It's one of biology's great dreams: Seeing all the different kinds of proteins inside a cell as they go about their business and understanding exactly what it is they're doing that makes the machinery of life work.
Now that dream is a big step closer with the release of a massive study out of the University of Toronto that marks the first comprehensive map showing the abundance and location for some 3,000 different types of proteins that operate within a single yeast cell.
A key feature of the effort was the U of T team's use of specially designed robots to automatically prepare and image 20 million individual cells for computer analysis. The proteins were tagged with a fluorescent marker that makes it easier to locate them within different parts of a cell.
A machine learning approach helped the system teach itself to sort through the reams of images faster and more efficiently than an army of biologists staring into microscopes could have managed.
Yeast is frequently an organism of choice for scientists who study cell function because at a basic level it has much in common with more complex life forms, including humans.
While the work, published Thursday in the journal Cell, falls firmly in the domain of fundamental science, it suggests the tools now available for deciphering the complex inner world of the cell are evolving so rapidly that the results are likely to have a practical impact on medicine sooner rather than later.
"It's happening at a pace where these discoveries could end up playing a major role in your health treatment," said Charles Boone, a professor of molecular genetics at the University of Toronto's Donnelly Centre for Cellular and Biomolecular Research and one of the lead researchers on the study.
In the study, Dr. Boone and his colleagues charted how the numbers and locations of proteins changed as some of the genes within the yeast cells were modified or the cells were exposed to different drugs. The task would be akin to taking aerial photos of a city and watching crews of workers moving around to gather clues about what they're doing, then watching how their movements vary as the city is disrupted in different ways.
Since proteins are the functional units within cells, such disruptions can reveal how protein function is affected by genetic mutations or other factors that can cause disease.
"The work offers the exciting prospect of beginning to extend this type of approach to human cells," said Stanley Fields, a professor of genome sciences at the University of Washington in Seattle who was not involved in the study.
Dr. Fields called the effort a "tour de force" that demonstrated what could be accomplished by combining recent advances made possible by genome sequencing with an automated platform and a smart system for extracting patterns from complex data.
He added that such an approach might allow researchers in future to discern subtle consequences of various drugs – consequences that might otherwise go unnoticed.
Dr. Boone said a combination of federal and provincial grants allowed the U of T team to develop their automated system at scale that would have been hard to do in other countries, including the United States, because of differences in the funding systems.
He said the next step for the team is to look at combinations of mutations that could better reveal how proteins work together to achieve various cell functions.
A database with the newly published protein map has been made open access and is free for other researchers to use.