Pink1 and Parkin regulate Drosophila intestinal stem cell proliferation during stress and aging.

Intestinal stem cells (ISCs) maintain the midgut epithelium in Drosophila melanogaster Proper cellular turnover and tissue function rely on tightly regulated rates of ISC division and appropriate differentiation of daughter cells. However, aging and epithelial injury cause elevated ISC proliferation and decreased capacity for terminal differentiation of daughter enteroblasts (EBs). The mechanisms causing functional decline of stem cells with age remain elusive; however, recent findings suggest that stem cell metabolism plays an important role in the regulation of stem cell activity. Here, we investigate how alterations in mitochondrial homeostasis modulate stem cell behavior in vivo via RNA interference-mediated knockdown of factors involved in mitochondrial dynamics. ISC/EB-specific knockdown of the mitophagy-related genes Pink1 or Parkin suppresses the age-related loss of tissue homeostasis, despite dramatic changes in mitochondrial ultrastructure and mitochondrial damage in ISCs/EBs. Maintenance of tissue homeostasis upon reduction of Pink1 or Parkin appears to result from reduction of age- and stress-induced ISC proliferation, in part, through induction of ISC senescence. Our results indicate an uncoupling of cellular, tissue, and organismal aging through inhibition of ISC proliferation and provide insight into strategies used by stem cells to maintain tissue homeostasis despite severe damage to organelles

Disrupted in Schizophrenia 1 Regulates Neuronal Progenitor Proliferation via Modulation of GSK3β/β-Catenin Signaling

The Disrupted in Schizophrenia 1 (DISC1) gene is disrupted by a balanced chromosomal translocation (1; 11) (q42; q14.3) in a Scottish family with a high incidence of major depression, schizophrenia, and bipolar disorder. Subsequent studies provided indications that DISC1 plays a role in brain development. Here, we demonstrate that suppression of DISC1 expression reduces neural progenitor proliferation, leading to premature cell cycle exit and differentiation. Several lines of evidence suggest that DISC1 mediates this function by regulating GSK3β. First, DISC1 inhibits GSK3β activity through direct physical interaction, which reduces β-catenin phosphorylation and stabilizes β-catenin. Importantly, expression of stabilized β-catenin overrides the impairment of progenitor proliferation caused by DISC1 loss of function. Furthermore, GSK3 inhibitors normalize progenitor proliferation and behavioral defects caused by DISC1 loss of function. Together, these results implicate DISC1 in GSK3β/β-catenin signaling pathways and provide a framework for understanding how alterations in this pathway may contribute to the etiology of psychiatric disorders.National Alliance for Research on Schizophrenia and Depression (U.S.) (Young Investigator Award)Natural Sciences and Engineering Research Council of Canada (Postdoctoral Award)Human Frontier Science Program (Strasbourg, France) (Fellowship)Singleton FellowshipNational Institutes of Health (U.S.) (Grant NS37007

The DEEP Groth Strip Survey VI. Spectroscopic, Variability, and X-ray Detection of AGN

We identify active galactic nuclei (AGN) in the Groth-Westphal Survey Strip (GSS) using the independent and complementary selection techniques of optical spectroscopy and photometric variability. We discuss the X-ray properties of these AGN using Chandra/XMM data for this region. From a sample of 576 galaxies with high quality spectra we identify 31 galaxies with AGN signatures. Seven of these have broad emission lines (Type 1 AGNs). We also identify 26 galaxies displaying nuclear variability in HST WFPC2 images of the GSS separated by ~7 years. The primary overlap of the two selected AGN samples is the set of broad-line AGNs, of which 80% appear as variable. Only a few narrow-line AGNs approach the variability threshold. The broad-line AGNs have an average redshift of z~1.1 while the other spectroscopic AGNs have redshifts closer to the mean of the general galaxy population (z~0.7). Eighty percent of the identified broad-line AGNs are detected in X-rays and these are among the most luminous X-ray sources in the GSS. Only one narrow-line AGN is X-ray detected. Of the variable nuclei galaxies within the X-ray survey, 27% are X-ray detected. We find that 1.9+/-0.6% of GSS galaxies to V=24 are broad-line AGNs, 1.4+/-0.5% are narrow-line AGNs, and 4.5+/-1.4% contain variable nuclei. The fraction of spectroscopically identified BLAGNs and NLAGNs at z~1 reveals a marginally significant increase of 1.3+/-0.9% when compared to the local population.Comment: 29 pages, 8 figures, accepted for publication in ApJ

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos

EXPLICIT: a feasibility study of remote expert elicitation in health technology assessment

This is the final version of the article. Available from BioMed Central via the DOI in this recordBACKGROUND: Expert opinion is often sought to complement available information needed to inform model-based economic evaluations in health technology assessments. In this context, we define expert elicitation as the process of encoding expert opinion on a quantity of interest, together with associated uncertainty, as a probability distribution. When availability for face-to-face expert elicitation with a facilitator is limited, elicitation can be conducted remotely, overcoming challenges of finding an appropriate time to meet the expert and allowing access to experts situated too far away for practical face-to-face sessions. However, distance elicitation is associated with reduced response rates and limited assistance for the expert during the elicitation session. The aim of this study was to inform the development of a remote elicitation tool by exploring the influence of mode of elicitation on elicited beliefs. METHODS: An Excel-based tool (EXPLICIT) was developed to assist the elicitation session, including the preparation of the expert and recording of their responses. General practitioners (GPs) were invited to provide expert opinion about population alcohol consumption behaviours. They were randomised to complete the elicitation by either a face-to-face meeting or email. EXPLICIT was used in the elicitation sessions for both arms. RESULTS: Fifteen GPs completed the elicitation session. Those conducted by email were longer than the face-to-face sessions (13 min 30 s vs 10 min 26 s, p = 0.1) and the email-elicited estimates contained less uncertainty. However, the resulting aggregated distributions were comparable. CONCLUSIONS: EXPLICIT was useful in both facilitating the elicitation task and in obtaining expert opinion from experts via email. The findings support the opinion that remote, self-administered elicitation is a viable approach within the constraints of HTA to inform policy making, although poor response rates may be observed and additional time for individual sessions may be required.This paper presents independent research funded by the National Institute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care (CLAHRC) for the South West Peninsula

A Simple Standard for Sharing Ontological Mappings (SSSOM).

Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

Molecular Characterization of Cryptosporidium Species and Giardia duodenalis from Symptomatic Cambodian Children

Background: In a prospective study, 498 single faecal samples from children aged under 16 years attending an outpatient clinic in the Angkor Hospital for Children, northwest Cambodia, were examined for Cryptosporidium oocysts and Giardia cysts using microscopy and molecular assays. Methodology/Principal Findings: Cryptosporidium oocysts were detected in 2.2% (11/498) of samples using microscopy and in 7.7% (38/498) with molecular tests. Giardia duodenalis cysts were detected in 18.9% (94/498) by microscopy and 27.7% (138/498) by molecular tests; 82% of the positive samples (by either method) were from children aged 1–10 years. Cryptosporidium hominis was the most common species of Cryptosporidium, detected in 13 (34.2%) samples, followed by Cryptosporidium meleagridis in 9 (23.7%), Cryptosporidium parvum in 8 (21.1%), Cryptosporidium canis in 5 (13.2%), and Cryptosporidium suis and Cryptosporidium ubiquitum in one sample each. Cryptosporidium hominis and C. parvum positive samples were subtyped by sequencing the GP60 gene: C. hominis IaA16R6 and C. parvum IIeA7G1 were the most abundant subtypes. Giardia duodenalis was typed using a multiplex real-time PCR targeting assemblages A and B. Assemblage B (106; 76.8% of all Giardia positive samples) was most common followed by A (12.3%) and mixed infections (5.1%). Risk factors associated with Cryptosporidium were malnutrition (AOR 9.63, 95% CI 1.67–55.46), chronic medical diagnoses (AOR 4.51, 95% CI 1.79–11.34) and the presence of birds in the household (AOR 2.99, 95% CI 1.16–7.73); specifically C. hominis (p = 0.03) and C. meleagridis (p<0.001) were associated with the presence of birds. The use of soap was protective against Giardia infection (OR 0.74, 95% CI 0.58–0.95). Conclusions/Significance: This is the first report to describe the different Cryptosporidium species and subtypes and Giardia duodenalis assemblages in Cambodian children. The variety of Cryptosporidium species detected indicates both anthroponotic and zoonotic transmission in this population. Interventions to improve sanitation, increase hand washing after defecation and before preparing food and promote drinking boiled water may reduce the burden of these two parasites

Coupling and cooperativity in voltage activation of a limited-state BK channel gating in saturating Ca2+

Voltage-dependent gating mechanisms of large conductance Ca2+ and voltage-activated (BK) channels were investigated using two-dimensional maximum likelihood analysis of single-channel open and closed intervals. To obtain sufficient data at negative as well as positive voltages, single-channel currents were recorded at saturating Ca2+ from BK channels mutated to remove the RCK1 Ca2+ and Mg2+ sensors. The saturating Ca2+ acting on the Ca2+ bowl sensors of the resulting BKB channels increased channel activity while driving the gating into a reduced number of states, simplifying the model. Five highly constrained idealized gating mechanisms based on extensions of the Monod-Wyman-Changeux model for allosteric proteins were examined. A 10-state model without coupling between the voltage sensors and the opening/closing transitions partially described the voltage dependence of Po but not the single-channel kinetics. With allowed coupling, the model gave improved descriptions of Po and approximated the single-channel kinetics; each activated voltage sensor increased the opening rate approximately an additional 23-fold while having little effect on the closing rate. Allowing cooperativity among voltage sensors further improved the description of the data: each activated voltage sensor increased the activation rate of the remaining voltage sensors approximately fourfold, with little effect on the deactivation rate. The coupling factor was decreased in models with cooperativity from ∼23 to ∼18. Whether the apparent cooperativity among voltage sensors arises from imposing highly idealized models or from actual cooperativity will require additional studies to resolve. For both cooperative and noncooperative models, allowing transitions to five additional brief (flicker) closed states further improved the description of the data. These observations show that the voltage-dependent single-channel kinetics of BKB channels can be approximated by highly idealized allosteric models in which voltage sensor movement increases Po mainly through an increase in channel opening rates, with limited effects on closing rates

Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems.</p> <p>Results</p> <p>We have defined the functional coherence of modules with respect to the Gene Ontology (GO) by considering two complementary aspects: (i) the fragmentation of the GO functional categories into the different modules and (ii) the most representative functions of the modules. We have proposed a set of metrics to evaluate these two aspects and demonstrated their utility in <it>Arabidopsis thaliana</it>. We selected 2355 proteins for which experimentally established protein-protein interaction (PPI) data were available. From these we have constructed five relationship networks, four based on single types of data: PPI, co-expression, co-occurrence of protein names in scientific literature abstracts and sequence similarity and a fifth one combining these four evidence types. The ability of these networks to suggest biologically meaningful grouping of proteins was explored by applying Markov clustering and then by measuring the functional coherence of the clusters.</p> <p>Conclusions</p> <p>Relationship networks integrating multiple evidence-types are biologically informative and allow more proteins to be assigned to a putative functional module. Using additional evidence types concentrates the functional annotations in a smaller number of modules without unduly compromising their consistency. These results indicate that integration of more data sources improves the ability to uncover functional association between proteins, both by allowing more proteins to be linked and producing a network where modular structure more closely reflects the hierarchy in the gene ontology.</p