Application of processed organic municipal solid waste on agricultural land - a scenario analysis

Source separation, composting and anaerobic digestion, with associated land application, are increasingly being considered as alternative waste management strategies to landfilling and incineration of municipal solid waste (MSW). Environmental life cycle assessments are a useful tool in political decision-making about waste management strategies. However, due to the diversity of processed organic MSW and the situations in which it can be applied, the environmental impacts of land application are very hard to determine by experimental means. In the current study, we used the agroecosystem model Daisy to simulate a range of different scenarios representing different geographical areas, farm and soil types under Danish conditions and legislation. Generally, the application of processed organic MSW resulted in increased emissions compared with the corresponding standard scenarios, but with large differences between scenarios. Emission coefficients for nitrogen leaching to the groundwater ranged from 0.03 to 0.87, while those for nitrogen lost to surface waters through tile drains ranged from 0 to 0.30. Emission coefficients for N2O formation ranged from 0.013 to 0.022 and for ammonia volatilization from 0.016 to 0.11. These estimates are within reasonable range of observed values under similar conditions. Furthermore, a sensitivity analysis showed that the estimates were not very sensitive to the mineralization dynamics of the processed organic MSW. The results show that agroecosystem models can be powerful tools to estimate the environmental impacts of land application of processed MSW under different conditions. Despite this, agroecosystem models have only been used to a very limited degree for this purpose

Role of the Bombyx mori R2 element N-terminal domain in the target-primed reverse transcription (TPRT) reaction

R2 is a site-specific non-long terminal repeat (non-LTR) retrotransposon encoding a single polypeptide with reverse transcriptase, DNA endonuclease and nucleic acid-binding domains. The current model of R2 retrotransposition involves an ordered series of cleavage and polymerization steps carried out by at least two R2 protein subunits, one bound upstream and one bound downstream of the integration site. The role in the retrotransposition reaction of two conserved DNA-binding motifs, a C(2)H(2) zinc finger (ZF) and a Myb motif, located within the N-terminal domain of the protein are explored in this report. These motifs do not appear to play a role in RT or the ability of the protein to bind the R2 RNA transcript. Methylation and missing nucleoside interference-based DNA footprints using polypeptides to the N-terminal domain suggest the ZF and Myb motifs bind to regions −3 to −1 and +10 to +15 with reference to the insertion site. Mutations in these DNA sites or of the N-terminal protein domain blocked binding and the activity of the downstream subunit. Mutations of the protein domain also affected binding of the upstream subunit but not its function, suggesting the primary path to DNA target recognition by R2 involves both upstream and downstream subunits

Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level QM results obtained for a small protein with an RMSD of 0.25 ppm (r = 0.94). ProCS is interfaced with the PHAISTOS protein simulation program and is used to infer statistical protein ensembles that reflect experimentally measured amide proton chemical shift values. Such chemical shift-based structural refinements, starting from high-resolution X-ray structures of Protein G, ubiquitin, and SMN Tudor Domain, result in average chemical shifts, hydrogen bond geometries, and trans-hydrogen bond (h3JNC') spin-spin coupling constants that are in excellent agreement with experiment. We show that the structural sensitivity of the QM-based amide proton chemical shift predictions is needed to refine protein structures to this agreement. The ProCS method thus offers a powerful new tool for refining the structures of hydrogen bonding networks to high accuracy with many potential applications such as protein flexibility in ligand binding.Comment: PLOS ONE accepted, Nov 201

Inhibition of Nitric Oxide and Soluble Guanylyl Cyclase Signaling Affects Olfactory Neuron Activity in the Moth, \u3cem\u3eManduca sexta\u3c/em\u3e

Nitric oxide is emerging as an important modulator of many physiological processes including olfaction, yet the function of this gas in the processing of olfactory information remains poorly understood. In the antennal lobe of the moth, Manduca sexta, nitric oxide is produced in response to odor stimulation, and many interneurons express soluble guanylyl cyclase, a well-characterized nitric oxide target. We used intracellular recording and staining coupled with pharmacological manipulation of nitric oxide and soluble guanylyl cyclase to test the hypothesis that nitric oxide modulates odor responsiveness in olfactory interneurons through soluble guanylyl cyclase-dependent pathways. Nitric oxide synthase inhibition resulted in pronounced effects on the resting level of firing and the responses to odor stimulation in most interneurons. Effects ranged from bursting to strong attenuation of activity and were often accompanied by membrane depolarization coupled with a change in input resistance. Blocking nitric oxide activation of soluble guanylyl cyclase signaling mimicked the effects of nitric oxide synthase inhibitors in a subset of olfactory neurons, while other cells were differentially affected by this treatment. Together, these results suggest that nitric oxide is required for proper olfactory function, and likely acts through soluble guanylyl cyclase-dependent and -independent mechanisms in different subsets of neurons

Genomic Relationships and Speciation Times of Human, Chimpanzee, and Gorilla Inferred from a Coalescent Hidden Markov Model

The genealogical relationship of human, chimpanzee, and gorilla varies along the genome. We develop a hidden Markov model (HMM) that incorporates this variation and relate the model parameters to population genetics quantities such as speciation times and ancestral population sizes. Our HMM is an analytically tractable approximation to the coalescent process with recombination, and in simulations we see no apparent bias in the HMM estimates. We apply the HMM to four autosomal contiguous human–chimp–gorilla–orangutan alignments comprising a total of 1.9 million base pairs. We find a very recent speciation time of human–chimp (4.1 ± 0.4 million years), and fairly large ancestral effective population sizes (65,000 ± 30,000 for the human–chimp ancestor and 45,000 ± 10,000 for the human–chimp–gorilla ancestor). Furthermore, around 50% of the human genome coalesces with chimpanzee after speciation with gorilla. We also consider 250,000 base pairs of X-chromosome alignments and find an effective population size much smaller than 75% of the autosomal effective population sizes. Finally, we find that the rate of transitions between different genealogies correlates well with the region-wide present-day human recombination rate, but does not correlate with the fine-scale recombination rates and recombination hot spots, suggesting that the latter are evolutionarily transient

Life cycle modelling of environmental impacts of application of processed organic municipal solid waste on agricultural land (EASEWASTE)

A model capable of quantifying the potential environmental impacts of agricultural application of composted or anaerobically digested source-separated organic municipal solid waste (MSW) is presented. In addition to the direct impacts, the model accounts for savings by avoiding the production and use of commercial fertilizers. The model is part of a larger model, Environmental Assessment of Solid Waste Systems and Technology (EASEWASTE), developed as a decisionsupport model, focusing on assessment of alternative waste management options. The environmental impacts of the land application of processed organic waste are quantified by emission coefficients referring to the composition of the processed waste and related to specific crop rotation as well as soil type. The model contains several default parameters based on literature data, field experiments and modelling by the agro-ecosystem model, Daisy. All data can be modified by the user allowing application of the model to other situations. A case study including four scenarios was performed to illustrate the use of the model. One tonne of nitrogen in composted and anaerobically digested MSW was applied as fertilizer to loamy and sandy soil at a plant farm in western Denmark. Application of the processed organic waste mainly affected the environmental impact categories global warming (0.4–0.7 PE), acidification (–0.06 (saving)–1.6 PE), nutrient enrichment (–1.0 (saving)–3.1 PE), and toxicity. The main contributors to these categories were nitrous oxide formation (global warming), ammonia volatilization (acidification and nutrient enrichment), nitrate losses (nutrient enrichment and groundwater contamination), and heavy metal input to soil (toxicity potentials). The local agricultural conditions as well as the composition of the processed MSW showed large influence on the environmental impacts. A range of benefits, mainly related to improved soil quality from long-term application of the processed organic waste, could not be generally quantified with respect to the chosen life cycle assessment impact categories and were therefore not included in the model. These effects should be considered in conjunction with the results of the life cycle assessment