The utility of nuclear magnetic resonance spectroscopy in assisted reproduction

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.

Pre-Implantation Bovine Embryo Evaluation-From Optics to Omics and Beyond

Approximately 80% of the ~1.5 million bovine embryos transferred in 2021 were in vitro produced. However, only ~27% of the transferred IVP embryos will result in live births. The ~73% pregnancy failures are partly due to transferring poor-quality embryos, a result of erroneous stereomicroscopy-based morphological evaluation, the current method of choice for pre-transfer embryo evaluation. Numerous microscopic (e.g., differential interference contrast, electron, fluorescent, time-lapse, and artificial-intelligence-based microscopy) and non-microscopic (e.g., genomics, transcriptomics, epigenomics, proteomics, metabolomics, and nuclear magnetic resonance) methodologies have been tested to find an embryo evaluation technique that is superior to morphologic evaluation. Many of these research tools can accurately determine embryo quality/viability; however, most are invasive, expensive, laborious, technically sophisticated, and/or time-consuming, making them futile in the context of in-field embryo evaluation. However accurate they may be, using complex methods, such as RNA sequencing, SNP chips, mass spectrometry, and multiphoton microscopy, at thousands of embryo production/collection facilities is impractical. Therefore, future research is warranted to innovate field-friendly, simple benchtop tests using findings already available, particularly from omics-based research methodologies. Time-lapse monitoring and artificial-intelligence-based automated image analysis also have the potential for accurate embryo evaluation; however, further research is warranted to innovate economically feasible options for in-field applications.

Nontargeted metabolomics analysis of follicular fluid in patients with endometriosis provides a new direction for the study of oocyte quality

Endometriosis is a common, estrogen-dependent chronic gynecological disease that endangers the reproductive system and systemic metabolism of patients. We aimed to investigate the differences in metabolic profiles in the follicular fluid between infertile patients with endometriosis and controls. A total of 25 infertile patients with endometriosis and 25 infertile controls who were similar in age, BMI, fertilization method and ovulation induction treatment were recruited in this study. Metabolomics analysis of follicular fluid was performed by two methods of high-performance liquid chromatography tandem mass spectrometry. There were 36 upregulated and 17 downregulated metabolites in the follicular fluid of patients in the endometriosis group. KEGG pathway analysis revealed that these metabolites were enriched in phenylalanine, tyrosine and tryptophan biosynthesis, aminoacyl-tRNA biosynthesis, phenylalanine metabolism and pyrimidine metabolism pathways. A biomarker panel consisting of 20 metabolites was constructed by random forest, with an accuracy of 0.946 and an AUC of 0.988. This study characterizes differences in follicular fluid metabolites and associated pathway profiles in infertile patients with endometriosis. These findings can provide a better comprehensive understanding of the disease and a new direction for the study of oocyte quality, as well as potential metabolic markers for the prognosis of endometriosis.

Combining Machine Learning with Metabolomic and Embryologic Data Improves Embryo Implantation Prediction

This study investigated whether combining metabolomic and embryologic data with machine learning (ML) models improve the prediction of embryo implantation potential. In this prospective cohort study, infertile couples (n=56) undergoing day-5 single blastocyst transfer between February 2019 and August 2021 were included. After day-5 single blastocyst transfer, spent culture medium (SCM) was subjected to metabolite analysis using nuclear magnetic resonance (NMR) spectroscopy. Derived metabolite levels and embryologic parameters between successfully implanted and failed groups were incorporated into ML models to explore their predictive potential regarding embryo implantation. The SCM of blastocysts that resulted in successful embryo implantation had significantly lower pyruvate (p<0.05) and threonine (p<0.05) levels compared to medium control but not compared to SCM related to embryos that failed to implant. Notably, the prediction accuracy increased when classical ML algorithms were combined with metabolomic and embryologic data. Specifically, the custom artificial neural network (ANN) model with regularized parameters for metabolomic data provided 100% accuracy, indicating the efficiency in predicting implantation potential. Hence, combining ML models (specifically, custom ANN) with metabolomic and embryologic data improves the prediction of embryo implantation potential. The approach could potentially be used to derive clinical benefits for patients in real-time.

V, Joseph D, Meitei HY, Asampille G, Kumar P, Gowda G. A. N, Kalthur G, Kovacic B, Adiga SK. ICSI in non-male factor infertility patients does not alter metabolomic signature in sibling embryos as evidenced by sensitivity enhanced nuclear magnetic resonance (NMR) spectroscopy

Intracytoplasmic sperm injection (ICSI) was developed to overcome male factor infertility, however, there recently has been an increasing trend in ICSI usage irrespective of the etiology, demonstrating an overuse of this insemination technique. There is a limited knowledge on the behaviour of ICSI derived embryos in non-male factor infertility patients. Metabolomic assessment of preimplantation embryos in conjunction with morphological evaluation can provide better understanding of embryonic behaviour. Hence, this study was undertaken to explore if there are any metabolomic differences between IVF and ICSI derived sibling day-5 blastocysts from non-male factor infertility patients. This prospective study included nineteen couples with non-male factor infertility undergoing Assisted Reproductive Technology. The sibling oocytes retrieved from each patient were randomly assigned to two groups and inseminated either by IVF or ICSI. Spent culture media (SCM) in which embryos were cultured up to day 5 were collected and investigated using sensitivity enhanced NMR based metabolite profiling utilizing high resolution (800 MHz) NMR equipped with cryogenically cooled micro-coil (1.7 mm) probe. The metabolomic signature between IVF and ICSI derived sibling blastocysts was assessed. A significant reduction in the concentrations of pyruvate, citrate, glucose and lysine were observed in both IVF and ICSI sibling embryos compared to medium control (P< 0.05-0.001). Further, histidine and valine level was found lower in ICSI embryos compared to medium control (P<0.05) during 96 hours of in vitro culture. Notably, between IVF and ICSI SCM, no significant difference in the concentration of the metabolites was found. Our results suggest that ICSI in non-male factor does not alter the SCM metabolomic signature during 96 hours of embryonic development.

Are the Follicular Fluid Characteristics of Recovered Coronavirus Disease 2019 Patients Different From Those of Vaccinated Women Approaching in vitro Fertilization?

The aim of this pilot study is to evaluate if SARS-CoV-2 infection or vaccination against SARS-CoV-2 infection induce observable metabolic effects in follicular fluid of women who are following in vitro fertilization (IVF) treatments. The possible impact of coronavirus disease 2019 (COVID-19) on fertility and IVF outcome is considered. We have selected for this study: six women vaccinated against SARS-CoV-2 infection, five recovered COVID-19 patients, and we used nine healthy women as the control group. At the time of oocytes retrieval from participants in the study, follicular fluids were collected and metabolomic analysis was performed by ¹H NMR spectroscopy in combination with multivariate analysis to interpret the spectral data. The search for antibody positivity in the follicular fluid aspirates was also carried out, together with the western blotting analysis of some inflammatory proteins, interleukin-6, tumor necrosis factor α (TNFα), and the free radical scavenger superoxide dismutase 2. Higher levels of Ala and Pro together with lower levels of lipids and trimethylamine N-oxide (TMAO) were found in follicular fluids (FFs) of vaccinated women while lower levels of many metabolites were detected in FFs of recovered COVID patients. Expression level of TNF-α was significantly lower both in recovered COVID-19 patients and vaccinated women in comparison to healthy controls.

Why Has Metabolomics So Far Not Managed to Efficiently Contribute to the Improvement of Assisted Reproduction Outcomes? The Answer through a Review of the Best Available Current Evidence

Metabolomics emerged to give clinicians the necessary information on the competence, in terms of physiology and function, of gametes, embryos, and the endometrium towards a targeted infertility treatment, namely, assisted reproduction techniques (ART). Our minireview aims to investigate the current status of the use of metabolomics in assisted reproduction, the potential flaws in its use, and to propose specific solutions towards the improvement of ART outcomes through the use of the intervention. We used published reports assessing the role of metabolomic investigation of the endometrium, oocytes, and embryos in improving clinical outcomes in women undergoing ART. We initially found that there is no evidence to support that fertility outcomes can be improved through metabolomics profiling. In contrast, it may be helpful for understanding and appraising the nutritional environment of oocytes and embryos. The causes include the different infertility populations, the difference between animals and humans, technical limitations, and the great heterogeneity in the variables employed. Suggested steps include the standardization of variables of the method itself, the universal creation of a panel where all biomarkers are stored concerning specific infertile populations with different phenotypes or etiologies, specific bioinformatics contribution, significant computing power for data processing, and importantly, properly conducted trials.

Sperm Metabolomics through Nuclear Magnetic Resonance Spectroscopy

Simple Summary

Proton nuclear magnetic resonance spectroscopy (¹ H-NMR) is of special interest for the analysis of metabolites present in seminal plasma and spermatozoa. This metabolomic approach has been used to identify the presence of new biomarkers or their proportions in a non-invasive manner and is, therefore, an interesting tool for male fertility diagnosis. In this paper, we review current knowledge of the use of ¹ H-NMR to examine sperm metabolomics in different species with special attention paid to humans and farm animals. We also describe the use of ¹ H-NMR to establish a possible relationship between the mammalian diet and the presence of certain hydrophilic and lipophilic metabolites in spermatozoa.

Abstract

This report reviews current knowledge of sperm metabolomics analysis using proton nuclear magnetic resonance spectroscopy (¹ H-NMR) with particular emphasis on human and farm animals. First, we present the benefits of NMR over other techniques to identify sperm metabolites and then describe the specific methodology required for NMR sperm analysis, stressing the importance of analyzing metabolites extracted from both the hydrophilic and lipophilic phases. This is followed by a description of advances produced to date in the use of NMR to diagnose infertility in humans and to identify metabolic differences among the sperm of mammalian herbivore, carnivore, and omnivore species. This last application of NMR mainly seeks to explore the possible use of lipids to fuel sperm physiology, contrary to previous theories that glycolysis and oxidative phosphorylation (OXPHOS) are the only sources of sperm energy. This review describes the use of NMR to identify sperm and seminal plasma metabolites as possible indicators of semen quality, and to examine the metabolites needed to maintain sperm motility, induce their capacitation, and consequently, to predict animal fertility.

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.