Why Multiple Biopsies Using the Stable Tracer Deuterium May Be a Misstep

In recent decades, considerable focus has been placed on ways to measure muscle protein turnover in humans. The use of deuterium oxide (D 2 O) as a stable tracer has allowed measurements of rates of protein synthesis in free-living humans over days to weeks. While D 2 O labeling is a powerful tool for measuring protein turnover in complex and heterogeneous tissues like skeletal muscle, its use still must adhere to basic tracer principles. In studies using isotope-labeled amino acids for protein synthesis repeated biopsies were used to examine responses over time. Thus, this same approach was adopted for studies using D 2 O to measure protein synthesis over time or in response to an intervention. We have contended that repeated muscle biopsies are not appropriate for comparing synthesis rates when using D 2 O labeling. Thus, we hypothesized that the timing of biopsies and period of D 2 O labeling impacts protein synthesis rates in a way that invalidates comparisons of repeated biopsies. To test this hypothesis, we used multi-timepoint D 2 O labeling followed by proteomic analysis by data independent acquisition (DIA) on LC-MS/MS. We used 23 month-old male C57Bl/6 mice (n=3/timepoint) control mice or mice with heart failure with preserved ejection fraction (HFpEF) using an established two-hit model. We then determined the contribution of the synthesis rates of individual proteins to a cumulative synthesis rate at each time point. This analysis showed that the cumulative synthesis rates at early time points was largely determined by rapidly-synthesized proteins. As the time course became more prolonged, the synthesis rates of the rapidly synthesized proteins saturated while slowly synthesized proteins had increasing representation. The differences between early and later sampling times demonstrate that the proteins represented in the synthesis rates of a “pre” and a “post” biopsy would be representative of different pools of proteins. Therefore, repeated biopsies lead to conclusions based on different proteins rather than the changes occurring because of a treatment or intervention. By demonstrating this biologically and mathematically, we hope we can encourage researchers to consider this concept carefully when planning studies and interpreting previous results. This work was supported by: AHA Postdoctoral Fellowship 23POST1012408 (K.A.K) Oklahoma Center for Adult Stem Cell Research (OCASCR) Research Grant (Y.A.C). This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

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Journal
Physiology
Published
2025-05-01
DOI
https://doi.org/10.1152/physiol.2025.40.s1.1605
Primary Topic
Cancer Genomics and Diagnostics
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article
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article

Why Multiple Biopsies Using the Stable Tracer Deuterium May Be a Misstep

Ying Ann Chiao, Benjamin F. Miller, Mike Taylor, Rovshan G. Sadygov et al.
Physiology
Cancer Genomics and Diagnostics
article

Why Multiple Biopsies Using the Stable Tracer Deuterium May Be a Misstep

Ying Ann Chiao, Benjamin F. Miller, Mike Taylor, Rovshan G. Sadygov, Colleen L. O’Reilly, Michael T Kinter, Kamil Kobak
article en

Abstract

In recent decades, considerable focus has been placed on ways to measure muscle protein turnover in humans. The use of deuterium oxide (D 2 O) as a stable tracer has allowed measurements of rates of protein synthesis in free-living humans over days to weeks. While D 2 O labeling is a powerful tool for measuring protein turnover in complex and heterogeneous tissues like skeletal muscle, its use still must adhere to basic tracer principles. In studies using isotope-labeled amino acids for protein synthesis repeated biopsies were used to examine responses over time. Thus, this same approach was adopted for studies using D 2 O to measure protein synthesis over time or in response to an intervention. We have contended that repeated muscle biopsies are not appropriate for comparing synthesis rates when using D 2 O labeling. Thus, we hypothesized that the timing of biopsies and period of D 2 O labeling impacts protein synthesis rates in a way that invalidates comparisons of repeated biopsies. To test this hypothesis, we used multi-timepoint D 2 O labeling followed by proteomic analysis by data independent acquisition (DIA) on LC-MS/MS. We used 23 month-old male C57Bl/6 mice (n=3/timepoint) control mice or mice with heart failure with preserved ejection fraction (HFpEF) using an established two-hit model. We then determined the contribution of the synthesis rates of individual proteins to a cumulative synthesis rate at each time point. This analysis showed that the cumulative synthesis rates at early time points was largely determined by rapidly-synthesized proteins. As the time course became more prolonged, the synthesis rates of the rapidly synthesized proteins saturated while slowly synthesized proteins had increasing representation. The differences between early and later sampling times demonstrate that the proteins represented in the synthesis rates of a “pre” and a “post” biopsy would be representative of different pools of proteins. Therefore, repeated biopsies lead to conclusions based on different proteins rather than the changes occurring because of a treatment or intervention. By demonstrating this biologically and mathematically, we hope we can encourage researchers to consider this concept carefully when planning studies and interpreting previous results. This work was supported by: AHA Postdoctoral Fellowship 23POST1012408 (K.A.K) Oklahoma Center for Adult Stem Cell Research (OCASCR) Research Grant (Y.A.C). This abstract was presented at the American Physiology Summit 2025 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

PhysiologyVol. 40(S1)
Oklahoma Medical Research Foundation (US), The University of Texas Medical Branch at Galveston (US)
Openalex Percentile: Top 79%
Cancer Genomics and Diagnostics
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