Histone markers identify the mode of action for compounds positive in the TK6 micronucleus assay

102

Several endpoints associated with cellular responses to DNA damage as well as overt cytotoxicity were multiplexed into a miniaturized, “add and read” type flow cytometric assay. Reagents included a detergent to liberate nuclei, propidium iodide and RNase to serve as a pan-DNA dye, fluorescent antibodies against γH2AX, phospho-histone H3, and p53, and fluorescent microspheres for absolute nuclei counts. The assay was applied to TK6 cells and 67 diverse reference chemicals that served as a training set. Exposure was for 24 hrs in 96 well plates, and unless precipitation or foreknowledge about cytotoxicity suggested otherwise, the highest concentration was 1 mM. At 4 and 24 hrs aliquots were removed and added to microtiter plates containing the reagent mix. Following a brief incubation period robotic sampling facilitated walk-away data acquisition. Univariate analyses identified biomarkers and time points that were valuable for classifying agents into one of three groups: clastogenic, aneugenic, or non-genotoxic. These mode of action predictions were optimized with a forward-stepping process that considered Wald test p-values, receiver operator characteristic curves, and pseudo R2 values, among others. A particularly high performing multinomial logistic regression model was comprised of four factors: 4hr γH2AX and phospho-histone H3 values, and 24 hr p53 and polyploidy values. For the training set chemicals, the four-factor model resulted in 94% concordance with our a priori classifications. Cross validation occurred via a leave-one-out approach, and in this case 91% concordance was observed. A test set of 17 chemicals that were not used to construct the model were evaluated, some of which utilized a short-term treatment in the presence of a metabolic activation system, and in 16 cases mode of action was correctly predicted. These initial results are encouraging as they suggest a machine learning strategy can be used to rapidly and reliably predict new chemicals’ genotoxic mode of action based on data from an efficient and highly scalable multiplexed assay.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genotoxic mode of action predictions from a multiplexed flow cytometric assay and a machine learning approach

Bryce

Bernacki

Bemis

et al. 2016

102

“…These goals explain recent efforts to develop higher information content genotoxicity assays that are amenable to rapid, automatic data acquisition platforms. Diverse approaches have been investigated, and include automation of conventional genotoxicity endpoints [Avlasevich et al, 2006;Rossnerova et al, 2011], identification of toxicogenomic signatures [Li et al, 2015], use of stably transfected cells with reporters for GADD45a, p53, or other DNA damage signaling pathways [Yang and Duerksen-Hughes, 1998;Hendriks et al, 2012;Walmsley and Tate, 2012], and use of various phenotype-based biomarkers of genotoxicity, for example induction of hypo-/ hyperdiploidy in mitotic cells [Muehlbauer and Schuler, 2005;Muehlbauer et al, 2008], or gH2AX [Audebert et al, 2010;Smart et al, 2011;Garcia-Canton et al, 2013;Nikolova et al, 2014;Cheung et al, 2015].…”

mentioning

confidence: 99%

Interlaboratory evaluation of a multiplexed high information content in vitro genotoxicity assay

Bryce

Bernacki

Bemis

et al. 2017

Self Cite

We previously described a multiplexed in vitro genotoxicity assay based on flow cytometric analysis of detergent-liberated nuclei that are simultaneously stained with propidium iodide and labeled with fluorescent antibodies against p53, γH2AX, and phospho-histone H3. Inclusion of a known number of microspheres provides absolute nuclei counts. The work described herein was undertaken to evaluate the interlaboratory transferability of this assay, commercially known as MultiFlow™ DNA Damage Kit— p53, γH2AX, Phospho-histone H3. For these experiments seven laboratories studied reference chemicals from a group of 84 representing clastogens, aneugens, and non-genotoxicants. TK6 cells were exposed to chemicals in 96-well plates over a range of concentrations for 24 hrs. At 4 and 24 hrs cell aliquots were added to the MultiFlow reagent mix and following a brief incubation period flow cytometric analysis occurred, in most cases directly from a 96-well plate via a robotic walk-away data acquisition system. Multiplexed response data were evaluated using two analysis approaches, one based on global evaluation factors (i.e., cutoff values derived from all inter-laboratory data), and a second based on multinomial logistic regression that considers multiple biomarkers simultaneously. Both data analysis strategies were devised to categorize chemicals as predominately exhibiting a clastogenic, aneugenic, or non-genotoxic mode of action (MoA). Based on the aggregate 231 experiments that were performed, assay sensitivity, specificity, and concordance in relation to a priori MoA grouping were ≥ 92%. These results are encouraging as they suggest that two distinct data analysis strategies can rapidly and reliably predict new chemicals’ predominant genotoxic MoA based on data from an efficient and transferable multiplexed in vitro assay.

“…The flow cytometric MN assay (MicroFlow ® ) was considered positive if a ≥3‐fold increase in MN frequency was observed compared to the solvent control [Bryce et al, ]. Our findings revealed that two genotoxic compounds (H 2 O 2 and BP) were judged inconclusive and three nongenotoxicants (CCCP, TG, and TC) were tested positive and therefore represented the frequently misleading positives in the MNT due to secondary effects [Walmsley and Billinton, ; Bryce et al, ; Cheung et al, ]. For these studies, cytotoxicity measurements were based on RNC that has been shown to underestimate cytotoxicity compared to relative population doubling (RPD) or relative increase in cell count (RICC) [Fellows et al, ; Galloway et al, ].…”

Section: Discussionmentioning

confidence: 80%

Classification of in vitro genotoxicants using a novel multiplexed biomarker assay compared to the flow cytometric micronucleus test

Wilde

Dambowsky

Hempt

et al. 2017

Regulatory in vitro genotoxicity testing exhibits shortcomings in specificity and mode of action (MoA) information. Thus, the aim of this work was to evaluate the performance of the novel MultiFlow V R assay composed of mechanistic biomarkers quantified in TK6 cells after treatment (4 and 24 hr): gH2AX (DNA double strand breaks), phosphorylated H3 (mitotic cells), translocated p53 (genotoxicity), and cleaved PARP1 (apoptosis). A reference dataset of 31 compounds with well-established MoA was studied using the MicroFlow V R micronucleus assay. A positive call was raised following the earlier published criteria from Litron Laboratories. In the light of our data, these evaluation criteria should probably be adjusted since only 8/11 (73%) nongenotoxicants and 18/20 (90%) genotoxicants were correctly identified. Moreover, there is a need for new in vitro tools to delineate the predominant MoA as in the MicroFlow V R assay only 5/9 (56%) aneugens and 4/11 (36%) clastogens were correctly classified. In contrast, the MultiFlow V R assay provides more in-depth information about the MoA and therefore reliably discriminates clastogens, aneugens, and nongenotoxicants. By using a labspecific, practical threshold for the aforementioned biomarkers, 10/11 (91%) nongenotoxicants and 19/20 genotoxicants (95%), 9/11 (82%) clastogens, and 8/9 (89%) aneugens were correctly categorized, suggesting a clear improvement over the MicroFlow V R . Furthermore, the MultiFlow markers were benchmarked against established methods to assess the validity of the data. Altogether, these findings demonstrated good agreement between the MultiFlow V R assay and the benchmarking methods. Finally, p21 may improve class discrimination given the correct identification of 4/4 (100%) aneugens and 2/5 (40%) clastogens.