947 resultados para single-cell analysis
Resumo:
Studies of subcellular Ca(2+) signaling rely on methods for labeling cells with fluorescent Ca(2+) indicator dyes. In this study, we demonstrate the use of single-cell electroporation for Ca(2+) indicator loading of individual neurons and small neuronal networks in rat neocortex in vitro and in vivo. Brief voltage pulses were delivered through glass pipettes positioned close to target cells. This approach resulted in reliable and rapid (within seconds) loading of somata and subsequent complete labeling of dendritic and axonal arborizations. By using simultaneous whole-cell recordings in brain slices, we directly addressed the effect of electroporation on neurons. Cell viability was high (about 85%) with recovery from the membrane permeabilization occurring within a minute. Electrical properties of recovered cells were indistinguishable before and after electroporation. In addition, Ca(2+) transients with normal appearance could be evoked in dendrites, spines, and axonal boutons of electroporated cells. Using negative-stains of somata, targeted single-cell electroporation was equally applicable in vivo. We conclude that electroporation is a simple approach that permits Ca(2+) indicator loading of multiple cells with low background staining within a short amount of time, which makes it especially well suited for functional imaging of subcellular Ca(2+) dynamics in small neuronal networks.
Resumo:
This tutorial gives a step by step explanation of how one uses experimental data to construct a biologically realistic multicompartmental model. Special emphasis is given on the many ways that this process can be imprecise. The tutorial is intended for both experimentalists who want to get into computer modeling and for computer scientists who use abstract neural network models but are curious about biological realistic modeling. The tutorial is not dependent on the use of a specific simulation engine, but rather covers the kind of data needed for constructing a model, how they are used, and potential pitfalls in the process.
Resumo:
During development, the genome undergoes drastic reorganization within the nuclear space. To determine tridimensional genome folding, genome-wide techniques (damID/Hi-C) can be applied using cell populations, but these have to be calibrated using microscopy and single-cell analysis of gene positioning. Moreover, the dynamic behavior of chromatin has to be assessed on living samples. Combining fast stereotypic development with easy genetics and microscopy, the nematode C. elegans has become a model of choice in recent years to study changes in nuclear organization during cell fate acquisition. Here we present two complementary techniques to evaluate nuclear positioning of genes either by fluorescence in situ hybridization in fixed samples or in living worm embryos using the GFP-lacI/lacO chromatin-tagging system.
Resumo:
Autophagy is an evolutionarily conserved process that functions to maintain homeostasis and provides energy during nutrient deprivation and environmental stresses for the survival of cells by delivering cytoplasmic contents to the lysosomes for recycling and energy generation. Dysregulation of this process has been linked to human diseases including immune disorders, neurodegenerative muscular diseases and cancer. Autophagy is a double edged sword in that it has both pro-survival and pro-death roles in cancer cells. Its cancer suppressive roles include the clearance of damaged organelles, which could otherwise lead to inflammation and therefore promote tumorigenesis. In its pro-survival role, autophagy allows cancer cells to overcome cytotoxic stresses generated the cancer environment or cancer treatments such as chemotherapy and evade cell death. A better understanding of how drugs that perturb autophagy affect cancer cell signaling is of critical importance toimprove the cancer treatment arsenal. In order to gain insights in the relationship between autophagy and drug treatments, we conducted a high-throughput drug screen to identify autophagy modulators. Our high-throughput screen utilized image based fluorescent microscopy for single cell analysis to identify chemical perturbants of the autophagic process. Phenothiazines emerged as the largest family of drugs that alter the autophagic process by increasing LC3-II punctae levels in different cancer cell lines. In addition, we observed multiple biological effects in cancer cells treated with phenothiazines. Those antitumorigenic effects include decreased cell migration, cell viability, and ATP production along with abortive autophagy. Our studies highlight the potential role of phenothiazines as agents for combinational therapy with other chemotherapeutic agents in the treatment of different cancers.