Metabolomics: a state-of-the-art technology for better understanding of male infertility

Metabolomic signature of sperm in men with obesity-associated asthenozoospermia

PURPOSE

Obese men have a significantly increased risk of developing asthenozoospermia. Sperm motility is directly related to cellular energy supply and metabolic status. Sperm metabolomics research based on Gas chromatography-mass spectrometry (GC-MS) technology can provide useful information for the pathological mechanism, diagnosis, and treatment of obesity-associated asthenozoospermia.

METHODS

Sperm samples were obtained from a healthy control group (n = 49) and patients with obesity-associated asthenozoospermia (n = 40). After the analysis of sperm samples using GC-MS, various multivariate statistical methods such as principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) were conducted.

RESULTS

A total of 56 metabolites were identified in the sperm samples. Among them, 19 differential metabolites were found between the two groups. Metabolites such as glutamic acid, fumaric acid, and cysteine were significantly downregulated in the sperm of patients with obesity-associated asthenozoospermia, while metabolites like palmitic acid, stearic acid, and alanine were significantly upregulated. The differential metabolites were enriched in D-glutamine and D-glutamate metabolism; proline, aspartate, and glutamate metabolism; glutathione metabolism and the other metabolic pathways.

CONCLUSION

Obesity may influence the composition of metabolic products in sperm, and metabolomic analysis proves beneficial for the future diagnosis and treatment of obesity-associated asthenozoospermia.

Understanding seminal plasma in male infertility: emerging markers and their implications

Infertility affects a significant proportion of the reproductive-aged population, with male-associated factors contributing to over half of the cases. However, current diagnostic tools have limitations, leading to an underestimation of the true prevalence of male infertility. While traditional semen parameters provide some insights, they fail to determine the true fertility potential in a substantial number of instances. Therefore, it is crucial to investigate additional molecular targets responsible for male infertility to improve understanding and identification of such cases. Seminal plasma, the main carrier of molecules derived from male reproductive glands, plays a crucial role in reproduction. Amongst its multifarious functions, it regulates processes such as sperm capacitation, sperm protection and maturation, and even interaction with the egg's zona pellucida. Seminal plasma offers a non-invasive sample for urogenital diagnostics and has shown promise in identifying biomarkers associated with male reproductive disorders. This review aims to provide an updated and comprehensive overview of seminal plasma in the diagnosis of male infertility, exploring its composition, function, methods used for analysis, and the application of emerging markers. Apart from the application, the potential challenges of seminal plasma analysis such as standardisation, marker interpretation and confounding factors have also been addressed. Moreover, we have also explored future avenues for enhancing its utility and its role in improving diagnostic strategies. Through comprehensive exploration of seminal plasma's diagnostic potential, the present analysis seeks to advance the understanding of male infertility and its effective management.

A metabolomic perspective on the mechanisms by which environmental pollutants and lifestyle lead to male infertility

The incidence of male infertility (MI) is rising annually. According to epidemiological studies, environmental pollution (e.g., organic, inorganic, and air pollutants), occupational exposure (e.g., high temperature, organic solvents, and pesticides), and poor lifestyle (e.g., diet, sleep, smoking, alcohol consumption, and exercise) are important non-genetic causative factors of MI. Due to multiple and complex causative factors, the dose-effect relationship, and the uncertainty of pathogenicity, the pathogenesis of MI is far from fully clarified. Recent data show that the pathogenesis of MI can be monitored by the metabolites in serum, seminal plasma, urine, testicular tissue, sperm, and other biological samples. It is considered that these metabolites are closely related to MI phenotypes and can directly reflect the individual pathological and physiological conditions. Therefore, qualitative and quantitative analysis of the metabolome, the related metabolic pathways, and the identification of biomarkers will help to explore the MI-related metabolic problems and provide valuable insights into its pathogenic mechanisms. Here, we summarized new findings in MI metabolomics biomarkers research and their abnormal metabolic pathways triggered by the presented non-genetic risk factors, providing a metabolic landscape of semen and seminal plasma in general MI patients. Then, we compared the similarities and differences in semen and seminal plasma biomarkers between MI patients exposed to environmental and poor lifestyle factors and MI patients in general, and summarized some common biomarkers. We provide a better understanding of the biological underpinnings of MI pathogenesis, which might offer novel diagnostic, prognostic, and precise treatment approaches to MI.

Oxidative Stress Biomarkers in Male Infertility: Established Methodologies and Future Perspectives

Male fertility can be affected by oxidative stress (OS), which occurs when an imbalance between the production of reactive oxygen species (ROS) and the body's ability to neutralize them arises. OS can damage cells and influence sperm production. High levels of lipid peroxidation have been linked to reduced sperm motility and decreased fertilization ability. This literature review discusses the most commonly used biomarkers to measure sperm damage caused by ROS, such as the high level of OS in seminal plasma as an indicator of imbalance in antioxidant activity. The investigated biomarkers include 8-hydroxy-2-deoxyguanosine acid (8-OHdG), a marker of DNA damage caused by ROS, and F2 isoprostanoids (8-isoprostanes) produced by lipid peroxidation. Furthermore, this review focuses on recent methodologies including the NGS polymorphisms and differentially expressed gene (DEG) analysis, as well as the epigenetic mechanisms linked to ROS during spermatogenesis along with new methodologies developed to evaluate OS biomarkers. Finally, this review addresses a valuable insight into the mechanisms of male infertility provided by these advances and how they have led to new treatment possibilities. Overall, the use of biomarkers to evaluate OS in male infertility has supplied innovative diagnostic and therapeutic approaches, enhancing our understanding of male infertility mechanisms.

Metabolomics of male infertility

This review explores the use of metabolomics in male infertility. Metabolomics, an evolving omics technology that targets the products of cellular metabolism, is valuable for elucidating underlying pathophysiology of many disorders including male infertility. The identification of reliable biomarkers is essential for accurate diagnosis and for developing precision therapeutics for those afflicted by reproductive dysfunction. Unfortunately, despite significant progress to date, the intricate relationships between these metabolic pathways and male infertility remain elusive. It is clear, however, that additional research is required to more fully characterize the role of metabolomics in this disorder and in the potential development of targeted therapies for precision medicine.

Application and discoveries of metabolomics and proteomics in the study of female infertility

Introduction

Female infertility is defined as the absence of clinical pregnancy after 12 months of regular unprotected sexual intercourse.

Methods

This study employed metabolomics and proteomics approaches to investigate the relationship between metabolites and proteins and female infertility. The study used metabolomics and proteomics data from the UK Biobank to identify metabolites and proteins linked to infertility.

Results

The results showed that GRAM domain-containing protein 1C and metabolites fibrinogen cleavage peptides ADpSGEGDFXAEGGGVR and 3-Hydroxybutyrate had a positive correlation with infertility, whereas proteins such as Interleukin-3 receptor subunit alpha, Thrombospondin type-1 domain-containing protein 1, Intestinal-type alkaline phosphatase, and platelet and endothelial cell adhesion molecule 1 exhibited a negative correlation. These findings provide new clues and targets for infertility diagnosis and treatment. However, further research is required to validate these results and gain a deeper understanding of the specific roles of these metabolites and proteins in infertility pathogenesis.

Discussion

In conclusion, metabolomics and proteomics techniques have significant application value in the study of infertility, allowing for a better understanding of the biological mechanisms underlying infertility and providing new insights and strategies for its diagnosis and treatment. These research findings provide a crucial biological mechanistic basis for early infertility screening, prevention, and treatment.

Comparison of the metabolite profile of donkey and horse seminal plasma and its relationship with sperm viability and motility

Previous research revealed that several seminal plasma (SP) metabolites are related to sperm functionality, fertility, and preservation. While it is understood that variations between species exist, whether the SP metabolome differs between donkeys and horses has not been previously investigated. The aim of this work, therefore, was to characterize and compare donkey and horse SP metabolites using nuclear magnetic resonance (NMR) spectroscopy, and relate them to sperm viability and motility. For this purpose, ejaculates from 18 different donkeys and 18 different horses were collected and separated into two aliquots: one for harvesting the SP by centrifugation and obtaining the metabolic profile through NMR, and the other for evaluating sperm viability and motility. Based on total motility and sperm viability, samples were classified as with good (GQ) or poor (PQ) quality. The metabolomic profile of donkey and horse SP revealed the presence of 28 metabolites, which coincided in the two species. Yet, differences between horses and donkeys were observed in the concentration of 18 of these 28 metabolites, as well as between ejaculates classified as GQ or PQ and in the relationship of metabolites with sperm motility and viability. These findings suggest that sperm from donkeys and horses differ in their metabolism and energetic requirements, and that the concentration of specific SP metabolites may be related to sperm functionality. Further research should shed light on the metabolic needs of donkey and horse sperm, and evaluate how the knowledge collected from the contribution of these metabolites can help improve semen preservation in the two species.

Metabolomics profiling of seminal plasma in obesity-induced asthenozoospermia

BACKGROUND

Asthenozoospermia is one of the essential causes of male infertility, and its incidence is significantly higher in obese men. Due to its complex etiology and unknown pathomechanism, the diagnosis and treatment of obesity-induced asthenozoospermia is a prevalent problem in reproductive medicine.

OBJECTIVE

This study aims to explore major differential metabolites and metabolic pathways in seminal plasma and pathological mechanisms for obesity-induced asthenozoospermia.

MATERIALS AND METHODS

We performed non-target metabolomic studies on the seminal plasma of healthy men with normal semen parameters (HN group, n = 20), obese men with normal semen parameters (ON group, n = 20), and men with obesity-induced asthenozoospermia (OA group, n = 20) based on gas chromatography-mass spectrometry. Metabolic profilings and related pathway analyses were conducted to discriminate differential metabolites and metabolic pathways.

RESULTS

A total of 20 differential metabolites including fructose, succinic acid, aconitic acid, methylmaleic acid, glucopyranose, serine, valine, leucine, phenylalanine, glycine, glutamic acid, alanine, proline and threonine were identified in HN group and ON group; 24 differential metabolites including glucose, fructose, pyruvic acid, citric acid, succinic acid, aconitic acid, glucopyranose, glutamic acid, valine, leucine, glycine, phenylalanine, lysine, citrulline, proline and alanine were produced in OA group and ON group; and 28 differential metabolites including glucose, fructose, citric acid, succinic acid, glucopyranose, valine, glycine, serine, leucine, phenylalanine, alanine, threonine, proline, glutamic acid, citrulline, lysine and tyrosine were produced in OA group and HN group. In addition, abnormal energy metabolism including carbohydrate metabolism (TCA cycle, glycolysis/gluconeogenesis, and pyruvate metabolism) and amino acid metabolism (phenylalanine, tyrosine, and tryptophan biosynthesis, D-glutamine and D-glutamate metabolism; phenylalanine metabolism, etc.) were found in ON group and OA group.

CONCLUSION

Obesity could affect the metabolite composition in seminal plasma and abnormal energy metabolism in seminal plasma mainly including carbohydrate metabolism and amino acid metabolism were closely related to obesity-induced asthenozoospermia.

A different approach to the quantification of human seminal plasma metabolites using high-resolution NMR spectroscopy

In this study, a reliable method was established for the absolute quantification of metabolite concentrations in human seminal plasma using ERETIC2, a quantification tool developed by Bruker based on the PULCON principle. The performance of the ERETIC2 was examined using an AVANCE III HD NMR spectrometer (600 MHz) equipped with a triple inverse 1.7 mm TXI probe in terms of some experimental parameters that may affect the accuracy and precision of the quantitative results. Then, the accuracy, precision, and repeatibility of ERETIC2 were determined using L-asparagine solutions at different concentrations. And it was evaluated by comparing it with the classical internal standard (IS) quantification method. The relative standard deviation (RSD) values for ERETIC2 were calculated in the range of 0.55-1.90% and the minimum recovery value was 99.9%, while the RSD values for the IS method were calculated in the range of 0.88-5.83% and recovery value was minimum 91.0%. Besides, the RSD values of the inter-day precisions for the ERETIC2 and IS methods were obtained to be in the range of 1.25 - 3.03% and 0.97 - 3.46%, respectively. Finally, the concentration values of seminal plasma metabolites were determined using different pulse programs with both methods for samples obtained from normozoospermic control and azoospermic patient groups. The results proved that this quantification method developed using NMR spectroscopy is easy to use in complex sample systems such as biological fluids and is a good alternative to the classical internal standard method in terms of accuracy and sensitivity. In addition, the improvement of the spectral resolution and sensitivity with the microcoil probe technology and the possibility of analyzing with minimum sample quantities has contributed positively to the results of this method.

Seminal plasma biomarkers for predicting successful sperm retrieval in patients with nonobstructive azoospermia: a narrative review of human studies

BACKGROUND

Non-obstructive azoospermia (NOA) is considered to be the most severe form of male infertility. Before the emergence of surgical testicular sperm extraction and assisted reproductive technology, NOA patients could hardly become biological fathers of their children. However, failure of the surgery could cause physical and psychological harm to patients such as testicular damage, pain, hopeless of fertility and additional cost. Therefore, predicting the successful sperm retrieval (SSR) is so important for NOA patients to make their choice whether to do the surgery or not. Because seminal plasma is secreted by the testes and accessory gonads, it can reflect the spermatogenic environment, making it a preferential choice for SSR valuation. The purpose of this paper is to summarize the available evidence and provide the reader with a broad overview of biomarkers in seminal plasma for SSR prediction.

RESULTS

A total of 15,390 studies were searched from PUBMED, EMBASE, CENTRAL and Web of Science, but only 6615 studies were evaluated after duplications were removed. The abstracts of 6513 articles were excluded because they were irrelevant to the topic. The full texts of 102 articles were obtained, with 21 of them being included in this review. The included studies range in quality from medium to high. In the included articles, surgical sperm extraction methods included conventional testicular sperm extraction (TESE) and microdissection testicular sperm extraction (micro-TESE). Currently, the biomarkers in seminal plasma used to predict SSR are primarily RNAs, metabolites, AMH, inhibin B, leptin, survivin, clusterin, LGALS3BP, ESX1, TEX101, TNP1, DAZ, PRM1 and PRM2.

CONCLUSION

The evidence does not conclusively indicate that AMH and INHB in seminal plasma are valuable to predict the SSR. It is worth noting that RNAs, metabolites and other biomarkers in seminal plasma have shown great potential in predicting SSR. However, existing evidence is insufficient to provide clinicians with adequate decision support, and more prospective, large sample size, and multicenter trials are urgently needed.

Towards a Multi-Omics of Male Infertility

Infertility is a common problem affecting one in six couples and in 30% of infertile couples, the male factor is a major cause. A large number of genes are involved in spermatogenesis and a significant proportion of male infertility phenotypes are of genetic origin. Studies on infertility have so far primarily focused on chromosomal abnormalities and sequence variants in protein-coding genes and have identified a large number of disease-associated genes. However, it has been shown that a multitude of factors across various omics levels also contribute to infertility phenotypes. The complexity of male infertility has led to the understanding that an integrated, multi-omics analysis may be optimal for unravelling this disease. While there is a vast array of different factors across omics levels associated with infertility, the present review focuses on known factors from the genomics, epigenomics, transcriptomics, proteomics, metabolomics, glycomics, lipidomics, miRNomics, and integrated omics levels. These include: repeat expansions in AR, POLG, ATXN1, DMPK, and SHBG, multiple SNPs, copy number variants in the AZF region, disregulated miRNAs, altered H3K9 methylation, differential MTHFR, MEG3, PEG1, and LIT1 methylation, altered protamine ratios and protein hypo/hyperphosphorylation. This integrative review presents a step towards a multi-omics approach to understanding the complex etiology of male infertility. Currently only a few genetic factors, namely chromosomal abnormalities and Y chromosome microdeletions, are routinely tested in infertile men undergoing intracytoplasmic sperm injection. A multi-omics approach to understanding infertility phenotypes may yield a more holistic view of the disease and contribute to the development of improved screening methods and treatment options. Therefore, beside discovering as of yet unknown genetic causes of infertility, integrating multiple fields of study could yield valuable contributions to the understanding of disease development. Future multi-omics studies will enable to synthesise fragmented information and facilitate biomarker discovery and treatments in male infertility.

Metabolomic fingerprinting of pig seminal plasma identifies in vivo fertility biomarkers

Background

Metabolomic approaches, which include the study of low molecular weight molecules, are an emerging -omics technology useful for identification of biomarkers. In this field, nuclear magnetic resonance (NMR) spectroscopy has already been used to uncover (in) fertility biomarkers in the seminal plasma (SP) of several mammalian species. However, NMR studies profiling the porcine SP metabolome to uncover in vivo fertility biomarkers are yet to be carried out. Thus, this study aimed to evaluate the putative relationship between SP-metabolites and in vivo fertility outcomes. To this end, 24 entire ejaculates (three ejaculates per boar) were collected from artificial insemination (AI)-boars throughout a year (one ejaculate every 4 months). Immediately after collection, ejaculates were centrifuged to obtain SP-samples, which were stored for subsequent metabolomic analysis by NMR spectroscopy. Fertility outcomes from 1525 inseminations were recorded over a year, including farrowing rate, litter size, stillbirths per litter and the duration of pregnancy.

Results

A total of 24 metabolites were identified and quantified in all SP-samples. Receiver operating characteristic (ROC) curve analysis showed that lactate levels in SP had discriminative capacity for farrowing rate (area under the curve [AUC] = 0.764) while carnitine (AUC = 0.847), hypotaurine (AUC = 0.819), sn-glycero-3-phosphocholine (AUC = 0.833), glutamate (AUC = 0.799) and glucose (AUC = 0.750) showed it for litter size. Similarly, citrate (AUC = 0.743), creatine (AUC = 0.812), phenylalanine (AUC = 0.750), tyrosine (AUC = 0.753) and malonate (AUC = 0.868) levels had discriminative capacity for stillbirths per litter; and malonate (AUC = 0.767) and fumarate (AUC = 0.868) levels for gestation length.

Conclusions

The assessment of selected SP-metabolites in ejaculates through NMR spectroscopy could be considered as a promising non-invasive tool to predict in vivo fertility outcomes in pigs. Moreover, supplementing AI-doses with specific metabolites should also be envisaged as a way to improve their fertility potential.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-021-00636-5.

Looking at time dependent differentiation of mesenchymal stem cells by culture media using MALDI-TOF-MS

Mesenchymal stem cells (MSCs) are multipotent cells which are popular in human regenerative medicine. These cells can renew themselves and differentiate into several specialized cell types including osteoblasts, adipocytes, and chondrocytes under physiological and experimental conditions. MSCs can secret a lot of components including proteins and metabolites. These components have significant effects on their surrounding cells and also can be used to characterize them. This characterization of multipotent MSCs plays a critical role in their therapeutic potential. The metabolic profile of culture media verified by applying matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF-MS) techniques. Also, the differentiation and development of MSCs have monitored through culture media metabolome or secretome (secreted metabolites). Totally, 24 potential metabolites were identified. Between them 12 metabolites are unique to BM-MSCs and 5 metabolites are unique to AD-MSCs. Trilineage differentiation including chondrocytes, osteoblasts, and adipocytes, as well as metabolites that are being differentiated, have been shown in different weeks. In the present study, the therapeutic effects of MSCs analyzed by decoding the metabolome for MSCs secretome via metabolic profiling using MALDI-TOF-MS techniques.

Metabolite Profiling of Pig Seminal Plasma Identifies Potential Biomarkers for Sperm Resilience to Liquid Preservation

Metabolomic approaches allow the study of downstream gene expression events since metabolites are considered as the products of cell signaling pathways. For this reason, many studies in humans have already been conducted to determine the influence of the metabolites present in seminal plasma (SP) on sperm physiology, and to identify putative biomarkers. However, in livestock species, these relationships are yet to be uncovered. Thus, the present study aimed to explore: (i) if concentrations of metabolites in pig SP are related to sperm quality and functionality, and (ii) if they could predict the sperm resilience to liquid storage at 17°C. To this end, 28 ejaculates were individually collected and split into three aliquots: one was used for SP analysis through nuclear magnetic resonance (NMR) spectroscopy; another served for the evaluation of sperm concentration and morphology; and the last one was utilized to determine sperm functionality parameters using computer-assisted sperm analysis (CASA) and flow cytometry after 0 h and 72 h of liquid-storage at 17°C. NMR analysis allowed the identification and quantification of 23 metabolites present in pig SP which, except for fumarate, were not observed to follow a breed-dependent behavior. Moreover, specific relationships between metabolites and sperm variables were identified: (i) glutamate, methanol, trimethylamine N-oxide, carnitine, and isoleucine were seen to be related to some sperm quality and functionality parameters evaluated immediately after semen collection; (ii) leucine, hypotaurine, carnitine and isoleucine were found to be associated to the sperm ability to withstand liquid storage; and (iii) Bayesian multiple regression models allowed the identification of metabolite patterns for specific sperm parameters at both 0 h and 72 h. The identification of these relationships opens up the possibility of further investigating these metabolites as potential sperm functional biomarkers.

Maternal age at delivery and fertility of the next generation

BACKGROUND

While most known causes of infertility relate to the health of the woman and/or her partner, questions have been raised regarding the possible contributions of transgenerational or epigenetic factors.

OBJECTIVE

The goal of this hypothesis-generating work was to examine whether Generation 1's (G1's) age at the delivery of G2 (Generation 2) was associated with G2's fertility in later life.

METHODS

We conducted a retrospective cohort study of women (G2s) recruited online in 2016. A questionnaire queried G2s regarding demographics and fertility. The primary exposure was G1's age at G2's birth. Outcome measures included the following: 12-month infertility, time to pregnancy, and childlessness. The adjusted relative risk (RR) of G2 infertility and childlessness by G1 age at G2's birth was estimated through a modified Poisson regression approach. The fecundity odds ratio (FOR) for the association between G1's age at G2 birth and time to pregnancy for G2 was estimated by discrete-time survival models, with complementary log-log link.

RESULTS

A total of 2,854 women enrolled. We found no association between G1 age at G2's birth and G2 infertility. Being born to a G1 aged 15-19 years was associated with a longer time to pregnancy for G2 (FOR 0.84, 95% confidence interval 0.72, 0.99), relative to being born to a G1 aged 20-24 years. We observed the suggestion of a possible increased risk of childlessness among G2s born to older G1s, but the estimate was imprecise.

CONCLUSIONS

While being born to a G1 who was 15-19 years old was associated with an increase in G2 time to pregnancy, we found no association between G1 age at G2's birth and infertility and only the suggestion of a modest association with childlessness. These data suggest a possible subtle effect of G1 age at G2's birth on G2 fertility, which warrants further study.

1H Nuclear Magnetic Resonance of Pig Seminal Plasma Reveals Intra-Ejaculate Variation in Metabolites

In pigs, ejaculate is expelled in fractions, mainly the sperm-rich fraction (SRF) and the post-SRF (PSRF), which differ in both sperm content and origin. In addition, intra-ejaculate variability between fractions in terms of sperm reproductive characteristics has been previously reported, the highest sperm quality being observed in the first 10 mL of the SRF (SRF-P1). As seminal plasma (SP) composition has been purported to influence sperm physiology, the aim of this study was to profile pig SP metabolite composition and to find putative differences between the ejaculate portions (SRF-P1, the rest of SRF [SRF-P2], PSRF) and entire ejaculate (EE). To this end, ejaculates (n = 8, one per boar) were collected in fractions and SP was analyzed using 1H Nuclear Magnetic Resonance spectroscopy. We identified 19 metabolites present in all ejaculate portions and the EE, and reported correlations between the metabolites. Additionally, and for the first time in mammals, we found intra-ejaculate variability in the SP metabolites, observing different relative abundances in choline, glycerophosphocholine and glycine. Regarding their influence in sperm physiology, we hypothesize that these metabolites may explain the specific reproductive characteristics of each ejaculate portion. Finally, the reported SP metabolites could serve as a first steppingstone in the study of quality, functionality, and fertility biomarkers.

Spectral deep learning for prediction and prospective validation of functional groups

State-of-the-art identification of the functional groups present in an unknown chemical entity requires the expertise of a skilled spectroscopist to analyse and interpret Fourier transform infra-red (FTIR), mass spectroscopy (MS) and/or nuclear magnetic resonance (NMR) data. This process can be time-consuming and error-prone, especially for complex chemical entities that are poorly characterised in the literature, or inefficient to use with synthetic robots producing molecules at an accelerated rate. Herein, we introduce a fast, multi-label deep neural network for accurately identifying all the functional groups of unknown compounds using a combination of FTIR and MS spectra. We do not use any database, pre-established rules, procedures, or peak-matching methods. Our trained neural network reveals patterns typically used by human chemists to identify standard groups. Finally, we experimentally validated our neural network, trained on single compounds, to predict functional groups in compound mixtures. Our methodology showcases practical utility for future use in autonomous analytical detection.

[CEP55 may be a potential therapeutic target for non-obstructive azoospermia with maturation arrest]

OBJECTIVE

To explore the effect of small interfering RNA (siRNA)-mediated CEP55 gene silencing on the proliferation of mouse spermatogonia.

METHODS

Six patients with azoospermia diagnosed to have maturation arrest (3 cases) or normal spermatogenesis (3 cases) based on testicular biopsy between January 1 and December 31, 2017 in our center were examined for differential proteins in the testicular tissue using isobaric tags for relative and absolute quantitation (iTRAQ), and CEP55 was found to differentially expressed between the two groups of patients. We constructed a CEP55 siRNA for transfection in mouse spermatogonia and examined the inhibitory effects on CEP55 expressions using Western blotting and qPCR. The effect of CEP55 gene silencing on the proliferation of mouse spermatogonia was evaluated with CCK8 assay.

RESULTS

In the testicular tissues from the 6 patients with azoospermia, iTRAQ combined with LC/MS/MS analysis identified over two hundred differentially expressed proteins, among which CEP55 showed the most significant differential expression between the patients with maturation arrest and those with normal spermatogenesis. The cell transfection experiment showed that compared with the cells transfected with the vehicle or the negative control sequence, the mouse spermatogonia transfected with CEP55 siRNA showed significantly lowered expressions of CEP55 mRNA and protein (P < 0.05) and significantly decreased proliferation rate as shown by CCK8 assay (P < 0.05).

CONCLUSIONS

CEP55 may play a key role in spermatogenesis and may serve as a potential therapeutic target for non-obstructive azoospermia with maturation arrest.

Reactive oxygen species-induced alterations in H19-Igf2 methylation patterns, seminal plasma metabolites, and semen quality

PURPOSE

This study was conducted in order to investigate the effects of reactive oxygen species (ROS) levels on the seminal plasma (SP) metabolite milieu and sperm dysfunction.

METHODS

Semen specimens of 151 normozoospermic men were analyzed for ROS by chemiluminescence and classified according to seminal ROS levels [in relative light units (RLU)/s/106 sperm]: group 1 (n = 39): low (ROS < 20), group 2 (n = 38): mild (20 ≤ ROS < 40), group 3 (n = 31): moderate (40 ≤ ROS < 60), and group 4 (n = 43): high (ROS ≥ 60). A comprehensive analysis of SP and semen parameters, including conventional semen characteristics, measurement of total antioxidant capacity (TAC), sperm DNA fragmentation index (DFI), chromatin maturation index (CMI), H19-Igf2 methylation status, and untargeted seminal metabolic profiling using nuclear magnetic resonance spectroscopy (1H-NMR), was carried out.

RESULT(S)

The methylation status of H19 and Igf2 was significantly different in specimens with high ROS (P < 0.005). Metabolic fingerprinting of these SP samples showed upregulation of trimethylamine N-oxide (P < 0.001) and downregulations of tryptophan (P < 0.05) and tyrosine/tyrosol (P < 0.01). High ROS significantly reduced total sperm motility (P < 0.05), sperm concentration (P < 0.001), and seminal TAC (P < 0.001) but increased CMI and DFI (P < 0.005). ROS levels have a positive correlation with Igf2 methylation (r = 0.19, P < 0.05), DFI (r = 0.40, P < 0.001), CMI (r = 0.39, P < 0.001), and trimethylamine N-oxide (r = 0.45, P < 0.05) and a negative correlation with H19 methylation (r = - 0.20, P < 0.05), tryptophan (r = - 0.45, P < 0.05), sperm motility (r = - 0.20, P < 0.05), sperm viability (r = - 0.23, P < 0.01), and sperm concentration (r = - 0.30, P < 0.001).

CONCLUSION(S)

Results showed significant correlation between ROS levels and H19-Igf2 gene methylation as well as semen parameters. These findings are critical to identify idiopathic male infertility and its management through assisted reproduction technology (ART).

Plasma Metabolomics Analysis Based on GC-MS in Infertile Males with Kidney-Yang Deficiency Syndrome

Introduction

Chinese medicine syndrome diagnosis is the key requisite in the treatment of male infertility with traditional Chinese medicine (TCM). Kidney-Yang deficiency syndrome (KYDS) is the critical Chinese medicine syndrome of male infertility. To explore the modernized mechanisms of KYDS in male infertility, this study aims to investigate the metabolomics of males with KYDS.

Methods

The gas chromatography-mass spectrometry method was applied to analyze the plasma samples of 67 infertile males with KYDS compared with 55 age-matched healthy controls. The chemometric methods including principal component and partial least squares-discriminate analyses were employed to identify the potential biochemical patterns. With the help of the variable importance for the projection and receiver operating characteristic curve analyses, the potential biomarkers were extracted to define the clinical utility. Simultaneously the high-quality KEGG metabolic pathways database was used to identify the related metabolic pathways.

Results

The metabolomics profiles of infertile males with KYDS including 10 potential biomarkers and six metabolic pathways were identified. They precisely distinguished infertile males with KYDS from healthy controls.

Conclusions

These potential biomarkers and pathways suggest the substantial basis of infertile males with KYDS. The metabolomics profiles highlight the modernized mechanisms of infertile males with KYDS.

Livestock metabolomics and the livestock metabolome: A systematic review

Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.