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. 2022 Dec 15;11(24):4064.
doi: 10.3390/cells11244064.

Proteomic Landscape of Human Spermatozoa: Optimized Extraction Method and Application

Affiliations

Proteomic Landscape of Human Spermatozoa: Optimized Extraction Method and Application

Mengqi Luo et al. Cells. .

Abstract

Human spermatozoa proteomics exposed to some physical, biological or chemical stressors is being explored. However, there is a lack of optimized sample preparation methods to achieve in-depth protein coverage for sperm cells. Meanwhile, it is not clear whether antibiotics can regulate proteins to affect sperm quality. Here, we systematically compared a total of six different protein extraction methods based the combination of three commonly used lysis buffers and physical lysis strategies. The urea buffer combined with ultrasonication (UA-ultrasonication) produced the highest protein extraction rate, leading to the deepest coverage of human sperm proteome (5685 protein groups) from healthy human sperm samples. Since the antibiotics, amoxicillin and clarithromycin, have been widely used against H. pylori infection, we conduct a longitudinal study of sperm proteome via data-independent acquisition tandem mass spectrometry (DIA-MS/MS) on an infected patient during on and off therapy with these two drugs. The semen examination and morphological analysis were performed combined with proteomics analysis. Our results indicated that antibiotics may cause an increase in the sperm concentration and the rate of malformed sperm and disrupt proteome expression in sperm. This work provides an optimized extraction method to characterize the in-depth human sperm proteome and to extend its clinical applications.

Keywords: antibiotic; extraction method; mass spectrometry; proteomics; spermatozoa.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Figure 1
Figure 1
Comparison of quantitative proteins using different sample processing methods. (A), workflow of semen sample processing; (B), SDS-PAGE analysis of sperm proteins; (C), Venn plot of quantified proteins; (D), number of quantitative peptides and proteins.
Figure 2
Figure 2
In-depth proteomics analysis of human sperm. (A), in-depth proteomic workflow of human sperm based on DDA; (B), analysis summary of LC-MS/MS spectral database search: total MS2 spectra, matched MS2 spectra, unique peptides and identified protein groups; (C), Gene Ontology analysis of identified proteins; (D), sperm protein groups identified currently compared with the previous study and review.
Figure 3
Figure 3
Semen examination and morphological analysis of human sperm after antibiotic therapy. (A), abnormalities in sperm morphology observed in sperm after antibiotic therapy by the Papanicolaou method and light microscopy (scale bars, 5 μm, were used to calculate sperm size and length); (B), sperm concentration of the ten samples collected in the medication period (M) and withdrawal period (W); (C), ratio of sperm with heck defects in the M and W groups; (D), ratio of sperm with tail defects in the M and W groups. * means p < 0.05.
Figure 4
Figure 4
Quantitative proteomics analysis of human sperm after antibiotic therapy. (A), quantitative proteomics workflow of human sperm based on direct DIA; (B), analysis summary of LC-MS/MS spectral database search using strict thresholds; (C), volcano plot of sperm proteomic data. (D), PCA of differentially expressed sperm proteins; (E), Gene Ontology analysis of differentially expressed sperm proteins in the W group compared to the M group.
Figure 5
Figure 5
Heatmap analysis of differentially expressed sperm proteins between the M and W groups.
Figure 6
Figure 6
Western blot validation (A) and LC-MS/MS quantification (B) of four representative sperm proteins.

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