3 resultados para Reagents

em eResearch Archive - Queensland Department of Agriculture


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A new test for pathogenic Leptospira isolates, based on RAPD-PCR and high-resolution melt (HRM) analysis (which measures the melting temperature of amplicons in real time, using a fluorescent DNA-binding dye), has recently been developed. A characteristic profile of the amplicons can be used to define serovars or detect genotypes. Ten serovars, of leptospires from the species Leptospira interrogans (serovars Australis, Robinsoni, Hardjo, Pomona, Zanoni, Copenhageni and Szwajizak), L. borgpetersenii (serovar Arborea), L. kirschneri (serovar Cynopteri) and L. weilii (serovar Celledoni), were typed against 13 previously published RAPD primers, using a real-time cycler (the Corbett Life Science RotorGene 6000) and the optimised reagents from a commercial kit (Quantace SensiMix). RAPD-HRM at specific temperatures generated defining amplicon melt profiles for each of the tested serovars. These profiles were evaluated as difference-curve graphs generated using the RotorGene software package, with a cut-off of at least 8 'U' (plus or minus). The results demonstrated that RAPD-HRM can be used to measure serovar diversity and establish identity, with a high degree of stability. The characterisation of Leptospira serotypes using a DNA-based methodology is now possible. As an objective and relatively inexpensive and rapid method of serovar identification, at least for cultured isolates, RAPD-HRM assays show convincing potentia.

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BACKGROUND: In order to rapidly and efficiently screen potential biofuel feedstock candidates for quintessential traits, robust high-throughput analytical techniques must be developed and honed. The traditional methods of measuring lignin syringyl/guaiacyl (S/G) ratio can be laborious, involve hazardous reagents, and/or be destructive. Vibrational spectroscopy can furnish high-throughput instrumentation without the limitations of the traditional techniques. Spectral data from mid-infrared, near-infrared, and Raman spectroscopies was combined with S/G ratios, obtained using pyrolysis molecular beam mass spectrometry, from 245 different eucalypt and Acacia trees across 17 species. Iterations of spectral processing allowed the assembly of robust predictive models using partial least squares (PLS). RESULTS: The PLS models were rigorously evaluated using three different randomly generated calibration and validation sets for each spectral processing approach. Root mean standard errors of prediction for validation sets were lowest for models comprised of Raman (0.13 to 0.16) and mid-infrared (0.13 to 0.15) spectral data, while near-infrared spectroscopy led to more erroneous predictions (0.18 to 0.21). Correlation coefficients (r) for the validation sets followed a similar pattern: Raman (0.89 to 0.91), mid-infrared (0.87 to 0.91), and near-infrared (0.79 to 0.82). These statistics signify that Raman and mid-infrared spectroscopy led to the most accurate predictions of S/G ratio in a diverse consortium of feedstocks. CONCLUSION: Eucalypts present an attractive option for biofuel and biochemical production. Given the assortment of over 900 different species of Eucalyptus and Corymbia, in addition to various species of Acacia, it is necessary to isolate those possessing ideal biofuel traits. This research has demonstrated the validity of vibrational spectroscopy to efficiently partition different potential biofuel feedstocks according to lignin S/G ratio, significantly reducing experiment and analysis time and expense while providing non-destructive, accurate, global, predictive models encompassing a diverse array of feedstocks.

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Puccinia psidii (Myrtle rust) is an emerging pathogen that has a wide host range in the Myrtaceae family; it continues to show an increase in geographic range and is considered to be a significant threat to Myrtaceae plants worldwide. In this study, we describe the development and validation of three novel real-time polymerase reaction (qPCR) assays using ribosomal DNA and β-tubulin gene sequences to detect P. psidii. All qPCR assays were able to detect P. psidii DNA extracted from urediniospores and from infected plants, including asymptomatic leaf tissues. Depending on the gene target, qPCR was able to detect down to 0.011 pg of P. psidii DNA. The most optimum qPCR assay was shown to be highly specific, repeatable, and reproducible following testing using different qPCR reagents and real-time PCR platforms in different laboratories. In addition, a duplex qPCR assay was developed to allow coamplification of the cytochrome oxidase gene from host plants for use as an internal PCR control. The most optimum qPCR assay proved to be faster and more sensitive than the previously published nested PCR assay and will be particularly useful for high-throughput testing and to detect P. psidii at the early stages of infection, before the development of sporulating rust pustules.