Incautious design of shRNAs for stable overexpression of miRNAs could result in generation of undesired isomiRs.

shRNA-mediated strategy of miRNA overexpression based on RNA Polymerase III (Pol III) expression cassettes is widely used for miRNA functional studies. For some miRNAs, e.g., encoded in the genome as a part of a polycistronic miRNA cluster, it is most likely the only way for their individual stable overexpression. Here we have revealed that expression of miRNAs longer than 19 nt (e.g. 23 nt in length hsa-miR-93-5p) using such approach could be accompanied by undesired predominant generation of 5' end miRNA isoforms (5'-isomiRs). Extra U residues (up to five) added by Pol III at the 3' end of the transcribed shRNA during transcription termination could cause a shift in the Dicer cleavage position of the shRNA. This results in the formation of 5'-isomiRs, which have a significantly altered seed region compared to the initially encoded canonical hsa-miR-93-5p. We demonstrated that the commonly used qPCR method is insensitive to the formation of 5'-isomiRs and cannot be used to confirm miRNA overexpression. However, the predominant expression of 5'-isomiRs without three or four first nucleotides instead of the canonical isoform could be disclosed based on miRNA-Seq analysis. Moreover, mRNA sequencing data showed that the 5'-isomiRs of hsa-miR-93-5p presumably regulate their own mRNA targets. Thus, omitting miRNA-Seq analysis may lead to erroneous conclusions regarding revealed mRNA targets and possible molecular mechanisms in which studied miRNA is involved. Overall, the presented results show that structures of shRNAs for stable overexpression of miRNAs requires careful design to avoid generation of undesired 5'-isomiRs.

DiCleave: a deep learning model for predicting human Dicer cleavage sites.

BACKGROUND: MicroRNAs (miRNAs) are a class of non-coding RNAs that play a pivotal role as gene expression regulators. These miRNAs are typically approximately 20 to 25 nucleotides long. The maturation of miRNAs requires Dicer cleavage at specific sites within the precursor miRNAs (pre-miRNAs). Recent advances in machine learning-based approaches for cleavage site prediction, such as PHDcleav and LBSizeCleav, have been reported. ReCGBM, a gradient boosting-based model, demonstrates superior performance compared with existing methods. Nonetheless, ReCGBM operates solely as a binary classifier despite the presence of two cleavage sites in a typical pre-miRNA. Previous approaches have focused on utilizing only a fraction of the structural information in pre-miRNAs, often overlooking comprehensive secondary structure information. There is a compelling need for the development of a novel model to address these limitations. RESULTS: In this study, we developed a deep learning model for predicting the presence of a Dicer cleavage site within a pre-miRNA segment. This model was enhanced by an autoencoder that learned the secondary structure embeddings of pre-miRNA. Benchmarking experiments demonstrated that the performance of our model was comparable to that of ReCGBM in the binary classification tasks. In addition, our model excelled in multi-class classification tasks, making it a more versatile and practical solution than ReCGBM. CONCLUSIONS: Our proposed model exhibited superior performance compared with the current state-of-the-art model, underscoring the effectiveness of a deep learning approach in predicting Dicer cleavage sites. Furthermore, our model could be trained using only sequence and secondary structure information. Its capacity to accommodate multi-class classification tasks has enhanced the practical utility of our model.

Substrate promiscuity of Dicer toward precursors of the let-7 family and their 3'-end modifications.

The human let-7 miRNA family consists of thirteen members that play critical roles in many biological processes, including development timing and tumor suppression, and their levels are disrupted in several diseases. Dicer is the endoribonuclease responsible for processing the precursor miRNA (pre-miRNA) to yield the mature miRNA, and thereby plays a crucial role in controlling the cellular levels of let-7 miRNAs. It is well established that the sequence and structural features of pre-miRNA hairpins such as the 5'-phosphate, the apical loop, and the 2-nt 3'-overhang are important for the processing activity of Dicer. Exceptionally, nine precursors of the let-7 family (pre-let-7) contain a 1-nt 3'-overhang and get mono-uridylated in vivo, presumably to allow efficient processing by Dicer. Pre-let-7 are also oligo-uridylated in vivo to promote their degradation and likely prevent their efficient processing by Dicer. In this study, we systematically investigated the impact of sequence and structural features of all human let-7 pre-miRNAs, including their 3'-end modifications, on Dicer binding and processing. Through the combination of SHAPE structural probing, in vitro binding and kinetic studies using purified human Dicer, we show that despite structural discrepancies among pre-let-7 RNAs, Dicer exhibits remarkable promiscuity in binding and cleaving these substrates. Moreover, the 1- or 2-nt 3'-overhang, 3'-mono-uridylation, and 3'-oligo-uridylation of pre-let-7 substrates appear to have little effect on Dicer binding and cleavage rates. Thus, this study extends current knowledge regarding the broad substrate specificity of Dicer and provides novel insight regarding the effect of 3'-modifications on binding and cleavage by Dicer.

HT-SELEX-based identification of binding pre-miRNA hairpin-motif for small molecules.

Selective targeting of biologically relevant RNAs with small molecules is a long-standing challenge due to the lack of clear understanding of the binding RNA motifs for small molecules. The standard SELEX procedure allows the identification of specific RNA binders (aptamers) for the target of interest. However, more effort is needed to identify and characterize the sequence-structure motifs in the aptamers important for binding to the target. Herein, we described a strategy integrating high-throughput (HT) sequencing with conventional SELEX followed by bioinformatic analysis to identify aptamers with high binding affinity and target specificity to unravel the sequence-structure motifs of pre-miRNA, which is essential for binding to the recently developed new water-soluble small-molecule CMBL3aL. To confirm the fidelity of this approach, we investigated the binding of CMBL3aL to the identified motifs by surface plasmon resonance (SPR) spectroscopy and its potential regulatory activity on dicer-mediated cleavage of the obtained aptamers and endogenous pre-miRNAs comprising the identified motif in its hairpin loop. This new approach would significantly accelerate the identification process of binding sequence-structure motifs of pre-miRNA for the compound of interest and would contribute to increase the spectrum of biomedical application.

Efficacy, accumulation, and transcriptional profile of anti-HIV shRNAs expressed from human U6, 7SK, and H1 promoters.

The expression of short hairpin RNAs (shRNAs) in cells has many potential therapeutic applications, including as a functional cure for HIV. The RNA polymerase III promoters H1, 7SK, and U6 have all been used to express shRNAs. However, there have been no direct and simultaneous comparisons of shRNA potency, expression level, and transcriptional profile between the promoters. We show that the 7SK and U6 promoters result in higher shRNA levels and potency compared to the H1 promoter but that in transduced T lymphocytes, higher expression levels can also lead to growth defects. We present evidence that Dicer cleavage of shRNAs is measured from the first base pair in the shRNA stem, rather than from the 5' end as previously shown for structurally related microRNAs. As a result, guide-strand identity was unaffected by variations in 5' transcription start sites among the different promoters, making expression levels the main determinant of shRNA potency. While all promoters generated shRNAs with variable start sites, the U6 promoter was the most accurate in using its intended +1 position. Our results have implications for the development of therapeutic small RNAs for gene therapy and for our understanding of how shRNAs are processed in cells.

ReCGBM: a gradient boosting-based method for predicting human dicer cleavage sites.

BACKGROUND: Human dicer is an enzyme that cleaves pre-miRNAs into miRNAs. Several models have been developed to predict human dicer cleavage sites, including PHDCleav and LBSizeCleav. Given an input sequence, these models can predict whether the sequence contains a cleavage site. However, these models only consider each sequence independently and lack interpretability. Therefore, it is necessary to develop an accurate and explainable predictor, which employs relations between different sequences, to enhance the understanding of the mechanism by which human dicer cleaves pre-miRNA. RESULTS: In this study, we develop an accurate and explainable predictor for human dicer cleavage site - ReCGBM. We design relational features and class features as inputs to a lightGBM model. Computational experiments show that ReCGBM achieves the best performance compared to the existing methods. Further, we find that features in close proximity to the center of pre-miRNA are more important and make a significant contribution to the performance improvement of the developed method. CONCLUSIONS: The results of this study show that ReCGBM is an interpretable and accurate predictor. Besides, the analyses of feature importance show that it might be of particular interest to consider more informative features close to the center of the pre-miRNA in future predictors.

High-yield production of human Dicer by transfection of human HEK293-EBNA1 cells grown in suspension.

BACKGROUND: Dicer is a 219-kDa protein that plays key roles in gene regulation, particularly as the ribonuclease III enzyme responsible for cleaving precursor miRNA substrates. Its enzymatic activity is highly regulated by protein factors, and this regulation can impact on the levels of miRNAs and modulate the behavior of a cell. To better understand the underlying mechanisms of regulation, detailed enzymatic and structural characterization of Dicer are needed. However, these types of studies generally require several milligrams of recombinant protein, and efficient preparation of such quantities of pure human Dicer remains a challenge. To prepare large quantities of human Dicer, we have optimized transfection in HEK293-6E cells grown in suspension and streamlined a purification procedure. RESULTS: Transfection conditions were first optimized to achieve expression levels between 10 and 18 mg of recombinant Dicer per liter of culture. A three-step purification protocol was then developed that yields 4-9 mg of purified Dicer per liter of culture in a single day. From SEC-MALS/RI analysis and negative stain TEM, we confirmed that the purified protein is monomerically pure ( ≥ 98%) and folds with the characteristic L-shape geometry. Using an electrophoretic mobility shift assay, a dissociation constant (Kd) of 5 nM was measured for Dicer binding to pre-let-7a-1, in agreement with previous reports. However, when probing the cleavage activity of Dicer for pre-let-7a-1, we measured kcat (7.2 ± 0.5 min- 1) and KM (1.2 ± 0.3 µM) values that are much higher than previously reported due to experimental conditions that better respect the steady-state assumption. CONCLUSIONS: The expression and purification protocols described here provide high yields of monomerically pure and active human Dicer. Cleavage studies of a pre-let-7 substrate with this purified Dicer reveal higher kcat and KM values than previously reported and support the current view that conformational changes are associated with substrate binding. Large quantities of highly pure Dicer will be valuable for future biochemical, biophysical and structural investigations of this key protein of the miRNA pathway.

Design of Multimodal Small Molecules Targeting miRNAs Biogenesis: Synthesis and In Vitro Evaluation.

microRNAs (miRNAs) are emerging as novel biological targets for medicinal chemists to develop chemical tools for intracellular regulation. In this context, the discovery of small-molecule drugs targeting specific miRNAs and modulating their production or function represents a very promising approach that could be further developed for targeted therapy in miRNA-related pathologies. Here, we describe the design of multimodal small molecules as RNA ligands targeting DICER-mediated miRNA maturation. The synthesis and the biochemical evaluation as ligands of stem-loop-structured precursor microRNAs (pre-miRNAs) are reported.

LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length.

BACKGROUND: Dicer is necessary for the process of mature microRNA (miRNA) formation because the Dicer enzyme cleaves pre-miRNA correctly to generate miRNA with correct seed regions. Nonetheless, the mechanism underlying the selection of a Dicer cleavage site is still not fully understood. To date, several studies have been conducted to solve this problem, for example, a recent discovery indicates that the loop/bulge structure plays a central role in the selection of Dicer cleavage sites. In accordance with this breakthrough, a support vector machine (SVM)-based method called PHDCleav was developed to predict Dicer cleavage sites which outperforms other methods based on random forest and naive Bayes. PHDCleav, however, tests only whether a position in the shift window belongs to a loop/bulge structure. RESULT: In this paper, we used the length of loop/bulge structures (in addition to their presence or absence) to develop an improved method, LBSizeCleav, for predicting Dicer cleavage sites. To evaluate our method, we used 810 empirically validated sequences of human pre-miRNAs and performed fivefold cross-validation. In both 5p and 3p arms of pre-miRNAs, LBSizeCleav showed greater prediction accuracy than PHDCleav did. This result suggests that the length of loop/bulge structures is useful for prediction of Dicer cleavage sites. CONCLUSION: We developed a novel algorithm for feature space mapping based on the length of a loop/bulge for predicting Dicer cleavage sites. The better performance of our method indicates the usefulness of the length of loop/bulge structures for such predictions.