Two Princeton University computer science professors will lead a new Google AI lab opening in January in the town of Princeton. The lab is expected to expand New Jersey's burgeoning innovation ecosystem by building a collaborative effort to advance research in artificial intelligence.
Bacteria have multiple strategies to survive antibiotics: developing genetic resistance to the drugs; delaying their growth; or hiding in protective biofilms. New results from researchers at Princeton and California State University-Northridge (CSUN) have shed light on yet another approach: self-sacrifice.
In a population of E. coli bacteria treated with a particular antimicrobial molecule, the researchers found, some dying cells absorbed large amounts of the antibiotic, allowing their neighbors to survive and continue growing. The researchers created a modified, green fluorescent version of the antibiotic of interest, a peptide molecule known as LL37 that is naturally produced by human skin, airways and other organs that frequently contact bacteria from the outside world. Tracking the glowing molecule’s movements through a population of bacteria, as shown in the figure above, revealed that the antibiotic was accumulating in a subset of dying cells.
Andrej Ko≈°mrlj, an assistant professor of mechanical and aerospace engineering at Princeton, collaborated with the CSUN team to develop a mathematical model to more fully explain the phenomenon and aid further investigations.
The model describes the dynamics of bacterial populations facing different concentrations of the antimicrobial, showing how dead cells sequester the dangerous molecule and predicting the delayed growth of surviving cells – calculations borne out by experiments in the laboratory of Sattar Taheri-Araghi, an assistant professor of physics at CSUN and co-senior author of the study along with Ko≈°mrlj.
“The model provided a physical explanation for how this actually works,” said Ko≈°mrlj. “We had a surprising observation that the critical inhibitory concentration of antimicrobial peptides depends on the number of bacteria, and our model was able to explain why this happens.”
Despite this new understanding, questions remain about what is happening at the molecular level, said Taheri-Araghi in a news release. “This research opens the doors to a lot of questions that were never asked before. Our findings have profound implications for the evolution of bacteria – which have been around for billions of years – as well as in medicine for the design and administration of novel antibiotics.”
The researchers reported their results in a paper published Dec. 18, 2018, in eLife. In addition to Taheri-Araghi, the CSUN team included former undergraduate students Mehdi Snoussi and Nathan-Alexander Del Rosario, physics graduate student John Paul Talledo and research associate Salimeh Mohammadi. Bae-Yeun Ha, a physics professor at the University of Waterloo in Canada, was also a co-author. The work was supported in part by the U.S. National Institutes of Health and National Science Foundation, including an NSF-sponsored Partnership for Research and Education in Materials between CSUN and the Princeton Center for Complex Materials.