key: cord-0933563-fqg2ld7b
authors: Gupta, Rohit; Gupta, Prashant; Wang, Zheyu; Seth, Anushree; Morrissey, Jeremiah; George, Ige; Gandra, Sumanth; Storch, Gregory; Parikh, Bijal; Genin, Guy; Singamaneni, Srikanth
title: Plasmon-enhanced Quantitative Lateral Flow Assay for Femtomolar Detection of SARS-CoV-2 Antibodies and Antigens
date: 2022-02-21
journal: Res Sq
DOI: 10.21203/rs.3.rs-1258688/v1
sha: 48faa9305a6afbfec05f8441dc761a8d5246c233
doc_id: 933563
cord_uid: fqg2ld7b

Lateral flow assays (LFAs) are the cornerstone of point-of-care diagnostics. Although rapid and inexpensive, they are 1000-fold less sensitive than laboratory-based tests and cannot be used for definitive negative diagnosis. Here, we overcome this fundamental limitation by employing plasmonically-enhanced nanoscale colorimetric and fluorescent labels. Plasmonic LFAs (p-LFAs) enabled ultrasensitive detection and quantification of low abundance analytes, without compromising the direct visual detection of conventional LFAs. Dynamic ranges and limits of detection were up to 100-fold superior to “gold standard” ELISA (enzyme-linked immunosorbent assay). p-LFAs had sample-to-answer time of 20 min, compared to 4 hours for ELISA, while achieving over 95% analytical sensitivity and 100% analytical specificity for antibodies and antigens of SARS-CoV-2 in human specimens. We also demonstrate that the p-LFAs enable quantitative detection of the target analytes in a standard-free manner. p-LFAs offer potential as a broadly adaptable point-of-care diagnostic platform that outperforms standard laboratory tests in sensitivity, speed, dynamic range, ease of use, and cost.

Lateral ow (immuno)assays (LFAs) are amongst the simplest, fastest, and cheapest point-of-care (POC) diagnostic platforms, and offer broad potential for population-level screening for disease. [1] [2] However, this potential has not yet been fully achieved. Although numerous LFAs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies 3-5 and antigens [6] [7] have been introduced, none have sensitivity and quantitation comparable to laboratory-based diagnostics such as real-time reverse transcription polymerase chain reaction (RT-PCR) and enzyme-linked immunosorbent assay (ELISA), which constrains their widespread use. [8] [9] [10] In general, conventional colorimetric-LFAs are ~1000-fold less sensitive than these standard laboratory tests, [11] [12] and diagnosis using LFAs requires an additional con rmatory laboratory-based test to correctly establish negative results. Colorimetric-LFAs offer limited quanti cation ability owing to the limited color change with respect to variation of the target analyte's concentration. 13 The COVID-19 pandemic highlights the need for improved LFAs for precise and rapid clinical diagnoses, mass screenings and epidemiological studies. [14] [15] RT-PCR [16] [17] and direct antigen tests [18] [19] have been the mainstay for diagnosis of COVID-19, and serological assays are important for determination of infection stage and vaccine e cacy, and epidemiological studies. 3, [20] [21] These diagnostic platforms are available only in quali ed microbiology laboratories and remain expert-dependent, labor-intensive, and time-intensive, limitations that have precluded conduction of the millions of tests per day needed during epidemiological surges. [22] [23] Therefore, a critical need exists for diagnostic and screening tools that are not only as accurate as laboratory-based assays, but also rapid, easy-to-use, inexpensive, readily available (e.g., home-based and POC), and scalable for rapid population-level screening.

Efforts to improve bioanalytical performance of LFAs have included using uorescent molecules or quantum dots as reporter elements. [24] [25] Although uorescent reporters improve quanti cation, their relatively weak signal intensity limits their sensitivity and point-of-care diagnostic utility, and their low light absorption compared to conventional colloidal gold nanoparticles (AuNPs) 26 precludes the direct visual detection available in conventional LFAs, and moreover requires use of external LFA readers or powerful excitation light sources. These limit the utility of uorescent LFAs in mass screening and resource-limited settings. 10 We envision a "bimodal" LFA in which an initial screening can be performed with a visual test, and subsequent quantitative testing can be performed when needed on the same LFA strip using a uorescence reader. To achieve this, we employed an ultrabright uorescent nanoconstruct that we have recently introduced, 27 called plasmonic-uor, as a bimodal colorimetric and uorescent reporter in LFAs ( Figure 1A ). These nanoconstructs harness plasmon-enhanced uorescence [28] [29] [30] [31] [32] to achieve nearly 7000fold brighter uorescence signal compared to conventional molecular uorophores. We modi ed plasmonic-uors with detection antibodies and applied them to enable rapid and ultrasensitive colorimetric and uorescent detection of analytes, using human IL-6 (LOD: 93 fg ml −1 ), SARS-CoV-2 S1

(subunit of the spike protein) antibodies (LOD: 185 pg ml −1 ), and SARS-CoV-2 antigen (nucleocapsid) protein (LOD: 212 pg ml −1 ). We validated the clinical e cacy of the plasmonic-uors-based LFAs (p-LFAs) for COVID-19 by testing plasma samples for SARS-CoV-2 S1 antibodies and nasopharyngeal swab samples for nucleocapsid protein SARS-CoV-2 variants-of-concern, respectively, and achieved high analytical speci city (100%) and sensitivity (~97%). Signi cantly, this technology can also be employed as an alternative to laboratory-based test for the diagnosis of clinically relevant pathogenic infections and possible future pandemics.

2.1 Using plasmonic-uors in LFAs increases sensitivity over AuNPs by 10000-fold Plasmonic enhancement was rst applied to overcome three fundamental limitations of the 30-40 nm AuNPs used as conventional colorimetric labels in LFAs. AuNPs have low capture rate (<5%), low signalto-background ratio, and thus relatively low sensitivity. [33] [34] Even with use of 100 nm AuNPs, shown recently to improve LFA sensitivity, 35 these problems persist. Because of these three limitations, color changes in AuNP-based LFAs are limited to qualitative analysis or simply a binary output, indicating the presence or absence of the target analyte.

To assess whether plasmonic-uors could overcome these limitations, we compared their performance to AuNPs on a nitrocellulose membrane. We set out to determine the minimum number of AuNPs and plasmonic-uors required to produce a detectable visible or uorescence signal. When serially diluted AuNPs ( Figure 1B ) and plasmonic-uors ( Figure 1C ) of known particle concentration were drop-casted onto nitrocellulose membrane, accumulations of approximately ~10 6 nanoparticles were needed to produce a discernable visible signal ( Figure 1D and S1). However, only ~10 2 plasmonic-uors were required to produce a detectable uorescence signal ( Figure 1E and S2).

Plasmonic-uors exhibited colorimetric signal nearly identical to that of AuNPs ( Figure S3 ). The colorimetric signal enabled qualitative visual detection (by naked eye), obviating the need for specialized read-out equipment at a relatively high concentration of the target analyte, while the uorescence signal enabled ultrasensitive detection and quanti cation of low abundance analytes. Thus, plasmonic-uor function as a bimodal nanolabel (colorimetric+ uorescent) and offers ultrasensitive detection in a biological detection assay representative of LFAs.

Next, to compare the performance of plasmonic-uors and AuNPs in LFA format, we employed the wellcharacterized biotin-streptavidin conjugate pairing, known to exhibit extremely high binding a nity. 36 Both AuNPs and plasmonic-uors were functionalized with streptavidin and biotinylated bovine serum albumin (BSA) was used as a capture-ligand. LFA strips were then subjected to different known concentrations of streptavidin-conjugated AuNPs and plasmonic-uors for 20 min ( Figure S4 ). Nanolabels ows along the nitrocellulose membrane by capillary force and gets captured by the captureligand, leading to the accumulation of nanoparticles at the test spot. Accumulation of su cient number of nanolabels converts the color at the test site to red, indicating a positive result and the presence of the target analyte. The average greyscale intensity of the colorimetric signal at the test site with AuNPs and the uorescence signal with plasmonic-uors monotonically increased with the concentration of the nanolabels ( Figure 1G and 1H). Signi cantly, for both AuNPs and PFs, approximately ~10 7 nanoparticles are needed to produce a discernable visible signal, however, only ~10 3 PFs are enough to produce a detectable uorescence signal. The four-order magnitude lower concentration threshold for a detectable signal with plasmonic-uors compared to AuNPs in the LFA format is consistent with the drop-casting approach discussed above. These results manifest the fundamental basis that plasmonic-uors can serve as ultrabright nanolabels for ultrasensitive detection of target analytes in an LFA.

The bioanalytical performance of plasmonic LFAs can be further improved by tuning LFA parameters Next, we optimized the bioanalytical performance of LFA by tuning concentration of capture ligand and nanolabels. We employed biotin-streptavidin as a model system. Both AuNPs and plasmonic-uors were biotin functionalized, streptavidin and biotinylated BSA were utilized as target analyte and capture ligand, respectively (Figure 2A and S5) . It was observed that as the concentration of capture-ligand (i.e., biotinylated BSA) increased, both mean greyscale intensity and uorescence intensity of the test spot corresponding to AuNPs ( Figure 2B and S6) and plasmonic-uors ( Figure 2C and S7), respectively, increased. These results suggest that higher concentrations of capture-ligand results in better signal intensity. Further, as the number of nanolabels increased, both mean greyscale intensity and uorescence intensity of the test spot corresponding to AuNPs ( Figure 2D and S8) and plasmonic-uors ( Figure 2E and S9), respectively, increased, implying better signal intensity with higher number of nanolabels. However, in both cases, the background signal (signal from the LFA strip outside the capture spot) also increased with the number of nanolabels. Therefore, the optimum number of nanolabels for both AuNPs-based LFA and p-LFA was determined by subtracting the background signal from the test spot signal. As expected, the optimum number of plasmonic-uors (1.2 x 10 6 ) was four orders magnitude lower than the AuNPs (1.78 x 10 10 ).

Next, we compared the bioanalytical parameters (limit-of-detection (LOD), limit-of-quantitation (LOQ) and dynamic range) of biotin-streptavidin AuNPs-based LFA and p-LFA. It is worth noting that colorimetric signal, obtained from the 8-bit ImageJ processed images of LFA strips, from both AuNPs (Figures 2F) and plasmonic-uors (Figures 2G) exhibit similar LOD, suggesting no loss in visual detection capabilities in p-LFAs ( Figure S10 ). The LOD (de ned as mean + 3σ of the blank) of AuNPs-based LFA was calculated to be ~ 5 ng ml -1 ( Figure 2I ). In contrast, the uorescence signal from p-LFA (Figures 2H) enabled the detection down to 11 pg ml -1 ( Figure 2J , four-parameter logistic t), representing a 927-fold improvement in the LOD. The LOQ (de ned as mean + 10σ of the blank) of p-LFA is ~570-fold better than the LOQ of AuNPs-based LFA. Further, the uorescent component of plasmonic-uor augmented the dynamic range of the assay by three orders of magnitude. Therefore, owing to the ultrabright uorescence signal of the plasmonic-uors, the p-LFAs enable ultrasensitive detection of target analyte over a much broader range of analyte concentration.

Cytokines are small (5-26 kDa) proteins, involved in cell signaling and immuno-modulation and are critical indicators of health and disease. 37 Several diseases including cancer, sepsis, HIV, chronic in ammation and auto-immune diseases are known to be associated with dysregulation of immune system, leading to disruption of the subtle balance between pro-in ammatory and anti-in ammatory cytokines. [38] [39] The pro-in ammatory cytokines include IL-1 (interleukin-1), IL-6, IL-12, TNFα (tumor necrosis factor α) and IFNγ (interferon γ), while the anti-in ammatory cytokines include TGFβ (transforming growth factor β), IL-10 and IL-4. Rapid monitoring of the immune status by analyzing serum cytokines and early diagnosis of these diseases is essential for prompt clinical intervention and for inhibiting disease progression. Though few LFAs for IL-6 detection have been introduced recently, 40-41 none provide sensitivity and quantitation comparable to gold-standard ELISA. Therefore, we employed IL-6 as a model target analyte to investigate the applicability of our p-LFA.

Human IL-6 capture antibodies and sheep anti-immunoglobulin G (IgG) antibodies were immobilized on a nitrocellulose membrane to form test and control spots, respectively ( Figure 3A and S11). The LOD of AuNPs-based LFA ( Figure 3B ) was calculated to be ~ 100 pg ml −1 ( Figure 3C ). In contrast, the uorescence signal intensity obtained from p-LFA ( Figure 3D ) enabled the detection down to 93 fg ml −1 ( Figure 3E , four-parameter logistic t), which represents a 1075-fold improvement in the LOD compared with conventional AuNPs-based LFAs and signi cantly higher than the recently reported LFAs [40] [41] . The LOQ of p-LFA (300 fg ml −1 ) is ~1300-fold better than the LOQ of AuNPs-based LFA (400 pg ml −1 ). Further, the plasmonic-uor improved the dynamic range of the LFA by nearly three-order magnitude. The colorimetric signal from both AuNPs and p-LFA exhibited similar LODs, suggesting no loss in visual detection capabilities in p-LFAs ( Figure 3F , 3G and S12). Additionally, the uorescence signal from the plasmonic-uors enabled ultrasensitive detection and quantitative analysis over a much broader range of analyte concentration ( Figure 3E and 3H).

We also compared the sensitivity and LOD of p-LFA with standard ELISA and plasmonic-uor linked immunosorbent assay (p-FLISA) ( Figure S13 ) implemented on a microtiter plate. The LOD of p-LFA is nearly 30-fold lower compared to conventional sandwich ELISA (2.9 pg ml −1 ) and only 5-fold inferior to that of p-FLISA (16.8 fg ml −1 ) ( Figure 3I ). However, the sample-to-answer time for p-LFAs was 20 min whereas ELISA and p-FLISA require 4 h.

Next, to determine the quantitative detection ability of p-LFA, multiple IL-6 standard curves were acquired over a span of six months ( Figure S14 ). Using these standard curves, IL-6 concentration ranging from 1 pg ml −1 to 50 pg ml −1 were accurately quanti ed with less than 20% deviation ( Figure 3J and S15). The ability to accurately quantify the analyte concentration, which has not been reported with LFA platforms, ascertains that p-LFAs enable quantitative detection of target analyte in standard-free manner. Thus, p-LFAs overcome the long-standing limitation of LFAs -limited sensitivity, low accuracy and smaller analytical range compared to laboratory tests, and limited quantitation ability.

To assess the potential for clinical translation of our p-LFA, we next optimized it for detection of SARS-CoV-2 antibodies. A pressing need persists for sensitive, rapid and POC serological assays for SARS-CoV-2, both for epidemiological studies and for vaccine e cacy against SARS-CoV-2 studies. 3, 20 Several LFAs 3-4, 42 and other assay platforms 43 exist that employ SARS-CoV-2 spike protein as recognition element for detection of SARS-CoV-2 antibodies. Using p-LFA, our goal was to extend the sensitivity and limit of detection beyond the range possible with current assays, and into the range of ELISA.

Recombinant SARS-CoV-2 S1 subunit of spike protein was immobilized at the test spot and sheep IgG was used for control spot ( Figure 4A and S16). We rst determined the bioanalytical parameters of AuNPs-based LFA ( Figure 4B ) and to p-LFA ( Figure 4D ) for detection of SARS-CoV-2 S1 antibody. Using the colorimetric signal obtained from LFA strips, the LOD of AuNPs-based LFA was determined to be ~ 1.2 µg ml −1 ( Figure 4C ). In contrast, p-LFA exhibited an LOD of 185 pg ml −1 ( Figure 4E , four-parameter logistic t), which represents a nearly 6500-fold improvement. Further, as expected, the mean greyscale intensities obtained from both AuNPs and p-LFA exhibited similar sensitivity, suggesting no compromise in the visual detection capabilities ( Figure 4F , 4G and S17). However, the uorescence signal from plasmonic-uors enabled ultrasensitive detection and quantitative analysis over a much broader (3 to 4 orders of magnitude higher) range of analyte concentration ( Figure 4E and 4H). p-LFA displayed 165-fold improvement in LOD as compared to conventional sandwich ELISA and comparable LOD to p-FLISA ( Figure 4I ).

To assess the translational potential of p-LFAs, we tested 79 plasma samples obtained from COVID-19 positive individuals and 48 archived de-identi ed serum/plasma samples which were collected pre-COVID-19 (March-October 2019) under HRPO 201102546 44 for the presence of SARS-CoV-2 S1 antibodies. All 127 plasma samples were diluted 500-fold and tested using p-LFA. Out of 79 IgG positive samples (tested positive by ELISA), 76 were tested positive (sample SNR ≥ blank SNR + 3σ of blank) with LFA, indicating 96.2% sensitivity. All pre-COVID-19 samples tested negative with LFA for SARS-CoV-2 S1

IgGs, indicating 100% speci city ( Figure 4J) . Thus, the p-LFAs for SARS-CoV-2 antibodies detection offers POC applicability with accuracy comparable to gold standard ELISA and with potential applicability to vaccine e cacy and epidemiological studies.

Finally, we evaluated the potential of p-LFAs to ll the critical need for a POC test that can provide information about whether a patient is currently infectious. State of the art diagnosis of common respiratory virus infections does not achieve this. The challenge is that in serological testing of virusspeci c immunoglobulins, the antibody responses to viral antigens are usually detected in the late stage of infection (7-14 days after virus exposure), therefore serological antibody tests cannot achieve accurate screening of asymptomatic populations or early stages of infection. 45 Further, RT-PCR, the current gold standard in diagnosing COVID-19, has proven highly successful in identifying individuals who have contracted the SARS-CoV-2 virus, however, they fail to distinguish between infectious patients and noninfectious individual, and can yield false positive results for months after a patient has recovered from the disease. [46] [47] Since antigens are expressed only when the virus is actively replicating, the antigen-based tests have better correlation with infectiousness than RNA detection by RT-PCR. Current antigen detection tests for diagnosing COIVD-19 are scalable and convenient but are limited by their low and wide ranging accuracy. [48] [49] [50] [51] LFAs for detection of SARS-CoV-2 antigens can be the most important tool owing to their ease of use, lower-cost and better correlation with infectivity. Currently, several LFA-based antigen [6] [7] 52 assays have been reported and are widely used but none offers the optimal sensitivity, 53 thus, a negative result with such platforms in a symptomatic patient requires a con rmatory RT-PCR test. Therefore, there is an urgent need for a more sensitive POC antigen assay that would be just as reliable and accurate as the RT-PCR method.

p-LFA provided the accuracy and sensitivity needed for this in samples from patients who simultaneously had PCR tests performed. Our test focused on the detection of SARS-CoV-2 nucleocapsid protein (N protein). Test and the control spots on the LFA strips were prepared by immobilizing N protein capture antibodies and sheep IgG, respectively ( Figure 5A ). The uorescence signals obtained from p-LFAs increased monotonically with an increase in the concentration of N protein standard ( Figure 5B ). The LOD and LOQ were calculated to be 212 pg ml −1 and 1.02 ng ml −1 , respectively ( Figure 5C , four-parameter logistic t). The p-LFA displayed 37-fold improvement in LOD as compared to conventional sandwich ELISA and comparable LOD to p-FLISA ( Figure S19) .

Next, to demonstrate the clinical translational potential of p-LFAs for detection of N protein, we tested 35 PCR-positive samples, comprised of 16 delta variant samples, and 19 PCR-negative NP swab samples. The negative NP swab samples comprised a mix of healthy samples, and samples tested positive for seasonal coronaviruses and other respiratory viruses. All the 19 PCR-negative samples tested negative (SNR < mean + 3σ) via p-LFAs, suggesting 100% analytical speci city to COVID-19 N protein and no cross-reactivity with other viruses and different seasonal coronaviruses. Of the 35 PCR positive samples, 34 tested positive with p-LFAs (SNR > mean + 3σ), indicating 97.1% analytical sensitivity ( Figure 5D) . (Table S1 ). The diagnostic sensitivity of p-LFA for samples with low viral load (cycle threshold (CT) values ≥ 25) is 91.7% (11 out of 12) and for samples with high viral load (CT values < 25) is 100% (23 out of 23). This is signi cantly higher than the previously reported rapid antigen/POC SARS-CoV-2 tests' diagnostic sensitivity (~80% for samples with CT values < 25 and 20-40% for samples with CT values ≥ 25). 7, 53-55 These results substantiate that p-LFAs enable ultrasensitive, accurate, rapid, inexpensive, and point-of-care diagnosis of COVID-19 antigen and antibodies and thus can be a potential tool for rapidly and precise diagnosis of symptomatic and asymptomatic infections.

In summary, plasmonic-uors were demonstrated as a bimodal (colorimetric+ uorescent) reporter element for overcoming long-standing limitations of LFAs: limited sensitivity, low accuracy and small dynamic range compared to laboratory tests, and limited quantitation ability. Plasmonic-uors produced a discernable uorescence signal at densities 10000-fold lower than those needed in conventional colorimetric AuNPs. p-LFAs for various analytes (IL-6, SARS-CoV-2 S1 antibodies, and SARS-CoV-2 antigen) exhibited ~1000-fold improvement in bioanalytical parameters (LOD, LOQ and dynamic range).

p-LFAs offered standard-free quantitative detection and the sensitivity of gold standard ELISA, but with a much lower sample-to-answer time (20 min versus 4-6 hours). p-LFAs for detection of COVID-19 antibodies and antigens present in plasma and nasopharyngeal swab samples, respectively, achieved >95% sensitivity and 100% speci city, demonstrating its clinical applicability. We believe p-LFAs are highly attractive for point-of-care settings with better accuracy than conventional colorimetric LFAs, and with faster sample-to-answer time and lower cost than molecular tests. The platform technology demonstrated here can be readily adapted for the detection of other infectious pathogens and disease biomarkers, and can be employed as an alternative to laboratory-based test for the diagnosis of clinically relevant pathogenic infections and possible future pandemics.

Plasmonic-uors consists of plasmonically active core, gold nanorod synthesized by seed-mediated method, 56 a polymer spacer layer, uorophores and universal biorecognition element (biotin). Plasmonicuors were synthesized following the similar procedure described in our previous study. 27 Detailed stepwise procedure is discussed in the supplementary information.

Citrate-stabilized AuNPs were synthesized using seed-mediate synthesis method and using citrate as reducing agent. Au seeds (~15 nm) were synthesized as described previously by Frens et al. 57 Brie y, 20 ml 0.25 mM of HAuCl 4 (Sigma Aldrich, 520918) was brought to boil under vigorous stirring, 800 rpm.

Immediately after the solution started boiling, 0.2 ml of 3% (w/v) sodium citrate (Sigma Aldrich, 1613859) aqueous solution was added and maintained under boiling condition until the solution color changed to wine red, indicating the formation of Au seeds. Next ~100 nm AuNPs were synthesized using hydroquinone (Sigma Aldrich, H9003) as reducing agent for reduction of ionic gold.

TEM images were obtained using a JEOL JEM-2100F eld emission instrument. The extinction spectra of plasmonic nanostructures were obtained using a Shimadzu UV-1800 spectrophotometer. Fluorescence mappings were recorded using LI-COR Odyssey CLx imaging system. Digital camera (Sony cybershot DSC HX300) and imaging software, ImageJ were employed to characterize mean gray intensities. SpectraMax iD3 (Molecular Devices) plate reader was used to measure the optical density in ELISA.

To functionalize nanolabels with streptavidin (Sigma Aldrich, SA101), 1 µl 10 mg ml -1 of streptavidin (or BSA-Biotin or detection antibody) was added to 1 ml OD1 of nanolabels and incubated for 1 h on a shaker at room temperature. To stabilize the particles, 1 ul 10 mg ml -1 of BSA (Sigma Aldrich, A7030) was added to the solution and further incubated for 20 min. Unbound protein was removed by washing the solution four times with pH 10 nanopure water (1 µl NaOH in 10 ml of water). Finally, nanolabels were redispersed in 1% BSA in 1X PBS solution for use in the LFAs. To functionalize nanolabels with antibodies (IL-6 and N protein detection antibody and anti-human IgG), similar process was employed.

Lateral ow immunoassay assembly and preparation procedures Nitrocellulose test membrane and absorbent pads with adhesive backing material (GE healthcare, FF120HP) were employed for fabricating the LFA strips. The test membrane and absorbent pad was cut into 4 mm wide strips using a paper trimmer. For preparing the LFA strip, biorecognition element (e.g., capture antibody) solution was pipetted onto the test membrane and dried at room temperature for 30 min. Subsequently, the test membrane was blocked using 3% BSA in 1X PBS solution. Next, strips were washed with PBST (1X PBS and 0.5% Tween20 (Sigma Aldrich, P9416), followed by drying at room temperature in a vacuum desiccator for 1 h. After drying, absorbent pads (GE healthcare, CF5) were assembled onto the polystyrene adhesive backing next to nitrocellulose test membrane. To ensure e cient transfer of the solution from the test membrane to the absorbent pad, we ensured an overlap of 1-2 mm between both strips. Experiments were performed by dipping LFAs into 96-well plates lled with 100 µl of sample/standard solutions for 20 min. The visual signals of LFAs were obtained by a digital camera. The images were converted to 8-bit gray scale image using ImageJ. Mean gray values of the test spot were calculated by averaging the test spot grayscale intensities obtained from ImageJ. The uorescence signals were obtained by averaging test dot uorescence intensities obtained using LI-COR Odyssey CLx uorescence scanner using the following scan parameters: laser power~L2; resolution 21 µm; channel 800 nm; height 0 mm.

To determine the optimum concentration of biotinylated BSA on the test spot, different LFA strips with varying concentrations of biotinylated BSA (100 µg ml -1 to 5 mg ml -1 ) were prepared. LFAs were then subjected to the same concentration of streptavidin (1000 ng ml -1 for AuNP-LFA and 1 ng ml -1 for p-LFA) and biotinylated nanolabels. To determine the optimal concentration of the nanolabels, LFA strips with the same concentration of the capture element and biotinylated BSA (5 mg ml -1 ) were prepared. These LFA strips were then subjected to the same concentration of streptavidin (1000 ng ml -1 for AuNPs and 1 ng ml −1 for plasmonic-uors) but different numbers of biotin-functionalized nanolabels (4.45x10 6 to 3.56x10 10 for AuNPs and 1.2x10 4 to 6x10 6 for plasmonic-uors). The optimum number of nanolabels for both AuNPs-based LFA and p-LFA was determined by subtracting the background signal from the test spot signal.

Test spots were formed by pipetting 0.5 µl of 5 mg ml -1 biotinylated-BSA onto the nitrocellulose membrane. The LFA strip was assembled as described above. LFA strips were dipped into microtiter wells lled with 100 µl of different concentrations of streptavidin solutions (0.1 pg ml -1 to 1000 µg ml -1 ) for 20 min.

Human IL-6 immunoassays Human IL-6 DuoSet ELISA kit (R&D systems, DY206) was utilized in the study. For AuNP-based IL-6 LFA, AuNPs were conjugated with IL-6 detection antibody for the test spot and with anti-sheep IgG (R&D systems, BAF016) for the control spot. For p-LFA, plasmonic-uors were conjugated with IL-6 detection antibody for the test spot and AuNPs were conjugated with anti-sheep IgG for the control spots, respectively. To prepare LFA strips for IL-6 immunoassay, 0.5 µl of 2 mg ml -1 IL-6 capture antibody and 0.5 µl of 2 mg ml -1 sheep IgG (R&D systems, 5-001-A) was pipetted onto the nitrocellulose membrane at different spots to create test and control spot, respectively. Subsequently similar steps, mentioned above, were followed for LFA preparation and assembly. For AuNP-based IL-6 LFA, 1 µl of IL-6 detection antibody-conjugated AuNPs and 1 µl of anti-sheep IgG conjugated-AuNPs for test and control spot, respectively, were mixed with 98 µl of different concentrations of human IL-6 standard solutions (100 fg ml -1 to 5 ng ml -1 ) in 96-well plates to allow the binding of the analyte with the detection antibodyconjugated nanolabels. LFA strips were then exposed to the sample/standard solution for 20 min. For IL-6 p-LFA, 1 µl of IL-6 detection antibody-conjugated plasmonic-uors and 1 µl of anti-sheep IgG conjugated AuNPs were mixed with 98 µl of human IL-6 standard solutions (1 fg ml -1 to 1 ng ml -1 ) in 96well plates. The visual signals and the uorescence signals were obtained according to the procedure described above.

Human IL-6 ELISA was carried out according to the procedure described in DuoSet ELISA kit manual and is discussed in detail in supplementary information. Plasmonic uor-linked immunosorbent assay (p-FLISA) was carried out by adopting a similar approach, expect that the HRP-labeled streptavidin (provided in the ELISA kit) was replaced by streptavidin-functionalized plasmonic-uor. Instead of streptavidin-HRP, 100 µl of streptavidin-plasmonic-uors (OD 1) was incubated for 30 min, and then the plate was washed three times with PBST. The uorescence signal was obtained by averaging the uorescence intensities from the microtiter wells obtained using LI-COR Odyssey CLx with the following scan parameters: laser power~L2; resolution 169 µm; channel 800 nm; height 4 mm.

Four IL-6 standard curves were generated over a span of 6 months and samples with varying IL-6 concentrations (0.5 pg ml -1 to 62.5 pg ml −1 ) were tested in a standard-free manner. Their experimental concentrations were determined using each standard curve, and deviation from actual concentrations were calculated.

We pipetted 0.5 µl of 2 mg ml -1 recombinant SARS-CoV-2 S1 protein (R&D systems, 10522-CV) and 0.5 µl of 2 mg ml -1 sheep IgG onto the nitrocellulose membrane as test and control spot, respectively. Subsequently, we followed the same steps described above to prepare the LFA strips. For detecting SARS-CoV-2 S1 antibodies, AuNP-LFA and p-LFA, AuNPs and plasmonic-uors were conjugated with biotinylated anti-human IgG for test spots, respectively. In both cases, AuNPs were conjugated with antisheep IgG for control spot. For AuNP-based SARS-CoV-2 S1 antibody LFA, 1 µl of anti-human IgG conjugated-AuNPs and 1 µl of anti-sheep IgG conjugated-AuNPs were mixed with different concentrations of standard solutions (16 pg ml -1 to 25 µg ml -1 ) in 96-well plates, prior to exposure to LFA strip for 20 min.

For plasmonic-uor-based SARS-CoV-2 S1 antibody LFA, 1 µl of anti-human IgG conjugated-plasmonicuors and 1 µl of anti-sheep IgG conjugated-AuNPs were mixed with different concentrations of standard solutions (16 pg ml -1 to 1 µg ml -1 ) in 96-well plates, prior to exposure to LFA strip for 20 min. Plasma samples were diluted 500-fold in reagent diluent (1X PBS containing 3% BSA, 0.2 µm ltered) before use. The visual signals and the uorescence signals were obtained by employing the same procedure mentioned above.

SARS-CoV-2 S1 antibody ELISA was carried out according to the following procedure. Microtiter wells were coated with 100 µl of 5 µg ml −1 (in 1X PBS) recombinant SARS-CoV-2 S1 protein via overnight incubation at room temperature. For blocking, 300 µl of reagent diluent was added to the wells for a minimum of 1 h. Next, 100 µl of serially-diluted standard samples were incubated for 2 h, followed by incubation of 100 µl of 100 ng ml −1 biotinylated anti-human IgG for 2 h. Next, 100 µl of 500 ng ml -1 streptavidin-labelled HRP (Thermo Fisher scienti c, N100) was incubated for 20 min, followed by the addition of 100 µl of substrate solution for 20 min. The reaction was stopped by addition of 50 µl of 2N H 2 SO 4 (R&D Systems, DY994) and immediately the optical density at 450 nm was measured using a microplate reader. p-FLISA was carried out by adopting a similar procedure, expect that the HRP-labelled streptavidin was replaced by streptavidin functionalized-plasmonic-uor. Instead of HRP, 100 µl of plasmonic-uors (OD 1) were incubated for 30 min, and then the plate was washed three times with PBST. The uorescence signal was obtained by averaging the uorescence intensities from the microtiter wells obtained using LI-COR Odyssey CLx.

We pipetted 0.5 µl of 2 mg ml -1 nucleocapsid protein capture antibodies (SinoBiologicals, 40143-MM08) and 0.5 µl of 2 mg ml -1 sheep IgG onto the nitrocellulose membrane as test and control spots, respectively. For N protein p-LFA, plasmonic-uors were conjugated with biotinylated N protein detection antibody for the test spots. AuNPs conjugated with anti-sheep IgG were employed for control spot.

Subsequently, similar steps mentioned above were followed to prepare and assemble the LFA strips. For plasmonic-uor-based N protein LFA, 1 µl of detection antibodies conjugated-plasmonic-ours and 1 µl of anti-sheep IgG conjugated-AuNPs were incubated with different concentrations of standard solution (12 pg ml -1 and 1 µg ml -1 ; SinoBiologicals, 40588-V08B) in 96-well plates prior to exposure to LFA strips for 20 min. p-LFAs were employed for the detection of N protein present in patient nasal swab samples. The nasal swab samples were in universal transport media and were used without any dilution or processing. The visual signals and the uorescence signals were obtained employing the similar process described above.

N protein ELISA was carried out by rst coating the microtiter wells with 100 µl of 100 ng ml −1 N protein capture antibodies (in 1X PBS) via overnight incubation at room temperature. For blocking, 300 µl of reagent diluent was added to the wells for a minimum of 1 h. Next, 100 µl of serially-diluted standard samples were incubated for 2 h, followed by incubation of 100 µl of 200 ng ml −1 biotinylated N protein detection antibody for 2 h. Next, 100 µl of 500 ng ml -1 streptavidin-labelled HRP (Thermo Fisher scienti c, N100) was incubated for 20 min, followed by the addition of 100 µl of substrate solution for 20 min. The reaction was stopped by addition of 50 µl of 2N H 2 SO 4 (R&D Systems, DY994) and immediately the optical density at 450 nm was measured using a microplate reader. p-FLISA was carried out by adopting a similar procedure, expect that the HRP-labelled streptavidin was replaced by streptavidin-functionalized plasmonic-uor. Instead of HRP, 100 µl of plasmonic-uors (OD 1) were incubated for 30 min, and then the plate was washed three times with PBST. The uorescence signal was obtained by averaging the uorescence intensities from the microtiter wells obtained using LI-COR Odyssey CLx.

The clinical samples used in the study were acquired from the repository of saliva and nasopharyngeal samples from individuals con rmed/suspected with COVID-19 disease, located at Washington University (A) Schematic illustration of the SARS-CoV-2 S1 antibody LFA strips comprising of recombinant SARS-CoV-2 S1 protein as capture element at the test spot and sheep IgG at the control spot. Schematic description of (B) AuNP-based SARS-CoV-2 S1 antibody LFA and (D) p-LFA. (C) Dose-dependent mean grey values, corresponding to different SARS-CoV-2 S1 antibody concentrations, acquired from AuNPsbased LFA and (E) Dose-dependent signal-to-noise ratio of SARS-CoV-2 S1 antibody p-LFA performed in 20 min. 8-bit ImageJ processed images of (F) AuNP-based SARS-CoV-2 S1 antibody LFA and (G) SARS-CoV-2 S1 antibody p-LFA depicting the visual readout mode. (H) Fluorescence image of the SARS-CoV-2 S1 antibody p-LFA strips depicting the uorescence readout mode. (I) Dose-dependent optical densities and uorescence intensities, corresponding to different SARS-CoV-2 S1 antibody concentrations, obtained by standard ELISA (red circle) and p-FLISA (black square) implemented on a microtiter plate, performed in 4 h. (J) Table depicting the analytical sensitivity and speci city of the SARS-CoV-2 S1

antibody p-LFA. 

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SupplementaryinformationpLFAforSARSCoV2antibodyandantigen.docx

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We acknowledge support from National Science Foundation (CBET-2027145, CBET-2029105, and CMMI 1548571), National Cancer Institute-Innovative Molecular Analysis Technologies (R21CA236652 and R21CA236652-S1). Research reported in this publication was supported by the Washington University Bioscience. These potential con icts of interest have been disclosed and are being managed by Washington University in St. Louis.