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Quantitative proteom ics of m ulticellularorganism s For the first time, researchers have used metabolic labeling of multicellular organisms for subsequent quantitative proteomic analysis. Jeroen Krijgsveld and colleagues from Utrecht University, Leiden University, and the University of Amsterdam (all in The Netherlands) successfully incorporated 15N at levels of 94% or higher in proteins of the wellstudied nematode Caenorhabditis elegans and the common fruit fly Drosophila melanogaster. The method was shown to be reproducible and avoids using in vitro labels, such as isotope-coded affinity tags, to aid analysis. Fully incorporating 15N into the organisms required waiting for two generations to undergo metabolic labeling. For example, a generation of fruit flies and their embryos were raised on 15Nlabeled yeast before the proteins were collected. MS analysis showed that all the proteins were labeled. To test the approach for proteomic analysis, the researchers grew wild-type C. elegans on 15N, while a mutant strain glp-4 that stops proliferating at an early
Carefully picking proteins Tandem MS—in which proteins are identified from fragments of their former selves— is a cornerstone of proteomics. However, protein identification from observed peptides is not always accurate and may produce a significant number of incorrect protein assignments. Alexey Nesvizskii, Andrew Keller, and colleagues at the Institute for Systems Biology (Seattle, Wash.) introduce a statistical model that determines the probability that a peptide belongs to a certain protein and thereby can help discriminate between correct and incorrect protein identifications. Proteins are typically identified by comparing the peptide fragments to a database of © 2003 American Chemical Society
Full-bodylabeling.Overview of the C. elegans quantitative proteomic analysis experiment, beginning with growth on 15Nlabeled E. coli. Protein expression differences were identified regardless of whether the mutant or wild-type nematode was labeled. (Adapted with permission. Copyright 2003 Nature Publishing Group.)
stage was raised on unlabeled food under similar conditions. Equal volumes of labeled and unlabeled nematodes were mixed together, their proteins separated on 2-D gels, and spots were randomly excised and analyzed by MALDITOF MS. Peak heights were normalized and then compared between the two strains, and variations were evident in several proteins, notably the absence of major sperm protein in glp-4. The experiment was then repeated with the mutant raised on 15N media, and the wild-type nematode was left unlabeled. The results were nearly identical, with a standard deviation of only 0.16 for the abundance ratios from the two sets of proteins. A separate RNA expression study with glp-4 using DNA microarrays investigated nearly 12,000 genes. Significantly, three genes that changed expression levels in the microarray study were observed to have no differences in the proteomic study, a result suggesting that varying mRNA expression levels do not necessarily translate into related protein concentrations. (Nat. Biotechnol. 2003, 21, 927–931)
automated, non-heuristic sysThe system requires no protein sequences. The tem for predicting how reasubjective manual validation, process becomes difficult sonable protein identification and researchers see the maxiwhen the peptide sequence is results are. mum number of possible found in more than one entry proteins or just the in the database. The most probable ones. researchers develIn addition, the caloped a method that culation of the combines the probprobabilities proabilities that correvides a potentially sponding peptides new standard for are correct after publishing largeadjusting for scale proteomics observed protein data sets in the grouping informaliterature. The retion. The system searchers indicate also combines that the software, duplicate database ProteinProphet, will entries and groups be available to the together proteins public at http:// that are impossible systemsbiology.org/ to differentiate, From fragm entationtoprediction.The protein sample is digested leading to more into peptides, and MS/MS spectra are generated. The peptides research/software. accurate results. are observed, and then protein identification results are grouped html. (Anal. Chem. The researchers say to produce the probability of the parent proteins. 2003, 75, 4646– that this is the first 4658) JournalofProteom e Research •Vol. 2, No. 5, 2003
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currents Holey m icrow ellcovers Preventing the evaporation of very small volumes of samples is difficult and remains an important issue in ultrahighthroughput screening. Previously, a variety of approaches were used to control evaporation, such as establishing high humidity, adding glycerol to the reaction media, or covering the wells with hydrocarbons or a glass slide. Robert Moerman and Gijs W. K. van Dedem at Delft University of Technology (The Netherlands) introduce a possible solution by covering microwell plates with a poly(methyl methacrylate) (PMMA) or quartz coverslip with holes, which also provides an avenue to deliver sample to the wells. The wells, which are 100–200 µm in diameter, are prefilled with reagents and are covered by the PMMA or quartz top. The holes in the cover are 200–300 µm in diameter and are initially positioned over the solid surface of the microwell plate, not over the wells. The sample is pipetted into the holes, where it wets the surface of the plate. The plate is then moved to partially align the wells with the holes in the lid. The sample liquid flows into the well as air trapped in the well escapes, and the plate is slid back to seal the wells. The plates effectively pre-
M apping the m itochondrialinner m em brane Jean-ClaudeMartinou and colleagues at the University of Geneva and Serono Pharmaceutical Research Institute (both in Switzerland) have mapped the first proteome of the mitochondrial inner membrane (MIM) using samples from the livers of four female mice. Mitochondria are crucial for maintaining the proper balance of intracellular and extracellular levels of ion, oxygen, and ATP production, and the MIM contains ion channels, carrier proteins and, most importantly, many components of the respiratory chain complexes. Using 2-D LC/MS/ MS to analyze highly purified mouse liver MIMs, the researchers found 182 proteins, with 45% containing 2–16 transmem-
M IM s from m ice.Subcellular localization of five previously unknown proteins in HeLa cells by coimmunostaining with antibody against a known mitochondrial protein. (Adapted with permission. Copyright 2003 American Society for Biochemistry and Molecular Biology.)
vented evaporation for 30 min, long enough for fluorescence measurements to be taken. The method is being improved to prevent carryover from prefilled reactants and to provide longer-term storage. (Anal. Chem. 2003, 75, 4132–4138)
Circles and squares.(a) Sample is pipetted into the holes (circles) but not into the wells (squares), which contain reactants. (b) When the cover plate is moved, air escapes from within the microwells and sample enters.
Targeting N O-dependent interactions Nitric oxide influences many cellular functions through posttranslational nitrosylation of proteins, yet researchers habitually omit it from proteomics experiments. Jonathan Stamler and colleagues at Duke University Medical Center thought that approach made it tough to get an accurate picture of important processes, so they modified the yeast two-hybrid system to detect protein–protein interactions that require NO. As they had hoped, they found some previously unknown functions for this small signaling molecule. Stamler and colleagues transformed yeast with a “bait” plasmid and various “prey” plasmids from a library derived from macrophages that generate NO. The cultures
brane domains, thus validating their method for protein identification. They also found proteins with widely varying molecular weights (⬍10 kDa and ⬎100 kDa), pI values, and hydrophobicities. What the researchers did not foresee as they scurried through the mice’s MIMs was the discovery of 22 new proteins, 7 of which were known to exist but had not previously been considered part of the MIM. Further study in mammalian cells confirmed that some of these 22 proteins are localized in the MIM, and therefore a remodeling of the mitochondrial network is required. However, the study failed to identify Ca2+ ion channels or ATP K+ channels normally present in the MIM. ( J. Biol. Chem. 2003, 10.1074/jbc.M304940200)
were grown in a liquid histidine-deficient medium with physiological levels of NO (~300 nM), so only transformants with both plasmids would grow. After an amplification step, the prey plasmids were retransfected into yeast expressing a bait protein to enrich for NO-dependent protein interactions. Additional screening using an assay for activation of β-galactosidase confirmed the results and indicated the relative dependence on NO. The researchers performed several rounds of screening using various baits. One set of experiments suggested that inducible NO synthase is selfregulating, perhaps serving a function analogous to a kinase in phosphorylation. Other data demonstrated that endogenous NO reversibly regulates the interaction of the apopto-
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currents sis-related proteins procaspase-3 and acid sphingomyelinase in mammalian cells. Mitochondrial interaction between procaspase-3 and acid sphingomyelinase is also regulated by NO synthase activity. Furthermore, NO modification of procaspase-3 can increase the affinity of the enzyme’s interactions or keep the protein in an inactive state. The researchers conclude that nitrosylation, like phosphorylation, may regulate a wide range of protein–protein interactions and cellular signaling networks. They also note that their method might be extended to other redoxactive molecules. (Science 2003, 301, 657–661)
Expression in cultured vs xenografted cells Many cancer studies are carried out on cells in a culture dish, but the in vitro environment in this situation is very different from what a cell encounters while growing inside a living organism. Chad Creighton and colleagues at the University of Michigan use a proteomics approach to better understand how cancer cells respond to these differences.The researchers compared gene expression levels between cultured and xenografted tumors for two cancer cell lines. They found that cells grown in vitro express different classes of genes from cells grown in vivo in mice and that this diversity is lineage-specific. Creighton and his team examined the mRNA from cultured and xenografted A549 lung cancer cells and U118 brain cancer cells. A total of 357 genes differ significantly in their expression levels between A549 cells grown in vitro and those grown in vivo, and similarly 368 genes
differ for U118 cells in the two conditions. Differentially expressed genes were grouped into functional classes by common Gene Ontology annotation or Medical Subject Heading Index terms from the literature. Genes implicated in cell division are overrepresented in both cultured cell lines when compared to xenografted cells. In contrast, genes involved in cell adhesion, the formation of new blood vessels, and the extracellular matrix are preferentially up-regulated in tumor cells. When the researchers look at which genes are overrepresented, A549 and U118 tumor cells have only 10 highly expressed genes in common. Creighton and colleagues conclude that lineagespecific signaling pathways are turned on in tumors originating from different tissues, even if they are xenografted into similar environments. They say that these differences could be used to develop therapies specific to certain types of cancers. (Genome Biol. 2003, 4, R46)
CE forG proteins the G protein–probe complexes were separated from free probe in ⬍30 s by CE and detected with laser-induced fluorescence. The detection limit for Gαo was 2 nm, which corresponds to a mass of 3 amol. The dissociation constant, the onand off-rates for the probe to Gαo, and the half-life of the complexes determined with this method were in good agreement with data obtained using Free vsG.The separation of free probes, BGTPγS, established techfrom probes in a complex with the Gαo subunit. niques. Experiments were also conducted with the Gαi1 sub~106-fold more mass-sensitive than gel electrophoresis. unit, Ras, and Rab3A. Previous affinity probe The researchers note that CE assays have used antibodmost of the experiments were ies or aptamers to bind anaconducted on a CE system lytes or proteins to detect that had been optimized for drugs, but such interactions high-speed separations. The tend to be very specific. method did not perform as Kennedy and colleagues went well on a commercial CE after a wide range of interacinstrument, which had longer tions instead, using a fluorescapillaries and separation cently labeled GTP analogue, times. Lowering the temperawhich binds to the ␣ subunit ture at which the separation of a G protein, as the probe. was performed from 25 to After sample incubation, 15 ˚C helped, but the com-
Robert Kennedy and colleagues at the University of Michigan use affinity probe CE to detect a wide range of G proteins and report that the method is 100-fold faster and
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mercial system’s best detection limit was still ~22 nM compared with 2 nM on the optimized instrument. (Anal. Chem. 2003, 75, 4297–4304)
CGE instead of m icroarrays? Edward Yeung and Wenwan Zhong at Iowa State University developed a high-throughput capillary gel electrophoresis (CGE) method to differentiate among the RNA expression profiles of kidney, normal breast, and breast tumor tissues. Yeung and Zhong say that this method allows researchers to include small or previously unidentified RNAs in their analyses, which is not possible with current microarray technology. The researchers obtain total RNA, which includes ribosomal, transfer, and messenger RNAs, of three types of tissues. Using random hexamer primers, they stimulate reverse transcription to make fluorophore-labeled cDNAs, which they separate by CGE. Many cDNAs of varying lengths are produced from each RNA, and this complex assortment of RNAs cannot be completely resolved with
current CGE technology. Nevertheless, the researchers study the patterns of peaks on the electropherograms and find that the peak patterns are reproducible for each type of tissue. Although it is difficult to assign a particular electropherogram to a certain tissue type by eye, some slight differences are apparent when they are overlaid. The differences in the RNA expression pattern are even more obvious when Yeung and Zhong perform statistical tests on the data. All three tissue types are easily sorted into classes, and the researchers find that normal kidney and breast tissue samples are more similar to each other than either one is to the tumor sample. The researchers say that the method can be modified to analyze mRNA alone, and internal standards could be used to normalize signal intensity variations. Performing PCR on cDNAs in the collected fractions, followed by sequencing of the products, could help identify the differentially expressed RNAs. (Anal. Chem. 2003, 75, 4415– 4422)
