Salk researchers share a how-to secret for biologists: code for Amazon Cloud that significantly reduces the time necessary to process data-intensive microscopic images
The method promises to speed research into the underlying causes of disease by making single-molecule microscopy of practical use for more laboratories.
"This is an extremely cost-effective way for labs to process super-resolution images," says Hu Cang, Salk assistant professor in the Waitt Advanced Biophotonics Center and coauthor of the paper. "Depending on the size of the data set, it can save over a week's worth of time."
The latest frontier in basic biomedical research is to better understand the "molecular machines" called proteins and enzymes. Determining how they interact is key to discovering cures for diseases. Simply put, finding new therapies is akin to troubleshooting a broken mechanical assembly line-if you know all the steps in the manufacturing process, it's much easier to identify the step where something went wrong. In the case of human cells, some of the parts of the assembly line can be as small as single molecules.
According to the Abbe limit, it is impossible to see the difference between any two objects if they are smaller than half the wavelength of the imaging light. Since the shortest wavelength we can see is around 400 nanometers (nm), that means anything 200 nm or below appears as a blurry spot. The challenge for biologists is that the molecules they want to see are often only a few tens of nanometers in size.
"You have no idea how many single molecules are distributed within that blurry spot, so essential features and ideas remain obscure to you," says Jennifer Lippincott-Schwartz, a Salk non-resident fellow and coauthor on the paper.
In the early 2000s, several techniques were developed to break through the Abbe Limit, launching the new field of super-resolution microscopy. Among them was a method developed by Lippincott-Schwartz and her colleagues called Photoactivated Localization Microscopy, or PALM.
PALM, and its sister techniques, work because mathematics can see what the eye cannot: within the blurry spot, there are concentrations of photons that form bright peaks, which represent single molecules. The downside to these approaches is that it can take several hours to several days to crunch all the numbers required just to produce one usable image.