This work was partly supported by the project &#34;A Greek Research Infrastructure for Visualizing and Monitoring Fundamental Biological Processes (BioImaging-GR)&#34; (MIS 5002755) which is implemented under the Action &#34;Reinforcement of the Research and Innovation Infrastructure&#34;, funded by the Operational Programme &#34;Competitiveness, Entrepreneurship and Innovation&#34; (NSRF 2014-2020) and co-financed by Greece and the E. U.

1. Inoculum preparation
NOTE: All steps should be performed under a laminar flow cabinet.
<ol>
	<li>Streak out fungal strain of interest, from a glycerol stock (-80 &#176;C) using a sterile inoculation loop, onto plates of minimal media (MM) supplemented with the appropriate nutritional requirements relevant to the strain examined&#160;[MM: 10.0 g/L glucose, 20 mL/L salt solution (salt solution: 26 g/L KCl, 26 g/L MgSO4&#183;7H2O, 76 g/L KH2PO4, 2.0 mL/L chloroform) and 1 mL/L trace elements (trace elements: 40 mg/L Na2B4O7&#183;H2O, 400 mg/L CuSO4, 8 g/L ZnSO4, 800 mg/L MnSO4, 800 mg/L FePO4), adjust pH to 6.8 with 1 M NaOH, add 1 % (w/v) agar and the required supplements as described in16 and autoclave] (Figure 1). 
	NOTE: Salt solution, trace elements solution and supplements are autoclaved.</li>
	<li>Incubate for 2-3 days at 37 &#176;C.</li>
	<li>Use a sterile toothpick (or an inoculation loop), transfer a small number of conidia, by gently touching a single colony, to plates of complete media (CM) [CM: 10.0 g/L glucose, 2.0 g/L peptone, 1.0 g/L yeast extract, 1.0 g/L casamino acids, 20 mL/L salt solution, 1 mL/L trace elements, 5 mL/L vitamin solution (vitamin solution: 0.1 g/L riboflavin, 0.1 g/L nicotinamide, 0.01 g/L p-amino benzoic acid, 0.05 g/L pyridoxine HCl, 1.0 mg/L biotin), adjust pH to 6.8 with 1 M NaOH, add 1 % (w/v) agar and the required supplements as described in16 and autoclave]. Autoclave and store the vitamin solution in a dark bottle at 4 &#176;C. 
	NOTE: In case fungal growth is too dense to identify and isolate individual colonies, re-streak onto a new agar plate to obtain single colonies.</li>
	<li>Incubate for 3-4 days at 37 &#176;C.</li>
	<li>Obtain a conidial suspension of approximately 2 x 106 cells/mL by scratching 1 cm from the surface of a conidiated fungal colony grown on CM agar plates, using a sterile toothpick (Figure S1). 
	NOTE: When necessary, count conidia with a hemocytometer.</li>
	<li>Harvest conidia of A. nidulans in a sterile 1.5 mL centrifuge tube with 1.0 mL of autoclaved distilled water containing 0.05% (v/v) Tween 80 for reducing the number of conidia clumps. 
	NOTE: Conidia can be stored for up to 2-3 weeks at 4 &#176;C without a relevant loss of viability (A. Athanasopoulos and V. Sophianopoulou, unpublished data). However, it is recommended to filter and/or to wash conidial suspension to remove mycelial parts and nutrients, in order to prevent conidial swelling.</li>
</ol>
2. Preparation for imaging filamentous fungi growing on agar (solid) mediums
NOTE: A modified version of the &#39;inverted agar method17,18 is used.
<ol>
	<li>Initially, spot 10 &#181;L aliquots of vigorously vortexed conidial (approximately 2 x 104 cells/mL) at several points onto Petri dishes (&#216;9 cm) 15 mL of MM with 1% (w/v) agar (Figure 2). 
	NOTE: Using the modified version of the &#39;inverted agar method&#39;, it is possible to image fungal samples for many hours without apparent deleterious effects on growing hyphae.</li>
	<li>Incubate the experimental culture according to the developmental stage intended to be investigated.</li>
	<li>Slice out a &#8776;0.8 mm2 block of agar containing the colony using a sterile scalpel. 
	NOTE: The dimensions of the agar block to be sliced out depends on the dimensions of the equipment to be placed afterwards. In the present work, 8 well &#181;-slides are used (see below).</li>
	<li>Invert and place the agar block into a well of an &#181;-slide or similar 8 chambered coverglass with coverslip suitable for live imaging. 
	&#8203;NOTE: In case transmitted light microscopy will be used in combination with fluorescence (labeling) microscopy, the agar block can be inverted onto a droplet of liquid medium containing the live cell staining dye, just before imaging.</li>
</ol>
3. Preparation for imaging filamentous fungi growing on liquid medium
<ol>
	<li>Transfer 10 &#181;L aliquots of a vigorously vortexed conidial suspension (approximately 2 x 104 cells/mL) in the wells of an 8 well &#181;-slide containing 200 &#181;L of (liquid) MM with the appropriate supplements (see above).</li>
	<li>Incubate for the desired time at the desired temperature (Figure 3). 
	&#8203;NOTE: If transmitted light microscopy will be used in combination with fluorescence (labeling) microscopy, liquid cultures have the great advantage that fluorescent dyes can be added at any desired time point during the experiment19.</li>
</ol>
4. Capture images
NOTE: The choice of microscope depends upon the available equipment. In any case the microscope setup should include an inverted stage, an environmental chamber or at least a room with precise air temperature control.
<ol>
	<li>Preheat the thermostated microscope chamber at 37 &#176;C (unless otherwise indicated or as suitable for the used fungal species) to stabilize the temperature before starting. This chamber allows temperature modulation of the microscope optics and sample stage during time-lapse experiments. Be aware that optical aberrations20 are introduced when normal immersion oils (designed for use at 23 &#176;C) oils are used at 37 &#176;C or above. 
	NOTE: On a tight budget, incubation chambers can be made out of cardboard and insulating packing material21 or by using a 3D printer22.</li>
	<li>Turn on the microscope, the scanner power, the laser power and computer, and load the imaging software. Place the &#181;-slide (prepared previously) in the microscope stage and focus.</li>
	<li>Find fields of view that contain isolated/not overlapping cells (or at least not overcrowded), in order to facilitate growth measurements during image analysis. Capture at least 50 growing cells per sample&#160;to allow robust statistical analysis.</li>
	<li>Select the desired transmitted light microscopy approach. Reduce the exposure time or laser power and pixel dwell time and/or increase pinhole diameters, in order to minimize photobleaching of fungal cells, as described elsewhere 23,24.</li>
	<li>Set microscope to acquire images at desired time intervals and start time series acquisition. 
	&#8203;NOTE: To correct for focal drift over time (especially for long experiments), due to thermal drift, diverse cell sizes, and cell motion use an autofocus strategy if&#160;available in your microscope software.</li>
</ol>
5. Image Analysis
NOTE: This section describes the key steps of processing time-lapse microscopy images for measuring growth rate of A. nidulans. Opening, visualization and processing of images is accomplished with the open source ImageJ/Fiji software25.
<ol>
	<li>Import the images to Fiji using Plugins | Bio-Formats | Bio-Formats Importer from the Fiji menu with default settings (Figure 4A). 
	NOTE: Check whether the Bio-Formats Importer properly recognize the image calibration. The picture dimension shown in the upper information field image window, must be equal to the original picture dimensions (Figure 4B). Press Shift + P to display and change image properties in ImageJ/Fiji software.</li>
	<li>Where needed, use histogram matching26 for illumination correction between different frames (Image | Adjust | Bleach Correction | Histogram Matching) (Figure 4C).</li>
	<li>Where needed, use SIFT-algorithm (Plugins | Registration | Linear Stack Alignment with SIFT) for aligning or matching image stacks (Figure 4D). Selecting &#34;Translation&#34; from the expected transformation menu should be enough to correct any x-y drift. 
	NOTE: Other plugins can be also used to align a stack of image slices, such as Image Stabilizer (https://imagej.net/Image_Stabilizer)&#160;or StackReg (http://bigwww.epfl.ch/thevenaz/stackreg/).</li>
	<li>Select hyphae that grow parallel to coverslip, avoiding those that are tilted. Be sure to select hyphae that propagate by polar extension and avoid hyphae presenting lateral and/or apical branching.</li>
	<li>Use MTrackJ (Plugins | MTrackJ) plugin to track growing hyphal tips (Figure 4E)27. To add a track, select the Add button in the toolbar and place the first point at a hyphal tip using the left click of the mouse. The time series will automatically move to the next frame. To complete the tracking process, double click the mouse on the final point (or press the Esc key) (Figure 4F). Move to another point of interest (i.e., growing hyphal tip) in the initial time frame and restart the procedure by measuring growth rate of another hypha. 
	NOTE: To install MTrackJ follow the instructions presented at https://imagescience.org/meijering/software/mtrackj/</li>
	<li>Click the Measure button in the MTrackJ dialog (Figure 4G) to open the output table. Save track measurements (File | Save As) to the desired file format (e.g., csv), analyze and plot them (Figure 4H). 
	NOTE: By selecting the Movie button, a movie is produced showing the image and track progression.</li>
</ol>

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J., Williams, G. A., Chan, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+analysis+of+filamentous+microbial+morphology+with+AnaMorf.">Automated analysis of filamentous microbial morphology with AnaMorf.</a> Biotechnology Progress. 31 (3), 849-852 (2015).</li></ol>

The authors have nothing to disclose.

Monitoring fungal cell growth and phenotype by time-lapse microscopy is a powerful approach to assess cellular behavior in real-time and quantitatively and accurately determine whether a particular drug treatment and/or genetic intervention results in detectable cell growth or phenotypic differences over time.
In this study, a reliable live-cell imaging methodology was described to measure and quantitatively analyze fungal development, including the dynamics of germ tube and hyphal tip growth ...

Filamentous fungi are of great socioeconomic and ecological importance, being both crucial as industrial/agricultural tools for enzyme and antibiotic production1,2 and as pathogens of crop plants3, pest insects4 and humans3. Moreover, filamentous fungi such as Aspergillus&#160;nidulans are widely used as model organisms for fundamental research, such as studies in genetics, cell and evolutionary biology as well as for the study of hyphal extension5. Filamentous fungi are highly polarized organisms that elongate through the continuous supply of membrane lipids/proteins and the de novo synthesis of cell wall at the extending tip6. A central role in the hyphal tip growth and polarity maintenance is a specialized structure named &#39;Spitzenkorper&#39; (SPK), a highly ordered structure consisting mostly of cytoskeletal components and the polarized distribution of the Golgi6,7,8.
Environmental stimuli/signals, such water-air interface, light, CO2 concentration, and the nutritional status are responsible for the developmental decisions made by these molds9. In submerged (liquid) cultures the differentiation of A. nidulans is repressed and growth occurs by hyphal tip elongation6. During vegetative growth, asexual spores (conidia) germinate by apical extension, forming an undifferentiated network of interconnected hyphal cells, the mycelium, which may continue to grow indefinitely as long as nutrients and space are available. On the other hand, on solid media hyphal tips elongate and after a defined period of vegetative growth (developmental competence), asexual reproduction is initiated and aerial conidiophore stalks extend from specialized foot cells of the mycelium6. These give rise to specialized developmental multicellular structures called conidiophores, which produce long chains of haploid conidia10 that can restart growth under favorable environmental conditions.
A widely used method for measuring filamentous fungal growth is to inoculate spores on nutrient agar contained in a Petri dish and macroscopically measure the diameter of the colony a few days later11. The diameter/area of the colony, most dependent on changes in mycelial growth rate and less on conidiophore density12, is then used as a value of growth. Although, measuring fungal population (colony) size growing on solid surfaces is quite adequate, it is by no means the most accurate measure of growth. Compared to population level averages (averages of fungal colony size), single cell&#160;measurements can capture the heterogeneity of a cell population and allow identification of novel sub-populations of cells, states13, dynamics, pathways as well as the biological mechanisms by which cells respond to endogenous and environmental changes14,15. Monitoring fungal cell growth and phenotype by time-lapse microscopy is arguably the most widely employed quantitative single cell observation approach.
Herein, we detail a label-free live imaging protocol using transmitted light microscopy techniques (such as phase-contrast, differential interference contrast (DIC), and polarized microscopy) to capture images, which independently of the combined use of fluorescence microscopy can be employed to analyze and quantify polar growth of A. nidulans strains in both submerged cultures and solid media.

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			<td>&#181;-Slide 8 Well</td>
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			<td>80826</td>
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		<tr>
			<td>4-Aminobenzoic acid</td>
			<td>Merck</td>
			<td>A9878</td>
			<td></td>
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			<td>azhA&#916; ngnA&#916;</td>
			<td></td>
			<td></td>
			<td>Genotype: zhA&#916;::pyrGAf; ngnA&#916;::pyrGAf; pyroA4 pantoB100 / References:Laboratory collection, Athanasopoulos et al., 2013</td>
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			<td>Gibco</td>
			<td>223030</td>
			<td></td>
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			<td>B4639</td>
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			<td>Merck</td>
			<td>67-66-3</td>
			<td></td>
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		<tr>
			<td>Copper(II) sulfate pentahydrate</td>
			<td>Merck</td>
			<td>C8027</td>
			<td></td>
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		<tr>
			<td>Glucose</td>
			<td>Merck</td>
			<td>G8270</td>
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		<tr>
			<td>GraphPad Prism 8.0</td>
			<td>GraphPad Software</td>
			<td></td>
			<td>Statistical Software</td>
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		<tr>
			<td>ImageJ</td>
			<td>NIH</td>
			<td></td>
			<td>Image processing and analysis software</td>
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			<td>Inoculating Loop</td>
			<td>Merck</td>
			<td>I8263-500EA</td>
			<td></td>
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		<tr>
			<td>Iron(III) phosphate</td>
			<td>Merck</td>
			<td>1.03935</td>
			<td></td>
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			<td>Leica Application Suite X</td>
			<td>Leica Microsystems</td>
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			<td>Merck</td>
			<td>63138</td>
			<td></td>
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		<tr>
			<td>Manganese(II) sulfate monohydrate</td>
			<td>Merck</td>
			<td>M7899</td>
			<td></td>
		</tr>
		<tr>
			<td>Microscope Leica TCS SP8</td>
			<td>Leica Microsystems</td>
			<td></td>
			<td></td>
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		<tr>
			<td>Nicotinamide (Niacinamide)</td>
			<td>Supelco</td>
			<td>47865-U</td>
			<td></td>
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		<tr>
			<td>Peptone</td>
			<td>Millipore</td>
			<td>68971</td>
			<td></td>
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			<td>KISKER</td>
			<td>G090</td>
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			<td>Potassium chloride</td>
			<td>Merck</td>
			<td>P4504</td>
			<td></td>
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			<td>Potassium phosphate monobasic</td>
			<td>Merck</td>
			<td>P5655</td>
			<td></td>
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		<tr>
			<td>Pyridoxine hydrochloride</td>
			<td>Merck</td>
			<td>P6280</td>
			<td></td>
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			<td>Quali - Microcentrifuge Tubes, 1,7 mL, DNase-, RNase and pyrogen free, sterile</td>
			<td>KISKER</td>
			<td>G052-S</td>
			<td></td>
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			<td>Quali - Microcentrifuge Tubes, 2.0 mL, sterile</td>
			<td>KISKER</td>
			<td>G053-S</td>
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			<td>Quali - Standard Tips, Bevelled, 100-1000 &#181;L</td>
			<td>KISKER</td>
			<td>VL004G</td>
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			<td>Quali - Standard Tips, Bevelled, 1-200 &#181;L</td>
			<td>KISKER</td>
			<td>VL700G</td>
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			<td>Quali Microvolume Tips, DNase-, RNase free, 0,1-10 &#181;L/clear</td>
			<td>KISKER</td>
			<td>GC.TIPS.B</td>
			<td></td>
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			<td>Riboflavin (B2)</td>
			<td>Supelco</td>
			<td>47861</td>
			<td></td>
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		<tr>
			<td>Scalpel blades NO. 11</td>
			<td>OdontoMed2011</td>
			<td>S2771</td>
			<td></td>
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			<td>Sodium chloride</td>
			<td>Merck</td>
			<td>S7653</td>
			<td></td>
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			<td>Sodium hydroxide</td>
			<td>Merck</td>
			<td>S8045</td>
			<td></td>
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			<td>Sodium tetraborate decahydrate</td>
			<td>Merck</td>
			<td>S9640</td>
			<td></td>
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		<tr>
			<td>VS151 (PilA-GFP and H1-mRFP)</td>
			<td></td>
			<td></td>
			<td>Genotype: pyrG89; pilA::sgfp::AfpyrG+ argB2 nkuA&#916;::argB+&#160; pyroA4 hhoA::mrfp::Afribo+ riboB2 / References:Laboratory collection, Biratsi et al., 2021</td>
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		<tr>
			<td>WT</td>
			<td></td>
			<td></td>
			<td>Genotype: nkuA&#916;::argB; pyrG89; pyroA4;pyrG89 / References: TN02A3 -FGSC A1149</td>
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			<td>Yeast Extract</td>
			<td>Millipore</td>
			<td>70161</td>
			<td></td>
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		<tr>
			<td>ZnSO4</td>
			<td></td>
			<td></td>
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quantitative analysis of aspergillus nidulans growth rate using live microscopy and open-source software

It is well established that colony growth of filamentous fungi, mostly dependent on changes in hyphae/mycelia apical growth rate, is macroscopically estimated on solidified media by comparing colony size. However, to quantitatively measure the growth rate of genetically different fungal strains or strains under different environmental/growth conditions (pH, temperature, carbon and nitrogen sources, antibiotics, etc.) is challenging. Thus, the pursuit of complementary approaches to quantify growth kinetics becomes mandatory in order to better understand fungal cell growth. Furthermore, it is well-known that filamentous fungi, including Aspergillus spp., have distinct modes of growth and differentiation under sub-aerial conditions on solid media or submerged cultures. Here, we detail a quantitative microscopic method for analyzing growth kinetics of&#160;the model fungus Aspergillus nidulans, using live imaging in both submerged cultures and solid media. We capture images, analyze, and quantify growth rates of different fungal strains in a reproducible and reliable manner using an open source, free software for bio-images (e.g., Fiji), in a way that does not require any prior image analysis expertise from the user.

Following this protocol, we captured and analyzed various images corresponding to different growth/developmental stages of the filamentous fungus A. nidulans. The data presented in this study were processed and analyzed using the Fiji software. Measurements were saved as csv files, statistically analyzed and prepared as graphs using commercial statistical software and/or Python programming language using software libraries like pandas, numpy, statsmodels, matplotlib and seaborn. More details can be found in the ...

Watch this Scientific Journal Video about Quantitative Analysis of Aspergillus nidulans Growth Rate using Live Microscopy and Open-Source Software at JoVE.com

Quantitative Analysis of Aspergillus nidulans Growth Rate using Live Microscopy and Open-Source Software

We present a label-free live imaging protocol using transmitted light microscopy techniques to capture images, analyze and quantify growth kinetics of the filamentous fungus A. nidulans in both submerged cultures and solid media. This protocol can be used in conjunction with fluorescence microscopy.

Quantitative Analysis of Aspergillus nidulans Growth Rate using Live Microscopy and Open-Source Software

It is well established that colony growth of filamentous fungi, mostly dependent on changes in hyphae/mycelia apical growth rate, is macroscopically ...

quantitative-analysis-aspergillus-nidulans-growth-rate-using-live

Research

JoVE Journal

Biology

3.6K Views.  National Centre for Scientific Research, Demokritos (NCSRD). We present a label-free live imaging protocol using transmitted light microscopy techniques to capture images, analyze and quantify growth kinetics of the filamentous fungus A. nidulans in both submerged cultures and solid media. This protocol can be used in conjunction with fluorescence microscopy.

Video: Quantitative Analysis of Aspergillus nidulans Growth Rate using Live Microscopy and Open-Source Software

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Embryonic epithelial cells serve as an ideal model to study morphogenesis where multi-cellular tissues undergo changes in their geometry, such as changes in cell surface area and cell height, and where cells undergo mitosis and migrate. Furthermore, epithelial cells can also regulate morphogenetic movements in adjacent tissues1. A traditional method to study epithelial cells and tissues involve chemical fixation and histological methods to determine cell morphology or localization of particular proteins of interest. These approaches continue to be useful and provide "snapshots" of cell shapes and tissue architecture, however, much remains to be understood about how cells acquire specific shapes, how various proteins move or localize to specific positions, and what paths cells follow toward their final differentiated fate. High resolution live imaging complements traditional methods and also allows more direct investigation into the dynamic cellular processes involved in the formation, maintenance, and morphogenesis of multicellular epithelial sheets. Here we demonstrate experimental methods from the isolation of animal cap tissues from Xenopus laevis embryos to confocal imaging of epithelial cells and simple measurement approaches that together can augment molecular and cellular studies of epithelial morphogenesis.

Live-cell Imaging and Quantitative Analysis of Embryonic Epithelial Cells in Xenopus laevis

Xenopus embryonic epithelia are an ideal model system to study cell behaviors such as polarity development and shape change during epithelial morphogenesis. Traditional histology of fixed samples is increasingly being complemented by live-cell confocal imaging. Here we demonstrate methods to isolate frog tissues and visualize live epithelial cells and their cytoskeleton using live-cell confocal microscopy.

Embryonic epithelial cells serve as an ideal model to study morphogenesis where multi-cellular tissues undergo changes in their geometry, such as changes ...

Imaging C. elegans Embryos using an Epifluorescent Microscope and Open Source Software

Cellular processes, such as chromosome assembly, segregation and cytokinesis,are inherently dynamic. Time-lapse imaging of living cells, using fluorescent-labeled reporter proteins or differential interference contrast (DIC) microscopy, allows for the examination of the temporal progression of these dynamic events which is otherwise inferred from analysis of fixed samples1,2. Moreover, the study of the developmental regulations of cellular processes necessitates conducting time-lapse experiments on an intact organism during development. The Caenorhabiditis elegans embryo is light-transparent and has a rapid, invariant developmental program with a known cell lineage3, thus providing an ideal experiment model for studying questions in cell biology4,5and development6-9. C. elegans is amendable to genetic manipulation by forward genetics (based on random mutagenesis10,11) and reverse genetics to target specific genes (based on RNAi-mediated interference and targeted mutagenesis12-15). In addition, transgenic animals can be readily created to express fluorescently tagged proteins or reporters16,17. These traits combine to make it easy to identify the genetic pathways regulating fundamental cellular and developmental processes in vivo18-21. In this protocol we present methods for live imaging of C. elegans embryos using DIC optics or GFP fluorescence on a compound epifluorescent microscope. We demonstrate the ease with which readily available microscopes, typically used for fixed sample imaging, can also be applied for time-lapse analysis using open-source software to automate the imaging process.

Imaging C. elegans Embryos using an Epifluorescent Microscope and Open Source Software

The C. elegans embryo is a powerful system for studying cell biology and development. We present a protocol for live imaging of C. elegans embryos utilizing DIC optics or fluorescence using readily available epifluorescent microscopes and open-source software.

Cellular processes, such as chromosome assembly, segregation and cytokinesis,are inherently dynamic. Time-lapse imaging of living cells, using ...

Quantitative Live Cell Fluorescence-microscopy Analysis of Fission Yeast

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using fluorochromes like Green Fluorescent Protein (GFP) directly attached to the protein of interest has become increasingly popular 1. Using GFP and similar fluorochromes the subcellular localisations and movements of proteins can be detected in a fluorescent microscope. Moreover, also the subnuclear localisation of a certain region of a chromosome can be studied using this technique. GFP is fused to the Lac Repressor protein (LacR) and ectopically expressed in the cell where tandem repeats of the lacO sequence has been inserted into the region of interest on the chromosome2. The LacR-GFP will bind to the lacO repeats and that area of the genome will be visible as a green dot in the fluorescence microscope. Yeast is especially suited for this type of manipulation since homologous recombination is very efficient and thereby enables targeted integration of the lacO repeats and engineered fusion proteins with GFP 3. Here we describe a quantitative method for live cell analysis of fission yeast. Additional protocols for live cell analysis of fission yeast can be found, for example on how to make a movie of the meiotic chromosomal behaviour 4. In this particular experiment we focus on subnuclear organisation and how it is affected during gene induction. We have labelled a gene cluster, named Chr1, by the introduction of lacO binding sites in the vicinity of the genes. The gene cluster is enriched for genes that are induced early during nitrogen starvation of fission yeast 5. In the strain the nuclear membrane (NM) is labelled by the attachment of mCherry to the NM protein Cut11 giving rise to a red fluorescent signal. The Spindle Pole body (SPB) compound Sid4 is fused to Red Fluorescent Protein (Sid4-mRFP) 6. In vegetatively growing yeast cells the centromeres are always attached to the SPB that is embedded in the NM 7. The SPB is identified as a large round structure in the NM. By imaging before and 20 minutes after depletion of the nitrogen source we can determine the distance between the gene cluster (GFP) and the NM/SPB. The mean or median distances before and after nitrogen depletion are compared and we can thus quantify whether or not there is a shift in subcellular localisation of the gene cluster after nitrogen depletion.

The fission yeast, Schizosaccharomyces pombe, is a good model system to study basic cellular processes. Here we describe a method to perform quantitative live cell analysis of fission yeast. In this particular experiment we focus on organisation of the genome within the cell nucleus, but the method can also be used to study cytosolic factors.

Several microscopy techniques are available today that can detect a specific protein within the cell. During the last decade live cell imaging using ...

Quantitative Analysis of Random Migration of Cells Using Time-lapse Video Microscopy

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During directional migration, cells move rapidly in response to an extracellular chemotactic signal, or in response to intrinsic cues 3 provided by the basic motility machinery. Random migration occurs when a cell possesses low intrinsic directionality, allowing the cells to explore their local environment.
Cell migration is a complex process, in the initial response cell undergoes polarization and extends protrusions in the direction of migration 2. Traditional methods to measure migration such as the Boyden chamber migration assay is an easy method to measure chemotaxis in vitro, which allows measuring migration as an end point result. However, this approach neither allows measurement of individual migration parameters, nor does it allow to visualization of morphological changes that cell undergoes during migration.
Here, we present a method that allows us to monitor migrating cells in real time using video - time lapse microscopy. Since cell migration and invasion are hallmarks of cancer, this method will be applicable in studying cancer cell migration and invasion in vitro. Random migration of platelets has been considered as one of the parameters of platelet function 4, hence this method could also be helpful in studying platelet functions. This assay has the advantage of being rapid, reliable, reproducible, and does not require optimization of cell numbers. In order to maintain physiologically suitable conditions for cells, the microscope is equipped with CO2 supply and temperature thermostat. Cell movement is monitored by taking pictures using a camera fitted to the microscope at regular intervals. Cell migration can be calculated by measuring average speed and average displacement, which is calculated by Slidebook software.

This method allows monitoring of cells in real time and quantitative measurements of different cell migration parameters such as speed, displacement, and velocity. Unlike the traditional methods, this real time approach is not based on endpoint quantitative migration measurements; instead it allows monitoring and calculating different parameters continuously.

Cell migration is a dynamic process, which is important for embryonic development, tissue repair, immune system function, and tumor invasion 1, 2. During ...

Quantitative Analysis of Autophagy using Advanced 3D Fluorescence Microscopy

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, traditional chemotherapeutic approaches have been largely unsuccessful. Hormone therapy is effective at early stage, but often fails with the eventual development of hormone-refractory tumors. We have been interested in developing therapeutics targeting specific metabolic deficiency of tumor cells. We recently showed that prostate tumor cells specifically lack an enzyme (argininosuccinate synthase, or ASS) involved in the synthesis of the amino acid arginine1. This condition causes the tumor cells to become dependent on exogenous arginine, and they undergo metabolic stress when free arginine is depleted by arginine deiminase (ADI)1,10. Indeed, we have shown that human prostate cancer cells CWR22Rv1 are effectively killed by ADI with caspase-independent apoptosis and aggressive autophagy (or macroautophagy)1,2,3. Autophagy is an evolutionarily-conserved process that allows cells to metabolize unwanted proteins by lysosomal breakdown during nutritional starvation4,5. Although the essential components of this pathway are well-characterized6,7,8,9, many aspects of the molecular mechanism are still unclear - in particular, what is the role of autophagy in the death-response of prostate cancer cells after ADI treatment? In order to address this question, we required an experimental method to measure the level and extent of autophagic response in cells - and since there are no known molecular markers that can accurately track this process, we chose to develop an imaging-based approach, using quantitative 3D fluorescence microscopy11,12.
Using CWR22Rv1 cells specifically-labeled with fluorescent probes for autophagosomes and lysosomes, we show that 3D image stacks acquired with either widefield deconvolution microscopy (and later, with super-resolution, structured-illumination microscopy) can clearly capture the early stages of autophagy induction. With commercially available digital image analysis applications, we can readily obtain statistical information about autophagosome and lysosome number, size, distribution, and degree of colocalization from any imaged cell. This information allows us to precisely track the progress of autophagy in living cells and enables our continued investigation into the role of autophagy in cancer chemotherapy.

Autophagy is a ubiquitous process that enables cells to degrade and recycle proteins and organelles. We apply advanced fluorescence microscopy to visualize and quantify the small, but essential, physical changes associated with the induction of autophagy, including the formation and distribution of autophagosomes and lysosomes, and their fusion into autolysosomes.

Prostate cancer is the leading form of malignancies among men in the U.S. While surgery carries a significant risk of impotence and incontinence, ...

Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly dependent on modes of single-cell analysis. Methods which deliver composite data reflecting the mean values of biomarkers from cell populations risk losing subpopulation dynamics that reflect the heterogeneity of the studied biological system. In keeping with this, traditional approaches are being replaced by, or supported with, more sophisticated forms of cellular assay developed to allow assessment by high-content microscopy. These assays potentially generate large numbers of images of fluorescent biomarkers, which enabled by accompanying proprietary software packages, allows for multi-parametric measurements per cell. However, the relatively high capital costs and overspecialization of many of these devices have prevented their accessibility to many investigators.
Described here is a universally applicable workflow for the quantification of multiple fluorescent marker intensities from specific subcellular regions of individual cells suitable for use with images from most fluorescent microscopes. Key to this workflow is the implementation of the freely available Cell Profiler software1&#160;to distinguish individual cells in these images, segment them into defined subcellular regions and deliver fluorescence marker intensity values specific to these regions. The extraction of individual cell intensity values from image data is the central purpose of this workflow and will be illustrated with the analysis of control data from a siRNA screen for G1 checkpoint regulators in adherent human cells. However, the workflow presented here can be applied to analysis of data from other means of cell perturbation (e.g., compound screens) and other forms of fluorescence based cellular markers and thus should be useful for a wide range of laboratories.

Presented is a flexible informatics workflow enabling multiplexed image-based analysis of fluorescently labeled cells. The workflow quantifies nuclear and cytoplasmic markers and computes marker translocation between these compartments. Procedures are provided for perturbation of cells using siRNA and reliable methodology for marker detection by indirect immunofluorescence in 96-well formats.

Advances in understanding the control mechanisms governing the behavior of cells in adherent mammalian tissue culture models are becoming increasingly ...

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics1,2. One of the most well-known and widely-utilized +TIPs for analyzing MT dynamics is the End-Binding protein, EB1, which binds all growing MT plus-ends, and thus, is a marker for MT polymerization1. Many studies of EB1 behavior within growth cones have used time-consuming and biased computer-assisted, hand-tracking methods to analyze individual MTs1-3. Our approach is to quantify global parameters of MT dynamics using the software package, plusTipTracker4, following the acquisition of high-resolution, live images of tagged EB1 in cultured embryonic growth cones5. This software is a MATLAB-based, open-source, user-friendly package that combines automated detection, tracking, visualization, and analysis for movies of fluorescently-labeled +TIPs. Here, we present the protocol for using plusTipTracker for the analysis of fluorescently-labeled +TIP comets in cultured Xenopus laevis growth cones. However, this software can also be used to characterize MT dynamics in various cell types6-8.

Using plusTipTracker Software to Measure Microtubule Dynamics in Xenopus laevis Growth Cones

The MATLAB-based, open source software package, plusTipTracker, can be used to analyze image series of fluorescently-labeled +TIPs to quantify microtubule dynamics.

Microtubule (MT) plus-end-tracking proteins (+TIPs) localize to the growing plus-ends of MTs and regulate MT dynamics1,2. One of the most well-known and ...

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools

Quantitatively capturing developmental processes is crucial to derive mechanistic models and key to identify and describe mutant phenotypes. Here protocols are presented for preparing embryos and adult C. elegans animals for short- and long-term time-lapse microscopy and methods for tracking and quantification of developmental processes. The methods presented are all based on C. elegans strains available from the Caenorhabditis Genetics Center and on open-source software that can be easily implemented in any laboratory independently of the microscopy system used. A reconstruction of a 3D cell-shape model using the modelling software IMOD, manual tracking of fluorescently-labeled subcellular structures using the multi-purpose image analysis program Endrov, and an analysis of cortical contractile flow using PIVlab (Time-Resolved Digital Particle Image Velocimetry Tool for MATLAB) are shown. It is discussed how these methods can also be deployed to quantitatively capture other developmental processes in different models, e.g., cell tracking and lineage tracing, tracking of vesicle flow.

Tracking and Quantifying Developmental Processes in C. elegans Using Open-source Tools

Here it is shown how to track and quantify developmental processes in C. elegans. The methods presented are based on open-source tools that can be easily implemented. It is demonstrated how to reconstruct 3D cell-shape models, how to manually track subcellular structures, and how to analyze cortical contractile flow.

Quantitatively capturing developmental processes is crucial to derive mechanistic models and key to identify and describe mutant phenotypes. Here ...

Open Source High Content Analysis Utilizing Automated Fluorescence Lifetime Imaging Microscopy

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts of fixed or live cells in multiwell plates. This provides a means to screen for cell signaling processes read out using intramolecular FRET biosensors or intermolecular FRET of protein interactions such as oligomerization or heterodimerization, which can be used to identify binding partners. We describe here the functionality of this automated multiwell plate FLIM instrumentation and present exemplar data from our studies of HIV Gag protein oligomerization and a time course of a FRET biosensor in live cells. A detailed description of the practical implementation is then provided with reference to a list of hardware components and a description of the open source data acquisition software written in &#181;Manager. The application of FLIMfit, an open source MATLAB-based client for the OMERO platform, to analyze arrays of multiwell plate FLIM data is also presented. The protocols for imaging fixed and live cells are outlined and a demonstration of an automated multiwell plate FLIM experiment using cells expressing fluorescent protein-based FRET constructs is presented. This is complemented by a walk-through of the data analysis for this specific FLIM FRET data set.

We present an open source high content analysis (HCA) instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions using F&#246;rster resonance energy transfer (FRET) based readouts. Data acquisition for this openFLIM-HCA instrument is controlled by software written in &#181;Manager and data analysis is undertaken in FLIMfit.

We present an open source high content analysis instrument utilizing automated fluorescence lifetime imaging (FLIM) for assaying protein interactions ...

Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper

Super-resolution fluorescence microscopy is currently revolutionizing cell biology research. Its capacity to break the resolution limit of around 300 nm allows for the routine imaging of nanoscale biological complexes and processes. This increase in resolution also means that methods popular in electron microscopy, such as single-particle analysis, can readily be applied to super-resolution fluorescence microscopy. By combining this analytical approach with super-resolution optical imaging, it becomes possible to take advantage of the molecule-specific labeling capacity of fluorescence microscopy to generate structural maps of molecular elements within a metastable structure. To this end, we have developed a novel algorithm &#8212; VirusMapper &#8212; packaged as an easy-to-use, high-performance, and high-throughput ImageJ plugin. This article presents an in-depth guide to this software, showcasing its ability to uncover novel structural features in biological molecular complexes. Here, we present how to assemble compatible data and provide a step-by-step protocol on how to use this algorithm to apply single-particle analysis to super-resolution images.

This manuscript uses the Fiji-based open-source software package VirusMapper to apply single-particle analysis to super-resolution microscopy images in order to generate precise models of nanoscale structure.

Super-resolution fluorescence microscopy is currently revolutionizing cell biology research. Its capacity to break the resolution limit of around 300 nm ...