Measurement

Introduction

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It's been 7 years since the CRISPR/Cas13a (class 2 typeVI) system was discovered, and still, this innovative biotechnology toolbox has not been translated into diagnostic molecular devices for the detection of disease-related RNAs. With the exception of SHERLOCK diagnostic device for COVID-19 testing (Joung et al., 2020), other efforts by researchers to develop reliable CRISPR/Cas13 based-reliable tools for medical diagnosis encounter complicated translational processes and cannot enter the marker. On the other side, other researchers hesitate to indulge with the CRISPR-based systems because of their biological complexity and challenges. The CRISPR/Cas13a system application for diagnostic purposes requires well-designed and standardized measurement methodologies maximizing the reliability and the validity of the findings. Inadequate measurements with high inconsistency hinder the translational process of the diagnostic tool towards clinical application and may give false positive or false negative results.

To facilitate the implementation of CRISPR/Cas13 systems for diagnostic applications while ensuring the reliability of the obtained quantitative data, we developed a well-characterized experimental measurement workflow that can be easily adapted to different RNA-based detection assays. The method aims to minimize the effect of factors that endanger the reliability of the measurement data. As illustrated in Figure 1, the major sources of reliability issues (biases) can be grouped into the following main categories:

• Researcher-related source of bias. The researcher can produce systematic errors during the experimental procedures due to improper pipetting techniques or even random errors in case of complicated experimental protocols
• Risk of reliability issues related to the functionality of the molecular tools exploited for the measurement. Depending on storage time and conditions the Cas13a enzymes' functionality can be reduced causing inconsistent measurement results. In addition, the specific RNAs employed for the detection reactions can be degraded resulting in decreased concentration changing the molecular dynamics of the reaction.
• Issues regarding the tools/instruments of data collection. A reliable instrument should measure what it is supposed to measure in a constant manner. On the other side, faulty measurement instruments can lead to inconsistent results.
• External factors. The detection assay should be held under the proper and controlled environmental conditions to reduce variability (Merom et al., 2019).

The proposed experimental measure workflow aims to reduce the reliability issues derived from the researcher and the external factors standardizing the CRISPR/Cas13a based measurement approach and encouraging future iGEM teams to implement the CRISPR/Cas13a systems to their project design. In addition, with the crPRep-crRNA preparation kit that we firstly introduced, researchers can easily design and produce the crRNA required for the desired target miRNA for the detection assay. This methodology simplifies the in silico design and the experimental process of a functional miRNA-targeted crRNA and requires only the design of the spacer FWD interchangeable primer following the guidelines provided in Figures 5-6 in the contribution page. The cloning steps required for the crRNA in vitro transcription as well as the 3 additional primers for the PCR steps remain the same.

In addition, the information provided in the following sections enables future iGEM teams to study the Cas13a enzyme kinetics and investigate the conditions which affect the reaction rates and the assay performance. A detailed Michaelis-Menten Kinetics model is provided and can be easily applied to explain how the rate of an enzyme-catalyzed reaction depends on the concentration of the enzyme and its substrate.

Detailed measurement workflow

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As described above, the measurement workflow is designed in a way to enable easy completion of the experimental procedures minimizing the influence of any involved factors that could disrupt system's reliability such as pipetting errors and temperature fluctuations.

However, the first step towards implementing the Cas13/crRNA methodology of analyte quantification is to investigate the suitable reaction conditions such as the required RNA reporter concentration for achieving the best performance. Afterwards, a Cas13a enzyme kinetics analysis could provide useful data regarding the factors that affect the rate of an enzyme-catalyzed reaction such as the concentration of the enzyme and the RNA reporter substrate. This information can be used to further optimize reaction conditions achieving even better detection accuracy and performance.

Michaelis-Menten analysis

For the Michaelis Menten analysis, the concentrations of the crRNA 17-3p standard, LbuCas13a and miR 17-3p selected to be 10, 20 and 1 nM respectively for all the experiments. The concentration of reporter RNA were selected to have values 1, 0.75, 0.5, 0.25, 0.1 μM. In the figures provided below, it can be seen that the samples containing the target miRNA (positive) demonstrate elevated fluorescence values compared to the control samples (negative) that do not contain the target miRNA.

1.00μM

0.75μM

0.50μM

0.25μM

Every curve shows a maximum fluorescence intensity at around 5 minutes since reaction initiation. The curves presented on Figure 2 can be split into 2 main parts. The first part of the curves is the linear increasing part that corresponds to the time interval between reaction initiation (o min) and the time point that the curves hit their maximum fluorescence intensity. The linear part of the curve is needed for the efficient detection of the target RNA. The linear behavior can be described by the mathematical formula of Michaelis - Menten enzyme kinetics which is:

Where \( dF / dt \) is the slope term of the increasing part of the curve, \( V_m \) is the maximum velocity of the reaction and \( K_m \) is the concentration of the substrate (reporter) that will result in half \( V_m \) velocity. This mathematical formula can be transformed as:

So, the first step of the analysis is to find the slopes of the linear-increasing part of the curves. We firstly identify the maximum value of the fluorescence on each of the curves, then we take all the points before the maximum and finally we apply the least square line fitting.

Calculating the slope of the least line square fitting, we can find the velocity (\( \upsilon_0 \)) for every reaction. The next step is to plot the variables \( 1 / \upsilon_0 \) on the y-axes and the \( 1 / [\text{reporter}] \) on the x-axes (figure 4). Applying the least squares line fitting on the \( X \) and \( Y \), we can derive the parameters of \( K_m / V_m \) and \( 1 / V_m \) from formula (2).

After the calculation of the \( V_m \) and \( K_m \) parameters, we can calculate the catalytic activity of the enzyme based on the equation:

Where \( V_m \) is the maximum velocity of the reaction and \( E_t \) is the concentration of the active enzyme and in our case the concentration of the target miR (\( 10^{-9} M \)).

By converting the fluorescence Arbitrary Units to concentration the derived values of the parameters found to be:

Calibration curve construction

Regardless of the CRISPR/Cas13a system final implementation for diagnostic purposes, the target molecules (analyte) that should be detected and quantified are RNA molecules including miRNAs, mRNAs or even viral RNA. As followed in all bioanalytical quantification methods, the first step towards developing a high performance detection platform for the target analyte is to investigate the reaction conditions and construct a calibration curve. The CRISPR/Cas13a-based detection approach is based on the resulting trans cleavage of RNA reporters upon crRNA-guided target ssRNA recognition. As a result the digested RNA reporter emits fluorescence signals by a fluorophore getting rid of the fluorescence resonance energy transfer (FRET) effect. Therefore, a calibration curve should be constructed plotting different target analyte concentrations in known tested samples (spike-in/standards) against fluorescence intensity signals caused by Cas13a/crRNA reaction. The standard curve represents a linear relationship between concentration of an analyte (independent variable-target RNA added) and response (dependent variable-fluorescence intensity). This relationship is used to predict the unknown concentration of the analyte in a complex matrix such as the blood or serum. A well-constructed calibration curve with the coefficient of determination R2 approaching 1 validates the detection system's performance and accuracy.

To construct a calibration curve for CRISPR/Cas13a systems minimizing sources of bias derived from the researcher or external factors, we provide the following guidelines and experimental workflow.

The first step is to perform serial dilutions of the target RNA (standard) initiating from the stock solution generating the SD mixtures. Utilizing the serial diluted mixtures (standards) the researchers should prepare the RS mixtures which contain the standards and a specified concentration of the reporter RNA in a 5X reaction buffer. In our case the 5X reaction buffer contains 10mM Tris-HCl, 50mM NaCl and 10 mM MgCl2 (pH 7.9). Afterwards, the CC reaction mixture should be prepared calculating the total number of required standards and taking into account the technical replicates. The CC reaction mixture contains the Cas13a enzyme and the desired concentration of the crRNA in 5X reaction buffer. Then, a specified amount (20μl) of the CC reaction mixture is added into each of the RS mixtures generating the final MM master mixtures which are loaded into the microplate wells. At this point, we should emphasize that the concentrations of all molecular components (target RNA standards, reporter RNA and crRNA) in the SD, RS and CC mixtures are multiplied by 5 to achieve a 1X final concentration of the components in the MM mixtures. All reaction mixtures (RS, CC and MM) are designed in accordance with other enzymatic reactions standard methods such as the PCR or qPCR to enhance the understanding of the protocol steps and to facilitate the easy completion of the assay.

Step 1 (SD mixtures preparation)

Initiating from a stock solution, prepare serial dilutions (SD1-SD5) of the target RNA (standard) utilizing the water as a solvent. The SD2 mixture is prepared by pipetting the suitable amount of the SD1 solution into SD2 solution in water solvent. Repeat this process by pipetting from the previous solution (SD2) a suitable volume into the SD3 solution. This process is repeated until the completion of all SD solutions. To construct an efficient standard curve at lesta 5 standards should be prepared.

Step 2 (RS mixtures preparation)

The RS reaction mix contains the reagents that are shown in Table 2 in a final volume of 30μl. Each RS mixture is prepared by adding the same volume of RNA reporter, reaction buffer 5X and water. However, in each RSx mixture a specified volume of the corresponding SDx mixture is added until completion of all RS mixtures.

Step 3 (CC reaction mixture preparation)

The CC reaction mix contains the reagents that are shown in Table 3 in a final volume of 20μl.

Step 4 (MM master mixture preparation)

Depending on the technical replicates required for each standard, the suitable volume of CC mixture should be added in each RSx mixture generating the final MMx mixture. For example, for the MMx reaction mixture preparation of 4 technical replicates, 120 μl of RSx mixture and 80μl of CC mixture should be added. Then, a specified volume (50μl) of MMx mixture is added in each well of the microplate, followed by fluorescence detection in plate reader. After the MMx mixtures addition into the microplate wells, the fluorescence detection should be conducted within the first 10 min after reaction initiation to achieve the best performance. The above method for standard curve construction is illustrated on Figure 5.

Utilizing the described measurement workflow, we constructed a calibration curve that plots the miR-17-3P concentration in known samples (standards) against fluorescence intensity. Specifically, 50μl of Cas13a mix was prepared with 20nM LbuCas13a, 20nM crRNA, 0.5μΜ FQ5U Reporter, different concentrations of target miRNA (0-negative control, 1pM, 5pM, 10pM, 50pM, 100pM) and 1X Reaction buffer (10mM Tris-HCl, 50mM NaCl, 10 mM MgCl2, pH 7.9). The fluorescence detection was performed at 37 °C for 60 min using a fluorescence plate reader with fluorescence collected every two minutes. To construct the final standard curve for the detection system we plotted the fluorescence intensity of each miRNA tested concentration versus time analyzing the data from the plate reader. For each time point, a standard curve was constructed along with the corresponding linear trendline and coefficient of determination (R2). As clearly depicted in Figure 6 the coefficient of determination R2, which is a measure of how well a linear regression line fits the data, approaches 1 indicating a perfect fit.

Consequently, the perfect linearity in the standard curve validates the assay performance and verifies the reliability of the measurement workflow minimizing potential sources of bias derived from handling errors or external factors.