Sulfur Isotope Measurement in Human Serum

Importance of the Topic

The analysis of sulfur isotope ratios in human biological fluids provides unique insights into metabolic pathways, disease mechanisms, and nutritional status. Traditional EA-IRMS methods require milligram quantities of sulfur and can suffer interference and combustion issues when analyzing complex matrices such as serum or plasma. The introduction of multicollector inductively coupled plasma mass spectrometry (MC-ICP-MS) in high-resolution mode allows precise measurement of 34S/32S and 33S/32S ratios with nanogram-level samples, opening new possibilities for biomedical and clinical applications.

Study Objectives and Overview

This application note evaluates the feasibility, accuracy, and precision of MC-ICP-MS for sulfur isotope measurement in human serum and plasma. Key aims include:

• Comparing MC-ICP-MS performance with conventional EA-IRMS.
• Validating the method using IAEA reference materials (S1, S2, S3, S4).
• Measuring sulfur isotope compositions in small volumes (≈200 μL) of human serum, plasma, free-sulfur fractions, and cell-membrane extracts.
• Assessing the potential to couple sulfur isotope analysis with Cu, Zn, and Fe separations on a single sample aliquot.

Methodology and Instrumentation

Samples of human serum and plasma were digested in HNO₃/H₂O₂ at 130 °C, oxidized thoroughly, and subjected to a single-column anion-exchange purification (AG1-X8 resin). Sulfur was eluted in 0.5 N HNO₃ with a recovery of 98 ± 2% and procedural blank of ~15 ng S. Prior to analysis, Suprapur™ ammonia was added to balance sulfate charge and improve transmission through the Cetac Aridus II desolvator.

Instrumentation

• Thermo Scientific™ Neptune Plus™ MC-ICP-MS operated in high-resolution mode (R ≈ 9 000)
• Cetac Aridus II desolvator: spray chamber at 110 °C, membrane at 160 °C
• Standard cones; Jet cones tested for low-S samples yielding 20 V/ppm sensitivity
• Measurement parameters: 40 cycles, 4 s integration, on-peak zero background correction, sample-standard bracketing

Main Results and Discussion

Reproducibility for δ34S and δ33S on Alfa Aesar standard (8 mg/L S) was ±0.10‰ and ±0.15‰ (2σ), matching EA-IRMS precision while requiring 10²−10³ times less sulfur. Jet cones further reduced sample requirement to 12 nmol S (0.375 μg). Isotope ratios for IAEA S1–S4 agreed within uncertainty with published values. Analysis of two healthy donors showed:

• Whole serum and plasma δ34S values of 5–6‰ (V-CDT)
• Free-sulfur (low-molecular weight) and red-cell membrane fractions enriched in light isotopes relative to bulk fluid
• Minimal isotopic bias introduced by combined Cu, Zn, Fe, and S chemical separations

Correlation of 33S/32S vs. 34S/32S slopes (0.5073) confirms mass-dependent fractionation and effective interference removal.

Benefits and Practical Applications

The MC-ICP-MS method enables:

• High-precision sulfur isotope analysis on microliter-scale biological samples
• Simultaneous isotopic studies of multiple trace elements (Fe, Cu, Zn, S) on one aliquot
• Investigation of isotopic fractionation in metabolic, nutritional, and disease contexts
• High throughput (≈48 samples/12 h) with low blank and minimal sample prep

Future Trends and Opportunities

Advances in sensitivity and automation will allow sulfur isotope analysis on cell cultures, organ extracts, and even subcellular fractions. Integration with clinical workflows could yield diagnostic biomarkers based on sulfur metabolism. Coupled multi-isotope tracer studies (S, Fe, Cu, Zn) promise deeper insight into metallobiology, oxidative stress, and nutrient assimilation. Further miniaturization and desolvation improvements will expand applications in proteomics and metabolomics.

Conclusion

This work demonstrates that high-resolution MC-ICP-MS offers a robust, sensitive, and precise alternative to EA-IRMS for sulfur isotope measurements in human serum, plasma, and derived fractions. The low sample requirement and compatibility with multi-element separations position this method as a powerful tool for biomedical research and clinical diagnostics.

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