KRAS mutation is a common point mutation which occurs in ~30% of all human cancers. Early assessment of KRAS mutation status is critical for prediction of clinical treatment outcomes. However, current diagnostic methods are based on either polymerase-chain-reaction (PCR) or next-generation-sequencing (NGS) analysis of biopsy samples, which are complex, time consuming, and lack portability. Here, we report a cost-effective smartphone-based fluorescence microscopy platform for detection of KRAS point mutations by imaging targeted DNA sequencing reactions in preserved tumor slides. Smartphone-based KRAS mutation detection was conducted in two steps: 1) in situ rolling-circle-amplification (RCA) combined with ligation chemistry to label wild type/mutant strains with different fluorescent colors, and 2) rapidly scanning the sample by a smartphone microscope to quantify mutant-to-wild type ratios. This smartphone microscope contains two laser diodes (532 and 638 nm) for dual-color fluorescence detection (Cy3 & Cy5) and an additional white LED for brightfield imaging. We first imaged and analyzed synthetic or extracted DNA from model cell lines captured and amplified on glass slides. The smartphone fluorescence microscope was able to detect as low as 1fM target DNA sequence, and demonstrated a high sequencing depth (1:1000 mutant:wild type ratio), comparable to the sensitivity of FDA-approved KRAS PCR-based tests. Furthermore, the device was applied for in situ mutation detection in cell lines and real patient tumor slices. A machine learning algorithm was also developed to improve the recognition of target signals against the nonspecific background. Overall, smartphone-based in situ mutation detection resulted in 100% concordance to clinical NGS analysis.
We have recently presented a method that enables single molecule enumeration by transforming specific molecular recognition events at nanometer dimensions to micrometer-sized DNA macromolecules. This transformation process is mediated by target specific padlock probe ligation, followed by rolling circle amplification (RCA) resulting in the creation of one rolling circle product (RCP) for each recognized target. The transformation makes optical detection and quantification possible by counting the number of generated RCPs using standard epi-fluorescence or confocal fluorescence microscopes. We have characterized the performance of the epi-fluorescence and the confocal readout formats. Both formats exhibit a linear response of the number of counted objects as a function of starting circles, and the dynamic range is three orders of magnitude employing epi-fluorescence readout and four when using confocal. In the epi-fluorescence format flow rate has to be below 1 μl/min and flow variations are likely to be the limiting factor for precision. If the flow rate is above 3 μl/min the precision of the confocal readout format is limited only by Poisson counting statistics, due to the accurate volume definition of the confocal optics. The limit of detection in the confocal format was reduced by a factor of three by increasing the data acquisition rate by a factor of ten.