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Revealing system-level correlations between aging and calorie restriction using a mouse transcriptome

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Abstract

Although systems biology is a perfect framework for investigating system-level declines during aging, only a few reports have focused on a comprehensive understanding of system-level changes in the context of aging systems. The present study aimed to understand the most sensitive biological systems affected during aging and to reveal the systems underlying the crosstalk between aging and the ability of calorie restriction (CR) to effectively slow-down aging. We collected and analyzed 478 aging- and 586 CR-related mouse genes. For the given genes, the biological systems that are significantly related to aging and CR were examined according to three aspects. First, a global characterization by Gene Ontology (GO) was performed, where we found that the transcriptome (a set of genes) for both aging and CR were strongly related in the immune response, lipid metabolism, and cell adhesion functions. Second, the transcriptional modularity found in aging and CR was evaluated by identifying possible functional modules, sets of genes that show consistent expression patterns. Our analyses using the given functional modules, revealed systemic interactions among various biological processes, as exemplified by the negative relation shown between lipid metabolism and the immune response at the system level. Third, transcriptional regulatory systems were predicted for both the aging and CR transcriptomes. Here, we suggest a systems biology framework to further understand the most important systems as they age.

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Acknowledgements

This research was supported by the Korea Science and Engineering Foundation (KOSEF) [NO.2007-00376 and R01-2007-000-20852-0(2007)]. We thank the Aging Tissue Bank for providing aging research resources.

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Authors and Affiliations

  1. Department of Life Science, Gwangju Institute of Science and Technology, 1 Oryong-dong, Buk-gu, Gwangju, 500-712, Republic of Korea

    Seong-Eui Hong

  2. Interdisciplinary Research Program of Bioinformatics, College of Natural Science, Pusan National University, Gumjung-gu, Busan, 609-735, Republic of Korea

    Hyoung-Sam Heo

  3. Department of Pharmacy, Aging Tissue Bank, College of Pharmacy, Pusan National University, 30 Changjeon-dong, Kumjung-gu, Busan, 609-735, Republic of Korea

    Dae Hyun Kim, Min-Sun Kim, Jaewon Lee & Hae Young Chung

  4. Korean BioInformation Center, Korea Research Institute of Bioscience and Biotechnology, 52 Eoeun-dong, Yooseong-goo, Daejeon, 305-333, Republic of Korea

    Chul Hong Kim

  5. Department of Molecular Biology, College of Natural Sciences, Pusan National University, Gumjung-gu, Busan, 609-735, Republic of Korea

    Mi-Ae Yoo

  6. Department of Physiology, The University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA

    Byung Pal Yu

  7. Department of Aging and Geriatrics, College of Medicine, University of Florida, Gainesville, FL, 21611-2610, USA

    Christiaan Leeuwenburgh & Hae Young Chung

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  1. Seong-Eui Hong
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  10. Hae Young Chung
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Corresponding author

Correspondence to Hae Young Chung.

Electronic supplementary material

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ESM File 1

List of microarray studies used for coherence analysis. Four microarray studies were analyzed to investigate the consistent expressional patterns between transcription factors and their downstream genes. (DOC 29 kb)

ESM File 2

Detailed information on the aging and CR transcriptomes. This file gives detailed information (e.g., gene name, the various IDs, and expressional changes) about the aging and CR transcriptomes and contains two separate sheets for each transcriptome. (XLS 195 kb)

ESM File 3

List of microarray studies used for the construction of functional modules. Detailed information about the microarray studies used for the construction of functional modules is contained in this file. The information is referred from the annotations of the GEO platform. (XLS 52 kb)

ESM File 4

Consistent expression patterns between Tmp4 and Dck. The expression profiles of Tmp4 and Dck across aging-related conditions listed in ESM File 2 are consistent to each other. The similar expression profiles indicate the close relation in their function; however, few studies on the functional relation between these genes are available. Experimental validation remains challenging. (TIF 891 kb)

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Hong, SE., Heo, HS., Kim, D.H. et al. Revealing system-level correlations between aging and calorie restriction using a mouse transcriptome. AGE 32, 15–30 (2010). https://doi.org/10.1007/s11357-009-9106-3

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  • DOI: https://doi.org/10.1007/s11357-009-9106-3

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