Identification of RNA Binding Partners of CRISPR-Cas Proteins in Prokaryotes Using RIP-Seq

CRISPR-Cas systems consist of a complex ribonucleoprotein (RNP) machinery encoded in prokaryotic genomes to confer adaptive immunity against foreign mobile genetic elements. Of these, especially the class 2, Type II CRISPR-Cas9 RNA-guided systems with single protein effector modules have recently received much attention for their application as programmable DNA scissors that can be used for genome editing in eukaryotes. While many studies have concentrated their efforts on improving RNA-mediated DNA targeting with these Type II systems, little is known about the factors that modulate processing or binding of the CRISPR RNA (crRNA) guides and the trans-activating tracrRNA to the nuclease protein Cas9, and whether Cas9 can also potentially interact with other endogenous RNAs encoded within the host genome. Here, we describe RIP-seq as a method to globally identify the direct RNA binding partners of CRISPR-Cas RNPs using the Cas9 nuclease as an example. RIP-seq combines co-immunoprecipitation (coIP) of an epitope-tagged Cas9 followed by isolation and deep sequencing analysis of its co-purified bound RNAs. This method can not only be used to study interactions of Cas9 with its known interaction partners, crRNAs and tracrRNA in native systems, but also to reveal potential additional RNA substrates of Cas9. For example, in RIP-seq analysis of Cas9 from the foodborne pathogen Campylobacter jejuni (CjeCas9), we recently identified several endogenous RNAs bound to CjeCas9 RNP in a crRNA-dependent manner, leading to the discovery of PAM-independent RNA cleavage activity of CjeCas9 as well as non-canonical crRNAs. RIP-seq can be easily adapted to any other effector RNP of choice from other CRISPR-Cas systems, allowing for the identification of target RNAs. Deciphering novel RNA-protein interactions for CRISPR-Cas proteins within host bacterial genomes will lead to a better understanding of the molecular mechanisms and functions of these systems and enable us to use the in vivo identified interaction rules as design principles for nucleic acid-targeting applications, fitted to each nuclease of interest.