摘要：The ever-increasing number of chemicals and complex mixtures demands a high-throughput and cost-effective approach for chemical safety assessment. High-throughput transcriptomics (HTT) is promising in investigating genome-scale perturbation of chemical exposure in concentration-dependent manner. However, the application of HTT has been limited due to lack of methodology for single chemicals and mixture assessment. This study aimed to evaluate the ability of a newly-developed human reduced transcriptomics (RHT) approach to assess pathway-based profiles of single chemicals, and to develop a biological pathway-based approach for benchmarking mixture potency using single chemical-based prediction model. First, concentration-dependent RHT were used to qualitatively and quantitatively differentiate pathway-based patterns of different chemicals, using three model toxicants, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), triclosan (TCS) and 5-Chloro-6-hydroxy-2,2′,4,4′-tetrabromodiphenyl ether (5-Cl-6-OH-BDE-47). AHR-regulated genes and pathways were most sensitively induced by TCDD, while TCS and 5-Cl-6-OH-BDE-47 were much less potent in AHR-associated activation, which was concordant with known MoA of each single chemical. Second, two artificial mixtures and their components of twelve individual chemicals were performed with concentration-dependent RHT. Concentration addition (CA) and independent action (IA) models were used to predict transcriptional potency of mixtures from transcriptomics of individual chemicals. For overall bioactivity, CA and IA models can both predict potency of observed responses within 95% confidence interval. For specific biological processes, multiple biological processes such as hormone signaling and DNA damage can be predicted using CA models for mixtures. The concentration-dependent RHT can provide a powerful approach for qualitative and quantitative assessment of biological pathway perturbated by environment chemical and mixtures.
关键词：Transcriptomics ; Concentration-dependent ; Biological potency ; Mixture assessment ; 5-Cl-6-OH-BDE-47 5-Chloro-6-hydroxy-2,2′,4,4′-tetrabromodiphenyl ether ; AHR Aryl hydrocarbon receptor ; AOP Adverse outcome pathway ; BaP Benzo(a)pyrene ; BbF Benzo(b)fluoranthene ; BPA Bisphenol A ; CA Concentration addition ; CAR Constitutive androstane receptor ; CLP Chlorophene ; CPD Cyprodinil ; CRGs Concentration-responsive genes ; DAZ Diazinon ; DFC Diclofenac ; DIR Diuron ; EDA Effect-directed analysis ; ES Enrichment scores ; GCA Generalized concentration addition model ; GES Genistein ; GO Gene Ontology ; GSEA Gene set enrichment analysis ; HTS High-throughput screening ; HTT High-throughput transcriptomics ; IA Independent addition ; KEGG Kyoto Encyclopedia of Genes and Genomes ; MIE Molecular initiating event ; MoA Mode of action ; PAHs Polycyclic aromatic hydrocarbons ; PCZ Propiconazole ; POD Point of departure ; PODgene Gene-level point of departure ; PODpath Pathway-level point of departure ; PODT Transcriptional point of departure ; PXR Pregnane X receptor ; RHT Reduced human transcriptomics ; ROS Reactive oxygen species ; SD Standard derivation ; TCDD 2,3,7,8-tetrachlorodibenzo-p-dioxin ; TCS Triclosan ; TCS Triclosan ; ToxPi Toxicological Prioritization Index ; TPP Triphenylphosphate
