We thank Deok Joong Lee for critical reading of the manuscript and testing the Python code. This research was sponsored by the National Research Foundation of Korea 2017R1A5A2015369 (K.-h.Y.) and 2019R1C1C1008708 (K.-h.Y.).

1. Setting up the imaging apparatus (Figure 1A-E)
<ol>
	<li>Ensure that a smartphone camera with the following minimum requirements is available: 
	12&#160;megapixel (MP) camera 
	1080p resolution video 
	5 GB&#160;of storage space (20 min video is 3-4 Gb) 
	Time-lapse video app from the application store (free applications available)</li>
	<li>Place the LED light box on the bottom rack of the 25 &#176;C incubator where the assay will take place.</li>
	<li>To hide the dotted pattern on the LED light surface, spread two sheets of tissues to cover the entire surface of the LED box.</li>
	<li>Make an elevated stage for the specimen (Figure 1A,D). The elevated stage is a clear plastic sheet supported by hollow rectangular tunnels. Tunnels function like a condenser to focus light, providing better contrast to the specimen (Figure 1C). Ensure that the tunnel&#39;s walls are somewhat dark to minimize light scatter. This study used brown paper boxes. The dimension of the tunnel is 5.5 cm x 17 cm x 4.5 cm (W x L x H). The LED light box can fit up to five tunnels.</li>
	<li>Place another rack above the stage to place the phones for recording (Figure 1B,E). Each phone will record three to six plates (one to two rows of three plates), so adjust the rack height accordingly. This will be approximately 15 cm above the specimen (Figure 1B).</li>
	<li>Put a power strip inside the incubator to plug in the phones during overnight recording.</li>
</ol>
2. Preparation of buffers and media
<ol>
	<li>Prepare M9 buffer by adding 3 g of KH2PO4, 6 g of Na2HPO4, and 5 g of NaCl to 1 L of distilled H2O. Sterilize by autoclaving at 121 &#176;C for 20 min. Cool the buffer and then add 1 mL of 1 M MgSO4.</li>
	<li>Prepare 1 M KPO4 buffer by adding 108.3 g of KH2PO4 and 35.6 g of K2HPO4 to 1 L of H2O. Adjust the pH to 6.0 by adding KOH. Sterilize by autoclaving.</li>
	<li>Prepare worm bleaching solution by mixing 1 mL of bleach, 0.4 mL of 1 M NaOH, and 2.6 mL of H2O.</li>
	<li>Prepare nematode growth media (NGM) agar plates.
	<ol>
		<li>Add 3 g of NaCl, 2.5 g of bacto peptone, and 17 g of bacto agar in a 3 L flask. Add 975 mL of distilled water and insert a stir bar.</li>
		<li>Sterilize by autoclaving, then cool to 55 &#176;C, and add 1 mL of cholesterol (5 mg/mL in ethanol), 1 mL of 1 M CaCl2, 1 mL of 1 M MgSO4, and 25 mL of 1 M KPO4 buffer (pH 6.0). Stir to mix well. Pour into 6 cm plates. Let the plates dry for at least 2 days.</li>
	</ol>
	</li>
	<li>Seed NGM agar plates with OP50 E. coli by pipetting approximately 1 mL of an overnight culture of OP50 to form a lawn of bacteria. Leave at room temperature (RT) until ready to use.</li>
</ol>
3. Preparation of high-peptone NGM plates (for PA14)
NOTE: These plates should be made at least 5 days before the assay.
<ol>
	<li>Make NGM containing 0.35% peptone. Mix 0.3 g of NaCl, 0.35 g of bacto peptone, and 1.7 g of bacto agar in a 250 mL Erlenmeyer flask. Add 97.5 mL of distilled water and insert a stir bar.</li>
	<li>Cover the mouth of the flask with aluminum foil and autoclave at 121 &#176;C for 20 min.</li>
	<li>Cool down to 55 &#176;C and add 0.1 mL of cholesterol (5 mg/mL in ethanol), 0.1 mL of 1 M CaCl2, 0.1 mL of 1 M MgSO4, and 2.5 mL of 1 M KPO4 buffer (pH 6.0). Stir to mix well.</li>
	<li>Pour high-peptone NGM into 35 mm Petri dishes.</li>
	<li>Dry the plates for at least 2 days.</li>
</ol>
4. Synchronizing worms by bleaching
NOTE: Start this step 3 days before the assay.
<ol>
	<li>Take plates with gravid adult worms and collect them into a 1.7 mL microtube by washing the plates with M9 buffer.</li>
	<li>Remove as much liquid as possible, then add 400 &#181;L of bleaching solution. Wait about 4-5 min with intermittent vortexing, until the adult worm bodies break, releasing the eggs.</li>
	<li>Add M9 buffer to fill the rest of the microtube to dilute the bleaching solution. Spin at maximum speed (12,000 to 13,000 x g) for 1-2 s. Remove the supernatant and wash three more times with M9 buffer.</li>
	<li>Transfer the eggs into an empty 35 mm Petri dish containing M9 buffer. Let the eggs hatch overnight at 20 &#176;C. In the absence of food, hatched worms will arrest at the L1 larval stage, synchronizing the developmental stage of all worms. 
	NOTE: Coating the 35 mm Petri dish with gelatin solution (0.05% gelatin in autoclaved water) can prevent the eggs from sticking to the bottom and minimize egg loss.</li>
	<li>The next day, transfer L1 stage worms to OP50 seeded NGM plates.</li>
	<li>Incubate the worms at 20 &#176;C for 53-54 h until the worms reach the L4 larval stage.</li>
</ol>
5. Preparation of bacteria (&#160;Pseudomonas aeruginosa, PA14)
NOTE: Start this step 4 days before the assay.
<ol>
	<li>Streak thawed bacteria from -80 &#176;C on a Luria Bertani (LB) agar plate without any antibiotic and incubate overnight at 37 &#176;C. 
	NOTE: Always use fresh bacteria. Streaked plates should be stored at 4 &#176;C for no more than 1 week.</li>
	<li>Inoculate a single colony into 3 mL of King&#39;s broth and grow overnight in a 37 &#176;C shaking incubator.</li>
	<li>The next day, seed 7 &#181;L of the overnight culture onto the high-peptone NGM plates and incubate at 37 &#176;C for 24 h.</li>
	<li>Move the seeded plates to RT and incubate for another 24 h before use. Once ready, use the plate within the next 24 h.</li>
</ol>
6. Preparing to record
NOTE: Do this right before the assay.
<ol>
	<li>Plug in the smartphone to the power strip connected to a power outlet. Make sure to disable the auto-lock setting to prevent the phone returning to the lock screen while recording.</li>
	<li>Open the time-lapse camera app and set the time-lapse interval to 2 s. Set the video quality to 1080p at 30 fps.</li>
	<li>Place the smartphone with the screen facing up to record with the back-facing camera. Check the screen to make sure that the paper box tunnels fit within the field of view.</li>
</ol>
7. Lawn avoidance assay
<ol>
	<li>Using a platinum wire pick, transfer 30 synchronized L4 stage worms (53-54 h from L1) to the PA14 plate. Place the worms in the middle of the bacteria lawn. For each condition in this study, two plates were tested (i.e., 60 worms per condition).</li>
	<li>Place the two plates on the elevated stage of the recording apparatus with the lid facing down. The side with the agar will be facing up toward the camera.</li>
	<li>On the smartphone screen, tap where the plate is, so the camera can focus on the assay plates. It helps to have a label or writing on the plate as the camera can use that to focus correctly. 
	NOTE: Writing on the bottom of the plates does not interfere with the imaging of worms as long as it is toward the edge. Fortunately, worms stay near the lawn even after they leave, so an unobstructed view is only needed of the immediate area surrounding the lawn.</li>
	<li>Start the recording.</li>
	<li>Once the recording has started, add more plates to the stage. There may be a significant lag time between the plates due to the time it takes to transfer worms by picking. Note the lag time afterward so that each condition can be counted at the time it began.</li>
	<li>Record for 20 h from the last set of plates placed on the stage. In the final time-lapse video, 20 h of recording will result in a 20 min long video. 
	NOTE: It may be worthwhile to count the worms directly from the plates after the assay, at least at the beginning for the first few occasions. This can be compared against values obtained through video imaging to ensure they yield similar numbers.</li>
</ol>
8. Processing of video using Python script
<ol>
	<li>Transfer the movie file to a computer for processing. The extension will be a MOV (iPhone) or MP4 file (Android).</li>
	<li>Use a Python code to process the videos. The code can be found at github.com/khyoon201/wormavoid.</li>
	<li>To run the Python scripts, ensure that the following are preinstalled on the computer: ffmpeg, a tool for converting video files (directions for installation can be found on its website, ffmpeg.org/download), and the Python packages os, pandas, tkinter, and ffmpeg-python.</li>
	<li>Find the dimensions and coordinates of each plate using the extract_frame.py script.
	<ol>
		<li>Run the extract_frame.py script. A window will appear to select the video file stored on the computer. After running is completed, a jpeg file with the same name will appear in the same directory.</li>
		<li>Open the jpeg file in ImageJ (imagej.org).</li>
		<li>From the menu, choose Analyze &#62; Set Measurements. Ensure that the Display Label box is checked (Figure 2A). Close the window.</li>
		<li>Using the Straight Line tool, measure the diameter of a plate by drawing a line across it, then choosing Analyze &#62; Measure from the menu. If the video is in 1080p, each plate will be about 480 pixels wide. Write this information down and close the Results window.</li>
		<li>Using the Multi-point tool, mark points on the upper left side of each plate. These points will become the upper left corner of the cropped videos (Figure 2B). The order matters; mark in order of when the plates were started. After creating a point for all the plates, choose Analyze &#62; Measure from the menu. Measurements, including the X and Y coordinates of the points, will appear in the Results window.</li>
		<li>To process multiple videos, repeat the process in ImageJ with other jpeg files. All X and Y coordinates will be listed in the same Results window.</li>
		<li>Save the Results window into a csv file. The file should be saved to the same directory as the movie files.</li>
	</ol>
	</li>
	<li>Find the starting time for each plate.
	<ol>
		<li>Play the movie, either on the computer or phone, and take note of the starting times of each set of plates placed under the camera.</li>
		<li>Open the Results.csv file with the coordinates and add a &#34;start&#34; column. For each row corresponding to individual plates, enter the appropriate start time, in seconds, under the &#34;start&#34; column (e.g., if the start time is 0:00:08, enter 8). Save. 
		NOTE: The column name must be &#34;start&#34; (in lower case, without quotation marks) to be recognized by the next script for cropping and trimming.</li>
	</ol>
	</li>
	<li>Crop and trim the videos.
	<ol>
		<li>Run the crop_n_trim.py script.</li>
		<li>When prompted, choose the Results.csv file. 
		NOTE: Make sure the Results.csv file and all the movie files are in the same directory.</li>
		<li>Enter the plate dimensions. Enter the pixel value noted earlier. 
		&#8203;NOTE: The script will now read each row of the Results.csv file to find the correct movie file by reading the file name in the &#34;label&#34; column, and crop according to the coordinates indicated in columns &#34;X&#34; and &#34;Y&#34;. The start time of each plate will be determined by the time indicated in the &#34;start&#34; column. After the script finishes running, a folder will appear with the same name as the movie, followed by the start time (e.g., &#34;Movie1_8&#34;), in which 10 s videos corresponding to each hourly time point of the assay will be saved.</li>
	</ol>
	</li>
</ol>
9. Manual counting using ImageJ
<ol>
	<li>Open each AVI file in ImageJ.</li>
	<li>Count the worms that are visible outside the lawn. Worms that are overlapped in one frame usually move apart in another frame so that they can be counted correctly.</li>
	<li>Calculate the occupancy rate for each time point: 
	Occupancy rate = (total worms - number of worms outside the lawn)/total worms 
	NOTE: The worms will move in and out of the lawn during the video, but this will not significantly alter the results. Try to go with the number that seems to be the average, or the number of worms at the exact hourly time point (5 s into the video).</li>
</ol>

Smartphone-Based Imaging for C. elegans Lawn Avoidance Assay

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No conflicts of interest declared.

Imaging animal behavior, rather than relying on direct observation, is not only convenient but also has the advantage of leaving visual documentation. This allows for blind analysis by an objective third person, or could even be used for automated analysis using image recognition techniques. Despite the advantages, the standard equipment usually offered is high in cost, so one is committed to the setup once purchased.
Using smartphones to collect video recordings of simple C. elegans ...

Among the many advantages of studying C. elegans, its simple nervous system offers the opportunity to study how changes at the genetic and cellular level impact network function and behavioral output. Despite having a limited number of neurons, C. elegans display a wide range of complex behaviors. One of these is lawn avoidance, in which the bacterivorous nematode responds to a harmful food source by leaving the bacterial lawn. C. elegans avoid lawns of pathogenic bacteria1,2,3, lawns of bacteria that produce toxins or are spiked with toxins1,4, and even RNAi-expressing bacteria whose target gene knockdown is detrimental to the health of the worms4,5. Studies have shown that worms respond to external cues such as metabolites produced by the pathogenic bacteria1,6, or internal cues that indicate that the food is making them sick4,7. These cues are processed through conserved signaling pathways, such as the mitogen-activated protein kinase (MAPK) pathway and the transforming growth factor beta (TGF&#946;) pathway, and require communication between the gut and the nervous system4,6,7,8.
Although the assay is simple, the learned behavior develops over many hours, often overnight. While there are mutants that are incapable of leaving, in which case scoring avoidance at just one time point is sufficient to demonstrate the defect, many mutants do leave eventually but are slower to come out. For these, the movement of the worms needs to be tracked every few hours, which can be difficult to do overnight. Counting itself also takes time, creating a lag time between the plates, and thus limits the number of plates that can be tested at the same time. Using an imaging setup to record many plates simultaneously for the whole duration of the assay would be very useful, but the cost of setup can be prohibitive, depending on the funding situation of the research lab.
To address this, we devised a very simple method that uses smartphones to record avoidance assays. Each phone can record time-lapse videos of up to six assay plates. To provide transmitted light, we use a light emitting diode (LED) light box that can be easily purchased online. Assay plates are placed on an elevated platform, supported by hollow rectangular tunnels, that focus the incoming light, creating contrast. We also provide a Python script that converts the videos into audio video interleave (AVI) files showing 10 s clips of each hourly time point. The videos are then cropped to individual plates and saved in separate files to use for manual counting.
The method provides a low-cost procedure that is also extremely easy to use, using items that are readily available to most people. Here, we describe the method using the well-established lawn avoidance assay against the human pathogen Pseudomonas aeruginosa (PA14), whose protocol has been previously described2,9. Finally, we also review the considerations and limitations of the imaging method for those that want to apply it to other C. elegans behavior experiments.

<table><tbody><tr><td>35 mm Petri dish</td><td>SPL</td><td>#10035</td><td></td></tr><tr><td>Bacto agar</td><td>BD</td><td>#214010</td><td></td></tr><tr><td>Bacto Peptone</td><td>BD</td><td>#211677</td><td></td></tr><tr><td>CaCl&lt;sub&gt;2&lt;/sub&gt;</td><td>DAEJUNG</td><td>2507-1400</td><td></td></tr><tr><td>Cholesterol</td><td>BioBasic</td><td>CD0122</td><td></td></tr><tr><td>Dipotassium hydrogen phosphate (K&lt;sub&gt;2&lt;/sub&gt;HPO&lt;sub&gt;4&lt;/sub&gt;)</td><td>JUNSEI</td><td>84120-0350</td><td></td></tr><tr><td>Glycerol</td><td>BioBasic</td><td>GB0232</td><td></td></tr><tr><td>King B Broth</td><td>MB cell</td><td>MB-K0827</td><td></td></tr><tr><td>LED light box multi-pad</td><td>Artmate</td><td>N/A</td><td>This is a USB powered, LED light pad for tracing and drawing purposes. Artmate is a Korean brand, but searching for &quot;LED light box for tracing&quot; in any search engine should yield numerous options from other brands. Overall dimension is around 9&quot; x 12&quot; (A4 size). For example, from amazon US: https://www.amazon.com/LITENERGY-Ultra-Thin-Adjustable-Streaming-Stenciling/dp/B07H7FLJX1/ref=sr_1_5?crid=YMYU0VYY226R&amp;amp;keywords=&lt;br/&gt; LED%2Blight%2Bbox&amp;amp;qid=1674183224&amp;amp;sprefix&lt;br/&gt; =led%2Blight%2Bbo%2Caps%2C270&amp;amp;sr=8-5&amp;amp;th=1</td></tr><tr><td>MgSO&lt;sub&gt;4&lt;/sub&gt;</td><td>DAEJUNG</td><td>5514-4400</td><td></td></tr><tr><td>Plastic paper sleeve (clear)</td><td>Smead</td><td>#85753</td><td>Any clear plastic sheet with a bit of stiffness can be used as stage. For example, from Amazon US: https://www.amazon.com/Smead-Organized-Translucent-Project-85753/dp/B07HJTRCT7/ref=psdc_1069554_t3_B09J48GXQ&lt;br/&gt; 8</td></tr><tr><td>Potassium dihydrogen phosphate (KH&lt;sub&gt;2&lt;/sub&gt;PO&lt;sub&gt;4&lt;/sub&gt;)</td><td>JUNSEI</td><td>84185-0350</td><td></td></tr><tr><td>Power strip&amp;nbsp;</td><td></td><td></td><td>To accommodate 3 phones and one LED box, you need at least 4 outlets.</td></tr><tr><td>Smartphone</td><td>N/A</td><td>N/A</td><td>Minimum requirement: 12MP wide camera, 1080p HD video recording at 30fps</td></tr><tr><td>Sodium chloride(NaCl)</td><td>DAEJUNG</td><td>#7548-4100</td><td></td></tr><tr><td>Sodium phosphate dibasic anhydrous (Na&lt;sub&gt;2&lt;/sub&gt;HPO&lt;sub&gt;4&lt;/sub&gt;)</td><td>YAKURI</td><td>#31727</td><td></td></tr></tbody></table>

a smartphone-based imaging method for c. elegans lawn avoidance assay

When exposed to toxic or pathogenic bacteria, the nematode Caenorhabditis elegans displays a learned lawn avoidance behavior, in which the worms gradually leave their food source and prefer to remain outside the bacterial lawn. The assay is an easy way to test the worms' ability to sense external or internal cues to properly respond to harmful conditions. Though a simple assay, counting is time consuming, particularly with multiple samples, and assay durations that span overnight are inconvenient for researchers. An imaging system that can image many plates over a long period is useful but costly. Here, we describe a smartphone-based imaging method to record lawn avoidance in C. elegans. The method requires only a smartphone and a light emitting diode (LED) light box, to serve as a transmitted light source. Using free time-lapse camera applications, each phone can image up to six plates, with sufficient sharpness and contrast to manually count worms outside the lawn. The resulting movies are processed into 10 s audio video interleave (AVI) files for every hourly time point, then cropped to show each single plate to make them more amenable for counting. This method is a cost-effective way for those looking to examine avoidance defects and can potentially be extended to other C. elegans assays.

The first video produced by the script is 1 h from the start of the assay. The video for 0 h is not saved, as worms start the assay inside the lawn, so the occupancy rate is always 100%.
Wild-type N2 worms are compared against npr-1 mutants, whose lawn avoidance defect is well-established in the literature6,10 (Figure 3A-E). As can be seen in the wild type, worms ...

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Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay  

This article describes a simple, low-cost method of recording the lawn avoidance behavior of Caenorhabditis elegans, using readily available items such as a smartphone and a light emitting diode (LED) light box. We also provide a Python script to process the video file into a format more amenable for counting.

A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

When exposed to toxic or pathogenic bacteria, the nematode Caenorhabditis elegans displays a learned lawn avoidance behavior, in which the worms gradually ...

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Universidad de Cartagena UDEC

Research

JoVE Journal

Behavior

9.7K Views.  Yonsei University Wonju College of Medicine. This article describes a simple, low-cost method of recording the lawn avoidance behavior of Caenorhabditis elegans, using readily available items such as a smartphone and a light emitting diode (LED) light box. We also provide a Python script to process the video file into a format more amenable for counting. 

Video: Author Spotlight: A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay  

Single Wavelength Shadow Imaging of Caenorhabditis elegans Locomotion Including Force Estimates

This study demonstrates an inexpensive and straightforward technique that allows the measurement of physical properties such as position, velocity, acceleration and forces involved in the locomotory behavior of nematodes suspended in a column of water in response to single wavelengths of light. We demonstrate how to evaluate the locomotion of a microscopic organism using Single Wavelength Shadow Imaging (SWSI) using two different examples.
The first example is a systematic and statistically viable study of the average descent of C. elegans in a column of water. For this study, we used living and dead wildtype C. elegans. When we compared the velocity and direction of nematode active movement with the passive descent of dead worms within the gravitational field, this study showed no difference in descent-times. The average descent was 1.5 mm/sec &#177; 0.1 mm/sec for both the live and dead worms using 633 nm coherent light.
The second example is a case study of select individual C. elegans changing direction during the descent in a vertical water column. Acceleration and force are analyzed in this example. This case study demonstrates the scope of other physical properties that can be evaluated using SWSI while evaluating the behavior using single wavelengths in an environment that is not accessible with traditional microscopes. Using this analysis we estimated an individual nematode is capable of thrusting with a force in excess of 28 nN.
Our findings indicate that living nematodes exert 28 nN when turning, or moving against the gravitational field. The findings further suggest that nematodes passively descend in a column of water, but can actively resist the force of gravity primarily by turning direction.

Single Wavelength Shadow Imaging of Caenorhabditis elegans Locomotion Including Force Estimates

The technique presented here measures the path of freely swimming microscopic species using single wavelength exposure. C. elegans are used to demonstrate shadow imaging as an inexpensive alternative to costly microscopes. This technique can be adapted to accommodate various orientations, environments and species to measure direction, speed, acceleration and forces.

This study demonstrates an inexpensive and straightforward technique that allows the measurement of physical properties such as position, velocity, ...

Engineering

Simple Microfluidic Devices for in vivo Imaging of C. elegans, Drosophila and Zebrafish

Micro fabricated fluidic devices provide an accessible micro-environment for in vivo studies on small organisms. Simple fabrication processes are available for microfluidic devices using soft lithography techniques 1-3. Microfluidic devices have been used for sub-cellular imaging 4,5, in vivo laser microsurgery 2,6 and cellular imaging 4,7. In vivo imaging requires immobilization of organisms. This has been achieved using suction 5,8, tapered channels 6,7,9, deformable membranes 2-4,10, suction with additional cooling 5, anesthetic gas 11, temperature sensitive gels 12, cyanoacrylate glue 13 and anesthetics such as levamisole 14,15. Commonly used anesthetics influence synaptic transmission 16,17 and are known to have detrimental effects on sub-cellular neuronal transport 4. In this study we demonstrate a membrane based poly-dimethyl-siloxane (PDMS) device that allows anesthetic free immobilization of intact genetic model organisms such as Caenorhabditis elegans (C. elegans), Drosophila larvae and zebrafish larvae. These model organisms are suitable for in vivo studies in microfluidic devices because of their small diameters and optically transparent or translucent bodies. Body diameters range from ~10 &mu;m to ~800 &mu;m for early larval stages of C. elegans and zebrafish larvae and require microfluidic devices of different sizes to achieve complete immobilization for high resolution time-lapse imaging. These organisms are immobilized using pressure applied by compressed nitrogen gas through a liquid column and imaged using an inverted microscope. Animals released from the trap return to normal locomotion within 10 min.
We demonstrate four applications of time-lapse imaging in C. elegans namely, imaging mitochondrial transport in neurons, pre-synaptic vesicle transport in a transport-defective mutant, glutamate receptor transport and Q neuroblast cell division. Data obtained from such movies show that microfluidic immobilization is a useful and accurate means of acquiring in vivo data of cellular and sub-cellular events when compared to anesthetized animals (Figure 1J and 3C-F 4).
Device dimensions were altered to allow time-lapse imaging of different stages of C. elegans, first instar Drosophila larvae and zebrafish larvae. Transport of vesicles marked with synaptotagmin tagged with GFP (syt.eGFP) in sensory neurons shows directed motion of synaptic vesicle markers expressed in cholinergic sensory neurons in intact first instar Drosophila larvae. A similar device has been used to carry out time-lapse imaging of heartbeat in ~30 hr post fertilization (hpf) zebrafish larvae. These data show that the simple devices we have developed can be applied to a variety of model systems to study several cell biological and developmental phenomena in vivo.

Simple Microfluidic Devices for in vivo Imaging of C. elegans, Drosophila and Zebrafish

A simple microfluidic device has been developed to perform anesthetic free in vivo imaging of C. elegans, intact Drosophila larvae and zebrafish larvae. The device utilizes a deformable PDMS membrane to immobilize these model organisms in order to perform time lapse imaging of numerous processes such as heart beat, cell division and sub-cellular neuronal transport. We demonstrate the use of this device and show examples of different types of data collected from different model systems.

Micro fabricated fluidic devices provide an accessible micro-environment for in vivo studies on small organisms. Simple fabrication processes are ...

Bioengineering

Microfluidic-based Electrotaxis for On-demand Quantitative Analysis of Caenorhabditis elegans' Locomotion

The nematode Caenorhabditis elegans is a versatile model organism for biomedical research because of its conservation of disease-related genes and pathways as well as its ease of cultivation. Several C. elegans disease models have been reported, including neurodegenerative disorders such as Parkinson's disease (PD), which involves the degeneration of dopaminergic (DA) neurons 1. Both transgenes and neurotoxic chemicals have been used to induce DA neurodegeneration and consequent movement defects in worms, allowing for investigations into the basis of neurodegeneration and screens for neuroprotective genes and compounds 2,3.
Screens in lower eukaryotes like C. elegans provide an efficient and economical means to identify compounds and genes affecting neuronal signaling. Conventional screens are typically performed manually and scored by visual inspection; consequently, they are time-consuming and prone to human errors. Additionally, most focus on cellular level analysis while ignoring locomotion, which is an especially important parameter for movement disorders.
We have developed a novel microfluidic screening system (Figure 1) that controls and quantifies C. elegans' locomotion using electric field stimuli inside microchannels. We have shown that a Direct Current (DC) field can robustly induce on-demand locomotion towards the cathode ("electrotaxis") 4. Reversing the field's polarity causes the worm to quickly reverse its direction as well. We have also shown that defects in dopaminergic and other sensory neurons alter the swimming response 5. Therefore, abnormalities in neuronal signaling can be determined using locomotion as a read-out. The movement response can be accurately quantified using a range of parameters such as swimming speed, body bending frequency and reversal time.
Our work has revealed that the electrotactic response varies with age. Specifically, young adults respond to a lower range of electric fields and move faster compared to larvae 4. These findings led us to design a new microfluidic device to passively sort worms by age and phenotype 6.
We have also tested the response of worms to pulsed DC and Alternating Current (AC) electric fields. Pulsed DC fields of various duty cycles effectively generated electrotaxis in both C. elegans and its cousin C. briggsae 7. In another experiment, symmetrical AC fields with frequencies ranging from 1 Hz to 3 KHz immobilized worms inside the channel 8.
Implementation of the electric field in a microfluidic environment enables rapid and automated execution of the electrotaxis assay. This approach promises to facilitate high-throughput genetic and chemical screens for factors affecting neuronal function and viability.

Microfluidic-based Electrotaxis for On-demand Quantitative Analysis of Caenorhabditis elegans' Locomotion

A semi-automated micro-electro-fluidic method to induce on-demand locomotion in Caenorhabditis elegans is described. This method is based on the neurophysiologic phenomenon of worms responding to mild electric fields (&#x201C;electrotaxis&#x201D;) inside microfluidic channels. Microfluidic electrotaxis serves as a rapid, sensitive, low-cost, and scalable technique to screen for factors affecting neuronal health.

The nematode Caenorhabditis elegans is a versatile model organism for biomedical research because of its conservation of disease-related genes and ...

Automated Analysis of a Nematode Population-based Chemosensory Preference Assay

The nematode, Caenorhabditis elegans' compact nervous system of only 302 neurons underlies a diverse repertoire of behaviors. To facilitate the dissection of the neural circuits underlying these behaviors, the development of robust and reproducible behavioral assays is necessary. Previous C. elegans behavioral studies have used variations of a "drop test", a "chemotaxis assay", and a "retention assay" to investigate the response of C. elegans to soluble compounds. The method described in this article seeks to combine the complementary strengths of the three aforementioned assays. Briefly, a small circle in the middle of each assay plate is divided into four quadrants with the control and experimental solutions alternately placed. After the addition of the worms, the assay plates are loaded into a behavior chamber where microscope cameras record the worms' encounters with the treated regions. Automated video analysis is then performed and a preference index (PI) value for each video is generated. The video acquisition and automated analysis features of this method minimizes the experimenter's involvement and any associated errors. Furthermore, minute amounts of the experimental compound are used per assay and the behavior chamber's multi-camera setup increases experimental throughput. This method is particularly useful for conducting behavioral screens of genetic mutants and novel chemical compounds. However, this method is not appropriate for studying stimulus gradient navigation due to the close proximity of the control and experimental solution regions. It should also not be used when only a small population of worms is available. While suitable for assaying responses only to soluble compounds in its current form, this method can be easily modified to accommodate multimodal sensory interaction and optogenetic studies. This method can also be adapted to assay the chemosensory responses of other nematode species.

We present a behavior recording setup and protocol that enables automated analysis of the nematode, Caenorhabditis elegans' preference for soluble compounds in a population-based assay. This article describes the construction of a behavior chamber, the behavioral assay protocol, and video analysis software usage.

The nematode, Caenorhabditis elegans' compact nervous system of only 302 neurons underlies a diverse repertoire of behaviors. To facilitate the dissection ...

Automated Quantification of Synaptic Fluorescence in C. elegans

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall neural circuit function. Synapse strength critically depends on the abundance of neurotransmitter receptors clustered at synaptic sites on the postsynaptic membrane. Receptor levels are established developmentally, and can be altered by receptor trafficking between surface-localized, subsynaptic, and intracellular pools, representing important mechanisms of synaptic plasticity and neuromodulation. Rigorous methods to quantify synaptically-localized neurotransmitter receptor abundance are essential to study synaptic development and plasticity. Fluorescence microscopy is an optimal approach because it preserves spatial information, distinguishing synaptic from non-synaptic pools, and discriminating among receptor populations localized to different types of synapses. The genetic model organism Caenorhabditis elegans is particularly well suited for these studies due to the small size and relative simplicity of its nervous system, its transparency, and the availability of powerful genetic techniques, allowing examination of native synapses in intact animals.
Here we present a method for quantifying fluorescently-labeled synaptic neurotransmitter receptors in C. elegans. Its key feature is the automated identification and analysis of individual synapses in three dimensions in multi-plane confocal microscope output files, tabulating position, volume, fluorescence intensity, and total fluorescence for each synapse. This approach has two principal advantages over manual analysis of z-plane projections of confocal data. First, because every plane of the confocal data set is included, no data are lost through z-plane projection, typically based on pixel intensity averages or maxima. Second, identification of synapses is automated, but can be inspected by the experimenter as the data analysis proceeds, allowing fast and accurate extraction of data from large numbers of synapses. Hundreds to thousands of synapses per sample can easily be obtained, producing large data sets to maximize statistical power. Considerations for preparing C. elegans for analysis, and performing confocal imaging to minimize variability between animals within treatment groups are also discussed. Although developed to analyze C. elegans postsynaptic receptors, this method is generally useful for any type of synaptically-localized protein, or indeed, any fluorescence signal that is localized to discrete clusters, puncta, or organelles.
The procedure is performed in three steps: 1) preparation of samples, 2) confocal imaging, and 3) image analysis. Steps 1 and 2 are specific to C. elegans, while step 3 is generally applicable to any punctate fluorescence signal in confocal micrographs.

Automated Quantification of Synaptic Fluorescence in C. elegans

The abundance of neurotransmitter receptors clustered at synapses strongly influences synaptic strength. This method quantifies fluorescently-labeled neurotransmitter receptors in three dimensions with single-synapse resolution in C. elegans, allowing hundreds of synapses to be rapidly characterized within a single sample without distortions introduced by z-plane projection.

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall ...

Neuroscience

C. elegans Tracking and Behavioral Measurement

We have developed instrumentation, image processing, and data analysis techniques to quantify the locomotory behavior of C. elegans as it crawls on the surface of an agar plate. For the study of the genetic, biochemical, and neuronal basis of behavior, C. elegans is an ideal organism because it is genetically tractable, amenable to microscopy, and shows a number of complex behaviors, including taxis, learning, and social interaction1,2. Behavioral analysis based on tracking the movements of worms as they crawl on agar plates have been particularly useful in the study of sensory behavior3, locomotion4, and general mutational phenotyping5. Our system works by moving the camera and illumination system as the worms crawls on a stationary agar plate, which ensures no mechanical stimulus is transmitted to the worm. Our tracking system is easy to use and includes a semi-automatic calibration feature. A challenge of all video tracking systems is that it generates an enormous amount of data that is intrinsically high dimensional. Our image processing and data analysis programs deal with this challenge by reducing the worms shape into a set of independent components, which comprehensively reconstruct the worms behavior as a function of only 3-4 dimensions6,7. As an example of the process we show that the worm enters and exits its reversal state in a phase specific manner.

C. elegans Tracking and Behavioral Measurement

We have developed a video-rate tracking microscope system that can record and quantify C. elegans behavior at high resolution and high speeds. We have also developed computational methods to reduce the dimensionality of the worm images to a fundamental set of measurements that completely describe the shape of the worm.

We have developed instrumentation, image processing, and data analysis techniques to quantify the locomotory behavior of C. elegans as it crawls on the ...

Using an Adapted Microfluidic Olfactory Chip for the Imaging of Neuronal Activity in Response to Pheromones in Male C. Elegans Head Neurons

The use of calcium indicators has greatly enhanced our understanding of neural dynamics and regulation. The nematode Caenorhabditis elegans, with its completely mapped nervous system and transparent anatomy, presents an ideal model for understanding real-time neural dynamics using calcium indicators. In combination with microfluidic technologies and experimental designs, calcium-imaging studies using these indicators are performed in both free-moving and trapped animals. However, most previous studies utilizing trapping devices, such as the olfactory chip described in Chronis et al., have devices designed for use in the more common hermaphrodite, as the less common male is both morphologically and structurally dissimilar. An adapted olfactory chip was designed and fabricated for increased efficiency in male neuronal imaging with using young adult animals. A turn was incorporated into the worm loading port to rotate the animals and to allow for the separation of the individual neurons within a bilateral pair in 2D imaging. Worms are exposed to a controlled flow of odorant within the microfluidic device, as described in previous hermaphrodite studies. Calcium transients are then analyzed using the open-source software ImageJ. The procedure described herein should allow for an increased amount of male-based C. elegans calcium imaging studies, deepening our understanding of the mechanisms of sex-specific neuronal signaling.

Using an Adapted Microfluidic Olfactory Chip for the Imaging of Neuronal Activity in Response to Pheromones in Male C. Elegans Head Neurons

The use of an adapted &#34;olfactory chip&#34; for the efficient calcium imaging of C. elegans males is described here. Studies of male exposure to glycerol and a pheromone are also shown.

The use of calcium indicators has greatly enhanced our understanding of neural dynamics and regulation. The nematode Caenorhabditis elegans, with its ...

A Simple Microfluidic Chip for Long-Term Growth and Imaging of Caenorhabditis elegans

Caenorhabditis elegans (C. elegans) have proved to be a valuable model system for studying developmental and cell biological processes. Understanding these biological processes often requires long-term and repeated imaging of the same animal. Long recovery times associated with conventional immobilization methods done on agar pads have detrimental effects on animal health making it inappropriate to repeatedly image the same animal over long periods of time. This paper describes a microfluidic chip design, fabrication method, on-chip C. elegans culturing protocol, and three examples of long-term imaging to study developmental processes in individual animals. The chip, fabricated with polydimethylsiloxane and bonded on a cover glass, immobilizes animals on a glass substrate using an elastomeric membrane that is deflected using nitrogen gas. Complete immobilization of C. elegans enables robust time-lapse imaging of cellular and sub-cellular events in an anesthetic-free manner. A channel geometry with a large cross-section allows the animal to move freely within two partially sealed isolation membranes permitting growth in the channel with a continuous food supply. Using this simple chip, imaging of developmental phenomena such as neuronal process growth, vulval development, and dendritic arborization in the PVD sensory neurons, as the animal grows inside the channel, can be performed. The long-term growth and imaging chip operates with a single pressure line, no external valves, inexpensive fluidic consumables, and utilizes standard worm handling protocols that can easily be adapted by other laboratories using C. elegans.

A Simple Microfluidic Chip for Long-Term Growth and Imaging of Caenorhabditis elegans

The protocol describes a simple microfluidic chip design and microfabrication methodology used to grow C. elegans in presence of a continuous food supply for up to 36 h. The growth and imaging device also enables intermittent long-term high-resolution imaging of cellular and sub-cellular processes during development for several days.

Caenorhabditis elegans (C. elegans) have proved to be a valuable model system for studying developmental and cell biological processes. Understanding ...

C. elegans Chemotaxis Assay

Chemotaxis is a process in which cells or organisms move in response to a chemical stimulus. In nature, chemotaxis is important for organisms to sense and move toward food sources and move away from stimuli that may be toxic or harmful. Chemotaxis is also important at the cellular level. For example, chemotaxis is required for the movement of sperm toward an egg prior to fertilization. In the lab, chemotaxis is frequently examined in the nematode, C. elegans, which is known to migrate towards food sources in soil, but away from toxins such as heavy metals, substances with a low pH, and detergents. This video demonstrates how to perform a chemotaxis assay, which includes preparing the chemotaxis plates and the worms, running the assay, and analyzing the data. Then, we discuss examples of how chemotaxis assays can be used in C. elegans as a tool to understand learning and memory, olfactory adaptation, and neurological disease such as Alzheimer&quot;s disease. Chemotaxis experiments in C. elegans have near-limitless possibilities for learning more about the cellular and genetic mechanisms of many biological processes, and may lead to a greater understanding of human biology, development, and disease.

Chemotaxis Assay in Caenorhabditis elegans

Chemotaxis is a process in which cells or organisms move in response to a chemical stimulus. In nature, chemotaxis is important for organisms to sense and ...

Education

JoVE Science Education

Basic Biology

Biology I: yeast, Drosophila and C. elegans

Electrotaxis Assay: A Method to Observe Locomotion in C. elegans

Source: Tong, J,&#160;et al. <a href="https://jove.unicartagenaproxy.elogim.com/video/50226/microfluidic-based-electrotaxis-for-on-demand-quantitative-analysis">Microfluidic-based Electrotaxis for On-demand Quantitative Analysis of&#160;Caenorhabditis elegans&#39; Locomotion.</a>&#160;J. Vis. Exp.&#160;(2013).
Researchers can trigger on-demand movement in C. elegans by applying an electric field that worms sense and respond to.&#160; This video introduces electrotactic behavior and shows a sample protocol that is done in a microfluidic device.

Source: Tong, J,&#160;et al. Microfluidic-based Electrotaxis for On-demand Quantitative Analysis of&#160;Caenorhabditis elegans&#39; Locomotion.&#160;J. ...

A Smartphone-Based Imaging Method for C. elegans Lawn Avoidance Assay

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Chapters in this video

Single Wavelength Shadow Imaging of Caenorhabditis elegans Locomotion Including Force Estimates

Simple Microfluidic Devices for in vivo Imaging of C. elegans, Drosophila and Zebrafish

Microfluidic-based Electrotaxis for On-demand Quantitative Analysis of Caenorhabditis elegans' Locomotion

Automated Analysis of a Nematode Population-based Chemosensory Preference Assay

Automated Quantification of Synaptic Fluorescence in C. elegans

C. elegans Tracking and Behavioral Measurement

Using an Adapted Microfluidic Olfactory Chip for the Imaging of Neuronal Activity in Response to Pheromones in Male C. Elegans Head Neurons

A Simple Microfluidic Chip for Long-Term Growth and Imaging of Caenorhabditis elegans

C. elegans Chemotaxis Assay

Electrotaxis Assay: A Method to Observe Locomotion in C. elegans