MDS) of the docked complex, which included only modest structural adjustments, corroborated the strong binding affinity of SAM and SAH to the HP. Evidence for HP's possible role as an SAM-dependent MTase was therefore given by the findings of Multiple sequence alignment (MSA), MD, and molecular dynamic modeling. These in silico data suggest that the investigated HP might be used as a useful adjunct in the investigation of Pasteurella infections and the development of drugs to treat zoonotic pasteurellosis.

In silico analysis reveals mir-98-5p as a potential inhibitor of tumor cell proliferation and metastasis in colorectal cancer by targeting the fzd3 receptor of the Wnt signaling pathway.

BACKGROUND: Colorectal Cancer (CRC) is the third most common cancer type and the second leading cause of cancer-related deaths worldwide. However, the existing treatment, as well as prognosis strategies for CRC patients, need to be improved in order to increase the chance of survival. Targeted therapies of CRC, as opposed to ordinary therapies, target key biological features and pathways of cancerous cells hence minimizing the subsequent damage to normal cells. MicroRNAs have been reported to play a crucial role in inhibiting and/or suppressing major pathways in various cancer types by targeting transcripts of key genes in such pathways. METHODS: The purpose of this study was to analyze in silico the differentially expressed genes from five microarray datasets of patients with CRC. Furthermore, miRNAs were investigated to inhibit cancer cell proliferation and metastasis by targeting a key gene-frizzled receptor 3 (FZD3) in the Wnt signaling pathway. RESULTS: The Wnt pathway receptor FZD3 is upregulated in CRC along with other pathway genes, which play a critical role in tumorigenesis. In contrast, miR-98-5p inhibits the activity of FZD3 by binding directly to the 3'UTR of its mRNA, therefore exerting a suppressor effect on colorectal tumors. CONCLUSION: The study reveals miR-98-5p as a novel target of FZD3 and an inhibitor of the Wnt signaling pathway hence being a potential candidate for developing targeted therapies against CRC.

Genomic surveillance unfolds the SARS-CoV-2 transmission and divergence dynamics in Bangladesh.

The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4,622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7,659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure. Together with an ongoing genomic surveillance program, these data will contribute to a better understanding of SARS-CoV-2, as well as its evolution pattern and pandemic characteristics in Bangladesh.

An in-silico study of the mutation-associated effects on the spike protein of SARS-CoV-2, Omicron variant.

The emergence of Omicron (B.1.1.529), a new Variant of Concern in the COVID-19 pandemic, while accompanied by the ongoing Delta variant infection, has once again fueled fears of a new infection wave and global health concern. In the Omicron variant, the receptor-binding domain (RBD) of its spike glycoprotein is heavily mutated, a feature critical for the transmission rate of the virus by interacting with hACE2. In this study, we used a combination of conventional and advanced neural network-based in silico approaches to predict how these mutations would affect the spike protein. The results demonstrated a decrease in the electrostatic potentials of residues corresponding to receptor recognition sites, an increase in the alkalinity of the protein, a change in hydrophobicity, variations in functional residues, and an increase in the percentage of alpha-helix structure. Moreover, several mutations were found to modulate the immunologic properties of the potential epitopes predicted from the spike protein. Our next step was to predict the structural changes of the spike and their effect on its interaction with the hACE2. The results revealed that the RBD of the Omicron variant had a higher affinity than the reference. Moreover, all-atom molecular dynamics simulations concluded that the RBD of the Omicron variant exhibits a more dispersed interaction network since mutations resulted in an increased number of hydrophobic interactions and hydrogen bonds with hACE2.

Environmental prevalence of toxigenic Vibrio cholerae O1 in Bangladesh coincides with V. cholerae non-O1 non-O139 genetic variants which overproduce autoinducer-2.

Prevalence of toxigenic Vibrio cholerae O1 in aquatic reservoirs in Bangladesh apparently increases coinciding with the occurrence of seasonal cholera epidemics. In between epidemics, these bacteria persist in water mostly as dormant cells, known as viable but non-culturable cells (VBNC), or conditionally viable environmental cells (CVEC), that fail to grow in routine culture. CVEC resuscitate to active cells when enriched in culture medium supplemented with quorum sensing autoinducers CAI-1 or AI-2 which are signal molecules that regulate gene expression dependent on cell density. V. cholerae O1 mutant strains with inactivated cqsS gene encoding the CAI-1 receptor has been shown to overproduce AI-2 that enhance CVEC resuscitation in water samples. Since V. cholerae non-O1 non-O139 (non-cholera-vibrios) are abundant in aquatic ecosystems, we identified and characterized naturally occurring variant strains of V. cholerae non-O1 non-O139 which overproduce AI-2, and monitored their co-occurrence with V. cholerae O1 in water samples. The nucleotide sequence and predicted protein products of the cqsS gene carried by AI-2 overproducing variant strains showed divergence from that of typical V. cholerae O1 or non-O1 strains, and their culture supernatants enhanced resuscitation of CVEC in water samples. Furthermore, prevalence of V. cholerae O1 in the aquatic environment was found to coincide with an increase in AI-2 overproducing non-O1 non-O139 strains. These results suggest a possible role of non-cholera vibrios in the environmental biology of the cholera pathogen, in which non-O1 non-O139 variant strains overproducing AI-2 presumably contribute in resuscitation of the latent pathogen, leading to seasonal cholera epidemics. Importance. Toxigenic Vibrio cholerae which causes seasonal epidemics of cholera persists in aquatic reservoirs in endemic areas. The bacteria mostly exist in a dormant state during inter-epidemic periods, but periodically resuscitate to the active form. The resuscitation is enhanced by signal molecules called autoinducers (AIs). Toxigenic V. cholerae can be recovered from water samples that normally test negative for the organism in conventional culture, by supplementing the culture medium with exogenous AIs. V. cholerae belonging to the non-O1 non-O139 serogroups which do not cause cholera are also abundant in natural waters, and they are capable of producing AIs. In this study we characterized V. cholerae non-O1 non-O139 variant strains which overproduce an autoinducer called AI-2, and found that the abundance of the cholera pathogen in aquatic reservoirs correlates with an increase in the AI-2 overproducing strains. Our results suggest a probable role of these variant strains in the environmental biology and epidemiology of toxigenic V. cholerae, and may lead to novel means for surveillance, prevention and control of cholera.

In silico comparative genomics of SARS-CoV-2 to determine the source and diversity of the pathogen in Bangladesh.

The COVID19 pandemic caused by SARS-CoV-2 virus has severely affected most countries of the world including Bangladesh. We conducted comparative analysis of publicly available whole-genome sequences of 64 SARS-CoV-2 isolates in Bangladesh and 371 isolates from another 27 countries to predict possible transmission routes of COVID19 to Bangladesh and genomic variations among the viruses. Phylogenetic analysis indicated that the pathogen was imported in Bangladesh from multiple countries. The viruses found in the southern district of Chattogram were closely related to strains from Saudi Arabia whereas those in Dhaka were similar to that of United Kingdom and France. The 64 SARS-CoV-2 sequences from Bangladesh belonged to three clusters. Compared to the ancestral SARS-CoV-2 sequence reported from China, the isolates in Bangladesh had a total of 180 mutations in the coding region of the genome, and 110 of these were missense. Among these, 99 missense mutations (90%) were predicted to destabilize protein structures. Remarkably, a mutation that leads to an I300F change in the nsp2 protein and a mutation leading to D614G change in the spike protein were prevalent in SARS-CoV-2 genomic sequences, and might have influenced the epidemiological properties of the virus in Bangladesh.