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Intramural Papers of the Month

By Robin Arnette
June 2009

Urate May Protect Against Parkinson's Disease

NIEHS researchers have found that a higher concentration of urate in the blood was associated with a lower risk of Parkinson's disease. Previous studies from other research groups suggested that urate offered a protective effect against Parkinson's disease among Caucasian men, but data on Caucasian women and other ethnic groups were lacking.

The study population included 15,036 volunteers of the Atherosclerosis Risk In Communities (ARIC) cohort, a twenty-year long, biracial and population-based study that included 55 percent women and 27 percent African Americans. These participants were recruited from four communities in the U.S. between 1987 and 1989 and have since been followed with three triennial visits and annual surveillance.

In this study, the plasma concentration of urate measured at baseline was inversely associated with Parkinson's risk. The association was clear for Caucasian men and was also suggested for Caucasian women and African Americans. Since oxidative stress destroys the dopaminergic neurons in the substantia nigra, scientists theorized that urate - a potent endogenous antioxidant - removes reactive nitrogen and oxygen radicals and thus prevents neuronal loss.

Citation: Chen H, Mosley TH, Alonso A, Huang X (http://www.ncbi.nlm.nih.gov/pubmed/19299404?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum) Exit NIEHS. 2009. Plasma urate and Parkinson's disease in the Atherosclerosis Risk in Communities (ARIC) study. Am J Epidemiol 169(9):1064-1069.

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Cholesterol-Rich Membrane Microdomains Play Crucial Role in MEK-ERK Pathway

Lipopolysaccharide (LPS), an initiator of the macrophage innate immune response, triggers downstream signaling by recruiting and activating proteins in lipid rafts - cholesterol-rich membrane microdomains. NIEHS investigators have determined that raft compartmentalization regulates proteasome activity in activation of the MEK-ERK pathway.

Previous reports suggested an essential role for proteasomal degradation of IKB kinase-phosphorylated p105 in LPS activation of ERK mitogen-activated protein kinase, so the research team used quantitative proteomics to analyze macrophage detergent-resistant membrane (DRM) raft isolates during LPS exposure to identify a role for rafts in organizing these events.

The research team uncovered the following results:

  • The LPS signaling cascade from proteasomal degradation of p105 to ERK activation occurs in rafts and requires raft integrity.
  • LPS alters the complement of 26S proteasome subunits in rafts, selectively activating the proteasome within this subcellular compartment. This report is the first publication to directly demonstrate proteasome function within rafts.

This work provides evidence that proteasome subunits localize to rafts, organize within rafts following LPS exposure, and experience functional changes in activity during LPS signaling.

Citation: Dhungana S, Merrick BA, Tomer KB, Fessler MB (http://www.ncbi.nlm.nih.gov/pubmed/18815123?ordinalpos=4&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum) Exit NIEHS. 2009. Quantitative proteomics analysis of macrophage rafts reveals compartmentalized activation of the proteasome and of proteasome-mediated ERK activation in response to lipopolysaccharide. Mol Cell Proteomics 8(1):201-213.

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SIRT1 May Prevent Obesity-Associated Diseases

SIRT1, a member of the family of NAD+-dependent histone deacetylases (HDACs) known as sirtuins, regulates lipid homeostasis in response to nutrient and hormonal signals. The research, performed by NIEHS scientists, showed that a major target of SIRT1 in the liver is the peroxisome proliferators-activated receptor α (PPARα) - a nuclear receptor that mediates the response to fasting and starvation.

Since the liver is the key metabolic organ that regulates lipid metabolism, its dysfunction is responsible for many human illnesses, such as dyslipidemia and fatty liver disease. The research team sought to better understand the mechanisms that control lipid and energy metabolism, with the goal of developing new therapeutic strategies.

The authors demonstrated that specific deletion of hepatic SIRT1 drastically impaired PPARα signaling, while over expression of SIRT1 induced the expression of PPARα targets. When fed a high-fat diet, liver-specific SIRT1 knockout mice developed hepatic inflammation, endoplasmic reticulum stress, and hepatic steatosis - the buildup of fat in liver cells. The findings suggest that therapeutic strategies designed to modulate SIRT1 activity may be helpful in treating hepatic diseases and obesity-associated metabolic syndrome.

Citation: Purushotham A, Schug TT, Xu Q, Surapureddi S, Guo X, Li X (http://www.ncbi.nlm.nih.gov/pubmed/19356714?ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_DefaultReportPanel.Pubmed_RVDocSum) Exit NIEHS. 2009. Hepatocyte-specific deletion of SIRT1 alters fatty acid metabolism and results in hepatic steatosis and inflammation. Cell Metab 9(4):327-338.

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A New Algorithm for Protein Binding Site Analysis

Scientists looking for a faster way to identify motifs in large amounts of sequence data now have a free de novo motif discovery tool called GADEM that can do the job. Developed by researchers at NIEHS, GADEM combines word-enumeration with a local expectation-maximization (EM) search technique that employs an efficient search algorithm. It is an extension of the well-known MEME algorithm and is easy to use.

GADEM's initial models are generated from spaced dyads that use over-represented words, usually three to six characters in length, as "seeds." Then, GADEM uses a genetic algorithm (GA) to guide the formation of the spaced dyads from the seeds. When the program was applied to six genome-wide ChIP datasets, which totaled approximately 0.5 to 1 million nucleotides, the expected p53 motif was identified every time. In addition, 15-30 motifs of various lengths were identified in each dataset.

GADEM is a novel de novo motif discovery tool that may be applied to large scale sequence data for unbiased motif discovery.

Citation: Li L (http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed&cmd=DetailsSearch&term=GADEM%5BTitle%5D+AND+(genetic%5BTitle%5D+AND+algorithm%5BTitle%5D+AND+guided%5BTitle%5D+AND+formation%5BTitle%5D+AND+spaced%5BTitle%5D+AND+dyads%5BTitle%5D+AND+coupled%5BTitle%5D+AND+EM%5BTitle%5D)&log$=activity) Exit NIEHS. 2009. GADEM: A genetic algorithm guided formation of spaced dyads coupled with an EM algorithm for motif discovery. J Comput Biol 16(2):317-329.



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