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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 C. elegans to quantitatively compare the extent of tissue and organelle structural changes as a result of genetic mutations.
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.
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’s disease, Parkinson’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’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.
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.
1. Growth and maintenance of C. elegans strains
2. Age-synchronizing C. elegans
3. Preparation of slides for imaging
4. Assessing synaptic morphology
NOTE: The effects of MEC-17 overexpression on synapse integrity in the posterior lateral microtubule (PLM) touch receptor neurons were studied by quantifying the synaptic size and localization using line scanning confocal microscopy. The PLM neurons (including the synaptic regions) were visualized using the uIs115(Pmec-17::tagRFP) transgene (strain: TU40655) and the synaptic region was specifically labeled with jsIs37(Pmec-7::snb-1::GFP) (strain: NM6646). This study was performed in synchronized L3 non-transgenic and transgenic animals of the extrachromosomal MEC-17 overexpression strain BXN507 [cjnEx036(Pmec-4::mec-17, Pmyo-2::mCherry); jsIs37; uIs115]7. A complete list of strains used in this study is included in Table 1.
5. Quantifying body wall muscle structure
6. Quantifying mitochondrial morphology
NOTE: For the quantification of mitochondrial morphology, this study used the BXN0387 strain containing the uIs115(Pmec-17::tagRFP)5 transgene to visualize the PLM neurons and jsIs609(Pmec-4::MLS::GFP)11 to visualize mitochondria specifically within the PLM neurons. This study was performed in synchronized 3 day old adult worms, but has successfully been performed at other ages, as well as in other tissues7.
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...
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 authors declare that they have no competing interests.
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.
Name | Company | Catalog Number | Comments |
Agar-agar | Merck | 1.01614.1000 | |
Agarose | Invitrogen | 16500-500 | |
Confocal microscope | Leica | TCS SP8 | Inverted platform |
Fluorescence microscope | Carl Zeiss AG | Zeiss Axio Imager M2 | |
Glass coverslips #1 | Thermo scientifique | MENCS22221GP | |
Glass coverslips #1.5 | Zeiss | 474030-9000-000 | Made by SCHOTT |
Glass slides | Thermo scientifique | MENS41104A/40 | |
Light LED | Schott | KL 300 LED | |
Stereo Microscope | Olympus | SZ51 | |
Tryptone (Peptone from casein) | Merck | 107213 | Ingredients for Lysogeny Broth (LB) medium |
Yeast Extract | Merck | 103753 | Ingredients for Lysogeny Broth (LB) medium |
Sodium chloride | Merck | 106404 | Ingredients for Lysogeny Broth (LB) medium |
Peptone (Peptone from meat) | Merck | 107214 | Ingredients for Nematode Growth Media (NGM) agar |
Agar | Sigma | A1296 | Ingredients for Nematode Growth Media (NGM) agar |
Sodium chloride | Merck | 106404 | Ingredients for Nematode Growth Media (NGM) agar |
Cholesterol | Sigma | C8667-25G | Ingredients for Nematode Growth Media (NGM) agar |
Calcium chloride | Merck | 102382 | Ingredients for Nematode Growth Media (NGM) agar |
Magnesium sulfate | Merck | 105886 | Ingredients for Nematode Growth Media (NGM) agar |
Dipotassium phosphate | Merck | 105101 | Ingredients for Nematode Growth Media (NGM) agar |
Potassium dihydrogen phosphate | Merck | 104873 | Ingredients for Nematode Growth Media (NGM) agar |
Disodium phosphate | Merck | 106586 | Ingredients for M9 buffer |
Sodium chloride | Merck | 106404 | Ingredients for M9 buffer |
Potassium dihydrogen phosphate | Merck | 104873 | Ingredients for M9 buffer |
Magnesium sulfate | Merck | 105886 | Ingredients for M9 buffer |
Pasteur pipette | Corning | CLS7095D5X-200EA | |
Petri dishes | Corning | CLS430589-500EA | |
Platinum wire | Sigma | 267201-2G | |
Spatula | Met-app | 2616 | |
Tetramisole hydrochloride | Sigma | L9756-5G |
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