Deep Metabolomic Profiling Reveals Alterations in Fatty Acid Synthesis and Ketone Body Degradations in Spermatozoa and Seminal Plasma of Astheno-Oligozoospermic Bulls

Abstract

Male fertility is extremely important in dairy animals because semen from a single bull is used to inseminate several thousand females. Asthenozoospermia (reduced sperm motility) and oligozoospermia (reduced sperm concentration) are the two important reasons cited for idiopathic infertility in crossbred bulls; however, the etiology remains elusive. In this study, using a non-targeted liquid chromatography with tandem mass spectrometry-based approach, we carried out a deep metabolomic analysis of spermatozoa and seminal plasma derived from normozoospermic and astheno-oligozoospermic bulls. Using bioinformatics tools, alterations in metabolites and metabolic pathways between normozoospermia and astheno-oligozoospermia were elucidated. A total of 299 and 167 metabolites in spermatozoa and 183 and 147 metabolites in seminal plasma were detected in astheno-oligozoospermic and normozoospermic bulls, respectively. Among the mapped metabolites, 75 sperm metabolites were common to both the groups, whereas 166 and 50 sperm metabolites were unique to astheno-oligozoospermic and normozoospermic bulls, respectively. Similarly, 86 metabolites were common to both the groups, whereas 45 and 37 seminal plasma metabolites were unique to astheno-oligozoospermic and normozoospermic bulls, respectively. Among the differentially expressed metabolites, 62 sperm metabolites and 56 seminal plasma metabolites were significantly dysregulated in astheno-oligozoospermic bulls. In spermatozoa, selenocysteine, deoxyuridine triphosphate, and nitroprusside showed significant enrichment in astheno-oligozoospermic bulls. In seminal plasma, malonic acid, 5-diphosphoinositol pentakisphosphate, D-cysteine, and nicotinamide adenine dinucleotide phosphate were significantly upregulated, whereas tetradecanoyl-CoA was significantly downregulated in the astheno-oligozoospermia. Spermatozoa from astheno-oligozoospermic bulls showed alterations in the metabolism of fatty acid and fatty acid elongation in mitochondria pathways, whereas seminal plasma from astheno-oligozoospermic bulls showed alterations in synthesis and degradation of ketone bodies, pyruvate metabolism, and inositol phosphate metabolism pathways. The present study revealed vital information related to semen metabolomic differences between astheno-oligozoospermic and normospermic crossbred breeding bulls. It is inferred that fatty acid synthesis and ketone body degradations are altered in the spermatozoa and seminal plasma of astheno-oligozoospermic crossbred bulls. These results open up new avenues for further research, and current findings can be applied for the modulation of identified pathways to restore sperm motility and concentration in astheno-oligozoospermic bulls.

Keywords: dairy bulls; mass spectrometry; metabolomics; semen quality; seminal plasma; spermatozoa.

Figure 1

Venn diagram of total mapped metabolites of spermatozoa and seminal plasma of astheno-oligozoospermia and normozoospermia bulls in HMDB search.

Figure 2

Normalization of common metabolites of spermatozoa (A) and seminal plasma (B) of both groups, prior to statistical analysis based on quantile normalization, log transformation and pareto scaling.

Figure 3

PLS-DA based on score plot (A) and Heat map (B) of Vip score of significant metabolites in spermatozoa of astheno-oligozoospermia bulls. (C) Cross validation of PLS-DA based on score plot of significant metabolites in spermatozoa of astheno-oligozoospermia bulls where Q2 is an estimate of the predictive ability of the model, and is calculated via cross validation. In each CV, the predicted data are compared with the original data, and the sum of squared error is calculated. The prediction error is summed over all samples (Predicted residual sum of squares or PRESS). For convivence, the PRESS is divided by initial sum of the squares and subtracted from 1 to resemble the scale of the R2. Good prediction will have low PRESS or high Q2. It is also possible to have negative Q2, which means that the model is not at all predictive or overfitted.

Figure 4

K-means clustering of spermatozoa metabolites of astheno-oligozoospermia bulls.

Figure 5

PLS-DA based on score plot (A) and Heat map (B) of Vip score of significant metabolites in seminal plasma of astheno-oligozoospermia bulls. (C) Cross validation of PLS-DA based on score plot of significant metabolites in seminal plasma of astheno-oligozoospermia bulls where Q2 is an estimate of the predictive ability of the model, and is calculated via cross validation. In each CV, the predicted data are compared with the original data, and the sum of squared error is calculated. The prediction error is summed over all samples (Predicted residual sum of squares or PRESS). For convivence, the PRESS is divided by initial sum of the squares and subtracted from 1 to resemble the scale of the R2. Good prediction will have low PRESS or high Q2. It is also possible to have negative Q2, which means that the model is not at all predictive or overfitted.

Figure 6

K-means clustering of seminal plasma metabolites of astheno-oligozoospermia bulls.

Figure 7

Metscape of network based on compound-enzyme-gene reaction.