Comparative Host-Coronavirus Protein Interaction Networks Reveal Pan
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Role of Mitochondrial Ribosomal Protein S18-2 in Cancerogenesis and in Regulation of Stemness and Differentiation
From THE DEPARTMENT OF MICROBIOLOGY TUMOR AND CELL BIOLOGY (MTC) Karolinska Institutet, Stockholm, Sweden ROLE OF MITOCHONDRIAL RIBOSOMAL PROTEIN S18-2 IN CANCEROGENESIS AND IN REGULATION OF STEMNESS AND DIFFERENTIATION Muhammad Mushtaq Stockholm 2017 All previously published papers were reproduced with permission from the publisher. Published by Karolinska Institutet. Printed by E-Print AB 2017 © Muhammad Mushtaq, 2017 ISBN 978-91-7676-697-2 Role of Mitochondrial Ribosomal Protein S18-2 in Cancerogenesis and in Regulation of Stemness and Differentiation THESIS FOR DOCTORAL DEGREE (Ph.D.) By Muhammad Mushtaq Principal Supervisor: Faculty Opponent: Associate Professor Elena Kashuba Professor Pramod Kumar Srivastava Karolinska Institutet University of Connecticut Department of Microbiology Tumor and Cell Center for Immunotherapy of Cancer and Biology (MTC) Infectious Diseases Co-supervisor(s): Examination Board: Professor Sonia Lain Professor Ola Söderberg Karolinska Institutet Uppsala University Department of Microbiology Tumor and Cell Department of Immunology, Genetics and Biology (MTC) Pathology (IGP) Professor George Klein Professor Boris Zhivotovsky Karolinska Institutet Karolinska Institutet Department of Microbiology Tumor and Cell Institute of Environmental Medicine (IMM) Biology (MTC) Professor Lars-Gunnar Larsson Karolinska Institutet Department of Microbiology Tumor and Cell Biology (MTC) Dedicated to my parents ABSTRACT Mitochondria carry their own ribosomes (mitoribosomes) for the translation of mRNA encoded by mitochondrial DNA. The architecture of mitoribosomes is mainly composed of mitochondrial ribosomal proteins (MRPs), which are encoded by nuclear genomic DNA. Emerging experimental evidences reveal that several MRPs are multifunctional and they exhibit important extra-mitochondrial functions, such as involvement in apoptosis, protein biosynthesis and signal transduction. Dysregulations of the MRPs are associated with severe pathological conditions, including cancer. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization I International Bureau (10) International Publication Number (43) International Publication Date WO 2019/079361 Al 25 April 2019 (25.04.2019) W 1P O PCT (51) International Patent Classification: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, C12Q 1/68 (2018.01) A61P 31/18 (2006.01) DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, C12Q 1/70 (2006.01) HR, HU, ID, IL, IN, IR, IS, JO, JP, KE, KG, KH, KN, KP, KR, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, (21) International Application Number: MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, PCT/US2018/056167 OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, (22) International Filing Date: SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, 16 October 2018 (16. 10.2018) TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (25) Filing Language: English (84) Designated States (unless otherwise indicated, for every kind of regional protection available): ARIPO (BW, GH, (26) Publication Language: English GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, (30) Priority Data: UG, ZM, ZW), Eurasian (AM, AZ, BY, KG, KZ, RU, TJ, 62/573,025 16 October 2017 (16. 10.2017) US TM), European (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, ΓΕ , IS, IT, LT, LU, LV, (71) Applicant: MASSACHUSETTS INSTITUTE OF MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TECHNOLOGY [US/US]; 77 Massachusetts Avenue, TR), OAPI (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, Cambridge, Massachusetts 02139 (US). -
Computational and Experimental Approaches for Evaluating the Genetic Basis of Mitochondrial Disorders
Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Lieber, Daniel Solomon. 2013. Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders. Doctoral dissertation, Harvard University. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11158264 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders A dissertation presented by Daniel Solomon Lieber to The Committee on Higher Degrees in Systems Biology in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Systems Biology Harvard University Cambridge, Massachusetts April 2013 © 2013 - Daniel Solomon Lieber All rights reserved. Dissertation Adviser: Professor Vamsi K. Mootha Daniel Solomon Lieber Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders Abstract Mitochondria are responsible for some of the cell’s most fundamental biological pathways and metabolic processes, including aerobic ATP production by the mitochondrial respiratory chain. In humans, mitochondrial dysfunction can lead to severe disorders of energy metabolism, which are collectively referred to as mitochondrial disorders and affect approximately 1:5,000 individuals. These disorders are clinically heterogeneous and can affect multiple organ systems, often within a single individual. Symptoms can include myopathy, exercise intolerance, hearing loss, blindness, stroke, seizures, diabetes, and GI dysmotility. -
Plos Biology
PLOS BIOLOGY RESEARCH ARTICLE A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19 Yadi Zhou1☯, Yuan Hou1☯, Jiayu Shen1, Reena Mehra2,3, Asha Kallianpur1,2, Daniel A. Culver4,5, Michaela U. Gack6, Samar Farha4,5, Joe Zein2,4, Suzy Comhair2,4, 2,4 2,4 2,4 1,2,4,7,8 Claudio Fiocchi , Thaddeus StappenbeckID , Timothy Chan , Charis EngID , Jae 2,4 2,3 2,4 1,2,8 a1111111111 U. Jung , Lara JehiID , Serpil Erzurum , Feixiong ChengID * a1111111111 a1111111111 1 Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 2 Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western a1111111111 Reserve University, Cleveland, Ohio, United States of America, 3 Neurological Institute, Cleveland Clinic, a1111111111 Cleveland, Ohio, United States of America, 4 Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 5 Department of Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 6 Florida Research and Innovation Center, Cleveland Clinic, Port Saint Lucie, Florida, United States of America, 7 Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America, 8 Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, OPEN ACCESS United States of America Citation: Zhou Y, Hou Y, Shen J, Mehra R, Kallianpur A, Culver DA, et al. (2020) A network ☯ These authors contributed equally to this work. * [email protected] medicine approach to investigation and population- based validation of disease manifestations and drug repurposing for COVID-19. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Final Draft.Docx
Three-Dimensional Modeling of Chicken Anemia Virus VP3 and Porcine Circovirus Type 1 VP3 A Major Qualifying Project Submitted to the faculty of WORCESTER POLYTECHNIC INSTITUTE in partial fulfillment of the requirements for the Degree of Bachelor of Science in Biochemistry and Chemistry by: __________________________ Sam Eisenberg __________________________________________ Lee Hermsdorf-Krasin __________________________ Curtis Innamorati September 12th, 2013 Approved: _________________________________ Dr. Destin Heilman, Advisor Department of Chemistry and Biochemistry, WPI Abstract The third viral protein (VP3) of the Chicken Anemia Virus (Apoptin) and Porcine Circovirus Type 1 (PCV1VP3) have potential therapeutic cancer killing properties. Though advances have been made in understanding their apoptotic mechanisms, the reasons behind their cancer cell selectivity have thus far eluded researchers. Further, researchers have been unable to isolate and crystallize these proteins, and this lack of a known structure greatly contributes to the difficulty of studying their selectivity. In the past decade protein prediction algorithms have made great strides in the ability to accurately predict secondary and tertiary structures of proteins. This project aimed to generate possible functional models of these proteins using the available prediction techniques. One significant and well defined function of these proteins is their ability to specifically localize to the cell nucleus or cytoplasm. In order to link and evaluate the results generated from tertiary structure predictions with possible mechanisms for localization, experiments regarding the activity of nuclear export signals in the proteins were performed. The generated models strongly suggest that a conformational change plays a significant role regarding the localization of Apoptin and that the export capabilities of PCV1VP3 are CRM1-dependent. -
Chapter 4.1 a 400 Kb Duplication, 2.4 Mb Triplication and 130 Kb
High-resolution karyotyping by oligonucleotide microarrays : the next revolution in cytogenetics Gijsbers, A.C.J. Citation Gijsbers, A. C. J. (2010, November 30). High-resolution karyotyping by oligonucleotide microarrays : the next revolution in cytogenetics. Retrieved from https://hdl.handle.net/1887/16187 Version: Corrected Publisher’s Version Licence agreement concerning inclusion of doctoral thesis in the License: Institutional Repository of the University of Leiden Downloaded from: https://hdl.handle.net/1887/16187 Note: To cite this publication please use the final published version (if applicable). Chapter 4.1 A 400 kb duplication, 2.4 Mb triplication and 130 kb duplication of 9q34.3 in a patient with severe mental retardation Antoinet CJ Gijsbers, Emilia K Bijlsma, Marjan M Weiss, Egbert Bakker, Martijn H Breuning, Mariëtte JV Hoffer and Claudia AL Ruivenkamp Center for Human and Clinical Genetics; Leiden University Medical Center (LUMC), Leiden, The Netherlands Eur J Med Genet 2008;51:479-487 Chapter 4 Abstract The presence of a duplication as well as a triplication in one chromosome is a rare rearrangement and not easy to distinguish with routine chromosomal analysis. Recent developments in array technologies, however, not only allow screening of the whole genome at a higher resolution, but also make it possible to characterize complex chromosomal rearrangements in more detail. Here we report a molecular cytogenetic analysis of a 16-year old female with severe mental retardation and an abnormality on the end of the long arm of chromosome 9. Subtelomeric multiplex ligation-dependent probe amplification (MLPA) analysis revealed that the extra material originated from the telomeric end of chromosome 9q. -
PDF Output of CLIC (Clustering by Inferred Co-Expression)
PDF Output of CLIC (clustering by inferred co-expression) Dataset: Num of genes in input gene set: 13 Total number of genes: 16493 CLIC PDF output has three sections: 1) Overview of Co-Expression Modules (CEMs) Heatmap shows pairwise correlations between all genes in the input query gene set. Red lines shows the partition of input genes into CEMs, ordered by CEM strength. Each row shows one gene, and the brightness of squares indicates its correlations with other genes. Gene symbols are shown at left side and on the top of the heatmap. 2) Details of each CEM and its expansion CEM+ Top panel shows the posterior selection probability (dataset weights) for top GEO series datasets. Bottom panel shows the CEM genes (blue rows) as well as expanded CEM+ genes (green rows). Each column is one GEO series dataset, sorted by their posterior probability of being selected. The brightness of squares indicates the gene's correlations with CEM genes in the corresponding dataset. CEM+ includes genes that co-express with CEM genes in high-weight datasets, measured by LLR score. 3) Details of each GEO series dataset and its expression profile: Top panel shows the detailed information (e.g. title, summary) for the GEO series dataset. Bottom panel shows the background distribution and the expression profile for CEM genes in this dataset. Overview of Co-Expression Modules (CEMs) with Dataset Weighting Scale of average Pearson correlations Num of Genes in Query Geneset: 13. Num of CEMs: 1. 0.0 0.2 0.4 0.6 0.8 1.0 Rps29 Rps28 Fau Rps6 Mrps2 Rps18 Mrps6 Rps25 -
Genetic Analyses of Human Fetal Retinal Pigment Epithelium Gene Expression Suggest Ocular Disease Mechanisms
ARTICLE https://doi.org/10.1038/s42003-019-0430-6 OPEN Genetic analyses of human fetal retinal pigment epithelium gene expression suggest ocular disease mechanisms Boxiang Liu 1,6, Melissa A. Calton2,6, Nathan S. Abell2, Gillie Benchorin2, Michael J. Gloudemans 3, 1234567890():,; Ming Chen2, Jane Hu4, Xin Li 5, Brunilda Balliu5, Dean Bok4, Stephen B. Montgomery 2,5 & Douglas Vollrath2 The retinal pigment epithelium (RPE) serves vital roles in ocular development and retinal homeostasis but has limited representation in large-scale functional genomics datasets. Understanding how common human genetic variants affect RPE gene expression could elu- cidate the sources of phenotypic variability in selected monogenic ocular diseases and pin- point causal genes at genome-wide association study (GWAS) loci. We interrogated the genetics of gene expression of cultured human fetal RPE (fRPE) cells under two metabolic conditions and discovered hundreds of shared or condition-specific expression or splice quantitative trait loci (e/sQTLs). Co-localizations of fRPE e/sQTLs with age-related macular degeneration (AMD) and myopia GWAS data suggest new candidate genes, and mechan- isms by which a common RDH5 allele contributes to both increased AMD risk and decreased myopia risk. Our study highlights the unique transcriptomic characteristics of fRPE and provides a resource to connect e/sQTLs in a critical ocular cell type to monogenic and complex eye disorders. 1 Department of Biology, Stanford University, Stanford, CA 94305, USA. 2 Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA. 3 Program in Biomedical Informatics, Stanford University School of Medicine, Stanford 94305 CA, USA. 4 Department of Ophthalmology, Jules Stein Eye Institute, UCLA, Los Angeles 90095 CA, USA. -
Supplementary Dataset S2
mitochondrial translational termination MRPL28 MRPS26 6 MRPS21 PTCD3 MTRF1L 4 MRPL50 MRPS18A MRPS17 2 MRPL20 MRPL52 0 MRPL17 MRPS33 MRPS15 −2 MRPL45 MRPL30 MRPS27 AURKAIP1 MRPL18 MRPL3 MRPS6 MRPS18B MRPL41 MRPS2 MRPL34 GADD45GIP1 ERAL1 MRPL37 MRPS10 MRPL42 MRPL19 MRPS35 MRPL9 MRPL24 MRPS5 MRPL44 MRPS23 MRPS25 ITB ITB ITB ITB ICa ICr ITL original ICr ICa ITL ICa ITL original ICr ITL ICr ICa mitochondrial translational elongation MRPL28 MRPS26 6 MRPS21 PTCD3 MRPS18A 4 MRPS17 MRPL20 2 MRPS15 MRPL45 MRPL52 0 MRPS33 MRPL30 −2 MRPS27 AURKAIP1 MRPS10 MRPL42 MRPL19 MRPL18 MRPL3 MRPS6 MRPL24 MRPS35 MRPL9 MRPS18B MRPL41 MRPS2 MRPL34 MRPS5 MRPL44 MRPS23 MRPS25 MRPL50 MRPL17 GADD45GIP1 ERAL1 MRPL37 ITB ITB ITB ITB ICa ICr original ICr ITL ICa ITL ICa ITL original ICr ITL ICr ICa translational termination MRPL28 MRPS26 6 MRPS21 PTCD3 C12orf65 4 MTRF1L MRPL50 MRPS18A 2 MRPS17 MRPL20 0 MRPL52 MRPL17 MRPS33 −2 MRPS15 MRPL45 MRPL30 MRPS27 AURKAIP1 MRPL18 MRPL3 MRPS6 MRPS18B MRPL41 MRPS2 MRPL34 GADD45GIP1 ERAL1 MRPL37 MRPS10 MRPL42 MRPL19 MRPS35 MRPL9 MRPL24 MRPS5 MRPL44 MRPS23 MRPS25 ITB ITB ITB ITB ICa ICr original ICr ITL ICa ITL ICa ITL original ICr ITL ICr ICa translational elongation DIO2 MRPS18B MRPL41 6 MRPS2 MRPL34 GADD45GIP1 4 ERAL1 MRPL37 2 MRPS10 MRPL42 MRPL19 0 MRPL30 MRPS27 AURKAIP1 −2 MRPL18 MRPL3 MRPS6 MRPS35 MRPL9 EEF2K MRPL50 MRPS5 MRPL44 MRPS23 MRPS25 MRPL24 MRPS33 MRPL52 EIF5A2 MRPL17 SECISBP2 MRPS15 MRPL45 MRPS18A MRPS17 MRPL20 MRPL28 MRPS26 MRPS21 PTCD3 ITB ITB ITB ITB ICa ICr ICr ITL original ITL ICa ICa ITL ICr ICr ICa original -
Structural Basis of Mitochondrial Translation Shintaro Aibara1†, Vivek Singh1,2, Angelika Modelska3‡, Alexey Amunts1,2*
RESEARCH ARTICLE Structural basis of mitochondrial translation Shintaro Aibara1†, Vivek Singh1,2, Angelika Modelska3‡, Alexey Amunts1,2* 1Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden; 2Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden; 3Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, Italy Abstract Translation of mitochondrial messenger RNA (mt-mRNA) is performed by distinct mitoribosomes comprising at least 36 mitochondria-specific proteins. How these mitoribosomal proteins assist in the binding of mt-mRNA and to what extent they are involved in the translocation of transfer RNA (mt-tRNA) is unclear. To visualize the process of translation in human mitochondria, we report ~3.0 A˚ resolution structure of the human mitoribosome, including the L7/L12 stalk, and eight structures of its functional complexes with mt-mRNA, mt-tRNAs, recycling factor and additional trans factors. The study reveals a transacting protein module LRPPRC-SLIRP that delivers mt-mRNA to the mitoribosomal small subunit through a dedicated platform formed by the mitochondria-specific protein mS39. Mitoribosomal proteins of the large subunit mL40, mL48, and *For correspondence: mL64 coordinate translocation of mt-tRNA. The comparison between those structures shows [email protected] dynamic interactions between the mitoribosome and its ligands, suggesting a sequential Present address: †Department mechanism of conformational changes. of Molecular Biology, Max- Planck-Institute for BiophysicalChemistry, Go¨ ttingen, Germany; ‡Aix Marseille Introduction Universite´, CNRS, INSERM, Translation in humans takes place in the cytosol and mitochondria. Mitochondrial translation is Centre d’Immunologie responsible for the maintenance of the cellular energetic balance through synthesis of proteins deMarseille-Luminy (CIML), Marseille, France involved in oxidative phosphorylation.