Anti-epileptogenic effect of FC99 and resveratrol.

Toll-like receptor 3 (TLR3), plays an important role in the development of epilepsy after brain insults. Previously, TLR3 deficiency in a pilocarpine model of temporal lobe epilepsy (TLE) was shown to reduce mortality, spontaneous recurrent seizures (SRS) and neuroinflammation. We hypothesized that pharmacological inhibition of TLR3 would reduce epileptogenesis following status epilepticus. We show that Resveratrol and FC99, two TLR3 blockers, demonstrate anti-epileptogenic effects in a pilocarpine model of TLE. While both Resveratrol and FC99 were previously shown to benefit in other pathologies, neither of these blockers had been proposed for the treatment of epilepsy. Our results provide substantial evidence to the importance of TLR3 inhibition in the prevention of epilepsy and specifically highlighting FC99 as a promising novel anti-epileptic drug. We anticipate our data to be a starting point for further studies assessing the anti-epileptogenic potential of FC99 and other TLR3 blockers, paving the way for pharmacological interventions that prevent epileptogenesis.

The intercorrelations between blood levels of ferritin, sCD163, and IL-18 in COVID-19 patients and their association to prognosis.

Coronavirus disease 2019 (COVID-19) is associated with immune dysregulation, severe respiratory failure, and multiple organ dysfunction caused by a cytokine storm involving high blood levels of ferritin and IL-18. Furthermore, there is a resemblance between COVID-19 and macrophage activation syndrome (MAS) characterized by high concentrations of soluble CD163 (sCD163) receptor and IL-18. High levels of ferritin, IL-18, and sCD163 receptor are associated with "hyperferritinemic syndrome", a family of diseases that appears to include COVID-19. In this retrospective cohort study, we tested the association and intercorrelations in the serum levels of ferritin, sCD163, and IL-18 and their impact on the prognosis of COVID-19. We analyzed data of 70 hospitalized patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The levels of sCD163, ferritin, and IL-18 were measured and the correlation of these parameters with the respiratory deterioration and overall 30-day survival was assessed. Among the 70 patients, 60 survived 30 days from hospitalization. There were substantial differences between the subjects who were alive following 30 days compared to those who expired. The differences were referring to lymphocyte and leukocyte count, CRP, D-dimer, ferritin, sCD163, and IL-18. Results showed high levels of IL-18 (median, 444 pg/mL in the survival group compared with 916 pg/mL in the mortality group, p-value 8.54 × 10-2), a statistically significant rise in levels of ferritin (median, 484 ng/mL in the survival group compared with 1004 ng/mL in the mortality group p-value, 7.94 × 10-3), and an elevated value of in sCD163 (mean, 559 ng/mL in the survival group compared with 840 ng/mL in the mortality group, p-value 1.68 × 10-2). There was no significant correlation between the rise of ferritin and the levels sCD163 or IL-18. Taken together, sCD163, ferritin, and IL-18 were found to correlate with the severity of COVID-19 infection. Although these markers are associated with COVID-19 and might contribute to the cytokine storm, no intercorrelation was found among them. It cannot be excluded though that the results depend on the timing of sampling, assuming that they play distinct roles in different stages of the disease course. The data represented herein may provide clinical benefit in improving our understanding of the pathological course of the disease. Furthermore, measuring these biomarkers during the disease progression may help target them at the right time and refine the decision-making regarding the requirement for hospitalization.

Computational normal mode analysis accurately replicates the activity and specificity profiles of CRISPR-Cas9 and high-fidelity variants.

The CRISPR-Cas system has transformed the field of gene-editing and created opportunities for novel genome engineering therapeutics. The field has significantly progressed, and recently, CRISPR-Cas9 was utilized in clinical trials to target disease-causing mutations. Existing tools aim to predict the on-target efficacy and potential genome-wide off-targets by scoring a particular gRNA according to an array of gRNA design principles or machine learning algorithms based on empirical results of large numbers of gRNAs. However, such tools are unable to predict the editing outcome by variant Cas enzymes and can only assess potential off-targets related to reference genomes. Here, we employ normal mode analysis (NMA) to investigate the structure of the Cas9 protein complexed with its gRNA and target DNA and explore the function of the protein. Our results demonstrate the feasibility and validity of NMA to predict the activity and specificity of SpyCas9 in the presence of mismatches by comparison to empirical data. Furthermore, despite the absence of their exact structures, this method accurately predicts the enzymatic activity of known high-fidelity engineered Cas9 variants.

Single-Base Resolution: Increasing the Specificity of the CRISPR-Cas System in Gene Editing.

The CRISPR-Cas system holds great promise in the treatment of diseases caused by genetic variations. The Cas protein, an RNA-guided programmable nuclease, generates a double-strand break at precise genomic loci. However, the use of the clustered regularly interspersed short palindromic repeats (CRISPR)-Cas system to distinguish between single-nucleotide variations is challenging. The promiscuity of the guide RNA (gRNA) and its mismatch tolerance make allele-specific targeting an elusive goal. This review presents a meta-analysis of previous studies reporting position-dependent mismatch tolerance within the gRNA. We also examine the conservativity of the seed sequence, a region within the gRNA with stringent sequence dependency, and propose the existence of a subregion within the seed sequence with a higher degree of specificity. In addition, we summarize the reports on high-fidelity Cas nucleases with improved specificity and compare the standard gRNA design methodology to the single-nucleotide polymorphism (SNP)-derived protospacer adjacent motif (PAM) approach, an alternative method for allele-specific targeting. The combination of the two methods may be advantageous in designing CRISPR-based therapeutics and diagnostics for heterozygous patients.

CrisPam: SNP-Derived PAM Analysis Tool for Allele-Specific Targeting of Genetic Variants Using CRISPR-Cas Systems.

Clustered regularly interspaced short palindromic repeats (CRISPR) is a promising novel technology that holds the potential of treating genetic diseases. Safety and specificity of the treatment are to be further studied and developed prior to implementation of the technology into the clinic. The guide-RNA (gRNA) allows precise position-specific DNA targeting, although it may tolerate small changes such as point mutations. The permissive nature of the CRISPR-Cas system makes allele-specific targeting a challenging goal. Hence, an allele-specific targeting approach is in need for future treatments of heterozygous patients suffering from diseases caused by dominant negative mutations. The single-nucleotide polymorphism (SNP)-derived protospacer adjacent motif (PAM) approach allows highly allele-specific DNA cleavage due to the existence of a novel PAM sequence only at the target allele. Here, we present CrisPam, a computational tool that detects PAMs within the variant allele for allele-specific targeting by CRISPR-Cas systems. The algorithm scans the sequences and attempts to identify the generation of multiple PAMs for a given reference sequence and its variations. A successful result is such that at least a single PAM is generated by the variation nucleotide. Since the PAM is present within the variant allele only, the Cas enzyme will bind the variant allele exclusively. Analyzing a dataset of human pathogenic point mutations revealed that 90% of the analyzed mutations generated at least a single PAM. Thus, the SNP-derived PAM approach is ideal for targeting most of the point mutations in an allele-specific manner. CrisPam simplifies the gRNAs design process to specifically target the allele of interest and scans a wide range of 26 unique PAMs derived from 23 Cas enzymes. CrisPam is freely available at https://www.danioffenlab.com/crispam.

Prediction of synonymous corrections by the BE-FF computational tool expands the targeting scope of base editing.

Base editing is a genome-editing approach that employs the CRISPR/Cas system to precisely install point mutations within the genome. A deaminase enzyme is fused to a deactivated Cas and enables transition conversions. The diversified repertoire of base editors provides a wide range of base editing possibilities. However, existing base editors cannot induce transversion substitutions and activate only within a specified region relative to the binding site, thus, they cannot precisely correct every point mutation. Here, we present BE-FF (Base Editors Functional Finder), a novel computational tool that identifies suitable base editors to correct the translated sequence erred by a point mutation. When a precise correction is impossible, BE-FF aims to mutate bystander nucleotides in order to induce synonymous corrections that will correct the coding sequence. To measure BE-FF practicality, we analysed a database of human pathogenic point mutations. Out of the transition mutations, 60.9% coding sequences could be corrected. Notably, 19.4% of the feasible corrections were not achieved by precise corrections but only by synonymous corrections. Moreover, 298 cases of transversion-derived pathogenic mutations were detected to be potentially repairable by base editing via synonymous corrections, although base editing is considered impractical for such mutations.