Aged intestinal stem cells propagate cell-intrinsic sources of inflammaging in mice.

Low-grade chronic inflammation is a hallmark of ageing, associated with impaired tissue function and disease development. However, how cell-intrinsic and -extrinsic factors collectively establish this phenotype, termed inflammaging, remains poorly understood. We addressed this question in the mouse intestinal epithelium, using mouse organoid cultures to dissect stem cell-intrinsic and -extrinsic sources of inflammaging. At the single-cell level, we found that inflammaging is established differently along the crypt-villus axis, with aged intestinal stem cells (ISCs) strongly upregulating major histocompatibility complex class II (MHC-II) genes. Importantly, the inflammaging phenotype was stably propagated by aged ISCs in organoid cultures and associated with increased chromatin accessibility at inflammation-associated loci in vivo and ex vivo, indicating cell-intrinsic inflammatory memory. Mechanistically, we show that the expression of inflammatory genes is dependent on STAT1 signaling. Together, our data identify that intestinal inflammaging in mice is promoted by a cell-intrinsic mechanism, stably propagated by ISCs, and associated with a disbalance in immune homeostasis.

Enhanced SARS-CoV-2 entry via UPR-dependent AMPK-related kinase NUAK2.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) remodels the endoplasmic reticulum (ER) to form replication organelles, leading to ER stress and unfolded protein response (UPR). However, the role of specific UPR pathways in infection remains unclear. Here, we found that SARS-CoV-2 infection causes marginal activation of signaling sensor IRE1α leading to its phosphorylation, clustering in the form of dense ER-membrane rearrangements with embedded membrane openings, and XBP1 splicing. By investigating the factors regulated by IRE1α-XBP1 during SARS-CoV-2 infection, we identified stress-activated kinase NUAK2 as a novel host-dependency factor for SARS-CoV-2, HCoV-229E, and MERS-CoV entry. Reducing NUAK2 abundance or kinase activity impaired SARS-CoV-2 particle binding and internalization by decreasing cell surface levels of viral receptors and viral trafficking likely by modulating the actin cytoskeleton. IRE1α-dependent NUAK2 levels were elevated in SARS-CoV-2-infected and bystander non-infected cells, promoting viral spread by maintaining ACE2 cell surface levels and facilitating virion binding to bystander cells.

A global genetic interaction network by single-cell imaging and machine learning.

Cellular and organismal phenotypes are controlled by complex gene regulatory networks. However, reference maps of gene function are still scarce across different organisms. Here, we generated synthetic genetic interaction and cell morphology profiles of more than 6,800 genes in cultured Drosophila cells. The resulting map of genetic interactions was used for machine learning-based gene function discovery, assigning functions to genes in 47 modules. Furthermore, we devised Cytoclass as a method to dissect genetic interactions for discrete cell states at the single-cell resolution. This approach identified an interaction of Cdk2 and the Cop9 signalosome complex, triggering senescence-associated secretory phenotypes and immunogenic conversion in hemocytic cells. Together, our data constitute a genome-scale resource of functional gene profiles to uncover the mechanisms underlying genetic interactions and their plasticity at the single-cell level.

Targeting euchromatic histone lysine methyltransferases sensitizes colorectal cancer to histone deacetylase inhibitors.

Epigenetic dysregulation is an important feature of colorectal cancer (CRC). Combining epigenetic drugs with other antineoplastic agents is a promising treatment strategy for advanced cancers. Here, we exploited the concept of synthetic lethality to identify epigenetic targets that act synergistically with histone deacetylase (HDAC) inhibitors to reduce the growth of CRC. We applied a pooled CRISPR-Cas9 screen using a custom sgRNA library directed against 614 epigenetic regulators and discovered that knockout of the euchromatic histone-lysine N-methyltransferases 1 and 2 (EHMT1/2) strongly enhanced the antiproliferative effect of clinically used HDAC inhibitors. Using tissue microarrays from 1066 CRC samples with different tumor stages, we showed that low EHMT2 protein expression is predominantly found in advanced CRC and associated with poor clinical outcome. Cotargeting of HDAC and EHMT1/2 with specific small molecule inhibitors synergistically reduced proliferation of CRC cell lines. Mechanistically, we used a high-throughput Western blot assay to demonstrate that both inhibitors elicited distinct cellular mechanisms to reduce tumor growth, including cell cycle arrest and modulation of autophagy. On the epigenetic level, the compounds increased H3K9 acetylation and reduced H3K9 dimethylation. Finally, we used a panel of patient-derived CRC organoids to show that HDAC and EHMT1/2 inhibition synergistically reduced tumor viability in advanced models of CRC.

SARS-CoV-2 infection induces a pro-inflammatory cytokine response through cGAS-STING and NF-κB.

SARS-CoV-2 is a novel virus that has rapidly spread, causing a global pandemic. In the majority of infected patients, SARS-CoV-2 leads to mild disease; however, in a significant proportion of infections, individuals develop severe symptoms that can lead to long-lasting lung damage or death. These severe cases are often associated with high levels of pro-inflammatory cytokines and low antiviral responses, which can cause systemic complications. Here, we have evaluated transcriptional and cytokine secretion profiles and detected a distinct upregulation of inflammatory cytokines in infected cell cultures and samples taken from infected patients. Building on these observations, we found a specific activation of NF-κB and a block of IRF3 nuclear translocation in SARS-CoV-2 infected cells. This NF-κB response was mediated by cGAS-STING activation and could be attenuated through several STING-targeting drugs. Our results show that SARS-CoV-2 directs a cGAS-STING mediated, NF-κB-driven inflammatory immune response in human epithelial cells that likely contributes to inflammatory responses seen in patients and could be therapeutically targeted to suppress severe disease symptoms.

Cloud-Based Design of Short Guide RNA (sgRNA) Libraries for CRISPR Experiments.

CRISPR/Cas-based genome editing in any biological application requires the evaluation of suitable genomic target sites to design efficient reagents. Considerations for the design of short guide (sg) RNAs include the assessment of possible off-target activities, the prediction of on-target efficacies and mutational outcome. Manual design of sgRNAs taking into account these parameters, however, remains a difficult task. Thus, computational tools to design sgRNA reagents from small scale to genome-wide libraries have been developed that assist during all steps of the design process. Here, we will describe practical guidance for the sgRNA design process using the web-based tool E-CRISP used in the design of individual sgRNAs. E-CRISP ( www.e-crisp.org ) has been the first web-based sgRNA design tool and uniquely features simple, yet efficient, scoring schemes in combination with fast evaluation and simple usage. We will also discuss the installation of a dockerized version of CRISPR Library Designer (CLD) that can be deployed locally or in the cloud to support the end-to-end design of sgRNA libraries for more than 50 different organisms. CLD was built upon E-CRISP to further increase the scope of sgRNA design to more experimental modalities (CRISPRa/i, Cas12a, all possible protospacer adjacency motifs) offering the same flexibility as E-CRISP, plus the scalability through local and cloud installation. Together, these tools facilities the design of small and large-scale CRISPR/Cas experiments.

A large-scale resource for tissue-specific CRISPR mutagenesis in Drosophila.

Genetic screens are powerful tools for the functional annotation of genomes. In the context of multicellular organisms, interrogation of gene function is greatly facilitated by methods that allow spatial and temporal control of gene abrogation. Here, we describe a large-scale transgenic short guide (sg) RNA library for efficient CRISPR-based disruption of specific target genes in a constitutive or conditional manner. The library consists currently of more than 2600 plasmids and 1700 fly lines with a focus on targeting kinases, phosphatases and transcription factors, each expressing two sgRNAs under control of the Gal4/UAS system. We show that conditional CRISPR mutagenesis is robust across many target genes and can be efficiently employed in various somatic tissues, as well as the germline. In order to prevent artefacts commonly associated with excessive amounts of Cas9 protein, we have developed a series of novel UAS-Cas9 transgenes, which allow fine tuning of Cas9 expression to achieve high gene editing activity without detectable toxicity. Functional assays, as well as direct sequencing of genomic sgRNA target sites, indicates that the vast majority of transgenic sgRNA lines mediate efficient gene disruption. Furthermore, we conducted the so far largest fully transgenic CRISPR screen in any metazoan organism, which further supported the high efficiency and accuracy of our library and revealed many so far uncharacterized genes essential for development.

Twenty years after the release of the sequence of the human genome, the role of many genes is still unknown. This is partly because some of these genes may only be active in specific types of cells or for short periods of time, which makes them difficult to study. A powerful way to gather information about human genes is to examine their equivalents in 'model' animals such as fruit flies. Researchers can use genetic methods to create strains of insects where genes are deactivated; evaluating the impact of these manipulations on the animals helps to understand the roles of the defunct genes. However, the current methods struggle to easily delete target genes, especially only in certain cells, or at precise times. Here, Port et al. genetically engineered flies that carry CRISPR-Cas9, a biological system that can be programmed to 'cut' and mutate precise genetic sequences. The insects were also manipulated in such a way that the CRISPR elements could be switched on at will, and their quantity finely tuned. This work resulted in a collection of more than 1,700 fruit fly strains in which specific genes could be deactivated on demand in precise cells. Further experiments confirmed that this CRISPR system could mutate target genes in different parts of the fly, including in the eyes, gut and wings. Port et al. have made their collection of genetically engineered fruit flies publically available, so that other researchers can use the strains in their experiments. The CRISPR technology they refined and developed may also lay the foundation for similar collections in other model organisms.

Time-resolved mapping of genetic interactions to model rewiring of signaling pathways.

Context-dependent changes in genetic interactions are an important feature of cellular pathways and their varying responses under different environmental conditions. However, methodological frameworks to investigate the plasticity of genetic interaction networks over time or in response to external stresses are largely lacking. To analyze the plasticity of genetic interactions, we performed a combinatorial RNAi screen in Drosophila cells at multiple time points and after pharmacological inhibition of Ras signaling activity. Using an image-based morphology assay to capture a broad range of phenotypes, we assessed the effect of 12768 pairwise RNAi perturbations in six different conditions. We found that genetic interactions form in different trajectories and developed an algorithm, termed MODIFI, to analyze how genetic interactions rewire over time. Using this framework, we identified more statistically significant interactions compared to end-point assays and further observed several examples of context-dependent crosstalk between signaling pathways such as an interaction between Ras and Rel which is dependent on MEK activity. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Machine learning and image-based profiling in drug discovery.

The increase in imaging throughput, new analytical frameworks and high-performance computational resources open new avenues for data-rich phenotypic profiling of small molecules in drug discovery. Image-based profiling assays assessing single-cell phenotypes have been used to explore mechanisms of action, target efficacy and toxicity of small molecules. Technological advances to generate large data sets together with new machine learning approaches for the analysis of high-dimensional profiling data create opportunities to improve many steps in drug discovery. In this review, we will discuss how recent studies applied machine learning approaches in functional profiling workflows with a focus on chemical genetics. While their utility in image-based screening and profiling is predictably evident, examples of novel insights beyond the status quo based on the applications of machine learning approaches are just beginning to emerge. To enable discoveries, future studies also need to develop methodologies that lower the entry barriers to high-throughput profiling experiments by streamlining image-based profiling assays and providing applications for advanced learning technologies such as easy to deploy deep neural networks.

RNA Interference (RNAi) Screening in Drosophila.

In the last decade, RNA interference (RNAi), a cellular mechanism that uses RNA-guided degradation of messenger RNA transcripts, has had an important impact on identifying and characterizing gene function. First discovered in Caenorhabditis elegans, RNAi can be used to silence the expression of genes through introduction of exogenous double-stranded RNA into cells. In Drosophila, RNAi has been applied in cultured cells or in vivo to perturb the function of single genes or to systematically probe gene function on a genome-wide scale. In this review, we will describe the use of RNAi to study gene function in Drosophila with a particular focus on high-throughput screening methods applied in cultured cells. We will discuss available reagent libraries and cell lines, methodological approaches for cell-based assays, and computational methods for the analysis of high-throughput screens. Furthermore, we will review the generation and use of genome-scale RNAi libraries for tissue-specific knockdown analysis in vivo and discuss the differences and similarities with the use of genome-engineering methods such as CRISPR/Cas9 for functional analysis.

Toward an integrated map of genetic interactions in cancer cells.

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and create vulnerabilities for potential therapeutic exploitation. To identify genotype-dependent vulnerabilities, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework to integrate CRISPR/Cas9 screens originating from different libraries building on approaches pioneered for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cells combining functional data with information on genetic variants to explore more than 2.1 million gene-background relationships. In addition to known dependencies, we identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities identified GANAB and PRKCSH as new positive regulators of Wnt/ß-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data are included.

Data-analysis strategies for image-based cell profiling.

Image-based cell profiling is a high-throughput strategy for the quantification of phenotypic differences among a variety of cell populations. It paves the way to studying biological systems on a large scale by using chemical and genetic perturbations. The general workflow for this technology involves image acquisition with high-throughput microscopy systems and subsequent image processing and analysis. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

HTSvis: a web app for exploratory data analysis and visualization of arrayed high-throughput screens.

SUMMARY: Arrayed high-throughput screens (HTS) cover a broad range of applications using RNAi or small molecules as perturbations and specialized software packages for statistical analysis have become available. However, exploratory data analysis and integration of screening results has remained challenging due to the size of the data sets and the lack of user-friendly tools for interpretation and visualization of screening results. Here we present HTSvis, a web application to interactively visualize raw data, perform quality control and assess screening results from single to multi-channel measurements such as image-based screens. Per well aggregated raw and analyzed data of various assay types and scales can be loaded in a generic tabular format. AVAILABILITY AND IMPLEMENTATION: HTSvis is distributed as an open-source R package, downloadable from https://github.com/boutroslab/HTSvis and can also be accessed at http://htsvis.dkfz.de . CONTACT: m.boutros@dkfz.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online .

GenomeCRISPR - a database for high-throughput CRISPR/Cas9 screens.

Over the past years, CRISPR/Cas9 mediated genome editing has developed into a powerful tool for modifying genomes in various organisms. In high-throughput screens, CRISPR/Cas9 mediated gene perturbations can be used for the systematic functional analysis of whole genomes. Discoveries from such screens provide a wealth of knowledge about gene to phenotype relationships in various biological model systems. However, a database resource to query results efficiently has been lacking. To this end, we developed GenomeCRISPR (http://genomecrispr.org), a database for genome-scale CRISPR/Cas9 screens. Currently, GenomeCRISPR contains data on more than 550 000 single guide RNAs (sgRNA) derived from 84 different experiments performed in 48 different human cell lines, comprising all screens in human cells using CRISPR/Cas published to date. GenomeCRISPR provides data mining options and tools, such as gene or genomic region search. Phenotypic and genome track views allow users to investigate and compare the results of different screens, or the impact of different sgRNAs on the gene of interest. An Application Programming Interface (API) allows for automated data access and batch download. As more screening data will become available, we also aim at extending the database to include functional genomic data from other organisms and enable cross-species comparisons.

CRISPR library designer (CLD): software for multispecies design of single guide RNA libraries.

BACKGROUND: Genetic screens using CRISPR/Cas9 are a powerful method for the functional analysis of genomes. RESULTS: Here we describe CRISPR library designer (CLD), an integrated bioinformatics application for the design of custom single guide RNA (sgRNA) libraries for all organisms with annotated genomes. CLD is suitable for the design of libraries using modified CRISPR enzymes and targeting non-coding regions. To demonstrate its utility, we perform a pooled screen for modulators of the TNF-related apoptosis inducing ligand (TRAIL) pathway using a custom library of 12,471 sgRNAs. CONCLUSION: CLD predicts a high fraction of functional sgRNAs and is publicly available at https://github.com/boutroslab/cld.

caRpools: an R package for exploratory data analysis and documentation of pooled CRISPR/Cas9 screens.

MOTIVATION: Genetic screens by CRISPR/Cas9-mediated genome engineering have become a powerful tool for functional genomics. However, there is currently a lack of end-to-end software pipelines to analyze CRISPR/Cas9 screens based on next generation sequencing. RESULTS: The CRISPR-AnalyzeR for pooled screens (caRpools) is an R package for exploratory data analysis that provides a complete workflow to analyze CRISPR/Cas9 screens. To further support the analysis of large-scale screens, caRpools integrates screening documentation and generation of standardized analysis reports. AVAILABILITY AND IMPLEMENTATION: caRpools, manuals and an open virtual appliance are available at http://github.com/boutroslab/caRpools.

Microscopy-Based High-Content Screening.

Image-based screening is used to measure a variety of phenotypes in cells and whole organisms. Combined with perturbations such as RNA interference, small molecules, and mutations, such screens are a powerful method for gaining systematic insights into biological processes. Screens have been applied to study diverse processes, such as protein-localization changes, cancer cell vulnerabilities, and complex organismal phenotypes. Recently, advances in imaging and image-analysis methodologies have accelerated large-scale perturbation screens. Here, we describe the state of the art for image-based screening experiments and delineate experimental approaches and image-analysis approaches as well as discussing challenges and future directions, including leveraging CRISPR/Cas9-mediated genome engineering.

E-TALEN: a web tool to design TALENs for genome engineering.

Use of transcription activator-like effector nucleases (TALENs) is a promising new technique in the field of targeted genome engineering, editing and reverse genetics. Its applications span from introducing knockout mutations to endogenous tagging of proteins and targeted excision repair. Owing to this wide range of possible applications, there is a need for fast and user-friendly TALEN design tools. We developed E-TALEN (http://www.e-talen.org), a web-based tool to design TALENs for experiments of varying scale. E-TALEN enables the design of TALENs against a single target or a large number of target genes. We significantly extended previously published design concepts to consider genomic context and different applications. E-TALEN guides the user through an end-to-end design process of de novo TALEN pairs, which are specific to a certain sequence or genomic locus. Furthermore, E-TALEN offers a functionality to predict targeting and specificity for existing TALENs. Owing to the computational complexity of many of the steps in the design of TALENs, particular emphasis has been put on the implementation of fast yet accurate algorithms. We implemented a user-friendly interface, from the input parameters to the presentation of results. An additional feature of E-TALEN is the in-built sequence and annotation database available for many organisms, including human, mouse, zebrafish, Drosophila and Arabidopsis, which can be extended in the future.

Acetic acid treatment in S. cerevisiae creates significant energy deficiency and nutrient starvation that is dependent on the activity of the mitochondrial transcriptional complex Hap2-3-4-5.

Metabolic pathways play an indispensable role in supplying cellular systems with energy and molecular building blocks for growth, maintenance and repair and are tightly linked with lifespan and systems stability of cells. For optimal growth and survival cells rapidly adopt to environmental changes. Accumulation of acetic acid in stationary phase budding yeast cultures is considered to be a primary mechanism of chronological aging and induction of apoptosis in yeast, which has prompted us to investigate the dependence of acetic acid toxicity on extracellular conditions in a systematic manner. Using an automated computer controlled assay system, we investigated and model the dynamic interconnection of biomass yield- and growth rate-dependence on extracellular glucose concentration, pH conditions and acetic acid concentration. Our results show that toxic concentrations of acetic acid inhibit glucose consumption and reduce ethanol production. In absence of carbohydrates uptake, cells initiate synthesis of storage carbohydrates, trehalose and glycogen, and upregulate gluconeogenesis. Accumulation of trehalose and glycogen, and induction of gluconeogenesis depends on mitochondrial activity, investigated by depletion of the Hap2-3-4-5 complex. Analyzing the activity of glycolytic enzymes, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), pyruvate kinase (PYK), and glucose-6-phosphate dehydrogenase (G6PDH) we found that while high acetic acid concentration increased their activity, lower acetic acids concentrations significantly inhibited these enzymes. With this study we determined growth and functional adjustment of metabolism to acetic acid accumulation in a complex range of extracellular conditions. Our results show that substantial acidification of the intracellular environment, resulting from accumulation of dissociated acetic acid in the cytosol, is required for acetic acid toxicity, which creates a state of energy deficiency and nutrient starvation.