Low-Cost Paper-Based Assays for Multiplexed Genetic Analysis using Surface Enhanced Raman Spectroscopy

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In order to improve human health it is critical to develop low-cost sensors for chemical detection and healthcare applications. Low-cost chemical detectors can enable pervasive monitoring to identify health threats. Rapid yet accessible infectious disease diagnostics have the potential to improve patient quality of care, reduce healthcare costs and speed recovery. In both cases, when multiple targets can be detected with a single test (multiplexing), accessibility is improved through lowered costs and simplicity of operation.

In this work we have investigated the practical considerations and applications of ink-jet printed paper surface enhanced Raman spectroscopy (SERS) devices. SERS enables specific simultaneous detection of numerous analytes using a single excitation source and detector. Sensitive detection is demonstrated in several real-world applications. We use a low-cost portable spectrometer for detection, further emphasizing the potential for on-site detection.

These ink-jet printed devices are then used to develop a novel DNA detection assay, in which the multiplexing capabilities of SERS are combined with DNA amplification through polymerase chain reaction (PCR). In this assay, the chromatographic properties of paper are leveraged to perform discrimination within the substrate itself. As a test case, this assay is then used to perform duplex detection of the Methicillin-resistant Staphylococcus aureus (MRSA) genes mecA and femB, two genes which confer antibiotic resistance on MRSA. Finally, we explore statistical multiplexing methods to enable this assay to be applied to perform highly-multiplexed detection gene targets (5+), and demonstrate the differentiation of these samples using partial least-squares regression (PLS). By averaging the signal over a region of the SERS substrate, substrate variability was mitigated allowing effective identification and differentiation, even for the complex spectra from highly multiplexed samples which were impossible to visually analyze.