Quantitative gas chromatography mass spectrometric analysis of 2'-deoxyinosine in tissue DNA

Several studies examining DNA deamination have published levels of 2'-deoxyinosine that illustrated a large variation between studies. Most of them are the result of artifactual DNA deamination that occurs during the process of sample preparation, particularly acid hydrolysis. This protocol for measurement of 2'-deoxyinosine describes the use of nuclease P1 and alkaline phosphatase to achieve release of nucleosides from DNA, followed by HPLC prepurification with subsequent gas chromatography-mass spectrometry analysis of the nucleosides. It has been used in the measurement of the levels of 2'-deoxyinosine in DNA of commercial sources and DNA from cells and animal tissues, and gives values ranging from 3 to 7 2'-deoxyinosine per 10(6) 2-deoxyadenosine. This protocol should take approximately 7 days to complete.     

A family-based approach to preventing excessive weight gain

Objective: Preventing weight gain in adults and excessive weight gain in children is a high priority. We evaluated the ability of a family‐based program aimed at increasing steps and cereal consumption (for breakfast and snacks) to reduce weight gain in children and adults. Research Methods and Procedures: Families (n = 105) with at least one 8‐ to 12‐year‐old child who was at‐risk‐for‐overweight or overweight (designated as the target child) were recruited for the study. Eighty‐two families were randomly assigned to receive the family‐based intervention and 23 families to the control condition. The 13‐week intervention consisted of specific increases in daily steps (an additional 2000 steps/d) and consumption of 2 servings/d of ready‐to‐eat cereal. Results: The intervention was successful in increasing walking (steps) and cereal consumption. The intervention had positive, significant effects on percentage BMI‐for‐age and percentage body fat for target children and weight, BMI, and percentage body fat for parents. On further analysis, the positive effects of the intervention were seen largely in target girls and moms, rather than in target boys and dads. Discussion: This family‐based weight gain prevention program based on small changes holds promise for reducing excessive weight gain in families and especially in growing overweight children.     

Proteomic analysis of root meristems and the effects of acetohydroxyacid synthase-inhibiting herbicides in the root of Medicago truncatula

Quantitative proteome analyses of meristematic and nonmeristematic tissues from Medicago truncatula primary and lateral roots and meristem tissues from plants treated with acetohydroxyacid synthase-inhibiting herbicides were made. The accumulation of 81 protein spots changed in meristematic and nonmeristematic tissues and 51 protein spots showed significant changes in accumulation in herbicide-treated meristems. Identified proteins indicate two trends, (i) increased accumulation of cell division and redox-mediating proteins in meristems compared to nonmeristematic tissues and (ii) increased accumulation of pathogenesis-related and decreased accumulation of metabolic proteins in herbicide-treated roots.     

Normalization approaches for removing systematic biases associated with mass spectrometry and label-free proteomics

Central tendency, linear regression, locally weighted regression, and quantile techniques were investigated for normalization of peptide abundance measurements obtained from high-throughput liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR MS). Arbitrary abundances of peptides were obtained from three sample sets, including a standard protein sample, two Deinococcus radiodurans samples taken from different growth phases, and two mouse striatum samples from control and methamphetamine-stressed mice (strain C57BL/6). The selected normalization techniques were evaluated in both the absence and presence of biological variability by estimating extraneous variability prior to and following normalization. Prior to normalization, replicate runs from each sample set were observed to be statistically different, while following normalization replicate runs were no longer statistically different. Although all techniques reduced systematic bias to some degree, assigned ranks among the techniques revealed that for most LC-FTICR-MS analyses linear regression normalization ranked either first or second. However, the lack of a definitive trend among the techniques suggested the need for additional investigation into adapting normalization approaches for label-free proteomics. Nevertheless, this study serves as an important step for evaluating approaches that address systematic biases related to relative quantification and label-free proteomics.     

Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice

A novel statistically integrated proteometabonomic method has been developed and applied to a human tumor xenograft mouse model of prostate cancer. Parallel 2D-DIGE proteomic and 1H NMR metabolic profile data were collected on blood plasma from mice implanted with a prostate cancer (PC-3) xenograft and from matched control animals. To interpret the xenograft-induced differences in plasma profiles, multivariate statistical algorithms including orthogonal projection to latent structure (OPLS) were applied to generate models characterizing the disease profile. Two approaches to integrating metabonomic data matrices are presented based on OPLS algorithms to provide a framework for generating models relating to the specific and common sources of variation in the metabolite concentrations and protein abundances that can be directly related to the disease model. Multiple correlations between metabolites and proteins were found, including associations between serotransferrin precursor and both tyrosine and 3-D-hydroxybutyrate. Additionally, a correlation between decreased concentration of tyrosine and increased presence of gelsolin was also observed. This approach can provide enhanced recovery of combination candidate biomarkers across multi-omic platforms, thus, enhancing understanding of in vivo model systems studied by multiple omic technologies.     

c-Type cytochrome-dependent formation of U(IV) nanoparticles by Shewanella oneidensis

Modern approaches for bioremediation of radionuclide contaminated environments are based on the ability of microorganisms to effectively catalyze changes in the oxidation states of metals that in turn influence their solubility. Although microbial metal reduction has been identified as an effective means for immobilizing highly-soluble uranium(VI) complexes in situ, the biomolecular mechanisms of U(VI) reduction are not well understood. Here, we show that c-type cytochromes of a dissimilatory metal-reducing bacterium, Shewanella oneidensis MR-1, are essential for the reduction of U(VI) and formation of extracellular UO(2) nanoparticles. In particular, the outer membrane (OM) decaheme cytochrome MtrC (metal reduction), previously implicated in Mn(IV) and Fe(III) reduction, directly transferred electrons to U(VI). Additionally, deletions of mtrC and/or omcA significantly affected the in vivo U(VI) reduction rate relative to wild-type MR-1. Similar to the wild-type, the mutants accumulated UO(2) nanoparticles extracellularly to high densities in association with an extracellular polymeric substance (EPS). In wild-type cells, this UO(2)-EPS matrix exhibited glycocalyx-like properties and contained multiple elements of the OM, polysaccharide, and heme-containing proteins. Using a novel combination of methods including synchrotron-based X-ray fluorescence microscopy and high-resolution immune-electron microscopy, we demonstrate a close association of the extracellular UO(2) nanoparticles with MtrC and OmcA (outer membrane cytochrome). This is the first study to our knowledge to directly localize the OM-associated cytochromes with EPS, which contains biogenic UO(2) nanoparticles. In the environment, such association of UO(2) nanoparticles with biopolymers may exert a strong influence on subsequent behavior including susceptibility to oxidation by O(2) or transport in soils and sediments.     

Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data

Over the last decade the availability of SNP-trait associations from genome-wide association studies has led to an array of methods for performing Mendelian randomization studies using only summary statistics. A common feature of these methods, besides their intuitive simplicity, is the ability to combine data from several sources, incorporate multiple variants and account for biases due to weak instruments and pleiotropy. With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well developed summary data methods to individual level data, and to explore the use of more sophisticated causal methods allowing for non-linearity and effect modification.In this paper we describe a general procedure for optimally applying any two sample summary data method using one sample data. Our procedure first performs a meta-analysis of summary data estimates that are intentionally contaminated by collider bias between the genetic instruments and unmeasured confounders, due to conditioning on the observed exposure. These estimates are then used to correct the standard observational association between an exposure and outcome. Simulations are conducted to demonstrate the method’s performance against naive applications of two sample summary data MR. We apply the approach to the UK Biobank cohort to investigate the causal role of sleep disturbance on HbA1c levels, an important determinant of diabetes.Our approach can be viewed as a generalization of Dudbridge et al. (Nat. Comm. 10: 1561), who developed a technique to adjust for index event bias when uncovering genetic predictors of disease progression based on case-only data. Our work serves to clarify that in any one sample MR analysis, it can be advantageous to estimate causal relationships by artificially inducing and then correcting for collider bias.     

The role of contextual conditioning in the effect of reinforcer devaluation on instrumental performance by rats

Different groups of rats received different amounts of training to lever press for a food reinforcer before an aversion was conditioned to the food. This devaluation of the reinforcer reduced responding in both subsequent extinction and reinforced tests of responding to a degree that was independent of the amount of instrumental training. Moreover, interpolating context extinction between aversion conditioning and the extinction test reduced the magnitude of the devaluation effect, thereby indicating that Pavlovian contextual conditioning may play a role in the instrumental devaluation effect.