Optimized models for design of efficient miR30-based shRNAs

An In-silico Approach to Design and Validate siRNA against Monkeypox Virus

INTRODUCTION

The monkeypox virus has emerged as an uncommon zoonotic infection. The recent outbreak of MPXV in Europe and abroad in 2022 presented a major threat to individuals at risk. At present, no specific MPXV vaccinations or medications are available.

METHODS

In this study, we predicted the most effective siRNA against the conserved region of the MPXV and validated the activity by performing molecular docking studies.

RESULTS

Ultimately, the most efficient siRNA molecule was shortlisted against the envelope protein gene (B6R) based on its toxicity, effectivity, thermodynamic stability, molecular interaction, and molecular dynamics simulations (MD) with the Human Argonaute 2 protein.

CONCLUSION

Thus, the strategy may offer a platform for the development of potential antiviral RNA therapeutics that target MPXV at the genomic level.

ILGBMSH: an interpretable classification model for the shRNA target prediction with ensemble learning algorithm

Short hairpin RNA (shRNA)-mediated gene silencing is an important technology to achieve RNA interference, in which the design of potent and reliable shRNA molecules plays a crucial role. However, efficient shRNA target selection through biological technology is expensive and time consuming. Hence, it is crucial to develop a more precise and efficient computational method to design potent and reliable shRNA molecules. In this work, we present an interpretable classification model for the shRNA target prediction using the Light Gradient Boosting Machine algorithm called ILGBMSH. Rather than utilizing only the shRNA sequence feature, we extracted 554 biological and deep learning features, which were not considered in previous shRNA prediction research. We evaluated the performance of our model compared with the state-of-the-art shRNA target prediction models. Besides, we investigated the feature explanation from the model's parameters and interpretable method called Shapley Additive Explanations, which provided us with biological insights from the model. We used independent shRNA experiment data from other resources to prove the predictive ability and robustness of our model. Finally, we used our model to design the miR30-shRNA sequences and conducted a gene knockdown experiment. The experimental result was perfectly in correspondence with our expectation with a Pearson's coefficient correlation of 0.985. In summary, the ILGBMSH model can achieve state-of-the-art shRNA prediction performance and give biological insights from the machine learning model parameters.

Erythroid lineage-specific lentiviral RNAi vectors suitable for molecular functional studies and therapeutic applications

Numerous genes exert multifaceted roles in hematopoiesis. Therefore, we generated novel lineage-specific RNA interference (RNAi) lentiviral vectors, H23B-Ery-Lin-shRNA and H234B-Ery-Lin-shRNA, to probe the functions of these genes in erythroid cells without affecting other hematopoietic lineages. The lineage specificity of these vectors was confirmed by transducing multiple hematopoietic cells to express a fluorescent protein. Unlike the previously reported erythroid lineage RNAi vector, our vectors were designed for cloning the short hairpin RNAs (shRNAs) for any gene, and they also provide superior knockdown of the target gene expression with a single shRNA integration per cell. High-level lineage-specific downregulation of BCL11A and ZBTB7A, two well-characterized transcriptional repressors of HBG in adult erythroid cells, was achieved with substantial induction of fetal hemoglobin with a single-copy lentiviral vector integration. Transduction of primary healthy donor CD34+ cells with these vectors resulted in >80% reduction in the target protein levels and up to 40% elevation in the γ-chain levels in the differentiated erythroid cells. Xenotransplantation of the human CD34+ cells transduced with H23B-Ery-Lin-shBCL11A LV in immunocompromised mice showed ~ 60% reduction in BCL11A protein expression with ~ 40% elevation of γ-chain levels in the erythroid cells derived from the transduced CD34+ cells. Overall, the novel erythroid lineage-specific lentiviral RNAi vectors described in this study provide a high-level knockdown of target gene expression in the erythroid cells, making them suitable for their use in gene therapy for hemoglobinopathies. Additionally, the design of these vectors also makes them ideal for high-throughput RNAi screening for studying normal and pathological erythropoiesis.

Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes

Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.

Prediction of potent shRNAs with a sequential classification algorithm

We present SplashRNA, a sequential classifier to predict potent microRNA-based short hairpin RNAs (shRNAs). Trained on published and novel datasets, SplashRNA outperforms previous algorithms and reliably predicts the most efficient shRNAs for a given gene. Combined with an optimized miR-E backbone, >90% of high-scoring SplashRNA predictions trigger >85% protein knockdown when expressed from a single genomic integration. SplashRNA can significantly improve the accuracy of loss-of-function genetics studies and facilitates the generation of compact shRNA libraries.

Near-Perfect Synaptic Integration by Nav1.7 in Hypothalamic Neurons Regulates Body Weight

Neurons are well suited for computations on millisecond timescales, but some neuronal circuits set behavioral states over long time periods, such as those involved in energy homeostasis. We found that multiple types of hypothalamic neurons, including those that oppositely regulate body weight, are specialized as near-perfect synaptic integrators that summate inputs over extended timescales. Excitatory postsynaptic potentials (EPSPs) are greatly prolonged, outlasting the neuronal membrane time-constant up to 10-fold. This is due to the voltage-gated sodium channel Na_v1.7 (Scn9a), previously associated with pain-sensation but not synaptic integration. Scn9a deletion in AGRP, POMC, or paraventricular hypothalamic neurons reduced EPSP duration, synaptic integration, and altered body weight in mice. In vivo whole-cell recordings in the hypothalamus confirmed near-perfect synaptic integration. These experiments show that integration of synaptic inputs over time by Na_v1.7 is critical for body weight regulation and reveal a mechanism for synaptic control of circuits regulating long term homeostatic functions.

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Hypothalamic neurons that regulate body weight are near-perfect synaptic integrators

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Near-perfect synaptic integration is observed in hypothalamic neurons in vivo

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Near-perfect synaptic integration depends on the voltage-gated sodium channel Na_v1.7

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Loss of Na_v1.7 in hypothalamic neurons disrupts regulation of body weight

Molecular genetic mechanisms of allelic specific regulation of murine Comt expression

A functional allele of the mouse catechol-O-methyltransferase (Comt) gene is defined by the insertion of a B2 short interspersed repeat element in its 3'-untranslated region (UTR). This allele has been associated with a number of phenotypes, such as pain and anxiety. In comparison with mice carrying the ancestral allele (Comt+), Comt B2i mice show higher Comt mRNA and enzymatic activity levels. Here, we investigated the molecular genetic mechanisms underlying this allelic specific regulation of Comt expression. Insertion of the B2 element introduces an early polyadenylation signal generating a shorter Comt transcript, in addition to the longer ancestral mRNA. Comparative analysis and in silico prediction of Comt mRNA potential targets within the transcript 3' to the B2 element was performed and allowed choosing microRNA (miRNA) candidates for experimental screening: mmu-miR-3470a, mmu-miR-3470b, and mmu-miR-667. Cell transfection with each miRNA downregulated the expression of the ancestral transcript and COMT enzymatic activity. Our in vivo experiments showed that mmu-miR-667-3p is strongly correlated with decreasing amounts of Comt mRNA in the brain, and lentiviral injections of mmu-miR-3470a, mmu-miR-3470b, and mmu-miR-667 increase hypersensitivity in the mouse formalin model, consistent with reduced COMT activity. In summary, our data demonstrate that the Comt+ transcript contains regulatory miRNA signals in its 3'-untranslated region leading to mRNA degradation; these signals, however, are absent in the shorter transcript, resulting in higher mRNA expression and activity levels.

Improved knockdown from artificial microRNAs in an enhanced miR-155 backbone: a designer's guide to potent multi-target RNAi

Artificial microRNA (amiRNA) sequences embedded in natural microRNA (miRNA) backbones have proven to be useful tools for RNA interference (RNAi). amiRNAs have reduced off-target and toxic effects compared to other RNAi-based methods such as short-hairpin RNAs (shRNA). amiRNAs are often less effective for knockdown, however, compared to their shRNA counterparts. We screened a large empirically-designed amiRNA set in the synthetic inhibitory BIC/miR-155 RNA (SIBR) scaffold and show common structural and sequence-specific features associated with effective amiRNAs. We then introduced exogenous motifs into the basal stem region which increase amiRNA biogenesis and knockdown potency. We call this modified backbone the enhanced SIBR (eSIBR) scaffold. Using chained amiRNAs for multi-gene knockdown, we show that concatenation of miRNAs targeting different genes is itself sufficient for increased knockdown efficacy. Further, we show that eSIBR outperforms wild-type SIBR (wtSIBR) when amiRNAs are chained. Finally, we use a lentiviral expression system in cultured neurons, where we again find that eSIBR amiRNAs are more potent for multi-target knockdown of endogenous genes. eSIBR will be a valuable tool for RNAi approaches, especially for studies where knockdown of multiple targets is desired.

Advances in CRISPR-Cas9 genome engineering: lessons learned from RNA interference

The discovery that the machinery of the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9 bacterial immune system can be re-purposed to easily create deletions, insertions and replacements in the mammalian genome has revolutionized the field of genome engineering and re-invigorated the field of gene therapy. Many parallels have been drawn between the newly discovered CRISPR-Cas9 system and the RNA interference (RNAi) pathway in terms of their utility for understanding and interrogating gene function in mammalian cells. Given this similarity, the CRISPR-Cas9 field stands to benefit immensely from lessons learned during the development of RNAi technology. We examine how the history of RNAi can inform today's challenges in CRISPR-Cas9 genome engineering such as efficiency, specificity, high-throughput screening and delivery for in vivo and therapeutic applications.

Inducible and reversible lentiviral and Recombination Mediated Cassette Exchange (RMCE) systems for controlling gene expression

Manipulation of gene expression to invoke loss of function (LoF) or gain of function (GoF) phenotypes is important for interrogating complex biological questions both in vitro and in vivo. Doxycycline (Dox)-inducible gene expression systems are commonly used although success is often limited by high background and insufficient sensitivity to Dox. Here we develop broadly applicable platforms for reliable, tightly controlled and reversible Dox-inducible systems for lentiviral mediated generation of cell lines or FLP Recombination-Mediated Cassette Exchange (RMCE) into the Collagen 1a1 (Col1a1) locus (FLP-In Col1a1) in mouse embryonic stem cells. We significantly improve the flexibility, usefulness and robustness of the Dox-inducible system by using Tetracycline (Tet) activator (Tet-On) variants which are more sensitive to Dox, have no background activity and are expressed from single Gateway-compatible constructs. We demonstrate the usefulness of these platforms in ectopic gene expression or gene knockdown in multiple cell lines, primary neurons and in FLP-In Col1a1 mouse embryonic stem cells. We also improve the flexibility of RMCE Dox-inducible systems by generating constructs that allow for tissue or cell type-specific Dox-inducible expression and generate a shRNA selection algorithm that can effectively predict potent shRNA sequences able to knockdown gene expression from single integrant constructs. These platforms provide flexible, reliable and broadly applicable inducible expression systems for studying gene function.

A computational algorithm to predict shRNA potency

The strength of conclusions drawn from RNAi-based studies is heavily influenced by the quality of tools used to elicit knockdown. Prior studies have developed algorithms to design siRNAs. However, to date, no established method has emerged to identify effective shRNAs, which have lower intracellular abundance than transfected siRNAs and undergo additional processing steps. We recently developed a multiplexed assay for identifying potent shRNAs and used this method to generate ∼250,000 shRNA efficacy data points. Using these data, we developed shERWOOD, an algorithm capable of predicting, for any shRNA, the likelihood that it will elicit potent target knockdown. Combined with additional shRNA design strategies, shERWOOD allows the ab initio identification of potent shRNAs that specifically target the majority of each gene's multiple transcripts. We validated the performance of our shRNA designs using several orthogonal strategies and constructed genome-wide collections of shRNAs for humans and mice based on our approach.

Impact of RNA-guided technologies for target identification and deconvolution

For well over a decade, RNA interference (RNAi) has provided a powerful tool for investigators to query specific gene targets in an easily modulated loss-of-function setting, both in vitro and in vivo. Hundreds of publications have demonstrated the utility of RNAi in arrayed and pooled-based formats, in a wide variety of cell-based systems, including clonal, stem, transformed, and primary cells. Over the years, there have been significant improvements in the design of target-specific small-interfering RNA (siRNA) and short-hairpin RNA (shRNA), expression vectors, methods for mitigating off-target effects, and accurately interpreting screening results. Recent developments in RNAi technology include the Sensor assay, high-efficiency miR-E shRNAs, improved shRNA virus production with Pasha (DRGC8) knockdown, and assessment of RNAi off-target effects by using the C9-11 method. An exciting addition to the arsenal of RNA-mediated gene modulation is the clustered regularly interspaced short palindromic repeats/Cas9 (CRISPR/Cas) system for genomic editing, allowing for gene functional knockout rather than knockdown.

Optimization of Critical Hairpin Features Allows miRNA-based Gene Knockdown Upon Single-copy Transduction

Gene knockdown using micro RNA (miRNA)-based vector constructs is likely to become a prominent gene therapy approach. It was the aim of this study to improve the efficiency of gene knockdown through optimizing the structure of miRNA mimics. Knockdown of two target genes was analyzed: CCR5 and green fluorescent protein. We describe here a novel and optimized miRNA mimic design called mirGE comprising a lower stem length of 13 base pairs (bp), positioning of the targeting strand on the 5' side of the miRNA, together with nucleotide mismatches in upper stem positions 1 and 12 placed on the passenger strand. Our mirGE proved superior to miR-30 in four aspects: yield of targeting strand incorporation into RNA-induced silencing complex (RISC); incorporation into RISC of correct targeting strand; precision of cleavage by Drosha; and ratio of targeting strand over passenger strand. A triple mirGE hairpin cassette targeting CCR5 was constructed. It allowed CCR5 knockdown with an efficiency of over 90% upon single-copy transduction. Importantly, single-copy expression of this construct rendered transduced target cells, including primary human macrophages, resistant to infection with a CCR5-tropic strain of HIV. Our results provide new insights for a better knockdown efficiency of constructs containing miRNA. Our results also provide the proof-of-principle that cells can be rendered HIV resistant through single-copy vector transduction, rendering this approach more compatible with clinical applications.

Stable RNA interference rules for silencing

RNA interference has become an indispensable tool for loss-of-function studies across eukaryotes. By enabling stable and reversible gene silencing, shRNAs provide a means to study long-term phenotypes, perform pool-based forward genetic screens and examine the consequences of temporary target inhibition in vivo. However, efficient implementation in vertebrate systems has been hindered by technical difficulties affecting potency and specificity. Focusing on these issues, we analyse current strategies to obtain maximal knockdown with minimal off-target effects.