Using proteomics and cell biology to blaze a trail through blood vessels
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PHIL OH
currents
A major challenge for researchers to deliver drugs, imaging agents, or other molecules to a particular tissue in vivo is to figure out how to get the molecules through blood vessels to the appropriate destination. So, Jan Schnitzer and researchers at the Sidney Kimmel Cancer Center; Gamma Medica, Inc.; the University of California Los Angeles; and the University of Alabama Birmingham Coming through! (a) An antibody against IgG remains in a blood vessel, but (b) fluorescently labeled applied proteomics and cell-biology mAPP is transported through the same vessel into the neighboring lung tissue. (c) Phase-contrast know-how to the problem. After the image of vessel; scale bar = 20 µm. researchers identified a particular molecule with proteomics methods, they exploited the endocytotic properties of caveolae in the ized its journey by intravital microscopy. Donor rat lung tissue endothelial cells that line blood vessels to effectively target was transplanted into mice, and rat mAPP was injected into imaging agents to the lungs. their tail veins. The antibody rapidly and specifically accuEndothelial cell-surface caveolae were isolated from rat mulated in the grafted lung area. Moreover, the mAPP signal lungs. Proteins in these structures were identified by MS/MS. was observed at blood vessel walls and in the lung tissue. In By mass spectral intensities, the most abundant protein was addition, mAPP did not accumulate in other grafted organs. aminopeptidase P (APP), which is specifically expressed in The researchers also tested antibodies to IgG and caveoendothelial cells from lungs but not in those isolated from othlin, another protein in caveolae, but neither passed into the er organs. The researchers generated monoclonal antibodlung tissue. Finally, dynamic planar gamma scintigraphy was performed to visualize mAPP transport in living rats. Again, ies to APP (mAPP) and demonstrated by electron microscopy that the antibodies could target colloidal gold nanoparticles mAPP was targeted to the lungs and also outperformed othto lung caveolae. er antibodies that had been generated to lung proteins. AcTo test whether mAPP could ferry cargo through endothecording to the scientists, therapeutic or imaging agents could lial cells to lung tissue in a living animal, Schnitzer and colbe attached to caveolae-specific antibodies for delivery to leagues conjugated a fluorophore to the antibody and visualthe lungs. (Nat. Biotechnol. 2007, 25, 327–337)
Proteomics of HDL When cholesterol is bound to highdensity lipoprotein (HDL), it often is referred to as “good cholesterol” because this form is disposed of by the body. HDL removes cholesterol from tissues, including arterial walls, and transports it to the liver where it is metabolized. In addition, high levels of HDL are associated with a low risk of cardiovascular disease. To better understand how HDL accomplishes its mission, Jay Heinecke and co-workers at the University of Washington School of Medicine, Wake Forest University School of Medicine, and Harvard Medical School turned to proteomics approaches. They identified 48 proteins in HDL and discovered proteins that were differentially regulated in healthy subjects and those with coronary artery disease (CAD). © 2007 American Chemical Society
Blood samples were taken from 33 male subjects who had CAD or were healthy. HDL was isolated from the samples by ultracentrifugation. Proteins were digested with trypsin, and peptides were analyzed by LC/MS/MS. Almost all of the proteins that are known to comprise HDL were identified in addition to several others, including endopeptidase inhibitors and immune-response proteins. Heinecke and co-workers say that this finding supports their theory that HDL has previously unrecognized roles in several processes. The researchers suspected that the composition of HDL differs in healthy and CAD subjects. To test this hypothesis, they compared the protein content of HDL isolated from samples obtained from seven men with CAD and six healthy men. Spectral counting provid-
ed a semiquantitative assessment of the protein levels in the dense subfraction of HDL, known as HDL 3. CAD HDL 3 was significantly enriched for five proteins, including apoE, which is involved in lipid metabolism. The scientists also used an antibody-based method to examine apoE levels in HDL 3 of 32 healthy women and 32 with CAD. Again, apoE levels were higher in HDL 3 isolated from CAD subjects than from controls, so gender was not a factor. Finally, HDL was purified from carotid atherosclerotic tissue from six patients. In this case, three of the five proteins that were enriched in CAD samples, including apoE, also were observed in HDL from atherosclerotic tissue. The HDL of CAD patients therefore has a different composition from that of healthy subjects. ( J. Clin. Invest. 2007, 117, 746 –756)
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currents SpectraST for spectral library searching Traditional MS/MS search algorithms, such as Sequest, compare an experimental spectrum with theoretical ones generated by in silico digestion of sequences stored in public databases. These algorithms are slow and errorprone, so Ruedi Aebersold and colleagues at the Institute for Systems Biology, the Fred Hutchinson Cancer Research Center, the U.S. National Institute of Standards and Technology, and ETH Zurich took a different approach. They developed an algorithm called SpectraST and used it to search a high-quality spectral library composed of millions of Saccharomyces cerevisiae MS/MS spectra culled from data repositories. The researchers compared the new tool’s performance with that of Sequest for four datasets. SpectraST typically found matches ~1000× faster and was more sensitive than Sequest. The researchers say that spectral searching is so fast because the search space is greatly reduced compared with traditional strategies. In addition, SpectraST considers more spectral features than traditional search algorithms. According to Aebersold and colleagues, spectral searching is ideal for targeted proteomics experiments. SpectraST is open-source. (Proteomics 2007, 7, 655–667)
Standard format for iTRAQ Standard data formats, such as mzData, are starting to emerge in the field of proteomics. However, formats do not exist yet for quantitative data. So, Simon Hubbard and colleagues at the University of Manchester and the European Bioinformatics Institute (both in the U.K.) developed a standard format for quantitative data obtained from experiments that incorporate isobaric tags for relative and absolute quantitation (iTRAQ). Although the format was originally designed for iTRAQ data, it also allows researchers to report on other types of experiments that include multiple samples. The format is compatible with the Proteomics Identifications Database (known as PRIDE). The software is open-source and is freely available at www.mcisb.org/software/PrideWizard. (Proteome Sci. 2007, 5, 4)
Prenatal vitamin D deficiency and neuropsychiatric disorders Recently, vitamin D deficiency has been associated with several diseases, including cancer, multiple sclerosis (MS), and schizophrenia. To study the possible link between developmental vitamin D (DVD) deficiency and neuropsychiatric disorders, François Féron and co-workers at the Park Centre for Mental Health, the University of Queensland, Griffith University (all in Australia), the Université de la Méditerranée, and Gensodi (both in France) conducted a proteomics study. They identified several proteins that were differentially regulated in control rats and those born of mothers fed a vitamin-D-deficient diet while they were
pregnant. Of the identified proteins, many have been implicated in schizophrenia and MS. Protein expression in the frontal cortex and hippocampus regions of the brains of DVD deficient and control rats were analyzed by 2DE. A total of 36 proteins were differentially regulated, and most of these were located in the mitochondria, cytoskeleton, and synapses. After searching the literature, the researchers concluded that 15 of the identified proteins also are abnormally expressed in schizophrenia or MS or both diseases. Therefore, the researchers recommend that pregnant women consume healthful levels of vitamin D. (Proteomics 2007, 7, 769 –780)
Who will get COPD?
We all know that cigarette smoking is bad for us. It can cause numerous diseases, such as cancer, pulmonary hypertension, chronic obstructive pulmonary disease (COPD), and pneumonia, to develop in susceptible individuals. To study the differences between smokers and nonsmokers at the protein level, Amelie Plymoth and colleagues at Lund University, Sahlgrenska University Hospital, AstraZeneca (all in Sweden), and AstraZeneca (U.K.) analyzed data generated from a long-term study of bronchoalveolar lavage (BAL) samples from male smokers and nonsmokers. Looking back over the data, the researchers realized that protein profiles of samples taken at the beginning of the study, when subjects were asymptomatic, could be used to predict which smokers developed COPD years later. BAL samples from 60-year-old men (29 light and heavy smokers and 18 nonsmokers) were obtained. Proteins taken from these baseline samples were separated by 2DE. A total of 944 protein spots were detected among the groups. Plymoth and colleagues constructed a model that allowed the data to be displayed on three axes. On the x axis, protein expression levels in the smoker samples relative to the levels in the nonsmoker group were plotted. On the y axis, standard spot number counts were plotted. The z axis contained data for proteins that were present in ≥30% of the samples up through proteins that
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Breathing easy? Protein expression levels can help researchers predict who will develop COPD.
were present in ≥90% of the samples. With this distribution plot, the researchers could easily categorize the relative protein expression for the smoker and nonsmoker groups. Similar expression patterns were observed for most of the proteins, but ~2% of the proteins were down-regulated and ~13% were up-regulated in smokers. Principal components analysis and partial least-squares discriminant analysis (PLS-DA) helped to distinguish heavy and light smokers. At the follow-up stage (6–7 years after the baseline samples were taken), 7 of the 29 smokers, but none of the nonsmokers, had developed moderate COPD. After analyzing the data with successive rounds of PLS-DA, the researchers discovered that the levels of 100 proteins in the baseline samples could predict which smokers would eventually develop the disease. The scientists say that their analysis methods could be applied to various types of clinical samples. (Clin. Chem. 2007, 53, 636–644)
currents
Over-the-counter drugs (OTCs), such as acetaminophen and ibuprofen, and their metabolites can confound large-scale epidemiological studies of populations. Questionnaires typically are the only tools that researchers have to find out whether subjects have taken OTCs. Study participants, however, may not want to reveal that they have taken an OTC or simply may not recall taking one. Therefore, Jeremy Nicholson and colleagues at Imperial College London, the Chinese Academy of Sciences, Northwestern University, and AstraZeneca (U.K.) applied a high-throughput metabonomic method to detect these compounds in urine samples in an unbiased way. The method also can be used to detect other xenobiotics, such as pollutants and dietary components. Urine samples collected for the INTERMAP study, which was designed to examine the association between diet
Ham with a pinch of peptides
and blood pressure, were analyzed in a high-throughput regimen by 1D NMR. Acetaminophen and its metabolites were assigned on the basis of values reported in the literature and extensive 2D NMR measurements on selected samples. When principal components analysis was performed on 1D NMR spectra, the researchers observed that the acetaminophen spectra were outliers. Orthogonal projection to latent structure discriminant analysis (known as OPLS-DA) on a subset of spectra from acetaminophen users and nonusers clearly differentiated the two groups. Statistical correlation spectroscopy (known as STOCSY) enabled Nicholson and colleagues to identify acetaminophen metabolites. Similarly, urine samples also were examined for the presence of ibuprofen. With these statistical methods, the researchers detected OTCs and their metabolites without the need for time-consuming 2D NMR measurements. (Anal. Chem. 2007, 79, 2629–2640)
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Detection of the xenometabolome
Mmm. There’s nothing like a little prosciutto to jazz up a pasta dish or a mozzarellaand-basil salad. But is your prosciutto the best it can be? These days, the meat industry is becoming more vigilant about standardizing the quality of dry-cured hams such as prosciutto, but the molecular reactions that occur during the dry-curing process still are not well understood. Proteolysis of the muscle tissue What a ham. Researchers identify peptides in dry-cured is known to occur, but few ham. peptides in dry-cured ham have been described. Peptides may contribute to the flavor or Spanish dry-cured ham on a reversedtexture of the final product, so Miguel phase LC column and analyzed it with Ángel Sentandreu and co-workers at MS and MS/MS. With this procedure, the Spanish National Research Counfour peptides were isolated and secil (known as CSIC) and the French quenced. They were identified as piecNational Institute for Agricultural Rees of the protein actin. Although the search (known as INRA) went on the researchers did not isolate the enzyme hunt for peptides in Spanish dry-cured that produced these fragments, they ham with a proteomics approach. Accite another study in which cathepsin cording to the researchers, their report D is reported to degrade actin into pepis the first to identify actin peptides in tides that are similar to those identithis type of meat. fied in the current work. (J. Agric. Food The researchers ran an extract of Chem. 2007, doi 10.1021/jf061911g)
Toolbox TOPP Oliver Kohlbacher and co-workers at Eberhard Karls University Tübingen (Germany) and Free University Berlin have developed a flexible set of tools for proteomics analysis called the OpenMS Proteomics Pipeline (TOPP). The tools can be combined in various ways, depending on the experiment. The import/export component of TOPP includes tools to convert files into several common formats, extract parts of a file on the basis of user-defined rules, and export and import data between an OpenMS database and other files. Researchers also can perform noise reduction and baseline correction with TOPP algorithms. In addition, the pipeline features tools for peptide identification, quantitation, and analyses. To demonstrate the performance of TOPP, Kohlbacher and co-workers identified peptides and determined the concentration of a protein with the tools. TOPP is available at www.OpenMS.de. (Bioinformatics 2007, 23, e191–e197)
Peak screening H. W. Ressom and co-workers at Georgetown University Medical Center, the U.S. National Institutes of Health, and the National Hepatology and Tropical Medicine Research Institute (Egypt) have developed a preprocessing method called peak screening that reduces noise in MS spectra of clinical samples. The method eliminates peaks that are due to nondisease factors, such as age, gender, and smoking status. Combined with other preprocessing techniques, peak screening allows researchers to home in on disease-related peaks that could represent potential biomarkers. The computational method combines ant colony optimization and support vector machines to select peaks. The researchers applied the hybrid method to the analysis of MALDI TOFMS spectra obtained from a lowmolecular-weight serum fraction. Peak screening allowed them to choose peaks that distinguished patients with hepatocellular carcinoma from those with cirrhosis. The method was highly sensitive and specific. The researchers say they plan to identify and validate the peptides. (Bioinformatics 2007, 23, 619–626)
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