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Décomposition tensorielle de signaux luminescents émis par des biosenseurs bactériens pour l'identification de Systèmes Métaux-Bactéries

Abstract : Availability and persistence of heavy metals could be critical for future use of agricultural or urban areas, on which many industrial sites have installed in the past. The management of these complex environnemental situations requiring the developpement of new analytical methods minimally invasive, such as bacterial biosensors, to identify and directly assess the biological effects and the chemical availability of metals. The aims of this thesis was to identify the responses of fluorescent bacterial sensors invarious environmental conditions, using mathematical tools of algebra multilinear, whether stress caused by the presence of high dose of a metal or a nutrient deficiency caused by his absence. This identification is based on quantitative analysis of multidimensional signals at the bacterial population-scale. It is based in particular on (i) the acquisition of multivariate spectral data on suspensions of multicolored biosensors interacting with metals and (ii) the development of algortihms for tensor decomposition. The proposed methods, developed and used in this study attempt to identify functional response of biosensors without \textsl{a priori} by decomposition of tensor containing the spectral signals. These methods take advantage of the variability of systemic responses and allow to determine the basic sources identifying the system and their behavior to external factors. They are inspired by the CP and PARALIND methods. The advantage of this approach, compared to conventional approaches, is the unique identification of the responses of biosensors at low constraints. The work was to develop efficient algorithms for the source separation of fluorescent signals emitted by bacterial sensors, ensuring the sources separability and the uniqueness of the decomposition. The original point of this thesis is the consideration of the physical constraints of analyzed phenomena such as (i) the sparsity of mixing coefficients or positivity of sources signals in order to minimize the used of a priori or (ii) the non-empirical determination of the order of decomposition (number of sources).This posture has also improved the identification optimizing physical measurements by the use of synchronous spectra or providing sufficient diversity in design of experiments. The use of synchronous spectra proved crucial both to improve the separation of fluorescent sources, but also to increase the signal to noise ratio of the lowest biosensors. This original method of spectral analysis can greatly expand the color range of multicolored fluorescent biosensors used simultaneously. Finally, a new method of estimating the concentration of metal pollutants present in a sample from the spectral response of a mixture of non-specific biosensor was developed.
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Submitted on : Wednesday, January 22, 2014 - 10:48:40 AM
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  • HAL Id : tel-01749867, version 2

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Fabrice Caland. Décomposition tensorielle de signaux luminescents émis par des biosenseurs bactériens pour l'identification de Systèmes Métaux-Bactéries. Interfaces continentales, environnement. Université de Lorraine, 2013. Français. ⟨NNT : 2013LORR0093⟩. ⟨tel-01749867v2⟩

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