The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry

Accepted Manuscript Title: The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry Authors: Matthew A. Rodrigues, Lindsay A. Beaton-Green, Ruth C. Wilkins, Michael F. Fenech PII: DOI: Reference:

S1383-5718(18)30049-4 https://doi.org/10.1016/j.mrgentox.2018.05.003 MUTGEN 402906

To appear in:

Mutation Research

Received date: Revised date: Accepted date:

14-2-2018 27-3-2018 3-5-2018

Please cite this article as: Matthew A.Rodrigues, Lindsay A.Beaton-Green, Ruth C.Wilkins, Michael F.Fenech, The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry, Mutation Research/Genetic Toxicology and Environmental Mutagenesis https://doi.org/10.1016/j.mrgentox.2018.05.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

The potential for complete automated scoring of the cytokinesis block micronucleus cytome assay using imaging flow cytometry

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Matthew A. Rodriguesa,*, Lindsay A. Beaton-Greenb, Ruth C. Wilkinsb, Michael F. Fenechc

Amnis (part of MilliporeSigma), 645 Elliott Ave W, Suite 100, Seattle, WA, 98119, USA

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Consumer and Clinical Radiation Protection Bureau, Health Canada, Ottawa, Ontario, K1A

1C1, Canada

Genome Health Foundation, North Brighton, SA, 5048, Australia

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*Corresponding author. Email address: [email protected] (M.A.

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Rodrigues)

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Graphical Abstract

Highlights  The CBMN cytome assay is typically performed by visual microscopy 

The assay includes three biomarkers of DNA damage (MN, NPB, NBUD)

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The assay also includes three biomarkers of cytotoxicity (NDI, necrosis, apoptosis)

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Automated microscopy or flow cytometry cannot score the full range of biomarkers

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Performing the assay by imaging flow cytometry may overcome these limitations

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Abstract The lymphocyte Cytokinesis-Block Micronucleus (CBMN) assay was originally developed for the measurement of micronuclei (MN) exclusively in binucleated (BN) cells which represent the population of cells that can express MN because they completed nuclear division. Recently the

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assay has evolved into a comprehensive cytome method to include biomarkers that measure chromosomal instability and cytotoxicity by quantification of nuclear buds (NBUDs),

nucleoplasmic bridges (NPBs) and apoptotic/necrotic cells. Furthermore, enumeration of monoand polynucleated cells allows for computation of the nuclear division index (NDI) to assess mitotic activity. Typically performed by manual microscopy, the CBMN cytome assay is

laborious and subject to scorer bias and fatigue, leading to inter- and intra-scorer variability. Automated microscopy and conventional flow cytometry methods have been developed to

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automate scoring of the traditional and cytome versions of the assay. However, these methods

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have several limitations including the requirement to create high-quality microscope slides, lack

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of staining consistency and sub-optimal nuclear/cytoplasmic visualization. In the case of flow cytometry, stripping of the cytoplasmic membrane makes it impossible to measure MN in BN

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cells, calculating the NDI and quantifying apoptotic or necrotic cells. Moreover, the absence of cellular visualization using conventional flow cytometry, makes it impossible to quantify

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NBUDs and NPBs. In this review, we propose that imaging flow cytometry (IFC), which

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combines high resolution microscopy with flow cytometry, may overcome these limitations. We demonstrate that by using IFC, images from cells in suspension can be captured, removing the

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need for microscope slides and allowing visualization of intact cytoplasmic membranes and DNA content. Thus, mono-, bi- and polynucleated cells with and without MN can be rapidly and

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automatically identified and quantified. Finally, we present high-resolution cell images containing NBUDs and NPBs, illustrating that IFC possesses the potential for completely

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automated scoring of all components of the CBMN cytome assay. LIST OF ABBREVIATIONS BF brightfield BN binucleated C+ centromere-positive C– centromere-negative CBMN cytokinesis block micronucleus CBMN Cyt cytome assay 3 of 38

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cytokinesis block proliferation index charge-coupled device cytochalasin-B double strand break ethidium monoazide fluorescence in situ hybridization false positive Image Data Exploration and Analysis Software imaging flow cytometry ImageStream®X mouse lymphoma micronucleus mononucleated nuclear bud nuclear division index nucleoplasmic bridge peripheral blood lymphocyte polynucleated replication index spot distance minimum human lymphoblast

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CBPI CCD Cyt-B DSB EMA FISH FP IDEAS® IFC ISX L5178Y MN MONO NBUD NDI NPB PBL POLY RI SDM TK6

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Keywords: Micronucleus Assay, Lymphocytes, TK6 cells, Chemical genotoxins, Radiation biodosimetry, Imaging flow cytometry

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1. Introduction With advances in technology as well as increasing awareness and concern for possible health

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effects from environmental, consumer and medical products, pharmaceuticals, chemicals and large-scale emergency incidents, the fields of toxicological assessment and radiation

biodosimetry are evolving quickly. As such, it is becoming increasingly necessary to develop

rapid, reproducible, high-throughput and statistically robust in vitro testing methods to estimate genotoxicity of biological doses from various exposure pathways [1-3]. Much of this work involves measuring the amount of induced DNA damage from exposure to chemical and

radiological genotoxins. One of the most widely used in vitro techniques for identifying and

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quantifying chromosomal damage resulting from exposure to both of these agents is the

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micronucleus (MN) assay in human lymphocytes [4-7]. During mitosis, dividing lymphocytes

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that contain chromosomal aberrations often express this damage as MN, formed from whole chromosomes or chromosome fragments that do not interact with the mitotic spindle at the

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metaphase-anaphase transition. As a result, the lagging whole chromosomes or chromosome fragments are not included in either of the main daughter nuclei at the completion of mitosis and

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become expressed as a MN once the cell has completed nuclear division [8-10]. It is therefore

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essential to verify that the cells scored for MN are exclusively those that have completed a single nuclear division. These cells can be easily identified as binucleated (BN) cells by blocking

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cytokinesis with cytochalasin-B (Cyt-B) [4, 8, 9]. This version of the MN assay is known as the cytokinesis-block micronucleus (CBMN) assay and MN are scored exclusively in BN cells (Fig.

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1a), which ensures that only first metaphase cells are analyzed. It should be noted that the fate of MN in non-Cyt-B blocked cells is not well characterized, and MN might be extruded from the cell or reincorporated into one of the main nuclei following a second nuclear division [11-14].

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This and any variation in mitotic rate due to inter-individual differences in response to mitogens used to stimulate nuclear division may result in an underestimation of MN [11]. Scoring MN in BN cells, as per the CBMN assay, results in a more accurate MN frequency estimation as the score is restricted only to those cells that can express DNA damage as MN because they have completed nuclear division. For in vitro genetic toxicology applications, the use of the lymphocyte MN assay with and without Cyt-B is common for testing toxic thresholds of dose 5 of 38

but in the latter case (i.e. without Cyt-B) evidence has to be provided that the nuclear division rate has not been substantially diminished to the extent of leading to a false negative result [4]. The lymphocyte CBMN assay is the preferred method for dose estimation in biodosimetry applications following in vivo ionizing radiation exposure [5] and for determining whether environmental or occupational exposure to chemical genotoxins has resulted in an increase in

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DNA damage [15].

Visual microscope-based scoring of BN cells and MN is a laborious task that is time-

consuming and can be subjective in nature. Over the past two decades, there has been significant interest and progress towards automation of the CBMN assay to eliminate individual bias and to enhance sample throughput and statistical power. The MNScore software system for the MetaferTM slide-scoring module (Metasystems, Germany) as well as the PathFinderTM

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CellscanTM system (IMSTAR, Paris, France) have been developed, tested and recently validated

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to automatically identify MN [16-24]. Additionally, laser scanning cytometry systems have been developed, validated and used to visualize MN as well as the cytoplasm of BN cells [25-27].

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Furthermore, a conventional flow cytometry method has been developed to differentiate isolated

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MN from the main nuclei based on differences in fluorescence intensity [28-32]. Most recently, the CBMN assay has been adapted to imaging flow cytometry (IFC) which allows direct

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visualization of the cytoplasm using brightfield (BF) imagery together with the main nuclei and

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MN using fluorescent imagery. In addition, the IFC system allows for unattended data acquisition from samples as well as automated batch analysis through the use of an optimized, validated data analysis template that is applied uniformly to all data files. Furthermore, no

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additional user intervention steps or semi-automated scoring verification steps, such as those involved in some automated slide-scoring procedures, are required to verify that MN-positive

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events are indeed genuine [3, 33-37]. All imagery can be stored indefinitely in sample-specific data files, should re-evaluation be necessary.

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In recent years, the CBMN assay has evolved into a “cytome” assay (CBMN Cyt) of

chromosomal instability in which more nuclear anomalies and many more cells in the sample can be included in the analysis and categorized to provide a more comprehensive view of DNA damage, cytostasis and cell death [6, 7, 13, 38]. The CBMN Cyt assay is typically performed using visual microscopy to classify each cell cytologically according to Figure 1. The spectrum of biomarkers scored in the CBMN Cyt assay are as follows: 6 of 38

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MN scored in BN cells which provide a measure of chromosome breakage or loss as explained above. MN in BN cells is the best validated biomarker in the CBMN Cyt assay.

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Nucleoplasmic bridges (NPBs) which are formed between nuclei in BN cells when the centromeres of dicentric chromosomes or incompletely separated sister chromatids are pulled towards opposite poles of the cell at anaphase (Fig. 1b). NPBs provide a measure

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of genome damage either from incorrectly repaired DNA double strand breaks (DSB)

leading to asymmetrical exchange-type chromosome aberrations, or telomere end fusions or failure of sister chromatid separation, all of which cannot be scored through quantitation of MN [38]. 

Nuclear buds (NBUDs) have the same morphology as typical MN but are connected to the main nucleus by a stalk of nucleoplasmic material (Fig. 1c). They arise from the

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elimination of amplified DNA or unresolved DNA repair complexes from the nucleus

MN that have been formed in vivo may appear in MONO cells prior to nuclear division

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[39, 40].

ex vivo (Fig. 1d). MONO cells with MN can provide evidence for previous chronic in

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vivo exposures to genotoxic chemicals or ionizing radiation [6, 7, 41, 42]. NBUDS can also occur in non-divided mononucleated cells (Fig 1e). MN may arise from whole chromosomes or acentric fragments which can be

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differentiated through the identification of centromere-containing MN (Fig. 1f and 1g) [19]. The presence of centromere-positive (C+) MN indicates MN that are likely to be

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composed of a whole chromosome while centromere-negative (C–) MN indicate MN that have developed from acentric fragments, such as those that have occurred typically as a result of ionizing radiation exposure [19, 43, 44].

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Mononucleated (MONO), Binucleated (BN) and polynucleated (POLY) cells are an

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indicator of the number of cell divisions, with BN and POLY cells only accumulated in

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sufficient numbers for analysis in the presence of Cyt-B (Fig. 1h, 1i, 1j). Apoptotic and necrotic cells can be identified by the altered morphology and staining intensities of the cytosplasm and nucleus (Fig. 1k and 1l).

The results of this scoring can provide information on the status of the cell population as follows: 7 of 38

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Quantitation of MONO and POLY cells, as well as BN cells (Fig. 1h – 1j) enables calculation of a number of parameters, such as Nuclear Division Index (NDI), Replication Index (RI) and the Cytokinesis Block Proliferation Index (CBPI), that provide a measure of mitogen response and cytostatic impact of a specific agent.

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Determining the proportion of cells undergoing apoptosis or necrosis (Fig. 1k and 1l)

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provides important information on cytotoxicity and can quantify the viability status [13, 38]. 

Identification of MN, NPBs and NBUDs (Fig. 1a – 1c) provides a measure of chromosomal damage or instability.

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Scoring of MN and NBUDs in MONO peripheral blood lymphocytes (PBLs) (Fig. 1d and 1e) expressed prior to nuclear division during ex vivo culture can provide an indication of

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DNA damage that occurred in vivo in the dividing precursor cells in the bone marrow

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[13].

The purpose of this review is to demonstrate the potential and limitations of IFC to fully

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automate the CBMN Cyt assay. Additionally, several limitations of traditional automated micronucleus assay methods that make automated scoring of the full spectrum of biomarkers in

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the CBMN Cyt assay difficult or impossible to achieve will be discussed. This review describes:

(1) Current automated CBMN assay scoring methods and their limitations concerning

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achieving complete automation of the CBMN Cyt assay. (2) The unique features of IFC, and recent advances made in the IFC-based CBMN assay in radiation biodosimetry.

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(3) The potential for IFC to fully automate the CBMN Cyt assay for application in both

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radiation biodosimetry and genetic toxicology testing generally.

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2. Limited practicality of microscope and conventional flow cytometry-based techniques for the lymphocyte CBMN cytome assay 2.1. Conventional microscopy and flow cytometry-based methods for the MN and CBMN assays A validated visual microscope slide-scoring method for both the in vitro MN and CBMN

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assays has been used extensively to identify potential toxicological effects of chemicals, drugs or drug compounds [45-50]. Use of the CBMN assay as a method for dose estimation in radiation biodosimetry has also been validated and well documented in the literature over the last three

decades [5, 43, 51-61]. In in vitro and in vivo toxicology, following exposure to various doses of a potential genotoxic agent, the frequency of MN is determined in both MONO and BN cells. MN frequencies from treated samples are then compared to MN frequencies from controls,

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allowing for the determination of a specific dose (or doses) of agents that yield a genotoxic

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response [15, 50]. In radiation biodosimetry, the frequency of MN per BN cell in a blood sample from a patient suspected of having been exposed to ionizing radiation is determined and then

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compared to a previously developed dose response calibration curve. This allows for an estimate

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of dose to the individual such that medical intervention, if necessary, may begin as quickly as possible [62, 63]. Visual microscope slide-scoring of the CBMN assay in these applications has

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some important drawbacks, such as the need to prepare slides from the cells in culture and the laborious nature of physically scoring many samples. In radiation biodosimetry, it has recently

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been demonstrated that scoring 200 BN cells, rather than the recommended 1000, which takes an experienced scorer roughly 5-10 min can provide accurate dose estimates for triage [63].

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However, if several hundred individuals require screening for exposure, manual microscopy remains impractical. Similarly, in genetic toxicology testing, at least 1000 BN cells must be

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scored per sample [4] and scoring of many samples can introduce scorer fatigue and variability which may generate substantial discrepancies in results between scorers both within and between

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laboratories [64]. Furthermore, visual microscopy suffers from the time-consuming aspect of creating high-quality slides, which varies widely based on laboratory conditions and technical expertise. In an effort to increase sample throughput and reproducibility of scoring, automated microscopy methods and conventional flow cytometry methods have been developed. The three main microscope-based methods that have been developed for automated CBMN slide-scoring

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are the MetaferTM MNScore (Metasystems, GmbH Altlussheim, Germany) [16-18], the PathFinderTM CellscanTM (IMSTAR, Paris, France) [23, 24] and the Compucyte iCyte® laser scanning cytometer (Thorlabs, Sterling VA, USA) [25, 26]. All three systems allow for automatic scanning of slides to identify nuclei and MN in cells and to identify and record images of MONO, BN and POLY cells. In each system, the number of MN in BN cells are enumerated

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automatically and 1000 BN cells can be scanned and scored in about 5 – 10 minutes depending on the quality of the slides [65]. Furthermore, saved images can be reviewed as required and stored slides can be re-loaded to review cells under the microscope.

A conventional flow cytometry method to perform the in vitro MN assay has also been

developed by Litron Laboratories (Rochester, NY, USA) [28, 29]. As this method requires lysing of cells to release the main nuclei and MN, cytokinesis blocking is not used. Viable nuclei are

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differentiated from necrotic or apoptotic cells using ethidium monoazide (EMA). EMA-free

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nuclei are then stained with SYTOX green and are enumerated by acquiring 20,000 EMAnegative events per sample [28]. The main nuclei and MN are then differentiated based on

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SYTOX green intensity.

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Despite significant advances in each of these methods, several specific limitations for automated microscope slide-scoring and conventional flow cytometry methods are inherent in

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terms of both the traditional CBMN assay as well as the CBMN Cyt assay. These limitations are

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discussed below.

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2.2. Limitations of automated microscope slide-scoring methods Automated microscope slide-scoring methods have increased sample throughput in

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comparison to manual scoring methods. However, a number of limitations in these methods exist such as lengthy and/or complex sample processing protocols, the requirement to consistently

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create high quality microscope slides, and high rates of false positive (FP) BN cells and MN. Many current fixation methods typically involve some combination of methanol and acetic acid and often require that samples be resuspended and stored in the fixative for many hours [22] or that prepared slides be dried overnight [24]. This can be problematic, especially in the case of triage radiation biodosimetry with a high number of potential casualties requiring results as rapidly as possible. Another significant consideration for automated scoring algorithms is

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ensuring that slides are prepared with an optimal cell density. On the MetaferTM system, the cytoplasm is not visualized and the software must rely on mathematical algorithms trained using the proximity of the main nuclei and MN in order to correctly identify BN cells along with their associated MN. On slides with cell densities that are too low, the frequency of MN can be underestimated and on slides with cell densities that are too high, BN cells and MN are difficult

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to resolve due to the lack of cytoplasmic boundaries [22]. Furthermore, using the iCyte® system, cells with overlapping cytoplasmic boundaries on high density slides can be difficult to separate and score accurately [25]. The false positive (FP) rate of BN cells using the MetaferTM system

has been reported to be as high as 6.3% [16], and using the PathfinderTM system was shown to be higher than 1% and greater than 50% in some samples [24]. Rates of FP and false negatives (FN) using the iCyte® system have not been reported. The use of a calibration curve in radiation

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biodosimetry would account for FPs, making this high rate of FPs slightly more acceptable.

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However, in in vitro genetic toxicology studies, calibration curves are not used when comparing treated samples to control samples. This means that high rates of FP MN may lead to misleading

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results for genotoxicology studies. To address the FP events, visual verification of the image

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gallery for each sample is typically performed to ensure accuracy in the BN cell and MN populations. Although this verification step only takes a few minutes, this further reduces sample

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throughput and may re-introduce scorer bias [16, 24].

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With respect to the CBMN Cyt assay, until recently MONO and POLY cells were not able to be scored using automated slide-scoring platforms, but in the last few years algorithms have been generated that allow for these events to be identified and quantified. However, in most cases,

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slides must be scanned twice: first for BN cells and then re-scanned to identify MONO and POLY cells. This process can take an additional 20-40 min per slide, depending on slide quality

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and cell density [21]. Additionally, with regards to automating the CBMN Cyt assay, NPBs and NBUDs have yet to be reliably identified, however, image analysis algorithms have been

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recently developed towards detecting and scoring these events [66, 67]. While recent advances in automated slide-scoring methods have expanded the applicability

of the systems described above, the necessity to create high quality microscope slides remains the major bottleneck regarding throughput for the CBMN assay and may be a challenge for the analysis of additional components for the CBMN Cyt assay.

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2.3. Limitations of conventional flow cytometry methods Conventional flow cytometry methods to perform the MN assay were first developed in the 1980s and 1990s [68-71]. Irradiated mouse Ehrlich ascites tumor cells were lysed to generate a suspension in which MN were separated from the main nuclei. The presence of MN was then

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identified by quantifying differences in DNA intensity [68]. One major drawback of this

technique however, was the inability to distinguish MN from the chromatin of necrotic and

mid/late apoptotic bodies. To address these issues, Litron Laboratories expanded the original

method, using EMA to identify and differentiate necrotic and apoptotic bodies from free-floating SYTOX Green-stained nuclei and MN in suspension in mouse lymphoma (L5178Y) cells and human lymphoblast (TK6) cells [28-32].

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The two main limitations to adapting this method to the CBMN Cyt assay stem from the

absence of Cyt-B in cell cultures and the requirement to lyse cells in order to liberate the main

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nuclei and MN. The absence of Cyt-B does not allow for the quantification of the rate of MN per

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BN cell, which is the fundamental endpoint in the CBMN assay. In addition, as discussed, the

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uncertainty regarding the fate of MN in non-Cyt-B blocked cells may cause an underestimation of MN [14]. Despite being able to somewhat differentiate MN from other particles that may be in

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suspension [28], the requirement to lyse the cell membrane creates a solution that may contain other debris such as individual chromosomes or chromosome aggregates, chromatin granules

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from apoptotic cells or individual apoptotic bodies or other cellular debris. As such, a clear distinction between MN and DNA positive debris is not guaranteed [25]. In addition, lysing of

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the cell membrane makes it impossible to associate a MN with a particular cell or other nuclear anomalies within that cell, or to quantify events in which multiple MN are contained within a

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single cell, an important parameter at higher doses [72]. Furthermore, the number of POLY cells, which is required to calculate the NDI, RI or CBPI cannot be determined [4].

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While performing the MN assay using conventional flow cytometry does allow for very large

numbers of events to be captured rapidly, the data analysis to identify MN and the main nuclei relies on characteristic distribution of DNA intensity histograms and bivariate plots in which gating is typically based on a priori knowledge. This can introduce subjective gate boundary placement since visual verification of cells is not possible and therefore, optimization and verification of boundary locations cannot be performed. Unlike microscopy-based techniques or

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IFC techniques, no data beyond histograms and bivariate plots can be obtained for individual cells using conventional flow cytometers. Although recent advances in conventional flow cytometry methods have allowed the MN assay to be performed in genetic toxicology testing, differentiation between MN and other DNA positive debris remains an issue, especially at high doses [32].

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In the context of an automated flow CBMN Cyt assay, the lack of any cell imaging is the

largest limiting factor as important parameters such as NBUDs and NPBs cannot be quantified using conventional flow cytometry methods. In addition, even if Cyt-B were employed in the

assay, cytoplasmic stripping during sample processing does not allow for the distinction to be made between the rate of MN contained in MONO cells and the rate of MN contained in BN

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cells.

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3. Use of imaging flow cytometry to perform the lymphocyte CBMN assay in radiation biodosimetry 3.1. Overview of imaging flow cytometry technology and applications

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Imaging flow cytometry (IFC) (e.g. ImageStream®X (ISX) (Amnis, part of MilliporeSigma)) combines the visual information content of fluorescent microscopy with the speed, statistical robustness and rare event capture capability of conventional flow cytometry. As with

conventional flow cytometers, particles in suspension are introduced into a fluidics system and

hydrodynamically focused into the center of the flow cell cuvette. Particles are then interrogated by a brightfield (BF) light-emitting diode and at least one laser. This creates transmitted,

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scattered and fluorescent light based on the morphology and labelling of particles which is then collected by objective lenses. This light then passes through a spectral decomposition element

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that simultaneously generates spectral images of each object separated into specific wavelength

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ranges and focuses them onto a charge-coupled device (CCD) camera. Current technology is

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capable of generating up to 12 images per cell [73].

All BF and fluorescent images captured from a sample are stored in a data file that allows analysis to be performed at any time post-acquisition using a software such as the Image Data

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Exploration and Analysis Software (IDEAS®) (Amnis, part of MilliporeSigma). The data sets

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allow the linkage between cell images and histograms or bivariate plots so that a dot on any bivariate plot can be selected and its corresponding image will be displayed in the image gallery

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(Fig. 2a). In addition, any image selected from the image gallery is automatically highlighted on all bivariate plots in the analysis area. This allows efficient gating strategies to be created

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through the use of truth populations which are created by visual confirmation of the images containing the desired features. Images of a population of interest can be selected, saved as a new population and displayed on any bivariate plot. Gates with optimized boundaries can then be

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created such that the positive population is included and the majority of the negative population and other debris are excluded (Fig. 2b). Image analysis in IDEAS® is performed through the use of masks and features. Masks highlight pixels within a specified region of interest of an image while features are mathematical expressions that contain quantitative and positional information about the image. Features can be applied to specific locations within the region of interest in each image by applying masks to them. Figure 2c illustrates this process using a BN TK6 cell 14 of 38

stained with Hoechst 33342, demonstrating that the entirety of the cytoplasm can be visualized using the BF image and all pixels with intensities higher than the background can be identified using the Adaptive Erode mask. Furthermore, the Hoechst-stained main nuclei can be identified individually through a combination of the Levelset and Watershed masks. Using these masks, features such as Area, Diameter, Circularity and Aspect Ratio can then be computed, their

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numerical values can be used for additional calculations and a data analysis template consisting of a series of histograms and bivariate plots can be created. To analyze many data files, IDEAS® offers a batch processing option in which a specific data analysis template can be applied to all

data files in the batch. Upon completion of batch processing, desired population statistics such as the total number or percentage of gated events, can be generated and exported. This allows for

unattended processing of many files and removes potential user bias associated with analyzing

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data files individually.

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3.2. Adaptation of the CBMN assay to an IFC method for radiation biodosimetry

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Recently, the CBMN assay has been adapted to be performed using IFC technology for radiation biodosimetry [33-37]. This advancement over traditional microscopy methods involves

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standard culture of whole blood for 48 h or 72 h, followed by lysis of red blood cells and fixing

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of lymphocytes. Finally, a DNA stain (e.g. DRAQ5, DAPI, Hoechst 33342, etc.) is added to stain both the main nuclei and MN. Samples can be acquired immediately in suspension on the ISX,

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eliminating the time-consuming process of creating microscope slides [33]. Data files containing several thousand cell images can be collected in about 5 min at either 40x or 60x magnification. Automated data analysis is performed in IDEAS® using a custom designed template that has

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been optimized using truth populations [36]. The template selects BN cells and filters out other events such as cell debris or aggregates, unfocused images and cells that do not meet the scoring

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criteria described by Fenech [13] (Fig. 3a - c). Identification and enumeration of BN cells and MN is accomplished automatically using masking, component analysis and spot counting as described above (Fig. 3d). Applying this template to data collected from in vitro irradiated whole blood samples resulted in a dose response calibration curve that is similar in magnitude to other curves published in the literature obtained through the use of automated or semi‑automated scoring the CBMN assay [36]. The method was validated by generating dose estimates from 15 of 38

blinded, irradiated samples, with an accuracy of better than ± 0.5 Gy in most cases following 72 h of culture time and data acquisition time of 5-10 min per sample [63]. The sensitivity of the IFC CBMN, however, has not yet been carefully evaluated as the development has focused on high throughput rather than high sensitivity. Currently the sensitivity is on the order of 1 Gy, which is higher than the 0.2-0.3 Gy sensitivity of the CBMN assay achieved when it is

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performed by visual microscopy [5, 74]. Recent advances in sample preparation and using the

latest IFC technology (ISX Mark II, Amnis, part of MilliporeSigma), now allows over 2000 BN cells to be collected from most samples, which increases the statistical robustness of the assay

over standard and triage microscope-based scoring modes in biodosimetry that score 1000 and 200 BN cells, respectively. Most recently we have demonstrated that our method is able to

maintain ± 0.5 Gy accuracy in dose estimation when using reduced initial blood culture volumes

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(200 μL) and after only 48 h of culture time, while maintaining a BN cell frequency of 200 cells

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or more [37].

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4. Potential for development of a fully automated imaging flow cytometry CBMN cytome assay The current automated techniques for performing the CBMN assay, namely automated slidescoring and conventional flow cytometry, have limited potential to evaluate the complete

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spectrum of biomarkers required for the CBMN Cyt assay (i.e. frequency of MN and NBUD in MONO and BN cells, NPB in BN cells, MONO, BN and POLY cells, necrotic and apoptotic cells). As discussed in previous sections, events such as MONO and POLY cells, as well as

NBUDs and NPBs are either difficult or impossible to identify due to various limitations. This section demonstrates, with sample images captured from in vitro irradiated whole blood and chemically treated TK6 cells, that imaging flow cytometry possesses the potential for full

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automation of CBMN Cyt assay.

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4.1. Identification of MONO and POLY cells with and without MN

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A key component of the CBMN Cyt assay is scoring MONO and POLY cells to assess mitotic activity through calculation of the NDI, RI or CBPI. Furthermore, quantifying MN in these cell types is an important metric to assess in vivo exposure. All of these events can be

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imaged by current IFC technology, including the ISX and ISX Mark II, and analyzed by imaging

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analysis software such as IDEAS® through a combination of masks and features. Figure 4 illustrates the identification of MONO and POLY TK6 cells through the use of component

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masking and features that measure nuclear aspect ratio and circularity. A new polynucleated cell mask was created through a combination of the Levelset, Watershed and Range masks similar to

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the BN cell mask. Using the Component feature on the polynucleated mask, each nucleus within every cell can be highlighted separately and additional features can then be calculated for each nucleus (Fig 4a). The scoring criteria for MONO and POLY cells are slightly less stringent than

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for BN cells and only require candidate cells to have an in-tact cytoplasm and possess normal nuclear morphology [13]. Therefore, the most efficient way to identify MONO and POLY cells that meet the scoring criteria is through a bivariate plot of the Aspect Ratio (ratio of semi-minor axis to semi-major axis) and Circularity (measurement of the mask’s deviation from a circle) features. For MONO cells, nuclei with Aspect Ratio values close to one and Circularity scores above 15 will be highly circular and will meet the scoring criteria (Fig. 4b). For POLY cells, the 17 of 38

average Aspect Ratio and Circularity values for each nucleus can be computed and cells containing nuclei with average scores similar to those for MONO cells will meet the scoring criteria (Fig. 4c and 4d). Finally, by applying the MN spot mask (created in previous work [33, 35]) to these populations, scoring of MN within MONO and POLY cells can be achieved (Fig. 4e). The numbers of MONO and POLY cells from each sample can then be exported to allow for

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calculation of the NDI, RI or CBPI.

4.2. Identification of NBUDs, NPBs and apoptotic cells

Further requirements of the CBMN Cyt assay are the scoring of NBUDs, NPBs and apoptotic cells. Current IFC technology possesses the capability to capture images of these events as well

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as the potential to automate their scoring. Figure 5 illustrates a number of these events captured

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at 60x magnification on the ISX in both MONO and BN cells, demonstrating that spot masking

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algorithms can be created to highlight and enumerate NBUDs, NPBs and apoptotic cells. Figure 5a shows NBUDs detected in MONO TK6 cells that have been exposed to Mitomycin

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C in the absence of Cyt-B. The new NBUD mask possesses the same parameters as the MN mask; however, the Spot Distance Minimum (SDM) feature is used to determine if identified

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spots are touching the nucleus. The SDM feature measures the distance between two masked

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spots in an image. To differentiate MN from NBUDs, the nuclear mask was dilated by 2 pixels such that it fit tightly to the periphery of the nucleus and then the SDM between both the nuclear

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mask and the MN or NBUD mask was calculated. Spots with an SDM of zero are NBUDs while spots with an SDM greater than zero are free-floating MN within the cytoplasm, separate from the main nuclei. Figure 5b shows NBUDs in BN TK6 cells that have been exposed to Mitomycin

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C and Cyt-B. The process to identify NBUDs in BN cells is similar to the process described above, however, each nucleus in the BN cell is masked separately using component masking.

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The SDM feature is applied again to compute the distance between identified spots and each main nucleus. Images with NBUDs attached to either nucleus will have SDM values of zero and these BN cells can be differentiated from BN cells that contain free-floating MN. In addition, the third image in Fig. 5b shows a BN cell with both a NBUD (cyan) and MN (red), demonstrating that both of these events can be imaged and identified within the same cell.

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Figure 5c shows images of Hoechst-stained PBLs containing NPBs along with a new Bridge mask that has been created to highlight these events. The Bridge mask also possesses similar parameters to the MN mask and the SDM feature is used to identify spots that are between the two main nuclei of a BN cell. After computing the SDM for the Bridge mask and the first nuclear component mask combination and then the SDM for the Bridge mask and the second nuclear

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component combination, both SDM values can be summed. For true NPBs, the sum of these

SDM values will be zero, indicating that the identified spot resides between the two nuclei. The images shown in Fig. 5c demonstrate that the ISX possesses sufficient spatial resolution to capture these events and that through the use of modified spot masking, identification and scoring of NPBs is possible.

In Fig. 5d a bivariate plot of BF Contrast versus Hoechst Area demonstrates that both large

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and small apoptotic cells can be identified for quantification and/or eliminated from analysis

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through the use of the BF Contrast feature, something we have demonstrated in a previous publication [35]. It can be seen that the BF imagery of apoptotic cells possesses a significant

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amount of dark black spots consistent with blebbing and chromatin condensation; two hallmarks

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of apoptosis. A number of publications in the literature have demonstrated the use of the ISX to determine if cells are viable, apoptotic or necrotic based on changes in membrane lipid

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composition, integrity, and permeability [75-77]. Thus, it would be relatively straightforward to

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introduce apoptotic or necrotic markers to assess cell membrane composition which would allow a more accurate assessment of these cells in the CBMN Cyt assay. Furthermore, masks and features in IDEAS® could also be developed to identify fragmented nuclei to further quantify the

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proportion of apoptotic or necrotic cells in a sample.

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4.3. Limitations of MN analysis by IFC

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Despite all of the advantages that IFC technology presents, there remain some limitations. In

previous publications, we have reported that the MN frequency obtained using IFC from irradiated PBLs is roughly 30% of that measured using manual microscopy methods at doses of 4 Gy [36]. When compared to automated slide-scoring methods however, the MN frequency was more consistent with a number of dose response calibration curves that have appeared in published literature [36]. The discrepancy between the MN frequency obtained by IFC methods 19 of 38

and manual slide-based scoring is likely attributed to two major factors; the first being the threedimensional nature of the IFC and the second being the strictness of scoring parameters implemented in image analysis. In the IFC, cells in suspension flow single-file through the flow cell and the resultant image is a two-dimensional projection of a three-dimensional cell. In some images, it is possible that

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some MN can either be hidden behind the main nucleus or may reside at a different depth of

focus than the main nuclei. The former makes identification of MN impossible and the latter makes discriminating MN from image artifacts very difficult due to their low intensity. In

addition to the limitations encountered during image acquisition, image-based data analysis is governed by mathematical algorithms that currently lack the flexibility and judgment of the

human eye in manual scoring. In the IDEAS® software, masks can be created that form a tight fit

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around the periphery of the nucleus. However, some MN that reside very close to or touch the

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main nuclei may still be incorrectly enveloped within these nuclear masks and can be inadvertently missed or misclassified. Furthermore, some small MN that could be scored through

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visual microscopy might be missed in automated image analysis due to the need to increase the

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lower area limit of MN masks to avoid incorrectly scoring small debris or artifacts. In a recent publication, we attempted to optimize the IDEAS® data analysis template in an effort to capture

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some of these missed MN [36]. In that work, we examined impacts on MN frequency by

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reducing the area of the BN cell mask in the hopes of avoiding enveloping MN in close proximity to the main nuclei. This was only partially successful as some smaller, DNA-positive debris were incorrectly masked as a main nucleus. We also attempted to reduce the area of the

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MN mask such that smaller MN could be masked. However, this caused small image artifacts, particularly at the periphery of the main nuclei, to be falsely counted as MN. Despite a number

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of enhancements in the BN cell and MN masks, only partial improvement in the overall detection of MN was possible. The overall reduction in MN frequency observed when using automated

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slide-scoring methods as well as IFC methods in comparison to manual msicroscopy, may simply be a general limitation of current technologies and image processing algorithms. The advantages and limitations of all methods for performing the CBMN assay discussed in this paper are summarized in Table 1.

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5. Future research directions This review details the potential of improving the robustness and throughput of the automated CBMN Cyt assay through the use of IFC. In general, the application of IFC to perform micronucleus assays is relatively new and a number of research areas should be 

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explored to improve and expand the technique to achieve full CBMN Cyt automation. True MN form their own nuclear envelope. Markers that attach to the nuclear lamina of both the main nuclei and MN can be incorporated into sample preparation protocols.

Capturing imagery of both the nuclear content as well as the nuclear envelope by IFC

will allow for markedly improved differentiation between genuine MN and other DNA positive bodies.

Our group has previously demonstrated the quantification of dicentric chromosomes in

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irradiated whole blood through the use of a pan-centromere peptide nucleic acid probe

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using IFC [78]. For the CBMN Cyt assay on IFC, the use of fluorescence in situ

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hybridization (FISH) with pan-centromeric probes or anti-kinetochore antibodies (e.g.

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CREST) may allow for the identification of MN that contain one or more centromere positive chromosomes (C+) and differentiation from MN that contain only acentric chromosome fragments (C-).

As with conventional flow cytometry methods, apoptotic and necrotic markers can be

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

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added to better separate these events from viable cells. Applying these markers in IFC methods would allow for direct visualization and quantification of both viable and 

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dying/dead cells as required by the CBMN Cyt assay. Future technical advances in image flow cytometry should also be directed towards the

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possibility of obtaining multiple images of a single cell from different angles so that all nuclear anomalies become visible regardless of location leading to the possibility of a 3-

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dimensional image which should facilitate a more comprehensive capture of all CBMN Cyt biomarkers.

Due to the multi-spectral nature of IFC and the variety of masks and image analysis features available in IDEAS® for data analysis, it is conceivable that any or all of these markers could be introduced to samples simultaneously which would expand the applicability and practicality of the CBMN Cyt assay. All of these proposed future research directions would increase the 21 of 38

capacity with which the CBMN Cyt assay could be performed with automated data analysis

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capabilities in IDEAS® further improving scoring throughput and versatility.

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6. Conclusions This review demonstrates the potential for full automation of the CBMN Cyt assay using IFC technology. In a recent publication evaluating the MetaferTM and conventional flow cytometry based MN methods for high-throughput MN scoring, Verma et al. stated that “a test system that

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combines the high-throughput, high-content and multiplexing potential of flow cytometry, with the re-validation and data storage benefits for image analysis, would be a major step forward in achieving a truly twenty-first century approach” [79]. We have demonstrated here that IFC is able to identify and automatically score BN cells with and without MN, and possesses the

potential to automatically identify and quantify all other key components of the CBMN Cyt

assay, namely MONO and POLY cells, NBUDs, NPBs and apoptotic and necrotic cells. Through the use of various bivariate plots, features and masks in a customizable data analysis template,

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automated identification of all of these events in all data files is possible. Furthermore, all data

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files can be stored for re-analysis or re-validation at any time. Automation of MN assays through

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the use of imaging flow cytometry represents an important step forward in this area of research

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and indeed represents a “twenty-first century approach”.

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Conflicts of interest statement

Matthew A. Rodrigues is employed by MilliporeSigma, the maker of the Amnis® brand

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ImageStream® imaging flow cytometer that has been discussed in this paper

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There are no other conflicts of interest

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Figure captions

Figure 1 DNA damage and cytotoxicity biomarkers in the lymphocyte Cytokinesis-Block Micronucleus Cytome [CBMN Cyt] assay. DNA damage biomarkers include (a) binucleated [BN] cells with a

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micronucleus [MN], (b) BN cells with a nucleoplasmic bridge [NPB], (c) BN cells with a nuclear bud [NBUD], (d) mononucleated [MONO] cells with a MN and (e) MONO cells with a NBUD. The type of MN can be further classified based on the absence or presence of a centromere

detected with centromere specific probes: (f) BN cell with a centromere negative MN, (g) BN

cell with a centromere positive MN. Cytotoxicity biomarkers include the relative frequencies of (h) MONO cells, (i) BN cells and (j) cells with three or more nuclei which together are used to

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measure the nuclear division index, a measure of cytostatic effects. In addition (k) necrotic cells

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and (l) apoptotic cells are also scored to obtain a measure of total cell death and the type of cell

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death.

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This figure has been adapted from Figs. 2b and 3 in Fenech MF, Knasmueller S, Bolognesi C, Bonassi C, Holland N, Migliore L, Palitti F, Natarajan AT, Kirsch-Volders M. Molecular

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mechanisms by which in vivo exposure to exogenous chemical genotoxic agents can lead to

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micronucleus formation in lymphocytes in vivo and ex vivo in humans. Mutat Res. 2016 June 7; 12-25. The images of centromere detection (f,g) were reproduced from Figures 2a and 2b in Vral A, Fenech M, Thierens H. The micronucleus assay as a biological dosimeter of in vivo ionising

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radiation exposure. Mutagenesis. 2011 Jan;26(1):11-7. Permission was obtained from the

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publishers Elsevier and Oxford University Press.

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Figure 2 Illustration of how individual cells and truth populations can be highlighted on bivariate plots, as well as some example parameters that can be calculated in IDEAS®. (a) a bivariate plot of Brightfield (BF) Aspect Ratio versus BF Area of TK6 cells treated with Cyt-B and stained with Hoechst, demonstrating that individual events can be selected to visualize BF, DNA and

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composite images; (b) example bivariate plot of Aspect Ratio Intensity (ARI) of both nuclear components of Hoechst-stained TK6 BN cells demonstrating how truth populations can be

highlighted on each plot and used to optimize gate boundaries. The Cyan events are BN cells

(positive population) and the red events are non-BN cells (negative population); (c) a binucleated TK6 cell showing how the cytoplasm can be highlighted by using the Adaptive Erode mask and how the Hoechst-stained main nuclei can be highlighted using a combination of the Levelset and

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Watershed masks. These masks allow tight delineation of structural boundaries and allow

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various mathematical parameters such as Area, Diameter, Circularity and Aspect Ratio to be

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calculated.

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Figure 3 Bivariate plots and histograms created in IDEAS® to separate binucleated (BN) cells from debris and other false positive events and to enumerate micronuclei (MN). (a) bivariate plot of Brightfield (BF) Aspect Ratio versus BF Area used to isolate single cells while removing doublet events and large multicellular aggregates; (b) bivariate plot of Aspect Ratio Intensity of both

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nuclear components of a BN cell plotted against one another allowing for a circularity

comparison; (c) bivariate plot of Component Intensity Ratio versus Component Area Ratio of the main nuclei allowing for selection of events containing two nuclei that are similar in both area

and intensity; (d) histogram of the Spot Count feature applied to the MN mask using the final BN cell population, along with representative images from each bin, to identify and automatically

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enumerate MN from a whole blood sample that was x-irradiated in vitro with 2 Gy.

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Figure 4 Illustration of how mononucleated (MONO) and polynucleated (POLY) cells can be highlighted using the POLY mask and separated from debris. (a) quadranucleated, trinucleated and mononucleated cells identified using the POLY mask. The Component Mask allows for the identification of individual nuclei within POLY cells; (b-d) separation of MONO and POLY

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cells containing nuclei with normal morphology from cells that possess poor nuclear morphology through the use of the Aspect Ratio and Circularity features; (e) example images of MONO and POLY cells containing micronuclei (MN). The main nuclei and MN can be masked and

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separately scored by using the POLY mask and the MN mask.

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Various images captured from Hoechst-stained TK6 and PBL cells containing NBUDs, NPBs as well as illustrating how apoptotic cells can be differentiated from healthy cells. (a) MONO TK6

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cells with NBUDs demonstrating masking of the main nucleus with the MONO mask and NBUDs with the NBUD mask; (b) BN TK6 cells illustrating the presence of NBUDs and the ability to mask them using the NBUD mask. The third row shows that both NBUDs and MN can be captured and masked within the same image using the NBUD mask (cyan) and MN mask (red), respectively; (c) BN PBLs x-irradiated in vitro to 3 Gy showing that NPBs can be both imaged on the ImageStream® and identified using the Bridge mask; (d) Bivariate plot of BF 35 of 38

Contrast versus Hoechst Area showing how apoptotic cells can be separated from healthy cells. Apoptotic cells possess a higher BF Contrast due to the many dark black spots that indicate

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blebbing and chromatin condensation.

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Table Captions

Table 1 Summary of the advantages and limitations of visual microscopy, automated microscopy, conventional flow cytometry and imaging flow cytometry methods in the context of performing

Automated microscopy

Automatic scanning of slides to identify nuclei and MN in cells and to identify and record images of MONO, BN and POLY cells. Images can be stored and slides can be rescanned if necessary Higher throughput than visual microscopy (1,000-2,000 BN cells can be detected in about 2 minutes)

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Conventional flow cytometry

Fully automated scoring of nuclei and MN Viable nuclei can be differentiated from necrotic or apoptotic cells High throughput data acquisition (10,000 events can be scored in a few minutes)

Limitations Inter-laboratory and scorer variations make MN scoring subjective Laborious, time-consuming and suffers from low throughput, especially within the context of scoring the CBMN Cyt assay High-quality microscope slides must be created; quality can vary based on laboratory conditions and technical expertise Total number of cells that can be scored is limited and restricts statistical robustness

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Advantages Direct visualization of all required events (e.g. MONO, BN and POLY cells, MN, NPBs, NBUDs and apoptotic/necrotic cells) Sufficiently validated sample preparation protocols and scoring procedures Stained slides can be stored and re-analyzed if necessary

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Scoring method Visual microscopy

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the Cytokinesis-Block Micronucleus Cytome assay.

High-quality microscope slides must be created; quality can vary based on laboratory conditions and technical expertise Lack of cytoplasmic visualization High rates of false positive BN cells and MN requiring visual verification of the image gallery, which may reduce throughput and may re-introduce scorer bias In many cases, slides must be scanned twice: first for BN cells and then rescanned to identify MONO and POLY cells NPBs and NBUDs cannot yet be reliably identified Absence of Cyt-B does not allow quantification of the rate of MN per BN cell, the fundamental endpoint in the CBMN assay Cell membrane lysis creates a solution that may contain debris and does not allow 37 of 38

clear distinction between MN and DNA positive debris POLY cells, NBUDs and NPBs cannot be quantified MN frequency obtained using IFC has been shown to be roughly 30% of that measured using manual microscopy in radiation biodosimetry The two-dimensional projection of a threedimensional cell may cause some MN to be hidden behind the main nucleus or to reside at a different depth of focus than the main nuclei Mathematical algorithms used to perform image analysis lack the flexibility and judgment of the human eye and may cause smaller MN or MN that reside very close to the main nuclei to be missed

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Direct visualization and potential for fully automated scoring of all required events (e.g. MONO, BN and POLY cells, MN, NPBs, NBUDs and apoptotic/necrotic cells) Cytoplasmic visualization using brightfield imagery High throughput data acquisition (several thousand events can be scored in a few minutes) Multiple excitation lasers and image channels allow for several cellular structures to be imaged simultaneously Cellular imagery is stored in data files permitting re-analysis if necessary Custom data analysis templates enable CBMN Cyt scoring criteria to be implemented using mathematical algorithms

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Imaging flow cytometry

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