Support for this study was provided by the U.S. National Science Foundation (Project #: CHE-1339637) with additional support from the U.S. Environmental Protection Agency. We thank Dr. Jone Corrales, Dr. Lauren Kristofco, Gavin Saari, Samuel Haddad, Bekah Burket and Bridgett Hill for general lab support.

Studies in this protocol generally follow standardized experimental design and recommended statistical analysis guidelines from the US Environmental Protection Agency (EPA no. 2000.0) for fathead minnows and the Organization for Economic Cooperation and Development (OECD no. 236) for zebrafish.&#160;These experimental designs (e.g., increasing replication) can be modified within the current protocol for future studies. Fish culture conditions follow previously published literature17. All experimental procedures and fish culture protocols followed Institutional Animal Care and Use Committee protocols approved at Baylor University.
1. Exposing Fish to Chemical Treatment
<ol>
	<li>Prepare caffeine exposure solutions by dissolving caffeine in reconstituted hard water. Perform appropriate serial dilutions by diluting higher caffeine treatments with hard water to produce lower caffeine treatment levels. 
	NOTE: Table 1 summarizes each of the treatment levels used in this experiment.</li>
</ol>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td colspan="2">Zebrafish</td>
			<td></td>
			<td colspan="2">Fathead Minnow</td>
		</tr>
		<tr>
			<td>Treatment</td>
			<td>Nominal Caffeine Concentration (mg/L)</td>
			<td>Measured Caffeine Concentration (mg/L)</td>
			<td>Treatment</td>
			<td>Nominal Caffeine Concentration (mg/L)</td>
			<td>Measured Caffeine Concentration (mg/L)</td>
		</tr>
		<tr>
			<td>Control</td>
			<td>0</td>
			<td>&#60;LOD</td>
			<td>Control</td>
			<td>0</td>
			<td>&#60;LOD</td>
		</tr>
		<tr>
			<td>75th Centile*</td>
			<td>0.001</td>
			<td>0.001</td>
			<td>75th Centile*</td>
			<td>0.001</td>
			<td>0.001</td>
		</tr>
		<tr>
			<td>95th Centile*</td>
			<td>0.039</td>
			<td>0.013</td>
			<td>95th Centile*</td>
			<td>0.039</td>
			<td>0.009</td>
		</tr>
		<tr>
			<td>99th Centile*</td>
			<td>0.412</td>
			<td>0.361</td>
			<td>99th Centile*</td>
			<td>0.412</td>
			<td>0.310</td>
		</tr>
		<tr>
			<td>THV</td>
			<td>4.07</td>
			<td>3.81</td>
			<td>THV</td>
			<td>4.07</td>
			<td>4.12</td>
		</tr>
		<tr>
			<td>10% LC50</td>
			<td>48.46</td>
			<td>46.66</td>
			<td>10% LC50</td>
			<td>14.1</td>
			<td>14.7</td>
		</tr>
		<tr>
			<td>40% LC50</td>
			<td>193.82</td>
			<td>186.67</td>
			<td>40% LC50</td>
			<td>56.38</td>
			<td>53.91</td>
		</tr>
	</tbody>
</table>
Table 1: Experimental caffeine treatments for zebrafish and fathead minnow experiments. Nominal and measured values of caffeine for each treatment are given. *The caffeine treatments used in this study represent the upper centiles of exposure distributions based on measured environmental values of caffeine16. THV: Therapeutic Hazard Value. LOD: Limit of Detection
<ol start="2">
	<li>Pour the prepared solution in individual exposure champers. Use 100 mL glass beakers filled with 20 mL of exposure solution for zebrafish exposure chambers and 500 mL beakers with 200 mL of exposure solution for fathead minnow exposure chambers.</li>
	<li>Using a transfer pipette, place 10 zebrafish embryos aged 4&#8211;6 h post fertilization (hpf) in each of four replicate exposure chambers per treatment.</li>
	<li>Place 10 fathead minnow larvae aged within 24 h of hatching in each of three replicate exposure chambers per treatment. To accommodate the larger size of fathead minnow larvae, cut the tip of the transfer pipette off prior to transfer.</li>
	<li>Maintain zebrafish experiments at a 16:8 h light:dark photoperiod and a constant temperature of 28 &#177; 1 &#176;C. Use the same photoperiod regime for fathead minnow studies, but at a temperature of 25 &#177; 1 &#176;C.</li>
	<li>After 96 h of chemical exposure, load individual fish in separate wells of 48 (for zebrafish) and 24 (for fathead minnow) well plates.
	<ol>
		<li>To ensure that each well contains an equal volume of solution, transfer zebrafish larvae to 48 well plates using a 5,000 &#181;L autopipette for a 1,000 &#181;L volume per well. Use the autopipette to withdraw and transfer both the zebrafish larvae and exposure solution simultaneously.</li>
		<li>Due to their larger size, transfer fathead minnow larvae using a transfer pipette with the tip cut off. Prior to transferring fathead minnow larvae to individual wells, fill each well to 2,000 &#181;L using an autopipette. When transferring individual fathead larvae to wells, place the tip of the transfer pipette in the well solution and allow the fish to swim from the pipette tip into the well.</li>
	</ol>
	</li>
</ol>
2. Calibration of Video-tracking Parameters
<ol>
	<li>Prior to behavioral measures, set observation and calibration parameters in the video track software (see Table of Materials).
	<ol>
		<li>Place a well plate in the recording chamber with at least 1 larval fish in an individual well. Use the plate and associated fish as representations to set calibration parameters.</li>
		<li>In the video track software, click &#34;File | Generate Protocol&#34;, which will open a &#8220;protocol creation wizard&#8221; dialogue box. In the &#34;Location Count&#34; field, enter the number of individuals wells of the well plate and then click &#34;OK&#34;.</li>
		<li>At the top of the screen, click &#34;View | Full Screen&#34;, which will prompt the system to display an overhead camera view of the well plate.</li>
		<li>Click the &#34;Draw Areas&#34; icon, which appears as three multicolored shapes. To the right of the well plate viewing area, select the circle icon in the field labeled &#34;Areas&#34;.</li>
		<li>Use the cursor to delineate the circular video tracking area in the top left well of the well plate. Select &#34;Top-Right Mark&#34; and then outline the viewing area of the top right well. Then, select &#34;Bottom Mark&#34; to outline the bottom right well. 
		NOTE: After drawing the circular outline, its position will likely need to be adjusted.&#160; To adjust the position of the outline, click &#8220;select&#8221; and then use the cursor to move the outlined area. Also, outlines can be replicated by clicking &#34;Copy&#34; and then &#34;Paste&#34;.&#160;</li>
		<li>After the top left, top right, and bottom right well tracking areas have been defined, click &#34;Build&#34; to prompt the software to automatically delineate the viewing areas of the remaining wells.</li>
		<li>In the area labeled &#34;Calibration&#34;, click &#34;Draw Scale&#34;. Use the cursor to draw a horizontal line across the plate. Once the line is drawn, a dialogue box labeled &#8220;Calibration measurement&#8221; will appear. Enter the well plate length and click &#34;OK&#34;.</li>
		<li>Exit the drawing manager by clicking the &#34;Draw Areas&#34; icon.</li>
		<li>Click the &#34;Tiles&#34; icon.&#160; Using the cursor, highlight all the boxes that appear on the viewing screen so that each box is green. 
		NOTE: The Tiles icon appears as a group of six individual small squares</li>
		<li>&#34;Click View| Full Screen&#34;. &#160;To the right of the plate viewing area, click &#34;Bkg&#34; in the box labeled &#34;Detection Threshold&#34;. Use the threshold adjustment bar to set the pixel detection threshold. Once, the appropriate pixel detection threshold is selected, click &#34;Apply to Group&#34;. 
		NOTE: This protocol sets the detection threshold at 13 in black mode for zebrafish observations and at 110 in transparent mode for fathead minnow observations.</li>
		<li>In the box labeled &#34;Movement Threshold&#34;, enter the desired movement speed tracking parameters. Once speed parameters are set, click &#34;Apply to Group&#34;. 
		NOTE: This protocol sets small/large movements at 20 mm/s and inactive/small movements at 5 mm/s. These selections program the software to track larval fish movement at three different speed levels: inactive (freezing) = &#60;5 mm/s, small (cruising) = 5&#8211;20 mm/s, and large (bursting) = &#62;20 mm/s.</li>
		<li>Click &#34;Parameters | Protocol Parameters&#34; from the drop-down menu. In the dialogue box, select the &#34;Time&#34; tab. Enter the observation time and the integration time. After parameters are entered click &#34;Ok&#34;.</li>
		<li>To set the light/dark photoperiod times and light intensity for each photoperiod open the light driver settings dialogue box by selecting &#34;Light Driving&#34; from the &#34;Parameters&#34; drop down menu. 
		NOTE: See protocol video for setting multiple light-dark photoperiods.</li>
		<li>After the video tracking parameters have been set, save the observation protocol. 
		NOTE: This protocol observes fish behavior over a 50 min period that includes a 10 min acclimation phase followed by 4 altering light/dark phases consisting of two 10 min light periods and two 10 min dark periods. The integration time is set to measure behavior for each minute of the 50 min behavioral trial.</li>
	</ol>
	</li>
</ol>
3. Observation of Larval Fish Locomotor and Photomotor Behavior
<ol>
	<li>Place the well plate containing experimental fish in the behavioral recording chamber.</li>
	<li>In the video tracking software, open the tracking protocol developed in step 3.</li>
	<li>In the video tracking viewer, check to make sure that all larvae are visible on the computer screen, that only one individual larva is present in each well, and that individual wells are aligned within the observation areas that were defined in steps 2.1.5 and 2.1.6.</li>
	<li>Click on &#34;Experiment | Execute&#34;. 
	NOTE: The system will prompt the user to provide a name and location to save the observation data.</li>
	<li>Once the name and save location of the observation data have been specified, click on the &#34;Several Live Images&#34; icon to highlight all the pre-defined viewing areas 
	NOTE: This icon is located at the top of the computer screen and appears as a box divided into four smaller squares. Clicking on this icon will highlight all the pre-defined viewing areas.</li>
	<li>Close the panel of the recording chamber and click &#34;Background | Start&#34; on the computer monitor.</li>
</ol>
4. Analyzing Behavioral Data
<ol>
	<li>To retrieve larval fish activity data, open the spreadsheet, which is automatically compiled by the tracking software and is in the folder specified by the user before initiating behavioral trials (Step 3.4).</li>
	<li>Refer to Figures 1A and 1B for representative measurements of naive locomotor activity of unexposed zebrafish and fathead minnow larvae, respectively. Refer to Figures 1C and 1D for PMR calculations, which effectively examine the magnitude of movement difference between light to dark or dark to light transitions.</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57938/57938fig1.jpg" /> 
Figure 1: Example of baseline activity of unexposed zebrafish (A and B) and fathead minnow (C and D). The mean (&#177; SEM) distance swam for zebrafish (A) and fathead minnow (C) is given by dots each representing one-minute intervals of activity. Two dark and two light periods of photomotor responses are measured. The last (a, c, e, and g) and first (b, d, f, and h) minute of each photoperiod are used to calculate PMRs. Photomotor responses of zebrafish (B) and fathead minnow (D) are measured as the change in mean (&#177;SEM) distance traveled between the last minute of an initial photoperiod and the first minute of the following period. <a href="https://www.jove.com/files/ftp_upload/57938/57938fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

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T., Chan, E. C. Y., Gong, Z., Lam, S. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zebrafish+for+drug+toxicity+screening:+bridging+the+in+vitro+cell-based+models+and+in+vivo+mammalian+models.">Zebrafish for drug toxicity screening: bridging the in vitro cell-based models and in vivo mammalian models.</a> Expert Opinion on Drug Metabolism &amp; Toxicology. 7 (5), 579-589 (2011).</li><li>Ankley, G. T., Villeneuve, D. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+fathead+minnow+in+aquatic+toxicology:+past,+present+and+future.">The fathead minnow in aquatic toxicology: past, present and future.</a> Aquatic Toxicology. 78 (1), 91-102 (2006).</li><li>Hutson, L. D., Liang, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Making+an+impact:+zebrafish+in+education.">Making an impact: zebrafish in education.</a> Zebrafish. 6, 119 (2009).</li><li>Hutson, L. D., Liang, J. O., Pickart, M. A., Pierret, C., Tomasciewicz, H. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Making+a+difference:+education+at+the+10th+international+conference+on+zebrafish+development+and+genetics.">Making a difference: education at the 10th international conference on zebrafish development and genetics.</a> Zebrafish. 9 (4), 151-154 (2012).</li><li>Kane, A., Salierno, J., Brewer, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fish+models+in+behavioral+toxicology:+automated+techniques,+updates+and+perspectives.">Fish models in behavioral toxicology: automated techniques, updates and perspectives.</a> Methods in Aquatic Toxicology. 2, 559-590 (2005).</li><li>Rodriguez, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ToxTrac:+a+fast+and+robust+software+for+tracking+organisms.">ToxTrac: a fast and robust software for tracking organisms.</a> Methods in Ecology and Evolution. 9 (3), 460-464 (2018).</li><li>Hamm, J., Wilson, B., Hinton, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Increasing+uptake+and+bioactivation+with+development+positively+modulate+diazinon+toxicity+in+early+life+stage+medaka+(Oryzias+latipes).">Increasing uptake and bioactivation with development positively modulate diazinon toxicity in early life stage medaka (Oryzias latipes).</a> Toxicological Sciences. 61 (2), 304-313 (2001).</li><li>Kristofco, L. A., Haddad, S. P., Chambliss, C. K., Brooks, B. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differential+uptake+of+and+sensitivity+to+diphenhydramine+in+embryonic+and+larval+zebrafish.">Differential uptake of and sensitivity to diphenhydramine in embryonic and larval zebrafish.</a> Environmental Toxicology and Chemistry. 37, 1175-1181 (2018).</li><li>Steele, W. B., Kristofco, L. A., Corrales, J., Saari, G. N., Haddad, S. P., Gallagher, E. P., Kavanagh, T. J., Kostal, J., Zimmerman, J. B., Voutchkova-Kostal, A., Anastas, P. T., Brooks, B. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparative+behavioral+toxicology+of+two+common+larval+fish+models:+exploring+relationships+between+modes+of+action+and+locomotor+responses.">Comparative behavioral toxicology of two common larval fish models: exploring relationships between modes of action and locomotor responses.</a> Science of the Total Environment. 460-461, 1587-1600 (2018).</li></ol>

The authors have nothing to disclose.

When selecting chemical treatment levels for behavioral toxicology studies, several factors must be considered. Caffeine treatment levels in the present study were selected based on upper centile values for predicted environmental exposure scenarios from wastewater effluent16. When possible, we routinely select treatment levels for aquatic toxicology studies using probabilistic exposure assessments of environmental observations19,20,21. A THV, which is calculable for medicines, was also included as a treatment level in the present study. THV values (Eq. 1)22,23 are defined as predicted water concentrations leading to human therapeutic doses (Cmax) of pharmaceuticals in fish23, are inspired from initial plasma modeling efforts24, and are calculated based on blood:water chemical partitioning coefficients (Eq. 2)25.
THV = Cmax / log PBW&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; (Eq. 1)
log PBW = log [(100.73 . log Kow &#183; 0.16)+0.84]&#160;&#160;&#160;&#160; (Eq. 2)
Here, we also select sublethal treatment levels relative to zebrafish and fathead minnow LC50 values. We consider this approach a useful benchmarking procedure for behavioral responses, particularly when comparing thresholds of specific behaviors with a fish model across multiple chemicals. It further facilitates calculations of acute to chronic ratios, which can be diagnostically useful in aquatic toxicology for mechanistic studies and assessments. LC50 values were obtained from preliminary toxicity bioassays following the standardized guidelines given in step 2.1.
In this protocol, we employ common experimental designs and statistical techniques recommended by the US EPA and OECD standardized methods for toxicology studies with fish models. Though we report p values (e.g., &#60;0.01, &#60;0.05, &#60;0.10), significant differences (&#945; = 0.10) in activity levels are identified among treatments using analysis of variance (ANOVA) if normality and equivalence of variance assumptions are met. Dunnett&#39;s or Tukey&#39;s HSD post hoc tests are performed to identify treatment level differences. We select this alpha (&#945; = 0.10) value to reduce type II errors, particularly for early tier assays and when an understanding of biologically important effect size is limited for understudied behavioral endpoints and model organisms26, instead of employing procedures more common in the biomedical sciences for multiple comparisons (e.g., Bonferroni correction for RNA-Seq data)27.&#160;&#160;Future studies are needed to understand variability of these behavioral responses and potentially modify experimental designs (e.g., increase replication) accordingly.
A number of factors can influence behavior of larval fish in addition to chemical exposure. For example, time of day, age, well size, temperature, lighting condition, and volume of exposure solution in each well represent important considerations11,30. For these reasons, precautions should be taken to minimize the effects of external factors that could influence locomotor behavior of the larval fish during experimentation. Behavioral observations should be performed in narrow time windows (3 to 4 h) and across time periods when time of day effects are expected to have minimal influence on larval locomotor behavior11. Additionally, larval fish should be maintained at a consistent temperature (28 &#177; 1 &#176;C for zebrafish and 24 &#177; 1 &#176;C for FHM) and on a defined light/dark cycle in temperature-controlled incubators throughout the exposure period. In addition, the temperature of the laboratory where behaviors are recorded should be maintained to conditions approximating experimental conditions to avoid temperature influences on behaviors. Further, wells used during behavioral observations should be maintained at a consistent volume for each individual fish.
Larval and embryonic zebrafish PMRs have been previously used in the biomedical sciences to identify potential therapeutic targets for novel compounds12,13. This protocol expands on previous behavioral research with zebrafish by utilizing 38 endpoints to investigate chemical bioactivity of environmental contaminants. Although caffeine is a common aquatic contaminant with an understood mechanism of action (MoA), many compounds in commerce lack important mechanistic data. Therefore, this protocol can be employed to gain insight of MoAs for compounds lacking toxicity data, including commercial chemicals39. Furthermore, the protocol provides methods for two of the most commonly used fish models. As noted previously, whereas the zebrafish is a common biomedical fish model that is becoming increasingly popular in ecotoxicology, the fathead minnow is commonly used as an ecological model for environmental assessment applications but has received comparatively less attention in behavioral studies with automated systems compared to the zebrafish.&#160;Though there remains no standardized regulatory methods for fish behavioral toxicology studies, this protocol provides an approach to support future efforts.
Caffeine elicited behavioral responses in each of the fish models at levels that have been detected in the aquatic environment16. Rodriguez-Gil et al. 2018 developed global environmental exposure distributions in aquatic systems based on measured values of caffeine16. Specifically, 95% of predicted wastewater effluent concentrations would fall below the LOECs for the most sensitive behavioral endpoints of zebrafish and fathead minnow in the present study (Table 2). Though several behavioral effects of caffeine were observed in zebrafish (particularly in dark conditions) at environmentally relevant levels, it is unclear whether these behavioral modifications might occur in natural fish populations or result in ecologically important adverse outcomes. Though useful for sensitive, diagnostic screening purposes, larval fish behavioral thresholds may not be representative of other life history stages or of fish in natural populations. Further research is warranted to determine whether similar behavioral response thresholds would occur in nature and be indicative of adverse outcomes at the individual or population levels of biological organization.

Though fish models are increasingly used for biomedical studies, fish have been routinely employed for ecology and physiology studies, to examine contamination of surface waters, and to understand toxicological thresholds of chemicals. Such efforts are important because chemical contamination can impair aquatic ecosystems and jeopardize the quality of source water supplies1,2. Most of the chemicals in commerce, however, lack even basic toxicology information3.
Animal model assays traditionally used in regulatory toxicity testing are resource intensive and cannot provide the high throughput, early tier screening needed for toxicity testing in the 21st century4. Subsequently, there is a growing impetus to adopt and utilize in vitro models that can more rapidly and efficiently screen compounds for biological activities3,5. Though cell based models present many opportunities, they often lack biological complexity, and thus do not account for many important whole organism processes, including metabolism6.
The zebrafish is a common biomedical animal model that is gaining popularity as an alternative model in aquatic toxicology and ecotoxicology7,8. Given their small size, rapid development, and high fecundity, fish models can be used to rapidly and efficiently screen chemicals for bioactivity and toxicity at the whole organism scale9. With the aid of automated tracking software, larval zebrafish behaviors provide enhanced diagnostic utility in screening contaminants for toxicity10,11. Studies in the pharmaceutical sciences have demonstrated that locomotor endpoints are informative of chemical mechanisms of action, can be used to phenotype behaviors, and then may tentatively identify subcellular targets for novel molecules12,13. Whereas the zebrafish is a popular larval fish model in the biomedical sciences, the fathead minnow is a common, ecologically important fish model that is used for ecotoxicology studies and during prospective (e.g., new chemical evaluations) and retrospective (e.g., ambient surface water or wastewater effluent discharge monitoring) environmental assessments. Unfortunately, behavioral responses of larval fathead minnows have received markedly less attention than zebrafish. Our ongoing research with two common larval fish models, the zebrafish and fathead minnow, suggests that larval fish swimming patterns appear unique to anticipated modes or mechanisms of action for diverse chemicals. Thus, behavioral endpoints provide the potential to rapidly and sensitively examine chemicals for toxicity and to identify subcellular targets for industrial chemical and other contaminants, particularly during early tier assessments.
Here, we report a protocol for examining behavioral response profiles in larval fish. We demonstrate these methods using caffeine, a model neurostimulant and a common aquatic contaminant that is introduced to aquatic systems through discharge from wastewater treatments plants following human consumption of foods, beverages, and pharmaceuticals formulated with caffeine14. We examine behavioral responses to caffeine in both larval zebrafish and fathead minnow, including to a sudden change in lighting condition, which is often referred to as a photomotor response (PMR) during pharmaceutical studies with embryonic and larval zebrafish13,15. We further identify effects of caffeine across several locomotor endpoints to develop chemical response profiles for each fish model. Caffeine treatment levels used in this study represent the upper centiles of exposure distributions based on measured environmental values of caffeine16. We also include treatments benchmarked to larval fish LC50 values, and the therapeutic hazard value (THV), a pharmaceutical concentration in water that is anticipated to result in plasma levels in fish consistent with a human therapeutic plasma dose.

<table>
	<tbody>
		<tr>
			<td>ViewPoint Zebrabox</td>
			<td>ViewPoint</td>
			<td></td>
			<td>ZebraLab and ZebraLab platform for automated behavioral observations</td>
		</tr>
		<tr>
			<td>Caffeine</td>
			<td>Sigma-Aldrich</td>
			<td>C0750-100G</td>
			<td>Study chemical</td>
		</tr>
		<tr>
			<td>Incubator</td>
			<td>VWR</td>
			<td>9110589</td>
			<td>Maintains light/dark cycle and temperature for fathead minnow experiments</td>
		</tr>
		<tr>
			<td>Incubator</td>
			<td>Thermo Fisher Scientific</td>
			<td>35824-636</td>
			<td>Maintains light/dark cycle and temperature for zebrafish experiments</td>
		</tr>
		<tr>
			<td>100 ml glass beakers</td>
			<td>VWR</td>
			<td>89000-200</td>
			<td>Zebrafish exposure chambers&#160;</td>
		</tr>
		<tr>
			<td>500 ml glass beakers&#160;</td>
			<td>Pyrex</td>
			<td>EW-34502-03</td>
			<td>Fathead minnow exposure chambers</td>
		</tr>
		<tr>
			<td>5000 &#181;l auto-pipette</td>
			<td>Eppendorf</td>
			<td>Research 5000</td>
			<td>Used to fill individual wells in well plates</td>
		</tr>
		<tr>
			<td>Transfer Pippettes</td>
			<td>VWR</td>
			<td>414-004-004</td>
			<td>Used to transfer study organisms&#160;</td>
		</tr>
		<tr>
			<td>48-well plates</td>
			<td>Fisher Scientific</td>
			<td>08-772-52</td>
			<td>Larval zebrafish behavioral recording chambers</td>
		</tr>
		<tr>
			<td>24-well plates</td>
			<td>VWR</td>
			<td>10062-896</td>
			<td>Larval fathead minnow behavioral recording chambers</td>
		</tr>
		<tr>
			<td>Calcium sulfate dihydrate</td>
			<td>Sigma-Aldrich</td>
			<td>C3771</td>
			<td>For reconstituted hard water</td>
		</tr>
		<tr>
			<td>Magnesium Sulfate</td>
			<td>Sigma-Aldrich</td>
			<td>M7506</td>
			<td>For reconstituted hard water</td>
		</tr>
		<tr>
			<td>Sodium Bicarbonate&#160;</td>
			<td>Sigma-Aldrich</td>
			<td>S5761</td>
			<td>For reconstituted hard water</td>
		</tr>
		<tr>
			<td>Potassium Chloride</td>
			<td>Sigma-Aldrich</td>
			<td>P9333</td>
			<td>For reconstituted hard water</td>
		</tr>
		<tr>
			<td>z-mod recirculating system</td>
			<td>Marine Biotech Systems</td>
			<td></td>
			<td>Recirculating system to maintian zebrafish cultures</td>
		</tr>
		<tr>
			<td>Statistical analysis software</td>
			<td>Sigma Plot&#160;</td>
			<td>Version 13.0</td>
			<td>Used to analyze beahvioral data and produce figures</td>
		</tr>
		<tr>
			<td>Statistical analysis software</td>
			<td>Graphpad Prism</td>
			<td>Prism 5</td>
			<td>Used to produce figures&#160;</td>
		</tr>
		<tr>
			<td>Autosampler/quaternary pumping system</td>
			<td>Agilent Technologies</td>
			<td>Infinity 1260 model&#160;</td>
			<td>Analytical verification of caffeine treatment levels</td>
		</tr>
		<tr>
			<td>Jet stream thermal gradient electrospray ionization source</td>
			<td>Agilent Technologies</td>
			<td></td>
			<td>Analytical verification of caffeine treatment levels</td>
		</tr>
		<tr>
			<td>Triple quadrupole mass analyzer&#160;</td>
			<td>Agilent Technologies</td>
			<td>Model 6420</td>
			<td>Analytical verification of caffeine treatment levels</td>
		</tr>
		<tr>
			<td>10&#160;cm&#160;&#215;&#160;2.1&#160;mm Poroshell 120 SB-AQ column (120&#197;, 2.7)&#160;</td>
			<td>Agilent Technologies</td>
			<td>685775-914T</td>
			<td>Caffiene chromatography&#160;</td>
		</tr>
		<tr>
			<td>MassHunter Optimizer Software&#160;</td>
			<td>Agilent Technologies</td>
			<td></td>
			<td>Determine the ionization mode, monitored transitions, and instrumental parameters for caffeine/caffeine-d9 and paraxanthine/paraxanthine-d6</td>
		</tr>
	</tbody>
</table>

experimental protocol for examining behavioral response profiles in larval fish: application to the neuro-stimulant caffeine

Fish models and behaviors are increasingly used in the biomedical sciences; however, fish have long been the subject of ecological, physiological and toxicological studies. Using automated digital tracking platforms, recent efforts in neuropharmacology are leveraging larval fish locomotor behaviors to identify potential therapeutic targets for novel small molecules. Similar to these efforts, research in the environmental sciences and comparative pharmacology and toxicology is examining various behaviors of fish models as diagnostic tools in tiered evaluation of contaminants and real-time monitoring of surface waters for contaminant threats. Whereas the zebrafish is a popular larval fish model in the biomedical sciences, the fathead minnow is a common larval fish model in ecotoxicology. Unfortunately, fathead minnow larvae have received considerably less attention in behavioral studies. Here, we develop and demonstrate a behavioral profile protocol using caffeine as a model neurostimulant. Though photomotor responses of fathead minnows were occasionally affected by caffeine, zebrafish&#160;were markedly more sensitive for photomotor and locomotor endpoints, which responded at environmentally relevant levels. Future studies are needed to understand comparative behavioral sensitivity differences among fish with age and time of day, and to determine whether similar behavioral effects would occur in nature and be indicative of adverse outcomes at the individual or population levels of biological organization.

Caffeine treatment levels did not appreciably vary during the 96 h experiments with zebrafish and fathead minnows. For example, Table 1 presents analytically verified concentrations of each treatment level. This protocol verified water samples for caffeine treatment levels by isotope-dilution liquid chromatography tandem mass spectrometry (LC-MS/MS) generally following previously reported methods28. The formation of paraxanthine, the primary metabolite of caffeine, was also quantified. A description of these analytical procedures is provided in the supplemental analytical information. Because of the similarities between nominal and analytical verification of treatments, nominal treatment levels are presented throughout the remainder&#160;of this manuscript. Caffeine significantly altered zebrafish and fathead minnow behaviors. However, zebrafish locomotor responses were consistently more sensitive to caffeine than fathead minnows. The most sensitive behavioral endpoints for zebrafish and fathead minnow larvae were affected by caffeine at a concentration of 0.039 mg/L. Table 2 summarizes lowest observed effect concentrations (LOECs) and no observed effect concentrations (NOECs) for each behavioral endpoint in both fish models.
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td colspan="3">Zebrafish&#160;&#160;</td>
			<td colspan="3">Fathead minnow&#160;&#160;</td>
		</tr>
		<tr>
			<td>Endpoint&#160;</td>
			<td>LOEC (mg/L)</td>
			<td>NOEC (mg/L)</td>
			<td>Endpoint&#160;</td>
			<td>LOEC (mg/L)</td>
			<td>NOEC (mg/L)</td>
		</tr>
		<tr>
			<td>Total Distance Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Total Distance Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Total Distance Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Total Distance Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Total Counts Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Total Counts Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Total Counts Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Total Counts Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Distance Dark</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Bursting Distance Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Distance Light</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Bursting Distance Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Counts Dark</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Bursting Counts Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Counts Light</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Bursting Counts Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Duration Dark</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Bursting Duration Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Duration Light</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Bursting Duration Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Distance Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Cruising Distance Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Distance Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Distance Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Counts Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Cruising Counts Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Counts Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Counts Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Duration Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Cruising Duration Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Duration Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Duration Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Distance Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Freezing Distance Dark</td>
			<td>0.039</td>
			<td>0.001</td>
		</tr>
		<tr>
			<td>Freezing Distance Light</td>
			<td>0.039</td>
			<td>0.001</td>
			<td>Freezing Distance Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Counts Dark</td>
			<td>0.412</td>
			<td>0.039</td>
			<td>Freezing Counts Dark</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Counts Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Freezing Counts Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Duration Dark</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Freezing Duration Dark</td>
			<td>56.38</td>
			<td>14.10</td>
		</tr>
		<tr>
			<td>Freezing Duration Light</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Freezing Duration Light</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Dark 1 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Dark 1 PMR</td>
			<td>0.039</td>
			<td>0.001</td>
		</tr>
		<tr>
			<td>Light 1 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Light 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Dark 2 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Dark 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Light 2 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Light 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Dark 1 PMR</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Bursting Dark 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Light 1 PMR</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Bursting Light 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Dark 2 PMR</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Bursting Dark 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Bursting Light 2 PMR</td>
			<td>&#8722;</td>
			<td>193.82</td>
			<td>Bursting Light 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Dark 1 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Dark 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Light 1 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Light 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Dark 2 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Cruising Dark 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Cruising Light 2 PMR</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Cruising Light 2 PMR</td>
			<td>56.38</td>
			<td>14.10</td>
		</tr>
		<tr>
			<td>Freezing Dark 1 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Freezing Dark 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Light 1 PMR</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Freezing Light 1 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Dark 2 PMR</td>
			<td>48.46</td>
			<td>4.07</td>
			<td>Freezing Dark 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
		<tr>
			<td>Freezing Light 2 PMR</td>
			<td>193.82</td>
			<td>48.46</td>
			<td>Freezing Light 2 PMR</td>
			<td>&#8722;</td>
			<td>56.38</td>
		</tr>
	</tbody>
</table>
Table 2: Zebrafish and fathead minnow behavioral NOECs and LOECs for Caffeine. No Observed Effect Concentration (NOEC) and Lowest Observed Effect Concentration (LOEC) (mg/L) values for each of the light/dark swimming activity endpoints and photomotor responses for zebrafish and fathead minnows exposed to caffeine. Dashes indicate that no effects were observed at a particular endpoint across all treatment levels.
Figure 2 presents total locomotor activity and PMRs of zebrafish and fathead minnow following 96 h exposure to caffeine. Fathead minnow larvae PMRs were altered by caffeine at lower treatment levels (0.038 mg/L) than zebrafish, but a markedly larger number of photomotor endpoints were affected in zebrafish. The highest treatment level of caffeine (193.82 mg/L) altered PMR in zebrafish, in which these responses were exactly opposite from controls. At this elevated treatment level, however, PMRs decreased in dark and increased in light conditions.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57938/57938fig2.jpg" /> 
Figure 2: Swimming activity and photomotor responses of zebrafish (A and B) and fathead minnow (C and D) after 96 h exposure to caffeine. The mean (&#177; SEM) distance swam for zebrafish (A) and fathead minnow (C) is given by dots each representing 1-min intervals of activity. Photomotor responses of zebrafish (B) and fathead minnow (D) are measured as the change in mean (&#177; SE) total distance traveled between the last minutes of an initial photoperiod and the first minute of the following period. Two dark and two light period photomotor responses were measured. A total of 24 (4 replicates each of 6 larvae) zebrafish and 12 (3 replicates each of 4 larvae) fathead minnows were used for behavioral observation. *p &#60;0.10; ** p &#60;0.05; *** p &#60;0.01. <a href="https://www.jove.com/files/ftp_upload/57938/57938fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
In addition to measuring larval PMRs, light and dark locomotor activity was analyzed across three speed thresholds for distance moved, number of movements, and duration of movements. This data is used to develop behavioral response profiles for caffeine (Figure 3, Supplemental Figure 1). In both of the fish models, caffeine inhibited activity at all significantly affected locomotor endpoints. Both fish models demonstrated increased activity at the bursting speed thresholds following exposure to caffeine, though not significantly. Similar to the results of the PMR observations, caffeine effected a greater number of zebrafish locomotor endpoints. In fact, caffeine significantly altered several locomotor responses under dark conditions at environmentally realistic levels below the THV. However, fathead minnow locomotor activity was not significantly affected under light conditions by any treatment level.
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/57938/57938fig3.jpg" /> 
Figure 3: Response profiles of larval zebrafish and fathead minnows after 96 h exposure to caffeine. Mean zebrafish dark (A) and light (B) swimming activity compared to mean fathead minnow dark (C) and light (D) activity after 96 h exposure to caffeine. Plotted data represents activity over two 10 min dark photoperiods and two 10 min light photoperiods for each fish model. Data is normalized to control, which is represented at the 0 axis in each figure. Behavioral parameters include distance swam, number of movements (counts), and duration of each movement across 3 speed levels, bursting (&#62;20 mm/s), cruising (5&#8211;20 mm/s), and freezing (&#60;5 mm/s). In addition to movement patterns at each of the speed thresholds, total distance swam, and total number of movements is represented. &#8593; represents a significant increase in activity in comparison to control and &#8595; indicates a significant decrease in activity in comparison to control. A total of 24 (4 replicates each of 6 larvae) zebrafish and 12 (3 replicates each of 4 larvae) fathead minnow where used in behavioral observations for each group. *p &#60;0.10; ** p &#60;0.05; *** p &#60;0.01. <a href="https://www.jove.com/files/ftp_upload/57938/57938fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Supplemental Figure 1: Photomotor responses of zebrafish (A and B) and fathead minnow (C and D) across three speed thresholds. Zebrafish (A, B, and C) and fathead minnow larvae (D, E, and F) photomotor responses across three speed thresholds (Freezing: 20 mm/s) after 96hr exposure to caffeine. Photomotor responses of zebrafish and fathead minnow are measured as the change in mean (&#177;SE) total distance traveled between the last minutes of an initial photoperiod and the first minute of the following period. Two dark and two light period photomotor responses were measured. A total of 24 (4 replicates each of 6 larvae) zebrafish and 12 (3 replicates of 4 larvae) fathead minnows were used for behavioral observation. *p &#60;0.01 <a href="https://www.jove.com/files/ftp_upload/57938/Steele_et_al_JoVE_Supplemental_Figure_1_01302018.pptx">Please click here to download this file.</a>

Watch this Scientific Journal Video about Experimental Protocol for Examining Behavioral Response Profiles in Larval Fish: Application to the Neuro-stimulant Caffeine at JoVE.com

Experimental Protocol for Examining Behavioral Response Profiles in Larval Fish: Application to the Neuro-stimulant Caffeine

Here, we present a protocol to examine larval zebrafish and fathead minnow locomotor activities and photomotor responses (PMR) using an automated tracking software. When incorporated in common toxicology bioassays, analyses of these behaviors provide a diagnostic tool to examine chemical bioactivity. This protocol is described using caffeine, a model neurostimulant.

Fish models and behaviors are increasingly used in the biomedical sciences; however, fish have long been the subject of ecological, physiological and ...

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JoVE Journal

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11.1K Views.  Baylor University. Here, we present a protocol to examine larval zebrafish and fathead minnow locomotor activities and photomotor responses (PMR) using an automated tracking software. When incorporated in common toxicology bioassays, analyses of these behaviors provide a diagnostic tool to examine chemical bioactivity. This protocol is described using caffeine, a model neurostimulant.

Video: Experimental Protocol for Examining Behavioral Response Profiles in Larval Fish: Application to the Neuro-stimulant Caffeine

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 ...

Experimental Protocol for Manipulating Plant-induced Soil Heterogeneity

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as plant-soil feedbacks (PSF) have large effects on plant performance, and create environmental heterogeneity that depends on the community composition. Understanding the importance of PSF for plant community assembly necessitates understanding of the role of heterogeneity in PSF, in addition to mean PSF effects. Here, we describe a protocol for manipulating plant-induced soil heterogeneity. Two example experiments are presented: (1) a field experiment with a 6-patch grid of soils to measure plant population responses and (2) a greenhouse experiment with 2-patch soils to measure individual plant responses. Soils can be collected from the zone of root influence (soils from the rhizosphere and directly adjacent to the rhizosphere) of plants in the field from conspecific and heterospecific plant species. Replicate collections are used to avoid pseudoreplicating soil samples. These soils are then placed into separate patches for heterogeneous treatments or mixed for a homogenized treatment. Care should be taken to ensure that heterogeneous and homogenized treatments experience the same degree of soil disturbance. Plants can then be placed in these soil treatments to determine the effect of plant-induced soil heterogeneity on plant performance. We demonstrate that plant-induced heterogeneity results in different outcomes than predicted by traditional coexistence models, perhaps because of the dynamic nature of these feedbacks. Theory that incorporates environmental heterogeneity influenced by the assembling community and additional empirical work is needed to determine when heterogeneity intrinsic to the assembling community will result in different assembly outcomes compared with heterogeneity extrinsic to the community composition.

Understanding the role of environmental heterogeneity in species coexistence has typically focused on types of heterogeneity that are extrinsic to the community&#8217;s species composition. We provide novel detailed methods for creating soil heterogeneity treatments using soils subject to plant-soil feedback conditioning, or heterogeneity intrinsic to the community composition.

Coexistence theory has often treated environmental heterogeneity as being independent of the community composition; however biotic feedbacks such as ...

A Fish-feeding Laboratory Bioassay to Assess the Antipredatory Activity of Secondary Metabolites from the Tissues of Marine Organisms

Marine chemical ecology is a young discipline, having emerged from the collaboration of natural products chemists and marine ecologists in the 1980s with the goal of examining the ecological functions of secondary metabolites from the tissues of marine organisms. The result has been a progression of protocols that have increasingly refined the ecological relevance of the experimental approach. Here we present the most up-to-date version of a fish-feeding laboratory bioassay that enables investigators to assess the antipredatory activity of secondary metabolites from the tissues of marine organisms. Organic metabolites of all polarities are exhaustively extracted from the tissue of the target organism and reconstituted at natural concentrations in a nutritionally appropriate food matrix. Experimental food pellets are presented to a generalist predator in laboratory feeding assays to assess the antipredatory activity of the extract. The procedure described herein uses the bluehead, Thalassoma bifasciatum, to test the palatability of Caribbean marine invertebrates; however, the design may be readily adapted to other systems. Results obtained using this laboratory assay are an important prelude to field experiments that rely on the feeding responses of a full complement of potential predators. Additionally, this bioassay can be used to direct the isolation of feeding-deterrent metabolites through bioassay-guided fractionation. This feeding bioassay has advanced our understanding of the factors that control the distribution and abundance of marine invertebrates on Caribbean coral reefs and may inform investigations in diverse fields of inquiry, including pharmacology, biotechnology, and evolutionary ecology.

This bioassay employs a model predatory fish to assess the presence of feeding-deterrent metabolites from organic extracts of the tissues of marine organisms at natural concentrations using a nutritionally comparable food matrix.

Marine chemical ecology is a young discipline, having emerged from the collaboration of natural products chemists and marine ecologists in the 1980s with ...

Experimental Protocol for Biodiesel Production with Isolation of Alkenones as Coproducts from Commercial Isochrysis Algal Biomass

The need to replace petroleum fuels with alternatives from renewable and more environmentally sustainable sources is of growing importance. Biomass-derived biofuels have gained considerable attention in this regard, however first generation biofuels from edible crops like corn ethanol or soybean biodiesel have generally fallen out of favor. There is thus great interest in the development of methods for the production of liquid fuels from domestic and superior non-edible sources. Here we describe a detailed procedure for the production of a purified biodiesel from the marine microalgae Isochrysis. Additionally, a unique suite of lipids known as polyunsaturated long-chain alkenones are isolated in parallel as potentially valuable coproducts to offset the cost of biodiesel production. Multi-kilogram quantities of Isochrysis are purchased from two commercial sources, one as a wet paste (80% water) that is first dried prior to processing, and the other a dry milled powder (95% dry). Lipids are extracted with hexanes in a Soxhlet apparatus to produce an algal oil (&#34;hexane algal oil&#34;) containing both traditional fats (i.e., triglycerides, 46-60% w/w) and alkenones (16-25% w/w). Saponification of the triglycerides in the algal oil allows for separation of the resulting free fatty acids (FFAs) from alkenone-containing neutral lipids. FFAs are then converted to biodiesel (i.e., fatty acid methyl esters, FAMEs) by acid-catalyzed esterification while alkenones are isolated and purified from the neutral lipids by crystallization. We demonstrate that biodiesel from both commercial Isochrysis biomasses have similar but not identical FAME profiles, characterized by elevated polyunsaturated fatty acid contents (approximately 40% w/w). Yields of biodiesel were consistently higher when starting from the Isochrysis wet paste (12% w/w vs. 7% w/w), which can be traced to lower amounts of hexane algal oil obtained from the powdered Isochrysis product.

Experimental Protocol for Biodiesel Production with Isolation of Alkenones as Coproducts from Commercial Isochrysis Algal Biomass

Detailed methods are presented for the production of biodiesel along with the co-isolation of alkenones as valuable coproducts from commercial Isochrysis microalgae.

The need to replace petroleum fuels with alternatives from renewable and more environmentally sustainable sources is of growing importance. ...

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

Global warming and eutrophication make some aquatic ecosystems behave as true bioreactors that trigger rapid and massive cyanobacterial growth; this has relevant health and economic consequences. Many cyanobacterial strains are toxin producers, and only a few cells are necessary to induce irreparable damage to the environment. Therefore, water-body authorities and administrations require rapid and efficient early-warning systems providing reliable data to support their preventive or curative decisions. This manuscript reports an experimental protocol for the in-field detection of toxin-producing cyanobacterial strains by using an antibody microarray chip with 17 antibodies (Abs) with taxonomic resolution (CYANOCHIP). Here, a multiplex fluorescent sandwich microarray immunoassay (FSMI) for the simultaneous monitoring of 17 cyanobacterial strains frequently found blooming in freshwater ecosystems, some of them toxin producers, is described. A microarray with multiple identical replicates (up to 24) of the CYANOCHIP was printed onto a single microscope slide to simultaneously test a similar number of samples. Liquid samples can be tested either by direct incubation with the antibodies (Abs) or after cell concentration by filtration through a 1- to 3-&#956;m filter. Solid samples, such as sediments and ground rocks, are first homogenized and dispersed by a hand-held ultrasonicator in an incubation buffer. They are then filtered (5 - 20 &#956;m) to remove the coarse material, and the filtrate is incubated with Abs. Immunoreactions are revealed by a final incubation with a mixture of the 17 fluorescence-labeled Abs and are read by a portable fluorescence detector. The whole process takes around 3 h, most of it corresponding to two 1-h periods of incubation. The output is an image, where bright spots correspond to the positive detection of cyanobacterial markers.

Experimental Protocol for Detecting Cyanobacteria in Liquid and Solid Samples with an Antibody Microarray Chip

The presence of cyanobacterial toxins in fresh water reservoirs for human consumption is a major concern for water management authorities. To evaluate the risk of water contamination, this article describes an protocol for the in-field detection of cyanobacterial strains in liquid and solid samples by using an antibody microarray chip.

Global warming and eutrophication make some aquatic ecosystems behave as true bioreactors that trigger rapid and massive cyanobacterial growth; this has ...

Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of scientific publications address microplastic pollution of the sea surface. The protocol below describes the methodology for sampling, sample preparation, separation and chemical identification of microplastic particles. A manta net fixed on an &#187;A frame&#171; attached to the side of the vessel was used for sampling. Microplastic particles caught in the cod end of the net were separated from samples by visual identification and use of stereomicroscopes. Particles were analyzed for their size using an image analysis program and for their chemical structure using ATR-FTIR and micro FTIR spectroscopy. The described protocol is in line with recommendations for microplastics monitoring published by the Marine Strategy Framework Directive (MSFD) Technical Subgroup on Marine Litter. This written protocol with video guide will support the work of researchers that deal with microplastics monitoring all over the world.

The protocol below describes the methodology for: microplastics sampling on the sea surface, separation of microplastic and chemical identification of particles. This protocol is in line with the recommendations for microplastics monitoring published by the MSFD Technical Subgroup on Marine Litter.

Microplastic pollution in the marine environment is a scientific topic that has received increasing attention over the last decade. The majority of ...

Development of New Methods for Quantifying Fish Density Using Underwater Stereo-video Tools

The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and estimating fish abundance. We developed and implemented a rotating stereo-video camera tool that covers a full 360 degrees of sampling, which maximizes sampling effort compared to stationary camera tools. A variety of studies have detailed the ability of static, stereo-camera systems to obtain highly accurate and precise measurements of fish; the focus here was on the development of methodological approaches to quantify fish density using rotating camera systems. The first approach was to develop a modification of the metric MaxN, which typically is a conservative count of the minimum number of fish observed on a given camera survey. We redefine MaxN to be the maximum number of fish observed in any given rotation of the camera system. When precautions are taken to avoid double counting, this method for MaxN may more accurately reflect true abundance than that obtained from a fixed camera. Secondly, because stereo-video allows fish to be mapped in three-dimensional space, precise estimates of the distance-from-camera can be obtained for each fish. By using the 95% percentile of the observed distance from camera to establish species-specific areas surveyed, we account for differences in detectability among species while avoiding diluting density estimates by using the maximum distance a species was observed. Accounting for this range of detectability is critical to accurately estimate fish abundances. This methodology will facilitate the integration of rotating stereo-video tools in both applied science and management contexts.

We describe a new method for counting fishes, and estimating relative abundance (MaxN) and fish density using rotating stereo-video camera systems. We also demonstrate how to use distance from camera (Z distance) to estimate species-specific detectability.

The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and ...

Experimental Protocol for Detecting Mitochondrial Function in Hepatocytes Exposed to Organochlorine Pesticides

This paper presents detailed methods on detecting hepatic mitochondrial function for a better understanding the cause of metabolic disorders caused by environmental organochlorine pesticides (OCPs) in hepatocytes. HepG2 cells were exposed to &#946;-hexachlorocyclohexane (&#946;-HCH) for 24 h at an equivalent dose of internal exposure in general population. Ultrastructure in hepatocytes was examined by transmission electron microscopy (TEM) to show the damage of mitochondria. Mitochondrial function was further evaluated by mitochondrial fluorescence intensity, adenosine 5'-triphosphate (ATP) levels, oxygen consumption rate (OCR) and mitochondrial membrane potential (MMP) in HepG2 cells incubated with &#946;-HCH. The mitochondria fluorescence intensity after stained by mitochondrial green fluorescent probe was observed with a fluorescence microscopy. The luciferin-luciferase reaction was used to determine ATP levels. The MMP was detected by the cationic dye JC-1 and analyzed under flow cytometry. OCR was measured with an extracellular flux analyzer. In summary, these protocols were used in detecting mitochondrial function in hepatocytes with to investigate mitochondria damages.

Understanding the influence of environmental organochlorine pesticides (OCPs) on mitochondrial function in hepatocytes is important in exploring the mechanism of OCPs causing metabolic disorders. This paper presents detailed methods on detecting hepatic mitochondrial function.

This paper presents detailed methods on detecting hepatic mitochondrial function for a better understanding the cause of metabolic disorders caused by ...

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current measures to combat such pathogens have proved too conservative and, thus, not sufficiently effective, and they can potentially pose environmental risks. Therefore, it is extremely necessary to identify host-resistance factors to assist in controlling plant diseases naturally through the identification of resistant germplasm, the isolation and characterization of resistance genes, and the molecular breeding of resistant cultivars. In this regard, there is need to establish an accurate, rapid, and large-scale inoculation method to breed and develop plant resistance genes. The rice blast fungal pathogen Magnaporthe grisea causes severe disease symptoms and yield losses. Recently, M. grisea has emerged as a model organism for studying the mechanisms of plant-fungal pathogen interactions. Hence, we report the development of a plant virulence test method that is specific for M. grisea. This method provides for both spray inoculation with a conidial suspension and wounding inoculation with mycelium cubes or droplets of conidial suspension. The key step of the wounding inoculation method for detached rice leaves is to make wounds on plant leaves, which avoids any interference caused by host penetration resistance. This spray/wounding protocol contributes to the rapid, accurate, and large-scale screening of the pathotypes of M. grisea isolates. This integrated and systematic plant infection method will serve as an excellent starting point for gaining a broad perspective of issues in plant pathology.

The Plant Infection Test: Spray and Wound-Mediated Inoculation with the Plant Pathogen Magnaporthe Grisea

Here, we present a protocol to test plant virulence with the plant pathogen Magnaporthe grisea. This report will contribute to the large-scale screening of the pathotypes of fungi isolates and serve as an excellent starting point for understanding the resistant mechanisms of plants during molecular breeding.

Plants possess a powerful system to defend themselves against potential threats by pathogenic fungi. For agriculturally important plants, however, current ...

An Experimental Protocol for Studying Mineral Effects on Organic Hydrothermal Transformations

Organic-mineral interactions are widely occurring in hydrothermal environments, such as hot springs, geysers on land, and the hydrothermal vents in the deep ocean. Roles of minerals are critical in many hydrothermal organic geochemical processes. Traditional hydrothermal methodology, which includes using reactors made of gold, titanium, platinum, or stainless-steel, is usually associated with the high cost or undesired metal catalytic effects. Recently, there is a growing tendency for using the cost-effective and inert quartz or fused silica glass tubes in hydrothermal experiments. Here, we provide a protocol for carrying out organic-mineral hydrothermal experiments in silica tubes, and we describe the essential steps in the sample preparation, experimental setup, products separation, and quantitative analysis. We also demonstrate an experiment using a model organic compound, nitrobenzene, to show the effect of an iron-containing mineral, magnetite, on its degradation under a specific hydrothermal condition. This technique can be applied to study complex organic-mineral hydrothermal interactions in a relatively simple laboratory system.

Earth-abundant minerals play important roles in the natural hydrothermal systems. Here, we describe a reliable and cost-effective method for the experimental investigation of organic-mineral interactions under hydrothermal conditions.

Organic-mineral interactions are widely occurring in hydrothermal environments, such as hot springs, geysers on land, and the hydrothermal vents in the ...