In December 2019, several patients were hospitalized in Wuhan City, Hubei province, China, with pneumonia-like respiratory symptoms of unknown etiology, with subsequent studies showing compelling evidence that Wuhan’s Huanan seafood and wildlife market could be related to the outbreak. The causative agent was identified as a betacoronavirus of sarbecovirus subgenus, belonging to Orthocoronavirinae subfamily, and was initially named as 2019-nCoV, which later would be renamed as SARS-CoV-2 [1].
Coronaviruses are enveloped single-stranded positive sense RNA viruses that affect mainly the respiratory tract, but are also capable of causing neurological, enteric and hepatic effects [2–3]. Up until December 2019, six coronaviruses were known to infect humans, with four of them causing mild flu-like symptoms, while the other two were responsible for highly pathogenic epidemics: SARS-CoV and MERS-CoV [4–6]. Likewise, in March 2020, the World Health Organization (WHO) declared the novel coronavirus disease (COVID-19) a global pandemic, caused by SARS-CoV-2 [7–8].
SARS-CoV-2 shares 79,5% genetic similarity with SARS-CoV and viral particle assembly is dependent on four main structural proteins: membrane (M), nucleocapsid (N), envelope (E) and spike (S) proteins, in addition to nonstructural and accessory proteins [9–10]. SARS-CoV-2 main method of infection relies on Spike glycoprotein, which shows a trimeric structure on the surface of the virus. It is comprised of two subunits: S1 and S2, being that S1 has a receptor binding domain (RBD) and is responsible for binding with angiotensin-converting enzyme 2 (ACE2), the main receptor for SARS-CoV-2 in host cells [11]. For this reason, Spike protein has been targeted with great attention for research and development of therapeutic drugs and vaccines for COVID-19 [12]. However, Spike protein is also the structural protein that is most affected by genetic mutations on different variants of SARS-CoV-2, which leads to important changes in antibody recognition, affecting diagnostic tests and vaccines [13]. Similar studies showed that N protein is much more conserved between variants and its mutations do not affect antibody binding in rapid diagnostic tests so far, making it a better target for SARS-CoV-2 antigen rapid testing [14].
Rapid testing offers several advantages over traditional laboratory methods that require trained personnel, equipment and take longer time for obtaining results [15]. Moreover, antigen testing tends to correlate well with the contagiousness status of the patient, revealing itself as a powerful tool for isolating the infected and reducing viral spread, when compared to molecular methods [16].
In this scenario, Hilab is a remote clinical laboratory that is able to perform several clinical tests in different human samples with the aid of portable proprietary equipment developed by the company’s team of multidisciplinary researchers. Hilab service uses internet of things (IoT) and artificial intelligence (AI) technologies to provide double verified results that are collected from the samples through the devices and analyzed by deep learning networks that provide a first insight into a patient's health status. This data is then verified by health professionals that validate, sign and release the reports back to the patient’s e-mails and cellular phones in minutes. Hilab Flow (Fig. 1) is one of the company’s main devices, a small handheld analyzer (12.4×12.4×12.7 cm; 0.45 kg) operating in a multi-methodology scenario that is able to perform immunochromatography, immunofluorescence, colorimetry and dry chemistry point of care tests with the company’s service technology as a background. Gasparin et al. recently published a work describing usage of Hilab Flow for hemoglobin measurement by vertical flow dry chemistry colorimetry in whole blood as part of a complete blood count test developed by Hilab researchers, although most of the tests performed in Hilab Flow are based on lateral flow immunoassays (LFIAs) [17].
LFIA are well recognized for their good performance for point of care testing, eliminating the need for highly trained professionals or laboratory infrastructure, and providing affordability with their low cost [18]. These attributes make LFIAs especially effective in reaching populations with low resources and/or lack of structure, as well as high demand testing scenarios such as health emergencies or pandemics [19]. "Sandwich” type LFIAs are paper-based diagnostic devices that function with immunochromatographic principles for the detection of clinically relevant analytes in a variety of samples. After dispensing the sample with a running buffer on the sample pad, the analyte, if present, interacts with dried reagents such as nanoparticles conjugated with antibodies and migrates by capillary action until the immune complexes reach the test line, comprised of a second antibody for the same analyte, which will bind the reagents and show a reactive signal. The test strip also contains a second line with specific antibodies for a control conjugate, to demonstrate that the strip is functioning correctly, acting as an internal control [20].
In order to guarantee good management of the viral spread in COVID-19, rapid tests used for screening must show good sensitivity for detection of SARS-CoV-2 N protein, avoiding false negatives and providing correct information about infection status. With this in mind, the concept of limit of detection as the lowest concentration of analyte that can be safely differentiated from blank is an important tool for the evaluation of sensitivity in diagnostic tests [21], and this information may lead to the identification of the need for sensitivity amplification strategies when developing these solutions. Clinical sensitivity performance of several SARS-CoV-2 N antigen diagnostic tests commercially available in Brazil were compared in a recent paper published by Freire et al., in which the authors described the sensitivity variation in a range from 9.8–81.1%. Low sensitivities from these screening tests could hinder mass test efficacy in controlling SARS-CoV-2 viral spread by allowing infected individuals to stay in close contact with healthy counterparts [22].
In this work we described a comparative information about sensitivity-boosting strategies applied in the development of a gold nanoparticle LFIA for the detection of SARS-CoV-2 antigen (N protein). Firstly, an increase in antibody concentration in the test line was able to double the sensitivity of the prototype. To further enhance the sensitivity and reach or surpass comparable limits of detection to benchmarking tests of the market, a second strategy was necessary. In this regard, two routes were evaluated: increase of concentration of colloidal gold conjugate and insertion of a cotton intermembrane in order to increase antibody-antigen interaction time.