Enhanced analysis of tryptophan and its metabolites in the kynurenine pathway

Tryptophan functions as a building block in the biosynthesis of proteins and is a central precursor of the kynurenine pathway which leads to the production of nicotinamide adenine dinucleotide (NAD) due to the intermediate quinolinic acid. Due to its importance accurate analytical monitoring of tryptophan and its metabolites is desirable. 

The coordinating compounds in the pathway pose a challenge for conventional analytical setups, as nonspecific absorption leads to peak tailing and reduced recovery. A new Application Note outlines a robust method for the quantification of all relevant metabolites in the kynurenine pathway. The approach uses a bioinert YMC Accura Triart C18 column, designed to minimise undesired interactions and ensure reproducible performance across complex biological matrices.

Method optimisation using different column hardware types

Figure 2 illustrates the comparison between conventional stainless-steel and bioinert coated YMC Accura hardware. While xanthurenic acid and kynurenic acid are hardly affected by the stainless-steel hardware, quinolinic acid and picolinic acid show massive peak tailing and reduced recovery. By using the bioinert coated YMC Accura Triart C18 column, peak tailing can be significantly improved and a higher peak sensitivity can be achieved. 

Quantification of tryptophan and its metabolites in teleost brain tissue using LC- MS/MS
For the application of the method to a biological matrix, teleost brain tissue was extracted with 1 mL methanol. Centrifugation removed protein components from the sample. The resulting supernatant was evaporated and reconstituted in a 50:50 mixture of eluent A and B. All target compounds are reliably quantified in the biological sample (see link below).

Conclusion

The bioinert coated YMC Accura Triart C18 column enhances sensitivity and delivers sharper peaks for the analysis of tryptophan and its metabolites. This Application Note confirms the method’s suitability for complex biological matrices and demonstrates its robustness under real-world conditions.

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