Tertiary structure-based analysis of microRNA-target interactions

Omicron Spike Protein Has a Positive Electrostatic Surface That Promotes ACE2 Recognition and Antibody Escape

High transmissibility is a hallmark of the Omicron variant of SARS-CoV-2. Understanding the molecular determinants of Omicron’s transmissibility will impact development of intervention strategies. Here we map the electrostatic potential surface of the Spike protein to show that major SARS-CoV-2 variants have accumulated positive charges in solvent-exposed regions of the Spike protein, especially its ACE2-binding interface. Significantly, the Omicron Spike-ACE2 complex has complementary electrostatic surfaces. In contrast, interfaces between Omicron and neutralizing antibodies tend to have similar positively charged surfaces. Structural modeling demonstrates that the electrostatic property of Omicron’s Spike receptor binding domain (S RBD) plays a role in enhancing ACE2 recognition and destabilizing Spike-antibody complexes. Specifically, the Omicron S RBD has favorable electrostatic interaction energy with ACE2 that is 3-5 times greater than the Delta variant over a range of 20 Å, implying efficient recognition of host receptors. Computed binding affinities of six representative S RBD-antibody complexes show that Omicron can escape most antibodies targeting the ACE2-binding region of S RBD. Interestingly, a straightforward assessment of the electrostatic surfaces of 18 neutralizing antibodies correctly predicted the Omicron escape status of 80% of cases. Collectively, our structural analysis implies that Omicron S RBD interaction interfaces have been optimized to simultaneously promote access to human ACE2 receptors and evade antibodies. These findings suggest that electrostatic interactions are a major contributing factor for increased Omicron transmissibility relative to other variants.

Structural Modeling of the SARS-CoV-2 Spike/Human ACE2 Complex Interface can Identify High-Affinity Variants Associated with Increased Transmissibility

The COVID-19 pandemic has triggered concerns about the emergence of more infectious and pathogenic viral strains. As a public health measure, efficient screening methods are needed to determine the functional effects of new sequence variants. Here we show that structural modeling of SARS-CoV-2 Spike protein binding to the human ACE2 receptor, the first step in host-cell entry, predicts many novel variant combinations with enhanced binding affinities. By focusing on natural variants at the Spike-hACE2 interface and assessing over 700 mutant complexes, our analysis reveals that high-affinity Spike mutations (including N440K, S443A, G476S, E484R, G502P) tend to cluster near known human ACE2 recognition sites (K31 and K353). These Spike regions are structurally flexible, allowing certain mutations to optimize interface interaction energies. Although most human ACE2 variants tend to weaken binding affinity, they can interact with Spike mutations to generate high-affinity double mutant complexes, suggesting variation in individual susceptibility to infection. Applying structural analysis to highly transmissible variants, we find that circulating point mutations S477N, E484K and N501Y form high-affinity complexes (~40% more than wild-type). By combining predicted affinities and available antibody escape data, we show that fast-spreading viral variants exploit combinatorial mutations possessing both enhanced affinity and antibody resistance, including S477N/E484K, E484K/N501Y and K417T/E484K/N501Y. Thus, three-dimensional modeling of the Spike/hACE2 complex predicts changes in structure and binding affinity that correlate with transmissibility and therefore can help inform future intervention strategies.

Novel LOTUS-domain proteins are organizational hubs that recruit C. elegans Vasa to germ granules

We describe MIP-1 and MIP-2, novel paralogous C. elegans germ granule components that interact with the intrinsically disordered MEG-3 protein. These proteins promote P granule condensation, form granules independently of MEG-3 in the postembryonic germ line, and balance each other in regulating P granule growth and localization. MIP-1 and MIP-2 each contain two LOTUS domains and intrinsically disordered regions and form homo- and heterodimers. They bind and anchor the Vasa homolog GLH-1 within P granules and are jointly required for coalescence of MEG-3, GLH-1, and PGL proteins. Animals lacking MIP-1 and MIP-2 show temperature-sensitive embryonic lethality, sterility, and mortal germ lines. Germline phenotypes include defects in stem cell self-renewal, meiotic progression, and gamete differentiation. We propose that these proteins serve as scaffolds and organizing centers for ribonucleoprotein networks within P granules that help recruit and balance essential RNA processing machinery to regulate key developmental transitions in the germ line.

IL1B Increases Intestinal Tight Junction Permeability by Up-regulation of MIR200C-3p, Which Degrades Occludin mRNA

BACKGROUND & AIMS

Defects in the epithelial tight junction (TJ) barrier contribute to development of intestinal inflammation associated with diseases. Interleukin 1 beta (IL1B) increases intestinal permeability in mice. We investigated microRNAs that are regulated by IL1B and their effects on expression of TJ proteins and intestinal permeability.

METHODS

We used Targetscan to identify microRNAs that would bind the 3' untranslated region (3'UTR) of occludin mRNA; regions that interacted with microRNAs were predicted using the V-fold server and Assemble2, and 3-dimensional models were created using UCSF Chimera linked with Assemble2. Caco-2 cells were transfected with vectors that express microRNAs, analyzed by immunoblots and real-time polymerase chain reaction (PCR), and grown as monolayers; permeability in response to IL1B was assessed with the marker inulin. Male C57BL/6 mice were given intraperitoneal injections of IL1B and intestinal recycling perfusion was measured; some mice were given dextran sodium sulfate to induce colitis and/or gavage with an antagonist to MIR200C-3p (antagomiR-200C) or the nonspecific antagomiR (control). Intestinal tissues were collected from mice and analyzed by histology and real-time PCR; enterocytes were isolated by laser capture microdissection. We also analyzed colon tissues and organoids from patients with and without ulcerative colitis.

RESULTS

Incubation of Caco-2 monolayers with IL1B increased TJ permeability and reduced levels of occludin protein and mRNA without affecting the expression of other transmembrane TJ proteins. Targetscan identified MIR122, MIR200B-3p, and MIR200C-3p, as miRNAs that might bind to the occludin 3'UTR. MIR200C-3p was rapidly increased in Caco-2 cells incubated with IL1B; the antagomiR-200c prevented the IL1B-induced decrease in occludin mRNA and protein and reduced TJ permeability. Administration of IL1B to mice increased small intestinal TJ permeability, compared with mice given vehicle; enterocytes isolated from mice given IL1B had increased expression of MIR200C-3p and decreased levels of occludin messenger RNA (mRNA) and protein. Intestinal tissues from mice with colitis had increased levels of IL1B mRNA and MIR200C-3p and decreased levels of occludin mRNA; gavage of mice with antagomiR-200C reduced levels of MIR200C-3p and prevented the decrease in occludin mRNA and the increase in colonic permeability. Colon tissues and organoids from patients with ulcerative colitis had increased levels of IL1B mRNA and MIR200C-3p compared with healthy controls. Using 3-dimensional molecular modeling and mutational analyses, we identified the nucleotide bases in the occluding mRNA 3'UTR that interact with MIR200C-3p.

CONCLUSIONS

Intestine tissues from patients with ulcerative colitis and mice with colitis have increased levels of IL1B mRNA and MIR200C-3p, which reduces expression of occludin by enterocytes and thereby increases TJ permeability. Three-dimensional modeling of the interaction between MIR200C-3p and the occludin mRNA 3'UTR identified sites of interaction. The antagomiR-200C prevents the decrease in occludin in enterocytes and intestine tissues of mice with colitis, maintaining the TJ barrier.

miRNA target identification and prediction as a function of time in gene expression data

The understanding of miRNA target interactions is still limited due to conflicting data and the fact that high-quality validation of targets is a time-consuming process. Faster methods like high-throughput screens and bioinformatics predictions are employed but suffer from several problems. One of these, namely the potential occurrence of downstream (i.e. secondary) effects in high-throughput screens has been only little discussed so far. However, such effects limit usage for both the identification of interactions and for the training of bioinformatics tools. In order to analyse this problem more closely, we performed time-dependent microarray screening experiments overexpressing human miR-517a-3p, and, together with published time-dependent datasets of human miR-17-5p, miR-135b and miR-124 overexpression, we analysed the dynamics of deregulated genes. We show that the number of deregulated targets increases over time, whereas seed sequence content and performance of several miRNA target prediction algorithms actually decrease over time. Bioinformatics recognition success of validated miR-17 targets was comparable to that of data gained only 12 h post-transfection. We therefore argue that the timing of microarray experiments is of critical importance for detecting direct targets with high confidence and for the usability of these data for the training of bioinformatics prediction tools.

Effects of the PIWI/MID domain of Argonaute protein on the association of miRNAi's seed base with the target

The small interfering RNAs (siRNA) or microRNAs (miRNA) incorporated into the RNA-induced silencing complex with the Argonaute (Ago) protein associates with target mRNAs through base-pairing, which leads to the cleavage or knockdown of the target mRNA. The seed region of the s(m)iRNA is crucial for target recognition. In this work, a molecular dynamic simulation was utilized to study the thermodynamics and kinetic properties of the third seed base binding to the target in the presence of the PIWI/MID domain of Ago. The results showed that in the presence of the PIWI/MID domain, the entropy and enthalpy changes for the association of the seed base with the target were smaller than those in the absence of protein. The binding affinity was increased due to the reduced entropy penalty, which resulted from the preorganization of the seed base into the A-helix form. In the presence of the protein, the association barrier resulting from the unfavorable entropy loss and the dissociation barrier coming from the destruction of hydrogen bonding and base-stacking interactions were lower than those in the absence of the protein. These results indicate that the seed region is crucial for fast recognition and association with the correct target.

The Role of Tertiary Structure in MicroRNA Target Recognition

Translational repression and degradation of transcripts by microRNAs (miRNAs) is mediated by a ribonucleoprotein complex called the miRNA-induced silencing complex (miRISC, or RISC). Advances in experimental determination of RISC structures have enabled detailed analysis and modeling of known miRNA targets, yet a full appreciation of the structural factors influencing target recognition remains a challenge, primarily because target recognition involves a combination of RNA-RNA and RNA-protein interactions that can vary greatly among different miRNA-target pairs. In this chapter, we review progress toward understanding the role of tertiary structure in miRNA target recognition using computational approaches to assemble RISC complexes at known targets and physics-based methods for computing target interactions. Using this framework to examine RISC structures and dynamics, we describe how the conformational flexibility of Argonautes plays an important role in accommodating the diversity of miRNA-target duplexes formed at canonical and noncanonical target sites. We then discuss applications of tertiary structure-based approaches to emerging topics, including the structural effects of SNPs in miRNA targets and cooperative interactions involving Argonaute-Argonaute complexes. We conclude by assessing the prospects for genome-scale modeling of RISC structures and modeling of higher-order Argonaute complexes associated with miRNA biogenesis, mRNA regulation, and other functions.

Recent Molecular Genetic Explorations of Caenorhabditis elegans MicroRNAs

MicroRNAs are small, noncoding RNAs that regulate gene expression at the post-transcriptional level in essentially all aspects of Caenorhabditis elegans biology. More than 140 genes that encode microRNAs in C. elegans regulate development, behavior, metabolism, and responses to physiological and environmental changes. Genetic analysis of C. elegans microRNA genes continues to enhance our fundamental understanding of how microRNAs are integrated into broader gene regulatory networks to control diverse biological processes, including growth, cell division, cell fate determination, behavior, longevity, and stress responses. As many of these microRNA sequences and the related processing machinery are conserved over nearly a billion years of animal phylogeny, the assignment of their functions via worm genetics may inform the functions of their orthologs in other animals, including humans. In vivo investigations are especially important for microRNAs because in silico extrapolation of their functions using mRNA target prediction programs can easily assign microRNAs to incorrect genetic pathways. At this mezzanine level of microRNA bioinformatic sophistication, genetic analysis continues to be the gold standard for pathway assignments.

A non-canonical site reveals the cooperative mechanisms of microRNA-mediated silencing

Although strong evidence supports the importance of their cooperative interactions, microRNA (miRNA)-binding sites are still largely investigated as functionally independent regulatory units. Here, a survey of alternative 3΄UTR isoforms implicates a non-canonical seedless site in cooperative miRNA-mediated silencing. While required for target mRNA deadenylation and silencing, this site is not sufficient on its own to physically recruit miRISC. Instead, it relies on facilitating interactions with a nearby canonical seed-pairing site to recruit the Argonaute complexes. We further show that cooperation between miRNA target sites is necessary for silencing in vivo in the C. elegans embryo, and for the recruitment of the Ccr4-Not effector complex. Using a structural model of cooperating miRISCs, we identified allosteric determinants of cooperative miRNA-mediated silencing that are required for both embryonic and larval miRNA functions. Our results delineate multiple cooperative mechanisms in miRNA-mediated silencing and further support the consideration of target site cooperation as a fundamental characteristic of miRNA function.

TargetLink, a new method for identifying the endogenous target set of a specific microRNA in intact living cells

MicroRNAs are small non-coding RNAs acting as posttranscriptional repressors of gene expression. Identifying mRNA targets of a given miRNA remains an outstanding challenge in the field. We have developed a new experimental approach, TargetLink, that applied locked nucleic acid (LNA) as the affinity probe to enrich target genes of a specific microRNA in intact cells. TargetLink also consists a rigorous and systematic data analysis pipeline to identify target genes by comparing LNA-enriched sequences between experimental and control samples. Using miR-21 as a test microRNA, we identified 12 target genes of miR-21 in a human colorectal cancer cell by this approach. The majority of the identified targets interacted with miR-21 via imperfect seed pairing. Target validation confirmed that miR-21 repressed the expression of the identified targets. The cellular abundance of the identified miR-21 target transcripts varied over a wide range, with some targets expressed at a rather low level, confirming that both abundant and rare transcripts are susceptible to regulation by microRNAs, and that TargetLink is an efficient approach for identifying the target set of a specific microRNA in intact cells. C20orf111, one of the novel targets identified by TargetLink, was found to reside in the nuclear speckle and to be reliably repressed by miR-21 through the interaction at its coding sequence.

A structural view of microRNA-target recognition

It is well established that the correct identification of the messenger RNA targeted by a given microRNA (miRNA) is a difficult problem, and that available methods all suffer from low specificity. We hypothesize that the correct identification of the pairing should take into account the effect of the Argonaute protein (AGO), an essential catalyst of the recognition process. Therefore, we developed a strategy named MiREN for building and scoring three-dimensional models of the ternary complex formed by AGO, a miRNA and 22 nt of a target mRNA that putatively interacts with it. We show here that MiREN can be used to assess the likelihood that an RNA molecule is the target of a given miRNA and that this approach is more accurate than other existing methods, usually based on sequence or sequence-related features. Our results also suggest that AGO plays a relevant role in the selection of the miRNA targets. Our method can represent an additional step for refining predictions made by faster but less accurate classical methods for the identification of miRNA targets.

Modeling of Protein-RNA Complex Structures Using Computational Docking Methods

A significant part of biology involves the formation of RNA-protein complexes. X-ray crystallography has added a few solved RNA-protein complexes to the repertoire; however, it remains challenging to capture these complexes and often only the unbound structures are available. This has inspired a growing interest in finding ways to predict these RNA-protein complexes. In this study, we show ways to approach this problem by computational docking methods, either with a fully automated NPDock server or with a workflow of methods for generation of many alternative structures followed by selection of the most likely solution. We show that by introducing experimental information, the structure of the bound complex is rendered far more likely to be within reach. This study is meant to help the user of docking software understand how to grapple with a typical realistic problem in RNA-protein docking, understand what to expect in the way of difficulties, and recognize the current limitations.

Assembly and analysis of eukaryotic Argonaute-RNA complexes in microRNA-target recognition

Experimental studies have uncovered a variety of microRNA (miRNA)–target duplex structures that include perfect, imperfect and seedless duplexes. However, non-canonical binding modes from imperfect/seedless duplexes are not well predicted by computational approaches, which rely primarily on sequence and secondary structural features, nor have their tertiary structures been characterized because solved structures to date are limited to near perfect, straight duplexes in Argonautes (Agos). Here, we use structural modeling to examine the role of Ago dynamics in assembling viable eukaryotic miRNA-induced silencing complexes (miRISCs). We show that combinations of low-frequency, global modes of motion of Ago domains are required to accommodate RNA duplexes in model human and C. elegans Ago structures. Models of viable miRISCs imply that Ago adopts variable conformations at distinct target sites that generate distorted, imperfect miRNA-target duplexes. Ago's ability to accommodate a duplex is dependent on the region where structural distortions occur: distortions in solvent-exposed seed and 3′-end regions are less likely to produce steric clashes than those in the central duplex region. Energetic analyses of assembled miRISCs indicate that target recognition is also driven by favorable Ago-duplex interactions. Such structural insights into Ago loading and target recognition mechanisms may provide a more accurate assessment of miRNA function.

Computational Prediction of microRNA Targets

Computational prediction of microRNA (miRNA) targets is a fundamental step towards the characterization of miRNA function and the understanding of their role in disease. A single miRNA can regulate hundreds of different gene transcripts through partial sequence complementarity and a single gene may be regulated by several miRNAs acting cooperatively. The remarkable advances made in recent years have allowed the identification of key features for functional miRNA binding sites. A plethora of prediction tools are now available, but their accuracies remain rather poor, as miRNA target recognition has revealed itself to be a very complex and dynamic mechanism, still only partially understood.In this chapter, the principles of miRNA target prediction in animals are presented, together with the most up-to-date and effective computational approaches and tools available.

Mature miRNAs form secondary structure, which suggests their function beyond RISC

The generally accepted model of the miRNA-guided RNA down-regulation suggests that mature miRNA targets mRNA in a nucleotide sequence-specific manner. However, we have shown that the nucleotide sequence of miRNA is not the only determinant of miRNA specificity. Using specific nucleases, T1, V1 and S1 as well as NMR, UV/Vis and CD spectroscopies, we found that miR-21, miR-93 and miR-296 can adopt hairpin and/or homoduplex structures. The secondary structure of those miRNAs in solution is a function of RNA concentration and ionic conditions. Additionally, we have shown that a formation of miRNA hairpin is facilitated by cellular environment.Looking for functional consequences of this observation, we have perceived that structure of these miRNAs resemble RNA aptamers, short oligonucleotides forming a stable 3D structures with a high affinity and specificity for their targets. We compared structures of anti-tenascin C (anti-Tn-C) aptamers, which inhibit brain tumor glioblastoma multiforme (GBM, WHO IV) and selected miRNA. A strong overexpression of miR-21, miR-93 as well Tn-C in GBM may imply some connections between them. The structural similarity of these miRNA hairpins and anti-Tn-C aptamers indicates that miRNAs may function also beyond RISC and are even more sophisticated regulators, that it was previously expected. We think that the knowledge of the miRNA structure may give a new insight into miRNA-dependent gene regulation mechanism and be a step forward in the understanding their function and involvement in cancerogenesis. This may improve design process of anti-miRNA therapeutics.

Cooperative gene regulation by microRNA pairs and their identification using a computational workflow

MicroRNAs (miRNAs) are an integral part of gene regulation at the post-transcriptional level. Recently, it has been shown that pairs of miRNAs can repress the translation of a target mRNA in a cooperative manner, which leads to an enhanced effectiveness and specificity in target repression. However, it remains unclear which miRNA pairs can synergize and which genes are target of cooperative miRNA regulation. In this paper, we present a computational workflow for the prediction and analysis of cooperating miRNAs and their mutual target genes, which we refer to as RNA triplexes. The workflow integrates methods of miRNA target prediction; triplex structure analysis; molecular dynamics simulations and mathematical modeling for a reliable prediction of functional RNA triplexes and target repression efficiency. In a case study we analyzed the human genome and identified several thousand targets of cooperative gene regulation. Our results suggest that miRNA cooperativity is a frequent mechanism for an enhanced target repression by pairs of miRNAs facilitating distinctive and fine-tuned target gene expression patterns. Human RNA triplexes predicted and characterized in this study are organized in a web resource at www.sbi.uni-rostock.de/triplexrna/.