Biology subjects

Sekirov, I.

Publications and source records attributed to Sekirov, I..

4 recordsLinked to original sources

bioRxiv2023

Challenges of Whole Genome Sequencing based Molecular Identification of Zoonotic Tuberculosis caused by Mycobacterium orygis

A recently described member of the Mycobacterium tuberculosis complex (MTBC) is Mycobacterium orygis, which can cause disease primarily in animals but also in humans. Although M. orygis has been reported from different geographic regions around the world, due to a lack of proper identification techniques, the contribution of this emerging pathogen to the global burden of zoonotic tuberculosis is not fully understood. In the present work, we report single nucleotide polymorphisms (SNPs) analysis using whole genome sequencing (WGS) that can accurately identify M. orygis and differentiate it from other members of MTBC species. WGS-based SNPs analysis was performed for 61 isolates from different Provinces in Canada that were identified as M. orygis. A total of 56 M. orygis sequences from the public databases were also included in the analysis. Several unique SNPs in gyrB, PPE55, Rv2042c, leuS, mmpL6, and mmpS6 genes were used to determine their effectiveness as genetic markers for the identification of M. orygis. To the best of our knowledge, five of these SNPs, viz., gyrB277 (A[->]G), gyrB1478 (T[->]C), leuS1064 (A[->]T), mmpL6486 (T[->]C), and mmpS6334 (C[->]G) are reported for the first time in this study. Our results also revealed several SNPs specific to other species within MTBC. The phylogenetic analysis shows that studied genomes were genetically diverse and clustered with M. orygis sequences of human and animal origin reported from different geographic locations. Therefore, the present study provides a new insight into the high confidence identification of M. orygis from MTBC species based on WGS data, which can be useful for reference and diagnostic laboratories.

microbiology↗

bioRxiv2022

Comparing transmission reconstruction models with Mycobacterium tuberculosis whole genome sequence data

Pathogen genomic epidemiology is now routinely used worldwide to interrogate infectious disease dynamics. Multiple computational tools that reconstruct transmission networks by coupling genomic data with epidemiological modelling have been developed. The resulting inferences are often used to inform outbreak investigations, yet to date, the performance of these transmission reconstruction tools has not been compared specifically for tuberculosis, a disease process with complex epidemiology that includes variable latency periods and within-host heterogeneity. Here, we carried out a systematic comparison of seven publicly available transmission reconstruction tools, evaluating their accuracy in predicting transmission events in both simulated and real-world Mycobacterium tuberculosis outbreaks. No tool was able to fully resolve transmission networks, though both the single-tree and multi-tree input implementations of TransPhylo identified the most epidemiologically supported transmission events and the fewest false positive links. We observed a high degree of variability in the transmission networks inferred by each approach. Our findings may inform an end-users choice of tools in future tuberculosis transmission analyses and underscore the need for caution when interpreting transmission networks produced using probabilistic approaches.

bioinformatics↗

bioRxiv2021

SARS-CoV-2 Omicron Variant: ACE2 Binding, Cryo-EM Structure of Spike Protein-ACE2 Complex and Antibody Evasion

The newly reported Omicron variant is poised to replace Delta as the most rapidly spread SARS-CoV-2 variant across the world. Cryo-EM structural analysis of the Omicron variant spike protein in complex with human ACE2 reveals new salt bridges and hydrogen bonds formed by mutated residues R493, S496 and R498 in the RBD with ACE2. These interactions appear to compensate for other Omicron mutations such as K417N known to reduce ACE2 binding affinity, explaining our finding of similar biochemical ACE2 binding affinities for Delta and Omicron variants. Neutralization assays show that pseudoviruses displaying the Omicron spike protein exhibit increased antibody evasion, with greater evasion observed in sera obtained from unvaccinated convalescent patients as compared to doubly vaccinated individuals (8-vs 3-fold). The retention of strong interactions at the ACE2 interface and the increase in antibody evasion are molecular factors that likely contribute to the increased transmissibility of the Omicron variant.

biochemistry↗

bioRxiv2021

Structural and Biochemical Rationale for Enhanced Spike Protein Fitness in Delta and Kappa SARS-CoV-2 Variants

The Delta and Kappa variants of SARS-CoV-2 co-emerged in India in late 2020, with the Delta variant underlying the resurgence of COVID-19, even in countries with high vaccination rates. In this study, we assess structural and biochemical aspects of viral fitness for these two variants using cryo-electron microscopy (cryo-EM), ACE2-binding and antibody neutralization analyses. Both variants demonstrate escape of antibodies targeting the N-terminal domain, an important immune hotspot for neutralizing epitopes. Compared to wild-type and Kappa lineages, Delta variant spike proteins show modest increase in ACE2 affinity, likely due to enhanced electrostatic complementarity at the RBD-ACE2 interface, which we characterize by cryo-EM. Unexpectedly, Kappa variant spike trimers form a novel head-to-head dimer-of-trimers assembly, which we demonstrate is a result of the E484Q mutation. The combination of increased antibody escape and enhanced ACE2 binding provides an explanation, in part, for the rapid global dominance of the Delta variant.

biochemistry↗