Three-Dimensional Human Bronchial-Tracheal Epithelial Tissue-Like Assemblies (TLAs) as Hosts for Severe Acute Respiratory Syndrome (SARS)-CoV Infection

A three-dimensional (3-D) tissue-like assembly (TLA) of human bronchial-tracheal mesenchymal (HBTC) cells with an overlay of human bronchial epithelial (BEAS-2B) cells was constructed using a NASA Bioreactor to survey the infectivity of SARS-CoV. This TLA was inoculated with a low passage number Urbani strain of SARS-CoV. At selected intervals over a 10-day period, media and cell aliquots of the 3-D TLA were harvested for viral titer assay and for light and electron microscopy examination. All viral titer assays were negative in both BEAS-2B two-dimensional monolayer and TLA. Light microscopy immunohistochemistry demonstrated antigen-antibody reactivity with anti-SARS-CoV polyclonal antibody to spike and nuclear proteins on cell membranes and cytoplasm. Coronavirus Group 2 cross-reactivity was demonstrated by positive reaction to anti-FIPV 1 and anti-FIPV 1 and 2 antibodies. TLA examination by transmission electron microscopy indicated increasing cytoplasmic vacuolation with numerous electron-dense bodies measuring 45 to 270 nm from days 4 through 10. There was no evidence of membrane blebbing, membrane duplication, or fragmentation of organelles in the TLAs. However, progressive disruption of endoplasmic reticulum was observed throughout the cells. Antibody response to SARS-CoV specific spike and nucleocapsid glycoproteins, cross-reactivity with FIPV antibodies, and the cytoplasmic pathology suggests this HBTE TLA model is permissive to SARS-CoV infection

Childhood abuse is associated with methylation of multiple loci in adult DNA

Childhood abuse is associated with increased adult disease risk, suggesting that processes acting over the long-term, such as epigenetic regulation of gene activity, may be involved. DNA methylation is a critical mechanism in epigenetic regulation. We aimed to establish whether childhood abuse was associated with adult DNA methylation profiles

Psychosocial adversity and socioeconomic position during childhood and epigenetic age: analysis of two prospective cohort studies

Psychosocial adversity in childhood (e.g. abuse) and low socioeconomic position (SEP) can have significant lasting effects on social and health outcomes. DNA methylation-based biomarkers are highly correlated with chronological age; departures of methylation-predicted age from chronological age can be used to define a measure of age acceleration, which may represent a potential biological mechanism linking environmental exposures to later health outcomes. Using data from two cohorts of women Avon Longitudinal Study of Parents and Children, (ALSPAC), N = 989 and MRC National Survey of Health and Development, NSHD, N = 773), we assessed associations of SEP, psychosocial adversity in childhood (parental physical or mental illness or death, parental separation, parental absence, sub-optimal maternal bonding, sexual, emotional and physical abuse and neglect) and a cumulative score of these psychosocial adversity measures, with DNA methylation age acceleration in adulthood (measured in peripheral blood at mean chronological ages 29 and 47 in ALSPAC and buccal cells at age 53 in NSHD). Sexual abuse was strongly associated with age acceleration in ALSPAC (sexual abuse data were not available in NSHD), e.g. at the 47-year time point sexual abuse associated with a 3.41 years higher DNA methylation age (95% CI 1.53 to 5.29) after adjusting for childhood and adulthood SEP. No associations were observed between low SEP, any other psychosocial adversity measure or the cumulative psychosocial adversity score and age acceleration. DNA methylation age acceleration is associated with sexual abuse, suggesting a potential mechanism linking sexual abuse with adverse outcomes. Replication studies with larger sample sizes are warranted

Stilbenoids remodel the DNA methylation patterns in breast cancer cells and inhibit oncogenic NOTCH signaling through epigenetic regulation of MAML2 transcriptional activity

DNA hypomethylation was previously implicated in cancer progression and metastasis. The purpose of this study was to examine whether stilbenoids, resveratrol and pterostilbene thought to exert anticancer effects, target genes with oncogenic function for de novo methylation and silencing, leading to inactivation of related signaling pathways. Following Illumina 450K, genome-wide DNA methylation analysis reveals that stilbenoids alter DNA methylation patterns in breast cancer cells. On average, 75% of differentially methylated genes have increased methylation, and these genes are enriched for oncogenic functions, including NOTCH signaling pathway. MAML2, a coactivator of NOTCH targets, is methylated at the enhancer region and transcriptionally silenced in response to stilbenoids, possibly explaining the downregulation of NOTCH target genes. The increased DNA methylation at MAML2 enhancer coincides with increased occupancy of repressive histone marks and decrease in activating marks. This condensed chromatin structure is associated with binding of DNMT3B and decreased occupancy of OCT1 transcription factor at MAML2 enhancer, suggesting a role of DNMT3B in increasing methylation of MAML2 after stilbenoid treatment. Our results deliver a novel insight into epigenetic regulation of oncogenic signals in cancer and provide support for epigenetic-targeting strategies as an effective anticancer approach

Efficient Syntax-Driven Lumping of Differential Equations

We present an algorithm to compute exact aggregations of a class of systems of ordinary differential equations (ODEs). Our approach consists in an extension of Paige and Tarjan’s seminal solution to the coarsest refinement problem by encoding an ODE system into a suitable discrete-state representation. In particular, we consider a simple extension of the syntax of elementary chemical reaction networks because (i) it can express ODEs with derivatives given by polynomials of degree at most two, which are relevant in many applications in natural sciences and engineering; and (ii) we can build on two recently introduced bisimulations, which yield two complementary notions of ODE lumping. Our algorithm computes the largest bisimulations in O(r⋅s⋅logs)O(r⋅s⋅log⁡s) time, where r is the number of monomials and s is the number of variables in the ODEs. Numerical experiments on real-world models from biochemistry, electrical engineering, and structural mechanics show that our prototype is able to handle ODEs with millions of variables and monomials, providing significant model reductions

Prenatal and early life influences on epigenetic age in children:a study of mother-offspring pairs from two cohort studies

DNA methylation-based biomarkers of aging are highly correlated with actual age. Departures of methylation-estimated age from actual age can be used to define epigenetic measures of child development or age acceleration (AA) in adults. Very little is known about genetic or environmental determinants of these epigenetic measures of aging. We obtained DNA methylation profiles using Infinium HumanMethylation450 BeadChips across five time-points in 1018 mother-child pairs from the Avon Longitudinal Study of Parents and Children. Using the Horvath age estimation method, we calculated epigenetic age for these samples. AA was defined as the residuals from regressing epigenetic age on actual age. AA was tested for associations with cross-sectional clinical variables in children. We identified associations between AA and sex, birth weight, birth by caesarean section and several maternal characteristics in pregnancy, namely smoking, weight, BMI, selenium and cholesterol level. Offspring of non-drinkers had higher AA on average but this difference appeared to resolve during childhood. The associations between sex, birth weight and AA found in ARIES were replicated in an independent cohort (GOYA). In children, epigenetic AA measures are associated with several clinically relevant variables, and early life exposures appear to be associated with changes in AA during adolescence. Further research into epigenetic aging, including the use of causal inference methods, is required to better our understanding of aging

Genetic Control of Tissue Specific Growth in the Drosophila Trachea

In most organisms, different tissues and organs grow at different rates relative to each other, suggesting underlying growth mechanisms that act tissue specifically. The mechanisms of tissue specific growth are less well understood than those governing the growth of an entire organism. To gain a better understanding of these tissue specific growth mechanisms, our lab has characterized mutations that specifically alter the growth of the larval trachea in Drosophila melanogaster. Larval trachea growth is well suited for these studies since the trachea shows allometric growth during the larval stages, can be imaged and measured in living animals and gene expression can be specifically altered in the trachea using breathless-GAL4. Importantly, we and others have identified mutations in genes whose mutant phenotypes suggest that they normally regulate tissue-specific growth in the larval trachea. For example, animals with mutations in uninflatable (uif) and Matrix metalloproteinase 1 (Mmp1) have larval tracheae that are roughly half the relative size of those in wild type animals. Here we report the results of a screen of EMS-induced larval lethal mutations that recovered seven different alleles that cause either overgrowth or undergrowth of the larval trachea. Three of these mutations form one complementation group, and we have used complementation mapping and RNA interference to show that the affected gene is CG11340. This gene encodes a glycine gated chloride channel previously thought to function only in neurotransmitters. We have named this gene rio based upon its long and convoluted tracheal phenotype. Here we show its function as a negative growth regulator in the trachea and demonstrate its interaction with the previously characterized positive growth regulators in tracheal specific growth

An integrated network visualization framework towards metabolic engineering applications

Background Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential. Results In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks. Conclusions The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.This work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within project ref. COMPETE FCOMP-01-0124-FEDER-015079 and the FCT Strategic Project PEst-OE/EQB/LA0023/2013. The work of PV is funded by PhD grant ref. SFRH/BDE/51442/2011