Research ArticleGENETICS

Facile profiling of molecular heterogeneity by microfluidic digital melt

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Science Advances  26 Sep 2018:
Vol. 4, no. 9, eaat6459
DOI: 10.1126/sciadv.aat6459
  • Fig. 1 HYPER-Melt workflow.

    (A) The reaction and target mixture, which are prepared on benchtop, is loaded into the microfluidic chip where rare methylated epialleles are digitized. (B) The chip is then placed on a flatbed heater to undergo PCR amplification followed by the Melt reaction, in which a MILC captures fluorescent images of the array during temperature ramping. (C) The images are analyzed to find the melt temperature, which corresponds to the initial template sequence. (D) A molecular heterogeneity histogram reveals different populations, which can be separated by thresholding and classified by methylation density, providing a quantitative analysis of the molecular heterogeneity of the sample. RFU, relative fluorescence units.

  • Fig. 2 Microfluidic device design and operation.

    (A) Breakout of the microfluidic chip. The layers include a PDMS-coated glass slide, single PDMS pattern layer, thin glass coverslide, and PDMS tubing adapter for the inlet, outlet, and hydration line. (B) A single ultrathin pattern layer and hydration line effectively prevent evaporation through the permeable material. (C) The chip is desiccated to produce a negative pressure differential across the inlet. When punctured, the sample mixture automatically loads into the chambers. Next, a partitioning fluid is pressurized through the channels to isolate the reaction chambers.

  • Fig. 3 Melt curve acquisition and discrimination by melt temperature.

    (A) Fluorescent images are acquired of the entire chip at each temperature interval to visualize denaturation of the amplicons (subset shown). (B) The fluorescence data of each well are filtered and plotted against temperature to produce a melt curve. The inflection point of the curve is defined as the melt temperature (Tm) of the template sequence. The Tm is then used to discriminate the methylation density of the original template epiallele.

  • Fig. 4 Detected versus expected DNA copy number.

    Mixed epialleles were diluted into a background of 2 million unmethylated templates. After amplification and HRM-based discrimination, the detected copy number of each epiallele was calculated according to a Poisson distribution. The average epiallelic detected copy number was compared to the expected. The array chip demonstrates linearity from ~1 to 1000 copies. x refers to expected number of copies of epiallele (DNA), and y refers to detected number of copies.

  • Fig. 5 HYPER-Melt analysis.

    (A) HYPER-Melt was used to analyze p14ARF synthetic sequences ranging in copy numbers of 0 to 1000 of each epiallelic species in 2 million unmethylated background molecules. (B) A subset of melt curve derivatives from each serial dilution, color-coded by melt temperature, demonstrates methylation density–independent amplification of all species and single-copy sensitivity. (C) The digital heatmap reflects the methylation density of the template molecule in each well. (D) The populations of the four epiallelic species can be quantified and assessed upon inspection and thresholding of the DREAMing histogram. (E) Corresponding bulk analysis validates amplification but demonstrates limited sensitivity due to the low–copy number methylated peaks being eclipsed by the high background.

  • Fig. 6 Liquid biopsy (cfDNA) biomarker detection and analysis via HYPER-Melt.

    Methylation data acquired for the NDRG4 locus from DNA extracted from plasma samples from both mCRC and normal patients. (A) Three different levels of methylation density (low, medium, and heavy) were identified for each patient via the HYPER-Melt platform. The total number of methylated epialleles detected from each patient sample was compared to that of the gold standard, MSP. HYPER-Melt histograms show the number of copies detected at each epiallelic fraction from plasma of (B) CRC patients and (C) healthy volunteers.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/9/eaat6459/DC1

    Table S1. Assay primers and synthetic targets.

    Fig. S1. Ultrathin microfabrication.

    Fig. S2. Digital melt platform.

    Fig. S3. Illumination optimization.

    Fig. S4. Pixel-space definition mapping.

    Fig. S5. Annealing temperature on-chip optimization.

    Fig. S6. NDRG4 copies detected in plasma samples.

    Fig. S7. Clinical sample workflow, patient characteristics, and validation of MSP assay.

    Fig. S8. Genomic validation of HYPER-Melt platform.

    Fig. S9. Comparison of HYPER-Melt with ddPCR.

    Movie S1. Loading and partitioning in the microfluidic device.

  • Supplementary Materials

    The PDF file includes:

    • Table S1. Assay primers and synthetic targets.
    • Fig. S1. Ultrathin microfabrication.
    • Fig. S2. Digital melt platform.
    • Fig. S3. Illumination optimization.
    • Fig. S4. Pixel-space definition mapping.
    • Fig. S5. Annealing temperature on-chip optimization.
    • Fig. S6. NDRG4 copies detected in plasma samples.
    • Fig. S7. Clinical sample workflow, patient characteristics, and validation of MSP assay.
    • Fig. S8. Genomic validation of HYPER-Melt platform.
    • Fig. S9. Comparison of HYPER-Melt with ddPCR.
    • Legend for movie S1

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    Other Supplementary Material for this manuscript includes the following:

    • Movie S1 (.wmv format). Loading and partitioning in the microfluidic device.

    Files in this Data Supplement:

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