A urine-based ELISA with recombinant non-glycosylated SARS-CoV-2 spike protein for detecting anti-SARS-CoV-2 spike antibodies.

Serological assays have been widely used to detect anti-SARS-CoV-2 antibodies, which are generated from previous exposure to the virus or after vaccination. The presence of anti-SARS-CoV-2 Nucleocapsid antibodies was recently reported in patients´ urine using an in-house urine-based ELISA-platform, allowing a non-invasive way to collect clinical samples and assess immune conversion. In the current study, we evaluated and validated another in-house urine-based ELISA for the detection of anti-SARS-CoV-2 Spike antibodies. Three partial recombinant SARS-CoV-2 Spike proteins comprising the Receptor Binding Domain, expressed in eukaryotic or prokaryotic systems, were tested in an ELISA platform against a panel of over 140 urine and paired serum samples collected from 106 patients confirmed positive for SARS-CoV-2 by qRT-PCR. The key findings from our study were that anti-SARS-CoV-2 Spike antibodies could be detected in urine samples and that the prokaryotic expression of the rSARS-CoV-2 Spike protein was not a barrier to obtain relatively high serology efficiency for the urine-based assay. Thus, use of a urine-based ELISA assay with partial rSARS-CoV-2 Spike proteins, expressed in a prokaryotic system, could be considered as a convenient tool for screening for the presence of anti-SARS-CoV-2 Spike antibodies, and overcome the difficulties arising from sample collection and the need for recombinant proteins produced with eukaryotic expression systems.

Heterogeneity of humoral response patterns in mildly symptomatic, non-hospitalized COVID-19 patients: A one-year longitudinal study.

The duration and protectiveness of antibodies against SARS-CoV-2 in infected subjects are still uncertain; nonetheless, anti-S-specific antibodies can contribute to protective immunity against new infections. It has been described that the level of antibodies produced in COVID-19 is related to the severity of symptoms, and the majority of the humoral response studies have been conducted in hospitalized patients who have been, then, followed over time. However, about 80% of SARS-CoV-2 infections in unvaccinated people are mild to asymptomatic, and this percentage reaches more than 95% in vaccinated individuals. Therefore, understanding the long-term dynamics of the antibody responses in this predominant part of the COVID-19-affected population is essential. In this study, we followed a cohort of individuals with mild COVID-19 who did not require hospitalization. We collected blood samples at sequential times after the SARS-CoV-2-positive qRT-PCR result. From 65 recruited patients, 50 had detectable antibodies at screening. Anti-SARS-CoV-2 IgM levels peaked around two weeks post-COVID-19 diagnostics, becoming undetectable after 65 days. IgG levels reached a peak in approximately one month and remained detectable for more than one year. In contrast to the levels of anti-SARS-CoV-2, antibody neutralization potency indexes persisted over time. In this study, humoral responses in mild COVID-19 patients persisted for more than one year. This is an important long-term follow-up study that includes responses from COVID-19 patients before and after vaccination, a scenery that has become increasingly difficult to evaluate due to the growing vaccination of the world human population.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

DEVELOPMENT AND VALIDATION OF AN ENZYME-LINKED IMMUNOASSAY KIT FOR DIAGNOSIS AND SURVEILLANCE OF COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

Development and validation of an enzyme-linked immunoassay kit for diagnosis and surveillance of COVID-19.

There is a massive demand to identify alternative methods to detect new cases of COVID-19 as well as to investigate the epidemiology of the disease. In many countries, importation of commercial kits poses a significant impact on their testing capacity and increases the costs for the public health system. We have developed an ELISA to detect IgG antibodies against SARS-CoV-2 using a recombinant viral nucleocapsid (rN) protein expressed in E. coli. Using a total of 894 clinical samples we showed that the rN-ELISA was able to detect IgG antibodies against SARS-CoV-2 with high sensitivity (97.5%) and specificity (96.3%) when compared to a commercial antibody test. After three external validation studies, we showed that the test accuracy was higher than 90%. The rN-ELISA IgG kit constitutes a convenient and specific method for the large-scale determination of SARS-CoV-2 antibodies in human sera with high reliability.

Detecting anti-SARS-CoV-2 antibodies in urine samples: A noninvasive and sensitive way to assay COVID-19 immune conversion.

Serum-based ELISA (enzyme-linked immunosorbent assay) has been widely used to detect anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. However, to date, no study has investigated patient urine as a biological sample to detect SARS-CoV-2 virus-specific antibodies. An in-house urine-based ELISA was developed using recombinant SARS-CoV-2 nucleocapsid protein. The presence of SARS-CoV-2 antibodies in urine was established, with 94% sensitivity and 100% specificity for the detection of anti-SARS-CoV-2 antibodies with the urine-based ELISA and 88% sensitivity and 100% specificity with a paired serum-based ELISA. The urine-based ELISA that detects anti-SARS-CoV-2 antibodies is a noninvasive method with potential application as a facile COVID-19 immunodiagnostic platform, which can be used to report the extent of exposure at the population level and/or to assess the risk of infection at the individual level.

Previous Infection with SARS-CoV-2 Correlates with Increased Protective Humoral Responses after a Single Dose of an Inactivated COVID-19 Vaccine.

Previous studies have indicated that antibody responses can be robustly induced after the vaccination in individuals previously infected by SARS-CoV-2. To evaluate anti-SARS-CoV-2 humoral responses in vaccinated individuals with or without a previous history of COVID-19, we compared levels of anti-SARS-CoV-2 antibodies in the sera from 21 vaccinees, including COVID-19-recovered or -naïve individuals in different times, before and after immunization with an inactivated COVID-19 vaccine. Anti-SARS-CoV-2-specific antibodies elicited after COVID-19 and/or immunization with an inactivated vaccine were measured by ELISA and Plaque Reduction Neutralizing assays. Antibody kinetics were consistently different between the two vaccine doses for naïve individuals, contrasting with the SARS-CoV-2-recovered subjects in which we observed no additional increase in antibody levels following the second dose. Sera from SARS-CoV2-naïve individuals had no detectable neutralizing activity against lineage B.1 SARS-CoV-2 or Gamma variant five months after the second vaccine dose. Contrarily, SARS-CoV-2-recovered subjects retained considerable neutralizing activity against both viruses. We conclude that a single inactivated SARS-CoV-2 vaccine dose may be sufficient to induce protective antibody responses in individuals with previous history of SARS-CoV-2 infection.

The use of denaturing solution as collection and transport media to improve SARS-CoV-2 RNA detection and reduce infection of laboratory personnel.

Accurate testing to detect SARS-CoV-2 RNA is key to counteract the virus spread. Nonetheless, the number of diagnostic laboratories able to perform qPCR tests is limited, particularly in developing countries. We describe the use of a virus-inactivating, denaturing solution (DS) to decrease virus infectivity in clinical specimens without affecting RNA integrity. Swab samples were collected from infected patients and from laboratory personnel using a commercially available viral transport solution and the in-house DS. Samples were tested by RT-qPCR, and exposure to infective viruses was also accessed by ELISA. The DS used did not interfere with viral genome detection and was able to maintain RNA integrity for up to 16 days at room temperature. Furthermore, virus loaded onto DS were inactivated, as attested by attempts to grow SARS-CoV-2 in cell monolayers after DS desalt filtration to remove toxic residues. The DS described here provides a strategy to maintain diagnostic accuracy and protects diagnostic laboratory personnel from accidental infection, as it has helped to protect our lab crew.