We thank Amy Chen for her help in preparing for the video shoot and for demonstrating the technique. This work conducted by ENIGMA: Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory, was supported by the Office of Science, Office of Biological and Environmental Research, of the U. S. Department of Energy under Contract No. DE-AC02-05CH11231.

Note: The protocol below is tailored for determination of gene targets of the RR DVU3023 from the bacterium Desulfovibrio vulgaris Hildenborough. It can be adapted to any other transcriptional regulator of interest.
1. Clone and Purify RR
<ol>
	<li>Clone the RR gene, specifically DVU3023, from D. vulgaris Hildenborough into an Escherichia coli expression vector such that the gene is C-terminally His-tagged and expression is under the control of a T7 promoter. 
	Note: Several cloning methods may be used and is determined by the researcher. Alternate affinity tags may also be used.</li>
	<li>Transform the expression construct into E. coli BL21 (DE3) expression strain.</li>
	<li>Grow up 1 L of the BL21 expression strain at 37 &#176;C. At mid-log phase, add IPTG to 0.5 mM to induce protein expression. Continue growth at room temperature for 24 hr.</li>
	<li>Centrifuge cells at 5,000 x g for 10 min at 4 &#176;C. Resuspend cells in lysis buffer (20 mM sodium phosphate, pH 7.4, 500 mM NaCl, 40 mM imidazole, 1 mg/ml lysozyme, 1x benzonase nuclease). Lyse cells using a French press at 4 &#176;C.</li>
	<li>Centrifuge lysate at 15,000 x g for 30 min at 4 &#176;C. Filter using a 0.45 &#181;m syringe filter.</li>
	<li>Wash a 1 ml Ni Sepharose column on an FPLC instrument using 10 ml of wash buffer (20 mM sodium phosphate, pH 7.4, 500 mM NaCl, 40 mM imidazole).</li>
	<li>Load lysate on the column. Wash column with 20 ml of wash buffer.</li>
	<li>Elute DVU3023 using a gradient of 0-100% elution buffer (20 mM sodium phosphate, pH 7.4, 500 mM NaCl, 500 mM imidazole).</li>
	<li>Load eluted fractions on a desalting column, and wash with a desalting buffer (20 mM sodium phosphate pH 7.4, 100 mM NaCl).</li>
	<li>Centrifuge protein sample in a high molecular weight cutoff centrifuge filter to concentrate the protein. Add DTT to 0.1 mM and glycerol to 50% and store protein at -20 &#176;C. 
	Note: Purification methods will need to be optimized individually for each protein under study.</li>
</ol>
2. Determine Gene Target for RR Using Electrophoretic Mobility Shift Assay (EMSA)
<ol>
	<li>PCR amplify 400 bp region upstream of the candidate target gene DVU3025, using D. vulgaris Hildenborough genomic DNA as the template, and a forward unlabeled primer and a reverse 5&#8217;-biotin-labeled primer. 
	Note: Tips to select a candidate target gene: Often RRs bind the upstream regions of their own gene/operon, or they may regulate proximally encoded genes. If the RR has orthologs in other species, look for genes that are conserved in the neighborhood. Alternate methods include choosing candidate genes based on regulon predictions (e.g.,&#160;RegPrecise5), or predicting sigma54-dependent promoters6 for RRs that are themselves sigma54-dependent.</li>
	<li>Run the PCR product on a 1% agarose gel, cut out the 400 bp sized product, and purify the DNA using a gel extraction clean up kit.</li>
	<li>Mix DVU3023 protein (0.5 pmol) with 100 fmol of biotinylated DNA substrate in 10 mM Tris HCl, pH 7.5, 50 mM KCl, 5 mM MgCl2, 1 mM DTT, 25% glycerol and 1 &#181;g/ml poly dI.dC (non-specific competitor DNA) in a total volume of 20 &#181;l. Also set up a reaction without any protein as a control. Incubate the reactions at room temperature on the bench for 20 min.</li>
	<li>Note: These are standard conditions listed and other reaction components may be added depending on the RR of interest. If activation is desired, add 50 mM acetyl phosphate to the reaction (often RRs will bind DNA in vitro without activation).</li>
	<li>Pre-run a precast mini 6% polyacrylamide-0.5x TBE gel in 0.5x TBE buffer at 100 V for 30 min. Add 5 &#181;l of 5x loading buffer (0.1% bromophenol blue, 0.1% xylene cyanol, 30% glycerol in 1x TBE) to the binding reactions and load 18 &#181;l of the reactions on to the gel. Run at 100 V for 2 hr. 
	Note: In order to avoid overheating, which can lead to disassociation of the protein-DNA complexes, fill the outer buffer chamber in the electrophoresis system with running buffer such that the majority of the gel is insulated by buffer. Alternately, the gel may be run at 4 &#176;C.</li>
	<li>Cut a charged nylon membrane to the size of the gel and soak it in 0.5x TBE for at least ten minutes. Remove the gel from the cassette. Cut any ridges off the gel and sandwich the gel and membrane between two thick filter papers soaked in 0.5x TBE, and place inside a semi-dry blotting apparatus and run at 20 V for 30 min.</li>
	<li>Place the membrane inside a commercial UV light crosslinker instrument and set the time to 3 min. 
	Note: The membrane may now be stored dry at room temperature for several days before proceeding to the next step.</li>
	<li>Use a commercially available chemiluminescent detection kit that employs a streptavidin-horse radish peroxidase conjugate to develop the blot as per manufacturer&#8217;s instructions.</li>
	<li>Image the blot using a computer hooked up to a CCD equipped camera and look for a shift in the DNA substrate mobility in the presence of the RR, which indicates that the RR binds the DNA being tested. 
	Note: The specificity of the protein-DNA shift can be tested by including in the reaction an excess of unlabeled competitor DNA, which should eliminate or decrease the shift seen.</li>
</ol>
3. Verify Target Enrichment after Genomic DNA-protein Binding
<ol>
	<li>Genomic DNA-protein binding reaction
	<ol>
		<li>Shear genomic DNA to an average size of 500 bp by sonicating 100 &#181;l genomic DNA (at concentrations 100-200 ng/&#181;l) in a 1.5 ml microfuge tube using a microtip with 9 low amplitude pulses of 1 sec, with 2 sec gap in between each. 
		Note: If the DNA splatters to the sides of the tube, spin down the contents after every 3 pulses. The exact conditions used will vary with the sonicator instrument used. The sheared DNA fragments may range from 100-1000 bp, but the average size should be within 400-600 bp. Too much shearing may result in fewer intact binding sites, and either too much or too little shearing will affect library preparation during the downstream whole genome amplification steps.</li>
		<li>Mix 2-3 &#181;g of sheared genomic DNA with RR protein (0.5 pmol of DVU3023) in 10 mM Tris-HCl pH 7.5, 1 mM DTT, 50 mM KCl, 5 mM MgCl2, 25% glycerol, and 50 mM acetyl phosphate. Incubate reactions at 25 &#176;C for 30 min. Transfer 10 &#181;l of this reaction to a 1.5 ml tube and label as input DNA. 
		Note: Acetyl phosphate is added to activate the protein by in vitro phosphorylation. Phosphorylation stimulates DNA binding, but many RRs also bind DNA in vitro without activation7. The amount of protein added to the reaction will depend on activity of the protein prep. The EMSA may be used to optimize this amount.</li>
	</ol>
	</li>
	<li>Affinity purify the protein-bound DNA
	<ol>
		<li>Add 30 &#181;l of Ni-NTA agarose resin to a 0.6 ml microfuge tube. Centrifuge at 100 x g for 1 min to collect the resin at the bottom, and remove the supernatant. Add 100 &#181;l of wash buffer (10 mM Tris-HCl, pH 7.5, 5 mM MgCl2, 50 mM KCl, 25% glycerol), flick the tube to mix, and centrifuge at 100 x g for 2 min. Remove supernatant.</li>
		<li>Add the remaining 90 &#181;l of the binding reaction to the washed Ni-NTA resin and incubate in a rotary shaker for 30 min.</li>
		<li>Centrifuge at 100 x g for 2 min, and remove the supernatant (unbound DNA). Add 100 &#181;l of wash buffer, flick the tube to mix contents, and centrifuge at 100 x g for 2 min. Remove supernatant. Repeat the wash step twice more.</li>
		<li>Add 35 &#181;l of elution buffer (20 mM sodium phosphate buffer pH 8, 500 mM NaCl, 500 mM imidazole) to the resin and mix by vortexing. Incubate on the bench at RT for 5 min. Centrifuge at 100 x g for 2 min. Transfer the supernatant to a new 1.5 ml tube and label as the protein-bound DNA fraction.</li>
		<li>Also add 35 &#181;l of the elution buffer to the input DNA.</li>
		<li>Purify the input and the protein-bound DNA fractions using a PCR purification kit.</li>
	</ol>
	</li>
	<li>Whole genome amplify the input and protein-bound DNA samples.
	<ol>
		<li>Add 10 &#181;l of the input and protein-bound DNA to separate PCR tubes. Add 1 &#181;l of 10x Fragmentation buffer, 2 &#181;l of Library Preparation buffer, and 1 &#181;l of Library Stabilization solution to each sample. Mix well by vortexing. Heat in a thermocycler at 95 &#176;C for 2 min, and chill on ice. 
		Note: The starting amount of DNA should be at least 10 ng in order to avoid introducing amplification bias.</li>
		<li>Add 1 &#181;l of Library Preparation Enzyme, mix by pipetting, and incubate in thermal cycler at 16 &#176;C/20 min, 24 &#176;C/20 min, 37 &#176;C for 20 min, 75 &#176;C/5 min, and hold at 4 &#176;C.</li>
		<li>To each tube, add 47.5 &#181;l of water, 7.5 &#181;l of 10x amplification master mix, and 5 &#181;l of polymerase. Mix well and heat at 95 &#176;C/3 min, followed by 20 cycles of 94 &#176;C/15 sec, 65 &#176;C/5 min. Hold reactions at 4 &#176;C.</li>
		<li>Purify the amplified DNA samples using a PCR purification kit and measure DNA concentration spectrophotometrically.</li>
	</ol>
	</li>
	<li>Verify target enrichment in the protein-bound DNA using qPCR
	<ol>
		<li>Design qPCR primers to amplify 200 bp of the upstream region of the EMSA-verified target gene (DVU3025) using any freely available primer design software.</li>
		<li>Set up triplicate qPCR reactions for each DNA template with each primer set. Prepare a master mix for each primer set. 1x master mix contains 10 &#181;l of 2x Sybr Green qPCR mix, 0.5 &#181;M of each primer and water to a total of 18 &#181;l. Aliquot 18 &#181;l of the master mix per well of a 96-well PCR plate.</li>
		<li>Dilute the amplified and purified input and protein-bound DNA samples to 5 ng/&#181;l with water and use as DNA template. Add 2 &#181;l of DNA template to the wells.</li>
		<li>Seal the plate with an ultra clear qPCR sealing film, spin down plate in a centrifuge at 200 x g/1 min. Place plate in a real time qPCR machine. Cycle as follows using the associated qPCR software: 95 &#176;C/1 min, and 40 cycles of 95 &#176;C/10 sec, 59 &#176;C/15 sec, and 70 &#176;C/35 sec.</li>
		<li>Also set up triplicate qPCR reactions with primers to amplify upstream regions of an unrelated gene (negative control).</li>
		<li>Calculate &#916;CT by subtracting CT value of protein-bound DNA from that of the input DNA. Calculate fold enrichment of target gene in the protein-bound DNA as 2&#916;CT. 
		Note: If the target upstream region was enriched in the protein-bound DNA vs. the input DNA, it indicates that the binding reactions and affinity purification were successful. Proceed to step 4. If enrichment of the target upstream region was not observed, repeat the binding reactions (step 3.1) with different amount of protein.</li>
	</ol>
	</li>
</ol>
4. DNA Labeling and Array Hybridization
<ol>
	<li>Label Input DNA with Cy3 and Enriched DNA with Cy5
	 ote: Cy3 and Cy5 dyes are light sensitive and care should be taken to keep light exposure to a minimum.
	<ol>
		<li>Mix 1 &#181;g DNA with 40 &#181;l Cy3/Cy5-labeled 9-mers and adjust volume to 80 &#181;l with water.</li>
		<li>Heat denature at 98 &#176;C for 10 min in the dark (in a thermocycler). Quick chill on ice for 2 min.</li>
		<li>Add 2 &#181;l Klenow polymerase (3&#8217;-5&#8217;-exo-, 50,000 U/ml), 5 mM dNTPs, and 8 &#181;l water to each reaction, mix well, and incubate at 37 &#176;C for 2 hr in the dark (in a thermocycler).</li>
		<li>Add EDTA to 50 mM to stop the reaction and NaCl solution to 0.5 M.</li>
		<li>Transfer samples to 1.5 ml tubes containing 0.9 volume of isopropanol, incubate in dark for 10 min, and centrifuge at 12,000 x g for 10 min. The pellet should be pink for Cy3-labeled DNA and blue for Cy5-labeled DNA.</li>
		<li>Wash pellet with 80% ethanol (500 &#181;l) and centrifuge at 12,000 x g for 2 min. Air-dry pellets for 5-10 min in dark. 
		Note: Pellets may be stored at -20 &#176;C.</li>
		<li>Resuspend pellet in 25 &#181;l water. Measure DNA concentration spectrophotometrically.</li>
		<li>Pool together 6 &#181;g each of the Cy3- and Cy5-labeled DNA in a 1.5 ml tube and vacuum dry in a centrifuge on low heat in the dark (cover the centrifuge lid if it is transparent). 
		Note: Pellets may be stored at -20 &#176;C until ready for hybridization.</li>
	</ol>
	</li>
	<li>Microarray Hybridization
	<ol>
		<li>Turn the hybridization system on 3-4 hr prior to use and set the temperature to 42 &#176;C.</li>
		<li>Prepare a hybridization solution master mix such that 1x solution contains 11.8 &#181;l 2x Hybridization buffer, 4.7 &#181;l Hybridization Component A, and 0.5 &#181;l alignment oligo.</li>
		<li>Resuspend the pellets in 5 &#181;l water. Add 13 &#181;l of this mix to the sample. Vortex for 15 sec, incubate at 95 &#176;C in a dry bath for 5 min. Keep samples at 42 &#176;C in the hybridization system until ready for loading.</li>
		<li>Prepare the microarray slide-mixer assembly, according to manufacturer&#8217;s protocol.</li>
		<li>Place the mixer-slide assembly within the hybridization system. Load 16 &#181;l of sample into the fill port, seal the ports with an adhesive film, turn mixing on in the system, and hybridize for 16-20 hr at 42 &#176;C.</li>
		<li>Prepare 1x wash buffers I (250 ml), II (50 ml) and III (50 ml) by diluting the 10x commercially available buffers in water, and to each add DTT to 1 mM. Warm Buffer I to 42 &#176;C.</li>
		<li>Slide the mixer-slide into a disassembly tool, and place inside a dish containing warm Buffer I. Peel the mixer off, while vigorously shaking the disassembly tool by hand.</li>
		<li>Place the slide into a container with 50 ml of Wash buffer I and shake vigorously for 2 min by hand.</li>
		<li>Transfer slide into a second container with 50 ml Wash buffer II and shake vigorously for 1 min by hand.</li>
		<li>Transfer slide into a third container with 50 ml Wash buffer III, and shake vigorously for 15 sec by hand.</li>
		<li>Quickly blot the edges of the slide on a paper towel, and place in a slide rack. Centrifuge at 200 x g for 2 min to dry the slide. Place within slide case, wrap it with foil, and store in a desiccator.</li>
	</ol>
	</li>
	<li>Scanning the Array
	<ol>
		<li>Place the slide within the microarray scanner according to the instrument&#8217;s instructions.</li>
		<li>Use a scanner software to set the wavelengths as 532 nm = Cy3 and 635 nm = Cy5, and the initial photomultiplier gains between 350 and 400.</li>
		<li>Preview the slide to locate the array on the slide. Select the array region for scanning.</li>
		<li>Scan the array and adjust the photomultiplier settings such that the array features are mostly yellow. The histogram should show the red and green curves superimposed or as close to each other as possible. The curves should end above the 10-5 normalized counts at saturation.</li>
		<li>Save both 532 and 635 nm images separately.</li>
	</ol>
	</li>
	<li>Array Data Analysis
	<ol>
		<li>Import the images into an array analysis software. Using the software, create two pair reports (.pair) for each array (for Cy3 and Cy5 images). Create scaled log2ratio files using the pair files. Use log2ratio files to search for peaks using a sliding window of 500 bp. Map the peak loci to the upstream regions of gene targets.</li>
		<li>Check if the positive target (determined using EMSA and confirmed by qPCR, DVU3025 in this example) appears within the top peaks. 
		Note: If the positive target is not among the top hits, it is possible that the RR under consideration has several gene targets and replicate DAP-chips can be conducted and peaks common to all replicates can be used to generate a target list.</li>
	</ol>
	</li>
</ol>
5. Binding Site Motif Prediction and Validation
<ol>
	<li>Retrieve sequences for upstream regions (400 bp) for the top gene targets as generated by DAP-chip analysis. Apply MEME on these sequences through Microbes Online (meme.nbcr.net) to predict motifs. 
	Note: Enhancer binding proteins such as sigma54-dependent regulators can bind several hundred base pairs upstream of the start site. For other transcriptional regulators, a shorter region such as 200 bp upstream will be sufficient.</li>
	<li>Design top and bottom strand DNA oligomers that contain the predicted binding site motif flanked by 10 bases on either end. Order the top strand 5&#8217; biotinylated.</li>
	<li>Mix the top and bottom strand oligos in 1:1.5 ratio in 10 mM Tris HCl, pH 8.0, 1 mM EDTA, and 50 mM NaCl in a total reaction volume of 20 &#181;l in PCR tubes. Heat to 95 &#176;C for 5 min in a thermal cycler, followed by slow cooling to 25 &#176;C. Dilute ten fold and use as wild type dsDNA substrate for EMSA.</li>
	<li>Prepare modified substrates using the same steps as above, but design oligomers to carry 4-6 substitutions in the conserved bases of the binding motif.</li>
	<li>Set up binding reactions with the RR and the wild type or modified substrates and examine using EMSA as described in step 2.</li>
	<li>Note: The predicted motif is validated if the RR binds the wild type substrate but not the modified one.</li>
</ol>
6. Conservation of Motif in Other Related Bacterial Species
<ol>
	<li>Select genomes of interest that contain orthologs of DVU3023. Obtain sequence and annotation files for the genomes from the NCBI site.</li>
	<li>Use a programming language such as Perl to write scripts that will use the motif sequences from the DAP-chip targets to build a position weighted matrix and use the matrix to score similar motifs present in other sequenced genomes.</li>
</ol>

<ol>
	<li>Galperin, M. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diversity+of+structure+and+function+of+response+regulator+output+domains.">Diversity of structure and function of response regulator output domains.</a> Curr Opin Microbiol. 13, 150-159 (2010).</li><li>Casino, P., Rubio, V., Marina, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+mechanism+of+signal+transduction+by+two-component+systems.">The mechanism of signal transduction by two-component systems.</a> Curr Opin Struct Biol. 20, 763-771 (2010).</li><li>Aparicio, O., Geisberg, J. V., Struhl, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromatin+immunoprecipitation+for+determining+the+association+of+proteins+with+specific+genomic+sequences+in+vivo.">Chromatin immunoprecipitation for determining the association of proteins with specific genomic sequences in vivo.</a> Curr Protoc Cell Biol. 17 (17), (2004).</li><li>McCleary, W. R., Stock, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acetyl+phosphate+and+the+activation+of+two-component+response+regulators.">Acetyl phosphate and the activation of two-component response regulators.</a> J Biol Chem. 269, 31567-31572 (1994).</li><li>Novichkov, P. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=RegPrecise+web+services+interface:+programmatic+access+to+the+transcriptional+regulatory+interactions+in+bacteria+reconstructed+by+comparative+genomics.">RegPrecise web services interface: programmatic access to the transcriptional regulatory interactions in bacteria reconstructed by comparative genomics.</a> Nucleic Acids Res. 40, 604-608 (2012).</li><li>Studholme, D. J., Buck, M., Nixon, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+potential+sigma(N)-dependent+promoters+in+bacterial+genomes.">Identification of potential sigma(N)-dependent promoters in bacterial genomes.</a> Microbiology. 146 (12), 3021-3023 (2000).</li><li>Rajeev, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+mapping+of+two+component+response+regulators+to+gene+targets+in+a+model+sulfate+reducing+bacterium.">Systematic mapping of two component response regulators to gene targets in a model sulfate reducing bacterium.</a> Genome Biol. 12, 99 (2011).</li><li>Crooks, G. E., Hon, G., Chandonia, J. M., Brenner, S. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WebLogo:+a+sequence+logo+generator.">WebLogo: a sequence logo generator.</a> Genome Res. 14, 1188-1190 (2004).</li><li>Barbieri, C. M., Mack, T. R., Robinson, V. L., Miller, M. T., Stock, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Regulation+of+response+regulator+autophosphorylation+through+interdomain+contacts.">Regulation of response regulator autophosphorylation through interdomain contacts.</a> J Biol Chem. 285, 32325-32335 (2010).</li><li>Bourret, R. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Receiver+domain+structure+and+function+in+response+regulator+proteins.">Receiver domain structure and function in response regulator proteins.</a> Curr Opin Microbiol. 13, 142-149 (2010).</li><li>Gao, R., Stock, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Molecular+strategies+for+phosphorylation-mediated+regulation+of+response+regulator+activity.">Molecular strategies for phosphorylation-mediated regulation of response regulator activity.</a> Curr Opin Microbiol. 13, 160-167 (2010).</li><li>Hung, D. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oligomerization+of+the+response+regulator+ComE+from+Streptococcus+mutans+is+affected+by+phosphorylation.">Oligomerization of the response regulator ComE from Streptococcus mutans is affected by phosphorylation.</a> J Bacteriol. 194, 1127-1135 (2012).</li><li>Ladds, J. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+response+regulator+Spo0A+from+Bacillus+subtilis+is+efficiently+phosphorylated+in+Escherichia+coli.">The response regulator Spo0A from Bacillus subtilis is efficiently phosphorylated in Escherichia coli.</a> FEMS Microbiol Lett. 223, 153-157 (2003).</li><li>Wen, Y., Feng, J., Scott, D. R., Marcus, E. A., Sachs, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Involvement+of+the+HP0165-HP0166+two-component+system+in+expression+of+some+acidic-pH-upregulated+genes+of+Helicobacter+pylori.">Involvement of the HP0165-HP0166 two-component system in expression of some acidic-pH-upregulated genes of Helicobacter pylori.</a> J Bacteriol. 188, 1750-1761 (2006).</li><li>Liu, X., Noll, D. M., Lieb, J. D., Clarke, N. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DIP-chip:+rapid+and+accurate+determination+of+DNA-binding+specificity.">DIP-chip: rapid and accurate determination of DNA-binding specificity.</a> Genome Res. 15, 421-427 (2005).</li><li>Gossett, A. J., Lieb, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+Immunoprecipitation+(DIP)+for+the+Determination+of+DNA-Binding+Specificity.">DNA Immunoprecipitation (DIP) for the Determination of DNA-Binding Specificity.</a> CSH Protoc. 2008, (2008).</li><li>Mascher, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Streptococcus+pneumoniae+cia+regulon:+CiaR+target+sites+and+transcription+profile+analysis.">The Streptococcus pneumoniae cia regulon: CiaR target sites and transcription profile analysis.</a> J Bacteriol. 185, 60-70 (2003).</li><li>Park, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChIP-seq:+advantages+and+challenges+of+a+maturing+technology.">ChIP-seq: advantages and challenges of a maturing technology.</a> Nat Rev Genet. 10, 669-680 (2009).</li><li>Lefrancois, P., Zheng, W., Snyder, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChIP-Seq+using+high-throughput+DNA+sequencing+for+genome-wide+identification+of+transcription+factor+binding+sites.">ChIP-Seq using high-throughput DNA sequencing for genome-wide identification of transcription factor binding sites.</a> Methods Enzymol. 470, 77-104 (2010).</li><li>Ho, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChIP-chip+versus+ChIP-seq:+lessons+for+experimental+design+and+data+analysis.">ChIP-chip versus ChIP-seq: lessons for experimental design and data analysis.</a> BMC Genomics. 12, 134 (2011).</li><li>Liu, X., Lee, C. K., Granek, J. A., Clarke, N. D., Lieb, J. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Whole-genome+comparison+of+Leu3+binding+in+vitro+and+in+vivo+reveals+the+importance+of+nucleosome+occupancy+in+target+site+selection.">Whole-genome comparison of Leu3 binding in vitro and in vivo reveals the importance of nucleosome occupancy in target site selection.</a> Genome Res. 16, 1517-1528 (2006).</li></ol>

The authors have no conflict of interest to disclose.

The DAP-chip method described here was successfully used to determine the gene targets for several RRs in Desulfovibrio vulgaris Hildenborough7 of which one is shown here as a representative result. For RR DVU3023, choosing a candidate gene target was straightforward. DVU3025 is located immediately downstream of the RR gene, and the RR and target genes are conserved in several Desulfovibrio species, and additionally DVU3025 has a predicted sigma54-dependent promoter. The EMSA provides a simpl...

The ability of bacteria to survive and thrive is critically dependent on how well they are able to perceive and respond to perturbations in their environments, and this in turn is dependent on their signal transduction systems. The number of signaling systems a bacterium encodes has been called its &#8220;microbial IQ&#8221; and can be an indication of both variability of its environment and its ability to sense multiple signals and fine tune its response1. Two component signal transduction systems (TCS) are the most prevalent signaling systems used by bacteria, and they consist of a histidine kinase (HK) that senses the external signal and transmits via phosphorylation to an effector response regulator (RR)2. RRs can have a variety of output domains and thus different effector modes, but the most common response is transcriptional regulation via a DNA binding domain1. The signals sensed and the corresponding functions of the vast majority of TCSs remain unknown.
Although in vivo methods such as ChIP-chip are routinely used for determination of genomic binding sites of transcription factors3, they can only be used for bacterial two component system RRs if the activating conditions or signals are known. Often the environmental cues that activate a TCS are harder to determine than their gene targets. The in vitro microarray based assay described here can be used to effectively and rapidly determine the gene targets and predict functions of TCSs. This assay takes advantage of the fact that RRs can be phosphorylated and thus activated in vitro using small molecule donors like acetyl phosphate4.
In this method, named DAP-chip for DNA-affinity-purified-chip (Figure 1), the RR gene of interest is cloned with a His-tag in E. coli, and a subsequently purified tagged protein is allowed to bind to sheared genomic DNA. The protein-bound DNA is then enriched by affinity-purification, the enriched and input DNA are amplified, fluorescently labeled, pooled together and hybridized to a tiling array that is custom made to the organism of interest (Figure 1). Microarray experiments are subject to artifacts and therefore additional steps are employed to optimize the assay. One such step is to attempt to determine one target for the RR under study using electrophoretic mobility shift assays (EMSA) (see workflow in Figure 2). Then, following binding to genomic DNA and the DAP steps, the protein-bound and input DNA are examined by qPCR to see if the positive target is enriched in the protein-bound fraction relative to the input fraction, thus confirming optimal binding conditions for the RR (Figure 2). After array hybridization, the data are analyzed to find peaks of higher intensity signal indicating genomic loci where the protein had bound. Functions may be predicted for the RR based on the gene targets obtained. The target genomic loci are used to predict binding site motifs, which are then experimentally validated using EMSAs (Figure 2). The functional predictions and gene targets for the RR may then be extended to closely related species that encode orthologous RRs by scanning those genomes for similar binding motifs (Figure 2). The DAP-chip method can provide a wealth of information for a TCS where previously there was none. The method can also be used for any transcriptional regulator if the protein can be purified and DNA binding conditions can be determined, and for any organism of interest with a genome sequence available.
<img alt="Figure 1" fo:content-width="5in" src="/files/ftp_upload/51715/51715fig1highres.jpg" width="500" /> 
Figure 1. The DNA-affinity-purified-chip (DAP-chip) strategy7. The RR gene from the organism of interest is cloned with a carboxy-terminal His-tag into an E. coli expression strain. Purified His-tagged protein is activated by phosphorylation with acetyl phosphate, and mixed with sheared genomic DNA. An aliquot of the binding reaction is saved as input DNA, while the rest is subjected to affinity purification using Ni-NTA resin. The input and the RR-bound DNA are whole genome amplified, and labeled with Cy3 and Cy5, respectively. The labeled DNA is pooled together and hybridized to a tiling array, which is then analyzed to determine the gene targets. Figure modified and reprinted using the creative commons license from7.
<img alt="Figure 2" fo:content-width="5in" src="/files/ftp_upload/51715/51715fig2highres.jpg" width="500" /> 
Figure 2. Summary of workflow. For any purified tagged protein, begin by determining a target using EMSA. Allow protein to bind genomic DNA and then DNA-affinity-purify (DAP) and whole genome amplify (WGA) the enriched and input DNA. If a gene target is known, use qPCR to ensure that the known target is enriched in the protein-bound fraction. If no target could be determined, proceed directly to DNA labeling and array hybridization. If enrichment by qPCR could not be observed, then repeat the protein-gDNA binding and DAP-WGA steps using different protein amounts. Use array analysis to find peaks and map them to target genes. Use the upstream regions of target genes to predict binding site motifs. Validate the motifs experimentally using EMSAs. Use the motif to scan the genomes of related species encoding orthologs of the RR under study, and predict genes targeted in those species as well. Based on the gene targets obtained, the physiological function of the RR and its orthologs may be predicted. Figure modified and reprinted using the creative commons license from7.

<table><tbody><tr><td>HisTrapFF column (Ni-Sepharose column)</td><td>GE Lfe Sciences, Pittsburgh, PA, USA</td><td>17-5255-01</td><td></td></tr><tr><td>Akta explorer (FPLC instrument)</td><td>GE Lfe Sciences, Pittsburgh, PA, USA</td><td></td><td></td></tr><tr><td>HiPrep 26/10 Desalting column</td><td>GE Lfe Sciences, Pittsburgh, PA, USA</td><td>17-5087-01</td><td></td></tr><tr><td>Qiaquick Gel extraction kit</td><td>Qiagen Inc, Valencia, CA, USA</td><td>28704</td><td></td></tr><tr><td>Biotin-labeled oligonucleotides</td><td>Integrated DNA Technologies</td><td>N/A</td><td></td></tr><tr><td>6% polyacrylamide-0.5x TBE precast mini DNA retardation gel</td><td>Life Technologies, Grand Island, NY, USA</td><td>EC63652BOX</td><td>Alternately, you can pour your own gel.</td></tr><tr><td>Nylon membrane</td><td>EMD Millipore, Billerica, MA, USA</td><td>INYC00010</td><td></td></tr><tr><td>Trans-Blot SD Semi-dry electrophoretic transfer cell</td><td>Biorad, Hercules, CA, USA</td><td>170-3940</td><td></td></tr><tr><td>Extra thick blot paper, 8 x 13.5 cm</td><td>Biorad, Hercules, CA, USA</td><td>170-3967</td><td></td></tr><tr><td>UV crosslinker Model XL-1000</td><td>Fisher Scientific</td><td>11-992-89</td><td></td></tr><tr><td>Nucleic Acid chemiluminescent detection kit (Pierce)</td><td>Thermo fisher Scientific, Rockford, IL, USA</td><td>89880</td><td></td></tr><tr><td>Ni-NTA agarose resin</td><td>Qiagen Inc, Valencia, CA, USA</td><td>30210</td><td></td></tr><tr><td>GenomePlex Whole genome amplification kit (Fragmentation buffer, library preparation buffer, library stabilization solution, library preparation enzyme, 10x amplification master mix, WGA polymerase)</td><td>Sigma-Aldrich, St. Louis, MO, USA</td><td>WGA2-50RXN</td><td></td></tr><tr><td>Nanodrop ND-1000</td><td>Thermo Scientific, Wilmington, DE, USA</td><td>For quantitation of DNA</td><td></td></tr><tr><td>Perfecta Sybr Green SuperMix, with ROX</td><td>Quanta biosciences</td><td>95055-500</td><td>Any Sybr Green PCR mix may be used</td></tr><tr><td>PlateMax Ultra clear heat sealing film for qPCR</td><td>Axygen</td><td></td><td></td></tr><tr><td colspan="4">[header]</td></tr><tr><td>96-well clear low profile PCR microplate</td><td>Life Technologies, Grand Island, NY, USA</td><td>PCR-96-LP-AB-C</td><td></td></tr><tr><td>Applied Biosystems StepOne Plus Real time PCR system</td><td>Life Technologies, Grand Island, NY, USA</td><td>4376600</td><td>Any real time PCR system may be used</td></tr><tr><td>Qiaquick PCR purification kit</td><td>Qiagen Inc, Valencia, CA, USA</td><td>28104</td><td>Any PCR clean up kit may be used</td></tr><tr><td>Cy3/Cy5-labeled nonamers</td><td>Trilink biotechnologies, San Diego, CA, USA</td><td>N46-0001, N46-0002</td><td></td></tr><tr><td>Klenow polymerase 50,000 U/ml, 3&#039;-5&#039; exo&lt;sup&gt;-&lt;/sup&gt;</td><td>New England Biolabs, Ipswich, MA</td><td>M0212M</td><td></td></tr><tr><td>Hybridization system</td><td>Roche-Nimblegen, Madison, WI, USA</td><td>N/A</td><td>This company no longer makes arrays or related items, so alternate sources such as Agilent or Affymetrix will need to be used.</td></tr><tr><td>Custom printed microarrays and mixers</td><td>Roche-Nimblegen, Madison, WI, USA</td><td>N/A</td><td></td></tr><tr><td>Hybridization kit (2x Hybridization buffer, Hybridization component A, Alignment oligo)</td><td>Roche-Nimblegen, Madison, WI, USA</td><td>N/A</td><td></td></tr><tr><td>Wash buffer kit (10x Wash buffer I, II, III, 1 M DTT)</td><td>Roche-Nimblegen, Madison, WI, USA</td><td>N/A</td><td></td></tr><tr><td>GenePix 4200A microarray scanner</td><td>Molecular Devices, Sunnyvale CA, USA</td><td>This model has been replaced by superior ones</td><td></td></tr><tr><td>GenePix Pro microarray software</td><td>Molecular Devices, Sunnyvale CA, USA</td><td></td><td></td></tr><tr><td>Nimblescan v.2.4, ChIP-chip analysis software</td><td>Roche-Nimblegen, Madison, WI, USA</td><td>N/A</td><td></td></tr></tbody></table>

dna-affinity-purified chip (dap-chip) method to determine gene targets for bacterial two component regulatory systems

In vivo methods such as ChIP-chip are well-established techniques used to determine global gene targets for transcription factors. However, they are of limited use in exploring bacterial two component regulatory systems with uncharacterized activation conditions. Such systems regulate transcription only when activated in the presence of unique signals. Since these signals are often unknown, the in vitro microarray based method described in this video article can be used to determine gene targets and binding sites for response regulators. This DNA-affinity-purified-chip method may be used for any purified regulator in any organism with a sequenced genome. The protocol involves allowing the purified tagged protein to bind to sheared genomic DNA and then affinity purifying the protein-bound DNA, followed by fluorescent labeling of the DNA and hybridization to a custom tiling array. Preceding steps that may be used to optimize the assay for specific regulators are also described. The peaks generated by the array data analysis are used to predict binding site motifs, which are then experimentally validated. The motif predictions can be further used to determine gene targets of orthologous response regulators in closely related species. We demonstrate the applicability of this method by determining the gene targets and binding site motifs and thus predicting the function for a sigma54-dependent response regulator DVU3023 in the environmental bacterium Desulfovibrio vulgaris Hildenborough.

The above method was applied to determine the global gene targets of the RRs in the model sulfate reducing bacterium Desulfovibrio vulgaris Hildenborough7. This organism has a large number of TCSs represented by over 70 RRs, indicating the wide variety of possible signals that it senses and responds to. In vivo analyses on the functions of these signaling systems are hard to perform since their signals and thus their activating conditions are unknown. Here the DAP-chip method was used to dete...

Watch this Scientific Journal Video about DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems at JoVE.com

DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

This video article describes an in vitro microarray based method to determine the gene targets and binding sites for two component system response regulators.

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

In vivo methods such as ChIP-chip are well-established techniques used to determine global gene targets for transcription factors. However, they are of ...

dna-affinity-purified-chip-dap-chip-method-to-determine-gene-targets

Research

JoVE Journal

Biology

16.7K Views.  Lawrence Berkeley National Laboratory.  Deze video artikel beschrijft een in vitro microarray gebaseerde methode om het gen doelstellingen en bindingsplaatsen bepalen voor twee componenten systeem respons toezichthouders. 

Video: DNA-affinity-purified Chip DAP-chip Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

A Chromatin Immunoprecipitation Assay to Identify Novel NFAT2 Target Genes in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western countries. The majority of CLL patients show an indolent course of the disease as well as an anergic phenotype of their leukemia cells, referring to a B cell receptor unresponsive to external stimulation. We have recently shown that the transcription factor NFAT2 is a crucial regulator of anergy in CLL. A major challenge in the analysis of the role of a transcription factor in different diseases is the identification of its specific target genes. This is of&#160;great significance for the elucidation of pathogenetic mechanisms and potential therapeutic interventions. Chromatin immunoprecipitation (ChIP) is a classic technique to demonstrate protein-DNA interactions and can, therefore, be used to identify direct target genes of transcription factors in mammalian cells. Here, ChIP was used to identify LCK as a direct target gene of NFAT2 in human CLL cells. DNA and associated proteins are crosslinked using formaldehyde and subsequently sheared by sonication into DNA fragments of approximately 200-500 base pairs (bp). Cross-linked DNA fragments associated with NFAT2 are then selectively immunoprecipitated from cell debris using an &#945;NFAT2 antibody. After purification, associated DNA fragments are detected via quantitative real-time PCR (qRT-PCR). DNA sequences with evident enrichment represent regions of the genome which are targeted by NFAT2 in vivo. Appropriate shearing of the DNA and the selection of the required antibody are particularly crucial for the successful application of this method. This protocol is ideal for the demonstration of direct interactions of NFAT2 with target genes. Its major limitation is the difficulty to employ ChIP in large-scale assays analyzing the target genes of multiple transcription factors in intact organisms.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. NFAT transcription factors are important regulators of development and activation in numerous cell types. Here, we present a protocol for the use of chromatin immunoprecipitation (ChIP) in human CLL cells to identify novel target genes of NFAT2.

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western ...

Cancer Research

A Fluorescence-based Method to Study Bacterial Gene Regulation in Infected Tissues

Bacterial virulence genes are often regulated at the transcriptional level by multiple factors that respond to different environmental signals. Some factors act directly on virulence genes; others control pathogenesis by adjusting the expression of downstream regulators or the accumulation of signals that affect regulator activity. While regulation has been studied extensively during in vitro growth, relatively little is known about how gene expression is adjusted during infection. Such information is important when a particular gene product is a candidate for therapeutic intervention. Transcriptional approaches like quantitative, real-time RT-PCR and RNA-Seq are powerful ways to examine gene expression on a global level but suffer from many technical challenges including low abundance of bacterial RNA compared to host RNA, and sample degradation by RNases. Evaluating regulation using fluorescent reporters is relatively easy and can be multiplexed with fluorescent proteins with unique spectral properties. The method allows for single-cell, spatiotemporal analysis of gene expression in tissues that exhibit complex three-dimensional architecture and physiochemical gradients that affect bacterial regulatory networks. Such information is lost when data are averaged over the bulk population. Herein, we describe a method for quantifying gene expression in bacterial pathogens in situ. The method is based on simple tissue processing and direct observation of fluorescence from reporter proteins. We demonstrate the utility of this system by examining the expression of Staphylococcus aureus thermonuclease (nuc), whose gene product is required for immune evasion and full virulence ex vivo and in vivo. We show that nuc-gfp is strongly expressed in renal abscesses and reveal heterogeneous gene expression due in part to apparent spatial regulation of nuc promoter activity in abscesses fully engaged with the immune response. The method can be applied to any bacterium with a manipulatable genetic system and any infection model, providing valuable information for preclinical studies and drug development.

Described here is a method for analyzing bacterial gene expression in animal tissues at a cellular level. This method provides a resource for studying the phenotypic diversity occurring within a bacterial population in response to the tissue environment during an infection.

Bacterial virulence genes are often regulated at the transcriptional level by multiple factors that respond to different environmental signals. Some ...

Genetics

Stress-induced Antibiotic Susceptibility Testing on a Chip

We have developed a rapid microfluidic method for antibiotic susceptibility testing in a stress-based environment. Fluid is passed at high speeds over bacteria immobilized on the bottom of a microfluidic channel. In the presence of stress and antibiotic, susceptible strains of bacteria die rapidly. However, resistant bacteria survive these stressful conditions. The hypothesis behind this method is new: stress activation of biochemical pathways, which are targets of antibiotics, can accelerate antibiotic susceptibility testing. As compared to standard antibiotic susceptibility testing methods, the rate-limiting step -&#160;bacterial growth -&#160;is omitted during antibiotic application. The technical implementation of the method is in a combination of standard techniques and innovative approaches. The standard parts of the method include bacterial culture protocols, defining microfluidic channels in polydimethylsiloxane&#160;(PDMS), cell viability monitoring with fluorescence, and batch image processing for bacteria counting. Innovative parts of the method are in the use of culture media flow for mechanical stress application, use of enzymes to damage but not kill the bacteria, and use of microarray substrates for bacterial attachment. The developed platform can be used in antibiotic and nonantibiotic related drug development and testing. As compared to the standard bacterial suspension experiments, the effect of the drug can be turned on and off repeatedly over controlled time periods. Repetitive observation of the same bacterial population is possible over the course of the same experiment.

We have developed a microfluidic platform for rapid antibiotic susceptibility testing. Fluid is passed at high speeds over bacteria immobilized on the bottom of a microfluidic channel. In the presence of stress and antibiotic, susceptible strains of bacteria die rapidly. However, resistant bacteria can survive these stressful conditions.

We have developed a rapid microfluidic method for antibiotic susceptibility testing in a stress-based environment. Fluid is passed at high speeds over ...

Bioengineering

An Assay for Quantifying Protein-RNA Binding in Bacteria

In the initiation step of protein translation, the ribosome binds to the initiation region of the mRNA. Translation initiation can be blocked by binding of an RNA binding protein (RBP) to the initiation region of the mRNA, which interferes with ribosome binding. In the presented method, we utilize this blocking phenomenon to quantify the binding affinity of RBPs to their cognate and non-cognate binding sites. To do this, we insert a test binding site in the initiation region of a reporter mRNA and induce the expression of the test RBP. In the case of RBP-RNA binding, we observed a sigmoidal repression of the reporter expression as a function of RBP concentration. In the case of no-affinity or very low affinity between binding site and RBP, no significant repression was observed. The method is carried out in live bacterial cells, and does not require expensive or sophisticated machinery. It is useful for quantifying and comparing between the binding affinities of different RBPs that are functional in bacteria to a set of designed binding sites. This method may be inappropriate for binding sites with high structural complexity. This is due to the possibility of repression of ribosomal initiation by complex mRNA structure in the absence of RBP, which would result in lower basal reporter gene expression, and thus less-observable reporter repression upon RBP binding.

In this method, we quantify the binding affinity of RNA binding proteins (RBPs) to cognate and non-cognate binding sites using a simple, live, reporter assay in bacterial cells. The assay is based on repression of a reporter gene.

In the initiation step of protein translation, the ribosome binds to the initiation region of the mRNA. Translation initiation can be blocked by binding ...

Discovering CsgD Regulatory Targets in Salmonella Biofilm Using Chromatin Immunoprecipitation and High-Throughput Sequencing (ChIP-seq)

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a technique that can be used to discover the regulatory targets of transcription factors, histone modifications, and other DNA-associated proteins. ChIP-seq data can also be used to find differential binding of transcription factors in different environmental conditions or cell types. Initially, ChIP was performed through hybridization on a microarray (ChIP-chip); however, ChIP-seq has become the preferred method through technological advancements, decreasing financial barriers to sequencing, and massive amounts of high-quality data output. Techniques of performing ChIP-seq with bacterial biofilms, a major source of persistent and chronic infections, are described in this protocol. ChIP-seq is performed on Salmonella enterica serovar Typhimurium biofilm and planktonic cells, targeting the master biofilm regulator, CsgD, to determine differential binding in the two cell types. Here, we demonstrate the appropriate amount of biofilm to harvest, normalizing to a planktonic control sample, homogenizing biofilm for cross-linker access, and performing routine ChIP-seq steps to obtain high quality sequencing results.

Discovering CsgD Regulatory Targets in Salmonella Biofilm Using Chromatin Immunoprecipitation and High-Throughput Sequencing ChIP-seq

Chromatin immunoprecipitation coupled with next-generation sequencing (ChIP-seq) is a method used to establish interactions between transcription factors and the genomic sequences they control. This protocol outlines techniques for performing ChIP-seq with bacterial biofilms, using Salmonella enterica serovar Typhimurium bacterial biofilm as an example.

Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a technique that can be used to discover the regulatory targets of transcription ...

Gene Expression Profiling of Infecting Microbes Using a Digital Bar-coding Platform

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene transcripts from infected tissues. Pathogen RNA constitutes a tiny portion of the total RNA isolated from infected tissue samples. Both microarray and RNAseq technologies have difficulties in generating reliable reads for weakly expressed pathogen genes. Mutant pathogen strains with reduced in vivo proliferation pose an even bigger challenge. Here we describe an in vivo gene expression profiling protocol that is very fast, extremely sensitive and highly reproducible. We developed this protocol during our investigation of the fungal pathogen Candida albicans in a murine model of hematogenously disseminated candidiasis. Using this protocol, we have documented time courses of dynamically regulated C. albicans gene expression during kidney infection, and discovered unexpected features of gene expression responses to antifungal drug treatment in vivo.

We developed a protocol that is fast, sensitive and reproducible for pathogen gene expression profiling during an infection.

For most mammalian pathogens, gene expression profiling studies have been limited by technical difficulties to accurately quantify pathogen gene ...

Immunology and Infection

Pulldown Assay Coupled with Co-Expression in Bacteria Cells as a Time-Efficient Tool for Testing Challenging Protein-Protein Interactions

Pulldown is an easy and widely used protein-protein interaction assay. However, it has limitations in studying protein complexes that do not assemble effectively in vitro. Such complexes may require co-translational assembly and the presence of molecular chaperones; either they form stable oligomers which cannot dissociate and re-associate in vitro or are unstable without a binding partner. To overcome these problems, it is possible to use a method based on the bacterial co-expression of differentially tagged proteins using a set of compatible vectors followed by the conventional pulldown techniques. The workflow is more time-efficient compared to traditional pulldown because it lacks the time-consuming steps of separate purification of interacting proteins and their following incubation. Another advantage is a higher reproducibility due to a significantly smaller number of steps and a shorter period of time in which proteins that exist within the in vitro environment are exposed to proteolysis and oxidation. The method was successfully applied for studying a number of protein-protein interactions when other in vitro techniques were found to be unsuitable. The method can be used for batch testing protein-protein interactions. Representative results are shown for studies of interactions between BTB domain and intrinsically disordered proteins, and of heterodimers of zinc-finger-associated domains.

Here, we describe a method for the bacterial co-expression of differentially tagged proteins using a set of compatible vectors, followed by the conventional pulldown techniques to study protein complexes that cannot assemble in vitro.

Pulldown is an easy and widely used protein-protein interaction assay. However, it has limitations in studying protein complexes that do not assemble ...

Biochemistry

Precision DNAzyme Nanomachines for Discriminative RNA and DNA Analysis

DNAzyme 10-23 - Based Nanomachines for Nucleic Acid Recognition

DNAzyme-based nanomachines (DNM) for the detection of DNA and RNA sequences (analytes) are multifunctional structures made of oligonucleotides. Their functions include tight analyte binding, highly selective analyte recognition, fluorescent signal amplification by multiple catalytic cleavages of a fluorogenic reporter substrate, and fluorogenic substrate attraction for an increase in sensor response. Functional units are attached to a common DNA scaffold for their cooperative action. The RNA-cleaving 10-23 DNMs feature&#160;improved sensitivity in comparison with non-catalytic hybridization probes. The stability of the DNM and the increased chances of substrate recognition are provided&#160;by a double-stranded DNA fragment,&#160;a tile. DNM can differentiate two analytes with a single nucleotide difference in a folded RNA and a double-stranded DNA and detect analytes at concentrations ~1000 times lower than other protein-free hybridization probes. This article presents the concept behind the diagnostic potential of DNA-nanomachine activity and overviews DNM design, assembly, and application&#160;in nucleic acid detection assays.

Author Spotlight: Advancements in DNA Nanosensors &#8211; Addressing Sensitivity and Selectivity Challenges in Molecular Detection

The DNAzyme-based nanomachines can be used for highly selective and sensitive detection of nucleic acids. This article describes a detailed protocol for the design of DNAzyme-based nanomachines with a 10-23 core using free software and their application in the detection of an Epstein-Barr virus fragment as an example.

DNAzyme-based nanomachines (DNM) for the detection of DNA and RNA sequences (analytes) are multifunctional structures made of oligonucleotides. Their ...

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Phenotypes are determined by a complex series of physical (e.g. protein-protein) and functional (e.g. gene-gene or genetic) interactions (GI)1. While physical interactions can indicate which bacterial proteins are associated as complexes, they do not necessarily reveal pathway-level functional relationships1. GI screens, in which the growth of double mutants bearing two deleted or inactivated genes is measured and compared to the corresponding single mutants, can illuminate epistatic dependencies between loci and hence provide a means to query and discover novel functional relationships2. Large-scale GI maps have been reported for eukaryotic organisms like yeast3-7, but GI information remains sparse for prokaryotes8, which hinders the functional annotation of bacterial genomes. To this end, we and others have developed high-throughput quantitative bacterial GI screening methods9, 10.
Here, we present the key steps required to perform quantitative E. coli Synthetic Genetic Array (eSGA) screening procedure on a genome-scale9, using natural bacterial conjugation and homologous recombination to systemically generate and measure the fitness of large numbers of double mutants in a colony array format. Briefly, a robot is used to transfer, through conjugation, chloramphenicol (Cm) - marked mutant alleles from engineered Hfr (High frequency of recombination) 'donor strains' into an ordered array of kanamycin (Kan) - marked F- recipient strains. Typically, we use loss-of-function single mutants bearing non-essential gene deletions (e.g. the 'Keio' collection11) and essential gene hypomorphic mutations (i.e. alleles conferring reduced protein expression, stability, or activity9, 12, 13) to query the functional associations of non-essential and essential genes, respectively. After conjugation and ensuing genetic exchange mediated by homologous recombination, the resulting double mutants are selected on solid medium containing both antibiotics. After outgrowth, the plates are digitally imaged and colony sizes are quantitatively scored using an in-house automated image processing system14. GIs are revealed when the growth rate of a double mutant is either significantly better or worse than expected9. Aggravating (or negative) GIs often result between loss-of-function mutations in pairs of genes from compensatory pathways that impinge on the same essential process2. Here, the loss of a single gene is buffered, such that either single mutant is viable. However, the loss of both pathways is deleterious and results in synthetic lethality or sickness (i.e. slow growth). Conversely, alleviating (or positive) interactions can occur between genes in the same pathway or protein complex2 as the deletion of either gene alone is often sufficient to perturb the normal function of the pathway or complex such that additional perturbations do not reduce activity, and hence growth, further. Overall, systematically identifying and analyzing GI networks can provide unbiased, global maps of the functional relationships between large numbers of genes, from which pathway-level information missed by other approaches can be inferred9.

Mapping Bacterial Functional Networks and Pathways in Escherichia Coli using Synthetic Genetic Arrays

Systematic, large-scale synthetic genetic (gene-gene or epistasis) interaction screens can be used to explore genetic redundancy and pathway cross-talk. Here, we describe a high-throughput quantitative synthetic genetic array screening technology, termed eSGA that we developed for elucidating epistatic relationships and exploring genetic interaction networks in Escherichia coli.

Phenotypes  are determined by a complex series of physical (e.g. protein-protein) and  functional (e.g. gene-gene or genetic) interactions (GI)1. While ...

Reporter Gene Repression Assay to Study Translational Regulation of a Target Gene

Source: Katz, N., et al. <a href="https://app.jove.com/v/59611">An Assay for Quantifying Protein-RNA Binding in Bacteria.</a> J. Vis. Exp. (2019)
This video demonstrates an in vivo assay in bacteria to study the interaction of RNA-binding proteins (RBPs) with RNA. The bacterial cells are transformed with two plasmid constructs &#8212; a binding-site plasmid encoding an mRNA containing a fluorescent reporter gene downstream of an RBP-binding site &#8212; while an RBP plasmid expresses the RBP proteins under the control of an inducer. Upon inducer-mediated increase in RBP production, the RBPs bind to the mRNA, resulting in translational repression of the reporter via inhibition of ribosome binding.

DNA-affinity-purified Chip (DAP-chip) Method to Determine Gene Targets for Bacterial Two component Regulatory Systems

Samenvatting

Meer video's verkennen

Hoofdstukken in deze video