Conference Agenda

The stable isotope composition of amino acids records (bio)synthetic pathway and/or environmental conditions, and are thus of great importance in biogeochemistry [1]. While most isotope analysis are conducted at the molecular (or ‘bulk’) level, novel approaches such as position-specific isotope analysis (PSIA) could prove useful in deciphering different sources of amino acids.

Building up on the pioneering work of Abelson & Hoering (1961)[2], we used the ninhydrin reaction to form CO₂ and acetaldehyde (CH₃CHO) from alanine (CH₃-CHNH₂-COOH). The d¹³C of the CO₂ evolved can be measured directly and that of each position in acetaldehyde can be determined through the on-line pyrolysis approach [3]. The method thus allows the determination of d¹³C values of all positions in alanine.

The approach can be applied directly to a mixture of amino acids (typically a protein hydrolysate) where all amino acids are decarboxylated through the ninhydrin reaction, leaving CO₂ and aldehydes in the headspace of the vial. While the carboxyl position is averaged over all amino acids, the method allows PSIA of the remaining skeleton of the most volatile aldehydes, corresponding to non-polar amino acids: alanine, valine, leucine, isoleucine, phenylalanine, methionine.

We show that the difference between the methyl (CH₃) and the amine group (CHNH₂) in alanine from C₃, C₄ and CAM plants is correlated to that found between the two carbons of ethanol, as expected from their common precursor pyruvate. This high-throughput approach can be easily applied to recent sediments, cell cultures or hair, and shows great potential to refine our understanding of the sources of amino acids in natural samples.

[1] Hayes, “Fractionation of the Isotopes of Carbon and Hydrogen in Biosynthetic Processes,” 2001.

[2] Abelson and Hoering, Proc. Natl. Acad. Sci., vol. 47, 1961

[3] Hattori et al., J. Agric. Food Chem., vol. 59, 2011

Reproducible data processing is a key prerequisite for efficient data exchange, methodological progress, consistent training of new users, and productive discourse in stable isotope research. However, producing a faithful record of every step of the data reduction process from raw data to final results in a reproducible manner can currently be prohibitively time-consuming. All too often data processing that is both transparent and easy to communicate thus falls victim to the enormous effort required to design experiments well, run complex analytical procedures, and interpret the results in the proper geochemical/geologic/ecological context. While this is understandable, insufficiently documented data processing workflows create a high risk for errors to go undetected and become propagated. Additionally, they create barriers to sharing and discussing one’s approach to data reduction effectively. These drawbacks limit opportunities for exchange of ideas, methodological progress, and large-scale data repository efforts aimed at extracting maximum benefit from stable isotope data across the many disciplines that make us of it.

The goal of the ISOVERSE (www.isoverse.org) is to fill this gap by creating a comprehensive software ecosystem of free, open-source tools for efficient, transparent, and reproducible processing of stable isotope data from raw analytical measurements all the way to fully processed stable isotope data ready for publication and repository deposition. By building on best practices in modern data science and software engineering, the ISOVERSE seeks to empower scientists at all career stages and programming levels to share their work more easily and contribute fully reproducible data sets to data repository efforts. In this presentation, I will introduce some of the existing key capabilities of the ISOVERSE and discuss implementation plans for next stage of development over the coming 2+ (grant-funded) years with the goal of stimulating discussion and eliciting constructive feedback from the community of stable isotope experts at JESIUM.