Nanocapillary sampling coupled to liquid chromatography mass spectrometry delivers single cell drug measurement and lipid fingerprints

Single-Cell Untargeted Lipidomics Using Liquid Chromatography and Data-Dependent Acquisition after Live Cell Selection

We report the development and validation of an untargeted single-cell lipidomics method based on microflow chromatography coupled to a data-dependent mass spectrometry method for fragmentation-based identification of lipids. Given the absence of single-cell lipid standards, we show how the methodology should be optimized and validated using a dilute cell extract. The methodology is applied to dilute pancreatic cancer and macrophage cell extracts and standards to demonstrate the sensitivity requirements for confident assignment of lipids and classification of the cell type at the single-cell level. The method is then coupled to a system that can provide automated sampling of live, single cells into capillaries under microscope observation. This workflow retains the spatial information and morphology of cells during sampling and highlights the heterogeneity in lipid profiles observed at the single-cell level. The workflow is applied to show changes in single-cell lipid profiles as a response to oxidative stress, coinciding with expanded lipid droplets. This demonstrates that the workflow is sufficiently sensitive to observing changes in lipid profiles in response to a biological stimulus. Understanding how lipids vary in single cells will inform future research into a multitude of biological processes as lipids play important roles in structural, biophysical, energy storage, and signaling functions.

Investigating the Metabolic Heterogeneity of Cancer Cells Using Functional Single-Cell Selection and nLC Combined with Multinozzle Emitter Mass Spectrometry

Tumor metastasis and cancer recurrence are often a result of cell heterogeneity, where specific subpopulations of tumor cells may be resistant to radio- or chemotherapy. To investigate this physiological and phenotypic diversity, single-cell metabolomics provides a powerful approach at the chemical level, where distinct lipid profiles can be found in different tumor cells. Here, we established a highly sensitive platform using nanoflow liquid chromatography (nLC) combined with multinozzle emitter electrospray ionization mass spectrometry for more in-depth metabolomics profiling. Our platform identified 15 and 17 lipids from individual osteosarcoma (U2OS) and glioblastoma (GBM) cells when analyzing single-cell samples. Additionally, we used the functional single-cell selection (fSCS) pipeline to analyze the subpopulations of cells with a DNA damage response (DDR) in U2OS cells and fast migration in GBM cells. Specifically, we observed a down-regulation of polyunsaturated fatty acids (PUFAs) in U2OS cells undergoing DDR, such as fatty acids FA 20:3; O2 and FA 17:4; O3. Furthermore, ceramides (Cer 38:0; O3) and triglycerides (TG 36:0) were found to be down-regulated in fast-migrating GBM cells compared to the slow-migrating subpopulation. These findings suggest the potential roles of these metabolites and/or lipids in the cellular behavior of the subpopulations.

Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells

In this work, we demonstrate the development and first application of nanocapillary sampling followed by analytical flow liquid chromatography-mass spectrometry for single-cell lipidomics. Around 260 lipids were tentatively identified in a single cell, demonstrating remarkable sensitivity. Human pancreatic ductal adenocarcinoma cells (PANC-1) treated with the chemotherapeutic drug gemcitabine can be distinguished from controls solely on the basis of their single-cell lipid profiles. Notably, the relative abundance of LPC(0:0/16:0) was significantly affected in gemcitabine-treated cells, in agreement with previous work in bulk. This work serves as a proof of concept that live cells can be sampled selectively and then characterized using automated and widely available analytical workflows, providing biologically relevant outputs.

Spatial single cell metabolomics: Current challenges and future developments

Single cell metabolomics is a rapidly advancing field of bio-analytical chemistry which aims to observe cellular biology with the greatest detail possible. Mass spectrometry imaging and selective cell sampling (e.g. using nanocapillaries) are two common approaches within the field. Recent achievements such as observation of cell-cell interactions, lipids determining cell states and rapid phenotypic identification demonstrate the efficacy of these approaches and the momentum of the field. However, single cell metabolomics can only continue with the same impetus if the universal challenges to the field are met, such as the lack of strategies for standardisation and quantification, and lack of specificity/sensitivity. Mass spectrometry imaging and selective cell sampling come with unique advantages and challenges which, in many cases are complementary to each other. We propose here that the challenges specific to each approach could be ameliorated with collaboration between the two communities driving these approaches.