IFNγ mediates the resistance of tumor cells to distinct NK cell subsets.

Background: Immune checkpoint blockade targeting the adaptive immune system has revolutionized the treatment of cancer. Despite impressive clinical benefits observed, patient subgroups remain non-responsive underscoring the necessity for combinational therapies harnessing additional immune cells. Natural killer (NK) cells are emerging tools for cancer therapy.

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.

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.

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.

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.

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.

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

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.

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

Unlabelled: 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 cells at multiple time points and after pharmacological inhibition of Ras signaling activity.

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.

RNA Interference (RNAi) Screening in .

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 , RNAi can be used to silence the expression of genes through introduction of exogenous double-stranded RNA into cells. In , RNAi has been applied in cultured cells or to perturb the function of single genes or to systematically probe gene function on a genome-wide scale.

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.

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.

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.

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.

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.

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.

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.

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.

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.

KOMA: ELISA-microarray calibration and data analysis based on kinetic signal amplification.

Antibody microarrays with enzyme-linked immunosorbent technology are used for quantitative, simultaneous and high-throughput analysis of multiple proteins in a single probe. Kinetic detection can significantly improve precision and quantification range of microarray measurements. Here we present the open source software Kinetic Operating Microarray Analyzer (KOMA) that enables calibration and high-throughput analysis of quantitative microarray data collected using a time-resolved kinetic detection protocol of the enzymatic signal.

Microarray-based kinetic colorimetric detection for quantitative multiplex protein phosphorylation analysis.

Commonly used colorimetric detection applied to protein microarrays with enzymatic signal amplification leads to non-linear signal production upon increase in analyte concentration, thereby considerably limiting the range and accuracy of quantitative readout interpretation. To extend the detection range, we developed a kinetic colorimetric detection protocol for the analysis of ELISA microarrays designed to measure multiple phosphorylated proteins using the platforms ArrayTube™ and ArrayStrip™. With our novel quantification approach, microarrays were calibrated over a broad concentration range spanning four orders of magnitude of analyte concentration with picomolar threshold.