Polyamine metabolism is a central determinant of helper T cell lineage fidelity.

Polyamine synthesis represents one of the most profound metabolic changes during T cell activation, but the biological implications of this are scarcely known. Here, we show that polyamine metabolism is a fundamental process governing the ability of CD4+ helper T cells (TH) to polarize into different functional fates. Deficiency in ornithine decarboxylase, a crucial enzyme for polyamine synthesis, results in a severe failure of CD4+ T cells to adopt correct subset specification, underscored by ectopic expression of multiple cytokines and lineage-defining transcription factors across TH cell subsets. Polyamines control TH differentiation by providing substrates for deoxyhypusine synthase, which synthesizes the amino acid hypusine, and mice in which T cells are deficient for hypusine develop severe intestinal inflammatory disease. Polyamine-hypusine deficiency caused widespread epigenetic remodeling driven by alterations in histone acetylation and a re-wired tricarboxylic acid (TCA) cycle. Thus, polyamine metabolism is critical for maintaining the epigenome to focus TH cell subset fidelity.

Phosphoinositide acyl chain saturation drives CD8+ effector T cell signaling and function.

How lipidome changes support CD8+ effector T (Teff) cell differentiation is not well understood. Here we show that, although naive T cells are rich in polyunsaturated phosphoinositides (PIPn with 3-4 double bonds), Teff cells have unique PIPn marked by saturated fatty acyl chains (0-2 double bonds). PIPn are precursors for second messengers. Polyunsaturated phosphatidylinositol bisphosphate (PIP2) exclusively supported signaling immediately upon T cell antigen receptor activation. In late Teff cells, activity of phospholipase C-γ1, the enzyme that cleaves PIP2 into downstream mediators, waned, and saturated PIPn became essential for sustained signaling. Saturated PIP was more rapidly converted to PIP2 with subsequent recruitment of phospholipase C-γ1, and loss of saturated PIPn impaired Teff cell fitness and function, even in cells with abundant polyunsaturated PIPn. Glucose was the substrate for de novo PIPn synthesis, and was rapidly utilized for saturated PIP2 generation. Thus, separate PIPn pools with distinct acyl chain compositions and metabolic dependencies drive important signaling events to initiate and then sustain effector function during CD8+ T cell differentiation.

Mitochondrial Priming by CD28.

T cell receptor (TCR) signaling without CD28 can elicit primary effector T cells, but memory T cells generated during this process are anergic, failing to respond to secondary antigen exposure. We show that, upon T cell activation, CD28 transiently promotes expression of carnitine palmitoyltransferase 1a (Cpt1a), an enzyme that facilitates mitochondrial fatty acid oxidation (FAO), before the first cell division, coinciding with mitochondrial elongation and enhanced spare respiratory capacity (SRC). microRNA-33 (miR33), a target of thioredoxin-interacting protein (TXNIP), attenuates Cpt1a expression in the absence of CD28, resulting in cells that thereafter are metabolically compromised during reactivation or periods of increased bioenergetic demand. Early CD28-dependent mitochondrial engagement is needed for T cells to remodel cristae, develop SRC, and rapidly produce cytokines upon restimulation-cardinal features of protective memory T cells. Our data show that initial CD28 signals during T cell activation prime mitochondria with latent metabolic capacity that is essential for future T cell responses.

Inflammatory macrophage dependence on NAD+ salvage is a consequence of reactive oxygen species-mediated DNA damage.

The adoption of Warburg metabolism is critical for the activation of macrophages in response to lipopolysaccharide. Macrophages stimulated with lipopolysaccharide increase their expression of nicotinamide phosphoribosyltransferase (NAMPT), a key enzyme in NAD+ salvage, and loss of NAMPT activity alters their inflammatory potential. However, the events that lead to the cells' becoming dependent on NAD+ salvage remain poorly defined. We found that depletion of NAD+ and increased expression of NAMPT occurred rapidly after inflammatory activation and coincided with DNA damage caused by reactive oxygen species (ROS). ROS produced by complex III of the mitochondrial electron-transport chain were required for macrophage activation. DNA damage was associated with activation of poly(ADP-ribose) polymerase, which led to consumption of NAD+. In this setting, increased NAMPT expression allowed the maintenance of NAD+ pools sufficient for glyceraldehyde-3-phosphate dehydrogenase activity and Warburg metabolism. Our findings provide an integrated explanation for the dependence of inflammatory macrophages on the NAD+ salvage pathway.

An LKB1-mitochondria axis controls TH17 effector function.

CD4+ T cell differentiation requires metabolic reprogramming to fulfil the bioenergetic demands of proliferation and effector function, and enforce specific transcriptional programmes1-3. Mitochondrial membrane dynamics sustains mitochondrial processes4, including respiration and tricarboxylic acid (TCA) cycle metabolism5, but whether mitochondrial membrane remodelling orchestrates CD4+ T cell differentiation remains unclear. Here we show that unlike other CD4+ T cell subsets, T helper 17 (TH17) cells have fused mitochondria with tight cristae. T cell-specific deletion of optic atrophy 1 (OPA1), which regulates inner mitochondrial membrane fusion and cristae morphology6, revealed that TH17 cells require OPA1 for its control of the TCA cycle, rather than respiration. OPA1 deletion amplifies glutamine oxidation, leading to impaired NADH/NAD+ balance and accumulation of TCA cycle metabolites and 2-hydroxyglutarate-a metabolite that influences the epigenetic landscape5,7. Our multi-omics approach revealed that the serine/threonine kinase liver-associated kinase B1 (LKB1) couples mitochondrial function to cytokine expression in TH17 cells by regulating TCA cycle metabolism and transcriptional remodelling. Mitochondrial membrane disruption activates LKB1, which restrains IL-17 expression. LKB1 deletion restores IL-17 expression in TH17 cells with disrupted mitochondrial membranes, rectifying aberrant TCA cycle glutamine flux, balancing NADH/NAD+ and preventing 2-hydroxyglutarate production from the promiscuous activity of the serine biosynthesis enzyme phosphoglycerate dehydrogenase (PHGDH). These findings identify OPA1 as a major determinant of TH17 cell function, and uncover LKB1 as a sensor linking mitochondrial cues to effector programmes in TH17 cells.

Sulfur sequestration promotes multicellularity during nutrient limitation.

The behaviour of Dictyostelium discoideum depends on nutrients1. When sufficient food is present these amoebae exist in a unicellular state, but upon starvation they aggregate into a multicellular organism2,3. This biology makes D. discoideum an ideal model for investigating how fundamental metabolism commands cell differentiation and function. Here we show that reactive oxygen species-generated as a consequence of nutrient limitation-lead to the sequestration of cysteine in the antioxidant glutathione. This sequestration limits the use of the sulfur atom of cysteine in processes that contribute to mitochondrial metabolism and cellular proliferation, such as protein translation and the activity of enzymes that contain an iron-sulfur cluster. The regulated sequestration of sulfur maintains D. discoideum in a nonproliferating state that paves the way for multicellular development. This mechanism of signalling through reactive oxygen species highlights oxygen and sulfur as simple signalling molecules that dictate cell fate in an early eukaryote, with implications for responses to nutrient fluctuations in multicellular eukaryotes.

Targeting MDM2 enhances antileukemia immunity after allogeneic transplantation via MHC-II and TRAIL-R1/2 upregulation.

Patients with acute myeloid leukemia (AML) often achieve remission after allogeneic hematopoietic cell transplantation (allo-HCT) but subsequently die of relapse driven by leukemia cells resistant to elimination by allogeneic T cells based on decreased major histocompatibility complex II (MHC-II) expression and apoptosis resistance. Here we demonstrate that mouse-double-minute-2 (MDM2) inhibition can counteract immune evasion of AML. MDM2 inhibition induced MHC class I and II expression in murine and human AML cells. Using xenografts of human AML and syngeneic mouse models of leukemia, we show that MDM2 inhibition enhanced cytotoxicity against leukemia cells and improved survival. MDM2 inhibition also led to increases in tumor necrosis factor-related apoptosis-inducing ligand receptor-1 and -2 (TRAIL-R1/2) on leukemia cells and higher frequencies of CD8+CD27lowPD-1lowTIM-3low T cells, with features of cytotoxicity (perforin+CD107a+TRAIL+) and longevity (bcl-2+IL-7R+). CD8+ T cells isolated from leukemia-bearing MDM2 inhibitor-treated allo-HCT recipients exhibited higher glycolytic activity and enrichment for nucleotides and their precursors compared with vehicle control subjects. T cells isolated from MDM2 inhibitor-treated AML-bearing mice eradicated leukemia in secondary AML-bearing recipients. Mechanistically, the MDM2 inhibitor-mediated effects were p53-dependent because p53 knockdown abolished TRAIL-R1/2 and MHC-II upregulation, whereas p53 binding to TRAILR1/2 promotors increased upon MDM2 inhibition. The observations in the mouse models were complemented by data from human individuals. Patient-derived AML cells exhibited increased TRAIL-R1/2 and MHC-II expression on MDM2 inhibition. In summary, we identified a targetable vulnerability of AML cells to allogeneic T-cell-mediated cytotoxicity through the restoration of p53-dependent TRAIL-R1/2 and MHC-II production via MDM2 inhibition.

LC-MS-Based Targeted Metabolomics for FACS-Purified Rare Cells.

Metabolism plays a fundamental role in regulating cellular functions and fate decisions. Liquid chromatography-mass spectrometry (LC-MS)-based targeted metabolomic approaches provide high-resolution insights into the metabolic state of a cell. However, the typical sample size is in the order of 105-107 cells and thus not compatible with rare cell populations, especially in the case of a prior flow cytometry-based purification step. Here, we present a comprehensively optimized protocol for targeted metabolomics on rare cell types, such as hematopoietic stem cells and mast cells. Only 5000 cells per sample are required to detect up to 80 metabolites above background. The use of regular-flow liquid chromatography allows for robust data acquisition, and the omission of drying or chemical derivatization avoids potential sources of error. Cell-type-specific differences are preserved while the addition of internal standards, generation of relevant background control samples, and targeted metabolite with quantifiers and qualifiers ensure high data quality. This protocol could help numerous studies to gain thorough insights into cellular metabolic profiles and simultaneously reduce the number of laboratory animals and the time-consuming and costly experiments associated with rare cell-type purification.

automRm: An R Package for Fully Automatic LC-QQQ-MS Data Preprocessing Powered by Machine Learning.

Preprocessing of liquid chromatography-mass spectrometry (LC-MS) raw data facilitates downstream statistical and biological data analyses. In the case of targeted LC-MS data, consistent recognition of chromatographic peaks is a main challenge, in particular, for low abundant signals. Fully automatic preprocessing is faster than manual peak review and does not depend on the individual operator. Here, we present the R package automRm for fully automatic preprocessing of LC-MS data recorded in MRM mode. Using machine learning (ML) for detection of chromatographic peaks and quality control of reported results enables the automatic recognition of complex patterns in raw data. In addition, this approach renders automRm generally applicable to a wide range of analytical methods including hydrophilic interaction liquid chromatography (HILIC), which is known for sample-to-sample variations in peak shape and retention time. We demonstrate the impact of the choice of training data set, of the applied ML algorithm, and of individual peak characteristics on automRm's ability to correctly report chromatographic peaks. Next, we show that automRm can replicate results obtained by manual peak review on published data. Moreover, automRm outperforms alternative software solutions regarding the variation in peak integration among replicate measurements and the number of correctly reported peaks when applied to a HILIC-MS data set. The R package is freely available from gitlab (https://gitlab.gwdg.de/joerg.buescher/automrm).

Assimilating genome-scale metabolic reconstructions with modelBorgifier.

MOTIVATION: Genome-scale reconstructions and models, as collections of genomic and metabolic information, provide a useful means to compare organisms. Comparison requires that models are similarly notated to pair shared components. RESULT: Matching and comparison of genome-scale reconstructions and models are facilitated by modelBorgifier. It reconciles models in light of different annotation schemes, allowing diverse models to become useful for synchronous investigation. AVAILABILITY AND IMPLEMENTATION: The modelBorgifier toolbox is freely available at http://www.brain-biotech.de/downloads/modelBorgifier.zip.

Targeted Metabolomics on Rare Primary Cells.

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.

Functional multi-organelle units control inflammatory lipid metabolism of macrophages.

Eukaryotic cells contain several membrane-separated organelles to compartmentalize distinct metabolic reactions. However, it has remained unclear how these organelle systems are coordinated when cells adapt metabolic pathways to support their development, survival or effector functions. Here we present OrgaPlexing, a multi-spectral organelle imaging approach for the comprehensive mapping of six key metabolic organelles and their interactions. We use this analysis on macrophages, immune cells that undergo rapid metabolic switches upon sensing bacterial and inflammatory stimuli. Our results identify lipid droplets (LDs) as primary inflammatory responder organelle, which forms three- and four-way interactions with other organelles. While clusters with endoplasmic reticulum (ER) and mitochondria (mitochondria-ER-LD unit) help supply fatty acids for LD growth, the additional recruitment of peroxisomes (mitochondria-ER-peroxisome-LD unit) supports fatty acid efflux from LDs. Interference with individual components of these units has direct functional consequences for inflammatory lipid mediator synthesis. Together, we show that macrophages form functional multi-organellar units to support metabolic adaptation and provide an experimental strategy to identify organelle-metabolic signalling hubs.

Prostaglandin E2 controls the metabolic adaptation of T cells to the intestinal microenvironment.

Immune cells must adapt to different environments during the course of an immune response. Here we study the adaptation of CD8+ T cells to the intestinal microenvironment and how this process shapes the establishment of the CD8+ T cell pool. CD8+ T cells progressively remodel their transcriptome and surface phenotype as they enter the gut wall, and downregulate expression of mitochondrial genes. Human and mouse intestinal CD8+ T cells have reduced mitochondrial mass, but maintain a viable energy balance to sustain their function. We find that the intestinal microenvironment is rich in prostaglandin E2 (PGE2), which drives mitochondrial depolarization in CD8+ T cells. Consequently, these cells engage autophagy to clear depolarized mitochondria, and enhance glutathione synthesis to scavenge reactive oxygen species (ROS) that result from mitochondrial depolarization. Impairing PGE2 sensing promotes CD8+ T cell accumulation in the gut, while tampering with autophagy and glutathione negatively impacts the T cell pool. Thus, a PGE2-autophagy-glutathione axis defines the metabolic adaptation of CD8+ T cells to the intestinal microenvironment, to ultimately influence the T cell pool.

Oncogene induced TIM-3 ligand expression dictates susceptibility to anti-TIM-3 therapy in mice.

Leukemia relapse is a major cause of death after allogeneic hematopoietic cell transplantation (allo-HCT). We tested the potential of targeting TIM-3 for improving graft-versus-leukemia (GVL) effects. We observed differential expression of TIM-3 ligands when hematopoietic stem cells overexpressed certain oncogenic-driver mutations. Anti-TIM-3 Ab-treatment improved survival of mice bearing leukemia with oncogene-induced TIM-3 ligand expression. Conversely, leukemia cells with low ligand expression were anti-TIM-3 treatment-resistant. In vitro, TIM-3 blockade or genetic deletion in CD8+ T cells (Tc) enhanced Tc activation, proliferation and IFN-γ production while enhancing GVL effects, preventing Tc exhaustion and improving Tc cytotoxicity and glycolysis in vivo. Conversely, TIM-3 deletion in myeloid cells did not affect allogeneic Tc proliferation and activation in vitro, suggesting that anti-TIM-3-treatment-mediated GVL effects are Tc-induced. In contrast to anti-PD-1 and anti-CTLA-4-treatment, anti-TIM-3-treatment did not enhance acute graft-versus-host-disease (aGVHD). TIM-3 and its ligands were frequently expressed in acute myeloid leukemia (AML) cells of patients with post-allo-HCT relapse. We deciphered the connection between oncogenic mutations found in AML and TIM-3 ligands expression and identify anti-TIM-3-treatment as a strategy to enhance GVL effects via metabolic and transcriptional Tc-reprogramming, without exacerbation of aGVHD. Our findings support clinical testing of anti-TIM-3 Abs in patients with AML relapse post-allo-HCT.

Metabolomics: Going Deeper, Going Broader, Going Further.

Metabolomics is a continuously dynamic field of research that is driven by demanding research questions and technological advances alike. In this review we highlight selected recent and ongoing developments in the area of mass spectrometry-based metabolomics. The field of view that can be seen through the metabolomics lens can be broadened by adoption of separation techniques such as hydrophilic interaction chromatography and ion mobility mass spectrometry (going broader). For a given biospecimen, deeper metabolomic analysis can be achieved by resolving smaller entities such as rare cell populations or even single cells using nano-LC and spatially resolved metabolomics or by extracting more useful information through improved metabolite identification in untargeted metabolomic experiments (going deeper). Integration of metabolomics with other (omics) data allows researchers to further advance in the understanding of the complex metabolic and regulatory networks in cells and model organisms (going further). Taken together, diverse fields of research from mechanistic studies to clinics to biotechnology applications profit from these technological developments.

Metabolic rewiring tunes dermal macrophages in staphylococcal skin infection.

The skin needs to balance tolerance of colonizing microflora with rapid detection of potential pathogens. Flexible response mechanisms would seem most suitable to accommodate the dynamic challenges of effective antimicrobial defense and restoration of tissue homeostasis. Here, we dissected macrophage-intrinsic mechanisms and microenvironmental cues that tune macrophage signaling in localized skin infection with the colonizing and opportunistic pathogen Staphylococcus aureus. Early in skin infection, the cytokine granulocyte-macrophage colony-stimulating factor (GM-CSF) produced by γδ T cells and hypoxic conditions within the dermal microenvironment diverted macrophages away from a homeostatic M-CSF- and hypoxia-inducible factor 1α (HIF-1α)-dependent program. This allowed macrophages to be metabolically rewired for maximal inflammatory activity, which requires expression of Irg1 and generation of itaconate, but not HIF-1α. This multifactorial macrophage rewiring program was required for both the timely clearance of bacteria and for the provision of local immune memory. These findings indicate that immunometabolic conditioning allows dermal macrophages to cycle between antimicrobial activity and protection against secondary infections.

Metabolic and functional remodeling of colonic macrophages in response to high-fat diet-induced obesity.

Little is known about the effects of high-fat diet (HFD)-induced obesity on resident colonic lamina propria (LP) macrophages (LPMs) function and metabolism. Here, we report that obesity and diabetes resulted in increased macrophage infiltration in the colon. These macrophages exhibited the residency phenotype CX3CR1hiMHCIIhi and were CD4-TIM4-. During HFD, resident colonic LPM exhibited a lipid metabolism gene expression signature that overlapped that used to define lipid-associated macrophages (LAMs). Via single-cell RNA sequencing, we identified a sub-cluster of macrophages, increased in HFD, that were responsible for the LAM signature. Compared to other macrophages in the colon, these cells were characterized by elevated glycolysis, phagocytosis, and efferocytosis signatures. CX3CR1hiMHCIIhi colonic resident LPMs had fewer lipid droplets (LDs) and decreased triacylglycerol (TG) content compared to equivalent cells in lean mice and exhibited increased phagocytic capacity, suggesting that HFD induces adaptive responses in LPMs to limit bacterial translocation.

Prostaglandin E 2 controls the metabolic adaptation of T cells to the intestinal microenvironment.

Immune cells must adapt to different environments during the course of an immune response. We studied the adaptation of CD8 + T cells to the intestinal microenvironment and how this process shapes their residency in the gut. CD8 + T cells progressively remodel their transcriptome and surface phenotype as they acquire gut residency, and downregulate expression of mitochondrial genes. Human and mouse gut-resident CD8 + T cells have reduced mitochondrial mass, but maintain a viable energy balance to sustain their function. We found that the intestinal microenvironment is rich in prostaglandin E 2 (PGE 2 ), which drives mitochondrial depolarization in CD8 + T cells. Consequently, these cells engage autophagy to clear depolarized mitochondria, and enhance glutathione synthesis to scavenge reactive oxygen species (ROS) that result from mitochondrial depolarization. Impairing PGE 2 sensing promotes CD8 + T cell accumulation in the gut, while tampering with autophagy and glutathione negatively impacts the T cell population. Thus, a PGE 2 -autophagy-glutathione axis defines the metabolic adaptation of CD8 + T cells to the intestinal microenvironment, to ultimately influence the T cell pool.

Hydrophobicity and charge shape cellular metabolite concentrations.

What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ~100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts.

Targeted LC-MS/MS-based metabolomics and lipidomics on limited hematopoietic stem cell numbers.

Metabolism is important for the regulation of hematopoietic stem cells (HSCs) and drives cellular fate. Due to the scarcity of HSCs, it has been technically challenging to perform metabolome analyses gaining insight into HSC metabolic regulatory networks. Here, we present two targeted liquid chromatography-mass spectrometry approaches that enable the detection of metabolites after fluorescence-activated cell sorting when sample amounts are limited. One protocol covers signaling lipids and retinoids, while the second detects tricarboxylic acid cycle metabolites and amino acids. For complete details on the use and execution of this protocol, please refer to Schönberger et al. (2022).