| Literature DB >> 29956556 |
Abstract
Humans are exposed to a wide variety of nanoparticles (NPs) present in the environment, in consumer, health and medical products, and in food. Conventional cytotoxicity testing compared to animal testing is less expensive, faster and avoids ethical problems at the expense of a lower predictive value. New cellular models and exposure conditions have been developed to overcome the limitations of conventional cell culture and obtain more predictive data. The use of three-dimensional culture, co-culture and inclusion of mechanical stimulation can provide physiologically more relevant culture conditions. These systems are particularly relevant for oral, respiratory and intravenous exposure to NPs and it may be assumed that physiologically relevant application of the NPs can improve the predictive value of in vitro testing. Various groups have used advanced culture and exposure systems, but few direct comparisons between data from conventional cultures and from advanced systems exist. In silico models may present another option to predict human health risk by NPs without using animal studies. In the absence of validation, the question whether these alternative models provide more predictive data than conventional testing remains elusive.Entities:
Keywords: Alternative models; co-culture; inhalation exposure; intravenous exposure; nanoparticles; oral exposure
Mesh:
Year: 2018 PMID: 29956556 PMCID: PMC6214528 DOI: 10.1080/21691401.2018.1479709
Source DB: PubMed Journal: Artif Cells Nanomed Biotechnol ISSN: 2169-1401 Impact factor: 5.678
Specific issues in the toxicity testing of NPs.
| Parameter | Specific issues with NPs |
|---|---|
| Exposure medium | Exposure medium is important because particle parameters are changed by medium composition (agglomeration) |
| Duration of exposure | Usually too short as NPs are metabolized to lower extent than conventional compounds |
| Monolayer culture | NPs cross cell layers by diffusion and paracellular transport to lower extent than conventional compounds |
| Monoculture | Cell uptake differs between phagocytes and non-phagocytes for NPs and less for conventional compounds |
| Absence of dynamics | NPs get in contact with cells by sedimentation, which does not play a role for conventional compounds |
| Low cell differentiation | Secretion of mucus hinders permeation of NPs to higher degree than conventional compounds due to the size exclusion effect |
aSize exclusion means that NPs, due to their size, are sieved though the mucus mesh.
Figure 1.Extent of NP exposure, translocation and use of advanced cell culture models in the testing for epithelial barriers and internal organs. Independent from the extent of exposure use of in vitro models for protective barriers (cornea, epidermis, oral cavity, vaginal epithelium) is low as good ex vivo systems are available. In vitro systems are used when particle exposure is high and robust ex vivo systems are missing (alveolar and intestinal epithelium).
Origin and use of cell lines in the physiologically relevant models.
| Cell line | Species | Origin | Use |
|---|---|---|---|
| 16HBE14o– | Human | SV40 immortalized bronchial epithelial cells | Bronchial epithelium, toxicity |
| A549 | Human | Lung carcinoma | Alveolar epithelium, toxicity |
| BEAS-2 | Human | Epithelial virus transformed bronchial epithelial cells | Bronchial epithelium, toxicity |
| Caco-2 | Human | Colorectal adenocarcinoma | Intestinal epithelium, barrier function, toxicity |
| CAL27 | Human | Oral squamous cell carcinoma | Cancer cell |
| Calu-3 | Human | Lung adenocarcinoma | Bronchial epithelium, barrier function |
| CRL-2102 (C2BBe1) | Human | Clone of Caco-2 cells | Enterocytes |
| EAhy926 | Human | Fusion of HUVEC with human pulmonary adenocarcinoma A549 cells | Endothelium |
| Fa2N4 | Human | SV 40 immortalized hepatocytes | Hepatocytes |
| hAELVI | Human | Lentivirus immortalized alveolar epithelial cells | Alveolar epithelium, barrier function |
| HeLa | Human | Cervical cancer | Cancer cell |
| Hep3B | Human | Hepatocellular carcinoma | Hepatocytes |
| HepaRG | Human | Liver progenitor cells | Hepatocytes |
| HepG2 Hep2/C3a | Human | Hepatocellular carcinoma derived from HepG2 cells | Hepatocytes |
| HK-2 | Human | Proximal tubule papilloma | Renal tubule cells, barrier function |
| HMC-1 | Human | Mast cell leukaemia | Mast cells |
| HPMEC-ST1.6R | Human | Virus transfected microvascular endothelial cells | Endothelial cells |
| HT29 and HT29-MTX | Human | Colon adenocarcinoma cells and cells treated with methotrexate to induce mucus production | Goblet cells |
| Huh7 | Human | Hepatocellular carcinoma | Hepatocytes |
| ISO-HAS 1 | Human | Haemangiosarcoma | Endothelium |
| J774.A1 | Mouse | Reticulum cell sarcoma | Monocytes/macrophages function |
| LLC-PK1 | Pig | Kidney cells | Renal tubule cells, barrier function |
| LS174 | Human | Colorectal adenocarcinoma | Intestinal epithelium |
| LS513 | Human | Colorectal carcinoma | Intestinal epithelium |
| M5076 | Mouse | Ovarian sarcoma | Cancer cells |
| MCF-7 | Human | Breast adenocarcinoma | Metabolization, action of transporters |
| MDCK | Dog | Distal renal tubules | Renal tubule cells, barrier function |
| MG63 | Human | Osteosarcoma | Osteoblasts |
| MH-S | Murine | Simian virus 40 transformed alveolar macrophages | Alveolar macrophages |
| MLE 12 | Mouse | Lung epithelial cells | Alveolar epithelium |
| MRC-5 | Human | Foetal lung fibroblasts | Fibroblasts |
| NCI-H322 | Human | Bronchoalveolar carcinoma | Alveolar epithelium, toxicity |
| NCI-H441 | Human | Papillary lung adenocarcinoma | Alveolar epithelium |
| NCI-H460 | Human | Large-cell lung cancer | Cancer cell |
| NIH/3T3 | Mouse | Embryonal fibroblasts | Fibroblasts |
| NKi-2 | Human | hTERT immortalized proximal tubule cells | Proximal renal tubule cells |
| NRK52K | Rat | Kidney epithelial cells | Renal tubule cells, barrier function |
| Raji B | Human | Burkitt’s Lymphoma | Induction of M cell formation in co-culture |
| Rat-2 | Rat | Foetal fibroblasts | Fibroblasts |
| RAW 264.7 | Mouse | Abelson murine leukaemia virus-induced tumour | Monocytes/macrophages function |
| T84 | Human | Colorectal carcinoma | Intestinal epithelium |
| THP-1 | Human | Acute monocytic leukaemia | Monocytes/macrophages function |
| TK6 | Human | Hereditary spherocytosis lymphoblasts | Genotoxicity testing |
| TLT | Human | Macrophages | Macrophages |
| U937 | Human | Histiocytic lymphoma | Monocytes/macrophages function |
Figure 2.Use of transwell membranes in advanced culture models. Monoculture for permeation experiments (A), indirect contact (B) and direct or indirect contact (C) co-culture of only one cell type in each chamber. Cells can be cultured or separated by matrices that may either be acellular (D) or contain one (E) or several types of cells (E, F). Co-culture systems may consist of two and more cell types in the apical compartment (G), co-culture of two and more cell types in the apical compartment in indirect culture with one cell type in the basolateral compartment (H), co-culture of one cell type in the apical and several types of cells in the basolateral compartment (I), combined direct contact and indirect contact culture (J), direct contact culture of several cell types in the apical compartment and one type in the basolateral compartment (K). The separation line in H, J and K indicates that different cell types in monoculture can be used in the basolateral compartment or in the apical compartment (E).
Figure 3.Particle and biological parameter that were identified to play a role in in silico modelling of metal oxide NPs (according to the meta-analysis by Ha et al. [105]). Parameters can be influenced by the use of advanced cell culture models, either by medium composition (M) or by the culture method (C). Medium composition may have an influence on aggregation (hydrodynamic size) and influence the dose that reaches the cell. In addition, surface parameters may be changed. The culture method influences mainly cellular differences by increasing cell differentiation and the exposure time as physiologically relevant culture methods usually enable exposure for longer time periods.
Parameters included in QSAR models.
| Nanomaterial | Toxicity endpoint | Characterization | Reference |
|---|---|---|---|
| 18 NMs (carbon-based, metal oxides) | Cytotoxicity, apoptosis, pro-inflammatory effects, haemolysis, viability, mitochondrial membrane potential, morphology | 7 descriptors: size, surface area, morphology, metal content, reactivity, free radical generation, zeta potential | [ |
| 18 NMs | Viability | 17 quantum mechanical descriptors (enthalpy of formation of nanocluster, total and electronic energy, core–core repulsion energy, solvent accessible surface, energy of the highest occupied molecular orbital, energy of the lowest unoccupied molecular orbital, gap between both, electronic chemical potential, valence band, conduction band, Mulliken’s electronegativity, Parr and Pople’s absolute hardness, Schüürmann Molecular Orbital shift alpha quantities, polarizability derived from the heat of formation, and polarizability derived from dipole moment) and 11 experimental descriptors (area, volume, surface diameter, volume/mass diameter, volume/surface diameter, aspect ratio, porosity, sphericity, circularity) | [ |
| 51 NMs with four metal core structures | Viability, reducing equivalents, apoptosis, mitochondrial membrane potential | 5 descriptors: core composition, coating, surface modification, relaxivities, zeta potential | [ |
| 42 NMs with two cores | Cytotoxicity | 6 descriptors: primary particle size, size in water, size in PBS, cell in cell culture medium, concentration, zeta potential | [ |
| 13 pure, core-shell and alloy Au/Pd TiO2 NMs | Cytotoxicity (CHO-K1 cells) | 2 descriptors: size, surface area | [ |
| 9 metal oxide NMs | Cytotoxicity (BEAS-2B cells) | 14 descriptors: atomization energy of the metal oxide, period of the NP metal, and NP primary size, in addition to NP volume fraction (in solution) were identified as most predictive | [ |
| 24 metal oxide NMs | ROS, oxidative stress, pulmonary inflammation in mice | 30 theoretical descriptors: conduction band energy predictive for some, solubility for other metal oxide NPs | [ |
| 41 metal oxide NMs | Cytotoxicity | 4 descriptors; size, electronegativity, polarizability, molar volume | [ |
| 17 metal oxide NMs | Cytotoxicity (HaCaT cells) | 7 theoretical descriptors (number of metal atoms, number of oxygen atoms, molecular weight, charge of the metal cation corresponding to a given oxide, metal electronegativity, sum of metal electronegativity for the individual metal oxide, sum of metal electronegativity for the individual metal oxide divided by the number of oxygen atoms in a specific metal oxide) | [ |
| 24 metal oxide NMs | Viability, 2 cell lines | 30 descriptors: conduction band energy and ionic index were identified as very predictive | [ |
| 44 iron oxide NMs | 4 cell types, 4 assays | 4 descriptors: primary size, spin–lattice, spin–spin relaxivities, zeta potential; no single parameter performed best | [ |
| 6 metal oxide NMs | Oxidative stress | 1 descriptor: energy band structure | [ |
| 307 studies, Cd quantum dots | Viability | 24 qualitative and quantitative features (ligand, shell, surface modification, assay type, exposure time, exposure concentration, cell anatomical type, cell origin) | [ |
| 20 C60 fullerene NPs | Mutagenicity | 3 descriptors: dose, illumination, metabolic activation | [ |
| 84 f-MWCNTs | Cytotoxicity, protein binding, immune response | 5 descriptors: zeta potential, electrophoretic mobility, surface area, porosity, solubility | [ |