Identification of novel genes expressed during rhabdomyosarcoma differentiation using cDNA microarrays

Rhabdomyosarcomas (RMS) are highly aggressive tumors that are thought to arise as a consequence of the regulatory disruption of the growth and differentiation of skeletal muscle progenitor cells. Normal myogenesis is characterized by the expression of the myogenic regulatory factor gene family but, despite their expression in RMS, these tumor cells fail to complete the latter stages of myogenesis. The RMS cell line RD-A was treated with 12-O-tetradecanoylphorbol-13-acetate to induce differentiation and cultured for 10 days. RNA was extracted on days 1, 3, 6, 8 and 10. A human skeletal muscle cDNA microarray was developed and used to analyze the global gene expression of RMS tumors over the time-course of differentiation. As a comparison, the genes identified were subsequently examined during the differentiated primary human skeletal muscle cultures. Prothymosin alpha (PTMA), and translocase of inner mitochondrial membrane 10 (Tim10), two genes not previously implicated in RMS, showed reduced expression during differentiation. Marked differences in the expression of PTMA and Tim10 were observed during the differentiation of human primary skeletal muscle cells. These results identify several new genes with potential roles in the myogenic arrest present in rhabdomyosarcoma. PTMA expression in RMS biopsy samples might prove to be an effective diagnostic marker for this disease.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches

CIDB: Chlamydia Interactive Database for cross-querying genomics, transcriptomics and proteomics data

Chlamydiae are important pathogens of humans, birds and a wide range of animals. They are a unique group of bacteria, characterized by their developmental cycle. Chlamydia has been difficult to study because of their obligate intracellular growth habit and lack of a genetic transformation system. However, the past 5 years has seen the full genome sequencing of seven strains of Chlamydia and a rapid expansion of genomic, transcriptomic (RT-PCR, microarray) and proteomic analysis of these pathogens. The Chlamydia Interactive Database (CIDB) described here is the first database of its type that holds genomic, RT-PCR, microarray and proteomics data sets that can be cross-queried by researchers for patterns in the data. Combining the data of many research groups into a single database and cross-querying from different perspectives should enhance our understanding of the complex cell biology of these pathogens. The database is available at: http://www3.it.deakin.edu.au:8080/CIDB/.

An effective non-parametric method for globally clustering genes from expression profiles

Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm.

Suppression by ABA of salicylic acid and lignin accumulation and the expression of multiple genes, in Arabidopsis infected with Pseudomonas syringae pv. tomato

Abscisic acid (ABA) has been implicated in determining the outcome of interactions between many plants and their pathogens. We had previously shown that increased concentrations of ABA within leaves of Arabidopsis induced susceptibility towards an avirulent strain of Pseudomonas syringae pathovar (pv.) tomato. We now show that ABA induces susceptibility via suppression of the accumulation of components crucial for a resistance response. Lignin and salicylic acid concentrations in leaves were increased during a resistant interaction but reduced when plants were treated with ABA. The reduction in lignin and salicylic acid production was independent of the development of the hypersensitive response (HR), indicating that, in this host-pathogen system, HR is not required for resistance. Genome-wide gene expression analysis using microarrays showed that treatment with ABA suppressed the expression of many defence-related genes, including those important for phenylpropanoid biosynthesis and those encoding resistance-related proteins. Together, these results show that resistance induction in Arabidopsis to an avirulent strain of P. syringae pv. tomato is regulated by ABA.

U18666A-mediated apoptosis in cultured murine cortical neurons : role of caspases, calpains and kinases

Studies have suggested that cholesterol imbalance in the brain might be related to the development of neurological disorders such as Alzheimer's disease and Niemann–Pick disease type C. Previously, we have reported that U18666A, a cholesterol transport-inhibiting agent, leads to apoptosis and intracellular cholesterol accumulation in primary cortical neurons. In this study, we examined the effects of U18666A-mediated neuronal apoptosis, and found that chronic exposure to U18666A led to the activation of caspases and calpains and hyperphosphorylation of tau. Tau hyperphosphorylation is regulated by several kinases that phosphorylate specific sites of tau in vitro. Surprisingly, the kinase activity of cyclin-dependent kinase 5 decreased in U18666A-treated cortical neurons whereas its protein level remained unchanged. The amount of glycogen synthase kinase 3 and mitogen-activated protein kinases were found to decrease in their phosphorylated states by Western blot analysis. Gene transcription was further studied using microarray analysis. Genes encoding for kinases and phosphatases were differentially expressed with most up-regulated and some down-regulated in expression upon U18666A treatment. The activation of cysteine proteases and cholesterol accumulation with tauopathies may provide clues to the cellular mechanism of the inhibition of cholesterol transport-mediated cell death in neurodegenerative diseases.

Disease fingerprinting with cDNA microarrays reveals distinct gene expression profiles in lethal type 1 and type 2 cytokine-mediated inflammatory reactions

Development of polarized immune responses controls resistance and susceptibility to many microorganisms. However, studies of several infectious, allergic, and autoimmune diseases have shown that chronic type-1 and type-2 cytokine responses can also cause significant morbidity and mortality if left unchecked. We used mouse cDNA microarrays to molecularly phenotype the gene expression patterns that characterize two disparate but equally lethal forms of liver pathology that develop in Schistosoma mansoni infected mice polarized for type-1 and type-2 cytokine responses. Hierarchical clustering analysis identified at least three groups of genes associated with a polarized type-2 response and two linked with an extreme type-1 cytokine phenotype. Predictions about liver fibrosis,  apoptosis, and granulocyte recruitment and activation generated by the microarray studies were confirmed later by traditional biological assays. The data show that cDNA microarrays are useful not only for determining  coordinated gene expression profiles but are also highly effective for molecularly “fingerprinting” diseased tissues. Moreover, they illustrate the potential of genome-wide approaches for generating comprehensive views on the molecular and biochemical mechanisms regulating infectious  disease pathogenesis.

Lignin production and monolignol pathway gene expression is suppressed by abscisic acid during defence reactions of Arabidopsis

The phytohormone, abscisic acid (ABA) has been shown to influence the outcome of the interactions between various hosts with biotrophic and hemibiotrophic pathogens. Susceptibility to avirulent isolates can be induced by addition of low physiological concentrations of ABA to plants. In contrast, addition of ABA biosynthesis inhibitors induced resistance following challenge of plants by virulent isolates. ABA deficient mutants of Arabidopsis, such as aba1-1, were resistant to virulent isolates of Peronospora parasitica. In interactions of Arabidopsis with avirulent isolates of Pseudomonas syringae pv. tomato, susceptibility was induced following addition of ABA or imposition of drought stress. These results indicate a pivotal, albiet undefined, role for ABA in determining either susceptibility or resistance to pathogen attack. We have found that the production of the cell wall strengthening compound, lignin, is increased during resistant interactions of aba1-1 but suppressed in ABA induced susceptible interactions. Using RT-PCR and microarray analysis we have found down-regulation by ABA of key genes of the phenylpropanoid pathway especially of those genes involved directly in lignin biosynthesis. ABA also down-regulates a number of genes in other functional classes including those involved in defence and cell signalling.

Suppression by abscisic acid of lignin production and monolignol pathway gene expression in interactions of Arabidopsis with oomycete and bacterial pathogens

The phytohormone, abscisic acid (ABA) has been shown to influence the outcome of the interactions between various hosts with biotrophic and hemibiotrophic pathogens. Susceptibility to avirulent isolates can be induced in plants by addition of low physiological concentrations of ABA. In contrast, addition of ABA biosynthesis inhibitors induced resistance following challenge of plants by virulent isolates. ABA deficient mutants of Arabidopsis, such as aba1-1, were resistant to virulent isolates of Peronospora parasitica. In interactions of Arabidopsis with avirulent isolates of Pseudomonas syringae pv. tomato, susceptibility was induced following addition of ABA or imposition of drought stress. These results indicate a pivotal, albiet undefined, role for ABA in determining either susceptibility or resistance to pathogen attack. We have found that the production of the cell wall strengthening compound, lignin, is increased during resistant interactions of aba1-1 but suppressed in ABA-induced susceptible interactions. Using RT-PCR and microarray analysis we have found down-regulation by ABA of key genes of the phenylpropanoid pathway especially of those genes involved directly in lignin biosynthesis. ABA also down-regulates a number of genes in other functional classes including those involved in defence and cell signalling.

Investigation of plasmodiophora brassicae (clubroot disease) in vegetable brassica using arabidopsis thaliana as a model system

Clubroot, caused by Plasmodiophora brassicae, is the most devastating soil-borne disease of vegetable brassicas. It occurs all over the world and is responsible for crop losses of up to 10% every year. In Australia, the disease is being managed effectively with chemicals and cultural practices, but ideally control can be improved in the long term by the introduction of resistant cultivars. The life cycle ofP. brassicae and mode of action of plant resistance has not been fully elucidated because of the technical difficulties of working with an obligate, soil-borne plant pathogen. However, Arabidopsis thaliana, which is a host ofP. brassicae, has great potential as a model system for studying the life cycle, the infection process and development of resistance. We have developed a sand-liquid-culture system for growing Arabidopsis that allows easy observation of all life stages and, most importantly, the primary plasmodial stages within the root hair. The method was first optimised for observations of the lifecycle of the pathogen in a susceptible Arabidopsis ecotype (Col-3) where all stages of the lifecycle have now been observed and characterised. Further screening of Arabidopsis ecotypes for disease resistance has utilised one of the most virulent Australian pathotypes of brassica (ECD number 16/19/31). To date, Arabidopsis ecotype Ta-0 has shown a level of tolerance to the disease even though the roots get infected. It has been reported earlier that resistance toP. brassicae in Arabidopsis is due to one or a small number of genes. To examine changes in gene expression during the early, critical stages of infection, RNA was extracted from the susceptible and resistant ecotypes at two time points, 4 days and 17 days after inoculation. Microarray analysis will be used to investigate genome wide changes in gene expression during infection but also to identify candidate genes that may confer resistance to Australian isolates of the pathogen.

Global and targeted gene expression and protein content in skeletal muscle of young men following short-term creatine monohydrate supplementation

Creatine monohydrate (CrM) supplementation has been shown to increase fat-free mass and muscle power output possibly via cell swelling. Little is known about the cellular response to CrM. We investigated the effect of short-term CrM supplementation on global and targeted mRNA expression and protein content in human skeletal muscle. In a randomized, placebo-controlled, crossover, double-blind design, 12 young, healthy, nonobese men were supplemented with either a placebo (PL) or CrM (loading phase, 20 g/day x 3 days; maintenance phase, 5 g/day x 7 days) for 10 days. Following a 28-day washout period, subjects were put on the alternate supplementation for 10 days. Muscle biopsies of the vastus lateralis were obtained and were assessed for mRNA expression (cDNA microarrays + real-time PCR) and protein content (Kinetworks KPKS 1.0 Protein Kinase screen). CrM supplementation significantly increased fat-free mass, total body water, and body weight of the participants (P < 0.05). Also, CrM supplementation significantly upregulated (1.3- to 5.0-fold) the mRNA content of genes and protein content of kinases involved in osmosensing and signal transduction, cytoskeleton remodeling, protein and glycogen synthesis regulation, satellite cell proliferation and differentiation, DNA replication and repair, RNA transcription control, and cell survival. We are the first to report this large-scale gene expression in the skeletal muscle with short-term CrM supplementation, a response that suggests changes in cellular osmolarity.

A clustering based hybrid system for mass spectrometry data analysis

Recently, much attention has been given to the mass spectrometry (MS) technology based disease classification, diagnosis, and protein-based biomarker identification. Similar to microarray based investigation, proteomic data generated by such kind of high-throughput experiments are often with high feature-to-sample ratio. Moreover, biological information and pattern are compounded with data noise, redundancy and outliers. Thus, the development of algorithms and procedures for the analysis and interpretation of such kind of data is of paramount importance. In this paper, we propose a hybrid system for analyzing such high dimensional data. The proposed method uses the k-mean clustering algorithm based feature extraction and selection procedure to bridge the filter selection and wrapper selection methods. The potential informative mass/charge (m/z) markers selected by filters are subject to the k-mean clustering algorithm for correlation and redundancy reduction, and a multi-objective Genetic Algorithm selector is then employed to identify discriminative m/z markers generated by k-mean clustering algorithm. Experimental results obtained by using the proposed method indicate that it is suitable for m/z biomarker selection and MS based sample classification.

Functional and metabolic remodelling in GLUT4-deficient hearts confers hyper-responsiveness to substrate intervention

Impaired glucose uptake is associated with both cardiac hypertrophy and contractile dysfunction, but whether there are common underlying  mechanisms linking these conditions is yet to be determined. Using a ‘gene dose’ Cre-Lox GLUT4-deficient murine model, we examined the effect of suppressed glucose availability on global myocardial gene expression and glycolysis substrate bypass on the function of isolated perfused hearts. Performance of hearts from 22- to 60-week-old male GLUT4 knockout (KO, > 95% reduction in GLUT4), GLUT4 knockdown (KD, 85% reduction in cardiac GLUT4) and C57Bl/6 wild-type (WT) controls was measured ex vivo in Langendorff mode perfusion. DNA microarray was used to profile mRNA expression differences between GLUT4-KO and GLUT4-KD hearts. At 22 weeks, GLUT4-KO hearts exhibited cardiac hypertrophy and impaired contractile function ex vivo, characterized by a 40% decrease in developed pressure. At 60 weeks, dysfunction was accentuated in GLUT4-KO hearts and evident in GLUT4-KD hearts. Exogenous pyruvate (5 mM) restored systolic pressure to a level equivalent to WT (GLUT4-KO, 176.8 ± 13.2 mmHg vs. WT, 146.4 ± 9.56 mmHg) in 22-week-old GLUT4-KO hearts but not in 60-week-old GLUT4-KO hearts. In GLUT4-KO, DNA microarray analysis detected downregulation of a number of genes centrally involved in mitochondrial oxidation and upregulation of other genes indicative of a shift to cytosolic β-oxidation of long chain fatty acids. A direct link between cardiomyocyte GLUT4 deficiency, hypertrophy and contractile dysfunction is demonstrated. These data provide mechanistic insight into the myocardial metabolic adaptations associated with short and long-term insulin resistance and indicate a window of opportunity for substrate intervention and functional ‘rescue’.

Identification of secreted proteins associated with obesity and type 2 diabetes in Psammomys obesus

Objective: Skeletal muscle produces a variety of secreted proteins that have important roles in intercellular communication and affects processes such as glucose homoeostasis. The objective of this study was to develop a novel Signal Sequence Trap (SST) in conjunction with cDNA microarray technology to identify proteins secreted from skeletal muscle of Psammomys obesus that were associated with obesity and type 2 diabetes (T2D).

Design: Secreted proteins that were differentially expressed between lean, normal glucose tolerant (NGT), overweight and impaired glucose tolerant (IGT) and obese, T2D P. obesus were isolated using SST in conjunction with cDNA microarray technology. Subsequent gene expression was measured in tissues from P. obesus by real-time PCR (RT-PCR).

Results: The SST yielded 1600 positive clones, which were screened for differential expression. A total of 91 (B6%) clones were identified by microarray to be differentially expressed between NGT, IGT and T2D P. obesus. These clones were sequenced to identify 51 genes, of which only 27 were previously known to encode secreted proteins. Three candidate genes not previously associated with obesity or type 2 diabetes, sushi domain containing 2, collagen and calcium-binding EGF domains 1 and periostin (Postn), as well as one gene known to be associated, complement component 1, were shown by RT-PCR to be differentially expressed in  skeletal muscle of P. obesus. Further characterization of the secreted protein Postn revealed it to be predominantly expressed in adipose tissue, with higher expression in visceral compared with subcutaneous adipose depots.

Conclusion: SST in conjunction with cDNA microarray technology is a powerful tool to identify differentially expressed secreted proteins involved in complex diseases such as obesity and type 2 diabetes. Furthermore, a number of candidate genes were identified, in particular, Postn, which may have a role in the development of obesity and type 2 diabetes.

Data pre-processing for more effective gene clustering

The high-throughput experimental data from the new gene microarray technology has spurred numerous efforts to find effective ways of processing microarray data for revealing real biological relationships among genes. This work proposes an innovative data pre-processing approach to identify noise data in the data sets and eliminate or reduce the impact of the noise data on gene clustering, With the proposed algorithm, the pre-processed data sets make the clustering results stable across clustering algorithms with different similarity metrics, the important information of genes and features is kept, and the clustering quality is improved. The primary evaluation on real microarray data sets has shown the effectiveness of the proposed algorithm.