Published June 3, 2021 | Version v1
Poster Open

In silico design of a SHERLOCK-based point-of-care diagnostic for HIV-1 drug resistance

Authors/Creators

  • 1. Scarsdale High School, Scarsdale, NY, USA
  • 2. Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
  • 3. School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, USA
  • 4. Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA; Center for Molecular Virology and Translational Neuroscience, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, USA; Sydney Kimmel Cancer Center, Thomas Jefferson University, Philadelphia, PA, USA
  • 5. Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA; Center for Molecular Virology and Translational Neuroscience, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, USA

Description

Recent developments in antiretroviral therapy (ART) have reduced human immunodeficiency virus type 1 (HIV-1) infection from a potent killer to a chronic illness. However, major HIV-1 drug resistance mutations (DRMs) hamper ART’s efficacy. Low-resource regions cannot screen for DRMs due to poor infrastructure and high testing costs. To overcome this obstacle, we propose using Specific High-sensitivity Enzymatic Reporter unLOCKing (SHERLOCK) to act as a rapid and inexpensive HIV-1 DRM diagnostic assay. Here, we present an in silico proof-of-concept using HIV-1 protease. SHERLOCK employs Loop-mediated isothermal AMPlification (LAMP) and a Cas12b-guide RNA (gRNA) complex to isothermally amplify protease sequences and detect any amplified DRM targets, respectively. Different LAMP primers and gRNAs were packaged together to account for HIV-1 genetic variation. DRMs and sequences were collected from the 2019 IAS-USA Drug Resistance Mutations List and Stanford HIV Sequence Database, respectively. LAMP primers were scored by their target diversity and thermodynamic characteristics to select sensitive primer sets. Sequences not targeted by these sets were re-inputted into the pipeline. The best sets from three iterations were combined into a sensitive (70.5%) package. Next, DRM-specific gRNAs were ranked by F3-score and the top 128 gRNAs with ≥95% specificity for each DRM were considered for packaging. gRNAs were incrementally added to DRM-specific packages until the following ranked gRNA would only provide an additional sensitivity of <1%. All packages were specific (92.2%±4.3%) and a majority (21/24) were highly sensitive (≥90%). DRM-specific packages were then combined into highly sensitive (95.2%±2.1%) drug-specific meta-packages. Future directions entail improving LAMP primer and gRNA robustness and validating package performances in vitro.

Notes

This work is supported by NIMH R01 MH110360 (Contact PI, BW), NIMH P30 MH092177 (CNAC/CTRC, Drexel Component PI, BW), NIMH T32 MH079785 (Drexel Component PI, BW)

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