Transformation of metabolism with age and lifestyle in Antarctic seals: a case study of systems biology approach to cross-species microarray experiment

*_Background:_* The metabolic transformation that changes Weddell seal pups born on land into aquatic animals is not only interesting for the study of general biology, but it also provides a model for the acquired and congenital muscle disorders which are associated with oxygen metabolism in skeletal muscle. However, the analysis of gene expression in seals is hampered by the lack of specific microarrays and the very limited annotation of known Weddell seal (_Leptonychotes weddellii_) genes.

*_Results:_* Muscle samples from newborn, juvenile, and adult Weddell seals were collected during an Antarctic expedition. Extracted RNA was hybridized on Affymetrix Human Expression chips. Preliminary studies showed a detectable signal from at least 7000 probe sets present in all samples and replicates. Relative expression levels for these genes was used for further analysis of the biological pathways implicated in the metabolism transformation which occurs in the transition from newborn, to juvenile, to adult seals. Cytoskeletal remodeling, WNT signaling, FAK signaling, hypoxia-induced HIF1 activation, and insulin regulation were identified as being among the most important biological pathways involved in transformation. 

*_Conclusion:_* In spite of certain losses in specificity and sensitivity, the cross-species application of gene expression microarrays is capable of solving challenging puzzles in biology. A Systems Biology approach based on gene interaction patterns can compensate adequately for the lack of species-specific genomics information.
&#xa

Comprehensive analysis of circadian periodic pattern in plant transcriptome

Abstract Background Circadian rhythm is a crucial factor in orchestration of plant physiology, keeping it in synchrony with the daylight cycle. Previous studies have reported that up to 16% of plant transcriptome are circadially expressed. Results Our studies of mammalian gene expression revealed circadian baseline oscillation in nearly 100% of genes. Here we present a comprehensive analysis of periodicity in two independent data sets. Application of the advanced algorithms and analytic approached already tested on animal data reveals oscillation in almost every gene of Arabidopsis thaliana. Conclusion This study indicates an even more pervasive role of oscillation in molecular physiology of plants than previously believed. Earlier studies have dramatically underestimated the prevalence of circadian oscillation in plant gene expression.</p

New Algorithms for EST clustering

Philosophiae Doctor - PhDExpressed sequence tag database is a rich and fast growing source of data for gene expression analysis and drug discovery. Clustering of raw EST data is a necessary step for further analysis and one of the most challenging problems of modem computational biology. There are a few systems, designed for this purpose and a few more are currently under development. These systems are reviewed in the "Literature and software review". Different strategies of supervised and unsupervised clustering are discussed, as well as sequence comparison techniques, such as based on alignment or oligonucleotide compositions. Analysis of potential bottlenecks and estimation of computation complexity of EST clustering is done in Chapter 2. This chapter also states the goals for the research and justifies the need for new algorithm that has to be fast, but still sensitive to relatively short (40 bp) regions of local similarity. A new sequence comparison algorithm is developed and described in Chapter 3. This algorithm has a linear computation complexity and sufficient sensitivity to detect short regions of local similarity between nucleotide sequences. The algorithm utilizes an asymmetric approach, when one of the compared sequences is presented in a form of oligonucleotide table, while the second sequence is in standard, linear form. A short window is moved along the linear sequence and all overlapping oligonucleotides of a constant length in the frame are compared for the oligonucleotide table. The result of comparison of two sequences is a single figure, which can be compared to a threshold. For each measure of sequence similarity a probability of false positive and false negative can be estimated. The algorithm was set up and implemented to recognize matching ESTs with overlapping regions of 40bp with 95% identity, which is better than resolution ability of contemporary EST clustering tools This algorithm was used as a sequence comparison engine for two EST clustering programs, described in Chapter 4. These programs implement two different strategies: stringent and loose clustering. Both are tested on small, but realistic benchmark data sets and show the results, similar to one of the best existing clustering programs, 02_cluster, but with a significant advantage in speed and sensitivity to small overlapping regions of ESTs. On three different CPUs the new algorithm run at least two times faster, leaving less singletons and producing bigger clusters. With parallel optimization this algorithm is capable of clustering millions of ESTs on relatively inexpensive computers. The loose clustering variant is a highly portable application, relying on third-party software for cluster assembly. It was built to the same specifications as 02_ cluster and can be immediately included into the STACKPack package for EST clustering. The stringent clustering program produces already assembled clusters and can apprehend alternatively processed variants during the clustering process

Permutation test for periodicity in short time series data

Abstract Background Periodic processes, such as the circadian rhythm, are important factors modulating and coordinating transcription of genes governing key metabolic pathways. Theoretically, even small fluctuations in the orchestration of circadian gene expression patterns among different tissues may result in functional asynchrony at the organism level and may contribute to a wide range of pathologic disorders. Identification of circadian expression pattern in time series data is important, but equally challenging. Microarray technology allows estimation of relative expression of thousands of genes at each time point. However, this estimation often lacks precision and microarray experiments are prohibitively expensive, limiting the number of data points in a time series expression profile. The data produced in these experiments carries a high degree of stochastic variation, obscuring the periodic pattern and a limited number of replicates, typically covering not more than two complete periods of oscillation. Results To address this issue, we have developed a simple, but effective, computational technique for the identification of a periodic pattern in relatively short time series, typical for microarray studies of circadian expression. This test is based on a random permutation of time points in order to estimate non-randomness of a periodogram. The Permutated time, or Pt-test, is able to detect oscillations within a given period in expression profiles dominated by a high degree of stochastic fluctuations or oscillations of different irrelevant frequencies. We have conducted a comprehensive study of circadian expression on a large data set produced at PBRC, representing three different peripheral murine tissues. We have also re-analyzed a number of similar time series data sets produced and published independently by other research groups over the past few years. Conclusion The Permutated time test (Pt-test) is demonstrated to be effective for detection of periodicity in short time series typical for high-density microarray experiments. The software is a set of C++ programs available from the authors on the open source basis.</p

Analysis of circadian pattern reveals tissue-specific alternative transcription in leptin signaling pathway

*Background*&#xd;&#xa;It has been previously reported that most mammalian genes display a circadian oscillation in their baseline expression. Consequently, the phase and amplitude of each component of a signal transduction cascade has downstream consequences. &#xd;&#xa;&#xd;&#xa;*Results*&#xd;&#xa;We report our analysis of alternative transcripts in the leptin signaling pathway which is responsible for the systemic regulation of macronutrient storage and energy balance. We focused on the circadian expression pattern of a critical component of the leptin signaling system, suppressor of cytokine signaling 3 (SOCS3). On an Affymetrix GeneChip 430A2 microarray, this gene is represented by three probe sets targeting different regions within the 3&#x2019; end of the last exon. We demonstrate that in murine brown adipose tissue two downstream 3&#x2019; probe sets experience circadian baseline oscillation in counter-phase to the upstream probe set. Such differences in expression patterns are a telltale sign of alternative splicing within the last exon of SOCS3. In contrast, all three probe sets oscillated in a common phase in murine liver and white adipose tissue. This suggests that the regulation of SOCS3 expression in brown fat is tissue specific. Another component of the signaling pathway, Janus kinase (JAK), is directly regulated by SOCS and has alternative transcript probe sets oscillating in counter-phase in a white adipose tissue specific manner.&#xd;&#xa; &#xd;&#xa;*Conclusion*&#xd;&#xa;We hypothesize that differential oscillation of alternative transcripts may provide a mechanism to maintain steady levels of expression in spite of circadian baseline variation

Digital Signal Processing Reveals Circadian Baseline Oscillation in Majority of Mammalian Genes

In mammals, circadian periodicity has been described for gene expression in the hypothalamus and multiple peripheral tissues. It is accepted that 10%–15% of all genes oscillate in a daily rhythm, regulated by an intrinsic molecular clock. Statistical analyses of periodicity are limited by the small size of datasets and high levels of stochastic noise. Here, we propose a new approach applying digital signal processing algorithms separately to each group of genes oscillating in the same phase. Combined with the statistical tests for periodicity, this method identifies circadian baseline oscillation in almost 100% of all expressed genes. Consequently, circadian oscillation in gene expression should be evaluated in any study related to biological pathways. Changes in gene expression caused by mutations or regulation of environmental factors (such as photic stimuli or feeding) should be considered in the context of changes in the amplitude and phase of genetic oscillations

Unsupervised clustering of gene expression data points at hypoxia as possible trigger for metabolic syndrome

BACKGROUND: Classification of large volumes of data produced in a microarray experiment allows for the extraction of important clues as to the nature of a disease. RESULTS: Using multi-dimensional unsupervised FOREL (FORmal ELement) algorithm we have re-analyzed three public datasets of skeletal muscle gene expression in connection with insulin resistance and type 2 diabetes (DM2). Our analysis revealed the major line of variation between expression profiles of normal, insulin resistant, and diabetic skeletal muscle. A cluster of most "metabolically sound" samples occupied one end of this line. The distance along this line coincided with the classic markers of diabetes risk, namely obesity and insulin resistance, but did not follow the accepted clinical diagnosis of DM2 as defined by the presence or absence of hyperglycemia. Genes implicated in this expression pattern are those controlling skeletal muscle fiber type and glycolytic metabolism. Additionally myoglobin and hemoglobin were upregulated and ribosomal genes deregulated in insulin resistant patients. CONCLUSION: Our findings are concordant with the changes seen in skeletal muscle with altitude hypoxia. This suggests that hypoxia and shift to glycolytic metabolism may also drive insulin resistance

Resveratrol suppresses human colon cancer cell proliferation and induces apoptosis via targeting the pentose phosphate and the talin-FAK signaling pathways-A proteomic approach

<p>Abstract</p> <p>Background</p> <p>We and others have previously reported that resveratrol (RSV) suppresses colon cancer cell proliferation and elevates apoptosis <it>in vitro </it>and/or <it>in vivo</it>, however molecular mechanisms are not fully elucidated. Particularly, little information is available on RSV's effects on metabolic pathways and the cell-extra cellular matrix (ECM) communication that are critical for cancer cell growth. To identify important targets of RSV, we analyzed whole protein fractions from HT-29 advanced human colon cancer cell line treated with solvent control, IGF-1 (10 nM) and RSV (150 μM) using LC/MS/MS-Mud PIT (Multidimensional Protein Identification Technology).</p> <p>Results</p> <p>Pentose phosphate pathway (PPP), a vital metabolic pathway for cell cycle progression, was elevated and suppressed by IGF-1 and RSV, respectively in the HT-29 cell line. Enzymatic assays confirmed RSV suppression of glucose-6 phosphate dehydrogenase (rate limiting) and transketolase, key enzymes of the PPP. RSV (150 μM) suppressed, whereas IGF-1 (10 nM) elevated focal adhesion complex (FAC) proteins, talin and pFAK, critical for the cell-ECM communication. Western blotting analyses confirmed the suppression or elevation of these proteins in HT-29 cancer cells treated with RSV or IGF-1, respectively.</p> <p>Conclusions</p> <p>Proteomic analysis enabled us to establish PPP and the talin-pFAK as targets of RSV which suppress cancer cell proliferation and induce apoptosis in the colon cancer cell line HT-29. RSV (150 μM) suppressed these pathways in the presence and absence of IGF-1, suggesting its role as a chemo-preventive agent even in obese condition.</p

Regional Societies: Fostering Competitive Research Through Virtual Infrastructures

The MidSouth Computational Biology and Bioinformatics Society (MCBIOS) describes its efforts to provide local opportunities for researchers to learn and connect with colleague

Expression profiling in canine osteosarcoma: identification of biomarkers and pathways associated with outcome

<p>Abstract</p> <p>Background</p> <p>Osteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities.</p> <p>Methods</p> <p>We analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform.</p> <p>Results</p> <p>Potential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion.</p> <p>Conclusions</p> <p>This profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention.</p