1
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Velu PD, Sipley J, Marino J, Ghanshani S, Lukose G, Cong L, Serrano L, Ly T, Yeh RK, Wu F, Mansukhani M, Berry GJ, Rennert H. Evaluation of a Zoonotic Orthopoxvirus PCR Assay for the Detection of Mpox Virus Infection. J Mol Diagn 2023; 25:740-747. [PMID: 37474002 DOI: 10.1016/j.jmoldx.2023.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 06/02/2023] [Accepted: 06/12/2023] [Indexed: 07/22/2023] Open
Abstract
An epidemic caused by an outbreak of mpox (formerly monkeypox) in May 2022 rapidly spread internationally, requiring an urgent response from the clinical diagnostics community. A detailed description of the clinical validation and implementation of a laboratory-developed real-time PCR test for detecting nonvariola Orthopoxvirus-specific DNA based on the newly designed RealStar Zoonotic Orthopoxvirus assay is presented. The validation was performed using an accuracy panel (n = 97) comprising skin lesion swabs in universal transport media and from mpox virus genomic DNA spiked into pooled mpox virus-negative remnant universal transport media of lesion specimens submitted for routine clinical testing in the NewYork-Presbyterian Hospital clinical laboratory system. Accuracy testing demonstrated excellent assay agreement between expected and observed results and comparable diagnostic performance to three different reference tests. Analytical sensitivity with 95% detection probability was 126 copies/mL, and analytical specificity, clinical sensitivity, and clinical specificity were 100%. In summary, the RealStar Zoonotic Orthopoxvirus assay provides a sensitive and reliable method for routine diagnosis of mpox infections.
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Affiliation(s)
- Priya D Velu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | - John Sipley
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | - Jamie Marino
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | | | - Georgi Lukose
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | - Lin Cong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | - Liliana Serrano
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York
| | - Thanh Ly
- NewYork-Presbyterian Hospital, New York, New York; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York
| | - Raymond K Yeh
- NewYork-Presbyterian Hospital, New York, New York; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York
| | - Fann Wu
- NewYork-Presbyterian Hospital, New York, New York; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York
| | - Mahesh Mansukhani
- NewYork-Presbyterian Hospital, New York, New York; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York
| | - Gregory J Berry
- NewYork-Presbyterian Hospital, New York, New York; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York
| | - Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; NewYork-Presbyterian Hospital, New York, New York.
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2
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Butler D, Mozsary C, Meydan C, Foox J, Rosiene J, Shaiber A, Danko D, Afshinnekoo E, MacKay M, Sedlazeck FJ, Ivanov NA, Sierra M, Pohle D, Zietz M, Gisladottir U, Ramlall V, Sholle ET, Schenck EJ, Westover CD, Hassan C, Ryon K, Young B, Bhattacharya C, Ng DL, Granados AC, Santos YA, Servellita V, Federman S, Ruggiero P, Fungtammasan A, Chin CS, Pearson NM, Langhorst BW, Tanner NA, Kim Y, Reeves JW, Hether TD, Warren SE, Bailey M, Gawrys J, Meleshko D, Xu D, Couto-Rodriguez M, Nagy-Szakal D, Barrows J, Wells H, O'Hara NB, Rosenfeld JA, Chen Y, Steel PAD, Shemesh AJ, Xiang J, Thierry-Mieg J, Thierry-Mieg D, Iftner A, Bezdan D, Sanchez E, Campion TR, Sipley J, Cong L, Craney A, Velu P, Melnick AM, Shapira S, Hajirasouliha I, Borczuk A, Iftner T, Salvatore M, Loda M, Westblade LF, Cushing M, Wu S, Levy S, Chiu C, Schwartz RE, Tatonetti N, Rennert H, Imielinski M, Mason CE. Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions. Nat Commun 2021; 12:1660. [PMID: 33712587 PMCID: PMC7954844 DOI: 10.1038/s41467-021-21361-7] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 01/25/2021] [Indexed: 02/08/2023] Open
Abstract
In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.
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Affiliation(s)
- Daniel Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Christopher Mozsary
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Joel Rosiene
- New York Genome Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Alon Shaiber
- New York Genome Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - David Danko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Matthew MacKay
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nikolay A Ivanov
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Clinical & Translational Science Center, Weill Cornell Medicine, New York, NY, USA
| | - Maria Sierra
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Diana Pohle
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Michael Zietz
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Undina Gisladottir
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Vijendra Ramlall
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
- Department of Cellular, Molecular Physiology & Biophysics, Columbia University, Columbia, NY, USA
| | - Evan T Sholle
- Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, USA
| | - Edward J Schenck
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Craig D Westover
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Ciaran Hassan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Benjamin Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | | | - Dianna L Ng
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Andrea C Granados
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Yale A Santos
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Venice Servellita
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Scot Federman
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Phyllis Ruggiero
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | | | | | | | | | | | | | | | | | | | | | - Justyna Gawrys
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Dmitry Meleshko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional Computational Biology & Medicine Program, Weill Cornell Medicine, New York, NY, USA
| | - Dong Xu
- Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, USA
| | | | - Dorottya Nagy-Szakal
- Biotia, Inc., New York, NY, USA
- Department of Cell Biology, SUNY Downstate Health Sciences University, New York, NY, USA
| | | | | | - Niamh B O'Hara
- Biotia, Inc., New York, NY, USA
- Department of Cell Biology, SUNY Downstate Health Sciences University, New York, NY, USA
| | - Jeffrey A Rosenfeld
- Rutgers Cancer Institute of New Jersey, New York, NJ, USA
- Department of Pathology, Robert Wood Johnson Medical School, New York, NJ, USA
| | - Ying Chen
- Rutgers Cancer Institute of New Jersey, New York, NJ, USA
| | - Peter A D Steel
- Department of Emergency Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Amos J Shemesh
- Department of Emergency Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jenny Xiang
- Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Angelika Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Daniela Bezdan
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | | | - Thomas R Campion
- Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - John Sipley
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Lin Cong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Arryn Craney
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Priya Velu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Ari M Melnick
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Sagi Shapira
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Iman Hajirasouliha
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Alain Borczuk
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Mirella Salvatore
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Massimo Loda
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Lars F Westblade
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Melissa Cushing
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Shixiu Wu
- Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, China
- Department of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, China
| | - Shawn Levy
- HudsonAlpha Discovery Institute, Huntsville, AL, USA
| | - Charles Chiu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, CA, USA
| | | | - Nicholas Tatonetti
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA.
| | - Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
| | - Marcin Imielinski
- New York Genome Center, New York, NY, USA.
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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3
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Velu P, Craney A, Ruggiero P, Sipley J, Cong L, Hissong EM, Loda M, Westblade LF, Cushing M, Rennert H. Rapid Implementation of Severe Acute Respiratory Syndrome Coronavirus 2 Emergency Use Authorization RT-PCR Testing and Experience at an Academic Medical Institution. J Mol Diagn 2020; 23:149-158. [PMID: 33285285 PMCID: PMC7718583 DOI: 10.1016/j.jmoldx.2020.10.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 10/11/2020] [Accepted: 10/21/2020] [Indexed: 01/19/2023] Open
Abstract
An epidemic caused by an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China in December 2019 has since rapidly spread internationally, requiring urgent response from the clinical diagnostics community. We present a detailed overview of the clinical validation and implementation of the first laboratory-developed real-time RT-PCR test offered in the NewYork-Presbyterian Hospital system following the Emergency Use Authorization issued by the US Food and Drug Administration. Nasopharyngeal and sputum specimens (n = 174) were validated using newly designed dual-target real-time RT-PCR (altona RealStar SARS-CoV-2 Reagent) for detecting SARS-CoV-2 in upper respiratory tract and lower respiratory tract specimens. Accuracy testing demonstrated excellent assay agreement between expected and observed values and comparable diagnostic performance to reference tests. The limit of detection was 2.7 and 23.0 gene copies per reaction for nasopharyngeal and sputum specimens, respectively. Retrospective analysis of 1694 upper respiratory tract specimens from 1571 patients revealed increased positivity in older patients and males compared with females, and an increasing positivity rate from approximately 20% at the start of testing to 50% at the end of testing 3 weeks later. Herein, we demonstrate that the assay accurately and sensitively identifies SARS-CoV-2 in multiple specimen types in the clinical setting and summarize clinical data from early in the epidemic in New York City.
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Affiliation(s)
- Priya Velu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Arryn Craney
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Phyllis Ruggiero
- Department of Pathology and Laboratory Medicine, NewYork-Presbyterian Hospital-Weill Cornell Medicine, New York, New York
| | - John Sipley
- Department of Pathology and Laboratory Medicine, NewYork-Presbyterian Hospital-Weill Cornell Medicine, New York, New York
| | - Lin Cong
- Department of Pathology and Laboratory Medicine, NewYork-Presbyterian Hospital-Weill Cornell Medicine, New York, New York
| | - Erika M Hissong
- Department of Pathology and Laboratory Medicine, NewYork-Presbyterian Hospital-Weill Cornell Medicine, New York, New York
| | - Massimo Loda
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Lars F Westblade
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York; Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, New York
| | - Melissa Cushing
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York
| | - Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, New York.
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4
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Butler DJ, Mozsary C, Meydan C, Danko D, Foox J, Rosiene J, Shaiber A, Afshinnekoo E, MacKay M, Sedlazeck FJ, Ivanov NA, Sierra M, Pohle D, Zietz M, Gisladottir U, Ramlall V, Westover CD, Ryon K, Young B, Bhattacharya C, Ruggiero P, Langhorst BW, Tanner N, Gawrys J, Meleshko D, Xu D, Steel PAD, Shemesh AJ, Xiang J, Thierry-Mieg J, Thierry-Mieg D, Schwartz RE, Iftner A, Bezdan D, Sipley J, Cong L, Craney A, Velu P, Melnick AM, Hajirasouliha I, Horner SM, Iftner T, Salvatore M, Loda M, Westblade LF, Cushing M, Levy S, Wu S, Tatonetti N, Imielinski M, Rennert H, Mason CE. Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions. bioRxiv 2020:2020.04.20.048066. [PMID: 32511352 PMCID: PMC7255793 DOI: 10.1101/2020.04.20.048066] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.
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Affiliation(s)
- Daniel J. Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | | | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, NY, USA
| | - David Danko
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- Tri-Institutional Computational Biol. & Medicine Program, Weill Cornell Medicine, NY, USA
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
| | - Joel Rosiene
- New York Genome Center, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Alon Shaiber
- New York Genome Center, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, NY, USA
| | - Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, NY, USA
| | - Matthew MacKay
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nikolay A. Ivanov
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
- Clinical & Translational Science Center, Weill Cornell Medicine, NY, USA
| | - Maria Sierra
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | - Diana Pohle
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Germany
| | - Michael Zietz
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, NY, USA
| | - Undina Gisladottir
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, NY, USA
| | - Vijendra Ramlall
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, NY, USA
- Department of Cellular, Molecular Physiology & Biophysics, Columbia University, NY, USA
| | - Craig D. Westover
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | - Benjamin Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
| | | | - Phyllis Ruggiero
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | | | | | - Justyna Gawrys
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Dmitry Meleshko
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- Tri-Institutional Computational Biol. & Medicine Program, Weill Cornell Medicine, NY, USA
| | - Dong Xu
- Genomics Resources Core Facility, Weill Cornell Medicine, NY, USA
| | | | - Amos J. Shemesh
- Department of Emergency Medicine, Weill Cornell Medicine, NY, USA
| | - Jenny Xiang
- Genomics Resources Core Facility, Weill Cornell Medicine, NY, USA
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, NY, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, MD, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, MD, USA
| | | | - Angelika Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Germany
| | - Daniela Bezdan
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Germany
| | - John Sipley
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Lin Cong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Arryn Craney
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Priya Velu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | | | - Iman Hajirasouliha
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, NY, USA
| | - Stacy M. Horner
- Department of Molecular Genetics and Microbiology, Duke University Medical Center, NC, USA
- Department of Medicine, Duke University Medical Center, NC, USA
| | - Thomas Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Germany
| | - Mirella Salvatore
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, NY, USA
| | - Massimo Loda
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Lars F. Westblade
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
- Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, NY, USA
| | - Melissa Cushing
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Shawn Levy
- HudsonAlpha Discovery Institute, Huntsville, AL, USA
| | - Shixiu Wu
- Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, China
- Department of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, China
| | - Nicholas Tatonetti
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, NY, USA
| | - Marcin Imielinski
- New York Genome Center, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, NY, USA
| | - Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, NY, USA
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, NY, USA
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, NY, USA
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5
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Sipley J, Stassi D, Dunn J, Goldman E. Analysis of bacteriophage T7 gene 10A and frameshifted 10B proteins. Gene Expr 2018; 1:127-36. [PMID: 1820210 PMCID: PMC5952207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Bacteriophage T7 capsid protein 10B has previously been proposed to arise by a translational frameshift near the 3' end of the capsid gene 10A coding sequence, adding an additional 53 amino acid residues to the carboxyl-terminal end of the protein. Here we show by peptide mapping experiments as well as by direct partial sequence analysis of an overlapping "junction" peptide, that 10B is in fact related to 10A by a -1 switch in reading frame in a narrow region near the carboxy terminus of 10A. Peptide mapping experiments demonstrate that 10A and 10B have the same amino terminus as well as virtually identical methionine-labeled peptide maps. However, the predicted unique carboxyl-terminal peptide from 10B was also identified. An overlapping peptide was isolated from 10B which spans the junction region in which the proposed translational frameshift is thought to occur. Partial sequencing of this junction peptide confirms a -1 frameshift within the last few codons of 10A.
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Affiliation(s)
- J Sipley
- Department of Microbiology and Molecular Genetics, University of Medicine and Dentistry of New Jersey, Newark 07103
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6
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Rennert H, Ramrattan G, Chen Z, McIntire P, Michaeel A, Khazanova A, Jenkins SG, Sipley J. Evaluation of a human adenovirus viral load assay using the Altona RealStar® PCR test. Diagn Microbiol Infect Dis 2017; 90:257-263. [PMID: 29433999 DOI: 10.1016/j.diagmicrobio.2017.11.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2017] [Revised: 10/29/2017] [Accepted: 11/21/2017] [Indexed: 10/18/2022]
Abstract
This study evaluated the performance of the Altona Diagnostics RealStar® Adenovirus Research Use Only (RUO) real-time PCR reagents for HAdV quantitation in plasma samples from immunodeficient patients. The assay was linear from 2.30-9.17 log10 copies/mL (coefficient of determination; R2=0.998) with limits of detection and quantification of 2.19 log10 and 2.30 log10 copies/mL (>95% positivity rate), respectively. Assay precision was highly reproducible with coefficients of variance ranging from 0% to 4.7%. A comparison of 66 matched samples showed good agreement (R2=0.845) between the Altona and the reference laboratory assay, with an average negative bias (-0.24 log10 copies/mL). Genotyping analysis demonstrated that HAdV species B and C accounted for 77% of the positive samples. A significant (≥0.9 log10) difference in quantitation between both tests was found for three HAdV types (HAdV types A12, B14 and F41). In conclusion, the Altona RealStar® test is a reliable and sensitive assay for HAdV DNA quantitation.
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Affiliation(s)
- Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY.
| | - Girish Ramrattan
- Department of Pathology and Laboratory Medicine, New York-Presbyterian Hospital, New York, NY
| | - Zhengming Chen
- Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, New York, NY
| | - Patrick McIntire
- Department of Pathology and Laboratory Medicine, New York-Presbyterian Hospital, New York, NY
| | - Alber Michaeel
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
| | - Anna Khazanova
- Department of Pathology and Laboratory Medicine, New York-Presbyterian Hospital, New York, NY
| | - Stephen G Jenkins
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY
| | - John Sipley
- Department of Pathology and Laboratory Medicine, New York-Presbyterian Hospital, New York, NY
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7
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McIntire P, Sipley J, Khazanova A, Michaeel A, Rennert H. Characterization of Human Adenovirus Serotypes Infection in Clinical Specimens from Immunodeficient Patients at NYPH. Am J Clin Pathol 2016. [DOI: 10.1093/ajcp/aqw156.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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8
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Rennert H, Fernandes H, Gilani Z, Sipley J. Development of a BK virus real-time quantitative assay using the bioMérieux analyte-specific reagents in plasma specimens. Am J Clin Pathol 2015; 144:909-15. [PMID: 26572998 DOI: 10.1309/ajcpxkuglg3q3mpx] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES Viral load testing for BK virus (BKV) has become the standard of care for diagnosing BKV infection and monitoring therapy in kidney transplant patients. However, there are currently no US Food and Drug Administration-approved assays and no standardization among available tests. METHODS This study evaluated the performance of the analyte-specific reagent (ASR) BKV primers r-gene and probe r-gene reagents (bioMérieux, Marcy l'Étoile, France) soon to become available on the US market for accuracy, linearity, precision, analytical sensitivity, specificity, and correlation with the Qiagen (Germantown, MD) BKV ASR test using commercial material and patient plasma samples. RESULTS The assay was linear from 204 to 3.92 million (2.31-6.6 log10) DNA copies/mL (coefficient of determination: R(2) =0.999). A dilution series demonstrated limits of detection and quantitation of 2.14 log10 and 2.30 log10 copies/mL (95% hit rate detection), respectively. Interrun precision was highly reproducible, with coefficients of variance ranging from 2.2% to 6.0%. A comparison of 34 matched samples showed a good agreement (R(2) = 0.87) between the bioMérieux BKV laboratory test and the Qiagen BKV ASR assay results, with an average negative bias (-0.28 log10 copies/mL). CONCLUSIONS The laboratory-developed test with bioMérieux BKV reagents is a reliable and sensitive assay for BKV DNA quantitation compared with the Qiagen ASR test.
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9
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Rennert H, Jenkins SG, Azurin C, Sipley J. Evaluation of a BK virus viral load assay using the QIAGEN Artus BK Virus RG PCR test. J Clin Virol 2012; 54:260-4. [PMID: 22494899 DOI: 10.1016/j.jcv.2012.03.007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2011] [Revised: 03/07/2012] [Accepted: 03/13/2012] [Indexed: 10/28/2022]
Abstract
BACKGROUND Viral load testing for BK Virus (BKV) has become the standard of care for the diagnosis of infection and monitoring of therapy of kidney transplant patients infected with BKV. However, there are currently no FDA-approved BKV quantification assays and no standardization among available tests. OBJECTIVE AND STUDY DESIGN This study evaluated the performance of the Artus BK Virus RG PCR (RUO) assay (QIAGEN) for accuracy, linearity, precision, analytical sensitivity, specificity, and correlation with a referral laboratory test in patient samples. RESULTS Linear regression analysis of the quantitative results demonstrated a linear range of quantification from 192 to 194 million (2.28 to 8.29 log(10)) DNA copies/mL and a coefficient of determination (R(2)) of 0.994. A dilution series demonstrated a limit of detection and a limit of quantification of 2.00 log(10), and 2.30 log(10) copies/mL (>95% positivity rate), respectively. The precision of the assay was highly reproducible among runs with coefficients of variance (CV) ranging from 0.2% to 7.0%. A comparison of 34 matched samples showed a good agreement (R(2)=0.983) between the Artus BK test and the referral laboratory results, with an average positive bias (0.39 log(10) copies/mL). Genotyping analysis using large-T antigen sequences demonstrated that 90% of the positive samples were BKV type I, and that there was no significant difference in quantification between the referral laboratory and Artus BK Virus tests. CONCLUSIONS The Artus BK Virus RG PCR test is a reliable and sensitive assay for BKV DNA quantification as compared to the referral laboratory test.
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Affiliation(s)
- Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY 10065, USA.
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10
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Bossler A, Gunsolly C, Pyne MT, Rendo A, Rachel J, Mills R, Miller M, Sipley J, Hillyard D, Jenkins S, Essmyer C, Young S, Lewinski M, Rennert H. Performance of the COBAS® AmpliPrep/COBAS TaqMan® automated system for hepatitis C virus (HCV) quantification in a multi-center comparison. J Clin Virol 2010; 50:100-3. [PMID: 21145783 DOI: 10.1016/j.jcv.2010.10.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2010] [Accepted: 09/05/2010] [Indexed: 12/09/2022]
Abstract
BACKGROUND Quantitative HCV RNA testing is considered standard of care for monitoring during treatment of patients infected with HCV. The COBAS(®) AmpliPrep/COBAS(®) TaqMan(®) HCV Test fully automates specimen processing and reaction assembly for HCV viral load testing using reverse transcription and real-time PCR amplification. OBJECTIVES The performance of the COBAS(®) AmpliPrep/COBAS(®) TaqMan(®) HCV Test was evaluated in a multi-center study. STUDY DESIGN Typical plasma based specimens were tested for accuracy, analytic range of measurement, reproducibility and genotype specific quantitation. RESULTS Linear regression analysis of the quantitative results demonstrated a linear range of detection from 50 to 5 million (1.7-6.7 log(10))IU/mL and a coefficient of determination (R(2)) of 0.9948. The precision of the assay was highly reproducible within and between runs and among laboratories with coefficients of variance (CV) ranging from 6.7% to 40.0% across the seven laboratories. A representative sample for each of the six major HCV genotypes demonstrated reproducible quantitation between the seven laboratories. CONCLUSIONS The COBAS(®) AmpliPrep/COBAS(®) TaqMan(®) HCV Test is a reliable and sensitive assay for HCV RNA quantitation.
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Affiliation(s)
- Aaron Bossler
- University of Iowa, Roy J and Lucille A. Carver College of Medicine, Department of Pathology, 200 Hawkins Drive, Iowa City, IA 52242, USA.
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11
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Choi YK, Yoon BI, Kook YH, Won YS, Kim JH, Lee CH, Hyun BH, Oh GT, Sipley J, Kim DY. Overexpression of urokinase-type plasminogen activator in human gastric cancer cell line (AGS) induces tumorigenicity in severe combined immunodeficient mice. Jpn J Cancer Res 2002; 93:151-6. [PMID: 11856478 PMCID: PMC5926960 DOI: 10.1111/j.1349-7006.2002.tb01253.x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023] Open
Abstract
The significance of urokinase-type plasminogen activator (uPA) expression in gastric cancer development was tested by using a human uPA cDNA transfection approach and an in vivo severe combined immunodeficient (SCID) mouse model. The AGS gastric cancer cell line, which has urokinase-type plasminogen-activator receptor (uPAR) but lacks uPA, was transfected with a plasmid containing human uPA cDNA and injected into the backs of SCID mice. Compared with the parent AGS cells, uPA protein secretion in AGS-2-, AGS-4-, and AGS-8-transfected cells increased by 26.1-, 34.6-, and 4.8-fold, respectively (P < 0.05). mRNA expression levels of uPA in the AGS-4 clone were much stronger than those in AGS-2 and AGS-8 clones. After the cancer cells (2 x 10(6)) were injected s.c. into the SCID mice, a palpable mass was observed at the injection site at around 140 days post-injection, followed by accelerated growth of the xenograft up to 180 days post-injection only in the high uPA-producing clone (AGS-4). These results suggest that continuous and high production of uPA by tumor cells is one of the important factors reflecting the malignancy of gastric cancer cells.
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Affiliation(s)
- Yang-Kyu Choi
- Korea Research Institute of Bioscience and Biotechnology, Taejon, 305-333, Korea
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12
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Hahn-Dantona E, Ramos-DeSimone N, Sipley J, Nagase H, French DL, Quigley JP. Activation of proMMP-9 by a plasmin/MMP-3 cascade in a tumor cell model. Regulation by tissue inhibitors of metalloproteinases. Ann N Y Acad Sci 1999; 878:372-87. [PMID: 10415742 DOI: 10.1111/j.1749-6632.1999.tb07696.x] [Citation(s) in RCA: 78] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
To examine MMP-9 activation in a cellular setting we employed cultures of human tumor cells that were induced to produce MMP-9 over a 200-fold concentration range (0.03 to 8.1 nM). The secreted levels of TIMPs in all the induced cultures remain relatively constant at 1-4 nM. Quantitation of the zymogen/active enzyme status of MMP-9 in the cultures indicates that even in the presence of potential activators, the molar ratio of endogenous MMP-9 to TIMP dictates whether proMMP-9 activation can progress. When the MMP-9/TIMP ratio exceeds 1.0, MMP-9 activation progresses, but only via an interacting protease cascade involving plasmin and stromelysin 1 (MMP-3). Plasmin, generated by the endogenous plasminogen activator (uPA), is not an efficient activator of proMMP-9. Plasmin, however, is very efficient at generating active MMP-3 from exogenously added proMMP-3. The activated MMP-3, when its concentration exceeds that to TIMP, becomes a potent activator of proMMP-9. Addition to the cultures of already-activated MMP-3 relinquishes the requirement for plasminogen and proMMP-3 additions and results in direct activation of the endogenous proMMP-9. The activated MMP-9 enhances the invasive phenotype of the cultured cells as their ability to transverse basement membrane is significantly increased following zymogen activation. That this enhanced tissue remodeling capability is due to the activation of MMP-9 is demonstrated through the use of a specific anti-MMP-9-blocking monoclonal antibody.
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Affiliation(s)
- E Hahn-Dantona
- Department of Pathology, State University of New York at Stony Brook 11794-8691, USA
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13
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Ramos-DeSimone N, Hahn-Dantona E, Sipley J, Nagase H, French DL, Quigley JP. Activation of matrix metalloproteinase-9 (MMP-9) via a converging plasmin/stromelysin-1 cascade enhances tumor cell invasion. J Biol Chem 1999. [PMID: 10224058 DOI: 10.110.1074/jbc.274.19.13066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Matrix metalloproteinase-9 (MMP-9) may play a critical catalytic role in tissue remodeling in vivo, but it is secreted by cells as a stable, inactive zymogen, pro-MMP-9, and requires activation for catalytic function. A number of proteolytic enzymes activate pro-MMP-9 in vitro, but the natural activator(s) of MMP-9 is unknown. To examine MMP-9 activation in a cellular setting we employed cultures of human tumor cells (MDA-MB-231 breast carcinoma cells) that were induced to produce MMP-9 over a 200-fold concentration range (0.03-8.1 nM). The levels of tissue inhibitors of metalloproteinase (TIMPs) in the induced cultures remain relatively constant at 1-4 nM. Quantitation of the zymogen/active enzyme status of MMP-9 in the MDA-MB-231 cultures indicates that even in the presence of potential activators, the molar ratio of endogenous MMP-9 to TIMP dictates whether pro-MMP-9 activation can progress. When the MMP-9/TIMP ratio exceeds 1.0, MMP-9 activation progresses, but through an interacting protease cascade involving plasmin and stromelysin 1 (MMP-3). Plasmin, generated by the endogenous urokinase-type plasminogen activator, is not an efficient activator of pro-MMP-9, neither the secreted pro-MMP-9 nor the very low levels of pro-MMP-9 associated with intact cells. Although plasmin can proteolytically process pro-MMP-9, this limited action does not yield an enzymatically active MMP-9, nor does it cause the MMP-9 to be more susceptible to activation. Plasmin, however, is very efficient at generating active MMP-3 (stromelysin-1) from exogenously added pro-MMP-3. The activated MMP-3 becomes a potent activator of the 92-kDa pro-MMP-9, yielding an 82-kDa species that is enzymatically active in solution and represents up to 50-75% conversion of the zymogen. The activated MMP-9 enhances the invasive phenotype of the cultured cells as their ability to both degrade extracellular matrix and transverse basement membrane is significantly increased following zymogen activation. That this enhanced tissue remodelling capability is due to the activation of MMP-9 is demonstrated through the use of a specific anti-MMP-9 blocking monoclonal antibody.
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Affiliation(s)
- N Ramos-DeSimone
- Department of Pathology, State University of New York at Stony Brook, Stony Brook, New York 11794-8691, USA
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14
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Ramos-DeSimone N, Hahn-Dantona E, Sipley J, Nagase H, French DL, Quigley JP. Activation of matrix metalloproteinase-9 (MMP-9) via a converging plasmin/stromelysin-1 cascade enhances tumor cell invasion. J Biol Chem 1999; 274:13066-76. [PMID: 10224058 DOI: 10.1074/jbc.274.19.13066] [Citation(s) in RCA: 450] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Matrix metalloproteinase-9 (MMP-9) may play a critical catalytic role in tissue remodeling in vivo, but it is secreted by cells as a stable, inactive zymogen, pro-MMP-9, and requires activation for catalytic function. A number of proteolytic enzymes activate pro-MMP-9 in vitro, but the natural activator(s) of MMP-9 is unknown. To examine MMP-9 activation in a cellular setting we employed cultures of human tumor cells (MDA-MB-231 breast carcinoma cells) that were induced to produce MMP-9 over a 200-fold concentration range (0.03-8.1 nM). The levels of tissue inhibitors of metalloproteinase (TIMPs) in the induced cultures remain relatively constant at 1-4 nM. Quantitation of the zymogen/active enzyme status of MMP-9 in the MDA-MB-231 cultures indicates that even in the presence of potential activators, the molar ratio of endogenous MMP-9 to TIMP dictates whether pro-MMP-9 activation can progress. When the MMP-9/TIMP ratio exceeds 1.0, MMP-9 activation progresses, but through an interacting protease cascade involving plasmin and stromelysin 1 (MMP-3). Plasmin, generated by the endogenous urokinase-type plasminogen activator, is not an efficient activator of pro-MMP-9, neither the secreted pro-MMP-9 nor the very low levels of pro-MMP-9 associated with intact cells. Although plasmin can proteolytically process pro-MMP-9, this limited action does not yield an enzymatically active MMP-9, nor does it cause the MMP-9 to be more susceptible to activation. Plasmin, however, is very efficient at generating active MMP-3 (stromelysin-1) from exogenously added pro-MMP-3. The activated MMP-3 becomes a potent activator of the 92-kDa pro-MMP-9, yielding an 82-kDa species that is enzymatically active in solution and represents up to 50-75% conversion of the zymogen. The activated MMP-9 enhances the invasive phenotype of the cultured cells as their ability to both degrade extracellular matrix and transverse basement membrane is significantly increased following zymogen activation. That this enhanced tissue remodelling capability is due to the activation of MMP-9 is demonstrated through the use of a specific anti-MMP-9 blocking monoclonal antibody.
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Affiliation(s)
- N Ramos-DeSimone
- Department of Pathology, State University of New York at Stony Brook, Stony Brook, New York 11794-8691, USA
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15
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Abstract
We have tested the effect of increased ribosomal fidelity on a modified version of the programmed release factor 2 (RF2) translational frameshift. In the constructs tested, the original UGA codon at the site of the shift was replaced by either of two sense codons, UGG (tryptophan), which allows a frameshift of approximately 13%, or CUG (leucine), which allows a frameshift of only approximately 2%. We confirmed the results of Curran and Yarus [Curran, J. F. & Yarus, M. (1989) J. Mol. Biol. 209, 65-77] in a wild-type ribosomal host, including a reduction of the UGG shift following induction of tRNA(Trp) from a plasmid copy of the tRNA gene. But to our surprise, in a hyperaccurate streptomycin pseudo-dependent host, the UGG frameshift increased to more than 50%. When we added a tRNA(Trp) plasmid to these cells, induction of the tRNA(Trp) gene reduced the shift back to approximately 7%. Messenger RNA levels did not vary greatly under these different induced conditions. Other increased accuracy alleles also showed increased frameshifting with UGG at the frameshift site. All increased accuracy alleles led to slower translation rates, and there appeared to be a proportionality between the extent of reduction of synthesis for the in-frame reporter and the extent of UGG frameshift for the out-of-frame reporter. There were little effects of increased accuracy on the lower level CUG frameshift. However, over-production of the cognate tRNA(1Leu) dramatically reduced even this lower level of shift, despite the fact that tRNA(1Leu) is already the most abundant isoacceptor in Escherichia coli. These results can be rationalized by following the hypothesis of Curran and Yarus as follows: with wild-type ribosomes, limited availability of tRNA(Trp) (about 1% of total tRNA) facilitates a pause at the UGG codon (due to the vacant A site), allowing increased opportunity for ribosome realignment. Excess tRNA(Trp) reduces the time the A site is vacant and thus reduces the frameshift. The slower hyperaccurate ribosomes increase the pause time and thus increase the opportunity for shifting, a process again reversed by increasing the in-frame cognate tRNA(Trp). These data provide strong support for a model in which the extent of ribosome pause time at a programmed frameshift site is a major determinant in the efficiency of the frameshift and in which tRNA availability can be a major influence on this process.
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MESH Headings
- Base Sequence
- Codon/genetics
- Escherichia coli/genetics
- Escherichia coli/metabolism
- Frameshift Mutation
- Genes, Bacterial
- Molecular Sequence Data
- Mutagenesis, Site-Directed
- Oligodeoxyribonucleotides
- Plasmids
- Protein Biosynthesis
- RNA, Messenger/genetics
- RNA, Messenger/metabolism
- RNA, Transfer/genetics
- RNA, Transfer/metabolism
- RNA, Transfer, Leu/genetics
- RNA, Transfer, Leu/metabolism
- Ribosomes/metabolism
- beta-Galactosidase/genetics
- beta-Galactosidase/metabolism
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Affiliation(s)
- J Sipley
- Department of Microbiology and Molecular Genetics, New Jersey Medical School, Newark
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16
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Sipley J, Dunn J, Goldman E. Bacteriophage T7 morphogenesis and gene 10 frameshifting in Escherichia coli showing different degrees of ribosomal fidelity. Mol Gen Genet 1991; 230:376-84. [PMID: 1766436 PMCID: PMC7088377 DOI: 10.1007/bf00280294] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Bacteriophage T7 infection has been studied in Escherichia coli strains showing both increased and decreased ribosome fidelity and in the presence of streptomycin, which stimulates translational misreading, in an effort to determine effects on the apparent programmed translational frameshift that occurs during synthesis of the gene 10 capsid protein. Quantitation of the protein bands from SDS-PAGE failed to detect any significant effects on the amounts of the shifted 10B protein relative to the in-frame 10A protein under all fidelity conditions tested. However, any changes in fidelity conditions led to inhibition of phage morphogenesis in single-step growth experiments, which could not be accounted for by reduced amounts of phage protein synthesis, nor, at least in the case of decreased accuracy, by reduced amounts of phage DNA synthesis. Reduction in phage DNA synthesis did appear to account for a substantial proportion of the reduction in phage yield seen under conditions of increased accuracy. Similar effects of varying ribosomal fidelity on growth were also seen with phage T3, and to a lesser extent with phage T4. The absence of change in the high-frequency T7 gene 10 frameshift differs from earlier reports that ribosomal fidelity affects low-frequency frameshift errors.
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Affiliation(s)
- J Sipley
- Department of Microbiology and Molecular Genetics, New Jersey Medical School, University of Medicine and Dentistry of New Jersey, Newark 07103
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