Ontology highlight
ABSTRACT:
PROVIDER: PRJNA612953 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11319435_1.fastq.gz | Fastqsanger.gz | |||
| SRR11319435_2.fastq.gz | Fastqsanger.gz | |||
| SRR11319436_1.fastq.gz | Fastqsanger.gz | |||
| SRR11319436_2.fastq.gz | Fastqsanger.gz | |||
| SRR11319437_1.fastq.gz | Fastqsanger.gz |
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Project description:Two-stage two-phase biogas reactor systems consisting each of one batch downflow hydrolysis reactor (HR, vol. 10 L), one process fluid storage tank (vol. 10 L), and one downstream upflow anaerobic filter reactor (AF, vol. 10 L), were operated at mesophilic (M, 37 °C) and thermophilic (T, 55 °C) temperatures and over a period of > 750 d (Figure 1, Additional file 1). For each reactor system and for each process temperature, two replicates were conducted in parallel, denominated further as biological replicates. Further process details were as previously published. Start-up of all fermenters were performed using liquid fermenter material from a biogas plant converting cattle manure in co-digestion with grass and maize silage and other biomass at varying concentrations and at mesophilic temperatures. Silage of perennial ryegrass (Lolium perenne L.) was digested as sole substrate in batches of varying amounts with retention times of 28 d (storage of bale silage at -20 °C, cutting length 3 cm, volatile substances (VS) 32 % of fresh mass (FM), total Kjeldahl nitrogen 7.6 g kgFM-1, NH4+-N 0.7 g kgFM-1, acetic acid 2.6 g kgFM-1, propionic acid < 0.04 g kgFM-1, lactic acid 2.6 g kgFM-1, ethanol 2.2 g kgFM-1, C/N ratio 19.3, chemical oxygen demand (COD) 357.7 g kgFM-1, analysis of chemical properties according to [6]. No spoilage was observed in the silage. Biogas yields were calculated as liters normalized to 0 °C and 1013 hPa (LN) per kilogram volatile substances (kgVS). For chemical analysis, samples were taken from the effluents of HR and AF. For sequencing of 16S rRNA gene amplicon libraries, microbial metagenomes, and microbial metatranscriptomes, samples were taken from the silage digestate in the HR digested for 2 d. At this time point, high AD rates were detected as indicated by the fast increase of volatile fatty acids (VFA), e.g., acetic acid. Sampling was performed at two different organic loading rates (OLR), i.e., batch-fermentation of 500 g (denominated as “low OLR”, samples MOLR500 and TOLR500) and 1,500 g silage (denominated as “increased OLR”, samples MOLR1500 and TOLR1500).
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Project description:In this study, microbial communities from triplicate leach-bed anaerobic bioreactors digesting grass were analysed. Each reactor comprised two microbial fractions, one immobilized on grass (biofilm) and the other in a planktonic state present in the leachate. Microbial communities from the two fractions were systematically investigated for community composition and function. This was carried out using DNA, RNA and protein co-extraction. The microbial structure of each fraction was examined using 16S rRNA deep sequencing, while the active members of the consortia were identified using the same approach on cDNA generated from co-extracted RNA samples. Microbial function was investigated using a metaproteomic workflow combining SDS-PAGE and LC-MS/MS analysis.
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Project description:The effect of nitrate reduction (anaerobic cultivation in the presence of heme, vitamin K2 and nitrate) was compared with anaerobic cultivation supplemented with citrate (Lactobacillus plantarum). The medium was chemically defined medium with mannitol as main carbon source Two-condition experiment, nitrate vs citrate reducing cells. Biological replicates: 4 nitrate reducing cultures, 4 citrate reducing cultures, independently grown and harvested. Two slides were used, each slide contained 8 Arrays. Citrate reducing cultures are called reactor 1-4, Nitrate reducing cultures are called reactor A-D
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Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
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