Structural and wetting properties of nature\u27s finest silks (order Embioptera)

Insects from the order Embioptera (webspinners) spin silk fibres which are less than 200 nm in diameter. In this work, we characterized and compared the diameters of single silk fibres from nine species—Antipaluria urichi, Pararhagadochir trinitatis, Saussurembia calypso, Diradius vandykei, Aposthonia ceylonica, Haploembia solieri, H. tarsalis, Oligotoma nigra and O. saundersii. Silk from seven of these species have not been previously quantified. Our studies cover five of the 10 named taxonomic families and represent about one third of the known taxonomic family-level diversity in the order Embioptera. Naturally spun silk varied in diameter from 43.6 ± 1.7 nm for D. vandykei to 122.4 ± 3.2 nm for An. urichi. Mean fibre diameter did not correlate with adult female body length. Fibre diameter is more similar in closely related species than in more distantly related species. Field observations indicated that silk appears shiny and smooth when exposed to rainwater. We therefore measured contact angles to learn more about interactions between silk and water. Higher contact angles were measured for silks with wider fibre diameter and higher quantity of hydrophobic amino acids. High static contact angles (ranging up to 122° ± 3° for An. urichi) indicated that silken sheets spun by four arboreal, webspinner species were hydrophobic. A second contact angle measurement made on a previously wetted patch of silk resulted in a lower contact angle (average difference was greater than 27°) for all four species. Our studies suggest that silk fibres which had been previously exposed to water exhibited irreversible changes in hydrophobicity and water adhesion properties. Our results are in alignment with the ‘super-pinning’ site hypothesis by Yarger and co-workers to describe the hydrophobic, yet water adhesive, properties exhibited by webspinner silk fibres. The physical and chemical insights gained here may inform the synthesis and development of smaller diameter silk fibres with unique water adhesion properties

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Integrative approaches to the prediction of protein functions based on the feature selection

<p>Abstract</p> <p>Background</p> <p>Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue.</p> <p>Results</p> <p>We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in <it>Mus musculus</it>, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO) terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR), and a kernel based <it>L1</it>-norm regularized logistic regression (KL1LR). In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among a group of protein functions that have the same parent in the GO hierarchy.</p> <p>Conclusions</p> <p>In contrast to previous integration methods, our approaches not only increase the prediction quality but also gather information about highly contributing data sources for each protein function. This information can help researchers collect relevant data sources for annotating protein functions.</p

Epidermal growth factor receptor variant III mediates head and neck cancer cell invasion via STAT3 activation

Epidermal growth factor receptor (EGFR) is frequently overexpressed in head and neck squamous cell carcinoma (HNSCC) where aberrant signaling downstream of this receptor contributes to tumor growth. EGFR variant III (EGFRvIII) is the most commonly altered form of EGFR and contains a truncated ligand-binding domain. We previously reported that EGFRvIII is expressed in up to 40% of HNSCC tumors where it is associated with increased proliferation, tumor growth and chemoresistance to antitumor drugs including the EGFR-targeting monoclonal antibody cetuximab. Cetuximab was FDA-approved in 2006 for HNSCC but has not been shown to prevent invasion or metastasis. This study was undertaken to evaluate the mechanisms of EGFRvIII-mediated cell motility and invasion in HNSCC. We found that EGFRvIII induced HNSCC cell migration and invasion in conjunction with increased signal transducer and activator of transcription 3 (STAT3) activation, which was not abrogated by cetuximab treatment. Further investigation showed that EGF-induced expression of the STAT3 target gene HIF1-α, was abolished by cetuximab in HNSCC cells expressing wild-type EGFR under hypoxic conditions, but not in EGFRvIII-expressing HNSCC cells. These results suggest that EGFRvIII mediates HNSCC cell migration and invasion by increased STAT3 activation and induction of HIF1-α, which contribute to cetuximab resistance in EGFRvIII-expressing HNSCC tumors

Antitumor Effects of EGFR Antisense Guanidine-Based Peptide Nucleic Acids in Cancer Models

[Image: see text] Peptide nucleic acids have emerged over the past two decades as a promising class of nucleic acid mimics because of their strong binding affinity and sequence selectivity toward DNA and RNA, and resistance to enzymatic degradation by proteases and nucleases. While they have been shown to be effective in regulation of gene expression in vitro, and to a small extent in vivo, their full potential for molecular therapy has not yet been fully realized due to poor cellular uptake. Herein, we report the development of cell-permeable, guanidine-based peptide nucleic acids targeting the epidermal growth factor receptor (EGFR) in preclinical models as therapeutic modality for head and neck squamous cell carcinoma (HNSCC) and nonsmall cell lung cancer (NSCLC). A GPNA oligomer, 16 nucleotides in length, designed to bind to EGFR gene transcript elicited potent antisense effects in HNSCC and NSCLC cells in preclinical models. When administered intraperitoneally in mice, EGFRAS-GPNA was taken-up by several tissues including the xenograft tumor. Systemic administration of EGFRAS-GPNA induced antitumor effects in HNSCC xenografts, with similar efficacies as the FDA-approved EGFR inhibitors: cetuximab and erlotinib. In addition to targeting wild-type EGFR, EGFRAS-GPNA is effective against the constitutively active EGFR vIII mutant implicated in cetuximab resistance. Our data reveals that GPNA is just as effective as a molecular platform for treating cetuximab resistant cells, demonstrating its utility in the treatment of cancer