Reciprocal Changes in Phosphoenolpyruvate Carboxykinase and Pyruvate Kinase with Age Are a Determinant of Aging in Caenorhabditis elegans.

Aging involves progressive loss of cellular function and integrity, presumably caused by accumulated stochastic damage to cells. Alterations in energy metabolism contribute to aging, but how energy metabolism changes with age, how these changes affect aging, and whether they can be modified to modulate aging remain unclear. In locomotory muscle of post-fertile Caenorhabditis elegans, we identified a progressive decrease in cytosolic phosphoenolpyruvate carboxykinase (PEPCK-C), a longevity-associated metabolic enzyme, and a reciprocal increase in glycolytic pyruvate kinase (PK) that were necessary and sufficient to limit lifespan. Decline in PEPCK-C with age also led to loss of cellular function and integrity including muscle activity, and cellular senescence. Genetic and pharmacologic interventions of PEPCK-C, muscle activity, and AMPK signaling demonstrate that declines in PEPCK-C and muscle function with age interacted to limit reproductive life and lifespan via disrupted energy homeostasis. Quantifications of metabolic flux show that reciprocal changes in PEPCK-C and PK with age shunted energy metabolism toward glycolysis, reducing mitochondrial bioenergetics. Last, calorie restriction countered changes in PEPCK-C and PK with age to elicit anti-aging effects via TOR inhibition. Thus, a programmed metabolic event involving PEPCK-C and PK is a determinant of aging that can be modified to modulate aging.

Levodopa-Induced Motor and Dopamine Receptor Changes in Caenorhabditis elegans Overexpressing Human Alpha-Synuclein.

BACKGROUND: Levodopa-induced dyskinesia (LID) is a disabling complication of levodopa therapy in Parkinson's disease (PD) with no effective treatments. Fluctuations in levels of levodopa constitute a key risk factor of LID. There is a pressing need for the development of a simple animal model of LID. Several genetic and toxin-based models of PD in Caenorhabditis elegans have been described, which have advanced our understanding of PD pathophysiology. We aimed to study levodopa-induced changes in a Parkinson's disease model of C. elegans expressing human α-synuclein. METHODS: We exposed the α-synuclein C. elegans to levodopa in continuous and alternating fashions. Automated behavioral analysis was then used to quantify changes in motor activity. Confocal microscopy was used next to quantify changes in dopamine receptor distribution and expression in motor neurons of live C. elegans. RESULTS: Chronic exposure to levodopa led to hyperactivity of the α-synuclein C. elegans without meaningful increase in motor activity. There was also an increase in peripheral clustering and expression of dopamine receptors in motor neurons. Both of these changes were significantly higher with alternating, compared to continuous, exposure to levodopa. CONCLUSIONS: This is the first report of changes in motor and dopamine receptors induced by levodopa in C. elegans overexpressing human α-synuclein. We propose that these phenotypes represent a simple animal model of LID in C. elegans. Such a model holds the promise of enabling high-throughput screenings for potential therapeutic targets and drug candidates.

Combination of pulsed-wave Doppler and real-time three-dimensional color Doppler echocardiography for quantifying the stroke volume in the left ventricular outflow tract.

Real-time three-dimensional (3-D) color Doppler echocardiography (RT3D) is capable of quantifying flow. However, low temporal resolution limits its application to stroke volume (SV) measurements. The aim of the present study was, therefore, to develop a reliable method to quantify SV. In animal experiments, cross-sectional images of the LV outflow tract were selected from the RT3D data to calculate peak flow rates (Q(p3D)). Conventional pulsed-wave (PW) Doppler was performed to measure the velocity-time integral (VTI) and the peak velocity (V(p)). By assuming that the flow is proportional to the velocity temporal waveform, SV was calculated as alpha x Q(p3D) x VTI/V(p), where alpha is a temporal correction factor. There was an excellent correlation between the reference flow meter and RT3D SV (mean difference = -1. 3 mL, y = 1. 05 x -2. 5, r = 0. 94, p < 0. 01). The new method allowed accurate SV estimations without any geometric assumptions of the spatial velocity distributions.