We describe protocols for using the wide field-of-view nematode tracking platform (WF-NTP), which enables high-throughput phenotypic characterization of large populations of Caenorhabditis elegans. These protocols can be used to characterize subtle behavioral changes in mutant strains or in response to pharmacological treatment in a highly scalable fashion.
Caenorhabditis elegans is a well-established animal model in biomedical research, widely employed in functional genomics and ageing studies. To assess the health and fitness of the animals under study, one typically relies on motility readouts, such as the measurement of the number of body bends or the speed of movement. These measurements usually involve manual counting, making it challenging to obtain good statistical significance, as time and labor constraints often limit the number of animals in each experiment to 25 or less. Since high statistical power is necessary to obtain reproducible results and limit false positive and negative results when weak phenotypic effects are investigated, efforts have recently been made to develop automated protocols focused on increasing the sensitivity of motility detection and multi-parametric behavioral profiling. In order to extend the limit of detection to the level needed to capture the small phenotypic changes that are often crucial in genetic studies and drug discovery, we describe here a technological development that enables the study of up to 5,000 individual animals simultaneously, increasing the statistical power of the measurements by about 1,000-fold compared to manual assays and about 100-fold compared to other available automated methods.
Approximately half a century ago, Sydney Brenner introduced Caenorhabditis elegans (C. elegans) as a model system to study development and neurobiology, as this small (1 mm in length), transparent nematode worm is easy to manipulate genetically and to maintain in the laboratory1. Today, C. elegans is used to study a wide variety of biological processes including apoptosis, cell signaling, the nature of the cell cycle, gene regulation, metabolism, and ageing2. Furthermore, the cellular and tissue complexity, protein expression patterns and the conservation of disease pathways between C. elegans and higher organisms (80% of worm genes have a human orthologue), linked with the simplicity and cost-effectiveness of cultivation, make it an effective in vivo model organism amenable to high-throughput genetic3,4,5,6,7,8,9,10,11,12,13 and drug14,15,16 screenings. For all these reasons, C. elegans has been employed for the characterization of normal and disease-related molecular pathways; in the field of neurodegeneration, for example, it has enabled the exploration of the effects of ageing on protein aggregation3,4,7,15,17,18, and the characterization of promoters and inhibitors of protein aggregation3,4,5,6,7,14,18.
The overall fitness of the worms, which is an important behavioral parameter to be defined in this type of study, can be measured manually in a variety of ways, such as by counting the number of body bends per minute (BPM)4,6,19, or by measuring the speed of movement20,21,22, as well as by measuring the average lifespan and rates of paralysis. Although manual measurements of body bends and speed of movement have led to many important insights into a variety of molecular pathways and mechanisms3,4,14,19,20,23, manual assays remain currently low-throughput, highly labor-intensive, and time-consuming whilst being prone to errors and to human biases. These issues present considerable challenges in the collection of data with sufficient statistical power to distinguish subtle behavioral changes. This limitation is particularly relevant for drug screening as treatments with potential drug molecules often lead to small phenotypic changes24, therefore requiring the study of large numbers of animals in order to acquire reproducible results. To illustrate this point, recent studies have shown that a high power of detection (POD) is necessary to define with confidence any significant changes in behavior and to limit false positive results25. This has resulted in a strong motivation in the C. elegans community to replace manual counting with reproducible, automated, time- and cost-effective measurements. To meet this demand, several laboratories have recently developed methods for high-sensitivity measurements and accurate worm tracking of larger number of worms22,26,27,28,29,30,31,32,33.
In order to expand further the process of automation to the large cohorts of animals needed for statistically significant measurements, we have recently developed a wide field-of-view nematode tracking platform (WF-NTP)15,34,35,36, which enables the simultaneous investigation of multiple phenotypic readouts on very large worm populations, a key factor in statistically relevant phenotypical detection25. Not only can the WF-NTP currently monitor up to 5,000 animals in parallel, but the phenotypic readouts also include multiple parameters, including the rate and amplitude of body bends, the speed of movement, the fraction of the population that is paralyzed, and the size of the animals. It is therefore readily possible to screen thousands of worms in parallel and to combine the different readouts into a behavioral map to create a multidimensional fingerprint36. The associated open-source software is written in Python, which is also required to operate it and is completely customizable. A graphical user interface (GUI) is also provided to enable users to adopt this technology.
Here, we present a series of protocols that illustrate some of the potential applications of the WF-NTP. In particular, we discuss the administration of compounds, ranging from small molecules to protein therapeutics, and describe how to screen their effects directly over large populations of worms, thus effectively removing the need to sample small sub-populations. The use of the WF-NTP for such a purpose has already brought significant advantages in procedures aimed to design drug discovery programs of Alzheimer's disease (AD)15,34,35 and Parkinson's disease (PD)18 using in vivo data for the assessment of therapeutic candidates35,37.
1. Preparation of Materials for C. elegans Protocols
2. Preparation of C. elegans for Use with the WF-NTP
3. General WF-NTP Protocol
4. Optimization for Discrete Dose Studies
5. Analyzing the Video Data
The ease of operating, multiparametric analysis, and high throughput of the illustrated WF-NTP protocol (Figures 1 and 2) makes it possible to determine very small changes in worm behavior in a very accurate manner. The imaging platform is based on custom-made opto-mechanics, and it can be assembled using a 6 MP monochrome camera combined with 16 mm focal length high-resolution lens for 1'' sensor, illuminated with a 8'' by 8'' white backlight (see Table of Materials and also reference36 for additional details). The associated WF-NTP software is written in Python and was developed to run on Windows platforms. It runs on a custom assembled computer with 3.00 GHz octa-core processor and 64 GB of random-access memory (RAM). The software was also designed to parallelize the work and video analysis based on the RAM and CPU of the computer; i.e., a machine with a lower calculation power will result in less videos run in parallel. The setup we are currently using is optimized to run up to ca. 16 videos in parallel and can complete an analysis of ca. 100 videos overnight. Moreover, the high level of detail of customization provided in the GUI of the WF-NTP allows great control of the quality of the imaging analysis. The GUI can be used to directly upload large datasets in parallel or individual videos; specific frames can also be selected for detailed sub-analysis, together with a pixel conversion factor, which can be used to estimate behavioral metrics. One of the two different tracking algorithms (keep dead and Z-transform) can be chosen depending on whether or not the user would like to consider paralyzed animals in the analysis. The thresholding parameter can be tuned accordingly with the video and experimental quality. The opening and closing parameters allow the user to remove the noise and further implement the thresholding functionality. The skeletonizing algorithm offers an alternative method of analysis. The object size cut-offs (filtering) provide an additional filter for background noise and the worm-like parameter allows the user to consider worms only objects with an ellipsoidal shape, hence distinguishing from other objects that may have the same pixel size of the worms. After these thresholding operations, all the resulting labelled regions can be identified as individual worms and the positions of those regions are then stored for each frame for subsequent analysis and tracking. The eccentricity of each tracked worm is used to estimate the worm metrics such as the extent of worm bending (BPM) as a function of time. The users are also allowed to select the number of frames used to keep a worm in the memory of the software following collisions, and the number of pixels that a worm can move between frames can also be tuned to distinguish the animals from the noise. The minimum track length option allows the user to discard worms that have been tracked for only a few frames. Other key parameters, such as bends and velocity, allow the user to select the degree of bending necessary to be counted as a body bend and the number of frames considered to be needed to estimate the speed of the animals. Cut-off parameters can be further tuned for the inclusion of paralyzed animals. The output is automatically shown in the result files. These values are considered as upper limits for the evaluation of the fraction of paralyzed animals. The user can also select one or more regions of interest. This feature is particularly useful to analyze subpopulations of the worms and the output is sorted automatically in the results files. The output option allows the user to select the output folder and the number of tracking frames that will be produced for it. Various tool sets can also be used for further data analysis, such as the plot path tool that shows individual worm tracks and the fingerprinting tool that allows the user to create fingerprint maps.
This methodology enables new approaches to be adopted, not only for biological studies of C. elegans but also for pharmacological and medical research purposes, such as high-throughput screening of genetic modifications and drug treatments. We have illustrated this potential by describing the characterization of the phenotypes for large population studies (N > 1000) of various worm models of neurodegenerative disease (frontotemporal dementia (FTD)39, Parkinson's disease (PD)7, Alzheimer's disease (AD)16,40, and amyotrophic lateral sclerosis (ALS)19 (Figure 3a), and characterizing the effects of potential therapeutic molecules using worm models of PD18 and AD15,12 (Figure 3b). Two small molecules, squalamine18 and bexarotene15, were administered at concentrations up to 25 µM to PD (Figure 3b) and 10 µM to AD38 (Figure 3b) worms, respectively. Both compounds showed clear dose-dependent effects over the range of concentrations tested. We have shown that this high accuracy of the measurements is achieved by increasing the number of worms that can be analyzed compared to traditional methods (Figure 3c). We illustrated the importance of the sample size (Figure 3c) in molecular screening as well as in characterization of mutant strains. The increase in temperature from 20 °C leads to approximately half of the AD worms becoming paralyzed after 3 days of adulthood. Worm populations were screened under different conditions, e.g., when worms over-expressing the 42-residue form of the amyloid-β peptide (Aβ1-42) (AD worms) were exposed to subtle temperature variations (Figure 3c, left panel), when Aβ1-42 was expressed in all the neurons (Figure 3c, central panel), or when AD worms were exposed to bexarotene (Figure 3c, right panel). Worms were also analyzed from small ROIs randomly selected from the full field of view of the videos acquired with the WF-NTP (N < 50, yellow bars) highlighting the comparison of the motility of these worms with the average motility of the whole worm population (N < 1,000). In all the panels, the difference measured on the whole worm population appears to be statistically significant with p ≤ 0.0001 (****).
The WF-NTP protocol described here also allows the simultaneous recording of multiple parameters (Figure 1b) to support, in an optimal manner, both internal validation and the development of a comprehensive fingerprint of a wide range of conditions relative to a control sample, allowing for meaningful comparisons across multiple studies. This multi-parametric approach includes the simultaneous analysis of multiple behavioral features, including bending frequency, speed, paralysis rate, size, bend amplitude, and bend displacement36. This allows thousands of animals to be monitored in great detail and at a very high sensitivity and statistical significance and provides opportunities for large populations studies. This tracking procedure also has the advantage of allowing paralysis studies to be performed in parallel with other behavioral measurements, a key feature in molecular screening studies.
The results that have been achieved so far in AD15,34,35 and PD18 drug discovery demonstrate the importance of wide field-of-view data acquisition to greatly increase the numbers of animals that can be monitored in a single experiment, significantly decreasing the experimental errors and greatly improving the statistical validity of the studies. Based on these results, we anticipate that the WF-NTP protocol, which we made readily available for the community36, will significantly extend the use of C. elegans.
Figure 1: WF-NTP analysis steps and example of a fingerprint. (a) 1. Original video. 2. Background image. 3. Background subtracted image. 4-6. Thresholding steps. 7-9. Single labelling of worms.(b) Multiple phenotypes are reported with a fingerprint for wild-type worms and worm models of PD and AD. Please click here to view a larger version of this figure.
Figure 2: Graphical user interface (GUI) of the WF-NTP. Specific videos and selected frames can be selected in the GUI for analysis, and a pixel conversion factor can be inserted, after which the analysis is carried out with one of the two given tracking algorithms. It is possible to select the degree of bending necessary to count as a body bend as well as the number of frames needed to estimate the speed of the animals. Body bends and speed thresholds can determine the paralyzed worm statistics. Please click here to view a larger version of this figure.
Figure 3: Examples of applications enabled by the WF-NTP method. (a) Application of WF-NTP in large population studies (N > 1,000) of BPM measurements for C. elegans models of a range of neurodegenerative diseases including FTD, PD, AD, and ALS. (b) Application of WF-NTP in drug discovery. (c) Importance of the population studies in temperature sensitivity, drug efficacy, and mutant strain characterization. Phenotypes of subpopulations N < 50 (yellow bars) are compared with those of the whole worm population (N < 1,000). The error bars indicate the standard error of the mean (SEM). Please click here to view a larger version of this figure.
Because of the rapid expansion of techniques within the field of optical sciences, it is now possible to address the requirement for automated methods in C. elegans studies in substantially new ways. As a result, a number of digital tracking platforms20,41,42,43,44,45,46 have been designed and made available over the last few years in order to replace manual counting of parameters such as speed of movement, bending frequency, paralysis rate, as well as more complex forms of behaviors such as omega turns, and lifespan measurements. Most recent automated platforms have greatly improved the reproducibility and sensitivity of C. elegans studies41 and provided high quality data on small cohorts or even individual animals. We decided to extend the automation of the analysis of worm behavior to make it also possible to evaluate the phenotypes of cohorts of thousands of animals in parallel. The main advantage of the approach of studying worm cohorts is that it allows for accounting for the high intrinsic variability of worm behavior24 and for the fact that drug treatment studies often lead to subtle phenotypic variations, which are difficult to detect with sufficient statistical significance when using a small group of animals. A high power of detection (POD) is indeed necessary to detect with confidence any significant variation in behavior and to limit false positive results25.
Here, we have described a series of protocols based on a recently reported automated screening method for C. elegans, the wide field-of-view nematode tracking platform (WF-NTP)36. The protocol described here is divided into 5 parts. Parts 1 and 2 describe the preparation of large worm populations. Critical steps are the sterility of the working conditions and preparation of reagents and plates necessary to run the experiments. We note that, due to the increased throughput provided by this protocol compared to other screening methodologies36, it also requires increased quantities of reagents; this factor needs to be considered carefully in the experimental design. We also note that the bleaching step is critical and needs to be tested in advance as a large number of eggs and healthy larvae are necessary to run these experiments. Part 3 of this protocol details how to deliver drugs in solid media and screen worm populations. We note that this part of the protocol is strongly dependent on the number of drugs and drug concentrations to be tested by the user in parallel. The complete automation of the screening procedure and rapid data acquisition shift the limiting step from behavioral observation to reagent preparation and growth and synchronization of large worm populations. The key steps during the behavioral screening are the timings of the recording and any worm handling steps (e.g., the transfer of worms from the NGM plates to the tracking platform). The protocol described here is an example designed to screen the worms for up to 9 days during the adult lifespan; however, this protocol can be easily adapted to screen as many time points as the user desires, e.g., 18 consecutive days36. Part 4 then illustrates the application of the protocol to deliver protein molecules (e.g., antibodies and molecular chaperones) into C. elegans, and shows how the protocol illustrated in Parts 1-3 can be easily customized, depending on the desired application. We demonstrate how this procedure can be extended not only to the delivery of drug-like molecules but also for the administration of molecular chaperones or antibodies37. The first four steps (parts) are carried out under sterile conditions, unless noted otherwise. All liquid components should be autoclaved prior to use and the incubation steps should be performed at 70% relative humidity. In Part 5, we describe how to use the software package provided in combination with the tracking stage. This software has been custom designed for the analysis of WF-NTP data related to the behavior of large worm populations. We suggest that the user follows the guidelines provided in Part 5 for the data analysis; however, these parameters are dependent on the specific features of the recorded videos (i.e., fps, field of view, video resolution, number of acquired frames). The example function provided in the GUI has been designed to facilitate the evaluation of the correct parameters prior to the analysis.
These series of protocols make it possible to analyze the phenotypes of large populations of C. elegans (currently up to 5,000 individual worms in parallel) effectively, reducing artefacts due to the intrinsic variability of the behavior of the animals, in agreement with preliminary studies on the power of detection necessary to achieve statistical significance for studies of C. elegans25. The platform uses a system of high-resolution cameras, capable of recording images of large numbers of animals at a high speed, while simultaneously recording multiple large cohorts. The high performance and high throughput of the WF-NTP protocol makes it possible to determine very small changes in worm behavior in a very accurate manner. Therefore, this methodology enables new approaches to be considered not only for the study of the biology of C. elegans, but additionally for pharmacological and medical research, such as the high-throughput screening of genetic modifications and drug treatments. This procedure also has the advantage of allowing paralysis studies to be performed in parallel with other behavioral measurements, a key feature in molecular screening studies.
The results that have been achieved so far in the drug discovery programs of AD15,34,35 and PD18 demonstrate the importance of wide field-of-view data acquisition in substantially increasing the numbers of animals that can be monitored in a single experiment, thereby significantly decreasing the experimental errors and greatly improving the statistical validity of studies. While the current approach described in this protocol has focused on addressing challenges in the field of drug discovery, we hope that the methodology will be widely adopted in the community, and that its application will be extended to complex genetic and behavioral studies and expand the number of phenotypes that are currently detectable.
This work was supported by the Centre for Misfolding Diseases (CMD). FAA is supported by a Senior Research Fellowship award from the Alzheimer's Society, UK (Grant Number 317, AS-SF-16-003). The C. elegans strains were obtained from the Caenorhabditis elegans Genetic Centre (CGC).
Name | Company | Catalog Number | Comments |
Consumable reagents | |||
monobasic potassium phosphate | Sigma Aldrich | P0662 | |
dibasic sodium phosphate | Sigma Aldrich | S3264 | |
sodium chloride | Sigma Aldrich | 13422 | |
magnesium sulphate | Sigma Aldrich | M7506 | |
Agar | Sigma Aldrich | A1296 | |
Difco casein digest | Scientific Laboratory Supplies | 211610 | |
calcium chloride dihydrate | Sigma Aldrich | C3881 | |
cholesterol | Acros | 110190250 | |
absolute ethanol | Vwr | 20821.33 | |
5-Fluoro-2'-deoxyuridine 98% | Alfa Aesar | L16497.ME | |
LB medium capsules | MP biomedicals | 3002-031 | |
13% sodium hypochlorite | Acros Organics | AC219255000 | |
Sodium hydroxide | Fisher Chemical | S/4880/53 | |
Name | Company | Catalog Number | Comments |
Strains | |||
E coli strain OP50 | Supplied by CGC | Op50 | E coli strain |
C. elegans strain wild type | Supplied by CGC | N2 | C. elegans strain |
C. elegans strain AD | Supplied by CGC | GMC101 | C. elegans strain |
C. elegans strain PD | Supplied by CGC | NL5901 | C. elegans strain |
C. elegans strain ALS | Supplied by CGC | AM725 | C. elegans strain |
C. elegans strain Tau | Supplied by CGC | BR5485 | C. elegans strain |
Name | Company | Catalog Number | Comments |
Equipment | |||
Tactrol 2 Autoclave | Priorclave | ||
9 cm sterile petri dishes. | Fisher Scientific | 11309283 | |
2 L erlenmeyer flasks | Scientific Laboratory Supplies | FLA4036 | |
Nalgene 1 L Centrifuge pots | Fisher Scientific | 3120-1000 | |
RC5C plus floor mounted centrifuge | Sorvall | 9900884 | |
15 mL centrifuge tubes | Fisher Scientific | 05-539-12 | |
Heraeus Multifuge X3R | Thermofisher scientific | 75004515 | |
Inoculating Spreaders | Fisher Scientific | 11821741 | |
M4 multipette | Eppendorf | 4982000012 | |
P1000 pipette | Eppendorf Research Plus | ||
P200 pipette | Eppendorf Research Plus | 3123000055 | |
P10 pipette | Eppendorf Research Plus | 3123000020 | |
1000 μL low retention tips | Sarstedt | ||
300 μL low retention tips | Sarstedt | 70.765.105 | |
10 μL low retention tips | Sarstedt | 70.1130.105 | |
pipeteboy 2 | VWR | 612-0927 | |
50 mL serological pipette | Appleton Woods | CC117 | |
25 mL serological pipette | Appleton Woods | CC216 | |
10 mL serological pipette | Appleton Woods | CC214 | |
glass pipette 270 mm | Fisherbrand | FB50255 | Camera for videos recording |
pulsin | Polyplus Transfection | 501-04 | Transduction reagent |
Multitron Standard shaking incubator | Infors HT | INFO28573 | |
air duster | Office Depot | 1511631 | |
Name | Company | Catalog Number | Comments |
WF-NTP Tracker Components and Image Capture Software | |||
8'' by 8'' Backlight | Edmond Optics | 88-508 | Tracker component |
16 mm FL high resolution lens for 1'' sensor | Edmond Optics | 86-571 | Tracker component |
6 Mpx camera | Edmond Optics | 33540 | Tracker component |
FlyCapture Software | PointGrey | SDK v2.12 | Image capture software |
WF-NTP Software | Cambridge Enterprise | v1.0 | Image analysis software |
Office Package | Microsoft | Office 365 | Statistical analysis software |
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