This work was supported by National Institutes of Health (Grants # AI122034 and AI140167) and New Jersey Health Foundation (Grant # PC 20-18).

1. Preparation of proteins
<ol>
	<li>Use a dialysis bag (with an appropriate cut-off size) to dialyze each protein to be used for BLI assays (including both the His-tagged ligand and the analyte) against 1,000 volumes of the BLI buffer (25 mM Tris-HCl, 150 mM NaCl, 0.1 mM EDTA, 10 mM MgCl2, 0.1 mM DTT, pH 8.0, pre-chilled to 4 &#730;C) at 4 &#730;C for 4 h. 
	NOTE: BLI assays require the ligand to be present at concentrations that saturate the binding sites on the biosensor and the analyte to be highly purified so that the molar concentrations of the analyte that react with the ligand is known. Methodologies for the expression and purification of His- and Strep-tagged proteins are not covered here, but can be found in previous publications14,15. Although this system does not require the ligand to be in highly purified form, it is essential to dialyze even unpurified ligands to the BLI buffer in order to minimize shifts in white-light interference patterns caused by any buffer changes during the assay.</li>
	<li>Switch to fresh BLI buffer and continue the dialysis for another 4 h.</li>
</ol>
2. Biosensor hydration and assay set-up
<ol>
	<li>Approximately 10 min prior to the start of an assay, pipette 200 &#181;L of the BLI buffer into a PCR tube.</li>
	<li>Remove a Ni-NTA-biosensor from the original packaging by holding the wide portion of the biosensor using a gloved hand.</li>
	<li>Place the biosensor over the PCR-tube such that only the glass tip of the biosensor is submerged in the BLI buffer.</li>
	<li>Keep the biosensor tip submerged for at least 10 min to ensure full hydration.
	<ol>
		<li>Verify that the glass tip of the Ni-NTA-biosensor does not touch anything other than the BLI buffer during the above step. 
		NOTE: This protocol uses a Ni-NTA-biosensor in conjunction with a His-tagged ligand. If needed, a SA-Streptavidin-biosensor can be used in conjunction with a biotinylated ligand instead if: (i) both the ligand and analyte carry a His tag or (ii) neither of them does.</li>
	</ol>
	</li>
	<li>Turn the BLItz machine on.</li>
	<li>Ensure that the machine is connected to the computer through a USB data output port at the back of the machine.</li>
	<li>On the computer, open the associated software (e.g., BLItz Pro), and click on Advanced Kinetics on the left-hand side of the screen.</li>
	<li>On the software, type out all appropriate information about the experiment (including the Experiment Name, Description, Sample ID, and Protein Concentration) under each respective heading.</li>
	<li>Click on Biosensor Type and choose Ni-NTA from the drop-down menu.
	<ol>
		<li>Under the Run Settings heading, verify that the Shaker is set to Enable.</li>
		<li>Under the Step Type List heading, verify that there are 5 items listed: Initial Baseline, Loading, Baseline, Association, and Dissociation. 
		NOTE: The duration of each step can be changed from default as needed. For optimal results, use a minimum of 30 s for Initial Baseline and Baseline; and 120 s for Association and Dissociation. The duration of the Loading step (ranging from 120 to 240 s) will depend upon the concentration of the ligand and affinity of the His-epitope tag on the ligand to the Ni-NTA-biosensor.</li>
	</ol>
	</li>
	<li>Remove the hydrated Ni-NTA-biosensor from the PCR tube and affix it to the biosensor mount on the machine by sliding the wide portion of the biosensor onto the mount. 
	NOTE: Do not let the biosensor dry out during the experiment.</li>
	<li>Place a 0.5 mL black microcentrifuge tube into the tube holder of the machine and pipette 400 &#181;L of the BLI buffer into it.</li>
	<li>Verify that the slider of the machine is positioned such that the tube holder is situated in front of the black arrow on the machine.</li>
	<li>Close the cover of the machine such that the biosensor tip becomes submerged in the buffer in the microcentrifuge tube.</li>
	<li>Click Next on the software to begin recording the Initial Baseline.</li>
</ol>
3. Loading of ligand onto biosensor
<ol>
	<li>After the Initial Baseline step has finished recording, open the cover of the machine.</li>
	<li>Move the slider to the right such that the drop holder (instead of the tube holder) is situated in front of the black arrow.</li>
	<li>Pipette 4 &#181;L of a dialyzed His-tagged ligand (from Step 1.1) onto the drop holder and close the cover of the machine. 
	NOTE: The optimal concentration of the ligand to be used may vary for each protein. A concentration between 1.0 to 2.0 mg/mL is usually adequate to saturate the NTA at the tip of the biosensor in 240 s.</li>
	<li>On the software, click Next to begin Loading.</li>
</ol>
4. Washing away additional ligand
<ol>
	<li>After the Loading step has finished recording, open the cover of the machine.</li>
	<li>Move the slider to the left such that the tube holder is once again situated in front of the black arrow.</li>
	<li>Close the lid of the machine and ensure that the biosensor tip is submerged into the BLI buffer of the tube in the tube holder.</li>
	<li>Click Next once again on the software to begin recording the Baseline.</li>
</ol>
5. Association of analyte to ligand
<ol>
	<li>After the Baseline step has finished recording, open the cover of the machine.</li>
	<li>Remove the drop holder and clean it by pipetting out any protein and rinsing it with double-deionized water (ddH2O) for a total of 5 times.
	<ol>
		<li>Use a tissue wipe to clean the surface of the drop holder after the wash.</li>
	</ol>
	</li>
	<li>Replace the drop holder back onto the machine.</li>
	<li>Move the slider on the machine to the right such that the drop holder is once again situated in front of the black arrow.</li>
	<li>Pipette 4 &#181;L of a dialyzed analyte (from Step 1.1) onto the drop holder and close the cover of the machine.</li>
	<li>On the software, click Next to begin Association.</li>
</ol>
6. Dissociation of analyte from ligand
<ol>
	<li>After the Association step has finished recording, open the cover of the machine.</li>
	<li>Move the slider on the machine to the right such that the tube holder is once again situated in front of the black arrow.</li>
	<li>On the software, click Next to begin Dissociation.</li>
	<li>After the Dissociation step has finished recording, open the cover of the machine.</li>
	<li>Remove the drop holder and tube holder.</li>
	<li>Rinse both with ddH2O thoroughly to wash away any protein.</li>
	<li>Remove the biosensor and discard it safely.</li>
</ol>
7. Repeating interactions with different concentrations
<ol>
	<li>Repeat Steps 2-7 for the same ligand-analyte pair using different analyte concentrations. 
	NOTE: The concentration of the analyte may need to be adjusted across several runs before obtaining optimal results. In our experience, a ratio of 1:5:10 of analyte concentrations, starting with 75 nM, is usually adequate.</li>
</ol>
8. Analyzing the data using the software
<ol>
	<li>Once all runs have finished, save the data on the software by clicking File and then Save Experiment As on the left side of the screen.</li>
	<li>Under the Run Data heading, select Step Correction and Fitting (1:1) and click Analyze to generate kinetic data.</li>
	<li>To extract the quantitative data into a worksheet and generate graphs, click on Export to CSV and save the recorded data as a .csv file. Open the .csv file using spreadsheet software.
	<ol>
		<li>To most effectively show the Association and Dissociation kinetics, remove all plot points prior to the Baseline step, and normalize all subsequent plot points from the final Baseline value.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Vvedenskaya, I. O., 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=Interactions+between+RNA+polymerase+and+the+core+recognition+element+are+a+determinant+of+transcription+start+site+selection.">Interactions between RNA polymerase and the core recognition element are a determinant of transcription start site selection.</a> Proceedings of the National Academy of Sciences of the U.S.A. 113 (21), E2899-E2905 (2016).</li><li>Feklistov, A., Sharon, B. D., Darst, S. A., Gross, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bacterial+sigma+factors:+a+historical,+structural,+and+genomic+perspective.">Bacterial sigma factors: a historical, structural, and genomic perspective.</a> Annual Review of Microbiology. 68, 357-376 (2014).</li><li>Visweswariah, S. S., Busby, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evolution+of+bacterial+transcription+factors:+how+proteins+take+on+new+tasks,+but+do+not+always+stop+doing+the+old+ones.">Evolution of bacterial transcription factors: how proteins take on new tasks, but do not always stop doing the old ones.</a> Trends in Microbiology. 23 (8), 463-467 (2015).</li><li>Taylor, H. R., Burton, M. J., Haddad, D., West, S., Wright, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trachoma.">Trachoma.</a> Lancet. 384 (9960), 2142-2152 (2014).</li><li>WHO. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+incidence+and+prevalence+of+selected+curable+sexually+transmitted+infections:+2008.">Global incidence and prevalence of selected curable sexually transmitted infections: 2008.</a> Sexual and Reproductive Health Matters. 20, (2012).</li><li>Schmidt, S. M., Muller, C. E., Mahner, B., Wiersbitzky, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence,+rate+of+persistence+and+respiratory+tract+symptoms+of+Chlamydia+pneumoniae+infection+in+1211+kindergarten+and+school+age+children.">Prevalence, rate of persistence and respiratory tract symptoms of Chlamydia pneumoniae infection in 1211 kindergarten and school age children.</a> The Pediatric Infectious Disease Journal. 21 (8), 758-762 (2002).</li><li>De Puysseleyr, K., 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=Evaluation+of+the+presence+and+zoonotic+transmission+of+Chlamydia+suis+in+a+pig+slaughterhouse.">Evaluation of the presence and zoonotic transmission of Chlamydia suis in a pig slaughterhouse.</a> BMC Infectious Diseases. 14 (560), (2014).</li><li>Hulin, V., 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=Host+preference+and+zoonotic+potential+of+Chlamydia+psittaci+and+C.+gallinacea+in+poultry.">Host preference and zoonotic potential of Chlamydia psittaci and C. gallinacea in poultry.</a> Pathogens and Disease. 73 (1), 1-11 (2015).</li><li>Belland, R., Ojcius, D. M., Byrne, G. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chlamydia.">Chlamydia.</a> Nature Review of Microbiol. 2 (7), 530-531 (2004).</li><li>Belland, R. J., 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=Genomic+transcriptional+profiling+of+the+developmental+cycle+of+Chlamydia+trachomatis.">Genomic transcriptional profiling of the developmental cycle of Chlamydia trachomatis.</a> Proceedings of the National Academy of Sciences of the USA. 100 (14), 8478-8483 (2003).</li><li>Nicholson, T. L., Olinger, L., Chong, K., Schoolnik, G., Stephens, R. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+stage-specific+gene+regulation+during+the+developmental+cycle+of+Chlamydia+trachomatis.">Global stage-specific gene regulation during the developmental cycle of Chlamydia trachomatis.</a> Journal of Bacteriology. 185 (10), 3179-3189 (2003).</li><li>Tan, M., Tan, M., Bavoil , P. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Intracellular pathogens I: Chlamydiales. , 149-169 (2012).</li><li>Domman, D., Horn, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Following+the+Footsteps+of+Chlamydial+Gene+Regulation.">Following the Footsteps of Chlamydial Gene Regulation.</a> Molecular Biology and Evolution. 32 (12), 3035-3046 (2015).</li><li>Bao, X., Nickels, B. E., Fan, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chlamydia+trachomatis+protein+GrgA+activates+transcription+by+contacting+the+nonconserved+region+of+&#963;66.">Chlamydia trachomatis protein GrgA activates transcription by contacting the nonconserved region of &#963;66.</a> Proceedings of the National Academy of Sciences of the USA. 109 (42), 16870-16875 (2012).</li><li>Desai, M., 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=Role+for+GrgA+in+regulation+of+&#963;28-dependent+transcription+in+the+obligate+intracellular+bacterial+pathogen+Chlamydia+trachomatis.">Role for GrgA in regulation of &#963;28-dependent transcription in the obligate intracellular bacterial pathogen Chlamydia trachomatis.</a> Journal of Bacteriology. 200 (20), (2018).</li><li>Joy, 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=Label-Free+Detection+of+Biomolecular+Interactions+Using+BioLayer+Interferometry+for+Kinetic+Characterization.">Label-Free Detection of Biomolecular Interactions Using BioLayer Interferometry for Kinetic Characterization.</a> Combinatorial Chemistry &amp; High Throughput Screening. 12 (8), 791-800 (2009).</li><li>Abdiche, Y., Malashock, D., Pinkerton, A., Pons, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Determining+kinetics+and+affinities+of+protein+interactions+using+a+parallel+real-time+label-free+biosensor,+the+Octet.">Determining kinetics and affinities of protein interactions using a parallel real-time label-free biosensor, the Octet.</a> Analytical Biochemistry. 377 (2), 209-217 (2008).</li><li>Szabo, A., Stolz, L., Granzow, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surface+plasmon+resonance+and+its+use+in+biomolecular+interaction+analysis+(BIA).">Surface plasmon resonance and its use in biomolecular interaction analysis (BIA).</a> Current Opinion in Structural Biology. 5 (5), 699-705 (1995).</li><li>Nelson, R. W., Krone, J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advances+in+surface+plasmon+resonance+biomolecular+interaction+analysis+mass+spectrometry+(BIA/MS).">Advances in surface plasmon resonance biomolecular interaction analysis mass spectrometry (BIA/MS).</a> Journal of Molecular Recognition. 12 (2), 77-93 (1999).</li><li>Yang, D., Singh, A., Wu, H., Kroe-Barrett, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparison+of+biosensor+platforms+in+the+evaluation+of+high+affinity+antibody-antigen+binding+kinetics.">Comparison of biosensor platforms in the evaluation of high affinity antibody-antigen binding kinetics.</a> Analytical Biochemistry. 508, 78-96 (2016).</li><li>Visentin, J., 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=Overcoming+non-specific+binding+to+measure+the+active+concentration+and+kinetics+of+serum+anti-HLA+antibodies+by+surface+plasmon+resonance.">Overcoming non-specific binding to measure the active concentration and kinetics of serum anti-HLA antibodies by surface plasmon resonance.</a> Biosensors and Bioelectronics. 117, 191-200 (2018).</li><li>Baba, A., Taranekar, P., Ponnapati, R. R., Knoll, W., Advincula, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Electrochemical+surface+plasmon+resonance+and+waveguide-enhanced+glucose+biosensing+with+N-alkylaminated+polypyrrole/glucose+oxidase+multilayers.">Electrochemical surface plasmon resonance and waveguide-enhanced glucose biosensing with N-alkylaminated polypyrrole/glucose oxidase multilayers.</a> ACS Applied Materials &amp; Interfaces. 2 (8), 2347-2354 (2010).</li><li>Del Vecchio, K., Stahelin, R. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+Surface+Plasmon+Resonance+to+Quantitatively+Assess+Lipid-Protein+Interactions.">Using Surface Plasmon Resonance to Quantitatively Assess Lipid-Protein Interactions.</a> Methods in Molecular Biology (Clifton, N.J.). 1376, 141-153 (2016).</li><li>Wang, D. S., Fan, S. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microfluidic+Surface+Plasmon+Resonance+Sensors:+From+Principles+to+Point-of-Care+Applications.">Microfluidic Surface Plasmon Resonance Sensors: From Principles to Point-of-Care Applications.</a> Sensors (Basel, Switzerland). 16 (8), 1175 (2016).</li><li>Shah, N. B., Duncan, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bio-layer+interferometry+for+measuring+kinetics+of+protein-protein+interactions+and+allosteric+ligand+effects.">Bio-layer interferometry for measuring kinetics of protein-protein interactions and allosteric ligand effects.</a> Journal of visualized experiments : JoVE. (84), e51383 (2014).</li><li>Wartchow, C. A., 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=Biosensor-based+small+molecule+fragment+screening+with+biolayer+interferometry.">Biosensor-based small molecule fragment screening with biolayer interferometry.</a> Journal of Computer-Aided Molecular Design. 25 (7), 669-676 (2011).</li></ol>

The authors have nothing to disclose.

Protein-protein interactions are crucial for the regulation of transcription and other biological processes. They are most commonly studied through pulldown assays. Although pulldown assays are relatively easy to perform, they are poorly quantitative and may fail to detect weak but biologically meaningful interactions. In comparison, by detecting real-time association and dissociation between a ligand and an analyte, BLI provides association and dissociation rate constants, as well as, overall affinity.
<p class="jov...

Transcription, which produces RNA molecules using DNA as template, is the very first step of gene expression. Bacterial RNA synthesis begins following the binding of the RNA polymerase (RNAP) holoenzyme to a target promoter1,2. The RNAP holoenzyme (RNAPholo) is comprised of a multi-subunit catalytic core (RNAPcore) and a &#963; factor, which is required for recognizing the promoter sequence. Transcription activators and repressors, collectively termed TFs, regulate the gene expression through the binding components of the RNAPcore, &#963; factors, and/or DNA. Depending on the organism, a significant portion of its genome may be devoted to TFs that regulate transcription in response to physiological needs and environmental cues3.
Chlamydia is an obligate intracellular bacterium responsible for a variety of diseases in humans and animals4,5,6,7,8. For example, Chlamydia trachomatis is arguably the number one sexually transmitted pathogen in humans worldwide, and a leading cause of blindness in some underdeveloped countries4,5. Chlamydia has a unique developmental cycle characterized by two alternating cellular forms termed the elementary body (EB) and reticulate body (RB)9. Whereas, EBs are capable of survival in an extracellular environment, they are incapable of proliferation. EBs enter host cells through endocytosis and differentiate into larger RBs in a vacuole in the host cytoplasm within hours post-inoculation. No longer infectious, RBs proliferate through binary fission. Around 20 h, they start to differentiate back to the EBs, which exit the host cells around 30-70 h.
Progression of the chlamydial developmental cycle is regulated by transcription. Whereas a supermajority of the nearly 1,000 chlamydial genes are expressed during the midcycle during which RBs are actively replicating, only a small number of genes are transcribed immediately after the entry of EBs into the host cells to initiate the conversion of EBs into RBs, and another small set of genes are transcribed or increasingly transcribed to enable the differentiation of RBs into EBs10,11.
The chlamydial genome encodes three &#963; factors, namely &#963;66, &#963;28 and &#963;54. &#963;66, which is equivalent to the housekeeping &#963;70 of E. coli and other bacteria, is responsible for recognizing promoters of early and mid-cycle genes as well as some late genes, whereas &#963;28 and &#963;54 are required for the transcription of certain late genes. Several genes are known to carry both a &#963;66-dependent promoter and a &#963;28-dependent promoter12.
Despite a complicated developmental cycle, only a small number of TFs have been found in chlamydiae13. GrgA (previously annotated as a hypothetical protein CT504 in C. trachomatis serovar D and CTL0766 in C. trachomatis L2) is a Chlamydia-specific TF initially recognized as an activator of &#963;66-dependent genes14. Affinity pulldown assays have demonstrated that GrgA activates their transcription by binding both &#963;66 and DNA. Interestingly, it was later found with that GrgA also co-precipitates with &#963;28, and activates transcription from &#963;28-dependent promoters in vitro15. To investigate whether GrgA has similar or different affinities for &#963;66 and &#963;28, we resorted to using BLI. BLI assays have shown that GrgA interacts with &#963;66 at a 30-fold higher affinity than with &#963;28, suggesting that GrgA may play differential roles in &#963;66-dependent transcription and &#963;28-dependent transcription15.
BLI detects the interference pattern of white light that reflects from a layer of immobilized protein on the tip of a biosensor and compares it to that of an internal reference layer16. Through the analysis of these two interference patterns, BLI can provide valuable and real-time information about the amount of protein bound to the tip of the biosensor. The protein that is immobilized to the tip of the biosensor is referred to as the ligand, and is generally immobilized with the help of a common antibody or epitope tag (e.g., a poly-His- or biotin-tag) that has an affinity for an associated particle (such as NTA or Streptavidin) on the tip of the biosensor. The binding of a secondary protein, referred to as the analyte, with the ligand at the tip of the biosensor creates changes in the opacity of the biosensor and therefore results in changes in interference patterns. When repeated over different concentrations of the analyte, BLI can provide not only qualitative but also quantitative information about the affinity between the ligand and analyte16.
To the best of our knowledge, we were the first to employ BLI to characterize protein-protein interactions in transcription15. In this publication, we demonstrate that a GrgA fragment, which was previously shown to be required for &#963;28-binding, indeed mediates the binding. This manuscript focuses on steps of the BLI assays, and generation of BLI graphs and parameters of binding kinetics. Methods for the production (and purification) of ligands and analytes are not covered here.

<table>
	<tbody>
		<tr>
			<td>BLItz machine</td>
			<td>ForteBio</td>
			<td>45-5000</td>
			<td></td>
		</tr>
		<tr>
			<td>Dialysis tubing cellulose membrane</td>
			<td>MilliporeSigma</td>
			<td>D9652</td>
			<td></td>
		</tr>
		<tr>
			<td>Dip and Read Ni-NTA biosensor tray</td>
			<td>ForteBio</td>
			<td>18-5101</td>
			<td>Ready-to-use Ni-NTA biosensors for poly-His-tagged Proteins</td>
		</tr>
		<tr>
			<td>Drop holder</td>
			<td>ForteBio</td>
			<td>45-5004</td>
			<td></td>
		</tr>
		<tr>
			<td>PCR tubes (0.2 mL)</td>
			<td>Thomas Scientific</td>
			<td>CLS6571</td>
			<td></td>
		</tr>
		<tr>
			<td>Microcentrifuge tubes (black)</td>
			<td>Thermo Fisher Scientific</td>
			<td>03-391-166</td>
			<td></td>
		</tr>
		<tr>
			<td>Kimwipes</td>
			<td>Thermo Fisher Scientific</td>
			<td>06-666A</td>
			<td></td>
		</tr>
		<tr>
			<td>DTT</td>
			<td>Thermo Fisher Scientific</td>
			<td>R0861</td>
			<td></td>
		</tr>
		<tr>
			<td>EDTA</td>
			<td>MilliporeSigma</td>
			<td>E6758</td>
			<td></td>
		</tr>
		<tr>
			<td>MgCl2</td>
			<td>MilliporeSigma</td>
			<td>M8266</td>
			<td></td>
		</tr>
		<tr>
			<td>NaCl</td>
			<td>MilliporeSigma</td>
			<td>S9888</td>
			<td></td>
		</tr>
		<tr>
			<td>Tris-HCl</td>
			<td>GoldBio</td>
			<td>T095100</td>
			<td></td>
		</tr>
	</tbody>
</table>

application of biolayer interferometry (bli) for studying protein-protein interactions in transcription

A transcription factor&#160;(TF) is a protein that regulates gene expression by interacting with the RNA polymerase, another TF, and/or template DNA. GrgA is a novel transcription activator found specifically in the obligate intracellular bacterial pathogen Chlamydia. Protein pulldown assays using affinity beads have revealed that GrgA binds two &#963; factors, namely &#963;66 and &#963;28, which recognize different sets of promoters for genes whose products are differentially required at developmental stages. We have used BLI to confirm and further characterize the interactions. BLI demonstrates several advantages over pulldown: 1) It reveals real-time association and dissociation between binding partners, 2) It generates quantitative kinetic parameters, and 3) It can detect bindings that pulldown assays often fail to detect. These characteristics have enabled us to deduce the physiological roles of GrgA in gene expression regulation in Chlamydia, and possible detailed interaction mechanisms. We envision that this relatively affordable technology can be extremely useful for studying transcription and other biological processes.

Through BLI assays, we previously established that binding of GrgA to &#963;28 is dependent on a 28 amino acid middle region (residues 138-165) of GrgA15. Accordingly, compared with N-terminally His-tagged full length GrgA (NH-GrgA), a GrgA deletion construct lacking this region (NH-GrgA&#916;138-165) had a decreased association rate and an increased dissociation rate, leading to a 3 million-fold loss of overall affinity (Table 1). Here, we demonstrate that this middle ...

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Application of Biolayer Interferometry BLI for Studying Protein-Protein Interactions in Transcription

Interactions of transcription factors (TFs) with the RNA polymerase are usually studied using pulldown assays. We apply a Biolayer Interferometry (BLI) technology to characterize the interaction of GrgA with the chlamydial RNA polymerase. Compared to pulldown assays, BLI detects real-time association and dissociation, offers higher sensitivity, and is highly quantitative.

Application of Biolayer Interferometry (BLI) for Studying Protein-Protein Interactions in Transcription

A transcription factor&#160;(TF) is a protein that regulates gene expression by interacting with the RNA polymerase, another TF, and/or template DNA. GrgA ...

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13.4K Views.  Rutgers University. Interactions of transcription factors (TFs) with the RNA polymerase are usually studied using pulldown assays. We apply a Biolayer Interferometry (BLI) technology to characterize the interaction of GrgA with the chlamydial RNA polymerase. Compared to pulldown assays, BLI detects real-time association and dissociation, offers higher sensitivity, and is highly quantitative.

Video: Application of Biolayer Interferometry BLI for Studying Protein-Protein Interactions in Transcription

Fluorescence Anisotropy as a Tool to Study Protein-protein Interactions

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is necessary to characterize it at the structural and mechanistic level. Several biochemical and biophysical methods exist for such purpose. Among them, fluorescence anisotropy is a powerful technique particularly used when the fluorescence intensity of a fluorophore-labeled protein remains constant upon protein-protein interaction. In this technique, a fluorophore-labeled protein is excited with vertically polarized light of an appropriate wavelength that selectively excites a subset of the fluorophores according to their relative orientation with the incoming beam. The resulting emission also has a directionality whose relationship in the vertical and horizontal planes defines anisotropy (r) as follows: r=(IVV-IVH)/(IVV+2IVH), where IVV and IVH are the fluorescence intensities of the vertical and horizontal components, respectively. Fluorescence anisotropy is sensitive to the rotational diffusion of a fluorophore, namely the apparent molecular size of a fluorophore attached to a protein, which is altered upon protein-protein interaction. In the present text, the use of fluorescence anisotropy as a tool to study protein-protein interactions was exemplified to address the binding between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor like-1 GTPase (EFL1). Conventionally, labeling of a protein with a fluorophore is carried out on the thiol groups (cysteine) or in the amino groups (the N-terminal amine or lysine) of the protein. However, SBDS possesses several cysteines and lysines that did not allow site directed labeling of it. As an alternative technique, the dye 4&#39;,5&#39;-bis(1,3,2 dithioarsolan-2-yl) fluorescein was used to specifically label a tetracysteine motif, Cys-Cys-Pro-Gly-Cys-Cys, genetically engineered in the C-terminus of the recombinant SBDS protein. Fitting of the experimental data provided quantitative and mechanistic information on the binding mode between these proteins.

Protein interactions are at the heart of a cell&#39;s function. Calorimetric and spectroscopic techniques are commonly used to characterize them. Here we describe fluorescence anisotropy as a tool to study the interaction between the protein mutated in the Shwachman-Diamond Syndrome (SBDS) and the Elongation factor-like 1 GTPase (EFL1).

Protein-protein interactions play an essential role in the function of a living organism. Once an interaction has been identified and validated it is ...

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating these studies, reincorporation of detergent-solubilized membrane proteins into liposomes is a stochastic process where protein topology is impossible to enforce. This paper offers an alternative method to these challenging techniques that utilizes a liposome-based scaffold. Protein solubility is enhanced by deletion of the transmembrane domain, and these amino acids are replaced with a tethering moiety, such as a His-tag. This tether interacts with an anchoring group (Ni2+ coordinated by nitrilotriacetic acid (NTA(Ni2+)) for His-tagged proteins), which enforces a uniform protein topology at the surface of the liposome. An example is presented wherein the interaction between Dynamin-related protein 1 (Drp1) with an integral membrane protein, Mitochondrial Fission Factor (Mff), was investigated using this scaffold liposome method. In this work, we have demonstrated the ability of Mff to efficiently recruit soluble Drp1 to the surface of liposomes, which stimulated its GTPase activity. Moreover, Drp1 was able to tubulate the Mff-decorated lipid template in the presence of specific lipids. This example demonstrates the effectiveness of scaffold liposomes using structural and functional assays and highlights the role of Mff in regulating Drp1 activity.

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

This paper describes a method for assessing the interactions and assemblies of integral membrane proteins in vitro with various partner factors in a lipid-proximal environment.

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating ...

Time-resolved ElectroSpray Ionization Hydrogen-deuterium Exchange Mass Spectrometry for Studying Protein Structure and Dynamics

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. Hydrogen-Deuterium Exchange (HDX) measured at rapid time scales is uniquely suited to detect structures and hydrogen bonding networks that are briefly populated, allowing for the characterization of transient conformers in native ensembles. Coupling of HDX to mass spectrometry offers several key advantages, including high sensitivity, low sample consumption and no restriction on protein size. This technique has advanced greatly in the last several decades, including the ability to monitor HDX labeling times on the millisecond time scale. In addition, by incorporating the HDX workflow onto a microfluidic platform housing an acidic protease microreactor, we are able to localize dynamic properties at the peptide level. In this study, Time-Resolved ElectroSpray Ionization Mass Spectrometry (TRESI-MS) coupled to HDX was used to provide a detailed picture of residual structure in the tau protein, as well as the conformational shifts induced upon hyperphosphorylation.

Conformational flexibility plays a critical role in protein function. Herein, we describe the use of time-resolved electrospray ionization mass spectrometry coupled to hydrogen-deuterium exchange for probing the rapid structural changes that drive function in ordered and disordered proteins.

Intrinsically disordered proteins (IDPs) have long been a challenge to structural biologists due to their lack of stable secondary structure elements. ...

Biotinylated Cell-penetrating Peptides to Study Intracellular Protein-protein Interactions

Here we present a protocol to study intracellular protein-protein interactions that is based on the widely used biotin-avidin pull-down system. The modification presented includes the combination of this technique with cell-penetrating sequences. We propose to design cell-penetrating baits that can be incubated with living cells instead of cell lysates and therefore the interactions found will reflect those that occur within the intracellular context. Connexin43 (Cx43), a protein that forms gap junction channels and hemichannels is down-regulated in high-grade gliomas. The Cx43 region comprising amino acids 266-283 is responsible for the inhibition of the oncogenic activity of c-Src in glioma cells. Here we use TAT as the cell-penetrating sequence, biotin as the pull-down tag and the region of Cx43 comprised between amino acids 266-283 as the target to find intracellular interactions in the hard-to-transfect human glioma stem cells. One of the limitations of the proposed method is that the molecule used as bait could fail to fold properly and, consequently, the interactions found could not be associated with the effect. However, this method can be especially interesting for the interactions involved in signal transduction pathways because they are usually carried out by intrinsically disordered regions and, therefore, they do not require an ordered folding. In addition, one of the advantages of the proposed method is that the relevance of each residue on the interaction can be easily studied. This is a modular system; therefore, other cell-penetrating sequences, other tags, and other intracellular targets can be employed. Finally, the scope of this protocol is far beyond protein-protein interaction because this system can be applied to other bioactive cargoes such as RNA sequences, nanoparticles, viruses or any molecule that can be transduced with cell-penetrating sequences and fused to pull-down tags to study their intracellular mechanism of action.

This is a protocol to study intracellular protein-protein interactions based on the biotin-avidin pull-down system with the novelty of combining cell-penetrating sequences. The main advantage is that the target sequence is incubated with living cells instead of cell lysates and therefore the interactions will occur within the cellular context.

Here we present a protocol to study intracellular protein-protein interactions that is based on the widely used biotin-avidin pull-down system. The ...

Analyzing Dynamic Protein Complexes Assembled On and Released From Biolayer Interferometry Biosensor Using Mass Spectrometry and Electron Microscopy

In vivo, proteins are often part of large macromolecular complexes where binding specificity and dynamics ultimately dictate functional outputs. In this work, the pre-endosomal anthrax toxin is assembled and transitioned into the endosomal complex. First, the N-terminal domain of a cysteine mutant lethal factor (LFN) is attached to a biolayer interferometry (BLI) biosensor through disulfide coupling in an optimal orientation, allowing protective antigen (PA) prepore to bind (Kd 1 nM). The optimally oriented LFN-PAprepore complex then binds to soluble capillary morphogenic gene-2 (CMG2) cell surface receptor (Kd 170 pM), resulting in a representative anthrax pre-endosomal complex, stable at pH 7.5. This assembled complex is then subjected to acidification (pH 5.0) representative of the late endosome environment to transition the PAprepore into the membrane inserted pore state. This PApore state results in a weakened binding between the CMG2 receptor and the LFN-PApore and a substantial dissociation of CMG2 from the transition pore. The thio-attachment of LFN to the biosensor surface is easily reversed by dithiothreitol. Reduction on the BLI biosensor surface releases the LFN-PAprepore-CMG2 ternary complex or the acid transitioned LFN-PApore complexes into microliter volumes. Released complexes are then visualized and identified using electron microscopy and mass spectrometry. These experiments demonstrate how to monitor the kinetic assembly/disassembly of specific protein complexes using label-free BLI methodologies and evaluate the structure and identity of these BLI assembled complexes by electron microscopy and mass spectrometry, respectively, using easy-to-replicate sequential procedures.

Here we present a protocol to monitor the assembly and disassembly of the anthrax toxin using biolayer interferometry (BLI). Following assembly/disassembly on the biosensor surface, the large protein complexes are released from the surface for visualization and identification of components of the complexes using electron microscopy and mass spectrometry, respectively.

In vivo, proteins are often part of large macromolecular complexes where binding specificity and dynamics ultimately dictate functional outputs. In this ...

A Fluorescence Fluctuation Spectroscopy Assay of Protein-Protein Interactions at Cell-Cell Contacts

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring cells. Of interest, only few assays are capable of specifically probing such interactions directly in living cells. Here, we present an assay to measure the binding of proteins expressed at the surfaces of neighboring cells, at cell-cell contacts. This assay consists of two steps: mixing of cells expressing the proteins of interest fused to different fluorescent proteins, followed by fluorescence fluctuation spectroscopy measurements at cell-cell contacts using a confocal laser scanning microscope. We demonstrate the feasibility of this assay in a biologically relevant context by measuring the interactions of the amyloid precursor-like protein 1 (APLP1) across cell-cell junctions. We provide detailed protocols on the data acquisition using fluorescence-based techniques (scanning fluorescence cross-correlation spectroscopy, cross-correlation number and brightness analysis) and the required instrument calibrations. Further, we discuss critical steps in the data analysis and how to identify and correct external, spurious signal variations, such as those due to photobleaching or cell movement.
In general, the presented assay is applicable to any homo- or heterotypic protein-protein interaction at cell-cell contacts, between cells of the same or different types and can be implemented on a commercial confocal laser scanning microscope. An important requirement is the stability of the system, which needs to be sufficient to probe diffusive dynamics of the proteins of interest over several minutes.

This protocol describes a fluorescence fluctuation spectroscopy-based approach to investigate interactions among proteins mediating cell-cell interactions, i.e. proteins localized in cell junctions, directly in living cells. We provide detailed guidelines on instrument calibration, data acquisition and analysis, including corrections to possible artefact sources.

A variety of biological processes involves cell-cell interactions, typically mediated by proteins that interact at the interface between neighboring ...

Evaluation of Protein&#8211;Protein Interactions using an On-Membrane Digestion Technique

Numerous intracellular proteins physically interact in accordance with their intracellular and extracellular circumstances. Indeed, cellular functions largely depend on intracellular protein&#8211;protein interactions. Therefore, research regarding these interactions is indispensable to facilitating the understanding of physiologic processes. Co-precipitation of associated proteins, followed by mass spectrometry (MS) analysis, enables the identification of novel protein interactions. In this study, we have provided details of the novel technique of immunoprecipitation-liquid chromatography (LC)-MS/MS analysis combined with on-membrane digestion for the analysis of protein&#8211;protein interactions. This technique is suitable for crude immunoprecipitants and can improve the throughput of proteomic analyses. Tagged recombinant proteins were precipitated using specific antibodies; next, immunoprecipitants blotted onto polyvinylidene difluoride membrane pieces were subjected to reductive alkylation. Following trypsinization, the digested protein residues were analyzed using LC-MS/MS. Using this technique, we were able to identify several candidate associated proteins. Thus, this method is convenient and useful for the characterization of novel protein&#8211;protein interactions.

Here, we present a protocol for an on-membrane digestion technique for the preparation of samples for mass spectrometry. This technique facilitates the convenient analysis of protein&#8211;protein interactions.

Numerous intracellular proteins physically interact in accordance with their intracellular and extracellular circumstances. Indeed, cellular functions ...

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 ...

Characterization of Ternary Complex Formation in PROTACs Using Biophysical Assays

The Development and Application of Biophysical Assays for Evaluating Ternary Complex Formation Induced by Proteolysis Targeting Chimeras (PROTACS)

E3 ligases and proteins targeted for degradation can be induced to form complexes by heterobifunctional molecules in a multi-step process. The kinetics and thermodynamics of the interactions involved contribute to efficiency of ubiquitination and resulting degradation of the protein. Biophysical techniques such as surface plasmon resonance (SPR), biolayer interferometry (BLI), and isothermal titration calorimetry (ITC) provide valuable information that can be used in the optimization of those interactions. Using two model systems, a biophysical assay tool kit for understanding the cooperativity of ternary complex formation and the impact of the &#39;hook effect&#39; on binding kinetics was established. In one case, a proteolysis targeting chimera (PROTAC) molecule that induced ternary complex formation between Brd4BD2 and VHL was evaluated. The heterobifunctional molecule, MZ1, has nM affinities for both the Brd4BD2 protein (SPR KD = 1 nM, ITC KD = 4 nM) and the VHL complex (SPR KD = 29 nM, ITC KD = 66 nM). For this system, robust SPR, BLI, and ITC assays were developed that reproduced published results demonstrating the cooperativity of ternary complex formation. In the other case, a molecule that induced ternary complexes between a 46.0 kDa protein, PPM1D, and cereblon [CRBN (319-442)] was studied. The heterobifunctional molecule, BRD-5110, has an SPR KD = 1 nM for PPM1D but much weaker binding against the truncated CRBN (319-442) complex (SPR KD= ~ 3 &#181;M). In that case, the binding for CRBN in SPR was not saturable, resulting in a &#34;hook-effect&#34;. Throughput and reagent requirements for SPR, BLI, and ITC were evaluated, and general recommendations for their application to PROTAC projects were provided.

Author Spotlight: Evaluating Biophysical Assays for Characterizing PROTACS Ternary Complexes 

Here we describe protocols for the biophysical characterization of ternary complex formation induced by proteolysis targeting chimeras (PROTACS) that involve the ubiquitin ligases Von Hippel-Lindau E3 ligase (VHL) and Cereblon (CRBN). Biophysical methods illustrated herein include surface plasmon resonance (SPR), biolayer interferometry (BLI), and isothermal titration calorimetry (ITC).

E3 ligases and proteins targeted for degradation can be induced to form complexes by heterobifunctional molecules in a multi-step process. The kinetics ...

Predicting Amino Acid Preferences of Protein-Protein Binding Interfaces

Computational Prediction of Amino Acid Preferences of Potentially Multispecific Peptide-Binding Domains Involved in Protein-Protein Interactions

Many protein-protein interactions involve the binding of short protein segments to peptide-binding domains. Usually, such interactions require the recognition of linear motifs with variable conservation. The combination of highly conserved and more variable regions in the same ligands often contributes to the multispecificity of binding, a common property of enzymes and cell signaling proteins. Characterization of amino acid preferences of peptide-binding domains is important for the design of mediators of protein-protein interactions (PPIs). Computational methods are an efficient alternative to the often costly and cumbersome experimental techniques, enabling the design of potential mediators that can be later validated in downstream experiments. Here, we described a methodology using the Pepspec application of the Rosetta molecular modeling package to predict the amino acid preferences of peptide-binding domains. This methodology is useful when the structure of the receptor protein and the nature of the peptide ligand are both known or can be inferred. The methodology starts with a well-characterized anchor from the ligand, which is extended by randomly adding amino acid residues. The binding affinity of peptides generated this way is then evaluated by flexible-backbone peptide docking in order to select the peptides with the best predicted binding scores. These peptides are then used to calculate amino acid preferences and to optionally compute a position-weight matrix (PWM) that can be used in further studies. To illustrate the application of this methodology, we used the interaction between subunits of human interferon regulatory factor 5 (IRF5), previously known to be multispecific but globally guided by a short conserved motif called pLxIS. The estimated amino acid preferences were consistent with previous knowledge about the IRF5 binding surface. Positions occupied by phosphorylatable serine residues exhibited a high frequency of aspartate and glutamate, likely because their negatively charged side chains are similar to phosphoserine.

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

We describe a methodology based on sequence diversification to estimate the amino acid preferences of multispecific binding sites in protein-protein interactions (PPIs). In this strategy, thousands of potential peptide ligands are generated and screened in silico, thus overcoming some limitations of available experimental methods.