Targeted Metabolomics on Rare Primary Cells

Summary

Here, we present a protocol to accurately and reliably measure metabolites in rare cell types. Technical improvements, including a modified sheath fluid for cell sorting and the generation of relevant blank samples, enable a comprehensive quantification of metabolites with an input of only 5000 cells per sample.

Abstract

Cellular function critically depends on metabolism, and the function of the underlying metabolic networks can be studied by measuring small molecule intermediates. However, obtaining accurate and reliable measurements of cellular metabolism, particularly in rare cell types like hematopoietic stem cells, has traditionally required pooling cells from multiple animals. A protocol now enables researchers to measure metabolites in rare cell types using only one mouse per sample while generating multiple replicates for more abundant cell types. This reduces the number of animals that are required for a given project. The protocol presented here involves several key differences over traditional metabolomics protocols, such as using 5 g/L NaCl as a sheath fluid, sorting directly into acetonitrile, and utilizing targeted quantification with rigorous use of internal standards, allowing for more accurate and comprehensive measurements of cellular metabolism. Despite the time required for the isolation of single cells, fluorescent staining, and sorting, the protocol can preserve differences among cell types and drug treatments to a large extent.

Introduction

Metabolism is an essential biological process that occurs in all living cells. Metabolic processes involve a vast network of biochemical reactions that are tightly regulated and interconnected, allowing cells to produce energy and synthesize essential biomolecules¹. To understand the function of metabolic networks, researchers measure the levels of small molecule intermediates within cells. These intermediates serve as important indicators of metabolic activity and can reveal critical insights into cellular function.

Mass spectrometry (MS) is the most popular choice for the specific detection of metabolites in complex samples^1,2. Nuclear magnetic resonance (NMR) has advantages in the absolute quantification of compounds and structure elucidation, but MS can often resolve more components in complex mixtures such as biofluids or cell extracts. More often than not, MS is combined with prior separation of the compound by capillary electrophoresis (CE), gas chromatography (GC), or liquid chromatography (LC)³. The choice of separation platform is mostly driven by the range of target metabolites and the type of sample and, in a real-world setting, by the availability of machines and expertise. All three separation platforms have a broad and overlapping range of suitable metabolites but different limitations. Briefly, CE can only separate charged molecules and requires a lot of expertise to implement robust analysis of a large number of samples⁴. GC is limited to molecules that are small and apolar enough to evaporate before decomposing³. Considering all commercially available LC columns, any two metabolites can be separated by this technology⁵. However, many LC methods exhibit less resolving power than CE or GC methods of similar length.

The typical amount of starting material for metabolomics measurements is usually in the range of 5 x 10⁵ to 5 x 10⁷ cells per sample, 5-50 mg of wet tissue, or 5-50 µL of body fluid⁶. However, it can be challenging to obtain such amounts of starting material when working with primary cells of rare cell types, such as for example hematopoietic stem cells (HSCs) or circulating tumor cells. These cells are often present in very low numbers and cannot be cultivated without compromising critical cellular features.

HSCs and multipotent progenitor cells (MPPs) are the least differentiated cells of the hematopoietic system and continuously produce new blood cells throughout an organism's life. The regulation of hematopoiesis is of clinical relevance in conditions such as leukemia and anemia. Despite their importance, HSCs and MPPs are among the rarest cells within the hematopoietic system. From a single mouse, typically, about 5000 HSCs can be isolated^7,8,9. As traditional metabolomics methods require more input material, pooling cells from multiple mice was often necessary to analyze rare cell types^10,11.

Here, we aimed to develop a protocol that enables the measurement of metabolites in as little as 5000 cells per sample to enable the generation of metabolomics data from the HSCs of a single mouse¹². At the same time, this method allows to generate multiple replicates from a single mouse for more abundant cell types like lymphocytes. This approach reduces the number of animals required for a given project, thus contributing to the "3R" (reduction, replacement, refinement) of animal experiments.

Metabolites in cells can have very high turnover rates, often in the order of seconds¹³. However, preparing samples for fluorescence-activated cell sorting (FACS) can take hours, and FACS sorting itself can take minutes to hours, leading to potential alterations in the metabolome due to non-physiological conditions. Some of the reagents used in this protocol (such as ammonium-chloride-potassium [ACK] lysis buffer) can have similar effects. These conditions can cause cellular stress and impact the levels and ratios of metabolites within cells, leading to inaccurate or biased measurements of cellular metabolism^14,15,16. The metabolic changes due to sample preparation are sometimes referred to as sorting artifacts. Long digestion protocols and harsh reagents that might be required to produce single-cell suspensions from hard or tough tissues can aggravate this issue. What changes can occur likely depends on the cell type and the processing condition. The precise nature of the changes remains unknown, as the metabolic state of the undisturbed cells in the living tissue cannot be measured.

The protocol presented here involves several key differences compared to traditional methods, namely the use of 5 g/L NaCl as a sheath fluid, sorting directly into extraction buffer, injecting large sample volumes on hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS), and utilizing targeted quantification, rigorous use of internal standards and background controls (Figure 1). This protocol has the potential to preserve differences among cell types and between drug treatment and vehicle control to a large extent¹². Even for cultured cells, it compares favorably to alternative approaches, such as the more established centrifugation and manual removal of supernatant. However, as sorting artifacts may still occur, data must be interpreted with caution. Despite this limitation, the protocol represents a significant improvement in the field of metabolic profiling, allowing for more accurate and comprehensive measurements of cellular metabolism in rare primary cells¹².

The ability to robustly measure broad metabolic profiles in rare primary cells opens the door to new experiments in biomedical research involving these cells. For example, metabolically mediated regulation in HSCs has been shown to impact dormancy self-renewal capacity, with implications for anemia and leukemia^11,17. In patient-derived circulating tumor cells, differences in the expression of metabolic genes between tumor and adjacent cells have been shown^18,19. This protocol now allows researchers to study these differences systematically on a metabolic level, which is generally regarded as closer to the cellular phenotype than gene expression.

Protocol

Breeding and husbandry of all mice used for this protocol were conducted in a conventional animal facility at the Max Planck Institute for Immunobiology and Epigenetics (MPI-IE) according to the regulations of the local authorities (Regierungspräsidium Freiburg). Mice were euthanized with CO2 and cervical dislocation by FELASA B-trained personnel following guidelines and regulations approved by the animal welfare committee of the MPI-IE and the local authorities. No animal experimentation was performed, a…

Representative Results

FACS sorting enables the isolation of clean populations of different cell types from the same cell suspension (Figure 2 and Figure 3). The specificity of this method relies on the staining of the different cell types with specific surface markers (for example, B cells and T cells from the spleen) or specific combinations of surface markers (for example HSCs and MPPs). Staining of intracellular markers typically requires permeabilization of the cell membrane. Thi…

Discussion

The most critical steps for successful implementation of targeted metabolomics using this protocol are 1) a robust staining and gating strategy that will yield clean cell populations 2) precise handling of liquid volumes, 3) reproducible timing of all experimental steps, in particular all steps prior to metabolite extraction. Ideally, all samples belonging to one experiment should be processed and measured in one batch to minimize batch effects²². For larger experiments, we suggest collecting cell…

Materials

13C yeast extract	Isotopic Solutions	ISO-1
40 µm cell strainer	Corning	352340
Acetonitrile, LC-MS grade	VWR	83640.32
ACK lysis buffer	Gibco	104921	Alternatively: Lonza, Cat# BP10-548E
Adenosine diphosphate (ADP)	Sigma Aldrich	A2754
Adenosine monophosphate (AMP)	Sigma Aldrich	A1752
Adenosine triphosphate (ATP)	Sigma Aldrich	A2383
Ammonium Carbonate, HPLC grade	Fisher Scientific	A/3686/50
Atlantis Premier BEH Z-HILIC column (100 x 2.1 mm, 1.7 µm)	Waters	186009982
B220-A647	Invitrogen	103226
B220-PE/Cy7	BioLegend	103222	RRID:AB_313005
CD11b-PE/Cy7	BioLegend	101216	RRID:AB_312799
CD150-BV605	BioLegend	115927	RRID:AB_11204248
CD3-PE	Invitrogen	12-0031-83
CD48-BV421	BioLegend	103428	RRID:AB_2650894
CD4-PE/Cy7	BioLegend	100422	RRID:AB_2660860
CD8a-PE/Cy7	BioLegend	100722	RRID:AB_312761
cKit-PE	BioLegend	105808	RRID:AB_313217
Dynabeads Untouched Mouse CD4 Cells Kit	Invitrogen	11415D
FACSAria III	BD
Gr1-PE/Cy7	BioLegend	108416	RRID:AB_313381
Heat sealing foil	Neolab	Jul-18
Isoleucine	Sigma Aldrich	58880
JetStream ESI Source	Agilent	G1958B
Leucine	Sigma Aldrich	L8000
Medronic acid	Sigma Aldrich	M9508-1G
Methanol, LC-MS grade	Carl Roth	HN41.2
NaCl	Fluka	31434-1KG
PBS	Sigma Aldrich	D8537
Sca1-APC/Cy7	BioLegend	108126	RRID:AB_10645327
TER119-PE/Cy7	BioLegend	116221	RRID:AB_2137789
Triple Quadrupole Mass Spectrometer	Agilent	6495B
Twin.tec PCR plate 96 well LoBind skirted	Eppendorf	30129512
UHPLC Autosampler	Agilent	G7157B
UHPLC Column Thermostat	Agilent	G7116B
UHPLC Pump	Agilent	G7120A
UHPLC Sample Thermostat	Agilent	G4761A