Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

<p>Abstract</p> <p>Background</p> <p>Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, <it>post hoc </it>tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has <it>a priori </it>information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.</p> <p>Results</p> <p>We developed a four step, <it>post hoc </it>pattern matching (PPM) algorithm to automate single channel gene expression pattern identification/significance. First, 1-Way Analysis of Variance (ANOVA), coupled with <it>post hoc </it>'all pairwise' comparisons are calculated for all genes. Second, for each ANOVA-significant gene, all pairwise contrast results are encoded to create unique pattern ID numbers. The # genes found in each pattern in the data is identified as that pattern's 'actual' frequency. Third, using Monte Carlo simulations, those patterns' frequencies are estimated in random data ('random' gene pattern frequency). Fourth, a Z-score for overrepresentation of the pattern is calculated ('actual' against 'random' gene pattern frequencies). We wrote a Visual Basic program (StatiGen) that automates PPM procedure, constructs an Excel workbook with standardized graphs of overrepresented patterns, and lists of the genes comprising each pattern. The visual basic code, installation files for StatiGen, and sample data are available as supplementary material.</p> <p>Conclusion</p> <p>The PPM procedure is designed to augment current microarray analysis procedures by allowing researchers to incorporate all of the information from post hoc tests to establish unique, overarching gene expression patterns in which there is no overlap in gene membership. In our hands, PPM works well for studies using from three to six treatment groups in which the researcher is interested in treatment-related patterns of gene expression. Hardware/software limitations and extreme number of theoretical expression patterns limit utility for larger numbers of treatment groups. Applied to a published microarray experiment, the StatiGen program successfully flagged patterns that had been manually assigned in prior work, and further identified other gene expression patterns that may be of interest. Thus, over a moderate range of treatment groups, PPM appears to work well. It allows researchers to assign statistical probabilities to patterns of gene expression that fit <it>a priori </it>expectations/hypotheses, it preserves the data's ability to show the researcher interesting, yet unanticipated gene expression patterns, and assigns the majority of ANOVA-significant genes to non-overlapping patterns.</p

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Inhibition of PbGP43 expression may suggest that gp43 is a virulence factor in Paracoccidioides brasiliensis

ABSTARCT: Glycoprotein gp43 is an immunodominant diagnostic antigen for paracoccidioidomycosis caused by Paracoccidioides brasiliensis. It is abundantly secreted in isolates such as Pb339. It is structurally related to beta-1,3-exoglucanases, however inactive. Its function in fungal biology is unknown, but it elicits humoral, innate and protective cellular immune responses; it binds to extracellular matrix-associated proteins. In this study we applied an antisense RNA (aRNA) technology and Agrobacterium tumefaciens-mediated transformation to generate mitotically stable PbGP43 mutants (PbGP43 aRNA) derived from wild type Pb339 to study its role in P. brasiliensis biology and during infection. Control PbEV was transformed with empty vector. Growth curve, cell vitality and morphology of PbGP43 aRNA mutants were indistinguishable from those of controls. PbGP43 expression was reduced 80-85% in mutants 1 and 2, as determined by real time PCR, correlating with a massive decrease in gp43 expression. This was shown by immunoblotting of culture supernatants revealed with anti-gp43 mouse monoclonal and rabbit polyclonal antibodies, and also by affinity-ligand assays of extracellular molecules with laminin and fibronectin. In vitro, there was significantly increased TNF-α production and reduced yeast recovery when PbGP43 aRNA1 was exposed to IFN-γ-stimulated macrophages, suggesting reduced binding/uptake and/or increased killing. In vivo, fungal burden in lungs of BALB/c mice infected with silenced mutant was negligible and associated with decreased lung ΙΛ-10 and IL-6. Therefore, our results correlated low gp43 expression with lower pathogenicity in mice, but that will be definitely proven when PbGP43 knockouts become available.

Short-Term Enrichment Makes Male Rats More Attractive, More Defensive and Alters Hypothalamic Neurons

Innate behaviors are shaped by contingencies built during evolutionary history. On the other hand, environmental stimuli play a significant role in shaping behavior. In particular, a short period of environmental enrichment can enhance cognitive behavior, modify effects of stress on learned behaviors and induce brain plasticity. It is unclear if modulation by environment can extend to innate behaviors which are preserved by intense selection pressure. In the present report we investigate this issue by studying effects of relatively short (14-days) environmental enrichment on two prominent innate behaviors in rats, avoidance of predator odors and ability of males to attract mates. We show that enrichment has strong effects on both the innate behaviors: a) enriched males were more avoidant of a predator odor than non-enriched controls, and had a greater rise in corticosterone levels in response to the odor; and b) had higher testosterone levels and were more attractive to females. Additionally, we demonstrate decrease in dendritic length of neurons of ventrolateral nucleus of hypothalamus, important for reproductive mate-choice and increase in the same in dorsomedial nucleus, important for defensive behavior. Thus, behavioral and hormonal observations provide evidence that a short period of environmental manipulation can alter innate behaviors, providing a good example of gene-environment interaction

A Phosphoproteomic Approach towards the Understanding of the Role of TGF-β in Trypanosoma cruzi Biology

Transforming growth factor beta (TGF-β) plays a pivotal role in Chagas disease, not only in the development of chagasic cardiomyopathy, but also in many stages of the T. cruzi life cycle and survival in the host cell environment. The intracellular signaling pathways utilized by T. cruzi to regulate these mechanisms remain unknown. To identify parasite proteins involved in the TGF-β response, we utilized a combined approach of two-dimensional gel electrophoresis (2DE) analysis and mass spectrometry (MS) protein identification. Signaling via TGF-β is dependent on events of phosphorylation, which is one of the most relevant and ubiquitous post-translational modifications for the regulation of gene expression, and especially in trypanosomatids, since they lack several transcriptional control mechanisms. Here we show a kinetic view of T. cruzi epimastigotes (Y strain) incubated with TGF-β for 1, 5, 30 and 60 minutes, which promoted a remodeling of the parasite phosphorylation network and protein expression pattern. The altered molecules are involved in a variety of cellular processes, such as proteolysis, metabolism, heat shock response, cytoskeleton arrangement, oxidative stress regulation, translation and signal transduction. A total of 75 protein spots were up- or down-regulated more than twofold after TGF-β treatment, and from these, 42 were identified by mass spectrometry, including cruzipain–the major T. cruzi papain-like cysteine proteinase that plays an important role in invasion and participates in the escape mechanisms used by the parasite to evade the host immune system. In our study, we observed that TGF-β addition favored epimastigote proliferation, corroborating 2DE data in which proteins previously described to be involved in this process were positively stimulated by TGF-β

Pattern recognition receptors in immune disorders affecting the skin.

Contains fulltext : 109004.pdf (publisher's version ) (Open Access)Pattern recognition receptors (PRRs) evolved to protect organisms against pathogens, but excessive signaling can induce immune responses that are harmful to the host. Putative PRR dysfunction is associated with numerous immune disorders that affect the skin, such as systemic lupus erythematosus, cryopyrin-associated periodic syndrome, and primary inflammatory skin diseases including psoriasis and atopic dermatitis. As yet, the evidence is often confined to genetic association studies without additional proof of a causal relationship. However, insight into the role of PRRs in the pathophysiology of some disorders has already resulted in new therapeutic approaches based on immunomodulation of PRRs

The apicomplexan plastid and its evolution

Protistan species belonging to the phylum Apicomplexa have a non-photosynthetic secondary plastid—the apicoplast. Although its tiny genome and even the entire nuclear genome has been sequenced for several organisms bearing the organelle, the reason for its existence remains largely obscure. Some of the functions of the apicoplast, including housekeeping ones, are significantly different from those of other plastids, possibly due to the organelle’s unique symbiotic origin

Rule-Based Cell Systems Model of Aging using Feedback Loop Motifs Mediated by Stress Responses

Investigating the complex systems dynamics of the aging process requires integration of a broad range of cellular processes describing damage and functional decline co-existing with adaptive and protective regulatory mechanisms. We evolve an integrated generic cell network to represent the connectivity of key cellular mechanisms structured into positive and negative feedback loop motifs centrally important for aging. The conceptual network is casted into a fuzzy-logic, hybrid-intelligent framework based on interaction rules assembled from a priori knowledge. Based upon a classical homeostatic representation of cellular energy metabolism, we first demonstrate how positive-feedback loops accelerate damage and decline consistent with a vicious cycle. This model is iteratively extended towards an adaptive response model by incorporating protective negative-feedback loop circuits. Time-lapse simulations of the adaptive response model uncover how transcriptional and translational changes, mediated by stress sensors NF-κB and mTOR, counteract accumulating damage and dysfunction by modulating mitochondrial respiration, metabolic fluxes, biosynthesis, and autophagy, crucial for cellular survival. The model allows consideration of lifespan optimization scenarios with respect to fitness criteria using a sensitivity analysis. Our work establishes a novel extendable and scalable computational approach capable to connect tractable molecular mechanisms with cellular network dynamics underlying the emerging aging phenotype