Development of a high-throughput enzyme-linked immunosorbent assay for the routine detection of the carcinogen acrylamide in food, via rapid derivatisation pre-analysis

The spontaneous formation of the neurotoxic carcinogen acrylamide in a wide range of cooked foods has recently been discovered. These foods include bread and other bakery products, crisps, chips, breakfast cereals, and coffee. To date, the diminutive size of acrylamide (71.08Da) has prevented the development of screening immunoassays for this chemical. In this study, a polyclonal antibody capable of binding the carcinogen was produced by the synthesis of an immunogen comprising acrylamide derivatised with 3-mercaptobenzoic acid (3-MBA), and its conjugation to the carrier protein bovine thyroglobulin. Antiserum from the immunised rabbit was harvested and fully characterised. it displayed no binding affinity for acrylamide or 3-MBA but had a high affinity for 3-MBA-derivitised acrylamide. The antisera produced was utilised in the development of an ELISA based detection system for acrylamide. Spiked water samples were assayed for acrylamide content using a previously published extraction method validated for coffee, crispbread, potato, milk chocolate and potato crisp matrices. Extracted acrylamide was then subjected to a rapid 1-h derivatisation with 3-MBA, pre-analysis. The ELISA was shown to have a high specificity for acrylamide, with a limit of detection in water samples of 65.7 mu g kg(-1), i.e. potentially suitable for acrylamide detection in a wide range of food commodities. Future development of this assay will increase sensitivity further. This is the first report of an immunoassay capable of detecting the carcinogen, as its small size has necessitated current analytical detection via expensive, slower, physico-chemical techniques such as Gas or Liquid Chromatography coupled to Mass Spectrometry. (c) 2007 Elsevier B.V. All rights reserved.

Part-whole relations between food webs and the validity of local food-web descriptions

This work analyzes the relationship between large food webs describing potential feeding relations between species and smaller sub-webs thereof describing relations actually realized in local communities of various sizes. Special attention is given to the relationships between patterns of phylogenetic correlations encountered in large webs and sub-webs. Based on the current theory of food-web topology as implemented in the matching model, it is shown that food webs are scale invariant in the following sense: given a large web described by the model, a smaller, randomly sampled sub-web thereof is described by the model as well. A stochastic analysis of model steady states reveals that such a change in scale goes along with a re-normalization of model parameters. Explicit formulae for the renormalized parameters are derived. Thus, the topology of food webs at all scales follows the same patterns, and these can be revealed by data and models referring to the local scale alone. As a by-product of the theory, a fast algorithm is derived which yields sample food webs from the exact steady state of the matching model for a high-dimensional trophic niche space in finite time. (C) 2008 Elsevier B.V. All rights reserved.

Food webs: Experts consuming families of experts

Food webs of habitats as diverse as takes or desert valleys are known to exhibit common

Some properties of the speciation model for food-web structure - Mechanisms for degree distributions and intervality

We present a mathematical analysis of the speciation model for food-web structure, which had in previous work been shown to yield a good description of empirical data of food-web topology. The degree distributions of the network are derived. Properties of the speciation model are compared to those of other models that successfully describe empirical data. It is argued that the speciation model unities the underlying ideas of previous theories. In particular, it offers a mechanistic explanation for the success of the niche model of Williams and Martinez and the frequent observation of intervality in empirical food webs. (c) 2005 Elsevier Ltd. All rights reserved.

An explanatory model for food-web structure and evolution

Food webs are networks describing who is eating whom in an ecological community. By now it is clear that many aspects of food-web structure are reproducible across diverse habitats, yet little is known about the driving force behind this structure. Evolutionary and population dynamical mechanisms have been considered. We propose a model for the evolutionary dynamics of food-web topology and show that it accurately reproduces observed food-web characteristics in the steady state. It is based on the observation that most consumers are larger than their resource species and the hypothesis that speciation and extinction rates decrease with increasing body mass. Results give strong support to the evolutionary hypothesis. (C) 2005 Elsevier B.V. All rights reserved.

Soil resource supply influences faunal size-specific distributions in natural food webs

The large range of body-mass values of soil organisms provides a tool to assess the ecological organization of soil communities. The goal of this paper is to identify graphical and quantitative indicators of soil community composition and ecosystem functioning, and to illustrate their application to real soil food webs. The relationships between log-transformed mass and abundance of soil organisms in 20 Dutch meadows and heathlands were investigated. Using principles of allometry, maximal use can be made of ecological theory to build and explain food webs. The aggregate contribution of small invertebrates such as nematodes to the entire community is high under low soil phosphorus content and causes shifts in the mass-abundance relationships and in the trophic structures. We show for the first time that the average of the trophic link lengths is a reliable predictor for assessing soil fertility responses. Ordered trophic link pairs suggest a self-organizing structure of food webs according to resource availability and can predict environmental shifts in ecologically meaningful ways.