Biology subjects

Eils, R.

Publications and source records attributed to Eils, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

Deep molecular characterization linked to drug response profiling of pancreatic ductal adenocarcinoma using patient-derived organoids.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by high drug resistance and poor prognosis. Novel therapeutic and stratification strategies are urgently needed. Here, we present an integration of in-depth genomic and transcriptomic characterization with drug screening and clinical outcome based on a catalogue of 51 patient-derived tumor organoids (PDOs) from resected PDAC. Known PDAC molecular subtypes and their prognostic value are conserved in organoids. Integration of transcriptomic and drug response profiles suggest a metabolism-mediated modulations of drug resistance. Copy number alterations on chromosome 13q and wild-type status of TP53 emerged as potential novel genomic biomarkers for sensitivity to 5-FU and oxaliplatin treatment, respectively. Functional testing of targeted drugs in PDOs revealed its additional value for genome-driven personalized oncology. Co-deletion of TP53/POLR2A increased vulnerability to RNA polymerase II inhibition, pointing to a promising target for personalized treatment in PDAC. SignificancePatient-derived PDAC organoids hold great promise as surrogate tumor models for personalized oncology. By integrating highly granular molecular, drug sensitivity and clinical data, we demonstrate that PDOs are valid models for molecular characterization and response prediction that also enable identification of novel drug sensitivity biomarkers and resistance mechanisms in PDAC.

cancer biology↗

bioRxiv2021

Dynamics of SARS-CoV-2 host cell interactions inferred from transcriptome analyses

The worldwide spread of severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) caused an urgent need for an in-depth understanding of interactions between the virus and its host. Here, we dissected the dynamics of virus replication and the host cell transcriptional response to SARS-CoV-2 infection at a systems level by combining time-resolved RNA sequencing with mathematical modeling. We observed an immediate transcriptional activation of inflammatory pathways linked to the anti-viral response followed by increased expression of genes involved in ribosome and mitochondria function, thus hinting at rapid alterations in protein production and cellular energy supply. At later stages, metabolic processes, in particular those depending on cytochrome P450 enzymes, were downregulated. To gain a deeper understanding of the underlying transcriptional dynamics, we developed an ODE model of SARS-CoV-2 infection and replication. Iterative model reduction and refinement revealed that a negative feedback from virus proteins on the expression of anti-viral response genes was essential to explain our experimental dataset. Our study provides insights into SARS-CoV-2 virus-host interaction dynamics and facilitates the identification of druggable host pathways supporting virus replication.

systems biology↗

bioRxiv2021

Intratumoural heterogeneity and immune modulation in lung adenocarcinoma of female smokers and never smokers

Lung cancer is still the leading cause of cancer death worldwide despite declining smoking prevalence in industrialised countries. Although lung cancer is highly associated with smoking status, a significant proportion of lung cancer cases develop in patients who never smoked, with an observable bias towards female never smokers. A better understanding of lung cancer heterogeneity and immune system involvement during tumour evolution and progression in never smokers is therefore highly warranted. We employed single nucleus transcriptomics of surgical lung adenocarcinoma (LADC) and normal lung tissue samples from patients with or without smoking history. Immune cells as well as fibroblasts and endothelial cells respond to tobacco smoke exposure by inducing a highly inflammatory state in normal lung tissue. In the presence of LADC, we identified differentially expressed transcriptional programmes in macrophages and cancer-associated fibroblasts, providing insight into how the niche favours tumour progression. Within tumours, we distinguished eight subpopulations of neoplastic cells in female smokers and never smokers. Through pseudotemporal ordering, we inferred a trajectory towards two differentiated tumour cell states implicated in cancer progression and invasiveness. A proliferating cell population sustaining tumour growth exhibits differential immune modulating signatures in both patient groups. Our results resolve cellular heterogeneity and immune interactions in LADC, with a special emphasis on female never smokers and implications for the design of therapeutic approaches.

cancer biology↗

bioRxiv2020

Integrative Ranking Of Enhancer Networks Facilitates The Discovery Of Epigenetic Markers In Cancer

Regulation of gene expression through multiple epigenetic components is a highly combinatorial process. Alterations in any of these layers, as is commonly found in cancer diseases, can lead to a cascade of downstream effects on tumor suppressor or oncogenes. Hence, deciphering the effects of epigenetic alterations on regulatory elements requires innovative computational approaches that can benefit from the huge amounts of epigenomic datasets that are available from multiple consortia, such as Roadmap or BluePrint. We developed a software tool named Irene (Integrative Ranking of Epigenetic Network of Enhancers), which performs quantitative analyses on differential epigenetic modifications through an integrated, network-based approach. The method takes into account the additive effect of alterations on multiple regulatory elements of a gene. Applying this tool to well-characterized test cases, it successfully found many known cancer genes from publicly available cancer epigenome datasets.

bioinformatics↗

bioRxiv2020

The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability

BackgroundCancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. ResultsHere, we combined the notions of epipolymorphism and epiallele switching to analyze DNA methylation heterogeneity in MM patients. We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High entropy change is associated with poor outcomes and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. ConclusionWe propose that disordered methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.

cancer biology↗

bioRxiv2020

The COVID-19 PHARMACOME: Rational Selection of Drug Repurposing Candidates from Multimodal Knowledge Harmonization

The SARS-CoV-2 pandemic has challenged researchers at a global scale. The scientific communitys massive response has resulted in a flood of experiments, analyses, hypotheses, and publications, especially in the field of drug repurposing. However, many of the proposed therapeutic compounds obtained from SARS-CoV-2 specific assays are not in agreement and thus demonstrate the need for a singular source of COVID-19 related information from which a rational selection of drug repurposing candidates can be made. In this paper, we present the COVID-19 PHARMACOME, a comprehensive drug-target-mechanism graph generated from a compilation of 10 separate disease maps and sources of experimental data focused on SARS-CoV-2 / COVID-19 pathophysiology. By applying our systematic approach, we were able to predict the synergistic effect of specific drug pairs, such as Remdesivir and Thioguanosine or Nelfinavir and Raloxifene, on SARS-CoV-2 infection. Experimental validation of our results demonstrate that our graph can be used to not only explore the involved mechanistic pathways, but also to identify novel combinations of drug repurposing candidates.

bioinformatics↗

bioRxiv2020

Single-cell analysis of patient-derived PDAC organoids reveals cell state heterogeneity and a conserved developmental hierarchy

Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality by 2030. Bulk transcriptomic analyses have distinguished classical pancreatic tumors from basal-like tumors with more aggressive clinical behaviour. We derived PDAC organoids from primary tumors of 18 patients, together with two matched samples from liver metastases. By single-cell RNA sequencing, we show that PDAC organoids consist of ductal cells with patient-specific expression of several gene groups, including genes which encode cell surface proteins. We report classical and basal-like cells coexisting within single primary tumors or metastases, with greater intratumor subtype heterogeneity linked to higher tumor grade. Single-cell transcriptome analysis of PDAC organoids and primary PDAC identified distinct tumor cell states shared across patients, including a cycling progenitor cell state and a differentiated secretory state. We show that these cell states are connected by a differentiation hierarchy, with classical subtype cells concentrated at the endpoint of this hierarchy. In an imaging-based drug screen, expression of classical subtype genes also correlates with better response to clinical drugs. Our results thus uncover a functional hierarchy of PDAC cell states linked to transcriptional tumor subtypes, and support the use of PDAC organoids as a clinically relevant model for in vitro studies of tumor heterogeneity.

cancer biology↗

bioRxiv2020

SARS-CoV-2 receptor ACE2 and TMPRSS2 are predominantly expressed in a transient secretory cell type in subsegmental bronchial branches

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection and replication. SARS-CoV-2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS-CoV-2 infection. Our data provide a rich resource for future investigations of COVID-19 infection and pathogenesis.

genomics↗

bioRxiv2020

Automated screening by 3D light-sheet microscopy with high spatial and temporal resolution reveals mitotic phenotypes

3D cell cultures enable the in vitro study of dynamic biological processes such as the cell cycle, but their use in high-throughput screens remains impractical with conventional fluorescent microscopy. Here, we present a screening workflow for the automated evaluation of mitotic phenotypes in 3D cell cultures by light-sheet microscopy. After sample preparation by a liquid handling robot, three-dimensional cell spheroids are imaged for 24 hours in toto with a dual inverted selective plane illumination (diSPIM) microscope with a much improved signal-to-noise ratio, higher imaging speed, isotropic resolution and reduced light exposure compared to a spinning disc confocal microscope. A dedicated high-content image processing pipeline implements convolutional neural network based phenotype classification. We illustrate the potential of our approach by siRNA knock-down and epigenetic modification of 28 mitotic target genes for assessing their phenotypic role in mitosis. By rendering light-sheet microscopy operational for high-throughput screening applications, this workflow enables target gene characterization or drug candidate evaluation in tissue-like 3D cell culture models.

cell biology↗

bioRxiv2019

Induced aneuploidy disrupts MCF10A acini formation and CCND1 expression

Abnormal karyotypes, namely aneuploidy, can be detected in nearly all cancer entities at different grades. The impact of these altering mutations on epigenetic regulation, especially on promoter-enhancer interactions are not well understood. Here, we applied a 3D model of MCF10A cells in a high-content screen to measure induced aneuploidy by RNA interference of 82 mitotic genes associated with aneuploidy and breast cancer. Perturbation of ESPL1 and TOP2A expression led to increased mitotic instability and subsequent aneuploidy and polylobed nuclei. During acinus formation these polylobed cells disrupted proper acinus rotation inhibiting the development of a hollow lumen and a polarized outer cell layer. Further, gene expression profiling identified upregulated CCND1 among other breast cancer related genes. We show that acquisition of aneuploidy affects the morphogenesis of MCF10A acini and expression of cancer relevant genes. By conducting 4C chromosome capturing experiments we linked the alteration of interactions of the promoter region to CCND1 upregulation.

cancer biology↗

bioRxiv2019

Optogenetic control of Neisseria meningitidis Cas9 genome editing using an engineered, light-switchable anti-CRISPR protein

Optogenetic control of CRISPR-Cas9 systems has significantly improved our ability to perform genome perturbations in living cells with high precision in time and space. As new Cas orthologues with advantageous properties are rapidly being discovered and engineered, the need for straightforward strategies to control their activity via exogenous stimuli persists. The Cas9 from Neisseria meningitidis (Nme) is a particularly small and target-specific Cas9 orthologue, and thus of high interest for in vivo genome editing applications. Here, we report the first optogenetic tool to control NmeCas9 activity in mammalian cells via an engineered, light-dependent anti-CRISPR (Acr) protein. Building on our previous Acr engineering work, we created hybrids between the NmeCas9 inhibitor AcrIIC3 and the LOV2 blue light sensory domain from Avena sativa. Two AcrIIC3-LOV2 hybrids from our collection potently blocked NmeCas9 activity in the dark, while permitting robust genome editing at various endogenous loci upon blue light irradiation. Structural analysis revealed that, within these hybrids, the LOV2 domain is located in striking proximity to the Cas9 binding surface. Together, our work demonstrates optogenetic regulation of a type II-C CRISPR effector and might suggest a new route for the design of optogenetic Acrs.

synthetic biology↗

bioRxiv2019

Segmentation-free inference of cell-types from in situ transcriptomics data

Multiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a novel method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. We found that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types.

bioinformatics↗

bioRxiv2019

Gene set inference from single-cell sequencing data using a hybrid of matrix factorization and variational autoencoders

Recent advances in single-cell RNA sequencing (scRNA-Seq) have driven the simultaneous measurement of the expression of 1,000s of genes in 1,000s of single cells. These growing data sets allow us to model gene sets in biological networks at an unprecedented level of detail, in spite of heterogenous cell populations. Here, we propose an unsupervised deep neural network model that is a hybrid of matrix factorization and conditional variational autoencoders (CVA), which utilizes weights as matrix factorizations to obtain gene sets, while class-specific inputs to the latent variable space facilitate a plausible identification of cell types. This artificial neural network model seamlessly integrates functional gene set inference, experimental batch effect correction, and static gene identification, which we conceptually prove here for three single-cell RNA-Seq datasets and suggest for future single-cell-gene analytics.

bioinformatics↗

bioRxiv2019

Single nucleus RNA sequencing maps acinar cell states in a human pancreas cell atlas

Molecular evidence of cellular heterogeneity in the human exocrine pancreas has not been established, due to the local concentration of hydrolytic enzymes that can rapidly degrade cells and RNA upon resection. Here we innovated single-nucleus RNA sequencing protocols, and profiled more than 120,000 cells from adult and neonatal human donors to create the first comprehensive atlas of human pancreas cells, including epithelial and non-epithelial constituents. Adult and neonatal pancreata shared common features, including the presence of previously undetected acinar subtypes, but also showed marked differences in the composition of the endocrine, endothelial, and immune compartments. Spatial cartography, including cell proximity mapping through in situ sequencing, revealed dynamic developmental cell topographies in the endocrine and exocrine pancreas. Our human pancreas cell atlas can be interrogated to understand pancreatic cell biology, and provides a crucial reference set for future comparisons with diseased tissue samples to map the cellular foundations of pancreatic diseases.

genomics↗

bioRxiv2019

Computational design of anti-CRISPR proteins with improved inhibition potency and expanded specificity

Anti-CRISPR (Acr) proteins are bacteriophage-derived antagonists of CRISPR-Cas systems. To date, Acrs were obtained either by mining sequence databanks or experimentally screening phage collections, both of which yield a limited repertoire of naturally occurring variants. Here, we applied structure-based engineering on AcrIIC1, a broad-spectrum inhibitor of type II-C CRISPR systems, to improve its efficacy and expand its specificity. We first show that fusing exogenous protein domains into AcrIIC1 dramatically enhances inhibition of the natural Neisseria meningitidis Cas9 target. Then, using structure-guided design, we converted AcrIIC1 into AcrX, a potent inhibitor of the type II-A CRISPR-Cas9 from Staphylococcus aureus widely applied for in vivo genome editing. Our work introduces designer Acrs as important biotechnological tools and provides an innovative strategy to safeguard the CRISPR technology.

synthetic biology↗

bioRxiv2019

Modeling glioblastoma invasion using human brain organoids and single-cell transcriptomics

Glioblastoma multiforme (GBM) are devastating neoplasms with high invasive capacity. GBM has been difficult to study in vitro. Therapeutic progress is also limited by cellular heterogeneity within and between tumors. To address these challenges, we present an experimental model using human cerebral organoids as a scaffold for patient-derived glioblastoma cell invasion. By tissue clearing and confocal microscopy, we show that tumor cells within organoids extend a network of long microtubes, recapitulating the in vivo behavior of GBM. Single-cell RNA-seq of GBM cells before and after co-culture with organoid cells reveals transcriptional changes implicated in the invasion process that are coherent across patient samples, indicating that GBM cells reactively upregulate genes required for their dispersion. Functional therapeutic targets are identified by an in silico receptor-ligand pairing screen detecting potential interactions between GBM and organoid cells. Taken together, our model has proven useful for studying GBM invasion and transcriptional heterogeneity in vitro, with applications for both pharmacological screens and patient-specific treatment selection at a time scale amenable to clinical practice.

cancer biology↗

bioRxiv2019

Whole-genome fingerprint of the DNA methylome during chemically induced differentiation of the human AML cell line HL-60/S4

BackgroundMyeloid differentiation gives rise to a plethora of immune cells in the human body. This differentiation leaves strong signatures in the epigenome through each differentiated state of genetically identical cells. The leukemic HL-60/S4 promyelocytic cell can be easily differentiated from its undifferentiated promyelocyte state into neutrophil-and macrophage-like cell states, making it an excellent system for studying myeloid differentiation. In this study, we present the underlying genome and epigenome architecture of HL-60/S4 through its undifferentiated and differentiated cell states.\n\nResultsWe performed whole genome bisulphite sequencing of HL-60/S4 cells and their differentiated counterparts. With the support of karyotyping, we show that HL-60/S4 maintains a stable genome throughout differentiation. Analysis of differential CpG methylation reveals that most methylation changes occur in the macrophage-like state. Differential methylation of promoters was associated with immune related terms. Key immune genes, CEBPA, GFI1, MAFB and GATA1 showed differential expression and methylation. However, we observed strongest enrichment of methylation changes in enhancers and CTCF binding sites, implying that methylation plays a major role in large scale transcriptional reprogramming and chromatin reorganisation during differentiation. Correlation of differential expression and distal methylation with support from chromatin capture experiments allowed us to identify putative proximal and long-range enhancers for a number of immune cell differentiation genes, including CEBPA and CCNF. Integrating expression data, we present a model of HL-60/S4 differentiation in relation to the wider scope of myeloid differentiation.\n\nConclusionsFor the first time, we elucidate the genome and CpG methylation landscape of HL-60/S4 during differentiation. We identify all differentially methylated regions and positions. We link these to immune function and to important factors in myeloid differentiation. We demonstrate that methylation plays a more significant role in modulating transcription via enhancer reprogramming, rather than by promoter regulation. We identify novel regulatory regions of key components in myeloid differentiation that are regulated by differential methylation. This study contributes another layer of \"omics\" characterisation of the HL-60/S4 cell line, making it an excellent model system for studying rapid in vitro cell differentiation.\n\nSummary statementEpigenomics plays a major role in cell identity and differentiation. We present the DNA methylation landscape of leukemic cells during in-vitro differentiation, to add another omics layer to better understand the mechanisms behind differentiation.

genomics↗

bioRxiv2018

Cell-specific CRISPR/Cas9 activation by microRNA-dependent expression of anti-CRISPR proteins

The rapid development of CRISPR/Cas technologies brought a personalized and targeted treatment of genetic disorders into closer reach. To render CRISPR-based therapies precise and safe, strategies to confine the activity of Cas(9) to selected cells and tissues are highly desired. Here, we developed a cell type-specific Cas-ON switch based on miRNA-regulated expression of anti-CRISPR (Acr) proteins. We inserted target sites for miR-122 or miR-1, which are abundant specifically in liver and muscle cells, respectively, into the 3UTR of Acr transgenes. Co-expressing these with Cas9 and sgRNAs resulted in Acr knockdown and correspondingly in Cas9 activation solely in hepatocytes or myocytes, while Cas9 was efficiently inhibited in off-target cells. We demonstrate control of genome editing and gene activation using a miR-dependent AcrIIA4 in combination with different Streptococcus pyogenes (Spy)Cas9 variants (full-length Cas9, split-Cas9, dCas9-VP64). Finally, to showcase its modularity, we adapted our Cas-ON system to the smaller and more target-specific Neisseria meningitidis (Nme)Cas9 orthologue and its cognate inhibitors AcrIIC1 and AcrIIC3. Our Cas-ON switch should facilitate cell-specific activation of any CRISPR/Cas orthologue, for which a potent anti-CRISPR protein is known.

synthetic biology↗