exploring subcellular organization and function …...exploring subcellular organization and...

Exploring Subcellular Organization and Function with Quantitative Fluorescence Microscopy

M. Kodiha, H. Mahboubi and U. Stochaj Department of Physiology, McGill University, Montréal, Quebec, Canada

Cellular homeostasis relies on the proper organization of biological functions in space and time. In eukaryotes, subcellular organelles and compartments provide a framework to coordinate these diverse activities. To adapt to endogenous and environmental changes, many organelles and compartments are dynamic with respect to composition and function. This scenario applies especially to compartments that are generated only under specific physiological conditions. To fully understand these dynamics, it is mandatory to measure compartment-specific parameters in a quantitative fashion. However, such measurements are challenging if compartments are fragile or difficult to isolate. Quantitative fluorescence microscopy can overcome some of these obstacles. To achieve this, we developed new tools for automated image acquisition and quantification of fluorescence signals. We discuss our protocols that measure compartment-specific parameters for images acquired by confocal or wide-field microscopy in conjunction with high-throughput instrumentation. By applying our tools, we obtained new insights into the nucleocytoplasmic distribution of signaling molecules as well as the functional organization of nuclear envelopes, nucleoli and stress granules.

Keywords: Fluorescence microscopy; signal quantification; automated detection; subcellular compartments; nucleus; nuclear envelope; nucleolus; stress granules; high-throughput screening

1. Introduction

Eukaryotic cells have evolved specialized organelles and compartments to ensure that complex biological processes take place in an organized and efficient fashion. The proper regulation of these functions involves the dynamic recruitment of macromolecules to specific subcellular locations. These locations include subcellular organelles with well-defined membrane boundaries as well as compartments that lack a membranous border [1]. Most organelles and compartments are not static, but highly dynamic with respect to their organization and function. Moreover, some compartments exist only in a transient fashion, i.e. they assemble under physiological conditions when the cell requires specific functions. This ability to adapt and modulate cellular processes at the subcellular level is particularly important when homeostasis is threatened by environmental or disease-induced stress. Quantitative measurements of organelles and compartments are crucial to define and understand the molecular mechanisms that regulate cell physiology. Thus, powerful tools are needed to measure the abundance of molecules in defined cellular locations. This chapter reviews the procedures that we designed to automatically demarcate and measure different subcellular structures [2-4]. Here, we will focus on the nucleus, nuclear envelope, nucleoli and cytoplasmic stress granules. Our computer-based automated procedures quantify multiple parameters and thereby provide a rigorous analysis of the compartment of interest. We discuss several examples that demonstrate the novelty and effectiveness of our protocols. These applications revealed previously unidentified biological and structural characteristics of key subcellular compartments. We further present some of the obstacles that have to be overcome to allow the wide-spread use of these methods. The chapter concludes by highlighting future directions in quantitative fluorescence microscopy as they relate to subcellular compartments.

2. Why do we need quantitative fluorescence microscopy?

2.1 Inherent difficulties of cell fractionation

To date, the analysis of subcellular organelles and compartments has relied heavily on cell fractionation combined with proteomics. However, despite its common use, the approach is not universally applicable and faces significant challenges. One of the problems of cell fractionation is the redistribution of material upon cell lysis and the cross-contamination between different fractions. The leakage of macromolecules is particularly eminent for nuclei [5], and a prominent example is the small GTPase Ran. While Ran is mostly nuclear in intact cells, the protein leaks into the cytoplasm when cells are lysed [6]. The proper assignment of molecules to subcellular locations is even more difficult for membraneless compartments such as nucleoli and stress granules (SGs), because they may disintegrate during isolation. Cell fractionation faces further problems when dynamic processes have to be measured. Thus, it is difficult to identify and quantify compartment-specific molecular interactions, if they are only weak or short-lived. This is exemplified by the nucleolar protein fibrillarin which spends less than 40 seconds in the nucleoli of mammalian cells [7]. Proper assignment to a subcellular location is complicated not only for endogenous macromolecules, but also for

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nonbiological material that has been introduced into cells. For instance, attempts to allocate large nanoparticles to the cytoplasm or nucleus of mammalian cells fail, because large particles may sediment, independent of their organelle association [8]. Taken together, cell fractionation is especially error-prone for nuclei and nucleoli. On the other hand, efforts to isolate intact SGs have failed so far. To overcome these obstacles, alternative methods are required that provide reliable information on the subcellular distribution of molecules. As discussed here, quantitative fluorescence microscopy provides a powerful approach for the analysis of dynamic biological molecules and processes that cannot be easily examined by standard biochemical procedures, such as cell fractionation.

2.2 The concept of quantitative fluorescence microscopy

Quantitative fluorescence microscopy combined with image analysis presents an effective strategy to analyze the organization and function of cells. This procedure combines the visualization of specific molecules with a fluorescent label, image acquisition and image analysis. In the past, the manual demarcation and measurements of subcellular compartments made large-scale quantitative studies time-consuming, while preventing the efficient use of high-throughput screening (HTS) technology. It was therefore crucial to develop methods that fulfill several requirements: first, the identification of subcellular compartments is fast, simple and unbiased; second, fluorescent signals in these compartments are reliably quantified; third, measurements can be performed with HTS instrumentation. Identification of subcellular compartments. The initial step of the protocol identifies a subcellular compartment of interest. Compartment identification relies on a marker that distinguishes a specific location from the rest of the cell. The appropriate choice of marker is critical for this step. A proper marker satisfies a set of criteria which are based on marker abundance in the compartment and the ease of marker detection. Hence, a marker is either highly abundant or excluded from the compartment of interest (summarized in Table 1). Marker visualization by fluorescence microscopy should be reliable and simple. Examples of appropriate markers are stained DNA, fluorescently labeled nucleic acids or proteins and other fluorescent compounds. A marker is particularly useful if it associates stably with the compartment of interest under a wide range of experimental conditions. Preferably, this includes conditions which partially disrupt the integrity of the compartment. If necessary, several markers can be combined to improve the proper demarcation of a compartment [9, 10]. An ideal marker also works with cells of different origins. While this may not always apply to antibody-based labeling, DNA stains such as DAPI function well with all cells we have tested (human, animal and yeast cells). Table 1 Frequently used markers for the detection of cellular organelles or compartments. The list is not comprehensive.

Compartment Marker or probe Stain or tag Multiple Fluorescently tagged

protein GFP, YFP, mCherry and others

Multiple Nucleic acids Fluorescent hybridization probes

Multiple Antibody against compartment marker

Fluorescent primary or secondary antibodies

Mitochondria Mitochondrial activity MitoTracker® Lysosomes pH LysoTracker®,

LysoSensor™

Markers relevant to this chapter Nucleus DNA DAPI, Hoechst, DRAQ5™,

NucRed® Nuclear envelope DNA, lamins, nucleoporins DNA stain, fluorescent

antibodies Nucleoli DAPI, nucleolin, fibrillarin,

RNA-polymerase II, CAS, HuR

Fluorescent secondary antibodies

Nucleolar RNA synthesis 5-ethynyluridine Fluorochrome Stress granules G3BP1, poly(A)-containing

RNA Fluorescent secondary antibodies or probes

Software and markers used for our applications. For all applications described in section 4, images were processed with MetaXpress® software in an automated fashion. We used this software to identify different subcellular compartments. However, many of the principles discussed here also apply to other commercial or freely available imaging software.


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Nucleus and cytoplasm. Labeling and detection of nuclei is relatively straightforward due to their large size and the availability of good markers that preferentially stain the nuclear area. For example, DAPI provides a reliable marker for the nucleus. Guided by the DAPI fluorescence, the imaging software distinguishes between the nucleus and cytoplasm. Nuclear envelope. The staining of nuclear DNA is also useful to demarcate the nuclear envelope (NE); based on DAPI-derived signals we designed protocols to quantify pixel intensities that are located at the NE [2]. The method takes advantage of the drop in fluorescence intensity between the edge of the labeled nucleus and the surrounding cytoplasm. This drop defines the nuclear margin. Using the nuclear margin as a reference, the software creates a region that extends into the nuclear interior on one side and the cytoplasm on the other side. By selecting the appropriate width for this region, it will co-localize with the NE. As a further refinement, molecules located at the cytoplasmic side of the NE can be measured after immunostaining [11, 12]. To this end, the plasma membrane is selectively permeabilized with digitonin. As the NE stays intact, antibodies will not have access to the nuclear interior. Nucleoli. The reliable demarcation of nucleoli is challenging for several reasons. The rapidly changing composition of the nucleolar proteome limits the use of nucleolar proteins for compartment identification. Other factors add to the complexity of nucleolar detection. Nucleoli are heterogeneous in size and shape. Furthermore, cells may contain several nucleoli that differ in their fluorescence intensities. This complicates the design of proper settings for automated compartment detection, a step essential for the processing of large data sets. Due to their dynamic properties, many nucleolar proteins are not always suitable for compartment demarcation. Nevertheless, nucleolin provided a marker for a number of experimental conditions [10]. Since the protein is sensitive to some treatments that disintegrate the nucleolus, we developed alternative methods to define the compartment. These protocols are based on fluorescent staining patterns that generate “dark holes” for nucleoli (Fig. 1). Such dark holes are produced if a signal is much lower in nucleoli as compared to the surrounding nucleoplasm. The simplest method that produces dark holes for nucleoli is DAPI staining. Once the dark holes have been identified by the software, segments are generated that demarcate nucleoli [9, 10]. Similar to DAPI, immunolabeling of RNA polymerase II also produces dark holes, because the protein is concentrated in the nucleoplasm, with low concentration in nucleoli [9]. Although these markers were appropriate for many experimental settings, they did not perform satisfactorily under severe stress conditions. The nuclear transporter CAS and the RNA-binding protein HuR provide additional options to detect nucleoli as dark holes ([10] and Fig. 1, 4). While an individual marker can define the nucleolus, the accuracy of compartment detection can be further improved when the software combines the information for two markers [9, 10]. Taken together, we identified multiple markers that, either alone or in combination, delimit nucleoli with high precision. These nucleolar markers function for a diverse set of experimental conditions.

Fig. 1 Demarcation of nucleoli. CAS, HuR and nucleolin were detected by indirect immunofluorescence in MCF7 breast cancer cells. The “black holes” in nuclei obtained after CAS staining were used by the software to demarcate nucleoli and generate segments. The original image was then overlaid with the segments (white). Note that the “black holes” obtained for HuR can delimit the nucleoli as well. Under nonstress conditions, shown in the image, nucleolin is also a suitable marker for identification of the nucleolus. Size bar, 20 μm. Adapted from [10] with permission.

Stress granules. The eukaryotic cytoplasm contains a multitude of compartments, some of which form only transiently in response to specific stimuli. For example, the non-membrane-bound SGs assemble upon certain forms of stress. While SGs contain proteins and RNA, they are highly dynamic and their composition depends on the stressor. Nonetheless, some constituents are present in all SGs and thereby provide markers for this compartment; one such marker is the Ras GTPase-activating protein-binding protein 1 (G3BP1) [13]. Furthermore, as SGs contain poly(A)-mRNAs, they can be detected through in situ hybridization with labeled oligo(dT) or other appropriate probes. Quantification of fluorescent signals. Once the compartment area has been delimited, pixel intensities in this area are measured for the molecule under investigation. The protocol of compartment identification and fluorescence measurement can be divided into multiple steps: (i) images are corrected for background fluorescence; (ii) compartment margins are detected; (iii) the imaging software creates segments that co-localize with the compartment (see Fig. 1 for nucleoli); (iv) segments are overlaid with the original image; and (v) fluorescence intensities of the molecule examined are quantified for the original image. In addition to pixel intensities associated with the location, other parameters that can be measured include compartment size and number of compartments/cell [2, 4, 9, 10].


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Imaging with high throughput screening equipment and assay development. Our methods provide robust, fast and reliable tools to analyze biological processes that take place in different cellular locations. These tools were initially developed for images acquired with confocal microscopes. HTS technology is used extensively to identify small molecules that modify the organization and/or function of subcellular compartments. HTS platforms facilitate the simultaneous examination of multiple biological variables and the analysis of large data sets. In many cases, HTS-based image acquisition relies on wide-field microscopy. It was therefore important to determine whether our methods are compatible with HTS instrumentation. As shown in section 4.5, this is indeed the case. We went beyond this step and developed HTS assays for nucleoli and SGs. As part of the assay development, the Z-factor is determined. This is a statistical factor which evaluates the quality of an assay [14]. Meaningful values for the Z-factor range from −1.0 to +1.0; an excellent assay is distinguished by a Z-factor which is ≥0.5. In section 4, we applied our protocols to examine the nucleus, nuclear envelope, and two membrane-less compartments, the nucleolus [15] and cytoplasmic SGs [16]. To put these applications in the proper context, we first introduce those biological properties of the compartments that are relevant to our studies (section 3). This is followed by biological applications of our quantitative imaging approaches.

3. Dynamic properties of the nucleus, nuclear envelopes, nucleoli and stress granules

3.1 Nucleus and cytoplasm

The proper distribution of molecules within different cellular locations is crucial to maintain cellular homeostasis. This is particularly important for components involved in signal transduction, as their location determines the specificity and duration of signaling events. Signal transduction in eukaryotic cells frequently involves communication between the nucleus and cytoplasm. Moreover, some of the signaling pathways have branches in the nucleus and cytoplasm [17, 18]. For example, kinases can be located in multiple subcellular compartments, where they modify different targets. Such compartment-specific effects are important, because the target modification regulates the subsequent downstream events. As described in section 4, quantitative imaging helped to elucidate some of these processes [19-21].

3.2 Nuclear envelope

The nucleus is demarcated by the NE, a membranous border that separates the nuclear interior from the cytoplasm [22]. The NE is organized into multiple sub-compartments, the outer nuclear membrane, perinuclear space and inner nuclear membrane. Also part of the NE is the nuclear lamina, a filamentous network that underlies the inner nuclear membrane [22]. Located at the junctions of the inner and outer nuclear membranes, nuclear pore complexes (NPCs) serve as gates that translocate macromolecular cargo in or out of the nucleus [23, 24]. NPCs are composed of nucleoporins, and some of the nucleoporins, such as Nup358, provide docking sites for the carriers that move cargo across the NE. As one of the best-understood carriers, Crm1 promotes nuclear protein export (section 4.2). Some of the NE sub-compartments are highly dynamic. Thus, the composition of NEs and the molecules associated with NPCs are sensitive to intrinsic and environmental stimuli. For instance, nucleoporins are degraded during apoptosis or when cells are hijacked by viruses [25]. As well, the NPC binding of nuclear carriers and the thickness of nuclear laminae are controlled by physiological changes, such as stress and aging [26, 27].

3.3 Nucleoli

Nucleoli are compartments inside the nucleus where they function as key regulators of cell physiology [28-35]. They are organized around rDNA gene clusters that encode the 47S precursor of 28S, 18S and 5.8 S rRNA. Besides transcribing rDNA, nucleoli process pre-rRNA, assemble ribosomal subunits, produce signal recognition particle (SRP), control stress responses, cell cycle progression, telomerase activity and apoptosis. The nucleolus contains several thousand proteins, many of which shuttle between nucleoli and the surrounding nucleoplasm [33]. The association of these proteins with the nucleolus is transient and sensitive to endogenous and environmental stimuli. Due to their dynamic nature, nucleoli rapidly adapt to changing conditions and serve as stress sensors [30]. Nucleoli are not only essential for cell growth and survival, they have also emerged as targets of anti-cancer therapy [36]. Notably, nucleolar organization and function are sensitive to many pharmacological compounds, including several anti-cancer drugs [9, 10, 20, 37]. The ability to measure nucleolar parameters is therefore critical to the understanding of basic biological processes and for clinical applications. The morphology, organization and protein profile of nucleoli are important, because they are quantifiable parameters that reflect the functional state of the nucleolus ([30, 34, 38, 39] and references therein). As an example, inhibition of rDNA transcription induces nucleolar fragmentation (reviewed in [40]). In general, this reorganization is linked to a redistribution of several nucleolar proteins [9, 10, 41] and accompanied by changes in nucleolar function ([30, 38] and references therein).


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3.4 Cytoplasmic stress granules

Upon exposure to stress, the formation of cytoplasmic SGs is one of the strategies that eukaryotes use to restore homeostasis and prevent cell death. SG assembly is a conserved cellular defense mechanism against various types of insults. These compartments have been detected in organisms throughout the phylogenetic tree, ranging from budding yeast, C. elegans, Drosophila to mammals [42]. On a functional level, SGs are crucial to regulate mRNA stability and translation. In addition to translationally silenced poly(A)-mRNAs, they contain different proteins involved in RNA stability, transport and processing [16]. SGs are highly dynamic, as they constantly exchange proteins and RNAs with the surrounding milieu [43, 44]. Recent findings extend the cellular functions of SGs and suggest they operate as signaling hubs that integrate key regulatory processes. Signaling components associated with SGs range from kinases like mTOR and JNK to non-coding RNAs [16, 45]. The importance of SGs is highlighted by their essential contributions to cell fate decisions and the overall health of the organism. For example, SGs are generated in response to various pathologies, such as neurodegenerative diseases, cancer and some virus infections [46-48]. Indeed, several therapeutic agents currently approved or under clinical evaluation directly target the SG assembly process [49, 50]. Therefore, tools that measure SGs are crucial to define their biological properties and evaluate the impact of candidate drugs on SG formation.

4. Applications of quantitative fluorescence microscopy in cell biology

We have employed our quantitative fluorescence approach to perform a thorough analysis of diverse cellular processes. Specifically, our tools were critical to compare the organization and function of compartments under normal and stress conditions. The following sections discuss how quantitative fluorescence microscopy answered important biological questions and shed new light on eukaryotic cell physiology.

4.1 Analysis of signaling events in eukaryotic cells

Stress affects many signaling pathways; it impinges on events that are associated with diverse subcellular compartments. In mammalian cells, our work examined the signaling mediated by PI3 kinase→AKT, MEK→ERK1/2 and 5’-AMP-activated protein kinase (AMPK). To define the effects of oxidants on the intracellular activation and localization of protein kinases, we initially focused on ERK1/2 and Akt [19]. These studies demonstrated crosstalk between the two signaling routes in the nucleus. Our research also provided new insights into the stress-induced activation and subcellular distribution of AMPK. Several forms of stress, including heat, energy depletion and oxidants, concentrate AMPK in nuclei, whereas high cell density confines AMPK to the cytoplasm [21]. As shown in Fig. 2, our quantitative analyses revealed further that pharmacological AMPK activators have different effects on the nuclear and cytoplasmic pools of the kinase [20].

Fig. 2 The AMPK activator phenformin leads to preferential phosphorylation of AMPK-α1/2 in the cytoplasm. LLCPK1 kidney cells were incubated for 1 h at 37°C with the AMPK activator phenformin (5 mM) or vehicle (control) [20]. Cells were fixed and processed for immunostaining with antibodies that recognize AMPK-α1 and α2 subunits phosphorylated on Thr172 (p-AMPK-α1/2). Thr172 phosphorylation of the α-subunit is a prerequisite for AMPK activation. Pixel intensities in the nucleus and cytoplasm were measured and the ratio N/C was calculated. Nuclear and cytoplasmic intensities or the N/C ratio were each normalized to control samples. The bar graph shows averages +SD. Size bar is 20 μm; ** p < 0.01. Note that our image quantification demonstrated that phenformin-induced Thr172 phosphorylation is much less pronounced in nuclei (Nuc) [51] as compared to the cytoplasm (Cyt). Reproduced from [20] with permission.

4.2 Quantification of molecules located at the NE

Using software modules that measure fluorescence at the NE, in the nucleus or cytoplasm, we dissected the molecular mechanisms of classical nuclear import and Crm1-mediated nuclear export. To achieve this, growing or semi-intact HeLa cells were used as model systems to assess the impact of stress on nuclear transport factors, classical nuclear


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protein import or export. Our research demonstrated that heat has multiple effects on importin-α, an adaptor that links protein cargo to the nuclear import carrier. Specifically, heat upregulates importin-α docking at the NE and compromises importin-α exit from the nucleus. Hyperthermia also concentrates CAS, the nuclear exporter of importin-α, in the nucleus [11]. Our protocols enabled us to evaluate different aspects of NE organization, in particular carrier binding to the NE as well as NPC organization [11, 12, 52]. As shown in Fig. 3 and published earlier [11, 12, 52], Crm1 and several nucleoporins (Nup358, Nup214, Nup62, Nup153, Nup88) are sensitive to oxidants. Oxidative stress also alters the NE binding of nuclear transport adaptors and other carriers (importin-α, CAS [11, 52]). Overall, quantitative fluorescence microscopy was key to these studies. It led to the identification of molecular events that mediate the stress-induced inhibition of classical nuclear import and Crm1- or CAS-dependent nuclear export.

Fig. 3 Oxidative stress alters the NE association of the nuclear exporter Crm1 and nucleoporin Nup358. HeLa cells were treated with the oxidant diethyl maleate (DEM) or the vehicle ethanol (EtOH) as described [12]. After immunostaining, signals for fluorescent secondary antibodies were quantified at the NE. Results are depicted as averages +SD; ** p < 0.01. Size bar is 20 μm. Oxidant exposure causes a significant increase of Crm1 at the NE. At the same time, Nup358 was significantly reduced at the NE. Adapted from [12] with permission.

4.3 Exploring the biology of the nucleolus

One of the most valuable applications of our quantitative fluorescence protocols is the ability to analyze thoroughly the structural and functional organization of the nucleolus. In particular, we gained in-depth information about the impact of stress on this dynamic compartment [9, 10, 20]. Effect of stress on nucleolar organization and function. To better define the biology of nucleoli, we investigated the subcellular distribution of B23/nucleophosmin and nucleolin, nucleolar proteins that are essential for compartment organization and function. The oxidant diethyl maleate (DEM) increased the concentration of nucleolin, but not B23, in the nucleolus (Fig. 4). A different picture emerged for the casein kinase II inhibitor 5,6-dichloro-1-β-D-ribofuranosyl benzimidazole (DRB), which reduced significantly the nucleolar levels for both proteins. These studies set the stage to analyze the effect of pharmacological compounds with chemotherapeutic potential on the nucleolar integrity in a quantitative fashion. Importantly, our approach is also suitable to measure nucleolar functions, as exemplified by transcription in this compartment. These studies demonstrated that AMPK activators, oxidative stress and DRB inhibit de novo RNA synthesis in nucleoli [9, 10, 20].

Fig. 4 DEM and DRB alter the protein profile of nucleoli. HeLa cells were incubated with the vehicle (ethanol – EtOH, DMSO), DEM or DRB as described [10]. Fluorescence intensities were measured for B23 and nucleolin in the same nucleoli. Together, CAS and nucleolin were used to demarcate nucleoli for cells incubated with ethanol or DEM. CAS alone defined nucleoli for samples treated with DMSO or DRB. Results show the averages +SEM for several independent experiments; ** p < 0.01. Size bar is 20 μm. Adapted from [10], with permission.


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Gold nanoparticles inhibit nucleolar functions. Gold nanoparticles are powerful tools with applications in the field of drug delivery, cellular imaging, biomedical diagnostics and therapeutics. They are especially promising for cancer research and treatment. We recently defined how they affect the nucleolus. Gold nanoparticles indeed alter the organization [53] and function of the nucleolus (Fig. 5). Interestingly, the size and shape of gold nanoparticles are critical for the damage they inflict on nucleoli. Taken together, our imaging and image analysis protocols provide an ideal platform to study nucleolar biology and to evaluate novel strategies for the killing of cancer cells [53].

Fig. 5 MCF7 cells were incubated with vehicle (V), small gold nanospheres (S), gold nanoflowers (F) or big gold nanospheres (B), and de novo synthesized RNA was labeled with 5-ethynyluridine (EU). EU was visualized with a fluorochrome by click-chemistry and pixel intensities/area were measured in nucleoli. Results are averages of at least three independent experiments. * p < 0.05; size bar is 20 μm. Original data were published in [53]. Note that the treatment with small gold nanoparticles or gold nanoflowers inhibits new RNA synthesis in nucleoli.

4.4 Quantification of SG parameters defines granule biogenesis under different stress conditions

Previous analyses of cytoplasmic SGs relied on the manual demarcation and counting of granules. As this approach is prone to bias and time-consuming, it impedes the processing of large data sets. Semi-automated methods based on ImageJ plugins have also been applied in some studies [54]. Although these protocols are somewhat faster than the manual approach, they still require user input. Importantly, they currently lack quantitative SG parameters, such as the pixel intensities associated with granules. Moreover, the cells have to be counted manually or by running additional plugins. Finally, ImageJ-based protocols are compatible with only a limited number of image formats and settings. To circumvent these limitations, we developed a novel approach to automatically detect and quantify granular cell compartments, including SGs. Our methods generate quantitative data at the single cell level and for individual SGs [4]. To validate these protocols, we investigated SG formation in human cancer cells. To this end, cells were exposed to heat shock or oxidants, and the properties of stress-induced granules were compared. Among the parameters analyzed were granule size, number of SGs/cell, and the concentration of specific molecules in the granule. Fig. 6 shows an example of our studies, the SG marker G3BP1 was used to demarcate the compartment, and poly(A)-containing RNA was detected by in situ hybridization with fluorescent oligo-dT(50). Fig. 6 and our published results [4] uncovered stress-dependent differences in SG characteristics. Thus, compared to the oxidants DEM or sodium arsenite, heat shock produced smaller granules. Moreover, even different oxidants generated SGs with distinct properties. As compared to arsenite, considerably larger granules assembled upon DEM treatment; DEM-induced SGs had also significantly higher fluorescence per unit area (Fig. 6). Furthermore, our quantitative data revealed that RNAs and proteins occupy different territories within SGs [4], further supporting the idea that SGs are organized into sub-compartments [55]. In summary, our methods represent the first fully-automated protocol for the detection and measurement of granular compartments, as exemplified by SGs. With these methods, we demonstrated that the type of stress controls the morphology and composition of SGs. Given the link between granular compartments and human health, our protocols are promising tools for disease diagnosis and prognosis.


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Fig. 6 Confocal microcopy of HeLa cells exposed to diethyl maleate (DEM) or sodium arsenite (arsen.); both compounds induce oxidative stress. The SG marker G3BP1 was detected by immunofluorescent staining; Cy3-labeled oligo-dT(50) was used as a probe to locate poly(A)-containing RNA. Pixel intensities/area were quantified for G3BP1 and oligo-dT(50) for both treatments (left bar graph). Data were normalized to arsenite-treated cells. In addition, the relationship between areas occupied in SGs by oligo-dT(50) and G3BP1 were measured and the ratio oligo-dT(50)/G3BP1 was calculated for individual SGs (right bar graph). Note that DEM and arsenite-treated cells show significant differences for pixel intensities/area; this applies to both G3BP1 and oligo-dT(50). The relative areas occupied by oligo-dT(50) and G3BP1 are also significantly different for the two oxidants. Scale bar is 20 μm; ***, p values <0.001. Adapted from [4] with permission.

4.5 High-throughput screening assays to analyze nucleoli and SGs

Here, we discuss the integration of quantitative microscopy and HTS instrumentation to examine nucleoli and SGs. The importance of nucleoli and SGs for cell physiology and their essential contributions to human health are well established ([15, 46] and section 3). High-throughput technology is instrumental for the further in-depth characterization of both compartments. Aside from defining their biological properties, HTS will also help to identify the role nucleoli and SGs play in human disease. Ultimately, this will advance the development of new clinically relevant therapies. Nucleoli. Nucleoli contain several thousand different proteins and are intimately linked to cancer cell growth and proliferation. Accordingly, they represent a large repertoire of potential drug targets for cancer treatment. Towards this goal, our tools successfully analyzed nucleoli in an HTS setting [9]. With a Z-factor of 0.57, the measurement of compartment area is an excellent assay to quantify the impact of chemotherapeutic drugs on nucleoli (Fig. 7A). As we have shown earlier [9], this assay is suitable for the large-scale screening of compound libraries to develop drugs that target nucleoli. SGs. As described for nucleoli, our quantitative methods were combined with HTS technology. Our assays measure different SG parameters in a high throughput setting [4]. Quantifying the number of SGs in DEM-treated cells is highly suitable for HTS, as shown by the Z-factor of 0.64. Importantly, HTS technology confirmed that SGs induced by DEM or arsenite differ in their biological properties, confirming the novel insights into SG biology we had gained by confocal microscopy [4].


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Fig. 7 Nucleoli and SGs were analyzed with HTS instrumentation. (A) Nucleoli were detected with the marker protein fibrillarin. The percentage of nucleoli with an area < 4 μm2 was determined in HeLa cells incubated with vehicle (DMSO) or actinomycin D (Act D). (B) An excellent assay suitable for HTS was developed for the formation of SGs. This assay is based on the number of SGs induced by DEM treatment. Parts A and B of the figure were adapted from our publications [4, 9], with permission.

5. Conclusions and future directions

Our chapter provides an overview of the fluorescence microscopy protocols we designed to quantify compartment-specific parameters in a fully automated fashion. Our methods generated new insights into fundamental aspects of cellular organization and function. Future applications of these methods go beyond basic science and include questions that are directly relevant to human health. For example, nucleolar properties are critical to cancer cell growth and proliferation, whereas subcellular granules and inclusions are frequently associated with neurodegenerative disorders or virus infections. The quantitative assessment of such structures and their responses to pharmacological drugs will be crucial to the development of new diagnostic and therapeutic approaches. Given the obvious advantages of quantitative fluorescence microscopy, some limitations may preclude its wide-spread use. As such, there is no universally applicable setting to acquire and analyze images for a specific compartment. Accordingly, compartment markers and constraints for compartment identification and measurements have to be optimized. Thus, it is necessary to adjust these variables to the cell type and experimental conditions at the beginning of the study. Due to the overlap in fluorochrome excitation or emission and restrictions imposed by the instrumentation, there is only a limited number of components that can be evaluated simultaneously in the same image. As a result, a global examination of compartment properties may be difficult, especially if the compartment is composed of a large number of constituents. Although significant progress has been made in recent years, future studies will benefit from further improvements to the analysis software. For instance, in addition to intensity and size thresholds, other criteria for compartment demarcation will be useful. These include better filters or modules that recognize complex shapes or morphologies relevant to cell biology. Examples of such complex structures are insulin crystals located inside secretory granules [56], invading parasites [57], dysmorphic NEs [53, 58] or even non-biological components, represented by irreregularly shaped nanoparticles [53, 59]. We anticipate that the protocols presented here will expand the understanding of subcellular organelles and compartments in future studies. To this end, our methods can enhance live cell imaging, where the collection of time-lapse images and their automatic quantification are instrumental to define dynamic intracellular events [60]. Furthermore, the accurate demarcation and measurement of organelles or compartments in 3D will generate information on the changes in volume, organization and function in the whole-cell context. Ultimately, this will promote the use of HTS combined with 3D analysis, as in recent studies of metastasis [61]. Our methods will advance these developments by providing a robust and reliable set of markers and protocols that have been succesful for the analysis of essential subcellular organelles and compartments.

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