Culture independent analysis of greyback canegrub-associated microflora and microbial community comparison using subtractive hybridisation

Greyback canegrubs cost the Australian sugarcane industry around $13 million per annum in damage and control. A novel and cost effective biocontrol bacterium could play an important role in the integrated pest management program currently in place to reduce damage and control associated costs. During the course of this project, terminal restriction fragment length polymorphism (TRFLP), 16-S rDNA cloning, suppressive subtractive hybridisation (SSH) and entomopathogen-specific PCR screening were used to investigate the little studied canegrub-associated microflora in an attempt to discover novel pathogens from putatively-diseased specimens. Microflora associated with these soil-dwelling insects was found to be both highly diverse and divergent between individual specimens. Dominant members detected in live specimens were predominantly from taxa of known insect symbionts while dominant sequences amplified from dead grubs were homologous to putativelysaprophytic bacteria and bacteria able to grow during refrigeration. A number of entomopathogenic bacteria were identified such as Photorhabdus luminescens and Pseudomonas fluorescens. Dead canegrubs prior to decomposition need to be analysed if these bacteria are to be isolated. Novel strategies to enrich putative pathogen-associated sequences (SSH and PCR screening) were shown to be promising approaches for pathogen discovery and the investigation of canegrubsassociated microflora. However, due to inter- and intra-grub-associated community diversity, dead grub decomposition and PCR-specific methodological limitations (PCR bias, primer specificity, BLAST database restrictions, 16-S gene copy number and heterogeneity), recommendations have been made to improve the efficiency of such techniques. Improved specimen collection procedures and utilisation of emerging high-throughput sequencing technologies may be required to examine these complex communities in more detail. This is the first study to perform a whole-grub analysis and comparison of greyback canegrub-associated microbial communities. This work also describes the development of a novel V3-PCR based SSH technique. This was the first SSH technique to use V3-PCR products as a starting material and specifically compare bacterial species present in a complex community.

Differences in the performance of safety performance functions estimated for total crash count and for crash count by crash type

In recent years the development and use of crash prediction models for roadway safety analyses have received substantial attention. These models, also known as safety performance functions (SPFs), relate the expected crash frequency of roadway elements (intersections, road segments, on-ramps) to traffic volumes and other geometric and operational characteristics. A commonly practiced approach for applying intersection SPFs is to assume that crash types occur in fixed proportions (e.g., rear-end crashes make up 20% of crashes, angle crashes 35%, and so forth) and then apply these fixed proportions to crash totals to estimate crash frequencies by type. As demonstrated in this paper, such a practice makes questionable assumptions and results in considerable error in estimating crash proportions. Through the use of rudimentary SPFs based solely on the annual average daily traffic (AADT) of major and minor roads, the homogeneity-in-proportions assumption is shown not to hold across AADT, because crash proportions vary as a function of both major and minor road AADT. For example, with minor road AADT of 400 vehicles per day, the proportion of intersecting-direction crashes decreases from about 50% with 2,000 major road AADT to about 15% with 82,000 AADT. Same-direction crashes increase from about 15% to 55% for the same comparison. The homogeneity-in-proportions assumption should be abandoned, and crash type models should be used to predict crash frequency by crash type. SPFs that use additional geometric variables would only exacerbate the problem quantified here. Comparison of models for different crash types using additional geometric variables remains the subject of future research.

Health risk from the use of roof-harvested rainwater in Southeast Queensland, Australia, as potable or nonpotable water, determined using quantitative microbial risk assessment

A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analysed for the zoonotic bacterial and protozoan pathogen using real-time binary PCR and quantitative PCR (qPCR). Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from potable and non-potable uses of roof-harvested rainwater. Of the 214 samples tested, 10.7%, 9.8%, and 5.6%, and 0.4% samples were positive for Salmonella invA, Giardia lamblia β-giardin , Legionella pneumophila mip, and Campylobacter jejuni mapA genes. Cryptosporidium parvum could not be detected. The estimated numbers of viable Salmonella spp., G. lamblia β-giradin, and L. pneumophila genes ranged from 1.6 × 101 to 9.5 × 101 cells, 1.4 × 10-1 to 9.0 × 10-1 cysts, and 1.5 × 101 to 4.3 × 101 per 1000 ml of water, respectively. Six risk scenarios were considered from exposure to Salmonella spp., G. lamblia and L. pneumophila. For Salmonella spp., and G. lamblia, these scenarios were: (1) liquid ingestion due to drinking of rainwater on a daily basis (2) accidental liquid ingestion due to garden hosing twice a week (3) aerosol ingestion due to showering on a daily basis, and (4) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were: (5) aerosol inhalation due to showering on a daily basis, and (6) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeds this threshold value, and indicates that if undisinfected rainwater were ingested by drinking, then the gastrointestinal diseases of Salmonellosis and Giardiasis is expected to range from 5.0 × 100 to 2.8 × 101 (Salmonellosis) and 1.0 × 101 to 6.4 × 101 (Giardiasis) cases per 10,000 persons per year, respectively. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for potable use.

Networked aquatic microbial observing systems: An overview

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Ability of silver-impregnated contact lenses to control microbial growth and colonisation

Purpose: To examine the ability of silver nano-particles to prevent the growth of Pseudomonas aeruginosa and Staphylococcus aureus in solution or when adsorbed into contact lenses. To examine the ability of silver nano-particles to prevent the growth of Acanthamoeba castellanii. ----- ----- Methods: Etafilcon A lenses were soaked in various concentrations of silver nano-particles. Bacterial cells were then exposed to these lenses, and numbers of viable cells on lens surface or in solution compared to etafilcon A lenses not soaked in silver. Acanthamoeba trophozoites were exposed to silver nano-particles and their ability to form tracks was examined. ----- ----- Results: Silver nano-particle containing lenses reduced bacterial viability and adhesion. There was a dose-dependent response curve, with 10 ppm or 20 ppm silver showing > 5 log reduction in bacterial viability in solution or on the lens surface. For Acanthamoeba, 20 ppm silver reduced the ability to form tracks by approximately 1 log unit. ----- ----- Conclusions: Silver nanoparticles are effective antimicrobial agents, and can reduce the ability of viable bacterial cells to colonise contact lenses once incorporated into the lens.----- ----- Resumen: Objetivos: Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Pseudomonas aeruginosa y Staphylococcus aureus en soluciones para lentes de contacto o cuando éstas las adsorben. Examinar la capacidad de las nanopartículas de plata para prevenir el crecimiento de Acanthamoeba castellanii.----- ----- Métodos: Se sumergieron lentes etafilcon A en diversas concentraciones de nanopartículas de plata. Las células bacterianas fueron posteriormente expuestas a dichas lentes, y se compararon cantidades de células viables en la superficie de la lente o en la solución con las presentes en lentes etafilcon A que no habían sido sumergidas en plata. Trofozoítos de Acanthamoeba fueron expuestos a nanopartículas de plata y se examinó su capacidad para formar quistes.----- ----- Resultados: Las lentes que contienen nanopartículas de plata redujeron la viabilidad bacteriana y la adhesión. Hubo una curva de respuesta dependiente de la dosis, en la que 10 ppm o 20 ppm de plata mostró una reducción logarítmica > 5 en la viabilidad bacteriana tanto en la solución como en la superficie de la lente. Para Acanthamoeba, 20 ppm de plata redujeron la capacidad de formar quistes en aproximadamente 1 unidad logarítmica.----- ----- Conclusiones: Las nanopartículas de plata son agentes antimicrobianos eficaces y pueden reducir la capacidad de células bacterianas viables para colonizar las lentes de contacto una vez que se han incorporado en la lente.

Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

Using data mining to predict road crash count with a focus on skid resistance values

Road crashes cost world and Australian society a significant proportion of GDP, affecting productivity and causing significant suffering for communities and individuals. This paper presents a case study that generates data mining models that contribute to understanding of road crashes by allowing examination of the role of skid resistance (F60) and other road attributes in road crashes. Predictive data mining algorithms, primarily regression trees, were used to produce road segment crash count models from the road and traffic attributes of crash scenarios. The rules derived from the regression trees provide evidence of the significance of road attributes in contributing to crash, with a focus on the evaluation of skid resistance.

Tubal damage, infertility and tubal ectopic pregnancy : chlamydia trachomatis and other microbial aetiologies

Infertility is a worldwide health problem with one in six couples suffering from this condition and with a major economic burden on the global healthcare industry. Estimates of the current global infertility rate suggest that 15% of couples are infertile (Zegers-Hochschild et al 2009) defined as: (1) failure to conceive after 12 months of unprotected sexual intercourse (i.e. infertility); (2) repeated implantation failure following ART cycles; or (3) recurrent miscarriage without difficulty conceiving (natural conceptions). Tubal factor infertility is among the leading causes of female factor infertility accounting for 7-9.8% of all female factor infertilities. Tubal disease directly causes from 36% to 85% of all cases of female factor infertility in developed and developing nations respectively and is associated with polymicrobial aetiologies. One of the leading global causes of tubal factor infertility is thought to be symptomatic (and asymptomatic in up to 70% cases) infection of the female reproductive tract with the sexually transmitted pathogen, Chlamydia trachomatis. Infection-related damage to the Fallopian tubes caused by Chlamydia accounts for more than 70% of cases of infertility in women from developing nations such as sub-Saharan Africa (Sharma et al 2009). Bacterial vaginosis, a condition associated with increased transmission of sexually transmitted infections including those caused by Neisseria gonorrhoeae and Mycoplasma genitalium is present in two thirds of women with pelvic inflammatory disease (PID). This review will focus on (1) the polymicrobial aetiologies of tubal factor infertility and (2) studies involved in screening for, and treatment and control of, Chlamydial infection to prevent PID and the associated sequelae of Fallopian tube inflammation that may lead to infertility and ectopic pregnancy.