A team of scientists at the Whitehead Institute for Biomedical Research, MIT Broad Institute and Harvard University has evaluated the functions of more than 5,000 essential human genes using a new, pooled, imaging-based screening method. Their analysis uses CRISPR-Cas9 technology to eliminate gene activity and constitute the first resource of its kind to understand and visualize gene function in a broad range of cellular processes at spatial and temporal resolution. The team’s findings span more than 31 million individual cells and include quantitative data on hundreds of different parameters that enable predictions about how genes function and work together. The new study appears in November 7 online edition of the magazine cell.
“Throughout my career, I’ve wanted to see what happens in cells when the function of an essential gene is knocked out,” says MIT professor Ian Cheesman, senior author of the study and a member of the Whitehead Institute. “Now, we can do this, not just for a single gene but for every single gene important to a human cell dividing in a dish, and it’s incredibly powerful. The resource we’ve created will benefit not only our lab, but also labs around the world.”
Systemic inactivation of essential gene function is not a new concept, but traditional methods have been constrained by various factors, including cost, feasibility, and ability to completely eliminate the activity of essential genes. Cheesman, MIT’s Hermann and Margaret Sokol Professor of Biology, and colleagues collaborated with MIT Assistant Professor Paul Blayney and his team at the Broad Institute to define and achieve this ambitious joint goal. Broad Institute researchers have created a new genetic screening technology that combines two approaches – large-scale pooled genetic screens using CRISPR-Cas9 technology and cell imaging to detect quantitative and qualitative differences. Moreover, the method is inexpensive compared to other methods and is practiced using commercially available equipment.
“We are proud to demonstrate the amazing resolution of accessible cellular processes with low-cost imaging assays in partnership with Iain’s lab at the Whitehead Institute,” says Blainey, a senior author of the study and associate professor in the Department of Biology. Engineering at MIT, a member of the Koch Institute for Integrative Cancer Research at MIT, and a core institute member at the Broad Institute. “And this is clearly just the tip of the iceberg of our approach. The ability to correlate genetic disorders based on more detailed phenotypic readouts is essential, and now accessible, for many areas of future research.”
Cheesman adds, “Being able to do biological screening of aggregated cells is fundamentally a game changer. You have two cells sitting right next to each other, so your ability to make statistically significant calculations about whether they are the same or not is much higher, and you can discern small differences.” very “.
Cheeseman, Blainey, and lead authors Luke Funk, Kuan-Chung Su, and colleagues evaluated the functions of 5072 essential genes in a human cell line. They analyzed four markers across cells in their screen – DNA; DNA damage response, a key cellular pathway that detects and responds to damaged DNA; and two important structural proteins, actin and tubulin. In addition to the initial screen, the scientists also conducted a smaller follow-up screen that focused on about 200 genes involved in cell division (also called “mitosis”). Genes in the initial screen were identified as clearly playing a role in mitosis but not previously linked to the process. This data is provided via Companion websiteproviding a resource for other scientists to investigate the functions of genes of interest.
There’s a tremendous amount of information we’ve collected about these cells. For example, for the nucleus of cells, it’s not just how bright it is, but how big it is, how round it is, and are the edges smooth or jagged? Cheeseman says. “A computer can really extract a wealth of spatial information.”
Based on this rich multidimensional data, the scientists’ work provides a kind of cell biological “fingerprint” for each gene analyzed in the screen. Using complex computational clustering strategies, researchers can compare fingerprints with each other and build potential regulatory relationships between genes. Because the team’s data confirm multiple relationships already known, they can be used with confidence to make predictions about genes whose functions and/or interactions with other genes are unknown.
Several notable discoveries emerge from the researchers’ examining data, including a surprising finding related to ion channels. Jinan AQP7 And the ATP1A1, for their roles in mitosis, specifically the proper segregation of chromosomes. These genes encode membrane-bound proteins that transport ions into and out of the cell. “In all the years I’ve been working on mitosis, I never imagined that ion channels were involved,” Cheeseman says.
He adds: “We are really just scratching the surface of what can be discovered from our data. We hope that not only others – but also others – will benefit from this resource.”
This work was supported by grants from the US National Institutes of Health as well as support from the Gordon and Betty Moore Foundation, a National Defense Science and Engineering Graduate Fellowship, and a Natural Sciences and Engineering Research Council Fellowship.