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 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.
The accumulation of misfolded proteins into insoluble deposits occurs in a wide range of diseases. Well-known examples are the aggregation of amyloid-β and tau in Alzheimer's disease, α-synuclein in Parkinson's disease, and huntingtin with expanded polyQ in Huntington's disease1,2. The misfolding of these polypeptides into amyloid fibrils is associated with toxicity and cell death by mechanisms that are still largely unclear. Elucidating the mechanisms of amyloid formation will be crucial to developing effective therapies, which are currently unavailable.
Detailed investigations of amyloid formation have been performed in vitro based on thioflavin T fluorescence measurements, leading to a mechanistic understanding of the aggregation process and the effect of inhibitory molecules3,4,5. However, it is not clear whether the same aggregation mechanisms hold true in the complex environment of living cells and organisms. The nematode worm Caenorhabditis elegans is a suitable model organism to study protein aggregation in vivo. It has a relatively simple anatomy but consists of multiple tissues, including muscle, intestine, and a nervous system. It is genetically well-characterized, and tools for genetic modification are readily available. Furthermore, it has a short generation time of ~3 days and a total lifespan of 2-3 weeks. As such, protein aggregation can be examined across the lifespan of the animal on an experimentally convenient timescale. Finally, the nematode is optically transparent, enabling the tracking of the aggregation of fluorescently labeled proteins in live animals.
These features of C. elegans have been previously exploited to investigate the aggregation of polyQ proteins as a model for Huntington's and other polyQ expansion diseases. Above the pathogenic threshold of 35-40 glutamine residues, the polyQ proteins labeled with yellow fluorescent protein (YFP) can be observed to form insoluble inclusions in the muscle tissue6,7, neurons8, and the intestine9,10. These features have been widely used to screen for genes11,12,13 and small-molecule modifiers14 of protein aggregation and toxicity.
C. elegans has the potential to play an important role in bridging the gap between in vitro studies of protein aggregation and more complex disease models such as mice15. C. elegans is amenable to drug screening16 but can also be exploited to obtain a fundamental understanding of the molecular mechanisms of protein aggregation in vivo, as demonstrated recently17. However, for both applications, it is of prime importance to extract a quantitative and reproducible measure of protein aggregation. Here, this is achieved with the use of a high-throughput confocal microscope combined with a dedicated image analysis pipeline (Figure 1).
1. Growth of an age-synchronized population of C. elegans
2. Sample preparation of C. elegans in a multiwell plate
NOTE: As the imaging procedure requires anesthetics that will eventually kill the animals, the same animals cannot be reused for subsequent time points. Instead, different animals from the same age-synchronized batch are imaged on different days. Even though most strains will have few inclusions at day 1, it is recommended to include this time point as a baseline.
3. Image acquisition on the high-throughput confocal microscope
NOTE: This experiment can also be set up on a regular spinning disk confocal microscope with a multiwell plate holder. A camera with a large field-of-view is beneficial to limit the number of tiles needed to be imaged to span the entire well. See the Table of Materials for details about the microscope and software used in this protocol.
4. Stitching tiled images in ImageJ
NOTE: This step is only required when using an objective larger than 4x, for which the image of each well is acquired as multiple tiles. In this analysis workflow, stitching of the tiles is performed using the free software FIJI/ImageJ19 (Figure 2). Depending on the instrument used in step 3, it may also be possible to perform stitching directly in the accompanying software.
5. Automated inclusion counting using CellProfiler22
6. Global fitting of inclusion count data using AmyloFit5
NOTE: This step can only be performed when data for multiple protein concentrations are available. For Q40-YFP, a set of four strains with different levels of overexpression in the body wall muscle cells has been created previously17. In other cases, novel strains should be generated using plasmid microinjection and genomic integration24.
The method described here (Figure 1) was used to analyze the aggregation kinetics of a construct comprising 40 glutamines fused to YFP (Q40-YFP). The protein is expressed under the control of the unc-54 promoter, driving expression in the body wall muscle cells. As these are relatively large and easy to visualize, the use of a 10x objective is sufficient to resolve the inclusions formed by Q40-YFP in this tissue. Four strains (lines A-D) were previously developed expressing the protein to different extents to assess the concentration-dependence of polyQ aggregation in vivo17.
Age-synchronized populations of lines A-D were generated by a 2 h egg-lay, followed by daily transfer once the offspring reached adulthood. From day 1 to day 10 of adulthood, 20 animals from each of the four strains were imaged in a 384-well plate, using a high-throughput confocal microscope. The images of the wells were acquired as 6 tiles, which were stitched together using a plugin in ImageJ21 (Figure 2). The stitched images were subsequently analyzed using a custom-made CellProfiler22 pipeline (Figure 3) to quantify the average inclusion number per animal for each strain and time point.
The data were then fitted to a mathematical model in AmyloFit5 (Figure 4). The model is based on the assumption that each of the 95 body wall muscle cells independently acquires one inclusion by a rate-limiting nucleation event, followed by fast aggregate growth17. The fit yielded a nucleation rate constant of 9.9 × 105 molecules M-2.1 d-1 cell-1 and a reaction order of 2.1, corresponding to a nucleation rate of 0.38 molecules d-1 cell-1 at an intracellular protein concentration of 1 mM. Two independent biological replicates led to closely corresponding values for the nucleation rate and reaction order, which are in agreement with a previous study using a similar protocol17 (Table 1).
Figure 1: Schematic overview of the method. (A) Age-synchronized C. elegans populations are generated by a timed egg-lay. (B) Animals from the same population are imaged in a 384-well plate at different time points. (C) The tiles are stitched together to form images of the entire wells, which are analyzed in CellProfiler to quantify the inclusion numbers per animal. (D) The data are fitted to a mathematical model using AmyloFit. Please click here to view a larger version of this figure.
Figure 2: Screenshots of the stitching procedure in ImageJ using the plugin Grid/Collection stitching21. Please click here to view a larger version of this figure.
Figure 3: Schematic of the CellProfiler pipeline to quantify inclusions numbers. (A–C) The brightfield image (A) is used to identify the worms (B, close-up in C). (D–G) The fluorescence image (D, close-up in E) is used to identify the inclusions (F). The worms and inclusions are related to provide the number of inclusions for each worm in the well (G). The images shown are of Q40 line A animals at day 3 of adulthood. Please click here to view a larger version of this figure.
Figure 4: Fitting the data to a mathematical model in AmyloFit. (A) Data are uploaded to AmyloFit. (B) A custom equation is entered to model inclusion formation, assuming independent nucleation events in each cell. (C) Fitting of the aggregation kinetics for C. elegans lines A-D expressing different levels of Q40-YFP. The data are representative of two independent biological replicates. Please click here to view a larger version of this figure.
Dataset 1 | Dataset 2 | Sinnige et al.17 | |
n | 2.1 | 1.9 | 1.6 |
Kcell (molecules M-n d-1 cell-1) | 9.9 x 105 | 1.4 x 105 | 3.1 x 104 |
Nucleation rate at 1 mM (molecules d-1 cell-1) | 0.38 | 0.21 | 0.35 |
Table 1: Values of the nucleation rate and reaction order of Q40-YFP aggregation. Data for two independent biological replicates of the protocol and comparison with previously published data17.
The method presented herein facilitates an unbiased and quantitative analysis of protein aggregation kinetics in the model organism C. elegans. It depends on four key elements (Figure 1): 1) maintaining an age-synchronized population of nematodes; 2) fluorescence microscopy in multiwell plates; 3) automated inclusion counting in CellProfiler; 4) data fitting in AmyloFit. Compared to manual counting of inclusions in freely moving animals or from saved images26, quantification in CellProfiler is both faster and more unbiased. The other key advancement of the protocol is the acquisition of kinetic data, rather than single timepoints, which provides quantitative insights into the aggregation mechanism upon fitting the data to a mathematical model.
The four elements of the protocol can be used as independent modules that can be modified depending on the application. Age-synchronized populations can also be maintained using 5-fluoro-2′-deoxyuridine (FUDR) to sterilize the animals. This compound affects lifespan and proteostasis24,25 and is highly carcinogenic to the experimenter; however, it precludes manual transfer of the worms, which can be labor-intensive when large numbers are handled. Other alternatives are the use of sterile mutants29 or filtration devices to separate offspring30.
The fluorescence microscopy step can also be adjusted, for example, using higher magnifications to monitor protein aggregation in neurons. Widefield microscopy may be sufficient to monitor polyQ aggregation in muscle cells when the relative difference between conditions is more important than the absolute numbers of inclusions. The CellProfiler pipeline can still be used in these cases, although the settings to recognize worms and inclusions will need to be adjusted by the user. The throughput of the technique is currently limited by the need for manual picking of the animals into the 384-well plate. This can potentially be remedied by the use of microfluidic devices16. Sodium azide is a relatively harsh anesthetic, which could be replaced by physical immobilization with hydrogels or beads28,29.
The analysis in AmyloFit presented here is based on an aggregation mechanism consisting of independent nucleation events in individual cells. In cases where this model does not fit, the user should consider an alternative such as the cooperative aggregation model developed previously17. A limitation of this approach is that strains expressing the protein of interest at different concentrations need to be available, although these can be generated using routine C. elegans methods24.
Altogether, this protocol provides the means to obtain high-quality data for protein aggregation kinetics in an in vivo model system, allowing for detailed analysis of aggregation mechanisms17. Although the method was demonstrated for polyQ aggregation in the C. elegans muscle tissue, future applications of the protocol may include other proteins and tissues and the effects of proteostasis factors and small molecules.
The authors have nothing to disclose.
We thank the Morimoto lab for C. elegans strains and Esmeralda Bosman for assistance on the high-throughput confocal microscope. This work was funded by a start-up grant from Utrecht University to T.S.
384-well plate | Greiner | 781091 | Black with flat clear bottom |
AmyloFit | Knowles lab | v2.0 | Access at www.amylofit.ch.cam.ac.uk |
C. elegans Q40 line A | Morimoto lab | AM1228 | Genotype rmIs404[unc-54p::Q40::YFP] |
C. elegans Q40 line B | Morimoto lab | AM1229 | Genotype rmIs404[unc-54p::Q40::YFP] |
C. elegans Q40 line C | Morimoto lab | AM1230 | Genotype rmIs404[unc-54p::Q40::YFP] |
C. elegans Q40 line D | Morimoto lab | AM1231 | Genotype rmIs404[unc-54p::Q40::YFP] |
CellProfiler | Broad Institute | 4.1.3 | Downloaded from https://cellprofiler.org |
E. coli OP50 | Caenorhabditis Genetics Center (CGC) | OP50 | |
FIJI | Open-source | (Fiji Is Just) ImageJ v2.1/1.5.3j | Downloaded from https://imagej.net/software/fiji/ |
High-throughput confocal microscope | Yokogawa | CellVoyager CV8000 | |
M9 buffer | Home-made | 3 g/L KH2PO4, 6 g/L Na2HPO4, 0.5 g/L NaCl, 1 mM MgSO4 | |
NGM plates | Home-made | 17 g/L agar, 2.5 g/L bacto-peptone, 3 g/L NaCl, 25 mM KPO4 buffer pH 6.0, 1 mM MgSO4, 1 mM CaCl2, 5 mg/L cholesterol | |
Pasteur pipette | WU Mainz | 250 | To make worm pick, 150 mm length |
Platinum iridium wire | Alfa Aesar | 39383 | To make worm pick, 0.25 mm diameter |
Sodium azide | Sigma-Aldrich | S2002 | |
Stereomicroscope | Leica | S9 |