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Pang J, Tan HN, Mak TM, Octavia S, Maurer-Stroh S, Sirota FL, Chan MPC, Leong IYO, Koh VTJ, Ooi PL, Vasoo S, Fisher D, Cui L, Rafman H, Cutter J, Lee VJ. Epidemiological, Clinical, and Phylogenetic Characteristics of the First SARS-CoV-2 Transmission in a Nursing Home of Singapore: A Prospective Observational Investigation. Front Med (Lausanne) 2022; 8:790177. [PMID: 35155470 PMCID: PMC8831716 DOI: 10.3389/fmed.2021.790177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 12/15/2021] [Indexed: 11/13/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has resulted in a significant burden among nursing home facilities globally. This prospective observational cohort study aims to define the potential sources of introduction and characteristics of SARS-CoV-2 transmission of the first nursing home facility in Singapore. An epidemiological serial point-prevalence survey of SARS-CoV-2 was conducted among 108 residents and 56 healthcare staff (HCS). In the current study, 14 (13%) residents and two (3.6%) HCS were diagnosed with coronavirus disease 2019 (COVID-19), with a case fatality rate (CFR) of 28.6% (4/14) among the residents. The median age of the infected residents was 86.5 [interquartile range (IQR) 78.5-88] and 85.7% were women. Five residents were symptomatic (35.7%) and the others were asymptomatic (64.3%). A higher proportion of residents who succumbed to COVID-19 had hypertension than those who recovered. The SARS-CoV-2 whole-genome sequencing showed lineage B.6 which is rare globally but common regionally during the early phase of the pandemic. Household transmission is a potential source of introduction into the nursing home, with at least six epidemiologically linked secondary cases. Male residents were less implicated due to the staff segregation plan by block. Among residents, a higher proportion of the non-survivors were asymptomatic and had hypertension compared with survivors.
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Affiliation(s)
- Junxiong Pang
- Ministry of Health, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Huei Nuo Tan
- Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore, Singapore
| | - Tze Minn Mak
- National Public Health Laboratory, National Centre for Infectious Diseases, Singapore, Singapore
| | - Sophie Octavia
- National Public Health Laboratory, National Centre for Infectious Diseases, Singapore, Singapore
| | - Sebastian Maurer-Stroh
- National Public Health Laboratory, National Centre for Infectious Diseases, Singapore, Singapore
- Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Fernanda L. Sirota
- Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore
- Genome Institute of Singapore and Bioinformatics Institute, Agency for Science, Technology and Research, Singapore, Singapore
| | - Mark Peng Chew Chan
- Department of Geriatric Medicine, Tan Tock Seng Hospital, Singapore, Singapore
| | - Ian Yi Onn Leong
- Division of Central Health, Tan Tock Seng Hospital, Singapore, Singapore
| | | | - Peng Lim Ooi
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- National Public Health and Epidemiology Unit, National Centre for Infectious Diseases, Singapore, Singapore
| | - Shawn Vasoo
- National Public Health and Epidemiology Unit, National Centre for Infectious Diseases, Singapore, Singapore
| | - Dale Fisher
- Yong Loo Lin School of Medicine, National University Hospital and National University Health System, Singapore, Singapore
| | - Lin Cui
- National Public Health Laboratory, National Centre for Infectious Diseases, Singapore, Singapore
| | - Heidi Rafman
- Agency for Integrated Care, Singapore, Singapore
| | - Jeffery Cutter
- Ministry of Health, Singapore, Singapore
- National Public Health and Epidemiology Unit, National Centre for Infectious Diseases, Singapore, Singapore
| | - Vernon J. Lee
- Ministry of Health, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
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Sirota FL, Maurer-Stroh S, Li Z, Eisenhaber F, Eisenhaber B. Functional Classification of Super-Large Families of Enzymes Based on Substrate Binding Pocket Residues for Biocatalysis and Enzyme Engineering Applications. Front Bioeng Biotechnol 2021; 9:701120. [PMID: 34409021 PMCID: PMC8366029 DOI: 10.3389/fbioe.2021.701120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 07/12/2021] [Indexed: 11/13/2022] Open
Abstract
Large enzyme families such as the groups of zinc-dependent alcohol dehydrogenases (ADHs), long chain alcohol oxidases (AOxs) or amine dehydrogenases (AmDHs) with, sometimes, more than one million sequences in the non-redundant protein database and hundreds of experimentally characterized enzymes are excellent cases for protein engineering efforts aimed at refining and modifying substrate specificity. Yet, the backside of this wealth of information is that it becomes technically difficult to rationally select optimal sequence targets as well as sequence positions for mutagenesis studies. In all three cases, we approach the problem by starting with a group of experimentally well studied family members (including those with available 3D structures) and creating a structure-guided multiple sequence alignment and a modified phylogenetic tree (aka binding site tree) based just on a selection of potential substrate binding residue positions derived from experimental information (not from the full-length sequence alignment). Hereupon, the remaining, mostly uncharacterized enzyme sequences can be mapped; as a trend, sequence grouping in the tree branches follows substrate specificity. We show that this information can be used in the target selection for protein engineering work to narrow down to single suitable sequences and just a few relevant candidate positions for directed evolution towards activity for desired organic compound substrates. We also demonstrate how to find the closest thermophile example in the dataset if the engineering is aimed at achieving most robust enzymes.
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Affiliation(s)
- Fernanda L Sirota
- Bioinformatics Institute (BII), Agency for Science Technology and Research (ASTAR), Singapore, Singapore
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute (BII), Agency for Science Technology and Research (ASTAR), Singapore, Singapore.,Department of Biological Sciences, National University of Singapore, Singapore, Singapore
| | - Zhi Li
- Department of Chemical and Biomolecular Engineering, National University of Singapore, Singapore, Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science Technology and Research (ASTAR), Singapore, Singapore.,Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.,School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Birgit Eisenhaber
- Bioinformatics Institute (BII), Agency for Science Technology and Research (ASTAR), Singapore, Singapore.,Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore
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Wong HH, Seet SH, Maier M, Gurel A, Traspas RM, Lee C, Zhang S, Talim B, Loh AY, Chia CY, Teoh TS, Sng D, Rensvold J, Unal S, Shishkova E, Cepni E, Nathan FM, Sirota FL, Liang C, Yarali N, Simsek-Kiper PO, Mitani T, Ceylaner S, Arman-Bilir O, Mbarek H, Gumruk F, Efthymiou S, Çïmen DU, Georgiadou D, Sotiropoulou K, Houlden H, Paul F, Pehlivan D, Lainé C, Chai G, Ali NA, Choo SC, Keng SS, Boisson B, Yılmaz E, Xue S, Coon JJ, Nguyen Ly TT, Gilani N, Hasbini D, Kayserili H, Zaki MS, Isfort RJ, Ordonez N, Tripolszki K, Bauer P, Rezaei N, Seyedpour S, Khotaei GT, Bascom CC, Maroofian R, Chaabouni M, Alsubhi A, Eyaid W, Işıkay S, Gleeson JG, Lupski JR, Casanova JL, Pagliarini DJ, Akarsu NA, Maurer-Stroh S, Cetinkaya A, Bertoli-Avella A, Mathuru AS, Ho L, Bard FA, Reversade B. Loss of C2orf69 defines a fatal autoinflammatory syndrome in humans and zebrafish that evokes a glycogen-storage-associated mitochondriopathy. Am J Hum Genet 2021; 108:1356. [PMID: 34214448 DOI: 10.1016/j.ajhg.2021.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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4
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Wong HH, Seet SH, Maier M, Gurel A, Traspas RM, Lee C, Zhang S, Talim B, Loh AYT, Chia CY, Teoh TS, Sng D, Rensvold J, Unal S, Shishkova E, Cepni E, Nathan FM, Sirota FL, Liang C, Yarali N, Simsek-Kiper PO, Mitani T, Ceylaner S, Arman-Bilir O, Mbarek H, Gumruk F, Efthymiou S, Uğurlu Çi Men D, Georgiadou D, Sotiropoulou K, Houlden H, Paul F, Pehlivan D, Lainé C, Chai G, Ali NA, Choo SC, Keng SS, Boisson B, Yılmaz E, Xue S, Coon JJ, Ly TTN, Gilani N, Hasbini D, Kayserili H, Zaki MS, Isfort RJ, Ordonez N, Tripolszki K, Bauer P, Rezaei N, Seyedpour S, Khotaei GT, Bascom CC, Maroofian R, Chaabouni M, Alsubhi A, Eyaid W, Işıkay S, Gleeson JG, Lupski JR, Casanova JL, Pagliarini DJ, Akarsu NA, Maurer-Stroh S, Cetinkaya A, Bertoli-Avella A, Mathuru AS, Ho L, Bard FA, Reversade B. Loss of C2orf69 defines a fatal autoinflammatory syndrome in humans and zebrafish that evokes a glycogen-storage-associated mitochondriopathy. Am J Hum Genet 2021; 108:1301-1317. [PMID: 34038740 PMCID: PMC8322802 DOI: 10.1016/j.ajhg.2021.05.003] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 05/07/2021] [Indexed: 12/20/2022] Open
Abstract
Human C2orf69 is an evolutionarily conserved gene whose function is unknown. Here, we report eight unrelated families from which 20 children presented with a fatal syndrome consisting of severe autoinflammation and progredient leukoencephalopathy with recurrent seizures; 12 of these subjects, whose DNA was available, segregated homozygous loss-of-function C2orf69 variants. C2ORF69 bears homology to esterase enzymes, and orthologs can be found in most eukaryotic genomes, including that of unicellular phytoplankton. We found that endogenous C2ORF69 (1) is loosely bound to mitochondria, (2) affects mitochondrial membrane potential and oxidative respiration in cultured neurons, and (3) controls the levels of the glycogen branching enzyme 1 (GBE1) consistent with a glycogen-storage-associated mitochondriopathy. We show that CRISPR-Cas9-mediated inactivation of zebrafish C2orf69 results in lethality by 8 months of age due to spontaneous epileptic seizures, which is preceded by persistent brain inflammation. Collectively, our results delineate an autoinflammatory Mendelian disorder of C2orf69 deficiency that disrupts the development/homeostasis of the immune and central nervous systems.
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Affiliation(s)
- Hui Hui Wong
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Sze Hwee Seet
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Michael Maier
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Ayse Gurel
- Department of Medical Genetics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | - Ricardo Moreno Traspas
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Cheryl Lee
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Cardiovascular and Metabolic Diseases, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Shan Zhang
- Department of Medical Genetics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | - Beril Talim
- Pediatric Pathology Unit, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | - Abigail Y T Loh
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Crystal Y Chia
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Tze Shin Teoh
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Danielle Sng
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Jarred Rensvold
- Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Morgridge Institute for Research, Madison, WI 53715, USA
| | - Sule Unal
- Pediatric Hematology Unit, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey; Research Center of Fanconi Anemia and Other Inherited Bone Marrow Failure Syndromes, Hacettepe University, Ankara 06230, Turkey
| | - Evgenia Shishkova
- National Center for Quantitative Biology of Complex Systems, Madison, WI 53562, USA; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53562, USA
| | - Ece Cepni
- Institute of Health Sciences, Koç University, 34010 Istanbul, Turkey
| | - Fatima M Nathan
- Yale-NUS College, 12 College Avenue West, Singapore 138610, Singapore
| | - Fernanda L Sirota
- Bioinformatics Institute, A(∗)STAR, Biopolis, Singapore 138671, Singapore
| | - Chao Liang
- Department of Medical Genetics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | - Nese Yarali
- Ankara Child Health and Diseases Hematology Oncology Training and Research Hospital, Ankara 06110, Turkey
| | - Pelin O Simsek-Kiper
- Pediatric Genetics Unit, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | - Tadahiro Mitani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Ozlem Arman-Bilir
- Ankara Child Health and Diseases Hematology Oncology Training and Research Hospital, Ankara 06110, Turkey
| | - Hamdi Mbarek
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Fatma Gumruk
- Pediatric Hematology Unit, Department of Pediatrics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey; Research Center of Fanconi Anemia and Other Inherited Bone Marrow Failure Syndromes, Hacettepe University, Ankara 06230, Turkey
| | - Stephanie Efthymiou
- Molecular and Clinical Sciences Institute, St. George's University of London, Cranmer Terrace, London SW17 0RE, UK
| | - Deniz Uğurlu Çi Men
- Medical Genetics Department, Koç University School of Medicine, 34010 Istanbul, Turkey
| | - Danai Georgiadou
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Kortessa Sotiropoulou
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Henry Houlden
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, Queen Square, London WC1N 3BG, UK
| | - Franziska Paul
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Davut Pehlivan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA; Texas Children's Hospital, Houston, TX 77030, USA
| | - Candice Lainé
- Paris University, Imagine Institute, Paris 75015, France; Laboratory of Human Genetics of Infectious Disease, Necker Branch, INSERM U1163, Paris, France
| | - Guoliang Chai
- Rady Children's Institute for Genomic Medicine, San Diego, CA 92123, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - Nur Ain Ali
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Siew Chin Choo
- Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore
| | - Soh Sok Keng
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore
| | - Bertrand Boisson
- Paris University, Imagine Institute, Paris 75015, France; Laboratory of Human Genetics of Infectious Disease, Necker Branch, INSERM U1163, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA
| | - Elanur Yılmaz
- Medical Genetics Department, Koç University School of Medicine, 34010 Istanbul, Turkey
| | - Shifeng Xue
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Joshua J Coon
- Morgridge Institute for Research, Madison, WI 53715, USA; National Center for Quantitative Biology of Complex Systems, Madison, WI 53562, USA; Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, WI 53562, USA; Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53562, USA
| | - Thanh Thao Nguyen Ly
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | | | - Dana Hasbini
- Chief Division Pediatric Neurology, Department of Pediatrics, Rafic Hariri University Hospital, Beirut, Lebanon
| | - Hulya Kayserili
- Medical Genetics Department, Koç University School of Medicine, 34010 Istanbul, Turkey
| | - Maha S Zaki
- Clinical Genetics Department, National Research Centre, Cairo 12622, Egypt
| | - Robert J Isfort
- Corporate Research, The Procter and Gamble Company, Cincinnati, OH 45040, USA
| | | | | | - Peter Bauer
- Genomic Research, CENTOGENE GmbH, 18055 Rostock, Germany
| | - Nima Rezaei
- Research Center for Immunodeficiencies, Children's Medical Center, Tehran University of Medical Sciences, Tehran 14194, Iran; Network of Immunity in Infection, Malignancy and Autoimmunity, Universal Scientific Education and Research Network, Tehran 14197, Iran
| | - Simin Seyedpour
- Laboratoire d'analyses spécialisé en Génétique, Tunis 1082, Tunisia
| | - Ghamar Taj Khotaei
- Department of Pediatric Infectious Diseases, Children's Medical Center, Tehran University of Medical Sciences, Tehran 14194, Iran
| | - Charles C Bascom
- Corporate Research, The Procter and Gamble Company, Cincinnati, OH 45040, USA
| | - Reza Maroofian
- Molecular and Clinical Sciences Institute, St. George's University of London, Cranmer Terrace, London SW17 0RE, UK
| | - Myriam Chaabouni
- Laboratoire d'analyses spécialisé en Génétique, Tunis 1082, Tunisia
| | - Afaf Alsubhi
- Division of Genetics, Department of Pediatrics, King Abdullah Specialized Children Hospital, King Abdulaziz Medical City, MNGHA, Riyadh 14611, Saudi Arabia; King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, MNGHA, Riyadh 11481, Saudi Arabia
| | - Wafaa Eyaid
- Division of Genetics, Department of Pediatrics, King Abdullah Specialized Children Hospital, King Abdulaziz Medical City, MNGHA, Riyadh 14611, Saudi Arabia; King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, MNGHA, Riyadh 11481, Saudi Arabia
| | - Sedat Işıkay
- Department of Pediatrics, Division of Neurology, University of Gaziantep, School of Medicine, Gaziantep 27310, Turkey
| | - Joseph G Gleeson
- Rady Children's Institute for Genomic Medicine, San Diego, CA 92123, USA; Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA; Texas Children's Hospital, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Jean-Laurent Casanova
- Paris University, Imagine Institute, Paris 75015, France; Laboratory of Human Genetics of Infectious Disease, Necker Branch, INSERM U1163, Paris, France; St. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065, USA; Pediatric Immunology-Hematology Unit, Assistance Publique-Hôpitaux de Paris, Necker Hospital for Sick Children, Paris 75015, France; Howard Hughes Medical Institute, New York, NY 10065, USA
| | - David J Pagliarini
- Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO 63110, USA; Morgridge Institute for Research, Madison, WI 53715, USA; National Center for Quantitative Biology of Complex Systems, Madison, WI 53562, USA; Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA; Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Nurten A Akarsu
- Department of Medical Genetics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | | | - Arda Cetinkaya
- Department of Medical Genetics, Faculty of Medicine, Hacettepe University, Ankara 06230, Turkey
| | | | - Ajay S Mathuru
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Yale-NUS College, 12 College Avenue West, Singapore 138610, Singapore; Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore
| | - Lena Ho
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Cardiovascular and Metabolic Diseases, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Frederic A Bard
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore.
| | - Bruno Reversade
- Institute of Molecular and Cell Biology, A(∗)STAR, Biopolis, Singapore 138673, Singapore; Laboratory of Human Genetics & Therapeutics, Genome Institute of Singapore, A(∗)STAR, Biopolis, Singapore 138672, Singapore; Medical Genetics Department, Koç University School of Medicine, 34010 Istanbul, Turkey; Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore.
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Eisenhaber B, Sinha S, Jadalanki CK, Shitov VA, Tan QW, Sirota FL, Eisenhaber F. Conserved sequence motifs in human TMTC1, TMTC2, TMTC3, and TMTC4, new O-mannosyltransferases from the GT-C/PMT clan, are rationalized as ligand binding sites. Biol Direct 2021; 16:4. [PMID: 33436046 PMCID: PMC7801869 DOI: 10.1186/s13062-021-00291-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 01/04/2021] [Indexed: 12/05/2022] Open
Abstract
BACKGROUND The human proteins TMTC1, TMTC2, TMTC3 and TMTC4 have been experimentally shown to be components of a new O-mannosylation pathway. Their own mannosyl-transferase activity has been suspected but their actual enzymatic potential has not been demonstrated yet. So far, sequence analysis of TMTCs has been compromised by evolutionary sequence divergence within their membrane-embedded N-terminal region, sequence inaccuracies in the protein databases and the difficulty to interpret the large functional variety of known homologous proteins (mostly sugar transferases and some with known 3D structure). RESULTS Evolutionary conserved molecular function among TMTCs is only possible with conserved membrane topology within their membrane-embedded N-terminal regions leading to the placement of homologous long intermittent loops at the same membrane side. Using this criterion, we demonstrate that all TMTCs have 11 transmembrane regions. The sequence segment homologous to Pfam model DUF1736 is actually just a loop between TM7 and TM8 that is located in the ER lumen and that contains a small hydrophobic, but not membrane-embedded helix. Not only do the membrane-embedded N-terminal regions of TMTCs share a common fold and 3D structural similarity with subgroups of GT-C sugar transferases. The conservation of residues critical for catalysis, for binding of a divalent metal ion and of the phosphate group of a lipid-linked sugar moiety throughout enzymatically and structurally well-studied GT-Cs and sequences of TMTCs indicates that TMTCs are actually sugar-transferring enzymes. We present credible 3D structural models of all four TMTCs (derived from their closest known homologues 5ezm/5f15) and find observed conserved sequence motifs rationalized as binding sites for a metal ion and for a dolichyl-phosphate-mannose moiety. CONCLUSIONS With the results from both careful sequence analysis and structural modelling, we can conclusively say that the TMTCs are enzymatically active sugar transferases belonging to the GT-C/PMT superfamily. The DUF1736 segment, the loop between TM7 and TM8, is critical for catalysis and lipid-linked sugar moiety binding. Together with the available indirect experimental data, we conclude that the TMTCs are not only part of an O-mannosylation pathway in the endoplasmic reticulum of upper eukaryotes but, actually, they are the sought mannosyl-transferases.
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Affiliation(s)
- Birgit Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore.
- Genome Institute of Singapore (BII), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Republic of Singapore.
| | - Swati Sinha
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
| | - Chaitanya K Jadalanki
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
| | - Vladimir A Shitov
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
- Siberian State Medical University, Moskovskiy Trakt, 2, Tomsk, Tomsk Oblast, 634050, Russia
| | - Qiao Wen Tan
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
- School of Biological Science (SBS), Nanyang Technological University (NTU), 60 Nanyang Drive, Singapore, 637551, Republic of Singapore
| | - Fernanda L Sirota
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Republic of Singapore.
- Genome Institute of Singapore (BII), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Singapore, 138672, Republic of Singapore.
- School of Biological Science (SBS), Nanyang Technological University (NTU), 60 Nanyang Drive, Singapore, 637551, Republic of Singapore.
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6
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Goh F, Zhang MM, Lim TR, Low KN, Nge CE, Heng E, Yeo WL, Sirota FL, Crasta S, Tan Z, Ng V, Leong CY, Zhang H, Lezhava A, Chen SL, Hoon SS, Eisenhaber F, Eisenhaber B, Kanagasundaram Y, Wong FT, Ng SB. Identification and engineering of 32 membered antifungal macrolactone notonesomycins. Microb Cell Fact 2020; 19:71. [PMID: 32192516 PMCID: PMC7081687 DOI: 10.1186/s12934-020-01328-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 03/12/2020] [Indexed: 12/29/2022] Open
Abstract
Notonesomycin A is a 32-membered bioactive glycosylated macrolactone known to be produced by Streptomyces aminophilus subsp. notonesogenes 647-AV1 and S. aminophilus DSM 40186. In a high throughput antifungal screening campaign, we identified an alternative notonesomycin A producing strain, Streptomyces sp. A793, and its biosynthetic gene cluster. From this strain, we further characterized a new more potent antifungal non-sulfated analogue, named notonesomycin B. Through CRISPR–Cas9 engineering of the biosynthetic gene cluster, we were able to increase the production yield of notonesomycin B by up to 18-fold as well as generate a strain that exclusively produces this analogue.
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Affiliation(s)
- Falicia Goh
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.,Biotransformation Innovation Platform, A*STAR, 61 Biopolis Drive, Proteos Level 4, Singapore, 138673, Singapore
| | - Mingzi M Zhang
- Metabolic Engineering, Functional Molecules & Polymers, Institute of Chemical and Engineering Sciences, A*STAR, 31 Biopolis Way, Nanos #01-01, Singapore, 138669, Singapore.,Institute of Molecular and Genomic Medicine, National Health Research Institutes, Miaoli County, Taiwan, R.O.C
| | - Tian Ru Lim
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Kia Ngee Low
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Choy Eng Nge
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Elena Heng
- Molecular Engineering Laboratory, Institute of Bioengineering and Nanotechnology, A*STAR, 31 Biopolis Way, Nanos, Singapore, 138669, Singapore
| | - Wan Lin Yeo
- Metabolic Engineering, Functional Molecules & Polymers, Institute of Chemical and Engineering Sciences, A*STAR, 31 Biopolis Way, Nanos #01-01, Singapore, 138669, Singapore
| | - Fernanda L Sirota
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Sharon Crasta
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Zann Tan
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Veronica Ng
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Chung Yan Leong
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | - Huibin Zhang
- Genome Institute of Singapore, A*STAR, 60 Biopolis Street, Genome #02-01, Singapore, 138672, Singapore
| | - Alexander Lezhava
- Genome Institute of Singapore, A*STAR, 60 Biopolis Street, Genome #02-01, Singapore, 138672, Singapore
| | - Swaine L Chen
- Genome Institute of Singapore, A*STAR, 60 Biopolis Street, Genome #02-01, Singapore, 138672, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, 1E Kent Ridge Road, NUHS Tower Block, Level 10, Singapore, 119228, Singapore
| | - Shawn S Hoon
- Molecular Engineering Laboratory, Institute of Bioengineering and Nanotechnology, A*STAR, 31 Biopolis Way, Nanos, Singapore, 138669, Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.,School of Computer Science and Engineering, Nanyang Technological University (NTU), 50 Nanyang Drive, Singapore, 637553, Singapore
| | - Birgit Eisenhaber
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore
| | | | - Fong T Wong
- Molecular Engineering Laboratory, Institute of Bioengineering and Nanotechnology, A*STAR, 31 Biopolis Way, Nanos, Singapore, 138669, Singapore.
| | - Siew Bee Ng
- Bioinformatics Institute, A*STAR, 30 Biopolis Street, #07-01 Matrix, Singapore, 138671, Singapore.
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7
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Berger KA, Pigott DM, Tomlinson F, Godding D, Maurer-Stroh S, Taye B, Sirota FL, Han A, Lee RTC, Gunalan V, Eisenhaber F, Hay SI, Russell CA. The Geographic Variation of Surveillance and Zoonotic Spillover Potential of Influenza Viruses in Domestic Poultry and Swine. Open Forum Infect Dis 2018; 5:ofy318. [PMID: 30619908 PMCID: PMC6309522 DOI: 10.1093/ofid/ofy318] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2018] [Accepted: 11/23/2018] [Indexed: 12/14/2022] Open
Abstract
Background Avian and swine influenza viruses circulate worldwide and pose threats to both animal and human health. The design of global surveillance strategies is hindered by information gaps on the geospatial variation in virus emergence potential and existing surveillance efforts. Methods We developed a spatial framework to quantify the geographic variation in outbreak emergence potential based on indices of potential for animal-to-human and secondary human-to-human transmission. We then compared our resultant raster model of variation in emergence potential with the global distribution of recent surveillance efforts from 359105 reports of surveillance activities. Results Our framework identified regions of Southeast Asia, Eastern Europe, Central America, and sub-Saharan Africa with high potential for influenza virus spillover. In the last 15 years, however, we found that 78.43% and 49.01% of high-risk areas lacked evidence of influenza virus surveillance in swine and domestic poultry, respectively. Conclusions Our work highlights priority areas where improved surveillance and outbreak mitigation could enhance pandemic preparedness strategies.
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Affiliation(s)
- Kathryn A Berger
- Department of Veterinary Medicine, University of Cambridge, United Kingdom.,Agrimetrics Ltd., Harpenden, United Kingdom
| | - David M Pigott
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | | | - David Godding
- Department of Veterinary Medicine, University of Cambridge, United Kingdom
| | | | - Biruhalem Taye
- Bioinformatics Institute, ASTAR, Singapore.,European Molecular Biology Laboratory, Deutsches Elektronen-Synchrotron, Hamburg, Germany
| | | | - Alvin Han
- Bioinformatics Institute, ASTAR, Singapore.,National University of Singapore
| | | | | | - Frank Eisenhaber
- Bioinformatics Institute, ASTAR, Singapore.,National University of Singapore
| | - Simon I Hay
- Institute for Health Metrics and Evaluation, University of Washington, Seattle
| | - Colin A Russell
- Academic Medical Center, University of Amsterdam, The Netherlands
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8
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Sirota FL, Goh F, Low KN, Yang LK, Crasta SC, Eisenhaber B, Eisenhaber F, Kanagasundaram Y, Ng SB. Isolation and Identification of an Anthracimycin Analogue from Nocardiopsis kunsanensis, a Halophile from a Saltern, by Genomic Mining Strategy. J Genomics 2018; 6:63-73. [PMID: 29805716 PMCID: PMC5970133 DOI: 10.7150/jgen.24368] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Accepted: 04/25/2018] [Indexed: 11/23/2022] Open
Abstract
Modern medicine is unthinkable without antibiotics; yet, growing issues with microbial drug resistance require intensified search for new active compounds. Natural products generated by Actinobacteria have been a rich source of candidate antibiotics, for example anthracimycin that, so far, is only known to be produced by Streptomyces species. Based on sequence similarity with the respective biosynthetic cluster, we sifted through available microbial genome data with the goal to find alternative anthracimycin-producing organisms. In this work, we report about the prediction and experimental verification of the production of anthracimycin derivatives by Nocardiopsis kunsanensis, a non-Streptomyces actinobacterial microorganism. We discovered N. kunsanensis to predominantly produce a new anthracimycin derivative with methyl group at C-8 and none at C-2, labeled anthracimycin BII-2619, besides a minor amount of anthracimycin. It displays activity against Gram-positive bacteria with similar low level of mammalian cytotoxicity as that of anthracimycin.
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Affiliation(s)
- Fernanda L Sirota
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Falicia Goh
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Kia-Ngee Low
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Lay-Kien Yang
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Sharon C Crasta
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Birgit Eisenhaber
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore.,School of Computer Engineering, Nanyang Technological University (NTU), 50 Nanyang Drive, Singapore 637553, Republic of Singapore
| | - Yoganathan Kanagasundaram
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
| | - Siew Bee Ng
- Bioinformatics Institute, Agency for Science, Technology and Research (ASTAR), 30 Biopolis Street, #07-01 Matrix, Singapore 138671, Republic of Singapore
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9
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Sirota FL, Maurer-Stroh S, Eisenhaber B, Eisenhaber F. Single-residue posttranslational modification sites at the N-terminus, C-terminus or in-between: To be or not to be exposed for enzyme access. Proteomics 2016; 15:2525-46. [PMID: 26038108 PMCID: PMC4745020 DOI: 10.1002/pmic.201400633] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2014] [Revised: 04/17/2015] [Accepted: 05/29/2015] [Indexed: 11/30/2022]
Abstract
Many protein posttranslational modifications (PTMs) are the result of an enzymatic reaction. The modifying enzyme has to recognize the substrate protein's sequence motif containing the residue(s) to be modified; thus, the enzyme's catalytic cleft engulfs these residue(s) and the respective sequence environment. This residue accessibility condition principally limits the range where enzymatic PTMs can occur in the protein sequence. Non‐globular, flexible, intrinsically disordered segments or large loops/accessible long side chains should be preferred whereas residues buried in the core of structures should be void of what we call canonical, enzyme‐generated PTMs. We investigate whether PTM sites annotated in UniProtKB (with MOD_RES/LIPID keys) are situated within sequence ranges that can be mapped to known 3D structures. We find that N‐ or C‐termini harbor essentially exclusively canonical PTMs. We also find that the overwhelming majority of all other PTMs are also canonical though, later in the protein's life cycle, the PTM sites can become buried due to complex formation. Among the remaining cases, some can be explained (i) with autocatalysis, (ii) with modification before folding or after temporary unfolding, or (iii) as products of interaction with small, diffusible reactants. Others require further research how these PTMs are mechanistically generated in vivo.
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Affiliation(s)
- Fernanda L Sirota
- Bioinformatics Institute (BII), Agency for Science and Technology (A*STAR), Matrix, Singapore
| | - Sebastian Maurer-Stroh
- Bioinformatics Institute (BII), Agency for Science and Technology (A*STAR), Matrix, Singapore.,School of Biological Sciences (SBS), Nanyang Technological University (NTU), Singapore
| | - Birgit Eisenhaber
- Bioinformatics Institute (BII), Agency for Science and Technology (A*STAR), Matrix, Singapore
| | - Frank Eisenhaber
- Bioinformatics Institute (BII), Agency for Science and Technology (A*STAR), Matrix, Singapore.,Department of Biological Sciences (DBS), National University of Singapore (NUS), Singapore.,School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore
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10
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Plasman K, Maurer-Stroh S, Ahmad J, Hao H, Kaiserman D, Sirota FL, Jonckheere V, Bird PI, Gevaert K, Van Damme P. Conservation of the extended substrate specificity profiles among homologous granzymes across species. Mol Cell Proteomics 2013; 12:2921-34. [PMID: 23788529 DOI: 10.1074/mcp.m113.028670] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
Granzymes are structurally related serine proteases involved in cell death and immunity. To date four out of five human granzymes have assigned orthologs in mice; however for granzyme H, no murine ortholog has been suggested and its role in cytotoxicity remains controversial. Here, we demonstrate that, as is the case for granzyme C, human granzyme H is an inefficient cytotoxin that together with their similar pattern of GrB divergence and functional similarity strongly hint to their orthologous relationship. Besides analyzing the substrate specificity profile of granzyme H by substrate phage display, substrate cleavage susceptibility of human granzyme H and mouse granzyme C was assessed on a proteome-wide level. The extended specificity profiles of granzymes C and H (i.e. beyond cleavage positions P4-P4') match those previously observed for granzyme B. We demonstrate conservation of these extended specificity profiles among various granzymes as granzyme B cleavage susceptibility of an otherwise granzyme H/C specific cleavage site can simply be conferred by altering the P1-residue to aspartate, the preferred P1-residue of granzyme B. Our results thus indicate a conserved, but hitherto underappreciated specificity-determining role of extended protease-substrate contacts in steering cleavage susceptibility.
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Affiliation(s)
- Kim Plasman
- Department of Medical Protein Research, VIB, B-9000 Ghent, Belgium
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11
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Sirota FL, Batagov A, Schneider G, Eisenhaber B, Eisenhaber F, Maurer-Stroh S. Beware of moving targets: reference proteome content fluctuates substantially over the years. J Bioinform Comput Biol 2012; 10:1250020. [PMID: 22867629 DOI: 10.1142/s0219720012500205] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Reference proteomes are generated by increasingly sophisticated annotation pipelines as part of regular genome build releases; yet, the corresponding changes in reference proteomes' content are dramatic. In the history of the NCBI-curated human proteome, the total number of entries has remained roughly constant but approximately half of the proteins from the 2003 build 33 are no longer represented by entries in current releases, while about the same number of new proteins have been added (for sequence identity thresholds 50-90%). Although mostly hypothetical proteins are affected, there are also spectacular cases of entry removal/addition of well studied proteins. The changes between the 2003 and recent human proteomes are in a similar order of magnitude as the differences between recent human and chimpanzee proteome releases. As an application example, we show that the proteome fluctuations affect the interpretation (about 74% of hits) of organelle-specific mass-spectrometry data. Although proteome quality tends to improve with more recent releases as, for example, the fraction of proteins with functional annotation has increased over time, existing evidence implies that, apparently, the proteome content still remains incomplete, not just pertaining to isoforms/sequence variants but also to proteins and their families that are clearly distinct.
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Affiliation(s)
- Fernanda L Sirota
- Bioinformatics Institute (BII), Agency for Science and Technology (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore.
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12
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Tan J, Kuchibhatla D, Sirota FL, Sherman WA, Gattermayer T, Kwoh CY, Eisenhaber F, Schneider G, Maurer-Stroh S. Tachyon search speeds up retrieval of similar sequences by several orders of magnitude. ACTA ACUST UNITED AC 2012; 28:1645-6. [PMID: 22531216 PMCID: PMC3371831 DOI: 10.1093/bioinformatics/bts197] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Summary: The usage of current sequence search tools becomes increasingly slower as databases of protein sequences continue to grow exponentially. Tachyon, a new algorithm that identifies closely related protein sequences ~200 times faster than standard BLAST, circumvents this limitation with a reduced database and oligopeptide matching heuristic. Availability and implementation: The tool is publicly accessible as a webserver at http://tachyon.bii.a-star.edu.sg and can also be accessed programmatically through SOAP. Contact:sebastianms@bii.a-star.edu.sg Supplementary information:Supplementary data are available at the Bioinformatics online.
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Affiliation(s)
- Joshua Tan
- Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), 30 Biopolis Street, #07-01, Matrix, 138671, Singapore
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13
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Sirota FL, Ooi HS, Gattermayer T, Schneider G, Eisenhaber F, Maurer-Stroh S. Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset. BMC Genomics 2010; 11 Suppl 1:S15. [PMID: 20158872 PMCID: PMC2822529 DOI: 10.1186/1471-2164-11-s1-s15] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2023] Open
Abstract
BACKGROUND Algorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable. RESULTS First, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended default parameters, the programs tested are producing a wide range of predictions at different levels of specificity and sensitivity. We identify settings, in which the different predictors have the same false positive rate. We assess conditions when sets of predictors can be run together to derive consensus or complementary predictions. This is useful in the framework of proteome-wide applications where high specificity is required such as in our in-house sequence analysis pipeline and the ANNIE webserver. CONCLUSIONS This work identifies parameter settings and thresholds for a selection of disorder predictors to produce comparable results at a desired level of specificity over a newly derived benchmark dataset that accounts equally for ordered and disordered regions of different lengths.
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Affiliation(s)
- Fernanda L Sirota
- Biomolecular Function Discovery Division, Bioinformatics Institute (BII), Agency for Science Technology and Research (A*STAR), Matrix, Singapore.
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14
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Schneider G, Wildpaner M, Sirota FL, Maurer-Stroh S, Eisenhaber B, Eisenhaber F. Integrated tools for biomolecular sequence-based function prediction as exemplified by the ANNOTATOR software environment. Methods Mol Biol 2010; 609:257-267. [PMID: 20221924 DOI: 10.1007/978-1-60327-241-4_15] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Given the amount of sequence data available today, in silico function prediction, which often includes detecting distant evolutionary relationships, requires sophisticated bioinformatic workflows. The algorithms behind these workflows exhibit complex data structures; they need the ability to spawn subtasks and tend to demand large amounts of resources. Performing sequence analytic tasks by manually invoking individual function prediction algorithms having to transform between differing input and output formats has become increasingly obsolete. After a period of linking individual predictors using ad hoc scripts, a number of integrated platforms are finally emerging. We present the ANNOTATOR software environment as an advanced example of such a platform.
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Affiliation(s)
- Georg Schneider
- Bioinformatics Institute, Agency for Science, Technology, and Research, Singapore
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15
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Ooi HS, Kwo CY, Wildpaner M, Sirota FL, Eisenhaber B, Maurer-Stroh S, Wong WC, Schleiffer A, Eisenhaber F, Schneider G. ANNIE: integrated de novo protein sequence annotation. Nucleic Acids Res 2009; 37:W435-40. [PMID: 19389726 PMCID: PMC2703921 DOI: 10.1093/nar/gkp254] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Function prediction of proteins with computational sequence analysis requires the use of dozens of prediction tools with a bewildering range of input and output formats. Each of these tools focuses on a narrow aspect and researchers are having difficulty obtaining an integrated picture. ANNIE is the result of years of close interaction between computational biologists and computer scientists and automates an essential part of this sequence analytic process. It brings together over 20 function prediction algorithms that have proven sufficiently reliable and indispensable in daily sequence analytic work and are meant to give scientists a quick overview of possible functional assignments of sequence segments in the query proteins. The results are displayed in an integrated manner using an innovative AJAX-based sequence viewer. ANNIE is available online at: http://annie.bii.a-star.edu.sg. This website is free and open to all users and there is no login requirement.
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16
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Malevanets A, Sirota FL, Wodak SJ. Mechanism and energy landscape of domain swapping in the B1 domain of protein G. J Mol Biol 2008; 382:223-35. [PMID: 18588900 DOI: 10.1016/j.jmb.2008.06.025] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2008] [Revised: 06/05/2008] [Accepted: 06/06/2008] [Indexed: 10/21/2022]
Abstract
Three-dimensional domain swapping has emerged as a ubiquitous process for homo-oligomer formation in many unrelated proteins, but the molecular mechanism of this process is still poorly understood. Here we present a mechanism for the swapping reaction in the B1 domain of the immunoglobulin G binding protein from group G of Streptococcus (GB1). This is a particularly attractive system for investigating the swapping process, as the swapped dimer formed by the quadruple mutant (L5V/F30V/Y33F/A34F) of GB1 was recently shown to exist in equilibrium with a monomer-like conformation over time scales of minutes. According to our mechanism, swapping in GB1 starts from the C-terminus of the polypeptide chain and progresses by exchanging an increasing portion of the chains until a stable conformational state is reached. This exchange process does not involve unfolding. Rather, the conformational changes of individual monomers and their association are tightly coupled to minimize solvent exposure and maximize the total number of native contacts at all times, thereby closely approximating the minimum energy path of the reaction. Using detailed atomic descriptions, we compute the complete free-energy profiles of the exchange reaction for the GB1 quadruple mutant that forms swapped dimers and for the wild-type protein, which is monomeric. In both GB1 forms, intermediates sample a surprisingly wide range of nearly isoenergetic association modes and hinge conformations, indicating that the exchange reaction is a non-specific process akin to encounter complex formation where the amino acid sequence plays a marginal role. The main role of the mutations in the swapping process is to destabilize the GB1 monomer state, while stabilizing the swapped dimer conformation, with non-native intersubunit interactions, fostered by mutant side chains, contributing significantly to this stabilization. Our findings are rationalized in terms of a generic swapping mechanism that involves the association of activated molecular species, and it is argued that a similar mechanism may apply to swapping in other protein systems.
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Affiliation(s)
- Anatoly Malevanets
- Department of Biochemistry, University of Toronto, Toronto, Ontario, Canada M5S 1A8.
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17
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Sirota FL, Héry-Huynh S, Maurer-Stroh S, Wodak SJ. Role of the amino acid sequence in domain swapping of the B1 domain of protein G. Proteins 2008; 72:88-104. [DOI: 10.1002/prot.21901] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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18
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Maurer-Stroh S, Koranda M, Benetka W, Schneider G, Sirota FL, Eisenhaber F. Towards complete sets of farnesylated and geranylgeranylated proteins. PLoS Comput Biol 2007; 3:e66. [PMID: 17411337 PMCID: PMC1847700 DOI: 10.1371/journal.pcbi.0030066] [Citation(s) in RCA: 118] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2006] [Accepted: 02/23/2007] [Indexed: 11/18/2022] Open
Abstract
Three different prenyltransferases attach isoprenyl anchors to C-terminal motifs in substrate proteins. These lipid anchors serve for membrane attachment or protein–protein interactions in many pathways. Although well-tolerated selective prenyltransferase inhibitors are clinically available, their mode of action remains unclear since the known substrate sets of the various prenyltransferases are incomplete. The Prenylation Prediction Suite (PrePS) has been applied for large-scale predictions of prenylated proteins. To prioritize targets for experimental verification, we rank the predictions by their functional importance estimated by evolutionary conservation of the prenylation motifs within protein families. The ranked lists of predictions are accessible as PRENbase (http://mendel.imp.univie.ac.at/sat/PrePS/PRENbase) and can be queried for verification status, type of modifying enzymes (anchor type), and taxonomic distribution. Our results highlight a large group of plant metal-binding chaperones as well as several newly predicted proteins involved in ubiquitin-mediated protein degradation, enriching the known functional repertoire of prenylated proteins. Furthermore, we identify two possibly prenylated proteins in Mimivirus. The section HumanPRENbase provides complete lists of predicted prenylated human proteins—for example, the list of farnesyltransferase targets that cannot become substrates of geranylgeranyltransferase 1 and, therefore, are especially affected by farnesyltransferase inhibitors (FTIs) used in cancer and anti-parasite therapy. We report direct experimental evidence verifying the prediction of the human proteins Prickle1, Prickle2, the BRO1 domain–containing FLJ32421 (termed BROFTI), and Rab28 (short isoform) as exclusive farnesyltransferase targets. We introduce PRENbase, a database of large-scale predictions of protein prenylation substrates ranked by evolutionary conservation of the motif. Experimental evidence is presented for the selective farnesylation of targets with an evolutionary conserved modification site. Various cellular functions require reversible membrane localization of proteins. This is often facilitated by attaching lipids to the respective proteins, thus anchoring them to the membrane. For example, addition of prenyl lipid anchors (prenylation) is directed by a motif in the protein sequence that can be predicted using a recently developed method. We describe the prediction of protein prenylation in all currently known proteins. The annotated results are available as an online database: PRENbase. A ranking of the predictions is introduced, assuming that existence of a prenylation sequence motif in related proteins from different species (evolutionary conservation) relates to functional importance of the lipid anchor. We present experimental evidence for high-ranked human proteins predicted to be affected by anticancer drugs inhibiting prenylation.
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Maurer-Stroh S, Gouda M, Novatchkova M, Schleiffer A, Schneider G, Sirota FL, Wildpaner M, Hayashi N, Eisenhaber F. MYRbase: analysis of genome-wide glycine myristoylation enlarges the functional spectrum of eukaryotic myristoylated proteins. Genome Biol 2004; 5:R21. [PMID: 15003124 PMCID: PMC395771 DOI: 10.1186/gb-2004-5-3-r21] [Citation(s) in RCA: 70] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2003] [Revised: 12/17/2003] [Accepted: 01/08/2004] [Indexed: 11/25/2022] Open
Abstract
We evaluated the evolutionary conservation of glycine myristoylation within eukaryotic sequences. Our large-scale cross-genome analyses, available as MYRbase, show that the functional spectrum of myristoylated proteins is currently largely underestimated. We give experimental evidence for in vitro myristoylation of selected predictions. Furthermore, we classify five membrane-attachment factors that occur most frequently in combination with, or even replacing, myristoyl anchors, as some protein family examples show.
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Affiliation(s)
- Sebastian Maurer-Stroh
- IMP Research Institute of Molecular Pathology, Dr, Bohr-Gasse 7, A-1030 Vienna, Austria.
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Abstract
The intracellular linker L(III-IV) of voltage-gated sodium channels is known to be involved in their mechanism of inactivation. Its primary sequence is well conserved in sodium channels from different tissues and species. However, the role of charged residues in this region, first thought to play an important role in inactivation, has not been well identified, whereas the IFM triad (I1488-M1490) has been characterized as the crucial element for inactivation. In this work, we constructed theoretical models and performed molecular dynamics simulations, exploring the role of L(III-IV)-charged residues in the presence of a polar/nonpolar planar interface represented by a dielectric discontinuity. From structural predictions, two alpha-helical segments are proposed. Moreover, from dynamics simulations, a time-conserved motif is detected and shown to play a relevant role in guiding the inactivation particle toward its receptor site.
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Affiliation(s)
- Fernanda L Sirota
- Instituto de Biofísica Carlos Chagas Filho UFRJ - Universidade Federal do Rio de Janeiro, Brazil
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