Search

Because of the extreme conditions of the Deepwater Horizon (DWH) release (turbulent flow at 1500m depth and 5°C water temperature) and the sub-surface application of dispersant, small but neutrally buoyant oil droplets

Molecular microbial community analyses provide information on thousands of microorganisms simultaneously, and integrate biotic and abiotic perturbations caused by fecal contamination entering water bodies. A few studies have explored community methods as emerging approaches for microbial source tracking (MST), however, an evaluation of the current state of this approach is lacking. Here, we utilized three types of community-based methods with 64 blind, single- or dual-source, challenge samples generated from 12 sources, including: humans (feces), sewage, septage, dogs, pigs, deer, horses, cows, chickens, gulls, pigeons, and geese. Each source was a composite from multiple donors from four representative geographical regions in California. Methods evaluated included terminal restriction fragment polymorphism (TRFLP), phylogenetic microarray (PhyloChip), and next generation (Illumina) sequencing. These methods correctly identified dominant (or sole) sources in over 90% of the challenge samples, and exhibited excellent specificity regardless of source, rarely detecting a source that was not present in the challenge sample. Sensitivity, however, varied with source and community analysis method. All three methods distinguished septage from human feces and sewage, and identified deer and horse with 100% sensitivity and 100% specificity. Method performance improved if the composition of blind dual-source reference samples were defined by DNA contribution of each single source within the mixture, instead of by Enterococcus colony forming units. Data analysis approach also influenced method performance, indicating the need to standardize data interpretation. Overall, results of this study indicate that community analysis methods hold great promise as they may be used to identify any source, and they are particularly useful for sources that currently do not have, and may never have, a source-specific single marker gene.

The population of microbes (microbiome) in the intestine is a symbiotic ecosystem conferring trophic and protective functions. Since the biochemical environment shapes the structure and function of the microbiome, we tested whether uremia and/or dietary and pharmacologic interventions in chronic kidney disease alters the microbiome. To identify different microbial populations, microbial DNA was isolated from the stools of 24 patients with end-stage renal disease (ESRD) and 12 healthy persons, and analyzed by phylogenetic microarray. There were marked differences in the abundance of 190 bacterial operational taxonomic units (OTUs) between the ESRD and control groups. OTUs from Brachybacterium, Catenibacterium, Enterobacteriaceae, Halomonadaceae, Moraxellaceae, Nesterenkonia, Polyangiaceae, Pseudomonadaceae, and Thiothrix families were markedly increased in patients with ESRD. To isolate the effect of uremia from inter-individual variations, comorbid conditions, and dietary and medicinal interventions, rats were studied 8 weeks post 5/6 nephrectomy or sham operation. This showed a significant difference in the abundance of 175 bacterial OTUs between the uremic and control animals, most notably as decreases in the Lactobacillaceae and Prevotellaceae families. Thus, uremia profoundly alters the composition of the gut microbiome. The biological impact of this phenomenon is unknown and awaits further investigation.

Globally, tussock-based grasslands are being modified to increase productive capacity. The impacts of cultivation and over-sowing with exotic grass and legumes on soil microbiology were assessed at four sites in New Zealand which differed in soil type, climate and vegetation. Primary alteration of the soil physicochemical status occurred with land use change. This was driven by addition of mineral fertiliser and alteration of pH. Genes associated with several biogeochemical cycles (GeoChip data) were impacted by land-use but not sampling location. A number of functional gene families associated with biogeochemical cycling of C, N and S were present in greater relative abundance in the undisturbed soils. Similarly, soil bacterial (PhyloChip) and fungal (TRFLP) communities were strongly influenced by land-use change, but unaffected by sampling location. Alteration of land-use increased the relative abundance of Firmicutes, Actinobacteria and OD1 phyla, but many of the less-common phyla, such as Verrucomicrobia and Dictyoglomi decreased in abundance; these phyla may be important in internal soil nutrient cycling processes. This work provides evidence that tussock grassland soils are strongly dependent on microbially-mediated nutrient cycling, and these processes are highly-sensitive to exogenous nutrient inputs and/or alteration of pH. De-coupling of processes following addition of fertilisers or removal of organic matter (grazing) may make these improved grassland systems more susceptible to nutrient leakage. This has important implications for environmental quality.

We have developed a Multi-Pathogen Identification (MPID) microarray for high confidence identification of eighteen pathogenic prokaryotes, eukaryotes and viruses. Analysis of amplified products from pathogen genomic DNA using microarray hybridization allows for highly specific and sensitive detection, and allows the discrimination between true amplification products and false positive amplification products that might be derived from primers annealing to non-target sequences. Species-specific primer sets were used to amplify multiple diagnostic regions unique to each individual pathogen. Amplified products were washed over the surface of the microarray, and labelled with phycoerythrin-streptavidin for fluorescence detection. A series of overlapping 20-mer oligonucleotide probes hybridize to the entire diagnostic region, while parallel hybridizations on the same surface allow simultaneous screening for all organisms. Comparison to probes that differ by a single mismatch at the central position reduced the contribution of non-specific hybridization. Samples containing individual pathogens were analyzed in separate experiments and the corresponding species-specific diagnostic regions were identified by fluorescence among their highly redundant probe sets. On average, 91% of the 53 660 pathogen probes on the MPID microarray performed as predicted. The limit of detection was found to be as little as 10 fg of B. anthracis DNA in samples that were amplified with six diagnostic primer-pairs. In contrast, PCR products were not observed at this concentration when identical samples were prepared and visualized by agarose gel electrophoresis.