RCA

Rolling Circle Amplification

RCA

Overview
RCA Design
RCA Experimentation
Statistical Analysis
References

Overview

Our project for the 2022 iGEM competition provides a point of care (POC) diagnostic tool for coronary artery disease (CAD) using circulating miRNA in blood as biomarkers.

Problem

In the United States, 1 in 5 deaths are due to cardiovascular disease (Centers for Disease Control, 2022). One of the most common heart diseases is coronary artery disease (CAD), accounting for 17.8 million annual deaths worldwide (World Health Organization, 2022). CAD is especially prevalent in the Southeastern United States, our iGEM team’s home region. In order to address this issue, we have developed a point-of-care (POC) diagnostic tool to detect and quantify microRNA (miRNA) by utilizing rolling circle amplification/transcription from a rolling circle product. This product is created by continuous transcription of the designed padlock probe to create long repeats containing complementary sequences to the miRNAs and the reporting mechanism. The reporting mechanisms emit fluorescence from the repeating product, which can then be quantified by a frugal device, MicroQ. In addition to other existing screening methods, this technique can aid healthcare professionals in the diagnosis of disease as results rely on the interpretation and laboratory work best suited to healthcare facilities. Moreover, this year’s team hoped to alleviate the high costs associated with current early diagnostic measures and provide an additional screening tool for physicians.

Methodology

Lambert iGEM identified two specific miRNAs — miRNA 1 and miRNA 133a— found to be upregulated in the correlation to CAD (Kaur et al., 2020). The proposed method aims to detect a certain threshold of these miRNAs to provide an early indication of CAD. We considered several methods to detect and quantify miRNA including toehold switches, RT-qPCR, padlock probes and SHERLOCK systems, summarized in Figure 1. However, consultations with experts in their field such as Dr. Koob (an expert in SHERLOCK) and further analysis on the protocols for each methodology revealed that the use of padlock probes would be best suited in detecting miRNAs. The short sequence of each miRNA and repeating nucleotides made them difficult to quantify and interfered with hybridization. Ultimately, we chose Rolling Circle Amplification (RCA) and Rolling Circle Transcription (RCT) due to the ability of padlock probes to detect the short sequences of miRNA and discriminate between different miRNAs with single-nucleotide selectivity. Through RCA/RCT and the respective reporting mechanisms, the miRNAs present in blood serum can eventually be detected and quantified.

Other Methods

Lambert iGEM chose the rolling circle methods instead of other methods due to their precision and easily quantifiable results (see Fig. 1). These include:

Figure 1. Table of current methods. (Forero et al., 2019; Koscianska et al., 2011; Li et al., 2009; Schwarzkopf et al., 2016; Shi et al., 2012; Song et al., 2010; Ouyang et al., 2019; Ye et al., 2019; Zheng et al., 2016).

Padlocks

Both rolling circle methods include padlock probes as part of their methodology. A padlock probe, which can be 30-150 nucleotides in length, is a single-stranded DNA (ssDNA) sequence designed to recognize a specific target sequence (see Fig. 2). The “arms” of a padlock probe are the ends of the ssDNA that are complementary to a specific target sequence (see Fig. 2). The middle sequence (the sequence between the arms) can be specifically designed to perform a function once amplified.

Figure 2. Diagram of a padlock probe.

Ligation

Some steps that are shared between RCA and RCT are the beginnings of hybridization and ligation. Hybridization is when the miRNA and the DNA attach, bringing the padlock arms close together. After hybridization, ligation occurs in which SplintR Ligase circularizes the miRNA. From here, RCT and RCA diverge.

SplintR Modification

Our team modified the protocols from the original paper used in their initial development. Instead of using T4 DNA ligase, we used SplintR Ligase since SplintR only ligates near RNA-DNA hybridization (Avantor Staff). As seen in Figure 3, SplintR works by utilizing the phosphate modification on the 5' arm and ATP to ligate the DNA strand.

Figure 3. Animation of SplintR Ligase Function.

Padlock Design

For the padlock probe (PLP) design, part of the reverse complement of the miRNA makes up each end of the padlock probe. To determine where the reverse complement is split properly, we determined the annealing temperatures of each arm through SnapGene. To allow successful hybridization and maximize the binding efficiency of the miRNA and the padlock arms, the arms need to have the same annealing temperature. Furthermore, we added a phosphate group modification to the 5’ end of the padlock sequence to allow ligation by SplintR ligase (Jonstrup et al., 2006).

Figure 4. Padlock probe arrangement and formation.

Additionally, the alignment of the 5’ and 3’ ends is essential to determine where each part of the padlock + arms matches up to the target miRNA (Liu et al., 2013). The miRNA strand hybridizes antiparallel to the padlock arms (see Fig. 4). Therefore, the 5’ end of the miRNA will end up overlapping the 5’ PLP arm, and the 3’ end of the miRNA will end up overlapping the 3’ PLP arm (Liu et al., 2013).

The following are the steps for generating a padlock probe by hand. Researchers will need a software tool that displays melting temperatures of sequences such as the sequence generator SnapGene.

  1. Paste your target biomarker in your software of choice.
  2. Take the reverse complementary sequence of your target biomarker.
  3. Split the sequence in half and put the second half in front of the first half to get the padlock arms.
  4. Insert the desired reporter sequence in between the two arms.
  5. Calculate the annealing temperature of both arms and move nucleotides one at a time from one end of an arm to the other end of the other arm until the difference between the annealing temperatures of the two arms is lowest.

Introduction to RCA/RCT

To optimize the miRNA point-of-care diagnostic tool, the team chose to experiment with both RCT (Rolling Circle Transcription) and RCA (Rolling Circle Amplification) to test their efficacy. Because they both use a similar approach, they share some of the same steps, including hybridization and ligation (Mohsen & Kool, 2016). The divergence in steps lies in the reporting mechanism where RCA utilizes fluorophore and quencher tagged linear DNA probes whereas RCT utilizes a broccoli aptamer (BBa_K3380153) (Filonov et al., 2014). Comparatively, the cost difference between using a linear DNA probe or an aptamer is negligible, and RCT and RCA provide straightforward outputs, making point-of-care diagnostics simple in both cases.

Overall, the rolling circle approach, with either RCT or RCA, provides great specificity for miRNA detection as it recognizes small nucleotide sequences and differences between types of miRNAs, as compared to SHERLOCK, toehold switches, and microarray analysis.

Therefore, the benefits of using one approach over the other are minimal, as both provide adequate approaches of measurement. However, researchers discovered RCT more recently than RCA, and less research exists on RCT’s usage for miRNA detection. As a result, we continued with RCT and RCA to test any differences between the two methods and their effectiveness in miRNA detection.

After experimentation, we have found that RCT was not successful in our lab. However, RCA has proved to create results that we can actually correlate to miRNA concentration. The predicted model made by our mathematical modeling team and the experimental curve tested by our RCA team matched up which proves that our biosensor mechanism does infact quantify miRNA.

RCA Design

RCA Process

Our biosensor design for RCA (Rolling Circle Amplification) utilizes rolling circle amplification and padlock probes. By using miRNAs as the target sequence, the miRNA and padlock probe arms form a DNA-RNA hybridization, allowing the arms to be brought closer together (Jonstrup et al., 2006) (see Fig. 5). SplintR ligase is then used to circularize the padlock probe (Jonstrup et al., 2006; Fang et al., 2021) (see Fig. 5). After ligation, phi29 DNA polymerase is added, which uses the miRNA hybridized to the padlock arms as a primer to initiate and perform amplification (Jonstrup et al., 2006; Fang et al., 2021) (see Fig. 5). The RCA product (RCP) will contain interspaced repeats of the middle sequence. Additionally, our reporter mechanism includes the use of linear DNA probes or the split DNA fluorescent aptamer lettuce.

By varying the concentration of the miRNA used to circularize the padlock, Lambert iGEM aims to correlate the fluorescence output to specific concentrations of miRNA, with the goal of quantifying miRNA levels in human blood serum.

Detection Mechanism (Linear Probes)

To report and quantify the presence and concentration of target miRNA in the sample, Lambert iGEM decided to utilize fluorophore and quencher-tagged linear DNA probes. Each probe contains part of the complement to the middle sequence of the RCP. One probe is tagged with a fluorophore, and one probe is tagged with a quencher.

Figure 6. Animation of the process of linear probes reporter mechanism with RCP.

Once the quencher-and fluorophore-tagged linear probes bind to the RCP, the quencher quenches the fluorophore, effectively shutting off the fluorescent signal (see Fig. 6). This fluorescence “shut-off” is the result of a fluorescence resonance energy transfer (FRET) reaction occurring (Zhou et al., 2015). FRET is a distance-dependent process, where non-radiative energy is transferred from the excited fluorophore to the quencher (Sekar & Periasamy, 2003). From here, the decrease in fluorescence in the solution can be correlated with a specific concentration of miRNA through further characterization. Changes in fluorescence will be measured using a plate reader in experimentation: the emission spectrum of FAM-DNA is 480 nm in wavelength, while the excitation spectrum is 528 nm in wavelength (Zhou et al., 2015). The plate reader, which is programmed to the above wavelengths, was then used to read the fluorescence of the reaction.

Detection Mechanism (Lettuce)

Lambert iGEM decided to test a split lettuce detection mechanism in conjunction with the use of quencher and fluorophore tagged DNA probes to ensure that we can provide a variety of methods to quanitfy our RCP. DNA aptamers are a recently discovered novel detection mechanism (VarnBuhler et al., 2022).

Figure 7. Diagram of the split lettuce mechanism (VarnBuhler et al., 2022).

Lettuce is a DNA fluorescent aptamer that binds the dye DFHBI-1T within the aptamer’s secondary structure, thus causing the dye to fluoresce (VarnBuhler et al., 2022) (see Fig. 7). The split Lettuce design includes two halves of the Lettuce aptamer and their flanking sequences. By binding the left and right sequences to the RCP, we can detect and quantify the RCP (see Fig. 7) (VarnBuhler et al., 2022).

The left flanking sequence will bind to the first half of the middle sequence of the RCP, and the right flanking sequence will bind to the second half of the middle sequence (see Fig. 7). After the RCA reactions, we added the split Lettuce sequences and the DFHBI-1T dye to the RCP. Therefore, the resulting fluorescence data should correlate to the concentration of RCP, which correlates to the concentration of miRNA detected by the reaction. With an increase in miRNA concentration, there should be an increase in fluorescence.

Figure 8. Animation of the process of split lettuce reporter mechanism with RCP.

RCA Experimentation

Experimentation with SYBR™ Safe

Our team ran the first round of experimentation to determine the success of our miRNA-1 biosensor in an in vitro reaction. Our goal was to determine the success of the ligation and rolling circle amplification. Instead of using a molecular beacon-based reporting mechanism, we utilized a SYBR™ Safe -based fluorescence readout to limit our reaction to the ligation and RCA steps.

The procedures for the preliminary experimentation consist of the hybridization, the ligation with Splint R ligase, and the RCA reaction with phi29 polymerase, all run in triplicates (see Experiments:SYBR™ Safe ).

Additionally, we ran three triplicates of controls: the first with the padlock probes, second with the miRNA, and the last with both the padlock and the miRNA. To analyze the results, we added SYBR™ Safe to all the samples and read the results in a plate reader.

We found one sample that showed some improvement over our controls. The plate reader’s readout from sample A6’s readout was 9899.64 which showed a significant increase from our third control which averaged 103.39. These results conveyed that either our padlock likely did not produce a successful RCP, or the SYBR™ Safe detection mechanism did not succeed.

Gel Experimentation

After our first round of experimentation, we could not successfully detect a long strand of DNA. Therefore, we decided to run our RCP (rolling circle product) on a gel in order to determine if our output is a very long DNA strand. Our protocols mostly remained the same with the exception of the reporter mechanism (see Experiments: Gel Experimentation ).

By analyzing the results on the gel, our team concluded that a very long strand of DNA, likely the RCP, was produced. The gel exhibited a fluorescent band of DNA very close to the well, which indicates that a long strand of DNA, greater than 1 kB, was produced due to our reaction. As a result, we can infer that the RCA reaction allowed the creation of a really long DNA stand— our RCP (see Fig. 9).

Figure 9. Image of gel with RCA reactions and controls.

Detection Limit

In blood, there are extremely low amounts of miRNA, reaching femtomolar concentrations in certain conditions. Since our team sought to detect miRNA in small concentrations of blood, the miRNA concentration would likely have been at the lower end of the limit. Therefore, our team continued to experiment with lower concentrations of miRNA to confirm that our biosensor could, in fact, reach these numbers.

The following concentrations of miRNA were used to determine the lower detection limit (link to experimentation), and all of these concentrations were ran with the gel experimentation protocols (see Experiments: Detection Limit ).

Our team ran RCA using the same protocols that were used in the gel experimentation. The only variation was the amount of water, which was adjusted to keep the reaction volume constant. We ran a gel with the RCP that contained the smallest concentration of miRNA (0.0408 pM). Our results showed a clear band close to the gel well; as a result, we can infer that all of the RCA reactions allowed the creation of a really long DNA stand—our RCP (see Fig. 10).

Figure 10. Image of an agarose gel run with RCP from RCA run with 0.0408 pM of miRNA-1 in reaction. Controls contain the same concentrations of padlock probe and miRNA-1, without the RCA reaction.

Linear Probes with Complement

We initially tested linear probes with the complement of the middle sequence to ensure that linear probes were an effective and characterizable means of quantifying miRNA. We followed the experimentation protocol on the experimentation page, linked here. (see Experiments: Linear Probes with Complement ).

Figure 11. displays a significant decrease in the fluorescence intensity of a triplicate with FAM Probe, BHQ Probe, and Linear Probe Complement as compared to a triplicate of just FAM tagged Probes. Therefore, we concluded that linear probes were an efficient means of reporting the output of our biosensor.
Figure 12. Characterization curve for parts BBa_K4245130 and BBa_K4245132 showing a negative logarithmic relationship between RFU and complement concentrations ranging from 0.1-100 μM. Note: 0-0.1 μM shows positive relationship, but large error bars at 0 μM suggest this was due to faulty pipetting.
Figure 13. Deterministic ODE Model Simulation of RFU output dependent on concentration of linear DNA probe complement concentration.

In order to quantify the relationship between linear probe complement concentration and fluorescence, we further characterized these parts with varying linear probe complement concentrations. There is a negative logarithmic correlation between the complement concentrations ranging from 0.1-100 mM and the relative fluorescence units (RFU) (see Fig. 12). The 0 mM complement concentration outputs less RFU than 0.1 mM, which does not align with the model. However, the large error bars at 0 mM suggests that there was some degree of significant error. Thus, this data point is insignificant and further trials should be performed to achieve more accurate results. Moreover, the data from 0.1-100 mM closely parallels the predictive ordinary differential equation (ODE) model (see Fig. 13) correlating complement concentration to RFU (see Model). Therefore, the overall data collected depicts an accurate relationship between the complement concentration and RFU.

Linear Probes with RCP

We use linear probes as a means to quantify and report the miRNAs that we sensed through rolling circle amplification (RCA) reactions. In addition, we characterized linear probes and quantified RCP in serum through the linear probes reporting mechanism. We followed the experimentation protocol below to test this. (see Experiments: Linear Probes with RCP ).

As shown by Figure 14, there is statistically significant decrease in the fluorescent output of a triplicate with FAM Probe, BHQ Probe, and RCP as compared to a triplicate of just FAM tagged Probes. This confirms that we did produce our desired RCP in the RCA reaction for our miRNA-1-3p and miRNA-133a-3p sensors and that this mechanism was an effective reporting method for our sensor.
Figure 15. Characterization curve for showing a negative logarithmic relationship between RFU from linear DNA probes and miRNA concentrations
Figure 16. Deterministic ODE Model Simulation of RFU output dependent on miRNA concentration.

In order to quantify the relationship between miRNA concentration and fluorescence, we further characterized these parts with varying linear probe complement concentrations. There is a negative logarithmic correlation between the complement concentrations and the relative fluorescence units (RFU) (see Fig. 15). Moreover, the data shown above closely parallels the predictive ordinary differential equation (ODE) model (see Fig. 16) correlating complement concentration to RFU (see Model .Therefore, the overall data collected depicts an accurate relationship between the miRNA concentration and RFU, further validating that RCA coupled with linear probes are an effective and efficient means of quantifying miRNA concentrations.

Figure 17. Linear DNA Probe Fluorescence from Serum Extracted miRNA-1-3p Rolling Circle Amplification. Results show significant decrease in fluorescence, indicating a successful Proof of Concept.

As shown by Figure 17, there is statistically significant decrease in the fluorescent output of a triplicate with FAM Probe, BHQ Probe, and RCP as compared to a triplicate of just FAM tagged Probes. This confirms that we did produce our desired RCP in the RCA reaction performed on our miRNA-1-3p spiked serum. This further validates that biosensors utilizing RCA coupled with FAM and BHQ-1 linear DNA probes is an effective sensing and reporting mechanism for miR-1-3p.

Lettuce with Complement

We tested the split lettuce design with a complementary ssDNA sequence as the target. Since RCA reactions were run in SplintR Ligase Buffer and phi29 Buffer, the split lettuce reaction was tested in the buffers used in the RCA reaction in order to determine the feasibility of the method.

We developed the protocol for the lettuce aptamer experimentation with RCP based on the experimentation by VarnBuhler et al and tested the full lettuce DNA aptamer with the sequence ordered as a DNA oligo from Integrated DNA Technologies (IDT) which displayed significant fluorescence in the presence of DFHBI-1T.

To determine the feasibility of the aptamer with our RCP, we ran the reaction of our aptamer with a sequence (from IDT) replicating the middle sequence of the RCP. The following protocols were used: (see Experiments: Lettuce with Complement).

From these results, we saw an increase in fluorescence with the presence of simulated RCP and lettuce in the reaction as compared to the controls (see Fig. 18). This shows that the lettuce aptamer hybridized to the RCP and the dye, causing fluorescence.

We observed a significant decrease in fluorescence in the lettuce reaction tube when compared to the dye background (see Fig. 18). This decrease is most likely due to the opaqueness of the lettuce DNA sequences. In contrast, the lettuce with complement reaction greatly increased in fluorescence when compared to the controls.

Figure 18. Graph of fluorescence of Lettuce with Complement of middle sequence and DFHBI-1T.

Lettuce with RCP

After confirming the efficacy of the split lettuce reaction with the linear probe complement, we ran the reaction with RCP and created controls with and without DFHBI-1T to compare the fluorescence before and after the dye was added. The following protocols were used. (see Experiments: Lettuce with RCP).

The results of the split Lettuce reaction in conjunction with RCP suggested that this reporter mechanism can successfully correlate the presence of a specific miRNA to an increase in fluorescence through RCA and the Lettuce aptamer.

Figure 19. Graph of change in fluorescence from left to right: 1) water + dye control, 2) split lettuce + dye control, 3) split lettuce + RCP + dye, 4) split lettuce + padlock & miRNA control + dye.

The increase in fluorescence of the RCP + Lettuce + dye was significantly greater than the controls, which suggests that the split Lettuce was successfully bound to the RCP (see Fig. 19). In addition, the DFHBI-1T was also successfully bound within the split lettuce secondary folding. According to these results, RCA and the reaction between the split lettuce and RCP was successful.

Statistical Analysis

Analysis of Variation (ANOVA)

To further validate our experimental results, we decided to run significance tests. Using RStudio, a statistical computer analysis interface utilizing R, we ran an Analysis of Variation Model (ANOVA) to analyze the difference of means for fluorescence between the following categories (see Fig. 20 and 21).

Linear Probes

  • Quencher
  • Fluorophore
  • TE Buffer
  • RCP with Fluorophores with Quencher

Lettuce Aptamers

  • Background Dye
  • Lettuce + Dye
  • RCP + Lettuce
  • Padlock + miR + Lettuce
Figure 20. Results of one-way ANOVA on experimental results for RCA run with Linear Probes on hsa-miRNA-1-3p, displaying an F-value of \(917.6\) a p-value of \(1 * 10 ^{-10}\), showing a highly statistically significant difference between group means.
Figure 21. Results of one-way ANOVA test on experimental results for RCA run with Lettuce Aptamers on hsa-miRNA-1-3p, displaying an F-value of \(31.376\) a p-value of \(3.22 * 10^{-5}\), also showing a highly statistically significant difference between group means.

Based on the results above (see Fig. 20 and 21), the p-values for both Linear Probes and Lettuce Aptamers are \(\leq 0.001\), a statistical benchmark for showing a high significance.

If our differences were not statistically significant (null hypothesis), there would be a \(1 * 10 ^ {-8} \hspace{4px} \% %\) and \(3.22* 10^{-3} \hspace{4px} \% %\) chance respectively that these results could be replicated in a random environment. Therefore, our reporting mechanisms experimentally show a significant difference, which is not due to random chance.

Post-Hoc Tests

ANOVA analyses are prone to Type I experimental error rates, especially as the number of groups compared increases. This error rate can be up to 26% for a comparison between 4 groups (Frost, 2011). To remedy this, post-hoc tests are usually run, which allow a specification of the error rate and adjusts the p-values (p-adj) to match the error rate within pairwise comparisons. We ran Tukey’s Honest Significant Difference (HSD) post-hoc test to compare the pairwise difference between each of the specific means (see Fig. 22 and 23) using a 95% confidence interval.

Figure 22: Tukey Post-Hoc Test on experimental results for RCA run with Linear Probes on miRNA-1 with a 95% confidence interval. The p-adj values for RCP_Fluorophore_Quencher vs the other reagents each have values less than 0.001, further displaying a highly statistically significant difference.
Figure 23: Tukey Post-Hoc Test on experimental results for RCA run with Lettuce on miRNA-1 with a 95% confidence interval. The p-adj values for RCP + Lettuce vs the other reagents each have values less than 0.001, further displaying a highly statistically significant difference between specifically RCP + Lettuce-Background Dye and other control reagents.

Based on the results above (see Fig. 22 and 23), the p-values for both Linear Probes and Lettuce Aptamers are \(\leq 0.001\), a statistical benchmark for showing a high significance.

If our differences were not statistically significant (null hypothesis), there would be a \(5.8 * 10 ^ {-4} \hspace{4px} \% %\) and \(4.3 * 10 ^{-3} \hspace{4px} \% %\) chance respectively that these results could be replicated in a random environment. Therefore, our reporting mechanisms experimentally show a significant difference, which is not due to random chance.

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