This work was supported in part by the Van Andel Research Institute and a research grant from the National Institutes of Health (CA181343) to S.B.R.

1. Installing and Running ArrayNinja
<ol>
	<li>Download and install Oracle Virtual Box from www.virtualbox.org.</li>
	<li>Download and uncompress the ArrayNinja virtual machine (VM) from http://research.vai.org/Tools/arrayninja.</li>
	<li>Open Virtual Box and add the ArrayNinja VM by clicking &#39;Machine,&#39; &#39;Add,&#39; and select arrayninja.vbox from the folder where ArrayNinja VM was saved.</li>
	<li>Start ArrayNinja by selecting it inside Virtual Box and clicking the green &#39;start&#39; arrow.</li>
	<li>Virtual Box will open a new window and display a message that the VM can be accessed by navigating the web browser to localhost:2080.&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; NOTE: A containerized version of ArrayNinja is also available via hub.docker.com/r/bradley.dickson/arrayninja/</li>
</ol>
2. Designing the Array Slide and Source Plate Layout
<ol>
	<li>Under the &#39;Plan a slide layout&#39; heading on the ArrayNinja interface, click on the link that corresponds to the microarray printer being used. 
	NOTE: ArrayNinja has been programmed to mimic the robotic movement of two commonly used microarray printers (see Table 1). Compatibility with the other arrayers can be configured upon request.</li>
	<li>Click inside the &#39;Load plate&#39; dialog box, type &#34;empty&#34;, and click &#39;enter.&#39; See Figure 2 for a screenshot of the ArrayNinja design module.</li>
	<li>Adjust the spot diameter to 275 &#181;m and spot spacing to 375 &#181;m. Adjust the remaining settings (Plate Blocks/plate row, Total plate Rows, replicates, features in y, Super Arrays, SuperA fudge; see Figure 2) to customize how the features will appear on the microarray slide. 
	NOTE: The spot diameter is determined by the size of the microarray pin. As these settings are adjusted, the cartoon slide will update in real-time. Use this cartoon to preview how each setting is modifying the final slide layout.</li>
	<li>After the layout of features on the slide is finalized, mouse over each unique feature and enter the feature identifier in the pop-up dialog box. 
	NOTE: Feature identifiers can consist of numbers, letters, or combinations. This is only required for unique features, and a dialog box will not appear when replicates are selected.</li>
	<li>After all unique features have been assigned an identifier, click &#39;populate.&#39; Enter a name for the slide layout and click &#39;print your plate&#39; to save. A new page will open displaying the number of 384-well source plates needed to fabricate the chosen slide design and a table mapping the physical location of each feature to be loaded in the source plate(s). 
	NOTE: Remember this name, as it will be used to recall this design when analyzing microarray data (see section 6.2). Clicking &#39;print your plate&#39; saves the layout within ArrayNinja.</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55912/55912fig2.jpg" /> 
Figure 2: ArrayNinja Design Module. A screen shot of the ArrayNinja design module is shown in the dotted line. The control panel (top) shows all of the parameters that can be altered on the microarray printer. As these parameters are adjusted, the cartoon image of the slide layout (bottom left) updates in real time. After the layout is set, the user can mouse over individual spots to enter unique feature identifiers. ArrayNinja constructs from this user input a map of the position of each feature in the source plate(s) (bottom right) needed to fabricate a specified microarray slide layout. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55912/55912fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
3. Fabricating Microarrays
<ol>
	<li>Preparing the Source Plate
	<ol>
		<li>Use the map generated with ArrayNinja in section 2.5 to create the 384-well source plate(s). 
		NOTE: Detailed descriptions of peptides queried on this platform can be found elsewhere17.</li>
		<li>Deposit 1 - 2 &#181;L of each feature (e.g., biotinylated histone peptide) into the correct well of the 384-well source plate(s). 
		NOTE: Biotinylated histone peptides are typically deposited from 200 - 400 &#181;M stock solutions, which equates to 10 to 25-fold molar excess of peptide to streptavidin binding sites in a single array spot. This is calculated using the equation: 
		<img alt="Equation" src="/files/ftp_upload/55912/55912eq1.jpg" /> 
		where V is the volume delivered by a pin, [P] is the concentration of the feature being printed, NA is Avogadro&#39;s number, and S is the surface area of a spot. C is the coverage of the slide, expressed as the number of streptavidin molecules per unit area multiplied by three (the average number of available streptavidin binding sites). V and C are obtained by the respective manufacturer&#39;s. Other features may require different concentrations depending on the size of the biomolecule where crowding may be a concern. A range of printing concentrations for each new type of feature should be tested empirically to determine the optimum printing concentration.</li>
		<li>Dilute each feature 10-fold with 1x printing buffer supplemented with 1% bovine serum albumin (BSA). Spin the source plate(s) at 500 x g for 2 min at room temperature. 
		NOTE: The inclusion of fluorescein-labeled biotin (5 &#181;g/&#181;L) in the printing buffer is recommended as a spotting control and as a visual aid to facilitate proper array alignment during analysis (see Figure 4).</li>
	</ol>
	</li>
	<li>Printing Protocol (Figure 3A &#8211; B).
	<ol>
		<li>Prepare the arrayer by emptying the waste collection container and filling the wash solution container and humidifier container with sterile distilled water.</li>
		<li>Enter the parameters used to design the slide in ArrayNinja (section 2 and Figure 2) into the microarray printer control program.</li>
		<li>Using the microarray printer control program, set the washing procedure for a 1 s wash with one immersion. Set the post-wash settings to re-dip the pins 5 times following each wash. Set the humidity to 60%. 
		NOTE: The optimal wash configuration may vary depending on the microarray printer being used. The optimal post-wash pin dip configuration may vary depending on the microarray printer being used.</li>
		<li>Insert functionalized slides (e.g., streptavidin-coated glass) into the substrate platens and place all platens into the platen elevator. Insert the source plate(s) into the plate holder(s) and place into the source plate elevator.</li>
		<li>Click &#39;print&#39;. Monitor the printing process for a few rounds of feature deposition to ensure all wash and dip settings are correct. When the print run is complete, remove the substrate platens from the arrayer. 
		NOTE: When large print runs prohibit completion of blocking steps within one day, printed slides can be incubated in a humidified chamber at 4 &#176;C overnight. Incubate the slides next to a small beaker of water inside a cardboard box sealed with plastic wrap.</li>
		<li>Block the slides with blocking buffer for 30 min at room temperature with mixing.</li>
		<li>Wash the slides 2 x 10 min at room temperature in phosphate buffered saline (PBS), pH 7.6 with mixing. Dry the slides by spinning in a microarray slide centrifuge for 30 s at room temperature. 
		NOTE: For processing a large number of slides at once, a high-throughput microscope slide washing chamber can be used, allowing 50 slides to be washed in parallel.</li>
		<li>For slides designed to be partitioned with wax, proceed to section 4.1. For all other designs, store slides at 4 &#176;C protected from light and moisture. 
		NOTE: Printed biotinylated histone peptides are stable for at least 6 months when stored this way.</li>
	</ol>
	</li>
</ol>
4. Partitioning Microarray Slides
<ol>
	<li>Hydrophobic Wax Pen (Figure 3C)
	<ol>
		<li>Apply wax around the areas that contain features using a wax pen. Allow wax to air dry for 5 min before proceeding to section 5. 
		NOTE: After blocking, the array spots can be very difficult to visualize by eye. The slide design from ArrayNinja can be printed to scale and used as a guide for applying wax.</li>
	</ol>
	</li>
	<li>Silicon gasket (Figure 3D)
	<ol>
		<li>Peel the clear film off the back of the array gasket and place adhesive side down onto the microarray slide.</li>
		<li>Hold the gasket in place for 5 s prior to proceeding to section 5.</li>
	</ol>
	</li>
	<li>Wax Imprint (Figure 3E)
	<ol>
		<li>For slides designed to be partitioned by wax, print a test slide on plain glass using 10% BSA. Use this test slide to optimize the wax imprinter guides or array settings to ensure all features will be within the wax-mold chambers.</li>
		<li>Heat the microarray wax imprinter to 85 &#176;C until all the wax is completely melted, approximately 30 min.</li>
		<li>Insert the slide with the printed side facing down and push the slide all the way to the right guide on the microarray imprinter. Pull up the lever to bring the mold into contact with the surface of the slide. Hold for 2 s. 
		NOTE: The hold time can be altered to achieve optimal wax border thickness.</li>
		<li>Quickly remove the slide and visually inspect the wax borders to ensure all wells are enclosed and that the borders are not so thick that they encroach on the spots. Store slides at 4 &#176;C protected from moisture and light. 
		NOTE: The hold time can be increased or decreased to obtain thicker or thinner borders.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55912/55912fig3.jpg" /> 
Figure 3: Microarray Fabrication. (A) Histone peptide microarray fabrication on streptavidin-coated microscope slides using a contact microarray printer. (B) Microarrays fabricated with 3 subarrays of a 48 x 48 grid of peptide features. Separation of (C) 3 subarrays with a hydrophobic wax pen, (D) 2 subarrays with a silicon adhesive, and (E) 48 subarrays with a wax imprint. All microarrays shown are fabricated using 25 x 75 mm microscope slides. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55912/55912fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
5. Hybridizing a Histone PTM Antibody with a Peptide Microarray
<ol>
	<li>Prepare hybridization buffer (PBS, pH 7.6, 5% BSA, 0.1% Tween-20).</li>
	<li>Equilibrate the slide in hybridization buffer using a hybridization vessel. Completely cover the entire slide in hybridization buffer and incubate for 30 min at 4 &#176;C on an orbital shaker at low speed.</li>
	<li>Prepare a solution containing diluted histone PTM antibody in hybridization buffer. 
	NOTE: In the example data, both histone Antibody #1 and Antibody #2 were diluted 1:1,000 in hybridization buffer. A dilution range similar to that used for immunoblotting is recommended as a starting point.</li>
	<li>Incubate the array with the antibody solution for 1 h at 4 &#176;C. Remove the antibody solution and wash the array 3 times for 5 min at 4 &#176;C with cold PBS, pH 7.6.</li>
	<li>Prepare a 1:5,000 - 1:10,000 dilution of fluorescent dye-conjugated secondary antibody in hybridization buffer.</li>
	<li>Incubate the array with secondary antibody solution for 30 min at 4 &#176;C protected from light. Remove the secondary antibody solution and wash the microarray slide 3 times for 5 min at 4 &#176;C with PBS, pH 7.6. Dip the microarray in a 50-mL conical tube containing 0.1x PBS, pH 7.6 to remove excess salt at room temperature. Dry the slide in a microarray slide centrifuge at room temperature.</li>
	<li>Scan the slide with a microarray scanner at 25 &#181;m resolution or higher, following the microarray scanner manufacturer&#39;s recommended scanning protocol. 
	NOTE: If fluorescein-labeled biotin tracer is present, scan both the green channel (ex: 488 nm, em: 509 nm) and the channel that corresponds to the fluorescent dye-conjugated secondary antibody, typically red (ex: 635 nm, em: 677 nm). The goal of scanning is to obtain single channel .tif files that can be merged into a single .png file (as described in section 6.1).</li>
</ol>
6. Analysis of Microarray Data using ArrayNinja
<ol>
	<li>Preparing a merged microarray image 
	NOTE: The goal of this section is to create a .png image file that merges the two single-channel .tif files (obtained in section 5). This is the only image format compatible with the ArrayNinja analysis module. The following instructions represent one possible way to obtain a merged image file. However, other solutions are available (e.g., the freeware ImageJ).
	<ol>
		<li>From the command line in a bash terminal of a computer with the freeware ImageMagick installed, navigate to the folder that contains the single channel .tif files and copy/paste the following steps, hitting &#39;enter&#39; between each step (6.1.4 - 6.1.7). 
		NOTE: File names in capital letters (e.g., RED_CHANNEL) should be replaced with the file name of the microarray slide images.</li>
		<li>If necessary, first invert the images using the command &#39;convert INPUT.tif -negate OUTPUT.tif&#39;. This is required if the scanner saves .tif files with the signal in white and background in black.
		<ol>
			<li>convert -depth 16 RED_CHANNEL.TIF -clone 0 -channel GB -evaluate set 0 -delete 0 out.png 2&#62;error.file.</li>
			<li>convert - depth 16 CONTROL_CHANNEL.TIF -clone 0 -channel RB -evaluate set 0 -delete 0 outa.png 2&#62;error.file.</li>
			<li>convert -depth 16 CONTROL_CHANNEL.TIF -clone 0 -channel RG -evaluate set 0 -delete 0 outB.png 2&#62;error.file.</li>
			<li>convert out.png outa.png outB.png -set colorspace RGV -combine merged.png. 
			NOTE: A file named &#39;merged.png&#39; will be saved in the same folder as the original .tif files.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Quantifying data using ArrayNinja
	<ol>
		<li>Open ArrayNinja and click on the appropriate microarray printer link under &#34;To quantify images which have a known source plate.&#34; Type the name of the saved slide design (step 2.5) in the &#34;load plate&#34; dialog box and click &#39;enter.&#39; See Figure 4 for a screenshot of the ArrayNinja analysis module.</li>
		<li>Click &#39;Choose File&#39; and navigate to and select the &#39;merged.png&#39; file created in section 6.1. The merged image will load as well as a grid for the slide layout.</li>
		<li>Use the sliders at the bottom of the ArrayNinja control panel to adjust the contrast, brightness, and midpoint. 
		NOTE: These adjustments are for visualization purposes only and have no impact on quantification.</li>
		<li>Select &#34;resolution&#34; and enter the value that matches the resolution of the scanned image. Use the &#34;margin side&#34; and &#34;margin top&#34; to move the grid into alignment with the spots on the array. Adjust as needed to get the grid as closely aligned over each spot as possible.</li>
		<li>Click &#39;Spot Seek&#39; and wait until the button returns to the original grey color. 
		NOTE: This can be repeated several times to center the grid circles on individual spots. The Seek function relaxes the grid toward each spot to fine-tune the alignment.</li>
		<li>Change the &#34;Super Arrays&#34; value to &#34;1&#34; to work up each sub array panel individually (if desired). If using a 4 x 12 wax imprint slide layout (Figure 3E), use the &#34;iPin&#34; &#34;jPin&#34; and &#34;subA&#34; controls to turn off features to analyze any desired combination of 4 x 12 wells. For example, to analyze the top left and top right wells as replicates of each other, enter &#34;1 4&#34; into iPin, &#34;1 1&#34; into jPin and &#34;1 4&#34; into subA. Press &#39;enter&#39;.</li>
		<li>Hover the mouse over individual spots to view the identity of that feature.</li>
		<li>Click &#39;Toggle zoom&#39; to review features more carefully. Select background reference spots by pressing the &#39;R&#39; key while the mouse is over a spot. Reference spots will be highlighted in orange. 
		NOTE: In &#34;toggle zoom&#34; mode, a magnified image of the feature that the mouse is over is displayed in the upper right hand corner. A detailed discussion of additional background correction features in ArrayNinja are discussed elsewhere28.</li>
		<li>Toggle off spots (with widely varied spot morphology or debris that would affect accurate quantification) by pressing the &#39;A&#39; key while hovering the mouse over the affected spots. Inactivated spots will turn white.</li>
		<li>Click &#39;populate&#39; followed by &#39;Submit&#39; to quantify the spots. 
		NOTE: A new tab will open and display a bar graph of data normalized to the brightest spot average. A table below the bar graph contains both the normalized and raw data values. This table can be copied into a spreadsheet for archiving and further analysis.</li>
	</ol>
	</li>
</ol>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55912/55912fig4.jpg" /> 
Figure 4: ArrayNinja Analysis Module. A screen shot of the ArrayNinja analysis module is shown. The control panel (top left) shows all of the parameters that can be adjusted to visualize the array, find spots, and align a grid over the array image. Hovering the mouse over a feature shows a zoomed-in view (top right) and displays a popup that contains the identification information associated with that feature (bottom). Reference spots selected for background correction are orange. Features to be excluded from downstream analysis are white. ArrayNinja contains a text-based search feature that highlights matching features in yellow, as shown in the example for H4K16. <a href="https://cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55912/55912fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

The authors have nothing to disclose.

Antibody reliability in biomedical research applications is paramount46,47. This is especially true in chromatin biochemistry given the position of antibodies as key tools for the majority of techniques developed to characterize the abundance and distribution of histone PTMs. The protocol presented here details an optimized pipeline for the design, fabrication, and use of peptide microarrays to analyze histone PTM antibody specificity. This pipeline has been used to screen a large number of commercially available and widely used histone PTM antibodies, and data generated from these experiments are freely available through an online and expanding Histone Antibody Specificity Database (www.histoneantibodies.com)17.
Apparent from our and others&#39; work are frequent instances of unfavorable histone PTM antibody behavior that can complicate the interpretation of data generated with these reagents12,15,17. More rigorous and comprehensive quality control measures from antibody companies are therefore warranted. Experimentalists and epigenome consortium leaders (e.g., ENCODE, BLUEPRINT) need to also show rigor in their own evaluation of histone PTM antibodies when choosing a reagent for their study. In addition, efforts to minimize batch-to-batch variability, standardize the use of highly validated affinity reagents across epigenome mapping platforms, and develop alternative affinity tools are all actionable items to address this research problem.
Microarrays have a number of advantages over microplate-based assays (e.g., ELISA) that make them particularly useful for characterizing histone PTM antibody specificity. Microarrays enable parallel and competitive analysis of thousands of individual peptide-antibody interactions with minimal material consumption. In the protocol described here, 700 picomoles of each peptide feature is sufficient to produce 100 microarray slides. Additionally, antibody analysis can be completed using less than 1 &#181;g of antibody, and custom array formats enable multiple antibodies and various antibody dilutions to be screened in parallel.
Designing custom feature layouts on microarrays can be a laborious task. Additionally, each new microarray design requires build-out of a new analysis template. We found this to be prohibitive for realizing the full utility of microarray technology. This motivated our development of ArrayNinja, an interactive, open-source software application that seamlessly integrates the design and analysis aspects of microarray experiments28. The design module of ArrayNinja allows the user to interactively design a slide to fit the layout required for an experiment. ArrayNinja virtually maps the robotic motion of the printer and translates this to the source plate layout for a given slide design (Figure 2). Creating custom array formats is now a quick and routine practice. Another key feature of ArrayNinja is the connection between the design and analysis steps of microarray work. With user-defined settings from the design module, ArrayNinja overlays an interactive grid on a scanned microarray image, allowing the user to mouse over any feature to reveal its identity or search for features of interest (Figure 4).
Several critical steps of this pipeline are worth noting. First, while designing the print layout, consideration should be taken to include enough replicate spots in order to attain significance in data collection. Additionally, to account for pin-to-pin variability, each feature should be deposited by at least two different pins. Finally, perhaps the most critical step is the physical generation of the source plate. Successful use of the high-density microarrays described in this protocol relies on the ability to map the identity of each feature to their physical location on the final slide. This mapping task is not trivial, but ArrayNinja greatly facilitates this step by providing a plate map. Any deviations to this map while creating the source plates will lead to incorrect conclusions during analysis.
It is important to consider the limitations of using microarrays for the analysis of antibody specificity. While off-target histone PTM antibody properties captured on the array have been demonstrated to translate to experimental approaches with similar hybridization conditions (e.g., immunoblot)17,18, the extent to which array-based profiling of antibody specificity translates to ChIP protocols is suggestive14,17 but warrants more critical evaluation.
Variations to this pipeline have been previously described for analysis of histone readers, writers, and erasers23,24. Modifying this platform for utility beyond epigenetics research could be easily adapted for any printable library of interest. It is also possible that material more complex than peptides can be used to construct microarrays for chromatin biochemistry research. For example, recombinant nucleosomes displaying various PTMs are now routinely being generated in the laboratory setting48 and profiling the specificity of histone PTM antibodies in the context of this physiologically-relevant chromatin subunit will be an exciting area of future study.
A widely-used alternative approach to the protocol described here utilizes SPOT array technology, where hundreds of peptides are directly synthesized on a cellulose membrane support49. The membrane itself can then be used for microarray applications50. SPOT technology is advantageous from the standpoint of library complexity and synthesis cost. However, the purity of peptides synthesized using the SPOT method have been reported to vary, and quality control and purification measures common to solid-phase peptide synthesis (e.g., HPLC and mass spectrometry) are not routinely performed50,51. Additionally, peptide presentation on nitrocellulose is not uniform and may shield epitopes. Notably, both types of histone peptide array platforms are available commercially for users who do not have access to the specialized equipment needed to synthesize peptides and fabricate arrays.

Genomic DNA is elegantly packaged inside the eukaryotic cell nucleus with histone proteins to form chromatin. The repeating subunit of chromatin is the nucleosome, which consists of 147 base pairs of DNA wrapped around an octameric core of histone proteins &#8211; H2A, H2B, H3, and H41. Chromatin is broadly organized into loosely packed euchromatin and tightly packed heterochromatin domains. The degree of chromatin compaction regulates the extent to which protein machineries can access the underlying DNA to carry out fundamental DNA-templated processes like replication, transcription, and repair.
Key regulators of genome accessibility in the context of chromatin are PTMs on the unstructured tail and core domains of histone proteins2,3. Histone PTMs function directly by influencing the structure of chromatin4 and indirectly through the recruitment of reader proteins and their associated macromolecular complexes that have chromatin remodeling, enzymatic, and scaffolding activities5. Studies of histone PTM function over the past two decades overwhelmingly suggest these marks play key roles in regulating cell fate, organismal development, and disease initiation/progression. Fueled by advances in mass spectrometry-based proteomic technology, more than 20 unique histone PTMs on more than 80 distinct histone residues have been discovered6. Notably, these modifications often occur in combinations, and consistent with the &#34;histone code&#34; hypothesis, numerous studies suggest that reader proteins are targeted to discrete regions of chromatin through recognition of specific combinations of histone PTMs7,8,9. A key challenge moving forward will be to assign functions to the growing list of histone PTMs and to determine how specific combinations of histone PTMs orchestrate the dynamic functions associated with chromatin.
Antibodies are the lynchpin reagents for the detection of histone PTMs. As such, more than 1,000 histone PTM-specific antibodies have been commercially developed for use in chromatin biochemistry research. With the rapid development of high-throughput DNA sequencing technology, these reagents are being used extensively by individual investigators and large-scale epigenomics &#34;roadmap&#34; initiatives (e.g., ENCODE and BLUEPRINT) in ChIP-seq (chromatin immunoprecipitation coupled with next-generation sequencing) pipelines to generate high-resolution spatial maps of histone PTM distribution genome-wide10,11. However, recent studies have shown that the specificity of histone PTM antibodies can be highly variable and that these reagents exhibit unfavorable properties such as off-target epitope recognition, strong positive and negative influence by neighboring PTMs, and difficulty discriminating the modification order on a particular residue (e.g., mono-, di-, or tri-methyllysine)12,13,14,15,16,17,18. Therefore, rigorous quality control of histone PTM-specific antibody reagents is necessary to accurately interpret data generated with these valuable reagents.
Microarray technology enables the simultaneous interrogation of thousands of macromolecular interactions in a high-throughput, reproducible, and miniaturized format. For this reason, a variety of microarray platforms have been created to analyze protein-DNA19,20, protein-protein 21, and protein-peptide interactions22. Indeed, histone peptide microarrays have emerged as an informative discovery platform for chromatin biochemistry research, enabling high-throughput profiling of the writers, erasers, and readers of histone PTMs15,23,24, and also for the analysis of histone antibody specificity17,25. Beyond their application in chromatin and epigenetics research, histone peptide arrays have potential utility as a diagnostic/prognostic test for systemic lupus erythematosus and other autoimmune diseases where anti-chromatin autoantibodies are generated26,27.
Here, we describe an integrated pipeline that we have developed for designing, fabricating, and querying histone peptide microarrays to generate specificity profiles for antibodies that recognize histones and their PTMs. The pipeline is facilitated by ArrayNinja, an open-source, interactive software application that we recently developed, which integrates the design and analysis stages of microarray experiments28. ArrayNinja works best in Google Chrome. Briefly, a robotic contact microarray printer is used to deposit a library of biotin-conjugated histone peptides at defined positions on streptavidin-coated glass microscope slides. Arrays can then be used in a competitive and parallel assay format to interrogate antibody-epitope interactions (Figure 1). The peptide library consists of hundreds of unique synthetic peptides harboring PTMs (lysine acetylation, lysine/arginine methylation, and serine/threonine phosphorylation) alone and in relevant combinations largely derived from proteomics datasets. Methods for peptide synthesis and validation are detailed elsewhere23. Data generated from our ongoing histone PTM antibody screening efforts utilizing this array platform are archived on a public web resource, the Histone Antibody Specificity Database (www.histoneantibodies.com). Notably, histone peptide microarrays fabricated with variations of this protocol have also been used extensively to characterize the activity of histone PTM reader domains8,29,30,31,32,33,34,35,36,37 and more recently to profile histone PTM writer and eraser activities24.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55912/55912fig1.jpg" /> 
Figure 1: Cartoon Depiction of the Stepwise Procedure for Antibody Screening on a Histone Peptide microarray. Biotinylated histone peptides harboring defined post-translational modifications (red and blue circles) are co-printed with biotin-fluorescein on streptavidin-coated glass. Positive interactions are visualized as red fluorescence. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55912/55912fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

<table border="0" cellpadding="0" cellspacing="0" width="746">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Printing Buffer</td>
			<td style="width:107px;">ArrayIt</td>
			<td style="width:105px;">PPB</td>
			<td style="width:281px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">BSA</td>
			<td style="width:107px;">Omnipure</td>
			<td align="right" style="width:105px;">2390</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">Streptavidin-coated glass microscope slides</td>
			<td style="width:107px;">Greiner Bio-one</td>
			<td>439003-25</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">polypropylene 384 well plate</td>
			<td style="width:107px;">Greiner Bio-one</td>
			<td align="right" style="width:105px;">784201</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Biotin-fluorescein</td>
			<td style="width:107px;">Sigma</td>
			<td align="right" style="width:105px;">53608</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">contact microarray printer</td>
			<td style="width:107px;">Aushon</td>
			<td align="right" style="width:105px;">2470</td>
			<td style="width:281px;">Aushon 2470 Microarray Printer</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">contact microarray printer</td>
			<td style="width:107px;">Gene Machines</td>
			<td style="width:105px;">OmniGrid 100</td>
			<td style="width:281px;">OmniGrid Microarray Printer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">PBS</td>
			<td style="width:107px;">Invitrogen</td>
			<td align="right" style="width:105px;">14190</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Blocking Buffer</td>
			<td style="width:107px;">ArrayIt</td>
			<td style="width:105px;">SBB</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Hydrophobic wax pen</td>
			<td style="width:107px;">Vector Labs</td>
			<td style="width:105px;">H-4000</td>
			<td>ImmEdge Hydrophobic Barrier PAP Pen</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Silicon Gasket</td>
			<td style="width:107px;">Grace Bio-labs</td>
			<td align="right" style="width:105px;">622511</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">Hybridization Vessel</td>
			<td style="width:107px;">Thermo Scientific</td>
			<td align="right">267061</td>
			<td>or similar vessel</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">Fluorescent-dye conjugated secondary antibody</td>
			<td style="width:107px;">Life Technologies</td>
			<td>A-21244</td>
			<td style="width:281px;">Alexa Fluor 647 (anti-rabbit)</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">Fluorescent-dye conjugated secondary antibody</td>
			<td style="width:107px;">Life Technologies</td>
			<td>A-21235</td>
			<td style="width:281px;">Alexa Fluor 647 (anti-mouse)</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Wax Imprinter</td>
			<td style="width:107px;">ArrayIt</td>
			<td>MSI48</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Tween-20</td>
			<td style="width:107px;">Omnipure</td>
			<td align="right" style="width:105px;">9490</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Microarray Scanner</td>
			<td style="width:107px;">Innopsys</td>
			<td style="width:105px;">InnoScan 1100AL</td>
			<td>or equivalent microarray scanner</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">EipTitan Histone Peptide Microarray</td>
			<td style="width:107px;">Epicypher</td>
			<td align="right" style="width:105px;">112001</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">AbSurance Pro Histone Peptide Microarray</td>
			<td style="width:107px;">Millipore</td>
			<td align="right" style="width:105px;">16668</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">MODified Histone Peptide Array</td>
			<td style="width:107px;">Active Motif</td>
			<td align="right" style="width:105px;">13001</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Histone Code Peptide Microarrays</td>
			<td style="width:107px;">JPT</td>
			<td style="width:105px;">His_MA_01</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Wax</td>
			<td style="width:107px;">Royal Oak</td>
			<td style="width:105px;">GulfWax</td>
			<td>for wax imprinter</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">Humidified Microarray Slide Hybridization Chamber</td>
			<td style="width:107px;">VWR</td>
			<td style="width:105px;">97000-284</td>
			<td></td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:255px;">High throughput microscope slide washing chamber</td>
			<td style="width:107px;">ArrayIt</td>
			<td style="width:105px;">HTW</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Microscope slide centrifuge</td>
			<td style="width:107px;">VWR</td>
			<td>93000-204</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Antibody 1</td>
			<td>Abcam</td>
			<td align="right" style="width:105px;">8898</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">Antibody 2</td>
			<td style="width:107px;">Millipore</td>
			<td style="width:105px;">07-473</td>
			<td></td>
		</tr>
		<tr height="64">
			<td height="64" style="height:64px;width:255px;">Biotinylated histone peptide</td>
			<td style="width:107px;">EpiCypher</td>
			<td>12-0001</td>
			<td style="width:281px;">Example peptide. Similar peptides with various modifications are available from several commercial sources.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">ImageMagick</td>
			<td style="width:107px;"></td>
			<td style="width:105px;"></td>
			<td>https://www.imagemagick.org/script/index.php</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:255px;">ArrayNinja</td>
			<td style="width:107px;"></td>
			<td style="width:105px;"></td>
			<td>https://rothbartlab.vai.org/tools/</td>
		</tr>
	</tbody>
</table>

analysis of histone antibody specificity with peptide microarrays

Post-translational modifications (PTMs) on histone proteins are widely studied for their roles in regulating chromatin structure and gene expression. The mass production and distribution of antibodies specific to histone PTMs has greatly facilitated research on these marks. As histone PTM antibodies are key reagents for many chromatin biochemistry applications, rigorous analysis of antibody specificity is necessary for accurate data interpretation and continued progress in the field. This protocol describes an integrated pipeline for the design, fabrication and use of peptide microarrays for profiling the specificity of histone antibodies. The design and analysis aspects of this procedure are facilitated by ArrayNinja, an open-source and interactive software package we recently developed to streamline the customization of microarray print formats. This pipeline has been used to screen a large number of commercially available and widely used histone PTM antibodies, and data generated from these experiments are freely available through an online and expanding Histone Antibody Specificity Database. Beyond histones, the general methodology described herein can be applied broadly to the analysis of PTM-specific antibodies.

This protocol has been used to design and fabricate a peptide microarray platform for the analysis of histone PTM antibody specificity. The array queries a library of more than 300 unique peptide features (20 - 40 residues in length) representing many of the known combinations of PTMs found on core and variant histone proteins38. This pipeline has been a workhorse for the screening of many widely used and commercially available histone PTM antibodies, and full datasets are available on the Histone Antibody Specificity Database (www.histoneantibodies.com).17
The backbone of our pipeline is ArrayNinja, an open-source software application that we recently developed, which integrates the planning and analysis stages of microarray work28. The ArrayNinja analysis module allows users to interact in informative ways with their raw array image file. The printed feature identities are automatically integrated with the image, and these identities can be revealed by hovering the mouse cursor over a spot. This integration also enables rapid searching for features of interest by name and exclusion of features from downstream analysis. ArrayNinja also provides options for local and nonlocal background noise correction as well as a correction scheme that adapts to spot morphology. Full details of ArrayNinja and its capabilities can be found elsewhere28.
ArrayNinja calculates signal intensities for each peptide feature and aggregates those intensities into averages with error based on feature identity. Raw and normalized signal averages are returned, where the normalization constant is determined by the brightest feature average. The signal intensities for each peptide can be used to compare the relative affinity of the antibody among features on the microarray. Here, we show representative datasets for two antibodies profiled with this pipeline, highlighting epitope recognition properties that should be considered when interpreting results obtained with these reagents (Figure 5).
Off-target recognition is a concern for all antibodies, and commonalities in epitopes surrounding modifiable histone residues makes this a particular challenge for histone PTM antibodies. Indeed, an antibody raised to recognize tri-methylated lysine 9 on histone H3 (H3K9me3) binds peptides tri-methylated at H3K18, H3K27, and lysine 20 on histone H4 (H4K20me3) as well or better than H3K9me3 (Figure 5A). The sequence surrounding H3K9 (ARKS) is conserved with H3K27, and cross-reactivity of histone PTM antibodies and chromatin regulators that bind and modify these sites has been noted elsewhere15,39,40,41. Another observed off-target recognition property common to methyl-lysine antibodies is an inability to discriminate methyl order. This is exemplified by results obtained with an H3K4me3 antibody, which cross-reacts with H3K4me2 and H3K4me1 peptides (Figure 5B). Distinguishing between the methyl order is important, as studies have shown that H3K4me3, H3K4me2, and H3K4me1 are distributed differently across the genome and likely function in different ways42,43. For example, H3K4me3 is located at the transcription start sites of most actively transcribed genes, whereas active enhancers are commonly marked by H3K4me144.
In addition to off-target recognition, positive and negative influence by neighboring PTMs is a commonly observed property of histone antibodies. The H3K9me3 antibody shown in Figure 5A is positively influenced by acetyl groups on neighboring lysine residues. Indeed, recent mass spectrometry analysis shows that acetyl groups, particularly H3K14ac, frequently co-occur with H3K9me338. The H3K4me3 antibody shown in Figure 5B is negatively impacted by neighboring phosphorylation at threonine 6 (H3T6p). H3T6p is known to have both positive and negative impact on the recognition of H3K4me3 by reader proteins, and this may serve as a dynamic mechanism to regulate recruitment of specific chromatin factors15,45.
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/55912/55912fig5.jpg" /> 
Figure 5: Analysis of Antibodies on Peptide Microarrays. Analysis of (A) H3K9me3 (Antibody #1) and (B) H3K4me3 (Antibody #2) antibodies on peptide microarrays. Green lines/bars indicate the peptide harboring only the intended target PTM. Grey lines/bars indicate peptides whose signal intensity is not significantly different (p &#62; 0.05) from the green line/bar, calculated using a one-way ANOVA comparing the mean relative intensity of all peptides to the target peptide. Red and blue lines/bars indicate signal that is significantly decreased or increased (p &#60; 0.05) from the green line/bar, respectively. Orange lines/bars indicate off-target peptides. Data are displayed as (left) a visual illustration of PTM complexity on peptides spanning N-terminal regions of the H3 and H4 tails, where the width of each line corresponds to the relative intensity measured for that peptide feature, and (right) bar graphs displaying the relative signal intensity averages &#177; SEM from 6 individual spot measurements on microarrays. All peptides included in this analysis are 20 amino acids in length corresponding to either histone H3 amino acids 1 - 20 or 15 - 34. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55912/55912fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Analysis of Histone Antibody Specificity with Peptide Microarrays at JoVE.com

Analysis of Histone Antibody Specificity with Peptide Microarrays

This manuscript describes methods for applying peptide microarray technology to specificity profiling of antibodies that recognize histones and their post-translational modifications.

Post-translational modifications (PTMs) on histone proteins are widely studied for their roles in regulating chromatin structure and gene expression. The ...

analysis-of-histone-antibody-specificity-with-peptide-microarrays

Nanyang Technological University

Research

JoVE Journal

Biochemistry

39.8K Views.  Van Andel Research Institute. This manuscript describes methods for applying peptide microarray technology to specificity profiling of antibodies that recognize histones and their post-translational modifications. 

Video: Analysis of Histone Antibody Specificity with Peptide Microarrays

Laboratory Scale Production and Purification of a Therapeutic Antibody

Ensuring the successful production of a therapeutic antibody begins early on in the development process. The first stage is vector expression of the antibody genes followed by stable transfection into a suitable cell line. The stable clones are subjected to screening in order to select those clones with desired production and growth characteristics. This is a critical albeit time-consuming step in the process. This protocol considers vector selection and sourcing of antibody sequences for the expression of a therapeutic antibody. The methods describe preparation of vector DNA for stable transfection of a suspension variant of human embryonic kidney 293 (HEK-293) cell line, using polyethylenimine (PEI). The cells are transfected as adherent cells in serum-containing media to maximize transfection efficiency, and afterwards adapted to serum-free conditions. Large scale production, setup as batch overgrow cultures is used to yield antibody protein that is purified by affinity chromatography using an automated fast protein liquid chromatography (FPLC) instrument. The antibody yields produced by this method can provide sufficient protein to begin initial characterization of the antibody. This may include in vitro assay development or physicochemical characterization to aid in the time-consuming task of clonal screening for lead candidates. This method can be transferable to the development of an expression system for the production of biosimilar antibodies.

This protocol describes the production of a therapeutic antibody in a mammalian expression system. The methods described include preparation of vector DNA, stable transfection and serum-free adaptation of a human embryonic kidney 293 cell line, set up of large scale cultures and purification using affinity chromatography.

Ensuring the successful production of a therapeutic antibody begins early on in the development process. The first stage is vector expression of the ...

Easy Manipulation of Architectures in Protein-based Hydrogels for Cell Culture Applications

Hydrogels are recognized as promising materials for cell culture applications due to their ability to provide highly hydrated cell environments. The field of 3D templates is rising due to the potential resemblance of those materials to the natural extracellular matrix. Protein-based hydrogels are particularly promising because they can easily be functionalized and can achieve defined structures with adjustable physicochemical properties. However, the production of macroporous 3D templates for cell culture applications using natural materials is often limited by their weaker mechanical properties compared to those of synthetic materials. Here, different methods were evaluated to produce macroporous bovine serum albumin (BSA)-based hydrogel systems, with adjustable pore sizes in the range of 10 to 70 &#181;m in radius. Furthermore, a method to generate channels in this protein-based material that are several hundred microns long was established. The different methods to produce pores, as well as the influence of pore size on material properties such as swelling ratio, pH, temperature stability, and enzymatic degradation behavior, were analyzed. Pore sizes were investigated in the native, swollen state of the hydrogels using confocal laser scanning microscopy. The feasibility for cell culture applications was evaluated using a cell-adhesive RGD peptide modification of the protein system and two model cell lines: human breast cancer cells (A549) and adenocarcinomic human alveolar basal epithelial cells (MCF7).

Different methods to manipulate three-dimensional architecture in protein-based hydrogels are evaluated here with respect to material properties. The macroporous networks are functionalized with a cell-adhesive peptide, and their feasibility in cell culture is evaluated using two different model cell lines.

Hydrogels are recognized as promising materials for cell culture applications due to their ability to provide highly hydrated cell environments. The field ...

Semi-automated Biopanning of Bacterial Display Libraries for Peptide Affinity Reagent Discovery and Analysis of Resulting Isolates

Biopanning bacterial display libraries is a proven technique for peptide affinity reagent discovery for recognition of both biotic and abiotic targets. Peptide affinity reagents can be used for similar applications to antibodies, including sensing and therapeutics, but are more robust and able to perform in more extreme environments. Specific enrichment of peptide capture agents to a protein target of interest is enhanced using semi-automated sorting methods which improve binding and wash steps and therefore decrease the occurrence of false positive binders. A semi-automated sorting method is described herein for use with a commercial automated magnetic-activated cell sorting device with an unconstrained bacterial display sorting library expressing random 15-mer peptides. With slight modifications, these methods are extendable to other automated devices, other sorting libraries, and other organisms. A primary goal of this work is to provide a comprehensive methodology and expound the thought process applied in analyzing and minimizing the resulting pool of candidates. These techniques include analysis of on-cell binding using fluorescence-activated cell sorting (FACS), to assess affinity and specificity during sorting and in comparing individual candidates, and the analysis of peptide sequences to identify trends and consensus sequences for understanding and potentially improving the affinity to and specificity for the target of interest.

Biopanning bacterial display libraries is a proven technique for discovery of peptide affinity reagents, a robust alternative to antibodies. The semi-automated sorting method herein has streamlined biopanning to decrease the occurrence of false positives. Here we illustrate the thought process and techniques applied in evaluating candidates and minimizing downstream analysis.

Biopanning bacterial display libraries is a proven technique for peptide affinity reagent discovery for recognition of both biotic and abiotic targets. ...

The Determination of Protease Specificity in Mouse Tissue Extracts by MALDI-TOF Mass Spectrometry: Manipulating PH to Cause Specificity Changes

Proteases have several biological functions, including protein activation/inactivation and food digestion. Identifying protease specificity is important for revealing protease function. The method proposed in this study determines protease specificity by measuring the molecular weight of unique substrates using Matrix-assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) mass spectrometry. The substrates contain iminobiotin, while the cleaved site consists of amino acids, and the spacer consists of polyethylene glycol. The cleaved substrate will generate a unique molecular weight using a cleaved amino acid. One of the merits of this method is that it may be carried out in one pot using crude samples, and it is also suitable for assessing multiple samples. In this article, we describe a simple experimental method optimized with samples extracted from mouse lung tissue, including tissue extraction, placement of digestive substrates into samples, purification of digestive substrates under different pH conditions, and measurement of the substrates&#39; molecular weight using MALDI-TOF mass spectrometry. In summary, this technique allows for the identification of protease specificity in crude samples derived from tissue extracts using MALDI-TOF mass spectrometry, which may easily be scaled up for multiple sample processing.

Here, we present a protocol to determine protease specificity in crude mouse tissue extracts using MALDI-TOF spectrometry.

Proteases have several biological functions, including protein activation/inactivation and food digestion. Identifying protease specificity is important ...

Kinase Inhibitor Screening In Self-assembled Human Protein Microarrays

The screening of kinase inhibitors is crucial for better understanding properties of a drug and for the identification of potentially new targets with clinical implications. Several methodologies have been reported to accomplish such screening. However, each has its own limitations (e.g., the screening of only ATP analogues, restriction to using purified kinase domains, significant costs associated with testing more than a few kinases at a time, and lack of flexibility in screening protein kinases with novel mutations). Here, a new protocol that overcomes some of these limitations and can be used for the unbiased screening of kinase inhibitors is presented. A strength of this method is its ability to compare the activity of kinase inhibitors across multiple proteins, either between different kinases or different variants of the same kinase. Self-assembled protein microarrays generated through the expression of protein kinases by a human-based in vitro transcription and translation system (IVTT) are employed. The proteins displayed on the microarray are active, allowing for measurement of the effects of kinase inhibitors. The following procedure describes the protocol steps in detail, from the microarray generation and screening to the data analysis.

A detailed protocol for the generation of self-assembled human protein microarrays for the screening of kinase inhibitors is presented.

The screening of kinase inhibitors is crucial for better understanding properties of a drug and for the identification of potentially new targets with ...

Isolation of Histone from Sorghum Leaf Tissue for Top Down Mass Spectrometry Profiling of Potential Epigenetic Markers

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. Post-translational modifications (PTMs) of histones, which are highly dynamic and can be added or removed by enzymes, play critical roles in regulating gene expression. In plants, epigenetic factors, including histone PTMs, are related to their adaptive responses to the environment. Understanding the molecular mechanisms of epigenetic control can bring unprecedented opportunities for innovative bioengineering solutions. Herein, we describe a protocol to isolate the nuclei and purify histones from sorghum leaf tissue. The extracted histones can be analyzed in their intact forms by top-down mass spectrometry (MS) coupled with online reversed-phase (RP) liquid chromatography (LC). Combinations and stoichiometry of multiple PTMs on the same histone proteoform can be readily identified. In addition, histone tail clipping can be detected using the top-down LC-MS workflow, thus, yielding the global PTM profile of core histones (H4, H2A, H2B, H3). We have applied this protocol previously to profile histone PTMs from sorghum leaf tissue collected from a large-scale field study, aimed at identifying epigenetic markers of drought resistance. The protocol could potentially be adapted and optimized for chromatin immunoprecipitation-sequencing (ChIP-seq), or for studying histone PTMs in similar plants.

The protocol has been developed to effectively extract intact histones from sorghum leaf materials for profiling of histone post-translational modifications that can serve as potential epigenetic markers to aid engineering drought resistant crops.

Histones belong to a family of highly conserved proteins in eukaryotes. They pack DNA into nucleosomes as functional units of chromatin. ...

Rapid Determination of Antibody-Antigen Affinity by Mass Photometry

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this protocol, we describe the implementation of a new single-molecule technique, mass photometry (MP), for this purpose. MP is a label- and immobilization-free technique that detects and quantifies molecular masses and populations of antibodies and antigen-antibody complexes on a single-molecule level. MP analyzes the antigen-antibody sample within minutes, allowing for the precise determination of the binding affinity and simultaneously providing information on the stoichiometry and the oligomeric state of the proteins. This is a simple and straightforward technique that requires only picomole quantities of protein and no expensive consumables. The same procedure can be used to study protein-protein binding for proteins with a molecular mass larger than 50 kDa. For multivalent protein interactions, the affinities of multiple binding sites can be obtained in a single measurement. However, the single-molecule mode of measurement and the lack of labeling imposes some experimental limitations. This method gives the best results when applied to measurements of sub-micromolar interaction affinities, antigens with a molecular mass of 20 kDa or larger, and relatively pure protein samples. We also describe the procedure for performing the required fitting and calculation steps using basic data analysis software.

We describe a single-molecule approach to antigen-antibody affinity measurements using mass photometry (MP). The MP-based protocol is fast, accurate, uses a very small amount of material, and does not require protein modification.

Measurements of the specificity and affinity of antigen-antibody interactions are critically important for medical and research applications. In this ...

Cell-Free Production of Proteoliposomes for Functional Analysis and Antibody Development Targeting Membrane Proteins

Membrane proteins play essential roles in a variety of cellular processes and perform vital functions. Membrane proteins are medically important in drug discovery because they are the targets of more than half of all drugs. An obstacle to conducting biochemical, biophysical, and structural studies of membrane proteins as well as antibody development has been the difficulty in producing large amounts of high-quality membrane protein with correct conformation and activity. Here we describe a &#8220;bilayer-dialysis method&#8221; using a wheat germ cell-free system, liposomes, and dialysis cups to efficiently synthesize membrane proteins and prepare purified proteoliposomes in a short time with a high success rate. Membrane proteins can be produced as much as in several milligrams, such as GPCRs, ion channels, transporters, and tetraspanins. This cell-free method contributes to reducing the time, cost and effort for preparing high-quality proteoliposomes, and provides suitable means for functional analysis of membrane proteins, drug targets screening, and antibody development.

This protocol describes an efficient cell-free method for production of high-quality proteoliposome by bilayer-dialysis method using wheat cell-free system and liposomes. This method provides suitable means for functional analysis of membrane proteins, drug targets screening, and antibody development.

Membrane proteins play essential roles in a variety of cellular processes and perform vital functions. Membrane proteins are medically important in drug ...

Cryo-EM and Single-Particle Analysis with Scipion

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at near-atomic resolution. In single-particle analysis, the vitrified sample is imaged by an electron beam and the detectors at the end of the microscope column produce movies of that sample. These movies contain thousands of images of identical particles in random orientations. The data need to go through an image processing workflow with multiple steps to obtain the final 3D reconstructed volume. The goal of the image processing workflow is to identify the acquisition parameters to be able to reconstruct the specimen under study. Scipion provides all the tools to create this workflow using several image processing packages in an integrative framework, also allowing the traceability of the results. In this article the whole image processing workflow in Scipion is presented and discussed with data coming from a real test case, giving all the details necessary to go from the movies obtained by the microscope to a high resolution final 3D reconstruction. Also, the power of using consensus tools that allow combining methods, and confirming results along every step of the workflow, improving the accuracy of the obtained results, is discussed.

Single-particle analysis in cryo-electron microscopy is one of the main techniques used to determine the structure of biological ensembles at high resolution. Scipion provides the tools to create the whole pipeline to process the information acquired by the microscope and achieve a 3D reconstruction of the biological specimen.

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at ...

In Vitro Characterization of Histone Chaperones using Analytical, Pull-Down and Chaperoning Assays

Histone proteins associate with DNA to form the eukaryotic chromatin. The basic unit of chromatin is a nucleosome, made up of a histone octamer consisting of two copies of the core histones H2A, H2B, H3, and H4, wrapped around by the DNA. The octamer is composed of two copies of an H2A/H2B dimer and a single copy of an H3/H4 tetramer. The highly charged core histones are prone to non-specific interactions with several proteins in the cellular cytoplasm and the nucleus. Histone chaperones form a diverse class of proteins that shuttle histones from the cytoplasm into the nucleus and aid their deposition onto the DNA, thus assisting the nucleosome assembly process. Some histone chaperones are specific for either H2A/H2B or H3/H4, and some function as chaperones for both. This protocol describes how in vitro laboratory techniques such as pull-down assays, analytical size-exclusion chromatography, analytical ultra-centrifugation, and histone chaperoning assay could be used in tandem to confirm whether a given protein is functional as a histone chaperone.

In Vitro Characterization of Histone Chaperones using Analytical, Pull-Down and Chaperoning Assays

This protocol describes a battery of methods that includes analytical size-exclusion chromatography to study histone chaperone oligomerization and stability, pull-down assay to unravel histone chaperone-histone interactions, AUC to analyze the stoichiometry of the protein complexes, and histone chaperoning assay to functionally characterize a putative histone chaperone in vitro.

Histone proteins associate with DNA to form the eukaryotic chromatin. The basic unit of chromatin is a nucleosome, made up of a histone octamer consisting ...