Endothelium‐derived lactate is required for pericyte function and blood–brain barrier maintenance

Article3 March 2022free access Transparent process Endothelium-derived lactate is required for pericyte function and blood–brain barrier maintenance Heon-Woo Lee Heon-Woo Lee orcid.org/0000-0002-0620-6937 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Contribution: Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, ​Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Yanying Xu Yanying Xu Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China Contribution: Conceptualization, Data curation, Software, Formal analysis, Validation, ​Investigation, Visualization, Methodology Search for more papers by this author Xiaolong Zhu Xiaolong Zhu orcid.org/0000-0002-1894-8727 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Contribution: ​Investigation, Visualization Search for more papers by this author Cholsoon Jang Cholsoon Jang Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA Contribution: Software, Formal analysis, ​Investigation Search for more papers by this author Woosoung Choi Woosoung Choi orcid.org/0000-0002-8017-3838 School of Life Sciences and Cell Logistics Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea Contribution: Data curation, Software, ​Investigation, Visualization Search for more papers by this author Hosung Bae Hosung Bae orcid.org/0000-0001-5848-7972 Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA Contribution: Software, Formal analysis, ​Investigation Search for more papers by this author Weiwei Wang Weiwei Wang W. M. Keck Biotechnology Resource Laboratory, Yale University School of Medicine, New Haven, CT, USA Contribution: Data curation, Software, Formal analysis, Validation Search for more papers by this author Liqun He Liqun He orcid.org/0000-0003-2127-7597 Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden Contribution: Software, Formal analysis, Validation Search for more papers by this author Suk-Won Jin Suk-Won Jin Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA School of Life Sciences and Cell Logistics Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea Contribution: Supervision, ​Investigation, Visualization Search for more papers by this author Zoltan Arany Zoltan Arany Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Contribution: Supervision Search for more papers by this author Michael Simons Corresponding Author Michael Simons [email protected] orcid.org/0000-0003-0348-7734 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Department of Cell Biology, Yale University School of Medicine, New Haven, CT, USA Contribution: Conceptualization, Supervision, Funding acquisition, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Heon-Woo Lee Heon-Woo Lee orcid.org/0000-0002-0620-6937 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Contribution: Conceptualization, Resources, Data curation, Software, Formal analysis, Validation, ​Investigation, Visualization, Methodology, Writing - original draft, Writing - review & editing Search for more papers by this author Yanying Xu Yanying Xu Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China Contribution: Conceptualization, Data curation, Software, Formal analysis, Validation, ​Investigation, Visualization, Methodology Search for more papers by this author Xiaolong Zhu Xiaolong Zhu orcid.org/0000-0002-1894-8727 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Contribution: ​Investigation, Visualization Search for more papers by this author Cholsoon Jang Cholsoon Jang Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA Contribution: Software, Formal analysis, ​Investigation Search for more papers by this author Woosoung Choi Woosoung Choi orcid.org/0000-0002-8017-3838 School of Life Sciences and Cell Logistics Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea Contribution: Data curation, Software, ​Investigation, Visualization Search for more papers by this author Hosung Bae Hosung Bae orcid.org/0000-0001-5848-7972 Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA Contribution: Software, Formal analysis, ​Investigation Search for more papers by this author Weiwei Wang Weiwei Wang W. M. Keck Biotechnology Resource Laboratory, Yale University School of Medicine, New Haven, CT, USA Contribution: Data curation, Software, Formal analysis, Validation Search for more papers by this author Liqun He Liqun He orcid.org/0000-0003-2127-7597 Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden Contribution: Software, Formal analysis, Validation Search for more papers by this author Suk-Won Jin Suk-Won Jin Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA School of Life Sciences and Cell Logistics Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea Contribution: Supervision, ​Investigation, Visualization Search for more papers by this author Zoltan Arany Zoltan Arany Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA Contribution: Supervision Search for more papers by this author Michael Simons Corresponding Author Michael Simons [email protected] orcid.org/0000-0003-0348-7734 Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA Department of Cell Biology, Yale University School of Medicine, New Haven, CT, USA Contribution: Conceptualization, Supervision, Funding acquisition, Writing - original draft, Project administration, Writing - review & editing Search for more papers by this author Author Information Heon-Woo Lee1,†, Yanying Xu1,2,†, Xiaolong Zhu1, Cholsoon Jang3, Woosoung Choi4, Hosung Bae3, Weiwei Wang5, Liqun He6, Suk-Won Jin1,4, Zoltan Arany7 and Michael Simons *,1,8 1Yale Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT, USA 2Department of Cardiovascular Medicine, Xiangya Hospital, Central South University, Changsha, China 3Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA 4School of Life Sciences and Cell Logistics Research Center, Gwangju Institute of Science and Technology (GIST), Gwangju, Korea 5W. M. Keck Biotechnology Resource Laboratory, Yale University School of Medicine, New Haven, CT, USA 6Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden 7Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 8Department of Cell Biology, Yale University School of Medicine, New Haven, CT, USA † These authors contributed equally to this work *Corresponding author. Tel: +1 203 737 4643; E-mail: [email protected] The EMBO Journal (2022)41:e109890https://doi.org/10.15252/embj.2021109890 See also: M Castro & M Potente (May 2022) PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions Figures & Info Abstract Endothelial cells differ from other cell types responsible for the formation of the vascular wall in their unusual reliance on glycolysis for most energy needs, which results in extensive production of lactate. We find that endothelium-derived lactate is taken up by pericytes, and contributes substantially to pericyte metabolism including energy generation and amino acid biosynthesis. Endothelial–pericyte proximity is required to facilitate the transport of endothelium-derived lactate into pericytes. Inhibition of lactate production in the endothelium by deletion of the glucose transporter-1 (GLUT1) in mice results in loss of pericyte coverage in the retina and brain vasculatures, leading to the blood–brain barrier breakdown and increased permeability. These abnormalities can be largely restored by oral lactate administration. Our studies demonstrate an unexpected link between endothelial and pericyte metabolisms and the role of endothelial lactate production in the maintenance of the blood–brain barrier integrity. In addition, our observations indicate that lactate supplementation could be a useful therapeutic approach for GLUT1 deficiency metabolic syndrome patients. Synopsis The contribution of circulating nutrients and metabolic pathways to crosstalk between endothelial cells and neurovascular pericytes remains ill-defined. Here, lactate secreted by endothelial cells is identified as a principle source of carbons fueling pericyte metabolism and maintaining blood-brain barrier integrity. Endothelium-derived lactate is utilized for energy production and amino acid synthesis by pericytes in the CNS vasculature in mice. Loss of GLUT1 in endothelial cells reduces lactate secretion and pericyte coverage, increasing blood brain barrier permeability. MCT5 and MCT12 are lactate transporters responsible for shuttling lactate between endothelial cells and pericytes. Introduction Vascular integrity and the dynamic control of permeability are crucial to normal organ functions. Structurally, vascular integrity is maintained by formation of endothelial cell–cell junctions that can open and close in response to various signals. Another important element is the extent of pericyte coverage of blood vessels. Pericytes wrap around capillary and venular endothelial cells and share the basement membrane with the endothelium, thereby ensuring close physical and paracrine contacts between these two cell types. Pericytes are particularly important in the central nervous system (CNS) where they help to maintain the blood–brain barrier (BBB) (Armulik et al, 2010) and regulate microvascular blood flow (Yamanishi et al, 2006). A deficiency of pericytes in the CNS results in the BBB breakdown and death (Hellstrom et al, 2001; Armulik et al, 2010; Nikolakopoulou et al, 2019). While endothelial–pericyte communications are clearly important, their nature is not fully understood. Endothelial cells (ECs) are unusual in their reliance on glycolysis as the primary means of energy generation (Krutzfeldt et al, 1990; De Bock et al, 2013a; Schoors et al, 2014; Kim et al, 2017; Yu et al, 2017a; Faulkner et al, 2020). The hallmark of glycolysis is the production of large amounts of lactate and, indeed, most of endothelial glucose (~90%) is catabolized to lactate and secreted as lactate extracellularly (Kim et al, 2017). With this much endothelial lactate entering the extracellular space, a significant amount of lactate would be expected to be present in the inner basement membrane space shared by ECs and pericytes, thereby making endothelial cells-produced lactate available to pericytes. It was the purpose of this study to identify the metabolic fate of endothelium-derived lactate in pericyte metabolism and the role of this metabolic crosstalk in maintenance of vascular homeostasis. Several studies have shown that lactate can be used as fuel while quantitative analysis of lactate fluxes in mice suggests that it can be the primary source of carbons for the TCA cycle in a number of tissues (van Hall, 2010; Hui et al, 2017; Brooks, 2018; Jin et al, 2019). In the brain, lactate accounts for ~10–20% of energy generation under normal condition but that can rise to 60% when the lactate transporter is fully saturated (Boumezbeur et al, 2010; Hui et al, 2017). At the cellular level, neurons (Waagepetersen et al, 1998; Descalzi et al, 2019), fibroblasts (Shen et al, 2020), macrophages (Liu et al, 2020b; Zhang et al, 2020), and cancer cells (Bonuccelli et al, 2010) have all been reported to utilize lactate for energy generation albeit few details of this process are understood. We found that lactate is an important source of carbons for pericyte metabolism and that it contributes directly to energy generation and amino acid biogenesis in these cells. Endothelial lactate export is mediated by MCT1 and MCT5 transporters while pericytes utilize MCT12 to import lactate. In the absence of endothelium-derived lactate, pericytes in the CNS vasculature undergo apoptotic cell death resulting in impaired BBB and increased permeability while oral lactate supplementation can restore both pericyte coverage and the BBB integrity. These observations point to the crucial role of endothelial lactate in endothelium-pericyte communications and maintenance of the BBB integrity. Results Deficiency of GLUT1 in ECs inhibits glucose uptake, glycolysis, and ATP production The 14-member family of glucose transporters (GLUTs) plays an important role in cellular glucose uptake and glucose homeostasis in mammals (Bertrand et al, 2020). To study the expression of glucose transporters in ECs, we took advantages of the publicly available endothelial scRNAseq atlas (EC atlas) (Kalucka et al, 2020). Analysis of the atlas data suggested that Glut1 is the predominant glucose transporter in brain ECs (Appendix Fig S1A). This was confirmed by immunostaining of the brain and retinal vasculature that showed high level and EC specificity of Glut1 expression (Appendix Fig S1B and C). To explore the role of GLUT1 in the endothelium, we first examined glucose uptake after GLUT1 knockdown (siGLUT1) in BMECs (Appendix Fig S2A) using 2-deoxy-2-[(7-nitro-2,1,3-benzoxadiazol-4-yl)amino]-d-glucose (2-NBDG), a fluorescence-labeled glucose analog. As expected, there was a significant reduction in the number of 2-NBDG positive cells following GLUT1 knockdown (Appendix Fig S2B–D) compared to control siRNA-treated BMECs (siCON). Next, we evaluated the effect of GLUT1 knockdown on the extracellular acidification rate (ECAR) during sequential treatment with glucose, oligomycin, and 2-DG. While control (siCON) BMECs were able to increase ECAR after glucose treatment, indicating glycolytic activity, it was significantly decreased in siGLUT1-treated ECs (Appendix Fig S2E and F). The subsequent treatment with oligomycin triggered a further increase in ECAR in siCON-treated ECs, revealing preserved glycolytic capacity, while no comparable increase was observed in siGLUT1-treated BMECs (Appendix Fig S2E and G). With 2-DG treatment, we found there was a strong reduction in glycolytic reserve in siGLUT1-treated compared to siCON-treated BMECs (Appendix Fig S2E and H). To investigate whether these changes in glycolytic activity following GLUT1 KD affected ATP production, we measured total ATP level and mitochondrial (mitoATP) and glycolytic (glycoATP) ATP production rates using a Seahorse analyzer. As expected, both total ATP and glycoATP production were decreased in siGLUT1-treated ECs (Appendix Fig S2I). However, mitoATP production was increased, suggesting that an increase in oxidative phosphorylation is compensating for the decreased glycolytic ATP production (Appendix Fig S2I). Deficiency of GLUT1 in ECs inhibits angiogenesis and vascular integrity A previous study using a Glut1 chemical inhibitor (BAY-876) reported reduced proliferation but not migration of endothelial cells in culture (Veys et al, 2020). In agreement with these data, siRNA-mediated Glut1 knockdown also inhibited endothelial proliferation (Appendix Fig S3A and B). However, we observed a reduction in EC migration following GLUT1 KD (Appendix Fig S3C and D). As expected with the observed decrease in migration, there was a profound reduction in the number of filopodia in siGLUT1-treated BMECs (Appendix Fig S3E and F) and Glut1-deleted tipECs in retinal vasculature (Appendix Fig S3G and H). To further investigate the role of GLUT1 in vivo, we generated endothelial-specific inducible Glut1 knockout mice (Glut1fx/fxCdh5(PAC)CreERT2, hereafter denoted Glut1iECKO) (Appendix Fig S4A–C). We first analyzed the effect of endothelial Glut1 deletion on angiogenesis using retinal vasculature. Neonatal littermates (WT, Glut1iEC+/fx (Glut1 haplodeficient mice in EC) and Glut1iECKO) were intraperitoneally injected with tamoxifen at P1 (postnatal day 1) and P2, and vasculature was observed at P6.5 using retinal whole mounts. Isolection-B4 staining showed a gene dose-dependent reduction in angiogenic outgrowth (Appendix Fig S5A and B). Consistent with a previous report using an inducible PDGFβ-Cre-driven Glut1 deletion mice (Veys et al, 2020), our Glut1iECKO mice also displayed severe weight loss (Appendix Fig S5C) and lethality (Appendix Fig S5D) starting on P6 with all mice dying by P15. Endothelial Glut1 deletion in fully mature 8-week-old mice also resulted in universal lethality with similar kinetics (Appendix Fig S5E). To further evaluate the effect of endothelial Glut1 deletion on blood vessels, we examined pericyte coverage in Glut1iECKO and control mice. Immunostaining showed a striking reduction in pericyte coverage in the retinal vasculature of P6 Glut1iECKO compared to wild-type littermates (Fig 1A and B). The analysis of the retinal and brain vasculature in adult mice (8-weeks old) 10 days after induction of endothelial GLUT1 deletion also showed a significant reduction in pericyte coverage (Appendix Fig S6A and B and Fig 1C and D) while SMC coverage was not altered (Fig 1C and E). In addition, a tight junction protein (claudin 5) was absent in the brain vasculature of Glut1iECKO mice (Fig 1F) suggesting that the pericyte loss is affecting the integrity of the BBB. To investigate the mechanism of the pericyte loss, we performed immunostaining for apoptotic cell death marker (cleaved caspase-3) and found caspase-3-positive pericytes in Glut1iECKO mice showing that the loss of pericytes is mediated by apoptotic cell death (Fig 1G). Figure 1. Loss of GLUT1 in EC decreases pericyte coverage on the vasculature and alters BBB permeability Retinal whole mount immunostaining for Isolectin-B4 (red) and Desmin (green) in WT (top panel) and Glut1iECKO (bottom panel) mice showing pericyte coverage in the vasculature. Left and right panels show representative images with 20× or 63× magnification, respectively. Quantification of the pericytes coverage in the retinal vasculature of WT (blue) and Glut1iECKO (orange) mice. (n = 9 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Immunostaining for CD31 (green), CD13 (white; pericyte marker) and αSMA (cyan) using paraffin section from WT (top panel) and Glut1iECKO (bottom panel) mice. Quantification of the pericytes coverage using CD13 immunostaining in the brain vasculature of WT (blue) and Glut1iECKO (orange) mice. (n = 7 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Quantification of the smooth muscle cell coverage using αSMA immunostaining in the brain vasculature of WT (blue) and Glut1iECKO (orange) mice. (n = 13 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Immunostaining for Cldn5 (green) and CD31 (red) using a brain section of WT (top panel) and Glut1iECKO (bottom panel) mice. Immunostaining for caspas-3 (green), CD13 (red) and CD31 (cyan) using a brain section of WT (top panel) and Glut1iECKO (bottom panel) mice. Permeability assay using vibratome section showing the leakage of retro-orbital injected cadaverine dye (red) in the brain of WT (top panel) and Glut1iECKO (bottom panel) mice. DAPI staining (white) shows the boundary of brain section. Permeability assay using vibratome section showing the leakage of retro-orbital injected cadaverine dye (red) in the brain of WT (top panel) and Glut1iECKO (bottom panel) mice. Note that cadaverine is retained in the intravascular area of WT mice (upper panel), but extravasated and accumulated in the brain parenchyma (white arrowheads) of Glut1iECKO (bottom panel) mice. Representative confocal images of fibrin (green), CD31 (red) and DAPI (blue) immunostaining in the brain vasculature of WT (top panel) and Glut1iECKO (bottom panel) mice. Quantification of the number of cadaverine 555 positive brain parenchyma cells in WT (blue) and Glut1iECKO (orange) mice. (n = 13 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Quantification of extravascular fibrin deposits in WT (blue) and Glut1iECKO (orange) mice. (n = 9 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Quantification of lactate in the cerebrospinal fluid of WT (blue) and Glut1iECKO (orange) mice. (n = 3 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Download figure Download PowerPoint Since the absence of pericytes in the vasculature results in increased permeability (Armulik et al, 2010), and given that the deletion of Glut1 in ECs causes pericyte depletion, we sought to determine whether there was an increase in permeability of the brain vasculature in Glut1iECKO mice. To this end, we tested extravascular accumulation of an exogenous fluorescent dye (cadaverine) and endogenous plasma protein (fibrin). Retroorbital cadaverine injection demonstrated a significantly higher appearance of the dye in the brain of Glut1iECKO compared to wild-type littermates (Fig 1H). While cadaverine was retained almost exclusively intravascularly in WT mice, large amounts were observed in the brain parenchyma of Glut1iECKO mice (Fig 1I and K). Similarly, there was a marked increase in extravascular fibrin in the brains of Glut1iECKO mice compared with wild-type littermates (Fig 1J and L). Finally, we examined whether Glut1 deficiency in ECs affects endothelial permeability. Staining of an endothelial monolayer for VE-cadherin showed no changes in its localization or the appearance of adherence junctions in siGLUT1-treated BMECs (Appendix Fig S7A and B) and in vitro permeability assay using FITC-dextran also showed no differences in permeability between siCON and siGLUT1-treated BMECs (Appendix Fig S7C). This indicates that the altered BBB permeability in Glut1iECKO mice is not caused by endothelial autonomous phenotype, but by pericyte loss. Reduced concentration of lactate in the cerebrospinal fluid (CSF) is one of the key abnormalities in patients with GLUT1 mutations (De Vivo et al, 1991). In agreement with these data, measurements of CSF lactate level demonstrated a significant reduction in Glut1iECKO mice compared to wild-type littermates (Fig 1M). The CSF lactate reduction and pericyte loss in Glut1iECKO mice imply that lactate plays an important role to maintain pericyte coverage. Endothelium-derived lactate feeds pericytes Proper interaction with endothelial cells is essential for recruitment and migration of pericytes along blood vessels (Armulik et al, 2005; Yang et al, 2011). Since endothelial cells produce and release large amount of lactate into the vasculature (De Bock et al, 2013a; Kim et al, 2017) and given their close physical proximity to pericytes, we tested whether endothelial lactate plays an important role in pericyte biology. To check whether pericytes utilize endothelium-derived lactate, we used Laconic, a Forster Resonance Energy Transfer (FRET)-based quantitative intracellular lactate sensor (San Martin et al, 2013). HBVPs (human brain vascular pericytes) were infected with the Laconic-expressing adenovirus and cultured in a presence of the glycolysis inhibitor (iodoacetic acid, 500 nM) to minimize basal glycolytic lactate production. As expected, increasing lactate concentration, from 2 to 100 mM, led to a dose-dependent increase in the mTFP/Venus fluorescence ratio (Fig 2A and B). To study whether EC-derived lactate is taken up by pericytes, we used a two-well cell culture dish to coculture BMECs and HBVPs (Fig 2C). Both dish chambers were seeded with, respectively, BMECs and Laconic-expressing HBVPs. Once the cells were attached (24 h after seeding), the culture insert was removed, allowing cell migration to take place (Fig 2D). When examined after another 24 h, we observed a striking increase in the mTFP/Venus fluorescence ratio in HBVPs in direct contact with ECs but not in HBVPs cells that were not in contact with the ECs (Fig 2E–G). Given that a knockdown of GLUT1 in ECs reduced their glycolysis, we further explored whether endothelial glycolysis affects lactate transport into pericytes. HBVPs in contact with siGLUT1-treated BMECs showed markedly reduced mTFP/Venus fluorescence ratio than HBVPs in contact with siCON-treated EC (Fig 2H and I). Taken together, those data indicate that ECs-derived lactate can enter pericytes and that this process is facilitated by endothelial–pericyte proximity. Figure 2. Endothelium-derived lactate feed pericytes Quantification of the mTFP/Venus fluorescence ratio of laconic (lactate sensor) showing concentration-dependent lactate uptake in HBVPs. (n = 8 from 3 independent experiments. Error bars indicate the standard error of the mean (SEM)). Representative images showing mTFP (blue) and Venus (yellow) fluorescence in control and lactate (20 mM)-treated HBVPs. Schematic illustration for the lactate uptake assay with 2 well chamber. Cells were seeded on a glass bottom dish. BMECs and adenoviral laconic-infected HBVPs were separated by 2 well chamber. After attachment, the 2 well chamber was removed for cell migration. Schematic illustration for the lactate uptake assay after chamber removal. At 24 h after chamber removal, the fluorescence of mTFP and Venus were observed in the middle of the wells (yellow area). Representative stitched image showing mTFP (green), Venus (yellow), DAPI (blue) and ERG1/2/3 (purple) fluorescence from BMECs and laconic-infected HBVPs on a 2 well chamber. Representative images (high magnification; 60×) showing mTFP (cyan), Venus (yellow) and VECAD (purple) fluorescence from BMECs and laconic-infected HBVPs on a 2 well chamber. The upper panel shows HBVPs with endothelial contact and the lower panel shows HBVPs without endothelial contact. Quantification of the mTFP/Venus fluorescence ratio of laconic in HBVPs with endothelial contact (EC-PC contact) or HBVPs alone (PC only). (n = 16 from independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Representative images showing mTFP (cyan) and Venus (yellow) fluorescence in HBVPs which have direct contact with control (upper panel) or GLUT1 (lower panel) siRNA-treated BMECs. VECAD immunostaining (purple) was used for endothelial staining. Quantification of the mTFP/Venus fluorescence ratio of laconic in HBVPs which have direct contact with control (siCON) or GLUT1 (siGLUT1) siRNA-treated BMECs (n = 12 from independent experiments. Error bars indicate the standard error of the mean (SEM) from unpaired Student’s t test). Download figure Download PowerPoint Pericytes utilize lactate for oxygen consumption and pyruvate synthesis We next explored the metabolic role of lactate in various vascular and nonvascular cell types. First, we evaluated the effect of lactate supplementation on oxygen consumption rate (OCR) to test whether cells use lactate for mitochondrial oxidation. Only HBVPs and mouse brain pericytes (mBPs), but not human aortic smooth-muscle cells (HASMCs), human brain microvascular endothelial cells (BMECs), or fibroblasts (3T3L1) increased their OCR rate (Fig 3A). Importantly, pericyte OCR was increased in a lactate concentration-dependent manner (Fig 3B). Furthermore, lactate treatment also increased OCR in HBVPs even in the presence of other nutrients such as glucose (5 mM), pyruvate (0.5 mM), and glutamine (0.5 mM) (Fig 3C). In agreement with these data, mass spectroscopy analysis demonstrated increase in ATP in HBVPs following lactate treatment (Fig 3D and Appendix Fig S8A and B). Figure 3. Lactate induces oxygen consumption in pericytes Quantification of oxygen consumption rate (OCR) showing the effect of lactate treatment on the respiration (induced) in various cells including HBVP, mBP, HASMC, BMEC and 3T3L1. The media was changed into glucose-, pyruvate- and glutamine-free media before OCR measurement and lactate (2 mM)