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Grad-Seq Guides the Discovery of Proq As a Major Small RNA-Binding Protein

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Grad-Seq Guides the Discovery of Proq As a Major Small RNA-Binding Protein Grad-seq guides the discovery of ProQ as a major small RNA-binding protein Alexandre Smirnova, Konrad U. Förstnera,b, Erik Holmqvista, Andreas Ottoc, Regina Günstera, Dörte Becherc, Richard Reinhardtd, and Jörg Vogela,e,1 aRNA Biology Group, Institute of Molecular Infection Biology, University of Würzburg, D-97080 Wurzburg, Germany; bCore Unit Systems Medicine, University of Würzburg, D-97080 Wurzburg, Germany; cInstitute for Microbiology, University of Greifswald, D-17489 Greifswald, Germany; dMax Planck Genome Centre Cologne, Max Planck Institute for Plant Breeding Research, D-50829 Cologne, Germany; and eResearch Centre for Infectious Diseases (ZINF), University of Würzburg, D-97070 Wurzburg, Germany Edited by Gisela Storz, NIH, Bethesda, MD, and approved July 29, 2016 (received for review June 20, 2016) The functional annotation of transcriptomes and identification of which, for example, has been used to define Argonaute-associated noncoding RNA (ncRNA) classes has been greatly facilitated by the miRNAs or piRNAs (8, 9). In bacteria, the largest class of post- advent of next-generation RNA sequencing which, by reading the transcriptional regulators is represented by the sRNAs that asso- nucleotide order of transcripts, theoretically allows the rapid pro- ciate with the Hfq protein (10, 11). This RNA chaperone both filing of all transcripts in a cell. However, primary sequence per se is a stabilizes bound sRNAs and helps them regulate their mRNA poor predictor of function, as ncRNAs dramatically vary in length and targets via imperfect base pairing (12–15). Together, Hfq and its structure and often lack identifiable motifs. Therefore, to visualize an associated sRNAs impact the expression >20% of all genes in en- informative RNA landscape of organisms with potentially new RNA teric model bacteria such as Escherichia coli and Salmonella enterica biology that are emerging from microbiome and environmental (16, 17). A second widespread class of bacterial sRNAs interact studies requires the use of more functionally relevant criteria. One with proteins of the CsrA/RsmA family via GGA motifs. In E. coli, such criterion is the association of RNAs with functionally important the CsrB/C and McaS sRNAs sequester the translational repressor cognate RNA-binding proteins. Here we analyze the full ensemble of CsrA,whichinturnregulateshundredsofmRNAs(18,19). cellular RNAs using gradient profiling by sequencing (Grad-seq) in Importantly, even the well-characterized model bacteria Salmonella enterica the bacterial pathogen , partitioning its coding E. coli and Salmonella contain many additional sRNAs that lack MICROBIOLOGY and noncoding transcripts based on their network of RNA–protein the motifs recognized by Hfq and CsrA (20–22), whereas other interactions. In addition to capturing established RNA classes based prokaryotes possess functional ncRNAs but no Hfq homolog on their biochemical profiles, the Grad-seq approach enabled the (7, 23, 24). This strongly suggests that additional global RBPs discovery of an overlooked large collective of structured small RNAs and associated classes of sRNAs with roles in posttranscriptional that form stable complexes with the conserved protein ProQ. We regulation exist, but have escaped identification by conventional show that ProQ is an abundant RNA-binding protein with a wide genetic and biochemical approaches. Here, we have combined a range of ligands and a global influence on Salmonella gene expres- classic biochemical technique with high-throughput analysis to sion. Given its generic ability to chart a functional RNA landscape reveal the complete functional RNA landscape of a bacterial irrespective of transcript length and sequence diversity, Grad-seq cell. Our global partitioning of cellular transcripts based on their promises to define functional RNA classes and major RNA-binding biochemical behavior has resulted in the discovery of a domain proteins in both model species and genetically intractable organisms. of posttranscriptional control by ProQ, a widespread RBP with a small RNA | noncoding RNA | RNA–protein interaction | ProQ | Hfq Significance he genomes of many studied organisms are pervasively tran- Understanding the functions of cellular transcripts based on their Tscribed, and a significant proportion of this RNA output is sequence is challenging, in particular for noncoding RNAs, which accounted for by noncoding RNA (ncRNA) (1, 2). This collective tend to lack easily recognizable motifs. A more functionally rel- term encompasses different types of transcripts such as ribosomal, evant criterion is the association of RNAs with cognate RNA- transfer, and other housekeeping RNAs [e.g., signal recognition binding proteins. Here, we describe the gradient profiling by particle (SRP) and RNase P RNA components, tmRNA, or sequencing (Grad-seq) approach to draft global RNA landscapes CRISPR RNAs], and also many regulatory RNA species. The latter through partitioning all cellular transcripts into diverse coding group is particularly vast and heterogeneous, and several new and noncoding groups based on their shared RNA–protein in- classes, such as siRNAs, micro RNAs (miRNAs), PIWI-interacting teractions. Grad-seq has enabled us to define a large class of RNAs (piRNAs), long noncoding RNAs, and various bacterial structured small RNAs that commonly associate with the con- regulatory small RNAs (sRNAs), have emerged as important served RNA-binding protein ProQ and appears to constitute a modulators of gene expression (3, 4). new branch of posttranscriptional control in bacteria. The generic The discovery of new RNA classes has been greatly facilitated by nature of the Grad-seq approach will help to rapidly describe next-generation sequencing, which, by reading transcript sequences, functional RNA landscapes in numerous understudied microbes. theoretically allows the rapid profiling of all RNA molecules in a Author contributions: A.S. and J.V. designed research; A.S., E.H., A.O., R.G., D.B., and R.R. cell (5, 6). However, the sequence per se has limited predictive performed research; A.O. and R.R. contributed new reagents/analytic tools; A.S., K.U.F., E.H., power when used to identify classes of functionally related ncRNAs, A.O., R.G., D.B., R.R., and J.V. analyzed data; and A.S. and J.V. wrote the paper. as these often lack easily identifiable motifs such as the translation The authors declare no conflict of interest. signals of protein-coding transcripts. This has been particularly ev- This article is a PNAS Direct Submission. ident for the bacterial sRNAs, which dramatically vary in length and Freely available online through the PNAS open access option. structure within and among bacteria (4, 7). Therefore, an in- Data deposition: The data reported in this paper have been deposited in the Gene Ex- formative description of the ncRNA landscape in any organism pression Omnibus (GEO) database, www.ncbi.nlm.nih.gov/geo (accession no. GSE62988). necessitates the use of more direct and functionally relevant criteria. 1To whom correspondence should be addressed. Email: [email protected]. One powerful diagnostic trait for ncRNA classes is their This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10. complex formation with particular RNA-binding proteins (RBPs), 1073/pnas.1609981113/-/DCSupplemental. www.pnas.org/cgi/doi/10.1073/pnas.1609981113 PNAS Early Edition | 1of6 Downloaded by guest on September 27, 2021 previously unknown large suite of cellular targets, which include 1C): both indicated the formation of a ∼16S complex, corresponding many highly structured regulatory sRNAs. to a previously reported particle of 500–600 kDa (27). Regulatory ncRNAs were more heterogeneously distributed. Results and Discussion For instance, Hfq-associated sRNAs (11) sedimented broadly in 0 Global Partitioning of Cellular RNAs by Grad-Seq. To describe the fractions 3–7 (average s 20,w ∼11S, or ∼350 kDa) with additional RNP landscape in the model enteric bacterium S. enterica serovar peaks in the 30S or 70S ribosome fractions (SI Appendix, Fig. Typhimurium (henceforth Salmonella), we applied a high- S1). Representatives of other functional RNA classes (attenua- throughput biochemical profiling approach (Grad-seq) (Fig. 1A). tors, antisense RNAs, Hfq-independent sRNAs) displayed even Grad-seq relies on the sedimentation of cellular RNAs and pro- more disparate distributions, suggesting that they are associated teins in a glycerol gradient, which sorts complexes by size and shape with several distinct RBPs. As expected, mRNAs abundantly and offers a means to assess their involvement in various macro- populate both the 30S and 70S ribosome fractions (SI Appendix, molecular assemblies (25, 26). Following this biochemical parti- Fig. S1). The mRNA reads in lower molecular weight fractions tioning step, we analyzed the RNA content of each of the 20 likely represent untranslated mRNAs in complex with regulatory gradient fractions by Illumina cDNA sequencing and visualized the proteins or stable decay intermediates. Of note, the profile of the sedimentation profiles of 3,969 individual Salmonella transcripts dual-function tmRNA, which rescues stalled ribosomes (28), (SI Appendix,Figs.S1andS2and Dataset S1). These profiles combined profile features of both coding and noncoding RNAs readily matched the expected distributions of housekeeping RNAs with pronounced peaks in both low molecular weight and 70S in glycerol gradients, including the 16S and 23S rRNAs, which fractions (Fig.
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