We acknowledge the DFG (KI-1988/5-1 to JK, NeuroCure PhD fellowship by the NeuroCure Cluster of Excellence to MLP) for funding. We also acknowledge the Imaging Core Facility of the Leibniz Research Institute for Molecular Pharmacology Berlin (FMP) for providing the imaging set up. In addition, we would like to thank Diogo Feleciano who established the Dendra2 system in the lab and provided instructions.

1. Generation of&#160;&#160;C. elegans expressing neuronal Huntingtin-Dendra2 fusion protein
<ol>
	<li>Clone the gene encoding the POI in a nematode expression vector (i.e., pPD95_75, Addgene #1494), by traditional restriction enzyme digest10, Gibson assembly11, or any method of choice. Insert a promoter to drive expression in a desired tissue or at a desired developmental stage. Insert the Dendra2 fluorophore either N- or C-terminally in frame with the POI.</li>
	<li>Generate transgenic C. elegans expressing the fusion construct (e.g., via microinjection)12. 
	NOTE: The plasmid carrying the transgene will remain as an extrachromosomal array. Integration of the construct is not necessary but can be performed if desired13. In this protocol, C. elegans were microinjected with a plasmid carrying the fusion construct huntingtin exon 1-Dendra2 (HTT-D2) under the control of the pan-neuronal promoter Prgef-1. The C. elegans expression backbone was obtained from Kreis et al.14, the huntingtin exon 1 with either Q25 or Q97 was obtained from Juenemann et al.15, and Dendra2 was obtained from Hamer et al.16.</li>
</ol>
2. Age matching and maintenance of&#160;&#160;C. elegans
<ol>
	<li>Age match all nematodes by synchronizing either with alkaline hypochlorite solution treatment17 or via egg laying for 4 h at 20 &#176;C. For egg laying, place 10 gravid adults on a freshly seeded nematode growth media (NGM) plate and leave for 4 h before removing. The eggs laid in this timespan will give rise to synchronized nematodes.</li>
	<li>Keep experimental C. elegans on nematode growth media (NGM) plates seeded with the bacterial food source E. coli OP50, following standard nematode husbandry18.</li>
	<li>Grow nematodes at 20 &#176;C to the desired stage. For this protocol, the required ages are days 4 and 10. 
	NOTE: Young adults at day 4 can be identified by the presence of eggs in their gonads and their high mobility. Aged day 10 nematodes are post-fertile, and undergo tissue deterioration and locomotive decline19.</li>
	<li>For day 10 nematodes, passage daily after the L4 stage at day 3, once nematodes are fertile, to avoid a mixed population.</li>
</ol>
3. Preparation of microscopy slides for imaging
<ol>
	<li>Prepare the microscopy slides on the day of imaging. In a microwave, melt general grade agarose at a concentration of 3% (w/v) in ddH2O. Leave to cool slightly.</li>
	<li>Cut the tip of a 1 mL pipette tip and aspirate roughly 400 &#181;L of melted agarose. Gently place a few drops of agarose onto a clean glass slide and immediately place another slide on top, making sure that a thin pad of agarose is created between the two. Let dry before gently sliding or lifting the top slide off.</li>
	<li>Place the agarose pad slides in a humidified container to prevent them from drying out. These can be used within 2-3 h. 
	NOTE: Avoid formation of small bubbles in the agarose, as the nematodes can be trapped within.</li>
</ol>
4. Definition of confocal microscope parameters
NOTE: Before mounting the nematodes and data acquisition, define all settings on the confocal acquisition software. The settings can be adapted to the imaging hardware and software of choice.
<ol>
	<li>Open the confocal software and define the laser imaging settings. Set the light path for excitation/emission for green Dendra2 at 486-553 nm and for red Dendra2 at 580-740 nm. Adjust the power and gain of both channels/lasers according to the intensity of the fluorophore. Do not change the digital gain or offset and set the pinhole as fully open.</li>
	<li>Define the acquisition setup: select a sequential channel mode and switch track every frame. Set the scan mode as frame, and the frame size as 1,024 x 1,024, with a line step of 1. Set the averaging to 2, and average by mean method and mode of unidirectional line. Set the bit depth to 8 bits.</li>
	<li>Define the multidimensional acquisitions settings for the conversion of Dendra2. For conversion and bleaching use the 405 nm diode laser set at 60% energy power. If available, activate the safe bleaching GaAsP to protect the detectors.</li>
	<li>Select a time series of two cycles, with a 0.0 ms interval in between, and normal start and stop. Start bleaching after scan 1 of 2 and repeat for 30 iterations. Stop bleaching when the intensity drops to 50%.</li>
	<li>Define the speed of acquisition/pixel dwell as fast (e.g., maximum = 12) for conversion, and medium speed (e.g., medium = 5) for capturing a snap image. 
	NOTE: The bleaching parameters defined here are guidelines. For other Dendra2 tagged POIs the laser power settings and bleaching iterations and values must be established empirically.</li>
</ol>
5. Mounting of C. elegans onto microscopy slides
NOTE: If possible, place a mounting stereomicroscope close to the confocal microscope setup and mount the nematodes just before imaging.
<ol>
	<li>On the glass cover slide on the opposite side of the agarose pad, draw a window with four squares with a permanent marker and number them.</li>
	<li>Pipette 15 &#181;L of levamisole in the middle of the agarose pad. The concentration of levamisole will vary according to the nematode&#39;s age: When imaging day 4 nematodes use 2 mM levamisole; when imaging day 10 nematodes use 0.5 mM levamisole.</li>
	<li>Transfer four nematodes into the liquid using a wire pick. With the help of an eyelash pick, gently move each individual nematode to a window square. Swivel the eyelash so that any trace of E. coli OP50 is diluted and its fluorescent background does not interfere with signal acquisition.</li>
	<li>Wait for the nematodes to almost stop moving and gently place a cover slip on top of the liquid to immobilize the nematodes in the layer of levamisole between the agarose pad and the cover slip.</li>
	<li>Place the inverted slide on the confocal stage to image the nematodes.</li>
</ol>
6. Conversion of green Dendra2: Data acquisition at time zero
NOTE: The pulse-chase experiments start by irreversibly converting the Dendra2 fusion protein from a green emitting fluorophore to a red one.
<ol>
	<li>Using the microscope&#39;s eyepiece, locate the first nematode with a 20x objective under green fluorescence. Focus on the head or tail and switch to confocal mode.</li>
	<li>Start live laser scanning with the 488 nm blue laser to visualize the green Dendra2 in the EGFP green channel (ex/em = 486-553 nm). Select a single neuron and bring it into focus. Zoom in 3x and increase the target of the laser beam4. 
	NOTE: Select one neuron per nematode. Each neuron will constitute one sample or data point.</li>
	<li>Find the maximum projection plane and, according to the brightness of the fluorophore, increase or decrease the gain or laser power to obtain a saturated but not overexposed image identifiable by the color range indicator. Once this is defined, stop the scanning. 
	NOTE: Do not irradiate the sample for too long or with too much power, as excitation with visible blue 488 nm light can also convert Dendra2, albeit slowly and less efficiently4.</li>
	<li>In the software, open the tab to select the regions of interest (ROIs) and draw a first ROI around the selected neuron. Define a larger second region of interest encompassing the nematode&#39;s head and including the first ROI.</li>
	<li>In the bleaching settings, select for the first ROI to be acquired, bleached, and analyzed. Select for the second ROI to be acquired and analyzed but not bleached.</li>
	<li>Set the speed of scanning to maximum (i.e., fast pixel dwell) and start the experiment to convert the selected Dendra2 neurons. 
	NOTE: Once the experiment is done the acquired picture will result in two images: one before and one after conversion. For the green channel, the first image should have a higher green signal that diminishes in the second image due to the conversion of the green Dendra2. For the red channel, the first image should be negative and show no signal, with a red signal appearing in the after conversion image. If the green signal does not diminish, the conversion did not occur, and the settings, such as the 405 laser power or the number of iterations, should be modified. If there is a red signal in the first image, then the 488 nm laser power used was too high and a portion of the green Dendra2 was already converted to red. In this case, a new neuron/nematode should be selected.</li>
	<li>Immediately after conversion, start live scanning with the green 561 nm laser to visualize Dendra2 in the red channel (ex/em = 580-740 nm). Find the focus and respective maximum projection of the converted neuron using the range color indicator to avoid overexposure.</li>
	<li>Quickly set the scan rate to a lower pixel dwell speed (e.g., 5x) and acquire a snapshot image of both channels at a higher resolution. This image is defined as timepoint zero (T0) after conversion. 
	NOTE: The speed of acquisition for the converted image can be varied. However, once chosen, this speed needs to stay constant throughout the data collection.</li>
	<li>Save the scan with an identifiable name and/or number, followed by the time zero label (T0). 
	NOTE: It is advisable to also save the image of the conversion experiment (step 6.6) to illustrate the lack of red signal before conversion and its appearance afterwards.</li>
</ol>
7. Imaging of converted red Dendra2 for data acquisition at a selected second time point
<ol>
	<li>To track Dendra2 degradation over time, define a second timepoint to reimage the same nematode/neuron. Select the second timepoint experimentally to address any relevant biological question. For the protocol described here, Dendra2 is imaged both at 2 h (T2) and 24 h (T24) post conversion.
	<ol>
		<li>At the selected timepoint, find the same nematode/neuron with the use of the eyepiece and red fluorescence.</li>
		<li>Open the T0 image of the respective nematode/neuron and reload/reuse the image settings. Ensure that the acquisition settings of the snapshot are precisely the same when acquiring the T0, T2, and T24 h images.</li>
		<li>Scanning live in the red channel, bring the converted red neuron into focus. Because the red Dendra2 degrades over time the range indicator will show a less intense maximum projection. Do not change any acquisition parameters and obtain a snapshot at the same speed (e.g., 5x) as the first image.</li>
	</ol>
	</li>
	<li>To track the degradation of Dendra2 after 4 h or longer, rescue the nematodes after conversion.
	<ol>
		<li>Remove the slide from the microscope immediately after converting and imaging the four nematodes. Gently remove the coverslip and with the use of a wire pick, lift each nematode from the agarose pad.</li>
		<li>Place each nematode individually on an appropriately labelled and identifiable NGM plate.</li>
		<li>For the second time point, mount the nematode again onto a fresh agarose pad and proceed with the imaging of the converted red Dendra2 following the instructions in section 6.</li>
	</ol>
	</li>
</ol>
8. Image analysis of converted Dendra2
NOTE: Analysis of the degradation of Dendra2 is performed with Fiji/ImageJ software20.
<ol>
	<li>Open Fiji and drag and drop the .lsm file into the Fiji bar. Open the T0 image taken just after conversion and the image of the same nematode taken at the selected time point after conversion (T2 or T24 h). 
	NOTE: To track the degradation of the protein of interest fused to Dendra2 only the red channel needs to be analyzed.</li>
	<li>Establish the measurement parameters from the menu: Analyze | Set Measurements. Select the Area and Integrated Density functions.</li>
	<li>Select the image obtained with the red channel. Select the Polygon Selection Tool from the Fiji bar.</li>
	<li>Identify the converted neuron on the T0 image and draw an ROI around it using the selection tool.
	<ol>
		<li>To properly identify the contours of the neuron, highlight the intensity thresholds by selecting from the bar Image | Adjust | Threshold. Drag the bar cursor to delineate the threshold and track around this area with the polygon tool. To generate an accurate ROI, it is also possible to use the contour of the selected neuron from the green channel.</li>
	</ol>
	</li>
	<li>Once the selection has been made in the red channel window, press Analyze | Measure. A pop-up window named Results will appear and include the ROI values for Area, IntDen, and RawIntDen.</li>
	<li>Perform the same process of selection and measurement for the image of the second time point (T2 or T24 h).</li>
	<li>Copy the obtained values into a spreadsheet software, taking care to appropriately record the values at T0 after conversion, and at T2 or T24 h after conversion.</li>
</ol>
9. Calculating the ratio of Dendra2 degradation
<ol>
	<li>To calculate the ratio of degradation, first assign a value of 1 (or 100%) to time the degradation from time point zero (i.e., just after conversion, when all of the red Dendra2 converted is still present). This results from dividing the value of IntRawDen of T0 by itself.</li>
	<li>To calculate the reduction of the red Dendra2 intensity signal over time, and the degradation, divide the value of RawIntDen of the second time point (e.g., T2 or T24 h) by the value of the RawIntDen of T0. The resulting number should be less than 1. These values can also be expressed as percentages, defining T0 as 100%.</li>
	<li>Repeat section 7 for each nematode converted. For a graphical representation of the degradation of Dendra2, chart a scatter plot or bar graph with the percentage or ratio values of fluorescence decrease obtained in the y axis. Apply any desired statistical analysis and illustrate it on the graph.</li>
</ol>

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The authors have nothing to disclose.

To comprehend a protein&#39;s function it is important to understand its synthesis, location, and degradation. With the development of novel, stable, and bright FPs, visualizing and monitoring POIs has become easier and more efficient. Genetically expressed fusion PAFPs such as Dendra2 are uniquely positioned to study the stability of a POI. Upon exposure to purple-blue light, Dendra2 breaks at a precise location within a triad of conserved amino acids. The fluorophore undergoes a small structural change, resulting in a ...

The proteome of a living organism is constantly renewing itself. Proteins are continuously degraded and synthesized according to the physiological demand of a cell. Some proteins are quickly eliminated, whereas others are longer lived. Monitoring protein dynamics is a simpler, more accurate, and less invasive task when using genetically encoded fluorescent proteins (FPs). FPs form autocatalytically and can be fused to any protein of interest (POI), but do not require enzymes to fold or need cofactors save for oxygen1. A newer generation of FPs has recently been engineered to switch color upon irradiation with a light pulse of determined wavelength. These photoactivatable FPs (PAFPs) allow for labeling and tracking of POIs, or the organelles or cells they reside in, and to examine their quantitative and/or qualitative parameters2. FPs make it possible to track any POI&#39;s movement, directionality, rate of locomotion, coefficient of diffusion, mobile versus immobile fractions, the time it resides in one cellular compartment, as well as its turnover rate. For specific organelles, locomotion and transport, or fission and fusion events can be determined. For a particular cell type, a cell&#39;s position, rate of division, volume, and shape can be established. Crucially, the use of PAFPs allows tracking without continuous visualization and without interference from any newly synthetized probe. Studies both in cells and in whole organisms have successfully employed PAFPs to address biological questions in vivo, such as the development of cancer and metastasis, assembly or disassembly of the cytoskeleton, and RNA-DNA/protein interactions3. In this manuscript, light microscopy and PAFPs are used to uncover the turnover rates of the aggregation-prone protein huntingtin (HTT) in vivo in a C. elegans model of neurodegenerative disease.
The protocol described here quantifies the stability and degradation of the fusion protein huntingtin-Dendra2 (HTT-D2). Dendra2 is a second-generation monomeric PAFP4 that irreversibly switches its emission/excitation spectra from green to red in response to either UV or visible blue light, with an increase in its intensity of up to 4,000-fold5,6. Huntingtin is the protein responsible for causing Huntington&#39;s disease (HD), a fatal hereditary neurodegenerative disorder. Huntingtin exon-1 contains a stretch of glutamines (CAG, Q). When the protein is expressed with over 39Q, it misfolds into a mutant, toxic, and pathogenic protein. Mutant HTT is prone to aggregation and leads to neuronal cell death and degeneration, either as&#160;short oligomeric species or as larger highly structured amyloids7.
The nematode is a model system for studying aging and neurodegeneration thanks to its ease of manipulation, isogenic nature, short lifespan, and its optical transparency8. To study the stability of HTT in vivo, a fusion construct was expressed in the nervous system of C. elegans. A HTT-D2 transgene containing either a physiological stretch of 25Qs (HTTQ25-D2) or a pathological stretch of 97Qs (HTTQ97-D2) is overexpressed pan-neuronally throughout the nematode&#39;s lifetime9. By subjecting live C. elegans to a brief and focused point of light, a single neuron is photoswitched and the converted HTT-D2 is tracked over time. To establish the amount of HTT-D2 degraded, the difference between the red signal of the freshly converted HTT-D2 is compared to the remaining red signal of HTT-D2 after a determined period of time. Therefore, it becomes possible to investigate how huntingtin is degraded when found in its expanded and toxic form compared to its physiological form; how anterior or posterior neurons respond differently to the presence of Q97 versus Q25, especially over prolonged time periods; and how the collapse of the proteostasis network (PN) during aging contribute to the differences in degradation rates. These results only describe a small set of observations on the turnover of HTT-D2. However, many more biological questions relevant to both the field of protein aggregation and proteostasis can be addressed with this in vivo application.

<table><tbody><tr><td>Agar-Agar Kobe I</td><td>Carl Roth GmbH + Co. KG</td><td>5210.2</td><td>NGM component</td></tr><tr><td>Agarose, Universal Grade</td><td>Bio &amp;amp; Sell GmbH</td><td>BS20.46.500</td><td>Mounting slide component</td></tr><tr><td>BD Bacto Peptone</td><td>BD-Bionsciences</td><td>211677</td><td>NGM component</td></tr><tr><td>Deckgl&amp;auml;ser-18x18mm</td><td>Carl Roth GmbH + Co. KG</td><td>0657.2</td><td>Cover slips</td></tr><tr><td>EC Plan-Neufluar 20x/0.50 Ph2 M27</td><td>Carl Zeiss AG</td><td></td><td>Objective</td></tr><tr><td>Fiji/ImageJ 1.52p</td><td>NIH</td><td></td><td>Analysis Software</td></tr><tr><td>Levamisole Hydrochloride</td><td>AppliChem GmbH</td><td>A4341</td><td>Anesthetic</td></tr><tr><td>LSM710-ConfoCor3</td><td>Carl Zeiss AG</td><td></td><td>Laser Scanning Confocal Micoscope</td></tr><tr><td>Mounting stereomicroscope</td><td>Leica Camera AG</td><td></td><td>Mounting microscope</td></tr><tr><td>neuronal-HTTQ25-Dendra2</td><td>this paper</td><td></td><td>&lt;em&gt;C. elegans&lt;/em&gt; strain</td></tr><tr><td>neuronal-HTTQ97-Dendra2</td><td>this paper</td><td></td><td>&lt;em&gt;C. elegans&lt;/em&gt; strain</td></tr><tr><td>OP50 Escherichia coli</td><td>CAENORHABDITIS GENETICS CENTER (CGC)</td><td>OP50</td><td>Nematode food source</td></tr><tr><td>Sodium Chloride</td><td>Carl Roth GmbH + Co. KG</td><td>3957.2</td><td>NGM component</td></tr><tr><td>Standard-Objekttr&amp;auml;ger</td><td>Carl Roth GmbH + Co. KG</td><td>0656.1</td><td>Glass slides</td></tr><tr><td>ZEN2010 B SP1</td><td>Carl Zeiss AG</td><td></td><td>Confocal acquisition software</td></tr></tbody></table>

in vivo quantification of protein turnover in aging c. elegans using photoconvertible dendra2

Proteins are synthesized and degraded constantly within a cell to maintain homeostasis. Being able to monitor the degradation of a protein of interest is key to understanding not only its life cycle, but also to uncover imbalances in the proteostasis network. This method shows how to track the degradation of the disease-causing protein huntingtin. Two versions of huntingtin fused to Dendra2 are expressed in the C. elegans nervous system: a physiological version or one with an expanded and pathogenic stretch of glutamines. Dendra2 is a photoconvertible fluorescent protein; upon a short ultraviolet (UV) irradiation pulse, Dendra2 switches its excitation/emission spectra from green to red. Similar to a pulse-chase experiment, the turnover of the converted red-Dendra2 can be monitored and quantified, regardless of the interference from newly synthesized green-Dendra2. Using confocal-based microscopy and due to the optical transparency of C. elegans, it is possible to monitor and quantify the degradation of huntingtin-Dendra2 in a living, aging organism. Neuronal huntingtin-Dendra2 is partially degraded soon after conversion and cleared further over time. The systems controlling degradation are deficient in the presence of mutant huntingtin and are further impaired with aging. Neuronal subtypes within the same nervous system exhibit different turnover capacities for huntingtin-Dendra2. Overall, monitoring any protein of interest fused to Dendra2 can provide important information not only on its degradation and the players of the proteostasis network involved, but also on its location, trafficking, and transport.

Two nematode strains expressing the huntingtin exon-1 protein fragment in frame with the photoconvertible protein Dendra2 were obtained via microinjection and the plasmids were kept as an extrachromosomal array. The fusion construct was expressed in the whole C. elegans nervous system from development throughout aging. Here, HTT-D2 contained either the physiological 25 polyglutamine stretch (HTTQ25-D2, Figure 1A) or a fully penetrant...

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In Vivo Quantification of Protein Turnover in Aging C. Elegans using Photoconvertible Dendra2

Presented here is a protocol to monitor degradation of the protein huntingtin fused to the photoconvertible fluorophore Dendra2.

In Vivo Quantification of Protein Turnover in Aging C. Elegans using Photoconvertible Dendra2

Proteins are synthesized and degraded constantly within a cell to maintain homeostasis. Being able to monitor the degradation of a protein of interest is ...

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Research

JoVE Journal

Biology

6.2K Views.  Leibniz Research Institute for Molecular Pharmacology im Forschungsverbund. Dit protocol maakt het bijhouden en kwantificeren van de afbraak van een eiwit van belang in levende en vergrijzende C.elegans mogelijk. Deze in vivo en niet-invasieve techniek vereist slechts weinig microscopie opgezet om op betrouwbare wijze om te zetten Dendra2 in een heldere en stabiele fluorofofoër. De methode is aanpasbaar aan zoogdiersystemen, evenals zebravissen.Om te studeren, zet in de omzet binnen het proteostatis netwerk, alsmede vervoer en handel. Zorg ervoor dat u geen o...

Video: In Vivo Quantification of Protein Turnover in Aging C. Elegans using Photoconvertible Dendra2

Measuring Protein Stability in Living Zebrafish Embryos Using Fluorescence Decay After Photoconversion (FDAP)

Protein stability influences many aspects of biology, and measuring the clearance kinetics of proteins can provide important insights into biological systems. In FDAP experiments, the clearance of proteins within living organisms can be measured. A protein of interest is tagged with a photoconvertible fluorescent protein, expressed in vivo and photoconverted, and the decrease in the photoconverted signal over time is monitored. The data is then fitted with an appropriate clearance model to determine the protein half-life. Importantly, the clearance kinetics of protein populations in different compartments of the organism can be examined separately by applying compartmental masks. This approach has been used to determine the intra- and extracellular half-lives of secreted signaling proteins during zebrafish development. Here, we describe a protocol for FDAP experiments in zebrafish embryos. It should be possible to use FDAP to determine the clearance kinetics of any taggable protein in any optically accessible organism.

Measuring Protein Stability in Living Zebrafish Embryos Using Fluorescence Decay After Photoconversion FDAP

Protein levels in cells and tissues are often tightly regulated by the balance of protein production and clearance. Using Fluorescence Decay After Photoconversion (FDAP), the clearance kinetics of proteins can be experimentally measured in vivo.

Protein stability influences many aspects of biology, and measuring the clearance kinetics of proteins can provide important insights into biological ...

Developmental Biology

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Sensory systems allow animals to detect, process, and respond to their environment. Food abundance is an environmental cue that has profound effects on animal physiology and behavior. Recently, we showed that modulation of longevity in the nematode Caenorhabditis elegans by food abundance is more complex than previously recognized. The responsiveness of the lifespan to changes in food level is determined by specific genes that act by controlling information processing within a neural circuit. Our framework combines genetic analysis, high-throughput quantitative imaging and information theory. Here, we describe how these techniques can be used to characterize any gene that has a physiological relevance to broad-range dietary restriction. Specifically, this workflow is designed to reveal how a gene of interest regulates lifespan under broad-range dietary restriction; then to establish how the expression of the gene varies with food level; and finally, to provide an unbiased quantification of the amount of information conveyed by gene expression about food abundance in the environment. When several genes are examined simultaneously under the context of a neural circuit, this workflow can uncover the coding strategy employed by the circuit.

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Here, we present a framework to relate broad-range dietary restriction to gene expression and lifespan. We describe protocols for broad-range dietary restriction and for quantitative imaging of gene expression under this paradigm. We further outline computational analyses to reveal underlying information processing features of the genetic circuits involved in food-sensing.

Sensory systems allow animals to detect, process, and respond to their environment. Food abundance is an environmental cue that has profound effects on ...

Genetics

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

The Replica Set method is an approach to quantitatively measure lifespan or survival of Caenorhabditis elegans nematodes in a high-throughput manner, thus allowing a single investigator to screen more treatments or conditions over the same amount of time without loss of data quality. The method requires common equipment found in most laboratories working with C. elegans and is thus simple to adopt. The approach centers on assaying independent samples of a population at each observation point, rather than a single sample over time as with traditional longitudinal methods. Scoring entails adding liquid to the wells of a multi-well plate, which stimulates C. elegans to move and facilitates quantifying changes in healthspan. Other major benefits of the Replica Set method include reduced exposure of agar surfaces to airborne contaminants (e.g. mold or fungus), minimal handling of animals, and robustness to sporadic mis-scoring (such as calling an animal as dead when it is still alive). To appropriately analyze and visualize the data from a Replica Set style experiment, a custom software tool was also developed. Current capabilities of the software include plotting of survival curves for both Replica Set and traditional (Kaplan-Meier) experiments, as well as statistical analysis for Replica Set. The protocols provided here describe the traditional experimental approach and the Replica Set method, as well as an overview of the corresponding data analysis.

The Replica Set Method: A High-throughput Approach to Quantitatively Measure Caenorhabditis elegans Lifespan

Here we describe the Replica Set method, an approach to quantitatively measure C. elegans lifespan/survival and healthspan in a high-throughput and robust manner, thus allowing screening of many conditions without sacrificing data quality. This protocol details the strategy and provides a software tool for analysis of Replica Set data.

The Replica Set method is an approach to quantitatively measure lifespan or survival of Caenorhabditis elegans nematodes in a high-throughput manner, thus ...

Monitoring Protein Aggregation Kinetics In Vivo using Automated Inclusion Counting in Caenorhabditis elegans

Protein aggregation into insoluble inclusions is a hallmark of a variety of human diseases, many of which are age-related. The nematode Caenorhabditis elegans is a well-established model organism that has been widely used in the field to study protein aggregation and toxicity. Its optical transparency enables the direct visualization of protein aggregation by fluorescence microscopy. Moreover, the fast reproductive cycle and short lifespan make the nematode a suitable model to screen for genes and molecules that modulate this process.
However, the quantification of aggregate load in living animals is poorly standardized, typically performed by manual inclusion counting under a fluorescence dissection microscope at a single time point. This approach can result in high variability between observers and limits the understanding of the aggregation process. In contrast, amyloid-like protein aggregation in vitro is routinely monitored by thioflavin T fluorescence in a highly quantitative and time-resolved fashion.
Here, an analogous method is presented for the unbiased analysis of aggregation kinetics in living C. elegans, using a high-throughput confocal microscope combined with custom-made image analysis and data fitting. The applicability of this method is demonstrated by monitoring inclusion formation of a fluorescently labeled polyglutamine (polyQ) protein in the body wall muscle cells. The image analysis workflow allows the determination of the numbers of inclusions at different timepoints, which are fitted to a mathematical model based on independent nucleation events in individual muscle cells. The method described here may prove useful to assess the effects of proteostasis factors and potential therapeutics for protein aggregation diseases in a living animal in a robust and quantitative manner.

Monitoring Protein Aggregation Kinetics In Vivo using Automated Inclusion Counting in Caenorhabditis elegans

Here, a method is presented for the analysis of protein aggregation kinetics in the nematode Caenorhabditis elegans. Animals from an age-synchronized population are imaged at different time points, followed by semiautomated inclusion counting in CellProfiler and fitting to a mathematical model in AmyloFit.

Protein aggregation into insoluble inclusions is a hallmark of a variety of human diseases, many of which are age-related. The nematode Caenorhabditis ...

Biochemistry

Methods to Assess Subcellular Compartments of Muscle in C. elegans

Muscle is a dynamic tissue that responds to changes in nutrition, exercise, and disease state. The loss of muscle mass and function with disease and age are significant public health burdens. We currently understand little about the genetic regulation of muscle health with disease or age. The nematode C. elegans is an established model for understanding the genomic regulation of biological processes of interest. This worm&#8217;s body wall muscles display a large degree of homology with the muscles of higher metazoan species. Since C. elegans is a transparent organism, the localization of GFP to mitochondria and sarcomeres allows visualization of these structures in vivo. Similarly, feeding animals cationic dyes, which accumulate based on the existence of a mitochondrial membrane potential, allows the assessment of mitochondrial function in vivo. These methods, as well as assessment of muscle protein homeostasis, are combined with assessment of whole animal muscle function, in the form of movement assays, to allow correlation of sub-cellular defects with functional measures of muscle performance. Thus, C. elegans provides a powerful platform with which to assess the impact of mutations, gene knockdown, and/or chemical compounds upon muscle structure and function. Lastly, as GFP, cationic dyes, and movement assays are assessed non-invasively, prospective studies of muscle structure and function can be conducted across the whole life course and this at present cannot be easily investigated in vivo in any other organism.

Methods to Assess Subcellular Compartments of Muscle in C. elegans

Skeletal muscle is essential for locomotion and is the bodies&#8217; main protein store. Muscle health measurements within C. elegans are described. Prospective changes to muscle structure and function are assessed using localized GFP and cationic dyes.

Muscle is a dynamic tissue that responds to changes in nutrition, exercise, and disease state. The loss of muscle mass and function with disease and age ...

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 age-associated disorders are characterized by the appearance of protein aggregates with fibrillary structure in the brains of these patients. Exactly why normally soluble proteins undergo an aggregation process remains poorly understood. The discovery that protein aggregation is not limited to disease processes and instead part of the normal aging process enables the study of the molecular and cellular mechanisms that regulate protein aggregation, without using ectopically expressed human disease-associated proteins. Here we describe methodologies to examine inherent protein aggregation in Caenorhabditis elegans through complementary approaches. First, we examine how to grow large numbers of age-synchronized C. elegans to obtain aged animals and we present the biochemical procedures to isolate highly-insoluble-large aggregates. In combination with a targeted genetic knockdown, it is possible to dissect the role of a gene of interest in promoting or preventing age-dependent protein aggregation by using either a comprehensive analysis with quantitative mass spectrometry or a candidate-based analysis with antibodies. These findings are then confirmed by in vivo analysis with transgenic animals expressing fluorescent-tagged aggregation-prone proteins. These methods should help clarify why certain proteins are prone to aggregate with age and ultimately how to keep these proteins fully functional.

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

The goal of the method presented here is to explore protein aggregation during normal aging in the model organism C. elegans. The protocol represents a powerful tool to study the highly insoluble large aggregates that form with age and to determine how changes in proteostasis impact protein aggregation.

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

Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans

The ability to maintain proper function and folding of the proteome (protein homeostasis) declines during normal aging, facilitating the onset of a growing number of age-associated diseases. For instance, proteins with polyglutamine expansions are prone to aggregation, as exemplified with the huntingtin protein and concomitant onset of Huntington&#8217;s disease. The age-associated deterioration of the proteome has been widely studied through the use of transgenic Caenorhabditis elegans expressing polyQ repeats fused to a yellow fluorescent protein (YFP). This polyQ::YFP transgenic animal model facilitates the direct quantification of the age-associated decline of the proteome through imaging the progressive formation of fluorescent foci (i.e., protein aggregates) and subsequent onset of locomotion defects that develop as a result of the collapse of the proteome. Further, the expression of the polyQ::YFP transgene can be driven by tissue-specific promoters, allowing the assessment of proteostasis across tissues in the context of an intact multicellular organism. This model is highly amenable to genetic analysis, thus providing an approach to quantify aging that is complementary to lifespan assays. We describe how to accurately measure polyQ::YFP foci formation within either neurons or body wall muscle during aging, and the subsequent onset of behavioral defects. Next, we highlight how these approaches can be adapted for higher throughput, and potential future applications using other emerging strategies for C. elegans genetic analysis.

Quantifying Tissue-Specific Proteostatic Decline in Caenorhabditis elegans

Proteostatic decline is a hallmark of aging, facilitating the onset of neurodegenerative diseases. We outline a protocol to quantifiably measure proteostasis in two different Caenorhabditis elegans tissues through heterologous expression of polyglutamine repeats fused to a fluorescent reporter. This model allows rapid in vivo genetic analysis of proteostasis.

The ability to maintain proper function and folding of the proteome (protein homeostasis) declines during normal aging, facilitating the onset of a ...

Assessment of de novo Protein Synthesis Rates in Caenorhabditis elegans

Maintaining a healthy proteome is essential for cell and organismal homeostasis. Perturbation of the balance between protein translational control and degradation instigates a multitude of age-related diseases. Decline of proteostasis quality control mechanisms is a hallmark of ageing. Biochemical methods to detect de novo protein synthesis are still limited, have several disadvantages and cannot be performed in live cells or animals. Caenorhabditis elegans, being transparent and easily genetically modified, is an excellent model to monitor protein synthesis rates by using imaging techniques. Here, we introduce and describe a method to measure de novo protein synthesis in vivo utilizing fluorescence recovery after photobleaching (FRAP). Transgenic animals expressing fluorescent proteins in specific cells or tissues are irradiated by a powerful light source resulting in fluorescence photobleaching. In turn, assessment of fluorescence recovery signifies new protein synthesis in cells and/or tissues of interest. Hence, the combination of transgenic nematodes, genetic and/or pharmacological interventions together with live imaging of protein synthesis rates can shed light on mechanisms mediating age-dependent proteostasis collapse.

Assessment of de novo Protein Synthesis Rates in Caenorhabditis elegans

Here, we introduce and describe a nonradioactive and noninvasive method to assess de novo protein synthesis in vivo, utilizing the nematode Caenorhabditis elegans and fluorescence recovery after photobleaching (FRAP). This method can be combined with genetic and/or pharmacological screens to identify novel modulators of protein synthesis.

Maintaining a healthy proteome is essential for cell and organismal homeostasis. Perturbation of the balance between protein translational control and ...

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble proteins over 40% of the time results in an extension of the lifespan in C. elegans, suggesting that many of these proteins are key determinants of the aging process. Isolation and quantitative identification of these insoluble proteins are crucial to understand key biological processes that occur during aging. Here, we present a modified and improved protocol that details how to extract and isolate the SDS-insoluble proteins (insolublome) from C. elegans more efficiently to streamline mass spectrometric workflows via a novel label-free quantitative proteomics analysis. This improved protocol utilizes a highly efficient sonicator for worm lysis that greatly increases efficiency for protein extraction and allows us to use significantly less starting material (approximately 3,000 worms) than in previous protocols (typically using at least 40,000 worms). Subsequent quantitative proteomic analysis of the insolublome was performed using data-dependent acquisition (DDA) for protein discovery and identification and data-independent acquisition (DIA) for comprehensive and more accurate protein quantification. Bioinformatic analysis of quantified proteins provides potential candidates that can be easily followed up with other molecular methods in C. elegans. With this workflow, we routinely identify more than 1000 proteins and quantify more than 500 proteins. This new protocol enables efficient compound screening with C. elegans. Here, we validated and applied this improved protocol to wild-type C. elegans N2-Bristol strain and confirmed that aged day-10 N2 worms showed greater accumulation of the insolublome than day-2 young worms.

Quantification of Insoluble Protein Aggregation in Caenorhabditis elegans during Aging with a Novel Data-Independent Acquisition Workflow

This novel workflow efficiently extracts and isolates SDS-insoluble proteins (insolublome) from Caenorhabditis elegans with minimal starting material for quantitative differential proteomic analysis. The protocol uses a comprehensive data-independent acquisition mass spectrometry analysis to quantify the insolublome and bioinformatic analysis to gain biological insights into aging mechanisms and pathologies.

We and others have shown that the aging process results in a proteome-wide accumulation of insoluble proteins. Knocking down genes encoding the insoluble ...

Evaluating Metabolism and Aging Pattern in Caenorhabditis elegans

Using Low-Cost Dyes to Visualize Glycogen Accumulation and Gut Integrity in Caenorhabditis elegans

Caenorhabditis elegans (C. elegans) is a transparent, non-parasitic nematode with a simple biology, which makes it a great tool for biological sciences teaching through the staining of the cells or their molecular content. Lugol dye (iodine-potassium iodide solution) has been widely used in biochemistry to stain glycogen stores. In this context, it is possible to observe differences between fed and starved animals, besides the effects of different conditions, such as different diets and oxygen levels. Erioglaucine is a blue dye that indicates the loss of the intestinal barrier. When the intestinal barrier is intact, the blue dye stains inside the lumen; however, when this integrity is disrupted, the dye leaks into the body cavity. Using a stereomicroscope or a microscope, teachers can demonstrate physiological and biochemical alterations, or they can instigate students to ask a scientific question and hypothesize and test their hypothesis using these assays. The present protocol describes two staining techniques in C. elegans that can be easily carried out by students.

Author Spotlight: Exploring Metabolic and Aging Processes in C. elegans Using Low-Cost, High-Impact Assays

Teaching biological sciences can be made more stimulating for students through the use of experimentation. This manuscript presents two different yet complementary protocols that can be utilized in the classroom to encourage students to formulate and test hypotheses related to high-calorie diets, starvation, and aging.

Caenorhabditis elegans (C. elegans) is a transparent, non-parasitic nematode with a simple biology, which makes it a great tool for biological sciences ...

In Vivo Quantification of Protein Turnover in Aging C. Elegans using Photoconvertible Dendra2

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