An Easy Path for Correlative Electron and Super-Resolution Light Microscopy.

A number of new Correlative Light and Electron Microscopy approaches have been developed over the past years, offering the opportunity to combine the specificity and bio-compatibility of light microscopy with the high resolution achieved in electron microscopy. More recently, these approaches have taken one step further and also super-resolution light microscopy was combined with transmission or scanning electron microscopy. This combination usually requires moving the specimen between different imaging systems, an expensive set-up and relatively complicated imaging workflows. Here we present a way to overcome these difficulties by exploiting a commercially available wide-field fluorescence microscope integrated in the specimen chamber of a Scanning Electron Microscope (SEM) to perform correlative LM/EM studies. Super-resolution light microscopy was achieved by using a recently developed algorithm - the Super-Resolution Radial Fluctuations (SRRF) - to improve the resolution of diffraction limited fluorescent images. With this combination of hardware/software it is possible to obtain correlative super-resolution light and scanning electron microscopy images in an easy and fast way. The imaging workflow is described and demonstrated on fluorescently labelled amyloid fibrils, fibrillar protein aggregates linked to the onset of multiple neurodegenerative diseases, revealing information about their polymorphism.

Apoptosis and eryptosis: Striking differences on biomembrane level.

The cell plasma membrane plays an essential role in programmed cell death of nucleated cells (apoptosis) and erythrocytes (eryptosis), and its changes due to loss of transmembrane asymmetry are quite similar. However, nucleated cells possess the network of intracellular membranes, which are missing in erythrocytes. Providing comparative studies with series of molecular probes, we observe dramatic differences in membrane lipid order in the course of apoptosis and eryptosis. In contrast to nucleated cells, in which a significant drop of the lipid order in the plasma membrane is observed, the erythrocyte membrane retains the relatively high level of the lipid order. Observation in nucleated cells of significant differences between inner and plasma membranes and detection of apoptotic bodies with different organization suggest that the decrease in the lipid order of their plasma membrane could be at least partially explained by the phospholipid and/or cholesterol exchange between membranes. Such features are absent in erythrocytes.

Genome-wide RNAi Screening Identifies Protein Modules Required for 40S Subunit Synthesis in Human Cells.

Ribosome biogenesis is a highly complex process requiring many assisting factors. Studies in yeast have yielded comprehensive knowledge of the cellular machinery involved in this process. However, many aspects of ribosome synthesis are different in higher eukaryotes, and the global set of mammalian ribosome biogenesis factors remains unexplored. We used an imaging-based, genome-wide RNAi screen to find human proteins involved in 40S ribosomal subunit biogenesis. Our analysis identified ∼ 300 factors, many part of essential protein modules such as the small subunit (SSU) processome, the eIF3 and chaperonin complexes, and the ubiquitin-proteasome system. We demonstrate a role for the vertebrate-specific factor RBIS in ribosome synthesis, uncover a requirement for the CRL4 E3 ubiquitin ligase in nucleolar ribosome biogenesis, and reveal that intracellular glutamine synthesis supports 40S subunit production.

CIDRE: an illumination-correction method for optical microscopy.

Uneven illumination affects every image acquired by a microscope. It is often overlooked, but it can introduce considerable bias to image measurements. The most reliable correction methods require special reference images, and retrospective alternatives do not fully model the correction process. Our approach overcomes these issues for most optical microscopy applications without the need for reference images.

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.

Experimenting liver fibrosis diagnostic by two photon excitation microscopy and Bag-of-Features image classification.

The accurate staging of liver fibrosis is of paramount importance to determine the state of disease progression, therapy responses, and to optimize disease treatment strategies. Non-linear optical microscopy techniques such as two-photon excitation fluorescence (TPEF) and second harmonic generation (SHG) can image the endogenous signals of tissue structures and can be used for fibrosis assessment on non-stained tissue samples. While image analysis of collagen in SHG images was consistently addressed until now, cellular and tissue information included in TPEF images, such as inflammatory and hepatic cell damage, equally important as collagen deposition imaged by SHG, remain poorly exploited to date. We address this situation by experimenting liver fibrosis quantification and scoring using a combined approach based on TPEF liver surface imaging on a Thioacetamide-induced rat model and a gradient based Bag-of-Features (BoF) image classification strategy. We report the assessed performance results and discuss the influence of specific BoF parameters to the performance of the fibrosis scoring framework.

Nuclear motility in glioma cells reveals a cell-line dependent role of various cytoskeletal components.

Nuclear migration is a general term for the movement of the nucleus towards a specific site in the cell. These movements are involved in a number of fundamental biological processes, such as fertilization, cell division, and embryonic development. Despite of its importance, the mechanism of nuclear migration is still poorly understood in mammalian cells. In order to shed light on the mechanical processes underlying nuclear movements, we adapted a micro-patterning based assay. C6 rat and U87 human glioma cells seeded on fibronectin patterns--thereby forced into a bipolar morphology--displayed oscillatory movements of the nucleus or the whole cell, respectively. We found that both the actomyosin system and microtubules are involved in the nuclear/cellular movements of both cell lines, but their contributions are cell-/migration-type specific. Dynein activity was necessary for nuclear migration of C6 cells but active myosin-II was dispensable. On the other hand, coupled nuclear and cellular movements of U87 cells were driven by actomyosin contraction. We explain these cell-line dependent effects by the intrinsic differences in the overall mechanical tension due to the various cytoskeletal elements inside the cell. Our observations showed that the movements of the nucleus and the centrosome are strongly correlated and display large variation, indicating a tight but flexible coupling between them. The data also indicate that the forces responsible for nuclear movements are not acting directly via the centrosome. Based on our observations, we propose a new model for nuclear oscillations in C6 cells in which dynein and microtubule dynamics are the main drivers of nuclear movements. This mechanism is similar to the meiotic nuclear oscillations of Schizosaccharomyces pombe and may be evolutionary conserved.

RNAiAtlas: a database for RNAi (siRNA) libraries and their specificity.

Large-scale RNA interference (RNAi) experiments, especially the ones based on short-interfering RNA (siRNA) technology became increasingly popular over the past years. For such knock-down/screening purposes, different companies offer sets of oligos/reagents targeting the whole genome or a subset of it for various organisms. Obviously, the sequence (and structure) of the corresponding oligos is a key factor in obtaining reliable results in these large-scale studies and the companies use a variety of (often not fully public) algorithms to design them. Nevertheless, as the genome annotations are still continuously changing, oligos may become obsolete, so siRNA reagents should be periodically re-annotated according to the latest version of the sequence database (which of course has serious consequences also on the interpretation of the screening results). In our article, we would like to introduce a new software/database tool, the RNAiAtlas. It has been created for exploration, analysis and distribution of large scale RNAi libraries (currently limited to the human genome) with their latest annotation (including former history) but in addition it contains also specific on-target analysis results (design quality, side effects, off-targets). Database URL: http://www.rnaiatlas.ethz.ch.

Machine learning improves the precision and robustness of high-content screens: using nonlinear multiparametric methods to analyze screening results.

Imaging-based high-content screens often rely on single cell-based evaluation of phenotypes in large data sets of microscopic images. Traditionally, these screens are analyzed by extracting a few image-related parameters and use their ratios (linear single or multiparametric separation) to classify the cells into various phenotypic classes. In this study, the authors show how machine learning-based classification of individual cells outperforms those classical ratio-based techniques. Using fluorescent intensity and morphological and texture features, they evaluated how the performance of data analysis increases with increasing feature numbers. Their findings are based on a case study involving an siRNA screen monitoring nucleoplasmic and nucleolar accumulation of a fluorescently tagged reporter protein. For the analysis, they developed a complete analysis workflow incorporating image segmentation, feature extraction, cell classification, hit detection, and visualization of the results. For the classification task, the authors have established a new graphical framework, the Advanced Cell Classifier, which provides a very accurate high-content screen analysis with minimal user interaction, offering access to a variety of advanced machine learning methods.

Acquisition speed comparison of microscope software programs.

Reliable software is a prerequisite for successful operation of a modern wide field fluorescence microscope. When used for live cell imaging, acquisition speed is of particular interest. This is both because biological processes can be highly-dynamic, and to avoid unnecessary photobleaching and phototoxicity of living samples. This article shows that besides the hardware (microscope) components themselves, the acquisition control software is an important influencing factor of speed performance. We tested and compared the speed performance of five different generic applications (Image-Pro Plus, MetaMorph, Micro-Manager, SlideBook, and Volocity) using typical experimental setups involving a single specific state-of-the-art fluorescence microscope configuration. The test measurements included multichannel experiments, z-stacking, burst acquisition, as well as combinations of these measurements with time-lapse acquisitions. The measured data provided values for guiding the testing and analysis of other microscope systems with similar configurations. Despite the identical hardware settings, significant and surprisingly large speed differences were evident among the various software applications. Additionally, no application was identifiable as the fastest in all tests. Our work pinpoints the importance of the control software in determining a system's "real" maximal imaging speed. The study could serve as basis for further tests, eventually influencing the system selection criteria for speed-sensitive applications.

Kernelized Z' factor in multiparametric screening technology.

RNA interference (RNAi) high-content screening (HCS) enables massive parallel gene silencing and is increasingly being used to reveal novel connections between genes and disease-relevant phenotypes. The application of genome-scale RNAi relies on the development of high quality HCS assays. The Z' factor statistic provides a way to evaluate whether or not screening run conditions (reagents, protocols, instrumentation, kinetics, and other conditions not directly related to the test compounds) are optimized. Z' factor, introduced by Zhang et al. (1), is a dimensionless value that represents both the variability and the dynamic range between two sets of sample control data. This paper describes a new extension of the Z' factor, which integrates multiple readouts for screening quality assessment. Currently presented multivariate Z' factor is based on linear projection, which may not be suitable for data with nonlinear structure. This paper proposes an algorithm which extends existing algorithm to deal with nonlinear data by using the kernel function. Using kernel methods for projections, multiple readouts are condensed to a single parameter, based on which the screening run quality is monitored.

A protein inventory of human ribosome biogenesis reveals an essential function of exportin 5 in 60S subunit export.

The assembly of ribosomal subunits in eukaryotes is a complex, multistep process so far mostly studied in yeast. In S. cerevisiae, more than 200 factors including ribosomal proteins and trans-acting factors are required for the ordered assembly of 40S and 60S ribosomal subunits. To date, only few human homologs of these yeast ribosome synthesis factors have been characterized. Here, we used a systematic RNA interference (RNAi) approach to analyze the contribution of 464 candidate factors to ribosomal subunit biogenesis in human cells. The screen was based on visual readouts, using inducible, fluorescent ribosomal proteins as reporters. By performing computer-based image analysis utilizing supervised machine-learning techniques, we obtained evidence for a functional link of 153 human proteins to ribosome synthesis. Our data show that core features of ribosome assembly are conserved from yeast to human, but differences exist for instance with respect to 60S subunit export. Unexpectedly, our RNAi screen uncovered a requirement for the export receptor Exportin 5 (Exp5) in nuclear export of 60S subunits in human cells. We show that Exp5, like the known 60S exportin Crm1, binds to pre-60S particles in a RanGTP-dependent manner. Interference with either Exp5 or Crm1 function blocks 60S export in both human cells and frog oocytes, whereas 40S export is compromised only upon inhibition of Crm1. Thus, 60S subunit export is dependent on at least two RanGTP-binding exportins in vertebrate cells.

Workflow-based software environment for large-scale biological experiments.

High-content screening (HCS) technologies are becoming increasingly used in both large-scale drug discovery and basic research programs. These automated imaging and analysis technologies enable the researcher to elucidate the complex biology that underlies the functions of genes, proteins, and other biomolecules at the cellular level. HCS combines the power of automated digital microscopy and advanced software-based image analysis algorithms to detect and quantify biological changes in cells and tissues. This technology is a particularly powerful tool when used to interrogate the cellular effects of exogenously applied agents such as RNAi and/or small molecules. HCS allows for the evaluation of cellular perturbations that occur both at the level of the single cell and within cellular populations. In a multivariate approach, multiple cellular parameters are collected, allowing for more complex analysis. However, in these scenarios, data flow and management still represent substantial bottlenecks in HCS projects. HCS data include a diversity of information from multiple sources such as details pertaining to screening libraries (e.g., siRNA and small molecules), image stacks acquired from automated microscopes (of which there may be up to several million), and the image analysis data. From this, postprocessing algorithms are required to generate statistical, quality control bioinformatic information and ultimately a final hit list. To accomplish these individual tasks, numerous tools can be used to perform each analytical step; however, management of the entire information flow currently requires the use of commercially available proprietary software, the scope of which is often limited, or bespoke customized scripts. In this article, the authors introduce an open-source research tool that allows for the management of the entire data flow of the HCS data chain, by handling and linking information and providing many powerful postprocessing and visualization tools.

Automated suppression of sample-related artifacts in Fluorescence Correlation Spectroscopy.

Fluorescence Correlation Spectroscopy (FCS) in cells often suffers from artifacts caused by bright aggregates or vesicles, depletion of fluorophores or bleaching of a fluorescent background. The common practice of manually discarding distorted curves is time consuming and subjective. Here we demonstrate the feasibility of automated FCS data analysis with efficient rejection of corrupted parts of the signal. As test systems we use a solution of fluorescent molecules, contaminated with bright fluorescent beads, as well as cells expressing a fluorescent protein (ICA512-EGFP), which partitions into bright secretory granules. This approach improves the accuracy of FCS measurements in biological samples, extends its applicability to especially challenging systems and greatly simplifies and accelerates the data analysis.

A classical NLS and the SUN domain contribute to the targeting of SUN2 to the inner nuclear membrane.

Integral membrane proteins of the inner nuclear membrane (INM) are inserted into the endoplasmic reticulum membrane during their biogenesis and are then targeted to their final destination. We have used human SUN2 to delineate features that are required for INM targeting and have identified multiple elements that collectively contribute to the efficient localization of SUN2 to the nuclear envelope (NE). One such targeting element is a classical nuclear localization signal (cNLS) present in the N-terminal, nucleoplasmic domain of SUN2. A second motif proximal to the cNLS is a cluster of arginines that serves coatomer-mediated retrieval of SUN2 from the Golgi. Unexpectedly, also the C-terminal, lumenal SUN domain of SUN2 supports NE localization, showing that targeting elements are not limited to cytoplasmic or transmembrane domains of INM proteins. Together, SUN2 represents the first mammalian INM protein relying on a functional cNLS, a Golgi retrieval signal and a perinuclear domain to mediate targeting to the INM.

Locomotion of fish epidermal keratocytes on spatially selective adhesion patterns.

Cell migration results from forces generated by assembly, contraction, and adhesion of the cytoskeleton. To address how these forces integrate in space and time, novel assays are required that allow spatial separation of the different force categories. We used micro-contact printing of fibronectin on glass substrates to study the effect of adhesion patterns on fish epidermal keratocytes locomotion. Cells migrated at similar speeds on homogeneously adhesive substrates and on patterns with 5 microm-wide adhesive stripes interleaved by non-adhesive stripes with a width varied between 5 and 13 microm. The leading edge protruded on adhesive stripes and lagged behind on non-adhesive stripes. On patterns with non-adhesive stripes wider than 13 microm cells halted, although the lamellipodium did not collapse. High correlation was found between the widths of protruding and lagging edge segments and the widths of the underlying stripes. We explain our data by the force balances between actin polymerization, contraction and adhesion on fibronectin stripes; and between actin polymerization, contraction and lamellipodium-internal elastic tension on non-adhesive stripes. We tested our model further by blocking lamellipodium actin network contraction and polymerization. In both experiments we observed that cells eventually lost their ability to move. However, the two perturbations induced distinct morphological responses. The data suggested that forces powering forward motion of keratocytes are largely associated with network assembly whereas contraction maintains cell polarity. This study establishes spatially selective adhesion substrates and cell morphological readouts as a means to elucidate the mechanical balance between substrate adhesion and cytoskeleton-internal tension in cell migration.

Surface engineering approaches to micropattern surfaces for cell-based assays.

The ability to produce patterns of single or multiple cells through precise surface engineering of cell culture substrates has promoted the development of cellular bioassays that provide entirely new insights into the factors that control cell adhesion to material surfaces, cell proliferation, differentiation and molecular signaling pathways. The ability to control shape and spreading of attached cells and cell-cell contacts through the form and dimension of the cell-adhesive patches with high precision is important. Commitment of stem cells to different specific lineages depends strongly on cell shape, implying that controlled microenvironments through engineered surfaces may not only be a valuable approach towards fundamental cell-biological studies, but also of great importance for the design of cell culture substrates for tissue engineering. Furthermore, cell patterning is an important tool for organizing cells on transducers for cell-based sensing and cell-based drug discovery concepts. From a material engineering standpoint, patterning approaches have greatly profited by combining microfabrication technologies, such as photolithography, with biochemical functionalization to present to the cells biological cues in spatially controlled regions where the background is rendered non-adhesive ("non-fouling") by suitable chemical modification. The focus of this review is on the surface engineering aspects of biologically motivated micropatterning of two-dimensional (flat) surfaces with the aim to provide an introductory overview and critical assessment of the many techniques described in the literature. In particular, the importance of non-fouling surface chemistries, the combination of hard and soft lithography with molecular assembly techniques as well as a number of less well known, but useful patterning approaches, including direct cell writing, are discussed.

Tocopherol cyclase (VTE1) localization and vitamin E accumulation in chloroplast plastoglobule lipoprotein particles.

Chloroplasts contain lipoprotein particles termed plastoglobules. Plastoglobules are generally believed to have little function beyond lipid storage. Here we report on the identification of plastoglobule proteins using mass spectrometry methods in Arabidopsis thaliana. We demonstrate specific plastoglobule association of members of the plastid lipid-associated proteins/fibrillin family as well as known metabolic enzymes, including the tocopherol cyclase (VTE1), a key enzyme of tocopherol (vitamin E) synthesis. Moreover, comparative analysis of chloroplast membrane fractions shows that plastoglobules are a site of vitamin E accumulation in chloroplasts. Thus, in addition to their lipid storage function, we propose that plastoglobules are metabolically active, taking part in tocopherol synthesis and likely other pathways.

Focal adhesion size controls tension-dependent recruitment of alpha-smooth muscle actin to stress fibers.

Expression of alpha-smooth muscle actin (alpha-SMA) renders fibroblasts highly contractile and hallmarks myofibroblast differentiation. We identify alpha-SMA as a mechanosensitive protein that is recruited to stress fibers under high tension. Generation of this threshold tension requires the anchoring of stress fibers at sites of 8-30-microm-long "supermature" focal adhesions (suFAs), which exert a stress approximately fourfold higher (approximately 12 nN/microm2) on micropatterned deformable substrates than 2-6-microm-long classical FAs. Inhibition of suFA formation by growing myofibroblasts on substrates with a compliance of < or = 11 kPa and on rigid micropatterns of 6-microm-long classical FA islets confines alpha-SMA to the cytosol. Reincorporation of alpha-SMA into stress fibers is established by stretching 6-microm-long classical FAs to 8.1-microm-long suFA islets on extendable membranes; the same stretch producing 5.4-microm-long classical FAs from initially 4-microm-long islets is without effect. We propose that the different molecular composition and higher phosphorylation of FAs on supermature islets, compared with FAs on classical islets, accounts for higher stress resistance.