What do luminescent bacterial metal-sensors probe? Insights from confrontation between experiments and flux-based theory

Pagnout, Christophe; Présent, Romain M.; Billard, Patrick; Rotureau, Elise; Duval, Jérôme F. L.

doi:10.1016/j.snb.2018.05.033

Cited by 14 publications

(51 citation statements)

References 58 publications

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“…AFM force curves were measured on the deep rough Escherichia coli bacterial strain BW25113 (rod-shaped cells with 700 to 800 nm diameter and 2 to 3 mm length 47 ) obtained from the Coli Genetic Stock Center of Yale University, USA, [48][49][50][51][52][53] and selected here for testing the performance of our automated treatment of force curves. For the experiments, cells were streaked from glycerol stocks on LB agar plates.…”

Section: Bacterial Culturementioning

confidence: 99%

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Fast automated processing of AFM PeakForce curves to evaluate spatially resolved Young modulus and stiffness of turgescent cells

et al. 2020

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Section: Bacterial Culturementioning

confidence: 99%

“…4 nm as independently conrmed by detailed electrohydrodynamic analysis of BW25113 electrophoretic properties. 51…”

Section: Bacterial Culturementioning

confidence: 99%

Fast automated processing of AFM PeakForce curves to evaluate spatially resolved Young modulus and stiffness of turgescent cells

et al. 2020

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“…Electrophoresis is a well-established technique for addressing the electrostatic properties of abiotic and biotic colloidal particles in aqueous solution [1][2]. Pending proper conversion of the measured electrophoretic mobility into relevant particle electrostatic descriptors, electrophoresis provides a way to capture how electrostatics contributes to (bio)particles stability against aggregation [2][3], how it impacts (or not) nanoparticle-cell, cell-cell or nanoparticle-functionalized surface interactions [4][5][6], the attachment of bacteria to surfaces [7][8][9], the binding of metal ions to (nano)particles [10][11][12], the transport of particles in porous media [13][14][15], the accumulation of metal ions in microorganisms [16] or even the response of bioluminescent metal-sensing bacterial reporters [17][18]. Quantitative interpretation of electrophoretic mobility data and subsequent evaluation of the defining particle electrostatic features differ according to the type of particles examined, in particular the magnitude of their permeability to electrolyte ions and to the (electroosmotic) flow developed under electrokinetic conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Soft particles also include colloids consisting of a permeable polymeric material in the absence of intraparticulate core component (so-called porous particles) [25]. Paradigms of systems whose electrophoresis behavior relates to that of soft particles include polyelectrolyte particles [26][27][28], bacteria [1,[17][18][29][30][31], viruses [32][33], (bio)functionalized, thermo-and/or iono-responsive (nano)particles [34][35][36], recombinant protein particles [37], environmental particles like humic substances [38], and polyelectrolyte multi-layered particles [39][40], to quote only a few. It has long been recognized that the electrophoretic properties of soft particles deviate substantially from that of hard particles and that the concept of zeta-potential is inapplicable to soft particles for which the gradual suppression of the electroosmotic flow profile within the permeable component renders impossible any a priori definition of a slip plane [1,25,[41][42].…”

Section: Introductionmentioning

confidence: 99%

Electrophoresis of composite soft particles with differentiated core and shell permeabilities to ions and fluid flow

Maurya

Gopmandal

Ohshima

et al. 2020

Journal of Colloid and Interface Science

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Within the framework of analytical theories for soft surface electrophoresis, soft particles are classically defined by a hard impermeable core of given surface charge density surrounded by a polyelectrolyte shell layer permeable to both electroosmotic flow and ions from background electrolyte. This definition excludes practical core-shell particles, e.g. dendrimers, viruses or multi-layered polymeric particles, defined by a polyelectrolytic core where structural charges are distributed and where counter-ions concentration and electroosmotic flow velocity can be significant. Whereas a number of important approximate expressions has been derived for the electrophoretic mobility of hard and soft particles, none of them is applicable to such generic composite core-shell particles with differentiated ions-and fluid flow-permeabilities of their core and shell components. In this work, we elaborate an original closed-form electrophoretic mobility expression for this generic composite particle type within the Debye-Hückel electrostatic framework and thin double layer approximation. The expression explicitly involves the screening Debye layer thickness and the Brinkman core and shell hydrodynamic length scales, which favors so-far missing analysis of the respective core and shell contributions to overall particle mobility. Limits of this expression successfully reproduce results from Ohshima's electrophoresis theory solely applicable to soft particles with or without hard core.

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“…In the absence of this element, the expression of reporter genes is repressed by the repressor attached to the promoter. Inactivation of the repressor occurs when the latter forms a complex with the metal ion, thus allowing the expression of reporter genes and the production of so-called reporter proteins (e.g., GFP or luciferase) at the origin of the measured signal (e.g., fluorescence or luminescence). , Many so-constructed whole-cell bacterial sensors are listed in the literature − with detection limits from a few nM to ten μM.…”

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Decoding the Time-Dependent Response of Bioluminescent Metal-Detecting Whole-Cell Bacterial Sensors

Duval

Pagnout

2019

ACS Sens.

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The signal produced by aqueous dispersions of bioluminescent, metal-responsive whole-cell bacterial sensors is indicative of the concentration of bioavailable metal ions in solution. The conventional calibration-based strategy followed for measuring this concentration is however inadequate to provide any quantitative prediction of the cells response over time as a function of e.g. their growth features, their defining metal accumulation properties, or the physicochemical medium composition. Such an evaluation is still critically needed for assessing on a mechanistic level the performance of biosensors in terms of metal bioavailability and toxicity monitoring. Herein we report a comprehensive formalism unraveling how the dependence of bioluminescence on time is governed by the dynamics of metal biouptake, by the activation kinetics of lux-based reporter gene, by the ensuing rate of luciferase production, the kinetics of light emission and quenching. It is shown that bioluminescence signal corresponds to the convolution product between two time-dependent functions, one detailing the dynamic interplay of the above microand nanoscale processes, and the other pertaining to the change in concentration of photoactive cell sensors over time. Numerical computations illustrate how the shape and magnitude of the bioluminescence peak(s) are intimately connected to the dependence of the photoactive cells concentration on time and to the magnitudes of Deborah numbers that compare the relevant timescales of the biointerfacial and intracellular events controlling light emission. Explicit analytical expressions are further derived for practical situations where bioluminescence is proportional to the concentration of metal ions in solution. The theory is further quantitatively supported by experiments performed on luminescent cadmium-responsive lux-based Escherichia coli biosensors.Substituting the expressions of diff J and u J into eq 2, it is shown that u J is provided by eq 2 with   diff J t defined by (details in Supporting Information, SI-1)Bn J c t c t Metal concentration at the membrane surface (mol m -3 ). M,f c  Bulk concentration of bioavailable metal ions (mol m -3 ). M,f c  Dimensionless bulk concentration of bioavailable metal ions.f Time-dependent (dimensionless) function defined by eq 12.g Time-dependent (dimensionless) function defined by eq 10. diff J M diffusion flux at the membrane surface (mol m -2 s -1 ). u J Metal biouptake flux (mol m -2 s -1 ). u J  Maximum metal biouptake flux (mol m -2 s -1 ). u J Dimensionless M biouptake flux defined by u u / J J  . u,0

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What do luminescent bacterial metal-sensors probe? Insights from confrontation between experiments and flux-based theory

Cited by 14 publications

References 58 publications

Fast automated processing of AFM PeakForce curves to evaluate spatially resolved Young modulus and stiffness of turgescent cells

Fast automated processing of AFM PeakForce curves to evaluate spatially resolved Young modulus and stiffness of turgescent cells

Electrophoresis of composite soft particles with differentiated core and shell permeabilities to ions and fluid flow

Decoding the Time-Dependent Response of Bioluminescent Metal-Detecting Whole-Cell Bacterial Sensors

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