Defective Ribonucleoproteins, Mistakes in RNA Processing, and Diseases

Cryptic splicing events result in unexpected protein products from calpain-10 (CAPN10) cDNA

Calpain-10 (CAPN10) belongs to the calpain superfamily. Genetic polymorphisms of the CAPN10 gene are associated with susceptibility to develop type 2 diabetes mellitus. Although the role of CAPN10 in the pathophysiology of diabetes has been extensively investigated, its biochemical properties are largely unknown. In this report, we made the surprising discovery that CAPN10 cDNA transcripts are subject to cryptic splicing and unexpected protein products were expressed. The same set of splicing products was reproducibly detected in four types of cultured cells including the primary culture of mouse myoblast. At least, one of the products was identical to a natural splicing variant. Sequence analysis of the splicing potential of CAPN10 cDNA, together with mutagenesis studies, resulted in the identification of a powerful splicing acceptor site at the junction of the sequences encoded by exons 9 and 10. We successfully extended the analysis to create expression construct resistant to splicing for both human and mouse CAPN10. The construct allowed us to analyze two major CAPN10 isoforms and reveal their difference in substrate proteolysis and potential cell functions. These results demonstrate that proteins produced from cDNA do not necessarily reflect the original nucleotide sequence. We provide insight into the property of recombinantly expressed CAPN10 proteins in cultured cells circumventing unexpected protein products.

A comparative analysis of machine learning classifiers for predicting protein-binding nucleotides in RNA sequences

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RNA are master players in various cellular and biological processes and RNA-protein interactions are vital for proper functioning of cellular machineries.

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Knowledge of binding sites is crucial to decipher their functional implications.

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RNA NC-triplet and NC-quartet features could give reasonably high performance.

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RF model outperformed other machine learning classifiers with 85% accuracy and 0.93 AUC and performed better than few existing methods.

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An online webserver “Nucpred” is developed with trained model and freely accessible for scientific community.

RNA-protein interactions play vital roles in driving the cellular machineries. Despite significant involvement in several biological processes, the underlying molecular mechanism of RNA-protein interactions is still elusive. This may be due to the experimental difficulties in solving co-crystallized RNA-protein complexes. Inherent flexibility of RNA molecules to adopt different conformations makes them functionally diverse. Their interactions with protein have implications in RNA disease biology. Thus, study of binding interfaces can provide a mechanistic insight of the molecular functioning and aberrations caused due to altered interactions. Moreover, high-throughput sequencing technologies have generated huge sequence data compared to available structural data of RNA-protein complexes. In such a scenario, efficient computational algorithms are required for identification of protein-binding interfaces of RNA in the absence of known structures. We have investigated several machine learning classifiers and various features derived from nucleotide sequences to identify protein-binding nucleotides in RNA. We achieve best performance with nucleotide-triplet and nucleotide-quartet feature-based random forest models. An overall accuracy of 84.8%, sensitivity of 83.2%, specificity of 86.1%, MCC of 0.70 and AUC of 0.93 is achieved. We have further implemented the developed models in a user-friendly webserver “Nucpred”, which is freely accessible at “http://www.csb.iitkgp.ac.in/applications/Nucpred/index”.

Endogenous microRNA triggered enzyme-free DNA logic self-assembly for amplified bioimaging and enhanced gene therapy via in situ generation of siRNAs

BACKGROUND

Small interfering RNA (siRNA) has emerged as a kind of promising therapeutic agents for cancer therapy. However, the off-target effect and degradation are the main challenges for siRNAs delivery. Herein, an enzyme-free DNA amplification strategy initiated by a specific endogenous microRNA has been developed for in situ generation of siRNAs with enhanced gene therapy effect on cervical carcinoma.

METHODS

This strategy contains three DNA hairpins (H1, H2/PS and H3) which can be triggered by microRNA-21 (miR-21) for self-assembly of DNA nanowheels (DNWs). Notably, this system is consistent with the operation of a DNA logic circuitry containing cascaded "AND" gates with feedback mechanism. Accordingly, a versatile biosensing and bioimaging platform is fabricated for sensitive and specific analysis of miR-21 in HeLa cells via fluorescence resonance energy transfer (FRET). Meanwhile, since the vascular endothelial growth factor (VEGF) antisense and sense sequences are encoded in hairpin reactants, the performance of this DNA circuit leads to in situ assembly of VEGF siRNAs in DNWs, which can be specifically recognized and cleaved by Dicer for gene therapy of cervical carcinoma.

RESULTS

The proposed isothermal amplification approach exhibits high sensitivity for miR-21 with a detection limit of 0.25 pM and indicates excellent specificity to discriminate target miR-21 from the single-base mismatched sequence. Furthermore, this strategy achieves accurate and sensitive imaging analysis of the expression and distribution of miR-21 in different living cells. To note, compared to naked siRNAs alone, in situ siRNA generation shows a significantly enhanced gene silencing and anti-tumor effect due to the high reaction efficiency of DNA circuit and improved delivery stability of siRNAs.

CONCLUSIONS

The endogenous miRNA-activated DNA circuit provides an exciting opportunity to construct a general nanoplatform for precise cancer diagnosis and efficient gene therapy, which has an important significance in clinical translation.

RNA oxidation in chromatin modification and DNA-damage response following exposure to formaldehyde

Formaldehyde is an environmental and occupational chemical carcinogen implicated in the damage of proteins and nucleic acids. However, whether formaldehyde provokes modifications of RNAs such as 8-oxo-7,8-dihydroguanine (8-oxoG) and the role that these modifications play on conferring long-term adverse health effects remains unexplored. Here, we profile 8-oxoG modifications using RNA-immunoprecipitation and RNA sequencing (8-oxoG RIP-seq) to identify 343 RNA transcripts heavily enriched in oxidations in human bronchial epithelial BEAS-2B cell cultures exposed to 1 ppm formaldehyde for 2 h. RNA oxidation altered expression of many transcripts involved in chromatin modification and p53-mediated DNA-damage responses, two pathways that play key roles in sustaining genome integrity and typically deregulated in tumorigenesis. Given that these observations were identified in normal cells exhibiting minimal cell stress and death phenotypes (for example, lack of nuclear shrinkage, F-actin alterations or increased LDH activity); we hypothesize that oxidative modification of specific RNA transcripts following formaldehyde exposure denotes an early process occurring in carcinogenesis analogous to the oxidative events surfacing at early stages of neurodegenerative diseases. As such, we provide initial investigations of RNA oxidation as a potentially novel mechanism underlying formaldehyde-induced tumorigenesis.

Post-transcriptional air pollution oxidation to the cholesterol biosynthesis pathway promotes pulmonary stress phenotypes

The impact of environmentally-induced chemical changes in RNA has been fairly unexplored. Air pollution induces oxidative modifications such as 8-oxo-7,8-dihydroguanine (8-oxoG) in RNAs of lung cells, which could be associated with premature lung dysfunction. We develop a method for 8-oxoG profiling using immunocapturing and RNA sequencing. We find 42 oxidized transcripts in bronchial epithelial BEAS-2B cells exposed to two air pollution mixtures that recreate urban atmospheres. We show that the FDFT1 transcript in the cholesterol biosynthesis pathway is susceptible to air pollution-induced oxidation. This process leads to decreased transcript and protein expression of FDFT1, and reduced cholesterol synthesis in cells exposed to air pollution. Knockdown of FDFT1 replicates alterations seen in air pollution exposure such as transformed cell size and suppressed cytoskeleton organization. Our results argue of a possible novel biomarker and of an unseen mechanism by which air pollution selectively modifies key metabolic-related transcripts facilitating cell phenotypes in bronchial dysfunction.

Gonzales-Rivera et al. develop a method for 8-oxoG profiling using immunocapturing and RNA sequencing. They show that the FDFT1 transcript is susceptible to air pollution-induced oxidation, after identifying 42 transcripts that are differentially oxidized in bronchial epithelial BEAS-2B cells under air pollution conditions relative to clean air. FDFT1 oxidation affects cholesterol synthesis pathway, leading to phenotypes associated with several lung diseases.

Computational evolution of an RNA-binding protein towards enhanced oxidized-RNA binding

The oxidation of RNA has been implicated in the development of many diseases. Among the four ribonucleotides, guanosine is the most susceptible to oxidation, resulting in the formation of 8-oxo-7,8-dihydroguanosine (8-oxoG). Despite the limited knowledge about how cells regulate the detrimental effects of oxidized RNA, cellular factors involved in its regulation have begun to be identified. One of these factors is polynucleotide phosphorylase (PNPase), a multifunctional enzyme implicated in RNA turnover. In the present study, we have examined the interaction of PNPase with 8-oxoG in atomic detail to provide insights into the mechanism of 8-oxoG discrimination. We hypothesized that PNPase subunits cooperate to form a binding site using the dynamic SFF loop within the central channel of the PNPase homotrimer. We evolved this site using a novel approach that initially screened mutants from a library of beneficial mutations and assessed their interactions using multi-nanosecond Molecular Dynamics simulations. We found that evolving this single site resulted in a fold change increase in 8-oxoG affinity between 1.2 and 1.5 and/or selectivity between 1.5 and 1.9. In addition to the improvement in 8-oxoG binding, complementation of K12 Δpnp with plasmids expressing mutant PNPases caused increased cell tolerance to H₂O₂. This observation provides a clear link between molecular discrimination of RNA oxidation and cell survival. Moreover, this study provides a framework for the manipulation of modified-RNA protein readers, which has potential application in synthetic biology and epitranscriptomics.

Computational approaches in design of nucleic acid-based therapeutics

Recent advances in computational and experimental methods have led to novel avenues for therapeutic development. Utilization of nucleic acids as therapeutic agents and/or targets has been recently gaining attention due to their potential as high-affinity, selective molecular building blocks for various therapies. Notably, development of computational algorithms for predicting accessible RNA binding sites, identifying therapeutic target sequences, modeling delivery into tissues, and designing binding aptamers have enhanced therapeutic potential for this new drug category. Here, we review trends in drug development within the pharmaceutical industry and ways by which nucleic acid-based drugs have arisen as effective therapeutic candidates. In particular, we focus on computational and experimental approaches to nucleic acid-based drug design, commenting on challenges and outlooks for future applications.