COVID-19 : confirmed that antibodies are detected up to 3 months after infection

0
119

A new study in health care workers led by the Barcelona Institute for Global Health (ISGlobal) shows that IgA and IgM antibodies to SARS-CoV-2 decay quickly, while IgG antibody levels are maintained for at least three months after infection.

The longer follow-up of this cohort will provide much-needed information on the duration of different types of antibodies to SARS-CoV-2, the virus that causes COVID-19, as well as their role in protecting from disease and reinfection.

Since the start of the COVID-19 pandemic, there have been two burning questions: how many people have really been infected, and whether infected people are protected from future reinfections or disease.

ISGlobal researchers Carlota Dobaño and Alberto García-Basteiro joined forces to help answer these questions with the SEROCOV1 study, which intends to follow-up a cohort of over 550 health care workers at the Hospital Clínic of Barcelona.

The team showed that, at the peak of the COVID-19 pandemic in Spain, the prevalence of SARS-CoV-2 infection among health care workers was 11.2% (9.2% had antibodies and 2% had active infection detected by PCR).

This was slightly higher than the antibody prevalence among the general population in Barcelona (7%), estimated by a national seroprevalence study performed shortly after.

In this new study, researchers from ISGlobal and Hospital Clínic present data after three months of follow-up of the same cohort of health care workers. As in the first study, an immune assay based on the Luminex technology developed by Dobaño’s team was used to measure three main types of antibodies (IgM, IgG and IgA) directed against the receptor binding domain (RBD) of the SARS-CoV-2 Spike protein, which allows it to infect human cells.

The results show that, one month after the initial seroprevalence assessment conducted at the beginning of April 2020, the percentage of participants with evidence of previous or current infection had increased to 15% and that around 60% of the new infections detected were asymptomatic.

“In one month, we found 25 new infections among the participants, which is quite high, considering that the peak of the pandemic had passed and the population had been confined for more than one month,” says García-Basteiro, who is also a medical doctor at the International Health Service of Hospital Clínic.

Of the 82 seropositive participants detected at month 1, 66 were followed up for an additional two months. By month three, most (78%) had no longer detectable levels of IgM, some (24.5%) had no longer detectable IgA, but the majority (97%) maintained detectable levels of IgG.

In fact, IgG levels in some of the participants increased as compared to the first analysis. Symptomatic cases had higher levels of IgA but no differences in the speed at which antibodies declined were observed between asymptomatic and symptomatic infections. Overall, IgG1 levels were higher, although high IgG2 levels correlated with a longer duration of symptoms.

“Our findings confirm that IgM and IgA antibodies rapidly decline within the first month or two after infection, which should be kept in mind when performing seroprevalence studies or interpreting serological results” says Gemma Moncunill, first author of the study.

“While the duration of detectable IgG antibodies following infection is still unknown, our results show that they remain relatively stable for at least three months,” she adds. The SEROCOV1 team (which includes researchers from several ISGlobal’s programs and from the Occupational Health, Preventive Medicine and International Health departments at Hospital Clínic) plans to follow-up this cohort for a longer time, in order to assess the evolution of the seroprevalence in this high risk group, the duration of detectable antibodies, including several isotypes and subclasses to several antigens, and their role in protecting from disease and reinfection.

An extremely powerful assay to measure SARS-CoV-2 antibodies

In fact, Dobaño’s team has recently developed and published a multiplex assay for simultaneously measuring IgM, IgA and IgG to a panel of eight different viral fragments (antigens) from SARS-CoV-2 spike (S), nucleoprotein (N) and membrane (M) proteins.

The assays show a specificity of 100% and a sensitivity of over 95%, and have been optimized to minimize processing time. By combining multiple markers, these assays can detect a wider range of low-level antibody responses in the population.

“In addition to better assessing SARS-CoV-2 immunity in the population, these assays can be of great value for evaluating markers of protection when testing COVID-19 vaccines,” says Dobaño.


Antibodies play an important role in neutralizing virus and provide protection to the host against viral re-infection. The antibody response to SARS-CoV-2 infection has been extensively studied in the blood (serum, plasma) of COVID-19 patients in order to gain insights into the host immune response.

Antibody levels to the spike protein are particularly important since this large trimeric glycoprotein harbors the receptor-binding domain (RBD). The RBD facilitates SARS-CoV-2 access to human cells by binding to its counter receptor angiotensin-converting enzyme 2 (ACE-2) (1), and neutralizing antibodies have been shown to target the RBD (2).

Most studies agree that the IgG antibodies to SARS-CoV-2 spike and RBD antigens are detected in the blood of greater than 90% of subjects by 10–11 days post-symptom onset (PSO) (3–7). However, whether levels of IgG specific for SARS-CoV-2 antigen persist (8–13), or alternatively decay (14), remains a debated issue.

Examination of different biofluids from multiple cohorts, and attention to the antigens tested, is required to resolve this extremely important issue that has high relevance to vaccine design.

Another gap in our knowledge is that we know very little about the local antibody response at the site of infection. SARS-CoV-2 enters the naso- and oro-pharyngeal tracts where it subsequently replicates (15). For this reason, nasopharyngeal and throat swabs are used to test for virus using reverse transcriptase quantitative PCR (RT-qPCR) to detect viral RNA.

However, saliva has also been shown to be an effective biofluid for testing for the presence of SARS-CoV-2 mRNA (16–19). This makes sense given that pharyngeal SARS-CoV-2 shedding precedes viral replication in the lungs (15), and, like cytomegalovirus (20, 21), the salivary glands themselves can be a reservoir for the virus (22).

Yet in spite of the oral cavity being a site for viral replication, few studies have examined anti-SARS-CoV-2 antibodies in this compartment.

In this study, we examined the anti-SARS-CoV-2 antibody response over a 115-day period in the serum and saliva from n=439 (serum) and n=128 (saliva) patients with COVID-19, compared to controls. Antigen-specific IgG in both biofluids was maximally detected by 16–30 days PSO and did not drastically decline in relative level as late as 105-115 days PSO.

In contrast, antigen-specific IgM and IgA were rapidly induced but subsequently declined in both serum and saliva. In serum, neutralizing antibodies reached their maximum by 31–45 days PSO and slowly declined up to 105 days, with a more pronounced drop in the last blood draw (105–115 days PSO)

Importantly, IgG and IgM levels against both antigens were strongly correlated across paired serum and saliva samples (n=71), indicating that saliva can be used for monitoring the immune response to SARS-CoV-2 infection. Taken together, the systemic and mucosal IgG response to SARS-CoV-2 is sustained over a 3-month period, while the IgM and IgA response occurs early and is transient.

RESULTS

A chemiluminescent fully automated method for detecting antibodies to SARS-CoV-2 antigens in the serum of acute and convalescent patients

To study the antibody response to SARS-CoV-2, we initially focused on antibodies (IgM, IgG, IgA) to the spike homotrimer and the RBD, since neutralizing antibodies are directed to the spike protein (23). Enzyme-linked immunosorbent assays (ELISAs) for the detection in serum (or plasma) of anti-spike trimer and anti-spike RBD antibodies were built as in (3, 24) as 96-well colorimetric assays, and implemented as automated 384-well chemiluminescence assays.

For all serum-based assays, blank-subtracted colorimetric or chemiluminescent values were normalized to a pool of convalescent sera added to each assay plate, and expressed as ratios to this pool of positive samples (ratio-converted ELISA reads; see Methods).

Receiver-Operating Characteristic (ROC) curves were generated on cohorts of true negatives (banked samples collected pre-COVID, n=339 for manual and automated assays) and positives (convalescent patients with confirmed PCR diagnostic, n=402 for manual and automated assays, see Table 1).

For manual and automated IgG assays, sensitivities of 95.6% and 95.5% for spike and 93.8% and 91.3% for RBD, respectively, at a false positive rate of ≤1%, were obtained in these cohorts (Figure S1A-B, and Table S1 for ROC statistics). The Areas Under the Curves (AUCs) were ≥0.97 in all cases, indicating excellent assay performance.

Automated assays for the detection of IgA and IgM were also developed (Figure S1C-D), though the sensitivity/specificity characteristics were lower than those of the IgG assays at least in part because, as is described below, these antibody responses wane more rapidly. The results for the automated and manual IgG assays were well correlated (Figure S1E-F).


Table 1

Cohorts of patients and negative controls.

SALIVABLOOD
No. patientsNo. samplesMedian AgeSexNo. patientsNo. samplesMedian AgeSex
No. MNo.
F
No. MNo. F
All samples247263141106All samples739796379360
Patients with COVID-19Cohort 14754612819Patients with COVID-1943949658229210
Cohort 28190584833
Pre-COVID Negative ControlsCohort 100000Pre-COVID Negative Controls30030054.5150150
Cohort 22727431215
Unexposed Negative Controls Collected in 2020Cohort 14242602418
Cohort 25050582921
Matched saliva-serum samples7171583338

These automated ELISA assays were used to profile cohorts of confirmed acute and convalescent sera from COVID-19 patients collected as part of COVID-19 surveillance by the Toronto Invasive Bacterial Diseases Network (Table 1).

As expected, based on the ROC analysis the convalescent and pre-COVID controls had very different ratio distributions for both antigens (Fig. 1A, D). On the other hand, serum collected from patients less than 21 days PSO (acute serum, n=132) had bimodal distributions in their IgG responses for both antigens (with an overall lower mean), suggesting that antibody concentrations were increasing over time.

To compare the relationship between RBD and spike trimer IgG levels, we plotted their values against each other. While there was an overall high correlation between the antigens (Fig. 1G), we noted many more acute specimens with high spike-trimer and low RBD responses than vice versa, consistent with the fact that RBD is included within the spike trimer antigen.

The concentration of IgA and IgM in convalescent serum was also clearly higher than that of the pre-COVID samples, but the acute cases had a higher median than the convalescents (Fig. 1B & E, C & F). The IgA and IgM levels to RBD and spike were also well correlated (Fig. 1H-I).

Fig. 1 Cross-sectional analysis of IgG and IgA responses to the spike and RBD antigens of SARS-CoV2 in serum.
(A-F) Indicated immunoglobulins to spike and RBD were profiled by ELISA in cohorts of pre-COVID samples (n=300), hospitalized patients with acute COVID infection (n=132) and convalescent patients (n=364). All data, expressed as ratio-converted ELISA reads to a pool of convalescent samples (relative ratio), were plotted using bean plots. Solid bars denote the median and dotted line represents the median across all samples used in the plot. (G-I) levels of IgG (G), IgA (H) and IgM (I) to the RBD (y-axis) and spike (x-axis) antigens for the indicated patient groups. Spearman correlation coefficient is indicated. Mann-Whitney U test for significance was performed. n.s = not significant, *= p ≤ 0.05, **** = p < 0.0001.

The bimodal distribution of the IgG responses in the acute serum (Fig. 1A, D), along with the different patterns of response for IgG versus IgA/IgM in acute and convalescent specimens (Fig. 1B & E, C & F), prompted us to plot the antibody levels against days PSO.

Spearman rank correlation analysis revealed an overall increase in the IgG response versus a decrease in the IgA and IgM response to both antigens over time, and the IgG response in particular did not appear to be linear (compare panels A-B to C-D and E-F in Figure S2; IgG results were reproduced in the analysis of the manual IgG assays, shown in panels G-H).

To look at this response more closely, specimens were binned by days PSO (15-day intervals), and the levels of the different immunoglobulins were plotted (the pre-COVID negative control samples were plotted alongside for comparison; Fig. 2). As was reported in other studies (3, 4, 7), the IgG levels peaked in the 16–30 days bin, and the levels of IgG against spike trimer appeared relatively sustained over 115 days (Fig. 2A).

IgG levels against RBD showed a ~25.3% decrease by day 105, and ~46.0% by day 115 (Fig. 2D). IgA and IgM levels to both antigens were by contrast much less sustained: after reaching a maximum in the 16–30 days bin, there was a clear and continuous decline throughout the time series such that by 115 days, the anti-spike and anti-RBD IgA levels were ~74.1% and ~84.2% of their respective maximal levels, while IgM levels were ~66.2% and ~75.1%, respectively (Fig. 2B, E & C, F).

Multivariable analyses adjusting for severity of illness, sex, and patient age, did not change conclusions about the aforementioned relationships between time PSO and anti-RBD IgM, anti-spike IgM, anti-RBD IgA, anti-spike IgA, and anti-RBD IgG; however, the modest decline in anti-spike IgG after day 35 was statistically significant (data not shown).

The relative stability of the IgG anti-spike trimer levels, partial decrease in the anti-RBD IgG and anti-spike IgA levels, and a near complete loss in the anti-RBD IgM and IgA levels over time results were also detected in pairs of serum samples from hospitalized patients (n=57), collected at admission and 3–12 weeks later, using a nonparametric loess analysis (Fig. 3 as in (25)).

Fig. 3 A longitudinal analysis of IgG and IgA responses to the spike and RBD antigens of SARS-CoV2 in serum.
Analysis of the changes in the indicated Ig-antigen levels in patients profiled twice, in comparisons to the relative levels in pre-COVID negative controls (left). Dots represent individual serum samples collected at the indicated times, and the samples from the same patients are connected by the lines. A non-parametric loess function is shown as the blue line, with the grey shade representing the 95% confidence interval.

Although our focus was on the spike protein, we also examined the antibody response to nucleocapsid (a.k.a. nucleoprotein, NP), since this is the antigen targeted by multiple commercial assays. We developed an assay using bacterially-expressed NP (Figure S3A–C). When we examined the levels of anti-NP antibodies binned for time PSO, we found that their patterns closely resembled those for anti-spike and anti-RBD IgG and IgA/IgM responses, namely a relative stability in the IgG and more rapid decline in IgA/IgM levels in both the binned time series and the longitudinal series (Figure S3D-F).

To evaluate the neutralization potential of these antibodies, we used our recently established protein-based surrogate neutralization ELISA (snELISA) approach (Fig. 2G; (24)). Briefly, the snELISA measures the ability of antibodies (in serum in our case) to prevent the association of soluble biotinylated ACE2 to immobilized RBD: a higher signal (snELISA integrated score) in this assay indicates low neutralization.

Using the binned time series as above, we report that the neutralization reaches its maximum in the 31–45 day PSO bin, and decreases to an intermediate median plateau in the 46–105 day PSO bins before more drastically dropping in the 106–115 day PSO samples (we note, however, that fewer samples are in this time bin (n=9) compared to the other bins (n=20); Fig. 2G).

In summary, in a large cross-sectional survey, IgG, but not IgA or IgM levels persisted for at least 3 months PSO for all antigens measured, with the levels of antibodies to the spike trimer being more stable over time than those to the RBD and NP. Neutralizing antibodies levels mirrored these antibody levels, though the drop observed in the last bin (105–115 days PSO), which was not as powered as the other bins, will need to be investigated more closely.

Antibodies to SARS-CoV-2 antigens are detected in the saliva of COVID-19 patients

While our serum-based assays are scalable and robust, saliva represents a relatively unexplored biofluid for detecting antibodies to SARS-CoV-2 antigens with many practical benefits, including being noninvasive and the capacity for self-collection at home. The disadvantage of saliva as a biofluid is its very low concentration of antibodies (26), making it necessary to optimize the sensitivity of detection.

We explored various assay designs and found that capturing biotinylated spike and RBD antigens on streptavidin-coated plates (rather than adsorbing non-biotinylated proteins directly on the ELISA plates) was required to obtain reliable signal-to-noise ratios. This method also required that the saliva be pre-adsorbed to remove any streptavidin-binding protein. While heat (65°C for 30 min) prevented detection of antibodies in the saliva, treatment of saliva samples with Triton X-100 was compatible with our assay (Figure S4) and resulted in viral inactivation (Table S2).

Bolstered by these findings, we first performed a pilot experiment, using expectorated saliva samples acquired during the early phase of the pandemic, measuring antibody levels to SARS-CoV-2 antigens in n=54 COVID-19 patients (cohort 1), comparing to unexposed negative controls collected locally (n=42).

Since these samples were diluted to varying degrees, we normalized values to total IgG/IgA (depending on the isotype assay) or to albumin levels as done before by others (27). The mean, standard deviation and concentration range of total IgA and IgG from the COVID-19 patients were 60.2 ± 99.2 μg/ml (4.6 μg/ml – 656.9 μg/ml) and 25.5 ± 47.7 μg/ml (2.5 μg/ml – 275.1 μg/ml), respectively. The mean, standard deviation and concentration range of total IgA and IgG from the unexposed negative controls were 89.3 ± 72.7 μg/ml (7.0 μg/ml – 452.9 μg/ml) and 7.0 ± 7.8 μg/ml (2.4 μg/ml – 48.8 μg/ml), respectively.

The mean, standard deviation and concentration range of albumin from the COVID-19 patients and unexposed negative controls were 9.6 ± 8.1 μg/ml (1.3 μg/ml – 32.6 μg/ml) and 9.3 ± 9.4 μg/ml (1.2 μg/ml – 45.8 μg/ml), respectively. Saliva samples from COVID-19 patients displayed a significantly higher level of IgG and IgA levels to spike and RBD compared to negative controls when normalized with either method (Figure S5).

Following this pilot experiment, we proceeded with further saliva collections using Salivettes® to standardize our collection method without using a diluent (cohort 2) in order to measure IgG, IgA and IgM levels to both spike and RBD antigens. In cohort 2, we obtained n=90 samples from 80 patients ranging in time PSO from day 3–104. These were compared to 50 unexposed negative controls for cohort 2, of which 42 were also negative controls for cohort 1. To these negative controls, we also added pre-COVID era saliva samples as an additional comparator (n=27).

Our antigen assays had a working volume of 50 μl in each well, and in these assays, we measured anti-spike and anti-RBD antibodies in the samples at three dilutions: 1/5, 1/10 and 1/20. In every experimental plate, we ran a positive control (pooled saliva from several COVID-19 patients) and negative control (pooled saliva from unexposed subjects) also plated at 1/5, 1/10 and 1/20. We measured the area under the curve of every sample and performed a normalization to the internal plate controls as shown in Figure S6.

We reported the normalized values as a percentage of the positive control (denoted as “integrated score”). While we did not normalize to total Ig levels in cohort 2, we still measured Ig levels in the saliva of COVID-19 patients and negative controls. The working volume of these experiments was 50 μl and several different dilution series were run for each sample, depending on the antibody isotype being measured, to best determine total IgA/M/G concentrations.

Total IgG levels, but not IgA or IgM levels, were found to be higher in COVID-19 patients compared to controls (Fig. 4A-C). Moreover, cohort 2 exhibited statistically significant differences between the relative levels of IgG, IgA and IgM antibodies specific to spike and RBD antigens compared to saliva from negative controls (Fig. 4D-I).

The sensitivity of the saliva assays for IgG antibodies to spike and RBD (at a false discovery rate <2%) were 89% and 85%, respectively, while the sensitivity of the assays for IgA antibodies to spike and RBD were 51% and 30%, respectively, and the sensitivity of the assays for IgM antibodies to spike and RBD were 57% and 33%, respectively. (Figure S7 and Table S3).

The lower sensitivity of the IgA assays is attributed in part to the higher levels of anti-spike and anti-RBD IgA levels in the negative controls (see Discussion).

Fig. 4 Cross-sectional analysis of antibody responses to the spike and RBD antigens of SARS-CoV-2 in saliva.
Saliva specimens from the cohort of COVID-19 patients were tested for the presence of IgG, IgA and IgM antibodies to SARS-CoV-2 spike and RBD antigens (Positive), comparing with a mixture of unexposed asymptomatic controls collected locally and pre-COVID era controls (Negative). In these cohort 2 samples collected in Salivettes® we had sufficient material to perform several dilutions and to generate an integrated score for each subject (see Methods). Because the saliva was not diluted during collection, we were able to derive the concentration of antibodies in both negative controls and COVID-19 patients. (A-C) Total IgG, IgA and IgM levels in the saliva. (D-I) Saliva data for negative controls versus COVID-19 patients. Solid bars denote the median and dotted line represents the median across all samples used in the plot. Mann-Whitney U test for significance was performed. **** = p < 0.0001, n.s. = not significant.

Next, we examined the levels of anti-spike and anti-RBD antibodies in our cross-sectional cohort over time PSO. Similar to the serum data, IgG levels in saliva to the spike and RBD antigens remained stable throughout the 3-month collection period. In contrast, significant decreases were observed for IgA levels to spike and RBD (ρ=-0.307 and ρ=-0.300, respectively), and similar results were observed for IgM levels to spike and RBD (ρ=-0.33 and ρ=-0.32, respectively). By day 100, anti-spike and anti-RBD IgA and IgM levels were barely detectable (Fig. 5). In summary, infection with SARS-CoV-2 results in detectable IgG, IgA and IgM responses in saliva against the spike and RBD antigens, with only the IgG response persisting beyond day 60.

Fig. 5 A cross-sectional analysis of antibody responses to the spike and RBD antigens of SARS-CoV-2 in saliva correlated with time PSO.
A second cohort of COVID-19 patients (n=90) was tested for the presence of IgG and IgA antibodies to SARS-CoV-2 spike and RBD antigens in the saliva, comparing with a mixture of unexposed negative controls collected locally and pre-COVID era negative controls. (A-F) Saliva data for all 6 antigen-specific ELISA readouts plotted as time PSO. Spearman correlation coefficients (ρ) and p-value are indicated. In multivariable analysis adjusted for age, sex and severity of illness, there was a significant decline in anti-RBD and anti-spike IgA, but not significant change in the level of anti-RBD or anti-spike IgG.

Antibody levels to SARS-CoV-2 antigens in the serum correlate with those in the saliva

As mentioned, saliva has many advantages for biofluid collection over serum. To assess whether saliva might be reliably used in a diagnostic test, we determined whether the antibody levels to spike and RBD in the saliva correlated with those measured in the serum. Of the COVID-19 patients analyzed, n=71 had paired saliva and serum samples taken at similar timepoints (i.e., within 4 days).

We observed a significant positive correlation between saliva and serum for each antigen-antibody combination (Fig. 6; values are plotted on log scales; see legend for details). Correlations for anti-RBD and anti-spike IgG (ρ=0.71, ρ=0.54), and anti-RBD and anti-spike IgM (ρ=0.65, ρ=0.58) were stronger than those for the levels of serum and saliva anti-RBD and anti-spike IgA (ρ=0.39 and ρ=0.54 respectively).

Therefore, at least for anti-spike IgM and anti-RBD IgG measurements, saliva may represent a good alternative for antibody testing.

Fig. 6
Correlation of IgG, IgA and IgM responses to the spike and RBD antigens in serum and saliva. (A-F) A subset of serum and saliva sample pairs (n=71) collected from the same patient within 4 days were analyzed for correlations in levels of anti-spike and anti-RBD IgG, IgA and IgM antibodies. For serum, data are presented as ratio-normalized ELISA reads, while the saliva results are expressed as an integrated score, as in previous figures. The data are presented on a logarithmic scale. Spearman correlation coefficient (ρ) and p-value are indicated.

DISCUSSION

Antibodies are key components in the arsenal of protective immunity against novel viral infections such as SARS-CoV-2. Understanding their durability and their system compartmentalization across a diverse population are critical pieces of data informing our ability to monitor seroprevalence in communities, to select plasma donors for treatment, and to design vaccines against COVID-19.

We examined the stability of antibody levels over the first three months after infection in both the serum and the saliva. We observed no drastic decline in levels of anti-spike, anti-RBD or anti-NP IgG levels over a 3-month period. The same was true for the antigen-specific measurements in saliva (anti-spike and anti-RBD IgG).

On the other hand, similar to other findings (28, 29), IgA and IgM responses to SARS-CoV-2 antigens were found to decline in both serum and saliva.

In summary, our data show that a durable IgG response against SARS-CoV-2 antigens is generated in both the saliva and serum in most patients with COVID-19.

Of the three isotypes measured, the IgA response correlates the least between serum and saliva, particularly for the RBD antigen.

This may suggest some compartmentalization of the IgA response in the oral cavity versus the periphery.

Given the presence of SARS-CoV-2 RNA in saliva, it is reasonable to hypothesize that, like other viruses such as rubella (26), 229E alpha-coronavirus (30), and MERS beta-coronavirus (31), the mucosae and draining lymph nodes of the oro- and nasopharyngeal tracts serve as a site for initiation of an immune response to SARS-CoV-2.

If so, then plasma cells (PC) that produce antibodies to SARS-CoV-2 will migrate back to the oro- and nasopharyngeal mucosae and produce antibodies that should be detectable in the saliva, a fluid that already has high levels of IgA (32). With time, this response will be detected in the systemic circulation, possibly due to migration of PC into new niches as we have previously described in mice (33).

Indeed, we and two other groups have observed SARS-CoV-2 specific antibodies in saliva (34, 35). There are some variations between study protocols that are important to consider: Randad et al. applied a brush on the gum line as a means to capture IgG from the blood, heat inactivated this material, and performed multiplex antibody immunoassays using Luminex technology to detect antigen-specific antibody levels (35).

In contrast, our strategy was to collect saliva in a manner that best approximates the immune response that takes place in the local mucosa. In this way, our study more resembles that of Faustini et al., who used ELISA technology on whole saliva, amplifying the signal with an additional antibody step (34).

Although Faustini et al. employed saliva dilutions in the same range as what we used (1:5 to 1:20), the degree of correlation between the serum and saliva for each antibody/antigen ELISA pair was less obvious in that study than in ours (34). Whether these discrepancies are methodological (i.e., detection of specific versus total Igs) and/or relate to the higher number of asymptomatic subjects in the Faustini et al. study remains to be determined.

While the specificity of the saliva assays was very good for anti-spike and anti-RBD IgG responses based on ROC curves, this was less true for IgA, particularly the anti-RBD IgA response. This is because some of our negative controls, irrespective of whether they were collected during the pandemic (unexposed negatives) or prior to the pandemic, exhibit levels of anti-RBD IgA that approach 50% of the pooled control saliva (see Fig. 4H).

It is unclear why this would occur for only the IgA/RBD combination. Presumably these are cross-reactive IgA that bind to SARS-CoV-2 RBD. Of interest, thus far SARS-CoV-2 neutralizing antibodies appear to have limited somatic hypermutation (36, 37), suggesting that they may originate from a naïve repertoire or from B cells that have been activated in extrafollicular responses where somatic hypermutation is limited.

It is tempting to speculate that these pre-existing IgA antibodies may provide some stop-gap protection against SARS-CoV-2 in the oral cavity, and if so, it is essential to ascertain their original antigenic specificity. Future work is required to confirm these results in a greater array of subjects and using different sources of RBD antigen.

Our findings that the IgG response to SARS-CoV-2 antigens is stable over a 3-month period are consistent with other studies who likewise noted durability in the IgG response to the spike trimer (8–13). These data and ours contrast with those of Long et al., who showed rapid decay of antibody levels when profiling the response to a linear peptide motif of the C-terminal part of the spike protein (14) instead of the spike trimer used here, and it is possible that the antigen selection accounts for some of the differences.

However, this does not explain discrepant results with respect to the anti-NP response in the serum, which we find also largely persisted over the 3-month period. One potential difference that could explain these divergent results is that we employed a sensitive and robust chemiluminescence plate-based ELISA whereas Long et al. employed magnetic chemiluminescence enzyme immunoassay kits with immobilized recombinant or peptide antigens.

A limitation of our study is that we have not looked beyond the day 115 PSO – our collections began in mid-March 2020 – and it is entirely plausible that antigen-specific IgG levels will eventually wane with time. Although IgG antibodies to spike remained fairly stable, even at day 115 PSO, our surrogate neutralization assay revealed a dip in activity in the last time interval bin (days 116 – 115 PSO), consistent with some previous studies (9, 13, 14).

This final collection interval is not as well powered as the other bins, thus this requires further investigation. Nevertheless, a dip in neutralization activity using the surrogate assay does mirror the significant reduction in antigen-specific IgA (and IgM). The contributions of these isotypes to the overall neutralization activity at different time points after infection remains to be assessed.

Indeed, IgA is an important mediator of protection against gastrointestinal viruses (38), is essential in achieving immunity against avian viruses (39), has been shown to contribute to the neutralizing antibody (nAb) response to SARS-CoV-2 (28), and may even be a more potent nAb isotype than IgG (40).

In addition, a monoclonal antibody cloned from B cells derived from SARS-CoV-infected humanized mice was found to provide cross-reactive neutralizing activity to SARS-CoV-2 when engineered on the IgA backbone, and this neutralizing activity was further enhanced if the IgA was co-expressed with J chain to produce dimeric IgA and secretory component to produce secretory IgA – the form of IgA that is secreted at mucosal surfaces (41).

Although Sterlin et al. show that the initial IgA plasmablast response quickly declines, IgA-producing plasma cells have been shown to persist for decades in the gut mucosae of humans (42), and these will not be readily measurable in the blood. Indeed, we found that of all 3 isotypes measured, antigen-specific IgA levels in the saliva exhibited the poorest correlation with antigen-specific IgA levels in the serum.

When combined with the parallel formation of re-activatable memory B cells (43), many of which will be tissue-resident (25), the host has excellent mechanisms for mounting swift and robust humoral immunity upon pathogen re-exposure that may be missed using blood-based measurements. An epidemiological study that prospectively follows confirmed COVID-19 cases for several months will determine if these immunological principles hold true in the context of SARS-CoV-2 infection.

In conclusion, our study provides evidence that the IgG response to SARS-CoV-2 spike persists in the saliva and the serum, and that this response can be correlated between the two biofluids, particularly for IgG. Given that the virus can also be measured in saliva by PCR (16–19), using saliva as a biofluid for both virus and antibody measurements may have some diagnostic value.

Since SARS-CoV-2 initially replicates in the oro- and nasopharyngeal tracts, in the future it will be critical to characterize the nature and kinetics of salivary antibodies at the earliest time points post-infection in contact-traced individuals in order to determine if there are correlates of protection that impact viral setpoint and COVID-19 disease progression.

References and Notes

  1. M. Letko, A. Marzi, V. Munster, Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses. Nat. Microbiol. 5, 562–569 (2020). doi:10.1038/s41564-020-0688-ypmid:32094589
  2. J. D. Berry, K. Hay, J. M. Rini, M. Yu, L. Wang, F. A. Plummer, C. R. Corbett, A. Andonov, Neutralizing epitopes of the SARS-CoV S-protein cluster independent of repertoire, antigen structure or mAb technology. MAbs 2, 53–66 (2010). doi:10.4161/mabs.2.1.10788pmid:20168090
  3. F. Amanat, D. Stadlbauer, S. Strohmeier, T. H. O. Nguyen, V. Chromikova, M. McMahon, K. Jiang, G. A. Arunkumar, D. Jurczyszak, J. Polanco, M. Bermudez-Gonzalez, G. Kleiner, T. Aydillo, L. Miorin, D. S. Fierer, L. A. Lugo, E. M. Kojic, J. Stoever, S. T. H. Liu, C. Cunningham-Rundles, P. L. Felgner, T. Moran, A. García-Sastre, D. Caplivski, A. C. Cheng, K. Kedzierska, O. Vapalahti, J. M. Hepojoki, V. Simon, F. Krammer, A serological assay to detect SARS-CoV-2 seroconversion in humans. Nat. Med. 26, 1033–1036 (2020). doi:10.1038/s41591-020-0913-5pmid:32398876
  4. Q. X. Long, B.-Z. Liu, H.-J. Deng, G.-C. Wu, K. Deng, Y.-K. Chen, P. Liao, J.-F. Qiu, Y. Lin, X.-F. Cai, D.-Q. Wang, Y. Hu, J.-H. Ren, N. Tang, Y.-Y. Xu, L.-H. Yu, Z. Mo, F. Gong, X.-L. Zhang, W.-G. Tian, L. Hu, X.-X. Zhang, J.-L. Xiang, H.-X. Du, H.-W. Liu, C.-H. Lang, X.-H. Luo, S.-B. Wu, X.-P. Cui, Z. Zhou, M.-M. Zhu, J. Wang, C.-J. Xue, X.-F. Li, L. Wang, Z.-J. Li, K. Wang, C.-C. Niu, Q.-J. Yang, X.-J. Tang, Y. Zhang, X.-M. Liu, J.-J. Li, D.-C. Zhang, F. Zhang, P. Liu, J. Yuan, Q. Li, J.-L. Hu, J. Chen, A.-L. Huang, Antibody responses to SARS-CoV-2 in patients with COVID-19. Nat. Med. 26, 845–848 (2020). doi:10.1038/s41591-020-0897-1pmid:32350462
  5. L. Premkumar, B. Segovia-Chumbez, R. Jadi, D. R. Martinez, R. Raut, A. Markmann, C. Cornaby, L. Bartelt, S. Weiss, Y. Park, C. E. Edwards, E. Weimer, E. M. Scherer, N. Rouphael, S. Edupuganti, D. Weiskopf, L. V. Tse, Y. J. Hou, D. Margolis, A. Sette, M. H. Collins, J. Schmitz, R. S. Baric, A. M. de Silva, The receptor binding domain of the viral spike protein is an immunodominant and highly specific target of antibodies in SARS-CoV-2 patients. Sci. Immunol. 5, eabc8413 (2020). doi:10.1126/sciimmunol.abc8413pmid:32527802
  6. J. Zhao, Q. Yuan, H. Wang, W. Liu, X. Liao, Y. Su, X. Wang, J. Yuan, T. Li, J. Li, S. Qian, C. Hong, F. Wang, Y. Liu, Z. Wang, Q. He, Z. Li, B. He, T. Zhang, Y. Fu, S. Ge, L. Liu, J. Zhang, N. Xia, Z. Zhang, Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019. Clin. Infect. Dis. ciaa344 (2020). doi:10.1093/cid/ciaa344pmid:32221519
  7. N. M. A. Okba, M. A. Müller, W. Li, C. Wang, C. H. GeurtsvanKessel, V. M. Corman, M. M. Lamers, R. S. Sikkema, E. de Bruin, F. D. Chandler, Y. Yazdanpanah, Q. Le Hingrat, D. Descamps, N. Houhou-Fidouh, C. B. E. M. Reusken, B.-J. Bosch, C. Drosten, M. P. G. Koopmans, B. L. Haagmans, Severe Acute Respiratory Syndrome Coronavirus 2-Specific Antibody Responses in Coronavirus Disease Patients. Emerg. Infect. Dis. 26, 1478–1488 (2020). doi:10.3201/eid2607.200841pmid:32267220
  8. A. S. Iyera et al., Dynamics and significance of the antibody response to SARS-CoV-2 infection. MedRxiv, https://www.medrxiv.org/content/10.1101/2020.07.18.20155374v1 (2020).
  9. A. Wajnberg et al., SARS-CoV-2 infection induces robust, neutralizing antibody responses that are 1 stable for at least three months. medRxiv https://www.medrxiv.org/content/10.1101/2020.07.14.20151126v1 (2020).
  10. N. Baumgarth, J. Nikolich-Žugich, F. E. Lee, D. Bhattacharya, Antibody Responses to SARS-CoV-2: Let’s Stick to Known Knowns. J. Immunol. •••, ji2000839 (2020). doi:10.4049/jimmunol.2000839pmid:32887754
  11. T. J. Ripperger et al., Detection, prevalence, and duration of humoral responses to SARS-CoV-2 under conditions of limited population exposure. medRxiv, https://www.medrxiv.org/content/10.1101/2020.08.14.20174490v1 (2020).
  12. L. B. Rodda et al., Functional SARS-CoV-2-specific immune memory persists after mild COVID-19. medRxiv, (2020). doi:10.1101/2020.08.11.20171843
  13. K. H. D. Crawford et al., Dynamics of neutralizing antibody titers in the months after SARS-CoV-2 infection. MedRxiv https://www.medrxiv.org/content/10.1101/2020.08.06.20169367v1 (2020).
  14. Q. X. Long, X.-J. Tang, Q.-L. Shi, Q. Li, H.-J. Deng, J. Yuan, J.-L. Hu, W. Xu, Y. Zhang, F.-J. Lv, K. Su, F. Zhang, J. Gong, B. Wu, X.-M. Liu, J.-J. Li, J.-F. Qiu, J. Chen, A.-L. Huang, Clinical and immunological assessment of asymptomatic SARS-CoV-2 infections. Nat. Med. 26, 1200–1204 (2020). doi:10.1038/s41591-020-0965-6pmid:32555424
  15. R. Wölfel, V. M. Corman, W. Guggemos, M. Seilmaier, S. Zange, M. A. Müller, D. Niemeyer, T. C. Jones, P. Vollmar, C. Rothe, M. Hoelscher, T. Bleicker, S. Brünink, J. Schneider, R. Ehmann, K. Zwirglmaier, C. Drosten, C. Wendtner, Virological assessment of hospitalized patients with COVID-2019. Nature 581, 465–469 (2020). doi:10.1038/s41586-020-2196-xpmid:32235945
  16. J. Li et al., Virus-host interactome and proteomic survey of PMBCs from COVID-19 patients reveal potential virulence factors influencing SARS-CoV-2 pathogenesis. bioRxiv, 2020.2003.2031.019216 (2020).
  17. K. K. To, O. T.-Y. Tsang, C. C.-Y. Yip, K.-H. Chan, T.-C. Wu, J. M.-C. Chan, W.-S. Leung, T. S.-H. Chik, C. Y.-C. Choi, D. H. Kandamby, D. C. Lung, A. R. Tam, R. W.-S. Poon, A. Y.-F. Fung, I. F.-N. Hung, V. C.-C. Cheng, J. F.-W. Chan, K.-Y. Yuen, Consistent detection of 2019 novel coronavirus in saliva. Clin. Infect. Dis. 71, 841–843 (2020). doi:10.1093/cid/ciaa149pmid:32047895
  18. R. Sabino-Silva, A. C. G. Jardim, W. L. Siqueira, Coronavirus COVID-19 impacts to dentistry and potential salivary diagnosis. Clin. Oral Investig. 24, 1619–1621 (2020). doi:10.1007/s00784-020-03248-xpmid:32078048
  19. Z. Khurshid, F. Y. I. Asiri, H. Al Wadaani, Human Saliva: Non-Invasive Fluid for Detecting Novel Coronavirus (2019-nCoV). Int. J. Environ. Res. Public Health 17, 2225 (2020). doi:10.3390/ijerph17072225pmid:32224986
  20. I. R. Humphreys, C. de Trez, A. Kinkade, C. A. Benedict, M. Croft, C. F. Ware, Cytomegalovirus exploits IL-10-mediated immune regulation in the salivary glands. J. Exp. Med. 204, 1217–1225 (2007). doi:10.1084/jem.20062424pmid:17485516
  21. A. E. Campbell, V. J. Cavanaugh, J. S. Slater, The salivary glands as a privileged site of cytomegalovirus immune evasion and persistence. Med. Microbiol. Immunol. (Berl.) 197, 205–213 (2008). doi:10.1007/s00430-008-0077-2pmid:18259775
  22. J. Xu, Y. Li, F. Gan, Y. Du, Y. Yao, Salivary Glands: Potential Reservoirs for COVID-19 Asymptomatic Infection. J. Dent. Res. 99, 989 (2020). doi:10.1177/0022034520918518pmid:32271653
  23. A. McKie, A. Vyse, C. Maple, Novel methods for the detection of microbial antibodies in oral fluid. Lancet Infect. Dis. 2, 18–24 (2002). doi:10.1016/S1473-3099(01)00169-4pmid:11892490
  24. K. T. Abe et al., A simple protein-based SARS-CoV-2 surrogate neutralization assay. bioRxiv https://www.biorxiv.org/content/10.1101/2020.07.10.197913v1, (2020).
  25. J. L. Johnson, R. L. Rosenthal, J. J. Knox, A. Myles, M. S. Naradikian, J. Madej, M. Kostiv, A. M. Rosenfeld, W. Meng, S. R. Christensen, S. E. Hensley, J. Yewdell, D. H. Canaday, J. Zhu, A. B. McDermott, Y. Dori, M. Itkin, E. J. Wherry, N. Pardi, D. Weissman, A. Naji, E. T. L. Prak, M. R. Betts, M. P. Cancro, The Transcription Factor T-bet Resolves Memory B Cell Subsets with Distinct Tissue Distributions and Antibody Specificities in Mice and Humans. Immunity 52, 842–855.e6 (2020). doi:10.1016/j.immuni.2020.03.020pmid:32353250
  26. J. J. Ceron, E. Lamy, S. Martinez-Subiela, P. Lopez-Jornet, F. Capela E Silva, P. D. Eckersall, A. Tvarijonaviciute, Use of Saliva for Diagnosis and Monitoring the SARS-CoV-2: A General Perspective. J. Clin. Med. 9, 1491 (2020). doi:10.3390/jcm9051491pmid:32429101
  27. A. Aase, H. Sommerfelt, L. B. Petersen, M. Bolstad, R. J. Cox, N. Langeland, A. B. Guttormsen, H. Steinsland, S. Skrede, P. Brandtzaeg, Salivary IgA from the sublingual compartment as a novel noninvasive proxy for intestinal immune induction. Mucosal Immunol. 9, 884–893 (2016). doi:10.1038/mi.2015.107pmid:26509875
  28. D. Sterlin et al., IgA dominates the early neutralizing antibody response to SARS-CoV-2. medRxiv https://www.medrxiv.org/content/10.1101/2020.06.10.20126532v1, (2020).
  29. C. Cervia et al., Systemic and mucosal antibody secretion specific to SARS-CoV-2 during mild versus severe COVID-19. bioRxiv https://www.biorxiv.org/content/10.1101/2020.05.21.108308v1, (2020).
  30. K. A. Callow, H. F. Parry, M. Sergeant, D. A. Tyrrell, The time course of the immune response to experimental coronavirus infection of man. Epidemiol. Infect. 105, 435–446 (1990). doi:10.1017/S0950268800048019pmid:2170159
  31. D. Muth, V. M. Corman, B. Meyer, A. Assiri, M. Al-Masri, M. Farah, K. Steinhagen, E. Lattwein, J. A. Al-Tawfiq, A. Albarrak, M. A. Müller, C. Drosten, Z. A. Memish, Infectious Middle East Respiratory Syndrome Coronavirus Excretion and Serotype Variability Based on Live Virus Isolates from Patients in Saudi Arabia. J. Clin. Microbiol. 53, 2951–2955 (2015). doi:10.1128/JCM.01368-15pmid:26157150
  32. J. V. Parry, K. R. Perry, P. P. Mortimer, Sensitive assays for viral antibodies in saliva: An alternative to tests on serum. Lancet 2, 72–75 (1987). doi:10.1016/S0140-6736(87)92737-1pmid:2885575
  33. O. L. Rojas, A.-K. Pröbstel, E. A. Porfilio, A. A. Wang, M. Charabati, T. Sun, D. S. W. Lee, G. Galicia, V. Ramaglia, L. A. Ward, L. Y. T. Leung, G. Najafi, K. Khaleghi, B. Garcillán, A. Li, R. Besla, I. Naouar, E. Y. Cao, P. Chiaranunt, K. Burrows, H. G. Robinson, J. R. Allanach, J. Yam, H. Luck, D. J. Campbell, D. Allman, D. G. Brooks, M. Tomura, R. Baumann, S. S. Zamvil, A. Bar-Or, M. S. Horwitz, D. A. Winer, A. Mortha, F. Mackay, A. Prat, L. C. Osborne, C. Robbins, S. E. Baranzini, J. L. Gommerman, Recirculating Intestinal IgA-Producing Cells Regulate Neuroinflammation via IL-10. Cell 176, 610–624.e18 (2019). doi:10.1016/j.cell.2018.11.035pmid:30612739
  34. S. E. Faustini et al., Detection of antibodies to the SARS-CoV-2 spike glycoprotein in both serum and saliva enhances detection of infection. medRxiv, (2020).
  35. P. R. Randad et al., COVID-19 serology at population scale: SARS-CoV-2-specific antibody responses in saliva. medRxiv, (2020).
  36. C. Kreer, M. Zehner, T. Weber, M. S. Ercanoglu, L. Gieselmann, C. Rohde, S. Halwe, M. Korenkov, P. Schommers, K. Vanshylla, V. Di Cristanziano, H. Janicki, R. Brinker, A. Ashurov, V. Krähling, A. Kupke, H. Cohen-Dvashi, M. Koch, J. M. Eckert, S. Lederer, N. Pfeifer, T. Wolf, M. J. G. T. Vehreschild, C. Wendtner, R. Diskin, H. Gruell, S. Becker, F. Klein, Longitudinal Isolation of Potent Near-Germline SARS-CoV-2-Neutralizing Antibodies from COVID-19 Patients. Cell 182, 1663–1673 (2020). doi:10.1016/j.cell.2020.08.046pmid:32946786
  37. E. Seydoux, L. J. Homad, A. J. MacCamy, K. R. Parks, N. K. Hurlburt, M. F. Jennewein, N. R. Akins, A. B. Stuart, Y.-H. Wan, J. Feng, R. E. Whaley, S. Singh, M. Boeckh, K. W. Cohen, M. J. McElrath, J. A. Englund, H. Y. Chu, M. Pancera, A. T. McGuire, L. Stamatatos, Analysis of a SARS-CoV-2-Infected Individual Reveals Development of Potent Neutralizing Antibodies with Limited Somatic Mutation. Immunity 53, 98–105.e5 (2020). doi:10.1016/j.immuni.2020.06.001pmid:32561270
  38. S. E. Blutt, M. E. Conner, The gastrointestinal frontier: IgA and viruses. Front. Immunol. 4, 402 (2013). doi:10.3389/fimmu.2013.00402pmid:24348474
  39. H. Toro, I. Fernandez, Avian infectious bronchitis: Specific lachrymal IgA level and resistance against challenge. Zentralbl. Veterinärmed. B. 41, 467–472 (1994). doi:10.1111/j.1439-0450.1994.tb00252.xpmid:7701859
  40. Z. Wang et al., Enhanced SARS-CoV-2 Neutralization by Secretory IgA in vitro. bioRxiv https://www.biorxiv.org/content/10.1101/2020.09.09.288555v1, (2020).
  41. M. Ejemel, Q. Li, S. Hou, Z. A. Schiller, J. A. Tree, A. Wallace, A. Amcheslavsky, N. Kurt Yilmaz, K. R. Buttigieg, M. J. Elmore, K. Godwin, N. Coombes, J. R. Toomey, R. Schneider, A. S. Ramchetty, B. J. Close, D.-Y. Chen, H. L. Conway, M. Saeed, C. Ganesa, M. W. Carroll, L. A. Cavacini, M. S. Klempner, C. A. Schiffer, Y. Wang, A cross-reactive human IgA monoclonal antibody blocks SARS-CoV-2 spike-ACE2 interaction. Nat. Commun. 11, 4198 (2020). doi:10.1038/s41467-020-18058-8pmid:32826914
  42. O. J. Landsverk, O. Snir, R. B. Casado, L. Richter, J. E. Mold, P. Réu, R. Horneland, V. Paulsen, S. Yaqub, E. M. Aandahl, O. M. Øyen, H. S. Thorarensen, M. Salehpour, G. Possnert, J. Frisén, L. M. Sollid, E. S. Baekkevold, F. L. Jahnsen, Antibody-secreting plasma cells persist for decades in human intestine. J. Exp. Med. 214, 309–317 (2017). doi:10.1084/jem.20161590pmid:28104812
  43. N. L. Bernasconi, E. Traggiai, A. Lanzavecchia, Maintenance of serological memory by polyclonal activation of human memory B cells. Science 298, 2199–2202 (2002). doi:10.1126/science.1076071pmid:12481138
  44. M. E. Darnell, D. R. Taylor, Evaluation of inactivation methods for severe acute respiratory syndrome coronavirus in noncellular blood products. Transfusion 46, 1770–1777 (2006). doi:10.1111/j.1537-2995.2006.00976.xpmid:17002634
  45. D. Wrapp, N. Wang, K. S. Corbett, J. A. Goldsmith, C.-L. Hsieh, O. Abiona, B. S. Graham, J. S. McLellan, Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 367, 1260–1263 (2020). doi:10.1126/science.abb2507pmid:32075877
  46. A. Poulain, A. Mullick, B. Massie, Y. Durocher, Reducing recombinant protein expression during CHO pool selection enhances frequency of high-producing cells. J. Biotechnol. 296, 32–41 (2019). doi:10.1016/j.jbiotec.2019.03.009pmid:30885656
  47. A. Poulain, S. Perret, F. Malenfant, A. Mullick, B. Massie, Y. Durocher, Rapid protein production from stable CHO cell pools using plasmid vector and the cumate gene-switch. J. Biotechnol. 255, 16–27 (2017). doi:10.1016/j.jbiotec.2017.06.009pmid:28625678
  48. D. K. Kim, J. J. Knapp, D. Kuang, A. Chawla, P. Cassonnet, H. Lee, D. Sheykhkarimli, P. Samavarchi-Tehrani, H. Abdouni, A. Rayhan, R. Li, O. Pogoutse, É. Coyaud, S. van der Werf, C. Demeret, A. C. Gingras, M. Taipale, B. Raught, Y. Jacob, F. P. Roth, A Comprehensive, Flexible Collection of SARS-CoV-2 Coding Regions. G3 (Bethesda) 10, 3399–3402 (2020). doi:10.1534/g3.120.401554pmid:32763951
  49. S. Miersch et al., Synthetic antibodies neutralize SARS-CoV-2 infection of mammalian cells. bioRxiv https://www.biorxiv.org/content/10.1101/2020.06.05.137349v2, (2020).
  50. A. Banerjee, J. A. Nasir, P. Budylowski, L. Yip, P. Aftanas, N. Christie, A. Ghalami, K. Baid, A. R. Raphenya, J. A. Hirota, M. S. Miller, A. J. McGeer, M. Ostrowski, R. A. Kozak, A. G. McArthur, K. Mossman, S. Mubareka, Isolation, Sequence, Infectivity, and Replication Kinetics of Severe Acute Respiratory Syndrome Coronavirus 2. Emerg. Infect. Dis. 26, 2054–2063 (2020). doi:10.3201/eid2609.201495pmid:
  51. J. Pallesen, N. Wang, K. S. Corbett, D. Wrapp, R. N. Kirchdoerfer, H. L. Turner, C. A. Cottrell, M. M. Becker, L. Wang, W. Shi, W.-P. Kong, E. L. Andres, A. N. Kettenbach, M. R. Denison, J. D. Chappell, B. S. Graham, A. B. Ward, J. S. McLellan, Immunogenicity and structures of a rationally designed prefusion MERS-CoV spike antigen. Proc. Natl. Acad. Sci. U.S.A. 114, E7348–E7357 (2017). doi:10.1073/pnas.1707304114pmid:28807998
  52. Z. Li, I. P. Michael, D. Zhou, A. Nagy, J. M. Rini, Simple piggyBac transposon-based mammalian cell expression system for inducible protein production. Proc. Natl. Acad. Sci. U.S.A. 110, 5004–5009 (2013). doi:10.1073/pnas.1218620110pmid:23476064

More information: Gemma Moncunill et al, SARS-CoV-2 seroprevalence and antibody kinetics among health care workers in a Spanish hospital after three months of follow-up, The Journal of Infectious Diseases (2020). DOI: 10.1093/infdis/jiaa696

LEAVE A REPLY

Please enter your comment!
Please enter your name here

Questo sito usa Akismet per ridurre lo spam. Scopri come i tuoi dati vengono elaborati.