Correlative light microscopy for high-content screening

Split but merge: Golgi fragmentation in physiological and pathological conditions

The Golgi complex is a highly dynamic and tightly regulated cellular organelle with essential roles in the processing as well as the sorting of proteins and lipids. Its structure undergoes rapid disassembly and reassembly during normal physiological processes, including cell division, migration, polarization, differentiation, and cell death. Golgi dispersal or fragmentation also occurs in pathological conditions, such as neurodegenerative diseases, infectious diseases, congenital disorders of glycosylation diseases, and cancer. In this review, current knowledge about both structural organization and morphological alterations in the Golgi in physiological and pathological conditions is summarized together with the methodologies that help to reveal its structure.

Single-molecule localization microscopy

Single-molecule localization microscopy (SMLM) describes a family of powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. In SMLM, individual fluorescent molecules are computationally localized from diffraction-limited image sequences and the localizations are used to generate a super-resolution image or a time course of super-resolution images, or to define molecular trajectories. In this Primer, we introduce the basic principles of SMLM techniques before describing the main experimental considerations when performing SMLM, including fluorescent labelling, sample preparation, hardware requirements and image acquisition in fixed and live cells. We then explain how low-resolution image sequences are computationally processed to reconstruct super-resolution images and/or extract quantitative information, and highlight a selection of biological discoveries enabled by SMLM and closely related methods. We discuss some of the main limitations and potential artefacts of SMLM, as well as ways to alleviate them. Finally, we present an outlook on advanced techniques and promising new developments in the fast-evolving field of SMLM. We hope that this Primer will be a useful reference for both newcomers and practitioners of SMLM.

Registration and Visualization of Correlative Super-Resolution Microscopy Data

We introduce a method for registration and visualization of correlative super-resolution microscopy images from different microscopy techniques. We established an automated registration procedure based on the generalized Hough transform. We developed a software tool to apply this algorithm and visualize correlated images from structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). To demonstrate the potential of this super-resolution correlator, we visualize the distribution of the presynaptic protein bassoon in the active zones of synapses in the molecular layer of the mouse cerebellum. First, a multiple labeled sample is imaged by SIM, followed by imaging of one of the fluorescent labels by dSTORM. To avoid the use of artificial fiducial markers, we used the signal of Alexa Fluor 647 recorded in switching buffer on the two microscopes for image superposition. We recorded multicolor SIM images in 20-μm thick brain slices to identify synapses in the dendritic system of Purkinje cells and put higher-resolved dSTORM images of the synaptic distribution of bassoon in registry.

Concepts in Light Microscopy of Viruses

Viruses threaten humans, livestock, and plants, and are difficult to combat. Imaging of viruses by light microscopy is key to uncover the nature of known and emerging viruses in the quest for finding new ways to treat viral disease and deepening the understanding of virus–host interactions. Here, we provide an overview of recent technology for imaging cells and viruses by light microscopy, in particular fluorescence microscopy in static and live-cell modes. The review lays out guidelines for how novel fluorescent chemical probes and proteins can be used in light microscopy to illuminate cells, and how they can be used to study virus infections. We discuss advantages and opportunities of confocal and multi-photon microscopy, selective plane illumination microscopy, and super-resolution microscopy. We emphasize the prevalent concepts in image processing and data analyses, and provide an outlook into label-free digital holographic microscopy for virus research.

Fluorescence-Based High-Throughput and Targeted Image Acquisition and Analysis for Phenotypic Screening

Applying the right acquisition method in a fluorescence imaging-based screening context is of great importance to obtain an appropriate readout and to select the right scale of the screen. In order to save imaging time and data, we have developed routines for multiscale targeted imaging, providing both a broad overview of a sample and additional in-depth information for targets of interest identified within the screen. These objects can be identified and acquired on-the-fly by an interconnection of image acquisition and image analysis.

Deconvolution of images from 3D printed cells in layers on a chip

Layer-by-layer cell printing is useful in mimicking layered tissue structures inside the human body and has great potential for being a promising tool in the field of tissue engineering, regenerative medicine, and drug discovery. However, imaging human cells cultured in multiple hydrogel layers in 3D-printed tissue constructs is challenging as the cells are not in a single focal plane. Although confocal microscopy could be a potential solution for this issue, it compromises the throughput which is a key factor in rapidly screening drug efficacy and toxicity in pharmaceutical industries. With epifluorescence microscopy, the throughput can be maintained at a cost of blurred cell images from printed tissue constructs. To rapidly acquire in-focus cell images from bioprinted tissues using an epifluorescence microscope, we created two layers of Hep3B human hepatoma cells by printing green and red fluorescently labeled Hep3B cells encapsulated in two alginate layers in a microwell chip. In-focus fluorescent cell images were obtained in high throughput using an automated epifluorescence microscopy coupled with image analysis algorithms, including three deconvolution methods in combination with three kernel estimation methods, generating a total of nine deconvolution paths. As a result, a combination of Inter-Level Intra-Level Deconvolution (ILILD) algorithm and Richardson-Lucy (RL) kernel estimation proved to be highly useful in bringing out-of-focus cell images into focus, thus rapidly yielding more sensitive and accurate fluorescence reading from the cells in different layers. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:445-454, 2018.

Localization-based super-resolution imaging meets high-content screening

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

Super-Resolution High Content Screening and Analysis

Revealing the subcellular phenotypes at the molecular scale is critical to understand the mechanisms by which the cells function and respond to chemical treatments. Super-resolution microscopy and robust analysis tools enabled biologists to reveal and quantify phenotypes at unprecedented resolution. Developing automated imaging analysis solutions for super-resolution imaging will make high-content-screening (HCS) applicable for super-resolution microscopy, which will give access to new complex information. Here, I provide an instant automated analysis procedure for analyzing super-resolution images via CellProfiler ( www.cellprofiler.org ) platform.

Quantifying Golgi structure using EM: combining volume-SEM and stereology for higher throughput

Investigating organelles such as the Golgi complex depends increasingly on high-throughput quantitative morphological analyses from multiple experimental or genetic conditions. Light microscopy (LM) has been an effective tool for screening but fails to reveal fine details of Golgi structures such as vesicles, tubules and cisternae. Electron microscopy (EM) has sufficient resolution but traditional transmission EM (TEM) methods are slow and inefficient. Newer volume scanning EM (volume-SEM) methods now have the potential to speed up 3D analysis by automated sectioning and imaging. However, they produce large arrays of sections and/or images, which require labour-intensive 3D reconstruction for quantitation on limited cell numbers. Here, we show that the information storage, digital waste and workload involved in using volume-SEM can be reduced substantially using sampling-based stereology. Using the Golgi as an example, we describe how Golgi populations can be sensed quantitatively using single random slices and how accurate quantitative structural data on Golgi organelles of individual cells can be obtained using only 5–10 sections/images taken from a volume-SEM series (thereby sensing population parameters and cell–cell variability). The approach will be useful in techniques such as correlative LM and EM (CLEM) where small samples of cells are treated and where there may be variable responses. For Golgi study, we outline a series of stereological estimators that are suited to these analyses and suggest workflows, which have the potential to enhance the speed and relevance of data acquisition in volume-SEM.

Single-Molecule Localization Microscopy in Eukaryotes

Super-resolution fluorescence imaging by photoactivation or photoswitching of single fluorophores and position determination (single-molecule localization microscopy, SMLM) provides microscopic images with subdiffraction spatial resolution. This technology has enabled new insights into how proteins are organized in a cellular context, with a spatial resolution approaching virtually the molecular level. A unique strength of SMLM is that it delivers molecule-resolved information, along with super-resolved images of cellular structures. This allows quantitative access to cellular structures, for example, how proteins are distributed and organized and how they interact with other biomolecules. Ultimately, it is even possible to determine protein numbers in cells and the number of subunits in a protein complex. SMLM thus has the potential to pave the way toward a better understanding of how cells function at the molecular level. In this review, we describe how SMLM has contributed new knowledge in eukaryotic biology, and we specifically focus on quantitative biological data extracted from SMLM images.

3D d STORM Imaging of Fixed Brain Tissue

Central nervous system tissue contains a high density of synapses each composed of an intricate molecular machinery mediating precise transmission of information. Deciphering the molecular nanostructure of pre- and postsynaptic specializations within such a complex tissue architecture poses a particular challenge for light microscopy. Here, we describe two approaches suitable to examine the molecular nanostructure of synapses at 20-30 nm lateral and 50-70 nm axial resolution within an area of 500 μm × 500 μm and a depth of 0.6 μm to several micrometers. We employ single-molecule localization microscopy (SMLM) on immunolabeled fixed brain tissue slices. tomoSTORM utilizes array tomography to achieve SMLM in 40 nm thick resin-embedded sections. dSTORM of cryo-sectioned slices uses optical sectioning in 0.1-4 μm thick hydrated sections. Both approaches deliver 3D nanolocalization of two or more labeled proteins within a defined tissue volume. We review sample preparation, data acquisition, analysis, and interpretation.

Quantification of telomere features in tumor tissue sections by an automated 3D imaging-based workflow

The microscopic analysis of telomere features provides a wealth of information on the mechanism by which tumor cells maintain their unlimited proliferative potential. Accordingly, the analysis of telomeres in tissue sections of patient tumor samples can be exploited to obtain diagnostic information and to define tumor subgroups. In many instances, however, analysis of the image data is conducted by manual inspection of 2D images at relatively low resolution for only a small part of the sample. As the telomere feature signal distribution is frequently heterogeneous, this approach is prone to a biased selection of the information present in the image and lacks subcellular details. Here we address these issues by using an automated high-resolution imaging and analysis workflow that quantifies individual telomere features on tissue sections for a large number of cells. The approach is particularly suited to assess telomere heterogeneity and low abundant cellular subpopulations with distinct telomere characteristics in a reproducible manner. It comprises the integration of multi-color fluorescence in situ hybridization, immunofluorescence and DNA staining with targeted automated 3D fluorescence microscopy and image analysis. We apply our method to telomeres in glioblastoma and prostate cancer samples, and describe how the imaging data can be used to derive statistically reliable information on telomere length distribution or colocalization with PML nuclear bodies. We anticipate that relating this approach to clinical outcome data will prove to be valuable for pretherapeutic patient stratification.

Intracellular Golgi Complex organization reveals tissue specific polarity during zebrafish embryogenesis

BACKGROUND

Cell polarity is essential for directed migration of mesenchymal cells and morphogenesis of epithelial tissues. Studies in cultured cells indicate that a condensed Golgi Complex (GC) is essential for directed protein trafficking to establish cell polarity underlying directed cell migration. Dynamic changes of the GC intracellular organization during early vertebrate development remain to be investigated.

RESULTS

We used antibody labeling and fusion proteins in vivo to study the organization and intracellular placement of the GC during early zebrafish embryogenesis. We found that the GC was dispersed into several puncta containing cis- and trans-Golgi Complex proteins, presumably ministacks, until the end of the gastrula period. By early segmentation stages, the GC condensed in cells of the notochord, adaxial mesoderm, and neural plate, and its intracellular position became markedly polarized away from borders between these tissues.

CONCLUSIONS

We find that GC is dispersed in early zebrafish cells, even when cells are engaged in massive gastrulation movements. The GC accumulates into patches in a stage and cell-type specific manner, and becomes polarized away from borders between the embryonic tissues. With respect to tissue borders, intracellular GC polarity in notochord is independent of mature apical/basal polarity, Wnt/PCP, or signals from adaxial mesoderm. Developmental Dynamics 245:678-691, 2016. © 2016 Wiley Periodicals, Inc.

High-Content Analysis of the Golgi Complex by Correlative Screening Microscopy

The Golgi complex plays a central role in a number of diverse cellular processes, and numerous regulators that control these functions and/or morphology of the Golgi complex are known by now. Many of them were identified by large-scale experiments, such as RNAi-based screening. However, high-throughput experiments frequently provide only initial information that a particular protein might play a role in regulating structure and function of the Golgi complex. Multiple follow-up experiments are necessary to functionally characterize the selected hits. In order to speed up the discovery, we have established a system for correlative screening microscopy that combines rapid data collection and high-resolution imaging in one experiment. We describe here a combination of wide-field microscopy and dual-color direct stochastical optical reconstruction microscopy (dSTORM). We apply the technique to simultaneously capture and differentiate alterations of the cis- and trans-Golgi network when depleting several proteins in a singular and combinatorial manner.

Super-resolution imaging for cell biologists: concepts, applications, current challenges and developments

The recent 2014 Nobel Prize in chemistry honored an era of discoveries and technical advancements in the field of super-resolution microscopy. However, the applications of diffraction-unlimited imaging in biology have a long road ahead and persistently engage scientists with new challenges. Some of the bottlenecks that restrain the dissemination of super-resolution techniques are tangible, and include the limited performance of affinity probes and the yet not capillary diffusion of imaging setups. Likewise, super-resolution microscopy has introduced new paradigms in the design of projects that require imaging with nanometer-resolution and in the interpretation of biological images. Besides structural or morphological characterization, super-resolution imaging is quickly expanding towards interaction mapping, multiple target detection and live imaging. Here we review the recent progress of biologists employing super-resolution imaging, some pitfalls, implications and new trends, with the purpose of animating the field and spurring future developments.

Systems biology in 3D space--enter the morphome

Systems-based understanding of living organisms depends on acquiring huge datasets from arrays of genes, transcripts, proteins, and lipids. These data, referred to as 'omes', are assembled using 'omics' methodologies. Currently a comprehensive, quantitative view of cellular and organellar systems in 3D space at nanoscale/molecular resolution is missing. We introduce here the term 'morphome' for the distribution of living matter within a 3D biological system, and 'morphomics' for methods of collecting 3D data systematically and quantitatively. A sampling-based approach termed stereology currently provides rapid, precise, and minimally biased morphomics. We propose that stereology solves the 'big data' problem posed by emerging wide-scale electron microscopy (EM) and can establish quantitative links between the newer nanoimaging platforms such as electron tomography, cryo-EM, and correlative microscopy.

Visualization and analysis of hepatitis C virus structural proteins at lipid droplets by super-resolution microscopy

Cytosolic lipid droplets are central organelles in the Hepatitis C Virus (HCV) life cycle. The viral capsid protein core localizes to lipid droplets and initiates the production of viral particles at lipid droplet–associated ER membranes. Core is thought to encapsidate newly synthesized viral RNA and, through interaction with the two envelope proteins E1 and E2, bud into the ER lumen. Here, we visualized the spatial distribution of HCV structural proteins core and E2 in vicinity of small lipid droplets by three-color 3D super-resolution microscopy. We observed and analyzed small areas of colocalization between the two structural proteins in HCV-infected cells with a diameter of approximately 100 nm that might represent putative viral assembly sites.

Integrated and correlative high-throughput and super-resolution microscopy

We have developed a method to perform microscopic temporal and spacial multi-scale experiments by imaging cellular phenotypes of interest on complementary fluorescence microscopy systems. In a low-resolution fast data acquisition screen for phenotypic cellular responses induced by small interfering RNA (siRNA), cells in spots of siRNA cell arrays showing characteristic alterations have been selected automatically by feature space analysis. These objects were imaged on a second super-resolution dSTORM microscope (direct stochastic optical reconstruction microscopy). The coordinate transfer was based on fixed cells as reference points without the use of additional fiducial markers. This procedure is suitable to combine any kind of fluorescence microscopy technique, in order to gain further insights on the observed specimen at multiple temporal or special scales.