Haplotype Analysis Reveals a Possible Founder Effect of RET Mutation R114H for Hirschsprung's Disease in the Chinese Population

Background Hirschsprung's disease (HSCR) is a congenital disorder associated with the lack of intramural ganglion cells in the myenteric and sub-mucosal plexuses along varying segments of the gastrointestinal tract. The RET gene is the major gene implicated in this gastrointestinal disease. A highly recurrent mutation in RET (RETR114H) has recently been identified in ~6-7% of the Chinese HSCR patients which, to date, has not been found in Caucasian patients or controls nor in Chinese controls. Due to the high frequency of RETR114H in this population, we sought to investigate whether this mutation may be a founder HSCR mutation in the Chinese population. Methodology and Principal Findings To test whether all RETR114H were originated from a single mutational event, we predicted the approximate age of RETR114H by applying a Bayesian method to RET SNPs genotyped in 430 Chinese HSCR patients (of whom 25 individuals had the mutation) to be between 4-23 generations old depending on growth rate. We reasoned that if RETR114H was a founder mutation then those with the mutation would share a haplotype on which the mutation resides. Including SNPs spanning 509.31 kb across RET from a recently obtained 500 K genome-wide dataset for a subset of 181 patients (14 RETR114H patients), we applied haplotype estimation methods to determine whether there were any segments shared between patients with RETR114H that are not present in those without the mutation or controls. Analysis yielded a 250.2 kb (51 SNP) shared segment over the RET gene (and downstream) in only those patients with the mutation with no similar segments found among other patients. Conclusions This suggests that RETR114H is a founder mutation for HSCR in the Chinese population. © 2010 Cornes et al.published_or_final_versio

Photocatalytic activity of nitrogen-doped TiO2-based nanowires: a photo-assisted Kelvin probe force microscopy study

The emerging industrial business partnerships, which feature cross-functional and cross-company development efforts, raise the barrier for the establishment of effective knowledge sharing practices in the larger organization. This chapter aims to highlight the role of knowledge as a key enabler for effective engineering activities in the light of such emerging enterprise collaboration models. Knowledge Enabled Engineering (KEE) is presented as an approach to enhance the extended organization’s capability to establish effective collaboration among its parts, in spite of different organizational structures, technologies or processes. KEE is analysed in its constituent parts, highlighting areas, methods and tools that are particularly interesting for leveraging companies’ knowledge sharing capabilities

Fast Visuomotor Processing of Redundant Targets: The Role of the Right Temporo-Parietal Junction

Parallel processing of multiple sensory stimuli is critical for efficient, successful interaction with the environment. An experimental approach to studying parallel processing in sensorimotor integration is to examine reaction times to multiple copies of the same stimulus. Reaction times to bilateral copies of light flashes are faster than to single, unilateral light flashes. These faster responses may be due to ‘statistical facilitation’ between independent processing streams engaged by the two copies of the light flash. On some trials, however, reaction times are faster than predicted by statistical facilitation. This indicates that a neural ‘coactivation’ of the two processing streams must have occurred. Here we use fMRI to investigate the neural locus of this coactivation. Subjects responded manually to the detection of unilateral light flashes presented to the left or right visual hemifield, and to the detection of bilateral light flashes. We compared the bilateral trials where subjects' reaction times exceeded the limit predicted by statistical facilitation to bilateral trials that did not exceed the limit. Activity in the right temporo-parietal junction was higher in those bilateral trials that showed coactivation than in those that did not. These results suggest the neural coactivation observed in visuomotor integration occurs at a cognitive rather than sensory or motor stage of processing

Alzheimer's risk variants in the clusterin gene are associated with alternative splicing

Genetic variation in CLU encoding clusterin has been associated with Alzheimer's disease (AD) through replicated genome-wide studies, but the underlying mechanisms remain unknown. Following earlier reports that tightly regulated CLU alternative transcripts have different functions, we tested CLU single-nucleotide polymorphisms (SNPs), including those associated with AD for quantitative effects on individual alternative transcripts. In 190 temporal lobe samples without pathology, we found that the risk allele of the AD-associated SNP rs9331888 increases the relative abundance of transcript NM_203339 (P=4.3 × 10−12). Using an independent set of 115 AD and control samples, we replicated this result (P=0.0014) and further observed that multiple CLU transcripts are at higher levels in AD compared with controls. The AD SNP rs9331888 is located in the first exon of NM_203339 and therefore, it is a functional candidate for the observed effects. We tested this hypothesis by in vitro dual luciferase assays using SK-N-SH cells and mouse primary cortical neurons and found allelic effects on enhancer function, consistent with our results on post-mortem human brain. These results suggest a biological mechanism for the genetic association of CLU with AD risk and indicate that rs9331888 is one of the functional DNA variants underlying this association

Molecular Dynamics Simulation Study and Hybrid Pharmacophore Model Development in Human LTA4H Inhibitor Design

Human leukotriene A4 hydrolase (hLTA4H) is a bi-functional enzyme catalyzes the hydrolase and aminopeptidase functions upon the fatty acid and peptide substrates, respectively, utilizing the same but overlapping binding site. Particularly the hydrolase function of this enzyme catalyzes the rate-limiting step of the leukotriene (LT) cascade that converts the LTA4 to LTB4. This product is a potent pro-inflammatory activator of inflammatory responses and thus blocking this conversion provides a valuable means to design anti-inflammatory agents. Four structurally very similar chemical compounds with highly different inhibitory profile towards the hydrolase function of hLTA4H were selected from the literature. Molecular dynamics (MD) simulations of the complexes of hLTA4H with these inhibitors were performed and the results have provided valuable information explaining the reasons for the differences in their biological activities. Binding mode analysis revealed that the additional thiophene moiety of most active inhibitor helps the pyrrolidine moiety to interact the most important R563 and K565 residues. The hLTA4H complexes with the most active compound and substrate were utilized in the development of hybrid pharmacophore models. These developed pharmacophore models were used in screening chemical databases in order to identify lead candidates to design potent hLTA4H inhibitors. Final evaluation based on molecular docking and electronic parameters has identified three compounds of diverse chemical scaffolds as potential leads to be used in novel and potent hLTA4H inhibitor design

The development of novel LTA4H modulators to selectively target LTB4 generation

The pro-inflammatory mediator leukotriene B4 (LTB4) is implicated in the pathologies of an array of diseases and thus represents an attractive therapeutic target. The enzyme leukotriene A4 hydrolase (LTA4H) catalyses the distal step in LTB4 synthesis and hence inhibitors of this enzyme have been actively pursued. Despite potent LTA4H inhibitors entering clinical trials all have failed to show efficacy. We recently identified a secondary anti-inflammatory role for LTA4H in degrading the neutrophil chemoattractant Pro-Gly-Pro (PGP) and rationalized that the failure of conventional LTA4H inhibitors may be that they inadvertently prevented PGP degradation. We demonstrate that these inhibitors do indeed fail to discriminate between the dual activities of LTA4H, and enable PGP accumulation in mice. Accordingly, we have developed novel compounds that potently inhibit LTB4 generation whilst leaving PGP degradation unperturbed. These novel compounds could represent a safer and superior class of LTA4H inhibitors for translation into the clinic

Disordered microbial communities in asthmatic airways.

A rich microbial environment in infancy protects against asthma [1], [2] and infections precipitate asthma exacerbations [3]. We compared the airway microbiota at three levels in adult patients with asthma, the related condition of COPD, and controls. We also studied bronchial lavage from asthmatic children and controls.We identified 5,054 16S rRNA bacterial sequences from 43 subjects, detecting >70% of species present. The bronchial tree was not sterile, and contained a mean of 2,000 bacterial genomes per cm(2) surface sampled. Pathogenic Proteobacteria, particularly Haemophilus spp., were much more frequent in bronchi of adult asthmatics or patients with COPD than controls. We found similar highly significant increases in Proteobacteria in asthmatic children. Conversely, Bacteroidetes, particularly Prevotella spp., were more frequent in controls than adult or child asthmatics or COPD patients.The results show the bronchial tree to contain a characteristic microbiota, and suggest that this microbiota is disturbed in asthmatic airways

Clustering metagenomic sequences with interpolated Markov models

<p>Abstract</p> <p>Background</p> <p>Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and sequenced by traditional methods. Because the output from metagenomic sequencing is a large set of reads of unknown origin, clustering reads together that were sequenced from the same species is a crucial analysis step. Many effective approaches to this task rely on sequenced genomes in public databases, but these genomes are a highly biased sample that is not necessarily representative of environments interesting to many metagenomics projects.</p> <p>Results</p> <p>We present S<smcaps>CIMM</smcaps> (Sequence Clustering with Interpolated Markov Models), an unsupervised sequence clustering method. S<smcaps>CIMM</smcaps> achieves greater clustering accuracy than previous unsupervised approaches. We examine the limitations of unsupervised learning on complex datasets, and suggest a hybrid of S<smcaps>CIMM</smcaps> and supervised learning method Phymm called P<smcaps>HY</smcaps>S<smcaps>CIMM</smcaps> that performs better when evolutionarily close training genomes are available.</p> <p>Conclusions</p> <p>S<smcaps>CIMM</smcaps> and P<smcaps>HY</smcaps>S<smcaps>CIMM</smcaps> are highly accurate methods to cluster metagenomic sequences. S<smcaps>CIMM</smcaps> operates entirely unsupervised, making it ideal for environments containing mostly novel microbes. P<smcaps>HY</smcaps>S<smcaps>CIMM</smcaps> uses supervised learning to improve clustering in environments containing microbial strains from well-characterized genera. S<smcaps>CIMM</smcaps> and P<smcaps>HY</smcaps>S<smcaps>CIMM</smcaps> are available open source from <url>http://www.cbcb.umd.edu/software/scimm</url>.</p

Current understanding of the human microbiome

Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature Medicine 24 (2018): 392–400, doi:10.1038/nm.4517.Our understanding of the link between the human microbiome and disease, including obesity, inflammatory bowel disease, arthritis and autism, is rapidly expanding. Improvements in the throughput and accuracy of DNA sequencing of the genomes of microbial communities associated with human samples, complemented by analysis of transcriptomes, proteomes, metabolomes and immunomes, and mechanistic experiments in model systems, have vastly improved our ability to understand the structure and function of the microbiome in both diseased and healthy states. However, many challenges remain. In this Review, we focus on studies in humans to describe these challenges, and propose strategies that leverage existing knowledge to move rapidly from correlation to causation, and ultimately to translation.Many of the studies described here in our laboratories were supported by the NIH, NSF, DOE, and the Alfred P. Sloan Foundation.2018-10-1