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).

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
<ol>
	<li>Obtain chemicals (Table 1 and Table of Materials).</li>
	<li>Determine the highest and lowest dosage of the individual chemicals for a minimum concentration of 100% lethality (LC100, 24 h) and a maximum concentration of 100% nonlethality (LC0, 24 h) to worms. Use at least six dilutions of the highest concentration (Table 1). 
	NOTE: Conduct a preliminary worm lethality test9 to explore LC100 and LC0 for a new chemical, to determine the dosage.</li>
	<li>Dilute each chemical with K-medium (Table of Materials) to 2x the required concentration. Use K-medium as a control to compare the phenotype alterations caused by the chemicals.
	<ol>
		<li>For example, prepare 7 gradient concentrations of cadmium chloride (CdCl2) (Table 1). To prepare 2x the highest concentrated aqueous solution (4.64 mg/mL), dissolve 92.8 mg of CdCl2 solid powder in 8 mL of K-medium and fill up to 10 mL after the powder has fully dissolved. Prepare the other concentration levels by dilution with K-medium.</li>
	</ol>
	</li>
	<li>Prepare eight parallel wells for every concentration in the chemical gradient. Each well contains 50 &#181;L of the 2x chemical solution. Prepare at least three groups of eight parallel wells of K-medium as&#160;controls (Table 2). 
	NOTE: In brief, a volume of 500 &#181;L of 2x working solution is necessary for a single dose of each chemical.</li>
</ol>
2. Worm preparation
<ol>
	<li>Obtain wild-type N2 worms and Escherichia coli OP50 strains from the Caenorhabditis Genetics Center (CGC).</li>
	<li>Obtain synchronized L4 worms.
	<ol>
		<li>Pick a single colony of E. coli OP50 from the streak plate. Aseptically inoculate the colony in 100 mL of LB broth and grow it overnight at 37 &#176;C. 
		NOTE: The E. coli OP50 solution is now ready for seeding to nematode growth medium (NGM, Table of Materials) plates.</li>
		<li>Pour NGM into a 90 mm plastic Petri plate. Seed each plate with 300 &#181;L of E. coli OP50 solution the day after pouring. Incubate N2 worms on the NGM plates with OP50 at 20 &#176;C for about 2-3 days until most of the worms have reached the adult stage.</li>
		<li>Harvest gravid worms into a 15 mL sterile conical centrifuge tube with sterile H2O. Let the worms settle down for at least 2 min, aspirate the H2O, and add 5 mL of bleach buffer (Table of Materials).</li>
		<li>Vortex the tube for 5 min, spin the tube for 30 s (at 1,300 x g) to pellet the eggs, and discard the supernatant.</li>
		<li>Wash the eggs with 5 mL of sterile H2O and vortex the tube for 5 s. Centrifuge the tube for 30 s (at 1,300 x g), remove the supernatant, and wash again.</li>
		<li>Pipette the eggs onto a new NGM plate with OP50. Incubate them at 20 &#176;C. Monitor the hatched L1 worms the next morning; the worms will reach the L4 stage in approximately 40 h.</li>
	</ol>
	</li>
	<li>Wash the L4 worms off the 90 mm Petri plates with K-medium into a 50 mL sterile conical tube. Adjust the concentration of worms to ~40 animals per 100 &#181;L of K-medium under a stereomicroscope. Add 50 &#181;L (~20 worms) into each well of the 384-well plate. These synchronized worms (L4 stage) are ready for the following treatment by chemicals.</li>
</ol>
3. Chemical treatment and video capture
NOTE: In a 384-well plate, worms (50 &#181;L in each well) are treated to six to seven dosages of an individual chemical (Table 1). Prepare eight parallel wells, each containing 50 &#181;L 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.
<ol>
	<li>Before adding the chemicals, set the 384-well plate with the synchronized worms on the automatic stage and take videos of each well with the programmed acquisition procedure (7 frames per second for 2 s; it takes ~25&#160;min to scan each plate).</li>
	<li>Add 50 &#181;L of the 2x chemical stock prepared according to section 1 for each well (Table 2). Set the time as the 0 h point.</li>
	<li>Incubate the 384-well plate at 20 &#176;C and shake it at 80 rpm in an incubator shaker.</li>
	<li>Remove the plate from the incubator and transfer it to an automatic stage. Take videos of each well of the whole plate, at 12 h and at 24 h, to check the phenotypes of the worms for each specific chemical treatment in K-medium. Approximately 25 min are required for one plate screen.</li>
</ol>
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.
<ol>
	<li>In the graphical user interface (GUI, Figure 1), add the parameters, such as the frame sequence directory, the output directory, the worm size parameter, and the movement threshold parameter. Click the Analyze button to process the experimental images.
	<ol>
		<li>Click the Select button to choose the source images directory.</li>
		<li>Add the middle result directory in the interface. 
		NOTE: The middle results include the segmented images. These middle results are useful for the visual observation of the processed images.</li>
		<li>Add the final result directory in the interface.</li>
		<li>Add the average worm size parameter in the Worm Size textbox in the interface. 
		NOTE: The size parameter used in the experiments is 2,000.</li>
		<li>Add the Threshold of moved ratio in the interface. 
		NOTE: The ratio used in the experiments is 0.93.</li>
		<li>Click the Analyze button to start the image processing. Click the Reset button to clear the added parameters. 
		NOTE: There are 33 features defined and quantified for worms. All the defined phenotypes are sorted by categories (listed in Table 3). These features can be quantified from experimental images. A quantitative comparison among different chemicals, which have different toxicities, can be done by comparing these features.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

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 ident...

Along with the rapid development of chemical compounds applied to industrial production and people&#39;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&#160;[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&#39; 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.&#160;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.

<table border="0" cellpadding="0" cellspacing="0" style="width:959px;" width="957">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">2-Propanol</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">59300</td>
			<td style="width:407px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">384-well plates</td>
			<td style="width:171px;">Throme</td>
			<td style="width:175px;">142761</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Agar</td>
			<td>Bacto</td>
			<td style="width:175px;">214010</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Atropine sulfate</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">PHL80892</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Bleach buffer</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td>0.5 mL of 10 M NaOH, 0.5 mL of5% NaClO, 9 mL ofultrapure water</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Cadmium chloride</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">202908</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Calcium chloride</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">21074</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">CCD camera</td>
			<td style="width:171px;">Zeiss</td>
			<td style="width:175px;">AxioCam HRm</td>
			<td style="width:407px;">Zeiss microscopy GmbH</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Cholesterol</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">C8667</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Copper(II) sulfate</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">451657</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Ethanol</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">24105</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Ethylene glycol</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">324558</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Glycerol</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">G5516</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">K-Medium</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td style="width:407px;">3.04 g of NaCl and 2.39 g of KCl in 1 L ultrapure water</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">LB Broth&#160;</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td style="width:407px;">10&#160;g/L&#160;Tryptone,&#160;5&#160;g/L&#160;Yeast&#160;Extract,&#160;5&#160;g/L&#160;NaCl&#160;</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:207px;">Magnesium sulfate heptahydrate</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">63140</td>
			<td></td>
		</tr>
		<tr height="84">
			<td height="84" style="height:84px;width:207px;">NGM Plate</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td style="width:407px;">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</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Peptone</td>
			<td>Bacto</td>
			<td style="width:175px;">211677</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Potassium chloride</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">60130</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Potassium phosphate dibasic</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">795496</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:207px;">Potassium phosphate monobasic</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">795488</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">PPB buffer</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td style="width:407px;">35.6 g of K2HPO4, 108.3 g of KH2PO4 in 1 L ultrapure water</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">shaker</td>
			<td style="width:171px;">ZHICHENG</td>
			<td style="width:175px;">ZWY-200D</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Sodium chloride</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">71382</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Sodium fluoride</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">s7920</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Sodium hydroxide</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">71690</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">Sodium hypochlorite solution</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">239305</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:207px;">The link of program</td>
			<td style="width:171px;"></td>
			<td style="width:175px;"></td>
			<td style="width:407px;">https://github.com/weiyangc/ImageProcessForWellPlate</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Tryptone</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">T7293</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast extract</td>
			<td style="width:171px;">Sigma-Aldrich</td>
			<td style="width:175px;">Y1625</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:207px;">Zeiss automatic microscope&#160;</td>
			<td style="width:171px;">Zeiss</td>
			<td style="width:175px;">AXIO Observer.Z1</td>
			<td style="width:407px;">Zeiss automatic microsco with peproprietary software Zen2012 and charge coupled device(CCD) camera</td>
		</tr>
	</tbody>
</table>

a high-throughput assay for the prediction of chemical toxicity by automated phenotypic profiling of caenorhabditis elegans

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.

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 p...

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A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

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.

A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

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 ...

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JoVE Journal

Environment

7.2K Views.  Beijing Center for Disease Prevention and Control/Beijing Center of Preventive Medicine Research, China. 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.

Video: A High-throughput Assay for the Prediction of Chemical Toxicity by Automated Phenotypic Profiling of Caenorhabditis elegans

Determination of Microbial Extracellular Enzyme Activity in Waters, Soils, and Sediments using High Throughput Microplate Assays

Much of the nutrient cycling and carbon processing in natural environments occurs through the activity of extracellular enzymes released by microorganisms. Thus, measurement of the activity of these extracellular enzymes can give insights into the rates of ecosystem level processes, such as organic matter decomposition or nitrogen and phosphorus mineralization. Assays of extracellular enzyme activity in environmental samples typically involve exposing the samples to artificial colorimetric or fluorometric substrates and tracking the rate of substrate hydrolysis. Here we describe microplate based methods for these procedures that allow the analysis of large numbers of samples within a short time frame. Samples are allowed to react with artificial substrates within 96-well microplates or deep well microplate blocks, and enzyme activity is subsequently determined by absorption or fluorescence of the resulting end product using a typical microplate reader or fluorometer. Such high throughput procedures not only facilitate comparisons between spatially separate sites or ecosystems, but also substantially reduce the cost of such assays by reducing overall reagent volumes needed per sample.

Microplate based procedures are described for the colorimetric or fluorometric analysis of extracellular enzyme activity. These procedures allow for the rapid assay of such activity in large numbers of environmental samples within a manageable time frame.

Much of the nutrient cycling and carbon  processing in natural environments occurs through the activity of extracellular  enzymes released by ...

High-throughput Fluorometric Measurement of Potential Soil Extracellular Enzyme Activities

Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be assimilated for energy and nutrients. Measuring soil microbial enzyme activity is crucial in understanding soil ecosystem functional dynamics. The general concept of the fluorescence enzyme assay is that synthetic C-, N-, or P-rich substrates bound with a fluorescent dye are added to soil samples. When intact, the labeled substrates do not fluoresce. Enzyme activity is measured as the increase in fluorescence as the fluorescent dyes are cleaved from their substrates, which allows them to fluoresce. Enzyme measurements can be expressed in units of molarity or activity. To perform this assay, soil slurries are prepared by combining soil with a pH buffer. The pH buffer (typically a 50 mM sodium acetate or 50 mM Tris buffer), is chosen for the buffer&#39;s particular acid dissociation constant (pKa) to best match the soil sample pH. The soil slurries are inoculated with a nonlimiting amount of fluorescently labeled (i.e. C-, N-, or P-rich) substrate. Using soil slurries in the assay serves to minimize limitations on enzyme and substrate diffusion. Therefore, this assay controls for differences in substrate limitation, diffusion rates, and soil pH conditions; thus detecting potential enzyme activity rates as a function of the difference in enzyme concentrations (per sample).
Fluorescence enzyme assays are typically more sensitive than spectrophotometric (i.e. colorimetric) assays,&#160;but can suffer from interference caused by impurities and the instability of many fluorescent compounds when exposed to light; so caution is required when handling fluorescent substrates. Likewise, this method only assesses potential enzyme activities under laboratory conditions when substrates are not limiting. Caution should be used when interpreting the data representing cross-site comparisons with differing temperatures or soil types, as in situ soil type and temperature can influence enzyme kinetics.

To measure potential rates of soil extracellular enzyme activities, synthetic substrates that are bound to a fluorescent dye are added to soil samples. Enzyme activity is measured as the fluorescent dye is released from the substrate by an enzyme-catalyzed reaction, where higher fluorescence indicates more substrate degradation.

Microbes in soils and other environments produce extracellular enzymes to depolymerize and hydrolyze organic macromolecules so that they can be ...

Optimized Negative Staining: a High-throughput Protocol for Examining Small and Asymmetric Protein Structure by Electron Microscopy

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of natural proteins have a molecular mass between 40 - 200 kDa1,2, a robust and high-throughput method with a nanometer resolution capability is needed. Negative staining (NS) electron microscopy (EM) is an easy, rapid, and qualitative approach which has frequently been used in research laboratories to examine protein structure and protein-protein interactions. Unfortunately, conventional NS protocols often generate structural artifacts on proteins, especially with lipoproteins that usually form presenting rouleaux artifacts. By using images of lipoproteins from cryo-electron microscopy (cryo-EM) as a standard, the key parameters in NS specimen preparation conditions were recently screened and reported as the optimized NS protocol (OpNS), a modified conventional NS protocol 3 . Artifacts like rouleaux can be greatly limited by OpNS, additionally providing high contrast along with reasonably high&#8208;resolution (near 1 nm) images of small and asymmetric proteins. These high-resolution and high contrast images are even favorable for an individual protein (a single object, no average) 3D reconstruction, such as a 160 kDa antibody, through the method of electron tomography4,5. Moreover, OpNS can be a high&#8208;throughput tool to examine hundreds of samples of small proteins. For example, the previously published mechanism of 53 kDa cholesteryl ester transfer protein (CETP) involved the screening and imaging of hundreds of samples 6. Considering cryo-EM rarely successfully images proteins less than 200 kDa has yet to publish any study involving screening over one hundred sample conditions, it is fair to call OpNS a high-throughput method for studying small proteins. Hopefully the OpNS protocol presented here can be a useful tool to push the boundaries of EM and accelerate EM studies into small protein structure, dynamics and mechanisms.

More than half of proteins are small proteins (molecular mass &#60;200 kDa) that are challenging for both electron microscope imaging and three-dimensional reconstructions. Optimized negative staining is a robust and high-throughput protocol to obtain high contrast and relatively high resolution (~1 nm) images of small asymmetric proteins or complexes under different physiological conditions.

Structural determination of proteins is rather challenging for proteins with molecular masses between 40 - 200 kDa. Considering that more than half of ...

Physical, Chemical and Biological Characterization of Six Biochars Produced for the Remediation of Contaminated Sites

The physical and chemical properties of biochar vary based on feedstock sources and production conditions, making it possible to engineer biochars with specific functions (e.g. carbon sequestration, soil quality improvements, or contaminant sorption). In 2013, the International Biochar Initiative (IBI) made publically available their Standardized Product Definition and Product Testing Guidelines (Version 1.1) which set standards for physical and chemical characteristics for biochar. Six biochars made from three different feedstocks and at two temperatures were analyzed for characteristics related to their use as a soil amendment. The protocol describes analyses of the feedstocks and biochars and includes: cation exchange capacity (CEC), specific surface area (SSA), organic carbon (OC) and moisture percentage, pH, particle size distribution, and proximate and ultimate analysis. Also described in the protocol are the analyses of the feedstocks and biochars for contaminants including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), metals and mercury as well as nutrients (phosphorous, nitrite and nitrate and ammonium as nitrogen). The protocol also includes the biological testing procedures, earthworm avoidance and germination assays. Based on the quality assurance / quality control (QA/QC) results of blanks, duplicates, standards and reference materials, all methods were determined adequate for use with biochar and feedstock materials. All biochars and feedstocks were well within the criterion set by the IBI and there were little differences among biochars, except in the case of the biochar produced from construction waste materials. This biochar (referred to as Old biochar) was determined to have elevated levels of arsenic, chromium, copper, and lead, and failed the earthworm avoidance and germination assays. Based on these results, Old biochar would not be appropriate for use as a soil amendment for carbon sequestration, substrate quality improvements or remediation.

Biochar is a carbon-rich material used as a soil amendment with the ability to sustainably sequester carbon, improve substrate quality and sorb contaminants. This protocol describes the 17 analytical methods used for the characterization of biochar, which is required prior to large scale implementation of these amendments in the environment.

The physical and chemical properties of biochar vary based on feedstock sources and production conditions, making it possible to engineer biochars with ...

High-throughput Screening of Recalcitrance Variations in Lignocellulosic Biomass: Total Lignin, Lignin Monomers, and Enzymatic Sugar Release

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the use of non-renewable energy sources. In order to identify which plants, out of a diverse pool, have the desired chemical traits for downstream applications, attributes, such as cellulose and lignin content, or monomeric sugar release following an enzymatic saccharification, must be compared. The experimental and data analysis protocols of the standard methods of analysis can be time-consuming, thereby limiting the number of samples that can be measured. High-throughput (HTP) methods alleviate the shortcomings of the standard methods, and permit the rapid screening of available samples to isolate those possessing the desired traits. This study illustrates the HTP sugar release and pyrolysis-molecular beam mass spectrometry pipelines employed at the National Renewable Energy Lab. These pipelines have enabled the efficient assessment of thousands of plants while decreasing experimental time and costs through reductions in labor and consumables.

Plant cell wall structure and chemistry traits are evaluated to identify ideal feedstocks for biofuels and bio-materials. Standard methods have limitations when applied to large data sets. These high-throughput pretreatment, enzyme saccharification, and pyrolysis-molecular beam mass spectrometry methods compare large numbers of biomass samples with decreased experimental time and cost.

The conversion of lignocellulosic biomass to fuels, chemicals, and other commodities has been explored as one possible pathway toward reductions in the ...

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (Zea mays L.)

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole grain composition and processing characteristics vary among maize hybrids and can impact the quality of the final processed product. Therefore, in order to produce healthier processed food products from maize, it is necessary to know how to optimize processing parameters for particular sets of germplasm to account for these differences in grain composition and processing characteristics. This includes a better understanding of how current processing techniques impact the nutritional quality of the final processed food product. Here, we describe a microscale protocol that both simulates the processing pipeline to produce cornflakes from large flaking grits and allows for the processing of multiple grain samples simultaneously. The flaking grits, the intermediate processed products, or final processed product, as well as the corn grain itself, can be analyzed for nutritional content as part of a high-throughput analytical pipeline. This procedure was developed specifically for incorporation into a maize breeding research program, and it can be modified for other grain crops. We provide an example of the analysis of insoluble-bound ferulic acid and p-coumaric acid content in maize. Samples were taken at five different processing stages. We demonstrate that sampling can take place at multiple stages during microscale processing, that the processing technique can be utilized in the context of a specialized maize breeding program, and that, in our example, most of the nutritional content was lost during food product processing.

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Here, we present a microscale protocol for processing grain samples and for incorporating this microscale approach into a high-throughput analytical pipeline. This is a higher throughput adaptation of currently available protocols.

Maize is an important grain crop in the United States and worldwide. However, maize grain must be processed prior to human consumption. Furthermore, whole ...

A 3-dimensional (3D)-printed Template for High Throughput Zebrafish Embryo Arraying

The zebrafish is a globally recognized fresh water organism frequently used in developmental biology, environmental toxicology, and human disease related research fields. Thanks to its unique features, including large fecundity, embryo translucency, rapid and simultaneous development, etc., zebrafish embryos are often used for large scale toxicity assessment of chemicals and drug/compound screening. A typical screening procedure involves adult zebrafish spawning, embryos selection, and arraying the embryos into multi-well plates. From there, embryos are subjected to exposure and the toxicity of chemical, or the effectiveness of the drugs/compounds can be evaluated relatively quickly based on phenotypic observations. Among these processes, embryos arraying is one of the most time-consuming and labor-intensive steps that limits the throughput level. In this protocol, we present an innovative approach that makes use of a 3D-printed arraying template coupled with vacuum manipulation to speed up this laborious step. The protocol herein describes the overall design of the arraying template, a detailed experimental setup and step-by-step procedure, followed by representative results. When implemented, this approach should prove beneficial in a variety of research applications using zebrafish embryos as testing subjects.

A 3-dimensional 3D-printed Template for High Throughput Zebrafish Embryo Arraying

Here, we present a protocol to design and fabricate a zebrafish embryo arraying template, followed by a detailed procedure on the use of such template for high throughput zebrafish embryo arraying into a 96-well plate.

The zebrafish is a globally recognized fresh water organism frequently used in developmental biology, environmental toxicology, and human disease related ...

High-throughput Siderophore Screening from Environmental Samples: Plant Tissues, Bulk Soils, and Rhizosphere Soils

Siderophores (low-molecular weight metal chelating compounds) are important in various ecological phenomenon ranging from iron (Fe) biogeochemical cycling in soils, to pathogen competition, plant growth promotion, and cross-kingdom signaling. Furthermore, siderophores are also of commercial interest in bioleaching and bioweathering of metal-bearing minerals and ores. A rapid, cost effective, and robust means of quantitatively assessing siderophore production in complex samples is key to identifying important aspects of the ecological ramifications of siderophore activity, including, novel siderophore producing microbes. The method presented here was developed to assess siderophore activity of in-tact microbiome communities, in environmental samples, such as soil or plant tissues. The samples were homogenized and diluted in a modified M9 medium (without Fe), and enrichment cultures were incubated for 3 days. Siderophore production was assessed in samples at 24, 48, and 72 hours (h) using a novel 96-well microplate CAS (Chrome azurol sulphonate)-Fe agar assay, an adaptation of the traditionally tedious and time-consuming colorimetric method of assessing siderophore activity, performed on individual cultivated microbial isolates. We applied our method to 4 different genotypes/Lines of wheat (Triticum aestivum L.), including Lewjain, Madsen, and PI561725, and PI561727 commonly grown in the inland Pacific Northwest. Siderophore production was clearly impacted by the genotype of wheat, and in the specific types of plant tissues observed. We successfully used our method to rapidly screen for the influence of plant genotype on siderophore production, a key function in terrestrial and aquatic ecosystems. We produced many technical replicates, yielding very reliable statistical differences in soils and within plant tissues. Importantly, the results show the proposed method can be used to rapidly examine siderophore production in complex samples with a high degree of reliability, in a manner that allows communities to be preserved for later work to identify taxa and functional genes.

We present a protocol for rapid screening of environmental samples for siderophore potential contributing to micronutrient bioavailability and turnover in terrestrial systems.

Siderophores (low-molecular weight metal chelating compounds) are important in various ecological phenomenon ranging from iron (Fe) biogeochemical cycling ...

Using Caenorhabditis elegans for Studying Trans- and Multi-Generational Effects of Toxicants

Information about toxicities of chemicals are essential in their application and waste management. For chemicals at low concentrations, the long-term effects are very important in judging their consequences in the environment and on human health. In demonstrating long-term influences, effects of chemicals over generations in recent studies provide new insight. Here, we describe protocols for studying effects of chemicals over multiple generations using free-living nematode Caenorhabditis elegans. Two aspects are presented: (1) trans-generational (TG) and (2) multi-generational effect studies, the latter of which is separated to multi-generational exposure (MGE) and multi-generational residual (MGR) effect studies. The TG effect study is robust with a simple purpose to determine whether chemical exposure to parents can result in any residual consequences on offspring. After the effects are measured on parents, sodium hypochlorite solutions are used to kill the parents and keep the offspring so as to facilitate effect measurement on the offspring. The TG effect study is used to determine whether the offspring are affected when their parent is exposed to the pollutants. The MGE and MGR effect study is systematical used to determine whether continuous generational exposure can result in adaptive responses in offspring over generations. Careful pick-up and transfer are used to distinguish generations to facilitate effect measurement on each generation. We also combined protocols to measure locomotion behavior, reproduction, lifespan, biochemical and gene expression changes. Some example experiments are also presented to illustrate the trans- and multi-generational effect studies.

Using Caenorhabditis elegans for Studying Trans- and Multi-Generational Effects of Toxicants

Trans- and multi-generational effects of persistent chemicals are essential in judging their long-term consequences in the environment and on the human health. We provide novel detailed methods for studying trans- and multi-generational effects using free-living nematode Caenorhabditis elegans.

Information about toxicities of chemicals are essential in their application and waste management. For chemicals at low concentrations, the long-term ...

Standardized Methods for Measuring Induction of the Heat Shock Response in Caenorhabditis elegans

The heat shock response (HSR) is a cellular stress response induced by cytosolic protein misfolding that functions to restore protein folding homeostasis, or proteostasis. Caenorhabditis elegans occupies a unique and powerful niche for HSR research because the HSR can be assessed at the molecular, cellular, and organismal levels. Therefore, changes at the molecular level can be visualized at the cellular level and their impacts on physiology can be quantitated at the organismal level. While assays for measuring the HSR are straightforward, variations in the timing, temperature, and methodology described in the literature make it challenging to compare results across studies. Furthermore, these issues act as a barrier for anyone seeking to incorporate HSR analysis into their research. Here, a series of protocols is&#160;presented for measuring induction of the HSR in a robust and reproducible manner with RT-qPCR, fluorescent reporters, and an organismal thermorecovery assay. Additionally, we show that a widely used thermotolerance assay is not dependent on the well-established master regulator of the HSR, HSF-1, and therefore should not be used for HSR research. Finally, variations in these assays found in the literature are discussed and best practices are proposed to help standardize results across the field, ultimately facilitating neurodegenerative disease, aging, and HSR research.

Standardized Methods for Measuring Induction of the Heat Shock Response in Caenorhabditis elegans

Here, standardized protocols are presented to assess induction of the heat shock response (HSR) in Caenorhabditis elegans using RT-qPCR at the molecular level, fluorescent reporters at the cellular level, and thermorecovery at the organismal level.

The heat shock response (HSR) is a cellular stress response induced by cytosolic protein misfolding that functions to restore protein folding homeostasis, ...