Dataset Information

D.melanogaster - Whole organism, SC (Xing,proteomics,2014)

ABSTRACT: abundance based on Spectral counting, Interaction consistency score: 25.8, Coverage: 60

ORGANISM(S): 7227

SUBMITTER: Christian von Mering

PROVIDER: 1621505028 | PAXDB | 2014

REPOSITORIES: PAXDB

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	bioprojects-abundance-files-v4.0.zip	Other

Items per page:

1 - 1 of 1

Publications

Qualitative and quantitative analysis of the adult Drosophila melanogaster proteome.

Xing Xiaohua X Zhang Chengpu C Li Ning N Zhai Linhui L Zhu Yunping Y Yang Xiaoming X Xu Ping P

Proteomics 20140106 2-3

Drosophila melanogaster is one of the most widely used model organisms in life sciences. Mapping its proteome is of great significance for understanding the biological characteristics and tissue functions of this species. However, the comprehensive coverage of its proteome remains a challenge. Here, we describe a high-coverage analysis of whole fly through a 1D gel electrophoresis and LC-MS/MS approach. By combining the datasets of two types of SDS-PAGE and two kinds of tagmata, the high-coverag ...[more]

PMID: 24259522

Similar Datasets

Project description:Less than 30% of children with high-risk (HR) metastatic neuroblastoma (NB) show a long survival (Pearson 2000). In order to identify novel molecular prognostic markers useful to better predict patientsM-bM-^@M-^Y relapse risk estimation, we performed genome- and/or transcriptome-wide analyses of 129 stage 4 HR-NBs. This is the largest study for this NB subtype. Children older than 1 year of age at diagnosis were categorized as M-bM-^@M-^\short-survivorsM-bM-^@M-^] (dead of disease within 5 years from diagnosis) and M-bM-^@M-^\long-survivorsM-bM-^@M-^] (alive with an overall survival time > 5 years). A significant correlation of patient survival with the presence of small number of segmental copy number aberrations (CNA < 3) was observed. Thus, within the group of stage 4 HR-NBs, we identified a specific subgroup of patients (those with highest number of CNA) that have a higher risk of progression/recurrence. The complex genomic pattern is an independent prognostic marker, since MYCN oncogene amplification only affects the predictive value of single CNA (i.e., 1p loss, 17q gain). Integrative analysis of genomic and expression signatures demonstrated that fatal outcome is associated with loss of cell cycle control and with progression of tumor due to deregulation of Rho GTPase signaling and genes related to cell motility. Tumors with MYCN amplification showed a lower chromosome instability compared to MYCN-single copy NBs (P=0.0008), dominated by 17q gain and 1p loss. Moreover, our results suggest that the MYCN amplification mainly drives the disruption of neuronal differentiation and the reduction of cell adhesion process involved in tumor invasion and metastasis. For array-CGH profiling, we analyzed 91 samples of metastatic neuroblastomas. All patients were classified as stage 4 and they were older than 1 year of age at time of diagnosis. Regarding the clinical course, 46 were short-survivors (dead of disease within 60 months from diagnosis. Deaths due to toxicity were censored) and 45 were long-survivors (alive with an overall survival time > 60 months). This submission consists of 22 new samples and 69 other cases previously deposited in GEO under Series accessions GSE14109 and GSE25771.

Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.

Project description:Anaplasma phagocytophilum is an emerging zoonotic pathogen that causes human granulocytic anaplasmosis. These intracellular bacteria establish infection by affecting cell function in both the vertebrate host and the tick vector, Ixodes scapularis. Previous studies have characterized the tick transcriptome and proteome in response to A. phagocytophilum infection. However, in the post-genomic era, the integration of omics datasets through a systems biology approach allows network-based analyses to describe the complexity and functionality of biological systems such as host-pathogen interactions and the discovery of new targets for prevention and control of infectious diseases. This study reports for the first time a systems biology integration of metabolomics, transcriptomics and proteomics data to characterize essential metabolic pathways involved in the response of tick cells to A. phagocytophilum infection. The results showed that infection affected protein processing in endoplasmic reticulum and glucose metabolic pathways in tick cells. These results supported tick-Anaplasma co-evolution by providing new evidence of how tick cells limit pathogen infection, while the pathogen benefits from the tick cell response to establish infection. The results suggested that A. phagocytophilum induces protein misfolding to limit the tick cell response and facilitate infection, but requires protein degradation to prevent ER stress and cell apoptosis to survive in infected cells. Additionally, A. phagocytophilum may benefit from the tick cellâs ability to limit bacterial infection through PEPCK inhibition leading to decreased glucose metabolism, which also results in the inhibition of cell apoptosis that increases infection of tick cells. These results support the use of this experimental approach to systematically identify tick cell pathways and molecular mechanisms involved in tick-pathogen interactions Two samples with two replicates each were analyzed. Samples included Ixodes scapularis ISE6 cells uninfected (control) and infected with Anaplasma phagocytophilum human NY18 isolate.