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. Co-targeting 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.

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.

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.

Supplementary information

Supplementary data are available at Bioinformatics online.

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/β-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.

Abstract B16: Epistatic mapping of signaling and chromatin regulators

Phenotypes are often not only based on the effect of a single gene, but are rather influenced by multiple genetic (also termed epistatic) interactions. Prominent examples are synthetic lethal interactions, where the individual loss-of-function of two genes does not lead to phenotypic alterations, whereas their simultaneous perturbation results in reduced fitness or even cell death. Previously, we have established large-scale genetic interaction mapping experiments in Drosophila cells that discovered a high-number of functional interactions of conserved factors. Here, we aim to create a platform to investigate epistatic interactions of genes encoding chromatin remodeling and signaling factors in human cells.

As part of the transcriptional regulatory machinery, chromatin remodeling enzymes buffer various genetic perturbations via adaptations within the transcriptional program, e.g. via repression of mutant or activation of functional alleles. Furthermore, chromatin remodeling factors link epigenetic modifications to corresponding signaling pathway outputs. While some of these enzymes have been extensively studied, many remain largely uncharacterized. As epigenetic dysregulation constitutes a characteristic feature of many cancers, chromatin remodeling proteins are promising targets in anticancer therapies.

To map interaction networks of chromatin and signaling factors, we use pooled genome-scale CRISPR/Cas9 genetic interaction screens. To this end, CRISPR/Cas9 mapping will be performed in a human cell line to reveal unknown functions and interactions of chromatin remodeling enzymes. We will present our screening platform, including custom library design and analysis tools to identify screening hits that emerge to be promising for synthetic lethality targeting in anticancer therapy.

Citation Format: Luisa Henkel, Florian Heigwer, Jan Winter, Benedikt Rauscher, Michael Boutros. Epistatic mapping of signaling and chromatin regulators [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr B16.

Abstract A10: CRISPR-AnalyzeR (caR): Web-based, interactive and exploratory analysis and documentation of pooled CRISPR/Cas9 screens

Since the availability of the CRISPR/Cas9 gene editing technique, pooled CRISPR/Cas9 screens have become a powerful and versatile tool for the investigation of functional genomics in a variety of organisms. Pooled CRISPR/Cas9 screens are cost-effective and do not require lab automation, which allows even small labs to perform genome-wide genetic perturbation screens. The analysis of such screens so far requires in-depth knowledge in either bioinformatics or data analysis as there is a limited availability of end-to-end data analysis pipelines (Li et al., 2014; Winter et al., 2015). Moreover, the explorative analysis of screening data using end-to-end analysis tools often comes with certain limitations. Either these pipelines require sufficient computing power on the user machine or have to be run in command-line mode on dedicated machines, which constrains the usability.

A special need for wet-lab scientists is the availability of analysis pipelines which allow them to analyze the screening data on their own, knowing best about potential candidates and the biological background. Here we describe the CRISPR-AnalyzeR (caR), which is a web-based and fully-interactive tool to analyze pooled CRISPR/Cas9 screens meant for wet-lab scientists. caR combines both, end-to-end data analysis and explorative screen analysis that can be accessed via a regular web-browser such as Google Chrome or Firefox from any device - allowing the user to analyze the data in a comfortable, convenient and exploratory way. Moreover, caR uses latest visualization technologies to provide interactive plots and tables, allowing even novice users to analyze their own screens in an exploratory way. caR performs hit-calling using six different analysis methods, which gives the user the power and flexibility to select appropriate follow-up candidates. caR provides an easy-to-follow workflow and guides the user through the whole analysis process, which includes quality control, hit calling, in-depth gene information, data annotation enrichment and downloadable interactive reports to provide a comprehensive documentation.

Since caR is a web-based tool, it can be used via a provided web-server at http://crispr-analyzer.dkfz.de or can be downloaded for a local network installation.

Citation Format: Jan Winter, Marc Schwering, Benedikt Rauscher, Florian Heigwer, Michael Boutros. CRISPR-AnalyzeR (caR): Web-based, interactive and exploratory analysis and documentation of pooled CRISPR/Cas9 screens [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr A10.

Abstract A23: Multi-parametric genetic interactions map dynamic genetic network rewiring upon anti-proliferative treatment

Signaling pathways are often characterized as rather static networks whose outcome is the result of state changes of pathway components, e.g. by protein phosphorylation or other post-translational modifications. These state changes along signaling networks have been systematically studied using, for example proteomics methods. However it remained unknown how networks rewire under the influence of external stimuli, such as anti-cancer drug treatment. To analyze dynamic rewiring of a signaling network, we performed an arrayed high-throughput co-RNAi screen in a Drosophila melanogaster cell line (Dmel-2). Therin, we assessed statistic genetic interactions measured by 26 880 pairwise RNAi experiments under MEK1/2 inhibitor treatment over the time course of 96 hours. As phenotypic readout we conducted high-content imaging of DNA, cytoskeleton and microtubule markers and extracted >150 cellular features from 4 423 680 images each representing a specific condition, and marker. Together these features precisely characterize ~100 000 alleviating and 160 000 aggravating synergistic effects resulting from combinatorial perturbations. While only 2 % of all interactions are explained by cell viability the vast majority of dynamic differential interactions is explained by other features. Correlation of genetic interaction profiles across those features allows us to precisely how genes change pathway affiliation under different conditions. Our results show that, among others, key signaling nodes e.g. ERK1/2 or the Mediator complex build different connections within genetic networks depending on the environmental conditions and reveal yet unknown synthetic interactions. Using the confidence we gain from time resolved measurements of different cellular features we could identify numerous interactions which could resolve mechanisms of resistance to MEK inhibitor driven treatments and reveal potential new therapeutic targets.

Citation Format: Florian Heigwer, Christian Scheeder, Thilo Miersch, Claudia Blass, Michael Boutros. Multi-parametric genetic interactions map dynamic genetic network rewiring upon anti-proliferative treatment [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr A23.

Abstract B06: HTSvis: An user-friendly application for analysis of arrayed high-throughput experiments by interactive data representations

The presented application HTSvis provides an user-interface tool for interactive analysis of arrayed high-throughput screening experiments. Arrayed formats are broadly used for cell-based screens which help to reveal mechanisms of complex diseases such as cancer. Technological advances allow to screen tens of thousands experimental conditions in a single experiments resulting in large datasets with complicated annotation files. Software packages for standardized analysis with a minimized programming effort have been developed accordingly. Even though such pipelines provide comprehensive analysis options, interpretation of the results remains a challenge as the user has to manually compare files and possibly re-run the analysis to prosecute certain hypotheses. Here we present HTSvis, a web application that visualizes data from arrayed screens. The data can be read-in as result files of the established R package CellHTS2 or as any spreadsheet table. This enables the user to feed in data which has been statistically analyzed whilst preserving flexibility to analyze data independent of the CellHTS2 package. The application provides several informative data representations like heatmaps, scatter plots and tables. Within the application, the data can be browsed in an ad hoc manner via the implemented user interface. This allows the user to assess data quality, compare experiments, identify measurements of interest and to verify generated hypotheses in an exploratory manner. The direct allocation of data points to experimental conditions is preserved in all representations facilitating an intuitive interpretation. HTSvis is easy to install, data input is straight forward and no programming skills are required for the usage. The application is compatible with common web browsers and can be set up on local computers as well as on server clusters which allows parallel access for multiple users. Summarized, HTSvis provides a helpful tool for interactive data analysis and interpretation for both, users with and without programming skills. Thereby, the application also promotes the cooperation and exchange of ideas between bioinformaticians and experimental biologists or between collaborators.

Citation Format: Christian Scheeder, Florian Heigwer, Michael Boutros. HTSvis: An user-friendly application for analysis of arrayed high-throughput experiments by interactive data representations [abstract]. In: Proceedings of the AACR Precision Medicine Series: Opportunities and Challenges of Exploiting Synthetic Lethality in Cancer; Jan 4-7, 2017; San Diego, CA. Philadelphia (PA): AACR; Mol Cancer Ther 2017;16(10 Suppl):Abstract nr B06.

Abstract 5766: High-content microscopy-based screening of colorectal organoids

High-content screening of cells has become a widespread approach for cellular assays due to its capacity to capture complex biological processes. However, conventional cell culture is limited with respect to cell and tissue architecture. Organoids are a unique model system for the intact and diseased intestinal epithelium. The 3D model can be used for the functional study of cancer development and, potentially, prospective therapeutic testing of drugs in patient derived tumor organoids. Here, we present a high-content microscopy based screening workflow to study organoid self-organization and growth with up to single cell resolution. After seeding of organoid fragments in a basal membrane extract, screening plates are incubated to allow for organoid formation. Subsequent treatment and incubation is followed by staining and imaging on a high-throughput microscopy platform followed by automated image analysis using open-source software. Profiling of both complete organoids and their individual architecture enables the quantitative description of population and tissue heterogeneity in the context of various perturbations. We generated four distinct colon organoid lines from mice carrying mutations of APC and KRAS in different combinations. These are profiled for differential phenotypic responses to a library of >1000 drug-like compounds. Also, this methodology is used to screen for clinically relevant differential treatment responses in patient derived tumor and normal colon organoids. Hence, based on this work we are able to analyze gene-drug interactions in early colon cancer development and drug response of patient derived colorectal cancer organoids.

Citation Format: Niklas T. Rindtorff, Johannes Betge, Jan Sauer, Thilo Miersch, Tianzuo Zhan, Florian Heigwer, Claudia Scholl, Matthias Ebert, Bernd Fischer, Michael Boutros. High-content microscopy-based screening of colorectal organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5766. doi:10.1158/1538-7445.AM2017-5766

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.

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.

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.

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.