The authors would like to thank Sam Noonan for his help and advice, Sven Uthicke for the use of the initial respirometry chambers, Ben Shelab for his engineering illustration, and the Australian Institute of Marine Science workshop for bespoke machining of respirometry chamber adaptors and holders. The corals were collected under the following Great Barrier Reef Marine Park permit to AIMS G12/ 35236.1. Corals do not require ethics permits.

1. Setup of equipment and corals within the respiration chambers
NOTE: Reproductively ready corals (i.e., those that had pinkish pigmented egg/sperm bundles visible from fragmented branchlets from the species Acropora tenuis colonies) were dislodged from the reef at Magnetic Island (19&#176; 6.249&#39;S; 146&#176; 51.728&#39;E) on the day of a full moon in October 2018 (permit number: G12/35236.1), collected, and brought into the laboratory for coral spawning, where juvenile corals were bred and grown.
<ol>
	<li>On the day of measurements, connect the two water bath plates using blue polypipe and connectors (see Table of Materials; Figure 1 [5], Figure 2A,B). These will serve as incubators after connection with the blue polypipe to the water heater/chiller. Ensure that the motor plate can clearly be seen through the transparent water bath plates when the respirometry chambers are not in place.</li>
	<li>Connect the two hoses to the water heater/chiller (see Table of Materials). Switch on the water heater/chiller and then set the desired experimental temperature (27 &#176;C or 31 &#176;C).</li>
	<li>Connect the base of the water bath (step 1.1) to the base motor plate with the magnetic gears (Figure 1 [6, 7] and Figure 3A), and then connect this assembly to a power source (Figure 3B). Turn on the power source to activate the gears, which will activate the stirrer bars in the chambers.</li>
	<li>Modulate the water flow as required (e.g., continuous, gentle flow set at 75 L/h with slow stirring at 30 rpm) using the valve connector knobs (Figure 3C).</li>
	<li>To assemble the respirometry chamber, add the magnetic bead (Figure 1 [1.5]) to the glass chamber (Figure 1 [1.6]), and then the opaque plastic flow-through stand base (Figure 1 [1.4]) into the glass chamber (Figure 4A). The size of the chamber and the magnetic bead will depend on the organism and study system of interest. 
	NOTE: There are holes in the plastic base to allow for water flow and circulation from the movement of the magnetic bead in the bottom.</li>
	<li>Glue the coral using aquarium glue (see Table of Materials) to the black zip-tie placed in the plastic base (Figure 4B-D). To do this, first, glue the coral juvenile to a piece of black plastic, and then glue this piece to the plastic base. Once the coral is affixed securely (curing of the glue is almost instantaneous), screw the lid with the O-ring (Figure 4A) onto the glass chamber. Perform these actions underwater in a separate basin to make sure that no air is within the respirometry chamber. 
	NOTE: The volume of water in the respirometer (i.e., effective volume = 1.5 ml) was determined through the complete submersion of the chamber underwater. The assumption is that, relative to the water volume, the displacement from the mass/density of the very small coral is negligible. The 1.5 mL microcentrifuge tube is shown here for scale (Figure 4A).</li>
	<li>Firmly place the chambers into the water baths (Figure 5A). Ensure that the glass chambers are in contact with the temperature-controlled water for the experiment.</li>
	<li>Connect the O2 fiber optic cables (see Table of Materials) so they are in contact with the oxygen sensor spots (hereafter referred to as spots; see Table of Materials) by inserting them into the hole drilled into the side of the lid chambers. These small spots are oxygen-sensitive and will detect and transmit the signal from within the chamber through the fiber optic cable.
	<ol>
		<li>Add plumbing tape (white thin self-sealing tape) to make the cable fit snuggly and to let it remain firmly inside the water chamber. Ensure that the individual coral can be seen (as seen in Figure 5B), with brown tentacles facing up, inside the chamber (Figure 5B, Video 1). 
		NOTE: Cost estimates of the components in the apparatus are provided in Table 1.</li>
	</ol>
	</li>
</ol>
2. Standard operating procedure for measuring respiration using the O2 system
<ol>
	<li>Open the oxygen measurement software (see Table of Materials).</li>
	<li>Measure the temperature of the room where the calibration will be performed. This will be needed later for the calibration stage (step 2.8).</li>
	<li>Assemble the optical sensors and caps. To do this, connect all the fiber optics to the matching port in the O2 module. Make sure to match cap 1 with sensor 1, cap 2 with sensor 2, and so on.</li>
	<li>To set up the chambers for calibration, first moisten a piece of clean sponge with a bit of reverse osmosis (RO) water and insert it into each chamber. 
	NOTE: The sponge should not drip, only be moist. It may drip on the fiber optic spot. Ensure that the spot is not wet before proceeding to the next step.</li>
	<li>Place the chambers upside down with the matching fiber optic (Figure 6). This will allow unscrewing the chamber without touching the fiber optic and adding the sodium sulfite for the 0% calibration.</li>
	<li>Check the signal of each sensor before the start of the calibration. Go through all the tabs in the software interface and check the signal value (top left corner) (Figure 7A), ensuring that they do not vary significantly. Check the O2 manual for the acceptable values for the experimental setup (depending on the organism and conditions of interest). For this specific setup, at a room temperature of 25.3 &#176;C, an FTC (oxygen sensor spot flow through cell normal range) of 20.59 with the signal at 179.5 is acceptable.</li>
	<li>Open Program and check the settings in the software to confirm they are correct as outlined below. If the pop-up window doesn&#39;t show up immediately after opening the program, this can be done by clicking the Settings button in the left bottom corner of the software interface.</li>
	<li>Check that the external temperature sensor is activated (Figure 7B). Change the setting to Fixed temperature (Figure 7C). Then, add the room temperature value and click copy setting to all other channels.</li>
	<li>Change the setting to Reduce Signal Drift (Figure 7C). Then, select Sensor Settings and select level 2. Otherwise, if using small volumes, the drift will be so high that it will be difficult to calibrate.</li>
	<li>Check the general settings of the channels. Press Ok if adequate. Click copy settings to all the channels, and then click ok.</li>
	<li>Calibrate the sensors. For channel 1 calibration, go to the Channel 1 tab and press the Calibrate button. Select 2-Point in Water or Humid Air.</li>
	<li>For the &#34;air&#34; calibration, dip a piece of foam in water, place it inside the chamber, and wait for the signal to stabilize (see the before and after air calibration images). When stable, press &#34;set air&#34;. Click air &#62; Calibrate &#62; set air.</li>
	<li>Set the 0% and 100% calibration (Figure 7D). Remove the chamber from the cap and place it in the next cap so that the air calibration signal is ready when the 0% calibration in the first sensor is finished. Use a transfer pipette and fill the cap with 2% sodium sulfite. Wait for the signal to stabilize. 
	NOTE: The signal usually takes more time to stabilize compared to the air calibration. If a warning message appears that says that the &#34;values are out of typical range&#34;, make sure the sodium sulfite is fresh. Repeat the same calibration process for all the channels. Prepare the sodium sulfite by adding 2 g in 100 mL of RO water.</li>
	<li>Once the calibration is completed, rinse the respiration chambers well and dry the chambers and caps. Make sure there is no water in the fiber optic hole.</li>
	<li>Place the organism (single coral juveniles, in this example) inside the respiration chambers and close with lids. When placing the lids, make sure to do it when the chambers are fully submerged and there is absolutely no air inside.</li>
	<li>Place the chambers firmly in the stirring plate and connect the fiber optics.</li>
	<li>Turn on the power supply. Make sure that the water inside the chambers gets mixed completely. Set the temperature in the chiller/heater to the chosen experimental temperatures.</li>
	<li>Turn the pump and the heater on (steps 1.2 and 1.4).</li>
	<li>Press log on the O2 measurement software interface to start recording.</li>
</ol>

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The authors have nothing to disclose.

This work outlines the construction of a custom-made micro-respirometry setup that can be used to quantify the amount of oxygen consumed and produced by small sessile aquatic organisms. The critical components of this protocol include the setup of the chambers, including the spots, and the calibration of the low signal using the respR package, in which a low signal can be defined as rates typified by shallow or noisy slopes. The custom chamber and its setup allows for the detection of even low signals, whilst the use of the R package helps safeguard against issues in which the occurrence of shallow or noisy slopes could lead to the misinterpretation of results (e.g., false-positives).
Potential modifications that will be needed for other users include the securing of the organism of interest within the custom-made chamber. In this case, a small, rigid zip-tie and aquarium glue were used to secure the single juvenile to the plastic base, which was then glued to the tie. It should be noted that, for this experiment, coral juveniles were settled on black plastic sheeting. This plastic allowed for the easy removal of the coral juveniles, which effectively slid off the plastic, so as not to physically harm them during the removal. Coral juveniles affix to the substrate they settle on, so it is recommended to settle them on similar plastic material, using an artificial peptide16 to facilitate their removal for the gluing process. To further minimize handling stress and impact on the respiration response, it is recommended to allow the corals mounted to zip-ties to acclimate for 1-2 weeks, as is common in many adult coral stress experiments. Other modifications may be needed to secure the organism above the spot in the lid and to allow for water circulation. Another key troubleshooting step involves signal detection, specifically on the slope of the oxygen time-series where rates should be determined. Ultimately, this comes down to a combination of using good judgment to exclude obviously unstable data, and the functions within respR to allow rates to be extracted from either consistently chosen regions or automatically by identifying linear regions of the data. Further examples of how to do this are available on the respR website.
This method was developed to extend measurements of the lower limit of respiration to extremely small, sessile marine invertebrates. The obvious limitation is that this protocol may be more prone to false-positives compared to protocols designed for larger biomasses. However, given this was the point of the design-to measure these lower limits-this has been factored into the design, and the procedure can be used with the respR package to better guard against false-positives. It is also important to acknowledge that other systems exist for measuring respiration30, and the measurement of small organisms, including respirometry on individual copepods31 in smaller volumes than this (~0.5-1 mL), but are either expensive or lack specific components (stirring ability). However, this system is open-source and of relative low-cost compared to commercial systems (e.g., Core Microplate system). This system also incorporates key methodological considerations like stirring, which other systems may lack. The internal stirring bar feature is essential to replicate the natural water mixing of many marine organisms (e.g., copepods via swimming), that is often not possible and may render the data largely unusable. In contrast, other mixing methods available involve placing the whole respirometer on a giant rocker bench, which requires additional equipment and has limited success in mixing, or mixing via vibration, which can cause disturbance to the organism. For this reason, this is the only system that can perform respirometry on juvenile corals or other very small sessile organisms. For reference, the size range of the specimens included here ranged from 2.1 to 3.6 polyps (corresponding to only a few months old), with a minimum to maximum mean area of 1.3 to 4.5 mm2.
Respirometry is a fundamental measure in ecological studies, and many methods exist for this purpose. Most of these existing methods, however, target high biomass samples, including whole fish, coral fragments, or seagrasses32,33,34. This method is the first to use individual coral juveniles. In addition, there are many potential applications for this method, as it provides key physiological information about the functioning of the organism. This can be important for studies looking to characterize baseline health estimates35, understand the role of acute or long-term stress during coral ontogeny such as heat stress36, or to provide thresholds which managers can set to help protect and improve the health of coral reefs37. Given that the coral is a holobiont and the symbiont community is relatively flexible at this stage and throughout the first year of life38, it would be interesting to pair respirometry data with changes in communities over time, to fully contextualize the functioning of the organism as a whole. Importantly, this method contributes to &#39;open science&#39; techniques that help to provide an outline for creating custom experimental setups that can be shared, improved, and standardized openly.

Respiration is a critical biological measurement that signals the overall metabolic activity of an organism, but like other critical traits (growth), is hard to measure in small organisms1. Respiration can be defined as the oxidation of organic molecules through the use of oxygen. This process generates the chemical energy needed for cellular function (i.e., metabolism), which is essential for the survival of organisms. Alternatively, anaerobic metabolism results in oxygen debt2. Respiration rates can be determined using optodes that measure the usage (and therefore the decrease) of oxygen concentration over time in a closed chamber, a practice generally known as respirometry3. Given that the majority of organisms do not store oxygen, the rate of metabolism can be inferred through the direct correlation between respiration and carbon usage. Because of this, respiration rates can be converted to daily carbon usage, which informs critical metabolic functions like growth, reproduction, and the ability to maintain metabolic homeostasis during times of environmental stress4,5, including heatwave conditions that generally lead to stress or bleaching in corals.
Coral reefs are declining globally at an accelerating rate. The coral animal houses a consortium of partners (including dinoflagellate Symbiodiniaceae, fungi, bacteria, and viruses), collectively referred to as the &#34;holobiont&#34;6. As ocean temperatures rise, corals, and therefore coral reefs, are under increasing pressure to survive, as high temperatures lead to the loss of the dinoflagellate Symbiodiniaceae (hereafter symbionts), a phenomenon known as bleaching7. Many nutrients are otherwise unavailable to corals in oligotrophic tropical waters, including inorganic nitrogen and phosphorus8. To cope, corals form an obligate nutritional symbiosis with their dinoflagellate symbionts (Symbiodiniaceae), which provide the majority of the nutrients needed by the coral host to survive and deposit their calcium carbonate skeletons9. A functioning symbiosis may be characterized by high levels of carbon sharing between partners10,11, and the regulation of symbiosis involves a dynamic homeostasis12.
During heat stress, this dynamic regulation and communication are disrupted, resulting in dysbiosis and bleaching (reviewed in reference13). Metabolic measurements, such as photosynthesis and respiration, therefore, hold the potential to elucidate both the healthy and unregulated, dysbiotic states of corals, and accurately measuring these processes across ontogeny is critical to understanding organismal functioning. This is particularly important as the frequency and magnitude of mass bleaching events increase, with the potential to influence changes in nutrient sharing from the symbionts, where carbon transfer has been found to decrease as temperatures increase14. This could be due to directed mechanisms by the symbiont sequestering nutrients or from hard-physiological trade-offs (increased thermal tolerance but a decrease in host survival15,16,17). Disruptions in symbiosis may stem from both the symbiont and the host, although a leading factor is likely the cellular malfunctioning of the symbiont18. However, stress caused by increases in seawater temperatures destabilizes this symbiosis; carbon sharing from symbiont to host is diminished19,20, and starvation of the coral may ensue. This may be reflected in diminished lipid and carbohydrate stores in corals due to increased host usage (&#34;increased catabolism of fixed carbon&#34;), likely due to diminished sharing by symbionts11. Alongside the contribution of photosynthesis and respiration of the corals&#39; symbionts, respiration of the coral animal is an important measure to understand coral health, the impacts of bleaching and nutrient exchange between these partners, and the growth of the holobiont, a phenotype relevant for surviving environmental change8,21,22. Finally, given many corals are symbiotic, the use of respirometry to characterize photosynthesis in addition to respiration is particularly useful for contextualizing P:R ratios and understanding if the symbiosis is stable or not (e.g., reference23).
Environmental changes, therefore, cause shifts in the energy budgets of the coral and its symbionts, leading to differences in growth14. To cope, the coral host may increase respiration and lipid usage to meet its metabolic demands; heat stress can reduce net productivity by 60% due to this increased respiration14, as measured by a change in dissolved oxygen. Symbiodiniaceae&#160;may also increase nitrogen assimilation and carbon retention14,24, and then use these reserves to shift energy toward their own repair and protective mechanisms25,26. The balance of N and C is important for regulating growth, and P in particular27, which may manifest as a dynamic regulation of symbiont abundance. Indeed, evidence collected from corals across large reef expanses (&#62;1,000 km) suggests that hosts have the capacity to limit symbiont growth through the regulation of P, although this varies by coral species27.
Taken together, these studies suggest a gain of heat tolerance with a concomitant decrease in either the production or translocation of nutrients (i.e., the propensity for symbiosis) due to environmental changes. Powerful single-juvenile methods, such as quantifying oxygen use via micro-respirometry, should therefore be used to understand the fundamental mechanisms relating to metabolism and then applied to conservation questions such as understanding heat tolerance acquisition. This is presented here as a micro-respirometry tool for physiological measures, intended to query the nutritional relationship between coral juveniles and their algal symbionts, but suitable for other small marine organisms.
The use or production of oxygen by organisms can be measured by placing them into individual, hermetically sealed respirometry chambers or &#39;respirometers&#39; (hereafter chambers), where oxygen change is measured using optodes3. Optodes are probes that measure oxygen concentration using light pulses, and logging measurements over time allows the calculation of respiration and/or photosynthesis rates. In practice, measuring respiration is similar to measuring photosynthesis in corals, except that the corals are incubated in total darkness. Subtracting the total daily respiration of the coral and symbionts from the total daily photosynthesis results in an oxygen differential (oxygen delta)2,3. Generally, organisms use more oxygen than they produce, resulting in a deficit. This can be converted to carbon equivalents since oxygen and carbon are consumed in a fixed ratio2. The carbon surplus can be used by the coral for growth, mucus synthesis and reproduction, and other essential metabolic needs12.
This protocol describes a micro-respiration method (Figure 1) that was employed for measuring rates of respiration (R) for individual coral juveniles using a custom-made 1.5 mL glass chamber design (vial with GL25 thread and 20 mm high, with bump/ridge, flat-ground rim, and screw cap with hole; see Table of Materials) filled with 0.5 &#181;m filtered seawater. Fiberoptic optodes (see Table of Materials)&#160;were inserted into each chamber through a hole in the side of the lid. Each individual coral was attached above a hard mesh, flow-through stirrer plate platform above a magnetic stir-bar to ensure adequate mixing of water within the chamber. In the representative example here, two controls or &#34;blanks&#34; (chambers that were identical except for the presence of the specimen) were measured concurrently to the three replicate specimen chambers, as we had multiple controllers running simultaneously. However, the setup example (Figure 2) only shows the use of four channels; this can be increased using multiple controllers and multiple flow-through stands. The temperature could also be controlled in this system by submerging each chamber in a custom-made water bath with preset water temperatures (27 &#176;C for control or 31 &#176;C for the high temperature stress in the example data here) using a recirculating flow-through (continuous, gentle flow set at 75 L/h) system. The stirrer plate platform and the stirrer plate with gears can be any size and can be made as large or as small as required to accommodate the number of glass chambers. In this example, the platform and plate were about 34 cm x 26 cm x 3 cm (Table of Materials). Calibration of the optodes was performed before each run using two standard solutions representing 0% and 100% oxygen saturation at the appropriate water temperature and salinity for this experimental setting.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>&#160;&#160;</td>
			<td>&#160;&#160;</td>
			<td>&#160;&#160;</td>
			<td>Cost</td>
		</tr>
		<tr>
			<td>(1.1 &#8211; 1.6) Custom respirometry chambers&#160;</td>
			<td>LabGlass Party Ldt.</td>
			<td>1.5 ml</td>
			<td>$407.26</td>
		</tr>
		<tr>
			<td>1.1 lids</td>
			<td>AIMS workshop</td>
			<td>Vial GL25 thread</td>
			<td>~$10</td>
		</tr>
		<tr>
			<td>1.2 fiber-optics spots (FireStingO2 II fiberoptic optodes)</td>
			<td>PyroScience</td>
			<td>Oxygen sensor spots, 125 &#181;m PET foil, &#216;5 mm, with optical isolation, SN: 183801947</td>
			<td>$41.25 AUD each</td>
		</tr>
		<tr>
			<td>1.3 individual organism&#160;</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>1.4 flow-through stand&#160;</td>
			<td>AIMS workshop</td>
			<td>Custom</td>
			<td>included in points 5 and 6 price (the workshop gave me an estimate of the lids, stand with gears, motor, incubation flow through</td>
		</tr>
		<tr>
			<td>1.5 magnetic stirrer&#160;</td>
			<td>Any manufactuer is suitable</td>
			<td>NA</td>
			<td>~$2?</td>
		</tr>
		<tr>
			<td>1.6 glass chamber (vial GL25 thread x 20 mm high, with bump/ridge, flat-ground rim, screw cap with hole, Labglass Pty Ltd, Stafford QLD)</td>
			<td>Labglass Pty Ltd, Stafford QLD</td>
			<td>Vial GL25 thread x 20 mm high, with bump/ridge, flat-ground rim, screw cap with hole</td>
			<td>$50.9 AUD</td>
		</tr>
		<tr>
			<td>2 FireSting controller (2)&#160;</td>
			<td>PyroSciences</td>
			<td>NA</td>
			<td>4 sensors is 4000 Euros. 8 sensors used here.</td>
		</tr>
		<tr>
			<td>3 computer&#160;</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>4 heater/chiller&#160;</td>
			<td>VWR International</td>
			<td>NA</td>
			<td>Small models around $4,000 AUD</td>
		</tr>
		<tr>
			<td>5 respirometry plate platform</td>
			<td>AIMS workshop</td>
			<td>34 cm x 26 cm x 3 cm (although any dimensions are adequate to fit desired number of chambers)&#160;</td>
			<td>$1250 AUD</td>
		</tr>
		<tr>
			<td>6 stirrer plate with gears (7)</td>
			<td>AIMS workshop</td>
			<td>34 cm x 26 cm x 3 cm&#160;</td>
			<td>$1250 AUD</td>
		</tr>
		<tr>
			<td>8 powered by the motor&#160;</td>
			<td>AIMS workshop</td>
			<td>Custom</td>
			<td>$700 AUD</td>
		</tr>
		<tr>
			<td>9 power supply</td>
			<td>Non-specific</td>
			<td>NA</td>
			<td>~$300 AUD</td>
		</tr>
		<tr>
			<td>Aquarium glue</td>
			<td>Seachem reef glue</td>
			<td>20g</td>
			<td>$14</td>
		</tr>
		<tr>
			<td>Oxygen Logger Software</td>
			<td>PyroScience&#160;</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Polypipe and connectors</td>
			<td>John Guest</td>
			<td>NA</td>
			<td>$20</td>
		</tr>
		<tr>
			<td>Sodium Sulfite</td>
			<td>Sigma</td>
			<td>S0505-250G (CAS number 7757-83-7)</td>
			<td>$54</td>
		</tr>
	</tbody>
</table>

physiological characterization of the coral holobiont using a new micro-respirometry tool

Metabolic activity, defined as the sum of organismal processes that involve energy, is of critical importance in understanding the function and evolution of life on earth. Measuring organismal metabolic rates is, therefore, at the center of explaining the physiological states of organisms, their ecological roles, and the impact of environmental change on species within terrestrial and aquatic ecosystems. On coral reefs, measures of metabolism have been used to quantify symbiosis functioning between corals and their obligate algal symbionts (Symbiodiniaceae), as well as assess how environmental stressors, including climate change, will impact coral health. Despite this significance, there is a lack of methods, and therefore data, relating to metabolic rate measurements in coral offspring, likely due to their small size. To address this gap, this study aimed to develop a custom setup for measuring the respiration of small (millimeter size range) marine animal ecologies. This low cost and easy setup should allow for the improved measurement of metabolic rate. This will be essential for applied ecological research utilizing the sexual production of corals for reef restoration.

Data processing and analysis 
While there are numerous methods to process the raw data from respirometry experiments, it is recommended to use the R package respR28. In keeping with the sharing of the protocols above, which advocate for open science and reproducibility, this package allows data processing and analysis to be shared in an easily reproducible form and has been designed with that in mind. It is a free, open-source platform and probe-system agnostic, and easily installable either from CRAN or GitHub. Full code and examples for respR are maintained and can be found at&#160;https://github.com/januarharianto/respR.
The respR package has functions to import, visualize, and perform quality control on respirometry data, and to calculate respiration rates either automatically or from manually chosen regions. It can also adjust rates for background respiration and conversion rates to commonly used output units. The steps to process the data from the micro-respirometry system are detailed below. In this study, the data from the respirometry system was used as an example, but the package also accepts inputs from the majority of commercially available oxygen probe systems as well as generic R data objects. More details about the package, including full documentation and tutorials, can be found on the package website at&#160;https://januarharianto.github.io/respR/index.html.
Importing raw data 
The raw output file (.txt) is imported. respR recognizes the format and parses it to a generic R data frame that can be used in subsequent functions. However, it is important to note that this is optional; these files and virtually any oxygen time series data can also be imported using base functions (given below) by anyone with a basic knowledge of R.
#load respR 
Library(respR)
#Import --- 
Data &#60;- import_file(&#34;file.txt&#34;) 
#Firesting-Pryo file detected
Inspecting and visualizing the data 
A vital part of any data analysis task is to plot and inspect the data to look for obvious anomalies or patterns, or even to just help to understand it. The inspect function is used here (Figure 8A), which checks for issues common to respirometry data such as non-numeric or missing values.
#inspect a single oxygen column 
Insp &#60;-inspect(data, time = 3, oxygen = 8, width = 0.2)
This function also plots the oxygen timeseries and calculates a rolling rate (bottom panel) to help elucidate how this rate may change over the course of the experiment. These rolling rate plots help inform about which regions of those rate curves should be extracted. In the case of standard or routine metabolic rates, the desired regions are those where the rate shows stability (e.g., after around timepoint 3,000; Figure 8B).
Here, declining oxygen only becomes detectable after around row 200 in the full timeseries panel. Patterns such as this are very common in respirometry data; there is often an extended period of instability at the start of an experiment as the system stabilizes and specimen becomes acclimated to the experimental conditions. It is recommended that rates should only be extracted from the timeseries after this initial instability, which also highlights the importance of visualizations.
Extract rates 
respR has two functions for extracting respiration rates. The first is the calc_rate() function, which allows a rate to be extracted manually by specifying a region of time, row, or oxygen level. This is very common in respirometry analyses, and a perfectly acceptable method of determining a rate as long as selection criteria are decided upon and applied consistently28.
A more robust and objective way is to use the auto_rate() function, which identifies linear regions of the data. These regions are those of consistently sustained respiration rates, assigned automatically using machine learning. This function is also useful for the detection of low signals (as in the samples used in this current study, due to the low biomass at this age). This function allows for the identification of the most linear, minimum, and maximum rates using independent, objective, and statistically robust methods28. The example here identifies a linear region occurring from around timepoints 3,000 to 5,000. It should be noted that multiple linear regions may be identified, but this section is the highest ranked, or most linear, region (Figure 8C).
#Determine most linear (i.e., consistent) rate 
rate &#60;-auto_rate(insp)
Background adjustment 
Background rates from control experiments can be determined in a similar manner to the above example, and can be used to adjust the specimen rates using the adjust_rate() function (Figure 9A; note that the full analysis is not shown here, only the adjustment). Full examples are detailed on the respR website.
#Adjust rate for background 
rate_adj &#60;-adjust_rate(rate, by = bg) #saved bg object 
print(rate_adj)
Convert rates 
The final step is to convert the rates to the desired output units, using the original units of the raw data, effective volume of the respirometer, and other experimental data, including normalizing to blank measurements (Figure 9B). The output can be an absolute respiration rate, that is, of the entire specimen, or a mass- or surface area-specific rate. The surface area-specific rate was the output used here, which specifically is the absolute rate divided by the surface area of the specimen (Figure 9C).
As discussed above, this system was developed to measure very small specimens. Therefore, we expected low values and potential overlap with blank measurements. Some level of signal is expected within the blanks, and when examined, these values are within the expected range of general experimental noise, possibly due to probe drift, slight temperatures changes, or bubbles on the probes. By design and due to the small specimen size, and therefore small effective volume used, the use of blanks is particularly important here, especially for each run. Representative values have been included here as an example (Figure 10). Given the small specimen size, we recommend the use of the blanks at each run to standardize measurements per run.
These blank values are then used to standardize treatment measurements values. Given corals respire in addition to producing oxygen, the metabolic rate can range from negative to positive values. An example of representative results of the range of respiration values detected from the micro-respiration tool is given here. These results were determined from a successful experiment on single coral juveniles (Figure 10). Overall, respiration was expected to be difficult to detect in this example dataset (by design), given the small size of the samples; this underscores the value of this method in capturing this low signal threshold. These representative results show respiration in the dark at the smallest specimens sizes tested, underscoring the minimum detection threshold of this system. We also measured under two conditions (control and high temperature stress). After standardizing to the blanks measured per run, values ranged from close to zero (control) to a median of ~-5e-5 for the stress treatment. As expected, respiration was low. These results clearly show representative values for blanks, as well as a control versus high temperature comparison for these very small samples.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/64812/64812fig01v2.jpg" /> 
Figure 1: Schematic representation of the new micro-respirometry tool for the physiological characterization of the coral holobiont (coral animal + symbionts) or any small organism (&#60;1 mm). Custom respirometry chambers were made (number 1; 1.1-1.6). These include lids (1.1) with oxygen sensor spots (1.2), and the individual juvenile (1.3) is placed on a flow-through stand (1.4) set atop a magnetic stirrer (1.5), all of which fit within the glass chamber (1.6). The controller (2) is attached to the spot with a fiber optic cable that fits into the lid (1) and connected to the computer (3). The heater/chiller (4) connects to the respirometry plate (5) with the flow-through water (indicated by chevron arrows for direction), which sits on top of the stirrer plate (6) with gears (7), powered by the motor (8) and power supply (9). <a href="https://www.jove.com/files/ftp_upload/64812/64812fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/64812/64812fig02.jpg" /> 
Figure 2: Micro-respirometry setup. Multiple options are available, including (A)&#160;one respirometry plate, or (B)&#160;connected to multiple plates. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/64812/64812fig03.jpg" /> 
Figure 3: Custom built magnetic stirrer plate on top of respirometry plate. Each chamber has (A)&#160;a magnetic stirrer gear underneath, (B) powered by a motor, with (C)&#160;the respirometry plate connected by tubing to the heater/chiller. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig03large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/64812/64812fig04.jpg" /> 
Figure 4: Custom respirometry chamber setup. (A) Components (left to right: lid, glass vial, stand, 1.5 ml tube for scale, and stirrer bar). (B) Individual flow-through stand that the specimen sits within. (C)&#160;Top-down view of the flow-through stand. (D) and with the stand placed inside the glass vial with the lid screwed on. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig04large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/64812/64812fig05.jpg" /> 
Figure 5: Glass vials placed within the stirrer plate. (A) Custom built stirrer plate with (B) a close-up of the complete glass vial with the lid setup. The juvenile coral can be seen through the lid here (brown dot), on top of the zip-tie, with the fiber optic placed in the lid opening. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig05large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 6" class="xfigimg" src="/files/ftp_upload/64812/64812fig06.jpg" /> 
Figure 6: Chambers placed upside down, ready for calibration. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig06large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 7" class="xfigimg" src="/files/ftp_upload/64812/64812fig07.jpg" /> 
Figure 7: Key steps in the oxygen measurement software. (A) Check the signal of each sensor. An optimal signal for this study and sensors is shown in the oxygen sensor spot FTC (normal range). (B) Check the signal drift. (C) Set and check the treatment temperatures. (D) Set and check the 0% and 100% calibrations. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig07large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 8" class="xfigimg" src="/files/ftp_upload/64812/64812fig08.jpg" /> 
Figure 8: respR analysis output steps I. (A) Inspect the command and output. (B)&#160;Check the rate stability. (C) Determine the most linear rate. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig08large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 9" class="xfigimg" src="/files/ftp_upload/64812/64812fig09.jpg" /> 
Figure 9: respR analysis output steps II. (A) Adjust the rate for background, (B) Convert and (C) check the rates. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig09large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 10" class="xfigimg" src="/files/ftp_upload/64812/64812fig10.jpg" /> 
Figure 10: Representative results produced from the micro-respirometry tool. Median respiration (O2 &#177; standard error) of replicate individual coral juveniles, including blank values as well as respiration of individuals under control and high temperature stress conditions. <a href="https://www.jove.com/files/ftp_upload/64812/64812fig10large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
Video 1: Top-down view of the respirometry chamber with the juvenile coral inside during a measurement session. <a href="https://www.jove.com/files/ftp_upload/64812/20190420_150135.mp4" target="_blank">Please click here to download this Video.</a>
Table 1: Cost estimates of components of the respirometry apparatus. <a href="https://www.jove.com/files/ftp_upload/64812/Table 1.xlsx" target="_blank">Please click here to download this Table.</a>

Watch this Scientific Journal Video about Physiological Characterization of the Coral Holobiont Using a New Micro-Respirometry Tool at JoVE.com

Physiological Characterization of the Coral Holobiont Using a New Micro-Respirometry Tool

This protocol describes the setup and running of a micro-respirometry system that can be employed to investigate the physiological features of the coral holobiont.

Metabolic activity, defined as the sum of organismal processes that involve energy, is of critical importance in understanding the function and evolution ...

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Research

JoVE Journal

Biology

835 Views.  Minderoo Foundation. This protocol describes the setup and running of a micro-respirometry system that can be employed to investigate the physiological features of the coral holobiont.

Video: Physiological Characterization of the Coral Holobiont Using a New Micro-Respirometry Tool

Visually Mediated Odor Tracking During Flight in Drosophila

Flying insects use visual cues to stabilize their heading in a wind stream. Many animals additionally track odors carried in the wind. As such, visual stabilization of upwind tracking directly aids in odor tracking. But do olfactory signals directly influence visual tracking behavior independently from wind cues? Additionally, recent advances in olfactory molecular genetics and neurophysiology have motivated novel quantitative behavioral analyses to assess the behavioral influence of (e.g.) genetically inactivating specific olfactory activation circuits. We modified a magnetic tether system originally devised for vision experiments by equipping the arena with narrow laminar flow odor plumes. Here we focus on experiments that can be performed after a fly is tethered and is able to navigate in the magnetic arena. We show how to acquire video images optimized for measuring body angle, how to judge stable odor tracking, and we illustrate two experiments to examine the influence of visual cues on odor tracking.

Here we describe how to optimize the acquired video image for an olfactory magnetic-tether (OMT) apparatus. We also describe two sample experimental protocols for studying visuo-olfactory fusion.

Flying insects use visual cues to stabilize their heading in a wind stream. Many animals additionally track odors carried in the wind. As such, visual ...

A high-throughput method to globally study the organelle morphology in S. cerevisiae

High-throughput methods to examine protein localization or organelle morphology is an effective tool for studying protein interactions and can help achieve an comprehensive understanding of molecular pathways. In Saccharomyces cerevisiae, with the development of the non-essential gene deletion array, we can globally study the morphology of different organelles like the endoplasmic reticulum (ER) and the mitochondria using GFP (or variant)-markers in different gene backgrounds. However, incorporating GFP markers in each single mutant individually is a labor-intensive process. Here, we describe a procedure that is routinely used in our laboratory. By using a robotic system to handle high-density yeast arrays and drug selection techniques, we can significantly shorten the time required and improve reproducibility. In brief, we cross a GFP-tagged mitochondrial marker (Apc1-GFP) to a high-density array of 4,672 nonessential gene deletion mutants by robotic replica pinning.  Through diploid selection, sporulation, germination and dual marker selection, we recover both alleles. As a result, each haploid single mutant contains Apc1-GFP incorporated at its genomic locus. Now, we can study the morphology of mitochondria in all non-essential mutant background. Using this high-throughput approach, we can conveniently study and delineate the pathways and genes involved in the inheritance and the formation of organelles in a genome-wide setting.

GFP-fusion proteins are widely used to visualize organelles by confocal microscopy. However, screening for mutations that affect the morphology of organelles generally requires individual mutagenesis and is time consuming. Here, we demonstrate a method to simultaneously incorporate organelle-GFP markers in almost 5,000 non-essential genes in yeast.

High-throughput methods to examine protein localization or organelle morphology is an effective tool for studying protein interactions and can help ...

Lensless On-chip Imaging of Cells Provides a New Tool for High-throughput Cell-Biology and Medical Diagnostics

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite effective, this classical approach has certain limitations for miniaturization of the imaging platform to make it compatible with the advanced state of the art in microfluidics. In this report, we introduce experimental details of a lensless on-chip imaging concept termed LUCAS (Lensless Ultra-wide field-of-view Cell monitoring Array platform based on Shadow imaging) that does not require any microscope objectives or other bulky optical components to image a heterogeneous cell solution over an ultra-wide field of view that can span as large as ~18 cm2. Moreover, unlike conventional microscopes, LUCAS can image a heterogeneous cell solution of interest over a depth-of-field of ~5 mm without the need for refocusing which corresponds to up to ~9 mL sample volume. This imaging platform records the shadows (i.e., lensless digital holograms) of each cell of interest within its field of view, and automated digital processing of these cell shadows can determine the type, the count and the relative positions of cells within the solution. Because it does not require any bulky optical components or mechanical scanning stages it offers a significantly miniaturized platform that at the same time reduces the cost, which is quite important for especially point of care diagnostic tools. Furthermore, the imaging throughput of this platform is orders of magnitude better than conventional optical microscopes, which could be exceedingly valuable for high-throughput cell-biology experiments.

Lensfree on-chip imaging and characterization of cells is illustrated. This on-chip cell imaging approach provides a compact and cost-effective tool for medical diagnostics and high-throughput cell biology applications, making it especially suitable for resource poor settings.

Conventional optical microscopes image cells by use of objective lenses that work together with other lenses and optical components. While quite ...

Micro-Mechanical Characterization of Lung Tissue Using Atomic Force Microscopy

Matrix stiffness strongly influences growth, differentiation and function of adherent cells1-3. On the macro scale the stiffness of tissues and organs within the human body span several orders of magnitude4. Much less is known about how stiffness varies spatially within tissues, and what the scope and spatial scale of stiffness changes are in disease processes that result in tissue remodeling. To better understand how changes in matrix stiffness contribute to cellular physiology in health and disease, measurements of tissue stiffness obtained at a spatial scale relevant to resident cells are needed. This is particularly true for the lung, a highly compliant and elastic tissue in which matrix remodeling is a prominent feature in diseases such as asthma, emphysema, hypertension and fibrosis. To characterize the local mechanical environment of lung parenchyma at a spatial scale relevant to resident cells, we have developed methods to directly measure the local elastic properties of fresh murine lung tissue using atomic force microscopy (AFM) microindentation. With appropriate choice of AFM indentor, cantilever, and indentation depth, these methods allow measurements of local tissue shear modulus in parallel with phase contrast and fluorescence imaging of the region of interest. Systematic sampling of tissue strips provides maps of tissue mechanical properties that reveal local spatial variations in shear modulus. Correlations between mechanical properties and underlying anatomical and pathological features illustrate how stiffness varies with matrix deposition in fibrosis. These methods can be extended to other soft tissues and disease processes to reveal how local tissue mechanical properties vary across space and disease progression.

The stiffness of the extracellular matrix strongly influences multiple behaviors of adherent cells. Matrix stiffness varies spatially throughout a tissue, and undergoes modification in various disease conditions. Here we develop methods to characterize spatial variations in stiffness in normal and fibrotic mouse lung tissue using atomic force microscopy microindentation.

Matrix stiffness strongly influences growth, differentiation and function of adherent cells1-3.  On the macro scale the stiffness of tissues and organs ...

Scale-Up of Mammalian Cell Culture using a New Multilayered Flask

A growing number of cell-based applications require large numbers of cells. Usage of single layer T-flasks, that are adequate during small-scale expansion, may become cumbersome, laborious and time-consuming when large numbers of cells are required. To address this need, the performance of a new multi-layered cell culture vessel to facilitate easy scale up of cells from single layered T-flasks will be discussed. The flasks tested are available in 3- and 5-layer format and enable culture and complete recovery of three and five times the number of cells respectively, compared to T-175 flasks. A key feature of the BD Multi-Flask is a mix/equilibration port that allows rapid in-vessel mixing as well as uniform distribution of cells and reagents within and 
between layers of each vessel and consistently produce cells that can be cultured in an environment that is congruent to T-175 flasks.
The design of these Multi-Flasks also allows for convenient pipette access for adding reagents and cells directly into the flasks as well as efficient recovery of valuable cells and reagents and reduces risk of contamination due to pouring. For applications where pouring is preferred over pipetting, the design allows for minimal residual liquid retention so as to reduce wastage of valuable cells and reagents.

Cells play an instrumental and increasing role in research, and the discovery and development of new therapeutics. With this increasing need for greater number of cells we need more efficient and effective ways for growing and harvesting attachment dependent cells. A Multilayered flask with the right features can serve this purpose.

A growing number of cell-based applications require large numbers of cells. Usage of single layer T-flasks, that are adequate during small-scale ...

Identification and Characterization of Protein Glycosylation using Specific Endo- and Exoglycosidases

Glycosylation, the addition of covalently linked sugars, is a major post-translational modification of proteins that can significantly affect processes such as cell adhesion, molecular trafficking, clearance, and signal transduction1-4. In eukaryotes, the most common glycosylation modifications in the secretory pathway are additions at consensus asparagine residues (N-linked); or at serine or threonine residues (O-linked) (Figure 1). Initiation of N-glycan synthesis is highly conserved in eukaryotes, while the end products can vary greatly among different species, tissues, or proteins. Some glycans remain unmodified ("high mannose N-glycans") or are further processed in the Golgi ("complex N-glycans"). Greater diversity is found for O-glycans, which start with a common N-Acetylgalactosamine (GalNAc) residue in animal cells but differ in lower organisms1.
The detailed analysis of the glycosylation of proteins is a field unto itself and requires extensive resources and expertise to execute properly. However a variety of available enzymes that remove sugars (glycosidases) makes possible to have a general idea of the glycosylation status of a protein in a standard laboratory setting. Here we illustrate the use of glycosidases for the analysis of a model glycoprotein: recombinant human chorionic gonadotropin beta (hCG&beta;), which carries two N-glycans and four O-glycans 5. The technique requires only simple instrumentation and typical consumables, and it can be readily adapted to the analysis of multiple glycoprotein samples.
Several enzymes can be used in parallel to study a glycoprotein. PNGase F is able to remove almost all types of N-linked glycans6,7. For O-glycans, there is no available enzyme that can cleave an intact oligosaccharide from the protein backbone. Instead, O-glycans are trimmed by exoglycosidases to a short core, which is then easily removed by O-Glycosidase. The Protein Deglycosylation Mix contains PNGase F, O-Glycosidase, Neuraminidase (sialidase), &beta;1-4 Galactosidase, and &beta;-N-Acetylglucosaminidase. It is used to simultaneously remove N-glycans and some O-glycans8 . Finally, the Deglycosylation Mix was supplemented with a mixture of other exoglycosidases (&alpha;-N-Acetylgalactosaminidase, &alpha;1-2 Fucosidase, &alpha;1-3,6 Galactosidase, and &beta;1-3 Galactosidase ), which help remove otherwise resistant monosaccharides that could be present in certain O-glycans.
SDS-PAGE/Coomasie blue is used to visualize differences in protein migration before and after glycosidase treatment. In addition, a sugar-specific staining method, ProQ Emerald-300, shows diminished signal as glycans are successively removed. This protocol is designed for the analysis of small amounts of glycoprotein (0.5 to 2 &mu;g), although enzymatic deglycosylation can be scaled up to accommodate larger quantities of protein as needed.

Using specific glycosidases to remove sugars from glycoproteins followed by SDS-PAGE is a valuable method to detect glycan modifications on protein samples and is a good choice for initial glycobiology studies. Changes following deglycosylation can be detected as shifts in gel mobility or by staining with glycan sensitive reagents.

Glycosylation, the addition of covalently linked sugars, is a major post-translational modification of proteins that can significantly affect processes ...

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

The quantity and quality of detritus entering the soil determines the rate of decomposition by microbial communities as well as recycle rates of nitrogen (N) and carbon (C) sequestration1,2. Plant litter comprises the majority of detritus3, and so it is assumed that decomposition is only marginally influenced by biomass inputs from animals such as herbivores and carnivores4,5. However, carnivores may influence microbial decomposition of plant litter via a chain of interactions in which predation risk alters the physiology of their herbivore prey that in turn alters soil microbial functioning when the herbivore carcasses are decomposed6. A physiological stress response by herbivores to the risk of predation can change the C:N elemental composition of herbivore biomass7,8,9 because stress from predation risk increases herbivore basal energy demands that in nutrient-limited systems forces herbivores to shift their consumption from N-rich resources to support growth and reproduction to C-rich carbohydrate resources to support heightened metabolism6. Herbivores have limited ability to store excess nutrients, so stressed herbivores excrete N as they increase carbohydrate-C consumption7. Ultimately, prey stressed by predation risk increase their body C:N ratio7,10, making them poorer quality resources for the soil microbial pool likely due to lower availability of labile N for microbial enzyme production6. Thus, decomposition of carcasses of stressed herbivores has a priming effect on the functioning of microbial communities that decreases subsequent ability to of microbes to decompose plant litter6,10,11.
We present the methodology to evaluate linkages between predation risk and litter decomposition by soil microbes. We describe how to: induce stress in herbivores from predation risk; measure those stress responses, and measure the consequences on microbial decomposition. We use insights from a model grassland ecosystem comprising the hunting spider predator (Pisuarina mira), a dominant grasshopper herbivore (Melanoplus femurrubrum),and a variety of grass and forb plants9.

We present methods to evaluate how predation risk can alter the chemical quality of herbivore prey by inducing dietary changes to meet demands of heightened stress, and how the decomposition of carcasses from these stressed herbivores slows subsequent plant litter decomposition by soil microbes.

The quantity and quality of detritus entering the soil  determines the rate of decomposition by microbial communities as well as  recycle rates of ...

The c-FOS Protein Immunohistological Detection: A Useful Tool As a Marker of Central Pathways Involved in Specific Physiological Responses In Vivo and Ex Vivo

Many studies seek to identify and map the brain regions involved in specific physiological regulations. The proto-oncogene c-fos, an immediate early gene, is expressed in neurons in response to various stimuli. The protein product can be readily detected with immunohistochemical techniques leading to the use of c-FOS detection to map groups of neurons that display changes in their activity. In this article, we focused on the identification of brainstem neuronal populations involved in the ventilatory adaptation to hypoxia or hypercapnia. Two approaches were described to identify involved neuronal populations in vivo in animals and ex vivo in deafferented brainstem preparations. In vivo, animals were exposed to hypercapnic or hypoxic gas mixtures. Ex vivo, deafferented preparations were superfused with hypoxic or hypercapnic artificial cerebrospinal fluid. In both cases, either control in vivo animals or ex vivo preparations were maintained under normoxic and normocapnic conditions. The comparison of these two approaches allows the determination of the origin of the neuronal activation i.e., peripheral and/or central. In vivo and ex vivo, brainstems were collected, fixed, and sliced into sections. Once sections were prepared, immunohistochemical detection of the c-FOS protein was made in order to identify the brainstem groups of cells activated by hypoxic or hypercapnic stimulations. Labeled cells were counted in brainstem respiratory structures. In comparison to the control condition, hypoxia or hypercapnia increased the number of c-FOS labeled cells in several specific brainstem sites that are thus constitutive of the neuronal pathways involved in the adaptation of the central respiratory drive.

The c-FOS Protein Immunohistological Detection: A Useful Tool As a Marker of Central Pathways Involved in Specific Physiological Responses In Vivo and Ex Vivo

Here, we present a protocol based on c-FOS protein immunohistological detection, a classical technique used for the identification of neuronal populations involved in specific physiological responses in vivo and ex vivo.

Many studies seek to identify and map the brain regions involved in specific physiological regulations. The proto-oncogene c-fos, an immediate early gene, ...

Imaging Spatial Reorganization of a MAPK Signaling Pathway Using the Tobacco Transient Expression System

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular fluorescent complementation (BiFC) assay in tobacco epidermal cells, from testing protein-protein interaction to monitoring spatial distribution of signal transduction in plant cells. In this protocol, we used the BiFC assay to show that the interaction and the signaling between the Arabidopsis MAPKKK YODA and MAPK6 occur at the plasma membrane. When the scaffold protein BASL was co-expressed, the YODA-MAPK interaction redistributed and spatially co-polarized with CFP-BASL. This modified tobacco expression system allows for quick examination of signaling localization and dynamic changes (less than 4 days) and can accommodate multiple of fluorescent protein colors (at least three). We also presented detailed methods to quantify protein distribution (asymmetric spatial localization, or &#34;polarization&#34;) in tobacco cells. This advanced tobacco expression system has a potential to be used widely for quick testing of dynamic signaling events in live plant cells.

At the subcellular level, signaling events are dynamically modulated by developmental and environmental cues. Here we describe a protocol that employs the tobacco transient expression system to monitor dynamic protein-protein interaction and to disclose spatial organization of signal transduction in plant cells.

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular ...

Sample Preparation for Metabolic Profiling using MALDI Mass Spectrometry Imaging

Metabolomics, the study to identify and quantify small molecules and metabolites present in an experimental sample, has emerged as an important tool to investigate the biological activities during development and diseases. Metabolomics approaches&#160;are widely employed in the study of cancer, nutrition/diet, diabetes, and other physiological and pathological conditions involving metabolic processes. An advantageous tool that aids in metabolomic profiling advocated in this paper is matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI). Its ability to detect metabolites in situ without labeling, structural modifications, or other specialized reagents, such as those used in immunostaining, makes MALDI MSI a unique tool in advancing methodologies relevant in the field of metabolomics. An appropriate sample preparation process is critical to yield optimal results and will be the focus of this paper.

The goal of this protocol is to provide detailed guidance on the sample preparation when planning for experiments using MALDI MSI to maximize metabolic and molecular detection in biological samples.

Metabolomics, the study to identify and quantify small molecules and metabolites present in an experimental sample, has emerged as an important tool to ...