The impact of gene expression regulation on evolution of extracellular signaling pathways

Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research

With the wealth of data accumulated from completely sequenced genomes and other high-throughput experiments, global studies of biological systems, by simultaneously investigating multiple biological entities (e.g. genes, transcripts, proteins), has become a routine. Network representation is frequently used to capture the presence of these molecules as well as their relationship. Network biology has been widely used in molecular biology and genetics, where several network properties have been shown to be functionally important. Here, we discuss how such methodology can be useful to translational biomedical research, where scientists traditionally focus on one or a small set of genes, diseases, and drug candidates at any one time. We first give an overview of network representation frequently used in biology: what nodes and edges represent, and review its application in preclinical research to date. Using cancer as an example, we review how network biology can facilitate system-wide approaches to identify targeted small molecule inhibitors. These types of inhibitors have the potential to be more specific, resulting in high efficacy treatments with less side effects, compared to the conventional treatments such as chemotherapy. Global analysis may provide better insight into the overall picture of human diseases, as well as identify previously overlooked problems, leading to rapid advances in medicine. From the clinicians’ point of view, it is necessary to bridge the gap between theoretical network biology and practical biomedical research, in order to improve the diagnosis, prevention, and treatment of the world’s major diseases.

Development of an antigen microarray for high throughput monoclonal antibody selection

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Development of an antigen array for high throughput monoclonal antibody selection.

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Identification of cross-reactive antibodies at an early stage of screening.

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Convenient screening method to identify functional recombinant antibodies.

Monoclonal antibodies are valuable laboratory reagents and are increasingly being exploited as therapeutics to treat a range of diseases. Selecting new monoclonal antibodies that are validated to work in particular applications, despite the availability of several different techniques, can be resource intensive with uncertain outcomes. To address this, we have developed an approach that enables early screening of hybridoma supernatants generated from an animal immunised with up to five different antigens followed by cloning of the antibody into a single expression plasmid. While this approach relieved the cellular cloning bottleneck and had the desirable ability to screen antibody function prior to cloning, the small volume of hybridoma supernatant available for screening limited the number of antigens for pooled immunisation. Here, we report the development of an antigen microarray that significantly reduces the volume of supernatant required for functional screening. This approach permits a significant increase in the number of antigens for parallel monoclonal antibody selection from a single animal. Finally, we show the successful use of a convenient small-scale transfection method to rapidly identify plasmids that encode functional cloned antibodies, addressing another bottleneck in this approach. In summary, we show that a hybrid approach of combining established hybridoma antibody technology with refined screening and antibody cloning methods can be used to select monoclonal antibodies of desired functional properties against many different antigens from a single immunised host.

A benchmarked protein microarray-based platform for the identification of novel low-affinity extracellular protein interactions

Low-affinity extracellular protein interactions are critical for cellular recognition processes, but existing methods to detect them are limited in scale, making genome-wide interaction screens technically challenging. To address this, we report here the miniaturization of the AVEXIS (avidity-based extracellular interaction screen) assay by using protein microarray technology. To achieve this, we have developed protein tags and sample preparation methods that enable the parallel purification of hundreds of recombinant proteins expressed in mammalian cells. We benchmarked the protein microarray-based assay against a set of known quantified receptor–ligand pairs and show that it is sensitive enough to detect even very weak interactions that are typical of this class of interactions. The increase in scale enables interaction screening against a dilution series of immobilized proteins on the microarray enabling the observation of saturation binding behaviors to show interaction specificity and also the estimation of interaction affinities directly from the primary screen. These methodological improvements now permit screening for novel extracellular receptor–ligand interactions on a genome-wide scale.

A secreted protein microarray platform for extracellular protein interaction discovery

Characterization of the extracellular protein interactome has lagged far behind that of intracellular proteins, where mass spectrometry and yeast two-hybrid technologies have excelled. Improved methods for identifying receptor-ligand and extracellular matrix protein interactions will greatly accelerate biological discovery in cell signaling and cellular communication. These technologies must be able to identify low-affinity binding events that are often observed between membrane-bound coreceptor molecules during cell-cell or cell-extracellular matrix contact. Here we demonstrate that functional protein microarrays are particularly well-suited for high-throughput screening of extracellular protein interactions. To evaluate the performance of the platform, we screened a set of 89 immunoglobulin (Ig)-type receptors against a highly diverse extracellular protein microarray with 686 genes represented. To enhance detection of low-affinity interactions, we developed a rapid method to assemble bait Fc fusion proteins into multivalent complexes using protein A microbeads. Based on these screens, we developed a statistical methodology for hit calling and identification of nonspecific interactions on protein microarrays. We found that the Ig receptor interactions identified using our methodology are highly specific and display minimal off-target binding, resulting in a 70% true-positive to false-positive hit ratio. We anticipate that these methods will be useful for a wide variety of functional protein microarray users.

Neurexins, neuroligins and LRRTMs: synaptic adhesion getting fishy

Recent studies have identified the leucine rich repeat protein LRRTM2 as a post-synaptic ligand of Neurexins. Neurexins also bind the post-synaptic adhesion molecules, Neuroligins. All three families of genes have been implicated in the etiologies of neurodevelopmental disorders, specifically autism spectrum disorders and schizophrenia. Does the binding promiscuity of Neurexins now suggest complex cooperativity or redundancy at the synapse? While recent studies in primary neuronal cultures and also systematic extracellular protein interaction screens suggest summative effects of these systems, we propose that studying these interactions in the developing zebrafish embryo or larvae may shed more light on their functions during synaptogenesis in vivo. These gene families have recently been extensively characterized in zebrafish, demonstrating high sequence conservation with the human genes. The simpler circuitry of the zebrafish, together with the characterization of the expression patterns down to single, identifiable neurons and the ability to knock-down or over-express multiple genes in a rapid way lend themselves to dissecting complex interaction pathways. Furthermore, the capability of performing high-throughput drug screens suggests that these small vertebrates may prove extremely useful in identifying pharmacological approaches to treating autism spectrum disorders.

Construction of a large extracellular protein interaction network and its resolution by spatiotemporal expression profiling

Extracellular interactions involving both secreted and membrane-tethered receptor proteins are essential to initiate signaling pathways that orchestrate cellular behaviors within biological systems. Because of the biochemical properties of these proteins and their interactions, identifying novel extracellular interactions remains experimentally challenging. To address this, we have recently developed an assay, AVEXIS (avidity-based extracellular interaction screen) to detect low affinity extracellular interactions on a large scale and have begun to construct interaction networks between zebrafish receptors belonging to the immunoglobulin and leucine-rich repeat protein families to identify novel signaling pathways important for early development. Here, we expanded our zebrafish protein library to include other domain families and many more secreted proteins and performed our largest screen to date totaling 16,544 potential unique interactions. We report 111 interactions of which 96 are novel and include the first documented extracellular ligands for 15 proteins. By including 77 interactions from previous screens, we assembled an expanded network of 188 extracellular interactions between 92 proteins and used it to show that secreted proteins have twice as many interaction partners as membrane-tethered receptors and that the connectivity of the extracellular network behaves as a power law. To try to understand the functional role of these interactions, we determined new expression patterns for 164 genes within our clone library by using whole embryo in situ hybridization at five key stages of zebrafish embryonic development. These expression data were integrated with the binding network to reveal where each interaction was likely to function within the embryo and were used to resolve the static interaction network into dynamic tissue- and stage-specific subnetworks within the developing zebrafish embryo. All these data were organized into a freely accessible on-line database called ARNIE (AVEXIS Receptor Network with Integrated Expression; www.sanger.ac.uk/arnie) and provide a valuable resource of new extracellular signaling interactions for developmental biology.