Feng Ge Similar Datasets
Project description:Seeking to identify HLA class I peptides that originate from vaccinia virus proteins to understand the mechanism of immune protection. Note that vaccinia-infected B cells will still continue to present (primarily) a wide variety of peptides originating from endogenous proteins; this data set contains evidence for more than 5000 such peptides. The objective and challenge is to detect and identify the peptides that originate from the pathogen (vaccinia virus) in the presence (background) of this large number of endogensous 'self' peptides. Keywords: Peptide search results from multiple injections of multiple strong cation exchange fractions combined into one set of results.
2009-08-31 | GSE10549 | GEO
Project description:Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease.
2010-07-14 | GSE19433 | GEO
Project description:Proteins involved in taking up cyclic peptides
| PRJNA837234 | ENA
Project description:Understanding the immune response to tuberculosis requires greater knowledge of humoral responses. To characterize antibody targets and the effect of disease parameters on target recognition, we developed a systems immunology approach that integrated detection of antibodies against the entire Mycobacterium tuberculosis proteome, bacterial metabolic and regulatory pathway information, and patient data. Probing ~4,000 M. tuberculosis proteins with sera from >500 suspected tuberculosis patients worldwide revealed that antibody responses recognized ~10% of the bacterial proteome. This result defines the immunoproteome of M. tuberculosis, which is rich in membrane-associated and extracellular proteins. Most serum reactivity during active tuberculosis focused onto ~0.5% of the proteome. Within this pool, which is selectively enriched for extracellular proteins (but not for membrane-associated proteins), relative target preference varied among patients. The shift in relative M. tuberculosis protein reactivity observed with active tuberculosis defines the evolution of the humoral immune response during M. tuberculosis infection and disease. Peripheral blood was collected from prospectively enrolled TB suspects among subjects seeking care for pulmonary symptoms at clinics associated with national TB control programs in 11 countries. M. tuberculosis proteome microarrays representing 4099 bacterial protein spots were probed with sera from 561 TB suspects. Based on the final diagnosis, they belonged to two classes: TB (n=254) and Non-TB Disease (n=307). In addition, healthy individuals negative to Latent TB Infection (LTBI neg, n=64) were also tested (negative control sera). Each serum was tested with a single array and no replicate experiments were performed. The reactivity of a serum to an M. tuberculosis protein (reactivity call) was defined based on the distribution of negative control sera intensity for that protein using Z-statistics. Based on the distribution of reactivity calls, 27 outlier samples reacting with more than 20 proteins were excluded from further analysis. The association of reactivity calls of each protein with TB/NTBD status of TB suspects was determined by estimating odds ratio and 95% confidence interval.
2010-07-13 | E-GEOD-19433 | biostudies-arrayexpress
Project description:Dengue and Zika are two mosquito-borne diseases of great concern, affecting mainly the tropical and subtropical regions worldwide. The arrival of Zika virus (ZIKV) in dengue virus (DENV) endemic areas imposed challenges for differential diagnosis and the development of candidate vaccines. The use of peptides has shown great potential to achieve these goals. We aimed to identify the linear epitope profile recognized by the serum samples of dengue and Zika patients in the E and NS1 proteins of DENV and ZIKV to select peptides with the potential for the development of diagnostic tests and vaccines. Analysis of a peptide microarray platform with serum samples of dengue and Zika patients demonstrated that the epitopes were evenly distributed across the entire viral proteins, showing no preference for particular regions. However, several epitopes were within epitope hot spots constituted by clusters of peptides recognized in more than 30% of the sub-arrays analyzed with individual or pools of serum samples. The serum samples of dengue and Zika patients showed a high level of cross-reaction for epitopes in the DENV and ZIKV proteins. Analysis of an additional peptide microarray platform containing selected peptides based on the results of the first screening showed that three peptides (DENV: TQGEPSLNEEQDKRF and TQTVGPWHLGKLEID; ZIKV: LELDPPFGDSYIVIG), highly specific for their cognate viruses (p<0.05), were within the epitope hot spots; however, these peptides showed low detection rates (32.5, 35.0, and 28.6%, respectively). We also found two peptides (DENV: WEVEDYGFGVFTTNI and LELDFDLCEGTTVVV) in the epitope hot spots detected by both dengue and Zika patients with similarly high rates (arbitrary detection rate cut-off threshold of ≥40%). The epitope hot spots harbor several immunodominant epitopes recognized by a higher number of individuals when compared to the 15 aa sequence peptides. Therefore, the entire epitope hot spots, spanning up to ~30 aa, would have more potential than peptides of only 15 aa to serve as antigens in diagnostic tests and vaccine developments.
2023-10-11 | GSE235044 | GEO
Project description:Dengue and Zika are two mosquito-borne diseases of great concern, affecting mainly the tropical and subtropical regions worldwide. The arrival of Zika virus (ZIKV) in dengue virus (DENV) endemic areas imposed challenges for differential diagnosis and the development of candidate vaccines. The use of peptides has shown great potential to achieve these goals. We aimed to identify the linear epitope profile recognized by the serum samples of dengue and Zika patients in the E and NS1 proteins of DENV and ZIKV to select peptides with the potential for the development of diagnostic tests and vaccines. Analysis of a peptide microarray platform with serum samples of dengue and Zika patients demonstrated that the epitopes were evenly distributed across the entire viral proteins, showing no preference for particular regions. However, several epitopes were within epitope hot spots constituted by clusters of peptides recognized in more than 30% of the sub-arrays analyzed with individual or pools of serum samples. The serum samples of dengue and Zika patients showed a high level of cross-reaction for epitopes in the DENV and ZIKV proteins. Analysis of an additional peptide microarray platform containing selected peptides based on the results of the first screening showed that three peptides (DENV: TQGEPSLNEEQDKRF and TQTVGPWHLGKLEID; ZIKV: LELDPPFGDSYIVIG), highly specific for their cognate viruses (p<0.05), were within the epitope hot spots; however, these peptides showed low detection rates (32.5, 35.0, and 28.6%, respectively). We also found two peptides (DENV: WEVEDYGFGVFTTNI and LELDFDLCEGTTVVV) in the epitope hot spots detected by both dengue and Zika patients with similarly high rates (arbitrary detection rate cut-off threshold of ≥40%). The epitope hot spots harbor several immunodominant epitopes recognized by a higher number of individuals when compared to the 15 aa sequence peptides. Therefore, the entire epitope hot spots, spanning up to ~30 aa, would have more potential than peptides of only 15 aa to serve as antigens in diagnostic tests and vaccine developments.
2023-10-11 | GSE235043 | GEO
Project description:Sample collection and identification of biomarker for personalized therapy in tuberculosis patients
2020-03-30 | GSE147690 | GEO
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression.
2012-07-06 | GSE30721 | GEO
Project description:Human infection with Mycobacterium tuberculosis results in a continuum of ill-defined, clinical manifestations with stable latent M. tuberculosis infection (LTBI) and severe active disease at the ends. Identifying different states of infection is of importance to tuberculosis (TB) control since risk of developing active disease varies among different asymptomatic states while infectiousness varies among patients with different bacterial burden. We investigated changes in proteome-scale antibody responses during disease progression in a non-human primate model of tuberculosis. We probed M. tuberculosis proteome microarrays with serial sera collected from three infection-outcome groups (active, reactivation, and latent). We found that each infection outcome is associated with characteristic changes in the antibody levels and number of antigenic targets, which suggested an association between antibody responses and bacillary burden. Additional proteome-scale serological profiling of > 400 human TB suspects established that antibody responses are positively associated with bacterial load. Thus tuberculosis-specific antibody levels and number of antigenic targets increases with disease progression.
2012-07-06 | GSE30722 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE30721: Profiling proteome-scale antibody responses to M. tuberculosis proteins in sera of macaques infected with M. tuberculosis GSE30722: Profiling proteome-scale antibody responses to M. tuberculosis proteins in TB suspect's sera Refer to individual Series
2012-07-05 | E-GEOD-31368 | biostudies-arrayexpress