Formic acid pretreatment of serum and plasma samples significantly improves the performance of untargeted liquid chromatography-mass spectrometry (LC-MS) metabolomics, according to a new study in Analytical Chemistry. The approach, developed by researchers at the National Institute of Standards and Technology (NIST), increases the number of detectable metabolite features and enhances ionization efficiency, offering a simple yet effective way to improve metabolomic profiling in clinical and systems biology research.
The authors compared standard sample preparation using methanol alone to a modified protocol in which methanol containing 0.5 percent formic acid (FA) was used for protein precipitation and metabolite extraction. Across four LC–MS workflows combining different chromatographic and ionization modes, they found that FA-treated samples yielded 30–50 percent more features, depending on the mode. Notably, the FA pretreatment enhanced signals for a broad range of compound classes, including lipids, amino acids, and central carbon metabolites.
The improvement was observed in both hydrophilic interaction liquid chromatography (HILIC) and reversed-phase liquid chromatography (RPLC), under positive and negative electrospray ionization (ESI). Using pooled quality control samples and spiked-in internal standards, the study demonstrated that FA addition increased the detection of both endogenous metabolites and reference compounds with varying physicochemical properties. Importantly, the protocol did not introduce measurable biases in retention time or ion suppression.
In terms of reproducibility, the FA protocol yielded comparable or improved coefficients of variation (CVs) across multiple runs. As the authors report, “these data suggest that formic acid pretreatment can be implemented without affecting sample composition or compromising analytical reproducibility.”
Metabolite identification was supported by spectral matching using NIST’s in-house tandem MS libraries. In one representative workflow (HILIC-positive), FA pretreatment increased the number of matched metabolite features by 40 percent compared to controls. These findings underscore the practical value of mild acidification for enhancing metabolome coverage in untargeted LC–MS.
The authors conclude that “the addition of FA at 0.5 percent is a broadly beneficial strategy for untargeted LC–MS metabolomics studies in both serum and plasma matrices.”
Newsletters
Receive the latest analytical science news, personalities, education, and career development – weekly to your inbox.
