Sensitive and Rapid Detection of Genetic Modified Soybean (Roundup Ready) by Loop-Mediated Isothermal Amplification

Using the LAMP method, a highly specific and sensitive detection system for genetically modified soybean (Roundup Ready) was designed. In this detection system, a set of four primers was designed by targeting the exogenous 35S epsps gene. Target DNA was amplified and visualized on agarose gel within 45 min under isothermal conditions at 65 degrees C. Without gel electrophoresis, the LAMP amplicon was visualized directly in the reaction tube by the addition of SYBR Green I for naked-eye inspection. The detection sensitivity of LAMP was 10-fold higher than the nested PCR established in our laboratory. Moreover, the LAMP method was much quicker, taking only 70 min, as compared with 300 min for nested PCR to complete the analysis of the GM soybean. Compared with traditional PCR approaches, the LAMP procedure is faster and more sensitive, and there is no need for a special PCR machine or electrophoresis equipment. Hence, this method can be a very useful tool for GMO detection and is particularly convenient for fast screening.

Determination of heavy metal ions by capillary electrophoresis with contactless conductivity detection after field-amplified sample injection

A method has been developed for determining of heavy metal ions by field-amplified sample injection capillary electrophoresis with contactless conductivity detection. The effects of the 2-N-morpholinoethanesulfonic acid/histidine (MES/His) concentration in the sample matrix, the injection time and organic additives on the enrichment factor were studied. The results showed that MES/His with a low concentration in the sample matrix, an increase of the injection time and the addition of acetonitrile improved the enrichment factor. Four heavy metal ions (Zn2+, Co2+, Cu2+ and Ni2+) were dissolved in deionized water, separated in a 10 mM MES/His running buffer at pH 4.9 and detected by contactless conductivity detection. The detection sensitivity was enhanced by about three orders of magnitude with respect to the non-stacking injection mode. The limits of detection were in the range from 5 nM (Zn2+) to 30 nM (Cu2+). The method has been used to determine heavy metal ions in tap water.

Improved Detection of Mycobacterium bovis Infection in Bovine Lymph Node Tissue Using Immunomagnetic Separation (IMS)-Based Methods

Immunomagnetic separation (IMS) can selectively isolate and concentrate Mycobacterium bovis cells from lymph node tissue to facilitate subsequent detection by PCR (IMS-PCR) or culture (IMS-MGIT). This study describes application of these novel IMS-based methods to test for M. bovis in a survey of 280 bovine lymph nodes (206 visibly lesioned (VL), 74 non-visibly lesioned (NVL)) collected at slaughter as part of the Northern Ireland bovine TB eradication programme. Their performance was evaluated relative to culture. Overall, 174 (62.1%) lymph node samples tested positive by culture, 162 (57.8%) by IMS-PCR (targeting IS6110), and 196 (70.0%) by IMS-MGIT culture. Twelve (6.9%) of the 174 culture positive lymph node samples were not detected by either of the IMS-based methods. However, an additional 78 M. bovis positive lymph node samples (26 (12.6%) VL and 54 (73.0%) NVL) were detected by the IMS-based methods and not by culture. When low numbers of viable M. bovis are present in lymph nodes (e.g. in NVLs of skin test reactor cattle) decontamination prior to culture may adversely affect viability, leading to false negative culture results. In contrast, IMS specifically captures whole M. bovis cells (live, dead or potentially dormant) which are not subject to any deleterious treatment before detection by PCR or MGIT culture. During this study only 2.7% of NVL lymph nodes tested culture positive, whereas 73% of the same samples tested M. bovis positive by the IMS-based tests. Results clearly demonstrate that not only are the IMS-based methods more rapid but they have greater detection sensitivity than the culture approach currently used for the detection of M. bovis infection in cattle.. Adoption of the IMS-based methods for lymph node testing would have the potential to improve M. bovis detection in clinical samples.

Two sequential PCR amplifications for detection of Schistosoma mansoni in stool samples with low parasite load

Schistosomiasis constitutes a major public health problem, with an estimated 200 million individuals infected worldwide and 700 million people living in risk areas. In Brazil there are areas of high, medium and low endemicity. Studies have shown that in endemic areas with a low prevalence of Schistosoma infection the sensitivity of parasitological methods is clearly reduced. Consequently diagnosis is often impeded due to the presence of false-negative results. The aim of this study is to present the PCR reamplification (Re-PCR) protocol for the detection of Schistosoma mansoni in samples with low parasite load (with less than 100 eggs per gram (epg) of feces). Three methods were used for the lysis of the envelopes of the S. mansoni eggs and two techniques of DNA extraction were carried out. Extracted DNA was quantified, and the results suggested that the extraction technique, which mixed glass beads with a guanidine isothiocyanate/phenol/chloroform (GT) solution, produced good results. PCR reamplification was conducted and detection sensitivity was found to be five eggs per 500 mg of artificially marked feces. The results achieved using these methods suggest that they are potentially viable for the detection of Schistosoma infection with low parasite load.

Streak detection algorithm for space debris detection on optical images.

Any image processing object detection algorithm somehow tries to integrate the object light (Recognition Step) and applies statistical criteria to distinguish objects of interest from other objects or from pure background (Decision Step). There are various possibilities how these two basic steps can be realized, as can be seen in the different proposed detection methods in the literature. An ideal detection algorithm should provide high recognition sensitiv ity with high decision accuracy and require a reasonable computation effort . In reality, a gain in sensitivity is usually only possible with a loss in decision accuracy and with a higher computational effort. So, automatic detection of faint streaks is still a challenge. This paper presents a detection algorithm using spatial filters simulating the geometrical form of possible streaks on a CCD image. This is realized by image convolution. The goal of this method is to generate a more or less perfect match between a streak and a filter by varying the length and orientation of the filters. The convolution answers are accepted or rejected according to an overall threshold given by the ackground statistics. This approach yields as a first result a huge amount of accepted answers due to filters partially covering streaks or remaining stars. To avoid this, a set of additional acceptance criteria has been included in the detection method. All criteria parameters are justified by background and streak statistics and they affect the detection sensitivity only marginally. Tests on images containing simulated streaks and on real images containing satellite streaks show a very promising sensitivity, reliability and running speed for this detection method. Since all method parameters are based on statistics, the true alarm, as well as the false alarm probability, are well controllable. Moreover, the proposed method does not pose any extraordinary demands on the computer hardware and on the image acquisition process.

A Loop-mediated Isothermal Amplification Method for Rapid Direct Detection and Differentiation of Non-pathogenic and Verocytotoxigenic Escherichia coli in Beef and Bovine Faeces

The aim of this study was to develop a multiplex loop-mediated isothermal amplification (LAMP) method capable of detecting Escherichia coli generally and verocytotoxigenic E. coli (VTEC) specifically in beef and bovine faeces. The LAMP assay developed was highly specific (100%) and able to distinguish between E. coli and VTEC based on the amplification of the phoA, and stx1 and/or stx2 genes, respectively. In the absence of an enrichment step, the limit of detection 50% (LOD50) of the LAMP assay was determined to be 2.83, 3.17 and 2.83-3.17 log CFU/g for E. coli with phoA, stx1 and stx2 genes, respectively, when artificially inoculated minced beef and bovine faeces were tested. The LAMP calibration curves generated with pure cultures, and spiked beef and faeces, suggested that the assay had good quantification capability. Validation of the assay, performed using retail beef and bovine faeces samples, demonstrated good correlation between counts obtained by the LAMP assay and by a conventional culture method, but suggested the possibility of false negative LAMP results for 12.5-14.7% of samples tested. The multiplex LAMP assay developed potentially represents a rapid alternative to culture for monitoring E.coli levels in beef or faeces and it would provide additional information on the presence of VTEC. However, some further optimisation is needed to improve detection sensitivity.

Sensitive and specific detection of viable Mycobacterium avium subsp. paratuberculosis in raw milk by the Peptide-mediated magnetic separation (PMS)-phage assay

This study describes further validation of a previously described Peptide-mediated magnetic separation (PMS)-Phage assay, and its application to test raw cows’ milk for presence of viable Mycobacterium avium subsp. paratuberculosis (MAP). The inclusivity and exclusivity of the PMS-phage assay were initially assessed, before the 50% limit of detection (LOD50) was determined and compared with those of PMS-qPCR (targeting both IS900 and f57) and PMS-culture. These methods were then applied in parallel to test 146 individual milk samples and 22 bulk tank milk samples from Johne’s affected herds. Viable MAP were detected by the PMS-phage assay in 31 (21.2%) of 146 individual milk samples (mean plaque count of 228.1 PFU/50 ml, range 6-948 PFU/50 ml), and 13 (59.1%) of 22 bulk tank milks (mean plaque count of 136.83 PFU/50 ml, range 18-695 PFU/50 ml). In contrast, only 7 (9.1%) of 77 individual milks and 10 (45.4%) of 22 bulk tank milks tested PMS-qPCR positive, and 17 (11.6%) of 146 individual milks and 11 (50%) of 22 bulk tank milks tested PMS-culture positive. The mean 50% limits of detection (LOD50) of the PMS-phage, PMS-IS900 qPCR and PMS-f57 qPCR assays, determined by testing MAP-spiked milk, were 0.93, 135.63 and 297.35 MAP CFU/50 ml milk, respectively. Collectively, these results demonstrate that, in our laboratory, the PMS-phage assay is a sensitive and specific method to quickly detect the presence of viable MAP cells in milk. However, due to its complicated, multi-step nature, the method would not be a suitable MAP screening method for the dairy industry.

MICROFLUIDIC ASSAY PERFORMANCE ENHANCEMENT USING POROUS VOLUMETRIC DETECTION ELEMENTS FOR IMPEDEMETRIC AND OPTICAL SENSING

Microfluidic technologies have great potential to help create automated, cost-effective, portable devices for rapid point of care (POC) diagnostics in diverse patient settings. Unfortunately commercialization is currently constrained by the materials, reagents, and instrumentation required and detection element performance. While most microfluidic studies utilize planar detection elements, this dissertation demonstrates the utility of porous volumetric detection elements to improve detection sensitivity and reduce assay times. Impedemetric immunoassays were performed utilizing silver enhanced gold nanoparticle immunoconjugates (AuIgGs) and porous polymer monolith or silica bead bed detection elements within a thermoplastic microchannel. For a direct assay with 10 µm spaced electrodes the detection limit was 0.13 fM AuIgG with a 3 log dynamic range. The same assay was performed with electrode spacing of 15, 40, and 100 µm with no significant difference between configurations. For a sandwich assay the detection limit was10 ng/mL with a 4 log dynamic range. While most impedemetric assays rely on expensive high resolution electrodes to enhance planar senor performance, this study demonstrates the employment of porous volumetric detection elements to achieve similar performance using lower resolution electrodes and shorter incubation times. Optical immunoassays were performed using porous volumetric capture elements perfused with refractive index matching solutions to limit light scattering and enhance signal. First, fluorescence signal enhancement was demonstrated with a porous polymer monolith within a silica capillary. Next, transmission enhancement of a direct assay was demonstrated by infusing aqueous sucrose solutions through silica bead beds with captured silver enhanced AuIgGs yielding a detection limit of 0.1 ng/mL and a 5 log dynamic range. Finally, ex situ functionalized porous silica monolith segments were integrated into thermoplastic channels for a reflectance based sandwich assay yielding a detection limit of 1 ng/mL and a 5 log dynamic range. The simple techniques for optical signal enhancement and ex situ element integration enable development of sensitive, multiplexed microfluidic sensors. Collectively the demonstrated experiments validate the use of porous volumetric detection elements to enhance impedemetric and optical microfluidic assays. The techniques rely on commercial reagents, materials compatible with manufacturing, and measurement instrumentation adaptable to POC diagnostics.

Hierarchical Bayesian models for estimating the extent of plant pest invasions

Plant biosecurity requires statistical tools to interpret field surveillance data in order to manage pest incursions that threaten crop production and trade. Ultimately, management decisions need to be based on the probability that an area is infested or free of a pest. Current informal approaches to delimiting pest extent rely upon expert ecological interpretation of presence / absence data over space and time. Hierarchical Bayesian models provide a cohesive statistical framework that can formally integrate the available information on both pest ecology and data. The overarching method involves constructing an observation model for the surveillance data, conditional on the hidden extent of the pest and uncertain detection sensitivity. The extent of the pest is then modelled as a dynamic invasion process that includes uncertainty in ecological parameters. Modelling approaches to assimilate this information are explored through case studies on spiralling whitefly, Aleurodicus dispersus and red banded mango caterpillar, Deanolis sublimbalis. Markov chain Monte Carlo simulation is used to estimate the probable extent of pests, given the observation and process model conditioned by surveillance data. Statistical methods, based on time-to-event models, are developed to apply hierarchical Bayesian models to early detection programs and to demonstrate area freedom from pests. The value of early detection surveillance programs is demonstrated through an application to interpret surveillance data for exotic plant pests with uncertain spread rates. The model suggests that typical early detection programs provide a moderate reduction in the probability of an area being infested but a dramatic reduction in the expected area of incursions at a given time. Estimates of spiralling whitefly extent are examined at local, district and state-wide scales. The local model estimates the rate of natural spread and the influence of host architecture, host suitability and inspector efficiency. These parameter estimates can support the development of robust surveillance programs. Hierarchical Bayesian models for the human-mediated spread of spiralling whitefly are developed for the colonisation of discrete cells connected by a modified gravity model. By estimating dispersal parameters, the model can be used to predict the extent of the pest over time. An extended model predicts the climate restricted distribution of the pest in Queensland. These novel human-mediated movement models are well suited to demonstrating area freedom at coarse spatio-temporal scales. At finer scales, and in the presence of ecological complexity, exploratory models are developed to investigate the capacity for surveillance information to estimate the extent of red banded mango caterpillar. It is apparent that excessive uncertainty about observation and ecological parameters can impose limits on inference at the scales required for effective management of response programs. The thesis contributes novel statistical approaches to estimating the extent of pests and develops applications to assist decision-making across a range of plant biosecurity surveillance activities. Hierarchical Bayesian modelling is demonstrated as both a useful analytical tool for estimating pest extent and a natural investigative paradigm for developing and focussing biosecurity programs.

Transcription and expression of Plasmodium falciparum histidine-rich proteins in different stages and strains : implications for rapid diagnostic tests

Background: Although rapid diagnostic tests (RDTs) for Plasmodium falciparum infection that target histidine rich protein 2 (PfHRP2) are generally sensitive, their performance has been reported to be variable. One possible explanation for variable test performance is differences in expression level of PfHRP in different parasite isolates. Methods: Total RNA and protein were extracted from synchronised cultures of 7 P. falciparum lines over 5 time points of the life cycle, and from synchronised ring stages of 10 falciparum lines. Using quantitative real-time polymerase chain reaction, Western blot analysis and ELISA we investigated variations in the transcription and protein levels of pfhrp2, pfhrp3 and PfHRP respectively in the different parasite lines, over the parasite intraerythrocytic life cycle. Results: Transcription of pfhrp2 and pfhrp3 in different parasite lines over the parasite life cycle was observed to vary relative to the control parasite K1. In some parasite lines very low transcription of these genes was observed. The peak transcription was observed in ring-stage parasites. Pfhrp2 transcription was observed to be consistently higher than pfhrp3 transcription within parasite lines. The intraerythrocytic lifecycle stage at which the peak level of protein was present varied across strains. Total protein levels were more constant relative to total mRNA transcription, however a maximum 24 fold difference in expression at ring-stage parasites relative to the K1 strain was observed. Conclusions: The levels of transcription of pfhrp2 and pfhrp3, and protein expression of PfHRP varied between different P. falciparum strains. This variation may impact on the detection sensitivity of PfHRP2-detecting RDTs.

Plasmodium falciparum parasites lacking histidine-rich protein 2 and 3 : a review and recommendations for accurate reporting

Malaria rapid diagnostic tests (RDTs) play a critical role in malaria case management, surveillance and case investigations. Test performance is largely determined by design and quality characteristics, such as detection sensitivity, specificity, and thermal stability. However, parasite characteristics such as variable or absent expression of antigens targeted by RDTs can also affect RDT performance. Plasmodium falciparum parasites lacking the PfHRP2 protein, the most common target antigen for detection of P. falciparum, have been reported in some regions. Therefore, accurately mapping the presence and prevalence of P. falciparum parasites lacking pfhrp2 would be an important step so that RDTs targeting alternative antigens, or microscopy, can be preferentially selected for use in such regions. Herein the available evidence and molecular basis for identifying malaria parasites lacking PfHRP2 is reviewed, and a set of recommended procedures to apply for future investigations for parasites lacking PfHRP2, is proposed.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

SERS-barcoded colloidal gold NP assemblies as imaging agents for use in biodiagnostics

There is a growing need for new biodiagnostics that combine high throughput with enhanced spatial resolution and sensitivity. Gold nanoparticle (NP) assemblies with sub-10 nm particle spacing have the benefits of improving detection sensitivity via Surface enhanced Raman scattering (SERS) and being of potential use in biomedicine due to their colloidal stability. A promising and versatile approach to form solution-stable NP assemblies involves the use of multi-branched molecular linkers which allows tailoring of the assembly size, hot-spot density and interparticle distance. We have shown that linkers with multiple anchoring end-groups can be successfully employed as a linker to assemble gold NPs into dimers, linear NP chains and clustered NP assemblies. These NP assemblies with diameters of 30-120 nm are stable in solution and perform better as SERS substrates compared with single gold NPs, due to an increased hot-spot density. Thus, tailored gold NP assemblies are potential candidates for use as biomedical imaging agents. We observed that the hot-spot density and in-turn the SERS enhancement is a function of the linker polymer concentration and polymer architecture. New deep Raman techniques like Spatially Offset Raman Spectroscopy (SORS) have emerged that allow detection from beneath diffusely scattering opaque materials, including biological media such as animal tissue. We have been able to demonstrate that the gold NP assemblies could be detected from within both proteinaceous and high lipid containing animal tissue by employing a SORS technique with a backscattered geometry.

Titania nanowires as substrates for sensing and photocatalysis of common textile industry effluents

Sensing and photocatalysis of textile industry effluents such as dyes using mesoporous anatase titania nanowires are discussed here.Spectroscopic investigations show that the titania nanowires preferentially sense cationic (e.g. Methylene Blue, Rhodamine B) over anionic (e.g. Orange G, Remazol Brilliant Blue R) dyes. The adsorbed dye concentration on titania nanowires increased with increase in nanowire dimensions and dye solution pH. Electrochemical sensing directly corroborated spectroscopic findings. Electrochemical detection sensitivity for Methylene Blue increased by more than two times in magnitude with tripling of nanowire average length. Photodegradation of Methylene Blue using titania nanowires is also more efficient than the commercial P25-TiO2 nanopowders. Keeping illumination protocol and observation times constant, the Methylene Blue concentration in solution decreased by only 50% in case of P25-TiO2 nanoparticles compared to a 100% decrease for titania nanowires. Photodegradation was also found to be function of exposure times and dye solution pH.Excellent sensing ability and photocatalytic activity of the titania nanowires is attributed to increased effective reaction area of the controlled nanostructured morphology. (C) 2010 Elsevier B.V. All rights reserved.