Lipid droplets play a central role in energy storage and metabolism on a cellular scale. Their core is comprised of hydrophobic lipids covered by a surface region consisting of amphiphilic lipids and proteins. For example, high and low density lipoproteins (HDL and LDL, respectively) are essentially lipid droplets surrounded by specific proteins, their main function being to transport cholesterol. Interfacial tension and surface pressure of these particles are of great interest because they are related to the shape and the stability of the droplets and to protein adsorption at the interface. Here we use coarse-grained molecular-dynamics simulations to consider a number of related issues by calculating the interfacial tension in protein-free lipid droplets, and in HDL and LDL particles mimicking physiological conditions. First, our results suggest that the curvature dependence of interfacial tension becomes significant for particles with a radius of ∼5 nm, when the area per molecule in the surface region is <1.4 nm(2). Further, interfacial tensions in the used HDL and LDL models are essentially unaffected by single apo-proteins at the surface. Finally, interfacial tensions of lipoproteins are higher than in thermodynamically stable droplets, suggesting that HDL and LDL are kinetically trapped into a metastable state.

We explore the effects of probabilistic RNA partitioning during cell division on the normalized variance of RNA numbers across generations of bacterial populations. We first characterize these effects in model cell populations, where gene expression is modeled as a delayed stochastic process, as a function of the synchrony in cell division, the rate of division, and the RNA degradation rate. We further explore the additional variance that arises if the partitioning is biased. Next, in Escherichia coli cells expressing RNA tagged with MS2d-GFP, we measured the normalized variance of RNA numbers across several generations, with cell divisions synchronized by heat shock. We show that synchronized cell populations exhibit transient increases in normalized variance following cell divisions, as predicted by the model, which are not observed in unsynchronized populations. We conclude that errors in partitioning of RNA molecules generate diversity between the offspring of individual bacteria and thus constitute a form of reproductive bet-hedging.

Postnatal maturation of the neurons whose main phenotype and basic synaptic contacts are already established includes neuronal growth, refinement of synaptic contacts, final steps of differentiation, programmed cell death period (PCD) etc. In the sympathetic neurons, postnatal maturation includes permanent end of the PCD that occurs with the same time schedule in vivo and in vitro suggesting that the process could be genetically determined. Also many other changes in the neuronal maturation could be permanent and thus based on stable changes in the genome expression. However, postnatal maturation of the neurons is poorly studied. Here we compared the gene expression profiles of immature and mature sympathetic neurons using Affymetrix microarray assay. We found 1310 significantly up-regulated and 1151 significantly down-regulated genes in the mature neurons. Gene ontology analysis reveals up-regulation of genes related to neuronal differentiation, chromatin and epigenetic changes, extracellular factors and their receptors, and cell adhesion, whereas many down-regulated genes were related to metabolic and biosynthetic processes. We show that termination of PCD is not related to major changes in the expression of classical genes for apoptosis or cell survival. Our dataset is deposited to the ArrayExpress database and is a valuable source to select candidate genes in the studies of neuronal maturation. As an example, we studied the changes in the expression of selected genes Igf2bp3, Coro1A, Zfp57, Dcx, and Apaf1 in the young and mature sympathetic ganglia by quantitative PCR and show that these were strongly downregulated in the mature ganglia.

Primary explant culture preserves three-dimensional architecture of tumor tissue, intra-tumoral heterogeneity and aspects of tumor microenvironment, including interactions between tumor cells and the adjacent tissue cells. For these reasons, it is believed that the explant cultures capture tumor-specific pathways and their complexities better than possibly any other in vitro or ex vivo tumor model. We are developing a primary human breast tumor explant platform allowing integration of rapid, small-scale genome profiling with validation of tumor specific targets. We show that the explants, processed to 100 uM fragments and cultured on a 3D matrix, contain both epithelial and stromal cells and maintain the viability for up to 12 days. To characterize the explant phenotype and similarity to the original tumor, we have examined explants and the original tumors side-by-side by immunohistochemistry (IHC), immunocytochemistry (ICC) and genome profiling. The biomarkers analyzed by IHC and/or ICC include hormone receptors, cytokines, epithelial and stromal cell markers as well as proliferation and apoptosis markers. A small-scale genome profiling analysis was performed with TruSeq Amplicon Cancer panel. Cancer-related missense mutations were identical in 60% of original tumor/ explant pairs and had minor differences in 40% of original tumor/ explant pairs. Compared to original tumors, proliferation was increased in explants but clear correlation in the level of proliferation between original tumor/ explant was observed. In conclusion, our preliminary findings suggest surprisingly similar genetic landscapes between breast tumor explants and the cognate primary tumors. Therefore, breast tumor explant platforms could predict well the efficacy of molecular targeted and personalized therapies. Citation Format: Liina Nevalaita, Hanna Ala-Hongisto, Maria Lehtivaara, Päivi Heikkilä, Marjut Leidenius, Panu Kovanen, Outi Monni, Juha Klefström. Primary human breast tumor explant platform for integrated profiling and target validation. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1188. doi:10.1158/1538-7445.AM2014-1188