Sushama Telwatte
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Recent Grants
Grant: Close
Novel assays for characterizing SARS-CoV-2 transcription
Open Date: 2020-05-01
Close Date: 2020-11-01
Grant: Close
Single cell transcriptomics of ex vivo HIV-infected cells
Open Date: 2020-02-01
Close Date: 2022-01-01
Grant: Close
Defining the cellular and viral factors underlying HIV latency at the single cell
Open Date: 2019-03-01
Close Date: 2020-03-01
Grant: Close
Role of silent mutations K65K and K66K in subtype B HIV-1 reverse transcriptase selected during drug therapy
Open Date: 2015-06-01
Close Date: 2015-08-01
Grant: Close
Role of silent mutations K65K and K66K in subtype B HIV-1 reverse transcriptase selected during drug therapy
Open Date: 2011-05-01
Close Date: 2015-05-01
Articles (10)
In most people living with HIV (PLWH) on effective antiretroviral therapy (ART), cell-associated viral transcripts are readily detectable in CD4+ T cells despite the absence of viremia. Quantification of HIV RNA species provides insights into the transcriptional activity of proviruses that persist in cells and tissues throughout the body during ART (‘HIV reservoir’). One such technique for HIV RNA quantitation, ‘HIV transcription profiling’, developed in the Yukl laboratory, measures a series of HIV RNA species using droplet digital PCR. To take advantage of advances in digital (d)PCR, we adapted the ‘HIV transcription profiling’ technique to Qiagen’s dPCR platform (QIAcuity) and compared its performance to droplet digital (dd)PCR (Bio-Rad QX200 system). Using RNA standards, the two technologies were tested in parallel and assessed for multiple parameters including sensitivity, specificity, linearity, and intra- and inter-assay variability. The newly validated dPCR assays were then applied to samples from PLWH to determine HIV transcriptional activity relative to HIV reservoir size. We report that HIV transcriptional profiling was readily adapted to dPCR and assays performed similarly to ddPCR, with no differences in assay characteristics. We applied these assays in a cohort of 23 PLWH and found that HIV reservoir size, based on genetically intact proviral DNA, does not predict HIV transcriptional activity. In contrast, levels of total DNA correlated with levels of most HIV transcripts (initiated, proximally and distally elongated, unspliced, and completed, but not multiply spliced), suggesting that a considerable proportion of HIV transcripts likely originate from defective proviruses. These findings may have implications for measuring and assessing curative strategies and clinical trial outcomes.
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2023
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2022
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2022
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2022
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2021
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2021
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2020
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2020
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2020
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2020
Collaborators (3)
Joseph Wong
Professor
University of California, San Francisco
Yijia Li
Assistant Professor
UPMC Presbyterian
Steven A. Yukl
University of California
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