key: cord-0756451-i8xu20qm
authors: Zhang, Dayi; Zhang, Xiaoling; Ma, Rui; Deng, Songqiang; Wang, Xinzi; Wang, Xinquan; Zhang, Xian; Huang, Xia; Liu, Yi; Li, Guanghe; Qu, Jiuhui; Zhu, Yu; Li, Junyi
title: Ultra-fast and onsite interrogation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in waters via surface enhanced Raman scattering (SERS)
date: 2021-05-13
journal: Water Res
DOI: 10.1016/j.watres.2021.117243
sha: 530918a90ccc56195e015b4dd3729667d0fd293f
doc_id: 756451
cord_uid: i8xu20qm

The outbreak of coronavirus infectious disease-2019 (COVID-19) pneumonia challenges the rapid interrogation of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in human and environmental samples. In this study, we developed an assay using surface enhanced Raman scattering (SERS) coupled with multivariate analysis to detect SARS-CoV-2 in an ultra-fast manner without any pretreatment (e.g., RNA extraction). Using silver-nanorod SERS array functionalized with cellular receptor angiotensin-converting enzyme 2 (ACE2), we obtained strong SERS signals of ACE2 at 1032, 1051, 1089, 1189, 1447 and 1527 cm(−1). The recognition and binding of receptor binding domain (RBD) of SARS-CoV-2 spike protein on SERS assay significantly quenched the spectral intensities of most peaks and exhibited a shift from 1189 to 1182 cm(−1). On-site tests on 23 water samples with a portable Raman spectrometer proved its accuracy and easy-operation for spot detection of SARS-CoV-2 to evaluate disinfection performance, explore viral survival in environmental media, assess viral decay in wastewater treatment plant and track SARS-CoV-2 in pipe network. Our findings raise a state-of-the-art spectroscopic tool to screen and interrogate viruses with RBD for human cell entry, proving its feasibility and potential as an ultra-fast detection tool for wastewater-based epidemiology.

The outbreak of coronavirus infectious disease-2019 (COVID-19) pneumonia since 2019 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (Li et al., 2020b) and it has rapidly spread throughout 202 countries around the world. Till 19 th March 2021, there have been over 125 million confirmed cases and nearly 3 million deaths globally, and the number is still increasing rapidly. As there is clear evidence of human-to-human transmission of SARS-CoV-2 (Chan et al., 2020; Chang et al., 2020; Li et al., 2020b; Poon and Peiris, 2020) , e.g., direct contact, respiratory droplets (Carlos et al., 2020; Lai et al., 2020; Wu et al., 2020) and stools , how to interrogate SARS-CoV-2 in human and environmental samples draws more attentions for effectively confirming COVID-19 cases and identifying transmission routes (Zhang et al., 2021) . It brings urgent requirement of developing detection tools that can rapidly and specifically recognize SARS-CoV-2 to track patients.

Many approaches can detect SARS-CoV-2 with high specificity, e.g., real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR) colloidal gold immunochromatography. RT-qPCR targeted viral specific RNA fragment with specific primers for the open reading frame 1ab (CDDC-ORF), nucleocapsid protein (CDDC-N), envelope protein, membrane protein, or RNA-dependent RNA polymerase (RdRp) (Jung et al., 2020; Nalla et al., 2020; Ong et al., 2020; Wang et al., 2020) . RNA extraction from swab samples is necessary for RT-qPCR and requires time-consuming pretreatment, normally taking more than 4 hours (Nolan et al., 2006; Schmittgen and Livak, 2008) and bringing a barrier for rapid diagnosis of SARS-CoV-2. Alternatively, colloidal gold immunochromatography is a commonly used immunoassay to detect antibodies (IgG or IgM) stimulated by antigen entry (Auta et al., 2017) , targeting the immunological markers, IgM and IgG antibodies, which are reported to increase in the blood of most patients more than a week after infection (Woo et al., 2005) . However, this method is still time-consuming and not feasible for detecting SARS-CoV-2 in environmental media which do not have immunological markers (Amanat et al., 2020; Stadlbauer et al., 2020; Weiss et al., 2020) . It is of great urgency to develop a rapid, reproducible, cheap and sensitive assay detecting SARS-CoV-2, especially applicable for different environmental samples.

Raman spectroscopy is a vibrational spectroscopy of ability to detect chemical bonds via photon scattering (Morais et al., 2019) , but the generated signals are extremely weak comparing to the incident beam. Thus, surface enhanced Raman scattering (SERS) is introduced to overcome such inherent limitation and interrogate trace materials by exploiting the enormous electromagnetic field enhancement resulted from the excitation of localized surface plasmon resonances at nanostructured metallic surfaces, mostly gold or silver (Moskovits, 1985; Stiles et al., 2008) . It has been widely applied for biological analysis, e.g., living cell classification (Nam et al., 2019) , cancer detection (Vendrell et al., 2013) , biological imaging (Zavaleta et al., 2009) and virus detection (Zhang et al., 2011) . For SARS-CoV-2, the spike glycoprotein consists of S1 and S2 subunits, and S1 subunit contains a receptor binding domain (RBD) directly recognizing the human receptor angiotensin converting enzyme 2 (ACE2) for cell entry (Lan et al., 2020; Zhao et al., 2020) . Such recognition and binding might alter the structure of ACE2 and lead to changes

in Raman spectra. Additionally, the binding specificity allows ACE2 as an anchor to capture SARS-CoV-2 from human or environmental samples for interrogation.

In this study, we proposed a 'capture-quenching' strategy to rapidly detect SARS-CoV-2 and developed a SERS assay introducing ACE2 functionalized on silver-nanorod SERS substrates to capture and interrogate SARS-CoV-2 spike protein ( Figure 1 ). We firstly functionalized ACE2 on an aligned silver-nanorod SERS (SN-SERS) array in oblique angle deposition to capture and interrogate SARS-CoV-2 spike protein. The induced SERS signal quenching was documented by either red-shift or whole spectral alterations in multivariate analysis as indicators for the presence of SARS-CoV-2 in real environmental water samples.

The aligned silver-nanorod SERS (SN-SERS) array was fabricated in oblique angle deposition (OAD) using a custom-designed electron beam/sputtering evaporation system (Suzhou Derivative Biotechnology Co., LTD.) and formed randomly on a 4-inch silicon wafer with increasing deposition time (Shanmukh et al., 2006) . Briefly, Si-wafer was immersed in absolute alcohol and blow-dried up using N 2 gas prior to loading on the substrate holder. The substrate holder was then fixed on the specially designed Glancing Angle Deposition (GLAD) sample stage in an e-beam evaporator. Deposition was performed at a base pressure lower than 3×10 -4 Pa. The thickness of film growth was monitored 9 / 40 using a quartz crystal microbalance. Firstly, a thin layer of about 20 nm was deposited to assist the adhesion of silver on Si-wafer, followed by the deposition of a base layer of 200 nm silver. The GLAD stage was then tilt to 84° with respect to the incident vapor. A layer of 80 nm was then deposited with substrate rotation at 0.1 rev/s to improve the seeding for nanorod growth. The deposition rate was 2 Å/s in each stage and lasted about 3 h.

ACE2 was purchased from Novoprotein (China) and stored in borate buffer solution (0.1 M, pH=7.2) at -80°C before use and the ACE2@SN-SERS substrate was fabricated by Suzhou Yiqing Environmental Science and Technology LTD (China). Briefly, SN-SERS substrate was firstly cleaned by thorough rinse with deionized water and dried using N 2 gas flow. Subsequently, 1 μL of ACE2 stock solution (30 pg) was loaded to SN-SERS substrate and placed in an incubator under constant temperature and humidity conditions (25°C; 75%, w/w) for 4 h. ACE2 was then bound onto the surface of SN-SERS substrate, designated as ACE2@SN-SERS substrate, which could be stored in 4°C for 2 weeks before use.

Twenty-three water samples were collected from rivers, hospitals and pipe networks in Wuhan (China) from 24 th March to 10 th April, 2020 (Table 1) .

Around 2.0 L of water was directly collected in a plexiglass sampler, placed in 4 °C ice-boxes and immediately transferred into laboratory for RNA extraction following our reported protocol . Briefly, after centrifugation at 3,000 rpm to remove suspended solids, the supernatant was subsequently supplemented with NaCl (0.3 mol/L) and PEG-6000 (10%), settled overnight at 4 °C, and centrifuged at 10,000 g for 30 minutes. Viral RNA in pellets was extracted using the EZ1 virus Mini kit (Qiagen, Germany) according to the manufacturer's instructions. SARS-CoV-2 RNA was quantified by RT-qPCR using AgPath-ID™ One- Step Quantitative fluorescent signal for each sample was normalized by ROX™ passive reference dye provided in 2×RT-PCR buffer. For each RT-qPCR run, both positive and negative controls were included. The copy numbers of SARS-CoV-2 was obtained from a standard calibration curve by a 10-fold serial dilution of genes encoding nucleocapsid protein with an amplification efficiency of 102.6%, calculated as copies=10 .086)/3.262] (R 2 =0.991). For quality control, a reagent blank and extraction blank were included for RNA extraction procedure and no contamination was observed.

To (Whitworth et al., 2020; Wood et al., 2020) . It was purchased from DSMZ-German Collection of Microorganisms and Cell Cultures GmbH as vacuum-dried suspensions on filter paper in double-vial glass ampoules.

Bacteriophage Phil6 was carefully revitalized by a previous protocol (Whitworth et al., 2020) , harvested and purified in the suspension of sterile water, and stored at 4°C prior to test. SARS-CoV-2 spike proteins were extracted and provided by School of Life Sciences (Tsinghua University) following a reported protocol (Lan et al., 2020) .

Five microliters of stock solutions (E. coli DH5α cells and bacteriophage Phi6, around 10 3 copies; E. coli DH5α proteins and SARS-CoV-2 spike proteins, 12 / 40 around 10 pg) and water samples were directly loaded onto the fabricated ACE2@SN-SERS substrate and incubated at room temperature for 5 min.

After dryness, the substrate was ready for Raman spectral acquisition and can be stored at 4°C for at least 1 week. A series dilution of SARS-CoV-2 spike proteins were used to obtain the qualitative curves between Raman shifts and SARS-CoV-2 spike proteins, ranging from 0.1 pg to 10 pg.

For laboratory test, Raman spectra were acquired using a near-infrared confocal Raman microscope (HR evolution, Horiba, USA) equipped with a 785 nm near-IR laser source, a 300 l/mm grating and a semiconductor-cooling detector (CCD). All Raman spectra were collected with a 50× objective lens (NA=0.7) at an exposure time of 10 seconds, 3 accumulations, and laser power of 10 mW prior to lens. Raman spectroscopic system was calibrated with a silicon wafer at Raman shift of 520 cm −1 . At least five random regions

were measured for each sample, and a minimum of 9 individual spectra were acquired per sample. A 785-nm portable Raman spectrometer (Finder Edge, Zolix, China) was used for on-site detection, and the ACE2@SN-SERS substrate was placed on the probe of the portable Raman spectrometer with the following parameters: 0.5 s acquisition time and 300 mW laser power. This portable Raman spectrometer has a satisfactory spectral resolution of 4 cm -1 to distinguish possible spectral shift of biological samples. At least five-time measurement was conducted for each sample. For both laboratory and on-site test, all Raman spectra were recorded in the range of 100-3500 cm -1 in biological triplicates. On-site spectra acquisition took only 2 min, followed by multivariate analysis for about 3 min to allow overall test within 5 min.

Raw spectral data were pre-processed by using the open source IRootLab toolbox performed on MATLAB r2012 (Trevisan et al., 2013) . Briefly, each acquired Raman spectrum was cut to a biochemical-cell fingerprint region (900-1800 cm −1 ), baseline corrected, wavelet de-noised, and vector normalized. Unlike RT-qPCR and ELISA assay, our ACE2@SN-SERS assay generates Raman spectral data, which are multivariate and difficult to generate an individual variable for SARS-CoV-2. Thus, we used two approaches to distinguish the difference between positive and negative samples. Firstly, the ratio of Raman intensity at 1182 cm -1 to that at 1189 cm -1 was calculated, designated as 1182/1189 ratio, as an indicator for positivity prediction.

Alternatively, multivariate analysis was applied to the pre-processed spectral data to reduce data dimensions and extract key information. Principal component analysis (PCA) is an unsupervised data analytical method reducing the dimensionality of data, determining principal components (PCs) and

extracting key features (Jin et al., 2017; Li et al., 2020a) . The first 10 PCs, which account for more than 90% of the variance of the selected spectral regions, were then inputted into linear discriminate analysis (LDA), which determines the discriminant function line that maximizes the inter-class distance and minimizes the intra-class distance to derive an optimal linear boundary separating the different classes. Generally, PCA-LDA score plots and cluster vectors are generated, and the scores of the linear discriminant 1

(LD1) provides the best classification .

One-way ANOVA was used to compare the difference between samples and p-value less than 0.05 refers to statistically significant difference. Nevertheless, the intrinsic SERS analysis provided convoluted Raman signals derived from ACE2 proteins or complexes of ACE2 and spike protein of SARS-CoV-2 located in plasmonic hot spot regions, it is crucial to employ multivariate method to extract information in these complex multivariable spectroscopic data for a better interrogation. Herein, the whole spectra from 900 to 1800 cm -1 were analyzed by PCA-LDA, and the score plot clearly segregates the positive and negative groups ( Figure 3B ). LD1 derived from PCA-LDA model provided the best classification, mainly representing the shift of 1189 to 1182 cm -1 and the declining peaks at 1089 and 1447 cm -1 . In addition, LD2 also explained a small proportion of variance between positive and negative samples, consisting of peaks at 1032 and 1587 cm -1 . Accordingly, LD1 scores are assigned as criteria and exhibit significant difference between the positive and negative groups ( Figure 3D , p<0.001). When LD1 scores range from 0.070 to 0.120, the false-positive percentage slightly increases from 0.0% to 20.0%, whereas the false-negative percentage decreases from 40.0% to 0.0%. Accordingly, the highest accuracy of LD1 scores is 93.33%

when the threshold is 0.080 ( Figure S4B ).

Further analysis on the spectral region from 1170 to 1200 cm -1 ( Figure S3 to detect SARS-CoV-2 viruses has been raised by many researchers (Lukose et al., 2021) , these studies mainly focus on the detection sensitivity or substrate fabrication with artificial samples and there is no report on the detection of real environmental samples or accuracy (Jadhav et al., 2021; Peng et al., 2021) . Our findings proved the feasibility of ACE2@SN-SERS assay to on-site interrogate SARS-CoV-2 in real water samples, and both indicators have satisfactory performance. (Table 1) . However, both 1182/1189 ratios and LD1 scores by ACE2@SN-SERS assay had contradictory results that SARS-CoV-2 was present in all wastewater samples throughout in the treatment process despite of slight decay ( Figure 4A and 4E). It might be explained by higher stability of SARS-CoV-2 spike protein than RNA after disinfection, and the residual spike proteins were still detectable but the infectivity was of low risk. Our findings indicated a decay of SARS-CoV-2 viral RNA along wastewater treatment process, consistent with previous reported facts that both RNA (Norovirus GGI, GGII, sapovirus, and Aichi virus) and DNA 20 / 40 viruses (enteric adenoviruses, JC polyomaviruses, BK polyomaviruses) were effectively removed in conventional and biological wastewater treatment plants (Hata et al., 2013; Kitajima et al., 2014; Nordgren et al., 2009) For all water samples collected from Yangtze and Hanjiang River did not exhibited significant Raman shift from1189 cm -1 to 1182 cm -1 ( Figure 3A ), consistent with qPCR results (Table 1 ). These results indicated that no SARS-CoV-2 was detectable in and its spreading risk through natural rivers are neglectable. Although both Yangtze River and Hanjiang River received treated discharge from wastewater treatment plants in Wuhan, which had influent with SARS-CoV-2 ( Figure 4A ), disinfection can effectively remove viral RNA ( Figure 4B ) and leave limited risks of SARS-CoV-2 spillover from into natural environment. The occurrence of SARS-CoV-2 in wastewater and rivers has been reported in Paris (Rimoldi et al., 2020) , and its potential transmission and spread in the urban and rural water cycle might pose threats to public health (Bhowmick et al., 2020) . For rivers or lakes receiving untreated sewage, this ACE2@SN-SERS assay might be a solution for rapid and online detecting SARS-CoV-2 viral RNA for drinking water safety.

The developed ACE2@SN-SERS assay provides good accuracy and Table   Table 1 . Sampling sites and copy numbers of SARS-CoV-2 RNA in water samples.

Description SARS-CoV-2

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Human cellular receptor Angiotensin-Converting Enzyme 2 (ACE2) is functionalized on silver-nanorod SERS (SN-SERS) substrate, designated as ACE2@SN-SERS array, generated strong SERS signals (1032, 1051, 1089, 1189, 1447 and 1527 cm -1 ). The recognition and binding of receptor binding domain

Functionalized ACE2 protein is present as 'islands' (red circle). (C) Comparison of SERS signals between ACE2@SN-SERS substrate, SARS-CoV-2 spike protein on SN-SERS substrate and SARS-CoV-2 spike protein on ACE2@SN-SERS substrate. Featured SERS signals of ACE2 protein include 1032, 1089, 1189, 1447 and 1587 cm -1 . (D) Comparison of SERS signals between SARS-CoV-2 spike protein

SERS spectra of ACE2@SN-SERS and 23 tested water samples by ACE2@SN-SERS assay (mean value) using a portable Raman spectrometer. (B) Segregation of positive and negative water sample groups in PCA-LDA score plot. Red dots represent positive water samples for SARS-CoV-2. , and refer to negative water samples collected from wastewater disinfected units, hospitals, rivers and Huanan Seafood Market, respectively

Change of 1182/1189 ratio (A) and LD1 score (E) along wastewater treatment process for wastewater treatment plant management. Significant difference of 1182/1189 ratio (B) and LD1 score (F) between crude and disinfected waters for determination of disinfection efficiency. Change of 1182/1189 ratio (C) and LD1 score (G) for viral survival in environmental media. Occurrence of SARS-CoV-2 in the pipeline of Huanan Seafood Market by 1182/1189 ratio (D) and LD1 score (H)

The authors would like to thank the projects from the Major Program of National Natural Science Foundation of China (52091543) 

Waters in pipeline joint point Negative