Reference
Reference TypeLiterature
TitlePattern recognition in pulmonary tuberculosis defined by high content peptide microarray chip analysis representing 61 proteins from M. tuberculosis.
AuthorsSimani Gaseitsiwe; Davide Valentini; Shahnaz Mahdavifar; Isabelle Magalhaes; Daniel F Hoft; Johannes Zerweck; Mike Schutkowski; Jan Andersson; Marie Reilly; Markus J Maeurer
AffiliationsDepartment of Microbiology, Tumor and Cell Biology Center (MTC), Karolinska Institutet Stockholm, Stockholm, Sweden.
JournalPLoS One
Year2008
AbstractBACKGROUND: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M. tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations. METHOD: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M. tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations.We constructed a high-content peptide microarray with 61 M. tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/-. FINDINGS: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M. tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations.We constructed a high-content peptide microarray with 61 M. tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/-.Three distinct patterns of IgG reactivity were identified: 89/7446 peptides were differentially recognized (in 34/34 TB+ patients and in 35/35 healthy individuals) and are highly predictive of the division into TB+ and TB-, other targets were exclusively recognized in all patients with TB (e.g. sigmaF) but not in any of the healthy individuals, and a third peptide set was recognized exclusively in healthy individuals (35/35) but no in TB+ patients. The segregation between TB+ and TB- does not cluster into specific recognition of distinct MTB proteins, but into specific peptide epitope 'hotspots' at different locations within the same protein. Antigen recognition pattern profiles in serum from TB+ patients from Armenia vs. patients recruited in Sweden showed that IgG-defined MTB epitopes are very similar in individuals with different genetic background. CONCLUSIONS: Serum antibody-based target identification has been used to identify tumor-associated antigens (TAAs) for development of anti-cancer vaccines. A similar approach can be helpful to identify biologically relevant and clinically meaningful targets in M. tuberculosis (MTB) infection for diagnosis or TB vaccine development in clinically well defined populations.We constructed a high-content peptide microarray with 61 M. tuberculosis proteins as linear 15 aa peptide stretches with 12 aa overlaps resulting in 7446 individual peptide epitopes. Antibody profiling was carried with serum from 34 individuals with active pulmonary TB and 35 healthy individuals in order to obtain an unbiased view of the MTB epitope pattern recognition pattern. Quality data extraction was performed, data sets were analyzed for significant differences and patterns predictive of TB+/-.Three distinct patterns of IgG reac...
Curation Last Updated2023-08-18 20:41:28
Epitope
Epitope ID103747
Chemical TypeLinear peptide
Linear SequenceYIGISFLDQASQRGL
Source Molecule Nameperiplasmic phosphate-binding lipoprotein PSTS1 (PBP-1) (PSTS1)
Source OrganismMycobacterium tuberculosis
Starting Position247
Ending Position261
Epitope Reference Details
Epitope Structure DefinesEpitope containing region/antigenic site
Location of Data in ReferenceSupplementary Table 3
Immunization
Host OrganismHomo sapiens (human)
Host Details
Host GeolocationEurope
1st In Vivo Process
In Vivo Process TypeOccurrence of infectious disease
Disease Statetuberculosis
Disease StageChronic;OGMS:0000064
1st Immunogen
Epitope RelationSource Organism
Object TypeOrganism
OrganismMycobacterium tuberculosis
B Cell Assay
Qualitative MeasurementPositive
Method/Techniquemicroarray
Measurement ofqualitative binding
Assayed Antibody
Assayed Antibody Source MaterialSerum
Assayed Antibody Immunoglobulin DomainEntire Antibody
Assayed Antibody Purification StatusPolyclonal
Assayed Antibody Heavy Chain TypeIgG
Antigen
Epitope RelationEpitope
Chemical TypeLinear peptide
Linear SequenceYIGISFLDQASQRGL
Source Molecule Nameperiplasmic phosphate-binding lipoprotein PSTS1 (PBP-1) (PSTS1)
Source OrganismMycobacterium tuberculosis
Starting Position247
Ending Position261
Assay Reference Details
Assay Comments by IEDB CuratorA positive result is defined as a higher level of binding by sera from TB+ patients than by sera from TB- patients, i.e., negative results were bound by sera from TB+ patients, but at a lower level than the binding by sera from TB- patients.
Location of Assay Data in ReferenceSupplementary Table 3