Differential Proteomic Analysis of Human Sperm: A Systematic Review to Identify Candidate Targets to Monitor Sperm Quality

Pedro O Corda; Jéssica Moreira; John Howl; Pedro F Oliveira; Margarida Fardilha; Joana Vieira Silva

doi:10.5534/wjmh.220262

Differential Proteomic Analysis of Human Sperm: A Systematic Review to Identify Candidate Targets to Monitor Sperm Quality

World J Mens Health. 2024 Jan;42(1):71-91. doi: 10.5534/wjmh.220262. Epub 2023 Apr 20.

Authors

Pedro O Corda¹, Jéssica Moreira¹, John Howl², Pedro F Oliveira³, Margarida Fardilha⁴, Joana Vieira Silva^{1

3

5}

Affiliations

¹ Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal.
² Research Institute in Healthcare Science, University of Wolverhampton, Wolverhampton, UK.
³ LAQV/REQUIMTE, Department of Chemistry, University of Aveiro, Aveiro, Portugal.
⁴ Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal. mfardilha@ua.pt.
⁵ Unit for Multidisciplinary Research in Biomedicine (UMIB), Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal.

Abstract

Purpose: The advent of proteomics provides new opportunities to investigate the molecular mechanisms underlying male infertility. The selection of relevant targets based on a single analysis is not always feasible, due to the growing number of proteomic studies with conflicting results. Thus, this study aimed to systematically review investigations comparing the sperm proteome of normozoospermic and infertile men to define a panel of proteins with the potential to be used to evaluate sperm quality.

Materials and methods: A literature search was conducted on PubMed, Web of Science, and Scopus databases following the PRISMA guidelines. To identify proteins systematically reported, first the studies were divided by condition into four groups (asthenozoospermia, low motility, unexplained infertility, and infertility related to risk factors) and then, all studies were analysed simultaneously (poor sperm quality). To gain molecular insights regarding identified proteins, additional searches were performed within the Human Protein Atlas, Mouse Genome Informatics, UniProt, and PubMed databases.

Results: Thirty-two studies were included and divided into 4 sub-analysis groups. A total of 2752 proteins were collected, of which 38, 1, 3 and 2 were indicated as potential markers for asthenozoospermia, low motility, unexplained infertility and infertility related to risk factors, respectively, and 58 for poor sperm quality. Among the identified proteins, ACR, ACRBP, ACRV1, ACTL9, AKAP4, ATG3, CCT2, CFAP276, CFAP52, FAM209A, GGH, HPRT1, LYZL4, PRDX6, PRSS37, REEP6, ROPN1B, SPACA3, SOD1, SPEM1, SPESP1, SPINK2, TEKT5, and ZPBP were highlighted due to their roles in male reproductive tissues, association with infertility phenotypes or participation in specific biological functions in spermatozoa.

Conclusions: Sperm proteomics allows the identification of protein markers with the potential to overcome limitations in male infertility diagnosis and to understand changes in sperm function at the molecular level. This study provides a reliable list of systematically reported proteins that could be potential targets for further basic and clinical studies.

Keywords: Biological processes; Male infertility; Proteome; Proteomics; Spermatozoa.

Abstract

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