PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Gene dispersion is the key determinant of the read count bias in differential expression analysis of RNA-seq data

Background: In differential expression analysis of RNA-sequencing (RNA-seq) read count data for two sample groups, it is known that highly expressed genes (or longer genes) are more likely to be differentially expressed which is called read count bias (or gene length bias). This bias had great effect on the downstream Gene Ontology over-representation analysis. However, such a bias has not been systematically analyzed for different replicate types of RNA-seq data. Results: We show that the dispersion coefficient of a gene in the negative binomial modeling of read counts is the critical determinant of the read count bias (and gene length bias) by mathematical inference and tests for a number of simulated and real RNA-seq datasets. We demonstrate that the read count bias is mostly confined to data with small gene dispersions (e.g., technical replicates and some of genetically identical replicates such as cell lines or inbred animals), and many biological replicate data from unrelated samples do not suffer from such a bias except for genes with some small counts. It is also shown that the sample-permuting GSEA method yields a considerable number of false positives caused by the read count bias, while the preranked method does not. Conclusion: We showed the small gene variance (similarly, dispersion) is the main cause of read count bias (and gene length bias) for the first time and analyzed the read count bias for different replicate types of RNA-seq data and its effect on gene-set enrichment analysis

The first small-molecule inhibitors of members of the ribonuclease E family

The Escherichia coli endoribonuclease RNase E is central to the processing and degradation of all types of RNA and as such is a pleotropic regulator of gene expression. It is essential for growth and was one of the first examples of an endonuclease that can recognise the 5′-monophosphorylated ends of RNA thereby increasing the efficiency of many cleavages. Homologues of RNase E can be found in many bacterial families including important pathogens, but no homologues have been identified in humans or animals. RNase E represents a potential target for the development of new antibiotics to combat the growing number of bacteria that are resistant to antibiotics in use currently. Potent small molecule inhibitors that bind the active site of essential enzymes are proving to be a source of potential drug leads and tools to dissect function through chemical genetics. Here we report the use of virtual high-throughput screening to obtain small molecules predicted to bind at sites in the N-terminal catalytic half of RNase E. We show that these compounds are able to bind with specificity and inhibit catalysis of Escherichia coli and Mycobacterium tuberculosis RNase E and also inhibit the activity of RNase G, a paralogue of RNase E

Occupancy maps of 208 chromatin-associated proteins in one human cell type

Transcription factors are DNA-binding proteins that have key roles in gene regulation. Genome-wide occupancy maps of transcriptional regulators are important for understanding gene regulation and its effects on diverse biological processes. However, only a minority of the more than 1,600 transcription factors encoded in the human genome has been assayed. Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP–seq) experiments using the human HepG2 cell line for 208 chromatin-associated proteins (CAPs). These comprise 171 transcription factors and 37 transcriptional cofactors and chromatin regulator proteins, and represent nearly one-quarter of CAPs expressed in HepG2 cells. The binding profiles of these CAPs form major groups associated predominantly with promoters or enhancers, or with both. We confirm and expand the current catalogue of DNA sequence motifs for transcription factors, and describe motifs that correspond to other transcription factors that are co-enriched with the primary ChIP target. For example, FOX family motifs are enriched in ChIP–seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers. This catalogue reveals high-occupancy target regions at which many CAPs associate, although each contains motifs for only a minority of the numerous associated transcription factors. These analyses provide a more complete overview of the gene regulatory networks that define this cell type, and demonstrate the usefulness of the large-scale production efforts of the ENCODE Consortium

Eukaryotic Cells Producing Ribosomes Deficient in Rpl1 Are Hypersensitive to Defects in the Ubiquitin-Proteasome System

It has recently become clear that the misassembly of ribosomes in eukaryotic cells can have deleterious effects that go far beyond a simple shortage of ribosomes. In this work we find that cells deficient in ribosomal protein L1 (Rpl1; Rpl10a in mammals) produce ribosomes lacking Rpl1 that are exported to the cytoplasm and that can be incorporated into polyribosomes. The presence of such defective ribosomes leads to slow growth and appears to render the cells hypersensitive to lesions in the ubiquitin-proteasome system. Several genes that were reasonable candidates for degradation of 60S subunits lacking Rpl1 fail to do so, suggesting that key players in the surveillance of ribosomal subunits remain to be found. Interestingly, in spite of rendering the cells hypersensitive to the proteasome inhibitor MG132, shortage of Rpl1 partially suppresses the stress-invoked temporary repression of ribosome synthesis caused by MG132.United States. National Institutes of Health (GM25532)United States. National Institutes of Health (ARRAGM25532-S1)United States. National Institutes of Health (GM085177)United States. National Institutes of Health (CAI-3330)Natural Sciences and Engineering Research Council of Canada (NSERC

CMS: A web-based system for visualization and analysis of genome-wide methylation data of human cancers

DNA methylation of promoter CpG islands is associated with gene suppression, and its unique genome-wide profiles have been linked to tumor progression. Coupled with high-throughput sequencing technologies, it can now efficiently determine genome-wide methylation profiles in cancer cells. Also, experimental and computational technologies make it possible to find the functional relationship between cancer-specific methylation patterns and their clinicopathological parameters.Cancer methylome system (CMS) is a web-based database application designed for the visualization, comparison and statistical analysis of human cancer-specific DNA methylation. Methylation intensities were obtained from MBDCap-sequencing, pre-processed and stored in the database. 191 patient samples (169 tumor and 22 normal specimen) and 41 breast cancer cell-lines are deposited in the database, comprising about 6.6 billion uniquely mapped sequence reads. This provides comprehensive and genome-wide epigenetic portraits of human breast cancer and endometrial cancer to date. Two views are proposed for users to better understand methylation structure at the genomic level or systemic methylation alteration at the gene level. In addition, a variety of annotation tracks are provided to cover genomic information. CMS includes important analytic functions for interpretation of methylation data, such as the detection of differentially methylated regions, statistical calculation of global methylation intensities, multiple gene sets of biologically significant categories, interactivity with UCSC via custom-track data. We also present examples of discoveries utilizing the framework.CMS provides visualization and analytic functions for cancer methylome datasets. A comprehensive collection of datasets, a variety of embedded analytic functions and extensive applications with biological and translational significance make this system powerful and unique in cancer methylation research. CMS is freely accessible at: http://cbbiweb.uthscsa.edu/KMethylomes/

Gene expression analysis indicates CB1 receptor upregulation in the hippocampus and neurotoxic effects in the frontal cortex 3 weeks after single-dose MDMA administration in Dark Agouti rats.

BACKGROUND: 3,4-methylenedioxymethamphetamine (MDMA, "ecstasy") is a widely used recreational drug known to impair cognitive functions on the long-run. Both hippocampal and frontal cortical regions have well established roles in behavior, memory formation and other cognitive tasks and damage of these regions is associated with altered behavior and cognitive functions, impairments frequently described in heavy MDMA users. The aim of this study was to examine the hippocampus, frontal cortex and dorsal raphe of Dark Agouti rats with gene expression arrays (Illumina RatRef bead arrays) looking for possible mechanisms and new candidates contributing to the effects of a single dose of MDMA (15 mg/kg) 3 weeks earlier. RESULTS: The number of differentially expressed genes in the hippocampus, frontal cortex and the dorsal raphe were 481, 155, and 15, respectively. Gene set enrichment analysis of the microarray data revealed reduced expression of 'memory' and 'cognition', 'dendrite development' and 'regulation of synaptic plasticity' gene sets in the hippocampus, parallel to the upregulation of the CB1 cannabinoid- and Epha4, Epha5, Epha6 ephrin receptors. Downregulated gene sets in the frontal cortex were related to protein synthesis, chromatin organization, transmembrane transport processes, while 'dendrite development', 'regulation of synaptic plasticity' and 'positive regulation of synapse assembly' gene sets were upregulated. Changes in the dorsal raphe region were mild and in most cases not significant. CONCLUSION: The present data raise the possibility of new synapse formation/synaptic reorganization in the frontal cortex three weeks after a single neurotoxic dose of MDMA. In contrast, a prolonged depression of new neurite formation in the hippocampus is suggested by the data, which underlines the particular vulnerability of this brain region after the drug treatment. Finally, our results also suggest the substantial contribution of CB1 receptor and endocannabinoid mediated pathways in the hippocampal impairments. Taken together the present study provides evidence for the participation of new molecular candidates in the long-term effects of MDMA

An Experimental Study and Analysis on Solar Drying of Bitter Gourd Using an Evacuated Tube Air Collector in Thanjavur, Tamil Nadu, India

The objective of this research work is to design and develop a forced convection solar dryer using evacuated tube air collector and study its performance on bitter gourd in Thanjavur District, Tamilnadu, India. The designed solar dryer consists of a drying chamber, evacuated tube air collector, a blower, and a chimney. Drying parameters, moisture ratio and drying rates, are calculated and their performance is compared with natural sun drying. The results of the present study show that the proposed solar dryer has greater efficiency, and the moisture content of bitter gourd is reduced from 91% to 6.25% in 6 hours as compared to 10 hours in natural sun drying. In this solar dryer, the products are uniformly dried, and the moisture content of the sample is controlled. It is found that the quality of the dried bitter gourd using solar dryer is higher than the natural sun-dried bitter gourd.</jats:p

C9ORF72 interaction with cofilin modulates actin dynamics in motor neurons.

Intronic hexanucleotide expansions in C9ORF72 are common in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, but it is unknown whether loss of function, toxicity by the expanded RNA or dipeptides from non-ATG-initiated translation are responsible for the pathophysiology. We determined the interactome of C9ORF72 in motor neurons and found that C9ORF72 was present in a complex with cofilin and other actin binding proteins. Phosphorylation of cofilin was enhanced in C9ORF72-depleted motor neurons, in patient-derived lymphoblastoid cells, induced pluripotent stem cell-derived motor neurons and post-mortem brain samples from ALS patients. C9ORF72 modulates the activity of the small GTPases Arf6 and Rac1, resulting in enhanced activity of LIM-kinases 1 and 2 (LIMK1/2). This results in reduced axonal actin dynamics in C9ORF72-depleted motor neurons. Dominant negative Arf6 rescues this defect, suggesting that C9ORF72 acts as a modulator of small GTPases in a pathway that regulates axonal actin dynamics