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.
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.
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.
Project description:Understanding microbial community diversity is thought to be crucial for improving process functioning and stabilities of wastewater treatment systems. However, current studies largely focus on taxonomic groups based on 16S rRNA, which are not necessarily linked to functioning, or a few selected functional genes. Here we launched a study to profile the overall functional genes of microbial communities in three full-scale wastewater treatment systems. Triplicate activated sludge samples from each system were analyzed using a high-throughput metagenomics tool named GeoChip 4.2, resulting in the detection of 38,507 to 40,647 functional genes. A high similarity of 75.5% to 79.7% shared genes was noted among the nine samples. Moreover, correlation analyses showed that the abundances of a wide array of functional genes were associated with system performances. For example, the abundances of overall nitrogen cycling genes had a strong correlation to total nitrogen (TN) removal rates (r = 0.7647, P < 0.01). The abundances of overall carbon cycling genes were moderately correlated with COD removal rates (r = 0.6515, P < 0.01). Lastly, we found that influent chemical oxygen demand (COD inf) and total phosphorus concentrations (TP inf), and dissolved oxygen (DO) concentrations were key environmental factors shaping the overall functional genes. Together, the results revealed vast functional gene diversity and some links between the functional gene compositions and microbe-mediated processes.
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples.
Project description:Samples of oil and production water were collected from five wells of the Qinghai Oilfield, China, and subjected to GeoChip hybridization experiments for microbial functional diversity profiling. Unexpectedly, a remarkable microbial diversity in oil samples, which was higher than that in the corresponding water samples, was observed, thus challenging previously believed assumptions about the microbial diversity in this ecosystem. Hierarchical clustering separated oil and water samples, thereby indicating distinct functional structures in the samples. Genes involved in the degradation of hydrocarbons, organic remediation, stress response, and carbon cycling were significantly abundant in crude oil, which is consistent with their important roles in residing in oil. Association analysis with environmental variables suggested that oil components comprising aromatic hydrocarbons, aliphatic hydrocarbons, and a polar fraction with nitrogen-, sulfur-, and oxygen-containing compounds were mainly influential on the structure of the microbial community. Furthermore, a comparison of microbial communities in oil samples indicated that the structures were depth/temperature-dependent. To our knowledge, this is the first thorough study to profile microbial functional diversity in crude oil samples. From the Qinghai Oilfield located in the Tibetan Plateau, northwest China, oil production mixtures were taken from four oil production wells (No. 813, 516, 48 and 27) and one injection well (No. 517) in the Yue-II block. The floating oil and water phases of the production mixtures were separated overnight by gravitational separation. Subsequently, the microbial community and the characteristics of the water solution (W813, W516, W48, and W27) and floating crude oil (O813, O516, O48, and O27) samples were analyzed. A similar analysis was performed with the injection water solution (W517).