A central goal of modern aging research is to seek innovative ways to identify molecular strategies to maximize human healthspan. Although model systems such as C. elegans have been exploited to define hundreds of genes affecting longevity, specific and directed genetic screens for mutations that extend healthspan have not yet been pursued. A major reason for the roadblock in unleashing powerful genetic approaches to this profoundly important problem is that there are no rapidly scored indicators of healthspan that can be used broadly in genetic screens. Here we propose a collaborative project in which we combine expertise in C. elegans aging biology with sophisticated, state-of-the-art image processing capability. Our goal is to develop motion analysis programs that measure and report multiple aspects of age-related locomotion decline, establishing an easily scored and broadly useful healthspan scale.
Our specific aims are:
Aim I. To develop image analysis protocols to rapidly and reliably measure multiple parameters/indicators of C. elegans locomotion in liquid.
Aim II. To use automated analysis to score age-related swimming decline in wild type and exemplary healthspan mutants.
Aim III. To adapt and optimize swimming imaging protocols for high throughput analysis of healthspan. By executing our collaborative project with careful controls and training sets, we will reveal a considerable amount about the biology of age-related locomotory decline. We will describe multiple quantitative parameters that indicate how slow-down transpires both in populations and in individual animals; we may define specific criteria for animals that age poorly vs. those that age well; we will describe in detail how insulin signaling boosts locomotory healthspan; we will survey representative groups of longevity genes that affect multiple processes to determine those that also confer healthspan effects. Over the long term (beyond the scope of this application), we will use the developed healthspan scoring capacity to identify genetic and pharmacological approaches toward extending healthspan. We plan to make this scoring system available to the C. elegans research community for use in aging studies and additional applications. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21AG027513-02
Application #
7342116
Study Section
Cellular Mechanisms in Aging and Development Study Section (CMAD)
Program Officer
Murthy, Mahadev
Project Start
2006-08-01
Project End
2008-07-31
Budget Start
2007-08-01
Budget End
2008-07-31
Support Year
2
Fiscal Year
2007
Total Cost
$146,591
Indirect Cost
Name
Rutgers University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
001912864
City
New Brunswick
State
NJ
Country
United States
Zip Code
08901
Ibáñez-Ventoso, Carolina; Herrera, Christopher; Chen, Esteban et al. (2016) Automated Analysis of C. elegans Swim Behavior Using CeleST Software. J Vis Exp :
Mendenhall, Alexander; Driscoll, Monica; Brent, Roger (2016) Using measures of single-cell physiology and physiological state to understand organismic aging. Aging Cell 15:4-13
Restif, Christophe; Ibáñez-Ventoso, Carolina; Vora, Mehul M et al. (2014) CeleST: computer vision software for quantitative analysis of C. elegans swim behavior reveals novel features of locomotion. PLoS Comput Biol 10:e1003702
Yu, Simon; Driscoll, Monica (2011) EGF signaling comes of age: promotion of healthy aging in C. elegans. Exp Gerontol 46:129-34
Tsechpenakis, Gabriel; Bianchi, Laura; Metaxas, Dimitris et al. (2008) A novel computational approach for simultaneous tracking and feature extraction of C. elegans populations in fluid environments. IEEE Trans Biomed Eng 55:1539-49
Huang, Junzhou; Huang, Xiaolei; Metaxas, Dimitris et al. (2007) Adaptive metamorphs model for 3D medical image segmentation. Med Image Comput Comput Assist Interv 10:302-10