We are indebted to Xuefei Yang, Sabine Both, Lin Chen and Kaitian Wang for coordinating the fieldwork and establishing the BEF-China experiment. We are also grateful to the whole BEF-China research group for their general support. BEF-China is mainly funded by the German Research Foundation (DFG FOR 891/1 and 2) and funding for this particular project was provided by the German Research Foundation to H.B. (DFG BR 1698/9-2). We are also thankful for the travel grants and summer schools financed by the Sino-German Centre for Research Promotion in Beijing (GZ 524, 592, 698, 699 and 785). In addition we would like to thank David Eichenberg, Michael Staab, Katja Grotius, Silvana Tornack, Lin Chen, and Shouren Zhang for their support in the field and in the lab.

1. Stomatal Conductance
<ol>
	<li>Measurements of stomatal conductance 
	NOTE: The authors made use of a simple type of steady state porometer (Decagon SC1). The porometer&#8217;s design has the advantage of small size, intuitive manual operation and high reliability. When measuring stomatal conductance in the field, make sure to minimize the distance between measured individuals for a repeated measurement cycle to be the most efficient possible.</li>
	<li>Choose leaves of different species and individuals according to a reproducible pattern (same height, same exposure, same position within the plant, if possible only from the same node, and only from one category; sun or shade leaves, etc.).
	<ol>
		<li>Only measure leaves in healthy, non-damaged and fully developed condition. Mark the leaves on the individuals (e.g., with cable ties or color tape), to ensure that the repeated measurements are done on the same leaf. 
		NOTE: Measurements of stomatal conductance should be made only on leaf surface whilst avoiding the midrib and strong leaf veins.</li>
		<li>Start measurements in the early morning hours before sunrise taking five to ten repeated measurements until stomatal conductance values shows a clear decline at noon. 
		NOTE: A daily course of measurements will deliver good data for analyzing the relationships between vpd and stomatal conductance.</li>
	</ol>
	</li>
	<li>Vpd measurements
	<ol>
		<li>With each gS measurement, record temperature and relative humidity preferably with portable loggers to directly measure the conditions at the position of the same leaf. For calculating the vapor pressure deficit use the August-Roche Magnus formula15.</li>
	</ol>
	</li>
</ol>
<img alt="Equation 1" fo:content-width="3in" src="/files/ftp_upload/52738/52738eq1.jpg" width="300" />
es=saturation water vapor pressure [hPa]
T=temperature [&#176;C]
<ol start="4">
	<li>Model gS - vpd response
	<ol>
		<li>Now plot species-wise all gS data against vpd, combining all daily courses of individual leaves into one analysis per species. Extract the maximum value observed from the stomatal conductance data by searching for the maximum value. To scale the model for species-wise comparability, divide the observed values through the maximum value observed for that species (gS/gSMAX).</li>
		<li>For each species, regress the logits of gS (gS/gSMAX) to vpd and the quadratic term of vpd using a generalized linear model with a binomial error distribution (a, b and c represent regression parameters):</li>
	</ol>
	</li>
</ol>
<img alt="Equation 2" src="/files/ftp_upload/52738/52738eq2.jpg" width="300" />
<img alt="Figure 1" src="/files/ftp_upload/52738/52738fig1highres.jpg" width="700" /> 
Figure 1. Example of the plotted values and the fitted model for gS - vpd. Stomatal conductance plotted as a function of vapor pressure deficit for the species Liquidambar formosana. Empty dots represent the observed values. (A) Maximum stomatal conductance, the vpd at maximum stomatal conductance and mean stomatal conductance was extracted from the absolute thus non-scaled stomatal conductance (gS) data. (B) Scaled stomatal conductance data (gS/gSMAX) were plotted to extract the relative parameters (shown as filled dots) 20. Re-print with permission from20. <a href="https://www.jove.com/files/ftp_upload/52738/52738fig1highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/52738/52738fig2highres.jpg" width="400" /> 
Figure 2. All fitted models for all species. Model graphs for the stomatal conductance data to vpd regression for all species. Evergreen species are represented by black lines, deciduous species by red lines 20. Re-print with permission from20.
NOTE: Using the logits instead of regressing gS directly to vpd, leads to the point that modeled maximum values do not exceed gSMAX and that gS approaches 0 at high vpd.
<ol start="5">
	<li>Extract parameter of stomatal regulation for every species
	<ol>
		<li>Calculate absolute modeled gSMAX values (MaxFit in Figure&#160;1B). To do this, calculate the vpd at maximum stomatal conductance from setting the first derivative of 1.4.2 to zero, which gives vpdgsMaxFit = -b/2a. Insert vpdgsMaxFit into the formula of 1.4.2 and raise to the power of e to obtain MaxFit. Calculate the mean of all conductance measurements per species (see Figure 1A). 
		NOTE: Use statistical software R (http://www.r-project.org).</li>
		<li>To calculate relative values, from the scaled model (gS/gSMAX), extract stomatal conductance and vpd values for the following two points: (1) stomatal conductance and vpd at the maximum of the model (MaxFit) and (2) vpd at the second point of inflection of the curve (see Figure 1B). Multiply these values by gSMAX to obtain absolute gS values for these points. See Figure 2 for a complete overlay of the single models of all 39 species analyzed.</li>
	</ol>
	</li>
</ol>
2. Measurements of Stomatal Traits
<ol>
	<li>Take samples preferably from exactly the same leaves that have been used for the measurements of stomatal conductance. If this is not possible, apply the same selection procedure that was applied to choose the leaves for the stomatal conductance measurements, preferably on the same individuals.</li>
	<li>Apply a thin layer of colorless, quickly drying nail polish (test different makes, some are more suitable than others) to a fresh sample. If the samples cannot be processed immediately, store them in 70% alcohol. After the nail polish has dried out, gently peel the impression of from the leaf and proceed for the microscopic analysis, as with a normal leaf sample. &#160; 
	NOTE: In the case of leaves with high trichome density a preceding step of applying sodium hydroxide or a 1:1 solution of acetic acid and oxygen peroxide can lead to better results.</li>
	<li>Optical microscope analytics
	<ol>
		<li>Connect a camera to an optical microscope capable of magnifications between 40X to 400X. After the camera is connected to the microscope, match the pictures taken to the optical magnification and resolution of the picture, e.g., with the help of a scale.</li>
		<li>Employing open source image processing software like ImageJ 16 analyze these pictures.
		<ol>
			<li>Draw a shape with the shape tool from the image analysis tool on the image in an area with no dirt, thumb prints, damaged areas, or large leaf veins. Count stomata in this area and in total of at least 50,000 &#181;m2 per sample.</li>
			<li>Measure stomatal guard cell length and pore length. Calculate the number of stomata per mm2. Calculate stomatal index as the ratio of stomatal density to epidermal cell number per mm2.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
3. Assessment of Leaf Vein Traits
NOTE: For the assessment of leaf vein traits, a modified a protocol from Sack &#38; Scoffoni 17 was employed.
<ol>
	<li>Sample preparation 
	NOTE: To optimize the visibility of the leaf veins, the leaves are first bleached and then stained with safranine and malachite green.
	<ol>
		<li>To bleach the leaves, leave them at least 72 hr in 50% solution of decolorizer (test different makes, again some might work better). Alternatively, use 5% NaOH solution or 10% KOH solution or 25% H2O2 solution.</li>
		<li>Heat the solution up to 30&#176; C or combine the different solutions from step 3.1.1 for better effects. Rinse several times in water afterwards. Adapt the bleaching process for the specific species, depending on their leaf characteristics. 
		NOTE: Thicker leaves may need longer periods of solution bath and or the more aggressive solutions. Thinner and more tender leaves may be bleached to a satisfactorily degree in less than 72 hr.</li>
		<li>To color the leaves place them in 100% ethanol. Color them for 2 &#8211; 30 min in 1% safranine solution. To enhance coloring, add an additional treatment with 1% malachite green solution only for several seconds. Adapt the protocol to every species in terms of timing and intensity to achieve optimal results. Rinse several times in water afterwards. If the leaves are to deeply stained, some time in ethanol or decolorizer may help.</li>
	</ol>
	</li>
	<li>Sample analysis
	<ol>
		<li>Scan the leaves with a backlight scanner at a resolution of ca. 1,200 dpi. Match the scans taken to the resolution of the picture, e.g., with the help of a scale, to ensure that pixel length can be traced back to absolute length measures of the scanned leaf.</li>
		<li>Measure area, circumference, length and width of the leaves. Calculate several indices, e.g., length/width and circumference2/area. Cut a 1 by 1 cm rectangle out of the middle of the picture. Measure diameter of the veins of first and second order (do not include the main middle vein). Measure the length of all veins of first order in this quadrat (vein density).</li>
	</ol>
	</li>
</ol>
4. Assessment of Other Leaf Traits
NOTE: Asses typical leaf traits such as specific leaf area (SLA), leaf dry matter content (LDMC), leaf area, element contents, leaf habit, leaf pinnation, leaf compound type, leaf margin type etc. following established protocols 18,19.
<ol>
	<li>Observational leaf traits
	<ol>
		<li>Assess leaf pinnation, leaf compound type, leaf margin type and the presence of extrafloral nectaries18,19 through observation in the field.</li>
	</ol>
	</li>
	<li>Analytical leaf traits
	<ol>
		<li>Collect fresh leaf samples, preferably on the same individuals as used for the other measurements, for the determination of specific leaf area (SLA), leaf area and leaf dry matter content (LDMC) 18,19. After 48 hr in the drying oven at 80 &#176;C, measure element contents and ratios, preferably on the same leaves.</li>
	</ol>
	</li>
</ol>

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The authors have nothing to disclose.

The parameters of stomatal regulation extracted by the method presented in this paper underline the importance of stomatal traits, such as stomata density and stomata index. These novel relationships demonstrate the potential of linking parameters from physiological models to morphological, anatomical and chemical leaf traits 20. Compared to other methods, the present approach bears the advantage of capturing a unique and unequivocal vpd value at which stomatal conductance is down-regulated to half of the modeled gs maximum.
Of all steps outlined in the protocol the most critical ones are the measurements of stomatal conductance. Due to the multifactorial regulation of stomatal conductance ambient weather conditions have a strong influence on gS. Stomatal conductance measurements at high relative humidity and low light intensity may be unreliable 21-23. With respect to morphological and anatomical traits, the protocol should always be adapted to the target species included in the study. In particular in the vein density analysis, the duration of bleaching and staining of leaves should be varied, depending on leaf structure and toughness. Potential limitations of the method include species, for which measurements of stomatal conductance are impossible or complicated and prone to error owing to extraordinary leaf forms. This may include conifers and grasses with very narrow leaf blades.
Our results partly confirm the first hypothesis of a link between stomatal conductance parameters and leaf traits of the leaf economics spectrum (LES), which corresponds to several other studies. For example, Poorter and Bongers (2006)24 reported a close link between gS and traits represented by the LES, e.g., with gS decreasing with increasing leaf lifespan. Accordingly, Schulze et al. (1994) 1 demonstrated clear links between leaf nitrogen content and gSMAX. Similarly, Juhrbandt et al. (2004) 25 found significant relationships between gSMAX and leaf area and leaf nitrogen content.
Our second hypothesis of clear differences with regard to leaf habit could not be confirmed. The high variation in the measured parameters and traits within evergreen and deciduous leaf habit indicate that leaf habit is not a good descriptor of the LES. Brodribb and Holbrook (2005) 26 discussed that leaf habit and leaf physiological strategies may not be inevitably connected since broad trait variation is common in all types of leaf habit.
The approach may be extended to traits and physiological characteristics of plant organs other than leaves, for example to traits related to xylem hydraulics such as specific xylem hydraulic conductivity and microscopy wood traits 27. Similarly, other types of leaf traits as derived from microscopy such as palisade parenchyma structure and epicuticular wax layer structure could be included 28.
In summary, this study confirmed the close connection between the LES and stomatal regulation. In addition, the method presented here revealed facets of stomatal regulation patterns that are not related to the LES. Especially specific leaf traits such as stomata size, density and index as well as vein length deserve future attention in functional plant studies.

To advance the functional understanding of plant leaves, many recent studies have attempted to relate morphological, anatomical and chemical leaf traits to physiological responses, such as leaf stomatal conductance (gS) 1-4. In addition, to leaf traits, stomatal conductance is strongly affected by environmental conditions, such as photosynthetically active photon flux density, air temperature and vpd 5. Various ways have been proposed to model gs - vpd curves6-8 which are mainly based on linear regression of gs on vpd 6. In contrast, the model presented in this study regresses the logits of relative stomatal conductance (i.e., the ratio of gS to maximum stomatal conductance gSMAX) on vpd and accounts for the non-linearity by adding vpd as a quadratic regressor term.
Compared to other models, the new model allows for deriving parameters that describe the vpd at which gS is down-regulated under water shortage. Similarly, the vpd is obtained at which gS is maximal. As such physiological parameters can be expected to be tightly linked to carbon assimilation 9,10 a close link between these model parameters and the key leaf traits to nutrient and resource allocation as reflected in the LES should be expected 3,11. In consequence, there should be also a tight relationship between strategies of stomatal regulation with LES traits. Such a relationship is expected in particular for leaf habit (evergreen versus deciduous) as leaf habit is both correlated with the LES and with water use efficiency12,13. Evergreen species tend to grow slower, but are more efficient in environments poor in nutrients 14. Thus, leaf habit should translate into differing stomatal regulation patterns, with a more conservative water use strategy than deciduous species.
Comparing a large set of broad-leaved tree species in a common garden situation, the following hypotheses were tested: 1) Model parameters from gS - vpd models are connected to leaf traits related to the leaf economics spectrum. 2) Evergreen species have lower mean gS and gSMAX values than deciduous species.

<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>SC 1 Porometer</td>
			<td>Decagon</td>
			<td>NA</td>
			<td>Any other porometer is suitable</td>
		</tr>
		<tr>
			<td>Cable ties to mark leaves</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Plastic sample bags</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Paper sample bags</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Hygrometer</td>
			<td>Trotec</td>
			<td>NA</td>
			<td>Any other is suitable</td>
		</tr>
		<tr>
			<td>Nail polish</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Axioskop 2 plus</td>
			<td>Zeiss</td>
			<td>NA</td>
			<td>Any other is suitable</td>
		</tr>
		<tr>
			<td>Ethanol</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Bleach</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>5% NaOH</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>10% KOH</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>25% H2O2</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Malachite green</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
		<tr>
			<td>Safranine</td>
			<td>NA</td>
			<td>NA</td>
			<td>NA</td>
		</tr>
	</tbody>
</table>

relating stomatal conductance to leaf functional traits

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, morphological leaf traits have the potential to summarize plants strategies in terms of water use efficiency, growth pattern and nutrient use. The leaf economics spectrum (LES) is a recognized framework in functional plant ecology and reflects a gradient of increasing specific leaf area (SLA), leaf nitrogen, phosphorus and cation content, and decreasing leaf dry matter content (LDMC) and carbon nitrogen ratio (CN). The LES describes different strategies ranging from that of short-lived leaves with high photosynthetic capacity per leaf mass to long-lived leaves with low mass-based carbon assimilation rates. However, traits that are not included in the LES might provide additional information on the species&#39; physiology, such as those related to stomatal control. Protocols are presented for a wide range of leaf functional traits, including traits of the LES, but also traits that are independent of the LES. In particular, a new method is introduced that relates the plants&#8217; regulatory behavior in stomatal conductance to vapor pressure deficit. The resulting parameters of stomatal regulation can then be compared to the LES and other plant functional traits. The results show that functional leaf traits of the LES were also valid predictors for the parameters of stomatal regulation. For example, leaf carbon concentration was positively related to the vapor pressure deficit (vpd) at the point of inflection and the maximum of the conductance-vpd curve. However, traits that are not included in the LES added information in explaining parameters of stomatal control: the vpd at the point of inflection of the conductance-vpd curve was lower for species with higher stomatal density and higher stomatal index. Overall, stomata and vein traits were more powerful predictors for explaining stomatal regulation than traits used in the LES.

Many parameters of stomatal conductance and stomatal regulation were found to be related to morphological, anatomical and chemical leaf traits. In the following, the focus will be on the links to vpd at the point of inflection, which decreased with stomatal density (p=0.04) and stomatal index (p=0.03) and increased with leaf carbon content (p=0.02, See Figure 3). The results show that with decreasing vpd at the point of inflection there was a decrease in stomatal density and stomatal index. In contrast, no parameter of stomatal conductance showed a clear relationship to leaf habit. The high variation within the two groups of leaf habit shows that different regulatory mechanisms exist both within the group of evergreen and deciduous leaf habits.

<img alt="Figure 3" src="/files/ftp_upload/52738/52738fig3highres.jpg" width="700" /> 
Figure 3. Result figure for the links between patterns of stomatal conductance regulation and leaf traits. Vapor pressure deficit (vpd) at the point of inflection of the gS - vpd curve (VpdPoi) as a function of (A) stomata density, (B) stomata index, and (C) leaf carbon content 20. Re-print with permission from20. <a href="https://www.jove.com/files/ftp_upload/52738/52738fig3highres.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Relating Stomatal Conductance to Leaf Functional Traits at JoVE.com

Relating Stomatal Conductance to Leaf Functional Traits

Unraveling how physiology and morphology are linked allows a deeper understanding of mechanistic functioning of plant leaves. We present both a procedure to derive parameters of stomatal regulation from stomatal conductance measurements and correlations with traditional functional leaf traits.

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, ...

relating-stomatal-conductance-to-leaf-functional-traits

Research

JoVE Journal

Biology

18.9K Views.  Martin-Luther-University Halle-Wittenberg. Unraveling how physiology and morphology are linked allows a deeper understanding of mechanistic functioning of plant leaves. We present both a procedure to derive parameters of stomatal regulation from stomatal conductance measurements and correlations with traditional functional leaf traits.

Video: Relating Stomatal Conductance to Leaf Functional Traits

Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae

The cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel, that when mutated, can give rise to cystic fibrosis in humans.There is therefore considerable interest in this protein, but efforts to study its structure and activity have been hampered by the difficulty of expressing and purifying sufficient amounts of the protein1-3. Like many 'difficult' eukaryotic membrane proteins, expression in a fast-growing organism is desirable, but challenging, and in the yeast S. cerevisiae, so far low amounts were obtained and rapid degradation of the recombinant protein was observed 4-9. Proteins involved in the processing of recombinant CFTR in yeast have been described6-9 .In this report we describe a methodology for expression of CFTR in yeast and its purification in significant amounts. The protocol describes how the earlier proteolysis problems can be overcome and how expression levels of CFTR can be greatly improved by modifying the cell growth conditions and by controlling the induction conditions, in particular the time period prior to cell harvesting. The reagants associated with this protocol (murine CFTR-expressing yeast cells or yeast plasmids) will be distributed via the US Cystic Fibrosis Foundation, which has sponsored the research. An article describing the design and synthesis of the CFTR construct employed in this report will be published separately (Urbatsch, I.; Thibodeau, P. et al., unpublished). In this article we will explain our method beginning with the transformation of the yeast cells with the CFTR construct - containing yeast plasmid (Fig. 1). The construct has a green fluorescent protein (GFP) sequence fused to CFTR at its C-terminus and follows the system developed by Drew et al. (2008)10. The GFP allows the expression and purification of CFTR to be followed relatively easily. The JoVE visualized protocol finishes after the preparation of microsomes from the yeast cells, although we include some suggestions for purification of the protein from the microsomes. Readers may wish to add their own modifications to the microsome purification procedure, dependent on the final experiments to be carried out with the protein and the local equipment available to them. The yeast-expressed CFTR protein can be partially purified using metal ion affinity chromatography, using an intrinsic polyhistidine purification tag. Subsequent size-exclusion chromatography yields a protein that appears to be &gt;90% pure, as judged by SDS-PAGE and Coomassie-staining of the gel.

Expression and Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein in Saccharomyces cerevisiae

Attempts to express the cystic fibrosis transmembrane conductance regulator (CFTR) in Saccharomyces cerevisiae have, until now, yielded relatively low amounts of protein. This protocol and the associated reagents distributed via the Cystic Fibrosis Foundation should allow the preparation of milligram amounts of this 'difficult' eukaryotic membrane protein.

The  cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride  channel, that when mutated, can give rise to cystic fibrosis in  ...

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to achieve a high stomatal conductance (gs) to capture CO2 for photosynthesis, water is lost by transpiration1,2. Water evaporating from the airspaces is replaced from cell walls, in turn drawing water from the xylem of leaf veins, in turn drawing from xylem in the stems and roots. As water is pulled through the system, it experiences hydraulic resistance, creating tension throughout the system and a low leaf water potential (&Psi;leaf). The leaf itself is a critical bottleneck in the whole plant system, accounting for on average 30% of the plant hydraulic resistance3. Leaf hydraulic conductance (Kleaf = 1/ leaf hydraulic resistance) is the ratio of the water flow rate to the water potential gradient across the leaf, and summarizes the behavior of a complex system: water moves through the petiole and through several orders of veins, exits into the bundle sheath and passes through or around mesophyll cells before evaporating into the airspace and being transpired from the stomata. Kleaf is of strong interest as an important physiological trait to compare species, quantifying the effectiveness of the leaf structure and physiology for water transport, and a key variable to investigate for its relationship to variation in structure (e.g., in leaf venation architecture) and its impacts on photosynthetic gas exchange. Further, Kleaf responds strongly to the internal and external leaf environment3. Kleaf can increase dramatically with irradiance apparently due to changes in the expression and activation of aquaporins, the proteins involved in water transport through membranes4, and Kleaf declines strongly during drought, due to cavitation and/or collapse of xylem conduits, and/or loss of permeability in the extra-xylem tissues due to mesophyll and bundle sheath cell shrinkage or aquaporin deactivation5-10. Because Kleaf can constrain gs and photosynthetic rate across species in well watered conditions and during drought, and thus limit whole-plant performance they may possibly determine species distributions especially as droughts increase in frequency and severity11-14.
We present a simple method for simultaneous determination of Kleaf and gs on excised leaves. A transpiring leaf is connected by its petiole to tubing running to a water source on a balance. The loss of water from the balance is recorded to calculate the flow rate through the leaf. When steady state transpiration (E, mmol &bull; m-2 &bull; s-1) is reached, gs is determined by dividing by vapor pressure deficit, and Kleaf by dividing by the water potential driving force determined using a pressure chamber (Kleaf= E /- &Delta;&psi;leaf, MPa)15.
This method can be used to assess Kleaf responses to different irradiances and the vulnerability of Kleaf to dehydration14,16,17.

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method EFM

We describe a relatively rapid (30 min) and realistic method for simultaneously measurement of leaf hydraulic conductance (Kleaf) and stomatal conductance (gs) for transpiring excised leaves. The method can be modified to measure the light and dehydration responses of Kleaf and gs.

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to ...

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Defects in the cystic fibrosis transmembrane conductance regulator (CFTR) protein cause cystic fibrosis (CF), an autosomal recessive disease that currently limits the average life expectancy of sufferers to &#60;40 years of age. The development of novel drug molecules to restore the activity of CFTR is an important goal in the treatment CF, and the isolation of functionally active CFTR is a useful step towards achieving this goal.
We describe two methods for the purification of CFTR from a eukaryotic heterologous expression system, S. cerevisiae. Like prokaryotic systems, S. cerevisiae can be rapidly grown in the lab at low cost, but can also traffic and posttranslationally modify large membrane proteins. The selection of detergents for solubilization and purification is a critical step in the purification of any membrane protein. Having screened for the solubility of CFTR in several detergents, we have chosen two contrasting detergents for use in the purification that allow the final CFTR preparation to be tailored to the subsequently planned experiments.
In this method, we provide comparison of the purification of CFTR in dodecyl-&#946;-D-maltoside (DDM) and 1-tetradecanoyl-sn-glycero-3-phospho-(1&#39;-rac-glycerol) (LPG-14). Protein purified in DDM by this method shows ATPase activity in functional assays. Protein purified in LPG-14 shows high purity and yield, can be employed to study post-translational modifications, and can be used for structural methods such as small-angle X-ray scattering and electron microscopy. However it displays significantly lower ATPase activity.

Purification of the Cystic Fibrosis Transmembrane Conductance Regulator Protein Expressed in Saccharomyces cerevisiae

Heterologous expression and purification of the cystic fibrosis transmembrane conductance regulator (CFTR) are significant challenges and limiting factors in the development of drug therapies for cystic fibrosis. This protocol describes two methods for the isolation of milligram quantities of CFTR suitable for functional and structural studies.&#160;

Defects in the cystic fibrosis transmembrane conductance regulator (CFTR) protein cause cystic fibrosis (CF), an autosomal recessive disease that ...

Cardiac Pressure-Volume Loop Analysis Using Conductance Catheters in Mice

Cardiac pressure-volume loop analysis is the &#8220;gold-standard&#8221; in the assessment of load-dependent and load-independent measures of ventricular systolic and diastolic function. Measures of ventricular contractility and compliance are obtained through examination of cardiac response to changes in afterload and preload. These techniques were originally developed nearly three decades ago to measure cardiac function in large mammals and humans. The application of these analyses to small mammals, such as mice, has been accomplished through the optimization of microsurgical techniques and creation of conductance catheters. Conductance catheters allow for estimation of the blood pool by exploiting the relationship between electrical conductance and volume. When properly performed, these techniques allow for testing of cardiac function in genetic mutant mouse models or in drug treatment studies. The accuracy and precision of these studies are dependent on careful attention to the calibration of instruments, systematic conduct of hemodynamic measurements and data analyses. We will review the methods of conducting pressure-volume loop experiments using a conductance catheter in mice.

Cardiac pressure-volume loop analysis is the most comprehensive way to measure cardiac function in the intact heart. We describe a technique to perform and analyze cardiac pressure volume loops, using conductance catheters.

Cardiac pressure-volume loop analysis is the &#8220;gold-standard&#8221; in the assessment of load-dependent and load-independent measures of ventricular ...

Collection and Long-Term Maintenance of Leaf-Cutting Ants (Atta) in Laboratory Conditions

Ants are one of the most biodiverse groups of animals on the planet and inhabit different environments. The maintenance of ant colonies in controlled environments enables an enriched comprehension of their biology that can contribute to applied research. This practice is usually employed in population control studies of species that cause economic loss, such as Atta ants. To cultivate their mutualistic fungus, these leaf-cutting ants collect leaves and for this are considered agricultural pests widely distributed throughout the American continent. They are highly socially organized and inhabit elaborated underground nests composed of a variety of chambers. Their maintenance in a controlled environment depends on a daily routine of several procedures and frequent care that are described here. It starts with the collection of queens during the reproductive season (i.e., nuptial flight), which are then individually transferred to plastic containers. Due to the high mortality rate of queens, a second collection can be carried out about 6 months after the nuptial flight, when incipient nests with developed fungus wad are excavated, hand-picked, and placed in plastic containers. In the laboratory, leaves are daily provided to established colonies, and ant-produced waste is weekly removed along with remaining dry plant material. As the fungus garden keeps growing, colonies are transferred to different types of containers according to the experimental purpose. Leaf-cutting ant colonies are placed in interconnected containers, representing the organizational system with functional chambers built by those insects in nature. This setup is ideal to monitor factors such as waste amount, fungus garden health, and the behavior of workers and queen. Facilitated data collection and more detailed observations are considered the greatest advantage of keeping ant colonies in controlled conditions.

Collection and Long-Term Maintenance of Leaf-Cutting Ants Atta in Laboratory Conditions

Here, a protocol is described to successfully collect and maintain healthy Atta (Hymenoptera: Formicidae) ant colonies in laboratory conditions. Additionally, different nest types and configurations are detailed together with possible experimental procedures.

Ants are one of the most biodiverse groups of animals on the planet and inhabit different environments. The maintenance of ant colonies in controlled ...

Identification of the Genes Involved in Stomatal Development via Epidermal Phenotype Scoring

Stomata are small pores on the surface of land plants that are involved in gas exchange and water vapor release, and their function is critical for plant productivity and survival. As such, understanding the mechanisms by which stomata develop and pattern has tremendous agronomic value. This paper describes two phenotypic methods using Arabidopsis cotyledons that can be used to characterize the genes controlling stomatal development and patterning. Presented first are procedures for analyzing the stomatal phenotypes using toluidine blue O-stained cotyledons. This method is fast and reliable and does not require the use of epidermal peels, which are widely used for phenotypic analyses but require specialized training. Due to the presence of multiple cysteine residues, the identification and generation of bioactive EPF peptides that have a role in stomatal development have been challenging. Thus, presented second is a procedure used to identify stomatal ligands and monitor their biological activity by bioassays. The main advantage of this method is that it produces reproducible data relatively easily while reducing the amount of peptide solution and the time required to characterize the role of the peptides in controlling stomatal patterning and development. Overall, these well-designed protocols enhance the efficiency of studying the potential stomatal regulators, including cysteine-rich secretory peptides, which require highly complex structures for their activity.

Identification of the Genes Involved in Stomatal Development via Epidermal Phenotype Scoring

This paper describes two phenotyping methods without the use of epidermal peels to characterize the genes controlling stomatal development. The first method demonstrates how to analyze a stomatal phenotype using a toluidine blue O-stained plant epidermis. The second method describes how to identify stomatal ligands and monitor their biological activities.

Stomata are small pores on the surface of land plants that are involved in gas exchange and water vapor release, and their function is critical for plant ...

A Simple Protocol for Mapping the Plant Root System Architecture Traits

Comprehensive knowledge of plant root system architecture (RSA) development is critical for improving nutrient use efficiency and increasing crop cultivar tolerance to environmental challenges. An experimental protocol is presented for setting up the hydroponic system, plantlet growth, RSA spreading, and imaging. The approach used a magenta box-based hydroponic system containing polypropylene mesh supported by polycarbonate wedges. Experimental settings are exemplified by assessing the RSA of the plantlets under varying nutrient (phosphate [Pi]) supply. The system was established to examine the RSA of Arabidopsis, but it is readily adaptable to study other plants like Medicago sativa (Alfalfa). Arabidopsis thaliana (Col-0) plantlets are used in this investigation as an example to understand the plant RSA. Seeds are surface sterilized by treating ethanol and diluted commercial bleach, and kept at 4 &#176;C for stratification. The seeds are germinated and grown on a liquid half-MS medium on a polypropylene mesh supported by polycarbonate wedges. The plantlets are grown under standard growth conditions for the desired number days, gently picked out from the mesh, and submersed in water-containing agar plates. Each root system of the plantlets is spread gently on the water-filled plate with the help of a round art brush. These Petri plates are photographed or scanned at high resolution to document the RSA traits. The root traits, such as primary root, lateral roots, and branching zone, are measured using the freely available ImageJ software. This study provides techniques for measuring plant root characteristics in controlled environmental settings. We discuss how to (1) grow the plantlets, and collect and spread root samples, (2) obtain pictures of spread RSA samples, (3) capture the images, and (4) use image analysis software to quantify root attributes. The advantage of the present method is the versatile, easy, and efficient measurement of the RSA traits.

We use simple laboratory tools to examine the root system architecture (RSA) of Arabidopsis and Medicago. The plantlets are grown hydroponically over mesh and spread using an art brush to reveal the RSA. Images are taken using scanning or a high-resolution camera, then analyzed with ImageJ to map traits.

Comprehensive knowledge of plant root system architecture (RSA) development is critical for improving nutrient use efficiency and increasing crop cultivar ...

Spatiotemporal Investigation of ERL1 Dynamics via Confocal Imaging

Image-Based Methods to Study Membrane Trafficking Events in Stomatal Lineage Cells

In eukaryotic cells, membrane components, including proteins and lipids, are spatiotemporally transported to their destination within the endomembrane system. This includes the secretory transport of newly synthesized proteins to the cell surface or the outside of the cell, the endocytic transport of extracellular cargoes or plasma membrane components into the cell, and the recycling or shuttling transport of cargoes between the subcellular organelles, etc. Membrane trafficking events are crucial to the development, growth, and environmental adaptation of all eukaryotic cells and, thus, are under stringent regulation. Cell-surface receptor kinases, which perceive ligand signals from the extracellular space, undergo both secretory and endocytic transport. Commonly used approaches to study the membrane trafficking events using a plasma membrane-localized leucine-rich-repeat receptor kinase, ERL1, are described here. The approaches include plant material preparation, pharmacological treatment, and confocal imaging setup. To monitor the spatiotemporal regulation of ERL1, this study describes the co-localization analysis between ERL1 and a multi-vesicular body marker protein, RFP-Ara7, the time series analysis of these two proteins, and the z-stack analysis of ERL1-YFP treated with the membrane trafficking inhibitors brefeldin A and wortmannin.

Author Spotlight: Image-Based Methods to Study Membrane Trafficking Events in Stomatal Lineage Cells  

Several commonly used methods are introduced here to study the membrane trafficking events of a plasma membrane receptor kinase. This manuscript describes detailed protocols including the plant material preparation, pharmacological treatment, and confocal imaging setup.

In eukaryotic cells, membrane components, including proteins and lipids, are spatiotemporally transported to their destination within the endomembrane ...