Culture-independent molecular analysis of bacterial diversity in uranium-ore/-mine waste-contaminated and non-contaminated sites from uranium mines

Soil, water and sediment samples collected from in and around Jaduguda, Bagjata and Turamdih mines were analyzed for physicochemical parameters and cultured, and yet to be cultured microbial diversity. Culturable fraction of microbial community measured as Colony Forming Unit (CFU) on R2A medium revealed microbes between 104 and 109 CFU/g sample. Community DNA was extracted from all the samples; 16S rRNA gene amplified, cloned and subject to Amplified Ribosomal DNA Restriction Analysis. Clones representing each OTU were selected and sequenced. Sequence analyses revealed that non-contaminated samples were mostly represented by Acidobacteria, Bacteroidetes, Firmicutes and Proteobacteria (β-, γ-, and/or δ-subdivisions) along with less frequent phyla Nitrospira, Deferribacteres, Chloroflexi. In contrast, samples obtained from highly contaminated samples showed distinct abundance of β-,γ- and α-Proteobacteria along with Acidobacteria,Bacteroidetes and members of Firmicutes, Chloroflexi, Candidate division, Planctomycete, Cyanobacteria and Actinobacteria as minor groups. Our data represented the baseline information on bacterial community composition within non-contaminated samples which could potentially be useful for assessing the impact of metal and radionuclides contamination due to uranium mine activities

Pyrosequencing-Based Assessment of Bacterial Community Structure Along Different Management Types in German Forest and Grassland Soils

BACKGROUND: Soil bacteria are important drivers for nearly all biogeochemical cycles in terrestrial ecosystems and participate in most nutrient transformations in soil. In contrast to the importance of soil bacteria for ecosystem functioning, we understand little how different management types affect the soil bacterial community composition. METHODOLOGY/PRINCIPAL FINDINGS: We used pyrosequencing-based analysis of the V2-V3 16S rRNA gene region to identify changes in bacterial diversity and community structure in nine forest and nine grassland soils from the Schwäbische Alb that covered six different management types. The dataset comprised 598,962 sequences that were affiliated to the domain Bacteria. The number of classified sequences per sample ranged from 23,515 to 39,259. Bacterial diversity was more phylum rich in grassland soils than in forest soils. The dominant taxonomic groups across all samples (>1% of all sequences) were Acidobacteria, Alphaproteobacteria, Actinobacteria, Betaproteobacteria, Deltaproteobacteria, Gammaproteobacteria, and Firmicutes. Significant variations in relative abundances of bacterial phyla and proteobacterial classes, including Actinobacteria, Firmicutes, Verrucomicrobia, Cyanobacteria, Gemmatimonadetes and Alphaproteobacteria, between the land use types forest and grassland were observed. At the genus level, significant differences were also recorded for the dominant genera Phenylobacter, Bacillus, Kribbella, Streptomyces, Agromyces, and Defluviicoccus. In addition, soil bacterial community structure showed significant differences between beech and spruce forest soils. The relative abundances of bacterial groups at different taxonomic levels correlated with soil pH, but little or no relationships to management type and other soil properties were found. CONCLUSIONS/SIGNIFICANCE: Soil bacterial community composition and diversity of the six analyzed management types showed significant differences between the land use types grassland and forest. Furthermore, bacterial community structure was largely driven by tree species and soil pH

Korarchaeota Diversity, Biogeography, and Abundance in Yellowstone and Great Basin Hot Springs and Ecological Niche Modeling Based on Machine Learning

Over 100 hot spring sediment samples were collected from 28 sites in 12 areas/regions, while recording as many coincident geochemical properties as feasible (>60 analytes). PCR was used to screen samples for Korarchaeota 16S rRNA genes. Over 500 Korarchaeota 16S rRNA genes were screened by RFLP analysis and 90 were sequenced, resulting in identification of novel Korarchaeota phylotypes and exclusive geographical variants. Korarchaeota diversity was low, as in other terrestrial geothermal systems, suggesting a marine origin for Korarchaeota with subsequent niche-invasion into terrestrial systems. Korarchaeota endemism is consistent with endemism of other terrestrial thermophiles and supports the existence of dispersal barriers. Korarchaeota were found predominantly in >55°C springs at pH 4.7–8.5 at concentrations up to 6.6×106 16S rRNA gene copies g−1 wet sediment. In Yellowstone National Park (YNP), Korarchaeota were most abundant in springs with a pH range of 5.7 to 7.0. High sulfate concentrations suggest these fluids are influenced by contributions from hydrothermal vapors that may be neutralized to some extent by mixing with water from deep geothermal sources or meteoric water. In the Great Basin (GB), Korarchaeota were most abundant at spring sources of pH<7.2 with high particulate C content and high alkalinity, which are likely to be buffered by the carbonic acid system. It is therefore likely that at least two different geological mechanisms in YNP and GB springs create the neutral to mildly acidic pH that is optimal for Korarchaeota. A classification support vector machine (C-SVM) trained on single analytes, two analyte combinations, or vectors from non-metric multidimensional scaling models was able to predict springs as Korarchaeota-optimal or sub-optimal habitats with accuracies up to 95%. To our knowledge, this is the most extensive analysis of the geochemical habitat of any high-level microbial taxon and the first application of a C-SVM to microbial ecology

BIOELECTRICAL IMPEDANCE ANALYSIS VERSUS SKINFOLD CALIPERS BODY FAT PERCENTAGE MEASUREMENTS IN AMERICAN FOOTBALL PLAYERS

Michelle L. OtteƗ1, Lucas K. ShrumƗ1, Kelly D. BarnsƗ1, Kurt W. McDowellǂ1, Chelsey R. Geggǂ1, Ryan D. Napoliǂ1, Ryan J. Johnsonǂ1, Jeremy T. Barnesǂ1, Thomas J. Pujolǂ1, FACSM, & Jason D. Wagganerǂ1, 1Southeast Missouri State University, Cape Girardeau, MO Bioelectrical impedance (BIA) and skinfold (SKF) measurements are commonly used to assess body fat percentage (BF%) (i.e., fat vs. lean mass). There are many different quick and cost efficient methods of estimating body fat via BIA (i.e., hand held equipment such as the OMRON Fat Loss Monitor HBF-306C) or SKF (i.e., Lange SKF calipers). BIA and SKF calipers report similar accuracy ranges (i.e., +3.5%) if used by a trained technician and the subject has a normal hydration status. Other factors that can affect the accuracy of SKF assessments include lack of training and poor technique, incorrect site location, and/or an overly obese or extremely lean participant. Both methods of measurement are used in various field settings such as collegiate athletics due to reliability, ease of use, and affordability. PURPOSE: The purpose of this study was to compare college-aged American Football players BF% as measured by the OMRON Fat Loss Monitor HBF-306C compared to that estimated using Lange SKF calipers and the Jackson and Pollock formula. METHODS: Each participant (male=88; age=19.78+1.30 yrs; wt=105.82+22.82 kg; ht=183.67+6.20 cm) had BF% assessed, in the early morning, via the OMRON Fat Loss Monitor HBF-306C (in the Athletic mode) in the standing position. Body density was calculated based on measurements taken at three sites (i.e., chest, abdominal and thigh) using Lange SKF calipers. Then an ethnically appropriate equation was used to convert body density to body fat percent. RESULTS: A paired samples t-test indicated the OMRON Fat Loss Monitor HBF-306C BF% (18.50+6.50) was significantly higher than the Lange SKF calipers BF% (16.81+6.74) (p=.001). CONCLUSIONS: While the two modes of BF% were significantly different, they were within the manufacturer stated accuracy range. While the exact reason for this difference is unknown, some factors could be related to the bilateral (i.e., both hands) measurement via BIA compared to the unilateral (i.e., right side only) measurements taken by the calipers, hydration status, extremely high or low body fat, and/or human error. More research needs to be done comparing different modes of BF% amongst an athletic population

Energy landscapes shape microbial communities in hydrothermal systems on the Arctic Mid-Ocean Ridge

Methods developed in geochemical modelling combined with recent advances in molecular microbial ecology provide new opportunities to explore how microbial communities are shaped by their chemical surroundings. Here, we present a framework for analyses of how chemical energy availability shape chemotrophic microbial communities in hydrothermal systems through an investigation of two geochemically different basalt-hosted hydrothermal systems on the Arctic Mid-Ocean Ridge: the Soria Moria Vent field (SMVF) and the Loki’s Castle Vent Field (LCVF). Chemical energy landscapes were evaluated through modelling of the Gibbs energy from selected redox reactions under different mixing ratios between seawater and hydrothermal fluids. Our models indicate that the sediment-influenced LCVF has a much higher potential for both anaerobic and aerobic methane oxidation, as well as aerobic ammonium and hydrogen oxidation, than the SMVF. The modelled energy landscapes were used to develop microbial community composition models, which were compared with community compositions in environmental samples inside or on the exterior of hydrothermal chimneys, as assessed by pyrosequencing of partial 16S rRNA genes. We show that modelled microbial communities based solely on thermodynamic considerations can have a high predictive power and provide a framework for analyses of the link between energy availability and microbial community composition

Uncultured archaea in deep marine subsurface sediments: have we caught them all?

Deep marine subsurface sediments represent a novel archaeal biosphere with unknown physiology; the sedimentary subsurface harbors numerous novel phylogenetic lineages of archaea that are at present uncultured. Archaeal 16S rRNA analyses of deep subsurface sediments demonstrate their global occurrence and wide habitat range, including deep subsurface sediments, methane seeps and organic-rich coastal sediments. These subsurface archaeal lineages were discovered by PCR of extracted environmental DNA; their detection ultimately depends on the specificity of the archaeal PCR 16S rRNA primers. Surprisingly high mismatch frequencies for some archaeal PCR primers result in amplification bias against the corresponding archaeal lineages; this review presents some examples. Obviously, most archaeal 16S rRNA PCR primers were developed either before the discovery of these deep subsurface archaeal lineages, or without taking their sequence variants into account. PCR surveys with multiple primer combinations, revision and updates of primers whenever possible, and increasing use of PCR-independent methods in molecular microbial ecology will contribute to a more comprehensive view of subsurface archaeal communities