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Young Investigator Profile: Jonathan Karr

Fellow, Mount Sinai School of Medicine

Recommended by Eric Schadt, Mount Sinai School of Medicine

NEW YORK (GenomeWeb) – When Jonathan Karr was finishing college, systems biology was taking off and becoming popular. As a senior, he took a systems biology class and was hooked.

"I just really loved the course and the approach to biology — there was a sort of logical, mathematical, and physical way of thinking about biological systems to generate predictions," Karr told GenomeWeb. 

In particular, he became interested in combining high-throughput data, like gene expression and mass spectrometry data, with dynamic modeling to generate predictions.

These days, Karr and his collaborators at the Center for Regulatory Genomics in Spain are modeling growth in Mycoplasma pneumoniae with the eventual aim of engineering the bacteria. To do this, they are developing knockout bacterial strains in which they are measuring the growth rate and then feeding that data back into their models. Those models are then evaluating what changes need to be made to the M. pneumoniae genome — such as increasing the expression levels of certain genes while decreasing the expression of certain other genes — to increase bacterial growth.

In the end, he said they'd synthesize the new genome and transplant it to a recipient cell to boot it up as a new species.

At the same time, Karr and his colleagues are applying their modeling approach to human cells to build a comprehensive model of Mendelian diseases. This model, he said, might not be able to predict the function of every gene, but would be able to account for the function of the genes linked to Mendelian disease.

"The idea is that these Mendelian diseases, at least many of them, are diseases that appear very early in childhood or during embryonic development, so the hope is that if we have the models, maybe we can make patient-specific recommendations during IVF as doctors think about one embryo versus another to implant," he said.

The difficulty is that the models are limited by the data that's fed into them. Currently, Karr noted that he and his colleagues rarely have single cell-level data or dynamic data, and instead have to rely on population data.

To try to overcome this, he is working with groups that are actively collecting data for the organisms they are working on. That way, he can have some input to what data is collected and how that data is analyzed.

Paper of note

In 2012, Karr was the lead author on a Cell paper that showed that high-throughput genomic data could be used to build comprehensive models of individual living organisms. In it, they presented their model of M. genitalium that included all the annotated functions of the bacterium's 525 genes and reported that it recapitulated what experimental data had shown.

Many modelers had been focusing on metabolism, Karr said, and this paper showed that other physiological processes could also be included, "and that once you put it all together, you can generate much more quantitative predictions that you can if you just focus on one physiological process at a time," he said.

The paper also, he said, laid out a new scheme for developing a dynamic model that didn't rely solely on flux balance analysis, but could also include other mathematical representations like differential equations.

"So now, we're coming back and trying to use that same framework, but apply it to a much larger system, and much more data," Karr said.

Looking ahead

In the next few years, Karr said that more people would likely adopt methods like theirs to model more bacteria, especially ones with industrial applications like Escherichia coli or cyanobacteria.

Then in the years after that he said that's when people would start to use models to engineer bacteria — as long as the cost of genome synthesis comes down.

Medical applications are even further off, he added, but researchers will start to apply these models to mammalian systems in the next five or so years. It will take a bit of time to develop them, though, due to the increased complexity of mammals.

"The process of actually integrating that into clinical use will take another several years to really thoroughly validate the models and prove it to clinicians and test it in hospitals at a small scale," he said.

And the Nobel goes to…

If Karr were to win a Nobel or other prize, he'd like it to be for having an effect on medicine. "I’d love it to be for some contribution to medicine, hopefully allowing doctors to think about patients in a more systematic and rational way, enabling them to make individualized predictions," he said.

This is the seventh in a series of Young Investigator Profiles for 2015 that will appear on GenomeWeb over the next few months.