Neural stem and progenitor cell fate transition requires regulation of Musashi1 function

Background

There is increasing evidence of a pivotal role for regulated mRNA translation in control of developmental cell fate transitions. Physiological and pathological stem and progenitor cell self-renewal is maintained by the mRNA-binding protein, Musashi1 through repression of translation of key mRNAs encoding cell cycle inhibitory proteins. The mechanism by which Musashi1 function is modified to allow translation of these target mRNAs under conditions that require inhibition of cell cycle progression, is unknown.

Results

In this study, we demonstrate that differentiation of primary embryonic rat neural stem/progenitor cells (NSPCs) or human neuroblastoma SH-SY5Y cells results in the rapid phosphorylation of Musashi1 on the evolutionarily conserved site serine 337 (S337). Phosphorylation of this site has been shown to be required for cell cycle control during the maturation of Xenopus oocytes. S337 phosphorylation in mammalian NSPCs and human SH-SY5Y cells correlates with the de-repression and translation of a Musashi reporter mRNA and with accumulation of protein from the endogenous Musashi target mRNA, p21^WAF1/CIP1. Inhibition of Musashi regulatory phosphorylation, through expression of a phospho-inhibitory mutant Musashi1 S337A or over-expression of the wild-type Musashi, blocked differentiation of both NSPCs and SH-SY5Y cells. Musashi1 was similarly phosphorylated in NSPCs and SH-SY5Y cells under conditions of nutrient deprivation-induced cell cycle arrest. Expression of the Musashi1 S337A mutant protein attenuated nutrient deprivation-induced NSPC and SH-SY5Y cell death.

Conclusions

Our data suggest that in response to environmental cues that oppose cell cycle progression, regulation of Musashi function is required to promote target mRNA translation and cell fate transition. Forced modulation of Musashi1 function may present a novel therapeutic strategy to oppose pathological stem cell self-renewal.

     

Anticancer immunotherapy by CTLA-4 blockade: obligatory contribution of IL-2 receptors and negative prognostic impact of soluble CD25

The cytotoxic T lymphocyte antigen-4 (CTLA-4)-blocking antibody ipilimumab induces immune-mediated long-term control of metastatic melanoma in a fraction of patients. Although ipilimumab undoubtedly exerts its therapeutic effects via immunostimulation, thus far clinically useful, immunologically relevant biomarkers that predict treatment efficiency have been elusive. Here, we show that neutralization of IL-2 or blocking the α and β subunits of the IL-2 receptor (CD25 and CD122, respectively) abolished the antitumor effects and the accompanying improvement of the ratio of intratumoral T effector versus regulatory cells (Tregs), which were otherwise induced by CTLA-4 blockade in preclinical mouse models. CTLA-4 blockade led to the reduction of a suppressive CD4⁺ T cell subset expressing Lag3, ICOS, IL-10 and Egr2 with a concomitant rise in IL-2-producing effector cells that lost FoxP3 expression and accumulated in regressing tumors. While recombinant IL-2 improved the therapeutic efficacy of CTLA-4 blockade, the decoy IL-2 receptor α (IL-2Rα, sCD25) inhibited the anticancer effects of CTLA-4 blockade. In 262 metastatic melanoma patients receiving ipilimumab, baseline serum concentrations of sCD25 represented an independent indicator of overall survival, with high levels predicting resistance to therapy. Altogether, these results unravel a role for IL-2 and IL-2 receptors in the anticancer activity of CTLA-4 blockade. Importantly, our study provides the first immunologically relevant biomarker, namely elevated serum sCD25, that predicts resistance to CTLA-4 blockade in patients with melanoma.     

Large carbon release legacy from bark beetle outbreaks across Western United States

Warmer conditions over the past two decades have contributed to rapid expansion of bark beetle outbreaks killing millions of trees over a large fraction of western United States (US) forests. These outbreaks reduce plant productivity by killing trees and transfer carbon from live to dead pools where carbon is slowly emitted to the atmosphere via heterotrophic respiration which subsequently feeds back to climate change. Recent studies have begun to examine the local impacts of bark beetle outbreaks in individual stands, but the full regional carbon consequences remain undocumented for the western US. In this study, we quantify the regional carbon impacts of the bark beetle outbreaks taking place in western US forests. The work relies on a combination of postdisturbance forest regrowth trajectories derived from forest inventory data and a process‐based carbon cycle model tracking decomposition, as well as aerial detection survey (ADS) data documenting the regional extent and severity of recent outbreaks. We find that biomass killed by bark beetle attacks across beetle‐affected areas in western US forests from 2000 to 2009 ranges from 5 to 15 Tg C yr^?1 and caused a reduction of net ecosystem productivity (NEP) of about 6.1–9.3 Tg C y^?1 by 2009. Uncertainties result largely from a lack of detailed surveys of the extent and severity of outbreaks, calling out a need for improved characterization across western US forests. The carbon flux legacy of 2000–2009 outbreaks will continue decades into the future (e.g., 2040–2060) as committed emissions from heterotrophic respiration of beetle‐killed biomass are balanced by forest regrowth and accumulation.     

Live Cell Analysis and Mathematical Modeling Identify Determinants of Attenuation of Dengue Virus 2’-O-Methylation Mutant

Dengue virus (DENV) is the most common mosquito-transmitted virus infecting ~390 million people worldwide. In spite of this high medical relevance, neither a vaccine nor antiviral therapy is currently available. DENV elicits a strong interferon (IFN) response in infected cells, but at the same time actively counteracts IFN production and signaling. Although the kinetics of activation of this innate antiviral defense and the timing of viral counteraction critically determine the magnitude of infection and thus disease, quantitative and kinetic analyses are lacking and it remains poorly understood how DENV spreads in IFN-competent cell systems. To dissect the dynamics of replication versus antiviral defense at the single cell level, we generated a fully viable reporter DENV and host cells with authentic reporters for IFN-stimulated antiviral genes. We find that IFN controls DENV infection in a kinetically determined manner that at the single cell level is highly heterogeneous and stochastic. Even at high-dose, IFN does not fully protect all cells in the culture and, therefore, viral spread occurs even in the face of antiviral protection of naïve cells by IFN. By contrast, a vaccine candidate DENV mutant, which lacks 2’-O-methylation of viral RNA is profoundly attenuated in IFN-competent cells. Through mathematical modeling of time-resolved data and validation experiments we show that the primary determinant for attenuation is the accelerated kinetics of IFN production. This rapid induction triggered by mutant DENV precedes establishment of IFN-resistance in infected cells, thus causing a massive reduction of virus production rate. In contrast, accelerated protection of naïve cells by paracrine IFN action has negligible impact. In conclusion, these results show that attenuation of the 2’-O-methylation DENV mutant is primarily determined by kinetics of autocrine IFN action on infected cells.     

Psychometric properties of implementation measures for public health and community settings and mapping of constructs against the Consolidated Framework for Implementation Research: a systematic review

Background

Recent reviews have synthesised the psychometric properties of measures developed to examine implementation science constructs in healthcare and mental health settings. However, no reviews have focussed primarily on the properties of measures developed to assess innovations in public health and community settings. This review identified quantitative measures developed in public health and community settings, examined their psychometric properties, and described how the domains of each measure align with the five domains and 37 constructs of the Consolidated Framework for Implementation Research (CFIR).

Methods

MEDLINE, PsycINFO, EMBASE, and CINAHL were searched to identify publications describing the development of measures to assess implementation science constructs in public health and community settings. The psychometric properties of each measure were assessed against recommended criteria for validity (face/content, construct, criterion), reliability (internal consistency, test-retest), responsiveness, acceptability, feasibility, and revalidation and cross-cultural adaptation. Relevant domains were mapped against implementation constructs defined by the CFIR.

Results

Fifty-one measures met the inclusion criteria. The majority of these were developed in schools, universities, or colleges and other workplaces or organisations. Overall, most measures did not adequately assess or report psychometric properties. Forty-six percent of measures using exploratory factor analysis reported >50 % of variance was explained by the final model; none of the measures assessed using confirmatory factor analysis reported root mean square error of approximation (<0.06) or comparative fit index (>0.95). Fifty percent of measures reported Cronbach’s alpha of <0.70 for at least one domain; 6 % adequately assessed test-retest reliability; 16 % of measures adequately assessed criterion validity (i.e. known-groups); 2 % adequately assessed convergent validity (r?>?0.40). Twenty-five percent of measures reported revalidation or cross-cultural validation. The CFIR constructs most frequently assessed by the included measures were relative advantage, available resources, knowledge and beliefs, complexity, implementation climate, and other personal resources (assessed by more than ten measures). Five CFIR constructs were not addressed by any measure.

Conclusions

This review highlights gaps in the range of implementation constructs that are assessed by existing measures developed for use in public health and community settings. Moreover, measures with robust psychometric properties are lacking. Without rigorous tools, the factors associated with the successful implementation of innovations in these settings will remain unknown

     

The impact of low-magnitude high-frequency vibration on fracture healing is profoundly influenced by the oestrogen status in mice

Fracture healing is impaired in aged and osteoporotic individuals. Because adequate mechanical stimuli are able to increase bone formation, one therapeutical approach to treat poorly healing fractures could be the application of whole-body vibration, including low-magnitude high-frequency vibration (LMHFV). We investigated the effects of LMHFV on fracture healing in aged osteoporotic mice. Female C57BL/6NCrl mice (n=96) were either ovariectomised (OVX) or sham operated (non-OVX) at age 41 weeks. When aged to 49 weeks, all mice received a femur osteotomy that was stabilised using an external fixator. The mice received whole-body vibrations (20 minutes/day) with 0.3 g peak-to-peak acceleration and a frequency of 45 Hz. After 10 and 21 days, the osteotomised femurs and intact bones (contra-lateral femurs, lumbar spine) were evaluated using bending-testing, micro-computed tomography (μCT), histology and gene expression analyses. LMHFV disturbed fracture healing in aged non-OVX mice, with significantly reduced flexural rigidity (−81%) and bone formation (−80%) in the callus. Gene expression analyses demonstrated increased oestrogen receptor β (ERβ, encoded by Esr2) and Sost expression in the callus of the vibrated animals, but decreased β-catenin, suggesting that ERβ might mediate these negative effects through inhibition of osteoanabolic Wnt/β-catenin signalling. In contrast, in OVX mice, LMHFV significantly improved callus properties, with increased flexural rigidity (+1398%) and bone formation (+637%), which could be abolished by subcutaneous oestrogen application (0.025 mg oestrogen administered in a 90-day-release pellet). On a molecular level, we found an upregulation of ERα in the callus of the vibrated OVX mice, whereas ERβ was unaffected, indicating that ERα might mediate the osteoanabolic response. Our results indicate a major role for oestrogen in the mechanostimulation of fracture healing and imply that LMHFV might only be safe and effective in confined target populations.KEY WORDS: Whole-body vibration, LMHFV, Fracture healing, Oestrogen receptor signalling, Wnt signalling     

Stable-isotope probing and metagenomics reveal predation by protozoa drives E. coli removal in slow sand filters

Stable-isotope probing and metagenomics were applied to study samples taken from laboratory-scale slow sand filters 0.5, 1, 2, 3 and 4 h after challenging with ¹³C-labelled Escherichia coli to determine the mechanisms and organisms responsible for coliform removal. Before spiking, the filters had been continuously operated for 7 weeks using water from the River Kelvin, Glasgow as their influent source. Direct counts and quantitative PCR assays revealed a clear predator–prey response between protozoa and E. coli. The importance of top-down trophic-interactions was confirmed by metagenomic analysis, identifying several protozoan and viral species connected to E. coli attrition, with protozoan grazing responsible for the majority of the removal. In addition to top-down mechanisms, indirect mechanisms, such as algal reactive oxygen species-induced lysis, and mutualistic interactions between algae and fungi, were also associated with coliform removal. The findings significantly further our understanding of the processes and trophic interactions underpinning E. coli removal. This study provides an example for similar studies, and the opportunity to better understand, manage and enhance E. coli removal by allowing the creation of more complex trophic interaction models.     

Is Demography Destiny? Application of Machine Learning Techniques to Accurately Predict Population Health Outcomes from a Minimal Demographic Dataset

For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease.     

Isolation of Highly Active Monoclonal Antibodies against Multiresistant Gram-Positive Bacteria

Multiresistant nosocomial pathogens often cause life-threatening infections that are sometimes untreatable with currently available antibiotics. Staphylococci and enterococci are the predominant Gram-positive species associated with hospital-acquired infections. These infections often lead to extended hospital stay and excess mortality. In this study, a panel of fully human monoclonal antibodies was isolated from a healthy individual by selection of B-cells producing antibodies with high opsonic killing against E. faecalis 12030. Variable domains (VH and VL) of these immunoglobulin genes were amplified by PCR and cloned into an eukaryotic expression vector containing the constant domains of a human IgG1 molecule and the human lambda constant domain. These constructs were transfected into CHO cells and culture supernatants were collected and tested by opsonophagocytic assay against E. faecalis and S. aureus strains (including MRSA). At concentrations of 600 pg/ml, opsonic killing was between 40% and 70% against all strains tested. Monoclonal antibodies were also evaluated in a mouse sepsis model (using S. aureus LAC and E. faecium), a mouse peritonitis model (using S. aureus Newman and LAC) and a rat endocarditis model (using E. faecalis 12030) and were shown to provide protection in all models at a concentration of 4 μg/kg per animal. Here we present a method to produce fully human IgG1 monoclonal antibodies that are opsonic in vitro and protective in vivo against several multiresistant Gram-positive bacteria. The monoclonal antibodies presented in this study are significantly more effective compared to another monoclonal antibody currently in clinical trials.