This work was funded by National Science Foundation grants IOS-1256565 and IOS-1557638 to AWS. We thank Patricia Wittkopp and three anonymous reviewers for their helpful comments on an earlier version of this paper.

1. Specimen Mounting
NOTE: Store dead flies in 70% ethanol in water prior to imaging.
<ol>
	<li>Pour 10 mL of 1.25% agar dissolved in boiling water in a 60 mm x 15 mm Petri dish and allow it to set.</li>
	<li>Under a dissecting microscope, use a pair of fine-point forceps to make a ~20 mm ong, 2 mm wide, 1 mm deep groove in the surface of the gel. Using fine forceps, embed the ventral side of an adult fly in the groove, with the dorsal side of the fly projecting above the gel. 
	NOTE: The looseness of the gel allows for easy repositioning without damaging the specimen. The same groove can be used for multiple specimens, although it will become dirty, broken-up, and unusable with time. The user can then make another groove in the same gel. Each plate can be used to image ~200 flies.</li>
	<li>Completely cover the specimen in 70% ethanol in water to reduce any light reflections from the waxy cuticle and to prevent wing damage during specimen manipulation.</li>
</ol>
2. Microscope Setup
NOTE: Images are acquired using a dissecting scope, transmitted light base, digital camera, and gooseneck cold light source attached to a computer running image acquisition control software. Software instructions are specific to Micro-Manager v1.4.2044, which is an open-source software that incorporates ImageJ45.
<ol>
	<li>Turn on the microscope, digital camera, double gooseneck cold light source, and computer.</li>
	<li>Run the image capture software to open a Micro-Manager window and an ImageJ window. In the ImageJ window click &#34;Image&#34; &#62; &#34;Type&#34; &#62; &#34;8-Bit&#34; to set all images as 8-bit. Click &#34;live&#34; in the Micro-Manager window to open a &#34;Snap/Live&#34; window showing a real-time preview from the camera.
	<ol>
		<li>Maximize the size of the &#34;Snap/Live&#34; window if necessary. Select &#34;Grayscale&#34; in the pulldown &#34;Display mode&#34; menu in the &#34;Contrast&#34; tab of the Micro-Manager window.</li>
	</ol>
	</li>
	<li>Turn on the cold light source to its maximum intensity and position the tips of each gooseneck to approximately 120 mm from the stage, one on the left and one on the right. 
	NOTE: Users can also use an annular illuminator, although this may generate a ring of reflected light around the fly abdomen.</li>
	<li>Manually set the microscope magnification to 60X so that the field of view captures an area approximately 3 mm in diameter on the stage.</li>
	<li>Place a 2 mm stage micrometer on the stage (switching the background to white if necessary). While looking at the live preview, focus on the stage micrometer and adjust the exposure in the Micro-Manager window by entering the exposure time in ms in the &#34;Exposure&#34; box.</li>
	<li>To spatially calibrate the camera, select the &#34;straight line&#34; tool in the ImageJ window and draw a line the length of the stage micrometer. In the ImageJ window click &#34;Analyze&#34; &#62; &#34;Set Scale&#34; to open the &#34;Set Scale&#34; window, enter the length of the micrometer in &#181;m in the &#34;Known distance&#34; box, and enter &#34;&#181;m&#34; in the &#34;Unit of length&#34; box.
	<ol>
		<li>See that the &#34;Set Scale&#34; window then displays the scale in &#34;pixels/&#181;m.&#34; Make a note of the scale and click &#34;OK.&#34;</li>
	</ol>
	</li>
	<li>In the &#34;Snap/Live&#34; window, click &#34;Stop&#34; and then &#34;Snap&#34; to capture an image of the stage micrometer.</li>
	<li>Save the image as an 8-bit grayscale TIFF to ensure the ability to spatially calibrate the images again if necessary. In the ImageJ window click &#34;File&#34; &#62; &#34;Save As&#34; &#62; &#34;Tiff&#8230;&#34; Specify where to save the file in the file browser, name the file, and click &#34;Save.&#34;</li>
	<li>Switch the stage to black and place a Petri dish holding a fly mounted in agar (steps 1.1-1.2) on the stage.</li>
	<li>Look through the microscope and position the fly to ensure that the dorsal midline is straight up in order to best view the pigmentation pattern. Move any wings and appendages to ensure that the view of the abdomen is unobstructed. If the pigmented cuticle (a2-a5) is not visible, squeeze the abdomen laterally until it is (although the abdomen of flies stored in 70% ethanol in water stretch, so that this is not usually necessary). 
	NOTE: When positioning the fly, the user may need to use a lower magnification (20X). The magnification must be returned to 60X before proceeding.</li>
	<li>Manually focus on the dorsal abdomen of the fly. Manually adjust the tips of the light source to minimize the shadows and reflection on the dorsal abdomen.</li>
	<li>While looking at the live preview on the computer screen, and using the pixel value histogram in the &#34;Contrast&#34; tab of the Micro-Manager window, adjust the exposure as described in step 2.4 to maximize the range of pixel values of the preview image.</li>
	<li>Remove the fly and Petri dish and replace them with an LED (spectral output of 430-660 nm) connected to a voltage meter, centered in the field of view at the same position as the fly. Use the LED and voltage meter as a light meter46 and record the voltage generated by the light striking the LED (~125 mV). 
	NOTE: The LED and voltage meter are used to ensure that light levels are constant across multiple imaging sessions within a single experiment.</li>
	<li>For the duration of the experiment, do not further change the position or intensity of the light source, the magnification of the microscope, or the exposure of the camera.</li>
</ol>
3. Specimen Imaging
<ol>
	<li>Place a Petri dish holding a fly mounted in agar (steps 1.1-1.3) on the black microscope stage.Adjust the position of the fly so that the third and fourth abdominal segments are visible and the dorsal midline is straight up, as described in step 2.9. Ensure that the magnification is at 60x before proceeding.</li>
	<li>Manually focus the microscope such that the third and fourth dorsal abdominal tergites are in focus. Use the image capture software to acquire an image as an 8-bit grayscale TIFF, as described in step 2.6. 
	NOTE: The image can be captured in color and subsequently converted to grayscale for analysis.</li>
	<li>Save the image as &#34;SESH000_sampleID.tiff,&#34; as described in step 2.7. 
	NOTE: Here, [SESH] is constant, [000] is the session number and is variable but must be three digits long, and [sampleID] is whatever the user wishes, although it must not contain any additional underscore (_) characters and must be of a constant length. [sampleID] should include details of the factors used in the analysis of the pigmentation data (e.g., temperature or lineage), separated by a distinctive non-alphabetical character, such as a hyphen (-). This allows these factors to be easily parsed out of [sampleID] using standard statistical software.</li>
	<li>Remove the Petri dish from the stage and replace the fly with the next specimen. Repeat steps 3.1-3.3 until all the specimens have been imaged, without further adjusting the lighting levels, magnification, or exposure.</li>
</ol>
4. Imaging Across Multiple Sessions
<ol>
	<li>If images need to be taken over multiple sessions, maintain the light intensity, exposure, and magnification across sessions. At the beginning of each session, check the spatial calibration of the camera (step 2.4) and the light intensity at the stage (as measured by the LED/voltage meter, step 2.12).</li>
	<li>Capture and save an image of the stage micrometer (steps 2.5-2.7) to ensure the ability to spatially calibrate the images again, if necessary.</li>
	<li>Use at least 15 control specimens and randomly re-image them in each session to allow for the detection and elimination of session effects. Ensure that duplicate control specimens between sessions have the same [sampleID] but different [SESH000]. 
	NOTE: The control specimens are flies collected, stored, and mounted identically to experimental specimens but are re-imaged across sessions. The precise number of control specimens will depend on the user&#39;s experimental setup. See the discussion for further details.</li>
</ol>
5. Image Analysis
NOTE: Image analysis is conducted in ImageJ45 and uses the &#34;Measurement of Pigmentation.ijm,&#34; macro provided as a supplementary file.
<ol>
	<li>Place all images to be analyzed in the same folder.</li>
	<li>Start ImageJ and run the &#34;Measurement of Pigmentation.ijm&#34; macro by clicking &#34;Plugins&#34; &#62; &#34;Macro&#34; &#62; &#34;Run,&#34; selecting &#34;Measurement of Pigmentation.ijm&#34; in the file browser, and clicking &#34;open.&#34; 
	NOTE: All subsequent steps are within the macro. Each step is an individual macro command.</li>
	<li>Note that an &#34;Action Required&#34; dialog box opens, stating &#34;Choose the folder where images are stored.&#34; Click &#34;OK&#34; and use the file browser to select the folder containing the images and then click &#34;choose.&#34;</li>
	<li>Note that an &#34;Action Required&#34; dialog will box open, stating &#34;Choose the folder where you want the data to be stored.&#34; Click &#34;OK&#34; and use the file browser to select the desired folder for saving the pigmentation profiles. Click &#34;choose.&#34;</li>
	<li>Note that a dialog box will open, asking &#34;How many characters in your sample ID?&#34; In the data input box, enter the number of characters in [SampleID], as specified in step 3.3, and click &#34;OK.&#34;</li>
	<li>Note that a dialog box will open, asking &#34;How wide is your ROI?&#34; In the data input box, enter the pixel width of the anterior-posterior strip along which the pigmentation profile is to be read (green rectangle, Figure 1G, Figure 2A, and 2A&#39;). Click &#34;OK;&#34; the default is 20 pixels. 
	NOTE: The pigmentation profile is read across a strip of cuticle, rather than a line, to reduce noise due to hairs and bristles. The width of this strip will depend on the resolution of the image, but it should be ~1/20th of the width of the abdomen, in pixels.</li>
	<li>Note that the macro will open the image of the first fly, and a dialog box will ask whether to measure the current fly (click &#34;Yes&#34;), to go on to the next fly (click &#34;No&#34;), or to exit the macro (click &#34;Cancel&#34;).</li>
	<li>Note that a dialog box will open, stating &#34;Define the midline of the dorsal abdomen, from ANTERIOR to POSTERIOR.&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from anterior to posterior to define the midline of the dorsal abdomen. Click &#34;OK;&#34; see Figure 2A and 2A&#39;, yellow line. 
	NOTE: This is used to reorient the image so that the dorsal midline lies horizontally across the screen, with the anterior on the left, making the subsequent steps easier.</li>
	<li>Note that a dialog box will open, stating &#34;Define the POSTERIOR edge of Tergite 4 just behind the pigment band.&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from the posterior midline edge to the right-lateral edge, such that the center of the line (marked by a white square) sits just posteriorly to the posterior edge of the pigment band (cuticle a5). Click &#34;OK;&#34;. See Figure 2A and 2A&#8242;, magenta line. 
	NOTE: The R script will automatically detect the posterior edge of the pigment band from the pigmentation profile.</li>
	<li>Note that a dialog box will open, stating &#34;Define the ANTERIOR edge of Tergite 4 at the anterior edge of the pigmented cuticle (a2).&#34; The &#34;straight line&#34; tool will already be selected. Draw a line from the anterior midline edge to the right-lateral edge, such that the center of the line (marked by a white square) sits at the anterior edge of the pigmented cuticle (cuticle a2). Click &#34;OK;&#34;. See Figure 2A and 2A&#39;, cyan line. 
	NOTE: The R script will define this point as the anterior edge of the pigmented cuticle of the tergite. On the image, the macro will show the region of interest (ROI) along which the pigmentation profile is read (green rectangle, Figure 2A and 2A&#8242;, enlarged in Figure 2B and 2B&#8242;). The macro will also open a second window showing the pigmentation profile for the ROI (Figure 2C and 2C&#8242;), where the x-axis is the position, expressed as the number of pixels from the posterior edge of the profile, and the y-axis is the average pixel value at each position.</li>
	<li>View the plots of the pigmentation profile that will be opened by the macro. If necessary, click &#34;Live&#34; in the profile window to adjust the position of the ROI so that it does not include any structures (e.g., bristles) that would influence the pigmentation profile. Once the profile is satisfactory, click &#34;OK.&#34;</li>
	<li>Repeat steps 5.8-5.11 for Tergite 3. 
	NOTE: The macro then exports the pigmentation profiles as two CSV files, each named &#34;SESH000_samplename_TX_profile.csv,&#34; where [SESH000_samplename] is the image name and [TX] is either T3 or T4 for the third and fourth tergites, respectively.</li>
	<li>Note that the macro opens the next image. Repeat steps 5.7-5.13 until all images have been analyzed.</li>
</ol>
6. Data Preprocessing, Analysis, and Session Correction
NOTE: All data analysis is conducted in R47 and uses the &#34;Analysis of Pigmentation.R&#34; script provided. Below, &#34;L&#8230;&#34; indicates which line(s) of the script to run for each part of the analysis. See the Supplementary Information for additional details on how the analysis is conducted.
<ol>
	<li>Edit the R script to set the working directory (L6) and define the filepath to the folder containing the.csv profiles (L11).</li>
	<li>Run L13-15 to generate a list of the pigmentation profiles stored in the profile folder.</li>
	<li>Load and run the &#34;reader&#34; and &#34;addPrimaryKey&#34; functions (L17-41) to read the profiles into a single data frame.</li>
	<li>Edit the script at L43 to specify the spatial calibration of the images in &#181;m/pixels, as determined in step 2.5.</li>
	<li>Load and run the &#34;adjustments&#34; function (L46-58) to convert the profile position (x-axis, Figure 2C and 2C&#8242;) from pixels-from-posterior-edge-of-ROI to &#181;m-from-anterior-edge-of-ROI and the profile value (y-axis, Figure 2C and 2C&#8242;) from the pixel value (0 = black, 255 = white) to the pigmentation value (0 = no pigment, 255 = maximum pigment).</li>
	<li>Load and run the &#34;spline.der.er&#34; function (L60-71) to generate the cubic spline of the pigmentation profiles and its first and second derivatives (Figure 2D-2F and 2D&#8242;-2F&#8242;).</li>
	<li>Load and run the &#34;coord&#34; and &#34;assmbly.coord&#34; functions (L74-163), first to extract the position of the posterior (T3) and anterior (T2) edges of the pigment band (Figure 2D and 2D&#8242;) and the posterior edge of the a2 cuticle (T1, Figure 2D and 2D&#8242;), and then to extract the maximum (Pmax) and minimum (Pmin) pigmentation values, taken at T3 and T1, respectively. 
	NOTE: The anterior edge of the a2 cuticle has already been defined in step 5.9.</li>
	<li>Optional: Load and run the &#34;chek&#34; function (L165-175) to check whether the &#34;coord&#34; function is correctly identifying positions T1-3 for a randomly selected pigmentation profile.</li>
	<li>Load and run the index and metrics functions (L178-193) to generate a data table with the headings &#34;Session,&#34; &#34;Sample,&#34; &#34;Tergite,&#34; &#34;id&#34; (a concatenation of Sample and Tergite), &#34;Pmax,&#34; &#34;Pmin,&#34; &#34;Wband&#34;(width of the pigment band, = T3 - T2), and &#34;Wtergite&#34;(width of the pigmented cuticles a2-a5, = T3).</li>
	<li>Load and run the &#34;correction&#34; function (L196-234) to generate a data table that corrects Pmax and Pmin for any nuisance factors arising due to session effects. Use the average increase (or decrease) in Pmax or Pmin from the control specimens re-imaged across temporally adjacent sessions.</li>
</ol>

The authors have nothing to disclose.

This methodology allows for the precise, rapid, and repeatable acquisition of pigmentation data in a quantitative form suitable for multiple downstream analyses. The method has been used to acquire data on the effect of temperature on abdominal pigmentation in an isogenic line of flies. However, the methodology could be used in forward-genetics studies to identify genes that underlie pigmentation differences between individuals, populations, or species, or reverse-genetic studies to explore the effects of specific genes ...

Pigmentation shows enormous phenotypic variation between species, populations, and individuals, and even within individuals during ontogeny1,2,3,4,5,6. Although there are myriad studies of pigmentation in a wide variety of animals, pigmentation has perhaps been best studied in Drosophila melanogaster, where the full power of molecular genetics has been used to elucidate the developmental and physiological mechanisms that regulate pigmentation and how these mechanisms evolve1,6. Much is known about the genes that regulate the biochemical synthesis of pigments in D. melanogaster7,8 and the genes that control the temporal and spatial distribution of this biosynthesis9,10,11,12,13. Furthermore, genetic mapping has identified the genetic loci underlying intra- and interspecific differences in pigmentation in D. melanogaster14,15,16,17. The relationships between pigmentation and pleiotropic traits, such as behavior18,19 and immunity19,20, have also been explored, as has the adaptive significance of pigmentation patterns15,21,22. As such, pigmentation in D. melanogaster has emerged as a powerful yet simple model for the development and evolution of complex phenotypes.
Pigmentation in adult D. melanogaster is characterized by distinct patterns of melanization across the body, particularly on the wings and dorsal thorax and abdomen. It is the pigmentation of each cuticular plate (tergite) on the dorsal abdomen, however, that has received the most research attention. There is considerable variation in this pigmentation (Figure 1A-F), because of both genetic17,23 and environmental24,25 factors. The cuticle of an abdominal tergite is made up of anterior and posterior developmental compartments (Figure 1G), each of which can be further subdivided depending based on pigmentation and ornamentation26. The anterior compartment includes six cuticle types (a1-a6), and the posterior compartment includes three (p1-p3) (Figure 1G). Of these, the p1, p2, and a1 cuticle are typically folded under the tergite in un-stretched abdomens so that they are hidden. The reliably visible cuticle is characterized by a band of heavy pigmentation, here referred to as a &#34;pigment band,&#34; comprised of cuticle types a4 (hairy with moderate bristles) and a5 (hairy with large bristles), with the posterior edge of the band more intensely pigmented than the anterior edge (Figure 1G). Anterior to this band is a region of lightly pigmented hairy cuticle, which has bristles posteriorly (a3) but not anteriorly (a2). Variation in pigmentation between flies is observed in both the intensity of pigmentation and in the width of the pigment band. In general, variation is greatest in the most posterior segments (abdominal segments 5, 6, and 7) and is lower in the more anterior segments (abdominal segments 3 and 4)24. Furthermore, there is a sexual dimorphism in D. melanogaster pigmentation, with males generally having wholly pigmented fifth and sixth abdominal tergites (Figure 4C).
In most studies of abdominal pigmentation in D. melanogaster, pigmentation has been treated as a categorical or ordinal trait, with the pattern measured qualitatively27,28,29 or semi-quantitatively on a scale14,15,16,17,24,30,31,32,33,34,35,36,37. These methods inevitably suffer from a lack of precision, and because they rely on the subjective assessment of pigmentation, it is difficult to compare the data across studies. Several authors have quantified the spatial dimensions of pigmentation38,39, the intensity of pigmentation of a particular cuticle type23,25,39,40, or the average intensity of pigmentation across the abdominal tergite as a whole41,42,43. Nevertheless, these quantification methods do not measure both the intensity and the spatial distribution of abdominal pigmentation simultaneously and therefore do not capture the nuances of how pigmentation varies across the abdominal tergite. Furthermore, several of these quantification methods38,41,42,43 require the dissection and mounting of the abdominal cuticle. This is both time consuming and destroys the sample, making it unavailable for additional morphological analyses. As the understanding of the development and evolution of abdominal pigmentation deepens, more sophisticated tools to quickly and precisely measure both the spatial distribution and the intensity of pigmentation will be required.
The overall goal of this method is to utilize digital image analysis to obtain a replicable and more precise measure of the abdominal pigmentation in D. melanogaster. The methodology includes three stages. First, the adult fly is non-destructively mounted, and a digital image of the dorsal abdomen is taken. Second, using an ImageJ macro, the user defines an anterior-posterior strip of pixels that extends from the anterior of the a2 cuticle to the posterior of the a5 cuticle (green box, Figure 1G) on both the third and fourth abdominal segments. The average pixel value across the width of this strip is then extracted along its long axis, generating a profile that captures the spatial distribution and intensity of pigmentation as it changes from the anterior to the posterior of the tergite. Third, an R script is used to describe the pigmentation profile mathematically using a cubic spline. The R script then uses the spline and its first and second derivative to extract the width of the a2-a5 cuticle, the width of the pigment band, and the maximum and minimum levels of pigmentation. The method therefore quantifies both the spatial characteristics and the depth of abdominal pigmentation.
This methodology quantifies the pigmentation of the third and fourth abdominal tergites, which have been the focus of numerous previous studies1,15,23,24,25,28,33,39,42, either exclusively or in combination with more posterior tergites. Although less variable than the fifth and sixth abdominal tergites, the third and fourth tergites are not completely pigmented in males, so this protocol can be applied to both males and females. Nevertheless, as shown here, the protocol can be used to measure pigmentation in the fifth and sixth abdominal tergites in females. Furthermore, minor modifications of the scripts used to extract the characteristics of the pigmentation profile should allow for the method to be used to quantify the variation in pigmentation in a wide variety of other organisms.

<table><tbody><tr><td>Dumont #5 Biology Forceps</td><td>FST</td><td>11252-30</td><td></td></tr><tr><td>Agar</td><td>Sigma-Aldrich</td><td>5040</td><td></td></tr><tr><td>Dissecting Scope</td><td>Leica</td><td>MZ16FA</td><td></td></tr><tr><td>Base</td><td>Leica</td><td>MDG41</td><td></td></tr><tr><td>Camera</td><td>Leica</td><td>DFC280</td><td></td></tr><tr><td>Gooseneck Cold Light Source</td><td>Schott</td><td>ACE 1</td><td></td></tr><tr><td>Image Acquisition Control Software</td><td>Micro-Manager v1.3.20</td><td></td><td>https://micro-manager.org/</td></tr><tr><td>Image Analysis Software</td><td>ImageJ</td><td></td><td>https://imagej.nih.gov/ij/</td></tr><tr><td>Data Analysis Software</td><td>R 3.3.2</td><td></td><td>https://www.r-project.org/</td></tr><tr><td>LED</td><td>Thor Labs</td><td>LEDWE-15</td><td></td></tr><tr><td>Multimeter</td><td>Fluke</td><td>Fluke 75 Series II</td><td></td></tr><tr><td>60 mm x 15 mm Petri dish</td><td>Celltreat Scientific Products</td><td>229663</td><td></td></tr><tr><td>Stage micrometer</td><td>Klarman Rulings, Inc.</td><td>KR-867</td><td></td></tr></tbody></table>

quantifying abdominal pigmentation in drosophila melanogaster

Pigmentation is a morphologically simple but highly variable trait that often has adaptive significance. It has served extensively as a model for understanding the development and evolution of morphological phenotypes. Abdominal pigmentation in Drosophila melanogaster has been particularly useful, allowing researchers to identify the loci that underlie inter- and intraspecific variations in morphology. Hitherto, however, D. melanogaster abdominal pigmentation has been largely assayed qualitatively, through scoring, rather than quantitatively, which limits the forms of statistical analysis that can be applied to pigmentation data. This work describes a new methodology that allows for the quantification of various aspects of the abdominal pigmentation pattern of adult D. melanogaster. The protocol includes specimen mounting, image capture, data extraction, and analysis. All the software used for image capture and analysis feature macros written for open-source image analysis. The advantage of this approach is the ability to precisely measure pigmentation traits using a methodology that is highly reproducible across different imaging systems. While the technique has been used to measure variation in the tergal pigmentation patterns of adult D. melanogaster, the methodology is flexible and broadly applicable to pigmentation patterns in myriad different organisms.

The protocol was used to explore the effect of rearing temperature on abdominal pigmentation. Previous studies have shown that an increase in developmental temperature results in a decrease in the spread of abdominal pigmentation in several species of Drosophila, including D. melanogaster30,32. Specifically, in abdominal tergites 3 and 4, the extent of pigmentation (width of the pigment band) decreases from 17 &#...

Watch this Scientific Journal Video about Quantifying Abdominal Pigmentation in Drosophila melanogaster at JoVE.com

Quantifying Abdominal Pigmentation in Drosophila melanogaster

This work presents a method to quickly and precisely quantify the abdominal pigmentation of Drosophila melanogaster using digital image analysis. This method streamlines the procedures between phenotype acquisition and data analysis and includes specimen mounting, image acquisition, pixel value extraction, and trait measurement.

Quantifying Abdominal Pigmentation in Drosophila melanogaster

Pigmentation is a morphologically simple but highly variable trait that often has adaptive significance. It has served extensively as a model for ...

quantifying-abdominal-pigmentation-in-drosophila-melanogaster

Research

JoVE Journal

Genetics

8.9K Views.  Lake Forest College.  Dit werk biedt een methode om de abdominale pigmentatie van Drosophila melanogaster snel en nauwkeurig te kwantificeren met behulp van digitale beeldanalyse . Deze methode stroomlijnt de procedures tussen fenotype-acquisitie en data-analyse en omvat voorbeeldmontage, beeldverzameling, pixelwaarde-extractie en eigenschappen van eigenschappen. 

Video: Quantifying Abdominal Pigmentation in Drosophila melanogaster

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Drosophila is an excellent model organism that can be used to screen compounds that might be useful for cancer therapy. The method described here is a cost-effective in vivo method to identify heterochromatin-promoting compounds by using Drosophila. The Drosophila&#39;s DX1 strain, having a variegated eye color phenotype that reflects the extents of heterochromatin formation, thereby providing a tool for a heterochromatin-promoting drug screen. In this screening method, eye variegation is quantified based on the surface area of red pigmentation occupying parts of the eye and is scored on a scale from 1 to 5. The screening method is straightforward and sensitive and allows for testing compounds in vivo. Drug screening using this method provides a fast and inexpensive way for identifying heterochromatin-promoting drugs that could have beneficial effects in cancer therapeutics. Identifying compounds that promote the formation of heterochromatin could also lead to the discovery of epigenetic mechanisms of cancer development.

A Screening Method for Identification of Heterochromatin-Promoting Drugs Using Drosophila

Drosophila is a widely used experimental model suitable for screening drugs with potential applications for cancer therapy. Here, we describe the use of Drosophila variegated eye color phenotypes as a method for screening small-molecule compounds that promote heterochromatin formation.

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Dyeing Insects for Behavioral Assays: the Mating Behavior of Anesthetized Drosophila

Mating experiments using Drosophila have contributed greatly to the understanding of sexual selection and behavior. Experiments often require simple, easy and cheap methods to distinguish between individuals in a trial. A standard technique for this is CO2 anaesthesia and then labelling or wing clipping each fly. However, this is invasive and has been shown to affect behavior. Other techniques have used coloration to identify flies. This article presents a simple and non-invasive method for labelling Drosophila that allows them to be individually identified within experiments, using food coloring. This method is used in trials where two males compete to mate with a female. Dyeing allowed quick and easy identification. There was, however, some difference in the strength of the coloration across the three species tested. Data is presented showing the dye has a lower impact on mating behavior than CO2 in Drosophila melanogaster. The impact of CO2 anaesthesia is shown to depend on the species of Drosophila, with D. pseudoobscura and D. subobscura showing no impact, whereas D. melanogaster males had reduced mating success. The dye method presented is applicable to a wide range of experimental designs.

Dyeing Insects for Behavioral Assays: the Mating Behavior of Anesthetized Drosophila

This protocol describes a simple, cost effective way to individually identify Drosophila or other insects. Demonstration data investigating mating success across three species of Drosophila show that this method is comparable or better than the use of CO2 anaesthesia.

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Neuroscience

Unbiased Quantification of Ommatidia in Drosophila Eye Models

Quantifying Drosophila melanogaster Eye Phenotypes: A Computational Approach Integrating ilastik and Flynotyper

The Drosophila melanogaster compound eye is a well-structured and comprehensive array of around 800 ommatidia, exhibiting a symmetrical and hexagonal pattern. This regularity and ease of observation make the Drosophila eye system a powerful tool to model various human neurodegenerative diseases. However, ways of quantifying abnormal phenotypes, such as manual ranking of eye severity scores, have limitations, especially when ranking weak alterations in eye morphology. To overcome these limitations, computational approaches have been developed such as Flynotyper. The use of a ring light allows for better qualitative images accessing the intactness of individual ommatidia. However, these images cannot be analyzed by Flynotyper directly due to shadows on ommatidia introduced by the ring light. Here, we describe an unbiased way to quantify rough eye phenotypes observed in Drosophila disease models by combining two software, ilastik and Flynotyper. By preprocessing the images with ilastik, successful quantification of the rough eye phenotype can be achieved with Flynotyper.

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The Drosophila eye system is a useful tool for studying various biological processes, particularly human neurodegenerative diseases. However, manual quantification of rough eye phenotypes can be biased and unreliable. Here we describe a method by which ilastik and Flynotyper are used to quantify eye phenotype in an unbiased way.

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Developmental Biology

Drosophila Pupal Abdomen Immunohistochemistry

The Drosophila pupal abdomen is an established model system for the study of epithelial morphogenesis and the development of sexually dimorphic morphologies 1-3. During pupation, which spans approximately 96 hours (at 25 &deg;C), proliferating populations of imaginal cells replace the larval epidermis to generate the adult abdominal segments. These imaginal cells, born during embryogenesis, exist as lateral pairs of histoblast nests in each abdominal segment of the larvae. Four pairs of histoblast nests give rise to the adult dorsal cuticle (anterior and posterior dorsal nests), the ventral cuticle (ventral nests) and the spiracles associated with each segment (spiracle nests) 4. Upon puparation, these diploid cells (distinguishable by size from the larger polyploid larval epidermal cells- LECs) begin a stereotypical process of proliferation, migration and replacement of the LECs. Various molecular and genetic tools can be employed to investigate the contributions of genetic pathways involved in morphogenesis of the adult abdomen. Ultimate adult phenotypes are typically analyzed following dissection of adult abdominal cuticles. However, investigation of the underlying molecular processes requires immunohistochemical analyses of the pupal epithelium, which present unique challenges. Temporally dynamic morphogenesis and the interactions of two distinct epithelial populations (larval and imaginal) generate a fragile tissue prone to excessive cell loss during dissection and subsequent processing. We have developed methods of dissection, fixation, mounting and imaging of the Drosophila pupal abdominem epithelium for immunohistochemical studies that generate consistent high quality samples suitable for confocal or standard fluorescent microscopy.

Drosophila Pupal Abdomen Immunohistochemistry

Antibody staining of the Drosophila pupae can enhance genetic analyses of adult abdominal developmental genetics. We present our protocol for dissection, fixation and antibody staining of staged Drosophila pupal abdomen.

The Drosophila pupal abdomen is an established model system for the study of epithelial morphogenesis and the development of sexually dimorphic ...

Biology

Quantitative Comparison of cis-Regulatory Element (CRE) Activities in Transgenic Drosophila melanogaster

Gene expression patterns are specified by cis-regulatory element (CRE) sequences, which are also called enhancers or cis-regulatory modules. A typical CRE possesses an arrangement of binding sites for several transcription factor proteins that confer a regulatory logic specifying when, where, and at what level the regulated gene(s) is expressed. The full set of CREs within an animal genome encodes the organism&prime;s program for development1, and empirical as well as theoretical studies indicate that mutations in CREs played a prominent role in morphological evolution2-4. Moreover, human genome wide association studies indicate that genetic variation in CREs contribute substantially to phenotypic variation5,6. Thus, understanding regulatory logic and how mutations affect such logic is a central goal of genetics. 
Reporter transgenes provide a powerful method to study the in vivo function of CREs. Here a known or suspected CRE sequence is coupled to heterologous promoter and coding sequences for a reporter gene encoding an easily observable protein product. When a reporter transgene is inserted into a host organism, the CRE&prime;s activity becomes visible in the form of the encoded reporter protein. P-element mediated transgenesis in the fruit fly species Drosophila (D.) melanogaster7 has been used for decades to introduce reporter transgenes into this model organism, though the genomic placement of transgenes is random. Hence, reporter gene activity is strongly influenced by the local chromatin and gene environment, limiting CRE comparisons to being qualitative. In recent years, the phiC31 based integration system was adapted for use in D. melanogaster to insert transgenes into specific genome landing sites8-10. This capability has made the quantitative measurement of gene and, relevant here, CRE activity11-13 feasible. The production of transgenic fruit flies can be outsourced, including phiC31-based integration, eliminating the need to purchase expensive equipment and/or have proficiency at specialized transgene injection protocols. 
Here, we present a general protocol to quantitatively evaluate a CRE&prime;s activity, and show how this approach can be used to measure the effects of an introduced mutation on a CRE&prime;s activity and to compare the activities of orthologous CREs. Although the examples given are for a CRE active during fruit fly metamorphosis, the approach can be applied to other developmental stages, fruit fly species, or model organisms. Ultimately, a more widespread use of this approach to study CREs should advance an understanding of regulatory logic and how logic can vary and evolve.

Quantitative Comparison of cis-Regulatory Element CRE Activities in Transgenic Drosophila melanogaster

Phenotypic variation for traits can result from mutations in cis-regulatory element (CRE) sequences that control gene expression patterns. Methods derived for use in Drosophila melanogaster can quantitatively compare the levels of spatial and temporal patterns of gene expression mediated by modified or naturally occurring CRE variants.

Gene expression patterns are specified by cis-regulatory element (CRE) sequences, which are also called enhancers or cis-regulatory modules. A typical CRE ...

Electrophysiological Methods for Measuring Photopigment Levels in Drosophila Photoreceptors

The Drosophila G-protein-coupled photopigment rhodopsin (R) is composed of a protein (opsin) and a chromophore. The activation process of rhodopsin is initiated by photon absorption-inducing isomerization of the chromophore, promoting conformational changes of the opsin and resulting in a second dark-stable photopigment state (metarhodopsin, M). Investigation of this bi-stable photopigment using random mutagenesis requires simple and robust methods for screening mutant flies. Therefore, several methods for measuring reductions in functional photopigment levels have been designed. One such method exploits the charge displacements within the photopigment following photon absorption and the huge amounts of photopigment molecules expressed in the photoreceptors. This electrical signal, named the early receptor potential (or early receptor current), is measured by a variety of electrophysiological methods (e.g., electroretinogram and whole-cell recordings) and is linearly proportional to functional photopigment levels. The advantages of this method are the high signal-to-noise ratio, direct linear measurement of photopigment levels, and independence of phototransduction mechanisms downstream to rhodopsin or metarhodopsin activation. An additional electrophysiological method called prolonged depolarizing afterpotential (PDA) exploits the bi-stability of Drosophila photopigment and the absorption-spectral differences of fly R and M pigment states. The PDA is induced by intense blue light, converting saturating amounts of rhodopsin to metarhodopsin, resulting in the failure of light-response termination for an extended time in darkness, but it can be terminated by metarhodopsin to rhodopsin conversion using intense orange light. Since the PDA is a robust signal that requires massive photopigment conversion, even small defects in the biogenesis of the photopigment lead to readily detected abnormal PDA. Indeed, defective PDA mutants led to the identification of novel signaling proteins important for phototransduction.

Electrophysiological Methods for Measuring Photopigment Levels in Drosophila Photoreceptors

We present a protocol to electrophysiologically characterize bi-stable photopigments: (i) exploiting the charge displacements within the photopigment molecules following photon-absorption and their huge amount in the photoreceptors, and (ii) exploiting the absorption-spectra differences of rhodopsin and metarhodopsin photopigment states. These protocols are useful to screen for mutations affecting bi-stable photopigment systems.&#160;

The Drosophila G-protein-coupled photopigment rhodopsin (R) is composed of a protein (opsin) and a chromophore. The activation process of rhodopsin is ...

Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator

Epithelial ion transport is vital to systemic ion homeostasis as well as maintenance of essential cellular electrochemical gradients. Intracellular pH (pHi) is influenced by many ion transporters and thus monitoring pHi is a useful tool for assessing transporter activity. Modern Genetically Encoded pH-Indicators (GEpHIs) provide optical quantification of pHi in intact cells on a cellular and subcellular scale. This protocol describes real-time quantification of cellular pHi regulation in Malpighian Tubules (MTs) of Drosophila melanogaster through ex vivo live-imaging of pHerry, a pseudo-ratiometric GEpHI with a pKa well-suited to track pH changes in the cytosol. Extracted adult fly MTs are composed of morphologically and functionally distinct sections of single-cell layer epithelia, and can serve as an accessible and genetically tractable model for investigation of epithelial transport. GEpHIs offer several advantages over conventional pH-sensitive fluorescent dyes and ion-selective electrodes. GEpHIs can label distinct cell populations provided appropriate promoter elements are available. This labeling is particularly useful in ex vivo, in vivo, and in situ preparations, which are inherently heterogeneous. GEpHIs also permit quantification of pHi in intact tissues over time without need for repeated dye treatment or tissue externalization. The primary drawback of current GEpHIs is the tendency to aggregate in cytosolic inclusions in response to tissue damage and construct over-expression. These shortcomings, their solutions, and the inherent advantages of GEpHIs are demonstrated in this protocol through assessment of basolateral proton (H+) transport in functionally distinct principal and stellate cells of extracted fly MTs. The techniques and analysis described are readily adaptable to a wide variety of vertebrate and invertebrate preparations, and the sophistication of the assay can be scaled from teaching labs to intricate determination of ion flux via specific transporters.

Optical Quantification of Intracellular pH in Drosophila melanogaster Malpighian Tubule Epithelia with a Fluorescent Genetically-encoded pH Indicator

Cellular ion transport can often be assessed by monitoring intracellular pH (pHi). Genetically Encoded pH-Indicators (GEpHIs)&#160;provide optical quantification of intracellular pH in intact cells. This protocol details the quantification of intracellular pH through cellular ex vivo live-imaging of Malpighian tubules of Drosophila melanogaster with pHerry, a pseudo-ratiometric genetically encoded pH-indicator.

Epithelial ion transport is vital to systemic ion homeostasis as well as maintenance of essential cellular electrochemical gradients. Intracellular pH ...

Methods for Staging Pupal Periods and Measurement of Wing Pigmentation of Drosophila guttifera

Diversified species of Drosophila (fruit fly) provide opportunities to study mechanisms of development and genetic changes responsible for evolutionary changes. In particular, the adult stage is a rich source of morphological traits for interspecific comparison, including wing pigmentation comparison. To study developmental differences among species, detailed observation and appropriate staging are required for precise comparison. Here we describe protocols for staging of pupal periods and quantification of wing pigmentation in a polka-dotted fruit fly, Drosophila guttifera. First, we describe the method for detailed morphological observation and definition of pupal stages based on morphologies. This method includes a technique for removing the puparium, which is the outer chitinous case of the pupa, to enable detailed observation of pupal morphologies. Second, we describe the method for measuring the duration of defined pupal stages. Finally, we describe the method for quantification of wing pigmentation based on image analysis using digital images and ImageJ software. With these methods, we can establish a solid basis for comparing developmental processes of adult traits during pupal stages.

Methods for Staging Pupal Periods and Measurement of Wing Pigmentation of Drosophila guttifera

Protocols for staging pupal periods and measurement of wing pigmentation of Drosophila guttifera are described. Staging and quantification of pigmentation provide a solid basis for studying developmental mechanisms of adult traits and enable interspecific comparison of trait development.

Diversified species of Drosophila (fruit fly) provide opportunities to study mechanisms of development and genetic changes responsible for evolutionary ...

Reverse Genetic Approach to Identify Regulators of Pigmentation using Zebrafish

Melanocytes are specialized neural crest-derived cells present in the epidermal skin. These cells synthesize melanin pigment that protects the genome from harmful ultraviolet radiations. Perturbations in melanocyte functioning lead to pigmentary disorders such as piebaldism, albinism, vitiligo, melasma, and melanoma. Zebrafish is an excellent model system to understand melanocyte functions. The presence of conspicuous pigmented melanocytes, ease of genetic manipulation, and availability of transgenic fluorescent lines facilitate the study of pigmentation. This study employs the use of wild-type and transgenic zebrafish lines that drive green fluorescent protein (GFP) expression under mitfa and tyrp1 promoters that mark various stages of melanocytes. 
Morpholino-based silencing of candidate genes is achieved to evaluate the phenotypic outcome on larval pigmentation and is applicable to screen for regulators of pigmentation. This protocol demonstrates the method from microinjection to imaging and fluorescence-activated cell sorting (FACS)-based dissection of phenotypes using two candidate genes, carbonic anhydrase 14 (Ca14) and a histone variant (H2afv), to comprehensively assess the pigmentation outcome. Further, this protocol demonstrates segregating candidate genes into melanocyte specifiers and differentiators that selectively alter melanocyte numbers and melanin content per cell, respectively.

Regulators of melanocyte functions govern visible differences in the pigmentation outcome. Deciphering the molecular function of the candidate pigmentation gene poses a challenge. Herein, we demonstrate the use of a zebrafish model system to identify candidates and classify them into regulators of melanin content and melanocyte number.

Melanocytes are specialized neural crest-derived cells present in the epidermal skin. These cells synthesize melanin pigment that protects the genome from ...

Studying Membrane Protein Trafficking in Drosophila Photoreceptor Cells Using eGFP-Tagged Proteins

Membrane protein trafficking regulates the incorporation and removal of receptors and ion channels into the plasma membrane. This process is fundamentally important for cell function and cell integrity of neurons. Drosophila photoreceptor cells have become a model for studying membrane protein trafficking. Besides rhodopsin, which upon illumination becomes internalized from the photoreceptor membrane and is degraded, the transient receptor potential-like (TRPL) ion channel in Drosophila exhibits a light-dependent translocation between the rhabdomeral photoreceptor membrane (where it is located in the dark) and the photoreceptor cell body (to which it is transported upon illumination). This intracellular transport of TRPL can be studied in a simple and non-invasive way by expressing eGFP-tagged TRPL in photoreceptor cells. The eGFP fluorescence can then be observed either in the deep pseudopupil or by water immersion microscopy. These methods allow detection of fluorescence in the intact eye and are therefore useful for high-throughput assays and genetic screens for Drosophila mutants defective in TRPL translocation. Here, the preparation of flies, the microscopic techniques, as well as quantification methods used to study this light-triggered translocation of TRPL are explained in detail. These methods can be applied also for trafficking studies on other Drosophila photoreceptor proteins, for example, rhodopsin. In addition, by using eGFP-tagged rhabdomeral proteins, these methods can be used to assess the degeneration of photoreceptor cells.

Studying Membrane Protein Trafficking in Drosophila Photoreceptor Cells Using eGFP-Tagged Proteins

Here, non-invasive methods are described for localization of photoreceptor membrane proteins and assessment of retinal degeneration in the Drosophila compound eye using eGFP fluorescence.

Membrane protein trafficking regulates the incorporation and removal of receptors and ion channels into the plasma membrane. This process is fundamentally ...

Quantifying Abdominal Pigmentation in Drosophila melanogaster

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