High-throughput sample processing and sample management; the functional evolution of classical cytogenetic assay towards automation

Development of high-throughput systems for biodosimetry

Biomarkers for ionising radiation exposure have great utility in scenarios where there has been a potential exposure and physical dosimetry is missing or in dispute, such as for occupational and accidental exposures. Biomarkers that respond as a function of dose are particularly useful as biodosemeters to determine the dose of radiation to which an individual has been exposed. These dose measurements can also be used in medical scenarios to track doses from medical exposures and even have the potential to identify an individual's response to radiation exposure that could help tailor treatments. The measurement of biomarkers of exposure in medicine and for accidents, where a larger number of samples would be required, is limited by the throughput of analysis (i.e. the number of samples that could be processed and analysed), particularly for microscope-based methods, which tend to be labour-intensive. Rapid analysis in an emergency scenario, such as a large-scale accident, would provide dose estimates to medical practitioners, allowing timely administration of the appropriate medical countermeasures to help mitigate the effects of radiation exposure. In order to improve sample throughput for biomarker analysis, much effort has been devoted to automating the process from sample preparation through automated image analysis. This paper will focus mainly on biological endpoints traditionally analysed by microscopy, specifically dicentric chromosomes, micronuclei and gamma-H2AX. These endpoints provide examples where sample throughput has been improved through automated image acquisition, analysis of images acquired by microscopy, as well as methods that have been developed for analysis using imaging flow cytometry.

Fluorescence in situ hybridisation for interphase chromosomal aberration-based biological dosimetry

Metaphase spreads stained with Giemsa or painted with chromosome-specific probes by fluorescence in situ hybridisation (FISH) have been in use since long for retrospective dose assessment (biological dosimetry). However, in cases of accidental exposure to ionising radiation, the culturing of lymphocytes to obtain metaphase chromosomes and analysis of chromosomal aberrations is time-consuming and problematic after high radiation doses. Similarly, analysing chromosomal damage in G0/G1 cells or nondividing cells by premature chromosome condensation is laborious. Following large-scale radiological emergencies, the time required for analysis is more important than precision of dose estimate. Painting of whole chromosomes using chromosome-specific probes in interphase nuclei by the FISH technique will eliminate the time required for cell culture and allow a fast dose estimate, provided that a meaningful dose-response can be obtained by scoring the number of chromosomal domains visible in interphase nuclei. In order to test the applicability of interphase FISH for quick biological dosimetry, whole blood from a healthy donor was irradiated with 8 Gy of gamma radiation. Irradiated whole blood was kept for 2 h at 37°C to allow DNA repair and thereafter processed for FISH with probes specific for Chromosomes-1 and 2. Damaged chromosomal fragments, distinguished by extra color domains, were observed in interphase nuclei of lymphocytes irradiated with 8 Gy. These fragments were efficiently detected and quantified by the FISH technique utilising both confocal and single plane fluorescence microscopy. Furthermore, a clear dose-response curve for interphase fragments was achieved following exposure to 0, 1, 2, 4 and 8 Gy of gamma radiation. These results demonstrate interphase FISH as a promising test for biodosimetry and for studying cytogenetic effects of radiation in nondividing cells.

SETApp: A machine learning and image analysis based application to automate the sea urchin embryo test

Since countless xenobiotic compounds are being found in the environment, ecotoxicology faces an astounding challenge in identifying toxicants. The combination of high-throughput in vivo/in vitro bioassays with high-resolution chemical analysis is an effective way to elucidate the cause-effect relationship. However, these combined strategies imply an enormous workload that can hinder their implementation in routine analysis. The purpose of this study was to develop a new high throughput screening method that could be used as a predictive expert system that automatically quantifies the size increase and malformation of the larvae and, thus, eases the application of the sea urchin embryo test in complex toxicant identification pipelines such as effect-directed analysis. For this task, a training set of 242 images was used to calibrate the size-increase and malformation level of the larvae. Two classification models based on partial least squares discriminant analysis (PLS-DA) were built and compared. Moreover, Hierarchical PLS-DA shows a high proficiency in classifying the larvae, achieving a prediction accuracy of 84 % in validation. The scripts built along the work were compiled in a user-friendly standalone app (SETApp) freely accessible at https://github.com/UPV-EHU-IBeA/SETApp. The SETApp was tested in a real case scenario to fulfill the tedious requirements of a WWTP effect-directed analysis.

Intercomparison of conventional and QuickScan dicentric scoring for the validation of individual biodosimetry analysis in Taiwan

PURPOSE

The dicentric chromosome assay (DCA), the gold standard for radiation biodosimetry, evaluates an individual absorbed radiation dose by the analysis of DNA damage in human lymphocytes. The conventional (C-DCA) and QuickScan (QS-DCA) scoring methods are sensitive for estimating radiation dose. The Biodosimetry Laboratory at Institute of Nuclear Energy Research (INER), Taiwan, participated in intercomparison exercises conducted by Health Canada (HC) in 2014, 2015 and 2018 to validate the laboratory's accuracy and performance.

MATERIAL AND METHODS

Blood samples for the conventional dose response curve for Taiwan were irradiated with 0, 0.25, 0.5, 1, 2, 3, 4 and 5 Gy. Ten blind blood samples were provided by HC. Either or both of two methods of conventional (C) or QuickScan (QS) scoring could be chosen for the HC's intercomparison. For C-DCA triage scoring, only cells with 46 centromeres were counted and each scorer recorded the number of dicentrics in the first 50 metaphases or stopped scoring when 30 dicentrics were reached. Scorers also recorded how much time it took to analyze 10, 20, and 50 cells. Subsequently, the data were entered into the Dose Estimate software (DoseEstimate_v5.1) and dose estimates were calculated. With QS-DCA scoring, a minimum of 50 metaphase cells (or 30 dicentrics) were scored in apparently complete metaphases without verification of exactly 46 centromeres.

RESULTS

For the blinded blood samples irradiated at HC and shipped to INER, the mean absolute deviation (MAD) derived after scoring 50 cells for C-DCA and QS-DCA was <0.5 Gy for all three intercomparisons, meeting the criteria for acceptance.

CONCLUSION

The results indicated that the Biodosimetry Laboratory at INER can provide reliable dose estimates in the case of a large-scale radiation accident.

Transcriptomics for radiation biodosimetry: progress and challenges

PURPOSE

Transcriptomic-based approaches are being developed to meet the needs for large-scale radiation dose and injury assessment and provide population triage following a radiological or nuclear event. This review provides background and definition of the need for new biodosimetry approaches, and summarizes the major advances in this field. It discusses some of the major model systems used in gene signature development, and highlights some of the remaining challenges, including individual variation in gene expression, potential confounding factors, and accounting for the complexity of realistic exposure scenarios.

CONCLUSIONS

Transcriptomic approaches show great promise for both dose reconstruction and for prediction of individual radiological injury. However, further work will be needed to ensure that gene expression signatures will be robust and appropriate for their intended use in radiological or nuclear emergencies.

RABiT-II: A Fully-Automated Micronucleus Assay System with Shortened Time to Result

In this work, we describe a fully automated cytokinesis-block micronucleus (CBMN) assay with a significantly shortened time to result, motivated by the need for rapid high-throughput biodosimetric estimation of radiation doses from small-volume human blood samples. The Rapid Automated Biodosimetry Tool (RABiT-II) currently consists of two commercial automated systems: a PerkinElmer cell::explorer Workstation and a GE Healthcare IN Cell Analyzer 2000 Imager. Blood samples (30 μl) from eight healthy volunteers were gamma-ray irradiated ex vivo with 0 (control), 0.5, 1.5, 2.5, 3.5 or 4.5 Gy and processed with full automation in 96-well plates on the RABiT-II system. The total cell culture time was 54 h and total assay time was 3 days. DAPI-stained fixed samples were imaged on an IN Cell Analyzer 2000 with fully-automated image analysis using the GE Healthcare IN Cell Developer Toolbox version 1.9. A CBMN dose-response calibration curve was established, after which the capability of the system to predict known doses was assessed. Various radiation doses for irradiated samples from two donors were estimated within 20% of the true dose (±0.5 Gy below 2 Gy) in 97% of the samples, with the doses in some 5 Gy irradiated samples being underestimated by up to 25%. In summary, the findings from this work demonstrate that the accelerated CBMN assay can be automated in a high-throughput format, using commercial biotech robotic systems, in 96-well plates, providing a rapid and reliable bioassay for radiation exposure.

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome assays is traditionally a manual, labor-intensive process not well suited to handle the volume of samples which may require examination in the wake of a mass casualty event. Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates this process by examining sets of metaphase images using machine learning-based image processing techniques. The software selects appropriate images for analysis by removing unsuitable images, classifies each object as either a centromere-containing chromosome or non-chromosome, further distinguishes chromosomes as monocentric chromosomes (MCs) or dicentric chromosomes (DCs), determines DC frequency within a sample, and estimates biological radiation dose by comparing sample DC frequency with calibration curves computed using calibration samples. This protocol describes the usage of ADCI software. Typically, both calibration (known dose) and test (unknown dose) sets of metaphase images are imported to perform accurate dose estimation. Optimal images for analysis can be found automatically using preset image filters or can also be filtered through manual inspection. The software processes images within each sample and DC frequencies are computed at different levels of stringency for calling DCs, using a machine learning approach. Linear-quadratic calibration curves are generated based on DC frequencies in calibration samples exposed to known physical doses. Doses of test samples exposed to uncertain radiation levels are estimated from their DC frequencies using these calibration curves. Reports can be generated upon request and provide summary of results of one or more samples, of one or more calibration curves, or of dose estimation.

Chromosomal instability--mechanisms and consequences

Chromosomal instability is defined as a state of numerical and/or structural chromosomal anomalies in cells. Numerous studies have documented the incidence of chromosomal instability, which acutely or chronically may lead to accelerated ageing (tissue-wide or even organismal), cancer or other genetic disorders. Potential mechanisms leading to the generation of chromosome-genome instability include erroneous/inefficient DNA repair, chromosome segregation defects, spindle assembly defects, DNA replication stress, telomere shortening/dysfunction - to name a few. Understanding the cellular and molecular mechanisms for chromosomal instability in various human cells and tissues will be useful in elucidating the cause for many age associated diseases including cancer. This approach holds a great promise for the cytogenetic assays not only for prognosis but also for diagnostic purposes in clinical settings. In this review, a multi-dimensional approach has been attempted to portray the complexity behind the incidence of chromosome-genome instability including evolutionary implications at the species level for some of the mechanisms of chromosomal instability.