299 research outputs found

    Using the class 1 integron-integrase gene as a proxy for anthropogenic pollution

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    This is the final version of the article. Available from the publisher via the DOI in this record.Around all human activity, there are zones of pollution with pesticides, heavy metals, pharmaceuticals, personal care products and the microorganisms associated with human waste streams and agriculture. This diversity of pollutants, whose concentration varies spatially and temporally, is a major challenge for monitoring. Here, we suggest that the relative abundance of the clinical class 1 integron-integrase gene, intI1, is a good proxy for pollution because: (1) intI1 is linked to genes conferring resistance to antibiotics, disinfectants and heavy metals; (2) it is found in a wide variety of pathogenic and nonpathogenic bacteria; (3) its abundance can change rapidly because its host cells can have rapid generation times and it can move between bacteria by horizontal gene transfer; and (4) a single DNA sequence variant of intI1 is now found on a wide diversity of xenogenetic elements, these being complex mosaic DNA elements fixed through the agency of human selection. Here we review the literature examining the relationship between anthropogenic impacts and the abundance of intI1, and outline an approach by which intI1 could serve as a proxy for anthropogenic pollution.MRG is supported by the Australian Research Council, AP is supported by the Alfred P Sloan Foundation Microbiology of the Built Environment program and the National Science Foundation RAPID award no. 1402651, KS is supported by the Deutsche Forschungsgemeinschaft (DFG) funding the Research Unit FOR 566 ‘Veterinary Medicines in Soil: Basic Research for Risk Analysis’ (Grant No. SM59/5-3) and by the Umweltbundesamt (3713 63 402), JMT is supported by the US National Science Foundation and Y-GZ is supported by the National Science Foundation of China

    Tundra soil carbon is vulnerable to rapid microbial decomposition under climate warming

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    Microbial decomposition of soil carbon in high-latitude tundra underlain with permafrost is one of the most important, but poorly understood, potential positive feedbacks of greenhouse gas emissions from terrestrial ecosystems into the atmosphere in a warmer world. Using integrated metagenomic technologies, we showed that the microbial functional community structure in the active layer of tundra soil was significantly altered after only 1.5 years of warming, a rapid response demonstrating the high sensitivity of this ecosystem to warming. The abundances of microbial functional genes involved in both aerobic and anaerobic carbon decomposition were also markedly increased by this short-term warming. Consistent with this, ecosystem respiration (R eco) increased up to 38%. In addition, warming enhanced genes involved in nutrient cycling, which very likely contributed to an observed increase (30%) in gross primary productivity (GPP). However, the GPP increase did not offset the extra R eco, resulting in significantly more net carbon loss in warmed plots compared with control plots. Altogether, our results demonstrate the vulnerability of active-layer soil carbon in this permafrost-based tundra ecosystem to climate warming and the importance of microbial communities in mediating such vulnerability

    Global Change Could Amplify Fire Effects on Soil Greenhouse Gas Emissions

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    Background: Little is known about the combined impacts of global environmental changes and ecological disturbances on ecosystem functioning, even though such combined impacts might play critical roles in shaping ecosystem processes that can in turn feed back to climate change, such as soil emissions of greenhouse gases.[br/] Methodology/Principal Findings: We took advantage of an accidental, low-severity wildfire that burned part of a long-term global change experiment to investigate the interactive effects of a fire disturbance and increases in CO(2) concentration, precipitation and nitrogen supply on soil nitrous oxide (N(2)O) emissions in a grassland ecosystem. We examined the responses of soil N(2)O emissions, as well as the responses of the two main microbial processes contributing to soil N(2)O production - nitrification and denitrification - and of their main drivers. We show that the fire disturbance greatly increased soil N(2)O emissions over a three-year period, and that elevated CO(2) and enhanced nitrogen supply amplified fire effects on soil N(2)O emissions: emissions increased by a factor of two with fire alone and by a factor of six under the combined influence of fire, elevated CO(2) and nitrogen. We also provide evidence that this response was caused by increased microbial denitrification, resulting from increased soil moisture and soil carbon and nitrogen availability in the burned and fertilized plots. [br/] Conclusions/Significance: Our results indicate that the combined effects of fire and global environmental changes can exceed their effects in isolation, thereby creating unexpected feedbacks to soil greenhouse gas emissions. These findings highlight the need to further explore the impacts of ecological disturbances on ecosystem functioning in the context of global change if we wish to be able to model future soil greenhouse gas emissions with greater confidence

    Denitrification and nitrous oxide emissions from riparian forests soils exposed to prolonged nitrogen runoff

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    Compared to upland forests, riparian forest soils have greater potential to remove nitrate (NO3) from agricultural run-off through denitrification. It is unclear, however, whether prolonged exposure of riparian soils to nitrogen (N) loading will affect the rate of denitrification and its end products. This research assesses the rate of denitrification and nitrous oxide (N2O) emissions from riparian forest soils exposed to prolonged nutrient run-off from plant nurseries and compares these to similar forest soils not exposed to nutrient run-off. Nursery run-off also contains high levels of phosphate (PO4). Since there are conflicting reports on the impact of PO4 on the activity of denitrifying microbes, the impact of PO4 on such activity was also investigated. Bulk and intact soil cores were collected from N-exposed and non-exposed forests to determine denitrification and N2O emission rates, whereas denitrification potential was determined using soil slurries. Compared to the non-amended treatment, denitrification rate increased 2.7- and 3.4-fold when soil cores collected from both N-exposed and non-exposed sites were amended with 30 and 60 μg NO3-N g-1 soil, respectively. Net N2O emissions were 1.5 and 1.7 times higher from the N-exposed sites compared to the non-exposed sites at 30 and 60 μg NO3-N g-1 soil amendment rates, respectively. Similarly, denitrification potential increased 17 times in response to addition of 15 μg NO3-N g-1 in soil slurries. The addition of PO4 (5 μg PO4–P g-1) to soil slurries and intact cores did not affect denitrification rates. These observations suggest that prolonged N loading did not affect the denitrification potential of the riparian forest soils; however, it did result in higher N2O emissions compared to emission rates from non-exposed forests

    Evaluating amplified rDNA restriction analysis assay for identification of bacterial communities

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    Amplified ribosomal DNA restriction analysis (ARDRA) and restriction fragment length polymorphism were originally used for strain typing and for screening clone libraries to identify phylogenetic clusters within a microbial community. Here we used ARDRA as a model to examine the capacity of restriction-based techniques for clone identification, and the possibility of deriving phylogenetic information from ARDRA-based dendrograms. ARDRA was performed in silico on 48,759 sequences from the Ribosomal Database Project, and it was found that the fragmentation profiles were not necessarily unique for each sequence in the database, resulting in different species sharing fragmentation profiles. Although ARDRA-based clusters separated clones into different genera, these phylogenetic clusters did not overlap with trees constructed according to sequence alignment, calling into question the intra-genus ARDRA-based phylogeny. It is thus suggested that the prediction power of ARDRA clusters in identifying clone phylogeny be regarded with caution

    Time-course analysis of the Shewanella amazonensis SB2B proteome in response to sodium chloride shock

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    Shewanellae are microbial models for environmental stress response; however, the sequential expression of mechanisms in response to stress is poorly understood. Here we experimentally determine the response mechanisms of Shewanella amazonensis SB2B during sodium chloride stress using a novel liquid chromatography and accurate mass-time tag mass spectrometry time-course proteomics approach. The response of SB2B involves an orchestrated sequence of events comprising increased signal transduction associated with motility and restricted growth. Following a metabolic shift to branched chain amino acid degradation, motility and cellular replication proteins return to pre-perturbed levels. Although sodium chloride stress is associated with a change in the membrane fatty acid composition in other organisms, this is not the case for SB2B as fatty acid degradation pathways are not expressed and no change in the fatty acid profile is observed. These findings suggest that shifts in membrane composition may be an indirect physiological response to high NaCl stress

    Integrating Flux Balance Analysis into Kinetic Models to Decipher the Dynamic Metabolism of Shewanella oneidensis MR-1

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    Shewanella oneidensis MR-1 sequentially utilizes lactate and its waste products (pyruvate and acetate) during batch culture. To decipher MR-1 metabolism, we integrated genome-scale flux balance analysis (FBA) into a multiple-substrate Monod model to perform the dynamic flux balance analysis (dFBA). The dFBA employed a static optimization approach (SOA) by dividing the batch time into small intervals (i.e., ∼400 mini-FBAs), then the Monod model provided time-dependent inflow/outflow fluxes to constrain the mini-FBAs to profile the pseudo-steady-state fluxes in each time interval. The mini-FBAs used a dual-objective function (a weighted combination of “maximizing growth rate” and “minimizing overall flux”) to capture trade-offs between optimal growth and minimal enzyme usage. By fitting the experimental data, a bi-level optimization of dFBA revealed that the optimal weight in the dual-objective function was time-dependent: the objective function was constant in the early growth stage, while the functional weight of minimal enzyme usage increased significantly when lactate became scarce. The dFBA profiled biologically meaningful dynamic MR-1 metabolisms: 1. the oxidative TCA cycle fluxes increased initially and then decreased in the late growth stage; 2. fluxes in the pentose phosphate pathway and gluconeogenesis were stable in the exponential growth period; and 3. the glyoxylate shunt was up-regulated when acetate became the main carbon source for MR-1 growth
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