We demonstrate an automatic, high-throughput and high-sensitivity particle aggregation-based sensor that uses wide-field, compact and cost-effective lens-less microscopy, powered by deep neural networks. In this method, the post-reaction assay is imaged by a snapshot hologram over a wide field-of-view (20mm²). Using a deep learning-based holographic reconstruction, all the particle clusters are simultaneously reconstructed in ~30s. Using this method, we demonstrated accurate and rapid readout of an immunoassay to detect herpes simplex virus, which affects >50% of the adults in US, and achieved a clinically-relevant detection limit (~ 5viruses/µL). This method can be broadly used to quantify other particle-aggregation based immunoassays.
Development of portable and cost-effective optical imaging devices is essential for quantification of molecular bioassays at the point of care (POC). Mobile phone-based microscopy tools have shown great potential as biomedical reader platforms due to their small size, large distribution volume, and constantly improving optical properties. However, the optical detection sensitivity remains a challenge to further improve the diagnostic capabilities of microscopy and sensing devices based on mobile-phones. Here, we demonstrate a simple strategy to enhance the signal intensity of a smartphone fluorescence microscope by approximately an order of magnitude using surface-enhanced fluorescence (SEF) created by a thin silver film. This plasmonics-enhanced smartphone microscopy platform relies on an opto-mechanical attachment based on the Kretschmann configuration, where the sample is placed on a silver-coated glass coverslip and excited by a laser diode from the backside through a glass hemisphere. The fluorescence enhancement effect was systematically optimized by tuning the metal film thickness, spacer distance, excitation angle, and polarization, and experimentally validated by comparison to theoretical simulations. With this mobile device, single fluorescent beads as small as 50 nm and individual quantum dots (ca. 20 nm dia.) were detected. We further quantified the sensitivity limit of this mobile platform to be around 80 fluorophores per diffraction-limited spot by imaging DNA origami based brightness standards labeled with different numbers of fluorophores. We believe that this SEF-based mobile microscopy platform opens up various new opportunities for POC diagnostics and sensing applications in resource-limited-settings.
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.
Enzyme-linked immunosorbent assay (ELISA) in a microplate format has been a gold standard first-line clinical test for diagnosis of various diseases including infectious diseases. However, this technology requires a relatively large and expensive multi-well scanning spectrophotometer to read and quantify the signal from each well, hindering its implementation in resource-limited-settings. Here, we demonstrate a cost-effective and handheld smartphone-based colorimetric microplate reader for rapid digitization and quantification of immunoserology-related ELISA tests in a conventional 96-well plate format at the point of care (POC). This device consists of a bundle of 96 optical fibers to collect the transmitted light from each well of the microplate and direct all the transmission signals from the wells onto the camera of the mobile-phone. Captured images are then transmitted to a remote server through a custom-designed app, and both quantitative and qualitative diagnostic results are returned back to the user within ~1 minute per 96-well plate by using a machine learning algorithm. We tested this mobile-phone based micro-plate reader in a clinical microbiology lab using FDA-approved mumps IgG, measles IgG, and herpes simplex virus IgG (HSV-1 and HSV-2) ELISA tests on 1138 remnant patient samples (roughly 50% training and 50% testing), and achieved an overall accuracy of ~99% or higher for each ELISA test. This handheld and cost-effective platform could be immediately useful for large-scale vaccination monitoring in low-infrastructure settings, and also for other high-throughput disease screening applications at POC.
The development of sensitive optical microscopy methods for the detection of single DNA molecules has become an active research area which cultivates various promising applications including point-of-care (POC) genetic testing and diagnostics. Direct visualization of individual DNA molecules usually relies on sophisticated optical microscopes that are mostly available in well-equipped laboratories. For POC DNA testing/detection, there is an increasing need for the development of new single DNA imaging and sensing methods that are field-portable, cost-effective, and accessible for diagnostic applications in resource-limited or field-settings. For this aim, we developed a mobile-phone integrated fluorescence microscopy platform that allows imaging and sizing of single DNA molecules that are stretched on a chip. This handheld device contains an opto-mechanical attachment integrated onto a smartphone camera module, which creates a high signal-to-noise ratio dark-field imaging condition by using an oblique illumination/excitation configuration. Using this device, we demonstrated imaging of individual linearly stretched λ DNA molecules (48 kilobase-pair, kbp) over 2 mm2 field-of-view. We further developed a robust computational algorithm and a smartphone app that allowed the users to quickly quantify the length of each DNA fragment imaged using this mobile interface. The cellphone based device was tested by five different DNA samples (5, 10, 20, 40, and 48 kbp), and a sizing accuracy of <1 kbp was demonstrated for DNA strands longer than 10 kbp. This mobile DNA imaging and sizing platform can be very useful for various diagnostic applications including the detection of disease-specific genes and quantification of copy-number-variations at POC settings.
We introduce a fluorescent imaging method that is capable of detecting fluorescent micro-particles over an ultra-wide field of view of 19 cm × 28 cm using a modified flatbed scanner. We added a custom-designed absorbing emission filter, a computer controlled two dimensional LED array, and modified the driver of the scanner to maximize the sensitivity, exposure time, and gain for fluorescent detection of micro-objects. This high-throughput fluorescent imaging device used in conjunction with a microfluidic sample holder enables rapid screening of fluorescent micro-objects inside more than 2.2mL of optically dense media (i.e., whole blood) within 5 minutes. The device is sensitive enough to detect fluorescently labeled cells, and generates images that have an effective pixel count of 2.2 Giga-pixels.