Single-cell analysis of population context advances RNAi screening at multiple levels

High-Content Screening Approaches That Minimize Confounding Factors in RNAi, CRISPR, and Small Molecule Screening

Screening arrayed libraries of reagents, particularly small molecules began as a vehicle for drug discovery, but the in last few years it has become a cornerstone of biological investigation, joining RNAi and CRISPR as methods for elucidating functional relationships that could not be anticipated, and illustrating the mechanisms behind basic and disease biology, and therapeutic resistance. However, these approaches share some common challenges, especially with respect to specificity or selectivity of the reagents as they are scaled to large protein families or the genome. High-content screening (HCS) has emerged as an important complement to screening, mostly the result of a wide array of specific molecular events, such as protein kinase and transcription factor activation, morphological changes associated with stem cell differentiation or the epithelial-mesenchymal transition of cancer cells. Beyond the range of cellular events that can be screened by HCS, image-based screening introduces new processes for differentiating between specific and nonspecific effects on cells. This chapter introduces these complexities and discusses strategies available in image-based screening that can mitigate the challenges they can bring to screening.

Dynamic Proteomics of Herpes Simplex Virus Infection

The cellular response to viral infection is usually studied at the level of cell populations. Currently, it remains an open question whether and to what extent cell-to-cell variability impacts the course of infection. Here we address this by dynamic proteomics-imaging and tracking 400 yellow fluorescent protein (YFP)-tagged host proteins in individual cells infected by herpes simplex virus 1. By quantifying time-lapse fluorescence imaging, we analyze how cell-to-cell variability impacts gene expression from the viral genome. We identify two proteins, RFX7 and geminin, whose levels at the time of infection correlate with successful initiation of gene expression. These proteins are cell cycle markers, and we find that the position in the cell cycle at the time of infection (along with the cell motility and local cell density) can reasonably predict in which individual cells gene expression from the viral genome will commence. We find that the onset of cell division dramatically impacts the progress of infection, with 70% of dividing cells showing no additional gene expression after mitosis. Last, we identify four host proteins that are specifically modulated in infected cells, of which only one has been previously recognized. SUMO2 and RPAP3 levels are rapidly reduced, while SLTM and YTHDC1 are redistributed to form nuclear foci. These modulations are dependent on the expression of ICP0, as shown by infection with two mutant viruses that lack ICP0. Taken together, our results provide experimental validation for the long-held notion that the success of infection is dependent on the state of the host cell at the time of infection.IMPORTANCE High-throughput assays have revolutionized many fields in biology, both by allowing a more global understanding of biological processes and by deciphering rare events in subpopulations. Here we use such an assay, dynamic proteomics, to study viral infection at the single-cell level. We follow tens of thousands of individual cells infected by herpes simplex virus using fluorescence live imaging. Our results link the state of a cell at the time of virus infection with its probability to successfully initiate gene expression from the viral genome. Further, we identified three cellular proteins that were previously unknown to respond to viral infection. We conclude that dynamic proteomics provides a powerful tool to study single-cell differences during viral infection.

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. Here, we introduce the steps required to create high-quality image-based (i.e., morphological) profiles from a collection of microscopy images. We recommend techniques that have proven useful in each stage of the data analysis process, on the basis of the experience of 20 laboratories worldwide that are refining their image-based cell-profiling methodologies in pursuit of biological discovery. The recommended techniques cover alternatives that may suit various biological goals, experimental designs, and laboratories' preferences.

Quantitative profiling of innate immune activation by viral infection in single cells

Cells infected by viruses can exhibit diverse patterns of viral and cellular gene expression. The patterns arise in part from the stochastic or noisy reaction kinetics associated with the small number of genomes, enzymes, and other molecules that typically initiate virus replication and activate cellular anti-viral defenses. It is not known what features, if any, of the early viral or cellular gene expression correlate with later processes of viral replication or cell survival. Here we used two fluorescent reporters to visualize innate immune activation of human prostate cancer (PC3) cells against infection by vesicular stomatitis virus. The cells were engineered to express green-fluorescent protein under control of the promoter for IFIT2, an interferon-sensitive component of the anti-viral response, while red-fluorescent protein was expressed as a byproduct of virus infection. To isolate and quantitatively analyze single-cells, we used a unique microwell array device and open-source image processing software. Kinetic analysis of viral and cellular reporter profiles from hundreds of cells revealed novel relationships between gene expression and the outcome of infection. Specifically, the relative timing rather than the magnitude of the viral gene expression and innate immune activation correlated with the infection outcome. Earlier viral or anti-viral gene expression favored or hindered virus growth, respectively. Further, analysis of kinetic parameters estimated from these data suggests a trade-off between robust antiviral signaling and cell death, as indicated by a higher rate of detectable cell lysis in infected cells with a detectable immune response. In short, cells that activate an immune response lyse at a higher rate. More broadly, we demonstrate how the intrinsic heterogeneity of individual cell behaviors can be exploited to discover features of viral and host gene expression that correlate with single-cell outcomes, which will ultimately impact whether or not infections spread.

Herpes simplex virus 1 interferes with autophagy of murine dendritic cells and impairs their ability to stimulate CD8+ T lymphocytes

The MHC class I presentation is responsible for the presentation of viral proteins to CD8⁺ T lymphocytes and mainly depends on the classical antigen processing pathway. Recently, a second pathway involving autophagy has been implicated in this process. Here, we show an increase in the capacity of murine dendritic cells (DCs) to present viral antigens on MHC class I after infection with a mutant herpes simplex virus 1 (HSV-1-Δ34.5), lacking infected cell protein 34.5 (ICP34.5), when compared to its parental HSV-1 strain. The ICP34.5 protein counteracts host cell translational arrest and suppresses macroautophagy, and the lack of this protein resulted in a low viral protein abundance, which was processed and presented in an efficient way. Our study demonstrates an important role of autophagy in processing endogenous viral proteins in HSV-1-infected DCs.

High-Throughput Imaging for the Discovery of Cellular Mechanisms of Disease

High-throughput imaging (HTI) is a powerful tool in the discovery of cellular disease mechanisms. While traditional approaches to identify disease pathways often rely on knowledge of the causative genetic defect, HTI-based screens offer an unbiased discovery approach based on any morphological or functional defects of disease cells or tissues. In this review, we provide an overview of the use of HTI for the study of human disease mechanisms. We discuss key technical aspects of HTI and highlight representative examples of its practical applications for the discovery of molecular mechanisms of disease, focusing on infectious diseases and host-pathogen interactions, cancer, and rare genetic diseases. We also present some of the current challenges and possible solutions offered by novel cell culture systems and genome engineering approaches.

Multiparametric Analysis of Cell Shape Demonstrates that β-PIX Directly Couples YAP Activation to Extracellular Matrix Adhesion

Mechanical signals from the extracellular matrix (ECM) and cellular geometry regulate the nuclear translocation of transcriptional regulators such as Yes-associated protein (YAP). Elucidating how physical signals control the activity of mechanosensitive proteins poses a technical challenge, because perturbations that affect cell shape may also affect protein localization indirectly. Here, we present an approach that mitigates confounding effects of cell-shape changes, allowing us to identify direct regulators of YAP localization. This method uses single-cell image analysis and statistical models that exploit the naturally occurring heterogeneity of cellular populations. Through systematic depletion of all human kinases, Rho family GTPases, GEFs, and GTPase activating proteins (GAPs), together with targeted chemical perturbations, we found that β-PIX, a Rac1/Ccd42 GEF, and PAK2, a Rac1/Cdc42 effector, drive both YAP activation and cell-ECM adhesion turnover during cell spreading. Our observations suggest that coupling YAP to adhesion dynamics acts as a mechano-timer, allowing cells to rapidly tune gene expression in response to physical signals.

A Critical and Comparative Review of Fluorescent Tools for Live-Cell Imaging

Fluorescent tools have revolutionized our ability to probe biological dynamics, particularly at the cellular level. Fluorescent sensors have been developed on several platforms, utilizing either small-molecule dyes or fluorescent proteins, to monitor proteins, RNA, DNA, small molecules, and even cellular properties, such as pH and membrane potential. We briefly summarize the impressive history of tool development for these various applications and then discuss the most recent noteworthy developments in more detail. Particular emphasis is placed on tools suitable for single-cell analysis and especially live-cell imaging applications. Finally, we discuss prominent areas of need in future fluorescent tool development-specifically, advancing our capability to analyze and integrate the plethora of high-content data generated by fluorescence imaging.

Recombinant herpes simplex virus type 1 strains with targeted mutations relevant for aciclovir susceptibility

Here, we describe a novel reliable method to assess the significance of individual mutations within the thymidine kinase (TK) gene of herpes simplex virus type 1 (HSV-1) to nucleoside analogue resistance. Eleven defined single nucleotide polymorphisms that occur in the TK gene of clinical HSV-1 isolates and a fluorescence reporter were introduced into the HSV-1 strain 17⁺ that had been cloned into a bacterial artificial chromosome. The susceptibility of these different strains to aciclovir, penciclovir, brivudin, and foscarnet was determined with a modified cytopathic effect reduction assay. The strains were also tested for their aciclovir susceptibility by measuring the relative fluorescence intensity as an indicator for HSV-1 replication and by quantifying the virus yield. Our data indicate that the amino acid substitutions R41H, R106H, A118V, L139V, K219T, S276R, L298R, S345P, and V348I represent natural polymorphisms of the TK protein, whereas G61A and P84L mediate broad cross-resistance against aciclovir, penciclovir, brivudin, and susceptibility to foscarnet. This method allows the definition of the resistance genotype of otherwise unclear mutations in the TK gene of HSV-1. Thus, it provides a scientific basis for antiviral testing in clinical isolates of patients suffering from serious diseases and will facilitate testing of new antivirals against HSV-1.

HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1

Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of targeted experiments for the discovery of novel protein-protein interactions.

A Multi-Lineage Screen Reveals mTORC1 Inhibition Enhances Human Pluripotent Stem Cell Mesendoderm and Blood Progenitor Production

Human pluripotent stem cells (hPSCs) exist in heterogeneous micro-environments with multiple subpopulations, convoluting fate-regulation analysis. We patterned hPSCs into engineered micro-environments and screened responses to 400 small-molecule kinase inhibitors, measuring yield and purity outputs of undifferentiated, neuroectoderm, mesendoderm, and extra-embryonic populations. Enrichment analysis revealed mammalian target of rapamycin (mTOR) inhibition as a strong inducer of mesendoderm. Dose responses of mTOR inhibitors such as rapamycin synergized with Bone Morphogenetic protein 4 (BMP4) and activin A to enhance the yield and purity of BRACHYURY-expressing cells. Mechanistically, small interfering RNA knockdown of RAPTOR, a component of mTOR complex 1, phenocopied the mesendoderm-enhancing effects of rapamycin. Functional analysis during mesoderm and endoderm differentiation revealed that mTOR inhibition increased the output of hemogenic endothelial cells 3-fold, with a concomitant enhancement of blood colony-forming cells. These data demonstrate the power of our multi-lineage screening approach and identify mTOR signaling as a node in hPSC differentiation to mesendoderm and its derivatives.

High-Content Screening for Quantitative Cell Biology

High-content screening (HCS), which combines automated fluorescence microscopy with quantitative image analysis, allows the acquisition of unbiased multiparametric data at the single cell level. This approach has been used to address diverse biological questions and identify a plethora of quantitative phenotypes of varying complexity in numerous different model systems. Here, we describe some recent applications of HCS, ranging from the identification of genes required for specific biological processes to the characterization of genetic interactions. We review the steps involved in the design of useful biological assays and automated image analysis, and describe major challenges associated with each. Additionally, we highlight emerging technologies and future challenges, and discuss how the field of HCS might be enhanced in the future.

Applications in image-based profiling of perturbations

A dramatic shift has occurred in how biologists use microscopy images. Whether experiments are small-scale or high-throughput, automatically quantifying biological properties in images is now widespread. We see yet another revolution under way: a transition towards using automated image analysis to not only identify phenotypes a biologist specifically seeks to measure ('screening') but also as an unbiased and sensitive tool to capture a wide variety of subtle features of cell (or organism) state ('profiling'). Mapping similarities among samples using image-based (morphological) profiling has tremendous potential to transform drug discovery, functional genomics, and basic biological research. Applications include target identification, lead hopping, library enrichment, functionally annotating genes/alleles, and identifying small molecule modulators of gene activity and disease-specific phenotypes.

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. Recently, advances in imaging and image-analysis methodologies have accelerated large-scale perturbation screens. Here, we describe the state of the art for image-based screening experiments and delineate experimental approaches and image-analysis approaches as well as discussing challenges and future directions, including leveraging CRISPR/Cas9-mediated genome engineering.

Visualizing quantitative microscopy data: History and challenges

Data visualization is a fundamental aspect of science. In the context of microscopy-based studies, visualization typically involves presentation of the images themselves. However, data visualization is challenging when microscopy experiments entail imaging of millions of cells, and complex cellular phenotypes are quantified in a high-content manner. Most well-established visualization tools are inappropriate for displaying high-content data, which has driven the development of new visualization methodology. In this review, we discuss how data has been visualized in both classical and high-content microscopy studies; as well as the advantages, and disadvantages, of different visualization methods.

Vaccine and Wild-Type Strains of Yellow Fever Virus Engage Distinct Entry Mechanisms and Differentially Stimulate Antiviral Immune Responses

The live attenuated yellow fever virus (YFV) vaccine 17D stands as a “gold standard” for a successful vaccine. 17D was developed empirically by passaging the wild-type Asibi strain in mouse and chicken embryo tissues. Despite its immense success, the molecular determinants for virulence attenuation and immunogenicity of the 17D vaccine are poorly understood. 17D evolved several mutations in its genome, most of which lie within the envelope (E) protein. Given the major role played by the YFV E protein during virus entry, it has been hypothesized that the residues that diverge between the Asibi and 17D E proteins may be key determinants of attenuation. In this study, we define the process of YFV entry into target cells and investigate its implication in the activation of the antiviral cytokine response. We found that Asibi infects host cells exclusively via the classical clathrin-mediated endocytosis, while 17D exploits a clathrin-independent pathway for infectious entry. We demonstrate that the mutations in the 17D E protein acquired during the attenuation process are sufficient to explain the differential entry of Asibi versus 17D. Interestingly, we show that 17D binds to and infects host cells more efficiently than Asibi, which culminates in increased delivery of viral RNA into the cytosol and robust activation of the cytokine-mediated antiviral response. Overall, our study reveals that 17D vaccine and Asibi enter target cells through distinct mechanisms and highlights a link between 17D attenuation, virus entry, and immune activation.

The yellow fever virus (YFV) vaccine 17D is one of the safest and most effective live virus vaccines ever developed. The molecular determinants for virulence attenuation and immunogenicity of 17D are poorly understood. 17D was generated by serially passaging the virulent Asibi strain in vertebrate tissues. Here we examined the entry mechanisms engaged by YFV Asibi and the 17D vaccine. We found the two viruses use different entry pathways. We show that the mutations differentiating the Asibi envelope (E) protein from the 17D E protein, which arose during attenuation, are key determinants for the use of these distinct entry routes. Finally, we demonstrate that 17D binds and enters host cells more efficiently than Asibi. This results in a higher uptake of viral RNA into the cytoplasm and consequently a greater cytokine-mediated antiviral response. Overall, our data provide new insights into the biology of YFV infection and the mechanisms of viral attenuation.

Mammary Adipose Tissue-Derived Lysophospholipids Promote Estrogen Receptor-Negative Mammary Epithelial Cell Proliferation

Lysophosphatidic acid (LPA), acting in an autocrine or paracrine fashion through G protein-coupled receptors, has been implicated in many physiologic and pathologic processes, including cancer. LPA is converted from lysophosphatidylcholine (LPC) by the secreted phospholipase autotaxin (ATX). Although various cell types can produce ATX, adipocyte-derived ATX is believed to be the major source of circulating ATX and also to be the major regulator of plasma LPA levels. In addition to ATX, adipocytes secrete numerous other factors (adipokines); although several adipokines have been implicated in breast cancer biology, the contribution of mammary adipose tissue-derived LPC/ATX/LPA (LPA axis) signaling to breast cancer is poorly understood. Using murine mammary fat-conditioned medium, we investigated the contribution of LPA signaling to mammary epithelial cancer cell biology and identified LPA signaling as a significant contributor to the oncogenic effects of the mammary adipose tissue secretome. To interrogate the role of mammary fat in the LPA axis during breast cancer progression, we exposed mammary adipose tissue to secreted factors from estrogen receptor-negative mammary epithelial cell lines and monitored changes in the mammary fat pad LPA axis. Our data indicate that bidirectional interactions between mammary cancer cells and mammary adipocytes alter the local LPA axis and increase ATX expression in the mammary fat pad during breast cancer progression. Thus, the LPC/ATX/LPA axis may be a useful target for prevention in patients at risk of ER-negative breast cancer. Cancer Prev Res; 9(5); 367-78. ©2016 AACR.

A parallel genome-wide RNAi screening strategy to identify host proteins important for entry of Marburg virus and H5N1 influenza virus

BACKGROUND

Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening.

METHODS

Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits.

RESULTS

The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study.

CONCLUSIONS

This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.

A new age in functional genomics using CRISPR/Cas9 in arrayed library screening

CRISPR technology has rapidly changed the face of biological research, such that precise genome editing has now become routine for many labs within several years of its initial development. What makes CRISPR/Cas9 so revolutionary is the ability to target a protein (Cas9) to an exact genomic locus, through designing a specific short complementary nucleotide sequence, that together with a common scaffold sequence, constitute the guide RNA bridging the protein and the DNA. Wild-type Cas9 cleaves both DNA strands at its target sequence, but this protein can also be modified to exert many other functions. For instance, by attaching an activation domain to catalytically inactive Cas9 and targeting a promoter region, it is possible to stimulate the expression of a specific endogenous gene. In principle, any genomic region can be targeted, and recent efforts have successfully generated pooled guide RNA libraries for coding and regulatory regions of human, mouse and Drosophila genomes with high coverage, thus facilitating functional phenotypic screening. In this review, we will highlight recent developments in the area of CRISPR-based functional genomics and discuss potential future directions, with a special focus on mammalian cell systems and arrayed library screening.

Φ-score: A cell-to-cell phenotypic scoring method for sensitive and selective hit discovery in cell-based assays

Phenotypic screening monitors phenotypic changes induced by perturbations, including those generated by drugs or RNA interference. Currently-used methods for scoring screen hits have proven to be problematic, particularly when applied to physiologically relevant conditions such as low cell numbers or inefficient transfection. Here, we describe the Φ-score, which is a novel scoring method for the identification of phenotypic modifiers or hits in cell-based screens. Φ-score performance was assessed with simulations, a validation experiment and its application to gene identification in a large-scale RNAi screen. Using robust statistics and a variance model, we demonstrated that the Φ-score showed better sensitivity, selectivity and reproducibility compared to classical approaches. The improved performance of the Φ-score paves the way for cell-based screening of primary cells, which are often difficult to obtain from patients in sufficient numbers. We also describe a dedicated merging procedure to pool scores from small interfering RNAs targeting the same gene so as to provide improved visualization and hit selection.

Trajectories of cell-cycle progression from fixed cell populations

An accurate dissection of sources of cell-to-cell variability is crucial for quantitative biology at the single-cell level but has been challenging for the cell cycle. We present Cycler, a robust method that constructs a continuous trajectory of cell-cycle progression from images of fixed cells. Cycler handles heterogeneous microenvironments and does not require perturbations or genetic markers, making it generally applicable to quantifying multiple sources of cell-to-cell variability in mammalian cells.

Morphological Profiles of RNAi-Induced Gene Knockdown Are Highly Reproducible but Dominated by Seed Effects

RNA interference and morphological profiling-the measurement of thousands of phenotypes from individual cells by microscopy and image analysis-are a potentially powerful combination. We show that morphological profiles of RNAi-induced knockdown using the Cell Painting assay are in fact highly sensitive and reproducible. However, we find that the magnitude and prevalence of off-target effects via the RNAi seed-based mechanism make morphological profiles of RNAi reagents targeting the same gene look no more similar than reagents targeting different genes. Pairs of RNAi reagents that share the same seed sequence produce image-based profiles that are much more similar to each other than profiles from pairs designed to target the same gene, a phenomenon previously observed in small-scale gene-expression profiling experiments. Various strategies have been used to enrich on-target versus off-target effects in the context of RNAi screening where a narrow set of phenotypes are measured, mostly based on comparing multiple sequences targeting the same gene; however, new approaches will be needed to make RNAi morphological profiling (that is, comparing multi-dimensional phenotypes) viable. We have shared our raw data and computational pipelines to facilitate research.

Experimental approaches to phenotypic diversity in infection

Microbial infections are burdening human health, even after the advent of antibiotics, vaccines and hygiene. Thus, infection biology has aimed at the molecular understanding of the pathogen-host interaction. This has revealed key virulence factors, host cell signaling pathways and immune responses. However, our understanding of the infection process is still incomplete. Recent evidence suggests that phenotypic diversity can have important consequences for the infection process. Diversity arises from the formation of distinct subpopulations of pathogen cells (with distinct virulence factor expression patterns) and host cells (with distinct response capacities). For technical reasons, such phenotypic diversity has often been overlooked. We are highlighting several striking examples and discuss the experimental approaches available for analyzing the different subpopulations. Single cell reporters and approaches from systems biology do hold much promise.

Kallikrein-8 Proteolytically Processes Human Papillomaviruses in the Extracellular Space To Facilitate Entry into Host Cells

The entry of human papillomaviruses into host cells is a complex process. It involves conformational changes at the cell surface, receptor switching, internalization by a novel endocytic mechanism, uncoating in endosomes, trafficking of a subviral complex to the Golgi complex, and nuclear entry during mitosis. Here, we addressed how the stabilizing contacts in the capsid of human papillomavirus 16 (HPV16) may be reversed to allow uncoating of the viral genome. Using biochemical and cell-biological analyses, we determined that the major capsid protein L1 underwent proteolytic cleavage during entry. In addition to a dispensable cathepsin-mediated proteolysis that occurred likely after removal of capsomers from the subviral complex in endosomes, at least two further proteolytic cleavages of L1 were observed, one of which was independent of the low-pH environment of endosomes. This cleavage occurred extracellularly. Further analysis showed that the responsible protease was the secreted trypsin-like serine protease kallikrein-8 (KLK8) involved in epidermal homeostasis and wound healing. Required for infection, the cleavage was facilitated by prior interaction of viral particles with heparan sulfate proteoglycans. KLK8-mediated cleavage was crucial for further conformational changes exposing an important epitope of the minor capsid protein L2. Occurring independently of cyclophilins and of furin that mediate L2 exposure, KLK8-mediated cleavage of L1 likely facilitated access to L2, located in the capsid lumen, and potentially uncoating. Since HPV6 and HPV18 also required KLK8 for entry, we propose that the KLK8-dependent entry step is conserved.

IMPORTANCE

Our analysis of the proteolytic processing of incoming HPV16, an etiological agent of cervical cancer, demonstrated that the capsid is cleaved extracellularly by a serine protease active during wound healing and that this cleavage was crucial for infection. The cleavage of L1 is one of at least four structural alterations that prime the virus extracellularly for receptor switching, internalization, and possibly uncoating. This step was also important for HPV6 and HPV18, which may suggest that it is conserved among the papillomaviruses. This study advances the understanding of how HPV16 initially infects cells, strengthens the notion that wounding facilitates infection of epidermal tissue, and may help the development of antiviral measures.

A Multivariate Computational Method to Analyze High-Content RNAi Screening Data

High-content screening (HCS) using RNA interference (RNAi) in combination with automated microscopy is a powerful investigative tool to explore complex biological processes. However, despite the plethora of data generated from these screens, little progress has been made in analyzing HC data using multivariate methods that exploit the full richness of multidimensional data. We developed a novel multivariate method for HCS, multivariate robust analysis method (M-RAM), integrating image feature selection with ranking of perturbations for hit identification, and applied this method to an HC RNAi screen to discover novel components of the DNA damage response in an osteosarcoma cell line. M-RAM automatically selects the most informative phenotypic readouts and time points to facilitate the more efficient design of follow-up experiments and enhance biological understanding. Our method outperforms univariate hit identification and identifies relevant genes that these approaches would have missed. We found that statistical cell-to-cell variation in phenotypic responses is an important predictor of hits in RNAi-directed image-based screens. Genes that we identified as modulators of DNA damage signaling in U2OS cells include B-Raf, a cancer driver gene in multiple tumor types, whose role in DNA damage signaling we confirm experimentally, and multiple subunits of protein kinase A.

NEMix: single-cell nested effects models for probabilistic pathway stimulation

Nested effects models have been used successfully for learning subcellular networks from high-dimensional perturbation effects that result from RNA interference (RNAi) experiments. Here, we further develop the basic nested effects model using high-content single-cell imaging data from RNAi screens of cultured cells infected with human rhinovirus. RNAi screens with single-cell readouts are becoming increasingly common, and they often reveal high cell-to-cell variation. As a consequence of this cellular heterogeneity, knock-downs result in variable effects among cells and lead to weak average phenotypes on the cell population level. To address this confounding factor in network inference, we explicitly model the stimulation status of a signaling pathway in individual cells. We extend the framework of nested effects models to probabilistic combinatorial knock-downs and propose NEMix, a nested effects mixture model that accounts for unobserved pathway activation. We analyzed the identifiability of NEMix and developed a parameter inference scheme based on the Expectation Maximization algorithm. In an extensive simulation study, we show that NEMix improves learning of pathway structures over classical NEMs significantly in the presence of hidden pathway stimulation. We applied our model to single-cell imaging data from RNAi screens monitoring human rhinovirus infection, where limited infection efficiency of the assay results in uncertain pathway stimulation. Using a subset of genes with known interactions, we show that the inferred NEMix network has high accuracy and outperforms the classical nested effects model without hidden pathway activity. NEMix is implemented as part of the R/Bioconductor package ‘nem’ and available at www.cbg.ethz.ch/software/NEMix.

Experiments monitoring individual cells show that cells can behave differently even under same experimental conditions. Summarizing measurements over a population of cells can lead to weak and widely deviating signals, and subsequently applied modeling approaches, like network inference, will suffer from this information loss. Nested effects models, a method tailored to reconstruct signaling networks from high-dimensional read-outs of gene silencing experiments, have so far been only applied on the cell population level. These models assume the pathway under consideration to be activated in all cells. The signal flow is only disrupted, when genes are silenced. However, if this assumption is not met, inference results can be incorrect, because observed effects are interpreted wrongly. We extended nested effects models, to use the power of single-cell resolution data sets. We introduce a new unobserved factor, which describes the pathway activity of single cells. The pathway activity is learned for each cell during network inference. We apply our model to gene silencing screens, investigating human rhino virus infection of single cells from microscopy imaging features. Comparing the learned network to the known KEGG pathway of the genes shows that our method recovers networks significantly better than classical nested effects models without capturing of hidden signaling.

An investigation of herpes simplex virus type 1 latency in a novel mouse dorsal root ganglion model suggests a role for ICP34.5 in reactivation

After a primary lytic infection at the epithelia, herpes simplex virus type 1 (HSV-1) enters the innervating sensory neurons and translocates to the nucleus, where it establishes a quiescent latent infection. Periodically, the virus can reactivate and the progeny viruses spread back to the epithelium. Here, we introduce an embryonic mouse dorsal root ganglion (DRG) culture system, which can be used to study the mechanisms that control the establishment, maintenance and reactivation from latency. Use of acyclovir is not necessary in our model. We examined different phases of the HSV-1 life cycle in DRG neurons, and showed that WT HSV-1 could establish both lytic and latent form of infection in the cells. After reactivating stimulus, the WT viruses showed all markers of true reactivation. In addition, we showed that deletion of the γ(1)34.5 gene rendered the virus incapable of reactivation, even though the virus was clearly able to replicate and persist in a quiescent form in the DRG neurons.

Wnt directs the endosomal flux of LDL-derived cholesterol and lipid droplet homeostasis

The Wnt pathway, which controls crucial steps of the development and differentiation programs, has been proposed to influence lipid storage and homeostasis. In this paper, using an unbiased strategy based on high-content genome-wide RNAi screens that monitored lipid distribution and amounts, we find that Wnt3a regulates cellular cholesterol. We show that Wnt3a stimulates the production of lipid droplets and that this stimulation strictly depends on endocytosed, LDL-derived cholesterol and on functional early and late endosomes. We also show that Wnt signaling itself controls cholesterol endocytosis and flux along the endosomal pathway, which in turn modulates cellular lipid homeostasis. These results underscore the importance of endosome functions for LD formation and reveal a previously unknown regulatory mechanism of the cellular programs controlling lipid storage and endosome transport under the control of Wnt signaling.

An integrative approach for a network based meta-analysis of viral RNAi screens

BACKGROUND

Big data is becoming ubiquitous in biology, and poses significant challenges in data analysis and interpretation. RNAi screening has become a workhorse of functional genomics, and has been applied, for example, to identify host factors involved in infection for a panel of different viruses. However, the analysis of data resulting from such screens is difficult, with often low overlap between hit lists, even when comparing screens targeting the same virus. This makes it a major challenge to select interesting candidates for further detailed, mechanistic experimental characterization.

RESULTS

To address this problem we propose an integrative bioinformatics pipeline that allows for a network based meta-analysis of viral high-throughput RNAi screens. Initially, we collate a human protein interaction network from various public repositories, which is then subjected to unsupervised clustering to determine functional modules. Modules that are significantly enriched with host dependency factors (HDFs) and/or host restriction factors (HRFs) are then filtered based on network topology and semantic similarity measures. Modules passing all these criteria are finally interpreted for their biological significance using enrichment analysis, and interesting candidate genes can be selected from the modules.

CONCLUSIONS

We apply our approach to seven screens targeting three different viruses, and compare results with other published meta-analyses of viral RNAi screens. We recover key hit genes, and identify additional candidates from the screens. While we demonstrate the application of the approach using viral RNAi data, the method is generally applicable to identify underlying mechanisms from hit lists derived from high-throughput experimental data, and to select a small number of most promising genes for further mechanistic studies.

Probing the virus host interaction in high containment: an approach using pooled short hairpin RNA

The study of viruses in high containment offers unique challenges for technology-intense approaches. These approaches include high-throughput screening for small-molecule antivirals and genetic perturbation-based screens for host factors required for viral replication. Here, we describe the use of whole-genome scale pooled short hairpin RNA (shRNA) libraries to screen for host factors necessary for viral infection at BSL2, and the transition of this technique into the BSL4 environment. Pooled screening provides a unique way to circumvent many of the technological challenges associated with other high-throughput screening approaches in high containment. Our pooled screening approach identified host factors involved in the replication of orthopoxviruses (Vaccinia and Monkeypox) and filoviruses (Ebola and Marburg) under conditions that enable straightforward screen-to-follow-up approaches.

Prevention of herpes simplex virus induced stromal keratitis by a glycoprotein B-specific monoclonal antibody

The increasing incidence of acyclovir (ACV) and multidrug-resistant strains in patients with corneal HSV-1 infections leading to Herpetic Stromal Keratitis (HSK) is a major health problem in industrialized countries and often results in blindness. To overcome this obstacle, we have previously developed an HSV-gB-specific monoclonal antibody (mAb 2c) that proved to be highly protective in immunodeficient NOD/SCID-mice towards genital infections. In the present study, we examined the effectivity of mAb 2c in preventing the immunopathological disease HSK in the HSK BALB/c mouse model. Therefore, mice were inoculated with HSV-1 strain KOS on the scarified cornea to induce HSK and subsequently either systemically or topically treated with mAb 2c. Systemic treatment was performed by intravenous administration of mAb 2c 24 h prior to infection (pre-exposure prophylaxis) or 24, 40, and 56 hours after infection (post-exposure immunotherapy). Topical treatment was performed by periodical inoculations (5 times per day) of antibody-containing eye drops as control, starting at 24 h post infection. Systemic antibody treatment markedly reduced viral loads at the site of infection and completely protected mice from developing HSK. The administration of the antiviral antibody prior or post infection was equally effective. Topical treatment had no improving effect on the severity of HSK. In conclusion, our data demonstrate that mAb 2c proved to be an excellent drug for the treatment of corneal HSV-infections and for prevention of HSK and blindness. Moreover, the humanized counterpart (mAb hu2c) was equally effective in protecting mice from HSV-induced HSK when compared to the parental mouse antibody. These results warrant the future development of this antibody as a novel approach for the treatment of corneal HSV-infections in humans.

Application of the proximity-dependent assay and fluorescence imaging approaches to study viral entry pathways

Virus entry into cells is a complex, multistep process that requires the coordinated activities of a large number of cellular factors and multiple membrane compartments. Because viruses can enter cells via one or more of a large number of preexisting pathways, understanding the mechanism of virus entry and transport between various intracellular compartments is a challenging task. The arrival of "omics" technologies such as genome-wide RNA interference screens has greatly advanced our ability to study the molecular intricacies of viral entry. Bioinformatics analyses of high-throughput screen data can identify enriched gene categories and specific individual genes required for infection, which can yield important insights into the cellular compartments that viruses traverse during infection. Although there are a variety of well-established genetic and biochemical approaches to validate genome-wide screen findings, confirmation of phenotypes obtained from RNA interference studies remains an important challenge. Imaging techniques commonly used to visualize virus localization to cellular organelles are often prone to artifacts that result from the necessity of using a high multiplicity of infection. Fortunately, recent advances in microscopy-based methods for studying protein location have improved our ability to accurately pinpoint virus localization within its host cell. Here we describe in detail one such technique-the proximity ligation assay (PLA)-as a tool to validate findings from a genome-wide loss-of-function genetic screen. In addition, we discuss a number of important considerations for the utilization of immunofluorescence microscopy and RNA interference to investigate the molecular mechanisms of virus entry.

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

Simultaneous analysis of large-scale RNAi screens for pathogen entry

BACKGROUND

Large-scale RNAi screening has become an important technology for identifying genes involved in biological processes of interest. However, the quality of large-scale RNAi screening is often deteriorated by off-targets effects. In order to find statistically significant effector genes for pathogen entry, we systematically analyzed entry pathways in human host cells for eight pathogens using image-based kinome-wide siRNA screens with siRNAs from three vendors. We propose a Parallel Mixed Model (PMM) approach that simultaneously analyzes several non-identical screens performed with the same RNAi libraries.

RESULTS

We show that PMM gains statistical power for hit detection due to parallel screening. PMM allows incorporating siRNA weights that can be assigned according to available information on RNAi quality. Moreover, PMM is able to estimate a sharedness score that can be used to focus follow-up efforts on generic or specific gene regulators. By fitting a PMM model to our data, we found several novel hit genes for most of the pathogens studied.

CONCLUSIONS

Our results show parallel RNAi screening can improve the results of individual screens. This is currently particularly interesting when large-scale parallel datasets are becoming more and more publicly available. Our comprehensive siRNA dataset provides a public, freely available resource for further statistical and biological analyses in the high-content, high-throughput siRNA screening field.

Single-cell and multivariate approaches in genetic perturbation screens

Large-scale genetic perturbation screens are a classical approach in biology and have been crucial for many discoveries. New technologies can now provide unbiased quantification of multiple molecular and phenotypic changes across tens of thousands of individual cells from large numbers of perturbed cell populations simultaneously. In this Review, we describe how these developments have enabled the discovery of new principles of intracellular and intercellular organization, novel interpretations of genetic perturbation effects and the inference of novel functional genetic interactions. These advances now allow more accurate and comprehensive analyses of gene function in cells using genetic perturbation screens.

Coronavirus cell entry occurs through the endo-/lysosomal pathway in a proteolysis-dependent manner

Enveloped viruses need to fuse with a host cell membrane in order to deliver their genome into the host cell. While some viruses fuse with the plasma membrane, many viruses are endocytosed prior to fusion. Specific cues in the endosomal microenvironment induce conformational changes in the viral fusion proteins leading to viral and host membrane fusion. In the present study we investigated the entry of coronaviruses (CoVs). Using siRNA gene silencing, we found that proteins known to be important for late endosomal maturation and endosome-lysosome fusion profoundly promote infection of cells with mouse hepatitis coronavirus (MHV). Using recombinant MHVs expressing reporter genes as well as a novel, replication-independent fusion assay we confirmed the importance of clathrin-mediated endocytosis and demonstrated that trafficking of MHV to lysosomes is required for fusion and productive entry to occur. Nevertheless, MHV was shown to be less sensitive to perturbation of endosomal pH than vesicular stomatitis virus and influenza A virus, which fuse in early and late endosomes, respectively. Our results indicate that entry of MHV depends on proteolytic processing of its fusion protein S by lysosomal proteases. Fusion of MHV was severely inhibited by a pan-lysosomal protease inhibitor, while trafficking of MHV to lysosomes and processing by lysosomal proteases was no longer required when a furin cleavage site was introduced in the S protein immediately upstream of the fusion peptide. Also entry of feline CoV was shown to depend on trafficking to lysosomes and processing by lysosomal proteases. In contrast, MERS-CoV, which contains a minimal furin cleavage site just upstream of the fusion peptide, was negatively affected by inhibition of furin, but not of lysosomal proteases. We conclude that a proteolytic cleavage site in the CoV S protein directly upstream of the fusion peptide is an essential determinant of the intracellular site of fusion.

Enveloped viruses need to fuse with a host cell membrane in order to deliver their genome into the host cell. In the present study we investigated the entry of coronaviruses (CoVs). CoVs are important pathogens of animals and man with high zoonotic potential as demonstrated by the emergence of SARS- and MERS-CoVs. Previous studies resulted in apparently conflicting results with respect to CoV cell entry, particularly regarding the fusion-activating requirements of the CoV S protein. By combining cell-biological, infection, and fusion assays we demonstrated that murine hepatitis virus (MHV), a prototypic member of the CoV family, enters cells via clathrin-mediated endocytosis. Moreover, although MHV does not depend on a low pH for fusion, the virus was shown to rely on trafficking to lysosomes for proteolytic cleavage of its spike (S) protein and membrane fusion to occur. Based on these results we predicted and subsequently demonstrated that MERS- and feline CoV require cleavage by different proteases and escape the endo/lysosomal system from different compartments. In conclusion, we elucidated the MHV entry pathway in detail and demonstrate that a proteolytic cleavage site in the S protein of different CoVs is an essential determinant of the intracellular site of fusion.

New developments of RNAi in Paracoccidioides brasiliensis: prospects for high-throughput, genome-wide, functional genomics

Background

The Fungal Genome Initiative of the Broad Institute, in partnership with the Paracoccidioides research community, has recently sequenced the genome of representative isolates of this human-pathogen dimorphic fungus: Pb18 (S1), Pb03 (PS2) and Pb01. The accomplishment of future high-throughput, genome-wide, functional genomics will rely upon appropriate molecular tools and straightforward techniques to streamline the generation of stable loss-of-function phenotypes. In the past decades, RNAi has emerged as the most robust genetic technique to modulate or to suppress gene expression in diverse eukaryotes, including fungi. These molecular tools and techniques, adapted for RNAi, were up until now unavailable for P. brasiliensis.

Methodology/Principal Findings

In this paper, we report Agrobacterium tumefaciens mediated transformation of yeast cells for high-throughput applications with which higher transformation frequencies of 150±24 yeast cell transformants per 1×10⁶ viable yeast cells were obtained. Our approach is based on a bifunctional selective marker fusion protein consisted of the Streptoalloteichus hindustanus bleomycin-resistance gene (Shble) and the intrinsically fluorescent monomeric protein mCherry which was codon-optimized for heterologous expression in P. brasiliensis. We also report successful GP43 gene knock-down through the expression of intron-containing hairpin RNA (ihpRNA) from a Gateway-adapted cassette (cALf) which was purpose-built for gene silencing in a high-throughput manner. Gp43 transcript levels were reduced by 73.1±22.9% with this approach.

Conclusions/Significance

We have a firm conviction that the genetic transformation technique and the molecular tools herein described will have a relevant contribution in future Paracoccidioides spp. functional genomics research.

Diverse eukaryotes, including various fungi, utilize RNA interference (RNAi) pathways to regulate genome-wide gene expression. Since the initial characterization of these pathways and the demonstration of its artificial induction in the filamentous ascomycete Neurospora crassa, RNAi has emerged as the most robust reverse-genetic technique to scrutinize the function of genes and has been increasingly adopted in high-throughput functional genomics in search of new insights into fungal pathobiology. Herein, we have developed appropriate molecular tools and straightforward techniques to streamline the generation of stable loss-of-function phenotypes for the human-pathogen Paracoccidioides brasiliensis, which is phylogenetically related to Blastomyces dermatitidis, Coccidioides immitis and Histoplasma capsulatum. Likewise these thermo-dimorphic fungi, P. brasiliensis infection in immunocompetent or immunocompromised individuals ensue in a life-threatening systemic mycosis known as Paracoccidioidomycosis.

A new toolbox for assessing single cells

Unprecedented access to the biology of single cells is now feasible, enabled by recent technological advancements that allow us to manipulate and measure sparse samples and achieve a new level of resolution in space and time. This review focuses on advances in tools to study single cells for specific areas of biology. We examine both mature and nascent techniques to study single cells at the genomics, transcriptomics, and proteomics level. In addition, we provide an overview of tools that are well suited for following biological responses to defined perturbations with single-cell resolution. Techniques to analyze and manipulate single cells through soluble and chemical ligands, the microenvironment, and cell-cell interactions are provided. For each of these topics, we highlight the biological motivation, applications, methods, recent advances, and opportunities for improvement. The toolbox presented in this review can function as a starting point for the design of single-cell experiments.

Herpes simplex virus internalization into epithelial cells requires Na+/H+ exchangers and p21-activated kinases but neither clathrin- nor caveolin-mediated endocytosis

Herpes simplex virus 1 (HSV-1) is an alphaherpesvirus that has been reported to infect some epithelial cell types by fusion at the plasma membrane but others by endocytosis. To determine the molecular mechanisms of productive HSV-1 cell entry, we perturbed key endocytosis host factors using specific inhibitors, RNA interference (RNAi), or overexpression of dominant negative proteins and investigated their effects on HSV-1 infection in the permissive epithelial cell lines Vero, HeLa, HEp-2, and PtK2. HSV-1 internalization required neither endosomal acidification nor clathrin- or caveolin-mediated endocytosis. In contrast, HSV-1 gene expression and internalization were significantly reduced after treatment with 5-(N-ethyl-N-isopropyl)amiloride (EIPA). EIPA blocks the activity of Na(+)/H(+) exchangers, which are plasma membrane proteins implicated in all forms of macropinocytosis. HSV-1 internalization furthermore required the function of p21-activated kinases that contribute to macropinosome formation. However, in contrast to some forms of macropinocytosis, HSV-1 did not enlist the activities of protein kinase C (PKC), tyrosine kinases, C-terminal binding protein 1, or dynamin to activate its internalization. These data suggest that HSV-1 depends on Na(+)/H(+) exchangers and p21-activated kinases either for macropinocytosis or for local actin rearrangements required for fusion at the plasma membrane or subsequent passage through the actin cortex underneath the plasma membrane.

IMPORTANCE

After initial replication in epithelial cells, herpes simplex viruses (HSVs) establish latent infections in neurons innervating these regions. Upon primary infection and reactivation from latency, HSVs cause many human skin and neurological diseases, particularly in immunocompromised hosts, despite the availability of effective antiviral drugs. Many viruses use macropinocytosis for virus internalization, and many host factors mediating this entry route have been identified, although the specific perturbation profiles vary for different host and viral cargo. In addition to an established entry pathway via acidic endosomes, we show here that HSV-1 internalization depended on sodium-proton exchangers at the plasma membrane and p21-activated kinases. These results suggest that HSV-1 requires a reorganization of the cortical actin cytoskeleton, either for productive cell entry via pH-independent fusion from macropinosomes or for fusion at the plasma membrane, and subsequent cytosolic passage to microtubules that mediate capsid transport to the nucleus for genome uncoating and replication.

RNAi screening comes of age: improved techniques and complementary approaches

Gene silencing through sequence-specific targeting of mRNAs by RNAi has enabled genome-wide functional screens in cultured cells and in vivo in model organisms. These screens have resulted in the identification of new cellular pathways and potential drug targets. Considerable progress has been made to improve the quality of RNAi screen data through the development of new experimental and bioinformatics approaches. The recent availability of genome-editing strategies, such as the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system, when combined with RNAi, could lead to further improvements in screen data quality and follow-up experiments, thus promoting our understanding of gene function and gene regulatory networks.

Endocytosis, signaling, and beyond

The endocytic network comprises a vast and intricate system of membrane-delimited cell entry and cargo sorting routes running between biochemically and functionally distinct intracellular compartments. The endocytic network caters to the organization and redistribution of diverse subcellular components, and mediates appropriate shuttling and processing of materials acquired from neighboring cells or the extracellular milieu. Such trafficking logistics, despite their importance, represent only one facet of endocytic function. The endocytic network also plays a key role in organizing, mediating, and regulating cellular signal transduction events. Conversely, cellular signaling processes tightly control the endocytic pathway at different steps. The present article provides a perspective on the intimate relationships that exist between particular endocytic and cellular signaling processes in mammalian cells, within the context of understanding the impact of this nexus on integrated physiology.

High-throughput approaches to measuring cell death

Cell death is integral to developmental and disease processes, and high-throughput screening (HTS) has been instrumental both for understanding biological mechanisms underlying cell death and for discovering novel therapeutic agents targeting these pathways. The various cell death modalities and their distinctive morphological and biochemical features have led to the development of a staggering variety of assays to measure these features, many of which have been adapted to HTS format. Although not all cell death assays are readily amenable to a high-throughput format, the potential power of HTS assays and increasing accessibility to associated technology make it likely that new approaches will continue to emerge. In particular, many recent studies in this field have used multiplex assays and high-content imaging to measure several features concurrently. Here, we discuss a broad array of considerations for designing HTS cell death assays, including some common challenges and pitfalls. We aim to provide a framework for deciding the most appropriate biological readouts, assay strategy and mode, workflow, controls, validation, and bioinformatics.