The development and optimization of microbial molecular biomarkers for the in situ assessment of trace metal toxicity

Merged with duplicate record 10026.1/2607 on 06.20.2017 by CS (TIS)Microorganisms are fundamental components of many geochemical transformations occurring in the aquatic environment. Microbial redox and methylation of metals within the environment can alter metal speciation, mobility and ultimately, toxicity to eukaryotes. It is therefore practical that any environmental monitoring framework advocating the application of `early-warning biomarker system' should incorporate a holistic view of the environment beginning with microbial activity. This thesis describes the development of protocols for assessing the in situ condition of microbial ecosystems within a gradient of metal contaminated sites radiating downstream of the Anaconda Smelter, a USEPA-designated superfund site and within two control sites. Experiments focus on evaluating the incidence (i. e. prevalence and absence) of genes related to general stress and specific metal detoxification reactions. Moreover, a number of selected genes were quantified directly from the environment and statistically correlated with metal concentrations. Furthermore, the influence of metals on structuring microbial communities was also investigated by evaluating temporal communities shifts in response to changing metal concentrations using denaturant gradient gel electrophoresis (DGGE). The data recorded the highest prevalence of all genes was found at the most polluted site directly downstream of the Anaconda Smelter. Furthermore, significant correlations were observed between gene prevalence and metals (arsenic, copper and zinc) (P < 0.05) and organic carbon concentration (P < 0.05). A number of genes were successfully amplified from sediment with significantly higher gene copy number (/ ng DNA) at the more polluted sites when compared to corresponding control sites. Examination of community diversity found that long-term metal-contaminated sediments, adjacent to the Smelter, had microbial communities twice as diverse as corresponding reference sites. In addition, multivariate statistical techniques identified factors important to community structuring, concluding that geographic position and localized geochemistry fundamentally influence the structuring of communities. This thesis represents a significant advance in the use of microorganisms as `early warning systems' of deterioration in ecosystem health, while the application of advanced molecular methods facilitates their intergration within a traditional ecotoxicological framework.Montana State Universit

Phylogenetic conservation of soil bacterial responses to simulated global changes.

Soil bacterial communities are altered by anthropogenic drivers such as climate change-related warming and fertilization. However, we lack a predictive understanding of how bacterial communities respond to such global changes. Here, we tested whether phylogenetic information might be more predictive of the response of bacterial taxa to some forms of global change than others. We analysed the composition of soil bacterial communities from perturbation experiments that simulated warming, drought, elevated CO2 concentration and phosphorus (P) addition. Bacterial responses were phylogenetically conserved to all perturbations. The phylogenetic depth of these responses varied minimally among the types of perturbations and was similar when merging data across locations, implying that the context of particular locations did not affect the phylogenetic pattern of response. We further identified taxonomic groups that responded consistently to each type of perturbation. These patterns revealed that, at the level of family and above, most groups responded consistently to only one or two types of perturbations, suggesting that traits with different patterns of phylogenetic conservation underlie the responses to different perturbations. We conclude that a phylogenetic approach may be useful in predicting how soil bacterial communities respond to a variety of global changes. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'

Reactive transport model of sulfur cycling as impacted by perchlorate and nitrate treatments

Microbial souring in oil reservoirs produces toxic, corrosive hydrogen sulfide through microbial sulfate reduction, often accompanying (sea)­water flooding during secondary oil recovery. With data from column experiments as constraints, we developed the first reactive-transport model of a new candidate inhibitor, perchlorate, and compared it with the commonly used inhibitor, nitrate. Our model provided a good fit to the data, which suggest that perchlorate is more effective than nitrate on a per mole of inhibitor basis. Critically, we used our model to gain insight into the underlying competing mechanisms controlling the action of each inhibitor. This analysis suggested that competition by heterotrophic perchlorate reducers and direct inhibition by nitrite produced from heterotrophic nitrate reduction were the most important mechanisms for the perchlorate and nitrate treatments, respectively, in the modeled column experiments. This work demonstrates modeling to be a powerful tool for increasing and testing our understanding of reservoir-souring generation, prevention, and remediation processes, allowing us to incorporate insights derived from laboratory experiments into a framework that can potentially be used to assess risk and design optimal treatment schemes

Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle

Understanding the interactions between microbial communities and their environment sufficiently to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is problematic, because (i) communities are complex, (ii) most descriptions are qualitative, and (iii) quantitative understanding of the way communities interact with their surroundings remains incomplete. One approach to overcoming such complications is the integration of partial qualitative and quantitative descriptions into more complex networks. Here we outline the development of a probabilistic framework, based on Event Transition Graph (ETG) theory, to predict microbial community structure across observed chemical data. Using reverse engineering, we derive probabilities from the ETG that accurately represent observations from experiments and predict putative constraints on communities within dynamic environments. These predictions can feedback into the future development of field experiments by emphasizing the most important functional reactions, and associated microbial strains, required to characterize microbial ecosystems

Arctic tundra shrubification: a review of mechanisms and impacts on ecosystem carbon balance

Vegetation composition shifts, and in particular, shrub expansion across the Arctic tundra are some of the most important and widely observed responses of high-latitude ecosystems to rapid climate warming. These changes in vegetation potentially alter ecosystem carbon balances by affecting a complex set of soil-plant-atmosphere interactions. In this review, we synthesize the literature on (a) observed shrub expansion, (b) key climatic and environmental controls and mechanisms that affect shrub expansion, (c) impacts of shrub expansion on ecosystem carbon balance, and (d) research gaps and future directions to improve process representations in land models. A broad range of evidence, including in-situ observations, warming experiments, and remotely sensed vegetation indices have shown increases in growth and abundance of woody plants, particularly tall deciduous shrubs, and advancing shrublines across the circumpolar Arctic. This recent shrub expansion is affected by several interacting factors including climate warming, accelerated nutrient cycling, changing disturbance regimes, and local variation in topography and hydrology. Under warmer conditions, tall deciduous shrubs can be more competitive than other plant functional types in tundra ecosystems because of their taller maximum canopy heights and often dense canopy structure. Competitive abilities of tall deciduous shrubs vs herbaceous plants are also controlled by variation in traits that affect carbon and nutrient investments and retention strategies in leaves, stems, and roots. Overall, shrub expansion may affect tundra carbon balances by enhancing ecosystem carbon uptake and altering ecosystem respiration, and through complex feedback mechanisms that affect snowpack dynamics, permafrost degradation, surface energy balance, and litter inputs. Observed and projected tall deciduous shrub expansion and the subsequent effects on surface energy and carbon balances may alter feedbacks to the climate system. Land models, including those integrated in Earth System Models, need to account for differences in plant traits that control competitive interactions to accurately predict decadal- to centennial-scale tundra vegetation and carbon dynamics

Hysteresis Patterns of Watershed Nitrogen Retention and Loss Over the Past 50 years in United States Hydrological Basins

Patterns of watershed nitrogen (N) retention and loss are shaped by how watershed biogeochemical processes retain, biogeochemically transform, and lose incoming atmospheric deposition of N. Loss patterns represented by concentration, discharge, and their associated stream exports are important indicators of integrated watershed N retention behaviors. We examined continental United States (CONUS) scale N deposition (e.g., wet and dry atmospheric deposition), vegetation trends, and stream trends as potential indicators of watershed N-saturation and retention conditions, and how watershed N retention and losses vary over space and time. By synthesizing changes and modalities in watershed nitrogen loss patterns based on stream data from 2200 U.S. watersheds over a 50 years record, our work revealed two patterns of watershed N-retention and loss. One was a hysteresis pattern that reflects the integrated influence of hydrology, atmospheric inputs, land-use, stream temperature, elevation, and vegetation. The other pattern was a one-way transition to a new state. We found that regions with increasing atmospheric deposition and increasing vegetation health/biomass patterns have the highest N-retention capacity, become increasingly N-saturated over time, and are associated with the strongest declines in stream N exports—a pattern, that is, consistent across all land cover categories. We provide a conceptual model, validated at an unprecedented scale across the CONUS that links instream nitrogen signals to upstream mechanistic landscape processes. Our work can aid in the future interpretation of in-stream concentrations of DOC and DIN as indicators of watershed N-retention status and integrators of watershed hydrobiogeochemical processes

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using (14)C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of (14)C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)'s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem

Jazz Convocation

Program listing performers and works performed