July 19, 2019  |  

Single-molecule sequencing reveals the molecular basis of multidrug-resistance in ST772 methicillin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of hospital-associated infection, but there is growing awareness of the emergence of multidrug-resistant lineages in community settings around the world. One such lineage is ST772-MRSA-V, which has disseminated globally and is increasingly prevalent in India. Here, we present the complete genome sequence of DAR4145, a strain of the ST772-MRSA-V lineage from India, and investigate its genomic characteristics in regards to antibiotic resistance and virulence factors.Sequencing using single-molecule real-time technology resulted in the assembly of a single continuous chromosomal sequence, which was error-corrected, annotated and compared to nine draft genome assemblies of ST772-MRSA-V from Australia, Malaysia and India. We discovered numerous and redundant resistance genes associated with mobile genetic elements (MGEs) and known core genome mutations that explain the highly antibiotic resistant phenotype of DAR4145. Staphylococcal toxins and superantigens, including the leukotoxin Panton-Valentinin Leukocidin, were predominantly associated with genomic islands and the phage f-IND772PVL. Some of these mobile resistance and virulence factors were variably present in other strains of the ST772-MRSA-V lineage.The genomic characteristics presented here emphasize the contribution of MGEs to the emergence of multidrug-resistant and highly virulent strains of community-associated MRSA. Antibiotic resistance was further augmented by chromosomal mutations and redundancy of resistance genes. The complete genome of DAR4145 provides a valuable resource for future investigations into the global dissemination and phylogeography of ST772-MRSA-V.

July 19, 2019  |  

Recent advances in inferring viral diversity from high-throughput sequencing data.

Rapidly evolving RNA viruses prevail within a host as a collection of closely related variants, referred to as viral quasispecies. Advances in high-throughput sequencing (HTS) technologies have facilitated the assessment of the genetic diversity of such virus populations at an unprecedented level of detail. However, analysis of HTS data from virus populations is challenging due to short, error-prone reads. In order to account for uncertainties originating from these limitations, several computational and statistical methods have been developed for studying the genetic heterogeneity of virus population. Here, we review methods for the analysis of HTS reads, including approaches to local diversity estimation and global haplotype reconstruction. Challenges posed by aligning reads, as well as the impact of reference biases on diversity estimates are also discussed. In addition, we address some of the experimental approaches designed to improve the biological signal-to-noise ratio. In the future, computational methods for the analysis of heterogeneous virus populations are likely to continue being complemented by technological developments. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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