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The Yersinia pestis proteome was studied as a function of temperature and calcium by two-dimensional differential gel electrophoresis. Over 4,100 individual protein spots were detected, of which hundreds were differentially expressed. A total of 43 differentially expressed protein spots, representing 24 unique proteins, were identified by mass spectrometry. Differences in expression were observed for several virulence-associated factors, including catalase-peroxidase (KatY), murine toxin (Ymt), plasminogen activator (Pla), and F1 capsule antigen (Caf1), as well as several putative virulence factors and membrane-bound and metabolic proteins. Differentially expressed proteins not previously reported to contribute to virulence are candidates for more detailed mechanistic studies, representing potential new virulence determinants.

Abstract Background Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling. Results We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes. Conclusion Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems.

We are in the midst of a revolutionary period in the life sciences. Technological capabilities have dramatically expanded, we have a much improved understanding of the complex biology of selected [...]

Background: Recent technological advances in high-throughput data collection allow for experimental study of increasingly complex systems on the scale of the whole cellular genome and proteome. Gene network models are needed to interpret the resulting large and complex data sets. Rationally designed perturbations (e.g., gene knock-outs) can be used to iteratively refine hypothetical models, suggesting an approach for high-throughput biological system analysis. We introduce an approach to gene network modeling based on a scalable linear variant of fuzzy logic: a framework with greater resolution than Boolean logic models, but which, while still semi-quantitative, does not require the precise parameter measurement needed for chemical kinetics-based modeling. Results: We demonstrated our approach with exhaustive search for fuzzy gene interaction models that best fit transcription measurements by microarray of twelve selected genes regulating the yeast cell cycle. Applying an efficient, universally applicable data normalization and fuzzification scheme, the search converged to a small number of models that individually predict experimental data within an error tolerance. Because only gene transcription levels are used to develop the models, they include both direct and indirect regulation of genes. Conclusion: Biological relationships in the best-fitting fuzzy gene network models successfully recover direct and indirect interactions predicted from previous knowledge to result in transcriptional correlation. Fuzzy models fit on one yeast cell cycle data set robustly predict another experimental data set for the same system. Linear fuzzy gene networks and exhaustive rule search are the first steps towards a framework for an integrated modeling and experiment approach to high-throughput "reverse engineering" of complex biological systems. [ABSTRACT FROM AUTHOR]

Increasingly sophisticated technologies are needed for counterterrorism responses to biological and chemical warfare agents. Recently developed detection and identification systems are characterized by increased sensitivity, greater automation, and fewer false alarms. Attempts are also under way to reduce the cost and complexity of field-deployable systems. A broad range of decontamination reagents for equipment and personnel is emerging, but decontamination of large buildings, inaccessible spaces, and sensitive equipment remains problematic. [ABSTRACT FROM AUTHOR]

The authors discuss the move of the U.S. National Science Advisory Board for Biosecurity to explain its recommendations on the communication of experimental work on H5N1 influenza. They mentions that highly pathogenic avian influenza A infection has been a serious public health concern since its identification in Asia. The state that to date, no human pandemic has occurred.

Host–pathogen interactions result in protein expression changes within both the host and the pathogen. Here, results from proteomic characterization of host response following exposure to Yersinia pestis, the causative agent of plague, and to two near neighbors, Yersinia pseudotuberculosis and Yersinia enterocolitica, are reported. Human monocyte-like cells were chosen as a model for macrophage immune response to pathogen exposure. Two-dimensional electrophoresis followed by mass spectrometry was used to identify host proteins with differential expression following exposure to these three closely related Yersinia species. This comparative proteomic characterization of host response clearly shows that host protein expression patterns are distinct for the different pathogen exposures, and contributes to further understanding of Y. pestis virulence and host defense mechanisms. This work also lays the foundation for future studies aimed at defining biomarkers for presymptomatic detection of plague. [Copyright &y& Elsevier]

A novel method to screen for transcription factors binding to promoter DNA sequences has been developed using DNA chip surfaces and mass spectrometry. This technique was demonstrated with Escherichia coli lac repressor, LacI. The consensus promoter binding sequence for LacI and a scrambled version of the same DNA sequence were prepared on two affinity chip surfaces. Total E. coli protein lysate was applied to the two surfaces. A 38.2 kDa protein, as detected by SELDI-MS, was captured on the chip surface containing the binding sequence for LacI but not on the surface containing the scrambled sequence. The protein was identified following one-step, small-scale affinity capture and peptide mapping. Subsequent database searches identified the 38.2 kDa protein as the lac repressor of E. coli. We discuss application of DNA chip affinity capture to characterize transcription factors and to screen for differences in cellular regulatory networks. [Copyright &y& Elsevier]

In late 2010, the National Biodefense Analysis and Countermeasures Center (NBACC) implemented a Personnel Reliability Program (PRP) with the goal of enabling active participation by its staff to drive and improve the biosafety and biosecurity culture at the organization. A philosophical keystone for accomplishment of NBACC's scientific mission is simultaneous excellence in operations and outreach. Its personnel reliability program builds on this approach to: (1) enable and support a culture of responsibility based on human performance principles, (2) maintain compliance with regulations, and (3) address the risk associated with the insider threat. Recently, the Code of Federal Regulations (CFR) governing use and possession of biological select agents and toxins (BSAT) was amended to require a pre-access suitability assessment and ongoing evaluation for staff accessing Tier 1 BSAT. These 2 new requirements are in addition to the already required Federal Bureau of Investigation (FBI) Security Risk Assessment (SRA). Two years prior to the release of these guidelines, NBACC developed its PRP to supplement the SRA requirement as a means to empower personnel and foster an operational environment where any and all work with BSAT is conducted in a safe, secure, and reliable manner.

Yersinia pestis, the etiological agent of plague, is of concern to human health both from an infectious disease and a biodefense perspective. While Y. pestis and Yersinia pseudotuberculosis share more than 90% DNA homology, they have significantly different clinical manifestations. Plague is often fatal if untreated, yet Y. pseudotuberculosis causes severe intestinal distress but is rarely fatal. A better understanding of host response to these closely related pathogens may help explain the different mechanisms of virulence and pathogenesis that result in such different clinical outcomes. The aim of this study was to characterize host protein expression changes in human monocyte U937 cells after exposure to Y. pestis and Y. pseudotuberculosis. In order to gain global proteomic coverage of host response, proteins from cytoplasmic, nuclear and membrane fractions of host cells were studied by two-dimensional differential gel electrophoresis and relative protein expression differences were quantitated. Differentially expressed proteins, with at least 1.5-fold expression changes and p values of 0.01 or less, were identified by mass spectrometry including matrix-assisted laser desorption/ionization-MS or liquid chromatography tandem mass spectrometry. With these criteria, differential expression was detected in 16 human proteins after Y. pestis exposure and 13 human proteins after Y. pseudotuberculosis exposure, of which only two of the differentially expressed proteins identified were shared between the two exposures. Proteins identified in this study are reported to be involved in a wide spectrum of cellular functions and host defense mechanisms including apoptosis, cytoskeletal rearrangement, protein synthesis and degradation, DNA replication and transcription, metabolism, protein folding, and cell signaling. Notably, the differential expression patterns observed can distinguish the two pathogen exposures from each other and from unexposed host cells. The functions of the differentially expressed proteins identified provide insight on the different virulence and pathogenic mechanisms of Y. pestis and Y. pseudotuberculosis.