Klebsiella pneumoniae targets an EGF receptor-dependent pathway to subvert inflammation

The NF-kB transcriptional factor plays a key role governing the activation of immune responses. Klebsiella pneumoniae is an important cause of community-acquired and nosocomial pneumonia. Evidence indicates that K. pneumoniae infections are characterized by lacking an early in?ammatory response. Recently, we have demonstrated that Klebsiella antagonizes the activation of NF-kB via the deubiquitinase CYLD. In this work, by applying a high-throughput siRNA gain-of-function screen interrogating the human kinome, we identi?ed 17 kinases that when targeted by siRNA restored IL-1b-dependent NF-kB translocation in infected cells. Further characterization revealed that K. pneumoniae activates an EGF receptor (EGFR)- phosphatidylinositol 3-OH kinase (PI3K)–AKT–PAK4–ERK–GSK3b signalling pathway to attenuate the cytokine-dependent nuclear translocation of NF-kB. Our data also revealed that CYLD is a downstream effector of K. pneumoniae-induced EGFR–
PI3K–AKT–PAK4–ERK–GSK3b signalling pathway. Our efforts to identify the bacterial factor(s) responsible for EGFR activation demonstrate that a capsule (CPS) mutant did not activate EGFR hence
suggesting that CPS could mediate the activation of EGFR. Supporting this notion, puri?ed CPS did activate EGFR as well as the EGFR-dependent PI3K–AKT–PAK4–ERK–GSK3b signalling pathway. CPS-mediated EGFR activation was dependent on a TLR4–MyD88–c-SRC-dependent pathway. Several promising drugs have been developed to antagonize this cascade. We propose that agents targeting this signalling pathway might provide selective alternatives for the management of K. pneumoniae pneumonias.

The topography of DNA methylation in the non-neoplastic colonic mucosa surrounding colorectal cancers

The degree of gene hypermethylation in non-neoplastic colonic mucosa (NNCM) is a potentially important event in the development of colorectal cancer (CRC), particularly for the subgroup with a CpG island methylator phenotype (CIMP). In this study, we aimed to use an unbiased and high-throughput approach to evaluate the topography of DNA methylation in the non-neoplastic colonic mucosa (NNCM) surrounding colorectal cancer (CRC). A total of 61 tissue samples comprising 53 NNCM and 8 tumor samples were obtained from hemicolectomy specimens of two CRC patients (Cases 1 and 2). NNCM was stripped from the underlying colonic wall and samples taken at varying distances from the tumor. The level of DNA methylation in NNCM and tumor tissues was assessed at 1,505 CpG sites in 807 cancer-related genes using Illumina GoldenGate® methylation arrays. Case 1 tumor showed significantly higher levels of methylation compared to surrounding NNCM samples (P?

Development of a Portable Tissue Micro Array Instrument

Tissue micro array (TMA) is based on the idea of applying miniaturization and a high throughput approach to hybridization-based analyses of tissues. It facilitates biomedical research on a large scale in a single experiment; thus representing one of the most commonly used technologies in translational research. A critical analysis of the existing TMA instruments indicates that there are potential constraints in terms of portability, apart from costs and complexity. This paper will present the development of an affordable, configurable, and portable TMA instrument to allow an efficient collection of tissues, especially in instrument-to-tissue scenarios. The purely mechanical instrument requires no energy sources other than the user, is light weight, portable, and simple to use. [DOI: 10.1115/1.4004922]

Genetic and Epigenetic Risk Factors for Diabetic Kidney Disease

Diabetes is increasing at daunting rates worldwide, and approximately 40% of affected individuals will develop kidney complications. Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease, and there are significant healthcare costs providing appropriate renal replacement therapies to affected individuals. For several decades, investigators have sought to discover inherited risk factors and biomarkers for DKD. In recent years, advances in high-throughput laboratory techniques and computational analyses, coupled with the establishment of multicenter consortia, have helped to identify genetic loci that are replicated across multiple populations. Several genome-wide association studies (GWAS) have been conducted for DKD with further meta-analysis of GWAS and comprehensive ”single gene” meta-analyses now published. Despite these efforts, much of the inherited predisposition to DKD remains unexplained. Meta-analyses and integrated–omics pathway studies are being used to help elucidate underlying genetic risks. Epigenetic phenomena are increasingly recognized as important drivers of disease risk, and several epigenome-wide association studies have now been completed. This review describes key findings and ongoing genetic and epigenetic initiatives for DKD.

Personalized medicine: Has it started yet? A reconstruction of the early history

Within the last few years the field personalized medicine entered the stage. Accompanied with great hopes and expectations it is believed that this field may have the potential to revolutionize medical and clinical care by utilizing genomics information about the individual patients themselves. In this paper, we reconstruct the early footprints of personalized medicine as reflected by information retrieved from PubMed and Google Scholar. That means we are providing a data-driven perspective of this field to estimate its current status and potential problems.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Extremely Complex Populations of Small RNAs in the Mouse Retina and RPE/Choroid

Purpose: MicroRNAs (miRNAs) are small non-coding RNAs of ~18-22 nucleotides in length that regulate gene expression. They are widely expressed in the retina, being both required for its normal development and perturbed in disease. The aim of this study was to apply new high-throughput sequencing techniques to more fully characterise the microRNAs and other small RNAs expressed in the retina and retinal pigment epithelium (RPE)/choroid of the mouse.

Methods: Retina and RPE/choroid were dissected from eyes of 3 month-old C57BL/6J mice. Small RNA libraries were prepared and deep sequencing performed on a Genome Analyzer (Illumina). Reads were annotated by alignment to miRBase, other non-coding RNA databases and the mouse genome.

Results: Annotation of 9 million reads to 320 microRNAs in retina and 340 in RPE/choroid provides the most comprehensive profiling of microRNAs to date. Two novel microRNAs were identified in retina. Members of the sensory organ specific miR-183,-182,-96 cluster were amongst the most highly expressed, retina-enriched microRNAs. Remarkably, microRNA 'isomiRs', which vary slightly in length and are differentially detected by Taqman RT-PCR assays, existed for all the microRNAs identified in both tissues. More variation occurred at the 3' ends, including non-templated additions of T and A. Drosha-independent mirtron microRNAs and other small RNAs derived from snoRNAs were also detected.

Conclusions: Deep sequencing has revealed the complexity of small RNA expression in the mouse retina and RPE/choroid. This knowledge will improve the design and interpretation of future functional studies of the role of microRNAs and other small RNAs in retinal disease.

Cancer drug resistance:an evolving paradigm

Resistance to chemotherapy and molecularly targeted therapies is a major problem facing current cancer research. The mechanisms of resistance to 'classical' cytotoxic chemotherapeutics and to therapies that are designed to be selective for specific molecular targets share many features, such as alterations in the drug target, activation of prosurvival pathways and ineffective induction of cell death. With the increasing arsenal of anticancer agents, improving preclinical models and the advent of powerful high-throughput screening techniques, there are now unprecedented opportunities to understand and overcome drug resistance through the clinical assessment of rational therapeutic drug combinations and the use of predictive biomarkers to enable patient stratification.

Multi-standard sub-pixel interpolation architecture for video motion estimation

A new domain-specific reconfigurable sub-pixel interpolation architecture for multi-standard video Motion Estimation (ME) is presented. The mixed use of parallel and serial-input FIR filters achieves high throughput rate and efficient silicon utilisation. Flexibility has been achieved by using a multiplexed reconfigurable data-path controlled by a selection signal. Silicon design studies show that this can be implemented using 34.8K gates with area and performance that compares very favourably with existing fixed solutions based solely on the H.264 standard. ©2008 IEEE.

qPCR utilization for the study of RNA Polymerase I transcription

Ribosome biogenesis is a fundamental cellular process tightly linked to cell growth and proliferation, which requires the coordinated transcription of all three nuclear polymerases. Synthesis of ribosomal RNA (rRNA) by RNA polymerase I (Pol I) has been suggested as a key regulator of ribosome biogenesis, and there is a strong link between transcription of ribosomal RNAs and cellular proliferation. This makes Pol I transcription a valid and attractive target for anticancer therapy. At the moment however there are only a small number of compounds that act as specific inhibitors of Pol I transcription and this makes it very difficult for the development of drugs which would target rRNA transcription and consequently ribosome biogenesis. Therefore, to aid in the development of new inhibitors of Pol I, high-throughput methods to monitor and detect changes in Pol I activity need to be developed. This current study aimed to address the question of whether or not quantitative PCR (qPCR) could be used to detect changes in rRNA production in cells under different conditions that repress Pol I activity i.e. serum starvation and drug treatment. Our results have shown that using primers and a hydrolysis probe designed for the 5’ETS region of the pre-rRNA molecule, rRNA levels in both treated and untreated cells could be determined by using qPCR.
Amplification resulted in formation of a single product and S1 nuclease protection assay confirmed the down-regulation of Pol I transcription. Following serum-starvation and drug treatment there was a dramatic reduction in the amount of 5’ETS transcript quantitated by both Sybr Green chemistry and the use of a fluorescently labelled hydrolysis probe. The optimization of the qPCR strategy will be discussed.

Improved Detection of Mycobacterium bovis in Bovine Tissues Using Immunomagnetic Separation Approaches

Immunomagnetic separation (IMS) represents a simple but effective method of selectively capturing and concentrating Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), from tissue samples. It is a physical cell separation technique that does not impact cell viability, unlike traditional chemical decontamination prior to culture. IMS is performed with paramagnetic beads coated with M. bovis-specific antibody and peptide binders. Once captured by IMS, M. bovis cells can be detected by either PCR or cultural detection methods. Increased detection rates of M. bovis, particularly from non-visibly lesioned lymph node tissues from bTB reactor animals, have recently been reported when IMS-based methods were employed.

Multimedia Resource Allocation in mmWave 5G Networks

The 5G network infrastructure is driven by the evolution of today's most demanding applications. Already, multimedia applications such as on-demand HD video and IPTV require gigabit- per-second throughput and low delay, while future technologies include ultra HDTV and machine-to-machine communication. Mm-Wave technologies such as IEEE 802.15.3c and IEEE 802.11ad are ideal candidates to deliver high throughput to multiple users demanding differentiated QoS. Optimization is often used as a methodology to meet throughput and delay constraints. However, traditional optimization techniques are not suited to a mixed set of multimedia applications. Particle swarm optimization (PSO) is shown as a promising technique in this context. Channel-time allocation PSO (CTA-PSO) is successfully shown here to allocate resource even in scenarios where blockage of the 60 GHz signal poses significant challenges.

Multiplex Touchdown PCR for Rapid Typing of the Opportunistic Pathogen Propionibacterium acnes.

The opportunistic human pathogen Propionibacterium acnes is comprised of a number of distinct phylogroups, designated types IA1, IA2, IB, IC, II and III, that vary in their production of putative virulence factors, inflammatory potential, as well as biochemical, aggregative and morphological characteristics. Although Multilocus Sequence Typing (MLST) currently represents the gold standard for unambiguous phylogroup classification, and individual strain identification, it is a labour and time-consuming technique. As a consequence, we have developed a multiplex touchdown PCR assay that will, in a single reaction, confirm species identity and phylogeny of an isolate based on its pattern of reaction with six primer sets that target the 16S rRNA (all isolates), ATPase (type IA1, IA2, IC), sodA (type IA2, IB), atpD (type II) and recA (type III) housekeeping genes, as well as a Fic family toxin gene (type IC). When applied to 312 P. acnes isolates previously characterised by MLST, and representing type IA1 (n=145), IA2 (n=20), IB (n=65), IC (n=7), II (n=45) and III (n=30), the multiplex displayed 100% sensitivity and 100% specificity for the detection of isolates within each targeted phylogroup. No cross-reactivity with isolates from other bacterial species was observed. The multiplex assay will provide researchers with a rapid, high-throughput and technically undemanding typing method for epidemiological and phylogenetic investigations. It will facilitate studies investigating the association of lineages with various infections and clinical conditions, as well as a pre-screening tool to maximise the number of genetically diverse isolates selected for downstream, higher resolution sequence-based analyses.

MICROBIAL COMMUNITY COMPOSITION IN THE LUNGS OF PATIENTS WITH CYSTIC FIBROSIS AND NON-CF BRONCHIECTASIS

Introduction and Aims: Persistent bacterial infection is a major cause of morbidity and mortality in patients with both Cystic Fibrosis (CF) and non-CF Bronchiectasis (non-CFBX). Numerous studies have shown that CF and non-CFBX airways are colonised by a complex microbiota. However, many bacteria are difficult, if not impossible, to culture by conventional laboratory techniques. Therefore, molecular detection techniques offer a more comprehensive view of bacterial diversity within clinical specimens. The objective of this study was to characterise and compare bacterial diversity and relative abundance in patients with CF and non-CFBX during exacerbation and when clinically stable.

Methods: Sputum samples were collected from CF (n=50 samples) and non-CFBX (n=52 samples) patients at the start and end of treatment for an infective exacerbation and when clinically stable. Pyrosequencing was used to assess the microbial diversity and relative genera (or the closest possibly taxonomic order) abundance within the samples. Each sequence read was defined based on 3% difference.

Results: High-throughput pyrosequencing allowed a sensitive and detailed examination of microbial community composition. Rich microbial communities were apparent within both CF (171 species-level phylotypes per genus) and non-CFBX airways (144 species-level phylotypes per genus). Relative species distribution within those two environments was considerably different; however, relatively few genera formed a core of microorganisms, representing approximately 90% of all sequences, which dominated both environments. Relative abundance based on observed operational taxonomic units demonstrated that the most abundant bacteria in CF were Pseudomonas (28%), Burkholderia (22%), Streptococcus (13%), family Pseudomonadaceae (8%) and Prevotella (6%). In contrast, the most commonly detected operational taxonomic units in non-CFBX were Haemophilus (22%), Streptococcus (14%), other (unassigned taxa) (11%), Pseudomonas (10%), Veillonella (7%) and Prevotella (6%).

Conclusions: These results suggest that distinctive microbial communities are associated with infection and/or colonisation in patients with both CF and non-CFBX. Although relatively high species richness was observed within the two environments, each was dominated by different core taxa. This suggests that differences in the lung environment of these two diseases may affect adaptability of the relevant bacterial taxa.

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: a comprehensive profiling approach

BACKGROUND: Methylation-induced silencing of promoter CpG islands in tumor suppressor genes plays an important role in human carcinogenesis. In colorectal cancer, the CpG island methylator phenotype (CIMP) is defined as widespread and elevated levels of DNA methylation and CIMP+ tumors have distinctive clinicopathological and molecular features. In contrast, the existence of a comparable CIMP subtype in gastric cancer (GC) has not been clearly established. To further investigate this issue, in the present study we performed comprehensive DNA methylation profiling of a well-characterised series of primary GC.

METHODS: The methylation status of 1,421 autosomal CpG sites located within 768 cancer-related genes was investigated using the Illumina GoldenGate Methylation Panel I assay on DNA extracted from 60 gastric tumors and matched tumor-adjacent gastric tissue pairs. Methylation data was analysed using a recursively partitioned mixture model and investigated for associations with clinicopathological and molecular features including age, Helicobacter pylori status, tumor site, patient survival, microsatellite instability and BRAF and KRAS mutations.

RESULTS: A total of 147 genes were differentially methylated between tumor and matched tumor-adjacent gastric tissue, with HOXA5 and hedgehog signalling being the top-ranked gene and signalling pathway, respectively. Unsupervised clustering of methylation data revealed the existence of 6 subgroups under two main clusters, referred to as L (low methylation; 28% of cases) and H (high methylation; 72%). Female patients were over-represented in the H tumor group compared to L group (36% vs 6%; P = 0.024), however no other significant differences in clinicopathological or molecular features were apparent. CpG sites that were hypermethylated in group H were more frequently located in CpG islands and marked for polycomb occupancy.

CONCLUSIONS: High-throughput methylation analysis implicates genes involved in embryonic development and hedgehog signaling in gastric tumorigenesis. GC is comprised of two major methylation subtypes, with the highly methylated group showing some features consistent with a CpG island methylator phenotype.