minus (IgA/IgM/IgG) (Cod. S5393, Sigma, St. Louis, USA) was also used as a negative control in MN assay and ELISA. Three human serum samples containing heterologous neutralizing antibodies, provided by NIBSC (WHO 1st International Standard for Pertussis antiserum (lot. 06/140); WHO 2nd International Standard for antibody to influenza H1N1pdm virus (lot. 10/202); WHO 1st International Standard for Diphtheria Antitoxin (lot: 10/262)), plus a panel of commercial human serum samples (n=26, provided by BioIVT company (West Sussex, United Kingdom), with confirmed non SARS-CoV-2 virus cross reactivity (positive towards different HCoVs), were used to verify the specificity of the ELISA test.
Vero E6 cells, acquired from the American Type Culture Collection (ATCC -CRL 1586), were cultured in Dulbecco's Modified Eagle's Medium (DMEM) -High Glucose (Euroclone, Pero, Italy) supplemented with 2 mM L-Glutamine (Lonza, Milan, Italy), 100 units/mL penicillin-streptomycin mixture (Lonza, Milan, Italy) and 10% of Fetal Bovine Serum (FBS), at 37°C, in a 5% CO 2 humidified incubator. VERO E6 cells were seeded in a 96-well plate using D-MEM high glucose 2% FBS at a density of 1.5 x 10 6 cells per well, in order to obtain a 70-80% sub-confluent cell monolayer after 24 hours.
Five different purified recombinant S proteins (S1 and RBD domain) were tested for their ability to detect specific human antibodies: S1-SARS-CoV-2 (HEK293) Cod. REC31806-500, (Native Antigen, Oxford, UK); S1-SARS-CoV-2 (HEK293) Cod. SCV2-S1-150P (eEnzyme, Gaithersburg, MD, USA); S1-SARS-CoV-2 (HEK293) Cod. S1N-C52H3 (ACROBiosystems, Newark, DE, USA); Spike RBD-SARS-CoV-2 (Baculovirus-Insect cells) Cod. 40592-V08B and (HEK293) Cod. 40592-V08H (Sino Biological, Beijing, China). SARS CoV-2 -strain 2019-nCov/Italy-INMI1 -wild-type virus was purchased from the European Virus Archive Global (EVAg, Spallanzani Institute, Via Portuense, 292, 00148-00153, Rome). The virus was titrated in Biosecurity Level 3 laboratories (BSL) in serial 1-log dilutions to obtain a 50% tissue culture infective dose (TCID 50 ) on 96-well culture plates of VERO E6 cells. The plates have been observed daily for the presence of cytopathic effect (CPE) by means of an inverted optical microscope for a total of 4 days. The end-point titers were calculated according to the Spearman-Karber formula [18] .
The MN assay was performed as previously reported by Manenti et al. [19] . Briefly, 2-fold serial dilutions of heat-inactivated serum samples were mixed with an equal volume of viral solution containing 100 TCID 50 of SARS-CoV-2. The serum-virus mixture was incubated for 1 hour at 37°C in a humidified atmosphere with 5% CO 2 . After incubation, 100 µl of the mixture at each dilution was passed to a 96-well cell plate containing a 70-80% confluent VERO E6 monolayer. The plates were incubated for 3 days at 37°C in a humidified atmosphere with 5% CO 2 . After the incubation time, each well was inspected by means of an inverted optical microscope to evaluate the percentage of CPE. The highest serum dilution that protected more than 50% of cells from CPE was taken as the neutralization titer. expressed and purified from HEK 293 cells. After overnight incubation at +4°C, coated plates were washed three times with 300 µl/well of ELISA washing solution containing Tris Buffered Saline (TBS)-0.05% Tween 20, then blocked for 1 hour at 37°C with a solution of TBS containing 5% of Non-Fat Dry Milk (NFDM; Euroclone, Pero, Italy). Serum samples were heat-inactivated at 56°C for 1 hour in order to reduce the risk of the presence of live virus in the sample. Subsequently, 3-fold serial dilutions, starting from 1:100 in TBS-0.05% Tween 20 5% NFDM, were performed up to 1:2700. Plates were washed three times, as previously; then 100 µl of each serial dilution was added to the coated plates by means of a multichannel pipette and incubated for 1 hour at 37°C. Next, after the washing step, 100 µl/well of Goat anti-Human IgG-Fc Horse Radish Peroxidase (HRP)-conjugated antibody or IgM (µ-chain) and IgA (α-chain) diluted 1:100,000 or 1:100,000 and 1:75,000, respectively, (Bethyl Laboratories, Montgomery USA) were added. Plates were incubated at 37°C for 30 minutes. Following incubation, plates were washed and 100 µl/well of 3,3′,5,5′-Tetramethylbenzidine (TMB) substrate (Bethyl Laboratories, Montgomery, USA) was added and incubated in the dark at room temperature for 20 minutes. The reaction was stopped by adding 100 µl of ELISA stop solution (Bethyl Laboratories, Montgomery, USA) and read within 20 minutes at 450 nm. To evaluate the OD a SpectraMax ELISA plate (Medical Device) reader was used. A cut-off value was defined as 3 times the average of OD values from blank wells (background: no addition of analyte). Samples with the ODs under the cut off value at the first 1:100 dilution were assigned as negative, samples where the ODs at 1:100 dilution were above the cut-off value were assigned as positive. Borderline samples were defined where one replicate was under the cut-off and the other was above.
An indirect ELISA was performed in order to determine the RBD-specific IgG1, IgG2, IgG3 and IgG4 antibody concentration in serum samples [20] . 96-well plates were coated with 1µg/mL of purified Spike-RBD (Sino Biologicals). Serum samples were diluted from 1:50 to 1:400. Mouse anti-human IgG1, IgG2, IgG3 and IgG4 Fc-HRP (Southern Biotech, USA) secondary antibodies were used at 1:8000 dilution. The cut-off values were established as reported above (paragraph 1.5.1).
ELISA plates were coated with 10 µg/mL of high affinity purified goat anti-human IgA antibodies (Bethyl Laboratories) than blocked for 1 hour at 37°C. 10 µl of each heat inactivated serum sample (positive for MN and IgA ELISA) were then seeded in an ELISA coated plate and incubated for 2 hours at 37°C. After the incubation time the serum samples were harvested and stored at +4°C until the MN assay.
Spearman's rank correlation analysis enabled us to determine whether, and to what extent, the MN assay was associated with the ELISAs. A classification analysis gave further insight into the relationship between the MN and the in-house ELISAs. We defined the MN as the target variable and recoded its results by assigning the label "0" to values of 5, and the label "1" otherwise. We implemented an elastic net (EN) to classify the Micro-neutralization titers (MNT). The EN is a rather sophisticated generalized linear model (GLM), which addresses the issues caused by multi-collinearity among predictors. We set the binomial family for the GLM after dichotomizing the variable MNT; therefore, we followed a logistic-like model approach in the implementation of the EN. The EN produces a selection of the variables based on a convex penalty function, which is a combination of the ridge regression and the LASSO (Least Absolute Shrinkage and Selection Operator) penalties, say l1 and l2 respectively, controlled by the hyper-parameter alpha = l2/(l1+l2). The hyper-parameter, lambda, by contrast, regulates the level of penalization in the model [21] . To improve the generalization capability of the EN, we trained the model over a randomly selected subset of data (121/181) and verified its robustness over an independent subset of the residual data (60/181), J o u r n a l P r e -p r o o f which did not enter the model during the training stage. The cross-validation technique prevented the occurrence of over-fitting problems in the estimates. On the base of the values of the predictors of the test set, X, and their estimated EN coefficients, b, we built a score function, S, as follows:
( )
The probability of a positive MNT assignment for the predicted results was then expressed as:
We calculated the performance of the EN in terms of sensitivity, i.e., the percentage of positive MNT correctly predicted, and specificity, i.e., the percentage of negative MNT correctly predicted, and represented their related Receiver Operating Characteristic (ROC) curve. The optimal combination of sensitivity and specificity enabled us to detect the cut-off in the score function; test samples were classified as positive if their score was above this cut-off value and as negative if the score was below it, with the minimum error probability.
Several purified recombinant S-proteins (S1 and RBD domain) were tested for their ability to detect specific human antibodies: S1-SARS-CoV-2 (HEK293) (from Native Antigen); S1-SARS-CoV-2 (HEK293) (from eEnzyme); S1-SARS-CoV-2 (HEK293) (from ACROBiosystems); Spike RBD-SARS-CoV-2 (Baculovirus-Insect cells) and (HEK293) (from Sino Biological). Each protein was evaluated using three coating concentrations (1, 2 and 3 µg/mL) and four different dilutions of the secondary HRP conjugate anti-human IgG, IgM and IgA antibodies. The optimal concentration chosen for antigen coating was 1 microgram/mL while the optimal dilution for the secondary HRP conjugate anti-human IgG, IgM was 1:100,000 and 1: 75,000 for anti-Human IgA. We also evaluated the impact of the incubation time of the HRP by incubating the plates for 1 hour or 30 minutes, and concluded that the best and clearest signal was always seen after the shortest incubation.
To set the assays, three human serum samples derived from convalescent donors, along with a pool of MN and ELISA (commercial Kit)-negative human serum samples, were used as positive and negative controls, respectively. As a test control, human IgG1 monoclonal antibody (mAb) anti-SARS-CoV-2 spike (S1) (CR3022 Native antigen), human IgM mAb anti-SARS-CoV-2 spike (S1) (CR3022 Absolute antibody) and human IgG1 anti-Spike RBD (SCV2-RBD eEnzyme) were used. Additionally, several human sera hyper-immune to various infectious diseases (influenza, diphtheria and pertussis) were used to assess the specificity of the assay in detecting only antibodies against SARS-CoV-2 S1 or the RBD protein. Alternative blocking/diluent solutions containing 1% Bovine Serum Albumin (BSA), 2.5% milk and 5% milk were tested. The specificity of the test increased significantly on using the 5% milk blocking solution in comparison with BSA, which occasionally yielded non-specific results and displayed a generally higher background. Finally, the two proteins that yielded the best results in terms of sensitivity and specificity were chosen as candidates for the tests: the purified S1-protein (HEK derived) from eEnzyme and the Purified RBD protein (HEK derived) from Sino Biological.
Each serum sample was tested by means of in-house ELISA S1 and RBD-specific IgG, IgM and IgA (VM_IgG_S1, VM_IgG_RBD, VM_IgM_S1, VM_IgM_RBD, VM_IgA_RBD) and by means of the Euroimmun S1 Commercial ELISA kit, along with the functional MN assay ( Table 1 ). The distribution of the microneutralisation titers (MNTs) was strongly asymmetric, with most of the values (153/181) being equal to 5 (i.e. negative). The other values observed (from 10 to 1280 in a 2-fold dilution series) were uniformly J o u r n a l P r e -p r o o f distributed. Concerning the ELISA S1, we performed two different tests: one by means of a commercial (Euroimmun) kit and the other an in-house ELISA. According to Spearman's rank correlation coefficients and statistical significance (Tables 3 and 4) , we registered the highest agreement between the ELISA VM_IgG_RBD and MNT, and between the VM_IgA_RBD and MNT, with coefficients of 0.83 and 0.85, respectively. The lowest correlations were found for ELISA Euroimmun vs MNT, and for VM_IgG_S1 vs MNT, with coefficients of 0.49 and 0.45, respectively. As can be seen from the correlation plot (Figure 1 ), the IgA response was closely linked with a positive MN response. Moreover, on dissecting all the results for each serum sample (data not shown), we noted that, in those subjects in whom we registered a high neutralization titer, we always observed a positive IgA signal. Interestingly, in 9 MNT-positive samples, we found a complete absence of S1 signal on using Euroimmun, VM_IgG_S1 and VM_IgM_S1 ELISA kits but, on the other hand, high and detectable IgG and IgM RBDspecific signals.
To confirm the analytical specificity of the in-house RBD of the in-house RBD-ELISA test, commercial human serum samples with confirmed non-SARS-COV-2 Coronavirus cross-reactivity (positives towards different HCoVs) were tested and the selectivity of this test to discriminate between IgG/IgM and IgG only responses in COVID-19 positive samples was evaluated. Among these samples 5 were confirmed positives for IgG and IgM, while 3 samples were confirmed IgG positives and IgM negatives. For all the remaining 18 samples, positives towards different HCoV strains, (from n.9 to n.26) no cross-reactivity was confirmed and these panel of sera were tested by In-house RBD ELISA (Table 2) . Figure 1 . The correlation plot associated to the measured coefficients of Spearman's rank correlation. The magnitude of the coefficient is represented by circles and a color gradient: the larger the area of the circle and the more intense the tone of the color, the greater the correlation. The direction of the correlation is indicated by the color scale: blue tones for positive correlations and red tones for negative correlations.
Over a training set of data, the optimal hyper-parameters estimated for the Elastic Net (EN) model were lambda=0.0136 and alpha=0.76, which minimized the error of cross-validation (= 0.3809). The EN model selected three significant predictors of the MN results, namely VM-IgG-RBD, VM-IgM-RBD, and VM-IgA-RBD; the estimates of their coefficients were 0.0035, 0.0060 and 0.0013, respectively, while the intercept of the model was -2.9741. These results were entered into the score function, whereby we predicted the MNTs. From the ROC curve (Figure 2A) , we evaluated the performance of the predictions in terms of sensitivity and specificity. On balancing sensitivity and specificity, we obtained the optimal cut-off of 0.092, with sensitivity = 85.7 % (95% CI = [42.1% -99.6%]) and specificity = 98.1% (95% CI = [89.9% -99.6%]) ( Figure 2B ). Overall, these findings indicated that the in-house RBD-based ELISA methods were highly accurate and, particularly, presented the features of a highly specific diagnostic test when jointly considered. 
The samples, which yielded a score below the identified cut-off, were classified as "negative", and the remaining samples as "positive". We then compared these predictions with the known results of the testset ( Figure 2C ). 
We also evaluated the ELISA IgG subtyping response (IgG1, IgG2, IgG3, and IgG4) in a small subgroup (14) of MN-positive samples. ELISA plates were coated with RBD purified antigen. Our results, although derived from a small group of subjects, are in line with previous findings by Amanat and colleagues [22] . Strong reactivity for IgG1 and IgG3 was found in almost all samples, with the IgG3 subclass showing the highest percentage of detection. Low and very low reactivity was found for IgG4 and IgG3, respectively ( Figure 3) . 
Due to the high correlation observed between the IgA ELISA and MN results we tried to assess the real contribution of the IgA antibodies on the neutralizing potency of the serum samples. As is possible to observe in figure 4 and Table 5 , after the sample treatment we registered an evident decrease in the neutralizing titers. Interesting is the fact that the decrease is showed only in those sera that showed high starting neutralizing titers. Samples with medium/low MNTs did not show any decrease. 
Like most of the emerging infectious diseases that affect humans, this new HCoV also originated from animals [23, 24] . Owing to the rapid increase in some human practices, such as deforestation, urbanization and the husbandry of wild animal species, over the years the emergence of new pathogens has become an extremely serious problem. The rapid global spread of the novel SARS-CoV-2 is posing a serious health threat to the entire world. There is now an urgent need for well-standardized serological assays that can detect different classes of antibodies against the novel coronavirus, and which can be used alongside the classical diagnostic molecular methods such as RT-PCR. Indeed, due to the huge demand in the recent months, the availability of the reagents and equipment needed to promptly carry out analyses is still inadequate. Moreover, if sample collection and storage are improperly conducted,molecular tests may yield falsenegative results in subjects who carry the virus [25] . Previous studies on SARS-CoV-1 have shown that virusspecific IgG and IgM levels can be valid surrogate for serological diagnosis [26, 27] . Indeed, the present study had two major goals: a) to standardize and make as reliable as possible ELISA tests in order to detect different classes of immunoglobulins, and b) to broaden the data-set of information on comparisons between the results of different serological tests, which could be precious for future evaluation of serological diagnoses and vaccine assessments [28] . Specifically, in this study, ELISA results were always compared with those obtained by the functional assay (MN), which is commonly assumed as a benchmark and the gold standard. Since its first isolation and characterization, this new HCoV strain has been classified, according to the WHO guidelines, as BSL3 pathogen. This has placed some limits on the implementation of neutralization tests, as relatively few laboratories have level-3 biocontainment facilities. The ELISAs are a good surrogate for the MN assay in terms of sensitivity, safety and throughput [29] [30] [31] . However, it is very important to evaluate and estimate the best antigen/s to use in these platforms in order to obtain a reliable and similar response to that of the neutralization test, which indicates the functional response. This is why we compared all our results with those of the MNT. As in the case of influenza hemagglutinin [32] , antibodies specific to the RBD domain of the S-protein seem to strongly contribute to viral neutralization. In this study, together with the IgG, IgM and IgA analyses, we also evaluated the responses of IgG subclasses in those subjects who showed both a high RBD ELISA signal and proven neutralization activity. Our results are in line with previous findings [22] and confirm IgG1 and IgG3 as the subtypes with the strongest reactivity in all samples [33] . Only in a small number of subjects did we find IgG2 and IgG4 responses. IgG1 and IgG3 are involved in critical immunologic functions, such as neutralization, opsonization, complement fixation and antibody-dependent cellular cytotoxicity (ADCC). On the other hand, IgG2 plays an important role in protecting against infection by encapsulated microorganisms [34] ; IgG4 is generally a minor component of the total immunoglobulin response and is induced in response to continuous antigenic stimulation [35] .
Regarding the ELISA IgG, IgM and IgA, the main results can be summarized as follows: a) all the proposed statistical analyses indicated a close relationship between the results of MN and in-house RBD-based ELISAs, namely VM-IgG-RBD, VM-IgM-RBD and VM-IgA-RBD (results are in line with previous reports by Amanat and colleagues [22, 36] ); b) the cross-validation technique applied to the EN model allowed us to obtain robust results.
In the out-of-sample data (i.e., the randomly chosen test-data) highly accurate, and, particularly, highly specific performance was observed; c) in large-scale screening operations, it is very important to have a highly specific test, as this guards against the risk of misclassification of true-negative samples with a wide margin of certainty. A highly specific test is particularly useful in order to confirm a diagnosis already made by means of other methods, and when a false-positive result would have a great impact. Indeed, a highly specific test is of most help to the clinician when it provides a positive result. An overview of all the results yielded by ELISA and MN (data not shown), along with those obtained by treating the sample with anti-human IgA, reveals that the highest neutralization activity against SARS-CoV-2 is achieved when all three immunoglobulins, IgG, IgM and IgA are detected, as if to indicate the presence of a synergistic or additive effect between different classes of antibodies. This observation can be explained by the fact that the human population is completely naïve for SARS-CoV-2 and that IgG or IgM alone is not able to mount an ideal neutralizing immune response. Indeed, one of the most important features of adaptive immunity is the generation of immunological memory and the ability of the immune system to learn from its experiences of encounters with the same pathogen, thereby becoming more effective over time [37] . Interestingly, in nine samples, neither in-house nor commercial kits detected any IgG and IgM signal for the S1 protein, while a noticeable signal for RBD-specific IgG, IgM and IgA was detected. As all nine samples displayed exactly same trend, it seems that these results could be due to the folding of the three-dimensional S1 protein structure after the production in HEK293 cells, which could have masked some epitopes recognized by the antibodies expressed in these nine subjects. By contrast, these epitopes may be well exposed in the RBD protein and can be bound by antibodies, which would explain the differences in signals.
To conclude, these results confirm what has already been reported [38] , i.e. that the immune response to SARS-CoV-2 is very variable, but that antibodies targeting the RBD domain of Spike protein have an important role relatively to their neutralization activity.. However, it is unclear whether neutralizing antibodies to S protein are the major contributor to a protective immune response as evidenced by a recent study [39] . So, the present study constitutes preliminary research into the development of an ELISA that can semi-quantify anti-SARS-CoV-2 human antibodies in a specific and repeatable way. The next step will be to completely validate these ELISAs according to the criteria established by the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use [40] , and to analyze the performance and specificity of these tests with a panel human serum samples that are highly positive towards different HCoVs. J o u r n a l P r e -p r o o f Journal Pre-proof 