1
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Alser M, Lawlor B, Abdill RJ, Waymost S, Ayyala R, Rajkumar N, LaPierre N, Brito J, Ribeiro-Dos-Santos AM, Almadhoun N, Sarwal V, Firtina C, Osinski T, Eskin E, Hu Q, Strong D, Kim BDBD, Abedalthagafi MS, Mutlu O, Mangul S. Packaging and containerization of computational methods. Nat Protoc 2024:10.1038/s41596-024-00986-0. [PMID: 38565959 DOI: 10.1038/s41596-024-00986-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 02/12/2024] [Indexed: 04/04/2024]
Abstract
Methods for analyzing the full complement of a biomolecule type, e.g., proteomics or metabolomics, generate large amounts of complex data. The software tools used to analyze omics data have reshaped the landscape of modern biology and become an essential component of biomedical research. These tools are themselves quite complex and often require the installation of other supporting software, libraries and/or databases. A researcher may also be using multiple different tools that require different versions of the same supporting materials. The increasing dependence of biomedical scientists on these powerful tools creates a need for easier installation and greater usability. Packaging and containerization are different approaches to satisfy this need by delivering omics tools already wrapped in additional software that makes the tools easier to install and use. In this systematic review, we describe and compare the features of prominent packaging and containerization platforms. We outline the challenges, advantages and limitations of each approach and some of the most widely used platforms from the perspectives of users, software developers and system administrators. We also propose principles to make the distribution of omics software more sustainable and robust to increase the reproducibility of biomedical and life science research.
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Affiliation(s)
- Mohammed Alser
- Department of Information Technology and Electrical Engineering, ETH Zürich, Zurich, Switzerland
| | - Brendan Lawlor
- Department of Computer Science, Munster Technological University, Cork, Ireland
- Department of Biological Sciences, Munster Technological University, Cork, Ireland
| | - Richard J Abdill
- Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Sharon Waymost
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ram Ayyala
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | - Neha Rajkumar
- Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nathan LaPierre
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Jaqueline Brito
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
| | | | - Nour Almadhoun
- Department of Information Technology and Electrical Engineering, ETH Zürich, Zurich, Switzerland
| | - Varuni Sarwal
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Can Firtina
- Department of Information Technology and Electrical Engineering, ETH Zürich, Zurich, Switzerland
| | - Tomasz Osinski
- Center for Advanced Research Computing, University of Southern California, Los Angeles, CA, USA
| | - Eleazar Eskin
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, CA, USA
| | - Qiyang Hu
- Office of Advanced Research Computing, University of California, Los Angeles, CA, USA
| | - Derek Strong
- Center for Advanced Research Computing, University of Southern California, Los Angeles, CA, USA
| | - Byoung-Do B D Kim
- Center for Advanced Research Computing, University of Southern California, Los Angeles, CA, USA
| | - Malak S Abedalthagafi
- Department of Pathology & Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
- King Salman Center for Disability Research, Riyadh, Saudi Arabia
| | - Onur Mutlu
- Department of Information Technology and Electrical Engineering, ETH Zürich, Zurich, Switzerland
| | - Serghei Mangul
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA, USA.
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA.
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2
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Yu D, Ayyala R, Sadek SH, Chittampalli L, Farooq H, Jung J, Nahid AA, Boldirev G, Jung M, Park S, Nguyen A, Zelikovsky A, Mancuso N, Joo JWJ, Thompson RF, Alachkar H, Mangul S. A rigorous benchmarking of alignment-based HLA typing algorithms for RNA-seq data. bioRxiv 2024:2023.05.22.541750. [PMID: 38293199 PMCID: PMC10827116 DOI: 10.1101/2023.05.22.541750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Accurate identification of human leukocyte antigen (HLA) alleles is essential for various clinical and research applications, such as transplant matching and drug sensitivities. Recent advances in RNA-seq technology have made it possible to impute HLA types from sequencing data, spurring the development of a large number of computational HLA typing tools. However, the relative performance of these tools is unknown, limiting the ability for clinical and biomedical research to make informed choices regarding which tools to use. Here we report the study design of a comprehensive benchmarking of the performance of 12 HLA callers across 682 RNA-seq samples from 8 datasets with molecularly defined gold standard at 5 loci, HLA-A, -B, -C, -DRB1, and -DQB1. For each HLA typing tool, we will comprehensively assess their accuracy, compare default with optimized parameters, and examine for discrepancies in accuracy at the allele and loci levels. We will also evaluate the computational expense of each HLA caller measured in terms of CPU time and RAM. We also plan to evaluate the influence of read length over the HLA region on accuracy for each tool. Most notably, we will examine the performance of HLA callers across European and African groups, to determine discrepancies in accuracy associated with ancestry. We hypothesize that RNA-Seq HLA callers are capable of returning high-quality results, but the tools that offer a good balance between accuracy and computational expensiveness for all ancestry groups are yet to be developed. We believe that our study will provide clinicians and researchers with clear guidance to inform their selection of an appropriate HLA caller.
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Affiliation(s)
- Dottie Yu
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA
| | - Ram Ayyala
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, USA
| | - Sarah Hany Sadek
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Department of Biology, and Department of Computer Science, California State University, Fullerton, Fullerton, CA 92831
| | - Likhitha Chittampalli
- Department of Computer Science, Viterbi School of Engineering University of Southern California, Los Angeles, CA, USA
| | - Hafsa Farooq
- Department of Computer Science, Georgia State University Atlanta, GA 30303 USA
| | - Junghyun Jung
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, Los Angeles, CA, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Abdullah Al Nahid
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh
| | - Grigore Boldirev
- Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Mina Jung
- Department of Quantitative and Computational Biology, Dornsife College of Letters, Arts and Sciences, University of Southern California, 1975 Zonal Ave, Los Angeles, CA 90033, US
| | - Sungmin Park
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea
| | - Austin Nguyen
- Computational Biologist, Immune Monitoring & Cancer Omics Oregon Health & Science University, Biomedical Engineering, 3181 S.W. Sam Jackson Park Road Portland, OR 97239-3098
| | - Alex Zelikovsky
- Department of Computer Science, College of Arts and Sciences, Georgia State University, Atlanta, GA, 30303, USA
| | - Nicholas Mancuso
- Assistant Professor of Population and Public Health Sciences, Keck School of Medicina, University of Southern California, 1845 N. Soto Street, USA
| | - Jong Wha J Joo
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, 04620, South Korea
- Division of AI Software Convergence, Dongguk University-Seoul, Seoul, 04620, South Korea
| | - Reid F Thompson
- Assistant Professor of Radiation Medicine, School of Medicine, OHSU, Portland, OR 97239
- Assistant Professor of Biomedical Engineering, School of Medicine, OHSU, Portland, OR 97239
- Staff Physician, VA Portland Healthcare System, Portland OR 97239
| | - Houda Alachkar
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, CA, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles
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3
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Sharma NK, Ayyala R, Deshpande D, Patel YM, Munteanu V, Ciorba D, Fiscutean A, Vahed M, Sarkar A, Guo R, Moore A, Darci-Maher N, Nogoy NA, Abedalthagafi MS, Mangul S. Analytical code sharing practices in biomedical research. bioRxiv 2023:2023.07.31.551384. [PMID: 37609176 PMCID: PMC10441317 DOI: 10.1101/2023.07.31.551384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Data-driven computational analysis is becoming increasingly important in biomedical research, as the amount of data being generated continues to grow. However, the lack of practices of sharing research outputs, such as data, source code and methods, affects transparency and reproducibility of studies, which are critical to the advancement of science. Many published studies are not reproducible due to insufficient documentation, code, and data being shared. We conducted a comprehensive analysis of 453 manuscripts published between 2016-2021 and found that 50.1% of them fail to share the analytical code. Even among those that did disclose their code, a vast majority failed to offer additional research outputs, such as data. Furthermore, only one in ten papers organized their code in a structured and reproducible manner. We discovered a significant association between the presence of code availability statements and increased code availability (p=2.71×10-9). Additionally, a greater proportion of studies conducting secondary analyses were inclined to share their code compared to those conducting primary analyses (p=1.15*10-07). In light of our findings, we propose raising awareness of code sharing practices and taking immediate steps to enhance code availability to improve reproducibility in biomedical research. By increasing transparency and reproducibility, we can promote scientific rigor, encourage collaboration, and accelerate scientific discoveries. We must prioritize open science practices, including sharing code, data, and other research products, to ensure that biomedical research can be replicated and built upon by others in the scientific community.
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Affiliation(s)
- Nitesh Kumar Sharma
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
| | - Ram Ayyala
- Quantitative and Computational Biology Department, USC Dana and David Dornsife College of Letters, Arts, and Sciences, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089, USA
| | - Dhrithi Deshpande
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
| | - Yesha M Patel
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
| | - Viorel Munteanu
- Department of Computers, Informatics and Microelectronics, Technical University of Moldova, Chisinau, 2045, Moldova
| | - Dumitru Ciorba
- Department of Computers, Informatics and Microelectronics, Technical University of Moldova, Chisinau, 2045, Moldova
| | - Andrada Fiscutean
- Faculty of Journalism and Communication Studies, University of Bucharest, Soseaua Panduri, nr. 90, Sector 5, 050663, Bucharest, Romania
| | - Mohammad Vahed
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
| | - Aditya Sarkar
- School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, North Campus, Kamand, Mandi, Himachal Pradesh, 175005, India
| | - Ruiwei Guo
- Department of Pharmacology and Pharmaceutical Sciences, USC Alfred E. Mann School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089-9121, USA
| | - Andrew Moore
- Daniel J. Epstein Department of Industrial and Systems Engineering, Viterbi School of Engineering, University of Southern California
| | - Nicholas Darci-Maher
- Computational and Systems Biology, University of California, Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Nicole A Nogoy
- GigaScience Press, L26/F, Kings Wing Plaza 2, 1 On Kwan Street, Shek Mun, N.T., Hong Kong
| | - Malak S. Abedalthagafi
- Department of Pathology & Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
- King Salman Center for Disability Research, Riyadh, Saudi Arabia
| | - Serghei Mangul
- Titus Family Department of Clinical Pharmacy, USC Alfred E. Mann School of Pharmacy and Pharmaceutical Sciences, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California Dornsife College of Letters, Arts, and Sciences, Los Angeles, CA 90089, USA
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4
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Sarwal V, Niehus S, Ayyala R, Kim M, Sarkar A, Chang S, Lu A, Rajkumar N, Darfci-Maher N, Littman R, Chhugani K, Soylev A, Comarova Z, Wesel E, Castellanos J, Chikka R, Distler MG, Eskin E, Flint J, Mangul S. A comprehensive benchmarking of WGS-based deletion structural variant callers. Brief Bioinform 2022; 23:6618239. [PMID: 35753701 DOI: 10.1093/bib/bbac221] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [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: 11/08/2021] [Revised: 04/30/2022] [Accepted: 05/11/2022] [Indexed: 01/10/2023] Open
Abstract
Advances in whole-genome sequencing (WGS) promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from WGS data presents a substantial number of challenges and a plethora of SV detection methods have been developed. Currently, evidence that investigators can use to select appropriate SV detection tools is lacking. In this article, we have evaluated the performance of SV detection tools on mouse and human WGS data using a comprehensive polymerase chain reaction-confirmed gold standard set of SVs and the genome-in-a-bottle variant set, respectively. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of the SV detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance as the SV detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low- and ultralow-pass sequencing data as well as for different deletion length categories.
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Affiliation(s)
- Varuni Sarwal
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA.,Indian Institute of Technology Delhi, Hauz Khas, New Delhi, Delhi 110016, India
| | - Sebastian Niehus
- Berlin Institute of Health (BIH), Anna-Louisa-Karsch-Str. 2, 10178 Berlin, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Charitéplatz 1, 10117 Berlin, Germany
| | - Ram Ayyala
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Minyoung Kim
- Department of Quantitative and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089
| | - Aditya Sarkar
- School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Kamand, Mandi, Himachal Pradesh 175001, India
| | - Sei Chang
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Angela Lu
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Neha Rajkumar
- Department of Bioengineering, Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, 90095
| | - Nicholas Darfci-Maher
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Russell Littman
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Karishma Chhugani
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California 1985 Zonal Avenue Los Angeles, CA 90089-9121
| | - Arda Soylev
- Department of Computer Engineering, Konya Food and Agriculture University, Konya, Turkey
| | - Zoia Comarova
- Department Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, United States
| | - Emily Wesel
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Jacqueline Castellanos
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Rahul Chikka
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Margaret G Distler
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Eleazar Eskin
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA.,Department of Human Genetics, David Geffen School of Medicine at UCLA, 695 Charles E. Young Drive South, Box 708822, Los Angeles, CA, 90095, USA.,Department of Computational Medicine, David Geffen School of Medicine at UCLA, 73-235 CHS, Los Angeles, CA, 90095, USA
| | - Jonathan Flint
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California 1985 Zonal Avenue Los Angeles, CA 90089-9121
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5
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Knyazev S, Chhugani K, Sarwal V, Ayyala R, Singh H, Karthikeyan S, Deshpande D, Baykal PI, Comarova Z, Lu A, Porozov Y, Vasylyeva TI, Wertheim JO, Tierney BT, Chiu CY, Sun R, Wu A, Abedalthagafi MS, Pak VM, Nagaraj SH, Smith AL, Skums P, Pasaniuc B, Komissarov A, Mason CE, Bortz E, Lemey P, Kondrashov F, Beerenwinkel N, Lam TTY, Wu NC, Zelikovsky A, Knight R, Crandall KA, Mangul S. Unlocking capacities of genomics for the COVID-19 response and future pandemics. Nat Methods 2022; 19:374-380. [PMID: 35396471 PMCID: PMC9467803 DOI: 10.1038/s41592-022-01444-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [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: 02/07/2023]
Abstract
During the COVID-19 pandemic, genomics and bioinformatics have emerged as essential public health tools. The genomic data acquired using these methods have supported the global health response, facilitated development of testing methods, and allowed timely tracking of novel SARS-CoV-2 variants. Yet the virtually unlimited potential for rapid generation and analysis of genomic data is also coupled with unique technical, scientific, and organizational challenges. Here, we discuss the application of genomic and computational methods for the efficient data driven COVID-19 response, advantages of democratization of viral sequencing around the world, and challenges associated with viral genome data collection and processing.
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Affiliation(s)
- Sergey Knyazev
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Karishma Chhugani
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Varuni Sarwal
- Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Ram Ayyala
- Department of Translational Biomedical Informatics, University of Southern California, Los Angeles, CA, USA
| | - Harman Singh
- Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, India
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Dhrithi Deshpande
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Pelin Icer Baykal
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Zoia Comarova
- Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, USA
| | - Angela Lu
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Yuri Porozov
- World-Class Research Center "Digital biodesign and personalized healthcare", I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia
| | - Tetyana I Vasylyeva
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Joel O Wertheim
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Braden T Tierney
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, University of California, San Francisco, San Francisco, CA, USA
| | - Ren Sun
- Department of Molecular and Medical Pharmacology, University of California, Los Angeles, Los Angeles, CA, USA
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, P.R. China
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Suzhou Institute of Systems Medicine, Suzhou, China
| | - Malak S Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
- King Salman Center for Disability Research, Riyadh, Saudi Arabia
| | - Victoria M Pak
- Emory University, School of Nursing, Atlanta, GA, CA, USA
- Emory University, Rollins School of Public Health, Department of Epidemiology, Atlanta, GA, CA, USA
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Queensland, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Adam L Smith
- Astani Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA, USA
| | - Pavel Skums
- Department of Computer Science, College of Art and Science, Georgia State University, Atlanta, GA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Andrey Komissarov
- Smorodintsev Research Institute of Influenza, Saint Petersburg, Russia
| | - 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
- The 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
| | - Eric Bortz
- Department of Biological Sciences, University of Alaska Anchorage, Anchorage, AK, CA, USA
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven-University of Leuven, Leuven, Belgium
| | - Fyodor Kondrashov
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong, Hong Kong SAR, P.R. China
- Laboratory of Data Discovery for Health Limited, Hong Kong SAR, P.R. China
- Centre for Immunology & Infection Limited, Hong Kong SAR, P.R. China
| | - Nicholas C Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Alex Zelikovsky
- Department of Computer Science, College of Art and Science, Georgia State University, Atlanta, GA, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Keith A Crandall
- Computational Biology Institute and Department of Biostatistics & Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA.
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6
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Knyazev S, Chhugani K, Sarwal V, Ayyala R, Singh H, Karthikeyan S, Deshpande D, Comarova Z, Lu A, Porozov Y, Wu A, Abedalthagafi MS, Nagaraj SH, Smith AL, Skums P, Ladner J, Tsan-Yuk Lam T, Wu NC, Zelikovsky A, Knight R, Crandall KA, Mangul S. Unlocking capacities of viral genomics for the COVID-19 pandemic response. ARXIV 2021. [PMCID: PMC8109901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.
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Affiliation(s)
- Sergey Knyazev
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Room 618, Atlanta, GA 30303, USA,Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, 30333 GA, USA,Oak Ridge Institute for Science and Education, Oak Ridge, TN 37830, USA
| | - Karishma Chhugani
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089, USA
| | - Varuni Sarwal
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Ram Ayyala
- Department of Neuroscience, College of Life Sciences, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Harman Singh
- Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Dhrithi Deshpande
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089, USA
| | - Zoia Comarova
- Paradigm Environmental, 3911 Old Lee Highway, Fairfax, VA 22030
| | - Angela Lu
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089-9121, USA
| | - Yuri Porozov
- World-Class Research Center “Digital biodesign and personalized healthcare”, I.M. Sechenov First Moscow State Medical University, Moscow, Russia,Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia
| | - Aiping Wu
- Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China,Suzhou Institute of Systems Medicine, Suzhou, 215123, China
| | - Malak S. Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Shivashankar H. Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD 4059, Australia,Translational Research Institute, Brisbane, Australia
| | - Adam L. Smith
- Astani Department of Civil and Environmental Engineering, University of Southern California, 3620 South Vermont Avenue, Los Angeles, CA 90089
| | - Pavel Skums
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Floor 6, Atlanta, GA 30303, USA
| | - Jason Ladner
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong
| | - Nicholas C. Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA,Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Alex Zelikovsky
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Floor 6, Atlanta, GA 30303, USA,The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA,Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA,Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA,Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Keith A. Crandall
- Computational Biology Institute and Department of Biostatistics & Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC 20052
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
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Knyazev S, Chhugani K, Sarwal V, Ayyala R, Singh H, Karthikeyan S, Deshpande D, Comarova Z, Lu A, Porozov Y, Wu A, Abedalthagafi MS, Nagaraj SH, Smith AL, Skums P, Ladner J, Lam TTY, Wu NC, Zelikovsky A, Knight R, Crandall KA, Mangul S. Unlocking capacities of viral genomics for the COVID-19 pandemic response. ArXiv 2021:arXiv:2104.14005v3. [PMID: 33948451 PMCID: PMC8095210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 06/04/2021] [Indexed: 12/25/2022]
Abstract
More than any other infectious disease epidemic, the COVID-19 pandemic has been characterized by the generation of large volumes of viral genomic data at an incredible pace due to recent advances in high-throughput sequencing technologies, the rapid global spread of SARS-CoV-2, and its persistent threat to public health. However, distinguishing the most epidemiologically relevant information encoded in these vast amounts of data requires substantial effort across the research and public health communities. Studies of SARS-CoV-2 genomes have been critical in tracking the spread of variants and understanding its epidemic dynamics, and may prove crucial for controlling future epidemics and alleviating significant public health burdens. Together, genomic data and bioinformatics methods enable broad-scale investigations of the spread of SARS-CoV-2 at the local, national, and global scales and allow researchers the ability to efficiently track the emergence of novel variants, reconstruct epidemic dynamics, and provide important insights into drug and vaccine development and disease control. Here, we discuss the tremendous opportunities that genomics offers to unlock the effective use of SARS-CoV-2 genomic data for efficient public health surveillance and guiding timely responses to COVID-19.
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Affiliation(s)
- Sergey Knyazev
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Room 618, Atlanta, GA 30303, USA
| | - Karishma Chhugani
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089, USA
| | - Varuni Sarwal
- Department of Computer Science, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Ram Ayyala
- Department of Neuroscience, College of Life Sciences, University of California Los Angeles, 580 Portola Plaza, Los Angeles, CA 90095, USA
| | - Harman Singh
- Department of Electrical Engineering, Indian Institute of Technology, Hauz Khas, New Delhi, 110016, India
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Dhrithi Deshpande
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089, USA
| | - Zoia Comarova
- Paradigm Environmental, 3911 Old Lee Highway, Fairfax, VA 22030
| | - Angela Lu
- Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Room 713. Los Angeles, CA 90089-9121, USA
| | - Yuri Porozov
- World-Class Research Center "Digital biodesign and personalized healthcare", I.M. Sechenov First Moscow State Medical University, Moscow, Russia
- Department of Computational Biology, Sirius University of Science and Technology, Sochi, Russia
| | - Aiping Wu
- Center for Systems Medicine, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
- Suzhou Institute of Systems Medicine, Suzhou, 215123, China
| | - Malak S Abedalthagafi
- Genomics Research Department, Saudi Human Genome Project, King Fahad Medical City and King Abdulaziz City for Science and Technology, Riyadh, Saudi Arabia
| | - Shivashankar H Nagaraj
- Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, QLD 4059, Australia
- Translational Research Institute, Brisbane, Australia
| | - Adam L Smith
- Astani Department of Civil and Environmental Engineering, University of Southern California, 3620 South Vermont Avenue, Los Angeles, CA 90089
| | - Pavel Skums
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Floor 6, Atlanta, GA 30303, USA
| | - Jason Ladner
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011
| | - Tommy Tsan-Yuk Lam
- State Key Laboratory of Emerging Infectious Diseases, School of Public Health, The University of Hong Kong
| | - Nicholas C Wu
- Department of Biochemistry, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Alex Zelikovsky
- Department of Computer Science, College of Art and Science, Georgia State University, 1 Park Place, Floor 6, Atlanta, GA 30303, USA
- The Laboratory of Bioinformatics, I.M. Sechenov First Moscow State Medical University, Moscow, 119991, Russia
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Keith A Crandall
- Computational Biology Institute and Department of Biostatistics & Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC 20052
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1540 Alcazar Street, Los Angeles, CA 90033, USA
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Grabacka M, Waligorski P, Zapata A, Blake DA, Wyczechowska D, Wilk A, Rutkowska M, Vashistha H, Ayyala R, Ponnusamy T, John VT, Culicchia F, Wisniewska-Becker A, Reiss K. Fenofibrate subcellular distribution as a rationale for the intracranial delivery through biodegradable carrier. J Physiol Pharmacol 2015; 66:233-247. [PMID: 25903954 PMCID: PMC5865398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 06/29/2014] [Accepted: 01/27/2015] [Indexed: 06/04/2023]
Abstract
Fenofibrate, a well-known normolipidemic drug, has been shown to exert strong anticancer effects against tumors of neuroectodermal origin including glioblastoma. Although some pharmacokinetic studies were performed in the past, data are still needed about the detailed subcellular and tissue distribution of fenofibrate (FF) and its active metabolite, fenofibric acid (FA), especially in respect to the treatment of intracranial tumors. We used high performance liquid chromatography (HPLC) to elucidate the intracellular, tissue and body fluid distribution of FF and FA after oral administration of the drug to mice bearing intracranial glioblastoma. Following the treatment, FF was quickly cleaved to FA by blood esterases and FA was detected in the blood, urine, liver, kidney, spleen and lungs. We have also detected small amounts of FA in the brains of two out of six mice, but not in the brain tumor tissue. The lack of FF and FA in the intracranial tumors prompted us to develop a new method for intracranial delivery of FF. We have prepared and tested in vitro biodegradable poly-lactic-co-glycolic acid (PLGA) polymer wafers containing FF, which could ultimately be inserted into the brain cavity following resection of the brain tumor. HPLC-based analysis demonstrated a slow and constant diffusion of FF from the wafer, and the released FF abolished clonogenic growth of glioblastoma cells. On the intracellular level, FF and FA were both present in the cytosolic fraction. Surprisingly, we also detected FF, but not FA in the cell membrane fraction. Electron paramagnetic resonance spectroscopy applied to spin-labeled phospholipid model-membranes revealed broadening of lipid phase transitions and decrease of membrane polarity induced by fenofibrate. Our results indicate that the membrane-bound FF could contribute to its exceptional anticancer potential in comparison to other lipid-lowering drugs, and advocate for intracranial delivery of FF in the combined pharmacotherapy against glioblastoma.
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Affiliation(s)
- M Grabacka
- Department of Food Biotechnology, Faculty of Food Technology, University of Agriculture in Cracow, Cracow, Poland.
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Ayyala R. Cyclophotocoagulation for glaucoma after penetrating keratoplasty: Author's reply. Ophthalmology 1999. [DOI: 10.1016/s0161-6420(99)90180-x] [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: 10/27/2022] Open
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