Analysis and characterisation of bovine oocyte and embryo biomarkers by matrix-assisted desorption ionisation mass spectrometry imaging

Analysis and characterisation of bovine oocyte and embryo biomarkers by matrix-assisted desorption ionisation mass spectrometry imaging

In the field of 'single cell analysis', many classical strategies like immunofluorescence and electron microscopy are the primary techniques of choice. However, these methodologies are time consuming and do not permit direct identification of specific molecular classes, such as lipids. In...

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Bibliographic Details
Published in:Reproduction fertility and development Vol. 28; no. 3; p. 293
Main Authors: Gonçalves, Roseli F, Ferreira, Mónica S, de Oliveira, Diogo N, Canevarolo, Rafael, Achilles, Marcos A, D'Ercole, Daniela L, Bols, Peter E, Visintin, Jose A, Killian, Gary J, Catharino, Rodrigo R
Format: Journal Article
Language:English
Published: Australia 01-01-2016
Subjects:
Animals
Biomarkers - metabolism
Blastocyst - metabolism
Cattle
Embryo Culture Techniques
Embryonic Development
Female
Fertilization in Vitro
In Vitro Oocyte Maturation Techniques
Metabolomics - methods
Multivariate Analysis
Oocytes - metabolism
Phosphatidylcholines - metabolism
Pregnancy
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
Sphingomyelins - metabolism
Time Factors
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Summary:In the field of 'single cell analysis', many classical strategies like immunofluorescence and electron microscopy are the primary techniques of choice. However, these methodologies are time consuming and do not permit direct identification of specific molecular classes, such as lipids. In the present study, a novel mass spectrometry-based analytical approach was applied to bovine oocytes and embryos. This new metabolomics-based application uses mass spectrometry imaging (MSI), efficient data processing and multivariate data analysis. Metabolic fingerprinting (MF) was applied to the analysis of unfertilised oocytes, 2-, 4- and 8-cell embryos and blastocysts. A semiquantitative strategy for sphingomyelin [SM (16:0)+Na](+) (m/z 725) and phosphatidylcholine [PC (32:0)+Na](+) (m/z 756) was developed, showing that lipid concentration was useful for selecting the best metabolic biomarkers. This study demonstrates that a combination of MF, MSI features and chemometric analysis can be applied to discriminate cell stages, characterising specific biomarkers and relating them to developmental pathways. This information furthers our understanding of fertilisation and preimplantation events during bovine embryo development.
ISSN:1031-3613
DOI:10.1071/RD14047