Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip

Abstract

Respiratory viruses, especially coronaviruses, have resulted in worldwide pandemics in the past couple of decades. Saliva-based paper microfluidic assays represent an opportunity for noninvasive and rapid screening, yet both the sample matrix and test method come with unique challenges. In this work, we demonstrated the rapid and sensitive detection of SARS-CoV-2 from saliva samples, which could be simpler and more comfortable for patients than existing methods. Furthermore, we systematically investigated the components of saliva samples that affected assay performance. Using only a smartphone, an antibody-conjugated particle suspension, and a paper microfluidic chip, we made the assay user-friendly with minimal processing. Unlike the previously established flow rate assays that depended solely on the flow rate or distance, this unique assay analyzes the flow profile to determine infection status. Particle-target immunoagglutination changed the surface tension and subsequently the capillary flow velocity profile. A smartphone camera automatically measured the flow profile using a Python script, which was not affected by ambient light variations. The limit of detection (LOD) was 1 fg/μL SARS-CoV-2 from 1% saliva samples and 10 fg/μL from simulated saline gargle samples (15% saliva and 0.9% saline). This method was highly specific as demonstrated using influenza A/H1N1. The sample-to-answer assay time was <15 min, including <1-min capillary flow time. The overall accuracy was 89% with relatively clean clinical saline gargle samples. Despite some limitations with turbid clinical samples, this method presents a potential solution for rapid mass testing techniques during any infectious disease outbreak as soon as the antibodies become available.

Keywords: COVID-19; Capillary action; Particle immunoagglutination; Respiratory virus; Smartphone-based biosensor.

Fig. 1

Flow profile assay of SARS-CoV-2 on a paper-based microfluidic chip. (A) Paper-based microfluidic chip design containing green edge and three red squares for recognizing the chip area in automated flow distance measurement. (B) The chip holder and the chip lock. (C) A paper-based microfluidic chip was placed into a chip holder to flatten the chip. (D) 4 μL of sample was loaded directly onto the square inlet (top) of each channel and dried for 10 min. (E) A smartphone camera was held just above the chip to view the chip area and start recording the video. (F) 4 μL of Ab-particles were loaded, and the liquid flow on the paper microfluidic chip was recorded with the smartphone camera.

Fig. 2

Video processing algorithm. Python code was developed to automatically obtain the flow distance over time. (A) The red squares were detected, and each frame is rotated for orientation correction. (B) The green edge was recognized and cropped. (C) The cropped area was analyzed to generate an intensity histogram plot. Using appropriate thresholding, the liquid flow was recognized on paper. (D) The flow on each channel was read separately by recognizing it as the black pixels increasing along the vertical centerline. (E) Flow distance vs. time profile of mAb-particles on the preloaded 1000 fg/μL SARS-CoV-2 spiked sample. (F) Flow distance vs. time profile of pAb-particles on the preloaded 1000 fg/μL SARS-CoV-2 spiked sample.

Fig. 3

Assay LOD and Specificity. NC indicates negative control and * shows p < 0.05 between sample and NC using one-tailed student's t-test with unequal variance. Error bars represent standard error. (A) Flow distances at 30 s on the paper microfluidic chips preloaded with SARS-CoV-2 spiked in 1% v/v human pooled saliva, using polyclonal antibody conjugated particles at 0.04 μg/μL (n = 3). (B) Flow distances at 30 s on the paper microfluidic chips preloaded with SARS-CoV-2 spiked in simulated saline gargle samples (∼15% v/v saliva and 0.9% saline), using polyclonal antibody conjugated particles at 0.04 μg/μL, with the addition of 0.5% w/v Tween 20 (n = 3). (C) Specificity test results with 1 pg/μL SARS-CoV-2 and influenza A/H1N1 (Ct values of 25–28) spiked in 1% v/v and 10% v/v saliva in 0.9% saline using the pAb-particles, shown together with the no target control samples (1% or 10% saliva in 0.9% saline) (n = 3).

Fig. 4

Turbidity assessment of clinical saline gargle samples. Error bars represent standard error. (A) Photographs of negative and positive clinical saline gargle samples, obtained from human subjects. The normalized turbidity was determined by comparing the pixel intensities of the sample tubes against the black background. Red boxes indicate samples that were determined to be turbid using the procedure described in part B. (B) Using the normalized (to empty tube) turbidity, all clinical samples were classified into two categories, turbid and clear, using the threshold value of 1.41. Note: while all samples were classified in this manner, some could not undergo all subsequent testing due to low sample volume. (C) Surface tension measurements showed a decreasing trend with increased turbidity. (D) Total protein concentration of samples according to the Bradford assay. Turbid and clear samples showed no difference in total protein concentration, but SARS-CoV-2 positive samples had a higher (not significant) total protein concentration than negative samples. (n = 5 for negative clear, n = 3 for negative turbid, n = 6 for positive clear, and n = 4 for positive turbid). (E) Samples with a last oral intake (LOI) of 10–30 min prior to sample acquisition (n = 6) had higher turbidity than samples with a longer time since LOI (60+ min; n = 10), and the difference was statistically significant (p < 0.05). Average values are shown in the bar chart. (F) The time to constant velocity (n = 2) and surface tension of no toothpaste vs. toothpaste-added (10 mg/mL) NC samples, along with photos of the samples. Surface tension was measured at 0, 2, 4, 6, 8, and 10 s and the stabilized final value was chosen (hence no error bar). The accuracy of surface tension measurement is less than 1 mN/mm.

Fig. 5

Flow profile analysis of clinical saline gargle samples. (A–B) Flow distance profiles of representative positive and negative clinical samples, respectively. (C–D) Flow velocity profiles of the same, numerically differentiated from A and B. (E) The time to reach constant velocity (as demonstrated in A-B) for all clear negative and positive samples (n = 18). (F) Time to constant velocity for positive clear samples (n = 9) against the cycle threshold (Ct) values obtained with RT-qPCR. The lower the Ct value, the higher the virus titer in the sample.

Fig. 6

How particle immunoagglutination affects the flow distance and velocity profiles. (A) The flow distances at 30 s are longer with the positive samples (orange boxes) than the negative samples (blue boxes). (B) With no virus present, the singlet Ab-particles (green) quickly diffuse to the wetting front, lowering the surface tension and the flow velocity. Nitrocellulose fibers are colored in light orange and saliva proteins in dark orange. (C) With virus present (blue), immunoagglutination occurs, creating larger and heavier particle clusters, leaving very few singlet Ab-particles diffusing to the wetting front. (D) The Ab-particles on the negative sample are mostly in the singlet form and take more time to reach constant velocity (top), while fewer singlet Ab-particles on the positive sample are able to reach the flow interface due to immunoagglutination, so it takes less time to reach constant velocity (bottom).