Dataset Information

Astral-DIA Proteomics Deciphers the Molecular Landscape of Human Spermatozoa: A Comprehensive Quantitative Proteomic Characterization of Sperm Function and Fertility Potential

ABSTRACT: Male infertility is fundamentally rooted in developmental defects of germ cells and associated molecular dysregulation, yet the underlying mechanisms remain poorly understood. Data-independent acquisition (DIA) has emerged as a powerful tool in discovery proteomics, enabling the identification of disease biomarkers, therapeutic targets, and molecular pathways with high precision and reproducibility. T

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Spermatozoon

SUBMITTER: Ran Kong

LAB HEAD: Ran Kong

PROVIDER: PXD061725 | Pride | 2025-03-12

REPOSITORIES: Pride

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Publications

The PRIDE database at 20 years: 2025 update.

Perez-Riverol Yasset Y Bandla Chakradhar C Kundu Deepti J DJ Kamatchinathan Selvakumar S Bai Jingwen J Hewapathirana Suresh S John Nithu Sara NS Prakash Ananth A Walzer Mathias M Wang Shengbo S Vizcaíno Juan Antonio JA

Nucleic acids research 20250101 D1

The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world's leading mass spectrometry (MS)-based proteomics data repository and one of the founding members of the ProteomeXchange consortium. This manuscript summarizes the developments in PRIDE resources and related tools for the last three years. The number of submitted datasets to PRIDE Archive (the archival component of PRIDE) has reached on average around 534 datasets per month. This has been possible thanks ...[more]

PMID: 39494541

Similar Datasets

Project description:Infertility is a widespread problem, affecting around 15% of couples worldwide, and is defined as the inability to achieve pregnancy within one year despite unprotected intercourse 1. Infertility can be caused by either male or female reproductive issues. Various medical conditions including malignancies, infections, urogenital conditions, or genetic causes can contribute to male infertility. However, 30-40% of men in their reproductive age are affected by idiopathic infertility, according to the guidelines of European Association of Urology (EAU) 1. Towards a better understanding of male infertility, it is mandatory to achieve a comprehensive understanding of involved genes, their RNA transcripts, and regulatory factors, including miRNAs, which influence the expression level of proteins. Therefore, such proteins need to be identified to investigate their role in spermatogenesis and male infertility. Although there are numerous studies on RNAs, including miRNAs related to male infertility 2-9, there are few studies aiming to cover the whole proteome of human sperm 10. The sperm transcriptome comprises a total of 60,505 transcripts including 11,688 differentially expressed transcripts in infertile and fertile men, as reported by Joshi et al. (2022)11. The entire sperm proteome encompasses 6871 proteins, as summarized by Castillo et al. (2018)10. Nevertheless, there is still a lack of high-throughput studies aiming to identify dysregulated proteins in sperm from subfertile men. Only few studies focused on comparisons of the sperm proteome in men with asthenozoospermia and there is virtually no proteomic studies of oligoasthenozoospermic men 12. Some identified proteins in sperm have functions in maintaining sperm motility and enabling fertilization and are involved in structural composition and/or energy metabolism 12-14 and others are not yet functionally characterized. In this study, we employed Mass spectrometry (MS) technology that is still rarely used in the field of human reproductive research to investigate the proteomic landscape of human sperm and their differential expression patterns in men with subfertility.

Project description:The goal of this study was to use global gene expression as a diagnostic tool to compare hepatic gene expression patterns in both male and female FHM in streams with the lowest and highest reproductive success, and potentially identify a suite of mRNA transcripts indicative of reproduction in a population The goal of this study was to compare differences in hepatic mRNA expression between gender at high and low egg-producing streams, not differences between individual streams. A k-means cluster analysis was performed using eggs/pair/day on the original 17 streams to delineate 3 clusters: high, medium and low. From that analysis, FHM from 6 of the original 17-streams used in Crago et al. (2010) were chosen for the microarray experiment (Fig. 1, Table 1). In this study the experimental condition is reproductive success; High versus Low reproductive success. The streams grouped into High Reproductive Success were Oak Creek-2007 (2313 eggs), Point Creek (1277 eggs), Meeme Creek (1164 eggs) and Baird Creek (967 eggs). The streams grouped into Low Reproductive Success were: Ashwaubenon Creek (0 eggs), Devils Creek (541 eggs) and Oak Creek-2006 (642 eggs). Multiple regression analysis using the 22 sediment and water quality characteristics measured in the 6 streams with the highest (n = 4 and lowest (n = 3) streams demonstrated that there were no differences amongst the streams in regards to measure sediment and water variables. .5 One array was run for each gender from each stream. So that Males from Point Creek were pooled and run on one array, males from Ashwaubenon Creek were run on a separate array, and so forth. There were 14 arrays used in this study, 7 for males, 7 for females from individual rivers. So that Males from Point Creek were pooled and run on one array, males from Ashwaubenon Creek were run on a separate array, and so forth. In the case of Oak Creek, which was sampled in both years, there was a large difference in egg production between two years. Therefore separate arrays were run for Oak Creek 2006 and Oak Creek 2007. All streams chosen had overall survival rates of at least 80% through the 21-day sampling period, except Devils River. The survival rate for Devils River was at 100% until four days prior to the end of the experiment when six fish died or escaped.

			Action	DRS
	20240192_KR.xlsx	Xlsx
	20240275	Other
	20240275.tsv	Tabular
	20240275_L1.raw	Raw
	20240275_L10.raw	Raw