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To elucidate the number, structure, and regulation of genes involved in lignocellulosic cell wall attack, secretome and transcriptome analyses were performed on both wood decay fungi cultured for 5 days in media containing ball-milled aspen or glucose as the sole carbon source.

Viewed together with transcript profiles, P.

In contrast, under these same conditions, P. The two species display distinct expression patterns for oxidoreductase-encoding genes. Wood decay basidiomycetes, often categorized as white rot or brown rot fungi, are common inhabitants of forest litter, where they play a key role in carbon cycling White rot fungi degrade all components of plant cell walls, including cellulose, hemicellulose, and lignin.

Although unable to grow on lignin alone, these filamentous fungi have the unique ability to degrade a large proportion completely to CO2 and H2O. White rot fungi, such as Phanerochaete chrysosporium, also employ an array of extracellular hydrolases that attack cellulose and hemicellulose while simultaneously depolymerizing the lignin by oxidative mechanisms Brown rot fungi, exemplified by Postia placenta, employ a different approach.

Early in the decay process, they rapidly depolymerize cellulose but without concomitant weight loss. As decay progresses, brown rot fungi modify lignin extensively, but the products remain in situ as a polymeric residue 40 , Brown rot fungi are of considerable economic importance as the principal agents causing the destructive decay of wooden structures.

Although gross patterns of lignocellulose degradation differ substantially, the two decay types probably share at least some mechanisms, because molecular phylogeny, morphology, mating systems, and substrate preferences suggest that brown rot fungi have repeatedly evolved from white rot fungi Recent comparison of their genomes 36 indicated that the derivation of brown rot fungi is characterized largely by the contraction or loss of multiple gene families that are thought to be important in typical white rot, such as cellulases, lignin peroxidases LiPs , manganese peroxidases MnPs , copper radical oxidases CROs , cellobiose dehydrogenase CDH , and pyranoseoxidase POX.

This general pattern of simplification is consistent with the view that brown rot fungi have acquired novel mechanisms for cellulose depolymerization and lost key components of the white rot lignocellulose-degrading system Previous microarray studies provided quantitative transcript profiles for P. The transcriptome of P. These transcriptome investigations have been complemented by mass spectrometry identification of P. Considered together with numerous reports characterizing P.

In contrast, relatively little is known about the mechanism s of cellulose degradation by P. Analysis of the P. The genome completely lacks cellulose-binding domains, and the number of glycosyl hydrolases is relatively low, owing in part to the paucity of cellulases. One putative endoglucanase Ppl was shown to be expressed at high levels in medium containing microcrystalline cellulose, relative to levels in glucose-grown mycelia, but it seems unlikely that this endoglucanase alone can account for the efficient cellulose depolymerization by P.

Many investigations of the mechanisms employed by white rot and brown rot fungi have suggested the participation of low-molecular-weight oxidants.

To identify specific enzymes and provide insight into mechanisms of lignocellulose degradation, we report here the systematic comparisons of transcriptomes and secretomes of P. RNA for microarrays was obtained from P.

Aliquots of ml of medium in 2-liter Erlenmeyer flasks were inoculated with approximately P. Unless otherwise specified, cultures of P. Culture supernatants from all media were tested for lignin peroxidase 50 , manganese peroxidase 56 , glyoxal oxidase 31 , 32 , and cellobiose dehydrogenase 3 enzyme activities. In the case of P.

From a data set of 10, unique P. Seven gene models composed mostly of repetitive DNA were represented by only 2 to 11 mers. Complete design details for P. For each of the four combinations of species and medium BMA-P. Extraction buffer was prepared by combining 10 ml of mM sodium para-aminosalicylate Sigma-Aldrich, St.

Louis, MO with 10 ml of 56 mM sodium tri-isopropyl naphthalene sulfonate Sigma-Aldrich and placed on ice. The mixture was kept on ice and shaken just before use. Frozen fungal pellets were ground to a fine powder with liquid nitrogen in an acid-washed, prechilled mortar and pestle.

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The samples were vortexed vigorously and placed on ice until all samples were processed. The aqueous layer was removed to a new tube, and phenol-chloroform extractions were repeated until the interface between the aqueous and organic layers was clear. The final aqueous extractions were placed in clean tubes, to which was added a 0.

RNAs were eluted from the RNeasy spin columns using two spins, for a final volume of 2 ml. Three biological replicates per medium were used 12 separate arrays. Arrays were scanned on the Axon B scanner Molecular Dynamics , and data were extracted from the scanned image using NimbleScan v2. Analyses were based on three biological replicates per culture medium. Quantile normalization and robust multiarray averaging RMA 26 were applied to the entire data set. Scatter plots of results are shown in Fig.

S1 in the supplemental material. Gene-specific primers and amplicon information are listed in Table S3 of the supplemental material. Soluble extracellular protein was concentrated from culture filtrates as previously reported 53 , An in-house licensed Mascot search engine Matrix Science, London, United Kingdom identified peptides using the 10, and 17, gene models in the v2.

Reactions were terminated by acidification with 2. HPLC solvents were as follows: Dynamic exclusion was employed to increase dynamic range and maximize peptide identifications. Precursors remained on the exclusion list for 15 s.

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Sequest searches were done with a fragment ion mass tolerance of 0. Unless otherwise specified, protein identifications were accepted if they contained at least two identified peptides and if protein probabilities exceeded Detailed information for each protein can be directly accessed by appending the model number to the following strings: Alternatively, access can be obtained via search pages of the genome portals by entering protein ID numbers under Gene Models.

Microarray data accession numbers. The total number of unique P. Gene expression summary for P. Transcripts corresponding to P. Transcripts of 80 P. Taking these adjustments into account, P. The overall number of regulated P. However, variance between the replicated P. Of these, transcripts of 57 genes accumulated in BMA, while only 8 genes increased in the glucose medium. Scatter plots graphically illustrate transcript levels of all genes see Fig.

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Transcript levels in BMA medium were roughly correlated among putative orthologs in the two species correlation coefficient, 0. For example, of the above-mentioned P. Fourteen of these P. Focusing on the remaining minus 19 regulated P. Among the latter were genes potentially involved in aromatic compound metabolism phenylalanine ammonia lyase and aldehyde dehydrogenase and in iron homeostasis ferroxidase and iron permease.

High-scoring peptides corresponding to 67 P. The results were even more pronounced for P.

It is likely that the increased number of identified proteins was due to instrument sensitivity, but sample preparation also may have played some role. The identity and complete data for all proteins are presented in Tables S1 and S2 in the supplemental material. Regulated and highly expressed P. Among the 35 P. Peptides corresponding to 12 of these were identified in culture filtrates. The absence of CBH genes in P.

The latter gene likely encodes an endoxylanase, while the GH74 family is too functionally diverse to assign function.