The Report of the 2012-2013 Research and Graduate Affairs Committee

The RGA Committee met on October 29-30, 2012, in Crystal City, VA. The Committee corresponded via e-mail throughout the year, and had a conference call on June 13, 2013. The charge for the RGA Committee was to develop strategies on how to get our members to the right tables and at the right time for advancing pharmacy research and graduate education

Chitin Binding Proteins Act Synergistically with Chitinases in Serratia proteamaculans 568

Genome sequence of Serratia proteamaculans 568 revealed the presence of three family 33 chitin binding proteins (CBPs). The three Sp CBPs (Sp CBP21, Sp CBP28 and Sp CBP50) were heterologously expressed and purified. Sp CBP21 and Sp CBP50 showed binding preference to β-chitin, while Sp CBP28 did not bind to chitin and cellulose substrates. Both Sp CBP21 and Sp CBP50 were synergistic with four chitinases from S. proteamaculans 568 (Sp ChiA, Sp ChiB, Sp ChiC and Sp ChiD) in degradation of α- and β-chitin, especially in the presence of external electron donor (reduced glutathione). Sp ChiD benefited most from Sp CBP21 or Sp CBP50 on α-chitin, while Sp ChiB and Sp ChiD had major advantage with these Sp CBPs on β-chitin. Dose responsive studies indicated that both the Sp CBPs exhibit synergism ≥0.2 µM. The addition of both Sp CBP21 and Sp CBP50 in different ratios to a synergistic mixture did not significantly increase the activity. Highly conserved polar residues, important in binding and activity of CBP21 from S. marcescens (Sm CBP21), were present in Sp CBP21 and Sp CBP50, while Sp CBP28 had only one such polar residue. The inability of Sp CBP28 to bind to the test substrates could be attributed to the absence of important polar residues

KAP Degradation by Calpain Is Associated with CK2 Phosphorylation and Provides a Novel Mechanism for Cyclosporine A-Induced Proximal Tubule Injury

The use of cyclosporine A (CsA) is limited by its severe nephrotoxicity that includes reversible vasoconstrictor effects and proximal tubule cell injury, the latter associated whith chronic kidney disease progression. The mechanisms of CsA-induced tubular injury, mainly on the S3 segment, have not been completely elucidated. Kidney androgen-regulated protein (KAP) is exclusively expressed in kidney proximal tubule cells, interacts with the CsA-binding protein cyclophilin B and its expression diminishes in kidneys of CsA-treated mice. Since we reported that KAP protects against CsA toxicity in cultured proximal tubule cells, we hypothesized that low KAP levels found in kidneys of CsA-treated mice might correlate with proximal tubule cell injury. To test this hypothesis, we used KAP Tg mice developed in our laboratory and showed that these mice are more resistant to CsA-induced tubular injury than control littermates. Furthermore, we found that calpain, which was activated by CsA in cell cultures and kidney, is involved in KAP degradation and observed that phosphorylation of serine and threonine residues found in KAP PEST sequences by protein kinase CK2 enhances KAP degradation by calpain. Moreover, we also observed that CK2 inhibition protected against CsA-induced cytotoxicity. These findings point to a novel mechanism for CsA-induced kidney toxicity that might be useful in developing therapeutic strategies aimed at preventing tubular cell damage while maintaining the immunosuppressive effects of CsA

A Staphylococcus xylosus isolate with a new mecC allotype

Recently, a novel variant of mecA known as mecC (mecA(LGA251)) was identified in Staphylococcus aureus isolates from both humans and animals. In this study, we identified a Staphylococcus xylosus isolate that harbors a new allotype of the mecC gene, mecC1. Whole-genome sequencing revealed that mecC1 forms part of a class E mec complex (mecI-mecR1-mecC1-blaZ) located at the orfX locus as part of a likely staphylococcal cassette chromosome mec element (SCCmec) remnant, which also contains a number of other genes present on the type XI SCCmec

Deploying gas power with CCS: The role of operational flexibility, merit order and the future energy system

Combined cycle gas turbine (CCGT) power plants are an important part of many electricity systems. By fitting them with carbon capture their CO2 emissions could be virtually eliminated. We evaluate CCGT plants with different variations of post combustion capture using amine solvents, covering a range of options, including solvent storage, partial capture and shifting the energy penalty in time. The analysis is based on the UK electricity system in 2025. The behaviour of individual CCGT plants is governed by the plant’s place in the merit order and to a lesser extent by CO2 reduction targets for the electricity system. In the UK, CCGT plants built from 2016 onwards will emit ~90% of the CO2 emissions of the whole CCGT fleet in 2025. The typical ‘base case’ CCGT plant with capture is designed to capture 90% of the CO2 emissions and to operate dynamically with the power plant. Downsizing the capture facility could be attractive for low-merit plants, i.e. plants with high short-run marginal costs. Solvent storage enables electricity generation to be decoupled in time from the energy penalty associated with carbon capture. Beyond a few minutes of solvent storage, substantial tanks would be needed. If solvent storage is to play an important role, it will require definitions of ‘capture ready’ to be expanded to ensure sufficient land is available

Structural and pharmacological basis for the induction of mitochondrial biogenesis by formoterol but not clenbuterol

Mitochondrial dysfunction is associated with numerous acute and chronic degenerative diseases. The beta-2 adrenergic receptor (beta(2)AR) agonist formoterol induces mitochondrial biogenesis (MB), but other beta(2)AR agonists, such as clenbuterol, do not. We sought to identify the MB signaling pathway of formoterol and the differences in signaling between these two ligands that result in the differential induction of MB. While formoterol and clenbuterol increased cAMP, only formoterol increased the phosphorylation of Akt and its downstream target eNOS. The increase in Akt phosphorylation was G beta gamma- and PI3K-dependent, and the increase in eNOS phosphorylation was G beta gamma- and Akt-dependent. Only formoterol increased cGMP. Formoterol induced MB as measured by increases in uncoupled cellular respiration and PGC-1 alpha and NDUFS1 mRNA expression and was blocked by inhibitors of G beta gamma, Akt, NOS, and soluble guanylate cyclase. To identify distinct receptor-ligand interactions leading to these differences in signaling, we docked formoterol and clenbuterol to six structures of the beta(2)AR. Compared to clenbuterol, the methoxyphenyl group of formoterol interacted more frequently with V114 and F193, while its formamide group interacted more frequently with C191. These data indicate that the unique structural features of formoterol allow it to interact with the beta(2)AR to activate the G beta gamma-Akt-eNOS-sGC pathway to induce MB.National Institutes of Health [F30 DK104550, T32 GM008716, T32 HL007260, P20 GM103542, R01 GM084147]; Department of Veterans Affairs [1BX000851]This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Experimental methods in chemical engineering: Artificial neural networks–ANNs

Artificial neural networks (ANNs) are one of the most powerful and versatile tools provided by artificial intelligence and they have now been exploited by chemical engineers for several decades in countless applications. ANNs are computational tools providing a minimalistic mathematical model of neural functions. Coupled with raw data and a learning algorithm, they can be applied to tasks such as modelling, classification, and prediction. Recently, their popularity has grown remarkably and they now constitute one of the most relevant research areas within the fields of artificial intelligence and machine learning. ANNs are large collections of simple classifiers called neurons. Chemical engineers apply them to model complex relationships, predict reactor performance, and to automate process controllers. ANNs can leverage their ability to learn and exploit large data sets, but they can also get stuck in local minima or overfit and are difficult to reverse engineer. In 2016 and 2017, ANNs were cited in 13 245 Web of Science (WoS) articles, 538 of which were in chemical engineering; the top WoS categories were electrical & electronic engineering (1615 occurrences) artificial intelligence (1253), and energy & fuels (980). The top 4 journals mentioning ANNs were Neural Computing & Applications (117), Neurocomputing (84), Energies (76), and Renewable & Sustainable Energy Reviews (76). In the near future, as larger data sets become available (and arduous to analyze), chemical engineers will be able to apply and leverage more sophisticated ANN architectures