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Iori S, D'Onofrio C, Laham-Karam N, Mushimiyimana I, Lucatello L, Montanucci L, Lopparelli RM, Bonsembiante F, Capolongo F, Pauletto M, Dacasto M, Giantin M. Generation and characterization of cytochrome P450 3A74 CRISPR/Cas9 knockout bovine foetal hepatocyte cell line (BFH12). Biochem Pharmacol 2024; 224:116231. [PMID: 38648904 DOI: 10.1016/j.bcp.2024.116231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 04/04/2024] [Accepted: 04/19/2024] [Indexed: 04/25/2024]
Abstract
In human, the cytochrome P450 3A (CYP3A) subfamily of drug-metabolizing enzymes (DMEs) is responsible for a significant number of phase I reactions, with the CYP3A4 isoform superintending the hepatic and intestinal metabolism of diverse endobiotic and xenobiotic compounds. The CYP3A4-dependent bioactivation of chemicals may result in hepatotoxicity and trigger carcinogenesis. In cattle, four CYP3A genes (CYP3A74, CYP3A76, CYP3A28 and CYP3A24) have been identified. Despite cattle being daily exposed to xenobiotics (e.g., mycotoxins, food additives, drugs and pesticides), the existing knowledge about the contribution of CYP3A in bovine hepatic metabolism is still incomplete. Nowadays, CRISPR/Cas9 mediated knockout (KO) is a valuable method to generate in vivo and in vitro models for studying the metabolism of xenobiotics. In the present study, we successfully performed CRISPR/Cas9-mediated KO of bovine CYP3A74, human CYP3A4-like, in a bovine foetal hepatocyte cell line (BFH12). After clonal expansion and selection, CYP3A74 ablation was confirmed at the DNA, mRNA, and protein level. The subsequent characterization of the CYP3A74 KO clone highlighted significant transcriptomic changes (RNA-sequencing) associated with the regulation of cell cycle and proliferation, immune and inflammatory response, as well as metabolic processes. Overall, this study successfully developed a new CYP3A74 KO in vitro model by using CRISPR/Cas9 technology, which represents a novel resource for xenobiotic metabolism studies in cattle. Furthermore, the transcriptomic analysis suggests a key role of CYP3A74 in bovine hepatocyte cell cycle regulation and metabolic homeostasis.
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Affiliation(s)
- Silvia Iori
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Caterina D'Onofrio
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Nihay Laham-Karam
- University of Eastern Finland, A.I. Virtanen Institute for Molecular Sciences, Neulaniementie 2, 70211 Kuopio, Finland
| | - Isidore Mushimiyimana
- University of Eastern Finland, A.I. Virtanen Institute for Molecular Sciences, Neulaniementie 2, 70211 Kuopio, Finland
| | - Lorena Lucatello
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Ludovica Montanucci
- Department of Neurology, University of Texas Health Science Center, 6431 Fannin Street, Houston, TX, OH 44106, USA
| | - Rosa Maria Lopparelli
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Federico Bonsembiante
- Department of Animal Medicine, Production and Health, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Francesca Capolongo
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Marianna Pauletto
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Mauro Dacasto
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy
| | - Mery Giantin
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell'Università 16, Legnaro, 35020 Padua, Italy.
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Montanucci L, Brünger T, Bhattarai N, Boßelmann CM, Kim S, Allen JP, Zhang J, Klöckner C, Fariselli P, May P, Lemke JR, Myers SJ, Yuan H, Traynelis SF, Lal D. Distances from ligands as main predictive features for pathogenicity and functional effect of variants in NMDA receptors. medRxiv 2024:2024.05.06.24306939. [PMID: 38766179 PMCID: PMC11100844 DOI: 10.1101/2024.05.06.24306939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic variants in genes GRIN1 , GRIN2A , GRIN2B , and GRIN2D , which encode subunits of the N-methyl-D-aspartate receptor (NMDAR), have been associated with severe and heterogeneous neurologic diseases. Missense variants in these genes can result in gain or loss of the NMDAR function, requiring opposite therapeutic treatments. Computational methods that predict pathogenicity and molecular functional effects are therefore crucial for accurate diagnosis and therapeutic applications. We assembled missense variants: 201 from patients, 631 from general population, and 159 characterized by electrophysiological readouts showing whether they can enhance or reduce the receptor function. This includes new functional data from 47 variants reported here, for the first time. We found that pathogenic/benign variants and variants that increase/decrease the channel function were distributed unevenly on the protein structure, with spatial proximity to ligands bound to the agonist and antagonist binding sites being key predictive features. Leveraging distances from ligands, we developed two independent machine learning-based predictors for NMDAR missense variants: a pathogenicity predictor which outperforms currently available predictors (AUC=0.945, MCC=0.726), and the first binary predictor of molecular function (increase or decrease) (AUC=0.809, MCC=0.523). Using these, we reclassified variants of uncertain significance in the ClinVar database and refined a previous genome-informed epidemiological model to estimate the birth incidence of molecular mechanism-defined GRIN disorders. Our findings demonstrate that distance from ligands is an important feature in NMDARs that can enhance variant pathogenicity prediction and enable functional prediction. Further studies with larger numbers of phenotypically and functionally characterized variants will enhance the potential clinical utility of this method.
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Montanucci L, Brünger T, Lal D. Reply: Follow the allosteric transitions to predict variant pathogenicity: a channel-specific approach. Brain 2024; 147:e41-e42. [PMID: 38207091 DOI: 10.1093/brain/awae009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 12/19/2023] [Indexed: 01/13/2024] Open
Affiliation(s)
- Ludovica Montanucci
- Department of Neurology, McGovern Medical School at UTHealth Houston, Houston, TX 77030, USA
- Center for Neurogenetics, UTHealth Houston, Houston, TX 77030, USA
| | - Tobias Brünger
- Cologne Center for Genomics (CCG), University of Cologne, Cologne 50937, Germany
| | - Dennis Lal
- Department of Neurology, McGovern Medical School at UTHealth Houston, Houston, TX 77030, USA
- Center for Neurogenetics, UTHealth Houston, Houston, TX 77030, USA
- Cologne Center for Genomics (CCG), University of Cologne, Cologne 50937, Germany
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Stanley Center of Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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Stefanski A, Pérez-Palma E, Brünger T, Montanucci L, Gati C, Klöckner C, Johannesen KM, Goodspeed K, Macnee M, Deng AT, Aledo-Serrano Á, Borovikov A, Kava M, Bouman AM, Hajianpour MJ, Pal DK, Engelen M, Hagebeuk EEO, Shinawi M, Heidlebaugh AR, Oetjens K, Hoffman TL, Striano P, Freed AS, Futtrup L, Balslev T, Abulí A, Danvoye L, Lederer D, Balci T, Nouri MN, Butler E, Drewes S, van Engelen K, Howell KB, Khoury J, May P, Trinidad M, Froelich S, Lemke JR, Tiller J, Freed AN, Kang JQ, Wuster A, Møller RS, Lal D. SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis. Brain 2023; 146:5198-5208. [PMID: 37647852 PMCID: PMC10689929 DOI: 10.1093/brain/awad292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 06/05/2023] [Accepted: 07/08/2023] [Indexed: 09/01/2023] Open
Abstract
Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).
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Affiliation(s)
- Arthur Stefanski
- Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Eduardo Pérez-Palma
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, Santiago de Chile 7610658, Chile
| | - Tobias Brünger
- Cologne Center for Genomics (CCG), Medical Faculty of the University of Cologne, University Hospital of Cologne, Cologne 50931, Germany
| | - Ludovica Montanucci
- Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Cornelius Gati
- Department of Biological Sciences, Bridge Institute, USC Michelson Center for Convergent Bioscience, University of Southern California, Los Angeles, CA 90089, USA
| | - Chiara Klöckner
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig 04103, Germany
| | - Katrine M Johannesen
- Department of Epilepsy Genetics and Personalized Medicine, The Danish Epilepsy Centre, Dianalund 4293, Denmark
- Department of Genetics, University Hospital of Copenhagen, Rigshispitalet, Copenhagen 2100, Denmark
| | - Kimberly Goodspeed
- Children’s Health, Medical Center, Dallas, TX 75235, USA
- Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Marie Macnee
- Cologne Center for Genomics (CCG), Medical Faculty of the University of Cologne, University Hospital of Cologne, Cologne 50931, Germany
| | - Alexander T Deng
- Clinical Genetics, Guys and St Thomas NHS Trust, London SE19RT, UK
| | - Ángel Aledo-Serrano
- Epilepsy Program, Neurology Department, Hospital Ruber Internacional, Madrid 28034, Spain
| | - Artem Borovikov
- Research and Counseling Department, Research Centre for Medical Genetics, Moscow 115478, Russia
| | - Maina Kava
- Department of Neurology and Metabolic Medicine, Perth Children’s Hospital, Perth 6009, Australia
- School of Paediatrics and Child Health, UWA Medical School, University of Western Australia, Perth 6009, Australia
| | - Arjan M Bouman
- Department of Clinical Genetics, Erasmus MC, University Medical Center, Rotterdam 3015GD, The Netherlands
| | - M J Hajianpour
- Department of Pediatrics, Division of Medical Genetics and Genomics, Albany Medical College, Albany Med Health System, Albany, NY 12208, USA
| | - Deb K Pal
- Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College, London SE58AF, UK
- Department of Basic and Clinical Neurosciences, King’s College Hospital, London SE59RS, UK
| | - Marc Engelen
- Department of Pediatric Neurology, Amsterdam Public Health, Amsterdam University Medical Center, Amsterdam 1081HV, The Netherlands
| | - Eveline E O Hagebeuk
- Department of Pediatric Neurology, Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede and Zwolle 2103SW, The Netherlands
| | - Marwan Shinawi
- Division of Genetics and Genomic Medicine, Department of Pediatrics, St.Louis Children’s Hospital, Washington University School of Medicine, St. Louis, MO 63110, USA
| | | | - Kathryn Oetjens
- Autism and Developmental Medicine Institute, Geisinger, Danville, PA 17837, USA
| | - Trevor L Hoffman
- Department of Regional Genetics, Anaheim, Southern California Kaiser Permanente Medical Group, CA 92806, USA
| | - Pasquale Striano
- Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto Giannina Gaslini, Genoa 16147, Italy
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa 16132, Italy
| | - Amanda S Freed
- Department of Clinical Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, CA 91101, USA
| | - Line Futtrup
- Department of Paediatrics, Regional Hospital of Central Jutland, Viborg 8800, Denmark
| | - Thomas Balslev
- Department of Paediatrics, Regional Hospital of Central Jutland, Viborg 8800, Denmark
- Centre for Educational Development, Aarhus University, Aarhus 8200, Denmark
| | - Anna Abulí
- Department of Clinical and Molecular Genetics and Medicine Genetics Group, VHIR, University Hospital Vall d’Hebron, Barcelona 08035, Spain
| | - Leslie Danvoye
- Department of Neurology, Université catholique de Louvain, Cliniques universitaires Saint-Luc, Brussels 1200, Belgium
| | - Damien Lederer
- Centre for Human Genetics, Institute for Pathology and Genetics, Gosselies 6041, Belgium
| | - Tugce Balci
- Department of Pediatrics, Division of Medical Genetics, Western University, London, ON N6A3K7, Canada
- Medical Genetics Program of Southwestern Ontario, London Health Sciences Centre and Children's Health Research Institute, London, ON N6A5A5, Canada
| | - Maryam Nabavi Nouri
- Department of Paediatrics, Division of Pediatric Neurology, London Health Sciences Centre, London, ON N6A5W9, Canada
| | | | - Sarah Drewes
- Department of Medical Genetics, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, PA 15224, USA
| | - Kalene van Engelen
- Medical Genetics Program of Southwestern Ontario, London Health Sciences Centre, London, ON N6A5W9, Canada
| | - Katherine B Howell
- Department of Neurology, Royal Children’s Hospital, Melbourne, VIC 3052, Australia
- Department of Pediatrics, University of Melbourne, Melbourne, VIC 3052, Australia
- Murdoch Children’s Research Institute, Melbourne, VIC 3052, Australia
| | - Jean Khoury
- Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette 4362, Luxembourg
| | - Marena Trinidad
- Translational Genomics, BioMarin Pharmaceutical Inc., Novato, CA 94949, USA
| | - Steven Froelich
- Translational Genomics, BioMarin Pharmaceutical Inc., Novato, CA 94949, USA
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig 04103, Germany
- Center for Rare Diseases, University of Leipzig Medical Center, Leipzig 04103, Germany
| | | | | | - Jing-Qiong Kang
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37240, USA
- Neuroscience Graduate Program, Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurology, Vanderbilt Brain Institute, Nashville, TN 37235, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
- Vanderbilt Kennedy Center of Human Development, Nashville, TN 37203, USA
| | - Arthur Wuster
- Translational Genomics, BioMarin Pharmaceutical Inc., Novato, CA 94949, USA
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Medicine, The Danish Epilepsy Centre, Dianalund 4293, Denmark
- Department of Regional Health Research, University of Southern Denmark, Odense 5000, Denmark
| | - Dennis Lal
- Genomic Medicine Institute and Epilepsy Center, Cleveland Clinic, Cleveland, OH 44195, USA
- Stanley Center of Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Neurology, University of Texas Health Sciences Center at Houston, Houston, TX 77030, USA
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5
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Pauletto M, Giantin M, Tolosi R, Bassan I, Bardhi A, Barbarossa A, Montanucci L, Zaghini A, Dacasto M. Discovering the Protective Effects of Quercetin on Aflatoxin B1-Induced Toxicity in Bovine Foetal Hepatocyte-Derived Cells (BFH12). Toxins (Basel) 2023; 15:555. [PMID: 37755981 PMCID: PMC10534839 DOI: 10.3390/toxins15090555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/24/2023] [Accepted: 09/01/2023] [Indexed: 09/28/2023] Open
Abstract
Aflatoxin B1 (AFB1) induces lipid peroxidation and mortality in bovine foetal hepatocyte-derived cells (BFH12), with underlying transcriptional perturbations associated mainly with cancer, cellular damage, inflammation, bioactivation, and detoxification pathways. In this cell line, curcumin and resveratrol have proven to be effective in mitigating AFB1-induced toxicity. In this paper, we preliminarily assessed the potential anti-AFB1 activity of a natural polyphenol, quercetin (QUE), in BFH12 cells. To this end, we primarily measured QUE cytotoxicity using a WST-1 reagent. Then, we pre-treated the cells with QUE and exposed them to AFB1. The protective role of QUE was evaluated by measuring cytotoxicity, transcriptional changes (RNA-sequencing), lipid peroxidation (malondialdehyde production), and targeted post-transcriptional modifications (NQO1 and CYP3A enzymatic activity). The results demonstrated that QUE, like curcumin and resveratrol, reduced AFB1-induced cytotoxicity and lipid peroxidation and caused larger transcriptional variations than AFB1 alone. Most of the differentially expressed genes were involved in lipid homeostasis, inflammatory and immune processes, and carcinogenesis. As for enzymatic activities, QUE significantly reverted CYP3A variations induced by AFB1, but not those of NQO1. This study provides new knowledge about key molecular mechanisms involved in QUE-mediated protection against AFB1 toxicity and encourages in vivo studies to assess QUE's bioavailability and beneficial effects on aflatoxicosis.
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Affiliation(s)
- Marianna Pauletto
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell’Università 16, I-35020 Legnaro, Italy; (M.G.); (R.T.); (I.B.); (M.D.)
| | - Mery Giantin
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell’Università 16, I-35020 Legnaro, Italy; (M.G.); (R.T.); (I.B.); (M.D.)
| | - Roberta Tolosi
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell’Università 16, I-35020 Legnaro, Italy; (M.G.); (R.T.); (I.B.); (M.D.)
| | - Irene Bassan
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell’Università 16, I-35020 Legnaro, Italy; (M.G.); (R.T.); (I.B.); (M.D.)
| | - Anisa Bardhi
- Department of Veterinary Medical Sciences, Alma Mater Studiorum—University of Bologna, Via Tolara di Sopra 50, Ozzano dell’Emilia, I-40064 Bologna, Italy; (A.B.); (A.B.); (A.Z.)
| | - Andrea Barbarossa
- Department of Veterinary Medical Sciences, Alma Mater Studiorum—University of Bologna, Via Tolara di Sopra 50, Ozzano dell’Emilia, I-40064 Bologna, Italy; (A.B.); (A.B.); (A.Z.)
| | - Ludovica Montanucci
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA;
| | - Anna Zaghini
- Department of Veterinary Medical Sciences, Alma Mater Studiorum—University of Bologna, Via Tolara di Sopra 50, Ozzano dell’Emilia, I-40064 Bologna, Italy; (A.B.); (A.B.); (A.Z.)
| | - Mauro Dacasto
- Department of Comparative Biomedicine and Food Science, University of Padua, Viale dell’Università 16, I-35020 Legnaro, Italy; (M.G.); (R.T.); (I.B.); (M.D.)
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6
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Montanucci L, Lewis-Smith D, Collins RL, Niestroj LM, Parthasarathy S, Xian J, Ganesan S, Macnee M, Brünger T, Thomas RH, Talkowski M, Helbig I, Leu C, Lal D. Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals. Nat Commun 2023; 14:4392. [PMID: 37474567 PMCID: PMC10359300 DOI: 10.1038/s41467-023-39539-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 06/16/2023] [Indexed: 07/22/2023] Open
Abstract
Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice.
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Affiliation(s)
- Ludovica Montanucci
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, USA
| | - David Lewis-Smith
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Clinical Neurosciences, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.) and Harvard, Cambridge, USA
| | | | - Shridhar Parthasarathy
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Julie Xian
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Shiva Ganesan
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marie Macnee
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
| | - Tobias Brünger
- Cologne Center for Genomics, University of Cologne, Cologne, Germany
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Clinical Neurosciences, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Michael Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, USA
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.) and Harvard, Cambridge, USA
| | - Ingo Helbig
- The Epilepsy NeuroGenetics Initiative, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Biomedical and Health Informatics (DBHi), Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Neurology, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Costin Leu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, USA.
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK.
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and M.I.T, Cambridge, MA, USA.
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, US.
| | - Dennis Lal
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, USA.
- Program in Medical and Population Genetics, Broad Institute of Massachusetts Institute of Technology (M.I.T.) and Harvard, Cambridge, USA.
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and M.I.T, Cambridge, MA, USA.
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, US.
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7
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Pietropoli E, Pauletto M, Tolosi R, Iori S, Lopparelli RM, Montanucci L, Giantin M, Dacasto M, De Liguoro M. An In Vivo Whole-Transcriptomic Approach to Assess Developmental and Reproductive Impairments Caused by Flumequine in Daphnia magna. Int J Mol Sci 2023; 24:ijms24119396. [PMID: 37298348 DOI: 10.3390/ijms24119396] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/17/2023] [Accepted: 05/24/2023] [Indexed: 06/12/2023] Open
Abstract
Among veterinary antibiotics, flumequine (FLU) is still widely used in aquaculture due to its efficacy and cost-effectiveness. Although it was synthesized more than 50 years ago, a complete toxicological framework of possible side effects on non-target species is still far from being achieved. The aim of this research was to investigate the FLU molecular mechanisms in Daphnia magna, a planktonic crustacean recognized as a model species for ecotoxicological studies. Two different FLU concentrations (2.0 mg L-1 and 0.2 mg L-1) were assayed in general accordance with OECD Guideline 211, with some proper adaptations. Exposure to FLU (2.0 mg L-1) caused alteration of phenotypic traits, with a significant reduction in survival rate, body growth, and reproduction. The lower concentration (0.2 mg L-1) did not affect phenotypic traits but modulated gene expression, an effect which was even more evident under the higher exposure level. Indeed, in daphnids exposed to 2.0 mg L-1 FLU, several genes related with growth, development, structural components, and antioxidant response were significantly modulated. To the best of our knowledge, this is the first work showing the impact of FLU on the transcriptome of D. magna.
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Affiliation(s)
- Edoardo Pietropoli
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Marianna Pauletto
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Roberta Tolosi
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Silvia Iori
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Rosa Maria Lopparelli
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Ludovica Montanucci
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Mery Giantin
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Mauro Dacasto
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
| | - Marco De Liguoro
- Department Comparative Biomedicine and Food Science, University of Padova, 35020 Padova, Italy
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8
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Macnee M, Pérez-Palma E, Brünger T, Klöckner C, Platzer K, Stefanski A, Montanucci L, Bayat A, Radtke M, Collins RL, Talkowski M, Blankenberg D, Møller RS, Lemke JR, Nothnagel M, May P, Lal D. CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online. Bioinformatics 2023; 39:btad290. [PMID: 37104749 PMCID: PMC10174702 DOI: 10.1093/bioinformatics/btad290] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 01/17/2023] [Accepted: 04/26/2023] [Indexed: 04/29/2023] Open
Abstract
MOTIVATION Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts. RESULTS Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators' patient care and for basic scientists' translational genomic research. AVAILABILITY AND IMPLEMENTATION The web application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.
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Affiliation(s)
- Marie Macnee
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
| | - Eduardo Pérez-Palma
- Universidad del Desarrollo, Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, Santiago, Chile
| | - Tobias Brünger
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
| | - Chiara Klöckner
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Konrad Platzer
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Arthur Stefanski
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ludovica Montanucci
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Allan Bayat
- Department of Epilepsy Genetics and Personalized Medicine, Member of ERN Epicare, Danish Epilepsy Centre, Dianalund, Denmark
- Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Maximilian Radtke
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Ryan L Collins
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael Talkowski
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Blankenberg
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Medicine, Member of ERN Epicare, Danish Epilepsy Centre, Dianalund, Denmark
- Department of Regional Health Research, Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig, Germany
| | - Michael Nothnagel
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
- University Hospital Cologne, Cologne, Germany
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Dennis Lal
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
- Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA
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9
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Brünger T, Pérez-Palma E, Montanucci L, Nothnagel M, Møller RS, Schorge S, Zuberi S, Symonds J, Lemke JR, Brunklaus A, Traynelis SF, May P, Lal D. Conserved patterns across ion channels correlate with variant pathogenicity and clinical phenotypes. Brain 2023; 146:923-934. [PMID: 36036558 PMCID: PMC9976975 DOI: 10.1093/brain/awac305] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 07/29/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Clinically identified genetic variants in ion channels can be benign or cause disease by increasing or decreasing the protein function. As a consequence, therapeutic decision-making is challenging without molecular testing of each variant. Our biophysical knowledge of ion-channel structures and function is just emerging, and it is currently not well understood which amino acid residues cause disease when mutated. We sought to systematically identify biological properties associated with variant pathogenicity across all major voltage and ligand-gated ion-channel families. We collected and curated 3049 pathogenic variants from hundreds of neurodevelopmental and other disorders and 12 546 population variants for 30 ion channel or channel subunits for which a high-quality protein structure was available. Using a wide range of bioinformatics approaches, we computed 163 structural features and tested them for pathogenic variant enrichment. We developed a novel 3D spatial distance scoring approach that enables comparisons of pathogenic and population variant distribution across protein structures. We discovered and independently replicated that several pore residue properties and proximity to the pore axis were most significantly enriched for pathogenic variants compared to population variants. Using our 3D scoring approach, we showed that the strongest pathogenic variant enrichment was observed for pore-lining residues and alpha-helix residues within 5Å distance from the pore axis centre and not involved in gating. Within the subset of residues located at the pore, the hydrophobicity of the pore was the feature most strongly associated with variant pathogenicity. We also found an association between the identified properties and both clinical phenotypes and functional in vitro assays for voltage-gated sodium channels (SCN1A, SCN2A, SCN8A) and N-methyl-D-aspartate receptor (GRIN1, GRIN2A, GRIN2B) encoding genes. In an independent expert-curated dataset of 1422 neurodevelopmental disorder pathogenic patient variants and 679 electrophysiological experiments, we show that pore axis distance is associated with seizure age of onset and cognitive performance as well as differential gain versus loss-of-channel function. In summary, we identified biological properties associated with ion-channel malfunction and show that these are correlated with in vitro functional readouts and clinical phenotypes in patients with neurodevelopmental disorders. Our results suggest that clinical decision support algorithms that predict variant pathogenicity and function are feasible in the future.
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Affiliation(s)
- Tobias Brünger
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
| | - Eduardo Pérez-Palma
- Centro de Genética y Genómica, Facultad de Medicina Clínica Alemana, Universidad de Desarrollo, Santiago 7590943, Chile
| | - Ludovica Montanucci
- Lerner Research Institute Cleveland Clinic, Genomic Medicine Institute, Cleveland, OH 44195, USA
| | - Michael Nothnagel
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
- University Hospital Cologne, 50937 Cologne, Germany
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Treatment, the Danish Epilepsy Center, DK 4293 Dianalund, Denmark
| | - Stephanie Schorge
- Department of Neuroscience, Physiology and Pharmacology, UCL, London WC1E 6BT, UK
| | - Sameer Zuberi
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Joseph Symonds
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Center for Rare Diseases, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Andreas Brunklaus
- The Paediatric Neurosciences Research Group, Royal Hospital for Children, Glasgow, UK
- Institute of Health and Wellbeing, University of Glasgow, UK
| | - Stephen F Traynelis
- Department of Pharmacology, Emory University School of Medicine, Rollins Research Center, Atlanta, GA 30322-3090, USA
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg
| | - Dennis Lal
- Cologne Center for Genomics, University of Cologne, 50931 Cologne, Germany
- Lerner Research Institute Cleveland Clinic, Genomic Medicine Institute, Cleveland, OH 44195, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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10
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Montanucci L, Capriotti E, Birolo G, Benevenuta S, Pancotti C, Lal D, Fariselli P. DDGun: an untrained predictor of protein stability changes upon amino acid variants. Nucleic Acids Res 2022; 50:W222-W227. [PMID: 35524565 PMCID: PMC9252764 DOI: 10.1093/nar/gkac325] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/15/2022] [Accepted: 05/04/2022] [Indexed: 01/22/2023] Open
Abstract
Estimating the functional effect of single amino acid variants in proteins is fundamental for predicting the change in the thermodynamic stability, measured as the difference in the Gibbs free energy of unfolding, between the wild-type and the variant protein (ΔΔG). Here, we present the web-server of the DDGun method, which was previously developed for the ΔΔG prediction upon amino acid variants. DDGun is an untrained method based on basic features derived from evolutionary information. It is antisymmetric, as it predicts opposite ΔΔG values for direct (A → B) and reverse (B → A) single and multiple site variants. DDGun is available in two versions, one based on only sequence information and the other one based on sequence and structure information. Despite being untrained, DDGun reaches prediction performances comparable to those of trained methods. Here we make DDGun available as a web server. For the web server version, we updated the protein sequence database used for the computation of the evolutionary features, and we compiled two new data sets of protein variants to do a blind test of its performances. On these blind data sets of single and multiple site variants, DDGun confirms its prediction performance, reaching an average correlation coefficient between experimental and predicted ΔΔG of 0.45 and 0.49 for the sequence-based and structure-based versions, respectively. Besides being used for the prediction of ΔΔG, we suggest that DDGun should be adopted as a benchmark method to assess the predictive capabilities of newly developed methods. Releasing DDGun as a web-server, stand-alone program and docker image will facilitate the necessary process of method comparison to improve ΔΔG prediction.
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Affiliation(s)
- Ludovica Montanucci
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Emidio Capriotti
- BioFolD Unit, Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy
| | - Giovanni Birolo
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy
| | - Silvia Benevenuta
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy
| | - Corrado Pancotti
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy
| | - Dennis Lal
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
| | - Piero Fariselli
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126, Torino, Italy
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11
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Lucatello L, Merlanti R, De Jesus Inacio L, Bisutti V, Montanucci L, Capolongo F. Pyrrolizidine alkaloid concentrations in local Italian and retail honeys of different origin: A scenario of human exposure. J Food Compost Anal 2021. [DOI: 10.1016/j.jfca.2021.104182] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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12
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Sanavia T, Birolo G, Montanucci L, Turina P, Capriotti E, Fariselli P. Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine. Comput Struct Biotechnol J 2020; 18:1968-1979. [PMID: 32774791 PMCID: PMC7397395 DOI: 10.1016/j.csbj.2020.07.011] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [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: 03/15/2020] [Revised: 07/10/2020] [Accepted: 07/14/2020] [Indexed: 12/13/2022] Open
Abstract
Protein stability predictions are becoming essential in medicine to develop novel immunotherapeutic agents and for drug discovery. Despite the large number of computational approaches for predicting the protein stability upon mutation, there are still critical unsolved problems: 1) the limited number of thermodynamic measurements for proteins provided by current databases; 2) the large intrinsic variability of ΔΔG values due to different experimental conditions; 3) biases in the development of predictive methods caused by ignoring the anti-symmetry of ΔΔG values between mutant and native protein forms; 4) over-optimistic prediction performance, due to sequence similarity between proteins used in training and test datasets. Here, we review these issues, highlighting new challenges required to improve current tools and to achieve more reliable predictions. In addition, we provide a perspective of how these methods will be beneficial for designing novel precision medicine approaches for several genetic disorders caused by mutations, such as cancer and neurodegenerative diseases.
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Affiliation(s)
- Tiziana Sanavia
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy
| | - Giovanni Birolo
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy
| | - Ludovica Montanucci
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Viale dell'Università 16, 35020 Legnaro, Italy
| | - Paola Turina
- Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy
| | - Emidio Capriotti
- Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy
| | - Piero Fariselli
- Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy
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13
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Capriotti E, Montanucci L, Profiti G, Rossi I, Giannuzzi D, Aresu L, Fariselli P. Fido-SNP: the first webserver for scoring the impact of single nucleotide variants in the dog genome. Nucleic Acids Res 2020; 47:W136-W141. [PMID: 31114899 PMCID: PMC6602425 DOI: 10.1093/nar/gkz420] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2019] [Revised: 04/19/2019] [Accepted: 05/06/2019] [Indexed: 12/22/2022] Open
Abstract
As the amount of genomic variation data increases, tools that are able to score the functional impact of single nucleotide variants become more and more necessary. While there are several prediction servers available for interpreting the effects of variants in the human genome, only few have been developed for other species, and none were specifically designed for species of veterinary interest such as the dog. Here, we present Fido-SNP the first predictor able to discriminate between Pathogenic and Benign single-nucleotide variants in the dog genome. Fido-SNP is a binary classifier based on the Gradient Boosting algorithm. It is able to classify and score the impact of variants in both coding and non-coding regions based on sequence features within seconds. When validated on a previously unseen set of annotated variants from the OMIA database, Fido-SNP reaches 88% overall accuracy, 0.77 Matthews correlation coefficient and 0.91 Area Under the ROC Curve.
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Affiliation(s)
- Emidio Capriotti
- BioFolD Unit, Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via F. Selmi 3, 40126 Bologna, Italy
| | - Ludovica Montanucci
- Department of Comparative Biomedicine and Food Science. University of Padova, Viale dell'Università, 16, 35020 Legnaro (Padova), Italy
| | - Giuseppe Profiti
- BioDec srl. Via Calzavecchio 20, 40033 Casalecchio di Reno (Bologna), Italy
| | - Ivan Rossi
- BioDec srl. Via Calzavecchio 20, 40033 Casalecchio di Reno (Bologna), Italy
| | - Diana Giannuzzi
- Department of Comparative Biomedicine and Food Science. University of Padova, Viale dell'Università, 16, 35020 Legnaro (Padova), Italy
| | - Luca Aresu
- Department of Veterinary Sciences, University of Torino, Largo P. Braccini 2, 10095 Grugliasco, (Torino), Italy
| | - Piero Fariselli
- Department of Comparative Biomedicine and Food Science. University of Padova, Viale dell'Università, 16, 35020 Legnaro (Padova), Italy.,Department of Medical Sciences, University of Torino, Via Santena 19, 10126 Torino, Italy
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14
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Dobon B, Montanucci L, Peretó J, Bertranpetit J, Laayouni H. Gene connectivity and enzyme evolution in the human metabolic network. Biol Direct 2019; 14:17. [PMID: 31481097 PMCID: PMC6724310 DOI: 10.1186/s13062-019-0248-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [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: 02/22/2019] [Accepted: 08/21/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Determining the factors involved in the likelihood of a gene being under adaptive selection is still a challenging goal in Evolutionary Biology. Here, we perform an evolutionary analysis of the human metabolic genes to explore the associations between network structure and the presence and strength of natural selection in the genes whose products are involved in metabolism. Purifying and positive selection are estimated at interspecific (among mammals) and intraspecific (among human populations) levels, and the connections between enzymatic reactions are differentiated between incoming (in-degree) and outgoing (out-degree) links. RESULTS We confirm that purifying selection has been stronger in highly connected genes. Long-term positive selection has targeted poorly connected enzymes, whereas short-term positive selection has targeted different enzymes depending on whether the selective sweep has reached fixation in the population: genes under a complete selective sweep are poorly connected, whereas those under an incomplete selective sweep have high out-degree connectivity. The last steps of pathways are more conserved due to stronger purifying selection, with long-term positive selection targeting preferentially enzymes that catalyze the first steps. However, short-term positive selection has targeted enzymes that catalyze the last steps in the metabolic network. Strong signals of positive selection have been found for metabolic processes involved in lipid transport and membrane fluidity and permeability. CONCLUSIONS Our analysis highlights the importance of analyzing the same biological system at different evolutionary timescales to understand the evolution of metabolic genes and of distinguishing between incoming and outgoing links in a metabolic network. Short-term positive selection has targeted enzymes with a different connectivity profile depending on the completeness of the selective sweep, while long-term positive selection has targeted genes with fewer connections that code for enzymes that catalyze the first steps in the network. REVIEWERS This article was reviewed by Diamantis Sellis and Brandon Invergo.
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Affiliation(s)
- Begoña Dobon
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader 88, 08003, Barcelona, Catalonia, Spain
| | - Ludovica Montanucci
- Dipartimento di Biomedicina Comparata e Alimentazione, Università degli Studi di Padova, Padua, Italy
| | - Juli Peretó
- Institute for Integrative Systems Biology I2SysBio (University of Valencia-CSIC) and Department of Biochemistry and Molecular Biology, University of Valencia, Valencia, Spain
| | - Jaume Bertranpetit
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader 88, 08003, Barcelona, Catalonia, Spain.
| | - Hafid Laayouni
- Institut de Biologia Evolutiva (UPF-CSIC), Universitat Pompeu Fabra, Dr. Aiguader 88, 08003, Barcelona, Catalonia, Spain. .,Bioinformatics Studies, ESCI-UPF, Pg.Pujades 1, 08003, Barcelona, Catalonia, Spain.
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15
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Montanucci L, Capriotti E, Frank Y, Ben-Tal N, Fariselli P. DDGun: an untrained method for the prediction of protein stability changes upon single and multiple point variations. BMC Bioinformatics 2019; 20:335. [PMID: 31266447 PMCID: PMC6606456 DOI: 10.1186/s12859-019-2923-1] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [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] [Indexed: 12/20/2022] Open
Abstract
Background Predicting the effect of single point variations on protein stability constitutes a crucial step toward understanding the relationship between protein structure and function. To this end, several methods have been developed to predict changes in the Gibbs free energy of unfolding (∆∆G) between wild type and variant proteins, using sequence and structure information. Most of the available methods however do not exhibit the anti-symmetric prediction property, which guarantees that the predicted ∆∆G value for a variation is the exact opposite of that predicted for the reverse variation, i.e., ∆∆G(A → B) = −∆∆G(B → A), where A and B are amino acids. Results Here we introduce simple anti-symmetric features, based on evolutionary information, which are combined to define an untrained method, DDGun (DDG untrained). DDGun is a simple approach based on evolutionary information that predicts the ∆∆G for single and multiple variations from sequence and structure information (DDGun3D). Our method achieves remarkable performance without any training on the experimental datasets, reaching Pearson correlation coefficients between predicted and measured ∆∆G values of ~ 0.5 and ~ 0.4 for single and multiple site variations, respectively. Surprisingly, DDGun performances are comparable with those of state of the art methods. DDGun also naturally predicts multiple site variations, thereby defining a benchmark method for both single site and multiple site predictors. DDGun is anti-symmetric by construction predicting the value of the ∆∆G of a reciprocal variation as almost equal (depending on the sequence profile) to -∆∆G of the direct variation. This is a valuable property that is missing in the majority of the methods. Conclusions Evolutionary information alone combined in an untrained method can achieve remarkably high performances in the prediction of ∆∆G upon protein mutation. Non-trained approaches like DDGun represent a valid benchmark both for scoring the predictive power of the individual features and for assessing the learning capability of supervised methods. Electronic supplementary material The online version of this article (10.1186/s12859-019-2923-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Ludovica Montanucci
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Viale dell'Università 16, 35020, Legnaro, Italy
| | - Emidio Capriotti
- BioFolD Unit, Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Via Selmi 3, 40126, Bologna, Italy.
| | - Yotam Frank
- Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, 69978, Tel Aviv, Israel
| | - Nir Ben-Tal
- Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, 69978, Tel Aviv, Israel
| | - Piero Fariselli
- Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Viale dell'Università 16, 35020, Legnaro, Italy. .,Now at the Department of Medical Sciences, University of Torino, via Santena 19, 10126, Torino, Italy.
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16
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Montanucci L, Savojardo C, Martelli PL, Casadio R, Fariselli P. On the biases in predictions of protein stability changes upon variations: the INPS test case. Bioinformatics 2018; 35:2525-2527. [DOI: 10.1093/bioinformatics/bty979] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 09/13/2018] [Accepted: 11/28/2018] [Indexed: 02/06/2023] Open
Affiliation(s)
- Ludovica Montanucci
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Padova, Italy
| | - Castrense Savojardo
- Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Pier Luigi Martelli
- Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Rita Casadio
- Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
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Montanucci L, Martelli PL, Ben-Tal N, Fariselli P. A natural upper bound to the accuracy of predicting protein stability changes upon mutations. Bioinformatics 2018; 35:1513-1517. [DOI: 10.1093/bioinformatics/bty880] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 09/07/2018] [Accepted: 10/16/2018] [Indexed: 11/13/2022] Open
Affiliation(s)
- Ludovica Montanucci
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Pier Luigi Martelli
- Biocomputing Group, Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Nir Ben-Tal
- Department of Biochemistry and Molecular Biology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Piero Fariselli
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
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18
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Invergo BM, Montanucci L, Bertranpetit J. Dynamic sensitivity and nonlinear interactions influence the system-level evolutionary patterns of phototransduction proteins. Proc Biol Sci 2017; 282:20152215. [PMID: 26631565 DOI: 10.1098/rspb.2015.2215] [Citation(s) in RCA: 2] [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] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Abstract
Determining the influence of complex, molecular-system dynamics on the evolution of proteins is hindered by the significant challenge of quantifying the control exerted by the proteins on system output. We have employed a combination of systems biology and molecular evolution analyses in a first attempt to unravel this relationship. We employed a comprehensive mathematical model of mammalian phototransduction to predict the degree of influence that each protein in the system exerts on the high-level dynamic behaviour. We found that the genes encoding the most dynamically sensitive proteins exhibit relatively relaxed evolutionary constraint. We also investigated the evolutionary and epistatic influences of the many nonlinear interactions between proteins in the system and found several pairs to have coevolved, including those whose interactions are purely dynamical with respect to system output. This evidence points to a key role played by nonlinear system dynamics in influencing patterns of molecular evolution.
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Affiliation(s)
- Brandon M Invergo
- IBE-Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), CEXS-UPF-PRBB, Barcelona, Catalonia 08003, Spain
| | - Ludovica Montanucci
- IBE-Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), CEXS-UPF-PRBB, Barcelona, Catalonia 08003, Spain
| | - Jaume Bertranpetit
- IBE-Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), CEXS-UPF-PRBB, Barcelona, Catalonia 08003, Spain
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Invergo BM, Dell'Orco D, Montanucci L, Koch KW, Bertranpetit J. A comprehensive model of the phototransduction cascade in mouse rod cells. Mol Biosyst 2014; 10:1481-9. [PMID: 24675755 DOI: 10.1039/c3mb70584f] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
Vertebrate visual phototransduction is perhaps the most well-studied G-protein signaling pathway. A wealth of available biochemical and electrophysiological data has resulted in a rich history of mathematical modeling of the system. However, while the most comprehensive models have relied upon amphibian biochemical and electrophysiological data, modern research typically employs mammalian species, particularly mice, which exhibit significantly faster signaling dynamics. In this work, we present an adaptation of a previously published, comprehensive model of amphibian phototransduction that can produce quantitatively accurate simulations of the murine photoresponse. We demonstrate the ability of the model to predict responses to a wide range of stimuli and under a variety of mutant conditions. Finally, we employ the model to highlight a likely unknown mechanism related to the interaction between rhodopsin and rhodopsin kinase.
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Affiliation(s)
- Brandon M Invergo
- IBE - Institute of Evolutionary Biology (CSIC-Universitat Pompeu Fabra), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
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Colombo M, Laayouni H, Invergo BM, Bertranpetit J, Montanucci L. Metabolic flux is a determinant of the evolutionary rates of enzyme-encoding genes. Evolution 2013; 68:605-13. [PMID: 24102646 DOI: 10.1111/evo.12262] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2013] [Accepted: 08/15/2013] [Indexed: 01/25/2023]
Abstract
Relationships between evolutionary rates and gene properties on a genomic, functional, pathway, or system level are being explored to unravel the principles of the evolutionary process. In particular, functional network properties have been analyzed to recognize the constraints they may impose on the evolutionary fate of genes. Here we took as a case study the core metabolic network in human erythrocytes and we analyzed the relationship between the evolutionary rates of its genes and the metabolic flux distribution throughout it. We found that metabolic flux correlates with the ratio of nonsynonymous to synonymous substitution rates. Genes encoding enzymes that carry high fluxes have been more constrained in their evolution, while purifying selection is more relaxed in genes encoding enzymes carrying low metabolic fluxes. These results demonstrate the importance of considering the dynamical functioning of gene networks when assessing the action of selection on system-level properties.
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Affiliation(s)
- Martino Colombo
- Institute of Evolutionary Biology (CSIC- Pompeu Fabra University), CEXS-UPF-PRBB, Dr. Aiguader 88, 08003 Barcelona, Catalonia, Spain
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Invergo BM, Montanucci L, Koch KW, Bertranpetit J, Dell'orco D. Exploring the rate-limiting steps in visual phototransduction recovery by bottom-up kinetic modeling. Cell Commun Signal 2013; 11:36. [PMID: 23693153 PMCID: PMC3732082 DOI: 10.1186/1478-811x-11-36] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2013] [Accepted: 05/09/2013] [Indexed: 01/20/2023] Open
Abstract
Background Phototransduction in vertebrate photoreceptor cells represents a paradigm of signaling pathways mediated by G-protein-coupled receptors (GPCRs), which share common modules linking the initiation of the cascade to the final response of the cell. In this work, we focused on the recovery phase of the visual photoresponse, which is comprised of several interacting mechanisms. Results We employed current biochemical knowledge to investigate the response mechanisms of a comprehensive model of the visual phototransduction pathway. In particular, we have improved the model by implementing a more detailed representation of the recoverin (Rec)-mediated calcium feedback on rhodopsin kinase and including a dynamic arrestin (Arr) oligomerization mechanism. The model was successfully employed to investigate the rate limiting steps in the recovery of the rod photoreceptor cell after illumination. Simulation of experimental conditions in which the expression levels of rhodospin kinase (RK), of the regulator of the G-protein signaling (RGS), of Arr and of Rec were altered individually or in combination revealed severe kinetic constraints to the dynamics of the overall network. Conclusions Our simulations confirm that RGS-mediated effector shutdown is the rate-limiting step in the recovery of the photoreceptor and show that the dynamic formation and dissociation of Arr homodimers and homotetramers at different light intensities significantly affect the timing of rhodopsin shutdown. The transition of Arr from its oligomeric storage forms to its monomeric form serves to temper its availability in the functional state. Our results may explain the puzzling evidence that overexpressing RK does not influence the saturation time of rod cells at bright light stimuli. The approach presented here could be extended to the study of other GPCR signaling pathways.
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Affiliation(s)
- Brandon M Invergo
- Department of Life Sciences and Reproduction, Section of Biological Chemistry and Center for BioMedical Computing (CBMC), University of Verona, Strada le Grazie 8, 37134, Verona, Italy.
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Dall'Olio GM, Laayouni H, Luisi P, Sikora M, Montanucci L, Bertranpetit J. Distribution of events of positive selection and population differentiation in a metabolic pathway: the case of asparagine N-glycosylation. BMC Evol Biol 2012; 12:98. [PMID: 22731960 PMCID: PMC3426484 DOI: 10.1186/1471-2148-12-98] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2011] [Accepted: 06/25/2012] [Indexed: 01/11/2023] Open
Abstract
Background Asparagine N-Glycosylation is one of the most important forms of protein post-translational modification in eukaryotes. This metabolic pathway can be subdivided into two parts: an upstream sub-pathway required for achieving proper folding for most of the proteins synthesized in the secretory pathway, and a downstream sub-pathway required to give variability to trans-membrane proteins, and involved in adaptation to the environment and innate immunity. Here we analyze the nucleotide variability of the genes of this pathway in human populations, identifying which genes show greater population differentiation and which genes show signatures of recent positive selection. We also compare how these signals are distributed between the upstream and the downstream parts of the pathway, with the aim of exploring how forces of population differentiation and positive selection vary among genes involved in the same metabolic pathway but subject to different functional constraints. Results Our results show that genes in the downstream part of the pathway are more likely to show a signature of population differentiation, while events of positive selection are equally distributed among the two parts of the pathway. Moreover, events of positive selection are frequent on genes that are known to be at bifurcation points, and that are identified as being in key position by a network-level analysis such as MGAT3 and GCS1. Conclusions These findings indicate that the upstream part of the Asparagine N-Glycosylation pathway has lower diversity among populations, while the downstream part is freer to tolerate diversity among populations. Moreover, the distribution of signatures of population differentiation and positive selection can change between parts of a pathway, especially between parts that are exposed to different functional constraints. Our results support the hypothesis that genes involved in constitutive processes can be expected to show lower population differentiation, while genes involved in traits related to the environment should show higher variability. Taken together, this work broadens our knowledge on how events of population differentiation and of positive selection are distributed among different parts of a metabolic pathway.
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Affiliation(s)
- Giovanni Marco Dall'Olio
- IBE, Institut de Biologia Evolutiva (UPF-CSIC), Parc de Recerca Biomèdica de Barcelona (PRBB), Dr, Aiguader, 88, 08003, Barcelona, Catalonia, Spain
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Casals F, Sikora M, Laayouni H, Montanucci L, Muntasell A, Lazarus R, Calafell F, Awadalla P, Netea MG, Bertranpetit J. Genetic adaptation of the antibacterial human innate immunity network. BMC Evol Biol 2011; 11:202. [PMID: 21745391 PMCID: PMC3155920 DOI: 10.1186/1471-2148-11-202] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2011] [Accepted: 07/11/2011] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Pathogens have represented an important selective force during the adaptation of modern human populations to changing social and other environmental conditions. The evolution of the immune system has therefore been influenced by these pressures. Genomic scans have revealed that immune system is one of the functions enriched with genes under adaptive selection. RESULTS Here, we describe how the innate immune system has responded to these challenges, through the analysis of resequencing data for 132 innate immunity genes in two human populations. Results are interpreted in the context of the functional and interaction networks defined by these genes. Nucleotide diversity is lower in the adaptors and modulators functional classes, and is negatively correlated with the centrality of the proteins within the interaction network. We also produced a list of candidate genes under positive or balancing selection in each population detected by neutrality tests and showed that some functional classes are preferential targets for selection. CONCLUSIONS We found evidence that the role of each gene in the network conditions the capacity to evolve or their evolvability: genes at the core of the network are more constrained, while adaptation mostly occurred at particular positions at the network edges. Interestingly, the functional classes containing most of the genes with signatures of balancing selection are involved in autoinflammatory and autoimmune diseases, suggesting a counterbalance between the beneficial and deleterious effects of the immune response.
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Affiliation(s)
- Ferran Casals
- Institute of Evolutionary Biology (UPF-CSIC), CEXS - UPF - PRBB, Barcelona, Catalonia, Spain.
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Laayouni H, Montanucci L, Sikora M, Melé M, Dall'Olio GM, Lorente-Galdos B, McGee KM, Graffelman J, Awadalla P, Bosch E, Comas D, Navarro A, Calafell F, Casals F, Bertranpetit J. Similarity in recombination rate estimates highly correlates with genetic differentiation in humans. PLoS One 2011; 6:e17913. [PMID: 21464928 PMCID: PMC3065460 DOI: 10.1371/journal.pone.0017913] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [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: 12/22/2010] [Accepted: 02/14/2011] [Indexed: 11/18/2022] Open
Abstract
Recombination varies greatly among species, as illustrated by the poor conservation of the recombination landscape between humans and chimpanzees. Thus, shorter evolutionary time frames are needed to understand the evolution of recombination. Here, we analyze its recent evolution in humans. We calculated the recombination rates between adjacent pairs of 636,933 common single-nucleotide polymorphism loci in 28 worldwide human populations and analyzed them in relation to genetic distances between populations. We found a strong and highly significant correlation between similarity in the recombination rates corrected for effective population size and genetic differentiation between populations. This correlation is observed at the genome-wide level, but also for each chromosome and when genetic distances and recombination similarities are calculated independently from different parts of the genome. Moreover, and more relevant, this relationship is robustly maintained when considering presence/absence of recombination hotspots. Simulations show that this correlation cannot be explained by biases in the inference of recombination rates caused by haplotype sharing among similar populations. This result indicates a rapid pace of evolution of recombination, within the time span of differentiation of modern humans.
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Affiliation(s)
- Hafid Laayouni
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Ludovica Montanucci
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Martin Sikora
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Marta Melé
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | | | - Belén Lorente-Galdos
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Kate M. McGee
- National Cancer Institute, National Institutes of Health, Frederick, Maryland, United States of America
| | - Jan Graffelman
- Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, Barcelona, Spain
| | - Philip Awadalla
- Faculty of Medicine, Ste-Justine Hospital Research Centre, University of Montreal, Montreal, Quebec, Canada
| | - Elena Bosch
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - David Comas
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Arcadi Navarro
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Catalonia, Spain
- National Institute for Bioinformatics (INB), Barcelona, Spain
| | - Francesc Calafell
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
| | - Ferran Casals
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
- Faculty of Medicine, Ste-Justine Hospital Research Centre, University of Montreal, Montreal, Quebec, Canada
| | - Jaume Bertranpetit
- IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain
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Dall'Olio GM, Jassal B, Montanucci L, Gagneux P, Bertranpetit J, Laayouni H. The annotation of the asparagine N-linked glycosylation pathway in the Reactome database. Glycobiology 2011; 21:1395-400. [PMID: 21199820 DOI: 10.1093/glycob/cwq215] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Asparagine N-linked glycosylation is one of the most important forms of protein post-translational modification in eukaryotes and is one of the first metabolic pathways described at a biochemical level. Here, we report a new annotation of this pathway for the Human species, published after passing a peer-review process in Reactome. The new annotation presented here offers a high level of detail and provides references and descriptions for each reaction, along with integration with GeneOntology and other databases. The open-source approach of Reactome toward annotation encourages feedback from its users, making it easier to keep the annotation of this pathway updated with future knowledge. Reactome's web interface allows easy navigation between steps involved in the pathway to compare it with other pathways and resources in other scientific databases and to export it to BioPax and SBML formats, making it accessible for computational studies. This new entry in Reactome expands and complements the annotations already published in databases for biological pathways and provides a common reference to researchers interested in studying this important pathway in the human species. Finally, we discuss the status of the annotation of this pathway and point out which steps are worth further investigation or need better experimental validation.
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Montanucci L, Laayouni H, Dall'Olio GM, Bertranpetit J. Molecular evolution and network-level analysis of the N-glycosylation metabolic pathway across primates. Mol Biol Evol 2010; 28:813-23. [PMID: 20924085 DOI: 10.1093/molbev/msq259] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
N-glycosylation is one of the most important forms of protein modification, serving key biological functions in multicellular organisms. N-glycans at the cell surface mediate the interaction between cells and the surrounding matrix and may act as pathogen receptors, making the genes responsible for their synthesis good candidates to show signatures of adaptation to different pathogen environments. Here, we study the forces that shaped the evolution of the genes involved in the synthesis of the N-glycans during the divergence of primates within the framework of their functional network. We have found that, despite their function of producing glycan repertoires capable of evading rapidly evolving pathogens, genes involved in the synthesis of the glycans are highly conserved, and no signals of positive selection have been detected within the time of divergence of primates. This suggests strong functional constraints as the main force driving their evolution. We studied the strength of the purifying selection acting on the genes in relation to the network structure considering the position of each gene along the pathway, its connectivity, and the rates of evolution in neighboring genes. We found a strong and highly significant negative correlation between the strength of purifying selection and the connectivity of each gene, indicating that genes encoding for highly connected enzymes evolve slower and thus are subject to stronger selective constraints. This result confirms that network topology does shape the evolution of the genes and that the connectivity within metabolic pathways and networks plays a major role in constraining evolutionary rates.
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Affiliation(s)
- Ludovica Montanucci
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology, Universitat Pompeu Fabra-Consejo Superior de Investigaciones Cientificas, Barcelona, Catalonia, Spain
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Bartoli L, Montanucci L, Fronza R, Martelli PL, Fariselli P, Carota L, Donvito G, Maggi GP, Casadio R. The bologna annotation resource: a non hierarchical method for the functional and structural annotation of protein sequences relying on a comparative large-scale genome analysis. J Proteome Res 2009; 8:4362-71. [PMID: 19552451 DOI: 10.1021/pr900204r] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein sequence annotation is a major challenge in the postgenomic era. Thanks to the availability of complete genomes and proteomes, protein annotation has recently taken invaluable advantage from cross-genome comparisons. In this work, we describe a new non hierarchical clustering procedure characterized by a stringent metric which ensures a reliable transfer of function between related proteins even in the case of multidomain and distantly related proteins. The method takes advantage of the comparative analysis of 599 completely sequenced genomes, both from prokaryotes and eukaryotes, and of a GO and PDB/SCOP mapping over the clusters. A statistical validation of our method demonstrates that our clustering technique captures the essential information shared between homologous and distantly related protein sequences. By this, uncharacterized proteins can be safely annotated by inheriting the annotation of the cluster. We validate our method by blindly annotating other 201 genomes and finally we develop BAR (the Bologna Annotation Resource), a prediction server for protein functional annotation based on a total of 800 genomes (publicly available at http://microserf.biocomp.unibo.it/bar/).
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Affiliation(s)
- Lisa Bartoli
- Biocomputing Group, CIRB/Dept of Biology, University of Bologna, Italy
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Abstract
Motivation: A basic question in protein science is to which extent mutations affect protein thermostability. This knowledge would be particularly relevant for engineering thermostable enzymes. In several experimental approaches, this issue has been serendipitously addressed. It would be therefore convenient providing a computational method that predicts when a given protein mutant is more thermostable than its corresponding wild-type. Results: We present a new method based on support vector machines that is able to predict whether a set of mutations (including insertion and deletions) can enhance the thermostability of a given protein sequence. When trained and tested on a redundancy-reduced dataset, our predictor achieves 88% accuracy and a correlation coefficient equal to 0.75. Our predictor also correctly classifies 12 out of 14 experimentally characterized protein mutants with enhanced thermostability. Finally, it correctly detects all the 11 mutated proteins whose increase in stability temperature is >10°C. Availability: The dataset and the list of protein clusters adopted for the SVM cross-validation are available at the web site http://lipid.biocomp.unibo.it/~ludovica/thermo-meso-MUT. Contact:casadio@alma.unibo.it
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Affiliation(s)
- Ludovica Montanucci
- Department of Biology, University of Bologna, via Irnerio 42, 40126 Bologna, Italy
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Montanucci L, Martelli PL, Fariselli P, Casadio R. Robust determinants of thermostability highlighted by a codon frequency index capable of discriminating thermophilic from mesophilic genomes. J Proteome Res 2007; 6:2502-8. [PMID: 17530792 DOI: 10.1021/pr060670p] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Can genome analysis tell us about the lifestyle of an organism? We ask this question considering a thorough cross comparison of thermophilic and mesophilic genomes, since presently the number of available genomes is enough to ensure statistical significance of the results. We analyze, by means of principal component analysis (PCA), the codon composition of a database comprising 116 genomes, selected so as to include one species for each genus and show that a cross genomic approach can allow the extraction of common determinants of thermostability at the genome level. The results of our analysis indicate that all the known features of thermostability can be found in the 64 component loadings of the second principal axis of PCA. By this, we develop an index of thermostability whose discriminative power between mesophiles and thermophiles scores with 98% accuracy at the genome level and with 95% accuracy at the protein sequence level. We also prove that these results are not due to phylogenetic differences between archaea and bacteria.
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Affiliation(s)
- Ludovica Montanucci
- Biocomputing Group, CIRB/Dept of Biology, University of Bologna, Bologna, Italy
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