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Kanfi Y, Naiman S, Amir G, Peshti V, Zinman G, Nahum L, Bar-Joseph Z, Cohen HY. The sirtuin SIRT6 regulates lifespan in male mice. Nature 2012; 483:218-21. [PMID: 22367546 DOI: 10.1038/nature10815] [Citation(s) in RCA: 739] [Impact Index Per Article: 61.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2010] [Accepted: 12/19/2011] [Indexed: 01/07/2023]
Abstract
The significant increase in human lifespan during the past century confronts us with great medical challenges. To meet these challenges, the mechanisms that determine healthy ageing must be understood and controlled. Sirtuins are highly conserved deacetylases that have been shown to regulate lifespan in yeast, nematodes and fruitflies. However, the role of sirtuins in regulating worm and fly lifespan has recently become controversial. Moreover, the role of the seven mammalian sirtuins, SIRT1 to SIRT7 (homologues of the yeast sirtuin Sir2), in regulating lifespan is unclear. Here we show that male, but not female, transgenic mice overexpressing Sirt6 (ref. 4) have a significantly longer lifespan than wild-type mice. Gene expression analysis revealed significant differences between male Sirt6-transgenic mice and male wild-type mice: transgenic males displayed lower serum levels of insulin-like growth factor 1 (IGF1), higher levels of IGF-binding protein 1 and altered phosphorylation levels of major components of IGF1 signalling, a key pathway in the regulation of lifespan. This study shows the regulation of mammalian lifespan by a sirtuin family member and has important therapeutic implications for age-related diseases.
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Affiliation(s)
- Yariv Kanfi
- The Mina & Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel
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Zinman G, Brower-Sinning R, Emeche CH, Ernst J, Huang GTW, Mahony S, Myers AJ, O'Dee DM, Flynn JL, Nau GJ, Ross TM, Salter RD, Benos PV, Bar Joseph Z, Morel PA. Large scale comparison of innate responses to viral and bacterial pathogens in mouse and macaque. PLoS One 2011; 6:e22401. [PMID: 21789257 PMCID: PMC3138787 DOI: 10.1371/journal.pone.0022401] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2011] [Accepted: 06/21/2011] [Indexed: 11/19/2022] Open
Abstract
Viral and bacterial infections of the lower respiratory tract are major causes of morbidity and mortality worldwide. Alveolar macrophages line the alveolar spaces and are the first cells of the immune system to respond to invading pathogens. To determine the similarities and differences between the responses of mice and macaques to invading pathogens we profiled alveolar macrophages from these species following infection with two viral (PR8 and Fuj/02 influenza A) and two bacterial (Mycobacterium tuberculosis and Francisella tularensis Schu S4) pathogens. Cells were collected at 6 time points following each infection and expression profiles were compared across and between species. Our analyses identified a core set of genes, activated in both species and across all pathogens that were predominantly part of the interferon response pathway. In addition, we identified similarities across species in the way innate immune cells respond to lethal versus non-lethal pathogens. On the other hand we also found several species and pathogen specific response patterns. These results provide new insights into mechanisms by which the innate immune system responds to, and interacts with, invading pathogens.
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Affiliation(s)
- Guy Zinman
- Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Rachel Brower-Sinning
- Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Chineye H. Emeche
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Jason Ernst
- Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
| | - Grace Tzu-Wei Huang
- Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Shaun Mahony
- Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Amy J. Myers
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Dawn M. O'Dee
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - JoAnne L. Flynn
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Gerard J. Nau
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Ted M. Ross
- Department of Microbiology and Molecular Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Russell D. Salter
- Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Panayiotis V. Benos
- Department of Computational Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
| | - Ziv Bar Joseph
- Lane Center for Computational Biology, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (PAM); (ZBJ)
| | - Penelope A. Morel
- Department of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America
- * E-mail: (PAM); (ZBJ)
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Klutstein M, Siegfried Z, Gispan A, Farkash-Amar S, Zinman G, Bar-Joseph Z, Simchen G, Simon I. Combination of genomic approaches with functional genetic experiments reveals two modes of repression of yeast middle-phase meiosis genes. BMC Genomics 2010; 11:478. [PMID: 20716365 PMCID: PMC3091674 DOI: 10.1186/1471-2164-11-478] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2010] [Accepted: 08/17/2010] [Indexed: 11/10/2022] Open
Abstract
Background Regulation of meiosis and sporulation in Saccharomyces cerevisiae is a model for a highly regulated developmental process. Meiosis middle phase transcriptional regulation is governed by two transcription factors: the activator Ndt80 and the repressor Sum1. It has been suggested that the competition between Ndt80 and Sum1 determines the temporal expression of their targets during middle meiosis. Results Using a combination of ChIP-on-chip and expression profiling, we characterized a middle phase transcriptional network and studied the relationship between Ndt80 and Sum1 during middle and late meiosis. While finding a group of genes regulated by both factors in a feed forward loop regulatory motif, our data also revealed a large group of genes regulated solely by Ndt80. Measuring the expression of all Ndt80 target genes in various genetic backgrounds (WT, sum1Δ and MK-ER-Ndt80 strains), allowed us to dissect the exact transcriptional network regulating each gene, which was frequently different than the one inferred from the binding data alone. Conclusion These results highlight the need to perform detailed genetic experiments to determine the relative contribution of interactions in transcriptional regulatory networks.
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Affiliation(s)
- Michael Klutstein
- Department of Microbiology and Molecular Genetics, The Institute for Medical Research-Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel
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Kuo D, Tan K, Zinman G, Ravasi T, Bar-Joseph Z, Ideker T. Evolutionary divergence in the fungal response to fluconazole revealed by soft clustering. Genome Biol 2010; 11:R77. [PMID: 20653936 PMCID: PMC2926788 DOI: 10.1186/gb-2010-11-7-r77] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2010] [Revised: 07/09/2010] [Accepted: 07/23/2010] [Indexed: 11/25/2022] Open
Abstract
Background Fungal infections are an emerging health risk, especially those involving yeast that are resistant to antifungal agents. To understand the range of mechanisms by which yeasts can respond to anti-fungals, we compared gene expression patterns across three evolutionarily distant species - Saccharomyces cerevisiae, Candida glabrata and Kluyveromyces lactis - over time following fluconazole exposure. Results Conserved and diverged expression patterns were identified using a novel soft clustering algorithm that concurrently clusters data from all species while incorporating sequence orthology. The analysis suggests complementary strategies for coping with ergosterol depletion by azoles - Saccharomyces imports exogenous ergosterol, Candida exports fluconazole, while Kluyveromyces does neither, leading to extreme sensitivity. In support of this hypothesis we find that only Saccharomyces becomes more azole resistant in ergosterol-supplemented media; that this depends on sterol importers Aus1 and Pdr11; and that transgenic expression of sterol importers in Kluyveromyces alleviates its drug sensitivity. Conclusions We have compared the dynamic transcriptional responses of three diverse yeast species to fluconazole treatment using a novel clustering algorithm. This approach revealed significant divergence among regulatory programs associated with fluconazole sensitivity. In future, such approaches might be used to survey a wider range of species, drug concentrations and stimuli to reveal conserved and divergent molecular response pathways.
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Affiliation(s)
- Dwight Kuo
- Department of Bioengineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA
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Champ PC, Binnewies TT, Nielsen N, Zinman G, Kiil K, Wu H, Bohlin J, Ussery DW. Genome update: purine strand bias in 280 bacterial genomes. Microbiology (Reading) 2006; 152:579-583. [PMID: 16514138 DOI: 10.1099/mic.0.28637-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- P Christoph Champ
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Tim T Binnewies
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Natasja Nielsen
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Guy Zinman
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Kristoffer Kiil
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Heng Wu
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - Jon Bohlin
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
| | - David W Ussery
- Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, The Technical University of Denmark, DK-2800 Kgs, Lyngby, Denmark
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