Engineering topics

Pounds, Joel G

Publications and source records attributed to Pounds, Joel G.

5 records

DOE OSTI2013

Diet-induced obesity reprograms the inflammatory response of the murine lung to inhaled endotoxin

The co-occurrence of environmental factors is common in complex human diseases and, as such, understanding the molecular responses involved is essential to determine risk and susceptibility to disease. We have investigated the key biological pathways that define susceptibility for pulmonary infection during obesity in diet-induced obese (DIO) and regular weight (RW) C57BL/6 mice exposed to inhaled lipopolysaccharide (LPS). LPS induced a strong inflammatory response in all mice as indicated by elevated cell counts of macrophages and neutrophils and levels of proinflammatory cytokines (MDC, MIP-1γ, IL-12, RANTES) in the bronchoalveolar lavage fluid. Additionally, DIO mice exhibited 50% greater macrophage cell counts, but decreased levels of the cytokines, IL-6, TARC, TNF-α, and VEGF relative to RW mice. Microarray analysis of lung tissue showed over half of the LPS-induced expression in DIO mice consisted of genes unique for obese mice, suggesting that obesity reprograms how the lung responds to subsequent insult. In particular, we found that obese animals exposed to LPS have gene signatures showing increased inflammatory and oxidative stress response and decreased antioxidant capacity compared with RW. Because signaling pathways for these responses can be common to various sources of environmentally induced lung damage, we further identified biomarkers that are indicative of specific toxicant exposure by comparing gene signatures after LPS exposure to those from a parallel study with cigarette smoke. These data show obesity may increase sensitivity to further insult and that co-occurrence of environmental stressors result in complex biosignatures that are not predicted from analysis of individual exposures. - Highlights: ► Obesity modulates inflammatory markers in BAL fluid after LPS exposure. ► Obese animals have a unique transcriptional signature in lung after LPS exposure. ► Obesity elevates inflammatory stress and reduces antioxidant capacity in the lung. ► Toxicant-specific biomarkers predict exposure independent of systemic inflammation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

A Comparative Analysis of Computational Approaches to Relative Protein Quantification Using Peptide Peak Intensities in Label-free LC-MS Proteomics Experiments

Liquid chromatography coupled with mass spectrometry (LC-MS) is widely used to identify and quantify peptides in complex biological samples. In particular, label-free shotgun proteomics is highly effective for the identification of peptides and subsequently obtaining a global protein profile of a sample. As a result, this approach is widely used for discovery studies. Typically, the objective of these discovery studies is to identify proteins that are affected by some condition of interest (e.g. disease, exposure). However, for complex biological samples, label-free LC-MS proteomics experiments measure peptides and do not directly yield protein quantities. Thus, protein quantification must be inferred from one or more measured peptides. In recent years, many computational approaches to relative protein quantification of label-free LC-MS data have been published. In this review, we examine the most commonly employed quantification approaches to relative protein abundance from peak intensity values, evaluate their individual merits, and discuss challenges in the use of the various computational approaches.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2012

Electrochemical Immunoassay of Cotinine in Serum Based on Nanoparticle Probe and Immunochromatographic Strip

A disposable sensor for the determination of cotinine in human serum was developed based on immunochromatographic test strip and quantum dot label. In this assay, cotinine modified on quantum dot competes with cotinine in sample to bind to anti-cotinine antibody in the test strip and the quantum dots serve as signal vehicles for electrochemical readout. Some parameters governing the performance of the sensor were optimized. The sensor shows a wide linear range from 1 ng mL-1 to 100 ng mL-1 cotinine with a detection limit of 1.0 ng mL-1. The relative standard deviation (R.S.D.) of the sensor was less than 2% for cotinine. The sensor was validated with spiked human serum samples and it was found that this method was reliable in measuring cotinine in human serum with average recovery of 100.99%. The results demonstrate that this sensor is a rapid, clinically accurate, and less expensive and has the potential for point of care (POC) detection of cotinine and fast screening of tobacco smoke exposure.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2011

Quantitative proteomics analysis of adsorbed plasma proteins classifies nanoparticles with different surface properties and size

In biofluids (e.g., blood plasma) nanoparticles are readily embedded in layers of proteins that can affect their biological activity and biocompatibility. Herein, we report a study on the interactions between human plasma proteins and nanoparticles with a controlled systematic variation of properties using stable isotope labeling and liquid chromatography-mass spectrometry (LC-MS) based quantitative proteomics. Novel protocol has been developed to simplify the isolation of nanoparticle bound proteins and improve the reproducibility. Plasma proteins associated with polystyrene nanoparticles with three different surface chemistries and two sizes as well as for four different exposure times (for a total of 24 different samples) were identified and quantified by LC-MS analysis. Quantitative comparison of relative protein abundances were achieved by spiking an 18 O-labeled 'universal reference' into each individually processed unlabeled sample as an internal standard, enabling simultaneous application of both label-free and isotopic labeling quantitation across the sample set. Clustering analysis of the quantitative proteomics data resulted in distinctive pattern that classifies the nanoparticles based on their surface properties and size. In addition, data on the temporal study indicated that the stable protein 'corona' that was isolated for the quantitative analysis appeared to be formed in less than 5 minutes. The comprehensive results obtained herein using quantitative proteomics have potential implications towards predicting nanoparticle biocompatibility.

18 O labeling↗

DOE OSTI2011

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If they are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.

60 APPLIED LIFE SCIENCES↗