Dr. Burstein's lab


In our lab, we investigate key mechanisms of microbial interactions to better understand the microbial world around us and make discoveries that lead to the development of novel biotechnological tools and new clinical approaches. Our research combines cutting-edge metagenomic techniques, which allow exploring a vast diversity of microbes in their natural environment, along with tailored machine-learning and experimental approaches to predict, test, and characterize genes of interest. Our main interests include phage defense mechanisms, focusing on CRISPR-Cas, antimicrobial resistance, and bacterial secretion systems.

During my postdoctoral fellowship with Prof. Jennifer Doudna and Prof. Jill Banfield at the University of California Berkeley, I obtained extensive experience in metagenomics and CRISPR-Cas biochemistry, leading to the discovery of several new CRISPR-Cas systems encoded by uncultivated organisms, including system shown to be applicable as sensitive genetic diagnostics and genome editing tools (Burstein*, Harrington*, et al., Nature 2017; Harrington*, Burstein*, et al., Science 2018). In 2018 I established my lab in Tel Aviv University, in which my interdisciplinary research team combines computational and experimental biology to produce verifiable biological discoveries with biotechnological and medical significance.

Partner's Genome Editing vision​

Our genome editing vision is that in-depth studies of interactions within microbial communities can lead to a better understanding of the mechanisms of currently used genome-editing systems and the discovery of additional programable tools for genome editing and manipulation. We believe that in addition to rational design and directed evolution, the study of naturally occurring microbial systems, which evolved through millions of years, can play an important role in developing and improving genome editing tools. Our team strives to keep leveraging the opportunities provided by the sequencing revolution to explore metagenomic data and utilize it to decipher the mode-of-action of existing genome editing tools and expand the genome editing and manipulation toolbox.

Partner's activity within the consortium

In our research as part of the CRISPR-IL consortium, we analyze vast amounts of genomic and metagenomic data and investigate millions of CRISPR-Cas systems that evolved as a result of natural “experiments” performed by bacteria and archaea throughout their evolution. We use the information from natural occurring systems as an input to a machine-learning framework to identify properties and patterns that can predict the efficiency and accuracy of editing using different guide RNAs (gRNA). The results of our research will capitalize on the wide perspective over different microbes and environments to yield better predictions for gRNA on-target and off-target effects. Eventually, we aim to develop, together with the other teams in the consortium, a generic and modular machine-learning framework that will suit the needs of the academia and industry for editing diverse sets of targets and organisms, using different editing tools in a variety of conditions.