Metabolomic Analysis Reveals Contributions of Citric and Citramalic Acids to Rare Earth Bioleaching by a Paecilomyces Fungus.

Conventional methods for extracting rare earth elements from monazite ore require high energy inputs and produce environmentally damaging waste streams. Bioleaching offers a potentially more environmentally friendly alternative extraction process. In order to better understand bioleaching mechanisms, we conducted an exo-metabolomic analysis of a previously isolated rare earth bioleaching fungus from the genus Paecilomyces (GenBank accession numbers KM874779 and KM 874781) to identify contributions of compounds exuded by this fungus to bioleaching activity. Exuded compounds were compared under two growth conditions: growth with monazite ore as the only phosphate source, and growth with a soluble phosphate source (K2HPO4) added. Overall metabolite profiling, in combination with glucose consumption and biomass accumulation data, reflected a lag in growth when this organism was grown with only monazite. We analyzed the relationships between metabolite concentrations, rare earth solubilization, and growth conditions, and identified several metabolites potentially associated with bioleaching. Further investigation using laboratory prepared solutions of 17 of these metabolites indicated statistically significant leaching contributions from both citric and citramalic acids. These contributions (16.4 and 15.0 mg/L total rare earths solubilized) accounted for a portion, but not all, of the leaching achieved with direct bioleaching (42 ± 15 mg/L final rare earth concentration). Additionally, citramalic acid released significantly less of the radioactive element thorium than did citric acid (0.25 ± 0.01 mg/L compared to 1.18 ± 0.01 mg/L), suggesting that citramalic acid may have preferable leaching properties for a monazite bioleaching process

Influence of trace erythromycin and eryhthromycin-H2O on carbon and nutrients removal and on resistance selection in sequencing batch reactors (SBRs).

Three sequencing batch reactors (SBRs) were operated in parallel to study the effects of trace erythromycin (ERY) and ERY-H2O on the treatment of a synthetic wastewater. Through monitoring (1) daily effluents and (2) concentrations of nitrogen (N) and phosphorous (P) in certain batch cycles of the three reactors operated from transient to steady states, the removal of carbon, N, and P was affected negligibly by ERY (100 microg/L) or ERY-H2O (50 microg/L) when compared with the control reactor. However, through analyzing microbial communities of the three steady state SBRs on high-density microarrays (Phylo-Chip), ERY, and ERY-H2O had pronounced effects on the community composition of bacteria related to N and P removal, leading to diversity loss and abundance change. The above observations indicated that resistant bacteria were selected upon exposure to ERY or ERY-H2O. Shortterm batch experiments further proved the resistance and demonstrated that ammonium oxidation (56-95%) was inhibited more significantly than nitrite oxidation (18-61%) in the presence of ERY (100, 400, or 800 microg/L). Therefore, the presence of ERY or ERY-H2O (at microg/L levels) shifted the microbial community and selected resistant bacteria, which may account for the negligible influence of the antibiotic ERY or its derivative ERY-H2O (at microg/L levels) on carbon, N, and P removal in the SBRs

Lattice Sigma Models with Exact Supersymmetry

We show how to construct lattice sigma models in one, two and four dimensions which exhibit an exact fermionic symmetry. These models are discretized and {\it twisted} versions of conventional supersymmetric sigma models with N=2 supersymmetry. The fermionic symmetry corresponds to a scalar BRST charge built from the original supercharges. The lattice theories possess local actions and in many cases admit a Wilson term to suppress doubles. In the two and four dimensional theorie s we show that these lattice theories are invariant under additional discrete symmetries. We argue that the presence of these exact symmetries ensures that no fine tuning is required to achieve N=2 supersymmetry in the continuum limit. As a concrete example we show preliminary numerical results from a simulation of the O(3) supersymmetric sigma model in two dimensions.Comment: 23 pages, 3 figures, formalism generalized to allow for explicit Wilson mass terms. New numerical results added. Version to be published in JHE

The Coronal Structure of AB Doradus

We perform a numerical simulation of the corona of the young, rapidly rotating K0 dwarf AB Doradus using a global MHD model. The model is driven by a surface map of the radial magnetic field constructed using Zeeman-Doppler Imaging. We find that the global structure of the stellar corona is dominated by strong azimuthal tangling of the magnetic field due to the rapid rotation. The MHD solution enables us to calculate realistic Alfv\'en surfaces and we can therefore estimate the stellar mass loss rate and angular momentum loss rate without making undue theoretical simplifications. We consider three cases, parametrized by the base density of the corona, that span the range of possible solutions for the system. We find that overall, the mass and angular-momentum loss rates are higher than in the solar case; the mass loss rates are 10 to 500 times higher, and the angular momentum loss rate can be up to $3\times{10}^4$ higher than present day solar values. Our simulations show that this model can be use to constrain the wide parameter space of stellar systems. It also shows that an MHD approach can provide more information about the physical system over the commonly used potential field extrapolation.Comment: 13 pages, 7 figure

Successful Cessation Programs that Reduce Comorbidity May Explain Surprisingly Low Smoking Rates Among Hospitalized COVID-19 Patients

A recent, non-peer-reviewed meta-analysis suggests that smoking may reduce the risk of hospitalization with COVID-19 because the prevalence of smoking among hospitalized COVID-19 is less than that of the general population. However, there are alternative explanations for this phenomena based on (1) the failure to report, or accurately record, smoking history during emergency hospital admissions and (2) a pre-disposition to avoid smoking among COVID-19 patients with tobacco-related comorbidities (a type of “reverse” causation). For example, urine testing of hospitalized patients in Australia for cotinine showed that smokers were under-counted by 37% because incoming patients failed to inform staff about their smoking behavior. Face-to-face interviews can introduce bias into the responses to attitudinal and behavioral questions not present in the self-completion interviews typically used to measure smoking prevalence in the general population. Subjects in face-to-face interviews may be unwilling to admit socially undesirable behavior and attitudes under direct questioning. Reverse causation may also contribute to the difference between smoking prevalence in the COVID-19 and general population. Patients hospitalized with COVID-19 may be simply less prone to use tobacco than the general population. A potentially robust “reverse causation” hypothesis for reduced prevalence of smokers in the COVID-19 population is the enrichment of patients in that population with serious comorbidities that motivates them to quit smoking. We judge that this “smoking cessation” mechanism may account for a significant fraction of the reduced prevalence of smokers in the COVID-19 population. Testing this hypothesis will require a focused research program

Incomplete Wood-Ljungdahl pathway facilitates one-carbon metabolism in organohalide-respiring Dehalococcoides mccartyi.

The acetyl-CoA "Wood-Ljungdahl" pathway couples the folate-mediated one-carbon (C1) metabolism to either CO2 reduction or acetate oxidation via acetyl-CoA. This pathway is distributed in diverse anaerobes and is used for both energy conservation and assimilation of C1 compounds. Genome annotations for all sequenced strains of Dehalococcoides mccartyi, an important bacterium involved in the bioremediation of chlorinated solvents, reveal homologous genes encoding an incomplete Wood-Ljungdahl pathway. Because this pathway lacks key enzymes for both C1 metabolism and CO2 reduction, its cellular functions remain elusive. Here we used D. mccartyi strain 195 as a model organism to investigate the metabolic function of this pathway and its impacts on the growth of strain 195. Surprisingly, this pathway cleaves acetyl-CoA to donate a methyl group for production of methyl-tetrahydrofolate (CH3-THF) for methionine biosynthesis, representing an unconventional strategy for generating CH3-THF in organisms without methylene-tetrahydrofolate reductase. Carbon monoxide (CO) was found to accumulate as an obligate by-product from the acetyl-CoA cleavage because of the lack of a CO dehydrogenase in strain 195. CO accumulation inhibits the sustainable growth and dechlorination of strain 195 maintained in pure cultures, but can be prevented by CO-metabolizing anaerobes that coexist with D. mccartyi, resulting in an unusual syntrophic association. We also found that this pathway incorporates exogenous formate to support serine biosynthesis. This study of the incomplete Wood-Ljungdahl pathway in D. mccartyi indicates a unique bacterial C1 metabolism that is critical for D. mccartyi growth and interactions in dechlorinating communities and may play a role in other anaerobic communities

Singularities in ternary mixtures of k-core percolation

Heterogeneous k-core percolation is an extension of a percolation model which has interesting applications to the resilience of networks under random damage. In this model, the notion of node robustness is local, instead of global as in uniform k-core percolation. One of the advantages of k-core percolation models is the validity of an analytical mathematical framework for a large class of network topologies. We study ternary mixtures of node types in random networks and show the presence of a new type of critical phenomenon. This scenario may have useful applications in the stability of large scale infrastructures and the description of glass-forming systems.Comment: To appear in Complex Networks, Studies in Computational Intelligence, Proceedings of CompleNet 201

Global genomic analysis of microbial biotransformation of arsenic highlights the importance of arsenic methylation in environmental and human microbiomes

Arsenic is a ubiquitous toxic element, the global cycle of which is highly affected by microbial redox reactions and assimilation into organoarsenic compounds through sequential methylation reactions. While microbial biotransformation of arsenic has been studied for decades, the past years have seen the discovery of multiple new genes related to arsenic metabolism. Still, most studies focus on a small set of key genes or a small set of cultured microorganisms. Here, we leveraged the recently greatly expanded availability of microbial genomes of diverse organisms from lineages lacking cultivated representatives, including those reconstructed from metagenomes, to investigate genetic repertoires of taxonomic and environmental controls on arsenic metabolic capacities. Based on the collection of arsenic-related genes, we identified thirteen distinct metabolic guilds, four of which combine the aio and ars operons. We found that the best studied phyla have very different combinations of capacities than less well-studied phyla, including phyla lacking isolated representatives. We identified a distinct arsenic gene signature in the microbiomes of humans exposed or likely exposed to drinking water contaminated by arsenic and that arsenic methylation is important in soil and in human microbiomes. Thus, the microbiomes of humans exposed to arsenic have the potential to exacerbate arsenic toxicity. Finally, we show that machine learning can predict bacterial arsenic metabolism capacities based on their taxonomy and the environment from which they were sampled

Deconfinement and the Hagedorn Transition in String Theory

Superseded and extended in hep-th/0105110 and hep-th/0208112.Comment: Superseded and extended in hep-th/0105110 and hep-th/020811

Impacts of Co-Solvent Flushing on Microbial Populations Capable of Degrading Trichloroethylene

With increased application of co-solvent flushing technologies for removal of nonaqueous phase liquids from groundwater aquifers, concern over the effects of the solvent on native microorganisms and their ability to degrade residual contaminant has also arisen. This study assessed the impact of ethanol flushing on the numbers and activity potentials of trichloroethylene (TCE)-degrading microbial populations present in aquifer soils taken immediately after and 2 years after ethanol flushing of a former dry cleaners site. Polymerase chain reaction analysis revealed soluble methane monooxygenase genes in methanotrophic enrichments, and 16S rRNA analysis identified Methylocystis parvus with 98% similarity, further indicating the presence of a type II methanotroph. Dissimilatory sulfite reductase genes in sulfate-reducing enrichments prepared were also observed. Ethanol flushing was simulated in columns packed with uncontaminated soils from the dry cleaners site that were dosed with TCE at concentrations observed in the field; after flushing, the columns were subjected to a continuous flow of 500 pore volumes of groundwater per week. Total acridine orange direct cell counts of the flushed and nonflushed soils decreased over the 15-week testing period, but after 5 weeks, the flushed soils maintained higher cell counts than the nonflushed soils. Inhibition of methanogenesis by sulfate reduction was observed in all column soils, as was increasing removal of total methane by soils incubated under methanotrophic conditions. These results showed that impacts of ethanol were not as severe as anticipated and imply that ethanol may mitigate the toxicity of TCE to the microorganisms