Feng Ge Similar Datasets
Project description:The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides was lacking. To this end, Akhilesh Pandey's lab reported a draft map of the human proteome based on high resolution Fourier transform mass spectrometry-based proteomics technology, which included an in-depth proteomic profiling of 30 histologically normal human samples including 17 adult tissues, 7 fetal tissues and 6 purified primary hematopoietic cells ( http://dx.doi.org/10.1038/nature13302 ). The profiling resulted in identification of proteins encoded by greater than 17,000 genes accounting for ~84% of the total annotated protein-coding genes in humans. This large human proteome catalog (available as an interactive web-based resource at http://www.humanproteomemap.org) complements available human genome and transcriptome data to accelerate biomedical research in health and disease. Pandey's lab and collaborators request that those considering use of this primary dataset for commercial purposes contact pandey@jhmi.edu. The full details of this study can be found in the PRIDE database: www.ebi.ac.uk/pride/archive/projects/PXD000561/. This ArrayExpress entry represents a top level summary of the metadata only which formed the basis of the reanalysis performed by Joyti Choudhary's team ( jc4@sanger.ac.uk ), results of which are presented in the Expression Atlas at EMBL-EBI : http://www.ebi.ac.uk/gxa/experiments/E-PROT-1.
2015-03-10 | E-PROT-1 | biostudies-arrayexpress
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
Project description:Nowadays, although single-cell multi-omics technologies are undergoing rapid development, simultaneous transcriptome and proteome analysis of a single-cell individual still faces great challenges. Here, we developed a single-cell simultaneous transcriptome and proteome (scSTAP) analysis platform based on microfluidics, high-throughput sequencing and mass spectrometry technology, to achieve deep and joint quantitative analysis of transcriptome and proteome at the single-cell level, providing an important resource for understanding the relationship between transcription and translation in cells. This platform was applied to analyze single mouse oocytes at different meiotic maturation stages, reaching an average quantification depth of 19948 genes and 2663 protein groups in single mouse oocytes.
2023-10-18 | GSE237932 | GEO
Project description:Mushrooms, such as Schizophyllum commune, have a specific odor. Whether this is linked to mating, prerequisite for mushroom formation, or also found in monokaryotic, unmated strains, was investigated with a comprehensive study on the transcriptome and proteome of this model organism. Mating interactions were investigated using a complete, cytosolic proteome map for unmated, monokaryotic, as well as for mated, dikaryotic mycelia. The regulations of the proteome were compared to transcriptional changes upon mating and to changes in smell by volatilome studies. We could show a good overlap between proteome and transcriptome data, but extensive posttranslational regulation was identified for more than 80 % of transcripts. This suggests down-stream regulation upon interaction of mating partners and formation of the dikaryon that is competent to form fruiting bodies. The volatilome was shown to respond to mating by a broader spectrum of volatiles and increased emission of the mushroom smell molecules 3-octanone and 1-octen-3-ol, as well as ethanol and ß-bisabolol in the dikaryon. Putatively involved biosynthetic proteins like alcohol dehydrogenases, Ppo-like oxygenases, or sesquiterpene synthases showed correlating transcriptional regulation depending on either mono- or dikaryotic stages.
2017-07-07 | GSE84124 | GEO
Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.
2024-05-06 | GSE247519 | GEO
Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.
2022-05-18 | GSE201575 | GEO
Project description:We report the development of a method (nanoSPLITS) capable of performing global proteome and transcriptome measurements from the same single-cell.
2022-12-05 | GSE219047 | 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. Serum samples collected from adult patients with suspected tuberculosis during a multi-site study was used to probe whole proteome microarrays. Subject recruitment was conducted under uniform protocols approved by the institutional ethics committee at each site. Final diagnosis of active TB was based on positive M. tuberculosis culture results. The active TB patients were further subdivided into smear-positive and negative disease based on results of Ziehl-Neelsen staining of sputum smears for acid fast bacilli. Active TB was excluded as a diagnosis (Non-TB Disease [NTBD] patients) based on having negative M. tuberculosis culture and smear results and on having an alternate diagnosis. All subjects were presumably negative for HIV infection given the very low incidence of HIV infection in the study sites. Sera from 169 TB and 242 NTBD patients were selected for microarray probing. The control sera (n = 14) which was used to generate negative control distribution for each protein were negative to latent M. tuberculosis infection, as indicated by negative results to tuberculin skin test.
2012-07-05 | E-GEOD-30722 | biostudies-arrayexpress
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: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. To investigate antibody responses during the course of infection, we probed M. tuberculosis proteome microarrays with serial sera collected from experimentally infected cynomolgus macaques. Based on infection outcome, the macaques were grouped into three classes; A) active disease (n = 4), B) latent infection (n=5) and C) reactivation disease (n = 5). Note that the macaques in the reactivation class developed signs of disease spontaneously without any experimental intervention. For each animal, we tested one pre-infection time point and approximately ten post-infection time points at one-month intervals.
2012-07-05 | E-GEOD-30721 | biostudies-arrayexpress