Single-Molecule cfDNA Sequencing for Reduced Methylation Bias
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Solution Overview
Problem
Conventional methylation sequencing of cell-free DNA (cfDNA) introduces biases such as GC skews and oxidative DNA damage, leading to significant PCR amplification biases and alignment artifacts, making it challenging to characterize methylated cfDNA from cancer patients effectively.
Innovation Solution
A method for high-throughput sequencing of cfDNA using single molecule sequencers like Oxford Nanopore and Pacific Biosciences, which characterizes methylation patterns without chemical or enzymatic conversion and PCR amplification, enabling direct detection of methylated DNA signals through machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional Illumina-based methylation sequencing with bisulfite conversion and PCR amplification is used, then methylation detection can be achieved, but significant biases such as GC skews, oxidative DNA damage, and PCR amplification biases are introduced
Solution Approach 1:
The patent extracts and removes the problematic steps of bisulfite conversion and PCR amplification from the methylation sequencing workflow. By using single-molecule sequencing that directly reads methylated DNA without these intermediate steps, the invention eliminates the sources of GC skews, oxidative damage, and amplification biases while maintaining methylation detection capability
Solution Approach 2:
The patent replaces the chemical conversion mechanism (bisulfite treatment) and enzymatic amplification mechanism (PCR) with a direct physical sequencing mechanism. Single-molecule sequencing reads the methylation state of individual DNA molecules directly, substituting the need for chemical modification and amplification with direct detection of native methylated DNA
2Measurement precision
If single molecule sequencing is used to avoid PCR biases, then measurement precision improves, but sequencing yield remains low without optimized library preparation
Solution Approach 1:
The patent optimizes library preparation parameters including DNA fragmentation size, adapter ligation conditions, and sequencing depth to maximize yield. By adjusting these parameters, the invention achieves high-throughput sequencing with single-molecule methods, producing millions to hundreds of millions of reads per sample while maintaining the precision benefits of bias-free sequencing
Solution Approach 2:
The patent uses excessive sequencing depth to compensate for the lower yield per molecule inherent in single-molecule sequencing. By sequencing millions of individual molecules, the invention achieves sufficient coverage and statistical power for accurate methylation profiling, overcoming the low yield per molecule through high throughput
3Productivity
If conventional library preparation protocols are used for single molecule sequencing, then workflow simplicity is maintained, but sequencing yield is insufficient for high-throughput analysis
Solution Approach 1:
The patent segments the library preparation process into distinct optimized steps: DNA fragmentation to specific size ranges, selective adapter ligation, and quality control. This segmentation allows each step to be optimized independently for yield while maintaining overall workflow manageability, achieving high-throughput sequencing with controlled complexity
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 provides accurate, high-throughput methylation profiling of cfDNA, overcoming biases and achieving an order of magnitude improvement in sequencing yield, allowing for precise detection of cancer-specific methylation patterns and tumor burden monitoring.
Implementation Method 1
high-throughput sequencing of cfDNA on single molecule sequencers, (e.g., Oxford Nanopore, Pacific Biosciences)
Implementation Method 2
Methylated DNA generates a unique single molecule sequencing signal compared to unmodified DNA, and is readily detected with various machine learning algorithms
Data Source
AI summary
The disclosure provides methods for detecting a molecule of tumor DNA (tDNA) in a sample of cell-free DNA (cfDNA). In certain embodiments, cfDNA is sequenced using a single molecule sequencing to obtain a methylation profile of a sequence read. Such methylation profile is compared to a reference methylation profile from a cancer cell and/or a non-cancer cell to identify the sequence read as being from a molecule of tDNA. Further embodiments provide estimating the number of molecules of tDNA in the sample of cfDNA and, to determine as a tumor load of the cfDNA, the proportion of the number of molecules of tDNA to the total number of molecules of cfDNA in the sample. Such tumor load can be used to monitor cancer progression in a subject or efficacy of a cancer therapy administered to a subject.