title: Human Spermatozoa Quantitative Proteomic Signature Classifies Normo- and Asthenozoospermia.
abstract: Scarcely understood defects lead to asthenozoospermia, which results in poor fertility outcomes. Incomplete knowledge of these defects hinders the development of new therapies and reliance on interventional therapies, such as in vitro fertilization, increases. Sperm cells, being transcriptionally and translationally silent, necessitate the proteomic approach to study the sperm function. We have performed a differential proteomics analysis of human sperm and seminal plasma and identified and quantified 667 proteins in sperm and 429 proteins in seminal plasma data set, which were used for further analysis. Statistical and mathematical analysis combined with pathway analysis and self-organizing maps clustering and correlation was performed on the data set.It was found that sperm proteomic signature combined with statistical analysis as opposed to the seminal plasma proteomic signature can differentiate the normozoospermic versus the asthenozoospermic sperm samples. This is despite the results that some of the seminal plasma proteins have big fold changes among classes but they fall short of statistical significance. S-Plot of the sperm proteomic data set generated some high confidence targets, which might be implicated in sperm motility pathways. These proteins also had the area under the curve value of 0.9 or 1 in ROC curve analysis.Various pathways were either enriched in these proteomic data sets by pathway analysis or they were searched by their constituent proteins. Some of these pathways were axoneme activation and focal adhesion assembly, glycolysis, gluconeogenesis, cellular response to stress and nucleosome assembly among others. The mass spectrometric data is available via ProteomeXchange with identifier PXD004098.
authors.affiliation: From the ‡Transplantation laboratory, Haartmaninkatu 3, PO Box 21, FI-00014 University of Helsinki, Finland.|§HUSLAB, Helsinki University Hospital, Helsinki, Finland.
authors.forename: Mayank
authors.initials: M
authors.lastname: Saraswat
authors.affiliation: §HUSLAB, Helsinki University Hospital, Helsinki, Finland.
authors.forename: Sakari
authors.initials: S
authors.lastname: Joenväärä
authors.affiliation: ¶School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Kamand-175005, Himachal Pradesh, India.
authors.forename: Tushar
authors.initials: T
authors.lastname: Jain
authors.affiliation: ‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
authors.forename: Anil Kumar
authors.initials: AK
authors.lastname: Tomar
authors.affiliation: ‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
authors.forename: Ashima
authors.initials: A
authors.lastname: Sinha
authors.affiliation: **Division of Clinical Microbiology & Molecular Medicine, Department of Laboratory Medicine, All India Institute of Medical Sciences, New Delhi-110029, India.
authors.forename: Sarman
authors.initials: S
authors.lastname: Singh
authors.affiliation: ‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
authors.forename: Savita
authors.initials: S
authors.lastname: Yadav
authors.affiliation: From the ‡Transplantation laboratory, Haartmaninkatu 3, PO Box 21, FI-00014 University of Helsinki, Finland; risto.renkonen@helsinki.fi.|§HUSLAB, Helsinki University Hospital, Helsinki, Finland.
authors.forename: Risto
authors.initials: R
authors.lastname: Renkonen
mesh_terms: D019540:Area Under Curve; D053627:Asthenozoospermia / Q000145:classification* / Q000378:metabolism; D016000:Cluster Analysis; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008297:Male; D025341:Principal Component Analysis; D060066:Protein Interaction Maps; D040901:Proteomics / Q000379:methods*; D012661:Semen / Q000378:metabolism*; D013094:Spermatozoa / Q000378:metabolism*