SHAPE reveals transcript-wide interactions, complex structural domains, and protein interactions across the Xist lncRNA in living cells

Long noncoding RNAs (lncRNAs) are important regulators of gene expression, but their structural features are largely unknown. We used structure-selective chemical probing to examine the structure of the Xist lncRNA in living cells and found that the RNA adopts well-defined and complex structures throughout its entire 18-kb length. By looking for changes in reactivity induced by the cellular environment, we were able to identify numerous previously unknown hubs of protein interaction. We also found that the Xist structure governs specific protein interactions in multiple distinct ways. Our results provide a detailed structural context for Xist function and lay a foundation for understanding structure–function relationships in all lncRNAs

Selective 2′-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis

SHAPE chemistries exploit small electrophilic reagents that react with the 2′-hydroxyl group to interrogate RNA structure at single-nucleotide resolution. Mutational profiling (MaP) identifies modified residues based on the ability of reverse transcriptase to misread a SHAPE-modified nucleotide and then counting the resulting mutations by massively parallel sequencing. The SHAPE-MaP approach measures the structure of large and transcriptome-wide systems as accurately as for simple model RNAs. This protocol describes the experimental steps, implemented over three days, required to perform SHAPE probing and construct multiplexed SHAPE-MaP libraries suitable for deep sequencing. These steps include RNA folding and SHAPE structure probing, mutational profiling by reverse transcription, library construction, and sequencing. Automated processing of MaP sequencing data is accomplished using two software packages. ShapeMapper converts raw sequencing files into mutational profiles, creates SHAPE reactivity plots, and provides useful troubleshooting information, often within an hour. SuperFold uses these data to model RNA secondary structures, identify regions with well-defined structures, and visualize probable and alternative helices, often in under a day. We illustrate these algorithms with the E. coli thiamine pyrophosphate riboswitch, E. coli 16S rRNA, and HIV-1 genomic RNAs. SHAPE-MaP can be used to make nucleotide-resolution biophysical measurements of individual RNA motifs, rare components of complex RNA ensembles, and entire transcriptomes. The straightforward MaP strategy greatly expands the number, length, and complexity of analyzable RNA structures

Catalysts from synthetic genetic polymers

The emergence of catalysis in early genetic polymers like RNA is considered a key transition in the origin of life1, predating the appearance of protein enzymes. DNA also demonstrates the capacity to fold into three-dimensional structures and form catalysts in vitro2. However, to what degree these natural biopolymers comprise functionally privileged chemical scaffolds3 for folding or the evolution of catalysis is not known. The ability of synthetic genetic polymers (XNAs) with alternative backbone chemistries not found in nature to fold into defined structures and bind ligands4 raises the possibility that these too might be capable of forming catalysts (XNAzymes). Here we report the discovery of such XNAzymes, elaborated in four different chemistries (ANA (arabino nucleic acids)5, FANA (2′-fluoroarabino nucleic acids)6, HNA (hexitol nucleic acids) and CeNA (cyclohexene nucleic acids)7 directly from random XNA oligomer pools, exhibiting in trans RNA endonuclease and ligase activities. We also describe an XNA-XNA ligase metalloenzyme in the FANA framework, establishing catalysis in an entirely synthetic system and enabling the synthesis of FANA oligomers and an active RNA endonuclease FANAzyme from its constituent parts. These results extend catalysis beyond biopolymers and establish technologies for the discovery of catalysts in a wide range of polymer scaffolds not found in nature8. Evolution of catalysis independent of any natural polymer has implications for the definition of chemical boundary conditions for the emergence of life on earth and elsewhere in the universe9

German evidence and consensus‐based (S3) guideline: Vaccination recommendations for the prevention of HPV‐associated lesions

Anogenital and oropharyngeal infections with human papilloma viruses (HPV) are common. Clinically manifest disease may significantly impact quality of life; the treatment of HPV-associated lesions is associated with a high rate of recurrence and invasive neoplasms, such as cervical, anal, vulvar, penile, and oropharyngeal cancers, which are characterized by significant morbidity and mortality. Vaccination against HPV is an effective and safe measure for the primary prevention of HPV-associated lesions, but immunization rates are still low in Germany. The present publication is an abridged version of the German evidence and consensus-based guideline "Vaccination recommendations for the prevention of HPV-associated lesions", which is available on the website of the German Association of the Scientific Medical Societies (AWMF). On the basis of a systematic review with meta-analyses, a representative panel developed and agreed upon recommendations for the vaccination of different populations against HPV. In addition, consensus-based recommendations were developed for specific issues relevant to everyday practice. Based on current evidence and a representative expert consensus, these recommendations are intended to provide guidance in a field in which there is often uncertainty and in which both patients and health care providers are sometimes confronted with controversial and emotionally charged points of view

Detection of RNA–Protein Interactions in Living Cells with SHAPE

SHAPE-MaP is unique among RNA structure probing strategies in that it both measures flexibility at single-nucleotide resolution and quantifies the uncertainties in these measurements. We report a straightforward analytical framework that incorporates these uncertainties to allow detection of RNA structural differences between any two states, and we use it here to detect RNA–protein interactions in healthy mouse trophoblast stem cells. We validate this approach by analysis of three model cytoplasmic and nuclear ribonucleoprotein complexes, in 2 min in-cell probing experiments. In contrast, data produced by alternative in-cell SHAPE probing methods correlate poorly (<i>r</i> = 0.2) with those generated by SHAPE-MaP and do not yield accurate signals for RNA–protein interactions. We then examine RNA–protein and RNA–substrate interactions in the RNase MRP complex and, by comparing in-cell interaction sites with disease-associated mutations, characterize these noncoding mutations in terms of molecular phenotype. Together, these results reveal that SHAPE-MaP can define true interaction sites and infer RNA functions under native cellular conditions with limited preexisting knowledge of the proteins or RNAs involved