Automating Amino Acid Analysis
Why do we measure Amino Acids?
Amino acids are both key metabolites in primary metabolism and the structural building blocks of proteins.
Analysing amino acids is done clinically for the diagnosis of metabolic disorders; and branched-chain amino acids are predictive biomarkers of metabolic syndrome, type-2 diabetes and insulin resistance. Amino acids measurements are routinely done in the food industry, for quality control, process control (e.g., to predict acrylamide formation potential or monitoring fermentation/cell culture) and nutritional labelling (e.g., human foods, pet-foods and animal feed analysis).
In the biotech and pharmaceutical industries, amino acid analysis is an integral tool in peptide identification and characterization and in the quality control of peptides and biopharmaceuticals.
The Conventional Approaches
Amino acid analysis is typically performed by ion exchange chromatography and high performance liquid chromatography (HPLC) techniques, typically with post-column or pre-column derivatization respectively.
Post-column derivatization is typically done with ninhydrin or ortho phthalaldehyde (OPA). These approaches benefit from being established methods with well characterized chemistry, whilst pre-column derivatization prior to reversed phase HPLC separations allow faster analysis times and increased sensitivity. There are also more pre-column derivatization reagents available, including OPA, PITC, FMOC and ACQ derivatives.
More recently ion chromatography with electrochemical detection has been used for the analysis of protein hydrolysates.
In metabolomics, GC-MS is also commonly used for amino acids analysis as it delivers a robust quantitative analyses, especially for 1H and 13C metabolic flux studies.
What’s wrong with the existing approaches?
Whilst there are lots of options for amino acid analysis, each approach has its limitations. The nature of the matrix can significantly affect many of the derivatives, necessitating extensive sample preparation and in addition, post-column derivatization methods, lead to long analysis times, limiting sample throughput.
Many of the methods also have performance limitations in one or more areas (resolution, dynamic range, precision and detection limits) and all of these approaches involve the use of labour intensive, complex, manual sample preparation protocols that are intolerant of even small changes to matrix composition.
Is there a better way?
We’ve recently been building on some proof-of-concept work done by Dr Katja Dettmer using alkyl-chloroformate derivatives and are currently working with several customers on this alternative approach that can be automated with the GERSTEL MultiPurpose Sampler (MPS).
These derivatives benefit from being fast and robust and can be applied to a range of aqueous samples (plant or food extracts, beverages, plasma, urine, cell culture/broths and protein hydrolysates) without the need for either sample clean-up or urea/protein removal.
They’re also analytically useful as, depending on the application, target metabolites and required detection limits, they can be analyzed by GC-FID, GC-MS or LC-MS2. The EI spectra of these derivatives are particularly valuable in 15N metabolic flux studies.
Building on Katja’s original work, we have added ITSP Solutions’ micro-scale cation exchange clean up, GERSTEL Multi Position Vortexer (mVORX) and Anatune CF200 Robotic Centrifuge to deliver a fully automated solution for amino acid determination.
We’re currently completing the development of this solution in our applications laboratory and already have several customers interested in developing this solution for the analysis of organic acids and TCA cycle intermediates.
Anatune can build metabolomics solutions for online (GC-MS, LC-MS) and offline sample preparation.
With the modularity and flexibility of the GERSTEL MPS PrepStation, we can automate what you currently do manually, and provide complete solutions using instrumentation from Agilent Technologies and GERSTEL.
Anatune will be sponsoring Metabolomics 2016 in the Conference Centre Dublin and will be there with our Partners GERSTEL and Agilent.
If you’re there too, come to our booth no. D5 to find out how we can work together to automate your amino acid analyses.
If you can’t meet us there and would like to know more call us on +44 (0)1223 279210 or email firstname.lastname@example.org.