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Akter, S.

Publications and source records attributed to Akter, S..

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A reverse-transcription/RNase H based protocol for depletion of mosquito ribosomal RNA facilitates viral intrahost evolution analysis, transcriptomics and pathogen discovery.

Studies aimed at identifying novel viral sequences or assessing intrahost viral variation require sufficient sequencing coverage to assemble contigs and make accurate variant calling at low frequencies. Many samples come from host tissues where ribosomal RNA represents more than 90% of total RNA preparations, making unbiased sequencing of viral samples inefficient and highly expensive, as many reads will be wasted on cellular RNAs. In the presence of this amount of ribosomal RNA, it is difficult to achieve sufficient sequencing depth to perform analyses such as variant calling, haplotype prediction, virus population analyses, virus discovery or transcriptomic profiling. Many methods for depleting unwanted RNA or enriching RNA of interest have been devised, including poly-A selection, RNase H based specific depletion, duplex-specific nuclease treatment and hybrid capture selection, among others. Although these methods can be efficient, they either cannot be used for some viruses (i.e. non-polyadenylated viruses), have been optimized for use in a single species, or have the potential to introduce bias. In this study, we describe a novel approach that uses an RNaseH possessing reverse transcriptase coupled with selective probes for ribosomal RNA designed to work broadly for three medically relevant mosquito genera; Aedes, Anopheles, and Culex. We demonstrate significant depletion of rRNA using multiple assessment techniques from a variety of sample types, including whole mosquitoes and mosquito midgut contents from FTA cards. To demonstrate the utility of our approach, we describe novel insect-specific virus genomes from numerous species of field collected mosquitoes that underwent rRNA depletion, thereby facilitating their detection. The protocol is straightforward, relatively low-cost and requires only common laboratory reagents and the design of several small oligonucleotides specific to the species of interest. This approach can be adapted for use with other organisms with relative ease, thus potentially aiding virus population genetics analyses, virus discovery and transcriptomic profiling in both laboratory and field samples.

microbiology

The relationship between transmission time and clustering methods in Mycobacterium tuberculosis epidemiology

BackgroundTracking recent transmission is a vital part of controlling widespread pathogens such as Mycobacterium tuberculosis. Multiple methods with specific performance characteristics exist for detecting recent transmission chains, usually by clustering strains based on genotype similarities. With such a large variety of methods available, informed selection of an appropriate approach for determining transmissions within a given setting/time period is difficult.\n\nMethodsThis study combines whole genome sequence (WGS) data derived from 324 isolates collected 2005-2010 in Kinshasa, Democratic Republic of Congo (DRC), a high endemic setting, with phylodynamics to unveil the timing of transmission events posited by a variety of standard genotyping methods. Clustering data based on Spoligotyping, 24-loci MIRU-VNTR typing, WGS based SNP (Single Nucleotide Polymorphism) and core genome multi locus sequence typing (cgMLST) typing were evaluated.\n\nFindingsOur results suggest that clusters based on Spoligotyping could encompass transmission events that occurred over 70 years prior to sampling while 24-loci-MIRU-VNTR often represented two or more decades of transmission. Instead, WGS based genotyping applying low SNP or cgMLST allele thresholds allows for determination of recent transmission events in timespans of up to 10 years e.g. for a 5 SNP/allele cut-off.\n\nInterpretationWith the rapid uptake of WGS methods in surveillance and outbreak tracking, the findings obtained in this study can guide the selection of appropriate clustering methods for uncovering relevant transmission chains within a given time-period. For high resolution cluster analyses, WGS-SNP and cgMLST based analyses have similar clustering/timing characteristics even for data obtained from a high incidence setting.

epidemiology