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Biology subjects

Chris Greening

Publications and source records attributed to Chris Greening.

2 recordsLinked to original sources

Aerobic H2 respiration enhances metabolic flexibility of methanotrophic bacteria

Methanotrophic bacteria are important soil biofilters for the climate-active gas methane. The prevailing opinion is that these bacteria exclusively metabolise single-carbon, and in limited instances, short-chain hydrocarbons for growth. This specialist lifestyle juxtaposes metabolic flexibility, a key strategy for environmental adaptation of microorganisms. Here we show that a methanotrophic bacterium from the phylum Verrucomicrobia oxidises hydrogen gas (H2) during growth and persistence. Methylacidiphilum sp. RTK17.1 expresses a membrane-bound hydrogenase to aerobically respire molecular H2 at environmentally significant concentrations. While H2 oxidation did not support growth as the sole electron source, it significantly enhanced mixotrophic growth yields under both oxygen-replete and oxygen-limiting conditions and was sustained in non-growing cultures starved for methane. We propose that H2 is consumed by this bacterium for mixotrophic growth and persistence in a manner similar to other non-methanotrophic soil microorganisms. We have identified genes encoding oxygen-tolerant uptake hydrogenases in all publicly-available methanotroph genomes, suggesting that H2 oxidation serves a general strategy for methanotrophs to remain energised in chemically-limited environments.

Microbiology

HydDB: A web tool for hydrogenase classification and analysis

H2 metabolism is proposed to be the most ancient and diverse mechanism of energy-conservation. The metalloenzymes mediating this metabolism, hydrogenases, are encoded by over 60 microbial phyla and are present in all major ecosystems. We developed a classification system and web tool, HydDB, for the structural and functional analysis of these enzymes. We show that hydrogenase function can be predicted by primary sequence alone using an expanded classification scheme (comprising 29 [NiFe], 8 [FeFe], and 1 [Fe] hydrogenase classes) that defines 11 new classes with distinct biological functions. Using this scheme, we built a web tool that rapidly and reliably classifies hydrogenase primary sequences using a combination of k-nearest neighbors algorithms and CDD referencing. Demonstrating its capacity, the tool reliably predicted hydrogenase content and function in 12 newly-sequenced bacteria, archaea, and eukaryotes. HydDB provides the capacity to browse the amino acid sequences of 3248 annotated hydrogenase catalytic subunits and also contains a detailed repository of physiological, biochemical, and structural information about the 38 hydrogenase classes defined here. The database and classifier are freely and publicly available at http://services.birc.au.dk/hyddb/

Bioinformatics