The microRNA-Processing Enzyme Dicer Is Essential for Thyroid Function

Dicer is a type III ribonuclease required for the biogenesis of microRNAs (miRNAs), a class of small non-coding RNAs regulating gene expression at the post-transcriptional level. To explore the functional role of miRNAs in thyroid gland function, we generated a thyrocyte-specific Dicer conditional knockout mouse. Here we show that development and early differentiation of the thyroid gland are not affected by the absence of Dicer, while severe hypothyroidism gradually develops after birth, leading to reduced body weight and shortened life span. Histological and molecular characterization of knockout mice reveals a dramatic loss of the thyroid gland follicular architecture associated with functional aberrations and down-regulation of several differentiation markers. The data presented in this study show for the first time that an intact miRNAs processing machinery is essential for thyroid physiology, suggesting that deregulation of specific miRNAs could be also involved in human thyroid dysfunctions

Intracerebral Transplantation and In Vivo Bioluminescence Tracking of Human Neural Progenitor Cells in the Mouse Brain

Cell therapy has long been an emerging treatment paradigm in experimental neurobiology. However, cell transplantation studies often rely on end-point measurements and can therefore only evaluate longitudinal changes of cell migration and survival to a limited extent. This paper provides a reliable, minimally invasive protocol to transplant and longitudinally track neural progenitor cells (NPCs) in the adult mouse brain. Before transplantation, cells are transduced with a lentiviral vector comprising a bioluminescent (firefly-luciferase) and fluorescent (green fluorescent protein [GFP]) reporter. The NPCs are transplanted into the right cortical hemisphere using stereotaxic injections in the sensorimotor cortex. Following transplantation, grafted cells were detected through the intact skull for up to five weeks (at days 0, 3, 14, 21, 35) with a resolution limit of 6,000 cells using in vivo bioluminescence imaging. Subsequently, the transplanted cells are identified in histological brain sections and further characterized with immunofluorescence. Thus, this protocol provides a valuable tool to transplant, track, quantify, and characterize cells in the mouse brain

Variegated silencing through epigenetic modifications of a large Xq region in a case of balanced X;2 translocation with Incontinentia Pigmenti-like phenotype

Molecular mechanisms underlying aberrant phenotypes in balanced X;autosome translocations are scarcely understood. We report the case of a de novo reciprocal balanced translocation X;2(q23;q33) presenting phenotypic alterations highly suggestive of Incontinentia Pigmenti (IP) syndrome, a genodermatosis with abnormal skin pigmentation and neurological failure, segregating as X-linked dominant disorder. Through molecular studies, we demonstrated that the altered phenotype could not be ascribed to chromosome microdeletions or to XIST-mediated inactivation of Xq24-qter. Interestingly, we found that the Xq24-qter region, which translocated downstream of the heterochromatic band 2q34, undergoes epigenetic silencing mediated by DNA methylation and histone alterations. Among the downregulated genes, we found the inhibitor of kappa light polypeptide gene enhancer in B cells, kinase gamma (IKBKG/NEMO), the causative gene of IP. We hypothesize that a mosaic functional nullisomy of the translocated genes, through a Position Effect Variegation-like heterochromatization, might be responsible for the proband's phenotypic anomalies. Partial silencing of IKBKG may be responsible for the skin anomalies observed, thereby mimicking the IP pathological condition. In addition to its clinical relevance, this paper addresses fundamental issues related to the chromatin status and nuclear localization of a human euchromatic region translocated proximally to heterochromatin. In conclusion, the study provides new insight into long-range gene silencing mechanisms and their direct impact in human disease

Xeno-free induced pluripotent stem cell-derived neural progenitor cells for in vivo applications

BACKGROUND: Currently, there is no regenerative therapy for patients with neurological and neurodegenerative disorders. Cell-therapies have emerged as a potential treatment for numerous brain diseases. Despite recent advances in stem cell technology, major concerns have been raised regarding the feasibility and safety of cell therapies for clinical applications. METHODS: We generated good manufacturing practice (GMP)-compatible neural progenitor cells (NPCs) from transgene- and xeno-free induced pluripotent stem cells (iPSCs) that can be smoothly adapted for clinical applications. NPCs were characterized in vitro for their differentiation potential and in vivo after transplantation into wild type as well as genetically immunosuppressed mice. RESULTS: Generated NPCs had a stable gene-expression over at least 15 passages and could be scaled for up to 10$^{18}$ cells per initially seeded 10$^{6}$ cells. After withdrawal of growth factors in vitro, cells adapted a neural fate and mainly differentiated into active neurons. To ensure a pure NPC population for in vivo applications, we reduced the risk of iPSC contamination by applying micro RNA-switch technology as a safety checkpoint. Using lentiviral transduction with a fluorescent and bioluminescent dual-reporter construct, combined with non-invasive in vivo bioluminescent imaging, we longitudinally tracked the grafted cells in healthy wild-type and genetically immunosuppressed mice as well as in a mouse model of ischemic stroke. Long term in-depth characterization revealed that transplanted NPCs have the capability to survive and spontaneously differentiate into functional and mature neurons throughout a time course of a month, while no residual pluripotent cells were detectable. CONCLUSION: We describe the generation of transgene- and xeno-free NPCs. This simple differentiation protocol combined with the ability of in vivo cell tracking presents a valuable tool to develop safe and effective cell therapies for various brain injuries

Visualizing alpha-synuclein and iron deposition in M83 mouse model of Parkinson's disease in vivo

BACKGROUND Abnormal alpha-synuclein and iron accumulation in the brain play an important role in Parkinson's disease (PD). Herein, we aim at visualizing alpha-synuclein inclusions and iron deposition in the brains of M83 (A53T) mouse models of PD in vivo . METHODS Fluorescently labelled pyrimidoindole-derivative THK-565 was characterized by using recombinant fibrils and brains from 10-11 months old M83 mice, which subsequently underwent in vivo concurrent wide-field fluorescence and volumetric multispectral optoacoustic tomography (vMSOT) imaging. The in vivo results were verified against structural and susceptibility weighted imaging (SWI) magnetic resonance imaging (MRI) at 9.4 Tesla and scanning transmission X-ray microscopy (STXM) of perfused brains. Brain slice immunofluorescence and Prussian blue staining were further performed to validate the detection of alpha-synuclein inclusions and iron deposition in the brain, respectively. RESULTS THK-565 showed increased fluorescence upon binding to recombinant alpha-synuclein fibrils and alpha-synuclein inclusions in post-mortem brain slices from patients with Parkinson's disease and M83 mice. i.v. administration of THK-565 in M83 mice showed higher cerebral retention at 20 and 40 minutes post-injection by wide-field fluorescence compared to non-transgenic littermate mice, in congruence with the vMSOT findings. SWI/phase images and Prussian blue indicated the accumulation of iron deposits in the brains of M83 mice, presumably in the Fe $^{3+}$ form, as evinced by the STXM results. CONCLUSION We demonstrated in vivo mapping of alpha-synuclein by means of non-invasive epifluorescence and vMSOT imaging assisted with a targeted THK-565 label and SWI/STXM identification of iron deposits in M83 mouse brains ex vivo

Candidate gene prioritization by network analysis of differential expression using machine learning approaches

<p>Abstract</p> <p>Background</p> <p>Discovering novel disease genes is still challenging for diseases for which no prior knowledge - such as known disease genes or disease-related pathways - is available. Performing genetic studies frequently results in large lists of candidate genes of which only few can be followed up for further investigation. We have recently developed a computational method for constitutional genetic disorders that identifies the most promising candidate genes by replacing prior knowledge by experimental data of differential gene expression between affected and healthy individuals.</p> <p>To improve the performance of our prioritization strategy, we have extended our previous work by applying different machine learning approaches that identify promising candidate genes by determining whether a gene is surrounded by highly differentially expressed genes in a functional association or protein-protein interaction network.</p> <p>Results</p> <p>We have proposed three strategies scoring disease candidate genes relying on network-based machine learning approaches, such as kernel ridge regression, heat kernel, and Arnoldi kernel approximation. For comparison purposes, a local measure based on the expression of the direct neighbors is also computed. We have benchmarked these strategies on 40 publicly available knockout experiments in mice, and performance was assessed against results obtained using a standard procedure in genetics that ranks candidate genes based solely on their differential expression levels (<it>Simple Expression Ranking</it>). Our results showed that our four strategies could outperform this standard procedure and that the best results were obtained using the <it>Heat Kernel Diffusion Ranking </it>leading to an average ranking position of 8 out of 100 genes, an AUC value of 92.3% and an error reduction of 52.8% relative to the standard procedure approach which ranked the knockout gene on average at position 17 with an AUC value of 83.7%.</p> <p>Conclusion</p> <p>In this study we could identify promising candidate genes using network based machine learning approaches even if no knowledge is available about the disease or phenotype.</p

Network Analysis of Differential Expression for the Identification of Disease-Causing Genes

Genetic studies (in particular linkage and association studies) identify chromosomal regions involved in a disease or phenotype of interest, but those regions often contain many candidate genes, only a few of which can be followed-up for biological validation. Recently, computational methods to identify (prioritize) the most promising candidates within a region have been proposed, but they are usually not applicable to cases where little is known about the phenotype (no or few confirmed disease genes, fragmentary understanding of the biological cascades involved). We seek to overcome this limitation by replacing knowledge about the biological process by experimental data on differential gene expression between affected and healthy individuals. Considering the problem from the perspective of a gene/protein network, we assess a candidate gene by considering the level of differential expression in its neighborhood under the assumption that strong candidates will tend to be surrounded by differentially expressed neighbors. We define a notion of soft neighborhood where each gene is given a contributing weight, which decreases with the distance from the candidate gene on the protein network. To account for multiple paths between genes, we define the distance using the Laplacian exponential diffusion kernel. We score candidates by aggregating the differential expression of neighbors weighted as a function of distance. Through a randomization procedure, we rank candidates by p-values. We illustrate our approach on four monogenic diseases and successfully prioritize the known disease causing genes

Comparative epidemiologic characteristics of pertussis in 10 Central and Eastern European countries, 2000-2013

Publisher Copyright: © 2016 Heininger et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.We undertook an epidemiological survey of the annual incidence of pertussis reported from 2000 to 2013 in ten Central and Eastern European countries to ascertain whether increased pertussis reports in some countries share common underlying drivers or whether there are specific features in each country. The annual incidence of pertussis in the participating countries was obtained from relevant government institutions and/or national surveillance systems. We reviewed the changes in the pertussis incidence rates in each country to explore differences and/or similarities between countries in relation to pertussis surveillance; case definitions for detection and confirmation of pertussis; incidence and number of cases of pertussis by year, overall and by age group; population by year, overall and by age group; pertussis immunization schedule and coverage, and switch from whole-cell pertussis vaccines (wP) to acellular pertussis vaccines (aP). There was heterogeneity in the reported annual incidence rates and trends observed across countries. Reported pertussis incidence rates varied considerably, ranging from 0.01 to 96 per 100,000 population, with the highest rates generally reported in Estonia and the lowest in Hungary and Serbia. The greatest burden appears for the most part in infants (<1 year) in Bulgaria, Hungary, Latvia, Romania, and Serbia, but not in the other participating countries where the burden may have shifted to older children, though surveillance of adults may be inappropriate. There was no consistent pattern associated with the switch from wP to aP vaccines on reported pertussis incidence rates. The heterogeneity in reported data may be related to a number of factors including surveillance system characteristics or capabilities, different case definitions, type of pertussis confirmation tests used, public awareness of the disease, as well as real differences in the magnitude of the disease, or a combination of these factors. Our study highlights the need to standardize pertussis detection and confirmation in surveillance programs across Europe, complemented with carefully-designed seroprevalence studies using the same protocols and methodologies.publishersversionPeer reviewe