Isolation and characterization of plasma membrane-associated cortical granules from sea urchin eggs

Cortical granules, which are specialized secretory organelles found in ova of many organisms, have been isolated from the eggs of the sea urchins Arbacia punctulata and Strongylocentrtus pupuratus by a simple, rapid procedure. Electron micropscope examination of cortical granules prepared by this procedure reveals that they are tightly attached to large segments of the plasma membrane and its associated vitelline layer. Further evidence that he cortical granules were associated with these cell surface layers was obtained by (125)I-labeling techniques. The cortical granule preparations were found to be rich in proteoesterase, which was purified 32-fold over that detected in a crude homogenate. Similarly, the specific radioactivity of a (125)I-labeled, surface glycoprotein was increased 40-fold. These facts, coupled with electron microscope observations, indicate the isolation procedure yields a preparation in which both the cortical granules and the plasma membrane-vitelline layer are purified to the same extent. Gel electrophoresis of the membrane-associated cortical granule preparation reveals the presence of at least eight polypeptides. The major polypeptide, which is a glycotprotein of apparent mol wt of 100,000, contains most of the radioactivity introduced by (125)I-labeling of the intact eggs. Lysis of the cortical granules is observed under hypotonic conditions, or under isotonic conditions if Ca(2+) ion is present. When lysis is under isotonic conditions is induced by addition of Ca(2+) ion, the electron-dense contents of the granules remain insoluble. In contrast, hypotonic lysis results in release of the contents of the granule in a soluble form. However, in both cases the (125)I-labeled glycoprotein remains insoluble, presumably because it is a component of either the plasma membrane or the vitelline layer. All these findings indicate that, using this purified preparation, it should be possible to carry out in vitro studies to better define some of the initial, surface-related events observed in vivo upon fertilization.     

Programmatic Cost Evaluation of Nontargeted Opt-Out Rapid HIV Screening in the Emergency Department

Background

The Centers for Disease Control and Prevention recommends nontargeted opt-out HIV screening in healthcare settings. Cost effectiveness is critical when considering potential screening methods. Our goal was to compare programmatic costs of nontargeted opt-out rapid HIV screening with physician-directed diagnostic rapid HIV testing in an urban emergency department (ED) as part of the Denver ED HIV Opt-Out Trial.

Methods

This was a prospective cohort study nested in a larger quasi-experiment. Over 16 months, nontargeted rapid HIV screening (intervention) and diagnostic rapid HIV testing (control) were alternated in 4-month time blocks. During the intervention phase, patients were offered HIV testing using an opt-out approach during registration; during the control phase, physicians used a diagnostic approach to offer HIV testing to patients. Each method was fully integrated into ED operations. Direct program costs were determined using the perspective of the ED. Time-motion methodology was used to estimate personnel activity costs. Costs per patient newly-diagnosed with HIV infection by intervention phase, and incremental cost effectiveness ratios were calculated.

Results

During the intervention phase, 28,043 eligible patients were included, 6,933 (25%) completed testing, and 15 (0.2%, 95% CI: 0.1%–0.4%) were newly-diagnosed with HIV infection. During the control phase, 29,925 eligible patients were included, 243 (0.8%) completed testing, and 4 (1.7%, 95% CI: 0.4%–4.2%) were newly-diagnosed with HIV infection. Total annualized costs for nontargeted screening were $148,997, whereas total annualized costs for diagnostic HIV testing were $31,355. The average costs per HIV diagnosis were $9,932 and $7,839, respectively. Nontargeted HIV screening identified 11 more HIV infections at an incremental cost of $10,693 per additional infection.

Conclusions

Compared to diagnostic testing, nontargeted HIV screening was more costly but identified more HIV infections. More effective and less costly testing strategies may be required to improve the identification of patients with undiagnosed HIV infection in the ED.     

DNA methylation in the human cerebral cortex is dynamically regulated throughout the life span and involves differentiated neurons

The role of DNA cytosine methylation, an epigenetic regulator of chromatin structure and function, during normal and pathological brain development and aging remains unclear. Here, we examined by MethyLight PCR the DNA methylation status at 50 loci, encompassing primarily 5' CpG islands of genes related to CNS growth and development, in temporal neocortex of 125 subjects ranging in age from 17 weeks of gestation to 104 years old. Two psychiatric disease cohorts--defined by chronic neurodegeneration (Alzheimer's) or lack thereof (schizophrenia)--were included. A robust and progressive rise in DNA methylation levels across the lifespan was observed for 8/50 loci (GABRA2, GAD1, HOXA1, NEUROD1, NEUROD2, PGR, STK11, SYK) typically in conjunction with declining levels of the corresponding mRNAs. Another 16 loci were defined by a sharp rise in DNA methylation levels within the first few months or years after birth. Disease-associated changes were limited to 2/50 loci in the Alzheimer's cohort, which appeared to reflect an acceleration of the age-related change in normal brain. Additionally, methylation studies on sorted nuclei provided evidence for bidirectional methylation events in cortical neurons during the transition from childhood to advanced age, as reflected by significant increases at 3, and a decrease at 1 of 10 loci. Furthermore, the DNMT3a de novo DNA methyl-transferase was expressed across all ages, including a subset of neurons residing in layers III and V of the mature cortex. Therefore, DNA methylation is dynamically regulated in the human cerebral cortex throughout the lifespan, involves differentiated neurons, and affects a substantial portion of genes predominantly by an age-related increase.     

Do Solitary Bees Osmia cornuta Latr. and Osmia lignaria Cresson Use Proximal Visual Cues to Localize Their Nest?

Female Osmia repeatedly return to their nest to provision it with food and building material. The present study investigates the bees' nest localization performance by modifying visual cues in the near-vicinity of the nest. Each of several arrays of nesting holes was surrounded by four geometrical shapes. Removing some or all of the shapes reduced the proportion of direct returns but never prevented a bee from finding the appropriate array and, within that array, its own nest. The more the pattern was modified, the higher was the error score and the longer the delay, but no bee failed finally to find its nest. Shifting the pattern as well as the whole array of holes shifted homing orientation accordingly. There was no effect of the positions of the removed shapes, of contrast inversion, or of modifying the holes array. Our data are discussed in the light of the snapshot theory.     

Automated Bayesian model development for frequency detection in biological time series

Background

The ability to perform quantitative studies using isotope tracers and metabolic flux analysis (MFA) is critical for detecting pathway bottlenecks and elucidating network regulation in biological systems, especially those that have been engineered to alter their native metabolic capacities. Mathematically, MFA models are traditionally formulated using separate state variables for reaction fluxes and isotopomer abundances. Analysis of isotope labeling experiments using this set of variables results in a non-convex optimization problem that suffers from both implementation complexity and convergence problems.

Results

This article addresses the mathematical and computational formulation of ¹³C MFA models using a new set of variables referred to as fluxomers. These composite variables combine both fluxes and isotopomer abundances, which results in a simply-posed formulation and an improved error model that is insensitive to isotopomer measurement normalization. A powerful fluxomer iterative algorithm (FIA) is developed and applied to solve the MFA optimization problem. For moderate-sized networks, the algorithm is shown to outperform the commonly used 13CFLUX cumomer-based algorithm and the more recently introduced OpenFLUX software that relies upon an elementary metabolite unit (EMU) network decomposition, both in terms of convergence time and output variability.

Conclusions

Substantial improvements in convergence time and statistical quality of results can be achieved by applying fluxomer variables and the FIA algorithm to compute best-fit solutions to MFA models. We expect that the fluxomer formulation will provide a more suitable basis for future algorithms that analyze very large scale networks and design optimal isotope labeling experiments.     

Genome-scale screen for DNA methylation-based detection markers for ovarian cancer

Background

The identification of sensitive biomarkers for the detection of ovarian cancer is of high clinical relevance for early detection and/or monitoring of disease recurrence. We developed a systematic multi-step biomarker discovery and verification strategy to identify candidate DNA methylation markers for the blood-based detection of ovarian cancer.

Methodology/Principal Findings

We used the Illumina Infinium platform to analyze the DNA methylation status of 27,578 CpG sites in 41 ovarian tumors. We employed a marker selection strategy that emphasized sensitivity by requiring consistency of methylation across tumors, while achieving specificity by excluding markers with methylation in control leukocyte or serum DNA. Our verification strategy involved testing the ability of identified markers to monitor disease burden in serially collected serum samples from ovarian cancer patients who had undergone surgical tumor resection compared to CA-125 levels.We identified one marker, IFFO1 promoter methylation (IFFO1-M), that is frequently methylated in ovarian tumors and that is rarely detected in the blood of normal controls. When tested in 127 serially collected sera from ovarian cancer patients, IFFO1-M showed post-resection kinetics significantly correlated with serum CA-125 measurements in six out of 16 patients.

Conclusions/Significance

We implemented an effective marker screening and verification strategy, leading to the identification of IFFO1-M as a blood-based candidate marker for sensitive detection of ovarian cancer. Serum levels of IFFO1-M displayed post-resection kinetics consistent with a reflection of disease burden. We anticipate that IFFO1-M and other candidate markers emerging from this marker development pipeline may provide disease detection capabilities that complement existing biomarkers.     

Epigenetic subgroups of esophageal and gastric adenocarcinoma with differential GATA5 DNA methylation associated with clinical and lifestyle factors

Background

Adenocarcinomas located near the gastroesophageal junction have unclear etiology and are difficult to classify. We used DNA methylation analysis to identify subtype-specific markers and new subgroups of gastroesophageal adenocarcinomas, and studied their association with epidemiological risk factors and clinical outcomes.

Methodology/Principal Findings

We used logistic regression models and unsupervised hierarchical cluster analysis of 74 DNA methylation markers on 45 tumor samples (44 patients) of esophageal and gastric adenocarcinomas obtained from a population-based case-control study to uncover epigenetic markers and cluster groups of gastroesophageal adenocarcinomas. No distinct epigenetic differences were evident between subtypes of gastric and esophageal cancers. However, we identified two gastroesophageal adenocarcinoma subclusters based on DNA methylation profiles. Group membership was best predicted by GATA5 DNA methylation status. We analyzed the associations between these two epigenetic groups and exposure using logistic regression, and the associations with survival time using Cox regression in a larger set of 317 tumor samples (278 patients). There were more males with esophageal and gastric cardia cancers in Cluster Group 1 characterized by higher GATA5 DNA methylation values (all p<0.05). This group also showed associations of borderline statistical significance with having ever smoked (p-value = 0.07), high body mass index (p-value = 0.06), and symptoms of gastroesophageal reflux (p-value = 0.07). Subjects in cluster Group 1 showed better survival than those in Group 2 after adjusting for tumor differentiation grade, but this was not found to be independent of tumor stage.

Conclusions/Significance

DNA methylation profiling can be used in population-based studies to identify epigenetic subclasses of gastroesophageal adenocarcinomas and class-specific DNA methylation markers that can be linked to epidemiological data and clinical outcome. Two new epigenetic subgroups of gastroesophageal adenocarcinomas were identified that differ to some extent in their survival rates, risk factors of exposure, and GATA5 DNA methylation.