Tracking genes on the path to genetic treatment
Before doctors like Matthias Kretzler can begin using the results of molecular research to treat patients, they need science to find an effective way to match genes with the specific cells involved in disease. As Kretzler explains, finding that link would eventually let physicians create far more effective diagnostic tools and treatments.
‘Among many uses, it would allow us to develop cell-type targeted therapies,’ said Kretzler, a University of Michigan professor of internal medicine and computational medicine and bioinformatics. He recently collaborated with Princeton University professor Olga Troyanskaya on a way to match genes to cells. ‘If you identify a [disease] that is in the liver or in the kidney, you could target those areas and not affect other parts of the body,’ he said.
Although scientists have decoded the human genome — the list of all the genes in human cells — they still have great difficulty determining the specific genes that are activated to make a kidney cell as opposed to a liver or heart cell.
In theory, an easy way to link genes to cells would be to isolate a cell and test it. However, solid human tissue is so closely packed that even the finest surgical techniques cannot separate types of cells efficiently enough for analysis. A kidney biopsy, for example, produces a mix of several different types of cells that Kretzler dismisses as ‘kidney soup.’
Princeton University and University of Michigan researchers have developed a system that allows computers to ‘virtually dissect’ a kidney in a way that surgery cannot. The machine uses data from an array of gene-activity measurements in patients’ kidney biopsies to mathematically separate cells and identify genes that are turned on in a specific cell type. The researchers identified 136 genes involved in the creation of a critical kidney cell called a podocyte, tiny cells that serve as filters in the kidneys and are frequently involved in kidney disease.
‘We call it in-silico nano-dissection,’ said Troyanskaya, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics. Using a large database of such gene-activity measurements to track genetic lineage allows scientists to refine their analysis through thousands of measurements, something that would be impossible with individual cell cultures, she said.
The method has proven far faster and significantly more effective than current techniques. Researchers from Kretzler’s lab at Michigan and Troyanskaya’s at Princeton reported that they had identified 136 genes involved in the creation of a critical kidney cell called a podocyte. In decades of research, only 46 had been previously identified.
‘The potential for this is huge,’ said Behzad Najafian, a University of Washington assistant professor of pathology who specializes in renal pathology. ‘I believe this novel technique, which is a significant improvement in cell lineage-specific gene-expression analysis, will not only help us understand the pathophysiology of kidney diseases better through biopsy studies, but also provides a strong tool for discovery or validation of cell-specific urine or plasma biomarkers.’ Princeton University
