Nuclear Magnetic Resonance Metabolomic Analysis of Spent Human Embryo Culture Media: Method Validation and Technical Considerations

Summary

Here, we present a protocol for collecting, preparing, and analyzing spent human embryo culture medium using nuclear magnetic resonance (NMR) spectroscopy, enabling reproducible detection of low-molecular-weight metabolites from microliter-scale samples under routine clinical culture conditions.

Abstract

Spent human embryo culture media contains low-molecular-weight metabolites that can provide a non-invasive readout of preimplantation embryo physiology. However, nuclear magnetic resonance (NMR)-based metabolomic analysis of these samples is technically challenging because routine embryo culture conditions involve microliter volumes, protein supplementation, and paraffin oil overlays that generate background signals and compromise spectral quality. Here, we present an optimized NMR metabolomics workflow for spent embryo culture media incorporating controlled droplet collection to minimize oil contamination, fluorinated ethylene propylene (FEP) tube liners to chemically isolate the sample from the external reference (TMSP) while accommodating microliter volumes, and acquisition using a Carr-Purcell-Meiboom-Gill pulse sequence to suppress macromolecular background signals. The protocol enables consistent detection and quantification of low-molecular-weight metabolites from individually cultured human embryos and supports reproducible analysis under routine laboratory conditions. Due to numerous technical challenges, the method must be properly validated before it can be used for research or clinical purposes.

Introduction

During preimplantation development in vitro., embryos continuously consume and release low-molecular-weight metabolites into the surrounding medium. The composition of spent embryo culture medium (SECM), therefore, reflects embryo metabolic activity and provides a non-invasive functional readout of embryo physiology and developmental competence^1,2. Analysis of this metabolic footprint may complement conventional assessment methods and improve embryo selection strategies in assisted reproductive technology^3,4. In particular, alterations in amino acid and carbohydrate turnover have been linked to embryo developmental potential and viability^5,6,7.

Nuclear magnetic resonance (NMR) spectroscopy is widely used for untargeted metabolite profiling of diverse biological samples, including spent embryo culture media^8,9,10. However, analysis of these samples remains analytically challenging¹¹. In routine clinical practice, embryos are cultured in defined microenvironments designed to mimic physiological conditions. Culture media are supplemented with proteins, typically albumin, to stabilize osmotic pressure, bind toxic compounds, and provide carrier molecules for lipids and growth factors that support normal development¹². To prevent evaporation and maintain constant solute concentrations, culture droplets are overlaid with sterile paraffin oil¹³.

Lipids originating from overlay oil and protein components generate broad background signals that obscure narrow resonances from low-molecular-weight metabolites such as glucose, pyruvate, and amino acids. Furthermore, analyzing microliter sample volumes in standard 5 mm NMR tubes requires significant dilution to reach the active volume of the RF coil. This reduction in analyte concentration severely diminishes the signal-to-noise ratio (S/N), masking low-abundance metabolites and hindering reproducible quantification. Although numerous studies have applied NMR-based metabolomics to spent human embryo culture media, the lack of standardized and reproducible collection and preparation protocols has limited reproducibility and inter-study comparability^8,9,11.

Here, we present an NMR-based metabolomics workflow (Figure 1) designed to overcome technical challenges associated with sampling and analyzing human embryo culture media. The approach combines controlled droplet collection to reduce oil carryover, microliter-volume acquisition using fluorinated ethylene propylene (FEP) liners to avoid dilution artifacts, and macromolecular signal attenuation using a Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence.

Protocol

This study was conducted between January and April 2023 at the Department of Reproductive Medicine and Gynaecological Endocrinology, University Medical Centre Maribor, Slovenia. NMR analysis was performed at the National Institute of Chemistry in Ljubljana, Slovenia. Written informed consent was obtained from all participants. It received approval from both the Institutional Ethics Committee (No: UKC-MB-KME-1/21) and the National Medical Ethics Committee (No: 0120-37/2021/15).

1. Study design

NOTE: The study analyzed human spent embryo culture media using NMR-based metabolomics.

1. Collect samples after extended embryo culture following intracytoplasmic sperm injection (ICSI). Collect an equal number of unspent incubated control samples.

2. Sample collection

1. Collect spent embryo culture media (SECM) samples following embryo incubation, as illustrated in Figure 2.
2. After removal of the embryo from the culture droplet, carefully aspirate excess overlay oil from the surface of the culture dish without disturbing the medium (Figure 2, step 1).
3. Using a sterile pipette, aspirate approximately 35 µL of culture medium from the original droplet, leaving approximately 5 µL behind to avoid drawing in residual surface oil. Transfer this volume into a sterile Petri dish to form a new droplet (Figure 2, step 2).
4. Under a stereomicroscope, visually inspect the newly formed droplet. Carefully aspirate approximately 30 µL from this droplet, again leaving approximately 5 µL behind to minimize oil carryover. Transfer this volume to a second sterile location to form a cleaner droplet (Figure 2, step 3).
5. Visually inspect the second droplet under magnification. Identify regions where oil droplets are least pronounced. Insert the pipette tip into this region and aspirate approximately 25 µL of medium, again leaving approximately 5 µL behind to minimize oil carryover (Figure 2, step 4).
6. Immediately transfer the collected 25 µL into a sterile, RNase-free microcentrifuge tube. Avoid touching the inner walls of the tube while dispensing the sample to prevent contamination and sample loss. Immediately snap freeze all collected samples in liquid nitrogen and store at -80 °C until NMR analysis (Figure 2, step 5).
7. Collect matched unspent incubated control droplets (medium incubated without embryos) prepared, incubated, and processed under identical culture conditions using the same culture dishes, overlay oil, incubation duration, incubator environment, and handling procedure described above to minimize environmental variability and potential systematic bias.
   NOTE: Strict adherence to sequential droplet transfer and visual inspection significantly reduces oil contamination. At this stage, the experiment may be paused and resumed prior to further sample processing for NMR acquisition.

3. Sample preparation for NMR analysis

1. Thaw samples at room temperature for ~10 min.
2. Prepare NMR mixture:
   1. Transfer 25 µL of SECM into a 1.5 mL microcentrifuge tube. Add 200 µL of D₂O. Vortex it for 10 s and then centrifuge at 1000 × g. for 10 s at room temperature.
3. Load insert: Transfer 225 µL of the mixture into a FEP liner.
4. Prepare the external reference tube.
   1. Fill a 5 mm NMR tube with 150 µL of D₂O containing 1 mM 3-(trimethylsilyl)propionic-2,2,3,3-d4 acid sodium salt (TMSP-d4).
5. Assemble the sample: Insert the FEP insert into the NMR tube and seal with parafilm.

4. NMR acquisition and spectral processing

1. Acquire ¹H-CPMG acquisition using the Bruker cpmgpr1d pulse sequence with: 64 scans; 65,536 data points; Relaxation delay: 8 s; Spectral width: 11.9 kHz; Echo time: 400 µs × 80 loops (effective T₂ filter 32 ms); Total acquisition time: ~15 min.
   NOTE: The effective CPMG T₂ filter duration of 64 ms was selected based on established metabolomics protocols for protein-containing biological samples, where this value provides efficient suppression of macromolecular signals while preserving low-molecular-weight metabolite resonances¹⁴.
2. Perform spectral processing:
   1. Obtain Fourier transform spectra.
   2. Apply 0.3 Hz exponential line broadening.
   3. Perform phase and baseline correction.
   4. Reference spectra to TMSP-d4 at 0 ppm.
   5. Reference chemical shifts (δ) to the external TMSP-d₄ signal at 0 ppm.
      NOTE: Because the sample mixture inside the FEP liner (225 µL) and the external TMSP-d₄ reference solution in the outer coaxial gap (150 µL) occupy distinct physical geometries and volumes within the active NMR coil detection window, their absolute signal intensities do not scale 1:1. Direct absolute quantification using the external reference requires a system-specific geometric calibration curve. Therefore, given the strictly constant sample volumes and highly reproducible pipetting precision of this protocol, raw bucket integrals were utilized directly to track relative metabolic variations between samples, omitting the need for external reference or total sum intensity normalization.
3. Perform spectral binning:
   1. Exclude the water resonance region (e.g., 4.65–5.00 ppm) and the TMSP-d4 reference region (e.g. -0.05–+0.05 ppm) prior to binning.
   2. Divide spectra into variable-width buckets to avoid splitting peaks.
   3. Use raw bucket integrals for statistical analysis rather than normalizing to the external TMSP-d4 signal, as the reference is physically isolated in the outer tube volume. This approach avoids quantification errors stemming from the different active volumes of the insert versus the outer tube.
   4. Export bucket integrals as a numerical data matrix for statistical analysis.
      NOTE: Each "bucket" (or bin) represents the summed numerical integral of all NMR signals within a defined ppm range. While these integrals reflect the relative concentration of the chemical groups present in that range, a single bucket may contain signals from multiple overlapping metabolites or only a portion of a specific metabolite's total signal.

5. Statistical analysis

1. Import processed ¹H-CPMG spectra into Python (v3.12) using nmrglue¹⁵.
2. Remove water and TMSP-d4 spectral regions.
3. Export bucket integrals for analysis.
4. Perform statistical testing using SciPy (v1.14.1):
   1. Assess normality of each spectral bucket using the Shapiro–Wilk test.
   2. Apply one-way ANOVA (for normally distributed data) or Kruskal-Wallis (for non-parametric data) to identify buckets with statistically significant differences between unspent incubated control and spent media.
   3. For buckets showing significant differences, perform structural assignment using a combination of 1D and 2D NMR experiments: ¹H-¹³C HSQC, ¹H-¹³C HMBC, and ¹H-¹H COSY.
   4. Compare the observed 2D correlations against standard databases (e.g., HMDB) to verify the identity of the metabolites contributing to the discriminatory buckets.

Results

The analytical workflow for untargeted NMR metabolomic profiling of spent embryo culture medium is summarized in Figure 1.

Removal of oil contamination during sampling
Figure 2 illustrates the sequential droplet transfer procedure used to reduce overlay oil carryover. Samples collected without careful pipetting exhibited broad hydrocarbon resonances spanning the aliphatic region of the spectrum (δ 0.5–2.3 ppm), resulting in substantial baseline distortion and obscuring low-molecular-weight metabolite signals (Figure 3A, green trace). In contrast, samples collected using the optimized sequential droplet transfer protocol showed near-complete elimination of detectable paraffin oil contamination, restoring baseline stability and revealing well-resolved metabolite resonances throughout the spectral region of interest (Figure 3B, black trace). Notably, the broad hydrocarbon envelope characteristic of paraffin oil contamination was effectively eliminated, indicating that sequential droplet transfer reduced residual oil contamination to below the practical limit of spectral detection and thereby enabled reliable downstream metabolite quantification.

Suppression of macromolecular background signals
Figure 4 presents suppression of protein-derived signals using two different approaches. Ultrafiltration (Figure 4A) reduced broad protein-derived signals but also decreased overall signal intensity. The ¹H-CPMG experiment (Figure 4B) removed broad resonances originating from proteins while preserving narrow metabolite peaks, improving spectral resolution and enabling identification of low-molecular-weight compounds.

FEP insert for sample Isolation and volume optimization
Figure 5 illustrates the high-quality spectra acquired from sequential media using the FEP liner. Unlike standard tubes, this setup enables high-resolution acquisition from microliter volumes while physically isolating the sample from the external reference (D₂O and TMSP). This dual-chamber approach ensures that the media remains chemically pristine while providing a stable lock and reference signal. As shown, the spectra exhibit uniform line shapes, stable baselines, and well-resolved resonances across both the aliphatic (0.9-4.3 ppm) and aromatic (6.8–8.6 ppm) regions, confirming that the FEP barrier does not compromise magnetic field homogeneity or spectral clarity.

Representative statistical workflow and validation of metabolite identification
To identify potential metabolic biomarkers of embryo development, a standardized statistical pipeline was applied to all integrated spectral buckets. This methodology is demonstrated through the analysis of the methyl resonance of Alanine (Figure 6), which serves as a representative case for the processed metabolites. The workflow initiates with the segmentation of raw ¹H NMR signals into discrete regions (Figure 6A), where the integrated area of the unspent incubated control (black) is compared against the spent culture media (red). To determine the appropriate statistical framework, the distribution of each bucket integral was assessed using the Shapiro–Wilk test. Given that the majority of the metabolite signals (including alanine) exhibited a non-normal distribution, the non-parametric Kruskal-Wallis test was employed to evaluate differences between experimental groups. As illustrated in the representative box plot (Figure 6B), this approach facilitates the identification of statistically significant metabolite changes between unspent incubated controls and spent culture media, as demonstrated by the increased alanine signal observed (secretion) following embryo culture. Signals in buckets demonstrating a significance level of p < 0.01 (indicated by double asterisks) were subsequently prioritized for biological interpretation and structural verification via 2D NMR spectroscopy.

To further assess the analytical reproducibility of the FEP-liner acquisition setup, alanine standard solutions spanning concentrations representative of native and low-abundance embryo-derived metabolites were analyzed in five consecutive replicate measurements. The intra-day coefficient of variation (%CV) was 0.22% at 1.000 mM, 0.34% at 0.090 mM, 0.55% at 0.039 mM, and 4.95% at 0.019 mM. Although relative variance increased at lower concentrations due to reduced signal-to-noise ratios, all measurements remained below the commonly accepted 10% threshold for analytical reproducibility, demonstrating robust signal stability across the concentration range relevant to SECM metabolomic analysis.

Metabolite uptake is demonstrated in Figure 6C, where pyruvate exhibited significantly lower signal intensity in spent culture media than in unspent incubated controls, consistent with net pyruvate consumption by the developing embryo. Together, the alanine and pyruvate examples demonstrate the ability of the proposed workflow to detect both metabolite release and metabolite uptake through comparison of spent and control culture media.

Figure 1: Workflow for NMR-based untargeted metabolomic profiling of spent embryo culture medium. The analytical workflow includes preparation of spent culture medium in D₂O buffer, NMR data acquisition, spectral processing and metabolite assignment, and downstream statistical analysis. Please click here to view a larger version of this figure.

Figure 2: Sequential sampling of spent embryo culture medium. After embryo removal, excess overlay oil is aspirated from the culture dish surface (step 1). Culture medium is transferred from the original droplet to a new location to form a secondary droplet (step 2), followed by a second transfer to further reduce oil carryover (step 3). A final aspiration is performed from the region with minimal visible oil contamination (step 4). The sample is dispensed into an RNase-free microcentrifuge tube and immediately snap-frozen for downstream analysis (step 5). Please click here to view a larger version of this figure.

Figure 3: Technical validation of paraffin oil removal efficiency. Comparative overlay of 1 H NMR spectra demonstrating the efficacy of the optimized droplet transfer protocol. (A) Green spectrum: incubated culture media collected via unoptimized manual pipetting, showing severe contamination from the paraffin oil overlay. The broad, intense alkane hydrocarbon signals (δ 0.5–2.3 ppm) create baseline distortions and mask crucial metabolite peaks. (B) Black spectrum: incubated culture media processed using the optimized sequential droplet transfer pipeline. The oil contamination is reduced below the limit of detection, successfully revealing the sharp, quantifiable resonances of small-molecule metabolites across the entire aliphatic region. The vertical intensity scale in this figure panel has been intentionally increased to permit clear visualization of low-abundance small-molecule metabolites, resulting in the expected truncation of high-intensity dominant peaks. Please click here to view a larger version of this figure.

Figure 4: Suppression of macromolecular signals in 1D ¹H NMR spectra of culture medium. (A) Comparison of spectra acquired from non-filtered (pink) and ultrafiltered (green) samples, demonstrating reduction of broad protein-derived resonances after ultrafiltration. (B) Comparison of standard 1D ¹H NOESYPR1D spectrum (pink) and 1D ¹H CPMG spectrum (green), showing attenuation of macromolecular signals and improved resolution of metabolite peaks. The vertical intensity scale in this figure panel has been intentionally increased to permit clear visualization of low-abundance small-molecule metabolites, resulting in the expected truncation of high-intensity dominant peaks. Please click here to view a larger version of this figure.

Figure 5: Use of a FEP liner insert for acquisition of 1D ¹H CPMG NMR spectra of culture medium samples. (A,B) Representative spectral regions obtained from two culture media samples (G1, blue; G2, red) measured using a FEP insert, showing metabolite resonances in the aliphatic (0.9–4.3 ppm) and aromatic (6.8–8.6 ppm) regions. The photograph shows the FEP insert placed inside a standard 5 mm NMR tube. The vertical intensity scale in this figure panel has been intentionally increased to permit clear visualization of low-abundance small-molecule metabolites, resulting in the expected truncation of high-intensity dominant peaks. Please click here to view a larger version of this figure.

Figure 6: Representative workflow for metabolite quantification and statistical validation. (A) Spectral expansion of the methyl region (1.42–1.50 ppm). The overlay displays the ¹H NMR traces for the unspent incubated control medium (black) and the spent culture medium (red). The vertical black lines indicate the bucketed region used for numerical integration of the signal. The increased alanine signal intensity observed in spent culture medium indicates net alanine secretion by the embryo. (B) Relative quantitative comparison of the bucket integrals for the region shown in (A). The box plot represents the distribution of the integrated values for the control and spent media groups. Following the assessment of the data distribution via the Shapiro-Wilk test, the Kruskal-Wallis test was applied to compare the groups. Double asterisks (**) indicate a statistical significance of p < 0.01. (C) Relative quantitative comparison of pyruvate bucket integrals. The box plot represents the distribution of integrated pyruvate signals in unspent incubated controls (green) and spent culture media (blue). The significantly lower pyruvate signal observed in spent culture media is consistent with net pyruvate uptake by the embryo. Double asterisks (**) indicate statistical significance of p < 0.01. Please click here to view a larger version of this figure.

Discussion

In this study, we addressed key analytical challenges associated with identifying and quantifying low-molecular-weight metabolites in spent embryo culture media using untargeted NMR metabolomics. Our results show that the optimized workflow enables acquisition of high-quality, information-rich spectra suitable for reliable detection of low-molecular-weight metabolites.

Careful sequential droplet transfer proved essential for reducing oil contamination, which otherwise generated broad resonances that masked low-molecular-weight metabolite signals of interest. Comparison of spectra acquired before and after implementation of the optimized sampling procedure demonstrated near-complete elimination of detectable paraffin oil signals, effectively removing the broad hydrocarbon background that obscured metabolite resonances. Macromolecular interference, primarily originating from albumin proteins, further limited reliable spectral interpretation. The CPMG pulse sequence, implemented using a literature-validated effective T₂ filter duration of 64 ms, selectively suppressed macromolecular resonances while preserving narrow metabolite peaks and was therefore superior to physical removal approaches such as ultrafiltration, which reduced background signals but also attenuated metabolite intensity.

We further demonstrate that FEP tube liners are highly suitable for microliter-scale NMR measurements. This setup confines the sample within the active detection volume of the NMR coil, thereby minimizing the dilution otherwise required to achieve the necessary filling height in standard 5 mm tubes. Although a small volume of D2O is still added to ensure a stable lock and eliminate air-sample interfaces within the liner, the final metabolite concentration remains substantially higher than in conventional tube-based acquisition. Furthermore, the use of the coaxial arrangement effectively isolates the sample from the TMSP reference signal located in the outer chamber. This prevents the external standard from interacting with the culture media, preserving the chemical integrity of the embryo metabolic footprint while maintaining a robust signal for chemical shift referencing.

Following protocol optimization, the improved spectral consistency facilitated robust statistical comparisons. Low variability in the concentrations of individual components within the control medium and deviations in the concentrations of certain metabolites in spent culture media serve as validation of the sensitivity of this analytical method. This is clearly demonstrated by the significant increase in alanine concentration, which served as a representative marker for embryo-derived alterations in the culture microenvironment. Thus, the consistent detection of metabolite uptake and release, particularly among amino acids and carbohydrates, demonstrates that the workflow reliably captures biologically meaningful metabolic activity.

Furthermore, the low intra-day coefficients of variation observed across the alanine concentration series further support the analytical reproducibility of the FEP-liner configuration and indicate that observed differences between samples are unlikely to arise from instrumental instability.

Despite technical advances, translation of embryo metabolomics into routine clinical decision-making remains limited. Currently, metabolomic profiling appears more valuable for characterizing embryo physiology and the biochemical microenvironment than for directly improving clinical ART outcomes. As noted in a recent systematic review, metabolomic approaches have not yet consistently improved implantation or live-birth rates. This gap is largely attributed to technical heterogeneity and the absence of standardized, high-resolution preparation protocols¹⁶. The optimized FEP-liner workflow presented here addresses several of these technical limitations by providing a reproducible method for analyzing microliter-scale samples without compromising signal quality or sample purity.

Metabolomic studies of human embryo culture media employ heterogeneous experimental designs and various analytical tools, thereby introducing substantial methodological heterogeneity and complicating comparability across studies^8,9,17,18,19. Some investigations compare groups of embryos based on developmental progression⁸, whereas others evaluate individual embryos and relate metabolic profiles to implantation or live-birth outcomes^9,11. Sampling strategies also differ considerably: certain studies collect media only at one single time point in development, usually at the end of culture^8,9,17,19, while others perform repeated sampling across developmental stages¹¹. Some studies focus only on samples derived from embryos that were clinically usable, discarding morphologically arrested embryos, which might still be metabolically active^9,11,18,19. Morphological arrest does not necessarily indicate metabolic inactivity, as arrested embryos may still contain viable, metabolically active blastomeres²⁰. Excluding these embryos introduces selection bias and removes important stress-related metabolic variation, potentially leading to misleading or weakened metabolomic associations.

Several analytical platforms have been applied to the metabolomic analysis of SECM, including spectroscopy-based techniques such as nuclear magnetic resonance (NMR)^8,9,10,11, Raman spectroscopy²¹, near-infrared spectroscopy (NIR)²², and Fourier transform infrared (FTIR) spectroscopy²³, as well as chromatography-based and mass spectrometry (MS)-based approaches, including liquid chromatography–mass spectrometry (LC-MS)¹⁸, liquid chromatography–tandem mass spectrometry (LC-MS/MS)²⁴ and gas chromatography–mass spectrometry (GC-MS)¹⁷. Recent reviews and meta-analyses have highlighted that each analytical platform offers distinct advantages and limitations depending on the analytical objectives and the metabolite classes of interest^25,26.

MS-based techniques generally provide superior sensitivity and broader metabolite coverage, enabling the detection of low-abundance metabolites and comprehensive profiling of complex biological samples²⁷. In particular, LC-MS/MS facilitates the discrimination of structurally related compounds through tandem mass spectrometric analysis and is widely used for both targeted and untargeted metabolomics workflows. GC-MS provides excellent analytical performance for volatile and derivatized metabolites, whereas Raman and NIR spectroscopy offer rapid analysis with minimal sample preparation but provide more limited metabolite specificity and structural information²⁶.

In contrast, NMR spectroscopy offers several advantages that are particularly relevant for SECM analysis, including excellent reproducibility, minimal sample preparation, non-destructive measurement, and robust structural elucidation capabilities. Importantly, NMR enables inherently quantitative analysis without requiring compound-specific calibration standards. Under standardized experimental conditions, signal integrals obtained from NMR spectra can be directly related to metabolite concentrations within complex biological mixtures. Although NMR is intrinsically less sensitive than MS-based approaches, with detection limits typically in the micromolar range, and exhibits a more limited dynamic range, its high analytical robustness, quantitative reliability, and inter-laboratory reproducibility make it a valuable platform for standardized metabolomic characterization of SECM²⁸. The present workflow is primarily optimized for the detection and quantification of higher-abundance low-molecular-weight metabolites.

General limitations inherent to metabolomic analyses should also be considered. The metabolome is highly dynamic and spans an extremely wide concentration range, from abundant nutrients to trace signalling molecules. As a result, no single analytical platform can comprehensively detect all metabolites²⁹. In addition, metabolomic measurements may be influenced by pre-analytical variables, including prolonged storage, improper handling, repeated freeze–thaw cycles, and sample degradation, all of which may compromise metabolite stability and confound metabolomic interpretation^30,31. In the present study, all samples were immediately snap-frozen in liquid nitrogen and stored at -80 °C until analysis to minimize metabolite degradation. Although long-term sample stability was not systematically evaluated, rapid metabolic quenching followed by ultra-low-temperature storage and minimization of freeze–thaw cycles is widely recommended to reduce pre-analytical variability and preserve metabolite integrity in metabolomics workflows³². In addition, current metabolomic annotation remains incomplete, and combined targeted and untargeted approaches are estimated to confidently identify only a small fraction of the human metabolome³³.

Nevertheless, reproducible analytical workflows such as the one presented in this study are essential for advancing research in embryo metabolomics. By implementing a coaxial FEP-liner workflow that maximizes signal-to-noise ratio through minimized dilution and ensures sample purity via reference isolation, this approach addresses the critical need for technical standardization in NMR-based metabolomic analysis of SECM. While the method is primarily optimized for the detection of higher-abundance low-molecular-weight metabolites and does not replace the sensitivity and metabolite coverage achievable with MS-based platforms, such standardization has the potential to reduce inter-study heterogeneity and improve comparability of metabolomic data across laboratories. Consequently, this workflow may facilitate future integrative studies combining NMR with complementary analytical platforms, including MS-based and spectroscopic techniques, as well as other multi-omics approaches, to achieve a more comprehensive understanding of the relationship between embryo metabolism and developmental competence in assisted reproductive technology.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
5 mm FEP tube liner	SP Wilmad-LabGlass	4682701	Inner insert for coaxial NMR
5 mm NMR tube	SP Wilmad-LabGlass	535-PP-7-SB	Outer tube
6-well culture plate	Oosafe	OOPW-SW02	Embryo culture dish
Cryogenic liquid nitrogen	Messer	Contact manufacturer	Sample snap-freezing
Deuterium oxide (D2O)	Eurisotop	D214L	NMR solvent
Micropipette (10–100 µL)	Eppendorf	4924000053	Adjustable volume pipette
Microcentrifuge tubes, 1.5 mL, RNase-free	Eppendorf	N216966N	Sample collection and storage
Mineral oil	Vitrolife	VTL-10029	Culture droplet overlay
NMR spectrometer, 600 MHz	Bruker	https://www.bruker.com/en/products-and-solutions/mr/nmr/avance-nmr-spectrometer.html	Spectral acquisition
Pasteur pipette	Falcon	FAL-357575	Droplet transfer
Pipette, single-channel mechanical	Sartorius	728060	Sample handling
Pipette tips, sterile	Eppendorf	22491148	Compatible with micropipette
Pipette tips, sterile filter	Sartorius	790201F	Aerosol barrier
Sequential G-series culture media	Vitrolife	VTL-10143	Embryo culture medium
TMSP-d4 (sodium 3-trimethylsilylpropionate-d4)	Cambridge Isotope Laboratories	DLM-48-1	Chemical shift reference
Tubes, Safe-Lock	Eppendorf	0030121589	Storage tubes