Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning.

Genome editing through the development of CRISPR (Clustered Regularly Interspaced Short Palindromic Repeat)-Cas technology has revolutionized many fields in biology. Beyond Cas9 nucleases, Cas12a (formerly Cpf1) has emerged as a promising alternative to Cas9 for editing AT-rich genomes. Despite the promises, guide RNA efficiency prediction through computational tools search still lacks accuracy. Through a computational meta-analysis, here we report that Cas12a target and off-target cleavage behavior are a factor of nucleotide bias combined with nucleotide mismatches relative to the protospacer adjacent motif (PAM) site. These features helped to train a Random Forest machine learning model to improve the accuracy by at least 15% over existing algorithms to predict guide RNA efficiency for the Cas12a enzyme. Despite the progresses, our report underscores the need for more representative datasets and further benchmarking to reliably and accurately predict guide RNA efficiency and off-target effects for Cas12a enzymes.

Disentangling morphology and genetics in two voles (Microtus pennsylvanicus and M. ochrogaster) in a region of sympatry.

Species in recent, rapid radiations can be difficult to distinguish from one another due to incomplete sorting of traits, insufficient time for novel morphologies to evolve, and elevated rates of hybridization and gene flow. The vole genus Microtus (58 spp.) is one such system where all three factors are likely at play. In the central United States, the prairie vole, Microtus ochrogaster, and the eastern meadow vole, M. pennsylvanicus, occur in sympatry and can be distinguished on the basis of molar cusp patterns but are known to be exceptionally difficult to distinguish using external morphological characters. Using a combination of morphometrics, pelage color analyses, and phylogenetics, we explored which traits are most effective for species identification and whether these same traits can be used to identify the subspecies M. o. ohionensis. While we were able to identify six traits that differed significantly between M. ochrogaster and M. pennsylvanicus, we also found substantial measurement overlap which limits the utility of these traits for species identification. The subspecies M. o. ohionensis was particularly difficult to distinguish from M. p. pennsylvanicus, and we did not find any evidence that this subspecies forms a distinct genetic clade. Furthermore, the full species M. ochrogaster and M. pennsylvanicus did not form reciprocal clades in phylogenetic analyses. We discuss several possible reasons for these patterns, including unrecognized variation in molar cusp patterns and/or localized hybridization. Overall, our results provide useful information that will aid in the identification of these species and subspecies in the future, and provides a case study of how genetics, morphometrics, and fur color analyses can be used to disentangle signatures of evolutionary history and hybridization.

The Comparative Assessment of Wellens' Syndrome With Proximal Left Anterior Descending Artery (LAD) Stenosis Versus Right Coronary Artery (RCA) or Circumflex Coronary Artery Stenosis and Its Prevalence: A Systematic Review.

Wellens' syndrome is well-known for its critical stenosis of the proximal left anterior descending artery (LAD) with characteristic electrocardiographic findings of biphasic or deeply inverted T waves in V2-V6 under specific diagnostic criteria. Although the syndrome is known as a high-grade LAD lesion, its sequence of events can also be seen with the right coronary artery (RCA) and the left circumflex artery (LCX). This systemic review attempts to expand on these findings while analyzing the prevalence of Wellens' syndrome with the RCA and/or the circumflex artery. This study also comparatively indicated that Wellens' syndrome is seen in RCA and circumflex artery stenoses when present; the indication of the same medical management is warranted for effective treatment and survival. We extracted and analyzed 24 case reports each with an atypical presentation of acute coronary syndrome (ACS) and specific Wellens' syndrome pattern of electrocardiogram (ECG) presentation with critical stenosis in the LAD, RCA, and left circumflex artery. The risk of bias assessment was undertaken using internal risk analysis by utilizing medical libraries and certain search phrases to find research articles with the involvement of the LAD as opposed to the RCA and LCX in Wellens' syndrome. Based on the number of respective primary research articles found, a bias calculation was done on the reported respective coronary artery involvement. The finding of our systemic review confirms that Wellens' syndrome is a precordial lead disease with T wave abnormalities that present with critical stenosis of not only the LAD but also the RCA and circumflex artery. The result of our systemic review affirmed that although most Wellens' syndrome cases reported involve the stenosis of the LAD, the critical occlusion of the RCA and/or the circumflex artery was found with Wellens' syndrome pattern of ECG presentation, meaning that the sequence of events is not limited to the proximal LAD.

Paediatric Inflammatory Multisystem Syndrome: A Diagnostic Challenge in a COVID-19-Negative Patient.

Paediatric inflammatory multisystem syndrome (PIMS) is associated with SARS-CoV-2 infection in patients aged 19 years or below according to World Health Organization (WHO) criteria. The condition is characterised by fever, inflammation and organ dysfunction. PIMS mimics Kawasaki disease or toxic shock syndrome. As SARS-CoV-2 infection is a global pandemic, clinicians need to be aware of the conditions associated with it. We present the case of 18-year-old woman who was admitted with multi-organ failure requiring admission to the intensive care unit. The differential diagnosis included toxic shock syndrome, Kawasaki disease and PIMS. The overall picture fit the criteria for PIMS but the patient had a negative polymerase chain reaction (PCR) test for SARS-CoV-2, which presented additional diagnostic difficulties. As the PCR test was negative, IgG antibodies against SARS-CoV-2 were measured to detect past infection and tested positive. The patient was diagnosed with PIMS as she met the WHO criteria after other differential diagnoses were excluded. She was successfully treated with methylprednisolone and intravenous immunoglobulin (IVIG). LEARNING POINTS: Paediatric inflammatory multisystem syndrome (PIMS) can also occur in young adults as clinical improvement was observed in a young woman after the administration of methylprednisolone and intravenous immunoglobulin (IVIG).Multidisciplinary care is important for the diagnosis and management of PIMS.The presentation of PIMS has a lot of similarities with Kawasaki disease and toxic shock syndrome.

Urgent Neurosurgical Interventions in the COVID-19-Positive Pediatric Population.

BACKGROUND: Urgent neurosurgical interventions for pediatric patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are rare. These cases pose additional stress on a potentially vulnerable dysregulated inflammatory response that can place the child at risk of further clinical deterioration. Our aim was to describe the perioperative course of SARS-CoV-2-positive pediatric patients who had required an urgent neurosurgical intervention. METHODS: We retrospectively analyzed pediatric patients aged ≤18 years who had been admitted to a quaternary children's hospital with a positive polymerase chain reaction test result for SARS-CoV-2 virus from March 2020 to October 2021. The clinical characteristics, anesthetic and neurosurgical operative details, surgical outcomes, and non-neurological symptoms were collected and analyzed. RESULTS: We identified 8 SARS-CoV-2-positive patients with a mean age of 8.83 years (median, 8.5 years; range, 0.58-18 years). Of the 8 patients, 6 were male. All children had had mild or asymptomatic coronavirus disease 2109. The anesthetic and surgical courses for these patients were, overall, uncomplicated. All the patients had been admitted to a specialized isolation unit in the pediatric intensive care unit for cardiopulmonary and neurological monitoring. The use of increased protective personal equipment during anesthesia and surgery did not impede a successful neurosurgical operation. CONCLUSIONS: SARS-CoV-2-positive pediatric patients with minimal coronavirus disease 2019-related symptoms who require urgent neurosurgical interventions face unique challenges regarding their anesthetic status, operative delays due to SARS-CoV-2 polymerase chain reaction testing, and requirements for additional protective personal equipment. Despite these clinical challenges, the patients in our study had not experienced adverse postoperative consequences, and no healthcare professional involved in their care had contracted the virus.

Inferred expression regulator activities suggest genes mediating cardiometabolic genetic signals.

Expression QTL (eQTL) analyses have suggested many genes mediating genome-wide association study (GWAS) signals but most GWAS signals still lack compelling explanatory genes. We have leveraged an adipose-specific gene regulatory network to infer expression regulator activities and phenotypic master regulators (MRs), which were used to detect activity QTLs (aQTLs) at cardiometabolic trait GWAS loci. Regulator activities were inferred with the VIPER algorithm that integrates enrichment of expected expression changes among a regulator's target genes with confidence in their regulator-target network interactions and target overlap between different regulators (i.e., pleiotropy). Phenotypic MRs were identified as those regulators whose activities were most important in predicting their respective phenotypes using random forest modeling. While eQTLs were typically more significant than aQTLs in cis, the opposite was true among candidate MRs in trans. Several GWAS loci colocalized with MR trans-eQTLs/aQTLs in the absence of colocalized cis-QTLs. Intriguingly, at the 1p36.1 BMI GWAS locus the EPHB2 cis-aQTL was stronger than its cis-eQTL and colocalized with the GWAS signal and 35 BMI MR trans-aQTLs, suggesting the GWAS signal may be mediated by effects on EPHB2 activity and its downstream effects on a network of BMI MRs. These MR and aQTL analyses represent systems genetic methods that may be broadly applied to supplement standard eQTL analyses for suggesting molecular effects mediating GWAS signals.

A 584 bp deletion in CTRB2 inhibits chymotrypsin B2 activity and secretion and confers risk of pancreatic cancer.

Genome-wide association studies (GWASs) have discovered 20 risk loci in the human genome where germline variants associate with risk of pancreatic ductal adenocarcinoma (PDAC) in populations of European ancestry. Here, we fine-mapped one such locus on chr16q23.1 (rs72802365, p = 2.51 × 10-17, OR = 1.36, 95% CI = 1.31-1.40) and identified colocalization (PP = 0.87) with aberrant exon 5-7 CTRB2 splicing in pancreatic tissues (pGTEx = 1.40 × 10-69, ßGTEx = 1.99; pLTG = 1.02 × 10-30, ßLTG = 1.99). Imputation of a 584 bp structural variant overlapping exon 6 of CTRB2 into the GWAS datasets resulted in a highly significant association with pancreatic cancer risk (p = 2.83 × 10-16, OR = 1.36, 95% CI = 1.31-1.42), indicating that it may underlie this signal. Exon skipping attributable to the deletion (risk) allele introduces a premature stop codon in exon 7 of CTRB2, yielding a truncated chymotrypsinogen B2 protein that lacks chymotrypsin activity, is poorly secreted, and accumulates intracellularly in the endoplasmic reticulum (ER). We propose that intracellular accumulation of a nonfunctional chymotrypsinogen B2 protein leads to ER stress and pancreatic inflammation, which may explain the increased pancreatic cancer risk in carriers of CTRB2 exon 6 deletion alleles.

Establishing the shadowline: the border between legally acceptable and unacceptable standards of surgical practice.

INTRODUCTION: Our study investigated how the standard of surgical care is assessed within the English and Welsh litigation process. The 'shadowline' represents the dividing line between acceptable and unacceptable standards of care. Our hypothesis was that different assessors risk adopting materially different interpretations regarding the acceptable standard of care. Any variation in the interpretation of where the shadowline falls will create uncertainty and unfairness to surgeons and patients alike. METHODS: We summarised the legal literature and suggested the factors affecting the assessment of surgical standards. We illustrated our findings on distribution curves. RESULTS: There was a risk that the shape of the curve and the location of the shadowline may vary according to the assessor. Importantly, a gap may have developed between the legal and clinical shadowlines in respect of the consenting process. DISCUSSION AND CONCLUSION: We suggested how a gap between the surgical and legal shadow lines could be narrowed. Clinical governance, balanced literature and realistic expert assessments were all part of the solution.

GOANA: A Universal High-Throughput Web Service for Assessing and Comparing the Outcome and Efficiency of Genome Editing Experiments.

The increased development of functionally diverse and highly specialized genome editors has created the need for comparative analytics tools that are able to profile the mutational outcomes, particularly rare and complex outcomes, to assess the editor's applicability to different domains. To address this need, we have developed Generalizable On-target activity ANAlyzer (GOANA), a high-throughput web-based software for determining editing efficiency and cataloguing rare outcomes from next-generation sequencing data. GOANA calculates mutation frequency and outcomes relative to a supplied control sample. It is scalable to thousands of target sites across the entire genome and is 4,000% faster than CRISPResso2. Mutations are reported on a "per-read" level rather than individually, enabling the identification of co-occurring mutations. GOANA is editor agnostic and can be applied to data generated from any targeted editing experiment, including base editors. Requiring only that control and treated reads are aligned to the same reference, GOANA can handle data from any library preparation method, including pooled amplicon and whole-genome sequencing. As a proof of principle, we analyze two large data sets of CRISPR-Cas9 and CRISPR-Cas12a editing, demonstrating the power of GOANA and highlighting several key differences between the two enzymes. GOANA is available for use at https://gt-scan.csiro.au/goana/ and as a command line tool from https://github.com/BauerLab/GOANA.

Domain-specific introduction to machine learning terminology, pitfalls and opportunities in CRISPR-based gene editing.

The use of machine learning (ML) has become prevalent in the genome engineering space, with applications ranging from predicting target site efficiency to forecasting the outcome of repair events. However, jargon and ML-specific accuracy measures have made it hard to assess the validity of individual approaches, potentially leading to misinterpretation of ML results. This review aims to close the gap by discussing ML approaches and pitfalls in the context of CRISPR gene-editing applications. Specifically, we address common considerations, such as algorithm choice, as well as problems, such as overestimating accuracy and data interoperability, by providing tangible examples from the genome-engineering domain. Equipping researchers with the knowledge to effectively use ML to better design gene-editing experiments and predict experimental outcomes will help advance the field more rapidly.

VariantSpark: Cloud-based machine learning for association study of complex phenotype and large-scale genomic data.

BACKGROUND: Many traits and diseases are thought to be driven by >1 gene (polygenic). Polygenic risk scores (PRS) hence expand on genome-wide association studies by taking multiple genes into account when risk models are built. However, PRS only considers the additive effect of individual genes but not epistatic interactions or the combination of individual and interacting drivers. While evidence of epistatic interactions ais found in small datasets, large datasets have not been processed yet owing to the high computational complexity of the search for epistatic interactions. FINDINGS: We have developed VariantSpark, a distributed machine learning framework able to perform association analysis for complex phenotypes that are polygenic and potentially involve a large number of epistatic interactions. Efficient multi-layer parallelization allows VariantSpark to scale to the whole genome of population-scale datasets with 100,000,000 genomic variants and 100,000 samples. CONCLUSIONS: Compared with traditional monogenic genome-wide association studies, VariantSpark better identifies genomic variants associated with complex phenotypes. VariantSpark is 3.6 times faster than ReForeSt and the only method able to scale to ultra-high-dimensional genomic data in a manageable time.

Reproducibility of CRISPR-Cas9 methods for generation of conditional mouse alleles: a multi-center evaluation.

BACKGROUND: CRISPR-Cas9 gene-editing technology has facilitated the generation of knockout mice, providing an alternative to cumbersome and time-consuming traditional embryonic stem cell-based methods. An earlier study reported up to 16% efficiency in generating conditional knockout (cKO or floxed) alleles by microinjection of 2 single guide RNAs (sgRNA) and 2 single-stranded oligonucleotides as donors (referred herein as "two-donor floxing" method). RESULTS: We re-evaluate the two-donor method from a consortium of 20 laboratories across the world. The dataset constitutes 56 genetic loci, 17,887 zygotes, and 1718 live-born mice, of which only 15 (0.87%) mice contain cKO alleles. We subject the dataset to statistical analyses and a machine learning algorithm, which reveals that none of the factors analyzed was predictive for the success of this method. We test some of the newer methods that use one-donor DNA on 18 loci for which the two-donor approach failed to produce cKO alleles. We find that the one-donor methods are 10- to 20-fold more efficient than the two-donor approach. CONCLUSION: We propose that the two-donor method lacks efficiency because it relies on two simultaneous recombination events in cis, an outcome that is dwarfed by pervasive accompanying undesired editing events. The methods that use one-donor DNA are fairly efficient as they rely on only one recombination event, and the probability of correct insertion of the donor cassette without unanticipated mutational events is much higher. Therefore, one-donor methods offer higher efficiencies for the routine generation of cKO animal models.

Unlocking HDR-mediated nucleotide editing by identifying high-efficiency target sites using machine learning.

Editing individual nucleotides is a crucial component for validating genomic disease association. It is currently hampered by CRISPR-Cas-mediated "base editing" being limited to certain nucleotide changes, and only achievable within a small window around CRISPR-Cas target sites. The more versatile alternative, HDR (homology directed repair), has a 3-fold lower efficiency with known optimization factors being largely immutable in experiments. Here, we investigated the variable efficiency-governing factors on a novel mouse dataset using machine learning. We found the sequence composition of the single-stranded oligodeoxynucleotide (ssODN), i.e. the repair template, to be a governing factor. Furthermore, different regions of the ssODN have variable influence, which reflects the underlying mechanism of the repair process. Our model improves HDR efficiency by 83% compared to traditionally chosen targets. Using our findings, we developed CUNE (Computational Universal Nucleotide Editor), which enables users to identify and design the optimal targeting strategy using traditional base editing or - for-the-first-time - HDR-mediated nucleotide changes.

The Effect of Using Different Types of Forceps in the Efficacy of Transbronchial Lung Biopsy.

BACKGROUND: Transbronchial lung biopsy (TBBX) is a common respiratory diagnostic procedure performed to investigate several lung diseases. There are different types of forceps used to perform this procedure. The alligator and cupped (oval) forceps are most commonly used ones. To date, there are few studies that have compared the efficacy of these two types of forceps. This study compares the two types of forceps relating to the rate of complications and diagnostic value. METHODS: In this retrospective observational study, 40 patients who underwent TBBX using the alligator forceps were compared to a previous group of 40 patients who underwent the same procedure using the cupped forceps. The two groups were compared with respect to the rate of complications (bleeding and pneumothorax), diagnostic value and size of biopsies. RESULTS: The rate of complications was higher in patients who underwent TBBX using alligator forceps, in which seven patients (17.5%) had significant bleeding in the group that used alligator forceps versus three patients (7.5%) in cupped forceps group. Pneumothorax developed in three patients, all of whom were in the alligator forceps group. While there was no significant difference in the adequacy and size of the samples, the diagnostic yield was higher in the cupped forceps group. CONCLUSIONS: The results of the study showed that using cupped forceps in performing TBBX had fewer complications (pneumothorax and bleeding) and a higher diagnostic yield in comparison with alligator forceps, but the difference did not reach a statistical significant value.

The Current State and Future of CRISPR-Cas9 gRNA Design Tools.

Recent years have seen the development of computational tools to assist researchers in performing CRISPR-Cas9 experiment optimally. More specifically, these tools aim to maximize on-target activity (guide efficiency) while also minimizing potential off-target effects (guide specificity) by analyzing the features of the target site. Nonetheless, currently available tools cannot robustly predict experimental success as prediction accuracy depends on the approximations of the underlying model and how closely the experimental setup matches the data the model was trained on. Here, we present an overview of the available computational tools, their current limitations and future considerations. We discuss new trends around personalized health by taking genomic variants into account when predicting target sites as well as discussing other governing factors that can improve prediction accuracy.

Delipidation of mammalian Atg8-family proteins by each of the four ATG4 proteases.

During macroautophagy/autophagy, mammalian Atg8-family proteins undergo 2 proteolytic processing events. The first exposes a COOH-terminal glycine used in the conjugation of these proteins to lipids on the phagophore, the precursor to the autophagosome, whereas the second releases the lipid. The ATG4 family of proteases drives both cleavages, but how ATG4 proteins distinguish between soluble and lipid-anchored Atg8 proteins is not well understood. In a fully reconstituted delipidation assay, we establish that the physical anchoring of mammalian Atg8-family proteins in the membrane dramatically shifts the way ATG4 proteases recognize these substrates. Thus, while ATG4B is orders of magnitude faster at processing a soluble unprimed protein, all 4 ATG4 proteases can be activated to similar enzymatic activities on lipid-attached substrates. The recognition of lipidated but not soluble substrates is sensitive to a COOH-terminal LIR motif both in vitro and in cells. We suggest a model whereby ATG4B drives very fast priming of mammalian Atg8 proteins, whereas delipidation is inherently slow and regulated by all ATG4 homologs.

High Activity Target-Site Identification Using Phenotypic Independent CRISPR-Cas9 Core Functionality.

The activity of CRISPR-Cas9 target sites can be measured experimentally through phenotypic assays or mutation rate and used to build computational models to predict activity of novel target sites. However, currently published models have been reported to perform poorly in situations other than their training conditions. In this study, we hence investigate how different sources of data influence predictive power and identify the best data set for the most robust predictive model. We use the activity of 28,606 target sites and a machine learning approach to train a predictive model of CRISPR-Cas9 activity, outperforming other published methods by an average increase in accuracy of 80% for prediction of the degree of activity and 13% for classification into active and inactive categories. We find that using data sets that measure CRISPR-Cas9 activity through sequencing provides more accurate predictions of activity. Our model, dubbed TUSCAN, is highly scalable, predicting the activity of 5000 target sites in under 7 s, making it suitable for genome-wide screens. We conclude that sophisticated machine learning methods can classify binary CRISPR-Cas9 activity; however, predicting fine-scale activity scores will require larger data sets directly measuring Indel insertion rate.