119 resultados para High-throughput sequencing


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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.

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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.

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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.

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Issues surrounding the misuse of prohibited and licensed substances in animals destined for food production and performance sport competition continue to be an enormous challenge to regulatory authorities charged with enforcing their control. Efficient analytical strategies are implemented to screen and confirm the presence of a wide range of exogenous substances in various biological matrices. However, such methods rely on the direct measurement of drugs and/or their metabolites in a targeted mode, allowing the detection of restricted number of compounds. As a consequence, emerging practices, in particular the use of natural hormones, designer drugs and low-dose cocktails, remain difficult to handle from a control point of view. A new SME-led FP7 funded project, DeTECH21, aims to overcome current limitations by applying an untargeted metabolomics approach based on liquid chromatography coupled to high resolution mass spectrometry and bioinformatic data analysis to identify bovine and equine animals which have been exposed to exogenous substances and assist in the identification of administered compounds. Markerbased strategies, dealing with the comprehensive analysis of metabolites present in a biological sample (urine/plasma/tissue), offer a reliable solution in the areas of food safety and animal sport doping control by effective, high-throughput and sensitive detection of exogenously administered agents. Therefore, the development of the first commercially available forensic test service based on metabolomics profiling will meet 21st century demands in animal forensics.

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Klebsiella pneumoniae is etiologic agent of community-acquired and nosocomial pneumonia. It has been shown that K. pneumoniae infections are characterized by reduced early inflammatory response. Recently our group have shown that K. pneumoniae dampens the activation of inflammatory responses by antagonizing the activation of the NF-κB canonical pathway. Our results revealed that K. pneumoniae capsule (CPS) was necessary but not sufficient to attenuate inflammation. To identify additional Klebsiella factors required to dampen inflammation, we standardized and applied a high-throughput gain-on-function screen to examine a Klebsiella transposon mutant library. We identified 114 mutants that triggered the activation of NF-κB. Two gene ontology categories accounted for half of the loci identified in the screening, that of metabolism and transport (32% of the mutants), and of enveloperelated genes (17%). Characterization of the mutants revealed that the lack of the enterobactin siderophore was linked to a reduced CPS expression which in turn underlined the NF- κB activation induced by the mutant. The lipopolysaccharide (LPS) O-polysaccharide and the pullulanase (PulA) type 2 secretion system (T2SS) are required for full effectiveness of immune evasion. Importantly, these factors do not play a redundant role. The fact that LPS Opolysaccharide and T2SS mutants-induced responses were dependent on TLR2-TLR4- MyD88 activation suggested that LPS Opolysaccharide and PulA perturbed TLRdependent recognition of K. pneumoniae. Finally, we demonstrate that LPS O-polysaccharide and pulA mutants are attenuated in the pneumonia mouse model. We propose that LPS Opolysaccharide and PulA T2SS could be new targets for designing new antimicrobials. Increasing TLR-governed defence responses might provide also selective alternatives for the management of K. pneumoniae pneumonia.

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Here is detailed a novel and low-cost experimental method for high-throughput automated fluid sample irradiation. The sample is delivered via syringe pump to a nozzle, where it is expressed in the form of a hanging droplet into the path of a beam of ionising radiation. The dose delivery is controlled by an upstream lead shutter, which allows the beam to reach the droplet for a user defined period of time. The droplet is then further expressed after irradiation until it falls into one well of a standard microplate. The entire system is automated and can be operated remotely using software designed in-house, allowing for use in environments deemed unsafe for the user (synchrotron beamlines, for example). Depending on the number of wells in the microplate, several droplets can be irradiated before any human interaction is necessary, and the user may choose up to 10 samples per microplate using an array of identical syringe pumps, the design of which is described here. The nozzles consistently produce droplets of 25.1 ± 0.5 μl.

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A polymeric hydrogel containing a photoinduced electron transfer (PET) based probe for Zn(ii) has been formulated into the wells of a 96-well plate. Upon addition of Zn(ii) ions to selected wells, the fluorescence of the gel was observed to increase in a concentration dependent manner in the 0.25-1.75 mM range. The millimolar binding constant observed for this probe is higher than that reported for other Zn(ii) probes in the literature and offers the possibility to determine the concentration of this ion in environments where the Zn(ii) concentration is high. The combination of the multi-well plate set-up with fluorescence detection offers the possibility of high-throughput screening using low sample volumes in a timely manner. To the best of our knowledge, this is the first reported example of a polymeric hydrogel sensor for zinc with capability for use in fluorescence multi-well plate assay.

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Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

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High-throughput genomic technologies have the potential to have a major impact on preclinical and clinical drug development and the selection and stratification of patients in clinical trials. These technologies, which are at varying stages of commercialization, include array-based comparative genomic hybridization, single-nucleotide polymorphism arrays, and (the most mature example) expression-based arrays. One of the rate-limiting steps in the routine clinical application of expression array-based technology is the need for suitable clinical samples. One of the major challenges moving forward, therefore, relates to the ability to use formalin-fixed, paraffin-embedded--derived tissue in expression profiling-based approaches.

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BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.

RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.

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The recent bankruptcy filing by deCODE, a company with an exceptional pedigree in associating genetic variance with disease onset, highlights the commercial risks of translational research. Indeed, deCODE's approach was similar to that adapted by academic researchers who seek to connect genetics and disease. We argue here that neither a purely corporate nor purely academic model is entirely appropriate for such research. Instead, we suggest that the private sector undertake the high-throughput elements of translational research, while the public sector and governments assume the role of providing long-term funding to develop gifted scientists with the confidence to attempt to use genetic data as a stepping stone to a truly mechanistic understanding of complex disease.

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Invasive urothelial cell carcinoma (UCC) is characterized by increased chromosomal instability and follows an aggressive clinical course in contrast to non-invasive disease. To identify molecular processes that confer and maintain an aggressive malignant phenotype, we used a high-throughput genome-wide approach to interrogate a cohort of high and low clinical risk UCC tumors. Differential expression analyses highlighted cohesive dysregulation of critical genes involved in the G(2)/M checkpoint in aggressive UCC. Hierarchical clustering based on DNA Damage Response (DDR) genes separated tumors according to a pre-defined clinical risk phenotype. Using array-comparative genomic hybridization, we confirmed that the DDR was disrupted in tumors displaying high genomic instability. We identified DNA copy number gains at 20q13.2-q13.3 (AURKA locus) and determined that overexpression of AURKA accompanied dysregulation of DDR genes in high risk tumors. We postulated that DDR-deficient UCC tumors are advantaged by a selective pressure for AURKA associated override of M phase barriers and confirmed this in an independent tissue microarray series. This mechanism that enables cancer cells to maintain an aggressive phenotype forms a rationale for targeting AURKA as a therapeutic strategy in advanced stage UCC.

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Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

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NanoStreams explores the design, implementation,and system software stack of micro-servers aimed at processingdata in-situ and in real time. These micro-servers can serve theemerging Edge computing ecosystem, namely the provisioningof advanced computational, storage, and networking capabilitynear data sources to achieve both low latency event processingand high throughput analytical processing, before consideringoff-loading some of this processing to high-capacity datacentres.NanoStreams explores a scale-out micro-server architecture thatcan achieve equivalent QoS to that of conventional rack-mountedservers for high-capacity datacentres, but with dramaticallyreduced form factors and power consumption. To this end,NanoStreams introduces novel solutions in programmable & con-figurable hardware accelerators, as well as the system softwarestack used to access, share, and program those accelerators.Our NanoStreams micro-server prototype has demonstrated 5.5×higher energy-efficiency than a standard Xeon Server. Simulationsof the microserver’s memory system extended to leveragehybrid DDR/NVM main memory indicated 5× higher energyefficiencythan a conventional DDR-based system.