Low copy target detection by Droplet Digital PCR through application of a novel open access bioinformatic pipeline, 'definetherain'

Abstract

Droplet Digital PCR (ddPCR) represents a new and alternative platform to conventional quantitative-PCR (qPCR) for the quantitation of DNA templates. However, the proposed improvement in sensitivity and reproducibility offered by ddPCR is not yet fully proven, partly because the delineation between positive and negative responses is not always clear. Data are presented demonstrating the sensitivity of the ddPCR system to both reagent concentrations and choice of cut-off for defining positive and negative results. By implementing k-nearest clustering, cut-offs are produced that improve the accuracy of ddPCR where target DNA is present at low copy numbers, a key application of ddPCR. This approach is applied to human albumin and HIV-1 proviral DNA ddPCR quantitative protocols. This tool is coded in JavaScript and has been made available for free in a web browser at http://www.definetherain.org.uk. Optimisation of the analyses of raw ddPCR data using 'definetherain' indicates that low target number detection can be improved by its implementation. Further application to patient samples will help define the clinical utility of this approach.

Keywords: Droplet Digital PCR; HIV-1; Quantitative PCR; k means clustering.

Fig. 1

Optimisation of ddPCR conditions from qPCR reaction protocols. Optimisation of ddPCR conditions from qPCR protocols. (a) Standard curve plot from the albumin qPCR assay. (b) Standard curve plot from the HIV-1 qPCR assay. (c) Dot plot showing fluorescent amplitude of droplets from the HIV-1 DNA assay at differing probe concentrations. Red droplets were classified as positive by QuantaSoft Auto threshold and green droplets were classified as negative. Shaded blue regions indicate areas where QS has identified incorrectly droplets in the negative cluster as positive. (d) Plot showing the HIV-1 copy number in duplicate (orange and black columns) as a surrogate for the frequency of false positives for three probe concentrations assayed using water controls in ddPCR. (e) Box and whiskers plot showing the calculated HIV-1 copy number for differing probe concentrations: 125 nM (n = 5), 250 nM (n = 6), 500 nM (n = 6). Expected copy number was 33,000 for each probe concentration. (f) Dot plot showing a typical droplet distribution for the Bio-Rad test assay, the albumin assay and the HIV-1 assay, with positive, negative and rain droplets indicated. It should be noted that the Bio-Rad test assay is a two channel (FAM and VIC) assay, hence the presence of two distinct negative clusters. (For interpretation of the references to color in this legend, the reader is referred to the web version of the article.)

Fig. 2

Defining ‘rain’ in the ddPCR platform. Results of ddPCR from (a) high (10⁵) and (b) low (10²) copy number samples assayed in the albumin quantitation assay. Droplets that do not appear to be distinguishable as either positive or negative (rain) are coloured red. The dashed horizontal line indicates the threshold above which Quantasoft determines a droplet to be positive. The full horizontal lines indicate limits that have been applied using ‘definetherain’ on a positive control sample. Droplets that fall between these cut-offs are defined as rain and are not included in the calculation to determine copy number. (For interpretation of the references to color in this legend, the reader is referred to the web version of the article.)

Fig. 3

Screenshots illustrating the application of ‘definetherain’. Screenshots illustrating the application of ‘definetherain’. (a) A modified screenshot from the ‘definetherain’ javascript program illustrating the k-nearest neighbour clustering of albumin positive control sample data. The control sample has been used to automatically define the cut-offs for a positive or a negative response. Intermediary values between the positive and negative clusters are classified as rain (the shaded grey region) and are excluded from further analysis. Droplets in any subsequent samples with amplitudes that fall within this range will not be included in the copy number calculation. (b) An example graphical output from ‘definetherain’ from an experiment sample with a low copy number. (c) An example graphical output from ‘definetherain’ from an experimental sample with high copy number. (For interpretation of the references to color in the text, the reader is referred to the web version of the article.)

Fig. 4

Comparison of ‘definetherain’ and QuantaSoft to report albumin and proviral HIV-1 DNA quantification by ddPCR. Comparison of ‘definetherain’ and QuantaSoft to report albumin and proviral HIV-1 DNA quantitation by ddPCR. Top row (panels a & b), data from the albumin dilution assay with copy number called by QuantaSoft and ‘definetherain’, respectively. Bottom row (panels c & d), data from the HIV-1 proviral dilution assay with copy number calculated by QuantaSoft and ‘definetherain’. The black line would indicate a 1:1 correspondence between the digital droplet copy number and the expected number. The blue or red line is a linear regression line based on the data points. The shaded area indicates the 95% confidence intervals for the regression. p Values, line gradients and correlation coefficients for each fit are shown. (For interpretation of the references to color in this legend, the reader is referred to the web version of the article.)