Glyoxal as an alternative fixative for single-cell RNA sequencing.

Single-cell RNA sequencing has become an important method to identify cell types, delineate the trajectories of cell differentiation in whole organisms, and understand the heterogeneity in cellular responses. Nevertheless, sample collection and processing remain a severe bottleneck for single-cell RNA sequencing experiments. Cell isolation protocols often lead to significant changes in the transcriptomes of cells, requiring novel methods to preserve cell states. Here, we developed and benchmarked protocols using glyoxal as a fixative for single-cell RNA sequencing applications. Using Drop-seq methodology, we detected a large number of transcripts and genes from glyoxal-fixed Drosophila cells after single-cell RNA sequencing. The effective glyoxal fixation of transcriptomes in Drosophila and human cells was further supported by a high correlation of gene expression data between glyoxal-fixed and unfixed samples. Accordingly, we also found highly expressed genes overlapping to a large extent between experimental conditions. These results indicated that our fixation protocol did not induce considerable changes in gene expression and conserved the transcriptome for subsequent single-cell isolation procedures. In conclusion, we present glyoxal as a suitable fixative for Drosophila cells and potentially cells of other species that allow high-quality single-cell RNA sequencing applications.

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.

Analysis of Single-Cell Transcriptome Data in Drosophila.

The fly Drosophila is a versatile model organism that has led to fascinating biological discoveries. In the past few years, Drosophila researchers have used single-cell RNA-sequencing (scRNA-seq) to gain insights into the cellular composition, and developmental processes of various tissues and organs. Given the success of single-cell technologies a variety of computational tools and software packages were developed to enable and facilitate the analysis of scRNA-seq data. In this book chapter we want to give guidance on analyzing droplet-based scRNA-seq data from Drosophila. We will initially describe the preprocessing commonly done for Drosophila, point out possible downstream analyses, and finally highlight computational methods developed using Drosophila scRNA-seq data.

Gene expression atlas of a developing tissue by single cell expression correlation analysis.

The Drosophila wing disc has been a fundamental model system for the discovery of key signaling pathways and for our understanding of developmental processes. However, a complete map of gene expression in this tissue is lacking. To obtain a gene expression atlas in the wing disc, we employed single cell RNA sequencing (scRNA-seq) and developed a method for analyzing scRNA-seq data based on gene expression correlations rather than cell mapping. This enables us to compute expression maps for all detected genes in the wing disc and to discover 824 genes with spatially restricted expression patterns. This approach identifies clusters of genes with similar expression patterns and functional relevance. As proof of concept, we characterize the previously unstudied gene CG5151 and show that it regulates Wnt signaling. Our method will enable the leveraging of scRNA-seq data for generating expression atlases of undifferentiated tissues during development.

Single-Cell RNA Sequencing with Drop-Seq.

Drop-Seq is a low-cost, high-throughput platform to profile thousands of cells by encapsualting them into individual droplets. Uniquely barcoded mRNA capture microparticles and cells are coconfined through a microfluidic device within the droplets where they undergo cell lysis and RNA hybridiztion. After breaking the droplets and pooling the hybridized particles, reverse transcription, PCR, and sequencing in single reactions allow to generate data from thousands of single-cell transcriptomes while maintaining information on the cellular origin of each transcript.

Retinoid resistance and multifaceted impairment of retinoic acid synthesis in glioblastoma.

Measuring concentrations of the differentiation-promoting hormone retinoic acid (RA) in glioblastoma tissues would help to understand the reason why RA treatment has been inefficient in clinical trials involving brain tumor patients. Here, we apply a recently established extraction and measurement protocol to screen glioblastoma tissues for the levels of the RA precursor retinol and biologically active RA. Combining this approach with mRNA analyses of 26 tumors and 8 normal brains, we identify a multifaceted disturbance of RA synthesis in glioblastoma, involving multiple aldehyde dehydrogenase 1 family and retinol dehydrogenase enzymes. Through database studies and methylation analyses, we narrow down chromosomal deletions and aberrant promoter hypermethylation as potential mechanisms accounting for these alterations. Employing chromatin immunoprecipitation analyses and cell-culture studies, we further show that chromatin at RA target genes is poised to RA substitution, but most glioblastoma cell cultures are completely resistant to RA treatment. This paradoxical RA response is unrelated to alternative RA signaling through the fatty acid-binding protein 5/peroxisome proliferator-activated receptor delta axis. Our data suggest a multifaceted disturbance of RA synthesis in glioblastoma and contribute to reconsider current RA treatment strategies.

Aberrant self-renewal and quiescence contribute to the aggressiveness of glioblastoma.

Cancer cells with enhanced self-renewal capacity influence tumour growth in glioblastoma. So far, a variety of surrogate markers have been proposed to enrich these cells, emphasizing the need to devise new characterization methods. Here, we screen a large panel of glioblastoma cultures (n = 21) cultivated under stem cell-permissive conditions and identify several cell lines with enhanced self-renewal capacity. These cell lines are capable of matrix-independent growth and form fast-growing, orthotopic tumours in mice. Employing isolation, re-plating, and label-retention techniques, we show that self-renewal potential of individual cells is partitioned asymmetrically between daughter cells in a robust and cell line-specific fashion. This yields populations of fast- and slow-cycling cells, which differ in the expression of cell cycle-associated transcripts. Intriguingly, fast-growing cells keep their slow-cycling counterparts in a reversible state of quiescence associated with high chemoresistance. Our results suggest that two different subpopulations of tumour cells contribute to aberrant growth and tumour recurrence after therapy in glioblastoma.

Functional characterization of ENPP1 reveals a link between cell cycle progression and stem-like phenotype in glioblastoma.

A high-throughput phenotypic screen in glioblastoma stem-like cells (GSCs) identified a novel molecular mechanism in which ectonucleotide pyrophosphatase/phosphodiesterase 1 (ENPP1) plays an important role in balancing the pool of nucleotides, thus maintaining GSCs in an undifferentiated proliferative state. This finding highlights the connection between cell cycle length and the stem-like tumor state.

LGR5 is a marker of poor prognosis in glioblastoma and is required for survival of brain cancer stem-like cells.

In various types of cancers including glioblastoma, accumulating evidence show the existence of cancer stem-like cells (CSCs), characterized by stem cell marker expression, capability of differentiation and self-renewal, and high potential for tumor propagation in vivo. LGR5, whose expression is positively regulated by the Wnt signaling pathway, is a stem cell marker in intestinal mucosa and hair follicle in the skin. As Wnt signaling is also involved in brain development, the function of LGR5 in the maintenance of brain CSCs is to be assessed. Our study showed that the LGR5 transcript level was increased in CSCs. Co-immunofluorescence staining demonstrated the co-localization of CD133- and LGR5-positive cells in glioblastoma tissue sections. Functionally, silencing of LGR5 by lentiviral shRNA-mediated knockdown induced apoptosis in brain CSCs. Moreover, LGR5 depletion led to a downregulation of L1 cell adhesion molecule expression. In line with an important function in glioma tumorigenesis, LGR5 expression increased with glioma progression and correlated with an adverse outcome. Our findings suggest that LGR5 plays a role in maintenance and/or survival of brain CSCs.

An activated mutant BRAF kinase domain is sufficient to induce pilocytic astrocytoma in mice.

Pilocytic astrocytoma (PA) is the most common type of primary brain tumor in children and the second most frequent cancer in childhood. Children with incompletely resected PA represent a clinically challenging patient cohort for whom conventional adjuvant therapies are only moderately effective. This has produced high clinical demand for testing of new molecularly targeted treatments. However, the development of new therapeutics for PA has been hampered by the lack of an adequate in vivo tumor model. Recent studies have identified activation of MAPK signaling, mainly by oncogenic BRAF activation, as a hallmark genetic event in the pathogenesis of human PA. Using in vivo retroviral somatic gene transfer into mouse neural progenitor cells, we have shown here that ectopic expression of the activated BRAF kinase domain is sufficient to induce PA in mice. Further in vitro analyses demonstrated that overexpression of activated BRAF led to increased proliferation of primary mouse astrocytes that could be inhibited by treatment with the kinase inhibitor sorafenib. Our in vivo model for PA shows that the activated BRAF kinase domain is sufficient to induce PA and highlights its role as a potential therapeutic target.