A Serological Survey of Infectious Disease in Yellowstone National Park’s Canid Community

BACKGROUND:Gray wolves (Canis lupus) were reintroduced into Yellowstone National Park (YNP) after a >70 year absence, and as part of recovery efforts, the population has been closely monitored. In 1999 and 2005, pup survival was significantly reduced, suggestive of disease outbreaks. METHODOLOGY/PRINCIPAL FINDINGS:We analyzed sympatric wolf, coyote (Canis latrans), and red fox (Vulpes vulpes) serologic data from YNP, spanning 1991-2007, to identify long-term patterns of pathogen exposure, identify associated risk factors, and examine evidence for disease-induced mortality among wolves for which there were survival data. We found high, constant exposure to canine parvovirus (wolf seroprevalence: 100%; coyote: 94%), canine adenovirus-1 (wolf pups [0.5-0.9 yr]: 91%, adults [>or=1 yr]: 96%; coyote juveniles [0.5-1.5 yrs]: 18%, adults [>or=1.6 yrs]: 83%), and canine herpesvirus (wolf: 87%; coyote juveniles: 23%, young adults [1.6-4.9 yrs]: 51%, old adults [>or=5 yrs]: 87%) suggesting that these pathogens were enzootic within YNP wolves and coyotes. An average of 50% of wolves exhibited exposure to the protozoan parasite, Neospora caninum, although individuals' odds of exposure tended to increase with age and was temporally variable. Wolf, coyote, and fox exposure to canine distemper virus (CDV) was temporally variable, with evidence for distinct multi-host outbreaks in 1999 and 2005, and perhaps a smaller, isolated outbreak among wolves in the interior of YNP in 2002. The years of high wolf-pup mortality in 1999 and 2005 in the northern region of the park were correlated with peaks in CDV seroprevalence, suggesting that CDV contributed to the observed mortality. CONCLUSIONS/SIGNIFICANCE:Of the pathogens we examined, none appear to jeopardize the long-term population of canids in YNP. However, CDV appears capable of causing short-term population declines. Additional information on how and where CDV is maintained and the frequency with which future epizootics might be expected might be useful for future management of the Northern Rocky Mountain wolf population

Metal-Substituted Microporous Aluminophosphates

This chapter aims to present the zeotypes aluminophosphates (AlPOs) as a complementary alternative to zeolites in the isomorphic incorporation of metal ions within all-inorganic microporous frameworks as well as to discuss didactically the catalytic consequences derived from the distinctive features of both frameworks. It does not intend to be a compilation of either all or the most significant publications involving metal-substituted microporous aluminophosphates. Families of AlPOs and zeolites, which include metal ion-substituted variants, are the dominant microporous materials. Both these systems are widely used as catalysts, in particular through aliovalent metal ions substitution. Here, some general description of the synthesis procedures and characterization techniques of the MeAPOs (metal-contained aluminophosphates) is given along with catalytic properties. Next, some illustrative examples of the catalytic possibilities of MeAPOs as catalysts in the transformation of the organic molecules are given. The oxidation of the hardly activated hydrocarbons has probably been the most successful use of AlPOs doped with the divalent transition metal ions Co2+, Mn2+, and Fe2+, whose incorporation in zeolites is disfavoured. The catalytic role of these MeAPOs is rationalized based on the knowledge acquired from a combination of the most advanced characterization techniques. Finally, the importance of the high specificity of the structure-directing agents employed in the preparation of MeAPOs is discussed taking N,N-methyldicyclohexylamine in the synthesis of AFI-structured materials as a driving force. It is shown how such a high specificity could be predicted and how it can open great possibilities in the control of parameters as critical in catalysis as crystal size, inter-and intracrystalline mesoporosity, acidity, redox properties, incorporation of a great variety of heteroatom ions or final environment of the metal site (surrounding it by either P or Al)

Tapping the wealth of microbial data in high-throughput metabolic model reconstruction

Genome-scale metabolic models are valuable tools in the metabolic engineering process, based on the ability of these models to integrate diverse sources of data to produce global predictions of organism behavior. At the most basic level, these models require only a genome sequence to construct, and once built, they may be used to predict essential genes, culture conditions, pathway utilization, and the modifications required to enhance a desired organism behavior. In this chapter, we address two key challenges associated with the reconstruction of metabolic models: (a) leveraging existing knowledge of microbiology, biochemistry, and available omics data to produce the best possible model; and (b) applying available tools and data to automate the reconstruction process. We consider these challenges as we progress through the model reconstruction process, beginning with genome assembly, and culminating in the integration of constraints to capture the impact of transcriptional regulation. We divide the reconstruction process into ten distinct steps: (1) genome assembly from sequenced reads; (2) automated structural and functional annotation; (3) phylogenetic tree-based curation of genome annotations; (4) assembly and standardization of biochemistry database; (5) genome-scale metabolic reconstruction; (6) generation of core metabolic model; (7) generation of biomass composition reaction; (8) completion of draft metabolic model; (9) curation of metabolic model; and (10) integration of regulatory constraints. Each of these ten steps is documented in detail.We acknowledge the entire SEED, Model SEED, and CytoSEED teams at Argonne National Laboratory, Fellowship for Interpretation of Genomes, Hope College and University of Chicago for efforts on the frameworks described in this chapter. This work was supported by the US Department of Energy under contract DE-ACO206CH11357 (J.F., F.X., C.H.), and the National Science Foundation under grants PGRP-1025398 (S.S.), EFRI-1137089 (R.C., T.K.) and MCB-1153413 (J.E.). José P Faria acknowledges funding from his Ph.D. grant SFRH/BD/70824/2010 of the FCT (Portuguese Foundation for Science and Technology)