Detection and enumeration of sulphate-reducing bacteria in estuarine sediments by competitive PCR

The distribution of sulphate-reducing bacteria (SRB) in the sediments of the Colne River estuary, Essex, UK covering different saline concentrations of sediment porewater was investigated by the use of quantitative competitive PCR. Here, we show that a new PCR primer set and a new quantitative method using PCR are useful tools for the detection and the enumeration of SRB in natural environments. A PCR primer set selective for the dissimilatory sulphite reductase gene (dsr) of SRB was designed. PCR amplification using the single set of dsr-specific primers resulted in PCR products of the expected size from all 27 SRB strains tested, including Gram-negative and positive species. Sixty clones derived from sediment DNA using the primers were sequenced and all were closely related with the predicted dsr of SRB. These results indicate that PCR using the newly designed primer set are useful for the selective detection of SRB from a natural sample. This primer set was used to estimate cell numbers by dsr selective competitive PCR using a competitor, which was about 20% shorter than the targeted region of dsr. This procedure was applied to sediment samples from the River Colne estuary, Essex, UK together with simultaneous measurement of in situ rates of sulphate reduction. High densities of SRB ranging from 0.2 - 5.7 × 108 cells ml-1 wet sediment were estimated by the competitive PCR assuming that all SRB have a single copy of dsr. Using these estimates cell specific sulphate reduction rates of 10-17 to 10-15 mol of SO42- cell-1 day-1 were calculated, which is within the range of, or lower than, those previously reported for pure cultures of SRB. Our results show that the newly developed competitive PCR technique targeted to dsr is a powerful tool for rapid and reproducible estimation of SRB numbers in situ and is superior to the use of culture-dependent techniques.

Development of a PCR-based assay for rapid and reliable identification of pathogenic Fusaria

Identification of Fusarium species has always been difficult due to confusing phenotypic classification systems. We have developed a fluorescent-based polymerase chain reaction assay that allows for rapid and reliable identification of five toxigenic and pathogenic Fusarium species. The species includes Fusarium avenaceum, F. culmorum, F. equiseti, F. oxysporum and F. sambucinum. The method is based on the PCR amplification of species-specific DNA fragments using fluorescent oligonucleotide primers, which were designed based on sequence divergence within the internal transcribed spacer region of nuclear ribosomal DNA. Besides providing an accurate, reliable, and quick diagnosis of these Fusaria, another advantage with this method is that it reduces the potential for exposure to carcinogenic chemicals as it substitutes the use of fluorescent dyes in place of ethidium, bromide. Apart from its multidisciplinary importance and usefulness, it also obviates the need for gel electrophoresis. (C) 2002 Published by Elsevier Science B.V. on behalf of the Federation of European Microbiological Societies.

A general model of error-prone PCR

In this paper, we generalise a previously-described model of the error-prone polymerase chain reaction (PCR) reaction to conditions of arbitrarily variable amplification efficiency and initial population size. Generalisation of the model to these conditions improves the correspondence to observed and expected behaviours of PCR, and restricts the extent to which the model may explore sequence space for a prescribed set of parameters. Error-prone PCR in realistic reaction conditions is predicted to be less effective at generating grossly divergent sequences than the original model. The estimate of mutation rate per cycle by sampling sequences from an in vitro PCR experiment is correspondingly affected by the choice of model and parameters. (c) 2005 Elsevier Ltd. All rights reserved.

Nested parallelism for multi-core HPC systems using Java

Since its introduction in 1993, the Message Passing Interface (MPI) has become a de facto standard for writing High Performance Computing (HPC) applications on clusters and Massively Parallel Processors (MPPs). The recent emergence of multi-core processor systems presents a new challenge for established parallel programming paradigms, including those based on MPI. This paper presents a new Java messaging system called MPJ Express. Using this system, we exploit multiple levels of parallelism - messaging and threading - to improve application performance on multi-core processors. We refer to our approach as nested parallelism. This MPI-like Java library can support nested parallelism by using Java or Java OpenMP (JOMP) threads within an MPJ Express process. Practicality of this approach is assessed by porting to Java a massively parallel structure formation code from Cosmology called Gadget-2. We introduce nested parallelism in the Java version of the simulation code and report good speed-ups. To the best of our knowledge it is the first time this kind of hybrid parallelism is demonstrated in a high performance Java application. (C) 2009 Elsevier Inc. All rights reserved.

Four-dimensional variational data assimilation for high resolution nested models

Four-dimensional variational data assimilation (4D-Var) is used in environmental prediction to estimate the state of a system from measurements. When 4D-Var is applied in the context of high resolution nested models, problems may arise in the representation of spatial scales longer than the domain of the model. In this paper we study how well 4D-Var is able to estimate the whole range of spatial scales present in one-way nested models. Using a model of the one-dimensional advection–diffusion equation we show that small spatial scales that are observed can be captured by a 4D-Var assimilation, but that information in the larger scales may be degraded. We propose a modification to 4D-Var which allows a better representation of these larger scales.

The development of a real-time PCR to detect pathogenic Leptospira species in kidney tissue

A LightCycler(R) real-time PCR hybridization probe-based assay that detects a conserved region of the 16S rRNA gene of pathogenic but not saprophytic Leptospira species was developed for the rapid detection of pathogenic leptospires directly from processed tissue samples. In addition, a differential PCR specific for saprophytic leptospires and a control PCR targeting the porcine beta-actin gene were developed. To assess the suitability of these PCR methods for diagnosis, a trial was performed on kidneys taken from adult pigs with evidence of leptospiral infection, primarily a history of reproductive disease and serological evidence of exposure to pathogenic leptospires (n = 180) and aborted pig foetuses (n = 24). Leptospire DNA was detected by the 'pathogenic' specific PCR in 25 tissues (14%) and the control beta-actin PCR was positive in all 204 samples confirming DNA was extracted from all samples. No leptospires were isolated from these samples by culture and no positives were detected with the 'saprophytic' PCR. In a subsidiary experiment, the 'pathogenic' PCR was used to analyse kidney samples from rodents (n = 7) collected as part of vermin control in a zoo, with show animals with high microagglutination titres to Leptospira species, and five were positive. Fifteen PCR amplicons from 1 mouse, 2 rat and 14 pig kidney samples, were selected at random from positive PCRs (n = 30) and sequenced. Sequence data indicated L. interrogans DNA in the pig and rat samples and L. inadai DNA, which is considered of intermediate pathogenicity, in the mouse sample. The only successful culture was from this mouse kidney and the isolate was confirmed to be L. inadai by classical serology. These data suggest this suite of PCRs is suitable for testing for the presence of pathogenic leptospires in pig herds where abortions and infertility occur and potentially in other animals such as rodents. Crown Copyright (C) 2007 Published by Elsevier Ltd. All rights reserved.

Evaluation and comparison of SYBR Green I Real-Time PCR and TaqMan Real-Time PCR methods for quantitative assay of Listeria monocytogenes in nutrient broth and milk

Specific traditional plate count method and real-time PCR systems based on SYBR Green I and TaqMan technologies using a specific primer pair and probe for amplification of iap-gene were used for quantitative assay of Listeria monocytogenes in seven decimal serial dilution series of nutrient broth and milk samples containing 1.58 to 1.58×107 cfu /ml and the real-time PCR methods were compared with the plate count method with respect to accuracy and sensitivity. In this study, the plate count method was performed using surface-plating of 0.1 ml of each sample on Palcam Agar. The lowest detectable level for this method was 1.58×10 cfu/ml for both nutrient broth and milk samples. Using purified DNA as a template for generation of standard curves, as few as four copies of the iap-gene could be detected per reaction with both real-time PCR assays, indicating that they were highly sensitive. When these real-time PCR assays were applied to quantification of L. monocytogenes in decimal serial dilution series of nutrient broth and milk samples, 3.16×10 to 3.16×105 copies per reaction (equals to 1.58×103 to 1.58×107 cfu/ml L. monocytogenes) were detectable. As logarithmic cycles, for Plate Count and both molecular assays, the quantitative results of the detectable steps were similar to the inoculation levels.

The development of a ligase mediated PCR with potential for the differentiation of serovars within Leptospira interrogans

A ligase mediated polymerase chain reaction (LMPCR) was developed to amplify between the repetitive element, IS1533, of Leptospira and adjacent chromosomally located BglII restriction endonuclease enzyme sites. To do this, complimentary oligonucleotide linkers designed to anneal together with an overhanging BglII end were ligated to BglII digested DNA from 35 leptospiral reference strains and field isolates, This ligated DNA was used as template for PCR with oligonucleotide primers specific for the linker and for the repetitive element IS1533. The resultant amplicon profile hybridised a 102 hp region derived from the terminus of IS1533 thus confirming that amplicons generated by LMPCR contained part of IS1533. The number of fragments generated containing IS1533 was significantly fewer than that generated by RFLP but the LMPCR method has the potential to use far less template DNA and be quicker than standard RFLP. Obvious and reproducible interserovar differences were demonstrated by LMPCR whereas for 20 of 21 L. hardjo-bovis isolates tested no intraserovar differences were observed. Of those serovars known to possess IS1533 homologues and tested here by LMPCR, each produced a unique amplicon profile which hybridised the IS1533 terminus probe. The limited heterogeneity amongst hardjo-bovis isolates is discussed as is the potential contribution of this method to diagnosis, differentiation and the phylogenetics of the Leptospires.

Correction of atmospheric delay effects in radar interferometry using a nested mesoscale atmospheric model

The temporal variability of the atmosphere through which radio waves pass in the technique of differential radar interferometry can seriously limit the accuracy with which the method can measure surface motion. A forward, nested mesoscale model of the atmosphere can be used to simulate the variable water content along the radar path and the resultant phase delays. Using this approach we demonstrate how to correct an interferogram of Mount Etna in Sicily associated with an eruption in 2004-5. The regional mesoscale model (Unified Model) used to simulate the atmosphere at higher resolutions consists of four nested domains increasing in resolution (12, 4, 1, 0.3 km), sitting within the analysis version of a global numerical model that is used to initiate the simulation. Using the high resolution 3D model output we compute the surface pressure, temperature and the water vapour, liquid and solid water contents, enabling the dominant hydrostatic and wet delays to be calculated at specific times corresponding to the acquisition of the radar data. We can also simulate the second-order delay effects due to liquid water and ice.

PCR-based markers diagnostic for spring and winter seasonal growth habit in barley

Toward the ultimate goal of replacing field-based evaluation of seasonal growth habit, we describe the design and validation of a multiplex polymerase chain reaction assay diagnostic for allelic status at the barley (Hordeum vulgare ssp. vulgare L.) vernalization locus, VRN-H1 By assaying for the presence of all known insertion–deletion polymorphisms thought to be responsible for the difference between spring and winter alleles, this assay directly tests for the presence of functional polymorphism at VRN-H1 Four of the nine previously recognized VRN-H1 haplotypes (including both winter alleles) give unique profiles using this assay. The remaining five spring haplotypes share a single profile, indicative of function-altering deletions spanning, or adjacent to, the putative “vernalization critical” region of intron 1. When used in conjunction with a previously published PCR-based assay diagnostic for alleles at VRN-H2, it was possible to predict growth habit in all the 100 contemporary UK spring and winter lines analyzed in this study. This assay is likely to find application in instances when seasonal growth habit needs to be determined without the time and cost of phenotypic assessment and during marker-assisted selection using conventional and multicross population analysis.

Nonlinear identification using orthogonal forward regression with nested optimal regularization

An efficient data based-modeling algorithm for nonlinear system identification is introduced for radial basis function (RBF) neural networks with the aim of maximizing generalization capability based on the concept of leave-one-out (LOO) cross validation. Each of the RBF kernels has its own kernel width parameter and the basic idea is to optimize the multiple pairs of regularization parameters and kernel widths, each of which is associated with a kernel, one at a time within the orthogonal forward regression (OFR) procedure. Thus, each OFR step consists of one model term selection based on the LOO mean square error (LOOMSE), followed by the optimization of the associated kernel width and regularization parameter, also based on the LOOMSE. Since like our previous state-of-the-art local regularization assisted orthogonal least squares (LROLS) algorithm, the same LOOMSE is adopted for model selection, our proposed new OFR algorithm is also capable of producing a very sparse RBF model with excellent generalization performance. Unlike our previous LROLS algorithm which requires an additional iterative loop to optimize the regularization parameters as well as an additional procedure to optimize the kernel width, the proposed new OFR algorithm optimizes both the kernel widths and regularization parameters within the single OFR procedure, and consequently the required computational complexity is dramatically reduced. Nonlinear system identification examples are included to demonstrate the effectiveness of this new approach in comparison to the well-known approaches of support vector machine and least absolute shrinkage and selection operator as well as the LROLS algorithm.