Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10-fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable-core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.

A comprehensive characterization of the lipidome from limited starting material remains very challenging. Here we report a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry (TIMS). Taking advantage of parallel accumulation-serial fragmentation (PASEF), we fragment on average 15 precursors in each of 100 ms TIMS scans, while maintaining the full mobility resolution of co-eluting isomers. The acquisition speed of over 100 Hz allows us to obtain MS/MS spectra of the vast majority of isotope patterns. Analyzing 1 µL of human plasma, PASEF increases the number of identified lipids more than three times over standard TIMS-MS/MS, achieving attomole sensitivity. Building on high intra-and inter-laboratory precision and accuracy of TIMS collisional cross sections (CCS), we compile 1856 lipid CCS values from plasma, liver and cancer cells. Our study establishes PASEF in lipid analysis and paves the way for sensitive, ion mobilityenhanced lipidomics in four dimensions.

Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary. Chemical labeling-based single-cell approaches introduce hundreds of cells into the MS, but direct analysis of single cells has not yet reached the necessary sensitivity, robustness and quantitative accuracy to answer biological questions. Here, we develop a robust workflow combining miniaturized sample preparation, very-low flow-rate chromatography and a novel trapped ion mobility mass spectrometer, resulting in a more than ten-fold improved sensitivity. We accurately and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators such as CDK2NA, E2 ubiquitin ligases such as UBE2S and highlights potential novel ones. Comparing the variability in more than 420 single-cell proteomes to transcriptome data revealed a stable core proteome despite perturbation. Our technology can readily be applied to ultra-high sensitivity analysis of tissue material, including post-translational modifications and to small molecule studies.

Objective Glucagon is well known to regulate blood glucose but may be equally important for amino acid metabolism. Plasma levels of amino acids are regulated by glucagon-dependent mechanism(s), while amino acids stimulate glucagon secretion from alpha cells, completing the recently described liver-alpha cell axis. The mechanisms underlying the cycle and the possible impact of hepatic steatosis are unclear. Methods We assessed amino acid clearance in vivo in mice treated with a glucagon receptor antagonist (GRA), transgenic mice with 95% reduction in alpha cells, and mice with hepatic steatosis. In addition, we evaluated urea formation in primary hepatocytes from ob/ob mice and humans, and we studied acute metabolic effects of glucagon in perfused rat livers. We also performed RNA sequencing on livers from glucagon receptor knock-out mice and mice with hepatic steatosis. Finally, we measured individual plasma amino acids and glucagon in healthy controls and in two independent cohorts of patients with biopsy-verified non-alcoholic fatty liver disease (NAFLD). Results Amino acid clearance was reduced in mice treated with GRA and mice lacking endogenous glucagon (loss of alpha cells) concomitantly with reduced production of urea. Glucagon administration markedly changed the secretion of rat liver metabolites and within minutes increased urea formation in mice, in perfused rat liver, and in primary human hepatocytes. Transcriptomic analyses revealed that three genes responsible for amino acid catabolism ( Cps1 , Slc7a2 , and Slc38a2 ) were downregulated both in mice with hepatic steatosis and in mice with deletion of the glucagon receptor. Cultured ob/ob hepatocytes produced less urea upon stimulation with mixed amino acids, and amino acid clearance was lower in mice with hepatic steatosis. Glucagon-induced ureagenesis was impaired in perfused rat livers with hepatic steatosis. Patients with NAFLD had hyperglucagonemia and increased levels of glucagonotropic amino acids, including alanine in particular. Both glucagon and alanine levels were reduced after diet-induced reduction in Homeostatic Model Assessment for Insulin Resistance (HOMA-IR, a marker of hepatic steatosis). Conclusions Glucagon regulates amino acid metabolism both non-transcriptionally and transcriptionally. Hepatic steatosis may impair glucagon-dependent enhancement of amino acid catabolism.

A challenge facing metabolomics in the analysis of large human cohorts is the cross-laboratory comparability of quantitative metabolomics measurements. In this study, 14 laboratories analyzed various blood specimens using a common experimental protocol provided with Biocrates AbsoluteIDQ p400HR kit, to quantify up to 408 metabolites. The specimens included human plasma and serum from male and female donors, mouse and rat plasma as well as NIST SRM 1950 reference plasma. The metabolite classes covered range from polar (e.g. amino acids and biogenic amines), to nonpolar (e.g. diacyl-and triacyl-glycerols), and span 11 common metabolite classes. The manuscript describes a strict system suitability testing (SST) criteria used to evaluate each laboratory's readiness to perform the assay, and provides the SST Skyline documents for public dissemination. The study found approximately 250 metabolites were routinely quantified in the sample types tested, using Orbitrap instruments. Inter-laboratory variance for the NIST SRM-1950 has a median of 10% for amino acids, 24% for biogenic amines, 38% for acylcarnitines, 25% for glycerolipids, 23% for glycerophospholipids, 16% for cholesteryl esters, 15% for sphingolipids, and 9% for hexoses. Comparing to consensus values for NIST SRM-1950, nearly 80% of comparable analytes demonstrated bias of <50% from the reference value. The findings of this study result in recommendations of best practices for system suitability, quality control, and calibration. We demonstrate that with appropriate controls, high-resolution metabolomics can provide accurate results with good precision across laboratories, and the p400HR therefore is a reliable approach for generating consistent and comparable metabolomics data.