Washington, Feb 3 (IANS) Researchers have now devised a code that crunches vast quantity of data in hours, instead of days and week, to produce images of single molecules in detail.
It is easy enough to identify glitches in a manufacturing process -- but where human cells are involved, with parts being as small as single molecules, it becomes a difficult task.
Now, Salk Institute researchers have got around this problem by devising a code for Amazon Cloud that crunches a vast quantity of data to produce images of single molecules in extraordinary detail.
Existing microscopy could not clearly show molecular structures such as proteins and enzymes. Even available alternatives, such as electron microscopy, could not be effectively used with living cells, the journal Nature Methods reports.
"This is an extremely cost-effective way for labs to process super-resolution images," said Hu Cang, assistant professor at the Salk's Waitt Advanced Biophotonics Centre and study co-author.
"Depending on the size of the data set, it can save over a week's worth of time."
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 nanometres (nm), that means anything 200 nm or below appears as a blurry spot.
The challenge is that the molecules are often only a few tens of nanometres in size, according to a Salk Institute statement.
"You have no idea how many single molecules are distributed within that blurry spot, so essential features and ideas remain obscure to you," said Jennifer Lippincott-Schwartz, Salk non-resident fellow and study co-author.
A method previously developed by Lippincott-Schwartz and colleagues, called Photoactivated Localization Microscopy, or PALM and its sister techniques, work because mathematics can see what the eye cannot.
Within the blurry spot, however, there are concentrations of photons that form bright peaks, representing single molecules.
Producing one usable image can take several hours to several days to crunch all the numbers required just to produce one usable image.
"It's like taking a movie, then you go through some very complex math, so what you see is the end result of processing, which is extremely slow because there's so many parameters," Cang said.
"When I first saw PALM, I was shocked by how good it was. I wanted to use it right away, but when I actually tried to use it, I found its usefulness was limited by computing speed."
The researchers offer other scientists the tools they need to use an easier alternative-the Amazon Elastic Compute Cloud (Amazon Elastic EC2), a service that provides access to super computing via the Internet, allowing massive computing tasks to be distributed over banks of computers.