Transcription profiling of different developmental stages of a novel natural isolate of the model organism Ashbya gossypii
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ABSTRACT:
ORGANISM(S): Ashbya gossypii
SUBMITTER: Riccarda Rischatsch
PROVIDER: E-MEXP-1955 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:In contrast to most filamentous fungi, A. gossypii displays <br>a very simple haploid life cycle. This is a transcriptome analysis <br>of A. gossypii at different developmental stages. Individual transcription profiles<br>were developed from spores to bipolar germlings (time<br>frame 9 h), from bipolar germlings to advanced mycelia<br>and to very fast growing hyphae (time frame 9h and 4 d, <br>respectively) and from very fast growing hyphae to <br>sporulating mycelium (time frame 2 d).
2011-01-31 | E-MEXP-1945 | biostudies-arrayexpress
Project description:The goal of this experiment concerned the comparison of genes controling the mating and filamentation pathways in S. cerevisiae and the filamentous fungus A. gossypii. Even though the A. gossypii genome encodes homologous genes of all components of these two pathways, there are major differences in the modes of growth beween the two organisms, and the potential for mating is unknown in A. gossypii. To shed light on functional conservation the two pathway including transcriptional regulation, a bioinfomatics analysis that looked into transcription factor conservation was carried out. To experimentally investigate regulatory network conservation, the two transcription factors AgTec1. AgSte12 and the repressor AgDig1.2 that act at the end of the pathways were deleted. Subsequent comparisons of mRNA levels of the deletion mutants with wild type allowed the identification of genes and gene groups which are regulated by the transcription factors or the repressor.
2011-01-31 | E-MEXP-1954 | biostudies-arrayexpress
Project description:Phenotypic plasticity, the ability of one genotype to express different phenotypes in response to changing environmental conditions, is one of the most common phenomena characterising the living world and is not only relevant for the ecology but also for the evolution of species. Daphnia, the waterflea, is a textbook example for predator induced phenotypic plastic defences including changes in life-history, behaviour and morphology. However, the analysis of molecular mechanisms underlying these inducible defences is still in its early stages.<br><br>We exposed Daphnia magna to chemical cues of the predator Triops cancriformis to identify key processes underlying plastic defensive trait formation. D. magna is known to develop an array of morphological changes in the presence of T. cancriformis including changes of carapace morphology and cuticle hardening. To get a more comprehensive idea of this phenomenon, we studied four different genotypes originating from habitats with different predation history, reaching from predator-free to temporary habitats containing T. cancriformis.<br><br>We analysed the morphologies as well as proteomes of predator-exposed and control animals. Three genotypes showed morphological changes when the predator was present. Using a high-throughput proteomics approach, we found 294 proteins which were significantly altered in their abundance after predator exposure in a general or genotype dependant manner. Proteins connected to genotype dependant responses were related to the cuticle, protein synthesis and calcium binding whereas the yolk protein vitellogenin increased in abundance in all genotypes, indicating their involvement in a more general response. Furthermore, genotype dependant responses at the proteome level correlated well with local adaptation to Triops predation.<br><br>Altogether, our study provides new insights concerning genotype dependant and general molecular processes involved in predator-induced phenotypic plasticity in D. magna.
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Project description:In honey bees (Apis mellifera), the reproductive queen produces a pheromonal signal that regulates many aspects of worker behavior and physiology and is critical for maintaining colony organization. Queen mandibular pheromone (QMP) inhibits worker reproduction, attracts workers from a short distance (retinue response), inhibits the rearing of new queens, modulates age-related division of labor and globally alters brain gene expression in worker bees. Interestingly, substantial variation in worker retinue responses to QMP has been found between colonies, but the molecular and physiological bases for variation in individual responses to the queen have not been characterized. Here, we demonstrate that individual retinue response is negatively correlated with traits associated with reproductive potential. Workers with low response to QMP have more ovarioles and higher levels of vitellogenin transcripts than workers with a high response to QMP, suggesting that workers with greater reproductive potential may be attempting to escape queen control. Retinue response appears to be associated with a suite of behavioral and physiological traits that may be pleiotropically linked. However, while these phenotypes are all correlated at the organismal level, the underlying brain expression patterns and gene networks associated with each trait are independent, suggesting that these phenotypes are uncoupled at the molecular level in adult bees. These studies provide insights into the ultimate and proximate causes of natural variation in pheromone response in honey bees.
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2004-12-31 | E-MEXP-155 | biostudies-arrayexpress
Project description:We applied a non targeted mass spectrometric assay (LCMSE), to quantify 55 abundant plasma proteins in specimens from 31 healthy volunteers. Quantitation was done by HI3 peptide measurement using a single internal standard to estimate protein concentrations. Results for 7 apolipoproteins were compared with those obtained using isotope labelled standards, while 12 proteins were compared to routine immunoassays. Blood samples were obtained from 31 healthy volunteers (17 males; 14 females) with a median age of 46 years and a range of 22-67 years. Total plasma protein concentration was assayed with a BCA-assay (20) according to the manufacturer’s protocol (Thermo). Samples were diluted tenfold in 0.1% Rapigest SF (Waters Corporation, Milford, MA), 50 mM ammonium bicarbonate and heated at 95° C for 15 min. Subsequently, plasma samples were reduced with 5 mM dithiothreitol (60° C, 30 min) and alkylated with 15 mM iodoacetamide (ambient temperature, dark, 30 min). Proteolytic digestion was performed with modified trypsin (gold grade, Promega, Madison WI) at 0.3 units/µg protein, (37° C, 20 hours) unless indicated otherwise. Following digestion, Rapigest SF was broken down by adding 1% trifluoroacetic acid (pH<2, 37 °C, 45 min). Peptide solutions were centrifuged (20,000 x g, 10 min) and supernatant was collected. Prior to analyses a MASSPREP protein digestion standard (Waters Corporation, ADH1 or ENO from Saccharomyces cerevisiae) was added for quantitation purposes. LC-MS analyses were performed using ~ 0.21 µg of the final plasma protein digest mixtures (384 times total dilution) unless indicated otherwise. LC separations of tryptic peptides were performed with a NanoAcquity system (Waters Corporation), coupled to a Synapt G2 quadrupole time of flight mass spectrometer (Waters Corporation, Manchester, UK). Accurate mass precursor and fragment ion LC-MS data were collected in data independent LCMSE mode of acquisition. Continuum LC-MS data were processed using ProteinLynx GlobalSERVER version 2.5 (PLGS 2.5, Waters Corporation). Parameter settings: digest reagent trypsin, allow 1 ‘missed cleavage’, search tolerances automatic, typically 5 ppm for precursor and 15 ppm for product ions, fixed modification cysteine carbamidomethylation, and variable modification methionine oxidation. Protein identifications were obtained searching the human SwissProt entries of an UniProt database (release 13.2). This database was modified to include N-terminal processing of proteins using protein maturation device software, with ADH1 and ENO1 of S. cerevisiae appended as internal standard to address technical variation and allow concentration determinations. Estimation of false-positive identification rates was done by searching a randomized version of the abovementioned human protein database generated within PLGS 2.5. Data were exported as csv-files for further, detailed analysis. Stringent criteria were applied for quantitation, protein identifications were only considered significant if reported in 14 or more samples. Protein false positive identification rates were estimated using the criteria mentioned above and no false positives were identified in these searches. DATASET: KC1-31: 31 healthy volunteers QC1-10: 10 times injection of a single sample to ascertain analytical variation over 9 days of measurements. 20120802_QC1-QC6: 6 pooled plasma samples worked up and analysed during a single day of measurements to ascertain Intra-assay variation. 20120427_S2,S4;20120525_S18,S19;20120626_S3,S4;20120802_QC7: 7 pooled plasma samples processed and analysed during 3 months of routine measurements to analyse Inter-assay variation 20130416_s1-s5: pooled plasma samples spiked with a QCONCATAMER for 11 apolipoproteins labelled by heavy Lysine and Arginine (+6.02 AMU) to quantify apolipoproteins by internal isotope labelled standard.
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