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Comparative study of gene expression during the differentiation of white and brown preadipocytes
(2002)
Introduction Mammals have two types of adipose tissue: the lipid storing white adipose tissue and the brown adipose tissue characterised by its capacity for non-shivering thermogenesis. White and brown adipocytes have the same origin in mesodermal stem cells. Yet nothing is known so far about the commitment of precursor cells to the white and brown adipose lineage. Several experimental approaches indicate that they originate from the differentiation of two distinct types of precursor cells, white and brown preadipocytes. Based on this hypothesis, the aim of this study was to analyse the gene expression of white and brown preadipocytes in a systematic approach. Experimental approach The white and brown preadipocytes to compare were obtained from primary cell cultures of preadipocytes from the Djungarian dwarf hamster. Representational difference analysis was used to isolate genes potentially differentially expressed between the two cell types. The thus obtained cDNA libraries were spotted on microarrays for a large scale gene expression analysis in cultured preadipocytes and adipocytes and in tissue samples. Results 4 genes with higher expression in white preadipocytes (3 members of the complement system and a fatty acid desaturase) and 8 with higher expression in brown preadipocytes were identified. From the latter 3 coded for structural proteins (fibronectin, metargidin and a actinin 4), 3 for proteins involved in transcriptional regulation (necdin, vigilin and the small nuclear ribonucleoprotein polypeptide A) and 2 are of unknown function. Cluster analysis was applied to the gene expression data in order to characterise them and led to the identification of four major typical expression profiles: genes up-regulated during differentiation, genes down-regulated during differentiation, genes higher expressed in white preadipocytes and genes higher expressed in brown preadipocytes. Conclusion This study shows that white and brown preadipocytes can be distinguished by different expression levels of several genes. These results draw attention to interesting candidate genes for the determination of white and brown preadipocytes (necdin, vigilin and others) and furthermore indicate that potential importance of several functional groups in the differentiation of white and brown preadipocytes, mainly the complement system and extracellular matrix.
Recent high-throughput technologies enable the acquisition of a variety of complementary data and imply regulatory networks on the systems biology level. A common approach to the reconstruction of such networks is the cluster analysis which is based on a similarity measure. We use the information theoretic concept of the mutual information, that has been originally defined for discrete data, as a measure of similarity and propose an extension to a commonly applied algorithm for its calculation from continuous biological data. We compare our approach to previously existing algorithms. We develop a performance optimised software package for the application of the mutual information to large-scale datasets. Furthermore, we design and implement a web-based service for the analysis of integrated data measured with different technologies. Application to biological data reveals biologically relevant groupings and reconstructed signalling networks show agreements with physiological findings.
SLocX predicting subcellular localization of Arabidopsis proteins leveraging gene expression data
(2011)
Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mito-chondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.
ORS1, an H2O2-Responsive NAC Transcription Factor, Controls Senescence in Arabidopsis thaliana
(2011)
We report here that ORS1, a previously uncharacterized member of the NAC transcription factor family, controls leaf senescence in Arabidopsis thaliana. Overexpression of ORS1 accelerates senescence in transgenic plants, whereas its inhibition delays it. Genes acting downstream of ORS1 were identified by global expression analysis using transgenic plants producing dexamethasone-inducible ORS1-GR fusion protein. Of the 42 up-regulated genes, 30 (similar to 70%) were previously shown to be up-regulated during age-dependent senescence. We also observed that 32 (similar to 76%) of the ORS1-dependent genes were induced by long-term (4 d), but not short-term (6 h) salinity stress (150 mM NaCl). Furthermore, expression of 16 and 24 genes, respectively, was induced after 1 and 5 h of treatment with hydrogen peroxide (H2O2), a reactive oxygen species known to accumulate during salinity stress. ORS1 itself was found to be rapidly and strongly induced by H2O2 treatment in both leaves and roots. Using in vitro binding site selection, we determined the preferred binding motif of ORS1 and found it to be present in half of the ORS1-dependent genes. ORS1 is a paralog of ORE1/ANAC092/AtNAC2, a previously reported regulator of leaf senescence. Phylogenetic footprinting revealed evolutionary conservation of the ORS1 and ORE1 promoter sequences in different Brassicaceae species, indicating strong positive selection acting on both genes. We conclude that ORS1, similarly to ORE1, triggers expression of senescence-associated genes through a regulatory network that may involve cross-talk with salt- and H2O2-dependent signaling pathways.
Die Strahlentherapie ist neben der Chemotherapie und einer operativen Entfernung die stärkste Waffe für die Bekämpfung bösartiger Tumore in der Krebsmedizin. Nach Herz-Kreislauf-Erkrankungen ist Krebs die zweithäufigste Todesursache in der westlichen Welt, wobei Prostatakrebs heutzutage die häufigste, männliche Krebserkrankung darstellt. Trotz technologischer Fortschritte der radiologischen Verfahren kann es noch viele Jahre nach einer Radiotherapie zu einem Rezidiv kommen, was zum Teil auf die hohe Resistenzfähigkeit einzelner, entarteter Zellen des lokal vorkommenden Tumors zurückgeführt werden kann. Obwohl die moderne Strahlenbiologie viele Aspekte der Resistenzmechanismen näher beleuchtet hat, bleiben Fragestellungen, speziell über das zeitliche Ansprechen eines Tumors auf ionisierende Strahlung, größtenteils unbeantwortet, da systemweite Untersuchungen nur begrenzt vorliegen. Als Zellmodelle wurden vier Prostata-Krebszelllinien (PC3, DuCaP, DU-145, RWPE-1) mit unterschiedlichen Strahlungsempfindlichkeiten kultiviert und auf ihre Überlebensfähigkeit nach ionisierender Bestrahlung durch einen Trypanblau- und MTT-Vitalitätstest geprüft. Die proliferative Kapazität wurde mit einem Koloniebildungstest bestimmt. Die PC3 Zelllinie, als Strahlungsresistente, und die DuCaP Zelllinie, als Strahlungssensitive, zeigten dabei die größten Differenzen bezüglich der Strahlungsempfindlichkeit. Auf Grundlage dieser Ergebnisse wurden die beiden Zelllinien ausgewählt, um anhand ihrer transkriptomweiten Genexpressionen, eine Identifizierung potentieller Marker für die Prognose der Effizienz einer Strahlentherapie zu ermöglichen. Weiterhin wurde mit der PC3 Zelllinie ein Zeitreihenexperiment durchgeführt, wobei zu 8 verschiedenen Zeitpunkten nach Bestrahlung mit 1 Gy die mRNA mittels einer Hochdurchsatz-Sequenzierung quantifiziert wurde, um das dynamisch zeitversetzte Genexpressionsverhalten auf Resistenzmechanismen untersuchen zu können. Durch das Setzen eines Fold Change Grenzwertes in Verbindung mit einem P-Wert < 0,01 konnten aus 10.966 aktiven Genen 730 signifikant differentiell exprimierte Gene bestimmt werden, von denen 305 stärker in der PC3 und 425 stärker in der DuCaP Zelllinie exprimiert werden. Innerhalb dieser 730 Gene sind viele stressassoziierte Gene wiederzufinden, wie bspw. die beiden Transmembranproteingene CA9 und CA12. Durch Berechnung eines Netzwerk-Scores konnten aus den GO- und KEGG-Datenbanken interessante Kategorien und Netzwerke abgeleitet werden, wobei insbesondere die GO-Kategorien Aldehyd-Dehydrogenase [NAD(P)+] Aktivität (GO:0004030) und der KEGG-Stoffwechselweg der O-Glykan Biosynthese (hsa00512) als relevante Netzwerke auffällig wurden. Durch eine weitere Interaktionsanalyse konnten zwei vielversprechende Netzwerke mit den Transkriptionsfaktoren JUN und FOS als zentrale Elemente identifiziert werden. Zum besseren Verständnis des dynamisch zeitversetzten Ansprechens der strahlungsresistenten PC3 Zelllinie auf ionisierende Strahlung, konnten anhand der 10.840 exprimierten Gene und ihrer Expressionsprofile über 8 Zeitpunkte interessante Einblicke erzielt werden. Während es innerhalb von 30 min (00:00 - 00:30) nach Bestrahlung zu einer schnellen Runterregulierung der globalen Genexpression kommt, folgen in den drei darauffolgenden Zeitabschnitten (00:30 - 01:03; 01:03 - 02:12; 02:12 - 04:38) spezifische Expressionserhöhungen, die eine Aktivierung schützender Netzwerke, wie die Hochregulierung der DNA-Reparatursysteme oder die Arretierung des Zellzyklus, auslösen. In den abschließenden drei Zeitbereichen (04:38 - 09:43; 09:43 - 20:25; 20:25 - 42:35) liegt wiederum eine Ausgewogenheit zwischen Induzierung und Supprimierung vor, wobei die absoluten Genexpressionsveränderungen ansteigen. Beim Vergleich der Genexpressionen kurz vor der Bestrahlung mit dem letzten Zeitpunkt (00:00 - 42:53) liegen mit 2.670 die meisten verändert exprimierten Gene vor, was einer massiven, systemweiten Genexpressionsänderung entspricht. Signalwege wie die ATM-Regulierung des Zellzyklus und der Apoptose, des NRF2-Signalwegs nach oxidativer Stresseinwirkung und die DNA-Reparaturmechanismen der homologen Rekombination, des nicht-homologen End Joinings, der MisMatch-, der Basen-Exzision- und der Strang-Exzision-Reparatur spielen bei der zellulären Antwort eine tragende Rolle. Äußerst interessant sind weiterhin die hohen Aktivitäten RNA-gesteuerter Ereignisse, insbesondere von small nucleolar RNAs und Pseudouridin-Prozessen. Demnach scheinen diese RNA-modifizierenden Netzwerke einen bisher unbekannten funktionalen und schützenden Einfluss auf das Zellüberleben nach ionisierender Bestrahlung zu haben. All diese schützenden Netzwerke mit ihren zeitspezifischen Interaktionen sind essentiell für das Zellüberleben nach Einwirkung von oxidativem Stress und zeigen ein komplexes aber im Einklang befindliches Zusammenspiel vieler Einzelkomponenten zu einem systemweit ablaufenden Programm.
Plasma secretion of acid sphingomyelinase is a hallmark of cellular stress response resulting in the formation of membrane embedded ceramide-enriched lipid rafts and the reorganization of receptor complexes. Consistently, decompartmentalization of ceramide formation from inert sphingomyelin has been associated with signaling events and regulation of the cellular phenotype. Herein, we addressed the question of whether the secretion of acid sphingomyelinase is involved in host response during sepsis. We found an exaggerated clinical course in mice genetically deficient in acid sphingomyelinase characterized by an increased bacterial burden, an increased phagocytotic activity, and a more pronounced cytokine storm. Moreover, on a functional level, leukocyte-endothelial interaction was found diminished in sphingomyelinase-deficient animals corresponding to a distinct leukocytes' phenotype with respect to rolling and sticking as well as expression of cellular surface proteins.(jlr) We conclude that hydrolysis of membrane-embedded sphingomyelin, triggered by circulating sphingomyelinase, plays a pivotal role in the first line of defense against invading microorganisms. This function might be essential during the early phase of infection leading to an adaptive response of remote cells and tissues.-Jbeily, N., I. Suckert, F. A. Gonnert, B. Acht, C. L. Bockmeyer, S. D. Grossmann, M. F. Blaess, A. Lueth, H.-P. Deigner, M. Bauer, and R. A. Claus. Hyperresponsiveness of mice deficient in plasma-secreted sphingomyelinase reveals its pivotal role in early phase of host response. J. Lipid Res. 2013. 54: 410-424.
Honey bees are important model organisms for neurobiology, because they display a large array of behaviors. To link behavior with individual gene function, quantitative polymerase chain reaction is frequently used. Comparing gene expression of different individuals requires data normalization using adequate reference genes. These should ideally be expressed stably throughout lifetime. Unfortunately, this is frequently not the case. We studied how well three commonly used reference genes are suited for this purpose and measured gene expression in the brains of honey bees differing in age and social role. Although rpl32 is used most frequently, it only remains stable in expression between newly emerged bees, nurse-aged bees, and pollen foragers but shows a peak at the age of 12 days. The genes gapdh and ef1 alpha-f1, in contrast, are expressed stably in the brain throughout all age groups except newly emerged bees. According to stability software, gapdh was expressed most stably, followed by rpl32 and ef1 alpha-f1.
Background
The forelimb-specific gene tbx5 is highly conserved and essential for the development of forelimbs in zebrafish, mice, and humans. Amongst birds, a single order, Dinornithiformes, comprising the extinct wingless moa of New Zealand, are unique in having no skeletal evidence of forelimb-like structures.
Results
To determine the sequence of tbx5 in moa, we used a range of PCR-based techniques on ancient DNA to retrieve all nine tbx5 exons and splice sites from the giant moa, Dinornis. Moa Tbx5 is identical to chicken Tbx5 in being able to activate the downstream promotors of fgf10 and ANF. In addition we show that missexpression of moa tbx5 in the hindlimb of chicken embryos results in the formation of forelimb features, suggesting that Tbx5 was fully functional in wingless moa. An alternatively spliced exon 1 for tbx5 that is expressed specifically in the forelimb region was shown to be almost identical between moa and ostrich, suggesting that, as well as being fully functional, tbx5 is likely to have been expressed normally in moa since divergence from their flighted ancestors, approximately 60 mya.
Conclusions
The results suggests that, as in mice, moa tbx5 is necessary for the induction of forelimbs, but is not sufficient for their outgrowth. Moa Tbx5 may have played an important role in the development of moa’s remnant forelimb girdle, and may be required for the formation of this structure. Our results further show that genetic changes affecting genes other than tbx5 must be responsible for the complete loss of forelimbs in moa.
The control of gene expression by transcriptional regulators and other types of functionally relevant DNA transactions such as chromatin remodeling and replication underlie a vast spectrum of biological processes in all organisms. DNA transactions require the controlled interaction of proteins with DNA sequence motifs which are often located in nucleosome-depleted regions (NDRs) of the chromatin. Formaldehyde-assisted isolation of regulatory elements (FAIRE) has been established as an easy-to-implement method for the isolation of NDRs from a number of eukaryotic organisms, and it has been successfully employed for the discovery of new regulatory segments in genomic DNA from, for example, yeast, Drosophila, and humans. Until today, however, FAIRE has only rarely been employed in plant research and currently no detailed FAIRE protocol for plants has been published. Here, we provide a step-by-step FAIRE protocol for NDR discovery in Arabidopsis thaliana. We demonstrate that NDRs isolated from plant chromatin are readily amenable to quantitative polymerase chain reaction and next-generation sequencing. Only minor modification of the FAIRE protocol will be needed to adapt it to other plants, thus facilitating the global inventory of regulatory regions across species.
Recent advances in high-throughput omics techniques render it possible to decode the function of genes by using the "guilt-by-association" principle on biologically meaningful clusters of gene expression data. However, the existing frameworks for biological evaluation of gene clusters are hindered by two bottleneck issues: (1) the choice for the number of clusters, and (2) the external measures which do not take in consideration the structure of the analyzed data and the ontology of the existing biological knowledge. Here, we address the identified bottlenecks by developing a novel framework that allows not only for biological evaluation of gene expression clusters based on existing structured knowledge, but also for prediction of putative gene functions. The proposed framework facilitates propagation of statistical significance at each of the following steps: (1) estimating the number of clusters, (2) evaluating the clusters in terms of novel external structural measures, (3) selecting an optimal clustering algorithm, and (4) predicting gene functions. The framework also includes a method for evaluation of gene clusters based on the structure of the employed ontology. Moreover, our method for obtaining a probabilistic range for the number of clusters is demonstrated valid on synthetic data and available gene expression profiles from Saccharomyces cerevisiae. Finally, we propose a network-based approach for gene function prediction which relies on the clustering of optimal score and the employed ontology. Our approach effectively predicts gene function on the Saccharomyces cerevisiae data set and is also employed to obtain putative gene functions for an Arabidopsis thaliana data set.