Dynamic visualization of expressed gene networks

TRIB2 confers resistance to anti-cancer therapy by activating the serine/threonine protein kinase AKT

Intrinsic and acquired resistance to chemotherapy is the fundamental reason for treatment failure for many cancer patients. The identification of molecular mechanisms involved in drug resistance or sensitization is imperative. Here we report that tribbles homologue 2 (TRIB2) ablates forkhead box O activation and disrupts the p53/MDM2 regulatory axis, conferring resistance to various chemotherapeutics. TRIB2 suppression is exerted via direct interaction with AKT a key signalling protein in cell proliferation, survival and metabolism pathways. Ectopic or intrinsic high expression of TRIB2 induces drug resistance by promoting phospho-AKT (at Ser473) via its COP1 domain. TRIB2 expression is significantly increased in tumour tissues from patients correlating with an increased phosphorylation of AKT, FOXO3a, MDM2 and an impaired therapeutic response. This culminates in an extremely poor clinical outcome. Our study reveals a novel regulatory mechanism underlying drug resistance and suggests that TRIB2 functions as a regulatory component of the PI3K network, activating AKT in cancer cells.

Competition between members of the tribbles pseudokinase protein family shapes their interactions with mitogen activated protein kinase pathways

Spatio-temporal regulation of intracellular signalling networks is key to normal cellular physiology; dysregulation of which leads to disease. The family of three mammalian tribbles proteins has emerged as an important controller of signalling via regulating the activity of mitogen activated protein kinases (MAPK), the PI3-kinase induced signalling network and E3 ubiquitin ligases. However, the importance of potential redundancy in the action of tribbles and how the differences in affinities for the various binding partners may influence signalling control is currently unclear. We report that tribbles proteins can bind to an overlapping set of MAPK-kinases (MAPKK) in live cells and dictate the localisation of the complexes. Binding studies in transfected cells reveal common regulatory mechanisms and suggest that tribbles and MAPKs may interact with MAPKKs in a competitive manner. Computational modelling of the impact of tribbles on MAPK activation suggests a high sensitivity of this system to changes in tribbles levels, highlighting that these proteins are ideally placed to control the dynamics and balance of activation of concurrent signalling pathways.

Network approaches to the functional analysis of microbial proteins

Large amounts of detailed biological data have been generated over the past few decades. Much of these data is freely available in over 1000 online databases; an enticing, but frustrating resource for microbiologists interested in a systems-level view of the structure and function of microbial cells. The frustration engendered by the need to trawl manually through hundreds of databases in order to accumulate information about a gene, protein, pathway, or organism of interest can be alleviated by the use of computational data integration to generated network views of the system of interest. Biological networks can be constructed from a single type of data, such as protein-protein binding information, or from data generated by multiple experimental approaches. In an integrated network, nodes usually represent genes or gene products, while edges represent some form of interaction between the nodes. Edges between nodes may be weighted to represent the probability that the edge exists in vivo. Networks may also be enriched with ontological annotations, facilitating both visual browsing and computational analysis via web service interfaces. In this review, we describe the construction, analysis of both single-data source and integrated networks, and their application to the inference of protein function in microbes.

A handcuff model for the cohesin complex

The cohesin complex is responsible for the accurate separation of sister chromatids into two daughter cells. Several models for the cohesin complex have been proposed, but the one-ring embrace model currently predominates the field. However, the static configuration of the embrace model is not flexible enough for cohesins to perform their functions during DNA replication, transcription, and DNA repair. We used coimmunoprecipitation, a protein fragment complement assay, and a yeast two-hybrid assay to analyze the protein-protein interactions among cohesin subunits. The results show that three of the four human cohesin core subunits (Smc1, Smc3, and Rad21) interact with themselves in an Scc3 (SA1/SA2)-dependent manner. These data support a two-ring handcuff model for the cohesin complex, which is flexible enough to establish and maintain sister chromatid cohesion as well as ensure the fidelity of chromosome segregation in higher eukaryotes.

Vectors for multi-color bimolecular fluorescence complementation to investigate protein-protein interactions in living plant cells

BACKGROUND

The investigation of protein-protein interactions is important for characterizing protein function. Bimolecular fluorescence complementation (BiFC) has recently gained interest as a relatively easy and inexpensive method to visualize protein-protein interactions in living cells. BiFC uses "split YFP" tags on proteins to detect interactions: If the tagged proteins interact, they may bring the two split fluorophore components together such that they can fold and reconstitute fluorescence. The sites of interaction can be monitored using epifluorescence or confocal microscopy. However, "conventional" BiFC can investigate interactions only between two proteins at a time. There are instances when one may wish to offer a particular "bait" protein to several "prey" proteins simultaneously. Preferential interaction of the bait protein with one of the prey proteins, or different sites of interaction between the bait protein and multiple prey proteins, may thus be observed.

RESULTS

We have constructed a series of gene expression vectors, based upon the pSAT series of vectors, to facilitate the practice of multi-color BiFC. The bait protein is tagged with the C-terminal portion of CFP (cCFP), and prey proteins are tagged with the N-terminal portions of either Venus (nVenus) or Cerulean (nCerulean). Interaction of cCFP-tagged proteins with nVenus-tagged proteins generates yellow fluorescence, whereas interaction of cCFP-tagged proteins with nCerulean-tagged proteins generates blue fluorescence. Additional expression of mCherry indicates transfected cells and sub-cellular structures. Using this system, we have determined in both tobacco BY-2 protoplasts and in onion epidermal cells that Agrobacterium VirE2 protein interacts with the Arabidopsis nuclear transport adapter protein importin alpha-1 in the cytoplasm, whereas interaction of VirE2 with a different importin alpha isoform, importin alpha-4, occurs predominantly in the nucleus.

CONCLUSION

Multi-color BiFC is a useful technique to determine interactions simultaneously between a given" bait" protein and multiple "prey" proteins in living plant cells. The vectors we have constructed and tested will facilitate the study of protein-protein interactions in many different plant systems.

Universal strategies in research and drug discovery based on protein-fragment complementation assays

Changes in the interactions among proteins that participate in a biochemical pathway can reflect the immediate regulatory responses to intrinsic or extrinsic perturbations of the pathway. Thus, methods that allow for the direct detection of the dynamics of protein-protein interactions can be used to probe the effects of any perturbation on any pathway of interest. Here we describe experimental strategies - based on protein-fragment complementation assays (PCAs) - that can achieve this. PCA-based strategies can be used with or instead of traditional target-based drug discovery strategies to identify novel pathway-component proteins of therapeutic interest, to increase the quantity and quality of information about the actions of potential drugs, and to gain insight into the intricate networks that make up the molecular machinery of living cells.

PIN-G--a novel reporter for imaging and defining the effects of trafficking signals in membrane proteins

BACKGROUND

The identification of protein trafficking signals, and their interacting mechanisms, is a fundamental objective of modern biology. Unfortunately, the analysis of trafficking signals is complicated by their topography, hierarchical nature and regulation. Powerful strategies to test candidate motifs include their ability to direct simpler reporter proteins, to which they are fused, to the appropriate cellular compartment. However, present reporters are limited by their endogenous expression, paucity of cloning sites, and difficult detection in live cells.

RESULTS

Consequently, we have engineered a mammalian expression vector encoding a novel trafficking reporter--pIN-G--consisting of a simple, type I integral protein bearing permissive intra/extracellular cloning sites, green fluorescent protein (GFP), cMyc and HA epitope tags. Fluorescence imaging, flow cytometry and biochemical assays of transfected HEK293 cells, confirm the size, topology and surface expression of PIN-G. Moreover, a pIN-G fusion construct, containing a Trans-Golgi Network (TGN) targeting determinant, internalises rapidly from the cell surface and localises to the TGN. Additionally, another PIN-G fusion protein and its mutants reveal trafficking determinants in the cytoplasmic carboxy terminus of Kv1.4 voltage-gated potassium channels.

CONCLUSION

Together, these data indicate that pIN-G is a versatile, powerful, new reporter for analysing signals controlling membrane protein trafficking, surface expression and dynamics.

Fluorescent protein-based cellular assays analyzed by laser-scanning microplate cytometry in 1536-well plate format

Microtiter plate readers have evolved from photomultiplier and charged-coupled device-based readers, where a population-averaged signal is detected from each well, to microscope-based imaging systems, where cellular characteristics from individual cells are measured. For these systems, speed and ease of data analysis are inversely proportional to the amount of data collected from each well. Microplate laser cytometry is a technology compatible with a 1536-well plate format and capable of population distribution analysis. Microplate cytometers such as the Acumen Explorer can monitor up to four fluorescent signals from single objects in microtiter plates with densities as high as 1536 wells. These instruments can measure changes in fluorescent protein expression, cell shape, or simple cellular redistribution events such as cytoplasmic to nuclear translocation. To develop high-throughput screening applications using laser-scanning microplate cytometry, we used green fluorescent protein- and yellow fluorescent protein-expressing cell lines designed to measure diverse biological functions such as nuclear translocation, epigenetic signaling, and G protein-coupled receptor activation. This chapter illustrates the application of microplate laser cytometry to these assays in a manner that is suitable for screening large compound collections in high throughput.

Chemical biology on PINs and NeeDLes

Systematic studies of the organization of biochemical networks that make up the living cell can be defined by studying the organization and dynamics of protein interaction networks (PINs). Here, we describe recent conceptual and experimental advances that can achieve this aim and how chemical perturbations of interactions can be used to define the organization of biochemical networks. Resulting perturbation profiles and subcellular locations of interactions allow us to 'place' each gene product at its relevant point in a network. We discuss how experimental strategies can be used in conjunction with other genome-wide analyses of physical and genetic protein interactions and gene transcription profiles to determine network dynamic linkage (NDL) in the living cell. It is through such dynamic studies that the intricate networks that make up the chemical machinery of the cell will be revealed.

Interaction networks: coordinating responses to xenobiotic exposure

In the last decade the increased usage of '-omic' technologies, plus the sequencing of over 800 complete genomes has led to a vast increase in the amount of information available to the researcher for examining cellular responses to xenobiotics. Much effort has been put into the identification and analysis of expression profiles associated with pathobiological conditions and/or xenobiotic exposure. These profiles are commonly used in two applications. Firstly, comparative profile experiments are used to classify pathobiological states and for the screening of novel chemical entities to predict their action(s) on the body. Secondly, mechanistic investigations will gain information on the molecular mechanisms underlying toxic responses/pathobiological states. During the course of such analysis it has become increasingly clear that a series of highly refined interaction networks exist within the body, regulating both the sensitivity and selectivity of the body's response to pathobiological states/xenobiotic exposure. These interaction networks exist at several levels: Firstly, within individual cells, the interaction between factors that transmit xenobiotics signals will determine the overall cellular response. Secondly, intraorgan communication occurs between the different cell types/sub-types which makes up an organ, coordinating the overall organ response. Finally, interorgan interactions provide axes of response through the body.