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.

The drug-induced phenotypic landscape of colorectal cancer organoids.

Patient-derived organoids resemble the biology of tissues and tumors, enabling ex vivo modeling of human diseases. They have heterogeneous morphologies with unclear biological causes and relationship to treatment response. Here, we use high-throughput, image-based profiling to quantify phenotypes of over 5 million individual colorectal cancer organoids after treatment with >500 small molecules. Integration of data using multi-omics modeling identifies axes of morphological variation across organoids: Organoid size is linked to IGF1 receptor signaling, and cystic vs. solid organoid architecture is associated with LGR5 + stemness. Treatment-induced organoid morphology reflects organoid viability, drug mechanism of action, and is biologically interpretable. Inhibition of MEK leads to cystic reorganization of organoids and increases expression of LGR5, while inhibition of mTOR induces IGF1 receptor signaling. In conclusion, we identify shared axes of variation for colorectal cancer organoid morphology, their underlying biological mechanisms, and pharmacological interventions with the ability to move organoids along them.

High-speed fluorescence image-enabled cell sorting.

Fast and selective isolation of single cells with unique spatial and morphological traits remains a technical challenge. Here, we address this by establishing high-speed image-enabled cell sorting (ICS), which records multicolor fluorescence images and sorts cells based on measurements from image data at speeds up to 15,000 events per second. We show that ICS quantifies cell morphology and localization of labeled proteins and increases the resolution of cell cycle analyses by separating mitotic stages. We combine ICS with CRISPR-pooled screens to identify regulators of the nuclear factor κB (NF-κB) pathway, enabling the completion of genome-wide image-based screens in about 9 hours of run time. By assessing complex cellular phenotypes, ICS substantially expands the phenotypic space accessible to cell-sorting applications and pooled genetic screening.

Patient-derived gene and protein expression signatures of NGLY1 deficiency.

N-Glycanase 1 (NGLY1) deficiency is a rare and complex genetic disorder. Although recent studies have shed light on the molecular underpinnings of NGLY1 deficiency, a systematic characterization of gene and protein expression changes in patient-derived cells has been lacking. Here, we performed RNA-sequencing and mass spectrometry to determine the transcriptomes and proteomes of 66 cell lines representing four different cell types derived from 14 NGLY1 deficient patients and 17 controls. Although NGLY1 protein levels were up to 9.5-fold downregulated in patients compared with parents, residual and likely non-functional NGLY1 protein was detectable in all patient-derived lymphoblastoid cell lines. Consistent with the role of NGLY1 as a regulator of the transcription factor Nrf1, we observed a cell type-independent downregulation of proteasomal genes in NGLY1 deficient cells. In contrast, genes involved in ribosome biogenesis and mRNA processing were upregulated in multiple cell types. In addition, we observed cell type-specific effects. For example, genes and proteins involved in glutathione synthesis, such as the glutamate-cysteine ligase subunits GCLC and GCLM, were downregulated specifically in lymphoblastoid cells. We provide a web application that enables access to all results generated in this study at https://apps.embl.de/ngly1browser. This resource will guide future studies of NGLY1 deficiency in directions that are most relevant to patients.

Multi-omics integration identifies a selective vulnerability of colorectal cancer subtypes to YM155.

Tumor heterogeneity is a major challenge to the treatment of colorectal cancer (CRC). Recently, a transcriptome-based classification was developed, segregating CRC into four consensus molecular subtypes (CMS) with distinct biological and clinical characteristics. Here, we applied the CMS classification on CRC cell lines to identify novel subtype-specific drug vulnerabilities. We combined publicly available transcriptome data from multiple resources to assign 157 CRC cell lines to CMS. By integrating results from large-scale drug screens, we discovered that the CMS1 subtype is highly vulnerable to the BIRC5 suppressor YM155. We confirmed our results using an independent panel of CRC cell lines and demonstrated a 100-fold higher sensitivity of CMS1. This vulnerability was specific to YM155 and not observed for commonly used chemotherapeutic agents. In CMS1 CRC, low concentrations of YM155 induced apoptosis and expression signatures associated with ER stress-mediated apoptosis signaling. Using a genome-wide CRISPR/Cas9 screen, we further discovered a novel role of genes involved in LDL-receptor trafficking as modulators of YM155 sensitivity in the CRC cell line HCT116. Our work shows that combining drug response data with CMS classification in cell lines can reveal selective vulnerabilities and proposes YM155 as a novel subtype-specific drug.

Genome-scale CRISPR screening at high sensitivity with an empirically designed sgRNA library.

BACKGROUND: In recent years, large-scale genetic screens using the CRISPR/Cas9 system have emerged as scalable approaches able to interrogate gene function with unprecedented efficiency and specificity in various biological contexts. By this means, functional dependencies on both the protein-coding and noncoding genome of numerous cell types in different organisms have been interrogated. However, screening designs vary greatly and criteria for optimal experimental implementation and library composition are still emerging. Given their broad utility in functionally annotating genomes, the application and interpretation of genome-scale CRISPR screens would greatly benefit from consistent and optimal design criteria. RESULTS: We report advantages of conducting viability screens in selected Cas9 single-cell clones in contrast to Cas9 bulk populations. We further systematically analyzed published CRISPR screens in human cells to identify single-guide (sg) RNAs with consistent high on-target and low off-target activity. Selected guides were collected in a novel genome-scale sgRNA library, which efficiently identifies core and context-dependent essential genes. CONCLUSION: We show how empirically designed libraries in combination with an optimized experimental design increase the dynamic range in gene essentiality screens at reduced library coverage.

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.

Detection of mutational patterns in cell-free DNA of colorectal cancer by custom amplicon sequencing.

Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell-free (cf) DNA offers a noninvasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatic workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open-software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our workflow to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from a pilot cohort of 34 patients with advanced colorectal cancer. Using our method, we could detect recurrent and patient-specific mutational patterns in the majority of patients. Furthermore, we show that dynamic changes of mutant allele frequencies in cfDNA correlate well with disease progression. Finally, we demonstrate that sequencing of cfDNA can reveal mechanisms of resistance to anti-Epidermal Growth Factor Receptor(EGFR) antibody treatment. Thus, our approach offers a simple and highly customizable method to explore genetic alterations in cfDNA.

MEK inhibitors activate Wnt signalling and induce stem cell plasticity in colorectal cancer.

In colorectal cancer (CRC), aberrant Wnt signalling is essential for tumorigenesis and maintenance of cancer stem cells. However, how other oncogenic pathways converge on Wnt signalling to modulate stem cell homeostasis in CRC currently remains poorly understood. Using large-scale compound screens in CRC, we identify MEK1/2 inhibitors as potent activators of Wnt/ß-catenin signalling. Targeting MEK increases Wnt activity in different CRC cell lines and murine intestine in vivo. Truncating mutations of APC generated by CRISPR/Cas9 strongly synergize with MEK inhibitors in enhancing Wnt responses in isogenic CRC models. Mechanistically, we demonstrate that MEK inhibition induces a rapid downregulation of AXIN1. Using patient-derived CRC organoids, we show that MEK inhibition leads to increased Wnt activity, elevated LGR5 levels and enrichment of gene signatures associated with stemness and cancer relapse. Our study demonstrates that clinically used MEK inhibitors inadvertently induce stem cell plasticity, revealing an unknown side effect of RAS pathway inhibition.

Context-dependent genetic interactions in cancer.

Genetic co-dependencies have been found in many contexts, from processes during the development of organisms to many diseases in man, including cancer. Genetic interactions - and in particular synthetic lethal phenotypes - have provided fundamental insights into the genetic architecture of cells and identified potential new opportunities for therapeutic interventions. However, recent studies also demonstrated that genetic interactions are highly context dependent and synthetic lethal interactions in one tumor context might not be translatable to others. Therefore, to better define and understand contexts will be a key challenge for future studies to fully exploit genetic interaction networks for target identification and cancer therapy. In this review, we summarize recent developments in mapping context-specific genetic interaction networks with a particular focus on conceptual and experimental advances in the past years. We then discuss genetic and environmental contexts that influence genetic interaction networks. Finally, we outline challenges of putting genetic interaction networks into context and give an outlook on future directions.

ß-catenin-independent regulation of Wnt target genes by RoR2 and ATF2/ATF4 in colon cancer cells.

Wnt signaling is an evolutionarily conserved signaling route required for development and homeostasis. While canonical, ß-catenin-dependent Wnt signaling is well studied and has been linked to many forms of cancer, much less is known about the role of non-canonical, ß-catenin-independent Wnt signaling. Here, we aimed at identifying a ß-catenin-independent Wnt target gene signature in order to understand the functional significance of non-canonical signaling in colon cancer cells. Gene expression profiling was performed after silencing of key components of Wnt signaling pathway and an iterative signature algorithm was applied to predict pathway-dependent gene signatures. Independent experiments confirmed several target genes, including PLOD2, HADH, LCOR and REEP1 as non-canonical target genes in various colon cancer cells. Moreover, non-canonical Wnt target genes are regulated via RoR2, Dvl2, ATF2 and ATF4. Furthermore, we show that the ligands Wnt5a/b are upstream regulators of the non-canonical signature and moreover regulate proliferation of cancer cells in a ß-catenin-independent manner. Our experiments indicate that colon cancer cells are dependent on both ß-catenin-dependent and -independent Wnt signaling routes for growth and proliferation.

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.

Phenotype databases for genetic screens in human cells.

Genetic screens are powerful tools to identify components that make up biological systems. Perturbations introduced by methods such as RNA interference (RNAi) or CRISPR/Cas9-mediated genome editing lead to biological phenotypes that can be examined to understand the molecular function of genes in the cell. Over the years, many of such experiments have been conducted providing a wealth of knowledge about genotype-to-phenotype relationships. These data are a rich source of information and it is in a common interest to make them available in a simplified and integrated format. Thus, an important challenge is that genetic screening data can be stored in databases in standardized ways, allowing users to gain new biological insights through data mining and integrated analyses. Here, we provide an overview of available phenotype databases for human cells. We review in detail two databases for high-throughput screens, GenomeRNAi and GenomeCRISPR, and describe how these resources are integrated into the German Network for Bioinformatics Infrastructure de.NBI as part of the European infrastructure for life-science information ELIXIR.

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.

MSAViewer: interactive JavaScript visualization of multiple sequence alignments.

The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is 'web ready': written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. AVAILABILITY AND IMPLEMENTATION: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/Supplementary information: Supplementary data are available at Bioinformatics online. CONTACT: msa@bio.sh.