# RPLC- and HILIC-based non-targeted metabolomics workflow for blood microsamples

## TL;DR

This paper presents a new workflow for non-targeted metabolomics using blood microsamples with RPLC- and HILIC-based methods to analyze a wide range of metabolites.

## Contribution

The study introduces two new HILIC-MS methods and optimizes extraction protocols for non-targeted metabolomics from blood microsamples.

## Key findings

- A 15-minute HILIC-MS method with column re-equilibration was developed for polar metabolites.
- A 20% H2O/80% MeOH extraction mixture provided good metabolite detection across multiple pathways.
- The workflow successfully covered amino acids, acylcarnitines, and bile acids from blood microsamples.

## Abstract

Blood microsampling (BμS) has emerged as an alternative to invasive sampling methods, including blood and plasma sampling. Several studies have shown that BμS are suitable alternatives for analyzing endogenous metabolites and for metabolomics applications. Dried blood spots (DBS) have long been used for clinical applications, particularly for newborn screening. New quantitative BμS have emerged, including volumetric absorptive microsampling (VAMS).

We aimed to develop an extraction protocol from BµS for non-targeted metabolomics analysis using a reversed-phase liquid chromatography/mass spectrometry (RPLC-MS) method for the mid- to non-polar metabolome and a hydrophilic interaction chromatography/mass spectrometry (HILIC-MS) method for the polar metabolome, based on existing protocols from the literature. To improve coverage, two new HILIC-MS methods have been developed.

We used an in-house RPLC-MS method for the analysis of mid- to non-polar metabolites. Two new HILIC-MS/MS methods were developed using 73 chemical reference standards of polar metabolites from various classes. To optimize extraction, five procedures were investigated and compared to identify the most appropriate protocol for extracting metabolites from BµS for non-targeted metabolomics analysis. The final workflow was optimized on both DBS and VAMS.

We developed and optimized a 15-minute HILIC-MS method that included column re-equilibration. Our experiments showed that using a 20% H2O/80% MeOH (v/v) mixture for extraction, with sample rehydration, is a good compromise for detecting many metabolite features. Our extraction and LC-MS methodology covered metabolites from many pathways, including amino acids, acylcarnitines, and bile acids.

The online version contains supplementary material available at 10.1007/s11306-026-02402-y.