The use of Escherichia coli bearing a phoN gene for the removal of uranium and nickel from aqueous flows

A Citrobacter sp. originally isolated from metal-polluted soil accumulates heavy metals via metal-phosphate deposition utilizing inorganic phosphate liberated via PhoN phosphatase activity. Further strain development was limited by the non-transformability of this environmental isolate. Recombinant Escherichia coli DH5α bearing cloned phoN or the related phoC acquired metal-accumulating ability, which was compared with that of the Citrobacter sp. with respect to removal of uranyl ion (UO₂ ²⁺) from dilute aqueous flows and its deposition in the form of polycrystalline hydrogen uranyl phosphate (HUO₂PO₄). Subsequently, HUO₂PO₄-laden cells removed Ni²⁺ from dilute aqueous flows via intercalation of Ni²⁺ into the HUO₂PO₄ lattice. Despite comparable acid phosphatase activity in all three strains, the E. coli DH5α (phoN) construct was superior to Citrobacter N14 in both uranyl and nickel accumulation, while the E. coli DH5α (phoC) construct was greatly inferior in both respects. Expression of phosphatase activity alone is not the only factor that permits efficient and prolonged metal phosphate accumulation, and the data highlight possible differences in the PhoN and PhoC phosphatases, which are otherwise considered to be related in many respects. Received: 30 December 1997 / Received revision: 25 March 1998 / Accepted: 26 March 1998     

fastSTRUCTURE: Variational Inference of Population Structure in Large SNP Data Sets

Tools for estimating population structure from genetic data are now used in a wide variety of applications in population genetics. However, inferring population structure in large modern data sets imposes severe computational challenges. Here, we develop efficient algorithms for approximate inference of the model underlying the STRUCTURE program using a variational Bayesian framework. Variational methods pose the problem of computing relevant posterior distributions as an optimization problem, allowing us to build on recent advances in optimization theory to develop fast inference tools. In addition, we propose useful heuristic scores to identify the number of populations represented in a data set and a new hierarchical prior to detect weak population structure in the data. We test the variational algorithms on simulated data and illustrate using genotype data from the CEPH–Human Genome Diversity Panel. The variational algorithms are almost two orders of magnitude faster than STRUCTURE and achieve accuracies comparable to those of ADMIXTURE. Furthermore, our results show that the heuristic scores for choosing model complexity provide a reasonable range of values for the number of populations represented in the data, with minimal bias toward detecting structure when it is very weak. Our algorithm, fastSTRUCTURE, is freely available online at http://pritchardlab.stanford.edu/structure.html.     

A social science view on the FRAME symposium: identities and networks

This paper, written by two social scientists, presents a social science perspective on the issues raised at the FRAME symposium on Human Alternatives to Animal Studies. Drawing upon the authors' experience of conducting research with stem cell scientists, issues around access to human tissue for in vitro uses are considered. The paper concludes by raising questions pertinent to both interested social scientists and the Three Rs agenda.     

Bacteria in cancer therapy: a novel experimental strategy

Resistance to conventional anticancer therapies in patients with advanced solid tumors has prompted the need of alternative cancer therapies. Moreover, the success of novel cancer therapies depends on their selectivity for cancer cells with limited toxicity to normal tissues. Several decades after Coley's work a variety of natural and genetically modified non-pathogenic bacterial species are being explored as potential antitumor agents, either to provide direct tumoricidal effects or to deliver tumoricidal molecules. Live, attenuated or genetically modified non-pathogenic bacterial species are capable of multiplying selectively in tumors and inhibiting their growth. Due to their selectivity for tumor tissues, these bacteria and their spores also serve as ideal vectors for delivering therapeutic proteins to tumors. Bacterial toxins too have emerged as promising cancer treatment strategy. The most potential and promising strategy is bacteria based gene-directed enzyme prodrug therapy. Although it has shown successful results in vivo yet further investigation about the targeting mechanisms of the bacteria are required to make it a complete therapeutic approach in cancer treatment.     

Evaluation of extraction processes for intracellular metabolite profiling of mammalian cells: matching extraction approaches to cell type and metabolite targets

In this study we report on the optimisation of the technologies for generation of a global metabolomics profile for intracellular metabolites in Chinese hamster ovary (CHO) cells. We evaluated the effectiveness of a range of different extraction methods applied to CHO cells which had been quenched using a previously optimised approach. The extraction methods tested included cold methanol, hot ethanol, acid, alkali and methanol/chloroform plus combinations of these. The extraction of metabolites using two 100% methanol extractions followed by a final water extraction recovered the largest range of metabolites. For the majority of metabolites, extracts generated in this manner exhibited the greatest recovery with high reproducibility. Therefore, this was the best extraction method for attaining a global metabolic profile from a single sample. However, another parallel extraction method (e.g. alkali) may also be required to maximise the range of metabolites recovered (e.g. non-polar metabolites).     

Production of haploids and doubled haploids in oil palm

Background

Studies on host-pathogen interactions in a range of pathosystems have revealed an array of mechanisms by which plants reduce the efficiency of pathogenesis. While R-gene mediated resistance confers highly effective defense responses against pathogen invasion, quantitative resistance is associated with intermediate levels of resistance that reduces disease progress. To test the hypothesis that specific loci affect distinct stages of fungal pathogenesis, a set of maize introgression lines was used for mapping and characterization of quantitative trait loci (QTL) conditioning resistance to Setosphaeria turcica, the causal agent of northern leaf blight (NLB). To better understand the nature of quantitative resistance, the identified QTL were further tested for three secondary hypotheses: (1) that disease QTL differ by host developmental stage; (2) that their performance changes across environments; and (3) that they condition broad-spectrum resistance.

Results

Among a set of 82 introgression lines, seven lines were confirmed as more resistant or susceptible than B73. Two NLB QTL were validated in BC₄F₂ segregating populations and advanced introgression lines. These loci, designated qNLB1.02 and qNLB1.06, were investigated in detail by comparing the introgression lines with B73 for a series of macroscopic and microscopic disease components targeting different stages of NLB development. Repeated greenhouse and field trials revealed that qNLB1.06 _Tx303 (the Tx303 allele at bin 1.06) reduces the efficiency of fungal penetration, while qNLB1.02 _B73 (the B73 allele at bin 1.02) enhances the accumulation of callose and phenolics surrounding infection sites, reduces hyphal growth into the vascular bundle and impairs the subsequent necrotrophic colonization in the leaves. The QTL were equally effective in both juvenile and adult plants; qNLB1.06 _Tx303 showed greater effectiveness in the field than in the greenhouse. In addition to NLB resistance, qNLB1.02 _B73 was associated with resistance to Stewart's wilt and common rust, while qNLB1.06 _Tx303 conferred resistance to Stewart's wilt. The non-specific resistance may be attributed to pleiotropy or linkage.

Conclusions

Our research has led to successful identification of two reliably-expressed QTL that can potentially be utilized to protect maize from S. turcica in different environments. This approach to identifying and dissecting quantitative resistance in plants will facilitate the application of quantitative resistance in crop protection.