New Hydrocarbon Degradation Pathways in the Microbial Metagenome from Brazilian Petroleum Reservoirs

PubMed Central

Sierra-García, Isabel Natalia; Correa Alvarez, Javier; Pantaroto de Vasconcellos, Suzan; Pereira de Souza, Anete; dos Santos Neto, Eugenio Vaz; de Oliveira, Valéria Maia

2014-01-01

Current knowledge of the microbial diversity and metabolic pathways involved in hydrocarbon degradation in petroleum reservoirs is still limited, mostly due to the difficulty in recovering the complex community from such an extreme environment. Metagenomics is a valuable tool to investigate the genetic and functional diversity of previously uncultured microorganisms in natural environments. Using a function-driven metagenomic approach, we investigated the metabolic abilities of microbial communities in oil reservoirs. Here, we describe novel functional metabolic pathways involved in the biodegradation of aromatic compounds in a metagenomic library obtained from an oil reservoir. Although many of the deduced proteins shared homology with known enzymes of different well-described aerobic and anaerobic catabolic pathways, the metagenomic fragments did not contain the complete clusters known to be involved in hydrocarbon degradation. Instead, the metagenomic fragments comprised genes belonging to different pathways, showing novel gene arrangements. These results reinforce the potential of the metagenomic approach for the identification and elucidation of new genes and pathways in poorly studied environments and contribute to a broader perspective on the hydrocarbon degradation processes in petroleum reservoirs. PMID:24587220

Phylogenetic convolutional neural networks in metagenomics.

PubMed

Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

2018-03-08

Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

A highly optimized grid deployment: the metagenomic analysis example.

PubMed

Aparicio, Gabriel; Blanquer, Ignacio; Hernández, Vicente

2008-01-01

Computational resources and computationally expensive processes are two topics that are not growing at the same ratio. The availability of large amounts of computing resources in Grid infrastructures does not mean that efficiency is not an important issue. It is necessary to analyze the whole process to improve partitioning and submission schemas, especially in the most critical experiments. This is the case of metagenomic analysis, and this text shows the work done in order to optimize a Grid deployment, which has led to a reduction of the response time and the failure rates. Metagenomic studies aim at processing samples of multiple specimens to extract the genes and proteins that belong to the different species. In many cases, the sequencing of the DNA of many microorganisms is hindered by the impossibility of growing significant samples of isolated specimens. Many bacteria cannot survive alone, and require the interaction with other organisms. In such cases, the information of the DNA available belongs to different kinds of organisms. One important stage in Metagenomic analysis consists on the extraction of fragments followed by the comparison and analysis of their function stage. By the comparison to existing chains, whose function is well known, fragments can be classified. This process is computationally intensive and requires of several iterations of alignment and phylogeny classification steps. Source samples reach several millions of sequences, which could reach up to thousands of nucleotides each. These sequences are compared to a selected part of the "Non-redundant" database which only implies the information from eukaryotic species. From this first analysis, a refining process is performed and alignment analysis is restarted from the results. This process implies several CPU years. The article describes and analyzes the difficulties to fragment, automate and check the above operations in current Grid production environments. This environment has been

Sparse distance-based learning for simultaneous multiclass classification and feature selection of metagenomic data.

PubMed

Liu, Zhenqiu; Hsiao, William; Cantarel, Brandi L; Drábek, Elliott Franco; Fraser-Liggett, Claire

2011-12-01

Direct sequencing of microbes in human ecosystems (the human microbiome) has complemented single genome cultivation and sequencing to understand and explore the impact of commensal microbes on human health. As sequencing technologies improve and costs decline, the sophistication of data has outgrown available computational methods. While several existing machine learning methods have been adapted for analyzing microbiome data recently, there is not yet an efficient and dedicated algorithm available for multiclass classification of human microbiota. By combining instance-based and model-based learning, we propose a novel sparse distance-based learning method for simultaneous class prediction and feature (variable or taxa, which is used interchangeably) selection from multiple treatment populations on the basis of 16S rRNA sequence count data. Our proposed method simultaneously minimizes the intraclass distance and maximizes the interclass distance with many fewer estimated parameters than other methods. It is very efficient for problems with small sample sizes and unbalanced classes, which are common in metagenomic studies. We implemented this method in a MATLAB toolbox called MetaDistance. We also propose several approaches for data normalization and variance stabilization transformation in MetaDistance. We validate this method on several real and simulated 16S rRNA datasets to show that it outperforms existing methods for classifying metagenomic data. This article is the first to address simultaneous multifeature selection and class prediction with metagenomic count data. The MATLAB toolbox is freely available online at http://metadistance.igs.umaryland.edu/. zliu@umm.edu Supplementary data are available at Bioinformatics online.

Resolving the Complexity of Human Skin Metagenomes Using Single-Molecule Sequencing

PubMed Central

Tsai, Yu-Chih; Deming, Clayton; Segre, Julia A.; Kong, Heidi H.; Korlach, Jonas

2016-01-01

ABSTRACT Deep metagenomic shotgun sequencing has emerged as a powerful tool to interrogate composition and function of complex microbial communities. Computational approaches to assemble genome fragments have been demonstrated to be an effective tool for de novo reconstruction of genomes from these communities. However, the resultant “genomes” are typically fragmented and incomplete due to the limited ability of short-read sequence data to assemble complex or low-coverage regions. Here, we use single-molecule, real-time (SMRT) sequencing to reconstruct a high-quality, closed genome of a previously uncharacterized Corynebacterium simulans and its companion bacteriophage from a skin metagenomic sample. Considerable improvement in assembly quality occurs in hybrid approaches incorporating short-read data, with even relatively small amounts of long-read data being sufficient to improve metagenome reconstruction. Using short-read data to evaluate strain variation of this C. simulans in its skin community at single-nucleotide resolution, we observed a dominant C. simulans strain with moderate allelic heterozygosity throughout the population. We demonstrate the utility of SMRT sequencing and hybrid approaches in metagenome quantitation, reconstruction, and annotation. PMID:26861018

Classifying short genomic fragments from novel lineages using composition and homology

PubMed Central

2011-01-01

Background The assignment of taxonomic attributions to DNA fragments recovered directly from the environment is a vital step in metagenomic data analysis. Assignments can be made using rank-specific classifiers, which assign reads to taxonomic labels from a predetermined level such as named species or strain, or rank-flexible classifiers, which choose an appropriate taxonomic rank for each sequence in a data set. The choice of rank typically depends on the optimal model for a given sequence and on the breadth of taxonomic groups seen in a set of close-to-optimal models. Homology-based (e.g., LCA) and composition-based (e.g., PhyloPythia, TACOA) rank-flexible classifiers have been proposed, but there is at present no hybrid approach that utilizes both homology and composition. Results We first develop a hybrid, rank-specific classifier based on BLAST and Naïve Bayes (NB) that has comparable accuracy and a faster running time than the current best approach, PhymmBL. By substituting LCA for BLAST or allowing the inclusion of suboptimal NB models, we obtain a rank-flexible classifier. This hybrid classifier outperforms established rank-flexible approaches on simulated metagenomic fragments of length 200 bp to 1000 bp and is able to assign taxonomic attributions to a subset of sequences with few misclassifications. We then demonstrate the performance of different classifiers on an enhanced biological phosphorous removal metagenome, illustrating the advantages of rank-flexible classifiers when representative genomes are absent from the set of reference genomes. Application to a glacier ice metagenome demonstrates that similar taxonomic profiles are obtained across a set of classifiers which are increasingly conservative in their classification. Conclusions Our NB-based classification scheme is faster than the current best composition-based algorithm, Phymm, while providing equally accurate predictions. The rank-flexible variant of NB, which we term ε-NB, is

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification

DOE PAGES

Wang, Felix; Quach, Tu-Thach; Wheeler, Jason; ...

2018-04-05

File fragment classification is an important step in the task of file carving in digital forensics. In file carving, files must be reconstructed based on their content as a result of their fragmented storage on disk or in memory. Existing methods for classification of file fragments typically use hand-engineered features such as byte histograms or entropy measures. In this paper, we propose an approach using sparse coding that enables automated feature extraction. Sparse coding, or sparse dictionary learning, is an unsupervised learning algorithm, and is capable of extracting features based simply on how well those features can be used tomore » reconstruct the original data. With respect to file fragments, we learn sparse dictionaries for n-grams, continuous sequences of bytes, of different sizes. These dictionaries may then be used to estimate n-gram frequencies for a given file fragment, but for significantly larger n-gram sizes than are typically found in existing methods which suffer from combinatorial explosion. To demonstrate the capability of our sparse coding approach, we used the resulting features to train standard classifiers such as support vector machines (SVMs) over multiple file types. Experimentally, we achieved significantly better classification results with respect to existing methods, especially when the features were used in supplement to existing hand-engineered features.« less

A Graph-Centric Approach for Metagenome-Guided Peptide and Protein Identification in Metaproteomics

PubMed Central

Tang, Haixu; Li, Sujun; Ye, Yuzhen

2016-01-01

Metaproteomic studies adopt the common bottom-up proteomics approach to investigate the protein composition and the dynamics of protein expression in microbial communities. When matched metagenomic and/or metatranscriptomic data of the microbial communities are available, metaproteomic data analyses often employ a metagenome-guided approach, in which complete or fragmental protein-coding genes are first directly predicted from metagenomic (and/or metatranscriptomic) sequences or from their assemblies, and the resulting protein sequences are then used as the reference database for peptide/protein identification from MS/MS spectra. This approach is often limited because protein coding genes predicted from metagenomes are incomplete and fragmental. In this paper, we present a graph-centric approach to improving metagenome-guided peptide and protein identification in metaproteomics. Our method exploits the de Bruijn graph structure reported by metagenome assembly algorithms to generate a comprehensive database of protein sequences encoded in the community. We tested our method using several public metaproteomic datasets with matched metagenomic and metatranscriptomic sequencing data acquired from complex microbial communities in a biological wastewater treatment plant. The results showed that many more peptides and proteins can be identified when assembly graphs were utilized, improving the characterization of the proteins expressed in the microbial communities. The additional proteins we identified contribute to the characterization of important pathways such as those involved in degradation of chemical hazards. Our tools are released as open-source software on github at https://github.com/COL-IU/Graph2Pro. PMID:27918579

Identification of fungi in shotgun metagenomics datasets

PubMed Central

Donovan, Paul D.; Gonzalez, Gabriel; Higgins, Desmond G.

2018-01-01

Metagenomics uses nucleic acid sequencing to characterize species diversity in different niches such as environmental biomes or the human microbiome. Most studies have used 16S rRNA amplicon sequencing to identify bacteria. However, the decreasing cost of sequencing has resulted in a gradual shift away from amplicon analyses and towards shotgun metagenomic sequencing. Shotgun metagenomic data can be used to identify a wide range of species, but have rarely been applied to fungal identification. Here, we develop a sequence classification pipeline, FindFungi, and use it to identify fungal sequences in public metagenome datasets. We focus primarily on animal metagenomes, especially those from pig and mouse microbiomes. We identified fungi in 39 of 70 datasets comprising 71 fungal species. At least 11 pathogenic species with zoonotic potential were identified, including Candida tropicalis. We identified Pseudogymnoascus species from 13 Antarctic soil samples initially analyzed for the presence of bacteria capable of degrading diesel oil. We also show that Candida tropicalis and Candida loboi are likely the same species. In addition, we identify several examples where contaminating DNA was erroneously included in fungal genome assemblies. PMID:29444186

Practical application of self-organizing maps to interrelate biodiversity and functional data in NGS-based metagenomics.

PubMed

Weber, Marc; Teeling, Hanno; Huang, Sixing; Waldmann, Jost; Kassabgy, Mariette; Fuchs, Bernhard M; Klindworth, Anna; Klockow, Christine; Wichels, Antje; Gerdts, Gunnar; Amann, Rudolf; Glöckner, Frank Oliver

2011-05-01

Next-generation sequencing (NGS) technologies have enabled the application of broad-scale sequencing in microbial biodiversity and metagenome studies. Biodiversity is usually targeted by classifying 16S ribosomal RNA genes, while metagenomic approaches target metabolic genes. However, both approaches remain isolated, as long as the taxonomic and functional information cannot be interrelated. Techniques like self-organizing maps (SOMs) have been applied to cluster metagenomes into taxon-specific bins in order to link biodiversity with functions, but have not been applied to broad-scale NGS-based metagenomics yet. Here, we provide a novel implementation, demonstrate its potential and practicability, and provide a web-based service for public usage. Evaluation with published data sets mimicking varyingly complex habitats resulted into classification specificities and sensitivities of close to 100% to above 90% from phylum to genus level for assemblies exceeding 8 kb for low and medium complexity data. When applied to five real-world metagenomes of medium complexity from direct pyrosequencing of marine subsurface waters, classifications of assemblies above 2.5 kb were in good agreement with fluorescence in situ hybridizations, indicating that biodiversity was mostly retained within the metagenomes, and confirming high classification specificities. This was validated by two protein-based classifications (PBCs) methods. SOMs were able to retrieve the relevant taxa down to the genus level, while surpassing PBCs in resolution. In order to make the approach accessible to a broad audience, we implemented a feature-rich web-based SOM application named TaxSOM, which is freely available at http://www.megx.net/toolbox/taxsom. TaxSOM can classify reads or assemblies exceeding 2.5 kb with high accuracy and thus assists in linking biodiversity and functions in metagenome studies, which is a precondition to study microbial ecology in a holistic fashion.

Practical application of self-organizing maps to interrelate biodiversity and functional data in NGS-based metagenomics

PubMed Central

Weber, Marc; Teeling, Hanno; Huang, Sixing; Waldmann, Jost; Kassabgy, Mariette; Fuchs, Bernhard M; Klindworth, Anna; Klockow, Christine; Wichels, Antje; Gerdts, Gunnar; Amann, Rudolf; Glöckner, Frank Oliver

2011-01-01

Next-generation sequencing (NGS) technologies have enabled the application of broad-scale sequencing in microbial biodiversity and metagenome studies. Biodiversity is usually targeted by classifying 16S ribosomal RNA genes, while metagenomic approaches target metabolic genes. However, both approaches remain isolated, as long as the taxonomic and functional information cannot be interrelated. Techniques like self-organizing maps (SOMs) have been applied to cluster metagenomes into taxon-specific bins in order to link biodiversity with functions, but have not been applied to broad-scale NGS-based metagenomics yet. Here, we provide a novel implementation, demonstrate its potential and practicability, and provide a web-based service for public usage. Evaluation with published data sets mimicking varyingly complex habitats resulted into classification specificities and sensitivities of close to 100% to above 90% from phylum to genus level for assemblies exceeding 8 kb for low and medium complexity data. When applied to five real-world metagenomes of medium complexity from direct pyrosequencing of marine subsurface waters, classifications of assemblies above 2.5 kb were in good agreement with fluorescence in situ hybridizations, indicating that biodiversity was mostly retained within the metagenomes, and confirming high classification specificities. This was validated by two protein-based classifications (PBCs) methods. SOMs were able to retrieve the relevant taxa down to the genus level, while surpassing PBCs in resolution. In order to make the approach accessible to a broad audience, we implemented a feature-rich web-based SOM application named TaxSOM, which is freely available at http://www.megx.net/toolbox/taxsom. TaxSOM can classify reads or assemblies exceeding 2.5 kb with high accuracy and thus assists in linking biodiversity and functions in metagenome studies, which is a precondition to study microbial ecology in a holistic fashion. PMID:21160538

IDENTIFICATION OF AVIAN-SPECIFIC FECAL METAGENOMIC SEQUENCES USING GENOME FRAGMENT ENRICHMENTS

EPA Science Inventory

Sequence analysis of microbial genomes has provided biologists the opportunity to compare genetic differences between closely related microorganisms. While random sequencing has also been used to study natural microbial communities, metagenomic comparisons via sequencing analysis...

Interactive metagenomic visualization in a Web browser.

PubMed

Ondov, Brian D; Bergman, Nicholas H; Phillippy, Adam M

2011-09-30

A critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables. Here we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools. Krona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: http://krona.sourceforge.net.

Interactive metagenomic visualization in a Web browser

PubMed Central

2011-01-01

Background A critical output of metagenomic studies is the estimation of abundances of taxonomical or functional groups. The inherent uncertainty in assignments to these groups makes it important to consider both their hierarchical contexts and their prediction confidence. The current tools for visualizing metagenomic data, however, omit or distort quantitative hierarchical relationships and lack the facility for displaying secondary variables. Results Here we present Krona, a new visualization tool that allows intuitive exploration of relative abundances and confidences within the complex hierarchies of metagenomic classifications. Krona combines a variant of radial, space-filling displays with parametric coloring and interactive polar-coordinate zooming. The HTML5 and JavaScript implementation enables fully interactive charts that can be explored with any modern Web browser, without the need for installed software or plug-ins. This Web-based architecture also allows each chart to be an independent document, making them easy to share via e-mail or post to a standard Web server. To illustrate Krona's utility, we describe its application to various metagenomic data sets and its compatibility with popular metagenomic analysis tools. Conclusions Krona is both a powerful metagenomic visualization tool and a demonstration of the potential of HTML5 for highly accessible bioinformatic visualizations. Its rich and interactive displays facilitate more informed interpretations of metagenomic analyses, while its implementation as a browser-based application makes it extremely portable and easily adopted into existing analysis packages. Both the Krona rendering code and conversion tools are freely available under a BSD open-source license, and available from: http://krona.sourceforge.net. PMID:21961884

Consensus statement: Virus taxonomy in the age of metagenomics.

PubMed

Simmonds, Peter; Adams, Mike J; Benkő, Mária; Breitbart, Mya; Brister, J Rodney; Carstens, Eric B; Davison, Andrew J; Delwart, Eric; Gorbalenya, Alexander E; Harrach, Balázs; Hull, Roger; King, Andrew M Q; Koonin, Eugene V; Krupovic, Mart; Kuhn, Jens H; Lefkowitz, Elliot J; Nibert, Max L; Orton, Richard; Roossinck, Marilyn J; Sabanadzovic, Sead; Sullivan, Matthew B; Suttle, Curtis A; Tesh, Robert B; van der Vlugt, René A; Varsani, Arvind; Zerbini, F Murilo

2017-03-01

The number and diversity of viral sequences that are identified in metagenomic data far exceeds that of experimentally characterized virus isolates. In a recent workshop, a panel of experts discussed the proposal that, with appropriate quality control, viruses that are known only from metagenomic data can, and should be, incorporated into the official classification scheme of the International Committee on Taxonomy of Viruses (ICTV). Although a taxonomy that is based on metagenomic sequence data alone represents a substantial departure from the traditional reliance on phenotypic properties, the development of a robust framework for sequence-based virus taxonomy is indispensable for the comprehensive characterization of the global virome. In this Consensus Statement article, we consider the rationale for why metagenomic sequence data should, and how it can, be incorporated into the ICTV taxonomy, and present proposals that have been endorsed by the Executive Committee of the ICTV.

MetaCAA: A clustering-aided methodology for efficient assembly of metagenomic datasets.

PubMed

Reddy, Rachamalla Maheedhar; Mohammed, Monzoorul Haque; Mande, Sharmila S

2014-01-01

A key challenge in analyzing metagenomics data pertains to assembly of sequenced DNA fragments (i.e. reads) originating from various microbes in a given environmental sample. Several existing methodologies can assemble reads originating from a single genome. However, these methodologies cannot be applied for efficient assembly of metagenomic sequence datasets. In this study, we present MetaCAA - a clustering-aided methodology which helps in improving the quality of metagenomic sequence assembly. MetaCAA initially groups sequences constituting a given metagenome into smaller clusters. Subsequently, sequences in each cluster are independently assembled using CAP3, an existing single genome assembly program. Contigs formed in each of the clusters along with the unassembled reads are then subjected to another round of assembly for generating the final set of contigs. Validation using simulated and real-world metagenomic datasets indicates that MetaCAA aids in improving the overall quality of assembly. A software implementation of MetaCAA is available at https://metagenomics.atc.tcs.com/MetaCAA. Copyright © 2014 Elsevier Inc. All rights reserved.

MetaStorm: A Public Resource for Customizable Metagenomics Annotation

PubMed Central

Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S.; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

2016-01-01

Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution. PMID:27632579

MetaStorm: A Public Resource for Customizable Metagenomics Annotation.

PubMed

Arango-Argoty, Gustavo; Singh, Gargi; Heath, Lenwood S; Pruden, Amy; Xiao, Weidong; Zhang, Liqing

2016-01-01

Metagenomics is a trending research area, calling for the need to analyze large quantities of data generated from next generation DNA sequencing technologies. The need to store, retrieve, analyze, share, and visualize such data challenges current online computational systems. Interpretation and annotation of specific information is especially a challenge for metagenomic data sets derived from environmental samples, because current annotation systems only offer broad classification of microbial diversity and function. Moreover, existing resources are not configured to readily address common questions relevant to environmental systems. Here we developed a new online user-friendly metagenomic analysis server called MetaStorm (http://bench.cs.vt.edu/MetaStorm/), which facilitates customization of computational analysis for metagenomic data sets. Users can upload their own reference databases to tailor the metagenomics annotation to focus on various taxonomic and functional gene markers of interest. MetaStorm offers two major analysis pipelines: an assembly-based annotation pipeline and the standard read annotation pipeline used by existing web servers. These pipelines can be selected individually or together. Overall, MetaStorm provides enhanced interactive visualization to allow researchers to explore and manipulate taxonomy and functional annotation at various levels of resolution.

HPMCD: the database of human microbial communities from metagenomic datasets and microbial reference genomes.

PubMed

Forster, Samuel C; Browne, Hilary P; Kumar, Nitin; Hunt, Martin; Denise, Hubert; Mitchell, Alex; Finn, Robert D; Lawley, Trevor D

2016-01-04

The Human Pan-Microbe Communities (HPMC) database (http://www.hpmcd.org/) provides a manually curated, searchable, metagenomic resource to facilitate investigation of human gastrointestinal microbiota. Over the past decade, the application of metagenome sequencing to elucidate the microbial composition and functional capacity present in the human microbiome has revolutionized many concepts in our basic biology. When sufficient high quality reference genomes are available, whole genome metagenomic sequencing can provide direct biological insights and high-resolution classification. The HPMC database provides species level, standardized phylogenetic classification of over 1800 human gastrointestinal metagenomic samples. This is achieved by combining a manually curated list of bacterial genomes from human faecal samples with over 21000 additional reference genomes representing bacteria, viruses, archaea and fungi with manually curated species classification and enhanced sample metadata annotation. A user-friendly, web-based interface provides the ability to search for (i) microbial groups associated with health or disease state, (ii) health or disease states and community structure associated with a microbial group, (iii) the enrichment of a microbial gene or sequence and (iv) enrichment of a functional annotation. The HPMC database enables detailed analysis of human microbial communities and supports research from basic microbiology and immunology to therapeutic development in human health and disease. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Studying long 16S rDNA sequences with ultrafast-metagenomic sequence classification using exact alignments (Kraken).

PubMed

Valenzuela-González, Fabiola; Martínez-Porchas, Marcel; Villalpando-Canchola, Enrique; Vargas-Albores, Francisco

2016-03-01

Ultrafast-metagenomic sequence classification using exact alignments (Kraken) is a novel approach to classify 16S rDNA sequences. The classifier is based on mapping short sequences to the lowest ancestor and performing alignments to form subtrees with specific weights in each taxon node. This study aimed to evaluate the classification performance of Kraken with long 16S rDNA random environmental sequences produced by cloning and then Sanger sequenced. A total of 480 clones were isolated and expanded, and 264 of these clones formed contigs (1352 ± 153 bp). The same sequences were analyzed using the Ribosomal Database Project (RDP) classifier. Deeper classification performance was achieved by Kraken than by the RDP: 73% of the contigs were classified up to the species or variety levels, whereas 67% of these contigs were classified no further than the genus level by the RDP. The results also demonstrated that unassembled sequences analyzed by Kraken provide similar or inclusively deeper information. Moreover, sequences that did not form contigs, which are usually discarded by other programs, provided meaningful information when analyzed by Kraken. Finally, it appears that the assembly step for Sanger sequences can be eliminated when using Kraken. Kraken cumulates the information of both sequence senses, providing additional elements for the classification. In conclusion, the results demonstrate that Kraken is an excellent choice for use in the taxonomic assignment of sequences obtained by Sanger sequencing or based on third generation sequencing, of which the main goal is to generate larger sequences. Copyright © 2016 Elsevier B.V. All rights reserved.

Does semi-automatic bone-fragment segmentation improve the reproducibility of the Letournel acetabular fracture classification?

PubMed

Boudissa, M; Orfeuvre, B; Chabanas, M; Tonetti, J

2017-09-01

The Letournel classification of acetabular fracture shows poor reproducibility in inexperienced observers, despite the introduction of 3D imaging. We therefore developed a method of semi-automatic segmentation based on CT data. The present prospective study aimed to assess: (1) whether semi-automatic bone-fragment segmentation increased the rate of correct classification; (2) if so, in which fracture types; and (3) feasibility using the open-source itksnap 3.0 software package without incurring extra cost for users. Semi-automatic segmentation of acetabular fractures significantly increases the rate of correct classification by orthopedic surgery residents. Twelve orthopedic surgery residents classified 23 acetabular fractures. Six used conventional 3D reconstructions provided by the center's radiology department (conventional group) and 6 others used reconstructions obtained by semi-automatic segmentation using the open-source itksnap 3.0 software package (segmentation group). Bone fragments were identified by specific colors. Correct classification rates were compared between groups on Chi 2 test. Assessment was repeated 2 weeks later, to determine intra-observer reproducibility. Correct classification rates were significantly higher in the "segmentation" group: 114/138 (83%) versus 71/138 (52%); P<0.0001. The difference was greater for simple (36/36 (100%) versus 17/36 (47%); P<0.0001) than complex fractures (79/102 (77%) versus 54/102 (53%); P=0.0004). Mean segmentation time per fracture was 27±3min [range, 21-35min]. The segmentation group showed excellent intra-observer correlation coefficients, overall (ICC=0.88), and for simple (ICC=0.92) and complex fractures (ICC=0.84). Semi-automatic segmentation, identifying the various bone fragments, was effective in increasing the rate of correct acetabular fracture classification on the Letournel system by orthopedic surgery residents. It may be considered for routine use in education and training. III: prospective

RIEMS: a software pipeline for sensitive and comprehensive taxonomic classification of reads from metagenomics datasets.

PubMed

Scheuch, Matthias; Höper, Dirk; Beer, Martin

2015-03-03

Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck. To overcome the bottleneck of data analysis, we developed an automated computational workflow called RIEMS - Reliable Information Extraction from Metagenomic Sequence datasets. RIEMS assigns every individual read sequence within a dataset taxonomically by cascading different sequence analyses with decreasing stringency of the assignments using various software applications. After completion of the analyses, the results are summarised in a clearly structured result protocol organised taxonomically. The high accuracy and performance of RIEMS analyses were proven in comparison with other tools for metagenomics data analysis using simulated sequencing read datasets. RIEMS has the potential to fill the gap that still exists with regard to data analysis for metagenomics studies. The usefulness and power of RIEMS for the analysis of genuine sequencing datasets was demonstrated with an early version of RIEMS in 2011 when it was used to detect the orthobunyavirus sequences leading to the discovery of Schmallenberg virus.

Metavir 2: new tools for viral metagenome comparison and assembled virome analysis

PubMed Central

2014-01-01

Background Metagenomics, based on culture-independent sequencing, is a well-fitted approach to provide insights into the composition, structure and dynamics of environmental viral communities. Following recent advances in sequencing technologies, new challenges arise for existing bioinformatic tools dedicated to viral metagenome (i.e. virome) analysis as (i) the number of viromes is rapidly growing and (ii) large genomic fragments can now be obtained by assembling the huge amount of sequence data generated for each metagenome. Results To face these challenges, a new version of Metavir was developed. First, all Metavir tools have been adapted to support comparative analysis of viromes in order to improve the analysis of multiple datasets. In addition to the sequence comparison previously provided, viromes can now be compared through their k-mer frequencies, their taxonomic compositions, recruitment plots and phylogenetic trees containing sequences from different datasets. Second, a new section has been specifically designed to handle assembled viromes made of thousands of large genomic fragments (i.e. contigs). This section includes an annotation pipeline for uploaded viral contigs (gene prediction, similarity search against reference viral genomes and protein domains) and an extensive comparison between contigs and reference genomes. Contigs and their annotations can be explored on the website through specifically developed dynamic genomic maps and interactive networks. Conclusions The new features of Metavir 2 allow users to explore and analyze viromes composed of raw reads or assembled fragments through a set of adapted tools and a user-friendly interface. PMID:24646187

Optimizing and evaluating the reconstruction of Metagenome-assembled microbial genomes.

PubMed

Papudeshi, Bhavya; Haggerty, J Matthew; Doane, Michael; Morris, Megan M; Walsh, Kevin; Beattie, Douglas T; Pande, Dnyanada; Zaeri, Parisa; Silva, Genivaldo G Z; Thompson, Fabiano; Edwards, Robert A; Dinsdale, Elizabeth A

2017-11-28

Microbiome/host interactions describe characteristics that affect the host's health. Shotgun metagenomics includes sequencing a random subset of the microbiome to analyze its taxonomic and metabolic potential. Reconstruction of DNA fragments into genomes from metagenomes (called metagenome-assembled genomes) assigns unknown fragments to taxa/function and facilitates discovery of novel organisms. Genome reconstruction incorporates sequence assembly and sorting of assembled sequences into bins, characteristic of a genome. However, the microbial community composition, including taxonomic and phylogenetic diversity may influence genome reconstruction. We determine the optimal reconstruction method for four microbiome projects that had variable sequencing platforms (IonTorrent and Illumina), diversity (high or low), and environment (coral reefs and kelp forests), using a set of parameters to select for optimal assembly and binning tools. We tested the effects of the assembly and binning processes on population genome reconstruction using 105 marine metagenomes from 4 projects. Reconstructed genomes were obtained from each project using 3 assemblers (IDBA, MetaVelvet, and SPAdes) and 2 binning tools (GroopM and MetaBat). We assessed the efficiency of assemblers using statistics that including contig continuity and contig chimerism and the effectiveness of binning tools using genome completeness and taxonomic identification. We concluded that SPAdes, assembled more contigs (143,718 ± 124 contigs) of longer length (N50 = 1632 ± 108 bp), and incorporated the most sequences (sequences-assembled = 19.65%). The microbial richness and evenness were maintained across the assembly, suggesting low contig chimeras. SPAdes assembly was responsive to the biological and technological variations within the project, compared with other assemblers. Among binning tools, we conclude that MetaBat produced bins with less variation in GC content (average standard deviation: 1

Anatomy and classification of the posterior tibial fragment in ankle fractures.

PubMed

Bartoníček, Jan; Rammelt, Stefan; Kostlivý, Karel; Vaněček, Václav; Klika, Daniel; Trešl, Ivo

2015-04-01

The aim of this study was to analyze the pathoanatomy of the posterior fragment on the basis of a comprehensive CT examination, including 3D reconstructions, in a large patient cohort. One hundred and forty one consecutive individuals with an ankle fracture or fracture-dislocation of types Weber B or Weber C and evidence of a posterior tibial fragment in standard radiographs were included in the study. The mean patient age was 49 years (range 19-83 years). The exclusion criteria were patients below 18 years of age, inability to provide written consent, fractures of the tibial pilon, posttraumatic arthritis and pre-existing deformities. In all patients, post-injury radiographs were obtained in anteroposterior, mortise and lateral views. All patients underwent CT scanning in transverse, sagittal and frontal planes. 3D CT reconstruction was performed in 91 patients. We were able to classify 137 cases into one of the following four types with constant pathoanatomic features: type 1: extraincisural fragment with an intact fibular notch, type 2: posterolateral fragment extending into the fibular notch, type 3: posteromedial two-part fragment involving the medial malleolus, type 4: large posterolateral triangular fragment. In the 4 cases it was not possible to classify the type of the posterior tibial fragment. These were collectively termed type 5 (irregular, osteoporotic fragments). It is impossible to assess the shape and size of the posterior malleolar fragment, involvement of the fibular notch, or the medial malleolus, on the basis of plain radiographs. The system that we propose for classification of fractures of the posterior malleolus is based on CT examination and takes into account the size, shape and location of the fragment, stability of the tibio-talar joint and the integrity of the fibular notch. It may be a useful indication for surgery and defining the most useful approach to these injuries.

IDENTIFICATION OF CHICKEN-SPECIFIC FECAL MICROBIAL SEQUENCES USING A METAGENOMIC APPROACH

EPA Science Inventory

In this study, we applied a genome fragment enrichment (GFE) method to select for genomic regions that differ between different fecal metagenomes. Competitive DNA hybridizations were performed between chicken fecal DNA and pig fecal DNA (C-P) and between chicken fecal DNA and an ...

Ensemble-based classification approach for micro-RNA mining applied on diverse metagenomic sequences.

PubMed

ElGokhy, Sherin M; ElHefnawi, Mahmoud; Shoukry, Amin

2014-05-06

MicroRNAs (miRNAs) are endogenous ∼22 nt RNAs that are identified in many species as powerful regulators of gene expressions. Experimental identification of miRNAs is still slow since miRNAs are difficult to isolate by cloning due to their low expression, low stability, tissue specificity and the high cost of the cloning procedure. Thus, computational identification of miRNAs from genomic sequences provide a valuable complement to cloning. Different approaches for identification of miRNAs have been proposed based on homology, thermodynamic parameters, and cross-species comparisons. The present paper focuses on the integration of miRNA classifiers in a meta-classifier and the identification of miRNAs from metagenomic sequences collected from different environments. An ensemble of classifiers is proposed for miRNA hairpin prediction based on four well-known classifiers (Triplet SVM, Mipred, Virgo and EumiR), with non-identical features, and which have been trained on different data. Their decisions are combined using a single hidden layer neural network to increase the accuracy of the predictions. Our ensemble classifier achieved 89.3% accuracy, 82.2% f-measure, 74% sensitivity, 97% specificity, 92.5% precision and 88.2% negative predictive value when tested on real miRNA and pseudo sequence data. The area under the receiver operating characteristic curve of our classifier is 0.9 which represents a high performance index.The proposed classifier yields a significant performance improvement relative to Triplet-SVM, Virgo and EumiR and a minor refinement over MiPred.The developed ensemble classifier is used for miRNA prediction in mine drainage, groundwater and marine metagenomic sequences downloaded from the NCBI sequence reed archive. By consulting the miRBase repository, 179 miRNAs have been identified as highly probable miRNAs. Our new approach could thus be used for mining metagenomic sequences and finding new and homologous miRNAs. The paper investigates a

Functional metagenomics to decipher food-microbe-host crosstalk.

PubMed

Larraufie, Pierre; de Wouters, Tomas; Potocki-Veronese, Gabrielle; Blottière, Hervé M; Doré, Joël

2015-02-01

The recent developments of metagenomics permit an extremely high-resolution molecular scan of the intestinal microbiota giving new insights and opening perspectives for clinical applications. Beyond the unprecedented vision of the intestinal microbiota given by large-scale quantitative metagenomics studies, such as the EU MetaHIT project, functional metagenomics tools allow the exploration of fine interactions between food constituents, microbiota and host, leading to the identification of signals and intimate mechanisms of crosstalk, especially between bacteria and human cells. Cloning of large genome fragments, either from complex intestinal communities or from selected bacteria, allows the screening of these biological resources for bioactivity towards complex plant polymers or functional food such as prebiotics. This permitted identification of novel carbohydrate-active enzyme families involved in dietary fibre and host glycan breakdown, and highlighted unsuspected bacterial players at the top of the intestinal microbial food chain. Similarly, exposure of fractions from genomic and metagenomic clones onto human cells engineered with reporter systems to track modulation of immune response, cell proliferation or cell metabolism has allowed the identification of bioactive clones modulating key cell signalling pathways or the induction of specific genes. This opens the possibility to decipher mechanisms by which commensal bacteria or candidate probiotics can modulate the activity of cells in the intestinal epithelium or even in distal organs such as the liver, adipose tissue or the brain. Hence, in spite of our inability to culture many of the dominant microbes of the human intestine, functional metagenomics open a new window for the exploration of food-microbe-host crosstalk.

A novel genome signature based on inter-nucleotide distances profiles for visualization of metagenomic data

NASA Astrophysics Data System (ADS)

Xie, Xian-Hua; Yu, Zu-Guo; Ma, Yuan-Lin; Han, Guo-Sheng; Anh, Vo

2017-09-01

There has been a growing interest in visualization of metagenomic data. The present study focuses on the visualization of metagenomic data using inter-nucleotide distances profile. We first convert the fragment sequences into inter-nucleotide distances profiles. Then we analyze these profiles by principal component analysis. Finally the principal components are used to obtain the 2-D scattered plot according to their source of species. We name our method as inter-nucleotide distances profiles (INP) method. Our method is evaluated on three benchmark data sets used in previous published papers. Our results demonstrate that the INP method is good, alternative and efficient for visualization of metagenomic data.

Reconstructing the Genomic Content of Microbiome Taxa through Shotgun Metagenomic Deconvolution

PubMed Central

Carr, Rogan; Shen-Orr, Shai S.; Borenstein, Elhanan

2013-01-01

Metagenomics has transformed our understanding of the microbial world, allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples. However, associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge. Existing binning methods, based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa. Here, we introduce a novel computational framework, integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members. This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction. An implementation of this framework is available at http://elbo.gs.washington.edu/software.html. We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components. We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples. We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes. We finally apply metagenomic deconvolution to samples from the Human Microbiome Project, successfully reconstructing genus-level genomic content of various microbial genera, based solely on variation in gene count. These reconstructed genera are shown to correctly capture genus-specific properties. With the accumulation of metagenomic

Accessing the Soil Metagenome for Studies of Microbial Diversity▿ †

PubMed Central

Delmont, Tom O.; Robe, Patrick; Cecillon, Sébastien; Clark, Ian M.; Constancias, Florentin; Simonet, Pascal; Hirsch, Penny R.; Vogel, Timothy M.

2011-01-01

Soil microbial communities contain the highest level of prokaryotic diversity of any environment, and metagenomic approaches involving the extraction of DNA from soil can improve our access to these communities. Most analyses of soil biodiversity and function assume that the DNA extracted represents the microbial community in the soil, but subsequent interpretations are limited by the DNA recovered from the soil. Unfortunately, extraction methods do not provide a uniform and unbiased subsample of metagenomic DNA, and as a consequence, accurate species distributions cannot be determined. Moreover, any bias will propagate errors in estimations of overall microbial diversity and may exclude some microbial classes from study and exploitation. To improve metagenomic approaches, investigate DNA extraction biases, and provide tools for assessing the relative abundances of different groups, we explored the biodiversity of the accessible community DNA by fractioning the metagenomic DNA as a function of (i) vertical soil sampling, (ii) density gradients (cell separation), (iii) cell lysis stringency, and (iv) DNA fragment size distribution. Each fraction had a unique genetic diversity, with different predominant and rare species (based on ribosomal intergenic spacer analysis [RISA] fingerprinting and phylochips). All fractions contributed to the number of bacterial groups uncovered in the metagenome, thus increasing the DNA pool for further applications. Indeed, we were able to access a more genetically diverse proportion of the metagenome (a gain of more than 80% compared to the best single extraction method), limit the predominance of a few genomes, and increase the species richness per sequencing effort. This work stresses the difference between extracted DNA pools and the currently inaccessible complete soil metagenome. PMID:21183646

A function-based screen for seeking RubisCO active clones from metagenomes: novel enzymes influencing RubisCO activity.

PubMed

Böhnke, Stefanie; Perner, Mirjam

2015-03-01

Ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO) is a key enzyme of the Calvin cycle, which is responsible for most of Earth's primary production. Although research on RubisCO genes and enzymes in plants, cyanobacteria and bacteria has been ongoing for years, still little is understood about its regulation and activation in bacteria. Even more so, hardly any information exists about the function of metagenomic RubisCOs and the role of the enzymes encoded on the flanking DNA owing to the lack of available function-based screens for seeking active RubisCOs from the environment. Here we present the first solely activity-based approach for identifying RubisCO active fosmid clones from a metagenomic library. We constructed a metagenomic library from hydrothermal vent fluids and screened 1056 fosmid clones. Twelve clones exhibited RubisCO activity and the metagenomic fragments resembled genes from Thiomicrospira crunogena. One of these clones was further analyzed. It contained a 35.2 kb metagenomic insert carrying the RubisCO gene cluster and flanking DNA regions. Knockouts of twelve genes and two intergenic regions on this metagenomic fragment demonstrated that the RubisCO activity was significantly impaired and was attributed to deletions in genes encoding putative transcriptional regulators and those believed to be vital for RubisCO activation. Our new technique revealed a novel link between a poorly characterized gene and RubisCO activity. This screen opens the door to directly investigating RubisCO genes and respective enzymes from environmental samples.

Captured metagenomics: large-scale targeting of genes based on ‘sequence capture’ reveals functional diversity in soils

PubMed Central

Manoharan, Lokeshwaran; Kushwaha, Sandeep K.; Hedlund, Katarina; Ahrén, Dag

2015-01-01

Microbial enzyme diversity is a key to understand many ecosystem processes. Whole metagenome sequencing (WMG) obtains information on functional genes, but it is costly and inefficient due to large amount of sequencing that is required. In this study, we have applied a captured metagenomics technique for functional genes in soil microorganisms, as an alternative to WMG. Large-scale targeting of functional genes, coding for enzymes related to organic matter degradation, was applied to two agricultural soil communities through captured metagenomics. Captured metagenomics uses custom-designed, hybridization-based oligonucleotide probes that enrich functional genes of interest in metagenomic libraries where only probe-bound DNA fragments are sequenced. The captured metagenomes were highly enriched with targeted genes while maintaining their target diversity and their taxonomic distribution correlated well with the traditional ribosomal sequencing. The captured metagenomes were highly enriched with genes related to organic matter degradation; at least five times more than similar, publicly available soil WMG projects. This target enrichment technique also preserves the functional representation of the soils, thereby facilitating comparative metagenomics projects. Here, we present the first study that applies the captured metagenomics approach in large scale, and this novel method allows deep investigations of central ecosystem processes by studying functional gene abundances. PMID:26490729

Structural and Functional Insights from the Metagenome of an Acidic Hot Spring Microbial Planktonic Community in the Colombian Andes

PubMed Central

Jiménez, Diego Javier; Andreote, Fernando Dini; Chaves, Diego; Montaña, José Salvador; Osorio-Forero, Cesar; Junca, Howard; Zambrano, María Mercedes; Baena, Sandra

2012-01-01

A taxonomic and annotated functional description of microbial life was deduced from 53 Mb of metagenomic sequence retrieved from a planktonic fraction of the Neotropical high Andean (3,973 meters above sea level) acidic hot spring El Coquito (EC). A classification of unassembled metagenomic reads using different databases showed a high proportion of Gammaproteobacteria and Alphaproteobacteria (in total read affiliation), and through taxonomic affiliation of 16S rRNA gene fragments we observed the presence of Proteobacteria, micro-algae chloroplast and Firmicutes. Reads mapped against the genomes Acidiphilium cryptum JF-5, Legionella pneumophila str. Corby and Acidithiobacillus caldus revealed the presence of transposase-like sequences, potentially involved in horizontal gene transfer. Functional annotation and hierarchical comparison with different datasets obtained by pyrosequencing in different ecosystems showed that the microbial community also contained extensive DNA repair systems, possibly to cope with ultraviolet radiation at such high altitudes. Analysis of genes involved in the nitrogen cycle indicated the presence of dissimilatory nitrate reduction to N2 (narGHI, nirS, norBCDQ and nosZ), associated with Proteobacteria-like sequences. Genes involved in the sulfur cycle (cysDN, cysNC and aprA) indicated adenylsulfate and sulfite production that were affiliated to several bacterial species. In summary, metagenomic sequence data provided insight regarding the structure and possible functions of this hot spring microbial community, describing some groups potentially involved in the nitrogen and sulfur cycling in this environment. PMID:23251687

Preparation of metagenomic libraries from naturally occurring marine viruses.

PubMed

Solonenko, Sergei A; Sullivan, Matthew B

2013-01-01

Microbes are now well recognized as major drivers of the biogeochemical cycling that fuels the Earth, and their viruses (phages) are known to be abundant and important in microbial mortality, horizontal gene transfer, and modulating microbial metabolic output. Investigation of environmental phages has been frustrated by an inability to culture the vast majority of naturally occurring diversity coupled with the lack of robust, quantitative, culture-independent methods for studying this uncultured majority. However, for double-stranded DNA phages, a quantitative viral metagenomic sample-to-sequence workflow now exists. Here, we review these advances with special emphasis on the technical details of preparing DNA sequencing libraries for metagenomic sequencing from environmentally relevant low-input DNA samples. Library preparation steps broadly involve manipulating the sample DNA by fragmentation, end repair and adaptor ligation, size fractionation, and amplification. One critical area of future research and development is parallel advances for alternate nucleic acid types such as single-stranded DNA and RNA viruses that are also abundant in nature. Combinations of recent advances in fragmentation (e.g., acoustic shearing and tagmentation), ligation reactions (adaptor-to-template ratio reference table availability), size fractionation (non-gel-sizing), and amplification (linear amplification for deep sequencing and linker amplification protocols) enhance our ability to generate quantitatively representative metagenomic datasets from low-input DNA samples. Such datasets are already providing new insights into the role of viruses in marine systems and will continue to do so as new environments are explored and synergies and paradigms emerge from large-scale comparative analyses. © 2013 Elsevier Inc. All rights reserved.

MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

PubMed Central

Zhou, Quan

2017-01-01

An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples. PMID:28350876

Xander: employing a novel method for efficient gene-targeted metagenomic assembly

DOE PAGES

Wang, Qiong; Fish, Jordan A.; Gilman, Mariah; ...

2015-08-05

Here, metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. Current methods often assemble only fragmented partial genes. We present a novel method for targeting assembly of specific protein-coding genes. This method combines a de Bruijn graph, as used in standard assembly approaches, and a protein profile hidden Markov model (HMM) for the gene of interest, as used in standard annotation approaches. These are used to create a novel combined weighted assembly graph. Xander performs both assembly and annotation concomitantly using information incorporated in this graph. We demonstrate the utility ofmore » this approach by assembling contigs for one phylogenetic marker gene and for two functional marker genes, first on Human Microbiome Project (HMP)-defined community Illumina data and then on 21 rhizosphere soil metagenomic datasets from three different crops totaling over 800 Gbp of unassembled data. We compared our method to a recently published bulk metagenome assembly method and a recently published gene-targeted assembler and found our method produced more, longer, and higher quality gene sequences. In conclusion, xander combines gene assignment with the rapid assembly of full-length or near full-length functional genes from metagenomic data without requiring bulk assembly or post-processing to find genes of interest. HMMs used for assembly can be tailored to the targeted genes, allowing flexibility to improve annotation over generic annotation pipelines.« less

Xander: employing a novel method for efficient gene-targeted metagenomic assembly.

PubMed

Wang, Qiong; Fish, Jordan A; Gilman, Mariah; Sun, Yanni; Brown, C Titus; Tiedje, James M; Cole, James R

2015-01-01

Metagenomics can provide important insight into microbial communities. However, assembling metagenomic datasets has proven to be computationally challenging. Current methods often assemble only fragmented partial genes. We present a novel method for targeting assembly of specific protein-coding genes. This method combines a de Bruijn graph, as used in standard assembly approaches, and a protein profile hidden Markov model (HMM) for the gene of interest, as used in standard annotation approaches. These are used to create a novel combined weighted assembly graph. Xander performs both assembly and annotation concomitantly using information incorporated in this graph. We demonstrate the utility of this approach by assembling contigs for one phylogenetic marker gene and for two functional marker genes, first on Human Microbiome Project (HMP)-defined community Illumina data and then on 21 rhizosphere soil metagenomic datasets from three different crops totaling over 800 Gbp of unassembled data. We compared our method to a recently published bulk metagenome assembly method and a recently published gene-targeted assembler and found our method produced more, longer, and higher quality gene sequences. Xander combines gene assignment with the rapid assembly of full-length or near full-length functional genes from metagenomic data without requiring bulk assembly or post-processing to find genes of interest. HMMs used for assembly can be tailored to the targeted genes, allowing flexibility to improve annotation over generic annotation pipelines. This method is implemented as open source software and is available at https://github.com/rdpstaff/Xander_assembler.

Comprehensive benchmarking and ensemble approaches for metagenomic classifiers.

PubMed

McIntyre, Alexa B R; Ounit, Rachid; Afshinnekoo, Ebrahim; Prill, Robert J; Hénaff, Elizabeth; Alexander, Noah; Minot, Samuel S; Danko, David; Foox, Jonathan; Ahsanuddin, Sofia; Tighe, Scott; Hasan, Nur A; Subramanian, Poorani; Moffat, Kelly; Levy, Shawn; Lonardi, Stefano; Greenfield, Nick; Colwell, Rita R; Rosen, Gail L; Mason, Christopher E

2017-09-21

One of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole-genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest-to-date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of 11 metagenomic classifiers. Tools were characterized on the basis of their ability to identify taxa at the genus, species, and strain levels, quantify relative abundances of taxa, and classify individual reads to the species level. Strikingly, the number of species identified by the 11 tools can differ by over three orders of magnitude on the same datasets. Various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species. Overall, pairing tools with different classification strategies (k-mer, alignment, marker) can combine their respective advantages. This study provides positive and negative controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision, accuracy, and recall. We show that proper experimental design and analysis parameters can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

Localizing text in scene images by boundary clustering, stroke segmentation, and string fragment classification.

PubMed

Yi, Chucai; Tian, Yingli

2012-09-01

In this paper, we propose a novel framework to extract text regions from scene images with complex backgrounds and multiple text appearances. This framework consists of three main steps: boundary clustering (BC), stroke segmentation, and string fragment classification. In BC, we propose a new bigram-color-uniformity-based method to model both text and attachment surface, and cluster edge pixels based on color pairs and spatial positions into boundary layers. Then, stroke segmentation is performed at each boundary layer by color assignment to extract character candidates. We propose two algorithms to combine the structural analysis of text stroke with color assignment and filter out background interferences. Further, we design a robust string fragment classification based on Gabor-based text features. The features are obtained from feature maps of gradient, stroke distribution, and stroke width. The proposed framework of text localization is evaluated on scene images, born-digital images, broadcast video images, and images of handheld objects captured by blind persons. Experimental results on respective datasets demonstrate that the framework outperforms state-of-the-art localization algorithms.

Unravelling core microbial metabolisms in the hypersaline microbial mats of Shark Bay using high-throughput metagenomics

PubMed Central

Ruvindy, Rendy; White III, Richard Allen; Neilan, Brett Anthony; Burns, Brendan Paul

2016-01-01

Modern microbial mats are potential analogues of some of Earth's earliest ecosystems. Excellent examples can be found in Shark Bay, Australia, with mats of various morphologies. To further our understanding of the functional genetic potential of these complex microbial ecosystems, we conducted for the first time shotgun metagenomic analyses. We assembled metagenomic next-generation sequencing data to classify the taxonomic and metabolic potential across diverse morphologies of marine mats in Shark Bay. The microbial community across taxonomic classifications using protein-coding and small subunit rRNA genes directly extracted from the metagenomes suggests that three phyla Proteobacteria, Cyanobacteria and Bacteriodetes dominate all marine mats. However, the microbial community structure between Shark Bay and Highbourne Cay (Bahamas) marine systems appears to be distinct from each other. The metabolic potential (based on SEED subsystem classifications) of the Shark Bay and Highbourne Cay microbial communities were also distinct. Shark Bay metagenomes have a metabolic pathway profile consisting of both heterotrophic and photosynthetic pathways, whereas Highbourne Cay appears to be dominated almost exclusively by photosynthetic pathways. Alternative non-rubisco-based carbon metabolism including reductive TCA cycle and 3-hydroxypropionate/4-hydroxybutyrate pathways is highly represented in Shark Bay metagenomes while not represented in Highbourne Cay microbial mats or any other mat forming ecosystems investigated to date. Potentially novel aspects of nitrogen cycling were also observed, as well as putative heavy metal cycling (arsenic, mercury, copper and cadmium). Finally, archaea are highly represented in Shark Bay and may have critical roles in overall ecosystem function in these modern microbial mats. PMID:26023869

Taxonomic and functional assignment of cloned sequences from high Andean forest soil metagenome.

PubMed

Montaña, José Salvador; Jiménez, Diego Javier; Hernández, Mónica; Angel, Tatiana; Baena, Sandra

2012-02-01

Total metagenomic DNA was isolated from high Andean forest soil and subjected to taxonomical and functional composition analyses by means of clone library generation and sequencing. The obtained yield of 1.7 μg of DNA/g of soil was used to construct a metagenomic library of approximately 20,000 clones (in the plasmid p-Bluescript II SK+) with an average insert size of 4 Kb, covering 80 Mb of the total metagenomic DNA. Metagenomic sequences near the plasmid cloning site were sequenced and them trimmed and assembled, obtaining 299 reads and 31 contigs (0.3 Mb). Taxonomic assignment of total sequences was performed by BLASTX, resulting in 68.8, 44.8 and 24.5% classification into taxonomic groups using the metagenomic RAST server v2.0, WebCARMA v1.0 online system and MetaGenome Analyzer v3.8 software, respectively. Most clone sequences were classified as Bacteria belonging to phlya Actinobacteria, Proteobacteria and Acidobacteria. Among the most represented orders were Actinomycetales (34% average), Rhizobiales, Burkholderiales and Myxococcales and with a greater number of sequences in the genus Mycobacterium (7% average), Frankia, Streptomyces and Bradyrhizobium. The vast majority of sequences were associated with the metabolism of carbohydrates, proteins, lipids and catalytic functions, such as phosphatases, glycosyltransferases, dehydrogenases, methyltransferases, dehydratases and epoxide hydrolases. In this study we compared different methods of taxonomic and functional assignment of metagenomic clone sequences to evaluate microbial diversity in an unexplored soil ecosystem, searching for putative enzymes of biotechnological interest and generating important information for further functional screening of clone libraries.

Under-detection of endospore-forming Firmicutes in metagenomic data

DOE PAGES

Filippidou, Sevasti; Junier, Thomas; Wunderlin, Tina; ...

2015-04-25

Microbial diversity studies based on metagenomic sequencing have greatly enhanced our knowledge of the microbial world. However, one caveat is the fact that not all microorganisms are equally well detected, questioning the universality of this approach. Firmicutes are known to be a dominant bacterial group. Several Firmicutes species are endospore formers and this property makes them hardy in potentially harsh conditions, and thus likely to be present in a wide variety of environments, even as residents and not functional players. While metagenomic libraries can be expected to contain endospore formers, endospores are known to be resilient to many traditional methodsmore » of DNA isolation and thus potentially undetectable. In this study we evaluated the representation of endospore-forming Firmicutes in 73 published metagenomic datasets using two molecular markers unique to this bacterial group ( spo0A and gpr). Both markers were notably absent in well-known habitats of Firmicutes such as soil, with spo0A found only in three mammalian gut microbiomes. A tailored DNA extraction method resulted in the detection of a large diversity of endospore-formers in amplicon sequencing of the 16S rRNA and spo0A genes. However, shotgun classification was still poor with only a minor fraction of the community assigned to Firmicutes. Thus, removing a specific bias in a molecular workflow improves detection in amplicon sequencing, but it was insufficient to overcome the limitations for detecting endospore-forming Firmicutes in whole-genome metagenomics. In conclusion, this study highlights the importance of understanding the specific methodological biases that can contribute to improve the universality of metagenomic approaches.« less

Under-detection of endospore-forming Firmicutes in metagenomic data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Filippidou, Sevasti; Junier, Thomas; Wunderlin, Tina

Microbial diversity studies based on metagenomic sequencing have greatly enhanced our knowledge of the microbial world. However, one caveat is the fact that not all microorganisms are equally well detected, questioning the universality of this approach. Firmicutes are known to be a dominant bacterial group. Several Firmicutes species are endospore formers and this property makes them hardy in potentially harsh conditions, and thus likely to be present in a wide variety of environments, even as residents and not functional players. While metagenomic libraries can be expected to contain endospore formers, endospores are known to be resilient to many traditional methodsmore » of DNA isolation and thus potentially undetectable. In this study we evaluated the representation of endospore-forming Firmicutes in 73 published metagenomic datasets using two molecular markers unique to this bacterial group ( spo0A and gpr). Both markers were notably absent in well-known habitats of Firmicutes such as soil, with spo0A found only in three mammalian gut microbiomes. A tailored DNA extraction method resulted in the detection of a large diversity of endospore-formers in amplicon sequencing of the 16S rRNA and spo0A genes. However, shotgun classification was still poor with only a minor fraction of the community assigned to Firmicutes. Thus, removing a specific bias in a molecular workflow improves detection in amplicon sequencing, but it was insufficient to overcome the limitations for detecting endospore-forming Firmicutes in whole-genome metagenomics. In conclusion, this study highlights the importance of understanding the specific methodological biases that can contribute to improve the universality of metagenomic approaches.« less

Prospecting Metagenomic Enzyme Subfamily Genes for DNA Family Shuffling by a Novel PCR-based Approach*

PubMed Central

Wang, Qiuyan; Wu, Huili; Wang, Anming; Du, Pengfei; Pei, Xiaolin; Li, Haifeng; Yin, Xiaopu; Huang, Lifeng; Xiong, Xiaolong

2010-01-01

DNA family shuffling is a powerful method for enzyme engineering, which utilizes recombination of naturally occurring functional diversity to accelerate laboratory-directed evolution. However, the use of this technique has been hindered by the scarcity of family genes with the required level of sequence identity in the genome database. We describe here a strategy for collecting metagenomic homologous genes for DNA shuffling from environmental samples by truncated metagenomic gene-specific PCR (TMGS-PCR). Using identified metagenomic gene-specific primers, twenty-three 921-bp truncated lipase gene fragments, which shared 64–99% identity with each other and formed a distinct subfamily of lipases, were retrieved from 60 metagenomic samples. These lipase genes were shuffled, and selected active clones were characterized. The chimeric clones show extensive functional and genetic diversity, as demonstrated by functional characterization and sequence analysis. Our results indicate that homologous sequences of genes captured by TMGS-PCR can be used as suitable genetic material for DNA family shuffling with broad applications in enzyme engineering. PMID:20962349

Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen.

PubMed

Stewart, Robert D; Auffret, Marc D; Warr, Amanda; Wiser, Andrew H; Press, Maximilian O; Langford, Kyle W; Liachko, Ivan; Snelling, Timothy J; Dewhurst, Richard J; Walker, Alan W; Roehe, Rainer; Watson, Mick

2018-02-28

The cow rumen is adapted for the breakdown of plant material into energy and nutrients, a task largely performed by enzymes encoded by the rumen microbiome. Here we present 913 draft bacterial and archaeal genomes assembled from over 800 Gb of rumen metagenomic sequence data derived from 43 Scottish cattle, using both metagenomic binning and Hi-C-based proximity-guided assembly. Most of these genomes represent previously unsequenced strains and species. The draft genomes contain over 69,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in public databases. Inclusion of the 913 genomes presented here improves metagenomic read classification by sevenfold against our own data, and by fivefold against other publicly available rumen datasets. Thus, our dataset substantially improves the coverage of rumen microbial genomes in the public databases and represents a valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome.

Open resource metagenomics: a model for sharing metagenomic libraries.

PubMed

Neufeld, J D; Engel, K; Cheng, J; Moreno-Hagelsieb, G; Rose, D R; Charles, T C

2011-11-30

Both sequence-based and activity-based exploitation of environmental DNA have provided unprecedented access to the genomic content of cultivated and uncultivated microorganisms. Although researchers deposit microbial strains in culture collections and DNA sequences in databases, activity-based metagenomic studies typically only publish sequences from the hits retrieved from specific screens. Physical metagenomic libraries, conceptually similar to entire sequence datasets, are usually not straightforward to obtain by interested parties subsequent to publication. In order to facilitate unrestricted distribution of metagenomic libraries, we propose the adoption of open resource metagenomics, in line with the trend towards open access publishing, and similar to culture- and mutant-strain collections that have been the backbone of traditional microbiology and microbial genetics. The concept of open resource metagenomics includes preparation of physical DNA libraries, preferably in versatile vectors that facilitate screening in a diversity of host organisms, and pooling of clones so that single aliquots containing complete libraries can be easily distributed upon request. Database deposition of associated metadata and sequence data for each library provides researchers with information to select the most appropriate libraries for further research projects. As a starting point, we have established the Canadian MetaMicroBiome Library (CM(2)BL [1]). The CM(2)BL is a publicly accessible collection of cosmid libraries containing environmental DNA from soils collected from across Canada, spanning multiple biomes. The libraries were constructed such that the cloned DNA can be easily transferred to Gateway® compliant vectors, facilitating functional screening in virtually any surrogate microbial host for which there are available plasmid vectors. The libraries, which we are placing in the public domain, will be distributed upon request without restriction to members of both the

Open resource metagenomics: a model for sharing metagenomic libraries

PubMed Central

Neufeld, J.D.; Engel, K.; Cheng, J.; Moreno-Hagelsieb, G.; Rose, D.R.; Charles, T.C.

2011-01-01

Both sequence-based and activity-based exploitation of environmental DNA have provided unprecedented access to the genomic content of cultivated and uncultivated microorganisms. Although researchers deposit microbial strains in culture collections and DNA sequences in databases, activity-based metagenomic studies typically only publish sequences from the hits retrieved from specific screens. Physical metagenomic libraries, conceptually similar to entire sequence datasets, are usually not straightforward to obtain by interested parties subsequent to publication. In order to facilitate unrestricted distribution of metagenomic libraries, we propose the adoption of open resource metagenomics, in line with the trend towards open access publishing, and similar to culture- and mutant-strain collections that have been the backbone of traditional microbiology and microbial genetics. The concept of open resource metagenomics includes preparation of physical DNA libraries, preferably in versatile vectors that facilitate screening in a diversity of host organisms, and pooling of clones so that single aliquots containing complete libraries can be easily distributed upon request. Database deposition of associated metadata and sequence data for each library provides researchers with information to select the most appropriate libraries for further research projects. As a starting point, we have established the Canadian MetaMicroBiome Library (CM2BL [1]). The CM2BL is a publicly accessible collection of cosmid libraries containing environmental DNA from soils collected from across Canada, spanning multiple biomes. The libraries were constructed such that the cloned DNA can be easily transferred to Gateway® compliant vectors, facilitating functional screening in virtually any surrogate microbial host for which there are available plasmid vectors. The libraries, which we are placing in the public domain, will be distributed upon request without restriction to members of both the

Methods for comparative metagenomics

PubMed Central

Huson, Daniel H; Richter, Daniel C; Mitra, Suparna; Auch, Alexander F; Schuster, Stephan C

2009-01-01

Background Metagenomics is a rapidly growing field of research that aims at studying uncultured organisms to understand the true diversity of microbes, their functions, cooperation and evolution, in environments such as soil, water, ancient remains of animals, or the digestive system of animals and humans. The recent development of ultra-high throughput sequencing technologies, which do not require cloning or PCR amplification, and can produce huge numbers of DNA reads at an affordable cost, has boosted the number and scope of metagenomic sequencing projects. Increasingly, there is a need for new ways of comparing multiple metagenomics datasets, and for fast and user-friendly implementations of such approaches. Results This paper introduces a number of new methods for interactively exploring, analyzing and comparing multiple metagenomic datasets, which will be made freely available in a new, comparative version 2.0 of the stand-alone metagenome analysis tool MEGAN. Conclusion There is a great need for powerful and user-friendly tools for comparative analysis of metagenomic data and MEGAN 2.0 will help to fill this gap. PMID:19208111

Strong spurious transcription likely contributes to DNA insert bias in typical metagenomic clone libraries.

PubMed

Lam, Kathy N; Charles, Trevor C

2015-01-01

Clone libraries provide researchers with a powerful resource to study nucleic acid from diverse sources. Metagenomic clone libraries in particular have aided in studies of microbial biodiversity and function, and allowed the mining of novel enzymes. Libraries are often constructed by cloning large inserts into cosmid or fosmid vectors. Recently, there have been reports of GC bias in fosmid metagenomic libraries, and it was speculated to be a result of fragmentation and loss of AT-rich sequences during cloning. However, evidence in the literature suggests that transcriptional activity or gene product toxicity may play a role. To explore possible mechanisms responsible for sequence bias in clone libraries, we constructed a cosmid library from a human microbiome sample and sequenced DNA from different steps during library construction: crude extract DNA, size-selected DNA, and cosmid library DNA. We confirmed a GC bias in the final cosmid library, and we provide evidence that the bias is not due to fragmentation and loss of AT-rich sequences but is likely occurring after DNA is introduced into Escherichia coli. To investigate the influence of strong constitutive transcription, we searched the sequence data for promoters and found that rpoD/σ(70) promoter sequences were underrepresented in the cosmid library. Furthermore, when we examined the genomes of taxa that were differentially abundant in the cosmid library relative to the original sample, we found the bias to be more correlated with the number of rpoD/σ(70) consensus sequences in the genome than with simple GC content. The GC bias of metagenomic libraries does not appear to be due to DNA fragmentation. Rather, analysis of promoter sequences provides support for the hypothesis that strong constitutive transcription from sequences recognized as rpoD/σ(70) consensus-like in E. coli may lead to instability, causing loss of the plasmid or loss of the insert DNA that gives rise to the transcription. Despite

Swine Fecal Metagenomics

EPA Science Inventory

Metagenomic approaches are providing rapid and more robust means to investigate the composition and functional genetic potential of complex microbial communities. In this study, we utilized a metagenomic approach to further understand the functional diversity of the swine gut. To...

EBI metagenomics--a new resource for the analysis and archiving of metagenomic data.

PubMed

Hunter, Sarah; Corbett, Matthew; Denise, Hubert; Fraser, Matthew; Gonzalez-Beltran, Alejandra; Hunter, Christopher; Jones, Philip; Leinonen, Rasko; McAnulla, Craig; Maguire, Eamonn; Maslen, John; Mitchell, Alex; Nuka, Gift; Oisel, Arnaud; Pesseat, Sebastien; Radhakrishnan, Rajesh; Rocca-Serra, Philippe; Scheremetjew, Maxim; Sterk, Peter; Vaughan, Daniel; Cochrane, Guy; Field, Dawn; Sansone, Susanna-Assunta

2014-01-01

Metagenomics is a relatively recently established but rapidly expanding field that uses high-throughput next-generation sequencing technologies to characterize the microbial communities inhabiting different ecosystems (including oceans, lakes, soil, tundra, plants and body sites). Metagenomics brings with it a number of challenges, including the management, analysis, storage and sharing of data. In response to these challenges, we have developed a new metagenomics resource (http://www.ebi.ac.uk/metagenomics/) that allows users to easily submit raw nucleotide reads for functional and taxonomic analysis by a state-of-the-art pipeline, and have them automatically stored (together with descriptive, standards-compliant metadata) in the European Nucleotide Archive.

Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

PubMed Central

Freitas, Tracey Allen K.; Li, Po-E; Scholz, Matthew B.; Chain, Patrick S. G.

2015-01-01

A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. PMID:25765641

Metagenome Assembly at the DOE JGI (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Chain, Patrick

2018-01-25

Patrick Chain of DOE JGI at LANL, Co-Chair of the Metagenome-specific Assembly session, on Metagenome Assembly at the DOE JGIat the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

The new intra-articular calcaneal fracture classification system in term of sustentacular fragment configurations and incorporation of posterior calcaneal facet fractures with fracture components of the calcaneal body.

PubMed

Harnroongroj, Thossart; Harnroongroj, Thos; Suntharapa, Thongchai; Arunakul, Marut

2016-10-01

The aim of this study was to develop a new calcaneal fracture classification system which will consider sustentacular fragment configuration and relation of posterior calcaneal facet to calcaneal body. The new classification system used sustentacular fragment configuration and relation of posterior calcaneal facet fracture with fracture components of calcaneal body as key aspects of main types and subtypes. Between 2000 and 2014, 126 intraarticular calcaneal fractures were classified according to the new classification system by using computed tomography images. The new classification system was studied in term of reliability, correlation to choices of treatment, implant fixation and quality of fracture reduction. Types of sustentacular fragment comprised type A, B and C. Type A sustentacular fragment included sustentacular tali containing middle calcaneal facet. In Type B and C fractures sustentacular fragment included medial aspect and entire posterior calcaneal facet as a single unit, respectively. The fractures with type A, B and C sustentacular fragments were classified as main type A, B and C intra-articular calcaneal fractures. The main type A and B comprised 4 subtypes. Subtypes A1, A3, B1, and B3 associated with avulsion and bending fragments of calcaneal body. Subtype A2, B2, and B4 associated with burst calcaneal body. Subtype B4 was not found in the study. Main type C had no subtype and associated with burst calcaneal body. The data showed good reliability. The study showed that our new intra-articular calcaneal fracture classification system correlates to choices of treatment, implant fixation and quality of fracture reduction. Level IV, Study of Diagnostic Test. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Metagenomics as a Tool for Enzyme Discovery: Hydrolytic Enzymes from Marine-Related Metagenomes.

PubMed

Popovic, Ana; Tchigvintsev, Anatoly; Tran, Hai; Chernikova, Tatyana N; Golyshina, Olga V; Yakimov, Michail M; Golyshin, Peter N; Yakunin, Alexander F

2015-01-01

This chapter discusses metagenomics and its application for enzyme discovery, with a focus on hydrolytic enzymes from marine metagenomic libraries. With less than one percent of culturable microorganisms in the environment, metagenomics, or the collective study of community genetics, has opened up a rich pool of uncharacterized metabolic pathways, enzymes, and adaptations. This great untapped pool of genes provides the particularly exciting potential to mine for new biochemical activities or novel enzymes with activities tailored to peculiar sets of environmental conditions. Metagenomes also represent a huge reservoir of novel enzymes for applications in biocatalysis, biofuels, and bioremediation. Here we present the results of enzyme discovery for four enzyme activities, of particular industrial or environmental interest, including esterase/lipase, glycosyl hydrolase, protease and dehalogenase.

Exploring neighborhoods in the metagenome universe.

PubMed

Aßhauer, Kathrin P; Klingenberg, Heiner; Lingner, Thomas; Meinicke, Peter

2014-07-14

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.

Exploring Neighborhoods in the Metagenome Universe

PubMed Central

Aßhauer, Kathrin P.; Klingenberg, Heiner; Lingner, Thomas; Meinicke, Peter

2014-01-01

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. PMID:25026170

Technical Report: Algorithm and Implementation for Quasispecies Abundance Inference with Confidence Intervals from Metagenomic Sequence Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McLoughlin, Kevin

2016-01-11

This report describes the design and implementation of an algorithm for estimating relative microbial abundances, together with confidence limits, using data from metagenomic DNA sequencing. For the background behind this project and a detailed discussion of our modeling approach for metagenomic data, we refer the reader to our earlier technical report, dated March 4, 2014. Briefly, we described a fully Bayesian generative model for paired-end sequence read data, incorporating the effects of the relative abundances, the distribution of sequence fragment lengths, fragment position bias, sequencing errors and variations between the sampled genomes and the nearest reference genomes. A distinctive featuremore » of our modeling approach is the use of a Chinese restaurant process (CRP) to describe the selection of genomes to be sampled, and thus the relative abundances. The CRP component is desirable for fitting abundances to reads that may map ambiguously to multiple targets, because it naturally leads to sparse solutions that select the best representative from each set of nearly equivalent genomes.« less

Discovery of new cellulases from the metagenome by a metagenomics-guided strategy.

PubMed

Yang, Chao; Xia, Yu; Qu, Hong; Li, An-Dong; Liu, Ruihua; Wang, Yubo; Zhang, Tong

2016-01-01

Energy shortage has become a global problem. Production of biofuels from renewable biomass resources is an inevitable trend of sustainable development. Cellulose is the most abundant and renewable resource in nature. Lack of new cellulases with unique properties has become the bottleneck of the efficient utilization of cellulose. Environmental metagenomes are regarded as huge reservoirs for a variety of cellulases. However, new cellulases cannot be obtained easily by functional screening of metagenomic libraries. In this work, a metagenomics-guided strategy for obtaining new cellulases from the metagenome was proposed. Metagenomic sequences of DNA extracted from the anaerobic beer lees converting consortium enriched at thermophilic conditions were assembled, and 23 glycoside hydrolase (GH) sequences affiliated with the GH family 5 were identified. Among the 23 GH sequences, three target sequences (designated as cel7482, cel3623 and cel36) showing low identity with those known GHs were chosen as the putative cellulase genes to be functionally expressed in Escherichia coli after PCR cloning. The three cellulases were classified into endo-β-1,4-glucanases by product pattern analysis. The recombinant cellulases were more active at pH 5.5 and within a temperature range of 60-70 °C. Computer-assisted 3D structure modeling indicated that the active residues in the active site of the recombinant cellulases were more similar to each other compared with non-active site residues. The recombinant cel7482 was extremely tolerant to 2 M NaCl, suggesting that cel7482 may be a halotolerant cellulase. Moreover, the recombinant cel7482 was shown to have an ability to resist three ionic liquids (ILs), which are widely used for cellulose pretreatment. Furthermore, active cel7482 was secreted by the twin-arginine translocation (Tat) pathway of Bacillus subtilis 168 into the culture medium, which facilitates the subsequent purification and reduces the formation of inclusion body in

Microbial Metagenomics: Beyond the Genome

NASA Astrophysics Data System (ADS)

Gilbert, Jack A.; Dupont, Christopher L.

2011-01-01

Metagenomics literally means “beyond the genome.” Marine microbial metagenomic databases presently comprise ˜400 billion base pairs of DNA, only ˜3% of that found in 1 ml of seawater. Very soon a trillion-base-pair sequence run will be feasible, so it is time to reflect on what we have learned from metagenomics. We review the impact of metagenomics on our understanding of marine microbial communities. We consider the studies facilitated by data generated through the Global Ocean Sampling expedition, as well as the revolution wrought at the individual laboratory level through next generation sequencing technologies. We review recent studies and discoveries since 2008, provide a discussion of bioinformatic analyses, including conceptual pipelines and sequence annotation and predict the future of metagenomics, with suggestions of collaborative community studies tailored toward answering some of the fundamental questions in marine microbial ecology.

Mining virulence genes using metagenomics.

PubMed

Belda-Ferre, Pedro; Cabrera-Rubio, Raúl; Moya, Andrés; Mira, Alex

2011-01-01

When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens.

Arsenic metabolism in high altitude modern stromatolites revealed by metagenomic analysis.

PubMed

Kurth, Daniel; Amadio, Ariel; Ordoñez, Omar F; Albarracín, Virginia H; Gärtner, Wolfgang; Farías, María E

2017-04-21

Modern stromatolites thrive only in selected locations in the world. Socompa Lake, located in the Andean plateau at 3570 masl, is one of the numerous extreme Andean microbial ecosystems described over recent years. Extreme environmental conditions include hypersalinity, high UV incidence, and high arsenic content, among others. After Socompa's stromatolite microbial communities were analysed by metagenomic DNA sequencing, taxonomic classification showed dominance of Proteobacteria, Bacteroidetes and Firmicutes, and a remarkably high number of unclassified sequences. A functional analysis indicated that carbon fixation might occur not only by the Calvin-Benson cycle, but also through alternative pathways such as the reverse TCA cycle, and the reductive acetyl-CoA pathway. Deltaproteobacteria were involved both in sulfate reduction and nitrogen fixation. Significant differences were found when comparing the Socompa stromatolite metagenome to the Shark Bay (Australia) smooth mat metagenome: namely, those involving stress related processes, particularly, arsenic resistance. An in-depth analysis revealed a surprisingly diverse metabolism comprising all known types of As resistance and energy generating pathways. While the ars operon was the main mechanism, an important abundance of arsM genes was observed in selected phyla. The data resulting from this work will prove a cornerstone for further studies on this rare microbial community.

Current and future resources for functional metagenomics

PubMed Central

Lam, Kathy N.; Cheng, Jiujun; Engel, Katja; Neufeld, Josh D.; Charles, Trevor C.

2015-01-01

Functional metagenomics is a powerful experimental approach for studying gene function, starting from the extracted DNA of mixed microbial populations. A functional approach relies on the construction and screening of metagenomic libraries—physical libraries that contain DNA cloned from environmental metagenomes. The information obtained from functional metagenomics can help in future annotations of gene function and serve as a complement to sequence-based metagenomics. In this Perspective, we begin by summarizing the technical challenges of constructing metagenomic libraries and emphasize their value as resources. We then discuss libraries constructed using the popular cloning vector, pCC1FOS, and highlight the strengths and shortcomings of this system, alongside possible strategies to maximize existing pCC1FOS-based libraries by screening in diverse hosts. Finally, we discuss the known bias of libraries constructed from human gut and marine water samples, present results that suggest bias may also occur for soil libraries, and consider factors that bias metagenomic libraries in general. We anticipate that discussion of current resources and limitations will advance tools and technologies for functional metagenomics research. PMID:26579102

Current and future resources for functional metagenomics.

PubMed

Lam, Kathy N; Cheng, Jiujun; Engel, Katja; Neufeld, Josh D; Charles, Trevor C

2015-01-01

Functional metagenomics is a powerful experimental approach for studying gene function, starting from the extracted DNA of mixed microbial populations. A functional approach relies on the construction and screening of metagenomic libraries-physical libraries that contain DNA cloned from environmental metagenomes. The information obtained from functional metagenomics can help in future annotations of gene function and serve as a complement to sequence-based metagenomics. In this Perspective, we begin by summarizing the technical challenges of constructing metagenomic libraries and emphasize their value as resources. We then discuss libraries constructed using the popular cloning vector, pCC1FOS, and highlight the strengths and shortcomings of this system, alongside possible strategies to maximize existing pCC1FOS-based libraries by screening in diverse hosts. Finally, we discuss the known bias of libraries constructed from human gut and marine water samples, present results that suggest bias may also occur for soil libraries, and consider factors that bias metagenomic libraries in general. We anticipate that discussion of current resources and limitations will advance tools and technologies for functional metagenomics research.

A Primer on Metagenomics

PubMed Central

Wooley, John C.; Godzik, Adam; Friedberg, Iddo

2010-01-01

Metagenomics is a discipline that enables the genomic study of uncultured microorganisms. Faster, cheaper sequencing technologies and the ability to sequence uncultured microbes sampled directly from their habitats are expanding and transforming our view of the microbial world. Distilling meaningful information from the millions of new genomic sequences presents a serious challenge to bioinformaticians. In cultured microbes, the genomic data come from a single clone, making sequence assembly and annotation tractable. In metagenomics, the data come from heterogeneous microbial communities, sometimes containing more than 10,000 species, with the sequence data being noisy and partial. From sampling, to assembly, to gene calling and function prediction, bioinformatics faces new demands in interpreting voluminous, noisy, and often partial sequence data. Although metagenomics is a relative newcomer to science, the past few years have seen an explosion in computational methods applied to metagenomic-based research. It is therefore not within the scope of this article to provide an exhaustive review. Rather, we provide here a concise yet comprehensive introduction to the current computational requirements presented by metagenomics, and review the recent progress made. We also note whether there is software that implements any of the methods presented here, and briefly review its utility. Nevertheless, it would be useful if readers of this article would avail themselves of the comment section provided by this journal, and relate their own experiences. Finally, the last section of this article provides a few representative studies illustrating different facets of recent scientific discoveries made using metagenomics. PMID:20195499

The Metagenome of Utricularia gibba's Traps: Into the Microbial Input to a Carnivorous Plant

PubMed Central

Alcaraz, Luis David; Martínez-Sánchez, Shamayim; Torres, Ignacio; Ibarra-Laclette, Enrique; Herrera-Estrella, Luis

2016-01-01

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. PMID:26859489

Metagenomic assembly through the lens of validation: recent advances in assessing and improving the quality of genomes assembled from metagenomes.

PubMed

Olson, Nathan D; Treangen, Todd J; Hill, Christopher M; Cepeda-Espinoza, Victoria; Ghurye, Jay; Koren, Sergey; Pop, Mihai

2017-08-07

Metagenomic samples are snapshots of complex ecosystems at work. They comprise hundreds of known and unknown species, contain multiple strain variants and vary greatly within and across environments. Many microbes found in microbial communities are not easily grown in culture making their DNA sequence our only clue into their evolutionary history and biological function. Metagenomic assembly is a computational process aimed at reconstructing genes and genomes from metagenomic mixtures. Current methods have made significant strides in reconstructing DNA segments comprising operons, tandem gene arrays and syntenic blocks. Shorter, higher-throughput sequencing technologies have become the de facto standard in the field. Sequencers are now able to generate billions of short reads in only a few days. Multiple metagenomic assembly strategies, pipelines and assemblers have appeared in recent years. Owing to the inherent complexity of metagenome assembly, regardless of the assembly algorithm and sequencing method, metagenome assemblies contain errors. Recent developments in assembly validation tools have played a pivotal role in improving metagenomics assemblers. Here, we survey recent progress in the field of metagenomic assembly, provide an overview of key approaches for genomic and metagenomic assembly validation and demonstrate the insights that can be derived from assemblies through the use of assembly validation strategies. We also discuss the potential for impact of long-read technologies in metagenomics. We conclude with a discussion of future challenges and opportunities in the field of metagenomic assembly and validation. © The Author 2017. Published by Oxford University Press.

Critical Assessment of Metagenome Interpretation – a benchmark of computational metagenomics software

PubMed Central

Sczyrba, Alexander; Hofmann, Peter; Belmann, Peter; Koslicki, David; Janssen, Stefan; Dröge, Johannes; Gregor, Ivan; Majda, Stephan; Fiedler, Jessika; Dahms, Eik; Bremges, Andreas; Fritz, Adrian; Garrido-Oter, Ruben; Jørgensen, Tue Sparholt; Shapiro, Nicole; Blood, Philip D.; Gurevich, Alexey; Bai, Yang; Turaev, Dmitrij; DeMaere, Matthew Z.; Chikhi, Rayan; Nagarajan, Niranjan; Quince, Christopher; Meyer, Fernando; Balvočiūtė, Monika; Hansen, Lars Hestbjerg; Sørensen, Søren J.; Chia, Burton K. H.; Denis, Bertrand; Froula, Jeff L.; Wang, Zhong; Egan, Robert; Kang, Dongwan Don; Cook, Jeffrey J.; Deltel, Charles; Beckstette, Michael; Lemaitre, Claire; Peterlongo, Pierre; Rizk, Guillaume; Lavenier, Dominique; Wu, Yu-Wei; Singer, Steven W.; Jain, Chirag; Strous, Marc; Klingenberg, Heiner; Meinicke, Peter; Barton, Michael; Lingner, Thomas; Lin, Hsin-Hung; Liao, Yu-Chieh; Silva, Genivaldo Gueiros Z.; Cuevas, Daniel A.; Edwards, Robert A.; Saha, Surya; Piro, Vitor C.; Renard, Bernhard Y.; Pop, Mihai; Klenk, Hans-Peter; Göker, Markus; Kyrpides, Nikos C.; Woyke, Tanja; Vorholt, Julia A.; Schulze-Lefert, Paul; Rubin, Edward M.; Darling, Aaron E.; Rattei, Thomas; McHardy, Alice C.

2018-01-01

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions. PMID:28967888

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reddy, Tatiparthi B. K.; Thomas, Alex D.; Stamatis, Dimitri

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Within this paper, we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencingmore » projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. Lastly, GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards.« less

The Genomes OnLine Database (GOLD) v.5: a metadata management system based on a four level (meta)genome project classification

PubMed Central

Reddy, T.B.K.; Thomas, Alex D.; Stamatis, Dimitri; Bertsch, Jon; Isbandi, Michelle; Jansson, Jakob; Mallajosyula, Jyothi; Pagani, Ioanna; Lobos, Elizabeth A.; Kyrpides, Nikos C.

2015-01-01

The Genomes OnLine Database (GOLD; http://www.genomesonline.org) is a comprehensive online resource to catalog and monitor genetic studies worldwide. GOLD provides up-to-date status on complete and ongoing sequencing projects along with a broad array of curated metadata. Here we report version 5 (v.5) of the database. The newly designed database schema and web user interface supports several new features including the implementation of a four level (meta)genome project classification system and a simplified intuitive web interface to access reports and launch search tools. The database currently hosts information for about 19 200 studies, 56 000 Biosamples, 56 000 sequencing projects and 39 400 analysis projects. More than just a catalog of worldwide genome projects, GOLD is a manually curated, quality-controlled metadata warehouse. The problems encountered in integrating disparate and varying quality data into GOLD are briefly highlighted. GOLD fully supports and follows the Genomic Standards Consortium (GSC) Minimum Information standards. PMID:25348402

Loeffler 4.0: Diagnostic Metagenomics.

PubMed

Höper, Dirk; Wylezich, Claudia; Beer, Martin

2017-01-01

A new world of possibilities for "virus discovery" was opened up with high-throughput sequencing becoming available in the last decade. While scientifically metagenomic analysis was established before the start of the era of high-throughput sequencing, the availability of the first second-generation sequencers was the kick-off for diagnosticians to use sequencing for the detection of novel pathogens. Today, diagnostic metagenomics is becoming the standard procedure for the detection and genetic characterization of new viruses or novel virus variants. Here, we provide an overview about technical considerations of high-throughput sequencing-based diagnostic metagenomics together with selected examples of "virus discovery" for animal diseases or zoonoses and metagenomics for food safety or basic veterinary research. © 2017 Elsevier Inc. All rights reserved.

Metagenomic Assembly: Overview, Challenges and Applications

PubMed Central

Ghurye, Jay S.; Cepeda-Espinoza, Victoria; Pop, Mihai

2016-01-01

Advances in sequencing technologies have led to the increased use of high throughput sequencing in characterizing the microbial communities associated with our bodies and our environment. Critical to the analysis of the resulting data are sequence assembly algorithms able to reconstruct genes and organisms from complex mixtures. Metagenomic assembly involves new computational challenges due to the specific characteristics of the metagenomic data. In this survey, we focus on major algorithmic approaches for genome and metagenome assembly, and discuss the new challenges and opportunities afforded by this new field. We also review several applications of metagenome assembly in addressing interesting biological problems. PMID:27698619

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data.

PubMed

Correia, Damien; Doppelt-Azeroual, Olivia; Denis, Jean-Baptiste; Vandenbogaert, Mathias; Caro, Valérie

2015-01-01

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users' input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user's input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy's main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive

Bambus 2: scaffolding metagenomes.

PubMed

Koren, Sergey; Treangen, Todd J; Pop, Mihai

2011-11-01

Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources. We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly. Bambus 2 is open source and available from http://amos.sf.net. mpop@umiacs.umd.edu. Supplementary data are available at Bioinformatics online.

Bambus 2: scaffolding metagenomes

PubMed Central

Koren, Sergey; Treangen, Todd J.; Pop, Mihai

2011-01-01

Motivation: Sequencing projects increasingly target samples from non-clonal sources. In particular, metagenomics has enabled scientists to begin to characterize the structure of microbial communities. The software tools developed for assembling and analyzing sequencing data for clonal organisms are, however, unable to adequately process data derived from non-clonal sources. Results: We present a new scaffolder, Bambus 2, to address some of the challenges encountered when analyzing metagenomes. Our approach relies on a combination of a novel method for detecting genomic repeats and algorithms that analyze assembly graphs to identify biologically meaningful genomic variants. We compare our software to current assemblers using simulated and real data. We demonstrate that the repeat detection algorithms have higher sensitivity than current approaches without sacrificing specificity. In metagenomic datasets, the scaffolder avoids false joins between distantly related organisms while obtaining long-range contiguity. Bambus 2 represents a first step toward automated metagenomic assembly. Availability: Bambus 2 is open source and available from http://amos.sf.net. Contact: mpop@umiacs.umd.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21926123

An application of statistics to comparative metagenomics

PubMed Central

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-01-01

Background Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Results Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. Conclusion The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems. PMID:16549025

An application of statistics to comparative metagenomics.

PubMed

Rodriguez-Brito, Beltran; Rohwer, Forest; Edwards, Robert A

2006-03-20

Metagenomics, sequence analyses of genomic DNA isolated directly from the environments, can be used to identify organisms and model community dynamics of a particular ecosystem. Metagenomics also has the potential to identify significantly different metabolic potential in different environments. Here we use a statistical method to compare curated subsystems, to predict the physiology, metabolism, and ecology from metagenomes. This approach can be used to identify those subsystems that are significantly different between metagenome sequences. Subsystems that were overrepresented in the Sargasso Sea and Acid Mine Drainage metagenome when compared to non-redundant databases were identified. The methodology described herein applies statistics to the comparisons of metabolic potential in metagenomes. This analysis reveals those subsystems that are more, or less, represented in the different environments that are compared. These differences in metabolic potential lead to several testable hypotheses about physiology and metabolism of microbes from these ecosystems.

Multisubstrate Isotope Labeling and Metagenomic Analysis of Active Soil Bacterial Communities

PubMed Central

Verastegui, Y.; Cheng, J.; Engel, K.; Kolczynski, D.; Mortimer, S.; Lavigne, J.; Montalibet, J.; Romantsov, T.; Hall, M.; McConkey, B. J.; Rose, D. R.; Tomashek, J. J.; Scott, B. R.

2014-01-01

ABSTRACT Soil microbial diversity represents the largest global reservoir of novel microorganisms and enzymes. In this study, we coupled functional metagenomics and DNA stable-isotope probing (DNA-SIP) using multiple plant-derived carbon substrates and diverse soils to characterize active soil bacterial communities and their glycoside hydrolase genes, which have value for industrial applications. We incubated samples from three disparate Canadian soils (tundra, temperate rainforest, and agricultural) with five native carbon (12C) or stable-isotope-labeled (13C) carbohydrates (glucose, cellobiose, xylose, arabinose, and cellulose). Indicator species analysis revealed high specificity and fidelity for many uncultured and unclassified bacterial taxa in the heavy DNA for all soils and substrates. Among characterized taxa, Actinomycetales (Salinibacterium), Rhizobiales (Devosia), Rhodospirillales (Telmatospirillum), and Caulobacterales (Phenylobacterium and Asticcacaulis) were bacterial indicator species for the heavy substrates and soils tested. Both Actinomycetales and Caulobacterales (Phenylobacterium) were associated with metabolism of cellulose, and Alphaproteobacteria were associated with the metabolism of arabinose; members of the order Rhizobiales were strongly associated with the metabolism of xylose. Annotated metagenomic data suggested diverse glycoside hydrolase gene representation within the pooled heavy DNA. By screening 2,876 cloned fragments derived from the 13C-labeled DNA isolated from soils incubated with cellulose, we demonstrate the power of combining DNA-SIP, multiple-displacement amplification (MDA), and functional metagenomics by efficiently isolating multiple clones with activity on carboxymethyl cellulose and fluorogenic proxy substrates for carbohydrate-active enzymes. PMID:25028422

Identifying biologically relevant differences between metagenomic communities.

PubMed

Parks, Donovan H; Beiko, Robert G

2010-03-15

Metagenomics is the study of genetic material recovered directly from environmental samples. Taxonomic and functional differences between metagenomic samples can highlight the influence of ecological factors on patterns of microbial life in a wide range of habitats. Statistical hypothesis tests can help us distinguish ecological influences from sampling artifacts, but knowledge of only the P-value from a statistical hypothesis test is insufficient to make inferences about biological relevance. Current reporting practices for pairwise comparative metagenomics are inadequate, and better tools are needed for comparative metagenomic analysis. We have developed a new software package, STAMP, for comparative metagenomics that supports best practices in analysis and reporting. Examination of a pair of iron mine metagenomes demonstrates that deeper biological insights can be gained using statistical techniques available in our software. An analysis of the functional potential of 'Candidatus Accumulibacter phosphatis' in two enhanced biological phosphorus removal metagenomes identified several subsystems that differ between the A.phosphatis stains in these related communities, including phosphate metabolism, secretion and metal transport. Python source code and binaries are freely available from our website at http://kiwi.cs.dal.ca/Software/STAMP CONTACT: beiko@cs.dal.ca Supplementary data are available at Bioinformatics online.

Rapid identification and classification of bacteria by 16S rDNA restriction fragment melting curve analyses (RFMCA).

PubMed

Rudi, Knut; Kleiberg, Gro H; Heiberg, Ragnhild; Rosnes, Jan T

2007-08-01

The aim of this work was to evaluate restriction fragment melting curve analyses (RFMCA) as a novel approach for rapid classification of bacteria during food production. RFMCA was evaluated for bacteria isolated from sous vide food products, and raw materials used for sous vide production. We identified four major bacterial groups in the material analysed (cluster I-Streptococcus, cluster II-Carnobacterium/Bacillus, cluster III-Staphylococcus and cluster IV-Actinomycetales). The accuracy of RFMCA was evaluated by comparison with 16S rDNA sequencing. The strains satisfying the RFMCA quality filtering criteria (73%, n=57), with both 16S rDNA sequence information and RFMCA data (n=45) gave identical group assignments with the two methods. RFMCA enabled rapid and accurate classification of bacteria that is database compatible. Potential application of RFMCA in the food or pharmaceutical industry will include development of classification models for the bacteria expected in a given product, and then to build an RFMCA database as a part of the product quality control.

Metazen - metadata capture for metagenomes.

PubMed

Bischof, Jared; Harrison, Travis; Paczian, Tobias; Glass, Elizabeth; Wilke, Andreas; Meyer, Folker

2014-01-01

As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. Unfortunately, these tools are not specifically designed for metagenomic surveys; in particular, they lack the appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.

Beyond Biodiversity: Fish Metagenomes

PubMed Central

Ardura, Alba; Planes, Serge; Garcia-Vazquez, Eva

2011-01-01

Biodiversity and intra-specific genetic diversity are interrelated and determine the potential of a community to survive and evolve. Both are considered together in Prokaryote communities treated as metagenomes or ensembles of functional variants beyond species limits. Many factors alter biodiversity in higher Eukaryote communities, and human exploitation can be one of the most important for some groups of plants and animals. For example, fisheries can modify both biodiversity and genetic diversity (intra specific). Intra-specific diversity can be drastically altered by overfishing. Intense fishing pressure on one stock may imply extinction of some genetic variants and subsequent loss of intra-specific diversity. The objective of this study was to apply a metagenome approach to fish communities and explore its value for rapid evaluation of biodiversity and genetic diversity at community level. Here we have applied the metagenome approach employing the Barcoding target gene COI as a model sequence in catch from four very different fish assemblages exploited by fisheries: freshwater communities from the Amazon River and northern Spanish rivers, and marine communities from the Cantabric and Mediterranean seas. Treating all sequences obtained from each regional catch as a biological unit (exploited community) we found that metagenomic diversity indices of the Amazonian catch sample here examined were lower than expected. Reduced diversity could be explained, at least partially, by overexploitation of the fish community that had been independently estimated by other methods. We propose using a metagenome approach for estimating diversity in Eukaryote communities and early evaluating genetic variation losses at multi-species level. PMID:21829636

Beyond biodiversity: fish metagenomes.

PubMed

Ardura, Alba; Planes, Serge; Garcia-Vazquez, Eva

2011-01-01

Biodiversity and intra-specific genetic diversity are interrelated and determine the potential of a community to survive and evolve. Both are considered together in Prokaryote communities treated as metagenomes or ensembles of functional variants beyond species limits.Many factors alter biodiversity in higher Eukaryote communities, and human exploitation can be one of the most important for some groups of plants and animals. For example, fisheries can modify both biodiversity and genetic diversity (intra specific). Intra-specific diversity can be drastically altered by overfishing. Intense fishing pressure on one stock may imply extinction of some genetic variants and subsequent loss of intra-specific diversity. The objective of this study was to apply a metagenome approach to fish communities and explore its value for rapid evaluation of biodiversity and genetic diversity at community level. Here we have applied the metagenome approach employing the barcoding target gene coi as a model sequence in catch from four very different fish assemblages exploited by fisheries: freshwater communities from the Amazon River and northern Spanish rivers, and marine communities from the Cantabric and Mediterranean seas.Treating all sequences obtained from each regional catch as a biological unit (exploited community) we found that metagenomic diversity indices of the Amazonian catch sample here examined were lower than expected. Reduced diversity could be explained, at least partially, by overexploitation of the fish community that had been independently estimated by other methods.We propose using a metagenome approach for estimating diversity in Eukaryote communities and early evaluating genetic variation losses at multi-species level.

The metagenomic data life-cycle: standards and best practices

PubMed Central

ten Hoopen, Petra; Finn, Robert D.; Bongo, Lars Ailo; Corre, Erwan; Meyer, Folker; Mitchell, Alex; Pelletier, Eric; Pesole, Graziano; Santamaria, Monica; Willassen, Nils Peder

2017-01-01

Abstract Metagenomics data analyses from independent studies can only be compared if the analysis workflows are described in a harmonized way. In this overview, we have mapped the landscape of data standards available for the description of essential steps in metagenomics: (i) material sampling, (ii) material sequencing, (iii) data analysis, and (iv) data archiving and publishing. Taking examples from marine research, we summarize essential variables used to describe material sampling processes and sequencing procedures in a metagenomics experiment. These aspects of metagenomics dataset generation have been to some extent addressed by the scientific community, but greater awareness and adoption is still needed. We emphasize the lack of standards relating to reporting how metagenomics datasets are analysed and how the metagenomics data analysis outputs should be archived and published. We propose best practice as a foundation for a community standard to enable reproducibility and better sharing of metagenomics datasets, leading ultimately to greater metagenomics data reuse and repurposing. PMID:28637310

The metagenomic data life-cycle: standards and best practices

DOE Office of Scientific and Technical Information (OSTI.GOV)

ten Hoopen, Petra; Finn, Robert D.; Bongo, Lars Ailo

Metagenomics data analyses from independent studies can only be compared if the analysis workflows are described in a harmonised way. In this overview, we have mapped the landscape of data standards available for the description of essential steps in metagenomics: (1) material sampling, (2) material sequencing (3) data analysis and (4) data archiving & publishing. Taking examples from marine research, we summarise essential variables used to describe material sampling processes and sequencing procedures in a metagenomics experiment. These aspects of metagenomics dataset generation have been to some extent addressed by the scientific community but greater awareness and adoption is stillmore » needed. We emphasise the lack of standards relating to reporting how metagenomics datasets are analysed and how the metagenomics data analysis outputs should be archived and published. We propose best practice as a foundation for a community standard to enable reproducibility and better sharing of metagenomics datasets, leading ultimately to greater metagenomics data reuse and repurposing.« less

Metagenomics of an Alkaline Hot Spring in Galicia (Spain): Microbial Diversity Analysis and Screening for Novel Lipolytic Enzymes.

PubMed

López-López, Olalla; Knapik, Kamila; Cerdán, Maria-Esperanza; González-Siso, María-Isabel

2015-01-01

A fosmid library was constructed with the metagenomic DNA from the water of the Lobios hot spring (76°C, pH = 8.2) located in Ourense (Spain). Metagenomic sequencing of the fosmid library allowed the assembly of 9722 contigs ranging in size from 500 to 56,677 bp and spanning ~18 Mbp. 23,207 ORFs (Open Reading Frames) were predicted from the assembly. Biodiversity was explored by taxonomic classification and it revealed that bacteria were predominant, while the archaea were less abundant. The six most abundant bacterial phyla were Deinococcus-Thermus, Proteobacteria, Firmicutes, Acidobacteria, Aquificae, and Chloroflexi. Within the archaeal superkingdom, the phylum Thaumarchaeota was predominant with the dominant species "Candidatus Caldiarchaeum subterraneum." Functional classification revealed the genes associated to one-carbon metabolism as the most abundant. Both taxonomic and functional classifications showed a mixture of different microbial metabolic patterns: aerobic and anaerobic, chemoorganotrophic and chemolithotrophic, autotrophic and heterotrophic. Remarkably, the presence of genes encoding enzymes with potential biotechnological interest, such as xylanases, galactosidases, proteases, and lipases, was also revealed in the metagenomic library. Functional screening of this library was subsequently done looking for genes encoding lipolytic enzymes. Six genes conferring lipolytic activity were identified and one was cloned and characterized. This gene was named LOB4Est and it was expressed in a yeast mesophilic host. LOB4Est codes for a novel esterase of family VIII, with sequence similarity to β-lactamases, but with unusual wide substrate specificity. When the enzyme was purified from the mesophilic host it showed half-life of 1 h and 43 min at 50°C, and maximal activity at 40°C and pH 7.5 with p-nitrophenyl-laurate as substrate. Interestingly, the enzyme retained more than 80% of maximal activity in a broad range of pH from 6.5 to 8.

Assembling the Marine Metagenome, One Cell at a Time

PubMed Central

Woyke, Tanja; Xie, Gary; Copeland, Alex; González, José M.; Han, Cliff; Kiss, Hajnalka; Saw, Jimmy H.; Senin, Pavel; Yang, Chi; Chatterji, Sourav; Cheng, Jan-Fang; Eisen, Jonathan A.; Sieracki, Michael E.; Stepanauskas, Ramunas

2009-01-01

The difficulty associated with the cultivation of most microorganisms and the complexity of natural microbial assemblages, such as marine plankton or human microbiome, hinder genome reconstruction of representative taxa using cultivation or metagenomic approaches. Here we used an alternative, single cell sequencing approach to obtain high-quality genome assemblies of two uncultured, numerically significant marine microorganisms. We employed fluorescence-activated cell sorting and multiple displacement amplification to obtain hundreds of micrograms of genomic DNA from individual, uncultured cells of two marine flavobacteria from the Gulf of Maine that were phylogenetically distant from existing cultured strains. Shotgun sequencing and genome finishing yielded 1.9 Mbp in 17 contigs and 1.5 Mbp in 21 contigs for the two flavobacteria, with estimated genome recoveries of about 91% and 78%, respectively. Only 0.24% of the assembling sequences were contaminants and were removed from further analysis using rigorous quality control. In contrast to all cultured strains of marine flavobacteria, the two single cell genomes were excellent Global Ocean Sampling (GOS) metagenome fragment recruiters, demonstrating their numerical significance in the ocean. The geographic distribution of GOS recruits along the Northwest Atlantic coast coincided with ocean surface currents. Metabolic reconstruction indicated diverse potential energy sources, including biopolymer degradation, proteorhodopsin photometabolism, and hydrogen oxidation. Compared to cultured relatives, the two uncultured flavobacteria have small genome sizes, few non-coding nucleotides, and few paralogous genes, suggesting adaptations to narrow ecological niches. These features may have contributed to the abundance of the two taxa in specific regions of the ocean, and may have hindered their cultivation. We demonstrate the power of single cell DNA sequencing to generate reference genomes of uncultured taxa from a complex

Human milk metagenome: a functional capacity analysis

PubMed Central

2013-01-01

Background 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. Results 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. Conclusions 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

The Amordad database engine for metagenomics.

PubMed

Behnam, Ehsan; Smith, Andrew D

2014-10-15

Several technical challenges in metagenomic data analysis, including assembling metagenomic sequence data or identifying operational taxonomic units, are both significant and well known. These forms of analysis are increasingly cited as conceptually flawed, given the extreme variation within traditionally defined species and rampant horizontal gene transfer. Furthermore, computational requirements of such analysis have hindered content-based organization of metagenomic data at large scale. In this article, we introduce the Amordad database engine for alignment-free, content-based indexing of metagenomic datasets. Amordad places the metagenome comparison problem in a geometric context, and uses an indexing strategy that combines random hashing with a regular nearest neighbor graph. This framework allows refinement of the database over time by continual application of random hash functions, with the effect of each hash function encoded in the nearest neighbor graph. This eliminates the need to explicitly maintain the hash functions in order for query efficiency to benefit from the accumulated randomness. Results on real and simulated data show that Amordad can support logarithmic query time for identifying similar metagenomes even as the database size reaches into the millions. Source code, licensed under the GNU general public license (version 3) is freely available for download from http://smithlabresearch.org/amordad andrewds@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Streaming fragment assignment for real-time analysis of sequencing experiments

PubMed Central

Roberts, Adam; Pachter, Lior

2013-01-01

We present eXpress, a software package for highly efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time, and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data, showing greater efficiency than other quantification methods. PMID:23160280

MetaGenSense: A web-application for analysis and exploration of high throughput sequencing metagenomic data

PubMed Central

Denis, Jean-Baptiste; Vandenbogaert, Mathias; Caro, Valérie

2016-01-01

The detection and characterization of emerging infectious agents has been a continuing public health concern. High Throughput Sequencing (HTS) or Next-Generation Sequencing (NGS) technologies have proven to be promising approaches for efficient and unbiased detection of pathogens in complex biological samples, providing access to comprehensive analyses. As NGS approaches typically yield millions of putatively representative reads per sample, efficient data management and visualization resources have become mandatory. Most usually, those resources are implemented through a dedicated Laboratory Information Management System (LIMS), solely to provide perspective regarding the available information. We developed an easily deployable web-interface, facilitating management and bioinformatics analysis of metagenomics data-samples. It was engineered to run associated and dedicated Galaxy workflows for the detection and eventually classification of pathogens. The web application allows easy interaction with existing Galaxy metagenomic workflows, facilitates the organization, exploration and aggregation of the most relevant sample-specific sequences among millions of genomic sequences, allowing them to determine their relative abundance, and associate them to the most closely related organism or pathogen. The user-friendly Django-Based interface, associates the users’ input data and its metadata through a bio-IT provided set of resources (a Galaxy instance, and both sufficient storage and grid computing power). Galaxy is used to handle and analyze the user’s input data from loading, indexing, mapping, assembly and DB-searches. Interaction between our application and Galaxy is ensured by the BioBlend library, which gives API-based access to Galaxy’s main features. Metadata about samples, runs, as well as the workflow results are stored in the LIMS. For metagenomic classification and exploration purposes, we show, as a proof of concept, that integration of intuitive

Toward Accurate and Quantitative Comparative Metagenomics

PubMed Central

Nayfach, Stephen; Pollard, Katherine S.

2016-01-01

Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. PMID:27565341

Metagenomic applications in environmental monitoring and bioremediation

DOE PAGES

Techtmann, Stephen M.; Hazen, Terry C.

2016-01-01

With the rapid advances in sequencing technology, the cost of sequencing has dramatically dropped and the scale of sequencing projects has increased accordingly. This has provided the opportunity for the routine use of sequencing techniques in the monitoring of environmental microbes. While metagenomic applications have been routinely applied to better understand the ecology and diversity of microbes, their use in environmental monitoring and bioremediation is increasingly common. In this review we seek to provide an overview of some of the metagenomic techniques used in environmental systems biology, addressing their application and limitation. We will also provide several recent examples ofmore » the application of metagenomics to bioremediation. We discuss examples where microbial communities have been used to predict the presence and extent of contamination, examples of how metagenomics can be used to characterize the process of natural attenuation by unculturable microbes, as well as examples detailing the use of metagenomics to understand the impact of biostimulation on microbial communities.« less

Metagenomic applications in environmental monitoring and bioremediation.

PubMed

Techtmann, Stephen M; Hazen, Terry C

2016-10-01

With the rapid advances in sequencing technology, the cost of sequencing has dramatically dropped and the scale of sequencing projects has increased accordingly. This has provided the opportunity for the routine use of sequencing techniques in the monitoring of environmental microbes. While metagenomic applications have been routinely applied to better understand the ecology and diversity of microbes, their use in environmental monitoring and bioremediation is increasingly common. In this review we seek to provide an overview of some of the metagenomic techniques used in environmental systems biology, addressing their application and limitation. We will also provide several recent examples of the application of metagenomics to bioremediation. We discuss examples where microbial communities have been used to predict the presence and extent of contamination, examples of how metagenomics can be used to characterize the process of natural attenuation by unculturable microbes, as well as examples detailing the use of metagenomics to understand the impact of biostimulation on microbial communities.

Single Cell and Metagenomic Assemblies: Biology Drives Technical Choices and Goals (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Stepanauskas, Ramunas

2018-02-06

DOE JGI's Tanja Woyke, chair of the Single Cells and Metagenomes session, delivers an introduction, followed by Bigelow Laboratory's Ramunas Stepanauskas on "Single Cell and Metagenomic Assemblies: Biology Drives Technical Choices and Goals" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Toward Accurate and Quantitative Comparative Metagenomics.

PubMed

Nayfach, Stephen; Pollard, Katherine S

2016-08-25

Shotgun metagenomics and computational analysis are used to compare the taxonomic and functional profiles of microbial communities. Leveraging this approach to understand roles of microbes in human biology and other environments requires quantitative data summaries whose values are comparable across samples and studies. Comparability is currently hampered by the use of abundance statistics that do not estimate a meaningful parameter of the microbial community and biases introduced by experimental protocols and data-cleaning approaches. Addressing these challenges, along with improving study design, data access, metadata standardization, and analysis tools, will enable accurate comparative metagenomics. We envision a future in which microbiome studies are replicable and new metagenomes are easily and rapidly integrated with existing data. Only then can the potential of metagenomics for predictive ecological modeling, well-powered association studies, and effective microbiome medicine be fully realized. Copyright © 2016 Elsevier Inc. All rights reserved.

Challenges and Opportunities of Airborne Metagenomics

PubMed Central

Behzad, Hayedeh; Gojobori, Takashi; Mineta, Katsuhiko

2015-01-01

Recent metagenomic studies of environments, such as marine and soil, have significantly enhanced our understanding of the diverse microbial communities living in these habitats and their essential roles in sustaining vast ecosystems. The increase in the number of publications related to soil and marine metagenomics is in sharp contrast to those of air, yet airborne microbes are thought to have significant impacts on many aspects of our lives from their potential roles in atmospheric events such as cloud formation, precipitation, and atmospheric chemistry to their major impact on human health. In this review, we will discuss the current progress in airborne metagenomics, with a special focus on exploring the challenges and opportunities of undertaking such studies. The main challenges of conducting metagenomic studies of airborne microbes are as follows: 1) Low density of microorganisms in the air, 2) efficient retrieval of microorganisms from the air, 3) variability in airborne microbial community composition, 4) the lack of standardized protocols and methodologies, and 5) DNA sequencing and bioinformatics-related challenges. Overcoming these challenges could provide the groundwork for comprehensive analysis of airborne microbes and their potential impact on the atmosphere, global climate, and our health. Metagenomic studies offer a unique opportunity to examine viral and bacterial diversity in the air and monitor their spread locally or across the globe, including threats from pathogenic microorganisms. Airborne metagenomic studies could also lead to discoveries of novel genes and metabolic pathways relevant to meteorological and industrial applications, environmental bioremediation, and biogeochemical cycles. PMID:25953766

Metagenomics and novel gene discovery

PubMed Central

Culligan, Eamonn P; Sleator, Roy D; Marchesi, Julian R; Hill, Colin

2014-01-01

Metagenomics provides a means of assessing the total genetic pool of all the microbes in a particular environment, in a culture-independent manner. It has revealed unprecedented diversity in microbial community composition, which is further reflected in the encoded functional diversity of the genomes, a large proportion of which consists of novel genes. Herein, we review both sequence-based and functional metagenomic methods to uncover novel genes and outline some of the associated problems of each type of approach, as well as potential solutions. Furthermore, we discuss the potential for metagenomic biotherapeutic discovery, with a particular focus on the human gut microbiome and finally, we outline how the discovery of novel genes may be used to create bioengineered probiotics. PMID:24317337

Survey of (Meta)genomic Approaches for Understanding Microbial Community Dynamics.

PubMed

Sharma, Anukriti; Lal, Rup

2017-03-01

Advancement in the next generation sequencing technologies has led to evolution of the field of genomics and metagenomics in a slim duration with nominal cost at precipitous higher rate. While metagenomics and genomics can be separately used to reveal the culture-independent and culture-based microbial evolution, respectively, (meta)genomics together can be used to demonstrate results at population level revealing in-depth complex community interactions for specific ecotypes. The field of metagenomics which started with answering "who is out there?" based on 16S rRNA gene has evolved immensely with the precise organismal reconstruction at species/strain level from the deeply covered metagenome data outweighing the need to isolate bacteria of which 99% are de facto non-cultivable. In this review we have underlined the appeal of metagenomic-derived genomes in providing insights into the evolutionary patterns, growth dynamics, genome/gene-specific sweeps, and durability of environmental pressures. We have demonstrated the use of culture-based genomics and environmental shotgun metagenome data together to elucidate environment specific genome modulations via metagenomic recruitments in terms of gene loss/gain, accessory and core-genome extent. We further illustrated the benefit of (meta)genomics in the understanding of infectious diseases by deducing the relationship between human microbiota and clinical microbiology. This review summarizes the technological advances in the (meta)genomic strategies using the genome and metagenome datasets together to increase the resolution of microbial population studies.

EBI metagenomics in 2016 - an expanding and evolving resource for the analysis and archiving of metagenomic data

PubMed Central

Mitchell, Alex; Bucchini, Francois; Cochrane, Guy; Denise, Hubert; Hoopen, Petra ten; Fraser, Matthew; Pesseat, Sebastien; Potter, Simon; Scheremetjew, Maxim; Sterk, Peter; Finn, Robert D.

2016-01-01

EBI metagenomics (https://www.ebi.ac.uk/metagenomics/) is a freely available hub for the analysis and archiving of metagenomic and metatranscriptomic data. Over the last 2 years, the resource has undergone rapid growth, with an increase of over five-fold in the number of processed samples and consequently represents one of the largest resources of analysed shotgun metagenomes. Here, we report the status of the resource in 2016 and give an overview of new developments. In particular, we describe updates to data content, a complete overhaul of the analysis pipeline, streamlining of data presentation via the website and the development of a new web based tool to compare functional analyses of sequence runs within a study. We also highlight two of the higher profile projects that have been analysed using the resource in the last year: the oceanographic projects Ocean Sampling Day and Tara Oceans. PMID:26582919

Metazen – metadata capture for metagenomes

DOE PAGES

Bischof, Jared; Harrison, Travis; Paczian, Tobias; ...

2014-12-08

Background: As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. These tools are not specifically designed for metagenomic surveys; in particular, they lack themore » appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Results: Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Conclusion: Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.« less

Metazen – metadata capture for metagenomes

PubMed Central

2014-01-01

Background As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. Unfortunately, these tools are not specifically designed for metagenomic surveys; in particular, they lack the appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Results Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Conclusions Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility. PMID:25780508

Metazen – metadata capture for metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bischof, Jared; Harrison, Travis; Paczian, Tobias

Background: As the impact and prevalence of large-scale metagenomic surveys grow, so does the acute need for more complete and standards compliant metadata. Metadata (data describing data) provides an essential complement to experimental data, helping to answer questions about its source, mode of collection, and reliability. Metadata collection and interpretation have become vital to the genomics and metagenomics communities, but considerable challenges remain, including exchange, curation, and distribution. Currently, tools are available for capturing basic field metadata during sampling, and for storing, updating and viewing it. These tools are not specifically designed for metagenomic surveys; in particular, they lack themore » appropriate metadata collection templates, a centralized storage repository, and a unique ID linking system that can be used to easily port complete and compatible metagenomic metadata into widely used assembly and sequence analysis tools. Results: Metazen was developed as a comprehensive framework designed to enable metadata capture for metagenomic sequencing projects. Specifically, Metazen provides a rapid, easy-to-use portal to encourage early deposition of project and sample metadata. Conclusion: Metazen is an interactive tool that aids users in recording their metadata in a complete and valid format. A defined set of mandatory fields captures vital information, while the option to add fields provides flexibility.« less

MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads.

PubMed

Petersen, Thomas Nordahl; Lukjancenko, Oksana; Thomsen, Martin Christen Frølund; Maddalena Sperotto, Maria; Lund, Ole; Møller Aarestrup, Frank; Sicheritz-Pontén, Thomas

2017-01-01

An increasing amount of species and gene identification studies rely on the use of next generation sequence analysis of either single isolate or metagenomics samples. Several methods are available to perform taxonomic annotations and a previous metagenomics benchmark study has shown that a vast number of false positive species annotations are a problem unless thresholds or post-processing are applied to differentiate between correct and false annotations. MGmapper is a package to process raw next generation sequence data and perform reference based sequence assignment, followed by a post-processing analysis to produce reliable taxonomy annotation at species and strain level resolution. An in-vitro bacterial mock community sample comprised of 8 genuses, 11 species and 12 strains was previously used to benchmark metagenomics classification methods. After applying a post-processing filter, we obtained 100% correct taxonomy assignments at species and genus level. A sensitivity and precision at 75% was obtained for strain level annotations. A comparison between MGmapper and Kraken at species level, shows MGmapper assigns taxonomy at species level using 84.8% of the sequence reads, compared to 70.5% for Kraken and both methods identified all species with no false positives. Extensive read count statistics are provided in plain text and excel sheets for both rejected and accepted taxonomy annotations. The use of custom databases is possible for the command-line version of MGmapper, and the complete pipeline is freely available as a bitbucked package (https://bitbucket.org/genomicepidemiology/mgmapper). A web-version (https://cge.cbs.dtu.dk/services/MGmapper) provides the basic functionality for analysis of small fastq datasets.

RubisCO Gene Clusters Found in a Metagenome Microarray from Acid Mine Drainage

PubMed Central

Guo, Xue; Yin, Huaqun; Cong, Jing; Dai, Zhimin; Liang, Yili

2013-01-01

The enzyme responsible for carbon dioxide fixation in the Calvin cycle, ribulose-1,5-bisphosphate carboxylase/oxygenase (RubisCO), is always detected as a phylogenetic marker to analyze the distribution and activity of autotrophic bacteria. However, such an approach provides no indication as to the significance of genomic content and organization. Horizontal transfers of RubisCO genes occurring in eubacteria and plastids may seriously affect the credibility of this approach. Here, we presented a new method to analyze the diversity and genomic content of RubisCO genes in acid mine drainage (AMD). A metagenome microarray containing 7,776 large-insertion fosmids was constructed to quickly screen genome fragments containing RubisCO form I large-subunit genes (cbbL). Forty-six cbbL-containing fosmids were detected, and six fosmids were fully sequenced. To evaluate the reliability of the metagenome microarray and understand the microbial community in AMD, the diversities of cbbL and the 16S rRNA gene were analyzed. Fosmid sequences revealed that the form I RubisCO gene cluster could be subdivided into form IA and IB RubisCO gene clusters in AMD, because of significant divergences in molecular phylogenetics and conservative genomic organization. Interestingly, the form I RubisCO gene cluster coexisted with the form II RubisCO gene cluster in one fosmid genomic fragment. Phylogenetic analyses revealed that horizontal transfers of RubisCO genes may occur widely in AMD, which makes the evolutionary history of RubisCO difficult to reconcile with organismal phylogeny. PMID:23335778

Rapid and efficient method to extract metagenomic DNA from estuarine sediments.

PubMed

Shamim, Kashif; Sharma, Jaya; Dubey, Santosh Kumar

2017-07-01

Metagenomic DNA from sediments of selective estuaries of Goa, India was extracted using a simple, fast, efficient and environment friendly method. The recovery of pure metagenomic DNA from our method was significantly high as compared to other well-known methods since the concentration of recovered metagenomic DNA ranged from 1185.1 to 4579.7 µg/g of sediment. The purity of metagenomic DNA was also considerably high as the ratio of absorbance at 260 and 280 nm ranged from 1.88 to 1.94. Therefore, the recovered metagenomic DNA was directly used to perform various molecular biology experiments viz. restriction digestion, PCR amplification, cloning and metagenomic library construction. This clearly proved that our protocol for metagenomic DNA extraction using silica gel efficiently removed the contaminants and prevented shearing of the metagenomic DNA. Thus, this modified method can be used to recover pure metagenomic DNA from various estuarine sediments in a rapid, efficient and eco-friendly manner.

Challenges and opportunities of airborne metagenomics.

PubMed

Behzad, Hayedeh; Gojobori, Takashi; Mineta, Katsuhiko

2015-05-06

Recent metagenomic studies of environments, such as marine and soil, have significantly enhanced our understanding of the diverse microbial communities living in these habitats and their essential roles in sustaining vast ecosystems. The increase in the number of publications related to soil and marine metagenomics is in sharp contrast to those of air, yet airborne microbes are thought to have significant impacts on many aspects of our lives from their potential roles in atmospheric events such as cloud formation, precipitation, and atmospheric chemistry to their major impact on human health. In this review, we will discuss the current progress in airborne metagenomics, with a special focus on exploring the challenges and opportunities of undertaking such studies. The main challenges of conducting metagenomic studies of airborne microbes are as follows: 1) Low density of microorganisms in the air, 2) efficient retrieval of microorganisms from the air, 3) variability in airborne microbial community composition, 4) the lack of standardized protocols and methodologies, and 5) DNA sequencing and bioinformatics-related challenges. Overcoming these challenges could provide the groundwork for comprehensive analysis of airborne microbes and their potential impact on the atmosphere, global climate, and our health. Metagenomic studies offer a unique opportunity to examine viral and bacterial diversity in the air and monitor their spread locally or across the globe, including threats from pathogenic microorganisms. Airborne metagenomic studies could also lead to discoveries of novel genes and metabolic pathways relevant to meteorological and industrial applications, environmental bioremediation, and biogeochemical cycles. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Technical Report on Modeling for Quasispecies Abundance Inference with Confidence Intervals from Metagenomic Sequence Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McLoughlin, K.

2016-01-11

The overall aim of this project is to develop a software package, called MetaQuant, that can determine the constituents of a complex microbial sample and estimate their relative abundances by analysis of metagenomic sequencing data. The goal for Task 1 is to create a generative model describing the stochastic process underlying the creation of sequence read pairs in the data set. The stages in this generative process include the selection of a source genome sequence for each read pair, with probability dependent on its abundance in the sample. The other stages describe the evolution of the source genome from itsmore » nearest common ancestor with a reference genome, breakage of the source DNA into short fragments, and the errors in sequencing the ends of the fragments to produce read pairs.« less

Comparative Viral Metagenomics of Environmental Samples from Korea

PubMed Central

Kim, Min-Soo; Whon, Tae Woong

2013-01-01

The introduction of metagenomics into the field of virology has facilitated the exploration of viral communities in various natural habitats. Understanding the viral ecology of a variety of sample types throughout the biosphere is important per se, but it also has potential applications in clinical and diagnostic virology. However, the procedures used by viral metagenomics may produce technical errors, such as amplification bias, while public viral databases are very limited, which may hamper the determination of the viral diversity in samples. This review considers the current state of viral metagenomics, based on examples from Korean viral metagenomic studies-i.e., rice paddy soil, fermented foods, human gut, seawater, and the near-surface atmosphere. Viral metagenomics has become widespread due to various methodological developments, and much attention has been focused on studies that consider the intrinsic role of viruses that interact with their hosts. PMID:24124407

Phylogenetic screening of a bacterial, metagenomic library using homing endonuclease restriction and marker insertion

PubMed Central

Yung, Pui Yi; Burke, Catherine; Lewis, Matt; Egan, Suhelen; Kjelleberg, Staffan; Thomas, Torsten

2009-01-01

Metagenomics provides access to the uncultured majority of the microbial world. The approaches employed in this field have, however, had limited success in linking functional genes to the taxonomic or phylogenetic origin of the organism they belong to. Here we present an efficient strategy to recover environmental DNA fragments that contain phylogenetic marker genes from metagenomic libraries. Our method involves the cleavage of 23S ribsosmal RNA (rRNA) genes within pooled library clones by the homing endonuclease I-CeuI followed by the insertion and selection of an antibiotic resistance cassette. This approach was applied to screen a library of 6500 fosmid clones derived from the microbial community associated with the sponge Cymbastela concentrica. Several fosmid clones were recovered after the screen and detailed phylogenetic and taxonomic assignment based on the rRNA gene showed that they belong to previously unknown organisms. In addition, compositional features of these fosmid clones were used to classify and taxonomically assign a dataset of environmental shotgun sequences. Our approach represents a valuable tool for the analysis of rapidly increasing, environmental DNA sequencing information. PMID:19767618

Antibiotic Resistome: Improving Detection and Quantification Accuracy for Comparative Metagenomics.

PubMed

Elbehery, Ali H A; Aziz, Ramy K; Siam, Rania

2016-04-01

The unprecedented rise of life-threatening antibiotic resistance (AR), combined with the unparalleled advances in DNA sequencing of genomes and metagenomes, has pushed the need for in silico detection of the resistance potential of clinical and environmental metagenomic samples through the quantification of AR genes (i.e., genes conferring antibiotic resistance). Therefore, determining an optimal methodology to quantitatively and accurately assess AR genes in a given environment is pivotal. Here, we optimized and improved existing AR detection methodologies from metagenomic datasets to properly consider AR-generating mutations in antibiotic target genes. Through comparative metagenomic analysis of previously published AR gene abundance in three publicly available metagenomes, we illustrate how mutation-generated resistance genes are either falsely assigned or neglected, which alters the detection and quantitation of the antibiotic resistome. In addition, we inspected factors influencing the outcome of AR gene quantification using metagenome simulation experiments, and identified that genome size, AR gene length, total number of metagenomics reads and selected sequencing platforms had pronounced effects on the level of detected AR. In conclusion, our proposed improvements in the current methodologies for accurate AR detection and resistome assessment show reliable results when tested on real and simulated metagenomic datasets.

Phylogenetic analysis of a spontaneous cocoa bean fermentation metagenome reveals new insights into its bacterial and fungal community diversity.

PubMed

Illeghems, Koen; De Vuyst, Luc; Papalexandratou, Zoi; Weckx, Stefan

2012-01-01

This is the first report on the phylogenetic analysis of the community diversity of a single spontaneous cocoa bean box fermentation sample through a metagenomic approach involving 454 pyrosequencing. Several sequence-based and composition-based taxonomic profiling tools were used and evaluated to avoid software-dependent results and their outcome was validated by comparison with previously obtained culture-dependent and culture-independent data. Overall, this approach revealed a wider bacterial (mainly γ-Proteobacteria) and fungal diversity than previously found. Further, the use of a combination of different classification methods, in a software-independent way, helped to understand the actual composition of the microbial ecosystem under study. In addition, bacteriophage-related sequences were found. The bacterial diversity depended partially on the methods used, as composition-based methods predicted a wider diversity than sequence-based methods, and as classification methods based solely on phylogenetic marker genes predicted a more restricted diversity compared with methods that took all reads into account. The metagenomic sequencing analysis identified Hanseniaspora uvarum, Hanseniaspora opuntiae, Saccharomyces cerevisiae, Lactobacillus fermentum, and Acetobacter pasteurianus as the prevailing species. Also, the presence of occasional members of the cocoa bean fermentation process was revealed (such as Erwinia tasmaniensis, Lactobacillus brevis, Lactobacillus casei, Lactobacillus rhamnosus, Lactococcus lactis, Leuconostoc mesenteroides, and Oenococcus oeni). Furthermore, the sequence reads associated with viral communities were of a restricted diversity, dominated by Myoviridae and Siphoviridae, and reflecting Lactobacillus as the dominant host. To conclude, an accurate overview of all members of a cocoa bean fermentation process sample was revealed, indicating the superiority of metagenomic sequencing over previously used techniques.

Metagenomic Assembly Reveals Hosts of Antibiotic Resistance Genes and the Shared Resistome in Pig, Chicken, and Human Feces.

PubMed

Ma, Liping; Xia, Yu; Li, Bing; Yang, Ying; Li, Li-Guan; Tiedje, James M; Zhang, Tong

2016-01-05

The risk associated with antibiotic resistance disseminating from animal and human feces is an urgent public issue. In the present study, we sought to establish a pipeline for annotating antibiotic resistance genes (ARGs) based on metagenomic assembly to investigate ARGs and their co-occurrence with associated genetic elements. Genetic elements found on the assembled genomic fragments include mobile genetic elements (MGEs) and metal resistance genes (MRGs). We then explored the hosts of these resistance genes and the shared resistome of pig, chicken and human fecal samples. High levels of tetracycline, multidrug, erythromycin, and aminoglycoside resistance genes were discovered in these fecal samples. In particular, significantly high level of ARGs (7762 ×/Gb) was detected in adult chicken feces, indicating higher ARG contamination level than other fecal samples. Many ARGs arrangements (e.g., macA-macB and tetA-tetR) were discovered shared by chicken, pig and human feces. In addition, MGEs such as the aadA5-dfrA17-carrying class 1 integron were identified on an assembled scaffold of chicken feces, and are carried by human pathogens. Differential coverage binning analysis revealed significant ARG enrichment in adult chicken feces. A draft genome, annotated as multidrug resistant Escherichia coli, was retrieved from chicken feces metagenomes and was determined to carry diverse ARGs (multidrug, acriflavine, and macrolide). The present study demonstrates the determination of ARG hosts and the shared resistome from metagenomic data sets and successfully establishes the relationship between ARGs, hosts, and environments. This ARG annotation pipeline based on metagenomic assembly will help to bridge the knowledge gaps regarding ARG-associated genes and ARG hosts with metagenomic data sets. Moreover, this pipeline will facilitate the evaluation of environmental risks in the genetic context of ARGs.

Taxonomy-aware feature engineering for microbiome classification.

PubMed

Oudah, Mai; Henschel, Andreas

2018-06-15

What is a healthy microbiome? The pursuit of this and many related questions, especially in light of the recently recognized microbial component in a wide range of diseases has sparked a surge in metagenomic studies. They are often not simply attributable to a single pathogen but rather are the result of complex ecological processes. Relatedly, the increasing DNA sequencing depth and number of samples in metagenomic case-control studies enabled the applicability of powerful statistical methods, e.g. Machine Learning approaches. For the latter, the feature space is typically shaped by the relative abundances of operational taxonomic units, as determined by cost-effective phylogenetic marker gene profiles. While a substantial body of microbiome/microbiota research involves unsupervised and supervised Machine Learning, very little attention has been put on feature selection and engineering. We here propose the first algorithm to exploit phylogenetic hierarchy (i.e. an all-encompassing taxonomy) in feature engineering for microbiota classification. The rationale is to exploit the often mono- or oligophyletic distribution of relevant (but hidden) traits by virtue of taxonomic abstraction. The algorithm is embedded in a comprehensive microbiota classification pipeline, which we applied to a diverse range of datasets, distinguishing healthy from diseased microbiota samples. We demonstrate substantial improvements over the state-of-the-art microbiota classification tools in terms of classification accuracy, regardless of the actual Machine Learning technique while using drastically reduced feature spaces. Moreover, generalized features bear great explanatory value: they provide a concise description of conditions and thus help to provide pathophysiological insights. Indeed, the automatically and reproducibly derived features are consistent with previously published domain expert analyses.

MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads

PubMed Central

Lukjancenko, Oksana; Thomsen, Martin Christen Frølund; Maddalena Sperotto, Maria; Lund, Ole; Møller Aarestrup, Frank; Sicheritz-Pontén, Thomas

2017-01-01

An increasing amount of species and gene identification studies rely on the use of next generation sequence analysis of either single isolate or metagenomics samples. Several methods are available to perform taxonomic annotations and a previous metagenomics benchmark study has shown that a vast number of false positive species annotations are a problem unless thresholds or post-processing are applied to differentiate between correct and false annotations. MGmapper is a package to process raw next generation sequence data and perform reference based sequence assignment, followed by a post-processing analysis to produce reliable taxonomy annotation at species and strain level resolution. An in-vitro bacterial mock community sample comprised of 8 genuses, 11 species and 12 strains was previously used to benchmark metagenomics classification methods. After applying a post-processing filter, we obtained 100% correct taxonomy assignments at species and genus level. A sensitivity and precision at 75% was obtained for strain level annotations. A comparison between MGmapper and Kraken at species level, shows MGmapper assigns taxonomy at species level using 84.8% of the sequence reads, compared to 70.5% for Kraken and both methods identified all species with no false positives. Extensive read count statistics are provided in plain text and excel sheets for both rejected and accepted taxonomy annotations. The use of custom databases is possible for the command-line version of MGmapper, and the complete pipeline is freely available as a bitbucked package (https://bitbucket.org/genomicepidemiology/mgmapper). A web-version (https://cge.cbs.dtu.dk/services/MGmapper) provides the basic functionality for analysis of small fastq datasets. PMID:28467460

Comparative analysis of sugarcane bagasse metagenome reveals unique and conserved biomass-degrading enzymes among lignocellulolytic microbial communities.

PubMed

Mhuantong, Wuttichai; Charoensawan, Varodom; Kanokratana, Pattanop; Tangphatsornruang, Sithichoke; Champreda, Verawat

2015-01-01

As one of the most abundant agricultural wastes, sugarcane bagasse is largely under-exploited, but it possesses a great potential for the biofuel, fermentation, and cellulosic biorefinery industries. It also provides a unique ecological niche, as the microbes in this lignocellulose-rich environment thrive in relatively high temperatures (50°C) with varying microenvironments of aerobic surface to anoxic interior. The microbial community in bagasse thus presents a good resource for the discovery and characterization of new biomass-degrading enzymes; however, it remains largely unexplored. We have constructed a fosmid library of sugarcane bagasse and obtained the largest bagasse metagenome to date. A taxonomic classification of the bagasse metagenome reviews the predominance of Proteobacteria, which are also found in high abundance in other aerobic environments. Based on the functional characterization of biomass-degrading enzymes, we have demonstrated that the bagasse microbial community benefits from a large repertoire of lignocellulolytic enzymes, which allows them to digest different components of lignocelluoses into single molecule sugars. Comparative genomic analyses with other lignocellulolytic and non-lignocellulolytic metagenomes show that microbial communities are taxonomically separable by their aerobic "open" or anoxic "closed" environments. Importantly, a functional analysis of lignocellulose-active genes (based on the CAZy classifications) reveals core enzymes highly conserved within the lignocellulolytic group, regardless of their taxonomic compositions. Cellulases, in particular, are markedly more pronounced compared to the non-lignocellulolytic group. In addition to the core enzymes, the bagasse fosmid library also contains some uniquely enriched glycoside hydrolases, as well as a large repertoire of the newly defined auxiliary activity proteins. Our study demonstrates a conservation and diversification of carbohydrate-active genes among diverse

Exploiting HPC Platforms for Metagenomics: Challenges and Opportunities (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Canon, Shane

2018-01-24

DOE JGI's Zhong Wang, chair of the High-performance Computing session, gives a brief introduction before Berkeley Lab's Shane Canon talks about "Exploiting HPC Platforms for Metagenomics: Challenges and Opportunities" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

MetaSort untangles metagenome assembly by reducing microbial community complexity

PubMed Central

Ji, Peifeng; Zhang, Yanming; Wang, Jinfeng; Zhao, Fangqing

2017-01-01

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities. PMID:28112173

PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures

PubMed Central

Lipinski, Leszek; Dziembowski, Andrzej

2018-01-01

Abstract Plasmids are mobile genetics elements that play an important role in the environmental adaptation of microorganisms. Although plasmids are usually analyzed in cultured microorganisms, there is a need for methods that allow for the analysis of pools of plasmids (plasmidomes) in environmental samples. To that end, several molecular biology and bioinformatics methods have been developed; however, they are limited to environments with low diversity and cannot recover large plasmids. Here, we present PlasFlow, a novel tool based on genomic signatures that employs a neural network approach for identification of bacterial plasmid sequences in environmental samples. PlasFlow can recover plasmid sequences from assembled metagenomes without any prior knowledge of the taxonomical or functional composition of samples with an accuracy up to 96%. It can also recover sequences of both circular and linear plasmids and can perform initial taxonomical classification of sequences. Compared to other currently available tools, PlasFlow demonstrated significantly better performance on test datasets. Analysis of two samples from heavy metal-contaminated microbial mats revealed that plasmids may constitute an important fraction of their metagenomes and carry genes involved in heavy-metal homeostasis, proving the pivotal role of plasmids in microorganism adaptation to environmental conditions. PMID:29346586

Strain/species identification in metagenomes using genome-specific markers

PubMed Central

Tu, Qichao; He, Zhili; Zhou, Jizhong

2014-01-01

Shotgun metagenome sequencing has become a fast, cheap and high-throughput technology for characterizing microbial communities in complex environments and human body sites. However, accurate identification of microorganisms at the strain/species level remains extremely challenging. We present a novel k-mer-based approach, termed GSMer, that identifies genome-specific markers (GSMs) from currently sequenced microbial genomes, which were then used for strain/species-level identification in metagenomes. Using 5390 sequenced microbial genomes, 8 770 321 50-mer strain-specific and 11 736 360 species-specific GSMs were identified for 4088 strains and 2005 species (4933 strains), respectively. The GSMs were first evaluated against mock community metagenomes, recently sequenced genomes and real metagenomes from different body sites, suggesting that the identified GSMs were specific to their targeting genomes. Sensitivity evaluation against synthetic metagenomes with different coverage suggested that 50 GSMs per strain were sufficient to identify most microbial strains with ≥0.25× coverage, and 10% of selected GSMs in a database should be detected for confident positive callings. Application of GSMs identified 45 and 74 microbial strains/species significantly associated with type 2 diabetes patients and obese/lean individuals from corresponding gastrointestinal tract metagenomes, respectively. Our result agreed with previous studies but provided strain-level information. The approach can be directly applied to identify microbial strains/species from raw metagenomes, without the effort of complex data pre-processing. PMID:24523352

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification.

PubMed

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-05-01

Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. ivan.borozan@gmail.com Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Integrating alignment-based and alignment-free sequence similarity measures for biological sequence classification

PubMed Central

Borozan, Ivan; Watt, Stuart; Ferretti, Vincent

2015-01-01

Motivation: Alignment-based sequence similarity searches, while accurate for some type of sequences, can produce incorrect results when used on more divergent but functionally related sequences that have undergone the sequence rearrangements observed in many bacterial and viral genomes. Here, we propose a classification model that exploits the complementary nature of alignment-based and alignment-free similarity measures with the aim to improve the accuracy with which DNA and protein sequences are characterized. Results: Our model classifies sequences using a combined sequence similarity score calculated by adaptively weighting the contribution of different sequence similarity measures. Weights are determined independently for each sequence in the test set and reflect the discriminatory ability of individual similarity measures in the training set. Because the similarity between some sequences is determined more accurately with one type of measure rather than another, our classifier allows different sets of weights to be associated with different sequences. Using five different similarity measures, we show that our model significantly improves the classification accuracy over the current composition- and alignment-based models, when predicting the taxonomic lineage for both short viral sequence fragments and complete viral sequences. We also show that our model can be used effectively for the classification of reads from a real metagenome dataset as well as protein sequences. Availability and implementation: All the datasets and the code used in this study are freely available at https://collaborators.oicr.on.ca/vferretti/borozan_csss/csss.html. Contact: ivan.borozan@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573913

MetaCRAST: reference-guided extraction of CRISPR spacers from unassembled metagenomes.

PubMed

Moller, Abraham G; Liang, Chun

2017-01-01

Clustered regularly interspaced short palindromic repeat (CRISPR) systems are the adaptive immune systems of bacteria and archaea against viral infection. While CRISPRs have been exploited as a tool for genetic engineering, their spacer sequences can also provide valuable insights into microbial ecology by linking environmental viruses to their microbial hosts. Despite this importance, metagenomic CRISPR detection remains a major challenge. Here we present a reference-guided CRISPR spacer detection tool ( Meta genomic C RISPR R eference- A ided S earch T ool-MetaCRAST) that constrains searches based on user-specified direct repeats (DRs). These DRs could be expected from assembly or taxonomic profiles of metagenomes. We compared the performance of MetaCRAST to those of two existing metagenomic CRISPR detection tools-Crass and MinCED-using both real and simulated acid mine drainage (AMD) and enhanced biological phosphorus removal (EBPR) metagenomes. Our evaluation shows MetaCRAST improves CRISPR spacer detection in real metagenomes compared to the de novo CRISPR detection methods Crass and MinCED. Evaluation on simulated metagenomes show it performs better than de novo tools for Illumina metagenomes and comparably for 454 metagenomes. It also has comparable performance dependence on read length and community composition, run time, and accuracy to these tools. MetaCRAST is implemented in Perl, parallelizable through the Many Core Engine (MCE), and takes metagenomic sequence reads and direct repeat queries (FASTA or FASTQ) as input. It is freely available for download at https://github.com/molleraj/MetaCRAST.

Shotgun metagenomic data streams: surfing without fear

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berendzen, Joel R

2010-12-06

Timely information about bio-threat prevalence, consequence, propagation, attribution, and mitigation is needed to support decision-making, both routinely and in a crisis. One DNA sequencer can stream 25 Gbp of information per day, but sampling strategies and analysis techniques are needed to turn raw sequencing power into actionable knowledge. Shotgun metagenomics can enable biosurveillance at the level of a single city, hospital, or airplane. Metagenomics characterizes viruses and bacteria from complex environments such as soil, air filters, or sewage. Unlike targeted-primer-based sequencing, shotgun methods are not blind to sequences that are truly novel, and they can measure absolute prevalence. Shotgun metagenomicmore » sampling can be non-invasive, efficient, and inexpensive while being informative. We have developed analysis techniques for shotgun metagenomic sequencing that rely upon phylogenetic signature patterns. They work by indexing local sequence patterns in a manner similar to web search engines. Our methods are laptop-fast and favorable scaling properties ensure they will be sustainable as sequencing methods grow. We show examples of application to soil metagenomic samples.« less

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly

Comparative metagenomics of microbial communities inhabiting deep-sea hydrothermal vent chimneys with contrasting chemistries

PubMed Central

Xie, Wei; Wang, Fengping; Guo, Lei; Chen, Zeling; Sievert, Stefan M; Meng, Jun; Huang, Guangrui; Li, Yuxin; Yan, Qingyu; Wu, Shan; Wang, Xin; Chen, Shangwu; He, Guangyuan; Xiao, Xiang; Xu, Anlong

2011-01-01

Deep-sea hydrothermal vent chimneys harbor a high diversity of largely unknown microorganisms. Although the phylogenetic diversity of these microorganisms has been described previously, the adaptation and metabolic potential of the microbial communities is only beginning to be revealed. A pyrosequencing approach was used to directly obtain sequences from a fosmid library constructed from a black smoker chimney 4143-1 in the Mothra hydrothermal vent field at the Juan de Fuca Ridge. A total of 308 034 reads with an average sequence length of 227 bp were generated. Comparative genomic analyses of metagenomes from a variety of environments by two-way clustering of samples and functional gene categories demonstrated that the 4143-1 metagenome clustered most closely with that from a carbonate chimney from Lost City. Both are highly enriched in genes for mismatch repair and homologous recombination, suggesting that the microbial communities have evolved extensive DNA repair systems to cope with the extreme conditions that have potential deleterious effects on the genomes. As previously reported for the Lost City microbiome, the metagenome of chimney 4143-1 exhibited a high proportion of transposases, implying that horizontal gene transfer may be a common occurrence in the deep-sea vent chimney biosphere. In addition, genes for chemotaxis and flagellar assembly were highly enriched in the chimney metagenomes, reflecting the adaptation of the organisms to the highly dynamic conditions present within the chimney walls. Reconstruction of the metabolic pathways revealed that the microbial community in the wall of chimney 4143-1 was mainly fueled by sulfur oxidation, putatively coupled to nitrate reduction to perform inorganic carbon fixation through the Calvin–Benson–Bassham cycle. On the basis of the genomic organization of the key genes of the carbon fixation and sulfur oxidation pathways contained in the large genomic fragments, both obligate and facultative

Environmental Metagenomics: The Data Assembly and Data Analysis Perspectives

NASA Astrophysics Data System (ADS)

Kumar, Vinay; Maitra, S. S.; Shukla, Rohit Nandan

2015-03-01

Novel gene finding is one of the emerging fields in the environmental research. In the past decades the research was focused mainly on the discovery of microorganisms which were capable of degrading a particular compound. A lot of methods are available in literature about the cultivation and screening of these novel microorganisms. All of these methods are efficient for screening of microbes which can be cultivated in the laboratory. Microorganisms which live in extreme conditions like hot springs, frozen glaciers, acid mine drainage, etc. cannot be cultivated in the laboratory, this is because of incomplete knowledge about their growth requirements like temperature, nutrients and their mutual dependence on each other. The microbes that can be cultivated correspond only to less than 1 % of the total microbes which are present in the earth. Rest of the 99 % of uncultivated majority remains inaccessible. Metagenomics transcends the culture requirements of microbes. In metagenomics DNA is directly extracted from the environmental samples such as soil, seawater, acid mine drainage etc., followed by construction and screening of metagenomic library. With the ongoing research, a huge amount of metagenomic data is accumulating. Understanding this data is an essential step to extract novel genes of industrial importance. Various bioinformatics tools have been designed to analyze and annotate the data produced from the metagenome. The Bio-informatic requirements of metagenomics data analysis are different in theory and practice. This paper reviews the tools that are available for metagenomic data analysis and the capability such tools—what they can do and their web availability.

Evaluating the Quantitative Capabilities of Metagenomic Analysis Software.

PubMed

Kerepesi, Csaba; Grolmusz, Vince

2016-05-01

DNA sequencing technologies are applied widely and frequently today to describe metagenomes, i.e., microbial communities in environmental or clinical samples, without the need for culturing them. These technologies usually return short (100-300 base-pairs long) DNA reads, and these reads are processed by metagenomic analysis software that assign phylogenetic composition-information to the dataset. Here we evaluate three metagenomic analysis software (AmphoraNet--a webserver implementation of AMPHORA2--, MG-RAST, and MEGAN5) for their capabilities of assigning quantitative phylogenetic information for the data, describing the frequency of appearance of the microorganisms of the same taxa in the sample. The difficulties of the task arise from the fact that longer genomes produce more reads from the same organism than shorter genomes, and some software assign higher frequencies to species with longer genomes than to those with shorter ones. This phenomenon is called the "genome length bias." Dozens of complex artificial metagenome benchmarks can be found in the literature. Because of the complexity of those benchmarks, it is usually difficult to judge the resistance of a metagenomic software to this "genome length bias." Therefore, we have made a simple benchmark for the evaluation of the "taxon-counting" in a metagenomic sample: we have taken the same number of copies of three full bacterial genomes of different lengths, break them up randomly to short reads of average length of 150 bp, and mixed the reads, creating our simple benchmark. Because of its simplicity, the benchmark is not supposed to serve as a mock metagenome, but if a software fails on that simple task, it will surely fail on most real metagenomes. We applied three software for the benchmark. The ideal quantitative solution would assign the same proportion to the three bacterial taxa. We have found that AMPHORA2/AmphoraNet gave the most accurate results and the other two software were under

DOE JGI Quality Metrics; Approaches to Scaling and Improving Metagenome Assembly (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Copeland, Alex; Brown, C. Titus

2011-10-13

DOE JGI's Alex Copeland on "DOE JGI Quality Metrics" and Michigan State University's C. Titus Brown on "Approaches to Scaling and Improving Metagenome Assembly" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

DOE JGI Quality Metrics; Approaches to Scaling and Improving Metagenome Assembly (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Copeland, Alex; Brown, C. Titus

2018-04-27

DOE JGI's Alex Copeland on "DOE JGI Quality Metrics" and Michigan State University's C. Titus Brown on "Approaches to Scaling and Improving Metagenome Assembly" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Effective Analysis of NGS Metagenomic Data with Ultra-Fast Clustering Algorithms (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Li, Weizhong

2018-02-12

San Diego Supercomputer Center's Weizhong Li on "Effective Analysis of NGS Metagenomic Data with Ultra-fast Clustering Algorithms" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Identifying Differentially Abundant Metabolic Pathways in Metagenomic Datasets

NASA Astrophysics Data System (ADS)

Liu, Bo; Pop, Mihai

Enabled by rapid advances in sequencing technology, metagenomic studies aim to characterize entire communities of microbes bypassing the need for culturing individual bacterial members. One major goal of such studies is to identify specific functional adaptations of microbial communities to their habitats. Here we describe a powerful analytical method (MetaPath) that can identify differentially abundant pathways in metagenomic data-sets, relying on a combination of metagenomic sequence data and prior metabolic pathway knowledge. We show that MetaPath outperforms other common approaches when evaluated on simulated datasets. We also demonstrate the power of our methods in analyzing two, publicly available, metagenomic datasets: a comparison of the gut microbiome of obese and lean twins; and a comparison of the gut microbiome of infant and adult subjects. We demonstrate that the subpathways identified by our method provide valuable insights into the biological activities of the microbiome.

Metagenomic studies of the Red Sea.

PubMed

Behzad, Hayedeh; Ibarra, Martin Augusto; Mineta, Katsuhiko; Gojobori, Takashi

2016-02-01

Metagenomics has significantly advanced the field of marine microbial ecology, revealing the vast diversity of previously unknown microbial life forms in different marine niches. The tremendous amount of data generated has enabled identification of a large number of microbial genes (metagenomes), their community interactions, adaptation mechanisms, and their potential applications in pharmaceutical and biotechnology-based industries. Comparative metagenomics reveals that microbial diversity is a function of the local environment, meaning that unique or unusual environments typically harbor novel microbial species with unique genes and metabolic pathways. The Red Sea has an abundance of unique characteristics; however, its microbiota is one of the least studied among marine environments. The Red Sea harbors approximately 25 hot anoxic brine pools, plus a vibrant coral reef ecosystem. Physiochemical studies describe the Red Sea as an oligotrophic environment that contains one of the warmest and saltiest waters in the world with year-round high UV radiations. These characteristics are believed to have shaped the evolution of microbial communities in the Red Sea. Over-representation of genes involved in DNA repair, high-intensity light responses, and osmoregulation were found in the Red Sea metagenomic databases suggesting acquisition of specific environmental adaptation by the Red Sea microbiota. The Red Sea brine pools harbor a diverse range of halophilic and thermophilic bacterial and archaeal communities, which are potential sources of enzymes for pharmaceutical and biotechnology-based application. Understanding the mechanisms of these adaptations and their function within the larger ecosystem could also prove useful in light of predicted global warming scenarios where global ocean temperatures are expected to rise by 1-3°C in the next few decades. In this review, we provide an overview of the published metagenomic studies that were conducted in the Red Sea, and

BioCreative Workshops for DOE Genome Sciences: Text Mining for Metagenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Cathy H.; Hirschman, Lynette

The objective of this project was to host BioCreative workshops to define and develop text mining tasks to meet the needs of the Genome Sciences community, focusing on metadata information extraction in metagenomics. Following the successful introduction of metagenomics at the BioCreative IV workshop, members of the metagenomics community and BioCreative communities continued discussion to identify candidate topics for a BioCreative metagenomics track for BioCreative V. Of particular interest was the capture of environmental and isolation source information from text. The outcome was to form a “community of interest” around work on the interactive EXTRACT system, which supported interactive taggingmore » of environmental and species data. This experiment is included in the BioCreative V virtual issue of Database. In addition, there was broad participation by members of the metagenomics community in the panels held at BioCreative V, leading to valuable exchanges between the text mining developers and members of the metagenomics research community. These exchanges are reflected in a number of the overview and perspective pieces also being captured in the BioCreative V virtual issue. Overall, this conversation has exposed the metagenomics researchers to the possibilities of text mining, and educated the text mining developers to the specific needs of the metagenomics community.« less

De novo assembly of highly polymorphic metagenomic data using in situ generated reference sequences and a novel BLAST-based assembly pipeline.

PubMed

Lin, You-Yu; Hsieh, Chia-Hung; Chen, Jiun-Hong; Lu, Xuemei; Kao, Jia-Horng; Chen, Pei-Jer; Chen, Ding-Shinn; Wang, Hurng-Yi

2017-04-26

The accuracy of metagenomic assembly is usually compromised by high levels of polymorphism due to divergent reads from the same genomic region recognized as different loci when sequenced and assembled together. A viral quasispecies is a group of abundant and diversified genetically related viruses found in a single carrier. Current mainstream assembly methods, such as Velvet and SOAPdenovo, were not originally intended for the assembly of such metagenomics data, and therefore demands for new methods to provide accurate and informative assembly results for metagenomic data. In this study, we present a hybrid method for assembling highly polymorphic data combining the partial de novo-reference assembly (PDR) strategy and the BLAST-based assembly pipeline (BBAP). The PDR strategy generates in situ reference sequences through de novo assembly of a randomly extracted partial data set which is subsequently used for the reference assembly for the full data set. BBAP employs a greedy algorithm to assemble polymorphic reads. We used 12 hepatitis B virus quasispecies NGS data sets from a previous study to assess and compare the performance of both PDR and BBAP. Analyses suggest the high polymorphism of a full metagenomic data set leads to fragmentized de novo assembly results, whereas the biased or limited representation of external reference sequences included fewer reads into the assembly with lower assembly accuracy and variation sensitivity. In comparison, the PDR generated in situ reference sequence incorporated more reads into the final PDR assembly of the full metagenomics data set along with greater accuracy and higher variation sensitivity. BBAP assembly results also suggest higher assembly efficiency and accuracy compared to other assembly methods. Additionally, BBAP assembly recovered HBV structural variants that were not observed amongst assembly results of other methods. Together, PDR/BBAP assembly results were significantly better than other compared methods

Metagenomics: Probing pollutant fate in natural and engineered ecosystems.

PubMed

Bouhajja, Emna; Agathos, Spiros N; George, Isabelle F

2016-12-01

Polluted environments are a reservoir of microbial species able to degrade or to convert pollutants to harmless compounds. The proper management of microbial resources requires a comprehensive characterization of their genetic pool to assess the fate of contaminants and increase the efficiency of bioremediation processes. Metagenomics offers appropriate tools to describe microbial communities in their whole complexity without lab-based cultivation of individual strains. After a decade of use of metagenomics to study microbiomes, the scientific community has made significant progress in this field. In this review, we survey the main steps of metagenomics applied to environments contaminated with organic compounds or heavy metals. We emphasize technical solutions proposed to overcome encountered obstacles. We then compare two metagenomic approaches, i.e. library-based targeted metagenomics and direct sequencing of metagenomes. In the former, environmental DNA is cloned inside a host, and then clones of interest are selected based on (i) their expression of biodegradative functions or (ii) sequence homology with probes and primers designed from relevant, already known sequences. The highest score for the discovery of novel genes and degradation pathways has been achieved so far by functional screening of large clone libraries. On the other hand, direct sequencing of metagenomes without a cloning step has been more often applied to polluted environments for characterization of the taxonomic and functional composition of microbial communities and their dynamics. In this case, the analysis has focused on 16S rRNA genes and marker genes of biodegradation. Advances in next generation sequencing and in bioinformatic analysis of sequencing data have opened up new opportunities for assessing the potential of biodegradation by microbes, but annotation of collected genes is still hampered by a limited number of available reference sequences in databases. Although metagenomics

Metagenome phylogenetic profiling of microbial community evolution in a tetrachloroethene-contaminated aquifer responding to enhanced reductive dechlorination protocols.

PubMed

Reiss, Rebecca A; Guerra, Peter; Makhnin, Oleg

2016-01-01

Chlorinated solvent contamination of potable water supplies is a serious problem worldwide. Biostimulation protocols can successfully remediate chlorinated solvent contamination through enhanced reductive dechlorination pathways, however the process is poorly understood and sometimes stalls creating a more serious problem. Whole metagenome techniques have the potential to reveal details of microbial community changes induced by biostimulation. Here we compare the metagenome of a tetrachloroethene contaminated Environmental Protection Agency Superfund Site before and after the application of biostimulation protocols. Environmental DNA was extracted from uncultured microbes that were harvested by on-site filtration of groundwater one month prior to and five months after the injection of emulsified vegetable oil, nutrients, and hydrogen gas bioamendments. Pair-end libraries were prepared for high-throughput DNA sequencing and 90 basepairs from both ends of randomly fragmented 400 basepair DNA fragments were sequenced. Over 31 millions reads were annotated with Metagenome Rapid Annotation using Subsystem Technology representing 32 prokaryotic phyla, 869 genera, and 3,181 species. A 3.6 log 2 fold increase in biomass as measured by DNA yield per mL water was measured, but there was a 9% decrease in the number of genera detected post-remediation. We apply Bayesian statistical methods to assign false discovery rates to fold-change abundance data and use Zipf's power law to filter genera with low read counts. Plotting the log-rank against the log-fold-change facilitates the visualization of the changes in the community in response to the enhanced reductive dechlorination protocol. Members of the Archaea domain increased 4.7 log 2 fold, dominated by methanogens. Prior to remediation, classes Alphaproteobacteria and Betaproteobacteria dominated the community but exhibit significant decreases five months after biostimulation. Geobacter and Sulfurospirillum replace

MetaQUAST: evaluation of metagenome assemblies.

PubMed

Mikheenko, Alla; Saveliev, Vladislav; Gurevich, Alexey

2016-04-01

During the past years we have witnessed the rapid development of new metagenome assembly methods. Although there are many benchmark utilities designed for single-genome assemblies, there is no well-recognized evaluation and comparison tool for metagenomic-specific analogues. In this article, we present MetaQUAST, a modification of QUAST, the state-of-the-art tool for genome assembly evaluation based on alignment of contigs to a reference. MetaQUAST addresses such metagenome datasets features as (i) unknown species content by detecting and downloading reference sequences, (ii) huge diversity by giving comprehensive reports for multiple genomes and (iii) presence of highly relative species by detecting chimeric contigs. We demonstrate MetaQUAST performance by comparing several leading assemblers on one simulated and two real datasets. http://bioinf.spbau.ru/metaquast aleksey.gurevich@spbu.ru Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Activity-Based Screening of Metagenomic Libraries for Hydrogenase Enzymes.

PubMed

Adam, Nicole; Perner, Mirjam

2017-01-01

Here we outline how to identify hydrogenase enzymes from metagenomic libraries through an activity-based screening approach. A metagenomic fosmid library is constructed in E. coli and the fosmids are transferred into a hydrogenase deletion mutant of Shewanella oneidensis (ΔhyaB) via triparental mating. If a fosmid exhibits hydrogen uptake activity, S. oneidensis' phenotype is restored and hydrogenase activity is indicated by a color change of the medium from yellow to colorless. This new method enables screening of 48 metagenomic fosmid clones in parallel.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond.

PubMed

Hiraoka, Satoshi; Yang, Ching-Chia; Iwasaki, Wataru

2016-09-29

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

FY11 Report on Metagenome Analysis using Pathogen Marker Libraries

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, Shea N.; Allen, Jonathan E.; McLoughlin, Kevin S.

2011-06-02

A method, sequence library, and software suite was invented to rapidly assess whether any member of a pre-specified list of threat organisms or their near neighbors is present in a metagenome. The system was designed to handle mega- to giga-bases of FASTA-formatted raw sequence reads from short or long read next generation sequencing platforms. The approach is to pre-calculate a viral and a bacterial "Pathogen Marker Library" (PML) containing sub-sequences specific to pathogens or their near neighbors. A list of expected matches comparing every bacterial or viral genome against the PML sequences is also pre-calculated. To analyze a metagenome, readsmore » are compared to the PML, and observed PML-metagenome matches are compared to the expected PML-genome matches, and the ratio of observed relative to expected matches is reported. In other words, a 3-way comparison among the PML, metagenome, and existing genome sequences is used to quickly assess which (if any) species included in the PML is likely to be present in the metagenome, based on available sequence data. Our tests showed that the species with the most PML matches correctly indicated the organism sequenced for empirical metagenomes consisting of a cultured, relatively pure isolate. These runs completed in 1 minute to 3 hours on 12 CPU (1 thread/CPU), depending on the metagenome and PML. Using more threads on the same number of CPU resulted in speed improvements roughly proportional to the number of threads. Simulations indicated that detection sensitivity depends on both sequencing coverage levels for a species and the size of the PML: species were correctly detected even at ~0.003x coverage by the large PMLs, and at ~0.03x coverage by the smaller PMLs. Matches to true positive species were 3-4 orders of magnitude higher than to false positives. Simulations with short reads (36 nt and ~260 nt) showed that species were usually detected for metagenome coverage above 0.005x and coverage in the PML above 0

A Novel Bioinformatics Strategy to Analyze Microbial Big Sequence Data for Efficient Knowledge Discovery: Batch-Learning Self-Organizing Map (BLSOM).

PubMed

Iwasaki, Yuki; Abe, Takashi; Wada, Kennosuke; Wada, Yoshiko; Ikemura, Toshimichi

2013-11-20

With the remarkable increase of genomic sequence data of microorganisms, novel tools are needed for comprehensive analyses of the big sequence data available. The self-organizing map (SOM) is an effective tool for clustering and visualizing high-dimensional data, such as oligonucleotide composition on one map. By modifying the conventional SOM, we developed batch-learning SOM (BLSOM), which allowed classification of sequence fragments (e.g., 1 kb) according to phylotypes, solely depending on oligonucleotide composition. Metagenomics studies of uncultivable microorganisms in clinical and environmental samples should allow extensive surveys of genes important in life sciences. BLSOM is most suitable for phylogenetic assignment of metagenomic sequences, because fragmental sequences can be clustered according to phylotypes, solely depending on oligonucleotide composition. We first constructed oligonucleotide BLSOMs for all available sequences from genomes of known species, and by mapping metagenomic sequences on these large-scale BLSOMs, we can predict phylotypes of individual metagenomic sequences, revealing a microbial community structure of uncultured microorganisms, including viruses. BLSOM has shown that influenza viruses isolated from humans and birds clearly differ in oligonucleotide composition. Based on this host-dependent oligonucleotide composition, we have proposed strategies for predicting directional changes of virus sequences and for surveilling potentially hazardous strains when introduced into humans from non-human sources.

Marine Metagenome as A Resource for Novel Enzymes.

PubMed

Alma'abadi, Amani D; Gojobori, Takashi; Mineta, Katsuhiko

2015-10-01

More than 99% of identified prokaryotes, including many from the marine environment, cannot be cultured in the laboratory. This lack of capability restricts our knowledge of microbial genetics and community ecology. Metagenomics, the culture-independent cloning of environmental DNAs that are isolated directly from an environmental sample, has already provided a wealth of information about the uncultured microbial world. It has also facilitated the discovery of novel biocatalysts by allowing researchers to probe directly into a huge diversity of enzymes within natural microbial communities. Recent advances in these studies have led to a great interest in recruiting microbial enzymes for the development of environmentally-friendly industry. Although the metagenomics approach has many limitations, it is expected to provide not only scientific insights but also economic benefits, especially in industry. This review highlights the importance of metagenomics in mining microbial lipases, as an example, by using high-throughput techniques. In addition, we discuss challenges in the metagenomics as an important part of bioinformatics analysis in big data. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

Deciphering viral presences: two novel partial giant viruses detected in marine metagenome and in a mine drainage metagenome.

PubMed

Andreani, Julien; Verneau, Jonathan; Raoult, Didier; Levasseur, Anthony; La Scola, Bernard

2018-04-10

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.

MetaPhinder-Identifying Bacteriophage Sequences in Metagenomic Data Sets.

PubMed

Jurtz, Vanessa Isabell; Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.

Metagenomics: A new horizon in cancer research

PubMed Central

Banerjee, Joyita; Mishra, Neetu; Dhas, Yogita

2015-01-01

Metagenomics has broadened the scope of targeting microbes responsible for inducing various types of cancers. About 16.1% of cancers are associated with microbial infection. Metagenomics is an equitable way of identifying and studying micro-organisms within their habitat. In cancer research, this approach has revolutionized the way of identifying, analyzing and targeting the microbial diversity present in the tissue specimens of cancer patients. The genomic analyses of these micro-organisms through next generation sequencing techniques invariably facilitate in recognizing the microbial population in biopsies and their evolutionary relationships with each other. In this review an attempt has been made to generate current metagenomic view on cancer microbiota. Different types of micro-organisms have been found to be linked to various types of cancers, thus, contributing significantly in understanding the disease at molecular level. PMID:26110115

Metagenomics: The Next Culture-Independent Game Changer

PubMed Central

Forbes, Jessica D.; Knox, Natalie C.; Ronholm, Jennifer; Pagotto, Franco; Reimer, Aleisha

2017-01-01

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other ‘omics’ disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable

SPHINX--an algorithm for taxonomic binning of metagenomic sequences.

PubMed

Mohammed, Monzoorul Haque; Ghosh, Tarini Shankar; Singh, Nitin Kumar; Mande, Sharmila S

2011-01-01

Compared with composition-based binning algorithms, the binning accuracy and specificity of alignment-based binning algorithms is significantly higher. However, being alignment-based, the latter class of algorithms require enormous amount of time and computing resources for binning huge metagenomic datasets. The motivation was to develop a binning approach that can analyze metagenomic datasets as rapidly as composition-based approaches, but nevertheless has the accuracy and specificity of alignment-based algorithms. This article describes a hybrid binning approach (SPHINX) that achieves high binning efficiency by utilizing the principles of both 'composition'- and 'alignment'-based binning algorithms. Validation results with simulated sequence datasets indicate that SPHINX is able to analyze metagenomic sequences as rapidly as composition-based algorithms. Furthermore, the binning efficiency (in terms of accuracy and specificity of assignments) of SPHINX is observed to be comparable with results obtained using alignment-based algorithms. A web server for the SPHINX algorithm is available at http://metagenomics.atc.tcs.com/SPHINX/.

Motif-Based Text Mining of Microbial Metagenome Redundancy Profiling Data for Disease Classification.

PubMed

Wang, Yin; Li, Rudong; Zhou, Yuhua; Ling, Zongxin; Guo, Xiaokui; Xie, Lu; Liu, Lei

2016-01-01

Text data of 16S rRNA are informative for classifications of microbiota-associated diseases. However, the raw text data need to be systematically processed so that features for classification can be defined/extracted; moreover, the high-dimension feature spaces generated by the text data also pose an additional difficulty. Here we present a Phylogenetic Tree-Based Motif Finding algorithm (PMF) to analyze 16S rRNA text data. By integrating phylogenetic rules and other statistical indexes for classification, we can effectively reduce the dimension of the large feature spaces generated by the text datasets. Using the retrieved motifs in combination with common classification methods, we can discriminate different samples of both pneumonia and dental caries better than other existing methods. We extend the phylogenetic approaches to perform supervised learning on microbiota text data to discriminate the pathological states for pneumonia and dental caries. The results have shown that PMF may enhance the efficiency and reliability in analyzing high-dimension text data.

Identification of a Novel Human Papillomavirus by Metagenomic Analysis of Samples from Patients with Febrile Respiratory Illness

PubMed Central

Mokili, John L.; Dutilh, Bas E.; Lim, Yan Wei; Schneider, Bradley S.; Taylor, Travis; Haynes, Matthew R.; Metzgar, David; Myers, Christopher A.; Blair, Patrick J.; Nosrat, Bahador; Wolfe, Nathan D.; Rohwer, Forest

2013-01-01

As part of a virus discovery investigation using a metagenomic approach, a highly divergent novel Human papillomavirus type was identified in pooled convenience nasal/oropharyngeal swab samples collected from patients with febrile respiratory illness. Phylogenetic analysis of the whole genome and the L1 gene reveals that the new HPV identified in this study clusters with previously described gamma papillomaviruses, sharing only 61.1% (whole genome) and 63.1% (L1) sequence identity with its closest relative in the Papillomavirus episteme (PAVE) database. This new virus was named HPV_SD2 pending official classification. The complete genome of HPV-SD2 is 7,299 bp long (36.3% G/C) and contains 7 open reading frames (L2, L1, E6, E7, E1, E2 and E4) and a non-coding long control region (LCR) between L1 and E6. The metagenomic procedures, coupled with the bioinformatic methods described herein are well suited to detect small circular genomes such as those of human papillomaviruses. PMID:23554892

Oral Metagenomic Biomarkers in Rheumatoid Arthritis

DTIC Science & Technology

2017-09-01

AWARD NUMBER: W81XWH-15-1-0320 TITLE: Oral Metagenomic Biomarkers in Rheumatoid Arthritis PRINCIPAL INVESTIGATOR: Edward K Chan CONTRACTING... Rheumatoid Arthritis 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0320 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Edward K Chan 5d. PROJECT NUMBER...individuals with  rheumatoid   arthritis  (RA). The goal is to test the  hypothesis that oral microbiome and metagenomic analyses will allow us to identify new

Exploring variation-aware contig graphs for (comparative) metagenomics using MaryGold

PubMed Central

Nijkamp, Jurgen F.; Pop, Mihai; Reinders, Marcel J. T.; de Ridder, Dick

2013-01-01

Motivation: Although many tools are available to study variation and its impact in single genomes, there is a lack of algorithms for finding such variation in metagenomes. This hampers the interpretation of metagenomics sequencing datasets, which are increasingly acquired in research on the (human) microbiome, in environmental studies and in the study of processes in the production of foods and beverages. Existing algorithms often depend on the use of reference genomes, which pose a problem when a metagenome of a priori unknown strain composition is studied. In this article, we develop a method to perform reference-free detection and visual exploration of genomic variation, both within a single metagenome and between metagenomes. Results: We present the MaryGold algorithm and its implementation, which efficiently detects bubble structures in contig graphs using graph decomposition. These bubbles represent variable genomic regions in closely related strains in metagenomic samples. The variation found is presented in a condensed Circos-based visualization, which allows for easy exploration and interpretation of the found variation. We validated the algorithm on two simulated datasets containing three respectively seven Escherichia coli genomes and showed that finding allelic variation in these genomes improves assemblies. Additionally, we applied MaryGold to publicly available real metagenomic datasets, enabling us to find within-sample genomic variation in the metagenomes of a kimchi fermentation process, the microbiome of a premature infant and in microbial communities living on acid mine drainage. Moreover, we used MaryGold for between-sample variation detection and exploration by comparing sequencing data sampled at different time points for both of these datasets. Availability: MaryGold has been written in C++ and Python and can be downloaded from http://bioinformatics.tudelft.nl/software Contact: d.deridder@tudelft.nl PMID:24058058

Ray Meta: scalable de novo metagenome assembly and profiling

PubMed Central

2012-01-01

Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling. Ray Meta is a massively distributed metagenome assembler that is coupled with Ray Communities, which profiles microbiomes based on uniquely-colored k-mers. It can accurately assemble and profile a three billion read metagenomic experiment representing 1,000 bacterial genomes of uneven proportions in 15 hours with 1,024 processor cores, using only 1.5 GB per core. The software will facilitate the processing of large and complex datasets, and will help in generating biological insights for specific environments. Ray Meta is open source and available at http://denovoassembler.sf.net. PMID:23259615

Metagenome assembly through clustering of next-generation sequencing data using protein sequences.

PubMed

Sim, Mikang; Kim, Jaebum

2015-02-01

The study of environmental microbial communities, called metagenomics, has gained a lot of attention because of the recent advances in next-generation sequencing (NGS) technologies. Microbes play a critical role in changing their environments, and the mode of their effect can be solved by investigating metagenomes. However, the difficulty of metagenomes, such as the combination of multiple microbes and different species abundance, makes metagenome assembly tasks more challenging. In this paper, we developed a new metagenome assembly method by utilizing protein sequences, in addition to the NGS read sequences. Our method (i) builds read clusters by using mapping information against available protein sequences, and (ii) creates contig sequences by finding consensus sequences through probabilistic choices from the read clusters. By using simulated NGS read sequences from real microbial genome sequences, we evaluated our method in comparison with four existing assembly programs. We found that our method could generate relatively long and accurate metagenome assemblies, indicating that the idea of using protein sequences, as a guide for the assembly, is promising. Copyright © 2015 Elsevier B.V. All rights reserved.

Longitudinal Metagenomic Analysis of Hospital Air Identifies Clinically Relevant Microbes.

PubMed

King, Paula; Pham, Long K; Waltz, Shannon; Sphar, Dan; Yamamoto, Robert T; Conrad, Douglas; Taplitz, Randy; Torriani, Francesca; Forsyth, R Allyn

2016-01-01

We describe the sampling of sixty-three uncultured hospital air samples collected over a six-month period and analysis using shotgun metagenomic sequencing. Our primary goals were to determine the longitudinal metagenomic variability of this environment, identify and characterize genomes of potential pathogens and determine whether they are atypical to the hospital airborne metagenome. Air samples were collected from eight locations which included patient wards, the main lobby and outside. The resulting DNA libraries produced 972 million sequences representing 51 gigabases. Hierarchical clustering of samples by the most abundant 50 microbial orders generated three major nodes which primarily clustered by type of location. Because the indoor locations were longitudinally consistent, episodic relative increases in microbial genomic signatures related to the opportunistic pathogens Aspergillus, Penicillium and Stenotrophomonas were identified as outliers at specific locations. Further analysis of microbial reads specific for Stenotrophomonas maltophilia indicated homology to a sequenced multi-drug resistant clinical strain and we observed broad sequence coverage of resistance genes. We demonstrate that a shotgun metagenomic sequencing approach can be used to characterize the resistance determinants of pathogen genomes that are uncharacteristic for an otherwise consistent hospital air microbial metagenomic profile.

Metagenomic analysis of microbial community of an Amazonian geothermal spring in Peru.

PubMed

Paul, Sujay; Cortez, Yolanda; Vera, Nadia; Villena, Gretty K; Gutiérrez-Correa, Marcel

2016-09-01

Aguas Calientes (AC) is an isolated geothermal spring located deep into the Amazon rainforest (7°21'12″ S, 75°00'54″ W) of Peru. This geothermal spring is slightly acidic (pH 5.0-7.0) in nature, with temperatures varying from 45 to 90 °C and continually fed by plant litter, resulting in a relatively high degree of total organic content (TOC). Pooled water sample was analyzed at 16S rRNA V3-V4 hypervariable region by amplicon metagenome sequencing on Illumina HiSeq platform. A total of 2,976,534 paired ends reads were generated which were assigned into 5434 numbers of OTUs. All the resulting 16S rRNA fragments were then classified into 58 bacterial phyla and 2 archaeal phyla. Proteobacteria (88.06%) was found to be the highest represented phyla followed by Thermi (6.43%), Firmicutes (3.41%) and Aquificae (1.10%), respectively. Crenarchaeota and Euryarchaeota were the only 2 archaeal phyla detected in this study with low abundance. Metagenomic sequences were deposited to SRA database which is available at NCBI with accession number SRX1809286. Functional categorization of the assigned OTUs was performed using PICRUSt tool. In COG analysis "Amino acid transport and metabolism" (8.5%) was found to be the highest represented category whereas among predicted KEGG pathways "Metabolism" (50.6%) was the most abundant. This is the first report of a high resolution microbial phylogenetic profile of an Amazonian hot spring.

Antibiotic resistance genes across a wide variety of metagenomes.

PubMed

Fitzpatrick, David; Walsh, Fiona

2016-02-01

The distribution of potential clinically relevant antibiotic resistance (AR) genes across soil, water, animal, plant and human microbiomes is not well understood. We aimed to investigate if there were differences in the distribution and relative abundances of resistance genes across a variety of ecological niches. All sequence reads (human, animal, water, soil, plant and insect metagenomes) from the MG-RAST database were downloaded and assembled into a local sequence database. We show that there are many reservoirs of the basic form of resistance genes e.g. blaTEM, but the human and mammalian gut microbiomes contain the widest diversity of clinically relevant resistance genes using metagenomic analysis. The human microbiomes contained a high relative abundance of resistance genes, while the relative abundances varied greatly in the marine and soil metagenomes, when datasets with greater than one million genes were compared. While these results reflect a bias in the distribution of AR genes across the metagenomes, we note this interpretation with caution. Metagenomics analysis includes limits in terms of detection and identification of AR genes in complex and diverse microbiome population. Therefore, if we do not detect the AR gene is it in fact not there or just below the limits of our techniques? © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Metagenomes from two microbial consortia associated with Santa Barbara seep oil.

PubMed

Hawley, Erik R; Malfatti, Stephanie A; Pagani, Ioanna; Huntemann, Marcel; Chen, Amy; Foster, Brian; Copeland, Alexander; del Rio, Tijana Glavina; Pati, Amrita; Jansson, Janet R; Gilbert, Jack A; Tringe, Susannah Green; Lorenson, Thomas D; Hess, Matthias

2014-12-01

The metagenomes from two microbial consortia associated with natural oils seeping into the Pacific Ocean offshore the coast of Santa Barbara (California, USA) were determined to complement already existing metagenomes generated from microbial communities associated with hydrocarbons that pollute the marine ecosystem. This genomics resource article is the first of two publications reporting a total of four new metagenomes from oils that seep into the Santa Barbara Channel. Copyright © 2014 Elsevier B.V. All rights reserved.

Genetic variability of psychrotolerant Acidithiobacillus ferrivorans revealed by (meta)genomic analysis.

PubMed

González, Carolina; Yanquepe, María; Cardenas, Juan Pablo; Valdes, Jorge; Quatrini, Raquel; Holmes, David S; Dopson, Mark

2014-11-01

Acidophilic microorganisms inhabit low pH environments such as acid mine drainage that is generated when sulfide minerals are exposed to air. The genome sequence of the psychrotolerant Acidithiobacillus ferrivorans SS3 was compared to a metagenome from a low temperature acidic stream dominated by an A. ferrivorans-like strain. Stretches of genomic DNA characterized by few matches to the metagenome, termed 'metagenomic islands', encoded genes associated with metal efflux and pH homeostasis. The metagenomic islands were enriched in mobile elements such as phage proteins, transposases, integrases and in one case, predicted to be flanked by truncated tRNAs. Cus gene clusters predicted to be involved in copper efflux and further Cus-like RND systems were predicted to be located in metagenomic islands and therefore, constitute part of the flexible gene complement of the species. Phylogenetic analysis of Cus clusters showed both lineage specificity within the Acidithiobacillus genus as well as niche specificity associated with an acidic environment. The metagenomic islands also contained a predicted copper efflux P-type ATPase system and a polyphosphate kinase potentially involved in polyphosphate mediated copper resistance. This study identifies genetic variability of low temperature acidophiles that likely reflects metal resistance selective pressures in the copper rich environment. Copyright © 2014 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Metagenomics and the protein universe

PubMed Central

Godzik, Adam

2011-01-01

Metagenomics sequencing projects have dramatically increased our knowledge of the protein universe and provided over one-half of currently known protein sequences; they have also introduced a much broader phylogenetic diversity into the protein databases. The full analysis of metagenomic datasets is only beginning, but it has already led to the discovery of thousands of new protein families, likely representing novel functions specific to given environments. At the same time, a deeper analysis of such novel families, including experimental structure determination of some representatives, suggests that most of them represent distant homologs of already characterized protein families, and thus most of the protein diversity present in the new environments are due to functional divergence of the known protein families rather than the emergence of new ones. PMID:21497084

MetaVelvet: An Extension of Velvet Assembler to de novo Metagenome Assembly from Short Sequence Reads (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Sakakibara, Yasumbumi

2018-02-13

Keio University's Yasumbumi Sakakibara on "MetaVelvet: An Extension of Velvet Assembler to de novo Metagenome Assembly from Short Sequence Reads" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

MetaVelvet: An Extension of Velvet Assembler to de novo Metagenome Assembly from Short Sequence Reads (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakakibara, Yasumbumi

2011-10-13

Keio University's Yasumbumi Sakakibara on "MetaVelvet: An Extension of Velvet Assembler to de novo Metagenome Assembly from Short Sequence Reads" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Comparative fecal metagenomics unveils unique functional capacity of the swine gut

PubMed Central

2011-01-01

Background Uncovering the taxonomic composition and functional capacity within the swine gut microbial consortia is of great importance to animal physiology and health as well as to food and water safety due to the presence of human pathogens in pig feces. Nonetheless, limited information on the functional diversity of the swine gut microbiome is available. Results Analysis of 637, 722 pyrosequencing reads (130 megabases) generated from Yorkshire pig fecal DNA extracts was performed to help better understand the microbial diversity and largely unknown functional capacity of the swine gut microbiome. Swine fecal metagenomic sequences were annotated using both MG-RAST and JGI IMG/M-ER pipelines. Taxonomic analysis of metagenomic reads indicated that swine fecal microbiomes were dominated by Firmicutes and Bacteroidetes phyla. At a finer phylogenetic resolution, Prevotella spp. dominated the swine fecal metagenome, while some genes associated with Treponema and Anareovibrio species were found to be exclusively within the pig fecal metagenomic sequences analyzed. Functional analysis revealed that carbohydrate metabolism was the most abundant SEED subsystem, representing 13% of the swine metagenome. Genes associated with stress, virulence, cell wall and cell capsule were also abundant. Virulence factors associated with antibiotic resistance genes with highest sequence homology to genes in Bacteroidetes, Clostridia, and Methanosarcina were numerous within the gene families unique to the swine fecal metagenomes. Other abundant proteins unique to the distal swine gut shared high sequence homology to putative carbohydrate membrane transporters. Conclusions The results from this metagenomic survey demonstrated the presence of genes associated with resistance to antibiotics and carbohydrate metabolism suggesting that the swine gut microbiome may be shaped by husbandry practices. PMID:21575148

The fragmented nature of tundra landscape

NASA Astrophysics Data System (ADS)

Virtanen, Tarmo; Ek, Malin

2014-04-01

The vegetation and land cover structure of tundra areas is fragmented when compared to other biomes. Thus, satellite images of high resolution are required for producing land cover classifications, in order to reveal the actual distribution of land cover types across these large and remote areas. We produced and compared different land cover classifications using three satellite images (QuickBird, Aster and Landsat TM5) with different pixel sizes (2.4 m, 15 m and 30 m pixel size, respectively). The study area, in north-eastern European Russia, was visited in July 2007 to obtain ground reference data. The QuickBird image was classified using supervised segmentation techniques, while the Aster and Landsat TM5 images were classified using a pixel-based supervised classification method. The QuickBird classification showed the highest accuracy when tested against field data, while the Aster image was generally more problematic to classify than the Landsat TM5 image. Use of smaller pixel sized images distinguished much greater levels of landscape fragmentation. The overall mean patch sizes in the QuickBird, Aster, and Landsat TM5-classifications were 871 m2, 2141 m2 and 7433 m2, respectively. In the QuickBird classification, the mean patch size of all the tundra and peatland vegetation classes was smaller than one pixel of the Landsat TM5 image. Water bodies and fens in particular occur in the landscape in small or elongated patches, and thus cannot be realistically classified from larger pixel sized images. Land cover patterns vary considerably at such a fine-scale, so that a lot of information is lost if only medium resolution satellite images are used. It is crucial to know the amount and spatial distribution of different vegetation types in arctic landscapes, as carbon dynamics and other climate related physical, geological and biological processes are known to vary greatly between vegetation types.

In-depth resistome analysis by targeted metagenomics.

PubMed

Lanza, Val F; Baquero, Fernando; Martínez, José Luís; Ramos-Ruíz, Ricardo; González-Zorn, Bruno; Andremont, Antoine; Sánchez-Valenzuela, Antonio; Ehrlich, Stanislav Dusko; Kennedy, Sean; Ruppé, Etienne; van Schaik, Willem; Willems, Rob J; de la Cruz, Fernando; Coque, Teresa M

2018-01-15

Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of "resistomes" (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect "gene abundance" (from 2.0 to 83.2%) and "gene diversity" (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes

Activity screening of environmental metagenomic libraries reveals novel carboxylesterase families

DOE Office of Scientific and Technical Information (OSTI.GOV)

Popovic, Ana; Hai, Tran; Tchigvintsev, Anatoly

Metagenomics has made accessible an enormous reserve of global biochemical diversity. In order to tap into this vast resource of novel enzymes, we have screened over one million clones from metagenome DNA libraries derived from sixteen different environments for carboxylesterase activity and identified 714 positive hits. Here, we validated the esterase activity of 80 selected genes, which belong to 17 different protein families including unknown and cyclase-like proteins. Three metagenomic enzymes exhibited lipase activity, and seven proteins showed polyester depolymerization activity against polylactic acid and polycaprolactone. Detailed biochemical characterization of four new enzymes revealed their substrate preference, whereas their catalyticmore » residues were identified using site-directed mutagenesis. The crystal structure of the metal-ion dependent esterase MGS0169 from the amidohydrolase superfamily revealed a novel active site with a bound unknown ligand. Thus, activity-centered metagenomics has revealed diverse enzymes and novel families of microbial carboxylesterases, whose activity could not have been predicted using bioinformatics tools.« less

Activity screening of environmental metagenomic libraries reveals novel carboxylesterase families

DOE PAGES

Popovic, Ana; Hai, Tran; Tchigvintsev, Anatoly; ...

2017-03-08

Metagenomics has made accessible an enormous reserve of global biochemical diversity. In order to tap into this vast resource of novel enzymes, we have screened over one million clones from metagenome DNA libraries derived from sixteen different environments for carboxylesterase activity and identified 714 positive hits. Here, we validated the esterase activity of 80 selected genes, which belong to 17 different protein families including unknown and cyclase-like proteins. Three metagenomic enzymes exhibited lipase activity, and seven proteins showed polyester depolymerization activity against polylactic acid and polycaprolactone. Detailed biochemical characterization of four new enzymes revealed their substrate preference, whereas their catalyticmore » residues were identified using site-directed mutagenesis. The crystal structure of the metal-ion dependent esterase MGS0169 from the amidohydrolase superfamily revealed a novel active site with a bound unknown ligand. Thus, activity-centered metagenomics has revealed diverse enzymes and novel families of microbial carboxylesterases, whose activity could not have been predicted using bioinformatics tools.« less

MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets

PubMed Central

Villarroel, Julia; Lund, Ole; Voldby Larsen, Mette; Nielsen, Morten

2016-01-01

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder. PMID:27684958

MG-Digger: An Automated Pipeline to Search for Giant Virus-Related Sequences in Metagenomes

PubMed Central

Verneau, Jonathan; Levasseur, Anthony; Raoult, Didier; La Scola, Bernard; Colson, Philippe

2016-01-01

The number of metagenomic studies conducted each year is growing dramatically. Storage and analysis of such big data is difficult and time-consuming. Interestingly, analysis shows that environmental and human metagenomes include a significant amount of non-annotated sequences, representing a ‘dark matter.’ We established a bioinformatics pipeline that automatically detects metagenome reads matching query sequences from a given set and applied this tool to the detection of sequences matching large and giant DNA viral members of the proposed order Megavirales or virophages. A total of 1,045 environmental and human metagenomes (≈ 1 Terabase) were collected, processed, and stored on our bioinformatics server. In addition, nucleotide and protein sequences from 93 Megavirales representatives, including 19 giant viruses of amoeba, and 5 virophages, were collected. The pipeline was generated by scripts written in Python language and entitled MG-Digger. Metagenomes previously found to contain megavirus-like sequences were tested as controls. MG-Digger was able to annotate 100s of metagenome sequences as best matching those of giant viruses. These sequences were most often found to be similar to phycodnavirus or mimivirus sequences, but included reads related to recently available pandoraviruses, Pithovirus sibericum, and faustoviruses. Compared to other tools, MG-Digger combined stand-alone use on Linux or Windows operating systems through a user-friendly interface, implementation of ready-to-use customized metagenome databases and query sequence databases, adjustable parameters for BLAST searches, and creation of output files containing selected reads with best match identification. Compared to Metavir 2, a reference tool in viral metagenome analysis, MG-Digger detected 8% more true positive Megavirales-related reads in a control metagenome. The present work shows that massive, automated and recurrent analyses of metagenomes are effective in improving knowledge about

Integrative workflows for metagenomic analysis

PubMed Central

Ladoukakis, Efthymios; Kolisis, Fragiskos N.; Chatziioannou, Aristotelis A.

2014-01-01

The rapid evolution of all sequencing technologies, described by the term Next Generation Sequencing (NGS), have revolutionized metagenomic analysis. They constitute a combination of high-throughput analytical protocols, coupled to delicate measuring techniques, in order to potentially discover, properly assemble and map allelic sequences to the correct genomes, achieving particularly high yields for only a fraction of the cost of traditional processes (i.e., Sanger). From a bioinformatic perspective, this boils down to many GB of data being generated from each single sequencing experiment, rendering the management or even the storage, critical bottlenecks with respect to the overall analytical endeavor. The enormous complexity is even more aggravated by the versatility of the processing steps available, represented by the numerous bioinformatic tools that are essential, for each analytical task, in order to fully unveil the genetic content of a metagenomic dataset. These disparate tasks range from simple, nonetheless non-trivial, quality control of raw data to exceptionally complex protein annotation procedures, requesting a high level of expertise for their proper application or the neat implementation of the whole workflow. Furthermore, a bioinformatic analysis of such scale, requires grand computational resources, imposing as the sole realistic solution, the utilization of cloud computing infrastructures. In this review article we discuss different, integrative, bioinformatic solutions available, which address the aforementioned issues, by performing a critical assessment of the available automated pipelines for data management, quality control, and annotation of metagenomic data, embracing various, major sequencing technologies and applications. PMID:25478562

A user's guide to quantitative and comparative analysis of metagenomic datasets.

PubMed

Luo, Chengwei; Rodriguez-R, Luis M; Konstantinidis, Konstantinos T

2013-01-01

Metagenomics has revolutionized microbiological studies during the past decade and provided new insights into the diversity, dynamics, and metabolic potential of natural microbial communities. However, metagenomics still represents a field in development, and standardized tools and approaches to handle and compare metagenomes have not been established yet. An important reason accounting for the latter is the continuous changes in the type of sequencing data available, for example, long versus short sequencing reads. Here, we provide a guide to bioinformatic pipelines developed to accomplish the following tasks, focusing primarily on those developed by our team: (i) assemble a metagenomic dataset; (ii) determine the level of sequence coverage obtained and the amount of sequencing required to obtain complete coverage; (iii) identify the taxonomic affiliation of a metagenomic read or assembled contig; and (iv) determine differentially abundant genes, pathways, and species between different datasets. Most of these pipelines do not depend on the type of sequences available or can be easily adjusted to fit different types of sequences, and are freely available (for instance, through our lab Web site: http://www.enve-omics.gatech.edu/). The limitations of current approaches, as well as the computational aspects that can be further improved, will also be briefly discussed. The work presented here provides practical guidelines on how to perform metagenomic analysis of microbial communities characterized by varied levels of diversity and establishes approaches to handle the resulting data, independent of the sequencing platform employed. © 2013 Elsevier Inc. All rights reserved.

The single-species metagenome: subtyping Staphylococcus aureus core genome sequences from shotgun metagenomic data

PubMed Central

Li, Ben; Petit III, Robert A.; Qin, Zhaohui S.; Darrow, Lyndsey

2016-01-01

In this study we developed a genome-based method for detecting Staphylococcus aureus subtypes from metagenome shotgun sequence data. We used a binomial mixture model and the coverage counts at >100,000 known S. aureus SNP (single nucleotide polymorphism) sites derived from prior comparative genomic analysis to estimate the proportion of 40 subtypes in metagenome samples. We were able to obtain >87% sensitivity and >94% specificity at 0.025X coverage for S. aureus. We found that 321 and 149 metagenome samples from the Human Microbiome Project and metaSUB analysis of the New York City subway, respectively, contained S. aureus at genome coverage >0.025. In both projects, CC8 and CC30 were the most common S. aureus clonal complexes encountered. We found evidence that the subtype composition at different body sites of the same individual were more similar than random sampling and more limited evidence that certain body sites were enriched for particular subtypes. One surprising finding was the apparent high frequency of CC398, a lineage often associated with livestock, in samples from the tongue dorsum. Epidemiologic analysis of the HMP subject population suggested that high BMI (body mass index) and health insurance are possibly associated with S. aureus carriage but there was limited power to identify factors linked to carriage of even the most common subtype. In the NYC subway data, we found a small signal of geographic distance affecting subtype clustering but other unknown factors influence taxonomic distribution of the species around the city. PMID:27781166

Metagenomic sequence of saline desert microbiota from wild ass sanctuary, Little Rann of Kutch, Gujarat, India.

PubMed

Patel, Rajesh; Mevada, Vishal; Prajapati, Dhaval; Dudhagara, Pravin; Koringa, Prakash; Joshi, C G

2015-03-01

We report Metagenome from the saline desert soil sample of Little Rann of Kutch, Gujarat State, India. Metagenome consisted of 633,760 sequences with size 141,307,202 bp and 56% G + C content. Metagenome sequence data are available at EBI under EBI Metagenomics database with accession no. ERP005612. Community metagenomics revealed total 1802 species belonged to 43 different phyla with dominating Marinobacter (48.7%) and Halobacterium (4.6%) genus in bacterial and archaeal domain respectively. Remarkably, 18.2% sequences in a poorly characterized group and 4% gene for various stress responses along with versatile presence of commercial enzyme were evident in a functional metagenome analysis.

Metagenomic Taxonomy-Guided Database-Searching Strategy for Improving Metaproteomic Analysis.

PubMed

Xiao, Jinqiu; Tanca, Alessandro; Jia, Ben; Yang, Runqing; Wang, Bo; Zhang, Yu; Li, Jing

2018-04-06

Metaproteomics provides a direct measure of the functional information by investigating all proteins expressed by a microbiota. However, due to the complexity and heterogeneity of microbial communities, it is very hard to construct a sequence database suitable for a metaproteomic study. Using a public database, researchers might not be able to identify proteins from poorly characterized microbial species, while a sequencing-based metagenomic database may not provide adequate coverage for all potentially expressed protein sequences. To address this challenge, we propose a metagenomic taxonomy-guided database-search strategy (MT), in which a merged database is employed, consisting of both taxonomy-guided reference protein sequences from public databases and proteins from metagenome assembly. By applying our MT strategy to a mock microbial mixture, about two times as many peptides were detected as with the metagenomic database only. According to the evaluation of the reliability of taxonomic attribution, the rate of misassignments was comparable to that obtained using an a priori matched database. We also evaluated the MT strategy with a human gut microbial sample, and we found 1.7 times as many peptides as using a standard metagenomic database. In conclusion, our MT strategy allows the construction of databases able to provide high sensitivity and precision in peptide identification in metaproteomic studies, enabling the detection of proteins from poorly characterized species within the microbiota.

RNA viral metagenome of whiteflies leads to the discovery and characterization of a whitefly-transmitted carlavirus in North America.

PubMed

Rosario, Karyna; Capobianco, Heather; Ng, Terry Fei Fan; Breitbart, Mya; Polston, Jane E

2014-01-01

Whiteflies from the Bemisia tabaci species complex have the ability to transmit a large number of plant viruses and are some of the most detrimental pests in agriculture. Although whiteflies are known to transmit both DNA and RNA viruses, most of the diversity has been recorded for the former, specifically for the Begomovirus genus. This study investigated the total diversity of DNA and RNA viruses found in whiteflies collected from a single site in Florida to evaluate if there are additional, previously undetected viral types within the B. tabaci vector. Metagenomic analysis of viral DNA extracted from the whiteflies only resulted in the detection of begomoviruses. In contrast, whiteflies contained sequences similar to RNA viruses from divergent groups, with a diversity that extends beyond currently described viruses. The metagenomic analysis of whiteflies also led to the first report of a whitefly-transmitted RNA virus similar to Cowpea mild mottle virus (CpMMV Florida) (genus Carlavirus) in North America. Further investigation resulted in the detection of CpMMV Florida in native and cultivated plants growing near the original field site of whitefly collection and determination of its experimental host range. Analysis of complete CpMMV Florida genomes recovered from whiteflies and plants suggests that the current classification criteria for carlaviruses need to be reevaluated. Overall, metagenomic analysis supports that DNA plant viruses carried by B. tabaci are dominated by begomoviruses, whereas significantly less is known about RNA viruses present in this damaging insect vector.

Evaluation of the Cow Rumen Metagenome: Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Sczyrba, Alex

2018-02-13

DOE JGI's Alex Sczyrba on "Evaluation of the Cow Rumen Metagenome" and "Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Evaluation of the Cow Rumen Metagenome: Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sczyrba, Alex

2011-10-13

DOE JGI's Alex Sczyrba on "Evaluation of the Cow Rumen Metagenome" and "Assembly by Single Copy Gene Analysis and Single Cell Genome Assemblies" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roux, Simon; Emerson, Joanne B.; Eloe-Fadrosh, Emiley A.

BackgroundViral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we usedin silicomock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. ResultsTools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, andmore » IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization

Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity

DOE PAGES

Roux, Simon; Emerson, Joanne B.; Eloe-Fadrosh, Emiley A.; ...

2017-09-21

BackgroundViral metagenomics (viromics) is increasingly used to obtain uncultivated viral genomes, evaluate community diversity, and assess ecological hypotheses. While viromic experimental methods are relatively mature and widely accepted by the research community, robust bioinformatics standards remain to be established. Here we usedin silicomock viral communities to evaluate the viromic sequence-to-ecological-inference pipeline, including (i) read pre-processing and metagenome assembly, (ii) thresholds applied to estimate viral relative abundances based on read mapping to assembled contigs, and (iii) normalization methods applied to the matrix of viral relative abundances for alpha and beta diversity estimates. ResultsTools specifically designed for metagenomes, specifically metaSPAdes, MEGAHIT, andmore » IDBA-UD, were the most effective at assembling viromes. Read pre-processing, such as partitioning, had virtually no impact on assembly output, but may be useful when hardware is limited. Viral populations with 2–5 × coverage typically assembled well, whereas lesser coverage led to fragmented assembly. Strain heterogeneity within populations hampered assembly, especially when strains were closely related (average nucleotide identity, or ANI ≥97%) and when the most abundant strain represented <50% of the population. Viral community composition assessments based on read recruitment were generally accurate when the following thresholds for detection were applied: (i) ≥10 kb contig lengths to define populations, (ii) coverage defined from reads mapping at ≥90% identity, and (iii) ≥75% of contig length with ≥1 × coverage. Finally, although data are limited to the most abundant viruses in a community, alpha and beta diversity patterns were robustly estimated (±10%) when comparing samples of similar sequencing depth, but more divergent (up to 80%) when sequencing depth was uneven across the dataset. In the latter cases, the use of normalization

Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes.

PubMed

Niu, Sheng-Yong; Yang, Jinyu; McDermaid, Adam; Zhao, Jing; Kang, Yu; Ma, Qin

2017-05-08

Metagenomic and metatranscriptomic sequencing approaches are more frequently being used to link microbiota to important diseases and ecological changes. Many analyses have been used to compare the taxonomic and functional profiles of microbiota across habitats or individuals. While a large portion of metagenomic analyses focus on species-level profiling, some studies use strain-level metagenomic analyses to investigate the relationship between specific strains and certain circumstances. Metatranscriptomic analysis provides another important insight into activities of genes by examining gene expression levels of microbiota. Hence, combining metagenomic and metatranscriptomic analyses will help understand the activity or enrichment of a given gene set, such as drug-resistant genes among microbiome samples. Here, we summarize existing bioinformatics tools of metagenomic and metatranscriptomic data analysis, the purpose of which is to assist researchers in deciding the appropriate tools for their microbiome studies. Additionally, we propose an Integrated Meta-Function mapping pipeline to incorporate various reference databases and accelerate functional gene mapping procedures for both metagenomic and metatranscriptomic analyses. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

EBI metagenomics—a new resource for the analysis and archiving of metagenomic data

PubMed Central

Hunter, Sarah; Corbett, Matthew; Denise, Hubert; Fraser, Matthew; Gonzalez-Beltran, Alejandra; Hunter, Christopher; Jones, Philip; Leinonen, Rasko; McAnulla, Craig; Maguire, Eamonn; Maslen, John; Mitchell, Alex; Nuka, Gift; Oisel, Arnaud; Pesseat, Sebastien; Radhakrishnan, Rajesh; Rocca-Serra, Philippe; Scheremetjew, Maxim; Sterk, Peter; Vaughan, Daniel; Cochrane, Guy; Field, Dawn; Sansone, Susanna-Assunta

2014-01-01

Metagenomics is a relatively recently established but rapidly expanding field that uses high-throughput next-generation sequencing technologies to characterize the microbial communities inhabiting different ecosystems (including oceans, lakes, soil, tundra, plants and body sites). Metagenomics brings with it a number of challenges, including the management, analysis, storage and sharing of data. In response to these challenges, we have developed a new metagenomics resource (http://www.ebi.ac.uk/metagenomics/) that allows users to easily submit raw nucleotide reads for functional and taxonomic analysis by a state-of-the-art pipeline, and have them automatically stored (together with descriptive, standards-compliant metadata) in the European Nucleotide Archive. PMID:24165880

Metagenomic and Biochemical Characterizations of Sulfur Oxidation Metabolism in Uncultured Large Sausage-Shaped Bacterium in Hot Spring Microbial Mats

PubMed Central

Tamaki, Hideyuki; Kamagata, Yoichi; Hanada, Satoshi

2012-01-01

So-called “sulfur-turf” microbial mats in sulfide containing hot springs (55–70°C, pH 7.3–8.3) in Japan were dominated by a large sausage-shaped bacterium (LSSB) that is closely related to the genus Sulfurihydrogenibium. Several previous reports proposed that the LSSB would be involved in sulfide oxidation in hot spring. However, the LSSB has not been isolated yet, thus there has been no clear evidence showing whether it possesses any genes and enzymes responsible for sulfide oxidation. To verify this, we investigated sulfide oxidation potential in the LSSB using a metagenomic approach and subsequent biochemical analysis. Genome fragments of the LSSB (a total of 3.7 Mb sequence including overlapping fragments) were obtained from the metagenomic fosmid library constructed from genomic DNA of the sulfur-turf mats. The sequence annotation clearly revealed that the LSSB possesses sulfur oxidation-related genes coding sulfide dehydrogenase (SD), sulfide-quinone reductase and sulfite dehydrogenase. The gene encoding SD, the key enzyme for sulfide oxidation, was successfully cloned and heterologously expressed in Escherichia coli. The purified recombinant enzyme clearly showed SD activity with optimum temperature and pH of 60°C and 8.0, respectively, which were consistent with the environmental conditions in the hot spring where the sulfur-turf thrives. Furthermore, the affinity of SD to sulfide was relatively high, which also reflected the environment where the sulfide could be continuously supplied. This is the first report showing that the LSSB harbors sulfide oxidizing metabolism adapted to the hot spring environment and can be involved in sulfide oxidation in the sulfur-turf microbial mats. PMID:23185438

MetAMOS: a modular and open source metagenomic assembly and analysis pipeline

PubMed Central

2013-01-01

We describe MetAMOS, an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations. MetAMOS can aid in reducing assembly errors, commonly encountered when assembling metagenomic samples, and improves taxonomic assignment accuracy while also reducing computational cost. MetAMOS can be downloaded from: https://github.com/treangen/MetAMOS. PMID:23320958

Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments.

PubMed

Port, Jesse A; Cullen, Alison C; Wallace, James C; Smith, Marissa N; Faustman, Elaine M

2014-03-01

High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. We used a metagenomic epidemiology-based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments. Environ Health Perspect 122:222–228; http://dx.doi.org/10.1289/ehp

Metagenomic gene annotation by a homology-independent approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Froula, Jeff; Zhang, Tao; Salmeen, Annette

2011-06-02

Fully understanding the genetic potential of a microbial community requires functional annotation of all the genes it encodes. The recently developed deep metagenome sequencing approach has enabled rapid identification of millions of genes from a complex microbial community without cultivation. Current homology-based gene annotation fails to detect distantly-related or structural homologs. Furthermore, homology searches with millions of genes are very computational intensive. To overcome these limitations, we developed rhModeller, a homology-independent software pipeline to efficiently annotate genes from metagenomic sequencing projects. Using cellulases and carbonic anhydrases as two independent test cases, we demonstrated that rhModeller is much faster than HMMERmore » but with comparable accuracy, at 94.5percent and 99.9percent accuracy, respectively. More importantly, rhModeller has the ability to detect novel proteins that do not share significant homology to any known protein families. As {approx}50percent of the 2 million genes derived from the cow rumen metagenome failed to be annotated based on sequence homology, we tested whether rhModeller could be used to annotate these genes. Preliminary results suggest that rhModeller is robust in the presence of missense and frameshift mutations, two common errors in metagenomic genes. Applying the pipeline to the cow rumen genes identified 4,990 novel cellulases candidates and 8,196 novel carbonic anhydrase candidates.In summary, we expect rhModeller to dramatically increase the speed and quality of metagnomic gene annotation.« less

ELIXIR pilot action: Marine metagenomics - towards a domain specific set of sustainable services.

PubMed

Robertsen, Espen Mikal; Denise, Hubert; Mitchell, Alex; Finn, Robert D; Bongo, Lars Ailo; Willassen, Nils Peder

2017-01-01

Metagenomics, the study of genetic material recovered directly from environmental samples, has the potential to provide insight into the structure and function of heterogeneous microbial communities.  There has been an increased use of metagenomics to discover and understand the diverse biosynthetic capacities of marine microbes, thereby allowing them to be exploited for industrial, food, and health care products. This ELIXIR pilot action was motivated by the need to establish dedicated data resources and harmonized metagenomics pipelines for the marine domain, in order to enhance the exploration and exploitation of marine genetic resources. In this paper, we summarize some of the results from the ELIXIR pilot action "Marine metagenomics - towards user centric services".

Identifying areas of relative change in forest fragmentation in New Hampshire between 1990 and 2000

Treesearch

Tonya Lister; Andrew Lister; William McWilliams; Rachel Riemann

2007-01-01

Forest fragmentation potentially can impact many facets of natural ecosystems. Numerous methods have been employed to assess static forest fragmentation. Few studies, however, have analyzed changes in forest fragmentation over time. In this study, we developed new classifications from Landsat imagery data acquired in 1990 and 2000 for New Hampshire, assessed...

Computational prediction of CRISPR cassettes in gut metagenome samples from Chinese type-2 diabetic patients and healthy controls.

PubMed

Mangericao, Tatiana C; Peng, Zhanhao; Zhang, Xuegong

2016-01-11

CRISPR has been becoming a hot topic as a powerful technique for genome editing for human and other higher organisms. The original CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats coupled with CRISPR-associated proteins) is an important adaptive defence system for prokaryotes that provides resistance against invading elements such as viruses and plasmids. A CRISPR cassette contains short nucleotide sequences called spacers. These unique regions retain a history of the interactions between prokaryotes and their invaders in individual strains and ecosystems. One important ecosystem in the human body is the human gut, a rich habitat populated by a great diversity of microorganisms. Gut microbiomes are important for human physiology and health. Metagenome sequencing has been widely applied for studying the gut microbiomes. Most efforts in metagenome study has been focused on profiling taxa compositions and gene catalogues and identifying their associations with human health. Less attention has been paid to the analysis of the ecosystems of microbiomes themselves especially their CRISPR composition. We conducted a preliminary analysis of CRISPR sequences in a human gut metagenomic data set of Chinese individuals of type-2 diabetes patients and healthy controls. Applying an available CRISPR-identification algorithm, PILER-CR, we identified 3169 CRISPR cassettes in the data, from which we constructed a set of 1302 unique repeat sequences and 36,709 spacers. A more extensive analysis was made for the CRISPR repeats: these repeats were submitted to a more comprehensive clustering and classification using the web server tool CRISPRmap. All repeats were compared with known CRISPRs in the database CRISPRdb. A total of 784 repeats had matches in the database, and the remaining 518 repeats from our set are potentially novel ones. The computational analysis of CRISPR composition based contigs of metagenome sequencing data is feasible. It provides an efficient

Challenges and opportunities in understanding microbial communities with metagenome assembly (accompanied by IPython Notebook tutorial)

DOE PAGES

Howe, Adina; Chain, Patrick S. G.

2015-07-09

Metagenomic investigations hold great promise for informing the genetics, physiology, and ecology of environmental microorganisms. Current challenges for metagenomic analysis are related to our ability to connect the dots between sequencing reads, their population of origin, and their encoding functions. Assembly-based methods reduce dataset size by extending overlapping reads into larger contiguous sequences (contigs), providing contextual information for genetic sequences that does not rely on existing references. These methods, however, tend to be computationally intensive and are again challenged by sequencing errors as well as by genomic repeats. While numerous tools have been developed based on these methodological concepts, theymore » present confounding choices and training requirements to metagenomic investigators. To help with accessibility to assembly tools, this review also includes an IPython Notebook metagenomic assembly tutorial. This tutorial has instructions for execution any operating system using Amazon Elastic Cloud Compute and guides users through downloading, assembly, and mapping reads to contigs of a mock microbiome metagenome. Despite its challenges, metagenomic analysis has already revealed novel insights into many environments on Earth. As software, training, and data continue to emerge, metagenomic data access and its discoveries will to grow.« less

Challenges and opportunities in understanding microbial communities with metagenome assembly (accompanied by IPython Notebook tutorial)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Howe, Adina; Chain, Patrick S. G.

Metagenomic investigations hold great promise for informing the genetics, physiology, and ecology of environmental microorganisms. Current challenges for metagenomic analysis are related to our ability to connect the dots between sequencing reads, their population of origin, and their encoding functions. Assembly-based methods reduce dataset size by extending overlapping reads into larger contiguous sequences (contigs), providing contextual information for genetic sequences that does not rely on existing references. These methods, however, tend to be computationally intensive and are again challenged by sequencing errors as well as by genomic repeats. While numerous tools have been developed based on these methodological concepts, theymore » present confounding choices and training requirements to metagenomic investigators. To help with accessibility to assembly tools, this review also includes an IPython Notebook metagenomic assembly tutorial. This tutorial has instructions for execution any operating system using Amazon Elastic Cloud Compute and guides users through downloading, assembly, and mapping reads to contigs of a mock microbiome metagenome. Despite its challenges, metagenomic analysis has already revealed novel insights into many environments on Earth. As software, training, and data continue to emerge, metagenomic data access and its discoveries will to grow.« less

A machine learning approach for viral genome classification.

PubMed

Remita, Mohamed Amine; Halioui, Ahmed; Malick Diouara, Abou Abdallah; Daigle, Bruno; Kiani, Golrokh; Diallo, Abdoulaye Baniré

2017-04-11

Advances in cloning and sequencing technology are yielding a massive number of viral genomes. The classification and annotation of these genomes constitute important assets in the discovery of genomic variability, taxonomic characteristics and disease mechanisms. Existing classification methods are often designed for specific well-studied family of viruses. Thus, the viral comparative genomic studies could benefit from more generic, fast and accurate tools for classifying and typing newly sequenced strains of diverse virus families. Here, we introduce a virus classification platform, CASTOR, based on machine learning methods. CASTOR is inspired by a well-known technique in molecular biology: restriction fragment length polymorphism (RFLP). It simulates, in silico, the restriction digestion of genomic material by different enzymes into fragments. It uses two metrics to construct feature vectors for machine learning algorithms in the classification step. We benchmark CASTOR for the classification of distinct datasets of human papillomaviruses (HPV), hepatitis B viruses (HBV) and human immunodeficiency viruses type 1 (HIV-1). Results reveal true positive rates of 99%, 99% and 98% for HPV Alpha species, HBV genotyping and HIV-1 M subtyping, respectively. Furthermore, CASTOR shows a competitive performance compared to well-known HIV-1 specific classifiers (REGA and COMET) on whole genomes and pol fragments. The performance of CASTOR, its genericity and robustness could permit to perform novel and accurate large scale virus studies. The CASTOR web platform provides an open access, collaborative and reproducible machine learning classifiers. CASTOR can be accessed at http://castor.bioinfo.uqam.ca .

Genomics and metagenomics in medical microbiology.

PubMed

Padmanabhan, Roshan; Mishra, Ajay Kumar; Raoult, Didier; Fournier, Pierre-Edouard

2013-12-01

Over the last two decades, sequencing tools have evolved from laborious time-consuming methodologies to real-time detection and deciphering of genomic DNA. Genome sequencing, especially using next generation sequencing (NGS) has revolutionized the landscape of microbiology and infectious disease. This deluge of sequencing data has not only enabled advances in fundamental biology but also helped improve diagnosis, typing of pathogen, virulence and antibiotic resistance detection, and development of new vaccines and culture media. In addition, NGS also enabled efficient analysis of complex human micro-floras, both commensal, and pathological, through metagenomic methods, thus helping the comprehension and management of human diseases such as obesity. This review summarizes technological advances in genomics and metagenomics relevant to the field of medical microbiology. Copyright © 2013 Elsevier B.V. All rights reserved.

Metagenomic Exploration of Viruses throughout the Indian Ocean

PubMed Central

Lorenzi, Hernan A.; Fadrosh, Douglas W.; Brami, Daniel; Thiagarajan, Mathangi; McCrow, John P.; Tovchigrechko, Andrey; Yooseph, Shibu; Venter, J. Craig

2012-01-01

The characterization of global marine microbial taxonomic and functional diversity is a primary goal of the Global Ocean Sampling Expedition. As part of this study, 19 water samples were collected aboard the Sorcerer II sailing vessel from the southern Indian Ocean in an effort to more thoroughly understand the lifestyle strategies of the microbial inhabitants of this ultra-oligotrophic region. No investigations of whole virioplankton assemblages have been conducted on waters collected from the Indian Ocean or across multiple size fractions thus far. Therefore, the goals of this study were to examine the effect of size fractionation on viral consortia structure and function and understand the diversity and functional potential of the Indian Ocean virome. Five samples were selected for comprehensive metagenomic exploration; and sequencing was performed on the microbes captured on 3.0-, 0.8- and 0.1 µm membrane filters as well as the viral fraction (<0.1 µm). Phylogenetic approaches were also used to identify predicted proteins of viral origin in the larger fractions of data from all Indian Ocean samples, which were included in subsequent metagenomic analyses. Taxonomic profiling of viral sequences suggested that size fractionation of marine microbial communities enriches for specific groups of viruses within the different size classes and functional characterization further substantiated this observation. Functional analyses also revealed a relative enrichment for metabolic proteins of viral origin that potentially reflect the physiological condition of host cells in the Indian Ocean including those involved in nitrogen metabolism and oxidative phosphorylation. A novel classification method, MGTAXA, was used to assess virus-host relationships in the Indian Ocean by predicting the taxonomy of putative host genera, with Prochlorococcus, Acanthochlois and members of the SAR86 cluster comprising the most abundant predictions. This is the first study to holistically

Amplification of thermostable lipase genes fragment from thermogenic phase of domestic waste composting process

NASA Astrophysics Data System (ADS)

Nurhasanah, Nurbaiti, Santi; Madayanti, Fida; Akhmaloka

2015-09-01

Lipases are lipolytic enzymes, catalyze the hydrolysis of fatty acid ester bonds of triglycerides to produce free fatty acids and glycerol. The enzyme is widely used in various fields of biotechnological industry. Hence, lipases with unique properties (e.g.thermostable lipase) are still being explored by variation methods. One of the strategy is by using metagenomic approach to amplify the gene directly from environmental sample. This research was focused on amplification of lipase gene fragment directly from the thermogenic phase of domestic waste composting in aerated trenches. We used domestic waste compost from waste treatment at SABUGA, ITB for the sample. Total chromosomal DNA were directly extracted from several stages at thermogenic phase of compost. The DNA was then directly used as a template for amplification of thermostable lipase gene fragments using a set of internal primers namely Flip-1a and Rlip-1a that has been affixed with a GC clamp in reverse primer. The results showed that the primers amplified the gene from four stages of thermogenic phase with the size of lipase gene fragment of approximately 570 base pairs (bp). These results were further used for Denaturing Gradient Gel Electrophoresis (DGGE) analysis to determine diversity of thermostable lipase gene fragments.

Recovering complete and draft population genomes from metagenome datasets

DOE PAGES

Sangwan, Naseer; Xia, Fangfang; Gilbert, Jack A.

2016-03-08

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem ofmore » chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.« less

Recovering complete and draft population genomes from metagenome datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sangwan, Naseer; Xia, Fangfang; Gilbert, Jack A.

Assembly of metagenomic sequence data into microbial genomes is of fundamental value to improving our understanding of microbial ecology and metabolism by elucidating the functional potential of hard-to-culture microorganisms. Here, we provide a synthesis of available methods to bin metagenomic contigs into species-level groups and highlight how genetic diversity, sequencing depth, and coverage influence binning success. Despite the computational cost on application to deeply sequenced complex metagenomes (e.g., soil), covarying patterns of contig coverage across multiple datasets significantly improves the binning process. We also discuss and compare current genome validation methods and reveal how these methods tackle the problem ofmore » chimeric genome bins i.e., sequences from multiple species. Finally, we explore how population genome assembly can be used to uncover biogeographic trends and to characterize the effect of in situ functional constraints on the genome-wide evolution.« less

fRMSDPred: Predicting Local RMSD Between Structural Fragments Using Sequence Information

DTIC Science & Technology

2007-04-04

machine learning approaches for estimating the RMSD value of a pair of protein fragments. These estimated fragment-level RMSD values can be used to construct the alignment, assess the quality of an alignment, and identify high-quality alignment segments. We present algorithms to solve this fragment-level RMSD prediction problem using a supervised learning framework based on support vector regression and classification that incorporates protein profiles, predicted secondary structure, effective information encoding schemes, and novel second-order pairwise exponential kernel

Metagenomic Frameworks for Monitoring Antibiotic Resistance in Aquatic Environments

PubMed Central

Port, Jesse A.; Cullen, Alison C.; Wallace, James C.; Smith, Marissa N.

2013-01-01

Background: High-throughput genomic technologies offer new approaches for environmental health monitoring, including metagenomic surveillance of antibiotic resistance determinants (ARDs). Although natural environments serve as reservoirs for antibiotic resistance genes that can be transferred to pathogenic and human commensal bacteria, monitoring of these determinants has been infrequent and incomplete. Furthermore, surveillance efforts have not been integrated into public health decision making. Objectives: We used a metagenomic epidemiology–based approach to develop an ARD index that quantifies antibiotic resistance potential, and we analyzed this index for common modal patterns across environmental samples. We also explored how metagenomic data such as this index could be conceptually framed within an early risk management context. Methods: We analyzed 25 published data sets from shotgun pyrosequencing projects. The samples consisted of microbial community DNA collected from marine and freshwater environments across a gradient of human impact. We used principal component analysis to identify index patterns across samples. Results: We observed significant differences in the overall index and index subcategory levels when comparing ecosystems more proximal versus distal to human impact. The selection of different sequence similarity thresholds strongly influenced the index measurements. Unique index subcategory modes distinguished the different metagenomes. Conclusions: Broad-scale screening of ARD potential using this index revealed utility for framing environmental health monitoring and surveillance. This approach holds promise as a screening tool for establishing baseline ARD levels that can be used to inform and prioritize decision making regarding management of ARD sources and human exposure routes. Citation: Port JA, Cullen AC, Wallace JC, Smith MN, Faustman EM. 2014. Metagenomic frameworks for monitoring antibiotic resistance in aquatic environments

Comparative analysis of metagenomes of Italian top soil improvers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gigliucci, Federica, E-mail: Federica.gigliucci@li

Biosolids originating from Municipal Waste Water Treatment Plants are proposed as top soil improvers (TSI) for their beneficial input of organic carbon on agriculture lands. Their use to amend soil is controversial, as it may lead to the presence of emerging hazards of anthropogenic or animal origin in the environment devoted to food production. In this study, we used a shotgun metagenomics sequencing as a tool to perform a characterization of the hazards related with the TSIs. The samples showed the presence of many virulence genes associated to different diarrheagenic E. coli pathotypes as well as of different antimicrobial resistance-associatedmore » genes. The genes conferring resistance to Fluoroquinolones was the most relevant class of antimicrobial resistance genes observed in all the samples tested. To a lesser extent traits associated with the resistance to Methicillin in Staphylococci and genes conferring resistance to Streptothricin, Fosfomycin and Vancomycin were also identified. The most represented metal resistance genes were cobalt-zinc-cadmium related, accounting for 15–50% of the sequence reads in the different metagenomes out of the total number of those mapping on the class of resistance to compounds determinants. Moreover the taxonomic analysis performed by comparing compost-based samples and biosolids derived from municipal sewage-sludges treatments divided the samples into separate populations, based on the microbiota composition. The results confirm that the metagenomics is efficient to detect genomic traits associated with pathogens and antimicrobial resistance in complex matrices and this approach can be efficiently used for the traceability of TSI samples using the microorganisms’ profiles as indicators of their origin. - Highlights: • Sludge- and green- based biosolids analysed by metagenomics. • Biosolids may introduce microbial hazards in the food chain. • Metagenomics enables tracking biosolids’ sources.« less

A Delphi Technology Foresight Study: Mapping Social Construction of Scientific Evidence on Metagenomics Tests for Water Safety

PubMed Central

Birko, Stanislav; Dove, Edward S.; Özdemir, Vural

2015-01-01

Access to clean water is a grand challenge in the 21st century. Water safety testing for pathogens currently depends on surrogate measures such as fecal indicator bacteria (e.g., E. coli). Metagenomics concerns high-throughput, culture-independent, unbiased shotgun sequencing of DNA from environmental samples that might transform water safety by detecting waterborne pathogens directly instead of their surrogates. Yet emerging innovations such as metagenomics are often fiercely contested. Innovations are subject to shaping/construction not only by technology but also social systems/values in which they are embedded, such as experts’ attitudes towards new scientific evidence. We conducted a classic three-round Delphi survey, comprised of 107 questions. A multidisciplinary expert panel (n = 24) representing the continuum of discovery scientists and policymakers evaluated the emergence of metagenomics tests. To the best of our knowledge, we report here the first Delphi foresight study of experts’ attitudes on (1) the top 10 priority evidentiary criteria for adoption of metagenomics tests for water safety, (2) the specific issues critical to governance of metagenomics innovation trajectory where there is consensus or dissensus among experts, (3) the anticipated time lapse from discovery to practice of metagenomics tests, and (4) the role and timing of public engagement in development of metagenomics tests. The ability of a test to distinguish between harmful and benign waterborne organisms, analytical/clinical sensitivity, and reproducibility were the top three evidentiary criteria for adoption of metagenomics. Experts agree that metagenomic testing will provide novel information but there is dissensus on whether metagenomics will replace the current water safety testing methods or impact the public health end points (e.g., reduction in boil water advisories). Interestingly, experts view the publics relevant in a “downstream capacity” for adoption of

MOCAT: A Metagenomics Assembly and Gene Prediction Toolkit

PubMed Central

Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R.; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/. PMID:23082188

MOCAT: a metagenomics assembly and gene prediction toolkit.

PubMed

Kultima, Jens Roat; Sunagawa, Shinichi; Li, Junhua; Chen, Weineng; Chen, Hua; Mende, Daniel R; Arumugam, Manimozhiyan; Pan, Qi; Liu, Binghang; Qin, Junjie; Wang, Jun; Bork, Peer

2012-01-01

MOCAT is a highly configurable, modular pipeline for fast, standardized processing of single or paired-end sequencing data generated by the Illumina platform. The pipeline uses state-of-the-art programs to quality control, map, and assemble reads from metagenomic samples sequenced at a depth of several billion base pairs, and predict protein-coding genes on assembled metagenomes. Mapping against reference databases allows for read extraction or removal, as well as abundance calculations. Relevant statistics for each processing step can be summarized into multi-sheet Excel documents and queryable SQL databases. MOCAT runs on UNIX machines and integrates seamlessly with the SGE and PBS queuing systems, commonly used to process large datasets. The open source code and modular architecture allow users to modify or exchange the programs that are utilized in the various processing steps. Individual processing steps and parameters were benchmarked and tested on artificial, real, and simulated metagenomes resulting in an improvement of selected quality metrics. MOCAT can be freely downloaded at http://www.bork.embl.de/mocat/.

Automated and Accurate Estimation of Gene Family Abundance from Shotgun Metagenomes

PubMed Central

Nayfach, Stephen; Bradley, Patrick H.; Wyman, Stacia K.; Laurent, Timothy J.; Williams, Alex; Eisen, Jonathan A.; Pollard, Katherine S.; Sharpton, Thomas J.

2015-01-01

Shotgun metagenomic DNA sequencing is a widely applicable tool for characterizing the functions that are encoded by microbial communities. Several bioinformatic tools can be used to functionally annotate metagenomes, allowing researchers to draw inferences about the functional potential of the community and to identify putative functional biomarkers. However, little is known about how decisions made during annotation affect the reliability of the results. Here, we use statistical simulations to rigorously assess how to optimize annotation accuracy and speed, given parameters of the input data like read length and library size. We identify best practices in metagenome annotation and use them to guide the development of the Shotgun Metagenome Annotation Pipeline (ShotMAP). ShotMAP is an analytically flexible, end-to-end annotation pipeline that can be implemented either on a local computer or a cloud compute cluster. We use ShotMAP to assess how different annotation databases impact the interpretation of how marine metagenome and metatranscriptome functional capacity changes across seasons. We also apply ShotMAP to data obtained from a clinical microbiome investigation of inflammatory bowel disease. This analysis finds that gut microbiota collected from Crohn’s disease patients are functionally distinct from gut microbiota collected from either ulcerative colitis patients or healthy controls, with differential abundance of metabolic pathways related to host-microbiome interactions that may serve as putative biomarkers of disease. PMID:26565399

Comparing K-mer based methods for improved classification of 16S sequences.

PubMed

Vinje, Hilde; Liland, Kristian Hovde; Almøy, Trygve; Snipen, Lars

2015-07-01

The need for precise and stable taxonomic classification is highly relevant in modern microbiology. Parallel to the explosion in the amount of sequence data accessible, there has also been a shift in focus for classification methods. Previously, alignment-based methods were the most applicable tools. Now, methods based on counting K-mers by sliding windows are the most interesting classification approach with respect to both speed and accuracy. Here, we present a systematic comparison on five different K-mer based classification methods for the 16S rRNA gene. The methods differ from each other both in data usage and modelling strategies. We have based our study on the commonly known and well-used naïve Bayes classifier from the RDP project, and four other methods were implemented and tested on two different data sets, on full-length sequences as well as fragments of typical read-length. The difference in classification error obtained by the methods seemed to be small, but they were stable and for both data sets tested. The Preprocessed nearest-neighbour (PLSNN) method performed best for full-length 16S rRNA sequences, significantly better than the naïve Bayes RDP method. On fragmented sequences the naïve Bayes Multinomial method performed best, significantly better than all other methods. For both data sets explored, and on both full-length and fragmented sequences, all the five methods reached an error-plateau. We conclude that no K-mer based method is universally best for classifying both full-length sequences and fragments (reads). All methods approach an error plateau indicating improved training data is needed to improve classification from here. Classification errors occur most frequent for genera with few sequences present. For improving the taxonomy and testing new classification methods, the need for a better and more universal and robust training data set is crucial.

The effects of variable sample biomass on comparative metagenomics.

PubMed

Chafee, Meghan; Maignien, Loïs; Simmons, Sheri L

2015-07-01

Longitudinal studies that integrate samples with variable biomass are essential to understand microbial community dynamics across space or time. Shotgun metagenomics is widely used to investigate these communities at the functional level, but little is known about the effects of combining low and high biomass samples on downstream analysis. We investigated the interacting effects of DNA input and library amplification by polymerase chain reaction on comparative metagenomic analysis using dilutions of a single complex template from an Arabidopsis thaliana-associated microbial community. We modified the Illumina Nextera kit to generate high-quality large-insert (680 bp) paired-end libraries using a range of 50 pg to 50 ng of input DNA. Using assembly-based metagenomic analysis, we demonstrate that DNA input level has a significant impact on community structure due to overrepresentation of low-GC genomic regions following library amplification. In our system, these differences were largely superseded by variations between biological replicates, but our results advocate verifying the influence of library amplification on a case-by-case basis. Overall, this study provides recommendations for quality filtering and de-replication prior to analysis, as well as a practical framework to address the issue of low biomass or biomass heterogeneity in longitudinal metagenomic surveys. © 2014 Society for Applied Microbiology and John Wiley & Sons Ltd.

Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C)

PubMed Central

DeMaere, Matthew Z.

2016-01-01

Background Chromosome conformation capture, coupled with high throughput DNA sequencing in protocols like Hi-C and 3C-seq, has been proposed as a viable means of generating data to resolve the genomes of microorganisms living in naturally occuring environments. Metagenomic Hi-C and 3C-seq datasets have begun to emerge, but the feasibility of resolving genomes when closely related organisms (strain-level diversity) are present in the sample has not yet been systematically characterised. Methods We developed a computational simulation pipeline for metagenomic 3C and Hi-C sequencing to evaluate the accuracy of genomic reconstructions at, above, and below an operationally defined species boundary. We simulated datasets and measured accuracy over a wide range of parameters. Five clustering algorithms were evaluated (2 hard, 3 soft) using an adaptation of the extended B-cubed validation measure. Results When all genomes in a sample are below 95% sequence identity, all of the tested clustering algorithms performed well. When sequence data contains genomes above 95% identity (our operational definition of strain-level diversity), a naive soft-clustering extension of the Louvain method achieves the highest performance. Discussion Previously, only hard-clustering algorithms have been applied to metagenomic 3C and Hi-C data, yet none of these perform well when strain-level diversity exists in a metagenomic sample. Our simple extension of the Louvain method performed the best in these scenarios, however, accuracy remained well below the levels observed for samples without strain-level diversity. Strain resolution is also highly dependent on the amount of available 3C sequence data, suggesting that depth of sequencing must be carefully considered during experimental design. Finally, there appears to be great scope to improve the accuracy of strain resolution through further algorithm development. PMID:27843713

MPD: a pathogen genome and metagenome database

PubMed Central

Zhang, Tingting; Miao, Jiaojiao; Han, Na; Qiang, Yujun; Zhang, Wen

2018-01-01

Abstract Advances in high-throughput sequencing have led to unprecedented growth in the amount of available genome sequencing data, especially for bacterial genomes, which has been accompanied by a challenge for the storage and management of such huge datasets. To facilitate bacterial research and related studies, we have developed the Mypathogen database (MPD), which provides access to users for searching, downloading, storing and sharing bacterial genomics data. The MPD represents the first pathogenic database for microbial genomes and metagenomes, and currently covers pathogenic microbial genomes (6604 genera, 11 071 species, 41 906 strains) and metagenomic data from host, air, water and other sources (28 816 samples). The MPD also functions as a management system for statistical and storage data that can be used by different organizations, thereby facilitating data sharing among different organizations and research groups. A user-friendly local client tool is provided to maintain the steady transmission of big sequencing data. The MPD is a useful tool for analysis and management in genomic research, especially for clinical Centers for Disease Control and epidemiological studies, and is expected to contribute to advancing knowledge on pathogenic bacteria genomes and metagenomes. Database URL: http://data.mypathogen.org PMID:29917040

A retrospective metagenomics approach to studying Blastocystis.

PubMed

Andersen, Lee O'Brien; Bonde, Ida; Nielsen, Henrik Bjørn; Stensvold, Christen Rune

2015-07-01

Blastocystis is a common single-celled intestinal parasitic genus, comprising several subtypes. Here, we screened data obtained by metagenomic analysis of faecal DNA for Blastocystis by searching for subtype-specific genes in coabundance gene groups, which are groups of genes that covary across a selection of 316 human faecal samples, hence representing genes originating from a single subtype. The 316 faecal samples were from 236 healthy individuals, 13 patients with Crohn's disease (CD) and 67 patients with ulcerative colitis (UC). The prevalence of Blastocystis was 20.3% in the healthy individuals and 14.9% in patients with UC. Meanwhile, Blastocystis was absent in patients with CD. Individuals with intestinal microbiota dominated by Bacteroides were much less prone to having Blastocystis-positive stool (Matthew's correlation coefficient = -0.25, P < 0.0001) than individuals with Ruminococcus- and Prevotella-driven enterotypes. This is the first study to investigate the relationship between Blastocystis and communities of gut bacteria using a metagenomics approach. The study serves as an example of how it is possible to retrospectively investigate microbial eukaryotic communities in the gut using metagenomic datasets targeting the bacterial component of the intestinal microbiome and the interplay between these microbial communities. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

ELIXIR pilot action: Marine metagenomics – towards a domain specific set of sustainable services

PubMed Central

Robertsen, Espen Mikal; Denise, Hubert; Mitchell, Alex; Finn, Robert D.; Bongo, Lars Ailo; Willassen, Nils Peder

2017-01-01

Metagenomics, the study of genetic material recovered directly from environmental samples, has the potential to provide insight into the structure and function of heterogeneous microbial communities.  There has been an increased use of metagenomics to discover and understand the diverse biosynthetic capacities of marine microbes, thereby allowing them to be exploited for industrial, food, and health care products. This ELIXIR pilot action was motivated by the need to establish dedicated data resources and harmonized metagenomics pipelines for the marine domain, in order to enhance the exploration and exploitation of marine genetic resources. In this paper, we summarize some of the results from the ELIXIR pilot action “Marine metagenomics – towards user centric services”. PMID:28620454

Pooled assembly of marine metagenomic datasets: enriching annotation through chimerism.

PubMed

Magasin, Jonathan D; Gerloff, Dietlind L

2015-02-01

Despite advances in high-throughput sequencing, marine metagenomic samples remain largely opaque. A typical sample contains billions of microbial organisms from thousands of genomes and quadrillions of DNA base pairs. Its derived metagenomic dataset underrepresents this complexity by orders of magnitude because of the sparseness and shortness of sequencing reads. Read shortness and sequencing errors pose a major challenge to accurate species and functional annotation. This includes distinguishing known from novel species. Often the majority of reads cannot be annotated and thus cannot help our interpretation of the sample. Here, we demonstrate quantitatively how careful assembly of marine metagenomic reads within, but also across, datasets can alleviate this problem. For 10 simulated datasets, each with species complexity modeled on a real counterpart, chimerism remained within the same species for most contigs (97%). For 42 real pyrosequencing ('454') datasets, assembly increased the proportion of annotated reads, and even more so when datasets were pooled, by on average 1.6% (max 6.6%) for species, 9.0% (max 28.7%) for Pfam protein domains and 9.4% (max 22.9%) for PANTHER gene families. Our results outline exciting prospects for data sharing in the metagenomics community. While chimeric sequences should be avoided in other areas of metagenomics (e.g. biodiversity analyses), conservative pooled assembly is advantageous for annotation specificity and sensitivity. Intriguingly, our experiment also found potential prospects for (low-cost) discovery of new species in 'old' data. dgerloff@ffame.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs.

PubMed

Eloe-Fadrosh, Emiley A; Paez-Espino, David; Jarett, Jessica; Dunfield, Peter F; Hedlund, Brian P; Dekas, Anne E; Grasby, Stephen E; Brady, Allyson L; Dong, Hailiang; Briggs, Brandon R; Li, Wen-Jun; Goudeau, Danielle; Malmstrom, Rex; Pati, Amrita; Pett-Ridge, Jennifer; Rubin, Edward M; Woyke, Tanja; Kyrpides, Nikos C; Ivanova, Natalia N

2016-01-27

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum ('Candidatus Kryptonia') found exclusively in high-temperature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic 'blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestyle with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery.

MALINA: a web service for visual analytics of human gut microbiota whole-genome metagenomic reads.

PubMed

Tyakht, Alexander V; Popenko, Anna S; Belenikin, Maxim S; Altukhov, Ilya A; Pavlenko, Alexander V; Kostryukova, Elena S; Selezneva, Oksana V; Larin, Andrei K; Karpova, Irina Y; Alexeev, Dmitry G

2012-12-07

MALINA is a web service for bioinformatic analysis of whole-genome metagenomic data obtained from human gut microbiota sequencing. As input data, it accepts metagenomic reads of various sequencing technologies, including long reads (such as Sanger and 454 sequencing) and next-generation (including SOLiD and Illumina). It is the first metagenomic web service that is capable of processing SOLiD color-space reads, to authors' knowledge. The web service allows phylogenetic and functional profiling of metagenomic samples using coverage depth resulting from the alignment of the reads to the catalogue of reference sequences which are built into the pipeline and contain prevalent microbial genomes and genes of human gut microbiota. The obtained metagenomic composition vectors are processed by the statistical analysis and visualization module containing methods for clustering, dimension reduction and group comparison. Additionally, the MALINA database includes vectors of bacterial and functional composition for human gut microbiota samples from a large number of existing studies allowing their comparative analysis together with user samples, namely datasets from Russian Metagenome project, MetaHIT and Human Microbiome Project (downloaded from http://hmpdacc.org). MALINA is made freely available on the web at http://malina.metagenome.ru. The website is implemented in JavaScript (using Ext JS), Microsoft .NET Framework, MS SQL, Python, with all major browsers supported.

Construction and screening of marine metagenomic libraries.

PubMed

Weiland, Nancy; Löscher, Carolin; Metzger, Rebekka; Schmitz, Ruth

2010-01-01

Marine microbial communities are highly diverse and have evolved during extended evolutionary processes of physiological adaptations under the influence of a variety of ecological conditions and selection pressures. They harbor an enormous diversity of microbes with still unknown and probably new physiological characteristics. Besides, the surfaces of marine multicellular organisms are typically covered by a consortium of epibiotic bacteria and act as barriers, where diverse interactions between microorganisms and hosts take place. Thus, microbial diversity in the water column of the oceans and the microbial consortia on marine tissues of multicellular organisms are rich sources for isolating novel bioactive compounds and genes. Here we describe the sampling, construction of large-insert metagenomic libraries from marine habitats and exemplarily one function based screen of metagenomic clones.

Meta-Storms: efficient search for similar microbial communities based on a novel indexing scheme and similarity score for metagenomic data.

PubMed

Su, Xiaoquan; Xu, Jian; Ning, Kang

2012-10-01

It has long been intriguing scientists to effectively compare different microbial communities (also referred as 'metagenomic samples' here) in a large scale: given a set of unknown samples, find similar metagenomic samples from a large repository and examine how similar these samples are. With the current metagenomic samples accumulated, it is possible to build a database of metagenomic samples of interests. Any metagenomic samples could then be searched against this database to find the most similar metagenomic sample(s). However, on one hand, current databases with a large number of metagenomic samples mostly serve as data repositories that offer few functionalities for analysis; and on the other hand, methods to measure the similarity of metagenomic data work well only for small set of samples by pairwise comparison. It is not yet clear, how to efficiently search for metagenomic samples against a large metagenomic database. In this study, we have proposed a novel method, Meta-Storms, that could systematically and efficiently organize and search metagenomic data. It includes the following components: (i) creating a database of metagenomic samples based on their taxonomical annotations, (ii) efficient indexing of samples in the database based on a hierarchical taxonomy indexing strategy, (iii) searching for a metagenomic sample against the database by a fast scoring function based on quantitative phylogeny and (iv) managing database by index export, index import, data insertion, data deletion and database merging. We have collected more than 1300 metagenomic data from the public domain and in-house facilities, and tested the Meta-Storms method on these datasets. Our experimental results show that Meta-Storms is capable of database creation and effective searching for a large number of metagenomic samples, and it could achieve similar accuracies compared with the current popular significance testing-based methods. Meta-Storms method would serve as a suitable

Intracellular screen to identify metagenomic clones that induce or inhibit a quorum-sensing biosensor.

PubMed

Williamson, Lynn L; Borlee, Bradley R; Schloss, Patrick D; Guan, Changhui; Allen, Heather K; Handelsman, Jo

2005-10-01

The goal of this study was to design and evaluate a rapid screen to identify metagenomic clones that produce biologically active small molecules. We built metagenomic libraries with DNA from soil on the floodplain of the Tanana River in Alaska. We extracted DNA directly from the soil and cloned it into fosmid and bacterial artificial chromosome vectors, constructing eight metagenomic libraries that contain 53,000 clones with inserts ranging from 1 to 190 kb. To identify clones of interest, we designed a high throughput "intracellular" screen, designated METREX, in which metagenomic DNA is in a host cell containing a biosensor for compounds that induce bacterial quorum sensing. If the metagenomic clone produces a quorum-sensing inducer, the cell produces green fluorescent protein (GFP) and can be identified by fluorescence microscopy or captured by fluorescence-activated cell sorting. Our initial screen identified 11 clones that induce and two that inhibit expression of GFP. The intracellular screen detected quorum-sensing inducers among metagenomic clones that a traditional overlay screen would not. One inducing clone carries a LuxI homologue that directs the synthesis of an N-acyl homoserine lactone quorum-sensing signal molecule. The LuxI homologue has 62% amino acid sequence identity to its closest match in GenBank, AmfI from Pseudomonas fluorescens, and is on a 78-kb insert that contains 67 open reading frames. Another inducing clone carries a gene with homology to homocitrate synthase. Our results demonstrate the power of an intracellular screen to identify functionally active clones and biologically active small molecules in metagenomic libraries.

The soil microbiome — from metagenomics to metaphenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jansson, Janet K.; Hofmockel, Kirsten S.

Soil microorganisms carry out important processes, including support of plant growth and cycling of carbon and other nutrients. However, the majority of soil microbes have not yet been isolated and their functions are largely unknown. Although metagenomic sequencing reveals microbial identities and functional gene information, it includes DNA from microbes with vastly varying physiological states. Therefore, metagenomics is only predictive of community functional potential. We posit that the next frontier lies in understanding the metaphenome, the product of the combined genetic potential of the microbiome and available resources. Here in this paper we describe examples of opportunities towards gaining understandingmore » of the soil metaphenome.« less

The soil microbiome — from metagenomics to metaphenomics

DOE PAGES

Jansson, Janet K.; Hofmockel, Kirsten S.

2018-02-15

Soil microorganisms carry out important processes, including support of plant growth and cycling of carbon and other nutrients. However, the majority of soil microbes have not yet been isolated and their functions are largely unknown. Although metagenomic sequencing reveals microbial identities and functional gene information, it includes DNA from microbes with vastly varying physiological states. Therefore, metagenomics is only predictive of community functional potential. We posit that the next frontier lies in understanding the metaphenome, the product of the combined genetic potential of the microbiome and available resources. Here in this paper we describe examples of opportunities towards gaining understandingmore » of the soil metaphenome.« less

Laboratory procedures to generate viral metagenomes.

PubMed

Thurber, Rebecca V; Haynes, Matthew; Breitbart, Mya; Wegley, Linda; Rohwer, Forest

2009-01-01

This collection of laboratory protocols describes the steps to collect viruses from various samples with the specific aim of generating viral metagenome sequence libraries (viromes). Viral metagenomics, the study of uncultured viral nucleic acid sequences from different biomes, relies on several concentration, purification, extraction, sequencing and heuristic bioinformatic methods. No single technique can provide an all-inclusive approach, and therefore the protocols presented here will be discussed in terms of hypothetical projects. However, care must be taken to individualize each step depending on the source and type of viral-particles. This protocol is a description of the processes we have successfully used to: (i) concentrate viral particles from various types of samples, (ii) eliminate contaminating cells and free nucleic acids and (iii) extract, amplify and purify viral nucleic acids. Overall, a sample can be processed to isolate viral nucleic acids suitable for high-throughput sequencing in approximately 1 week.

A Metagenomic Approach to Cyanobacterial Genomics

PubMed Central

Alvarenga, Danillo O.; Fiore, Marli F.; Varani, Alessandro M.

2017-01-01

Cyanobacteria, or oxyphotobacteria, are primary producers that establish ecological interactions with a wide variety of organisms. Although their associations with eukaryotes have received most attention, interactions with bacterial and archaeal symbionts have also been occurring for billions of years. Due to these associations, obtaining axenic cultures of cyanobacteria is usually difficult, and most isolation efforts result in unicyanobacterial cultures containing a number of associated microbes, hence composing a microbial consortium. With rising numbers of cyanobacterial blooms due to climate change, demand for genomic evaluations of these microorganisms is increasing. However, standard genomic techniques call for the sequencing of axenic cultures, an approach that not only adds months or even years for culture purification, but also appears to be impossible for some cyanobacteria, which is reflected in the relatively low number of publicly available genomic sequences of this phylum. Under the framework of metagenomics, on the other hand, cumbersome techniques for achieving axenic growth can be circumvented and individual genomes can be successfully obtained from microbial consortia. This review focuses on approaches for the genomic and metagenomic assessment of non-axenic cyanobacterial cultures that bypass requirements for axenity. These methods enable researchers to achieve faster and less costly genomic characterizations of cyanobacterial strains and raise additional information about their associated microorganisms. While non-axenic cultures may have been previously frowned upon in cyanobacteriology, latest advancements in metagenomics have provided new possibilities for in vitro studies of oxyphotobacteria, renewing the value of microbial consortia as a reliable and functional resource for the rapid assessment of bloom-forming cyanobacteria. PMID:28536564

Bayesian mixture analysis for metagenomic community profiling.

PubMed

Morfopoulou, Sofia; Plagnol, Vincent

2015-09-15

Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix sofia.morfopoulou.10@ucl.ac.uk Supplementary data are available at Bionformatics online. © The Author 2015. Published by Oxford University Press.

Validation of Metagenomic Next-Generation Sequencing Tests for Universal Pathogen Detection.

PubMed

Schlaberg, Robert; Chiu, Charles Y; Miller, Steve; Procop, Gary W; Weinstock, George

2017-06-01

- Metagenomic sequencing can be used for detection of any pathogens using unbiased, shotgun next-generation sequencing (NGS), without the need for sequence-specific amplification. Proof-of-concept has been demonstrated in infectious disease outbreaks of unknown causes and in patients with suspected infections but negative results for conventional tests. Metagenomic NGS tests hold great promise to improve infectious disease diagnostics, especially in immunocompromised and critically ill patients. - To discuss challenges and provide example solutions for validating metagenomic pathogen detection tests in clinical laboratories. A summary of current regulatory requirements, largely based on prior guidance for NGS testing in constitutional genetics and oncology, is provided. - Examples from 2 separate validation studies are provided for steps from assay design, and validation of wet bench and bioinformatics protocols, to quality control and assurance. - Although laboratory and data analysis workflows are still complex, metagenomic NGS tests for infectious diseases are increasingly being validated in clinical laboratories. Many parallels exist to NGS tests in other fields. Nevertheless, specimen preparation, rapidly evolving data analysis algorithms, and incomplete reference sequence databases are idiosyncratic to the field of microbiology and often overlooked.

Recovery of a Medieval Brucella melitensis Genome Using Shotgun Metagenomics

PubMed Central

Kay, Gemma L.; Sergeant, Martin J.; Giuffra, Valentina; Bandiera, Pasquale; Milanese, Marco; Bramanti, Barbara

2014-01-01

ABSTRACT Shotgun metagenomics provides a powerful assumption-free approach to the recovery of pathogen genomes from contemporary and historical material. We sequenced the metagenome of a calcified nodule from the skeleton of a 14th-century middle-aged male excavated from the medieval Sardinian settlement of Geridu. We obtained 6.5-fold coverage of a Brucella melitensis genome. Sequence reads from this genome showed signatures typical of ancient or aged DNA. Despite the relatively low coverage, we were able to use information from single-nucleotide polymorphisms to place the medieval pathogen genome within a clade of B. melitensis strains that included the well-studied Ether strain and two other recent Italian isolates. We confirmed this placement using information from deletions and IS711 insertions. We conclude that metagenomics stands ready to document past and present infections, shedding light on the emergence, evolution, and spread of microbial pathogens. PMID:25028426

Biotechnological applications of functional metagenomics in the food and pharmaceutical industries.

PubMed

Coughlan, Laura M; Cotter, Paul D; Hill, Colin; Alvarez-Ordóñez, Avelino

2015-01-01

Microorganisms are found throughout nature, thriving in a vast range of environmental conditions. The majority of them are unculturable or difficult to culture by traditional methods. Metagenomics enables the study of all microorganisms, regardless of whether they can be cultured or not, through the analysis of genomic data obtained directly from an environmental sample, providing knowledge of the species present, and allowing the extraction of information regarding the functionality of microbial communities in their natural habitat. Function-based screenings, following the cloning and expression of metagenomic DNA in a heterologous host, can be applied to the discovery of novel proteins of industrial interest encoded by the genes of previously inaccessible microorganisms. Functional metagenomics has considerable potential in the food and pharmaceutical industries, where it can, for instance, aid (i) the identification of enzymes with desirable technological properties, capable of catalyzing novel reactions or replacing existing chemically synthesized catalysts which may be difficult or expensive to produce, and able to work under a wide range of environmental conditions encountered in food and pharmaceutical processing cycles including extreme conditions of temperature, pH, osmolarity, etc; (ii) the discovery of novel bioactives including antimicrobials active against microorganisms of concern both in food and medical settings; (iii) the investigation of industrial and societal issues such as antibiotic resistance development. This review article summarizes the state-of-the-art functional metagenomic methods available and discusses the potential of functional metagenomic approaches to mine as yet unexplored environments to discover novel genes with biotechnological application in the food and pharmaceutical industries.

Biotechnological applications of functional metagenomics in the food and pharmaceutical industries

PubMed Central

Coughlan, Laura M.; Cotter, Paul D.; Hill, Colin; Alvarez-Ordóñez, Avelino

2015-01-01

Microorganisms are found throughout nature, thriving in a vast range of environmental conditions. The majority of them are unculturable or difficult to culture by traditional methods. Metagenomics enables the study of all microorganisms, regardless of whether they can be cultured or not, through the analysis of genomic data obtained directly from an environmental sample, providing knowledge of the species present, and allowing the extraction of information regarding the functionality of microbial communities in their natural habitat. Function-based screenings, following the cloning and expression of metagenomic DNA in a heterologous host, can be applied to the discovery of novel proteins of industrial interest encoded by the genes of previously inaccessible microorganisms. Functional metagenomics has considerable potential in the food and pharmaceutical industries, where it can, for instance, aid (i) the identification of enzymes with desirable technological properties, capable of catalyzing novel reactions or replacing existing chemically synthesized catalysts which may be difficult or expensive to produce, and able to work under a wide range of environmental conditions encountered in food and pharmaceutical processing cycles including extreme conditions of temperature, pH, osmolarity, etc; (ii) the discovery of novel bioactives including antimicrobials active against microorganisms of concern both in food and medical settings; (iii) the investigation of industrial and societal issues such as antibiotic resistance development. This review article summarizes the state-of-the-art functional metagenomic methods available and discusses the potential of functional metagenomic approaches to mine as yet unexplored environments to discover novel genes with biotechnological application in the food and pharmaceutical industries. PMID:26175729

THE ROLE OF WATERSHED CLASSIFICATION IN DIAGNOSING CAUSES OF BIOLOGICAL IMPAIRMENT

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmention with a gewographically-based classification scheme for two case studies involving 1) Lake Superior tributaries and 2) watersheds of riverine coastal wetlands ...

deFUME: Dynamic exploration of functional metagenomic sequencing data.

PubMed

van der Helm, Eric; Geertz-Hansen, Henrik Marcus; Genee, Hans Jasper; Malla, Sailesh; Sommer, Morten Otto Alexander

2015-07-31

Functional metagenomic selections represent a powerful technique that is widely applied for identification of novel genes from complex metagenomic sources. However, whereas hundreds to thousands of clones can be easily generated and sequenced over a few days of experiments, analyzing the data is time consuming and constitutes a major bottleneck for experimental researchers in the field. Here we present the deFUME web server, an easy-to-use web-based interface for processing, annotation and visualization of functional metagenomics sequencing data, tailored to meet the requirements of non-bioinformaticians. The web-server integrates multiple analysis steps into one single workflow: read assembly, open reading frame prediction, and annotation with BLAST, InterPro and GO classifiers. Analysis results are visualized in an online dynamic web-interface. The deFUME webserver provides a fast track from raw sequence to a comprehensive visual data overview that facilitates effortless inspection of gene function, clustering and distribution. The webserver is available at cbs.dtu.dk/services/deFUME/and the source code is distributed at github.com/EvdH0/deFUME.

Protein Structure Determination using Metagenome sequence data

PubMed Central

Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha; Huang, Po-Ssu; Pavlopoulos, Georgios A.; Kim, David E.; Kamisetty, Hetunandan; Kyrpides, Nikos C.; Baker, David

2017-01-01

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families, and that metagenome sequence data more than triples the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact based structure matching and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the PDB. This approach provides the representative models for large protein families originally envisioned as the goal of the protein structure initiative at a fraction of the cost. PMID:28104891

Identification and characterization of a chitin deacetylase from a metagenomic library of deep-sea sediments of the Arctic Ocean.

PubMed

Liu, Jinlin; Jia, Zhijuan; Li, Sha; Li, Yan; You, Qiang; Zhang, Chunyan; Zheng, Xiaotong; Xiong, Guomei; Zhao, Jin; Qi, Chao; Yang, Jihong

2016-09-15

The chemical and biological compositions of deep-sea sediments are interesting because of the underexplored diversity when it comes to bioprospecting. The special geographical location and climates make Arctic Ocean a unique ocean area containing an abundance of microbial resources. A metagenomic library was constructed based on the deep-sea sediments of Arctic Ocean. Part of insertion fragments of this library were sequenced. A chitin deacetylase gene, cdaYJ, was identified and characterized. A metagenomic library with 2750 clones was obtained and ten clones were sequenced. Results revealed several interesting genes, including a chitin deacetylase coding sequence, cdaYJ. The CdaYJ is homologous to some known chitin deacetylases and contains conserved chitin deacetylase active sites. CdaYJ protein exhibits a long N-terminal and a relative short C-terminal. Phylogenetic analysis revealed that CdaYJ showed highest homology to CDAs from Alphaproteobacteria. The cdaYJ gene was subcloned into the pET-28a vector and the recombinant CdaYJ (rCdaYJ) was expressed in Escherichia coli BL21 (DE3). rCdaYJ showed a molecular weight of 43kDa, and exhibited deacetylation activity by using p-nitroacetanilide as substrate. The optimal pH and temperature of rCdaYJ were tested as pH7.4 and 28°C, respectively. The construction of metagenomic library of the Arctic deep-sea sediments provides us an opportunity to look into the microbial communities and exploiting valuable gene resources. A chitin deacetylase CdaYJ was identified from the library. It showed highest deacetylation activity under slight alkaline and low temperature conditions. CdaYJ might be a candidate chitin deacetylase that possesses industrial and pharmaceutical potentials. Copyright © 2016 Elsevier B.V. All rights reserved.

Genome and metagenome enabled analyses reveal new insight into the global biogeography and potential urea utilization in marine Thaumarchaeota.

NASA Astrophysics Data System (ADS)

Ahlgren, N.; Parada, A. E.; Fuhrman, J. A.

2016-02-01

Marine Thaumarchaea are an abundant, important group of marine microbial communities as they fix carbon, oxidize ammonium, and thus contribute to key N and C cycles in the oceans. From an enrichment culture, we have sequenced the complete genome of a new Thaumarchaeota strain, SPOT01. Analysis of this genome and other Thaumarchaeal genomes contributes new insight into its role in N cycling and clarifies the broader biogeography of marine Thaumarchaeal genera. Phylogenomics of Thaumarchaeota genomes reveal coherent separation into clusters roughly equivalent to the genus level, and SPOT01 represents a new genus of marine Thaumarchaea. Competitive fragment recruitment of globally distributed metagenomes from TARA, Ocean Sampling Day, and those generated from a station off California shows that the SPOT01 genus is often the most abundant genus, especially where total Thaumarchaea are most abundant in the overall community. The SPOT01 genome contains urease genes allowing it to use an alternative form of N. Genomic and metagenomic analysis also reveal that among planktonic genomes and populations, the urease genes in general are more frequently found in members of the SPOT01 genus and another genus dominant in deep waters, thus we predict these two genera contribute most significantly to urea utilization among marine Thaumarchaea. Recruitment also revealed broader biogeographic and ecological patterns of the putative genera. The SPOT01 genus was most abundant at colder temperatures (<16 C), reflective of its dominance at subpolar to polar latitudes (>45 degrees). The genus containing Nitrosopumilus maritimus had the highest temperature range, and the genus containing Candidatus Nitrosopelagicus brevis was typically most abundant at intermediate temperatures and intermediate latitudes ( 35-45 degrees). Together these genome and metagenome enabled analyses provide significant new insight into the ecology and biogeochemical contributions of marine archaea.

Heterologous viral expression systems in fosmid vectors increase the functional analysis potential of metagenomic libraries.

PubMed

Terrón-González, L; Medina, C; Limón-Mortés, M C; Santero, E

2013-01-01

The extraordinary potential of metagenomic functional analyses to identify activities of interest present in uncultured microorganisms has been limited by reduced gene expression in surrogate hosts. We have developed vectors and specialized E. coli strains as improved metagenomic DNA heterologous expression systems, taking advantage of viral components that prevent transcription termination at metagenomic terminators. One of the systems uses the phage T7 RNA-polymerase to drive metagenomic gene expression, while the other approach uses the lambda phage transcription anti-termination protein N to limit transcription termination. A metagenomic library was constructed and functionally screened to identify genes conferring carbenicillin resistance to E. coli. The use of these enhanced expression systems resulted in a 6-fold increase in the frequency of carbenicillin resistant clones. Subcloning and sequence analysis showed that, besides β-lactamases, efflux pumps are not only able contribute to carbenicillin resistance but may in fact be sufficient by themselves to convey carbenicillin resistance.

Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome

PubMed Central

Abubucker, Sahar; Segata, Nicola; Goll, Johannes; Schubert, Alyxandria M.; Izard, Jacques; Cantarel, Brandi L.; Rodriguez-Mueller, Beltran; Zucker, Jeremy; Thiagarajan, Mathangi; Henrissat, Bernard; White, Owen; Kelley, Scott T.; Methé, Barbara; Schloss, Patrick D.; Gevers, Dirk; Mitreva, Makedonka; Huttenhower, Curtis

2012-01-01

Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads

Assessment of the cPAS-based BGISEQ-500 platform for metagenomic sequencing.

PubMed

Fang, Chao; Zhong, Huanzi; Lin, Yuxiang; Chen, Bing; Han, Mo; Ren, Huahui; Lu, Haorong; Luber, Jacob M; Xia, Min; Li, Wangsheng; Stein, Shayna; Xu, Xun; Zhang, Wenwei; Drmanac, Radoje; Wang, Jian; Yang, Huanming; Hammarström, Lennart; Kostic, Aleksandar D; Kristiansen, Karsten; Li, Junhua

2018-03-01

More extensive use of metagenomic shotgun sequencing in microbiome research relies on the development of high-throughput, cost-effective sequencing. Here we present a comprehensive evaluation of the performance of the new high-throughput sequencing platform BGISEQ-500 for metagenomic shotgun sequencing and compare its performance with that of 2 Illumina platforms. Using fecal samples from 20 healthy individuals, we evaluated the intra-platform reproducibility for metagenomic sequencing on the BGISEQ-500 platform in a setup comprising 8 library replicates and 8 sequencing replicates. Cross-platform consistency was evaluated by comparing 20 pairwise replicates on the BGISEQ-500 platform vs the Illumina HiSeq 2000 platform and the Illumina HiSeq 4000 platform. In addition, we compared the performance of the 2 Illumina platforms against each other. By a newly developed overall accuracy quality control method, an average of 82.45 million high-quality reads (96.06% of raw reads) per sample, with 90.56% of bases scoring Q30 and above, was obtained using the BGISEQ-500 platform. Quantitative analyses revealed extremely high reproducibility between BGISEQ-500 intra-platform replicates. Cross-platform replicates differed slightly more than intra-platform replicates, yet a high consistency was observed. Only a low percentage (2.02%-3.25%) of genes exhibited significant differences in relative abundance comparing the BGISEQ-500 and HiSeq platforms, with a bias toward genes with higher GC content being enriched on the HiSeq platforms. Our study provides the first set of performance metrics for human gut metagenomic sequencing data using BGISEQ-500. The high accuracy and technical reproducibility confirm the applicability of the new platform for metagenomic studies, though caution is still warranted when combining metagenomic data from different platforms.

Metagenomics of Thermophiles with a Focus on Discovery of Novel Thermozymes

PubMed Central

DeCastro, María-Eugenia; Rodríguez-Belmonte, Esther; González-Siso, María-Isabel

2016-01-01

Microbial populations living in environments with temperatures above 50°C (thermophiles) have been widely studied, increasing our knowledge in the composition and function of these ecological communities. Since these populations express a broad number of heat-resistant enzymes (thermozymes), they also represent an important source for novel biocatalysts that can be potentially used in industrial processes. The integrated study of the whole-community DNA from an environment, known as metagenomics, coupled with the development of next generation sequencing (NGS) technologies, has allowed the generation of large amounts of data from thermophiles. In this review, we summarize the main approaches commonly utilized for assessing the taxonomic and functional diversity of thermophiles through metagenomics, including several bioinformatics tools and some metagenome-derived methods to isolate their thermozymes. PMID:27729905

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs

PubMed Central

Eloe-Fadrosh, Emiley A.; Paez-Espino, David; Jarett, Jessica; Dunfield, Peter F.; Hedlund, Brian P.; Dekas, Anne E.; Grasby, Stephen E.; Brady, Allyson L.; Dong, Hailiang; Briggs, Brandon R.; Li, Wen-Jun; Goudeau, Danielle; Malmstrom, Rex; Pati, Amrita; Pett-Ridge, Jennifer; Rubin, Edward M.; Woyke, Tanja; Kyrpides, Nikos C.; Ivanova, Natalia N.

2016-01-01

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum (‘Candidatus Kryptonia') found exclusively in high-temperature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic ‘blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestyle with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery. PMID:26814032

Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs

DOE PAGES

Eloe-Fadrosh, Emiley A.; Paez-Espino, David; Jarett, Jessica; ...

2016-01-27

Analysis of the increasing wealth of metagenomic data collected from diverse environments can lead to the discovery of novel branches on the tree of life. Here we analyse 5.2 Tb of metagenomic data collected globally to discover a novel bacterial phylum (' Candidatus Kryptonia') found exclusively in higherature pH-neutral geothermal springs. This lineage had remained hidden as a taxonomic 'blind spot' because of mismatches in the primers commonly used for ribosomal gene surveys. Genome reconstruction from metagenomic data combined with single-cell genomics results in several high-quality genomes representing four genera from the new phylum. Metabolic reconstruction indicates a heterotrophic lifestylemore » with conspicuous nutritional deficiencies, suggesting the need for metabolic complementarity with other microbes. Co-occurrence patterns identifies a number of putative partners, including an uncultured Armatimonadetes lineage. The discovery of Kryptonia within previously studied geothermal springs underscores the importance of globally sampled metagenomic data in detection of microbial novelty, and highlights the extraordinary diversity of microbial life still awaiting discovery.« less

A better sequence-read simulator program for metagenomics.

PubMed

Johnson, Stephen; Trost, Brett; Long, Jeffrey R; Pittet, Vanessa; Kusalik, Anthony

2014-01-01

There are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data. We present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approach to generate reads with lengths and quality values that closely match empirically-derived distributions. BEAR can emulate reads from various sequencing platforms, including Illumina, 454, and Ion Torrent. BEAR requires minimal user input, as it automatically determines appropriate parameter settings from user-supplied data. BEAR also uses a unique method for deriving run-specific error rates, and extracts useful statistics from the metagenomic data itself, such as quality-error models. Many existing simulators are specific to a particular sequencing technology; however, BEAR is not restricted in this way. Because of its flexibility, BEAR is particularly useful for emulating the behaviour of technologies like Ion Torrent, for which no dedicated sequencing simulators are currently available. BEAR is also the first metagenomic sequencing simulator program that automates the process of generating abundances, which can be an arduous task. BEAR is useful for evaluating data processing tools in genomics. It has many advantages over existing comparable software, such as generating more realistic reads and being independent of sequencing technology, and has features particularly useful for metagenomics work.

Applications of metagenomics for industrial bioproducts

USDA-ARS?s Scientific Manuscript database

Recent progress in mining the rich genetic resource of non-culturable microbes has led to the discovery of new genes, enzymes, and natural products. The impact of metagenomics is witnessed in the development of commodity and fine chemicals, agrochemicals and pharmaceuticals where the benefit of enz...

Preparation of fosmid libraries and functional metagenomic analysis of microbial community DNA.

PubMed

Martínez, Asunción; Osburne, Marcia S

2013-01-01

One of the most important challenges in contemporary microbial ecology is to assign a functional role to the large number of novel genes discovered through large-scale sequencing of natural microbial communities that lack similarity to genes of known function. Functional screening of metagenomic libraries, that is, screening environmental DNA clones for the ability to confer an activity of interest to a heterologous bacterial host, is a promising approach for bridging the gap between metagenomic DNA sequencing and functional characterization. Here, we describe methods for isolating environmental DNA and constructing metagenomic fosmid libraries, as well as methods for designing and implementing successful functional screens of such libraries. © 2013 Elsevier Inc. All rights reserved.

Metagenomic ventures into outer sequence space.

PubMed

Dutilh, Bas E

Sequencing DNA or RNA directly from the environment often results in many sequencing reads that have no homologs in the database. These are referred to as "unknowns," and reflect the vast unexplored microbial sequence space of our biosphere, also known as "biological dark matter." However, unknowns also exist because metagenomic datasets are not optimally mined. There is a pressure on researchers to publish and move on, and the unknown sequences are often left for what they are, and conclusions drawn based on reads with annotated homologs. This can cause abundant and widespread genomes to be overlooked, such as the recently discovered human gut bacteriophage crAssphage. The unknowns may be enriched for bacteriophage sequences, the most abundant and genetically diverse component of the biosphere and of sequence space. However, it remains an open question, what is the actual size of biological sequence space? The de novo assembly of shotgun metagenomes is the most powerful tool to address this question.

Genovo: De Novo Assembly for Metagenomes

NASA Astrophysics Data System (ADS)

Laserson, Jonathan; Jojic, Vladimir; Koller, Daphne

Next-generation sequencing technologies produce a large number of noisy reads from the DNA in a sample. Metagenomics and population sequencing aim to recover the genomic sequences of the species in the sample, which could be of high diversity. Methods geared towards single sequence reconstruction are not sensitive enough when applied in this setting. We introduce a generative probabilistic model of read generation from environmental samples and present Genovo, a novel de novo sequence assembler that discovers likely sequence reconstructions under the model. A Chinese restaurant process prior accounts for the unknown number of genomes in the sample. Inference is made by applying a series of hill-climbing steps iteratively until convergence. We compare the performance of Genovo to three other short read assembly programs across one synthetic dataset and eight metagenomic datasets created using the 454 platform, the largest of which has 311k reads. Genovo's reconstructions cover more bases and recover more genes than the other methods, and yield a higher assembly score.

Extremozymes from metagenome: Potential applications in food processing.

PubMed

Khan, Mahejibin; Sathya, T A

2017-06-12

The long-established use of enzymes for food processing and product formulation has resulted in an increased enzyme market compounding to 7.0% annual growth rate. Advancements in molecular biology and recognition that enzymes with specific properties have application for industrial production of infant, baby and functional foods boosted research toward sourcing the genes of microorganisms for enzymes with distinctive properties. In this regard, functional metagenomics for extremozymes has gained attention on the premise that such enzymes can catalyze specific reactions. Hence, metagenomics that can isolate functional genes of unculturable extremophilic microorganisms has expanded attention as a promising tool. Developments in this field of research in relation to food sector are reviewed.

Taxonomic and functional metagenomic profiling of gastrointestinal tract microbiome of the farmed adult turbot (Scophthalmus maximus).

PubMed

Xing, Mengxin; Hou, Zhanhui; Yuan, Jianbo; Liu, Yuan; Qu, Yanmei; Liu, Bin

2013-12-01

Metagenomics combined with 16S rRNA gene sequence analyses was applied to unveil the taxonomic composition and functional diversity of the farmed adult turbot gastrointestinal (GI) microbiome. Proteobacteria and Firmicutes which existed in both GI content and mucus were dominated in the turbot GI microbiome. 16S rRNA gene sequence analyses also indicated that the turbot GI tract may harbor some bacteria which originated from associated seawater. Functional analyses indicated that the clustering-based subsystem and many metabolic subsystems were dominant in the turbot GI metagenome. Compared with other gut metagenomes, quorum sensing and biofilm formation was overabundant in the turbot GI metagenome. Genes associated with quorum sensing and biofilm formation were found in species within Vibrio, including Vibrio vulnificus, Vibrio cholerae and Vibrio parahaemolyticus. In farmed fish gut metagenomes, the stress response and protein folding subsystems were over-represented and several genes concerning antibiotic and heavy metal resistance were also detected. These data suggested that the turbot GI microbiome may be affected by human factors in aquaculture. Additionally, iron acquisition and the metabolism subsystem were more abundant in the turbot GI metagenome when compared with freshwater fish gut metagenome, suggesting that unique metabolic potential may be observed in marine animal GI microbiomes. © 2013 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Use of simulated data sets to evaluate the fidelity of metagenomic processing methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mavromatis, K; Ivanova, N; Barry, Kerrie

2007-01-01

Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity-based ( blast hit distribution) and twomore » sequence composition-based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.« less

BeerDeCoded: the open beer metagenome project.

PubMed

Sobel, Jonathan; Henry, Luc; Rotman, Nicolas; Rando, Gianpaolo

2017-01-01

Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer.

BeerDeCoded: the open beer metagenome project

PubMed Central

Sobel, Jonathan; Henry, Luc; Rotman, Nicolas; Rando, Gianpaolo

2017-01-01

Next generation sequencing has radically changed research in the life sciences, in both academic and corporate laboratories. The potential impact is tremendous, yet a majority of citizens have little or no understanding of the technological and ethical aspects of this widespread adoption. We designed BeerDeCoded as a pretext to discuss the societal issues related to genomic and metagenomic data with fellow citizens, while advancing scientific knowledge of the most popular beverage of all. In the spirit of citizen science, sample collection and DNA extraction were carried out with the participation of non-scientists in the community laboratory of Hackuarium, a not-for-profit organisation that supports unconventional research and promotes the public understanding of science. The dataset presented herein contains the targeted metagenomic profile of 39 bottled beers from 5 countries, based on internal transcribed spacer (ITS) sequencing of fungal species. A preliminary analysis reveals the presence of a large diversity of wild yeast species in commercial brews. With this project, we demonstrate that coupling simple laboratory procedures that can be carried out in a non-professional environment with state-of-the-art sequencing technologies and targeted metagenomic analyses, can lead to the detection and identification of the microbial content in bottled beer. PMID:29123645

Intra- and interobserver agreement in the classification and treatment of distal third clavicle fractures.

PubMed

Bishop, Julie Y; Jones, Grant L; Lewis, Brian; Pedroza, Angela

2015-04-01

In treatment of distal third clavicle fractures, the Neer classification system, based on the location of the fracture in relation to the coracoclavicular ligaments, has traditionally been used to determine fracture pattern stability. To determine the intra- and interobserver reliability in the classification of distal third clavicle fractures via standard plain radiographs and the intra- and interobserver agreement in the preferred treatment of these fractures. Cohort study (Diagnosis); Level of evidence, 3. Thirty radiographs of distal clavicle fractures were randomly selected from patients treated for distal clavicle fractures between 2006 and 2011. The radiographs were distributed to 22 shoulder/sports medicine fellowship-trained orthopaedic surgeons. Fourteen surgeons responded and took part in the study. The evaluators were asked to measure the size of the distal fragment, classify the fracture pattern as stable or unstable, assign the Neer classification, and recommend operative versus nonoperative treatment. The radiographs were reordered and redistributed 3 months later. Inter- and intrarater agreement was determined for the distal fragment size, stability of the fracture, Neer classification, and decision to operate. Single variable logistic regression was performed to determine what factors could most accurately predict the decision for surgery. Interrater agreement was fair for distal fragment size, moderate for stability, fair for Neer classification, slight for type IIB and III fractures, and moderate for treatment approach. Intrarater agreement was moderate for distal fragment size categories (κ = 0.50, P < .001) and Neer classification (κ = 0.42, P < .001) and substantial for stable fracture (κ = 0.65, P < .001) and decision to operate (κ = 0.65, P < .001). Fracture stability was the best predictor of treatment, with 89% accuracy (P < .001). Fracture stability determination and the decision to operate had the highest interobserver agreement

Metagenomics, metaMicrobesOnline and Kbase Data Integration (MICW - Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Dehal, Paramvir

2018-02-06

Berkeley Lab's Paramvir Dehal on "Managing and Storing large Datasets in MicrobesOnline, metaMicrobesOnline and the DOE Knowledgebase" at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

19 CFR 102.20 - Specific rules by tariff classification.

Code of Federal Regulations, 2013 CFR

2013-04-01

... bonds are formed between the fragmented molecules and/or added elements so that one or more of the... between the fragmented molecules and/or added elements so that one or more of the original bonds no longer... requirements of these rules by reason of a change from one classification to another merely as the result of...

Comparison of methods for library construction and short read annotation of shellfish viral metagenomes.

PubMed

Wei, Hong-Ying; Huang, Sheng; Wang, Jiang-Yong; Gao, Fang; Jiang, Jing-Zhe

2018-03-01

The emergence and widespread use of high-throughput sequencing technologies have promoted metagenomic studies on environmental or animal samples. Library construction for metagenome sequencing and annotation of the produced sequence reads are important steps in such studies and influence the quality of metagenomic data. In this study, we collected some marine mollusk samples, such as Crassostrea hongkongensis, Chlamys farreri, and Ruditapes philippinarum, from coastal areas in South China. These samples were divided into two batches to compare two library construction methods for shellfish viral metagenome. Our analysis showed that reverse-transcribing RNA into cDNA and then amplifying it simultaneously with DNA by whole genome amplification (WGA) yielded a larger amount of DNA compared to using only WGA or WTA (whole transcriptome amplification). Moreover, higher quality libraries were obtained by agarose gel extraction rather than with AMPure bead size selection. However, the latter can also provide good results if combined with the adjustment of the filter parameters. This, together with its simplicity, makes it a viable alternative. Finally, we compared three annotation tools (BLAST, DIAMOND, and Taxonomer) and two reference databases (NCBI's NR and Uniprot's Uniref). Considering the limitations of computing resources and data transfer speed, we propose the use of DIAMOND with Uniref for annotating metagenomic short reads as its running speed can guarantee a good annotation rate. This study may serve as a useful reference for selecting methods for Shellfish viral metagenome library construction and read annotation.

Soil Bacterial Community Shifts after Chitin Enrichment: An Integrative Metagenomic Approach

PubMed Central

Jacquiod, Samuel; Franqueville, Laure; Cécillon, Sébastien; M. Vogel, Timothy; Simonet, Pascal

2013-01-01

Chitin is the second most produced biopolymer on Earth after cellulose. Chitin degrading enzymes are promising but untapped sources for developing novel industrial biocatalysts. Hidden amongst uncultivated micro-organisms, new bacterial enzymes can be discovered and exploited by metagenomic approaches through extensive cloning and screening. Enrichment is also a well-known strategy, as it allows selection of organisms adapted to feed on a specific compound. In this study, we investigated how the soil bacterial community responded to chitin enrichment in a microcosm experiment. An integrative metagenomic approach coupling phylochips and high throughput shotgun pyrosequencing was established in order to assess the taxonomical and functional changes in the soil bacterial community. Results indicate that chitin enrichment leads to an increase of Actinobacteria, γ-proteobacteria and β-proteobacteria suggesting specific selection of chitin degrading bacteria belonging to these classes. Part of enriched bacterial genera were not yet reported to be involved in chitin degradation, like the members from the Micrococcineae sub-order (Actinobacteria). An increase of the observed bacterial diversity was noticed, with detection of specific genera only in chitin treated conditions. The relative proportion of metagenomic sequences related to chitin degradation was significantly increased, even if it represents only a tiny fraction of the sequence diversity found in a soil metagenome. PMID:24278158

Whither or wither geomicrobiology in the era of 'community metagenomics'

USGS Publications Warehouse

Oremland, R.S.; Capone, D.G.; Stolz, J.F.; Fuhrman, J.

2005-01-01

Molecular techniques are valuable tools that can improve our understanding of the structure of microbial communities. They provide the ability to probe for life in all niches of the biosphere, perhaps even supplanting the need to cultivate microorganisms or to conduct ecophysiological investigations. However, an overemphasis and strict dependence on such large information-driven endeavours as environmental metagenomics could overwhelm the field, to the detriment of microbial ecology. We now call for more balanced, hypothesis-driven research efforts that couple metagenomics with classic approaches.

Thousands of Viral Populations Recovered from Peatland Soil Metagenomes Reveal Viral Impacts on Carbon Cycling in Thawing Permafrost

NASA Astrophysics Data System (ADS)

Emerson, J. B.; Brum, J. R.; Roux, S.; Bolduc, B.; Woodcroft, B. J.; Singleton, C. M.; Boyd, J. A.; Hodgkins, S. B.; Wilson, R.; Trubl, G. G.; Jang, H. B.; Crill, P. M.; Chanton, J.; Saleska, S. R.; Rich, V. I.; Tyson, G. W.; Sullivan, M. B.

2016-12-01

Methane and carbon dioxide emissions, which are under significant microbial control, provide positive feedbacks to climate change in thawing permafrost peatlands. Although viruses in marine systems have been shown to impact microbial ecology and biogeochemical cycling through host cell lysis, horizontal gene transfer, and auxiliary metabolic gene expression, viral ecology in permafrost and other soils remains virtually unstudied due to methodological challenges. Here, we identified viral sequences in 208 assembled bulk soil metagenomes derived from a permafrost thaw gradient in Stordalen Mire, northern Sweden, from 2010-2012. 2,048 viral populations were recovered, which genome- and network-based classification revealed to be largely novel, increasing known viral genera globally by 40%. Ecologically, viral communities differed significantly across the thaw gradient and by soil depth. Co-occurring microbial community composition, soil moisture, and pH were predictors of viral community composition, indicative of biological and biogeochemical feedbacks as permafrost thaws. Host prediction—achieved through clustered regularly interspaced short palindromic repeats (CRISPRs), tetranucleotide frequency patterns, and other sequence similarities to binned microbial population genomes—was able to link 38% of the viral populations to a microbial host. 5% of the implicated hosts were archaea, predominantly methanogens and ammonia-oxidizing Nitrososphaera, 45% were Acidobacteria or Verrucomicrobia (mostly predicted heterotrophic complex carbon degraders), and 21% were Proteobacteria, including methane oxidizers. Recovered viral genome fragments also contained auxiliary metabolic genes involved in carbon and nitrogen cycling. Together, these data reveal multiple levels of previously unknown viral contributions to biogeochemical cycling, including to carbon gas emissions, in peatland soils undergoing and contributing to climate change. This work represents a significant step

Simultaneous virus identification and characterization of severe unexplained pneumonia cases using a metagenomics sequencing technique.

PubMed

Zou, Xiaohui; Tang, Guangpeng; Zhao, Xiang; Huang, Yan; Chen, Tao; Lei, Mingyu; Chen, Wenbing; Yang, Lei; Zhu, Wenfei; Zhuang, Li; Yang, Jing; Feng, Zhaomin; Wang, Dayan; Wang, Dingming; Shu, Yuelong

2017-03-01

Many viruses can cause respiratory diseases in humans. Although great advances have been achieved in methods of diagnosis, it remains challenging to identify pathogens in unexplained pneumonia (UP) cases. In this study, we applied next-generation sequencing (NGS) technology and a metagenomic approach to detect and characterize respiratory viruses in UP cases from Guizhou Province, China. A total of 33 oropharyngeal swabs were obtained from hospitalized UP patients and subjected to NGS. An unbiased metagenomic analysis pipeline identified 13 virus species in 16 samples. Human rhinovirus C was the virus most frequently detected and was identified in seven samples. Human measles virus, adenovirus B 55 and coxsackievirus A10 were also identified. Metagenomic sequencing also provided virus genomic sequences, which enabled genotype characterization and phylogenetic analysis. For cases of multiple infection, metagenomic sequencing afforded information regarding the quantity of each virus in the sample, which could be used to evaluate each viruses' role in the disease. Our study highlights the potential of metagenomic sequencing for pathogen identification in UP cases.

Sequence-based screening for self-sufficient P450 monooxygenase from a metagenome library.

PubMed

Kim, B S; Kim, S Y; Park, J; Park, W; Hwang, K Y; Yoon, Y J; Oh, W K; Kim, B Y; Ahn, J S

2007-05-01

Cytochrome P450 monooxygenases (CYPs) are useful catalysts for oxidation reactions. Self-sufficient CYPs harbour a reductive domain covalently connected to a P450 domain and are known for their robust catalytic activity with great potential as biocatalysts. In an effort to expand genetic sources of self-sufficient CYPs, we devised a sequence-based screening system to identify them in a soil metagenome. We constructed a soil metagenome library and performed sequence-based screening for self-sufficient CYP genes. A new CYP gene, syk181, was identified from the metagenome library. Phylogenetic analysis revealed that SYK181 formed a distinct phylogenic line with 46% amino-acid-sequence identity to CYP102A1 which has been extensively studied as a fatty acid hydroxylase. The heterologously expressed SYK181 showed significant hydroxylase activity towards naphthalene and phenanthrene as well as towards fatty acids. Sequence-based screening of metagenome libraries is expected to be a useful approach for searching self-sufficient CYP genes. The translated product of syk181 shows self-sufficient hydroxylase activity towards fatty acids and aromatic compounds. SYK181 is the first self-sufficient CYP obtained directly from a metagenome library. The genetic and biochemical information on SYK181 are expected to be helpful for engineering self-sufficient CYPs with broader catalytic activities towards various substrates, which would be useful for bioconversion of natural products and biodegradation of organic chemicals.

Metagenomic analysis reveals a functional signature for biomass degradation by cecal microbiota in the leaf-eating flying squirrel (Petaurista alborufus lena)

PubMed Central

2012-01-01

Background Animals co-evolve with their gut microbiota; the latter can perform complex metabolic reactions that cannot be done independently by the host. Although the importance of gut microbiota has been well demonstrated, there is a paucity of research regarding its role in foliage-foraging mammals with a specialized digestive system. Results In this study, a 16S rRNA gene survey and metagenomic sequencing were used to characterize genetic diversity and functional capability of cecal microbiota of the folivorous flying squirrel (Petaurista alborufus lena). Phylogenetic compositions of the cecal microbiota derived from 3 flying squirrels were dominated by Firmicutes. Based on end-sequences of fosmid clones from 1 flying squirrel, we inferred that microbial metabolism greatly contributed to intestinal functions, including degradation of carbohydrates, metabolism of proteins, and synthesis of vitamins. Moreover, 33 polysaccharide-degrading enzymes and 2 large genomic fragments containing a series of carbohydrate-associated genes were identified. Conclusions Cecal microbiota of the leaf-eating flying squirrel have great metabolic potential for converting diverse plant materials into absorbable nutrients. The present study should serve as the basis for future investigations, using metagenomic approaches to elucidate the intricate mechanisms and interactions between host and gut microbiota of the flying squirrel digestive system, as well as other mammals with similar adaptations. PMID:22963241

Metagenomic analysis reveals a functional signature for biomass degradation by cecal microbiota in the leaf-eating flying squirrel (Petaurista alborufus lena).

PubMed

Lu, Hsiao-Pei; Wang, Yu-bin; Huang, Shiao-Wei; Lin, Chung-Yen; Wu, Martin; Hsieh, Chih-hao; Yu, Hon-Tsen

2012-09-10

Animals co-evolve with their gut microbiota; the latter can perform complex metabolic reactions that cannot be done independently by the host. Although the importance of gut microbiota has been well demonstrated, there is a paucity of research regarding its role in foliage-foraging mammals with a specialized digestive system. In this study, a 16S rRNA gene survey and metagenomic sequencing were used to characterize genetic diversity and functional capability of cecal microbiota of the folivorous flying squirrel (Petaurista alborufus lena). Phylogenetic compositions of the cecal microbiota derived from 3 flying squirrels were dominated by Firmicutes. Based on end-sequences of fosmid clones from 1 flying squirrel, we inferred that microbial metabolism greatly contributed to intestinal functions, including degradation of carbohydrates, metabolism of proteins, and synthesis of vitamins. Moreover, 33 polysaccharide-degrading enzymes and 2 large genomic fragments containing a series of carbohydrate-associated genes were identified. Cecal microbiota of the leaf-eating flying squirrel have great metabolic potential for converting diverse plant materials into absorbable nutrients. The present study should serve as the basis for future investigations, using metagenomic approaches to elucidate the intricate mechanisms and interactions between host and gut microbiota of the flying squirrel digestive system, as well as other mammals with similar adaptations.

Culture-independent discovery of natural products from soil metagenomes.

PubMed

Katz, Micah; Hover, Bradley M; Brady, Sean F

2016-03-01

Bacterial natural products have proven to be invaluable starting points in the development of many currently used therapeutic agents. Unfortunately, traditional culture-based methods for natural product discovery have been deemphasized by pharmaceutical companies due in large part to high rediscovery rates. Culture-independent, or "metagenomic," methods, which rely on the heterologous expression of DNA extracted directly from environmental samples (eDNA), have the potential to provide access to metabolites encoded by a large fraction of the earth's microbial biosynthetic diversity. As soil is both ubiquitous and rich in bacterial diversity, it is an appealing starting point for culture-independent natural product discovery efforts. This review provides an overview of the history of soil metagenome-driven natural product discovery studies and elaborates on the recent development of new tools for sequence-based, high-throughput profiling of environmental samples used in discovering novel natural product biosynthetic gene clusters. We conclude with several examples of these new tools being employed to facilitate the recovery of novel secondary metabolite encoding gene clusters from soil metagenomes and the subsequent heterologous expression of these clusters to produce bioactive small molecules.

Functional Metagenomic Investigations of Microbial Communities in a Shallow-Sea Hydrothermal System

PubMed Central

Tang, Kai; Liu, Keshao; Jiao, Nianzhi; Zhang, Yao; Chen, Chen-Tung Arthur

2013-01-01

Little is known about the functional capability of microbial communities in shallow-sea hydrothermal systems (water depth of <200 m). This study analyzed two high-throughput pyrosequencing metagenomic datasets from the vent and the surface water in the shallow-sea hydrothermal system offshore NE Taiwan. This system exhibited distinct geochemical parameters. Metagenomic data revealed that the vent and the surface water were predominated by Epsilonproteobacteria (Nautiliales-like organisms) and Gammaproteobacteria ( Thiomicrospira -like organisms), respectively. A significant difference in microbial carbon fixation and sulfur metabolism was found between the vent and the surface water. The chemoautotrophic microorganisms in the vent and in the surface water might possess the reverse tricarboxylic acid cycle and the Calvin−Bassham−Benson cycle for carbon fixation in response to carbon dioxide highly enriched in the environment, which is possibly fueled by geochemical energy with sulfur and hydrogen. Comparative analyses of metagenomes showed that the shallow-sea metagenomes contained some genes similar to those present in other extreme environments. This study may serve as a basis for deeply understanding the genetic network and functional capability of the microbial members of shallow-sea hydrothermal systems. PMID:23940820

Productivity and salinity structuring of the microplankton revealed by comparative freshwater metagenomics

PubMed Central

Eiler, Alexander; Zaremba-Niedzwiedzka, Katarzyna; Martínez-García, Manuel; McMahon, Katherine D; Stepanauskas, Ramunas; Andersson, Siv G E; Bertilsson, Stefan

2014-01-01

Little is known about the diversity and structuring of freshwater microbial communities beyond the patterns revealed by tracing their distribution in the landscape with common taxonomic markers such as the ribosomal RNA. To address this gap in knowledge, metagenomes from temperate lakes were compared to selected marine metagenomes. Taxonomic analyses of rRNA genes in these freshwater metagenomes confirm the previously reported dominance of a limited subset of uncultured lineages of freshwater bacteria, whereas Archaea were rare. Diversification into marine and freshwater microbial lineages was also reflected in phylogenies of functional genes, and there were also significant differences in functional beta-diversity. The pathways and functions that accounted for these differences are involved in osmoregulation, active transport, carbohydrate and amino acid metabolism. Moreover, predicted genes orthologous to active transporters and recalcitrant organic matter degradation were more common in microbial genomes from oligotrophic versus eutrophic lakes. This comparative metagenomic analysis allowed us to formulate a general hypothesis that oceanic- compared with freshwater-dwelling microorganisms, invest more in metabolism of amino acids and that strategies of carbohydrate metabolism differ significantly between marine and freshwater microbial communities. PMID:24118837

Introduction to Metagenomics at DOE JGI (Opening Remarks for the Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Kyrpides, Nikos [DOE JGI

2018-05-30

After a quick introduction by DOE JGI Director Eddy Rubin, DOE JGI's Nikos Kyrpides delivers the opening remarks at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Towards optimized methods to study viral impacts on soil microbial carbon cycling

NASA Astrophysics Data System (ADS)

Trubl, G. G.; Roux, S.; Jang, H. B.; Solonenko, N.; Sullivan, M. B.; Rich, V. I.

2016-12-01

Permafrost contains 50% of global soil carbon and is rapidly thawing. While the fate of this carbon is currently unknown, it will undoubtedly be shaped by microbes and their associated viruses, which modulate host activities via mortality and metabolic control. However, little is known about soil viruses generally and their impact on terrestrial biogeochemistry; this is partially due to the presence of inhibitory substances (e.g. humic acids) in soils that interfere with sample processing and sequence-based metagenomics surveys. To address this problem, we examined viral populations in three different peat soils along a permafrost thaw gradient. These samples yielded low viral DNA recoveries, and shallow metagenomic sequencing, but still resulted in the recovery of 40 viral genome fragments. Genome- and network-based classification suggested that these new references represented 11 viral clusters, and ecological patterns (based upon non-redundant fragment recruitment) showed that viral populations were distinct in each habitat. Although only 31% of the genes could be functionally classified, pairwise genome comparisons classified 63% of the viruses taxonomically. Additionally, comparison of the 40 viral genome fragments to 53 previously recovered fragments from the same site showed no overlap, suggesting only a small portion of the resident viral community has been sampled. A follow-up experiment was performed to remove more humics during extraction and thereby obtain better viral metagenomes. Three DNA extraction protocols were tested (CTAB, PowerSoil, and Wizard columns) and the DNA was further purified with an AMPure clean-up. The PowerSoil kit maximized DNA yield (3x CTAB and 6x Wizard), and yielded the purest DNA (based on NanoDrop 260:230 ratio). Given the important roles of viruses in biogeochemical cycles in better-studied systems, further research and humic-removal optimization on these thawing permafrost-associated viral communities is needed to clarify

Mining the metagenome of activated biomass of an industrial wastewater treatment plant by a novel method.

PubMed

Sharma, Nandita; Tanksale, Himgouri; Kapley, Atya; Purohit, Hemant J

2012-12-01

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.

Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes.

PubMed

Nielsen, H Bjørn; Almeida, Mathieu; Juncker, Agnieszka Sierakowska; Rasmussen, Simon; Li, Junhua; Sunagawa, Shinichi; Plichta, Damian R; Gautier, Laurent; Pedersen, Anders G; Le Chatelier, Emmanuelle; Pelletier, Eric; Bonde, Ida; Nielsen, Trine; Manichanh, Chaysavanh; Arumugam, Manimozhiyan; Batto, Jean-Michel; Quintanilha Dos Santos, Marcelo B; Blom, Nikolaj; Borruel, Natalia; Burgdorf, Kristoffer S; Boumezbeur, Fouad; Casellas, Francesc; Doré, Joël; Dworzynski, Piotr; Guarner, Francisco; Hansen, Torben; Hildebrand, Falk; Kaas, Rolf S; Kennedy, Sean; Kristiansen, Karsten; Kultima, Jens Roat; Léonard, Pierre; Levenez, Florence; Lund, Ole; Moumen, Bouziane; Le Paslier, Denis; Pons, Nicolas; Pedersen, Oluf; Prifti, Edi; Qin, Junjie; Raes, Jeroen; Sørensen, Søren; Tap, Julien; Tims, Sebastian; Ussery, David W; Yamada, Takuji; Renault, Pierre; Sicheritz-Ponten, Thomas; Bork, Peer; Wang, Jun; Brunak, Søren; Ehrlich, S Dusko

2014-08-01

Most current approaches for analyzing metagenomic data rely on comparisons to reference genomes, but the microbial diversity of many environments extends far beyond what is covered by reference databases. De novo segregation of complex metagenomic data into specific biological entities, such as particular bacterial strains or viruses, remains a largely unsolved problem. Here we present a method, based on binning co-abundant genes across a series of metagenomic samples, that enables comprehensive discovery of new microbial organisms, viruses and co-inherited genetic entities and aids assembly of microbial genomes without the need for reference sequences. We demonstrate the method on data from 396 human gut microbiome samples and identify 7,381 co-abundance gene groups (CAGs), including 741 metagenomic species (MGS). We use these to assemble 238 high-quality microbial genomes and identify affiliations between MGS and hundreds of viruses or genetic entities. Our method provides the means for comprehensive profiling of the diversity within complex metagenomic samples.

Metagenomic Approaches to Assess Bacteriophages in Various Environmental Niches

PubMed Central

Hayes, Stephen; Mahony, Jennifer; Nauta, Arjen; van Sinderen, Douwe

2017-01-01

Bacteriophages are ubiquitous and numerous parasites of bacteria and play a critical evolutionary role in virtually every ecosystem, yet our understanding of the extent of the diversity and role of phages remains inadequate for many ecological niches, particularly in cases in which the host is unculturable. During the past 15 years, the emergence of the field of viral metagenomics has drastically enhanced our ability to analyse the so-called viral ‘dark matter’ of the biosphere. Here, we review the evolution of viral metagenomic methodologies, as well as providing an overview of some of the most significant applications and findings in this field of research. PMID:28538703

Characterization of Erwinia chrysanthemi by pectinolytic isozyme polymorphism and restriction fragment length polymorphism analysis of PCR-amplified fragments of pel genes.

PubMed Central

Nassar, A; Darrasse, A; Lemattre, M; Kotoujansky, A; Dervin, C; Vedel, R; Bertheau, Y

1996-01-01

Conserved regions about 420 bp long of the pelADE cluster specific to Erwinia chrysanthemi were amplified by PCR and used to differentiate 78 strains of E. chrysanthemi that were obtained from different hosts and geographical areas. No PCR products were obtained from DNA samples extracted from other pectinolytic and nonpectinolytic species and genera. The pel fragments amplified from the E. chrysanthemi strains studied were compared by performing a restriction fragment length polymorphism (RFLP) analysis. On the basis of similarity coefficients derived from the RFLP analysis, the strains were separated into 16 PCR RFLP patterns grouped in six clusters, These clusters appeared to be correlated with other infraspecific levels of E. chrysanthemi classification, such as pathovar and biovar, and occasionally with geographical origin. Moreover, the clusters correlated well with the polymorphism of pectate lyase and pectin methylesterase isoenzymes. While the pectin methylesterase profiles correlated with host monocot-dicot classification, the pectate lyase polymorphism might reflect the cell wall microdomains of the plants belonging to these classes. PMID:8779560

SPRUCE Deep Peat Heat (DPH) Metagenomes for Peat Samples Collected June 2015

DOE Data Explorer

Klumber, Laurel A. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Yang, Zamin K. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.; Schadt, Christopher W. [Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee, U.S.A.

2015-01-01

This data set provides links to the results of metagenomic analyses of 38 peat core samples collected on 16 June 2015 from SPRUCE experiment treatment plots after approximately one year of belowground heating. These metagenomes are archived in the U.S. Department of Energy Joint Genome Institute (DOE JGI) Integrated Microbial Genomes (IMG) system and are available at the accession numbers provided in the accompanying inventory file.

Novel polyhydroxyalkanoate copolymers produced in Pseudomonas putida by metagenomic polyhydroxyalkanoate synthases.

PubMed

Cheng, Jiujun; Charles, Trevor C

2016-09-01

Bacterially produced biodegradable polyhydroxyalkanoates (PHAs) with versatile properties can be achieved using different PHA synthases (PhaCs). This work aims to expand the diversity of known PhaCs via functional metagenomics and demonstrates the use of these novel enzymes in PHA production. Complementation of a PHA synthesis-deficient Pseudomonas putida strain with a soil metagenomic cosmid library retrieved 27 clones expressing either class I, class II, or unclassified PHA synthases, and many did not have close sequence matches to known PhaCs. The composition of PHA produced by these clones was dependent on both the supplied growth substrates and the nature of the PHA synthase, with various combinations of short-chain-length (SCL) and medium-chain-length (MCL) PHA. These data demonstrate the ability to isolate diverse genes for PHA synthesis by functional metagenomics and their use for the production of a variety of PHA polymer and copolymer mixtures.

Morphology of the posteromedial fragment in pertrochanteric fractures: A three-dimensional computed tomography analysis.

PubMed

Sharma, Gaurav; Gn, Kiran Kumar; Khatri, Kavin; Singh, Ravijot; Gamanagatti, Shivanand; Sharma, Vijay

2017-02-01

In this study we describe the morphology of the posteromedial fragment in pertrochanteric fractures using 3D CT scans and answer two questions 1) Do differences exist between the 3D CT appearances of posteromedial fragments and the depictions made in the AO classification 2) Does the posteromedial fragment affect stability in pertrochanteric fractures, in terms of fracture collapse? Preoperative CT scans of eight 31-A1 and fifty 31-A2 fractures were analysed. The presence of PM fragment, its fragmentation, greater trochanter (GT) involvement, lesser trochanter (LT) fragment size (in terms of its posterior and medial extent as well as LT length), LT fragment displacement (in terms of medial displacement and rotation) were determined. All fractures were treated with a DHS. Fracture collapse was determined on postoperative radiographs. The relationship between fracture collapse and patient factors including age, gender, fracture type (A1 versus A2), characteristics of the posteromedial fragment, and the presence of a lateral wall fracture were determined. Three out of eight 31-A1 fractures demonstrated a separate GT fragment (three part fracture). Out of the 50 31-A2 fractures, 12 had a single PM fragment, which included the LT and GT in continuity. The more common four part fractures seem to form by further fragmentation of this basic form. In A2 fractures, the GT was almost always broken and the broken fragment comprised a mean 56% of normal GT. The LT fragment involved an average of 74% of the posterior wall, and an average of 36% of the medial wall of the proximal femur. Larger LT fragments were less displaced as compared to smaller fragments. Univariate regression analyses revealed that fracture collapse was significantly correlated with fracture type (A1 versus A2, p 0.036), GT size (p 0.002) and the presence of a lateral wall fracture (p<0.001). This study revealed some important differences between the 3D CT appearances and AO classification of pertrochanteric

Fragment-based prediction of skin sensitization using recursive partitioning

NASA Astrophysics Data System (ADS)

Lu, Jing; Zheng, Mingyue; Wang, Yong; Shen, Qiancheng; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2011-09-01

Skin sensitization is an important toxic endpoint in the risk assessment of chemicals. In this paper, structure-activity relationships analysis was performed on the skin sensitization potential of 357 compounds with local lymph node assay data. Structural fragments were extracted by GASTON (GrAph/Sequence/Tree extractiON) from the training set. Eight fragments with accuracy significantly higher than 0.73 ( p < 0.1) were retained to make up an indicator descriptor fragment. The fragment descriptor and eight other physicochemical descriptors closely related to the endpoint were calculated to construct the recursive partitioning tree (RP tree) for classification. The balanced accuracy of the training set, test set I, and test set II in the leave-one-out model were 0.846, 0.800, and 0.809, respectively. The results highlight that fragment-based RP tree is a preferable method for identifying skin sensitizers. Moreover, the selected fragments provide useful structural information for exploring sensitization mechanisms, and RP tree creates a graphic tree to identify the most important properties associated with skin sensitization. They can provide some guidance for designing of drugs with lower sensitization level.

An integrated metagenome and -proteome analysis of the microbial community residing in a biogas production plant.

PubMed

Ortseifen, Vera; Stolze, Yvonne; Maus, Irena; Sczyrba, Alexander; Bremges, Andreas; Albaum, Stefan P; Jaenicke, Sebastian; Fracowiak, Jochen; Pühler, Alfred; Schlüter, Andreas

2016-08-10

To study the metaproteome of a biogas-producing microbial community, fermentation samples were taken from an agricultural biogas plant for microbial cell and protein extraction and corresponding metagenome analyses. Based on metagenome sequence data, taxonomic community profiling was performed to elucidate the composition of bacterial and archaeal sub-communities. The community's cytosolic metaproteome was represented in a 2D-PAGE approach. Metaproteome databases for protein identification were compiled based on the assembled metagenome sequence dataset for the biogas plant analyzed and non-corresponding biogas metagenomes. Protein identification results revealed that the corresponding biogas protein database facilitated the highest identification rate followed by other biogas-specific databases, whereas common public databases yielded insufficient identification rates. Proteins of the biogas microbiome identified as highly abundant were assigned to the pathways involved in methanogenesis, transport and carbon metabolism. Moreover, the integrated metagenome/-proteome approach enabled the examination of genetic-context information for genes encoding identified proteins by studying neighboring genes on the corresponding contig. Exemplarily, this approach led to the identification of a Methanoculleus sp. contig encoding 16 methanogenesis-related gene products, three of which were also detected as abundant proteins within the community's metaproteome. Thus, metagenome contigs provide additional information on the genetic environment of identified abundant proteins. Copyright © 2016 Elsevier B.V. All rights reserved.

Ten years of maintaining and expanding a microbial genome and metagenome analysis system.

PubMed

Markowitz, Victor M; Chen, I-Min A; Chu, Ken; Pati, Amrita; Ivanova, Natalia N; Kyrpides, Nikos C

2015-11-01

Launched in March 2005, the Integrated Microbial Genomes (IMG) system is a comprehensive data management system that supports multidimensional comparative analysis of genomic data. At the core of the IMG system is a data warehouse that contains genome and metagenome datasets sequenced at the Joint Genome Institute or provided by scientific users, as well as public genome datasets available at the National Center for Biotechnology Information Genbank sequence data archive. Genomes and metagenome datasets are processed using IMG's microbial genome and metagenome sequence data processing pipelines and are integrated into the data warehouse using IMG's data integration toolkits. Microbial genome and metagenome application specific data marts and user interfaces provide access to different subsets of IMG's data and analysis toolkits. This review article revisits IMG's original aims, highlights key milestones reached by the system during the past 10 years, and discusses the main challenges faced by a rapidly expanding system, in particular the complexity of maintaining such a system in an academic setting with limited budgets and computing and data management infrastructure. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

PubMed Central

Maezato, Yukari; Wu, Yu-Wei; Romine, Margaret F.; Lindemann, Stephen R.

2015-01-01

To gain a predictive understanding of the interspecies interactions within microbial communities that govern community function, the genomic complement of every member population must be determined. Although metagenomic sequencing has enabled the de novo reconstruction of some microbial genomes from environmental communities, microdiversity confounds current genome reconstruction techniques. To overcome this issue, we performed short-read metagenomic sequencing on parallel consortia, defined as consortia cultivated under the same conditions from the same natural community with overlapping species composition. The differences in species abundance between the two consortia allowed reconstruction of near-complete (at an estimated >85% of gene complement) genome sequences for 17 of the 20 detected member species. Two Halomonas spp. indistinguishable by amplicon analysis were found to be present within the community. In addition, comparison of metagenomic reads against the consensus scaffolds revealed within-species variation for one of the Halomonas populations, one of the Rhodobacteraceae populations, and the Rhizobiales population. Genomic comparison of these representative instances of inter- and intraspecies microdiversity suggests differences in functional potential that may result in the expression of distinct roles in the community. In addition, isolation and complete genome sequence determination of six member species allowed an investigation into the sensitivity and specificity of genome reconstruction processes, demonstrating robustness across a wide range of sequence coverage (9× to 2,700×) within the metagenomic data set. PMID:26497460

Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelson, William C.; Maezato, Yukari; Wu, Yu-Wei

2015-10-23

To gain a predictive understanding of the interspecies interactions within microbial communities that govern community function, the genomic complement of every member population must be determined. Although metagenomic sequencing has enabled thede novoreconstruction of some microbial genomes from environmental communities, microdiversity confounds current genome reconstruction techniques. To overcome this issue, we performed short-read metagenomic sequencing on parallel consortia, defined as consortia cultivated under the same conditions from the same natural community with overlapping species composition. The differences in species abundance between the two consortia allowed reconstruction of near-complete (at an estimated >85% of gene complement) genome sequences for 17 ofmore » the 20 detected member species. TwoHalomonasspp. indistinguishable by amplicon analysis were found to be present within the community. In addition, comparison of metagenomic reads against the consensus scaffolds revealed within-species variation for one of theHalomonaspopulations, one of theRhodobacteraceaepopulations, and theRhizobialespopulation. Genomic comparison of these representative instances of inter- and intraspecies microdiversity suggests differences in functional potential that may result in the expression of distinct roles in the community. In addition, isolation and complete genome sequence determination of six member species allowed an investigation into the sensitivity and specificity of genome reconstruction processes, demonstrating robustness across a wide range of sequence coverage (9× to 2,700×) within the metagenomic data set.« less

Fizzy: feature subset selection for metagenomics.

PubMed

Ditzler, Gregory; Morrison, J Calvin; Lan, Yemin; Rosen, Gail L

2015-11-04

Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α- & β-diversity. Feature subset selection--a sub-field of machine learning--can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate between age groups in the human gut microbiome. We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.

An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS.

PubMed

Silva, Genivaldo Gueiros Z; Lopes, Fabyano A C; Edwards, Robert A

2017-01-01

One of the main goals in metagenomics is to identify the functional profile of a microbial community from unannotated shotgun sequencing reads. Functional annotation is important in biological research because it enables researchers to identify the abundance of functional genes of the organisms present in the sample, answering the question, "What can the organisms in the sample do?" Most currently available approaches do not scale with increasing data volumes, which is important because both the number and lengths of the reads provided by sequencing platforms keep increasing. Here, we present SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with real metagenomes, and the results show that it accurately predicts the subsystems present in the profiled microbial communities, is computationally efficient, and up to 1000 times faster than other tools. SUPER-FOCUS is freely available at http://edwards.sdsu.edu/SUPERFOCUS .

Metagenomic analysis of viral diversity in respiratory samples from patients with respiratory tract infections in Kuwait.

PubMed

Madi, Nada; Al-Nakib, Widad; Mustafa, Abu Salim; Habibi, Nazima

2018-03-01

A metagenomic approach based on target independent next-generation sequencing has become a known method for the detection of both known and novel viruses in clinical samples. This study aimed to use the metagenomic sequencing approach to characterize the viral diversity in respiratory samples from patients with respiratory tract infections. We have investigated 86 respiratory samples received from various hospitals in Kuwait between 2015 and 2016 for the diagnosis of respiratory tract infections. A metagenomic approach using the next-generation sequencer to characterize viruses was used. According to the metagenomic analysis, an average of 145, 019 reads were identified, and 2% of these reads were of viral origin. Also, metagenomic analysis of the viral sequences revealed many known respiratory viruses, which were detected in 30.2% of the clinical samples. Also, sequences of non-respiratory viruses were detected in 14% of the clinical samples, while sequences of non-human viruses were detected in 55.8% of the clinical samples. The average genome coverage of the viruses was 12% with the highest genome coverage of 99.2% for respiratory syncytial virus, and the lowest was 1% for torque teno midi virus 2. Our results showed 47.7% agreement between multiplex Real-Time PCR and metagenomics sequencing in the detection of respiratory viruses in the clinical samples. Though there are some difficulties in using this method to clinical samples such as specimen quality, these observations are indicative of the promising utility of the metagenomic sequencing approach for the identification of respiratory viruses in patients with respiratory tract infections. © 2017 Wiley Periodicals, Inc.

Introduction to Metagenomics at DOE JGI: Program Overview and Program Informatics (Metagenomics Informatics Challenges Workshop: 10K Genomes at a Time)

ScienceCinema

Tringe, Susannah

2018-01-15

Susannah Tringe of the DOE Joint Genome Institute talks about the Program Overview and Program Informatics at the Metagenomics Informatics Challenges Workshop held at the DOE JGI on October 12-13, 2011.

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples.

PubMed

Yu, Feiqiao Brian; Blainey, Paul C; Schulz, Frederik; Woyke, Tanja; Horowitz, Mark A; Quake, Stephen R

2017-07-05

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell.

Metagenomic approaches to exploit the biotechnological potential of the microbial consortia of marine sponges.

PubMed

Kennedy, Jonathan; Marchesi, Julian R; Dobson, Alan D W

2007-05-01

Natural products isolated from sponges are an important source of new biologically active compounds. However, the development of these compounds into drugs has been held back by the difficulties in achieving a sustainable supply of these often-complex molecules for pre-clinical and clinical development. Increasing evidence implicates microbial symbionts as the source of many of these biologically active compounds, but the vast majority of the sponge microbial community remain uncultured. Metagenomics offers a biotechnological solution to this supply problem. Metagenomes of sponge microbial communities have been shown to contain genes and gene clusters typical for the biosynthesis of biologically active natural products. Heterologous expression approaches have also led to the isolation of secondary metabolism gene clusters from uncultured microbial symbionts of marine invertebrates and from soil metagenomic libraries. Combining a metagenomic approach with heterologous expression holds much promise for the sustainable exploitation of the chemical diversity present in the sponge microbial community.

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks

PubMed Central

Walsh, Aaron M.; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C.; Arthur, Cornelius T.; Claesson, Marcus J.; Scott, Karen P.

2017-01-01

ABSTRACT The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. PMID

Strain-Level Metagenomic Analysis of the Fermented Dairy Beverage Nunu Highlights Potential Food Safety Risks.

PubMed

Walsh, Aaron M; Crispie, Fiona; Daari, Kareem; O'Sullivan, Orla; Martin, Jennifer C; Arthur, Cornelius T; Claesson, Marcus J; Scott, Karen P; Cotter, Paul D

2017-08-15

The rapid detection of pathogenic strains in food products is essential for the prevention of disease outbreaks. It has already been demonstrated that whole-metagenome shotgun sequencing can be used to detect pathogens in food but, until recently, strain-level detection of pathogens has relied on whole-metagenome assembly, which is a computationally demanding process. Here we demonstrated that three short-read-alignment-based methods, i.e., MetaMLST, PanPhlAn, and StrainPhlAn, could accurately and rapidly identify pathogenic strains in spinach metagenomes that had been intentionally spiked with Shiga toxin-producing Escherichia coli in a previous study. Subsequently, we employed the methods, in combination with other metagenomics approaches, to assess the safety of nunu, a traditional Ghanaian fermented milk product that is produced by the spontaneous fermentation of raw cow milk. We showed that nunu samples were frequently contaminated with bacteria associated with the bovine gut and, worryingly, we detected putatively pathogenic E. coli and Klebsiella pneumoniae strains in a subset of nunu samples. Ultimately, our work establishes that short-read-alignment-based bioinformatics approaches are suitable food safety tools, and we describe a real-life example of their utilization. IMPORTANCE Foodborne pathogens are responsible for millions of illnesses each year. Here we demonstrate that short-read-alignment-based bioinformatics tools can accurately and rapidly detect pathogenic strains in food products by using shotgun metagenomics data. The methods used here are considerably faster than both traditional culturing methods and alternative bioinformatics approaches that rely on metagenome assembly; therefore, they can potentially be used for more high-throughput food safety testing. Overall, our results suggest that whole-metagenome sequencing can be used as a practical food safety tool to prevent diseases or to link outbreaks to specific food products. Copyright �

MBMC: An Effective Markov Chain Approach for Binning Metagenomic Reads from Environmental Shotgun Sequencing Projects.

PubMed

Wang, Ying; Hu, Haiyan; Li, Xiaoman

2016-08-01

Metagenomics is a next-generation omics field currently impacting postgenomic life sciences and medicine. Binning metagenomic reads is essential for the understanding of microbial function, compositions, and interactions in given environments. Despite the existence of dozens of computational methods for metagenomic read binning, it is still very challenging to bin reads. This is especially true for reads from unknown species, from species with similar abundance, and/or from low-abundance species in environmental samples. In this study, we developed a novel taxonomy-dependent and alignment-free approach called MBMC (Metagenomic Binning by Markov Chains). Different from all existing methods, MBMC bins reads by measuring the similarity of reads to the trained Markov chains for different taxa instead of directly comparing reads with known genomic sequences. By testing on more than 24 simulated and experimental datasets with species of similar abundance, species of low abundance, and/or unknown species, we report here that MBMC reliably grouped reads from different species into separate bins. Compared with four existing approaches, we demonstrated that the performance of MBMC was comparable with existing approaches when binning reads from sequenced species, and superior to existing approaches when binning reads from unknown species. MBMC is a pivotal tool for binning metagenomic reads in the current era of Big Data and postgenomic integrative biology. The MBMC software can be freely downloaded at http://hulab.ucf.edu/research/projects/metagenomics/MBMC.html .

Moleculo Long-Read Sequencing Facilitates Assembly and Genomic Binning from Complex Soil Metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Richard Allen; Bottos, Eric M.; Roy Chowdhury, Taniya

ABSTRACT Soil metagenomics has been touted as the “grand challenge” for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600more » reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of “CandidatusPseudomonas sp. strain JKJ-1” from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundanceAcidobacteriawere highly transcriptionally active, whereas bins corresponding to high-relative-abundanceVerrucomicrobiawere not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities. IMPORTANCESoil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental

Moleculo Long-Read Sequencing Facilitates Assembly and Genomic Binning from Complex Soil Metagenomes

PubMed Central

White, Richard Allen; Bottos, Eric M.; Roy Chowdhury, Taniya; Zucker, Jeremy D.; Brislawn, Colin J.; Nicora, Carrie D.; Fansler, Sarah J.; Glaesemann, Kurt R.; Glass, Kevin

2016-01-01

ABSTRACT Soil metagenomics has been touted as the “grand challenge” for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600 reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of “Candidatus Pseudomonas sp. strain JKJ-1” from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundance Acidobacteria were highly transcriptionally active, whereas bins corresponding to high-relative-abundance Verrucomicrobia were not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities. IMPORTANCE Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental

A metagenomic viral discovery approach identifies potential zoonotic and novel mammalian viruses in Neoromicia bats within South Africa.

PubMed

Geldenhuys, Marike; Mortlock, Marinda; Weyer, Jacqueline; Bezuidt, Oliver; Seamark, Ernest C J; Kearney, Teresa; Gleasner, Cheryl; Erkkila, Tracy H; Cui, Helen; Markotter, Wanda

2018-01-01

Species within the Neoromicia bat genus are abundant and widely distributed in Africa. It is common for these insectivorous bats to roost in anthropogenic structures in urban regions. Additionally, Neoromicia capensis have previously been identified as potential hosts for Middle East respiratory syndrome (MERS)-related coronaviruses. This study aimed to ascertain the gastrointestinal virome of these bats, as viruses excreted in fecal material or which may be replicating in rectal or intestinal tissues have the greatest opportunities of coming into contact with other hosts. Samples were collected in five regions of South Africa over eight years. Initial virome composition was determined by viral metagenomic sequencing by pooling samples and enriching for viral particles. Libraries were sequenced on the Illumina MiSeq and NextSeq500 platforms, producing a combined 37 million reads. Bioinformatics analysis of the high throughput sequencing data detected the full genome of a novel species of the Circoviridae family, and also identified sequence data from the Adenoviridae, Coronaviridae, Herpesviridae, Parvoviridae, Papillomaviridae, Phenuiviridae, and Picornaviridae families. Metagenomic sequencing data was insufficient to determine the viral diversity of certain families due to the fragmented coverage of genomes and lack of suitable sequencing depth, as some viruses were detected from the analysis of reads-data only. Follow up conventional PCR assays targeting conserved gene regions for the Adenoviridae, Coronaviridae, and Herpesviridae families were used to confirm metagenomic data and generate additional sequences to determine genetic diversity. The complete coding genome of a MERS-related coronavirus was recovered with additional amplicon sequencing on the MiSeq platform. The new genome shared 97.2% overall nucleotide identity to a previous Neoromicia-associated MERS-related virus, also from South Africa. Conventional PCR analysis detected diverse adenovirus and

An evaluation of the accuracy and speed of metagenome analysis tools

PubMed Central

Lindgreen, Stinus; Adair, Karen L.; Gardner, Paul P.

2016-01-01

Metagenome studies are becoming increasingly widespread, yielding important insights into microbial communities covering diverse environments from terrestrial and aquatic ecosystems to human skin and gut. With the advent of high-throughput sequencing platforms, the use of large scale shotgun sequencing approaches is now commonplace. However, a thorough independent benchmark comparing state-of-the-art metagenome analysis tools is lacking. Here, we present a benchmark where the most widely used tools are tested on complex, realistic data sets. Our results clearly show that the most widely used tools are not necessarily the most accurate, that the most accurate tool is not necessarily the most time consuming, and that there is a high degree of variability between available tools. These findings are important as the conclusions of any metagenomics study are affected by errors in the predicted community composition and functional capacity. Data sets and results are freely available from http://www.ucbioinformatics.org/metabenchmark.html PMID:26778510

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahn, Tae-Hyuk; Chai, Juanjuan; Pan, Chongle

Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis. Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic readsmore » to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. In conclusion, the algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains. Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.« less

Sigma: Strain-level inference of genomes from metagenomic analysis for biosurveillance

DOE PAGES

Ahn, Tae-Hyuk; Chai, Juanjuan; Pan, Chongle

2014-09-29

Motivation: Metagenomic sequencing of clinical samples provides a promising technique for direct pathogen detection and characterization in biosurveillance. Taxonomic analysis at the strain level can be used to resolve serotypes of a pathogen in biosurveillance. Sigma was developed for strain-level identification and quantification of pathogens using their reference genomes based on metagenomic analysis. Results: Sigma provides not only accurate strain-level inferences, but also three unique capabilities: (i) Sigma quantifies the statistical uncertainty of its inferences, which includes hypothesis testing of identified genomes and confidence interval estimation of their relative abundances; (ii) Sigma enables strain variant calling by assigning metagenomic readsmore » to their most likely reference genomes; and (iii) Sigma supports parallel computing for fast analysis of large datasets. In conclusion, the algorithm performance was evaluated using simulated mock communities and fecal samples with spike-in pathogen strains. Availability and Implementation: Sigma was implemented in C++ with source codes and binaries freely available at http://sigma.omicsbio.org.« less

The MG-RAST Metagenomics Database and Portal in 2015

DOE PAGES

Wilke, Andreas; Bischof, Jared; Gerlach, Wolfgang; ...

2015-12-09

MG-RAST (http://metagenomics.anl.gov) is an opensubmission data portal for processing, analyzing, sharing and disseminating metagenomic datasets. Currently, the system hosts over 200 000 datasets and is continuously updated. The volume of submissions has increased 4-fold over the past 24 months, now averaging 4 terabasepairs per month. In addition to several new features, we report changes to the analysis workflow and the technologies used to scale the pipeline up to the required throughput levels. Lastly, to show possible uses for the data from MG-RAST, we present several examples integrating data and analyses from MG-RAST into popular third-party analysis tools or sequence alignmentmore » tools.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE PAGES

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.; ...

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musumeci, Matias A.; Lozada, Mariana; Rial, Daniela V.

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putativemore » monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. As a result, this work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.« less

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach.

PubMed

Musumeci, Matías A; Lozada, Mariana; Rial, Daniela V; Mac Cormack, Walter P; Jansson, Janet K; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M

2017-04-09

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer-Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments.

Prospecting Biotechnologically-Relevant Monooxygenases from Cold Sediment Metagenomes: An In Silico Approach

PubMed Central

Musumeci, Matías A.; Lozada, Mariana; Rial, Daniela V.; Mac Cormack, Walter P.; Jansson, Janet K.; Sjöling, Sara; Carroll, JoLynn; Dionisi, Hebe M.

2017-01-01

The goal of this work was to identify sequences encoding monooxygenase biocatalysts with novel features by in silico mining an assembled metagenomic dataset of polar and subpolar marine sediments. The targeted enzyme sequences were Baeyer–Villiger and bacterial cytochrome P450 monooxygenases (CYP153). These enzymes have wide-ranging applications, from the synthesis of steroids, antibiotics, mycotoxins and pheromones to the synthesis of monomers for polymerization and anticancer precursors, due to their extraordinary enantio-, regio-, and chemo- selectivity that are valuable features for organic synthesis. Phylogenetic analyses were used to select the most divergent sequences affiliated to these enzyme families among the 264 putative monooxygenases recovered from the ~14 million protein-coding sequences in the assembled metagenome dataset. Three-dimensional structure modeling and docking analysis suggested features useful in biotechnological applications in five metagenomic sequences, such as wide substrate range, novel substrate specificity or regioselectivity. Further analysis revealed structural features associated with psychrophilic enzymes, such as broader substrate accessibility, larger catalytic pockets or low domain interactions, suggesting that they could be applied in biooxidations at room or low temperatures, saving costs inherent to energy consumption. This work allowed the identification of putative enzyme candidates with promising features from metagenomes, providing a suitable starting point for further developments. PMID:28397770

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial.

PubMed

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-12-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the

Analysis of Metagenomic Sequences: From Megabases to Terabases

ScienceCinema

Krypides, Nikos

2018-05-04

Nikos Krypides of the DOE Joint Genome Institute discusses metagenomics and the challenge of dealing with terabases of data on June 4, 2010 at the "Sequencing, Finishing, Analysis in the Future" meeting in Santa Fe, NM.

IMG/M-HMP: a metagenome comparative analysis system for the Human Microbiome Project.

PubMed

Markowitz, Victor M; Chen, I-Min A; Chu, Ken; Szeto, Ernest; Palaniappan, Krishna; Jacob, Biju; Ratner, Anna; Liolios, Konstantinos; Pagani, Ioanna; Huntemann, Marcel; Mavromatis, Konstantinos; Ivanova, Natalia N; Kyrpides, Nikos C

2012-01-01

The Integrated Microbial Genomes and Metagenomes (IMG/M) resource is a data management system that supports the analysis of sequence data from microbial communities in the integrated context of all publicly available draft and complete genomes from the three domains of life as well as a large number of plasmids and viruses. IMG/M currently contains thousands of genomes and metagenome samples with billions of genes. IMG/M-HMP is an IMG/M data mart serving the US National Institutes of Health (NIH) Human Microbiome Project (HMP), focussed on HMP generated metagenome datasets, and is one of the central resources provided from the HMP Data Analysis and Coordination Center (DACC). IMG/M-HMP is available at http://www.hmpdacc-resources.org/imgm_hmp/.

International Standards for Genomes, Transcriptomes, and Metagenomes

PubMed Central

Mason, Christopher E.; Afshinnekoo, Ebrahim; Tighe, Scott; Wu, Shixiu; Levy, Shawn

2017-01-01

Challenges and biases in preparing, characterizing, and sequencing DNA and RNA can have significant impacts on research in genomics across all kingdoms of life, including experiments in single-cells, RNA profiling, and metagenomics (across multiple genomes). Technical artifacts and contamination can arise at each point of sample manipulation, extraction, sequencing, and analysis. Thus, the measurement and benchmarking of these potential sources of error are of paramount importance as next-generation sequencing (NGS) projects become more global and ubiquitous. Fortunately, a variety of methods, standards, and technologies have recently emerged that improve measurements in genomics and sequencing, from the initial input material to the computational pipelines that process and annotate the data. Here we review current standards and their applications in genomics, including whole genomes, transcriptomes, mixed genomic samples (metagenomes), and the modified bases within each (epigenomes and epitranscriptomes). These standards, tools, and metrics are critical for quantifying the accuracy of NGS methods, which will be essential for robust approaches in clinical genomics and precision medicine. PMID:28337071

A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments

PubMed Central

Cao, Chen; Wang, Guishen; Liu, An; Xu, Shutan; Wang, Lincong; Zou, Shuxue

2016-01-01

The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected. Next, the remaining fragments are clustered to obtain the central fragments for each cluster. Finally, the central fragments are used as a template to make assignments. Following a large-scale comparison of 11 secondary structure assignment methods, SACF, KAKSI and PROSS are found to have similar agreement with DSSP, while PCASSO agrees with DSSP best. SACF and PCASSO show preference to reducing residues in N and C cap regions, whereas KAKSI, P-SEA and SEGNO tend to add residues to the terminals when DSSP assignment is taken as standard. Moreover, our algorithm is able to assign subtle helices (310-helix, π-helix and left-handed helix) and make uniform assignments, as well as to detect rare SSEs in β-sheets or long helices as outlier fragments from other programs. The structural uniformity should be useful for protein structure classification and prediction, while outlier fragments underlie the structure–function relationship. PMID:26978354

Assessment of Landscape Fragmentation Associated With Urban Centers Using ASTER Data

NASA Astrophysics Data System (ADS)

Stefanov, W. L.

2002-12-01

The role of humans as an integral part of the environment and ecosystem processes has only recently been accepted into mainstream ecological thought. The realization that virtually all ecosystems on Earth have experienced some degree of human alteration or impact has highlighted the need to incorporate humans (and their environmental effects) into ecosystem models. A logical starting point for investigation of human ecosystem dynamics is examination of the land cover characteristics of large urban centers. Land cover and land use changes associated with urbanization are important drivers of local geological, hydrological, ecological, and climatic change. Quantification and monitoring of urban land cover/land use change is part of the primary mission of the ASTER instrument on board the NASA Terra satellite, and comprises the fundamental research objective of the Urban Environmental Monitoring (UEM) Program at Arizona State University. The UEM program seeks to acquire day/night, visible through thermal infrared data twice per year for 100 global urban centers (with an emphasis on semi-arid cities) over the nominal six-year life of the Terra mission. Data have been acquired for the majority of the target urban centers and are used to compare landscape fragmentation patterns on the basis of land cover classifications. Land cover classifications of urban centers are obtained using visible through mid-infrared reflectance and emittance spectra together with calculated vegetation index and spatial variance texture information (all derived from raw ASTER data). This information is combined within a classification matrix, using an expert system framework, to obtain final pixel classifications. Landscape fragmentation is calculated using a pixel per unit area metric for comparison between 55 urban centers with varying geographic and climatic settings including North America, South America, Europe, central and eastern Asia, and Australia. Temporal variations in land cover

Experimental Design and Bioinformatics Analysis for the Application of Metagenomics in Environmental Sciences and Biotechnology.

PubMed

Ju, Feng; Zhang, Tong

2015-11-03

Recent advances in DNA sequencing technologies have prompted the widespread application of metagenomics for the investigation of novel bioresources (e.g., industrial enzymes and bioactive molecules) and unknown biohazards (e.g., pathogens and antibiotic resistance genes) in natural and engineered microbial systems across multiple disciplines. This review discusses the rigorous experimental design and sample preparation in the context of applying metagenomics in environmental sciences and biotechnology. Moreover, this review summarizes the principles, methodologies, and state-of-the-art bioinformatics procedures, tools and database resources for metagenomics applications and discusses two popular strategies (analysis of unassembled reads versus assembled contigs/draft genomes) for quantitative or qualitative insights of microbial community structure and functions. Overall, this review aims to facilitate more extensive application of metagenomics in the investigation of uncultured microorganisms, novel enzymes, microbe-environment interactions, and biohazards in biotechnological applications where microbial communities are engineered for bioenergy production, wastewater treatment, and bioremediation.

Some considerations for analyzing biodiversity using integrative metagenomics and gene networks.

PubMed

Bittner, Lucie; Halary, Sébastien; Payri, Claude; Cruaud, Corinne; de Reviers, Bruno; Lopez, Philippe; Bapteste, Eric

2010-07-30

Improving knowledge of biodiversity will benefit conservation biology, enhance bioremediation studies, and could lead to new medical treatments. However there is no standard approach to estimate and to compare the diversity of different environments, or to study its past, and possibly, future evolution. We argue that there are two conditions for significant progress in the identification and quantification of biodiversity. First, integrative metagenomic studies - aiming at the simultaneous examination (or even better at the integration) of observations about the elements, functions and evolutionary processes captured by the massive sequencing of multiple markers - should be preferred over DNA barcoding projects and over metagenomic projects based on a single marker. Second, such metagenomic data should be studied with novel inclusive network-based approaches, designed to draw inferences both on the many units and on the many processes present in the environments. We reached these conclusions through a comparison of the theoretical foundations of two molecular approaches seeking to assess biodiversity: metagenomics (mostly used on prokaryotes and protists) and DNA barcoding (mostly used on multicellular eukaryotes), and by pragmatic considerations of the issues caused by the 'species problem' in biodiversity studies. Evolutionary gene networks reduce the risk of producing biodiversity estimates with limited explanatory power, biased either by unequal rates of LGT, or difficult to interpret due to (practical) problems caused by type I and type II grey zones. Moreover, these networks would easily accommodate additional (meta)transcriptomic and (meta)proteomic data.

From cultured to uncultured genome sequences: metagenomics and modeling microbial ecosystems.

PubMed

Garza, Daniel R; Dutilh, Bas E

2015-11-01

Microorganisms and the viruses that infect them are the most numerous biological entities on Earth and enclose its greatest biodiversity and genetic reservoir. With strength in their numbers, these microscopic organisms are major players in the cycles of energy and matter that sustain all life. Scientists have only scratched the surface of this vast microbial world through culture-dependent methods. Recent developments in generating metagenomes, large random samples of nucleic acid sequences isolated directly from the environment, are providing comprehensive portraits of the composition, structure, and functioning of microbial communities. Moreover, advances in metagenomic analysis have created the possibility of obtaining complete or nearly complete genome sequences from uncultured microorganisms, providing important means to study their biology, ecology, and evolution. Here we review some of the recent developments in the field of metagenomics, focusing on the discovery of genetic novelty and on methods for obtaining uncultured genome sequences, including through the recycling of previously published datasets. Moreover we discuss how metagenomics has become a core scientific tool to characterize eco-evolutionary patterns of microbial ecosystems, thus allowing us to simultaneously discover new microbes and study their natural communities. We conclude by discussing general guidelines and challenges for modeling the interactions between uncultured microorganisms and viruses based on the information contained in their genome sequences. These models will significantly advance our understanding of the functioning of microbial ecosystems and the roles of microbes in the environment.

MetaGenomic Assembly by Merging (MeGAMerge)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scholz Chien-Chi Lo, Matthew B.

2015-08-03

"MetaGenomic Assembly by Merging" (MeGAMerge)Is a novel method of merging of multiple genomic assembly or long read data sources for assembly by use of internal trimming/filtering of data, followed by use of two 3rd party tools to merge data by overlap based assembly.

Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw

USGS Publications Warehouse

MacKelprang, R.; Waldrop, M.P.; Deangelis, K.M.; David, M.M.; Chavarria, K.L.; Blazewicz, S.J.; Rubin, E.M.; Jansson, J.K.

2011-01-01

Permafrost contains an estimated 1672????????Pg carbon (C), an amount roughly equivalent to the total currently contained within land plants and the atmosphere. This reservoir of C is vulnerable to decomposition as rising global temperatures cause the permafrost to thaw. During thaw, trapped organic matter may become more accessible for microbial degradation and result in greenhouse gas emissions. Despite recent advances in the use of molecular tools to study permafrost microbial communities, their response to thaw remains unclear. Here we use deep metagenomic sequencing to determine the impact of thaw on microbial phylogenetic and functional genes, and relate these data to measurements of methane emissions. Metagenomics, the direct sequencing of DNA from the environment, allows the examination of whole biochemical pathways and associated processes, as opposed to individual pieces of the metabolic puzzle. Our metagenome analyses reveal that during transition from a frozen to a thawed state there are rapid shifts in many microbial, phylogenetic and functional gene abundances and pathways. After one week of incubation at 5 ??C, permafrost metagenomes converge to be more similar to each other than while they are frozen. We find that multiple genes involved in cycling of C and nitrogen shift rapidly during thaw. We also construct the first draft genome from a complex soil metagenome, which corresponds to a novel methanogen. Methane previously accumulated in permafrost is released during thaw and subsequently consumed by methanotrophic bacteria. Together these data point towards the importance of rapid cycling of methane and nitrogen in thawing permafrost. ?? 2011 Macmillan Publishers Limited. All rights reserved.

Functional metagenomics to mine the human gut microbiome for dietary fiber catabolic enzymes.

PubMed

Tasse, Lena; Bercovici, Juliette; Pizzut-Serin, Sandra; Robe, Patrick; Tap, Julien; Klopp, Christophe; Cantarel, Brandi L; Coutinho, Pedro M; Henrissat, Bernard; Leclerc, Marion; Doré, Joël; Monsan, Pierre; Remaud-Simeon, Magali; Potocki-Veronese, Gabrielle

2010-11-01

The human gut microbiome is a complex ecosystem composed mainly of uncultured bacteria. It plays an essential role in the catabolism of dietary fibers, the part of plant material in our diet that is not metabolized in the upper digestive tract, because the human genome does not encode adequate carbohydrate active enzymes (CAZymes). We describe a multi-step functionally based approach to guide the in-depth pyrosequencing of specific regions of the human gut metagenome encoding the CAZymes involved in dietary fiber breakdown. High-throughput functional screens were first applied to a library covering 5.4 × 10(9) bp of metagenomic DNA, allowing the isolation of 310 clones showing beta-glucanase, hemicellulase, galactanase, amylase, or pectinase activities. Based on the results of refined secondary screens, sequencing efforts were reduced to 0.84 Mb of nonredundant metagenomic DNA, corresponding to 26 clones that were particularly efficient for the degradation of raw plant polysaccharides. Seventy-three CAZymes from 35 different families were discovered. This corresponds to a fivefold target-gene enrichment compared to random sequencing of the human gut metagenome. Thirty-three of these CAZy encoding genes are highly homologous to prevalent genes found in the gut microbiome of at least 20 individuals for whose metagenomic data are available. Moreover, 18 multigenic clusters encoding complementary enzyme activities for plant cell wall degradation were also identified. Gene taxonomic assignment is consistent with horizontal gene transfer events in dominant gut species and provides new insights into the human gut functional trophic chain.

Quantitative Field Testing Rotylenchulus reniformis DNA from Metagenomic Samples Isolated Directly from Soil

PubMed Central

Showmaker, Kurt; Lawrence, Gary W.; Lu, Shien; Balbalian, Clarissa; Klink, Vincent P.

2011-01-01

A quantitative PCR procedure targeting the β-tubulin gene determined the number of Rotylenchulus reniformis Linford & Oliveira 1940 in metagenomic DNA samples isolated from soil. Of note, this outcome was in the presence of other soil-dwelling plant parasitic nematodes including its sister genus Helicotylenchus Steiner, 1945. The methodology provides a framework for molecular diagnostics of nematodes from metagenomic DNA isolated directly from soil. PMID:22194958

An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography

PubMed Central

Nayfach, Stephen; Rodriguez-Mueller, Beltran; Garud, Nandita

2016-01-01

We present the Metagenomic Intra-species Diversity Analysis System (MIDAS), which is an integrated computational pipeline for quantifying bacterial species abundance and strain-level genomic variation, including gene content and single-nucleotide polymorphisms (SNPs), from shotgun metagenomes. Our method leverages a database of more than 30,000 bacterial reference genomes that we clustered into species groups. These cover the majority of abundant species in the human microbiome but only a small proportion of microbes in other environments, including soil and seawater. We applied MIDAS to stool metagenomes from 98 Swedish mothers and their infants over one year and used rare SNPs to track strains between hosts. Using this approach, we found that although species compositions of mothers and infants converged over time, strain-level similarity diverged. Specifically, early colonizing bacteria were often transmitted from an infant’s mother, while late colonizing bacteria were often transmitted from other sources in the environment and were enriched for spore-formation genes. We also applied MIDAS to 198 globally distributed marine metagenomes and used gene content to show that many prevalent bacterial species have population structure that correlates with geographic location. Strain-level genetic variants present in metagenomes clearly reveal extensive structure and dynamics that are obscured when data are analyzed at a coarser taxonomic resolution. PMID:27803195

Metagenomic Sequencing for Surveillance of Food- and Waterborne Viral Diseases.

PubMed

Nieuwenhuijse, David F; Koopmans, Marion P G

2017-01-01

A plethora of viruses can be transmitted by the food- and waterborne route. However, their recognition is challenging because of the variety of viruses, heterogeneity of symptoms, the lack of awareness of clinicians, and limited surveillance efforts. Classical food- and waterborne viral disease outbreaks are mainly caused by caliciviruses, but the source of the virus is often not known and the foodborne mode of transmission is difficult to discriminate from human-to-human transmission. Atypical food- and waterborne viral disease can be caused by viruses such as hepatitis A and hepatitis E. In addition, a source of novel emerging viruses with a potential to spread via the food- and waterborne route is the repeated interaction of humans with wildlife. Wildlife-to-human adaptation may give rise to self- limiting outbreaks in some cases, but when fully adjusted to the human host can be devastating. Metagenomic sequencing has been investigated as a promising solution for surveillance purposes as it detects all viruses in a single protocol, delivers additional genomic information for outbreak tracing, and detects novel unknown viruses. Nevertheless, several issues must be addressed to apply metagenomic sequencing in surveillance. First, sample preparation is difficult since the genomic material of viruses is generally overshadowed by host- and bacterial genomes. Second, several data analysis issues hamper the efficient, robust, and automated processing of metagenomic data. Third, interpretation of metagenomic data is hard, because of the lack of general knowledge of the virome in the food chain and the environment. Further developments in virus-specific nucleic acid extraction methods, bioinformatic data processing applications, and unifying data visualization tools are needed to gain insightful surveillance knowledge from suspect food samples.

Metagenomic Sequencing for Surveillance of Food- and Waterborne Viral Diseases

PubMed Central

Nieuwenhuijse, David F.; Koopmans, Marion P. G.

2017-01-01

A plethora of viruses can be transmitted by the food- and waterborne route. However, their recognition is challenging because of the variety of viruses, heterogeneity of symptoms, the lack of awareness of clinicians, and limited surveillance efforts. Classical food- and waterborne viral disease outbreaks are mainly caused by caliciviruses, but the source of the virus is often not known and the foodborne mode of transmission is difficult to discriminate from human-to-human transmission. Atypical food- and waterborne viral disease can be caused by viruses such as hepatitis A and hepatitis E. In addition, a source of novel emerging viruses with a potential to spread via the food- and waterborne route is the repeated interaction of humans with wildlife. Wildlife-to-human adaptation may give rise to self- limiting outbreaks in some cases, but when fully adjusted to the human host can be devastating. Metagenomic sequencing has been investigated as a promising solution for surveillance purposes as it detects all viruses in a single protocol, delivers additional genomic information for outbreak tracing, and detects novel unknown viruses. Nevertheless, several issues must be addressed to apply metagenomic sequencing in surveillance. First, sample preparation is difficult since the genomic material of viruses is generally overshadowed by host- and bacterial genomes. Second, several data analysis issues hamper the efficient, robust, and automated processing of metagenomic data. Third, interpretation of metagenomic data is hard, because of the lack of general knowledge of the virome in the food chain and the environment. Further developments in virus-specific nucleic acid extraction methods, bioinformatic data processing applications, and unifying data visualization tools are needed to gain insightful surveillance knowledge from suspect food samples. PMID:28261185

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

PubMed Central

Yu, Feiqiao Brian; Blainey, Paul C; Schulz, Frederik; Woyke, Tanja; Horowitz, Mark A; Quake, Stephen R

2017-01-01

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell. DOI: http://dx.doi.org/10.7554/eLife.26580.001 PMID:28678007

A New Zamilon-like Virophage Partial Genome Assembled from a Bioreactor Metagenome

PubMed Central

Bekliz, Meriem; Verneau, Jonathan; Benamar, Samia; Raoult, Didier; La Scola, Bernard; Colson, Philippe

2015-01-01

Virophages replicate within viral factories inside the Acanthamoeba cytoplasm, and decrease the infectivity and replication of their associated giant viruses. Culture isolation and metagenome analyses have suggested that they are common in our environment. By screening metagenomic databases in search of amoebal viruses, we detected virophage-related sequences among sequences generated from the same non-aerated bioreactor metagenome as recently screened by another team for virophage capsid-encoding genes. We describe here the assembled partial genome of a virophage closely related to Zamilon, which infects Acanthamoeba with mimiviruses of lineages B and C but not A. Searches for sequences related to amoebal giant viruses, other Megavirales representatives and virophages were conducted using BLAST against this bioreactor metagenome (PRJNA73603). Comparative genomic and phylogenetic analyses were performed using sequences from previously identified virophages. A total of 72 metagenome contigs generated from the bioreactor were identified as best matching with sequences from Megavirales representatives, mostly Pithovirus sibericum, pandoraviruses and amoebal mimiviruses from three lineages A–C, as well as from virophages. In addition, a partial genome from a Zamilon-like virophage, we named Zamilon 2, was assembled. This genome has a size of 6716 base pairs, corresponding to 39% of the Zamilon genome, and comprises partial or full-length homologs for 15 Zamilon predicted open reading frames (ORFs). Mean nucleotide and amino acid identities for these 15 Zamilon 2 ORFs with their Zamilon counterparts were 89% (range, 81–96%) and 91% (range, 78–99%), respectively. Notably, these ORFs included two encoding a capsid protein and a packaging ATPase. Comparative genomics and phylogenetic analyses indicated that the partial genome was that of a new Zamilon-like virophage. Further studies are needed to gain better knowledge of the tropism and prevalence of virophages in

MP3: a software tool for the prediction of pathogenic proteins in genomic and metagenomic data.

PubMed

Gupta, Ankit; Kapil, Rohan; Dhakan, Darshan B; Sharma, Vineet K

2014-01-01

The identification of virulent proteins in any de-novo sequenced genome is useful in estimating its pathogenic ability and understanding the mechanism of pathogenesis. Similarly, the identification of such proteins could be valuable in comparing the metagenome of healthy and diseased individuals and estimating the proportion of pathogenic species. However, the common challenge in both the above tasks is the identification of virulent proteins since a significant proportion of genomic and metagenomic proteins are novel and yet unannotated. The currently available tools which carry out the identification of virulent proteins provide limited accuracy and cannot be used on large datasets. Therefore, we have developed an MP3 standalone tool and web server for the prediction of pathogenic proteins in both genomic and metagenomic datasets. MP3 is developed using an integrated Support Vector Machine (SVM) and Hidden Markov Model (HMM) approach to carry out highly fast, sensitive and accurate prediction of pathogenic proteins. It displayed Sensitivity, Specificity, MCC and accuracy values of 92%, 100%, 0.92 and 96%, respectively, on blind dataset constructed using complete proteins. On the two metagenomic blind datasets (Blind A: 51-100 amino acids and Blind B: 30-50 amino acids), it displayed Sensitivity, Specificity, MCC and accuracy values of 82.39%, 97.86%, 0.80 and 89.32% for Blind A and 71.60%, 94.48%, 0.67 and 81.86% for Blind B, respectively. In addition, the performance of MP3 was validated on selected bacterial genomic and real metagenomic datasets. To our knowledge, MP3 is the only program that specializes in fast and accurate identification of partial pathogenic proteins predicted from short (100-150 bp) metagenomic reads and also performs exceptionally well on complete protein sequences. MP3 is publicly available at http://metagenomics.iiserb.ac.in/mp3/index.php.

MP3: A Software Tool for the Prediction of Pathogenic Proteins in Genomic and Metagenomic Data

PubMed Central

Gupta, Ankit; Kapil, Rohan; Dhakan, Darshan B.; Sharma, Vineet K.

2014-01-01

The identification of virulent proteins in any de-novo sequenced genome is useful in estimating its pathogenic ability and understanding the mechanism of pathogenesis. Similarly, the identification of such proteins could be valuable in comparing the metagenome of healthy and diseased individuals and estimating the proportion of pathogenic species. However, the common challenge in both the above tasks is the identification of virulent proteins since a significant proportion of genomic and metagenomic proteins are novel and yet unannotated. The currently available tools which carry out the identification of virulent proteins provide limited accuracy and cannot be used on large datasets. Therefore, we have developed an MP3 standalone tool and web server for the prediction of pathogenic proteins in both genomic and metagenomic datasets. MP3 is developed using an integrated Support Vector Machine (SVM) and Hidden Markov Model (HMM) approach to carry out highly fast, sensitive and accurate prediction of pathogenic proteins. It displayed Sensitivity, Specificity, MCC and accuracy values of 92%, 100%, 0.92 and 96%, respectively, on blind dataset constructed using complete proteins. On the two metagenomic blind datasets (Blind A: 51–100 amino acids and Blind B: 30–50 amino acids), it displayed Sensitivity, Specificity, MCC and accuracy values of 82.39%, 97.86%, 0.80 and 89.32% for Blind A and 71.60%, 94.48%, 0.67 and 81.86% for Blind B, respectively. In addition, the performance of MP3 was validated on selected bacterial genomic and real metagenomic datasets. To our knowledge, MP3 is the only program that specializes in fast and accurate identification of partial pathogenic proteins predicted from short (100–150 bp) metagenomic reads and also performs exceptionally well on complete protein sequences. MP3 is publicly available at http://metagenomics.iiserb.ac.in/mp3/index.php. PMID:24736651

Fizzy. Feature subset selection for metagenomics

DOE PAGES

Ditzler, Gregory; Morrison, J. Calvin; Lan, Yemin; ...

2015-11-04

Background: Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α– & β–diversity. Feature subset selection – a sub-field of machine learning – can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate betweenmore » age groups in the human gut microbiome. Results: We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. Conclusions: We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.« less

Self-organizing approach for meta-genomes.

PubMed

Zhu, Jianfeng; Zheng, Wei-Mou

2014-12-01

We extend the self-organizing approach for annotation of a bacterial genome to analyze the raw sequencing data of the human gut metagenome without sequence assembling. The original approach divides the genomic sequence of a bacterium into non-overlapping segments of equal length and assigns to each segment one of seven 'phases', among which one is for the noncoding regions, three for the direct coding regions to indicate the three possible codon positions of the segment starting site, and three for the reverse coding regions. The noncoding phase and the six coding phases are described by two frequency tables of the 64 triplet types or 'codon usages'. A set of codon usages can be used to update the phase assignment and vice versa. An iteration after an initialization leads to a convergent phase assignment to give an annotation of the genome. In the extension of the approach to a metagenome, we consider a mixture model of a number of categories described by different codon usages. The Illumina Genome Analyzer sequencing data of the total DNA from faecal samples are then examined to understand the diversity of the human gut microbiome. Copyright © 2014 Elsevier Ltd. All rights reserved.

An Enrichment of CRISPR and Other Defense-Related Features in Marine Sponge-Associated Microbial Metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Horn, Hannes; Slaby, Beate M.; Jahn, Martin T.

Many marine sponges are populated by dense and taxonomically diverse microbial consortia. We employed a metagenomics approach to unravel the differences in the functional gene repertoire among three Mediterranean sponge species, Petrosia ficiformis, Sarcotragus foetidus, Aplysina aerophoba and seawater. Different signatures were observed between sponge and seawater metagenomes with regard to microbial community composition, GC content, and estimated bacterial genome size. Our analysis showed further a pronounced repertoire for defense systems in sponge metagenomes. Specifically, clustered regularly interspaced short palindromic repeats, restriction modification, DNA phosphorothioation and phage growth limitation systems were enriched in sponge metagenomes. These data suggest that defensemore » is an important functional trait for an existence within sponges that requires mechanisms to defend against foreign DNA from microorganisms and viruses. Furthermore, this study contributes to an understanding of the evolutionary arms race between viruses/phages and bacterial genomes and it sheds light on the bacterial defenses that have evolved in the context of the sponge holobiont.« less

An Enrichment of CRISPR and Other Defense-Related Features in Marine Sponge-Associated Microbial Metagenomes

DOE PAGES

Horn, Hannes; Slaby, Beate M.; Jahn, Martin T.; ...

2016-11-08

Many marine sponges are populated by dense and taxonomically diverse microbial consortia. We employed a metagenomics approach to unravel the differences in the functional gene repertoire among three Mediterranean sponge species, Petrosia ficiformis, Sarcotragus foetidus, Aplysina aerophoba and seawater. Different signatures were observed between sponge and seawater metagenomes with regard to microbial community composition, GC content, and estimated bacterial genome size. Our analysis showed further a pronounced repertoire for defense systems in sponge metagenomes. Specifically, clustered regularly interspaced short palindromic repeats, restriction modification, DNA phosphorothioation and phage growth limitation systems were enriched in sponge metagenomes. These data suggest that defensemore » is an important functional trait for an existence within sponges that requires mechanisms to defend against foreign DNA from microorganisms and viruses. Furthermore, this study contributes to an understanding of the evolutionary arms race between viruses/phages and bacterial genomes and it sheds light on the bacterial defenses that have evolved in the context of the sponge holobiont.« less

MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wu, Yu-Wei; Simmons, Blake A.; Singer, Steven W.

The recovery of genomes from metagenomic datasets is a critical step to defining the functional roles of the underlying uncultivated populations. We previously developed MaxBin, an automated binning approach for high-throughput recovery of microbial genomes from metagenomes. Here, we present an expanded binning algorithm, MaxBin 2.0, which recovers genomes from co-assembly of a collection of metagenomic datasets. Tests on simulated datasets revealed that MaxBin 2.0 is highly accurate in recovering individual genomes, and the application of MaxBin 2.0 to several metagenomes from environmental samples demonstrated that it could achieve two complementary goals: recovering more bacterial genomes compared to binning amore » single sample as well as comparing the microbial community composition between different sampling environments. Availability and implementation: MaxBin 2.0 is freely available at http://sourceforge.net/projects/maxbin/ under BSD license. Supplementary information: Supplementary data are available at Bioinformatics online.« less

Gut metagenomes of type 2 diabetic patients have characteristic single-nucleotide polymorphism distribution in Bacteroides coprocola.

PubMed

Chen, Yaowen; Li, Zongcheng; Hu, Shuofeng; Zhang, Jian; Wu, Jiaqi; Shao, Ningsheng; Bo, Xiaochen; Ni, Ming; Ying, Xiaomin

2017-02-01

Gut microbes play a critical role in human health and disease, and researchers have begun to characterize their genomes, the so-called gut metagenome. Thus far, metagenomics studies have focused on genus- or species-level composition and microbial gene sets, while strain-level composition and single-nucleotide polymorphism (SNP) have been overlooked. The gut metagenomes of type 2 diabetes (T2D) patients have been found to be enriched with butyrate-producing bacteria and sulfate reduction functions. However, it is not known whether the gut metagenomes of T2D patients have characteristic strain patterns or SNP distributions. We downloaded public gut metagenome datasets from 170 T2D patients and 174 healthy controls and performed a systematic comparative analysis of their metagenome SNPs. We found that Bacteroides coprocola, whose relative abundance did not differ between the groups, had a characteristic distribution of SNPs in the T2D patient group. We identified 65 genes, all in B. coprocola, that had remarkably different enrichment of SNPs. The first and sixth ranked genes encode glycosyl hydrolases (GenBank accession EDU99824.1 and EDV02301.1). Interestingly, alpha-glucosidase, which is also a glycosyl hydrolase located in the intestine, is an important drug target of T2D. These results suggest that different strains of B. coprocola may have different roles in human gut and a specific set of B. coprocola strains are correlated with T2D.

Biofilm-Growing Bacteria Involved in the Corrosion of Concrete Wastewater Pipes: Protocols for Comparative Metagenomic Analyses

EPA Science Inventory

Advances in high-throughput next-generation sequencing (NGS) technology for direct sequencing of environmental DNA (i.e. shotgun metagenomics) is transforming the field of microbiology. NGS technologies are now regularly being applied in comparative metagenomic studies, which pr...

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach

PubMed Central

Watson, Mick; Minot, Samuel S.; Rivera, Maria C.; Franklin, Rima B.

2017-01-01

Abstract Background: Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths

Microbes in deep marine sediments viewed through amplicon sequencing and metagenomics

NASA Astrophysics Data System (ADS)

Biddle, J.; Leon, Z. R.; Russell, J. A., III; Martino, A. J.

2016-12-01

Nearly twenty percent of microbial biomass on Earth can be found in the marine subsurface. The majority of this is concentrated on continental margins, which have been investigated by scientific drilling. On the Costa Rica Margin, Iberian Margin and Peru Margins, sediment samples have been investigated through DNA extraction followed by amplicon and metagenomic sequencing. Overall samples show a high degree of microbial diversity, including many lineages of newly defined groups. In this talk, metagenome assembled genomes of unusual lineages will be presented, including their relationships to shallower relatives. From Costa Rica, in particular, we have retrieved deep relatives of Lokiarchaeota and Thorarchaeota, as well as other deeply branching archaeal relatives. We discuss their genome similarities to both other archaea and eukaryotes. From the Iberian Margin, relatives of Atribacteria and Aerophobetes will be discussed. Finally, we will detail the knowledge lost or gained depending on whether samples are studied via amplicon sequencing or total metagenomics, as studies in other environments have shown that up to 15% of microbial diversity is ignored when samples are studied via amplicon sequencing alone.

The metagenomic approach and causality in virology

PubMed Central

Castrignano, Silvana Beres; Nagasse-Sugahara, Teresa Keico

2015-01-01

Nowadays, the metagenomic approach has been a very important tool in the discovery of new viruses in environmental and biological samples. Here we discuss how these discoveries may help to elucidate the etiology of diseases and the criteria necessary to establish a causal association between a virus and a disease. PMID:25902566

Dynamic changes of yak (Bos grunniens) gut microbiota during growth revealed by polymerase chain reaction-denaturing gradient gel electrophoresis and metagenomics

PubMed Central

Nie, Yuanyang; Zhou, Zhiwei; Guan, Jiuqiang; Xia, Baixue; Luo, Xiaolin; Yang, Yang; Fu, Yu; Sun, Qun

2017-01-01

Objective To understand the dynamic structure, function, and influence on nutrient metabolism in hosts, it was crucial to assess the genetic potential of gut microbial community in yaks of different ages. Methods The denaturing gradient gel electrophoresis (DGGE) profiles and Illumina-based metagenomic sequencing on colon contents of 15 semi-domestic yaks were investigated. Unweighted pairwise grouping method with mathematical averages (UPGMA) clustering and principal component analysis (PCA) were used to analyze the DGGE fingerprint. The Illumina sequences were assembled, predicted to genes and functionally annotated, and then classified by querying protein sequences of the genes against the Kyoto encyclopedia of genes and genomes (KEGG) database. Results Metagenomic sequencing showed that more than 85% of ribosomal RNA (rRNA) gene sequences belonged to the phylum Firmicutes and Bacteroidetes, indicating that the family Ruminococcaceae (46.5%), Rikenellaceae (11.3%), Lachnospiraceae (10.0%), and Bacteroidaceae (6.3%) were dominant gut microbes. Over 50% of non-rRNA gene sequences represented the metabolic pathways of amino acids (14.4%), proteins (12.3%), sugars (11.9%), nucleotides (6.8%), lipids (1.7%), xenobiotics (1.4%), coenzymes, and vitamins (3.6%). Gene functional classification showed that most of enzyme-coding genes were related to cellulose digestion and amino acids metabolic pathways. Conclusion Yaks’ age had a substantial effect on gut microbial composition. Comparative metagenomics of gut microbiota in 0.5-, 1.5-, and 2.5-year-old yaks revealed that the abundance of the class Clostridia, Bacteroidia, and Lentisphaeria, as well as the phylum Firmicutes, Bacteroidetes, Lentisphaerae, Tenericutes, and Cyanobacteria, varied more greatly during yaks’ growth, especially in young animals (0.5 and 1.5 years old). Gut microbes, including Bacteroides, Clostridium, and Lentisphaeria, make a contribution to the energy metabolism and synthesis of amino acid

Comparative Metagenomics of Freshwater Microbial Communities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hemme, Chris; Deng, Ye; Tu, Qichao

2010-05-17

Previous analyses of a microbial metagenome from uranium and nitric-acid contaminated groundwater (FW106) showed significant environmental effects resulting from the rapid introduction of multiple contaminants. Effects include a massive loss of species and strain biodiversity, accumulation of toxin resistant genes in the metagenome and lateral transfer of toxin resistance genes between community members. To better understand these results in an ecological context, a second metagenome from a pristine groundwater system located along the same geological strike was sequenced and analyzed (FW301). It is hypothesized that FW301 approximates the ancestral FW106 community based on phylogenetic profiles and common geological parameters; however,more » even if is not the case, the datasets still permit comparisons between healthy and stressed groundwater ecosystems. Complex carbohydrate metabolism has been almost entirely lost in the stressed ecosystem. In contrast, the pristine system encodes a wide diversity of complex carbohydrate metabolism systems, suggesting that carbon turnover is very rapid and less leaky in the healthy groundwater system. FW301 encodes many (~;;160+) carbon monoxide dehydrogenase genes while FW106 encodes none. This result suggests that the community is frequently exposed to oxygen from aerated rainwater percolating into the subsurface, with a resulting high rate of carbon metabolism and CO production. When oxygen levels fall, the CO then serves as a major carbon source for the community. FW301 appears to be capable of CO2 fixation via the reductive carboxylase (reverse TCA) cycle and possibly acetogenesis, activities; these activities are lacking in the heterotrophic FW106 system which relies exclusively on respiration of nitrate and/or oxygen for energy production. FW301 encodes a complete set of B12 biosynthesis pathway at high abundance suggesting the use of sodium gradients for energy production in the healthy groundwater community. Overall

Functional metagenomic selection of RubisCOs from uncultivated bacteria

USGS Publications Warehouse

Varaljay, Vanessa A; Satagopan, Sriram; North, Justin A.; Witteveen, Briana; Dourado, Manuella N.; Anantharaman, Karthik; Arbing, Mark A.; McCann, Shelley; Oremland, Ronald S.; Banfield, Jillian F.; Wrighton, Kelly C.; Tabita, F. Robert

2016-01-01

Ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO) is a critical yet severely inefficient enzyme that catalyses the fixation of virtually all of the carbon found on Earth. Here, we report a functional metagenomic selection that recovers physiologically active RubisCO molecules directly from uncultivated and largely unknown members of natural microbial communities. Selection is based on CO2-dependent growth in a host strain capable of expressing environmental deoxyribonucleic acid (DNA), precluding the need for pure cultures or screening of recombinant clones for enzymatic activity. Seventeen functional RubisCO-encoded sequences were selected using DNA extracted from soil and river autotrophic enrichments, a photosynthetic biofilm and a subsurface groundwater aquifer. Notably, three related form II RubisCOs were recovered which share high sequence similarity with metagenomic scaffolds from uncultivated members of theGallionellaceae family. One of the Gallionellaceae RubisCOs was purified and shown to possessCO2/O2 specificity typical of form II enzymes. X-ray crystallography determined that this enzyme is a hexamer, only the second form II multimer ever solved and the first RubisCO structure obtained from an uncultivated bacterium. Functional metagenomic selection leverages natural biological diversity and billions of years of evolution inherent in environmental communities, providing a new window into the discovery of CO2-fixing enzymes not previously characterized.

Functional metagenomics reveals novel β-galactosidases not predictable from gene sequences.

PubMed

Cheng, Jiujun; Romantsov, Tatyana; Engel, Katja; Doxey, Andrew C; Rose, David R; Neufeld, Josh D; Charles, Trevor C

2017-01-01

The techniques of metagenomics have allowed researchers to access the genomic potential of uncultivated microbes, but there remain significant barriers to determination of gene function based on DNA sequence alone. Functional metagenomics, in which DNA is cloned and expressed in surrogate hosts, can overcome these barriers, and make important contributions to the discovery of novel enzymes. In this study, a soil metagenomic library carried in an IncP cosmid was used for functional complementation for β-galactosidase activity in both Sinorhizobium meliloti (α-Proteobacteria) and Escherichia coli (γ-Proteobacteria) backgrounds. One β-galactosidase, encoded by six overlapping clones that were selected in both hosts, was identified as a member of glycoside hydrolase family 2. We could not identify ORFs obviously encoding possible β-galactosidases in 19 other sequenced clones that were only able to complement S. meliloti. Based on low sequence identity to other known glycoside hydrolases, yet not β-galactosidases, three of these ORFs were examined further. Biochemical analysis confirmed that all three encoded β-galactosidase activity. Lac36W_ORF11 and Lac161_ORF7 had conserved domains, but lacked similarities to known glycoside hydrolases. Lac161_ORF10 had neither conserved domains nor similarity to known glycoside hydrolases. Bioinformatic and structural modeling implied that Lac161_ORF10 protein represented a novel enzyme family with a five-bladed propeller glycoside hydrolase domain. By discovering founding members of three novel β-galactosidase families, we have reinforced the value of functional metagenomics for isolating novel genes that could not have been predicted from DNA sequence analysis alone.

SUPER-FOCUS: A tool for agile functional analysis of shotgun metagenomic data

DOE PAGES

Silva, Genivaldo Gueiros Z.; Green, Kevin T.; Dutilh, Bas E.; ...

2015-10-09

Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reducedmore » reference database to report the subsystems present in metagenomic datasets and profile their abundances. We tested SUPER-FOCUS with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools.« less

Metagenomic Analysis of Viruses in Feces from Unsolved Outbreaks of Gastroenteritis in Humans

PubMed Central

Moore, Nicole E.; Wang, Jing; Hewitt, Joanne; Croucher, Dawn; Williamson, Deborah A.; Paine, Shevaun; Yen, Seiha; Greening, Gail E.

2014-01-01

The etiology of an outbreak of gastroenteritis in humans cannot always be determined, and ∼25% of outbreaks remain unsolved in New Zealand. It is hypothesized that novel viruses may account for a proportion of unsolved cases, and new unbiased high-throughput sequencing methods hold promise for their detection. Analysis of the fecal metagenome can reveal the presence of viruses, bacteria, and parasites which may have evaded routine diagnostic testing. Thirty-one fecal samples from 26 gastroenteritis outbreaks of unknown etiology occurring in New Zealand between 2011 and 2012 were selected for de novo metagenomic analysis. A total data set of 193 million sequence reads of 150 bp in length was produced on an Illumina MiSeq. The metagenomic data set was searched for virus and parasite sequences, with no evidence of novel pathogens found. Eight viruses and one parasite were detected, each already known to be associated with gastroenteritis, including adenovirus, rotavirus, sapovirus, and Dientamoeba fragilis. In addition, we also describe the first detection of human parechovirus 3 (HPeV3) in Australasia. Metagenomics may thus provide a useful audit tool when applied retrospectively to determine where routine diagnostic processes may have failed to detect a pathogen. PMID:25339401

The Challenge and Potential of Metagenomics in the Clinic

PubMed Central

Mulcahy-O’Grady, Heidi; Workentine, Matthew L.

2016-01-01

The bacteria, fungi, and viruses that live on and in us have a tremendous impact on our day-to-day health and are often linked to many diseases, including autoimmune disorders and infections. Diagnosing and treating these disorders relies on accurate identification and characterization of the microbial community. Current sequencing technologies allow the sequencing of the entire nucleic acid complement of a sample providing an accurate snapshot of the community members present in addition to the full genetic potential of that microbial community. There are a number of clinical applications that stand to benefit from these data sets, such as the rapid identification of pathogens present in a sample. Other applications include the identification of antibiotic-resistance genes, diagnosis and treatment of gastrointestinal disorders, and many other diseases associated with bacterial, viral, and fungal microbiomes. Metagenomics also allows the physician to probe more complex phenotypes such as microbial dysbiosis with intestinal disorders and disruptions of the skin microbiome that may be associated with skin disorders. Many of these disorders are not associated with a single pathogen but emerge as a result of complex ecological interactions within microbiota. Currently, we understand very little about these complex phenotypes, yet clearly they are important and in some cases, as with fecal microbiota transplants in Clostridium difficile infections, treating the microbiome of the patient is effective. Here, we give an overview of metagenomics and discuss a number of areas where metagenomics is applicable in the clinic, and progress being made in these areas. This includes (1) the identification of unknown pathogens, and those pathogens particularly hard to culture, (2) utilizing functional information and gene content to understand complex infections such as Clostridium difficile, and (3) predicting antimicrobial resistance of the community using genetic determinants of

VIP: an integrated pipeline for metagenomics of virus identification and discovery

PubMed Central

Li, Yang; Wang, Hao; Nie, Kai; Zhang, Chen; Zhang, Yi; Wang, Ji; Niu, Peihua; Ma, Xuejun

2016-01-01

Identification and discovery of viruses using next-generation sequencing technology is a fast-developing area with potential wide application in clinical diagnostics, public health monitoring and novel virus discovery. However, tremendous sequence data from NGS study has posed great challenge both in accuracy and velocity for application of NGS study. Here we describe VIP (“Virus Identification Pipeline”), a one-touch computational pipeline for virus identification and discovery from metagenomic NGS data. VIP performs the following steps to achieve its goal: (i) map and filter out background-related reads, (ii) extensive classification of reads on the basis of nucleotide and remote amino acid homology, (iii) multiple k-mer based de novo assembly and phylogenetic analysis to provide evolutionary insight. We validated the feasibility and veracity of this pipeline with sequencing results of various types of clinical samples and public datasets. VIP has also contributed to timely virus diagnosis (~10 min) in acutely ill patients, demonstrating its potential in the performance of unbiased NGS-based clinical studies with demand of short turnaround time. VIP is released under GPLv3 and is available for free download at: https://github.com/keylabivdc/VIP. PMID:27026381

Characterization of the Gut Microbiome Using 16S or Shotgun Metagenomics

PubMed Central

Jovel, Juan; Patterson, Jordan; Wang, Weiwei; Hotte, Naomi; O'Keefe, Sandra; Mitchel, Troy; Perry, Troy; Kao, Dina; Mason, Andrew L.; Madsen, Karen L.; Wong, Gane K.-S.

2016-01-01

The advent of next generation sequencing (NGS) has enabled investigations of the gut microbiome with unprecedented resolution and throughput. This has stimulated the development of sophisticated bioinformatics tools to analyze the massive amounts of data generated. Researchers therefore need a clear understanding of the key concepts required for the design, execution and interpretation of NGS experiments on microbiomes. We conducted a literature review and used our own data to determine which approaches work best. The two main approaches for analyzing the microbiome, 16S ribosomal RNA (rRNA) gene amplicons and shotgun metagenomics, are illustrated with analyses of libraries designed to highlight their strengths and weaknesses. Several methods for taxonomic classification of bacterial sequences are discussed. We present simulations to assess the number of sequences that are required to perform reliable appraisals of bacterial community structure. To the extent that fluctuations in the diversity of gut bacterial populations correlate with health and disease, we emphasize various techniques for the analysis of bacterial communities within samples (α-diversity) and between samples (β-diversity). Finally, we demonstrate techniques to infer the metabolic capabilities of a bacteria community from these 16S and shotgun data. PMID:27148170

Finding and identifying the viral needle in the metagenomic haystack: trends and challenges

PubMed Central

Soueidan, Hayssam; Schmitt, Louise-Amélie; Candresse, Thierry; Nikolski, Macha

2015-01-01

Collectively, viruses have the greatest genetic diversity on Earth, occupy extremely varied niches and are likely able to infect all living organisms. Viral infections are an important issue for human health and cause considerable economic losses when agriculturally important crops or husbandry animals are infected. The advent of metagenomics has provided a precious tool to study viruses by sampling them in natural environments and identifying the genomic composition of a sample. However, reaching a clear recognition and taxonomic assignment of the identified viruses has been hampered by the computational difficulty of these problems. In this perspective paper we examine the trends in current research for the identification of viral sequences in a metagenomic sample, pinpoint the intrinsic computational difficulties for the identification of novel viral sequences within metagenomic samples, and suggest possible avenues to overcome them. PMID:25610431

The environment shapes microbial enzymes: five cold-active and salt-resistant carboxylesterases from marine metagenomes.

PubMed

Tchigvintsev, Anatoli; Tran, Hai; Popovic, Ana; Kovacic, Filip; Brown, Greg; Flick, Robert; Hajighasemi, Mahbod; Egorova, Olga; Somody, Joseph C; Tchigvintsev, Dmitri; Khusnutdinova, Anna; Chernikova, Tatyana N; Golyshina, Olga V; Yakimov, Michail M; Savchenko, Alexei; Golyshin, Peter N; Jaeger, Karl-Erich; Yakunin, Alexander F

2015-03-01

Most of the Earth's biosphere is cold and is populated by cold-adapted microorganisms. To explore the natural enzyme diversity of these environments and identify new carboxylesterases, we have screened three marine metagenome gene libraries for esterase activity. The screens identified 23 unique active clones, from which five highly active esterases were selected for biochemical characterization. The purified metagenomic esterases exhibited high activity against α-naphthyl and p-nitrophenyl esters with different chain lengths. All five esterases retained high activity at 5 °C indicating that they are cold-adapted enzymes. The activity of MGS0010 increased more than two times in the presence of up to 3.5 M NaCl or KCl, whereas the other four metagenomic esterases were inhibited to various degrees by these salts. The purified enzymes showed different sensitivities to inhibition by solvents and detergents, and the activities of MGS0010, MGS0105 and MGS0109 were stimulated three to five times by the addition of glycerol. Screening of purified esterases against 89 monoester substrates revealed broad substrate profiles with a preference for different esters. The metagenomic esterases also hydrolyzed several polyester substrates including polylactic acid suggesting that they can be used for polyester depolymerization. Thus, esterases from marine metagenomes are cold-adapted enzymes exhibiting broad biochemical diversity reflecting the environmental conditions where they evolved.

Unlocking the potential of metagenomics through replicated experimental design.

PubMed

Knight, Rob; Jansson, Janet; Field, Dawn; Fierer, Noah; Desai, Narayan; Fuhrman, Jed A; Hugenholtz, Phil; van der Lelie, Daniel; Meyer, Folker; Stevens, Rick; Bailey, Mark J; Gordon, Jeffrey I; Kowalchuk, George A; Gilbert, Jack A

2012-06-07

Metagenomics holds enormous promise for discovering novel enzymes and organisms that are biomarkers or drivers of processes relevant to disease, industry and the environment. In the past two years, we have seen a paradigm shift in metagenomics to the application of cross-sectional and longitudinal studies enabled by advances in DNA sequencing and high-performance computing. These technologies now make it possible to broadly assess microbial diversity and function, allowing systematic investigation of the largely unexplored frontier of microbial life. To achieve this aim, the global scientific community must collaborate and agree upon common objectives and data standards to enable comparative research across the Earth's microbiome. Improvements in comparability of data will facilitate the study of biotechnologically relevant processes, such as bioprospecting for new glycoside hydrolases or identifying novel energy sources.

Metagenomic analysis of the airborne environment in urban spaces.

PubMed

Be, Nicholas A; Thissen, James B; Fofanov, Viacheslav Y; Allen, Jonathan E; Rojas, Mark; Golovko, George; Fofanov, Yuriy; Koshinsky, Heather; Jaing, Crystal J

2015-02-01

The organisms in aerosol microenvironments, especially densely populated urban areas, are relevant to maintenance of public health and detection of potential epidemic or biothreat agents. To examine aerosolized microorganisms in this environment, we performed sequencing on the material from an urban aerosol surveillance program. Whole metagenome sequencing was applied to DNA extracted from air filters obtained during periods from each of the four seasons. The composition of bacteria, plants, fungi, invertebrates, and viruses demonstrated distinct temporal shifts. Bacillus thuringiensis serovar kurstaki was detected in samples known to be exposed to aerosolized spores, illustrating the potential utility of this approach for identification of intentionally introduced microbial agents. Together, these data demonstrate the temporally dependent metagenomic complexity of urban aerosols and the potential of genomic analytical techniques for biosurveillance and monitoring of threats to public health.

The Comprehensive AOCMF Classification System: Condylar Process Fractures - Level 3 Tutorial

PubMed Central

Neff, Andreas; Cornelius, Carl-Peter; Rasse, Michael; Torre, Daniel Dalla; Audigé, Laurent

2014-01-01

This tutorial outlines the detailed system for fractures of the condylar process at the precision level 3 and is organized in a sequence of sections dealing with the description of the classification system within topographical subdivisions along with rules for fracture coding and a series of case examples with clinical imaging. Basically, the condylar process comprises three fracture levels and is subdivided into the head region, the condylar neck, and the condylar base. Fractures of the condylar head show typical fracture lines either within the lateral pole zone, which may lead to loss of vertical height, or medially to the pole zone, with the latter ones usually not compromising the vertical condyle to fossa relation. In condylar head fractures, the morphology is further described by the presence of minor or major fragmentation, the vertical apposition of fragments at the plane of the head fracture, the displacement of the condylar head with regard to the fossa including a potential distortion of the condylar head congruency resulting in dystopic condyle to fossa relations and the presence or absence of a loss of vertical ramus height. A specific vertical fracture pattern extending from the head to the neck or base subregion is considered. Fractures of the condylar neck and base can be differentiated according to a newly introduced one-third to two-thirds rule with regard to the proportion of the fracture line above and below the level of the sigmoid notch, which is presented in the classification article, and are basically subdivided according to the presence or absence of displacement or dislocation. In both condylar neck and base fractures, the classification is again based on the above mentioned parameters such as fragmentation, displacement of the condylar head with regard to the fossa, including dystopic condyle to fossa relations and loss of vertical ramus height, that is, according to the measurement of the condylar process. In addition, the

IMG/M: integrated genome and metagenome comparative data analysis system

DOE PAGES

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; ...

2016-10-13

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support formore » examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review(ER) companion system (IMG/M ER: https://img.jgi.doe.gov/ mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.« less

Forest harvesting reduces the soil metagenomic potential for biomass decomposition.

PubMed

Cardenas, Erick; Kranabetter, J M; Hope, Graeme; Maas, Kendra R; Hallam, Steven; Mohn, William W

2015-11-01

Soil is the key resource that must be managed to ensure sustainable forest productivity. Soil microbial communities mediate numerous essential ecosystem functions, and recent studies show that forest harvesting alters soil community composition. From a long-term soil productivity study site in a temperate coniferous forest in British Columbia, 21 forest soil shotgun metagenomes were generated, totaling 187 Gb. A method to analyze unassembled metagenome reads from the complex community was optimized and validated. The subsequent metagenome analysis revealed that, 12 years after forest harvesting, there were 16% and 8% reductions in relative abundances of biomass decomposition genes in the organic and mineral soil layers, respectively. Organic and mineral soil layers differed markedly in genetic potential for biomass degradation, with the organic layer having greater potential and being more strongly affected by harvesting. Gene families were disproportionately affected, and we identified 41 gene families consistently affected by harvesting, including families involved in lignin, cellulose, hemicellulose and pectin degradation. The results strongly suggest that harvesting profoundly altered below-ground cycling of carbon and other nutrients at this site, with potentially important consequences for forest regeneration. Thus, it is important to determine whether these changes foreshadow long-term changes in forest productivity or resilience and whether these changes are broadly characteristic of harvested forests.

IMG/M: integrated genome and metagenome comparative data analysis system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support formore » examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review(ER) companion system (IMG/M ER: https://img.jgi.doe.gov/ mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system.« less

IMG/M: integrated genome and metagenome comparative data analysis system

PubMed Central

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Palaniappan, Krishna; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Andersen, Evan; Huntemann, Marcel; Varghese, Neha; Hadjithomas, Michalis; Tennessen, Kristin; Nielsen, Torben; Ivanova, Natalia N.; Kyrpides, Nikos C.

2017-01-01

The Integrated Microbial Genomes with Microbiome Samples (IMG/M: https://img.jgi.doe.gov/m/) system contains annotated DNA and RNA sequence data of (i) archaeal, bacterial, eukaryotic and viral genomes from cultured organisms, (ii) single cell genomes (SCG) and genomes from metagenomes (GFM) from uncultured archaea, bacteria and viruses and (iii) metagenomes from environmental, host associated and engineered microbiome samples. Sequence data are generated by DOE's Joint Genome Institute (JGI), submitted by individual scientists, or collected from public sequence data archives. Structural and functional annotation is carried out by JGI's genome and metagenome annotation pipelines. A variety of analytical and visualization tools provide support for examining and comparing IMG/M's datasets. IMG/M allows open access interactive analysis of publicly available datasets, while manual curation, submission and access to private datasets and computationally intensive workspace-based analysis require login/password access to its expert review (ER) companion system (IMG/M ER: https://img.jgi.doe.gov/mer/). Since the last report published in the 2014 NAR Database Issue, IMG/M's dataset content has tripled in terms of number of datasets and overall protein coding genes, while its analysis tools have been extended to cope with the rapid growth in the number and size of datasets handled by the system. PMID:27738135

Metagenomic and metabolic profiling of nonlithifying and lithifying stromatolitic mats of Highborne Cay, The Bahamas.

PubMed

Khodadad, Christina L M; Foster, Jamie S

2012-01-01

Stromatolites are laminated carbonate build-ups formed by the metabolic activity of microbial mats and represent one of the oldest known ecosystems on Earth. In this study, we examined a living stromatolite located within the Exuma Sound, The Bahamas and profiled the metagenome and metabolic potential underlying these complex microbial communities. The metagenomes of the two dominant stromatolitic mat types, a nonlithifying (Type 1) and lithifying (Type 3) microbial mat, were partially sequenced and compared. This deep-sequencing approach was complemented by profiling the substrate utilization patterns of the mats using metabolic microarrays. Taxonomic assessment of the protein-encoding genes confirmed previous SSU rRNA analyses that bacteria dominate the metagenome of both mat types. Eukaryotes comprised less than 13% of the metagenomes and were rich in sequences associated with nematodes and heterotrophic protists. Comparative genomic analyses of the functional genes revealed extensive similarities in most of the subsystems between the nonlithifying and lithifying mat types. The one exception was an increase in the relative abundance of certain genes associated with carbohydrate metabolism in the lithifying Type 3 mats. Specifically, genes associated with the degradation of carbohydrates commonly found in exopolymeric substances, such as hexoses, deoxy- and acidic sugars were found. The genetic differences in carbohydrate metabolisms between the two mat types were confirmed using metabolic microarrays. Lithifying mats had a significant increase in diversity and utilization of carbon, nitrogen, phosphorus and sulfur substrates. The two stromatolitic mat types retained similar microbial communities, functional diversity and many genetic components within their metagenomes. However, there were major differences detected in the activity and genetic pathways of organic carbon utilization. These differences provide a strong link between the metagenome and the

BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation

PubMed Central

Kiefer, Christina; Fehlmann, Tobias; Backes, Christina

2017-01-01

Abstract Metagenomics-based studies of mixed microbial communities are impacting biotechnology, life sciences and medicine. Computational binning of metagenomic data is a powerful approach for the culture-independent recovery of population-resolved genomic sequences, i.e. from individual or closely related, constituent microorganisms. Existing binning solutions often require a priori characterized reference genomes and/or dedicated compute resources. Extending currently available reference-independent binning tools, we developed the BusyBee Web server for the automated deconvolution of metagenomic data into population-level genomic bins using assembled contigs (Illumina) or long reads (Pacific Biosciences, Oxford Nanopore Technologies). A reversible compression step as well as bootstrapped supervised binning enable quick turnaround times. The binning results are represented in interactive 2D scatterplots. Moreover, bin quality estimates, taxonomic annotations and annotations of antibiotic resistance genes are computed and visualized. Ground truth-based benchmarks of BusyBee Web demonstrate comparably high performance to state-of-the-art binning solutions for assembled contigs and markedly improved performance for long reads (median F1 scores: 70.02–95.21%). Furthermore, the applicability to real-world metagenomic datasets is shown. In conclusion, our reference-independent approach automatically bins assembled contigs or long reads, exhibits high sensitivity and precision, enables intuitive inspection of the results, and only requires FASTA-formatted input. The web-based application is freely accessible at: https://ccb-microbe.cs.uni-saarland.de/busybee. PMID:28472498

Cost-benefit analysis of introducing next-generation sequencing (metagenomic) pathogen testing in the setting of pyrexia of unknown origin.

PubMed

Chai, Jia Hui; Lee, Chun Kiat; Lee, Hong Kai; Wong, Nicholas; Teo, Kahwee; Tan, Chuen Seng; Thokala, Praveen; Tang, Julian Wei-Tze; Tambyah, Paul Anantharajah; Oh, Vernon Min Sen; Loh, Tze Ping; Yoong, Joanne

2018-01-01

Pyrexia of unknown origin (PUO) is defined as a temperature of >38.3°C that lasts for >3 weeks, where no cause can be found despite appropriate investigation. Existing protocols for the work-up of PUO can be extensive and costly, motivating the application of recent advances in molecular diagnostics to pathogen testing. There have been many reports describing various analytical methods and performance of metagenomic pathogen testing in clinical samples but the economics of it has been less well studied. This study pragmatically evaluates the feasibility of introducing metagenomic testing in this setting by assessing the relative cost of clinically-relevant strategies employing this investigative tool under various cost and performance scenarios using Singapore as a demonstration case, and assessing the price and performance benchmarks, which would need to be achieved for metagenomic testing to be potentially considered financially viable relative to the current diagnostic standard. This study has some important limitations: we examined only impact of introducing the metagenomic test to the overall diagnostic cost and excluded costs associated with hospitalization and makes assumptions about the performance of the routine diagnostic tests, limiting the cost of metagenomic test, and the lack of further work-up after positive pathogen detection by the metagenomic test. However, these assumptions were necessary to keep the model within reasonable limits. In spite of these, the simplified presentation lends itself to the illustration of the key insights of our paper. In general, we find the use of metagenomic testing as second-line investigation is effectively dominated, and that use of metagenomic testing at first-line would typically require higher rates of detection or lower cost than currently available in order to be justifiable purely as a cost-saving measure. We conclude that current conditions do not warrant a widespread rush to deploy metagenomic testing to

Nonpareil 3: Fast Estimation of Metagenomic Coverage and Sequence Diversity.

PubMed

Rodriguez-R, Luis M; Gunturu, Santosh; Tiedje, James M; Cole, James R; Konstantinidis, Konstantinos T

2018-01-01

Estimations of microbial community diversity based on metagenomic data sets are affected, often to an unknown degree, by biases derived from insufficient coverage and reference database-dependent estimations of diversity. For instance, the completeness of reference databases cannot be generally estimated since it depends on the extant diversity sampled to date, which, with the exception of a few habitats such as the human gut, remains severely undersampled. Further, estimation of the degree of coverage of a microbial community by a metagenomic data set is prohibitively time-consuming for large data sets, and coverage values may not be directly comparable between data sets obtained with different sequencing technologies. Here, we extend Nonpareil, a database-independent tool for the estimation of coverage in metagenomic data sets, to a high-performance computing implementation that scales up to hundreds of cores and includes, in addition, a k -mer-based estimation as sensitive as the original alignment-based version but about three hundred times as fast. Further, we propose a metric of sequence diversity ( N d ) derived directly from Nonpareil curves that correlates well with alpha diversity assessed by traditional metrics. We use this metric in different experiments demonstrating the correlation with the Shannon index estimated on 16S rRNA gene profiles and show that N d additionally reveals seasonal patterns in marine samples that are not captured by the Shannon index and more precise rankings of the magnitude of diversity of microbial communities in different habitats. Therefore, the new version of Nonpareil, called Nonpareil 3, advances the toolbox for metagenomic analyses of microbiomes. IMPORTANCE Estimation of the coverage provided by a metagenomic data set, i.e., what fraction of the microbial community was sampled by DNA sequencing, represents an essential first step of every culture-independent genomic study that aims to robustly assess the sequence

Colonic Mucosal Microbiota in Colorectal Cancer: A Single-Center Metagenomic Study in Saudi Arabia.

PubMed

Alomair, Ahmed O; Masoodi, Ibrahim; Alyamani, Essam J; Allehibi, Abed A; Qutub, Adel N; Alsayari, Khalid N; Altammami, Musaad A; Alshanqeeti, Ali S

2018-01-01

Because genetic and geographic variations in intestinal microbiota are known to exist, the focus of this study was to establish an estimation of microbiota in colorectal cancer (CRC) patients in Saudi Arabia by means of metagenomic studies. From July 2010 to November 2012, colorectal cancer patients attending our hospital were enrolled for the metagenomic studies. All underwent clinical, endoscopic, and histological assessment. Mucosal microbiota samples were collected from each patient by jet-flushing colonic mucosa with distilled water at unified segments of the colon, followed by aspiration, during colonoscopy. Total purified dsDNA was extracted and quantified prior to metagenomic sequencing using an Illumina platform. Satisfactory DNA samples ( n = 29) were subjected to metagenomics studies, followed by comprehensive comparative phylogenetic analysis. An equal number of healthy age-matched controls were also examined for colonic mucosal microbiota. Metagenomics data on 29 patients (14 females) in the age range 38-77 years were analyzed. The majority 11 (37%) of our patients were overweight (BMI = 25-30). Rectal bleeding was the presenting symptom in 18/29 (62%), while symptomatic anemia was the presenting symptom in 11/29 (37%). The location of colon cancer was rectal in 14 (48%), while cecal growth was observed in 8 (27%). Hepatic flexure growth was found in 1 (3%), descending colonic growth was found in 2 (6%), and 4 (13%) patients had transverse colon growth. The metagenomics analysis was carried out, and a total of 3.58G reads were sequenced, and about 321.91G data were used in the analysis. This study identified 11 genera specific to colorectal cancer patients when compared to genera in the control group. Bacteroides fragilis and Fusobacterium were found to be significantly prevalent in the carcinoma group when compared to the control group. The current study has given an insight into the microbiota of colorectal cancer patients in Saudi Arabia and has

A Novel Prosthetic Joint Infection Pathogen, Mycoplasma salivarium, Identified by Metagenomic Shotgun Sequencing.

PubMed

Thoendel, Matthew; Jeraldo, Patricio; Greenwood-Quaintance, Kerryl E; Chia, Nicholas; Abdel, Matthew P; Steckelberg, James M; Osmon, Douglas R; Patel, Robin

2017-07-15

Defining the microbial etiology of culture-negative prosthetic joint infection (PJI) can be challenging. Metagenomic shotgun sequencing is a new tool to identify organisms undetected by conventional methods. We present a case where metagenomics was used to identify Mycoplasma salivarium as a novel PJI pathogen in a patient with hypogammaglobulinemia. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Production of indole antibiotics induced by exogenous gene derived from sponge metagenomes.

PubMed

Takeshige, Yuya; Egami, Yoko; Wakimoto, Toshiyuki; Abe, Ikuro

2015-05-01

Sponge metagenomes are accessible genetic sources containing genes and gene clusters responsible for the biosynthesis of sponge-derived bioactive natural products. In this study, we obtained the clone pDC112, producing turbomycin A and 2,2-di(3-indolyl)-3-indolone, based on the functional screening of the metagenome library derived from the marine sponge Discodermia calyx. The subcloning experiment identified ORF 25, which is homologous to inosine 5'-monophosphate dehydrogenase and required for the production of 2,2-di(3-indolyl)-3-indolone in Escherichia coli.

Windshield splatter analysis with the Galaxy metagenomic pipeline

PubMed Central

Kosakovsky Pond, Sergei; Wadhawan, Samir; Chiaromonte, Francesca; Ananda, Guruprasad; Chung, Wen-Yu; Taylor, James; Nekrutenko, Anton

2009-01-01

How many species inhabit our immediate surroundings? A straightforward collection technique suitable for answering this question is known to anyone who has ever driven a car at highway speeds. The windshield of a moving vehicle is subjected to numerous insect strikes and can be used as a collection device for representative sampling. Unfortunately the analysis of biological material collected in that manner, as with most metagenomic studies, proves to be rather demanding due to the large number of required tools and considerable computational infrastructure. In this study, we use organic matter collected by a moving vehicle to design and test a comprehensive pipeline for phylogenetic profiling of metagenomic samples that includes all steps from processing and quality control of data generated by next-generation sequencing technologies to statistical analyses and data visualization. To the best of our knowledge, this is also the first publication that features a live online supplement providing access to exact analyses and workflows used in the article. PMID:19819906

Long-term landscape change and bird abundance in Amazonian rainforest fragments.

PubMed

Stouffer, Philip C; Bierregaard, Richard O; Strong, Cheryl; Lovejoy, Thomas E

2006-08-01

The rainforests of the Amazon basin are being cut by humans at a rate >20,000 km2/year leading to smaller and more isolated patches of forest, with remaining fragments often in the range of 1-100 ha. We analyzed samples of understory birds collected over 20 years from a standardized mist-netting program in 1- to 100-ha rainforest fragments in a dynamic Amazonian landscape near Manaus, Brazil. Across bird guilds, the condition of second growth immediately surrounding fragments was often as important as fragment size or local forest cover in explaining variation in abundance. Some fragments surrounded by 100 m of open pasture showed reductions in insectivorous bird abundance of over 95%, even in landscapes dominated by continuous forest and old second growth. These extreme reductions may be typical throughout Amazonia in small (< or =10 ha), isolated fragments of rainforest. Abundance for some guilds returned to preisolation levels in 10- and 100-ha fragments connected to continuous forest by 20-year-old second growth. Our results show that the consequences of Amazonian forest loss cannot be accurately described without explicit consideration of vegetation dynamics in matrix habitat. Any dichotomous classification of the landscape into 'forest" and "nonforest" misses essential information about the matrix.

Comparative metagenomics of bathypelagic plankton and bottom sediment from the Sea of Marmara

PubMed Central

Quaiser, Achim; Zivanovic, Yvan; Moreira, David; López-García, Purificación

2011-01-01

To extend comparative metagenomic analyses of the deep-sea, we produced metagenomic data by direct 454 pyrosequencing from bathypelagic plankton (1000 m depth) and bottom sediment of the Sea of Marmara, the gateway between the Eastern Mediterranean and the Black Seas. Data from small subunit ribosomal RNA (SSU rRNA) gene libraries and direct pyrosequencing of the same samples indicated that Gamma- and Alpha-proteobacteria, followed by Bacteroidetes, dominated the bacterial fraction in Marmara deep-sea plankton, whereas Planctomycetes, Delta- and Gamma-proteobacteria were the most abundant groups in high bacterial-diversity sediment. Group I Crenarchaeota/Thaumarchaeota dominated the archaeal plankton fraction, although group II and III Euryarchaeota were also present. Eukaryotes were highly diverse in SSU rRNA gene libraries, with group I (Duboscquellida) and II (Syndiniales) alveolates and Radiozoa dominating plankton, and Opisthokonta and Alveolates, sediment. However, eukaryotic sequences were scarce in pyrosequence data. Archaeal amo genes were abundant in plankton, suggesting that Marmara planktonic Thaumarchaeota are ammonia oxidizers. Genes involved in sulfate reduction, carbon monoxide oxidation, anammox and sulfatases were over-represented in sediment. Genome recruitment analyses showed that Alteromonas macleodii ‘surface ecotype', Pelagibacter ubique and Nitrosopumilus maritimus were highly represented in 1000 m-deep plankton. A comparative analysis of Marmara metagenomes with ALOHA deep-sea and surface plankton, whale carcasses, Peru subsurface sediment and soil metagenomes clustered deep-sea Marmara plankton with deep-ALOHA plankton and whale carcasses, likely because of the suboxic conditions in the deep Marmara water column. The Marmara sediment clustered with the soil metagenome, highlighting the common ecological role of both types of microbial communities in the degradation of organic matter and the completion of biogeochemical cycles. PMID

Metagenome and metatranscriptome data for Rifle CMT-03 laboratory microcosm experiment completed in April 2014

DOE Data Explorer

Jewell, Talia [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Karaoz, Ulas [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Bill, Markus [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Chakraborty, Romy [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brodie, Eoin L [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Williams, Kenneth Hurst [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Beller, Harry R [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2014-04-01

Sediment samples were collected during installation of monitoring borehole CMT-03. Microcosms were constructed and inoculated under anerobic conditions with these sediments and anaerobic Rifle artificial groundwater. Microcosm metagenomes and metatranscriptomes were sampled every 5 days for a period of 20 days. The dataset gives gene-level annotations, binning, metagenomic and metatranscriptomic coverages for these microcosms.

Genomic and metagenomic challenges and opportunities for bioleaching: a mini-review.

PubMed

Cárdenas, Juan Pablo; Quatrini, Raquel; Holmes, David S

2016-09-01

High-throughput genomic technologies are accelerating progress in understanding the diversity of microbial life in many environments. Here we highlight advances in genomics and metagenomics of microorganisms from bioleaching heaps and related acidic mining environments. Bioleaching heaps used for copper recovery provide significant opportunities to study the processes and mechanisms underlying microbial successions and the influence of community composition on ecosystem functioning. Obtaining quantitative and process-level knowledge of these dynamics is pivotal for understanding how microorganisms contribute to the solubilization of copper for industrial recovery. Advances in DNA sequencing technology provide unprecedented opportunities to obtain information about the genomes of bioleaching microorganisms, allowing predictive models of metabolic potential and ecosystem-level interactions to be constructed. These approaches are enabling predictive phenotyping of organisms many of which are recalcitrant to genetic approaches or are unculturable. This mini-review describes current bioleaching genomic and metagenomic projects and addresses the use of genome information to: (i) build metabolic models; (ii) predict microbial interactions; (iii) estimate genetic diversity; and (iv) study microbial evolution. Key challenges and perspectives of bioleaching genomics/metagenomics are addressed. Copyright © 2016 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.

Gene and translation initiation site prediction in metagenomic sequences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hyatt, Philip Douglas; LoCascio, Philip F; Hauser, Loren John

2012-01-01

Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data. We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translationmore » initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.« less

CoMet: a workflow using contig coverage and composition for binning a metagenomic sample with high precision.

PubMed

Herath, Damayanthi; Tang, Sen-Lin; Tandon, Kshitij; Ackland, David; Halgamuge, Saman Kumara

2017-12-28

In metagenomics, the separation of nucleotide sequences belonging to an individual or closely matched populations is termed binning. Binning helps the evaluation of underlying microbial population structure as well as the recovery of individual genomes from a sample of uncultivable microbial organisms. Both supervised and unsupervised learning methods have been employed in binning; however, characterizing a metagenomic sample containing multiple strains remains a significant challenge. In this study, we designed and implemented a new workflow, Coverage and composition based binning of Metagenomes (CoMet), for binning contigs in a single metagenomic sample. CoMet utilizes coverage values and the compositional features of metagenomic contigs. The binning strategy in CoMet includes the initial grouping of contigs in guanine-cytosine (GC) content-coverage space and refinement of bins in tetranucleotide frequencies space in a purely unsupervised manner. With CoMet, the clustering algorithm DBSCAN is employed for binning contigs. The performances of CoMet were compared against four existing approaches for binning a single metagenomic sample, including MaxBin, Metawatt, MyCC (default) and MyCC (coverage) using multiple datasets including a sample comprised of multiple strains. Binning methods based on both compositional features and coverages of contigs had higher performances than the method which is based only on compositional features of contigs. CoMet yielded higher or comparable precision in comparison to the existing binning methods on benchmark datasets of varying complexities. MyCC (coverage) had the highest ranking score in F1-score. However, the performances of CoMet were higher than MyCC (coverage) on the dataset containing multiple strains. Furthermore, CoMet recovered contigs of more species and was 18 - 39% higher in precision than the compared existing methods in discriminating species from the sample of multiple strains. CoMet resulted in higher precision

FIELD TESTS OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED WATERSHED CLASSIFICATION SCHEMES IN THE GREAT LAKES BASIN

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme for two case studies involving 1) Lake Superior tributaries and 2) watersheds of riverine coastal wetlands...

FIELD TESTS OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED WATERSHED CLASSIFICATION SCHEMED IN THE GREAT LAKES BASIN

EPA Science Inventory

We compared classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme for two case studies involving 1)Lake Superior tributaries and 2) watersheds of riverine coastal wetlands ...

A metagenomic viral discovery approach identifies potential zoonotic and novel mammalian viruses in Neoromicia bats within South Africa

PubMed Central

Geldenhuys, Marike; Mortlock, Marinda; Weyer, Jacqueline; Bezuidt, Oliver; Seamark, Ernest C. J.; Kearney, Teresa; Gleasner, Cheryl; Erkkila, Tracy H.; Cui, Helen; Markotter, Wanda

2018-01-01

Species within the Neoromicia bat genus are abundant and widely distributed in Africa. It is common for these insectivorous bats to roost in anthropogenic structures in urban regions. Additionally, Neoromicia capensis have previously been identified as potential hosts for Middle East respiratory syndrome (MERS)-related coronaviruses. This study aimed to ascertain the gastrointestinal virome of these bats, as viruses excreted in fecal material or which may be replicating in rectal or intestinal tissues have the greatest opportunities of coming into contact with other hosts. Samples were collected in five regions of South Africa over eight years. Initial virome composition was determined by viral metagenomic sequencing by pooling samples and enriching for viral particles. Libraries were sequenced on the Illumina MiSeq and NextSeq500 platforms, producing a combined 37 million reads. Bioinformatics analysis of the high throughput sequencing data detected the full genome of a novel species of the Circoviridae family, and also identified sequence data from the Adenoviridae, Coronaviridae, Herpesviridae, Parvoviridae, Papillomaviridae, Phenuiviridae, and Picornaviridae families. Metagenomic sequencing data was insufficient to determine the viral diversity of certain families due to the fragmented coverage of genomes and lack of suitable sequencing depth, as some viruses were detected from the analysis of reads-data only. Follow up conventional PCR assays targeting conserved gene regions for the Adenoviridae, Coronaviridae, and Herpesviridae families were used to confirm metagenomic data and generate additional sequences to determine genetic diversity. The complete coding genome of a MERS-related coronavirus was recovered with additional amplicon sequencing on the MiSeq platform. The new genome shared 97.2% overall nucleotide identity to a previous Neoromicia-associated MERS-related virus, also from South Africa. Conventional PCR analysis detected diverse adenovirus and

Evaluation of FTA ® paper for storage of oral meta-genomic DNA.

PubMed

Foitzik, Magdalena; Stumpp, Sascha N; Grischke, Jasmin; Eberhard, Jörg; Stiesch, Meike

2014-10-01

The purpose of the present study was to evaluate the short-term storage of meta-genomic DNA from native oral biofilms on FTA(®) paper. Thirteen volunteers of both sexes received an acrylic splint for intraoral biofilm formation over a period of 48 hours. The biofilms were collected, resuspended in phosphate-buffered saline, and either stored on FTA(®) paper or directly processed by standard laboratory DNA extraction. The nucleic acid extraction efficiencies were evaluated by 16S rDNA targeted SSCP fingerprinting. The acquired banding pattern of FTA-derived meta-genomic DNA was compared to a standard DNA preparation protocol. Sensitivity and positive predictive values were calculated. The volunteers showed inter-individual differences in their bacterial species composition. A total of 200 bands were found for both methods and 85% of the banding patterns were equal, representing a sensitivity of 0.941 and a false-negative predictive value of 0.059. Meta-genomic DNA sampling, extraction, and adhesion using FTA(®) paper is a reliable method for storage of microbial DNA for a short period of time.

Comparative metagenomics reveals different hydrocarbon degradative abilities from enriched oil-drilling waste.

PubMed

Napp, Amanda P; Pereira, José Evandro S; Oliveira, Jorge S; Silva-Portela, Rita C B; Agnez-Lima, Lucymara F; Peralba, Maria C R; Bento, Fátima M; Passaglia, Luciane M P; Thompson, Claudia E; Vainstein, Marilene H

2018-06-11

The oil drilling process generates large volumes of waste with inadequate treatments. Here, oil drilling waste (ODW) microbial communities demonstrate different hydrocarbon degradative abilities when exposed to distinct nutrient enrichments as revealed by comparative metagenomics. The ODW was enriched in Luria Broth (LBE) and Potato Dextrose (PDE) media to examine the structure and functional variations of microbial consortia. Two metagenomes were sequenced on Ion Torrent platform and analyzed using MG-RAST. The STAMP software was used to analyze statistically significant differences amongst different attributes of metagenomes. The microbial diversity presented in the different enrichments was distinct and heterogeneous. The metabolic pathways and enzymes were mainly related to the aerobic hydrocarbons degradation. Moreover, our results showed efficient biodegradation after 15 days of treatment for aliphatic hydrocarbons (C8-C33) and polycyclic aromatic hydrocarbons (PAHs), with a total of about 50.5% and 46.4% for LBE and 44.6% and 37.9% for PDE, respectively. The results obtained suggest the idea that the enzymatic apparatus have the potential to degrade petroleum compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

MinION™ nanopore sequencing of environmental metagenomes: a synthetic approach.

PubMed

Brown, Bonnie L; Watson, Mick; Minot, Samuel S; Rivera, Maria C; Franklin, Rima B

2017-03-01

Environmental metagenomic analysis is typically accomplished by assigning taxonomy and/or function from whole genome sequencing or 16S amplicon sequences. Both of these approaches are limited, however, by read length, among other technical and biological factors. A nanopore-based sequencing platform, MinION™, produces reads that are ≥1 × 104 bp in length, potentially providing for more precise assignment, thereby alleviating some of the limitations inherent in determining metagenome composition from short reads. We tested the ability of sequence data produced by MinION (R7.3 flow cells) to correctly assign taxonomy in single bacterial species runs and in three types of low-complexity synthetic communities: a mixture of DNA using equal mass from four species, a community with one relatively rare (1%) and three abundant (33% each) components, and a mixture of genomic DNA from 20 bacterial strains of staggered representation. Taxonomic composition of the low-complexity communities was assessed by analyzing the MinION sequence data with three different bioinformatic approaches: Kraken, MG-RAST, and One Codex. Results: Long read sequences generated from libraries prepared from single strains using the version 5 kit and chemistry, run on the original MinION device, yielded as few as 224 to as many as 3497 bidirectional high-quality (2D) reads with an average overall study length of 6000 bp. For the single-strain analyses, assignment of reads to the correct genus by different methods ranged from 53.1% to 99.5%, assignment to the correct species ranged from 23.9% to 99.5%, and the majority of misassigned reads were to closely related organisms. A synthetic metagenome sequenced with the same setup yielded 714 high quality 2D reads of approximately 5500 bp that were up to 98% correctly assigned to the species level. Synthetic metagenome MinION libraries generated using version 6 kit and chemistry yielded from 899 to 3497 2D reads with lengths averaging 5700 bp with up

Functional Screening of Metagenome and Genome Libraries for Detection of Novel Flavonoid-Modifying Enzymes

PubMed Central

Rabausch, U.; Juergensen, J.; Ilmberger, N.; Böhnke, S.; Fischer, S.; Schubach, B.; Schulte, M.

2013-01-01

The functional detection of novel enzymes other than hydrolases from metagenomes is limited since only a very few reliable screening procedures are available that allow the rapid screening of large clone libraries. For the discovery of flavonoid-modifying enzymes in genome and metagenome clone libraries, we have developed a new screening system based on high-performance thin-layer chromatography (HPTLC). This metagenome extract thin-layer chromatography analysis (META) allows the rapid detection of glycosyltransferase (GT) and also other flavonoid-modifying activities. The developed screening method is highly sensitive, and an amount of 4 ng of modified flavonoid molecules can be detected. This novel technology was validated against a control library of 1,920 fosmid clones generated from a single Bacillus cereus isolate and then used to analyze more than 38,000 clones derived from two different metagenomic preparations. Thereby we identified two novel UDP glycosyltransferase (UGT) genes. The metagenome-derived gtfC gene encoded a 52-kDa protein, and the deduced amino acid sequence was weakly similar to sequences of putative UGTs from Fibrisoma and Dyadobacter. GtfC mediated the transfer of different hexose moieties and exhibited high activities on flavones, flavonols, flavanones, and stilbenes and also accepted isoflavones and chalcones. From the control library we identified a novel macroside glycosyltransferase (MGT) with a calculated molecular mass of 46 kDa. The deduced amino acid sequence was highly similar to sequences of MGTs from Bacillus thuringiensis. Recombinant MgtB transferred the sugar residue from UDP-glucose effectively to flavones, flavonols, isoflavones, and flavanones. Moreover, MgtB exhibited high activity on larger flavonoid molecules such as tiliroside. PMID:23686272

Current Advances on Virus Discovery and Diagnostic Role of Viral Metagenomics in Aquatic Organisms

PubMed Central

Munang'andu, Hetron M.; Mugimba, Kizito K.; Byarugaba, Denis K.; Mutoloki, Stephen; Evensen, Øystein

2017-01-01

The global expansion of the aquaculture industry has brought with it a corresponding increase of novel viruses infecting different aquatic organisms. These emerging viral pathogens have proved to be a challenge to the use of traditional cell-cultures and immunoassays for identification of new viruses especially in situations where the novel viruses are unculturable and no antibodies exist for their identification. Viral metagenomics has the potential to identify novel viruses without prior knowledge of their genomic sequence data and may provide a solution for the study of unculturable viruses. This review provides a synopsis on the contribution of viral metagenomics to the discovery of viruses infecting different aquatic organisms as well as its potential role in viral diagnostics. High throughput Next Generation sequencing (NGS) and library construction used in metagenomic projects have simplified the task of generating complete viral genomes unlike the challenge faced in traditional methods that use multiple primers targeted at different segments and VPs to generate the entire genome of a novel virus. In terms of diagnostics, studies carried out this far show that viral metagenomics has the potential to serve as a multifaceted tool able to study and identify etiological agents of single infections, co-infections, tissue tropism, profiling viral infections of different aquatic organisms, epidemiological monitoring of disease prevalence, evolutionary phylogenetic analyses, and the study of genomic diversity in quasispecies viruses. With sequencing technologies and bioinformatics analytical tools becoming cheaper and easier, we anticipate that metagenomics will soon become a routine tool for the discovery, study, and identification of novel pathogens including viruses to enable timely disease control for emerging diseases in aquaculture. PMID:28382024

Isolation and characterization of a novel metagenomic enzyme capable of degrading bacterial phytotoxin toxoflavin

PubMed Central

Lee, Boyoung; Park, Ji Hyun; Oh, Joon Young; Choi, Jung Sup; Kim, Jin-Cheol

2018-01-01

Toxoflavin, a 7-azapteridine phytotoxin produced by the bacterial pathogens such as Burkholderia glumae and Burkholderia gladioli, has been known as one of the key virulence factors in crop diseases. Because the toxoflavin had an antibacterial activity, a metagenomic E. coli clone capable of growing well in the presence of toxoflavin (30 μg/ml) was isolated and the first metagenome-derived toxoflavin-degrading enzyme, TxeA of 140 amino acid residues, was identified from the positive E. coli clone. The conserved amino acids for metal-binding and extradiol dioxygenase activity, Glu-12, His-8 and Glu-130, were revealed by the sequence analysis of TxeA. The optimum conditions for toxoflavin degradation were evaluated with the TxeA purified in E. coli. Toxoflavin was totally degraded at an initial toxoflavin concentration of 100 μg/ml and at pH 5.0 in the presence of Mn2+, dithiothreitol and oxygen. The final degradation products of toxoflavin and methyltoxoflavin were fully identified by MS and NMR as triazines. Therefore, we suggested that the new metagenomic enzyme, TxeA, provided the clue to applying the new metagenomic enzyme to resistance development of crop plants to toxoflavin-mediated disease as well as to biocatalysis for Baeyer-Villiger type oxidation. PMID:29293506

A functional metagenomic approach for expanding the synthetic biology toolbox for biomass conversion

PubMed Central

Sommer, Morten OA; Church, George M; Dantas, Gautam

2010-01-01

Sustainable biofuel alternatives to fossil fuel energy are hampered by recalcitrance and toxicity of biomass substrates to microbial biocatalysts. To address this issue, we present a culture-independent functional metagenomic platform for mining Nature's vast enzymatic reservoir and show its relevance to biomass conversion. We performed functional selections on 4.7 Gb of metagenomic fosmid libraries and show that genetic elements conferring tolerance toward seven important biomass inhibitors can be identified. We select two metagenomic fosmids that improve the growth of Escherichia coli by 5.7- and 6.9-fold in the presence of inhibitory concentrations of syringaldehyde and 2-furoic acid, respectively, and identify the individual genes responsible for these tolerance phenotypes. Finally, we combine the individual genes to create a three-gene construct that confers tolerance to mixtures of these important biomass inhibitors. This platform presents a route for expanding the repertoire of genetic elements available to synthetic biology and provides a starting point for efforts to engineer robust strains for biofuel generation. PMID:20393580

A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation.

PubMed

Sternes, Peter R; Lee, Danna; Kutyna, Dariusz R; Borneman, Anthony R

2017-07-01

Wine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. Commercially, there is now a growing trend away from using wine yeast (Saccharomyces) starter cultures, toward the historic practice of uninoculated or "wild" fermentation, where the yeasts and bacteria associated with the grapes and/or winery perform the fermentation. It is the varied metabolic contributions of these numerous non-Saccharomyces species that are thought to impart complexity and desirable taste and aroma attributes to wild ferments in comparison to their inoculated counterparts. To map the microflora of spontaneous fermentation, metagenomic techniques were employed to characterize and monitor the progression of fungal species in 5 different wild fermentations. Both amplicon-based ribosomal DNA internal transcribed spacer (ITS) phylotyping and shotgun metagenomics were used to assess community structure across different stages of fermentation. While providing a sensitive and highly accurate means of characterizing the wine microbiome, the shotgun metagenomic data also uncovered a significant overabundance bias in the ITS phylotyping abundance estimations for the common non-Saccharomyces wine yeast genus Metschnikowia. By identifying biases such as that observed for Metschnikowia, abundance measurements from future ITS phylotyping datasets can be corrected to provide more accurate species representation. Ultimately, as more shotgun metagenomic and single-strain de novo assemblies for key wine species become available, the accuracy of both ITS-amplicon and shotgun studies will greatly increase, providing a powerful methodology for deciphering the influence of the microbial community on the wine flavor and aroma. © The Authors 2017. Published by Oxford University Press.

A combined meta-barcoding and shotgun metagenomic analysis of spontaneous wine fermentation

PubMed Central

Sternes, Peter R.; Lee, Danna; Kutyna, Dariusz R.

2017-01-01

Abstract Wine is a complex beverage, comprising hundreds of metabolites produced through the action of yeasts and bacteria in fermenting grape must. Commercially, there is now a growing trend away from using wine yeast (Saccharomyces) starter cultures, toward the historic practice of uninoculated or “wild” fermentation, where the yeasts and bacteria associated with the grapes and/or winery perform the fermentation. It is the varied metabolic contributions of these numerous non-Saccharomyces species that are thought to impart complexity and desirable taste and aroma attributes to wild ferments in comparison to their inoculated counterparts. To map the microflora of spontaneous fermentation, metagenomic techniques were employed to characterize and monitor the progression of fungal species in 5 different wild fermentations. Both amplicon-based ribosomal DNA internal transcribed spacer (ITS) phylotyping and shotgun metagenomics were used to assess community structure across different stages of fermentation. While providing a sensitive and highly accurate means of characterizing the wine microbiome, the shotgun metagenomic data also uncovered a significant overabundance bias in the ITS phylotyping abundance estimations for the common non-Saccharomyces wine yeast genus Metschnikowia. By identifying biases such as that observed for Metschnikowia, abundance measurements from future ITS phylotyping datasets can be corrected to provide more accurate species representation. Ultimately, as more shotgun metagenomic and single-strain de novo assemblies for key wine species become available, the accuracy of both ITS-amplicon and shotgun studies will greatly increase, providing a powerful methodology for deciphering the influence of the microbial community on the wine flavor and aroma. PMID:28595314

Metagenomic investigation of gastrointestinal microbiome in cattle

PubMed Central

Kim, Minseok; Park, Tansol; Yu, Zhongtang

2017-01-01

The gastrointestinal (GI) tract, including the rumen and the other intestinal segments of cattle, harbors a diverse, complex, and dynamic microbiome that drives feed digestion and fermentation in cattle, determining feed efficiency and output of pollutants. This microbiome also plays an important role in affecting host health. Research has been conducted for more than a century to understand the microbiome and its relationship to feed efficiency and host health. The traditional cultivation-based research elucidated some of the major metabolism, but studies using molecular biology techniques conducted from late 1980’s to the late early 2000’s greatly expanded our view of the diversity of the rumen and intestinal microbiome of cattle. Recently, metagenomics has been the primary technology to characterize the GI microbiome and its relationship with host nutrition and health. This review addresses the main methods/techniques in current use, the knowledge gained, and some of the challenges that remain. Most of the primers used in quantitative real-time polymerase chain reaction quantification and diversity analysis using metagenomics of ruminal bacteria, archaea, fungi, and protozoa were also compiled. PMID:28830126

WHAM!: a web-based visualization suite for user-defined analysis of metagenomic shotgun sequencing data.

PubMed

Devlin, Joseph C; Battaglia, Thomas; Blaser, Martin J; Ruggles, Kelly V

2018-06-25

Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets.

Safety analysis of a Russian phage cocktail: from metagenomic analysis to oral application in healthy human subjects.

PubMed

McCallin, Shawna; Alam Sarker, Shafiqul; Barretto, Caroline; Sultana, Shamima; Berger, Bernard; Huq, Sayeda; Krause, Lutz; Bibiloni, Rodrigo; Schmitt, Bertrand; Reuteler, Gloria; Brüssow, Harald

2013-09-01

Phage therapy has a long tradition in Eastern Europe, where preparations are comprised of complex phage cocktails whose compositions have not been described. We investigated the composition of a phage cocktail from the Russian pharmaceutical company Microgen targeting Escherichia coli/Proteus infections. Electron microscopy identified six phage types, with numerically T7-like phages dominating over T4-like phages. A metagenomic approach using taxonomical classification, reference mapping and de novo assembly identified 18 distinct phage types, including 7 genera of Podoviridae, 2 established and 2 proposed genera of Myoviridae, and 2 genera of Siphoviridae. De novo assembly yielded 7 contigs greater than 30 kb, including a 147-kb Myovirus genome and a 42-kb genome of a potentially new phage. Bioinformatic analysis did not reveal undesired genes and a small human volunteer trial did not associate adverse effects with oral phage exposure. Copyright © 2013 Elsevier Inc. All rights reserved.

Metagenomic Analyses of Drinking Water Receiving Different Disinfection Treatments

EPA Science Inventory

A metagenome-based approach was utilized for assessing the taxonomic affiliation and function potential of microbial populations in free chlorine (CHL) and monochloramine (CHM) treated drinking water (DW). A total of 1,024, 242 (averaging 544 bp) and 849, 349 (averaging 554 bp) ...

Efficiency of the spectral-spatial classification of hyperspectral imaging data

NASA Astrophysics Data System (ADS)

Borzov, S. M.; Potaturkin, O. I.

2017-01-01

The efficiency of methods of the spectral-spatial classification of similarly looking types of vegetation on the basis of hyperspectral data of remote sensing of the Earth, which take into account local neighborhoods of analyzed image pixels, is experimentally studied. Algorithms that involve spatial pre-processing of the raw data and post-processing of pixel-based spectral classification maps are considered. Results obtained both for a large-size hyperspectral image and for its test fragment with different methods of training set construction are reported. The classification accuracy in all cases is estimated through comparisons of ground-truth data and classification maps formed by using the compared methods. The reasons for the differences in these estimates are discussed.

Validation of a new classification system for interprosthetic femoral fractures.

PubMed

Pires, Robinson Esteves Santos; Silveira, Marcelo Peixoto Sena; Resende, Alessandra Regina da Silva; Junior, Egidio Oliveira Santana; Campos, Tulio Vinicius Oliveira; Santos, Leandro Emilio Nascimento; Balbachevsky, Daniel; Andrade, Marco Antônio Percope de

2017-07-01

Interprosthetic femoral fracture (IFF) incidence is gradually increasing as the population is progressively ageing. However, treatment remains challenging due to several contributing factors, such as poor bone quality, patient comorbidities, small interprosthetic fragment, and prostheses instability. An effective and specific classification system is essential to optimize treatment management, therefore diminishing complication rates. This study aims to validate a previously described classification system for interprosthetic femoral fractures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improved assemblies using a source-agnostic pipeline for MetaGenomic Assembly by Merging (MeGAMerge) of contigs

DOE PAGES

Scholz, Matthew; Lo, Chien -Chi; Chain, Patrick S. G.

2014-10-01

Assembly of metagenomic samples is a very complex process, with algorithms designed to address sequencing platform-specific issues, (read length, data volume, and/or community complexity), while also faced with genomes that differ greatly in nucleotide compositional biases and in abundance. To address these issues, we have developed a post-assembly process: MetaGenomic Assembly by Merging (MeGAMerge). We compare this process to the performance of several assemblers, using both real, and in-silico generated samples of different community composition and complexity. MeGAMerge consistently outperforms individual assembly methods, producing larger contigs with an increased number of predicted genes, without replication of data. MeGAMerge contigs aremore » supported by read mapping and contig alignment data, when using synthetically-derived and real metagenomic data, as well as by gene prediction analyses and similarity searches. Ultimately, MeGAMerge is a flexible method that generates improved metagenome assemblies, with the ability to accommodate upcoming sequencing platforms, as well as present and future assembly algorithms.« less

Construction and Screening of Marine Metagenomic Large Insert Libraries.

PubMed

Weiland-Bräuer, Nancy; Langfeldt, Daniela; Schmitz, Ruth A

2017-01-01

The marine environment covers more than 70 % of the world's surface. Marine microbial communities are highly diverse and have evolved during extended evolutionary processes of physiological adaptations under the influence of a variety of ecological conditions and selection pressures. They harbor an enormous diversity of microbes with still unknown and probably new physiological characteristics. In the past, marine microbes, mostly bacteria of microbial consortia attached to marine tissues of multicellular organisms, have proven to be a rich source of highly potent bioactive compounds, which represent a considerable number of drug candidates. However, to date, the biodiversity of marine microbes and the versatility of their bioactive compounds and metabolites have not been fully explored. This chapter describes sampling in the marine environment, construction of metagenomic large insert libraries from marine habitats, and exemplarily one function based screen of metagenomic clones for identification of quorum quenching activities.

High definition for systems biology of microbial communities: metagenomics gets genome-centric and strain-resolved.

PubMed

Turaev, Dmitrij; Rattei, Thomas

2016-06-01

The systems biology of microbial communities, organismal communities inhabiting all ecological niches on earth, has in recent years been strongly facilitated by the rapid development of experimental, sequencing and data analysis methods. Novel experimental approaches and binning methods in metagenomics render the semi-automatic reconstructions of near-complete genomes of uncultivable bacteria possible, while advances in high-resolution amplicon analysis allow for efficient and less biased taxonomic community characterization. This will also facilitate predictive modeling approaches, hitherto limited by the low resolution of metagenomic data. In this review, we pinpoint the most promising current developments in metagenomics. They facilitate microbial systems biology towards a systemic understanding of mechanisms in microbial communities with scopes of application in many areas of our daily life. Copyright © 2016 Elsevier Ltd. All rights reserved.

Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community

DOE PAGES

Bowers, Robert M.; Clum, Alicia; Tice, Hope; ...

2015-10-24

Background: The rapid development of sequencing technologies has provided access to environments that were either once thought inhospitable to life altogether or that contain too few cells to be analyzed using genomics approaches. While 16S rRNA gene microbial community sequencing has revolutionized our understanding of community composi tion and diversity over time and space, it only provides a crude estimate of microbial functional and metabolic potential. Alternatively, shotgun metagenomics allows comprehensive sampling of all genetic material in an environment, without any underlying primer biases. Until recently, one of the major bottlenecks of shotgun metagenomics has been the requirement for largemore » initial DNA template quantities during library preparation. Results: Here, we investigate the effects of varying template concentrations across three low biomass library preparation protocols on their ability to accurately reconstruct a mock microbial community of known composition. We analyze the effects of input DNA quantity and library preparation method on library insert size, GC content, community composition, assembly quality and metagenomic binning. We found that library preparation method and the amount of starting material had significant impacts on the mock community metagenomes. In particular, GC content shifted towards more GC rich sequences at the lower input quantities regardless of library prep method, the number of low quality reads that could not be mapped to the reference genomes increased with decreasing input quantities, and the different library preparation methods had an impact on overall metagenomic community composition. Conclusions: This benchmark study provides recommendations for library creation of representative and minimally biased metagenome shotgun sequencing, enabling insights into functional attributes of low biomass ecosystem microbial communities.« less

Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bowers, Robert M.; Clum, Alicia; Tice, Hope

Background: The rapid development of sequencing technologies has provided access to environments that were either once thought inhospitable to life altogether or that contain too few cells to be analyzed using genomics approaches. While 16S rRNA gene microbial community sequencing has revolutionized our understanding of community composi tion and diversity over time and space, it only provides a crude estimate of microbial functional and metabolic potential. Alternatively, shotgun metagenomics allows comprehensive sampling of all genetic material in an environment, without any underlying primer biases. Until recently, one of the major bottlenecks of shotgun metagenomics has been the requirement for largemore » initial DNA template quantities during library preparation. Results: Here, we investigate the effects of varying template concentrations across three low biomass library preparation protocols on their ability to accurately reconstruct a mock microbial community of known composition. We analyze the effects of input DNA quantity and library preparation method on library insert size, GC content, community composition, assembly quality and metagenomic binning. We found that library preparation method and the amount of starting material had significant impacts on the mock community metagenomes. In particular, GC content shifted towards more GC rich sequences at the lower input quantities regardless of library prep method, the number of low quality reads that could not be mapped to the reference genomes increased with decreasing input quantities, and the different library preparation methods had an impact on overall metagenomic community composition. Conclusions: This benchmark study provides recommendations for library creation of representative and minimally biased metagenome shotgun sequencing, enabling insights into functional attributes of low biomass ecosystem microbial communities.« less

Direct Detection and Identification of Prosthetic Joint Infection Pathogens in Synovial Fluid by Metagenomic Shotgun Sequencing.

PubMed

Ivy, Morgan I; Thoendel, Matthew J; Jeraldo, Patricio R; Greenwood-Quaintance, Kerryl E; Hanssen, Arlen D; Abdel, Matthew P; Chia, Nicholas; Yao, Janet Z; Tande, Aaron J; Mandrekar, Jayawant N; Patel, Robin

2018-05-30

Background: Metagenomic shotgun sequencing has the potential to transform how serious infections are diagnosed by offering universal, culture-free pathogen detection. This may be especially advantageous for microbial diagnosis of prosthetic joint infection (PJI) by synovial fluid analysis, since synovial fluid cultures are not universally positive, and synovial fluid is easily obtained pre-operatively. We applied a metagenomics-based approach to synovial fluid in an attempt to detect microorganisms in 168 failed total knee arthroplasties. Results: Genus- and species-level analysis of metagenomic sequencing yielded the known pathogen in 74 (90%) and 68 (83%) of the 82 culture-positive PJIs analyzed, respectively, with testing of two (2%) and three (4%) samples, respectively, yielding additional pathogens not detected by culture. For the 25 culture-negative PJIs tested, genus- and species-level analysis yielded 19 (76%) and 21 (84%) samples with insignificant findings, respectively, and 6 (24%) and 4 (16%) with potential pathogens detected, respectively. Genus- and species-level analysis of the 60 culture-negative aseptic failure cases yielded 53 (88.3%) and 56 (93.3%) cases with insignificant findings, and 7 (11.7%) and 4 (6.7%) with potential clinically-significant organisms detected, respectively. There was one case of aseptic failure with synovial fluid culture growth; metagenomic analysis showed insignificant findings, suggesting possible synovial fluid culture contamination. Conclusion: Metagenomic shotgun sequencing can detect pathogens involved in PJI when applied to synovial fluid and may be particularly useful for culture-negative cases. Copyright © 2018 American Society for Microbiology.

Summer Workshop in Metagenomics: One Week Plus Eight Students Equals Gigabases of Cloned DNA †

PubMed Central

Rios-Velazquez, Carlos; Williamson, Lynn L.; Cloud-Hansen, Karen A.; Allen, Heather K.; McMahon, Mathew D.; Sabree, Zakee L.; Donato, Justin J.; Handelsman, Jo

2011-01-01

We designed a week-long laboratory workshop in metagenomics for a cohort of undergraduate student researchers. During this course, students learned and utilized molecular biology and microbiology techniques to construct a metagenomic library from Puerto Rican soil. Pre-and postworkshop assessments indicated student learning gains in technical knowledge, skills, and confidence in a research environment. Postworkshop construction of additional libraries demonstrated retention of research techniques by the students. PMID:23653755

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

PubMed Central

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; Breitbart, Mya; Edwards, Robert A.

2015-01-01

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set of publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. We propose adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution. PMID:26005436

Evolutionary, ecological and biotechnological perspectives on plasmids resident in the human gut mobile metagenome

PubMed Central

Ogilvie, Lesley A.; Firouzmand, Sepinoud; Jones, Brian V.

2012-01-01

Numerous mobile genetic elements (MGE) are associated with the human gut microbiota and collectively referred to as the gut mobile metagenome. The role of this flexible gene pool in development and functioning of the gut microbial community remains largely unexplored, yet recent evidence suggests that at least some MGE comprising this fraction of the gut microbiome reflect the co-evolution of host and microbe in the gastro-intestinal tract. In conjunction, the high level of novel gene content typical of MGE coupled with their predicted high diversity, suggests that the mobile metagenome constitutes an immense and largely unexplored gene-space likely to encode many novel activities with potential biotechnological or pharmaceutical value, as well as being important to the development and functioning of the gut microbiota. Of the various types of MGE that comprise the gut mobile metagenome, plasmids are of particular importance since these elements are often capable of autonomous transfer between disparate bacterial species, and are known to encode accessory functions that increase bacterial fitness in a given environment facilitating bacterial adaptation. In this article current knowledge regarding plasmids resident in the human gut mobile metagenome is reviewed, and available strategies to access and characterize this portion of the gut microbiome are described. The relative merits of these methods and their present as well as prospective impact on our understanding of the human gut microbiota is discussed. PMID:22126801

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

DOE PAGES

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia; ...

2015-05-08

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set ofmore » publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.« less

Multidimensional metrics for estimating phage abundance, distribution, gene density, and sequence coverage in metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, Ramy K.; Dwivedi, Bhakti; Akhter, Sajia

Phages are the most abundant biological entities on Earth and play major ecological roles, yet the current sequenced phage genomes do not adequately represent their diversity, and little is known about the abundance and distribution of these sequenced genomes in nature. Although the study of phage ecology has benefited tremendously from the emergence of metagenomic sequencing, a systematic survey of phage genes and genomes in various ecosystems is still lacking, and fundamental questions about phage biology, lifestyle, and ecology remain unanswered. To address these questions and improve comparative analysis of phages in different metagenomes, we screened a core set ofmore » publicly available metagenomic samples for sequences related to completely sequenced phages using the web tool, Phage Eco-Locator. We then adopted and deployed an array of mathematical and statistical metrics for a multidimensional estimation of the abundance and distribution of phage genes and genomes in various ecosystems. Experiments using those metrics individually showed their usefulness in emphasizing the pervasive, yet uneven, distribution of known phage sequences in environmental metagenomes. Using these metrics in combination allowed us to resolve phage genomes into clusters that correlated with their genotypes and taxonomic classes as well as their ecological properties. By adding this set of metrics to current metaviromic analysis pipelines, where they can provide insight regarding phage mosaicism, habitat specificity, and evolution.« less

Enrichment allows identification of diverse, rare elements in metagenomic resistome-virulome sequencing.

PubMed

Noyes, Noelle R; Weinroth, Maggie E; Parker, Jennifer K; Dean, Chris J; Lakin, Steven M; Raymond, Robert A; Rovira, Pablo; Doster, Enrique; Abdo, Zaid; Martin, Jennifer N; Jones, Kenneth L; Ruiz, Jaime; Boucher, Christina A; Belk, Keith E; Morley, Paul S

2017-10-17

Shotgun metagenomic sequencing is increasingly utilized as a tool to evaluate ecological-level dynamics of antimicrobial resistance and virulence, in conjunction with microbiome analysis. Interest in use of this method for environmental surveillance of antimicrobial resistance and pathogenic microorganisms is also increasing. In published metagenomic datasets, the total of all resistance- and virulence-related sequences accounts for < 1% of all sequenced DNA, leading to limitations in detection of low-abundance resistome-virulome elements. This study describes the extent and composition of the low-abundance portion of the resistome-virulome, using a bait-capture and enrichment system that incorporates unique molecular indices to count DNA molecules and correct for enrichment bias. The use of the bait-capture and enrichment system significantly increased on-target sequencing of the resistome-virulome, enabling detection of an additional 1441 gene accessions and revealing a low-abundance portion of the resistome-virulome that was more diverse and compositionally different than that detected by more traditional metagenomic assays. The low-abundance portion of the resistome-virulome also contained resistance genes with public health importance, such as extended-spectrum betalactamases, that were not detected using traditional shotgun metagenomic sequencing. In addition, the use of the bait-capture and enrichment system enabled identification of rare resistance gene haplotypes that were used to discriminate between sample origins. These results demonstrate that the rare resistome-virulome contains valuable and unique information that can be utilized for both surveillance and population genetic investigations of resistance. Access to the rare resistome-virulome using the bait-capture and enrichment system validated in this study can greatly advance our understanding of microbiome-resistome dynamics.

SUPER-FOCUS: a tool for agile functional analysis of shotgun metagenomic data

PubMed Central

Green, Kevin T.; Dutilh, Bas E.; Edwards, Robert A.

2016-01-01

Summary: Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools. Availability and implementation: SUPER-FOCUS was implemented in Python, and its source code and the tool website are freely available at https://edwards.sdsu.edu/SUPERFOCUS. Contact: redwards@mail.sdsu.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26454280

SUPER-FOCUS: a tool for agile functional analysis of shotgun metagenomic data.

PubMed

Silva, Genivaldo Gueiros Z; Green, Kevin T; Dutilh, Bas E; Edwards, Robert A

2016-02-01

Analyzing the functional profile of a microbial community from unannotated shotgun sequencing reads is one of the important goals in metagenomics. Functional profiling has valuable applications in biological research because it identifies the abundances of the functional genes of the organisms present in the original sample, answering the question what they can do. Currently, available tools do not scale well with increasing data volumes, which is important because both the number and lengths of the reads produced by sequencing platforms keep increasing. Here, we introduce SUPER-FOCUS, SUbsystems Profile by databasE Reduction using FOCUS, an agile homology-based approach using a reduced reference database to report the subsystems present in metagenomic datasets and profile their abundances. SUPER-FOCUS was tested with over 70 real metagenomes, the results showing that it accurately predicts the subsystems present in the profiled microbial communities, and is up to 1000 times faster than other tools. SUPER-FOCUS was implemented in Python, and its source code and the tool website are freely available at https://edwards.sdsu.edu/SUPERFOCUS. redwards@mail.sdsu.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

DOE PAGES

Rosen, Gail L.; Polikar, Robi; Caseiro, Diamantino A.; ...

2011-01-01

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for theirmore » ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.« less

Metagenomics for mining new genetic resources of microbial communities.

PubMed

Ferrer, Manuel; Beloqui, Ana; Timmis, Kenneth N; Golyshin, Peter N

2009-01-01

Recent progress has revealed that the capture of genetic resources of complex microbial communities in metagenome libraries allows the discovery of a richness of new enzymatic diversity that had not previously been imagined. Activity-based screening of such libraries has demonstrated that this new diversity is not simply variations on known sequence themes, but rather the existence of entirely new sequence classes and novel functionalities. This new diversity, the surface of which has thus far only been scratched, constitutes potential for a wealth of new and improved applications in industry, medicine, agriculture, etc., and promises to facilitate in a significant manner our transition to a sustainable society, by contributing to the transition to renewable sources of energy, chemicals and materials, the lowering of pollutant burdens, lower processes energies, etc. Current bottlenecks in metagenomics include insufficient functional characterization and amplifying non-validated annotations of proteins in databases. Copyright (c) 2008 S. Karger AG, Basel.

A Statistical Framework for the Functional Analysis of Metagenomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharon, Itai; Pati, Amrita; Markowitz, Victor

2008-10-01

Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements.more » They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.« less

Diverse circovirus-like genome architectures revealed by environmental metagenomics.

PubMed

Rosario, Karyna; Duffy, Siobain; Breitbart, Mya

2009-10-01

Single-stranded DNA (ssDNA) viruses with circular genomes are the smallest viruses known to infect eukaryotes. The present study identified 10 novel genomes similar to ssDNA circoviruses through data-mining of public viral metagenomes. The metagenomic libraries included samples from reclaimed water and three different marine environments (Chesapeake Bay, British Columbia coastal waters and Sargasso Sea). All the genomes have similarities to the replication (Rep) protein of circoviruses; however, only half have genomic features consistent with known circoviruses. Some of the genomes exhibit a mixture of genomic features associated with different families of ssDNA viruses (i.e. circoviruses, geminiviruses and parvoviruses). Unique genome architectures and phylogenetic analysis of the Rep protein suggest that these viruses belong to novel genera and/or families. Investigating the complex community of ssDNA viruses in the environment can lead to the discovery of divergent species and help elucidate evolutionary links between ssDNA viruses.

Metagenomic Survey for Viruses in Western Arctic Caribou, Alaska, through Iterative Assembly of Taxonomic Units

PubMed Central

Schürch, Anita C.; Schipper, Debby; Bijl, Maarten A.; Dau, Jim; Beckmen, Kimberlee B.; Schapendonk, Claudia M. E.; Raj, V. Stalin; Osterhaus, Albert D. M. E.; Haagmans, Bart L.; Tryland, Morten; Smits, Saskia L.

2014-01-01

Pathogen surveillance in animals does not provide a sufficient level of vigilance because it is generally confined to surveillance of pathogens with known economic impact in domestic animals and practically nonexistent in wildlife species. As most (re-)emerging viral infections originate from animal sources, it is important to obtain insight into viral pathogens present in the wildlife reservoir from a public health perspective. When monitoring living, free-ranging wildlife for viruses, sample collection can be challenging and availability of nucleic acids isolated from samples is often limited. The development of viral metagenomics platforms allows a more comprehensive inventory of viruses present in wildlife. We report a metagenomic viral survey of the Western Arctic herd of barren ground caribou (Rangifer tarandus granti) in Alaska, USA. The presence of mammalian viruses in eye and nose swabs of 39 free-ranging caribou was investigated by random amplification combined with a metagenomic analysis approach that applied exhaustive iterative assembly of sequencing results to define taxonomic units of each metagenome. Through homology search methods we identified the presence of several mammalian viruses, including different papillomaviruses, a novel parvovirus, polyomavirus, and a virus that potentially represents a member of a novel genus in the family Coronaviridae. PMID:25140520

Characteristic fragment size distributions in dynamic fragmentation

NASA Astrophysics Data System (ADS)

Zhou, Fenghua; Molinari, Jean-François; Ramesh, K. T.

2006-06-01

The one-dimensional fragmentation of a dynamically expanding ring (Mott's problem) is studied numerically to obtain the fragment signatures under different strain rates. An empirical formula is proposed to calculate an average fragment size. Rayleigh distribution is found to describe the statistical properties of the fragment populations.

Improving microbial fitness in the mammalian gut by in vivo temporal functional metagenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yaung, Stephanie J.; Deng, Luxue; Li, Ning

Elucidating functions of commensal microbial genes in the mammalian gut is challenging because many commensals are recalcitrant to laboratory cultivation and genetic manipulation. We present Temporal FUnctional Metagenomics sequencing (TFUMseq), a platform to functionally mine bacterial genomes for genes that contribute to fitness of commensal bacteria in vivo. Our approach uses metagenomic DNA to construct large-scale heterologous expression libraries that are tracked over time in vivo by deep sequencing and computational methods. To demonstrate our approach, we built a TFUMseq plasmid library using the gut commensal Bacteroides thetaiotaomicron (Bt) and introduced Escherichia coli carrying this library into germfree mice. Populationmore » dynamics of library clones revealed Bt genes conferring significant fitness advantages in E. coli over time, including carbohydrate utilization genes, with a Bt galactokinase central to early colonization, and subsequent dominance by a Bt glycoside hydrolase enabling sucrose metabolism coupled with co-evolution of the plasmid library and E. coli genome driving increased galactose utilization. Here, our findings highlight the utility of functional metagenomics for engineering commensal bacteria with improved properties, including expanded colonization capabilities in vivo.« less

Improving microbial fitness in the mammalian gut by in vivo temporal functional metagenomics

DOE PAGES

Yaung, Stephanie J.; Deng, Luxue; Li, Ning; ...

2015-03-11

Elucidating functions of commensal microbial genes in the mammalian gut is challenging because many commensals are recalcitrant to laboratory cultivation and genetic manipulation. We present Temporal FUnctional Metagenomics sequencing (TFUMseq), a platform to functionally mine bacterial genomes for genes that contribute to fitness of commensal bacteria in vivo. Our approach uses metagenomic DNA to construct large-scale heterologous expression libraries that are tracked over time in vivo by deep sequencing and computational methods. To demonstrate our approach, we built a TFUMseq plasmid library using the gut commensal Bacteroides thetaiotaomicron (Bt) and introduced Escherichia coli carrying this library into germfree mice. Populationmore » dynamics of library clones revealed Bt genes conferring significant fitness advantages in E. coli over time, including carbohydrate utilization genes, with a Bt galactokinase central to early colonization, and subsequent dominance by a Bt glycoside hydrolase enabling sucrose metabolism coupled with co-evolution of the plasmid library and E. coli genome driving increased galactose utilization. Here, our findings highlight the utility of functional metagenomics for engineering commensal bacteria with improved properties, including expanded colonization capabilities in vivo.« less

MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: unraveling the sulfur cycle

PubMed Central

Zapata-Peñasco, Icoquih; Poot-Hernandez, Augusto Cesar; Eguiarte, Luis E

2017-01-01

Abstract The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large “omic” datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H΄), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to

MEBS, a software platform to evaluate large (meta)genomic collections according to their metabolic machinery: unraveling the sulfur cycle.

PubMed

De Anda, Valerie; Zapata-Peñasco, Icoquih; Poot-Hernandez, Augusto Cesar; Eguiarte, Luis E; Contreras-Moreira, Bruno; Souza, Valeria

2017-11-01

The increasing number of metagenomic and genomic sequences has dramatically improved our understanding of microbial diversity, yet our ability to infer metabolic capabilities in such datasets remains challenging. We describe the Multigenomic Entropy Based Score pipeline (MEBS), a software platform designed to evaluate, compare, and infer complex metabolic pathways in large "omic" datasets, including entire biogeochemical cycles. MEBS is open source and available through https://github.com/eead-csic-compbio/metagenome_Pfam_score. To demonstrate its use, we modeled the sulfur cycle by exhaustively curating the molecular and ecological elements involved (compounds, genes, metabolic pathways, and microbial taxa). This information was reduced to a collection of 112 characteristic Pfam protein domains and a list of complete-sequenced sulfur genomes. Using the mathematical framework of relative entropy (H΄), we quantitatively measured the enrichment of these domains among sulfur genomes. The entropy of each domain was used both to build up a final score that indicates whether a (meta)genomic sample contains the metabolic machinery of interest and to propose marker domains in metagenomic sequences such as DsrC (PF04358). MEBS was benchmarked with a dataset of 2107 non-redundant microbial genomes from RefSeq and 935 metagenomes from MG-RAST. Its performance, reproducibility, and robustness were evaluated using several approaches, including random sampling, linear regression models, receiver operator characteristic plots, and the area under the curve metric (AUC). Our results support the broad applicability of this algorithm to accurately classify (AUC = 0.985) hard-to-culture genomes (e.g., Candidatus Desulforudis audaxviator), previously characterized ones, and metagenomic environments such as hydrothermal vents, or deep-sea sediment. Our benchmark indicates that an entropy-based score can capture the metabolic machinery of interest and can be used to efficiently classify

Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life.

PubMed

Parks, Donovan H; Rinke, Christian; Chuvochina, Maria; Chaumeil, Pierre-Alain; Woodcroft, Ben J; Evans, Paul N; Hugenholtz, Philip; Tyson, Gene W

2017-11-01

Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently available microbial genomes. This is being addressed by advances in sequencing throughput and computational techniques that allow for the cultivation-independent recovery of genomes from metagenomes. Here, we report the reconstruction of 7,903 bacterial and archaeal genomes from >1,500 public metagenomes. All genomes are estimated to be ≥50% complete and nearly half are ≥90% complete with ≤5% contamination. These genomes increase the phylogenetic diversity of bacterial and archaeal genome trees by >30% and provide the first representatives of 17 bacterial and three archaeal candidate phyla. We also recovered 245 genomes from the Patescibacteria superphylum (also known as the Candidate Phyla Radiation) and find that the relative diversity of this group varies substantially with different protein marker sets. The scale and quality of this data set demonstrate that recovering genomes from metagenomes provides an expedient path forward to exploring microbial dark matter.

Metagenomic approaches to identify and isolate bioactive natural products from microbiota of marine sponges.

PubMed

Gurgui, Cristian; Piel, Jörn

2010-01-01

Many marine sponges harbor massive consortia of symbiotic bacteria belonging to diverse phyla. Sponges are also an unusually rich source of biologically active natural products, and evidence is accumulating that these compounds might often be synthesized by the symbionts. Since the study of sponge-associated bacteria is generally hampered by very low cultivation rates, cultivation-independent, metagenomic methods have recently been applied to sponges. These methods allow for the isolation of biosynthetic gene clusters that can ultimately be exploited to develop sustainable natural product sources by heterologous expression. However, general challenges encountered in sponge metagenomic research are the poor quality of the isolated DNA with respect to size and yield, the difficulty to identify genes of interest among numerous homologs, insufficient clone numbers in metagenomic libraries, and time-consuming screening procedures to identify and isolate rare positive clones. Here, we give an overview of methods that address these problems and can be used to streamline isolation of biosynthetic and other genes of interest.

GenomePeek—an online tool for prokaryotic genome and metagenome analysis

DOE PAGES

McNair, Katelyn; Edwards, Robert A.

2015-06-16

As increases in prokaryotic sequencing take place, a method to quickly and accurately analyze this data is needed. Previous tools are mainly designed for metagenomic analysis and have limitations; such as long runtimes and significant false positive error rates. The online tool GenomePeek (edwards.sdsu.edu/GenomePeek) was developed to analyze both single genome and metagenome sequencing files, quickly and with low error rates. GenomePeek uses a sequence assembly approach where reads to a set of conserved genes are extracted, assembled and then aligned against the highly specific reference database. GenomePeek was found to be faster than traditional approaches while still keeping errormore » rates low, as well as offering unique data visualization options.« less

Evaluating the metagenome of two sampling locations in the nasal cavity of cattle with bovine respiratory disease complex

USDA-ARS?s Scientific Manuscript database

Bovine respiratory disease complex (BRDC) is a multi-factor disease, and disease incidence may be associated with an animal’s commensal microbiota (metagenome). Evaluation of the animal’s resident microbiota in the nasal cavity may help us to understand the impact of the metagenome on incidence of ...

Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses.

PubMed

Hurwitz, Bonnie L; Westveld, Anton H; Brum, Jennifer R; Sullivan, Matthew B

2014-07-22

Long-standing questions in marine viral ecology are centered on understanding how viral assemblages change along gradients in space and time. However, investigating these fundamental ecological questions has been challenging due to incomplete representation of naturally occurring viral diversity in single gene- or morphology-based studies and an inability to identify up to 90% of reads in viral metagenomes (viromes). Although protein clustering techniques provide a significant advance by helping organize this unknown metagenomic sequence space, they typically use only ∼75% of the data and rely on assembly methods not yet tuned for naturally occurring sequence variation. Here, we introduce an annotation- and assembly-free strategy for comparative metagenomics that combines shared k-mer and social network analyses (regression modeling). This robust statistical framework enables visualization of complex sample networks and determination of ecological factors driving community structure. Application to 32 viromes from the Pacific Ocean Virome dataset identified clusters of samples broadly delineated by photic zone and revealed that geographic region, depth, and proximity to shore were significant predictors of community structure. Within subsets of this dataset, depth, season, and oxygen concentration were significant drivers of viral community structure at a single open ocean station, whereas variability along onshore-offshore transects was driven by oxygen concentration in an area with an oxygen minimum zone and not depth or proximity to shore, as might be expected. Together these results demonstrate that this highly scalable approach using complete metagenomic network-based comparisons can both test and generate hypotheses for ecological investigation of viral and microbial communities in nature.

Modeling ecological drivers in marine viral communities using comparative metagenomics and network analyses

PubMed Central

Hurwitz, Bonnie L.; Westveld, Anton H.; Brum, Jennifer R.; Sullivan, Matthew B.

2014-01-01

Long-standing questions in marine viral ecology are centered on understanding how viral assemblages change along gradients in space and time. However, investigating these fundamental ecological questions has been challenging due to incomplete representation of naturally occurring viral diversity in single gene- or morphology-based studies and an inability to identify up to 90% of reads in viral metagenomes (viromes). Although protein clustering techniques provide a significant advance by helping organize this unknown metagenomic sequence space, they typically use only ∼75% of the data and rely on assembly methods not yet tuned for naturally occurring sequence variation. Here, we introduce an annotation- and assembly-free strategy for comparative metagenomics that combines shared k-mer and social network analyses (regression modeling). This robust statistical framework enables visualization of complex sample networks and determination of ecological factors driving community structure. Application to 32 viromes from the Pacific Ocean Virome dataset identified clusters of samples broadly delineated by photic zone and revealed that geographic region, depth, and proximity to shore were significant predictors of community structure. Within subsets of this dataset, depth, season, and oxygen concentration were significant drivers of viral community structure at a single open ocean station, whereas variability along onshore–offshore transects was driven by oxygen concentration in an area with an oxygen minimum zone and not depth or proximity to shore, as might be expected. Together these results demonstrate that this highly scalable approach using complete metagenomic network-based comparisons can both test and generate hypotheses for ecological investigation of viral and microbial communities in nature. PMID:25002514

Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods

PubMed Central

Dröge, J.; Gregor, I.; McHardy, A. C.

2015-01-01

Motivation: Metagenomics characterizes microbial communities by random shotgun sequencing of DNA isolated directly from an environment of interest. An essential step in computational metagenome analysis is taxonomic sequence assignment, which allows identifying the sequenced community members and reconstructing taxonomic bins with sequence data for the individual taxa. For the massive datasets generated by next-generation sequencing technologies, this cannot be performed with de-novo phylogenetic inference methods. We describe an algorithm and the accompanying software, taxator-tk, which performs taxonomic sequence assignment by fast approximate determination of evolutionary neighbors from sequence similarities. Results: Taxator-tk was precise in its taxonomic assignment across all ranks and taxa for a range of evolutionary distances and for short as well as for long sequences. In addition to the taxonomic binning of metagenomes, it is well suited for profiling microbial communities from metagenome samples because it identifies bacterial, archaeal and eukaryotic community members without being affected by varying primer binding strengths, as in marker gene amplification, or copy number variations of marker genes across different taxa. Taxator-tk has an efficient, parallelized implementation that allows the assignment of 6 Gb of sequence data per day on a standard multiprocessor system with 10 CPU cores and microbial RefSeq as the genomic reference data. Availability and implementation: Taxator-tk source and binary program files are publicly available at http://algbio.cs.uni-duesseldorf.de/software/. Contact: Alice.McHardy@uni-duesseldorf.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25388150

Metagenomic Insights into the Fibrolytic Microbiome in Yak Rumen

PubMed Central

Song, Lei; Liu, Di; Liu, Li; Chen, Furong; Wang, Min; Li, Jiabao; Zeng, Xiaowei; Dong, Zhiyang; Hu, Songnian; Li, Lingyan; Xu, Jian; Huang, Li; Dong, Xiuzhu

2012-01-01

The rumen hosts one of the most efficient microbial systems for degrading plant cell walls, yet the predominant cellulolytic proteins and fibrolytic mechanism(s) remain elusive. Here we investigated the cellulolytic microbiome of the yak rumen by using a combination of metagenome-based and bacterial artificial chromosome (BAC)-based functional screening approaches. Totally 223 fibrolytic BAC clones were pyrosequenced and 10,070 ORFs were identified. Among them 150 were annotated as the glycoside hydrolase (GH) genes for fibrolytic proteins, and the majority (69%) of them were clustered or linked with genes encoding related functions. Among the 35 fibrolytic contigs of >10 Kb in length, 25 were derived from Bacteroidetes and four from Firmicutes. Coverage analysis indicated that the fibrolytic genes on most Bacteroidetes-contigs were abundantly represented in the metagenomic sequences, and they were frequently linked with genes encoding SusC/SusD-type outer-membrane proteins. GH5, GH9, and GH10 cellulase/hemicellulase genes were predominant, but no GH48 exocellulase gene was found. Most (85%) of the cellulase and hemicellulase proteins possessed a signal peptide; only a few carried carbohydrate-binding modules, and no cellulosomal domains were detected. These findings suggest that the SucC/SucD-involving mechanism, instead of one based on cellulosomes or the free-enzyme system, serves a major role in lignocellulose degradation in yak rumen. Genes encoding an endoglucanase of a novel GH5 subfamily occurred frequently in the metagenome, and the recombinant proteins encoded by the genes displayed moderate Avicelase in addition to endoglucanase activities, suggesting their important contribution to lignocellulose degradation in the exocellulase-scarce rumen. PMID:22808161

Technical Report: Benchmarking for Quasispecies Abundance Inference with Confidence Intervals from Metagenomic Sequence Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

McLoughlin, K.

2016-01-22

The software application “MetaQuant” was developed by our group at Lawrence Livermore National Laboratory (LLNL). It is designed to profile microbial populations in a sample using data from whole-genome shotgun (WGS) metagenomic DNA sequencing. Several other metagenomic profiling applications have been described in the literature. We ran a series of benchmark tests to compare the performance of MetaQuant against that of a few existing profiling tools, using real and simulated sequence datasets. This report describes our benchmarking procedure and results.

Metagenomic Analysis of the Dynamic Changes in the Gut Microbiome of the Participants of the MARS-500 Experiment, Simulating Long Term Space Flight

PubMed Central

Mardanov, A.V.; Babykin, M.M.; Beletsky, A.V.; Grigoriev, A.I.; Zinchenko, V.V.; Kadnikov, V.V.; Kirpichnikov, M.P.; Mazur, A.M.; Nedoluzhko, A.V.; Novikova, N.D.; Prokhortchouk, E.B.; Ravin, N.V.; Skryabin, K.G.; Shestakov, S.V.

2013-01-01

A metagenomic analysis of the dynamic changes of the composition of the intestinal microbiome of five participants of the MARS-500 experiment was performed. DNA samples were isolated from the feces of the participants taken just before the experiment, upon 14, 30, 210, 363 and 510 days of isolation in the experimental module, and two weeks upon completion of the experiment. The taxonomic composition of the microbiome was analyzed by pyrosequencing of 16S rRNA gene fragments. Both the taxonomic and functional gene content of the microbiome of one participant were analyzed by whole metagenome sequencing using the SOLiD technique. Each participant had a specific microbiome that could be assigned to one of three recognized enterotypes. Two participants had enterotype I microbiomes characterized by the prevalence of Bacteroides, while the microbiomes of two others, assigned to type II, were dominated by Prevotella. One participant had a microbiome of mixed type. It was found that (1) changes in the taxonimic composition of the microbiomes occurred in the course of the experiment, but the enterotypes remained the same; (2) significant changes in the compositions of the microbiomes occurred just 14-30 days after the beginning of the experiment, presumably indicating the influence of stress factors in the first stage of the experiment; (3) a tendency toward a reversion of the microbiomes to their initial composition was observed two weeks after the end of the experiment, but complete recovery was not achieved. The metagenomic analysis of the microbiome of one of the participants showed that in spite of variations in the taxonomic compositions of microbiomes, the “functional” genetic composition was much more stable for most of the functional gene categories. Probably in the course of the experiment the taxonomic composition of the gut microbiome was adaptively changed to reflect the individual response to the experimental conditions. A new, balanced taxonomic

Metagenomic Analysis of the Dynamic Changes in the Gut Microbiome of the Participants of the MARS-500 Experiment, Simulating Long Term Space Flight.

PubMed

Mardanov, A V; Babykin, M M; Beletsky, A V; Grigoriev, A I; Zinchenko, V V; Kadnikov, V V; Kirpichnikov, M P; Mazur, A M; Nedoluzhko, A V; Novikova, N D; Prokhortchouk, E B; Ravin, N V; Skryabin, K G; Shestakov, S V

2013-07-01

A metagenomic analysis of the dynamic changes of the composition of the intestinal microbiome of five participants of the MARS-500 experiment was performed. DNA samples were isolated from the feces of the participants taken just before the experiment, upon 14, 30, 210, 363 and 510 days of isolation in the experimental module, and two weeks upon completion of the experiment. The taxonomic composition of the microbiome was analyzed by pyrosequencing of 16S rRNA gene fragments. Both the taxonomic and functional gene content of the microbiome of one participant were analyzed by whole metagenome sequencing using the SOLiD technique. Each participant had a specific microbiome that could be assigned to one of three recognized enterotypes. Two participants had enterotype I microbiomes characterized by the prevalence of Bacteroides, while the microbiomes of two others, assigned to type II, were dominated by Prevotella. One participant had a microbiome of mixed type. It was found that (1) changes in the taxonimic composition of the microbiomes occurred in the course of the experiment, but the enterotypes remained the same; (2) significant changes in the compositions of the microbiomes occurred just 14-30 days after the beginning of the experiment, presumably indicating the influence of stress factors in the first stage of the experiment; (3) a tendency toward a reversion of the microbiomes to their initial composition was observed two weeks after the end of the experiment, but complete recovery was not achieved. The metagenomic analysis of the microbiome of one of the participants showed that in spite of variations in the taxonomic compositions of microbiomes, the "functional" genetic composition was much more stable for most of the functional gene categories. Probably in the course of the experiment the taxonomic composition of the gut microbiome was adaptively changed to reflect the individual response to the experimental conditions. A new, balanced taxonomic composition

THE WESTERN LAKE SUPERIOR COMPARATIVE WATERSHED FRAMEWORK: A FIELD TEST OF GEOGRAPHICALLY-DEPENDENT VS. THRESHOLD-BASED GEOGRAPHICALLY-INDEPENDENT CLASSIFICATION

EPA Science Inventory

Stratified random selection of watersheds allowed us to compare geographically-independent classification schemes based on watershed storage (wetland + lake area/watershed area) and forest fragmentation with a geographically-based classification scheme within the Northern Lakes a...

Cloning and characterization of a novel α-amylase from a fecal microbial metagenome.

PubMed

Xu, Bo; Yang, Fuya; Xiong, Caiyun; Li, Junjun; Tang, Xianghua; Zhou, Junpei; Xie, Zhenrong; Ding, Junmei; Yang, Yunjuan; Huang, Zunxi

2014-04-01

To isolate novel and useful microbial enzymes from uncultured gastrointestinal microorganisms, a fecal microbial metagenomic library of the pygmy loris was constructed. The library was screened for amylolytic activity, and 8 of 50,000 recombinant clones showed amylolytic activity. Subcloning and sequence analysis of a positive clone led to the identification a novel gene (amyPL) coding for α-amylase. AmyPL was expressed in Escherichia coli BL21 (DE3) and the purified AmyPL was enzymatically characterized. This study is the first to report the molecular and biochemical characterization of a novel α-amylase from a gastrointestinal metagenomic library.

Electron Microprobe Analyses of Lithic Fragments and Their Minerals from Luna 20 Fines

NASA Technical Reports Server (NTRS)

Conrad, G. H.; Hlava, P. F.; Green, J. A.; Moore, R. B.; Moreland, G.; Dowty, E.; Prinz, M.; Keil, K.; Nehru, C. E.; Bunch, T. E.

1973-01-01

The bulk analyses (determined with the broad beam electron microprobe technique) of lithic fragments are given in weight percentages and are arranged according to the rock classification. Within each rock group the analyses are arranged in order of increasing FeO content. Thin section and lithic fragment numbers are given at the top of each column of analysis and correspond to the numbers recorded on photo mosaics on file in the Institute of Meteoritics. CIPW molecular norms are given for each analysis. Electron microprobe mineral analyses (given in oxide weight percentages), structural formulae and molecular end member values are presented for plagioclase, olivine, pyroxene and K-feldspar. The minerals are selected mostly from lithic fragments that were also analyzed for bulk composition. Within each mineral group the analyses are presented according to the section number and lithic fragment number. Within each lithic fragment the mineral analyses are arranged as follows: Plagioclase in order of increasing CaO; olivine and pyroexene in order of increasing FeO; and K-feldspar in order of increasing K2O. The mineral grains are identified at the top of each column of analysis by grain number and lithic fragment number.

Metagenomic investigation of the microbial diversity in a chrysotile asbestos mine pit pond, Lowell, Vermont, USA.

PubMed

Driscoll, Heather E; Vincent, James J; English, Erika L; Dolci, Elizabeth D

2016-12-01

Here we report on a metagenomics investigation of the microbial diversity in a serpentine-hosted aquatic habitat created by chrysotile asbestos mining activity at the Vermont Asbestos Group (VAG) Mine in northern Vermont, USA. The now-abandoned VAG Mine on Belvidere Mountain in the towns of Eden and Lowell includes three open-pit quarries, a flooded pit, mill buildings, roads, and > 26 million metric tons of eroding mine waste that contribute alkaline mine drainage to the surrounding watershed. Metagenomes and water chemistry originated from aquatic samples taken at three depths (0.5 m, 3.5 m, and 25 m) along the water column at three distinct, offshore sites within the mine's flooded pit (near 44°46'00.7673″, - 72°31'36.2699″; UTM NAD 83 Zone 18 T 0695720 E, 4960030 N). Whole metagenome shotgun Illumina paired-end sequences were quality trimmed and analyzed based on a translated nucleotide search of NCBI-NR protein database and lowest common ancestor taxonomic assignments. Our results show strata within the pit pond water column can be distinguished by taxonomic composition and distribution, pH, temperature, conductivity, light intensity, and concentrations of dissolved oxygen. At the phylum level, metagenomes from 0.5 m and 3.5 m contained a similar distribution of taxa and were dominated by Actinobacteria (46% and 53% of reads, respectively), Proteobacteria (45% and 38%, respectively), and Bacteroidetes (7% in both). The metagenomes from 25 m showed a greater diversity of phyla and a different distribution of reads than the two upper strata: Proteobacteria (60%), Actinobacteria (18%), Planctomycetes, (10%), Bacteroidetes (5%) and Cyanobacteria (2.5%), Armatimonadetes (< 1%), Verrucomicrobia (< 1%), Firmicutes (< 1%), and Nitrospirae (< 1%). Raw metagenome sequence data from each sample reside in NCBI's Short Read Archive (SRA ID: SRP056095) and are accessible through NCBI BioProject PRJNA277916.

Making a living while starving in the dark: metagenomic insights into the energy dynamics of a carbonate cave.

PubMed

Ortiz, Marianyoly; Legatzki, Antje; Neilson, Julia W; Fryslie, Brandon; Nelson, William M; Wing, Rod A; Soderlund, Carol A; Pryor, Barry M; Maier, Raina M

2014-02-01

Carbonate caves represent subterranean ecosystems that are largely devoid of phototrophic primary production. In semiarid and arid regions, allochthonous organic carbon inputs entering caves with vadose-zone drip water are minimal, creating highly oligotrophic conditions; however, past research indicates that carbonate speleothem surfaces in these caves support diverse, predominantly heterotrophic prokaryotic communities. The current study applied a metagenomic approach to elucidate the community structure and potential energy dynamics of microbial communities, colonizing speleothem surfaces in Kartchner Caverns, a carbonate cave in semiarid, southeastern Arizona, USA. Manual inspection of a speleothem metagenome revealed a community genetically adapted to low-nutrient conditions with indications that a nitrogen-based primary production strategy is probable, including contributions from both Archaea and Bacteria. Genes for all six known CO2-fixation pathways were detected in the metagenome and RuBisCo genes representative of the Calvin-Benson-Bassham cycle were over-represented in Kartchner speleothem metagenomes relative to bulk soil, rhizosphere soil and deep-ocean communities. Intriguingly, quantitative PCR found Archaea to be significantly more abundant in the cave communities than in soils above the cave. MEtaGenome ANalyzer (MEGAN) analysis of speleothem metagenome sequence reads found Thaumarchaeota to be the third most abundant phylum in the community, and identified taxonomic associations to this phylum for indicator genes representative of multiple CO2-fixation pathways. The results revealed that this oligotrophic subterranean environment supports a unique chemoautotrophic microbial community with potentially novel nutrient cycling strategies. These strategies may provide key insights into other ecosystems dominated by oligotrophy, including aphotic subsurface soils or aquifers and photic systems such as arid deserts.

The GAAS metagenomic tool and its estimations of viral and microbial average genome size in four major biomes.

PubMed

Angly, Florent E; Willner, Dana; Prieto-Davó, Alejandra; Edwards, Robert A; Schmieder, Robert; Vega-Thurber, Rebecca; Antonopoulos, Dionysios A; Barott, Katie; Cottrell, Matthew T; Desnues, Christelle; Dinsdale, Elizabeth A; Furlan, Mike; Haynes, Matthew; Henn, Matthew R; Hu, Yongfei; Kirchman, David L; McDole, Tracey; McPherson, John D; Meyer, Folker; Miller, R Michael; Mundt, Egbert; Naviaux, Robert K; Rodriguez-Mueller, Beltran; Stevens, Rick; Wegley, Linda; Zhang, Lixin; Zhu, Baoli; Rohwer, Forest

2009-12-01

Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions.

Genetic and functional properties of uncultivated thermophilic crenarchaeotes from a subsurface gold mine as revealed by analysis of genome fragments.

PubMed

Nunoura, Takuro; Hirayama, Hisako; Takami, Hideto; Oida, Hanako; Nishi, Shinro; Shimamura, Shigeru; Suzuki, Yohey; Inagaki, Fumio; Takai, Ken; Nealson, Kenneth H; Horikoshi, Koki

2005-12-01

Within a phylum Crenarchaeota, only some members of the hyperthermophilic class Thermoprotei, have been cultivated and characterized. In this study, we have constructed a metagenomic library from a microbial mat formation in a subsurface hot water stream of the Hishikari gold mine, Japan, and sequenced genome fragments of two different phylogroups of uncultivated thermophilic Crenarchaeota: (i) hot water crenarchaeotic group (HWCG) I (41.2 kb), and (ii) HWCG III (49.3 kb). The genome fragment of HWCG I contained a 16S rRNA gene, two tRNA genes and 35 genes encoding proteins but no 23S rRNA gene. Among the genes encoding proteins, several genes for putative aerobic-type carbon monoxide dehydrogenase represented a potential clue with regard to the yet unknown metabolism of HWCG I Archaea. The genome fragment of HWCG III contained a 16S/23S rRNA operon and 44 genes encoding proteins. In the 23S rRNA gene, we detected a homing-endonuclease encoding a group I intron similar to those detected in hyperthermophilic Crenarchaeota and Bacteria, as well as eukaryotic organelles. The reconstructed phylogenetic tree based on the 23S rRNA gene sequence reinforced the intermediate phylogenetic affiliation of HWCG III bridging the hyperthermophilic and non-thermophilic uncultivated Crenarchaeota.

Comparison of normalization methods for the analysis of metagenomic gene abundance data.

PubMed

Pereira, Mariana Buongermino; Wallroth, Mikael; Jonsson, Viktor; Kristiansson, Erik

2018-04-20

In shotgun metagenomics, microbial communities are studied through direct sequencing of DNA without any prior cultivation. By comparing gene abundances estimated from the generated sequencing reads, functional differences between the communities can be identified. However, gene abundance data is affected by high levels of systematic variability, which can greatly reduce the statistical power and introduce false positives. Normalization, which is the process where systematic variability is identified and removed, is therefore a vital part of the data analysis. A wide range of normalization methods for high-dimensional count data has been proposed but their performance on the analysis of shotgun metagenomic data has not been evaluated. Here, we present a systematic evaluation of nine normalization methods for gene abundance data. The methods were evaluated through resampling of three comprehensive datasets, creating a realistic setting that preserved the unique characteristics of metagenomic data. Performance was measured in terms of the methods ability to identify differentially abundant genes (DAGs), correctly calculate unbiased p-values and control the false discovery rate (FDR). Our results showed that the choice of normalization method has a large impact on the end results. When the DAGs were asymmetrically present between the experimental conditions, many normalization methods had a reduced true positive rate (TPR) and a high false positive rate (FPR). The methods trimmed mean of M-values (TMM) and relative log expression (RLE) had the overall highest performance and are therefore recommended for the analysis of gene abundance data. For larger sample sizes, CSS also showed satisfactory performance. This study emphasizes the importance of selecting a suitable normalization methods in the analysis of data from shotgun metagenomics. Our results also demonstrate that improper methods may result in unacceptably high levels of false positives, which in turn may lead

Evaluation method for the potential functionome harbored in the genome and metagenome

PubMed Central

2012-01-01

Background One of the main goals of genomic analysis is to elucidate the comprehensive functions (functionome) in individual organisms or a whole community in various environments. However, a standard evaluation method for discerning the functional potentials harbored within the genome or metagenome has not yet been established. We have developed a new evaluation method for the potential functionome, based on the completion ratio of Kyoto Encyclopedia of Genes and Genomes (KEGG) functional modules. Results Distribution of the completion ratio of the KEGG functional modules in 768 prokaryotic species varied greatly with the kind of module, and all modules primarily fell into 4 patterns (universal, restricted, diversified and non-prokaryotic modules), indicating the universal and unique nature of each module, and also the versatility of the KEGG Orthology (KO) identifiers mapped to each one. The module completion ratio in 8 phenotypically different bacilli revealed that some modules were shared only in phenotypically similar species. Metagenomes of human gut microbiomes from 13 healthy individuals previously determined by the Sanger method were analyzed based on the module completion ratio. Results led to new discoveries in the nutritional preferences of gut microbes, believed to be one of the mutualistic representations of gut microbiomes to avoid nutritional competition with the host. Conclusions The method developed in this study could characterize the functionome harbored in genomes and metagenomes. As this method also provided taxonomical information from KEGG modules as well as the gene hosts constructing the modules, interpretation of completion profiles was simplified and we could identify the complementarity between biochemical functions in human hosts and the nutritional preferences in human gut microbiomes. Thus, our method has the potential to be a powerful tool for comparative functional analysis in genomics and metagenomics, able to target unknown

Shotgun Pyrosequencing Metagenomic Analyses of Dusts from Swine Confinement and Grain Facilities

PubMed Central

Boissy, Robert J.; Romberger, Debra J.; Roughead, William A.; Weissenburger-Moser, Lisa; Poole, Jill A.; LeVan, Tricia D.

2014-01-01

Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70%) at the phylum level, Clostridia (44%) at the Class level, and Clostridiales at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses

Evaluation method for the potential functionome harbored in the genome and metagenome.

PubMed

Takami, Hideto; Taniguchi, Takeaki; Moriya, Yuki; Kuwahara, Tomomi; Kanehisa, Minoru; Goto, Susumu

2012-12-12

One of the main goals of genomic analysis is to elucidate the comprehensive functions (functionome) in individual organisms or a whole community in various environments. However, a standard evaluation method for discerning the functional potentials harbored within the genome or metagenome has not yet been established. We have developed a new evaluation method for the potential functionome, based on the completion ratio of Kyoto Encyclopedia of Genes and Genomes (KEGG) functional modules. Distribution of the completion ratio of the KEGG functional modules in 768 prokaryotic species varied greatly with the kind of module, and all modules primarily fell into 4 patterns (universal, restricted, diversified and non-prokaryotic modules), indicating the universal and unique nature of each module, and also the versatility of the KEGG Orthology (KO) identifiers mapped to each one. The module completion ratio in 8 phenotypically different bacilli revealed that some modules were shared only in phenotypically similar species. Metagenomes of human gut microbiomes from 13 healthy individuals previously determined by the Sanger method were analyzed based on the module completion ratio. Results led to new discoveries in the nutritional preferences of gut microbes, believed to be one of the mutualistic representations of gut microbiomes to avoid nutritional competition with the host. The method developed in this study could characterize the functionome harbored in genomes and metagenomes. As this method also provided taxonomical information from KEGG modules as well as the gene hosts constructing the modules, interpretation of completion profiles was simplified and we could identify the complementarity between biochemical functions in human hosts and the nutritional preferences in human gut microbiomes. Thus, our method has the potential to be a powerful tool for comparative functional analysis in genomics and metagenomics, able to target unknown environments containing various

Shotgun pyrosequencing metagenomic analyses of dusts from swine confinement and grain facilities.

PubMed

Boissy, Robert J; Romberger, Debra J; Roughead, William A; Weissenburger-Moser, Lisa; Poole, Jill A; LeVan, Tricia D

2014-01-01

Inhalation of agricultural dusts causes inflammatory reactions and symptoms such as headache, fever, and malaise, which can progress to chronic airway inflammation and associated diseases, e.g. asthma, chronic bronchitis, chronic obstructive pulmonary disease, and hypersensitivity pneumonitis. Although in many agricultural environments feed particles are the major constituent of these dusts, the inflammatory responses that they provoke are likely attributable to particle-associated bacteria, archaebacteria, fungi, and viruses. In this study, we performed shotgun pyrosequencing metagenomic analyses of DNA from dusts from swine confinement facilities or grain elevators, with comparisons to dusts from pet-free households. DNA sequence alignment showed that 19% or 62% of shotgun pyrosequencing metagenomic DNA sequence reads from swine facility or household dusts, respectively, were of swine or human origin, respectively. In contrast only 2% of such reads from grain elevator dust were of mammalian origin. These metagenomic shotgun reads of mammalian origin were excluded from our analyses of agricultural dust microbiota. The ten most prevalent bacterial taxa identified in swine facility compared to grain elevator or household dust were comprised of 75%, 16%, and 42% gram-positive organisms, respectively. Four of the top five swine facility dust genera were assignable (Clostridium, Lactobacillus, Ruminococcus, and Eubacterium, ranging from 4% to 19% relative abundance). The relative abundances of these four genera were lower in dust from grain elevators or pet-free households. These analyses also highlighted the predominance in swine facility dust of Firmicutes (70%) at the phylum level, Clostridia (44%) at the Class level, and Clostridiales at the Order level (41%). In summary, shotgun pyrosequencing metagenomic analyses of agricultural dusts show that they differ qualitatively and quantitatively at the level of microbial taxa present, and that the bioinformatic analyses

Identifying personal microbiomes using metagenomic codes

PubMed Central

Franzosa, Eric A.; Huang, Katherine; Meadow, James F.; Gevers, Dirk; Lemon, Katherine P.; Bohannan, Brendan J. M.; Huttenhower, Curtis

2015-01-01

Community composition within the human microbiome varies across individuals, but it remains unknown if this variation is sufficient to uniquely identify individuals within large populations or stable enough to identify them over time. We investigated this by developing a hitting set-based coding algorithm and applying it to the Human Microbiome Project population. Our approach defined body site-specific metagenomic codes: sets of microbial taxa or genes prioritized to uniquely and stably identify individuals. Codes capturing strain variation in clade-specific marker genes were able to distinguish among 100s of individuals at an initial sampling time point. In comparisons with follow-up samples collected 30–300 d later, ∼30% of individuals could still be uniquely pinpointed using metagenomic codes from a typical body site; coincidental (false positive) matches were rare. Codes based on the gut microbiome were exceptionally stable and pinpointed >80% of individuals. The failure of a code to match its owner at a later time point was largely explained by the loss of specific microbial strains (at current limits of detection) and was only weakly associated with the length of the sampling interval. In addition to highlighting patterns of temporal variation in the ecology of the human microbiome, this work demonstrates the feasibility of microbiome-based identifiability—a result with important ethical implications for microbiome study design. The datasets and code used in this work are available for download from huttenhower.sph.harvard.edu/idability. PMID:25964341

Insights into resistome and stress responses genes in Bubalus bubalis rumen through metagenomic analysis.

PubMed

Reddy, Bhaskar; Singh, Krishna M; Patel, Amrutlal K; Antony, Ancy; Panchasara, Harshad J; Joshi, Chaitanya G

2014-10-01

Buffalo rumen microbiota experience variety of diets and represents a huge reservoir of mobilome, resistome and stress responses. However, knowledge of metagenomic responses to such conditions is still rudimentary. We analyzed the metagenomes of buffalo rumen in the liquid and solid phase of the rumen biomaterial from river buffalo adapted to varying proportion of concentrate to green or dry roughages, using high-throughput sequencing to know the occurrence of antibiotics resistance genes, genetic exchange between bacterial population and environmental reservoirs. A total of 3914.94 MB data were generated from all three treatments group. The data were analysed with Metagenome rapid annotation system tools. At phyla level, Bacteroidetes were dominant in all the treatments followed by Firmicutes. Genes coding for functional responses to stress (oxidative stress and heat shock proteins) and resistome genes (resistance to antibiotics and toxic compounds, phages, transposable elements and pathogenicity islands) were prevalent in similar proportion in liquid and solid fraction of rumen metagenomes. The fluoroquinolone resistance, MDR efflux pumps and Methicillin resistance genes were broadly distributed across 11, 9, and 14 bacterial classes, respectively. Bacteria responsible for phages replication and prophages and phage packaging and rlt-like streptococcal phage genes were mostly assigned to phyla Bacteroides, Firmicutes and proteaobacteria. Also, more reads matching the sigma B genes were identified in the buffalo rumen. This study underscores the presence of diverse mechanisms of adaptation to different diet, antibiotics and other stresses in buffalo rumen, reflecting the proportional representation of major bacterial groups.

Marine metagenomics: strategies for the discovery of novel enzymes with biotechnological applications from marine environments

PubMed Central

Kennedy, Jonathan; Marchesi, Julian R; Dobson, Alan DW

2008-01-01

Metagenomic based strategies have previously been successfully employed as powerful tools to isolate and identify enzymes with novel biocatalytic activities from the unculturable component of microbial communities from various terrestrial environmental niches. Both sequence based and function based screening approaches have been employed to identify genes encoding novel biocatalytic activities and metabolic pathways from metagenomic libraries. While much of the focus to date has centred on terrestrial based microbial ecosystems, it is clear that the marine environment has enormous microbial biodiversity that remains largely unstudied. Marine microbes are both extremely abundant and diverse; the environments they occupy likewise consist of very diverse niches. As culture-dependent methods have thus far resulted in the isolation of only a tiny percentage of the marine microbiota the application of metagenomic strategies holds great potential to study and exploit the enormous microbial biodiversity which is present within these marine environments. PMID:18717988

Metagenomic analyses of bacteria on human hairs: a qualitative assessment for applications in forensic science.

PubMed

Tridico, Silvana R; Murray, Dáithí C; Addison, Jayne; Kirkbride, Kenneth P; Bunce, Michael

2014-01-01

Mammalian hairs are one of the most ubiquitous types of trace evidence collected in the course of forensic investigations. However, hairs that are naturally shed or that lack roots are problematic substrates for DNA profiling; these hair types often contain insufficient nuclear DNA to yield short tandem repeat (STR) profiles. Whilst there have been a number of initial investigations evaluating the value of metagenomics analyses for forensic applications (e.g. examination of computer keyboards), there have been no metagenomic evaluations of human hairs-a substrate commonly encountered during forensic practice. This present study attempts to address this forensic capability gap, by conducting a qualitative assessment into the applicability of metagenomic analyses of human scalp and pubic hair. Forty-two DNA extracts obtained from human scalp and pubic hairs generated a total of 79,766 reads, yielding 39,814 reads post control and abundance filtering. The results revealed the presence of unique combinations of microbial taxa that can enable discrimination between individuals and signature taxa indigenous to female pubic hairs. Microbial data from a single co-habiting couple added an extra dimension to the study by suggesting that metagenomic analyses might be of evidentiary value in sexual assault cases when other associative evidence is not present. Of all the data generated in this study, the next-generation sequencing (NGS) data generated from pubic hair held the most potential for forensic applications. Metagenomic analyses of human hairs may provide independent data to augment other forensic results and possibly provide association between victims of sexual assault and offender when other associative evidence is absent. Based on results garnered in the present study, we believe that with further development, bacterial profiling of hair will become a valuable addition to the forensic toolkit.

Statistical Methods for Detecting Differentially Abundant Features in Clinical Metagenomic Samples

PubMed Central

White, James Robert; Nagarajan, Niranjan; Pop, Mihai

2009-01-01

Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them. We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied

High yield of functional metagenomic library from mangroves constructed in fosmid vector.

PubMed

Gonçalves, A C S; dos Santos, A C F; dos Santos, T F; Pessoa, T B A; Dias, J C T; Rezende, R P

2015-10-02

In the present study, metagenomic technique and fosmid vectors were used to construct a library of clones for exploring the biotechnological potential of mangrove soils by isolation of functional genes encoding hydrolytic enzymes. The library was built with genomic DNA from the soil samples of mangrove sediments and the functional screening of 1824 clones (~64 Mbp) was performed to detect the hydrolytic activity specific for cellulases, amylases (at acidic, neutral and basic pH), lipases/esterases, proteases, and nitrilases. Significant numbers of clones, positive for the tested enzyme activities were obtained. Our results indicate the importance and biotechnological potential of mangrove soils especially when compared to those obtained using other soil metagenomic libraries.

Oral Metagenomic Biomarkers in Rheumatoid Arthritis

DTIC Science & Technology

2016-09-01

AWARD NUMBER: W81XWH-15-1-0320 TITLE: Oral Metagenomic Biomarkers in Rheumatoid Arthritis PRINCIPAL INVESTIGATOR: Edward K Chan CONTRACTING...Biomarkers in Rheumatoid Arthritis 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-15-1-0320 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Edward K Chan 5d...significant difference in the oral  microbiome at the subspecies level of individuals with  rheumatoid   arthritis  (RA). The goal is to test the

A metagenomic framework for the study of airborne microbial communities.

PubMed

Yooseph, Shibu; Andrews-Pfannkoch, Cynthia; Tenney, Aaron; McQuaid, Jeff; Williamson, Shannon; Thiagarajan, Mathangi; Brami, Daniel; Zeigler-Allen, Lisa; Hoffman, Jeff; Goll, Johannes B; Fadrosh, Douglas; Glass, John; Adams, Mark D; Friedman, Robert; Venter, J Craig

2013-01-01

Understanding the microbial content of the air has important scientific, health, and economic implications. While studies have primarily characterized the taxonomic content of air samples by sequencing the 16S or 18S ribosomal RNA gene, direct analysis of the genomic content of airborne microorganisms has not been possible due to the extremely low density of biological material in airborne environments. We developed sampling and amplification methods to enable adequate DNA recovery to allow metagenomic profiling of air samples collected from indoor and outdoor environments. Air samples were collected from a large urban building, a medical center, a house, and a pier. Analyses of metagenomic data generated from these samples reveal airborne communities with a high degree of diversity and different genera abundance profiles. The identities of many of the taxonomic groups and protein families also allows for the identification of the likely sources of the sampled airborne bacteria.

A Metagenomic Framework for the Study of Airborne Microbial Communities

PubMed Central

Tenney, Aaron; McQuaid, Jeff; Williamson, Shannon; Thiagarajan, Mathangi; Brami, Daniel; Zeigler-Allen, Lisa; Hoffman, Jeff; Goll, Johannes B.; Fadrosh, Douglas; Glass, John; Adams, Mark D.; Friedman, Robert; Venter, J. Craig

2013-01-01

Understanding the microbial content of the air has important scientific, health, and economic implications. While studies have primarily characterized the taxonomic content of air samples by sequencing the 16S or 18S ribosomal RNA gene, direct analysis of the genomic content of airborne microorganisms has not been possible due to the extremely low density of biological material in airborne environments. We developed sampling and amplification methods to enable adequate DNA recovery to allow metagenomic profiling of air samples collected from indoor and outdoor environments. Air samples were collected from a large urban building, a medical center, a house, and a pier. Analyses of metagenomic data generated from these samples reveal airborne communities with a high degree of diversity and different genera abundance profiles. The identities of many of the taxonomic groups and protein families also allows for the identification of the likely sources of the sampled airborne bacteria. PMID:24349140

Fragment-based lead generation: identification of seed fragments by a highly efficient fragment screening technology

NASA Astrophysics Data System (ADS)

Neumann, Lars; Ritscher, Allegra; Müller, Gerhard; Hafenbradl, Doris

2009-08-01

For the detection of the precise and unambiguous binding of fragments to a specific binding site on the target protein, we have developed a novel reporter displacement binding assay technology. The application of this technology for the fragment screening as well as the fragment evolution process with a specific modelling based design strategy is demonstrated for inhibitors of the protein kinase p38alpha. In a fragment screening approach seed fragments were identified which were then used to build compounds from the deep-pocket towards the hinge binding area of the protein kinase p38alpha based on a modelling approach. BIRB796 was used as a blueprint for the alignment of the fragments. The fragment evolution of these deep-pocket binding fragments towards the fully optimized inhibitor BIRB796 included the modulation of the residence time as well as the affinity. The goal of our study was to evaluate the robustness and efficiency of our novel fragment screening technology at high fragment concentrations, compare the screening data with biochemical activity data and to demonstrate the evolution of the hit fragments with fast kinetics, into slow kinetic inhibitors in an in silico approach.

Metagenomic analysis reveals a green sulfur bacterium as a potential coral symbiont.

PubMed

Cai, Lin; Zhou, Guowei; Tian, Ren-Mao; Tong, Haoya; Zhang, Weipeng; Sun, Jin; Ding, Wei; Wong, Yue Him; Xie, James Y; Qiu, Jian-Wen; Liu, Sheng; Huang, Hui; Qian, Pei-Yuan

2017-08-24

Coral reefs are ecologically significant habitats. Coral-algal symbiosis confers ecological success on coral reefs and coral-microbial symbiosis is also vital to coral reefs. However, current understanding of coral-microbial symbiosis on a genomic scale is largely unknown. Here we report a potential microbial symbiont in corals revealed by metagenomics-based genomic study. Microbial cells in coral were enriched for metagenomic analysis and a high-quality draft genome of "Candidatus Prosthecochloris korallensis" was recovered by metagenome assembly and genome binning. Phylogenetic analysis shows "Ca. P. korallensis" belongs to the Prosthecochloris clade and is clustered with two Prosthecochloris clones derived from Caribbean corals. Genomic analysis reveals "Ca. P. korallensis" has potentially important ecological functions including anoxygenic photosynthesis, carbon fixation via the reductive tricarboxylic acid (rTCA) cycle, nitrogen fixation, and sulfur oxidization. Core metabolic pathway analysis suggests "Ca. P. korallensis" is a green sulfur bacterium capable of photoautotrophy or mixotrophy. Potential host-microbial interaction reveals a symbiotic relationship: "Ca. P. korallensis" might provide organic and nitrogenous nutrients to its host and detoxify sulfide for the host; the host might provide "Ca. P. korallensis" with an anaerobic environment for survival, carbon dioxide and acetate for growth, and hydrogen sulfide as an electron donor for photosynthesis.

Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition

PubMed Central

Saeed, Isaam; Tang, Sen-Lin; Halgamuge, Saman K.

2012-01-01

An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis. PMID:22180538

A metagenomic window into carbon metabolism at 3 km depth in Precambrian continental crust

PubMed Central

Magnabosco, Cara; Ryan, Kathleen; Lau, Maggie C Y; Kuloyo, Olukayode; Sherwood Lollar, Barbara; Kieft, Thomas L; van Heerden, Esta; Onstott, Tullis C

2016-01-01

Subsurface microbial communities comprise a significant fraction of the global prokaryotic biomass; however, the carbon metabolisms that support the deep biosphere have been relatively unexplored. In order to determine the predominant carbon metabolisms within a 3-km deep fracture fluid system accessed via the Tau Tona gold mine (Witwatersrand Basin, South Africa), metagenomic and thermodynamic analyses were combined. Within our system of study, the energy-conserving reductive acetyl-CoA (Wood-Ljungdahl) pathway was found to be the most abundant carbon fixation pathway identified in the metagenome. Carbon monoxide dehydrogenase genes that have the potential to participate in (1) both autotrophic and heterotrophic metabolisms through the reversible oxidization of CO and subsequent transfer of electrons for sulfate reduction, (2) direct utilization of H2 and (3) methanogenesis were identified. The most abundant members of the metagenome belonged to Euryarchaeota (22%) and Firmicutes (57%)—by far, the highest relative abundance of Euryarchaeota yet reported from deep fracture fluids in South Africa and one of only five Firmicutes-dominated deep fracture fluids identified in the region. Importantly, by combining the metagenomics data and thermodynamic modeling of this study with previously published isotopic and community composition data from the South African subsurface, we are able to demonstrate that Firmicutes-dominated communities are associated with a particular hydrogeologic environment, specifically the older, more saline and more reducing waters. PMID:26325359

Molecular Diagnosis of Orthopedic-Device-Related Infection Directly from Sonication Fluid by Metagenomic Sequencing

PubMed Central

Sanderson, Nicholas D.; Atkins, Bridget L.; Brent, Andrew J.; Cole, Kevin; Foster, Dona; McNally, Martin A.; Oakley, Sarah; Peto, Leon; Taylor, Adrian; Peto, Tim E. A.; Crook, Derrick W.; Eyre, David W.

2017-01-01

ABSTRACT Culture of multiple periprosthetic tissue samples is the current gold standard for microbiological diagnosis of prosthetic joint infections (PJI). Additional diagnostic information may be obtained through culture of sonication fluid from explants. However, current techniques can have relatively low sensitivity, with prior antimicrobial therapy and infection by fastidious organisms influencing results. We assessed if metagenomic sequencing of total DNA extracts obtained direct from sonication fluid can provide an alternative rapid and sensitive tool for diagnosis of PJI. We compared metagenomic sequencing with standard aerobic and anaerobic culture in 97 sonication fluid samples from prosthetic joint and other orthopedic device infections. Reads from Illumina MiSeq sequencing were taxonomically classified using Kraken. Using 50 derivation samples, we determined optimal thresholds for the number and proportion of bacterial reads required to identify an infection and confirmed our findings in 47 independent validation samples. Compared to results from sonication fluid culture, the species-level sensitivity of metagenomic sequencing was 61/69 (88%; 95% confidence interval [CI], 77 to 94%; for derivation samples 35/38 [92%; 95% CI, 79 to 98%]; for validation samples, 26/31 [84%; 95% CI, 66 to 95%]), and genus-level sensitivity was 64/69 (93%; 95% CI, 84 to 98%). Species-level specificity, adjusting for plausible fastidious causes of infection, species found in concurrently obtained tissue samples, and prior antibiotics, was 85/97 (88%; 95% CI, 79 to 93%; for derivation samples, 43/50 [86%; 95% CI, 73 to 94%]; for validation samples, 42/47 [89%; 95% CI, 77 to 96%]). High levels of human DNA contamination were seen despite the use of laboratory methods to remove it. Rigorous laboratory good practice was required to minimize bacterial DNA contamination. We demonstrate that metagenomic sequencing can provide accurate diagnostic information in PJI. Our findings

Single sample resolution of rare microbial dark matter in a marine invertebrate metagenome

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, Ian J.; Weyna, Theodore R.; Fong, Stephen S.

Direct, untargeted sequencing of environmental samples (metagenomics) and de novo genome assembly enable the study of uncultured and phylogenetically divergent organisms. However, separating individual genomes from a mixed community has often relied on the differential-coverage analysis of multiple, deeply sequenced samples. In the metagenomic investigation of the marine bryozoan Bugula neritina, we uncovered seven bacterial genomes associated with a single B. neritina individual that appeared to be transient associates, two of which were unique to one individual and undetectable using certain “universal” 16S rRNA primers and probes. We recovered high quality genome assemblies for several rare instances of “microbial darkmore » matter,” or phylogenetically divergent bacteria lacking genomes in reference databases, from a single tissue sample that was not subjected to any physical or chemical pre-treatment. One of these rare, divergent organisms has a small (593 kbp), poorly annotated genome with low GC content (20.9%) and a 16S rRNA gene with just 65% sequence similarity to the closest reference sequence. Lastly, our findings illustrate the importance of sampling strategy and de novo assembly of metagenomic reads to understand the extent and function of bacterial biodiversity.« less

Single sample resolution of rare microbial dark matter in a marine invertebrate metagenome

DOE PAGES

Miller, Ian J.; Weyna, Theodore R.; Fong, Stephen S.; ...

2016-09-29

Direct, untargeted sequencing of environmental samples (metagenomics) and de novo genome assembly enable the study of uncultured and phylogenetically divergent organisms. However, separating individual genomes from a mixed community has often relied on the differential-coverage analysis of multiple, deeply sequenced samples. In the metagenomic investigation of the marine bryozoan Bugula neritina, we uncovered seven bacterial genomes associated with a single B. neritina individual that appeared to be transient associates, two of which were unique to one individual and undetectable using certain “universal” 16S rRNA primers and probes. We recovered high quality genome assemblies for several rare instances of “microbial darkmore » matter,” or phylogenetically divergent bacteria lacking genomes in reference databases, from a single tissue sample that was not subjected to any physical or chemical pre-treatment. One of these rare, divergent organisms has a small (593 kbp), poorly annotated genome with low GC content (20.9%) and a 16S rRNA gene with just 65% sequence similarity to the closest reference sequence. Lastly, our findings illustrate the importance of sampling strategy and de novo assembly of metagenomic reads to understand the extent and function of bacterial biodiversity.« less

Morphological characteristics of the posterior malleolar fragment according to ankle fracture patterns: a computed tomography-based study.

PubMed

Yi, Young; Chun, Dong-Il; Won, Sung Hun; Park, Suyeon; Lee, Sanghyeon; Cho, Jaeho

2018-02-13

The posterior malleolar fragment (PMF) of an ankle fracture can have various shapes depending on the injury mechanism. The purpose of this study was to evaluate the morphological characteristics of the PMF according to the ankle fracture pattern described in the Lauge-Hansen classification by using computed tomography (CT) images. We retrospectively analyzed CT data of 107 patients (107 ankles) who underwent surgery for trimalleolar fracture from January 2012 to December 2014. The patients were divided into two groups: 76 ankles in the supination-external rotation (SER) stage IV group and 31 ankles in the pronation-external rotation (PER) stage IV group. The PMF type of the two groups was assessed using the Haraguchi and Jan Bartonicek classification. The cross angle (α), fragment length ratio (FLR), fragment area ratio (FAR), sagittal angle (θ), and fragment height (FH) were measured to assess the morphological characteristics of the PMF. The PMF in the SER group mainly had a posterolateral shape, whereas that in the PER group mainly had a posteromedial two-part shape or a large posterolateral triangular shape (P = 0.02). The average cross angle was not significantly different between the two groups (SER group = 19.4°, PER group = 17.6°). The mean FLR and FH were significantly larger in the PER group than in the SER group (P = 0.024, P = 0.006). The mean fragment sagittal angle in the PER group was significantly smaller than that in the SER group (P = 0.017). With regard to the articular involvement, volume, and vertical nature, the SER-type fracture tends to have a smaller fragment due to the rotational force, whereas the PER-type fracture tends to have a larger fragment due to the combination of rotational and axial forces.

Constructing and Screening a Metagenomic Library of a Cold and Alkaline Extreme Environment.

PubMed

Glaring, Mikkel A; Vester, Jan K; Stougaard, Peter

2017-01-01

Natural cold or alkaline environments are common on Earth. A rare combination of these two extremes is found in the permanently cold (less than 6 °C) and alkaline (pH above 10) ikaite columns in the Ikka Fjord in Southern Greenland. Bioprospecting efforts have established the ikaite columns as a source of bacteria and enzymes adapted to these conditions. They have also highlighted the limitations of cultivation-based methods in this extreme environment and metagenomic approaches may provide access to novel extremophilic enzymes from the uncultured majority of bacteria. Here, we describe the construction and screening of a metagenomic library of the prokaryotic community inhabiting the ikaite columns.

Prediction and identification of sequences coding for orphan enzymes using genomic and metagenomic neighbours

PubMed Central

Yamada, Takuji; Waller, Alison S; Raes, Jeroen; Zelezniak, Aleksej; Perchat, Nadia; Perret, Alain; Salanoubat, Marcel; Patil, Kiran R; Weissenbach, Jean; Bork, Peer

2012-01-01

Despite the current wealth of sequencing data, one-third of all biochemically characterized metabolic enzymes lack a corresponding gene or protein sequence, and as such can be considered orphan enzymes. They represent a major gap between our molecular and biochemical knowledge, and consequently are not amenable to modern systemic analyses. As 555 of these orphan enzymes have metabolic pathway neighbours, we developed a global framework that utilizes the pathway and (meta)genomic neighbour information to assign candidate sequences to orphan enzymes. For 131 orphan enzymes (37% of those for which (meta)genomic neighbours are available), we associate sequences to them using scoring parameters with an estimated accuracy of 70%, implying functional annotation of 16 345 gene sequences in numerous (meta)genomes. As a case in point, two of these candidate sequences were experimentally validated to encode the predicted activity. In addition, we augmented the currently available genome-scale metabolic models with these new sequence–function associations and were able to expand the models by on average 8%, with a considerable change in the flux connectivity patterns and improved essentiality prediction. PMID:22569339

Beyond research: a primer for considerations on using viral metagenomics in the field and clinic.

PubMed

Hall, Richard J; Draper, Jenny L; Nielsen, Fiona G G; Dutilh, Bas E

2015-01-01

Powered by recent advances in next-generation sequencing technologies, metagenomics has already unveiled vast microbial biodiversity in a range of environments, and is increasingly being applied in clinics for difficult-to-diagnose cases. It can be tempting to suggest that metagenomics could be used as a "universal test" for all pathogens without the need to conduct lengthy serial testing using specific assays. While this is an exciting prospect, there are issues that need to be addressed before metagenomic methods can be applied with rigor as a diagnostic tool, including the potential for incidental findings, unforeseen consequences for trade and regulatory authorities, privacy and cultural issues, data sharing, and appropriate reporting of results to end-users. These issues will require consideration and discussion across a range of disciplines, with inclusion of scientists, ethicists, clinicians, diagnosticians, health practitioners, and ultimately the public. Here, we provide a primer for consideration on some of these issues.

Metagenomic characterization of viral communities in Goseong Bay, Korea

NASA Astrophysics Data System (ADS)

Hwang, Jinik; Park, So Yun; Park, Mirye; Lee, Sukchan; Jo, Yeonhwa; Cho, Won Kyong; Lee, Taek-Kyun

2016-12-01

In this study, seawater samples were collected from Goseong Bay, Korea in March 2014 and viral populations were examined by metagenomics assembly. Enrichment of marine viral particles using FeCl3 followed by next-generation sequencing produced numerous sequences. De novo assembly and BLAST search showed that most of the obtained contigs were unknown sequences and only 0.74% of sequences were associated with known viruses. As a result, 138 viruses, including bacteriophages (87%), viruses infecting algae and others (13%) were identified. The identified 138 viruses were divided into 11 orders, 14 families, 34 genera, and 133 species. The dominant viruses were Pelagibacter phage HTVC010P and Roseobacter phage SIO1. The viruses infecting algae, including the Ostreococcus species, accounted for 9.4% of total identified viruses. In addition, we identified pathogenic herpes viruses infecting fishes and giant viruses infecting parasitic acanthamoeba species. This is a comprehensive study to reveal the viral populations in the Goseong Bay using metagenomics. The information associated with the marine viral community in Goseong Bay, Korea will be useful for comparative analysis in other marine viral communities.

Genomics and Metagenomics of Extreme Acidophiles in Biomining Environments

NASA Astrophysics Data System (ADS)

Holmes, D. S.

2015-12-01

Over 160 draft or complete genomes of extreme acidophiles (pH < 3) have been published, many of which are from bioleaching and other biomining environments, or are closely related to such microorganisms. In addition, there are over 20 metagenomic studies of such environments. This provides a rich source of latent data that can be exploited for understanding the biology of biomining environments and for advancing biotechnological applications. Genomic and metagenomic data are already yielding valuable insights into cellular processes, including carbon and nitrogen management, heavy metal and acid resistance, iron and sulfur oxido-reduction, linking biogeochemical processes to organismal physiology. The data also allow the construction of useful models of the ecophysiology of biomining environments and provide insight into the gene and genome evolution of extreme acidophiles. Additionally, since most of these acidophiles are also chemoautolithotrophs that use minerals as energy sources or electron sinks, their genomes can be plundered for clues about the evolution of cellular metabolism and bioenergetic pathways during the Archaean abiotic/biotic transition on early Earth. Acknowledgements: Fondecyt 1130683.

From genus to phylum: large-subunit and internal transcribed spacer rRNA operon regions show similar classification accuracies influenced by database composition.

PubMed

Porras-Alfaro, Andrea; Liu, Kuan-Liang; Kuske, Cheryl R; Xie, Gary

2014-02-01

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5' section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets.

From Genus to Phylum: Large-Subunit and Internal Transcribed Spacer rRNA Operon Regions Show Similar Classification Accuracies Influenced by Database Composition

PubMed Central

Liu, Kuan-Liang; Kuske, Cheryl R.

2014-01-01

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5′ section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets. PMID:24242255

Back to the future of soil metagenomics

DOE PAGES

Nesme, Joseph; Achouak, Wafa; Agathos, Spiros N.; ...

2016-02-10

Here, direct extraction and characterization of microbial community DNA through PCR amplicon surveys and metagenomics has revolutionized the study of environmental microbiology and microbial ecology. In particular, metagenomic analysis of nucleic acids provides direct access to the genomes of the “uncultivated majority.” Accelerated by advances in sequencing technology, microbiologists have discovered more novel phyla, classes, genera, and genes from microorganisms in the first decade and a half of the twenty-first century than since these “many very little living animalcules” were first discovered by van Leeuwenhoek (Table 1). The unsurpassed diversity of soils promises continued exploration of a range of industrial,more » agricultural, and environmental functions. The ability to explore soil microbial communities with increasing capacity offers the highest promise for answering many outstanding who, what, where, when, why, and with whom questions such as: Which microorganisms are linked to which soil habitats? How do microbial abundances change with changing edaphic conditions? How do microbial assemblages interact and influence one another synergistically or antagonistically? What is the full extent of soil microbial diversity, both functionally and phylogenetically? What are the dynamics of microbial communities in space and time? How sensitive are microbial communities to a changing climate? What is the role of horizontal gene transfer in the stability of microbial communities? Do highly diverse microbial communities confer resistance and resilience in soils?« less

Back to the future of soil metagenomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nesme, Joseph; Achouak, Wafa; Agathos, Spiros N.

Here, direct extraction and characterization of microbial community DNA through PCR amplicon surveys and metagenomics has revolutionized the study of environmental microbiology and microbial ecology. In particular, metagenomic analysis of nucleic acids provides direct access to the genomes of the “uncultivated majority.” Accelerated by advances in sequencing technology, microbiologists have discovered more novel phyla, classes, genera, and genes from microorganisms in the first decade and a half of the twenty-first century than since these “many very little living animalcules” were first discovered by van Leeuwenhoek (Table 1). The unsurpassed diversity of soils promises continued exploration of a range of industrial,more » agricultural, and environmental functions. The ability to explore soil microbial communities with increasing capacity offers the highest promise for answering many outstanding who, what, where, when, why, and with whom questions such as: Which microorganisms are linked to which soil habitats? How do microbial abundances change with changing edaphic conditions? How do microbial assemblages interact and influence one another synergistically or antagonistically? What is the full extent of soil microbial diversity, both functionally and phylogenetically? What are the dynamics of microbial communities in space and time? How sensitive are microbial communities to a changing climate? What is the role of horizontal gene transfer in the stability of microbial communities? Do highly diverse microbial communities confer resistance and resilience in soils?« less

Improved glycerol to ethanol conversion by E. coli using a metagenomic fragment isolated from an anaerobic reactor.

PubMed

Loaces, Inés; Rodríguez, Cecilia; Amarelle, Vanesa; Fabiano, Elena; Noya, Francisco

2016-10-01

Crude glycerol obtained as a by-product of biodiesel production is a reliable feedstock with the potential to be converted into reduced chemicals with high yields. It has been previously shown that ethanol is the primary product of glycerol fermentation by Escherichia coli. However, few efforts were made to enhance this conversion by means of the expression of heterologous genes with the potential to improve glycerol transport or metabolism. In this study, a fosmid-based metagenomic library constructed from an anaerobic reactor purge sludge was screened for genetic elements that promote the use and fermentation of crude glycerol by E. coli. One clone was selected based on its improved growth rate on this feedstock. The corresponding fosmid, named G1, was fully sequenced (41 kbp long) and the gene responsible for the observed phenotype was pinpointed by in vitro insertion mutagenesis. Ethanol production from both pure and crude glycerol was evaluated using the parental G1 clone harboring the ethanologenic plasmid pLOI297 or the industrial strain LY180 complemented with G1. In mineral salts media containing 50 % (v/v) pure glycerol, ethanol concentrations increased two-fold on average when G1 was present in the cells reaching up to 20 g/L after 24 h fermentation. Similar fermentation experiments were done using crude instead of pure glycerol. With an initial OD620 of 8.0, final ethanol concentrations after 24 h were much higher reaching 67 and 75 g/L with LY180 cells carrying the control fosmid or the G1 fosmid, respectively. This translates into a specific ethanol production rate of 0.39 g h(-1) OD(-1) L(-1).

Metagenome, metatranscriptome and single-cell sequencing reveal microbial response to Deepwater Horizon oil spill.

PubMed

Mason, Olivia U; Hazen, Terry C; Borglin, Sharon; Chain, Patrick S G; Dubinsky, Eric A; Fortney, Julian L; Han, James; Holman, Hoi-Ying N; Hultman, Jenni; Lamendella, Regina; Mackelprang, Rachel; Malfatti, Stephanie; Tom, Lauren M; Tringe, Susannah G; Woyke, Tanja; Zhou, Jizhong; Rubin, Edward M; Jansson, Janet K

2012-09-01

The Deepwater Horizon oil spill in the Gulf of Mexico resulted in a deep-sea hydrocarbon plume that caused a shift in the indigenous microbial community composition with unknown ecological consequences. Early in the spill history, a bloom of uncultured, thus uncharacterized, members of the Oceanospirillales was previously detected, but their role in oil disposition was unknown. Here our aim was to determine the functional role of the Oceanospirillales and other active members of the indigenous microbial community using deep sequencing of community DNA and RNA, as well as single-cell genomics. Shotgun metagenomic and metatranscriptomic sequencing revealed that genes for motility, chemotaxis and aliphatic hydrocarbon degradation were significantly enriched and expressed in the hydrocarbon plume samples compared with uncontaminated seawater collected from plume depth. In contrast, although genes coding for degradation of more recalcitrant compounds, such as benzene, toluene, ethylbenzene, total xylenes and polycyclic aromatic hydrocarbons, were identified in the metagenomes, they were expressed at low levels, or not at all based on analysis of the metatranscriptomes. Isolation and sequencing of two Oceanospirillales single cells revealed that both cells possessed genes coding for n-alkane and cycloalkane degradation. Specifically, the near-complete pathway for cyclohexane oxidation in the Oceanospirillales single cells was elucidated and supported by both metagenome and metatranscriptome data. The draft genome also included genes for chemotaxis, motility and nutrient acquisition strategies that were also identified in the metagenomes and metatranscriptomes. These data point towards a rapid response of members of the Oceanospirillales to aliphatic hydrocarbons in the deep sea.

[Cloning, expression and characterization of a novel esterase from marine sediment microbial metagenomic library].

PubMed

Xu, Shiqing; Hu, Yongfei; Yuan, Aihua; Zhu, Baoli

2010-07-01

To clone, express and characterize a novel esterase from marine sediment microbial metagenomic library. Using esterase segregation agar containing tributyrin, we obtained esterase positive fosmid clone FL10 from marine sediment microbial metagenomic library. This fosmid was partially digested with Sau3A I to construct the sublibrary, from which the esterase positive subclone pFLS10 was obtained. The full length of the esterase gene was amplified and cloned into the expressing vector pET28a, and the recombinant plasmid was transformed into E. coli BL21 cells. We analyse the enzyme activity and study the characterization of the esterase after its expression and purification. An ORF (Open Reading Frame) of 924 bp was identified from the subclone pFLS10. Sequence analysis indicated that it showed 71% amino acid identity to esterase (ADA70030) from a marine sediment metagenomic library. The esterase is a novel low-temperature-active esterase and had highest lipolytic activity to the substrate of 4-nitrophenyl butyrate (C4). The optimum temperature of the esterase was 20 degrees C, the optimum pH was 7.5. The esterase in this study had good thermostability at 20 degrees C and good pH stability at pH8 -10. Significant increase in lipolytic activity was observed with addition of K+ and Mg2+, while decrease with Mn2+ etc. We obtained the novel esterase gene fls10 from the marine sediment microbial metagenomic library. The esterase had good thermostability and high lipolytic activity at low temperature and under basic conditions, which laid a basis for industrial application.

High frequency of phylogenetically diverse reductive dehalogenase-homologous genes in deep subseafloor sedimentary metagenomes

PubMed Central

Kawai, Mikihiko; Futagami, Taiki; Toyoda, Atsushi; Takaki, Yoshihiro; Nishi, Shinro; Hori, Sayaka; Arai, Wataru; Tsubouchi, Taishi; Morono, Yuki; Uchiyama, Ikuo; Ito, Takehiko; Fujiyama, Asao; Inagaki, Fumio; Takami, Hideto

2014-01-01

Marine subsurface sediments on the Pacific margin harbor diverse microbial communities even at depths of several hundreds meters below the seafloor (mbsf) or more. Previous PCR-based molecular analysis showed the presence of diverse reductive dehalogenase gene (rdhA) homologs in marine subsurface sediment, suggesting that anaerobic respiration of organohalides is one of the possible energy-yielding pathways in the organic-rich sedimentary habitat. However, primer-independent molecular characterization of rdhA has remained to be demonstrated. Here, we studied the diversity and frequency of rdhA homologs by metagenomic analysis of five different depth horizons (0.8, 5.1, 18.6, 48.5, and 107.0 mbsf) at Site C9001 off the Shimokita Peninsula of Japan. From all metagenomic pools, remarkably diverse rdhA-homologous sequences, some of which are affiliated with novel clusters, were observed with high frequency. As a comparison, we also examined frequency of dissimilatory sulfite reductase genes (dsrAB), key functional genes for microbial sulfate reduction. The dsrAB were also widely observed in the metagenomic pools whereas the frequency of dsrAB genes was generally smaller than that of rdhA-homologous genes. The phylogenetic composition of rdhA-homologous genes was similar among the five depth horizons. Our metagenomic data revealed that subseafloor rdhA homologs are more diverse than previously identified from PCR-based molecular studies. Spatial distribution of similar rdhA homologs across wide depositional ages indicates that the heterotrophic metabolic processes mediated by the genes can be ecologically important, functioning in the organic-rich subseafloor sedimentary biosphere. PMID:24624126

High frequency of phylogenetically diverse reductive dehalogenase-homologous genes in deep subseafloor sedimentary metagenomes.

PubMed

Kawai, Mikihiko; Futagami, Taiki; Toyoda, Atsushi; Takaki, Yoshihiro; Nishi, Shinro; Hori, Sayaka; Arai, Wataru; Tsubouchi, Taishi; Morono, Yuki; Uchiyama, Ikuo; Ito, Takehiko; Fujiyama, Asao; Inagaki, Fumio; Takami, Hideto

2014-01-01

Marine subsurface sediments on the Pacific margin harbor diverse microbial communities even at depths of several hundreds meters below the seafloor (mbsf) or more. Previous PCR-based molecular analysis showed the presence of diverse reductive dehalogenase gene (rdhA) homologs in marine subsurface sediment, suggesting that anaerobic respiration of organohalides is one of the possible energy-yielding pathways in the organic-rich sedimentary habitat. However, primer-independent molecular characterization of rdhA has remained to be demonstrated. Here, we studied the diversity and frequency of rdhA homologs by metagenomic analysis of five different depth horizons (0.8, 5.1, 18.6, 48.5, and 107.0 mbsf) at Site C9001 off the Shimokita Peninsula of Japan. From all metagenomic pools, remarkably diverse rdhA-homologous sequences, some of which are affiliated with novel clusters, were observed with high frequency. As a comparison, we also examined frequency of dissimilatory sulfite reductase genes (dsrAB), key functional genes for microbial sulfate reduction. The dsrAB were also widely observed in the metagenomic pools whereas the frequency of dsrAB genes was generally smaller than that of rdhA-homologous genes. The phylogenetic composition of rdhA-homologous genes was similar among the five depth horizons. Our metagenomic data revealed that subseafloor rdhA homologs are more diverse than previously identified from PCR-based molecular studies. Spatial distribution of similar rdhA homologs across wide depositional ages indicates that the heterotrophic metabolic processes mediated by the genes can be ecologically important, functioning in the organic-rich subseafloor sedimentary biosphere.

Morphometric comparison by the ISAS® CASA-DNAf system of two techniques for the evaluation of DNA fragmentation in human spermatozoa

PubMed Central

Sadeghi, Sara; García-Molina, Almudena; Celma, Ferran; Valverde, Anthony; Fereidounfar, Sogol; Soler, Carles

2016-01-01

DNA fragmentation has been shown to be one of the causes of male infertility, particularly related to repeated abortions, and different methods have been developed to analyze it. In the present study, two commercial kits based on the SCD technique (Halosperm® and SDFA) were evaluated by the use of the DNA fragmentation module of the ISAS® v1 CASA system. Seven semen samples from volunteers were analyzed. To compare the results between techniques, the Kruskal–Wallis test was used. Data were used for calculation of Principal Components (two PCs were obtained), and subsequent subpopulations were identified using the Halo, Halo/Core Ratio, and PC data. Results from both kits were significantly different (P < 0.001). In each case, four subpopulations were obtained, independently of the classification method used. The distribution of subpopulations differed depending on the kit used. From the PC data, a discriminant analysis matrix was obtained and a good a posteriori classification was obtained (97.1% for Halosperm and 96.6% for SDFA). The present results are the first approach on morphometric evaluation of DNA fragmentation from the SCD technique. This approach could be used for the future definition of a classification matrix surpassing the current subjective evaluation of this important sperm factor. PMID:27678463

Morphometric comparison by the ISAS® CASA-DNAf system of two techniques for the evaluation of DNA fragmentation in human spermatozoa.

PubMed

Sadeghi, Sara; García-Molina, Almudena; Celma, Ferran; Valverde, Anthony; Fereidounfar, Sogol; Soler, Carles

2016-01-01

DNA fragmentation has been shown to be one of the causes of male infertility, particularly related to repeated abortions, and different methods have been developed to analyze it. In the present study, two commercial kits based on the SCD technique (Halosperm ® and SDFA) were evaluated by the use of the DNA fragmentation module of the ISAS ® v1 CASA system. Seven semen samples from volunteers were analyzed. To compare the results between techniques, the Kruskal-Wallis test was used. Data were used for calculation of Principal Components (two PCs were obtained), and subsequent subpopulations were identified using the Halo, Halo/Core Ratio, and PC data. Results from both kits were significantly different (P < 0.001). In each case, four subpopulations were obtained, independently of the classification method used. The distribution of subpopulations differed depending on the kit used. From the PC data, a discriminant analysis matrix was obtained and a good a posteriori classification was obtained (97.1% for Halosperm and 96.6% for SDFA). The present results are the first approach on morphometric evaluation of DNA fragmentation from the SCD technique. This approach could be used for the future definition of a classification matrix surpassing the current subjective evaluation of this important sperm factor.

Exploring nucleo-cytoplasmic large DNA viruses in Tara Oceans microbial metagenomes

PubMed Central

Hingamp, Pascal; Grimsley, Nigel; Acinas, Silvia G; Clerissi, Camille; Subirana, Lucie; Poulain, Julie; Ferrera, Isabel; Sarmento, Hugo; Villar, Emilie; Lima-Mendez, Gipsi; Faust, Karoline; Sunagawa, Shinichi; Claverie, Jean-Michel; Moreau, Hervé; Desdevises, Yves; Bork, Peer; Raes, Jeroen; de Vargas, Colomban; Karsenti, Eric; Kandels-Lewis, Stefanie; Jaillon, Olivier; Not, Fabrice; Pesant, Stéphane; Wincker, Patrick; Ogata, Hiroyuki

2013-01-01

Nucleo-cytoplasmic large DNA viruses (NCLDVs) constitute a group of eukaryotic viruses that can have crucial ecological roles in the sea by accelerating the turnover of their unicellular hosts or by causing diseases in animals. To better characterize the diversity, abundance and biogeography of marine NCLDVs, we analyzed 17 metagenomes derived from microbial samples (0.2–1.6 μm size range) collected during the Tara Oceans Expedition. The sample set includes ecosystems under-represented in previous studies, such as the Arabian Sea oxygen minimum zone (OMZ) and Indian Ocean lagoons. By combining computationally derived relative abundance and direct prokaryote cell counts, the abundance of NCLDVs was found to be in the order of 104–105 genomes ml−1 for the samples from the photic zone and 102–103 genomes ml−1 for the OMZ. The Megaviridae and Phycodnaviridae dominated the NCLDV populations in the metagenomes, although most of the reads classified in these families showed large divergence from known viral genomes. Our taxon co-occurrence analysis revealed a potential association between viruses of the Megaviridae family and eukaryotes related to oomycetes. In support of this predicted association, we identified six cases of lateral gene transfer between Megaviridae and oomycetes. Our results suggest that marine NCLDVs probably outnumber eukaryotic organisms in the photic layer (per given water mass) and that metagenomic sequence analyses promise to shed new light on the biodiversity of marine viruses and their interactions with potential hosts. PMID:23575371

Exploring nucleo-cytoplasmic large DNA viruses in Tara Oceans microbial metagenomes.

PubMed

Hingamp, Pascal; Grimsley, Nigel; Acinas, Silvia G; Clerissi, Camille; Subirana, Lucie; Poulain, Julie; Ferrera, Isabel; Sarmento, Hugo; Villar, Emilie; Lima-Mendez, Gipsi; Faust, Karoline; Sunagawa, Shinichi; Claverie, Jean-Michel; Moreau, Hervé; Desdevises, Yves; Bork, Peer; Raes, Jeroen; de Vargas, Colomban; Karsenti, Eric; Kandels-Lewis, Stefanie; Jaillon, Olivier; Not, Fabrice; Pesant, Stéphane; Wincker, Patrick; Ogata, Hiroyuki

2013-09-01

Nucleo-cytoplasmic large DNA viruses (NCLDVs) constitute a group of eukaryotic viruses that can have crucial ecological roles in the sea by accelerating the turnover of their unicellular hosts or by causing diseases in animals. To better characterize the diversity, abundance and biogeography of marine NCLDVs, we analyzed 17 metagenomes derived from microbial samples (0.2-1.6 μm size range) collected during the Tara Oceans Expedition. The sample set includes ecosystems under-represented in previous studies, such as the Arabian Sea oxygen minimum zone (OMZ) and Indian Ocean lagoons. By combining computationally derived relative abundance and direct prokaryote cell counts, the abundance of NCLDVs was found to be in the order of 10(4)-10(5) genomes ml(-1) for the samples from the photic zone and 10(2)-10(3) genomes ml(-1) for the OMZ. The Megaviridae and Phycodnaviridae dominated the NCLDV populations in the metagenomes, although most of the reads classified in these families showed large divergence from known viral genomes. Our taxon co-occurrence analysis revealed a potential association between viruses of the Megaviridae family and eukaryotes related to oomycetes. In support of this predicted association, we identified six cases of lateral gene transfer between Megaviridae and oomycetes. Our results suggest that marine NCLDVs probably outnumber eukaryotic organisms in the photic layer (per given water mass) and that metagenomic sequence analyses promise to shed new light on the biodiversity of marine viruses and their interactions with potential hosts.

Metagenomic analysis of bacterial and archaeal assemblages in the soil-mousse surrounding a geothermal spring.

PubMed

Bhatia, Sonu; Batra, Navneet; Pathak, Ashish; Joshi, Amit; Souza, Leila; Almeida, Paulo; Chauhan, Ashvini

2015-09-01

The soil-mousse surrounding a geothermal spring was analyzed for bacterial and archaeal diversity using 16S rRNA gene amplicon metagenomic sequencing which revealed the presence of 18 bacterial phyla distributed across 109 families and 219 genera. Firmicutes, Actinobacteria, and the Deinococcus-Thermus group were the predominant bacterial assemblages with Crenarchaeota and Thaumarchaeota as the main archaeal assemblages in this largely understudied geothermal habitat. Several metagenome sequences remained taxonomically unassigned suggesting the presence of a repertoire of hitherto undescribed microbes in this geothermal soil-mousse econiche.

The Chicago classification of motility disorders: an update.

PubMed

Roman, Sabine; Gyawali, C Prakash; Xiao, Yinglian; Pandolfino, John E; Kahrilas, Peter J

2014-10-01

The Chicago Classification defines esophageal motility disorders in high resolution manometry. This is based on individual scoring of 10 swallows performed in supine position. Disorders of esophago-gastric junction (EGJ) outflow obstruction are defined by a median integrated relaxation pressure above the limit of normal and divided into 3 achalasia subtypes and EGJ outflow obstruction. Major motility disorders (aperistalsis, distal esophageal spasm, and hypercontractile esophagus) are patterns not encountered in controls in the context of normal EGJ relaxation. Finally with the latest version of the Chicago Classification, only two minor motor disorders are considered: ineffective esophageal motility and fragmented peristalsis. Copyright © 2014 Elsevier Inc. All rights reserved.

Accurate, Rapid Taxonomic Classification of Fungal Large-Subunit rRNA Genes