Wong Builds Catalog of Tools for Genetic Research

in BME Spotlight-Research, NEWS

By Liz Sheeley

Assistant Professor Wilson Wong (BME). Photo by Mike Pecci

When researchers want to study a specific gene’s function, a powerful strategy is to completely turn off the gene of interest, which makes it easy to understand if a gene is important, especially when you can control when and where to turn off the gene.

Developed in the 1980s, that type of experiment creates what is called a knockout model, which is frequently used throughout the scientific community today. But recombinases, the tools commonly used to produce a knockout model, haven’t evolved much since their inception.

Now, with a new publication in Nature Communications, Associate Professor Wilson Wong (BME) has accelerated the development of recombinase technology.

“Typically when researchers need to build a new recombinase for a specific study, they only build that one they need,” says Wong. “We decided to go further and construct the beginning of a library of inducible recombinases that are well classified and quantitatively tested.”

The key, new element in this work is that these recombinases are inducible—their functions can be turned on and off. A recombinase is an enzyme that can recognize a specific DNA sequence and then perform a specific function at that site such as cutting out a gene from the DNA.

“In cancer development, genes can get mutated in different orders, and there’s an indication that the order matters,” says Wong. “With our collection of recombinases, researchers could study how mutation order affects how the diseases progresses.”

Those types of studies could lead to a better understanding of why behavior between types of cancer can differ greatly, and potentially why one type of cancer has a wide array of responses to the same treatment in different patients.

Wong and his team built 20 versions of recombinases, and tested how well each functioned under inducible conditions. They were able to turn the recombinases on and off using a chemical, temperature or light signal. Some of the recombinases can be controlled with more than one of these signals.

That matters because if a researcher wanted to understand multiple functionalities, they would want to be able to turn on and off those functionalities with separate signals as to not confound the study.

They also built logic-based inducible recombinases, which will only turn on if multiple different conditions are met. This type of function helps researchers develop highly specific experiments. If, for example, they want to study only what happens when they turn off a gene in a certain type of tissue. By requiring the recombinase to turn on only when multiple and all signals are present, it reduces the risk of the system turning on somewhere it shouldn’t.

The team didn’t just produce a large collection of recombinases that are shown to work, but also classified how well they work under each type of inducer—chemical, temperature and light. Creating an open-source, quantitatively evaluated library like this for any experimental element is one of the goals of the Living Computing Project, a $10M, five-year National Science Foundation grant that Associate Proessors Douglas Densmore (ECE, BME), Ahmad ‘Mo’ Khalil (BME) and Wong are leading.

The multi-instructional project allows the scientists and engineers involved to collaborate with one another on projects such as this, which is why Dr. Jacob Beal was brought onto the team. Beal is a senior scientist at Raytheon BBN Technologies, who is also a principal investigator on the Living Computing Project. Wong says that Beal, a co-corresponding author on this study, was instrumental in developing the quantitative techniques they used in the paper to understand just how well each recombinase was working.

These new recombinases were sent to Addgene, a non-profit plasmid repository, where any lab can order from their catalog in an effort to increase collaboration and openness in science. This new recombinase collection will be very useful in mammalian genome engineering and gene expression control, and their applications will be in animal model development and cell-based therapy.