deepNEC: a novel alignment-free tool for the identification and classification of nitrogen biochemical network-related enzymes using deep learning.

Nitrogen is essential for life and its transformations are an important part of the global biogeochemical cycle. Being an essential nutrient, nitrogen exists in a range of oxidation states from +5 (nitrate) to -3 (ammonium and amino-nitrogen), and its oxidation and reduction reactions catalyzed by microbial enzymes determine its environmental fate. The functional annotation of the genes encoding the core nitrogen network enzymes has a broad range of applications in metagenomics, agriculture, wastewater treatment and industrial biotechnology. This study developed an alignment-free computational approach to determine the predicted nitrogen biochemical network-related enzymes from the sequence itself. We propose deepNEC, a novel end-to-end feature selection and classification model training approach for nitrogen biochemical network-related enzyme prediction. The algorithm was developed using Deep Learning, a class of machine learning algorithms that uses multiple layers to extract higher-level features from the raw input data. The derived protein sequence is used as an input, extracting sequential and convolutional features from raw encoded protein sequences based on classification rather than traditional alignment-based methods for enzyme prediction. Two large datasets of protein sequences, enzymes and non-enzymes were used to train the models with protein sequence features like amino acid composition, dipeptide composition (DPC), conformation transition and distribution, normalized Moreau-Broto (NMBroto), conjoint and quasi order, etc. The k-fold cross-validation and independent testing were performed to validate our model training. deepNEC uses a four-tier approach for prediction; in the first phase, it will predict a query sequence as enzyme or non-enzyme; in the second phase, it will further predict and classify enzymes into nitrogen biochemical network-related enzymes or non-nitrogen metabolism enzymes; in the third phase, it classifies predicted enzymes into nine nitrogen metabolism classes; and in the fourth phase, it predicts the enzyme commission number out of 20 classes for nitrogen metabolism. Among all, the DPC + NMBroto hybrid feature gave the best prediction performance (accuracy of 96.15% in k-fold training and 93.43% in independent testing) with an Matthews correlation coefficient (0.92 training and 0.87 independent testing) in phase I; phase II (accuracy of 99.71% in k-fold training and 98.30% in independent testing); phase III (overall accuracy of 99.03% in k-fold training and 98.98% in independent testing); phase IV (overall accuracy of 99.05% in k-fold training and 98.18% in independent testing), the DPC feature gave the best prediction performance. We have also implemented a homology-based method to remove false negatives. All the models have been implemented on a web server (prediction tool), which is freely available at http://bioinfo.usu.edu/deepNEC/.

Short-Term Nitrogen Fertilization Affects Microbial Community Composition and Nitrogen Mineralization Functions in an Agricultural Soil.

Soil extracellular enzymes play a significant role in the N mineralization process. However, few studies have documented the linkage between enzyme activity and the microbial community that performs the function. This study examined the effects of inorganic and organic N fertilization on soil microbial communities and their N mineralization functions over 4 years. Soils were collected from silage corn field plots with four contrasting N treatments: control (no additional N), ammonium sulfate (AS; 100 and 200 kg of N ha-1), and compost (200 kg of N ha-1). Illumina amplicon sequencing was used to comprehensively assess the overall bacterial community (16S rRNA genes), bacterial ureolytic community (ureC), and bacterial chitinolytic community (chiA). Selected genes involved in N mineralization were also examined using quantitative real-time PCR and metagenomics. Enzymes (and marker genes) included protease (npr and sub), chitinase (chiA), urease (ureC), and arginase (rocF). Compost significantly increased diversity of overall bacterial communities even after one application, while ammonium fertilizers had no influence on the overall bacterial communities over four seasons. Bacterial ureolytic and chitinolytic communities were significantly changed by N fertilization. Compost treatment strongly elevated soil enzyme activities after 4 years of repeated application. Functional gene abundances were not significantly affected by N treatments, and they were not correlated with corresponding enzyme activities. N mineralization genes were recovered from soil metagenomes based on a gene-targeted assembly. Understanding how the structure and function of soil microbial communities involved with N mineralization change in response to fertilization practices may indicate suitable agricultural management practices that improve ecosystem services while reducing negative environmental consequences.IMPORTANCE Agricultural N management practices influence the enzymatic activities involved in N mineralization. However, specific enzyme activities do not identify the microbial species directly involved in the measured process, leaving the link between the composition of the microbial community and the production of key enzymes poorly understood. In this study, the application of high-throughput sequencing, real-time PCR, and metagenomics shed light on how the abundance and diversity of microorganisms involved in N mineralization respond to N management. We suggest that N fertilization has significantly changed bacterial ureolytic and chitinolytic communities.

A Physiological and Genomic Comparison of Nitrosomonas Cluster 6a and 7 Ammonia-Oxidizing Bacteria.

Ammonia-oxidizing bacteria (AOB) within the genus Nitrosomonas perform the first step in nitrification, ammonia oxidation, and are found in diverse aquatic and terrestrial environments. Nitrosomonas AOB were grouped into six defined clusters, which correlate with physiological characteristics that contribute to adaptations to a variety of abiotic environmental factors. A fundamental physiological trait differentiating Nitrosomonas AOB is the adaptation to either low (cluster 6a) or high (cluster 7) ammonium concentrations. Here, we present physiological growth studies and genome analysis of Nitrosomonas cluster 6a and 7 AOB. Cluster 6a AOB displayed maximum growth rates at ≤ 1 mM ammonium, while cluster 7 AOB had maximum growth rates at ≥ 5 mM ammonium. In addition, cluster 7 AOB were more tolerant of high initial ammonium and nitrite concentrations than cluster 6a AOB. Cluster 6a AOB were completely inhibited by an initial nitrite concentration of 5 mM. Genomic comparisons were used to link genomic traits to observed physiological adaptations. Cluster 7 AOB encode a suite of genes related to nitrogen oxide detoxification and multiple terminal oxidases, which are absent in cluster 6a AOB. Cluster 6a AOB possess two distinct forms of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and select species encode genes for hydrogen or urea utilization. Several, but not all, cluster 6a AOB can utilize urea as a source of ammonium. Hence, although Nitrosomonas cluster 6a and 7 AOB have the capacity to fulfill the same functional role in microbial communities, i.e., ammonia oxidation, differentiating species-specific and cluster-conserved adaptations is crucial in understanding how AOB community succession can affect overall ecosystem function.

Live long and prosper: plant-soil feedback, lifespan, and landscape abundance covary.

Plant soil feedbacks (PSFs) are thought to be important to plant growth and species coexistence, but most support for these hypotheses is derived from short-term greenhouse experiments. Here we use a seven-year, common garden experiment to measure PSFs for seven native and six nonnative species common to the western United States. We use these long-term, field-based estimates to test correlations between PSF and plant landscape abundance, species origin, functional type, and lifespan. To assess potential PSF mechanisms, we also measured soil microbial community composition, root biomass, nitrogen cycling, bulk density, penetration resistance, and shear strength. Plant abundance on the landscape and plant lifespan were positively correlated with PSFs, though this effect was due to the relationships for native plants. PSFs were correlated with indices of soil microbial community composition. Soil nutrient and physical traits and root biomass differed among species but were not correlated with PSF. While results must be taken with caution because only 13 species were examined, these species represent most of the dominant plant species in the system. Results suggest that native plant abundance is associated with the ability of long-lived plants to create positive plant-soil microbe interactions, while short-lived nonnative plants maintain dominance by avoiding soil-borne antagonists, increasing nitrogen cycling and dedicating resources to aboveground growth and reproduction rather than to belowground growth. Broadly, results suggest that PSFs are correlated with a suite of traits that determine plant abundance.

Ammonia Oxidizers in a Grazing Land with a History of Poultry Litter Application.

Poultry litter (PL) is widely applied on grazing lands in Georgia. However, it is not clear how its long-term use affects soil microorganisms and their function. We examined changes in activity and community structure of ammonia-oxidizing archaea (AOA) and bacteria (AOB) in a grazing land with a history of PL application and compared it to treatment with urea ammonium nitrate (UAN). Soil samples (0-15 cm) were collected in 2009 (after 15 yr of PL application) and in 2013 (after 2 yr of no application). The abundance and community composition of ammonia oxidizers (AO) were determined with molecular techniques that targeted Nitrification potential (NP) was used for measuring their activity. Abundance of AO was significantly higher in PL (7.41 and 7.10 log copies g soil for AOB and AOA, respectively) than in UAN plots (6.82 and 6.50 log copies g soil for AOB and AOA, respectively) in 2009. This is consistent with NP, which was higher in PL (0.78 mg NO -N kg h) than in UAN (0.50 mg NO-N kg h) plots in 2009. The abundance of AO and NP decreased in 2013. There was no treatment effect on the composition of AO. Correlation analysis suggested that AOB were functionally more important than AOA, indicating the need to target AOB for efficient management of N in PL-receiving soils. Overall, the difference in nitrification between PL and UAN was mainly caused by the change in AO abundance rather than composition, and AO were not negatively affected by an increase in PL-derived trace metal concentrations.

The invasive annual cheatgrass releases more nitrogen than crested wheatgrass through root exudation and senescence.

Plant-soil feedbacks are an important aspect of invasive species success. One type of feedback is alteration of soil nutrient cycling. Cheatgrass invasion in the western USA is associated with increases in plant-available nitrogen (N), but the mechanism for this has not been elucidated. We labeled cheatgrass and crested wheatgrass, a common perennial grass in western rangelands, with (15)N-urea to determine if differences in root exudates and turnover could be a mechanism for increases in soil N. Mesocosms containing plants were either kept moist, or dried out during the final 10 days to determine the role of senescence in root N release. Soil N transformation rates were determined using (15)N pool dilution. After 75 days of growth, cheatgrass accumulated 30 % more total soil N and organic carbon than crested wheatgrass. Cheatgrass roots released twice as much N as crested wheatgrass roots (0.11 vs. 0.05 mg N kg(-1) soil day(-1)) in both soil moisture treatments. This occurred despite lower root abundance (7.0 vs. 17.3 g dry root kg(-1) soil) and N concentration (6.0 vs. 7.6 g N kg(-1) root) in cheatgrass vs. crested wheatgrass. We propose that increases in soil N pool sizes and transformation rates under cheatgrass are caused by higher rates of root exudation or release of organic matter containing relatively large amounts of labile N. Our results provide the first evidence for the underlying mechanism by which the invasive annual cheatgrass increases N availability and establishes positive plant-soil feedbacks that promote its success in western rangelands.

The invasive annual cheatgrass increases nitrogen availability in 24-year-old replicated field plots.

Previous studies comparing invaded and non-invaded sites suggest that cheatgrass (Bromus tectorum L.) causes soil N cycling to increase. Unfortunately, these correlative studies fail to distinguish whether cheatgrass caused the differences in N cycling, or if cheatgrass simply invaded sites where N availability was greater. We measured soil C and N concentrations and net and gross N-cycling rates on 24-year-old replicated field plots in a sagebrush-steppe ecosystem that had been plowed, fumigated, and seeded to different plant communities in 1984. Laboratory assays of soil collected throughout the soil profiles (0-60 cm) showed that soil NO3 (-), organic C and N, and net N mineralization, net nitrification, and soil respiration rates were all greater beneath cheatgrass than in sagebrush-perennial grass plots. In surface soils (0-10 cm), field and lab assays on five sampling dates during 2 years showed gross N mineralization, net N mineralization, and net nitrification rates were all faster beneath cheatgrass than in sagebrush-perennial grass plots. Modeling analyses based on soil respiration and gross N-cycling rates suggest that cheatgrass provides soil microbes with lower C:N substrates and that this could explain the faster N-cycling rates beneath cheatgrass. This is the first long-term replicated field study to conclusively show that cheatgrass created greater soil organic N pool sizes and stimulated N-cycling rates compared to similar-aged stands of sagebrush and native perennial grasses. Increased N-cycling rates may represent a positive plant-soil feedback that promotes continued dominance by cheatgrass, even in the absence of soil disturbance or fire.

Metagenome-assembled genomes of two nitrifying microorganisms from the freshwater archaeal ammonia-oxidizing enrichment culture BO1.

Two metagenome-assembled genomes (MAGs) were recovered from the ammonia-oxidizing enrichment culture BO1 obtained from the sediment of the freshwater reservoir Lake Burr Oak, Ohio, USA. High quality MAGs were assembled for the archaeal ammonia oxidizer Nitrosarchaeum sp. BO1 and the canonical nitrite oxidizer Nitrospira sp. BO1.

Are Plant-Soil Feedbacks Caused by Many Weak Microbial Interactions?

We used high-throughput sequencing and multivariate analyses to describe soil microbial community composition in two four-year field plant-soil feedback (PSF) experiments in Minnesota, USA and Jena, Germany. In descending order of variation explained, microbial community composition differed between the two study sites, among years, between bulk and rhizosphere soils, and among rhizosphere soils cultivated by different plant species. To try to identify soil organisms or communities that may cause PSF, we correlated plant growth responses with the microbial community composition associated with different plants. We found that plant biomass was correlated with values on two multivariate axes. These multivariate axes weighted dozens of soil organisms, suggesting that PSF was not caused by individual pathogens or symbionts but instead was caused by 'many weak' plant-microbe interactions. Taken together, the results suggest that PSFs result from complex interactions that occur within the context of a much larger soil microbial community whose composition is determined by factors associated with 'site' or year, such as soil pH, soil type, and weather. The results suggest that PSFs may be highly variable and difficult to reproduce because they result from complex interactions that occur in the context of a larger soil microbial community.

Plant-soil feedbacks help explain plant community productivity.

Plant productivity often increases with species richness, but the mechanisms explaining this diversity-productivity relationship are not fully understood. We tested if plant-soil feedbacks (PSF) can help to explain how biomass production changes with species richness. Using a greenhouse experiment, we measured all 240 possible PSFs for 16 plant species. At the same time, 49 plant communities with diversities ranging from one to 16 species were grown in replicated pots. A suite of plant community growth models, parameterized with (PSF) or without PSF (Null) effects, was used to predict plant growth observed in the communities. Selection effects and complementarity effects in modeled and observed data were separated. Plants created soils that increased or decreased subsequent plant growth by 25% ± 10%, but because PSFs were negative for C3 and C4 grasses, neutral for forbs, and positive for legumes, the net effect of all PSFs was a 2% ± 17% decrease in plant growth. Experimental plant communities with 16 species produced 37% more biomass than monocultures due to complementarity. Null models incorrectly predicted that 16-species communities would overyield due to selection effects. Adding PSF effects to Null models decreased selection effects, increased complementarity effects, and improved correlations between observed and predicted community biomass. PSF models predicted 26% of overyielding caused by complementarity observed in experimental communities. Relative to Null models, PSF models improved the predictions of the magnitude and mechanism of the diversity-productivity relationship. Results provide clear support for PSFs as one of several mechanisms that determine diversity-productivity relationships and help close the gap in understanding how biodiversity enhances ecosystem services such as biomass production.

Changes in microbial communities in soil treated with organic or conventional N sources.

Despite the extensive use of N fertilizers in agricultural soils, we are yet to fully understand their impact on soil microbial communities that mediate important soil processes. A 3-yr field study was undertaken in Georgia, where sweet corn (Zea mays L.) was grown under conventional or organic systems. Nitrogen (N) was supplied with ammonium sulfate at 112 kg N ha-1 (AS100) or 224 kg N ha-1 (AS200) or a combination of poultry litter, cover crop, and blood meal at 112 kg N ha-1 (PL100) or no N (control). Soil samples were collected from field plots to assess the impact of treatments on bacteria, fungi, and ammonia oxidizers using molecular methods that targeted 16S RNA, ITS2, and amoA genes, respectively. Treatment had significant impact on bacterial but not fungal composition. The AS200 significantly changed the relative abundances of Verrucomicrobia and Acidobacteria and decreased bacterial alpha diversity as compared with control. Beta-diversity analysis showed clear separation of microbial communities in AS200 vs. control and PL100. The abundance of ammonia-oxidizing bacteria (AOB) was more responsive to N input than ammonia oxidizing-archaea. It was also significantly and positively correlated with nitrification potential and soil nitrate with increasing N rates, indicating AOB's dominance in driving nitrification under high N input. Overall, the results indicated that AS200 changed bacterial composition and diversity, suggesting corresponding changes in soil processes related to N mineralization and nitrification. Understanding such changes in microbial communities can help us predict changes in soil processes to adopt sustainable management systems.

Genome sequence of Nitrosomonas sp. strain AL212, an ammonia-oxidizing bacterium sensitive to high levels of ammonia.

Nitrosomonas sp. strain AL212 is an obligate chemolithotrophic ammonia-oxidizing bacterium (AOB) that was originally isolated in 1997 by Yuichi Suwa and colleagues. This organism belongs to Nitrosomonas cluster 6A, which is characterized by sensitivity to high ammonia concentrations, higher substrate affinity (lower K(m)), and lower maximum growth rates than strains in Nitrosomonas cluster 7, which includes Nitrosomonas europaea and Nitrosomonas eutropha. Genome-informed studies of this ammonia-sensitive cohort of AOB are needed, as these bacteria are found in freshwater environments, drinking water supplies, wastewater treatment systems, and soils worldwide.

Plant-soil feedbacks help explain biodiversity-productivity relationships.

Species-rich plant communities can produce twice as much aboveground biomass as monocultures, but the mechanisms remain unresolved. We tested whether plant-soil feedbacks (PSFs) can help explain these biodiversity-productivity relationships. Using a 16-species, factorial field experiment we found that plants created soils that changed subsequent plant growth by 27% and that this effect increased over time. When incorporated into simulation models, these PSFs improved predictions of plant community growth and explained 14% of overyielding. Here we show quantitative, field-based evidence that diversity maintains productivity by suppressing plant disease. Though this effect alone was modest, it helps constrain the role of factors, such as niche partitioning, that have been difficult to quantify. This improved understanding of biodiversity-productivity relationships has implications for agriculture, biofuel production and conservation.

Moderate plant-soil feedbacks have small effects on the biodiversity-productivity relationship: A field experiment.

Plant-soil feedback (PSF) has gained attention as a mechanism promoting plant growth and coexistence. However, most PSF research has measured monoculture growth in greenhouse conditions. Translating PSFs into effects on plant growth in field communities remains an important frontier for PSF research. Using a 4-year, factorial field experiment in Jena, Germany, we measured the growth of nine grassland species on soils conditioned by each of the target species (i.e., 72 PSFs). Plant community models were parameterized with or without these PSF effects, and model predictions were compared to plant biomass production in diversity-productivity experiments. Plants created soils that changed subsequent plant biomass by 40%. However, because they were both positive and negative, the average PSF effect was 14% less growth on "home" than on "away" soils. Nine-species plant communities produced 29 to 37% more biomass for polycultures than for monocultures due primarily to selection effects. With or without PSF, plant community models predicted 28%-29% more biomass for polycultures than for monocultures, again due primarily to selection effects. Synthesis: Despite causing 40% changes in plant biomass, PSFs had little effect on model predictions of plant community biomass across a range of species richness. While somewhat surprising, a lack of a PSF effect was appropriate in this site because species richness effects in this study were caused by selection effects and not complementarity effects (PSFs are a complementarity mechanism). Our plant community models helped us describe several reasons that even large PSF may not affect plant productivity. Notably, we found that dominant species demonstrated small PSF, suggesting there may be selective pressure for plants to create neutral PSF. Broadly, testing PSFs in plant communities in field conditions provided a more realistic understanding of how PSFs affect plant growth in communities in the context of other species traits.

Nitrite Oxidizer Activity and Community Are More Responsive Than Their Abundance to Ammonium-Based Fertilizer in an Agricultural Soil.

Autotrophic nitrification is mediated by ammonia oxidizing bacteria (AOB) or ammonia oxidizing archaea (AOA) and nitrite oxidizing bacteria (NOB). Mounting studies have examined the impact of nitrogen (N) fertilization on the dynamic and diversity of AOA and AOB, while we have limited information on the response of the activity, abundance, and diversity of NOB to N fertilization. We investigated the influence of organic and inorganic N fertilizers on soil NOB in silage corn field plots that received contrasting nitrogen (N) treatments: control (no additional N), ammonium sulfate (AS 100 and 200 kg N ha-1), and compost (200 kg N ha-1). Nitrifying community was examined using a universal marker (16S rRNA gene), functional gene markers (AOB amoA and Nitrospira nxrB), and metagenomics. The overall nitrifying community was not altered after the first fertilization but was significantly shifted by 4-year repeated application of ammonium fertilizers. Nitrospira were the dominant NOB (>99.7%) in our agricultural soil. Both community compositions of AOB and Nitrospira were significantly changed by ammonium fertilizers but not by compost after 4 years of repeated applications. All nitrifiers, including comammox, were recovered in soil metagenomes based on a gene-targeted assembly, but their sequence counts were very low. Although N treatment did not affect the abundance of Nitrospira nxrB determined by real-time quantitative PCR, ammonium fertilizers significantly promoted rates of potential nitrite oxidation determined at 0.15 mM nitrite in soil slurries. Understanding the response of both ammonia oxidizers and nitrite oxidizers to N fertilization may initiate or improve strategies for mitigating potential environmental impacts of nitrate production in agricultural ecosystems.

Controls and Adaptive Management of Nitrification in Agricultural Soils.

Agriculture is responsible for over half of the input of reactive nitrogen (N) to terrestrial systems; however improving N availability remains the primary management technique to increase crop yields in most regions. In the majority of agricultural soils, ammonium is rapidly converted to nitrate by nitrification, which increases the mobility of N through the soil matrix, strongly influencing N retention in the system. Decreasing nitrification through management is desirable to decrease N losses and increase N fertilizer use efficiency. We review the controlling factors on the rate and extent of nitrification in agricultural soils from temperate regions including substrate supply, environmental conditions, abundance and diversity of nitrifiers and plant and microbial interactions with nitrifiers. Approaches to the management of nitrification include those that control ammonium substrate availability and those that inhibit nitrifiers directly. Strategies for controlling ammonium substrate availability include timing of fertilization to coincide with rapid plant update, formulation of fertilizers for slow release or with inhibitors, keeping plant growing continuously to assimilate N, and intensify internal N cycling (immobilization). Another effective strategy is to inhibit nitrifiers directly with either synthetic or biological nitrification inhibitors. Commercial nitrification inhibitors are effective but their use is complicated by a changing climate and by organic management requirements. The interactions of the nitrifying organisms with plants or microbes producing biological nitrification inhibitors is a promising approach but just beginning to be critically examined. Climate smart agriculture will need to carefully consider optimized seasonal timing for these strategies to remain effective management tools.

Benzo(a)pyrene inhibits the accumulation and toxicity of cadmium in subcellular fractions of Eisenia fetida.

Cadmium (Cd) and benzo [a]pyrene (BaP) often co-occur in the environment, and the critical body residue of organisms is used as an indicator of the toxic effects of contaminants. However, little is known about their distributions and toxicities when pollution of Cd and BaP are combined. Semi-static solution culture experiment was used to study the impacts of BaP on the subcellular distribution of the toxic metal Cd in the earthworm Eisenia fetida. We explored the mechanisms by which this organism responds to combined exposure to these pollutants by measuring the protein content of each of three subcellular fractions, as well as acetylcholinesterase (AChE) and glutathione S-transferase (GST) activities. The subcellular partitioning of Cd was heterogeneous and Cd mainly accumulated in the cytosolic fraction (Fraction C), which was previously reported to be involved in metal immobilization. In Fraction C, Cd accumulation was correlated with the external concentration to which the earthworm had been exposed; however, in the presence of BaP, Cd accumulation was inhibited and plateaued at high external Cd concentrations. A principal component analysis revealed that this decreased Cd accumulation might be caused by increases in GST activity, which likely increased the excretion of Cd. BaP was also found to stimulate protein biosynthesis and upregulate AChE and GST activities in the debris fraction (Fraction E), indicating other potential detoxification mechanisms in this fraction. Granule fraction (Fraction D) had a lower protein content, AChE and GST activities than the other subcellular fractions, supporting previous findings that Fraction D is largely inert.

Complete genome sequence of Nitrosospira multiformis, an ammonia-oxidizing bacterium from the soil environment.

The complete genome of the ammonia-oxidizing bacterium Nitrosospira multiformis (ATCC 25196(T)) consists of a circular chromosome and three small plasmids totaling 3,234,309 bp and encoding 2,827 putative proteins. Of the 2,827 putative proteins, 2,026 proteins have predicted functions and 801 are without conserved functional domains, yet 747 of these have similarity to other predicted proteins in databases. Gene homologs from Nitrosomonas europaea and Nitrosomonas eutropha were the best match for 42% of the predicted genes in N. multiformis. The N. multiformis genome contains three nearly identical copies of amo and hao gene clusters as large repeats. The features of N. multiformis that distinguish it from N. europaea include the presence of gene clusters encoding urease and hydrogenase, a ribulose-bisphosphate carboxylase/oxygenase-encoding operon of distinctive structure and phylogeny, and a relatively small complement of genes related to Fe acquisition. Systems for synthesis of a pyoverdine-like siderophore and for acyl-homoserine lactone were unique to N. multiformis among the sequenced genomes of ammonia-oxidizing bacteria. Gene clusters encoding proteins associated with outer membrane and cell envelope functions, including transporters, porins, exopolysaccharide synthesis, capsule formation, and protein sorting/export, were abundant. Numerous sensory transduction and response regulator gene systems directed toward sensing of the extracellular environment are described. Gene clusters for glycogen, polyphosphate, and cyanophycin storage and utilization were identified, providing mechanisms for meeting energy requirements under substrate-limited conditions. The genome of N. multiformis encodes the core pathways for chemolithoautotrophy along with adaptations for surface growth and survival in soil environments.

Changes in crested wheatgrass root exudation caused by flood, drought, and nutrient stress.

Root exudates can chelate inorganic soil contaminants, change rhizosphere pH, and may increase degradation of organic contaminants by microbial cometabolism. Root-zone stress may increase exudation and enhance phytoremediation. We studied the effects of low K+, high NH4+/NO3- ratio, drought, and flooding on the quantity and composition of exudates. Crested wheatgrass (Agropyron cristatum) was grown in Ottawa sand in sealed, flow-through glass columns under axenic conditions for 70 d. Root exudates were collected and analyzed for total organic carbon (TOC) and organic acid content to compare treatment effects. Plants in the low K+ treatment exuded 60% more TOC per plant per day (p = 0.01) than the unstressed control. Drought stress increased cumulative TOC exuded per gram dry plant by 71% (p = 0.05). The flooded treatment increased TOC exuded per gram dry plant by 45%, although this was not statistically significant based on the two replicate plants in this treatment. Exudation from the high NH4+/NO3- ratio treatment was 10% less than the control. Exudation rates in this study ranged from 8 to 50% of rates in four other published studies. Gas chromatography-mass spectrometry (GC-MS) analysis indicated that malic acid was the predominant organic acid exuded. Fumaric, malonic, succinic, and oxalic acids were also detected in the exudates of all treatments. These results demonstrate that nutrient and water stress have significant effects on the quantity and composition of root exudates. Cultural manipulations to induce stress may change the quantity of root exudates and thus increase the effectiveness of phytoremediation.

Complete Genome Sequence of Nitrosomonas cryotolerans ATCC 49181, a Phylogenetically Distinct Ammonia-Oxidizing Bacterium Isolated from Arctic Waters.

Nitrosomonas cryotolerans ATCC 49181 is a cold-tolerant marine ammonia-oxidizing bacterium isolated from seawater collected in the Gulf of Alaska. The high-quality complete genome contains a 2.87-Mbp chromosome and a 56.6-kbp plasmid. Chemolithoautotrophic modules encoding ammonia oxidation and CO2 fixation were identified.