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Lin CH, Yang XR, Lin MW, Chang HJ, Lee CH, Lin CS. Engineering a NanoBiT biosensor for detecting angiotensin-converting enzyme-2 (hACE2) interaction with SARS-CoV-2 spike protein and screening the inhibitors to block hACE2 and spike interaction. Biosens Bioelectron 2024; 263:116630. [PMID: 39102773 DOI: 10.1016/j.bios.2024.116630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 08/01/2024] [Accepted: 08/01/2024] [Indexed: 08/07/2024]
Abstract
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is facilitated by its trimeric surface spike protein, which binds to the human angiotensin-converting enzyme 2 (hACE2) receptor. This critical interaction facilitates viral entry and is a primary target for therapeutic intervention against COVID-19. However, it is difficult to fully optimize viral infection using existing protein-protein interaction methods. Herein, we introduce a nano-luciferase binary technology (NanoBiT)-based pseudoviral sensor designed to stimulate the dynamics of viral infection in both living cells and animals. Infection progression can be dynamically visualized via a rapid increase in luminescence within 3 h using an in vivo imaging system (IVIS). Inhibition of viral infection by baicalein and baicalin was evaluated using a NanoBiT-based pseudoviral sensor. These results indicate that the inhibitory efficacy of baicalein was strengthened by targeting the spike protein, whereas baicalin targeted the hACE2 protein. Additionally, under optimized conditions, baicalein and baicalin provided a synergistic combination to inhibit pseudoviral infection. Live bioluminescence imaging was used to evaluate the in vivo effects of baicalein and baicalin treatment on LgBiT-hACE2 mice infected with the BA.2-SmBiT spike pseudovirus. This innovative bioluminescent system functions as a sensitive and early-stage quantitative viral transduction in vitro and in vivo. This platform provides novel opportunities for studying the molecular biology of animal models.
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Affiliation(s)
- Cheng-Han Lin
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan
| | - Xin-Rui Yang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan
| | - Meng-Wei Lin
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan
| | - Ho-Ju Chang
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan
| | - Che-Hsiung Lee
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan; Department of Plastic and Reconstructive Surgery, Chang Gung Memorial Hospital, Linkou, Taoyuan, 333, Taiwan
| | - Chih-Sheng Lin
- Department of Biological Science and Technology, National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan; Center for Intelligent Drug Systems and Smart Bio-devices (IDS(2)B), National Yang Ming Chiao Tung University, Hsinchu, 300, Taiwan.
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Subroyen S, Pillay L, Bux F, Kumari S. Evaluating storage conditions and enhancement strategies on viral biomarker recovery for WBE applications. WATER SCIENCE AND TECHNOLOGY : A JOURNAL OF THE INTERNATIONAL ASSOCIATION ON WATER POLLUTION RESEARCH 2024; 90:213-224. [PMID: 39007315 DOI: 10.2166/wst.2024.203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Accepted: 05/31/2024] [Indexed: 07/16/2024]
Abstract
Wastewater-based epidemiology (WBE) is a valuable disease surveillance tool. However, little is known on how factors such as transportation, storage, and wastewater characteristics influence the accuracy of the quantification methods. Hence, this study investigated the impact of storage temperatures and physicochemical characteristics of wastewater on SARS-CoV-2 and influenza A stability using droplet digital PCR. Additionally, strategies to enhance viral recovery were explored. Municipal influent wastewater stored between ±25 and -80 °C was assessed for a period of 84 days to determine viral degradation. Degradation up to 94.1% of influenza A and SARS-CoV-2 was observed in all samples with the highest at ±25 °C. Viral degradation was correlated to the changes in wastewater physicochemical characteristics. The low degradation observed of SARS-CoV-2 in the spiked pellets were indicative of viral adhesion to wastewater solids, which correlated with changes in pH. Ultrasonication frequencies ranging from 4 to 16 kHz, increased SARS-CoV-2 concentrations in the supernatant between 3.30 and 35.65%, indicating viral RNA attachment to wastewater solids. These results highlight the importance of additional pretreatment methods for maximizing RNA recovery from wastewater samples. Based on these findings, it was deduced that wastewater preservation studies are essential, and pretreatment should be included in the WBE methodology.
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Affiliation(s)
- Sueyanka Subroyen
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Leanne Pillay
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Faizal Bux
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
| | - Sheena Kumari
- Institute for Water and Wastewater Technology, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa E-mail:
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Haltom J, Trovao NS, Guarnieri J, Vincent P, Singh U, Tsoy S, O'Leary CA, Bram Y, Widjaja GA, Cen Z, Meller R, Baylin SB, Moss WN, Nikolau BJ, Enguita FJ, Wallace DC, Beheshti A, Schwartz R, Wurtele ES. SARS-CoV-2 Orphan Gene ORF10 Contributes to More Severe COVID-19 Disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.27.23298847. [PMID: 38076862 PMCID: PMC10705665 DOI: 10.1101/2023.11.27.23298847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
The orphan gene of SARS-CoV-2, ORF10, is the least studied gene in the virus responsible for the COVID-19 pandemic. Recent experimentation indicated ORF10 expression moderates innate immunity in vitro. However, whether ORF10 affects COVID-19 in humans remained unknown. We determine that the ORF10 sequence is identical to the Wuhan-Hu-1 ancestral haplotype in 95% of genomes across five variants of concern (VOC). Four ORF10 variants are associated with less virulent clinical outcomes in the human host: three of these affect ORF10 protein structure, one affects ORF10 RNA structural dynamics. RNA-Seq data from 2070 samples from diverse human cells and tissues reveals ORF10 accumulation is conditionally discordant from that of other SARS-CoV-2 transcripts. Expression of ORF10 in A549 and HEK293 cells perturbs immune-related gene expression networks, alters expression of the majority of mitochondrially-encoded genes of oxidative respiration, and leads to large shifts in levels of 14 newly-identified transcripts. We conclude ORF10 contributes to more severe COVID-19 clinical outcomes in the human host.
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Affiliation(s)
- Jeffrey Haltom
- Department of Genetics Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- COVID-19 International Research Team, Medford, MA 02155, USA
| | - Nidia S Trovao
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA
- COVID-19 International Research Team, Medford, MA 02155, USA
| | - Joseph Guarnieri
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- COVID-19 International Research Team, Medford, MA 02155, USA
| | - Pan Vincent
- Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, 20892, USA
| | - Urminder Singh
- Bioinformatics and Computational Biology Program, and Genetics Program, Iowa State University, Ames, IA 50011, USA
| | - Sergey Tsoy
- Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Collin A O'Leary
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA
| | - Yaron Bram
- Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Gabrielle A Widjaja
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Zimu Cen
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Robert Meller
- Morehouse School of Medicine, Atlanta, GA , 30310-1495, USA
| | - Stephen B Baylin
- Department of Oncology, Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21231
- Van Andel Research Institute, Grand Rapids, MI 49503
| | - Walter N Moss
- Bioinformatics and Computational Biology Program, and Genetics Program, Iowa State University, Ames, IA 50011, USA
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA
| | - Basil J Nikolau
- Bioinformatics and Computational Biology Program, and Genetics Program, Iowa State University, Ames, IA 50011, USA
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011, USA
| | - Francisco J Enguita
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
| | - Douglas C Wallace
- Center for Mitochondrial and Epigenomic Medicine, Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Division of Human Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Afshin Beheshti
- COVID-19 International Research Team, Medford, MA 02155, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Blue Marble Space Institute of Science, Seattle, WA, 98104 USA
| | - Robert Schwartz
- Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Physiology, Biophysics and Systems Biology, Weill Cornell Medicine, New York, NY, USA
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Eve Syrkin Wurtele
- Bioinformatics and Computational Biology Program, and Genetics Program, Iowa State University, Ames, IA 50011, USA
- Department of Genetics Development and Cell Biology, Iowa State University, Ames, IA 50011, USA
- COVID-19 International Research Team, Medford, MA 02155, USA
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Niazi SK. The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives. Drug Des Devel Ther 2023; 17:2691-2725. [PMID: 37701048 PMCID: PMC10493153 DOI: 10.2147/dddt.s424991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/24/2023] [Indexed: 09/14/2023] Open
Abstract
Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computing, building on technologies that humanity has developed over millions of years-from the abacus to quantum computers. These tools have reached a pivotal moment in their development. In 2021 alone, the U.S. Food and Drug Administration (FDA) received over 100 product registration submissions that heavily relied on AI/ML for applications such as monitoring and improving human performance in compiling dossiers. To ensure the safe and effective use of AI/ML in drug discovery and manufacturing, the FDA and numerous other U.S. federal agencies have issued continuously updated, stringent guidelines. Intriguingly, these guidelines are often generated or updated with the aid of AI/ML tools themselves. The overarching goal is to expedite drug discovery, enhance the safety profiles of existing drugs, introduce novel treatment modalities, and improve manufacturing compliance and robustness. Recent FDA publications offer an encouraging outlook on the potential of these tools, emphasizing the need for their careful deployment. This has expanded market opportunities for retraining personnel handling these technologies and enabled innovative applications in emerging therapies such as gene editing, CRISPR-Cas9, CAR-T cells, mRNA-based treatments, and personalized medicine. In summary, the maturation of AI/ML technologies is a testament to human ingenuity. Far from being autonomous entities, these are tools created by and for humans designed to solve complex problems now and in the future. This paper aims to present the status of these technologies, along with examples of their present and future applications.
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