Distinct signature of altered homeostasis in aging rod photoreceptors: implications for retinal diseases

Background

Advanced age contributes to clinical manifestations of many retinopathies and represents a major risk factor for age-related macular degeneration, a leading cause of visual impairment and blindness in the elderly. Rod photoreceptors are especially vulnerable to genetic defects and changes in microenvironment, and are among the first neurons to die in normal aging and in many retinal degenerative diseases. The molecular mechanisms underlying rod photoreceptor vulnerability and potential biomarkers of the aging process in this highly specialized cell type are unknown.

Methodology/Principal Findings

To discover aging-associated adaptations that may influence rod function, we have generated gene expression profiles of purified rod photoreceptors from mouse retina at young adult to early stages of aging (1.5, 5, and 12 month old mice). We identified 375 genes that showed differential expression in rods from 5 and 12 month old mouse retina compared to that of 1.5 month old retina. Quantitative RT-PCR experiments validated expression change for a majority of the 25 genes that were examined. Macroanalysis of differentially expressed genes using gene class testing and protein interaction networks revealed overrepresentation of cellular pathways that are potentially photoreceptor-specific (angiogenesis and lipid/retinoid metabolism), in addition to age-related pathways previously described in several tissue types (oxidative phosphorylation, stress and immune response).

Conclusions/Significance

Our study suggests a progressive shift in cellular homeostasis that may underlie aging-associated functional decline in rod photoreceptors and contribute to a more permissive state for pathological processes involved in retinal diseases.     

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).     

Artificial signal peptide prediction by a hidden markov model to improve protein secretion via Lactococcus lactis bacteria

A hidden Markov model (HMM) has been utilized to predict and generate artificial secretory signal peptide sequences. The strength of signal peptides of proteins from different subcellular locations via Lactococcus lactis bacteria correlated with their HMM bit scores in the model. The results show that the HMM bit score +12 are determined as the threshold for discriminating secreteory signal sequences from the others. The model is used to generate artificial signal peptides with different bit scores for secretory proteins. The signal peptide with the maximum bit score strongly directs proteins secretion.     

Interaction of drugs amlodipine and paroxetine with the metabolizing enzyme CYP2B4: a molecular dynamics simulation study

The interactions of the drugs amlodipine and paroxetine, which are prescribed respectively for treatment of hypertension and depression, with the metabolizing enzyme cytochrome CYP2B4 as the drug target, have been studied by molecular dynamics (MD) simulation. Poly ethylene glycol was used to control the drugs’ interactions with each other and with the target CYP2B4. Thirteen simulation systems were carefully designed, and the results obtained from MD simulations indicated that amlodipine in the PEGylated form prescribed with paroxetine in the nonPEGylated form promotes higher cytochrome stability and causes fewer fluctuations as the drugs approach the target CYP2B4 and interact with it. The simulation results led us to hypothesize that the combination of the drugs with a specific drug ratio, as proposed in this work, manifests more effective diffusivity and less instability while metabolizing with enzyme CYP2B4. Also, the active residues in the CYP2B4 enzyme that interact with the drugs were determined by MD simulation, which were consistent with the reported experimental results.

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Graphical Abstract Efficient drug-enzyme interactions, as a result of PEGylation.

     

Graphene Functionalized Scaffolds Reduce the Inflammatory Response and Supports Endogenous Neuroblast Migration when Implanted in the Adult Brain

Electroactive materials have been investigated as next-generation neuronal tissue engineering scaffolds to enhance neuronal regeneration and functional recovery after brain injury. Graphene, an emerging neuronal scaffold material with charge transfer properties, has shown promising results for neuronal cell survival and differentiation in vitro. In this in vivo work, electrospun microfiber scaffolds coated with self-assembled colloidal graphene, were implanted into the striatum or into the subventricular zone of adult rats. Microglia and astrocyte activation levels were suppressed with graphene functionalization. In addition, self-assembled graphene implants prevented glial scarring in the brain 7 weeks following implantation. Astrocyte guidance within the scaffold and redirection of neuroblasts from the subventricular zone along the implants was also demonstrated. These findings provide new functional evidence for the potential use of graphene scaffolds as a therapeutic platform to support central nervous system regeneration.     

Optimizing neuronal differentiation of human pluripotent NT2 stem cells in monolayer cultures

Human pluripotent embryonal carcinoma (NT2) cells are increasingly considered as a suitable model for in vitro developmental toxicity and neurotoxicity (DT/DNT) studies as they undergo neuronal differentiation upon stimulation with retinoic acid (RA) and allow toxicity testing at different stages of maturation. However, differentiation of NT2 cells is not straightforward. There are different protocols available in the literature reporting varying results with regard to differentiation efficiency, expression of neuronal markers and morphological characteristics of differentiated cells. Yet, the efficiency of available protocols has not been systematically compared. To address this question, we quantified the number and size of cell cluster formed during differentiation using published and modified protocols and analyzed the abundance of neuronal and non‐neuronal expression markers using immunocytochemistry. In the course of the experiments we observed that differentiation results strongly depend on the cell density at differentiation‐initiation as well as on the type of used cell culture plastic ware. Based on those observations and the results from our comparative analysis, we created our own optimized and robust protocol that reproducibly reveals differentiated cells with high yield. We conclude that our method may be superior to differentiation of NT2 cells for systematic in vitro‐based primary screening for developmental toxicants and neurotoxicants at different stages of maturation over previous protocols used. Our approach will also contribute to reduce animal testing in the context of the 3Rs.     

Application of Quality by Design (QbD) Approach to Ultrasonic Atomization Spray Coating of Drug-Eluting Stents

The drug coating process for coated drug-eluting stents (DES) has been identified as a key source of inter- and intra-batch variability in drug elution rates. Quality-by-design (QbD) principles were applied to gain an understanding of the ultrasonic spray coating process of DES. Statistically based design of experiments (DOE) were used to understand the relationship between ultrasonic atomization spray coating parameters and dependent variables such as coating mass ratio, roughness, drug solid state composite microstructure, and elution kinetics. Defect-free DES coatings composed of 70% 85:15 poly(dl-lactide-co-glycolide) and 30% everolimus were fabricated with a constant coating mass. The drug elution profile was characterized by a mathematical model describing biphasic release kinetics. Model coefficients were analyzed as a DOE response. Changes in ultrasonic coating processing conditions resulted in substantial changes in roughness and elution kinetics. Based on the outcome from the DOE study, a design space was defined in terms of the critical coating process parameters resulting in optimum coating roughness and drug elution. This QbD methodology can be useful to enhance the quality of coated DES.KEY WORDS: biodegradable polymers, coating, drug-eluting stents, processing, quality by design     

The two mutations of actin–myosin interface and their effect on the dynamics,structures, and functions of skeletal muscle actin

Congenital myopathy is a broad category of muscular diseases with symptoms appearing at the time of birth. One type of congenital myopathy is Congenital Fiber Type Disproportion (CFTD), a severely debilitating disease. The G48D and G48C mutations in the D-loop and the actin–myosin interface are the two causes of CFTD. These mutations have been shown to significantly affect the structure and function of muscle fibers. To the author’s knowledge, the effects of these mutations have not yet been studied. In this work, the power stroke structure of the head domain of myosin and the wild and mutated types of actin were modeled. Then, a MD simulation was run for the modeled structures to study the effects of these mutations on the structure, function, and molecular dynamics of actin. The wild and mutated actins docked with myosin showed differences in hydrogen bonding patterns, free binding energies, and hydrogen bond occupation frequencies. The G48D and G48C mutations significantly impacted the conformation of D-loops because of their larger size compared to Glycine and their ability to interfere with the polarity or hydrophobicity of this neutralized and hydrophobic loop. Therefore, the mutated loops were unable to fit properly into the hydrophobic groove of the adjacent G-actin. The abnormal structure of D-loops seems to result in the abnormal assembly of F-actins, giving rise to the symptoms of CFTD. It was also noted that G48C and G48D did not form hydrogen bonds with myosin in the residue 48 location. Nevertheless, in this case, muscles are unable to contract properly due to muscle atrophy.     

Accuracy of PurePulse photoplethysmography technology of Fitbit Charge 2 for assessment of heart rate during sleep

Elevated asleep heart rate (HR) is a risk factor for cardiovascular disease and other-cause morbidity and mortality. We assessed the accuracy of Fitbit Inc. PurePulse® photoplethysmography with reference to three-lead electrocardiography (ECG) in determining HR during sleep. HR of 35 (17 female) healthy adults 25.1 ± 10.6 years of age (mean ± SD) was continuously recorded throughout a single night of sleep. There was no significant difference in asleep HR mean (0.09 beats per minute [bpm], P = 0.426) between Fitbit photoplethysmography and ECG; plus, there was excellent intraclass correlation (0.998) and narrow Bland–Altman agreement range (2.67 bpm). The regression analysis of Bland–Altman plot of mean asleep HR indicates Fitbit tends to slightly overestimate reference values in the lower range of HR (HR < 50 bpm) by 0.51 bpm and slightly underestimate reference values in the higher range of HR (HR > 80 bpm) by 0.63 bpm. Mixed model analysis of epoch-by-epoch (5-min epochs) asleep HR showed significant “U” shape trend (P < 0.001) in amount of Fitbit error (absolute amount of difference between ECG and Fitbit values regardless of overestimation or underestimation) in regard to HR, i.e. smaller error in the medium range of HR (60–80 bpm) and slightly larger error for lower (<60 bpm) and higher (>80 bpm) ranges of HR. However, effect of age, body mass index, gender, and subjective sleep quality measured by Pittsburgh sleep quality index (good/poor sleepers) on error in estimating HR by the Fitbit method was not significant. It is concluded that Fitbit photoplethysmography suitably tracks HR during sleep in healthy young adults.     

Using “Big Data” to Capture Overall Health Status: Properties and Predictive Value of a Claims-Based Health Risk Score

BackgroundInvestigators across many fields often struggle with how best to capture an individual’s overall health status, with options including both subjective and objective measures. With the increasing availability of “big data,” researchers can now take advantage of novel metrics of health status. These predictive algorithms were initially developed to forecast and manage expenditures, yet they represent an underutilized tool that could contribute significantly to health research. In this paper, we describe the properties and possible applications of one such “health risk score,” the DxCG Intelligence tool.MethodsWe link claims and administrative datasets on a cohort of U.S. workers during the period 1996–2011 (N = 14,161). We examine the risk score’s association with incident diagnoses of five disease conditions, and we link employee data with the National Death Index to characterize its relationship with mortality. We review prior studies documenting the risk score’s association with other health and non-health outcomes, including healthcare utilization, early retirement, and occupational injury.

Results and Conclusions

We find that the risk score is associated with outcomes across a variety of health and non-health domains. These examples demonstrate the broad applicability of this tool in multiple fields of research and illustrate its utility as a measure of overall health status for epidemiologists and other health researchers.