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.
A transcription factor (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 σ factors, namely σ66 and σ28, 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.
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 σ 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, σ 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 σ factors, namely σ66, σ28 and σ54. σ66, which is equivalent to the housekeeping σ70 of E. coli and other bacteria, is responsible for recognizing promoters of early and mid-cycle genes as well as some late genes, whereas σ28 and σ54 are required for the transcription of certain late genes. Several genes are known to carry both a σ66-dependent promoter and a σ28-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 σ66-dependent genes14. Affinity pulldown assays have demonstrated that GrgA activates their transcription by binding both σ66 and DNA. Interestingly, it was later found with that GrgA also co-precipitates with σ28, and activates transcription from σ28-dependent promoters in vitro15. To investigate whether GrgA has similar or different affinities for σ66 and σ28, we resorted to using BLI. BLI assays have shown that GrgA interacts with σ66 at a 30-fold higher affinity than with σ28, suggesting that GrgA may play differential roles in σ66-dependent transcription and σ28-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 σ28-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.
1. Preparation of proteins
2. Biosensor hydration and assay set-up
3. Loading of ligand onto biosensor
4. Washing away additional ligand
5. Association of analyte to ligand
6. Dissociation of analyte from ligand
7. Repeating interactions with different concentrations
8. Analyzing the data using the software
Through BLI assays, we previously established that binding of GrgA to σ28 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-GrgAΔ138-165) 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 region directly binds σ28 in the absence of the rest of the GrgA protein. In these experiments, the middle region tagged with an N-terminally His-tag (NH-GrgA138-165) was used as the ligand, which was first immobilized to the tip of a Ni-NTA biosensor (Figure 1A). After washing unbound NH-GrgA138-165 off the biosensor, real-time association with the analyte σ28 was recorded following the addition of σ28. Finally, the real-time dissociation was recorded following the wash. Recordings of experiments with three different analyte concentrations starting 30 s prior to ligand binding and ending 2 minutes after the beginning of wash are shown in Figure 1A. To better visualize the ligand-analyte interaction, we remove data prior to the addition of the ligand and reset the baseline to 0 to derive Figure 1B.
Values of kinetic parameters for interaction of the NH-GrgA138-165 fragment with σ28 are presented in Table 1. Compared to the NH-GrgA X σ28 interaction, the NH-GrgA138-165 X σ28 interaction displayed a trending statistically significant 60% reduction in ka, a highly statistically significant 64% increase in kd, and a highly statistically significant 3.5-fold increase in KD. These changes demonstrate that compared to NH-GrgA, NH-GrgA138-165 binds σ28 more slowly, dissociates from σ28 faster, and has a decreased overall affinity with σ28. Therefore, residues 138-165 in GrgA binds σ28 but with reduced affinity compared to full length GrgA.
Figure 1: A 28 amino acid middle region of GrgA binds σ28 in vitro.
(A) Real-time changes in light interference patterns recorded by in four stages: (i) binding of NH-GrgA138-165 (Ligand) to a Ni-NTA biosensor, (ii) wash, (iii) binding of NS-σ28 (Analyte) at different concentrations to the immobilized NH-GrgA-138-165 (Ligand), and (iv) subsequent wash. (B) Enhanced visualization of ligand-analyte association and dissociation following removal of values in the first two stages from (A) and reset of the baseline. Panel B is modified from Desai et al., 201815. Please click here to view a larger version of this figure.
Ligand | n | ka | kd | KD | Referanslar | |||||||||||
1/Ms | % control | 1/s | % control | M | % control | |||||||||||
NH-GrgA | 8 | (1.5 ± 1.7) x 104 | 100 | (2.8 ± 0.8) x 10-3 | 100 | (2.2 ± 0.3) x 10-7 | 100 | Desai et al, 2018 | ||||||||
NH-GrgAΔ138-165 | 2 | (5.6 ± 0.1) x 103 | 37 | (4.1 ± 0.3) x 102 | 1.5 x 107 | (6.9 ± 4.5) x 10-2 | 3.1 x 108 | Desai et al, 2018 | ||||||||
p=0.125 | p<0.002 | p<0.001 | ||||||||||||||
NH-GrgA138-165 | 3 | (6.0 ± 1.0) x 103 | 40 | (4.6 ± 0.4) x 10-3 | 164 | (7.7 ± 0.3) x 10-7 | 350 | This study | ||||||||
p=0.074 | p=0.006 | p<0.001 |
Table 1: A mutant of GrgA, containing only amino acid residues 138-165, binds σ28 despite lower affinity compared to the full-length GrgA.
BLI assays were performed with Ni-NTA biosensors using His-tagged full-length GrgA or deletion mutants as ligands and purified Strep-tagged σ28 as an analyte. Graphs of recordings are shown in Figure 1. Values of kinetic parameters (averages ± standard deviations) were generated with the associated software17. ka (association rate constant) is defined as the number of complexes formed per s in a 1 molar solution of A and B. kd (dissociation rate constant) is defined as the number of complexes that decay per second. KD (dissociation equilibrium constant), defined as the concentration at which 50% of ligand binding sites are occupied by the analytes, is kd divided by ka. n, number of experimental repeats. p values were calculated using 2-tailed Student’s t tests. Kinetic parameters for NH-GrgA and NH-GrgAΔ138-165 were from Desai et al., 201815.
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.
Compared to pulldown assays, BLI assays offer higher sensitivity. For example, GrgA-σ28 interactions are detected with lower nM concentrations of analytes by BLI but not by pulldown assays (unpublished data). Unlike pulldown, BLI does not rely on a detection antibody, which may significantly affect sensitivity.
More importantly, BLI analyses can provide mechanistic insights into the interaction between proteins, whereas pulldown assays cannot. This is exemplified by the interactions of σ28 with different GrgA constructs. Compared with NH-GrgA, NH-GrgAΔ138-165 and NH-GrgA138-165 suffer only a 60% loss in ka in binding σ28. These findings are consistent with our previous BLI data showing that GrgA lacking its N-terminal 64 residues has a decreased affinity with σ28, suggesting that the N-terminal sequence of GrgA contributes to σ28 binding. Although NH-GrgAΔ138-165 and NH-GrgA138-165 have similar ka values in binding σ28, the former has a 91,000-fold higher kd than the latter. These results indicate that binding of 138-165 triggers structural changes in GrgA, greatly stabilizing the complex.
With a longer history than BLI, surface plasmon resonance (SPR) can also quantify the real-time protein-protein interactions18,19. While the sensitivity of BLI is thought to be lower than that of SPR20, the former currently outperforms the latter in cost-effectiveness. For example, costs of SPR biosensors are much higher than those of BLI biosensors.
Due to the nature of the underlying principle of SPR, it is heavily influenced by the microfluidics of the media surrounding the protein. Therefore, experiments involving some SPR instruments require considerable perception on the part of the researcher to ensure optimal buffer conditions21,22,23,24. On the other hand, current BLI instruments feature a very limited temperature control range25 and, as such, are ill-fitted for determining thermodynamic parameters (such as enthalpy and Gibbs free energy) for a given interaction.
Glycerol, a commonly used cryoprotectant, is incompatible with BLI, despite its broad chemical compatibility. Therefore, it is critical to remove glycerol from the ligand and analyte by dialysis. The resulting glycerol-free proteins must be stored at 4 °C, which may lead to increased instability and inaccurate kinetic parameters. We recommend that BLI assays be performed soon after dialysis, particularly if inconsistent kinetic parameters are obtained from at different times. The exact time frame within which BLI assays should be completed will vary among proteins and be affected by their concentrations.
As with SPR, BLI has been used for small molecule screening26. Considering that newer BLI instruments offer high throughput options for screening, we envision that BLI can become very useful for the identification and characterization of small molecules that facilitate or interfere with protein-protein interactions.
The authors have nothing to disclose.
This work was supported by National Institutes of Health (Grants # AI122034 and AI140167) and New Jersey Health Foundation (Grant # PC 20-18).
BLItz machine | ForteBio | 45-5000 | |
Dialysis tubing cellulose membrane | MilliporeSigma | D9652 | |
Dip and Read Ni-NTA biosensor tray | ForteBio | 18-5101 | Ready-to-use Ni-NTA biosensors for poly-His-tagged Proteins |
Drop holder | ForteBio | 45-5004 | |
PCR tubes (0.2 mL) | Thomas Scientific | CLS6571 | |
Microcentrifuge tubes (black) | Thermo Fisher Scientific | 03-391-166 | |
Kimwipes | Thermo Fisher Scientific | 06-666A | |
DTT | Thermo Fisher Scientific | R0861 | |
EDTA | MilliporeSigma | E6758 | |
MgCl2 | MilliporeSigma | M8266 | |
NaCl | MilliporeSigma | S9888 | |
Tris-HCl | GoldBio | T095100 |