Evaluation of RNAi and CRISPR technologies by large-scale gene expression profiling in the Connectivity Map

CRISPR/Cas-mediated mRNA knockdown in the embryos of Xenopus tropicalis

The Xenopus tropicalis (Western clawed frog) is an important amphibian model for genetics, developmental and regenerative biology, due to its diploid genetic background and short generation time. CRISPR-Cas13 and CRISPR interference (CRISPRi) systems have recently been employed to suppress mRNA expression in many organisms such as yeast, plants, and mammalian cells. However, no systematic study of these two systems has been carried out in Xenopus tropicalis. Here, we show that CRISPRi rather than CRISPR-Cas13 is an effective and suitable approach to suppress specific mRNA transcription in Xenopus tropicalis embryos. We demonstrated that CRISPRi composed of dCas9 and KRAB-MeCP2 (dCas9-KM) can efficiently target exogenous and endogenous transcripts in Xenopus tropicalis embryos. Moreover, our data suggest that the new KRAB domain from ZIM3 protein (ZIM3-KRAB, ZIM3K) alone has a comparable transcript targeting capacity in Xenopus tropicalis embryos to the traditional fusion repressor KRAB-MeCP2 in which the KRAB domain from KOX1 protein. In conclusion, our results demonstrate that CRISPRi rather than CRISPR-Cas13 is an efficient knockdown platform to explore specific gene function in Xenopus tropicalis embryos.

PRODE recovers essential and context-essential genes through neighborhood-informed scores

Gene context-essentiality assessment supports precision oncology opportunities. The variability of gene effects inference from loss-of-function screenings across models and technologies limits identifying robust hits. We propose a computational framework named PRODE that integrates gene effects with protein-protein interactions to generate neighborhood-informed essential (NIE) and neighborhood-informed context essential (NICE) scores. It outperforms the canonical gene effect approach in recovering missed essential genes in shRNA screens and prioritizing context-essential hits from CRISPR-KO screens, as supported by in vitro validations. Applied to Her2 + breast cancer tumor samples, PRODE identifies oxidative phosphorylation genes as vulnerabilities with prognostic value, highlighting new therapeutic opportunities.

Arrayed CRISPRi library to suppress genes required for Schizosaccharomyces pombe viability

The fission yeast, Schizosaccharomyces pombe, is an excellent eukaryote model organism for studying essential biological processes. Its genome contains ∼1,200 genes essential for cell viability, most of which are evolutionarily conserved. To study these essential genes, resources enabling conditional perturbation of target genes are required. Here, we constructed comprehensive arrayed libraries of plasmids and strains to knock down essential genes in S. pombe using dCas9-mediated CRISPRi. These libraries cover ∼98% of all essential genes in fission yeast. We estimate that in ∼60% of these strains, transcription of a target gene was repressed so efficiently that cell proliferation was significantly inhibited. To demonstrate the usefulness of these libraries, we performed metabolic analyses with knockdown strains and revealed flexible interaction among metabolic pathways. Libraries established in this study enable comprehensive functional analyses of essential genes in S. pombe and will facilitate the understanding of essential biological processes in eukaryotes.

Synthetic lethal strategies for the development of cancer therapeutics

Synthetic lethality is a genetic phenomenon whereby the simultaneous presence of two different genetic alterations impairs cellular viability. Importantly, targeting synthetic lethal interactions offers potential therapeutic strategies for cancers with alterations in pathways that might otherwise be considered undruggable. High-throughput screening methods based on modern CRISPR-Cas9 technologies have emerged and become crucial for identifying novel synthetic lethal interactions with the potential for translation into biologically rational cancer therapeutic strategies as well as associated predictive biomarkers of response capable of guiding patient selection. Spurred by the clinical success of PARP inhibitors in patients with BRCA-mutant cancers, novel agents targeting multiple synthetic lethal interactions within DNA damage response pathways are in clinical development, and rational strategies targeting synthetic lethal interactions spanning alterations in epigenetic, metabolic and proliferative pathways have also emerged and are in late preclinical and/or early clinical testing. In this Review, we provide a comprehensive overview of established and emerging technologies for synthetic lethal drug discovery and development and discuss promising therapeutic strategies targeting such interactions.

Collateral lethality: A unique type of synthetic lethality in cancers

Genetic interactions play crucial roles in cell-essential functions. Intrinsic genetic defects in tumors typically involve gain-of- and loss-of-function mutations in tumor suppressor genes (TSGs) and oncogenes, respectively, providing potential antitumor vulnerabilities. Moreover, tumor cells with TSG deficiencies exhibit heightened sensitivity to the inhibition of compensatory pathways. Synthetic and collateral lethality are two strategies used for exploiting novel drug targets in multiple types of cancer. Collateral lethality is a unique type of synthetic lethality that occurs when passenger genes are co-deleted in neighboring TSGs. Although synthetic lethality has already been successfully demonstrated in clinical practice, antitumor therapeutics based on collateral lethality are predominantly still in the preclinical phase. Therefore, screening for potential genetic interactions within the cancer genome has emerged as a promising approach for drug development. Here, the two conceptual therapeutic strategies that involve the deletion or inactivation of cancer-specific TSGs are discussed. Moreover, existing approaches for screening and identifying potential gene partners are also discussed. Particularly, this review highlights the current advances of "collateral lethality" in the preclinical phase and addresses the challenges involved in translating them into therapeutic applications. This review provides insights into these strategies as new opportunities for the development of personalized antitumor therapies.

Systemic evaluation of various CRISPR/Cas13 orthologs for knockdown of targeted transcripts in plants

BACKGROUND

CRISPR/Cas13 system, recognized for its compact size and specificity in targeting RNA, is currently employed for RNA degradation. However, the potential of various CRISPR/Cas13 subtypes, particularly concerning the knockdown of endogenous transcripts, remains to be comprehensively characterized in plants.

RESULTS

Here we present a full spectrum of editing profiles for seven Cas13 orthologs from five distinct subtypes: VI-A (LwaCas13a), VI-B (PbuCas13b), VI-D (RfxCas13d), VI-X (Cas13x.1 and Cas13x.2), and VI-Y (Cas13y.1 and Cas13y.2). A systematic evaluation of the knockdown effects on two endogenous transcripts (GhCLA and GhPGF in cotton) as well as an RNA virus (TMV in tobacco) reveals that RfxCas13d, Cas13x.1, and Cas13x.2 exhibit enhanced stability with editing efficiencies ranging from 58 to 80%, closely followed by Cas13y.1 and Cas13y.2. Notably, both Cas13x.1 and Cas13y.1 can simultaneously degrade two endogenous transcripts through a tRNA-crRNA cassette approach, achieving editing efficiencies of up to 50%. Furthermore, different Cas13 orthologs enable varying degrees of endogenous transcript knockdown with minimal off-target effects, generating germplasms that exhibit a diverse spectrum of mutant phenotypes. Transgenic tobacco plants show significant reductions in damage, along with mild oxidative stress and minimal accumulation of viral particles after TMV infection.

CONCLUSIONS

In conclusion, our study presents an efficient and reliable platform for transcriptome editing that holds promise for plant functional research and future crop improvement.

CRISPR-based genetic screens advance cancer immunology

CRISPR technologies have revolutionized research areas ranging from fundamental science to translational medicine. CRISPR-based genetic screens offer a powerful platform for unbiased screening in various fields, such as cancer immunology. Immune checkpoint blockade (ICB) therapy has been shown to strongly affect cancer treatment. However, the currently available ICBs are limited and do not work in all cancer patients. Pooled CRISPR screens enable the identification of previously unknown immune regulators that can regulate T-cell activation, cytotoxicity, persistence, infiltration into tumors, cytokine secretion, memory formation, T-cell metabolism, and CD4+ T-cell differentiation. These novel targets can be developed as new immunotherapies or used with the current ICBs as new combination therapies that may yield synergistic efficacy. Here, we review the progress made in the development of CRISPR technologies, particularly technological advances in CRISPR screens and their application in novel target identification for immunotherapy.

NP-TCMtarget: a network pharmacology platform for exploring mechanisms of action of traditional Chinese medicine

The biological targets of traditional Chinese medicine (TCM) are the core effectors mediating the interaction between TCM and the human body. Identification of TCM targets is essential to elucidate the chemical basis and mechanisms of TCM for treating diseases. Given the chemical complexity of TCM, both in silico high-throughput compound-target interaction predicting models and biological profile-based methods have been commonly applied for identifying TCM targets based on the structural information of TCM chemical components and biological information, respectively. However, the existing methods lack the integration of TCM chemical and biological information, resulting in difficulty in the systematic discovery of TCM action pathways. To solve this problem, we propose a novel target identification model NP-TCMtarget to explore the TCM target path by combining the overall chemical and biological profiles. First, NP-TCMtarget infers TCM effect targets by calculating associations between herb/disease inducible gene expression profiles and specific gene signatures for 8233 targets. Then, NP-TCMtarget utilizes a constructed binary classification model to predict binding targets of herbal ingredients. Finally, we can distinguish TCM direct and indirect targets by comparing the effect targets and binding targets to establish the action pathways of herbal component-direct target-indirect target by mapping TCM targets in the biological molecular network. We apply NP-TCMtarget to the formula XiaoKeAn to demonstrate the power of revealing the action pathways of herbal formula. We expect that this novel model could provide a systematic framework for exploring the molecular mechanisms of TCM at the target level. NP-TCMtarget is available at http://www.bcxnfz.top/NP-TCMtarget.

Drug-target interaction prediction by integrating heterogeneous information with mutual attention network

BACKGROUND

Identification of drug-target interactions is an indispensable part of drug discovery. While conventional shallow machine learning and recent deep learning methods based on chemogenomic properties of drugs and target proteins have pushed this prediction performance improvement to a new level, these methods are still difficult to adapt to novel structures. Alternatively, large-scale biological and pharmacological data provide new ways to accelerate drug-target interaction prediction.

METHODS

Here, we propose DrugMAN, a deep learning model for predicting drug-target interaction by integrating multiplex heterogeneous functional networks with a mutual attention network (MAN). DrugMAN uses a graph attention network-based integration algorithm to learn network-specific low-dimensional features for drugs and target proteins by integrating four drug networks and seven gene/protein networks collected by a certain screening conditions, respectively. DrugMAN then captures interaction information between drug and target representations by a mutual attention network to improve drug-target prediction.

RESULTS

DrugMAN achieved the best performance compared with cheminformation-based methods SVM, RF, DeepPurpose and network-based deep learing methods DTINet and NeoDT in four different scenarios, especially in real-world scenarios. Compared with SVM, RF, deepurpose, DTINet, and NeoDT, DrugMAN showed the smallest decrease in AUROC, AUPRC, and F1-Score from warm-start to Both-cold scenarios. This result is attributed to DrugMAN's learning from heterogeneous data and indicates that DrugMAN has a good generalization ability. Taking together, DrugMAN spotlights heterogeneous information to mine drug-target interactions and can be a powerful tool for drug discovery and drug repurposing.

In vivo CRISPRi screen identified lncRNA portfolio crucial for cutaneous squamous cell carcinoma tumor growth

Cutaneous squamous cell carcinoma (cSCC) accounts for 20% of all skin cancer deaths globally, making it the second-highest subtype of skin cancer. The prevalence of cSCC in humans, as well as the poor capacity for an efficient prognosis, highlights the need to uncover alternative actors and mechanisms at the foundation of skin cancer development. Significant advances have been made to better understand some key factors in cSCC progression. However, little is known about the role of noncoding RNAs, particularly of a specific category called long noncoding RNA (lncRNA). By performing pseudobulk analysis of single-cell sequencing data from normal and cSCC human skin tissues, we determined a global portfolio of lncRNAs specifically expressed in keratinocyte subpopulations. Integration of CRISPR interference screens in vitro and the xenograft model identified several lncRNAs impacting the growth of cSCC cancer lines both in vitro and in vivo. Among these, we further validated LINC00704 and LINC01116 as proliferation-regulating lncRNAs in cSCC lines and potential biomarkers of cSCC progression. Taken together, our study provides a comprehensive signature of lncRNAs with roles in regulating cSCC progression.

Computational pipeline predicting cell death suppressors as targets for cancer therapy

Identification of promising targets for cancer therapy is a global effort in precision medicine. Here, we describe a computational pipeline integrating transcriptomic and vulnerability responses to cell-death inducing drugs, to predict cell-death suppressors as candidate targets for cancer therapy. The prediction is based on two modules; the transcriptomic similarity module to identify genes whose targeting results in similar transcriptomic responses of the death-inducing drugs, and the correlation module to identify candidate genes whose expression correlates to the vulnerability of cancer cells to the same death-inducers. The combined predictors of these two modules were integrated into a single metric. As a proof-of-concept, we selected ferroptosis inducers as death-inducing drugs in triple negative breast cancer. The pipeline reliably predicted candidate genes as ferroptosis suppressors, as validated by computational methods and cellular assays. The described pipeline might be used to identify repressors of various cell-death pathways as potential therapeutic targets for different cancer types.

A genome-scale deep learning model to predict gene expression changes of genetic perturbations from multiplex biological networks

Systematic characterization of biological effects to genetic perturbation is essential to the application of molecular biology and biomedicine. However, the experimental exhaustion of genetic perturbations on the genome-wide scale is challenging. Here, we show TranscriptionNet, a deep learning model that integrates multiple biological networks to systematically predict transcriptional profiles to three types of genetic perturbations based on transcriptional profiles induced by genetic perturbations in the L1000 project: RNA interference, clustered regularly interspaced short palindromic repeat, and overexpression. TranscriptionNet performs better than existing approaches in predicting inducible gene expression changes for all three types of genetic perturbations. TranscriptionNet can predict transcriptional profiles for all genes in existing biological networks and increases perturbational gene expression changes for each type of genetic perturbation from a few thousand to 26 945 genes. TranscriptionNet demonstrates strong generalization ability when comparing predicted and true gene expression changes on different external tasks. Overall, TranscriptionNet can systemically predict transcriptional consequences induced by perturbing genes on a genome-wide scale and thus holds promise to systemically detect gene function and enhance drug development and target discovery.

Gene essentiality in cancer is better predicted by mRNA abundance than by gene regulatory network-inferred activity

Gene regulatory networks (GRNs) are often deregulated in tumor cells, resulting in altered transcriptional programs that facilitate tumor growth. These altered networks may make tumor cells vulnerable to the inhibition of specific regulatory proteins. Consequently, the reconstruction of GRNs in tumors is often proposed as a means to identify therapeutic targets. While there are examples of individual targets identified using GRNs, the extent to which GRNs can be used to predict sensitivity to targeted intervention in general remains unknown. Here we use the results of genome-wide CRISPR screens to systematically assess the ability of GRNs to predict sensitivity to gene inhibition in cancer cell lines. Using GRNs derived from multiple sources, including GRNs reconstructed from tumor transcriptomes and from curated databases, we infer regulatory gene activity in cancer cell lines from ten cancer types. We then ask, in each cancer type, if the inferred regulatory activity of each gene is predictive of sensitivity to CRISPR perturbation of that gene. We observe slight variation in the correlation between gene regulatory activity and gene sensitivity depending on the source of the GRN and the activity estimation method used. However, we find that there is consistently a stronger relationship between mRNA abundance and gene sensitivity than there is between regulatory gene activity and gene sensitivity. This is true both when gene sensitivity is treated as a binary and a quantitative property. Overall, our results suggest that gene sensitivity is better predicted by measured expression than by GRN-inferred activity.

Dex-Benchmark: datasets and code to evaluate algorithms for transcriptomics data analysis

Many tools and algorithms are available for analyzing transcriptomics data. These include algorithms for performing sequence alignment, data normalization and imputation, clustering, identifying differentially expressed genes, and performing gene set enrichment analysis. To make the best choice about which tools to use, objective benchmarks can be developed to compare the quality of different algorithms to extract biological knowledge maximally and accurately from these data. The Dexamethasone Benchmark (Dex-Benchmark) resource aims to fill this need by providing the community with datasets and code templates for benchmarking different gene expression analysis tools and algorithms. The resource provides access to a collection of curated RNA-seq, L1000, and ChIP-seq data from dexamethasone treatment as well as genetic perturbations of its known targets. In addition, the website provides Jupyter Notebooks that use these pre-processed curated datasets to demonstrate how to benchmark the different steps in gene expression analysis. By comparing two independent data sources and data types with some expected concordance, we can assess which tools and algorithms best recover such associations. To demonstrate the usefulness of the resource for discovering novel drug targets, we applied it to optimize data processing strategies for the chemical perturbations and CRISPR single gene knockouts from the L1000 transcriptomics data from the Library of Integrated Network Cellular Signatures (LINCS) program, with a focus on understudied proteins from the Illuminating the Druggable Genome (IDG) program. Overall, the Dex-Benchmark resource can be utilized to assess the quality of transcriptomics and other related bioinformatics data analysis workflows. The resource is available from: https://maayanlab.github.io/dex-benchmark.

Revisiting the role of endogenous STAT3 in HPV-positive cervical cancer cells

Novel treatment options for human papillomavirus (HPV)-induced cancers are urgently required. The oncogenic transcription factor signal transducer and activator of transcription 3 (STAT3) is considered to be constitutively active in HPV-positive cervical cancer cells and essential for their proliferation. Moreover, STAT3 was reported to undergo mutually stimulatory interactions with the HPV E6/E7 oncogenes. Thus, inhibiting STAT3 in HPV-positive cancer cells is under discussion to provide a powerful novel therapeutic strategy. We here show that the antifungal drug ciclopirox destabilizes the STAT3 protein by acting as an iron chelator. However, by exploring the functional consequences of STAT3 inhibition in HPV-positive cancer cells, we obtained several unexpected results. Chemical STAT3 inhibitors heterogeneously affect cervical cancer cell proliferation and those which act antiproliferative also block the growth of STAT3 knockout cells, indicating induction of off-target effects. In contrast to several chemical inhibitors, genetic inhibition of STAT3 expression by either RNA interference or the CRISPR/Cas9 method does not appreciably affect cervical cancer cell proliferation. Transcriptome analyses indicate that blocking STAT3 expression in HPV-positive cancer cells has very limited effects on putative STAT3 target genes. Although the targeted inhibition of specific growth-promoting signaling pathways leads to a feedback activation of STAT3 in cervical cancer cells via Janus kinase 1/2, this does not lead to treatment resistance. Moreover, we did not obtain experimental evidence for a STAT3-linked activation of HPV E6/E7 oncogene expression or, vice versa, an E6/E7-dependent activation of STAT3, at endogenous conditions in cervical cancer cells. Collectively, these findings question the essential role of STAT3 in cervical cancer cell proliferation and the strategy to inhibit STAT3 in these cells for therapeutic purposes.

Exploring Cancer Dependency Map genes and immune subtypes in colon cancer, in which TIGD1 contributes to colon cancer progression

BACKGROUND

Tumour-dependent genes identified in CRISPR-Cas9 screens have been widely reported in Cancer Dependency Maps (CDMs). CDM-derived tumour-dependent genes play an important role in tumorigenesis and progression; however, they have not been investigated in colon cancer (CC).

METHODS

CDM genes overexpressed in CC were identified from the TCGA-COAD dataset and CDM platform. A CDM signature and prognostic nomogram were constructed by Lasso Cox regression and multivariate Cox analyses. A weighted correlation network analysis (WGCNA) and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. A comprehensive investigation was performed between the two subtypes and immune regulation, the immune microenvironment and the impact of immunotherapy.

RESULTS

First, 1304 overexpressed CDM genes were identified. Then, a CDM signature with five cancer-dependent genes (MMS19, NOP14, POLRMT, SNAPC5 and TIGD1) and a prognostic nomogram were constructed, and they demonstrated robust predictive performance and a close relationship with clinical characteristics in different CC datasets. Patients with high CDM risk scores showed worse survival outcome and weaker response to chemotherapy. Additionally, TIGD1 genes were oncogenes that affected the CC cell cycle, according to cell functional experiments that involved the suppression of the TIGD1 gene. Furthermore, WGCNA and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. Finally, systematic investigations were conducted with the relationship between the CDM subtypes and immune regulation.

CONCLUSIONS

This study constructed a CDM signature consisting of five risk genes that predict survival in CC patients. In addition, the immune subtypes provided valuable insights into immunotherapy for CC patients. TIGD1, as an oncogene, is independent prognostic factors for CC, and contributes to CC progression.

High-Throughput Identification, Modeling, and Analysis of Cancer Driver Genes In Vivo

The vast number of genomic and molecular alterations in cancer pose a substantial challenge to uncovering the mechanisms of tumorigenesis and identifying therapeutic targets. High-throughput functional genomic methods in genetically engineered mouse models allow for rapid and systematic investigation of cancer driver genes. In this review, we discuss the basic concepts and tools for multiplexed investigation of functionally important cancer genes in vivo using autochthonous cancer models. Furthermore, we highlight emerging technical advances in the field, potential opportunities for future investigation, and outline a vision for integrating multiplexed genetic perturbations with detailed molecular analyses to advance our understanding of the genetic and molecular basis of cancer.

Efficient CRISPR/Cas9-Mediated BAX Gene Ablation in CHO Cells To Impair Apoptosis and Enhance Recombinant Protein Production

Background

Despite recent advances in recombinant biotherapeutics production using CHO cells, their productivity remains lower than industrial needs, mainly due to apoptosis.

Objectives

Present study aimed to exploit CRISPR/Cas9 technology to specifically disrupt the BAX gene to attenuate apoptosis in recombinant Chinese hamster's ovary cells producing erythropoietin.

Materials and Methods

The STRING database was used to identify the key pro-apoptotic genes to be modified by CRISPR/Cas9 technique. The single guide RNAs (sgRNAs) targeting identified gene (BAX) were designed, and CHO cells were then transfected with vectors. Afterward, changes in the expression of the Bax gene and consequent production rates of erythropoietin were investigated in manipulated cells, even in the presence of an apoptosis inducer agent, oleuropein.

Results

BAX disruption significantly prolonged cell viability and increased proliferation rate in manipulated clones (152%, P-value = 0.0002). This strategy reduced the levels of Bax protein expression in manipulated cells by more than 4.3-fold (P-value <0.0001). The Bax-8 manipulated cells displayed higher threshold tolerance to the stress and consequence apoptosis compared to the control group. Also, they exhibited a higher IC50 compared to the control in the presence of oleuropein (5095 µM.ml^-1 Vs. 2505 µM.ml^-1). We found a significant increase in recombinant protein production levels in manipulated cells, even in the presence of 1,000 µM oleuropein compared to the control cell line (p-value=0.0002).

Conclusions

CRISPR/Cas9 assisted BAX gene ablation is promising to improve erythropoietin production in CHO cells via engineering anti-apoptotic genes. Therefore, exploiting genome editing tools such as CRISPR/Cas9 has been proposed to develop host cells that result in a safe, feasible, and robust manufacturing operation with a yield that meets the industrial requirements.

Large-scale genome editing in plants: approaches, applications, and future perspectives

As a powerful genome editing technology, CRISPR/Cas is revolutionizing both fundamental research and crop breeding, and has now evolved into large-scale editing tools that are efficient, simple, and programmable. With such CRISPR screening technologies, the numbers of genome-edited crops are rapidly increasing. Here, we describe the general workflow of a CRISPR screen in plants, including the selection of appropriate editors, genome-wide guide RNA design, pooled library construction, massive transformation, and high-throughput genotyping. We also discuss applications for the screening of candidate genes, the optimization of spatiotemporal expression, the evolution of protein activities, and the establishment of genome-wide libraries of knockout mutant. After considering the current challenges and limitations, we finally envision a virus-mediated strategy to improve CRISPR screens.

Applications of CRISPR/Cas genome editing in economically important fruit crops: recent advances and future directions

Fruit crops, consist of climacteric and non-climacteric fruits, are the major sources of nutrients and fiber for human diet. Since 2013, CRISPR/Cas (Clustered Regularly Interspersed Short Palindromic Repeats and CRISPR-Associated Protein) genome editing system has been widely employed in different plants, leading to unprecedented progress in the genetic improvement of many agronomically important fruit crops. Here, we summarize latest advancements in CRISPR/Cas genome editing of fruit crops, including efforts to decipher the mechanisms behind plant development and plant immunity, We also highlight the potential challenges and improvements in the application of genome editing tools to fruit crops, including optimizing the expression of CRISPR/Cas cassette, improving the delivery efficiency of CRISPR/Cas reagents, increasing the specificity of genome editing, and optimizing the transformation and regeneration system. In addition, we propose the perspectives on the application of genome editing in crop breeding especially in fruit crops and highlight the potential challenges. It is worth noting that efforts to manipulate fruit crops with genome editing systems are urgently needed for fruit crops breeding and demonstration.

Synthetic lethal gene pairs: Experimental approaches and predictive models

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

The double life of CRISPR-Cas13

Since the discovery of RNA-programmable nucleases from the prokaryotic adaptive immune system CRISPR-Cas, these proteins have seen rapid and widespread adoption for biotechnological and clinical research. A recently discovered system, CRISPR-Cas13, uses CRISPR RNA guides to target RNA. Interestingly, RNA targeting by Cas13 results in cleavage of both target RNA and bystander RNA. This feature has been used to develop innovative diagnostic tools for the detection of specific RNAs. Unlike in vitro detection of RNA using collateral RNA cleavage, however, initial studies of mammalian cells only revealed highly specific target RNA-knockdown activity. Although these findings have been confirmed subsequently, several recent publications do report Cas13-mediated toxicity and collateral RNA cleavage when using Cas13 in eukaryotes. Here, we review these conflicting observations and discuss its potential molecular basis.

Bioinformatics approaches to analyzing CRISPR screen data: from dropout screens to single-cell CRISPR screens

Background

Pooled CRISPR screen is a promising tool in drug targets or essential genes identification with the utilization of three different systems including CRISPR knockout (CRISPRko), CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa). Aside from continuous improvements in technology, more and more bioinformatics methods have been developed to analyze the data obtained by CRISPR screens which facilitate better understanding of physiological effects.

Results

Here, we provide an overview on the application of CRISPR screens and bioinformatics approaches to analyzing different types of CRISPR screen data. We also discuss mechanisms and underlying challenges for the analysis of dropout screens, sorting-based screens and single-cell screens.

Conclusion

Different analysis approaches should be chosen based on the design of screens. This review will help community to better design novel algorithms and provide suggestions for wet-lab researchers to choose from different analysis methods.

Targeting Caspase-3 Gene in rCHO Cell Line by CRISPR/Cas9 Editing Tool and Its Effect on Protein Production in Manipulated Cell Line

Background

Chinese hamster ovary (CHO) cells are the widely used mammalian cell host for biopharmaceutical manufacturing. During cell cultures, CHO cells lose viability mainly from apoptosis. Inhibiting cell death is useful because prolonging cell lifespans can direct to more productive cell culture systems for biotechnology requests.

Objectives

This study exploited a CRISPR/Cas9 technology to generate site-specific gene disruptions in the caspase-3 gene in the apoptosis pathway, which acts as an apoptotic regulator to extend cell viability in the CHO cell line.

Methods

The STRING database was used to identify the key pro-apoptotic genes to be modified by CRISPR/Cas9 system. The guide RNAs targeting the caspase-3 gene were designed, and vectors containing sgRNA and Cas9 were transfected into CHO cells that expressed erythropoietin as a heterologous protein. Indel formation was investigated by DNA sequencing. Caspase-3 expression was quantified by real-time PCR and western blot. The effect of editing the caspase-3 gene on the inhibition of apoptosis was also investigated by induction of apoptosis in manipulated cell lines by oleuropein. Finally, the erythropoietin production in the edited cells was compared to the control cells.

Results

The caspase-3 manipulation significantly prolongation of the cell viability and decreased the caspase-3 expression level of protein in manipulated CHO cells (more than 6-fold, P-value < 0.0001). Manipulated cells displayed higher threshold tolerance to apoptosis compared to the control cells when they were induced by oleuropein. They show a higher IC50 than the control ones (7271 µM/mL Vs. 5741 µM/mL). They also show a higher proliferation rate than the control cells in the presence of an apoptosis inducer (P-value < 0.0001). Furthermore, manipulated cell lines significantly produce more recombinant protein in the presence of 2,000 µM oleuropein compared to the control ones (P-value = 0.0021).

Conclusions

We understood that CRISPR/Cas9 could be effectively applied to suppress the expression of the caspase-3 gene and rescue CHO cells from apoptosis induced by cell stress and metabolites. The CRISPR/Cas9 system-assisted caspase-3 gene ablation can potentially increase erythropoietin yield in CHO cells.

Depletion of ALMS1 affects TGF-β signalling pathway and downstream processes such as cell migration and adhesion capacity

Background: ALMS1 is a ubiquitous gene associated with Alström syndrome (ALMS). The main symptoms of ALMS affect multiple organs and tissues, generating at last, multi-organic fibrosis in the lungs, kidneys and liver. TGF-β is one of the main pathways implicated in fibrosis, controlling the cell cycle, apoptosis, cell migration, cell adhesion and epithelial-mesenchymal transition (EMT). Nevertheless, the role of ALMS1 gene in fibrosis generation and other implicated processes such as cell migration or cell adhesion via the TGF- β pathway has not been elucidated yet. Methods: Initially, we evaluated how depletion of ALMS1 affects different processes like apoptosis, cell cycle and mitochondrial activity in HeLa cells. Then, we performed proteomic profiling with TGF-β stimuli in HeLa ALMS1 -/- cells and validated the results by examining different EMT biomarkers using qPCR. The expression of these EMT biomarkers were also studied in hTERT-BJ-5ta ALMS1 -/-. Finally, we evaluated the SMAD3 and SMAD2 phosphorylation and cell migration capacity in both models. Results: Depletion of ALMS1 generated apoptosis resistance to thapsigargin (THAP) and C2-Ceramide (C2-C), and G2/M cell cycle arrest in HeLa cells. For mitochondrial activity, results did not show significant differences between ALMS1 +/+ and ALMS1 -/-. Proteomic results showed inhibition of downstream pathways regulated by TGF-β. The protein-coding genes (PCG) were associated with processes like focal adhesion or cell-substrate adherens junction in HeLa. SNAI1 showed an opposite pattern to what would be expected when activating the EMT in HeLa and BJ-5ta. Finally, in BJ-5ta model a reduced activation of SMAD3 but not SMAD2 were also observed. In HeLa model no alterations in the canonical TGF-β pathway were observed but both cell lines showed a reduction in migration capacity. Conclusion: ALMS1 has a role in controlling the cell cycle and the apoptosis processes. Moreover, the depletion of ALMS1 affects the signal transduction through the TGF-β and other processes like the cell migration and adhesion capacity.

Optimization of specific RNA knockdown in mammalian cells with CRISPR-Cas13

Prokaryotic adaptive immune systems use Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) and CRISPR Associated (Cas) proteins to target and cleave foreign genetic elements in an RNA-guided manner [1-3]. Type VI CRISPR-Cas systems contain a single effector ribonuclease, Cas13, that binds and processes a CRISPR-RNA (crRNA; also known as a guide-RNA), forming an RNA-guided RNA-targeting effector complex [4,5]. Previous studies have shown that Cas13 can be engineered to target and modulate RNA processes in human cells, illustrating the versatility and specificity of Cas13 as an RNA knockdown (KD), splicing, editing, or imaging tool [6-8]. While Cas13 has been successfully used by several groups, our lab has observed significant variability in Cas13 KD ability depending which protocol is being followed [9-12]. To further understand this variability and generate a robust Cas13 KD protocol we thoroughly tested which Cas13 ortholog to use, the duration of KD experiments, the amount of plasmid DNA transfected, methods for analyzing KD efficiency, and report an optimized method for carrying out and analyzing Cas13 mediated RNA KD experiments. The method outlined in this paper illustrates a faster and more reliable protocol to iteratively test gRNA performance and target gene KD.

RISC-y Business: Limitations of Short Hairpin RNA-Mediated Gene Silencing in the Brain and a Discussion of CRISPR/Cas-Based Alternatives

Manipulating gene expression within and outside the nervous system is useful for interrogating gene function and developing therapeutic interventions for a variety of diseases. Several approaches exist which enable gene manipulation in preclinical models, and some of these have been approved to treat human diseases. For the last couple of decades, RNA interference (RNAi) has been a leading technique to knockdown (i.e., suppress) specific RNA expression. This has been partly due to the technology's simplicity, which has promoted its adoption throughout biomedical science. However, accumulating evidence indicates that this technology can possess significant shortcomings. This review highlights the overwhelming evidence that RNAi can be prone to off-target effects and is capable of inducing cytotoxicity in some cases. With this in mind, we consider alternative CRISPR/Cas-based approaches, which may be safer and more reliable for gene knockdown. We also discuss the pros and cons of each approach.

Efficient silencing of hepatitis B virus S gene through CRISPR-mediated base editing

Hepatitis B virus (HBV) infection is a major risk factor of liver cirrhosis and hepatocellular carcinoma. Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has been used to precisely edit the HBV genome and eliminate HBV through non-homologous end-joining repair of double-stranded break (DSB). However, the CRISPR/Cas9-mediated DSB triggers instability of host genome and exhibits low efficiency to edit genome, limiting its application. CRISPR cytidine base editors (CBEs) could silence genes by generating a premature stop codon. Here we developed a CRISPR base editor approach to precisely edit single nucleotide within the HBV genome to impair HBV gene expression. Specifically, a single-guide RNA (sgRNA) was designed to edit the 30th codon of HBV S gene, which encodes HBV surface antigen (HBsAg), from CAG (glutamine) to stop codon TAG. We next used human hepatoma PLC/PRF/5 cells carrying the HBV genome to establish a cell line that expresses a CBE (PLC/PRF/5-CBE). Lentivirus was used to introduce sgRNA into PLC/PRF/5-CBE cells. Phenotypically, 71% of PLC/PRF/5-CBE cells developed a premature stop codon within the S gene. Levels of HBs messenger RNA were significantly decreased. A 92% reduction of HBsAg secretion was observed in PLC/PRF/5-CBE cells. The intracellular HBsAg was also reduced by 84% after treatment of gRNA_S. Furthermore, no off-target effect was detected in predicted off-target loci within the HBV genome. Sequencing confirmed that 95%, 93%, 93%, 9%, and 72% S gene sequences of HBV genotypes B, C, F, G, and H had the binding site of sgRNA. Conclusion: Our findings indicate that CRISPR-mediated base editing is an efficient approach to silence the HBV S gene, suggesting its therapeutic potential to eliminate HBV.

Designing libraries for pooled CRISPR functional screens of long noncoding RNAs

Human and other genomes encode tens of thousands of long noncoding RNAs (lncRNAs), the vast majority of which remain uncharacterised. High-throughput functional screening methods, notably those based on pooled CRISPR-Cas perturbations, promise to unlock the biological significance and biomedical potential of lncRNAs. Such screens are based on libraries of single guide RNAs (sgRNAs) whose design is critical for success. Few off-the-shelf libraries are presently available, and lncRNAs tend to have cell-type-specific expression profiles, meaning that library design remains in the hands of researchers. Here we introduce the topic of pooled CRISPR screens for lncRNAs and guide readers through the three key steps of library design: accurate annotation of transcript structures, curation of optimal candidate sets, and design of sgRNAs. This review is a starting point and reference for researchers seeking to design custom CRISPR screening libraries for lncRNAs.

CRISPR genome surgery in a novel humanized model for autosomal dominant retinitis pigmentosa

Mutations in rhodopsin (RHO) are the most common causes of autosomal dominant retinitis pigmentosa (adRP), accounting for 20% to 30% of all cases worldwide. However, the high degree of genetic heterogeneity makes development of effective therapies cumbersome. To provide a universal solution to RHO-related adRP, we devised a CRISPR-based, mutation-independent gene ablation and replacement (AR) compound therapy carried by a dual AAV2/8 system. Moreover, we developed a novel hRHOC110R/hRHOWT humanized mouse model to assess the AR treatment in vivo. Results show that this humanized RHO mouse model exhibits progressive rod-cone degeneration that phenocopies hRHOC110R/hRHOWT patients. In vivo transduction of AR AAV8 dual vectors remarkably ablates endogenous RHO expression and overexpresses exogenous WT hRHO. Furthermore, the administration of AR during adulthood significantly hampers photoreceptor degeneration both histologically and functionally for at least 6 months compared with sole gene replacement or surgical trauma control. This study demonstrates the effectiveness of AR treatment of adRP in the human genomic context while revealing the feasibility of its application for other autosomal dominant disorders.

Knockout of Sf-Caspase-1 generates apoptosis-resistant Sf9 cell lines: Implications for baculovirus expression

The Sf9 cell line, originally isolated from the insect Spodoptera frugiperda, is commonly used alongside the baculovirus expression vector system (BEVS) to produce recombinant proteins and other biologics. As more BEVS-derived vaccines and therapeutics are approved by regulators and manufactured at scale, there is increasing interest in improving the Sf9 cell line to improve bioprocess robustness and increase product yields. CRISPR-Cas9 is a powerful genome-editing tool with great potential to improve cell line characteristics. Nevertheless, reports of genome-editing in Sf9 cells are scarce, and targets for engineering are elusive. To evaluate the effectiveness of CRISPR-Cas9 to improve BEVS yields, we generated Sf9 cell lines with functional knockouts in the Sf-Caspase-1 gene, which encodes an effector caspase involved in the execution of apoptosis. Deletion of Sf-Caspase-1 abolished the hallmarks of apoptotic cell death including plasma membrane blebbing and effector caspase activity. Following infection of Sf-Caspase-1 knockout Sf9 cultures with a recombinant baculovirus expressing β-galactosidase, we did not observe any differences in cell death kinetics or increases in productivity. Similar results were obtained when Sf-Caspase-1 expression was suppressed via RNA interference. We anticipate that the CRISPR-Cas9 workflow reported here will spur future efforts to rationally engineer Sf9 cells for improved baculovirus expression. This article is protected by copyright. All rights reserved.

Modulating intracellular pathways to improve non-viral delivery of RNA therapeutics

RNA therapeutics (e.g. siRNA, oligonucleotides, mRNA, etc.) show great potential for the treatment of a myriad of diseases. However, to reach their site of action in the cytosol or nucleus of target cells, multiple intra- and extracellular barriers have to be surmounted. Several non-viral delivery systems, such as nanoparticles and conjugates, have been successfully developed to meet this requirement. Unfortunately, despite these clear advances, state-of-the-art delivery agents still suffer from relatively low intracellular delivery efficiencies. Notably, our current understanding of the intracellular delivery process is largely oversimplified. Gaining mechanistic insight into how RNA formulations are processed by cells will fuel rational design of the next generation of delivery carriers. In addition, identifying which intracellular pathways contribute to productive RNA delivery could provide opportunities to boost the delivery performance of existing nanoformulations. In this review, we discuss both established as well as emerging techniques that can be used to assess the impact of different intracellular barriers on RNA transfection performance. Next, we highlight how several modulators, including small molecules but also genetic perturbation technologies, can boost RNA delivery by intervening at differing stages of the intracellular delivery process, such as cellular uptake, intracellular trafficking, endosomal escape, autophagy and exocytosis.

Combination of genetically engineered T cells and immune checkpoint blockade for the treatment of cancer

Immune checkpoint (IC) blockade using monoclonal antibodies is currently one of the most successful immunotherapeutic interventions to treat cancer. By reinvigorating antitumor exhausted T cells, this approach can lead to durable clinical responses. However, the majority of patients either does not respond or present a short-lived response to IC blockade, in part due to a scarcity of tumor-specific T cells within the tumor microenvironment. Adoptive transfer of T cells genetically engineered to express chimeric antigen receptors (CARs) or engineered T cell receptors (TCRs) provide the necessary tumor-specific immune cell population to target cancer cells. However, this therapy has been considerably ineffective against solid tumors in part due to IC-mediated immunosuppressive effects within tumor microenvironment. These limitations could be overcome by associating adoptive cell transfer of genetically engineered T cells and IC blockade. In this comprehensive review, we highlight the strategies and outcomes of preclinical and clinical attempts to disrupt IC signaling in adoptive T cell transfer against cancer. These strategies include combined administration of genetically engineered T cells and IC inhibitors, engineered T cells with intrinsic modifications to disrupt IC signaling and the design of CARs against IC molecules. The current landscape indicates that the synergy of the fast-paced refinements of gene-editing technologies and synthetic biology and the increased comprehension of IC signaling will certainly translate into novel and more effective immunotherapeutic approaches to treat patients with cancer.

Fluorescence Lifetime Imaging Probes for Cell-Based Measurements of Enzyme Activity

Posttranslational modification (PTM) enzymes are important modulators of protein structure and function. They typically act by chemically modifying amino acids, often on side chain functional groups, to change the physiochemical landscape of the protein and thus its biophysical behavior. In particular, protein kinases are enzymes that transfer phosphate from ATP to serine, threonine, or tyrosine in protein substrates. They are key regulators of vital cellular pathways such as survival, proliferation, and apoptosis, and their dysregulation in the context of cancer has been widely investigated for the purpose of development of anticancer drugs. However, several critical questions pertaining to their physiology, such as heterogeneity of kinase signaling within and between cells, and other factors that may play into the mechanisms of drug resistance, remain unanswered. Many of the current strategies to measure kinase activity lack the scope, subcellular resolution, and real-time monitoring ability needed to obtain the type of information needed about their dynamics and localization in cells. While FRET-based biosensors are capable of dynamic single cell imaging, their applications can be limited by difficulties in multiplexing and the inherent inadequacies of steady state measurements. In this chapter, we describe our fluorescence lifetime imaging microscopy (FLIM) probe technology in which peptide kinase substrates, linked to cell-penetrating peptides and labeled with small molecule fluorophores, are used to report kinase activity through time-resolved fluorescence imaging to visualize and quantify changes to the probe's fluorescence lifetime. These can be multiplexed for more than one kinase at a time, and interpretation is not affected by differences in local intensity due to probe uptake and distribution or photobleaching. With careful choice of peptide substrate(s), fluorophore label, and imaging set-up, high specificity and spatiotemporal resolution can be achieved. Due to the mechanism by which the lifetime change occurs, this approach is compatible with other PTMs (such as acetylation, methylation), and so the considerations for kinase FLIM probe design described in this chapter should be broadly applicable for other PTMs as well.

CRISPR-Based Screening for Stress Response Factors in Mammalian Cells

In the presence of different physiological and environmental stresses, cells rapidly initiate stress responses to re-establish cellular homeostasis. Stress responses usually orchestrate both transcriptional and translational programs via distinct mechanisms. With the advance of transcriptomics and proteomics technologies, transcriptional and translational outputs to a particular stress condition have become easier to measure; however, these technologies lack the ability to reveal the upstream regulatory pathways. Unbiased genetic screens based on a transcriptional or translational reporter are powerful approaches to identify regulatory factors of a specific stress response. CRISPR/Cas-based technologies, together with next-generation sequencing, enable genome-scale pooled screens to systematically elucidate gene function in mammalian cells, with a significant reduction in the rate of off-target effects compared to the previously used RNAi technology. Here, we describe our fluorescence-activated cell sorting (FACS)-based CRISPR interference (CRISPRi) screening platform using a translational reporter to identify novel genetic factors of the mitochondrial stress response in mammalian cells. This protocol provides a general framework for scientists who wish to establish a reporter-based CRISPRi screening platform to address questions in their area of research.

Gene Editing Technologies for Sugarcane Improvement: Opportunities and Limitations

Plant-based biofuels present a promising alternative to depleting non-renewable fuel resources. One of the benefits of biofuel is reduced environmental impact, including reduction in greenhouse gas emission which causes climate change. Sugarcane is one of the most important bioenergy crops. Sugarcane juice is used to produce table sugar and first-generation biofuel (e.g., bioethanol). Sugarcane bagasse is also a potential material for second-generation cellulosic biofuel production. Researchers worldwide are striving to improve sugarcane biomass yield and quality by a variety of means including biotechnological tools. This paper reviews the use of sugarcane as a feedstock for biofuel production, and gene manipulation tools and approaches, including RNAi and genome-editing tools, such as TALENs and CRISPR-Cas9, for improving its quality. The specific focus here is on CRISPR system because it is low cost, simple in design and versatile compared to other genome-editing tools. The advance of CRISPR-Cas9 technology has transformed plant research with its ability to precisely delete, insert or replace genes in recent years. Lignin is the primary material responsible for biomass recalcitrance in biofuel production. The use of genome editing technology to modify lignin composition and distribution in sugarcane cell wall has been realized. The current and potential applications of genome editing technology for sugarcane improvement are discussed. The advantages and limitations of utilizing RNAi and TALEN techniques in sugarcane improvement are discussed as well.

Identification of transcriptional regulatory network associated with response of host epithelial cells to SARS-CoV-2

Identification of transcriptional regulatory mechanisms and signaling networks involved in the response of host cells to infection by SARS-CoV-2 is a powerful approach that provides a systems biology view of gene expression programs involved in COVID-19 and may enable the identification of novel therapeutic targets and strategies to mitigate the impact of this disease. In this study, our goal was to identify a transcriptional regulatory network that is associated with gene expression changes between samples infected by SARS-CoV-2 and those that are infected by other respiratory viruses to narrow the results on those enriched or specific to SARS-CoV-2. We combined a series of recently developed computational tools to identify transcriptional regulatory mechanisms involved in the response of epithelial cells to infection by SARS-CoV-2, and particularly regulatory mechanisms that are specific to this virus when compared to other viruses. In addition, using network-guided analyses, we identified kinases associated with this network. The results identified pathways associated with regulation of inflammation (MAPK14) and immunity (BTK, MBX) that may contribute to exacerbate organ damage linked with complications of COVID-19. The regulatory network identified herein reflects a combination of known hits and novel candidate pathways supporting the novel computational pipeline presented herein to quickly narrow down promising avenues of investigation when facing an emerging and novel disease such as COVID-19.

Host directed therapies: COVID-19 and beyond

The global spread of SARS-CoV-2 has necessitated the development of novel, safe and effective therapeutic agents against this virus to stop the pandemic, however the development of novel antivirals may take years, hence, the best alternative available, is to repurpose the existing antiviral drugs with known safety profile in humans. After more than one year into this pandemic, global efforts have yielded the fruits and with the launch of many vaccines in the market, the world is inching towards the end of this pandemic, nonetheless, future pandemics of this magnitude or even greater cannot be denied. The preparedness against viruses of unknown origin should be maintained and the broad-spectrum antivirals with activity against range of viruses should be developed to curb future viral pandemics. The majority of antivirals developed till date are pathogen specific agents, which target critical viral pathways and lack broad spectrum activity required to target wide range of viruses. The surge in drug resistance among pathogens has rendered a compelling need to shift our focus towards host directed factors in the treatment of infectious diseases. This gains special relevance in the case of viral infections, where the pathogen encodes a handful of genes and predominantly depends on host factors for their propagation and persistence. Therefore, future antiviral drug development should focus more on targeting molecules of host pathways that are often hijacked by many viruses. Such cellular proteins of host pathways offer attractive targets for the development of broad-spectrum anticipatory antivirals. In the present article, we have reviewed the host directed therapies (HDTs) effective against viral infections with a special focus on COVID-19. This article also discusses the strategies involved in identifying novel host targets and subsequent development of broad spectrum HDTs.

Utilizing graph machine learning within drug discovery and development

Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development. After introducing key terms and modelling approaches, we move chronologically through the drug development pipeline to identify and summarize work incorporating: target identification, design of small molecules and biologics, and drug repurposing. Whilst the field is still emerging, key milestones including repurposed drugs entering in vivo studies, suggest GML will become a modelling framework of choice within biomedical machine learning.

Current Status and Perspectives on the Application of CRISPR/Cas9 Gene-Editing System to Develop a Low-Gluten, Non-Transgenic Wheat Variety

Wheat gluten contains epitopes that trigger celiac disease (CD). A life-long strict gluten-free diet is the only treatment accepted for CD. However, very low-gluten wheat may provide an alternative treatment to CD. Conventional plant breeding methods have not been sufficient to produce celiac-safe wheat. RNA interference technology, to some extent, has succeeded in the development of safer wheat varieties. However, these varieties have multiple challenges in terms of their implementation. Clustered Regularly Interspaced Short Palindromic Repeats-associated nuclease 9 (CRISPR/Cas9) is a versatile gene-editing tool that has the ability to edit immunogenic gluten genes. So far, only a few studies have applied CRISPR/Cas9 to modify the wheat genome. In this article, we reviewed the published literature that applied CRISPR/Cas9 in wheat genome editing to investigate the current status of the CRISPR/Cas9 system to produce a low-immunogenic wheat variety. We found that in recent years, the CRISPR/Cas9 system has been continuously improved to edit the complex hexaploid wheat genome. Although some reduced immunogenic wheat varieties have been reported, CRISPR/Cas9 has still not been fully explored in terms of editing the wheat genome. We conclude that further studies are required to apply the CRISPR/Cas9 gene-editing system efficiently for the development of a celiac-safe wheat variety and to establish it as a "tool to celiac safe wheat".

Microbe-Mediated Activation of Toll-like Receptor 2 Drives PDL1 Expression in HNSCC

Simple Summary

Tumors use immunosuppressive signals to evade detection by the immune system. While recurrent and metastatic head and neck squamous cell carcinoma has historically carried a poor prognosis, therapies targeting the immunosuppressive PD1:PDL1 axis have improved survival in certain patients. Defining mechanisms regulating PDL1 in various contexts may inform refinement of immunotherapy protocols. We identified a role for Toll-like Receptor 2 (TLR2) signaling in driving PDL1 expression. In antigen-presenting cells, TLR2 functions to initiate response to pathogens, and it is overexpressed or genetically altered in some tumors. We found that the synthetic TLR2 ligand Pam3CSK4, as well as whole bacteria, induced PDL1 expression in specific HNSCC cell line models, suggesting that TLR2 may contribute to immune evasion in chronically inflamed tissues.

Abstract

As immunotherapies targeting the PDL1 checkpoint have become a mainstay of treatment for a subset of head and neck squamous cell carcinoma (HNSCC) patients, a detailed understanding of the mechanisms underlying PDL1-mediated immune evasion is needed. To elucidate factors regulating expression of PDL1 in HNSCC cells, a genome-wide CRISPR profiling approach was implemented to identify genes and pathways conferring altered PDL1 expression in an HNSCC cell line model. Our screen nominated several candidate PDL1 drivers, including Toll-like Receptor 2 (TLR2). Depletion of TLR2 blocks interferon-γ-induced PDL1 expression, and stimulation of TLR2 with either Staphylococcus aureus or a bacterial lipopeptide mimetic, Pam3CSK4, enhanced PDL1 expression in multiple models. The data herein demonstrate a role for TLR2 in modulating the expression of PDL1 in HNSCC models and suggest that microbiota may directly modulate immunosuppression in cancer cells. Our study represents a step toward disentangling the diverse pathways and stimuli regulating PDL1 expression in HNSCC and underscores a need for future work to characterize the complex microbiome in HNSCC patients treated with immunotherapy.

The COP9 signalosome subunit 3 is necessary for early embryo survival by way of a stable protein deposit in mouse oocytes

Investigations of genes required in early mammalian development are complicated by protein deposits of maternal products, which continue to operate after the gene locus has been disrupted. This leads to delayed phenotypic manifestations and underestimation of the number of genes known to be needed during the embryonic phase of cellular totipotency. Here we expose a critical role of the gene Cops3 by showing that it protects genome integrity during the 2-cell stage of mouse development, in contrast to the previous functional assignment at postimplantation. This new role is mediated by a substantial deposit of protein (94th percentile of the proteome), divided between an exceptionally stable cortical rim, which is prevalent in oocytes, and an ancillary deposit in the embryonic nuclei. Since protein abundance and stability defeat prospects of DNA- or RNA-based gene inactivation in oocytes, we harnessed a classical method next to an emerging method for protein inactivation: antigen masking (for functional inhibition) versus TRIM21-mediated proteasomal degradation, also known as 'Trim away' (for physical removal). Both resulted in 2-cell embryo lethality, unlike the embryos receiving anti-green fluorescent protein. Comparisons between COPS3 protein-targeted and non-targeted embryos revealed large-scale transcriptome differences, which were most evident for genes associated with biological functions critical for RNA metabolism and for the preservation of genome integrity. The gene expression abnormalities associated with COPS3 inactivation were confirmed in situ by the occurrence of DNA endoreduplication and DNA strand breaks in 2-cell embryos. These results recruit Cops3 to the small family of genes that are necessary for early embryo survival. Overall, assigning genes with roles in embryogenesis may be less safe than assumed, if the protein products of these genes accumulate in oocytes: the inactivation of a gene at the protein level can expose an earlier phenotype than that identified by genetic techniques such as conventional gene silencing.

The Mammalian Family of Katanin Microtubule-Severing Enzymes

The katanin family of microtubule-severing enzymes is critical for cytoskeletal rearrangements that affect key cellular processes like division, migration, signaling, and homeostasis. In humans, aberrant expression, or dysfunction of the katanins, is linked to developmental, proliferative, and neurodegenerative disorders. Here, we review current knowledge on the mammalian family of katanins, including an overview of evolutionary conservation, functional domain organization, and the mechanisms that regulate katanin activity. We assess the function of katanins in dividing and non-dividing cells and how their dysregulation promotes impaired ciliary signaling and defects in developmental programs (corticogenesis, gametogenesis, and neurodevelopment) and contributes to neurodegeneration and cancer. We conclude with perspectives on future katanin research that will advance our understanding of this exciting and dynamic class of disease-associated enzymes.

Predicting and characterizing a cancer dependency map of tumors with deep learning

Genome-wide loss-of-function screens have revealed genes essential for cancer cell proliferation, called cancer dependencies. It remains challenging to link cancer dependencies to the molecular compositions of cancer cells or to unscreened cell lines and further to tumors. Here, we present DeepDEP, a deep learning model that predicts cancer dependencies using integrative genomic profiles. It uses a unique unsupervised pretraining that captures unlabeled tumor genomic representations to improve the learning of cancer dependencies. We demonstrated DeepDEP's improvement over conventional machine learning methods and validated the performance with three independent datasets. By systematic model interpretations, we extended the current dependency maps with functional characterizations of dependencies and a proof-of-concept in silico assay of synthetic essentiality. We applied DeepDEP to pan-cancer tumor genomics and built the first pan-cancer synthetic dependency map of 8000 tumors with clinical relevance. In summary, DeepDEP is a novel tool for investigating cancer dependency with rapidly growing genomic resources.

ADAR and hnRNPC deficiency synergize in activating endogenous dsRNA-induced type I IFN responses

Cytosolic double-stranded RNA (dsRNA) initiates type I IFN responses. Endogenous retroelements, notably Alu elements, constitute a source of dsRNA. Adenosine-to-inosine (A-to-I) editing by ADAR induces mismatches in dsRNA and prevents recognition by MDA5 and autoinflammation. To identify additional endogenous dsRNA checkpoints, we conducted a candidate screen in THP-1 monocytes and found that hnRNPC and ADAR deficiency resulted in synergistic induction of MDA5-dependent IFN responses. RNA-seq analysis demonstrated dysregulation of Alu-containing introns in hnRNPC-deficient cells via utilization of unmasked cryptic splice sites, including introns containing ADAR-dependent A-to-I editing clusters. These putative MDA5 ligands showed reduced editing in the absence of ADAR, providing a plausible mechanism for the combined effects of hnRNPC and ADAR. This study contributes to our understanding of the control of repetitive element-induced autoinflammation and suggests that patients with hnRNPC-mutated tumors might maximally benefit from ADAR inhibition-based immunotherapy.

Genetic and pharmacological interrogation of cancer vulnerability using a multiplexed cell line screening platform

The multiplexed cancer cell line screening platform PRISM demonstrated its utility in testing hundreds of cell lines in a single run, possessing the potential to speed up anti-cancer drug discovery, validation and optimization. Here we described the development and implementation of a next-generation PRISM platform combining Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9-mediated gene editing, cell line DNA barcoding and next-generation sequencing to enable genetic and/or pharmacological assessment of target addiction in hundreds of cell lines simultaneously. Both compound and CRISPR-knockout PRISM screens well recapitulated the results from individual assays and showed high consistency with a public database.

Xia et al. report the development and optimization of a high-throughput screening platform to systematically determine cancer cell sensitivity to pharmacological and genetic perturbations, BMS-PRISM, based on PRISM and high-throughput CRISPR/Cas9 loss-of-function screen technologies using cell line barcoding.

Genome-wide CRISPR screen identifies protein pathways modulating tau protein levels in neurons

Aggregates of hyperphosphorylated tau protein are a pathological hallmark of more than 20 distinct neurodegenerative diseases, including Alzheimer’s disease, progressive supranuclear palsy, and frontotemporal dementia. While the exact mechanism of tau aggregation is unknown, the accumulation of aggregates correlates with disease progression. Here we report a genome-wide CRISPR screen to identify modulators of endogenous tau protein for the first time. Primary screens performed in SH-SY5Y cells, identified positive and negative regulators of tau protein levels. Hit validation of the top 43 candidate genes was performed using Ngn2-induced human cortical excitatory neurons. Using this approach, genes and pathways involved in modulation of endogenous tau levels were identified, including chromatin modifying enzymes, neddylation and ubiquitin pathway members, and components of the mTOR pathway. TSC1, a critical component of the mTOR pathway, was further validated in vivo, demonstrating the relevance of this screening strategy. These findings may have implications for treating neurodegenerative diseases in the future.

Using an unbiased genome-wide CRISPR screen approach, Sanchez et al. identified modulators of endogenous tau protein. This study suggests that chromatin modifiers, neddylation, ubiquitination, and the mTOR pathways regulate overall levels of tau protein in neurons, which could help in future identification of therapeutics for neurodegenerative diseases.

Liposome technologies towards colorectal cancer therapeutics

Colorectal cancer (CRC) is the third most common cancer and the fourth most common deadly cancer worldwide. After treatment with curative intent recurrence rates vary with staging 0-13% in Stage 1, 11-61% in S2 and 28-73% in Stage 3. The toxicity to healthy tissues from chemotherapy and radiotherapy and drug resistance severely affect the quality of life and cancer specific outcomes of CRC patients. To overcome some of these limitations, many efforts have been made to develop nanomaterial-based drug delivery systems. Among these nanocarriers, liposomes represented one of the most successful candidates in delivering targeted oncological treatment, improving safety profile and therapeutic efficacy of encapsulated drugs. In this review we will discuss liposome design with a particular focus on the targeting feature and triggering functions. We will also summarise the recent advances in liposomal delivery system for CRC treatment in both the preclinical and clinical studies. We will finally provide our perspectives on the liposome technology development for the future clinical translation. STATEMENT OF SIGNIFICANCE: Conventional treatments for colorectal cancer (CRC) severely affect the therapeutic effects for advanced patients. With the development of nanomedicines, liposomal delivery system appears to be one of the most promising nanocarriers for CRC treatment. In last three years several reviews in this area have been published focusing on the preclinical research and drug delivery function, which is a fairly narrow focus in the field of liposome technology for CRC therapy. Our review presented the most recent advances of the liposome technology (both clinical and preclinical applications) for CRC with strong potential for further clinical translation. We believe it will attract lots of attention from various audiences, including researchers, clinicians and the industry.

ER-mitochondria contact sites in neurodegeneration: genetic screening approaches to investigate novel disease mechanisms

Mitochondria-ER contact sites (MERCS) are known to underpin many important cellular homoeostatic functions, including mitochondrial quality control, lipid metabolism, calcium homoeostasis, the unfolded protein response and ER stress. These functions are known to be dysregulated in neurodegenerative diseases, including Parkinson's disease (PD), Alzheimer's disease (AD) and amyloid lateral sclerosis (ALS), and the number of disease-related proteins and genes being associated with MERCS is increasing. However, many details regarding MERCS and their role in neurodegenerative diseases remain unknown. In this review, we aim to summarise the current knowledge regarding the structure and function of MERCS, and to update the field on current research in PD, AD and ALS. Furthermore, we will evaluate high-throughput screening techniques, including RNAi vs CRISPR/Cas9, pooled vs arrayed formats and how these could be combined with current techniques to visualise MERCS. We will consider the advantages and disadvantages of each technique and how it can be utilised to uncover novel protein pathways involved in MERCS dysfunction in neurodegenerative diseases.

CRISPR screens in plants: approaches, guidelines, and future prospects

Clustered regularly interspaced short palindromic repeat (CRISPR)-associated systems have revolutionized genome engineering by facilitating a wide range of targeted DNA perturbations. These systems have resulted in the development of powerful new screens to test gene functions at the genomic scale. While there is tremendous potential to map and interrogate gene regulatory networks at unprecedented speed and scale using CRISPR screens, their implementation in plants remains in its infancy. Here we discuss the general concepts, tools, and workflows for establishing CRISPR screens in plants and analyze the handful of recent reports describing the use of this strategy to generate mutant knockout collections or to diversify DNA sequences. In addition, we provide insight into how to design CRISPR knockout screens in plants given the current challenges and limitations and examine multiple design options. Finally, we discuss the unique multiplexing capabilities of CRISPR screens to investigate redundant gene functions in highly duplicated plant genomes. Combinatorial mutant screens have the potential to routinely generate higher-order mutant collections and facilitate the characterization of gene networks. By integrating this approach with the numerous genomic profiles that have been generated over the past two decades, the implementation of CRISPR screens offers new opportunities to analyze plant genomes at deeper resolution and will lead to great advances in functional and synthetic biology.