Viruses can be examined on a larger scale and in much greater and more significant detail, thanks to a new computational method developed by the Broad Institute of MIT and Harvard.
Pardis Sabeti, researcher at the Broad Institute, has created a process by which viruses can be identified in a swifter and more effective manner, even if there are very few examples of the particles present.
This breakthrough will allow for faster research and development within the field, allowing scientific and medical bodies to work quicker in the face of an outbreak, as well as learning more about the viruses along the way. It will also facilitate swifter diagnosis of unknown illnesses, which are suspected to originate from viral causes.
The study, led by MIT graduate student Hayden Metsky and postdoctoral researcher Katie Siddle, appeared online via Nature Biotechnology. It was further highlighted and explained by Broad Institute of MIT and Harvard representative, Leah Eisenstadt, in an article for Phys.org.
Eisenstadt described the newly developed computational method, referred to as the CATCH method: Compact Aggregation of Targets for Comprehensive Hybridization.
CATCH is able to construct a form of bait to lure any human-effecting virus into view. This is particularly significant because, in cases such as the Zika virus, traces can be elusive and difficult to pinpoint, even in the blood particles of those who are suffering from the illness.
The approach can help small sequencing centers around the globe conduct disease surveillance more efficiently and cost-effectively, which can provide crucial information for controlling outbreaks.
“As genomic sequencing becomes a critical part of disease surveillance, tools like CATCH will help us and others detect outbreaks earlier and generate more data on pathogens that can be shared with the wider scientific and medical research communities,” – Christian Matranga, co-senior author of the new study.
The current process adds an element of specificity to the previous method, known as “metagenomic” sequencing, in which a patient’s DNA was examined for traces of a virus. The results of such procedures were often unpredictable, and rarely, ultimately satisfying in terms of conclusivity. The new process improves greatly upon these methods.
“We wanted to rethink how we were actually designing the probes to do capture. We realized that we could capture viruses, including their known diversity, with fewer probes than we’d used before. To make this an effective tool for surveillance, we then decided to try targeting about 20 viruses at a time, and we eventually scaled up to the 356 viral species known to infect humans.” – Hayden Metsky
Using the National Center for Biotechnology Information’s GenBank sequence database as a resource, the team used computer sequencing to enhance the visibility and accessibility of select virus particles, allowing for further, and more detailed analysis.
According to Eisenstadt’s report:
‘Using CATCH, Metsky and colleagues generated a subset of viral probes directed at Zika and chikungunya, another mosquito-borne virus found in the same geographic regions. Along with Zika genomes generated with other methods, the data they generated using CATCH-designed probes helped them discover that the Zika virus had been introduced in several regions months before scientists were able to detect it, a finding that can inform efforts to control future outbreaks.’
With the potential to identify viral diseases before a severe outbreak occurs, CATCH could allow for greater control and treatment, making it a significant step in the fight against unknown and developing viruses.
The CATCH software is publicly accessible on GitHub. Its development and validation, supervised by Sabeti and Matranga, is described online in Nature Biotechnology.