The Challenge To Relate the Physicochemical Properties of Colloidal Nanoparticles to Their Cytotoxicity

Abstract

Nanomaterials offer opportunities to construct novel compounds for many different fields. Applications include devices for energy, including solar cells, batteries, and fuel cells, and for health, including contrast agents and mediators for photodynamic therapy and hyperthermia. Despite these promising applications, any new class of materials also bears a potential risk for human health and the environment. The advantages and innovations of these materials must be thoroughly compared against risks to evaluate each new nanomaterial. Although nanomaterials are often used intentionally, they can also be released unintentionally either inside the human body, through wearing of a prosthesis or the inhalation of fumes, or into the environment, through mechanical wear or chemical powder waste. This possibility adds to the importance of understanding potential risks from these materials. Because of fundamental differences in nanomaterials, sound risk assessment currently requires that researchers perform toxicology studies on each new nanomaterial. However, if toxicity could be correlated to the basic physicochemical properties of nanomaterials, those relationships could allow researchers to predict potential risks and design nanomaterials with minimum toxicity. In this Account we describe the physicochemical properties of nanoparticles (NPs) and how they can be determined and discuss their general importance for cytotoxicity. For simplicity, we focus primarily on in vitro toxicology that examines the interaction of living cells with engineered colloidal NPs with an inorganic core. Serious risk assessment of NPs will require additional in vivo studies. Basic physicochemical properties of nanoparticulate materials include colloidal stability, purity, inertness, size, shape, charge, and their ability to adsorb environmental compounds such as proteins. Unfortunately, the correlation of these properties with toxicity is not straightforward. First, for NPs released either unintentionally or intentionally, it can be difficult to pinpoint these properties in the materials. Therefore, researchers typically use NP models with better defined properties, which don't include the full complexity of most industrially relevant materials. In addition, many of these properties are strongly mutually connected. Therefore, it can be difficult to vary individual properties in NP models while keeping the others constant.

Assessing nanoparticle toxicity in cell-based assays: influence of cell culture parameters and optimized models for bridging the in vitro–in vivo gap

“…Nel et al have first raised this thought in 2006, emphasizing on the necessity to optimize the classical in vitro toxicity assays as they show several shortcomings when they are being applied for NP toxicity evaluation 28 . We believe that the major issues with the current in vitro methods are (i) the lack of a complete characterization of the particles, (ii ) the lack of standardisation and guidelines on how to perform a toxicological evaluation in vitro, (iii) the possibility of NP interfering with the assay and therefore lack of appropriate methods to evaluate nanotoxicity and (iv) the shortcomings inherent to the most used classical 2D monocultures 11,82,93,104,105 . It is therefore clear that further research on the optimization of methods is highly recommended in order to obtain reproducible data that would allow drawing firm conclusions regarding NP toxicity.…”

“…often differ between studies rendering it nearly impossible to retrieve reliable conclusions on the effect of a specific parameter. This originates from the fact that altering one physicochemical parameter, for example surface charge, without affecting any other (hydrodynamic size, colloidal stability, nature of the coating…) is not an easy task 105 . Therefore a multitude of parameters, that might potentially influence the outcome, must be optimised and standardised as far as possible.…”

“…Here consensus is needed on methods to determine the concentration as well as on the unit, in which this parameter should be expressed 106,107 . Expressing the concentration in terms of mass/volume is the easiest option, but is however not always the most relevant 105 . Which was pointed out in a review by Johnston et Subsequently attention should go to standardisation of nanotoxicity methods in terms of incubation conditions like NP concentration and incubation time as overexposure conditions should be avoided 113 .…”

Long term biotransformation and toxicity of dimercaptosuccinic acid-coated magnetic nanoparticles support their use in biomedical applications

“…1C); these studies are of interest as data indicate that particle size and surface charge can influence cell internalization and biodistribution of MNP [7,16]. However, nanoparticle physicochemical properties in a physiological medium may vary, due to protein adsorption to nanoparticle surface forming the so-called protein corona, which can influence nanoparticle stability, uptake, and toxicity [35,36]. We analyzed the MNP hydrodynamic size in complete culture medium, and size variations at different time points up to 72 h (Fig.…”

The performance of gradient alloy quantum dots in cell labeling

“…Although the gradual release of toxic ions can be exploited for biomedical purposes such as cancer therapy [12], it may also inadvertently affect healthy cells as long as this process remains only partially understood. A lot of attention has been put in determining the potential toxicity of Cd2+-containing QDots, but thus far, the safety of these NPs remains questionable due to several intrinsic difficulties that are associated with assessing NP safety: 1) the wide number of variations in QDot parameters (purity of the NPs, colloidal stability, chemical composition,size, core-only or core-shell, nature and thickness of the shell layer, type of coating …) [13], 2) the nature of the experiments performed (e.g. differences in cell types, media composition, experimental procedures such as incubation times, concentrations used…) [14], 3) discrepancies between in vitro and in vivo data due to intrinsic differences in experimental setups (effect of agglomeration and sedimentation, effect of continuous flow versus static model) [15,16].…”