Abstract
Study question
Can we separate between control and reversine-treated cells within the inner cell mass (ICM) of the mouse preimplantation embryo by using label-free and non-invasive hyperspectral microscopy?
Summary answer
Hyperspectral microscopy is able to discern between control and reversine-treated cells using cellular autofluorescence in the complete absence of fluorescence tags.
What is known already
Embryo mosaicism (containing cells that are euploid (46 chromosomes) and aneuploid (deviation from the expected number of chromosomes)) affects up to 17.3% of human blastocyst embryos. Current diagnosis of aneuploidy in the IVF clinic involves a biopsy of trophectoderm (TE) cells or spent media followed by sequencing. In some blastocyst embryos these approaches will fail to diagnose of the proportion of aneuploid cells within the fetal lineage (ICM).
Study design, size, duration
The impact of aneuploidy on cellular metabolism was assessed by using cellular autofluoresence and hyperspectral microscopy (broad spectral profile). Two models were employed: (i) Primary human fibroblast cells with known karyotypes (4-6 independent replicates, euploid n = 467; aneuploid n = 969) and reversine induced aneuploidy in mouse embryos (5-8 independent replicates, 30-44 cells per group). Both models were subjected to hyperspectral imaging to quantify native cell fluorescence.
Participants/materials, setting, methods
The human model is comprised of euploid (male and female) and aneuploid (triploid and trisomies: 13, 18, 21, XXX, and XXY) primary human fibroblast cells. For the mouse model, we treated embryos with reversine, a reversible spindle assembly checkpoint inhibitor, during the 4- to 8-cell division. Individual blastomeres were dissociated from control and reversine treated 8-cell embryos. Blastomeres were either imaged directly or used to generate chimeric blastocysts with differing ratios of control:reversine-treated cells.
Main results and the role of chance
Following unsupervised linear unmixing, the relative abundance of metabolic cofactors was quantified: reduced nicotinamide adenine dinucleotide (NAD(P)H) and flavins with the subsequent calculation of the optical redox ratio (ORR: Flavins/[NAD(P)H + Flavins]). Primary human fibroblast cells displayed an increase in the relative abundance of NAD(P)H with a decrease in flavins, leading to a significant reduction in the ORR for aneuploid cells (P < 0.05). The mouse embryos displayed an identical trend as the human model between control and reversine-treated embryos. Mathematical algorithms were applied and able to distinguish between (i) euploid and aneuploid primary human fibroblast cells, (ii) control and reversine-treated mouse blastomeres and (iii) chimeric blastocysts with differing ratios of control and reversine-treated cells. The accuracy of these separations was supported by receiver operating characteristic curves with areas under the curve. We also showed that hyperspectral imaging of the preimplantation embryo does not impact on embryo developmental competence, pregnancy outcome and offspring health in a mouse model. We believe the role of chance is low as both human somatic cells and mouse embryos showed a consistent shift in cellular metabolism in response to human fibroblast cells that are aneuploid and reversine treated mouse embryos.
Limitations, reasons for caution
Further validation of our approach could include sequencing of the ICM of individual blastocysts to determine the proportion of aneuploid cells in ICM and correlate this with the metabolic profile obtained through hyperspectral imaging.
Wider implications of the findings
With hyperspectral imaging able to discriminate between (i) euploid and aneuploid human fibroblast cells and (ii) control and reversine-treated mouse embryos, this could be an accurate, non-invasive and label-free optical imaging approach to assess mosaicism within the ICM of mouse embryos, potentially leading to a new diagnostic tool for embryos.
Trial registration number
Not applicable
Label-free hyperspectral imaging and quantification methods for surgical margin assessment of tissue specimens of cancer patients
