AGE

, Volume 35, Issue 5, pp 1937–1947

A comparative cellular and molecular biology of longevity database

Authors

    • Department of Biological SciencesBrock University
  • Ping Liang
    • Department of Biological SciencesBrock University
  • Xuemei Luo
    • Department of Biological SciencesBrock University
  • Melissa M. Page
    • Integrative and Environmental Physiology, Institute of Biological and Environmental SciencesUniversity of Aberdeen
  • Emily J. Gallagher
    • Department of Biological SciencesBrock University
  • Casey A. Christoff
    • Department of Biological SciencesBrock University
  • Ellen L. Robb
    • Department of Biological SciencesBrock University
Article

DOI: 10.1007/s11357-012-9458-y

Cite this article as:
Stuart, J.A., Liang, P., Luo, X. et al. AGE (2013) 35: 1937. doi:10.1007/s11357-012-9458-y

Abstract

Discovering key cellular and molecular traits that promote longevity is a major goal of aging and longevity research. One experimental strategy is to determine which traits have been selected during the evolution of longevity in naturally long-lived animal species. This comparative approach has been applied to lifespan research for nearly four decades, yielding hundreds of datasets describing aspects of cell and molecular biology hypothesized to relate to animal longevity. Here, we introduce a Comparative Cellular and Molecular Biology of Longevity Database, available at (http://genomics.brocku.ca/ccmbl/), as a compendium of comparative cell and molecular data presented in the context of longevity. This open access database will facilitate the meta-analysis of amalgamated datasets using standardized maximum lifespan (MLSP) data (from AnAge). The first edition contains over 800 data records describing experimental measurements of cellular stress resistance, reactive oxygen species metabolism, membrane composition, protein homeostasis, and genome homeostasis as they relate to vertebrate species MLSP. The purpose of this review is to introduce the database and briefly demonstrate its use in the meta-analysis of combined datasets.

Keywords

Life spanDatabaseDNA repairProtein homeostasisAntioxidant enzymesStress resistance

Copyright information

© American Aging Association 2012