A standardized and automated CBMN assay for biological dosimetry: the CytoRADx™ system.

Major nuclear accidents can result in many casualties, and it is important to assess the absorbed radiation dose to support treatment decisions. Biological dosimetry (BD) allows retrospective determination of dose using biological markers. To achieve consistent cytogenetic assay results across labs, the current practice requires each lab to generate periodic, unique calibration curves using in vitro dose-effect experiments. Here, we present CytoRADx™, a standardized biodosimetry system that integrates automated dose calculation in a high-throughput platform without the need for lab-specific calibration curves. CytoRADx consists of an improved, standardized Cytokinesis Block Micronucleus assay combined with automated analysis utilizing an established slide scanning device. We tested CytoRADx for accuracy and reproducibility across different instruments, sites, days and operators. Our results demonstrate that CytoRADx eliminates the time-consuming, lab-specific calibration curves, allowing multiple laboratories to obtain consistent results and to distribute the testing burden in the event of a large-scale accident.

CytoRADx: A High-Throughput, Standardized Biodosimetry Diagnostic System Based on the Cytokinesis-Block Micronucleus Assay.

In a large-scale catastrophe, such as a nuclear detonation in a major city, it will be crucial to accurately diagnose large numbers of people to direct scarce medical resources to those in greatest need. Currently no FDA-cleared tests are available to diagnose radiation exposures, which can lead to complex, life-threatening injuries. To address this gap, we have achieved substantial advancements in radiation biodosimetry through refinement and adaptation of the cytokinesis-block micronucleus (CBMN) assay as a high throughput, quantitative diagnostic test. The classical CBMN approach, which quantifies micronuclei (MN) resulting from DNA damage, suffers from considerable time and expert labor requirements, in addition to a lack of universal methodology across laboratories. We have developed the CytoRADx™ System to address these drawbacks by implementing a standardized reagent kit, optimized assay protocol, fully automated microscopy and image analysis, and integrated dose prediction. These enhancements allow the CytoRADx System to obtain high-throughput, standardized results without specialized labor or laboratory-specific calibration curves. The CytoRADx System has been optimized for use with both humans and non-human primates (NHP) to quantify radiation dose-dependent formation of micronuclei in lymphocytes, observed using whole blood samples. Cell nuclei and resulting MN are fluorescently stained and preserved on durable microscope slides using materials provided in the kit. Up to 1,000 slides per day are subsequently scanned using the commercially based RADxScan™ Imager with customized software, which automatically quantifies the cellular features and calculates the radiation dose. Using less than 1 mL of blood, irradiated ex vivo, our system has demonstrated accurate and precise measurement of exposures from 0 to 8 Gy (90% of results within 1 Gy of delivered dose). These results were obtained from 636 human samples (24 distinct donors) and 445 NHP samples (30 distinct subjects). The system demonstrated comparable results during in vivo studies, including an investigation of 43 NHPs receiving single-dose total-body irradiation. System performance is repeatable across laboratories, operators, and instruments. Results are also statistically similar across diverse populations, considering various demographics, common medications, medical conditions, and acute injuries associated with radiological disasters. Dose calculations are stable over time as well, providing reproducible results for at least 28 days postirradiation, and for blood specimens collected and stored at room temperature for at least 72 h. The CytoRADx System provides significant advancements in the field of biodosimetry that will enable accurate diagnoses across diverse populations in large-scale emergency scenarios. In addition, our technological enhancements to the well-established CBMN assay provide a pathway for future diagnostic applications, such as toxicology and oncology.

A new platform linking chromosomal and sequence information.

We have tested whether a direct correlation of sequence information and staining properties of chromosomes is possible and whether this combined information can be used to precisely map any position on the chromosome. Despite huge differences of compaction between the naked DNA and the DNA packed in chromosomes we found a striking correlation when visualizing the GGCC density on both levels. Software was developed that allows one to superimpose chromosomal fluorescence intensity profiles generated by chromolysin A3 (CMA3) staining with GGCC density extracted from the Ensembl database. Thus, any position along the chromosome can be defined in megabase pairs (Mb) besides the cytoband information, enabling direct alignment of chromosomal information with the sequence data. The mapping tool was validated using 13 different BAC clones, resulting in a mean difference from Ensembl data of 2 Mb (ranging from 0.79 to 3.57 Mb). Our results indicate that the sequence density information and information gained with sequence-specific fluorochromes are superimposable. Thus, the visualized GGCC motif density along the chromosome (sequence bands) provides a unique platform for comparing different types of genomic information.

Automated fluorescent in situ hybridization (FISH) analysis of t(9;22)(q34;q11) in interphase nuclei.

BACKGROUND: For chronic myeloid leukemia, the FISH detection of t(9;22)(q34;q11) in interphase nuclei of peripheral leukocytes is an alternative method to bone marrow karyotyping for monitoring treatment. With automation, several drawbacks of manual analysis may be circumvented. In this article, the capabilities of a commercially available automated image acquisition and analysis system were determined by detecting t(9;22)(q34;q11) in interphase nuclei of peripheral leukocytes. METHODS: Three peripheral blood samples of normal adults, 21 samples of CML patients, and one sample of a t(9;22)(q34;q11) positive cell-line were used. RESULTS: Single nuclei with correctly detected signals amounted to 99.6% of nuclei analyzed after exclusion of overlapping nuclei and nuclei with incorrect signal detection. A cut-off value of 0.84 mum was defined to discriminate between translocation positive and negative nuclei based on the shortest distance between signals. Using this value, the false positive rate of the automated analysis for negative samples was 7.0%, whereas that of the manual analysis was 5.8%. Automated and manual results showed strong correlation (R(2) = 0.985), the mean difference of results was only 3.7%. CONCLUSIONS: A reliable and objective automated analysis of large numbers of cells is possible, avoiding interobserver variability and producing statistically more accurate results than manual evaluation.

Automatic telomere length measurements in interphase nuclei by IQ-FISH.

To benefit from the fluorescence-based automatic microscope (FLAME), we have adapted a PNA FISH technique to automatically determine telomere length in interphase nuclei. The method relies on the simultaneous acquisition of pan-telomeric signals and reference probe signals. We compared the quantitative figures to those for existing methods, i.e. Southern blot analysis and quantitative FISH (Q-FISH). Quantitative-FISH on interphase nuclei (IQ-FISH) allows the exact quantification of telomere length in interphase nuclei. Thus, this enables us to obtain not only exact information on the telomere length, but also morphological and topological details. The automatic measurement of large cell numbers allows the measurement of statistically relevant cell populations.

Fetal cells in maternal blood: a comparison of methods for cell isolation and identification.

OBJECTIVE: A variety of methods have been used to select and identify fetal cells from maternal blood. In this study, a commonly used 3-step selection method is compared with selection directly from whole blood. Identification of fetal origin by XY FISH of male cells was also evaluated. METHODS: Maternal blood was drawn either before invasive chorion villus sampling (pre-CVS) or after (post-CVS) from women carrying a male fetus. Fetal cells were isolated either by density gradient centrifugation succeeded by CD45/CD14 depletion and CD71-positive selection from CD45/CD14-negative cells, or by CD71-positive selection directly from whole blood. The true origin of fetal cells recovered by the two methods was established by two rounds of XY chromosome FISH in reverse colors, in some instances combined with anti-zeta (zeta) or anti-zeta/anti-gamma (gamma) antibody staining. RESULTS: In blood samples taken post-CVS and enriched by CD71 selection directly from whole blood, fetal cells were identified with a frequency that was almost four orders of magnitude higher than in post-CVS samples enriched by the 3-step method. In blood samples taken pre-CVS and enriched by the 3-step procedure, no fetal cells were identified by reverse color FISH in 371 ml of blood. In similar samples enriched by CD71 selection on whole blood, two fetal cells were identified in 27 ml of blood. Rehybridization with X and Y chromosome probes with reverse colors was necessary to exclude false Y chromosome signals. Not all fetal cells identified by the presence of a true Y chromosome signal stained with anti-zeta antibody. CONCLUSIONS: Selection of fetal NRBCs from maternal blood by CD71-positive selection directly from whole blood is superior to density gradient centrifugation succeeded by CD45/CD14 depletion and CD71 selection of CD45/CD14-negative cells. Combining two markers for fetal origin is recommended for unambiguously identifying a cell as fetal.

Automatic identification of subcellular phenotypes on human cell arrays.

Light microscopic analysis of cell morphology provides a high-content readout of cell function and protein localization. Cell arrays and microwell transfection assays on cultured cells have made cell phenotype analysis accessible to high-throughput experiments. Both the localization of each protein in the proteome and the effect of RNAi knock-down of individual genes on cell morphology can be assayed by manual inspection of microscopic images. However, the use of morphological readouts for functional genomics requires fast and automatic identification of complex cellular phenotypes. Here, we present a fully automated platform for high-throughput cell phenotype screening combining human live cell arrays, screening microscopy, and machine-learning-based classification methods. Efficiency of this platform is demonstrated by classification of eleven subcellular patterns marked by GFP-tagged proteins. Our classification method can be adapted to virtually any microscopic assay based on cell morphology, opening a wide range of applications including large-scale RNAi screening in human cells.