High-Density Amplicon Sequencing Identifies Community Spread and Ongoing Evolution of SARS-CoV-2 in the Southern United States

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is constantly evolving. Prior studies focused on high-case-density locations, such as the northern and western metropolitan areas of the United States. This study demonstrates continued SARS-CoV-2 evolution in a suburban southern region of the United States by high-density amplicon sequencing of symptomatic cases. 57% of strains carry the spike D614G variant, which is associated with higher genome copy numbers, and its prevalence expands with time. Four strains carry a deletion in a predicted stem loop of the 3′ UTR. The data are consistent with community spread within local populations and the larger continental United States. The data instill confidence in current testing sensitivity and validate “testing by sequencing” as an option to uncover cases, particularly nonstandard coronavirus disease 2019 (COVID-19) clinical presentations. This study contributes to the understanding of COVID-19 through an extensive set of genomes from a non-urban setting and informs vaccine design by defining D614G as a dominant and emergent SARS-CoV-2 isolate in the United States

Viral Profiling Identifies Multiple Subtypes of Kaposi's Sarcoma

ABSTRACTKaposi’s sarcoma (KS), caused by KS-associated herpesvirus (KSHV), is the most common cancer among HIV-infected patients in Malawi and in the United States today. In Malawi, KSHV is endemic. We conducted a cross-sectional study of patients with HIV infection and KS with no history of chemo- or antiretroviral therapy (ART). Seventy patients were enrolled. Eighty-one percent had T1 (advanced) KS. Median CD4 and HIV RNA levels were 181cells/mm3 and 138,641 copies/ml, respectively. We had complete information and suitable plasma and biopsy samples for 66 patients. For 59/66 (89%) patients, a detectable KSHV load was found in plasma (median, 2,291 copies/ml; interquartile range [IQR], 741 to 5,623). We utilized a novel KSHV real-time quantitative PCR (qPCR) array with multiple primers per open reading frame to examine KSHV transcription. Seventeen samples exhibited only minimal levels of KSHV mRNAs, presumably due to the limited number of infected cells. For all other biopsy samples, the viral latency locus (LANA, vCyc, vFLIP, kaposin, and microRNAs [miRNAs]) was transcribed abundantly, as was K15 mRNA. We could identify two subtypes of treatment-naive KS: lesions that transcribed viral RNAs across the length of the viral genome and lesions that displayed only limited transcription restricted to the latency locus. This finding demonstrates for the first time the existence of multiple subtypes of KS lesions in HIV- and KS-treatment naive patients.IMPORTANCEKS is the leading cancer in people infected with HIV worldwide and is causally linked to KSHV infection. Using viral transcription profiling, we have demonstrated the existence of multiple subtypes of KS lesions for the first time in HIV- and KS-treatment-naive patients. A substantial number of lesions transcribe mRNAs which encode the viral kinases and hence could be targeted by the antiviral drugs ganciclovir or AZT in addition to chemotherapy

SeqAn An efficient, generic C++ library for sequence analysis

<p>Abstract</p> <p>Background</p> <p>The use of novel algorithmic techniques is pivotal to many important problems in life science. For example the sequencing of the human genome <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> would not have been possible without advanced assembly algorithms. However, owing to the high speed of technological progress and the urgent need for bioinformatics tools, there is a widening gap between state-of-the-art algorithmic techniques and the actual algorithmic components of tools that are in widespread use.</p> <p>Results</p> <p>To remedy this trend we propose the use of SeqAn, a library of efficient data types and algorithms for sequence analysis in computational biology. SeqAn comprises implementations of existing, practical state-of-the-art algorithmic components to provide a sound basis for algorithm testing and development. In this paper we describe the design and content of SeqAn and demonstrate its use by giving two examples. In the first example we show an application of SeqAn as an experimental platform by comparing different exact string matching algorithms. The second example is a simple version of the well-known MUMmer tool rewritten in SeqAn. Results indicate that our implementation is very efficient and versatile to use.</p> <p>Conclusion</p> <p>We anticipate that SeqAn greatly simplifies the rapid development of new bioinformatics tools by providing a collection of readily usable, well-designed algorithmic components which are fundamental for the field of sequence analysis. This leverages not only the implementation of new algorithms, but also enables a sound analysis and comparison of existing algorithms.</p