1
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Monteiro LM, Gouveia PJ, Vasques-Nóvoa F, Rosa S, Bardi I, Gomes RN, Correia-Santos S, Ricotti L, Vannozzi L, Guarnera D, Costa L, Leite-Moreira AM, Mendes-Ferreira P, Leite-Moreira AF, Perbellini F, Terracciano CM, Pinto-do-Ó P, Ferreira L, Nascimento DS. Nanoscale piezoelectric patches preserve electrical integrity of infarcted hearts. Mater Today Bio 2025; 32:101742. [PMID: 40290879 PMCID: PMC12033997 DOI: 10.1016/j.mtbio.2025.101742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2025] [Revised: 03/27/2025] [Accepted: 04/06/2025] [Indexed: 04/30/2025] Open
Abstract
Ischemic heart disease is the leading cause of death worldwide. Several approaches have been explored to restore cardiac function, however few investigated new strategies to improve electrical functional recovery. Herein, we have investigated the impact of piezoelectric patches (Piezo patches), capable of generating electric charges upon mechanical deformation, on rat cardiac slices, healthy and ischemic hearts (ex vivo), on infarcted mice (in vivo) and on healthy and infarcted pigs (in vivo). Piezo patches did not preclude cardiac slice contractility, while compared with electrically inert control patches. In addition, Piezo patches showed an adequate safety profile in a working heart model as no electrophysiologic alterations were detected in healthy hearts. Epicardial implantation of Piezo patches in acutely infarcted mice hearts significantly improved myocardial electrical integrity without disturbing systolic function. Moreover, Piezo patches partially prevented ischemia-related adverse cardiac remodeling, reducing left ventricular chamber dilatation and compensatory hypertrophy. Coherently, Piezo patch-implanted hearts revealed downregulation of genes associated with extracellular matrix remodeling. Importantly, in vivo implantation of Piezo patches in porcine hearts revealed to be electrically safe as no major effects in its electrophysiology were detected. Overall, the results presented here endorse Piezo patches as a promising therapeutic strategy to improve post-myocardial infarction structural and electrical remodeling.
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Affiliation(s)
- Luís M. Monteiro
- IIIUC-Institute of Interdisciplinary Research, University of Coimbra, Casa Costa Alemão, 3030-789, Coimbra, Portugal
- CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, UC, Biotech Parque Tecnológico de Cantanhede, 3060-197, Coimbra, Portugal
- PhD Programme in Experimental Biology and Biomedicine, Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Casa Costa Alemão, 3030-789, Coimbra, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Pedro J. Gouveia
- CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, UC, Biotech Parque Tecnológico de Cantanhede, 3060-197, Coimbra, Portugal
| | - Francisco Vasques-Nóvoa
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- INEB - Instituto Nacional de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
| | - Susana Rosa
- CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, UC, Biotech Parque Tecnológico de Cantanhede, 3060-197, Coimbra, Portugal
| | - Ifigeneia Bardi
- Imperial College London, National Heart & Lung Institute, London, United Kingdom
| | - Rita N. Gomes
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- INEB - Instituto Nacional de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
- ICBAS - Instituto de Ciências Biomédicas de Abel Salazar, Universidade do Porto, Porto, Portugal
| | - Simão Correia-Santos
- IIIUC-Institute of Interdisciplinary Research, University of Coimbra, Casa Costa Alemão, 3030-789, Coimbra, Portugal
- CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, UC, Biotech Parque Tecnológico de Cantanhede, 3060-197, Coimbra, Portugal
- PhD Programme in Experimental Biology and Biomedicine, Institute for Interdisciplinary Research (IIIUC), University of Coimbra, Casa Costa Alemão, 3030-789, Coimbra, Portugal
| | - Leonardo Ricotti
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
| | - Lorenzo Vannozzi
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
| | - Daniele Guarnera
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
- Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, Piazza Martiri della Libertà 33, 56127, Pisa, Italy
| | - Liliana Costa
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
| | - André M. Leite-Moreira
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
| | - Pedro Mendes-Ferreira
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
| | - Adelino F. Leite-Moreira
- UnIC@RISE, Department of Surgery and Physiology, Faculty of Medicine of the University of Porto, Porto, Portugal
| | - Filippo Perbellini
- Imperial College London, National Heart & Lung Institute, London, United Kingdom
| | | | - Perpétua Pinto-do-Ó
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- INEB - Instituto Nacional de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
- ICBAS - Instituto de Ciências Biomédicas de Abel Salazar, Universidade do Porto, Porto, Portugal
| | - Lino Ferreira
- CNC-Center for Neuroscience and Cell Biology, CIBB-Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, UC, Biotech Parque Tecnológico de Cantanhede, 3060-197, Coimbra, Portugal
- Faculty of Medicine of the University of Coimbra, 3000-548, Coimbra, Portugal
| | - Diana S. Nascimento
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- INEB - Instituto Nacional de Engenharia Biomédica, Universidade do Porto, Porto, Portugal
- ICBAS - Instituto de Ciências Biomédicas de Abel Salazar, Universidade do Porto, Porto, Portugal
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2
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Yamaguchi TN, Houlahan KE, Zhu H, Kurganovs N, Livingstone J, Fox NS, Yuan J, Sietsma Penington J, Jung CH, Schwarz T, Jaratlerdsiri W, van Riet J, Georgeson P, Mangiola S, Taraszka K, Lesurf R, Jiang J, Chow K, Heisler LE, Shiah YJ, Ramanand SG, Clarkson MJ, Nguyen A, Espiritu SMG, Stuchbery R, Jovelin R, Huang V, Bell C, O’Connor E, McCoy PJ, Lalansingh CM, Cmero M, Salcedo A, Chan EK, Liu LY, Stricker PD, Bhandari V, Bornman RM, Sendorek DH, Lonie A, Prokopec SD, Fraser M, Peters JS, Foucal A, Mutambirwa SB, Mcintosh L, Orain M, Wakefield M, Picard V, Park DJ, Hovington H, Kerger M, Bergeron A, Sabelnykova V, Seo JH, Pomerantz MM, Zaitlen N, Waszak SM, Gusev A, Lacombe L, Fradet Y, Ryan A, Kishan AU, Lolkema MP, Weischenfeldt J, Têtu B, Costello AJ, Hayes VM, Hung RJ, He HH, McPherson JD, Pasaniuc B, van der Kwast T, Papenfuss AT, Freedman ML, Pope BJ, Bristow RG, Mani RS, Corcoran NM, Reimand J, Hovens CM, Boutros PC. The Germline and Somatic Origins of Prostate Cancer Heterogeneity. Cancer Discov 2025; 15:988-1017. [PMID: 39945744 PMCID: PMC12046336 DOI: 10.1158/2159-8290.cd-23-0882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 12/06/2024] [Accepted: 02/10/2025] [Indexed: 02/23/2025]
Abstract
SIGNIFICANCE This study uncovered 223 recurrently mutated driver regions using the largest cohort of prostate tumors to date. It reveals associations between germline SNPs, somatic drivers, and tumor aggression, offering significant insights into how prostate tumor evolution is shaped by germline factors and the timing of somatic mutations.
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Affiliation(s)
- Takafumi N. Yamaguchi
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
| | - Kathleen E. Houlahan
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California
| | - Helen Zhu
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Natalie Kurganovs
- Ontario Institute for Cancer Research, Toronto, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | - Julie Livingstone
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
| | - Natalie S. Fox
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Jiapei Yuan
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas
| | | | - Chol-Hee Jung
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
| | - Tommer Schwarz
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, California
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, California
| | - Weerachai Jaratlerdsiri
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Job van Riet
- Department of Medical Oncology, Erasmus University, Rotterdam, the Netherlands
| | - Peter Georgeson
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
| | - Stefano Mangiola
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Bioinformatics Division, Walter and Eliza Hall Institute, Parkville, Australia
| | - Kodi Taraszka
- Department of Computer Science, University of California, Los Angeles, Los Angeles, California
| | - Robert Lesurf
- Ontario Institute for Cancer Research, Toronto, Canada
| | - Jue Jiang
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Ken Chow
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Division of Urology, Royal Melbourne Hospital, Parkville, Australia
| | | | - Yu-Jia Shiah
- Ontario Institute for Cancer Research, Toronto, Canada
| | | | - Michael J. Clarkson
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | - Anne Nguyen
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | | | - Ryan Stuchbery
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | | | - Vincent Huang
- Ontario Institute for Cancer Research, Toronto, Canada
| | - Connor Bell
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Edward O’Connor
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Patrick J. McCoy
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | | | - Marek Cmero
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Bioinformatics Division, Walter and Eliza Hall Institute, Parkville, Australia
| | - Adriana Salcedo
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Eva K.F. Chan
- St Vincent’s Clinical School, University of New South Wales, Randwick, Australia
- Department of Urology, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
| | - Lydia Y. Liu
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
| | - Phillip D. Stricker
- Department of Urology, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
| | - Vinayak Bhandari
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Riana M.S. Bornman
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | | | - Andrew Lonie
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
| | | | - Michael Fraser
- Ontario Institute for Cancer Research, Toronto, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Justin S. Peters
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | - Adrien Foucal
- Ontario Institute for Cancer Research, Toronto, Canada
| | | | - Lachlan Mcintosh
- Bioinformatics Division, Walter and Eliza Hall Institute, Parkville, Australia
| | - Michèle Orain
- Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Matthew Wakefield
- Bioinformatics Division, Walter and Eliza Hall Institute, Parkville, Australia
| | - Valérie Picard
- Division of Urology and Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Daniel J. Park
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
| | - Hélène Hovington
- Division of Urology and Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Michael Kerger
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
| | - Alain Bergeron
- Division of Urology and Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | | | - Ji-Heui Seo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Mark M. Pomerantz
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, Los Angeles, California
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, California
| | - Sebastian M. Waszak
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo and Oslo University Hospital, Oslo, Norway
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Alexander Gusev
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
- Division of Genetics, Brigham Women’s Hospital and Harvard Medical School, Boston, Massachusetts
- The Eli and Edythe L. Broad Institute, Cambridge, Massachusetts
| | - Louis Lacombe
- Division of Urology and Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Yves Fradet
- Division of Urology and Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Andrew Ryan
- TissuPath Specialist Pathology Services, Mount Waverley, Australia
| | - Amar U. Kishan
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, California
| | - Martijn P. Lolkema
- Department of Computer Science, University of California, Los Angeles, Los Angeles, California
- Center for Personalized Cancer Treatment, Rotterdam, the Netherlands
| | - Joachim Weischenfeldt
- Biotech Research & Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
- Finsen Laboratory, Rigshospitalet, Copenhagen, Denmark
- Department of Urology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Bernard Têtu
- Research Centre of CHU de Québec-Université Laval, Québec City, Canada
| | - Anthony J. Costello
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Division of Urology, Royal Melbourne Hospital, Parkville, Australia
| | - Vanessa M. Hayes
- St Vincent’s Clinical School, University of New South Wales, Randwick, Australia
- Department of Urology, St. Vincent’s Hospital Sydney, Darlinghurst, Australia
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
- Central Clinical School, University of Sydney, Camperdown, Australia
- Department of Medical Sciences, University of Limpopo, Mankweng, South Africa
| | - Rayjean J. Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Toronto, Canada
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Housheng H. He
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - John D. McPherson
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Bogdan Pasaniuc
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Pathology and Laboratory Medicine, University of California, Los Angeles, Los Angeles, California
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, California
| | | | - Anthony T. Papenfuss
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
- Department of Medical Biology, University of Melbourne, Parkville, Australia
- Department of Mathematics and Statistics, University of Melbourne, Parkville, Australia
- Peter MacCallum Cancer Centre, Victorian Comprehensive Cancer Centre, Melbourne, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, Australia
| | - Matthew L. Freedman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Division of Population Sciences, Dana-Farber Cancer Institute, Boston, Massachusetts
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Bernard J. Pope
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australia
- Department of Medicine, Monash University, Clayton, Australia
| | - Robert G. Bristow
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
- Manchester Cancer Research Centre, Manchester, United Kingdom
| | - Ram S. Mani
- Department of Pathology, UT Southwestern Medical Center, Dallas, Texas
- Department of Urology, UT Southwestern Medical Center, Dallas, Texas
| | - Niall M. Corcoran
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
- Division of Urology, Royal Melbourne Hospital, Parkville, Australia
- Department of Urology, Peninsula Health, Frankston, Australia
- The Victorian Comprehensive Cancer Centre, Parkville, Australia
| | - Jüri Reimand
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Christopher M. Hovens
- Australian Prostate Cancer Research Centre Epworth, Richmond, Australia
- Department of Surgery, The University of Melbourne, Parkville, Australia
| | - Paul C. Boutros
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California
- Jonsson Comprehensive Cancer Centre, University of California, Los Angeles, Los Angeles, California
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, California
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
- Vector Institute, Toronto, Canada
- Department of Urology, University of California, Los Angeles, Los Angeles, California
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3
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Motyer A, Jackson S, Yang B, Harliwong I, Tian W, Shiu WIA, Shao Y, Wang B, McLean C, Barnett M, Kilpatrick TJ, Leslie S, Rubio JP. Neuronal somatic mutations are increased in multiple sclerosis lesions. Nat Neurosci 2025; 28:757-765. [PMID: 40038527 DOI: 10.1038/s41593-025-01895-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Accepted: 01/09/2025] [Indexed: 03/06/2025]
Abstract
Neuroinflammation underpins neurodegeneration and clinical progression in multiple sclerosis (MS), but knowledge of processes linking these disease mechanisms remains incomplete. Here we investigated somatic single-nucleotide variants (sSNVs) in the genomes of 106 single neurons from post-mortem brain tissue of ten MS cases and 16 controls to determine whether somatic mutagenesis is involved. We observed an increase of 43.9 sSNVs per year in neurons from chronic MS lesions, a 2.5 times faster rate than in neurons from normal-appearing MS and control tissues. This difference was equivalent to 1,291 excess sSNVs in lesion neurons at 70 years of age compared to controls. We performed mutational signature analysis to investigate mechanisms underlying neuronal sSNVs and identified a signature characteristic of lesions with a strong, age-associated contribution to sSNV counts. This research suggests that neuroinflammation is mutagenic in the MS brain, potentially contributing to disease progression.
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Affiliation(s)
- Allan Motyer
- Melbourne Integrative Genomics, The University of Melbourne, Melbourne, Victoria, Australia
- School of Mathematics and Statistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Stacey Jackson
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | | | | | - Wei Tian
- BGI-Australia, Herston, Queensland, Australia
| | | | | | - Bo Wang
- China National GeneBank, Shenzhen, China
- Shenzhen Key Laboratory of Environmental Microbial Genomics and Application, BGI Research, Shenzhen, China
| | - Catriona McLean
- Department of Anatomical Pathology, Alfred Health, Melbourne, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Michael Barnett
- Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
| | - Trevor J Kilpatrick
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
- Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - Stephen Leslie
- Melbourne Integrative Genomics, The University of Melbourne, Melbourne, Victoria, Australia
- School of Mathematics and Statistics, The University of Melbourne, Melbourne, Victoria, Australia
| | - Justin P Rubio
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
- Florey Department of Neuroscience and Mental Health, The University of Melbourne, Melbourne, Victoria, Australia.
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4
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Rao J, Luo H, An D, Liang X, Peng L, Chen F. Performance evaluation of structural variation detection using DNBSEQ whole-genome sequencing. BMC Genomics 2025; 26:299. [PMID: 40133825 PMCID: PMC11938577 DOI: 10.1186/s12864-025-11494-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2024] [Accepted: 03/17/2025] [Indexed: 03/27/2025] Open
Abstract
BACKGROUND DNBSEQ platforms have been widely used for variation detection, including single-nucleotide variants (SNVs) and short insertions and deletions (INDELs), which is comparable to Illumina. However, the performance and even characteristics of structural variations (SVs) detection using DNBSEQ platforms are still unclear. RESULTS In this study, we assessed the detection of SVs using 40 tools on eight DNBSEQ whole-genome sequencing (WGS) datasets and two Illumina WGS datasets of NA12878. Our findings confirmed that the performance of SVs detection using the same tool on DNBSEQ and Illumina datasets was highly consistent, with correlations greater than 0.80 on metrics of number, size, precision and sensitivity, respectively. Furthermore, we constructed a "DNBSEQ" SV set (4,785 SVs) from the DNBSEQ datasets and an "Illumina" SV set (6,797 SVs) from the Illumina datasets. We found that these two SV sets were highly consistent of SV sites and genomic characteristics, including repetitive regions, GC distribution, difficult-to-sequence regions, and gene features, indicating the robustness of our comparative analysis and highlights the value of both platforms in understanding the genomic context of SVs. CONCLUSIONS Our study systematically analyzed and characterized germline SVs detected on WGS datasets sequenced from DNBSEQ platforms, providing a benchmark resource for further studies of SVs using DNBSEQ platforms.
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Affiliation(s)
- Junhua Rao
- MGI Tech, Shenzhen, 518083, China
- BGI, Shenzhen, 518083, China
| | | | - Dan An
- MGI Tech, Shenzhen, 518083, China
- BGI, Shenzhen, 518083, China
| | - Xinming Liang
- MGI Tech, Shenzhen, 518083, China
- BGI, Shenzhen, 518083, China
| | | | - Fang Chen
- MGI Tech, Shenzhen, 518083, China.
- BGI, Shenzhen, 518083, China.
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5
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Frias-Soler RC, Wellbrock NA, Bindila L, Wink M, Bairlein F. Transcriptome signatures of the lipid metabolism in the liver and partial characterisation of the plasma phospholipidome of a long-distance migratory bird, the Northern Wheatear (Oenanthe oenanthe). COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY. PART D, GENOMICS & PROTEOMICS 2025; 55:101452. [PMID: 39999724 DOI: 10.1016/j.cbd.2025.101452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 01/27/2025] [Accepted: 02/18/2025] [Indexed: 02/27/2025]
Abstract
The Northern Wheatear (Oenanthe oenanthe) is a long-distance migratory bird that has become a model species for the study of the phenomenology and molecular aspects of avian migration. Here, we analysed transcriptomic data related to the lipid metabolism in the liver of wheatears during the development and termination of the migratory fattening. In parallel, we partially characterised their plasma phospholipidome. Based on transcriptomic data, we found evidence of a fine-scale regulation of the lipogenesis/lipolysis rate and over the fatty acid composition during the migratory season. Furthermore, our results suggest a regulated production of oxylipins, signaling lipids derivatives of polyunsaturated fatty acids (PUFAs). Regarding the plasma phospholipid profiling, different lipid species showed a significant differential abundance among migratory stages: lysophosphatidylcholine (LPC 18:0), sphingomyelin (SM 34:1;O2) and phosphatidylinositols (PI 36:4 and PI 38:4). The liver transcriptomic and plasma lipidomic data agree well, showing the relevance of the liver in controlling the lipid metabolism in relation to migration. We hope that the results discussed in this publication would open the door for future functional genetic and metabolic studies regarding avian migration.
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Affiliation(s)
- Roberto Carlos Frias-Soler
- Institute of Avian Research, An der Vogelwarte 21, 26386 Wilhelmshaven, Germany; Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany; German Cancer Research Center (DKFZ), INF 581, 69120 Heidelberg, Germany.
| | - Natalie A Wellbrock
- Institute of Avian Research, An der Vogelwarte 21, 26386 Wilhelmshaven, Germany
| | - Laura Bindila
- Institute for Physiological Chemistry, University Medical Center of the Johannes Gutenberg-University Mainz, Duesbergweg 6, 55128 Mainz, Germany.
| | - Michael Wink
- Institute of Pharmacy and Molecular Biotechnology, Heidelberg University, Im Neuenheimer Feld 364, 69120 Heidelberg, Germany.
| | - Franz Bairlein
- Institute of Avian Research, An der Vogelwarte 21, 26386 Wilhelmshaven, Germany; Max Planck Institute of Animal Behavior, Am Obstberg 1, 78315 Radolfzell, Germany.
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6
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Wang R, Hastings WJ, Saliba JG, Bao D, Huang Y, Maity S, Kamal Ahmad OM, Hu L, Wang S, Fan J, Ning B. Applications of Nanotechnology for Spatial Omics: Biological Structures and Functions at Nanoscale Resolution. ACS NANO 2025; 19:73-100. [PMID: 39704725 PMCID: PMC11752498 DOI: 10.1021/acsnano.4c11505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Revised: 11/30/2024] [Accepted: 12/10/2024] [Indexed: 12/21/2024]
Abstract
Spatial omics methods are extensions of traditional histological methods that can illuminate important biomedical mechanisms of physiology and disease by examining the distribution of biomolecules, including nucleic acids, proteins, lipids, and metabolites, at microscale resolution within tissues or individual cells. Since, for some applications, the desired resolution for spatial omics approaches the nanometer scale, classical tools have inherent limitations when applied to spatial omics analyses, and they can measure only a limited number of targets. Nanotechnology applications have been instrumental in overcoming these bottlenecks. When nanometer-level resolution is needed for spatial omics, super resolution microscopy or detection imaging techniques, such as mass spectrometer imaging, are required to generate precise spatial images of target expression. DNA nanostructures are widely used in spatial omics for purposes such as nucleic acid detection, signal amplification, and DNA barcoding for target molecule labeling, underscoring advances in spatial omics. Other properties of nanotechnologies include advanced spatial omics methods, such as microfluidic chips and DNA barcodes. In this review, we describe how nanotechnologies have been applied to the development of spatial transcriptomics, proteomics, metabolomics, epigenomics, and multiomics approaches. We focus on how nanotechnology supports improved resolution and throughput of spatial omics, surpassing traditional techniques. We also summarize future challenges and opportunities for the application of nanotechnology to spatial omics methods.
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Affiliation(s)
- Ruixuan Wang
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Waylon J. Hastings
- Department
of Psychiatry and Behavioral Science, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Julian G. Saliba
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Duran Bao
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Yuanyu Huang
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Sudipa Maity
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Omar Mustafa Kamal Ahmad
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Logan Hu
- Groton
School, 282 Farmers Row, Groton, Massachusetts 01450, United States
| | - Shengyu Wang
- St.
Margaret’s Episcopal School, 31641 La Novia Avenue, San
Juan Capistrano, California92675, United States
| | - Jia Fan
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
| | - Bo Ning
- Center
for Cellular and Molecular Diagnostics, Tulane University School of Medicine, New Orleans, Louisiana 70112, United States
- Department
of Biochemistry and Molecular Biology, Tulane
University School of Medicine, New Orleans, Louisiana 70112, United States
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7
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He Q, Lai Z, Zhai Z, Zou B, Shi Y, Feng C. Advances of research in diabetic cardiomyopathy: diagnosis and the emerging application of sequencing. Front Cardiovasc Med 2025; 11:1501735. [PMID: 39872882 PMCID: PMC11769946 DOI: 10.3389/fcvm.2024.1501735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 12/27/2024] [Indexed: 01/30/2025] Open
Abstract
Diabetic cardiomyopathy (DCM) is one of the most prevalent and severe complications associated with diabetes mellitus (DM). The onset of DCM is insidious, with the symptoms being obvious only in the late stage. Consequently, the early diagnosis of DCM is a formidable challenge which significantly influences the treatment and prognosis of DCM. Thus, it becomes imperative to uncover innovative approaches to facilitate the prompt identification and diagnosis of DCM. On the traditional clinical side, we tend to use serum biomarkers as well as imaging as the most common means of diagnosing diseases because of their convenience as well as affordability. As we delve deeper into the mechanisms of DCM, a wide variety of biomarkers are becoming competitive diagnostic indicators. Meanwhile, the application of multiple imaging techniques has also made efforts to promote the diagnosis of DCM. Besides, the spurt in sequencing technology has made it possible to give hints about disease diagnosis from the genome as well as the transcriptome, making diagnosis less difficult, more sensitive, and more predictive. Overall, sequencing technology is expected to be the superior choice of plasma biomarkers for detecting lesions at an earlier stage than imaging, and its judicious utilization combined with imaging technologies will lead to a more sensitive diagnosis of DCM in the future. Therefore, this review meticulously consolidates the progress and utilization of various biomarkers, imaging methods, and sequencing technologies in the realm of DCM diagnosis, with the aim of furnishing novel theoretical foundation and guide future research endeavors towards enhancing the diagnostic and therapeutic landscape of DCM.
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Affiliation(s)
- Qianqian He
- Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China
| | - Ze Lai
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, China
| | - Zhengyao Zhai
- Department of Gynecological Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Beibei Zou
- Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China
| | - Yangkai Shi
- Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China
| | - Chao Feng
- Department of Cardiology, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, China
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8
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Zhang G, Wang Y, Jiang H, Wang Y. Genomic and transcriptomic analyses of Heteropoda venatoria reveal the expansion of P450 family for starvation resistance in spiders. Gigascience 2025; 14:giaf019. [PMID: 40117180 PMCID: PMC11927401 DOI: 10.1093/gigascience/giaf019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Revised: 12/09/2024] [Accepted: 02/06/2025] [Indexed: 03/23/2025] Open
Abstract
BACKGROUND Research on the mechanism of starvation resistance can help reveal how animals adjust their physiology and behavior to adapt to the uncertainty of food resources. A low metabolic rate is a significant characteristic of spider physiological activity and can increase spider starvation resistance and adapt to complex ecological environments. RESULTS We sequenced the genome of Heteropoda venatoria and discovered significant expansions in gene families related to lipid metabolism, such as cytochrome P450 and steroid hormone biosynthesis genes, through comparative genomic analysis. We also systematically analyzed the gene expression characteristics of H. venatoria at different starvation resistance stages and reported that the fat body plays a crucial role during starvation in spiders. This study indicates that during the early stages of starvation, H. venatoria relies on glucose metabolism to meet its energy demands. In the middle stage, gene expression stabilizes, whereas in the late stage of starvation, pathways for fatty acid metabolism and protein degradation are significantly activated, and autophagy is increased, serving as a survival strategy under extreme starvation. Notably, analysis of expanded P450 gene families revealed that H. venatoria has many duplicated CYP3 clan genes that are highly expressed in the fat body, which may help maintain a low-energy metabolic state, allowing H. venatoria to endure longer periods of starvation. We also observed that the motifs of P450 families in H. venatoria are less conserved than those in insects are, which may be related to the greater polymorphism of spider genomes. CONCLUSIONS This research not only provides important genetic and transcriptomic evidence for understanding the starvation mechanisms of spiders but also offers new insights into the adaptive evolution of arthropods.
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Affiliation(s)
- Guoqing Zhang
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City, Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Yiru Wang
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City, Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Hongcen Jiang
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City, Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Yi Wang
- Integrative Science Center of Germplasm Creation in Western China (CHONGQING) Science City, Biological Science Research Center, Southwest University, Chongqing 400715, China
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9
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Polonis K, Blommel JH, Hughes AEO, Spencer D, Thompson JA, Schroeder MC. Innovations in Short-Read Sequencing Technologies and Their Applications to Clinical Genomics. Clin Chem 2025; 71:97-108. [PMID: 39749506 DOI: 10.1093/clinchem/hvae173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Accepted: 09/23/2024] [Indexed: 01/04/2025]
Abstract
BACKGROUND Massively parallel sequencing (MPS) of nucleic acids has been a transformative technology for basic and applied genomic science, increasing efficiencies and decreasing costs to enable studies of unprecedented scope and impact. In clinical settings, these technological and scientific advances have led to the development of tests that are increasingly fast, comprehensive, and more frequently employed. Practitioners of genomic medicine have applied these tools across clinical settings, including diagnosis of inherited disorders and cancers and infectious disease detection and surveillance. In recent years, the commercial marketplace for MPS sequencers and reagents has been dominated by a few companies. The growing demand for sequencing has led to the recent emergence of several new sequencing platforms with techniques that may provide alternatives or improvements to existing workflows or allow the adoption of sequencing workflows in new settings. Clinical genomics laboratories will evaluate these platforms from a unique perspective, focusing on how technological advancements can improve patient care. CONTENT This review describes short-read sequencing platforms provided by Illumina, Element Biosciences, MGI, PacBio, Singular Genomics, Thermo Fisher Scientific, and Ultima Genomics. This review discusses their innovative approaches, principles, workflows, and applications. SUMMARY This review aims to inform laboratory geneticists, clinicians, and researchers about emerging short-read technologies and their applications in clinical genomics. By highlighting their principles and potential contributions, we aim to assist laboratories in selecting suitable solutions for their sequencing needs considering key factors such as applications, throughput, and integration with existing laboratory workflows.
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Affiliation(s)
- Katarzyna Polonis
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
| | - Joseph H Blommel
- Advanced Diagnostic Laboratories, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States
| | - Andrew E O Hughes
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
| | - David Spencer
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, United States
| | | | - Molly C Schroeder
- Division of Genomic and Molecular Pathology, Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, United States
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, United States
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10
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Ling R, Du C, Li Y, Wang S, Cong X, Huang D, Chen S, Zhu S. Protective Effect of Selenium-enriched Peptide from Cardamine violifolia on Ethanol-induced L-02 Hepatocyte Injury. Biol Trace Elem Res 2025; 203:139-152. [PMID: 38538964 DOI: 10.1007/s12011-024-04159-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 03/23/2024] [Indexed: 01/07/2025]
Abstract
In this study, we investigated the protective effect of selenium (Se)-enriched peptide isolated from Cardamine violifolia (SPE) against ethanol-induced liver injury. Cell proliferation assays show that different concentrations of SPE protect human embryonic liver L-02 cells against ethanol-induced injury in a dose-dependent manner. Treatment with 12 μmol/L Se increases the cell survival rate (82.44%) and reduces the release of alanine aminotransferase, aspartate transaminase, lactate dehydrogenase, and apoptosis rate. SPE treatment with 12 μmol/L Se effectively reduces the concentration of intracellular reactive oxygen species and increases the contents of intracellular superoxide dismutase (51.64 U/mg), catalase (4.41 U/mg), glutathione peroxidase (1205.28 nmol/g), and glutathione (66.67 μmol/g), thereby inhibiting the effect of ethanol-induced oxidative damage. The results of the transcriptomic analysis show that the glutathione metabolism and apoptotic pathway play significant roles in the protection of L-02 hepatocytes by SPE. Real-time qPCR analysis shows that SPE increases the mRNA expression of GPX1 and NGFR. The results of this study highlight the protective effects of SPE against ethanol-induced liver injury.
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Affiliation(s)
- Rongrui Ling
- School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 4122, Jiangsu, China
| | - Chaodong Du
- School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
| | - Yue Li
- School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
| | - Shan Wang
- School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China
| | - Xin Cong
- Enshi Se-Run Material Engineering Technology Co., Ltd, Enshi, 445000, Hubei, China
- National R&D Center for Se-Rich Agricultural Products Processing, Wuhan Polytechnic University, Wuhan, 430023, China
| | - Dejian Huang
- Department of Food Science and Technology, National University of Singapore, Singapore, 117543, Singapore
| | - Shangwei Chen
- Analysis and Testing Center, Jiangnan University, Wuxi, 4122, Jiangsu, China
| | - Song Zhu
- School of Food Science and Technology, Jiangnan University, Wuxi, 214122, Jiangsu, China.
- State Key Laboratory of Food Science and Resources, Jiangnan University, Wuxi, 4122, Jiangsu, China.
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11
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Ruppeka Rupeika E, D’Huys L, Leen V, Hofkens J. Sequencing and Optical Genome Mapping for the Adventurous Chemist. CHEMICAL & BIOMEDICAL IMAGING 2024; 2:784-807. [PMID: 39735829 PMCID: PMC11673194 DOI: 10.1021/cbmi.4c00060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 10/03/2024] [Accepted: 10/04/2024] [Indexed: 12/31/2024]
Abstract
This review provides a comprehensive overview of the chemistries and workflows of the sequencing methods that have been or are currently commercially available, providing a very brief historical introduction to each method. The main optical genome mapping approaches are introduced in the same manner, although only a subset of these are or have ever been commercially available. The review comes with a deck of slides containing all of the figures for ease of access and consultation.
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Affiliation(s)
| | - Laurens D’Huys
- Faculty
of Science, Chemistry, KU Leuven, Celestijnenlaan 200F, Leuven, Flanders 3001, Belgium
| | - Volker Leen
- Perseus
Biomics B.V., Industriepark
6 bus 3, Tienen 3300, Belgium
| | - Johan Hofkens
- Faculty
of Science, Chemistry, KU Leuven, Celestijnenlaan 200F, Leuven, Flanders 3001, Belgium
- Max
Planck Institute for Polymer Research, Mainz, Rheinland-Pfalz 55128, Germany
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12
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Pogner CE, Antunes C, Apangu GP, Bruffaerts N, Celenk S, Cristofori A, González Roldán N, Grinn-Gofroń A, Lara B, Lika M, Magyar D, Martinez-Bracero M, Muggia L, Muyshondt B, O'Connor D, Pallavicini A, Marchã Penha MA, Pérez-Badia R, Ribeiro H, Rodrigues Costa A, Tischner Z, Xhetani M, Ambelas Skjøth C. Airborne DNA: State of the art - Established methods and missing pieces in the molecular genetic detection of airborne microorganisms, viruses and plant particles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 957:177439. [PMID: 39549753 DOI: 10.1016/j.scitotenv.2024.177439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2024] [Revised: 10/27/2024] [Accepted: 11/05/2024] [Indexed: 11/18/2024]
Abstract
Bioaerosol is composed of different particles, originating from organisms, or their fragments with different origin, shape, and size. Sampling, analysing, identification and describing this airborne diversity has been carried out for over 100 years, and more recently the use of molecular genetic tools has been implemented. However, up to now there are no established protocols or standards for detecting airborne diversity of bacteria, fungi, viruses, pollen, and plant particles. In this review we evaluated commonalities of methods used in molecular genetic based studies in the last 23 years, to give an overview of applicable methods as well as knowledge gaps in diversity assessment. Various sampling techniques show different levels of effectiveness in detecting airborne particles based on their DNA. The storage and processing of samples, as well as DNA processing, influences the outcome of sampling campaigns. Moreover, the decisions on barcode selection, method of analysis, reference database as well as negative and positive controls may severely impact the results obtained. To date, the chain of decisions, methodological biases and error propagation have hindered DNA based molecular sequencing from offering a holistic picture of the airborne biodiversity. Reviewing the available studies, revealed a great diversity in used methodology and many publications didn't state all used methods in detail, making comparisons with other studies difficult or impossible. To overcome these limitations and ensure genuine comparability across studies, it is crucial to standardize protocols. Publications need to include all necessary information to enable comparison among different studies and to evaluate how methodological choices can impacts the results. Besides standardization, implementing of automatic tools and combining of different analytical techniques, such as real-time evaluation combined with sampling and molecular genetic analysis, could assist in achieving the goal of accurately assessing the actual airborne biodiversity.
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Affiliation(s)
- C-E Pogner
- Unit Bioresources, Center of Health and Bioresources, AIT Austrian Institute of Technology GmbH, Konrad-Lorenz-Straße 24, 3430 Tulln, Austria.
| | - C Antunes
- Department of Medical and Health Sciences, School of Health and Human Development University of Évora and Earth Sciences Institute (ICT), Pole of the University of Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
| | - G P Apangu
- Protecting Crops and the Environment, Rothamsted Research, West Common, Harpenden, Hertfordshire AL5 2JQ, UK
| | - N Bruffaerts
- Mycology and Aerobiology, Sciensano, Rue J. Wytsmanstraat 14, 1050 Brussels, Belgium
| | - S Celenk
- Bursa Uludag University, Arts and Science Faculty, Biology Department, Görükle-Bursa, Turkey
| | - A Cristofori
- Research and Innovation Centre, Fondazione Edmund Mach, San Michele all'Adige, Via Mach 1, 38098 San Michele all'Adige, TN, Italy; NBFC, National Biodiversity Future Center, 90133 Palermo, Italy
| | - N González Roldán
- Pollen Laboratory, Department of Biological and Environmental Sciences, University of Gothenburg, Medicinaregatan 7B, 41390 Gothenburg, Sweden
| | - A Grinn-Gofroń
- Institute of Biology, University of Szczecin, Wąska 13 Street, 71-415 Szczecin, Poland
| | - B Lara
- Institute of Environmental Sciences, University of Castilla-La Mancha, Avda Carlos III, s/n, 45071 Toledo, Spain
| | - M Lika
- Department of Biology, Faculty of Natural Sciences, University of Tirana, Tirana, Albania
| | - D Magyar
- National Center for Public Health and Pharmacy, Albert Flórián út 2-6, 1097 Budapest, Hungary
| | - M Martinez-Bracero
- Department of Botany, Ecology and Plant Physiology, Córdoba University, 14071 Córdoba, Spain
| | - L Muggia
- Department of Life Sciences, University of Trieste, via L. Giorgieri 7, 34127 Trieste, Italy
| | - B Muyshondt
- Mycology and Aerobiology, Sciensano, Rue J. Wytsmanstraat 14, 1050 Brussels, Belgium
| | - D O'Connor
- School of Chemical Sciences, Dublin City University, Dublin D09 V209, Ireland
| | - A Pallavicini
- Department of Life Sciences, University of Trieste, via L. Giorgieri 7, 34127 Trieste, Italy
| | - M A Marchã Penha
- Department of Medical and Health Sciences, School of Health and Human Development University of Évora and Earth Sciences Institute (ICT), Pole of the University of Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
| | - R Pérez-Badia
- Institute of Environmental Sciences, University of Castilla-La Mancha, Avda Carlos III, s/n, 45071 Toledo, Spain
| | - H Ribeiro
- Department of Geosciences, Environment and Spatial Plannings, Faculty of Sciences, Earth Sciences Institute (ICT), Pole of the Faculty of Sciences, University of Porto, Rua do Campo Alegre, 687, 4169-007 Porto, Portugal
| | - A Rodrigues Costa
- Department of Medical and Health Sciences, School of Health and Human Development University of Évora and Earth Sciences Institute (ICT), Pole of the University of Évora, Rua Romão Ramalho, 59, 7000-671 Évora, Portugal
| | - Z Tischner
- National Center for Public Health and Pharmacy, Albert Flórián út 2-6, 1097 Budapest, Hungary
| | - M Xhetani
- Department of Biology, Faculty of Natural Sciences, University of Tirana, Tirana, Albania
| | - C Ambelas Skjøth
- Department of Environmental Science, iCLIMATE, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark
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13
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Lee J, Han J, Song Y, Gu B, Kim E. Design and Optimization of Isothermal Gene Amplification for Generation of High-Gain Oligonucleotide Products by MicroRNAs. ACS MEASUREMENT SCIENCE AU 2024; 4:737-750. [PMID: 39713023 PMCID: PMC11660000 DOI: 10.1021/acsmeasuresciau.4c00063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2024] [Revised: 10/23/2024] [Accepted: 11/01/2024] [Indexed: 12/24/2024]
Abstract
Thermal cycling-based quantitative polymerase chain reaction (qPCR) represents the gold standard method for accurate and sensitive nucleic acid quantification in laboratory settings. However, its reliance on costly thermal cyclers limits the implementation of this technique for rapid point-of-care (POC) diagnostics. To address this, isothermal amplification techniques such as rolling circle amplification (RCA) have been developed, offering a simpler alternative that can operate without the need for sophisticated instrumentation. This study focuses on the development and optimization of toehold-mediated RCA (TRCA), which employs a conformationally switchable dumbbell DNA template for the sensitive and selective detection of cancer-associated miRNAs, specifically miR-21. In addition, we developed variants of hyperbranched TRCA (HTRCA), nicking-assisted TRCA (NTRCA), and hyperbranched NTRCA (HNTRCA) to facilitate exponential amplification by enhancing TRCA through the sequential incorporation of reverse primer (Pr) and nicking endonuclease (nE). By conducting a systematic kinetic analysis of the initial rate and end point signals for varying concentrations of key reaction components, we could identify optimal conditions that markedly enhanced the sensitivity and specificity of the TRCA variants. In particular, HNTRCA, which exploits the synergistic effect of Pr and nE, demonstrated an approximately 3000-fold improvement in the detection limit (260 fM) and a wider dynamic range of more than 4 log orders of magnitude compared to TRCA, thereby evidencing its superior performance. Also, we established a mechanistic model for TRCA that includes the roles of Pr and nE in different amplification processes. Model parameters were fitted to the experimental data, and additional simulations were conducted to compare the four amplification methods. Further tests with real biological samples revealed that this technique showed a good correlation with qPCR in quantifying miR-21 expression in various cell lines (0.9510 of Pearson's r), confirming its potential as a robust and rapid tool for nucleic acid detection. Therefore, the simplicity, high sensitivity, and potential for integration with POC diagnostic platforms make the HNTRCA system suitable for field deployment in resource-limited environments.
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Affiliation(s)
- Jihee Lee
- Department
of Bioengineering and Nano-Bioengineering, Research Center for Bio
Materials and Process Development, Incheon
National University, Incheon 22012, Republic of Korea
| | - Jueun Han
- Department
of Bioengineering and Nano-Bioengineering, Research Center for Bio
Materials and Process Development, Incheon
National University, Incheon 22012, Republic of Korea
| | - Yejin Song
- Department
of Bioengineering and Nano-Bioengineering, Research Center for Bio
Materials and Process Development, Incheon
National University, Incheon 22012, Republic of Korea
| | - Boram Gu
- School
of Chemical Engineering, Chonnam National
University, Gwangju 61186, Republic of Korea
| | - Eunjung Kim
- Department
of Bioengineering and Nano-Bioengineering, Research Center for Bio
Materials and Process Development, Incheon
National University, Incheon 22012, Republic of Korea
- Division
of Bioengineering, Incheon National University, Incheon 22012, Republic of Korea
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14
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Petrazzini BO, Balick DJ, Forrest IS, Cho J, Rocheleau G, Jordan DM, Do R. Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease. CELL REPORTS METHODS 2024; 4:100914. [PMID: 39657681 PMCID: PMC11704621 DOI: 10.1016/j.crmeth.2024.100914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/19/2024] [Accepted: 11/13/2024] [Indexed: 12/12/2024]
Abstract
Mode of inheritance (MOI) is necessary for clinical interpretation of pathogenic variants; however, the majority of variants lack this information. Furthermore, variant effect predictors are fundamentally insensitive to recessive-acting diseases. Here, we present MOI-Pred, a variant pathogenicity prediction tool that accounts for MOI, and ConMOI, a consensus method that integrates variant MOI predictions from three independent tools. MOI-Pred integrates evolutionary and functional annotations to produce variant-level predictions that are sensitive to both dominant-acting and recessive-acting pathogenic variants. Both MOI-Pred and ConMOI show state-of-the-art performance on standard benchmarks. Importantly, dominant and recessive predictions from both tools are enriched in individuals with pathogenic variants for dominant- and recessive-acting diseases, respectively, in a real-world electronic health record (EHR)-based validation approach of 29,981 individuals. ConMOI outperforms its component methods in benchmarking and validation, demonstrating the value of consensus among multiple prediction methods. Predictions for all possible missense variants are provided in the "Data and code availability" section.
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Affiliation(s)
- Ben O Petrazzini
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel J Balick
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Biomedical Informatics, Harvard, Medical School, Boston, MA, USA
| | - Iain S Forrest
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Judy Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ghislain Rocheleau
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel M Jordan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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15
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Zhao Y, Zhang W, Zhang X. Application of metagenomic next-generation sequencing in the diagnosis of infectious diseases. Front Cell Infect Microbiol 2024; 14:1458316. [PMID: 39619659 PMCID: PMC11604630 DOI: 10.3389/fcimb.2024.1458316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2024] [Accepted: 10/31/2024] [Indexed: 12/11/2024] Open
Abstract
Metagenomic next-generation sequencing (mNGS) is a transformative approach in the diagnosis of infectious diseases, utilizing unbiased high-throughput sequencing to directly detect and characterize microbial genomes from clinical samples. This review comprehensively outlines the fundamental principles, sequencing workflow, and platforms utilized in mNGS technology. The methodological backbone involves shotgun sequencing of total nucleic acids extracted from diverse sample types, enabling simultaneous detection of bacteria, viruses, fungi, and parasites without prior knowledge of the infectious agent. Key advantages of mNGS include its capability to identify rare, novel, or unculturable pathogens, providing a more comprehensive view of microbial communities compared to traditional culture-based methods. Despite these strengths, challenges such as data analysis complexity, high cost, and the need for optimized sample preparation protocols remain significant hurdles. The application of mNGS across various systemic infections highlights its clinical utility. Case studies discussed in this review illustrate its efficacy in diagnosing respiratory tract infections, bloodstream infections, central nervous system infections, gastrointestinal infections, and others. By rapidly identifying pathogens and their genomic characteristics, mNGS facilitates timely and targeted therapeutic interventions, thereby improving patient outcomes and infection control measures. Looking ahead, the future of mNGS in infectious disease diagnostics appears promising. Advances in bioinformatics tools and sequencing technologies are anticipated to streamline data analysis, enhance sensitivity and specificity, and reduce turnaround times. Integration with clinical decision support systems promises to further optimize mNGS utilization in routine clinical practice. In conclusion, mNGS represents a paradigm shift in the field of infectious disease diagnostics, offering unparalleled insights into microbial diversity and pathogenesis. While challenges persist, ongoing technological advancements hold immense potential to consolidate mNGS as a pivotal tool in the armamentarium of modern medicine, empowering clinicians with precise, rapid, and comprehensive pathogen detection capabilities.
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Affiliation(s)
- Yu Zhao
- Department of Urology Surgery, Beijing Chao-Yang Hospital Affiliated to Capital Medical University, Beijing, China
| | - Wenhui Zhang
- Department of Hepatobiliary Surgery, Beijing Chao-Yang Hospital Affiliated to Capital Medical University, Beijing, China
| | - Xin Zhang
- Department of Urology Surgery, Beijing Chao-Yang Hospital Affiliated to Capital Medical University, Beijing, China
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16
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Li J, Zhai Z, Zhang H, Su Z, Liu Y, Chen H, Li Y, Shen M. Deep learning enables the use of ultra-high-density array in DNBSEQ. Sci Rep 2024; 14:27847. [PMID: 39537672 PMCID: PMC11561341 DOI: 10.1038/s41598-024-78748-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 11/04/2024] [Indexed: 11/16/2024] Open
Abstract
DNBSEQ employs a patterned array to facilitate massively parallel sequencing of DNA nanoballs (DNBs), leading to a considerable boost in throughput. By employing the ultra-high-density (UHD) array with an increased density of DNB binding sites, the throughput of DNBSEQ can be further expanded. However, the typical imaging system of the DNBSEQ sequencer is unable to resolve adjacent DNBs spaced smaller than the resolution limit, resulting in poor base-calling performance of the UHD array and hindering its practical application. In this study, we propose a deep-learning-based DNB image super-resolution network named DNBSRN to address this problem. DNBSRN has a specifically designed structure for DNB images and employs a histogram-matching-based preprocessing approach. For the eight DNB image datasets generated from the DNBSEQ sequencer using UHD arrays with 360 nm pitch, the base-calling performances are significantly improved after super-resolution reconstruction by DNBSRN and reached a comparable level to those of the regular density array. In terms of reconstruction speed, DNBSRN takes only 7.61 ms for an input image with 500 × 500 pixels, which minimizes its influence on throughput. Furthermore, compared with state-of-the-art super-resolution networks, DNBSRN demonstrates superior performance in terms of both the quality and speed of DNB image reconstruction. DNBSRN successfully addresses the DNB image super-resolution task. Integrating DNBSRN into the image analysis workflow of DNBSEQ will allow for the application of UHD array, hence enabling a considerable improvement in throughput as well as tremendous savings in unit reagent cost.
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Affiliation(s)
- Junfeng Li
- BGI Research, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiwei Zhai
- BGI Research, Wuhan, 430074, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China
| | - Hao Zhang
- College of Engineering, Eastern Institute of Technology, Ningbo, 315200, China
| | - Zeyu Su
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China
| | - Yang Liu
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China
| | - Hongmin Chen
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China
| | - Yuxiang Li
- BGI Research, Shenzhen, 518083, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China.
| | - Mengzhe Shen
- BGI Research, Shenzhen, 518083, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen, 518120, China.
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17
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Bestard-Cuche N, Munro DAD, Beniazza M, Priller J, Williams A, Corsinotti A. Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics. Genes (Basel) 2024; 15:1436. [PMID: 39596636 PMCID: PMC11594097 DOI: 10.3390/genes15111436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2024] [Revised: 11/01/2024] [Accepted: 11/04/2024] [Indexed: 11/29/2024] Open
Abstract
BACKGROUND/OBJECTIVES High-throughput single-cell RNA sequencing (scRNA-seq) workflows produce libraries that demand extensive sequencing. However, standard next-generation sequencing (NGS) methods remain expensive, contributing to the high running costs of single-cell experiments and often negatively affecting the sample numbers and statistical strength of such projects. In recent years, a plethora of new sequencing technologies have become available to researchers through several manufacturers, often providing lower-cost alternatives to standard NGS. METHODS In this study, we compared data generated from mouse scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI's DNA nanoball sequencing (DNBSEQ). RESULTS Our findings reveal similar overall performance using both technologies. DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by higher Phred scores, lower read duplication rates and a greater number of genes mapping to the reference genome. Yet these improvements did not translate into meaningful differences in single-cell analysis parameters in our experiments, including detection of additional genes within cells, gene expression saturation levels and numbers of identified cells, with both technologies demonstrating equally robust performance in these aspects. The data produced by both sequencing platforms also produced comparable analytical outcomes for single-cell analysis. No significant difference in the annotation of cells into different cell types was observed and the same top genes were differentially expressed between populations and experimental conditions. CONCLUSIONS Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually indistinguishable results compared to standard methods, and providing cost-effective alternatives.
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Affiliation(s)
- Nadine Bestard-Cuche
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, MS Society Edinburgh Centre for MS Research, University of Edinburgh, Edinburgh EH16 4UU, UK; (N.B.-C.)
| | - David A. D. Munro
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH8 9AL, UK
| | - Meryam Beniazza
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, MS Society Edinburgh Centre for MS Research, University of Edinburgh, Edinburgh EH16 4UU, UK; (N.B.-C.)
| | - Josef Priller
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH8 9AL, UK
- Department of Psychiatry and Psychotherapy, School of Medicine and Health, Klinikum Rechts der Isar, Technical University Munich, and German Center for Mental Health (DZPG), 80333 Munich, Germany
| | - Anna Williams
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, MS Society Edinburgh Centre for MS Research, University of Edinburgh, Edinburgh EH16 4UU, UK; (N.B.-C.)
- UK Dementia Research Institute, University of Edinburgh, Edinburgh EH8 9AL, UK
| | - Andrea Corsinotti
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, MS Society Edinburgh Centre for MS Research, University of Edinburgh, Edinburgh EH16 4UU, UK; (N.B.-C.)
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18
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Hosoi S, Hirose T, Matsumura S, Otsubo Y, Saito K, Miyazawa M, Suzuki T, Masumura K, Sugiyama KI. Effect of sequencing platforms on the sensitivity of chemical mutation detection using Hawk-Seq™. Genes Environ 2024; 46:20. [PMID: 39385252 PMCID: PMC11462924 DOI: 10.1186/s41021-024-00313-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 09/22/2024] [Indexed: 10/12/2024] Open
Abstract
BACKGROUND Error-corrected next-generation sequencing (ecNGS) technologies have enabled the direct evaluation of genome-wide mutations after exposure to mutagens. Previously, we reported an ecNGS methodology, Hawk-Seq™, and demonstrated its utility in evaluating mutagenicity. The evaluation of technical transferability is essential to further evaluate the reliability of ecNGS-based assays. However, cutting-edge sequencing platforms are continually evolving, which can affect the sensitivity of ecNGS. Therefore, the effect of differences in sequencing instruments on mutation data quality should be evaluated. RESULTS We assessed the performance of four sequencing platforms (HiSeq2500, NovaSeq6000, NextSeq2000, and DNBSEQ-G400) with the Hawk-Seq™ protocol for mutagenicity evaluation using DNA samples from mouse bone marrow exposed to benzo[a]pyrene (BP). The overall mutation (OM) frequencies per 106 bp in vehicle-treated samples were 0.22, 0.36, 0.46, and 0.26 for HiSeq2500, NovaSeq6000, NextSeq2000, and DNBSEQ-G400, respectively. The OM frequency of NextSeq2000 was significantly higher than that of HiSeq2500, suggesting the difference to be based on the platform. The relatively higher value in NextSeq2000 was a consequence of the G:C to C:G mutations in NextSeq2000 data (0.67 per 106 G:C bp), which was higher than the mean of the four platforms by a ca. of 0.25 per 106 G:C bp. A clear dose-dependent increase in G:C to T:A mutation frequencies was observed in all four sequencing platforms after BP exposure. The cosine similarity values of the 96-dimensional trinucleotide mutation patterns between HiSeq and the three other platforms were 0.93, 0.95, and 0.92 for NovaSeq, NextSeq, and DNBSeq, respectively. These results suggest that all platforms can provide equivalent data that reflect the characteristics of the mutagens. CONCLUSIONS All platforms sensitively detected mutagen-induced mutations using the Hawk-Seq™ analysis. The substitution types and frequencies of the background errors differed depending on the platform. The effects of sequencing platforms on mutagenicity evaluation should be assessed before experimentation.
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Affiliation(s)
- Sayaka Hosoi
- R&D - Safety Science Research, Kao Corporation, 3-25-14 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-0821, Japan
| | - Takako Hirose
- R&D - Safety Science Research, Kao Corporation, 3-25-14 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-0821, Japan
| | - Shoji Matsumura
- R&D - Safety Science Research, Kao Corporation, 3-25-14 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-0821, Japan.
| | - Yuki Otsubo
- R&D - Safety Science Research, Kao Corporation, 3-25-14 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-0821, Japan
| | - Kazutoshi Saito
- R&D - Safety Science Research, Kao Corporation, 2606 Akabane, Ichikai-Machi, Haga-Gun, Tochigi, 321-3497, Japan
| | - Masaaki Miyazawa
- R&D - Safety Science Research, Kao Corporation, 2606 Akabane, Ichikai-Machi, Haga-Gun, Tochigi, 321-3497, Japan
| | - Takayoshi Suzuki
- Division of Genome Safety Science, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-9501, Japan
| | - Kenichi Masumura
- Division of Risk Assessment, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-9501, Japan
| | - Kei-Ichi Sugiyama
- Division of Genome Safety Science, National Institute of Health Sciences, 3-25-26 Tonomachi, Kawasaki-ku, Kawasaki-shi, Kanagawa, 210-9501, Japan
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19
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Yan RE, Greenfield JP. Challenges and Outlooks in Precision Medicine: Expectations Versus Reality. World Neurosurg 2024; 190:573-581. [PMID: 39425299 DOI: 10.1016/j.wneu.2024.06.142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 10/21/2024]
Abstract
Recent developments in technology have led to rapid advances in precision medicine, especially due to the rise of next-generation sequencing and molecular profiling. These technological advances have led to rapid advances in research, including increased tumor subtype resolution, new therapeutic agents, and mechanistic insights. Certain therapies have even been approved for molecular biomarkers across histopathological diagnoses; however, translation of research findings to the clinic still faces a number of challenges. In this review, the authors discuss several key challenges to the clinical integration of precision medicine, including the blood-brain barrier, both a lack and excess of molecular targets, and tumor heterogeneity/escape from therapy. They also highlight a few key efforts to address these challenges, including new frontiers in drug delivery, a rapidly expanding treatment repertoire, and improvements in active response monitoring. With continued improvements and developments, the authors anticipate that precision medicine will increasingly become the gold standard for clinical care.
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Affiliation(s)
- Rachel E Yan
- Department of Neurological Surgery, Weill Cornell Medicine, New York, New York, USA
| | - Jeffrey P Greenfield
- Department of Neurological Surgery, NewYork-Presbyterian Weill Cornell Medicine, New York, New York, USA.
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20
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Kumar KR, Cowley MJ, Davis RL. Next-Generation Sequencing and Emerging Technologies. Semin Thromb Hemost 2024; 50:1026-1038. [PMID: 38692283 DOI: 10.1055/s-0044-1786397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
Genetic sequencing technologies are evolving at a rapid pace with major implications for research and clinical practice. In this review, the authors provide an updated overview of next-generation sequencing (NGS) and emerging methodologies. NGS has tremendously improved sequencing output while being more time and cost-efficient in comparison to Sanger sequencing. The authors describe short-read sequencing approaches, such as sequencing by synthesis, ion semiconductor sequencing, and nanoball sequencing. Third-generation long-read sequencing now promises to overcome many of the limitations of short-read sequencing, such as the ability to reliably resolve repeat sequences and large genomic rearrangements. By combining complementary methods with massively parallel DNA sequencing, a greater insight into the biological context of disease mechanisms is now possible. Emerging methodologies, such as advances in nanopore technology, in situ nucleic acid sequencing, and microscopy-based sequencing, will continue the rapid evolution of this area. These new technologies hold many potential applications for hematological disorders, with the promise of precision and personalized medical care in the future.
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Affiliation(s)
- Kishore R Kumar
- Translational Genomics Group, Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, Australia
- Molecular Medicine Laboratory, Concord Hospital, Sydney, Australia
| | - Mark J Cowley
- Translational Genomics Group, Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- Computational Biology Group, Children's Cancer Institute, University of New South Wales, Randwick, New South Wales, Australia
| | - Ryan L Davis
- Translational Genomics Group, Kinghorn Centre for Clinical Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- Department of Neurogenetics, Kolling Institute, University of Sydney and Royal North Shore Hospital, St Leonards, New South Wales, Australia
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21
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Berdnikova AA, Zorkoltseva IV, Tsepilov YA, Elgaeva EE. Genotype imputation in human genomic studies. Vavilovskii Zhurnal Genet Selektsii 2024; 28:628-639. [PMID: 39440308 PMCID: PMC11491486 DOI: 10.18699/vjgb-24-70] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 04/23/2024] [Accepted: 07/04/2024] [Indexed: 10/25/2024] Open
Abstract
Imputation is a method that supplies missing information about genetic variants that could not be directly genotyped with DNA microarrays or low-coverage sequencing. Imputation plays a critical role in genome-wide association studies (GWAS). It leads to a significant increase in the number of studied variants, which improves the resolution of the method and enhances the comparability of data obtained in different cohorts and/or by using different technologies, which is important for conducting meta-analyses. When performing imputation, genotype information from the study sample, in which only part of the genetic variants are known, is complemented using the standard (reference) sample, which has more complete genotype data (most often the results of whole-genome sequencing). Imputation has become an integral part of human genomic research due to the benefits it provides and the increasing availability of imputation tools and reference sample data. This review focuses on imputation in human genomic research. The first section of the review provides a description of technologies for obtaining information about human genotypes and characteristics of these types of data. The second section describes the imputation methodology, lists the stages of its implementation and the corresponding programs, provides a description of the most popular reference panels and methods for assessing the quality of imputation. The review concludes with examples of the use of imputation in genomic studies of samples from Russia. This review shows the importance of imputation, provides information on how to carry it out, and systematizes the results of its application using Russian samples.
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Affiliation(s)
- A A Berdnikova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - I V Zorkoltseva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Y A Tsepilov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E E Elgaeva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
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22
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Mihajlovic M, De Boever S, Tabernilla A, Callewaert E, Sanz-Serrano J, Verhoeven A, Maerten A, Rosseel Z, De Waele E, Vinken M. Investigation of parenteral nutrition-induced hepatotoxicity using human liver spheroid co-cultures. Arch Toxicol 2024; 98:3109-3126. [PMID: 38740588 PMCID: PMC11324701 DOI: 10.1007/s00204-024-03773-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Accepted: 04/24/2024] [Indexed: 05/16/2024]
Abstract
Parenteral nutrition (PN) is typically administered to individuals with gastrointestinal dysfunction, a contraindication for enteral feeding, and a need for nutritional therapy. When PN is the only energy source in patients, it is defined as total parenteral nutrition (TPN). TPN is a life-saving approach for different patient populations, both in infants and adults. However, despite numerous benefits, TPN can cause adverse effects, including metabolic disorders and liver injury. TPN-associated liver injury, known as intestinal failure-associated liver disease (IFALD), represents a significant problem affecting up to 90% of individuals receiving TPN. IFALD pathogenesis is complex, depending on the TPN components as well as on the patient's medical conditions. Despite numerous animal studies and clinical observations, the molecular mechanisms driving IFALD remain largely unknown. The present study was set up to elucidate the mechanisms underlying IFALD. For this purpose, human liver spheroid co-cultures were treated with a TPN mixture, followed by RNA sequencing analysis. Subsequently, following exposure to TPN and its single nutritional components, several key events of liver injury, including mitochondrial dysfunction, endoplasmic reticulum stress, oxidative stress, apoptosis, and lipid accumulation (steatosis), were studied using various techniques. It was found that prolonged exposure to TPN substantially changes the transcriptome profile of liver spheroids and affects multiple metabolic and signaling pathways contributing to liver injury. Moreover, TPN and its main components, especially lipid emulsion, induce changes in all key events measured and trigger steatosis.
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Affiliation(s)
- Milos Mihajlovic
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Sybren De Boever
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Andrés Tabernilla
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Ellen Callewaert
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Julen Sanz-Serrano
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Anouk Verhoeven
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Amy Maerten
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Zenzi Rosseel
- Department of Pharmacy, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- Department of Clinical Nutrition, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Elisabeth De Waele
- Department of Clinical Nutrition, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
- Faculty of Medicine and Pharmacy, Vrije Universiteit Brussel, Brussels, Belgium
| | - Mathieu Vinken
- Department of Pharmaceutical and Pharmacological Sciences, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium.
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23
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Yang J, Su Q, Song C, Luo H, Jiang H, Ni M, Meng F. A comprehensive adsorption and desorption study on the interaction of DNA oligonucleotides with TiO 2 nanolayers. Phys Chem Chem Phys 2024; 26:22681-22695. [PMID: 39158972 DOI: 10.1039/d4cp02260b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/21/2024]
Abstract
The utilization of TiO2 nanolayers that possess excellent biocompatibility and physical properties in DNA sensing and sequencing remains largely to be explored. To examine their applicability in gene sequencing, a comprehensive study on the interaction of DNA oligonucleotides with TiO2 nanolayers was performed through adsorption and desorption experiments. TiO2 nanolayers with 10 nm thickness were fabricated via magnetron sputtering onto a 6-inch silicon wafer. A simple chip block method, validated via quartz crystal microbalance experiments with dissipation monitoring (QCM-D), was proposed to study the adsorption behaviors and interaction mechanisms under a variety of critical influencing factors, including DNA concentration, length, and type, adsorption time, pH, and metal ions. It is determined that the adsorption takes 2 h to reach saturation in the MES solution and the adsorption capacity is significantly enhanced by lowering the pH due to the isoelectric point being pH = 6 for TiO2. The adsorption percentages of nucleobases are largely similar in the MES solution while following 5T = 5G > 5C > 5A in HEPES buffer for an adsorption duration of 2.5 h. Through pre-adsorption experiments, it is deduced that DNA oligonucleotides are horizontally adsorbed on the nanolayer. This further demonstrates that mono-, di-, and tri-valent metal ions promote the adsorption, whereas Zn2+ has strong adsorption by inducing DNA condensation. Based on the desorption experiments, it is revealed that electrostatic force dominates the adsorption over van der Waals force and hydrogen bonds. The phosphate group is the main functional group for adsorption, and the adsorption strength increases with the length of the oligonucleotide. This study provides comprehensive data on the adsorption of DNA oligonucleotides onto TiO2 nanolayers and clarifies the interaction mechanisms therein, which will be valuable for applications of TiO2 in DNA-related applications.
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Affiliation(s)
- Jin Yang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- MGI Tech, Shenzhen 518083, China.
| | - Qiong Su
- MGI Tech, Shenzhen 518083, China.
| | | | | | | | - Ming Ni
- MGI Tech, Shenzhen 518083, China.
| | - Fanchao Meng
- Institute for Advanced Studies in Precision Materials, Yantai University, Yantai, Shandong 264005, China.
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24
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Liu X, Pang Y, Shan J, Wang Y, Zheng Y, Xue Y, Zhou X, Wang W, Sun Y, Yan X, Shi J, Wang X, Gu H, Zhang F. Beyond the base pairs: comparative genome-wide DNA methylation profiling across sequencing technologies. Brief Bioinform 2024; 25:bbae440. [PMID: 39256199 PMCID: PMC11387064 DOI: 10.1093/bib/bbae440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 07/28/2024] [Accepted: 08/21/2024] [Indexed: 09/12/2024] Open
Abstract
Deoxyribonucleic acid (DNA) methylation plays a key role in gene regulation and is critical for development and human disease. Techniques such as whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS) allow DNA methylation analysis at the genome scale, with Illumina NovaSeq 6000 and MGI Tech DNBSEQ-T7 being popular due to their efficiency and affordability. However, detailed comparative studies of their performance are not available. In this study, we constructed 60 WGBS and RRBS libraries for two platforms using different types of clinical samples and generated approximately 2.8 terabases of sequencing data. We systematically compared quality control metrics, genomic coverage, CpG methylation levels, intra- and interplatform correlations, and performance in detecting differentially methylated positions. Our results revealed that the DNBSEQ platform exhibited better raw read quality, although base quality recalibration indicated potential overestimation of base quality. The DNBSEQ platform also showed lower sequencing depth and less coverage uniformity in GC-rich regions than did the NovaSeq platform and tended to enrich methylated regions. Overall, both platforms demonstrated robust intra- and interplatform reproducibility for RRBS and WGBS, with NovaSeq performing better for WGBS, highlighting the importance of considering these factors when selecting a platform for bisulfite sequencing.
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Affiliation(s)
- Xin Liu
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
| | - Yu Pang
- Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing 101149, China
| | - Junqi Shan
- Department of Gastrointestinal Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Yunfei Wang
- Hangzhou ShengTing Biotech Co. Ltd, Hangzhou, Zhejiang Province 310018, China
| | - Yanhua Zheng
- Department of Hematology, The First Hospital of China Medical University, Shenyang, Liaoning, Shenyang, Liaoning province 110001, China
| | - Yuhang Xue
- Department of Hematology, The First Hospital of China Medical University, Shenyang, Liaoning, Shenyang, Liaoning province 110001, China
| | - Xuerong Zhou
- Department of Hematology, The First Hospital of China Medical University, Shenyang, Liaoning, Shenyang, Liaoning province 110001, China
| | - Wenjun Wang
- Hangzhou ShengTing Biotech Co. Ltd, Hangzhou, Zhejiang Province 310018, China
| | - Yanlai Sun
- Department of Gastrointestinal Surgery, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong 250117, China
| | - Xiaojing Yan
- Department of Hematology, The First Hospital of China Medical University, Shenyang, Liaoning, Shenyang, Liaoning province 110001, China
| | - Jiantao Shi
- State Key Laboratory of Molecular Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaoxue Wang
- Department of Hematology, The First Hospital of China Medical University, Shenyang, Liaoning, Shenyang, Liaoning province 110001, China
| | - Hongcang Gu
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
| | - Fan Zhang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
- Hefei Cancer Hospital, Chinese Academy of Sciences, Hefei, Anhui Province 230031, China
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25
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Mallawaarachchi V, Wickramarachchi A, Xue H, Papudeshi B, Grigson SR, Bouras G, Prahl RE, Kaphle A, Verich A, Talamantes-Becerra B, Dinsdale EA, Edwards RA. Solving genomic puzzles: computational methods for metagenomic binning. Brief Bioinform 2024; 25:bbae372. [PMID: 39082646 PMCID: PMC11289683 DOI: 10.1093/bib/bbae372] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 06/05/2024] [Accepted: 07/15/2024] [Indexed: 08/03/2024] Open
Abstract
Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.
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Affiliation(s)
- Vijini Mallawaarachchi
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | - Anuradha Wickramarachchi
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
| | - Hansheng Xue
- School of Computing, National University of Singapore, Singapore 119077, Singapore
| | - Bhavya Papudeshi
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | - Susanna R Grigson
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | - George Bouras
- Adelaide Medical School, Faculty of Health and Medical Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
- The Department of Surgery—Otolaryngology Head and Neck Surgery, University of Adelaide and the Basil Hetzel Institute for Translational Health Research, Central Adelaide Local Health Network, Adelaide, SA 5011, Australia
| | - Rosa E Prahl
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
| | - Anubhav Kaphle
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
| | - Andrey Verich
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
- The Kirby Institute, The University of New South Wales, Randwick, Sydney, NSW 2052, Australia
| | - Berenice Talamantes-Becerra
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Westmead, NSW 2145, Australia
| | - Elizabeth A Dinsdale
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
| | - Robert A Edwards
- Flinders Accelerator for Microbiome Exploration, College of Science and Engineering, Flinders University, Adelaide, SA 5042, Australia
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26
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Mo J, Bae J, Saqib J, Hwang D, Jin Y, Park B, Park J, Kim J. Current computational methods for spatial transcriptomics in cancer biology. Adv Cancer Res 2024; 163:71-106. [PMID: 39271268 DOI: 10.1016/bs.acr.2024.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/15/2024]
Abstract
Cells in multicellular organisms constitute a self-organizing society by interacting with their neighbors. Cancer originates from malfunction of cellular behavior in the context of such a self-organizing system. The identities or characteristics of individual tumor cells can be represented by the hallmark of gene expression or transcriptome, which can be addressed using single-cell dissociation followed by RNA sequencing. However, the dissociation process of single cells results in losing the cellular address in tissue or neighbor information of each tumor cell, which is critical to understanding the malfunctioning cellular behavior in the microenvironment. Spatial transcriptomics technology enables measuring the transcriptome which is tagged by the address within a tissue. However, to understand cellular behavior in a self-organizing society, we need to apply mathematical or statistical methods. Here, we provide a review on current computational methods for spatial transcriptomics in cancer biology.
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Affiliation(s)
- Jaewoo Mo
- School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul, Republic of Korea
| | - Junseong Bae
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Yangsan, Republic of Korea; Graduate School of Medical AI, Pusan National University, Yangsan, Republic of Korea
| | - Jahanzeb Saqib
- School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul, Republic of Korea
| | - Dohyun Hwang
- Department of Information Convergence Engineering, Pusan National University, Yangsan, Republic of Korea
| | - Yunjung Jin
- School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul, Republic of Korea
| | - Beomsu Park
- School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul, Republic of Korea
| | - Jeongbin Park
- Interdisciplinary Program of Genomic Data Science, Pusan National University, Yangsan, Republic of Korea; Department of Information Convergence Engineering, Pusan National University, Yangsan, Republic of Korea; School of Biomedical Convergence Engineering, Pusan National University, Yangsan, Republic of Korea.
| | - Junil Kim
- School of Systems Biomedical Science, Soongsil University, Dongjak-Gu, Seoul, Republic of Korea.
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27
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Garg S, Nain P, Kumar A, Joshi S, Punetha H, Sharma PK, Siddiqui S, Alshaharni MO, Algopishi UB, Mittal A. Next generation plant biostimulants & genome sequencing strategies for sustainable agriculture development. Front Microbiol 2024; 15:1439561. [PMID: 39104588 PMCID: PMC11299335 DOI: 10.3389/fmicb.2024.1439561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 06/25/2024] [Indexed: 08/07/2024] Open
Abstract
The best environment for plant growth and development contains certain essential metabolites. A broad category of metabolites known as "plant biostimulants" (PBs) includes biomolecules such as proteins, carbohydrates, lipids, and other secondary metabolites related to groups of terpenes, specific nitrogen-containing compounds, and benzene ring-conjugated compounds. The formation of biomolecules depends on both biotic and abiotic factors, such as the release of PB by plants, animals, and microorganisms, or it can result from the control of temperature, humidity, and pressure in the atmosphere, in the case of humic substances (HSs). Understanding the genomic outputs of the concerned organism (may be plants or others than them) becomes crucial for identifying the underlying behaviors that lead to the synthesis of these complex compounds. For the purposes of achieving the objectives of sustainable agriculture, detailed research on PBs is essential because they aid in increasing yield and other growth patterns of agro-economic crops. The regulation of homeostasis in the plant-soil-microbe system for the survival of humans and other animals is mediated by the action of plant biostimulants, as considered essential for the growth of plants. The genomic size and gene operons for functional and regulation control have so far been revealed through technological implementations, but important gene annotations are still lacking, causing a delay in revealing the information. Next-generation sequencing techniques, such as nanopore, nanoball, and Illumina, are essential in troubleshooting the information gaps. These technical advancements have greatly expanded the candidate gene openings. The secondary metabolites being important precursors need to be studied in a much wider scale for accurate calculations of biochemical reactions, taking place inside and outside the synthesized living cell. The present review highlights the sequencing techniques to provide a foundation of opportunity generation for agricultural sustainability.
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Affiliation(s)
- Shivanshu Garg
- Department of Biochemistry, CBSH-GBPUA&T, Pantnagar, India
| | - Pooja Nain
- Department of Soil Science, College of Agriculture, GBPUA&T, Pantnagar, India
| | - Ashish Kumar
- Department of Microbiology, CBSH-GBPUA&T, Pantnagar, India
| | - Samiksha Joshi
- School of Agriculture, Graphic Era Hill University, Bhimtal, India
| | | | - Pradeep Kumar Sharma
- Department of Environment Science, Graphic Era Deemed to be University, Dehradun, India
| | - Sazada Siddiqui
- Department of Biology, College of Science, King Khalid University, Abha, Saudi Arabia
| | | | | | - Amit Mittal
- School of Allied Sciences, Graphic Era Hill University, Bhimtal, India
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28
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He Y, Yang T, Zhong G, Yu X, Zhao Z, Shi Y, Huang B. Performance evaluation of a newly developed 2019-nCoV nucleic acid detection kit based on Ion Proton sequencing platform and its comparison with the MGI Tech (DNBSEQ-G99) platform. Diagn Microbiol Infect Dis 2024; 109:116323. [PMID: 38703530 DOI: 10.1016/j.diagmicrobio.2024.116323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2024] [Revised: 04/10/2024] [Accepted: 04/22/2024] [Indexed: 05/06/2024]
Abstract
PURPOSE To evaluate the performance of a newly developed 2019-nCoV nucleic acid detection kit based on Ion Proton sequencing platform and make comparation with MGI Tech (DNBSEQ-G99) platform. METHODS References and clinical samples were used to evaluate the precision, agreement rate, limit of detection (LOD), anti-interference ability and analytical specificity. Twenty-seven clinical specimens were used to make comparison between two platforms. RESULTS The kit showed good intra-assay, inter-assay, inter-day precision between different operators and laboratories, fine agreement rate with references, a relatively low LOD of 1 × 103 copies/ml, anti-interference capability of 5 % whole blood and 1mg/ml mucin and no cross reaction with twenty-nine common clinical pathogens. Consistency of variant classification was observed between two platforms. The WGS from Ion Proton tended to have higher coverage and less missing data. CONCLUSIONS The newly developed kit has shown satisfactory performances and excellent consistency with DNBSEQ-G99, making it a good alternative choice clinically.
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Affiliation(s)
- Yuting He
- Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Tingting Yang
- Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Guosheng Zhong
- Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Xuegao Yu
- Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Zhiwei Zhao
- Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China
| | - Yaling Shi
- Department of Clinical Laboratory, Guangzhou Eighth People's Hospital, Guangzhou Medical University
| | - Bin Huang
- Department of Clinical Laboratory, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, PR China.
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29
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Chaudhari JK, Pant S, Jha R, Pathak RK, Singh DB. Biological big-data sources, problems of storage, computational issues, and applications: a comprehensive review. Knowl Inf Syst 2024; 66:3159-3209. [DOI: 10.1007/s10115-023-02049-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 09/12/2023] [Accepted: 12/11/2023] [Indexed: 01/03/2025]
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30
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Xu Y, Lou J, Qian Y, Jin P, Qian Y, Hong J, Xu Y, Yin Y, Yi S, Dong M. Performance of noninvasive prenatal screening for fetal sex chromosome aneuploidies in a cohort of 116,862 pregnancies. Expert Rev Mol Diagn 2024; 24:467-472. [PMID: 38526221 DOI: 10.1080/14737159.2024.2333951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/20/2024] [Indexed: 03/26/2024]
Abstract
BACKGROUND Noninvasive prenatal screening (NIPS) has shown good performance in screening common aneuploidies. However, its performance in detecting fetal sex chromosome aneuploidies (SCAs) needs to be evaluated in a large cohort. RESEARCH DESIGN AND METHODS In this retrospective observation, a total of 116,862 women underwent NIPS based on DNA nanoball sequencing from 2015 to 2022. SCAs were diagnosed based on karyotyping or chromosomal microarray analysis (CMA). Among them, 2,084 singleton pregnancies received karyotyping and/or CMA. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of NIPS for fetal SCAs were evaluated. RESULTS The sensitivity was 97.7% (95%CI, 87.7-99.9), 87.3% (95% CI, 76.5-94.4), 96.1% (95%CI, 86.5-99.5), and 95.7% (95% CI, 78.1-99.9), the PPV was 25.8% (95%CI, 19.2-33.2), 80.9% (95%CI, 69.5-89.4), 79.0% (95%CI, 66.8-88.3), and 53.7% (95%CI, 37.4-69.3) for 45,X, 47,XXY, 47,XXX, and 47,XYY, respectively. The specificity was 94.1% (95%CI, 93.0-95.1) for 45,X, and more than 99.0% for sex chromosome trisomy (SCT). The NPV was over 99.0% for all. CONCLUSIONS NIPS screening for fetal SCAs has high sensitivity, specificity and NPV. The PPV of SCAs was moderate, but that of 45,X was lower than that of SCTs. Invasive prenatal diagnosis should be recommended for high-risk patients.
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Affiliation(s)
- Yanfei Xu
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jianbo Lou
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Department of Obstetrics and Gynecology, Shaoxing Maternal and Child Health Care Hospital, Shaoxing, China
| | - Yeqing Qian
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Reproductive Genetics, Ministry of Education (Zhejiang University), Hangzhou, China
| | - Pengzhen Jin
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yangwen Qian
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiawei Hong
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yuqing Xu
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yixuan Yin
- Hangzhou Women's Hospital, Prenatal Diagnosis Center, Hangzhou, China
| | - Songjia Yi
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Minyue Dong
- Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Key Laboratory of Reproductive Genetics, Ministry of Education (Zhejiang University), Hangzhou, China
- Department of Reproductive Medicine, Key Laboratory of Women's Reproductive Health of Zhejiang Province, Hangzhou, China
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31
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Aydin A, Klenk C, Nemec K, Işbilir A, Martin LM, Zauber H, Rrustemi T, Toka HR, Schuster H, Gong M, Stricker S, Bock A, Bähring S, Selbach M, Lohse MJ, Luft FC. ADAM19 cleaves the PTH receptor and associates with brachydactyly type E. Life Sci Alliance 2024; 7:e202302400. [PMID: 38331475 PMCID: PMC10853454 DOI: 10.26508/lsa.202302400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/25/2024] [Accepted: 01/25/2024] [Indexed: 02/10/2024] Open
Abstract
Brachydactyly type E (BDE), shortened metacarpals, metatarsals, cone-shaped epiphyses, and short stature commonly occurs as a sole phenotype. Parathyroid hormone-like protein (PTHrP) has been shown to be responsible in all forms to date, either directly or indirectly. We used linkage and then whole genome sequencing in a small pedigree, to elucidate BDE and identified a truncated disintegrin-and-metalloproteinase-19 (ADAM19) allele in all affected family members, but not in nonaffected persons. Since we had shown earlier that the extracellular domain of the parathyroid hormone receptor (PTHR1) is subject to an unidentified metalloproteinase cleavage, we tested the hypothesis that ADAM19 is a sheddase for PTHR1. WT ADAM19 cleaved PTHR1, while mutated ADAM-19 did not. We mapped the cleavage site that we verified with mass spectrometry between amino acids 64-65. ADAM-19 cleavage increased Gq and decreased Gs activation. Moreover, perturbed PTHR1 cleavage by ADAM19 increased ß-arrestin2 recruitment, while cAMP accumulation was not altered. We suggest that ADAM19 serves as a regulatory element for PTHR1 and could be responsible for BDE. This sheddase may affect other PTHrP or PTH-related functions.
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Affiliation(s)
- Atakan Aydin
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
| | - Christoph Klenk
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
| | - Katarina Nemec
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
- Department of Structural Biology and Center of Excellence for Data-Driven Discovery, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Ali Işbilir
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Institute of Pharmacology and Toxicology, University of Würzburg, Würzburg, Germany
| | - Lisa M Martin
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Henrik Zauber
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Trendelina Rrustemi
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Hakan R Toka
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
| | - Herbert Schuster
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
| | - Maolian Gong
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
| | - Sigmar Stricker
- Institute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany
| | - Andreas Bock
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Rudolf-Boehm-Institute of Pharmacology and Toxicology, Medical Faculty, University of Leipzig, Leipzig, Germany
| | - Sylvia Bähring
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
| | - Matthias Selbach
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
| | - Martin J Lohse
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- ISAR Bioscience Institute, Munich, Germany
| | - Friedrich C Luft
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany
- Experimental and Clinical Research Center, A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin, Berlin, Germany
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32
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Al-Sarraj Y, Taha RZ, Al-Dous E, Ahram D, Abbasi S, Abuazab E, Shaath H, Habbab W, Errafii K, Bejaoui Y, AlMotawa M, Khattab N, Aqel YA, Shalaby KE, Al-Ansari A, Kambouris M, Abouzohri A, Ghazal I, Tolfat M, Alshaban F, El-Shanti H, Albagha OME. The genetic landscape of autism spectrum disorder in the Middle Eastern population. Front Genet 2024; 15:1363849. [PMID: 38572415 PMCID: PMC10987745 DOI: 10.3389/fgene.2024.1363849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 03/04/2024] [Indexed: 04/05/2024] Open
Abstract
Introduction: Autism spectrum disorder (ASD) is characterized by aberrations in social interaction and communication associated with repetitive behaviors and interests, with strong clinical heterogeneity. Genetic factors play an important role in ASD, but about 75% of ASD cases have an undetermined genetic risk. Methods: We extensively investigated an ASD cohort made of 102 families from the Middle Eastern population of Qatar. First, we investigated the copy number variations (CNV) contribution using genome-wide SNP arrays. Next, we employed Next Generation Sequencing (NGS) to identify de novo or inherited variants contributing to the ASD etiology and its associated comorbid conditions in families with complete trios (affected child and the parents). Results: Our analysis revealed 16 CNV regions located in genomic regions implicated in ASD. The analysis of the 88 ASD cases identified 41 genes in 39 ASD subjects with de novo (n = 24) or inherited variants (n = 22). We identified three novel de novo variants in new candidate genes for ASD (DTX4, ARMC6, and B3GNT3). Also, we have identified 15 de novo variants in genes that were previously implicated in ASD or related neurodevelopmental disorders (PHF21A, WASF1, TCF20, DEAF1, MED13, CREBBP, KDM6B, SMURF1, ADNP, CACNA1G, MYT1L, KIF13B, GRIA2, CHM, and KCNK9). Additionally, we defined eight novel recessive variants (RYR2, DNAH3, TSPYL2, UPF3B KDM5C, LYST, and WNK3), four of which were X-linked. Conclusion: Despite the ASD multifactorial etiology that hinders ASD genetic risk discovery, the number of identified novel or known putative ASD genetic variants was appreciable. Nevertheless, this study represents the first comprehensive characterization of ASD genetic risk in Qatar's Middle Eastern population.
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Affiliation(s)
- Yasser Al-Sarraj
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Rowaida Z. Taha
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Eman Al-Dous
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Dina Ahram
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Somayyeh Abbasi
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Eman Abuazab
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Hibah Shaath
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Wesal Habbab
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Khaoula Errafii
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Yosra Bejaoui
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Maryam AlMotawa
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Namat Khattab
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Yasmin Abu Aqel
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Karim E. Shalaby
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Amina Al-Ansari
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Marios Kambouris
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
- Pathology & Laboratory Medicine Department, Genetics Division, Sidra Medicine, Doha, Qatar
| | - Adel Abouzohri
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Iman Ghazal
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Mohammed Tolfat
- The Shafallah Center for Children with Special Needs, Doha, Qatar
| | - Fouad Alshaban
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Hatem El-Shanti
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
- Department of Pediatrics, Carver College of Medicine, University of Iowa, Iowa City, IA, United States
| | - Omar M. E. Albagha
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
- Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University, Doha, Qatar
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Sinigaglia B, Escudero J, Biagini SA, Garcia-Calleja J, Moreno J, Dobon B, Acosta S, Mondal M, Walsh S, Aguileta G, Vallès M, Forrow S, Martin-Caballero J, Migliano AB, Bertranpetit J, Muñoz FJ, Bosch E. Exploring Adaptive Phenotypes for the Human Calcium-Sensing Receptor Polymorphism R990G. Mol Biol Evol 2024; 41:msae015. [PMID: 38285634 PMCID: PMC10859840 DOI: 10.1093/molbev/msae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 01/23/2024] [Accepted: 01/23/2024] [Indexed: 01/31/2024] Open
Abstract
Rainforest hunter-gatherers from Southeast Asia are characterized by specific morphological features including a particularly dark skin color (D), short stature (S), woolly hair (W), and the presence of steatopygia (S)-fat accumulation localized in the hips (DSWS phenotype). Based on previous evidence in the Andamanese population, we first characterized signatures of adaptive natural selection around the calcium-sensing receptor gene in Southeast Asian rainforest groups presenting the DSWS phenotype and identified the R990G substitution (rs1042636) as a putative adaptive variant for experimental follow-up. Although the calcium-sensing receptor has a critical role in calcium homeostasis by directly regulating the parathyroid hormone secretion, it is expressed in different tissues and has been described to be involved in many biological functions. Previous works have also characterized the R990G substitution as an activating polymorphism of the calcium-sensing receptor associated with hypocalcemia. Therefore, we generated a knock-in mouse for this substitution and investigated organismal phenotypes that could have become adaptive in rainforest hunter-gatherers from Southeast Asia. Interestingly, we found that mouse homozygous for the derived allele show not only lower serum calcium concentration but also greater body weight and fat accumulation, probably because of enhanced preadipocyte differentiation and lipolysis impairment resulting from the calcium-sensing receptor activation mediated by R990G. We speculate that such differential features in humans could have facilitated the survival of hunter-gatherer groups during periods of nutritional stress in the challenging conditions of the Southeast Asian tropical rainforests.
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Affiliation(s)
- Barbara Sinigaglia
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Jorge Escudero
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Simone A Biagini
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Jorge Garcia-Calleja
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Josep Moreno
- PCB-PRBB Animal Facility Alliance, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Begoña Dobon
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Sandra Acosta
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
- UB Institute of Neuroscience, Department of Pathology and Experimental Therapeutics, Universitat de Barcelona, Barcelona 08007, Spain
| | - Mayukh Mondal
- Institute of Genomics, University of Tartu, Tartu 51010, Estonia
- Institute of Clinical Molecular Biology, Christian-Albrechts-Universität zu Kiel, Kiel 24118, Germany
| | - Sandra Walsh
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Gabriela Aguileta
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Mònica Vallès
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Stephen Forrow
- Mouse Mutant Core Facility, Institute for Research in Biomedicine (IRB), Barcelona 08028, Spain
| | - Juan Martin-Caballero
- PCB-PRBB Animal Facility Alliance, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Andrea Bamberg Migliano
- Human Evolutionary Ecology Group, Department of Evolutionary Anthropology, University of Zurich, Zurich 8057, Switzerland
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Francisco J Muñoz
- Laboratory of Molecular Physiology, Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, Barcelona 08003, Spain
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Hu T, Chen J, Lin X, He W, Liang H, Wang M, Li W, Wu Z, Han M, Jin X, Kristiansen K, Xiao L, Zou Y. Comparison of the DNBSEQ platform and Illumina HiSeq 2000 for bacterial genome assembly. Sci Rep 2024; 14:1292. [PMID: 38221534 PMCID: PMC10788345 DOI: 10.1038/s41598-024-51725-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 01/09/2024] [Indexed: 01/16/2024] Open
Abstract
The Illumina HiSeq platform has been a commonly used option for bacterial genome sequencing. Now the BGI DNA nanoball (DNB) nanoarrays platform may provide an alternative platform for sequencing of bacterial genomes. To explore the impact of sequencing platforms on bacterial genome assembly, quality assessment, sequence alignment, functional annotation, mutation detection, and metagenome mapping, we compared genome assemblies based on sequencing of cultured bacterial species using the HiSeq 2000 and BGISEQ-500 platforms. In addition, simulated reads were used to evaluate the impact of insert size on genome assembly. Genome assemblies based on BGISEQ-500 sequencing exhibited higher completeness and fewer N bases in high GC genomes, whereas HiSeq 2000 assemblies exhibited higher N50. The majority of assembly assessment parameters, sequences of 16S rRNA genes and genomes, numbers of single nucleotide variants (SNV), and mapping to metagenome data did not differ significantly between platforms. More insertions were detected in HiSeq 2000 genome assemblies, whereas more deletions were detected in BGISEQ-500 genome assemblies. Insert size had no significant impact on genome assembly. Taken together, our results suggest that DNBSEQ platforms would be a valid substitute for HiSeq 2000 for bacterial genome sequencing.
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Affiliation(s)
- Tongyuan Hu
- BGI Research, Shenzhen, 518083, China
- BGI Research, Wuhan, 430074, China
| | | | - Xiaoqian Lin
- BGI Research, Shenzhen, 518083, China
- School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 510006, China
| | - Wenxin He
- BGI Research, Shenzhen, 518083, China
| | - Hewei Liang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Wuhan, 430074, China
| | | | - Wenxi Li
- BGI Research, Shenzhen, 518083, China
- School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 510006, China
| | - Zhinan Wu
- BGI Research, Shenzhen, 518083, China
| | - Mo Han
- BGI Research, Shenzhen, 518083, China
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Universitetsparken 13, 2100, Copenhagen, Denmark
| | - Xin Jin
- BGI Research, Shenzhen, 518083, China
| | - Karsten Kristiansen
- BGI Research, Shenzhen, 518083, China
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Universitetsparken 13, 2100, Copenhagen, Denmark
| | - Liang Xiao
- BGI Research, Shenzhen, 518083, China
- Shenzhen Engineering Laboratory of Detection and Intervention of Human Intestinal Microbiome, BGI Research, Shenzhen, 518083, China
| | - Yuanqiang Zou
- BGI Research, Shenzhen, 518083, China.
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Universitetsparken 13, 2100, Copenhagen, Denmark.
- Shenzhen Engineering Laboratory of Detection and Intervention of Human Intestinal Microbiome, BGI Research, Shenzhen, 518083, China.
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Feng Z, Peng F, Xie F, Liu Y, Zhang H, Ma J, Xing J, Guo X. Comparison of capture-based mtDNA sequencing performance between MGI and illumina sequencing platforms in various sample types. BMC Genomics 2024; 25:41. [PMID: 38191319 PMCID: PMC10773069 DOI: 10.1186/s12864-023-09938-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 12/24/2023] [Indexed: 01/10/2024] Open
Abstract
BACKGROUND Mitochondrial genome abnormalities can lead to mitochondrial dysfunction, which in turn affects cellular biology and is closely associated with the development of various diseases. The demand for mitochondrial DNA (mtDNA) sequencing has been increasing, and Illumina and MGI are two commonly used sequencing platforms for capture-based mtDNA sequencing. However, there is currently no systematic comparison of mtDNA sequencing performance between these two platforms. To address this gap, we compared the performance of capture-based mtDNA sequencing between Illumina's NovaSeq 6000 and MGI's DNBSEQ-T7 using tissue, peripheral blood mononuclear cell (PBMC), formalin-fixed paraffin-embedded (FFPE) tissue, plasma, and urine samples. RESULTS Our analysis indicated a high degree of consistency between the two platforms in terms of sequencing quality, GC content, and coverage. In terms of data output, DNBSEQ-T7 showed higher rates of clean data and duplication compared to NovaSeq 6000. Conversely, the amount of mtDNA data obtained by per gigabyte sequencing data was significantly lower in DNBSEQ-T7 compared to NovaSeq 6000. In terms of detection mtDNA copy number, both platforms exhibited good consistency in all sample types. When it comes to detection of mtDNA mutations in tissue, FFPE, and PBMC samples, the two platforms also showed good consistency. However, when detecting mtDNA mutations in plasma and urine samples, significant differenceof themutation number detected was observed between the two platforms. For mtDNA sequencing of plasma and urine samples, a wider range of DNA fragment size distribution was found in NovaSeq 6000 when compared to DNBSEQ-T7. Additionally, two platforms exhibited different characteristics of mtDNA fragment end preference. CONCLUSIONS In summary, the two platforms generally showed good consistency in capture-based mtDNA sequencing. However, it is necessary to consider the data preferences generated by two sequencing platforms when plasma and urine samples were analyzed.
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Affiliation(s)
- Zehui Feng
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China
| | - Fan Peng
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China
| | - Fanfan Xie
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China
- Department of Obstetrics and Gynecology, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, China
| | - Yang Liu
- Department of Clinical Diagnosis, Tangdu Hospital, Fourth Military Medical University, Xi'an, 710038, China
| | - Huanqin Zhang
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China
| | - Jing Ma
- Yanbian University Medical College, Yanji, 133002, China
| | - Jinliang Xing
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China.
| | - Xu Guo
- State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers and, Department of Physiology and Pathophysiology, Fourth Military Medical University, Xi'an, 710032, China.
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Shaukat A, Bakhtiari MH, Chaudhry DS, Khan MHF, Akhtar J, Abro AH, Haseeb MA, Sarwar A, Mazhar K, Umer Z, Tariq M. Mask exhibits trxG-like behavior and associates with H3K27ac marked chromatin. Dev Biol 2024; 505:130-140. [PMID: 37981061 DOI: 10.1016/j.ydbio.2023.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 10/28/2023] [Accepted: 11/13/2023] [Indexed: 11/21/2023]
Abstract
The Trithorax group (trxG) proteins counteract the repressive effect of Polycomb group (PcG) complexes and maintain transcriptional memory of active states of key developmental genes. Although chromatin structure and modifications appear to play a fundamental role in this process, it is not clear how trxG prevents PcG-silencing and heritably maintains an active gene expression state. Here, we report a hitherto unknown role of Drosophila Multiple ankyrin repeats single KH domain (Mask), which emerged as one of the candidate trxG genes in our reverse genetic screen. The genome-wide binding profile of Mask correlates with known trxG binding sites across the Drosophila genome. In particular, the association of Mask at chromatin overlaps with CBP and H3K27ac, which are known hallmarks of actively transcribed genes by trxG. Importantly, Mask predominantly associates with actively transcribed genes in Drosophila. Depletion of Mask not only results in the downregulation of trxG targets but also correlates with diminished levels of H3K27ac. The fact that Mask positively regulates H3K27ac levels in flies was also found to be conserved in human cells. Strong suppression of Pc mutant phenotype by mutation in mask provides physiological relevance that Mask contributes to the anti-silencing effect of trxG, maintaining expression of key developmental genes. Since Mask is a downstream effector of multiple cell signaling pathways, we propose that Mask may connect cell signaling with chromatin mediated epigenetic cell memory governed by trxG.
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Affiliation(s)
- Ammad Shaukat
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Mahnoor Hussain Bakhtiari
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Daim Shiraz Chaudhry
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Muhammad Haider Farooq Khan
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Jawad Akhtar
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Ahmed Hassan Abro
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Muhammad Abdul Haseeb
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Aaminah Sarwar
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Khalida Mazhar
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Zain Umer
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan
| | - Muhammad Tariq
- Epigenetics and Gene Regulation Laboratory, Department of Life Sciences, Syed Babar Ali School of Science and Engineering, Lahore University of Management Sciences, Lahore, 54792, Pakistan.
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Arslan S, Garcia FJ, Guo M, Kellinger MW, Kruglyak S, LeVieux JA, Mah AH, Wang H, Zhao J, Zhou C, Altomare A, Bailey J, Byrne MB, Chang C, Chen SX, Cho B, Dennler CN, Dien VT, Fuller D, Kelley R, Khandan O, Klein MG, Kim M, Lajoie BR, Lin B, Liu Y, Lopez T, Mains PT, Price AD, Robertson SR, Taylor-Weiner H, Tippana R, Tomaney AB, Zhang S, Abtahi M, Ambroso MR, Bajari R, Bellizzi AM, Benitez CB, Berard DR, Berti L, Blease KN, Blum AP, Boddicker AM, Bondar L, Brown C, Bui CA, Calleja-Aguirre J, Cappa K, Chan J, Chang VW, Charov K, Chen X, Constandse RM, Damron W, Dawood M, DeBuono N, Dimalanta JD, Edoli L, Elango K, Faustino N, Feng C, Ferrari M, Frankie K, Fries A, Galloway A, Gavrila V, Gemmen GJ, Ghadiali J, Ghorbani A, Goddard LA, Guetter AR, Hendricks GL, Hentschel J, Honigfort DJ, Hsieh YT, Hwang Fu YH, Im SK, Jin C, Kabu S, Kincade DE, Levy S, Li Y, Liang VK, Light WH, Lipsher JB, Liu TL, Long G, Ma R, Mailloux JM, Mandla KA, Martinez AR, Mass M, McKean DT, Meron M, Miller EA, Moh CS, Moore RK, Moreno J, Neysmith JM, et alArslan S, Garcia FJ, Guo M, Kellinger MW, Kruglyak S, LeVieux JA, Mah AH, Wang H, Zhao J, Zhou C, Altomare A, Bailey J, Byrne MB, Chang C, Chen SX, Cho B, Dennler CN, Dien VT, Fuller D, Kelley R, Khandan O, Klein MG, Kim M, Lajoie BR, Lin B, Liu Y, Lopez T, Mains PT, Price AD, Robertson SR, Taylor-Weiner H, Tippana R, Tomaney AB, Zhang S, Abtahi M, Ambroso MR, Bajari R, Bellizzi AM, Benitez CB, Berard DR, Berti L, Blease KN, Blum AP, Boddicker AM, Bondar L, Brown C, Bui CA, Calleja-Aguirre J, Cappa K, Chan J, Chang VW, Charov K, Chen X, Constandse RM, Damron W, Dawood M, DeBuono N, Dimalanta JD, Edoli L, Elango K, Faustino N, Feng C, Ferrari M, Frankie K, Fries A, Galloway A, Gavrila V, Gemmen GJ, Ghadiali J, Ghorbani A, Goddard LA, Guetter AR, Hendricks GL, Hentschel J, Honigfort DJ, Hsieh YT, Hwang Fu YH, Im SK, Jin C, Kabu S, Kincade DE, Levy S, Li Y, Liang VK, Light WH, Lipsher JB, Liu TL, Long G, Ma R, Mailloux JM, Mandla KA, Martinez AR, Mass M, McKean DT, Meron M, Miller EA, Moh CS, Moore RK, Moreno J, Neysmith JM, Niman CS, Nunez JM, Ojeda MT, Ortiz SE, Owens J, Piland G, Proctor DJ, Purba JB, Ray M, Rong D, Saade VM, Saha S, Tomas GS, Scheidler N, Sirajudeen LH, Snow S, Stengel G, Stinson R, Stone MJ, Sundseth KJ, Thai E, Thompson CJ, Tjioe M, Trejo CL, Trieger G, Truong DN, Tse B, Voiles B, Vuong H, Wong JC, Wu CT, Yu H, Yu Y, Yu M, Zhang X, Zhao D, Zheng G, He M, Previte M. Sequencing by avidity enables high accuracy with low reagent consumption. Nat Biotechnol 2024; 42:132-138. [PMID: 37231263 DOI: 10.1038/s41587-023-01750-7] [Show More Authors] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 03/15/2023] [Indexed: 05/27/2023]
Abstract
We present avidity sequencing, a sequencing chemistry that separately optimizes the processes of stepping along a DNA template and that of identifying each nucleotide within the template. Nucleotide identification uses multivalent nucleotide ligands on dye-labeled cores to form polymerase-polymer-nucleotide complexes bound to clonal copies of DNA targets. These polymer-nucleotide substrates, termed avidites, decrease the required concentration of reporting nucleotides from micromolar to nanomolar and yield negligible dissociation rates. Avidity sequencing achieves high accuracy, with 96.2% and 85.4% of base calls having an average of one error per 1,000 and 10,000 base pairs, respectively. We show that the average error rate of avidity sequencing remained stable following a long homopolymer.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Bill Lin
- Element Biosciences, San Diego, CA, USA
| | - Yu Liu
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | | | | | - Su Zhang
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Xiyi Chen
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | - Chao Feng
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Yu Li
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | - Rui Ma
- Element Biosciences, San Diego, CA, USA
| | | | | | | | - Max Mass
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Ben Tse
- Element Biosciences, San Diego, CA, USA
| | | | | | | | | | - Hua Yu
- Element Biosciences, San Diego, CA, USA
| | | | - Ming Yu
- Element Biosciences, San Diego, CA, USA
| | - Xi Zhang
- Element Biosciences, San Diego, CA, USA
| | - Da Zhao
- Element Biosciences, San Diego, CA, USA
| | | | - Molly He
- Element Biosciences, San Diego, CA, USA
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Wang Z, Tang X, Yang S, Zhao Y, Yin T, Chen M, Zhang Y, Wang Y, Zhang F, Wang L. Noninvasive prenatal screening with conventional sequencing depth to screen fetal copy number variants: A retrospective study of 19 144 pregnant women. J Obstet Gynaecol Res 2023; 49:2825-2835. [PMID: 37806662 DOI: 10.1111/jog.15805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 09/20/2023] [Indexed: 10/10/2023]
Abstract
AIM To investigate the detectability of noninvasive prenatal screening (NIPS) with conventional sequencing depth to detect fetal copy number variants. METHODS We performed a retrospective study in a total of 19 144 pregnant women. Their cell-free plasma DNA were assessed for trisomy 21, trisomy 18, trisomy 13, sex chromosome aneuploidies, and genome-wide copy number variants by NIPS at conventional sequencing depth. RESULTS Three hundred seventy-four cases (2.0%, 374/19 144) with abnormal results were detected, which including 84 cases (0.4%, 84/19 144) with high risk of trisomy 21, 18, and 13, 90 cases (0.5%, 90/19 144) with high risk of sex chromosome abnormalities (SCA), and 44 cases (0.2%, 44/19 144) with high risk of other chromosome aneuploidies. One hundred fifty-six cases (0.8%, 156/19 144) with high risk of copy number variations (CNVs) were also detected. In following prenatal diagnosis, composite positive predictive value (PPV) of trisomy 21, 18, and 13 was 69.6% (48/69). The PPV of SCAs was 37.3% (19/51). And the PPVs for CNVs was detected as 51.0% (<5 Mb), 71.4% (5 Mb ≤ CNV ≤10 Mb), 56.5% (>10 Mb). Finally, a follow-up about the pregnancy outcomes were conducted for all available cases. CONCLUSIONS NIPS yielded high PPVs for trisomy 21, 18, and 13 aneuploidies and moderate PPVs for SCAs and CNVs. The screening effectiveness was closely related to the size of CNV fragments. Larger CNVs, especially larger than 5 Mb, could be detected more accurately by NIPS in our analytic technique. Meanwhile, diagnostic confirmation by microarray analysis was highly recommended.
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Affiliation(s)
- Zhiwei Wang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Xinxin Tang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Shuting Yang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Yali Zhao
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Ting Yin
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Min Chen
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Yue Zhang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Yongan Wang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Fang Zhang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
| | - Leilei Wang
- Center of Prenatal Diagnosis, Lianyungang Maternal and Child Health Hospital, Lianyungang, Jiangsu, China
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Fu T, Wang C, Yang Y, Yang X, Wang J, Zhang L, Wang Z, Wang Y. Function identification of miR159a, a positive regulator during poplar resistance to drought stress. HORTICULTURE RESEARCH 2023; 10:uhad221. [PMID: 38077498 PMCID: PMC10709547 DOI: 10.1093/hr/uhad221] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/24/2023] [Indexed: 03/08/2024]
Abstract
Drought seriously affects the growth and development of plants. MiR159 is a highly conserved and abundant microRNA family that plays a crucial role in plant growth and stress responses. However, studies of its function in woody plants are still lacking. Here, the expression of miR159a was significantly upregulated after drought treatment in poplar, and the overexpression of miR159a (OX159a) significantly reduced the open area of the stomata and improved water-use efficiency in poplar. After drought treatment, OX159a lines had better scavenging ability of reactive oxygen species and damage of the membrane system was less than that in wild-type lines. MYB was the target gene of miR159a, as verified by psRNATarget prediction, RT-qPCR, degradome sequencing, and 5' rapid amplification of cDNA ends (5' RACE). Additionally, miR159a-short tandem target mimic suppression (STTM) poplar lines showed increased sensitivity to drought stress. Transcriptomic analysis comparing OX159a lines with wild-type lines revealed upregulation of a series of genes related to response to water deprivation and metabolite synthesis. Moreover, drought-responsive miR172d and miR398 were significantly upregulated and downregulated respectively in OX159a lines. This investigation demonstrated that miR159a played a key role in the tolerance of poplar to drought by reducing stomata open area, increasing the number and total area of xylem vessels, and enhancing water-use efficiency, and provided new insights into the role of plant miR159a and crucial candidate genes for the molecular breeding of trees with tolerance to drought stress.
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Affiliation(s)
- Tiantian Fu
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Chun Wang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Yuzhang Yang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Xiaoqian Yang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Jing Wang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Lichun Zhang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Zeqi Wang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
| | - Yanwei Wang
- State Key Laboratory of Tree Genetics and Breeding, National Engineering Research Center of Tree Breeding and Ecological Restoration, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants, Ministry of Education, The Tree and Ornamental Plant Breeding and Biotechnology Laboratory of National Forestry and Grassland Administration, College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing 100083, China
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Gayathiri E, Prakash P, Kumaravel P, Jayaprakash J, Ragunathan MG, Sankar S, Pandiaraj S, Thirumalaivasan N, Thiruvengadam M, Govindasamy R. Computational approaches for modeling and structural design of biological systems: A comprehensive review. PROGRESS IN BIOPHYSICS AND MOLECULAR BIOLOGY 2023; 185:17-32. [PMID: 37821048 DOI: 10.1016/j.pbiomolbio.2023.08.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 08/14/2023] [Accepted: 08/27/2023] [Indexed: 10/13/2023]
Abstract
The convergence of biology and computational science has ushered in a revolutionary era, revolutionizing our understanding of biological systems and providing novel solutions to global problems. The field of genetic engineering has facilitated the manipulation of genetic codes, thus providing opportunities for the advancement of innovative disease therapies and environmental enhancements. The emergence of bio-molecular simulation represents a significant advancement in this particular field, as it offers the ability to gain microscopic insights into molecular-level biological processes over extended periods. Biomolecular simulation plays a crucial role in advancing our comprehension of organismal mechanisms by establishing connections between molecular structures, interactions, and biological functions. The field of computational biology has demonstrated its significance in deciphering intricate biological enigmas through the utilization of mathematical models and algorithms. The process of decoding the human genome has resulted in the advancement of therapies for a wide range of genetic disorders, while the simulation of biological systems contributes to the identification of novel pharmaceutical compounds. The potential of biomolecular simulation and computational biology is vast and limitless. As the exploration of the underlying principles that govern living organisms progresses, the potential impact of this understanding on cancer treatment, environmental restoration, and other domains is anticipated to be transformative. This review examines the notable advancements achieved in the field of computational biology, emphasizing its potential to revolutionize the comprehension and enhancement of biological systems.
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Affiliation(s)
- Ekambaram Gayathiri
- Department of Plant Biology and Plant Biotechnology, Guru Nanak College (Autonomous), Chennai, 42, Tamil Nadu, India
| | - Palanisamy Prakash
- Department of Botany, Periyar University, Periyar Palkalai Nagar, Salem, 636011, Tamil Nadu, India
| | - Priya Kumaravel
- Department of Biotechnology, St. Joseph College (Arts & Science), Kovur, Chennai, Tamil Nadu, India
| | - Jayanthi Jayaprakash
- Department of Advanced Zoology and Biotechnology, Guru Nanak College, Chennai, Tamil Nadu, India
| | | | - Sharmila Sankar
- Department of Advanced Zoology and Biotechnology, Guru Nanak College, Chennai, Tamil Nadu, India
| | - Saravanan Pandiaraj
- Department of Self-Development Skills, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia
| | - Natesan Thirumalaivasan
- Department of Periodontics, Saveetha Dental College, and Hospitals, Saveetha Institute of Medical and Technical Sciences (SIMTAS), Chennai, 600077, Tamil Nadu, India
| | - Muthu Thiruvengadam
- Department of Applied Bioscience, College of Life and Environmental Sciences, Konkuk University, Seoul, 05029, South Korea
| | - Rajakumar Govindasamy
- Department of Orthodontics, Saveetha Dental College and Hospitals, Saveetha University, Chennai, India.
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Hoff FW, Qiu Y, Brown BD, Gerbing RB, Leonti AR, Ries RE, Gamis AS, Aplenc R, Kolb EA, Alonzo TA, Meshinchi S, Jenkins GN, Horton T, Kornblau SM. Valosin-containing protein (VCP/p97) is prognostically unfavorable in pediatric AML, and negatively correlates with unfolded protein response proteins IRE1 and GRP78: A report from the Children's Oncology Group. Proteomics Clin Appl 2023; 17:e2200109. [PMID: 37287368 PMCID: PMC10700663 DOI: 10.1002/prca.202200109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Revised: 04/25/2023] [Accepted: 05/25/2023] [Indexed: 06/09/2023]
Abstract
PURPOSE The endoplasmic reticulum (ER) is the major site of protein synthesis and folding in the cell. ER-associated degradation (ERAD) and unfolded protein response (UPR) are the main mechanisms of ER-mediated cell stress adaptation. Targeting the cell stress response is a promising therapeutic approach in acute myeloid leukemia (AML). EXPERIMENTAL DESIGN Protein expression levels of valosin-containing protein (VCP), a chief element of ERAD, were measured in peripheral blood samples from in 483 pediatric AML patients using reverse phase protein array methodology. Patients participated in the Children's Oncology Group AAML1031 phase 3 clinical trial that randomized patients to standard chemotherapy (cytarabine (Ara-C), daunorubicin, and etoposide [ADE]) versus ADE plus bortezomib (ADE+BTZ). RESULTS Low-VCP expression was significantly associated with favorable 5-year overall survival (OS) rate compared to middle-high-VCP expression (81% versus 63%, p < 0.001), independent of additional bortezomib treatment. Multivariable Cox regression analysis identified VCP as independent predictor of clinical outcome. UPR proteins IRE1 and GRP78 had significant negative correlation with VCP. Five-year OS in patients characterized by low-VCP, moderately high-IRE1 and high-GRP78 improved after treatment with ADE+BTZ versus ADE (66% versus 88%, p = 0.026). CONCLUSION AND CLINICAL RELEVANCE Our findings suggest the potential of the protein VCP as biomarker in prognostication prediction in pediatric AML.
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Affiliation(s)
- Fieke W. Hoff
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Yihua Qiu
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Brandon D. Brown
- Department of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Amanda R. Leonti
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Rhonda E. Ries
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Alan S. Gamis
- Department of Hematology-Oncology, Children’s Mercy Hospitals and Clinics, Kansas City, MO
| | - Richard Aplenc
- Division of Pediatric Oncology/Stem Cell Transplant, Children’s Hospital of Philadelphia, Philadelphia, PA
| | - E. Anders Kolb
- Nemours Center for Cancer and Blood Disorders, Alfred I. DuPont Hospital for Children, Wilmington, DE
| | - Todd A. Alonzo
- COG Statistics and Data Center, Monrovia, CA
- Keck School of Medicine, University of Southern California, CA
| | - Soheil Meshinchi
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Gaye N Jenkins
- Department of Pediatrics, Baylor College of Medicine/Dan L. Duncan Cancer Center and Texas Children’s Cancer Center, Houston, Texas
| | - Terzah Horton
- Department of Pediatrics, Baylor College of Medicine/Dan L. Duncan Cancer Center and Texas Children’s Cancer Center, Houston, Texas
| | - Steven M. Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX
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Ye Z, Mayer J, Leary EJ, Kitchner T, Dart RA, Brilliant MH, Hebbring SJ. Estimating the efficacy of pharmacogenomics over a lifetime. Front Med (Lausanne) 2023; 10:1006743. [PMID: 38020121 PMCID: PMC10645151 DOI: 10.3389/fmed.2023.1006743] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 07/10/2023] [Indexed: 12/01/2023] Open
Abstract
It is well known that common variants in specific genes influence drug metabolism and response, but it is currently unknown what fraction of patients are given prescriptions over a lifetime that could be contraindicated by their pharmacogenomic profiles. To determine the clinical utility of pharmacogenomics over a lifetime in a general patient population, we sequenced the genomes of 300 deceased Marshfield Clinic patients linked to lifelong medical records. Genetic variants in 33 pharmacogenes were evaluated for their lifetime impact on drug prescribing using extensive electronic health records. Results show that 93% of the 300 deceased patients carried clinically relevant variants. Nearly 80% were prescribed approximately three medications on average that may have been impacted by these variants. Longitudinal data suggested that the optimal age for pharmacogenomic testing was prior to age 50, but the optimal age is greatly influenced by the stability of the population in the healthcare system. This study emphasizes the broad clinical impact of pharmacogenomic testing over a lifetime and demonstrates the potential application of genomic medicine in a general patient population for the advancement of precision medicine.
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Greenstreet L, Afanassiev A, Kijima Y, Heitz M, Ishiguro S, King S, Yachie N, Schiebinger G. DNA-GPS: A theoretical framework for optics-free spatial genomics and synthesis of current methods. Cell Syst 2023; 14:844-859.e4. [PMID: 37751737 DOI: 10.1016/j.cels.2023.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 04/19/2023] [Accepted: 08/25/2023] [Indexed: 09/28/2023]
Abstract
While single-cell sequencing technologies provide unprecedented insights into genomic profiles at the cellular level, they lose the spatial context of cells. Over the past decade, diverse spatial transcriptomics and multi-omics technologies have been developed to analyze molecular profiles of tissues. In this article, we categorize current spatial genomics technologies into three classes: optical imaging, positional indexing, and mathematical cartography. We discuss trade-offs in resolution and scale, identify limitations, and highlight synergies between existing single-cell and spatial genomics methods. Further, we propose DNA-GPS (global positioning system), a theoretical framework for large-scale optics-free spatial genomics that combines ideas from mathematical cartography and positional indexing. DNA-GPS has the potential to achieve scalable spatial genomics for multiple measurement modalities, and by eliminating the need for optical measurement, it has the potential to position cells in three-dimensions (3D).
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Affiliation(s)
- Laura Greenstreet
- Department of Mathematics, The University of British Columbia, Vancouver, BC, Canada
| | - Anton Afanassiev
- Department of Mathematics, The University of British Columbia, Vancouver, BC, Canada
| | - Yusuke Kijima
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada; Department of Aquatic Bioscience, The University of Tokyo, Tokyo, Japan
| | - Matthieu Heitz
- Department of Mathematics, The University of British Columbia, Vancouver, BC, Canada
| | - Soh Ishiguro
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Samuel King
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada
| | - Nozomu Yachie
- School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada; Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan; Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Osaka, Japan; Graduate School of Media and Governance, Keio University, Fujisawa, Japan.
| | - Geoffrey Schiebinger
- Department of Mathematics, The University of British Columbia, Vancouver, BC, Canada; School of Biomedical Engineering, The University of British Columbia, Vancouver, BC, Canada.
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Li R, Wang Q, Yang J, Zhu J, Liu J, Wu R, Sun H. Comparison of three massively parallel sequencing platforms for single nucleotide polymorphism (SNP) genotyping in forensic genetics. Int J Legal Med 2023; 137:1361-1372. [PMID: 37336821 DOI: 10.1007/s00414-023-03035-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 05/30/2023] [Indexed: 06/21/2023]
Abstract
Three MPS platforms are being used in forensic genetic analysis, i.e., MiSeq FGx, Ion S5 XL, and MGISEQ-2000. However, few studies compared their performance. In this study, we sequenced 83 common SNPs of 71 samples using the ForenSeq™ DNA Signature Prep Kit on MiSeq FGx, the Precision ID Identity Panel on Ion S5 XL, and the MGIEasy Signature Identification Library Prep Kit on MGISEQ-2000 and then the performance was compared. Results showed that the MiSeq FGx had the highest sequence quality but the lowest sequencing depth and allele balance. Discordant genotypes were observed at six SNPs, which may be caused by variants at primer binding regions, indel errors, or misalignments. Besides, two kinds of background noises, allele-specific miscalled reads (ASMR) and allele-nonspecific miscalled reads (ANMR), were characterized. MGISEQ-2000 showed the highest level of ASMR while Ion S5 XL had the highest level of ANMR. Site- and genotype-dependent miscalled patterns were observed at several SNPs on Ion S5 XL and MGISEQ-2000, but few on MiSeq FGx. In conclusion, the three MPS platforms perform differently with respect to sequencing quality, sequencing depth, allele balance, concordance, and background noise. These findings may be useful for data comparison, mixture deconvolution, and heteroplasmy analysis in forensic genetics.
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Affiliation(s)
- Ran Li
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
- School of Medicine, Jiaying University, Meizhou, 514015, People's Republic of China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Qiangwei Wang
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Jingyi Yang
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Jianzhang Zhu
- Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510080, People's Republic of China
| | - Jiajun Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Riga Wu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China
| | - Hongyu Sun
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
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Furukawa S, Kushima I, Aleksic B, Ozaki N. Case reports of two siblings with autism spectrum disorder and 15q13.3 deletions. Neuropsychopharmacol Rep 2023; 43:462-466. [PMID: 37264739 PMCID: PMC10496043 DOI: 10.1002/npr2.12340] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 04/05/2023] [Accepted: 04/04/2023] [Indexed: 06/03/2023] Open
Abstract
BACKGROUND Copy number variations (CNVs) have been implicated in psychiatric and neurodevelopmental disorders. Especially, 15q13.3 deletions are strongly associated with autism spectrum disorder (ASD), intellectual disability (ID), schizophrenia (SCZ), attention deficithyperactivity disorder (ADHD), and mood disorder. CASE PRESENTATION We present two siblings with ASD. They had a father with bipolar disorder (BD). Patient 1 is a 21-year-old female with ASD and mild ID, who had language delay and repetitive behavior in childhood, social difficulties, and refused to go to school because of bullying. She was hospitalized in a psychiatric hospital several times. Patient 2 is a 19-year-old male with ASD and ADHD. He did not have developmental delay, but had social difficulties and impulsiveness, then refused to go to school because of bullying. He was treated by a psychiatrist for anxiety and disrupted sleep rhythms. Array comparative genomic hybridization was performed for the siblings and parents. 15q13.3 deletions were detected in the siblings and their healthy mothers. No other pathogenic CNVs were detected. We performed whole-genome sequencing of the family and identified 13 rare missense variants in brain-expressed genes, which may be responsible for the phenotypic differences between the siblings and their mother. CONCLUSIONS This study shows incomplete penetrance and variable expressivity in 15q13.3 deletions. We detected second-hit variants that may explain the phenotypic differences within this family. In addition, detecting 15q13.3 deletions may lead to early diagnosis and a better prognosis with careful follow-up.
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Affiliation(s)
- Sawako Furukawa
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
| | - Itaru Kushima
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
- Medical Genomics CenterNagoya University HospitalNagoyaJapan
| | - Branko Aleksic
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
| | - Norio Ozaki
- Department of PsychiatryNagoya University Graduate School of MedicineNagoyaJapan
- Institute for Glyco‐core ResearchNagoya UniversityNagoyaJapan
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Tang X, Chen J, Zhang X, Liu X, Xie Z, Wei K, Qiu J, Ma W, Lin C, Ke R. Improved in situ sequencing for high-resolution targeted spatial transcriptomic analysis in tissue sections. J Genet Genomics 2023; 50:652-660. [PMID: 36796537 DOI: 10.1016/j.jgg.2023.02.004] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/30/2023] [Accepted: 02/02/2023] [Indexed: 02/17/2023]
Abstract
Spatial transcriptomics enables the study of localization-indexed gene expression activity in tissues, providing the transcriptional landscape that in turn indicates the potential regulatory networks of gene expression. In situ sequencing (ISS) is a targeted spatial transcriptomic technique, based on padlock probe and rolling circle amplification combined with next-generation sequencing chemistry, for highly multiplexed in situ gene expression profiling. Here, we present improved in situ sequencing (IISS) that exploits a new probing and barcoding approach, combined with advanced image analysis pipelines for high-resolution targeted spatial gene expression profiling. We develop an improved combinatorial probe anchor ligation chemistry using a 2-base encoding strategy for barcode interrogation. The new encoding strategy results in higher signal intensity as well as improved specificity for in situ sequencing, while maintaining a streamlined analysis pipeline for targeted spatial transcriptomics. We show that IISS can be applied to both fresh frozen tissue and formalin-fixed paraffin-embedded tissue sections for single-cell level spatial gene expression analysis, based on which the developmental trajectory and cell-cell communication networks can also be constructed.
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Affiliation(s)
- Xinbin Tang
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Jiayu Chen
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Xinya Zhang
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Xuzhu Liu
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Zhaoxiang Xie
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Kaipeng Wei
- Department of Pathology, The 910 Hospital, Quanzhou, Fujian 362000, China
| | - Jianlong Qiu
- Department of Pathology, The 910 Hospital, Quanzhou, Fujian 362000, China
| | - Weiyan Ma
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China
| | - Chen Lin
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China.
| | - Rongqin Ke
- School of Medicine and School of Biomedical Sciences, Huaqiao University, Quanzhou, Fujian 362021, China.
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Tooze RS, Miller KA, Swagemakers SMA, Calpena E, McGowan SJ, Boute O, Collet C, Johnson D, Laffargue F, de Leeuw N, Morton JV, Noons P, Ockeloen CW, Phipps JM, Tan TY, Timberlake AT, Vanlerberghe C, Wall SA, Weber A, Wilson LC, Zackai EH, Mathijssen IMJ, Twigg SRF, Wilkie AOM. Pathogenic variants in the paired-related homeobox 1 gene (PRRX1) cause craniosynostosis with incomplete penetrance. Genet Med 2023; 25:100883. [PMID: 37154149 PMCID: PMC11554955 DOI: 10.1016/j.gim.2023.100883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/30/2023] [Accepted: 04/30/2023] [Indexed: 05/10/2023] Open
Abstract
PURPOSE Studies have previously implicated PRRX1 in craniofacial development, including demonstration of murine Prrx1 expression in the preosteogenic cells of the cranial sutures. We investigated the role of heterozygous missense and loss-of-function (LoF) variants in PRRX1 associated with craniosynostosis. METHODS Trio-based genome, exome, or targeted sequencing were used to screen PRRX1 in patients with craniosynostosis; immunofluorescence analyses were used to assess nuclear localization of wild-type and mutant proteins. RESULTS Genome sequencing identified 2 of 9 sporadically affected individuals with syndromic/multisuture craniosynostosis, who were heterozygous for rare/undescribed variants in PRRX1. Exome or targeted sequencing of PRRX1 revealed a further 9 of 1449 patients with craniosynostosis harboring deletions or rare heterozygous variants within the homeodomain. By collaboration, 7 additional individuals (4 families) were identified with putatively pathogenic PRRX1 variants. Immunofluorescence analyses showed that missense variants within the PRRX1 homeodomain cause abnormal nuclear localization. Of patients with variants considered likely pathogenic, bicoronal or other multisuture synostosis was present in 11 of 17 cases (65%). Pathogenic variants were inherited from unaffected relatives in many instances, yielding a 12.5% penetrance estimate for craniosynostosis. CONCLUSION This work supports a key role for PRRX1 in cranial suture development and shows that haploinsufficiency of PRRX1 is a relatively frequent cause of craniosynostosis.
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Affiliation(s)
- Rebecca S Tooze
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Kerry A Miller
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Sigrid M A Swagemakers
- Department of Pathology & Clinical Bioinformatics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Eduardo Calpena
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Simon J McGowan
- Centre for Computational Biology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
| | - Odile Boute
- Univ. Lille, CHU Lille, ULR 7364 - RADEME - Maladies Rares du Développement Embryonnaire et du Métabolisme, Clinique de Génétique, Lille, France
| | - Corinne Collet
- Genetics Department, Robert Debré University Hospital, APHP, Paris, France
| | - David Johnson
- Craniofacial Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Fanny Laffargue
- Clinical Genetics Service and Reference Centre for Rare Developmental Abnormalities and Intellectual Disabilities, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Nicole de Leeuw
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jenny V Morton
- West Midlands Regional Clinical Genetics Service and Birmingham Health Partners, Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Peter Noons
- Department of Craniofacial Surgery, Birmingham Children's Hospital NHS Foundation Trust, Birmingham, United Kingdom
| | - Charlotte W Ockeloen
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Julie M Phipps
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom; Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Tiong Yang Tan
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Australia; Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | - Andrew T Timberlake
- Hansjörg Wyss Department of Plastic Surgery, NYU Langone Medical Center, New York, NY
| | - Clemence Vanlerberghe
- Univ. Lille, CHU Lille, ULR 7364 - RADEME - Maladies Rares du Développement Embryonnaire et du Métabolisme, Clinique de Génétique, Lille, France
| | - Steven A Wall
- Craniofacial Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Astrid Weber
- Liverpool Centre for Genomic Medicine, Liverpool Women's NHS Foundation Trust, Liverpool, United Kingdom
| | - Louise C Wilson
- North East Thames Regional Genetics Service, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom
| | - Elaine H Zackai
- Clinical Genetics Center, Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Irene M J Mathijssen
- Department of Plastic and Reconstructive Surgery and Hand Surgery, Erasmus Medical Centre, University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Stephen R F Twigg
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom.
| | - Andrew O M Wilkie
- Clinical Genetics Group, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, United Kingdom
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Jia H, Liu H, Tu M, Wang Y, Wang X, Li J, Zhang G. Diagnostic efficacy of metagenomic next generation sequencing in bronchoalveolar lavage fluid for proven invasive pulmonary aspergillosis. Front Cell Infect Microbiol 2023; 13:1223576. [PMID: 37692168 PMCID: PMC10484620 DOI: 10.3389/fcimb.2023.1223576] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 08/02/2023] [Indexed: 09/12/2023] Open
Abstract
Objective To assess the diagnostic efficacy of metagenomic next generation sequencing (mNGS) for proven invasive pulmonary aspergillosis (IPA). Methods A total of 190 patients including 53 patients who had been diagnosed with proven IPA were retrospectively analyzed. Using the pathological results of tissue biopsy specimens as gold standard, we ploted the receiver operating characteristic (ROC) curve to determine the optimal cut-off value of mNGS species-specific read number (SSRN) of Aspergillus in bronchoalveolar lavage fluid (BALF)for IPA. Furthermore, we evaluated optimal cut-off value of mNGS SSRN in different populations. Results The optimal cut-off value of Aspergillus mNGS SSRN in BALF for IPA diagnosis was 2.5 for the whole suspected IPA population, and 1 and 4.5 for immunocompromised and diabetic patients, respectively. The accuracy of mNGS was 80.5%, 73.7% and 85.3% for the whole population, immunocompromised and diabetic patients, respectively. Conclusions The mNGS in BALF has a high diagnostic efficacy for proven IPA, superioring to Aspergillus culture in sputum and BALF and GM test in blood and BALF. However, the cut-off value of SSRN should be adjusted when in different population.
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Affiliation(s)
| | | | | | | | | | | | - Guojun Zhang
- Department of Pulmonary and Critical Care Medicine, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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Satam H, Joshi K, Mangrolia U, Waghoo S, Zaidi G, Rawool S, Thakare RP, Banday S, Mishra AK, Das G, Malonia SK. Next-Generation Sequencing Technology: Current Trends and Advancements. BIOLOGY 2023; 12:997. [PMID: 37508427 PMCID: PMC10376292 DOI: 10.3390/biology12070997] [Citation(s) in RCA: 300] [Impact Index Per Article: 150.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023]
Abstract
The advent of next-generation sequencing (NGS) has brought about a paradigm shift in genomics research, offering unparalleled capabilities for analyzing DNA and RNA molecules in a high-throughput and cost-effective manner. This transformative technology has swiftly propelled genomics advancements across diverse domains. NGS allows for the rapid sequencing of millions of DNA fragments simultaneously, providing comprehensive insights into genome structure, genetic variations, gene expression profiles, and epigenetic modifications. The versatility of NGS platforms has expanded the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Moreover, NGS has enabled the development of targeted therapies, precision medicine approaches, and improved diagnostic methods. This review provides an insightful overview of the current trends and recent advancements in NGS technology, highlighting its potential impact on diverse areas of genomic research. Moreover, the review delves into the challenges encountered and future directions of NGS technology, including endeavors to enhance the accuracy and sensitivity of sequencing data, the development of novel algorithms for data analysis, and the pursuit of more efficient, scalable, and cost-effective solutions that lie ahead.
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Affiliation(s)
- Heena Satam
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Kandarp Joshi
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Upasana Mangrolia
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Sanober Waghoo
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Gulnaz Zaidi
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Shravani Rawool
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Ritesh P. Thakare
- Department of Molecular Cell and Cancer Biology, UMass Chan Medical School, Worcester, MA 01605, USA; (R.P.T.); (S.B.); (A.K.M.)
| | - Shahid Banday
- Department of Molecular Cell and Cancer Biology, UMass Chan Medical School, Worcester, MA 01605, USA; (R.P.T.); (S.B.); (A.K.M.)
| | - Alok K. Mishra
- Department of Molecular Cell and Cancer Biology, UMass Chan Medical School, Worcester, MA 01605, USA; (R.P.T.); (S.B.); (A.K.M.)
| | - Gautam Das
- miBiome Therapeutics, Mumbai 400102, India; (H.S.); (K.J.); (U.M.); (S.W.); (G.Z.); (S.R.)
| | - Sunil K. Malonia
- Department of Molecular Cell and Cancer Biology, UMass Chan Medical School, Worcester, MA 01605, USA; (R.P.T.); (S.B.); (A.K.M.)
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50
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Fangma Y, Liu M, Liao J, Chen Z, Zheng Y. Dissecting the brain with spatially resolved multi-omics. J Pharm Anal 2023; 13:694-710. [PMID: 37577383 PMCID: PMC10422112 DOI: 10.1016/j.jpha.2023.04.003] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 08/15/2023] Open
Abstract
Recent studies have highlighted spatially resolved multi-omics technologies, including spatial genomics, transcriptomics, proteomics, and metabolomics, as powerful tools to decipher the spatial heterogeneity of the brain. Here, we focus on two major approaches in spatial transcriptomics (next-generation sequencing-based technologies and image-based technologies), and mass spectrometry imaging technologies used in spatial proteomics and spatial metabolomics. Furthermore, we discuss their applications in neuroscience, including building the brain atlas, uncovering gene expression patterns of neurons for special behaviors, deciphering the molecular basis of neuronal communication, and providing a more comprehensive explanation of the molecular mechanisms underlying central nervous system disorders. However, further efforts are still needed toward the integrative application of multi-omics technologies, including the real-time spatial multi-omics analysis in living cells, the detailed gene profile in a whole-brain view, and the combination of functional verification.
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Affiliation(s)
- Yijia Fangma
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Mengting Liu
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Jie Liao
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Zhong Chen
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
| | - Yanrong Zheng
- Key Laboratory of Neuropharmacology and Translational Medicine of Zhejiang Province, School of Pharmaceutical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, China
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