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Obesity and the metabolic disorders that constitute metabolic syndrome are a primary cause of morbidity and mortality in the world. Nonetheless, the changes in the proteins and the underlying molecular pathways involved in the relevant pathogenesis are poorly understood. In this study a proteomic analysis of the visceral adipose tissue isolated from metabolically healthy and unhealthy obese patients was used to identify presence of altered pathway(s) leading to metabolic dysfunction. Samples were obtained from 18 obese patients undergoing bariatric surgery and were subdivided into two groups based on the presence or absence of comorbidities as defined by the International Diabetes Federation. Two dimensional difference in-gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry was carried out. A total of 28 proteins were identified with a statistically significant difference in abundance and a 1.5-fold change (ANOVA, p ≤ 0.05) between the groups. 11 proteins showed increased abundance while 17 proteins were decreased in the metabolically unhealthy obese compared to the healthy obese. The differentially expressed proteins belonged broadly to three functional categories: (i) protein and lipid metabolism (ii) cytoskeleton and (iii) regulation of other metabolic processes. Network analysis by Ingenuity pathway analysis identified the NFκB, IRK/MAPK and PKC as the nodes with the highest connections within the connectivity map. The top network pathway identified in our protein data set related to cellular movement, hematological system development and function, and immune cell trafficking. The VAT proteome between the two groups differed substantially between the groups which could potentially be the reason for metabolic dysfunction.

Since the advent of the new proteomics era more than a decade ago, large-scale studies of protein profiling have been exploited to identify the distinctive molecular signatures in a wide array of biological systems spanning areas of basic biological research, various disease states, and biomarker discovery directed toward therapeutic applications. Recent advances in protein separation and identification techniques have significantly improved proteomics approaches, leading to enhancement of the depth and breadth of proteome coverage. Proteomic signatures specific for invasive lung cancer and preinvasive lesions have begun to emerge. In this review we provide a critical assessment of the state of recent advances in proteomic approaches and the biological lessons they have yielded, with specific emphasis on the discovery of biomarker signatures for the early detection of lung cancer.

The determination of the localization of various compounds in a whole animal is valuable for many applications, including pharmaceutical absorption, distribution, metabolism, and excretion (ADME) studies and biomarker discovery. Imaging mass spectrometry is a powerful tool for localizing compounds of biological interest with molecular specificity and relatively high resolution. Utilizing imaging mass spectrometry for whole-body animal sections offers considerable analytical advantages compared to traditional methods, such as whole-body autoradiography, but the experiment is not straightforward. This chapter addresses the advantages and unique challenges that the application of imaging mass spectrometry to whole-body animal sections entails, including discussions of sample preparation, matrix application, signal normalization, and image generation. Lipid and protein images obtained from whole-body tissue sections of mouse pups are presented along with detailed protocols for the experiments.

The northern leopard frog (Rana pipiens or Lithobates pipiens) is historically found in most of the provinces of Canada and the northern and southwest states of the United States. In the last 50 years, populations have suffered significant losses, especially in the western regions of the species range. Using a peptidomics approach, we show that the pattern of expressed antimicrobial skin peptides of frogs from three geographically separated populations are distinct, and we report the presence of four peptides (brevinin-1Pg, brevinin-1Pl, ranatuerin-2Pb, and ranatuerin-2Pc) that have not previously been found in skin secretions. The differences in expressed peptides reflect differences in the distribution of alleles for the newly described Brevinin1.1 locus in the three populations. When enriched peptide mixtures were tested for their ability to inhibit growth of the pathogenic amphibian chytrid (Batrachochytrium dendrobatidis), peptides from Minnesota or Vermont frogs were more effective that peptides from Michigan frogs. Four of the purified peptides were tested for their ability to inhibit growth of two bacterial pathogens (Aeromonas hydrophila and Staphylococcus epidermidis) and B. dendrobatidis. Three of the four were effective inhibitors of B. dendrobatidis and S. epidermidis, but none inhibited A. hydrophila. We interpret these differences in expression and activity of antimicrobial peptides as evidence to suggest that each population may have been selected to express a suite of peptides that reflects current and past encounters with skin microbes.

In an effort to further our understanding of lung cancer biology and to identify new candidate biomarkers to be used in the management of lung cancer, we need to probe these tissues and biological fluids with tools that address the biology of lung cancer directly at the protein level. Proteins are responsible of the function and phenotype of cells. Cancer cells express proteins that distinguish them from normal cells. Proteomics is defined as the study of the proteome, the complete set of proteins produced by a species, using the technologies of large-scale protein separation and identification. As a result, new technologies are being developed to allow the rapid and systematic analysis of thousands of proteins. The analytical advantages of mass spectrometry (MS), including sensitivity and high-throughput, promise to make it a mainstay of novel biomarker discovery to differentiate cancer from normal cells and to predict individuals likely to develop or recur with lung cancer. In this review, we summarize the progress made in clinical proteomics as it applies to the management of lung cancer. We will focus our discussion on how MS approaches may advance the areas of early detection, response to therapy, and prognostic evaluation.

MALDI imaging mass spectrometry (IMS) has become a valuable tool for the investigation of the content and distribution of molecular species in tissue specimens. Numerous methodological improvements have been made to optimize tissue section preparation and matrix deposition protocols, as well as MS data acquisition and processing. In particular for proteomic analyses, washing the tissue sections before matrix deposition has proven useful to improve spectral qualities by increasing ion yields and the number of signals observed. We systematically explore here the effects of several solvent combinations for washing tissue sections. To minimize experimental variability, all of the measurements were performed on serial sections cut from a single mouse liver tissue block. Several other key steps of the process such as matrix deposition and MS data acquisition and processing have also been automated or standardized. To assess efficacy, after each washing procedure the total ion current and number of peaks were counted from the resulting protein profiles. These results were correlated to on-tissue measurements obtained for lipids. Using similar approaches, several selected washing procedures were also tested for their ability to extend the lifetime as well as revive previously cut tissue sections. The effects of these washes on automated matrix deposition and crystallization behavior as well as their ability to preserve tissue histology were also studied. Finally, in a full-scale IMS study, these washing procedures were tested on a human renal cell carcinoma biopsy.

Profiling and imaging biological specimens using MALDI mass spectrometry has significant potential to contribute to our understanding and diagnosis of disease. The technique is efficient and high-throughput providing a wealth of data about the biological state of the sample from a very simple and direct experiment. However, in order for these techniques to be put to use for clinical purposes, the approaches used to process and analyze the data must improve. This study examines some of the existing tools to baseline subtract, normalize, align, and remove spectral noise for MALDI data, comparing the advantages of each. A preferred workflow is presented that can be easily implemented for data in ASCII format. The advantages of using such an approach are discussed for both molecular profiling and imaging mass spectrometry.

MALDI (matrix-assisted laser desorption/ionization) imaging mass spectrometry (IMS) is a new technology that generates molecular profiles and two-dimensional ion density maps of peptide and protein signals directly from the surface of thin tissue sections. This allows specific information to be obtained on the relative abundance and spatial distribution of proteins. One important aspect of this is the opportunity to correlate these specific ion images with histological features observed by optical microscopy. To facilitate this, we have developed protocols that allow MALDI mass spectrometry imaging and optical microscopy to be performed on the same section. Key components of these protocols involve the use of conductive glass slides as sample support for the tissue sections and MS-friendly tissue staining protocols. We show the effectiveness of these with protein standards and with several types of tissue sections. Although stain-specific intensity variations occur, the overall protein pattern and spectrum quality remain consistent between stained and control tissue samples. Furthermore, imaging mass spectrometry experiments performed on stained sections showed good image quality with minimal delocalization of proteins resulting from the staining protocols.

Epidemiologic evidence implicates cyclooxygenase activity in the pathogenesis of Alzheimer's disease, in which amyloid plaques have been found to contain increased levels of dimers and higher multimers of the amyloid beta peptide. The product of the oxygenation of arachidonic acid by the cyclooxygenases, prostaglandin H2 (PGH2), rearranges non-enzymatically to several prostaglandins, including the highly reactive gamma-keto aldehydes, levuglandins E2 and D2. We demonstrate that PGH2 markedly accelerates the formation of dimers and higher oligomers of amyloid beta1-42. This is associated with the formation of levuglandin adducts of the peptide. These findings provide the molecular basis for a hypothesis linking cyclooxygenase activity to the formation of oligomers of amyloid beta.