A target expression threshold dictates invader defense and autoimmunity by CRISPR-Cas13

Immune systems must recognize and clear foreign invaders without eliciting autoimmunity. CRISPR-Cas immune systems in prokaryotes manage this task by following two criteria: extensive guide:target complementarity and a defined target-flanking motif. Here we report an additional requirement for RNA-targeting CRISPR-Cas13 systems: expression of the target transcript exceeding a threshold. This finding is based on targeting endogenous non-essential transcripts, which rarely elicited dormancy through collateral RNA degradation. Instead, eliciting dormancy required over-expressing targeted transcripts above a threshold. A genome-wide screen confirmed target expression levels as the principal determinant of cytotoxic autoimmunity and revealed that the threshold shifts with the guide:target pair. This expression threshold ensured defense against a lytic bacteriophage yet allowed tolerance of a targeted beneficial gene expressed from an invading plasmid. These findings establish target expression levels as a third criterion for immune activation by RNA-targeting CRISPR-Cas systems, buffering against autoimmunity and distinguishing pathogenic and benign invaders.

A Combined mRNA- and miRNA-Sequencing Approach Reveals miRNAs as Potential Regulators of the Small Intestinal Transcriptome in Celiac Disease

Celiac disease (CeD) is triggered by gluten and results in inflammation and villous atrophy of the small intestine. We aimed to explore the role of miRNA-mediated deregulation of the transcriptome in CeD. Duodenal biopsies of CeD patients (n = 33) and control subjects (n = 10) were available for miRNA-sequencing, with RNA-sequencing also available for controls (n = 5) and CeD (n = 6). Differential expression analysis was performed to select CeD-associated miRNAs and genes. MiRNA‒target transcript pairs selected from public databases that also displayed a strong negative expression correlation in the current dataset (R < −0.7) were used to construct a CeD miRNA‒target transcript interaction network. The network includes 2030 miRNA‒target transcript interactions, including 423 experimentally validated pairs. Pathway analysis found that interactions are involved in immune-related pathways (e.g., interferon signaling) and metabolic pathways (e.g., lipid metabolism). The network includes 13 genes previously prioritized to be causally deregulated by CeD-associated genomic variants, including STAT1. CeD-associated miRNAs might play a role in promoting inflammation and decreasing lipid metabolism in the small intestine, thereby contributing unbalanced cell turnover in the intestinal crypt. Some CeD-associated miRNAs deregulate genes that are also affected by genomic CeD-risk variants, adding an additional layer of complexity to the deregulated transcriptome in CeD.

CASowary: CRISPR-Cas13 guide RNA predictor for transcript depletion

Recent discovery of the gene editing system - CRISPR (Clustered Regularly Interspersed Short Palindromic Repeats) associated proteins (Cas), has resulted in its widespread use for improved understanding of a variety of biological systems. Cas13, a lesser studied Cas protein, has been repurposed to allow for efficient and precise editing of RNA molecules. The Cas13 system utilizes base complementarity between a crRNA/sgRNA (crispr RNA or single guide RNA) and a target RNA transcript, to preferentially bind to only the target transcript. Unlike targeting the upstream regulatory regions of protein coding genes on the genome, the transcriptome is significantly more redundant, leading to many transcripts having wide stretches of identical nucleotide sequences. Transcripts also exhibit complex three-dimensional structures and interact with an array of RBPs (RNA Binding Proteins), both of which further limit the scope of effective target sequences. As a result, there currently exists no method to predict whether a specific sgRNA will effectively knockdown a transcript. Here we present a novel machine learning and computational tool, CASowary, to predict the efficacy of a sgRNA. We used publicly available RNA knockdown data from Cas13 characterization experiments for 555 sgRNAs targeting the transcriptome in HEK293 cells, in conjunction with transcriptome-wide protein occupancy information on RNA. Our model utilizes a Decision Tree architecture with a set of 112 sequence and target availability features, to classify sgRNA efficacy into one of four classes, based upon expected level of target transcript knockdown. After accounting for noise in the training data set, the noise-normalized accuracy exceeds 70%. Additionally, highly effective sgRNA predictions have been experimentally validated using an independent RNA targeting Cas system - CIRTS, confirming the robustness and reproducibility of our model's sgRNA predictions. Utilizing transcriptome wide protein occupancy map generated using POP-seq in Hela cells against publicly available protein-RNA interaction map in Hek293 cells, we show that CASowary can predict high quality guides for numerous transcripts in a cell line specific manner. Application of CASowary to whole transcriptomes should enable rapid deployment of CRISPR/Cas13 systems, facilitating the development of therapeutic interventions linked with aberrations in RNA regulatory processes.

Small Molecule-Inducible RNA-Targeting Systems for Temporal Control of RNA Regulation

<div>All aspects of mRNA lifetime and function, including its stability, translational to protein, and trafficking through the cell, are tightly regulated through coordinated post-transcriptional modifications and interactions with a multitude of effector proteins. Despite the increasing recognition of RNA regulation as a critical layer of mammalian gene expression control and its increasing excitement as a therapeutic target, tools to study and control RNA regulatory mechanisms with temporal precision in their endogenous environment are lacking. Here, we present small molecule-inducible RNA-targeting effectors based on our previously-developed CRISPR/Cas-inspired RNA targeting system (CIRTS). The CIRTS biosensor system is based on guide RNA (gRNA)-dependent RNA binding domains that interact with a target transcript using Watson-Crick-Franklin base pair interactions. Addition of a small molecule recruits an RNA effector to the target transcript, thereby eliciting a local effect on the transcript. In this work, we showcase that these CIRTS biosensors can trigger inducible RNA editing, degradation, or translation on target transcripts in a small molecule-dependent manner. We further go on to show that the new CIRTS editor can induce RNA base editing in a small molecule-dependent manner in vivo. Collectively this work provides a useful new set of tools to probe the dynamics of RNA regulatory systems and a new approach to control gene expression at the RNA level.</div>

Small Molecule-Inducible RNA-Targeting Systems for Temporal Control of RNA Regulation

<div>All aspects of mRNA lifetime and function, including its stability, translational to protein, and trafficking through the cell, are tightly regulated through coordinated post-transcriptional modifications and interactions with a multitude of effector proteins. Despite the increasing recognition of RNA regulation as a critical layer of mammalian gene expression control and its increasing excitement as a therapeutic target, tools to study and control RNA regulatory mechanisms with temporal precision in their endogenous environment are lacking. Here, we present small molecule-inducible RNA-targeting effectors based on our previously-developed CRISPR/Cas-inspired RNA targeting system (CIRTS). The CIRTS biosensor system is based on guide RNA (gRNA)-dependent RNA binding domains that interact with a target transcript using Watson-Crick-Franklin base pair interactions. Addition of a small molecule recruits an RNA effector to the target transcript, thereby eliciting a local effect on the transcript. In this work, we showcase that these CIRTS biosensors can trigger inducible RNA editing, degradation, or translation on target transcripts in a small molecule-dependent manner. We further go on to show that the new CIRTS editor can induce RNA base editing in a small molecule-dependent manner in vivo. Collectively this work provides a useful new set of tools to probe the dynamics of RNA regulatory systems and a new approach to control gene expression at the RNA level.</div>