Вихретоковый анизотропный термоэлектрический первичный преобразователь лучистого потока

Представлена оригинальная конструкция первичного преобразователя лучистого потока, который может служить основой для создания приемника неселективного излучения с повышенной чувствительностью

Deletion of a Rare Fungal PKS CgPKS11 Promotes Chaetoglobosin A Biosynthesis, Yet Defers the Growth and Development of Chaetomium globosum

We previously reported that chaetoglobosin A (ChA) exhibits a great potential in the biocontrol of nematodes and pathogenic fungi. To improve the production of ChA, a CRISPR-Cas9 system was created and applied for eliminating potential competitive polyketide products. One of the polyketide synthase encoding genes, Cgpks11, which is putatively involved in the biosynthesis of chaetoglocin A, was disrupted. Cgpks11 deletion led to the overexpression of the CgcheA gene cluster, which is responsible for ChA biosynthesis, and a 1.6-fold increase of ChA. Transcription of pks-1, a melanin PKS, was simultaneously upregulated. Conversely, the transcription of genes for chaetoglocin A biosynthesis, e.g., CHGG_10646 and CHGG_10649, were significantly downregulated. The deletion also led to growth retardation and seriously impaired ascospore development. This study found a novel regulatory means on the biosynthesis of ChA by CgPKS11. CgPKS11 affects chaetoglobosin A biosynthesis, growth, and development in Chaetomium globosum

Regulation of the Gα-cAMP/PKA signaling pathway in cellulose utilization of Chaetomium globosum

Abstract Background The canonical heterotrimeric G protein-cAMP/PKA pathway regulates numerous cellular processes in filamentous fungi. Chaetomium globosum, a saprophytic fungus, is known for producing many secondary metabolites, including cytotoxic chaetoglobosin A (ChA), as well as abundant cellulase and xylanase. Results Here we report on the functional characterization of this signaling pathway in C. globosum. We blocked the pathway by knocking down the putative Gα-encoding gene gna1 (in the pG14 mutant). This led to impaired cellulase production and significantly decreased transcription of the major cellulase and xylanase genes. Almost all the glycohydrolase family genes involved in cellulose degradation were downregulated, including the major cellulase genes, cel7a, cel6a, egl1, and egl2. Importantly, the expression of transcription factors was also found to be regulated by gna1, especially Ace1, Clr1/2 and Hap2/3/5 complex. Additionally, carbon metabolic processes including the starch and sucrose metabolism pathway were substantially diminished, as evidenced by RNA-Seq profiling and quantitative reverse transcription (qRT)-PCR. Interestingly, these defects could be restored by simultaneous knockdown of the pkaR gene encoding the regulatory subunit of cAMP-dependent PKA (in the pGP6 mutant) or supplement of the cAMP analog, 8-Br-cAMP. Moreover, the Gα-cAMP/PKA pathway regulating cellulase production is modulated by environmental signals including carbon sources and light, in which VelB/VeA/LaeA complex and ENVOY probably work as downstream effectors. Conclusion These results revealed, for the first time, the positive role of the heterotrimeric Gα-cAMP/PKA pathway in the regulation of cellulase and xylanase utilization in C. globosum

Genome-Wide Identification of circRNAs in Pathogenic Basidiomycetous Yeast Cryptococcus neoformans Suggests Conserved circRNA Host Genes over Kingdoms

Circular RNAs (circRNAs), a novel class of ubiquitous and intriguing noncoding RNA, have been found in a number of eukaryotes but not yet basidiomycetes. In this study, we identified 73 circRNAs from 39.28 million filtered RNA reads from the basidiomycete Cryptococcus neoformans JEC21 using next-generation sequencing (NGS) and the bioinformatics tool circular RNA identification (CIRI). Furthermore, mapping of newly found circRNAs to the genome showed that 73.97% of the circRNAs originated from exonic regions, whereas 20.55% were from intergenic regions and 5.48% were from intronic regions. Enrichment analysis of circRNA host genes was conducted based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases. The results reveal that host genes are mainly responsible for primary metabolism and, interestingly, ribosomal protein production. Furthermore, we uncovered a high-level circRNA that was a transcript from the guanosine triphosphate (GTP)ase gene CNM01190 (gene ID: 3255052) in our yeast. Coincidentally, YPT5, CNM01190′s ortholog of the GTPase in Schizosaccharomyces pombe, protists, and humans, has already been proven to generate circRNAs. Additionally, overexpression of RNA debranching enzyme DBR1 had varied influence on the expression of circRNAs, indicating that multiple circRNA biosynthesis pathways exist in C. neoformans. Our study provides evidence for the existence of stable circRNAs in the opportunistic human pathogen C. neoformans and raises a question regarding their role related to pathogenesis in this yeast

Method of Estimating Degraded Forest Area: Cases from Dominant Tree Species from Guangdong and Tibet in China

Forest degradation has been considered as one of the main causes of climate change in recent years. The knowledge of estimating degraded forest areas without the application of remote sensing tools can be useful in finding solutions to resolve degradation problems through appropriate restoration methods. Using the existing knowledge through literature review and field-based primary information, we generated new knowledge by combining the information obtained from multi-criteria decision analyses with an analytic hierarchy process, and this was then used to estimate degraded forest area. Estimation involves determining forest degradation index (FDI) and degradation threshold. Continuous inventory data of permanent sample plots collected from degraded forests, consisting of various forest types divided by dominant tree species in the Guangdong province and Tibet autonomous region of China, were used for the purposes. We identified four different forest degradation levels through the determination and comprehensive evaluation of FDI. The degraded forest area with broad-leaved species as dominant tree species in the Guangdong province was estimated to be 83.3% of a total forest area of 24,037 km2. In the same province, the degraded forest area with eucalyptus as a dominant tree species was 59.5% of a total forest area of 18,665 km2. In the Tibet autonomous region, the degraded forest area with spruce as a dominant tree species was 99.1% of a total forest area of 17,614 km2, and with fir as a dominant tree species, the degraded area was 98.4% of a forest area of 12,103 km2. A sampling accuracy of forest areas with national forest inventory was about 95% in both provinces. Our study concludes that the FDI method used has a certain scientific rationality in estimating degraded forest area. The forest provides a variety of tangible and intangible goods and services for humans. Therefore, forest management should focus on the improvement of its overall productivity, which is only possible with improving forest site quality. One of the important steps to improve the quality of a forest site is to resolve its degradation issues. The presented method in this article will be useful in finding the solutions to forest degradation problems. This method, which does not need any remote sensing tool, is simple and can be easily applied for estimating any degraded forest area and developing effective forest restoration plans

The AMP-Activated Protein Kinase Homolog Snf1 Concerts Carbon Utilization, Conidia Production and the Biosynthesis of Secondary Metabolites in the Taxol-Producer Pestalotiopsis microspora

Highly conserved, the Snf1/AMPK is a central regulator of carbon metabolism and energy production in the eukaryotes. However, its function in filamentous fungi has not been well established. In this study, we reported functional characterization of Snf1/AMPK in the growth, development and secondary metabolism in the filamentous fungus Pestalotiopsis microspora. By deletion of the yeast SNF1 homolog, we found that it regulated the utilization of carbon sources, e.g., sucrose, demonstrating a conserved function of this kinase in filamentous fungus. Importantly, several novel functions of SNF1 were unraveled. For instance, the deletion strain displayed remarkable retardation in vegetative growth and pigmentation and produced a diminished number of conidia, even in the presence of the primary carbon source glucose. Deletion of the gene caused damages in the cell wall as shown by its hypersensitivities to Calcofluor white and Congo red, suggesting a critical role of Snf1 in maintaining cell wall integrity. Furthermore, the mutant strain Δsnf1 was hypersensitive to stress, e.g., osmotic pressure (1 M sorbitol), drug G418 and heat shock, though the mechanism remains to be illustrated. Significantly, disruption of the gene altered the production of secondary metabolites. By high-performance liquid chromatography (HPLC) profiling, we found that Δsnf1 barely produced secondary metabolites, e.g., the known product pestalotiollide B. This study suggests that Snf1 is a key regulator in filamentous fungus Pestalotiopsis microspora concerting carbon metabolism and the filamentous growth, conidiation, cell wall integrity, stress tolerance and the biosynthesis of secondary metabolites

Analysis of stable isotope assisted metabolomics data acquired by GC-MS.

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., 13C, 18O and/or 15N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 13C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform 13C-glucose and 13C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples

Analysis of stable isotope assisted metabolomics data acquired by GC-MS

Stable isotope assisted metabolomics (SIAM) measures the abundance levels of metabolites in a particular pathway using stable isotope tracers (e.g., 13C, 18O and/or 15N). We report a method termed signature ion approach for analysis of SIAM data acquired on a GC-MS system equipped with an electron ionization (EI) ion source. The signature ion is a fragment ion in EI mass spectrum of a derivatized metabolite that contains all atoms of the underivatized metabolite, except the hydrogen atoms lost during derivatization. In this approach, GC-MS data of metabolite standards were used to recognize the signature ion from the EI mass spectra acquired from stable isotope labeled samples, and a linear regression model was used to deconvolute the intensity of overlapping isotopologues. A mixture score function was also employed for cross-sample chromatographic peak list alignment to recognize the chromatographic peaks generated by the same metabolite in different samples, by simultaneously evaluating the similarity of retention time and EI mass spectrum of two chromatographic peaks. Analysis of a mixture of 16 13C-labeled and 16 unlabeled amino acids showed that the signature ion approach accurately identified and quantified all isotopologues. Analysis of polar metabolite extracts from cells respectively fed with uniform 13C-glucose and 13C-glutamine further demonstrated that this method can also be used to analyze the complex data acquired from biological samples