Name: quantitative approaches for studying cellular structures and organelle morphology in caenorhabditis elegans
Uploaded: 2019-07-05T15:00:00
Description: Watch this Scientific Journal Video about Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans at JoVE.com

We thank members of the Neumann lab for valuable discussions and input. Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). The authors thank WormBase for its wealth of information on C. elegans, and acknowledge Monash Micro Imaging, Monash University, for the provision of instrumentation, training and technical support. This work was supported by CMTAA research grants (2015 and 2018), and NHMRC Project Grants 1101974 and 1099690 awarded to B.N.

1. Growth and maintenance of C. elegans strains
<ol>
	<li>Seed Nematode Growth Medium (NGM, see Table of Materials) agar plates with 300 &#181;L of the slow-growing E. coli strain OP50 in a laminar flow cabinet.</li>
	<li>Leave the NGM agar plates in the laminar flow cabinet to dry. 
	NOTE: In the absence of laminar flow cabinet, plates can be left to dry on the bench but they are more prone to contamination.</li>
	<li>Transfer at least 20 animals to each of two OP50-seeded NGM a...

<ol>
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Morphological variations have frequently been assessed via manual counting of noticeable differences or using arbitrary thresholds to determine defects in comparison to a wild-type phenotype. More recently, however, quantitative methods have been used for comparative studies of morphology to accurately measure and describe changes on a cellular and subcellular level in an unbiased fashion. The ability to identify subtle yet biologically relevant differences between phenotypes is a powerful means for understanding the und...

The nematode Caenorhabditis elegans (C. elegans) is increasingly utilized as a model system to uncover the biological and molecular processes involved in human disease. An adult nematode has a body length of just over 1 mm, and can produce a large brood of up to 300 eggs1. After hatching, C. elegans only require 3-4 days to reach adulthood, and live for around 2 to 3 weeks2. Due to its ease of culturing, C. elegans is currently one of the most sought-after in vivo animal models for conducting cost-effective, rapid drug screening to identify therapeutics for human diseases. Additionally, its genetic conservation, well defined behavioral paradigms, transparent body for fluorescence or light microscopy, and ease of genetic manipulation make the study of cellular and molecular consequences of genetic mutations readily achieveable3. The C. elegans genome shares approximately 60-80% orthology with human genes, and about 40% of those genes are known to be disease-related. Some of human diseases that have been modelled and studied in C. elegans include neurodegenerative disorders (Alzheimer&#8217;s disease, Parkinson&#8217;s disease, amyotrophic lateral sclerosis, Charcot-Marie-Tooth disease), muscle-associated diseases (Duchenne muscular dystrophy), and metabolic diseases (hyperglycemia)2,4. In most human disorders, disease-induced cellular and organelle localization and morphological changes occur, which can readily be evaluated in the nematode model.
Fluorescent markers have been widely used to label tissues and organelles for dynamic visualization under the microscope. However, in C. elegans, conventional methods that assess morphological irregularities due to genetic mutations have largely relied on visual descriptions. While qualitative assessments can cover wider ranges of phenotypic descriptions (synaptic morphology, GFP clumping, specific axonal shape, muscle fiber thickness, etc.) and provide a bird&#8217;s eye view of the morphological changes, they are less well suited for comparing small variations across different groups. Furthermore, qualitative assessments are based on visual, subjective evaluation, which may lead to over- or under-estimations of morphological abnormalities. Finally, qualitative observations can also vary greatly between individuals, creating difficulties with data replication.&#160;
In recent years, a number of user-friendly, readily available computational algorithms that can quantitatively analyse images have been developed. However, the utilization of such image analysis software for some morphological studies, especially in relation to body wall muscles and mitochondria, in C. elegans research has lagged behind. To improve underlying structural analysis in C. elegans, some of the readily available, open-source image analysis software were trialed to quantitatively compare the effects of genetic mutations on muscle mitochondria, body wall muscle and synaptic morphology. These experimental procedures outline in detail how these programs (Fiji, ilastik, CellProfiler, SQUASSH) can be used to evaluate changes in synaptic size and synaptic protein localization, body wall muscle area and fiber length, and mitochondrial size and circularity as a result of genetic mutations in the nematode.&#160;

<table>
	<tbody>
		<tr>
			<td>Agar-agar</td>
			<td>Merck</td>
			<td>1.01614.1000</td>
			<td></td>
		</tr>
		<tr>
			<td>Agarose</td>
			<td>Invitrogen</td>
			<td>16500-500</td>
			<td></td>
		</tr>
		<tr>
			<td>Confocal microscope</td>
			<td>Leica</td>
			<td>TCS SP8</td>
			<td>Inverted platform</td>
		</tr>
		<tr>
			<td>Fluorescence microscope</td>
			<td>Carl Zeiss AG</td>
			<td>Zeiss Axio Imager M2</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass coverslips #1</td>
			<td>Thermo scientifique</td>
			<td>MENCS22221GP</td>
			<td></td>
		</tr>
		<tr>
			<td>Glass coverslips #1.5</td>
			<td>Zeiss</td>
			<td>474030-9000-000</td>
			<td>Made by SCHOTT</td>
		</tr>
		<tr>
			<td>Glass slides</td>
			<td>Thermo scientifique</td>
			<td>MENS41104A/40</td>
			<td></td>
		</tr>
		<tr>
			<td>Light LED</td>
			<td>Schott</td>
			<td>KL 300 LED</td>
			<td></td>
		</tr>
		<tr>
			<td>Stereo Microscope</td>
			<td>Olympus</td>
			<td>SZ51</td>
			<td></td>
		</tr>
		<tr>
			<td>Tryptone (Peptone from casein)</td>
			<td>Merck</td>
			<td>107213</td>
			<td>Ingredients for Lysogeny Broth (LB) medium</td>
		</tr>
		<tr>
			<td>Yeast Extract</td>
			<td>Merck</td>
			<td>103753</td>
			<td>Ingredients for Lysogeny Broth (LB) medium</td>
		</tr>
		<tr>
			<td>Sodium chloride</td>
			<td>Merck</td>
			<td>106404</td>
			<td>Ingredients for Lysogeny Broth (LB) medium</td>
		</tr>
		<tr>
			<td>Peptone (Peptone from meat)</td>
			<td>Merck</td>
			<td>107214</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Agar</td>
			<td>Sigma</td>
			<td>A1296</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Sodium chloride</td>
			<td>Merck</td>
			<td>106404</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Cholesterol</td>
			<td>Sigma</td>
			<td>C8667-25G</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Calcium chloride</td>
			<td>Merck</td>
			<td>102382</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Magnesium sulfate</td>
			<td>Merck</td>
			<td>105886</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Dipotassium phosphate</td>
			<td>Merck</td>
			<td>105101</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Potassium dihydrogen phosphate</td>
			<td>Merck</td>
			<td>104873</td>
			<td>Ingredients for Nematode Growth Media (NGM) agar</td>
		</tr>
		<tr>
			<td>Disodium phosphate</td>
			<td>Merck</td>
			<td>106586</td>
			<td>Ingredients for M9 buffer</td>
		</tr>
		<tr>
			<td>Sodium chloride</td>
			<td>Merck</td>
			<td>106404</td>
			<td>Ingredients for M9 buffer</td>
		</tr>
		<tr>
			<td>Potassium dihydrogen phosphate</td>
			<td>Merck</td>
			<td>104873</td>
			<td>Ingredients for M9 buffer</td>
		</tr>
		<tr>
			<td>Magnesium sulfate</td>
			<td>Merck</td>
			<td>105886</td>
			<td>Ingredients for M9 buffer</td>
		</tr>
		<tr>
			<td>Pasteur pipette</td>
			<td>Corning</td>
			<td>CLS7095D5X-200EA</td>
			<td></td>
		</tr>
		<tr>
			<td>Petri dishes</td>
			<td>Corning</td>
			<td>CLS430589-500EA</td>
			<td></td>
		</tr>
		<tr>
			<td>Platinum wire</td>
			<td>Sigma</td>
			<td>267201-2G</td>
			<td></td>
		</tr>
		<tr>
			<td>Spatula</td>
			<td>Met-app</td>
			<td>2616</td>
			<td></td>
		</tr>
		<tr>
			<td>Tetramisole hydrochloride</td>
			<td>Sigma</td>
			<td>L9756-5G</td>
			<td></td>
		</tr>
	</tbody>
</table>

quantitative approaches for studying cellular structures and organelle morphology in caenorhabditis elegans

Defining the cellular mechanisms underlying disease is essential for the development of novel therapeutics. A strategy frequently used to unravel these mechanisms is to introduce mutations in candidate genes and qualitatively describe changes in the morphology of tissues and cellular organelles. However, qualitative descriptions may not capture subtle phenotypic differences, might misrepresent phenotypic variations across individuals in a population, and are frequently assessed subjectively. Here, quantitative approaches are described to study the morphology of tissues and organelles in the nematode Caenorhabditis elegans using laser scanning confocal microscopy combined with commercially available bio-image processing software. A quantitative analysis of phenotypes affecting synapse integrity (size and integrated fluorescence levels), muscle development (muscle cell size and myosin filament length), and mitochondrial morphology (circularity and size) was performed to understand the effects of genetic mutations on these cellular structures. These quantitative approaches are not limited to the applications described here, as they could readily be used to quantitatively assess the morphology of other tissues and organelles in the nematode, as well as in other model organisms.

C. elegans is an ideal model organism for studying morphology of different tissues and organelles due to its simplicity, known cell lineage, transparency, and available tools. Here, we provide quantitative approaches for studying organelles (e.g., mitochondria) and tissues, including synapses and muscles using live fluorescence imaging and free bio-image processing software.
Strict regulation of MEC-17 expressio...

Watch this Scientific Journal Video about Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans at JoVE.com

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

This study outlines quantitative measurements of synaptic size and localization, muscle morphology, and mitochondrial shape in C. elegans using freely available image processing tools. This approach allows future studies in&#160;C. elegans&#160;to quantitatively compare the extent of tissue and organelle structural changes as a result of genetic mutations.

Quantitative Approaches for Studying Cellular Structures and Organelle Morphology in Caenorhabditis elegans

Defining the cellular mechanisms underlying disease is essential for the development of novel therapeutics. A strategy frequently used to unravel these ...

The ability to quantify changes in the morphology of tissues and organelles is important for understanding gene function as well as the impact of genetic mutations. Our protocols explain how freely available software can be used for non-subjectively assessing the morphology of synapses, muscles, and mitochondria in a nematode, C.elegans. Many previous studies have relied upon qualitative methods for comparing morphological changes.However, these can be problematic as they may not capture subtle phenotypic differences, might over and underestimate changes, and are assessed subjectively. Our quantitative methods provide more robust and less biased means for assessing morphological changes. These methods could easily be used for studying morphological changes in other cellular structures or model organisms in order to define the gene function and the consequences of disease-associated mutations.Start by preparing slides for imaging. Place a drop a of melted agarose onto a microscope slide and immediately press down the droplet with another microscope slide, gently flattening the agarose. Leave the agarose to dry for one minute then carefully separate the two slides and leave the solidified pad on one of the slides.Place the slide on the microscope stage and add a five to 10-milliliter drop of anesthetic to the center of the agarose pad. Use a heat-sterilized pick to quickly transfer 10 to 15 animals from the stock plate to the anesthetic droplet before the solution dries out. Then apply a coverslip by positioning it just above the agarose pad and gently dropping it down.Image the synaptic regions with a line-scanning confocal microscope coupled to a 488 and 552 nanometer optically-pumped semi-conductor diode laser and equipped with image capture software. After locating the worms, switch to a 40X magnification and apply immersion medium. Visual the synaptic region by exciting the fluorophores with a 552 nanometer laser, 1%power for the tagRFP fluorophore, and 488 nanometers, 2%power for the GFP fluorophore.Capture images using a hybrid photodetector and set the gains to prevent overexposure of the fluorophores. Collect Z-stack images to cover the entire synapse using the optimal Z-step size depending on the objective. To analyze the synaptic region begin by loading the images into the CellProfiler 3.1.5 software.Set up the NameAndType module and determine the synaptic region by hand definition using the diffuse tagRFP expressed from the UIS-115 transgene. Measure the size and fluorescence of the hand-defined synapse by adding the MeasureObjectSizeShape and MeasureObjectIntensity modules to the pipeline. Then calculate the relative integrated fluorescence intensity by adding the CalculateMath module and dividing the integrated intensity units obtained from JSIS37 by those obtained from UIS-115.When finished export all measurements and calculations. To measure muscle cell area open the image in Fiji software and use polygon selection to carefully trace around a single oblique muscle cell. Adjust the line of the polygon at the end by dragging the anchor dot to improve tracing.Navigate to the Analyze tab at the top of the software and click Measure to calculate the selected area. For muscle cells with a degenerated or missing region trace the missing area with the polygon selection tool and click Measure again. If there are multiple gaps, trace each one separately.Calculate the ratio of the gap area to the area of the entire cell. A high ratio indicates a higher extent of muscle degeneration. And if there are no missing regions, the ratio is calculated as zero.Open Elastic and choose Pixel Classification under Create New Project. Then rename and save the project. Navigate to the input data tab and click Add New, and then Add separate images.Direct the pop-up window to the folder with the TIF files and select the desired image. In the Feature Selection tab click on Select Features to select all pixel features indicated by the green ticked boxes. The pixel selection in this step is used to distinguish the different classes of pixels in the next step.Use a Training panel to distinguish between the individual GFP-expressing myosin filaments and unwanted background. Click on Add Label and scrawl unwanted backgrounds and spaces between the filaments to begin classifier training. Add a second label, rename it to Filament, and scrawl over a number of filaments.Click on Live Update to make sure that the classification has been done correctly. If necessary, add more scrawls to fine tune the training. Once training classifier has been performed, go to the Prediction Export panel and click on Choose Export Image Settings with probabilities as the source.Make sure that the cutout subregions x and y are ticked, and c is unticked. Select zero and one as start and stop values for c, and Convert Data Type to unsigned 8-bit. Tick Renormalize and then change the output file video to png, renaming the file and directory as desired.Close the Export settings window and export the image that has just been segmented. Then open the png file in Fiji software. Adjust the threshold of the image using Default settings and apply the skeletonization plug-in, which will create a separate table of results.This protocol has been used to explore the function of alpha-tubulin acetyltransferase MEC-17 in synapse development. Quantitative analysis of images of the posterior/lateral microtubule or PLM synapses indicates that overexpression of MEC-17 disrupts normal neuron function. Compared to the wild type control animals overexpressing MEC-17 have significantly reduced presynaptic regions and synaptic integrity.These techniques have also been used to analyze C.elegans models of Charcot-Marie-Tooth type 2 or CMT2 carrying mutations in CMT2-associated genes. Visual assessment of body wall muscle morphology revealed a 2.5 to 3.5-fold increase in defects in the test animals compared to the wild type control. Animals with mutations in fzo-1 and unc-116 experienced loss of muscle striations, accumulation of cellular debris, and muscle fiber degeneration.While animals with mutations in dyn-1 experienced significantly less defects in muscle morphology. The fzo-1 and unc-116 mutants displayed a five to six-fold increase in the ratio of gap to total single cell area and a dramatically shorter average fiber length compared to wild type animals. For comparisons to be made between samples it is important to determine the most optimal conditions for image acquisition, and to ensure that these conditions are used consistently.These techniques will allow researchers to compare morphological changes across different genetic backgrounds with quantitative approaches. This reduces the subjectivity and therefore help to enhance the representability of the data generated.

Research

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JoVE Journal

JoVE Core

Cell Biology

Biology

Unit 1

Cells, Genomes, and Evolution

SCIENTISTS IN ACTION

Measuring Caenorhabditis elegans Life Span on Solid Media

Measuring Caenorhabditis elegans Life Span on Solid Media

Aging is a degenerative process characterized by a progressive deterioration of cellular components and organelles resulting in mortality. The nematode ...

A high-throughput method to globally study the organelle morphology in S. cerevisiae

High-throughput methods to examine protein localization or organelle morphology is an effective tool for studying protein interactions and can help ...

Visualization of Caenorhabditis elegans Cuticular Structures Using the Lipophilic Vital Dye DiI

Visualization of Caenorhabditis elegans Cuticular Structures Using the Lipophilic Vital Dye DiI

The cuticle of C. elegans is a highly resistant structure that surrounds the exterior of the animal1-4. The cuticle not only protects the animal from the ...

Vampiric Isolation of Extracellular Fluid from Caenorhabditis elegans

Vampiric Isolation of Extracellular Fluid from Caenorhabditis elegans

The genetically tractable model organism C. elegans has provided insights into a myriad of biological questions, enabled by its short generation time, ...

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Basic Caenorhabditis elegans Methods: Synchronization and Observation

Research into the molecular and developmental biology of the nematode Caenorhabditis elegans was begun in the early seventies by Sydney Brenner and it has ...

Analyzing and Building Nucleic Acid Structures with 3DNA

The 3DNA software package is a popular and versatile bioinformatics tool with capabilities to analyze, construct, and visualize three-dimensional nucleic ...

Prostaglandin Extraction and Analysis in Caenorhabditis elegans

Prostaglandin Extraction and Analysis in Caenorhabditis elegans

Caenorhabditis elegans is emerging as a powerful animal model to study the biology of lipids1-9. Prostaglandins are an important class of eicosanoids, ...

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

Methods to Study Changes in Inherent Protein Aggregation with Age in Caenorhabditis elegans

In the last decades, the prevalence of neurodegenerative disorders, such as Alzheimer's disease (AD) and Parkinson's disease (PD), has grown. These ...

Modeling Age-Associated Neurodegenerative Diseases in Caenorhabditis elegans

Modeling Age-Associated Neurodegenerative Diseases in Caenorhabditis elegans

Battling human neurodegenerative pathologies and managing their pervasive socioeconomic impact is becoming a global priority. Notwithstanding their ...

Automating Aggregate Quantification in Caenorhabditis elegans

Automating Aggregate Quantification in Caenorhabditis elegans

A rise in the prevalence of neurodegenerative protein conformational diseases (PCDs) has fostered a great interest in this subject over the years. This ...