Development and characterization of a 3D oral mucosa model as a tool for host-pathogen interactions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)CNPq: 163551/2012-0CNPq: 400658/2012-7CAPES: 99999.007120/2015-00The aim of this study was to (i) design, develop and validate a practical and physiologically relevant reconstituted in vitro oral mucosa tissue model and (ii) to assess its applicability in in vitro host-pathogen interactions with C. albicans and S. aureus. Co-culture organotypic constructions were created by incorporating specific numbers of keratinocytes (NOK-si) onto cellularised, collagen gel scaffolds containing human gingival fibroblasts incubated in KGM media and cultured for 14 days. The detection of the appropriate oral mucosa/epithelial structure was evaluated by histology (hematoxylin and eosin (HE), periodic acid–Schiff (P.A.S.) and Picrosirius red), and immunocytochemistry (cytokeratin 13, cytokeratin 14, Ki-67 and collagen IV) compared to a normal human gingiva. The morphology of the reconstituted tissue was analyzed by Transmission Electron Microscopy. To further quantitate tissue damage, lactate dehydrogenase (LDH) was measured in the tissue supernatant. NOK-si grown upon a gingival scaffold provided an organotypic model in an in vitro setting and exhibited structural characteristics typically associated with normal oral mucosa. Immunocytochemistry revealed the detection of epithelial cytokeratins 13 and 14, Col IV and Ki-67 in the reconstituted oral mucosa model. Infection was detected after 8 h and 16 h. This study presents an in vitro cellularised, organotypic model of reconstituted oral mucosa, which enables close control and characterization of its structure and differentiation over a mid-length period of time in culture

Non-cytotoxic 1,2,3-triazole tethered fused heterocyclic ring derivatives display Tax protein inhibition and impair HTLV-1 infected cells

Human T cell lymphotropic virus type 1 (HTLV-1) is a human retrovirus that infects approximately 10–20 million people worldwide and causes an aggressive neoplasia (adult T-cell leukemia/lymphoma - ATL). Therapeutic approaches for the treatment of ATL have variable effectiveness and poor prognosis, thus requiring strategies to identify novel compounds with activity on infected cells. In this sense, we initially screened a small series of 25 1,2,3-triazole derivatives to discover cell proliferation inhibitors and apoptosis inducers in HTLV-1-infected T-cell line (MT-2) for further assessment of their effect on viral tax activity through inducible-tax reporter cell line (Jurkat LTR-GFP). Eight promising compounds (02, 05, 06, 13, 15, 21, 22 and 25) with activity ≥70% were initially selected, based on a suitable cell-based assay using resazurin reduction method, and evaluated towards cell cycle, apoptosis and Tax/GFP expression analyses through flow cytometry. Compound 02 induced S phase cell cycle arrest and compounds 05, 06, 22 and 25 promoted apoptosis. Remarkably, compounds 22 and 25 also reduced GFP expression in an inducible-tax reporter cell, which suggests an effect on Tax viral protein. More importantly, compounds 02, 22 and 25 were not cytotoxic in human hepatoma cell line (Huh-7). Therefore, the discovery of 3 active and non-cytotoxic compounds against HTLV-1-infected cells can potentially contribute, as an initial promising strategy, to the development process of new drugs against ATL

Mapping an atlas of tissue-specific drosophila melanogaster metabolomes by high resolution mass spectrometry

Metabolomics can provide exciting insights into organismal function, but most work on simple models has focussed on the whole organism metabolome, so missing the contributions of individual tissues. Comprehensive metabolite profiles for ten tissues from adult Drosophila melanogaster were obtained here by two chromatographic methods, a hydrophilic interaction (HILIC) method for polar metabolites and a lipid profiling method also based on HILIC, in combination with an Orbitrap Exactive instrument. Two hundred and forty two polar metabolites were putatively identified in the various tissues, and 251 lipids were observed in positive ion mode and 61 in negative ion mode. Although many metabolites were detected in all tissues, every tissue showed characteristically abundant metabolites which could be rationalised against specific tissue functions. For example, the cuticle contained high levels of glutathione, reflecting a role in oxidative defence; the alimentary canal (like vertebrate gut) had high levels of acylcarnitines for fatty acid metabolism, and the head contained high levels of ether lipids. The male accessory gland uniquely contained decarboxylated S-adenosylmethionine. These data thus both provide valuable insights into tissue function, and a reference baseline, compatible with the FlyAtlas.org transcriptomic resource, for further metabolomic analysis of this important model organism, for example in the modelling of human inborn errors of metabolism, aging or metabolic imbalances such as diabetes

Combined effects of time spent in physical activity, sedentary behaviors and sleep on obesity and cardio-metabolic health markers: a novel compositional data analysis approach

<div><p>The associations between time spent in sleep, sedentary behaviors (SB) and physical activity with health are usually studied without taking into account that time is finite during the day, so time spent in each of these behaviors are codependent. Therefore, little is known about the combined effect of time spent in sleep, SB and physical activity, that together constitute a composite whole, on obesity and cardio-metabolic health markers. Cross-sectional analysis of NHANES 2005–6 cycle on N = 1937 adults, was undertaken using a compositional analysis paradigm, which accounts for this intrinsic codependence. Time spent in SB, light intensity (LIPA) and moderate to vigorous activity (MVPA) was determined from accelerometry and combined with self-reported sleep time to obtain the 24 hour time budget composition. The distribution of time spent in sleep, SB, LIPA and MVPA is significantly associated with BMI, waist circumference, triglycerides, plasma glucose, plasma insulin (all p<0.001), and systolic (p<0.001) and diastolic blood pressure (p<0.003), but not HDL or LDL. Within the composition, the strongest positive effect is found for the proportion of time spent in MVPA. Strikingly, the effects of MVPA replacing another behavior and of MVPA being displaced by another behavior are asymmetric. For example, re-allocating 10 minutes of SB to MVPA was associated with a lower waist circumference by 0.001% but if 10 minutes of MVPA is displaced by SB this was associated with a 0.84% higher waist circumference. The proportion of time spent in LIPA and SB were detrimentally associated with obesity and cardiovascular disease markers, but the association with SB was stronger. For diabetes risk markers, replacing SB with LIPA was associated with more favorable outcomes. Time spent in MVPA is an important target for intervention and preventing transfer of time from LIPA to SB might lessen the negative effects of physical inactivity.</p></div

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in a chapter of the book `Methods in Molecular Biology'. Note that this version of the manuscript may differ from the published versio