Researchers at the University of Toronto have invented a new method that uses DNA sequencing to measure metabolites. This enables rapid and precise analysis of biological compounds, such as sugars, vitamins, hormones and the hundreds of other metabolites that are critical for health.
The new platform for small molecule sequencing, called "smol-seq", employs short strands of DNA called aptamers to detect metabolites. Each aptamer is engineered to bind to a target metabolite and to carry a unique DNA barcode.
"We need to measure metabolites because of the role they play in our health, but it is very challenging to study this wide range of molecules," said June Tan, first author on the study and research associate at U of T's Donnelly Centre for Cellular and Biomolecular Research . "Until now, mass spectrometry has been the gold standard for measuring metabolite levels, but it is not as accessible or as fast as methods that sequence DNA. We wanted to develop a method that detects metabolites using DNA sequencing to make use of that incredible sequencing power."
The study was published today in the journal Nature Biotechnology .
Once an aptamer binds to its target, its structure alters to release its DNA barcode. For example, the glucose-detecting aptamer releases one barcode and the aptamer recognizing the stress hormone cortisol releases a different barcode.
This means that one can tell which aptamers found their targets simply by sequencing the released barcodes. The more of a metabolite target there is in a sample, the more of that barcode is released, allowing researchers to measure the concentration of different molecules in a mixture.
"Scientists have previously used aptamers to measure metabolites, but mostly through methods that only allow you to measure a few metabolites at a time," said Tan. "We realized that if we use DNA barcodes as tags for metabolites, we can measure hundreds or even thousands of metabolites simultaneously."
Now that the smol-seq platform is up and running, the next step is to develop aptamers for metabolites with biomedical potential. Eventually, the expanding database of aptamers will enable machine learning for predicting aptamer designs to bind new metabolite targets.
In addition to growing the aptamer database, the research team will fine-tune the platform to increase the precision with which aptamers bind to their targets. This can be achieved by refining aptamer development at the nucleic acid level—a degree of specificity that will be necessary as the number of metabolites the platform can be used to study increases.
"DNA sequencing is millions of times faster than it was 20 years ago, and we wanted to harness that power for metabolite detection," said Andrew Fraser, principal investigator on the study and professor of molecular genetics at U of T's Temerty Faculty of Medicine. "Smol-seq could transform diagnostics and biotechnology by making metabolite detection as easy and rapid as DNA sequencing."
This research was supported by the Canadian Institutes of Health Research.
