Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT): Developing a Data Analysis Pipeline for the Assessment of Developmental Toxicity with an Interlaboratory Study

Abstract

The embryonic zebrafish is a useful vertebrate model for assessing the effects of substances on growth and development. However, cross-laboratory developmental toxicity outcomes can vary and reported developmental defects in zebrafish may not be directly comparable between laboratories. To address these limitations for gaining broader adoption of the zebrafish model for toxicological screening, we established the Systematic Evaluation of the Application of Zebrafish in Toxicology (SEAZIT) program to investigate how experimental protocol differences can influence chemical-mediated effects on developmental toxicity (i.e., mortality and the incidence of altered phenotypes). As part of SEAZIT, three laboratories were provided a common and blinded dataset (42 substances) to evaluate substance-mediated effects on developmental toxicity in the embryonic zebrafish model. To facilitate cross-laboratory comparisons, all the raw experimental data were collected, stored in a relational database, and analyzed with a uniform data analysis pipeline. Due to variances in laboratory-specific terminology for altered phenotypes, we utilized ontology terms available from the Ontology Lookup Service (OLS) for Zebrafish Phenotype to enable additional cross-laboratory comparisons. In this manuscript, we utilized data from the first phase of screening (dose range finding, DRF) to highlight the methodology associated with the development of the database and data analysis pipeline, as well as zebrafish phenotype ontology mapping.

Keywords: danio rerio; data analysis pipeline; developmental toxicants; developmental toxicity testing; embryonic development; interlaboratory comparisons; phenotype ontology.

Figure 1

The entity relationship of tables in simplified SEAZIT database schema. The tables were put into three groups: substance (green), screening data (light orange), analyses (cyan). Only primary fields were shown in the tables. PK: primary key; FK: foreign key; chr: character; dbl: double; int: integer; dttm: date and time.

Figure 2

Quality check (QC) analysis for vehicle control (VC), positive control (PC), and duplicates (3 compounds, each of them has two substances) across three laboratories. (a) The response (%) distribution of three endpoints (Mortality@24, Mortality@120, MalformedAny+Mort@120) based on the response (%) from each plate of wells where embryos treated with only VC. (b) The distribution of standard deviation (SD) of the benchmark concentration (BMC) values of PC in all 120-hpf endpoints. Q2 represents the second quartile (median) of the distribution. (c) The BMC comparison of duplicates in all 120-hpf endpoints. The BMC is in log10(molar concentration) unit. The blue lines are diagonal lines with slope = 0, 1, −1 and intercept = 0. The blue dotted lines are diagonal lines with slope = 0.5, −0.5 and intercept = 0. The shape represents the three compounds: hollow circle as aldicarb; solid circle as bisphenol A; asterisk as valproic acid. Only BMC values different in replicate#1 and replicate#2 were kept in (c).

Figure 3

The distribution of the standard deviation (SD) values (dot) of BMC values of substances of endpoints in three laboratories (Lab-A: green; Lab-B: orange; Lab-C: blue). The endpoints were sorted based on the median value of the SD distribution.

Figure 4

The comparison of ontology terms that were recorded or non-recorded across three laboratories. The terms were organized (and were separated into groups on the heatmap) based on location: whole body, head, torso, appendage.

Figure 5

The comparison of the developmental defect groupings with number of associated recorded altered phenotypes and ontology terms across three laboratories. (a) developmental defects (granular). (b) developmental defects (general). The number in the cell represents the number of associated recorded altered phenotypes, and the number of associated ontology terms are in the parenthesis. The gray shading emphasized the number of recorded altered phenotypes (i.e., the darker gray color represents a higher number). The light-yellow color of the cell highlights the laboratory that did not have the associated developmental defect group recorded.

Figure 6

The hierarchical relationship of zebrafish altered phenotype ontology. The nodes from left to right are recorded altered phenotypes, ontology terms, developmental defects (granular), developmental defects (general). The color of recording nodes indicates the laboratory: green for Lab-A, orange for Lab-B, purple for Lab-C. The colors of the remaining nodes and flows indicate types from the highest hierarchy (developmental defects (general)). The number near each node summarizes the number of the incoming/outcoming flows. The number near the node of recorded altered phenotype indicates the number of the ontology terms associated with this recorded altered phenotype. The number near the node of ontology term indicates the number of laboratories having a recorded altered phenotype associated with this ontology term (maximum = 3 laboratories). The number near the node of either developmental defects (general) or developmental defects (granular) indicates the number of recorded altered phenotypes from all the laboratories associated with this group. Three ontology terms (light-green color, in the bottom of the plot) do not have the mapping of either developmental defects (general) nor developmental defects (granular) since they do not involve structural change.

Figure 7

The summary of the substance-induced altered phenotypes for the dose ranging finding (DRF) study of Lab-A. Only results that are specific in the respective chemical-ontology group (in this example, the general developmental defects grouping) pair are shown as colored dots. The size of the dot represents the degree of specificity score, and the color represents the degree of potency. The gray asterisk (*) indicates the respective substance-ontology group was checked but was non-specific or non-toxic. More examples are available in the Supplemental Figure S6.