A quantitative method has been developed to identify and predict the acute toxicity of chemicals by automatically analyzing the phenotypic profiling of Caenorhabditis elegans. This protocol describes how to treat worms with chemicals in a 384-well plate, capture videos, and quantify toxicological related phenotypes.
Applying toxicity testing of chemicals in higher order organisms, such as mice or rats, is time-consuming and expensive, due to their long lifespan and maintenance issues. On the contrary, the nematode Caenorhabditis elegans (C. elegans) has advantages to make it an ideal choice for toxicity testing: a short lifespan, easy cultivation, and efficient reproduction. Here, we describe a protocol for the automatic phenotypic profiling of C. elegans in a 384-well plate. The nematode worms are cultured in a 384-well plate with liquid medium and chemical treatment, and videos are taken of each well to quantify the chemical influence on 33 worm features. Experimental results demonstrate that the quantified phenotype features can classify and predict the acute toxicity for different chemical compounds and establish a priority list for further traditional chemical toxicity assessment tests in a rodent model.
Along with the rapid development of chemical compounds applied to industrial production and people's daily life, it is important to study the toxicity testing models for the chemicals. In many cases, the rodent animal model is employed to evaluate the potential toxicity of different chemicals on health. In general, the determination of lethal concentrations (i.e., the assayed 50% lethal dose [LD50] of different chemicals) is used as the traditional parameter in a rodent (rat/mouse) model in vivo, which is time-consuming and very expensive. In addition, due to the reduce, refine, or replace (3R) principle that is central to animal welfare and ethics, new methods that allow for the replacement of higher animals are valuable to scientific research1,2,3. C. elegans is a free-living nematode that has been isolated from soil. It has been widely used as a research organism in the laboratory because of its beneficial characteristics, such as a short lifespan, easy cultivation, and efficient reproduction. In addition, many fundamental biological pathways, including basic physiological processes and stress responses in C. elegans, are conserved in higher mammals4,5,6,7,8. In a couple of comparisons we and others have made, there is a good concordance between C. elegans toxicity and toxicity observed in rodents9. All of this makes C. elegans a good model to test the effects of chemical toxicities in vivo.
Recently, some studies quantified the phenotypic features of C. elegans. The features can be used to analyze the toxicities of chemicals2,3,10 and the aging of worms11. We also developed a method that combines a liquid worm culturing system and an image analysis system, in which the worms are cultured in a 384-well plate under different chemical treatments12. This quantitative technique has been developed to automatically analyze the 33 parameters of C. elegans after 12-24h of chemical treatment in a 384-well plate with liquid medium. An automated microscope stage is used for experimental video acquisition. The videos are processed by a custom-designed program, and 33 features related to the worms' moving behavior are quantified. The method is used to quantify the worm phenotypes under the treatment of 10 compounds. The results show that different toxicities can alter the phenotypes of C. elegans. These quantified phenotypes can be used to identify and predict the acute toxicity of different chemical compounds. The overall goal of this method is to facilitate the observation and phenotypic quantification of experiments with C. elegans in a liquid culture. This method is useful for the application of C. elegans in chemical toxicity evaluations and phenotype quantifications, which help predict the acute toxicity of different chemical compounds and establish a priority list for further traditional chemical toxicity assessment tests in a rodent model. In addition, this method can be applied to the toxicity screening and testing of new chemicals or the compound as the food additive agent pollution, pharmacautical compounds, environmental exogenous compound, and so on.
The protocol follows the animal care guidelines of the Animal Ethics Committee of the Beijing Center for Disease Prevention and Control in China.
1. Chemical preparation
2. Worm preparation
3. Chemical treatment and video capture
NOTE: In a 384-well plate, worms (50 µL in each well) are treated to six to seven dosages of an individual chemical (Table 1). Prepare eight parallel wells, each containing 50 µL of the 2x chemical solution for every dosage (eight wells are filled with the same chemical and the same concentration, Table 2). All videos are collected using a digital camera attached to an inverted microscope (Table of Materials). The chemical treatment experiment lasts for 24 h. Do not add bacterial food to each well during the 24 h chemical treatment experiment.
4. Experiment video processing
NOTE: A program for experimental video and images processing was written and packaged. It can be freely downloaded (see Table of Materials). The experimental video is stored in the form of an image frame sequence, and the frame sequence of each video is stored in a specific directory. The program can recognize worms and quantify phenotypes automatically.
We have tested the phenotypes of worms exposed to different concentrations of more than 10 chemicals12. In the test, 33 distinct features were quantified for each chemical compound at three time points (0 h, 12 h, and 24 h). Previously, a comparison between a manual and an automatic analysis of a lifespan assay was done11,12. In this assay, we found that chemicals and concentrations can influence the worm phenotypes. An overview of this method is shown in Figure 2.
The results (Figure 3 and Figure 4c,d) showed that the worms died quickly as the chemical concentration increased. At higher concentrations, the worms became straighter and less curved than at lower concentrations or in control groups (Figure 3 and Figure 4b). In the beginning (at 0 h), there was no significant difference between the control (K-medium) and chemical treatments for all phenotypes. After 12 h of treatment with a given chemical dosage, the phenotypes of worms showed different degrees of differences among control and different concentration groups. For example, the major axis length increased as time increased. There is also a gradient trend from lower to higher chemical concentrations. The gradient trend of different chemical concentrations was also significant in the minor axis length (Figure 4a,b).
In this assay, the worm's motility was calculated in two ways, based on the area the worm moved in and the motility ratio (Figure 4c,d). Motility results of both ways showed similar patterns. There were no significant differences of the worm motility among different concentrations and control groups at the beginning (at the 0 h time point). As time passed, the worms in the control groups showed a stable decrease in motility. At 12 h, the worms that underwent chemical treatments at different concentrations showed significant differences in motility compared with control groups. In addition, the worms under higher concentration treatments showed weak motility compared to the worms under lower concentration treatments. This indicates that worms under higher concentration treatments became less motile and died quicker (Figure 4c,d). These results suggest that the designed method is useful for chemical toxicity assessments, and the quantified phenotypes of C. elegans are useful markers for chemical toxicity identification.
Figure 1: The interface of the software. Please click here to view a larger version of this figure.
Figure 2: The pipeline of a high-throughput assay for the prediction of chemical toxicity by automated phenotypic profiling of Caenorhabditis elegans. Please click here to view a larger version of this figure.
Figure 3: Experimental images of worms under 4.64 mg/mL CdCl2 (upper panel), 0.464 mg/mL CdCl2 (middle panel), and K-medium (bottom panel), at different time points. The images show the status changes of worms under chemical treatment or in a control group in one representative well of the 384-well plate throughout time. Please click here to view a larger version of this figure.
Figure 4: The quantified features of worms under different concentrations of CdCl2. (a) The quantified major axis length. (b) The quantified minor axis length. (c) The quantified motility by the moved area. (d) The quantified motility by the moved area/worm size. The bar plots show the average quantification for each feature on single worms. The error bars denote ± standard deviation (SD). The concentration unit = mg/mL. Please click here to view a larger version of this figure.
Table 1: Exposure concentration of 10 chemicals for the 384-well-plate C. elegans acute toxicity test.
Table 2: A schematic of the 384-well plate layout.
Table 3: Defined phenotypes of worms.
The advantages of C. elegans have led to its increasing usage in toxicology9, both for mechanistic studies and high-throughput screening approaches. An increased role for C. elegans in complementing other model systems in toxicological research has been remarkable in recent years, especially for the rapid toxicity assessment of new chemicals. This article provides a new assay of high-throughput, quantitative screening of worm phenotypes in a 384-well plate for the automatic identification and assessment of chemical toxicity. This assay is ideal for acute toxicity testing of chemicals within 24 h, and it could be applied to subacute toxicity testing as well when more time points of data are collected and food source (OP50) is supplied for the worms.
The medium used for diluting the chemicals can vary; we chose K-medium in the assay by referring to Sofieet al.13. Worms were cultured in K-medium in both the control and chemical treatment groups. An artificial freshwater solution or a soil solution with low ionic strength could be alternatives to K-medium.
Chemicals with different toxicities can alter the phenotypes of C. elegans in different patterns. Chemicals used in this test were chosen from the third to sixth categories of the Globally Harmonized System of Classification and Labeling of Chemicals (GHS). C. elegans were exposed to chemicals at six or more dosage levels, which covered the 0%-100% mortality dosage range. For those chemicals with low water solubility, DMSO is recommended to promote the chemical dissolution in water. As a high concentration of DMSO may affect worm development and lifespan14, no more than 0.2% DMSO should be used for aquatic tests.
The automatically quantified features show significant difference among different toxicities, which demonstrates that these quantified phenotypes of worms are very useful in identifying the toxicity of chemicals. It indicated that phenotypic profiling revealed conserved functions to classify and predict the toxicity of different chemicals using nematode C. elegans as an in vivo model organism.
The US National Toxicology Program (NTP) established the Tox21 community through a memorandum of understanding with the U.S. Environmental Protection Agency (EPA) and the National Institutes of Health (NIH) Chemical Genomics Center, now the National Center for Advancing Translational Sciences (NCATS). Tox21 uses high-throughput in vitro screening and in vivo alternative animal model testing to identify mechanisms of toxicity, to prioritize chemicals for additional in vivo toxicity testing, and to develop predictive models of human toxicological responses. As part of that effort, C. elegans was used to screen the EPA's ToxCast Phase I and Phase II libraries, which contain 292 and 676 chemicals, respectively, for chemicals leading to decreased larval development and growth15. The COPAS (Complex Object Parametric Analyzer and Sorter) platform has also been used for the worm toxicological screening studies2. However, the COPAS platform only quantifies few features, such as worm width, worm length, and the fluorescence intensity. This method is an improvement to current methods using worms to rapidly prescreen the toxicity of new chemicals.
There are several critical steps within the protocol: the worm culture in a 384-well plate, the chemical treatment, the experimental image capture, and the phenotype quantification. Compared to traditional toxicity evaluation methods, this protocol can quantify some phenotypes of worms that are difficult to calculate manually and useful to reflect the toxicities of every chemical, such as the worm motility, worm width, worm size, and gray intensity. Clearly, this high-throughput assay for the prediction of chemical toxicity will be a valuable toxicity model approach and could be used for the prescreening of chemicals before rodent animal experiments.
In summary, this technique paves a way on rapid toxicity assessment in multiple areas. Researchers could apply the method to the emergency analysis of toxicity in foodborne toxicosis, the safety evaluation of pharmaceutical compounds, as well as the acute toxicity screening and detection of new chemicals and environmental exogenous compounds.
The authors have nothing to disclose.
The authors thank CGC for kindly sending the C. elegans. This work was supported by National Key Research and Development Program of China (#2018YFC1603102, #2018YFC1602705); National Natural Science Foundation of China Grant (#31401025, #81273108, #81641184), The Capital Health Research and Development of Special Project in Beijing (#2011-1013-03), the Opening Fund of the Beijing Key Laboratory of Environmental Toxicology (#2015HJDL03), and the Natural Science Foundation of Shandong Province, China (ZR2017BF041).
2-Propanol | Sigma-Aldrich | 59300 | |
384-well plates | Throme | 142761 | |
Agar | Bacto | 214010 | |
Atropine sulfate | Sigma-Aldrich | PHL80892 | |
Bleach buffer | 0.5 mL of 10 M NaOH, 0.5 mL of5% NaClO, 9 mL ofultrapure water | ||
Cadmium chloride | Sigma-Aldrich | 202908 | |
Calcium chloride | Sigma-Aldrich | 21074 | |
CCD camera | Zeiss | AxioCam HRm | Zeiss microscopy GmbH |
Cholesterol | Sigma-Aldrich | C8667 | |
Copper(II) sulfate | Sigma-Aldrich | 451657 | |
Ethanol | Sigma-Aldrich | 24105 | |
Ethylene glycol | Sigma-Aldrich | 324558 | |
Glycerol | Sigma-Aldrich | G5516 | |
K-Medium | 3.04 g of NaCl and 2.39 g of KCl in 1 L ultrapure water | ||
LB Broth | 10 g/L Tryptone, 5 g/L Yeast Extract, 5 g/L NaCl | ||
Magnesium sulfate heptahydrate | Sigma-Aldrich | 63140 | |
NGM Plate | 3 g ofNaCl, 17 g ofagar, 2.5 g ofpeptone in 1 L of ultrapure water, after autoclave add 1 mL of cholesterol (5 mg/mL in ethanol), 1 mL of MgSO4 (1 M), 1 mL of CaCl2 (1 M), 25 mL of PPB buffer | ||
Peptone | Bacto | 211677 | |
Potassium chloride | Sigma-Aldrich | 60130 | |
Potassium phosphate dibasic | Sigma-Aldrich | 795496 | |
Potassium phosphate monobasic | Sigma-Aldrich | 795488 | |
PPB buffer | 35.6 g of K2HPO4, 108.3 g of KH2PO4 in 1 L ultrapure water | ||
shaker | ZHICHENG | ZWY-200D | |
Sodium chloride | Sigma-Aldrich | 71382 | |
Sodium fluoride | Sigma-Aldrich | s7920 | |
Sodium hydroxide | Sigma-Aldrich | 71690 | |
Sodium hypochlorite solution | Sigma-Aldrich | 239305 | |
The link of program | https://github.com/weiyangc/ImageProcessForWellPlate | ||
Tryptone | Sigma-Aldrich | T7293 | |
Yeast extract | Sigma-Aldrich | Y1625 | |
Zeiss automatic microscope | Zeiss | AXIO Observer.Z1 | Zeiss automatic microsco with peproprietary software Zen2012 and charge coupled device(CCD) camera |