Forward genetic screens with genome-wide CRISPR libraries are powerful tools for resolving cellular circuits and signaling pathways. Applying this technology to organoids, however, has been hampered by technical limitations. Here we report improved accuracy and robustness for pooled-library CRISPR screens by capturing sgRNA integrations in single organoids, substantially reducing required cell numbers for genome-scale screening. We applied our approach to wild-type and APC mutant human intestinal organoids to identify genes involved in resistance to TGF-β-mediated growth restriction, a key process during colorectal cancer progression, and validated hits including multiple subunits of the tumor-suppressive SWI/SNF chromatin remodeling complex. Mutations within these genes require concurrent inactivation of APC to promote TGF-β resistance and attenuate TGF-β target gene transcription. Our approach can be applied to a variety of assays and organoid types to facilitate biological discovery in primary 3D tissue models.

Cancer is one of the most prevalent diseases in the world. Tumors arise due to important genes changing their activity, e.g. when inhibited or over-expressed. But these gene perturbations are difficult to observe directly. Molecular profiles of tumors can provide indirect evidence of gene perturbations. However, inferring perturbation profiles from molecular alterations is challenging due to error-prone molecular measurements and incomplete coverage of all possible molecular causes of gene perturbations.

In melanoma, a switch from a proliferative melanocytic to an invasive mesenchymal phenotype is based on dramatic transcriptional reprogramming which involves complex interactions between a variety of signaling pathways and their downstream transcriptional regulators. TGFβ/SMAD, Hippo/YAP/TAZ, and Wnt/β-catenin signaling pathways are major inducers of transcriptional reprogramming and converge at several levels. Here, we report that TGFβ/SMAD, YAP/TAZ, and β-catenin are all required for a proliferative-to-invasive phenotype switch. Loss and gain of function experimentation, global gene expression analysis, and computational nested effects models revealed the hierarchy between these signaling pathways and identified shared target genes. SMAD-mediated transcription at the top of the hierarchy leads to the activation of YAP/TAZ and of β-catenin, with YAP/TAZ governing an essential subprogram of TGFβ-induced phenotype switching. Wnt/β-catenin signaling is situated further downstream and exerts a dual role: it promotes the proliferative, differentiated melanoma cell phenotype and it is essential but not sufficient for SMAD or YAP/TAZ-induced phenotype switching. The results identify epistatic interactions among the signaling pathways underlying melanoma phenotype switching and highlight the priorities in targets for melanoma therapy.

Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.

Human pegivirus (HPgV) is transmitted through sexual or parenteral exposure and is common among patients receiving blood products. HPgV is associated with lower levels of human immunodeficiency virus (HIV) RNA and better survival among HIV-infected patients. This study aimed to investigate the prevalence of HPgV and determine its subtypes in HIV-infected individuals living in Istanbul, which has the highest rate of HIV infection in Türkiye. Total RNA extraction from plasma, cDNA synthesis, and nested PCR were performed for HPgV on plasma samples taken from 351 HIV-1-infected patients. The HPgV viral load was quantified on HPgV-positive samples. HPgV genotyping was performed by sequencing the corresponding amplicons. In the present study, the overall prevalence of HPgV RNA in HIV-infected patients was 27.3%. HPgV subtypes 1, 2a, and 2b were found, with subtype 2a being the most frequent (91.6%). Statistical analysis of HIV-1 viral load on HPgV viral load showed an opposing correlation between HIV-1 and HPgV loads. In conclusion, these data show that HPgV infection is common among HIV-positive individuals in Istanbul, Türkiye. Further comprehensive studies are needed to clarify both the cellular and molecular pathways of these two infections and to provide more information on the effect of HPgV on the course of the disease in HIV-infected individuals.

Understanding the structure and interplay of cellular signalling pathways is one of the great challenges in molecular biology. Boolean Networks can infer signalling networks from observations of protein activation. In situations where it is difficult to assess protein activation directly, Nested Effect Models are an alternative. They derive the network structure indirectly from downstream effects of pathway perturbations. To date, Nested Effect Models cannot resolve signalling details like the formation of signalling complexes or the activation of proteins by multiple alternative input signals. Here we introduce Boolean Nested Effect Models (B-NEM). B-NEMs combine the use of downstream effects with the higher resolution of signalling pathway structures in Boolean Networks.

Signaling pathways control cellular behavior. Dysregulated pathways, for example, due to mutations that cause genes and proteins to be expressed abnormally, can lead to diseases, such as cancer.

Determining SARS-CoV-2 immunity is critical to assess COVID-19 risk and the need for prevention and mitigation strategies. We measured SARS-CoV-2 Spike/Nucleocapsid seroprevalence and serum neutralizing activity against Wu01, BA.4/5 and BQ.1.1 in a convenience sample of 1,411 patients receiving medical treatment in the emergency departments of five university hospitals in North Rhine-Westphalia, Germany, in August/September 2022. 62% reported underlying medical conditions and 67.7% were vaccinated according to German COVID-19 vaccination recommendations (13.9% fully vaccinated, 54.3% one booster, 23.4% two boosters). We detected Spike-IgG in 95.6%, Nucleocapsid-IgG in 24.0%, and neutralization against Wu01, BA.4/5 and BQ.1.1 in 94.4%, 85.0%, and 73.8% of participants, respectively. Neutralization against BA.4/5 and BQ.1.1 was 5.6- and 23.4-fold lower compared to Wu01. Accuracy of S-IgG detection for determination of neutralizing activity against BQ.1.1 was reduced substantially. We explored previous vaccinations and infections as correlates of BQ.1.1 neutralization using multivariable and Bayesian network analyses. Given a rather moderate adherence to COVID-19 vaccination recommendations, this analysis highlights the need to improve vaccine-uptake to reduce the COVID-19 risk of immune evasive variants. The study was registered as clinical trial (DRKS00029414).