RNA-binding proteins are crucial to the function of coding and non-coding RNAs. The disruption of RNA–protein interactions is involved in many different pathological states. Several computational and experimental strategies have been developed to identify protein binders of selected RNA molecules. Amongst these, ‘in cell’ hybridization methods represent the gold standard in the field because they are designed to reveal the proteins bound to specific RNAs in a cellular context. Here, we compare the technical features of different ‘in cell’ hybridization approaches with a focus on their advantages, limitations, and current and potential future applications.
Methods to spatially profile the transcriptome are dominated by a trade-off between resolution and throughput. Here, we developed a method named EEL FISH that can rapidly process large tissue samples without compromising spatial resolution. By electrophoretically transferring RNA from a tissue section onto a capture surface, EEL speeds up data acquisition by reducing the amount of imaging needed, while ensuring that RNA molecules move straight down towards the surface, preserving single-cell resolution. We applied EEL on eight entire sagittal sections of the mouse brain and measured the expression patterns of up to 440 genes to reveal complex tissue organisation. Moreover, EEL enabled the study of challenging human samples by removing autofluorescent lipofuscin, so that we could study the spatial transcriptome of the human visual cortex. We provide full hardware specification, all protocols and complete software for instrument control, image processing, data analysis and visualization.
G•U wobble base pair frequently occurs in RNA structures. The unique chemical, thermodynamic, and structural properties of the G•U pair are widely exploited in RNA biology. In several RNA molecules, the G•U pair plays key roles in folding, ribozyme catalysis, and interactions with proteins. G•U may occur as a single pair or in tandem motifs with different geometries, electrostatics, and thermodynamics, further extending its biological functions. The metal binding affinity, which is essential for RNA folding, catalysis, and other interactions, differs with respect to the tandem motif type due to the different electrostatic potentials of the major grooves. In this work, we present the crystal structure of an RNA 8-mer duplex r[UCGUGCGA]2, providing detailed structural insights into the tandem motif I (5′UG/3′GU) complexed with Ba2+ cation. We compare the electrostatic potential of the presented motif I major groove with previously published structures of tandem motifs I, II (5′GU/3′UG), and III (5′GG/3′UU). A local patch of a strongly negative electrostatic potential in the major groove of the presented structure forms the metal binding site with the contributions of three oxygen atoms from the tandem. These results give us a better understanding of the G•U tandem motif I as a divalent metal binder, a feature essential for RNA functions.
The interior of the eukaryotic cell nucleus has a crowded and heterogeneous environment packed with chromatin polymers, regulatory proteins, and RNA molecules. Chromatin polymer, assisted by epigenetic modifications, protein and RNA binders, forms multi-scale compartments which help regulate genes in response to cellular signals. Furthermore, chromatin compartments are dynamic and tend to evolve in size and composition in ways that are not fully understood. The latest super-resolution imaging experiments have revealed a much more dynamic and stochastic nature of chromatin compartments than was appreciated before. An emerging mechanism explaining chromatin compartmentalization dynamics is the phase separation of protein and nucleic acids into membraneless liquid condensates. Consequently, concepts and ideas from soft matter and polymer systems have been rapidly entering the lexicon of cell biology. In this respect, the role of computational models is crucial for establishing a rigorous and quantitative foundation for the new concepts and disentangling the complex interplay of forces that contribute to the emergent patterns of chromatin dynamics and organization. Several multi-scale models have emerged to address various aspects of chromatin dynamics, ranging from equilibrium polymer simulations, hybrid non-equilibrium simulations coupling protein binding and chromatin folding, and mesoscopic field-theoretic models. Here, we review these emerging theoretical paradigms and computational models with a particular focus on chromatin’s phase separation and liquid-like properties as a basis for nuclear organization and dynamics.
Methylation is one of the most common and considerable modifications in biological systems mediated by multiple enzymes. Recent studies have shown that methylation has been widely identified in different RNA molecules. RNA methylation modifications have various kinds, such as 5-methylcytosine (m5C). However, for individual methylation sites, their functions still remain to be elucidated. Testing of all methylation sites relies heavily on high-throughput sequencing technology, which is expensive and labor consuming. Thus, computational prediction approaches could serve as a substitute. In this study, multiple machine learning models were used to predict possible RNA m5C sites on the basis of mRNA sequences in human and mouse. Each site was represented by several features derived from
-mers of an RNA subsequence containing such site as center. The powerful max-relevance and min-redundancy (mRMR) feature selection method was employed to analyse these features. The outcome feature list was fed into incremental feature selection method, incorporating four classification algorithms, to build efficient models. Furthermore, the sites related to features used in the models were also investigated.
The development of new sequencing technologies in the post-genomic era has accelerated the identification of causative mutations of several single gene disorders. Advances in cell and animal models provide insights into the underlining pathogenesis, which facilitates the development and maturation of new treatment strategies. The progress in biochemistry and molecular biology has established a new class of therapeutics—the short RNAs and expressible long RNAs. The sequences of therapeutic RNAs can be optimized to enhance their stability and translatability with reduced immunogenicity. The chemically-modified RNAs can also increase their stability during intracellular trafficking. In addition, the development of safe and high efficiency carriers that preserves the integrity of therapeutic RNA molecules also accelerates the transition of RNA therapeutics into the clinic. For example, for diseases that are caused by genetic defects in a specific protein, an effective approach termed “protein replacement therapy” can provide treatment through the delivery of modified translatable mRNAs. Short interference RNAs can also be used to treat diseases caused by gain of function mutations or restore the splicing aberration defects. Here we review the applications of newly developed RNA-based therapeutics and its delivery and discuss the clinical evidence supporting the potential of RNA-based therapy in single-gene neurological disorders.
Viroids are a unique class of plant pathogens that consist of small circular RNA molecules, between 220 and 450 nucleotides in size. Viroids encode no proteins and are the smallest known infectious agents. Viroids replicate via the rolling circle mechanism, producing multimeric intermediates which are cleaved to unit length either by ribozymes formed from both polarities of the viroid genomic RNA or by coopted host RNAses. Many viroid-like small circular RNAs are satellites of plant RNA viruses. Ribozyviruses, represented by human hepatitis delta virus, are larger viroid-like circular RNAs that additionally encode the viral nucleocapsid protein. It has been proposed that viroids are direct descendants of primordial RNA replicons that were present in the hypothetical RNA world. We argue, however, that much later origin of viroids, possibly, from recently discovered mobile genetic elements known as retrozymes, is a far more parsimonious evolutionary scenario. Nevertheless, viroids and viroid-like circular RNAs are minimal replicators that are likely to be close to the theoretical lower limit of replicator size and arguably comprise the paradigm for replicator emergence. Thus, although viroid-like replicators are unlikely to be direct descendants of primordial RNA replicators, the study of the diversity and evolution of these ultimate genetic parasites can yield insights into the earliest stages of the evolution of life.
AbstractGenome editing technologies introduce targeted chromosomal modifications in organisms yet are constrained by the inability to selectively modify repetitive genetic elements. Here we describe filtered editing, a genome editing method that embeds group 1 self-splicing introns into repetitive genetic elements to construct unique genetic addresses that can be selectively modified. We introduce intron-containing ribosomes into the E. coli genome and perform targeted modifications of these ribosomes using CRISPR/Cas9 and multiplex automated genome engineering. Self-splicing of introns post-transcription yields scarless RNA molecules, generating a complex library of targeted combinatorial variants. We use filtered editing to co-evolve the 16S rRNA to tune the ribosome’s translational efficiency and the 23S rRNA to isolate antibiotic-resistant ribosome variants without interfering with native translation. This work sets the stage to engineer mutant ribosomes that polymerize abiological monomers with diverse chemistries and expands the scope of genome engineering for precise editing and evolution of repetitive DNA sequences.
The application of CRISPR/Cas9 technology in human induced pluripotent stem cells (hiPSC) holds tremendous potential for basic research and cell-based gene therapy. However, the fulfillment of these promises relies on the capacity to efficiently deliver exogenous nucleic acids and harness the repair mechanisms induced by the nuclease activity in order to knock-out or repair targeted genes. Moreover, transient delivery should be preferred to avoid persistent nuclease activity and to decrease the risk of off-target events. We recently developed bacteriophage-chimeric retrovirus-like particles that exploit the properties of bacteriophage coat proteins to package exogenous RNA, and the benefits of lentiviral transduction to achieve highly efficient, non-integrative RNA delivery in human cells. Here, we investigated the potential of bacteriophage-chimeric retrovirus-like particles for the non-integrative delivery of RNA molecules in hiPSC for CRISPR/Cas9 applications.
We found that these particles efficiently convey RNA molecules for transient expression in hiPSC, with minimal toxicity and without affecting the cell pluripotency and subsequent differentiation. We then used this system to transiently deliver in a single step the CRISPR-Cas9 components (Cas9 mRNA and sgRNA) to generate gene knockout with high indel rate (up to 85%) at multiple loci. Strikingly, when using an allele-specific sgRNA at a locus harboring compound heterozygous mutations, the targeted allele was not altered by NHEJ/MMEJ, but was repaired at high frequency using the homologous wild type allele, i.e., by interallelic gene conversion.
Our results highlight the potential of bacteriophage-chimeric retrovirus-like particles to efficiently and safely deliver RNA molecules in hiPSC, and describe for the first time genome engineering by gene conversion in hiPSC. Harnessing this DNA repair mechanism could facilitate the therapeutic correction of human genetic disorders in hiPSC.