Abstract: Chronic atrial fibrillation (AF) is a complication associated with the dilated atria of patients with valvular heart disease and contributes to worsened pathology. We examined microRNA (miRNA) expression profiles in right and left atrial appendage tissue from valvular heart disease (VHD) patients. Right atrial (RA) appendage from patients undergoing coronary artery bypass grafting and left atrial (LA) appendage from healthy hearts, not used for transplant, were used as controls. There was no detectable effect of chronic AF on miRNA expression in LA tissue, but miRNA expression in RA was strongly influenced by AF, with 47 miRNAs (15 higher, 32 lower) showing differential expression between the AF and control sinus rhythm groups. VHD induced different changes in miRNA expression in LA compared with RA. Fifty-three (12 higher, 41 lower) miRNAs were altered by VHD in LA, compared with 5 (4 higher, 1 lower) in RA tissue. miRNA profiles also differed between VHD-LA and VHD-RA (13 higher, 26 lower). We conclude that VHD and AF influence miRNA expression patterns in LA and RA, but these are affected differently by disease progression and by the development of AF. These findings provide new insights into the progression of VHD.
Abstract: The Protein Interaction Network Analysis (PINA) platform is a comprehensive web resource, which includes a database of unified protein-protein interaction data integrated from six manually curated public databases, and a set of built-in tools for network construction, filtering, analysis and visualization. The second version of PINA enhances its utility for studies of protein interactions at a network level, by including multiple collections of interaction modules identified by different clustering approaches from the whole network of protein interactions ('interactome') for six model organisms. All identified modules are fully annotated by enriched Gene Ontology terms, KEGG pathways, Pfam domains and the chemical and genetic perturbations collection from MSigDB. Moreover, a new tool is provided for module enrichment analysis in addition to simple query function. The interactome data are also available on the web site for further bioinformatics analysis. PINA is freely accessible at http://cbg.garvan.unsw.edu.au/pina/.
Abstract: Krüppel-like factor 3 (Klf3) is a member of the Klf family of transcription factors. Klfs are widely expressed and have diverse roles in development and differentiation. In this study, we examine the function of Klf3 in B cell development by studying B lymphopoiesis in a Klf3 knockout mouse model. We show that B cell differentiation is significantly impaired in the bone marrow, spleen, and peritoneal cavity of Klf3 null mice and confirm that the defects are cell autonomous. In the bone marrow, there is a reduction in immature B cells, whereas recirculating mature cells are noticeably increased. Immunohistology of the spleen reveals a poorly structured marginal zone (MZ) that may in part be caused by deregulation of adhesion molecules on MZ B cells. In the peritoneal cavity, there are significant defects in B1 B cell development. We also report that the loss of Klf3 in MZ B cells is associated with reduced BCR signaling strength and an impaired ability to respond to LPS stimulation. Finally, we show increased expression of a number of Klf genes in Klf3 null B cells, suggesting that a Klf regulatory network may exist in B cells.
Abstract: Quantitative mass spectrometry using iTRAQ was used to identify differentially expressed proteins from 16 colorectal cancer (CRC) tumours compared to patient-paired adjacent normal mucosa. Over 1400 proteins were identified and quantitated, with 118 determined as differentially expressed by >1.3-fold, with false discovery rate < 0.05. Gene Ontology analysis indicated that proteins with increased expression levels in CRC tumours include those associated with glycolysis, calcium binding, and protease inhibition. Proteins with reduced levels in CRC tumours were associated with loss of ATP production through: (i) reduced β-oxidation of fatty acids, (ii) reduced NADH production by the tricarboxylic acid cycle and (iii) decreased oxidative phosphorylation activity. Additionally, biosyntheses of glycosaminoglycans and proteoglycans were significantly reduced in tumour samples. Validation experiments using immunoblotting and immunohistochemistry (IHC) showed strong concordance with iTRAQ data suggesting that this workflow is suitable for identifying biomarker candidates. We discuss the uses and challenges of this approach to generate biomarker leads for patient prognostication.
Abstract: Adipose tissue is a major target of GH action. GH stimulates lipolysis and reduces fat mass. The molecular mechanism underlying cellular and metabolic effects of GH in adipose tissue is not well understood.
Abstract: Epigenetic changes can be induced by adverse environmental exposures, such as nutritional imbalance, but little is known about the nature or extent of these changes. Here we have explored the epigenomic effects of a sustained nutritional change, excess dietary methyl donors, by assessing genomic CpG methylation patterns in isogenic mice exposed for one or six generations. We find stochastic variation in methylation levels at many loci; exposure to methyl donors increases the magnitude of this variation and the number of variable loci. Several gene ontology categories are significantly overrepresented in genes proximal to these methylation-variable loci, suggesting that certain pathways are susceptible to environmental influence on their epigenetic states. Long-term exposure to the diet (six generations) results in a larger number of loci exhibiting epigenetic variability, suggesting that some of the induced changes are heritable. This finding presents the possibility that epigenetic variation within populations can be induced by environmental change, providing a vehicle for disease predisposition and possibly a substrate for natural selection.
Abstract: Human islets are subjected to a number of stresses before and during their isolation that may influence their survival and engraftment after transplantation. Apoptosis is likely to be activated in response to these stresses. Apoptosis due to intrinsic stresses is regulated by pro- and anti-apoptotic members of the Bcl-2 family. While the role of the Bcl-2 family in apoptosis of rodent islets is becoming increasingly understood, little is known about which of these molecules are expressed or required for apoptosis of human islets. This study investigated the expression of the Bcl-2 family of molecules in isolated human islets. RNA and protein lysates were extracted from human islets immediately post-isolation. At the same time, standard quality control assays including viability staining and beta cell content were performed on each islet preparation. Microarrays, RT-PCR and western blotting were performed on islet RNA and protein. The pro-survival molecules Bcl-xl and Mcl-1, but not Bcl-2 were highly expressed. The multi-domain pro-apoptotic effector molecule Bax was expressed at higher levels than Bak. Pro-apoptotic BH3-only molecules were expressed at low levels, with Bid being the most abundant. The pro-apoptotic molecules BNIP3, BNIP3L and Beclin-1 were all highly expressed indicating exposure of islets to oxygen and nutrient deprivation during isolation. Our data provide a comprehensive analysis of expression levels of pro- and anti-apoptotic Bcl-2 family members in isolated human islets. Knowledge of which molecules are expressed will guide future research to understand the apoptotic pathways activated during isolation or after transplantation. This is crucial for the design of methods to achieve improved transplantation outcomes.
Abstract: The aim of this study was to characterize expression profiles of visceral and subcutaneous adipose tissue in children. Adipose tissue samples were collected from children having elective surgery (n = 71, [54 boys], 6.0 ± 4.3 years). Affymetrix microarrays (n = 20) were performed to characterize the functional profile and identify genes of interest in adipose tissue. Visceral adipose tissue had an overrepresentation of Gene Ontology themes related to immune and inflammatory responses and subcutaneous adipose tissue had an overrepresentation of themes related to adipocyte growth and development. Likewise, qPCR performed in the whole cohort showed a 30-fold increase in haptoglobin (P = 0.005), 7-fold increase in IL-10 (P < 0.001), 8-fold decrease in VEGF (P = 0.01) and a 28-fold decrease in TBOX15 (P < 0.001) in visceral compared to subcutaneous adipose tissue. The inflammatory pattern in visceral adipose tissue may represent an early stage of the adverse effects of this depot, and combined with chronic obesity, may contribute to increased metabolic and cardiovascular risk.
Abstract: T cells contribute to host-tumor interactions in patients with monoclonal gammopathies. Expansions of CD8(+)CD57(+) T-cell receptor Vbeta-positive (TCRVbeta(+))-restricted cytotoxic T-cell (CTL) clones are found in 48% of patients with multiple myeloma and confer a favorable prognosis. We now report that CTL clones with varying TCRVbeta repertoire are present in 70% of patients with Waldenström macroglobulinemia (WM; n = 20). Previous nucleoside analog (NA) therapy, associated with increased incidence of transformation to aggressive lymphoma, significantly influenced the presence of TCRVbeta expansions (chi(2) = 11.6; P < .001), as 83% of patients without (n = 6) and only 7% with (n = 14) TCRVbeta expansions had received NA. Clonality of CD3(+)CD8(+)CD57(+)TCRVbeta(+)-restricted CTLs was confirmed by TCRVbeta CDR3 size analysis and direct sequencing. The differential expression of CD3(+)CD8(+)CD57(+)TCRVbeta(+) cells was profiled using DNA microarrays and validated at mRNA and protein level. By gene set enrichment analysis, CTL clones expressed not only genes from cytotoxic pathways (GZMB, PRF1, FGFBP2) but also genes that suppress apoptosis, inhibit proliferation, arrest cell-cycle G1/S transition, and activate T cells (RAS, CSK, and TOB pathways). Proliferation tracking after stimulation confirmed their anergic state. Our studies demonstrate the incidence, NA sensitivity, and nature of clonal CTLs in WM and highlight mechanisms that cause anergy in these cells.
Abstract: Prolactin and progesterone act together to regulate mammary alveolar development, and both hormones have been implicated in breast cancer initiation and progression. Here we show that Elf5, a prolactin-induced ETS transcription factor that specifies the mammary secretory cell lineage, is also induced by progestins in breast cancer cells via a direct mechanism. To define the transcriptional response to progestin elicited via Elf5, we made an inducible Elf5 short hairpin-RNA knock-down model in T47D breast cancer cells and used it to prevent the progestin-induction of Elf5. Functional analysis of Affymetrix gene expression data using Gene Ontologies and Gene Set Enrichment Analysis showed enhancement of the progestin effects on cell cycle gene expression. Cell proliferation assays showed a more efficacious progestin-induced growth arrest when Elf5 was kept at baseline levels. These results showed that progestin induction of Elf5 expression tempered the antiproliferative effects of progestins in T47D cells, providing a further mechanistic link between prolactin and progestin in the regulation of mammary cell phenotype.
Abstract: The cold marine environment constitutes a large proportion of the Earth's biosphere. Sphingopyxis alaskensis was isolated as a numerically abundant bacterium from several cold marine locations, and has been extensively studied as a model marine bacterium. Recently, a metabolic labelling platform was developed to comprehensively identify and quantify proteins from S. alaskensis. The approach incorporated data normalization and statistical validation for the purpose of generating highly confident quantitative proteomics data. Using this approach, we determined quantitative differences between cells grown at 10°C (low temperature) and 30°C (high temperature). Cold adaptation was linked to specific aspects of gene expression: a dedicated protein-folding system using GroESL, DnaK, DnaJ, GrpE, SecB, ClpB and PPIase; polyhydroxyalkanoate-associated storage materials; a link between enzymes in fatty acid metabolism and energy generation; de novo synthesis of polyunsaturated fatty acids in the membrane and cell wall; inorganic phosphate ion transport by a phosphate import PstB homologue; TonB-dependent receptor and bacterioferritin in iron homeostasis; histidine, tryptophan and proline amino acid metabolism; and a large number of proteins without annotated functions. This study provides a new level of understanding on how important marine bacteria can adapt to compete effectively in cold marine environments. This study is also a benchmark for comparative proteomic analyses with other important marine bacteria and other cold-adapted organisms.
Abstract: Silencing of individual genes can occur by genetic and epigenetic processes during carcinogenesis, but the underlying mechanisms remain unclear. By creating an integrated prostate cancer epigenome map using tiling arrays, we show that contiguous regions of gene suppression commonly occur through long-range epigenetic silencing (LRES). We identified 47 LRES regions in prostate cancer, typically spanning about 2 Mb and harbouring approximately 12 genes, with a prevalence of tumour suppressor and miRNA genes. Our data reveal that LRES is associated with regional histone deacetylation combined with subdomains of different epigenetic remodelling patterns, which include re-enforcement, gain or exchange of repressive histone, and DNA methylation marks. The transcriptional and epigenetic state of genes in normal prostate epithelial and human embryonic stem cells can play a critical part in defining the mode of cancer-associated epigenetic remodelling. We propose that consolidation or effective reduction of the cancer genome commonly occurs in domains through a combination of LRES and LOH or genomic deletion, resulting in reduced transcriptional plasticity within these regions.
Abstract: GH abuse is a significant problem in many sports, and there is currently no robust test that allows detection of doping beyond a short window after administration.
Abstract: Comparative proteomics is a powerful analytical method for learning about the responses of biological systems to changes in growth parameters. To make confident inferences about biological responses, proteomics approaches must incorporate appropriate statistical measures of quantitative data. In the present work we applied microarray-based normalization and statistical analysis (significance testing) methods to analyze quantitative proteomics data generated from the metabolic labeling of a marine bacterium (Sphingopyxis alaskensis). Quantitative data were generated for 1,172 proteins, representing 1,736 high confidence protein identifications (54% genome coverage). To test approaches for normalization, cells were grown at a single temperature, metabolically labeled with (14)N or (15)N, and combined in different ratios to give an artificially skewed data set. Inspection of ratio versus average (MA) plots determined that a fixed value median normalization was most suitable for the data. To determine an appropriate statistical method for assessing differential abundance, a -fold change approach, Student's t test, unmoderated t test, and empirical Bayes moderated t test were applied to proteomics data from cells grown at two temperatures. Inverse metabolic labeling was used with multiple technical and biological replicates, and proteomics was performed on cells that were combined based on equal optical density of cultures (providing skewed data) or on cell extracts that were combined to give equal amounts of protein (no skew). To account for arbitrarily complex experiment-specific parameters, a linear modeling approach was used to analyze the data using the limma package in R/Bioconductor. A high quality list of statistically significant differentially abundant proteins was obtained by using lowess normalization (after inspection of MA plots) and applying the empirical Bayes moderated t test. The approach also effectively controlled for the number of false discoveries and corrected for the multiple testing problem using the Storey-Tibshirani false discovery rate (Storey, J. D., and Tibshirani, R. (2003) Statistical significance for genomewide studies. Proc. Natl. Acad. Sci. U.S.A. 100, 9440-9445). The approach we have developed is generally applicable to quantitative proteomics analyses of diverse biological systems.
Abstract: Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52-79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intraindividual differences. This will create substantial challenges in humans, where multiple tissues are not readily available.
Abstract: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients.
Abstract: Hierarchical and empirical Bayes approaches to inference are attractive for data arising from microarray gene expression studies because of their ability to borrow strength across genes in making inferences. Here we focus on the simplest case where we have data from replicated two colour arrays which compare two samples and where we wish to decide which genes are differentially expressed and obtain estimates of operating characteristics such as false discovery rates. The purpose of this paper is to examine the frequentist performance of Bayesian variable selection approaches to this problem for different prior specifications and to examine the effect on inference of commonly used empirical Bayes approximations to hierarchical Bayes procedures. The paper makes three main contributions. First, we describe how the log odds of differential expression can usually be computed analytically in the case where a double tailed exponential prior is used for gene effects rather than a normal prior, which gives an alternative to the commonly used B-statistic for ranking genes in simple comparative experiments. The second contribution of the paper is to compare empirical Bayes procedures for detecting differential expression with hierarchical Bayes methods which account for uncertainty in prior hyperparameters to examine how much is lost in using the commonly employed empirical Bayes approximations. Third, we describe an efficient MCMC scheme for carrying out the computations required for the hierarchical Bayes procedures. Comparisons are made via simulation studies where the simulated data are obtained by fitting models to some real microarray data sets. The results have implications for analysis of microarray data using parametric hierarchical and empirical Bayes methods for more complex experimental designs: generally we find that the empirical Bayes methods work well, which supports their use in the analysis of more complex experiments when a full hierarchical Bayes analysis would impose heavy computational demands.
Abstract: The view that changes to the control of gene expression rather than alterations to protein sequence are central to the evolution of organisms has become something of a truism in molecular biology. In reality, the direct evidence for this is limited, and only recently have we had the ability to look more globally at how genetic variation influences gene expression, focusing upon inter-individual variation in gene expression and using microarrays to test for differences in mRNA levels. Here, we review the scope of these experimental analyses, what they are designed to tell us about genetic variation, and what are their limitations from both a technical and a conceptual viewpoint. We conclude that while we are starting to understand the impact of this class of genetic variation upon steady-state mRNA levels, we are still far from identifying the potential phenotypic and evolutionary outcomes.
Abstract: The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.
Abstract: Recently, it has been shown that genetic variation that perturbs the regulation of gene ex- pression is widespread in eukaryotic genomes. Regulatory variation (RV) is expected to be an important driver of phenotypic differences, evolutionary change, and susceptibility to complex genetic diseases. Because trans-acting regulators of gene expression control mRNA levels of multiple genes simultaneously, we hypothesise that RV that affects these components will have a shared-influence upon the expression levels of multiple genes. Since genes are regulated in trans by combinations of basal and tissue specific factors, we further hypothesise that RV in these components may have different effects in each tissue.
We used microarrays to identify 755 genes that were affected by RV in at least one of the brain, kidney and liver of two inbred mouse strains, C57BL/6J and DBA/2J. Just 2% were affected in all three tissues, suggesting that the influence of RV is predominantly tissue specific. To study shared-RV, we measured the expression levels of these 755 genes in the same 3 tissues from a panel of recombinant inbred mice, and identified groups of correlated genes that are putatively under the influence of shared trans-acting RV. Using methods that we developed for studying the effects of RV in multiple tissues, we identified 212 genes that are correlated in all three tissues, which include 10 groups of at least 3 genes.
We developed a novel method called coherency analysis to show that RV consistently affected the expression levels of these groups of genes in different genetic backgrounds. Strikingly, the relative up- or down-regulation of genes in each group was markedly different in the three tissues of the same mouse, suggesting that the influence of RV itself is not tissue specific as previously expected, but that RV can influence genes with differing outcomes in each tissue. These observations are compatible with RV affecting combinations of basal and tissue specific regulatory factors. This is the first cross-tissue investigation into the influence of shared- RV in multiple tissues, which has important implications in humans, where access to the phenotypically relevant tissue may be necessarily limited.
