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Identification of microbes that actively utilize root exudates is essential to understand plant-microbe interactions. To identify active root exudate-utilizing microorganisms associated with switchgrass - a potential bioenergy crop - plants were labelled in situ with (13) CO2 , and 16S and 18S rRNA genes in the (13) C-labelled rhizosphere DNA were pyrosequenced. Multi-pulse labelling for 5 days produced detectable (13) C-DNA, which was well separated from unlabelled DNA. Methylibium from the order Burkholderiales were the most heavily labelled bacteria. Pythium, Auricularia and Galerina were the most heavily labelled eukaryotic microbes. We also identified a Glomus intraradices-like species; Glomus members are arbuscular mycorrhizal fungi that are able to colonize the switchgrass root. All of these heavily labelled microorganisms were also among the most abundant species in the rhizosphere. Species belonging to Methylibium and Pythium were the most heavily labelled and the most abundant bacteria and eukaryotes in the rhizosphere of switchgrass. Our results revealed that nearly all of the dominant rhizosphere bacterial and eukaryotic microbes were able to utilize root exudates. The enrichment of microbial species in the rhizosphere is selective and mostly due to root exudation, which functions as a nutrition source, promoting the growth of these microbes.

Increasingly, funding agencies are investing in integrated and transdisciplinary research to tackle “grand challenge” priority areas, critical for sustaining agriculture and protecting the envi -ronment. Coordinating multidisciplinary research teams capable of addressing these priority areas, however, presents its own unique set of chal-lenges, ranging from bridging across multiple dis -ciplinary perspectives to achieve common ques-tions and methods to facilitating engagement in holistic and integrative thinking that promotes linkages from scholarship to societal needs. We propose that structural equation modeling (SEM) can provide a powerful framework for synergizing multidisciplinary research teams around grand challenge issues. Structural equation modeling can integrate both visual and statistical expres-sion of complex hypotheses at all stages of the research process, from planning to analysis. Three elements of the SEM framework are par-ticularly beneficial to multidisciplinary research teams; these include (i) a common graphical lan-guage that transcends disciplinary boundaries, (ii) iterative, critical evaluation of complex hypoth -eses involving manifest and latent variables and direct and indirect interactions, and (iii) enhanced opportunities to discover unanticipated interac-tions or causal pathways as empirical data are tested statistically against the model. Using our ongoing multidisciplinary, multisite field inves-tigation of climate change adaptation and miti-gation in annual row crop agroecosystems as a case study, we demonstrate the value of the SEM framework for project design, coordination, and implementation and provide recommendations for its broader application as a means to more effectively engage and address issues of critical societal concern.R.G. Smith, L.W. Atwood, A.B. Daly, and A.S. Grandy, Dep. of Natural Resources and the Environment, Univ. of New Hampshire, Durham, NH 03824; A.S. Davis, USDA-ARS Global Change and Photosynthesis Research Unit, Urbana, IL 61801; N.R. Jordan and P. Ewing, Dep. of Agronomy and Plant Genetics, Univ. of Minnesota, St. Paul, MN 55108; M.C. Hunter, and D.A. Mortensen, Dep. of Plant Science, The Pennsylvania State Univ., University Park, PA 16802; R.T. Koide, Dep. of Biology, Brigham Young Univ., Provo, UT 84602; D. Kane and S.S. Snapp, Dep. of Plant, Soil and Microbial Sciences, Michigan State Univ., East Lansing, MI 48824; M. Li, Dep. of Crop Sciences, Univ. of Illinois, Urbana, IL 61801; Y. Lou and A.C. Yannarell, Dep. of Natural Resources and Environmental Sciences, Univ. of Illinois, Urbana, IL 61801; K.A. Spokas, USDA-ARS Soil and Water Management Research Unit, St. Paul, MN 55108. Received 19 July 2013. *Corresponding author (richard.smith@unh.edu).

A low-diversity microbial community, dominated by the γ-proteobacterium Halomonas sulfidaeris, was detected in samples of warm saline formation porewater collected from the Cambrian Mt. Simon Sandstone in the Illinois Basin of the North American Midcontinent (1.8 km/5872 ft burial depth, 50°C, pH 8, 181 bars pressure). These highly porous and permeable quartz arenite sandstones are directly analogous to reservoirs around the world targeted for large-scale hydrocarbon extraction, as well as subsurface gas and carbon storage. A new downhole low-contamination subsurface sampling probe was used to collect in situ formation water samples for microbial environmental metagenomic analyses. Multiple lines of evidence suggest that this H. sulfidaeris-dominated subsurface microbial community is indigenous and not derived from drilling mud microbial contamination. Data to support this includes V1-V3 pyrosequencing of formation water and drilling mud, as well as comparison with previously published microbial analyses of drilling muds in other sites. Metabolic pathway reconstruction, constrained by the geology, geochemistry and present-day environmental conditions of the Mt. Simon Sandstone, implies that H. sulfidaeris-dominated subsurface microbial community may utilize iron and nitrogen metabolisms and extensively recycle indigenous nutrients and substrates. The presence of aromatic compound metabolic pathways suggests this microbial community can readily adapt to and survive subsurface hydrocarbon migration.

Summary Biomass production for bioenergy may change soil microbes and influence ecosystem properties. To explore the impact of different bioenergy cropping systems on soil microorganisms, the compositions and quantities of soil microbial communities (16S rRNA gene) and N-cycling functional groups (nifH, bacterial amoA, archaeal amoA and nosZ genes) were assessed under maize, switchgrass and Miscanthus x giganteus at seven sites representing a climate gradient (precipitation and temperature) in Illinois, USA. Overall, the site-to-site variation in community composition surpassed the variation due to plant type, and microbial communities under each crop did not converge on a ‘typical’ species assemblage. Fewer than 5% of archaeal amoA, bacterial amoA, nifH and nosZ OTUs were significantly different among these crops, but the largest differences observed at each site were found between maize and the two perennial grasses. Quantitative PCR revealed that the abundance of the nifH gene was significantly higher in the perennial grasses than in maize, and we also found significantly higher total N in the perennial grass soils than in maize. Thus, we conclude that cultivation of these perennial grasses, instead of maize, as bioenergy feedstocks can improve soil ecosystem nitrogen sustainability by increasing the population size of N-fixing bacteria.

Antibiotics are used in animal livestock production for therapeutic treatment of disease and at subtherapeutic levels for growth promotion and improvement of feed efficiency. It is estimated that approximately 75% of antibiotics are not absorbed by animals and are excreted in waste. Antibiotic resistance selection occurs among gastrointestinal bacteria, which are also excreted in manure and stored in waste holding systems. Land application of animal waste is a common disposal method used in the United States and is a means for environmental entry of both antibiotics and genetic resistance determinants. Concerns for bacterial resistance gene selection and dissemination of resistance genes have prompted interest about the concentrations and biological activity of drug residues and break-down metabolites, and their fate and transport. Fecal bacteria can survive for weeks to months in the environment, depending on species and temperature, however, genetic elements can persist regardless of cell viability. Phylogenetic analyses indicate antibiotic resistance genes have evolved, although some genes have been maintained in bacteria before the modern antibiotic era. Quantitative measurements of drug residues and levels of resistance genes are needed, in addition to understanding the environmental mechanisms of genetic selection, gene acquisition, and the spatiotemporal dynamics of these resistance genes and their bacterial hosts. This review article discusses an accumulation of findings that address aspects of the fate, transport, and persistence of antibiotics and antibiotic resistance genes in natural environments, with emphasis on mechanisms pertaining to soil environments following land application of animal waste effluent.

Disturbance and recovery influence microbial community structure and ecosystem functions in most natural environments. This study from a hypersaline Bahamian lagoon details the response of a benthic cyanobacterial mat to disturbance by Hurricane Frances, a category-4 storm. Clone libraries of cyanobacterial small subunit r-RNA genes and nitrogenase genes revealed significant shifts in cyanobacterial and diazotroph community composition following the hurricane. Post-hurricane clone libraries were dominated by sequences that had been rare in pre-hurricane communities. In spite of this dominance shift, re-colonizing mat communities performed nitrogen fixation and photosynthesis at rates within the normal range of variation measured in the mat at similar salinities. There was a tendency for nitrogen fixation rates from mats re-colonizing sites with hurricane-related sand deposition to be higher than those from mats re-colonizing sites without significant sand deposition. This suggests that the altered communities responded to a carbon : nitrogen imbalance that was particularly pronounced in areas subjected to disturbance by sand burial. The post-hurricane dominance of organisms that had been previously rare suggests that pre-hurricane diversity and functional redundancy contributed to the rapid recovery of ecosystem function in the post-disturbance environment.

Species richness and species diversity of bacterioplankton, phytoplankton and protoplankton were examined in Crystal Bog, a humic lake in northern Wisconsin, as part of an NSF sponsored Microbial Observatory Program. Crystal Bog is part of the North Temperate Lakes Long-Term Ecological Research site. Automated ribosomal intergenic spacer analysis (ARISA) was used to assess bacterial diversity. Phytoplankton and protoplankton were enumerated in a settling chamber with an inverted microscope. Four distinct phases in the ice-free season of the bog can be recognized based on microbial populations. The first phase extends from ice-out until about the first week of April. During this phase three species of dinoflagellates come to dominate the phytoplankton, with Glenodinium quadridens representing 60% of total phytoplankton biovolume. By mid-April the spring dinoflagellate blooms collapse. The second phase is a period of instability as a series of species dominates the phytoplankton. In mid-July dinoflagellates again dominate the third phase, and Peridinium limbatum alone represents 90% of the bog phytoplankton. The fourth phase is a stable period as P. limbatum slowly declines in late summer and fall. A strong correlation was found between bacterial and phytoplankton diversity (Shannon–Weaver Index) in this bog, suggesting the two microbial communities are linked. The protoplankton, however, were relatively uniform throughout the ice-free period. The ice-covered period may be treated as a fifth phase. When snow accumulates over the ice-covered bog, light penetration is blocked and photosynthesis shut off. Heterotrophic protozoa assume dominance in the plankton.