High-Depth Methylation Sequencing With DNA-Preserving Conversion
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Solution Overview
Problem
Existing methylation sequencing methods, particularly bisulfite-based approaches, cause significant DNA degradation in cell-free DNA (cfDNA), leading to loss of fragment length information and requiring large blood volumes or low-depth coverage, and are costly and error-prone for analyzing methylation patterns in genetically heterogeneous samples.
Innovation Solution
A minimally-destructive conversion method, such as enzymatic conversion, is used to convert unmethylated cytosines to uracils, followed by amplification and probing with nucleic acid probes to enrich for sequences of interest, allowing high-depth sequencing and accurate methylation profiling with duplex sequencing for error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If bisulfite conversion is used for DNA methylation analysis, then methylation mapping accuracy is improved, but DNA degradation increases significantly
Solution Approach 1:
The patent introduces an intermediary enzyme system (TET enzymes and APOBEC enzymes) that mediates the conversion of unmethylated cytosines to uracils, replacing the direct chemical action of bisulfite. This enzymatic intermediary performs the same functional transformation while being gentler on the DNA structure, thus maintaining DNA integrity while achieving accurate methylation mapping.
2Ease of manufacture
If bisulfite conversion is performed before library construction, then single-stranded DNA libraries can be built, but DNA loss increases due to degradation
Solution Approach 1:
The patent performs the methylation conversion action after library construction rather than before, reversing the conventional sequence. By constructing the library first with intact DNA and then performing the enzymatic conversion, the method preserves DNA throughout the library preparation process while still enabling methylation analysis in the final sequencing step.
3Quantity of substance
If large blood volumes are collected to compensate for DNA degradation, then sufficient DNA quantity is obtained, but patient burden and cost increase
Solution Approach 1:
The patent converts the harmful effect of bisulfite degradation into a beneficial outcome by using enzymatic conversion that preserves DNA. The 'harm' of DNA loss in conventional methods is transformed into the 'benefit' of maintaining sufficient DNA quantity from small blood volumes, enabling liquid biopsy applications with minimal patient burden.
4Measurement precision
If high-depth sequencing is performed to achieve unique coverage, then methylation profiling accuracy is improved, but sequencing cost and time increase
Solution Approach 1:
The patent uses unique molecular identifiers (UMIs) that act as disposable tags for each DNA molecule. These short sequence tags enable computational tracking and error correction of individual molecules during sequencing, allowing accurate methylation profiling at lower sequencing depths by eliminating the need for excessive redundant sequencing.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach preserves DNA integrity, enhances sequencing accuracy, and reduces the need for large sample volumes, enabling precise methylation profiling and classification of disease states, including cancer detection and monitoring minimal residual disease.
Implementation Method 1
A minimally-destructive conversion method, such as enzymatic conversion, is used to convert unmethylated cytosines to uracils
Implementation Method 2
probing with nucleic acid probes to enrich for sequences of interest
Data Source
AI summary
Methods and systems provided herein address current limitations of bisulfite-based methylation sequencing by improving the quality and accuracy of nucleic acid methylation sequencing and uses thereof for detection of disease. Methods that include minimally-destructive conversion methods for methylation sequencing as well as specialized UMI adapters provide for improved quality of sequencing libraries and sequencing information. Greater accuracy and more complete methylation-state information permits higher quality feature generation for use in machine learning models and classifier generation.