RESUMO
Perfluorooctanoic acid (PFOA) is a persistent environmental contaminant that can accumulate in the human body due to its long half-life. This substance has been associated with liver, pancreatic, testicular and breast cancers, liver steatosis and endocrine disruption. PFOA is a member of a large group of substances also known as "forever chemicals" and the vast majority of substances of this group lack toxicological data that would enable their effective risk assessment in terms of human health hazards. This study aimed to derive a health-based guidance value for PFOA intake (ng/kg BW/day) from in vitro transcriptomics data. To this end, we developed an in silico workflow comprising five components: (i) sourcing in vitro hepatic transcriptomics concentration-response data; (ii) deriving molecular points of departure using BMDExpress3 and performing pathway analysis using gene set enrichment analysis (GSEA) to identify the most sensitive molecular pathways to PFOA exposure; (iii) estimating freely-dissolved PFOA concentrations in vitro using a mass balance model; (iv) estimating in vivo doses by reverse dosimetry using a PBK model for PFOA as part of a quantitative in vitro to in vivo extrapolation (QIVIVE) algorithm; and (v) calculating a tolerable daily intake (TDI) for PFOA. Fourteen percent of interrogated genes exhibited in vitro concentration-response relationships. GSEA pathway enrichment analysis revealed that "fatty acid metabolism" was the most sensitive pathway to PFOA exposure. In vitro free PFOA concentrations were calculated to be 2.9% of the nominal applied concentrations, and these free concentrations were input into the QIVIVE workflow. Exposure doses for a virtual population of 3,000 individuals were estimated, from which a TDI of 0.15 ng/kg BW/day for PFOA was calculated using the benchmark dose modelling software, PROAST. This TDI is comparable to previously published values of 1.16, 0.69, and 0.86 ng/kg BW/day by the European Food Safety Authority. In conclusion, this study demonstrates the combined utility of an "omics"-derived molecular point of departure and in silico QIVIVE workflow for setting health-based guidance values in anticipation of the acceptance of in vitro concentration-response molecular measurements in chemical risk assessment.
RESUMO
Malaria is a tropical disease caused by Plasmodium spp. and transmitted by the bite of infected Anopheles mosquitoes. Protein kinases (PKs) play key roles in the life cycle of the etiological agent of malaria, turning these proteins attractive targets for antimalarial drug discovery campaigns. As part of an effort to understand parasite signaling functions, we report the results of a bioinformatics pipeline analysis of PKs of eight Plasmodium species. To date, no P. malariae and P. ovale kinome assemble has been conducted. We classified, curated and annotated predicted kinases to update P. falciparum, P. vivax, P. yoelii, P. berghei, P. chabaudi, and P. knowlesi kinomes published to date, as well as report for the first time the kinomes of P. malariae and P. ovale. Overall, from 76 to 97 PKs were identified among all Plasmodium spp. kinomes. Most of the kinases were assigned to seven of nine major kinase groups: AGC, CAMK, CMGC, CK1, STE, TKL, OTHER; and the Plasmodium-specific group FIKK. About 30% of kinases have been deeply classified into group, family and subfamily levels and only about 10% remained unclassified. Furthermore, updating and comparing the kinomes of P. vivax and P. falciparum allowed for the prioritization and selection of kinases as potential drug targets that could be explored for discovering new drugs against malaria. This integrated approach resulted in the selection of 37 protein kinases as potential targets and the identification of investigational compounds with moderate in vitro activity against asexual P. falciparum (3D7 and Dd2 strains) stages that could serve as starting points for the search of potent antimalarial leads in the future.
