Elise Billoir

Modeling microbial competition in food: Application to the behavior of Listeria monocytogenes and lactic acid flora in pork meat products

Competition between background microflora and microbial pathogens raises questions about the application of predictive microbiology in situ, i.e., in non-sterile naturally contaminated foods. In this article, we present a review of the models developed in predictive microbiology to describe interactions between microflora in foods, with a special focus on two approaches: one based on the Jameson effect (simultaneous deceleration of all microbial populations) and one based on the Lotka-Volterra competition model. As an illustration of the potential of these models, we propose various modeling examples in estimation and in prediction of microbial growth curves, all related to the behavior of Listeria monocytogenes with lactic acid bacteria in three pork meat products (fresh pork meat and two types of diced bacon).

Statistical cautions when estimating DEBtox parameters

DEBtox (Dynamic Energy Budget in toxicology) models have been designed to analyse various results from classic tests in ecotoxicology. They consist of a set of mechanistic models describing how organisms manage their energy, when they are exposed to a contaminant. Until now, such a biology-based modeling approach has not been used within the regulatory context. However, these methods have been promoted and discussed in recent guidance documents on the statistical analysis of ecotoxicity data. Indeed, they help us to understand the underlying mechanisms. In this paper, we focused on the 21 day Daphnia magna reproduction test. We first aimed to clarify and detail the model building process leading to DEBtox models. Equations were rederived step by step, and for some of them we obtained results different from the published ones. Then, we statistically evaluated the estimation process quality when using a least squares approach. Using both experimental and simulated data, our analyses highlighted several statistical issues related to the fitting of DEBtox models on OECD-type reproduction data. In this case, particular attention had to be paid to parameter estimates and the interpretation of their confidence intervals.

WHAT TO DO WITH NOECS/NOELS—PROHIBITION OR INNOVATION?

This study attempted to be as realistic as possible when evaluating third-hand PAH residues resulting from 1 cigarette. Smokers were not asked to change their smoking habits, except to continuously hold the cigarette in 1 hand during the entire duration of the cigarette’s burning. Hand size (that is, the adsorptive surface area), duration of smoking, and environmental conditions such as wind, temperature, and humidity, in addition to other factors, may potentially influence PAH concentration. We conducted our third-hand smoke studies outdoors under environmental conditions, and therefore hypothesize that a similar study conducted in the more stable conditions of an indoor environment may reveal higher levels of contaminant residues on surfaces and smokers’ bodies. Moir et al. (2008) quantified PAH concentrations in second-hand tobacco smoke, defined as environmental tobacco smoke that is inhaled involuntarily or passively by someone who is not smoking. Using their study and our data set, we carried out a ‘‘back of the envelope’’ calculation to estimate the percentage of sidestream smoke (i.e., secondhand smoke) that becomes third-hand smoke. We conclude that the PAH inventory on 1 hand of a smoker represents 0.1% to 6% of that emitted from sidestream smoke. Third-hand PAH residues on a smoker’s hand represent only a fraction of the total PAH reservoir for a smoker (compared to residues on all exposed skin and clothing). We have begun to quantify this load of chemicals as the first step in assessing the potential for smokers to act as vectors for impairment of indoor air quality. To completely capture the health risk posed by third-hand smoke, further studies from our research group and others need to address the off-gassing or desorption potential of these compounds and more fully evaluate the significance of third-hand smoke residues in impairing indoor air quality and/or increasing PAH exposure to subpopulations such as children. A thorough ranking of the importance of this exposure route compared to other exposures modes (e.g., release of PAHs from cooking methods such as open fires, incense burning, indoor tobacco smoking, etc.) also remain to be quantified.

A new perspective on the Dunnett procedure: filling the gap between NOEC/LOEC and ECx concepts.

The no-observed-effect concentration (NOEC) is known to be based on a wrong usage of hypothesis tests, and the use of confidence intervals is preferred. The purpose of the present study is to provide an easy and proper way to interpret ecotoxicological tests based on simultaneous confidence intervals associated with the commonly used Dunnett procedure, and to show how these intervals may allow one to infer ECx values (effective concentrations).

Matrix Population Models as Relevant Modeling Tools in Ecotoxicology

Nowadays, one of the big challenge in ecotoxicology is to understand how individually measured effects can be used as predictive indices at the population level. A particular interesting aspect is to evaluate how individual measures of fitness and survival under various toxic conditions can be used to estimate the asymptotic population growth rate known as one of the most robust endpoint in population risk assessment. Among others, matrix population models are now widely recognized as a convenient mathematical formalism dedicated to the characterization of the population demographic health. They offer the advantage of simplicity, not only in the modeling process of underlying biological phenomena, but also in the sensitivity analyses and the simulation running. On the basis of different biological systems among aquatic animal species (from fish to zooplankton), we illustrate the use of matrix population models to quantify environmental stress effects of toxic type. We also show how critical demographic parameters for the population dynamics can be highlighted by sensitivity analyses. The first example will focus on coupled effects of food amount and exposure concentration on chironomid population dynamics in laboratory. The second example will exemplify the use of energy-based models coupled with matrix population ones to properly describe toxic effects on daphnid populations. Last, we will show how to introduce a spatial dimension in Leslie type models to describe space-specific aspects of contaminant induced population dynamics alteration with the case of brown trout population modeling at the river network scale.

Population-level modeling to account for multigenerational effects of uranium in Daphnia magna.

As part of the ecological risk assessment associated with radionuclides in freshwater ecosystems, toxicity of waterborne uranium was recently investigated in the microcrustacean Daphnia magna over a three-generation exposure (F0, F1, and F2). Toxic effects on daphnid life history and physiology, increasing over generations, were demonstrated at the organism level under controlled laboratory conditions. These effects were modeled using an approach based on the dynamic energy budget (DEB). For each of the three successive generations, DEBtox (dynamic energy budget applied to toxicity data) models were fitted to experimental data. Lethal and sublethal DEBtox outcomes and their uncertainty were projected to the population level using population matrix techniques. To do so, we compared two modeling approaches in which experimental results from F0, F1, and F2 generations were either considered separately (F0-, F1-, and F2-based simulations) or together in the actual succession of F0, F1, and F2 generations (multi-F-based simulation). The first approach showed that considering results from F0 only (equivalent to a standard toxicity test) would lead to a severe underestimation of uranium toxicity at the population level. Results from the second approach showed that combining effects in successive generations cannot generally be simplified to the worst case among F0-, F1-, and F2-based population dynamics.

From Individual to Population Level Effects of Toxicants in the Tubicifid Branchiura sowerbyi Using Threshold Effect Models in a Bayesian Framework

Effects of zinc were studied in the freshwater worm Branchiura sowerbyi using partial and full life-cycle tests. Only newborn and juveniles were sensitive to zinc, displaying effects on survival, growth, and age at first brood at environmentally relevant concentrations. Threshold effect models were proposed to assess toxic effects on individuals. They were fitted to life-cycle test data using Bayesian inference and adequately described life-history trait data in exposed organisms. The daily asymptotic growth rate of theoretical populations was then simulated with a matrix population model, based upon individual-level outputs. Population-level outputs were in accordance with existing literature for controls. Working in a Bayesian framework allowed incorporating parameter uncertainty in the simulation of the population-level response to zinc exposure, thus increasing the relevance of test results in the context of ecological risk assessment.

Efficiency of wipe sampling on hard surfaces for pesticides and PCB residues in dust

Pesticides and polychlorinated biphenyls (PCBs) are commonly found in house dust and have been described as a valuable matrix to assess indoor pesticide and PCB contamination. The aim of this study was to assess the efficiency and precision of cellulose wipe for collecting 48 pesticides, eight PCBs, and one synergist at environmental concentrations. First, the efficiency and repeatability of wipe collection were determined for pesticide and PCB residues that were directly spiked onto three types of household floors (tile, laminate, and hardwood). Second, synthetic dust was used to assess the capacity of the wipe to collect dust. Third, we assessed the efficiency and repeatability of wipe collection of pesticides and PCB residues that was spiked onto synthetic dust and then applied to tile. In the first experiment, the overall collection efficiency was highest on tile (38%) and laminate (40%) compared to hardwood (34%), p<0.001. The second experiment confirmed that cellulose wipes can efficiently collect dust (82% collection efficiency). The third experiment showed that the overall collection efficiency was higher in the presence of dust (72% vs. 38% without dust, p<0.001). Furthermore, the mean repeatability also improved when compounds were spiked onto dust (<30% for the majority of compounds). To our knowledge, this is the first study to assess the efficiency of wipes as a sampling method using a large number of compounds at environmental concentrations and synthetic dust. Cellulose wipes appear to be efficient to sample the pesticides and PCBs that adsorb onto dust on smooth and hard surfaces.

SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets

MOTIVATION Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network. AVAILABILITY SRV toolbox is encoded in MATLAB R2008A (Mathworks, Natick, MA) and in GNU Octave. It is available free of charge at http://www.prabi.fr/redmine/projects/srv/repository with a tutorial. CONTACT benjamin.blaise@chu-lyon.fr or vincent.navratil@univ-lyon1.fr.

Bayesian modelling of daphnid responses to time-varying cadmium exposure in laboratory aquatic microcosms

Experiments were carried out to test the effects of cadmium on five aquatic species in 2-L indoor freshwater/sediment microcosms. Experimental data were collected over 21 days in static conditions, i.e. the microcosms evolved without water renewal. Because of speciation, the total cadmium concentration in water decreased with time. Here we present a focus on Daphnia magna responses. For the three life history traits we considered (survival, growth and reproduction), mathematical effect models were built based on threshold stress functions involving no effect concentrations (NECs). These models took the time-varying conditions of exposure into account through a time-recurrent formalism. Within a Bayesian framework, four kinds of data were fitted simultaneously (exposure, survival, growth and reproduction), using an appropriate error model for each endpoint. Hence, NECs were determined as well as their associated estimation uncertainty. Through this modelling approach, we demonstrate that thresholds for stress functions can be successfully inferred even in experimental setup more complex than standard bioassays.