16 resultados para multilocus sequence analysis

em University of Queensland eSpace - Australia


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Aim: The aim of this study was to characterize the bacterial community adhering to the mucosa of the terminal ileum, and proximal and distal colon of the human digestive tract. Methods and Results: Pinch samples of the terminal ileum, proximal and distal colon were taken from a healthy 35-year-old, and a 68-year-old subject with mild diverticulosis. The 16S rDNA genes were amplified using a low number of PCR cycles, cloned, and sequenced. In total, 361 sequences were obtained comprising 70 operational taxonomic units (OTU), with a calculated coverage of 82.6%. Twenty-three per cent of OTU were common to the terminal ileum, proximal colon and distal colon, but 14% OTU were only found in the terminal ileum, and 43% were only associated with the proximal or distal colon. The most frequently represented clones were from the Clostridium group XIVa (24.7%), and the Bacteroidetes (Cytophaga-Flavobacteria-Bacteroides ) cluster (27.7%). Conclusion: Comparison of 16S rDNA clone libraries of the hindgut across mammalian species confirms that the distribution of phylogenetic groups is similar irrespective of the host species. Lesser site-related differences within groups or clusters of organisms, are probable. Significance and Impact: This study provides further evidence of the distribution of the bacteria on the mucosal surfaces of the human hindgut. Data contribute to the benchmarking of the microbial composition of the human digestive tract.

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Selection of machine learning techniques requires a certain sensitivity to the requirements of the problem. In particular, the problem can be made more tractable by deliberately using algorithms that are biased toward solutions of the requisite kind. In this paper, we argue that recurrent neural networks have a natural bias toward a problem domain of which biological sequence analysis tasks are a subset. We use experiments with synthetic data to illustrate this bias. We then demonstrate that this bias can be exploitable using a data set of protein sequences containing several classes of subcellular localization targeting peptides. The results show that, compared with feed forward, recurrent neural networks will generally perform better on sequence analysis tasks. Furthermore, as the patterns within the sequence become more ambiguous, the choice of specific recurrent architecture becomes more critical.

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The nuclectide sequence for pituitary prolactin cDNA from the marsupial bandicoot (Isoodon macrourus) was determined by reverse transcription-polymerase chain reaction and 5'/3' rapid amplification of cDNA ends. The deduced amino acid sequence showed high sequence identity with brushtail possum prolactin (95%) and all of the expected structural features of a quadruped prolactin. A prolactin gene tree was constructed and rates of evolution calculated for bandicoot, possum, opossum and several mammalian and non-mammalian prolactins. Bootstrap analysis provided strong support for marsupials as a sister group with eutherian mammals and weak support for opossum and bandicoot as an independent grouping from the brushtail possum. The rates of molecular evolution for marsupial prolactins were comparable to the slow rate seen in the majority of quadruped prolactins that have been sequenced. (c) 2005 Elsevier Inc. All rights reserved.

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Objective: The description and evaluation of the performance of a new real-time seizure detection algorithm in the newborn infant. Methods: The algorithm includes parallel fragmentation of EEG signal into waves; wave-feature extraction and averaging; elementary, preliminary and final detection. The algorithm detects EEG waves with heightened regularity, using wave intervals, amplitudes and shapes. The performance of the algorithm was assessed with the use of event-based and liberal and conservative time-based approaches and compared with the performance of Gotman's and Liu's algorithms. Results: The algorithm was assessed on multi-channel EEG records of 55 neonates including 17 with seizures. The algorithm showed sensitivities ranging 83-95% with positive predictive values (PPV) 48-77%. There were 2.0 false positive detections per hour. In comparison, Gotman's algorithm (with 30 s gap-closing procedure) displayed sensitivities of 45-88% and PPV 29-56%; with 7.4 false positives per hour and Liu's algorithm displayed sensitivities of 96-99%, and PPV 10-25%; with 15.7 false positives per hour. Conclusions: The wave-sequence analysis based algorithm displayed higher sensitivity, higher PPV and a substantially lower level of false positives than two previously published algorithms. Significance: The proposed algorithm provides a basis for major improvements in neonatal seizure detection and monitoring. Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.

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Increasing reports of the appearance of novel nonmultiresistant methicillin-resistant Staphylococcus aureus MRSA (MRSA) strains in the community and of the spread of hospital MRSA strains into the community are cause for public health concern. We conducted two national surveys of unique isolates of S. aureus from clinical specimens collected from nonhospitalized patients commencing in 2000 and 2002, respectively. A total of 11.7% of 2,498 isolates from 2000 and 15.4% of 2,486 isolates from 2002 were MRSA. Approximately 54% of the MRSA isolates were nonmultiresistant (resistant to less than three of nine antibiotics) in both surveys. The majority of multiresistant MRSA isolates in both surveys belonged to two strains (strains AUS-2 and AUS-3), as determined by pulsed-field gel electrophoresis (PFGE) and resistogram typing. The 3 AUS-2 isolates and 10 of the 11 AUS-3 isolates selected for multilocus sequence typing (MLST) and staphylococcal chromosomal cassette mec (SCCmec) analysis were ST239-MRSA-III (where ST is the sequence type) and thus belonged to the same clone as the eastern Australian MRSA strain of the 1980s, which spread internationally. Four predominant clones of novel nonmultiresistant MRSA were identified by PFGE, MLST, and SCCmec analysis: ST22-MRSA-IV (strain EMRSA-15), ST1-MRSA-IV (strain WA-1), ST30-MRSA-IV (strain SWP), and ST93-MRSA-IV (strain Queensland). The last three clones are associated with community acquisition. A total of 14 STs were identified in the surveys, including six unique clones of novel nonmultiresistant MRSA, namely, STs 73, 93, 129, 75, and 80sIv and a new ST. SCCmec types IV and V were present in diverse genetic backgrounds. These findings provide support for the acquisition of SCCmec by multiple lineages of S. aureus. They also confirm that both hospital and community strains of MRSA are now common in nonhospitalized patients throughout Australia.

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In this study, we propose a novel method to predict the solvent accessible surface areas of transmembrane residues. For both transmembrane alpha-helix and beta-barrel residues, the correlation coefficients between the predicted and observed accessible surface areas are around 0.65. On the basis of predicted accessible surface areas, residues exposed to the lipid environment or buried inside a protein can be identified by using certain cutoff thresholds. We have extensively examined our approach based on different definitions of accessible surface areas and a variety of sets of control parameters. Given that experimentally determining the structures of membrane proteins is very difficult and membrane proteins are actually abundant in nature, our approach is useful for theoretically modeling membrane protein tertiary structures, particularly for modeling the assembly of transmembrane domains. This approach can be used to annotate the membrane proteins in proteomes to provide extra structural and functional information.

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Full-length genome sequences of five virulent and five avirulent strains of Newcastle disease virus isolated between 1998 and 2002 in Victoria and New South Wales, Australia were determined. Comparisons between these strains revealed that coding sequence variability in the haemagglutinin-neuraminidase (HN), matrix (M) and phosphoprotein (P) gene sequences appeared to be more variable than in the fusion (F), nucleocapsid (N) and RNA dependent-RNA replicase (L) genes. Sequence analysis of a number of other isolates made during the recent virulent NDV outbreaks, also identified the presence of a number of variants with altered F gene cleavage sites, which resulted in altered biological properties of those viruses. Quasispecies analysis of a number of field isolates indicated the presence of virulent virus in one particular isolate. Gene sequence analysis of the progenitor virus isolated in 1998 showed very little sequence variation when compared to that of a progenitor-like virus isolated in 2001 demonstrating that in the field. viral genome sequence variation appears to be biologically restricted to that of a consensus sequence. (c) 2005 Elsevier B.V. All rights reserved.

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The aim of this study was to identify a set of genetic polymorphisms that efficiently divides methicillin-resistant Staphylococcus aureus (MRSA) strains into groups consistent with the population structure. The rationale was that such polymorphisms could underpin rapid real-time PCR or low-density array-based methods for monitoring MRSA dissemination in a cost-effective manner. Previously, the authors devised a computerized method for identifying sets of single nucleoticle polymorphisms (SNPs) with high resolving power that are defined by multilocus sequence typing (MLST) databases, and also developed a real-time PCR method for interrogating a seven-member SNP set for genotyping S. aureus. Here, it is shown that these seven SNPs efficiently resolve the major MRSA lineages and define 27 genotypes. The SNP-based genotypes are consistent with the MRSA population structure as defined by eBURST analysis. The capacity of binary markers to improve resolution was tested using 107 diverse MRSA isolates of Australian origin that encompass nine SNP-based genotypes. The addition of the virulence-associated genes cna, pvl and bbplsdrE, and the integrated plasmids pT181, p1258 and pUB110, resolved the nine SNP-based genotypes into 21 combinatorial genotypes. Subtyping of the SCCmec locus revealed new SCCmec types and increased the number of combinatorial genotypes to 24. It was concluded that these polymorphisms provide a facile means of assigning MRSA isolates into well-recognized lineages.

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One approach to microbial genotyping is to make use of sets of single-nucleotide polymorphisms (SNPs) in combination with binary markers. Here we report the modification and automation of a SNP-plus-binary-marker-based approach to the genotyping of Staphylococcus aureus and its application to 391 S. aureus isolates from southeast Queensland, Australia. The SNPs used were arcC210, tpi243, arcC162, gmk318, pta294, tpi36, tpi241, and pta383. These provide a Simpson's index of diversity (D) of 0.95 with respect to the S. aureus multilocus sequence typing database and define 61 genotypes and the major clonal complexes. The binary markers used were pvl, cna, sdrE, pT181, and pUB110. Two novel real-time PCR formats for interrogating these markers were compared. One of these makes use of light upon extension (LUX) primers and biplexed reactions, while the other is a streamlined modification of kinetic PCR using SYBR green. The latter format proved to be more robust. In addition, automated methods for DNA template preparation, reaction setup, and data analysis were developed. A single SNP-based method for ST-93 (Queensland clone) identification was also devised. The genotyping revealed the numerical importance of the South West Pacific and Queensland community-acquired methicillin-resistant S. aureus (MRSA) clones and the clonal complex 239 Aus-1/Aus-2 hospital-associated MRSA. There was a strong association between the community-acquired clones and pvl.