| Literature DB >> 32582672 |
Dania Movia1, Solene Bruni-Favier1, Adriele Prina-Mello1,2.
Abstract
When assessing the risk and hazard of a non-pharmaceutical compound, the first step is determining acute toxicity, including toxicity following inhalation. Inhalation is a major exposure route for humans, and the respiratory epithelium is the first tissue that inhaled substances directly interact with. Acute inhalation toxicity testing for regulatory purposes is currently performed only in rats and/or mice according to OECD TG403, TG436, and TG433 test guidelines. Such tests are biased by the differences in the respiratory tract architecture and function across species, making it difficult to draw conclusions on the potential hazard of inhaled compounds in humans. Research efforts have been therefore focused on developing alternative, human-relevant models, with emphasis on the creation of advanced In vitro models. To date, there is no In vitro model that has been accepted by regulatory agencies as a stand-alone replacement for inhalation toxicity testing in animals. Here, we provide a brief introduction to current OECD test guidelines for acute inhalation toxicity, the interspecies differences affecting the predictive value of such tests, and the current regulatory efforts to advance alternative approaches to animal-based inhalation toxicity studies. We then list the steps that should allow overcoming the current challenges in validating In vitro alternatives for the successful replacement of animal-based inhalation toxicity studies. These steps are inclusive and descriptive, and should be detailed when adopting in house-produced 3D cell models for inhalation tests. Hence, we provide a checklist of key parameters that should be reported in any future scientific publications for reproducibility and transparency.Entities:
Keywords: In vitro alternatives; air-liquid interface (ALI) culture; inhalation studies; lung epithelium; toxicity testing alternatives
Year: 2020 PMID: 32582672 PMCID: PMC7284111 DOI: 10.3389/fbioe.2020.00549
Source DB: PubMed Journal: Front Bioeng Biotechnol ISSN: 2296-4185
Figure 1Changes in markers of cellular- and tissue-specific KEs following a single-dose aerosol (N) exposure to benchmark substances. Cell cultures were exposed to liquid aerosols by means of a Vitrocell Cloud ALI system equipped with an Aeroneb® Pro nebulizer. Cellular-specific KEs included percentage (%) cytotoxicity, cytokines (IL-6, IL-8) and chemokines (MCP-1/CCL2, CXCL1/Groα, CXCL2/Groβ) secretion. Tissue-specific KEs included epithelial barrier impairment, quantified as changes in TEER. Data are presented as mean and normalized to untreated cultures. (A) SmallAir-HF™ (left) and MucilAir-HF™ (right) models were exposed to benchmarks for 72 h. (B) MucilAir-HF™ models were exposed to benchmarks up to 60 days. (A,B) Symbols (*), (**), and (***) indicate p < 0.05, p < 0.01, and p < 0.001, respectively (two-way ANOVA followed by Dunnett post-test; comparison to the untreated controls).
Figure 2Changes in markers of cellular- and tissue-specific KEs in SmallAir-HF™ (left) and MucilAir-HF™ (right) models following a single-dose exposure by aerosol (N) or by direct inoculation (I). Cellular-specific KE included percentage (%) cytotoxicity, cytokines (IL-6, IL-8) and chemokines (MCP-1/CCL2, CXCL1/Groα, CXCL2/Groβ) secretion. Tissue-specific KE included epithelial barrier impairment, quantified as changes in TEER. Data are presented as mean and normalized to untreated cultures. Symbols (*), (**), and (***) indicate p < 0.05, p < 0.01, and p < 0.001, respectively (two-way ANOVA followed by Dunnett post-test; comparison to the untreated controls).
Checklist describing key parameters that should be included in scientific publications, as well as in Section 3 of the ToxTemp document, when adopting in house-produced 3D cell models to test inhaled substances.
| Culturing substrate | Scaffold-based | Scaffold material and structure |
| Scaffold-free | Specialized cell culture plates or lab equipment (e.g. 3D printing) used | |
| Cells | Cell types | Mono- or co-culture, primary cells, immortalized and/or carcinogenic cell lines, differentiation protocol |
| Donors | Gender-balanced pool of cell donors | |
| Cell culture formation | Methodology | Air-Liquid Interface (ALI) conditions, cell seeding on scaffolds, incorporation into matrices, liquid overlay, partially separated or mixed ALI co-cultures |
| Growth time | Number of days/weeks | |
| Cell culture manipulation | Biological cues | Medium change, mechanical cues (e.g. substrate stiffness, sheer flow), soluble/chemical cues (e.g. hormones) |
| Biological functions of cells | Cell phenotype | Cell shape, polarity, proliferative activity, cell differentiation |
| Biological functions of culture | Geometry | Culture morphology (2D or 3D) and architecture, culture size. |
| Stability | Viability and phenotype changes overtime | |
| Comparison to tissue in humans | Cell-ECM and cell-cell interactions, formation of tissue-mimetic structures, mucus production | |
| Exposure | Exposure methodologies | Human-relevance of experimental exposure conditions |
| Verification | Model benchmarking | Comparison to known, human-relevant exposure scenarios |
| Validation | Benchmarks | Benchmark identification and validation of cell culture responses |
| Assay validation for toxicity/efficacy testing | Endpoints | Human-relevant endpoint definition (e.g. based on AOPs), overcoming diffusion issues (e.g. during immunostaining), positive controls |
| Accuracy | Benchmark data should include information on the variability and the upper and lower limits of accuracy metrics, as suggested by Leontaridou et al. ( |