An Assay for Quantifying Protein-RNA Binding in Bacteria

Summary

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.

Abstract

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.

Introduction

RNA binding protein (RBP)-based post-transcriptional regulation, specifically characterization of the interaction between RBPs and RNA, has been studied extensively in recent decades. There are multiple examples of translational down-regulation in bacteria originating from RBPs inhibiting, or directly competing with, ribosome binding^1,2,3. In the field of synthetic biology, RBP-RNA interactions are emerging as a significant tool for the design of transcription-based genetic circuits^4,5. Therefore, there is an increase in demand for characterization of such RBP-RNA interactions in a cellular context.

The most common methods for studying protein-RNA interactions are the electrophoretic mobility shift assay (EMSA)⁶, which is limited to in vitro settings, and various pull-down assays⁷, including the CLIP method^8,9. While such methods enable the discovery of de novo RNA binding sites, they suffer from drawbacks such as labor-intensive protocols and expensive deep sequencing reactions and may require a specific antibody for RBP pull-down. Due to the susceptible nature of RNA to its environment, many factors can affect RBP-RNA interactions, emphasizing the importance of interrogating RBP-RNA binding in the cellular context. For example, we and others have demonstrated significant differences between RNA structures in vivo and in vitro^10,11.

Based on the approach of a previous study¹², we recently demonstrated¹⁰ that when placing pre-designed binding sites for the capsid RBPs from the bacteriophages GA¹³, MS2¹⁴, PP7¹⁵, and Qβ¹⁶ in the translation initiation region of a reporter mRNA, reporter expression is strongly repressed. We present a relatively simple and quantitative method, based on this repression phenomenon, to measure the affinity between RBPs and their corresponding RNA binding sites in vivo.

Protocol

1. System Preparation

1. Design of binding-site plasmids
   1. Design the binding site cassette as depicted in Figure 1. Each minigene contains the following parts (5' to 3'): Eagl restriction site, ∼40 bases of the 5' end of the kanamycin (Kan) resistance gene, pLac-Ara promoter, ribosome binding site (RBS), AUG of the mCherry gene, a spacer (δ), an RBP binding site, 80 bases of the 5' end of the mCherry gene, and an ApaLI restriction site.
      NOTE: To increase the success rate of the assay, design three binding-site cassettes for each binding site, with spacers consisting of at least one, two, and three bases. See Representative Results section for further guidelines.
2. Cloning of binding site plasmids
   1. Order the binding-site cassettes as double-stranded DNA (dsDNA) minigenes. Each minigene is ∼500 bp long and contains an Eagl restriction site and an ApaLI restriction site at the 5' and 3' ends, respectively (see step 1.1.1).
      NOTE: In this experiment, mini-genes with half of the kanamycin gene were ordered to facilitate screening for positive colonies. However, Gibson assembly¹⁷ is also suitable here, in which case the binding site can be ordered as two shorter complementary single-stranded DNA oligos.
   2. Double-digest both the mini-genes and the target vector with Eagl-HF and ApaLI by the restriction protocol¹⁸, and column purify¹⁹.
   3. Ligate the digested minigenes to the binding-site backbone containing the rest of the mCherry reporter gene, terminator, and a kanamycin resistance gene²⁰.
   4. Transform the ligation solution into Escherichia coli TOP10 cells²¹.
   5. Identify positive transformants via Sanger sequencing.
      1. Design a primer 100 bases upstream to the region of interest (see Table 1 for primer sequences).
      2. Miniprep a few bacterial colonies²².
      3. Prepare 5 µL of a 5 mM solution of the primer and 10 µL of the DNA at 80 ng/µL concentration.
      4. Send the two solution to a convenient facility for Sanger sequencing²³.
   6. Store purified plasmids at -20 °C, and bacterial strains as glycerol stocks²⁴, both in the 96-well format. DNA will then be used for transformation into E. coli TOP10 cells containing one of four fusion-RBP plasmids (see step 1.3.5).
3. Design and construction of the RBP plasmid
   NOTE: Amino acid and nucleotide sequences of the coat proteins used in this study are listed in Table 2.
   1. Order the required RBP sequence lacking a stop codon as a custom-ordered dsDNA minigene lacking a stop codon with restriction sites at the ends (Figure 1).
   2. Clone the tested RBP lacking a stop codon immediately downstream of an inducible promoter and upstream of a fluorescent protein lacking a start codon (Figure 1), similar to steps 1.2.2-1.2.4. Make sure that the RBP plasmid contains a different antibiotic resistance gene than the binding-site plasmid.
   3. Identify positive transformants via Sanger sequencing, similar to step 1.2.5 (see Table 1 for primer sequences).
   4. Choose one positive transformant and make it chemically-competent²⁵. Store as glycerol purified plasmids at -20 °C and glycerol stocks of bacterial strains²⁴ at -80 °C in 96-well plates.
   5. Transform the binding-site plasmids (from step 1.2.6) stored in 96-well plates into chemically-competent bacterial cells already containing an RBP-mCerulean plasmid²¹. To save time, instead of plating the cells on Petri dishes, plate them using an 8-channel pipettor on 8-lane plates containing Luria-Bertani (LB)²⁶ agar with relevant antibiotics (Kan and Amp). Colonies should appear in 16 h.
   6. Select a single colony for each double transformant and grow overnight in LB medium with the relevant antibiotics (Kan and Amp) and store as glycerol stocks²⁴ at -80 °C in 96-well plates.

2. Experiment Setup

NOTE: The protocol presented here was performed using a liquid-handling robotic system in combination with an incubator and a plate reader. Each measurement was carried out for 24 inducer concentrations, with two duplicates for each strain + inducer combination. Using this robotic system, data for 16 strains per day with 24 inducer concentrations was collected. However, if such a device is unavailable, or if fewer experiments are necessary, these can easily be done by hand using an 8-channel multi-pipette and adapting the protocol accordingly. For example, preliminary results for four strains per day with 12 inducer concentrations and four time-points were acquired in this manner.

1. Prepare, in advance, 1 L of bioassay buffer (BA) by mixing 0.5 g of tryptone, 0.3 mL of glycerol, 5.8 g of NaCl, 50 mL of 1 M MgSO₄, 1 mL of 10x phosphate-buffered saline (PBS) buffer pH 7.4, and 950 mL of double distilled water (DDW). Autoclave or sterile filter the BA buffer.
2. Grow the double-transformant strains at 37 °C and 250 rpm shaking in 1.5 mL LB with appropriate antibiotics (kanamycin at a final concentration of 25 μg/mL and ampicillin at a final concentration of 100 μg/mL), in 48-well plates, over a period of 18 h (overnight).
3. In the morning, make the following preparations.
   1. Inducer plate. In a clean 96-well plate, prepare wells with semi-poor medium (SPM) consisting of 95% BA and 5% LB²⁶ in the incubator at 37 °C. The number of wells corresponds to the desired number of inducer concentrations. Add C4-HSL to the wells in the inducer plate that will contain the highest inducer concentration (218 nM).
   2. Program the robot to serially dilute medium from each of the highest-concentration wells into 23 lower concentrations ranging from 0 to 218 nM. The volume of each inducer dilution should be sufficient for all strains (including duplicates).
   3. While the inducer dilutions are being prepared, warm 180 μL of SPM in the incubator at 37 °C, in 96-well plates.
   4. Dilute the overnight strains from step 2.2 by a factor of 100 by serial dilutions: first dilute by a factor of 10 by mixing 100 μL of bacteria with 900 μL of SPM in 48-well plates, and then dilute again by a factor of 10 by taking 20 μL from the diluted solution into 180 μL of pre-warmed SPM, in 96-well plates suitable for fluorescent measurements.
   5. Add the diluted inducer from the inducer plate to the 96-well plates with the diluted strains according to the final concentrations.
4. Shake the 96-well plates at 37 °C for 6 h, while taking measurements of optical density at 595 nm (OD₅₉₅), mCherry (560 nm/612 nm) and mCerulean (460 nm/510 nm) fluorescence via a plate reader every 30 min. For normalization purposes, measure growth of SMP with no cells added.

3. Preliminary Results Analysis

1. For each day of experiment, choose a time interval of logarithmic growth according to the measured growth curves, between the linear growth phase and the stationary (T­₀, T_final). Take approximately 6−8 time points, while discarding the first and last measurements to avoid error derived from inaccuracy of exponential growth detection (see Figure 2A, top panel).
   NOTE: Discard strains that show abnormal growth curves or strains where logarithmic growth phase could not be detected and repeat the experiment.
2. Calculate the average normalized fluorescence of mCerulean and rate of production of mCherry, from the raw data of both mCerulean and mCherry fluorescence for each inducer concentration (Figure 2A).
   1. Calculate normalized mCerulean as follows:
      
      ​where blank(mCerulean) is the mCerulean level [a.u.] for medium only, blank(OD) is the optical density for medium only, and mCerulean and OD are the mCerulean fluorescence and optical density values, respectively.
   2. Average mCerulean over the different time points (Figure 2B, top two panels) as follows:
      
      ​where #Time points is the number of data timepoints taken into account, T₀ is the time at which the exponential growth phase begins, and T_final is the time at which the exponential growth phase ends.
   3. Calculate mCherry rate of production (Figure 2B, bottom two panels) as follows:
      
      where mCherry(t) is the mCherry level [a.u.] at time t, OD is the optical density value, T₀ is the time at which the exponential growth phase begins, and T_final is the time at which the exponential growth phase ends.
3. Finally, plot the mCherry rate of production as a function of mCerulean, creating dose response curves as a function of RBP-mCerulean fusion fluorescence (Figure 2C). Such plots represent production of the reporter gene as a function of RBP presence in the cell.

4. Dose Response Function Fitting Routine and K_RBP Extraction

1. Under the assumption that the ribosome rate of translation with the RBP bound is constant, model the mCherry production rate as follows (see Figure 2D, green line):
   
   where [x] is the normalized average mCerulean fluorescence calculated according to Eq. 2, mCherry production rate is the value calculated according to Eq. 3, K_RBP is the relative binding affinity [a.u.], K_unbound is the ribosome rate of translation with the RBP unbound, n is the cooperativity factor, and C is the base fluorescence [a.u.]. C, n, K_unbound, and K_RBP are found by fitting the mCherry production rate data to the model (Eq. 4).
2. Using data analysis software, conduct a fitting procedure on plots depicting mCherry production rate as a function of averaged mCerulean (step 3.3), and extract the fit parameters according to the formula in Eq. 4.
   NOTE: Only fitting results with R² > 0.6 are taken into account. For those fits, K_RBP error is mostly in the range of 0.5% to 20% of K_RBP values, for a 0.67 confidence interval, while those with higher K_RBP error can be also verified by eye.
3. Normalize K_RBP values by the respective maximal value of averaged mCerulean for each dose-response function.
   
   where K_RBP in [a.u.] is the value extracted from the fitting procedure in Eq. 4, and max (averaged mCerulean) is the maximal averaged mCerulean signal [a.u] observed for the current strain.
   NOTE: The normalization facilitates correct comparison of the regulatory effect across strains by eliminating the dependence on the particular maximal RBP expression levels.

Results

The presented method utilizes the competition between an RBP and the ribosome for binding to the mRNA molecule (Figure 1). This competition is reflected by decreasing mCherry levels as a function of increased production of RBP-mCerulean, due to increasing concentrations of inducer. In the case of increasing mCerulean fluorescence, with no significant changes in mCherry, a lack of RBP binding is deduced. Representative results for both a positive and a negativ...

Discussion

The method described in this article facilitates quantitative in vivo measurement of RBP-RNA binding affinity in E. coli cells. The protocol is relatively easy and can be conducted without the use of sophisticated machinery, and data analysis is straightforward. Moreover, the results are produced immediately, without the relatively long wait-time associated with next generation sequencing (NGS) results.

One limitation to this method is that it works only in bacterial cells. However, a...

Materials

Name	Company	Catalog Number	Comments
Ampicillin sodium salt	SIGMA	A9518
Magnesium sulfate (MgSO4)	ALFA AESAR	33337
48 plates	Axygen	P-5ML-48-C-S
8- lane plates	Axygen	RESMW8I
96-well plates	Axygen	P-DW-20-C
96-well plates for plate reader	Perkin Elmer	6005029
ApaLI	NEB	R0507
Binding site sequences	Gen9 Inc. and Twist Bioscience		see Table 1
E. coli TOP10 cells	Invitrogen	C404006
Eagl-HF	NEB	R3505
glycerol	BIO LAB	071205
incubator	TECAN	liconic incubator
Kanamycin solfate	SIGMA	K4000
KpnI- HF	NEB	R0142
ligase	NEB	B0202S
liquid-handling robotic system	TECAN	EVO 100, MCA 96-channel
Matlab analysis software	Mathworks
multi- pipette 8 lanes	Axygen	BR703710
N-butanoyl-L-homoserine lactone (C4-HSL)	cayman	K40982552 019
PBS buffer	Biological Industries	020235A
platereader	TECAN	Infinite F200 PRO
Q5 HotStart Polymerase	NEB	M0493
RBP seqeunces	Addgene	27121 & 40650	see Table 2
SODIUM CHLORIDE (NaCL)	BIO LAB	190305
SV Gel and PCR Clean-Up System	Promega	A9281
Tryptone	BD	211705