Currently, confirming the type of bacteria present in a liquid sample requires culturing bacterial cultures in the laboratory over hours or days. But the new laser technology works in just minutes.
It was already known that when exposed to laser light, bacteria reflect light in spectral patterns unique to certain species.
The problem is that other microscopic items in the sample, such as blood cells and viruses, also reflect light and put on their own spin. This means that the bacterial spectral “fingerprint” is lost in the background noise and cannot be identified.
Led by an associate. A team of scientists from Stanford University, Professor Jennifer Dionne, has devised a solution to this problem.
Their technology incorporates a modified inkjet printer that utilizes acoustic pulses to print tiny dots of the liquid in question. Each dot printed on the slide has a volume of only 1/2 trillion of a liter. Since the dots are so small that they contain only a few dozen cells at most, the bacteria present have little competition to be seen.
Additionally, gold nanorods added to a small sample attach to the bacteria and act as antennas to pull in the laser light. As a result, the bacterium’s reflectance spectral fingerprint makes him 1,500 times stronger than it otherwise would have been. This makes it very easy for machine-learning-based software to find that fingerprint and match it to a specific type of bacteria.
And although the technique was primarily developed using infected mouse blood as the fluid, Dionne believes it will be equally effective for analyzing other fluids. It can even be adapted to target other types of cells, such as viruses.
“This is an innovative solution with potentially life-saving effects,” said senior co-author of the study, a former postdoctoral fellow in Dionne’s lab and now a professor at the University of Cairo. Amr Saleh said. “We are now excited about the commercialization opportunity that will help redefine the standards for bacterial detection and single cell characterization.”
A paper on this study was recently published in the journal nanoletter.
Source: Cornell University
