Patent Application
20250129334
Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
Methods of generating hematopoietic cells from differentiating source cells selected from the group consisting of induced pluripotent stem cells (iPS), cells directly reprogrammed to pre-cursors of hematopoietic cells, cells directly reprogrammed to hematopoietic cells, and adult or neonatal hematopoietic cells derived from bone marrow, cord blood, prenatal tissue (e.g. placenta), or mobilized peripheral blood.
In the developing embryo, primitive hematopoiesis gives rise to erythrocytes, megakaryocytes and macrophages in the blood islands of the yolk sac (YS) (Palis, J., Robertson, S., Kennedy, M., Wall, C. & Keller, G. Development of erythroid and myeloid progenitors in the yolk sac and embryo proper of the mouse. Development 126, 5073-5084 (1999)). Next, a definitive wave of hematopoiesis produces more mature erythro-myeloid and lymphoid (Yoder, M. C. et al. Characterization of Definitive Lymphohematopoietic Stem Cells in the Day 9 Murine Yolk Sac. Immunity 7, 335-344 (1997); and Böiers, C. et al. Lymphomyeloid Contribution of an Immune-Restricted Progenitor Emerging Prior to Definitive Hematopoietic Stem Cells. Cell Stem Cell 13, 535-548 (2013)) progenitors. Around Carnegie stage (CS) (12-13), hematopoietic stem cells (HSCs) emerge in the aorta-gonad-mesonephros (AGM) region through a second definitive hematopoietic wave (Medvinsky, A. & Dzierzak, E. Definitive Hematopoiesis Is Autonomously Initiated by the AGM Region. Cell 86, 897-906 (1996); and Ivanovs, A. et al. Highly potent human hematopoietic stem cells first emerge in the intraembryonic aorta-gonad-mesonephros region. J Exp Med 208, 2417-2427 (2011)). Primitive erythrocytes, erythro-myeloid progenitors (EMPs) and HSCs derive from a hemogenic endothelial (HE) cell (Lancrin, C. et al. The haemangioblast generates haematopoietic cells through a haemogenic endothelium stage. Nature 457, 892-895 (2009); Frame, J. M., Fegan, K. H., Conway, S. J., McGrath, K. E. & Palis, J. Definitive Hematopoiesis in the Yolk Sac Emerges from Wnt-Responsive Hemogenic Endothelium Independently of Circulation and Arterial Identity. STEM CELLS 34, 431-444 (2016); and Stefanska, M. et al. Primitive erythrocytes are generated from hemogenic endothelial cells. Sci Rep 7, 1-10 (2017)) by a process known as endothelial to hematopoietic transition (EHT) (Boisset, J.-C. et al. In vivo imaging of haematopoietic cells emerging from the mouse aortic endothelium. Nature 464, 116-120 (2010); and Kissa, K. & Herbomel, P. Blood stem cells emerge from aortic endothelium by a novel type of cell transition. Nature 464, 112-115 (2010)). Studies on hematopoietic emergence during embryonic development have not only described EHT in spatial and temporal contexts in several animal models (Boisset, J.-C. et al. In vivo imaging of haematopoietic cells emerging from the mouse aortic endothelium. Nature 464, 116-120 (2010); and Kissa, K. & Herbomel, P. Blood stem cells emerge from aortic endothelium by a novel type of cell transition. Nature 464, 112-115 (2010)) but also led to a deep understanding of the growth and transcription factors regulating this process (Chen, M. J., Yokomizo, T., Zeigler, B. M., Dzierzak, E. & Speck, N. A. Runxl is required for the endothelial to haematopoietic cell transition but not thereafter. Nature 457, 887-891 (2009); Zhou, F. et al. Tracing haematopoietic stem cell formation at single-cell resolution. Nature 533, 487-492 (2016); and Swiers, G. et al. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nat Commun 4, 2924 (2013)). Some studies of the transcriptional landscape in mouse models have hinted towards an increase in metabolic processes during HSC emergence (Zhou, F. et al. Tracing haematopoietic stem cell formation at single-cell resolution. Nature 533, 487-492 (2016); Gao, P. et al. Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells. Genes Dev. (2020) doi:10.1101/gad.338202.120; and Oatley, M. et al. Single-cell transcriptomics identifies CD44 as a marker and regulator of endothelial to haematopoietic transition. Nat Commun 11, 1-18 (2020)).
Growing evidence points to the fact that metabolic pathways can control cell fate (Oburoglu, L. et al. Glucose and Glutamine Metabolism Regulate Human Hematopoietic Stem Cell Lineage Specification. Cell Stem Cell 15, 169-184 (2014); Moussaieff, A. et al. Glycolysis-Mediated Changes in Acetyl-CoA and Histone Acetylation Control the Early Differentiation of Embryonic Stem Cells. Cell Metabolism 21, 392-402 (2015) and Folmes, C. D. L. et al. Somatic Oxidative Bioenergetics Transitions into Pluripotency-Dependent Glycolysis to Facilitate Nuclear Reprogramming. Cell Metabolism 14, 264-271 (2011)). Specifically, the fate of bone marrow (BM) HSCs is regulated by several metabolic pathways. The hypoxic niche of the BM pushes HSCs to activate a minimal energy-providing pathway, anaerobic glycolysis, and ensures their quiescent state (Takubo, K. et al. Regulation of Glycolysis by Pdk Functions as a Metabolic Checkpoint for Cell Cycle Quiescence in Hematopoietic Stem Cells. Cell Stem Cell 12, 49-61 (2013)). HSC self-renewal and maintenance rely on fatty acid oxidation (Ito, K. et al. A PML-PPAR-S pathway for fatty acid oxidation regulates hematopoietic stem cell maintenance. Nat Med 18, 1350-1358 (2012)) and differentiating HSCs switch to oxidative phosphorylation (OXPHOS) to meet their energetic requirements (Yu, W.-M. et al. Metabolic Regulation by the Mitochondrial Phosphatase PTPMT1 Is Required for Hematopoietic Stem Cell Differentiation. Cell Stem Cell 12, 62-74 (2013); and Simsek, T. et al. The Distinct Metabolic Profile of Hematopoietic Stem Cells Reflects Their Location in a Hypoxic Niche. Cell Stem Cell 7, 380-390 (2010)).
The EHT process has been modelled extensively in vitro using pluripotent stem cells (PSCs) and the HE intermediate which arises in this context can give rise to both primitive and definitive hematopoietic cells (Garcia-Alegria, E. et al. Early Human Hemogenic Endothelium Generates Primitive and Definitive Hematopoiesis In Vitro. Stem Cell Reports 11, 1061-1074 (2018)). Several studies have focused on obtaining HE with definitive potential in vitro (Kennedy, M. et al. T Lymphocyte Potential Marks the Emergence of Definitive Hematopoietic Progenitors in Human Pluripotent Stem Cell Differentiation Cultures. Cell Reports 2, 1722-1735 (2012); Sugimura, R. et al. Haematopoietic stem and progenitor cells from human pluripotent stem cells. Nature 545, 432-438 (2017); Ng, E. S. et al. Differentiation of human embryonic stem cells to HOXA+ hemogenic vasculature that resembles the aorta-gonad-mesonephros. Nature Biotechnology 34, 1168-1179 (2016) and Sturgeon, C. M., Ditadi, A., Awong, G., Kennedy, M. & Keller, G. Wnt signaling controls the specification of definitive and primitive hematopoiesis from human pluripotent stem cells. Nat Biotech 32, 554-561 (2014)), by modulating various signaling pathways, in an effort to gain further insight into definitive hematopoietic cell development to ultimately produce functional and transplantable HSCs for therapeutic use. In this study, we set out to uncover whether metabolic modulations could prompt HE cells to preferentially adopt a definitive hematopoietic fate.
As EHT implicates tight-junction dissolution, gain of stem cell-like properties and leads to extensive transcriptional and phenotypic changes in the transitioning cell (Zhou, F. et al. Tracing haematopoietic stem cell formation at single-cell resolution. Nature 533, 487-492 (2016); Swiers, G. et al. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nat Commun 4, 2924 (2013); and Guibentif, C. et al. Single-Cell Analysis Identifies Distinct Stages of Human Endothelial to-Hematopoietic Transition. Cell Reports 19, 10-19 (2017)), we hypothesized that metabolism contributes to regulating these processes. Previously, in animal models, the emergence of HSCs was shown to be regulated by adenosine signaling and the PKA-CREB pathway (Jing, L. et al. Adenosine signaling promotes hematopoietic stem and progenitor cell emergence. J Exp Med 212, 649-663 (2015); and Kim, P. G. et al. Flow-induced protein kinase A-1 CREB pathway acts via BMP signaling to promote HSC emergence. J Exp Med 212, 633-648 (2015)), which are tightly controlled by ATP levels and availability; suggesting a change in energy demand during EHT. Moreover, glucose metabolism was shown to induce HSC emergence in zebrafish (Harris, J. M. et al. Glucose metabolism impacts the spatiotemporal onset and magnitude of HSC induction in vivo. Blood 121, 2483-2493 (2013)). However, use of metabolites and metabolic pathways to drive the emergence of hematopoietic cells has not been evaluated at length during development and such mechanisms may be useful for the production of particular stem cell lineages. Therefore, there is a need for methods and compositions that utilize metabolites and/or metabolic pathways to drive stem cell differentiation.
Some embodiments relate to a method of generating a hematopoietic cell, including:
It is routine to measure glycolysis and oxidative phosphorylation, for example by using a commercially available kit. Accordingly, the preferential use of glycolysis could be assessed, for example by using a glycolysis assay kit, and comparing a source cell treated with a metabolic regulator with an appropriate control, such as a source cell that has not been treated with a metabolic regulator. Identifying a higher rate of glycolysis may indicate preferential glycolysis for the source cell treated with a metabolic regulator. On the other hand, the preferential use of oxidative phosphorylation could be assessed, and a comparison made between a source cell treated with a metabolic regulator and an appropriate control, such as a source cell that has not been treated with a metabolic regulator. Identifying a higher rate of oxidative phosphorylation may indicate preferential oxidative phosphorylation for the source cell treated with a metabolic regulator. Alternatively, both glycolysis and oxidative phosphorylation could be assessed.
In some examples, the source cell is selected from the group consisting of a hemogenic endothelial (HE) cell, an iPS cell (e.g. a differentiating iPS cell), a cell directly reprogrammed to a known pre-cursor of a hematopoietic cell, a cell directly reprogrammed to a hematopoietic cell or precursor of a hematopoietic cell, a reprogrammed cell that is subsequently further reprogrammed to a hematopoietic cell or precursor of a hematopoietic cell, an adult hematopoietic cell derived from bone marrow or mobilized peripheral blood and a neonatal hematopoietic cell derived from cord blood or prenatal tissue (e.g. placenta).
In some examples, the metabolic regulator is a molecule selected from the group consisting of a drug, a protein, an RNA based system that regulates metabolic processes and any combination thereof.
In some examples, the metabolic regulator is selected from the group consisting of a viral vector, an RNA-based system, a CRISPR/CAS-based system that regulates metabolic processes and any combination thereof.
In some examples, the metabolic regulator is also combinations of 1 or more molecules selected from the group consisting of drugs, proteins, viral vectors, RNA-based systems, CRISPR/CAS-based systems that specifically regulate metabolic processes and any combination thereof.
In some examples, the source cell is directed to glycolysis by blocking pyruvate metabolism to generate GPA+ erythroid cells. For example, by blocking pyruvate entry to the mitochondria and limiting TCA cycle activity and/or OXPHOS, GLY+ erythroid cells can be generated. Alternatively, driving TCA cycle and/or OXPHOS via feeding the source cell with pyruvate (or similar) yields CD45+ non-erythroid cells. GPA+ and GLY+ are abbreviations for glycophorin A and are used herein interchangeably.
In some examples, pyruvate is blocked from entering mitochondria, thereby inhibiting tricarboxylic acid (TCA) cycle activity. The term “inhibiting”, as used herein, is used interchangeably with “reducing”, “silencing”, “downregulating”, “suppressing” and other similar terms, and includes any level of inhibition. In certain embodiments, a level of inhibition, e.g. for a metabolic regulator described herein, can be assessed in cell culture conditions. The inhibition of TCA cycle activity may be assessed, for example, by measuring the activity of one or more enzyme involved with the TCA cycle. For example, a metabolite derived from an enzyme involved with the TCA cycle may be quantified prior to exposure to the enzyme in the TCA cycle. A decrease in that metabolite would indicate that the activity of the TCA cycle has been inhibited. Alternatively, or additionally, the metabolite derived from an enzyme involved with the TCA cycle may be quantified after exposure to the enzyme in the TCA cycle. An increase in that metabolite would indicate that the activity of the TCA cycle has been enhanced (or no change in the quantified amount may indicate that the enzyme is not inhibited).
In some examples, the metabolic regulator blocks:
In some examples, the metabolic regulator that blocks MPC is UK5099, which inhibits MPC. Inhibition of MPC may be assessed by checking the detectable levels of a metabolite (e.g. pyruvate) that is transported by MPC before and after treatment with a metabolic regulator, or by comparing detectable levels of a metabolite (e.g. pyruvate) that is transported by MPC between a source cell that has been treated with a metabolic regulator and a control source cell that has not been treated with a metabolic regulator. For example, the detection of the metabolite may be based on its quantification in the cytoplasm and/or the mitochondria of a cell (wherein a decrease from the cytoplasm indicates increased transport into the mitochondria).
In some examples, the metabolic regulator that blocks PDH is 1-AA, which inhibits PDH. PDH is a complex of three enzymes that converts pyruvate into acetyl-CoA. Therefore, in some cases, inhibition of PDH may be assessed by checking the detectable levels of pyruvate and/or acetyl-CoA before and after treatment with a metabolic regulator that blocks PDH (e.g. 1-AA), or by comparing detectable levels of pyruvate and/or acetyl-CoA between a source cell that has been treated with a metabolic regulator that blocks PDH (e.g. 1-AA) and a control source cell that has not been treated with the metabolic regulator.
In some examples, the expression of MPC subunits (MPC1 and/or MPC2) is/are downregulated using shRNAs. The downregulation of the MPC subunits may be assessed in comparison with a relevant control (i.e. a control source cell that has not been treated with a metabolic regulator). Downregulation can be quantified as a percentage of the level of MPC subunits detectable after treatment with a metabolic regulator in comparison with the level of MPC subunits prior to said treatment.
In some examples, the source cell is directed to promote OXPHOS or tricarboxylic acid (TCA) cycle activity to generate CD45+ hematopoietic cells. By “promote”, we include the meaning that a higher level of OXPHOS or TCA cycle activity is occurring following treatment with the metabolic regulator, i.e. the metabolic regulator causes the source cell to undergo a higher level of OXPHOS, or a higher level of activity in the TCA cycle.
In some examples, the metabolic regulator that promotes tricarboxylic acid (TCA) cycle activity is selected from the group consisting of dimethyl α-ketoglutarate (DMK), alpha-ketoglutarate, a related molecule and any combination thereof.
In some examples, the source cell is directed to use pyruvate via oxidative phosphorylation (OXPHOS) and the source cell is differentiated into definitive CD45+ non-erythroid cells.
In some examples, the metabolic regulator promotes pyruvate use by the TCA cycle. The promotion of pyruvate use can be assessed by measuring a starting level of pyruvate in a source cell, and comparing that measurement to the level of pyruvate following treatment with a metabolic regulator. If the level of pyruvate decreases, then the metabolic regulator promotes use of pyruvate by the TCA cycle. Alternatively, or additionally, the metabolites of pyruvate following the TCA cycle may be measured, before and after treatment with a metabolic regulator, wherein an increase in at least one metabolite of pyruvate indicates that the metabolic regulator promotes use of pyruvate by the TCA cycle. These approaches could be coupled with known assays for assessing TCA cycle activity.
In some examples, DCA or a related molecule or an shRNA is used to inhibit pyruvate dehydrogenase kinases (PDKs) and thereby promote pyruvate use by OXPHOS.
In some examples, the method includes increasing pyruvate flux into mitochondria, which amplifies acetyl-CoA production and in turn promotes cholesterol metabolism and favors definitive hematopoietic output.
In some examples, the CD45+ non-erythroid cells are lymphoid cells. In some examples, the lymphoid cells are innate lymphoid cells (ILCs), optionally selected from the group consisting of ILC1s, ILC2s, ILC3s and combinations thereof.
In some examples, the lymphoid cells are T and/or B cells.
In some examples, the lymphoid cells are NK cells.
In some examples, the lymphoid cells are NKT cells.
In some examples, the lymphoid cells are lymphoid progenitors selected from the group consisting of common lymphoid progenitors (CLPs), pro-B cells, pre-B cells, thymocyte progenitors and precursors, NK cell progenitors and precursors and any combination thereof.
Some examples relate to a method of generating hematopoietic cells, including metabolically regulating a lipid biosynthesis pathway with an inhibitor of the lipid biosynthesis pathway, and thereby obtaining hematopoietic cells (such as a GLY+ erythroid cell or a CD45+ non-erythroid cell).
In some examples, the inhibitor of the lipid biosynthesis pathway is CP-640186.
Some examples relate to a method of generating hematopoietic cells including metabolically regulating a histone acetylation pathway with an inhibitor of the histone acetylation pathway, and thereby obtaining hematopoietic cells (such as a GLY+ erythroid cell or a CD45+ non-erythroid cell).
In some examples, the inhibitor of the histone acetylation pathway is C646.
In some examples, the metabolic regulator includes an inhibitor or activator targeting glutaminolysis. Glutaminolysis is a series of reactions where the glutamine is lysed to glutamate, aspartate, CO2, pyruvate, lactate, alanine and citrate. Therefore, a metabolic regulator that is an inhibitor targeting glutaminolysis may be assessed by measuring the levels of any of the metabolites derived from the lysis of glutamine, as a comparison prior to and after treatment with a metabolic regulator (or by comparing with an untreated source cell control), wherein a decrease in the level of one or more metabolite of glutamine in the treated cell indicates that the metabolic regulator includes an inhibitor targeting glutaminolysis. On the other hand, a metabolic regulator that is an activator targeting glutaminolysis may be assessed by measuring the levels of any of the metabolites derived from the lysis of glutamine, as a comparison prior to and after treatment with a metabolic regulator (or by comparing with an untreated source cell control), wherein an increase in the level of one or more metabolite of glutamine in the treated cell indicates that the metabolic regulator includes an inhibitor targeting glutaminolysis. Alternatively, or additionally, the inhibition or activation may be assessed based on a starting concentration of detectable glutamine (i.e. a baseline or background level) prior to treatment with a metabolic regulator, and an ending concentration of detectable glutamine after treatment with a metabolic regulator, wherein a lower concentration of glutamine following treatment indicates an activator, and a higher concentration of glutamine before treatment (or no change in concentration following treatment) indicates an inhibitor.
In some examples, the method further includes metabolically regulating alpha-ketoglutarate-dependent histone and DNA methylation with an inhibitor or activator targeting alpha-ketoglutarate-dependent histone and DNA methylation. Assays for measuring DNA methylation states are known to the skilled person. Therefore, it will be readily appreciated that an inhibitor targeting alpha-ketoglutarate-dependent histone and DNA methylation results in a lower level of DNA methylation (compared with a relevant control, such as an untreated control condition); and an activator targeting alpha-ketoglutarate-dependent histone and DNA methylation results in a higher level of DNA methylation (compared with a relevant control, such as an untreated control condition).
In some examples, the method further includes metabolically regulating a glutamine-dependent pathway with an inhibitor or activator targeting the glutamine-dependent pathway. A glutamine-dependent pathway may be a pathway in which glutamine is a metabolite processed by an enzyme within the pathway. Therefore, an inhibitor or activator targeting a glutamine-dependent pathway may be assessed based on a measurement of glutamine levels before and after treatment with a metabolic regulator, wherein no change or an increase in glutamine levels following treatment indicates an inhibitor, and a decrease in glutamine levels following treatment indicates an activator.
In some examples, the glutamine-dependent pathway is selected from the group consisting of nucleotide (purine and pyrimidine) biosynthesis, glutathione synthesis and non-essential amino acid synthesis and any combination thereof.
Some examples relate to a method of generating a hematopoietic cell, including:
Some examples relate to a method of generating a hematopoietic cell, including:
Some examples relate to a method of generating a hematopoietic cell including:
Some examples relate to a method of generating a hematopoietic cell including:
Some examples relate to a method of generating a hematopoietic cell, including:
Some examples relate to a method of providing hematopoietic cells to a subject with a malignancy or hematological disorder including:
In some examples, the hematopoietic cells are modified to express chimeric antigen receptors (CAR). In some examples, the hematopoietic cells modified to express CAR are “T cells redirected for antigen-unrestricted cytokine-initiated killing”, i.e. TRUCKs (also referred to as “4th generation” CAR T cells).
In some examples, the malignancy is selected from the group consisting of leukemia (acute lymphocytic (ALL), chronic lymphocytic (CLL), acute myeloid (AML), chronic myeloid (CML)), myeloma, and lymphoma (Hodgkin's and non-Hodgkin's (NHL), Glioblastoma, glioma, pancreatic malignancies, any other malignancy where a hematopoietic cell transplant could be used) and any combination thereof.
In some examples, the source cell is treated with a molecule that increases HMG-CoA reductase to increase cholesterol biosynthesis, thereby increasing output of NK cells. An increase in HMG-CoA reductase (i.e. the activity thereof) can be assessed based on a measurement of cholesterol. HMG-CoA reductase can be the rate-limiting step in cholesterol biosynthesis in certain circumstances, and so a higher level of cholesterol (for example, following treatment with a metabolic regulator) may be indicative of an increase in HMG-CoA reductase activity. Such activity has been shown to increase the output of NK cells, i.e. the percentage of NK cells detectable in a population of source cells is higher than an untreated control, for example as assessed by flow cytometry.
In some examples, the molecule that increases HMG-CoA reductase is thyroid hormone.
In some examples, the thyroid hormone is added to the source cell during the HE stage to increase NK cell output.
Some examples relate to a population of hematopoietic cells obtained from a source cell that has been treated with a metabolic regulator that directs the source cell to preferentially use glycolysis or oxidative phosphorylation, wherein the source cell is differentiated into a GPA+ erythroid cell or a CD45+ non-erythroid cell.
Some examples relate to the population of hematopoietic cells generated by the any of methods described herein.
Some examples relate to a population of hematopoietic cells for use in treating a subject with a malignancy or hematological disorder. In some examples of the use, the hematopoietic cells are modified to express chimeric antigen receptors (CAR). In some examples, the malignancy is selected from the group consisting of leukemia (acute lymphocytic (ALL), chronic lymphocytic (CLL), acute myeloid (AML), chronic myeloid (CML)), myeloma, and lymphoma (Hodgkin's and non-Hodgkin's (NHL), Glioblastoma, glioma, pancreatic malignancies, any other malignancy where a hematopoietic cell transplant could be used) and any combination thereof. In some examples, the source cell is treated with a molecule that increases HMG-CoA reductase to increase cholesterol biosynthesis, thereby increasing output of NK cells. In some examples, the molecule that increases HMG-CoA reductase is thyroid hormone, optionally wherein the thyroid hormone is added to the source cell during the HE stage to increase NK cell output.
Other features and advantages will be apparent from the following detailed description, taken in conjunction with the accompanying drawings of which:
Examples disclosed herein relate to methods, compositions, systems, and apparatuses for modulating cell differentiation toward specific lineages, such as specific hematopoietic lineages. The examples disclosed herein are not limited to cells matured to a particular lineage, the technologies disclosed herein may be broadly applicable to different cells and tissues.
During embryonic development, hematopoiesis occurs through primitive and definitive waves, giving rise to distinct blood lineages. Hematopoietic stem cells (HSCs) emerge from hemogenic endothelial (HE) cells, through endothelial to hematopoietic transition (EHT). In the adult, HSC quiescence, maintenance and differentiation are closely linked to changes in metabolism. However, as will be described further below, the emergence of blood may be regulated by multiple metabolic pathways that induce or modulate the differentiation towards specific hematopoietic lineages during human EHT. In both in vitro and in vivo settings, steering pyruvate use towards glycolysis or OXPHOS differentially skews the hematopoietic output of HE cells towards either an erythroid fate with primitive phenotype, or a definitive lymphoid fate, respectively. In certain examples, glycolysis-mediated differentiation of HE towards primitive erythroid hematopoiesis may be dependent on the epigenetic regulator LSD1. In examples, OXPHOS-mediated differentiation of HE towards definitive hematopoiesis may be dependent on cholesterol metabolism. As will be understood by one of skill in the art and explained further below, during EHT, metabolism may be a major regulator of primitive versus definitive hematopoietic differentiation.
Metabolic regulators that may cause preferential use of pyruvate by glycolysis include inhibitors of mitochondrial pyruvate carrier (MPC) (e.g., UK5099, also known as 2-Cyano-3-(1-phenyl-1H-indol-3-yl)-2-propenoic acid and PF-1005023), inhibitors of pyruvate dehydrogenase complex (PDH) (1-AA, i.e. aminoethylphosphinic acid), and shRNA inhibitors of MPC. UK5099 may be used at a concentration of 10 μM but may also be used at concentrations of 1 μM, 5 μM, 20 μM, 50 μM or 100 μM. 1 AA may be used at a concentration of 4 mM but may also be used at concentrations of 0.1 mM, 0.5 mM, 1 mM, 10 mM, 20 mM or 50 mM.
Metabolic regulators that may cause preferential use of pyruvate by oxidative phosphorylation include dichloroacetate (DCA) and shRNA inhibitors of pyruvate dehydrogenase kinases (PDK). DCA may be used at a concentration of 3 mM but may also be used at a concentration of 0.1 mM, 0.5 mM, 1 mM, 5 mM, 10 mM or 30 mM (or any range between these concentrations). For example, the DCA may be used at a concentration ranging from 0.1 mM to 30 mM, such as from 1 mM to 10 mM, or from 3 mM to 10 mM. In some embodiments, the metabolic regulator is CP, which may be used at a concentration of 2.5 μM but may also be used at a concentration of 1 μM, 1.5 μM, 2 μM, 3 μM, 3.5 μM, 4 μM, 4.5 μM or 5 μM (or any range between these concentrations). For example, the CP may be used at a concentration ranging from 1 μM to 5 μM, such as from 1.5 μM to 3.5 μM, or 2 μM to 3 μM. In some embodiments, the metabolic regulator is cholesterol, which may be used at a 0.5× concentration of a cholesterol lipid concentration, such as provided by Thermo Fisher 12531018 (250×), but may also be used at a 0.1×, 0.2×, 0.3×, 0.4×, 0.6× 0.7×, 0.8×, 0.9× or 1× concentration (or any range between these concentrations). For example, the cholesterol may be used at a concentration range from 0.1× to 1×, such as from 0.2× to 0.8×, or 0.4× to 0.6×.
Metabolic regulators that may cause preferential use of oxidative phosphorylation via glutamine metabolism pathway include derivatives of alpha-ketoglutarate such as dimethyl-α-ketoglutarate. Dimethyl-α-ketoglutarate may be used at a concentration of 1 mM but may also be used at concentrations of 0.1 mM, 0.5 mM, 1.5 mM, 2 mM, 5 mM or 10 mM (or any range between these concentrations). For example, the dimethyl-α-ketoglutarate may be used at a concentration ranging from 0.1 mM to 10 mM, such as from 1 mM to 10 mM, from 1 mM to 5 mM, or from 2 mM to 5 mM.
Techniques for determining changes in metabolic pathways are known to the skilled person, such as those described in the Examples herein. For example, promoting OXPHOS may be assessed based on an increased expression of at least one OXPHOS-related gene compared with a control, for example as per
Techniques for modifying hematopoietic cells to express a chimeric antigen receptor (CAR) are known in the art. The CAR may be introduced to the source cell prior to, during, and/or after treatment with the metabolic regulator. Preferably, the CAR may be introduced to the source cell (e.g. iPSC-CD34+) prior to treatment with a metabolic regulator, as the CAR expression is then passed down to daughter cells that derive from the source cell following cell expansion. Therefore, one can obtain CAR-NK cells that have been enhanced by the metabolic regulator treatment. Alternatively, the CAR may be introduced following enrichment of NK cells that derive from the source cells treated with a metabolic regulator. Alternatively, the CAR may be introduced at an intermediate stage between the aforementioned.
As demonstrated in the examples below, in embodiments during EHT, transitioning cells go through substantial changes in energy use and metabolism, with simultaneous increases in glycolysis and TCA cycle/OXPHOS. In certain examples, glucose may play a role in both glycolysis and the TCA cycle, and blocking its use with 2-DG may impair hematopoietic differentiation of HE cells. In quiescent HSCs, glycolysis may be regulated by hypoxia through the stabilization of hypoxia-inducible factor-1α (HIF-1α). In certain embodiments, the transition from HE to HSCs may also be regulated by HIF-1α. HIF1α may be a regulator of hematopoietic progenitor and stem cell development in hypoxic sites of the mouse embryo. Therefore, as will be understood by one of skill in the art, in embodiments, HIF-1α-dependent induction of glycolysis may be required for EHT.
In certain embodiments, glycolysis may be sufficient to provide energy for primitive hematopoiesis. At early embryonic stages, oxygen is not systemically available, and glycolysis may be the pathway of choice to produce energy. In developing embryos, primitive erythroid cells may perform high rates of glycolysis to fuel their rapid proliferation. In some embodiments, boosting glycolysis by blocking pyruvate entry into the mitochondria redirects HE differentiation towards primitive erythropoiesis at a very early stage of EHT, as shown by an increased frequency of erythroid transcription factor-expressing cells at the single cell level as well as higher levels of erythroid factors and embryonic/fetal-specific globins.
The examples below indicate a role for the TCA cycle and OXPHOS in preferentially inducing definitive hematopoietic identity. For example, fueling the TCA cycle with DCA treatment may lead to an increased differentiation of HE cells toward a definitive CD45+ lineage. While PDK inhibition with DCA may not affect primitive erythroid cell formation, it may induce definitive hematopoiesis, as measured by increased lymphoid lineage biases which we have shown both in vitro and in vivo. In embodiments, DCA-treatment of HE cells leads to an increased lymphoid reconstitution including T cells in NSG mice, therefore pyruvate may be able to not only modulate erythroid and lymphoid lineage outputs but also primitive and definitive states of HE-derived cells. In certain examples, DCA promotes Notch1-dependent CD45+ cell formation by fueling cholesterol biosynthesis in HE cells. Moreover, the accumulation of cholesterol in HE cells may lead to an increase in the expression of cholesterol efflux genes. Indeed, cholesterol efflux mechanisms have been previously shown to regulate HSPC proliferation. In certain embodiments, ATP-binding cassette transporters and HDL suppress hematopoietic stem cell proliferation and therefore HE cells transitioning to become HSPCs may express higher levels of cholesterol efflux genes. Consequently, as will be understood by one of skill in the art, a direct metabolic change in HE cells, namely increased acetyl-CoA content, can promote cholesterol metabolism and control definitive hematopoietic output.
Distinct EHT cell subsets or pre-HSCs can present different lineage propensities. Considering the examples below, in certain embodiments, metabolism can influence the differentiation of HE cells, suggesting that lineage propensities may be decided at the HE level. In line with this connection, a recent study combining scRNAseq with lentiviral lineage tracing revealed that cell fate biases appear at a much earlier stage during hematopoietic development than previously described with conventional methods. Murine HSCs may present lymphoid or myeloid hematopoietic lineage biases due to epigenetic priming which is established prior to their formation. Linking epigenetic changes to metabolism is a newly emerging field which reconciliates metabolic alterations with transcriptional regulation of cellular processes. In certain embodiments here, we show here that erythroid fate induction by MPC inhibition is dependent on an epigenetic factor, LSD1. As will be understood by one of skill in the art, additional epigenetic modifications that are occurring concomitantly to the metabolic changes in EHT may contribute to specify cell fate.
The examples described below indicate that the lineage propensities of primitive and definitive hematopoietic waves may be shaped by nutrient availability in the YS and AGM niches. Due to scarcity of oxygen in early embryonic stages, the primitive hematopoietic wave may depend on glycolysis to form erythroid cells expressing embryonic globins with high affinity for oxygen (
In certain embodiments, use of metabolic modulators to direct definitive HSC development in vitro from PSCs may provide a basis to produce transplantable cells, able to reconstitute the hematopoietic system of patients with hematological malignancies and disorders. For example, hematologic malignancies are cancers that affect the blood, bone marrow, and lymph nodes. This classification includes various types of leukemia (acute lymphocytic (ALL), chronic lymphocytic (CLL), acute myeloid (AML), chronic myeloid (CML)), myeloma, and lymphoma (Hodgkin's and non-Hodgkin's (NHL)).
We disclose the production of off-the-shelf hematopoietic cells or derived cells and/or products for therapeutics.
In certain embodiments, pyruvate may be blocked from entering the mitochondria, thereby reducing tricarboxylic acid (TCA) cycle activity. The metabolic regulator used for blocking may be a mitochondrial pyruvate carrier (MPC) and/or a pyruvate dehydrogenase complex (PDH). UK5099 may be used to inhibit MPC, while 1-AA may be used to inhibit PDH. In some embodiments, the expression of MPC subunits (MPC1 and/or MPC2) is/are downregulated using shRNAs.
In some embodiments, the source cell may be directed to use pyruvate via oxidative phosphorylation (OXPHOS) and the source cell may be differentiated into CD43+CD45+ non-erythroid cells by definitive hematopoietic differentiation. Such pyruvate use may be blocked by any suitable metabolic regulator disclosed herein. In embodiments, DCA or a related molecule or an shRNA may be used to inhibit pyruvate dehydrogenase kinases (PDKs) and thereby promote pyruvate use by OXPHOS. Pyruvate flux into the mitochondria may then be increased, thereby amplifying acetyl-CoA production and in turn promoting cholesterol metabolism and favoring non-erythroid hematopoietic output. Dimethyl α-ketoglutarate (DMK) or a related molecules may also be used to promote glutamine metabolism pathway feeding of the tricarboxylic activity/oxidative phosphorylation.
In embodiments, metabolic regulation of a method for generating hematopoietic calls such as described herein may include inhibitors of the lipid biosynthesis pathway, such as CP-640186 and related molecules.
In certain examples, metabolic regulation may include inhibitors of histone acetylation pathway, C646 and related molecules.
As will be understood by one of skill in the art, a method of reconstituting a hematopoietic system in a subject with a hematological malignancy or disorder such as described herein may involve any of the cells disclosed herein, such as the cells described in relation to
Any patents and applications and other references noted herein, including any that may be listed in accompanying filing papers, are incorporated herein by reference. Aspects of the disclosure can be modified, if necessary, to employ the systems, functions, and concepts of the various references described herein to provide yet further implementations.
Features, materials, characteristics, or groups described in conjunction with a particular aspect, embodiment, or example are to be understood to be applicable to any other aspect, embodiment or example described herein unless incompatible therewith. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or all of the steps of any method or process so disclosed, may be combined in any combination, except combinations where at least some of such features or steps are mutually exclusive. The protection is not restricted to the details of any foregoing embodiments. The protection extends to any novel one, or any novel combination, of the features disclosed in this specification (including any accompanying claims, abstract and drawings), or to any novel one, or any novel combination, of the steps of any method or process so disclosed.
While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of protection. Indeed, the novel methods and systems described herein may be embodied in a variety of other forms. Furthermore, various omissions, substitutions and changes in the form of the methods and systems described herein may be made. Those skilled in the art will appreciate that in some embodiments, the actual steps taken in the processes illustrated or disclosed may differ from those shown in the figures. Depending on the embodiment, certain of the steps described herein may be removed, others may be added. For example, the actual steps or order of steps taken in the disclosed processes may differ from those shown in the figure. Depending on the embodiment, certain of the steps described herein may be removed, others may be added. Furthermore, the features and attributes of the specific embodiments disclosed herein may be combined in different ways to form additional embodiments, all of which fall within the scope of the present disclosure.
Although the present disclosure includes certain embodiments, examples and applications, it will be understood by those skilled in the art that the present disclosure extends beyond the specifically disclosed embodiments to other alternative embodiments or uses and obvious modifications and equivalents thereof, including embodiments which do not provide all of the features and advantages set forth herein. Accordingly, the scope of the present disclosure is not intended to be limited by the described embodiments, and may be defined by claims as presented herein or as presented in the future.
Conditional language, such as “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements, or steps. Thus, such conditional language is not generally intended to imply that features, elements, or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without user input or prompting, whether these features, elements, or steps are included or are to be performed in any particular embodiment. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list. Likewise the term “and/or” in reference to a list of two or more items, covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list. Further, the term “each,” as used herein, in addition to having its ordinary meaning, can mean any subset of a set of elements to which the term “each” is applied. Additionally, the words “herein,” “above,” “below,” and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application.
Conjunctive language such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to convey that an item, term, etc. may be either X, Y, or Z. Thus, such conjunctive language is not generally intended to imply that certain embodiments require the presence of at least one of X, at least one of Y, and at least one of Z.
Language of degree used herein, such as the terms “approximately,” “about,” “generally,” and “substantially” as used herein represent a value, amount, or characteristic close to the stated value, amount, or characteristic that still performs a desired function or achieves a desired result. For example, the terms “approximately”, “about”, “generally,” and “substantially” may refer to an amount that is within less than 10% of, within less than 5% of, within less than 1% of, within less than 0.1% of, and within less than 0.01% of the stated amount. As another example, in certain embodiments, the terms “generally parallel” and “substantially parallel” refer to a value, amount, or characteristic that departs from exactly parallel by less than or equal to 15 degrees, 10 degrees, 5 degrees, 3 degrees, 1 degree, or 0.1 degree.
The scope of the present disclosure is not intended to be limited by the description of certain embodiments and may be defined by the claims. The language of the claims is to be interpreted broadly based on the language employed in the claims and not limited to the examples described in the present specification or during the prosecution of the application, which examples are to be construed as non-exclusive.
Various modifications to the implementations described in this disclosure may be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other implementations without departing from the spirit or scope of this disclosure. Thus, the disclosure is not intended to be limited to the implementations shown herein, but is to be accorded the widest scope consistent with the principles and features disclosed herein. Certain embodiments of the disclosure are encompassed in the claim set listed below or presented in the future.
Appendix 1 is a publication of Applicants work entitled “Pyruvate metabolism guides definitive lineage specification during hematopoietic emergence”, EMBO Reports, Volume 23, Issue 2: e54384, 3 Feb. 2022 (Published Online Dec. 16, 2021).
Certain embodiments of the disclosure are encompassed in the claims presented at the end of this specification, or in other claims presented at a later date.
The following non-limiting examples serve to illustrate various aspects of the disclosure.
To combine both primitive and definitive hematopoietic waves in cultures, two previously described small molecules were combined during human iPSC differentiation (
Next, we verified the hematopoietic potential of both HE and EHT populations. Both cell types gave rise to hematopoietic cells (CD43+) (
In order to describe the metabolic processes occurring in EHT populations, we first assessed glycolysis in HE, EHT and HSC-like cells. We observed a gradual increase in glycolytic capacity and glycolysis with differentiation (
To understand whether glycolytic activity is required during EHT, we treated HE cells with a glucose analog, 2-Deoxy-D-glucose (2-DG), which blocks glycolysis (
Along with increased glycolysis and proliferation, HSC-like cells also had increased glucose uptake compared to HE and EHT cells (
As we have shown that HE cells take up glucose at similar levels as EHT cells (
Although the levels of total CD43+ cells were unchanged between UK5099-treated and untreated conditions at day 6 (
To complement these findings, we sought to induce an opposite effect by increasing pyruvate flux into mitochondria to promote TCA cycle activity and OXPHOS. Using DCA, we blocked PDKs which repress the PDH complex: this allows pyruvate to be converted to acetyl-CoA and potentially fuel the TCA cycle (
Following 3 or 6 days of MPC inhibition with UK5099 in HE cells, we found that erythroid colony (CFU-E) formation was significantly increased compared to the untreated condition, while granulocyte and macrophage colonies were decreased (CFU-G, GM and M) (
Thyroid hormone increases hepatic HMG-CoA reductase levels by acting to increase both transcription and stability of the mRNA. HMG-CoA reductase is a molecule that catalyzes a rate limiting step in cholesterol biosynthesis. Thyroid hormone acts on liver cells in the body. It is well known that some blood cells have the thyroid hormone receptor, which is well known to be involved in red blood cell production. Therefore, the thyroid hormone receptor is likely to be present on other blood cells and the hemogenic endothelium.
To verify these findings in an in vivo setting, we injected pregnant mice with UK5099 or DCA at embryonic day (E) 9.5 (
Furthermore, while the frequency of phenotypic long-term HSCs (LT-HSCs) defined as LSK CD48−CD150+ (
In order to assess definitive hematopoietic potential of iPSC-derived cells, we intravenously injected 3-day DCA-treated HE cells co-cultured with OP9-DL1 stroma into irradiated NSG mice (
Since we did not see a difference in the frequency of HSC-like cells in vitro (
In order to dissect the molecular effects of pyruvate manipulation on HE cells, we assessed the transcriptomic profiles of these cells at an early time point of treatment (day 2), at the single cell level, in control and UK5099- or DCA-treated cells. First, we grouped all conditions together and separated the cells into 7 clusters (
Focusing on isolated clusters 6 and 7 (
We found that while the percentage of cells in cluster 6 was constant between conditions, there were 38% more UK5099-treated HE cells and 35% less DCA-treated HE cells in cluster 7 compared to the control (
We then confirmed that, in clusters 6 and 7, the average expression levels of erythroid lineage genes RYK, KLF3, TAL1, GATA2, ZFPM1, KLF1, NFE2, ANK1 and HBQ1 were higher in UK5099-treated HE cells as compared to the untreated HE cells and these factors were nearly absent in DCA-treated HE cells (left-hand dot plot,
Previous studies have shown that Lysine-Specific Demethylase 1 (LSD1) is essential for EHT and particularly the erythroid lineage (Takeuchi, M. et al. LSD1/KDM1A promotes hematopoietic commitment of hemangioblasts through downregulation of Etv2. PNAS 112, 13922-13927 (2015); and Thambyrajah, R. et al. GFI1 proteins orchestrate the emergence of haematopoietic stem cells through recruitment of LSD1. Nat Cell Biol 18, 21-32(2016)). During EHT, LSD1 acts in concert with HDAC1/2 (Thambyrajah, R. et al. HDAC1 and HDAC2 Modulate TGF-β Signaling during Endothelial-to-Hematopoietic Transition. Stem Cell Reports 10, 1369-1383 (2018)) and GFI1/GFI1B (Thambyrajah, R. et al. GFI1 proteins orchestrate the emergence of haematopoietic stem cells through recruitment of LSD1. Nat Cell Biol 18, 21-32 (2016)) to induce epigenetic changes. We confirmed that HDACs are essential for EHT using an HDAC1/2 inhibitor (Trichostatin A, TSA) which impaired the emergence of CD43+ hematopoietic cells, as CD43 levels only reached an intermediate level, suggesting a block during EHT (
Dichloroacetate may be directly used as a precursor of acetylation marks: acetate is converted to acetyl-CoA by ACSS2 and transferred onto histones via histone acetyltransferases (HATs) (
NK cell anti-tumour activity can occur via cytotoxic degranulation. CD107 is a marker that is present in the cytotoxic vesicles of NK cells, and so is not expressed on the cell surface of inactivated NK cells. However, upon NK cell activation and degranulation, the CD107 target becomes detectable on the cell surface. Therefore, the level of CD107 detected on NK cells correlates with cytotoxic degranulation. In this assay, several exemplary metabolic regulators were used to assess cytotoxic degranulation in a co-culture assay with K562 cells (an exemplary cancer cell model). As a negative control, iPSC-CD34+ untreated with a metabolic regulator were used, in which a basal level of 3.27% of degranulated NK cells (CD3−CD56+CD16+CD107+ cells) were observed (
hiPSC Culture, Hematopoietic Differentiation and Cell Isolation
The RB9-CB1 human iPSC line (Woods, N.-B. et al. Brief report: efficient generation of hematopoietic precursors and progenitors from human pluripotent stem cell lines. Stem Cells 29, 1158-1164 (2011)) was co-cultured with mouse embryonic fibroblasts (MEFs, Millipore), passaged every six days and processed to form embryoid bodies (EBs) as described previously (Guibentif, C. et al. Single-Cell Analysis Identifies Distinct Stages of Human Endothelial to-Hematopoietic Transition. Cell Reports 19, 10-19 (2017)). The differentiation protocol used in this study was previously described (Ditadi, A. & Sturgeon, C. M. Directed differentiation of definitive hemogenic endothelium and hematopoietic progenitors from human pluripotent stem cells. Methods 101, 65-72 (2016)), however, small modifications were made to induce both primitive and definitive hematopoiesis, as indicated below and in
Sorted HE (40,000), EHT (30,000) and HSC-like (5-20,000) cells were plated onto Matrigel (16 μg/cm2, Corning)-coated 96-well flat bottom plates in HE medium with 1% penicillin-streptomycin and kept in a humidified incubator at 37° C., 5% C02, 4% 02 overnight. The following day (day 0), wells were washed twice with PBS and fresh HE medium was added, together with 2-DG (1 mM), UK5099 (10 μM), DCA (3 mM or 10 mM), TSA (60 nM), TCP (300 nM), ACSS2i (5 μM), C646 (10 μM), CP-640186 (5 μM) or Atorvastatin (0.5 μM), where indicated. Media was changed and drugs were added every 2 days and cells were kept in a humidified incubator at 37° C., 5% CO2, 20% O2 for 6-7 days. Pictures were taken using an Olympus IX70 microscope equipped with a CellSens DP72 camera and CellSens Standard 1.6 software (Olympus). For single cell subcultures, single HE cells were directly sorted with a BD FACSAriaIII onto OP9-DL1 stroma in flat-bottom 96-well plates with 120 μl OP9 medium (OptiMEM medium with Glutamax (Invitrogen) with 10% FCS, 1% penicillin-streptomycin solution (Thermo Fisher Scientific) and 1% 2-mercaptoethanol (Invitrogen)) with SCF, IL-6, IL-11, IGF1 and EPO, and with or without 10 μM UK, or 3 mM or 10 mM DCA. The cells were kept in a humidified incubator at 37° C., 5% CO2, 4% O2 and media was replaced every 4 days. At day 14, the wells were collected and scored for GPA+ clones by flow cytometry, using a BD LSRII.
For comparisons between HE, EHT and HSC-like cells, day 10 FACS-sorted cells (≥40,000) were directly plated onto Seahorse XF96 Cell Culture Microplate wells coated with CellTak (0.56 μg/well) in 2-4 replicates and extracellular flux was assessed immediately on a Seahorse XF96 analyzer. For comparisons between HE and EHT cells, day 8 FACS-sorted cells (≥40,000) were plated onto Matrigel (16 μg/cm2, Corning)-coated Seahorse XF96 Cell Culture Microplate wells in 3-4 replicates and extracellular flux was assessed 2 days after plating, on a Seahorse XF96 analyzer. To assess glycolytic flux, ECAR was measured in XF medium with 2 mM glutamine under basal conditions (after 1-hour glucose starvation as per manufacturer's instructions) as well as after the addition of 25 mM glucose, 4 μM oligomycin and 50 mM 2-DG and data was normalized to cell number. The levels of glycolytic capacity (ECARoligomycin−ECAR2-DG) and glycolysis (ECARglucose−ECAR2-DG) were calculated. To assess oxidative phosphorylation, OCR was measured in XF medium with 10 mM glucose, 2 mM glutamine and 1 mM sodium pyruvate under basal conditions as well as after the addition of 4 μM oligomycin, 2 μM Carbonyl cyanide 4-(trifluoromethoxy)phenylhydrazone (FCCP) and 1 μM rotenone/40 μM Antimycin A and data was normalized to cell number. The levels of basal respiration (OCRbasal−OCRRotenone/AntimycinA), ATP-production (OCRbasal−OCROligomycin) and maximal respiration (OCRFCCP−OCRRotenone/AntimycinA) were calculated.
On days 3 and 6 of subculture, cells were collected after a 2-minute incubation at 37° C. with StemPro Accutase Cell Dissociation Reagent and stained with CD34-FITC, CD14-PE, CD33-PC7, CD11b-APC, CD45-AF700, CD43-APCH7, GPA-eF450, CD90-BV605 and the viability marker 7AAD and fluorescence was measured on a BD LSRII. To measure mitochondrial activity, cells were incubated with Tetramethylrhodamine ethyl ester (TMRE, 20 nM) for 30 minutes at 37° C. Negative controls were incubated with 100 μM FCCP for 30 minutes at 37° C., prior to TMRE staining. Fluorescence was measured on a BD FACSARIA III and MFI levels—MFI FMO were calculated. To measure glucose uptake, cells were incubated with 2-(N-(7-Nitrobenz-2-oxa-1,3-diazol-4-yl)Amino)-2-Deoxyglucose (2-NBDG) for 30 minutes at 37° C. and fluorescence was measured on a BD FACSARIA III. To measure proliferation, cells were processed with the CellTrace Violet (CTV) kit according to manufacturer's instructions (10-minute incubation) and fluorescence was measured on a BD LSRFortessa. To measure EdU incorporation, HE cells were assessed on day 1 or 2 of subculture after 24 h EdU pulses, using Click-iT EdU Flow Cytometry Cell Proliferation Assay (Thermo Fisher Scientific, C10424), according to manufacturer's instructions. Flow cytometry outputs were analyzed on FlowJo Software, with initial gatings on SSC-A/FSC-A, FSC-H/FSC-A, SSC-H/SSC-A and 7-AAD to exclude doublets and dead cells in all experiments.
Subcultured HE cells were treated with StemPro Accutase Cell Dissociation Reagent for 2 minutes at 37° C. and dissociated cells were resuspended in 3 ml Methocult H4230 (STEMCELL Technologies, France) (prepared according to manufacturer's instructions, with 20 mL Iscove's Modified Dulbecco's Medium containing 2.5 μg hSCF, 5 μg GM-CSF, 2.5 μg IL-3 and 500 U EPO). Each mixture was divided onto 2 wells of a non-tissue culture treated 6-well plate. Following a 12-day incubation in a humidified incubator at 37° C., 5% CO2, 20% O2, colonies were morphologically distinguished and scored. For globin analysis, colonies in Methocult wells were harvested with PBS, washed thoroughly and frozen in RLT buffer with β-mercaptoethanol. Following RNA extraction and RT (Qiagen), gene expression was assessed with taqman probes by q-PCR. The taqman probes used for this assay are HBA1/2 (Hs00361191_g1), HBE1 (Hs00362216_m1), HBG2/1 (Hs00361131_g1) and KLF1 (Hs00610592_m1).
Subculture day 3 HE cells cultured in the presence of UK5099 (10 μM) or DCA (3 mM or 10 mM), as indicated, were collected after a 2-minute incubation at 37° C. with StemPro Accutase Cell Dissociation Reagent and seeded onto 80% confluent OP9-DL1 stroma. Cells were cultured in OP9 medium (OptiMEM medium with Glutamax (Invitrogen) with 10% FCS, 1% penicillin-streptomycin solution (Thermo Fisher Scientific) and 1% 2-mercaptoethanol (Invitrogen)) with SCF (10 ng/ml), FLT3-L (10 ng/ml), IL-2 (5 ng/ml), IL-7 (5 ng/ml, first 15 days only) and IL-15 (10 ng/ml) with passaging onto new OP9-DL1 stroma every week, as described previously (Renoux, V. M. et al. Identification of a Human Natural Killer Cell Lineage-Restricted Progenitor in Fetal and Adult Tissues. Immunity 43, 394-407 (2015)). At day 35 of co-culture, cells were analyzed on a BD LSRFortessa.
Sorted HE, EHT and HSC-like cells as well magnetically selected (Miltenyi Biotec) cord blood CD34+ cells were plated onto Matrigel (16 μg/cm2, Corning)-coated 96-well flat bottom plates in HE medium (Ditadi, A. & Sturgeon, C. M. Directed differentiation of definitive hemogenic endothelium and hematopoietic progenitors from human pluripotent stem cells. Methods 101, 65-72 (2016)) with 1% penicillin-streptomycin and kept in a humidified incubator at 37° C., 5% CO2, 4% O2 overnight. The following day (day 0), wells were washed twice with PBS and fresh HE medium was added, together with UK5099 (10 μM) or DCA (3 mM), where indicated. On day 1 and 2 (as indicated), cells were washed twice with PBS 0.04% UltraPure BSA and collected after a 2-minute incubation at 37° C. with StemPro Accutase Cell Dissociation Reagent. Cells were spun down, resuspended in PBS 0.04% UltraPure BSA, counted (yield between 8,000-18,000 cells) and library preparation was conducted according to the Chromium Single Cell 3′ Reagent kit v3 instructions (10× Genomics). Sequencing was performed on a NOVASeq 6000 from Illumina with the run parameters (28-8-0-91) recommended by 10× Genomics with a final loading concentration of 300 pM of the pooled libraries. Human Umbilical Cord Blood samples were collected from Skine University Hospital (Lund and Malmo) and Helsingborg Hospital with informed consents according to guidelines approved by the regional ethical committee.
The data was processed and analyzed using Seurat v3.1.0, where cells were allowed to have up to 20% mitochondrial reads prior to log-normalization and finding the top 500 variable genes using the “vst” method. Cell cycle scores were calculated and the data was scaled regressing on mitochondrial content and the difference of the S and G2M score. Principal components were calculated prior to calculating a UMAP. Pseudotime trajectories describing two developmental routes were identified in our EHT dataset using Slingshot (Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19,477 (2018)) along which the cells were ordered. The cells were then binned along each trajectory where the cell type composition of each bin was calculated as percentages. Cord blood CD34+ cells were mapped to our data and labeled using scCoGAPS (Stein-O'Brien, G. L. et al. Decomposing Cell Identity for Transfer Learning across 23 Cellular Measurements, Platforms, Tissues, and Species. Cell Syst 8, 395-411.e8 (2019)). CS13 data from Zeng et al. (Zeng, Y. et al. Tracing the first hematopoietic stem cell generation in human embryo by single-cell RNA sequencing. Cell Res 1-14 (2019)) was read and processed to make a UMAP from which the cells they name as “AEC” and “Hem” were identified. These 99 cells were mapped to our data and labeled using SCMAP59. Carnegie Stage 13 data from Zeng et al. was mapped to our EHT dataset using scCoGAPS where 10 patterns were identified, named according to their respective weights (as shown in Table 1) and then projected using projectR. Table 1 shows how we have generated cells from iPS that have the same expression profiles as those published by Zeng et al. in the actual human embryo. This demonstrates that our in vitro protocol to generate developmentally relevant hematopoietic cells and precursors is excellent in that it recapitulates what happens in the embryo. The CS 13 dorsal aorta dataset from Zeng et al. was mapped onto our EHT dataset using scCoGAPS. The patterns resulting from this analysis were classified as the cell types described by Zeng et al.
Each cell was assigned to the group that achieved the highest weight. An overview showing the relationship between cell-types and patterns was done by forming a contingency table on which correspondence analysis was performed using the ca package for R Differentially expressed genes were found using the FindAllMarkers function. Cell numbers for day 1 samples are as follows: HE=1451, EHT=1523, HSC-like=732. Cell numbers for day 2 samples are as follows: HE ctrl=1195, HE+UK5099=718, HE+DCA=2309. All assessed endothelial and hematopoietic genes were previously used in several publications to validate the EHT process (Zhou, F. et al. Tracing haematopoietic stem cell formation at single-cell resolution. Nature 533, 487-492 (2016); Swiers, G. et al. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nat Commun 4, 2924 (2013); Ng, E. S. et al. Differentiation of human embryonic stem cells to HOXA+ hemogenic vasculature that resembles the aorta-gonad-mesonephros. Nature Biotechnology 34, 1168-1179 (2016); and Guibentif, C. et al. Single-Cell Analysis Identifies Distinct Stages of Human Endothelial to-Hematopoietic Transition. Cell Reports 19, 10-19 (2017)). For gene expression analyses, gene sets for glycolysis, oxidative phosphorylation and cholesterol efflux were downloaded from The Molecular signatures Database (MSigDB).
Downregulation Via shRNAs
Short-hairpin sequences recognizing the genes of interest were cloned into GFP-expressing pRRL26 SFFV vectors, embedded in a microRNA context for minimal toxicity, as described previously (Fellmann, C. et al. An Optimized microRNA Backbone for Effective Single-Copy RNAi. Cell Reports 5, 1704-1713 (2013)). Each lentivirus batch was produced in two T175 flasks of HEK 293T cells by co-transfecting 22 μg of pMD2.G, 15 μg of pRSV-Rev, 30 μg of pMDLg/pRRE and 75 μg of the shRNA vector using 2.5 M CaCl2. Medium was changed 16 hours after transfection and viruses were harvested 48 hours after transfection, pelleted at 20,000×g for 2 hours at 4° C., resuspended in 100 μl DMEM, aliquoted and kept at −80° C. The downregulation efficiency of each shRNA was measured by assessing the corresponding gene expression by qPCR in sorted GFP+ cells, 3 days after lentiviral transduction of cord blood CD34+ HSPCs. The taqman probes used for this assay are MPC1 (Hs00211484_m1), MPC2 (Hs00967250_m1), PDK1 (Hs01561847_m1), PDK2 (Hs00176865_m1), PDK3 (Hs00178440_m1), PDK4 (Hs01037712_m1), LSD1/KDM1A (Hs01002741_m1) and HPRT1 (Hs02800695_m1). HE cells were transduced by direct addition of lentivirus particles into the culture medium on the day after the sort.
For fetal liver analysis, pregnant female C57Bl/6xB6.SJL mice were injected intraperitoneally at E9.5 with UK5099 (4 mg/kg) or DCA (200 mg/kg) or PBS (control). Embryos were harvested at E14.5 and individually weighed and processed. Fetal livers were dissected and homogenised in 800 μL ice cold PBS supplemented with 2% fetal bovine serum (FBS) and FL cells were washed in PBS with 2%/FBS. For the differentiated lineage panel, cells were stained with B220 and CD19 (B-cell markers)-PE, CD3e-APC, Ter119-PeCy7 and CD71-FITC and analyzed on a BD FACSARIA III. For the HSC panel, samples were first treated with ammonium chloride solution (STEMCELL Technologies, France) to lyse red blood cells, washed twice in ice cold PBS with 2% FBS, stained with CD3e, B220, Ter119, Gr1 (Lineage)-PeCy5, c-Kit-Efluor780, Sca1-BV421, CD48-FITC, CD150-BV605 and 7-AAD (for dead cell exclusion) and analyzed on a BD FACSARIA III. Flow cytometry outputs were analyzed on FlowJo Software, with initial gatings on SSC-A/FSC-A and FSC-H/FSC-A to exclude doublets. For plating of CFU assays, 100 LT-HSCs were sorted (gating strategy shown in
Sorted human HE cells (350,000) were mixed with OP9-DL1 stroma (60,000) and subcultured for 3 days with or without DCA (3 mM) on Matrigel (16 μg/cm2, Corning)-coated 12-well plates in HE medium (32). Between 100,000-150,000 cells from control or DCA samples were transplanted into sub lethally irradiated (300 cGy) 8-week-old female NOD/Cg-Prkdcscid Il2tm1Wj1/SzJ mice (NSG, The Jackson Laboratory) together with 20,000 whole BM support cells from C57BV6.SJL mice (CD45.1+/CD45.2+, in house breeding). Cells were transplanted in single cell solution in 250 μL PBS with 2% FBS through intravenous tail vein injection. Drinking water of transplanted NSG mice was supplemented with ciprofloxacin (125 mg/L, HEXAL) for 3 weeks after transplantation to prevent infection. Mice were housed in a controlled environment with 12-hour light-dark cycles with chow and water provided ad libitim. Experiments and animal care were performed in accordance with the Lund University Animal Ethical Committee.
Peripheral Blood Analysis after NSG Mice Transplantations
Peripheral blood (PB) was collected from the tail vein into EDTA-coated microvette tubes (Sarstedt, Cat #20.1341.100). Peripheral blood was lysed for mature erythrocytes in ammonium chloride solution (STEMCELL technologies) for 10 minutes at room temperature, washed and stained for cell surface antibodies for 45 minutes at 4° C., washed and filtered prior to flow cytometry analysis on the FACS AriaIII (BD). Flow cytometry outputs were analyzed on FlowJo Software, with initial gatings on SSC Oburoglu et al. A/FSC-A and FSC-H/FSC-A for doublet exclusion, on DAPI for dead cell exclusion and on huCD45/muCD45.1 for murine cell exclusion.
Bone Marrow Analysis after NSG Mice Transplantations
Bone marrow was analyzed at the 12-week transplantation endpoint. Mice were euthanized by spinal dislocation followed by the dissection of both right and left femurs, tibias and iliac bones. Bone marrow was harvested through crushing with a pestle and mortar and cells were collected in 20 mL ice-cold PBS with 2% FBS, filtered and washed (350×g, 5 min). Bone marrow cells were lysed for red blood cells (ammonium chloride solution, STEMCELL technologies) for 10 minutes at room temperature, washed and stained for cell surface antibodies for 45 minutes at 4° C., washed and filtered prior to FACS analysis on the FACS AriaIII (BD). Flow cytometry outputs were analyzed on FlowJo Software, with initial gatings on SSC-A/FSC-A and FSC-H/FSC-A for doublet exclusion, on DAPI or 7AAD for dead cell exclusion and on huCD45/muCD45.1 for murine cell exclusion.
Thymus Analysis after NSG Mice Transplantations
Whole thymus was harvested at the 12-week transplantation endpoint. The thymocytes were mechanically dissociated from connective tissue in the thymus by pipetting up and down in PBS with 2% FBS, followed by filtration through a 50 μm sterile filter. Erythrocyte contamination was removed by lysing the sample in ammonium chloride solution (STEMCELL technologies) for 10 minutes at room temperature. Samples were washed and spun down after and the pellet of thymocytes was resuspended in FACS buffer and stained for cell surface antibodies for 45 minutes at 4° C., washed and filtered prior to FACS analysis on the FACS AriaIII (BD). Flow cytometry outputs were analyzed on FlowJo Software, with initial gatings on SSC-A/FSC-A and FSC-H/FSC-A for doublet exclusion, on DAPI for dead cell exclusion and on huCD45/muCD45.1 for murine cell exclusion.
For TMRE staining, on day 3 of subculture, half of the culture medium was removed and cells were stained with 20 nM TMRE (Thermo Fisher Scientific, T669) by direct addition into the culture medium of a 2× concentrated solution. After a 20-minute incubation at 37° C., wells were carefully washed with PBS and fresh HE medium was added. During acquisition, cells were kept in a humidified incubator at 37° C., 5% CO2, 20% O2. For immunocytochemistry, subculture day 2 HE cells (plated on coverslips) were washed twice in PBS, fixed with 4% PFA for 15 minutes at RT and washed three times with PBS. For filipin staining, fixed cells were incubated with 100 μg/ml filipin III (Sigma-Aldrich, F4767) for 1 hour, washed three times with PBS and rinsed with distilled water before mounting with PVA/DABCO. For H3K9 and H4 acetylation staining, fixed cells were permeabilized and blocked 1 hour at RT with PBS+0.25% Triton X-100+5% normal donkey serum (blocking solution) followed by incubation overnight at 4° C. with primary antibodies diluted in blocking solution. Cells were then washed 2×5 min with PBS+0.25% Triton X-100 (TPBS) and 5 min with blocking solution before incubation with secondary antibodies 2 hours at RT diluted in blocking solution. Cells were later washed 5 min with TPBS containing 1 μg/ml Hoechst and twice with PBS before being rinsed with distilled water and mounted with PVA:DABCO. Images were obtained with the 10× (TMRE) or 20× (Filipin and acetylation) objective of a Zeiss LSM 780 confocal microscope using the Zen software and a 1.5× zoom (TMRE) or 0.6× zoom (Filipin and acetylation). Acquisition settings were the same for all images of each experiment, taking the same number of stacks. Intensity quantification was performed using the Fiji software as follows. For TMRE, using the brightfield channel, ROIs were selected for 5 spindle shaped and 5 round cells (randomly chosen) and average intensity for each ROI was calculated in a summatory Z-stack of the TMRE channel. For filipin and acetylation, the summatory Z-stack for the filipin channel was obtained and average intensity calculated. A total of 2-3 independent experiments with 2-3 replicate wells were quantified. For each replicate well, 4-6 images were acquired.
Significance of differences between conditions were calculated using paired/unpaired t-tests, 1/2-way analysis of variance (ANOVA) tests or Kruskal-Wallis tests with multiple comparisons in GraphPad Prism 6 software, as indicated. p values are indicated in figures with the following abbreviations: ns, not significant, *p<0.05, **p<00.01, ***p<0.001, ****p<0.0001.
The single cell RNA sequencing data presented herein is available in the GEO database under the accession number GSE141189.
The present application also provides aspects according to the following paragraphs:
1. A method of generating a hematopoietic cell, comprising:
2. The method of paragraph 1, wherein the source cell is selected from the group consisting of a hemogenic endothelial (HE) cell, an iPS cell (such a differentiating iPS cell), a cell directly reprogrammed to a known pre-cursor of a hematopoietic cell, a cell directly reprogrammed to a hematopoietic cell or precursor of a hematopoietic cell, a reprogrammed cell that is subsequently further reprogrammed to a hematopoietic cell or precursor of a hematopoietic cell, an adult hematopoietic cell derived from bone marrow or mobilized peripheral blood and a neonatal hematopoietic cell derived from cord blood or prenatal tissue (e.g. placenta).
3. The method of paragraph 1, wherein the metabolic regulator is a molecule, a drug, protein, or RNA based system that regulates metabolic processes.
4. The method of paragraph 1, wherein the metabolic regulator is a viral vector, or an RNA-based system, or CRISPR/CAS-based system that regulates metabolic processes.
5. The method of paragraph 1, wherein the metabolic regulator is also combinations of 1 or more molecules, drugs, proteins, viral vectors, RNA-based systems, or CRISPR/CAS-based systems that specifically regulate metabolic processes.
6. The method of paragraph 1, wherein the source cell is directed to use pyruvate via glycolysis to generate GPA+ erythroid cells.
7. The method of paragraph 6, wherein pyruvate is blocked from entering mitochondria, thereby inhibiting tricarboxylic acid (TCA) cycle activity.
8. The method of paragraph 6, wherein the metabolic regulator is used to block:
9. The method of paragraph 8, wherein UK5099 is used to inhibit MPC.
10. The method of paragraph 8, wherein 1-AA is used to inhibit PDH.
11. The method of paragraph 8, wherein the expression of MPC subunits (MPC1 and/or MPC2) is/are downregulated using shRNAs.
12. The method of paragraph 1, wherein the source cell is directed to promote OXPHOS or tricarboxylic acid (TCA) cycle activity to generate CD45+ hematopoietic cells.
13. The method of paragraph 12, wherein the metabolic regulator that promotes tricarboxylic acid (TCA) cycle activity is dimethyl α-ketoglutarate (DMK), alpha-ketoglutarate, or a related molecule.
14. The method of paragraph 12, wherein the source cell is directed to use pyruvate via oxidative phosphorylation (OXPHOS) and the source cell is differentiated into definitive CD45+ non-erythroid cells.
15. The method of paragraph 12, wherein the metabolic regulator promotes pyruvate use by the TCA cycle.
16. The method of paragraph 12, wherein DCA or a related molecule or an shRNA is used to inhibit pyruvate dehydrogenase kinases (PDKs) and thereby promote pyruvate use by OXPHOS.
17. The method of paragraph 12 comprising increasing pyruvate flux into mitochondria, which amplifies acetyl-CoA production and in turn promotes cholesterol metabolism and favors definitive hematopoietic output.
18. The method of paragraph 12, wherein the CD45+ non-erythroid cells are lymphoid cells.
19. The method of paragraph 18, wherein the lymphoid cells are T and/or B cells.
20. The method of paragraph 18, wherein the lymphoid cells are NK cells.
21. The method of paragraph 18, wherein the lymphoid cells are NKT cells.
22. The method of paragraph 18, wherein the lymphoid cells are lymphoid progenitors including common lymphoid progenitors (CLPs), pro-B cells, pre-B cells and thymocytes and NK cell progenitors and precursors.
23. A method of generating hematopoietic cells, comprising metabolically regulating a lipid biosynthesis pathway with an inhibitor of the lipid biosynthesis pathway.
24. The method of paragraph 23, wherein the inhibitor of the lipid biosynthesis pathway is CP-640186.
25. A method of generating hematopoietic cells comprising metabolically regulating a histone acetylation pathway with an inhibitor of the histone acetylation pathway.
26. The method of paragraph 25, wherein the inhibitor of the histone acetylation pathway is C646.
27. The method of paragraph 1, wherein the metabolic regulator includes an inhibitor or activator targeting glutaminolysis.
28. The method of paragraph 1, further comprising metabolically regulating alpha-ketoglutarate-dependent histone and DNA methylation with an inhibitor or activator targeting alpha-ketoglutarate-dependent histone and DNA methylation.
29. The method of paragraph 1, further comprising metabolically regulating a glutamine-dependent pathway with an inhibitor or activator targeting the glutamine-dependent pathway.
30. The method of paragraph 29, wherein the glutamine-dependent pathway is selected from the group consisting of nucleotide (purine and pyrimidine) biosynthesis, glutathione synthesis and non-essential amino acid synthesis.
31. A method of generating a hematopoietic cell, comprising:
32. A method of generating a hematopoietic cell, comprising:
33. A method of generating a hematopoietic cell comprising:
34. A method of generating a hematopoietic cell comprising:
35. A method of generating a hematopoietic cell, comprising:
36. A method of providing hematopoietic cells to a subject with a malignancy or hematological disorder comprising:
37. The method of paragraph 36, wherein the hematopoietic cells are modified to express chimeric antigen receptors (CAR).
38. The method of paragraph 36, wherein the malignancy is selected from the group consisting of leukemia (acute lymphocytic (ALL), chronic lymphocytic (CLL), acute myeloid (AML), chronic myeloid (CML)), myeloma, and lymphoma (Hodgkin's and non-Hodgkin's (NHL), Glioblastoma, glioma, pancreatic malignancies, or any other malignancy where a hematopoietic cell transplant could be used).
39. The method of paragraph 20, wherein the source cell is treated with a molecule that increases HMG-CoA reductase to increase cholesterol biosynthesis, thereby increasing output of NK cells.
40. The method of paragraph 39, wherein the molecule that increases HMG-CoA reductase is thyroid hormone.
41. The method of paragraph 40, wherein the thyroid hormone is added to the source cell during the HE stage to increase NK cell output.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2130271-6 | Oct 2021 | SE | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/EP2022/077490 | 10/3/2022 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 63307937 | Feb 2022 | US | |
| 63365223 | May 2022 | US |
