Metabolic Mechanisms in Physiologic and Pathologic Oxygen

METABOLIC MECHANISMS IN PHYSIOLOGIC AND PATHOLOGIC OXYGEN

SENSING

OLIVIA ROSE STEPHENS

Submitted in partial fulfillment of the requirements for the degree of

Doctor of Philosophy

Department of Molecular Medicine

CASE WESTERN RESERVE UNIVERSITY

August 2019

CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES We hereby approve the thesis/dissertation of

OLIVIA ROSE STEPHENS

candidate for the degree of Doctor of Philosophy*.

Committee Chair Prasad Sathyamangla, PhD

Thesis Advisor Serpil Erzurum, MD

Clinical Mentor Kristin Highland, MD

Committee Member Bela Anand-Apte, MBBS, PhD

Committee Member Satish Kalhan, MD

Date of Defense

June 26, 2019

*We also certify that written approval has been obtained for any proprietary material contained therein.

Table of Contents

List of tables……………………………………………………………………………iv List of figures…………………………………………………………..………………v Abstract…………………………………………………………………..……….……vii 1. General Introduction I. Hypoxia and HIF-1  Physiological response to hypoxia………………………………………...1  HIF- 1…………………………………...…………………………………….1  Other regulators of HIF-1……………………………………………………2  HIF-1 target genes…………………………………………………………..3  HIF- 2……………...………………………………………………………….3 II. β-adrenergic receptors  β-adrenergic receptors (βAR)………………………………………………4  βAR signaling ………………………………………………………………..5  βAR pathways ……………………………………………………………….6  βAR regulation of HIF-1……………………………………………………..7  βAR under hypoxia…………………………………………………………..9 III. Pulmonary Arterial Hypertension  Pulmonary Arterial Hypertension (PAH)…………………………………10  Molecular pathology of PAH………………………………………………11  HIF in PAH ………………………………………………………………….12  βAR in PAH…………………………………………………………………12  β-blockers in PAH ………………………………………………………….13 IV. Microparticles and Mitochondria  Microparticles…...………………………………………………………….14  Microparticle contents……………………………………………………..16  Basic mitochondrial structure and function………………………………17  Release of intact mitochondria…………………………………………....18  Mitochondrial DAMPs……………………………………………...………19  Mitochondrial transfer……………………………………………...………19 2. Interdependence of hypoxia and β-adrenergic receptor signaling in Pulmonary Arterial Hypertension  Abstract………………………………………..……………………………21  Introduction…………………………………………………………………22  Materials and methods.………………...…………………………………25

 Results……………………………………………………………………...30  Discussion………………………………………………………………….39  Tables……………………………………………………….……………...47  Figures…………………………………………………….………………..48 3. Flow cytometric detection and characterization of cell-free mitochondria in murine and human circulation  Abstract……………………………………………………………………..61  Introduction...………………………………………………………...…….62  Materials and methods……………………………………………...... 64  Results ………………………………………………………..……...... 67  Discussion...………………………………………………………………..71  Figures……………………………………………………………..……….75  Supplemental figures………………………………………………...……82 4. Discussion and future directions  Expanding the β-adrenergic signaling model……………………….…..83  Predicting treatment response in Pulmonary Arterial Hypertension.…84  What is the mechanistic link between βAR and HIF-1?...... 85  Developing therapeutics based on ligand bias……………………….…87  Characterization of circulating mitochondria …………………….….…..89  Release of whole mitochondria in pathological conditions………...…..89 References…………………………………………………………………...... …..91

iii

List of Tables

Table 1: Characteristics of PAH patients with phenotype of high or low RV

Glucose uptake……………………………………………………………………...…47

List of Figures

Chapter 2

Figure 1: βAR ligands differentially regulate HIF-1 and cAMP in vitro………...….48

Figure 2: βAR ligands differentially affect hypoxia-induced HIF-1 activity in vitro……………………………………...…………………………………...50

Figure 3: Isoproterenol and salbutamol have opposing effects on erythropoietic response in vivo………………………………………………………..51

Figure 4: Overexpression of β2AR in HEK293 cells increases basal HIF-1 activity and downstream effects under normoxia……………………………………53

Figure 5: Hypoxia blunts cAMP response to isoproterenol and salbutamol in vitro……………………………………………………………………...55

Figure 6: PAH patients with the phenotype of high RV glucose uptake have more severe disease………………………………….…………………………56

Figure 7: Mononuclear cells from PAH patients with the phenotype of high RV glucose uptake do not produce cAMP in response to isoproterenol……..57

Figure 8: PAH patients with the high RV glucose uptake phenotype do not respond to carvedilol…………………………………….…………………………….59

Chapter 3

Figure 1: Optimization of MP isolation via centrifugation…………………….……75

Figure 2: Murine MPs stain positive for MitoTracker Green………………………76

Figure 3: MPs from GFP-mito mice are GFP positive and

MitoTracker Red positive…………………………..………………………………….78

Figure 4: Murine circulating mitochondria stain positive for CD41 and

CD144 but not CD45…………………………………………………………………..79

Figure 5: Human circulating mitochondria stain positive for CD41,

CD144, and CD45……………..……………………………………………………….80

Supplemental Figure 1: Illustrated method for optimizing isolation of plasma MP…………………………………………..………………………………….82

Metabolic Mechanisms in Physiologic and Pathologic Oxygen Sensing

Abstract

OLIVIA ROSE STEPHENS

The β-adrenergic receptor (βAR) exists in an equilibrium of inactive and active conformational states, which is modulated by ligands resulting in downstream signaling. In addition to cAMP, βAR regulates hypoxia-inducible factor 1 (HIF-1).

We hypothesized that HIF-1 signaling occurs via a unique, independent βAR conformation and that Pulmonary Arterial Hypertension (PAH) patients with HIF- biased conformations would have blunted cAMP response. We found isoproterenol and salbutamol, both cAMP agonists, had opposing effects on HIF-

1 in cells and mice. Additionally, hypoxia blunted agonist-stimulated cAMP in vitro, consistent with receptor equilibrium shifting towards HIF-activating conformations. βAR overexpression in cells increased HIF-1 activity and glycolysis which was blunted by HIF-1 inhibitors, suggesting increased βAR increases basal HIF-1 signaling. Because PAH is also characterized by HIF- related glycolytic shift, we dichotomized PAH patients in the PAHTCH trial

(NCT01586156) based on right ventricular glucose uptake to evaluate βAR signaling. Patients with high glucose uptake had more severe disease than those with low uptake and had no response to βAR ligands. The findings expand the paradigm of βAR regulation and uncover a novel PAH subtype that might benefit from β-blockers.

vii

Circulating cell-free mitochondrial components are well characterized as mediators of inflammation. Recent studies show cells also release microparticles

(MPs) containing intact mitochondria under conditions of stress or injury. However, detection of cell-free mitochondria and their cellular origin has not been studied in non-pathological conditions. Thus, we hypothesize that intact mitochondria are detectable in the circulation under physiological conditions. To test this, plasma

MPs were analyzed via flow cytometry. Murine platelet-depleted plasma showed a small cluster of MPs which was 65% positive for the mitochondrial marker

MitoTracker Green (MT Green). Additionally, transgenic mice expressing mitochondrial GFP had GFP positive MPs in their plasma. Human plasma also contained cell-free mitochondria, with approximately 11% of the total MPs staining

MT green positive. Platelets and endothelial cells were sources of MT green positive MPs in mice and humans, based on cell-specific surface markers.

Leukocytes were also a source of mitochondria in humans but not mice. Together these data show multiple cell types release intact mitochondria into the circulation in healthy individuals.

viii

Chapter 1: Introduction

I. Hypoxia and HIF

Physiologic responses to hypoxia

Exposure to hypoxia, or low oxygen concentrations, leads to a number of acute physiological effects. Low blood oxygen level is detected through peripheral chemoreceptors. Peripheral chemoreceptors detect minute changes in not only blood oxygen, but also carbon dioxide and pH. When low blood oxygen is detected, peripheral chemoreceptors stimulate vasoconstriction and bradycardia. However, peripheral chemoreceptors also stimulate increased ventilation, which leads to tachycardia. This overcomes the initial depression of heart rate. Thus, the acute physiologic response to hypoxia is tachycardia.

HIF-1

Prolonged exposure to hypoxia results in a number of cellular and molecular adaptations that are primarily regulated by hypoxia-inducible factor-1 (HIF-1). HIF-

1 is a transcription factor that consists of an α and a β subunit. Both subunits are constitutively expressed. However, the α subunit is degraded in an oxygen dependent manner (163). Specifically, HIF-1α is hydroxylated by prolyl hydroxylase domain proteins (PHD) using oxygen as a substrate. This hydroxylation provides a binding site for von Hippel Lindau (VHL) which interacts with an E3 ligase that ubiquitinates HIF-1α. Ubiquitination targets HIF-1α for proteasomal degradation (60, 69). Thus, when there is not enough oxygen to serve as a substrate for hydroxylation (i.e. hypoxia), HIF-1α accumulates and

translocates to the nucleus to dimerize with HIF-1β. As a heterodimer, HIF-1 binds hypoxia response elements (HRE) to stimulate transcription of many genes.

Other regulators of HIF-1

In addition to oxygen, PHD also utilize α-ketoglutarate, an intermediate of the tricarboxylic acid (TCA) cycle, as a substrate for hydroxylation of HIF-1α. Thus

HIF-1α levels are sensitive to changes α-ketoglutarate levels. PHD is inhibited by pyruvate and tricarboxylic acid (TCA) cycle intermediates such as isocitrate, oxaloacetate, succinate, and fumarate (52, 78, 88, 132). In addition to hydroxylation by PHD, HIF-1α is also hydroxylated by factor inhibiting HIF-1 (FIH-

1). Like PHD, FIH-1 function is dependent on oxygen and α-ketoglutarate levels.

However, instead of triggering degradation of HIF-1α, hydroxylation by FIH-1 blocks the interaction between HIF-1α and co-activators p300 and CREB binding protein (CBP), both necessary for HIF-1 transcriptional activity. Additionally, HIF-1 is regulated by a number of growth factors and cytokines such as epidermal growth factor (EGF), heregulin, insulin, insulin-like growth factors 1 and 2, and interleukin-

1β (37, 51, 82, 175). Regulation occurs through modulation of HIF-1α protein levels and HIF-1 transcriptional activity. The effects of these factors on HIF-1 are thought to be mediated by the phosphoinositide 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) and mitogen-activated protein kinases (MAPK) pathways. HIF-

1α is phosphorylated by several MAPK in vitro, such as ERK1/2 and p38 (124,

142), although the effects of this vary and may be stimuli- and cell-type-specific.

Regardless, inhibitors of MAPK kinase (MEK1), p38, and PI3K inhibited regulation of HIF-1α by these growth factors (82, 142).

HIF-1 target genes

HIF-1 regulates responses to hypoxia through transcriptional control of hundreds of genes. These genes are primarily involved in pathways that increase oxygen delivery or allow cells to survive in a hypoxic environment. To increase oxygen delivery, HIF-1 regulates a number of vascular functions such as vasoconstriction, erythropoiesis, and angiogenesis. HIF-1 upregulates endothelin-

1 which stimulate vasoconstriction (57), and erythropoietin (EPO) which stimulates red blood cell production (65). HIF-1 mediated angiogenesis is driven by upregulation of vascular endothelial growth factor (VEGF) (22). To help cells survive oxygen deprivation, HIF-1 regulates a metabolic shift to increased glycolysis, minimizing reliance on oxidative phosphorylation. This is achieved through upregulation of glucose transporters and glycolytic enzymes, paired with increased expression of TCA cycle inhibitors (75, 99, 112, 134). Additionally, HIF-

1 regulates a variety of other processes that promote cell proliferation and survival.

HIF-2

HIF-2α has 48% homology with HIF-1α and is regulated in the same oxygen-dependent manner through hydroxylation. Like HIF-1α, HIF-2α dimerizes with HIF-1β and the dimer binds the same HRE sequence as HIF-1 (153). While there is a lot of overlap between HIF-1 and HIF-2 target genes, there are some

genes uniquely regulated by each isoform which may be tissue- or cell-type- specific (55).

II. β-adrenergic receptors

β-adrenergic receptors (βAR)

The β-adrenergic receptor is a G-protein coupled receptor (GPCR) that is activated by norepinephrine and epinephrine. βAR primarily interact with stimulatory G-proteins, Gs. G-proteins have subunits: α, β, and γ. Upon activation of the receptor, G-proteins binds and are activated. This causes release of the Gα subunit from Gβγ. For Gs, the α subunit activates adenylyl cyclase (AC) which produces cAMP. cAMP activates protein kinase A (PKA) which phosphorylates a number of downstream effectors.

The βAR has three subtypes: β1AR, β2AR, and β3AR. β1AR is found primarily in the heart and comprises approximately 70-80% of the total cardiac

βAR. β2AR accounts for the remaining 20-30%. However, β2AR is the predominant subtype found in the vasculature and lungs. β3AR is expressed primarily in adipose tissue (126). βAR play an important role in regulating cardiovascular homeostasis through modulation of heart rate and vascular tone. In the heart, activation of β1AR on pacemaker cells activates PKA which phosphorylates a number of proteins that regulate K+ and Na+ flux. This leads to increased rate of diastolic depolarization and a lower threshold for action potentials. This results in shortened diastole, increasing heart rate. Additionally, in myocardial cells, activation of PKA via β1AR leads to phosphorylation of Ca2+ channels and other Ca2+ regulators. This causes

increased Ca2+ influx, thus increased contractility. In vascular smooth muscles,

β2AR activation of PKA leads to phosphorylation of myosin light chain kinase

(MLCK). MLCK is responsible for initiating smooth muscle cell contraction.

Phosphorylation of MLCK reduces its ability to activate contraction, leading to smooth muscle relaxation and subsequently, vasodilation.

βAR signaling

Initially, receptor signaling was believed to occur only when an agonist bound the receptor. An agonist induced a conformational change that allowed interaction with downstream signaling effectors. This could be prevented by an antagonist which bound the same site as an agonist and blocked receptor activation. The discovery of constitutive or spontaneous activity in the absence of a ligand challenged this view and led to a new model of receptor signaling (25, 85,

129). In this so called “two-state model,” the receptor was believed to shift between two conformations, an active (R*) and an inactive (R), which are in equilibrium (83).

Spontaneous shifts to the active conformation can initiate signaling in the absence of a ligand, leading to constitutive signaling. Ligand binding to a particular conformation stabilizes the receptor, shifting the equilibrium towards that conformation. Thus, ligands are classified based on their relative affinities for R and R*. Agonists preferentially bind the active conformation, shifting the equilibrium towards increased signaling. Inverse agonists bind R, shifting the equilibrium away from R* and decreasing basal signaling. Antagonists bind both R and R*, stabilizing the overall equilibrium of receptor conformations and preventing

the action of agonists and inverse agonists. Many ligands previously classified as antagonists were discovered to be inverse agonists (25). The phenomenon of inverse agonism further confirmed the two-state model of GPCR signaling.

However, the discovery of multiple independent signaling pathways through a single receptor brought this model into question. In addition to the canonical G- protein/cAMP pathway, βAR were discovered to signal via mitogen-activated protein kinases (MAPK) such as ERK1/2 (7, 136, 167). Ligands can have differential effects on these pathways, suggesting there are multiple active conformations (7, 42, 117). The three-state model of GPCR signaling was proposed (84), which extends the two-state model to include an additional active conformation (R**) which signals independently from R*. Ligand bias towards one pathway over another depends on the relative affinity of a ligand for R* versus R**.

This allows a ligand to activate one pathway while inhibiting another. More recent work however suggests the possibility of more active conformations (160).

Structural studies of the βAR demonstrate that there is considerable heterogeneity in the receptor conformations stabilized by different ligands, even amongst ligands with similar signaling profiles (67, 94). As more signaling pathways are discovered, the model may expand to accommodate the increasing complexity of GPCR signaling.

βAR pathways

The canonical pathway of βAR activation involves coupling of the receptor with Gs protein. However, the receptor is capable of interacting with a number of

effector proteins to initiate different signaling pathways. For example, βAR can couple with inhibitory Gi protein and β-arrestins. β-arrestins are scaffolding proteins that serve to interfere with G-protein interaction and target the receptor for internalization. Phosphorylation of GPCRs by G-protein coupled receptor kinase

(GRK) leads to the recruitment of β-arrestins. In addition to their role in desensitizing the receptor, β-arrestins can activate a number of MAPK such as

ERK1/2 (90), p38 kinase (148), and cJun N-terminal kinase (JNK3) (100). βAR coupling with Gi may be necessary for β-arrestin mediated activation of MAPK.

Interestingly, carvedilol-induced recruitment of β-arrestin is dependent on βAR coupling to Gi when mediated through β1AR (164). However, carvedilol-induced recruitment of β-arrestin to β2AR is G-protein independent (167), indicating potentially different signaling mechanisms amongst the βAR subtypes.

Additionally, while both carvedilol and propranolol activate MAPK through β2AR, propranolol activation of MAPK is G-protein dependent and does not involve β- arrestin (167). This suggests that despite similar downstream outcomes, every ligand may initiate a unique signaling cascade.

βAR regulation of HIF-1

Evidence of βAR regulation of HIF-1 and hypoxia responses traces back over 40 years. In 1975, Fink, et. al. demonstrated that pretreatment with propranolol (a non-selective β-blocker) blunts hypoxia-induced EPO production in rabbits (40). This was confirmed by a second study in which metipranolol (a non- selective β-blocker) also blunted hypoxia-induced EPO production in rats (180). At

the time these studies were performed, HIF-1 had not yet been discovered.

However, more recent studies have confirmed the regulatory effect of βAR on HIF-

1 in certain disease models. Propranolol, along with β1- and β2-specific blockers, reduced HIF-1α levels in mouse embryonic stem cells. This resulted in decreased

VEGF and VEGFR2 expression, an subsequently decreased angiogenesis (135).

In pancreatic cancer cell lines, β1-, β2-, and non-selective agonists increased HIF-

1α protein under normoxia, as well as mRNA expression of multiple HIF-1 regulated genes (56). Phosphorylation of ERK was also increased with β-agonist.

Inhibiting epidermal growth factor receptor (EGFR), which activates ERK, or PKA blocked β-agonist-induced HIF-1α. This suggests PKA and EGFR are part of the mechanistic link between βAR and HIF-1. A more recent study investigating the mechanism of HIF-1α regulation by the βAR also supports the role of PKA as a link between βAR and HIF-1. In HeLa cells, AC activator forskolin increased HIF-

1α levels in both normoxia and hypoxia. Treatment with PKA inhibitor blunted this response (21). PKA phosphorylated HIF-1α, inhibiting its degradation. PKA also promoted HIF-1α interaction with co-activator p300 to increase HIF-1 activity (21).

Our laboratory demonstrated activation of the βAR under normoxia increased HIF-

1α while inhibition of the βAR under hypoxia blunted hypoxia-induced HIF-1α accumulation (23). However, we found that forskolin alone was not sufficient to increase HIF-1α levels, and that inhibition of PKA did not affect HIF-1α accumulation. Furthermore, inhibition of GRK blunted hypoxia- and β-agonist- induced HIF-1α accumulation (23). Phosphorylation of the βAR by GRK was

necessary for hypoxia-induced HIF-1α accumulation. Thus, it is clear that βAR regulates HIF-1, however the mechanism linking HIF-1 to the βAR is still unknown.

βAR under hypoxia

Studies investigating the effect of hypoxia on βAR density and signal transduction have been inconsistent. One study showed hypoxia decreased surface βAR and increased cytosolic βAR in rat ventricular, suggesting increased receptor internalization (125). However, they also found increased cAMP production in response to β-agonist under hypoxia, despite decreased βAR expression. Another group also found decreased βAR density in rat left ventricles

(LV) exposed to hypoxia. However, hypoxia exposure had no effect on right ventricular (RV) βAR density (66). Interestingly, in this study the RV had decreased basal and isoproterenol-induced cAMP after hypoxia while the LV had no change.

These studies suggest βAR density does not necessarily correlate with signaling.

They also suggest hypoxia effect on βAR may be tissue specific. This is supported by a study showing hypoxia exposure in rats increased βAR density in the lungs but not in the LV or spleen (166). They also found increased proportion of β2AR relative to β1AR, suggesting the effects of hypoxia may also be subtype specific.

The increase in β2AR under hypoxia is supported by a study showing β2AR is regulated by oxygen through hydroxylation and ubiquitination, which leads to degradation. Under hypoxia, this process is blocked, increasing β2AR levels (169).

However, in rat alveolar epithelial cells, hypoxia decreases β2AR and cAMP response to β2-specific agonist (8). Thus, it is still unclear how hypoxia affects the

βAR. The effects appear to be tissue and subtype specific, and are likely affected by experimental conditions such as oxygen tension, time, and membrane preparation protocol.

III. Pulmonary Arterial Hypertension

Pulmonary Arterial Hypertension

Pulmonary hypertension, or increased pulmonary vascular pressure, can be caused by a number of conditions such as left heart disease, chronic lung diseases, or thromboembolic disease. Pulmonary hypertension that is caused by remodeling of the pulmonary artery walls is referred to as pulmonary arterial hypertension (PAH). PAH can be hereditary, mediated by pathogenic variants in genes such as bone morphogenetic protein receptor 2 (BMPR2). PAH can also be caused by drugs, toxins, or infections. Often, however, the etiology of PAH is unknown.

PAH is characterized by hyperproliferative, apoptosis-resistant pulmonary artery smooth muscle and endothelial cells (98, 115). This leads to progressive narrowing of the pulmonary arteries. Increased pulmonary artery pressure and pulmonary vascular resistance (PVR) leads to increased right ventricular (RV) afterload. This induces RV hypertrophy (RVH) which can be adaptive or maladaptive. Adaptive RVH maintains normal cardiac output, while maladaptive

RVH has reduced cardiac output with RV dilation and fibrosis (122). Maladaptive

RVH can lead to RV failure and death.

Molecular pathology of PAH

Vascular cells in PAH exhibit a number of molecular changes that cause increased vasoconstriction, decreased vasodilation, mitochondrial and metabolic changes, increased proliferation, and decreased apoptosis. Endothelial-derived regulators of vessel diameter include the vasoconstrictor endothelin-1 (ET-1) and vasodilators nitric oxide (NO) and prostacyclin. In PAH, ET-1 levels are increased

(24, 44) while NO and prostacyclin are decreased (28, 71, 156, 170). This imbalance in vasoactive mediators leads to increased vasoconstriction.

Furthermore, PAH pulmonary artery endothelial cells (PAEC) demonstrate increased proliferation and express higher levels of anti-apoptotic/pro-survival mediators such as IL-15, Bcl-2, and Mcl-2 (98). This leads to thickening of the endothelial layer, narrowing the vessel opening. Additionally, there are a number of metabolic changes in PAH. PAH PAEC have decreased mitochondrial numbers, decreased oxygen consumption, and increased glycolysis (171). PAH patients also exhibit increased RV glucose uptake, indicative of increased glycolysis, which correlated with increased RV dysfunction (89). Furthermore, the mitochondrial enzyme arginase II (ARG2), which converts arginine to ornithine and urea, has increased activity in PAH (170). This results in reduced arginine levels. Since arginine is also a substrate for NO production via nitric oxide synthases (NOS), reduced arginine levels causes reduced NO production (170).

The current accepted therapies for PAH focus on vasodilation. There are three main classes of drugs: endothelin receptor antagonists, phosphodiesterase

5 (PDE5) inhibitors, and prostacyclin analogs. Endothelin receptor antagonists

serve to block the vasoconstricting effects of endothelin-1. NO stimulates cGMP production through activation of soluble guanylate cyclase (sGC). PDE5 inhibitors prevent the breakdown of cGMP, a vasodilator. Prostacyclin is also a potent vasodilator thus prostacyclin analogs serve to increase vasodilation. Patients who do not respond to these therapies are often candidates for lung transplant (43).

HIF in PAH

HIF-1α levels are increased in PAH lungs and RV, independent of oxygen levels (39, 89, 155). In a mouse model of hypoxia-induced PH, inhibition of HIF-1α was protective (1). Similarly, HIF-1α-/+ mice demonstrate resistance to hypoxia- induced pulmonary hypertension (173). HIF-2α also plays a role in the development of pulmonary hypertension. HIF-2α is highly expressed in lung endothelium and epithelium. Similar to HIF-1α-/+ mice, HIF-2α-/+ mice are resistant to hypoxia-induced pulmonary hypertension (20). Additionally, hypoxia induces

ARG2 upregulation which is blunted in HIF-2α-/+ mice (29). Consequently, HIF-2α-

/+ mice have higher NO (29). HIF-1 is known to regulate metabolism, increasing glycolysis and inhibiting oxidative phosphorylation (75, 112, 134). Thus, HIF-1 may play a role in the metabolic shift observed in PAH.

βAR in PAH

βAR is also involved in the pathogenesis of PAH, particularly in the context of RV failure. βAR are desensitized and downregulated in failing RV from PAH patients (17). βAR density on circulating mononuclear cells (MNC), which

corresponds to cardiac βAR density (19), is decreased in PAH compared to healthy controls. Decreased MNC βAR correlates with decreased RV function (127). In rodent models of PAH, GRK2 activity is increased, leading to phosphorylation and internalization of βAR (113). This points to a potential mechanism of downregulation, however this is yet to be shown in humans.

β-blockers in PAH

The βAR abnormalities and changes in HIF-1α expression seen in PAH also occur in left heart failure (18, 53). β-blockers are an established treatment for left ventricular failure. β-blocker treatment in left heart failure restores βAR density and function and reduces HIF-1α expression (140). However, β-blocker treatment is controversial for RV failure in PAH. Animal studies show β-blocker treatment improves survival, reverses RV remodeling, and restores RV function in PAH models (12). Meanwhile, human studies of β-blocker in PAH have been variable.

This is likely due to the variation in β-blockers tested. One study showed withdrawal of propranolol improved cardiac output and decreased pulmonary vascular resistance suggesting β-blocker treatment is detrimental in portopulmonary hypertension (116). Propranolol non-selectively blocks the β1- and

β2AR, the latter may result in vasoconstriction of the pulmonary vasculature. Thus,

β1AR specific β-blockers may be more appropriate as they avoid negative pulmonary effects. β1AR-specific blockers bisoprolol and metoprolol have been studied for pulmonary hypertension with mixed results. In one study, bisoprolol had negative effects, reducing cardiac index and 6 minute walk distance (158).

However, another showed bisoprolol improved RV function with reduced RV dilation and increased tricuspid annular plane systolic excursion (TAPSE) (104).

Retrospective studies of β1AR-specific blockers show no difference in hemodynamic or RV parameters in treated groups (9, 152). Recent studies focusing on third generation β-blockers, which have vasodilatory effects, are promising. Although one retrospective study showed carvedilol had no effect on functional class or time to clinical worsening (9), one clinical trial showed carvedilol improved right ventricular ejection fraction (RVEF) and reduced right ventricular systolic pressure (RVSP) (46). Another trial confirmed the beneficial effects of carvedilol in PAH, demonstrating decreased RV glucose uptake and increased

βAR density (36). Nebivolol, another third-generation β-blocker, lowered pulmonary artery systolic pressure, RV size, and blood endothelin-1 levels (97).

These studies suggest third generation β-blockers (e.g. carvedilol or nebivolol) may be beneficial in PAH.

IV. Microparticles and Mitochondria

Microparticles

Extracellular vesicles (EVs) are membrane-bound particles released from cells. Exosomes are a type of EV that are released from cells via exocytosis and range in size from 50-150 nm (50). Larger particles (100-1000 nm) are released through membrane budding and shedding. These particles are often called microparticles (MPs). MPs are released by many different cell types and are found throughout the body. For example, MP have been identified in urine (31), saliva

(111), synovial fluid (14), cerebral spinal fluid (146), and plasma (6). MP primarily function as mediators of intercellular signaling both through their surface proteins and internal contents. Their distribution through the body and targeting to specific cells depends on binding to adhesion molecules and surface receptors. Thus, MP from different cells with different surface markers will have different distributions and targets. For example, MP derived from red blood cells can be found in many locations throughout the body such as the liver, bone, skin, muscle, spleen, and kidney (165). Meanwhile, melanoma cell-derived MP are found primarily in the lung and spleen (149). Once MPs reach their target cells, uptake occurs mainly through phagocytosis (27, 103). Membrane fusion is also a suggested mechanism for MP uptake. However, fusion requires similar membrane fluidity between the MP and recipient cells, which is not the case at neutral pH (147). This means membrane fusion is unlikely except in more acidic environments in which the fluidity of both membrane is the same. MPs may also influence target cells simply through activation of surface receptors on the target cell. The effects of MPs have been implicated in regulation of many physiological processes such as angiogenesis

(121), coagulation (11, 50), innate immunity (110), adaptive immunity (109), and tissue repair (5). They are also associated with many pathological conditions including cancer (27, 77, 106), myocardial infarction (15), metabolic syndrome (2), arthritis (13), asthma (33), and pulmonary hypertension (127).

Microparticle contents

MPs play an important role in intercellular trafficking. They carry a wide range of cargo which can be transferred from one cell to another. MPs can contain cytokines such as IL-1β (92), IL-6 (70), and TGF-β (162). Furthermore, MPs can contain many types of RNA such as mRNA (119, 157), microRNA (80), long noncoding RNA (77), and ribosomal RNA (61). These RNA serve to alter recipient cell translation. Specifically, mRNA from MPs can be transfer to recipient cells where it can be translated into functional proteins (119, 157). Additionally, microRNA transferred from MPs reduces expression of target genes in recipient cells (80). MPs have also been shown to contain DNA (150), however the physiological significance of this is still unclear. Bioactive lipids such as eicosanoids, fatty acids, and cholesterol have also been found in MPs (120), as have mitochondrial components such as mitochondrial DNA (47) and proteins (30).

Moreover, MPs have been shown to contain intact mitochondria that are respiratory-competent (14). These mitochondria can be transferred to nearby cells to improve their respiratory capacity (62). However, transfer of mitochondria via

MPs appears to be limited to specific donor cells that come in close proximity of damaged or stressed cells. It is unclear whether MPs could carry mitochondria further distances like other cargo or if transfer can only occur with cell-to-cell contact.

Basic mitochondrial structure and function

Mitochondria are subcellular organelles responsible for producing the majority of the ATP within a cell. Mitochondria are hypothesized to have originated as a prokaryote that was acquired by another cell and transitioned into an organelle. They consist of an outer membrane composed of ~30-40% lipid and 60-

70% protein. The outer membrane contains very few enzymes or transport proteins but is rich in porins which allow movement of ions across the membrane.

Conversely, the inner membrane is much more complex. It contains enzymes for electron transport chain (ETC) and oxidative phosphorylation. It is relatively impermeable to ions and contains a number of transporter systems to facilitate movement of substrates, metabolic intermediates, and nucleotides across the membrane. The inner membrane encloses the matrix, which contains the enzymes for the tricarboxylic acid (TCA) cycle and the mitochondrial genome. The mitochondrial genome is a circular, double-stranded DNA containing genes for 13 subunits of the ETC complexes, along with ribosomal RNA and transfer RNA.

Mitochondria also contain ribosomes and have the ability to translate their own protein. However, approximately 90% of the proteins in the mitochondria are nuclear-encoded, translated in the cytosol, and transported to the mitochondria.

The main function of mitochondria is production of ATP through oxidative phosphorylation. In the matrix, the TCA cycle oxidizes acetyl-CoA to CO2, generating electron donors NADH and FADH2. These donors transfer electrons to complexes I and II of the ETC. As electrons move through the ETC, an electrochemical gradient is generated by the transport of H+ protons into the

intermembrane space. This gradient drives the generation of ATP by ATP synthase. In addition to ATP synthesis, mitochondria play a role in regulation of intracellular calcium distribution, apoptosis, and production of reactive oxygen species.

Release of intact mitochondria

In response to inflammation or injury, cells release intact, functional mitochondria. In vitro, T-cells and fibroblasts exposed to apoptosis- or necrosis- inducing stimuli release intact mitochondria, which activate immune cells such as macrophages and dendritic cells (93, 179). Activated platelets also release intact, respiring mitochondria in culture and in platelet transfusion preparations. These mitochondria activate neutrophils and are associated with adverse transfusion reactions (14). In an in vitro injury model, mouse brains release intact mitochondria which produce ATP and reactive oxygen species (ROS) (178). Extracellular mitochondria have also been detected in vivo. Intact mitochondria can be found in synovial fluid from rheumatoid arthritis patients and brochoalveolar lavage (BAL) fluid from mice with acute lung injury (14). They are also found in BAL fluid from healthy and asthmatic humans (54). Circulating mitochondria are found in mice exposed to traumatic brain injury (178) and in deceased human organ donors

(114). Increased levels circulating mitochondria in the donor correlates with early allograft rejection in the recipient (114). Altogether, these results suggest inflammation and injury stimulate release of intact mitochondria, which serve to induce immune activation and further inflammatory response.

Mitochondrial DAMPs

Damage-associated molecular patterns (DAMPs) are endogenous molecules released by stressed or injured cells. Similar to pathogen-associated molecular patterns (PAMPs), DAMPs are recognized by pattern recognition receptors (PRRs) on innate immune cells. Mitochondria are a significant source of

DAMPs, especially considering their prokaryotic origins. For example, mitochondria have circular, CpG containing DNA which is recognized by the PRR

Toll-like receptor 9 (TLR9) (177). Additionally, the mitochondrial membrane contains unique, prokaryote-like lipid species such as cardiolipin, which activates inflammasomes (63). Mitochondria are also a source of N-formyl peptides, which are recognized by formyl peptide receptors (FPR) on immune cells (177). Thus, mitochondria and mitochondrial components are important mediators of inflammation.

Mitochondrial Transfer

Stem cells can transfer mitochondria to stressed or damaged cells to restore cell function and prevent apoptosis. Mitochondrial DNA (mtDNA)-depleted A549 cells (A549 ρᵒ) have nonfunctional mitochondria that are incapable of respiration.

However, in a co-cultured with bone-marrow derived stem/stromal cells (BMSCs), they regain their respiratory capacity (143). BMSCs donate mitochondria to the

A549 ρᵒ cells through cell-to-cell contact. Rescued A549 ρᵒ cells have increased

ATP production, reduced lactate production, and increased oxygen consumption

(143). Transfer of mitochondria has also been demonstrated in vivo. In a mouse

model of acute lung injury, BMSCs instilled intranasally transferred mitochondria to bronchial and alveolar epithelial cells (62). BMSCs released mitochondria enclosed in microparticles and also formed tunneling nanotubules (TNT) through which mitochondria are transported to adjacent cells. Transfer of mitochondria increased alveolar ATP levels (62), indicating that the mitochondria are functional.

This was confirmed in another study of acute lung injury. Mesenchymal stem cells

(MSC) transferred mitochondria to lung epithelial cells, increasing ATP production and decreasing apoptosis (3). Transfer occurred via TNT and was dependent on

Miro1, a mitochondrial transport protein that facilitates transport of mitochondria along microtubules (3). Interestingly, intercellular transfer appears to be a cell-type specific process. In all of these studies, only stem or stem-like cells were able to donate mitochondria. In a co-culture, MSCs transferred mitochondria to stressed endothelial cells. However, healthy endothelial cells were not able to transfer mitochondria to stressed MSCs (3). Furthermore, platelets and isolated mitochondria were not able to rescue A549 ρᵒ cell respiration (143). Lastly, unlike

BMSCs, 3T3 fibroblast cells instilled in injured mouse lungs did not transfer mitochondria to epithelial cells (62). A more recent study, however, showed mitochondrial transfer between astrocytes and neurons in an ischemic stroke mouse model (49). Thus, while the process is cell-type specific, it seems it is not limited to stem cells.

Chapter 2: Interdependence of hypoxia and β-adrenergic receptor signaling in Pulmonary Arterial Hypertension

Olivia R. Stephens, Kelly Weiss, Matthew Frimel, Jonathan A. Rose, Yu Sun, Kewal Asosingh, Samar Farha, Kristin B. Highland, Sathyamangla V. Naga Prasad, Serpil C. Erzurum Under review: American Journal of Physiology-Lung Cellular and Molecular Biology

ABSTRACT

The β-adrenergic receptor (βAR) exists in an equilibrium of inactive and active conformational states, which shifts in response to different ligands and results in downstream signaling. In addition to cAMP, βAR signals to hypoxia-inducible factor 1 (HIF-1). We hypothesized that a βAR active conformation (R**) that leads to HIF-1 is separable from the cAMP-activating conformation (R*), and that

Pulmonary Arterial Hypertension (PAH) patients with HIF-biased conformations would not respond to cAMP agonist. We compared two cAMP agonists, isoproterenol and salbutamol, in vitro. Isoproterenol increased cAMP and HIF-1 activity, while salbutamol increased cAMP and reduced HIF-1. Hypoxia blunted agonist-stimulated cAMP, consistent with receptor equilibrium shifting towards

HIF-activating conformations. Similarly, isoproterenol increased HIF-1 and erythropoiesis in mice, while salbutamol decreased erythropoiesis. βAR overexpression in cells increased glycolysis which was blunted by HIF-1 inhibitors, suggesting increased βAR leads to increased hypoxia-metabolic effects. Because

PAH is also characterized by HIF-related glycolytic shift, we dichotomized PAH patients in the PAHTCH trial (NCT01586156) based on right ventricular (RV) glucose uptake to evaluate βAR ligands. Patients with high glucose uptake had

more severe disease than those with low uptake. cAMP increased in response to isoproterenol in mononuclear cells from low uptake patients, but not in high uptake patients’ cells. When patients were treated with carvedilol for 1 week, the low uptake group decreased RV systolic pressures and pulmonary vascular resistance, but high uptake patients had no physiologic responses. The findings expand the paradigm of βAR activation, and uncover a novel PAH subtype that might benefit from β-blockers.

INTRODUCTION

The βAR is a classical G-protein coupled receptor (GPCR) that activates multiple downstream effectors, e.g. the canonical cAMP signaling pathway (42,

136). In its basal state the βAR is dynamic, shifting between various inactive and active conformations often designated as R and R*, respectively. Spontaneous shifts to R* accounts for constitutive signaling in the absence of a ligand. Receptor ligands affect signaling by modulating the equilibrium of these receptor conformations. For example, full agonists bind and stabilize R*, shifting the equilibrium towards an active state and signaling response. Partial agonists also stabilize R*, however these ligands only produce a partial cAMP signaling response compared to the full agonist. Inverse agonists have an opposite effect wherein they bind and stabilize R, shifting the equilibrium towards an inactive state.

Inverse agonists reduce signaling to levels lower than at basal equilibrium. In contrast, βAR antagonists have no apparent effect on the receptor equilibrium but prevent agonist or inverse agonist binding to either receptor conformations. Other

than cAMP, the βAR also regulates other downstream signaling pathways, e.g. the extracellular signal-related kinase 1/2 (ERK1/2) and hypoxia-inducible factor-1

(HIF-1) (23, 42, 136). The various conformations available in the equilibrium paradigm provide a model to understand how some pharmacologic agents serve as a full βAR cAMP-agonist, yet act as an inverse agonist or antagonist for the other downstream pathways (160, 167).

Previous work shows the βAR is sufficient for stabilization of HIF-1α in normoxia and necessary for HIF-1α stabilization in hypoxia (23). Interestingly, the

βAR is also coordinately regulated by oxygen tension through hydroxylation and phosphorylation (23, 169). HIF-1 is the primary transcription factor that regulates cellular responses to hypoxia. It is comprised of an α and β subunit, the former of which is degraded in an oxygen-dependent manner. When oxygen concentrations are low, HIF-1α is stabilized and translocates to the nucleus where it dimerizes with HIF-1β and stimulates transcription through binding to hypoxia-response elements (HRE). Despite recent evidence of the reciprocal regulation of HIF and

βAR, there is very little understanding of how the pharmacologic ligands may impact βAR signaling in conditions where the receptor is biased towards a specific conformation. The relationship between βAR and hypoxia signaling is particularly relevant to Pulmonary Arterial Hypertension (PAH), which is characterized by increased pulmonary vascular pressure and progressive right heart failure. β- blockers are a mainstay of left heart failure, and recently have been suggested to have benefit in right heart failure. Several clinical trials investigated different β- blockers in PAH with varying and inconclusive results (46, 97, 104, 158), which

may be related to phenotypes of PAH that are more or less responsive (24).

Mechanistically, βAR and HIF-1 signaling are abnormal in PAH and contribute to disease pathology. The βAR is dysfunctional and this is associated with worse right ventricular (RV) function (17, 127). Additionally, HIF-1α expression is increased in

PAH pulmonary vascular endothelial cells and hearts (89, 155). Metabolic evidence of this is provided in the multiple reports that PAH individuals have higher glucose uptake in the right ventricle, related to a shift towards glycolysis, a well- known HIF-1 driven effect (131, 134, 171). Understanding the linkage between

βAR and HIF-1 may provide insights into the variability of responses to β-blockers and identify those individuals in whom β-blockers would be most efficacious.

Here we hypothesize that there is a βAR conformation (R**) that leads to

HIF-1 signaling separable from the canonical activated receptor for cAMP (R*), and that biased signaling towards HIF-1 can be identified in patients with PAH who are non-responders to βAR ligands. We utilized a pharmacological approach to test this. Isoproterenol and salbutamol, both agonists for cAMP, were evaluated for effects on HIF-1 in vitro and in vivo. We also assessed whether or not hypoxia biases the βAR, altering its signaling profile towards HIF and away from cAMP.

Finally, using a recent study of carvedilol in patients with PAH in which RV glucose uptake was measured by 2-[18F] fluoro-2-deoxy-D-glucose (FDG) positron emission tomography (PET) scan (36, 131), patients were dichotomized to a high or low RV glucose uptake phenotype as a surrogate of high (or low) HIF-1 activity.

Blood mononuclear cells were evaluated in a subgroup of the two PAH phenotypes for response to isoproterenol. Subsequently, all patients received a low dose of

carvedilol for one week. Echocardiogram was done to evaluate cardiac responses to carvedilol. Blood responses characteristic of HIF, i.e. red blood cells and endothelin-1, were measured as well. The results identify an expanded model of

βAR regulation in which HIF-1 signaling occurs via a receptor state that is independent of cAMP pathway. This model may help explain the variability in PAH severity and treatment response.

MATERIALS AND METHODS Compounds:

(-)-Isoproterenol (+)-bitartate salt (Sigma I2760), salbutamol (Sigma S8260 for cells, Sigma 1012600 for mice), and carvedilol (Sigma C3993) were prepared fresh for each experiment.

Cell Culture:

Human embryonic kidney cells overexpressing the β2AR (HEK293-β2AR) and non- overexpressing cells (HEK293-WT) were cultured in MEM with 10% fetal bovine serum, 1% penicillin/streptomycin/fungizone. For hypoxia experiments cell were incubated in a sealed chamber at 37ᵒ C with 2% O2, 5% CO2, balanced with 93%

N2.

Luciferase Assays:

The luciferase reporter vector was a pGL2 basic vector (Promega E1641) containing three hypoxia-response elements (HRE) upstream of the firefly luciferase gene (HRE sequence: CACGTC). The luciferase vector was co- transfected with the constitutive control reporter pRL-SV40 Renilla luciferase vector (Promega E2231). HEK293-β2AR cells were plated on 100 mm plates at a

density of 10 x 106 cells/plate 24 hours prior to transfection. Cells were co- transfected with HRE-luciferase (1 µg) and pRL Renilla (0.5 µg) plasmids using

Lipofectamine 2000 (Invitrogen 11668019) for 6 hours in antibiotic-free media. 14 hours post-transfection, cells were split to 12-well plates at a density of 1 x 106 cells/well. For baseline HIF-1 comparisons in WT vs. overexpressing cells, lysates were collected the next day. For ligand studies, cells were serum starved for 2 hours then treated for 45 minutes prior to exposure to hypoxia (2% O2) or normoxia. After 20 hours cells were lysed and processed according to the manufacturer’s instructions in the Dual-Luciferase Reporter Assay System

(Promega E1910). cAMP Measurements:

6 HEK293-β2AR were plated on 6-well or 12-well plates at a density of 1.5 x 10 cells/well or 8.0 x 105, respectively. The next day cells were serum starved overnight. Cells were treated for 5 minutes. For hypoxia experiments, cells were placed in hypoxia (2% O2) then treated with compounds prepared in deoxygenated media for 5 minutes. Cells were washed with ice-cold PBS. For cAMP measurements, cells were lysed and processed according to the manufacturer’s instructions in the CatchPoint cAMP Fluorescent Assay Kit (Molecular Devices

R8089).

Radio-ligand βAR density

Cell lysates were processed for plasma membrane isolation as previously described (105). The early endosome fraction was recovered after ultracentrifugation of the crude cytosolic fraction for 1 hour at 300,000g. Receptor

binding was performed as previously described (105). Briefly, 20 µg of protein from the plasma membrane and early endosomal fraction were incubated with 250 pM

βAR ligand [125I] cyanopindolol (125I-CYP, PerkinElmer, NEX189100UC) and nonspecific binding was determined using 250 pM 125I-CYP plus 100 μM ICI-

118,552 (Sigma I127).

Animal Model:

Eight week old male C57BL/6 mice from Jackson Laboratory were treated with vehicle; 1, 5, or 10 mg/kg salbutamol dissolved in 2% methanol in saline; or 1, 5, or 10 mg/kg isoproterenol dissolved in saline via intraperitoneal injection. Doses were determined based on previously published reports (32, 45, 74, 86, 91, 174).

Doses at the low end of the reported range were chosen with a short duration to minimize risk of cardiac abnormalities. Mice were anesthetized with 10% isoflurane and blood was collected via cardiac puncture. Blood was stored in K2EDTA tubes and centrifuged at 500 g for 5 minutes to obtain plasma. Kidneys were flash frozen in liquid nitrogen. Bone marrow was collected from hind legs and processed fresh for flow cytometry. All animal experiments were approved by the Cleveland Clinic

Institutional Animal Care and Use Committee at the Lerner Research Institute in

Cleveland, Ohio.

Western Blot:

For HIF-1α westerns, 200 µg protein from kidney nuclear extracts was loaded.

Nuclear extracts were prepared according to manufacturer’s instructions in the

Nuclear Extraction Kit (Affymetrix AY2002). HIF-1α and Lamin B1 antibodies

(Novus NB100-479 and Santa Cruz sc-374015, respectively) were diluted 1:1000

in 5% non-fat milk. HIF-1α was detected with anti-rabbit IgG-HRP (GE Healthcare

NA9340) diluted 1:5000 in 5% non-fat milk. Lamin B1 was detected with anti- mouse IgG-HRP (GE Healthcare NA931). Lamin B1 and HIF-1α antibodies were previously validated for specificity (59, 130).

Flow Cytometry:

Bone marrow was analyzed fresh on the day of collection. Non-specific binding sites were blocked by with 10% normal goat serum in PBS for 15 minutes at room temperature. Cells were washed with 1% BSA in PBS and incubated with APC conjugated anti-CD45 (eBioscience 17-0451-82) at 1:100 (2 μg/mL), PE conjugated TER119 (eBioscience 12-5921-81) at 1:50 (4 μg/mL), and FITC conjugated anti-CD44 (eBioscience 11-0441-81) at 1:100 (5 μg/mL) for 30 minutes on ice. All antibodies were diluted in 1% BSA in PBS. Cells were washed twice with 1% BSA in PBS and resuspended in FACS Flow containing the dead cell marker 7-AAD (BD Biosciences 51-68981E) at 1:200. Samples were run on a

LSRII flow cytometer (Becton Dickenson) and data was analyzed using FlowJo

V10 (Tree Star Inc.). Aggregates, cell debris and dead cells were gated out.

Leukocytes were excluded using CD45. Three populations were defined based on size and CD44 and TER119 levels. Proerythroblasts were defined as CD44hi

TER119lo, and basophilic and polychromatic erythroblasts were defined as

TER119hi and selected based on decreasing size and CD44 expression.

Proerythroblasts, basophilic and polychromatic erythroblasts were defined such that the percentage of cells in each population fit the expected ratio of 1:2:4:8 (23,

87).

Seahorse XF24 Analysis:

5 HEK293-β2AR or HEK293-WT cells were seeded at a density of 1.5 x 10 cells/well in Seahorse XF24 Cell Culture Microplates (Agilent 100850-001) one day prior to the assay in MEM with 10% fetal bovine serum and 1% penicillin/streptomycin/fungizone. Cells were treated with 100 nM digoxin (Sigma

D6003), 30 µM chrysin (Sigma C80105), or vehicle for 4.5 hours prior to analysis.

Cells were analyzed on the Seahorse XF24 Analyzer (Agilent) using the Glycolytic

Stress Test Kit (Agilent 103020-100) according to the manufacturer’s instructions.

Briefly, extracellular acidification rate (ECAR) was measured at baseline, after 10 mM glucose addition, after 1 µM oligomycin treatment, and after 50 mM 2-DG treatment. Estimated glycolysis was calculated as maximum glucose stimulated

ECAR minus baseline ECAR.

Human studies

The Pulmonary Arterial Hypertension Treatment with Carvedilol for Heart Failure

(PAHTCH) clinical trial was approved by the Cleveland Clinic Institutional Review

Board (NCT01586156). 30 PAH subjects were consented and enrolled. All patients started with a 1 week, open-label treatment with carvedilol (3.125 mg, 2 x day).

Study design and participants have been previously described in detail (36). FDG-

PET standardized uptake values (SUV) in the RV vs. LV (RV/LV SUV), right ventricular systolic pressure (RVSP), and pulmonary vascular resistance (PVR) were measured as previously described (36). Serum endothelin-1 was measured by the Endothelin-1 Quantikine ELISA kit (R&D Systems, DET100). Urinary creatinine was measured by the Abbott Architect machine according to the

manufacturer’s instructions. Mononuclear cells for cAMP analysis were isolated from blood via RBC lysis and centrifugation. 2 x 106 cells/mL were treated with 300

µM isoproterenol for 10 minutes at 37ᵒC. Dose was chosen based on previous studies (23). Cells were then lysed and processed according to the CatchPoint cAMP Fluorescent Assay Kit instructions. Mononuclear cells for flow cytometric analysis of βAR density were treated with RBC lysis buffer then fixed with 4% formaldehyde and permeablized with 0.2% Triton-X100. Staining and flow cytometric analysis was performed as previously described (127).

Statistical Analysis:

Statistical analysis was performed using JMP Pro 13/14 and GraphPad Prism 5.

The p-value threshold for significance was 0.05. Data in figures 1-3 were normalized to vehicle control. P-values from Bonferroni post-test. Data in figure 4a, b, d-f were analyzed via student’s t-test. Figure 4c was analyzed via ANOVA. P- values in figure 5 derived from Bonferroni post-test. High and low groups in figures

6 and 7 were compared via student’s t-test. Data in figure 8 was analyzed via paired t-test.

RESULTS

A pharmacological approach was employed to determine how βAR regulation of HIF-1 fits into the overall model of receptor signaling. We utilized

HEK293 cells stably transfected with β2AR (HEK293-β2AR), a common model for investigating βAR signaling (7, 136, 167). Cells were treated with isoproterenol and salbutamol, both cAMP agonists, and carvedilol, an inverse agonist, to determine

effects on HIF-1 activity. Cells were treated with each ligand or vehicle control in normoxia for 20 hours. HIF-1 activity assessed via a hypoxia response element

(HRE)-luciferase reporter transfected into the cells. Vehicle control treatments had no effect on luciferase compared to untreated (Luciferase/renilla mean ± SD: untreated = 2.29 ± 1.03, DMSO = 1.96 ± 2.0, methanol= 2.3 ± 1.4, p=0.84). All three ligands had dose-dependent effects on HIF-1 activity. Low-dose isoproterenol resulted in a slight decrease in HIF-1 activity, while higher doses increased activity up to 148% above baseline (Fig. 1a). Conversely, salbutamol had a dose-dependent inverse agonist effect, reducing HIF-1 activity by up to 42%

(Fig. 1b). Carvedilol acted as partial agonist at 1 µM and inverse agonist at 10 µM

(Fig. 1c). We classified the effect of each drug based on the dose that caused the largest change in HRE-luciferase activity. Thus, isoproterenol and carvedilol act as partial agonists for HIF-1, while salbutamol acts as an inverse agonist. These effects are summarized in Figure 1d compared to the hypoxia (2% O2) control.

As anticipated, effects of the ligands on cAMP generation confirmed that isoproterenol and salbutamol increased cAMP levels 6.6- and 3.8-fold, respectively, i.e. cAMP agonists (Fig. 1e). Carvedilol has been previously described as an inverse agonist for cAMP (167). This means carvedilol treatment should decrease cAMP levels below baseline. Since baseline levels of cAMP are at the low end of our detection limit, we tested carvedilol in the presence of IBMX.

IBMX is a phosphodiesterase inhibitor that prevents the breakdown of cAMP. This raises the basal cAMP level without affecting cAMP production. This allows us to detect reductions in cAMP production below baseline. Indeed, cAMP levels

trended higher in IBMX treated compared to vehicle (111.3 ± 39.1 vs. 70.8 ± 28.0 nmol/g, p=0.06). We did not see a significant reduction of cAMP with carvedilol.

However, it seems even with IBMX treatment, cAMP levels were still at the lower detection limit of our assay so it was not possible to see changes below baseline.

Still, the results indicate that βAR regulation of HIF-1 is different from regulation of cAMP. The contrasting effect on HIF-1 between isoproterenol and salbutamol is particularly interesting since both ligands are equivalent agonists for cAMP. This suggests that salbutamol binds the cAMP conformation of the βAR, but not the

HIF-1 conformation, shifting the equilibrium away from HIF-1 activation (Fig. 1f).

Furthermore, carvedilol seems to have a partial agonist effect on HIF-1, despite acting as an inverse agonist for cAMP. This suggests carvedilol binds the HIF-1 conformation, pulling the equilibrium away from cAMP signaling. Isoproterenol appears to bind and activate both conformations.

These ligands were tested under normoxia. If salbutamol is truly an inverse agonist, we would expect inhibition of HIF-1 under hypoxia as well. To test this we pretreated HEK293-β2AR cells with isoproterenol, salbutamol, or carvedilol for 45 minutes prior to 20 hour hypoxia (2% O2) exposure. As expected, salbutamol reduced hypoxia-induced HIF-1 activity by approximately 15% (Fig 2b). This additional evidence suggests salbutamol shifts the equilibrium of receptor conformations away from HIF-1 activation. This reduces the availability for HIF-1 activation under hypoxia. Interestingly, though both function as partial agonists under normoxia, only carvedilol increased HIF-1 activity under hypoxia (Fig. 2a, c).

These results are summarized in Figure 2d.

To assess physiologic effects of βAR in vivo, we examined the effect of these ligands in mice. In these experiments, isoproterenol and salbutamol were used to discriminate differential effects on HIF-1α based on the in vitro findings in

HEK293 cells. Mice were treated with isoproterenol, salbutamol, or vehicle via I.P. injection in normoxic conditions 2 hours prior to sacrifice. Isoproterenol had a dose- dependent effect on HIF-1α levels. Only 5 mg/kg isoproterenol increased HIF-1α levels while the higher or lower doses (1 and 10 mg/kg) had no effect. Salbutamol treated mice had no significant change in HIF-1α at any dose compared to vehicle controls (Fig. 3a, b). Classically, HIF-1 stimulates erythropoiesis which can be measured via myeloid erythroid progenitor levels (23, 87). Erythroid progenitor populations in the bone marrow were measured via flow cytometry (87).

Proerythroblasts (Stage I), basophilic erythroblasts (Stage II), polychromatic erythroblasts (Stage III), and orthochromatic erythroblasts (Stage IV) were determine based on expression of TER119, CD44, and size (Fig 3c, d). Normal erythroid development shows a 1:2:4:8 ratio from Stage I to Stage IV which is shown in the vehicle treated mice (Fig. 3e-g). The isoproterenol treated mice had increased proportions of erythroid progenitor cells at every dose compared to controls while the salbutamol treated mice had decreased proportions of progenitors (Fig. 3e-g). Overall, isoproterenol induced a HIF-response; while we could not detect changes in HIF-1α with salbutamol. Furthermore, erythropoiesis, a sensitive biological marker of HIF-1, was increased with isoproterenol but reduced with salbutamol. Altogether, this data supports our in vitro data demonstrating opposing effects of these ligands on HIF-1.

If there is an independent receptor conformation that activates HIF-1, we would expect to see basal HIF-1 signaling through this conformation. To test this we compared HEK293-β2AR cells with native, non-overexpressing cells (HEK293-

WT). We reasoned that if HIF-1 signaling occurs via a specific receptor confirmation, increased expression of βAR in cells would increase spontaneous basal signaling via HIF-1. Our HEK293-β2AR cells have approximately 32-fold increase in β2AR as compared to the WT cells (mean ± SD: 550.1 ± 22.89 vs 16.86

± 0.6 fmol/mg, p<0.001) (Fig. 4a). HRE-luciferase was used to measure basal HIF-

1 activity in both cell types. HIF-1 activity was increased in the HEK293-β2AR cells compared to the WT cells (Fig. 4b). To determine the functional consequences of this increased basal signaling, we compared glycolytic rates in both cells types.

Hypoxia results in a shift towards increased glycolysis (168) due in part to transcriptional regulation of glycolytic enzymes by HIF-1 (134). Thus we would expect HEK293-β2AR cells to have increased levels of glycolysis. Glycolysis was determined based on the extracellular acidification rate (ECAR) using a Seahorse

XFe24 Analyzer (Agilent). The test measures ECAR at baseline, after glucose stimulation, following inhibition of oxidative phosphorylation with oligomycin, and after 2-deoxy-glucose (2-DG) treatment that inhibits glycolysis. Estimated glycolysis can be calculated by subtracting the baseline ECAR from glucose- stimulated ECAR. Overexpression of the β2AR caused an increase in glycolysis compared to the HEK293-WT cells. (Fig. 4c). To confirm that this effect was due to increased HIF-1 activity, we pretreated cells with two HIF-1 inhibitors. Digoxin inhibits HIF-1α protein synthesis (176) and chrysin increases ubiquitination and

degradation of HIF-1α (41). Pretreatment with digoxin (100 nM) or chrysin (30 µM) decreased glycolysis in the HEK293-β2AR but had no effect on the WT cells (Fig.

4c). In addition to increased glucose-stimulated ECAR, HEK293-β2AR also had higher maximal ECAR with oligomycin compared to WT cells (Fig. 4d). Chrysin and digoxin treatments reduced both glucose-stimulated and maximal ECAR in

HEK293-β2AR cells (Fig. 4e,f). The differences were lost after 2-DG treatment which confirms the changes in ECAR were due to changes in glycolysis. Overall, these results indicate β2AR overexpression leads to increased HIF-1 activity and higher levels of glycolysis. This is consistent with increased basal signaling due to increased receptor expression. This supports the theoretical βAR model for HIF-1 regulation via a unique receptor conformation that is capable of spontaneous basal signaling.

Next, the effect of hypoxia on βAR cAMP signal transduction was evaluated.

If hypoxia shifts the equilibrium towards a HIF signaling conformation, we would expect a reduction in βAR that are accessible for agonist induction of cAMP signaling. To test this, HEK293-β2AR cells were exposed to hypoxia for 2 hours then stimulated with isoproterenol, salbutamol, or vehicle for 5 minutes. Levels of cAMP were measured via a fluorescent assay. Vehicle control treatment had no significant effect on cAMP compared to untreated (cAMP nmol/g mean ± SD: untreated = 518.7 ± 199.9, methanol = 379.5 ± 166.7, p=0.25). Under normoxia, isoproterenol and salbutamol treatment resulted in significant, dose-dependent increases in cAMP levels (Fig. 5a, b). However, after 2 hours hypoxia exposure, cAMP response to isoproterenol and salbutamol was blunted by up to 46% and

57%, respectively (Fig. 5a, b). Interestingly, stimulation with low doses of isoproterenol (≤ 1 µM) was still able to induce a significant cAMP response under hypoxia despite blunted response to higher doses. This may represent of subset of βAR that are in a high-affinity state and are primed for cAMP signaling (145), which appear to be less sensitive to hypoxia. Longer exposure to hypoxia (8-24 hours) continued to blunt cAMP response to both agonists (Fig. 5c). After 2, 8, or

24 hours hypoxia, isoproterenol induced no significant response compared to the vehicle treatment. There was a slight recovery of response to salbutamol after 8 hours hypoxia, however after 24 hours, the response was completely dampened.

To determine whether the reduction in cAMP response was due to increased receptor internalization or degradation, we measured the βAR density on plasma membranes and endosomes. βAR were measured after 2 hours hypoxia or normoxia via [125I]-cyanopindolol (125I-CYP) binding. The receptor density in either plasma membranes or endosomes was no different under normoxia vs. hypoxia

(p=0.48, plasma membrane; p=0.61, endosomes) (Fig 5d). This suggests hypoxia leads to a receptor conformation less accessible to ligands for activation of cAMP, i.e. hypoxia shifts the equilibrium of receptor conformations towards a HIF-1 activating state (R**), reducing availability to activate cAMP (Fig. 5e).

To investigate these effects in a pathophysiologic context, patients with

PAH were studied in an ancillary study to the clinical trial of Pulmonary Arterial

Hypertension Treatment with Carvedilol for Heart Failure (PAHTCH)

(NCT01586156). The PAHTCH trial enrolled 30 PAH patients and 12 healthy controls at baseline. PAH patients received 1-week open-label low-dose carvedilol

at 3.125 mg twice daily prior to randomization to the main double-blind study.

Characteristics of the population and results of the main study have been previously published (24, 36). As previously reported, PAH was characterized by greater levels of endothelin-1 (ET-1) and RV glucose standardized uptake values relative to the LV (RV/LV SUV) as measured by 2-[18F] fluoro-2-deoxy-D-glucose

(FDG) positron emission tomography (PET) scan (36, 131). Although PAH patients had overall greater RV glucose uptake than controls, there was heterogeneity of uptake among PAH participants. In fact, the RV/LV SUV correlated to ET-1 and the red blood cell count (RBC), suggesting that RV glucose uptake could serve as a surrogate marker of HIF-1 activation (Fig. 6b,c). Using the median of the RV/LV

SUV, there was a clear grouping of PAH patients with high and low glycolytic phenotypes (Fig. 6d). The high RV glucose uptake group had a more severe disease phenotype, with higher right ventricular systolic pressure (RVSP), pulmonary vascular resistance (PVR), ET-1 levels, and lower cardiac index compared to the low group (Fig. 6e-g) (Table 1).

To determine whether shift towards HIF-1 activation is associated with diminished availability for cAMP signaling, mononuclear cells were isolated at baseline from a subgroup of the PAH participants (N=11) and exposed to 300 µM isoproterenol for 10 minutes (Fig. 7a). Experiment was performed blinded to levels of FDG-PET RV glucose uptake. After unblinding of samples, analyses of results showed that cells from the low RV glucose patients a 2.4-fold increase in cAMP with isoproterenol (n=5) , while cells from high RV glucose uptake patients did not respond to isoproterenol (n=6) (Fig. 7b). This was consistent with our previous

results showing blunted cAMP signaling in HEK293-β2AR cells under hypoxia. The

βAR levels were also measured in mononuclear cells from participants.

Mononuclear cells were incubated with biotinylated alprenolol which was detected with PE-conjugated streptavidin and measured via flow cytometry. Alprenolol binding was similar among the high and low RV glucose uptake groups confirming that changes in cAMP response were not due to changes in receptor levels (Fig

7c). Based on these results and the paradigm for receptor conformations, the βAR in high RV glucose uptake PAH patients is shifted towards a HIF-1 (R**) activating state, reducing levels of R and R* availability to activate cAMP (Fig. 7d).

Next, we used the 1 week open-label low dose (3.125 mg) carvedilol intervention of PAHTCH to investigate whether the RV glucose phenotype might predict responders to the βAR inverse agonist carvedilol. Analogous to the ex vivo studies in the mononuclear cells from patients, the low RV glucose uptake group had a significant response to carvedilol measured as a drop in RVSP and PVR

(Fig. 8a, b), while the high group had no response (Fig. 8c, d). Furthermore, the low RV glucose uptake group had a significant decrease in systolic blood pressure after one week carvedilol (baseline: 120.7 ± 18.1 mmHg, carvedilol: 113.5 ± 13.9 mmHg, p=0.033, paired T-test). The high RV glucose uptake group had no change in blood pressure with carvedilol (baseline: 112.9 ± 15.0 mmHg, carvedilol: 110.9

± 14.2 mmHg, p=0.48, paired T-test). These results support the proposed model that PAH patients with high RV glucose uptake have a shifted equilibrium of βAR to the hypoxia-responsive state, and blunted cAMP response to ligands (Fig. 8e).

DISCUSSION

There is increasing recognition of the complexity in βAR signaling as new pathways continue to be discovered. Regulation of HIF-1 is one of those newly discovered pathways wherein our previous studies (23) showed the necessity of

βAR for HIF-1α stabilization. However, the current model of receptor signaling for cAMP and HIF-1 responses was unknown. Here our results expand the current paradigm of the βAR receptor conformation model. Multiple unique receptor conformations are in equilibrium leading to low level basal activation of HIF-1 and cAMP. Bias towards different conformations (via ligands or hypoxia) leads to cAMP and/or HIF-1 signaling by shifting the equilibrium of receptors towards or away from specific pathways.

The two-state model of GPCR signaling proposed that receptors exist in two conformations, an active (R*) and an inactive (R), which are in equilibrium (83).

The active conformation can signal in the absence of a ligand resulting in constitutive baseline signaling. Ligand binding stabilizes a particular receptor state, shifting the equilibrium towards that state. With this model, ligands can be classified based on their relative affinities for R and R*. Agonists have higher affinity for the active conformation, stabilizing R* and shifting the equilibrium towards an active state. Inverse agonists have a higher affinity for R, shifting the equilibrium towards an inactive state and decreasing signaling below baseline.

Antagonists have equal affinity for both R and R*, stabilizing both and preventing the action of agonists and inverse agonists. However, the discovery of multiple independent signaling pathways through a single receptor revealed the

shortcomings of this prior model. The fact that ligands have different efficacies towards one pathway compared to another supports the idea of multiple active conformations (7, 42, 117). This led to the development of a three-state model of

GPCR signaling (84). This model extends the two-state model to include an additional active state (R**) which signals through a different pathway than R*.

Ligand bias towards one pathway over another depends on the relative affinity of a ligand for R* versus R**. More recent work suggests the possibility of even more active conformations (160). Consistently, structural studies of the βAR demonstrate that there is considerable heterogeneity in the receptor conformations stabilized by different ligands, even amongst ligands with similar signaling profiles

(67, 94). This indicates that our current understanding of the receptor signaling is incomplete and as more pathways are discovered, the model may expand to accommodate the increasing complexity of GPCR signaling.

Based on our results we propose to broaden the model to include an active

R** conformation that specifically activates HIF-1. We propose HIF-1 activation occurs via a βAR conformation that is different from the conformation that activates cAMP. This is based on our results which show isoproterenol and salbutamol, both agonists for cAMP, have differential effects on HIF-1 activity. Only isoproterenol activated HIF-1 while salbutamol reduced HIF-1 activity. This indicates that HIF-1 signaling is not downstream of cAMP but an independent parallel pathway. We theorize that the difference in isoproterenol and salbutamol effect on HIF-1 is due to differences in their relative affinities for one conformation over another. Although both can bind and activate cAMP signaling, isoproterenol is able to bind and

stabilize the HIF-1 conformation while salbutamol cannot. This is supported by our data which showed isoproterenol acted as an agonist for both HIF-1 and cAMP, stimulating both under normoxia. Salbutamol stimulated cAMP production but had an inverse agonist effect on HIF-1 which was maintained under hypoxia. This difference was maintained in vivo with isoproterenol increasing HIF-1α levels as well as erythropoiesis in mice under normoxia while salbutamol decreased erythropoiesis. By binding and stabilizing the cAMP generating conformation but not the HIF-1 conformation, salbutamol shifts the equilibrium towards cAMP and reduces the number of receptors available to activate HIF-1.

Based on the model, the conformations are in equilibrium at baseline leading to low levels of basal signaling. This is supported by the fact that simply overexpressing the βAR leads to increased HIF-1 activity and glycolysis, a HIF-1 driven function. Interestingly, digoxin blunted glycolysis in βAR overexpressing cells. Digoxin is used clinically to treat left heart failure. Heart failure is often associated with increased HIF-1 and a shift towards glycolysis (133). Based on our results, we speculate that the beneficial effects of digoxin may be due, in part, to inhibition of these pathological, HIF-1-driven metabolic changes.

Oxygen is the main regulator of HIF-1 and likely plays a pivotal role in βAR signaling. Previous studies suggest the βAR is involved in hypoxia sensing. The

βAR is hydroxylated in an oxygen-dependent manner which leads to ubiquitination and degradation (169). Additionally, hypoxia induces a unique phosphorylation pattern or “barcode” on the βAR (23). The phosphorylation barcode of the βAR regulates downstream signaling, with different barcodes leading to distinct

signaling pathways (108). Here we find that placing cells in hypoxia prior to agonist stimulation reduced cAMP levels by up to 57%. We confirmed the change in signaling is not due to a change in receptor amount. We found hypoxia exposure had no effect on receptor density in the plasma membrane or endosomes. This means under hypoxia, the receptor still is present on the cell surface but cannot activate the cAMP pathway in response to agonist stimulation. Our findings support the idea that hypoxia stabilizes the receptor in a conformation that activates HIF-1

(R**), shifting the equilibrium away from R*, thus reducing the availability for cAMP signaling. Thus, hypoxia mimics the effect of an agonist, stabilizing and activating

HIF-1 signaling through βAR. However, hypoxia did not induce receptor internalization or degradation. This is in contrast to cAMP agonists isoproterenol and salbutamol. Acutely, both agonists induce receptor phosphorylation within 1-

5 minutes of treatment which leads to immediate desensitization of the receptor.

This is followed by receptor internalization starting around 5 minutes and continuing for up to 30 minutes with treatment (64, 79, 161). Therefore, receptor density at the plasma membrane is reduced. Longer treatment with agonist (3-24 hours) results in sustained downregulation of surface receptors. Long-term agonist exposure also decreases receptor protein and mRNA levels (16, 73). Thus, although the effect of hypoxia on the βAR is similar to an agonist, the mechanism of stabilization is likely different.

This expanded model of βAR regulation can help us understand the variable responses to β-blockers in PAH, and perhaps in heart failure in general.

Knowledge of ligand bias and regulation of signaling pathways of other GPCRs

has already led to the development of new drugs that preferentially activate beneficial pathways while simultaneously blocking deleterious pathways (95, 128).

Thus, understanding the complexities of the βAR signaling model is imperative to improving and developing new treatments. β-blockers have been investigated for treatment of right heart failure in PAH with variable results. In one study, bisoprolol reduced cardiac index and 6 minute walk distance (158). However, another showed bisoprolol reduced RV dilation and improved tricuspid annular plane systolic excursion (104). Retrospective studies of β1-blockers show no difference in hemodynamic or RV parameters in treated groups (9, 152). Recent studies focusing on third generation β-blockers are promising. A clinical trial showed carvedilol improved right ventricular ejection fraction (RVEF) and reduced RVSP

(46). Another showed nebivolol lowered pulmonary artery systolic pressure, RV size, and blood endothelin-1 levels (97). Our 6-month clinical trial investigating carvedilol in PAH demonstrated efficacy of the treatment (36). However, within the cohort of 30 subjects, there was variable response to carvedilol and subjects could be classified as responders or non-responders based on cardiac functions and functional improvements (24).

Our new model of βAR regulation may help explain this phenomenon and underlying mechanisms. Here, we classified subjects based on their HIF-

1/glycolytic phenotype. We used RV glucose uptake as a marker for HIF-1 signaling activation. Increased glucose uptake suggests a metabolic shift towards glycolysis, a HIF-1 regulated effect (39, 134). While increased glucose uptake has been directly correlated with HIF-1α levels in rat models of PAH and in human

tumors (68, 72, 96), we were not able to directly correlate glucose uptake with HIF-

1 in our subjects. However, we found RV glucose uptake was positively correlated with ET-1 and RBC, both HIF-1 regulated effects. The RV glucose uptake defined two phenotypes of PAH, the one with high glucose uptake having much more severe clinical disease and poor response to carvedilol. The low RV glucose uptake group responded well to carvedilol, with lower RVSP and PVR after 1 week treatment. It is interesting to consider this differential response in the context of our current and previous studies. In our in vitro studies, carvedilol acted as a partial agonist for HIF-1 activity. Although partial agonists induce low levels of signaling, physiologically this signaling is negligible. In fact, the overall effect of partial agonists is to blunt endogenous signaling responses by blocking receptor activation. This is consistent with the results from our previous study demonstrating pretreatment with carvedilol blunts HIF-mediated erythropoiesis in mice under hypoxia (23). We speculate that carvedilol holds the receptor in conformations that precludes a robust HIF-1 response. About half of individuals with PAH are shifted towards high glucose uptake (i.e. HIF-1 signaling) phenotype. We theorize that patients with high glucose uptake have a bias towards the βAR conformation that activates HIF-1. In these people, carvedilol is unable to prevent HIF-1 activation, as their receptor conformation is already biased towards HIF-1 signaling. In the low uptake subjects, carvedilol may serve to inhibit cAMP and blunt HIF-1 activation. This explains the differential response to carvedilol between these two groups. It is interesting to speculate that the high glucose uptake group might respond to HIF-1 inhibitors (e.g. digoxin).

Here we have expanded the model of βAR signaling to include a new parallel pathway through HIF-1. HIF-1 signaling occurs through a unique receptor conformation that is part of the equilibrium spectrum of receptor conformations.

Understanding this equilibrium and how it affects βAR signaling is essential for understanding current therapies as well as developing new ones. Specifically, we find that PAH response to βAR ligands differs depending on how this equilibrium is shifted. This knowledge could help predict who would be a good candidate for

β-blocker treatment. Knowledge of βAR regulation may also have more broad implications. Signaling bias, or a receptor’s ability to activate a selective subset of downstream pathways, is a powerful tool for specifically activating beneficial signals while simultaneously blocking deleterious signals. Thus, an in-depth understanding of the βAR signaling model and how ligands affect different pathways could lead to development of new compounds that selectively activate only desired pathways.

ACKNOWLEDGEMENTS

We would like to thank Hoi I Cheong for her valuable insights, advice, and assistance in developing this project.

GRANTS

This work is supported by NIH grants (HL115008 and HL060917) and American

Heart Association grant # 17PRE33660021. ORS is in the Molecular Medicine PhD

Program of the Cleveland Clinic Lerner College of Medicine and Case Western

Reserve University. SCE is supported in part by the Alfred Lerner Memorial Chair in Innovative Biomedical Research.

DSICLOSURES

The authors declare that they have no conflicts of interest with the contents of this article.

TABLES High RV Low RV t-test glucose glucose uptake uptake p- value n = 15 n =15

Gender (n, male/female) 3/12 6/9 Race (n, Caucasian/African 11/4/0 12/2/1 American/Asian) Age (years) 42.7 ± 12.9 45.9 ± 10.8 0.47 Weight (kg) 86.1 ± 20.7 78.9 ± 18.6 0.33 Heart rate (bpm) 78.9 ± 7.4 74.8 ± 8.4 0.16 Systolic blood pressure (mmHg) 112.9 ± 15.0 120.7 ± 18.1 0.21 Diastolic blood pressure (mmHg) 71.5 ± 12.3 71.3 ± 12.0 0.96 Oxygen saturation (%) 95.9 ± 2.2 96.7 ± 2.7 0.38 RVSP (mmHg) 80.3 ± 29.6 53.7 ± 14.3 0.005 PVR (Wood) 3.3 ± 1.5 2.2 ± 0.8 0.019 Cardiac index (L/min/m2) 2.18 ± 0.67 2.76 ± 0.80 0.04 1,480.7 ± 1,545.3 ± 6 minute walk distance (feet) 0.65 328.6 438.8 RBC (millions/µL) 4.9 ± 0.6 4.6 ± 0.4 0.18 Hemoglobin (g/dL) 13.7 ± 2.1 13.3 ± 1.8 0.56 Glucose (mg/dL) 83.7 ± 16.2 87.9 ± 16.2 0.48 RV/LV SUV Ratio 1.8 ± 1.0 0.5 ± 0.1 0.0003 Endothelin-1 (pg/mL) 3.6 ± 1.8 2.5 ± 0.96 0.042 Urinary cAMP/creatinine (µmol/g) 1.3 ± 0.5 0.9 ± 0.7 0.04† β-adrenergic receptor density (median 89.9 ± 22.6 84.1 ± 24.2 0.51 fluorescence intensity x 103) Urinary cGMP/creatinine (nmol/g) 122.5 ± 47.3 117.8 ± 103.7 0.87

Table 1: Characteristics of PAH patients with phenotype of high or low RV glucose uptake. Mean ± SD, p-value from student’s T-test. †p-value from Mann-Whitney U test.

FIGURES

Figure 1: βAR ligands differentially regulate HIF-1 and cAMP in vitro.

HEK293-β2AR cells were treated in normoxic conditions for 20 hours with (A) isoproterenol, (B) salbutamol, or (C) carvedilol. HIF-1 activity was measured using an HRE-luciferase reporter. Error bars represent SEM, n=3-4, in triplicate.

**p<0.01, ***p<0.001, relative to vehicle, Bonferroni post-test. (D) Summary of (A-

C) effects on HRE-luciferase compared to hypoxia positive control. 30 µM isoproterenol, 100 µM salbutamol, and 1 µM carvedilol are shown. (E) Regulation of cAMP in HEK293-β2AR cells treated with isoproterenol (10 µM), salbutamol (10

µM), or carvedilol (10 µM) + IBMX (500 mM) for 5 minutes. cAMP was measured

via fluorescent assay and normalized to total protein. Error bars represent SEM, n=3-4 in duplicate **p<0.01, ***p<0.001 relative to vehicle, Bonferroni post-test. (F)

Theoretical model of βAR regulation. The receptor status is an equilibrium of multiple conformations that signal through different pathways. R, inactive conformation; R*, conformation that activates cAMP; R**, conformation that activates HIF-1. Ligands affect signaling by shifting the equilibrium of receptors towards or away from specific conformations. Results indicate that isoproterenol

(ISO) is an agonist for cAMP and a partial agonist for HIF-1, shifting the equilibrium towards both pathways. Salbutamol (SAL) is an agonist for cAMP and an inverse agonist for HIF-1, shifting the equilibrium away from HIF-1. Carvedilol (CAR) is an inverse agonist for cAMP and partial agonist for HIF-1, shifting the equilibrium away from cAMP and towards HIF-1.

Figure 2: βAR ligands differentially affect hypoxia-induced HIF-1 activity in vitro. HEK293-β2AR cells were treated for 45 minutes with (A) isoproterenol, (B) salbutamol, or (C) carvedilol then exposed to hypoxia (2% O2) for 20 hours. Data is represented as % change in HRE-luciferase activity compared to the vehicle control. (D) Summary of (A-C) HRE-luciferase effects with 30 µM isoproterenol,

100 µM salbutamol, and 1 µM carvedilol. Error bars represent SEM, n=3-4 in triplicate, *p<0.05, **p<0.01, ***p<0.001 compared to vehicle control, Bonferroni post-test.

Figure 3. Isoproterenol and salbutamol have opposing effects on erythropoietic response in vivo. Mice received 1, 5, or 10 mg/kg isoproterenol

(ISO), salbutamol (SAL), or vehicle via I.P. injection 2 hours prior to sacrifice. n=5 per group for 1 and 10 mg/kg, n=10 for 5 mg/kg doses. (A) Representative western blot of kidney HIF-1α levels. HIF-1α is normalized to Lamin B1. Samples were run on multiple gels in parallel. Data are normalized to vehicle treated group. Error

bars represent SEM, ** p<0.01, Bonferroni post-test. (C, D) Gating for erythroid progenitor stages measured via flow cytometry. Proerythroblast (stage I), basophilic erythroblasts (stage II), polychromatic erythroblasts (stage III), and orthochromatic erythroblasts (stage IV) were determined based on their expression of CD44, TER119, and size. (E-G) Quantification of stages I-IV by dose. Normal erythroid development shows a 1:2:4:8 ratio from stage I to stage IV.

Each treatment group was normalized to stage I. Error bars represent SEM,

*p<0.05, **p<0.01, ***p<0.001 relative to vehicle, Bonferroni post-test.

Figure 4. Overexpression of β2AR in HEK293 cells increases basal HIF-1 activity and downstream effects under normoxia. (A) β2AR density on the plasma membrane of HEK293-β2AR and HEK293-WT cells was determined via radio-ligand binding. Error bars represent SEM, n=3, ***p<0.001, student’s t-test.

(B) Basal HIF-1 activity was measured via HRE-luciferase activity normalized to

Renilla control plasmid in normoxia. Error bars represent SEM, n=18, ***p<0.001, student’s t-test. (C) Estimated glycolysis was determined using the Seahorse

Glycolytic Stress test. Glycolysis is calculated as maximal glucose stimulated

extracellular acidification rate (ECAR) minus baseline ECAR. Cells were pretreated with HIF-1 inhibitors digoxin (100 nM) or chrysin (30 µM) or vehicle control for 4.5 hours. Error bars represent SEM, n=3 in duplicate, p-values determined via

ANOVA, **p<0.01, *** p<0.001 compared to WT cells with same treatment, student’s t-test. (D) Vehicle, (E) chrysin, or (F) digoxin treated cells were measured at baseline, after 10 mM glucose addition to stimulate glycolysis, after 1 µM oligomycin addition to inhibit oxidative phosphorylation, and after 50 mM 2-DG to inhibit glycolysis. Error bars represent SEM, n=3 in duplicate, *p<0.05, **p<0.01,

***p<0.001, HEK293-β2AR vs. HEK293-WT, student’s T-test.

Figure 5: Hypoxia blunts cAMP response to isoproterenol and salbutamol in vitro. (A-B) HEK293-β2AR cells were exposed to hypoxia (2% O2) or normoxia for

2 hours then stimulated with isoproterenol or salbutamol for 5 minutes. cAMP was measured via fluorescent assay. Data are normalized to vehicle normoxic condition. Error bars represent SEM, n=3-5, *p<0.05, **p<0.01, hypoxia vs. normoxia, paired T-test. (C) HEK293-β2AR cells were exposed to hypoxia (2% O2) or normoxia for 2-24 hours then stimulated with isoproterenol (10 µM) or salbutamol (10 µM) for 5 minutes. Data are normalized to vehicle normoxic condition. Error bars represent SEM, n=3-5, *p<0.05, **p<0.01, ***p<0.001, compared to vehicle, Bonferroni post-test. (D) HEK293-β2AR cells were exposed to hypoxia or normoxia for 2 hours then βAR density on plasma membranes and

endosomes was measured via 125I-CYP binding. Error bars represent SEM, n=7, there were no significant difference between any condition based on student’s T- test. (E) Theoretical model of βAR regulation based on the data, suggest hypoxia shifts the equilibrium towards HIF-1 activation, reducing availability of R*, and thus blunting cAMP signaling.

Figure 6: PAH patients with the phenotype of high RV glucose uptake have more severe disease (A) PAH patients (n=30) underwent 2-[18F] fluoro-2-deoxy-

D-glucose (FDG)-PET scanning to obtain standardized uptake values (SUV) of glucose in the right ventricle (RV) determined relative to the left ventricle (LV), echocardiogram to estimate cardiac functions and pulmonary vascular resistance

(PVR), and blood draw for measure of serum endothelin-1 and red blood cell counts (RBC). (B,C) RV/LV SUV correlates with endothelin-1 and RBC. (D)

Patients were dichotomized into high or low RV glucose uptake based on their

RV/LV SUV using the log transformed median as a cut-off for high and low. (E-G)

PAH patients with high RV glucose uptake had higher right ventricular systolic pressure (RVSP), pulmonary vascular resistance (PVR), and endothelin-1 levels.

Error bars represent SEM, p-values from student’s T-test.

Figure 7: Mononuclear cells from PAH patients with the phenotype of high

RV glucose uptake do not produce cAMP in response to isoproterenol. (A)

Mononuclear cells isolated from PAH patients were treated with 300 µM

isoproterenol (ISO) for 10 minutes. (B) cAMP was measured via fluorescent assay.

Error bars represent SEM, n=5-6 per group, p-values from student’s T-test. (C)

βAR density on mononuclear cells from high or low glucose uptake phenotypes of patients is similar. Mononuclear cells were incubated with biotinylated alprenolol which was detected with PE-conjugated streptavidin. Cells were analyzed via flow cytometry to determine relative βAR density based on the median fluorescence intensity (MFI). Error bars represent SEM, p-values from student’s T-test. (D)

Model of βAR equilibrium in the high glucose uptake PAH phentoype. Patients who have high RV glucose uptake have their βAR shifted towards R** (glycolytic metabolism), and thus less R* availability and inability to activate cAMP signaling.

Figure 8: PAH patients with the high RV glucose uptake phenotype do not respond to carvedilol. PAH patients were all treated with low-dose carvedilol

(3.125 mg 2 x day) for one week. RVSP and PVR were measured at baseline and after 1-week treatment in the low (A,B) and high (C,D) RV glucose groups. Bars 59

show means of populations, n=15 for RVSP, 10 for PVR, p-values from paired T- test. (E) Theoretical model of βAR equilibrium in PAH. Individuals with high RV glucose uptake are shifted towards R**, and have less R* available for carvedilol.

Chapter 3: Flow cytometric detection and characterization of cell-free mitochondria in murine and human circulation Olivia R. Stephens, Serpil C. Erzurum, Kewal Asosingh

ABSTRACT

Circulating cell-free mitochondrial components are well characterized as mediators of inflammation. Recent studies show cells also release microparticles (MPs) containing intact mitochondria. Intact mitochondria have been detected in synovial fluid from rheumatoid arthritis patients, plasma from mice with traumatic brain injuries, and plasma from deceased organ donor. However, detection of cell-free mitochondria and their cellular origin have not been studied in non-pathological conditions. Thus, we hypothesize that intact mitochondria are detectable in the circulation under physiological conditions. To test this, MPs were analyzed using the Apogee A50 micro flow cytometer (detection limit of <100 nm). Murine platelet- depleted plasma showed a cluster of MPs around 500 nm (size determined relative to Apogee Mix beads ranging 0.11-1.3 µm) which was 65% positive for the mitochondrial marker MitoTracker Green (MT Green). Additionally, transgenic mice expressing mitochondrial GFP had GFP positive MPs in their plasma. Of the

MT Green positive MPs, 11.6 ± 9.0 % were also positive for the platelet marker

CD41 and 11.3 ± 2.3% were positive for the endothelial cell marker CD144. This suggests these mitochondria are contained in MPs released from platelets or endothelial cells. There was negligible positive staining (<1%) for the leukocyte marker CD45 suggesting leukocytes are not a significant source of circulating mitochondria in mice. Human plasma also contained cell-free mitochondria, with

10.7 ± 3.0% of the total MPs staining MT green positive. Furthermore, 11.3 ± 4.1% of the MT Green positive MPs were also CD41 positive, while 49.0 ± 18.6 % were

CD144 positive and 8.9 ± 4.2% were CD45 positive. Together these data show multiple cell types release intact mitochondria into the circulation under physiologic conditions.

INTRODUCTION

Microparticles (MPs) are membrane enclosed particles that are released from various cells types. They are important mediators of intercellular trafficking.

Often they contain cellular components such as DNA, microRNA, mRNA, cytokines, functional enzymes, or mitochondrial components (30, 80, 101, 141,

150). These components can be transferred to other cells, modulating their function (80, 118, 141). MPs have been implicated in regulation of many physiological processes such as angiogenesis (121), coagulation (11, 50), innate immunity (110), adaptive immunity (109), and tissue repair (5). Due to their ability to modulate cellular function and their role in intercellular communication, MPs have been implicated as a biomarker in many disease states such as cancer, asthma, metabolic syndrome, arthritis, pulmonary arterial hypertension, and cardiovascular disease (2, 13, 33, 58, 106, 127).

Recent work demonstrates MPs can contain not only mitochondrial components, but intact mitochondria as well (14, 54). Extracellular mitochondrial components are well described mediators of inflammation. Mitochondrial DNA

(mtDNA) and formyl peptides released from injured cells activate an innate

immune response that induces a sepsis-like state (177). Cells undergoing apoptosis or necrosis release intact mitochondria that activate inflammatory responses in vitro (93, 179). Similarly, activated platelets release both free and MP enclosed mitochondria in vitro which promote leukocyte activation (14).

Interestingly, these mitochondria consume oxygen, suggesting they are respiratory competent. In vivo, intact mitochondria have been detected in synovial fluid from rheumatoid arthritis patients (14), bronchoalveolar lavage (BAL) fluid from injured mouse lungs (14), plasma from mice with traumatic brain injuries (178), and plasma from deceased organ donors (114). Together these results suggest release of intact mitochondria occurs in response to cellular stress or damage. One study, however, detected MPs containing intact mitochondria in BAL from both healthy and asthmatic humans (54), demonstrating that release of whole mitochondria also occurs in the absence of pathological stimuli.

While intact mitochondria have been detected in plasma under pathological conditions (114, 178), cell-free mitochondria have not been studied in the circulation of healthy individuals. Here we used flow cytometry to detect circulating mitochondria in platelet-depleted plasma in healthy mice and humans.

Furthermore, we demonstrate that these mitochondria have platelet-, endothelial-

, and leukocyte-specific surface markers suggesting they originated from these cells.

MATERIALS AND METHODS

Mice

10 week old C57/BL6 WT mice (n=5 female, n=5 male) were used for MP surface marker staining. GFP-mito mice (n=7) (B6;129-Gt(ROSA)26Sortm4(CAG-GFP*)Nat/J) is a conditional Gt(ROSA)26Sor (gene trap ROSA 26, Philippe Soriano) knock-in strain, Cre excision of a floxed stop cassette enables CAG promoter-directed GFP expression that is specifically localized to mitochondria via an N-terminal 25 amino acid targeting signal derived from mouse cytochrome c oxidase, subunit VIIIa. A

C-terminal V5 epitope tag is also fused to GFP. Mice containing both Cre

Recombinase and GFP-Mito were obtained by breeding mice containing Cre

Recombinase (The Jackson Laboratory, Stock No. 003724) with mice containing

GFP-Mito (The Jackson Laboratory, Stock No. 021429) Tissue samples from the offspring were genotyped by Transnetyx (Cordova, TN). Quantitative PCR was performed as follows: 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 cycles of: 95°C for 15 seconds, 60°C for 60 seconds. The final concentration of the forward and reverse primers was 950nM, the probes at 250nM, while the DNA was at a concentration of 50-100ng/μL. The presence of Cre Recombinase was detected using the following: forward primer

(TTAATCCATATTGGCAGAACGAAAACG), reverse primer

(CAGGCTAAGTGCCTTCTCTACA), and reporter (CCTGCGGTGCTAACC). The presence of the GFP-Mito mutant allele was detected using the following: forward primer (CGTCGTCCTTGAAGAAGATGGT), reverse primer

(CACATGAAGCAGCACGACTT), and reporter (CATGCCCGAAGGCTAC). The

presence of a GFP-Mito wild type allele was detected using the following: forward primer (TTCCCTCGTGATCTGCAACTC), reverse primer

(CTTTAAGCCTGCCCAGAAGACT), and reporter

(CCGCCCATCTTCTAGAAAG).

All animal experiments were approved by the Cleveland Clinic Institutional Animal

Care and Use Committee at Lerner Research Institute in Cleveland, Ohio.

Human subjects

Healthy controls were recruited as part of the Asthma Inflammation Research study (NCT01536522). All subjects provided informed consent to participate in the study, which was approved by the Cleveland Clinic Institutional Review

Board.

MP preparation from mouse blood

Mice were anesthetized with 10% isoflurane and blood was drawn via cardiac puncture. Blood was stored in K2EDTA tubes and centrifuged at 500g for 5 minutes at 4ᵒC to collect plasma. Prostaglandin E1 (PGE1, Sigma P7527) was added to plasma for a final concentration of 10 µM to inhibit platelet activation. Plasma was centrifuged at 2,500g for 30 minutes at 4ᵒC to pellet platelets. Optimization of MP isolation was done by sequentially centrifuging platelet-depleted plasma at increasing speeds. Platelet-depleted plasma was centrifuged at 4,000g for 10 minutes at 4ᵒC. MP pellet is not visible so supernatants were collected but 100 µL was left to avoid disturbing the pellet. Pellets were saved and labeled based on the speed at which they were collected (4K=4,000g, 6K=6,000g, etc). Supernatants were collected and subjected to further centrifugation at increasing speeds. After

pelleting platelets, supernatants were centrifuged from 4,000g to 20,000g in increments of 2,000g (illustrated method in Supplemental Fig. 1). Tyrode’s buffer with 10 µM PGE1 was double-filtered through a 0.1 µm filter. MPs were resuspended in double-filtered Tyrode’s buffer with PGE1.

MP preparation from human blood

Blood was drawn into ACD tubes. Blood was centrifuged at 150g for 20 minutes to collect plasma. PGE1 was added to plasma for a final concentration of 10 µM.

Plasma was centrifuged at 150g for 10 minutes to further clear contaminating red and white blood cells. Plasma was centrifuged at 2,500g for 30 minutes at 4ᵒC to pellet platelets. Double-filtered Tyrode’s buffer with PGE1 was added to platelet- free plasma and centrifuged at 10,000g for 10 minutes at 4ᵒC to pellet MPs. MP pellet is not visible so samples were aspirated down to 100 µL to avoid disturbing the pellet. MPs were resuspended in double-filtered Tyrode’s buffer with PGE1.

MP staining for flow cytometry

All antibodies and probes were titrated using MPs to determine working concentrations. Antibodies and probes were prepared at 2X concentrations in double-filtered Tyrode’s buffer with PGE1. Antibodies/probe were combined with sample at 1:1 ratio. For surface marker staining MitoTracker Green FM (Invitrogen

M7514) staining was done first. Samples were incubated with 250 nM MitoTracker

Green for 30 minutes at 37ᵒC. Samples were washed with double-filtered Tyrode’s buffer with PGE1 and centrifuged at 10,000g for 10 minutes. Samples were then incubated with antibodies for 30 minutes on ice. Antibodies were used at the following concentrations: anti-human CD41-PECy7 1/200 (BioLegend 303718),

anti-human CD45-PE 1/100 (Invitrogen 12-0459-42), anti-human CD144-PE 1/4

(Santa Cruz sc-9989), anti-mouse CD41-PE 1/100 (eBioscience 12-0411-81), anti- mouse CD45-PerCP 1/160 (Invitrogen MA1-10234), and anti-mouse CD144-

PECy7 1/50 (eBioscience 25-1441-82). Antibodies and probes were centrifuged at

20,000g for 10 minutes to pellet potential aggregates prior to use. For staining of

GFP-mito MPs, samples were incubated with 125 nM MitoTracker Red CMXRos

(Invitrogen M7512) at 37ᵒC for 20 minutes. Samples were washed with double- filtered Tyrode’s buffer with PGE1 after staining.

Flow cytometry

GFP-mito MPs were analyzed on a Fortessa (Becton Dickinson) flow cytometer equipped with 5 lasers (355nm, 407nm, 488nm, 561nm and 641nm). Surface marker stained MPs were analyzed on an Apogee A50 micro flow cytometer equipped with a 488nm laser. Apogee bead mix (refractive index=1.43, Apogee

#1493) was used for size estimation and rainbow calibration particles (Spherotech

RCP-20-5) were used for fluorescence detector calibration between experiments.

AbC Total Antibody Compensation Bead kit (Invitrogen A10497) was used for the antibodies and platelets were used for MitoTracker compensation.

RESULTS

In order to analyze MPs via flow cytometry, we first aimed to determine the optimal centrifugation speed to isolate plasma MPs. To do this we collected murine plasma and subjected it to sequential centrifugation at increasing speeds. First, plasma was centrifuged at 2,500g for 30 minutes to pellet platelets. The resulting

supernatant was centrifuged at 4,000g for 10 minutes and the pellet collected was labeled 4K. This was repeated with increasing centrifuge speeds with the pellet at each speed collected for analysis and the resulting supernatant further centrifuged

(illustrated method in Supplement Fig. 1). Plasma, platelet pellet, and pellets from each centrifuge step were analyzed on the Apogee A50 microflow cytometer.

Plasma had a large population of platelets as well as a smaller cluster which we believe to be mitochondria based on their size (Fig. 1a). As centrifuge speeds increased, the platelet population was depleted while the mitochondria population was enriched (Figs. 1b-f). Quantification of each sample revealed that while the percentage of sample in the mitochondria population increased at higher centrifuge speeds (Fig. 1g), the overall number of particles decreased (Fig. 1h). Thus we chose an intermediate speed of 10,000g for isolation to ensure enrichment of mitochondria while minimizing the potential for damage due to excessive force.

We next aimed to confirm whether the small cluster is enriched in intact mitochondria. Plasma was obtained from wild-type (WT) mice and platelets were depleted via centrifugation. The Apogee Bead Mix (0.1-1 µm) was used to estimate particle size (Fig. 2a). These beads have a refractive index of 1.43 which is similar to the refractive index of MPs (1.40) (159). Platelet-depleted plasma had MPs ranging from 0.1-1 µm, with the small cluster believed to be mitochondria falling around 500 nm (Fig. 2b). This population represented 4.1 ± 1.8% of total sample.

To determine whether these are in fact mitochondria, we stained platelet-depleted plasma with the mitochondria-specific probe, MitoTracker Green (MT Green).

Unstained sample was used to set the gate for MT Green positivity (Fig. 2c). Within

the 500 nm cluster, approximately 65% of the particles were MT Green positive

(Fig. 2d). We further examined all of the MT Green positive particles in the platelet- depleted plasma (Fig. 2f) and found approximately 15% of the total MT Green positive particles fell within the 500 nm cluster (Fig. 2g). While the MT Green positive particles ranged in size (Fig. 2g), we decided to take a more stringent approach and focus on the 500 nm cluster of mitochondria for future analyses of murine plasma.

To further confirm the presence of circulating mitochondria under physiologic conditions, we analyzed platelet-depleted plasma from transgenic mice with global GFP-labeled mitochondria (GFP-mito) counterstained with

MitoTracker Red (MT Red). These samples were analyzed on a BD LSR II flow cytometer which has multiple, higher power lasers allowing for better detection of weak GFP signal and counterstaining with MT Red. Settings were optimized using the Apogee Bead mix (Fig. 3a). This cytometer lacks the sensitivity to separate populations under 1 µm so all MPs were analyzed as a single population (Fig. 3b).

Compared to the unstained control mouse (Fig. 3c), the stained GFP-mito mouse had approximately 69% double positive particles (Fig. 3f). Additionally, about 26% of the particles were MT Red positive but GFP negative (Fig. 3f). This may be due to loss of the nuclear-encoded GFP signal in mitochondria that have been out of a cell for long periods of time. These results further confirm the presence of intact mitochondria in healthy murine circulation.

MPs are formed though budding of the plasma membrane which subsequently pinches off from the cell. Thus, the MP membrane should contain

surface markers from the cell of origin. To determine the origin of MP enclosed mitochondria, we stained murine platelet-depleted plasma for surface markers of platelets (CD41), vascular endothelial cells (CD144), and leukocytes (CD45). We selected the mitochondria-enriched cluster for analysis (Fig. 4a), gating the MT

Green positive population to ensure all particles analyzed contained mitochondria

(Fig. 4b). For each marker, the unstained sample was used to set the gate for positivity (Fig. 4c, e, and g). We found approximately 11% of the mitochondria were

CD41 positive (Fig. 4d). Another 11% were CD144 positive (Fig. 4f). However, we found essentially no CD45 positive particles (Fig. 4h). These results indicate that platelets and endothelial cells are a source of circulating mitochondria but leukocytes are not. Additionally, over 75% of the mitochondria were negative for all three markers suggesting they are from another cell type or not enclosed in a

MP at all.

To determine whether cell-free mitochondria are present in humans, we analyzed MPs in platelet-depleted plasma from healthy individuals. When examining the platelet-depleted plasma via flow cytometry, we noted the presence of a few extraneous platelets remaining after depletion (Fig. 5b). To exclude these from our analysis, we used platelet rich plasma to define the platelet population based on size (> 1 µm) (Fig. 5a). This gate was applied to depleted plasma and particles within this gate were excluded from analysis (Fig. 5b). The human plasma did not contain a mitochondria-enriched cluster as seen in the murine plasma, so the entire population of MPs was analyzed together. We stained the MPs for MT

Green and used the unstained sample to set the gate for positivity (Fig. 5c). We

found approximately 11% of the particles were MT Green positive (Fig. 5d). We stained the plasma for cell surface markers CD41, CD144, and CD45, using the unstained samples to set the gates for positivity (Fig. 5e, g, and i). Amongst the

MT Green positive mitochondria, approximately 11% were CD41 positive (Fig. 5f).

This was similar to the murine plasma. However, unlike the mice, we found approximately 49% of the mitochondria were CD144 positive (Fig. 5h) and approximately 9% were CD45 positive (Fig. 5j). Interestingly, while humans and mice had similar proportions of platelet-derived mitochondria, humans had more endothelial- and leukocyte-derived mitochondria. To verify that this difference is not due to differences in gating strategies, we applied the gating from the human samples to the mice. Even with this less stringent gating, the mice had less leukocyte- and endothelial-derived mitochondria compared to the humans, although platelet-derived mitochondria were slightly higher with this strategy (0.25

± 0.3% CD45+, 11.76 ± 3.2% CD144+, 15.2 ± 8.5% CD41+, data not shown).

DISCUSSION

An increasing number of studies have shown cells release intact mitochondria under conditions of stress, injury, or disease. Here, we’ve shown intact mitochondria are also released in non-pathologic states and can be detected in circulation in mice and humans. Platelets, endothelial cells, and leukocytes all serve as sources of circulating mitochondria, although they did not account for all of the circulating mitochondria. Approximately 77% of the murine and 30% of the human mitochondria were negative for these cell surface markers. This suggests

there are other sources of circulating mitochondria. Neurons, astrocytes, fibroblasts, and bone marrow-derived stromal/stem cells (BMSCs) all release intact mitochondria in response to stress or damage (49, 62, 93, 178, 179). Thus, many cell types have the capacity to release mitochondria and may do so in the absence of damage signals. An alternative explanation for the lack of surface markers is release of free mitochondria, without a cell membrane around it. Activated platelets release free mitochondria (14) and they have also been detected in the circulation of deceased organ donors (114). However, without a protective membrane, these mitochondria would be less stable. They could be broken down by secreted phospholipases, releasing mtDNA and other inflammatory mitochondrial components (14). Thus, free mitochondria likely play a role in inflammatory signaling.

The physiological role of extracellular mitochondria is still unclear.

Extracellular mitochondrial components serve as damage associated molecular patterns (DAMPs) which are recognized by pattern recognition receptors (PRRs) on innate immune cells. Thus, extracellular mitochondria may serve to initiate or amplify inflammatory signaling. Indeed, mitochondria activate platelets, neutrophils, macrophages, and dendritic cells in vitro (14, 178, 179). In vivo, extracellular mitochondria are associated with increased neutrophil activation, inflammatory cytokines, and correlate with disease severity/adverse events (14,

114).

An alternative function of circulating mitochondria may be transfer to cells with dysfunctional mitochondria. Transfer of healthy mitochondria to rescue

dysfunctional cells has been demonstrated in a variety of contexts. In vitro, BMSC transfer mitochondria to A549 and endothelial cells with dysfunctional mitochondria, increasing oxygen consumption and ATP production in the recipient cells (3, 143). BMSCs also transfer mitochondria in vivo. In mouse models of acute lung injury and asthma, BMSC instilled into the lung transfer mitochondria to dysfunctional epithelial cells, restoring ATP production and attenuating disease severity (3, 62). Mitochondria are released from BMSC in MPs, demonstrating the role of MPs in transporting mitochondria between cells (62). However, mitochondrial transfer has only been demonstrated in conditions with cell-to-cell contact. It is unclear whether mitochondria could be transferred between cells via the circulation. Donor cells may require close contact with dysfunctional cells in order to detect stress signals that trigger release of mitochondria. Furthermore, it is unknown how long mitochondria maintain their function outside of a cell, as most of the proteins required for mitochondrial function are nuclear-encoded. One study reports function of isolated mitochondria is maintained up to 18 hours after isolation

(81). However, this is under optimal conditions in vitro. Further studies are needed to determine the functionality of circulating mitochondria. Even if function is maintained during transport, how mitochondria would be targeted to a dysfunctional cell is also unclear. Thus, targeted, intercellular transfer of mitochondria through the circulation is unlikely, but possible.

Release of intact mitochondria has been described in a number of diseases and inflammatory states. Here we demonstrate the presence of intact mitochondria in the circulation of healthy mice and humans. Characterization of these circulating

mitochondria is important, as it defines a baseline in healthy individuals that will allow for comparison in pathological states. Furthermore, it helps to define the physiological relevance of cell-free mitochondria, which gives context to pathological states. As research on extracellular mitochondria expands, defining their origins and functions are important next steps for understanding their overall impact on health and disease.

FIGURES

Figure 1: Optimization of MP isolation via centrifugation. Murine plasma was subjected to centrifugation at increasing speeds (from 2,500-20,000g) to determine the optimal speed for isolating MP. Pellets at each speed were analyzed on the Apogee A50 Microflow Cytometer, while supernatants were subjected to further centrifugation at higher speeds. Representative plots of various speeds are shown. (A) Plasma analyzed on a plot of long angle light scatter (LALS) vs. short

angle light scatter (SALS) show a large cluster of platelets and a smaller cluster that is believed to be mitochondria. Representative plots showing pellets from (B)

4,000g; (C) 8,000g; (D) 12,000g; (E) 16,000g; (F) and 20,000g centrifugation. (G)

Percentage of particles within the mitochondria gate at each speed. (H) Number of particles/µL in the mitochondria gate at each speed.

Figure 2: Murine MPs stain positive for MitoTracker Green. (A) Apogee Beads

Mix (100-1300 nm) was used to estimate particle size. (B) LALS vs. SALS plot of

murine platelet-depleted plasma MPs. A cluster of particles appear around 500 nm and are likely mitochondria. This population stained positive for MT Green (D) compared to unstained (C). (E) Ungated, unstained MPs were used to set a positive gate for MT Green. (F) MT Green positive particles were plotted on the

LALS vs. SALS plot (G). Plots are representative images, n=10.

Figure 3: MPs from GFP-mito mice are GFP positive and MitoTracker Red positive. (A) Apogee beads were used to determine the settings to detect submicron particles. (B) Plasma MPs were detectable with these settings. (C) MPs from an unstained, non-GFP mouse were used to set the gates for MT Red and

GFP positivity. (D) MPs from a non-GFP mouse stained positive for MT Red. (E)

Unstained MPs from GFP-mito mice were GFP positive. (F) MT Red stained MPs from GFP-mito mice were double positive for GFP and MT Red. Plots are representative images, percentages represent mean ± SD, n=7.

Figure 4: Murine circulating mitochondria stain positive for CD41 and CD144 but not CD45. Mitochondria were gated based on size (A), then based on MT

Green staining (B). The resulting population was then analyzed for CD41-PE staining (D), CD144-PECy7 staining (F), and CD45-PerCP staining (H).

Percentages represent the mean ± SD % positive for the respective stain. Positive

gates were set based on unstained samples (C, E, G). Plots are representative images, n=10.

Figure 5: Human circulating mitochondria stain positive for CD41, CD144, and CD45. Platelets were gated based on size in the platelet-rich plasma samples

(A). This gate was used to exclude extraneous platelets from the platelet-depleted plasma (B). MT Green positive gate was set based on the unstained sample (C).

MT Green positive particles were selected (D) and the resulting population was then analyzed for CD41-PECy7 staining (F), CD144-PE staining (H), and CD45-

PE staining (J). Percentages represent the mean ± SD % positive for the respective stain. Positive gates were set based on unstained samples (E, G, I). Plots are representative images, n=5.

SUPPLEMENTAL FIGURES

Supplemental Figure 1: Illustrated method for optimizing isolation of plasma

MP. Blood was centrifuged at 500g for 5 minutes to obtain plasma. Some plasma was saved for analysis, the remaining plasma was centrifuged at 2,500g for 30 minutes to pellet platelets. Platelet pellet was saved and the resulting supernatant was centrifuged at 4,000g for 10 minutes. Since MP pellets are too small to visualize, 100 µL of liquid is left when removing supernatant to avoid disturbing the pellet. Pellets at each speed were collected while resulting supernatants were centrifuged at increasing speeds up to 20,000g. Plasma, platelet pellets, and pellet from each speed were split into two tubes, stained and unstained, for analysis.

Chapter 4: Discussion and Future Directions

Expanding the β-adrenergic signaling model

The model of βAR signaling is continually evolving. Initially, βAR signaling was believed to occur when an inactive receptor was activated by binding of an agonist. This induced a conformation change that allowed the receptor to interact with a G protein, initiating a signaling cascade. However, we now understand regulation of βAR signaling is much more complex. The receptor can exist in multiple conformations that bind different ligands and activate different signaling pathways. These conformations are in equilibrium and ligands affect signaling by shifting this equilibrium.

Here we propose to expand the model of βAR signaling to include a conformation that activates HIF-1. We have shown that regulation of HIF-1 signaling through the βAR is independent of the canonical cAMP pathway.

Furthermore, we detected basal HIF-1 signaling through the βAR in the absence of ligand or hypoxia. Together, these findings suggest a unique conformation that regulates HIF-1 and is part of the equilibrium of receptors. We also show that hypoxia regulates the equilibrium of receptors, favoring the conformation that activates HIF-1. In humans with PAH, the status of the βAR equilibrium may predict disease severity and response to β-blockers.

Predicting treatment response in Pulmonary Arterial Hypertension

Study of β-blockers in the treatment of PAH has been inconclusive thus far, due in part to the wide variety of β-blockers tested. While previously classified based on their receptor specificity and effect on cAMP, we now know β-blockers can be further subcategorized based on their effects on other signaling pathways.

Thus, many ligands previously believed to have similar function are now revealed to have different signaling profiles. Additionally, we show here that there is variability in response to β-blocker depending on the patient’s metabolic status.

This variability also contributes to the difficulty in detecting benefits within small cohorts. However, it is interesting to consider that β-blocker treatment may only be appropriate for a specific subset of patients. Our results suggest RV glucose uptake levels predict response to carvedilol. This not only provided insights into the status of the βAR in PAH, but also provides a potential marker to predict who would benefit from carvedilol treatment. Clinical studies of larger cohorts would be needed to confirm this. Furthermore, measurement of glucose uptake via FDG-

PET is quite costly. Investigation of related markers such as glycolytic enzymes/metabolites or HIF-1-regulated genes in the prediction of β-blocker response would also be worthwhile.

In additional to predicting response to β-blockers, our results provide insights into non-responders. In our cohort, patients that had higher RV glucose uptake did not respond to carvedilol. Increased glucose uptake is a HIF-1 driven response (39, 134), suggesting these patients have increased HIF-1 activity. Given the role of HIF-1 in the development of PAH (138), this represents an intriguing

target for treatment. Indeed, in rodent models of PH, inhibition of HIF-1 attenuated the development of PH symptoms such as increased pulmonary artery pressure,

RV hypertrophy, and vascular remodeling (1, 172). While inhibition of HIF-1 has not been directly tested in humans, several small studies have investigated the effects of digoxin in PAH. Digoxin was tested primarily due to its hemodynamic effects, however it is also an inhibitor of HIF-1α protein synthesis. Two studies demonstrated digoxin increased cardiac output and decreased mortality in patients with PAH (34, 123), suggesting a potential benefit. However, more studies need to be performed to confirm this and demonstrate the role of HIF-1. Given our results, it is interesting to speculate that patients that do not respond to carvedilol may benefit from HIF-1 inhibiting therapy such as digoxin.

What is the mechanistic link between βAR and HIF-1?

While our results further demonstrate the role of the βAR in regulation of

HIF-1 and hypoxia sensing, the mechanistic link between the βAR and HIF-1 is still unknown. Few studies have examined the link between βAR and HIF-1, and among those studies the results are variable. One study demonstrated protein kinase A (PKA), which is activated by cAMP, directly phosphorylates HIF-1α, preventing its degradation. This was stimulated by both isoproterenol and the adenylyl cyclase activator forskolin. The PKA inhibitor H89 blunted hypoxia- induced HIF-1α activation as well (21). These results suggest βAR regulation of

HIF-1 occurs downstream of the cAMP pathway. However Cheong et. al. found that while isoproterenol did increase HIF-1α levels, cAMP, forskolin, and H89 had

no effect on HIF-1α levels (23). This suggests HIF-1 signaling is not downstream of cAMP signaling which aligns with our results here. Further, they found that

GPCR kinase 2 (GRK2) played a role in HIF-1α stabilization. GRK2 phosphorylates βAR in response to agonist binding. Inhibition of GRK2 activity reduced isoproterenol- and hypoxia-induced HIF-1α accumulation (23). This indicates that phosphorylation of the βAR by GRKs is important for HIF-1 activation. GRK phosphorylation of βAR leads to the recruitment of β-arrestins, scaffolding proteins that interfere with G-protein coupling to the receptor, thus desensitizing the receptor (10). However, β-arrestins can also activate a number of mitogen-activated protein kinases (MAPK) such as ERK1/2 (90), p38 kinase

(148), and cJun N-terminal kinase (JNK3) (100). Given their role in signaling, β- arrestins are prime candidates for regulation of HIF-1 through the βAR. Indeed, β- arrestin1 has been shown to interact with HIF-1α under hypoxia, enhancing HIF-1 transcriptional activity in breast cancer cells (137). Furthermore, knockdown of β- arrestin1 blunted hypoxia-induced HIF-1 activation. Thus, β-arrestins are necessary for HIF-1 activity, however whether they are sufficient to activate HIF-1 under normoxia is unclear. Nevertheless, the necessity of GRK2 phosphorylation and the ability of β-arrestins to interact with HIF-1 suggest β-arrestins may mediate

HIF-1 signaling through the βAR. Further investigation of the interaction between

β-arrestins and HIF-1 under normoxia are needed to confirm this. Studies demonstrating the necessity of β-arrestins for βAR-mediated activation would further solidify this theory.

Developing therapeutics based on ligand bias

The ability of ligands to activate specific subset of signaling pathways through a receptor is known as ligand bias. Understanding ligand bias is important for the development of treatments that specifically activate beneficial pathways, inhibit deleterious pathways, and avoid negative side effects. For example, in dilated cardiomyopathy and acute heart failure, angiotensin signaling through the angiotensin receptor (a GPCR) activates Gαq signaling which mediates maladaptive vasoconstriction (154) and cardiac hypertrophy (35). Thus, angiotensin receptor blockers are a common treatment. However, the receptor also couples to β-arrestin which mediates increased cardiomyocyte contractility

(76, 102) and anti-apoptotic signaling (4). This pathway is also blocked by angiotensin receptor blockers. The knowledge of this biased signaling has led to the development of ligands that preferentially recruit β-arrestin while simultaneously blocking G-protein mediated signaling. These ligands have shown promise in mouse models of dilated cardiomyopathy (128) and have led to clinical trials in humans with acute heart failure (38). Another example of the potential benefits of biased ligands is in opioid treatment. The opioid receptor mediates analgesic effects via Gi-protein, while negative side effects such as respiratory depression and constipation are thought to be mediated via β-arrestin. This led to the development of a ligand which preferentially activates Gi signaling while inhibiting recruitment of β-arrestin (95). In mice, this ligand provided similar analgesic effects while minimizing respiratory depression when compared to

traditional opioids. Thus, understanding ligand bias is beneficial for improving the efficacy of many treatments.

In the context of βAR, understanding ligand bias could lead to new uses for existing ligands. For example, β2AR has been shown to be required for the development of asthma in mouse models (107). This led to an interest in β- blockers to treat asthma. However, two clinical trials (one using nadolol and one using propranolol) showed opposing results (48, 139). It is interesting to note that while both block cAMP signaling, propranolol is also a partial agonist for ERK1/2, while nadolol has no effect on ERK1/2 (7, 42). To further examine this difference,

Thanawala, et.al., tested four different β-blockers – propranolol, carvedilol, atenolol, and nadolol – in mouse models of asthma. Nadolol is the only ligand out of the four that does not have partial agonist activity for ERK1/2 (42, 160).

Consequently, nadolol was the only ligand that prevented the asthma phenotype

(151). This suggests that while inhibition of cAMP signaling may be beneficial in attenuating asthma, this benefit only occurs in the absence of ERK1/2 activation.

Thus, only ligands with this unique signaling profile would be effective. While further work is necessary to confirm this, this study further demonstrates the importance of understanding ligand bias. Furthermore, knowledge of ligand bias at the βAR is guiding development of novel ligands with the aim of achieving specific signaling profiles (144).

Characterization of circulating mitochondria

While circulating intact mitochondria have been described previously (114,

178), this is the first study to our knowledge that detected and characterized circulating mitochondria in the absence of disease or injury. Here we show under physiologic conditions platelets, endothelial cells, and leukocytes release mitochondria into the circulation in both mice and humans. Understanding the sources of mitochondria and their relative proportions in the circulation in healthy individuals establishes a baseline for comparison in disease states. Although we have identified some of the major sources of mitochondria, more comprehensive analysis of other potential sources is needed to fully characterize the profile of circulating mitochondria. Furthermore, the functional capacity of these mitochondria remains to be determined.

Release of whole mitochondria in pathologic conditions

Previous reports describing release of intact mitochondria all occur in the context of stress, injury, or disease. In vitro, cells stimulated to undergo apoptosis release intact mitochondria which activate immune cells (93, 179). Activated platelets also release intact mitochondria in vitro (14). In mice, intact mitochondria have been found in cerebral spinal fluid after stroke (26), bronchoalveolar lavage fluid after acute lung injury (14), and plasma after traumatic brain injury (178). In humans, extracellular mitochondria have been described in plasma from deceased organ donors (114), synovial fluid from rheumatoid arthritis patients (14), and bronchoalveolar lavage fluid from asthmatics (54). Amongst all of the in vivo

descriptions of extracellular mitochondria, none determined the cellular source of the mitochondria. Although they are likely to come from the stressed or injured cells of the affected organs, it is also possible that some come from donor cells through the process of mitochondrial transfer. Thus, more in depth studies are needed to reveal the sources of extracellular mitochondria in disease. Our work here will provide context for physiologic release of mitochondria, aiding in the distinction of pathological events.

It is interesting to speculate that pathological mitochondrial release may play a role in PAH. Mitochondrial dysfunction is well described in PAH and contributes to disease progression. For example, pulmonary artery endothelial cells (PAECs) have decreased mitochondria numbers, decreased oxygen consumption, increased arginase activity, and a shift towards glycolytic metabolism (39, 170, 171). Cellular stress and mitochondrial dysfunction may stimulate the release of mitochondria in a similar manner to other disease states.

Additionally, PAECs with dysfunctional mitochondria may benefit from mitochondrial transfer which could restore mitochondrial function, similar to studies in mouse models of acute lung injury (3, 62). PAH represents a promising context to investigate circulating mitochondria and the potential role of mitochondrial transfer in ameliorating mitochondrial dysfunction.

REFERENCES:

1. Abud EM, Maylor J, Undem C, Punjabi A, Zaiman AL, Myers AC, Sylvester JT, Semenza GL, and Shimoda LA. Digoxin inhibits development of hypoxic pulmonary hypertension in mice. Proceedings of the National Academy of Sciences of the United States of America 109: 1239-1244, 2012. 2. Agouni A, Lagrue-Lak-Hal AH, Ducluzeau PH, Mostefai HA, Draunet- Busson C, Leftheriotis G, Heymes C, Martinez MC, and Andriantsitohaina R. Endothelial dysfunction caused by circulating microparticles from patients with metabolic syndrome. Am J Pathol 173: 1210-1219, 2008. 3. Ahmad T, Mukherjee S, Pattnaik B, Kumar M, Singh S, Kumar M, Rehman R, Tiwari BK, Jha KA, Barhanpurkar AP, Wani MR, Roy SS, Mabalirajan U, Ghosh B, and Agrawal A. Miro1 regulates intercellular mitochondrial transport & enhances mesenchymal stem cell rescue efficacy. EMBO J 33: 994-1010, 2014. 4. Ahn S, Kim J, Hara MR, Ren XR, and Lefkowitz RJ. {beta}-Arrestin-2 Mediates Anti-apoptotic Signaling through Regulation of BAD Phosphorylation. J Biol Chem 284: 8855-8865, 2009. 5. Aliotta JM, Sanchez-Guijo FM, Dooner GJ, Johnson KW, Dooner MS, Greer KA, Greer D, Pimentel J, Kolankiewicz LM, Puente N, Faradyan S, Ferland P, Bearer EL, Passero MA, Adedi M, Colvin GA, and Quesenberry PJ. Alteration of marrow cell gene expression, protein production, and engraftment into lung by lung-derived microvesicles: a novel mechanism for phenotype modulation. Stem cells (Dayton, Ohio) 25: 2245-2256, 2007. 6. Arraud N, Linares R, Tan S, Gounou C, Pasquet JM, Mornet S, and Brisson AR. Extracellular vesicles from blood plasma: determination of their morphology, size, phenotype and concentration. J Thromb Haemost 12: 614-627, 2014. 7. Azzi M, Charest PG, Angers S, Rousseau G, Kohout T, Bouvier M, and Pineyro G. Beta-arrestin-mediated activation of MAPK by inverse agonists reveals distinct active conformations for G protein-coupled receptors. Proceedings of the National Academy of Sciences of the United States of America 100: 11406-11411, 2003. 8. Baloglu E, Ke A, Abu-Taha IH, Bartsch P, and Mairbaurl H. In vitro hypoxia impairs beta2-adrenergic receptor signaling in primary rat alveolar epithelial cells. Am J Physiol Lung Cell Mol Physiol 296: L500-509, 2009. 9. Bandyopadhyay D, Bajaj NS, Zein J, Minai OA, and Dweik RA. Outcomes of beta-blocker use in pulmonary arterial hypertension: a propensity- matched analysis. Eur Respir J 46: 750-760, 2015. 10. Benovic JL, Kuhn H, Weyand I, Codina J, Caron MG, and Lefkowitz RJ. Functional desensitization of the isolated beta-adrenergic receptor by the beta-adrenergic receptor kinase: potential role of an analog of the retinal protein arrestin (48-kDa protein). Proceedings of the National Academy of Sciences of the United States of America 84: 8879-8882, 1987.

11. Berckmans RJ, Nieuwland R, Boing AN, Romijn FP, Hack CE, and Sturk A. Cell-derived microparticles circulate in healthy humans and support low grade thrombin generation. Thromb Haemost 85: 639-646, 2001. 12. Bogaard HJ, Natarajan R, Mizuno S, Abbate A, Chang PJ, Chau VQ, Hoke NN, Kraskauskas D, Kasper M, Salloum FN, and Voelkel NF. Adrenergic receptor blockade reverses right heart remodeling and dysfunction in pulmonary hypertensive rats. Am J Respir Crit Care Med 182: 652-660, 2010. 13. Boilard E, Nigrovic PA, Larabee K, Watts GF, Coblyn JS, Weinblatt ME, Massarotti EM, Remold-O'Donnell E, Farndale RW, Ware J, and Lee DM. Platelets amplify inflammation in arthritis via collagen-dependent microparticle production. Science 327: 580-583, 2010. 14. Boudreau LH, Duchez AC, Cloutier N, Soulet D, Martin N, Bollinger J, Pare A, Rousseau M, Naika GS, Levesque T, Laflamme C, Marcoux G, Lambeau G, Farndale RW, Pouliot M, Hamzeh-Cognasse H, Cognasse F, Garraud O, Nigrovic PA, Guderley H, Lacroix S, Thibault L, Semple JW, Gelb MH, and Boilard E. Platelets release mitochondria serving as substrate for bactericidal group IIA-secreted phospholipase A2 to promote inflammation. Blood 124: 2173-2183, 2014. 15. Boulanger CM, Scoazec A, Ebrahimian T, Henry P, Mathieu E, Tedgui A, and Mallat Z. Circulating microparticles from patients with myocardial infarction cause endothelial dysfunction. Circulation 104: 2649-2652, 2001. 16. Bouvier M, Collins S, O'Dowd BF, Campbell PT, de Blasi A, Kobilka BK, MacGregor C, Irons GP, Caron MG, and Lefkowitz RJ. Two distinct pathways for cAMP-mediated down-regulation of the beta 2-adrenergic receptor. Phosphorylation of the receptor and regulation of its mRNA level. J Biol Chem 264: 16786-16792, 1989. 17. Bristow M, Minobe W, Rasmussen R, Larrabee P, Skeri L, Klein J, Anderson F, Murray J, Mestroni L, Karwande S, Fowler M, and Ginsburg R. Beta-adrenergic neuroeffector abnormalities in the failing human heart are produced by local rather than systemic mechanisms. J Clin Invest 89: 803-815, 1992. 18. Bristow MR, Ginsburg R, Minobe W, Cubicciotti RS, Sageman WS, Lurie K, Billingham ME, Harrison DC, and Stinson EB. Decreased catecholamine sensitivity and beta-adrenergic-receptor density in failing human hearts. N Engl J Med 307: 205-211, 1982. 19. Brodde OE, Kretsch R, Ikezono K, Zerkowski HR, and Reidemeister JC. Human beta-adrenoceptors: relation of myocardial and lymphocyte beta- adrenoceptor density. Science 231: 1584-1585, 1986. 20. Brusselmans K, Compernolle V, Tjwa M, Wiesener MS, Maxwell PH, Collen D, and Carmeliet P. Heterozygous deficiency of hypoxia-inducible factor–2α protects mice against pulmonary hypertension and right ventricular dysfunction during prolonged hypoxia. Journal of Clinical Investigation 111: 1519- 1527, 2003. 21. Bullen JW, Tchernyshyov I, Holewinski RJ, DeVine L, Wu F, Venkatraman V, Kass DL, Cole RN, Van Eyk J, and Semenza GL. Protein

kinase A-dependent phosphorylation stimulates the transcriptional activity of hypoxia-inducible factor 1. Sci Signal 9: ra56, 2016. 22. Carmeliet P, Dor Y, Herbert JM, Fukumura D, Brusselmans K, Dewerchin M, Neeman M, Bono F, Abramovitch R, Maxwell P, Koch CJ, Ratcliffe P, Moons L, Jain RK, Collen D, and Keshert E. Role of HIF-1alpha in hypoxia-mediated apoptosis, cell proliferation and tumour angiogenesis. Nature 394: 485-490, 1998. 23. Cheong HI, Asosingh K, Stephens OR, Queisser KA, Xu W, Willard B, Hu B, Dermawan JK, Stark GR, Prasad SV, and Erzurum SC. Hypoxia sensing through beta-adrenergic receptors. JCI Insight 1: e90240, 2016. 24. Cheong HI, Farha S, Park MM, Thomas JD, Saygin D, Comhair SAA, Sharp J, Highland KB, Tang WHW, and Erzurum SC. Endothelial Phenotype Evoked by Low Dose Carvedilol in Pulmonary Hypertension. Frontiers in Cardiovascular Medicine 5: 2018. 25. Chidiac P, Hebert TE, Valiquette M, Dennis M, and Bouvier M. Inverse agonist activity of beta-adrenergic antagonists. Mol Pharmacol 45: 490-499, 1994. 26. Chou SH, Lan J, Esposito E, Ning M, Balaj L, Ji X, Lo EH, and Hayakawa K. Extracellular Mitochondria in Cerebrospinal Fluid and Neurological Recovery After Subarachnoid Hemorrhage. Stroke 48: 2231-2237, 2017. 27. Christianson HC, Svensson KJ, van Kuppevelt TH, Li JP, and Belting M. Cancer cell exosomes depend on cell-surface heparan sulfate proteoglycans for their internalization and functional activity. Proceedings of the National Academy of Sciences of the United States of America 110: 17380-17385, 2013. 28. Christman BW, McPherson CD, Newman JH, King GA, Bernard GR, Groves BM, and Loyd JE. An imbalance between the excretion of thromboxane and prostacyclin metabolites in pulmonary hypertension. N Engl J Med 327: 70- 75, 1992. 29. Cowburn AS, Crosby A, Macias D, Branco C, Colaço RDDR, Southwood M, Toshner M, Crotty Alexander LE, Morrell NW, Chilvers ER, and Johnson RS. HIF2α–arginase axis is essential for the development of pulmonary hypertension. Proceedings of the National Academy of Sciences 113: 8801-8806, 2016. 30. Dean WL, Lee MJ, Cummins TD, Schultz DJ, and Powell DW. Proteomic and functional characterisation of platelet microparticle size classes. Thromb Haemost 102: 711-718, 2009. 31. Dear JW, Street JM, and Bailey MA. Urinary exosomes: a reservoir for biomarker discovery and potential mediators of intrarenal signalling. Proteomics 13: 1572-1580, 2013. 32. Dong RQ, Wang ZF, Zhao C, Gu HR, Hu ZW, Xie J, and Wu YQ. Toll- like receptor 4 knockout protects against isoproterenol-induced cardiac fibrosis: the role of autophagy. Journal of cardiovascular pharmacology and therapeutics 20: 84-92, 2015. 33. Duarte D, Taveira-Gomes T, Sokhatska O, Palmares C, Costa R, Negrao R, Guimaraes JT, Delgado L, Soares R, and Moreira A. Increased

circulating platelet microparticles as a potential biomarker in asthma. Allergy 68: 1073-1075, 2013. 34. Eshtehardi P, Mojadidi MK, Khosraviani K, Pamerla M, and Zolty R. Effect of Digoxin on Mortality in Patients with Isolated Right Ventricular Dysfunction Secondary to Severe Pulmonary Hypertension. Journal of the American College of Cardiology 63: A750, 2014. 35. Fan G, Jiang YP, Lu Z, Martin DW, Kelly DJ, Zuckerman JM, Ballou LM, Cohen IS, and Lin RZ. A transgenic mouse model of heart failure using inducible Galpha q. J Biol Chem 280: 40337-40346, 2005. 36. Farha S, Saygin D, Park MM, Cheong HI, Asosingh K, Comhair SA, Stephens OR, Roach EC, Sharp J, Highland KB, DiFilippo FP, Neumann DR, Tang WHW, and Erzurum SC. Pulmonary arterial hypertension treatment with carvedilol for heart failure: a randomized controlled trial. JCI Insight 2: 2017. 37. Feldser D, Agani F, Iyer NV, Pak B, Ferreira G, and Semenza GL. Reciprocal positive regulation of hypoxia-inducible factor 1alpha and insulin-like growth factor 2. Cancer Res 59: 3915-3918, 1999. 38. Felker GM, Butler J, Collins SP, Cotter G, Davison BA, Ezekowitz JA, Filippatos G, Levy PD, Metra M, Ponikowski P, Soergel DG, Teerlink JR, Violin JD, Voors AA, and Pang PS. Heart failure therapeutics on the basis of a biased ligand of the angiotensin-2 type 1 receptor. Rationale and design of the BLAST-AHF study (Biased Ligand of the Angiotensin Receptor Study in Acute Heart Failure). JACC Heart failure 3: 193-201, 2015. 39. Fijalkowska I, Xu W, Comhair SA, Janocha AJ, Mavrakis LA, Krishnamachary B, Zhen L, Mao T, Richter A, Erzurum SC, and Tuder RM. Hypoxia inducible-factor1alpha regulates the metabolic shift of pulmonary hypertensive endothelial cells. Am J Pathol 176: 1130-1138, 2010. 40. Fink GD, Paulo LG, and Fisher JW. Effects of beta adrenergic blocking agents on erythropoietin production in rabbits exposed to hypoxia. J Pharmacol Exp Ther 193: 176-181, 1975. 41. Fu B, Xue J, Li Z, Shi X, Jiang BH, and Fang J. Chrysin inhibits expression of hypoxia-inducible factor-1alpha through reducing hypoxia-inducible factor-1alpha stability and inhibiting its protein synthesis. Molecular cancer therapeutics 6: 220-226, 2007. 42. Galandrin S, and Bouvier M. Distinct signaling profiles of beta1 and beta2 adrenergic receptor ligands toward adenylyl cyclase and mitogen-activated protein kinase reveals the pluridimensionality of efficacy. Mol Pharmacol 70: 1575-1584, 2006. 43. Galie N, Humbert M, Vachiery JL, Gibbs S, Lang I, Torbicki A, Simonneau G, Peacock A, Vonk Noordegraaf A, Beghetti M, Ghofrani A, Gomez Sanchez MA, Hansmann G, Klepetko W, Lancellotti P, Matucci M, McDonagh T, Pierard LA, Trindade PT, Zompatori M, and Hoeper M. 2015 ESC/ERS Guidelines for the diagnosis and treatment of pulmonary hypertension: The Joint Task Force for the Diagnosis and Treatment of Pulmonary Hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): Endorsed by: Association for European Paediatric

and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Respir J 46: 903-975, 2015. 44. Giaid A, Yanagisawa M, Langleben D, Michel RP, Levy R, Shennib H, Kimura S, Masaki T, Duguid WP, and Stewart DJ. Expression of endothelin-1 in the lungs of patients with pulmonary hypertension. N Engl J Med 328: 1732- 1739, 1993. 45. Gonzalez JP, Ramachandran J, Xie LH, Contreras JE, and Fraidenraich D. Selective Connexin43 Inhibition Prevents Isoproterenol-Induced Arrhythmias and Lethality in Muscular Dystrophy Mice. Sci Rep 5: 13490, 2015. 46. Grinnan D, Bogaard HJ, Grizzard J, Van Tassell B, Abbate A, DeWilde C, Priday A, and Voelkel NF. Treatment of group I pulmonary arterial hypertension with carvedilol is safe. Am J Respir Crit Care Med 189: 1562-1564, 2014. 47. Guescini M, Genedani S, Stocchi V, and Agnati LF. Astrocytes and Glioblastoma cells release exosomes carrying mtDNA. Journal of neural transmission (Vienna, Austria : 1996) 117: 1-4, 2010. 48. Hanania NA, Singh S, El-Wali R, Flashner M, Franklin AE, Garner WJ, Dickey BF, Parra S, Ruoss S, Shardonofsky F, O'Connor BJ, Page C, and Bond RA. The safety and effects of the beta-blocker, nadolol, in mild asthma: an open-label pilot study. Pulmonary pharmacology & therapeutics 21: 134-141, 2008. 49. Hayakawa K, Esposito E, Wang X, Terasaki Y, Liu Y, Xing C, Ji X, and Lo EH. Transfer of mitochondria from astrocytes to neurons after stroke. Nature 535: 551-555, 2016. 50. Heijnen HF, Schiel AE, Fijnheer R, Geuze HJ, and Sixma JJ. Activated platelets release two types of membrane vesicles: microvesicles by surface shedding and exosomes derived from exocytosis of multivesicular bodies and alpha-granules. Blood 94: 3791-3799, 1999. 51. Hellwig-Burgel T, Rutkowski K, Metzen E, Fandrey J, and Jelkmann W. Interleukin-1beta and tumor necrosis factor-alpha stimulate DNA binding of hypoxia-inducible factor-1. Blood 94: 1561-1567, 1999. 52. Hewitson KS, Lienard BM, McDonough MA, Clifton IJ, Butler D, Soares AS, Oldham NJ, McNeill LA, and Schofield CJ. Structural and mechanistic studies on the inhibition of the hypoxia-inducible transcription factor hydroxylases by tricarboxylic acid cycle intermediates. J Biol Chem 282: 3293- 3301, 2007. 53. Holscher M, Schafer K, Krull S, Farhat K, Hesse A, Silter M, Lin Y, Pichler BJ, Thistlethwaite P, El-Armouche A, Maier LS, Katschinski DM, and Zieseniss A. Unfavourable consequences of chronic cardiac HIF-1alpha stabilization. Cardiovasc Res 94: 77-86, 2012. 54. Hough KP, Trevor JL, Strenkowski JG, Wang Y, Chacko BK, Tousif S, Chanda D, Steele C, Antony VB, Dokland T, Ouyang X, Zhang J, Duncan SR, Thannickal VJ, Darley-Usmar VM, and Deshane JS. Exosomal transfer of mitochondria from airway myeloid-derived regulatory cells to T cells. Redox Biol 18: 54-64, 2018.

55. Hu CJ, Iyer S, Sataur A, Covello KL, Chodosh LA, and Simon MC. Differential regulation of the transcriptional activities of hypoxia-inducible factor 1 alpha (HIF-1alpha) and HIF-2alpha in stem cells. Molecular and cellular biology 26: 3514-3526, 2006. 56. Hu HT, Ma QY, Zhang D, Shen SG, Han L, Ma YD, Li RF, and Xie KP. HIF-1alpha links beta-adrenoceptor agonists and pancreatic cancer cells under normoxic condition. Acta Pharmacol Sin 31: 102-110, 2010. 57. Hu J, Discher DJ, Bishopric NH, and Webster KA. Hypoxia regulates expression of the endothelin-1 gene through a proximal hypoxia-inducible factor- 1 binding site on the antisense strand. Biochem Biophys Res Commun 245: 894- 899, 1998. 58. Hu SS, Zhang HG, Zhang QJ, and Xiu RJ. Circulating CD62P small microparticles levels are increased in hypertension. International journal of clinical and experimental pathology 7: 5324-5326, 2014. 59. Hu W, Zhang L, Li MX, Shen J, Liu XD, Xiao ZG, Wu DL, Ho IHT, Wu JCY, Cheung CKY, Zhang YC, Lau AHY, Ashktorab H, Smoot DT, Fang EF, Chan MTV, Gin T, Gong W, Wu WKK, and Cho CH. Vitamin D3 activates the autolysosomal degradation function against Helicobacter pylori through the PDIA3 receptor in gastric epithelial cells. Autophagy 1-19, 2019. 60. Huang LE, Gu J, Schau M, and Bunn HF. Regulation of hypoxia- inducible factor 1alpha is mediated by an O2-dependent degradation domain via the ubiquitin-proteasome pathway. Proceedings of the National Academy of Sciences of the United States of America 95: 7987-7992, 1998. 61. Huang X, Yuan T, Tschannen M, Sun Z, Jacob H, Du M, Liang M, Dittmar RL, Liu Y, Liang M, Kohli M, Thibodeau SN, Boardman L, and Wang L. Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC genomics 14: 319, 2013. 62. Islam MN, Das SR, Emin MT, Wei M, Sun L, Westphalen K, Rowlands DJ, Quadri SK, Bhattacharya S, and Bhattacharya J. Mitochondrial transfer from bone-marrow-derived stromal cells to pulmonary alveoli protects against acute lung injury. Nat Med 18: 759-765, 2012. 63. Iyer SS, He Q, Janczy JR, Elliott EI, Zhong Z, Olivier AK, Sadler JJ, Knepper-Adrian V, Han R, Qiao L, Eisenbarth SC, Nauseef WM, Cassel SL, and Sutterwala FS. Mitochondrial cardiolipin is required for Nlrp3 inflammasome activation. Immunity 39: 311-323, 2013. 64. January B, Seibold A, Whaley B, Hipkin RW, Lin D, Schonbrunn A, Barber R, and Clark RB. beta2-adrenergic receptor desensitization, internalization, and phosphorylation in response to full and partial agonists. J Biol Chem 272: 23871-23879, 1997. 65. Jiang BH, Rue E, Wang GL, Roe R, and Semenza GL. Dimerization, DNA binding, and transactivation properties of hypoxia-inducible factor 1. J Biol Chem 271: 17771-17778, 1996. 66. Kacimi R, Richalet JP, Corsin A, Abousahl I, and Crozatier B. Hypoxia-induced downregulation of beta-adrenergic receptors in rat heart. J Appl Physiol (1985) 73: 1377-1382, 1992.

67. Kahsai AW, Xiao K, Rajagopal S, Ahn S, Shukla AK, Sun J, Oas TG, and Lefkowitz RJ. Multiple ligand-specific conformations of the beta2-adrenergic receptor. Nat Chem Biol 7: 692-700, 2011. 68. Kaira K, Okumura T, Ohde Y, Takahashi T, Murakami H, Oriuchi N, Endo M, Kondo H, Nakajima T, and Yamamoto N. Correlation between 18F- FDG uptake on PET and molecular biology in metastatic pulmonary tumors. J Nucl Med 52: 705-711, 2011. 69. Kallio PJ, Wilson WJ, O'Brien S, Makino Y, and Poellinger L. Regulation of the hypoxia-inducible transcription factor 1alpha by the ubiquitin- proteasome pathway. J Biol Chem 274: 6519-6525, 1999. 70. Kandere-Grzybowska K, Letourneau R, Kempuraj D, Donelan J, Poplawski S, Boucher W, Athanassiou A, and Theoharides TC. IL-1 induces vesicular secretion of IL-6 without degranulation from human mast cells. Journal of immunology (Baltimore, Md : 1950) 171: 4830-4836, 2003. 71. Kaneko FT, Arroliga AC, Dweik RA, Comhair SA, Laskowski D, Oppedisano R, Thomassen MJ, and Erzurum SC. Biochemical reaction products of nitric oxide as quantitative markers of primary pulmonary hypertension. Am J Respir Crit Care Med 158: 917-923, 1998. 72. Kasahara N, Kaira K, Bao P, Higuchi T, Arisaka Y, Erkhem-Ochir B, Sunaga N, Ohtaki Y, Yajima T, Kosaka T, Oyama T, Yokobori T, Asao T, Nishiyama M, Tsushima Y, Kuwano H, Shimizu K, and Mogi A. Correlation of tumor-related immunity with 18F-FDG-PET in pulmonary squamous-cell carcinoma. Lung Cancer 119: 71-77, 2018. 73. Kassis S, and Fishman PH. Functional alteration of the beta-adrenergic receptor during desensitization of mammalian adenylate cyclase by beta- agonists. Proceedings of the National Academy of Sciences of the United States of America 81: 6686-6690, 1984. 74. Keranen T, Hommo T, Hamalainen M, Moilanen E, and Korhonen R. Anti-Inflammatory Effects of beta2-Receptor Agonists Salbutamol and Terbutaline Are Mediated by MKP-1. PLoS One 11: e0148144, 2016. 75. Kim JW, Tchernyshyov I, Semenza GL, and Dang CV. HIF-1-mediated expression of pyruvate dehydrogenase kinase: a metabolic switch required for cellular adaptation to hypoxia. Cell Metab 3: 177-185, 2006. 76. Kim KS, Abraham D, Williams B, Violin JD, Mao L, and Rockman HA. beta-Arrestin-biased AT1R stimulation promotes cell survival during acute cardiac injury. Am J Physiol Heart Circ Physiol 303: H1001-1010, 2012. 77. Kogure T, Yan IK, Lin WL, and Patel T. Extracellular Vesicle-Mediated Transfer of a Novel Long Noncoding RNA TUC339: A Mechanism of Intercellular Signaling in Human Hepatocellular Cancer. Genes & cancer 4: 261-272, 2013. 78. Koivunen P, Hirsila M, Remes AM, Hassinen IE, Kivirikko KI, and Myllyharju J. Inhibition of hypoxia-inducible factor (HIF) hydroxylases by citric acid cycle intermediates: possible links between cell metabolism and stabilization of HIF. J Biol Chem 282: 4524-4532, 2007. 79. Krasel C, Bunemann M, Lorenz K, and Lohse MJ. Beta-arrestin binding to the beta2-adrenergic receptor requires both receptor phosphorylation and receptor activation. J Biol Chem 280: 9528-9535, 2005.

80. Laffont B, Corduan A, Ple H, Duchez AC, Cloutier N, Boilard E, and Provost P. Activated platelets can deliver mRNA regulatory Ago2*microRNA complexes to endothelial cells via microparticles. Blood 122: 253-261, 2013. 81. Lanza IR, and Nair KS. Functional assessment of isolated mitochondria in vitro. Methods Enzymol 457: 349-372, 2009. 82. Laughner E, Taghavi P, Chiles K, Mahon PC, and Semenza GL. HER2 (neu) signaling increases the rate of hypoxia-inducible factor 1alpha (HIF-1alpha) synthesis: novel mechanism for HIF-1-mediated vascular endothelial growth factor expression. Molecular and cellular biology 21: 3995-4004, 2001. 83. Leff P. The two-state model of receptor activation. Trends Pharmacol Sci 16: 89-97, 1995. 84. Leff P, Scaramellini C, Law C, and McKechnie K. A three-state receptor model of agonist action. Trends Pharmacol Sci 18: 355-362, 1997. 85. Lefkowitz RJ, Cotecchia S, Samama P, and Costa T. Constitutive activity of receptors coupled to guanine nucleotide regulatory proteins. Trends Pharmacol Sci 14: 303-307, 1993. 86. Li H, Lu ZZ, Chen C, Song Y, Xiao H, and Zhang YY. Echocardiographic assessment of beta-adrenoceptor stimulation-induced heart failure with reduced heart rate in mice. Clin Exp Pharmacol Physiol 41: 58-66, 2014. 87. Liu J, Zhang J, Ginzburg Y, Li H, Xue F, De Franceschi L, Chasis JA, Mohandas N, and An X. Quantitative analysis of murine terminal erythroid differentiation in vivo: novel method to study normal and disordered erythropoiesis. Blood 121: e43-49, 2013. 88. Lu H, Dalgard CL, Mohyeldin A, McFate T, Tait AS, and Verma A. Reversible inactivation of HIF-1 prolyl hydroxylases allows cell metabolism to control basal HIF-1. J Biol Chem 280: 41928-41939, 2005. 89. Lundgrin EL, Park MM, Sharp J, Tang WH, Thomas JD, Asosingh K, Comhair SA, DiFilippo FP, Neumann DR, Davis L, Graham BB, Tuder RM, Dostanic I, and Erzurum SC. Fasting 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography to detect metabolic changes in pulmonary arterial hypertension hearts over 1 year. Ann Am Thorac Soc 10: 1-9, 2013. 90. Luttrell LM, Roudabush FL, Choy EW, Miller WE, Field ME, Pierce KL, and Lefkowitz RJ. Activation and targeting of extracellular signal-regulated kinases by beta-arrestin scaffolds. Proceedings of the National Academy of Sciences of the United States of America 98: 2449-2454, 2001. 91. Machado MP, Rocha AM, de Oliveira LF, de Cuba MB, de Oliveira Loss I, Castellano LR, Silva MV, Machado JR, Nascentes GA, Paiva LH, Savino W, Junior VR, Brum PC, Prado VF, Prado MA, Silva EL, Montano N, Ramirez LE, and Dias da Silva VJ. Autonomic nervous system modulation affects the inflammatory immune response in mice with acute Chagas disease. Exp Physiol 97: 1186-1202, 2012. 92. MacKenzie A, Wilson HL, Kiss-Toth E, Dower SK, North RA, and Surprenant A. Rapid secretion of interleukin-1beta by microvesicle shedding. Immunity 15: 825-835, 2001.

93. Maeda A, and Fadeel B. Mitochondria released by cells undergoing TNF- alpha-induced necroptosis act as danger signals. Cell death & disease 5: e1312, 2014. 94. Manglik A, Kim TH, Masureel M, Altenbach C, Yang Z, Hilger D, Lerch MT, Kobilka TS, Thian FS, Hubbell WL, Prosser RS, and Kobilka BK. Structural Insights into the Dynamic Process of beta2-Adrenergic Receptor Signaling. Cell 161: 1101-1111, 2015. 95. Manglik A, Lin H, Aryal DK, McCorvy JD, Dengler D, Corder G, Levit A, Kling RC, Bernat V, Hubner H, Huang XP, Sassano MF, Giguere PM, Lober S, Da D, Scherrer G, Kobilka BK, Gmeiner P, Roth BL, and Shoichet BK. Structure-based discovery of opioid analgesics with reduced side effects. Nature 537: 185-190, 2016. 96. Marsboom G, Wietholt C, Haney CR, Toth PT, Ryan JJ, Morrow E, Thenappan T, Bache-Wiig P, Piao L, Paul J, Chen CT, and Archer SL. Lung (1)(8)F-fluorodeoxyglucose positron emission tomography for diagnosis and monitoring of pulmonary arterial hypertension. Am J Respir Crit Care Med 185: 670-679, 2012. 97. Martyniuk TV, Konosova ID, and Chazova IE. [Use of nebivolol in patients with idiopathic pulmonary hypertension: results of the pilot study]. Terapevticheskii arkhiv 84: 49-53, 2012. 98. Masri FA, Xu W, Comhair SA, Asosingh K, Koo M, Vasanji A, Drazba J, Anand-Apte B, and Erzurum SC. Hyperproliferative apoptosis-resistant endothelial cells in idiopathic pulmonary arterial hypertension. Am J Physiol Lung Cell Mol Physiol 293: L548-554, 2007. 99. Maxwell PH, Dachs GU, Gleadle JM, Nicholls LG, Harris AL, Stratford IJ, Hankinson O, Pugh CW, and Ratcliffe PJ. Hypoxia-inducible factor-1 modulates gene expression in solid tumors and influences both angiogenesis and tumor growth. Proceedings of the National Academy of Sciences of the United States of America 94: 8104-8109, 1997. 100. McDonald PH, Chow CW, Miller WE, Laporte SA, Field ME, Lin FT, Davis RJ, and Lefkowitz RJ. Beta-arrestin 2: a receptor-regulated MAPK scaffold for the activation of JNK3. Science 290: 1574-1577, 2000. 101. Miranda KC, Bond DT, McKee M, Skog J, Paunescu TG, Da Silva N, Brown D, and Russo LM. Nucleic acids within urinary exosomes/microvesicles are potential biomarkers for renal disease. Kidney Int 78: 191-199, 2010. 102. Monasky MM, Taglieri DM, Henze M, Warren CM, Utter MS, Soergel DG, Violin JD, and Solaro RJ. The beta-arrestin-biased ligand TRV120023 inhibits angiotensin II-induced cardiac hypertrophy while preserving enhanced myofilament response to calcium. Am J Physiol Heart Circ Physiol 305: H856- 866, 2013. 103. Morelli AE, Larregina AT, Shufesky WJ, Sullivan ML, Stolz DB, Papworth GD, Zahorchak AF, Logar AJ, Wang Z, Watkins SC, Falo LD, Jr., and Thomson AW. Endocytosis, intracellular sorting, and processing of exosomes by dendritic cells. Blood 104: 3257-3266, 2004. 104. Moretti C, Grosso Marra W, D'Ascenzo F, Omede P, Cannillo M, Libertucci D, Fusaro E, Meynet I, Giordana F, Salera D, Annone U, Chen SL,

Marra S, and Gaita F. Beta blocker for patients with pulmonary arterial hypertension: A single center experience. Int J Cardiol 184: 528-532, 2015. 105. Naga Prasad SV, Barak LS, Rapacciuolo A, Caron MG, and Rockman HA. Agonist-dependent recruitment of phosphoinositide 3-kinase to the membrane by beta-adrenergic receptor kinase 1. A role in receptor sequestration. J Biol Chem 276: 18953-18959, 2001. 106. Nawaz M, Camussi G, Valadi H, Nazarenko I, Ekström K, Wang X, Principe S, Shah N, Ashraf NM, Fatima F, Neder L, and Kislinger T. The emerging role of extracellular vesicles as biomarkers for urogenital cancers. Nature Reviews Urology 11: 688, 2014. 107. Nguyen LP, Lin R, Parra S, Omoluabi O, Hanania NA, Tuvim MJ, Knoll BJ, Dickey BF, and Bond RA. Beta2-adrenoceptor signaling is required for the development of an asthma phenotype in a murine model. Proceedings of the National Academy of Sciences of the United States of America 106: 2435-2440, 2009. 108. Nobles KN, Xiao K, Ahn S, Shukla AK, Lam CM, Rajagopal S, Strachan RT, Huang TY, Bressler EA, Hara MR, Shenoy SK, Gygi SP, and Lefkowitz RJ. Distinct phosphorylation sites on the beta(2)-adrenergic receptor establish a barcode that encodes differential functions of beta-arrestin. Sci Signal 4: ra51, 2011. 109. Obregon C, Rothen-Rutishauser B, Gitahi SK, Gehr P, and Nicod LP. Exovesicles from human activated dendritic cells fuse with resting dendritic cells, allowing them to present alloantigens. Am J Pathol 169: 2127-2136, 2006. 110. Oehmcke S, Morgelin M, Malmstrom J, Linder A, Chew M, Thorlacius H, and Herwald H. Stimulation of blood mononuclear cells with bacterial virulence factors leads to the release of pro-coagulant and pro-inflammatory microparticles. Cellular microbiology 14: 107-119, 2012. 111. Ogawa Y, Miura Y, Harazono A, Kanai-Azuma M, Akimoto Y, Kawakami H, Yamaguchi T, Toda T, Endo T, Tsubuki M, and Yanoshita R. Proteomic analysis of two types of exosomes in human whole saliva. Biological & pharmaceutical bulletin 34: 13-23, 2011. 112. Papandreou I, Cairns RA, Fontana L, Lim AL, and Denko NC. HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption. Cell Metab 3: 187-197, 2006. 113. Piao L, Fang YH, Parikh KS, Ryan JJ, D'Souza KM, Theccanat T, Toth PT, Pogoriler J, Paul J, Blaxall BC, Akhter SA, and Archer SL. GRK2- mediated inhibition of adrenergic and dopaminergic signaling in right ventricular hypertrophy: therapeutic implications in pulmonary hypertension. Circulation 126: 2859-2869, 2012. 114. Pollara J, Edwards RW, Lin L, Bendersky VA, and Brennan TV. Circulating mitochondria in deceased organ donors are associated with immune activation and early allograft dysfunction. JCI Insight 3: 2018. 115. Prins KW, and Thenappan T. World Health Organization Group I Pulmonary Hypertension: Epidemiology and Pathophysiology. Cardiol Clin 34: 363-374, 2016.

100

116. Provencher S, Herve P, Jais X, Lebrec D, Humbert M, Simonneau G, and Sitbon O. Deleterious effects of beta-blockers on exercise capacity and hemodynamics in patients with portopulmonary hypertension. Gastroenterology 130: 120-126, 2006. 117. Rajagopal S, Ahn S, Rominger DH, Gowen-MacDonald W, Lam CM, Dewire SM, Violin JD, and Lefkowitz RJ. Quantifying ligand bias at seven- transmembrane receptors. Mol Pharmacol 80: 367-377, 2011. 118. Ramachandran S, and Palanisamy V. Horizontal transfer of RNAs: exosomes as mediators of intercellular communication. Wiley Interdiscip Rev RNA 3: 286-293, 2012. 119. Ratajczak J, Miekus K, Kucia M, Zhang J, Reca R, Dvorak P, and Ratajczak MZ. Embryonic stem cell-derived microvesicles reprogram hematopoietic progenitors: evidence for horizontal transfer of mRNA and protein delivery. Leukemia 20: 847-856, 2006. 120. Record M, Carayon K, Poirot M, and Silvente-Poirot S. Exosomes as new vesicular lipid transporters involved in cell-cell communication and various pathophysiologies. Biochim Biophys Acta 1841: 108-120, 2014. 121. Rhee JS, Black M, Schubert U, Fischer S, Morgenstern E, Hammes HP, and Preissner KT. The functional role of blood platelet components in angiogenesis. Thromb Haemost 92: 394-402, 2004. 122. Rich S, Pogoriler J, Husain AN, Toth PT, Gomberg-Maitland M, and Archer SL. Long-term effects of epoprostenol on the pulmonary vasculature in idiopathic pulmonary arterial hypertension. Chest 138: 1234-1239, 2010. 123. Rich S, Seidlitz M, Dodin E, Osimani D, Judd D, Genthner D, McLaughlin V, and Francis G. The short-term effects of digoxin in patients with right ventricular dysfunction from pulmonary hypertension. Chest 114: 787-792, 1998. 124. Richard DE, Berra E, Gothie E, Roux D, and Pouyssegur J. p42/p44 mitogen-activated protein kinases phosphorylate hypoxia-inducible factor 1alpha (HIF-1alpha) and enhance the transcriptional activity of HIF-1. J Biol Chem 274: 32631-32637, 1999. 125. Roche-Singh K, Honbo N, and Karliner J. Hypoxia and glucose independently regulate the beta-adrenergic receptor-adenylate cyclase system in cardiac myocytes. J Clin Invest 88: 204-213, 1991. 126. Rockman HA, Koch WJ, and Lefkowitz RJ. Seven-transmembrane- spanning receptors and heart function. Nature 415: 206-212, 2002. 127. Rose JA, Wanner N, Cheong HI, Queisser K, Barrett P, Park M, Hite C, Naga Prasad SV, Erzurum S, and Asosingh K. Flow Cytometric Quantification of Peripheral Blood Cell beta-Adrenergic Receptor Density and Urinary Endothelial Cell-Derived Microparticles in Pulmonary Arterial Hypertension. PLoS One 11: e0156940, 2016. 128. Ryba DM, Li J, Cowan CL, Russell B, Wolska BM, and Solaro RJ. Long-Term Biased beta-Arrestin Signaling Improves Cardiac Structure and Function in Dilated Cardiomyopathy. Circulation 135: 1056-1070, 2017.

101

129. Samama P, Cotecchia S, Costa T, and Lefkowitz RJ. A mutation- induced activated state of the beta 2-adrenergic receptor. Extending the ternary complex model. J Biol Chem 268: 4625-4636, 1993. 130. Sato Y, Tsuyama T, Sato C, Karim MF, Yoshizawa T, Inoue M, and Yamagata K. Hypoxia reduces HNF4alpha/MODY1 protein expression in pancreatic beta-cells by activating AMP-activated protein kinase. J Biol Chem 292: 8716-8728, 2017. 131. Saygin D, Highland KB, Farha S, Park M, Sharp J, Roach EC, Tang WHW, Thomas JD, Erzurum SC, Neumann DR, and DiFilippo FP. Metabolic and Functional Evaluation of the Heart and Lungs in Pulmonary Hypertension by Gated 2-[18F]-Fluoro-2-deoxy-D-glucose Positron Emission Tomography. Pulm Circ 7: 428-438, 2017. 132. Selak MA, Armour SM, MacKenzie ED, Boulahbel H, Watson DG, Mansfield KD, Pan Y, Simon MC, Thompson CB, and Gottlieb E. Succinate links TCA cycle dysfunction to oncogenesis by inhibiting HIF-alpha prolyl hydroxylase. Cancer Cell 7: 77-85, 2005. 133. Semenza GL. Hypoxia-inducible factor 1 and cardiovascular disease. Annu Rev Physiol 76: 39-56, 2014. 134. Semenza GL, Roth PH, Fang HM, and Wang GL. Transcriptional regulation of genes encoding glycolytic enzymes by hypoxia-inducible factor 1. J Biol Chem 269: 23757-23763, 1994. 135. Sharifpanah F, Saliu F, Bekhite MM, Wartenberg M, and Sauer H. Beta-adrenergic receptor antagonists inhibit vasculogenesis of embryonic stem cells by downregulation of nitric oxide generation and interference with VEGF signalling. Cell Tissue Res 358: 443-452, 2014. 136. Shenoy SK, Drake MT, Nelson CD, Houtz DA, Xiao K, Madabushi S, Reiter E, Premont RT, Lichtarge O, and Lefkowitz RJ. beta-arrestin- dependent, G protein-independent ERK1/2 activation by the beta2 adrenergic receptor. J Biol Chem 281: 1261-1273, 2006. 137. Shenoy SK, Han S, Zhao YL, Hara MR, Oliver T, Cao Y, and Dewhirst MW. beta-arrestin1 mediates metastatic growth of breast cancer cells by facilitating HIF-1-dependent VEGF expression. Oncogene 31: 282-292, 2012. 138. Shimoda LA, Yun X, and Sikka G. Revisiting the role of hypoxia- inducible factors in pulmonary hypertension. Current Opinion in Physiology 7: 33- 40, 2019. 139. Short PM, Williamson PA, Anderson WJ, and Lipworth BJ. Randomized placebo-controlled trial to evaluate chronic dosing effects of propranolol in asthma. Am J Respir Crit Care Med 187: 1308-1314, 2013. 140. Shyu K-G, Lu M-J, Chang H, Sun H-Y, Wang B-W, and Kuan P. Carvedilol Modulates the Expression of Hypoxia-Inducible Factor-1α and Vascular Endothelial Growth Factor in a Rat Model of Volume-Overload Heart Failure. Journal of Cardiac Failure 11: 152-159, 2005. 141. Skog J, Wurdinger T, van Rijn S, Meijer DH, Gainche L, Sena-Esteves M, Curry WT, Jr., Carter BS, Krichevsky AM, and Breakefield XO. Glioblastoma microvesicles transport RNA and proteins that promote tumour growth and provide diagnostic biomarkers. Nat Cell Biol 10: 1470-1476, 2008.

102

142. Sodhi A, Montaner S, Patel V, Zohar M, Bais C, Mesri EA, and Gutkind JS. The Kaposi's sarcoma-associated herpes virus G protein-coupled receptor up-regulates vascular endothelial growth factor expression and secretion through mitogen-activated protein kinase and p38 pathways acting on hypoxia-inducible factor 1alpha. Cancer Res 60: 4873-4880, 2000. 143. Spees JL, Olson SD, Whitney MJ, and Prockop DJ. Mitochondrial transfer between cells can rescue aerobic respiration. Proceedings of the National Academy of Sciences of the United States of America 103: 1283-1288, 2006. 144. Stanek M, Picard LP, Schmidt MF, Kaindl JM, Hubner H, Bouvier M, Weikert D, and Gmeiner P. Hybridization of beta-Adrenergic Agonists and Antagonists Confers G Protein Bias. J Med Chem 62: 5111-5131, 2019. 145. Stiles GL, Caron MG, and Lefkowitz RJ. Beta-adrenergic receptors: biochemical mechanisms of physiological regulation. Physiological reviews 64: 661-743, 1984. 146. Street JM, Barran PE, Mackay CL, Weidt S, Balmforth C, Walsh TS, Chalmers RT, Webb DJ, and Dear JW. Identification and proteomic profiling of exosomes in human cerebrospinal fluid. Journal of translational medicine 10: 5, 2012. 147. Subra C, Laulagnier K, Perret B, and Record M. Exosome lipidomics unravels lipid sorting at the level of multivesicular bodies. Biochimie 89: 205-212, 2007. 148. Sun Y, Cheng Z, Ma L, and Pei G. Beta-arrestin2 is critically involved in CXCR4-mediated chemotaxis, and this is mediated by its enhancement of p38 MAPK activation. J Biol Chem 277: 49212-49219, 2002. 149. Takahashi Y, Nishikawa M, Shinotsuka H, Matsui Y, Ohara S, Imai T, and Takakura Y. Visualization and in vivo tracking of the exosomes of murine melanoma B16-BL6 cells in mice after intravenous injection. Journal of biotechnology 165: 77-84, 2013. 150. Thakur BK, Zhang H, Becker A, Matei I, Huang Y, Costa-Silva B, Zheng Y, Hoshino A, Brazier H, Xiang J, Williams C, Rodriguez-Barrueco R, Silva JM, Zhang W, Hearn S, Elemento O, Paknejad N, Manova-Todorova K, Welte K, Bromberg J, Peinado H, and Lyden D. Double-stranded DNA in exosomes: a novel biomarker in cancer detection. Cell Res 24: 766-769, 2014. 151. Thanawala VJ, Valdez DJ, Joshi R, Forkuo GS, Parra S, Knoll BJ, Bouvier M, Leff P, and Bond RA. beta-Blockers have differential effects on the murine asthma phenotype. Br J Pharmacol 172: 4833-4846, 2015. 152. Thenappan T, Roy SS, Duval S, Glassner-Kolmin C, and Gomberg- Maitland M. beta-blocker therapy is not associated with adverse outcomes in patients with pulmonary arterial hypertension: a propensity score analysis. Circ Heart Fail 7: 903-910, 2014. 153. Tian H, McKnight SL, and Russell DW. Endothelial PAS domain protein 1 (EPAS1), a transcription factor selectively expressed in endothelial cells. Genes & development 11: 72-82, 1997.

103

154. Touyz RM, and Schiffrin EL. Signal transduction mechanisms mediating the physiological and pathophysiological actions of angiotensin II in vascular smooth muscle cells. Pharmacological reviews 52: 639-672, 2000. 155. Tuder RM, Chacon M, Alger L, Wang J, Taraseviciene-Stewart L, Kasahara Y, Cool CD, Bishop AE, Geraci M, Semenza GL, Yacoub M, Polak JM, and Voelkel NF. Expression of angiogenesis-related molecules in plexiform lesions in severe pulmonary hypertension: evidence for a process of disordered angiogenesis. J Pathol 195: 367-374, 2001. 156. Tuder RM, Cool CD, Geraci MW, Wang J, Abman SH, Wright L, Badesch D, and Voelkel NF. Prostacyclin synthase expression is decreased in lungs from patients with severe pulmonary hypertension. Am J Respir Crit Care Med 159: 1925-1932, 1999. 157. Valadi H, Ekstrom K, Bossios A, Sjostrand M, Lee JJ, and Lotvall JO. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol 9: 654-659, 2007. 158. van Campen JS, de Boer K, van de Veerdonk MC, van der Bruggen CE, Allaart CP, Raijmakers PG, Heymans MW, Marcus JT, Harms HJ, Handoko ML, de Man FS, Vonk Noordegraaf A, and Bogaard HJ. Bisoprolol in idiopathic pulmonary arterial hypertension: an explorative study. Eur Respir J 48: 787-796, 2016. 159. van der Pol E, Coumans FA, Sturk A, Nieuwland R, and van Leeuwen TG. Refractive index determination of nanoparticles in suspension using nanoparticle tracking analysis. Nano Lett 14: 6195-6201, 2014. 160. van der Westhuizen ET, Breton B, Christopoulos A, and Bouvier M. Quantification of ligand bias for clinically relevant beta2-adrenergic receptor ligands: implications for drug taxonomy. Mol Pharmacol 85: 492-509, 2014. 161. Violin JD, DiPilato LM, Yildirim N, Elston TC, Zhang J, and Lefkowitz RJ. beta2-adrenergic receptor signaling and desensitization elucidated by quantitative modeling of real time cAMP dynamics. J Biol Chem 283: 2949-2961, 2008. 162. Wang GJ, Liu Y, Qin A, Shah SV, Deng ZB, Xiang X, Cheng Z, Liu C, Wang J, Zhang L, Grizzle WE, and Zhang HG. Thymus exosomes-like particles induce regulatory T cells. Journal of immunology (Baltimore, Md : 1950) 181: 5242-5248, 2008. 163. Wang GL, Jiang BH, Rue EA, and Semenza GL. Hypoxia-inducible factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated by cellular O2 tension. Proceedings of the National Academy of Sciences of the United States of America 92: 5510-5514, 1995. 164. Wang J, Hanada K, Staus DP, Makara MA, Dahal GR, Chen Q, Ahles A, Engelhardt S, and Rockman HA. Galphai is required for carvedilol-induced beta1 adrenergic receptor beta-arrestin biased signaling. Nat Commun 8: 1706, 2017. 165. Willekens FL, Werre JM, Kruijt JK, Roerdinkholder-Stoelwinder B, Groenen-Dopp YA, van den Bos AG, Bosman GJ, and van Berkel TJ. Liver Kupffer cells rapidly remove red blood cell-derived vesicles from the circulation by scavenger receptors. Blood 105: 2141-2145, 2005.

104

166. Winter RJD, Dickinson KEJ, Rudd RM, and Sever PS. Tissue specific modulation of beta-adrenoceptor number in rats with chronic hypoxia with an attenuated response to down-regulation by salbutamol. Clinical Science 70: 159- 165, 1986. 167. Wisler JW, DeWire SM, Whalen EJ, Violin JD, Drake MT, Ahn S, Shenoy SK, and Lefkowitz RJ. A unique mechanism of beta-blocker action: carvedilol stimulates beta-arrestin signaling. Proceedings of the National Academy of Sciences of the United States of America 104: 16657-16662, 2007. 168. Wolfle D, and Jungermann K. Long-term effects of physiological oxygen concentrations on glycolysis and gluconeogenesis in hepatocyte cultures. European journal of biochemistry 151: 299-303, 1985. 169. Xie L, Xiao K, Whalen EJ, Forrester MT, Freeman RS, Fong G, Gygi SP, Lefkowitz RJ, and Stamler JS. Oxygen-regulated beta(2)-adrenergic receptor hydroxylation by EGLN3 and ubiquitylation by pVHL. Science Signaling 2: 2009. 170. Xu W, Kaneko FT, Zheng S, Comhair SA, Janocha AJ, Goggans T, Thunnissen FB, Farver C, Hazen SL, Jennings C, Dweik RA, Arroliga AC, and Erzurum SC. Increased arginase II and decreased NO synthesis in endothelial cells of patients with pulmonary arterial hypertension. FASEB journal : official publication of the Federation of American Societies for Experimental Biology 18: 1746-1748, 2004. 171. Xu W, Koeck T, Lara AR, Neumann D, DiFilippo FP, Koo M, Janocha AJ, Masri FA, Arroliga AC, Jennings C, Dweik RA, Tuder RM, Stuehr DJ, and Erzurum SC. Alterations of cellular bioenergetics in pulmonary artery endothelial cells. Proceedings of the National Academy of Sciences of the United States of America 104: 1342-1347, 2007. 172. Yan G, Hu S, Wang Q, Wang D, Wang J, Qiao Y, Tang C, Ma G, and Gu Y. [Effects of early digoxin treatment on hypoxia-induced pulmonary artery hypertension]. Zhonghua yi xue za zhi 94: 139-143, 2014. 173. Yu AY, Shimoda LA, Iyer NV, Huso DL, Sun X, McWilliams R, Beaty T, Sham JS, Wiener CM, Sylvester JT, and Semenza GL. Impaired physiological responses to chronic hypoxia in mice partially deficient for hypoxia-inducible factor 1alpha. J Clin Invest 103: 691-696, 1999. 174. Zarrindast MR, Ramezani-Tehrani B, and Ghadimi M. Effects of adrenoceptor agonists and antagonists on morphine-induced Straub tail in mice. Pharmacology, biochemistry, and behavior 72: 203-207, 2002. 175. Zelzer E, Levy Y, Kahana C, Shilo BZ, Rubinstein M, and Cohen B. Insulin induces transcription of target genes through the hypoxia-inducible factor HIF-1alpha/ARNT. Embo j 17: 5085-5094, 1998. 176. Zhang H, Qian DZ, Tan YS, Lee K, Gao P, Ren YR, Rey S, Hammers H, Chang D, Pili R, Dang CV, Liu JO, and Semenza GL. Digoxin and other cardiac glycosides inhibit HIF-1alpha synthesis and block tumor growth. Proceedings of the National Academy of Sciences of the United States of America 105: 19579-19586, 2008.

105

177. Zhang Q, Raoof M, Chen Y, Sumi Y, Sursal T, Junger W, Brohi K, Itagaki K, and Hauser CJ. Circulating mitochondrial DAMPs cause inflammatory responses to injury. Nature 464: 104-107, 2010. 178. Zhao Z, Zhou Y, Hilton T, Li F, Han C, Liu L, Yuan H, Li Y, Xu X, Wu X, Zhang F, Thiagarajan P, Cap A, Shi FD, Zhang J, and Dong JF. Extracellular mitochondria released from traumatized brains induced platelet procoagulant activity. Haematologica 2019. 179. Zhu M, Barbas AS, Lin L, Scheuermann U, Bishawi M, and Brennan TV. Mitochondria Released by Apoptotic Cell Death Initiate Innate Immune Responses. Immunohorizons 2: 384-397, 2018. 180. Zivny J, Ostadal B, Neuwirt J, Prochazka J, and Pelouch V. Effect of beta adrenergic blocking agents on erythropoiesis in rats. The Journal of Pharmacology and Experimental Therapeutics 226: 1983.

106