Recent methodological advances allowed the identification of an increasing number of RNA-binding proteins (RBPs) and their RNA-binding sites. Most of those methods rely, however, on capturing proteins associated to polyadenylated RNAs which neglects RBPs bound to non-adenylate RNA classes (tRNA, rRNA, pre-mRNA) as well as the vast majority of species that lack poly-A tails in their mRNAs (including all archea and bacteria). We have developed the Phenol Toluol extraction (PTex) protocol that does not rely on a specific RNA sequence or motif for isolation of cross-linked ribonucleoproteins (RNPs), but rather purifies them based entirely on their physicochemical properties. PTex captures RBPs that bind to RNA as short as 30 nt, RNPs directly from animal tissue and can be used to simplify complex workflows such as PAR-CLIP. Finally, we provide a global RNA-bound proteome of human HEK293 cells and the bacterium Salmonella Typhimurium.

RNA-binding proteins play key roles in controlling gene expression in many organisms, but relatively few have been identified and characterised in detail in Gram-positive bacteria. Here, we globally analyse RNA-binding proteins in methicillin-resistant Staphylococcus aureus (MRSA) using two complementary biochemical approaches. We identify hundreds of putative RNA-binding proteins, many containing unconventional RNA-binding domains such as Rossmann-fold domains. Remarkably, more than half of the proteins containing helix-turn-helix (HTH) domains, which are frequently found in prokaryotic transcription factors, bind RNA in vivo. In particular, the CcpA transcription factor, a master regulator of carbon metabolism, uses its HTH domain to bind hundreds of RNAs near intrinsic transcription terminators in vivo. We propose that CcpA, besides acting as a transcription factor, post-transcriptionally regulates the stability of many RNAs.

In recent years, hundreds of novel RNA-binding proteins (RBPs) have been identified, leading to the discovery of novel RNA-binding domains. Furthermore, unstructured or disordered low-complexity regions of RBPs have been identified to play an important role in interactions with nucleic acids. However, these advances in understanding RBPs are limited mainly to eukaryotic species and we only have limited tools to faithfully predict RNA-binders in bacteria. Here, we describe a support vector machine-based method, called TriPepSVM, for the prediction of RNA-binding proteins. TriPepSVM applies string kernels to directly handle protein sequences using tri-peptide frequencies. Testing the method in human and bacteria, we find that several RBP-enriched tri-peptides occur more often in structurally disordered regions of RBPs. TriPepSVM outperforms existing applications, which consider classical structural features of RNA-binding or homology, in the task of RBP prediction in both human and bacteria. Finally, we predict 66 novel RBPs in Salmonella Typhimurium and validate the bacterial proteins ClpX, DnaJ and UbiG to associate with RNA in vivo .

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