Development and quantitative evaluation of a high-resolution metabolomics technology

Abstract

Recent advances in mass spectrometry have allowed for unprecedented characterization of human metabolism and its contribution to disease. Despite these advances, limitations in metabolomics technology remain. Here, we describe a metabolomics strategy that consolidates several recent improvements in mass spectrometry technology. The platform involves a high-resolution Orbitrap mass spectrometer coupled to faster scanning speeds, allowing for polarity switching and improved ion optics resulting in enhanced sensitivity. When coupled to HILIC chromatography, we are able to quantify over 339 metabolites from an extract of HCT8 cells with a linear range of over 4 orders of magnitude in a single chromatographic run. These metabolites include diverse chemical classes ranging from amino acids to polar lipids. In addition, we also detect over 3000 additional potential metabolites present in mammalian cells. We applied this platform to characterize the metabolome of eight colorectal cancer cell lines and observed both commonalities and heterogeneities across their metabolic profiles when cells are grown in identical conditions. Together these results demonstrate that simultaneous profiling and quantitation of the human metabolome is feasible.

Figure 1

Overview of polar metabolite analysis platform. (A) The platform for polar metabolomics using LC-QE-MS. In positive mode, positively charged ions (red dots) are sent to S-lens (ion focusing), a quadrupole (low-resolution mass filter), C-trap (ions accumulate here until the targeted number of ions is reached), and finally Orbitrap high-resolution (HR) mass analyzer, where mass to charge ratio (m/z) of each ion and corresponding retention time (R.T.) are recorded. Once positive ions are sent to the Orbitrap from C-trap, the electronic field polarity is reversed, and only negatively charged ions (blue dots) are delivered from the HESI probe. (B) The duty cycle time when instrument is operated in pos/neg switch full scan mode with resolution of 70000. The typical duty cycle is between 512 and 912 ms, depending on the C-trap injection time (IT).

Figure 2

LC-QE-MS data analysis workflow. (A) Workflow for quantitative targeted and untargeted metabolomics study. (B) Workflow for unknown polar metabolites identification and scoring. Abbreviation: Stds = Standards.

Figure 3

MS/MS of positive ions with m/z of 428.04. (A) The extracted ion chromatogram (EIC) of m/z of 428.03669 (in positive mode) with a mass certainty within 10 ppm. (B) The full MS/MS chromatography of ions with m/z of 428.04 ± 1.25. (C) The MS/MS spectrum. The exact mass of fragment ion is shown below the corresponding fragment ion.

Figure 4

Dynamic range of QE-MS. (A) The total ion chromatogram (TIC) for positive mode for increasing numbers of cells used. (B) TIC for negative mode for increasing numbers of cells used. (C) The log₂-transformed intensity distribution of targeted metabolites in 3 × 10⁵ of HCT8 cells. An average of n = 3 biological replicates are considered. (D) The relationship between coefficient of variation (CV) of triplicate samples and MS intensity. The box plot shows the 75th/25th percentile, and the bar represents the median. (E) Linear regression analysis of each metabolite. The number of metabolites with a given r² value is shown.

Figure 5

MS intensity distribution and clustering in eight cell lines. (A) MS intensity distributions of cell extracts of colorectal cancer cell lines. Box plots represent the 75th/25th percentile, and the bars represent the median MS intensity. MS intensity is log₂ transformed. (B) MS intensity distribution as in (A) but with quantile normalization. (C) Heat map of Pearson clustering of MS intensity in eight cell lines. (D) Heat map as in (C) but with quantile normalization. (E) Heat map of Spearman ranking clustering of MS intensity in eight cell line. (F) Heat map as in (E) but with quantile normalization. The color code bar is applicable to each of (C–F).

Figure 6

Targeted metabolomic profiling in eight cell lines. (A) CV distribution of metabolites measured in eight cell lines. (B) CV distribution as in (A) except that quantile normalized MS intensity values were used. (C) Maxchange (log₂ transformed) distribution of targeted metabolites. (D) Maxchange distribution as in (C) but with quantile normalized MS intensity values. Abbreviation: Maxchange, the ratio of maximum and minimum MS intensity for every component across cell lines.

Figure 7

Untargeted component extraction. (A) CV (within biology triplicates) distribution of untargeted components. (B) MS intensity distribution of untargeted components in cell line SW620. (C) The relationship between the number of extracted components and CV cutoff values. (D) MS intensity distributions of cell extract of colorectal cancer cell lines. Box plots represent the 75th/25th percentile, and the bar represents the median. In (A and B), there are no filters applied to the extracted components, while in (D), filters of MS intensity higher than 10⁴ and CV (within triplicate) less than 20% were applied.

Figure 8

Metabolomic profiling in eight cell lines. (A) Maxchange distribution of cell extract. (B) Maxchange distribution as in (A) except that quantile normalized MS intensity values were used. (C) Heat map of Pearson clustering of MS intensity in eight cell line. (D) Heat map as in (C) but with quantile normalization. (E) Heat map of Spearman ranking clustering of MS intensity in eight cell lines. (F) Heat map as in (E) but with quantile normalization. The color code bar is applicable to (C–F). Abbreviation: Maxchange, the ratio of maximum and minimum MS intensity for every component across cell lines.