A UV-induced, Mg(2+)-dependent crosslink traps an active form of domain 3 of a self-splicing group II intron.

In vitro irradiation of a15 gamma group II intron RNA with low doses of 254 nm UV light induces a single major crosslink. This crosslink was mapped within the domain 3 substructure of this RNA and one of the participating nucleotides was identified. When an RNA containing only the domain 3 substructure is irradiated under the same conditions, an intramolecular crosslink forms between two specific pyrimidines, one of them identical to the nucleotide crosslinked in the full-length intron RNA. In both RNAs, the crosslink is magnesium ion-dependent and photoreversible. A trans assay for domain 3 function was developed and used to find that the crosslinked domain 3 RNA remains highly reactive. This suggests that crosslinking has trapped a functional, Mg(2+)-induced folded state of this group II intron substructure and that this folding is probably independent of the other domains of the intron.     

Biogeography of the ecosystems of the healthy human body

Background

Characterizing the biogeography of the microbiome of healthy humans is essential for understanding microbial associated diseases. Previous studies mainly focused on a single body habitat from a limited set of subjects. Here, we analyzed one of the largest microbiome datasets to date and generated a biogeographical map that annotates the biodiversity, spatial relationships, and temporal stability of 22 habitats from 279 healthy humans.

Results

We identified 929 genera from more than 24 million 16S rRNA gene sequences of 22 habitats, and we provide a baseline of inter-subject variation for healthy adults. The oral habitat has the most stable microbiota with the highest alpha diversity, while the skin and vaginal microbiota are less stable and show lower alpha diversity. The level of biodiversity in one habitat is independent of the biodiversity of other habitats in the same individual. The abundances of a given genus at a body site in which it dominates do not correlate with the abundances at body sites where it is not dominant. Additionally, we observed the human microbiota exhibit both cosmopolitan and endemic features. Finally, comparing datasets of different projects revealed a project-based clustering pattern, emphasizing the significance of standardization of metagenomic studies.

Conclusions

The data presented here extend the definition of the human microbiome by providing a more complete and accurate picture of human microbiome biogeography, addressing questions best answered by a large dataset of subjects and body sites that are deeply sampled by sequencing.     

Isotopic Analysis of some Romanian Wines by 2H NMR and IRMS

Isotopic analyses are now official or standard methods in Europe and North America for routine use in testing the authenticity of several food products. These methods are based on the measurement of stable isotope content (²H, ¹³C, ¹⁸O) of the product or of a specific component such as an ingredient or target molecule of the product. The determinations carried out using nuclear magnetic resonance (NMR), and Isotopic Ratio Mass Spectrometry (IRMS), provide information on the botanical and geographical origin of the food product. A deuterium natural abundance quantitative NMR method (SNIF-NMR: Site-specific Natural Isotope Fractionation) was developed as an efficient and powerful tool capable of characterizing the chemical origins of organic molecules and distinguishing their biological and geographical origin. The SNIF method is based on the measurement of deuterium / hydrogen (D/H) ratios at the specific sites of the ethanol. Using these methods, we present the obtained results for a series of Romanian wines. Our results may be used like reference data set for authenticity and origin control of wines.     

The Light Skin Allele of SLC24A5 in South Asians and Europeans Shares Identity by Descent

Skin pigmentation is one of the most variable phenotypic traits in humans. A non-synonymous substitution (rs1426654) in the third exon of SLC24A5 accounts for lighter skin in Europeans but not in East Asians. A previous genome-wide association study carried out in a heterogeneous sample of UK immigrants of South Asian descent suggested that this gene also contributes significantly to skin pigmentation variation among South Asians. In the present study, we have quantitatively assessed skin pigmentation for a largely homogeneous cohort of 1228 individuals from the Southern region of the Indian subcontinent. Our data confirm significant association of rs1426654 SNP with skin pigmentation, explaining about 27% of total phenotypic variation in the cohort studied. Our extensive survey of the polymorphism in 1573 individuals from 54 ethnic populations across the Indian subcontinent reveals wide presence of the derived-A allele, although the frequencies vary substantially among populations. We also show that the geospatial pattern of this allele is complex, but most importantly, reflects strong influence of language, geography and demographic history of the populations. Sequencing 11.74 kb of SLC24A5 in 95 individuals worldwide reveals that the rs1426654-A alleles in South Asian and West Eurasian populations are monophyletic and occur on the background of a common haplotype that is characterized by low genetic diversity. We date the coalescence of the light skin associated allele at 22–28 KYA. Both our sequence and genome-wide genotype data confirm that this gene has been a target for positive selection among Europeans. However, the latter also shows additional evidence of selection in populations of the Middle East, Central Asia, Pakistan and North India but not in South India.     

Divergent roles of HDAC1 and HDAC2 in the regulation of epidermal development and tumorigenesis

The histone deacetylases HDAC1 and HDAC2 remove acetyl moieties from lysine residues of histones and other proteins and are important regulators of gene expression. By deleting different combinations of Hdac1 and Hdac2 alleles in the epidermis, we reveal a dosage‐dependent effect of HDAC1/HDAC2 activity on epidermal proliferation and differentiation. Conditional ablation of either HDAC1 or HDAC2 in the epidermis leads to no obvious phenotype due to compensation by the upregulated paralogue. Strikingly, deletion of a single Hdac2 allele in HDAC1 knockout mice results in severe epidermal defects, including alopecia, hyperkeratosis, hyperproliferation and spontaneous tumour formation. These mice display impaired Sin3A co‐repressor complex function, increased levels of c‐Myc protein, p53 expression and apoptosis in hair follicles (HFs) and misregulation of HF bulge stem cells. Surprisingly, ablation of HDAC1 but not HDAC2 in a skin tumour model leads to accelerated tumour development. Our data reveal a crucial function of HDAC1/HDAC2 in the control of lineage specificity and a novel role of HDAC1 as a tumour suppressor in the epidermis.     

Multiple Single-Cell Genomes Provide Insight into Functions of Uncultured Deltaproteobacteria in the Human Oral Cavity

Despite a long history of investigation, many bacteria associated with the human oral cavity have yet to be cultured. Studies that correlate the presence or abundance of uncultured species with oral health or disease highlight the importance of these community members. Thus, we sequenced several single-cell genomic amplicons from Desulfobulbus and Desulfovibrio (class Deltaproteobacteria) to better understand their function within the human oral community and their association with periodontitis, as well as other systemic diseases. Genomic data from oral Desulfobulbus and Desulfovibrio species were compared to other available deltaproteobacterial genomes, including from a subset of host-associated species. While both groups share a large number of genes with other environmental Deltaproteobacteria genomes, they encode a wide array of unique genes that appear to function in survival in a host environment. Many of these genes are similar to virulence and host adaptation factors of known human pathogens, suggesting that the oral Deltaproteobacteria have the potential to play a role in the etiology of periodontal disease.     

Pre-Osteoblasts Stimulate Migration of Breast Cancer Cells via the HGF/MET Pathway

Introduction

The occurrence of skeletal metastases in cancer, e.g. breast cancer (BC), deteriorates patient life expectancy and quality-of-life. Current treatment options against tumor-associated bone disease are limited to anti-resorptive therapies and aimed towards palliation. There remains a lack of therapeutic approaches, which reverse or even prevent the development of bone metastases. Recent studies demonstrate that not only osteoclasts (OCs), but also osteoblasts (OBs) play a central role in the pathogenesis of skeletal metastases, partly by producing hepatocyte growth factor (HGF), which promotes tumor cell migration and seeding into the bone. OBs consist of a heterogeneous cell pool with respect to their maturation stage and function. Recent studies highlight the critical role of pre-OBs in hematopoiesis. Whether the development of bone metastases can be attributed to a particular OB maturation stage is currently unknown.

Methods and Results

Pre-OBs were generated from healthy donor (HD)-derived bone marrow stromal cells (BMSC) as well as the BMSC line KM105 and defined as ALP^low OPN^low RUNX2^high OSX ^high CD166^high. Conditioned media (CM) of pre-OBs, but not of undifferentiated cells or mature OBs, enhanced migration of metastatic BC cells. Importantly, HGF mRNA was significantly up-regulated in pre-OBs versus mature OBs, and CM of pre-OBs activated the MET signaling pathway. Highlighting a key role for HGF, CM from HGF-negative pre-OBs derived from the BMSC line HS27A did not support migration of BC cells. Genetically (siMET) or pharmacologically (INCB28060) targeting MET inhibited both HGF- and pre-OB CM- mediated BC cell migration.

Conclusions

Our data demonstrate for the first time a role for pre-OBs in mediating HGF/MET- dependent migration of BC cells and strongly support the clinical evaluation of INCB28060 and other MET inhibitors to limit and/or prevent BC-associated bone metastases.     

Precise periodic components estimation for chronobiological signals through Bayesian Inference with sparsity enforcing prior

The toxicity and efficacy of more than 30 anticancer agents present very high variations, depending on the dosing time. Therefore, the biologists studying the circadian rhythm require a very precise method for estimating the periodic component (PC) vector of chronobiological signals. Moreover, in recent developments, not only the dominant period or the PC vector present a crucial interest but also their stability or variability. In cancer treatment experiments, the recorded signals corresponding to different phases of treatment are short, from 7 days for the synchronization segment to 2 or 3 days for the after-treatment segment. When studying the stability of the dominant period, we have to consider very short length signals relative to the prior knowledge of the dominant period, placed in the circadian domain. The classical approaches, based on Fourier transform (FT) methods are inefficient (i.e., lack of precision) considering the particularities of the data (i.e., the short length). Another particularity of the signals considered in such experiments is the level of noise: such signals are very noisy and establishing the periodic components that are associated with the biological phenomena and distinguishing them from the ones associated with the noise are difficult tasks. In this paper, we propose a new method for the estimation of the PC vector of biomedical signals, using the biological prior informations and considering a model that accounts for the noise. The experiments developed in cancer treatment context are recording signals expressing a limited number of periods. This is a prior information that can be translated as the sparsity of the PC vector. The proposed method considers the PC vector estimation as an Inverse Problem (IP) using the general Bayesian inference in order to infer the unknown of our model, i.e. the PC vector but also the hyperparameters (i.e the variances). The sparsity prior information is modeled using a sparsity enforcing prior law. In this paper, we propose a Student’s t distribution, viewed as the marginal distribution of a bivariate normal-inverse gamma distribution. We build a general infinite Gaussian scale mixture (IGSM) hierarchical model where we assign prior distributions also for the hyperparameters. The expression of the joint posterior law of the unknown PC vector and hyperparameters is obtained via Bayes rule, and then, the unknowns are estimated via joint maximum a posteriori (JMAP) or posterior mean (PM). For the PM estimator, the expression of the posterior distribution is approximated by a separable one, via variational Bayesian approximation (VBA), using the Kullback-Leibler (KL) divergence. For the PM estimation, two possibilities are considered: an approximation with a partially separable distribution and an approximation with a fully separable one. Both resulting algorithms corresponding to the PM estimation and the one corresponding to the JMAP estimation are iterative algorithms. The algorithms are presented in detail and are compared with the ones corresponding to the Gaussian model. We examine the convergency of the algorithms and give simulation results to compare their performances. Finally, we show simulation results on synthetic and real data in cancer treatment applications. The real data considered in this paper examines the rest-activity patterns of KI/KI Per2::luc mouse, aged 10 weeks, singly housed in RealTime Biolumicorder (RT-BIO).