Identification of Proteins Binding Coding and Non-coding Human RNAs using Protein Microarrays
ABSTRACT: We describe a refined approach to identify new human RNA-protein interactions. In vitro transcribed labeled RNA is bound to ~9,400 human recombinant proteins spotted on protein microarrays. This approach identified 137 RNA-protein interactions for 10 human coding and non-coding RNAs, including an interaction between Staufen 1 protein and TP53 mRNA that promoted the latter’s stability. RNA hybridization to protein microarrays allows rapid identification of human RNA-protein interactions on a large scale. Sense and antisense strands for 10 RNA transcripts representing protein coding RNAs TP53, HRAS, MYC, BCL2 and non-coding sequences PWRN1, SOX2OT, OCC1, IGF2RNC, lncRBM26 and DLEU1 were in vitro transcribed, labeled with Cy5 and independently hybridized on human protein microarrays. The labeling process was optimized in order to achieve ~ 3 pmol dye per every microgram RNA with average efficacy of 1 dye molecule for approximately every 850 bp RNA to minimally influence RNA native structure and at the same time yield in signal intensities that were readily visualized.
Project description:Putative RNA-protein interactions with selected snoRNAs were screened using labaled RNA hybridized to a human protein microarray snoRNAs SNORD50A and SNORD50B were in vitro transcribed, labeled with Cy5 and independently hybridized on human protein microarrays. The labeling process was optimized in order to achieve ~ 3 pmol dye per every microgram RNA while maintaining signal intensities that were readily visualized.
Project description:Peripheral infusion of human umbilical cord mesenchymal stem cells (hUC-MSCs) can profoundly suppress the activation of c-Mos and remarkably improve hepatic histology, suppress the systemic inflammatory reaction, and promote animal survival in a large non-human primate model of acute liver failure (ALF). The mechanism through which hUC-MSCs inhibits c-Mos activation in vivo remains unclear. We hypothesized that hUC-MSCs can adaptively produce certain inhibitory cytokines in response to the pro-inflammatory microenvironment. To confirm this, we stimulated cultured hUC-MSCs with inflammatory monkey serum (serum isolated at day 1 following toxin challenge). After a 30-min stimulation, the cells were collected for microarray gene expression analysis. A whole human genome oligo microarray analysis was performed to reveal the altered gene expression profiles of the hUC-MSCs
Project description:Many protein-coding oncofetal genes are highly expressed in murine and human fetal liver and silenced in adult liver. The protein products of these hepatic oncofetal genes have been used as clinical markers for the recurrence of hepatocellular carcinoma (HCC) and as therapeutic targets for HCC. Herein, we examined the expression profiles of long non-coding RNAs (lncRNAs) and mRNAs found in fetal and adult liver in mice.LncRNA-mPvt1 is an oncofetal RNA that was found to promote cell proliferation, cell cycling and the expression of stem cell-like properties of murine cells. Human lncRNA-hPVT1 promotes cell proliferation, cell cycling and the acquisition of stem cell-like properties in HCC cells by stabilizing NOP2 protein. Regulation of the lncRNA-hPVT1/NOP2 pathway may have beneficial effects in the treatment of HCC. We collected mouse fetal livers (E12.5, E14.5, E17.5 days), neonatal murine livers and adult murine livers (8 weeks). The total RNAs recovered from these developmental livers and were used to acquire different expression profiles of mRNAs and lncRNAs.
Project description:Pattern discovery algorithms are methods for discovering recurrent, non-random motifs widely used in the analysis of biological sequences. Many algorithms exist but few comparisons have been made amongst them. We systematically profile eight representative methods at multiple parameter settings across 174 diverse experimental datasets, including ten novel ChIP-on-chip datasets. We executed 16,777 pattern discovery analyses to assess prediction accuracy, CPU usage and memory consumption. For 144 datasets we developed a gold-standard using machine-learning algorithms; cross-validation was used for the remaining datasets. Performance was highly disparate, with median accuracy ranging from 32% to 96%. Importantly we were unable to replicate previously reported algorithm-rankings, emphasizing the need to use many and diverse experimental datasets. We found deterministic algorithms like Projection and Oligo/Dyad had the highest prediction accuracy. Computational efficiency was not linearly related to dataset size and becomes critical: some algorithms are intractably slow on large datasets. This work provides the first combined assessment of the CPU, memory, and prediction accuracies of pattern discovery algorithms on real experimental datasets. HL60-Mnt-ChIP: ChIP-Chip with 10 biological replicates HL60-Trrap-ChIP: ChIP-Chip with 13 biological replicates
Project description:Hybridization of amplified genomic DNA against unamplified genomic DNA using three different amplification methods to assess the bias introduced by amplification alone. Keywords: genomic DNA Three different amplification methods were assessed and total genomic DNA hybridized against equal amounts of amplified genomic DNA for each method.
Project description:Analysis of technical variance of ChIP-on-Chip studies by characterization of Myc-binding in HL60 cells. Keywords: Chip-on-chip Fully-blocked study of technical variance in Myc-binding in HL60 cells. Two different antibodies were used to generate 6 biologically independent replicates each. Each replicate was hybridized to arrays from two different batches in both dye-swap orientations, leading to 48 total arrays.
Project description:Analysis of technical variance of ChIP-on-Chip studies by characterization of Myc-binding in HL60 cells. Keywords: Chip-on-chip Characterization of c-Myc binding in HL60 cells. Thirteen biologically independent replicates of growing HL60 cells were subjected to ChIP with an N-terminal c-Myc antibody and hybridized to CpG island microarrays
Project description:The Arraystar Human LncRNA Array v2.0 was designed for researchers who were interested in profiling both LncRNAs and protein-coding RNAs in human genome. 33,045 LncRNAs were collected from the authoritative data sources including RefSeq, UCSC knowngenes, Ensembl and many related literatures. This experiment is to profile lncRNAs and protein-coding RNAs using Arraystar Human LncRNA Array v2.0. Identification of coding RNAs and lncRNAs that are diffrentially expressed in colorectal cancer by comparing sample A-E (normal colorectal cells) vs sample F-J (colorectal tumor cells) and c-MYC-regulating lncRNAs by comparing sample 1-3 (triplicate of HCT116 cells treated with control siRNA) vs sample 4-6 (triplicate of HCT116 cells treated with siRNA targeting MYC) and sample 7-9 (triplicate of RKO cells treated with control siRNA) vs sample 10-12 (triplicate of RKO cells treated with siRNA targeting MYC) .
Project description:An early hallmark of Toxoplasma infection is the rapid control of the parasite population by a potent multifaceted innate immune response that engages resident and homing immune cells along with pro- and counter-inflammatory cytokines. In this context, IFN-γ activates a variety of Toxoplasma-targeting activities in immune and non-immune cells, but can also contribute to host immune pathology. Toxoplasma has evolved mechanisms to timely counteract the host IFN-γ defenses by interfering with the transcription of IFN-γ-stimulated genes. We now have identified TgIST as a critical molecular switch that is secreted by intracellular parasites and traffics to the host cell nucleus where it inhibits STAT1-dependent proinflammatory gene expression. We show that TgIST not only sequesters STAT1 on dedicated loci but also promotes shaping of a nonpermissive chromatin through its capacity to recruit the NuRD transcriptional repressor. We found that during mice acute infection, TgIST-deficient parasites are rapidly eliminated by the homing Gr1(+) inflammatory monocytes thus highlighting the protective role of TgIST against IFN-γ-mediated killing. By uncovering TgIST functions, this study brings novel evidence on how Toxoplasma has devised a molecular weapon of choice to take control over a ubiquitous immune gene expression mechanism in metazoans, as a way to promote long-term parasitism. HFF, 2fTGH (STAT1+/+) and U3A (STAT1-/-) human cells were left uninfected or infected for 24 hours with 76KGFP and 76KGFPΔTgIST Toxoplasma strains and stimulated with 100 U/ml IFN-γ for 6 hours before gene expression was measured. Three independent experiments were performed for each condition.
Project description:Escherichia coli strain MG1655 was grown in a New Brunswick Scientific Bioflow III Biofermentor under continuous culture (chemostat) conditions. Cells were grown in defined media containing 2 mM glycerol as the sole and limiting source of energy and carbon. The working volume was 200 ml, and the dilution rate 0.2 h-1. For aerobic growth, the air-flow rate was 0.1 l/min, and the dissolved oxygen tension was maintained at ~7% air saturation by measuring oxygen dissolved in the culture using a Broadley James D140 OxyProbe® electrode. For anaerobic growth, cells are grown on 100 % nitrogen gas bubbled at 0.1 l/min Cells were grown as above to steady-state, At steady-state, CORM-3 or iCORM-3 was added to the chemostat culture at a final concentration of 40 uM. Samples were taken immediately prior to the addition of CORM-3 or iCORM-3 and over a time course of 2.5, 5, 10, 20, 40 and 80 min exposure to (i)CORM-3 for subsequent analysis using microarrays. Cells were harvested directly into phenol:ethanol to stabilize RNA, and total RNA was purified using Qiagen’s RNeasy Mini kit as recommended by the suppliers. Time course experiment with samples taken immediately prior to or 2.5, 5, 10, 20, 40 or 80 minutes after addition of either 40uM CORM-3 or iCORM-3 under either 0 or 100 % perceived aerobiosis. 2 biological repeats were performed for each condition with 2 technical (dye swap) repeats per biological repeat.