Rapid detection of SARS-CoV-2 RNA in saliva via Cas13.

Rapid nucleic acid testing is central to infectious disease surveillance. Here, we report an assay for rapid COVID-19 testing and its implementation in a prototype microfluidic device. The assay, which we named DISCoVER (for diagnostics with coronavirus enzymatic reporting), involves extraction-free sample lysis via shelf-stable and low-cost reagents, multiplexed isothermal RNA amplification followed by T7 transcription, and Cas13-mediated cleavage of a quenched fluorophore. The device consists of a single-use gravity-driven microfluidic cartridge inserted into a compact instrument for automated running of the assay and readout of fluorescence within 60 min. DISCoVER can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in saliva with a sensitivity of 40 copies µl-1, and was 94% sensitive and 100% specific when validated (against quantitative PCR) using total RNA extracted from 63 nasal-swab samples (33 SARS-CoV-2-positive, with cycle-threshold values of 13-35). The device correctly identified all tested clinical saliva samples (10 SARS-CoV-2-positive out of 13, with cycle-threshold values of 23-31). Rapid point-of-care nucleic acid testing may broaden the use of molecular diagnostics.

Accelerated RNA detection using tandem CRISPR nucleases.

Direct, amplification-free detection of RNA has the potential to transform molecular diagnostics by enabling simple on-site analysis of human or environmental samples. CRISPR-Cas nucleases offer programmable RNA-guided RNA recognition that triggers cleavage and release of a fluorescent reporter molecule, but long reaction times hamper their detection sensitivity and speed. Here, we show that unrelated CRISPR nucleases can be deployed in tandem to provide both direct RNA sensing and rapid signal generation, thus enabling robust detection of ~30 molecules per µl of RNA in 20 min. Combining RNA-guided Cas13 and Csm6 with a chemically stabilized activator creates a one-step assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA extracted from respiratory swab samples with quantitative reverse transcriptase PCR (qRT-PCR)-derived cycle threshold (Ct) values up to 33, using a compact detector. This Fast Integrated Nuclease Detection In Tandem (FIND-IT) approach enables sensitive, direct RNA detection in a format that is amenable to point-of-care infection diagnosis as well as to a wide range of other diagnostic or research applications.

Accelerated RNA detection using tandem CRISPR nucleases.

Direct, amplification-free detection of RNA has the potential to transform molecular diagnostics by enabling simple on-site analysis of human or environmental samples. CRISPR-Cas nucleases offer programmable RNA-guided recognition of RNA that triggers cleavage and release of a fluorescent reporter molecule1,2, but long reaction times hamper sensitivity and speed when applied to point-of-care testing. Here we show that unrelated CRISPR nucleases can be deployed in tandem to provide both direct RNA sensing and rapid signal generation, thus enabling robust detection of ~30 RNA copies/microliter in 20 minutes. Combining RNA-guided Cas13 and Csm6 with a chemically stabilized activator creates a one-step assay that detected SARS-CoV-2 RNA from nasopharyngeal samples with PCR-derived Ct values up to 29 in microfluidic chips, using a compact imaging system. This Fast Integrated Nuclease Detection In Tandem (FIND-IT) approach enables direct RNA detection in a format amenable to point-of-care infection diagnosis, as well as to a wide range of other diagnostic or research applications.

Rapid, point-of-care molecular diagnostics with Cas13.

Rapid nucleic acid testing is a critical component of a robust infrastructure for increased disease surveillance. Here, we report a microfluidic platform for point-of-care, CRISPR-based molecular diagnostics. We first developed a nucleic acid test which pairs distinct mechanisms of DNA and RNA amplification optimized for high sensitivity and rapid kinetics, linked to Cas13 detection for specificity. We combined this workflow with an extraction-free sample lysis protocol using shelf-stable reagents that are widely available at low cost, and a multiplexed human gene control for calling negative test results. As a proof-of-concept, we demonstrate sensitivity down to 40 copies/µL of SARS-CoV-2 in unextracted saliva within 35 minutes, and validated the test on total RNA extracted from patient nasal swabs with a range of qPCR Ct values from 13-35. To enable sample-to-answer testing, we integrated this diagnostic reaction with a single-use, gravity-driven microfluidic cartridge followed by real-time fluorescent detection in a compact companion instrument. We envision this approach for Diagnostics with Coronavirus Enzymatic Reporting (DISCoVER) will incentivize frequent, fast, and easy testing.

Amplification-free detection of SARS-CoV-2 with CRISPR-Cas13a and mobile phone microscopy.

The December 2019 outbreak of a novel respiratory virus, SARS-CoV-2, has become an ongoing global pandemic due in part to the challenge of identifying symptomatic, asymptomatic, and pre-symptomatic carriers of the virus. CRISPR diagnostics can augment gold-standard PCR-based testing if they can be made rapid, portable, and accurate. Here, we report the development of an amplification-free CRISPR-Cas13a assay for direct detection of SARS-CoV-2 from nasal swab RNA that can be read with a mobile phone microscope. The assay achieved ∼100 copies/µL sensitivity in under 30 min of measurement time and accurately detected pre-extracted RNA from a set of positive clinical samples in under 5 min. We combined crRNAs targeting SARS-CoV-2 RNA to improve sensitivity and specificity and directly quantified viral load using enzyme kinetics. Integrated with a reader device based on a mobile phone, this assay has the potential to enable rapid, low-cost, point-of-care screening for SARS-CoV-2.

A Smartphone-Based Tool for Rapid, Portable, and Automated Wide-Field Retinal Imaging.

PURPOSE: High-quality, wide-field retinal imaging is a valuable method for screening preventable, vision-threatening diseases of the retina. Smartphone-based retinal cameras hold promise for increasing access to retinal imaging, but variable image quality and restricted field of view can limit their utility. We developed and clinically tested a smartphone-based system that addresses these challenges with automation-assisted imaging. METHODS: The system was designed to improve smartphone retinal imaging by combining automated fixation guidance, photomontage, and multicolored illumination with optimized optics, user-tested ergonomics, and touch-screen interface. System performance was evaluated from images of ophthalmic patients taken by nonophthalmic personnel. Two masked ophthalmologists evaluated images for abnormalities and disease severity. RESULTS: The system automatically generated 100° retinal photomontages from five overlapping images in under 1 minute at full resolution (52.3 pixels per retinal degree) fully on-phone, revealing numerous retinal abnormalities. Feasibility of the system for diabetic retinopathy (DR) screening using the retinal photomontages was performed in 71 diabetics by masked graders. DR grade matched perfectly with dilated clinical examination in 55.1% of eyes and within 1 severity level for 85.2% of eyes. For referral-warranted DR, average sensitivity was 93.3% and specificity 56.8%. CONCLUSIONS: Automation-assisted imaging produced high-quality, wide-field retinal images that demonstrate the potential of smartphone-based retinal cameras to be used for retinal disease screening. TRANSLATIONAL RELEVANCE: Enhancement of smartphone-based retinal imaging through automation and software intelligence holds great promise for increasing the accessibility of retinal screening.

Cellular softening mediates leukocyte demargination and trafficking, thereby increasing clinical blood counts.

Leukocytes normally marginate toward the vascular wall in large vessels and within the microvasculature. Reversal of this process, leukocyte demargination, leads to substantial increases in the clinical white blood cell and granulocyte count and is a well-documented effect of glucocorticoid and catecholamine hormones, although the underlying mechanisms remain unclear. Here we show that alterations in granulocyte mechanical properties are the driving force behind glucocorticoid- and catecholamine-induced demargination. First, we found that the proportions of granulocytes from healthy human subjects that traversed and demarginated from microfluidic models of capillary beds and veins, respectively, increased after the subjects ingested glucocorticoids. Also, we show that glucocorticoid and catecholamine exposure reorganizes cellular cortical actin, significantly reducing granulocyte stiffness, as measured with atomic force microscopy. Furthermore, using simple kinetic theory computational modeling, we found that this reduction in stiffness alone is sufficient to cause granulocyte demargination. Taken together, our findings reveal a biomechanical answer to an old hematologic question regarding how glucocorticoids and catecholamines cause leukocyte demargination. In addition, in a broader sense, we have discovered a temporally and energetically efficient mechanism in which the innate immune system can simply alter leukocyte stiffness to fine tune margination/demargination and therefore leukocyte trafficking in general. These observations have broad clinically relevant implications for the inflammatory process overall as well as hematopoietic stem cell mobilization and homing.

Point-of-care quantification of blood-borne filarial parasites with a mobile phone microscope.

Parasitic helminths cause debilitating diseases that affect millions of people in primarily low-resource settings. Efforts to eliminate onchocerciasis and lymphatic filariasis in Central Africa through mass drug administration have been suspended because of ivermectin-associated serious adverse events, including death, in patients infected with the filarial parasite Loa loa. To safely administer ivermectin for onchocerciasis or lymphatic filariasis in regions co-endemic with L. loa, a strategy termed "test and (not) treat" has been proposed whereby those with high levels of L. loa microfilariae (>30,000/ml) that put them at risk for life-threatening serious adverse events are identified and excluded from mass drug administration. To enable this, we developed a mobile phone-based video microscope that automatically quantifies L. loa microfilariae in whole blood loaded directly into a small glass capillary from a fingerprick without the need for conventional sample preparation or staining. This point-of-care device automatically captures and analyzes videos of microfilarial motion in whole blood using motorized sample scanning and onboard motion detection, minimizing input from health care workers and providing a quantification of microfilariae per milliliter of whole blood in under 2 min. To validate performance and usability of the mobile phone microscope, we tested 33 potentially Loa-infected patients in Cameroon and confirmed that automated counts correlated with manual thick smear counts (94% specificity; 100% sensitivity). Use of this technology to exclude patients from ivermectin-based treatment at the point of care in Loa-endemic regions would allow resumption/expansion of mass drug administration programs for onchocerciasis and lymphatic filariasis in Central Africa.

Multi-Contrast Imaging and Digital Refocusing on a Mobile Microscope with a Domed LED Array.

We demonstrate the design and application of an add-on device for improving the diagnostic and research capabilities of CellScope--a low-cost, smartphone-based point-of-care microscope. We replace the single LED illumination of the original CellScope with a programmable domed LED array. By leveraging recent advances in computational illumination, this new device enables simultaneous multi-contrast imaging with brightfield, darkfield, and phase imaging modes. Further, we scan through illumination angles to capture lightfield datasets, which can be used to recover 3D intensity and phase images without any hardware changes. This digital refocusing procedure can be used for either 3D imaging or software-only focus correction, reducing the need for precise mechanical focusing during field experiments. All acquisition and processing is performed on the mobile phone and controlled through a smartphone application, making the computational microscope compact and portable. Using multiple samples and different objective magnifications, we demonstrate that the performance of our device is comparable to that of a commercial microscope. This unique device platform extends the field imaging capabilities of CellScope, opening up new clinical and research possibilities.

Low-cost mobile phone microscopy with a reversed mobile phone camera lens.

The increasing capabilities and ubiquity of mobile phones and their associated digital cameras offer the possibility of extending low-cost, portable diagnostic microscopy to underserved and low-resource areas. However, mobile phone microscopes created by adding magnifying optics to the phone's camera module have been unable to make use of the full image sensor due to the specialized design of the embedded camera lens, exacerbating the tradeoff between resolution and field of view inherent to optical systems. This tradeoff is acutely felt for diagnostic applications, where the speed and cost of image-based diagnosis is related to the area of the sample that can be viewed at sufficient resolution. Here we present a simple and low-cost approach to mobile phone microscopy that uses a reversed mobile phone camera lens added to an intact mobile phone to enable high quality imaging over a significantly larger field of view than standard microscopy. We demonstrate use of the reversed lens mobile phone microscope to identify red and white blood cells in blood smears and soil-transmitted helminth eggs in stool samples.

Quantitative imaging with a mobile phone microscope.

Use of optical imaging for medical and scientific applications requires accurate quantification of features such as object size, color, and brightness. High pixel density cameras available on modern mobile phones have made photography simple and convenient for consumer applications; however, the camera hardware and software that enables this simplicity can present a barrier to accurate quantification of image data. This issue is exacerbated by automated settings, proprietary image processing algorithms, rapid phone evolution, and the diversity of manufacturers. If mobile phone cameras are to live up to their potential to increase access to healthcare in low-resource settings, limitations of mobile phone-based imaging must be fully understood and addressed with procedures that minimize their effects on image quantification. Here we focus on microscopic optical imaging using a custom mobile phone microscope that is compatible with phones from multiple manufacturers. We demonstrate that quantitative microscopy with micron-scale spatial resolution can be carried out with multiple phones and that image linearity, distortion, and color can be corrected as needed. Using all versions of the iPhone and a selection of Android phones released between 2007 and 2012, we show that phones with greater than 5 MP are capable of nearly diffraction-limited resolution over a broad range of magnifications, including those relevant for single cell imaging. We find that automatic focus, exposure, and color gain standard on mobile phones can degrade image resolution and reduce accuracy of color capture if uncorrected, and we devise procedures to avoid these barriers to quantitative imaging. By accommodating the differences between mobile phone cameras and the scientific cameras, mobile phone microscopes can be reliably used to increase access to quantitative imaging for a variety of medical and scientific applications.

Mobile digital fluorescence microscopy for diagnosis of tuberculosis.

Access to sputum smear microscopy in high-tuberculosis (TB)-burden regions is limited by a scarcity of microscopes and experienced technicians. We evaluated the accuracy of CellScope, a novel digital fluorescence microscope that may expand access to microscopy. The study utilized smear microscopy slides prepared from sputum specimens submitted by consecutive adults with ≥ 2 weeks of cough who were admitted to Mulago Hospital (Kampala, Uganda). Conventional light-emitting diode (LED) fluorescence microscopy (FM) and mycobacterial culture were performed by experienced technicians. Two U.S.-based postgraduate researchers without prior microscopy experience restained, imaged, and interpreted the slides using CellScope. We assessed whether sensitivity and specificity of CellScope-based LED FM was noninferior to conventional LED FM by using a preselected margin of inferiority of 15%. Of 525 patients included, 72% were HIV seropositive and 39% had culture-confirmed TB. The proportions of positive results were similar with CellScope and conventional LED FM (34% versus 32%, respectively; P = 0.32), and agreement was substantial. CellScope accuracy was within the noninferiority margin for both sensitivity (63% versus 70%; difference, -7%; 95% confidence interval [CI], -13% to -1%) and specificity (85% versus 92%; difference, -7%; 95% CI, -12% to -3%). A subanalysis of 43 slides evaluated by each CellScope reader found substantial interreader reliability (custom-weighted kappa, 0.65) and variable intrareader reliability (custom-weighted kappa, 0.11 versus 0.48). CellScope offers promise for expanding microscopy services. Future studies should evaluate the device when operated by health workers in low-resource settings, the feasibility of image transmission and analysis by experienced microscopists, and the accuracy of automated image analysis algorithms.

Automated tuberculosis diagnosis using fluorescence images from a mobile microscope.

In low-resource areas, the most common method of tuberculosis (TB) diagnosis is visual identification of rod-shaped TB bacilli in microscopic images of sputum smears. We present an algorithm for automated TB detection using images from digital microscopes such as CellScope, a novel, portable device capable of brightfield and fluorescence microscopy. Automated processing on such platforms could save lives by bringing healthcare to rural areas with limited access to laboratory-based diagnostics. Our algorithm applies morphological operations and template matching with a Gaussian kernel to identify candidate TB-objects. We characterize these objects using Hu moments, geometric and photometric features, and histograms of oriented gradients and then perform support vector machine classification. We test our algorithm on a large set of CellScope images (594 images corresponding to 290 patients) from sputum smears collected at clinics in Uganda. Our object-level classification performance is highly accurate, with average precision of 89.2% +/- 2.1%. For slide-level classification, our algorithm performs at the level of human readers, demonstrating the potential for making a significant impact on global healthcare.

Mobile phone based clinical microscopy for global health applications.

Light microscopy provides a simple, cost-effective, and vital method for the diagnosis and screening of hematologic and infectious diseases. In many regions of the world, however, the required equipment is either unavailable or insufficiently portable, and operators may not possess adequate training to make full use of the images obtained. Counterintuitively, these same regions are often well served by mobile phone networks, suggesting the possibility of leveraging portable, camera-enabled mobile phones for diagnostic imaging and telemedicine. Toward this end we have built a mobile phone-mounted light microscope and demonstrated its potential for clinical use by imaging P. falciparum-infected and sickle red blood cells in brightfield and M. tuberculosis-infected sputum samples in fluorescence with LED excitation. In all cases resolution exceeded that necessary to detect blood cell and microorganism morphology, and with the tuberculosis samples we took further advantage of the digitized images to demonstrate automated bacillus counting via image analysis software. We expect such a telemedicine system for global healthcare via mobile phone -- offering inexpensive brightfield and fluorescence microscopy integrated with automated image analysis -- to provide an important tool for disease diagnosis and screening, particularly in the developing world and rural areas where laboratory facilities are scarce but mobile phone infrastructure is extensive.