Skip to main content
Premium Trial:

Request an Annual Quote

Cell-Based Assets: 2005 NIH Awards for Cell-Based Assay Research


Indicator Cells for Antiviral Screening for Filoviruses. Start date: Aug. 1, 2002. Expires: Feb. 28, 2006. Fiscal year 2005 award amount: $368,309. Principal Investigator: Paul Olivo, Apath, St. Louis, Mo.

No abstract available.

Screening for Anti-RSV Compounds with Indicator Cells. Start date: July 1, 2000. Expires: April 30, 2005. Fiscal year 2005 award amount: $359,466. Principal Investigator: Paul Olivo, Apath, St. Louis, Mo.

According to the proposal abstract, the goal of this project is to use an infection-independent cell-based assay to identify compounds that inhibit respiratory syncytial virus (RSV). The basis of this bioassay is expression of a reporter gene from an artificial viral genome present within the cytoplasm of transfected cells. To identify “hits” that inhibit replication of RSV, the applicants plan to screen a unique library of natural compounds and several novel libraries of synthetic compounds. Apath’s partner has developed a proprietary system for making compound libraries from plant-based material.

Q3DM/Beckman Coulter IC 100 Automated Microscope System. Start date: Feb. 1, 2005. Expires: Jan. 31, 2006. Fiscal year 2005 award amount: $420,880. Principal Investigator: Mark Mercola, Burnham Institute, La Jolla, Calif.

According to the proposal abstract, the funding is requested for an automated, high throughput microscope manufactured by Q3DM/Beckman Coulter. The instrument (known as IC-100, previously Eidaq 100) automatically scans and acquires thousands of brightfield or fluorescent images of cells in multiwell dishes. Sophisticated software analyzes the images and calculates many measurements of the intensity and localization of fluorescent or brighfield objects within individual cells. Thus, it is possible to evaluate a range of subcellular changes, such as gene or protein expression, protein or organelle trafficking, and signal transduction, in response to many reagents or culture conditions on living or fixed cells. The sole accessory requested is a robotic arm and incubator to permit the automatic loading of multiwell cell culture plates onto the microscope. This will expand the capacity of the instrument by enabling unattended operation. The user base is large and diverse, representing the Burnham Institute, Salk Institute, and University of California, San Diego, the abstract states.

Bacterial Cell-Based Assays for Prion Proteins. Start date: March 1, 2005. Expires: Feb. 28, 2007. Fiscal year 2005 award amount: $211,875. Principal Investigator: Ann Hochschild, Harvard University Medical School, Boston.

According to the proposal abstract, the objective of the research is to develop a transcription-based assay for the conversion of protein domains to the prion state and to use such an assay as the basis for a genetic screen to identify prion-forming domains from bacteria and other organisms. The design of this assay will be informed by other transcription-based assays previously developed in the laboratory. The long-term goal of the proposed work is to mobilize bacterial genetics as a new tool to study the in vivo behavior of prion proteins, whether of bacterial origin or from eukaryotic cells.

Single-Cell Assay to Understand Signaling Networks. Start date: Jan.1, 2001. Expires: Dec. 31, 2005. Fiscal year 2005 award amount: $143,721. Principal Investigator: Mary Teruel, Stanford University, Stanford, Calif.

According to the proposal abstract, research candidate has recently co-developed an Evanescent-wave Single Cell Array Macroscope (E-SCAM) and has used it to show that time courses of protein translocation and activation can be measured in thousands of single cells simultaneously. By continuing to develop this E-SCAM system for monitoring multiple signaling events over time, along with methodology to quantitatively perturb such a network, the proposed work will be able to establish quantitative kinetic relationships between signaling network parameters and begin to generate models of how cellular signal transduction networks function.

An Automated Platform for Kinase Assays on Patient Cells. Start date: Aug.14, 2003. Expires: May 31, 2008. Fiscal year 2005 award amount: $16,557. Principal Investigator: Nancy Allbritton, University of California, Irvine.

According to the to proposal abstract, the funding is requested to help design, build, and test an analytical platform for the performance of single-cell kinase assays on primary patient cells. State-of-the art microfabrication technology will be employed to engineer a microfluidic system that integrates electronics and photonics for the performance of microanalytical chemical separations. The microfluidic system will be coupled to a meso-scale incubator for sample preparation. The components of the hybrid device will be designed and optimized individually for their given function, and then integrated into a multifunctional platform. This platform will be used to carry out a newly developed method for assaying the catalytic activity of specific kinases in individual cells. In the final phase of the work, assays of kinases known to be essential for the development and maintenance of an exemplary disease will be demonstrated in patient samples.

Yeast-Based Screening for Mammalian K Channel Modulators. Start date: Feb. 1, 2004. Expires: Jan. 31, 2006. Fiscal year 2005 award amount: $171,703. Principal Investigator: Elena Makina, University of Pittsburgh, Penn.

No abstract available.


The Scan

Shape of Them All

According to BBC News, researchers have developed a protein structure database that includes much of the human proteome.

For Flu and More

The Wall Street Journal reports that several vaccine developers are working on mRNA-based vaccines for influenza.

To Boost Women

China's Ministry of Science and Technology aims to boost the number of female researchers through a new policy, reports the South China Morning Post.

Science Papers Describe Approach to Predict Chemotherapeutic Response, Role of Transcriptional Noise

In Science this week: neural network to predict chemotherapeutic response in cancer patients, and more.