Proteomic profiling of neuromas reveals alterations in protein composition and local protein synthesis in hyper-excitable nerves

Neuropathic pain may arise following peripheral nerve injury though the molecular mechanisms associated with this are unclear. We used proteomic profiling to examine changes in protein expression associated with the formation of hyper-excitable neuromas derived from rodent saphenous nerves. A two-dimensional difference gel electrophoresis ( 2D-DIGE) profiling strategy was employed to examine protein expression changes between developing neuromas and normal nerves in whole tissue lysates. We found around 200 proteins which displayed a > 1.75-fold change in expression between neuroma and normal nerve and identified 55 of these proteins using mass spectrometry. We also used immunoblotting to examine the expression of low-abundance ion channels Nav1.3, Nav1.8 and calcium channel alpha 2 delta-1 subunit in this model, since they have previously been implicated in neuronal hyperexcitability associated with neuropathic pain. Finally, S(35)methionine in vitro labelling of neuroma and control samples was used to demonstrate local protein synthesis of neuron-specific genes. A number of cytoskeletal proteins, enzymes and proteins associated with oxidative stress were up-regulated in neuromas, whilst overall levels of voltage-gated ion channel proteins were unaffected. We conclude that altered mRNA levels reported in the somata of damaged DRG neurons do not necessarily reflect levels of altered proteins in hyper-excitable damaged nerve endings. An altered repertoire of protein expression, local protein synthesis and topological re-arrangements of ion channels may all play important roles in neuroma hyper-excitability.

Communicating neurons: a connectionist spiking neuron implementation of stochastic diffusion search

An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.