Date of Award
2025
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Chemistry
Department
Chemistry
First Advisor
Kelton McMahon
Abstract
The use of isotopes in the natural sciences stems from the principle that chemical reactions predictably alter the isotopic composition of a given sample. Recent advances in compound specific isotope analysis of amino acids (CSIA-AA) have paved the way for studies of increasingly complex ecological relationships, including the identification and characterization of organismal physiology, consumer-resource linkages, biogeochemical cycling, and movement ecology. The analytical power of CSIA-AA has caused an exponential increase in the number of application-based studies since its inception in the 1990s. With the technique constantly evolving to accommodate new research goals, it is important to understand how variation in methodology impact the accuracy, precision, and reproducibility of isotope data and our subsequent interpretation in an ecological context; yet to date, critical evaluations into the impact of methodological differences on amino acid isotope data have been limited. This thesis, therefore, aims to provide a systematic assessment of the relationship between CSIA-AA methodology and the data it produces.
Effectively assessing CSIA-AA methodology requires a thorough assessment of the current state of the field. Chapter 1 provides a meta-analysis of CSIA-AA application-based articles to analyze methodology patterns related to time, geography, and academic discipline. We found that amino acid derivatization is simultaneously the aspect of the workflow with the largest impact on the molecule and the aspect that sees the most methodological variability in published literature. We determined that the geographic location of the analyst largely determined the methodological approach as opposed to the experimental application, and this pattern is likely reflective of knowledge transfer in this new field is still largely passed through academic lineages. We find that the reproducibility of CSIA-AA data and its interlaboratory comparability would greatly benefit from method optimization and standardization and improve its accuracy and precision.
Following Chapter 1’s discovery that derivatization was the most variable stage of the CSIA-AA workflow, we quantitatively characterized the effects of derivatization method on d13C values for trifluoro-acetic acid (TFAA), the most common derivatization approach in the literature. For Chapter 2, we orthogonally tested variations of reaction time and temperature for the two-phase TFAA derivatization method and analyzed their statistical impact on d13C data using a combination of linear, multivariate, and mixed-effect models. We found that while the acylation reaction phase, overall, has comparatively minimal impact on amino acid d13C data, increasing esterification temperature significantly decreased the mean d13C value by upwards of 1 0/00. Similarly, increasing esterification reaction time substantially increased the spread of the data, as the standard deviation increased to upwards of 1.5 0/00 at the 120 min reaction time. The significant influence of reaction conditions on the resulting isotope data suggests that methodological artifacts could alter not only the reproducibility of CSIA-AA data but our interpretation of amino acid isotope data in organismal and physiological context as well. The impacts of reaction condition did not impact individual amino acids consistently, meaning that ecological CSIA-AA-based metrics that rely on relative patterns of amino acid d13C data (i.e., isotope fingerprinting and trophic position calculations) could be disproportionately skewed.
Methodological differences within a single derivatization procedure directly impacted the resulting amino acid isotope data, yet multiple different approaches are commonly used in CSIA-AA literature and compared under the assumption that all approaches result in the same outcome. As such, it was imperative to explore how different derivatization methods altered amino acid isotope values. For Chapter 3, we conducted an interlaboratory study in which we enlisted 13 laboratories worldwide to analyze three separate, well characterized samples: two reagent grade amino acid mixtures of known isotopic composition and one biological matrix reference material. Participants were asked to analyze replicates of each sample according to their respective in-house protocols and return d13C and d15N data for each sample. Submitted isotope data was analyzed for trends related to accuracy, precision, and reproducibility among individual laboratories, across derivatization procedures, and for the field overall.
This analysis revealed that across all amino acids, the average variance of reported data within a single laboratory was 1.23 0/00 for d13C and 0.58 0/00 for d15N. When comparing the mean reported isotope values across all participants, however, the calculated variance increased to 4.14 0/00 for d13C and 1.80 0/00 for d15N, indicating that while variance of individual laboratories is low (reflective of the consistency within a methodological approach), different laboratories reported different isotope values for the same samples. This indicates that comparisons of CSIA-AA data across published literature is likely biased as a result of different methodological approaches used among labs. Additionally, analysis of offsets from known d13C and d15N values of the amino acid mixtures revealed that overall, d13C data was less accurate than d15N data, likely due to the exogenous carbon added during derivatization. Among procedures with multiple contributing labs, acetyl derivatives had the least accurate data, with their offsets being -1.22 0/00 and 0.57 0/00 for d13C and d15N, respectively. Finally, this analysis also indicated that despite the vast range of reported isotope values across labs, data normalization reduced field variance to 2.92 0/00 for d13C and 1.28 0/00 for d15N, showing that the implementation of standardized data correction procedures can vastly improve interlaboratory data comparability.
This thesis reveals that differences in CSIA-AA methodology directly impact the resulting isotope data. The potential to arrive at different conclusions based on sample preparation procedures, alone, emphasizes the need for method standardization within the technique. This thesis offers an assessment of the CSIA-AA workflow, and the results demonstrate the efficacy of using a standard set of sample preparation procedures and the standardized data corrections. The introduction of a standardized approach to CSIA-AA can allow this burgeoning field to expand its reach even further.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Brown-Nash, Audreyana, "CHARACTERIZATION OF METHODOLOGICAL VARIABILITY IN COMPOUND SPECIFIC ISOTOPE ANALYSIS OF AMINO ACIDS (CSIA-AA)" (2025). Open Access Dissertations. Paper 4489.
https://digitalcommons.uri.edu/oa_diss/4489