Heterobimetallic Zeolite, InV-ZSM-5, Enables Efficient Conversion of Biomass Derived Ethanol to Renewable Hydrocarbons.

Direct catalytic conversion of ethanol to hydrocarbon blend-stock can increase biofuels use in current vehicles beyond the ethanol blend-wall of 10-15%. Literature reports describe quantitative conversion of ethanol over zeolite catalysts but high C2 hydrocarbon formation renders this approach unsuitable for commercialization. Furthermore, the prior mechanistic studies suggested that ethanol conversion involves endothermic dehydration step. Here, we report the complete conversion of ethanol to hydrocarbons over InV-ZSM-5 without added hydrogen and which produces lower C2 (<13%) as compared to that over H-ZSM-5. Experiments with C2H5OD and in situ DRIFT suggest that most of the products come from the hydrocarbon pool type mechanism and dehydration step is not necessary. Thus, our method of direct conversion of ethanol offers a pathway to produce suitable hydrocarbon blend-stock that may be blended at a refinery to produce fuels such as gasoline, diesel, JP-8, and jet fuel, or produce commodity chemicals such as BTX.

A general system for studying protein-protein interactions in Gram-negative bacteria.

One of the most promising methods for large-scale studies of protein interactions is isolation of an affinity-tagged protein with its in vivo interaction partners, followed by mass spectrometric identification of the copurified proteins. Previous studies have generated affinity-tagged proteins using genetic tools or cloning systems that are specific to a particular organism. To enable protein-protein interaction studies across a wider range of Gram-negative bacteria, we have developed a methodology based on expression of affinity-tagged "bait" proteins from a medium copy-number plasmid. This construct is based on a broad-host-range vector backbone (pBBR1MCS5). The vector has been modified to incorporate the Gateway DEST vector recombination region, to facilitate cloning and expression of fusion proteins bearing a variety of affinity, fluorescent, or other tags. We demonstrate this methodology by characterizing interactions among subunits of the DNA-dependent RNA polymerase complex in two metabolically versatile Gram-negative microbial species of environmental interest, Rhodopseudomonas palustris CGA010 and Shewanella oneidensis MR-1. Results compared favorably with those for both plasmid and chromosomally encoded affinity-tagged fusion proteins expressed in a model organism, Escherichia coli.

Statistically inferring protein-protein associations with affinity isolation LC-MS/MS assays.

Affinity isolation of protein complexes followed by protein identification by LC-MS/MS is an increasingly popular approach for mapping protein interactions. However, systematic and random assay errors from multiple sources must be considered to confidently infer authentic protein-protein interactions. To address this issue, we developed a general, robust statistical method for inferring authentic interactions from protein prey-by-bait frequency tables using a binomial-based likelihood ratio test (LRT) coupled with Bayes' Odds estimation. We then applied our LRT-Bayes' algorithm experimentally using data from protein complexes isolated from Rhodopseudomonas palustris. Our algorithm, in conjunction with the experimental protocol, inferred with high confidence authentic interacting proteins from abundant, stable complexes, but few or no authentic interactions for lower-abundance complexes. The algorithm can discriminate against a background of prey proteins that are detected in association with a large number of baits as an artifact of the measurement. We conclude that the experimental protocol including the LRT-Bayes' algorithm produces results with high confidence but moderate sensitivity. We also found that Monte Carlo simulation is a feasible tool for checking modeling assumptions, estimating parameters, and evaluating the significance of results in protein association studies.

Chemical composition of fingerprints for gender determination.

This work investigates the chemical nature of fingerprints to ascertain whether differences in chemical composition or the existence of chemical markers can be used to determine personal traits, such as age, gender, and personal habits. This type of information could be useful for reducing the pool of potential suspects in criminal investigations when latent fingerprints are unsuitable for comparison by traditional methods. Fingertip residue that has been deposited onto a bead was extracted with a solvent such as chloroform. Samples were analyzed by gas chromatography/mass spectrometry (GC/MS). The chemical components identified include fatty acids, long chain fatty acid esters, cholesterol and squalene. The area ratios of ten selected components relative to squalene were calculated for a small preliminary experiment that showed a slight gender difference for three of these components. However, when the experiment was repeated with a larger, statistically designed experiment no significant differences between genders were detected for any of the component ratios. The multivariate Hotelling's T2 test that tested all ten-component ratios simultaneously also showed no gender differences at the 5% significance level.

Genomes to Life "Center for Molecular and Cellular Systems": a research program for identification and characterization of protein complexes.

Goal 1 of Department of Energy's Genomes to Life (GTL) program seeks to identify and characterize the complete set of protein complexes within a cell. Goal 1 forms the foundation necessary to accomplish the other objectives of the GTL program, which focus on gene regulatory networks and molecular level characterization of interactions in microbial communities. Together this information would allow cells and their components to be understood in sufficient detail to predict, test and understand the responses of a biological system to its environment. The Center for Molecular and Cellular Systems has been established to identify and characterize protein complexes using high through-put analytical technologies.A dynamic research program is being developed that supports the goals of the Center by focusing on the development new capabilities for sample preparation and complex separations, molecular level identification of the protein complexes by mass spectrometry, characterization of the complexes in living cells by imaging techniques, and bioinformatics and computational tools for the collection and interpretation of data and formation of databases and tools to allow the data to be shared by the biological community.