Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth. Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the ‘‘hazard rate’’ that quantifies mortality risk ; (ii) a variable representing environmental degradation ; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels ; (iv) a new representation of the ‘‘lag time’’ based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory

Attitudes Toward Breast Cancer Genetic Testing in Five Special Population Groups

Purpose: This study examined interest in and attitudes toward genetic testing in 5 different population groups. Methods: The survey included African American, Asian American, Latina, Native American, and Appalachian women with varying familial histories of breast cancer. A total of 49 women were interviewed in person. Descriptive and nonparametric statistical techniques were used to assess ethnic group differences. Results: Overall, interest in testing was high. All groups endorsed more benefits than risks. There were group differences regarding endorsement of specific benefits and risks: testing to “follow doctor recommendations” (p=0.017), “concern for effects on family” (p=0.044), “distrust of modern medicine” (p=0.036), “cost” (p=0.025), and “concerns about communication of results to others” (p=0.032). There was a significant inverse relationship between interest and genetic testing cost (p Conclusion: Cost may be an important barrier to obtaining genetic testing services, and participants would benefit by genetic counseling that incorporates the unique cultural values and beliefs of each group to create an individualized, culturally competent program. Further research about attitudes toward genetic testing is needed among Asian Americans, Native Americans, and Appalachians for whom data are severely lacking. Future study of the different Latina perceptions toward genetic testing are encouraged

Nature of Guanine Oxidation in RNA via the Flash-Quench Technique versus Direct Oxidation by a Metal Oxo Complex

Oxidation of RNA can be effected by two different techniques: a photochemical, electron-transfer method termed “flash-quench” and direct oxidation by metal oxo complexes. The flash-quench method produces selective oxidation using a metal photosensitizer, tris(bipyridyl)ruthenium(III) trichloride (Ru(bpy)33+), and quencher, pentaamminechlorocobalt(III) chloride (Co(NH3)5Cl2+). We have optimized the flash-quench technique for the following RNAs: tRNAPhe, human ferritin iron-responsive element (IRE), and a mutated human ferritin IRE. We have also employed a chemical footprinting technique involving the oxoruthenium(IV) complex (Ru(tpy)(bpy)O2+ (tpy = 2,2′,2″-terpyridine; bpy = 2,2′-bipyridine)) to oxidize guanine. Comparison of the two methods shows that the flash-quench technique provides a visualization of nucleotide accessibility for a static conformation of RNA while the Ru(tpy)(bpy)O2+ complex selectively oxidizes labile guanines and gives a visualization of a composite of multiple conformations of the RNA structure

Performance of plate-based cytokine flow cytometry with automated data analysis

BACKGROUND: Cytokine flow cytometry (CFC) provides a multiparameter alternative to ELISPOT assays for rapid quantitation of antigen-specific T cells. To increase the throughput of CFC assays, we have optimized methods for stimulating, staining, and acquiring whole blood or PBMC samples in 96-well or 24-well plates. RESULTS: We have developed a protocol for whole blood stimulation and processing in deep-well 24- or 96-well plates, and fresh or cryopreserved peripheral blood mononuclear cell (PBMC) stimulation and processing in conventional 96-well round-bottom plates. Samples from both HIV-1-seronegative and HIV-1-seropositive donors were tested. We show that the percent response, staining intensity, and cell recovery are comparable to stimulation and processing in tubes using traditional methods. We also show the equivalence of automated gating templates to manual gating for CFC data analysis. CONCLUSION: When combined with flow cytometry analysis using an automated plate loader and an automated analysis algorithm, these plate-based methods provide a higher throughput platform for CFC, as well as reducing operator-induced variability. These factors will be important for processing the numbers of samples required in large clinical trials, and for epitope mapping of patient responses

Nano-La\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e Induces Honeybee (\u3cem\u3eApis mellifera\u3c/em\u3e) Death and Enriches for Pathogens in Honeybee Gut Bacterial Communities

Honeybees (Apis mellifera) can be exposed via numerous potential pathways to ambient nanoparticles (NPs), including rare earth oxide (REO) NPs that are increasingly used and released into the environment. Gut microorganisms are pivotal in mediating honeybee health, but how REO NPs may affect honeybee health and gut microbiota remains poorly understood. To address this knowledge gap, honeybees were fed pollen and sucrose syrup containing 0, 1, 10, 100, and 1000mgkg−1 of nano-La2O3 for 12days. Nano-La2O3 exerted detrimental effects on honeybee physiology, as reflected by dose-dependent adverse effects of nano-La2O3 on survival, pollen consumption, and body weight (p\u3c0.05). Nano-La2O3 caused the dysbiosis of honeybee gut bacterial communities, as evidenced by the change of gut bacterial community composition, the enrichment of pathogenic Serratia and Frischella, and the alteration of digestion-related taxa Bombella (p\u3c0.05). There were significant correlations between honeybee physiological parameters and the relative abundances of pathogenic Serratia and Frischella (p\u3c0.05), underscoring linkages between honeybee health and gut bacterial communities. Taken together, this study demonstrates that nano-La2O3 can cause detrimental effects on honeybee health, potentially by disordering gut bacterial communities. This study thus reveals a previously overlooked effect of nano-La2O3 on the ecologically and economically important honeybee species Apis mellifera

Standardization of cytokine flow cytometry assays

BACKGROUND: Cytokine flow cytometry (CFC) or intracellular cytokine staining (ICS) can quantitate antigen-specific T cell responses in settings such as experimental vaccination. Standardization of ICS among laboratories performing vaccine studies would provide a common platform by which to compare the immunogenicity of different vaccine candidates across multiple international organizations conducting clinical trials. As such, a study was carried out among several laboratories involved in HIV clinical trials, to define the inter-lab precision of ICS using various sample types, and using a common protocol for each experiment (see additional files online). RESULTS: Three sample types (activated, fixed, and frozen whole blood; fresh whole blood; and cryopreserved PBMC) were shipped to various sites, where ICS assays using cytomegalovirus (CMV) pp65 peptide mix or control antigens were performed in parallel in 96-well plates. For one experiment, antigens and antibody cocktails were lyophilised into 96-well plates to simplify and standardize the assay setup. Results (CD4(+)cytokine(+ )cells and CD8(+)cytokine(+ )cells) were determined by each site. Raw data were also sent to a central site for batch analysis with a dynamic gating template. Mean inter-laboratory coefficient of variation (C.V.) ranged from 17–44% depending upon the sample type and analysis method. Cryopreserved peripheral blood mononuclear cells (PBMC) yielded lower inter-lab C.V.'s than whole blood. Centralized analysis (using a dynamic gating template) reduced the inter-lab C.V. by 5–20%, depending upon the experiment. The inter-lab C.V. was lowest (18–24%) for samples with a mean of >0.5% IFNγ + T cells, and highest (57–82%) for samples with a mean of <0.1% IFNγ + cells. CONCLUSION: ICS assays can be performed by multiple laboratories using a common protocol with good inter-laboratory precision, which improves as the frequency of responding cells increases. Cryopreserved PBMC may yield slightly more consistent results than shipped whole blood. Analysis, particularly gating, is a significant source of variability, and can be reduced by centralized analysis and/or use of a standardized dynamic gating template. Use of pre-aliquoted lyophilized reagents for stimulation and staining can provide further standardization to these assays

Evolutionarily Conserved Substrate Substructures for Automated Annotation of Enzyme Superfamilies

The evolution of enzymes affects how well a species can adapt to new environmental conditions. During enzyme evolution, certain aspects of molecular function are conserved while other aspects can vary. Aspects of function that are more difficult to change or that need to be reused in multiple contexts are often conserved, while those that vary may indicate functions that are more easily changed or that are no longer required. In analogy to the study of conservation patterns in enzyme sequences and structures, we have examined the patterns of conservation and variation in enzyme function by analyzing graph isomorphisms among enzyme substrates of a large number of enzyme superfamilies. This systematic analysis of substrate substructures establishes the conservation patterns that typify individual superfamilies. Specifically, we determined the chemical substructures that are conserved among all known substrates of a superfamily and the substructures that are reacting in these substrates and then examined the relationship between the two. Across the 42 superfamilies that were analyzed, substantial variation was found in how much of the conserved substructure is reacting, suggesting that superfamilies may not be easily grouped into discrete and separable categories. Instead, our results suggest that many superfamilies may need to be treated individually for analyses of evolution, function prediction, and guiding enzyme engineering strategies. Annotating superfamilies with these conserved and reacting substructure patterns provides information that is orthogonal to information provided by studies of conservation in superfamily sequences and structures, thereby improving the precision with which we can predict the functions of enzymes of unknown function and direct studies in enzyme engineering. Because the method is automated, it is suitable for large-scale characterization and comparison of fundamental functional capabilities of both characterized and uncharacterized enzyme superfamilies

Using Sequence Similarity Networks for Visualization of Relationships Across Diverse Protein Superfamilies

The dramatic increase in heterogeneous types of biological data—in particular, the abundance of new protein sequences—requires fast and user-friendly methods for organizing this information in a way that enables functional inference. The most widely used strategy to link sequence or structure to function, homology-based function prediction, relies on the fundamental assumption that sequence or structural similarity implies functional similarity. New tools that extend this approach are still urgently needed to associate sequence data with biological information in ways that accommodate the real complexity of the problem, while being accessible to experimental as well as computational biologists. To address this, we have examined the application of sequence similarity networks for visualizing functional trends across protein superfamilies from the context of sequence similarity. Using three large groups of homologous proteins of varying types of structural and functional diversity—GPCRs and kinases from humans, and the crotonase superfamily of enzymes—we show that overlaying networks with orthogonal information is a powerful approach for observing functional themes and revealing outliers. In comparison to other primary methods, networks provide both a good representation of group-wise sequence similarity relationships and a strong visual and quantitative correlation with phylogenetic trees, while enabling analysis and visualization of much larger sets of sequences than trees or multiple sequence alignments can easily accommodate. We also define important limitations and caveats in the application of these networks. As a broadly accessible and effective tool for the exploration of protein superfamilies, sequence similarity networks show great potential for generating testable hypotheses about protein structure-function relationships