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Low-temperature antihydrogen atoms are an effective tool to probe the validity of the fundamental laws of Physics, for example the Weak Equivalence Principle (WEP) for antimatter, and -generally speaking- it is obvious that colder atoms will increase the level of precision. After the first production of cold antihydrogen in 2002 [1], experimental efforts have substantially progressed, with really competitive results already reached by adapting to cold antiatoms some well-known techniques pre- viously developed for ordinary atoms. Unfortunately, the number of antihydrogen atoms that can be produced in dedicated experiments is many orders of magnitude smaller than of hydrogen atoms, so the development of novel techniques to enhance the production of antihydrogen with well defined (and possibly controlled) conditions is essential to improve the sensitivity. We present here some experimental results achieved by the AEgIS Collaboration, based at the CERN AD (Antiproton Decelerator) on the production of antihydrogen in a pulsed mode where the production time of 90% of atoms is known with an uncertainty of ~ 250 ns [2]. The pulsed antihydrogen source is generated by the charge-exchange reaction between Rydberg positronium (Ps*) and an antiproton (p¯): p¯ + Ps* → H¯* + e−, where Ps* is produced via the implantation of a pulsed positron beam into a mesoporous silica target, and excited by two consecutive laser pulses, and antiprotons are trapped, cooled and manipulated in Penning-Malmberg traps. The pulsed production (which is a major milestone for AEgIS) makes it possible to select the antihydrogen axial temperature and opens the door for the tuning of the antihydrogen Rydberg states, their de-excitation by pulsed lasers and the manipulation through electric field gradients. In this paper, we present the results achieved by AEgIS in 2018, just before the Long Shutdown 2 (LS2), as well as some of the ongoing improvements to the system, aimed at exploiting the lower energy antiproton beam from ELENA [3].

The oscillation continuum in laser-induced fluorescence spectra of bound-free c3Σ+ → a3Σ+ and (4)1Σ+ → X1Σ+ transitions of the KCs molecule was recorded by a Fourier-transform spectrometer and modeled under the adiabatic approximation. The required interatomic potentials for ground a3Σ+ and X1Σ+ states were reconstructed in an analytical Chebyshev-polynomial-expansion form in the framework of the regularization direct-potential-fit procedure based on the simultaneous consideration of experimental line positions from Ferber et al. [Phys. Rev. A 80, 062501 (2009)] and the present ab initio calculation of short-range repulsive potential data. It was proved that the repulsive part over the dissociation limit of the derived a3Σ+ potential reproduces the experiment better than the potentials reported in the literature. It is also shown that all empirical and semi-empirical potentials available for the X1Σ+ state reproduce the bound-free (4)1Σ+ → X1Σ+ spectrum with equal quality in the range of observations. [ABSTRACT FROM AUTHOR]

We report on laser cooling of a large fraction of positronium (Ps) in free flight by strongly saturating the 1^{3}S-2^{3}P transition with a broadband, long-pulsed 243 nm alexandrite laser. The ground state Ps cloud is produced in a magnetic and electric field-free environment. We observe two different laser-induced effects. The first effect is an increase in the number of atoms in the ground state after the time Ps has spent in the long-lived 2^{3}P states. The second effect is one-dimensional Doppler cooling of Ps, reducing the cloud's temperature from 380(20) to 170(20) K. We demonstrate a 58(9)% increase in the fraction of Ps atoms with v&#95;{1D}<3.7×10^{4}  ms^{-1}.

The growth and activity of bacteria have been extensively studied in nearly every environment on Earth, but there have been limited studies focusing on the air. Suspended bacteria (outside of water droplets) may stay in the atmosphere for time frames that could allow for growth on volatile compounds, including the potent greenhouse gas methane. We investigated the ability of aerosolized methanotrophic bacteria to grow on methane in the airborne state in rotating gas-phase bioreactors. The physical half-life of the aerial bacterium-sized particles was 3 days. To assess the potential for airborne growth, gas-phase bioreactors containing the aerosolized cultures were amended with 1,500 ppmv 13 CH 4 or 12 CH 4 . Three of seven experiments demonstrated 13 C incorporation into DNA, indicating growth in air. Bacteria associated with the genera Methylocystis and Methylocaldum were detected in 13 C-DNA fractions, thus indicating that they were synthesizing new DNA, suggesting growth in air. We conclude that methanotrophs outside of water droplets in the air can potentially grow under certain conditions. Based on our data, humidity seems to be a major limitation to bacterial growth in air. Furthermore, low biomass levels can pose problems for detecting 13 C-DNA synthesis in our experimental system. IMPORTANCE Currently, the cellular activities of bacteria in the airborne state outside of water droplets have not been heavily studied. Evidence suggests that these airborne bacteria produce ribosomes and metabolize gaseous compounds. Despite having a potentially important impact on atmospheric chemistry, the ability of bacteria in the air to metabolize substrates such as methane is not well understood. Demonstrating that bacteria in the air can metabolize and grow on substrates will expand knowledge about the potential activities and functions of the atmospheric microbiome. This study provides evidence for DNA synthesis and, ultimately, growth of airborne methanotrophs.

Microbial communities inhabiting the acid mine drainage (AMD) have been extensively studied, but the microbial communities in the coal mining waste dump that may generate the AMD are still relatively under-explored. In this study, we characterized the microbial communities within these under-explored extreme habitats and compared with those in the downstream AMD creek. In addition, the interplay between the microbiota and the environmental parameters was statistically investigated. A Random Forest ensemble model indicated that pH was the most important environmental parameter influencing microbial community and diversity. Parameters associated with nitrogen cycling were also critical factors, with positive effects on microbial diversity, while S-related parameters had negative effects. The microbial community analysis also indicated that the microbial assemblage was driven by pH. Various taxa were enriched in different pH ranges: Sulfobacillus was the indicator genus in samples with pH < 3 while Acidobacteriaceae-affiliated bacteria prevailed in samples with 3 < pH < 3.5. The detection of some lineages that are seldom reported in mining areas suggested the coal mining dumps may be a reservoir of phylogenetic novelty. For example, potential nitrogen fixers, autotrophs, and heterotrophs may form diverse communities that actively self-perpetuate pyrite dissolution and acidic waste generation, suggesting unique ecological strategies adopted by these innate microorganisms. In addition, co-occurrence network analyses suggest that members of Acidimicrobiales play important roles in interactions with other taxa, especially Fe- and S-oxidizing bacteria such as Sulfobacillus spp.

Iron (Fe) plaque on rice roots contains a unique microbiota that connects the root and rhizosphere environments. However, the factors controlling the microbial community structure and function in Fe plaque are unknown. We performed Illumina sequencing of 16S rRNA gene amplicons and of total community DNA to compare the microbial community structure and metabolic potential of Fe plaques derived from arsenic (As)- and non-contaminated sites. Geobacter and Hydrogenophaga were identified as the genera that differed significantly in abundance between As-contaminated and control samples (P < 0.05). Significant differences were found between contaminated and control samples in the relative abundances of predicted As functional genes of the microbial community in Fe plaque, in which the relative abundances of the arsC (encoding As(V) reductase) and arsB genes (encoding As(III) efflux membrane protein) in Fe plaque from contaminated sites (YH and TP samples) were significantly higher than those from the control samples (P < 0.05). In addition, the As concentration in Fe plaque contributed significantly to the relative abundance of genes related to As metabolism and correlated most strongly with the abundance of arrB genes (encoding respiratory arsenate reductase, FeS subunit). These results suggest that As contamination influences the community structure and metabolic potential of Fe plaque-associated microorganisms and may help in understanding the environmental behavior of As at the interface of Fe plaque., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Sediments of combined sewers are seeded with microbes from a variety of sources, and experience varying biogeochemical conditions. A variety of redox processes have been demonstrated to occur within sewer systems, as well as transformation of several recalcitrant xenobiotic contaminants. Illumina sequencing of the 16S ribosomal RNA gene from sediments of three combined sewer systems in the northeastern United States resulted in 10 000 to 47 000 operational taxonomic units per sample. Whereas orders Clostridiales and Bacteroidales, considered human fecal indicators, were dominant in one city's sediments; other cities had communities suggestive of diverse redox processes, including reductive dechlorination of chlorinated organic compounds. Collection systems previously associated with polychlorinated biphenyl (PCB) biotransformation, and those with elevated in situ PCB concentrations, had high abundances of Dehalococcoidetes. The results suggest that wastewater collection systems have intrinsic passive treatment capacity, reducing contaminant loads on water resource recovery facilities and, ultimately, on receiving waters.

In this study, we sampled rhizosphere soils from seven different agricultural fields adjacent to mining areas and cultivated with different crops (corn, rice, or soybean), to study the interactions among the innate microbiota, soil chemical properties, plants, and metal contamination. The rhizosphere bacterial communities were characterized by Illumina sequencing of the 16S rRNA genes, and their interactions with the local environments, including biotic and abiotic factors, were analyzed. Overall, these soils were heavily contaminated with multiple metal(loid)s, including V, Cr, Cu, Sb, Pb, Cd, and As. The interactions between environmental parameters and microbial communities were identified using multivariate regression tree analysis, canonical correspondence analysis, and network analysis. Notably, metal-microbe interactions were observed to be crop specific. The rhizosphere communities were strongly correlated with V and Cr levels, although these sites were contaminated from Sb and Zn/Pb mining, suggesting that these two less-addressed metals may play important roles in shaping the rhizosphere microbiota. Members of Gaiellaceae cooccurred with other bacterial taxa (biotic interactions) and several metal(loid)s, suggesting potential metal(loid) resistance or cycling involving this less-well-known taxon. IMPORTANCE The rhizosphere is the "hub" for plant-microbe interactions and an active region for exchange of nutrients and energy between soil and plants. In arable soils contaminated by mining activities, the rhizosphere may be an important barrier resisting metal uptake. Therefore, the responses of the rhizosphere microbiota to metal contamination involve important biogeochemical processes, which can affect metal bioavailability and thus impact food safety. However, understanding these processes remains a challenge. The current study illustrates that metal-microbe interactions may be crop specific and some less-addressed metals, such as V and Cr, may play important roles in shaping bacterial communities. The current study provides new insights into metal-microbe interactions and contributes to future implementation and monitoring efforts in contaminated arable soils., (Copyright © 2018 American Society for Microbiology.)

Microorganisms inhabiting mine tailings require specific metabolic strategies to survive, which may hold potential for pollution clean up. Effective in situ bioremediation will rely on an in-depth understanding of the function of the bacterial communities, especially the abundant and metabolically active phylotypes. In this study, the bacterial communities collected from an alkaline tailing site were profiled by 16S rRNA gene amplicon sequencing as well as shotgun metagenomic analysis. Our results indicated that potentials for carbon and nitrogen fixation as well as metal resistance and transformation were widespread among the bacterial community members, especially in highly enriched phylotypes, such as members of Thiobacillus and Meiothermus. Important functional microbial guilds including carbon and nitrogen fixers may contribute to phytoremediation by providing nutrients for hyperaccumulator plants. In addition, metal-metabolizing bacteria may influence metal speciation and solubility. This discovery provides an understanding for microbial survival strategies in the tailings and lays the foundation for future potential manipulation of the tailing microbiome for in situ bioremediation.

Chlorinated benzenes are common groundwater contaminants in the United States, so demonstrating whether they undergo degradation in the subsurface is important in determining the best remedy for this contamination. The purpose of this work was to use a new data mining approach to investigate chlorinated benzene degradation pathways in the subsurface. Positive Matrix Factorization (PMF) was used to analyze long-term measurements of chlorinated benzene concentrations in groundwater at a contaminated site in New Jersey. A dataset containing 597 groundwater samples and 5 chlorinated benzenes and benzene collected from 144 wells over 20 years was investigated using PMF2 software. Despite the heterogeneity of this dataset, PMF analysis revealed patterns indicative of microbial dechlorination in the groundwater and provided insight about where dechlorination is occurring, to what extent, and under which geochemical conditions. PMF resolved a factor indicative of a source of 1,2,4-trichlorobenzene and 1,2-dichlorobenzene and two factors representing stages of dechlorination, one more advanced than the other. The PMF results indicated that virtually all of the 1,2-dichlorobenzene at the site arises from its use onsite, not from the dechlorination of trichlorobenzenes. Factors were further interpreted using ancillary data such as geochemical indicators and field parameters also measured in the samples. Analysis suggested that the partial and advanced dechlorination signals occur under different subsurface physical conditions. The results provided field validation of the current understanding of anaerobic dechlorination of chlorinated benzenes in the subsurface developed from laboratory studies. PMF is thereby shown to be a useful tool for investigating chlorinated benzene dechlorination., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

A limited number of studies have been conducted to analyze ribosomal RNA (rRNA, present in the ribosome) in bioaerosol samples to identify currently or potentially active airborne microbes, although its genomic counterpart, the rRNA gene (on the chromosome) has been frequently targeted for airborne microbial community analysis. A knowledge gap still exists regarding whether the bioaerosol rRNA abundances are affected by the bioaerosol collection process. We investigated the effect of air sampling stress on the measurement and characterization of 16S rRNA for bioaerosols in the laboratory and field experiments using quantitative polymerase chain reaction (qPCR) and high-throughput sequencing techniques. In a laboratory study, known quantities of freshly grown Escherichia coli cells were spiked onto the filter of a Button Aerosol Sampler and into liquids of BioSampler and SpinCon air samplers and then exposed to sampling stress when the samplers were operated for 2h. We found that the recovered cellular 16S rRNA abundance as determined by qPCR was dependent on sampler type. Further, two devices (Button Aerosol Sampler and BioSampler) that exhibited markedly different efficiency in preserving 16S rRNA were employed in an outdoor environment to collect bioaerosols simultaneously on eight days in two different seasons. The abundance of 16S rRNA in the outdoor air sample (1.3×10 6 -4.9×10 7 copies/m 3 ) was about two orders of magnitude higher than that of 16S rRNA gene (6.9×10 3 -1.5×10 5 copies/m 3 ). The 16S rRNA sequences revealed a different bacterial community compared with 16S rRNA gene-based results across all samples, and this difference depended on the sampling device. In addition, a number of bacterial taxa exhibited higher abundance in the 16S rRNA gene sequences than in 16S rRNA sequences, which suggests the potential activities of certain microbes in airborne phase. Overall, this study highlights the importance of sampling device selection when analyzing RNA in bioaerosols., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Rice paddies are a significant source of the greenhouse gas methane, which mainly originates from microbial activity. Methane generation in anaerobic systems involves complex interactions of multiple functional microbial groups. Rice paddies installed in hilly terrain are often terraced, providing multiple quasi-independent plots differing primarily in their elevation up a hillside. This represents an excellent study site to explore the influence of environmental factors on microbial communities and interactions among microbial populations. In this study, we used a combination of geochemical analyses, high-throughput amplicon sequencing, and statistical methods to elucidate these interactions. Sulfate, total nitrogen, total iron, and total organic carbon were determined to be critical factors in steering the ecosystem composition and function. Sulfate-reducing bacteria predominated in the rice terrace microbial communities, and Fe(III)-reducing and methane-oxidizing bacteria were abundant as well. Biotic interactions indicated by co-occurrence network analysis suggest mutualistic interactions among these three functional groups. Paddy-scale methane production may be affected by competition among methanogens and sulfate- and Fe(III)-reducing bacteria, or by direct methane oxidation by methane-oxidizing bacteria., Capsule: Microbial communities were characterized in rice terrace. The environment- and microbe-microbe interactions indicated the mitigation of sulfate and Fe on methane production., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Anaerobic digestion is a complicated microbiological process that involves a wide diversity of microorganisms. Acetate is one of the most important intermediates, and interactions between acetate-oxidizing bacteria and archaea could play an important role in the formation of methane in anoxic environments. Anaerobic digestion at thermophilic temperatures is known to increase methane production, but the effects on the microbial community are largely unknown. In the current study, stable isotope probing was used to characterize acetate- and lactate-oxidizing bacteria in thermophilic anaerobic digestion. In microcosms fed 13 C-acetate, bacteria related to members of Clostridium, Hydrogenophaga, Fervidobacterium, Spirochaeta, Limnohabitans, and Rhodococcus demonstrated elevated abundances of 13 C-DNA fractions, suggesting their activities in acetate oxidation. In the treatments fed 13 C-lactate, Anaeromyxobacter, Desulfobulbus, Syntrophus, Cystobacterineae, and Azospira were found to be the potential thermophilic lactate utilizers. PICRUSt predicted that enzymes related to nitrate and nitrite reduction would be enriched in 13 C-DNA fractions, suggesting that the acetate and lactate oxidation may be coupled with nitrate and/or nitrite reduction. Co-occurrence network analysis indicated bacterial taxa not enriched in 13 C-DNA fractions that may also play a critical role in thermophilic anaerobic digestion.

Mining of sulfide ore deposits containing metalloids, such as antimony and arsenic, has introduced serious soil contamination around the world, posing severe threats to food safety and human health. Hence, it is important to understand the behavior and composition of the microbial communities that control the mobilization or sequestration of these metal(loid)s. Here, we selected two sites in Southwest China with different levels of Sb and As contamination to study interactions among various Sb and As fractions and the soil microbiota, with a focus on the microbial response to metalloid contamination. Comprehensive geochemical analyses and 16S rRNA gene amplicon sequencing demonstrated distinct soil taxonomic inventories depending on Sb and As contamination levels. Stochastic gradient boosting indicated that citric acid extractable Sb(V) and As(V) contributed 5% and 15%, respectively, to influencing the community diversity. Random forest predicted that low concentrations of Sb(V) and As(V) could enhance the community diversity but generally, the Sb and As contamination impairs microbial diversity. Co-occurrence network analysis indicated a strong correlation between the indigenous microbial communities and various Sb and As fractions. A number of taxa were identified as core genera due to their elevated abundances and positive correlation with contaminant fractions (total Sb and As concentrations, bioavailable Sb and As extractable fractions, and Sb and As redox species). Shotgun metagenomics indicated that Sb and As biogeochemical redox reactions may exist in contaminated soils. All these observations suggest the potential for bioremediation of Sb- and As-contaminated soils.

Investigation of microbial communities of soils contaminated by antimony (Sb) and arsenic (As) is necessary to obtain knowledge for their bioremediation. However, little is known about the depth profiles of microbial community composition and structure in Sb and As contaminated soils. Our previous studies have suggested that historical factors (i.e., soil and sediment) play important roles in governing microbial community structure and composition. Here, we selected two different types of soil (flooded paddy soil versus dry corn field soil) with co-contamination of Sb and As to study interactions between these metalloids, geochemical parameters and the soil microbiota as well as microbial metabolism in response to Sb and As contamination. Comprehensive geochemical analyses and 16S rRNA amplicon sequencing were used to shed light on the interactions of the microbial communities with their environments. A wide diversity of taxonomical groups was present in both soil cores, and many were significantly correlated with geochemical parameters. Canonical correspondence analysis (CCA) and co-occurrence networks further elucidated the impact of geochemical parameters (including Sb and As contamination fractions and sulfate, TOC, Eh, and pH) on vertical distribution of soil microbial communities. Metagenomes predicted from the 16S data using PICRUSt included arsenic metabolism genes such as arsenate reductase (ArsC), arsenite oxidase small subunit (AoxA and AoxB), and arsenite transporter (ArsA and ACR3). In addition, predicted abundances of arsenate reductase (ArsC) and arsenite oxidase (AoxA and AoxB) genes were significantly correlated with Sb contamination fractions, These results suggest potential As biogeochemical cycling in both soil cores and potentially dynamic Sb biogeochemical cycling as well., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

A small watershed heavily contaminated by long-term acid mine drainage (AMD) from an upstream abandoned coal mine was selected to study the microbial community developed in such extreme system. The watershed consists of AMD-contaminated creek, adjacent contaminated soils, and a small cascade aeration unit constructed downstream, which provide an excellent contaminated site to study the microbial response in diverse extreme AMD-polluted environments. The results showed that the innate microbial communities were dominated by acidophilic bacteria, especially acidophilic Fe-metabolizing bacteria, suggesting that Fe and pH are the primary environmental factors in governing the indigenous microbial communities. The distribution of Fe-metabolizing bacteria showed distinct site-specific patterns. A pronounced shift from diverse communities in the upstream to Proteobacteria-dominated communities in the downstream was observed in the ecosystem. This location-specific trend was more apparent at genus level. In the upstream samples (sampling sites just below the coal mining adit), a number of Fe(II)-oxidizing bacteria such as Alicyclobacillus spp., Metallibacterium spp., and Acidithrix spp. were dominant, while Halomonas spp. were the major Fe(II)-oxidizing bacteria observed in downstream samples. Additionally, Acidiphilium, an Fe(III)-reducing bacterium, was enriched in the upstream samples, while Shewanella spp. were the dominant Fe(III)-reducing bacteria in downstream samples. Further investigation using linear discriminant analysis (LDA) effect size (LEfSe), principal coordinate analysis (PCoA), and unweighted pair group method with arithmetic mean (UPGMA) clustering confirmed the difference of microbial communities between upstream and downstream samples. Canonical correspondence analysis (CCA) and Spearman's rank correlation indicate that total organic carbon (TOC) content is the primary environmental parameter in structuring the indigenous microbial communities, suggesting that the microbial communities are shaped by three major environmental parameters (i.e., Fe, pH, and TOC). These findings were beneficial to a better understanding of natural attenuation of AMD.

To assess the impact of antimony (Sb) on microbial community structure, 12 samples were taken from an Sb tailings pile in Guizhou Province, Southwest China. All 12 samples exhibited elevated Sb concentrations, but the mobile and bioaccessible fractions were small in comparison to total Sb concentrations. Besides the geochemical analyses, microbial communities inhabiting the tailing samples were characterized to investigate the interplay between the microorganisms and environmental factors in mine tailings. In all samples, Proteobacteria and Actinobacteria were the most dominant phyla. At the genus level, Thiobacillus, Limnobacter, Nocardioides, Lysobacter, Phormidium, and Kaistobacter demonstrated relatively high abundances. The two most abundant genera, Thiobacillus and Limnobacter, are characterized as sulfur-oxidizing bacteria and thiosulfate-oxidizing bacteria, respectively, while the genus Lysobacter contains arsenic (As)-resistant bacteria. Canonical correspondence analysis (CCA) indicates that TOC and the sulfate to sulfide ratio strongly shaped the microbial communities, suggesting the influence of the environmental factors in the indigenous microbial communities.

An on-site field-scale bioreactor for passive treatment of antimony (Sb) contamination was installed downstream of an active Sb mine in Southwest China, and operated for one year (including a six month monitoring period). This bioreactor consisted of five treatment units, including one pre-aerobic cell, two aerobic cells, and two microaerobic cells. With the aerobic cells inoculated with indigenous mine water microflora, the bioreactor removed more than 90% of total soluble Sb and 80% of soluble antimonite (Sb(III)). An increase in pH and decrease of oxidation-reduction potential (Eh) was also observed along the flow direction. High-throughput sequencing of the small subunit ribosomal RNA (SSU rRNA) gene variable (V4) region revealed that taxonomically diverse microbial communities developed in the bioreactor. Metal (loid)-oxidizing bacteria including Ferrovum, Thiomonas, Gallionella, and Leptospirillum, were highly enriched in the bioreactor cells where the highest total Sb and Sb(III) removal occurred. Canonical correspondence analysis (CCA) indicated that a suite of in situ physicochemical parameters including pH and Eh were substantially correlated with the overall microbial communities. Based on an UPGMA (Unweighted Pair Group Method with Arithmetic Mean) tree and PCoA (Principal Coordinates Analysis), the microbial composition of each cell was distinct, indicating these in situ physicochemical parameters had an effect in shaping the indigenous microbial communities. Overall, this study was the first to employ a field-scale bioreactor to treat Sb-rich mine water onsite and, moreover, the findings suggest the feasibility of the bioreactor in removing elevated Sb from mine waters., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Mining activities have introduced various pollutants to surrounding aquatic and terrestrial environments, causing adverse impacts to the environment. Indigenous microbial communities are responsible for the biogeochemical cycling of pollutants in diverse environments, indicating the potential for bioremediation of such pollutants. Antimony (Sb) has been extensively mined in China and Sb contamination in mining areas has been frequently encountered. To date, however, the microbial composition and structure in response to Sb contamination has remained overlooked. Sb and As frequently co-occur in sulfide-rich ores, and co-contamination of Sb and As is observed in some mining areas. We characterized, for the first time, the microbial community profiles and their responses to Sb and As pollution from a watershed heavily contaminated by Sb tailing pond in Southwest China. The indigenous microbial communities were profiled by high-throughput sequencing from 16 sediment samples (535,390 valid reads). The comprehensive geochemical data (specifically, physical-chemical properties and different Sb and As extraction fractions) were obtained from river water and sediments at different depths as well. Canonical correspondence analysis (CCA) demonstrated that a suite of in situ geochemical and physical factors significantly structured the overall microbial community compositions. Further, we found significant correlations between individual phylotypes (bacterial genera) and the geochemical fractions of Sb and As by Spearman rank correlation. A number of taxonomic groups were positively correlated with the Sb and As extractable fractions and various Sb and As species in sediment, suggesting potential roles of these phylotypes in Sb biogeochemical cycling., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Located in Southwest China, the Chahe watershed has been severely contaminated by upstream active antimony (Sb) mines. The extremely high concentrations of Sb make the Chahe watershed an excellent model to elucidate the response of indigenous microbial activities within a severe Sb-contaminated environment. In this study, water and surface sediments from six locations in the Chahe watershed with different levels of Sb contamination were analyzed. Illumina sequencing of 16S rRNA amplicons revealed more than 40 phyla from the domain Bacteria and 2 phyla from the domain Archaea. Sequences assigned to the genera Flavobacterium, Sulfuricurvum, Halomonas, Shewanella, Lactobacillus, Acinetobacter, and Geobacter demonstrated high relative abundances in all sequencing libraries. Spearman's rank correlations indicated that a number of microbial phylotypes were positively correlated with different speciation of Sb, suggesting potential roles of these phylotypes in microbial Sb cycling. Canonical correspondence analysis further demonstrated that geochemical parameters, including water temperature, pH, total Fe, sulfate, aqueous Sb, and Eh, significantly structured the overall microbial community in Chahe watershed samples. Our findings offer a direct and reliable reference to the diversity of microbial communities in the presence of extremely high Sb concentrations, and may have potential implications for in situ bioremediation strategies of Sb contaminated sites., (Copyright © 2016 Elsevier B.V. All rights reserved.)

We present a one-dimensional reactive transport model to estimate benthic fluxes of dissolved inorganic carbon (DIC) and alkalinity (AT) from coastal marine sediments. The model incorporates the transport processes of sediment accumulation, molecular diffusion, bioturbation and bioirrigation, while the reactions included are the redox pathways of organic carbon oxidation, re-oxidation of reduced nitrogen, iron and sulfur compounds, pore water acid-base equilibria, and dissolution of particulate inorganic carbon (calcite, aragonite, and Mg-calcite). The coastal zone is divided into four environmental units with different particulate inorganic carbon (PIC) and particulate organic carbon (POC) fluxes: reefs, banks and bays, carbonate shelves and non-carbonate shelves. Model results are analyzed separately for each environment and then scaled up to the whole coastal ocean. The model-derived estimate for the present-day global coastal benthic DIC efflux is 126 Tmolyr-1 , based on a global coastal reactive POC depositional flux of 117 Tmolyr-1. The POC decomposition leads to a carbonate dissolution from shallow marine sediments of 7 Tmolyr-1 (on the order of 0.1 PgCyr-1). Assuming complete re-oxidation of aqueous sulfide released from sediments, the effective net flux of alkalinity to the water column is 29 Teqyr-1 , primarily from PIC dissolution (46 %) and ammonification (33%). Because our POC depositional flux falls in the high range of global values given in the literature, the reported DIC and alkalinity fluxes should be viewed as upper-bound estimates. Increasing coastal seawater DIC to what might be expected in year 2100 due to the uptake of anthropogenic CO2 increases PIC dissolution by 2.3 Tmolyr-1 and alkalinity eflux by 4.8 Teqyr-1. Our reactive transport modeling approach not only yields global estimates of benthic DIC, alkalinity and nutrient fluxes under variable scenarios of ocean productivity and chemistry, but also provides insights into the underlying processes. [ABSTRACT FROM AUTHOR]

Accurate enumeration of rRNA content in microbial cells, e.g. by using the 16S rRNA:16S rRNA gene ratio, is critical to properly understand its relationship to microbial activities. However, few studies have considered possible methodological artifacts that may contribute to the variability of rRNA analysis results. In this study, a technique utilizing genomic DNA and 16S rRNA from an exogenous species (Pseudomonas fluorescens) as dual internal references was developed to improve accuracy when determining the 16S rRNA:16S rRNA gene ratio of a target organism, Escherichia coli. This technique was able to adequately control the variability in sample processing and analysis procedures due to nucleic acid (DNA and RNA) losses, inefficient reverse transcription of RNA, and inefficient PCR amplification. The measured 16S rRNA:16S rRNA gene ratio of E. coli increased by 2-3 fold when E. coli 16S rRNA gene and 16S rRNA quantities were normalized to the sample-specific fractional recoveries of reference (P. fluorescens) 16S rRNA gene and 16S rRNA, respectively. In addition, the intra-sample variation of this ratio, represented by coefficients of variation from replicate samples, decreased significantly after normalization. This technique was applied to investigate the temporal variation of 16S rRNA:16S rRNA gene ratio of E. coli during its non-steady-state growth in a complex liquid medium, and to E. coli aerosols when exposed to particle-free air after their collection on a filter. The 16S rRNA:16S rRNA gene ratio of E. coli increased significantly during its early exponential phase of growth; when E. coli aerosols were exposed to extended filtration stress after sample collection, the ratio also increased. In contrast, no significant temporal trend in E. coli 16S rRNA:16S rRNA gene ratio was observed when the determined ratios were not normalized based on the recoveries of dual references. The developed technique could be widely applied in studies of relationship between cellular rRNA abundance and bacterial activity., (Copyright © 2015 Elsevier B.V. All rights reserved.)

Established theory addresses the idea that herbivory can have positive feedbacks on nutrient flow to plants. Positive feedbacks likely emerge from a greater availability of organic carbon that primes the soil by supporting nutrient turnover through consumer and especially microbially-mediated metabolism in the detrital pool. We developed an entirely novel stoichiometric model that demonstrates the mechanism of a positive feedback. In particular, we show that sloppy or partial feeding by herbivores increases detrital carbon and nitrogen allowing for greater nitrogen mineralization and nutritive feedback to plants. The model consists of differential equations coupling flows among pools of: plants, herbivores, detrital carbon and nitrogen, and inorganic nitrogen. We test the effects of different levels of herbivore grazing completion and of the stoichiometric quality (carbon to nitrogen ratio, C:N) of the host plant. Our model analyses show that partial feeding and plant C:N interact because when herbivores are sloppy and plant biomass is diverted to the detrital pool, more mineral nitrogen is available to plants because of the stoichiometric difference between the organisms in the detrital pool and the herbivore. This model helps to identify how herbivory may feedback positively on primary production, and it mechanistically connects direct and indirect feedbacks from soil to plant production.

The Portland Harbor (Oregon, USA) has been declared a "Superfund" site because it is impacted by a variety of contaminants, including polychlorinated biphenyls (PCBs) and polychlorinated dibenzo-p-dioxins and -furans (PCDD/Fs). Using data collected in the remedial investigation, concentrations of PCBs and PCDD/Fs in sediment and water were examined using positive matrix factorization to look for evidence that PCBs and PCDD/Fs are dechlorinated by anaerobic bacteria. This process has long been known to occur in sediments. Recently, it has been recognized that PCB and PCDD/F dechlorination may also occur in other anaerobic environments, such as in landfills, sewers, and groundwater. The results indicate that a factor related to the dechlorination of PCBs and PCDD/Fs was present in the water but not in the sediment. Spatial patterns in dechlorination products suggest that they come primarily from groundwater. Dechlorination products comprise 22% of the PCBs in the water. The Portland Harbor therefore represents the third major US watershed in which PCBs appear to undergo dechlorination in an environment other than sediment, suggesting that the microbial dechlorination of PCBs and PCDD/Fs is more common than previously assumed. In addition, the Portland Harbor is impacted by PCBs generated inadvertently during the production of pigments, such as PCB 11, which alone exceeded the 64 pg/L federal water quality standard for the sum of PCBs in two of 120 whole water samples.

Elevation is one of the most influential factors affecting soil characteristics and microbial communities in forest ecosystems. Nevertheless, there is no consensus on how soil characteristics, soil microbials, and their relationships response to the elevation of the mountain ecosystem. We investigated the soil physicochemical characteristics, the activity of soil enzymes, and the microbial community at elevational sites from 600 to 2400 m above sea level (asl) in the western slopes of the Fanjing Mountain ecosystem, China. The soil microbial communities were determined by high throughput 16S rRNA and ITS amplicon sequencing. The results demonstrated that soil total nitrogen (TN) showed a slight decrease, whereas total phosphorus (TP) and total potassium (TK) gradually tended to increase with increasing elevation. The large macroaggregates (>2 mm) accounted for the largest proportion of the aggregate fraction (66.23%–76.13%) in the 0–10 cm soil layer with elevation. The average values of the soil electrical conductivity (EC), soil organic carbon (SOC), and cation exchange capacity (CEC) concentration in the 0–60 cm layer undulated with increasing elevation, and the highest values were observed at 1500–1800 m asl and 1800–2100 m asl, respectively. The activities of soil urease, sucrase, acid phosphatase, and catalase clearly differed (p < 0.05) with increasing elevation, and the minimum values were found at 2100–2400 m asl. Interesting, with increasing soil depth, the values of these factors tended to decrease, indicating surface aggregation. In addition, the soil microbial (bacterial and fungal) community diversity exhibited a single-peak pattern with elevation. Our results also revealed that the soil bacterial and fungal communities varied significantly at different elevation sites. The bacterial communities were dominated by the phyla Acidobacteria, Pseudomonadota, and Chloroflexi, and the phyla Basidiomycota and Ascomycota dominated the fungal communities. The Pearson and redundancy analyses revealed that the SOC, TP, four soil enzymes, and soil aggregates were significant factors influencing the soil microbial community. In conclusion, soil properties and enzyme activities jointly explained the elevational pattern of the soil microbial community in the Fanjing Mountain. The results of this study provide insights into the influence of elevation on soil characteristics, microbial communities, and their relationships in the Fanjing Mountain ecosystem. [ABSTRACT FROM AUTHOR]

Soil cadmium (Cd) contamination in agriculture has intensified due to industrial development and human activities, which seriously affected the safety production in wheat. There are increasing evidences that rhizosphere bacteria contributed to alleviating Cd stress in plants, but the mechanism of how rhizosphere bacteria affecting the adaptive growth of wheat exposed to Cd contamination has not been extensively explored. Therefore, the rhizosphere bacterial community dynamics and plant growth for wheat were investigated under different levels of soil Cd contamination in accordance with risk control standard for soil contamination of agricultural land. The results showed that there was no significant difference in transport coefficient of Cd in wheat plants grown in different levels of soil Cd contamination conditions. Soil Cd contamination led to a decrease in soil pH value and an increase in exchangeable Cd content in rhizosphere soil. Although rhizosphere bacterial richness and diversity had no significant difference between soil Cd contamination conditions, as its community composition changed significantly. Under Cd contamination of risk screening value, Actinobacteria, Chloroflexi, and Nitrospira showed higher abundance, but Bacteroidetes, Patescibacteria, Sphingomonas, ADurbBin063-1 and Bryobacter were more prevalent under Cd contamination of risk intervention value. The enrichment of Patescibacteria, Proteobacteria and Acidobacteria was beneficial for Cd fixation, while Nitrospira enhanced nutrient uptake and utilization. Furthermore, Cd contamination with risk screening value enhanced the relationship among rhizosphere bacterial communities, and Cd contamination with risk intervention value increased the cooperative relationship among rhizosphere bacterial species. Additionally, soil Cd content showed a significantly positive correlation with Patescibacteria and ADurbBin063-1, and a significantly negative correlation with pH. Altogether, the shift in the community structures of rhizosphere bacterial was crucial for farmland protection and food safety in Cd polluted soil. [ABSTRACT FROM AUTHOR]

We performed Monte Carlo simulations of batch transformations of hydrophobic compounds using typical numbers of data points, extent of reaction, and measurement error, to identify the most appropriate biotransformation model to describe such data under different conditions. Highly hydrophobic compounds such as polychlorinated biphenyls (PCBs) and dioxins present special challenges for parameterization due to low environmental concentrations and slow biotransformation rates, which result in high sample variability, few samples, and limited substrate concentration range. Four models of varying complexity (zero-order, first-order, Monod, and Best) were fit to simulated data. Various combinations of initial concentration ( S 0 ), half saturation concentration ( K S ), maximum substrate utilization rate ( q max ), measurement error, number of data points per batch run, and extent of biotransformation were simulated. One thousand Monte-Carlo runs were performed for each parameter combination, and AIC c (Akaike's information criterion corrected for small numbers of data points) was used to determine the most appropriate model. Neither the Best model nor the zero-order model ever produced the lowest AIC c for a majority of simulations under any combination of test conditions. With 10% measurement error, the first-order model always outperformed the others. In the case of 1% measurement error with 10 evenly-spaced data points, the Monod model was the better choice when S 0 > K S and the system was not mass transfer limited [Formula: see text] otherwise, the first-order model was indicated. S 0 is constrained by the compound's aqueous solubility; therefore, for highly hydrophobic compounds such as PCBs or polychlorinated dibenzo- p -dioxins and dibenzofurans, a first-order model is likely to fit batch biotransformation data as well or better than a more complicated model.