As nascent polypeptides exit ribosomes, they are engaged by a series of processing, targeting and folding factors. Here we present a selective ribosome profiling strategy that enables global monitoring of when these factors engage polypeptides in the complex cellular environment. Studies of the Escherichia coli chaperone Trigger Factor (TF) reveal that, while TF can interact with many polypeptides, ß-barrel outer membrane proteins are the most prominent substrates. Loss of TF leads to broad outer membrane defects and premature, cotranslational protein translocation. While in vitro studies suggested that TF is prebound to ribosomes waiting for polypeptides to emerge from the exit channel, we find that in vivo TF engages ribosomes only after ~100 amino acids are translated. Moreover, excess TF interferes with cotranslational removal of the N-terminal formyl methionine. Our studies support a triaging model in which proper protein biogenesis relies on the fine-tuned, sequential engagement of processing, targeting ad folding factors. Overall design: Examination of translation in the Gram-negative bacterium Escherichia coli, as well as an analysis of the interactions between nascent chains and the molecular chaperone Trigger Factor.
Selective ribosome profiling reveals the cotranslational chaperone action of trigger factor in vivo.
Cell line, Subject
View SamplesThe primary aim of this project was to identify novel factors, in particular the cell-surface protein CD109, which regulate osteoclastogenesis. Microarray analysis was performed comparing two pre-osteoclast cell lines generated from the RAW 264.7 osteoclast cell line: one that has the capacity to fuse forming large multinucleated cells and one that does not fuse. It was found that CD109 was up-regulated by > 17-fold in the osteoclast forming cell line when compared to the cell line that does not fuse.
CD109 plays a role in osteoclastogenesis.
Specimen part, Cell line
View SamplesOsteoclast (OC) differentiation undergoes a two-step process: commitment of hematopoietic progenitor cells to tartrate-resistant acid phosphatase (TRAcP) positive OC precursors (OCPs), and fusion of OCPs into multinucleated OCs. In order to identify transcriptional profiles of genes in the transitional phase between OC commitment and fusion in OCG, Affymetrix Mouse Gene 1.0 ST arrays were performed on total RNA extracted from mouse (SV129/BL6 ) monocytes and pre-osteoclasts (pre-OCs), primed with macrophage colony-stimulated factor (M-CSF) or M-CSF and soluble recombinant receptor activator of NF-B ligand (sRANKL), respectively. The analysis identified 656 RANKL-up or down-regulated in the early stage of osteoclastogenesis.
The actin binding protein adseverin regulates osteoclastogenesis.
Specimen part
View SamplesRigosertib treatment of head and neck squamous cell cancer
The dual pathway inhibitor rigosertib is effective in direct patient tumor xenografts of head and neck squamous cell carcinomas.
Specimen part, Cell line
View SamplesThe ability to dissect heterogeneity in colorectal cancer (CRC) is a critical step in developing predictive biomarkers. The goal of this study was to develop a gene expression based molecular subgrouping model, which predicts the likelihood that patients will respond to specific therapies.
Activation of the mTOR Pathway by Oxaliplatin in the Treatment of Colorectal Cancer Liver Metastasis.
No sample metadata fields
View SamplesPurpose: Identify differentially expressed genes in placental samples from early-onset (EO) IUGR, EO-PE, as well as pregnancies complicated by both EO-PE and EO-IUGR Overall design: Methods: Isolated total RNA from human placenta at birth and used it for RNA-sequencing on the Hiseq2000. Sequences were aligned to the human transcriptome (hg19/genome_build37) . Aligned sequences were then used to obtain abundance measurements and conduct differential expression analysis.
Placental microRNAs in pregnancies with early onset intrauterine growth restriction and preeclampsia: potential impact on gene expression and pathophysiology.
Specimen part, Subject
View SamplesThis SuperSeries is composed of the SubSeries listed below.
Alignment of time course gene expression data and the classification of developmentally driven genes with hidden Markov models.
No sample metadata fields
View SamplesWe studied intragraft gene expression profiles of positive crossmatch (+XM) kidney transplant recipients who develop transplant glomerulopathy (TG) and those who do not. Whole genome microarray analysis and quantitative rt-PCR for 30 transcripts were performed on RNA from protocol renal allograft biopsies in 3 groups: 1) +XM/TG+ biopsies before and after TG; 2) +XM/NoTG; and 3) negative crossmatch kidney transplants (control). Microarray comparisons showed few differentially expressed genes between paired biopsies from +XM/TG+ recipients before and after the diagnosis of TG. Comparing +XM/TG+ and control groups, significantly altered expression was seen for 2,447 genes (18%) and 3,200 genes (24%) at early and late time points, respectively. Canonical pathway analyses of differentially expressed genes showed inflammatory genes associated with innate and adaptive immune responses. Comparing +XM/TG+ and +XM/NoTG groups, 3,718 probe sets were differentially expressed but these were over-represented in only 4 pathways. A classic accommodation phenotype was not identified. Using rt-PCR, the expression of inflammatory genes was significantly increased in +XM/TG+ recipients compared to control biopsies and to +XM/NoTG biopsies. In conclusion, pre-transplant DSA results in a gene expression profile characterized by inflammation and cellular infiltration and the majority of XM+ grafts are exposed to chronic injury.
Intragraft gene expression in positive crossmatch kidney allografts: ongoing inflammation mediates chronic antibody-mediated injury.
Specimen part, Time
View SamplesChanges in gene expression during berry development during a grape growing season were analysed.
Alignment of time course gene expression data and the classification of developmentally driven genes with hidden Markov models.
No sample metadata fields
View SamplesDifferences in gene expression were compared for grape berry flesh and skin.
Alignment of time course gene expression data and the classification of developmentally driven genes with hidden Markov models.
No sample metadata fields
View Samples