The Immune Inhibitor A1 Protease of \u3cem\u3eBacillus anthracis\u3c/em\u3e

Bacillus anthracis, an organism ubiquitous in the soil and the causative agent of anthrax, utilizes multiple mechanisms to regulate secreted factors; one example is the activity of secreted proteases. One of the most abundant proteins in the culture supernates of B. anthracis is the Immune Inhibitor A1 (InhA1) protease. Here, I demonstrate that InhA1 modulates the abundance of approximately half of the proteins secreted into the culture supernates, including substrates that are known to contribute to the ability of the organism to cause virulence. For example, InhA1 cleaves the anthrax toxin proteins, PA, LF, and EF. InhA1 also targets a number of additional proteases, including Npr599, contributing to a complex proteolytic regulatory cascade with far-reaching affects on the secretome. Using an intra-tracheal mouse model of infection, I found that an inhA-null strain is attenuated in relation to the parent strain. The data indicate that reduced virulence of the inhA mutant strain may be the result of toxin protein deregulation, decreased association with macrophages, and/or the inability to degrade host antimicrobial peptides. Given the significant modulation of the secretome by InhA1, it is likely that expression of the protease is tightly regulated. To test this I examined inhA1 transcript and protein levels in the parent and various isogenic mutant strains and found that InhA1 expression is regulated by several mechanisms. First, the steady state levels of inhA1 transcript are controlled by the regulatory protein SinR, which inhibits inhA1 expression. Second, InhA1 abundance is inversely proportional to the SinR-regulated protease camelysin, indicating the post-transcriptional regulation of InhA1 by camelysin. Third, InhA1 activity is dependent on a conserved zinc binding motif, suggesting that zinc availability regulates InhA1 activity. The convergence of these regulatory mechanisms signifies the importance of tight regulation of InhA1 activity, activity that substantially affects how B. anthracis interacts with its environment

Subtask 2.6 - Assessment of Alternative Fuels on CO2 Production

Many coal-based electric generating units use alternative fuels, and this effort assessed the impact of alternative fuels on CO{sub 2} production and other emissions and also assessed the potential impact of changes in emission regulations under the Clean Air Act (CAA) for facilities utilizing alternative fuels that may be categorized as wastes. Information was assembled from publicly available U.S. Department of Energy Energy Information Administration databases that included alternative fuel use for 2004 and 2005. Alternative fuel types were categorized along with information on usage by coal-based electric, number of facilities utilizing each fuel type, and the heating value of solid, liquid, and gaseous alternative fuels. The sulfur dioxide, nitrogen oxide, and carbon dioxide emissions associated with alternative fuels and primary fuels were also evaluated. Carbon dioxide emissions are also associated with the transport of all fuels. A calculation of carbon dioxide emissions associated with the transport of biomass-based fuels that are typically accessed on a regional basis was made. A review of CAA emission regulations for coal-based electric generating facilities from Section 112 (1) and Section 129 (2) for solid waste incinerators was performed with consideration for a potential regulatory change from Section 112 (1) regulation to Section 129 (2). Increased emission controls would be expected to be required if coal-based electric generating facilities using alternative fuels would be recategorized under CAA Section 129 (2) for solid waste incinerators, and if this change were made, it is anticipated that coal-fired electric generating facilities might reduce the use of alternative fuels. Conclusions included information on the use profile for alternative fuels and the impacts to emissions as well as the impact of potential application of emission regulations for solid waste incinerators to electric generating facilities using alternative fuels

Data Visualization Using Figural Animation

One of the important objectives of business data visualization for decision making is to assist the user in their cognition and recall of prominent features and patterns of data. In this study, we extend Chernoff faces to full-featured animated figures to represent multi-dimensional data. A prototype has been developed that allows the user to easily assign data attributes to figural features as well as superimpose the data values. Once these settings have been made and the temporal dimension assigned, the animation is rendered through Poser and the video is embedded within the user interface. The figural animation contains VCR-type controls allowing the user to examine any particular data point or play any portion of the video at various speeds. A series of tests are being designed to determine if the application enhances the user’s ability to recall and display patterns in data

MERCURY AND AIR TOXIC ELEMENT IMPACTS OF COAL COMBUSTION BY-PRODUCT DISPOSAL AND UTILIZATION

Preliminary work focused on initiating communications among the project sponsors and developing a detailed work plan for Year 1 of the project. Preparations for the project kickoff meeting included development of detailed work plans for all three years of the project, with emphasis on Year 1, development of sample selection criteria, and identification of information required on samples to be included in the study

Development of a coal combustion product (CCP) database system. Final report

Nearly 90 million tons of coal combustion products (CCPs) are produced annually in the United States. The value of CCPs is well established by research and commercial practice; however, only 25% of these products are utilized. The objective of this project was to develop a computer program containing a database of advanced analytical and comprehensive engineering information on CCPs, accessible through a user-friendly interface. Version 1.0 of the ACAA CCP Data Manager was specifically designed to: perform multiple-criteria queries to produce a set of sample for in-depth study; view and print standard test reports, such as C618 reports; compare and contrast analytical results in graphs and tables; graph utilization information by application and region; and save data to a file for use in other computer applications, such as spreadsheet programs. The program was designed to contain descriptive information about a given CCP sample, including sample formation data (material type, sample location, fuel type, collection device etc.), combustion system design data (steam generator type, furnace type, SO{sub 2} and NO{sub x} control information, ash-handling configurations), test data (chemical, mineralogical, and physical characterization data), and utilization potential of the CCP. The location of the plant is identified by region. The database has been initially populated with information on over 800 CCP samples, taken from the Coal Ash Resources Research Consortium (CARRC). An installation package and user`s guide was developed for unlimited distribution by the American Coal Ash Association (ACAA)

Development of a database management system for Coal Combustion By-Products (CCBs)

Coal combustion by-products (CCBs) are produced in high volumes worldwide. Utilization of these materials is economically and environmentally advantageous and is expected to increase as disposal costs increase. The American Coal Ash Association (ACAA) is developing a database to contain characterization and utilization information on CCBs. This database will provide information for use by managers, marketers, operations personnel, and researchers that will aid in their decision making and long-term planning for issues related to CCBs. The comprehensive nature of the database and the interactive user application will enable ACAA members to efficiently and economically access a wealth of data on CCBs and will promote the technically sound, environmentally safe, and commercially competitive use of CCBs

Contribution of murine IgG Fc regions to antibody binding to the capsule of Burkholderia pseudomallei.

Immunoglobulin G3 (IgG3) is the predominant IgG subclass elicited in response to polysaccharide antigens in mice. This specific subclass has been shown to crosslink its fragment crystallizable (Fc) regions following binding to multivalent polysaccharides. Crosslinking leads to increased affinity through avidity, which theoretically should lead to more effective protection against bacteria and yeast displaying capsular polysaccharides on their surface. To investigate this further we have analyzed the binding characteristics of 2 IgG monoclonal antibody (mAb) subclass families that bind to the capsular polysaccharide (CPS) of Burkholderia pseudomallei. The first subclass family originated from an IgG3 hybridoma cell line (3C5); the second family was generated from an IgG1 cell line (2A5). When the Fc region of the 3C5 IgG3 is removed by proteolytic cleavage, the resulting F(ab')2 fragments exhibit decreased affinity compared to the full-length mAb. Similarly, when the parent IgG3 mAb is subclass-switched to IgG1, IgG2b, and IgG2a, all of these subclasses exhibit decreased affinity. This decrease in affinity is not seen when the 2A5 IgG1 mAb is switched to an IgG2b or IgG2a, strongly suggesting the drop in affinity is related to the IgG3 Fc region

Effective Social Media Engagement Options for Minnesota’s Diversifying Population

Minnesota Department of Transportation (MnDOT) and Minnesota Local Road Research Board (LRRB) supported the University of Minnesota to investigate social media options for effective public engagement. A three-part approach assessed 1) the state of social media use through a literature review, 2) the status of social media use and interest in its use for transportation in Minnesota compared to national data, and 3) actual and perceived effectiveness of social media in two pairs of case studies in Minnesota. In sum, results reveal social media is effective as a strategic and select part of engagement plans and can likely effectively engage select groups. Survey results revealed 11-21% of respondents participated in planning for transportation programs, policies or projects in the last 12 months, 72% use social media of some sort, and 36% expressed interest in using social media to get information, provide feedback or make suggestions related to transportation. Finally, social media analytics and interviews related to four case studies revealed social media does indeed lead transportation projects to make more connections with stakeholders, but the quality and effectiveness of those connections vary. Four main opportunities include: 1) integrating social media into multi-pronged, dynamic engagement approaches, 2) considering the demographic qualities of the key stakeholders to determine how social media can be most useful, 3) employing best practices for social media engagement, and 4) expanding and/ or developing research and evaluation plans to understand and assess future social media engagement efforts

Multi-platform Approach for Microbial Biomarker Identification Using Borrelia burgdorferi as a Model

The identification of microbial biomarkers is critical for the diagnosis of a disease early during infection. However, the identification of reliable biomarkers is often hampered by a low concentration of microbes or biomarkers within host fluids or tissues. We have outlined a multi-platform strategy to assess microbial biomarkers that can be consistently detected in host samples, using Borrelia burgdorferi, the causative agent of Lyme disease, as an example. Key aspects of the strategy include the selection of a macaque model of human disease, in vivo Microbial Antigen Discovery (InMAD), and proteomic methods that include microbial biomarker enrichment within samples to identify secreted proteins circulating during infection. Using the described strategy, we have identified 6 biomarkers from multiple samples. In addition, the temporal antibody response to select bacterial antigens was mapped. By integrating biomarkers identified from early infection with temporal patterns of expression, the described platform allows for the data driven selection of diagnostic targets