Alkane hydroxylase genes in psychrophile genomes and the potential for cold active catalysis.

BackgroundPsychrophiles are presumed to play a large role in the catabolism of alkanes and other components of crude oil in natural low temperature environments. In this study we analyzed the functional diversity of genes for alkane hydroxylases, the enzymes responsible for converting alkanes to more labile alcohols, as found in the genomes of nineteen psychrophiles for which alkane degradation has not been reported. To identify possible mechanisms of low temperature optimization we compared putative alkane hydroxylases from these psychrophiles with homologues from nineteen taxonomically related mesophilic strains.ResultsSeven of the analyzed psychrophile genomes contained a total of 27 candidate alkane hydroxylase genes, only two of which are currently annotated as alkane hydroxylase. These candidates were mostly related to the AlkB and cytochrome p450 alkane hydroxylases, but several homologues of the LadA and AlmA enzymes, significant for their ability to degrade long-chain alkanes, were also detected. These putative alkane hydroxylases showed significant differences in primary structure from their mesophile homologues, with preferences for specific amino acids and increased flexibility on loops, bends, and α-helices.ConclusionA focused analysis on psychrophile genomes led to discovery of numerous candidate alkane hydroxylase genes not currently annotated as alkane hydroxylase. Gene products show signs of optimization to low temperature, including regions of increased flexibility and amino acid preferences typical of psychrophilic proteins. These findings are consistent with observations of microbial degradation of crude oil in cold environments and identify proteins that can be targeted in rate studies and in the design of molecular tools for low temperature bioremediation

Identification of Microbial Dark Matter in Antarctic Environments

Numerous studies have applied molecular techniques to understand the diversity, evolution, and ecological function of Antarctic bacteria and archaea. One common technique is sequencing of the 16S rRNA gene, which produces a nearly quantitative profile of community membership. However, the utility of this and similar approaches is limited by what is known about the evolution, physiology, and ecology of surveyed taxa. When representative genomes are available in public databases some of this information can be gleaned from genomic studies, and automated pipelines exist to carry out this task. Here the paprica metabolic inference pipeline was used to assess how well Antarctic microbial communities are represented by the available completed genomes. The NCBI’s Sequence Read Archive (SRA) was searched for Antarctic datasets that used one of the Illumina platforms to sequence the 16S rRNA gene. These data were quality controlled and denoised to identify unique reads, then analyzed with paprica to determine the degree of overlap with the closest phylogenetic neighbor with a completely sequenced genome. While some unique reads had perfect mapping to 16S rRNA genes from completed genomes, the mean percent overlap for all mapped reads was 86.6%. When samples were grouped by environment, some environments appeared more or less well represented by the available genomes. For the domain Bacteria, seawater was particularly poorly represented with a mean overlap of 80.2%, while for the domain Archaea glacial ice was particularly poorly represented with an overlap of only 48.0% for a single sample. These findings suggest that a considerable effort is needed to improve the representation of Antarctic microbes in genome sequence databases

Microbial Communities Can Be Described by Metabolic Structure: A General Framework and Application to a Seasonally Variable, Depth-Stratified Microbial Community from the Coastal West Antarctic Peninsula

Taxonomic marker gene studies, such as the 16S rRNA gene, have been used to successfully explore microbial diversity in a variety of marine, terrestrial, and host environments. For some of these environments long term sampling programs are beginning to build a historical record of microbial community structure. Although these 16S rRNA gene datasets do not intrinsically provide information on microbial metabolism or ecosystem function, this information can be developed by identifying metabolisms associated with related, phenotyped strains. Here we introduce the concept of metabolic inference; the systematic prediction of metabolism from phylogeny, and describe a complete pipeline for predicting the metabolic pathways likely to be found in a collection of 16S rRNA gene phylotypes. This framework includes a mechanism for assigning confidence to each metabolic inference that is based on a novel method for evaluating genomic plasticity. We applied this framework to 16S rRNA gene libraries from the West Antarctic Peninsula marine environment, including surface and deep summer samples and surface winter samples. Using statistical methods commonly applied to community ecology data we found that metabolic structure differed between summer surface and winter and deep samples, comparable to an analysis of community structure by 16S rRNA gene phylotypes. While taxonomic variance between samples was primarily driven by low abundance taxa, metabolic variance was attributable to both high and low abundance pathways. This suggests that clades with a high degree of functional redundancy can occupy distinct adjacent niches. Overall our findings demonstrate that inferred metabolism can be used in place of taxonomy to describe the structure of microbial communities. Coupling metabolic inference with targeted metagenomics and an improved collection of completed genomes could be a powerful way to analyze microbial communities in a high-throughput manner that provides direct access to metabolic and ecosystem function

Denitrification potential of the eastern oyster microbiome using a 16S rRNA gene based metabolic inference approach

The eastern oyster (Crassostrea virginica) is a foundation species providing significant ecosystem services. However, the roles of oyster microbiomes have not been integrated into any of the services, particularly nitrogen removal through denitrification. We investigated the composition and denitrification potential of oyster microbiomes with an approach that combined 16S rRNA gene analysis, metabolic inference, qPCR of the nitrous oxide reductase gene (nosZ), and N-2 flux measurements. Microbiomes of the oyster digestive gland, the oyster shell, and sediments adjacent to the oyster reef were examined based on next generation sequencing (NGS) of 16S rRNA gene amplicons. Denitrification potentials of the microbiomes were determined by metabolic inferences using a customized denitrification gene and genome database with the paprica (PAthway PRediction by phylogenetIC plAcement) bioinformatics pipeline. Denitrification genes examined included nitrite reductase (nirS and nirK) and nitrous oxide reductase (nosZ), which was further subdivided by genotype into clade I (nosZI) or clade II (nosZII). Continuous flow through experiments measuring N-2 fluxes were conducted with the oysters, shells, and sediments to compare denitrification activities. Paprica properly classified the composition of microbiomes, showing similar classification results from Silva, Greengenes and RDP databases. Microbiomes of the oyster digestive glands and shells were quite different from each other and from the sediments. The relative abundance of denitrifying bacteria inferred by paprica was higher in oysters and shells than in sediments suggesting that oysters act as hotspots for denitrification in the marine environment. Similarly, the inferred nosZI gene abundances were also higher in the oyster and shell microbiomes than in the sediment microbiome. Gene abundances for nosZI were verified with qPCR of nosZI genes, which showed a significant positive correlation (F-1,F-7 = 14.7, p = 6.0x10(-3), R-2 = 0.68). N-2 flux rates were significantly higher in the oyster (364.4 +/- 23.5 mu mol N-N-2 m(-2) h(-1)) and oyster shell (355.3 +/- 6.4 mu mol N-N-2 m(-2) h(-1)) compared to the sediment (270.5 +/- 20.1 mu mol N-N-2 m(-2) h(-1)). Thus, bacteria carrying nosZI genes were found to be an important denitrifier, facilitating nitrogen removal in oyster reefs. In addition, this is the first study to validate the use of 16S gene based metabolic inference as a method for determining microbiome function, such as denitrification, by comparing inference results with qPCR gene quantification and rate measurements

Effect of chlortetracycline on Salmonella and the fecal flora of swine

The goals of this study were to determine the impact of sub-therapeutic chlortetracycline in market swine diets on 1) the prevalence and antimicrobial resistance of Salmonella enterica 2) antimicrobial resistance of the aerobic Gram negative fecal flora. There was no significant difference in the prevalence or antimicrobial resistance of S. enterica isolates. For the gram-negative fecal flora, there was a statistically significant difference (p\u3c0.05) between treatment groups for the frequency of antimicrobial resistance in the gram negative flora with pigs receiving chlortetracycline having a greater frequency of isolates resistant tetracycline, gentamicin, and ceftriaxone, and a lesser proportion of isolates resistant to ampicillin

Wolverine, Gulo gulo, Home Range Size and Denning Habitat in Lowland Boreal Forest in Ontario

We conducted the first radio-telemetry study of Wolverines in northwestern Ontario during the winter of 2003-2004 to determine whether home ranges and movements of Wolverines in lowland boreal forest were typical of this species in other ecosystems and to describe reproductive den sites in this habitat type. Seven Wolverines (3 M, 4 F) were radio-tagged and monitored for 31 to 269 (Mean ± SE = 153 ± 35) days using a combination of remotely monitored Argos satellite and conventional aerial telemetry. Male and female 95% minimum convex polygon (MCP) home ranges (±SE) during December to October were 2,563 (796) km2 and 428 (118) km2, respectively, for combined VHF and Argos locations. A lactating female had a 95% MCP home range of 262 km2. The den site for this female included large boulders and downed trees, similar to dens described for this species in montane ecosystems. Boulder complexes and downed trees may be critical features of wolverine dens in lowland boreal forests. Mean road densities (± SE) within 95% MCP and 50% MCP home ranges were 0.43 (0.13) and 0.33 (0.23) km/km2, respectively, and our results suggest that road densities may affect selection of home ranges by Wolverines. The Wolverine population was a resident, reproductive population. Erratum for table included

Modeling polar marine ecosystem functions guided by bacterial physiological and taxonomic traits

Heterotrophic marine bacteria utilize organic carbon for growth and biomass synthesis. Thus, their physiological variability is key to the balance between the production and consumption of organic matter and ultimately particle export in the ocean. Here we investigate a potential link between bacterial traits and ecosystem functions in the rapidly warming West Antarctic Peninsula (WAP) region based on a bacteria-oriented ecosystem model. Using a data assimilation scheme, we utilize the observations of bacterial groups with different physiological traits to constrain the group-specific bacterial ecosystem functions in the model. We then examine the association of the modeled bacterial and other key ecosystem functions with eight recurrent modes representative of different bacterial taxonomic traits. Both taxonomic and physiological traits reflect the variability in bacterial carbon demand, net primary production, and particle sinking flux. Numerical experiments under perturbed climate conditions demonstrate a potential shift from low nucleic acid bacteria to high nucleic acid bacteria-dominated communities in the coastal WAP. Our study suggests that bacterial diversity via different taxonomic and physiological traits can guide the modeling of the polar marine ecosystem functions under climate change

Ecosystem Service Supply in the Antarctic Peninsula Region: Evaluating an Expert-Based Assessment Approach and a Novel Seascape Data Model

The Southern Ocean and coastal Antarctica provide a variety of ecosystem services with benefits for humankind that are of regional and global importance. Despite being nearly uninhabited, increasing exploitation of natural resources, a growing human presence, and environmental change threaten the sustained provisioning of these services. Ecosystem service assessments have proven as a suitable tool to understand the relevance of ecosystems for human well-being and guide decision-making, but the fluid and transboundary nature of marine ecosystems poses challenges to analyzing ecosystem services in regions with large marine sections. New methods to objectively assess the supply of ecosystem services for such realms are needed, and this need is exemplified by the Antarctic Peninsula region which encompasses rich marine, coastal, and terrestrial ecosystems but faces growing impacts and needs for taking action. In this study we applied the matrix method, an expert-based approach that employs a tabular matrix of ecosystem services and service providing units (SPUs) to elicit expert knowledge and rate the actual supply of key ecosystems services from the Antarctic Peninsula region. Further, we tested the applicability of this method on conventional definitions of SPUs and on objectively defined physico-chemical seascape units for a subset of the study region. Our results show high variations in the estimated supply of ecosystem services for the Antarctic Peninsula region, both with respect to the applied data models and in terms of the assessed service