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. To analyze the aberrant regulatory events in human sperm proteins associated with male reproductive disorders in a high-throughput, reproducible, and reliable manner, we employed the Orbitrap Astral mass spectrometer, which independently operates Orbitrap Full Scan and Astral MS/MS to generate high-resolution full-scan spectra and high-quality secondary maps.

INSTRUMENT(S): Orbitrap Astral

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Spermatozoon

SUBMITTER: Ran Kong

LAB HEAD: Ran Kong

PROVIDER: PXD061698 | Pride | 2025-03-11

REPOSITORIES: Pride

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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

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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.

Project description:We highlight the leap in performance made possible with new instrumentation in the Thermo Scientific Orbitrap Astral™ mass spectrometer. Integrated alongside a high-resolution accurate mass (HRAM) Orbitrap analyzer, the instrument introduces a fast-switching quadrupole mass filter congruent with downstream speeds of ion detection, a dual-pressure ion processor cell which fragments ions in the high-pressure cell before they are moved to the low-pressure cell for further accumulation and orthogonal extraction to the Astral analyzer, and a high dynamic range detector. Altogether, ions can be manipulated in five stages of the MS at once (Orbitrap, ion routing multipole, two ion processor stages, Astral analyzer), allowing for a high degree of parallelization which enables MS/MS scan speeds of 200 Hz while HRAM MS1 full scans are synchronously acquired in the Orbitrap analyzer. To provide such fast scan speeds, the Astral analyzer is capable of single-ion detection sensitivity like a linear ion trap, all while enabling resolving powers of 80,000 at m/z 524. Here, in triplicate 7-min microflow active LC gradients on the Orbitrap Astral MS, we report 7,852 protein groups from 94,267 peptides on average. When employing 15-, 30-, and 60-min active, nano-LC gradients, triplicate experiments yield an average of 9,831, 10,411, and 10,645 unique protein groups from 195,612, 234,406, and 245,754 unique peptides, respectively. These nanoflow methods delivered a median sequence coverage of 38%, 42.4% and 44.4% across identified proteins for each respective gradient length. Our 30-min method delivered approximately 347 proteins per minute. Finally, we applied our 30-min active gradient method to analyze a CRISPR-Cas9 knockout (KO) of the mitochondrial gene MGME1 in human HAP1 cells. There, we quantified an average of 10,353 proteins across three technical replicates and find 449 significantly up- or down-regulated proteins relative to wild-type (WT) HAP1 proteins. Proteins from the same sample quantified using a 61-min active gradient Orbitrap Ascend DIA method show strong fold-change correlations to and gene ontology (GO) term agreement with our results.Building upon the immense progress of the mass spectrometry and proteomics communities of the past ten years, here we report alongside other recent works, that the one-hour human proteome is now within reach.

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.

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