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Network analyses of sperm-egg recognition and binding: ready to rethink fertility mechanisms?

ABSTRACT: The rapid growth of published literature makes biomedical text mining increasingly invaluable for unpacking implicit knowledge hidden in unstructured text. We employed biomedical text mining and biological networks analyses to research the process of sperm egg recognition and binding (SERB). We selected from the literature the molecules expressed either on spermatozoa or on oocytes thought to be involved in SERB and, using an automated literature search software (Agilent Literature Search), we realized a network, SERBN, characterized by a hierarchical scale free and a small world topology. We used an integrated approach, either based on selection of hubs or by a cluster analysis, to discern the key molecules of SERB. We found that in most cases some of them are not directly situated on spermatozoa and oocyte, but are dispersed in oviductal fluid or embedded in exosomes present in the perivitelline space. To confirm and validate our results, we performed further analyses using STRING and Reactome FI software. Our findings underscore that the fertility is not a property of gametes in isolation, but rather depends on the functional integrity of the entire reproductive system. These observations collectively underscore the importance of integrative biology in exploring biological systems and in rethinking of fertility mechanisms in the light of this innovative approach.

SUBMITTER: Bernabo N

PROVIDER: S-EPMC4253145 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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Network analyses of sperm-egg recognition and binding: ready to rethink fertility mechanisms?

Bernabò Nicola N Ordinelli Alessandra A Di Agostino Raffaele R Mattioli Mauro M Barboni Barbara B

Omics : a journal of integrative biology 20141201 12

The rapid growth of published literature makes biomedical text mining increasingly invaluable for unpacking implicit knowledge hidden in unstructured text. We employed biomedical text mining and biological networks analyses to research the process of sperm egg recognition and binding (SERB). We selected from the literature the molecules expressed either on spermatozoa or on oocytes thought to be involved in SERB and, using an automated literature search software (Agilent Literature Search), we r ...[more]

PMID: 25454512

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Project description:The escalated use of artificial insemination in swine has increased the importance of determining fertility of a semen sample before it is used. Multiple laboratory assays have been developed to assess fertilizing potential but they have yielded inconsistent results. This experiment sought to determine the relationship between in vitro competitive zona binding ability and in vivo fertility based on heterospermic inseminations and paternity testing. The zona pellucida binding ability and fertility of sperm from 15 boars was assessed by comparing sperm from one boar with sperm from other individual boars in a pairwise fashion using four ejaculates. The relationship of zona binding ability to the mean number of piglets sired per litter for each boar as well as historic fertility data (litter size and farrowing rate) was assessed. The in vitro competition assay consisted of labeling sperm from each boar of the pair with a different fluorophore and incubating an equal number of sperm from each boar in the same droplet with porcine oocytes. The competitive assay was highly effective in ranking boars by zona binding ability (R2=0.94). Paternity testing using microsatellite markers was used to determine the mean number of piglets sired per litter for each boar during heterospermic inseminations. The pairwise heterospermic insemination assay was effective in ranking boar fertility (R2=0.59). Using historical data from these boars, average litter size and farrowing rate were correlated (r=0.81, p<0.001). However, zona binding ability was not significantly correlated with historic farrowing rate data or historic average litter size. Boar sperm zona binding ability was also not correlated significantly with the mean number of piglets sired per litter following heterospermic insemination. But the number of piglets sired by each boar was related to a combination of zona binding ability, sperm motility, normal morphology, acrosomal integrity, and the presence of distal droplets (R2=0.70). These results suggest that zona binding ability is not an accurate predictor of fertilizing ability when used alone; however, when coupled with other sperm assessments, fertility may be predicted successfully.

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Network analyses of sperm-egg recognition and binding: ready to rethink fertility mechanisms?

Publications

Network analyses of sperm-egg recognition and binding: ready to rethink fertility mechanisms?

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