A Quantitative and Predictive Model for RNA Binding by Human Pumilio Proteins

RNA ensembles from in vitro to in vivo: Toward predictive models of RNA cellular function

Deepening our understanding of RNA biology and accelerating development of RNA-based therapeutics go hand-in-hand-both requiring a transition from qualitative descriptions of RNA structure to quantitative models capable of predicting RNA behaviors, and from a static to an ensemble view. Ensembles are determined from their free energy landscapes, which define the relative populations of conformational states and the energetic barriers separating them. Experimental determination of RNA ensembles over the past decade has led to powerful predictive models of RNA behavior in vitro. It has also been shown during this time that the cellular environment redistributes RNA ensembles, changing the abundances of functionally relevant conformers relative to in vitro contexts with subsequent functional RNA consequences. However, recent studies have demonstrated that testing models built from in vitro ensembles with highly quantitative measurements of RNA cellular function, aided by emerging computational methodologies, enables predictive modelling of cellular activity and biological discovery.

Systematic analysis of the target recognition and repression by the Pumilio proteins

RNA binding proteins orchestrate the post-transcriptional fate of RNA molecules, but the principles of their action remain poorly understood. Pumilio (PUM) proteins bind 3' UTRs of mRNAs and lead to mRNA decay. To comprehensively map the determinants of recognition of sequences by PUM proteins in cells and to study the binding outcomes, we developed a massively parallel RNA assay that profiled thousands of PUM-binding sites in cells undergoing various perturbations or RNA immunoprecipitation. By studying fragments from the NORAD long non-coding RNA, we find two features that antagonize repression by PUM proteins - G/C rich sequences, particularly those upstream of the PUM recognition element, and binding of FAM120A, which limits the repression elicited by PUM-binding sites. We also find that arrays of PUM sites separated by 8-12 bases offer particularly strong repression and use them to develop a particularly sensitive reporter for PUM repression. In contrast, PUM sites separated by shorter linkers, such as some of those found in NORAD, exhibit strong activity interdependence, likely mediated by competition between PUM binding and formation of strong secondary structures. Overall, our findings expand our understanding of the determinants of PUM protein activity in human cells.

Biochemical principles of miRNA targeting in flies

MicroRNAs-direct Argonaute proteins to repress complementary target mRNAs via mRNA degradation or translational inhibition. While mammalian miRNA targeting has been well studied, the principles by which Drosophila miRNAs bind their target RNAs remain to be fully characterized. Here, we use RNA Bind-n-Seq to systematically identify binding sites and measure their affinities for four highly expressed Drosophila miRNAs. Our results reveal a narrower range of binding site diversity in flies compared to mammals, with fly miRNAs favoring canonical seed-matched sites and exhibiting limited tolerance for imperfections within these sites. We also identified non-canonical site types, including nucleation-bulged and 3'-only sites, whose binding affinities are comparable to canonical sites. These findings establish a foundation for future computational models of Drosophila miRNA targeting, enabling predictions of regulatory outcomes in response to cellular signals, and advancing our understanding of miRNA-mediated regulation in flies.

Identification of leader-trailer helices of precursor ribosomal RNA in all phyla of bacteria and archaea

Ribosomal RNAs are transcribed as part of larger precursor molecules. In Escherichia coli, complementary RNA segments flank each rRNA and form long leader-trailer (LT) helices, which are crucial for subunit biogenesis in the cell. A previous study of 15 representative species suggested that most but not all prokaryotes contain LT helices. Here, we use a combination of in silico folding and covariation methods to identify and characterize LT helices in 4464 bacterial and 260 archaeal organisms. Our results suggest that LT helices are present in all phyla, including Deinococcota, which had previously been suspected to lack LT helices. In very few organisms, our pipeline failed to detect LT helices for both 16S and 23S rRNA. However, a closer case-by-case look revealed that LT helices are indeed present but escaped initial detection. Over 3600 secondary structure models, many well supported by nucleotide covariation, were generated. These structures show a high degree of diversity. Yet, all exhibit extensive base-pairing between the leader and trailer strands, in line with a common and essential function.

FRET-guided modeling of nucleic acids

The functional diversity of RNAs is encoded in their innate conformational heterogeneity. The combination of single-molecule spectroscopy and computational modeling offers new attractive opportunities to map structural transitions within nucleic acid ensembles. Here, we describe a framework to harmonize single-molecule Förster resonance energy transfer (FRET) measurements with molecular dynamics simulations and de novo structure prediction. Using either all-atom or implicit fluorophore modeling, we recreate FRET experiments in silico, visualize the underlying structural dynamics and quantify the reaction coordinates. Using multiple accessible-contact volumes as a post hoc scoring method for fragment assembly in Rosetta, we demonstrate that FRET can be used to filter a de novo RNA structure prediction ensemble by refuting models that are not compatible with in vitro FRET measurement. We benchmark our FRET-assisted modeling approach on double-labeled DNA strands and validate it against an intrinsically dynamic manganese(II)-binding riboswitch. We show that a FRET coordinate describing the assembly of a four-way junction allows our pipeline to recapitulate the global fold of the riboswitch displayed by the crystal structure. We conclude that computational fluorescence spectroscopy facilitates the interpretability of dynamic structural ensembles and improves the mechanistic understanding of nucleic acid interactions.

Pumilio-1 mediated translational control of claudin-5 at the blood-brain barrier

Claudin-5 is one of the most essential tight junction proteins at the blood-brain barrier. A single nucleotide polymorphism rs10314 is located in the 3'-untranslated region of claudin-5 and has been shown to be a risk factor for schizophrenia. Here, we show that the pumilio RNA-binding protein, pumilio-1, is responsible for rs10314-mediated claudin-5 regulation. The RNA sequence surrounding rs10314 is highly homologous to the canonical pumilio-binding sequence and claudin-5 mRNA with rs10314 produces 25% less protein due to its inability to bind to pumilio-1. Pumilio-1 formed cytosolic granules under stress conditions and claudin-5 mRNA appeared to preferentially accumulate in these granules. Added to this, we observed granular pumilio-1 in endothelial cells in human brain tissues from patients with psychiatric disorders or epilepsy with increased/accumulated claudin-5 mRNA levels, suggesting translational claudin-5 suppression may occur in a brain-region specific manner. These findings identify a key regulator of claudin-5 translational processing and how its dysregulation may be associated with neurological and neuropsychiatric disorders.

Massively parallel dissection of RNA in RNA-protein interactions in vivo

Many of the biological functions performed by RNA are mediated by RNA-binding proteins (RBPs), and understanding the molecular basis of these interactions is fundamental to biology. Here, we present massively parallel RNA assay combined with immunoprecipitation (MPRNA-IP) for in vivo high-throughput dissection of RNA-protein interactions and describe statistical models for identifying RNA domains and parsing the structural contributions of RNA. By using custom pools of tens of thousands of RNA sequences containing systematically designed truncations and mutations, MPRNA-IP is able to identify RNA domains, sequences, and secondary structures necessary and sufficient for protein binding in a single experiment. We show that this approach is successful for multiple RNAs of interest, including the long noncoding RNA NORAD, bacteriophage MS2 RNA, and human telomerase RNA, and we use it to interrogate the hitherto unknown sequence or structural RNA-binding preferences of the DNA-looping factor CTCF. By integrating systematic mutation analysis with crosslinking immunoprecipitation, MPRNA-IP provides a novel high-throughput way to elucidate RNA-based mechanisms behind RNA-protein interactions in vivo.

PUF partner interactions at a conserved interface shape the RNA-binding landscape and cell fate in Caenorhabditis elegans

Protein-RNA regulatory networks underpin much of biology. C. elegans FBF-2, a PUF-RNA-binding protein, binds over 1,000 RNAs to govern stem cells and differentiation. FBF-2 interacts with multiple protein partners via a key tyrosine, Y479. Here, we investigate the in vivo significance of partnerships using a Y479A mutant. Occupancy of the Y479A mutant protein increases or decreases at specific sites across the transcriptome, varying with RNAs. Germline development also changes in a specific fashion: Y479A abolishes one FBF-2 function-the sperm-to-oocyte cell fate switch. Y479A's effects on the regulation of one mRNA, gld-1, are critical to this fate change, though other network changes are also important. FBF-2 switches from repression to activation of gld-1 RNA, likely by distinct FBF-2 partnerships. The role of RNA-binding protein partnerships in governing RNA regulatory networks will likely extend broadly, as such partnerships pervade RNA controls in virtually all metazoan tissues and species.

RNA structure profiling at single-cell resolution reveals new determinants of cell identity

RNA structure is critical for multiple steps in gene regulation. However, how the structures of transcripts differ both within and between individual cells is unknown. Here we develop a SHAPE-inspired method called single-cell structure probing of RNA transcripts that enables simultaneous determination of transcript secondary structure and abundance at single-cell resolution. We apply single-cell structure probing of RNA transcripts to human embryonic stem cells and differentiating neurons. Remarkably, RNA structure is more homogeneous in human embryonic stem cells compared with neurons, with the greatest homogeneity found in coding regions. More extensive heterogeneity is found within 3' untranslated regions and is determined by specific RNA-binding proteins. Overall RNA structure profiles better discriminate cell type identity and differentiation stage than gene expression profiles alone. We further discover a cell-type variable region of 18S ribosomal RNA that is associated with cell cycle and translation control. Our method opens the door to the systematic characterization of RNA structure-function relationships at single-cell resolution.

Specificity, synergy, and mechanisms of splice-modifying drugs

Drugs that target pre-mRNA splicing hold great therapeutic potential, but the quantitative understanding of how these drugs work is limited. Here we introduce mechanistically interpretable quantitative models for the sequence-specific and concentration-dependent behavior of splice-modifying drugs. Using massively parallel splicing assays, RNA-seq experiments, and precision dose-response curves, we obtain quantitative models for two small-molecule drugs, risdiplam and branaplam, developed for treating spinal muscular atrophy. The results quantitatively characterize the specificities of risdiplam and branaplam for 5' splice site sequences, suggest that branaplam recognizes 5' splice sites via two distinct interaction modes, and contradict the prevailing two-site hypothesis for risdiplam activity at SMN2 exon 7. The results also show that anomalous single-drug cooperativity, as well as multi-drug synergy, are widespread among small-molecule drugs and antisense-oligonucleotide drugs that promote exon inclusion. Our quantitative models thus clarify the mechanisms of existing treatments and provide a basis for the rational development of new therapies.

Systematic analysis of cotranscriptional RNA folding using transcription elongation complex display

RNA can fold into structures that mediate diverse cellular functions. Understanding how RNA primary sequence directs the formation of functional structures requires methods that can comprehensively assess how changes in an RNA sequence affect its structure and function. Here we have developed a platform for performing high-throughput cotranscriptional RNA biochemical assays, called Transcription Elongation Complex display (TECdisplay). TECdisplay measures RNA function by fractionating a TEC library based on the activity of cotranscriptionally displayed nascent RNA. In this way, RNA function is measured as the distribution of template DNA molecules between fractions of the transcription reaction. This approach circumvents typical RNA sequencing library preparation steps that can cause technical bias. We used TECdisplay to characterize the transcription antitermination activity of 32,768 variants of the Clostridium beijerinckii pfl ZTP riboswitch designed to perturb steps within its cotranscriptional folding pathway. Our findings establish TECdisplay as an accessible platform for high-throughput RNA biochemical assays.

RNA molecular recording with an engineered RNA deaminase

RNA deaminases are powerful tools for base editing and RNA molecular recording. However, the enzymes used in currently available RNA molecular recorders such as TRIBE, DART or STAMP have limitations due to RNA structure and sequence dependence. We designed a platform for directed evolution of RNA molecular recorders. We engineered an RNA A-to-I deaminase (an RNA adenosine base editor, rABE) that has high activity, low bias and low background. Using rABE, we present REMORA (RNA-encoded molecular recording in adenosines), wherein deamination by rABE writes a molecular record of RNA-protein interactions. By combining rABE with the C-to-U deaminase APOBEC1 and long-read RNA sequencing, we measured binding by two RNA-binding proteins on single messenger RNAs. Orthogonal RNA molecular recording of mammalian Pumilio proteins PUM1 and PUM2 shows that PUM1 competes with PUM2 for a subset of sites in cells. Furthermore, we identify transcript isoform-specific RNA-protein interactions driven by isoform changes distal to the binding site. The genetically encodable RNA deaminase rABE enables single-molecule identification of RNA-protein interactions with cell type specificity.

Significant roles in RNA-binding for the amino-terminal domains of Drosophila Pumilio and Nanos

The Drosophila Pumilio (Pum) and Nanos (Nos) RNA-binding proteins govern abdominal segmentation in the early embryo, as well as a variety of other events during development. They bind together to a compound Nanos Response Element (NRE) present in thousands of maternal mRNAs in the ovary and embryo, including hunchback ( hb ) mRNA, thereby regulating poly-adenylation, translation, and stability. Many studies support a model in which mRNA recognition and effector recruitment are achieved by distinct regions of each protein. The well-ordered Pum and Nos RNA-binding domains (RBDs) are sufficient to specifically recognize NREs; the relatively larger low-complexity N-terminal domains (NTDs) of each protein have been thought to act by recruiting mRNA regulators. Here we use yeast interaction assays to show that the NTDs also play a significant role in recognition of the NRE, acting via two mechanisms. First, the Pum and Nos NTDs interact in trans to promote assembly of the Pum/Nos/NRE ternary complex. Second, the Pum NTD acts via an unknown mechanism in cis, modifying base recognition by its RBD. These activities of the Pum NTD are important for its regulation of maternal hb mRNA in vivo.

Skipper analysis of eCLIP datasets enables sensitive detection of constrained translation factor binding sites

Technology for crosslinking and immunoprecipitation (CLIP) followed by sequencing (CLIP-seq) has identified the transcriptomic targets of hundreds of RNA-binding proteins in cells. To increase the power of existing and future CLIP-seq datasets, we introduce Skipper, an end-to-end workflow that converts unprocessed reads into annotated binding sites using an improved statistical framework. Compared with existing methods, Skipper on average calls 210%-320% more transcriptomic binding sites and sometimes >1,000% more sites, providing deeper insight into post-transcriptional gene regulation. Skipper also calls binding to annotated repetitive elements and identifies bound elements for 99% of enhanced CLIP experiments. We perform nine translation factor enhanced CLIPs and apply Skipper to learn determinants of translation factor occupancy, including transcript region, sequence, and subcellular localization. Furthermore, we observe depletion of genetic variation in occupied sites and nominate transcripts subject to selective constraint because of translation factor occupancy. Skipper offers fast, easy, customizable, and state-of-the-art analysis of CLIP-seq data.

Roles of the leader-trailer helix and antitermination complex in biogenesis of the 30S ribosomal subunit

Ribosome biogenesis occurs co-transcriptionally and entails rRNA folding, ribosomal protein binding, rRNA processing, and rRNA modification. In most bacteria, the 16S, 23S and 5S rRNAs are co-transcribed, often with one or more tRNAs. Transcription involves a modified RNA polymerase, called the antitermination complex, which forms in response to cis-acting elements (boxB, boxA and boxC) in the nascent pre-rRNA. Sequences flanking the rRNAs are complementary and form long helices known as leader-trailer helices. Here, we employed an orthogonal translation system to interrogate the functional roles of these RNA elements in 30S subunit biogenesis in Escherichia coli. Mutations that disrupt the leader-trailer helix caused complete loss of translation activity, indicating that this helix is absolutely essential for active subunit formation in the cell. Mutations of boxA also reduced translation activity, but by only 2- to 3-fold, suggesting a smaller role for the antitermination complex. Similarly modest drops in activity were seen upon deletion of either or both of two leader helices, termed here hA and hB. Interestingly, subunits formed in the absence of these leader features exhibited defects in translational fidelity. These data suggest that the antitermination complex and precursor RNA elements help to ensure quality control during ribosome biogenesis.

Massively Parallel Profiling of RNA-targeting CRISPR-Cas13d

Type VI CRISPR enzymes cleave target RNAs and are widely used for gene regulation, RNA tracking, and diagnostics. However, a systematic understanding of their RNA binding specificity and cleavage activation is lacking. Here, we describe RNA chip-hybridized association-mapping platform (RNA-CHAMP), a massively parallel platform that repurposes next-generation DNA sequencing chips to measure the binding affinity for over 10,000 RNA targets containing structural perturbations, mismatches, insertions, and deletions relative to the CRISPR RNA (crRNA). Deep profiling of Cas13d, a compact and widely used RNA nuclease, reveals that it does not require a protospacer flanking sequence (PFS) but is exquisitely sensitive to secondary structure within the target RNA. Cas13d binding is strongly penalized by mismatches, insertions, and deletions in the distal crRNA-target RNA regions, while alterations in the proximal region inhibit nuclease activity without affecting binding. A biophysical model built from these data reveals that target recognition begins at the distal end of unstructured target RNAs and proceeds to the proximal end. Using this model, we designed a series of partially mismatched guide RNAs that modulate nuclease activity to detect single nucleotide polymorphisms (SNPs) in circulating SARS-CoV-2 variants. This work describes the key determinants of RNA targeting by a type VI CRISPR enzyme to improve CRISPR diagnostics and in vivo RNA editing. More broadly, RNA-CHAMP provides a quantitative platform for systematically measuring protein-RNA interactions.

Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements

Structured RNAs and RNA/protein complexes perform critical cellular functions. They often contain structurally conserved tertiary contact "motifs," whose occurrence simplifies the RNA folding landscape. Prior studies have focused on the conformational and energetic modularity of intact motifs. Here, we turn to the dissection of one common motif, the 11nt receptor (11ntR), using quantitative analysis of RNA on a massively parallel array to measure the binding of all single and double 11ntR mutants to GAAA and GUAA tetraloops, thereby probing the energetic architecture of the motif. While the 11ntR behaves as a motif, its cooperativity is not absolute. Instead, we uncovered a gradient from high cooperativity amongst base-paired and neighboring residues to additivity between distant residues. As expected, substitutions at residues in direct contact with the GAAA tetraloop resulted in the largest decreases to binding, and energetic penalties of mutations were substantially smaller for binding to the alternate GUAA tetraloop, which lacks tertiary contacts present with the canonical GAAA tetraloop. However, we found that the energetic consequences of base partner substitutions are not, in general, simply described by base pair type or isostericity. We also found exceptions to the previously established stability-abundance relationship for 11ntR sequence variants. These findings of "exceptions to the rule" highlight the power of systematic high-throughput approaches to uncover novel variants for future study in addition to providing an energetic map of a functional RNA.

High-throughput biochemistry in RNA sequence space: predicting structure and function

RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.

Programmable RNA base editing with a single gRNA-free enzyme

Programmable RNA editing enables rewriting gene expression without changing genome sequences. Current tools for specific RNA editing dependent on the assembly of guide RNA into an RNA/protein complex, causing delivery barrier and low editing efficiency. We report a new gRNA-free system, RNA editing with individual RNA-binding enzyme (REWIRE), to perform precise base editing with a single engineered protein. This artificial enzyme contains a human-originated programmable PUF domain to specifically recognize RNAs and different deaminase domains to achieve efficient A-to-I or C-to-U editing, which achieved 60-80% editing rate in human cells, with a few non-specific editing sites in the targeted region and a low level off-target effect globally. The RNA-binding domain in REWIREs was further optimized to improve editing efficiency and minimize off-target effects. We applied the REWIREs to correct disease-associated mutations and achieve both types of base editing in mice. As a single-component system originated from human proteins, REWIRE presents a precise and efficient RNA editing platform with broad applicability.

A comprehensive thermodynamic model for RNA binding by the Saccharomyces cerevisiae Pumilio protein PUF4

Genomic methods have been valuable for identifying RNA-binding proteins (RBPs) and the genes, pathways, and processes they regulate. Nevertheless, standard motif descriptions cannot be used to predict all RNA targets or test quantitative models for cellular interactions and regulation. We present a complete thermodynamic model for RNA binding to the S. cerevisiae Pumilio protein PUF4 derived from direct binding data for 6180 RNAs measured using the RNA on a massively parallel array (RNA-MaP) platform. The PUF4 model is highly similar to that of the related RBPs, human PUM2 and PUM1, with one marked exception: a single favorable site of base flipping for PUF4, such that PUF4 preferentially binds to a non-contiguous series of residues. These results are foundational for developing and testing cellular models of RNA-RBP interactions and function, for engineering RBPs, for understanding the biophysical nature of RBP binding and the evolutionary landscape of RNAs and RBPs.

Exploring molecular biology in sequence space: The road to next-generation single-molecule biophysics

Next-generation sequencing techniques have led to a new quantitative dimension in the biological sciences. In particular, integrating sequencing techniques with biophysical tools allows sequence-dependent mechanistic studies. Using the millions of DNA clusters that are generated during sequencing to perform high-throughput binding affinity and kinetics measurements enabled the construction of energy landscapes in sequence space, uncovering relationships between sequence, structure, and function. Here, we review the approaches to perform ensemble fluorescence experiments on next-generation sequencing chips for variations of DNA, RNA, and protein sequences. As the next step, we anticipate that these fluorescence experiments will be pushed to the single-molecule level, which can directly uncover kinetics and molecular heterogeneity in an unprecedented high-throughput fashion. Molecular biophysics in sequence space, both at the ensemble and single-molecule level, leads to new mechanistic insights. The wide spectrum of applications in biology and medicine ranges from the fundamental understanding of evolutionary pathways to the development of new therapeutics.

Genome-wide RNA structure changes during human neurogenesis modulate gene regulatory networks

The distribution, dynamics, and function of RNA structures in human development are under-explored. Here, we systematically assayed RNA structural dynamics and their relationship with gene expression, translation, and decay during human neurogenesis. We observed that the human ESC transcriptome is globally more structurally accessible than differentiated cells and undergoes extensive RNA structure changes, particularly in the 3' UTR. Additionally, RNA structure changes during differentiation are associated with translation and decay. We observed that RBP and miRNA binding is associated with RNA structural changes during early neuronal differentiation, and splicing is associated during later neuronal differentiation. Furthermore, our analysis suggests that RBPs are major factors in structure remodeling and co-regulate additional RBPs and miRNAs through structure. We demonstrated an example of this by showing that PUM2-induced structure changes on LIN28A enable miR-30 binding. This study deepens our understanding of the widespread and complex role of RNA-based gene regulation during human development.

Spatial correlation statistics enable transcriptome-wide characterization of RNA structure binding

Molecular interactions at identical transcriptomic locations or at proximal but non-overlapping sites can mediate RNA modification and regulation, necessitating tools to uncover these spatial relationships. We present nearBynding, a flexible algorithm and software pipeline that models spatial correlation between transcriptome-wide tracks from diverse data types. nearBynding can process and correlate interval as well as continuous data and incorporate experimentally derived or in silico predicted transcriptomic tracks. nearBynding offers visualization functions for its statistics to identify colocalizations and adjacent features. We demonstrate the application of nearBynding to correlate RNA-binding protein (RBP) binding preferences with other RBPs, RNA structure, or RNA modification. By cross-correlating RBP binding and RNA structure data, we demonstrate that nearBynding recapitulates known RBP binding to structural motifs and provides biological insights into RBP binding preference of G-quadruplexes. nearBynding is available as an R/Bioconductor package and can run on a personal computer, making correlation of transcriptomic features broadly accessible.

RelA binding of mRNAs modulates translation or sRNA-mRNA basepairing depending on the position of the GGAG site

Previously, we reported that RelA protein facilitates Hfq-mediated mRNA-sRNA regulation by binding sRNAs carrying a Shine-Dalgarno-like GGAG sequence. In turn, sRNA-Hfq monomers are stabilized, enabling the attachment of more Hfq subunits to form a functional hexamer. Here, using CLIP-seq, we present a global analysis of RelA-bound RNAs showing that RelA interacts with sRNAs as well as with mRNAs carrying a GGAG motif. RelA binding of mRNAs carrying GGAG at position -7 relative to the initiation codon (AUG) inhibits translation by interfering with the binding of 30S ribosomes. The extent of inhibition depends on the distance of GGAG relative to the AUG, as shortening the spacing between GGAG and AUG abrogates RelA-mediated inhibition. Interestingly, RelA binding of target mRNAs carrying GGAG in the coding sequence or close to AUG facilitates target gene regulation by sRNA partners that lack GGAG. However, translation inhibition caused by RelA binding of mRNAs carrying GGAG at position -7 relative to the AUG renders sRNA-mRNA basepairing regulation ineffective. Our study indicates that by binding RNAs carrying GGAG the ribosome-associated RelA protein inhibits translation of specific newly synthesized incoming mRNAs or enables basepairing regulation by their respective sRNA partners, thereby introducing a new regulatory concept for the bacterial response.

rBPDL:Predicting RNA-Binding Proteins Using Deep Learning

RNA-binding protein (RBP) is a powerful and wide-ranging regulator that plays an important role in cell development, differentiation, metabolism, health and disease. The prediction of RBPs provides valuable guidance for biologists. Although experimental methods have made great progress in predicting RBP, they are time-consuming and not flexible. Therefore, we developed a network model, rBPDL, by combining a convolutional neural network and long short-term memory for multilabel classification of RBPs. Moreover, to achieve better prediction results, we used a voting algorithm for ensemble learning of the model. We compared rBPDL with state-of-the-art methods and found that rBPDL significantly improved identification performance for the RBP68 dataset, with a macro-Area Under Curve (AUC), micro-AUC, and weighted AUC of 0.936, 0.962, and 0.946, respectively. Furthermore, through AUC statistical analysis of the RBP domain, we analyzed the performance of rBPDL and found that the RBP identification performance in the same domain was similar. In addition, we analyzed the performance preferences and physicochemical properties of the binding protein amino acids and explored the characteristics that affect the binding by using the RBP86 dataset.

High-Throughput Selection and Characterisation of Aptamers on Optical Next-Generation Sequencers

Aptamers feature a number of advantages, compared to antibodies. However, their application has been limited so far, mainly because of the complex selection process. 'High-throughput sequencing fluorescent ligand interaction profiling' (HiTS-FLIP) significantly increases the selection efficiency and is consequently a very powerful and versatile technology for the selection of high-performance aptamers. It is the first experiment to allow the direct and quantitative measurement of the affinity and specificity of millions of aptamers simultaneously by harnessing the potential of optical next-generation sequencing platforms to perform fluorescence-based binding assays on the clusters displayed on the flow cells and determining their sequence and position in regular high-throughput sequencing. Many variants of the experiment have been developed that allow automation and in situ conversion of DNA clusters into base-modified DNA, RNA, peptides, and even proteins. In addition, the information from mutational assays, performed with HiTS-FLIP, provides deep insights into the relationship between the sequence, structure, and function of aptamers. This enables a detailed understanding of the sequence-specific rules that determine affinity, and thus, supports the evolution of aptamers. Current variants of the HiTS-FLIP experiment and its application in the field of aptamer selection, characterisation, and optimisation are presented in this review.

High-throughput dissection of the thermodynamic and conformational properties of a ubiquitous class of RNA tertiary contact motifs

Despite RNA's diverse secondary and tertiary structures and its complex conformational changes, nature utilizes a limited set of structural "motifs"-helices, junctions, and tertiary contact modules-to build diverse functional RNAs. Thus, in-depth descriptions of a relatively small universe of RNA motifs may lead to predictive models of RNA tertiary conformational landscapes. Motifs may have different properties depending on sequence and secondary structure, giving rise to subclasses that expand the universe of RNA building blocks. Yet we know very little about motif subclasses, given the challenges in mapping conformational properties in high throughput. Previously, we used "RNA on a massively parallel array" (RNA-MaP), a quantitative, high-throughput technique, to study thousands of helices and two-way junctions. Here, we adapt RNA-MaP to study the thermodynamic and conformational properties of tetraloop/tetraloop receptor (TL/TLR) tertiary contact motifs, analyzing 1,493 TLR sequences from different classes. Clustering analyses revealed variability in TL specificity, stability, and conformational behavior. Nevertheless, natural GAAA/11ntR TL/TLRs, while varying in tertiary stability by ∼2.5 kcal/mol, exhibited conserved TL specificity and conformational properties. Thus, RNAs may tune stability without altering the overall structure of these TL/TLRs. Furthermore, their stability correlated with natural frequency, suggesting thermodynamics as the dominant selection pressure. In contrast, other TL/TLRs displayed heterogenous conformational behavior and appear to not be under strong thermodynamic selection. Our results build toward a generalizable model of RNA-folding thermodynamics based on the properties of isolated motifs, and our characterized TL/TLR library can be used to engineer RNAs with predictable thermodynamic and conformational behavior.

Thermostability, Tunability, and Tenacity of RNA as Rubbery Anionic Polymeric Materials in Nanotechnology and Nanomedicine-Specific Cancer Targeting with Undetectable Toxicity

RNA nanotechnology is the bottom-up self-assembly of nanometer-scale architectures, resembling LEGOs, composed mainly of RNA. The ideal building material should be (1) versatile and controllable in shape and stoichiometry, (2) spontaneously self-assemble, and (3) thermodynamically, chemically, and enzymatically stable with a long shelf life. RNA building blocks exhibit each of the above. RNA is a polynucleic acid, making it a polymer, and its negative-charge prevents nonspecific binding to negatively charged cell membranes. The thermostability makes it suitable for logic gates, resistive memory, sensor set-ups, and NEM devices. RNA can be designed and manipulated with a level of simplicity of DNA while displaying versatile structure and enzyme activity of proteins. RNA can fold into single-stranded loops or bulges to serve as mounting dovetails for intermolecular or domain interactions without external linking dowels. RNA nanoparticles display rubber- and amoeba-like properties and are stretchable and shrinkable through multiple repeats, leading to enhanced tumor targeting and fast renal excretion to reduce toxicities. It was predicted in 2014 that RNA would be the third milestone in pharmaceutical drug development. The recent approval of several RNA drugs and COVID-19 mRNA vaccines by FDA suggests that this milestone is being realized. Here, we review the unique properties of RNA nanotechnology, summarize its recent advancements, describe its distinct attributes inside or outside the body and discuss potential applications in nanotechnology, medicine, and material science.

Systematic Analysis of Targets of Pumilio-Mediated mRNA Decay Reveals that PUM1 Repression by DNA Damage Activates Translesion Synthesis

RNA-binding proteins (RBPs) play a pivotal role in gene expression by modulating the stability of transcripts. However, the identification of degradation target mRNAs of RBPs remains difficult. By the combined analysis of transcriptome-wide mRNA stabilities and the binding of mRNAs to human Pumilio 1 (PUM1), we identify 48 mRNAs that both bind to PUM1 and exhibit PUM1-dependent degradation. Analysis of changes in the abundance of PUM1 and its degradation target mRNAs in RNA-seq data indicate that DNA-damaging agents negatively regulate PUM1-mediated mRNA decay. Cells exposed to cisplatin have reduced PUM1 abundance and increased PCNA and UBE2A mRNAs encoding proteins involved in DNA damage tolerance by translesion synthesis (TLS). Cells overexpressing PUM1 exhibit impaired DNA synthesis and TLS and increased sensitivity to the cytotoxic effect of cisplatin. Thus, our method identifies target mRNAs of PUM1-mediated decay and reveals that cells respond to DNA damage by inhibiting PUM1-mediated mRNA decay to activate TLS.

Human Pumilio proteins directly bind the CCR4-NOT deadenylase complex to regulate the transcriptome

Pumilio paralogs, PUM1 and PUM2, are sequence-specific RNA-binding proteins that are essential for vertebrate development and neurological functions. PUM1&2 negatively regulate gene expression by accelerating degradation of specific mRNAs. Here, we determined the repression mechanism and impact of human PUM1&2 on the transcriptome. We identified subunits of the CCR4-NOT (CNOT) deadenylase complex required for stable interaction with PUM1&2 and to elicit CNOT-dependent repression. Isoform-level RNA sequencing revealed broad coregulation of target mRNAs through the PUM-CNOT repression mechanism. Functional dissection of the domains of PUM1&2 identified a conserved amino-terminal region that confers the predominant repressive activity via direct interaction with CNOT. In addition, we show that the mRNA decapping enzyme, DCP2, has an important role in repression by PUM1&2 amino-terminal regions. Our results support a molecular model of repression by human PUM1&2 via direct recruitment of CNOT deadenylation machinery in a decapping-dependent mRNA decay pathway.

The kinetic landscape of an RNA-binding protein in cells

Gene expression in higher eukaryotic cells orchestrates interactions between thousands of RNA-binding proteins (RBPs) and tens of thousands of RNAs¹. The kinetics by which RBPs bind to and dissociate from their RNA sites are critical for the coordination of cellular RNA-protein interactions². However, these kinetic parameters have not been experimentally measured in cells. Here we show that time-resolved RNA-protein cross-linking with a pulsed femtosecond ultraviolet laser, followed by immunoprecipitation and high-throughput sequencing, allows the determination of binding and dissociation kinetics of the RBP DAZL for thousands of individual RNA-binding sites in cells. This kinetic cross-linking and immunoprecipitation (KIN-CLIP) approach reveals that DAZL resides at individual binding sites for time periods of only seconds or shorter, whereas the binding sites remain DAZL-free for markedly longer. The data also indicate that DAZL binds to many RNAs in clusters of multiple proximal sites. The effect of DAZL on mRNA levels and ribosome association correlates with the cumulative probability of DAZL binding in these clusters. Integrating kinetic data with mRNA features quantitatively connects DAZL-RNA binding to DAZL function. Our results show how kinetic parameters for RNA-protein interactions can be measured in cells, and how these data link RBP-RNA binding to the cellular function of RBPs.

Rapid and accurate determination of atomistic RNA dynamic ensemble models using NMR and structure prediction

Biomolecules form dynamic ensembles of many inter-converting conformations which are key for understanding how they fold and function. However, determining ensembles is challenging because the information required to specify atomic structures for thousands of conformations far exceeds that of experimental measurements. We addressed this data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformation library. Refinement of this library with NMR residual dipolar couplings provided an atomistic ensemble model for HIV-1 TAR, and the model accuracy was independently supported by comparisons to quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through designed ensemble redistribution via atomic mutagenesis. Applications to TAR bulge variants and more complex tertiary RNAs support the generality of this approach and the potential to make the determination of atomic-resolution RNA ensembles routine.

Determining dynamic ensembles of biomolecules is still challenging. Here the authors present an approach for rapid RNA ensemble determination that combines RNA structure prediction tools and NMR residual dipolar coupling data and use it to determine atomistic ensemble models for a variety of RNAs.

Principles of mRNA control by human PUM proteins elucidated from multimodal experiments and integrative data analysis

The human PUF-family proteins, PUM1 and PUM2, posttranscriptionally regulate gene expression by binding to a PUM recognition element (PRE) in the 3'-UTR of target mRNAs. Hundreds of PUM1/2 targets have been identified from changes in steady-state RNA levels; however, prior studies could not differentiate between the contributions of changes in transcription and RNA decay rates. We applied metabolic labeling to measure changes in RNA turnover in response to depletion of PUM1/2, showing that human PUM proteins regulate expression almost exclusively by changing RNA stability. We also applied an in vitro selection workflow to precisely identify the binding preferences of PUM1 and PUM2. By integrating our results with prior knowledge, we developed a "rulebook" of key contextual features that differentiate functional versus nonfunctional PREs, allowing us to train machine learning models that accurately predict the functional regulation of RNA targets by the human PUM proteins.

A molecular-level perspective on the frequency, distribution, and consequences of messenger RNA modifications

Cells use chemical modifications to alter the sterics, charge, and conformations of large biomolecules, modulating their biogenesis, function, and stability. Until recently post-transcriptional RNA modifications were thought to be largely limited to nonprotein coding RNA species. However, this dogma has rapidly transformed with the discovery of a host of modifications in protein coding messenger RNAs (mRNAs). Recent advancements in genome-wide sequencing technologies have enabled the identification of mRNA modifications as a potential new frontier in gene regulation-leading to the development of the epitranscriptome field. As a result, there has been a flurry of multiple groundbreaking discoveries, including new modifications, nucleoside modifying enzymes ("writers" and "erasers"), and RNA binding proteins that recognize chemical modifications ("readers"). These discoveries opened the door to understanding how post-transcriptional mRNA modifications can modulate the mRNA lifecycle, and established a link between the epitranscriptome and human health and disease. Despite a rapidly growing recognition of their importance, fundamental questions regarding the identity, prevalence, and functional consequences of mRNA modifications remain to be answered. Here, we highlight quantitative studies that characterize mRNA modification abundance, frequency, and interactions with cellular machinery. As the field progresses, we see a need for the further integration of quantitative and reductionist approaches to complement transcriptome wide studies in order to establish a molecular-level framework for understanding the consequences of mRNA chemical modifications on biological processes. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Processing > RNA Editing and Modification.

The evolution of the Puf superfamily of proteins across the tree of eukaryotes

BACKGROUND

Eukaryotic gene expression is controlled by a number of RNA-binding proteins (RBP), such as the proteins from the Puf (Pumilio and FBF) superfamily (PufSF). These proteins bind to RNA via multiple Puf repeat domains, each of which specifically recognizes a single RNA base. Recently, three diversified PufSF proteins have been described in model organisms, each of which is responsible for the maturation of ribosomal RNA or the translational regulation of mRNAs; however, less is known about the role of these proteins across eukaryotic diversity.

RESULTS

Here, we investigated the distribution and function of PufSF RBPs in the tree of eukaryotes. We determined that the following PufSF proteins are universally conserved across eukaryotes and can be broadly classified into three groups: (i) Nop9 orthologues, which participate in the nucleolar processing of immature 18S rRNA; (ii) 'classical' Pufs, which control the translation of mRNA; and (iii) PUM3 orthologues, which are involved in the maturation of 7S rRNA. In nearly all eukaryotes, the rRNA maturation proteins, Nop9 and PUM3, are retained as a single copy, while mRNA effectors ('classical' Pufs) underwent multiple lineage-specific expansions. We propose that the variation in number of 'classical' Pufs relates to the size of the transcriptome and thus the potential mRNA targets. We further distinguished full set of PufSF proteins in divergent metamonad Giardia intestinalis and initiated their cellular and biochemical characterization.

CONCLUSIONS

Our data suggest that the last eukaryotic common ancestor (LECA) already contained all three types of PufSF proteins and that 'classical' Pufs then underwent lineage-specific expansions.

High throughput approaches to study RNA-protein interactions in vitro

To understand the regulation of gene expression it is critical to determine how proteins interact with and discriminate between different RNAs. In this review, we discuss experimental techniques that utilize high throughput approaches to characterize the interactions of proteins with large numbers of RNAs in vitro. We describe the underlying principles for the main methods, briefly discuss their scope and limitations, and outline how insight from the techniques contributes to our understanding of specificity for RNA-protein interactions.

Characterization of RNP Networks of PUM1 and PUM2 Post-Transcriptional Regulators in TCam-2 Cells, a Human Male Germ Cell Model

Mammalian Pumilio (PUM) proteins are sequence-specific, RNA-binding proteins (RBPs) with wide-ranging roles. They are involved in germ cell development, which has functional implications in development and fertility. Although human PUM1 and PUM2 are closely related to each other and recognize the same RNA binding motif, there is some evidence for functional diversity. To address that problem, first we used RIP-Seq and RNA-Seq approaches, and identified mRNA pools regulated by PUM1 and PUM2 proteins in the TCam-2 cell line, a human male germ cell model. Second, applying global mass spectrometry-based profiling, we identified distinct PUM1- and PUM2-interacting putative protein cofactors, most of them involved in RNA processing. Third, combinatorial analysis of RIP and RNA-Seq, mass spectrometry, and RNA motif enrichment analysis revealed that PUM1 and PUM2 form partially varied RNP-regulatory networks (RNA regulons), which indicate different roles in human reproduction and testicular tumorigenesis. Altogether, this work proposes that protein paralogues with very similar and evolutionary highly conserved functional domains may play divergent roles in the cell by combining with different sets of protein cofactors. Our findings highlight the versatility of PUM paralogue-based post-transcriptional regulation, offering insight into the mechanisms underlying their diverse biological roles and diseases resulting from their dysfunction.

The roles of structural dynamics in the cellular functions of RNAs

RNAs fold into 3D structures that range from simple helical elements to complex tertiary structures and quaternary ribonucleoprotein assemblies. The functions of many regulatory RNAs depend on how their 3D structure changes in response to a diverse array of cellular conditions. In this Review, we examine how the structural characterization of RNA as dynamic ensembles of conformations, which form with different probabilities and at different timescales, is improving our understanding of RNA function in cells. We discuss the mechanisms of gene regulation by microRNAs, riboswitches, ribozymes, post-transcriptional RNA modifications and RNA-binding proteins, and how the cellular environment and processes such as liquid-liquid phase separation may affect RNA folding and activity. The emerging RNA-ensemble-function paradigm is changing our perspective and understanding of RNA regulation, from in vitro to in vivo and from descriptive to predictive.

Modulation of RNA Condensation by the DEAD-Box Protein eIF4A

Stress granules are condensates of non-translating mRNAs and proteins involved in the stress response and neurodegenerative diseases. Stress granules form in part through intermolecular RNA-RNA interactions, and to better understand how RNA-based condensation occurs, we demonstrate that RNA is effectively recruited to the surfaces of RNA or RNP condensates in vitro. We demonstrate that, through ATP-dependent RNA binding, the DEAD-box protein eIF4A reduces RNA condensation in vitro and limits stress granule formation in cells. This defines a function for eIF4A to limit intermolecular RNA-RNA interactions in cells. These results establish an important role for eIF4A, and potentially other DEAD-box proteins, as ATP-dependent RNA chaperones that limit the condensation of RNA, analogous to the function of proteins like HSP70 in combatting protein aggregates.

Approaches for measuring the dynamics of RNA-protein interactions

RNA-protein interactions are pivotal for the regulation of gene expression from bacteria to human. RNA-protein interactions are dynamic; they change over biologically relevant timescales. Understanding the regulation of gene expression at the RNA level therefore requires knowledge of the dynamics of RNA-protein interactions. Here, we discuss the main experimental approaches to measure dynamic aspects of RNA-protein interactions. We cover techniques that assess dynamics of cellular RNA-protein interactions that accompany biological processes over timescales of hours or longer and techniques measuring the kinetic dynamics of RNA-protein interactions in vitro. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Evolution and Genomics > Ribonomics.

Sequence-dependent RNA helix conformational preferences predictably impact tertiary structure formation

Structured RNAs and RNA complexes underlie biological processes ranging from control of gene expression to protein translation. Approximately 50% of nucleotides within known structured RNAs are folded into Watson-Crick (WC) base pairs, and sequence changes that preserve these pairs are typically assumed to preserve higher-order RNA structure and binding of macromolecule partners. Here, we report that indirect effects of the helix sequence on RNA tertiary stability are, in fact, significant but are nevertheless predictable from a simple computational model called RNAMake-∆∆G. When tested through the RNA on a massively parallel array (RNA-MaP) experimental platform, blind predictions for >1500 variants of the tectoRNA heterodimer model system achieve high accuracy (rmsd 0.34 and 0.77 kcal/mol for sequence and length changes, respectively). Detailed comparison of predictions to experiments support a microscopic picture of how helix sequence changes subtly modulate conformational fluctuations at each base-pair step, which accumulate to impact RNA tertiary structure stability. Our study reveals a previously overlooked phenomenon in RNA structure formation and provides a framework of computation and experiment for understanding helix conformational preferences and their impact across biological RNA and RNA-protein assemblies.