Ontology highlight
ABSTRACT:
PROVIDER: PRJNA655806 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12406759_1.fastq.gz | Fastqsanger.gz | |||
| SRR12406759_2.fastq.gz | Fastqsanger.gz | |||
| SRR12406760_1.fastq.gz | Fastqsanger.gz | |||
| SRR12406760_2.fastq.gz | Fastqsanger.gz | |||
| SRR12406761_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 6 |
Similar Datasets
Project description:Anaerobic digestion is a popular and effective microbial process for waste treatment. The performance of anaerobic digestion processes is contingent on the balance of the microbial food web in utilizing various substrates. Recently, co-digestion, i.e., supplementing the primary substrate with an organic-rich co-substrate has been exploited to improve waste treatment efficiency. Yet the potential effects of elevated organic loading on microbial functional gene community remains elusive. In this study, functional gene array (GeoChip 5.0) was used to assess the response of microbial community to the addition of poultry waste in anaerobic digesters treating dairy manure. Consistent with 16S rRNA gene sequences data, GeoChip data showed that microbial community compositions were significantly shifted in favor of copiotrophic populations by co-digestion, as taxa with higher rRNA gene copy number such as Bacilli were enriched. The acetoclastic methanogen Methanosarcina was also enriched, while Methanosaeta was unaltered but more abundant than Methanosarcina throughout the study period. The microbial functional diversity involved in anaerobic digestion were also increased under co-digestion.
2017-01-12 | GSE93419 | GEO
Project description:One of the most complex prokaryotic organelles are magnetosomes, which are formed by magnetotactic bacteria as sensors for navigation in the Earth’s magnetic field. In the alphaproteobacterium Magnetospirillum gryphiswaldense magnetosomes consist of chains of magnetite crystals (Fe3O4) that under suboxic conditions are biomineralized within membrane vesicles. To form such an intricate structure, the transcription of >30 specific structural genes clustered within the genomic magnetosome island (MAI) has to be coordinated with the expression of an as-yet unknown number of auxiliary genes encoding several generic metabolic functions. However, their global regulation and transcriptional organization in response to anoxic conditions most favorable for magnetite biomineralization are still unclear. Here, we compared transcriptional profiles of anaerobically grown magnetosome forming cells with those in which magnetosome biosynthesis has been suppressed by aerobic condition. Using whole transcriptome shotgun sequencing, we found that transcription of about 300 of the >4300 genes was significantly enhanced during magnetosome formation. The about 40 top upregulated genes are directly or indirectly linked to aerobic and anaerobic respiration (denitrification) or unknown functions. mam and mms gene clusters specifically controlling magnetosome biosynthesis were highly transcribed, but constitutively expressed irrespective of the growth condition. By Cappable-sequencing, we show that the transcriptional complexity of both the MAI and the entire genome decreased under anaerobic conditions optimal for magnetosome formation. In addition, predominant promoter structures were highly similar to sigma factor σ70 dependent promoters in other Alphaproteobacteria. Our transcriptome-wide analysis revealed that magnetite biomineralization relies on a complex interplay between generic metabolic processes such as aerobic and anaerobic respiration, cellular redox control, and the biosynthesis of specific magnetosome structures. In addition, we provide insights into global regulatory features that have remained uncharacterized in the widely studied model organism M. gryphiswaldense, including a comprehensive dataset of newly annotated transcription start sites and genome-wide operon detection as a community resource.
2022-10-19 | GSE197098 | GEO
Project description:Neural proliferation and differentiation fates of pluripotent stem cells are influenced by external natural forces. Despite the presence of biogenic magnetite nanoparticles in the central nervous system and constant exposure to Earth’s magnetic fields and other sources, there has been scant knowledge regarding the role of electromagnetic stimuli in neurogenesis. Moreover, the emerging application of electrical and magnetic stimulation to treat neurological disorders emphasizes the relevance of understanding the impact and mechanisms behind these stimuli. Here, the effects of magnetic nanoparticles (MNPs) contained in polymeric coatings and the static external magnetic field (EMF, 0.4 Tesla) were investigated on neural induction of murine embryonic stem cells (mESCs) and human induced pluripotent stem cells (hiPSCs) into induced dopaminergic neurons (iDA).
2021-12-17 | GSE190686 | GEO
Project description:The anaerobic digestion microbiomes has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and phenotypics, in their ability to reflect the full-scale anaerobic digestion microbiome. The phenotypic fingerprinting reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and phenotypic traits, yielded certain similar features yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, phenotypic fingerprinting is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.
2021-05-26 | PXD024788 | Pride
Project description:Microbial community of anaerobic digestion applied different shear stress
| PRJNA320789 | ENA
Project description:Whole transcriptome assessment of the Yersinia pseudotuberculosis strain YPIII grown under aerobic or anaerobic conditions to stationary phase. Y. pseudotuberculosis YPIII was grown at 25°C in LB medium supplemented with 10 g/l glucose and 0.2 M HEPES buffer under aeration or under anaerobic growth conditions (in a nitrogen atmosphere) on a rotary shaker. Total RNA was extracted using SV Total RNA Isolation System (Promega). The samples were treated with RNase-free DNase (Roche Applied Science) and the quality of the RNA was confirmed by the lack of PCR amplification of the hns gene and by using an Agilent 2100 Bioanalyzer.
2014-12-05 | E-GEOD-56476 | biostudies-arrayexpress
Project description:Whole transcriptome assessment of the Yersinia pseudotuberculosis strain YPIII grown under aerobic or anaerobic conditions to exponential phase. Y. pseudotuberculosis YPIII was grown at 25°C in LB medium supplemented with 10 g/l glucose and 0.2 M HEPES buffer under aeration or under anaerobic growth conditions (in a nitrogen atmosphere) on a rotary shaker. Total RNA was extracted using SV Total RNA Isolation System (Promega). The samples were treated with RNase-free DNase (Roche Applied Science) and the quality of the RNA was confirmed by the lack of PCR amplification of the hns gene and by using an Agilent 2100 Bioanalyzer.
2014-12-05 | E-GEOD-56475 | biostudies-arrayexpress