[Note: HIgh resolution photos of Carl Johnson and Hua Xu are available here and here.]
Figuring out how biological clocks evolved and extracting clues to environmental factors that cause cancer from electronic medical records: These are the goals of two projects that have been funded by a National Institutes of Health (NIH) program which supports speculative research that may have a profound impact on our understanding of biology and human disease.
In living organisms ranging from pond scum to humans, molecular pacemakers called biological clocks control a wide variety of basic biological processes. When they get out of whack, they cause a number of problems ranging from Seasonal Affective Disorder to some types of depression to obesity and cardiovascular disease.
A long-standing mystery regarding biological clocks is how a precise 24-hour cycle can evolve from basic cellular processes that operate at [millisecond/sub-second] time frames. Professor of Biological Sciences Carl Johnson has decided to address this question in a particularly direct fashion by seeing if he can force biological clocks to evolve in single-celled organisms that don’t have them.
With the support of the grant from the National Institute of General Medical Sciences, Johnson will put separate communities of the intestinal bacteria Escherichia coli and of Baker’s yeast into environments where the temperature, visible light and ultraviolet light vary on an 18-hour cycle. He will keep them in these conditions for 1,000 generations or more (something that will take several months) and see which environment factor, or combination of factors, leads to the development of 18-hour bioclocks. Understanding these links may help provide therapies for diseases related to clock disruption.
At the same time, Assistant Professor of Biomedical Informatics Hua Xu is applying “natural language processing technologies” to extract detailed information from electronic medical records that can aid studies of cancer in large populations.
Natural language processing is a way of teaching computers to read the text that doctors, nurses and other providers put into the electronic medical record. Statistical and informatics methods then can be used to look for common themes or concepts.
Observational epidemiological research to determine whether an environmental exposure may increase the risk for a certain cancer in a particular population, for example, is extremely labor-intensive and time-consuming.
With the help of the grant from the National Cancer Institute, Xu said he hopes to prove that computers can help answer an epidemiological question “in a very short time at a very low cost.”
Both grants were approved by NIH’s EUREKA program. EUREKA stands for Exceptional, Unconventional Research Enabling Knowledge Acceleration. According to NIH, the program funds exceptionally innovative research that, if successful, will have an unusually high impact. It targets investigators who are testing novel, unconventional hypotheses or are pursuing major methodological or technical challenges. Features of the EUREKA program include direct costs of up to $800,000 over four years.
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