Differential gene expression in adipose stem cells cultured in allogeneic human serum versus fetal bovine serum.

In preclinical studies, human adipose stem cells (ASCs) have been shown to have therapeutic applicability, but standard expansion methods for clinical applications remain yet to be established. ASCs are typically expanded in the medium containing fetal bovine serum (FBS). However, sera and other animal-derived culture reagents stage safety issues in clinical therapy, including possible infections and severe immune reactions. By expanding ASCs in the medium containing human serum (HS), the problem can be eliminated. To define how allogeneic HS (alloHS) performs in ASC expansion compared to FBS, a comparative in vitro study in both serum supplements was performed. The choice of serum had a significant effect on ASCs. First, to reach cell proliferation levels comparable with 10% FBS, at least 15% alloHS was required. Second, while genes of the cell cycle pathway were overexpressed in alloHS, genes of the bone morphogenetic protein receptor-mediated signaling on the transforming growth factor beta signaling pathway regulating, for example, osteoblast differentiation, were overexpressed in FBS. The result was further supported by differentiation analysis, where early osteogenic differentiation was significantly enhanced in FBS. The data presented here underscore the importance of thorough investigation of ASCs for utilization in cell therapies. This study is a step forward in the understanding of these potential cells.

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our reconstruction is able to serve as a valuable resource in additional analyses involving objects from multiple molecular -omes. For that purpose, RefRec is freely available in the Systems Biology Markup Language format.