Quantitative proteomic analysis of formalin–fixed, paraffin–embedded clear cell renal cell carcinoma tissue using stable isotopic dimethylation of primary amines

BACKGROUND: Formalin-fixed, paraffin-embedded (FFPE) tissues represent the most abundant resource of archived human specimens in pathology. Such tissue specimens are emerging as a highly valuable resource for translational proteomic studies. In quantitative proteomic analysis, reductive di-methylation of primary amines using stable isotopic formaldehyde variants is increasingly used due to its robustness and cost-effectiveness. RESULTS: In the present study we show for the first time that isotopic amine dimethylation can be used in a straightforward manner for the quantitative proteomic analysis of FFPE specimens without interference from formalin employed in the FFPE process. Isotopic amine dimethylation of FFPE specimens showed equal labeling efficiency as for cryopreserved specimens. For both FFPE and cryopreserved specimens, differential labeling of identical samples yielded highly similar ratio distributions within the expected range for dimethyl labeling. In an initial application, we profiled proteome changes in clear cell renal cell carcinoma (ccRCC) FFPE tissue specimens compared to adjacent non–malignant renal tissue. Our findings highlight increased levels of glyocolytic enzymes, annexins as well as ribosomal and proteasomal proteins. CONCLUSION: Our study establishes isotopic amine dimethylation as a versatile tool for quantitative proteomic analysis of FFPE specimens and underlines proteome alterations in ccRCC. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1768-x) contains supplementary material, which is available to authorized users

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a longterm storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.peerReviewe

Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks

Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex