Project description:BACKGROUND:The production of biogas takes place under anaerobic conditions and involves microbial decomposition of organic matter. Most of the participating microbes are still unknown and non-cultivable. Accordingly, shotgun metagenome sequencing currently is the method of choice to obtain insights into community composition and the genetic repertoire. FINDINGS:Here, we report on the deeply sequenced metagenome and metatranscriptome of a complex biogas-producing microbial community from an agricultural production-scale biogas plant. We assembled the metagenome and, as an example application, show that we reconstructed most genes involved in the methane metabolism, a key pathway involving methanogenesis performed by methanogenic Archaea. This result indicates that there is sufficient sequencing coverage for most downstream analyses. CONCLUSIONS:Sequenced at least one order of magnitude deeper than previous studies, our metagenome data will enable new insights into community composition and the genetic potential of important community members. Moreover, mapping of transcripts to reconstructed genome sequences will enable the identification of active metabolic pathways in target organisms.
Project description:We sequenced the metagenome of a microbial community enriched under strictly anaerobic conditions from wastewater treatment plant-derived digester sludge. The metagenomic analysis of the enrichment revealed that Acetobacterium and methanogenic archaea belonged to the dominant prokaryotes, and genes encoding components of the Wood-Ljungdahl pathway were identified.
Project description:Reconstructing the genomes of microbial community members is key to the interpretation of shotgun metagenome samples. Genome binning programs deconvolute reads or assembled contigs of such samples into individual bins. However, assessing their quality is difficult due to the lack of evaluation software and standardized metrics. Here, we present Assessment of Metagenome BinnERs (AMBER), an evaluation package for the comparative assessment of genome reconstructions from metagenome benchmark datasets. It calculates the performance metrics and comparative visualizations used in the first benchmarking challenge of the initiative for the Critical Assessment of Metagenome Interpretation (CAMI). As an application, we show the outputs of AMBER for 11 binning programs on two CAMI benchmark datasets. AMBER is implemented in Python and available under the Apache 2.0 license on GitHub.
Project description:The genome and transcriptome sequences of the aquatic, rootless, and carnivorous plant Utricularia gibba L. (Lentibulariaceae), were recently determined. Traps are necessary for U. gibba because they help the plant to survive in nutrient-deprived environments. The U. gibba's traps (Ugt) are specialized structures that have been proposed to selectively filter microbial inhabitants. To determine whether the traps indeed have a microbiome that differs, in composition or abundance, from the microbiome in the surrounding environment, we used whole-genome shotgun (WGS) metagenomics to describe both the taxonomic and functional diversity of the Ugt microbiome. We collected U. gibba plants from their natural habitat and directly sequenced the metagenome of the Ugt microbiome and its surrounding water. The total predicted number of species in the Ugt was more than 1,100. Using pan-genome fragment recruitment analysis, we were able to identify to the species level of some key Ugt players, such as Pseudomonas monteilii. Functional analysis of the Ugt metagenome suggests that the trap microbiome plays an important role in nutrient scavenging and assimilation while complementing the hydrolytic functions of the plant.
Project description:Metagenomic libraries herald the era of magnifying the microbial world, tapping into the vast metabolic potential of uncultivated microbes, and enhancing the rate of discovery of novel genes and pathways. In this paper, we describe a method that facilitates the extraction of metagenomic DNA from activated sludge of an industrial wastewater treatment plant and its use in mining the metagenome via library construction. The efficiency of this method was demonstrated by the large representation of the bacterial genome in the constructed metagenomic libraries and by the functional clones obtained. The BAC library represented 95.6 times the bacterial genome, while, the pUC library represented 41.7 times the bacterial genome. Twelve clones in the BAC library demonstrated lipolytic activity, while four clones demonstrated dioxygenase activity. Four clones in pUC library tested positive for cellulase activity. This method, using FTA cards, not only can be used for library construction, but can also store the metagenome at room temperature.
Project description:Crude oil-polluted sites are a global threat, raising the demand for remediation worldwide. Here, we investigated a crude oil metagenome from a former borehole in Wietze, Germany, and reconstructed 42 metagenome-assembled genomes, many of which contained genes involved in crude oil degradation with a high potential for bioremediation purposes.
Project description:Human milk contains a diverse population of bacteria that likely influences colonization of the infant gastrointestinal tract. Recent studies, however, have been limited to characterization of this microbial community by 16S rRNA analysis. In the present study, a metagenomic approach using Illumina sequencing of a pooled milk sample (ten donors) was employed to determine the genera of bacteria and the types of bacterial open reading frames in human milk that may influence bacterial establishment and stability in this primal food matrix. The human milk metagenome was also compared to that of breast-fed and formula-fed infants' feces (n?=?5, each) and mothers' feces (n?=?3) at the phylum level and at a functional level using open reading frame abundance. Additionally, immune-modulatory bacterial-DNA motifs were also searched for within human milk.The bacterial community in human milk contained over 360 prokaryotic genera, with sequences aligning predominantly to the phyla of Proteobacteria (65%) and Firmicutes (34%), and the genera of Pseudomonas (61.1%), Staphylococcus (33.4%) and Streptococcus (0.5%). From assembled human milk-derived contigs, 30,128 open reading frames were annotated and assigned to functional categories. When compared to the metagenome of infants' and mothers' feces, the human milk metagenome was less diverse at the phylum level, and contained more open reading frames associated with nitrogen metabolism, membrane transport and stress response (P?<?0.05). The human milk metagenome also contained a similar occurrence of immune-modulatory DNA motifs to that of infants' and mothers' fecal metagenomes.Our results further expand the complexity of the human milk metagenome and enforce the benefits of human milk ingestion on the microbial colonization of the infant gut and immunity. Discovery of immune-modulatory motifs in the metagenome of human milk indicates more exhaustive analyses of the functionality of the human milk metagenome are warranted.
Project description:Urine culture and microscopy techniques are used to profile the bacterial species present in urinary tract infections. To gain insight into the urinary flora, we analyzed clinical laboratory features and the microbial metagenome of 121 clean-catch urine samples. 16S rDNA gene signatures were successfully obtained for 116 participants, while metagenome sequencing data was successfully generated for samples from 49 participants. Although 16S rDNA sequencing was more sensitive, metagenome sequencing allowed for a more comprehensive and unbiased representation of the microbial flora, including eukarya and viral pathogens, and of bacterial virulence factors. Urine samples positive by metagenome sequencing contained a plethora of bacterial (median 41 genera/sample), eukarya (median 2 species/sample) and viral sequences (median 3 viruses/sample). Genomic analyses suggested cases of infection with potential pathogens that are often missed during routine urine culture due to species specific growth requirements. While conventional microbiological methods are inadequate to identify a large diversity of microbial species that are present in urine, genomic approaches appear to more comprehensively and quantitatively describe the urinary microbiome.
Project description:The variety of metagenomes in current databases provides a rapidly growing source of information for comparative studies. However, the quantity and quality of supplementary metadata is still lagging behind. It is therefore important to be able to identify related metagenomes by means of the available sequence data alone. We have studied efficient sequence-based methods for large-scale identification of similar metagenomes within a database retrieval context. In a broad comparison of different profiling methods we found that vector-based distance measures are well-suitable for the detection of metagenomic neighbors. Our evaluation on more than 1700 publicly available metagenomes indicates that for a query metagenome from a particular habitat on average nine out of ten nearest neighbors represent the same habitat category independent of the utilized profiling method or distance measure. While for well-defined labels a neighborhood accuracy of 100% can be achieved, in general the neighbor detection is severely affected by a natural overlap of manually annotated categories. In addition, we present results of a novel visualization method that is able to reflect the similarity of metagenomes in a 2D scatter plot. The visualization method shows a similarly high accuracy in the reduced space as compared with the high-dimensional profile space. Our study suggests that for inspection of metagenome neighborhoods the profiling methods and distance measures can be chosen to provide a convenient interpretation of results in terms of the underlying features. Furthermore, supplementary metadata of metagenome samples in the future needs to comply with readily available ontologies for fine-grained and standardized annotation. To make profile-based k-nearest-neighbor search and the 2D-visualization of the metagenome universe available to the research community, we included the proposed methods in our CoMet-Universe server for comparative metagenome analysis.
Project description:Nucleo-cytoplasmic large DNA viruses are doubled stranded DNA viruses capable of infecting eukaryotic cells. Since the discovery of Mimivirus and Pandoravirus, there has been no doubt about their extraordinary features compared to "classic" viruses. Recently, we reported the expansion of the proposed family Pithoviridae, with the description of Cedratvirus and Orpheovirus, two new viruses related to Pithoviruses. Studying the major capsid protein of Orpheovirus, we detected a homologous sequence in a mine drainage metagenome. The in-depth exploration of this metagenome, using the MG-Digger program, enabled us to retrieve up to 10 contigs with clear evidence of viral sequences. Moreover, phylogenetic analyses further extended our screening with the discovery in another marine metagenome of a second virus closely related to Orpheovirus IHUMI-LCC2. This virus is a misidentified virus confused with and annotated as a Rickettsiales bacterium. It presents a partial genome size of about 170 kbp.