Unifying the known and unknown microbial coding sequence space.

Genes of unknown function are among the biggest challenges in molecular biology, especially in microbial systems, where 40-60% of the predicted genes are unknown. Despite previous attempts, systematic approaches to include the unknown fraction into analytical workflows are still lacking. Here, we present a conceptual framework, its translation into the computational workflow AGNOSTOS and a demonstration on how we can bridge the known-unknown gap in genomes and metagenomes. By analyzing 415,971,742 genes predicted from 1749 metagenomes and 28,941 bacterial and archaeal genomes, we quantify the extent of the unknown fraction, its diversity, and its relevance across multiple organisms and environments. The unknown sequence space is exceptionally diverse, phylogenetically more conserved than the known fraction and predominantly taxonomically restricted at the species level. From the 71 M genes identified to be of unknown function, we compiled a collection of 283,874 lineage-specific genes of unknown function for Cand. Patescibacteria (also known as Candidate Phyla Radiation, CPR), which provides a significant resource to expand our understanding of their unusual biology. Finally, by identifying a target gene of unknown function for antibiotic resistance, we demonstrate how we can enable the generation of hypotheses that can be used to augment experimental data.

It is estimated that scientists do not know what half of microbial genes actually do. When these genes are discovered in microorganisms grown in the lab or found in environmental samples, it is not possible to identify what their roles are. Many of these genes are excluded from further analyses for these reasons, meaning that the study of microbial genes tends to be limited to genes that have already been described. These limitations hinder research into microbiology, because information from newly discovered genes cannot be integrated to better understand how these organisms work. Experiments to understand what role these genes have in the microorganisms are labor-intensive, so new analytical strategies are needed. To do this, Vanni et al. developed a new framework to categorize genes with unknown roles, and a computational workflow to integrate them into traditional analyses. When this approach was applied to over 400 million microbial genes (both with known and unknown roles), it showed that the share of genes with unknown functions is only about 30 per cent, smaller than previously thought. The analysis also showed that these genes are very diverse, revealing a huge space for future research and potential applications. Combining their approach with experimental data, Vanni et al. were able to identify a gene with a previously unknown purpose that could be involved in antibiotic resistance. This system could be useful for other scientists studying microorganisms to get a more complete view of microbial systems. In future, it may also be used to analyze the genetics of other organisms, such as plants and animals.

The antiSMASH database, a comprehensive database of microbial secondary metabolite biosynthetic gene clusters.

Secondary metabolites produced by microorganisms are the main source of bioactive compounds that are in use as antimicrobial and anticancer drugs, fungicides, herbicides and pesticides. In the last decade, the increasing availability of microbial genomes has established genome mining as a very important method for the identification of their biosynthetic gene clusters (BGCs). One of the most popular tools for this task is antiSMASH. However, so far, antiSMASH is limited to de novo computing results for user-submitted genomes and only partially connects these with BGCs from other organisms. Therefore, we developed the antiSMASH database, a simple but highly useful new resource to browse antiSMASH-annotated BGCs in the currently 3907 bacterial genomes in the database and perform advanced search queries combining multiple search criteria. antiSMASH-DB is available at http://antismash-db.secondarymetabolites.org/.

BioVeL: a virtual laboratory for data analysis and modelling in biodiversity science and ecology.

BACKGROUND: Making forecasts about biodiversity and giving support to policy relies increasingly on large collections of data held electronically, and on substantial computational capability and capacity to analyse, model, simulate and predict using such data. However, the physically distributed nature of data resources and of expertise in advanced analytical tools creates many challenges for the modern scientist. Across the wider biological sciences, presenting such capabilities on the Internet (as "Web services") and using scientific workflow systems to compose them for particular tasks is a practical way to carry out robust "in silico" science. However, use of this approach in biodiversity science and ecology has thus far been quite limited. RESULTS: BioVeL is a virtual laboratory for data analysis and modelling in biodiversity science and ecology, freely accessible via the Internet. BioVeL includes functions for accessing and analysing data through curated Web services; for performing complex in silico analysis through exposure of R programs, workflows, and batch processing functions; for on-line collaboration through sharing of workflows and workflow runs; for experiment documentation through reproducibility and repeatability; and for computational support via seamless connections to supporting computing infrastructures. We developed and improved more than 60 Web services with significant potential in many different kinds of data analysis and modelling tasks. We composed reusable workflows using these Web services, also incorporating R programs. Deploying these tools into an easy-to-use and accessible 'virtual laboratory', free via the Internet, we applied the workflows in several diverse case studies. We opened the virtual laboratory for public use and through a programme of external engagement we actively encouraged scientists and third party application and tool developers to try out the services and contribute to the activity. CONCLUSIONS: Our work shows we can deliver an operational, scalable and flexible Internet-based virtual laboratory to meet new demands for data processing and analysis in biodiversity science and ecology. In particular, we have successfully integrated existing and popular tools and practices from different scientific disciplines to be used in biodiversity and ecological research.

MyOSD 2014: Evaluating Oceanographic Measurements Contributed by Citizen Scientists in Support of Ocean Sampling Day.

The first Ocean Sampling Day (OSD) took place on June 21, 2014. In a coordinated effort, an internationally distributed group of scientists collected samples from marine surface waters in order to study microbial diversity on a single day with global granularity. Concurrently, citizen scientists enriched the OSD initiative through the MyOSD project, providing additional oceanographic measurements crucial to the contextualization of microbial diversity. Clear protocols, a user-friendly smartphone application, and an online web-form guided citizens in accurate data acquisition, promoting quality submissions to the project's information system. To evaluate the coverage and quality of MyOSD data submissions, we compared the sea surface temperature measurements acquired through OSD, MyOSD, and automatic in situ systems and satellite measurements. Our results show that the quality of citizen-science measurements was comparable to that of scientific measurements. As 79% of MyOSD measurements were conducted in geographic areas not covered by automatic in situ or satellite measurement, citizen scientists contributed significantly to worldwide oceanographic data gathering. Furthermore, survey results indicate that participation in MyOSD made citizens feel more engaged in ocean issues and may have increased their environmental awareness and ocean literacy.

Marine microbial biodiversity, bioinformatics and biotechnology (M2B3) data reporting and service standards.

Contextual data collected concurrently with molecular samples are critical to the use of metagenomics in the fields of marine biodiversity, bioinformatics and biotechnology. We present here Marine Microbial Biodiversity, Bioinformatics and Biotechnology (M2B3) standards for "Reporting" and "Serving" data. The M2B3 Reporting Standard (1) describes minimal mandatory and recommended contextual information for a marine microbial sample obtained in the epipelagic zone, (2) includes meaningful information for researchers in the oceanographic, biodiversity and molecular disciplines, and (3) can easily be adopted by any marine laboratory with minimum sampling resources. The M2B3 Service Standard defines a software interface through which these data can be discovered and explored in data repositories. The M2B3 Standards were developed by the European project Micro B3, funded under 7(th) Framework Programme "Ocean of Tomorrow", and were first used with the Ocean Sampling Day initiative. We believe that these standards have value in broader marine science.

The ocean sampling day consortium.

Ocean Sampling Day was initiated by the EU-funded Micro B3 (Marine Microbial Biodiversity, Bioinformatics, Biotechnology) project to obtain a snapshot of the marine microbial biodiversity and function of the world's oceans. It is a simultaneous global mega-sequencing campaign aiming to generate the largest standardized microbial data set in a single day. This will be achievable only through the coordinated efforts of an Ocean Sampling Day Consortium, supportive partnerships and networks between sites. This commentary outlines the establishment, function and aims of the Consortium and describes our vision for a sustainable study of marine microbial communities and their embedded functional traits.

Genomic standards consortium projects.

The Genomic Standards Consortium (GSC) is an open-membership community that was founded in 2005 to work towards the development, implementation and harmonization of standards in the field of genomics. Starting with the defined task of establishing a minimal set of descriptions the GSC has evolved into an active standards-setting body that currently has 18 ongoing projects, with additional projects regularly proposed from within and outside the GSC. Here we describe our recently enacted policy for proposing new activities that are intended to be taken on by the GSC, along with the template for proposing such new activities.

The founding charter of the Genomic Observatories Network.

The co-authors of this paper hereby state their intention to work together to launch the Genomic Observatories Network (GOs Network) for which this document will serve as its Founding Charter. We define a Genomic Observatory as an ecosystem and/or site subject to long-term scientific research, including (but not limited to) the sustained study of genomic biodiversity from single-celled microbes to multicellular organisms.An international group of 64 scientists first published the call for a global network of Genomic Observatories in January 2012. The vision for such a network was expanded in a subsequent paper and developed over a series of meetings in Bremen (Germany), Shenzhen (China), Moorea (French Polynesia), Oxford (UK), Pacific Grove (California, USA), Washington (DC, USA), and London (UK). While this community-building process continues, here we express our mutual intent to establish the GOs Network formally, and to describe our shared vision for its future. The views expressed here are ours alone as individual scientists, and do not necessarily represent those of the institutions with which we are affiliated.

A metagenomics portal for a democratized sequencing world.

The democratized world of sequencing is leading to numerous data analysis challenges; MG-RAST addresses many of these challenges for diverse datasets, including amplicon datasets, shotgun metagenomes, and metatranscriptomes. The changes from version 2 to version 3 include the addition of a dedicated gene calling stage using FragGenescan, clustering of predicted proteins at 90% identity, and the use of BLAT for the computation of similarities. Together with changes in the underlying software infrastructure, this has enabled the dramatic scaling up of pipeline throughput while remaining on a limited hardware budget. The Web-based service allows upload, fully automated analysis, and visualization of results. As a result of the plummeting cost of sequencing and the readily available analytical power of MG-RAST, over 78,000 metagenomic datasets have been analyzed, with over 12,000 of them publicly available in MG-RAST.

Ecogenomic perspectives on domains of unknown function: correlation-based exploration of marine metagenomes.

BACKGROUND: The proportion of conserved DNA sequences with no clear function is steadily growing in bioinformatics databases. Studies of sequence and structural homology have indicated that many uncharacterized protein domain sequences are variants of functionally described domains. If these variants promote an organism's ecological fitness, they are likely to be conserved in the genome of its progeny and the population at large. The genetic composition of microbial communities in their native ecosystems is accessible through metagenomics. We hypothesize the co-variation of protein domain sequences across metagenomes from similar ecosystems will provide insights into their potential roles and aid further investigation. METHODOLOGY/PRINCIPAL FINDINGS: We calculated the correlation of Pfam protein domain sequences across the Global Ocean Sampling metagenome collection, employing conservative detection and correlation thresholds to limit results to well-supported hits and associations. We then examined intercorrelations between domains of unknown function (DUFs) and domains involved in known metabolic pathways using network visualization and cluster-detection tools. We used a cautious "guilty-by-association" approach, referencing knowledge-level resources to identify and discuss associations that offer insight into DUF function. We observed numerous DUFs associated to photobiologically active domains and prevalent in the Cyanobacteria. Other clusters included DUFs associated with DNA maintenance and repair, inorganic nutrient metabolism, and sodium-translocating transport domains. We also observed a number of clusters reflecting known metabolic associations and cases that predicted functional reclassification of DUFs. CONCLUSION/SIGNIFICANCE: Critically examining domain covariation across metagenomic datasets can grant new perspectives on the roles and associations of DUFs in an ecological setting. Targeted attempts at DUF characterization in the laboratory or in silico may draw from these insights and opportunities to discover new associations and corroborate existing ones will arise as more large-scale metagenomic datasets emerge.

Ecological structuring of bacterial and archaeal taxa in surface ocean waters.

The Global Ocean Sampling (GOS) expedition is currently the largest and geographically most comprehensive metagenomic dataset, including samples from the Atlantic, Pacific, and Indian Oceans. This study makes use of the wide range of environmental conditions and habitats encompassed within the GOS sites in order to investigate the ecological structuring of bacterial and archaeal taxon ranks. Community structures based on taxonomically classified 16S ribosomal RNA (rRNA) gene fragments at phylum, class, order, family, and genus rank levels were examined using multivariate statistical analysis, and the results were inspected in the context of oceanographic environmental variables and structured habitat classifications. At all taxon rank levels, community structures of neritic, oceanic, estuarine biomes, as well as other exotic biomes (salt marsh, lake, mangrove), were readily distinguishable from each other. A strong structuring of the communities with chlorophyll a concentration and a weaker yet significant structuring with temperature and salinity were observed. Furthermore, there were significant correlations between community structures and habitat classification. These results were used for further investigation of one-to-one relationships between taxa and environment and provided indications for ecological preferences shaped by primary production for both cultured and uncultured bacterial and archaeal clades.

RCN4GSC Workshop Report: Modeling a Testbed for Managing Data at the Interface of Biodiversity and (Meta)Genomics, April 2011.

At the GSC11 meeting (4-6 April 2011, Hinxton, England, the GSC's genomic biodiversity working group (GBWG) developed an initial model for a data management testbed at the interface of biodiversity with genomics and metagenomics. With representatives of the Global Biodiversity Information Facility (GBIF) participating, it was agreed that the most useful course of action would be for GBIF to collaborate with the GSC in its ongoing GBWG workshops to achieve common goals around interoperability/data integration across (meta)-genomic and species level data. It was determined that a quick comparison should be made of the contents of the Darwin Core (DwC) and the GSC data checklists, with a goal of determining their degree of overlap and compatibility. An ad-hoc task group lead by Renzo Kottman and Peter Dawyndt undertook an initial comparison between the Darwin Core (DwC) standard used by the Global Biodiversity Information Facility (GBIF) and the MIxS checklists put forward by the Genomic Standards Consortium (GSC). A term-by-term comparison showed that DwC and GSC concepts complement each other far more than they compete with each other. Because the preliminary analysis done at this meeting was based on expertise with GSC standards, but not with DwC standards, the group recommended that a joint meeting of DwC and GSC experts be convened as soon as possible to continue this joint assessment and to propose additional work going forward.

RCN4GSC Workshop Report: Managing Data at the Interface of Biodiversity and (Meta)Genomics, March 2011.

Building on the planning efforts of the RCN4GSC project, a workshop was convened in San Diego to bring together experts from genomics and metagenomics, biodiversity, ecology, and bioinformatics with the charge to identify potential for positive interactions and progress, especially building on successes at establishing data standards by the GSC and by the biodiversity and ecological communities. Until recently, the contribution of microbial life to the biomass and biodiversity of the biosphere was largely overlooked (because it was resistant to systematic study). Now, emerging genomic and metagenomic tools are making investigation possible. Initial research findings suggest that major advances are in the offing. Although different research communities share some overlapping concepts and traditions, they differ significantly in sampling approaches, vocabularies and workflows. Likewise, their definitions of 'fitness for use' for data differ significantly, as this concept stems from the specific research questions of most importance in the different fields. Nevertheless, there is little doubt that there is much to be gained from greater coordination and integration. As a first step toward interoperability of the information systems used by the different communities, participants agreed to conduct a case study on two of the leading data standards from the two formerly disparate fields: (a) GSC's standard checklists for genomics and metagenomics and (b) TDWG's Darwin Core standard, used primarily in taxonomy and systematic biology.

Meeting Report: Hackathon-Workshop on Darwin Core and MIxS Standards Alignment (February 2012).

The Global Biodiversity Information Facility and the Genomic Standards Consortium convened a joint workshop at the University of Oxford, 27-29 February 2012, with a small group of experts from Europe, USA, China and Japan, to continue the alignment of the Darwin Core with the MIxS and related genomics standards. Several reference mappings were produced as well as test expressions of MIxS in RDF. The use and management of controlled vocabulary terms was considered in relation to both GBIF and the GSC, and tools for working with terms were reviewed. Extensions for publishing genomic biodiversity data to the GBIF network via a Darwin Core Archive were prototyped and work begun on preparing translations of the Darwin Core to Japanese and Chinese. Five genomic repositories were identified for engagement to begin the process of testing the publishing of genomic data to the GBIF network commencing with the SILVA rRNA database.

RCN4GSC Meeting Report: Initiating a Testbed for Managing Data at the Interface of Biodiversity and Genomics/Metagenomics, May 2011.

Following up on efforts from two earlier workshops, a meeting was convened in San Diego to (a) establish working connections between experts in the use of the Darwin Core and the GSC MIxS standards, (b) conduct mutual briefings to promote knowledge exchange and to increase the understanding of the two communities' approaches, constraints, community goals, subtleties, etc., (c) perform an element-by-element comparison of the two standards, assessing the compatibility and complementarity of the two approaches, (d) propose and consider possible use cases and test beds in which a joint annotation approach might be tried, to useful scientific effect, and (e) propose additional action items necessary to continue the development of this joint effort. Several focused working teams were identified to continue the work after the meeting ended.

CDinFusion--submission-ready, on-line integration of sequence and contextual data.

State of the art (DNA) sequencing methods applied in "Omics" studies grant insight into the 'blueprints' of organisms from all domains of life. Sequencing is carried out around the globe and the data is submitted to the public repositories of the International Nucleotide Sequence Database Collaboration. However, the context in which these studies are conducted often gets lost, because experimental data, as well as information about the environment are rarely submitted along with the sequence data. If these contextual or metadata are missing, key opportunities of comparison and analysis across studies and habitats are hampered or even impossible. To address this problem, the Genomic Standards Consortium (GSC) promotes checklists and standards to better describe our sequence data collection and to promote the capturing, exchange and integration of sequence data with contextual data. In a recent community effort the GSC has developed a series of recommendations for contextual data that should be submitted along with sequence data. To support the scientific community to significantly enhance the quality and quantity of contextual data in the public sequence data repositories, specialized software tools are needed. In this work we present CDinFusion, a web-based tool to integrate contextual and sequence data in (Multi)FASTA format prior to submission. The tool is open source and available under the Lesser GNU Public License 3. A public installation is hosted and maintained at the Max Planck Institute for Marine Microbiology at http://www.megx.net/cdinfusion. The tool may also be installed locally using the open source code available at http://code.google.com/p/cdinfusion.

The Genomic Standards Consortium.

A vast and rich body of information has grown up as a result of the world's enthusiasm for 'omics technologies. Finding ways to describe and make available this information that maximise its usefulness has become a major effort across the 'omics world. At the heart of this effort is the Genomic Standards Consortium (GSC), an open-membership organization that drives community-based standardization activities, Here we provide a short history of the GSC, provide an overview of its range of current activities, and make a call for the scientific community to join forces to improve the quality and quantity of contextual information about our public collections of genomes, metagenomes, and marker gene sequences.

Analysis of 23S rRNA genes in metagenomes - a case study from the Global Ocean Sampling Expedition.

As an evolutionary marker, 23S ribosomal RNA (rRNA) offers more diagnostic sequence stretches and greater sequence variation than 16S rRNA. However, 23S rRNA is still not as widely used. Based on 80 metagenome samples from the Global Ocean Sampling (GOS) Expedition, the usefulness and taxonomic resolution of 23S rRNA were compared to those of 16S rRNA. Since 23S rRNA is approximately twice as large as 16S rRNA, twice as many 23S rRNA gene fragments were retrieved from the GOS reads than 16S rRNA gene fragments, with 23S rRNA gene fragments being generally about 100bp longer. Datasets for 16S and 23S rRNA sequences revealed similar relative abundances for major marine bacterial and archaeal taxa. However, 16S rRNA sequences had a better taxonomic resolution due to their significantly larger reference database. Reevaluation of the specificity of previously published PCR amplification primers and group specific fluorescence in situ hybridization probes on this metagenomic set of non-amplified 23S rRNA sequences revealed that out of 16 primers investigated, only two had more than 90% target group coverage. Evaluations of two probes, BET42a and GAM42a, were in accordance with previous evaluations, with a discrepancy in the target group coverage of the GAM42a probe when evaluated against the GOS metagenomic dataset.