Variation of FMRP Expression in Peripheral Blood Mononuclear Cells from Individuals with Fragile X Syndrome.

Fragile X syndrome (FXS) is the most common heritable cause of intellectual disability and autism spectrum disorder. The syndrome is often caused by greatly reduced or absent protein expression from the fragile X messenger ribonucleoprotein 1 (FMR1) gene due to expansion of a 5'-non-coding trinucleotide (CGG) element beyond 200 repeats (full mutation). To better understand the complex relationships among FMR1 allelotype, methylation status, mRNA expression, and FMR1 protein (FMRP) levels, FMRP was quantified in peripheral blood mononuclear cells for a large cohort of FXS (n = 154) and control (n = 139) individuals using time-resolved fluorescence resonance energy transfer. Considerable size and methylation mosaicism were observed among individuals with FXS, with FMRP detected only in the presence of such mosaicism. No sample with a minimum allele size greater than 273 CGG repeats had significant levels of FMRP. Additionally, an association was observed between FMR1 mRNA and FMRP levels in FXS samples, predominantly driven by those with the lowest FMRP values. This study underscores the complexity of FMR1 allelotypes and FMRP expression and prompts a reevaluation of FXS therapies aimed at reactivating large full mutation alleles that are likely not capable of producing sufficient FMRP to improve cognitive function.

Predicting Influenza and Rhinovirus Infections in Airway Cells Utilizing Volatile Emissions.

BACKGROUND: Respiratory viral infections are common and potentially devastating to patients with underlying lung disease. Diagnosing viral infections often requires invasive sampling, and interpretation often requires specialized laboratory equipment. Here, we test the hypothesis that a breath test could diagnose influenza and rhinovirus infections using an in vitro model of the human airway. METHODS: Cultured primary human tracheobronchial epithelial cells were infected with either influenza A H1N1 or rhinovirus 1B and compared with healthy control cells. Headspace volatile metabolite measurements of cell cultures were made at 12-hour time points postinfection using a thermal desorption-gas chromatography-mass spectrometry method. RESULTS: Based on 54 compounds, statistical models distinguished volatile organic compound profiles of influenza- and rhinovirus-infected cells from healthy counterparts. Area under the curve values were 0.94 for influenza, 0.90 for rhinovirus, and 0.75 for controls. Regression analysis predicted how many hours prior cells became infected with a root mean square error of 6.35 hours for influenza- and 3.32 hours for rhinovirus-infected cells. CONCLUSIONS: Volatile biomarkers released by bronchial epithelial cells could not only be used to diagnose whether cells were infected, but also the timing of infection. Our model supports the hypothesis that a breath test could serve to diagnose viral infections.

Modeling cellular metabolomic effects of oxidative stress impacts from hydrogen peroxide and cigarette smoke on human lung epithelial cells.

The respiratory system is continuously exposed to variety of biological and chemical irritants that contain reactive oxygen species, and these are well known to cause oxidative stress responses in lung epithelial cells. There is a clinical need to identify biomarkers of oxidative stress which could potentially support early indicators of disease and health management. To identify volatile biomarkers of oxidative stress, we analyzed the headspace above human bronchial epithelial cell cultures (HBE1) before and after hydrogen peroxide (H2O2) and cigarette smoke extract (CSE) exposure. Using stir bar and headspace sorptive extraction-gas chromatography-mass spectrometry, we searched for volatile organic compounds (VOC) of these oxidative measures. In the H2O2 cell peroxidation experiments, four different H2O2 concentrations (0.1, 0.5, 10, 50 mM) were applied to the HBE1 cells, and VOCs were collected every 12 h over the time course of 48 h. In the CSE cell peroxidation experiments, four different smoke extract concentrations (0%, 10%, 30%, 60%) were applied to the cells, and VOCs were collected every 12 h over the time course of 48 h. We used partial-least squares (PLS) analysis to identify putative compounds from the mass spectrometry results that highly correlated with the known applied oxidative stress. We observed chemical emissions from the cells that related to both the intensity of the oxidative stress and followed distinct time courses. Additionally, some of these chemicals are aldehydes, which are thought to be non-invasive indicators of oxidative stress in exhaled human breath. Together, these results illustrate a powerful in situ cell culture model of oxidative stress that can be used to explore the putative biological genesis of exhaled breath biomarkers that are often observed in human clinical studies.

Wearable Environmental Monitor To Quantify Personal Ambient Volatile Organic Compound Exposures.

Air pollution can cause acute and chronic health problems. It has many components, and one component of interest is volatile organic compounds (VOCs). While the outdoor environment may have regulations regarding exposure limits, the indoor environment is often unregulated and VOCs often appear in greater concentrations in the indoor environment. Therefore, it is equally critical to monitor both the indoor and outdoor environments for ambient chemical levels that an individual person is exposed to. While a number of different chemical detectors exist, most lack the ability to provide portable monitoring. We have developed a portable and wearable sampler that collects environmental VOCs in a person's immediate "exposure envelope" onto custom micro-preconcentrator chips for later benchtop analysis. The system also records ambient temperature and humidity and the GPS location during sampling, and the chip cartridges can be used in sequence over time to complete a profile of individual chemical exposure over the course of hours/days/weeks/months. The system can be programmed to accumulate sample for various times with varying periodicity. We first tested our sampler in the laboratory by completing calibration curves and testing saturation times for various common chemicals. The sampler was also tested in the field by collecting both indoor and outdoor personal exposure samples. Additionally under IRB approval, a teenaged volunteer wore the sampler for 5 days during which it sampled periodically throughout a 12 h period each day and the volunteer replaced the micro-preconcentrator chip each day.