Ail Proteins of Yersinia pestis and Y. pseudotuberculosis Have Different Cell Binding and Invasion Activities

The Yersinia pestis adhesin Ail mediates host cell binding and facilitates delivery of cytotoxic Yop proteins. Ail from Y. pestis and Y. pseudotuberculosis is identical except for one or two amino acids at positions 43 and 126 depending on the Y. pseudotuberculosis strain. Ail from Y. pseudotuberculosis strain YPIII has been reported to lack host cell binding ability, thus we sought to determine which amino acid difference(s) are responsible for the difference in cell adhesion. Y. pseudotuberculosis YPIII Ail expressed in Escherichia coli bound host cells, albeit at ∼50% the capacity of Y. pestis Ail. Y. pestis Ail single mutants, Ail-E43D and Ail-F126V, both have decreased adhesion and invasion in E. coli when compared to wild-type Y. pestis Ail. Y. pseudotuberculosis YPIII Ail also had decreased binding to the Ail substrate fibronectin, relative to Y. pestis Ail in E. coli. When expressed in Y. pestis, there was a 30–50% decrease in adhesion and invasion depending on the substitution. Ail-mediated Yop delivery by both Y. pestis Ail and Y. pseudotuberculosis Ail were similar when expressed in Y. pestis, with only Ail-F126V giving a statistically significant reduction in Yop delivery of 25%. In contrast to results in E. coli and Y. pestis, expression of Ail in Y. pseudotuberculosis led to no measurable adhesion or invasion, suggesting the longer LPS of Y. pseudotuberculosis interferes with Ail cell-binding activity. Thus, host context affects the binding activities of Ail and both Y. pestis and Y. pseudotuberculosis Ail can mediate cell binding, cell invasion and facilitate Yop delivery.     

Arsenic Bioaccumulation in Freshwater Fishes

The arsenic ambient water quality criterion (AWQC) for protection of human health via ingestion of aquatic organisms is currently 0.14 μ g/L. This AWQC is derived using a bioconcentration factor (BCF) of 44, which is a consumption-weighted average based on two data points for oysters and fish that was proposed by the U.S. Environmental Protection Agency in 1980 for broad application to freshwater and marine environments. This BCF is based on the assumption that bioaccumulation is a simple linear function of the exposure concentration. In the nearly quarter of a century since this BCF was promulgated, there have been additions to the arsenic bioaccumulation database and a broader scientific understanding of bioaccumulation mechanisms and how they can be applied to estimating tissue concentrations in aquatic organisms. From this database, we identified 12 studies of arsenic bioaccumulation in freshwater fishes in order to explore differences in laboratory-generated BCFs and field-generated bioaccumulation factors (BAFs) and to assess their relationship to arsenic concentrations in water. Our analysis indicates that arsenic concentrations in tissue and arsenic BAFs may be power functions of arsenic concentration in water. A power function indicates that the highest BCF values may occur at low background levels and may decrease as environmental concentrations increase above the ambient range.     

Application of a bioinformatics training delivery method for reaching dispersed and distant trainees

Many initiatives have addressed the global need to upskill biologists in bioinformatics tools and techniques. Australia is not unique in its requirement for such training, but due to its large size and relatively small and geographically dispersed population, Australia faces specific challenges. A combined training approach was implemented by the authors to overcome these challenges. The “hybrid” method combines guidance from experienced trainers with the benefits of both webinar-style delivery and concurrent face-to-face hands-on practical exercises in classrooms. Since 2017, the hybrid method has been used to conduct 9 hands-on bioinformatics training sessions at international scale in which over 800 researchers have been trained in diverse topics on a range of software platforms. The method has become a key tool to ensure scalable and more equitable delivery of short-course bioinformatics training across Australia and can be easily adapted to other locations, topics, or settings.     

Attitudes Toward Weight Gain in Pregnancy

Recently, there has been increased interest in the influence of maternal prenatal nutrition on the course and outcome of pregnancy. Evidence has accumulated that a woman''s weight before pregnancy and the weight gained during pregnancy directly affect infant birth weight, incidence of neonatal mortality, and growth and development of the infant during the first year of life. Although recent recommendations for weight gain in pregnancy have been liberalized, a survey of 195 pregnant women who had prenatal visits in both clinic and private offices showed deficiencies in their understanding of the subject. Some 37 percent of women believed they should gain 20 pounds (9 kg) or less during pregnancy. Eight percent admitted to dieting before at least one antenatal visit and 54 percent thought their doctor would not be concerned about too little weight gained during pregnancy. This suggests that many women and some doctors are still ignorant of current concepts of proper nutrition during pregnancy. Apparently, increased lay and professional educational efforts are needed.     

Near-infrared spectroscopy for bioprocess monitoring and control.

This article describes the calibration of a spectroscopic scanning instrument for the measurement of selected contaminants in a complex biological process stream. Its use is for the monitoring of a process in which contaminants are to be removed selectively by flocculation from yeast cell homogenate. The main contaminants are cell debris, protein, and RNA. A low-cost instrument has been developed for sensitivity in the region of the NIR spectrum (from 1900 to 2500 nm) where preliminary work found NIR signatures from cell debris, protein, and RNA. Calibration models have been derived using a multivariate method for concentrations of these contaminants, such as would be found after the flocculation process. Two strategies were compared for calibrating the NIR instrument. In one case, samples were prepared by adding materials representative of the contaminants to clarified yeast homogenate so the contaminant levels were well known but outside the range of interest. In the other case, where samples were like those from the process stream after flocculation and floc removal, there was uncertainty of analysis of contaminant level, but the calibration was in the range of interest. Calibration using process stream samples gave results close to those derived from traditional assays. When the calibration models were used to predict the contaminant concentrations in previously unseen samples, the correlation coefficients between measurements and predictions were above 90% in all cases but one. The prediction errors were similar to the errors in the traditional assays.