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A high-throughput in vivo micronucleus assay for genome instability screening in mice

Nature Protocols volume 10, pages 205–215 (2015)Cite this article

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Abstract

We describe a sensitive, robust, high-throughput method for quantifying the formation of micronuclei, markers of genome instability, in mouse erythrocytes. Micronuclei are whole chromosomes or chromosome segments that have been separated from the nucleus. Other methods of detection rely on labor-intensive, microscopy-based techniques. Here we describe a 2-d, 96-well plate–based flow cytometric method of micronucleus scoring that is simple enough for a research technician experienced in flow cytometry to perform. The assay detects low levels of genome instability that cannot be readily identified by classic phenotyping, using 25 μl of blood. By using this assay, we have screened >10,000 blood samples and discovered novel genes that contribute to vertebrate genome maintenance, as well as novel disease models and mechanisms of genome instability disorders. We discuss experimental design considerations, including statistical power calculation, we provide troubleshooting tips and we discuss factors that contribute to a false-positive increase in the number of micronucleated red blood cells and to experimental variability.

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Figure 1: Micronucleus induction during erythropoiesis.
Figure 2: Workflow of the micronucleus assay.
Figure 3: Effect of sex and genetic background on micronucleus induction and determination of statistical power.
Figure 4: Micronucleus induction after genotoxic treatment or genetic modification.
Figure 5: Analysis of micronucleated red blood cells by flow cytometry.

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Acknowledgements

We thank M. Hitcham and N. Harman for assistance with blood collections, W. Cheng for assistance with flow cytometry during high-throughput screening and K. Dry for comments on the manuscript. R.E.M. is supported by Cancer Research UK (CRUK; project grant C20510/A12401). D.J.A. is supported by CRUK. D.J.A. and B.L.N. are supported by the Wellcome Trust. Research in the Jackson Laboratory is funded by CRUK program grant no. C6/A11224, the European Research Council and the European Community Seventh Framework Programme grant agreement no. HEALTH-F2-2010-259893 (DDResponse). Core funding is provided by CRUK (C6946/A14492) and the Wellcome Trust (WT092096). S.P.J. receives his salary from the University of Cambridge, UK, supplemented by CRUK. G.B. is funded by CRUK program grant no. C6/A11224.

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Authors and Affiliations

  1. The Wellcome Trust/Cancer Research UK Gurdon Institute, University of Cambridge, Cambridge, UK

    Gabriel Balmus & Stephen P Jackson

  2. Maintenance of Genome Stability, The Wellcome Trust Sanger Institute, Genome Campus, Cambridge, UK

    Gabriel Balmus & Stephen P Jackson

  3. The Sanger Mouse Genetics Project, The Wellcome Trust Sanger Institute, Genome Campus, Cambridge, UK

    Natasha A Karp

  4. Cytometry Core Facility, The Wellcome Trust Sanger Institute, Genome Campus, Cambridge, UK

    Bee Ling Ng

  5. Experimental Cancer Genetics, The Wellcome Trust Sanger Institute, Genome Campus, Cambridge, UK

    David J Adams & Rebecca E McIntyre

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Contributions

D.J.A. and S.P.J. conceived the idea of screening mice from large-scale mouse phenotyping pipelines for micronucleated erythrocytes. G.B. and R.E.M. performed the experimental analysis and wrote the manuscript with comments from all authors. B.L.N. assisted with flow cytometry and N.A.K. performed statistical analysis.

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Correspondence to David J Adams or Rebecca E McIntyre.

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Integrated supplementary information

Supplementary Figure 1 Severely increased red blood cell production (reticulocytosis) results in detection of nucleated and micronucleated (MN) normochromatic erythrocytes (NCE) in Q3.

Blood obtained from C57BL/6J-ApcMin/+ mice was processed according to the methods described herein. a) Representative flow-cytometric analysis for six week old Apc-/min mouse (left) and 16 week old Apcmin/+ mice (right). Note the change in % reticulocytes (RET) and %MN-NCE. During extremely high rates of erythropoiesis, such as that exhibited by severely anaemic, aged Apcmin/+ mice (right), the number of reticulocytes detected in the RET quadrant is vastly increased, however the process becomes error prone and the nucleus is not always expelled; both nucleated and micronucleated red blood cells are detected in the % MN-NCE quadrant, leading to a false-positive increase in %MN-NCE. b) Data shows %MN-NCE vs. %RET for Apcmin/+ mice (n=4) and Apc+/+ mice (n=10). Linear regression analysis shows that there is a significant correlation between increased % MN-NCE and % RET (P<0.01). c) Dot plot showing the average %RET in male C57BL/6 mice (mean ± standard deviation: 1.623±0.209; n=20).

Supplementary Figure 2 Effect of RNase, flow rate and fixation.

a) Blood sample obtained from male C57BL/6 mouse at 16 weeks of age, processed according to the methods described herein. b) The same sample was processed without the addition of RNase, which results in a shift of the FITC-conjugated transferrin receptor-positive (CD71-FITC+), propidium iodide negative (PI-) reticulocyte (RET) population over to the micronucleated-RET (MN-RET) quadrant. This is caused by PI binding to the RNA within the CD71-FITC+ RETs. c) Sample analyzed at a rate of 10000 events per second (vs. 1000 events in a) shows spikes of events in the CD71-FITC+ and PI+ quadrant (indicated by arrow head). d) The color of fixed samples can indicate whether samples have become too warm during preparation. Fresh blood samples were harvested and fixed in -80°C methanol in duplicate or in room temperature (RT; 20-25°C) methanol. The blood fixed in -80°C methanol shows characteristic red color while the sample fixed in RT methanol shows brown color. e) Samples maintained for long periods of time in -80°C methanol show characteristic red color and are suitable for processing. f) The same samples (from image d) were either placed in a -80°C freezer or left at RT. After 30 minutes the sample that was maintained at -80°C showed the characteristic red color while the sample that was left at RT became brown in color; no detectable change in color was seen at the sample fixed in RT methanol.

Supplementary Figure 3 Indicators of incorrect sample processing.

a) Correctly prepared sample. Blood sample obtained from male C57BL/6 mouse at 16 weeks of age, processed according to the methods described herein. The SSC-A vs. FSC-A plot (left) reveals correct separation of blood cell populations and minimal cell debris and the CD71-FITC vs. PI plot (right) reveals correct representation of populations within the quadrant gates. b) Slightly degraded blood sample. Blood sample left 5 days at 4˚C and fixed in -80˚C methanol. The SSC-A vs. FSC-A plot (left) reveals increased cell debris (black arrow) and incomplete separation of the cell populations. The gated populations plotted on CD71-FITC vs. PI plot (right) show no indication of degradation but there is a slight increase in MN-NCE (right). c) Very degraded blood sample. Blood sample left 3 weeks at 4˚C and fixed in -80˚C methanol. Both the SSC-A vs. FSC-A and CD71-FITC vs. PI plots are completely transformed. d) Blood sample fixed in warm methanol (room-temperature). The SSC-A vs. FSC-A plot (left) reveals increased cell debris (black arrow) and the CD71-FITC vs. PI plot (right) shows incorrect representation of populations. e) Blood sample fixed correctly (-80˚C methanol) but allowed to warm to room temperature (20-25°C) before processing. The SSC-A vs. FSC-A plot (left) reveals increased cell debris (black arrow) and incomplete separation of the cell populations, and the CD71-FITC vs. PI plot (right) shows incorrect representation of populations.

Supplementary Figure 4 Effect of incubation time in propidium iodide (PI) and time in storage.

a) Data shows %MN-NCE for replicate tubes of the same sample that were stored at -80˚C. Two tubes were processed at monthly intervals over a one-year period. Linear regression analysis shows that there is no significant difference in the detection of % MN-NCE up to one year after fixation (P=0.427). b) A single blood sample was added to each well of a 96-well plate and processed accordingly. After washing with buffer to remove the FITC-conjugated transferrin receptor (CD71-FITC)/RNase mix, samples were resuspended in buffer containing 1 mg/ml PI, and all 96 wells were immediately analyzed by flow-cytometry. Linear regression analysis shows that there is a statistically significant difference in the % micronucleated (MN)-normochromatic erythrocytes (NCE) obtained at the beginning of the plate versus those obtained at the end of the plate (*P<0.001). This could be due to saturation of DNA with PI over time. The biological effect is small but to avoid potential experimental bias, samples should be randomized across the plate and we recommend adding PI to 24 wells at a time.

Supplementary Figure 5 Flow-cytometric analysis of control samples and gating out autofluorescence.

Unstained samples are used to centralise the main cell population within the side scatter (SSC) versus forward scatter (FSC) plot (data not shown). The main population is gated (erythrocytes), and within the propidium iodide (PI) versus FITC-conjugated transferrin receptor (CD71-FITC) plot a quadrant gate is drawn. Single-stain controls are then analysed to determine the correct voltage and gain settings, which ensures the majority of events fall within the scale of the X and Y axes, and within the correct quadrant gate. a) Unstained control sample and b) CD71-FITC alone. Auto-fluorescence can be detected with samples stained with PI alone, either within the transferrin receptor FITC-conjugated (CD71-FITC) channel (c; indicated by arrowhead), or within the higher logarithmic scale (Log) of PI channel (d; indicated by arrowhead). To remove the effect of auto-fluorescence, Region gate R3 is created within the PI versus side scatter (SSC) plot (d).

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Balmus, G., Karp, N., Ng, B. et al. A high-throughput in vivo micronucleus assay for genome instability screening in mice. Nat Protoc 10, 205–215 (2015). https://doi.org/10.1038/nprot.2015.010

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