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Defining an additivity framework for mixture research in inducible whole-cell biosensors.

Martin-Betancor K, Ritz C, Fernández-Piñas F, Leganés F, Rodea-Palomares I - Sci Rep (2015)

Bottom Line: A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R.Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations.The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred.

View Article: PubMed Central - PubMed

Affiliation: Departament of Biology, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain.

ABSTRACT
A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R. The proposed method is a multivariate extension of the effective dose (EDp) concept. Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations. This allows a multivariate extension of Loewe additivity, enabling direct application in a biphasic dose-response framework. The proposed additivity definition was validated, and its applicability illustrated by studying the response of the cyanobacterial biosensor Synechococcus elongatus PCC 7942 pBG2120 to binary mixtures of Zn, Cu, Cd, Ag, Co and Hg. The novel method allowed by the first time to model complete dose-response profiles of an inducible whole cell biosensor to mixtures. In addition, the approach also allowed identification and quantification of departures from additivity (interactions) among analytes. The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred. The method is a useful contribution for the whole cell biosensors discipline and related areas allowing to perform appropriate assessment of mixture effects in non-monotonic dose-response frameworks.

No MeSH data available.


CIw Polygonograms.Polygonograms summarizing weighted combination index (CIw) for all the binary combinations of the 6 studied metal cations (Zn, Cu, Cd, Ag, Co and Hg) at three representative fractional effects (p): −50 (a), 0 (b), +50 (c). Departures from additivity are based on the risk management criterium (see Methods). Thin solid black lines represent additive effect (0.5 < CIw < 2). Solid green lines indicate synergism (CIw < 0.5). Dashed red lines indicate antagonism (CIw > 2).
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f7: CIw Polygonograms.Polygonograms summarizing weighted combination index (CIw) for all the binary combinations of the 6 studied metal cations (Zn, Cu, Cd, Ag, Co and Hg) at three representative fractional effects (p): −50 (a), 0 (b), +50 (c). Departures from additivity are based on the risk management criterium (see Methods). Thin solid black lines represent additive effect (0.5 < CIw < 2). Solid green lines indicate synergism (CIw < 0.5). Dashed red lines indicate antagonism (CIw > 2).

Mentions: The analysis of the departures from additivity for the 15 possible binary combinations of the studied metals revealed a complex scenario where the 9 possible theoretical combinations of the CID,E vectors anticipated in Theory section were actually found (Supplementary Material SM5). In order to get a global idea on the fitness to additivity of the response of the biosensor to the binary mixtures of metals, we computed CIw values according to Equation (11) which were summarized as well as polygonograms4 (for p levels −50, 0, +50) in Fig. 7. Interestingly, additive or near additive effects (according to the management criterion: 0.5 < CIw < 2) hold for binary mixtures of Zn, Cd, Ag and Cu at the three representative p levels (Fig. 7). However, some mixtures containing Hg, Co and Ag resulted in significant departures from additivity: The mixtures Hg:Co and Hg:Ag resulted in synergism and antagonism, respectively at the three representative p levels (−50, 0, +50). In addition, some mixtures resulted in effect-level dependent departures from additivity: the mixture Co:Zn resulted in synergism at p = 0 and p = +50, and the mixture Ag:Cd resulted in synergism at p = +50.


Defining an additivity framework for mixture research in inducible whole-cell biosensors.

Martin-Betancor K, Ritz C, Fernández-Piñas F, Leganés F, Rodea-Palomares I - Sci Rep (2015)

CIw Polygonograms.Polygonograms summarizing weighted combination index (CIw) for all the binary combinations of the 6 studied metal cations (Zn, Cu, Cd, Ag, Co and Hg) at three representative fractional effects (p): −50 (a), 0 (b), +50 (c). Departures from additivity are based on the risk management criterium (see Methods). Thin solid black lines represent additive effect (0.5 < CIw < 2). Solid green lines indicate synergism (CIw < 0.5). Dashed red lines indicate antagonism (CIw > 2).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4660423&req=5

f7: CIw Polygonograms.Polygonograms summarizing weighted combination index (CIw) for all the binary combinations of the 6 studied metal cations (Zn, Cu, Cd, Ag, Co and Hg) at three representative fractional effects (p): −50 (a), 0 (b), +50 (c). Departures from additivity are based on the risk management criterium (see Methods). Thin solid black lines represent additive effect (0.5 < CIw < 2). Solid green lines indicate synergism (CIw < 0.5). Dashed red lines indicate antagonism (CIw > 2).
Mentions: The analysis of the departures from additivity for the 15 possible binary combinations of the studied metals revealed a complex scenario where the 9 possible theoretical combinations of the CID,E vectors anticipated in Theory section were actually found (Supplementary Material SM5). In order to get a global idea on the fitness to additivity of the response of the biosensor to the binary mixtures of metals, we computed CIw values according to Equation (11) which were summarized as well as polygonograms4 (for p levels −50, 0, +50) in Fig. 7. Interestingly, additive or near additive effects (according to the management criterion: 0.5 < CIw < 2) hold for binary mixtures of Zn, Cd, Ag and Cu at the three representative p levels (Fig. 7). However, some mixtures containing Hg, Co and Ag resulted in significant departures from additivity: The mixtures Hg:Co and Hg:Ag resulted in synergism and antagonism, respectively at the three representative p levels (−50, 0, +50). In addition, some mixtures resulted in effect-level dependent departures from additivity: the mixture Co:Zn resulted in synergism at p = 0 and p = +50, and the mixture Ag:Cd resulted in synergism at p = +50.

Bottom Line: A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R.Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations.The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred.

View Article: PubMed Central - PubMed

Affiliation: Departament of Biology, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain.

ABSTRACT
A novel additivity framework for mixture effect modelling in the context of whole cell inducible biosensors has been mathematically developed and implemented in R. The proposed method is a multivariate extension of the effective dose (EDp) concept. Specifically, the extension accounts for differential maximal effects among analytes and response inhibition beyond the maximum permissive concentrations. This allows a multivariate extension of Loewe additivity, enabling direct application in a biphasic dose-response framework. The proposed additivity definition was validated, and its applicability illustrated by studying the response of the cyanobacterial biosensor Synechococcus elongatus PCC 7942 pBG2120 to binary mixtures of Zn, Cu, Cd, Ag, Co and Hg. The novel method allowed by the first time to model complete dose-response profiles of an inducible whole cell biosensor to mixtures. In addition, the approach also allowed identification and quantification of departures from additivity (interactions) among analytes. The biosensor was found to respond in a near additive way to heavy metal mixtures except when Hg, Co and Ag were present, in which case strong interactions occurred. The method is a useful contribution for the whole cell biosensors discipline and related areas allowing to perform appropriate assessment of mixture effects in non-monotonic dose-response frameworks.

No MeSH data available.