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:Stabilization ponds are a common treatment technology for wastewater generated by dairy industries. Large proportions of cheese whey are thrown into these ponds, creating an environmental problem because of the large volume produced and the high biological and chemical oxygen demands. Due to its composition, mainly lactose and proteins, it can be considered as a raw material for value-added products, through physicochemical or enzymatic treatments. ?-Galactosidases (EC 220.127.116.11) are lactose modifying enzymes that can transform lactose in free monomers, glucose and galactose, or galactooligosacharides. Here, the identification of novel genes encoding ?-galactosidases, identified via whole-genome shotgun sequencing of the metagenome of dairy industries stabilization ponds is reported. The genes were selected based on the conservation of catalytic domains, comparing against the CAZy database, and focusing on families with ?-galactosidases activity (GH1, GH2 and GH42). A total of 394 candidate genes were found, all belonging to bacterial species. From these candidates, 12 were selected to be cloned and expressed. A total of six enzymes were expressed, and five cleaved efficiently ortho-nitrophenyl-?-galactoside and lactose. The activity levels of one of these novel ?-galactosidase was higher than other enzymes reported from functional metagenomics screening and higher than the only enzyme reported from sequence-based metagenomics. A group of novel mesophilic ?-galactosidases from diary stabilization ponds' metagenomes was successfully identified, cloned and expressed. These novel enzymes provide alternatives for the production of value-added products from dairy industries' by-products.
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.