Diverse syntrophic partnerships from deep-sea methane vents revealed by direct cell capture and metagenomics

Microorganisms play a fundamental role in the cycling of nutrients and energy on our planet. A common strategy for many microorganisms mediating biogeochemical cycles in anoxic environments is syntrophy, frequently necessitating close spatial proximity between microbial partners. We are only now beginning to fully appreciate the diversity and pervasiveness of microbial partnerships in nature, the majority of which cannot be replicated in the laboratory. One notable example of such cooperation is the interspecies association between anaerobic methane oxidizing archaea (ANME) and sulfate-reducing bacteria. These consortia are globally distributed in the environment and provide a significant sink for methane by substantially reducing the export of this potent greenhouse gas into the atmosphere. The interdependence of these currently uncultured microbes renders them difficult to study, and our knowledge of their physiological capabilities in nature is limited. Here, we have developed a method to capture select microorganisms directly from the environment, using combined fluorescence in situ hybridization and immunomagnetic cell capture. We used this method to purify syntrophic anaerobic methane oxidizing ANME-2c archaea and physically associated microorganisms directly from deep-sea marine sediment. Metagenomics, PCR, and microscopy of these purified consortia revealed unexpected diversity of associated bacteria, including Betaproteobacteria and a second sulfate-reducing Deltaproteobacterial partner. The detection of nitrogenase genes within the metagenome and subsequent demonstration of 15N2 incorporation in the biomass of these methane-oxidizing consortia suggest a possible role in new nitrogen inputs by these syntrophic assemblages

CADRE: the Central Aspergillus Data REpository 2012

The Central Aspergillus Data REpository (CADRE; http://www.cadre-genomes.org.uk) is a public resource for genomic data extracted from species of Aspergillus. It provides an array of online tools for searching and visualising features of this significant fungal genus. CADRE arose from a need within the medical community to understand the human pathogen Aspergillus fumigatus. Due to the paucity of Aspergillus genomic resources 10 years ago, the long-term goal of this project was to collate and maintain Aspergillus genomes as they became available. Since our first release in 2004, the resource has expanded to encompass annotated sequence for eight other Aspergilli and provides much needed support to the international Aspergillus research community. Recent developments, however, in sequencing technology are creating a vast amount of genomic data and, as a result, we shortly expect a tidal wave of Aspergillus data. In preparation for this, we have upgraded the database and software suite. This not only enables better management of more complex data sets, but also improves annotation by providing access to genome comparison data and the integration of high-throughput data

FungiDB: an integrated functional genomics database for fungi

FungiDB (http://FungiDB.org) is a functional genomic resource for pan-fungal genomes that was developed in partnership with the Eukaryotic Pathogen Bioinformatic resource center (http://EuPathDB.org). FungiDB uses the same infrastructure and user interface as EuPathDB, which allows for sophisticated and integrated searches to be performed using an intuitive graphical system. The current release of FungiDB contains genome sequence and annotation from 18 species spanning several fungal classes, including the Ascomycota classes, Eurotiomycetes, Sordariomycetes, Saccharomycetes and the Basidiomycota orders, Pucciniomycetes and Tremellomycetes, and the basal ‘Zygomycete’ lineage Mucormycotina. Additionally, FungiDB contains cell cycle microarray data, hyphal growth RNA-sequence data and yeast two hybrid interaction data. The underlying genomic sequence and annotation combined with functional data, additional data from the FungiDB standard analysis pipeline and the ability to leverage orthology provides a powerful resource for in silico experimentation

Understanding Differences in the Crystallization Kinetics between One-Step Slot-Die Coating and Spin Coating of MAPbI₃ Using Multimodal In Situ Optical Spectroscopy

To develop a detailed understanding about halide perovskite processing from solution, the crystallization processes are investigated during spin coating and slot-die coating of MAPbI3 at different evaporation rates by simultaneous in situ photoluminescence, light scattering, and absorption measurements. Based on the time evolution of the optical parameters it is found that for both processing methods initially solvent-complex-structures form, followed by perovskite crystallization. The latter proceeds in two stages for spin coating, while for slot-die coating only one perovskite crystallization phase occurs. For both processing methods, it is found that with increasing evaporation rates, the crystallization kinetics of the solvent-complex structure and the perovskite crystallization remain constant on a relative time scale, whereas the duration of the second perovskite crystallization in spin coating increases. This second perovskite crystallization appears restricted due to differences in solvent-complex phase morphologies from which the perovskite forms. The work emphasizes the importance of the exact precursor state properties on the perovskite formation. It further demonstrates that detailed analyses of multimodal optical in situ spectroscopy allows gaining a fundamental understanding of the crystallization processes that take place during solution processing of halide perovskites, independent from the specific processing method

Large-scale identification of genetic design strategies using local search

In the past decade, computational methods have been shown to be well suited to unraveling the complex web of metabolic reactions in biological systems. Methods based on flux–balance analysis (FBA) and bi-level optimization have been used to great effect in aiding metabolic engineering. These methods predict the result of genetic manipulations and allow for the best set of manipulations to be found computationally. Bi-level FBA is, however, limited in applicability because the required computational time and resources scale poorly as the size of the metabolic system and the number of genetic manipulations increase. To overcome these limitations, we have developed Genetic Design through Local Search (GDLS), a scalable, heuristic, algorithmic method that employs an approach based on local search with multiple search paths, which results in effective, low-complexity search of the space of genetic manipulations. Thus, GDLS is able to find genetic designs with greater in silico production of desired metabolites than can feasibly be found using a globally optimal search and performs favorably in comparison with heuristic searches based on evolutionary algorithms and simulated annealing.Hertz Foundatio

Optimisation of substrate angles for multi-material and multi-functional inkjet printing

Three dimensional inkjet printing of multiple materials for electronics applications are challenging due to the limited material availability, inconsistencies in layer thickness between dissimilar materials and the need to expose the printed tracks of metal nanoparticles to temperature above 100 °C for sintering. It is envisaged that instead of printing a dielectric and a conductive material on the same plane, by printing conductive tracks on an angled dielectric surface, the required number of silver layers and consequently, the exposure of the polymer to high temperature and the build time of the component can be significantly reduced. Conductive tracks printed with a fixed print height (FH) showed significantly better resolution for all angles than the fixed slope (FS) sample where the print height varied to maintain the slope length. The electrical resistance of the tracks remained under 10Ω up to 60° for FH; whereas for the FS samples, the resistance remained under 10Ω for samples up to 45°. Thus by fixing the print height to 4 mm, precise tracks with low resistance can be printed at substrate angles up to 60°. By adopting this approach, the build height “Z” can be quickly attained with less exposure of the polymer to high temperature

A MIQE-Compliant Real-Time PCR Assay for Aspergillus Detection

PMCID: PMC3393739This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

TB database: an integrated platform for tuberculosis research

The effective control of tuberculosis (TB) has been thwarted by the need for prolonged, complex and potentially toxic drug regimens, by reliance on an inefficient vaccine and by the absence of biomarkers of clinical status. The promise of the genomics era for TB control is substantial, but has been hindered by the lack of a central repository that collects and integrates genomic and experimental data about this organism in a way that can be readily accessed and analyzed. The Tuberculosis Database (TBDB) is an integrated database providing access to TB genomic data and resources, relevant to the discovery and development of TB drugs, vaccines and biomarkers. The current release of TBDB houses genome sequence data and annotations for 28 different Mycobacterium tuberculosis strains and related bacteria. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives. TBDB currently hosts data for nearly 1500 public tuberculosis microarrays and 260 arrays for Streptomyces. In addition, TBDB provides access to a suite of comparative genomics and microarray analysis software. By bringing together M. tuberculosis genome annotation and gene-expression data with a suite of analysis tools, TBDB (http://www.tbdb.org/) provides a unique discovery platform for TB research

TB database: an integrated platform for tuberculosis research

The effective control of tuberculosis (TB) has been thwarted by the need for prolonged, complex and potentially toxic drug regimens, by reliance on an inefficient vaccine and by the absence of biomarkers of clinical status. The promise of the genomics era for TB control is substantial, but has been hindered by the lack of a central repository that collects and integrates genomic and experimental data about this organism in a way that can be readily accessed and analyzed. The Tuberculosis Database (TBDB) is an integrated database providing access to TB genomic data and resources, relevant to the discovery and development of TB drugs, vaccines and biomarkers. The current release of TBDB houses genome sequence data and annotations for 28 different Mycobacterium tuberculosis strains and related bacteria. TBDB stores pre- and post-publication gene-expression data from M. tuberculosis and its close relatives. TBDB currently hosts data for nearly 1500 public tuberculosis microarrays and 260 arrays for Streptomyces. In addition, TBDB provides access to a suite of comparative genomics and microarray analysis software. By bringing together M. tuberculosis genome annotation and gene-expression data with a suite of analysis tools, TBDB (http://www.tbdb.org/) provides a unique discovery platform for TB research