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Efficient analysis of small quantity of cells improves chances to understand disease

Date:
April 14, 2014
Source:
Virginia Tech (Virginia Polytechnic Institute and State University)
Summary:
Techniques have been developed that allow researchers to obtain reliable results over the course of disease development inside cells. Based on mouse studies, the researchers believe that "the single live animal data will grant unique insights into the molecular events involved in biological processes and provide an important basis for diagnosis, prognosis, drug design and discovery, and treatment strategy."

For more than a decade Chang Lu, associate professor of chemical engineering at Virginia Tech, has worked on the development of tools to efficiently analyze living cells. The long-term goal is to gain a better understanding of a range of diseases.

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In his lab, Lu and his students develop small devices with micrometer features for examining molecular events inside cells. These devices promote high sensitivity and are particularly suited for studying a low number of cells.

Based on their record of achievements, the National Institutes of Health (NIH) has awarded Lu a new $1.3 million, four-year research project, commonly referred to as an RO1 grant, to continue his work in probing dynamics in protein-DNA interactions during disease development. His collaborators are Liwu Li, professor of biological sciences at Virginia Tech, and Kai Tan, associate professor of internal medicine of the University of Iowa Carver College of Medicine.

Lu's earlier awards include a National Science Foundation CAREER Award and a Walter H. Coulter Early Career Award in Biomedical Engineering. He is also a core member of the School of Biomedical Engineering and Sciences, part of the Institute for Critical Technology and Applied Science at Virginia Tech.

Under the support of the new R01 grant, they will use live animal experiments with laboratory mice to understand the changes in the protein-DNA interaction as a disease develops, using tiny amounts of blood samples.

These blood samples are processed through Lu's investigative procedure called chromatin immunoprecipitation (ChIP) to examine the protein binding to DNA sites. The unique aspect of Lu's procedure is it produces reliable results based on as few as 10 to 100 cells as opposed to the previous standard that required as many as millions of cells, giving researchers a much more manageable process to use. The early versions of the work on this procedure were described in the journal, Lab on a Chip.

Lu's group will then monitor the same live mouse over the course of the disease development.

"We believe that the single live animal data will grant unique insights into the molecular events involved in these biological processes and provide an important basis for diagnosis, prognosis, drug design and discovery, and treatment strategy. Such data also most closely mimic what occurs in human patients during disease development and treatment, thus offering direct clinical relevance," Lu explained.


Story Source:

The above story is based on materials provided by Virginia Tech (Virginia Polytechnic Institute and State University). Note: Materials may be edited for content and length.


Journal Reference:

  1. Tao Geng, Ning Bao, Michael D. Litt, Trevor G. Glaros, Liwu Li, Chang Lu. Histone modification analysis by chromatin immunoprecipitation from a low number of cells on a microfluidic platform. Lab on a Chip, 2011; 11 (17): 2842 DOI: 10.1039/C1LC20253G

Cite This Page:

Virginia Tech (Virginia Polytechnic Institute and State University). "Efficient analysis of small quantity of cells improves chances to understand disease." ScienceDaily. ScienceDaily, 14 April 2014. <www.sciencedaily.com/releases/2014/04/140414091741.htm>.
Virginia Tech (Virginia Polytechnic Institute and State University). (2014, April 14). Efficient analysis of small quantity of cells improves chances to understand disease. ScienceDaily. Retrieved November 23, 2014 from www.sciencedaily.com/releases/2014/04/140414091741.htm
Virginia Tech (Virginia Polytechnic Institute and State University). "Efficient analysis of small quantity of cells improves chances to understand disease." ScienceDaily. www.sciencedaily.com/releases/2014/04/140414091741.htm (accessed November 23, 2014).

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