To understand the system of secreted proteins and receptors involved in cell-cell signaling, we produced a comprehensive set of recombinant secreted proteins and the extracellular domains of transmembrane proteins, which constitute most of the protein components of the extracellular space. Each protein was tested in a suite of assays that measured metabolic, growth, or transcriptional responses in diverse cell types. The pattern of responses across assays was analyzed for the degree of functional selectivity of each protein. One of the highly selective proteins was a previously undescribed ligand, designated interleukin-34 (IL-34), which stimulates monocyte viability but does not affect responses in a wide spectrum of other assays. In a separate functional screen, we used a collection of extracellular domains of transmembrane proteins to discover the receptor for IL-34, which was a known cytokine receptor, colony-stimulating factor 1 (also called macrophage colony-stimulating factor) receptor. This systematic approach is thus useful for discovering new ligands and receptors and assessing the functional selectivity of extracellular regulatory proteins.

Due to high mixing times and base addition from top of the vessel, pH inhomogeneities are most likely to occur during large-scale mammalian processes. The goal of this study was to set-up a scale-down model of a 10-12 m stirred tank bioreactor and to investigate the effect of pH perturbations on CHO cell physiology and process performance. Short-term changes in extracellular pH are hypothesized to affect intracellular pH and thus cell physiology. Therefore, batch fermentations, including pH shifts to 9.0 and 7.8, in regular one-compartment systems are conducted. The short-term adaption of the cells intracellular pH are showed an immediate increase due to elevated extracellular pH. With this basis of fundamental knowledge, a two-compartment system is established which is capable of simulating defined pH inhomogeneities. In contrast to state-of-the-art literature, the scale-down model is included parameters (e.g. volume of the inhomogeneous zone) as they might occur during large-scale processes. pH inhomogeneity studies in the two-compartment system are performed with simulation of temporary pH zones of pH 9.0. The specific growth rate especially during the exponential growth phase is strongly affected resulting in a decreased maximum viable cell density and final product titer. The gathered results indicate that even short-term exposure of cells to elevated pH values during large-scale processes can affect cell physiology and overall process performance. In particular, it could be shown for the first time that pH perturbations, which might occur during the early process phase, have to be considered in scale-down models of mammalian processes.

Abstract:The architecture and weights of an artificial neural network model that predicts putative transmembrane sequences have been developed and optimized by the algorithm of structure evolution. The resulting filter is able to classify membrane/ nonmembrane transition regions in sequences of integral human membrane proteins with high accuracy. Similar results have been obtained for both training and test set data, indicating that the network has focused on general features of transmembrane sequences rather than specializing on the training data. Seven physicochemical amino acid properties have been used for sequence encoding. The predictions are compared to hydrophobicity plots.

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Donor-derived sMHC are potential tolerogens for down-regulating the cytotoxic T-cell response of animals that undergo transplantation. Thus, these data provide for the first time a rationale for the application of directly injected sMHC in vivo to down-regulate immunological responses and aid the induction of graft tolerance.