Cadmium leachability and microbial population dynamics in a stabilized and bioaugmented model contaminated soil

This article presents a laboratory study on the consequences of the application of combined soil stabilization and bioaugmentation in the remediation of a model contaminated soil. Stabilization and bioaugmentation are two techniques commonly applied independently for the remediation of heavy metal and organic contamination respectively. However, for a cocktail of contaminants combined treatments are currently being considered. The model soil was contaminated with a cocktail of organics and heavy metals based on the soil and contaminant conditions in a real contaminated site. The soil stabilization treatment was applied using either zeolite or green waste compost as additives and a commercially available hydrocarbon degrading microbial consortium was used for the bioaugmentation treatment. The effects of stabilization with or without bioaugmentation on the leachability of cadmium and copper was observed using an EU batch leaching test procedure and a flow-through column leaching test, both using deionized water at a pH of 5.6. In addition, the population of hydrocarbon degrading microorganisms was monitored using a modified plate count procedure in cases where bioaugmentation was applied. It was found that while the stabilization treatment reduced the metal leachability by up to 60%, the bioaugmentation treatment increased it by up to 100% Microbial survival was also higher in the stabilized soil samples.

Effect of microbial activities on the mobility of copper in stabilised contaminated soil

Stabilisation, using a wide range of binders including wastes, is most effective for heavy metal soil contamination. Bioremediation techniques, including bioaugmentation to enhance soil microbial population, are most effective for organic contaminants in the soil. For mixed contaminant scenarios a combination of these two techniques is currently being investigated. An essential issue in this combined remediation system is the effect of microbial processes on the leachability of the heavy metals. This paper considers the use of zeolite and compost as binder additives combined with bioaugmentation treatments and their effect on copper leachability in a model contaminated soil. Different leaching test conditions are considered including both NRA and TCLP batch leaching tests as well as flow-through column tests. Two flow rates are applied in the flow-through tests and the two leaching tests are compared. Recommendations are given as to the effectiveness of this combined remediation technique in the immobilisation of copper. © 2005 Taylor & Francis Group.

Spread of Salmonella enterica in the body during systemic infection: unravelling host and pathogen determinants.

Salmonella enterica causes a range of life-threatening diseases in humans and animals worldwide. Current treatments for S. enterica infections are not sufficiently effective, and there is a need to develop new vaccines and therapeutics. An understanding of how S. enterica spreads in tissues has very important implications for targeting bacteria with vaccine-induced immune responses and antimicrobial drugs. Development of new control strategies would benefit from a more sophisticated evaluation of bacterial location, spatiotemporal patterns of spread and distribution in the tissues, and sites of microbial persistence. We review here recent studies of S. enterica serovar Typhimurium (S. Typhimurium) infections in mice, an established model of systemic typhoid fever in humans, which suggest that continuous bacterial spread to new infection foci and host phagocytes is an essential trait in the virulence of S. enterica during systemic infections. We further highlight how infections within host tissues are truly heterogeneous processes despite the fact that they are caused by the expansion of a genetically homogeneous microbial population. We conclude by discussing how understanding the within-host quantitative, spatial and temporal dynamics of S. enterica infections might aid the development of novel targeted preventative measures and drug regimens.

Modelling within-host spatiotemporal dynamics of invasive bacterial disease

Mechanistic determinants of bacterial growth, death, and spread within mammalian hosts cannot be fully resolved studying a single bacterial population. They are also currently poorly understood. Here, we report on the application of sophisticated experimental approaches to map spatiotemporal population dynamics of bacteria during an infection. We analyzed heterogeneous traits of simultaneous infections with tagged Salmonella enterica populations (wild-type isogenic tagged strains [WITS]) in wild-type and gene-targeted mice. WITS are phenotypically identical but can be distinguished and enumerated by quantitative PCR, making it possible, using probabilistic models, to estimate bacterial death rate based on the disappearance of strains through time. This multidisciplinary approach allowed us to establish the timing, relative occurrence, and immune control of key infection parameters in a true host-pathogen combination. Our analyses support a model in which shortly after infection, concomitant death and rapid bacterial replication lead to the establishment of independent bacterial subpopulations in different organs, a process controlled by host antimicrobial mechanisms. Later, decreased microbial mortality leads to an exponential increase in the number of bacteria that spread locally, with subsequent mixing of bacteria between organs via bacteraemia and further stochastic selection. This approach provides us with an unprecedented outlook on the pathogenesis of S. enterica infections, illustrating the complex spatial and stochastic effects that drive an infectious disease. The application of the novel method that we present in appropriate and diverse host-pathogen combinations, together with modelling of the data that result, will facilitate a comprehensive view of the spatial and stochastic nature of within-host dynamics. © 2008 Grant et al.

Population of nonnative states of lysozyme variants drives amyloid fibril formation.

The propensity of protein molecules to self-assemble into highly ordered, fibrillar aggregates lies at the heart of understanding many disorders ranging from Alzheimer's disease to systemic lysozyme amyloidosis. In this paper we use highly accurate kinetic measurements of amyloid fibril growth in combination with spectroscopic tools to quantify the effect of modifications in solution conditions and in the amino acid sequence of human lysozyme on its propensity to form amyloid fibrils under acidic conditions. We elucidate and quantify the correlation between the rate of amyloid growth and the population of nonnative states, and we show that changes in amyloidogenicity are almost entirely due to alterations in the stability of the native state, while other regions of the global free-energy surface remain largely unmodified. These results provide insight into the complex dynamics of a macromolecule on a multidimensional energy landscape and point the way for a better understanding of amyloid diseases.