Susceptibility of different insect pupae to the bacterial symbiont, Xenorhabdus nematophila, isolated from the entomopathogenic nematode Steinernema carpocapsae

Cells of the bacterial symbiont Xenorhabdus nematophila from the entomopathogenic nematode, Steinernema carpocapsae entered the pupae of Plutella xylostella after 15 minutes treatment with suspensions containing the bacterial cells. Secretions of Xenorhabdus nematophila, in either broth or water, were found lethal to the pupae of P. xylostella when applied in moist sand. The bacterial symbiont Xenorhabdus nematophila was found lethal to the pupae of greater wax moth (Galleria mellonella), beet armyworm (Spodoptera exigua), diamondback moth (Plutella xylostella) and black vine weevil (Otiorhynchus sulcatus) in the absence of the nematode vector and the cells of X. nematophila entered the haemocoele of the pupae.

Inclusion of nonlinear demand-supply relationships within large-scale partial equilibrium linear programming models

This paper presents a new method for the inclusion of nonlinear demand and supply relationships within a linear programming model. An existing method for this purpose is described first and its shortcomings are pointed out before showing how the new approach overcomes those difficulties and how it provides a more accurate and 'smooth' (rather than a kinked) approximation of the nonlinear functions as well as dealing with equilibrium under perfect competition instead of handling just the monopolistic situation. The workings of the proposed method are illustrated by extending a previously available sectoral model for the UK agriculture.

Modeling small-scale dairy farms in central Mexico using multi-criteria programming

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multicriteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, rye-grass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Analysis of feeding strategies for small-scale dairy systems in central Mexico using linear programming

A limitation of small-scale dairy systems in central Mexico is that traditional feeding strategies are less effective when nutrient availability varies through the year. In the present work, a linear programming (LP) model that maximizes income over feed cost was developed, and used to evaluate two strategies: the traditional one used by the small-scale dairy producers in Michoacan State, based on fresh lucerne, maize grain and maize straw; and an alternative strategy proposed by the LIP model, based on ryegrass hay, maize silage and maize grain. Biological and economic efficiency for both strategies were evaluated. Results obtained with the traditional strategy agree with previously published work. The alternative strategy did not improve upon the performance of the traditional strategy because of low metabolizable protein content of the maize silage considered by the model. However, the Study recommends improvement of forage quality to increase the efficiency of small-scale dairy systems, rather than looking for concentrate supplementation.

Forage production and nutrient availability in small-scale dairy systems in central Mexico using linear programming and partial budgeting

Small-scale dairy systems play an important role in the Mexican dairy sector and farm planning activities related to resource allocation have a significant impact on the profitability of such enterprises. Linear programming is a technique widely used for planning and ration formulation, and partial budgeting is a technique for assessing the impact of changes on the profitability of an enterprise. This study used both methods to optimise land use for forage production and nutrient availability, and to evaluate the economic impact of such changes in small-scale Mexican dairy systems. The model showed satisfactory performance when optimal solutions were compared with the traditional strategy. The strategy using fresh ryegrass, maize silage and oat hay, and the strategy using a combination of alfalfa hay, maize silage, fresh ryegrass and oat hay appeared attractive options for providing a better nutrient supply and maintaining a higher stocking rate throughout the year than the traditional strategy.

Bacterial evolution by genomic island transfer occurs via DNA transformation in planta

Our understanding of the evolution of microbial pathogens has been advanced by the discovery of "islands" of DNA that differ from core genomes and contain determinants of virulence [1, 2]. The acquisition of genomic islands (GIs) by horizontal gene transfer (HGT) is thought to have played a major role in microbial evolution. There are, however, few practical demonstrations of the acquisition of genes that control virulence, and, significantly, all have been achieved outside the animal or plant host. Loss of a GI from the bean pathogen Pseudomonas syringae pv. phaseolicola (Pph) is driven by exposure to the stress imposed by the plant's resistance response [3]. Here, we show that the complete episomal island, which carries pathogenicity genes including the effector avrPphB, transfers between strains of Pph by transformation in planta and inserts at a specific att site in the genome of the recipient. Our results show that the evolution of bacterial pathogens by HGT may be achieved via transformation, the simplest mechanism of DNA exchange. This process is activated by exposure to plant defenses, when the pathogen is in greatest need of acquiring new genetic traits to alleviate the antimicrobial stress imposed by plant innate immunity [4].

EfeO-cupredoxins: major new members of the cupredoxin superfamily with roles in bacterial iron transport

The EfeUOB system of Escherichia coli is a tripartite, low pH, ferrous iron transporter. It resembles the high-affinity iron transporter (Ftr1p-Fet3p) of yeast in that EfeU is homologous to Ftr1p, an integral-membrane iron-permease. However, EfeUOB lacks an equivalent of the Fet3p component—the multicopper oxidase with three cupredoxin-like domains. EfeO and EfeB are periplasmic but their precise roles are unclear. EfeO consists primarily of a C-terminal peptidase-M75 domain with a conserved ‘HxxE’ motif potentially involved in metal binding. The smaller N-terminal domain (EfeO-N) is predicted to be cupredoxin (Cup) like, suggesting a previously unrecognised similarity between EfeO and Fet3p. Our structural modelling of the E. coli EfeO Cup domain identifies two potential metal-binding sites. Site I is predicted to bind Cu2+ using three conserved residues (C41 and 103, and E66) and M101. Of these, only one (C103) is conserved in classical cupredoxins where it also acts as a Cu ligand. Site II most probably binds Fe3+ and consists of four well conserved surface Glu residues. Phylogenetic analysis indicates that the EfeO-Cup domains form a novel Cup family, designated the ‘EfeO-Cup’ family. Structural modelling of two other representative EfeO-Cup domains indicates that different subfamilies employ distinct ligand sets at their proposed metal-binding sites. The ~100 efeO homologues in the bacterial sequence databases are all associated with various iron-transport related genes indicating a common role for EfeO-Cup proteins in iron transport, supporting a new copper-iron connection in biology.

Bacterial polysaccharides suppress induced innate immunity by calcium chelation

Bacterial pathogens and symbionts must suppress or negate host innate immunity. However, pathogens release conserved oligomeric and polymeric molecules or MAMPs (Microbial Associated Molecular Patterns), which elicit host defenses [1], [2] and [3]. Extracellular polysaccharides (EPSs) are key virulence factors in plant and animal pathogenesis, but their precise function in establishing basic compatibility remains unclear [4], [5], [6] and [7]. Here, we show that EPSs suppress MAMP-induced signaling in plants through their polyanionic nature [4] and consequent ability to chelate divalent calcium ions [8]. In plants, Ca2+ ion influx to the cytosol from the apoplast (where bacteria multiply [4], [5] and [9]) is a prerequisite for activation of myriad defenses by MAMPs [10]. We show that EPSs from diverse plant and animal pathogens and symbionts bind calcium. EPS-defective mutants or pure MAMPs, such as the flagellin peptide flg22, elicit calcium influx, expression of host defense genes, and downstream resistance. Furthermore, EPSs, produced by wild-type strains or purified, suppress induced responses but do not block flg22-receptor binding in Arabidopsis cells. EPS production was confirmed in planta, and the amounts in bacterial biofilms greatly exceed those required for binding of apoplastic calcium. These data reveal a novel, fundamental role for bacterial EPS in disease establishment, encouraging novel control strategies.

Overview of mathematical approaches used to model bacterial chemotaxis I: the single cell

Mathematical modeling of bacterial chemotaxis systems has been influential and insightful in helping to understand experimental observations. We provide here a comprehensive overview of the range of mathematical approaches used for modeling, within a single bacterium, chemotactic processes caused by changes to external gradients in its environment. Specific areas of the bacterial system which have been studied and modeled are discussed in detail, including the modeling of adaptation in response to attractant gradients, the intracellular phosphorylation cascade, membrane receptor clustering, and spatial modeling of intracellular protein signal transduction. The importance of producing robust models that address adaptation, gain, and sensitivity are also discussed. This review highlights that while mathematical modeling has aided in understanding bacterial chemotaxis on the individual cell scale and guiding experimental design, no single model succeeds in robustly describing all of the basic elements of the cell. We conclude by discussing the importance of this and the future of modeling in this area.

Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller-Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.

Developmental programming: Deficits in reproductive hormone dynamics and ovulatory outcomes in prenatal, testosterone-treated sheep

Prenatal testosterone excess leads to neuroendocrine, ovarian, and metabolic disruptions, culminating in reproductive phenotypes mimicking that of women with polycystic ovary syndrome (PCOS). The objective of this study was to determine the consequences of prenatal testosterone treatment on periovulatory hormonal dynamics and ovulatory outcomes. To generate prenatal testosterone-treated females, pregnant sheep were injected intramuscularly (days 30-90 of gestation, term = 147 days) with 100 mg of testosterone-propionate in cottonseed oil semi-weekly. Female offspring born to untreated control females and prenatal testosterone-treated females were then studied during their first two breeding seasons. Sheep were given two injections of prostaglandin F-2alpha 11 days apart, and blood samples were collected at 2-h intervals for 120 h, 10-min intervals for 8 h during the luteal phase (first breeding season only), and daily for an additional 15 days to characterize changes in reproductive hormonal dynamics. During the first breeding season, prenatal testosterone-treated females manifested disruptions in the timing and magnitude of primary gonadotropin surges, luteal defects, and reduced responsiveness to progesterone negative feedback. Disruptions in the periovulatory sequence of events during the second breeding season included: 1) delayed but increased preovulatory estradiol rise, 2) delayed and severely reduced primary gonadotropin surge in prenatal testosterone-treated females having an LH surge, 3) tendency for an amplified secondary FSH surge and a shift in the relative balance of FSH regulatory proteins, and 4) luteal responses that ranged from normal to anovulatory. These outcomes are likely to be of relevance to developmental origin of infertility disorders and suggest that differences in fetal exposure or fetal susceptibility to testosterone may account for the variability in reproductive phenotypes.