Fungal denitrification: Bipolaris sorokiniana exclusively denitrifies inorganic nitrogen in the presence and absence of oxygen

Fungi may play an important role in the production of the greenhouse gas nitrous oxide (N2O). Bipolaris sorokiniana is a ubiquitous saprobe found in soils worldwide, yet denitrification by this fungal strain has not previously been reported. We aimed to test if B. sorokiniana would produce N2O and CO2 in the presence of organic and inorganic forms of nitrogen (N) under microaerobic and anaerobic conditions. Nitrogen source (organic-N, inorganic-N, no-N control) significantly affected N2O and CO2 production both in the presence and absence of oxygen, which contrasts with bacterial denitrification. Inorganic N addition increased denitrification of N2O (from 0 to 0.3 mu g N(2)0-N h(-1) g(-1) biomass) and reduced respiration of CO2 (from 0.1 to 0.02 mg CO2 h(-1) g(-1) biomass). Isotope analyses indicated that nitrite, rather than ammonium or glutamine, was transformed to N2O. Results suggest the source of N may play a larger role in fungal N2O production than oxygen status

Numerical calculations of the phase diagram of cubic blue phases in cholesteric liquid crystals

We study the static properties of cubic blue phases by numerically minimising the three-dimensional, Landau-de Gennes free energy for a cholesteric liquid crystal close to the isotropic-cholesteric phase transition. Thus we are able to refine the powerful but approximate, semi-analytic frameworks that have been used previously. We obtain the equilibrium phase diagram and discuss it in relation to previous results. We find that the value of the chirality above which blue phases appear is shifted by 20% (towards experimentally more accessible regions) with respect to previous estimates. We also find that the region of stability of the O5 structure -- which has not been observed experimentally -- shrinks, while that of BP I (O8-) increases thus giving the correct order of appearance of blue phases at small chirality. We also study the approach to equilibrium starting from the infinite chirality solutions and we find that in some cases the disclination network has to assemble during the equilibration. In these situations disclinations are formed via the merging of isolated aligned defects.Comment: 16 pages, 5 figures. Accepted for publication in Phys. Rev.

Isotropic-nematic phase transition in suspensions of filamentous virus and the neutral polymer Dextran

We present an experimental study of the isotropic-nematic phase transition in an aqueous mixture of charged semi-flexible rods (fd virus) and neutral polymer (Dextran). A complete phase diagram is measured as a function of ionic strength and polymer molecular weight. At high ionic strength we find that adding polymer widens the isotropic-nematic coexistence region with polymers preferentially partitioning into the isotropic phase, while at low ionic strength the added polymer has no effect on the phase transition. The nematic order parameter is determined from birefringence measurements and is found to be independent of polymer concentration (or equivalently the strength of attraction). The experimental results are compared with the existing theoretical predictions for the isotropic-nematic transition in rods with attractive interactions.Comment: 8 Figures. To be published in Phys. Rev. E. For more information see http://www.elsie.brandeis.ed

Mineralizable nitrogen and denitrification enzyme activity drive nitrate concentrations in well-drained stony subsoil under lucerne (Medicago sativa L.)

Nitrogen (N) inputs to agricultural systems contribute substantially to soil nitrate (NO₃¯) concentrations, which increase NO₃¯ leaching and contamination of groundwater. The influence of soil microbes in regulating NO₃¯ concentrations in the topsoil are well studied but it is often assumed that microbial regulation of NO₃¯ concentrations in the subsoil is negligible. The aim of this study was to test this assumption by determining the relationships between microbial properties and NO₃¯ concentrations in both the subsoil and the topsoil. We measured the size of the mineralizable N (Nm) pool, microbial properties (microbial biomass, bacterial richness), nitrifier gene abundance (amoA gene copy number), denitrifier gene abundance (nirK and nirS gene copy number), denitrifier enzyme activity and NO₃¯ concentrations in the topsoil and the subsoil in a well-drained stony soil under an established lucerne crop. We used structural equation modelling (SEM) to identify and compare the linkages of microbial properties with NO₃¯ concentrations at each depth. In the topsoil, we found higher Nm, gene abundance, denitrification enzyme activity, bacterial richness, and microbial biomass than those in the subsoil, but there were no relationships between these variables and NO₃¯ concentrations in the topsoil (the SEM model explained 0.06% of the variability in NO₃¯ concentrations). In contrast, in the subsoil, NO₃¯ concentrations were strongly correlated with bacterial amoA abundance and denitrification enzyme activity, with both variables associated significantly with Nm. We found that bacterial richness was also associated with Nm in the subsoil. Our findings highlight that microbial properties are associated with NO₃¯ concentrations in the subsoil (the SEM model explained 82% the variability in NO₃¯ concentrations) and this suggest that nitrification and denitrification may contribute to regulating NO₃¯ concentrations in the subsoil. Our findings also suggest that denitrification contributes to reducing NO₃¯ concentrations in the subsoil. We conclude that studies addressing drivers of NO₃¯ leaching need to consider the potential for microbially-mediated attenuation (or an increase) in NO₃¯ concentrations throughout the soil profile

Soil nitrogen treatment alters microbiome networks across farm niches

Agriculture is fundamental for food production, and microbiomes support agriculture through multiple essential ecosystem services. Despite the importance of individual (i.e., niche specific) agricultural microbiomes, microbiome interactions across niches are not well-understood. To observe the linkages between nearby agricultural microbiomes, multiple approaches (16S, 18S, and ITS) were used to inspect a broad coverage of niche microbiomes. Here we examined agricultural microbiome responses to 3 different nitrogen treatments (0, 150, and 300 kg/ha/yr) in soil and tracked linked responses in other neighbouring farm niches (rumen, faecal, white clover leaf, white clover root, rye grass leaf, and rye grass root). Nitrogen treatment had little impact on microbiome structure or composition across niches, but drastically reduced the microbiome network connectivity in soil. Networks of 16S microbiomes were the most sensitive to nitrogen treatment across amplicons, where ITS microbiome networks were the least responsive. Nitrogen enrichment in soil altered soil and the neighbouring microbiome networks, supporting our hypotheses that nitrogen treatment in soil altered microbiomes in soil and in nearby niches. This suggested that agricultural microbiomes across farm niches are ecologically interactive. Therefore, knock-on effects on neighbouring niches should be considered when management is applied to a single agricultural niche

Between and within-herd variation in blood and milk biomarkers in Holstein cows in early lactation

Both blood- and milk-based biomarkers have been analysed for decades in research settings, although often only in one herd, and without focus on the variation in the biomarkers that are specifically related to herd or diet. Biomarkers can be used to detect physiological imbalance and disease risk and may have a role in precision livestock farming (PLF). For use in PLF, it is important to quantify normal variation in specific biomarkers and the source of this variation. The objective of this study was to estimate the between- and within-herd variation in a number of blood metabolites (β-hydroxybutyrate (BHB), non-esterified fatty acids, glucose and serum IGF-1), milk metabolites (free glucose, glucose-6-phosphate, urea, isocitrate, BHB and uric acid), milk enzymes (lactate dehydrogenase and N-acetyl-β-D-glucosaminidase (NAGase)) and composite indicators for metabolic imbalances (Physiological Imbalance-index and energy balance), to help facilitate their adoption within PLF. Blood and milk were sampled from 234 Holstein dairy cows from 6 experimental herds, each in a different European country, and offered a total of 10 different diets. Blood was sampled on 2 occasions at approximately 14 days-in-milk (DIM) and 35 DIM. Milk samples were collected twice weekly (in total 2750 samples) from DIM 1 to 50. Multilevel random regression models were used to estimate the variance components and to calculate the intraclass correlations (ICCs). The ICCs for the milk metabolites, when adjusted for parity and DIM at sampling, demonstrated that between 12% (glucose-6-phosphate) and 46% (urea) of the variation in the metabolites’ levels could be associated with the herd-diet combination. Intraclass Correlations related to the herd-diet combination were generally higher for blood metabolites, from 17% (cholesterol) to approximately 46% (BHB and urea). The high ICCs for urea suggest that this biomarker can be used for monitoring on herd level. The low variance within cow for NAGase indicates that few samples would be needed to describe the status and potentially a general reference value could be used. The low ICC for most of the biomarkers and larger within cow variation emphasises that multiple samples would be needed - most likely on the individual cows - for making the biomarkers useful for monitoring. The majority of biomarkers were influenced by parity and DIM which indicate that these should be accounted for if the biomarker should be used for monitoring

Prediction of metabolic clusters in early lactation dairy cows using models based on 2 milk biomarkers

The aim of this study was to describe metabolism of early-lactation dairy cows by clustering cows based on glucose, insulin-like growth factor I (IGF-I), free fatty acid, and beta-hydroxybutyrate (BHB) using the k-means method. Predictive models for metabolic clusters were created and validated using 3 sets of milk biomarkers (milk metabolites and enzymes, glycans on the immuno-gamma globulin fraction of milk, and Fourier-transform mid-infrared spectra of milk). Metabolic clusters are used to identify dairy cows with a balanced or imbalanced metabolic profile. Around 14 and 35 d in milk, serum or plasma concentrations of BHB, free fatty acids, glucose, and IGF-I were determined. Cows with a favorable metabolic profile were grouped together in what was referred to as the "balanced" group (n = 43) and were compared with cows in what was referred to as the "other balanced" group (n = 64). Cows with an unfavorable metabolic profile were grouped in what was referred to as the "imbalanced" group (n = 19) and compared with cows in what was referred to as the "other imbalanced" group (n = 88). Glucose and IGF-I were higher in balanced compared with other balanced cows. Free fatty acids and BHB were lower in balanced compared with other balanced cows. Glucose and IGF-I were lower in imbalanced compared with other imbalanced cows. Free fatty acids arid BHB were higher in imbalanced cows. Metabolic clusters were related to production parameters. There was a trend for a higher daily increase in fat- and protein-corrected milk yield in balanced cows, whereas that of imbalanced cows was higher. Dry matter intake and the daily increase in dry matter intake were higher in balanced cows and lower in imbalanced cows. Energy balance was continuously higher in balanced cows and lower in imbalanced cows. Weekly or twice-weekly milk samples were taken and milk metabolites and enzymes (milk glucose, glucose-6-phosphate, BHB, lactate dehydrogenase, N-acetyl-beta-D-glucosaminidase, isocitrate), immunogamma globulin glycans (19 peaks), and Fourier-transform mid-infrared spectra (1,060 wavelengths reduced to 15 principal components) were determined. Milk biomarkers with or without additional cow information (days in milk, parity, milk yield featurs) were used to create predictive models for the metabolic clusters. Accuracy for prediction of balanced (80%) and imbalanced (88%) cows was highest using milk metabolites and enzymes combined with days in milk and parity. The results and models of the present study are part of the GplusE project and identify novel milk-based phenotypes that may be used as predictors for metabolic and performance traits in early-lactation dairy cows

Computational and Statistical Analyses of Amino Acid Usage and Physico-Chemical Properties of the Twelve Late Embryogenesis Abundant Protein Classes

Late Embryogenesis Abundant Proteins (LEAPs) are ubiquitous proteins expected to play major roles in desiccation tolerance. Little is known about their structure - function relationships because of the scarcity of 3-D structures for LEAPs. The previous building of LEAPdb, a database dedicated to LEAPs from plants and other organisms, led to the classification of 710 LEAPs into 12 non-overlapping classes with distinct properties. Using this resource, numerous physico-chemical properties of LEAPs and amino acid usage by LEAPs have been computed and statistically analyzed, revealing distinctive features for each class. This unprecedented analysis allowed a rigorous characterization of the 12 LEAP classes, which differed also in multiple structural and physico-chemical features. Although most LEAPs can be predicted as intrinsically disordered proteins, the analysis indicates that LEAP class 7 (PF03168) and probably LEAP class 11 (PF04927) are natively folded proteins. This study thus provides a detailed description of the structural properties of this protein family opening the path toward further LEAP structure - function analysis. Finally, since each LEAP class can be clearly characterized by a unique set of physico-chemical properties, this will allow development of software to predict proteins as LEAPs

Regenerative agriculture in Aotearoa New Zealand - research pathways to build science-based evidence and national narratives.

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