Evaluation of Dynamic Cell Processes and Behavior Using Video Bioinformatics Tools

Just as body language can reveal a person’s state of well-being, dynamic changes in cell behavior and morphology can be used to monitor processes in cultured cells. This chapter discusses how CL-Quant software, a commercially available video bioinformatics tool, can be used to extract quantitative data on: (1) growth/proliferation, (2) cell and colony migration, (3) reactive oxygen species (ROS) production, and (4) neural differentiation. Protocols created using CL-Quant were used to analyze both single cells and colonies. Time-lapse experiments in which different cell types were subjected to various chemical exposures were done using Nikon BioStations. Proliferation rate was measured in human embryonic stem cell colonies by quantifying colony area (pixels) and in single cells by measuring confluency (pixels). Colony and single cell migration were studied by measuring total displacement (distance between the starting and ending points) and total distance traveled by the colonies/cells. To quantify ROS production, cells were pre-loaded with MitoSOX Red™, a mitochondrial ROS (superoxide) indicator, treated with various chemicals, then total intensity of the red fluorescence was measured in each frame. Lastly, neural stem cells were incubated in differentiation medium for 12 days, and time lapse images were collected daily. Differentiation of neural stem cells was quantified using a protocol that detects young neurons. CLQuant software can be used to evaluate biological processes in living cells, and the protocols developed in this project can be applied to basic research and toxicological studies, or to monitor quality control in culture facilities

Epidemiology, radiology, and genetics of nicotine dependence in COPD

<p>Abstract</p> <p>Background</p> <p>Cigarette smoking is the principal environmental risk factor for developing COPD, and nicotine dependence strongly influences smoking behavior. This study was performed to elucidate the relationship between nicotine dependence, genetic susceptibility to nicotine dependence, and volumetric CT findings in smokers.</p> <p>Methods</p> <p>Current smokers with COPD (GOLD stage ≥ 2) or normal spirometry were analyzed from the COPDGene Study, a prospective observational study. Nicotine dependence was determined by the Fagerstrom test for nicotine dependence (FTND). Volumetric CT acquisitions measuring the percent of emphysema on inspiratory CT (% of lung <-950 HU) and gas trapping on expiratory CT (% of lung <-856 HU) were obtained. Genotypes for two SNPs in the CHRNA3/5 region (rs8034191, rs1051730) previously associated with nicotine dependence and COPD were analyzed for association to COPD and nicotine dependence phenotypes.</p> <p>Results</p> <p>Among 842 currently smoking subjects (335 COPD cases and 507 controls), 329 subjects (39.1%) showed high nicotine dependence. Subjects with high nicotine dependence had greater cumulative and current amounts of smoking. However, emphysema severity was negatively correlated with the FTND score in controls (ρ = -0.19, p < .0001) as well as in COPD cases (ρ = -0.18, p = 0.0008). Lower FTND score, male gender, lower body mass index, and lower FEV1 were independent risk factors for emphysema severity in COPD cases. Both CHRNA3/5 SNPs were associated with FTND in current smokers. An association of genetic variants in CHRNA3/5 with severity of emphysema was only found in former smokers, but not in current smokers.</p> <p>Conclusions</p> <p>Nicotine dependence was a negative predictor for emphysema on CT in COPD and control smokers. Increased inflammation in more highly addicted current smokers could influence the CT lung density distribution, which may influence genetic association studies of emphysema phenotypes.</p> <p>Trial registration</p> <p>ClinicalTrials (NCT): <a href="http://www.clinicaltrials.gov/ct2/show/NCT00608764">NCT00608764</a></p