A flow cytometric technique for scoring the incidence of micronucleated reticulocytes in rat peripheral blood was compared to a standard microscopy-based procedure. For these studies, groups of five male Sprague-Dawley rats were treated with vehicle or a broad range of chemical genotoxicants: 6-thioguanine, N-methyl-N'-nitro-N-nitrosoguanidine, vincristine, methylaziridine, acetaldehyde, methyl methanesulfonate, benzene, monocrotaline, and azathioprine. Animals were treated once a day for up to 2 days, and peripheral blood was collected between 24 and 48 h after the final administration. These samples were processed for flow cytometric scoring and microscopy-based analysis using supravital acridine orange staining, and the percentage of reticulocytes and micronucleated reticulocytes was determined for each sample. The resulting data demonstrate good agreement between these scoring methodologies, although careful execution of the flow cytometric method was found to enhance the micronucleus assay by reducing both scoring time and scoring error. These data add further support to the premise that the peripheral blood compartment of rats can be used effectively to detect genotoxicant-induced micronuclei.

The growth hormone releasing peptides (GHRPs) hexarelin, ipamorelin, alexamorelin, GHRP-1, GHRP-2, GHRP-4, GHRP-5, and GHRP-6 are all synthetic met-enkephalin analogues that include unnatural D-amino acids. They were designed specifically for their ability to stimulate growth hormone release and may serve as performance enhancing drugs. To regulate the use of these peptides within the horse racing industry and by human athletes, a method is presented for the extraction, derivatization, and detection of GHRPs from equine and human urine. This method takes advantage of a highly specific solid-phase extraction combined with a novel derivatization method to improve the chromatography of basic peptides. The method was validated with respect to linearity, repeatability, intermediate precision, specificity, limits of detection, limits of confirmation, ion suppression, and stability. As proof of principle, all eight GHRPs or their metabolites could be detected in urine collected from rats after intravenous administration.

The in vitro MultiFlow® DNA Damage Assay multiplexes γH2AX, p53, phospho-histone H3, and polyploidization biomarkers into a single flow cytometric analysis. The current report describes a tiered sequential data analysis strategy based on data generated from exposure of human TK6 cells to a previously described 85 chemical training set and a new pharmaceutical-centric test set (n = 40). In each case, exposure was continuous over a range of closely spaced concentrations, and cell aliquots were removed for analysis following 4 and 24 hr of treatment. The first data analysis step focused on chemicals’ genotoxic potential, and for this purpose, we evaluated the performance of a machine learning (ML) ensemble, a rubric that considered fold increases in biomarkers against global evaluation factors (GEFs), and a hybrid strategy that considered ML and GEFs. This first tier further used ML output and/or GEFs to classify genotoxic activity as clastogenic and/or aneugenic. Test set results demonstrated the generalizability of the first tier, with particularly good performance from the ML ensemble: 35/40 (88%) concordance with a priori genotoxicity expectations and 21/24 (88%) agreement with expected mode of action (MoA). A second tier applied unsupervised hierarchical clustering to the biomarker response data, and these analyses were found to group certain chemicals, especially aneugens, according to their molecular targets. Finally, a third tier utilized benchmark dose analyses and MultiFlow biomarker responses to rank genotoxic potency. The relevance of these rankings is supported by the strong agreement found between benchmark dose values derived from MultiFlow biomarkers compared to those generated from parallel in vitro micronucleus analyses. Collectively, the results suggest that a tiered MultiFlow data analysis pipeline is capable of rapidly and effectively identifying genotoxic hazards while providing additional information that is useful for modern risk assessments—MoA, molecular targets, and potency.

MultiFlow ® DNA Damage-p53, γH2AX, Phospho-Histone H3 is a miniaturized, flow cytometry-based assay that provides genotoxic mode of action information by distinguishing clastogens, aneugens, and nongenotoxicants. Work to date has focused on the p53-competent human cell line TK6. While mammalian cell genotoxicity assays typically supply exogenous metabolic activation in the form of concentrated rat liver S9, this is a less-than-ideal approach for several reasons, including 3Rs considerations. Here, we describe our experiences with low concentration S9 and saturating co-factors which were allowed to remain in contact with cells and test chemicals for 24 continuous hours. We exposed TK6 cells in 96-well plates to each of 15 reference chemicals over a range of concentrations, both in the presence and absence of 0.25% v/v phenobarbital/β-naphthoflavone-induced rat liver S9. After 4 and 24 hr of treatment cell aliquots were added to wells of a microtiter plate containing the working detergent/stain/antibody cocktail. After a brief incubation robotic sampling was employed for walk-away flow cytometric data acquisition.PROAST benchmark dose (BMD) modeling was used to characterize the resulting dose-response curves. For each of the 8 reference pro-genotoxicants studied, relative nuclei count, γH2AX, and/or p53 biomarker BMD values were order(s) of magnitude lower for 0.25% S9 conditions compared to 0% S9. Conversely, several of the direct-acting reference chemicals exhibited appreciably lower cytotoxicity and/or genotoxicity BMD values in the presence of S9 (eg, resorcinol). These results prove the efficacy of the low concentration S9 system, and indicate that an efficient and highly scalable multiplexed assay can effectively identify chemicals that require bioactivation to exert their genotoxic effects. K E Y W O R D SDNA damage, flow cytometry, metabolic activation, γH2AX, p53

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