347 stainless steel chemical composition The magnitude of venous or capillary blood, specific for SARS-CoV-2, T-cell responses determines immunity to COVID-19.

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347 stainless steel chemical composition

Stainless Steel 347 Coil Tube Chemical Composition

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Stainless Steel 347 Coil Tube Mechanical Properties

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SARS-CoV-2-specific T cells are thought to protect against infection and progression of COVID-19, but there is no direct evidence for this. Here, we compared whole blood measurements of SARS-CoV-2-specific interferon-γ positive T cells with positive COVID-19 diagnostic test results (PCR and/or lateral flow) within 6 months of Lian’s blood collection. Among 148 participants who donated venous blood samples, the magnitude of SARS-CoV-2-specific T cell response was significantly higher in those who remained protected than in those who were infected (P < 0.0001). % risk of infection, while high intensity reduced this risk to 5.4%. These results were generalized to an additional 299 participants who tested a scalable capillary blood assay that could facilitate access to population-scale T-cell immunity data (14.9% vs. 4.4%). Thus, the measurement of T cells specific for SARS-CoV-2 can predict the risk of infection and should be evaluated when monitoring individual and population immune status.
Measuring and understanding the immune response to SARS-CoV-2 infection is important to develop effective future strategies to minimize the public health and economic impacts of future COVID-19 outbreaks. Identification of immune correlates will provide important information about a population’s susceptibility to viral infection, possibly early warning of peak hospitalizations, and also allow people to personally manage their risk of infection and the risk of infecting others. Immune surveillance has proven critical to evaluate the effectiveness of COVID-19 vaccines in healthy and high-risk patients1,2,3 especially in SARS-CoV-24 mutants, and the detection of immunocompromised will mean the need to boost Immunity Get vaccinated and prevent future outbreaks .
An individual’s level of immunity to SARS-CoV-2 infection depends on multiple factors: viral load at the time of exposure, virus variants, age, previous vaccination/infection status, comorbidities, medications, and most importantly, anti-SARS-CoV infection. 2 adaptive immune response occurs at the time of exposure to the virus5. Evaluation of the immune response to SARS-CoV-2 infection and/or vaccination has focused on serological assays that measure the presence of antibodies specific for a structural protein (eg spike glycoprotein). However, the presence or absence of antibodies alone does not accurately determine a protective immune response, as responses are significantly attenuated over time6 and neutralization of SARS-CoV-2 variants in recovering or double-vaccinated individuals Weak activity, which could lead to a large number of breakthrough infections7. Indeed, protection against symptomatic COVID-19 caused by the Omicron variant (B.1.1.529) waned to about 10% after only 4–6 months of mRNA vaccination, although protection against severe disease persisted >68% for at least 7 months8 . Measuring adaptive memory T cell responses, which confer long-term protection against viral infection, is the best indicator of susceptibility to SARS-CoV-2 infection, and therefore a better indication of the risk of testing positive for COVID-199, since specific T cells can prevent infection. without seroconversion10,11. However, the measurement of T cell responses has received less attention due to methodological difficulties and logistical problems in obtaining and transporting venous blood samples, especially when conducting large observational studies to assess vaccine efficacy and monitor immunity. However, vaccinated individuals show robust T cell activity against SARS-CoV-2 variants, potentially offsetting the loss of antibody reactivity to limit the severity of COVID-1912,13.
Here, we sought to understand whether a single measurement of SARS-CoV-2 T cell response could predict the absolute risk of SARS-CoV-2 infection within 6 months of blood sampling, regardless of prior immune-influencing factors. In order to make the T cell test high throughput and applicable to larger studies, we also tried to make the test miniaturized so that it can be performed using a capillary fingerstick blood sample.
We measured cellular and humoral immune responses in healthy donors using a combined detection of SARS-CoV-2 T cells and IgG antibodies based on whole venous blood (for participant characteristics, see March 2022 14. In vaccinated donors, SARS-CoV-2-specific T -cellular responses were determined by measuring plasma interferon-γ (IFN-γ) levels following whole blood stimulation with SARS-CoV-2 peptide (as previously, refs. 14,15,16,17,18) and IgG responses associated with nucleocapsid (N) were increased in those who reported a previous infection, although both responses were higher in previously infected unvaccinated donors, maximal in the body (Fig. 1a,b). IgG responses against spike glycoproteins (RBD, S1, S2) were highest in previously infected vaccinated donors (Figure 1c–e).
a SARS-CoV-2-specific IFN-γ+ T cell responses were measured by venous whole blood assay and based on participants’ vaccinations and prior SARS-CoV-2 infection status (confirmed by PCR and/or lateral flow test)’ Vac + /Inf +’ n = 60 (green), ‘Vac + /Inf-’ n = 82 (blue), ‘Vac-/Inf +’ n = 4 (yellow), ‘Vac-/Inf-’ n = 1 (not applied). SARS-CoV-2-specific IgG binding reactions target nucleocapsid (“N”) (b; ****P < 0.0001, **P = 0.0016), spiked receptor-binding domain (“RBD”) (c; **P = 0.0022, *P < 0.015), spike subunit 1 (“S1”) (d; ***P = 0.0005, *(Vac + /Inf+ vs. Vac + /Inf-) P = 0.022, *(Vac-/Inf+ vs. Vac+/Inf-) P = 0.012) and peak subunit 2 (“S2”) (e) was measured by venous whole blood tests and based on participant vaccination and prior SARS -CoV-2 (confirmed by PCR and/or lateral flow test) infectious status. ‘Vac + /Inf +’ n = 60 (green), ‘Vac + /Inf-’ n = 71-82 (blue), ‘Vac-/Inf +’ n = 4 (yellow). Comparisons were made using the Kruskal-Wallis test, adjusted for multiple comparisons using the Dunn test. The data is displayed as charts (center line at median, upper limit at 75th percentile, lower limit at 25th percentile) with whiskers at the minimum and maximum values. Each dot represents a donor. Raw data are provided in the form of raw data files.
After blood sampling, participants were asked to self-report positive PCR and/or lateral flow test results for COVID-19; if participants tested positive between 1 September 2021 and 29 December 2021, they were presumed to be infected with Delta (B.1.617.2) variant coronavirus and Omicron (B.1.1.529) to Public Health Wales after December 29, 2021, when this option of concern becomes dominant. Among 148 evaluable donors, we observed an infection rate of 26.3% (39/148) within 6 months of blood donation, 38 of whom received a second or third dose of the COVID-19 vaccine (the infection breakthrough occurred after Pfizer/BioNTech (BNT162b2) mRNA vaccine or AstraZeneca vaccine (ChAdOx1 nCoV-19)); an unvaccinated donor was also infected. The magnitude of SARS-CoV-2-specific IFN-γ-positive T cell responses was significantly lower in those who reported a positive diagnostic test for COVID-19 than in uninfected donors (P < 0.0001; Fig. 2a), mainly due to optimal induction of T cell responses by vaccination in some participants (P = 0.050; Supplementary Fig. 1). There was no correlation between the magnitude of the IFN-γ+ T cell response and the time to a positive COVID-19 test result (Supplementary Figure 2). In contrast, neither RBD-, S1-, S2-binding IgG responses (Figures 2b–d) nor RBD-, S1-neutralizing antibody responses were specific for wild-type or delta SARS-CoV-2 (B.1.617 ). ) (Supplementary Fig. 3) can distinguish between people at risk of infection. However, low N-linked IgG responses against SARS-CoV-2 correlated with the risk of COVID-19 infection (P = 0.0084; Figure 2e); those who tested positive were 85% less likely (P = 0.00035; OR 0.15, 95). % CI: 0.047–0.39 (Supplementary Figure 4).
Venous blood samples from healthy donors (n = 148) assessed SARS-CoV-2-specific IFN-γ+ T-cell responses (a; ****P < 0.0001) and binding of the Spike receptor to the specific SARS-CoV-2 stimulus. domain (“RBD”) (b), spike 1 subunit (“S1″) (c), spike 2 subunit (“S2″) (d), and nucleocapsid (“N”) (e; **P = 0.0084 ). Participants who tested positive for COVID-19 (PCR and/or lateral flow) identified; all infections occurred within 6 months of blood sampling. Comparisons were made using a two-tailed Mann-Whitney test. The data is displayed as charts (center line at median, upper limit at 75th percentile, lower limit at 25th percentile) with whiskers at the minimum and maximum values. Each dot represents a donor. ns is not important. The heatmap f shows Spearman’s rank correlations between variables for the specified dataset. Comparisons that were not statistically significant were excluded from the matrix and marked with blank cells. Raw data are provided in the form of raw data files.
The preset diagnostic positive cutoff of 14 was considered too arbitrary to assess the risk of re-infection, so interquartile ranges were established to establish absolute risk parameters. The statistical model, which only included variables that had a significant effect on the results, showed that the magnitude of the SARS-CoV-2-specific IFN-γ+ T cell response was the most important immune biomarker for determining an individual’s chances of being tested for COVID. -19 positive (Figure 2f and Supplementary Figure 4). Patients with a SARS-CoV-2 specific IFN-γ+ T cell response in the third (194-489 pg/ml IFN-γ) and fourth (>489 pg/ml IFN-γ) quartiles 65% (P = 0.055; OR 0.35, 95% CI: 0.11–1.00) and 90% (P = 0.0050; OR 0.098, 95% CI: 0.014–0.42) had more participants. The chances are slim (Supplementary Fig. 4). Overall, participants with a SARS-CoV-2 specific T cell response from venous blood ≤79 pg/mL IFN-γ had a 43.2% risk of breakthrough infection at 6 months, compared with a response >489 pg/mL. ml of IFN-γ had a risk of infection of 5.4% (table 2).
Venous whole blood testing is limited in scope due to the need for sample collection by the phlebotomist. To increase the availability of T cell and IgG testing for SARS-CoV-2, an alternative capillary blood sampling method has been developed to allow participants to obtain fingerstick blood samples at home. To the best of our knowledge, there have been no previous reports on the measurement of antigen-specific T cell function in capillary blood samples. A strong correlation has previously been shown between lymphocyte counts obtained using comparable capillary and venous blood samples. In addition, it has been reported that whole blood-based assays measuring SARS-CoV-2-specific T cell responses use only 320 μL of venous blood,20 eliminating concerns about the frequency of progenitor T cells in capillary blood samples.
We used this high-throughput standardized collaborative assay of SARS-CoV-2 T cells and IgG antibodies based on capillary whole blood to measure cellular and humoral immune response in participants with various comorbidities and prior vaccination/infection status (Table 1). recruited from across the UK between 24 January and 14 March 202214. The majority (90.9%) of finger samples were correctly obtained and sent to the laboratory within 24 hours of collection. In some cases, samples were received within 48 hours of blood draw, but none of these samples passed quality control checks and did not affect overall T cell or antibody measurements (Supplementary Fig. 5). Although there were differences in the magnitude of the SARS-CoV-2-specific IFN-γ+ T cell response measured in respective capillary and venous blood samples in some individuals, there were no significant differences overall (P = 0.88; Supplementary Fig. 6 ). ).
SARS-CoV-2-specific IFN-γ+ T cell responses were significantly increased in vaccinated individuals who also reported a previous infection (P = 0.0001), but not significantly higher than in previously infected unvaccinated donor individuals ( P = 0.19, Fig. 3a). ). IgG responses against spike glycoprotein (RBD, S1, S2) were significantly higher in vaccinated donors than in unvaccinated donors, regardless of prior infection status (Figure 3b-d). Interestingly, the mean N-bound IgG response was highest in previously infected unvaccinated participants compared to vaccinated participants, although this did not reach significance (Figure 3e). Among unvaccinated and uninfected donors who self-declared, 15 of 37 (40.5%) participants were positive for N-linked IgG, above the previously established threshold of 2.0 BAU/mL14; these 15 participants Twelve of these patients tested positive for IFN-γ+ T cell response above the previously established threshold of 22.7 pg/mL IFN-γ14. Therefore, it is likely that these participants were previously infected with SARS-CoV-2 and were not tested for COVID-19 due to personal choice, lack of PCR and/or lateral flow equipment, or were asymptomatic. Although there was a significant correlation between T cell responses to IFN-γ+ and N-linked IgG levels in unvaccinated donors (P = 0.0044; Supplementary Figure, N-linked IgG response decreased faster than N-linked IgG response, whereas IFN-γ+ T cell responses were maintained regardless of vaccination status, although the number of donors at 50 weeks post-challenge was low (Supplementary Fig. 8).Vaccination type was generally little different in observed IgG responses specific for SARS-CoV- 2, T cells and RBD-associated, although participants who received two doses of BNT162b2 followed by mRNA1273 revaccination showed significantly higher levels of IFN-γ + T cells were more sensitive to SARS-CoV-2 than those who received two doses of ChAdOx1 and BNT162b2 (Supplementary Fig. 9) In addition, reported comorbidities had little overall difference in observed T cell responses compared to healthy donors (Supplementary Fig. 10).
a SARS-CoV-2-specific IFN-γ+ T cell responses were measured by whole blood capillary assay and were based on participants’ vaccinations and prior SARS-CoV-2 infectious status (confirmed by PCR and/or lateral flow test). ‘Vac + /Inf +’ n = 42 (green), ‘Vac + /Inf-’ n = 158 (blue), ‘Vac-/Inf +’ n = 33 (yellow), ‘Vac- /Inf-’ n = 37 (gray). ****P < 0.0001, ***P = 0.0001, *(Vac+/Inf- vs. Vac-/Inf-) P = 0.045, *(Vac-/Inf+ vs. Vac- /Inf-) P = 0.014. SARS-CoV-2 specific IgG binding reactions to the spike receptor binding domain (“RBD”) (b; ****P < 0.0001, ns: not significant), spike subunit 1 (“S1”) (c; * ***P < 0.0001, ns: not significant), spike subunit 2 (“S2″) (d; ****P < 0.0001, ***P = 0.0005, *P = 0.016 ) and nucleocapsid (“N”) (e; ****P < 0.0001, ns not significant) were measured using venous whole blood analysis and based on participants’ vaccinations and prior SARS-CoV-2 (confirmed by PCR and /or lateral flow analysis) Infections were subdivided by status. ‘Vac + /Inf +’ n = 46 (green), ‘Vac + /Inf-’ n = 182 (blue), ‘Vac-/Inf +’ n = 34 (yellow), ‘Vac-/Inf-’ n = 37 (gray). Comparisons were made using the Kruskal-Wallis test, adjusted for multiple comparisons using the Dunn test. The data is displayed as charts (center line at median, upper limit at 75th percentile, lower limit at 25th percentile) with whiskers at the minimum and maximum values. Each dot represents a donor. Raw data are provided in the form of raw data files.
As before, participants were asked to report positive PCR and/or lateral blood flow results for COVID-19; according to the UK Health Agency, participants were presumed to have been infected with the Omicron coronavirus (B.1.1.529) at the time of testing the positive virus variant, as it was the dominant variant in the UK during the study period. Among 299 evaluable donors, we observed an infection rate of 8.0% (24/299) within three months of capillary donation, seven of which were not vaccinated. The proportion of comorbidities among all participants was lower in those who tested positive for COVID-19 (10.7%) than those who tested negative for COVID-19 (24.4%, Table 1), which may be due to the fact that participants with certain diseases are more careful and protect against potential consequences such as diabetes and cancer. As observed in a venous blood cohort, SARS-CoV-2-specific interferon-γ (IFN-γ)-positive T cells measured in capillary blood samples from individuals reporting a positive diagnostic test for COVID-19. The response magnitude was significantly lower than in uninfected donors (P = 0.034; Figure 4a) due to the relatively poor induction of a T cell response by vaccination and/or prior infection (Supplementary Figure 11). Similarly, neither RBD-, S1-, S2-binding IgG responses (Figures 4b–d) nor RBD-, S1-neutralizing antibody responses were specific for wild-type or delta SARS-CoV-2 (B. 1.617). (Supplementary figure 12). Individuals at any significant risk of infection can be identified. In contrast to the venous cohort, N-related IgG responses also do not differentiate COVID-19 risk (Figure 4e), suggesting that the Omicron variant (B.1.1.529) increases immune evasion in previously infected individuals, as recently described 21. In contrast, the strength of the SARS-CoV-2-specific IFN-γ T cell response was again the most important variable in determining individual odds of testing positive for COVID-19 (Figure 4f). Overall, participants with a SARS-CoV-2-specific capillary T-cell response ≤23.7 pg/mL IFN-γ had a 14.9% risk of infection at three months compared to a response >141.6 pg/mL. ml IFN. -γ had a risk of infection of 4.4% (Table 2).
IFN-γ+ T cell responses specific for SARS-CoV-2 (a; *P = 0.034) and SARS-CoV-2 specific IgG-targeted receptor-binding domain (“RBD”) (b), spike subunit 1 (‘S1′) (c), spike subunit 2 (‘S2′) (d) and nucleocapsid binding reaction (‘N’) (e). Participants identified as positive for COVID-19 tests (PCR and/or lateral blood flow test), all infections occurred within 3 months of blood sampling. Comparisons were made using a two-tailed Mann-Whitney test. The data is displayed as charts (center line at median, upper limit at 75th percentile, lower limit at 25th percentile) with whiskers at the minimum and maximum values. Each dot represents a donor. ns is not important. The heatmap f shows Spearman’s rank correlations between variables for the specified dataset. Comparisons that were not statistically significant were excluded from the matrix and marked with blank cells. Raw data are provided in the form of raw data files.
As we move into the next phase of the COVID-19 pandemic, the focus will shift from prevention to individual risk management and identifying vulnerable members of society. Establishing correlates of immunity to COVID-19 is critical to effectively identify and treat these high-risk groups. There is now increasing evidence that T-cell immunity protects against SARS-CoV-2 infection and limits the severity of COVID-1910. The data presented here demonstrate that the combined strength of SARS-CoV-2-specific IFN-γ+ T cell responses against spike, membrane, and nucleocapsid structural proteins confer greater protection against COVID-19 than does antibody binding.19 promote or neutralize responses. and should be taken into account when assessing individual and/or herd immunity. RNA viruses such as SARS-CoV-2 or influenza A virus (IAV) avoid serological neutralization by rapidly evolving exposed B-cell epitopes on surface antigens recognized by antibodies. The protective immune response provided by T cells may reflect the targeting of epitopes from more conserved regions of viral proteins that cannot quickly escape an immune response. T cell-mediated protection against novel SARS-CoV-2 variants is similar to the heterosubtypic protection mediated by T cell targeting of conserved intrinsic proteins seen in IAV22,23 subtypes.
Despite the enormous potential for measuring the cellular immune response to COVID-19, relatively little attention has been paid to the development of accurate, high-throughput, standardized T-cell assays. The traditional complexities and costs associated with measuring T cell responses preclude the accurate determination of T cell immunity when screening for large population immunity. While several commercial whole blood peptide stimulation assays have recently become available, everyone currently requires a phlebotomist to obtain blood, limiting availability and scale. Capillary blood systems are widely used to determine the prevalence of SARS-CoV-2 antibodies in a population. We adapted capillary blood assays to perform whole blood peptide stimulation assays to assess T cell reactivity to SARS-CoV-2 structural proteins and SARS-CoV-2 specific antibody responses. In fact, the combined measurement of SARS-CoV-2-specific antibodies and T cells in the same capillary blood sample is very attractive: (i) reduces the need for multiple blood tests per participant, (ii) improves participant experience and understanding ; (iii) improve logistics and reduce duplication, (iv) reduce environmental impact as less laboratory consumables and sample delivery are required. Although overall IFN-γ reactivity was similar between matched venous and capillary blood samples, it was observed to be lower in the capillary blood cohort of participants (Fig. 4a) compared to the venous blood cohort (Fig. 2a). IFN-γ values ​​There are several explanations for this finding, namely, a large number of participants with comorbidities requiring immunosuppressive therapy were recruited into the capillary blood sampling cohort (Table 1) and Viability and/or function of T cells obtained from vascular samples may be low, especially taking into account the conditions of long-term storage of samples before peptide stimulation.
The currently widely available COVID-19 vaccine provides the best protection against severe disease for most recipients within 6 months of vaccination8. Encouragingly, despite the poor vaccine-induced serological neutralization of SARS-CoV-26,7 variants, T-cell responses elicited by vaccination against wild-type SARS-CoV-2 remained highly reactive, as 25 others emerged. The data we present here demonstrate the importance of a broader assessment of vaccine immunogenicity, highlighting vaccines with insufficient T-cell immunity to prevent sudden infection and persistent transmission of the virus. We also observed that many unvaccinated individuals recruited into the capillary cohort had a significant response of SARS-CoV-2-specific T cells (and N-binding IgG) regardless of previous vaccination, which is likely due to previous infection. Rather than vaccinate appropriate individuals, their risk of infection should be assessed based on their current immunization status and the informed choices made.
Limitations of this study include the assurance that participants self-reported infection with SARS-CoV-2 after blood collection to determine the relevance of immunity; some participants may have asymptomatic infection and are unable to undergo PCR and/or lateral flow testing for COVID-19. Our dataset also lacked information about participants’ medications at the time of blood sampling. In addition, given that all of our participants reported only mild/moderate symptoms or no symptoms, it was not possible to identify immune responses from our data set that predicted an increased risk of severe illness and hospitalization for COVID-19. However, the presence of CD8+ T cell responses against nucleocapsid-specific epitopes has recently been associated with protection against severe COVID-1926. In addition, the assay used here did not measure T cell responses to specific early expressed SARS-CoV-2 non-structural proteins that have recently been shown to preferentially accumulate in seronegative healthcare workers who have been in contact with infected patients. Based on this work, given the prevalence of community transmission at the time of recruitment and the high likelihood of contact infection in the population, the number of SARS-CoV-2 specific T cells found in our tests also appears to be capable of clearance. subclinical infections in our cohorts. Finally, we did not measure interleukin 2 production by T cells because our previous work demonstrated poor identification of SARS-CoV-214-specific T-cell responses, although IL-2-specific responses may indicate pre-existing cross-reactivity. cells associated with defense against SARS-CoV-211 infection.
Taken together, these data highlight the fundamental need for long-term longitudinal studies that incorporate SARS-CoV-2-specific T cell responses into measures of population-scale immunity. These efforts may be aided by the development of a new capillary blood test that measures T-cell response.
The research project recruited participants from February 2021 to March 2022. The cohort of healthy donors (n = 148) who donated venous blood samples consisted primarily of university staff and students participating in Cardiff University’s COVID-19 screening service or staff at a primary school in Cardiff. All participants were otherwise healthy and did not report taking any immunosuppressive drugs (see Table 1 for characteristics). The cohort of participants who donated capillary blood samples included all voluntary donors (aged 18+) from across the UK. Between January 24 and March 14, 2022, 342 participants were enrolled in the study, of whom 299 submitted blood samples to the laboratory. Many participants remained unvaccinated and/or reported serious comorbidities, including autoimmune diseases and cancer (see Table 1 for characteristics). This study received ethical approval from the Newcastle and North Tyneside 2 Research Ethics Committee (ID IRAS: 294246) and the Cardiff University School of Medicine Research Ethics Committee (SREC ref: SMREC 21/01). All participants gave written informed consent prior to inclusion. Participants did not receive any compensation for participating in this study.
Venous blood samples were obtained by venipuncture into 6 or 10 ml lithium or sodium heparin vacutainers (BD). Capillary blood samples were obtained with a finger lancet and then collected in heparin microcontainers (BD). A minimum of 400 µl of blood is required; any sample less than this amount will be rejected. Other reasons for sample rejection included massive coagulation and/or hemolysis and failure to collect viscous plasma for analysis (Supplementary Fig. 5). A total of 299 capillary blood samples were available for assessing antibody responses, of which 270 samples were also available for assessing T cell responses.
SARS-CoV-2 specific T cell responses were assessed using the COVID-19 Immuno-T assay (ImmunoServ Ltd) and performed as previously described14. Briefly, one 6 ml or 10 ml sodium heparin (BD) venous vacutainer was taken from each participant and processed in the laboratory within 12 hours of blood collection. Although most specimens were processed within 24 hours, one 400–600 μl heparinized microbleeding (BD) capillary blood was collected within 48 hours of fingerstick sampling. Venous and/or capillary blood samples were stimulated with separate peptide pools specific for SARS-CoV-2 (wild-type variant) as previously described14. This peptide library contains 420 15-mer sequences with 11 overlapping amino acids spanning the entire spike protein (S1 and S2) (S; NCBI protein: QHD43416 1), nucleocapsid phosphoprotein (NP; NCBI protein: QHD43423 2) and membrane glycoprotein (M ; NCBI protein: QHD43419 1) coding sequences (referred to as “S-/NP-/M-combinatorial peptide library”). All peptides were purified to >70%, dissolved in sterile water and used at a final concentration of 0.5 μg/ml per peptide. Samples were incubated at 37°C for 20-24 hours. The tubes were then centrifuged at 5000×g for 3 minutes and ~150 µl of plasma was collected from the top of each blood sample. Store plasma samples at -20°C for up to one month before running cytokine/antibody detection assays.
IFN-γ was measured using the IFN-γ ELISA MAX Deluxe Set (BioLegend, catalog number 430116) and performed according to the manufacturer’s instructions. Immediately after stop solution (2N H2SO4) was added, the microplate was read at 450 nm using a BioLegend Mini ELISA plate reader. IFN-γ was quantified by standard curve extrapolation using GraphPad Prism. Values ​​below the lower detection limit of the assay were recorded as 7.8 pg/ml, values ​​above the upper detection limit of the assay were recorded as 1000 pg/ml.
Anti-SARS-CoV-2 RBD/S1/S2/N IgG antibodies were measured using a Bio-Plex Pro Human IgG SARS-CoV-2 4-plex panel (Bio-Rad, cat. no. 12014634) and labeled according to manufacturer’s instructions . instructions . Samples reporting values ​​above the limit of quantitation were reanalyzed at a 1:1000 dilution. The average fluorescence intensity of the beads was measured on a Bio-Plex 200 instrument (Bio-Rad). Antibody concentrations were calculated by the VIROTROL SARS-CoV-2 single control assay (Bio-Rad) and converted to WHO/NIBSC 20/136 International Reference Standard Units (BAU/mL) using the manufacturer’s calibration factor.
RBD and S1 subunit-specific neutralizing antibodies against SARS-CoV-2 wild-type and delta (B.1.617) SARS-CoV-2 lines were measured using the Bio-Plex Pro Human SARS-CoV-2 Variant Neutralization Antibody Kit (Bio-Rad , part no. 12016897), according to the manufacturer’s instructions. Measure the average fluorescence intensity on the Bio-Plex 200 (Bio-Rad) and calculate the percent inhibition (i.e., neutralization) using the following formula:
Infectious neutralization assays for SARS-CoV-2 were performed as previously described28. Briefly, 600 PFU of wild-type SARS-CoV-2 were incubated with 3-fold serial dilutions of plasma in duplicate for 1 hour at 37°C. The mixture was then added to VeroE6 cells for 48 hours. Monolayers were fixed with 4% paraformaldehyde, permeabilized with 0.5% NP-40 and incubated for 1 hour in blocking buffer (PBS containing 0.1% tween and 3% skimmed milk). Primary antibody (anti-nucleocapsid 1C7, Stratech) was added to blocking buffer for 1 hour at room temperature. After washing, a secondary antibody (anti-mouse IgG-HRP, Pierce) was added to blocking buffer for 1 hour. Monolayers were washed, developed using Sigmafast OPD and read on a Clariostar Omega plate reader. Wells without virus, without virus but without antibodies, and normalized sera showing intermediate activity were included in each experiment as controls.
Statistical analysis was carried out in GraphPad Prism (version 9.4.1). The normality of the data set was tested using the Shapiro-Wilk test. Non-parametric criteria were used for all comparisons. The Mann-Whitney test was used for unpaired samples. All tests were two-sided with a nominal significance threshold of P ≤ 0.05.
The initial exploratory analysis of the dataset was done in R (version 4.0.3). This includes the development of Spearman’s univariate rank correlation matrix, where the correlation between two variables is represented by the size and color of the squares. Statistical significance between associations was calculated using Spearman’s rho, where values ​​≤0.05 were considered significant. Comparisons that were not statistically significant were excluded from the matrix and marked with blank cells. P-values ​​were adjusted for multiple comparisons using Holm’s correction. A binary logistic regression model was used to simulate the effect of variables in the dataset on positive response to COVID-19. IFN-γ T cell responses and anti-RBD/S1/S2/N IgG titer scores were converted into factors, where each individual was assigned to the appropriate quartile for each score. After that, an initial research model was developed using the glm function in the statistical package (V4.0.3). The odds ratios derived from this original model were extracted from the coefficients of the model using the ‘odds_plot’ function in the OddsPlotty package (V1.0.2). When developing the cross-validation model, we used the “bestglm” function from the bestglm package (V0.37.3) to limit user bias and ensure that the best subset of predictors can be selected. The method chosen was “exhaustive” and the information criterion used to assess model fit was AIC. The same workflow described above was used to obtain the odds ratio.
For more information on study design, see the Nature study abstract linked to this article.
Letters and requests for materials should be directed to Dr. Martin Scarr or Professor Andrew Godkin. This article provides the original data.
The R code used to create statistical models is publicly available without request29. Reprint information and licenses can be found at www.nature.com/reprints.
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