The "integrin" terminology was applied in a 1987 review article (1) to describe a family of structurally, immunochemically, and functionally related cell-surface heterodimeric receptors, which integrated the extracellular matrix with the intracellular cytoskeleton to mediate cell migration and adhesion. The three original ␤ subunits (␤ 1 , ␤ 2 , and ␤ 3 ) identified have now expanded to eight, and the number of ␣ subunits stands at 17. These subunits interact noncovalently in a restricted manner to form more than 20 family members. The diversity of integrins is expanded further by alternative splicing, post-translational modifications, and interactions with other cell-surface and intracellular molecules (2-4). The number of integrins and the remarkable breadth of their cellular distribution support the statement that the phenotype of virtually every cell is uniquely influenced by its display of integrins. Over the past 13 years, more than 14,000 scientific articles have dealt with various aspects of integrin biology and almost 1,000 have appeared in the Journal of Biological Chemistry. This article examines a central aspect of integrin biology: ligand recognition and the structural basis for this function. Ligand Repertoire and RecognitionRepertoire Considerations-A hallmark of the integrins is the ability of individual family members to recognize multiple ligands. Indeed, the extent of the integrin family pales in comparison with the number of their ligands. Table I summarizes the major extracellular ligands of integrins; the listing is undoubtedly incomplete. The list includes a large number of extracellular matrix proteins (bone matrix proteins, collagens, fibronectins, fibrinogen, laminins, thrombospondins, vitronectin, and von Willebrand factor), reflecting the primary function of integrins in cell adhesion to extracellular matrices. Many "counter-receptors" are ligands, reflecting the role of integrins in mediating cell-cell interactions. Included are numerous microorganisms, which utilize integrins to gain entry into cells. There are direct and multiple linkages between integrins and host defense systems, created by their recognition of hemostatic and complement factors. The preference of any given integrin among its ligands is determined by relative affinity, availability within a specific microenvironment, and the conformational state of the ligand, which controls exposure of its integrin recognition sequence.Integrin Recognition Sequences-A primary goal of many structure-function analyses in the integrin field has been the reduction of macromolecular ligands to minimal recognition sequences. This endeavor has been highly successful, and many bioactive amino acid sequences have been teased out of large extracellular matrix proteins (5). The prototypic example is the RGD sequence. RGD was originally identified as the sequence in fibronectin that engages the fibronectin receptor, integrin ␣ 5 ␤ 1 , but now is known to serve as a recognition motif in multiple ligands for several different integrins (see Ta...

Matrix metalloproteinases (MMPs) are implicated in the pathogenesis of neurodegenerative diseases and stroke. However, the mechanism of MMP activation remains unclear. We report that MMP activation involves S-nitrosylation. During cerebral ischemia in vivo, MMP-9 colocalized with neuronal nitric oxide synthase. S-Nitrosylation activated MMP-9 in vitro and induced neuronal apoptosis. Mass spectrometry identified the active derivative of MMP-9, both in vitro and in vivo, as a stable sulfinic or sulfonic acid, whose formation was triggered by S-nitrosylation. These findings suggest a potential extracellular proteolysis pathway to neuronal cell death in which S-nitrosylation activates MMPs, and further oxidation results in a stable posttranslational modification with pathological activity.

One of the fundamental principles of pharmacology is that most drugs have side effects. Although considerable attention is paid to detrimental side effects, drugs can also have beneficial side effects. Given the time and expense of drug development, it would be particularly exciting if a systematic method could be applied to reveal all of the activities, including the unappreciated actions, of a potential drug. The present study takes the first step along this path. An activity-based proteomics strategy was used to simultaneously identify targets and screen for their inhibitors in prostate cancer. Orlistat, a Food and Drug Administration-approved drug used for treating obesity, was included in this screen. Surprisingly, we find a new molecular target and a potential new application for Orlistat. Orlistat is a novel inhibitor of the thioesterase domain of fatty acid synthase, an enzyme strongly linked to tumor progression. By virtue of its ability to inhibit fatty acid synthase, Orlistat halts tumor cell proliferation, induces tumor cell apoptosis, and inhibits the growth of PC-3 tumors in nude mice.

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In order to study the differential protein expression in complex biological samples, strategies for rapid, highly reproducible and accurate quantification are necessary. Isotope labeling and fluorescent labeling techniques have been widely used in quantitative proteomics research. However, researchers are increasingly turning to label-free shotgun proteomics techniques for faster, cleaner, and simpler results. Mass spectrometry-based label-free quantitative proteomics falls into two general categories. In the first are the measurements of changes in chromatographic ion intensity such as peptide peak areas or peak heights. The second is based on the spectral counting of identified proteins. In this paper, we will discuss the technologies of these label-free quantitative methods, statistics, available computational software, and their applications in complex proteomics studies.

Metabolic rewiring is an established hallmark of cancer, but the details of this rewiring at a systems level are not well characterized. Here we acquire this insight in a melanoma cell line panel by tracking metabolic flux using isotopically labeled nutrients. Metabolic profiling and flux balance analysis were used to compare normal melanocytes to melanoma cell lines in both normoxic and hypoxic conditions. All melanoma cells exhibited the Warburg phenomenon; they used more glucose and produced more lactate than melanocytes. Other changes were observed in melanoma cells that are not described by the Warburg phenomenon. Hypoxic conditions increased fermentation of glucose to lactate in both melanocytes and melanoma cells (the Pasteur effect). However, metabolism was not strictly glycolytic, as the tricarboxylic acid (TCA) cycle was functional in all melanoma lines, even under hypoxia. Furthermore, glutamine was also a key nutrient providing a substantial anaplerotic contribution to the TCA cycle. In the WM35 melanoma line glutamine was metabolized in the "reverse" (reductive) direction in the TCA cycle, particularly under hypoxia. This reverse flux allowed the melanoma cells to synthesize fatty acids from glutamine while glucose was primarily converted to lactate. Altogether, this study, which is the first comprehensive comparative analysis of metabolism in melanoma cells, provides a foundation for targeting metabolism for therapeutic benefit in melanoma.Metabolism in cancer cells differs from that of normal nonproliferative cells. Perhaps the most common variation from the norm in cancer metabolism is "aerobic glycolysis" or the Warburg effect. Under the Warburg effect, metabolism of glucose is largely fermentative rather than respiratory, with increased production of lactate, in normal atmospheric oxygen conditions (1). This is also associated with increased uptake of glucose, a common characteristic of cancers detectable in tumors in patients via 18 F-deoxyglucose-PET (2). However, the extent to which the Warburg effect represents a rebalancing of metabolism (increasing fermentation while decreasing respiration) versus an amplification of metabolism (increasing fermentation while maintaining, or even increasing, respiration) is the subject of debate (3, 4). The Warburg effect contrasts with the Pasteur effect, in that the latter describes the switch from fermentation to respiration when oxygen is plentiful, and its reversal when oxygen is limiting (5), while the Warburg effect describes fermentative activity of cancer cells irrespective of oxygen. In the progression of tumors, cancer cells are subject to a range of oxygen concentrations, and low oxygen induces hypoxia-inducible factor (HIF), 2 which leads to a metabolic rewiring of cancer cells, resulting in a more glycolytic metabolism (6). Therefore, cancer cells may potentially demonstrate both Warburg and Pasteur effects. Furthermore, beyond glycolysis, altered oncogene expression has strong effects on other branches of central carbon metabolism. For insta...

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We carried out a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in LC-MS-based proteomics. We distributed a test sample consisting of an equimolar mix of 20 highly purified recombinant human proteins, to 27 laboratories for identification. Each protein contained one or more unique tryptic peptides of 1250 Da to also test for ion selection and sampling in the mass spectrometer. Of the 27 labs, initially only 7 labs reported all 20 proteins correctly, and only 1 lab reported all the tryptic peptides of 1250 Da. Nevertheless, a subsequent centralized analysis of the raw data revealed that all 20 proteins and most of the 1250 Da peptides had in fact been detected by all 27 labs. The centralized analysis allowed us to determine sources of problems encountered in the study, which include missed identifications (false negatives), environmental contamination, database matching, and curation of protein identifications. Improved search engines and databases are likely to increase the fidelity of mass spectrometry-based proteomics.