Managbanag J R, Witten Tarynn M, Bonchev Danail, Fox Lindsay A, Tsuchiya Mitsuhiro, Kennedy Brian K, Kaeberlein Matt
Center for the Study of Biological Complexity, Virginia Commonwealth University, Richmond, Virginia, United States of America.
PLoS One. 2008;3(11):e3802. doi: 10.1371/journal.pone.0003802. Epub 2008 Nov 25.
Identification of genes that modulate longevity is a major focus of aging-related research and an area of intense public interest. In addition to facilitating an improved understanding of the basic mechanisms of aging, such genes represent potential targets for therapeutic intervention in multiple age-associated diseases, including cancer, heart disease, diabetes, and neurodegenerative disorders. To date, however, targeted efforts at identifying longevity-associated genes have been limited by a lack of predictive power, and useful algorithms for candidate gene-identification have also been lacking.
METHODOLOGY/PRINCIPAL FINDINGS: We have utilized a shortest-path network analysis to identify novel genes that modulate longevity in Saccharomyces cerevisiae. Based on a set of previously reported genes associated with increased life span, we applied a shortest-path network algorithm to a pre-existing protein-protein interaction dataset in order to construct a shortest-path longevity network. To validate this network, the replicative aging potential of 88 single-gene deletion strains corresponding to predicted components of the shortest-path longevity network was determined. Here we report that the single-gene deletion strains identified by our shortest-path longevity analysis are significantly enriched for mutations conferring either increased or decreased replicative life span, relative to a randomly selected set of 564 single-gene deletion strains or to the current data set available for the entire haploid deletion collection. Further, we report the identification of previously unknown longevity genes, several of which function in a conserved longevity pathway believed to mediate life span extension in response to dietary restriction.
CONCLUSIONS/SIGNIFICANCE: This work demonstrates that shortest-path network analysis is a useful approach toward identifying genetic determinants of longevity and represents the first application of network analysis of aging to be extensively validated in a biological system. The novel longevity genes identified in this study are likely to yield further insight into the molecular mechanisms of aging and age-associated disease.
鉴定调控寿命的基因是衰老相关研究的主要焦点，也是公众高度关注的领域。除了有助于更好地理解衰老的基本机制外，这类基因还代表了多种与年龄相关疾病（包括癌症、心脏病、糖尿病和神经退行性疾病）治疗干预的潜在靶点。然而，迄今为止，识别与寿命相关基因的针对性研究因缺乏预测能力而受到限制，同时也缺乏用于识别候选基因的有效算法。
方法/主要发现：我们利用最短路径网络分析来鉴定酿酒酵母中调控寿命的新基因。基于一组先前报道的与寿命延长相关的基因，我们将最短路径网络算法应用于现有的蛋白质-蛋白质相互作用数据集，以构建最短路径寿命网络。为了验证该网络，我们测定了与最短路径寿命网络预测成分相对应的88个单基因缺失菌株的复制衰老潜力。我们在此报告，相对于随机选择的564个单基因缺失菌株或整个单倍体缺失文库的现有数据集，通过我们的最短路径寿命分析鉴定出的单基因缺失菌株中，赋予复制寿命增加或减少的突变显著富集。此外，我们报告了此前未知的寿命基因的鉴定结果，其中几个基因在一个保守的寿命途径中发挥作用，该途径被认为可介导因饮食限制而导致的寿命延长。
结论/意义：这项工作表明，最短路径网络分析是识别寿命遗传决定因素的一种有用方法，代表了衰老网络分析在生物系统中首次得到广泛验证的应用。本研究中鉴定出的新寿命基因可能会进一步深入了解衰老和与年龄相关疾病的分子机制。
