Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture

RNA-binding proteins potentially regulate the alternative splicing of apoptotic genes during knee osteoarthritis progression

BACKGROUND

Alternative splicing (AS) is a principal mode of genetic regulation and one of the most widely used mechanisms to generate structurally and functionally distinct mRNA and protein variants. Dysregulation of AS may result in aberrant transcription and protein products, leading to the emergence of human diseases. Although considered important for regulating gene expression, genome-wide AS dysregulation, underlying mechanisms, and clinical relevance in knee osteoarthritis (OA) remain unelucidated. Therefore, in this study, we elucidated and validated AS events and their regulatory mechanisms during OA progression.

RESULTS

In this study, we identified differentially expressed genes between human OA and healthy meniscus samples. Among them, the OA-associated genes were primarily enriched in biological pathways such as extracellular matrix organization and ossification. The predominant OA-associated regulated AS (RAS) events were found to be involved in apoptosis during OA development. The expression of the apoptosis-related gene BCL2L13, XAF1, and NF2 were significantly different between OA and healthy meniscus samples. The construction of a covariation network of RNA-binding proteins (RBPs) and RAS genes revealed that differentially expressed RBP genes LAMA2 and CUL4B may regulate the apoptotic genes XAF1 and BCL2L13 to undergo AS events during OA progression. Finally, RT-qPCR revealed that CUL4B expression was significantly higher in OA meniscus samples than in normal controls and that the AS ratio of XAF1 was significantly different between control and OA samples; these findings were consistent with their expected expression and regulatory relationships.

CONCLUSIONS

Differentially expressed RBPs may regulate the AS of apoptotic genes during knee OA progression. XAF1 and its regulator, CUL4B, may serve as novel biomarkers and potential therapeutic targets for this disease.

RNA binding protein PRRC2B mediates translation of specific mRNAs and regulates cell cycle progression

Accumulating evidence suggests that posttranscriptional control of gene expression, including RNA splicing, transport, modification, translation and degradation, primarily relies on RNA binding proteins (RBPs). However, the functions of many RBPs remain understudied. Here, we characterized the function of a novel RBP, Proline-Rich Coiled-coil 2B (PRRC2B). Through photoactivatable ribonucleoside-enhanced crosslinking and immunoprecipitation and sequencing (PAR-CLIP-seq), we identified transcriptome-wide CU- or GA-rich PRRC2B binding sites near the translation initiation codon on a specific cohort of mRNAs in HEK293T cells. These mRNAs, including oncogenes and cell cycle regulators such as CCND2 (cyclin D2), exhibited decreased translation upon PRRC2B knockdown as revealed by polysome-associated RNA-seq, resulting in reduced G1/S phase transition and cell proliferation. Antisense oligonucleotides blocking PRRC2B interactions with CCND2 mRNA decreased its translation, thus inhibiting G1/S transition and cell proliferation. Mechanistically, PRRC2B interactome analysis revealed RNA-independent interactions with eukaryotic translation initiation factors 3 (eIF3) and 4G2 (eIF4G2). The interaction with translation initiation factors is essential for PRRC2B function since the eIF3/eIF4G2-interacting defective mutant, unlike wild-type PRRC2B, failed to rescue the translation deficiency or cell proliferation inhibition caused by PRRC2B knockdown. Altogether, our findings reveal that PRRC2B is essential for efficiently translating specific proteins required for cell cycle progression and cell proliferation.

Viral RNA Is a Hub for Critical Host-Virus Interactions

RNA is a central molecule in the life cycle of viruses, acting not only as messenger (m)RNA but also as a genome. Given these critical roles, it is not surprising that viral RNA is a hub for host-virus interactions. However, the interactome of viral RNAs remains largely unknown. This chapter discusses the importance of cellular RNA-binding proteins in virus infection and the emergent approaches developed to uncover and characterise them.

Melanoma RBPome identification reveals PDIA6 as an unconventional RNA-binding protein involved in metastasis

RNA-binding proteins (RBPs) have been relatively overlooked in cancer research despite their contribution to virtually every cancer hallmark. Here, we use RNA interactome capture (RIC) to characterize the melanoma RBPome and uncover novel RBPs involved in melanoma progression. Comparison of RIC profiles of a non-tumoral versus a metastatic cell line revealed prevalent changes in RNA-binding capacities that were not associated with changes in RBP levels. Extensive functional validation of a selected group of 24 RBPs using five different in vitro assays unveiled unanticipated roles of RBPs in melanoma malignancy. As proof-of-principle we focused on PDIA6, an ER-lumen chaperone that displayed a novel RNA-binding activity. We show that PDIA6 is involved in metastatic progression, map its RNA-binding domain, and find that RNA binding is required for PDIA6 tumorigenic properties. These results exemplify how RIC technologies can be harnessed to uncover novel vulnerabilities of cancer cells.

RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins

RNA binding proteins (RBPs) are critical for the post-transcriptional control of RNAs and play vital roles in a myriad of biological processes, such as RNA localization and gene regulation. Therefore, computational methods that are capable of accurately identifying RBPs are highly desirable and have important implications for biomedical and biotechnological applications. Here, we propose a two-stage deep transfer learning-based framework, termed RBP-TSTL, for accurate prediction of RBPs. In the first stage, the knowledge from the self-supervised pre-trained model was extracted as feature embeddings and used to represent the protein sequences, while in the second stage, a customized deep learning model was initialized based on an annotated pre-training RBPs dataset before being fine-tuned on each corresponding target species dataset. This two-stage transfer learning framework can enable the RBP-TSTL model to be effectively trained to learn and improve the prediction performance. Extensive performance benchmarking of the RBP-TSTL models trained using the features generated by the self-supervised pre-trained model and other models trained using hand-crafting encoding features demonstrated the effectiveness of the proposed two-stage knowledge transfer strategy based on the self-supervised pre-trained models. Using the best-performing RBP-TSTL models, we further conducted genome-scale RBP predictions for Homo sapiens, Arabidopsis thaliana, Escherichia coli, and Salmonella and established a computational compendium containing all the predicted putative RBPs candidates. We anticipate that the proposed RBP-TSTL approach will be explored as a useful tool for the characterization of RNA-binding proteins and exploration of their sequence–structure–function relationships.

An atlas of posttranslational modifications on RNA binding proteins

RNA structure and function are intimately tied to RNA binding protein recognition and regulation. Posttranslational modifications are chemical modifications which can control protein biology. The role of PTMs in the regulation RBPs is not well understood, in part due to a lacking analysis of PTM deposition on RBPs. Herein, we present an analysis of posttranslational modifications (PTMs) on RNA binding proteins (RBPs; a PTM RBP Atlas). We curate published datasets and primary literature to understand the landscape of PTMs and use protein-protein interaction data to understand and potentially provide a framework for understanding which enzymes are controlling PTM deposition and removal on the RBP landscape. Intersection of our data with The Cancer Genome Atlas also provides researchers understanding of mutations that would alter PTM deposition. Additional characterization of the RNA-protein interface provided from in-cell UV crosslinking experiments provides a framework for hypotheses about which PTMs could be regulating RNA binding and thus RBP function. Finally, we provide an online database for our data that is easy to use for the community. It is our hope our efforts will provide researchers will an invaluable tool to test the function of PTMs controlling RBP function and thus RNA biology.

Targeted RNA editing: novel tools to study post-transcriptional regulation

RNA binding proteins (RBPs) regulate nearly all post-transcriptional processes within cells. To fully understand RBP function, it is essential to identify their in vivo targets. Standard techniques for profiling RBP targets, such as crosslinking immunoprecipitation (CLIP) and its variants, are limited or suboptimal in some situations, e.g. when compatible antibodies are not available and when dealing with small cell populations such as neuronal subtypes and primary stem cells. This review summarizes and compares several genetic approaches recently designed to identify RBP targets in such circumstances. TRIBE (targets of RNA binding proteins identified by editing), RNA tagging, and STAMP (surveying targets by APOBEC-mediated profiling) are new genetic tools useful for the study of post-transcriptional regulation and RBP identification. We describe the underlying RNA base editing technology, recent applications, and therapeutic implications.

Shaping the Innate Immune Response Through Post-Transcriptional Regulation of Gene Expression Mediated by RNA-Binding Proteins

Innate immunity is the frontline of defense against infections and tissue damage. It is a fast and semi-specific response involving a myriad of processes essential for protecting the organism. These reactions promote the clearance of danger by activating, among others, an inflammatory response, the complement cascade and by recruiting the adaptive immunity. Any disequilibrium in this functional balance can lead to either inflammation-mediated tissue damage or defense inefficiency. A dynamic and coordinated gene expression program lies at the heart of the innate immune response. This expression program varies depending on the cell-type and the specific danger signal encountered by the cell and involves multiple layers of regulation. While these are achieved mainly via transcriptional control of gene expression, numerous post-transcriptional regulatory pathways involving RNA-binding proteins (RBPs) and other effectors play a critical role in its fine-tuning. Alternative splicing, translational control and mRNA stability have been shown to be tightly regulated during the innate immune response and participate in modulating gene expression in a global or gene specific manner. More recently, microRNAs assisting RBPs and post-transcriptional modification of RNA bases are also emerging as essential players of the innate immune process. In this review, we highlight the numerous roles played by specific RNA-binding effectors in mediating post-transcriptional control of gene expression to shape innate immunity.

Validation and classification of RNA binding proteins identified by mRNA interactome capture

RNA binding proteins (RBPs) take part in all steps of the RNA life cycle and are often essential for cell viability. Most RBPs have a modular organization and comprise a set of canonical RNA binding domains. However, in recent years a number of high-throughput mRNA interactome studies on yeast, mammalian cell lines, and whole organisms have uncovered a multitude of novel mRNA interacting proteins that lack classical RNA binding domains. Whereas a few have been confirmed to be direct and functionally relevant RNA binders, biochemical and functional validation of RNA binding of most others is lacking. In this study, we used a combination of NMR spectroscopy and biochemical studies to test the RNA binding properties of six putative RBPs. Half of the analyzed proteins showed no interaction, whereas the other half displayed weak chemical shift perturbations upon titration with RNA. One of the candidates we found to interact weakly with RNA in vitro is Drosophila melanogaster end binding protein 1 (EB1), a master regulator of microtubule plus-end dynamics. Further analysis showed that EB1's RNA binding occurs on the same surface as that with which EB1 interacts with microtubules. RNA immunoprecipitation and colocalization experiments suggest that EB1 is a rather nonspecific, opportunistic RNA binder. Our data suggest that care should be taken when embarking on an RNA binding study involving these unconventional, novel RBPs, and we recommend initial and simple in vitro RNA binding experiments.

Recruitment of endoplasmic reticulum-targeted and cytosolic mRNAs into membrane-associated stress granules

Stress granules (SGs) are membraneless organelles composed of mRNAs and RNA binding proteins which undergo assembly in response to stress-induced inactivation of translation initiation. In general, SG recruitment is limited to a subpopulation of a given mRNA species and RNA-seq analyses of purified SGs revealed that signal sequence-encoding (i.e., endoplasmic reticulum [ER]-targeted) transcripts are significantly underrepresented, consistent with prior reports that ER localization can protect mRNAs from SG recruitment. Using translational profiling, cell fractionation, and single molecule mRNA imaging, we examined SG biogenesis following activation of the unfolded protein response (UPR) by 1,4-dithiothreitol (DTT) and report that gene-specific subsets of cytosolic and ER-targeted mRNAs can be recruited into SGs. Furthermore, we demonstrate that SGs form in close proximity to or directly associated with the ER membrane. ER-associated SG assembly was also observed during arsenite stress, suggesting broad roles for the ER in SG biogenesis. Recruitment of a given mRNA into SGs required stress-induced translational repression, though translational inhibition was not solely predictive of an mRNA's propensity for SG recruitment. SG formation was prevented by the transcriptional inhibitors actinomycin D or triptolide, suggesting a functional link between gene transcriptional state and SG biogenesis. Collectively these data demonstrate that ER-targeted and cytosolic mRNAs can be recruited into ER-associated SGs and this recruitment is sensitive to transcriptional inhibition. We propose that newly transcribed mRNAs exported under conditions of suppressed translation initiation are primary SG substrates, with the ER serving as the central subcellular site of SG formation.

The expanding world of metabolic enzymes moonlighting as RNA binding proteins

RNA binding proteins play key roles in many aspects of RNA metabolism and function, including splicing, transport, translation, localization, stability and degradation. Within the past few years, proteomics studies have identified dozens of enzymes in intermediary metabolism that bind to RNA. The wide occurrence and conservation of RNA binding ability across distant branches of the evolutionary tree suggest that these moonlighting enzymes are involved in connections between intermediary metabolism and gene expression that comprise far more extensive regulatory networks than previously thought. There are many outstanding questions about the molecular structures and mechanisms involved, the effects of these interactions on enzyme and RNA functions, and the factors that regulate the interactions. The effects on RNA function are likely to be wider than regulation of translation, and some enzyme-RNA interactions have been found to regulate the enzyme's catalytic activity. Several enzyme-RNA interactions have been shown to be affected by cellular factors that change under different intracellular and environmental conditions, including concentrations of substrates and cofactors. Understanding the molecular mechanisms involved in the interactions between the enzymes and RNA, the factors involved in regulation, and the effects of the enzyme-RNA interactions on both the enzyme and RNA functions will lead to a better understanding of the role of the many newly identified enzyme-RNA interactions in connecting intermediary metabolism and gene expression.

Eukaryote-Conserved Methylarginine Is Absent in Diplomonads and Functionally Compensated in Giardia

Methylation is a common posttranslational modification of arginine and lysine in eukaryotic proteins. Methylproteomes are best characterized for higher eukaryotes, where they are functionally expanded and evolved complex regulation. However, this is not the case for protist species evolved from the earliest eukaryotic lineages. Here, we integrated bioinformatic, proteomic, and drug-screening data sets to comprehensively explore the methylproteome of Giardia duodenalis-a deeply branching parasitic protist. We demonstrate that Giardia and related diplomonads lack arginine-methyltransferases and have remodeled conserved RGG/RG motifs targeted by these enzymes. We also provide experimental evidence for methylarginine absence in proteomes of Giardia but readily detect methyllysine. We bioinformatically infer 11 lysine-methyltransferases in Giardia, including highly diverged Su(var)3-9, Enhancer-of-zeste and Trithorax proteins with reduced domain architectures, and novel annotations demonstrating conserved methyllysine regulation of eukaryotic elongation factor 1 alpha. Using mass spectrometry, we identify more than 200 methyllysine sites in Giardia, including in species-specific gene families involved in cytoskeletal regulation, enriched in coiled-coil features. Finally, we use known methylation inhibitors to show that methylation plays key roles in replication and cyst formation in this parasite. This study highlights reduced methylation enzymes, sites, and functions early in eukaryote evolution, including absent methylarginine networks in the Diplomonadida. These results challenge the view that arginine methylation is eukaryote conserved and demonstrate that functional compensation of methylarginine was possible preceding expansion and diversification of these key networks in higher eukaryotes.

Mass spectrometry-based protein‒protein interaction techniques and their applications in studies of DNA damage repair

Proteins are major functional units that are tightly connected to form complex and dynamic networks. These networks enable cells and organisms to operate properly and respond efficiently to environmental cues. Over the past decades, many biochemical methods have been developed to search for protein-binding partners in order to understand how protein networks are constructed and connected. At the same time, rapid development in proteomics and mass spectrometry (MS) techniques makes it possible to identify interacting proteins and build comprehensive protein‒protein interaction networks. The resulting interactomes and networks have proven informative in the investigation of biological functions, such as in the field of DNA damage repair. In recent years, a number of proteins involved in DNA damage response and DNA repair pathways have been uncovered with MS-based protein‒protein interaction studies. As the technologies for enriching associated proteins and MS become more sophisticated, the studies of protein‒protein interactions are entering a new era. In this review, we summarize the strategies and recent developments for exploring protein‒protein interaction. In addition, we discuss the application of these tools in the investigation of protein‒protein interaction networks involved in DNA damage response and DNA repair.

The Role of Small Noncoding RNA in DNA Double-Strand Break Repair

DNA damage is a common phenomenon promoted through a variety of exogenous and endogenous factors. The DNA damage response (DDR) pathway involves a wide range of proteins, and as was indicated, small noncoding RNAs (sncRNAs). These are double-strand break-induced RNAs (diRNAs) and DNA damage response small RNA (DDRNA). Moreover, RNA binding proteins (RBPs) and RNA modifications have also been identified to modulate diRNA and DDRNA function in the DDR process. Several theories have been formulated regarding the synthesis and function of these sncRNAs during DNA repair; nevertheless, these pathways’ molecular details remain unclear. Here, we review the current knowledge regarding the mechanisms of diRNA and DDRNA biosynthesis and discuss the role of sncRNAs in maintaining genome stability.

Single and Combined Methods to Specifically or Bulk-Purify RNA-Protein Complexes

The ribonome interconnects the proteome and the transcriptome. Specific biology is situated at this interface, which can be studied in bulk using omics approaches or specifically by targeting an individual protein or RNA species. In this review, we focus on both RNA- and ribonucleoprotein-(RNP) centric methods. These methods can be used to study the dynamics of the ribonome in response to a stimulus or to identify the proteins that interact with a specific RNA species. The purpose of this review is to provide and discuss an overview of strategies to cross-link RNA to proteins and the currently available RNA- and RNP-centric approaches to study RNPs. We elaborate on some major challenges common to most methods, involving RNP yield, purity and experimental cost. We identify the origin of these difficulties and propose to combine existing approaches to overcome these challenges. The solutions provided build on the recently developed organic phase separation protocols, such as Cross-Linked RNA eXtraction (XRNAX), orthogonal organic phase separation (OOPS) and Phenol-Toluol extraction (PTex).

DNA:RNA hybrids form at DNA double-strand breaks in transcriptionally active loci

The recent discovery of DNA:RNA hybrids, or R-loops, actively forming at DNA double-strand breaks (DSBs) has unlocked fresh insight into how RNA participates in DNA repair. However, the manner of DSB-induced R-loop formation is vital in determining its mechanism of action and is currently under debate. Here, we analyse published DNA:RNA-hybrid sequencing to elucidate the features that determine DSB-induced R-loop formation. We found that pre-existing transcriptional activity was critical for R-loop generation at break sites, suggesting that these RNAs are transcribed prior to break induction. In addition, this appeared to be a specific DSB response at the break, distinct from traditional, co-transcriptionally formed R-loops. We hypothesise that R-loop formation is orchestrated by the damage response at transcriptionally active DSB loci to specifically maintain these genomic regions. Further investigation is required to fully understand how canonical repair processes regulate R-loops at breaks and how they participate in the repair process.

In silico, in vitro, and in vivo Approaches to Identify Molecular Players in Fragile X Tremor and Ataxia Syndrome

Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset neurodegenerative monogenetic disorder affecting carriers of premutation (PM) forms of the FMR1 gene, resulting in a progressive development of tremors, ataxia, and neuropsychological problems. This highly disabling disease is quite common in the general population with an estimation of about 20 million PM carriers worldwide. The chances of developing FXTAS increase dramatically with age, with about 45% of male carriers over the age of 50 being affected. Both the gene and pathogenic trigger, a mutant expansion of CGG RNA, causing FXTAS are known. This makes it an interesting disease to develop targeted therapeutic interventions for. Yet, no such interventions are available at this moment. Here we discuss in silico, in vitro, and in vivo approaches and how they have been used to identify the molecular determinants of FXTAS pathology. These approaches have yielded substantial information about FXTAS pathology and, consequently, many markers have emerged to play a key role in understanding the disease mechanism. Integration of the different approaches is expected to provide crucial information about the value of these markers as either therapeutic target or biomarker, essential to monitor therapeutic interventions in the future.

The roles of RNA in DNA double-strand break repair

Effective DNA repair is essential for cell survival: a failure to correctly repair damage leads to the accumulation of mutations and is the driving force for carcinogenesis. Multiple pathways have evolved to protect against both intrinsic and extrinsic genotoxic events, and recent developments have highlighted an unforeseen critical role for RNA in ensuring genome stability. It is currently unclear exactly how RNA molecules participate in the repair pathways, although many models have been proposed and it is possible that RNA acts in diverse ways to facilitate DNA repair. A number of well-documented DNA repair factors have been described to have RNA-binding capacities and, moreover, screens investigating DNA-damage repair mechanisms have identified RNA-binding proteins as a major group of novel factors involved in DNA repair. In this review, we integrate some of these datasets to identify commonalities that might highlight novel and interesting factors for future investigations. This emerging role for RNA opens up a new dimension in the field of DNA repair; we discuss its impact on our current understanding of DNA repair processes and consider how it might influence cancer progression.

RNA Binding Proteins and Gene Expression Regulation in Trypanosoma cruzi

The regulation of gene expression in trypanosomatids occurs mainly at the post-transcriptional level. In the case of Trypanosoma cruzi, the characterization of messenger ribonucleoprotein (mRNP) particles has allowed the identification of several classes of RNA binding proteins (RBPs), as well as non-canonical RBPs, associated with mRNA molecules. The protein composition of the mRNPs as well as the localization and functionality of the mRNAs depend on their associated proteins. mRNPs can also be organized into larger complexes forming RNA granules, which function as stress granules or P-bodies depending on the associated proteins. The fate of mRNAs in the cell, and consequently the genes expressed, depends on the set of proteins associated with the messenger molecule. These proteins allow the coordinated expression of mRNAs encoding proteins that are related in function, resulting in the formation of post-transcriptional operons. However, the puzzle posed by the combinatorial association of sets of RBPs with mRNAs and how this relates to the expressed genes remain to be elucidated. One important tool in this endeavor is the use of the CRISPR/CAS system to delete genes encoding RBPs, allowing the evaluation of their effect on the formation of mRNP complexes and associated mRNAs in the different compartments of the translation machinery. Accordingly, we recently established this methodology for T. cruzi and deleted the genes encoding RBPs containing zinc finger domains. In this manuscript, we will discuss the data obtained and the potential of the CRISPR/CAS methodology to unveil the role of RBPs in T. cruzi gene expression regulation.

RNA structure drives interaction with proteins

The combination of high-throughput sequencing and in vivo crosslinking approaches leads to the progressive uncovering of the complex interdependence between cellular transcriptome and proteome. Yet, the molecular determinants governing interactions in protein-RNA networks are not well understood. Here we investigated the relationship between the structure of an RNA and its ability to interact with proteins. Analysing in silico, in vitro and in vivo experiments, we find that the amount of double-stranded regions in an RNA correlates with the number of protein contacts. This relationship -which we call structure-driven protein interactivity- allows classification of RNA types, plays a role in gene regulation and could have implications for the formation of phase-separated ribonucleoprotein assemblies. We validate our hypothesis by showing that a highly structured RNA can rearrange the composition of a protein aggregate. We report that the tendency of proteins to phase-separate is reduced by interactions with specific RNAs.

The mRNA-bound Proteome of Leishmania mexicana: Novel Genetic Insight into an Ancient Parasite

Leishmania parasite infections, termed the leishmaniases, cause significant global infectious disease burden. The lifecycle of the parasite embodies three main stages that require precise coordination of gene regulation to survive environmental shifts between sandfly and mammalian hosts. Constitutive transcription in kinetoplastid parasites means that gene regulation is overwhelmingly reliant on post-transcriptional mechanisms, yet strikingly few Leishmania trans-regulators are known. Using optimized crosslinking and deep, quantified mass spectrometry, we present a comprehensive analysis of 1400 mRNA binding proteins (mRBPs) and whole cell proteomes from the three main Leishmania lifecycle stages. Supporting the validity, although the crosslinked RBPome is magnitudes more enriched, the protein identities of the crosslinked and non-crosslinked RBPomes were nearly identical. Moreover, multiple candidate RBPs were endogenously tagged and found to associate with discrete mRNA target pools in a stage-specific manner. Results indicate that in L. mexicana parasites, mRNA levels are not a strong predictor of the whole cell expression or RNA binding potential of encoded proteins. Evidence includes a low correlation between transcript and corresponding protein expression and stage-specific variation in protein expression versus RNA binding potential. Unsurprisingly, RNA binding protein enrichment correlates strongly with relative replication efficiency of the specific lifecycle stage. Our study is the first to quantitatively define and compare the mRBPome of multiple stages in kinetoplastid parasites. It provides novel, in-depth insight into the trans-regulatory mRNA:Protein (mRNP) complexes that drive Leishmania parasite lifecycle progression.

Computational identification of binding energy hot spots in protein-RNA complexes using an ensemble approach

Motivation

Identifying RNA-binding residues, especially energetically favored hot spots, can provide valuable clues for understanding the mechanisms and functional importance of protein-RNA interactions. Yet, limited availability of experimentally recognized energy hot spots in protein-RNA crystal structures leads to the difficulties in developing empirical identification approaches. Computational prediction of RNA-binding hot spot residues is still in its infant stage.

Results

Here, we describe a computational method, PrabHot (Prediction of protein-RNA binding hot spots), that can effectively detect hot spot residues on protein-RNA binding interfaces using an ensemble of conceptually different machine learning classifiers. Residue interaction network features and new solvent exposure characteristics are combined together and selected for classification with the Boruta algorithm. In particular, two new reference datasets (benchmark and independent) have been generated containing 107 hot spots from 47 known protein-RNA complex structures. In 10-fold cross-validation on the training dataset, PrabHot achieves promising performances with an AUC score of 0.86 and a sensitivity of 0.78, which are significantly better than that of the pioneer RNA-binding hot spot prediction method HotSPRing. We also demonstrate the capability of our proposed method on the independent test dataset and gain a competitive advantage as a result.

Availability and implementation

The PrabHot webserver is freely available at http://denglab.org/PrabHot/.

Contact

leideng@csu.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Recent advances in proximity-based labeling methods for interactome mapping

Proximity-based labeling has emerged as a powerful complementary approach to classic affinity purification of multiprotein complexes in the mapping of protein-protein interactions. Ongoing optimization of enzyme tags and delivery methods has improved both temporal and spatial resolution, and the technique has been successfully employed in numerous small-scale (single complex mapping) and large-scale (network mapping) initiatives. When paired with quantitative proteomic approaches, the ability of these assays to provide snapshots of stable and transient interactions over time greatly facilitates the mapping of dynamic interactomes. Furthermore, recent innovations have extended biotin-based proximity labeling techniques such as BioID and APEX beyond classic protein-centric assays (tag a protein to label neighboring proteins) to include RNA-centric (tag an RNA species to label RNA-binding proteins) and DNA-centric (tag a gene locus to label associated protein complexes) assays.

Ping-Pong-Tumor and Host in Pancreatic Cancer Progression

Metastasis is the main cause of high pancreatic cancer (PaCa) mortality and trials dampening PaCa mortality rates are not satisfying. Tumor progression is driven by the crosstalk between tumor cells, predominantly cancer-initiating cells (CIC), and surrounding cells and tissues as well as distant organs, where tumor-derived extracellular vesicles (TEX) are of major importance. A strong stroma reaction, recruitment of immunosuppressive leukocytes, perineural invasion, and early spread toward the peritoneal cavity, liver, and lung are shared with several epithelial cell-derived cancer, but are most prominent in PaCa. Here, we report on the state of knowledge on the PaCIC markers Tspan8, alpha6beta4, CD44v6, CXCR4, LRP5/6, LRG5, claudin7, EpCAM, and CD133, which all, but at different steps, are engaged in the metastatic cascade, frequently via PaCIC-TEX. This includes the contribution of PaCIC markers to TEX biogenesis, targeting, and uptake. We then discuss PaCa-selective features, where feedback loops between stromal elements and tumor cells, including distorted transcription, signal transduction, and metabolic shifts, establish vicious circles. For the latter particularly pancreatic stellate cells (PSC) are responsible, furnishing PaCa to cope with poor angiogenesis-promoted hypoxia by metabolic shifts and direct nutrient transfer via vesicles. Furthermore, nerves including Schwann cells deliver a large range of tumor cell attracting factors and Schwann cells additionally support PaCa cell survival by signaling receptor binding. PSC, tumor-associated macrophages, and components of the dysplastic stroma contribute to perineural invasion with signaling pathway activation including the cholinergic system. Last, PaCa aggressiveness is strongly assisted by the immune system. Although rich in immune cells, only immunosuppressive cells and factors are recovered in proximity to tumor cells and hamper effector immune cells entering the tumor stroma. Besides a paucity of immunostimulatory factors and receptors, immunosuppressive cytokines, myeloid-derived suppressor cells, regulatory T-cells, and M2 macrophages as well as PSC actively inhibit effector cell activation. This accounts for NK cells of the non-adaptive and cytotoxic T-cells of the adaptive immune system. We anticipate further deciphering the molecular background of these recently unraveled intermingled phenomena may turn most lethal PaCa into a curatively treatable disease.

Biological functions, regulatory mechanisms, and disease relevance of RNA localization pathways

The asymmetric subcellular distribution of RNA molecules from their sites of transcription to specific compartments of the cell is an important aspect of post-transcriptional gene regulation. This involves the interplay of intrinsic cis-regulatory elements within the RNA molecules with trans-acting RNA-binding proteins and associated factors. Together, these interactions dictate the intracellular localization route of RNAs, whose downstream impacts have wide-ranging implications in cellular physiology. In this review, we examine the mechanisms underlying RNA localization and discuss their biological significance. We also review the growing body of evidence pointing to aberrant RNA localization pathways in the development and progression of diseases.

Mapping transcriptome-wide protein-RNA interactions to elucidate RNA regulatory programs

BACKGROUND

Our understanding of post-transcriptional gene regulation has increased exponentially with the development of robust methods to define protein-RNA interactions across the transcriptome. In this review, we highlight the evolution and successful applications of crosslinking and immunoprecipitation (CLIP) methods to interrogate protein-RNA interactions in a transcriptome-wide manner.

RESULTS

Here, we survey the vast array of in vitro and in vivo approaches used to identify protein-RNA interactions, including but not limited to electrophoretic mobility shift assays, systematic evolution of ligands by exponential enrichment (SELEX), and RIP-seq. We particularly emphasize the advancement of CLIP technologies, and detail protocol improvements and computational tools used to analyze the output data. Importantly, we discuss how profiling protein-RNA interactions can delineate biological functions including splicing regulation, alternative polyadenylation, cytoplasmic decay substrates, and miRNA targets.

CONCLUSIONS

In summary, this review summarizes the benefits of characterizing RNA-protein networks to further understand the regulation of gene expression and disease pathogenesis. Our review comments on how future CLIP technologies can be adapted to address outstanding questions related to many aspects of RNA metabolism and further advance our understanding of RNA biology.

S-Adenosylmethionine Synthesis Is Regulated by Selective N6-Adenosine Methylation and mRNA Degradation Involving METTL16 and YTHDC1

S-adenosylmethionine (SAM) is an important metabolite as a methyl-group donor in DNA and histone methylation, tuning regulation of gene expression. Appropriate intracellular SAM levels must be maintained, because methyltransferase reaction rates can be limited by SAM availability. In response to SAM depletion, MAT2A, which encodes a ubiquitous mammalian methionine adenosyltransferase isozyme, was upregulated through mRNA stabilization. SAM-depletion reduced N⁶-methyladenosine (m⁶A) in the 3' UTR of MAT2A. In vitro reactions using recombinant METTL16 revealed multiple, conserved methylation targets in the 3' UTR. Knockdown of METTL16 and the m⁶A reader YTHDC1 abolished SAM-responsive regulation of MAT2A. Mutations of the target adenine sites of METTL16 within the 3' UTR revealed that these m⁶As were redundantly required for regulation. MAT2A mRNA methylation by METTL16 is read by YTHDC1, and we suggest that this allows cells to monitor and maintain intracellular SAM levels.

Oncoprotein AEG-1 is an endoplasmic reticulum RNA-binding protein whose interactome is enriched in organelle resident protein-encoding mRNAs

Astrocyte elevated gene-1 (AEG-1), an oncogene whose overexpression promotes tumor cell proliferation, angiogenesis, invasion, and enhanced chemoresistance, is thought to function primarily as a scaffolding protein, regulating PI3K/Akt and Wnt/β-catenin signaling pathways. Here we report that AEG-1 is an endoplasmic reticulum (ER) resident integral membrane RNA-binding protein (RBP). Examination of the AEG-1 RNA interactome by HITS-CLIP and PAR-CLIP methodologies revealed a high enrichment for endomembrane organelle-encoding transcripts, most prominently those encoding ER resident proteins, and within this cohort, for integral membrane protein-encoding RNAs. Cluster mapping of the AEG-1/RNA interaction sites demonstrated a normalized rank order interaction of coding sequence >5' untranslated region, with 3' untranslated region interactions only weakly represented. Intriguingly, AEG-1/membrane protein mRNA interaction sites clustered downstream from encoded transmembrane domains, suggestive of a role in membrane protein biogenesis. Secretory and cytosolic protein-encoding mRNAs were also represented in the AEG-1 RNA interactome, with the latter category notably enriched in genes functioning in mRNA localization, translational regulation, and RNA quality control. Bioinformatic analyses of RNA-binding motifs and predicted secondary structure characteristics indicate that AEG-1 lacks established RNA-binding sites though shares the property of high intrinsic disorder commonly seen in RBPs. These data implicate AEG-1 in the localization and regulation of secretory and membrane protein-encoding mRNAs and provide a framework for understanding AEG-1 function in health and disease.

The lncRNA GATA6-AS epigenetically regulates endothelial gene expression via interaction with LOXL2

Impaired or excessive growth of endothelial cells contributes to several diseases. However, the functional involvement of regulatory long non-coding RNAs in these processes is not well defined. Here, we show that the long non-coding antisense transcript of GATA6 (GATA6-AS) interacts with the epigenetic regulator LOXL2 to regulate endothelial gene expression via changes in histone methylation. Using RNA deep sequencing, we find that GATA6-AS is upregulated in endothelial cells during hypoxia. Silencing of GATA6-AS diminishes TGF-β2-induced endothelial-mesenchymal transition in vitro and promotes formation of blood vessels in mice. We identify LOXL2, known to remove activating H3K4me3 chromatin marks, as a GATA6-AS-associated protein, and reveal a set of angiogenesis-related genes that are inversely regulated by LOXL2 and GATA6-AS silencing. As GATA6-AS silencing reduces H3K4me3 methylation of two of these genes, periostin and cyclooxygenase-2, we conclude that GATA6-AS acts as negative regulator of nuclear LOXL2 function.

A Unique ISR Program Determines Cellular Responses to Chronic Stress

The integrated stress response (ISR) is a homeostatic mechanism induced by endoplasmic reticulum (ER) stress. In acute/transient ER stress, decreased global protein synthesis and increased uORF mRNA translation are followed by normalization of protein synthesis. Here, we report a dramatically different response during chronic ER stress. This chronic ISR program is characterized by persistently elevated uORF mRNA translation and concurrent gene expression reprogramming, which permits simultaneous stress sensing and proteostasis. The program includes PERK-dependent switching to an eIF3-dependent translation initiation mechanism, resulting in partial, but not complete, translational recovery, which, together with transcriptional reprogramming, selectively bolsters expression of proteins with ER functions. Coordination of transcriptional and translational reprogramming prevents ER dysfunction and inhibits "foamy cell" development, thus establishing a molecular basis for understanding human diseases associated with ER dysfunction.

The yeast noncoding RNA interaction network

This article describes the creation of the first expert manually curated noncoding RNA interaction networks for S. cerevisiae The RNA-RNA and RNA-protein interaction networks have been carefully extracted from the experimental literature and made available through the IntAct database (www.ebi.ac.uk/intact). We provide an initial network analysis and compare their properties to the much larger protein-protein interaction network. We find that the proteins that bind to ncRNAs in the network contain only a small proportion of classical RNA binding domains. We also see an enrichment of WD40 domains suggesting their direct involvement in ncRNA interactions. We discuss the challenges in collecting noncoding RNA interaction data and the opportunities for worldwide collaboration to fill the unmet need for this data.

Probing Long Non-coding RNA-Protein Interactions

Non-coding RNA sequences outnumber the protein-coding genes in the human genome, however our knowledge of their functions is still limited. RNA-binding proteins follow the transcripts, including non-coding RNAs, throughout their life, regulating not only maturation, nuclear export, stability and eventually translation, but also RNA functions. Therefore, development of sophisticated methods to study RNA-protein interactions are key to the systematic characterization of lncRNAs. Although mostly applicable to RNA-protein interactions in general, many approaches, especially the computational ones, need adjustment to be adapted to the length and complexity of lncRNA transcripts. Here we critically review all the wet lab and computational methods to study lncRNA-protein interactions and their potential to clarify the dark side of the genome.

Analysis of post-transcriptional regulation during cancer progression using a donor-derived isogenic model of tumorigenesis

Post-transcriptional regulation of gene expression by RNA binding proteins (RBPs) and non-coding RNAs plays an important role in global gene expression. Many post-transcriptional regulators are misexpressed and misregulated in cancers, resulting in altered programs of protein biosynthesis that can drive tumor progression. While comparative studies of several RBPs and microRNAs expressed in various cancer types have been reported, a model system that can be used to quantify RBP regulation and functional outcomes during the initiation and early stages of tumorigenesis is lacking. It was previously demonstrated that oncogenic transformation of normal human cells can be induced by expressing hTERT, p53^DD, cyclin D1, CDK4^R24C, C-MYC^T58A and H-RAS^G12V. Here we describe a user-friendly method for generating this genetically defined model of step-wise tumorigenesis beginning with normal donor-derived human cells. This method immortalizes a donor's normal cells in about a week, reducing the chances of senescence. The entire stable system can be established in less than 12weeks. We then demonstrate the utility of such a system in elucidating the expression of multiple RBPs at an early step of tumor formation. We identify significant changes in the expression levels of transcripts encoding RBPs prior to transformation, suggesting that our described donor-derived isogenic system can provide insight about post-transcriptional regulation during the earliest stages of tumorigenesis in the context of diverse genetic backgrounds.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches.

The Survival of Motor Neuron Protein Acts as a Molecular Chaperone for mRNP Assembly

Spinal muscular atrophy (SMA) is a motor neuron disease caused by reduced levels of the survival of motor neuron (SMN) protein. SMN is part of a multiprotein complex that facilitates the assembly of spliceosomal small nuclear ribonucleoproteins (snRNPs). SMN has also been found to associate with mRNA-binding proteins, but the nature of this association was unknown. Here, we have employed a combination of biochemical and advanced imaging methods to demonstrate that SMN promotes the molecular interaction between IMP1 protein and the 3' UTR zipcode region of β-actin mRNA, leading to assembly of messenger ribonucleoprotein (mRNP) complexes that associate with the cytoskeleton to facilitate trafficking. We have identified defects in mRNP assembly in cells and tissues from SMA disease models and patients that depend on the SMN Tudor domain and explain the observed deficiency in mRNA localization and local translation, providing insight into SMA pathogenesis as a ribonucleoprotein (RNP)-assembly disorder.

Computational Prediction of RNA-Protein Interactions

Experimental methods for identifying protein(s) bound by a specific promoter-associated RNA (paRNA) of interest can be expensive, difficult, and time-consuming. This chapter describes a general computational framework for identifying potential binding partners in RNA-protein complexes or RNA-protein interaction networks. Protocols for using three web-based tools to predict RNA-protein interaction partners are outlined. Also, tables listing additional webservers and software tools for predicting RNA-protein interactions, as well as databases that contain valuable information about known RNA-protein complexes and recognition sites for RNA-binding proteins, are provided. Although only one of the tools described, lncPro, was designed expressly to identify proteins that bind long noncoding RNAs (including paRNAs), all three approaches can be applied to predict potential binding partners for both coding and noncoding RNAs (ncRNAs).

Advances in the characterization of RNA-binding proteins

From transcription, to transport, storage, and translation, RNA depends on association with different RNA-binding proteins (RBPs). Methods based on next-generation sequencing and protein mass-spectrometry have started to unveil genome-wide interactions of RBPs but many aspects still remain out of sight. How many of the binding sites identified in high-throughput screenings are functional? A number of computational methods have been developed to analyze experimental data and to obtain insights into the specificity of protein-RNA interactions. How can theoretical models be exploited to identify RBPs? In addition to oligomeric complexes, protein and RNA molecules can associate into granular assemblies whose physical properties are still poorly understood. What protein features promote granule formation and what effects do these assemblies have on cell function? Here, we describe the newest in silico, in vitro, and in vivo advances in the field of protein-RNA interactions. We also present the challenges that experimental and computational approaches will have to face in future studies. WIREs RNA 2016, 7:793-810. doi: 10.1002/wrna.1378 For further resources related to this article, please visit the WIREs website.

Global profiling of protein complexes: current approaches and their perspective in biomedical research

INTRODUCTION

Despite the rapid evolution of proteomic methods, protein interactions and their participation in protein complexes - an important aspect of their function - has rarely been investigated on the proteome-wide level. Disease states, such as muscular dystrophy or viral infection, are induced by interference in protein-protein interactions within complexes. The purpose of this review is to describe the current methods for global complexome analysis and to critically discuss the challenges and opportunities for the application of these methods in biomedical research. Areas covered: We discuss advancements in experimental techniques and computational tools that facilitate profiling of the complexome. The main focus is on the separation of native protein complexes via size exclusion chromatography and gel electrophoresis, which has recently been combined with quantitative mass spectrometry, for a global protein-complex profiling. The development of this approach has been supported by advanced bioinformatics strategies and fast and sensitive mass spectrometers that have allowed the analysis of whole cell lysates. The application of this technique to biomedical research is assessed, and future directions are anticipated. Expert commentary: The methodology is quite new, and has already shown great potential when combined with complementary methods for detection of protein complexes.

A role for the survival of motor neuron protein in mRNP assembly and transport

Localization and local translation of mRNA plays a key role in neuronal development and function. While studies in various systems have provided insights into molecular mechanisms of mRNA transport and local protein synthesis, the factors that control the assembly of mRNAs and mRNA binding proteins into messenger ribonucleoprotein (mRNP) transport granules remain largely unknown. In this review we will discuss how insights on a motor neuron disease, spinal muscular atrophy (SMA), is advancing our understanding of regulated assembly of transport competent mRNPs and how defects in their assembly and delivery may contribute to the degeneration of motor neurons observed in SMA and other neurological disorders.