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Liu T, Simakov S, Liang F. An idealized human cardiomyocyte finite element model for studying the interaction between the cross-bridge state and cell mechanical response . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-5. [PMID: 38082753 DOI: 10.1109/embc40787.2023.10341055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The mechanical state of cardiomyocyte is directly related to the structure and function of internal sarcomeres. In the field of computational cardiac mechanics, attempts to establish models of human cardiomyocyte with a detailed representation of sarcomere cross-bridge (XB) are rare. In this study, we established a computational model for a cardiomyocyte with idealized geometry while containing a representative sarcomere composed of thick filament, thin filament, titin filament, and Z-disc. The formation of XB with passive tension in the model was simulated with the finite element (FE) method, and stochastic FE analyses were further carried out in conjunction with six sigma analysis to explore the interaction between the S1 power stroke and the twitch mechanics of cardiomyocyte. The proposed modeling method may help us better understand the working state of cardiomyocyte, and offer a potential means for exploring the cell-level mechanisms of cardiac diseases.
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Longchamps RJ, Yang SY, Castellani CA, Shi W, Lane J, Grove ML, Bartz TM, Sarnowski C, Liu C, Burrows K, Guyatt AL, Gaunt TR, Kacprowski T, Yang J, De Jager PL, Yu L, Bergman A, Xia R, Fornage M, Feitosa MF, Wojczynski MK, Kraja AT, Province MA, Amin N, Rivadeneira F, Tiemeier H, Uitterlinden AG, Broer L, Van Meurs JBJ, Van Duijn CM, Raffield LM, Lange L, Rich SS, Lemaitre RN, Goodarzi MO, Sitlani CM, Mak ACY, Bennett DA, Rodriguez S, Murabito JM, Lunetta KL, Sotoodehnia N, Atzmon G, Ye K, Barzilai N, Brody JA, Psaty BM, Taylor KD, Rotter JI, Boerwinkle E, Pankratz N, Arking DE. Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation. Hum Genet 2022; 141:127-146. [PMID: 34859289 PMCID: PMC8758627 DOI: 10.1007/s00439-021-02394-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 10/22/2021] [Indexed: 12/18/2022]
Abstract
Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).
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Affiliation(s)
- R J Longchamps
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - S Y Yang
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - C A Castellani
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - W Shi
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - J Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - M L Grove
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - T M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - C Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - K Burrows
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - A L Guyatt
- Department of Health Sciences, University of Leicester, University Road, Leicester, UK
| | - T R Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - T Kacprowski
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
- Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Brunswick, Germany
| | - J Yang
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - P L De Jager
- Center for Translational and Systems Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - L Yu
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - A Bergman
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - R Xia
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - M Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, USA
| | - M F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - A T Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - N Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Social and Behavioral Science, Harvard T.H. School of Public Health, Boston, USA
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L Broer
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - J B J Van Meurs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - C M Van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - L Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - S S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - M O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - C M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - A C Y Mak
- Cardiovascular Research Institute and Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - D A Bennett
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - S Rodriguez
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - J M Murabito
- Boston University School of Medicine, Boston University, Boston, MA, USA
| | - K L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - N Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - G Atzmon
- Department of Natural Science, University of Haifa, Haifa, Israel
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - K Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - N Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - J A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - B M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, USA
| | - K D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - J I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - E Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | - N Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - D E Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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Podvin S, Jones A, Liu Q, Aulston B, Mosier C, Ames J, Winston C, Lietz CB, Jiang Z, O’Donoghue AJ, Ikezu T, Rissman RA, Yuan SH, Hook V. Mutant Presenilin 1 Dysregulates Exosomal Proteome Cargo Produced by Human-Induced Pluripotent Stem Cell Neurons. ACS OMEGA 2021; 6:13033-13056. [PMID: 34056454 PMCID: PMC8158845 DOI: 10.1021/acsomega.1c00660] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 04/16/2021] [Indexed: 05/28/2023]
Abstract
The accumulation and propagation of hyperphosphorylated tau (p-Tau) is a neuropathological hallmark occurring with neurodegeneration of Alzheimer's disease (AD). Extracellular vesicles, exosomes, have been shown to initiate tau propagation in the brain. Notably, exosomes from human-induced pluripotent stem cell (iPSC) neurons expressing the AD familial A246E mutant form of presenilin 1 (mPS1) are capable of inducing tau deposits in the mouse brain after in vivo injection. To gain insights into the exosome proteome cargo that participates in propagating tau pathology, this study conducted proteomic analysis of exosomes produced by human iPSC neurons expressing A246E mPS1. Significantly, mPS1 altered the profile of exosome cargo proteins to result in (1) proteins present only in mPS1 exosomes and not in controls, (2) the absence of proteins in the mPS1 exosomes which were present only in controls, and (3) shared proteins which were upregulated or downregulated in the mPS1 exosomes compared to controls. These results show that mPS1 dysregulates the proteome cargo of exosomes to result in the acquisition of proteins involved in the extracellular matrix and protease functions, deletion of proteins involved in RNA and protein translation systems along with proteasome and related functions, combined with the upregulation and downregulation of shared proteins, including the upregulation of amyloid precursor protein. Notably, mPS1 neuron-derived exosomes displayed altered profiles of protein phosphatases and kinases involved in regulating the status of p-tau. The dysregulation of exosome cargo proteins by mPS1 may be associated with the ability of mPS1 neuron-derived exosomes to propagate tau pathology.
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Affiliation(s)
- Sonia Podvin
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Alexander Jones
- Biomedical
Sciences Graduate Program, University of
California, San Diego, La Jolla, San Diego 92093, California, United States
| | - Qing Liu
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
| | - Brent Aulston
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
| | - Charles Mosier
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Janneca Ames
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Charisse Winston
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
| | - Christopher B. Lietz
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Zhenze Jiang
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Anthony J. O’Donoghue
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
| | - Tsuneya Ikezu
- Department
of Pharmacology and Experimental Therapeutics, Department of Neurology,
Alzheimer’s Disease Research Center, Boston University, School of Medicine, Boston 02118, Massachusetts, United States
| | - Robert A. Rissman
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
- Veterans
Affairs San Diego Healthcare System,
La Jolla, San Diego 92161, California, United States
| | - Shauna H. Yuan
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
| | - Vivian Hook
- Skaggs
School of Pharmacy and Pharmaceutical Sciences, University of California San Diego,
La Jolla, San Diego 92093, California, United States
- Biomedical
Sciences Graduate Program, University of
California, San Diego, La Jolla, San Diego 92093, California, United States
- Department
of Neurosciences, School of Medicine, University
of California, San Diego, La Jolla, San Diego 92093, California, United States
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Oliveira CCV, Fatsini E, Fernández I, Anjos C, Chauvigné F, Cerdà J, Mjelle R, Fernandes JMO, Cabrita E. Kisspeptin Influences the Reproductive Axis and Circulating Levels of microRNAs in Senegalese Sole. Int J Mol Sci 2020; 21:ijms21239051. [PMID: 33260781 PMCID: PMC7730343 DOI: 10.3390/ijms21239051] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/25/2020] [Accepted: 11/26/2020] [Indexed: 12/11/2022] Open
Abstract
Kisspeptin regulates puberty and reproduction onset, acting upstream of the brain–pituitary–gonad (HPG) axis. This study aimed to test a kisspeptin-based hormonal therapy on cultured Senegalese sole (G1) breeders, known to have reproductive dysfunctions. A single intramuscular injection of KISS2-10 decapeptide (250 µg/kg) was tested in females and males during the reproductive season, and gonad maturation, sperm motility, plasma levels of gonadotropins (Fsh and Lh) and sex steroids (11-ketotestosterone, testosterone and estradiol), as well as changes in small non-coding RNAs (sncRNAs) in plasma, were investigated. Fsh, Lh, and testosterone levels increased after kisspeptin injection in both sexes, while sperm analysis did not show differences between groups. Let7e, miR-199a-3p and miR-100-5p were differentially expressed in females, while miR-1-3p miRNA was up-regulated in kisspeptin-treated males. In silico prediction of mRNAs targeted by miRNAs revealed that kisspeptin treatment might affect paracellular transporters, regulate structural and functional polarity of cells, neural networks and intracellular trafficking in Senegalese sole females; also, DNA methylation and sphingolipid metabolism might be altered in kisspeptin-treated males. Results demonstrated that kisspeptin stimulated gonadotropin and testosterone secretion in both sexes and induced an unanticipated alteration of plasma miRNAs, opening new research venues to understand how this neuropeptide impacts in fish HPG axis.
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Affiliation(s)
- Catarina C. V. Oliveira
- Center of Marine Sciences-CCMAR, University of Algarve, 8005-139 Faro, Portugal; (E.F.); (C.A.)
- Correspondence: (C.C.V.O.); (E.C.)
| | - Elvira Fatsini
- Center of Marine Sciences-CCMAR, University of Algarve, 8005-139 Faro, Portugal; (E.F.); (C.A.)
| | - Ignacio Fernández
- Aquaculture Research Center, Agrarian Technological Institute of Castile and Leon, Ctra. Arévalo, s/n, 40196 Segovia, Spain;
| | - Catarina Anjos
- Center of Marine Sciences-CCMAR, University of Algarve, 8005-139 Faro, Portugal; (E.F.); (C.A.)
| | - François Chauvigné
- IRTA-Institute of Biotechnology and Biomedicine (IBB), Universitat Autònoma de Barcelona, 08193 Barcelona, Spain; (F.C.); (J.C.)
| | - Joan Cerdà
- IRTA-Institute of Biotechnology and Biomedicine (IBB), Universitat Autònoma de Barcelona, 08193 Barcelona, Spain; (F.C.); (J.C.)
| | - Robin Mjelle
- Faculty of Bioscience and Aquaculture, Nord University, 8049 Bodø, Norway; (R.M.); (J.M.O.F.)
| | - Jorge M. O. Fernandes
- Faculty of Bioscience and Aquaculture, Nord University, 8049 Bodø, Norway; (R.M.); (J.M.O.F.)
| | - Elsa Cabrita
- Center of Marine Sciences-CCMAR, University of Algarve, 8005-139 Faro, Portugal; (E.F.); (C.A.)
- Correspondence: (C.C.V.O.); (E.C.)
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Fatumo S, Carstensen T, Nashiru O, Gurdasani D, Sandhu M, Kaleebu P. Complimentary Methods for Multivariate Genome-Wide Association Study Identify New Susceptibility Genes for Blood Cell Traits. Front Genet 2019; 10:334. [PMID: 31080455 PMCID: PMC6497788 DOI: 10.3389/fgene.2019.00334] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 03/28/2019] [Indexed: 02/02/2023] Open
Abstract
Genome-wide association studies (GWAS) have found hundreds of novel loci associated with full blood count (FBC) phenotypes. However, most of these studies were performed in a single phenotype framework without putting into consideration the clinical relatedness among traits. In this work, in addition to the standard univariate GWAS, we also use two different multivariate methods to perform the first multiple traits GWAS of FBC traits in ∼7000 individuals from the Ugandan General Population Cohort (GPC). We started by performing the standard univariate GWAS approach. We then performed our first multivariate method, in this approach, we tested for marker associations with 15 FBC traits simultaneously in a multivariate mixed model implemented in GEMMA while accounting for the relatedness of individuals and pedigree structures, as well as population substructure. In this analysis, we provide a framework for the combination of multiple phenotypes in multivariate GWAS analysis and show evidence of multi-collinearity whenever the correlation between traits exceeds the correlation coefficient threshold of r 2 >=0.75. This approach identifies two known and one novel loci. In the second multivariate method, we applied principal component analysis (PCA) to the same 15 correlated FBC traits. We then tested for marker associations with each PC in univariate linear mixed models implemented in GEMMA. We show that the FBC composite phenotype as assessed by each PC expresses information that is not completely encapsulated by the individual FBC traits, as this approach identifies three known and five novel loci that were not identified using both the standard univariate and multivariate GWAS methods. Across both multivariate methods, we identified six novel loci. As a proof of concept, both multivariate methods also identified known loci, HBB and ITFG3. The two multivariate methods show that multivariate genotype-phenotype methods increase power and identify novel genotype-phenotype associations not found with the standard univariate GWAS in the same dataset.
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Affiliation(s)
- Segun Fatumo
- Uganda Medical Informatics Centre, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda,London School of Hygiene and Tropical Medicine, London, United Kingdom,H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria,*Correspondence: Segun Fatumo, ;
| | - Tommy Carstensen
- Human Genetics, Wellcome Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Oyekanmi Nashiru
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja, Nigeria
| | - Deepti Gurdasani
- Human Genetics, Wellcome Sanger Institute, Hinxton, Cambridge, United Kingdom
| | - Manjinder Sandhu
- Human Genetics, Wellcome Sanger Institute, Hinxton, Cambridge, United Kingdom,Division of Computational Medicine, Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Pontiano Kaleebu
- Uganda Medical Informatics Centre, MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda,London School of Hygiene and Tropical Medicine, London, United Kingdom
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Bezerra MJB, Arruda-Alencar JM, Martins JAM, Viana AGA, Viana Neto AM, Rêgo JPA, Oliveira RV, Lobo M, Moreira ACO, Moreira RA, Moura AA. Major seminal plasma proteome of rabbits and associations with sperm quality. Theriogenology 2019; 128:156-166. [PMID: 30772659 DOI: 10.1016/j.theriogenology.2019.01.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 01/05/2019] [Accepted: 01/13/2019] [Indexed: 12/12/2022]
Abstract
The present study was conducted to describe the major seminal plasma proteome of rabbits and potential associations between seminal proteins and semen criteria. Semen samples were collected from 18 New Zealand adult rabbits, and seminal plasma proteins were analyzed by 2-D SDS-PAGE and tandem mass spectrometry. Sperm motility, vigor, concentration, morphology and membrane sperm viability were evaluated. Rabbits ejaculated 364 ± 70 million sperm/ml, with 81 ± 6.1% motile cells, 3.8 ± 0.2 vigor and 66.7 ± 2.5% sperm with normal morphology. Based on the viability and acrosome integrity assay, there were 65.8 ± 2.5% live sperm with intact acrosome and most spermatozoa had both intact acrosome and functional membrane. On average, 2-D gels of rabbit seminal plasma had 232 ± 69.5 spots, as determined by PDQuest software (Bio Rad, USA). Mass spectrometry allowed the identification of 137 different proteins. The most abundant proteins in rabbit seminal plasma were hemoglobin subunit zeta-like, annexins, lipocalin, FAM115 protein and albumin. The intensity of the spots associated with these five proteins represented 71.5% of the intensity of all spots detected in the master gel. Multiple regression models were estimated using sperm traits as dependent variables and seminal plasma proteins as independent ones. Also, sperm motility had positive association with beta-nerve growth factor and cysteine-rich secretory protein 1-like and a negative one with galectin-1. The percentage of rabbit sperm with intact membrane was related to seminal plasma protein FAM115 complex and tropomyosin. Then, the population of morphologically normal sperm in rabbit semen was positively linked to carcinoembryonic antigen-related cell adhesion molecule 6-like and down regulated by seminal plasma isocitrate dehydrogenase. Based on another regression model, the variation in the percentage of live sperm with intact acrosome was partially explained by the amount of leukocyte elastase inhibitor and the peptidyl-prolyl cis-trans isomerase A in the rabbit seminal fluid. The current study reports the identification of 137 proteins of rabbit seminal plasma. Major proteins of seminal secretion relate primarily to prevention of damages caused by lipid peroxide radicals and oxidative stress, membrane functionality, transport of lipids to the sperm membrane and temperature regulation. Moreover, finding seminal plasma proteins as indicators of semen parameters will improve assisted reproductive technologies.
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Affiliation(s)
- M J B Bezerra
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - J M Arruda-Alencar
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - J A M Martins
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - A G A Viana
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - A M Viana Neto
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - J P A Rêgo
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - R V Oliveira
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil
| | - M Lobo
- School of Pharmacy, University of Fortaleza, Fortaleza, CE, Brazil
| | - A C O Moreira
- School of Pharmacy, University of Fortaleza, Fortaleza, CE, Brazil
| | - R A Moreira
- School of Pharmacy, University of Fortaleza, Fortaleza, CE, Brazil
| | - A A Moura
- Department of Animal Science, Federal University of Ceará, Fortaleza, CE, Brazil.
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7
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Nahan KS, Walsh KB, Adeoye O, Landero-Figueroa JA. The metal and metalloprotein profile of human plasma as biomarkers for stroke diagnosis. J Trace Elem Med Biol 2017; 42:81-91. [PMID: 28595796 DOI: 10.1016/j.jtemb.2017.04.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Revised: 03/31/2017] [Accepted: 04/04/2017] [Indexed: 01/09/2023]
Abstract
Stroke, a major cause of disability and mortality, affects someone in the United States every 40s. Stroke biomarkers, including those that could be used as a blood test for diagnosis of stroke, have been particularly elusive. We performed a double blind study to identify human plasma biomarkers for the diagnosis of stroke, including acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH). We utilized a three-track approach based on the total metal profile, the metal cofactor levels among metalloproteins, and the identification of stroke-related metalloproteins. The study included 14 case-control pairs of AIS and 23 case-control pairs of ICH. Controls were matched to cases based on gender, ethnicity, and age (±5 years). AIS cases were statistically higher from their respective controls for protein bound co-factors Se and Cd, while unique correlations of metal cofactor concentrations among metalloproteins were identified between Pb-W, Sr-W, Pb-V, and Cu-V. ICH cases were statistically higher from their respective controls for Se and Co cofactors, whereas Cd and Pb were statistically lower. Unique correlations between metal cofactors for ICH cases were identified between Pb-W, Sr-W, Pb-V, and Cu-V. Stroke-related metalloproteins were identified, including calpain-15, protein-activated inward rectifier potassium channel 1, tau-tubulin kinase 1, and voltage-dependent L-type calcium channel subunit beta-3. Linear discriminant analysis (LDA) was able to classify patients between stroke cases or controls with 93% accuracy as well as classify patients with one of the four stroke groups with 85% accuracy. Additionally, this study found utmost importance in vanadium (V) and tungsten (W) correlations for both bound and total metal concentrations, suggestive of binding to transferrin or inhibition of oxidoreductases. Future work in stroke patients will seek to quantify varying selenoproteins, including selenoprotein P and glutathione peroxidase and identified zinc finger tissue leakage proteins, and further explore the role of trace metal fluctuations with transferrin.
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Affiliation(s)
- Keaton S Nahan
- University of Cincinnati/Agilent Technologies Metallomics Center of the Americas, Department of Chemistry, University of Cincinnati, Mail Location 0172, Cincinnati, OH 45221, USA.
| | - Kyle B Walsh
- University of Cincinnati Neuroscience Institute, Department of Emergency Medicine, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0769, USA.
| | - Opeolu Adeoye
- University of Cincinnati Neuroscience Institute, Department of Emergency Medicine, University of Cincinnati, College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0769, USA.
| | - Julio A Landero-Figueroa
- University of Cincinnati/Agilent Technologies Metallomics Center of the Americas, Department of Chemistry, University of Cincinnati, Mail Location 0172, Cincinnati, OH 45221, USA.
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8
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Pellacani C, Monari E, Zaffe D, Cuoghi A, Bellei E, Lucchi A, Bergamini S, Tomasi A, Bertoldi C. Analisi tissutale proteomica della tasca parodontale. Uno studio pilota. DENTAL CADMOS 2014. [DOI: 10.1016/s0011-8524(14)70231-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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9
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Cytotoxicity of single-walled carbon nanotubes on human hepatoma HepG2 cells: an iTRAQ-coupled 2D LC-MS/MS proteome analysis. Toxicol In Vitro 2011; 25:1820-7. [PMID: 22001959 DOI: 10.1016/j.tiv.2011.09.022] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2011] [Revised: 09/05/2011] [Accepted: 09/27/2011] [Indexed: 12/14/2022]
Abstract
Single-walled carbon nanotubes (SWCNTs) and its derivatives are promising candidates for applications in electronics, energy, materials and biomedical areas. However, with the growing potential biomedical applications and the rising societal concerns on nanosafety, mechanistic understanding of the interactions between nanomaterials and living systems has become imperative. In the present study, our group applied the iTRAQ-coupled 2D LC-MS/MS approach to analyze the protein profile change of mammalian cells in response to SWCNTs. Specifically, the human hepatoma HepG2 cells were chosen as the in vitro model to study the potential cytotoxicity of SWCNTs on the vital organ of liver. Overall 51 differentially expressed proteins that involved in metabolic pathway, redox regulation, signaling pathway, cytoskeleton formation and cell growth were identified. We found SWCNTs triggered the up-regulation of metabolic enzymes, heat shock proteins and proteins involved in redox regulation, which indicated SWCNTs could induce oxidative stress, perturb protein synthesis and interfere cellular metabolism. Our data also suggested that SWCNTs might induce the activation of apoptosis signal-regulating kinase 1, and finally lead to stress-induced apoptosis. The comparative protein profile obtained here provided molecular evidence on the cellular functions in response to SWCNTs, which should very useful to elucidate the cytotoxicity caused by those nanomaterials.
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10
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Abstract
Abnormal erythrocyte sodium-lithium countertransport is common in a subgroup of patients with essential hypertension and a strong family history of hypertension and cardiovascular disease. We have previously shown that the abnormality in sodium-lithium countertransport is associated with tropomyosin, a cytoskeletal protein required to stabilize actin filament formation. Leukocyte trafficking events, which depend on cytoskeletal reorganization, are also altered in patients with essential hypertension with abnormal sodium-lithium countertransport. The aim of this study was to determine whether there is an abnormality in isoforms of tropomyosin that are common to erythrocytes and leukocytes. Analysis of reticulocyte RNA by reverse transcription (RT) and polymerase chain reaction (PCR) showed expression of TPMN and TPM5b isoforms of tropomyosin. No other isoforms were expressed. These isoforms were also detected in RNA from leukocytes. In patients with essential hypertension with abnormal erythrocyte sodium-lithium countertransport compared with normal control subjects, there was a higher TPMN/TPM5b ratio of protein in erythrocytes (median 3.8 [range 1.8 to 6.6] versus 2.9 [1.9 to 4.0], P<0.001) and of RNA in leukocytes (3.7 [1.7 to 8.2] versus 2.6 [1.2 to 4.3], P<0.01). Furthermore, the protein ratio of TPMN/TPM5b in erythrocytes showed significant correlation with the V(max)/K(m) ratio of sodium-lithium countertransport across the patient groups (r=-0.42; P<0.01). Therefore, altered tropomyosin expression may be the underlying abnormality associated with blood cell membrane changes in essential hypertension and implicates the cytoskeleton in the pathogenesis of the disease in a major subgroup of patients.
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Affiliation(s)
- Stuart A Dunn
- Department of Medicine, Medical School, University of Newcastle-Upon-Tyne, Newcastle, England.
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