Functional Genomics Core, Mission: Impossible Experiments

Since 1600, the search for a needle in a haystack has symbolized a quixotic waste of time—looking for something very small in a too-large space.  Technology has come a long way since the 17th Century, and today, the University of Arizona Functional Genomics Core (FGC) invites researchers to bring on their needle-in-a-haystack problems.

“We have a robot that goes through the haystack!” explains Matthew Kaplan, Manager of the facility that is making the unfeasible feasible. 

Research in biology is increasingly about sifting through haystacks, according to FGC Faculty Director and Molecular and Cellular Biology Associate Professor Andrew Capaldi, “Over the last 20 years, we have moved away from looking at single genes and proteins to looking at networks.  You can’t attack modern problems in biology and medicine by studying one gene at a time. There is a need for high throughput screening.”

Want to run an infection cycle in different cells to see which genes are relevant?  Need to do that for over 1,000 genes?  That’s where the Functional Genomics Core comes in.  The facility’s instruments, sample libraries, and experimental design services help labs screen for drugs, assemble network wiring diagrams, look for pathways, and run a variety of other prohibitively labor-intensive experiments.

“Anything you’re doing that’s repetitive, we can program a robot to do it,” says Kaplan, who is an invaluable resource for the University of Arizona.  Kaplan sets up complex experiments using the Core’s sophisticated robots.  “I am not a programmer, and that’s my strength in this.  I have a background in doing molecular biology with my hands.”

A flick of the wrist, an efficient shimmy to remove a lid, Kaplan brings his human lab experience together with considerable programming expertise to save time and money for UA researchers.  He has “hacked” the FGC’s robots to add a variety of special touches that go beyond the original design of the machines, eliminating the potential for error and keeping experiments at the Core humming.

The power of high throughput? “We did 10,000 assays in six weeks, where one assay would have taken all day without the robots,” Capaldi grins. (That’s a savings of 1,994 weeks—just over 39 years.)

The idea for the FGC was born out of Capaldi’s research interests, “I wanted to do high throughput screens and network analysis, but we didn’t have anything available.”  After getting university buy-in for the need, “the Office of Research, Discovery & Innovation has invested a lot in this facility—we are really grateful,” Capaldi enthused.  “Anything repetitive, we can do it faster—and perfectly.”

The perfection of the results is a mathematical leap from hand-run experiments.

“We can measure the distribution of behavior in thousands of cell lines or controls,” Capaldi explains. “You don’t have to assume or guess it.”  The significance of results becomes much easier to observe and calculate—and easier to replicate.

The FGC staff, Kaplan along with Annalisa Medina, spend the bulk of their time preparing for the next experiment they are facilitating.  They tackle everything from programming equipment to advising researchers on the best experimental design.

“Nearly all of my time is spent on getting things to go,” Kaplan says, “and then I move on to the next puzzle.”

Over time, the FGC has become very efficient at starting up new experiments, making smaller projects more feasible.

“High throughput screening is our focus, but it’s also a curse.” Capaldi laments. “People think they need to do a really big project [to use the FGC].”

With the average pipeline for a project down to less than 2 days, it can be cheaper to let the robots handle even a medium-sized project instead of doing it by hand.

“People don’t take enough advantage of the robot and the premade protocols,” according to Kaplan. “For most things people want to do, it’s pretty simple.”

The FCG offers as much or as little support as labs need.

“We are happy to train people who aren’t familiar with the equipment,” Kaplan offers. “We are also happy to leave people alone who know what they are doing.”

When it comes to experimental design, there are often multiple options given the FGC’s capabilities, which include every possible way to measure a cell (the BioTek Synergy 2 plate reader, the Attune Acoustic Focusing Flow Cytometer, and the Operetta CLS system for analyzing images) and libraries—including the Ambion Complete Human Genome Silencer Select siRNA library, which knocks down each human gene three different ways.

“We can serve as consultants for a screen—helping people figure out the best method to get an experiment done,” Kaplan assures, encouraging labs to use the FGC’s knowledge. “Come to us early with your ideas to get better designed experiments.”

Often, the FGC assists labs with preliminary results for grant applications, and they urge researchers to come to the FGC early—Core staff can help with experimental design to ensure the quality of results and increase the odds of obtaining funding.

The Core works on a cost recovery basis, charging the lowest possible fees to keep instruments running, since service contracts are an ongoing cost.  With most of its potential customers located on the north side of campus, the FCG is moving in March from BioSciences West to the Keating Bioresearch Building.  Capaldi and Kaplan both emphasize that the facility is equipped to serve the entire UA research community.  With incubators located in the Core, samples can be prepared and stored on site.

Getting access to the facility is a simple matter of emailing a request to Kaplan (mkaplan@email.arizona.edu).  Interested to see what the FGC can do for you?  Visit the Core’s comprehensive website: http://fgc.arizona.edu/. 

With a range of successful experiments under their belts, Capaldi, Kaplan, and Medina challenge the UA community to bring on the next haystack.  They are ready to help find the needle.

Interested in how man and machine interact?  Watch the 2018 UA Science Lecture Series on Humans, Data, and Machines.

By: 
Zoja Bazarnic
Publish Date: 
Jan 30, 2018