Robust analysis of the yeast proteome under 50 kDa by molecular-mass-based fractionation and top-down mass spectrometry

As the process of top-down mass spectrometry continues to mature, we benchmark the next installment of an improving methodology that incorporates a tube-gel electrophoresis (TGE) device to separate intact proteins by molecular mass. Top-down proteomics is accomplished in a robust fashion to yield the identification of hundreds of unique proteins, many of which correspond to multiple protein forms. The TGE platform separates 0-50 kDa proteins extracted from the yeast proteome into 12 fractions prior to automated nanocapillary LC-MS/MS in technical triplicate. The process may be completed in less than 72 h. From this study, 530 unique proteins and 1103 distinct protein species were identified and characterized, thus representing the highest coverage to date of the Saccharomyces cerevisiae proteome using top-down proteomics. The work signifies a significant step in the maturation of proteomics based on direct measurement and fragmentation of intact proteins.     

Speciation and quantitative mapping of metal species in microbial biofilms using scanning transmission X-ray microscopy

A scanning transmission X-ray microscope illuminated with synchrotron light was used to investigate the speciation and spatial distributions of metals in a microbial biofilm cultivated from river water. Metal 2p absorption edge signals were used to provide metal speciation (through shapes of the absorption spectra) and quantitative spatial distributions of the metal species. This paper presents sample data and describes methods for extracting quantitative maps of metal species from image sequences recorded in the region of the metal 2p edges. Comparisons were made with biochemical characterization of the same region using images recorded at the C 1s and O 1s edges. The method is applied to detailed quantitative analysis of ferrous and ferric iron in a river biofilm, in concert with mapping Ni(II) and Mn(II) species in the same region. The distributions of the metal species are discussed in the context of the biofilm structure. These results demonstrate that soft X-ray STXM measurements at the metal 2p absorption edges can be used to speciate metals and to provide quantitative spatial distribution maps for metal species in environmental samples with 50 nm spatial resolution.     

Mysterious outbreaks of gastrointestinal illness associated with burritos supplied through school lunch programs

From October 1997 through March 1998, three outbreaks of gastrointestinal illness among school children were linked to company A burritos. In September 1998, a similar outbreak occurred in three North Dakota schools following lunches that included company B burritos. We conducted an investigation to determine the source of the North Dakota outbreak, identify other similar outbreaks, characterize the illness, and gather evidence about the cause. The investigation included epidemiologic analyses, environmental investigation, and laboratory analyses. In North Dakota, a case was defined as nausea, headache, abdominal cramps, vomiting, or diarrhea after lunch on 16 September 1998. Case definitions varied in the other states. In North Dakota, 504 students and staff met the case definition; predominant symptoms were nausea (72%), headache (68%), abdominal cramps (54%), vomiting (24%), and diarrhea (16%). The median incubation period was 35 min and median duration of illness was 6 h. Eating burritos was significantly associated with illness (odds ratio, 2.6; 95% confidence interval, 1.6 to 4.2). We identified 16 outbreaks that occurred in seven states from October 1997 through October 1998, affecting more than 1,900 people who ate burritos from two unrelated companies. All tortillas were made with wheat flour, but the fillings differed, suggesting that tortillas contained the etiologic agent. Results of plant inspections, tracebacks, and laboratory investigations were unrevealing. More than two million pounds of burritos were recalled or held from distribution. The short incubation period, symptoms, and laboratory data suggest that these outbreaks were caused by an undetected toxin or an agent not previously associated with this clinical syndrome. Mass psychogenic illness is an unlikely explanation because of the large number of sites where outbreaks occurred over a short period, the similarity of symptoms, the common food item, the lack of publicity, and the link to only two companies. A network of laboratories that can rapidly identify known and screen for unknown agents in food is a critical part of protecting the food supply against natural and intentional contamination.     

Is alpha-Pinene a Substrate for Permeability-Glycoprotein in Wood Rats?

alpha-Pinene is the dominant monoterpene in Juniperus monosperma. Wood rat species in the genus Neotoma that consume J. monosperma vary in their inclusion of it in their wild diet and in their tolerance of whole J. monosperma or alpha-pinene in laboratory feeding trials. A proposed mechanism for variable tolerance is a difference in absorption of alpha-pinene from the small intestine that is mediated by the intestinal transporter permeability glycoprotein (Pgp). To determine if alpha-pinene is a Pgp substrate, we tested whether it can competitively inhibit Pgp and thereby increase the accumulation of a known Pgp substrate (digoxin) in (1) everted sleeves of small intestine from Neotoma stephensi, a juniper specialist, N. albigula, a sympatric generalist that consumes juniper, N. cinerea, a more distantly related generalist, and Sprague-Dawley rats, and (2) in Caco-2 cells that over express Pgp. We also measured Pgp ATPase phosphate production in transfected insect membrane vesicles exposed to alpha-pinene. We found no significant increase in digoxin accumulation with competitive inhibition experiments, and no increase in phosphate production with transfected membranes, at any concentration of alpha-pinene up to 100 μM. To test whether other compounds in juniper affect Pgp activity, we acclimated five N. stephensi to a juniper diet for 5 d, but found no significant effect compared to animals on control diet. Our data suggest that alpha-pinene is not a Pgp substrate.     

Unexpected oxidation of a depsipeptide substrate analogue in crystalline isopenicillin N synthase

Isopenicillin N synthase (IPNS) is a non-heme iron(ii)-dependent oxidase that is central to penicillin biosynthesis. Herein, we report mechanistic studies of the IPNS reaction in the crystalline state, using the substrate analogue delta-(L-alpha-aminoadipoyl)-(3R)-methyl-L-cysteine D-alpha-hydroxyisovaleryl ester (AmCOV) to probe the early stages of the catalytic cycle. The X-ray crystal structure of the anaerobic IPNS:Fe(II):AmCOV complex was solved to 1.40 A resolution, and it reveals several subtle differences in the active site relative to the complex of the enzyme with its natural substrate. The crystalline IPNS:Fe(II):AmCOV complex was then exposed to oxygen gas at high pressure; this brought about reaction to give what appears to be a hydroxymethyl/ene-thiol product. A mechanism for this reaction is proposed. These results offer further insight into the delicate interplay of steric and electronic effects in the IPNS active site and the mechanistic intricacies of this remarkable enzyme.     

Land use greenhouse gas emissions from conventional oil production and oil sands

Debates surrounding the greenhouse gas (GHG) emissions from land use of biofuels production have created a need to quantify the relative land use GHG intensity of fossil fuels. When contrasting land use GHG intensity of fossil fuel and biofuel production, it is the energy yield that greatly distinguishes the two. Although emissions released from land disturbed by fossil fuels can be comparable or higher than biofuels, the energy yield of oil production is typically 2-3 orders of magnitude higher, (0.33-2.6, 0.61-1.2, and 2.2 5.1 PJ/ha) for conventional oil production, oil sands surface mining, and in situ production, respectively). We found that land use contributes small portions of GHGs to life cycle emissions of California crude and in situ oil sands production ( <0.4% or < 0.4 gCO?e/MJ crude refinery feedstock) and small to modest portions for Alberta conventional oil (0.1-4% or 0.1-3.4 gCO?e/MJ) and surface mining of oil sands (0.9-11% or 0.8-10.2 gCO?e/MJ).Our estimates are based on assumptions aggregated over large spatial and temporal scales and assuming 100% reclamation. Values on finer spatial and temporal scales that are relevant to policy targets need to account for site-specific information, the baseline natural and anthropogenic disturbance.     

Comparative modeling approaches for personal exposure to particle-associated PAH

Several models for simulation of personal exposure (PE) to particle-associated polycyclic aromatic hydrocarbons (PAH) have been developed and tested. The modeling approaches include linear regression models (Model 1), time activity weighted models (Models 2 and 3), a hybrid model (Model 4), a univariate linear model (Model 5), and machine learning technique models (Model 6 and 7). The hybrid model (Model 4), which utilizes microenvironment data derived from time-activity diaries (TAD) with the implementation of add-on variables to account for external factors that might affect PE, proved to be the best regression model (R(2) for B(a)P = 0.346, p < 0.01; N = 68). This model was compared with results from two machine learning techniques, namely decision trees (Model 6) and neural networks (Model 7), which represent an innovative approach to PE modeling. The neural network model was promising in giving higher correlation coefficient results for all PAH (R(2) for B(a)P = 0.567, p < 0.01; N = 68) and good performance with the smaller test data set (R(2) for B(a)P = 0.640, p < 0.01; N = 23). Decision tree accuracies (Model 6) which assess how precisely the algorithm can determine the correct classification of a PE concentration range indicate good performance, but this is not comparable to the other models through R(2) values. Using neural networks (Model 7) showed significant improvements over the performance of hybrid Model 4 and the univariate general linear Model 5 for test samples (not used in developing the models). The worst performance was given by linear regression Models 1 to 3 based solely on home and workplace concentrations and time-activity data.