Meeting report : 1st international functional metagenomics workshop May 7–8, 2012, St. Jacobs, Ontario, Canada

This report summarizes the events of the 1st International Functional Metagenomics Workshop. The workshop was held on May 7 and 8 in St. Jacobs, Ontario, Canada and was focused on building a core international functional metagenomics community, exploring strategic research areas, and identifying opportunities for future collaboration and funding. The workshop was initiated by researchers at the University of Waterloo with support from the Ontario Genomics Institute (OGI), Natural Sciences and Engineering Research Council of Canada (NSERC) and the University of Waterloo

Back to the future of soil metagenomics

JN was funded by a fellowship from the French MENESR.Peer reviewedPeer Reviewe

A communal catalogue reveals Earth's multiscale microbial diversity

Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

A communal catalogue reveals Earth’s multiscale microbial diversity

Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for D-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable

Insight into soil microbial ecology through the development and application of serial analysis of ribosomal sequence tags (SARST) and a community-specific microarray

In order to overcome technical hurdles hindering progress in soil microbial ecology, this project involved the development and application of a molecular assay for measuring microbial community composition and diversity. Serial analysis of ribosomal sequence tags (SARST) generates libraries of a short and variable portion of the 16S rRNA gene. A series of enzymatic reactions amplifies and ligates ribosomal sequence tags (RSTs) into concatemers that are cloned and sequenced. On average, 5-10 RSTs were obtained from multiple phylotypes with each sequencing reaction. SARST was initially tested on: 1) activated sludge, 2) boreal forest soil, 3) a mixture of pure cultures and 4) duplicate libraries from an arctic tundra soil sample. SARST was also used to study microbial communities within soils sampled from Canada and Spain. Bacterial diversity of geographically distinct locations was characterized for Canadian arctic tundra and boreal forest soil biomes. Composite samples taken from arctic tundra demonstrated significantly higher estimates of bacterial diversity than boreal forest soils. Also, despite climate differences, the overall phylotype compositions of boreal forest soil libraries did not cluster distinctly from tundra samples. As a result of large RST libraries, individual phylotypes were identified that were associated with all soil libraries and others were unique to specific samples. These sequences represent potentially cosmopolitan and endemic distributions of these organisms. Several soils in the Basque Country of Spain are contaminated with high concentrations of hexachlorocyclohexane (HCH). However, the impact of HCH on soil bacterial community structure is not well understood. SARST enabled the design of a community-specific microarray for comparing multiple soil samples. The RST array was tested with pure cultures and by comparing soil hybridizations to denaturing gradient gel electrophoresis (DGGE) fingerprints from these same soils. Hybridization and DGGE results suggested that in contaminated soils, microbial communities were less diverse and had a higher proportion of predominant phylotypes. Several probe signals were correlated with HCH contamination (r>0.70), including one corresponding to Sphingomonas, a genus with known HCH degraders. Environmental parameters such as depth, pH and organic matter were also correlated with community structure in the soil samples.Science, Faculty ofMicrobiology and Immunology, Department ofGraduat

Current and future resources for functional metagenomics

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

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

<div><p>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 <i>Sinorhizobium meliloti</i> (<i>α-Proteobacteria</i>) and <i>Escherichia coli</i> (<i>γ-Proteobacteria</i>) 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 <i>S</i>. <i>meliloti</i>. 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.</p></div