Detection of COVID-19: A review of the current literature and future perspectives

Abstract

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the coronavirus disease 2019 (COVID-19) worldwide pandemic. This unprecedented situation has garnered worldwide attention. An effective strategy for controlling the COVID-19 pandemic is to develop highly accurate methods for the rapid identification and isolation of SARS-CoV-2 infected patients. Many companies and institutes are therefore striving to develop effective methods for the rapid detection of SARS-CoV-2 ribonucleic acid (RNA), antibodies, antigens, and the virus. In this review, we summarize the structure of the SARS-CoV-2 virus, its genome and gene expression characteristics, and the current progression of SARS-CoV-2 RNA, antibodies, antigens, and virus detection. Further, we discuss the reasons for the observed false-negative and false-positive RNA and antibody detection results in practical clinical applications. Finally, we provide a review of the biosensors which hold promising potential for point-of-care detection of COVID-19 patients. This review thereby provides general guidelines for both scientists in the biosensing research community and for those in the biosensor industry to develop a highly sensitive and accurate point-of-care COVID-19 detection system, which would be of enormous benefit for controlling the current COVID-19 pandemic.

Keywords: COVID-19; Point-of-care testing; SARS-CoV-2.

Fig. 1

Schematic illustration of strategies for the detection of COVID-19 patients.

Fig. 2

Schematic illustration of the structure of the coronavirus genome and virion, the mechanism of coronavirus replication and transcription, and the expression abundance of sgRNA. (A) Schematic presentation of the SARS-CoV-2 genome organisation, the canonical subgenomic mRNA, and the virus structure. The black box indicates the leader sequence. Note that our data show no evidence for open reading frame 10 (ORF10) expression. S: spike protein, E: envelop protein, M: membrane protein, N: nucleocapsid protein, gRNA: genomic RNA, TRS-L: transcriptional regulatory sequences-leader, TRS-B: transcriptional regulatory sequences-body. Reproduced with permission from (Kim et al., 2020c). (B) Mechanism of coronavirus replication and transcription. The virus open reading frames (ORFs) are depicted in teal (nsp1-nsp16 genes), blue (ns2, ns4a, ns4b, and ns5a genes), and green (S, M, E, N, and I structural protein genes). The open red box represents the common 59-leader sequence and the barred circle represents the programmed (−1) frameshifting element. The translation products of the genome- and subgenome-length mRNAs are depicted, and the autoproteolytic processing of the ORF1a and ORF1a/ORF1b polyproteins into proteins nsp1 to nsp16 is shown. A number of confirmed and putative functional domains in the nsp proteins are also indicated. NeU, uridylate-specific endoribonuclease; PL1, papain-like protease 1; PL2, papain-like protease 2. Reproduced with permission from (Sawicki et al., 2007). (C) The relative abundance of sgRNA in vivo. Top, the break point ratios; middle, the TRS sequences within the SARS-COV-2 genome, solid dots indicate a matching base to the leader TRS sequence while a hollow one indicates a mismatch; bottom, schematic showing SARS-COV-2 annotation, the ORF supported by sgRNAs is indicated by the orange colour. Reproduced with permission from (Lv et al., 2020). (D) Top 50 expressed SARS-CoV-2 sgRNAs in Vero cells. The asterisk indicates an ORF beginning at 27,825, which may encode the 7b protein with an N-terminal truncation of 23 amino acids. The grey bars denote minor transcripts that encode proteins with an N-terminal truncation compared with the corresponding overlapping transcript. The black bars indicate minor transcripts that encode proteins in a different reading frame from the overlapping major mRNA. Reproduced with permission from (Kim et al., 2020c). (E) Phylogenetic tree of SARS-CoV-2 and other pathogenic human CoVs, including HCoV-229E, HCoV-HKU1, HCoV-NL63 HCoV-OC43, and MERS-CoV. Reproduced with permission from (Hou et al., 2020). (F) Putative function and proteolytic cleavage sites of 16 nonstructural protein in orf1a/b, as predicted by bioinformatics. Reproduced with permission from (Chan et al., 2020a). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

Schematic illustration of CRISPR-based SARS-CoV-2 RNA detection assay. (A) CRISPR-Cas 13-nCoV test combining a recombinase polymerase amplification step with T7 transcription and Cas13 detection. Reproduced with permission from (Hou et al., 2020). (B) SARS-CoV-2 DETECTR workflow. Conventional RNA extraction was used as the input for DETECTR (LAMP preamplification and Cas12-based detection), followed by a fluorescent reader or lateral flow strip. Reproduced with permission from (Broughton et al., 2020). (C) Cas13-based, Rugged, Equitable, Scalable Testing (CREST) method. (i-iii) Standard sample collection, RNA extraction, and reverse transcription. (iv) Amplification using cost-effective Taq polymerase and portable thermocyclers instead of isothermal reactions. (v) Transcription and Cas13 activation are followed by visualisation with a blue LED (~495 nm) and orange filter. Reproduced with permission from (Rauch et al., 2020). (D) CRISPR-Cas 12-nCoV test coupling recombinase polymerase amplification with Cas12 collateral cleavage fluorescence detection or lateral flow strip detection. Reproduced with permission from (Lucia et al., 2020). (E) All-In-One Dual CRISPR-Cas12a assay. SSB, single-stranded DNA binding protein. Reproduced with permission from (Ding et al., 2020). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

Fitted curve of the COVID-19 detection positive rate, by PCR, IgM, and IgG enzyme-linked immunosorbent assay (ELISA), on different days after symptom onset. (A) SARS-CoV-2 RNA and antibodies IgG and IgM targeting the NP. Reproduced with permission from (Guo et al., 2020a, Guo et al., 2020b). (A) SARS-CoV-2 RNA and total antibodies IgG and IgM targeting receptor bind region (RBD) of SP. Reproduced with permission from (Zhao et al., 2020).

Fig. 5

Schematic diagram of COVID-19 FET sensor operation procedure. Graphene as sensing material is selected and SARS-CoV-2 spike antibody is conjugated onto the graphene sheet via 1-pyrenebutyric acid n hydroxysuccinimide ester, which is an interfacing molecule used as a probe linker. Reproduced with permission from (Seo et al., 2020).

Fig. 6

(A) Schematic describing the operation protocol of on-chip pre-concentration and nucleic acid amplification. Reproduced with permission from (Kim et al., 2020a). (B) Workflow of free-flow electrophoretic virus particles at pre-concentration, followed by thermal lysis and gel-electrophoretic nucleic acid extraction. (a) Viruses (green) are captured in the sample chamber (sc) between the anode (red) and the cathode (black) at the separation gel (the blue line between sc and ec), using free-flow electrophoresis. (b) Thermal lysis of the concentrated viruses denatures the capsid, making the phage DNA accessible to electrophoretic transport. (c) Nucleic acids are transported through the separation gel into the elution chamber (ec) by gel electrophoresis (anode: red, cathode: black). Reproduced with permission from (Hugle et al., 2020). (C)Schematic illustration of electrokinetic pre-concentration (begins with loading the device with anti-FCV, pAb-labelled Protein A superparamagnetic beads to create a capture bed and incubating the anti-FCV mAb-labelled fluorescent liposomes with FCV). The sample is then loaded into the inlet well, concentrated at the nanoporous membrane, and eluted toward the capture bead bed. Reproduced with permission from (Connelly et al., 2012). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 7

(A) Schematic of the purification of nucleic acids using isotachophoresis. The purification can be initiated using at least two injection approaches. In the finite injection approach, (a1), the sample is injected into a channel and sandwiched between the trailing electrolyte (TE) and leading electrolyte (LE) regions that contain no samples. In the semi-infinite configuration approach, (a2), the sample is mixed into the TE reservoir. In either case, (b) the application of an electric current creates a steep electric field gradient at the TE-to-LE interface. NAs migrate faster than TE and accumulate at the TE-to-LE interface. The effective mobility of the TE anion is chosen to be higher than the mobilities of anionic impurities and, thus, impurities are gradually left behind. The NA eventually (c) elutes into the leading electrolyte reservoir, from which it can be extracted using a standard pipette for off-chip analysis. Reproduced with permission from (Rogacs et al., 2014). (B) Principle of PM-SET (a) The electrophoretic mobility of nucleic acids (NAs) is higher than that of proteins, so NAs concentrate farther from the Nafion membrane than proteins, where the electric field is weaker. (b) The concentration of proteins and NAs causes the rapid back-propagation of the NAs. (c) Under external hydrostatic pressure, proteins easily leak through the electric force barrier, while NAs are still effectively concentrated. (d) Under external hydrostatic pressure, NAs are stably concentrated near the ion depletion zone, while the background proteins are removed, enabling the simultaneous enrichment and purification of NAs. Reproduced with permission from (Ouyang et al., 2018). (C) The schematic of the Dimethyl Pimelimidate (DMP)-based Microfluidic System for extracting DNA or RNA. A mixture solution, including lysis buffer, samples, and DMP, is incubated at either RT for 10–20 min (for RNA) or 56 °C for 20 min (for DNA) to capture RNA or DNA through the DMP reagent on the amine modified surface of the thin film. Finally, the nucleic acids (RNA or DNA) are quickly washed and eluted. Reproduced with permission from (Jin et al., 2017).

Fig. 8

(A) Schematic illustrations of the experimental process of rapid RNA purification and NNV detection using an integrated microfluidic LAMP system. Reproduced with permission from (Wang et al., 2011). (B) Experimental workflow of a sample-to-answer, potable platform for rapid pathogen detection. Reproduced with permission from (Ma et al., 2019). (C) Schematic illustrations of a single-chamber, microfluidic cassette with an integrated FTA membrane (a) A photograph. (b) An amplified view of the reaction chamber without the FTA membrane. Two sets of protruding ledges are machined on the top and bottom of the LAMP chamber. (c) An amplified view of the reaction chamber with the installed FTA membrane, which separates the reaction chamber into a top main compartment and a bottom compartment. Reproduced with permission from (Liu et al., 2011). (D) Schematic of fluid travel through microRAAD. (a) The wash buffer (green) is constrained from flowing to the amplification zone and the sample (red blood cells and yellow plasma) is constrained from flowing to the LFIA by closed valves. (b) Upon thermally actuating the valves, wash buffer is released to the amplification zone and the RT-LAMP products migrate to the LFIA for (c) test band development. Reproduced with permission from (Phillips et al., 2019). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)