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This paper presents Synapse, a scalable protocol for information retrieval over the inter-connection of heterogeneous overlay networks. Applications on top of Synapse see those intra-overlay networks as a unique inter-overlay network. Scalability in Synapse is achieved via co-located nodes, i.e. nodes that are part of multiple overlay networks at the same time. Co-located nodes, playing the role of neural synapses and connected to several overlay networks, allow a larger search area and provide alternative routing. Synapse can either work with “open” overlays adapting their protocol to synapse interconnection requirements, or with “closed” overlays that will not accept any change to their protocol. Results from simulation and experiments show that Synapse is scalable, with a communication and state overhead scaling similarly as the networks interconnected. Thanks to alternate routing paths, Synapse also gives a practical solution to network partitions. We precisely capture the behavior of traditional metrics of overlay networks within Synapse and present results from simulations as well as some actual experiments of a client prototype on the Grid'5000 platform. The prototype developed implements the Synapse protocol in the particular case of the interconnection of many Chord overlay networks.