Groundwater and Intergovernmental Relations in the Southern San Joaquin Valley, California

25 pages (includes maps)

Solo librarian: jack-of-all-trades

pp. 109-11

Successful examples of the application of novel iterative trainable algorithms to guide rational mutation strategies for enzyme engineering: From prediction to lab testing to algorithm retraining

Both natural mutations occurring in a homologous enzyme family and mutations engineered in a given protein can have a tremendous impact in the activity and binding behavior of the enzyme towards substrates or other molecules. Binding and catalytic properties can be modified by rationally mutating selected amino acids in a protein. For instance, new specificity properties can be engineered into existing enzymes, which can be applied to the rational design of mutations to alter its catalysis. Although this approach has been largely used, the modifications introduced in the target protein have not been exempt of deleterious effects on protein function, binding or physicochemical properties. Much finer tuned modifications should be designed in order to alter the desired catalytic or binding properties of a protein and simultaneously not affecting other protein properties or functions. These engineered mutations usually require a thorough knowledge of the relevant structure-function relationships in the protein molecule. If no precise structure-function information is available for a protein, the amount of possible amino acid mutations to be tested precludes a direct search. Furthermore, in many cases a directed evolution strategy cannot be successfully used to achieve the desired results due to the unavailability of suitable screening tests. In the last years, we have developed new and powerful in silico methodologies to automatically propose, test and redesign mutagenesis strategies for a target protein, based only on evolutionarily conserved physicochemical properties of amino acids in a protein family where the target protein belongs, and on structural properties, including calculation of vibrational entropies, if available, with no need of explicit structure-function relationships. This methodology identifies amino acid positions that are putatively responsible for function, specificity, stability or binding interactions in a family of proteins and calculates amino acid propensity and distributions at each position. Not only conserved amino acid positions in a protein family can be labelled as functionally relevant, but also non-conserved amino acid positions can be identified to have a meaningful functional effect, and even amino acid substitutions that are unobserved in nature. These results can be used to predict if a given mutation can have a functional implication and which mutation is most likely to be functionally silent for a protein. Through several rounds of mutation suggestions, laboratory testing of the mutants and feedback of results to retrain the algorithms, our methodology can be used to rapidly and automatically discard any irrelevant mutation and guide the research focus toward functionally significant mutations. In this work, we will show how we have successfully used our publicly available methods to guide mutant design in enzyme engineering applied to xylanases (producing an improved octuple mutant in a single mutagenesis round), proteases, glucanases, ubiquitin ligases and other enzymes, to alter protein function, stability or thermodynamic properties independently of their catalytic properties in vitro and in vivo. We will also show how the predictions of these methods have been employed to shift chromatographic elution profiles of xylanases and ferritin nanocages for better purification without affecting their activity and to obtain ferritin variants with better properties to be used in nanotechnological applications, including modifications to the external and internal surface of the protein to change its interaction properties, improve its recombinant production, alter the characteristics of nanoparticles within or change its organic molecule carrier capacity. Finally, we will show how a similar approach has been integrated in an artificial intelligence classification scheme to identify somatic mutations in the human VHL gene that are related to renal clear-cell cancer and to predict the clinical outcome and prognosis of pVHL mutation and malfunction in humans, based on specific disruption of interactions with VHL binding partners. Clearly, our techniques show promising performance as a valuable and powerful bioinformatics tool to aid in the computer-aided design of engineered enzyme variants and in the understanding of function-structure, binding and affinity relationships in enzymes and other proteins

Genome-scale reconstruction of Salinispora tropica metabolism; Microbial engineering and its applications in secondary metabolite production

Bacteria within the order Actinomycetales are a well-known source of natural products such as antibiotics and anticancer agents, and the genus Salinispora is no exception. Salinispora tropica is a marine actinomycete that produces diverse secondary metabolites, including many that possess pharmaceutical properties such as Salinosporamide A (NPI-0052), a potent anticancer agent, and sporolides, candidates for antiviral compounds. Here, we present the first manually curated genome-scale metabolic model (iCC908) for Salinispora tropica strain CNB-440. The reconstruction enables characterization of the metabolic capabilities for understanding and modeling the cellular physiology of this newly sequenced genome. The model was based on physiological and biochemical information of primary and secondary metabolism pathways. The reconstructed stoichiometric matrix consists of 1169 biochemical reactions, 204 transport reactions and 1317 metabolites. A total of 908 structural open reading frames (ORFs) were included in the reconstructed network. The number of gene functions included corresponds to 20% of all characterized ORFs in the S. tropica genome. The genome-scale metabolic model was used to study strain-specific capabilities in defined minimal media and to analyze growth capabilities in 41 different minimal growth-supporting environments. These nutrient sources were evaluated experimentally to assess the accuracy of in-silico growth simulations. The model predicted no auxotrophies for essential amino acids, which was corroborated experimentally. The strain is able to use 21 different carbon sources, 8 nitrogen sources and 4 sulfur sources from the nutrient sources tested. Cases where the model was incorrect provided opportunities to gain new insights into the physiology of this specie and generate hypotheses. The incorporation of modifications led to increased accuracy in predicting the outcome of growth/no growth experiments from 76 to 93%. New data, and modifications can be incorporated into the reconstruction to iteratively improve the reconstruction. Since specialized pathways were included in the reconstruction, growth simulations and in silico gene deletions can be performed by using flux balance analysis (FBA) to dramatically increase secondary metabolites production and yield in Salinispora for possible “gene cluster identification” so specific pathways can be cloned in more efficient strains. For example, iCC908 has been used to define a production medium to improve Salinosporamide A production in a recombinant strain with increases over 20% compared to the wild type. This presentation will describe the main features of the metabolic flux analysis and microbial engineering methodology based on reconstruction of the whole metabolism and its applications in the optimization of secondary metabolite production

Federalism and the Wild and Scenic Rivers Act: Now You See It, Now You Don\u27t

This article investigates the proposed designation of the North Coast rivers under WSRA. It chronicles developments in the legal controversy and relates them to the larger issues of land and water management. The shifting legal framework and changing economic and political interests in the North Coast controversy are particularly enlightening to students of federalism. Lawyers are among those who may be tempted to view the North Coast controversy in terms of federal-state conflict or intergovernmental cooperation run amuck, and to view the courts as an umpire in a dispute over authority

Use of Genome-scale Models to get new insights into the MarineActinomycete genus Salinispora: Microbial engineering and its application in secondary metabolite production

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Thirty years of SN 1980K: Evidence for light echoes

We report optical and mid-infrared photometry of SN 1980K between 2004 and 2010, which show slow monotonic fading consistent with previous spectroscopic and photometric observations made 8 to 17 years after outburst. The slow rate-of-change over two decades suggests that this evolution may result from scattered and thermal light echoes off of extended circumstellar material. We present a semi- analytic dust radiative-transfer model that uses an empirically corrected effective optical depth to provide a fast and robust alternative to full Monte-Carlo radiative transfer modeling for homogenous dust at low to intermediate optical depths. We find that unresolved echoes from a thin circumstellar shell 14-15 lt-yr from the progenitor, and containing about 0.02 Msun of carbon-rich dust, can explain the broadband spectral and temporal evolution. The size, mass and dust composition are in good agreement with the contact discontinuity observed in scattered echoes around SN 1987A. The origin of slowly-changing high-velocity [O I] and Halpha lines is also considered. We propose an origin in shocked high-velocity metal-rich clumps of ejecta, rather than arising in the impact of ejecta on slowly-moving circumstellar material, as is the case with hot spots in SN 1987A.Comment: Accepted 2/14/12 to be published in ApJ. 15 pages, 10 figure