Benchmarking deep learning methods for predicting CRISPR/Cas9 sgRNA on- and off-target activities

Functional genomic screening in Komagataella phaffii enabled by high-activity CRISPR-Cas9 library

CRISPR-based high-throughput genome-wide loss-of-function screens are a valuable approach to functional genetics and strain engineering. The yeast Komagataella phaffii is a host of particular interest in the biopharmaceutical industry and as a metabolic engineering host for proteins and metabolites. Here, we design and validate a highly active 6-fold coverage genome-wide sgRNA library for this biotechnologically important yeast containing 30,848 active sgRNAs targeting over 99% of its coding sequences. Conducting fitness screens in the absence of functional non-homologous end joining (NHEJ), the dominant DNA repair mechanism in K. phaffii, provides a quantitative means to assess the activity of each sgRNA in the library. This approach allows for the experimental validation of each guide's targeting activity, leading to more precise screening outcomes. We used this approach to conduct growth screens with glucose as the sole carbon source and identify essential genes. Comparative analysis of the called gene sets identified a core set of K. phaffii essential genes, many of which relate to metabolic engineering targets, including protein production, secretion, and glycosylation. The high activity, genome-wide CRISPR library developed here enables functional genomic screening in K. phaffii, applied here to gene essentiality classification, and promises to enable other genetic screens.

Merkel Cell Polyomavirus-Pathophysiology and Treatment in the Era of Gene-Targeted Therapies

Merkel cell polyomavirus (MCPyV) is a significant contributor to the development of Merkel cell carcinoma (MCC), an aggressive skin cancer with high recurrence and a low survival rate. In fact, it is the deadliest skin cancer. The precise routes of transmission for MCPyV-positive MCC remain unclear, but several factors may trigger its development. Conventional treatments for MCC are not highly effective, especially in patients with metastasis, with a clear need for new treatment options. Gene-targeted therapies hold great promise for the treatment of MCC, including the use of siRNA and CRISPR/Cas (C/Cas) but critically none have yet been translated into clinical trials. Validating this approach is the fact that several siRNA products are already FDA licenced, while C/Cas has entered clinical trial, albeit for conditions other than MCC. There are many challenges that must be overcome to move from preclinical research to the clinic. In this review, we provide a comprehensive summary of the current understanding of MCC, with a particular focus on MCPyV-positive MCC, and the status of gene-targeted therapies. Additionally, we discuss the major obstacles that impede MCC research and explore future prospects.

Peptidase inhibitor 16 promotes proliferation of pancreatic ductal adenocarcinoma cells through OASL signaling

Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive cancer with a poor prognosis and a 5-year survival rate of less than 11%. As a member of the CAP superfamily of proteins, the role of peptidase inhibitor 16 (Pi16) in tumor progression is still unclear. Immunohistochemistry and quantitative RT-PCR methods were used to detect the expression levels of Pi16 protein and mRNA in PDAC patients. CRISPR/Cas9 technology was used to knock out the expression of Pi16 in PDAC cell lines. In vivo and in vitro experiments were used to verify the effect of Pi16 on PDAC proliferation ability. By RNA sequencing, we found that oligoadenylate synthetase L (OASL) can serve as a potential downstream target of Pi16. The expression of Pi16 was higher in PDAC tissues than in matched adjacent tissues. High expression of Pi16 was associated with PDAC progression and poor prognosis. Overexpression of Pi16 could promote the proliferation of PDAC cells in vitro and in vivo. Bioinformatics analysis and coimmunoprecipitation assays showed that Pi16 could bind to OASL. Moreover, the functional recovery test confirmed that Pi16 could promote the proliferation of PDAC via OASL. Our present study demonstrates that Pi16 might participate in the occurrence and development of PDAC by regulating cell proliferation by binding to OASL, indicating that Pi16 might be a promising novel therapeutic target for PDAC.

Gene editing technology to improve antitumor T-cell functions in adoptive immunotherapy

Adoptive immunotherapy, in which tumor-reactive T cells are prepared in vitro for adoptive transfer to the patient, can induce an objective clinical response in specific types of cancer. In particular, chimeric antigen receptor (CAR)-redirected T-cell therapy has shown robust responses in hematologic malignancies. However, its efficacy against most of the other tumors is still insufficient, which remains an unmet medical need. Accumulating evidence suggests that modifying specific genes can enhance antitumor T-cell properties. Epigenetic factors have been particularly implicated in the remodeling of T-cell functions, including changes to dysfunctional states such as terminal differentiation and exhaustion. Genetic ablation of key epigenetic molecules prevents the dysfunctional reprogramming of T cells and preserves their functional properties.Clustered, regularly interspaced, short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas)-based gene editing is a valuable tool to enable efficient and specific gene editing in cultured T cells. A number of studies have already identified promising targets to improve the therapeutic efficacy of CAR-T cells using genome-wide or focused CRISPR screening. In this review, we will present recent representative findings on molecular insights into T-cell dysfunction and how genetic modification contributes to overcoming it. We will also discuss several technical advances to achieve efficient gene modification using the CRISPR and other novel platforms.

Interpretable CRISPR/Cas9 off-target activities with mismatches and indels prediction using BERT

Off-target effects of CRISPR/Cas9 can lead to suboptimal genome editing outcomes. Numerous deep learning-based approaches have achieved excellent performance for off-target prediction; however, few can predict the off-target activities with both mismatches and indels between single guide RNA (sgRNA) and target DNA sequence pair. In addition, data imbalance is a common pitfall for off-target prediction. Moreover, due to the complexity of genomic contexts, generating an interpretable model also remains challenged. To address these issues, firstly we developed a BERT-based model called CRISPR-BERT for enhancing the prediction of off-target activities with both mismatches and indels. Secondly, we proposed an adaptive batch-wise class balancing strategy to combat the noise exists in imbalanced off-target data. Finally, we applied a visualization approach for investigating the generalizable nucleotide position-dependent patterns of sgRNA-DNA pair for off-target activity. In our comprehensive comparison to existing methods on five mismatches-only datasets and two mismatches-and-indels datasets, CRISPR-BERT achieved the best performance in terms of AUROC and PRAUC. Besides, the visualization analysis demonstrated how implicit knowledge learned by CRISPR-BERT facilitates off-target prediction, which shows potential in model interpretability. Collectively, CRISPR-BERT provides an accurate and interpretable framework for off-target prediction, further contributes to sgRNA optimization in practical use for improved target specificity in CRISPR/Cas9 genome editing. The source code is available at https://github.com/BrokenStringx/CRISPR-BERT.

R-Loops in Genome Instability and Cancer

R-loops are unique, three-stranded nucleic acid structures that primarily form when an RNA molecule displaces one DNA strand and anneals to the complementary DNA strand in a double-stranded DNA molecule. R-loop formation can occur during natural processes, such as transcription, in which the nascent RNA molecule remains hybridized with the template DNA strand, while the non-template DNA strand is displaced. However, R-loops can also arise due to many non-natural processes, including DNA damage, dysregulation of RNA degradation pathways, and defects in RNA processing. Despite their prevalence throughout the whole genome, R-loops are predominantly found in actively transcribed gene regions, enabling R-loops to serve seemingly controversial roles. On one hand, the pathological accumulation of R-loops contributes to genome instability, a hallmark of cancer development that plays a role in tumorigenesis, cancer progression, and therapeutic resistance. On the other hand, R-loops play critical roles in regulating essential processes, such as gene expression, chromatin organization, class-switch recombination, mitochondrial DNA replication, and DNA repair. In this review, we summarize discoveries related to the formation, suppression, and removal of R-loops and their influence on genome instability, DNA repair, and oncogenic events. We have also discussed therapeutical opportunities by targeting pathological R-loops.