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IMMUNOCAT-a data management system for epitope mapping studies.

Chung JL, Sun J, Sidney J, Sette A, Peters B - J. Biomed. Biotechnol. (2010)

Bottom Line: IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results.Through this system, we are able to perform queries and integrated analyses of the various types of data.This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

View Article: PubMed Central - PubMed

Affiliation: Division of Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla, CA 92037, USA.

ABSTRACT
To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established "IMMUNOCAT", an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

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ELICAT database: experimental design functionality. The figure shows two screens used to capture the experimental design of an ELISPOT experiment. By specifying the donor from whom T cells used in the experiment were derived, the experiment becomes linked to the information for that donor in DONORDB, and some fields such as the HLA alleles expressed by that donor become prepopulated. ELICAT also allows the users to specify the type of cytokines and cells used in the experiments (not shown here).
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fig5: ELICAT database: experimental design functionality. The figure shows two screens used to capture the experimental design of an ELISPOT experiment. By specifying the donor from whom T cells used in the experiment were derived, the experiment becomes linked to the information for that donor in DONORDB, and some fields such as the HLA alleles expressed by that donor become prepopulated. ELICAT also allows the users to specify the type of cytokines and cells used in the experiments (not shown here).

Mentions: ELICAT was designed for the management of data from ELISPOT assays. In these assays [13, 18], T cells are stimulated with peptide antigens, and those that respond by producing cytokines are visualized as individual spots. These recognized peptides are potential candidates for inclusion in an allergy vaccine. The experiments are performed on 96-well plates, and the numbers of spots are counted by an automated ELISPOT reader. The raw data generated is exported to a text file containing a matrix whose elements denote the number of spots detected in each well. This raw data is automatically imported into ELICAT, where it is connected with information about experimental design previously entered through the interface shown in Figure 5. An experiment is defined as one or more ELISPOT plates run with the same layout and cells from the same source. The plate layout specifies which wells are used to hold the tested peptides and which wells are used to hold the controls. The peptides used are specified in a separate file containing peptide identifiers.


IMMUNOCAT-a data management system for epitope mapping studies.

Chung JL, Sun J, Sidney J, Sette A, Peters B - J. Biomed. Biotechnol. (2010)

ELICAT database: experimental design functionality. The figure shows two screens used to capture the experimental design of an ELISPOT experiment. By specifying the donor from whom T cells used in the experiment were derived, the experiment becomes linked to the information for that donor in DONORDB, and some fields such as the HLA alleles expressed by that donor become prepopulated. ELICAT also allows the users to specify the type of cytokines and cells used in the experiments (not shown here).
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2871663&req=5

fig5: ELICAT database: experimental design functionality. The figure shows two screens used to capture the experimental design of an ELISPOT experiment. By specifying the donor from whom T cells used in the experiment were derived, the experiment becomes linked to the information for that donor in DONORDB, and some fields such as the HLA alleles expressed by that donor become prepopulated. ELICAT also allows the users to specify the type of cytokines and cells used in the experiments (not shown here).
Mentions: ELICAT was designed for the management of data from ELISPOT assays. In these assays [13, 18], T cells are stimulated with peptide antigens, and those that respond by producing cytokines are visualized as individual spots. These recognized peptides are potential candidates for inclusion in an allergy vaccine. The experiments are performed on 96-well plates, and the numbers of spots are counted by an automated ELISPOT reader. The raw data generated is exported to a text file containing a matrix whose elements denote the number of spots detected in each well. This raw data is automatically imported into ELICAT, where it is connected with information about experimental design previously entered through the interface shown in Figure 5. An experiment is defined as one or more ELISPOT plates run with the same layout and cells from the same source. The plate layout specifies which wells are used to hold the tested peptides and which wells are used to hold the controls. The peptides used are specified in a separate file containing peptide identifiers.

Bottom Line: IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results.Through this system, we are able to perform queries and integrated analyses of the various types of data.This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

View Article: PubMed Central - PubMed

Affiliation: Division of Vaccine Discovery, La Jolla Institute for Allergy & Immunology, La Jolla, CA 92037, USA.

ABSTRACT
To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established "IMMUNOCAT", an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.

Show MeSH