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Peptide-MHC cellular microarray with innovative data analysis system for simultaneously detecting multiple CD4 T-cell responses.

Ge X, Gebe JA, Bollyky PL, James EA, Yang J, Stern LJ, Kwok WW - PLoS ONE (2010)

Bottom Line: The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation.The data analysis system is reliable for T cell specificity and functional testing.Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings.

View Article: PubMed Central - PubMed

Affiliation: Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA.

ABSTRACT

Background: Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation.

Methodology/principal findings: We co-immobilized peptide:DR0401 complexes, anti-CD28, anti-CD11a and cytokine capture antibodies on the surface of chamber slides to generate a functional array that was able to detect rare Ag-specific T cell populations from previously primed in vitro T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells.

Conclusions/significance: The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings.

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Related in: MedlinePlus

The counts of epitope specific IFNgamma (A) or IL10 (B) response for each individuals.Each circle represents a diabetic (filled circle) or a non-diabetic subject (open circle). A Mann-Whitney test was used for statistical calculation.
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pone-0011355-g005: The counts of epitope specific IFNgamma (A) or IL10 (B) response for each individuals.Each circle represents a diabetic (filled circle) or a non-diabetic subject (open circle). A Mann-Whitney test was used for statistical calculation.

Mentions: A second, more challenging application was to compare self-antigen specific T cell responses in individuals expressing autoimmune Type 1 Diabetes susceptible Class II HLA-DR0401 haplotypes. We selected 10 epitopes derived from putative beta-cell self-antigens [9], [10], [11], [12], [13], [14], [15]. Purified CD4 T cells were stimulated with the candidate peptides in the presence of autologus antigen presenting cells to boost Ag-specific T cell frequencies prior the assays. The IFNgamma and the IL10 responses from T cells specific for the 10 candidate epitopes were investigated at the same time (Table 2). Like other cross-sectional studies, average −log[p] scores of T cell responses for T1D patients (n = 11) and non-diabetic individuals (n = 12) were compared (Table 3). Only the GAD65p70-specific IL10 response was significantly different between the two populations (p = 0.0315, Mann-Whitney test). The non-diabetic group was associated with higher GAD65p70 specific IL10 responses (0.4483±0.1609) than the T1D group (0.04909±0.04157). However, this difference of GAD65p70-specific IL10 responses between the two groups could be caused by chance alone since the p-value was higher than 0.05 after false discovery rate adjustment. The non-diabetic group was also associated with a trend of increased GAD65p15-specific IL10 responses (0.5817±0.1671) in comparison to the diabetic group (0.1973±0.1107). However, that difference was not statistically significant (p = 0.0777, Mann-Whitney test). We also examined the differences of T cell responses in a discontinuous trait fashion using a 95% confidence limit (p<0.05) to distinguish ambiguous results from those less ambiguous results. A positive response was defined as −log[p]≥1.30 (p≤0.05, 95% confidence limit), whereas a negative response was defined as −log[p]<1.30. A majority of subjects did not elicit any detectable IFNgamma or IL10 responses (Figure 5A–B). No donor responded to more than 4 epitopes. The counts of detectable epitope specific responses for each individual were almost evenly distributed between the diabetic and non-diabetic groups. For each individual epitope, no significant difference (Mann-Whitney Test) was detected between these two groups (Table 4), although there were trends showing that (i) GAD65p70-specific IFNgamma responses were slightly increased in T1D group; (ii) GAD65p15 and GAD65p35-specific IL10 responses were slightly increased in the non-diabetic group. Among all 10 epitopes we studied, GAD65p15 (6/23), PPIp57 (4/23), GAD65p70 (4/23) were associated with the most prevalent IFNgamma response while DMKp2 (5/22), GAD65p35 (4/23) and PPIp57 (3/23) were associated with the most prevalent IL10 responses (by examining the counts in Table 4).


Peptide-MHC cellular microarray with innovative data analysis system for simultaneously detecting multiple CD4 T-cell responses.

Ge X, Gebe JA, Bollyky PL, James EA, Yang J, Stern LJ, Kwok WW - PLoS ONE (2010)

The counts of epitope specific IFNgamma (A) or IL10 (B) response for each individuals.Each circle represents a diabetic (filled circle) or a non-diabetic subject (open circle). A Mann-Whitney test was used for statistical calculation.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2902358&req=5

pone-0011355-g005: The counts of epitope specific IFNgamma (A) or IL10 (B) response for each individuals.Each circle represents a diabetic (filled circle) or a non-diabetic subject (open circle). A Mann-Whitney test was used for statistical calculation.
Mentions: A second, more challenging application was to compare self-antigen specific T cell responses in individuals expressing autoimmune Type 1 Diabetes susceptible Class II HLA-DR0401 haplotypes. We selected 10 epitopes derived from putative beta-cell self-antigens [9], [10], [11], [12], [13], [14], [15]. Purified CD4 T cells were stimulated with the candidate peptides in the presence of autologus antigen presenting cells to boost Ag-specific T cell frequencies prior the assays. The IFNgamma and the IL10 responses from T cells specific for the 10 candidate epitopes were investigated at the same time (Table 2). Like other cross-sectional studies, average −log[p] scores of T cell responses for T1D patients (n = 11) and non-diabetic individuals (n = 12) were compared (Table 3). Only the GAD65p70-specific IL10 response was significantly different between the two populations (p = 0.0315, Mann-Whitney test). The non-diabetic group was associated with higher GAD65p70 specific IL10 responses (0.4483±0.1609) than the T1D group (0.04909±0.04157). However, this difference of GAD65p70-specific IL10 responses between the two groups could be caused by chance alone since the p-value was higher than 0.05 after false discovery rate adjustment. The non-diabetic group was also associated with a trend of increased GAD65p15-specific IL10 responses (0.5817±0.1671) in comparison to the diabetic group (0.1973±0.1107). However, that difference was not statistically significant (p = 0.0777, Mann-Whitney test). We also examined the differences of T cell responses in a discontinuous trait fashion using a 95% confidence limit (p<0.05) to distinguish ambiguous results from those less ambiguous results. A positive response was defined as −log[p]≥1.30 (p≤0.05, 95% confidence limit), whereas a negative response was defined as −log[p]<1.30. A majority of subjects did not elicit any detectable IFNgamma or IL10 responses (Figure 5A–B). No donor responded to more than 4 epitopes. The counts of detectable epitope specific responses for each individual were almost evenly distributed between the diabetic and non-diabetic groups. For each individual epitope, no significant difference (Mann-Whitney Test) was detected between these two groups (Table 4), although there were trends showing that (i) GAD65p70-specific IFNgamma responses were slightly increased in T1D group; (ii) GAD65p15 and GAD65p35-specific IL10 responses were slightly increased in the non-diabetic group. Among all 10 epitopes we studied, GAD65p15 (6/23), PPIp57 (4/23), GAD65p70 (4/23) were associated with the most prevalent IFNgamma response while DMKp2 (5/22), GAD65p35 (4/23) and PPIp57 (3/23) were associated with the most prevalent IL10 responses (by examining the counts in Table 4).

Bottom Line: The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation.The data analysis system is reliable for T cell specificity and functional testing.Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings.

View Article: PubMed Central - PubMed

Affiliation: Benaroya Research Institute at Virginia Mason, Seattle, Washington, USA.

ABSTRACT

Background: Peptide:MHC cellular microarrays have been proposed to simultaneously characterize multiple Ag-specific populations of T cells. The practice of studying immune responses to complicated pathogens with this tool demands extensive knowledge of T cell epitopes and the availability of peptide:MHC complexes for array fabrication as well as a specialized data analysis approach for result interpretation.

Methodology/principal findings: We co-immobilized peptide:DR0401 complexes, anti-CD28, anti-CD11a and cytokine capture antibodies on the surface of chamber slides to generate a functional array that was able to detect rare Ag-specific T cell populations from previously primed in vitro T cell cultures. A novel statistical methodology was also developed to facilitate batch processing of raw array-like data into standardized endpoint scores, which linearly correlated with total Ag-specific T cell inputs. Applying these methods to analyze Influenza A viral antigen-specific T cell responses, we not only revealed the most prominent viral epitopes, but also demonstrated the heterogeneity of anti-viral cellular responses in healthy individuals. Applying these methods to examine the insulin producing beta-cell autoantigen specific T cell responses, we observed little difference between autoimmune diabetic patients and healthy individuals, suggesting a more subtle association between diabetes status and peripheral autoreactive T cells.

Conclusions/significance: The data analysis system is reliable for T cell specificity and functional testing. Peptide:MHC cellular microarrays can be used to obtain multi-parametric results using limited blood samples in a variety of translational settings.

Show MeSH
Related in: MedlinePlus