A detailed depiction of the 'integrin adhesome', consisting of a complex network of 156 components linked together and modified by 690 interactions is presented. Different views of the network reveal several functional 'subnets' that are involved in switching on or off many of the molecular interactions within the network, consequently affecting cell adhesion, migration and cytoskeletal organization. Examination of the adhesome network motifs reveals a relatively small number of key motifs, dominated by three-component complexes in which a scaffolding molecule recruits both a signalling molecule and its downstream target. We discuss the role of the different network modules in regulating the structural and signalling functions of cell-matrix adhesions. Top-down and bottom-up approaches for studying the integrin adhesomeCell-extracellular matrix (ECM) interactions are mediated through specialized subcellular sites that contain specific adhesion receptors, cytoskeletal elements and a wide variety of interconnecting adaptor proteins [1][2][3] . These adhesion complexes permit cells to sense multiple extracellular signals that specify the chemical identity, geometry and physical properties of the ECM 4,5 . Thus, cells behave differently on two-and three-dimensional matrices 6 , distinguish between different ECM components 7 , can detect differences in adhesive ligand density 8 , and respond to mechanical perturbation and surface rigidity 9,10 . Competing Financial Interests:The authors declare no competing financial interests.Website -www.adhesome.org contains the adhesome database of components and interactions with an interface that allows dynamical navigation between hyperlinked subnets created for each component and for many network motifs within the adhesome network.Publisher's Disclaimer: Disclaimer: Nature Publishing Group has a collaboration with the Cell Migration Consortium for the creation and maintenance of the Cell Migration gateway (http://www.cellmigration.org/), but has no role in generating or curating the Cell Migration Consortium database content. As always, Nature Cell Biology Editors have been fully independent and solely responsible for the editorial content and peer review of this Analysis article. NIH Public Access Author ManuscriptNat Cell Biol. Author manuscript; available in PMC 2009 August 31. Published in final edited form as:Nat Cell Biol. 2007 August ; 9(8): 858-867. doi:10.1038/ncb0807-858. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptTo understand the mechanisms underlying these diverse responses, in-depth characterization of individual proteins or pathways 11,12 , and collection of information about multiple components that concertedly form the presumed adhesome 13,14 , have been undertaken. Each of these approaches has limitations, and individually is unlikely to explain how the adhesion machinery senses environmental cues and responds to them. However, combining data from the two approaches could produce new mechanistic insights into the structu...

The heterotrimeric guanine nucleotide-binding proteins (G proteins) are signal transducers that communicate signals from many hormones, neurotransmitters, chemokines, and autocrine and paracrine factors. The extracellular signals are received by members of a large superfamily of receptors with seven membrane-spanning regions that activate the G proteins, which route the signals to several distinct intracellular signaling pathways. These pathways interact with one another to form a network that regulates metabolic enzymes, ion channels, transporters, and other components of the cellular machinery controlling a broad range of cellular processes, including transcription, motility, contractility, and secretion. These cellular processes in turn regulate systemic functions such as embryonic development, gonadal development, learning and memory, and organismal homeostasis.

Intracellular signaling networks receive and process information to control cellular machines. The mitogen-activated protein kinase (MAPK) 1,2/protein kinase C (PKC) system is one such network that regulates many cellular machines, including the cell cycle machinery and autocrine/paracrine factor synthesizing machinery. We used a combination of computational analysis and experiments in mouse NIH-3T3 fibroblasts to understand the design principles of this controller network. We find that the growth factor-stimulated signaling network containing MAPK 1, 2/PKC can operate with one (monostable) or two (bistable) stable states. At low concentrations of MAPK phosphatase, the system exhibits bistable behavior, such that brief stimulus results in sustained MAPK activation. The MAPK-induced increase in the amounts of MAPK phosphatase eliminates the prolonged response capability and moves the network to a monostable state, in which it behaves as a proportional response system responding acutely to stimulus. Thus, the MAPK 1, 2/PKC controller network is flexibly designed, and MAPK phosphatase may be critical for this flexible response.

MicroRNAs (miRNAs) in body fluids are candidate diagnostics for a variety of conditions and diseases, including breast cancer. One premise for using extracellular miRNAs to diagnose disease is the notion that the abundance of the miRNAs in body fluids reflects their abundance in the abnormal cells causing the disease. As a result, the search for such diagnostics in body fluids has focused on miRNAs that are abundant in the cells of origin. Here we report that released miRNAs do not necessarily reflect the abundance of miRNA in the cell of origin. We find that release of miRNAs from cells into blood, milk and ductal fluids is selective and that the selection of released miRNAs may correlate with malignancy. In particular, the bulk of miR-451 and miR-1246 produced by malignant mammary epithelial cells was released, but the majority of these miRNAs produced by non-malignant mammary epithelial cells was retained. Our findings suggest the existence of a cellular selection mechanism for miRNA release and indicate that the extracellular and cellular miRNA profiles differ. This selective release of miRNAs is an important consideration for the identification of circulating miRNAs as biomarkers of disease.

Many distinct signaling pathways allow the cell to receive, process, and respond to information. Often, components of different pathways interact, resulting in signaling networks. Biochemical signaling networks were constructed with experimentally obtained constants and analyzed by computational methods to understand their role in complex biological processes. These networks exhibit emergent properties such as integration of signals across multiple time scales, generation of distinct outputs depending on input strength and duration, and self-sustaining feedback loops. Feedback can result in bistable behavior with discrete steady-state activities, well-defined input thresholds for transition between states and prolonged signal output, and signal modulation in response to transient stimuli. These properties of signaling networks raise the possibility that information for "learned behavior" of biological systems may be stored within intracellular biochemical reactions that comprise signaling pathways.