Infertility is one of principal health and social problems of this century. Male factors are involved in half of the cases and often the alteration concerns sperm motility. Seminogram is the gold standard technique for semen analysis, but it presents several limits. For this reason, we propose a new method for discriminating asthenozoospermic samples (low sperm motility) from normozoospermic ones (progressive motility > 32%) based on the never explored analysis of the volatile metabolites in the headspace of human semen sample by Gas Chromatograph (GC) equipped with two detectors: aMass Spectrometer (MS) and a metal oxide based gas sensor sensitive (MOX) to Volatile Organic Compounds (VOCs). VOC sensor signal profiles (resistance vs. time) showed a higher sensitivity to specific organic classes such as aldehydes and ketones. The sensorgrams were preprocessed and analysed by PLS-DA. The results showed that sensorgrams analysis by suitable bioinformatics techniques has a good discrimination power and could support physiological parameters in human semen assessment. The analysis of the human semen Volatilome may be a proof-of-concept for the development of a novel micro-GC device with a sensor array detector, a potential candidate for infertility assessment in clinical practice.
Characterization of Human Semen by GC-MS and VOC Sensor: An Unexplored Approach to the Study on Infertility
Zara, Vincenzo;Ferramosca, Alessandra;
2019-01-01
Abstract
Infertility is one of principal health and social problems of this century. Male factors are involved in half of the cases and often the alteration concerns sperm motility. Seminogram is the gold standard technique for semen analysis, but it presents several limits. For this reason, we propose a new method for discriminating asthenozoospermic samples (low sperm motility) from normozoospermic ones (progressive motility > 32%) based on the never explored analysis of the volatile metabolites in the headspace of human semen sample by Gas Chromatograph (GC) equipped with two detectors: aMass Spectrometer (MS) and a metal oxide based gas sensor sensitive (MOX) to Volatile Organic Compounds (VOCs). VOC sensor signal profiles (resistance vs. time) showed a higher sensitivity to specific organic classes such as aldehydes and ketones. The sensorgrams were preprocessed and analysed by PLS-DA. The results showed that sensorgrams analysis by suitable bioinformatics techniques has a good discrimination power and could support physiological parameters in human semen assessment. The analysis of the human semen Volatilome may be a proof-of-concept for the development of a novel micro-GC device with a sensor array detector, a potential candidate for infertility assessment in clinical practice.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
