An automatable screen for the rapid identification of proteins amenable to refolding

Insoluble expression of heterologous proteins in Escherichia coli is a major bottleneck of many structural genomics and high-throughput protein biochemistry projects. Many of these proteins may be amenable to refolding, but their identification is hampered by a lack of high-throughput methods. We have developed a matrix-assisted refolding approach in which correctly folded proteins are distinguished from misfolded proteins by their elution from affinity resin under nondenaturing conditions. Misfolded proteins remain adhered to the resin, presumably via hydrophobic interactions. The assay can be applied to insoluble proteins on an individual basis but is particularly well suited for high-throughput applications because it is rapid, automatable and has no rigorous sample preparation requirements. The efficacy of the screen is demonstrated on small-scale expression samples for 15 proteins. Refolding is then validated by large-scale expressions using SEC and circular dichroism.

A PCR method for the identification of methicillin-resistant Staphylococcus aureus (MRSA) from screening swabs

Aim: The aim of this study was to assess the discriminatory power and potential turn around time ( TAT) of a PCR-based method for the detection of methicillin-resistant Staphylococcus aureus (MRSA) from screening swabs. Methods: Screening swabs were examined using the current laboratory protocol of direct culture on mannitol salt agar supplemented with oxacillin (MSAO-direct). The PCR method involved pre-incubation in broth for 4 hours followed by a multiplex PCR with primers directed to mecA and nuc genes of MRSA. The reference standard was determined by pre-incubation in broth for 4 hours followed by culture on MSAO (MSAO-broth). Results: A total of 256 swabs was analysed. The rates of detection of MRSA using MSAO-direct, MSAO-broth and PCR were 10.2, 13.3 and 10.2%, respectively. For PCR, the sensitivity, specificity, positive predictive value and negative predictive values were 66.7% (95% CI 51.9 - 83.3%), 98.6% ( 95% CI 97.1 - 100%), 84.6% ( 95% CI 76.2 - 100%) and 95.2% ( 95% CI 92.4 - 98.0%), respectively, and these results were almost identical to those obtained from MSAO-direct. The agreement between MSAO-direct and PCR was 61.5% ( 95% CI 42.8 - 80.2%) for positive results, 95.6% ( 95% CI 93.0 - 98.2%) for negative results and overall was 92.2% ( 95% CI 88.9 - 95.5%). Conclusions: ( 1) The discriminatory power of PCR and MSAO-direct is similar but the level of agreement, especially for true positive results, is low. ( 2) The potential TAT for the PCR method provides a marked advantage over conventional methods. ( 3) Further modifications to the PCR method such as increased broth incubation time, use of selective broth and adaptation to real-time PCR may lead to improvement in sensitivity and TAT.

SeqDoC: rapid SNP and mutation detection by direct comparison of DNA sequence chromatograms

Background: This paper describes SeqDoC, a simple, web-based tool to carry out direct comparison of ABI sequence chromatograms. This allows the rapid identification of single nucleotide polymorphisms (SNPs) and point mutations without the need to install or learn more complicated analysis software. Results: SeqDoC produces a subtracted trace showing differences between a reference and test chromatogram, and is optimised to emphasise those characteristic of single base changes. It automatically aligns sequences, and produces straightforward graphical output. The use of direct comparison of the sequence chromatograms means that artefacts introduced by automatic base-calling software are avoided. Homozygous and heterozygous substitutions and insertion/deletion events are all readily identified. SeqDoC successfully highlights nucleotide changes missed by the Staden package 'tracediff' program. Conclusion: SeqDoC is ideal for small-scale SNP identification, for identification of changes in random mutagenesis screens, and for verification of PCR amplification fidelity. Differences are highlighted, not interpreted, allowing the investigator to make the ultimate decision on the nature of the change.

A concept for hip prosthesis identification using ultra wideband radar

Ultra wideband (UWB) radar has been extensively investigated both theoretically and practically for the identification buried artifacts. Ground probe radar (GPR) concentrates on the identification of lightly buried land mines, unexploded ordnance (UXO) and archeological targets. The same technology is proposed in a similar context for the rapid identification of in vivo implanted metallic prostheses. The technique is based on resonance based target identification and the paper investigates UWB scattering from a metallic hip prosthesis in free space as a first step in the identification process.

Typing mineral deposits using their grades and tonnages in an artificial neural network

A test of the ability of a probabilistic neural network to classify deposits into types on the basis of deposit tonnage and average Cu, Mo, Ag, Au, Zn, and Pb grades is conducted. The purpose is to examine whether this type of system might serve as a basis for integrating geoscience information available in large mineral databases to classify sites by deposit type. Benefits of proper classification of many sites in large regions are relatively rapid identification of terranes permissive for deposit types and recognition of specific sites perhaps worthy of exploring further. Total tonnages and average grades of 1,137 well-explored deposits identified in published grade and tonnage models representing 13 deposit types were used to train and test the network. Tonnages were transformed by logarithms and grades by square roots to reduce effects of skewness. All values were scaled by subtracting the variable's mean and dividing by its standard deviation. Half of the deposits were selected randomly to be used in training the probabilistic neural network and the other half were used for independent testing. Tests were performed with a probabilistic neural network employing a Gaussian kernel and separate sigma weights for each class (type) and each variable (grade or tonnage). Deposit types were selected to challenge the neural network. For many types, tonnages or average grades are significantly different from other types, but individual deposits may plot in the grade and tonnage space of more than one type. Porphyry Cu, porphyry Cu-Au, and porphyry Cu-Mo types have similar tonnages and relatively small differences in grades. Redbed Cu deposits typically have tonnages that could be confused with porphyry Cu deposits, also contain Cu and, in some situations, Ag. Cyprus and kuroko massive sulfide types have about the same tonnages. Cu, Zn, Ag, and Au grades. Polymetallic vein, sedimentary exhalative Zn-Pb, and Zn-Pb skarn types contain many of the same metals. Sediment-hosted Au, Comstock Au-Ag, and low-sulfide Au-quartz vein types are principally Au deposits with differing amounts of Ag. Given the intent to test the neural network under the most difficult conditions, an overall 75% agreement between the experts and the neural network is considered excellent. Among the largestclassification errors are skarn Zn-Pb and Cyprus massive sulfide deposits classed by the neuralnetwork as kuroko massive sulfides—24 and 63% error respectively. Other large errors are the classification of 92% of porphyry Cu-Mo as porphyry Cu deposits. Most of the larger classification errors involve 25 or fewer training deposits, suggesting that some errors might be the result of small sample size. About 91% of the gold deposit types were classed properly and 98% of porphyry Cu deposits were classes as some type of porphyry Cu deposit. An experienced economic geologist would not make many of the classification errors that were made by the neural network because the geologic settings of deposits would be used to reduce errors. In a separate test, the probabilistic neural network correctly classed 93% of 336 deposits in eight deposit types when trained with presence or absence of 58 minerals and six generalized rock types. The overall success rate of the probabilistic neural network when trained on tonnage and average grades would probably be more than 90% with additional information on the presence of a few rock types.

Changes in equine hindgut bacterial populations during oligofructose-induced laminitis

In the horse, carbohydrate overload is thought to play an integral role in the onset of laminitis by drastically altering the profile of bacterial populations in the hindgut. The objectives of this study were to develop and validate microbial ecology methods to monitor changes in bacterial populations throughout the course of experimentally induced laminitis and to identify the predominant oligofructose-utilizing organisms. Laminitis was induced in five horses by administration of oligofructose. Faecal specimens were collected at 8 h intervals from 72 h before to 72 h after the administration of oligofructose. Hindgut microbiota able to utilize oligofructose were enumerated throughout the course of the experiment using habitat-simulating medium. Isolates were collected and representatives identified by 16S rRNA gene sequencing. The majority of these isolates collected belonged to the genus Streptococcus, 91% of which were identified as being most closely related to Streptococcus infantarius ssp. coli. Furthermore, S. infantarius ssp. coli was the predominant oligofructose-utilizing organism isolated before the onset of lameness. Fluorescence in situ hybridization probes developed to specifically target the isolated Streptococcus spp. demonstrated marked population increases between 8 and 16 h post oligofructose administration. This was followed by a rapid population decline which corresponded with a sharp decline in faecal pH and subsequently lameness at 24-32 h post oligofructose administration. This research suggests that streptococci within the Streptococcus bovis/equinus complex may be involved in the series of events which precede the onset of laminitis in the horse.

Taxonomy of Australian Funnel-web spiders using rp-HPLC/ESI-MS profiling techniques

The complex nature of venom from spider species offers a unique natural source of potential pharmacological tools and therapeutic leads. The increased interest in spider venom molecules requires reproducible and precise identification methods. The current taxonomy of the Australian Funnel-web spiders is incomplete, and therefore, accurate identification of these spiders is difficult. Here, we present a study of venom from numerous morphologically similar specimens of the Hadronyche infensa species group collected from a variety of geographic locations in southeast Queensland. Analysis of the crude venoms using online reversed-phase high performance liquid chromatography/electrospray ionisation mass spectrometry (rp-HPLC/ESI-MS) revealed that the venom profiles provide a useful means of specimen identification, from the species level to species variants. Tables defining the descriptor molecules for each group of specimens were constructed and provided a quick reference of the relationship between one specimen and another. The study revealed that the morphologically similar specimens from the southeast Queensland region are a number of different species/species variants. Furthermore, the study supports aspects of the current taxonomy with respect to the H. infensa species group. Analysis of Australian Funnel-web spider venom by rp-HPLC/ESI-MS provides a rapid and accurate method of species/species variant identification. (c) 2006 Elsevier Ltd. All rights reserved.

Participatory approach for the identification of dairy industry needs in the design of research, development and extension actions: Australian and Brazilian case studies

In both Australia and Brazil there are rapid changes occurring in the macroenvironment of the dairy industry. These changes are sometimes not noticed in the microenvironment of the farm, due to the labour-intensive nature of family farms, and the traditionally weak links between production and marketing. Trends in the external environment need to be discussed in a cooperative framework, to plan integrated actions for the dairy community as a whole and to demand actions from research, development and extension (R, D & E). This paper reviews the evolution of R, D & E in terms of paradigms and approaches, the present strategies used to identify dairy industry needs in Australia and Brazil, and presents a participatory strategy to design R, D & E actions for both countries. The strategy incorporates an integration of the opinions of key industry actors ( defined as members of the dairy and associated communities), especially farm suppliers ( input market), farmers, R, D & E people, milk processors and credit providers. The strategy also uses case studies with farm stays, purposive sampling, snowball interviewing techniques, semi-structured interviews, content analysis, focus group meetings, and feedback analysis, to refine the priorities for R, D & E actions in the region.

Rapid evolution of noncoding RNAs: lack of conservation does not mean lack of function

The mammalian transcriptome contains many nonprotein-coding RNAs (ncRNAs), but most of these are of unclear significance and lack strong sequence conservation, prompting suggestions that they might be non-functional. However, certain long functional ncRNAs such as Air and Xist are also poorly conserved. In this article, we systematically analyzed the conservation of several groups of functional ncRNAs, including miRNAs, snoRNAs and longer ncRNAs whose function has been either documented or confidently predicted. As expected, miRNAs and snoRNAs were highly conserved. By contrast, the longer functional non-micro, non-sno ncRNAs were much less conserved with many displaying rapid sequence evolution. Our findings suggest that longer ncRNAs are under the influence of different evolutionary constraints and that the lack of conservation displayed by the thousands of candidate ncRNAs does not necessarily signify an absence of function.

Development of a DNA-based method for detection and identification of Phytophthora species

Phytophthora diseases cause major losses to agricultural and horticultural production in Australia and worldwide. Most Phytophthora diseases are soilborne and difficult to control, making disease prevention an important component of many disease management strategies. Detection and identification of the causal agent, therefore, is an essential part of effective disease management. This paper describes the development and validation of a DNA-based diagnostic assay that can detect and identify 27 different Phytophthora species. We have designed PCR primers that are specific to the genus Phytophthora. The resulting amplicon after PCR is subjected to digestion by restriction enzymes to yield a specific restriction pattern or fingerprint unique to each species. The restriction patterns are compared with a key comprising restriction patterns of type specimens or representative isolates of 27 different Phytophthora species. A number of fundamental issues, such as genetic diversity within and among species which underpin the development and validation of DNA-based diagnostic assays, are addressed in this paper.