Absence of the KhpA and KhpB (JAG/EloR) RNA-Binding Proteins Suppresses the Requirement for PBP2b by Overproduction of FtsA in Streptococcus pneumoniae D39

Suppressor mutations were isolated that obviate the requirement for essential PBP2b in peripheral elongation of peptidoglycan from the midcells of dividing Streptococcus pneumoniae D39 background cells. One suppressor was in a gene encoding a single KH-domain protein (KhpA). ΔkhpA suppresses deletions in most, but not all (mltG), genes involved in peripheral PG synthesis and in the gpsB regulatory gene. ΔkhpA mutations reduce growth rate, decrease cell size, minimally affect shape, and induce expression of the WalRK cell-wall stress regulon. Reciprocal co-immunoprecipitations show that KhpA forms a complex in cells with another KH-domain protein (KhpB/JAG/EloR). ΔkhpA and ΔkhpB mutants phenocopy each other exactly, consistent with a direct interaction. RNA-immunoprecipitation showed that KhpA/KhpB bind an overlapping set of RNAs in cells. Phosphorylation of KhpB reported previously does not affect KhpB function in the D39 progenitor background. A chromosome duplication implicated FtsA overproduction in Δpbp2b suppression. We show that cellular FtsA concentration is negatively regulated by KhpA/B at the post-transcriptional level and that FtsA overproduction is necessary and sufficient for suppression of Δpbp2b. However, increased FtsA only partially accounts for the phenotypes of ΔkhpA mutants. Together, these results suggest that multimeric KhpA/B may function as a pleiotropic RNA chaperone controlling pneumococcal cell division

Optimism and Risk of Incident Hypertension: A Target for Primordial Prevention

Aims Optimism is associated with reduced cardiovascular disease risk; however, few prospective studies have considered optimism in relation to hypertension risk specifically. We investigated whether optimism was associated with a lower risk of developing hypertension in U.S. service members, who are more likely to develop high blood pressure early in life. We also evaluated race/ethnicity, sex and age as potential effect modifiers of these associations. Methods Participants were 103 486 hypertension-free U.S. Army active-duty soldiers (mean age 28.96 years, 61.76% White, 20.04% Black, 11.01% Hispanic, 4.09% Asian, and 3.10% others). We assessed optimism, sociodemographic characteristics, health conditions, health behaviours and depression status at baseline (2009–2010) via self-report and administrative records, and ascertained incident hypertension over follow-up (2010–2014) from electronic health records and health assessments. We used Cox proportional hazards regression models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), and adjusted models for a broad range of relevant covariates. Results Over a mean follow-up of 3.51 years, 15 052 incident hypertension cases occurred. The highest v. lowest optimism levels were associated with a 22% reduced risk of developing hypertension, after adjusting for all covariates including baseline blood pressure (HR = 0.78; 95% CI = 0.74–0.83). The difference in hypertension risk between the highest v. lowest optimism was also maintained when we excluded soldiers with hypertension in the first two years of follow-up and, separately, when we excluded soldiers with prehypertension at baseline. A dose–response relationship was evident with higher optimism associated with a lower relative risk (p \u3c 0.001). Higher optimism was consistently associated with a lower risk of developing hypertension across sex, age and most race/ethnicity categories. Conclusions In a diverse cohort of initially healthy male and female service members particularly vulnerable to developing hypertension, higher optimism levels were associated with reduced hypertension risk independently of sociodemographic and health factors, a particularly notable finding given the young and healthy population. Results suggest optimism is a health asset and a potential target for public health interventions

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Critical Role of PI3K/Akt/GSK3β in Motoneuron Specification from Human Neural Stem Cells in Response to FGF2 and EGF

Fibroblast growth factor (FGF) and epidermal growth factor (EGF) are critical for the development of the nervous system. We previously discovered that FGF2 and EGF had opposite effects on motor neuron differentiation from human fetal neural stem cells (hNSCs), but the underlying mechanisms remain unclear. Here, we show that FGF2 and EGF differentially affect the temporal patterns of Akt and glycogen synthase kinase 3 beta (GSK3β) activation. High levels of phosphatidylinositol 3-kinase (PI3K)/Akt activation accompanied with GSK3β inactivation result in reduction of the motor neuron transcription factor HB9. Inhibition of PI3K/Akt by chemical inhibitors or RNA interference or overexpression of a constitutively active form of GSK3β enhances HB9 expression. Consequently, PI3K inhibition increases hNSCs differentiation into HB9+/microtubule-associated protein 2 (MAP2)+ motor neurons in vitro. More importantly, blocking PI3K not only enhances motor neuron differentiation from hNSCs grafted into the ventral horn of adult rat spinal cords, but also permits ectopic generation of motor neurons in the dorsal horn by overriding environmental influences. Our data suggest that FGF2 and EGF affect the motor neuron fate decision in hNSCs differently through a fine tuning of the PI3K/AKT/GSK3β pathway, and that manipulation of this pathway can enhance motor neuron generation

ENIGMA-Sleep:Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine

Histone Deacetylase Inhibitor Romidepsin Induces HIV Expression in CD4 T Cells from Patients on Suppressive Antiretroviral Therapy at Concentrations Achieved by Clinical Dosing

Persistent latent reservoir of replication-competent proviruses in memory CD4 T cells is a major obstacle to curing HIV infection. Pharmacological activation of HIV expression in latently infected cells is being explored as one of the strategies to deplete the latent HIV reservoir. In this study, we characterized the ability of romidepsin (RMD), a histone deacetylase inhibitor approved for the treatment of T-cell lymphomas, to activate the expression of latent HIV. In an in vitro T-cell model of HIV latency, RMD was the most potent inducer of HIV (EC50 = 4.5 nM) compared with vorinostat (VOR; EC50 = 3,950 nM) and other histone deacetylase (HDAC) inhibitors in clinical development including panobinostat (PNB; EC50 = 10 nM). The HIV induction potencies of RMD, VOR, and PNB paralleled their inhibitory activities against multiple human HDAC isoenzymes. In both resting and memory CD4 T cells isolated from HIV-infected patients on suppressive combination antiretroviral therapy (cART), a 4-hour exposure to 40 nM RMD induced a mean 6-fold increase in intracellular HIV RNA levels, whereas a 24-hour treatment with 1 μM VOR resulted in 2- to 3-fold increases. RMD-induced intracellular HIV RNA expression persisted for 48 hours and correlated with sustained inhibition of cell-associated HDAC activity. By comparison, the induction of HIV RNA by VOR and PNB was transient and diminished after 24 hours. RMD also increased levels of extracellular HIV RNA and virions from both memory and resting CD4 T-cell cultures. The activation of HIV expression was observed at RMD concentrations below the drug plasma levels achieved by doses used in patients treated for T-cell lymphomas. In conclusion, RMD induces HIV expression ex vivo at concentrations that can be achieved clinically, indicating that the drug may reactivate latent HIV in patients on suppressive cART

SOX9 Governs Differentiation Stage-Specific Gene Expression in Growth Plate Chondrocytes via Direct Concomitant Transactivation and Repression

Cartilage and endochondral bone development require SOX9 activity to regulate chondrogenesis, chondrocyte proliferation, and transition to a non-mitotic hypertrophic state. The restricted and reciprocal expression of the collagen X gene, Col10a1, in hypertrophic chondrocytes and Sox9 in immature chondrocytes epitomise the precise spatiotemporal control of gene expression as chondrocytes progress through phases of differentiation, but how this is achieved is not clear. Here, we have identified a regulatory element upstream of Col10a1 that enhances its expression in hypertrophic chondrocytes in vivo. In immature chondrocytes, where Col10a1 is not expressed, SOX9 interacts with a conserved sequence within this element that is analogous to that within the intronic enhancer of the collagen II gene Col2a1, the known transactivation target of SOX9. By analysing a series of Col10a1 reporter genes in transgenic mice, we show that the SOX9 binding consensus in this element is required to repress expression of the transgene in non-hypertrophic chondrocytes. Forced ectopic Sox9 expression in hypertrophic chondrocytes in vitro and in mice resulted in down-regulation of Col10a1. Mutation of a binding consensus motif for GLI transcription factors, which are the effectors of Indian hedgehog signaling, close to the SOX9 site in the Col10a1 regulatory element, also derepressed transgene expression in non-hypertrophic chondrocytes. GLI2 and GLI3 bound to the Col10a1 regulatory element but not to the enhancer of Col2a1. In addition to Col10a1, paired SOX9–GLI binding motifs are present in the conserved non-coding regions of several genes that are preferentially expressed in hypertrophic chondrocytes and the occurrence of pairing is unlikely to be by chance. We propose a regulatory paradigm whereby direct concomitant positive and negative transcriptional control by SOX9 ensures differentiation phase-specific gene expression in chondrocytes. Discrimination between these opposing modes of transcriptional control by SOX9 may be mediated by cooperation with different partners such as GLI factors

DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits