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# Goal/Experiment:
This protocol outlines an automated procedure for estimating methylation levels using Methylation-Sensitive High-Resolution Melting (MS-HRM) analysis. The goal is to facilitate the detection and quantification of disease-related DNA methylation changes which can provide clinically relevant information in personalized patient care.
# Automated Procedure for Estimation of Methylation Levels in MS-HRM Analysis
**Authors:**
- Sally Samsø Mathiasen
- Jan Bińkowski
- Tina Kjeldsen
- Tomasz K Wojdacz
- Lise Lotte Hansen
**Affiliations:**
- ¹Department of Biomedicine, Aarhus University, Aarhus DK-8000, Denmark
- ²Independent Clinical Epigenetics Laboratory, Pomeranian Medical University, Szczecin, Poland
- ³Department of Biomedicine, Aarhus University, Aarhus DK-8000, Denmark
## Abstract
Testing for disease-related DNA methylation changes provides clinically relevant information in personalized patient care. Methylation-Sensitive High-Resolution Melting (MS-HRM) is a method used for measuring methylation changes and has already been employed in diagnostic settings. This method uses one set of primers that initiate the amplification of both methylated and non-methylated templates. Quantification of methylation levels using MS-HRM is hampered by PCR bias, leading to inaccurate calculations. This protocol utilizes the Area Under the Curve (AUC), a derivative of the HRM curves, and least square approximation (LSA) to improve accuracy. Limitations of the technique have been comprehensively evaluated, leading to a procedure that allows methylation level inference with specific measurement limitations.
## Protocol Citation
```
Sally Samsø Mathiasen, Jan Bińkowski, Tina Kjeldsen, Tomasz K Wojdacz, Lise Lotte Hansen. Automated procedure for estimation of methylation levels in MS-HRM analysis. protocols.io. https://protocols.io/view/automated-procedure-for-estimation-of-methylation-b3ptqmn
```
## License
This protocol is made available under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), permitting unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
## Experimental Procedure
### Data Import
1. **MS-HRM Data Preparation for the Analyses (when using Light Cycler system – other PCR systems may require adjusting the data format):**
1.1 Normalize the HRM curves using the Gene Scanning software (we recommend default settings for normalization).
1.2 Generate difference plots for each normalized melting curve with the 100% methylation melting curve as the baseline/reference.
1.3 If data for any samples contain obvious outliers, consider removing them (note the name of the outlier).
1.4 Export the difference plot as a text file (example layout in supplementary materials S8-S11).
> **IMPORTANT:** Calculations using the Methylation Level Calculator (MLC) require layout as described in "Plate set up" section of the MLC template. Modify columns and rows accordingly for other layouts.
### Calculation of Experiment Specific Standard Curve
2. **Methylation Levels Estimation Procedure:**
2.1 Open the Methylation Levels Calculator (MLC).
2.2 Open the exported text file from LC480 instrument (e.g., S10-S11 MGMT assay text without outliers).
2.3 Copy all data and paste into the "imported data" sheet starting in cell B3. Ensure names in rows 2 and 3 match.
> **IMPORTANT:** Make sure the digital separator in the file exported from LC480 and Excel are the same. Modify the MLC for different sample layouts accordingly.
2.4 MLC will calculate and display AUC for each control and sample in row 1 of "Imported data" sheet.
2.5 Check if AUC for each replicate in row 1 is within the acceptable range. Replace outliers with 0 if necessary.
> **IMPORTANT:** If MLC does not perform calculations automatically, change Excel settings to Automatic (`Formulas > Calculation options > Automatic`).
2.6 Go to sheet "0 variable":
- Panel 1: AUC for each control replicate is calculated.
- Panel 2: Equation 1 calculates theoretical AUC for each methylation level.
- Panel 3: Theoretical and obtained AUC values for controls are plotted.
2.7 Go to sheet "1 variable":
- Panel 1: AUC for each control replicate is calculated.
- Panel 2: Equation 2 calculates theoretical AUC with M value set to 1.
- Panel 3: Theoretical and obtained AUC values for controls are plotted.
2.8 Go to sheet "1 variable after LSA":
- Solver Add-in is used.
2.9 Go to `Data > Solver > Solve`. Recalculate M value by LSA and recalculate standard curve.
2.10 Go to the sheet "2 variables":
- Panel 1: AUC for each control replicate is calculated.
- Panel 2: Equation 3 calculates theoretical AUC with N value set to 1.
- Panel 3: Theoretical and obtained AUC values for controls are plotted.
2.11 Go to sheet "2 variables after LSA":
- Solver Add-in is used.
2.12 Go to `Data > Solver > Solve`. Recalculate M and N values by LSA and recalculate standard curve.
### Estimation of Methylation Level in Unknown Samples
3. **Estimation of Methylation Level in Unknown Samples:**
- MLC uses polynomial trend function for calculation.
3.1 Go to sheet "PTF":
- Panel 1: Transform standard curve to describe methylation level as a function of AUC.
- Panel 2: Polynomial trend function describes the standard curve.
3.2 Go to sheet "USC":
- Panel 1.1: Sample name.
- Panel 1.2: AUC for each replicate.
- Panel 1.3: Methylation level calculated using equation 3 with M and N variables.
### Calculation of Experiment Specific Detection Window
4. **Calculation of Experiment Specific Detection Window:**
4.1 Go to sheet "Cut off (CO)":
- Panel 1.1-1.2: Calculate AUC for each control replicate.
- Panel 1.3-1.4: Calculate standard deviation and mean for each control replicate.
- Panel 2: Plot normal distribution for each control.
4.2 Go to sheet "Detection window":
- Panel 1.1-1.2: Calculate AUC for each control replicate.
- Panel 1.3-1.4: Calculate standard deviation and mean for each control replicate.
- Panel 2: Calculate overlap between consecutive controls.
- Panel 3: Fill lower (10%) and upper limits (50%-60%) of detection window in cells P7 and Q7.
### Calculation of Methylation Levels in the Assay Specific Detection Window
5. **Calculation of Methylation Levels in the Assay Specific Detection Window:**
5.1 Go to sheet "2 variables within DW":
- Solver Add-in is used. If calculations are not automatic, change Excel settings to Automatic.
5.2 Go to `Data > Solver > Solve`. Recalculate M and N values by LSA and standard curve.
5.3 Go to sheet "PTF within DW":
- The same procedure is applied within the detection window.
5.4 Go to sheet "USC within DW":
- Panel 1.1: Sample name.
- Panel 1.2: AUC for each sample replicate.
- Panel 1.3: Calculate methylation level with M and N variables within detection window.
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