Ontology highlight
ABSTRACT:
PROVIDER: PRJNA694784 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR13573602_1.fastq.gz | Fastqsanger.gz | |||
| SRR13573602_2.fastq.gz | Fastqsanger.gz | |||
| SRR13573603_1.fastq.gz | Fastqsanger.gz | |||
| SRR13573603_2.fastq.gz | Fastqsanger.gz | |||
| SRR13573604_1.fastq.gz | Fastqsanger.gz |
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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: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:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs.
2014-01-15 | GSE54055 | GEO
Project description:To understand microbial community functional structures of activated sludge in wastewater treatment plants (WWTPs) and the effects of environmental factors on their structure, 12 activated sludge samples were collected from four WWTPs in Beijing. GeoChip 4.2 was used to determine the microbial functional genes involved in a variety of biogeochemical processes. The results showed that, for each gene category, such as egl, amyA, nir, ppx, dsrA sox and benAB, there were a number of microorganisms shared by all 12 samples, suggestive of the presence of a core microbial community in the activated sludge of four WWTPs. Variance partitioning analyses (VPA) showed that a total of 53% of microbial community variation can be explained by wastewater characteristics (25%) and operational parameters (23%), respectively. This study provided an overall picture of microbial community functional structures of activated sludge in WWTPs and discerned the linkages between microbial communities and environmental variables in WWTPs. Four full-scale wastewater treatment systems located in Beijing were investigated. Triplicate samples were collected in each site.
2014-01-15 | E-GEOD-54055 | biostudies-arrayexpress
Project description:Wastewater treatment plants use a variety of bioreactor types and configurations to remove organic matter and nutrients. Little is known regarding the effects of different configurations and within-plant immigration on microbial community dynamics. Previously, we found that the structure of ammonia-oxidizing bacterial (AOB) communities in a full-scale dispersed growth activated sludge bioreactor correlated strongly with levels of NO2- entering the reactor from an upstream trickling filter (Wells et al 2009). Here, to further examine this puzzling association, we profile within-plant microbial biogeography (spatial variation) and test the hypothesis that substantial microbial immigration occurs along a transect (raw influent, trickling filter biofilm, trickling filter effluent, and activated sludge) at the same full-scale wastewater treatment plant. AOB amoA gene abundance increased >30-fold between influent and trickling filter effluent concomitant with NO2- production, indicating unexpected growth and activity of AOB within the trickling filter. Nitrosomonas europaea was the dominant AOB phylotype in trickling filter biofilm and effluent, while a distinct ‘Nitrosomonas-like’ lineage dominated in activated sludge. Prior time series indicated that this ‘Nitrosomonas-like’ lineage was dominant when NO2- levels in the trickling filter effluent (i.e., activated sludge influent) were low, while N. europaea became dominant in the activated sludge when NO2- levels were high. This is consistent with the hypothesis that NO2- production may co-occur with biofilm sloughing, releasing N. europaea from the trickling filter into the activated sludge bioreactor. Phylogenetic microarray (PhyloChip) analyses revealed significant spatial variation in taxonomic diversity, including a large excess of methanogens in the trickling filter relative to activated sludge and attenuation of Enterobacteriaceae across the transect, and demonstrated transport of a highly diverse microbial community via the trickling filter effluent to the activated sludge bioreactor. Our results provide compelling evidence that substantial immigration between coupled process units occurs and may exert significant influence over microbial community dynamics within staged bioreactors.
2015-11-03 | GSE52079 | GEO
Project description:Current developments have led to a reconsidering of energy policy in many countries with the aim of increasing the share of renewable energies in the energy supply, where the anaerobic digestion (AD) of biomass to produce methane also plays an important role. To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies became more important. By applying combined metagenome and metaproteome, as well as metagenomically assembled genome (MAG)-centric analyses, it is possible to determine not only the functional potential but also the expressed functions of the entire microbial community and also individual MAGs. This approach was used in this study for the production-scale biogas plant 35 (BP35) consisting of three digesters which were operated differently regarding process temperatures, feedstocks and other process parameters. Different process conditions were hypothesized to result in specific microbiome adaptations and differentially abundant metabolic functions in the digesters. Based on metagenomic single-read analyses, several taxa residing in the three digesters of BP35 were shown to correlate with the corresponding substrates and temperatures. In particular, the genus Defluviitoga showed the strongest correlation to the process temperature and the genus Acetomicrobium featured a direct correlation to the concentartions of different acids including acetic acid. Analysis of the functional potential and expressed functions of the entire microbial community of the three digesters revealed that the genes and key enzymes relevant for the biogas process were present and also expressed. Differences between the abundances of certain genes and expressed enzymes could be related to the specific parameters of the corresponding digesters. Regarding the biogas related metabolic pathways, MAG-centric metagenomics and metaproteomics indicated the functional potential and the actual expressed metabolic functions of certain MAGs that are differentially abundant in the three digesters. These MAGs, belonging to the phylum Firmicutes, the class Bacilli and the orders Caldicoprobacterales and Bacteroidales showed a specific metabolic activity within the three digesters and have important roles in the hydrolysis, acidogenesis or acetogenesis of the anaerobic digestion process. An archaeal MAG assigned to the species Methanothermobacter wolfeii was the most abundant and highly active hydrogenotrophic methanogen in digester 3 featuring an operation temperature of 54 °C. Beside the MAGs that were differentially abundant in the three digesters, also MAGs which were more evenly distributed were analyzed. The most abundant and highly active MAG in all digesters belongs to the class Limnochordia and was shown to be ubiquitous in all three digesters and exhibit activity in a variety of pathways representing hydrolysis as well as the acido- and acetogenesis steps of the biogas process. Other MAGs assigned to the phylum Firmicutes, genus Acetomicrobium and the hydrogenotrophic species Methanoculleus thermohydrogenotrophicum were also shown to be more evenly distributed and active in the three digesters. Corresponding taxa appeared to be more resilient to the different process parameters of the three digesters, and therefore, may support a stable biogas process. Overall, the combined metagenome and metaproteome analysis of biogas digesters helps to gain deeper insights into the composition of the whole microbial community, biogas related pathways and their expression, which could contribute to an improved microbiome-based process management in the future.
2024-01-26 | PXD044571 | Pride
Project description:Population dynamics of methanogenic genera was investigated in pilot anaerobic digesters. Cattle manure and two-phase olive mill wastes were codigested at a 3:1 ratio in two reactors operated at 37 ï¾°C and 55 ï¾°C. Other two reactors were run with either residue at 37 ï¾°C. Sludge DNA extracted from samples taken from all four reactors on days 4, 14 and 28 of digestion was used for hybridisation with the AnaeroChip, an oligonucleotide microarray targeting those groups of methanogenic archaea that are commonly found under mesophilic and thermophilic conditions (Franke-Whittle et al. 2009, in press, doi:10.1016/j.mimet.2009.09.017).
2010-11-10 | E-MEXP-2453 | biostudies-arrayexpress
Project description:Background: Methane yield and biogas productivity of biogas plants depend on microbial community structure and functionality, substrate supply, and general process parameters. Little is known, however, about the correlations between microbial community function and the process parameters. To close this knowledge gap the microbial community of 40 industrial biogas plants was evaluated by a metaproteomics approach in this study. Results: Liquid chromatography coupled to tandem mass spectrometry (Elite Hybrid Ion Trap Orbitrap) enabled the identification of 3138 metaproteins belonging to 162 biological processes and 75 different taxonomic orders. Therefore, database searches were performed against UniProtKB/Swiss-Prot and several metagenome databases. Subsequent clustering and principal component analysis of these data allowed to identify four main clusters associated to mesophilic and thermophilic process conditions, upflow anaerobic sludge blanket reactors and sewage sludge as substrate. Observations confirm a previous phylogenetic study of the same biogas plant samples that was based on 16S-rRNA gene by De Vrieze et al. (2015) (De Vrieze, Saunders et al. 2015). Both studies described similar microbial key players of the biogas process, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. In addition, a correlation study and a Gephi graph network based on the correlations between the taxonomic orders and process parameters suggested the presence of various trophic interactions, e.g. syntrophic hydrogen transfer between Thermoanaerobacteriales and Methanomicrobiales. For the elucidation of the main biomass degradation pathways the most abundant 1% of metaproteins were assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN) and (iv) sludge retention time (SRT) on these pathways was investigated. For example high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation. Conclusion: This study shows the benefit of large-scale proteotyping of biogas plants, enabling the identification of general correlations between the process parameters and the microbial community structure and function. Changes in the level of microbial key functions or even in the microbial community type represent a valuable hint for process problems and disturbances.
2016-04-19 | PXD003526 | Pride