Author Material: Neuroimaging evidence for a role of neural social stress processing in ethnic minority associated environmental risk

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Different but overlapping populations of Strongyloides stercoralis in dogs and humans-Dogs as a possible source for zoonotic strongyloidiasis

Strongyloidiasis is a much-neglected soil born helminthiasis caused by the nematode Strongyloides stercoralis. Human derived S. stercoralis can be maintained in dogs in the laboratory and this parasite has been reported to also occur in dogs in the wild. Some authors have considered strongyloidiasis a zoonotic disease while others have argued that the two hosts carry host specialized populations of S. stercoralis and that dogs play a minor role, if any, as a reservoir for zoonotic S. stercoralis infections of humans. We isolated S. stercoralis from humans and their dogs in rural villages in northern Cambodia, a region with a high incidence of strongyloidiasis, and compared the worms derived from these two host species using nuclear and mitochondrial DNA sequence polymorphisms. We found that in dogs there exist two populations of S. stercoralis, which are clearly separated from each other genetically based on the nuclear 18S rDNA, the mitochondrial cox1 locus and whole genome sequence. One population, to which the majority of the worms belong, appears to be restricted to dogs. The other population is indistinguishable from the population of S. stercoralis isolated from humans. Consistent with earlier studies, we found multiple sequence variants of the hypervariable region I of the 18 S rDNA in S. stercoralis from humans. However, comparison of mitochondrial sequences and whole genome analysis suggest that these different 18S variants do not represent multiple genetically isolated subpopulations among the worms isolated from humans. We also investigated the mode of reproduction of the free-living generations of laboratory and wild isolates of S. stercoralis. Contrary to earlier literature on S. stercoralis but similar to other species of Strongyloides, we found clear evidence of sexual reproduction. Overall, our results show that dogs carry two populations, possibly different species of Strongyloides. One population appears to be dog specific but the other one is shared with humans. This argues for the strong potential of dogs as reservoirs for zoonotic transmission of S. stercoralis to humans and suggests that in order to reduce the exposure of humans to infective S. stercoralis larvae, dogs should be treated for the infection along with their owners

MicroRNA-Related Polymorphism and Their Association with Fibromyalgia.

MicroRNAs are tissue-specific expressed short RNAs that serve post-transcriptional gene regulation. A specific microRNA can bind to mRNAs of different genes and thereby suppress their protein production. In the context of the complex phenotype of fibromyalgia, we used the Axiom miRNA Target Site Genotyping Array to search genome-wide for DNA variations in microRNA genes, their regulatory regions, and in the 3'UTR of protein-coding genes. To identify disease-relevant DNA polymorphisms, a cohort of 176 female fibromyalgia patients was studied in comparison to a cohort of 162 healthy women. The association between 48,329 markers and fibromyalgia was investigated using logistic regression adjusted for population stratification. Results show that 29 markers had p-values < 1 × 10(-3), and the strongest association was observed for rs758459 (p-value of 0.0001), located in the Neurogenin 1 gene which is targeted by hsa-miR-130a-3p. Furthermore, variant rs2295963 is predicted to affect binding of hsa-miR-1-3p. Both microRNAs were previously reported to be differentially expressed in fibromyalgia patients. Despite its limited statistical power, this study reports two microRNA-related polymorphisms which may play a functional role in the pathogenesis of fibromyalgia. For a better understanding of the disease pattern, further functional analyses on the biological significance of microRNAs and microRNA-related polymorphisms are required

A novel metagenome-derived viral RNA polymerase and its application in a cell-free expression system for metagenome screening

The mining of genomes from non-cultivated microorganisms using metagenomics is a powerful tool to discover novel proteins and other valuable biomolecules. However, function-based metagenome searches are often limited by the time-consuming expression of the active proteins in various heterologous host systems. We here report the initial characterization of novel single-subunit bacteriophage RNA polymerase, EM1 RNAP, identified from a metagenome data set obtained from an elephant dung microbiome. EM1 RNAP and its promoter sequence are distantly related to T7 RNA polymerase. Using EM1 RNAP and a translation-competent Escherichia coli extract, we have developed an efficient medium-throughput pipeline and protocol allowing the expression of metagenome-derived genes and the production of proteins in cell-free system is sufficient for the initial testing of the predicted activities. Here, we have successfully identified and verified 12 enzymes acting on bis(2-hydroxyethyl) terephthalate (BHET) in a completely clone-free approach and proposed an in vitro high-throughput metagenomic screening method

Sex-Specific Interaction Between Cortisol and Striato-Limbic Responses to Psychosocial Stress

Although women and men differ in psychological and endocrine stress responses as well as prevalence rates of stress-related disorders, knowledge on sex differences regarding stress regulation in the brain is scarce.Therefore, we performed an in-depth analysis of data from 67 healthy participants (31 women, taking oral contraceptives), who were exposed to the ScanSTRESS paradigm in an fMRI study. Changes in cortisol, affect, heart rate, and neural activation in response to psychosocial stress were examined in women and men as well as potential sex-specific interactions between stress response domains.Stress exposure led to significant cortisol increases with men exhibiting higher levels than women. Dependent on sex, cortisol elevations were differently associated with stress-related responses in striato-limbic structures: Higher increases were associated with activations in men but with deactivations in women. Regarding affect or heart rate responses, no sex differences emerged.Although women and men differ in their overall stress reactivity, our findings do not support the idea of distinct neural networks as base of this difference. Instead, we found differential stress reactions for women and men in identical structures. We propose considering quantitative predictors like sex-specific cortisol increases when exploring neural response differences of women and men

Impact on birth weight of maternal smoking throughout pregnancy mediated by DNA methylation

Background: Cigarette smoking has severe adverse health consequences in adults and in the offspring of mothers who smoke during pregnancy. One of the most widely reported effects of smoking during pregnancy is reduced birth weight which is in turn associated with chronic disease in adulthood. Epigenome-wide association studies have revealed that smokers show a characteristic “smoking methylation pattern”, and recent authors have proposed that DNA methylation mediates the impact of maternal smoking on birth weight. The aims of the present study were to replicate previous reports that methylation mediates the effect of maternal smoking on birth weight, and for the first time to investigate whether the observed mediation effects are sex-specific in order to account for known sex-specific differences in methylation levels. Methods: Methylation levels in the cord blood of 313 newborns were determined using the Illumina HumanMethylation450K Beadchip. A total of 5,527 CpG sites selected on the basis of evidence from the literature were tested. To determine whether the observed association between maternal smoking and birth weight was attributable to methylation, mediation analyses were performed for significant CpG sites. Separate analyses were then performed in males and females. Results: Following quality control, 282 newborns eventually remained in the analysis. A total of 25 mothers had smoked consistently throughout the pregnancy. The birthweigt of newborns whose mothers had smoked throughout pregnancy was reduced by &gt;200g. After correction for multiple testing, 30 CpGs showed differential methylation in the maternal smoking subgroup including top “smoking methylation pattern” genes AHRR, MYO1G, GFI1, CYP1A1, and CNTNAP2. The effect of maternal smoking on birth weight was partly mediated by the methylation of cg25325512 (PIM1); cg25949550 (CNTNAP2); and cg08699196 (ITGB7). Sex-specific analyses revealed a mediating effect for cg25949550 (CNTNAP2) in male newborns. Conclusion: The present data replicate previous findings that methylation can mediate the effect of maternal smoking on birth weight. The analysis of sex-dependent mediation effects suggests that the sex of the newborn may have an influence. Larger studies are warranted to investigate the role of both the identified differentially methylated loci and the sex of the newborn in mediating the association between maternal smoking during pregnancy and birth weight

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment shows involvement of circadian genes and immune pathways

Therapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic 'clocks' and that SD functions through 'resetting' dysregulated genes; additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. Patients (N = 78) and controls (N = 15) underwent SD, with blood taken at the same time of day before SD, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. Circadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD; in non-responders, little response was observed. Our findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level

The Helmholtz Analytics Toolkit (Heat) and its role in the landscape of massively-parallel scientific Python

When it comes to enhancing exploitation of massive data, machine learning methods are at the forefront of researchers’ awareness. Much less so is the need for, and the complexity of, applying these techniques efficiently across large-scale, memory-distributed data volumes. In fact, these aspects typical for the handling of massive data sets pose major challenges to the vast majority of research communities, in particular to those without a background in high-performance computing. Often, the standard approach involves breaking up and analyzing data in smaller chunks; this can be inefficient and prone to errors, and sometimes it might be inappropriate at all because the context of the overall data set can get lost. The Helmholtz Analytics Toolkit (Heat) library offers a solution to this problem by providing memory-distributed and hardware-accelerated array manipulation, data analytics, and machine learning algorithms in Python. The main objective is to make memory-intensive data analysis possible across various fields of research ---in particular for domain scientists being non-experts in traditional high-performance computing who nevertheless need to tackle data analytics problems going beyond the capabilities of a single workstation. The development of this interdisciplinary, general-purpose, and open-source scientific Python library started in 2018 and is based on collaboration of three institutions (German Aerospace Center DLR, Forschungszentrum Jülich FZJ, Karlsruhe Institute of Technology KIT) of the Helmholtz Association. The pillars of its development are... - ...to enable memory distribution of n-dimensional arrays, - to adopt PyTorch as process-local compute engine (hence supporting GPU-acceleration), - to provide memory-distributed (i.e., multi-node, multi-GPU) array operations and algorithms, optimizing asynchronous MPI-communication (based on mpi4py) under the hood, and - to wrap functionalities in NumPy- or scikit-learn-like API to achieve porting of existing applications with minimal changes and to enable the usage by non-experts in HPC. In this talk we will give an illustrative overview on the current features and capabilities of our library. Moreover, we will discuss its role in the existing ecosystem of distributed computing in Python, and we will address technical and operational challenges in further development