Investigations of 12Α-Hydroxylated Bile Acid Signaling in Intestinal Organoids

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INVESTIGATIONS OF 12α-HYDROXYLATED BILE ACID SIGNALING IN INTESTINAL ORGANOIDS

Tiara Rinjani Ahmad

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences

COLUMBIA UNIVERSITY

2019

Investigations of 12α-Hydroxylated Bile Acid Signaling in Intestinal Organoids

Tiara R. Ahmad

Bile acids (BAs) comprise a diverse group of cholesterol metabolites with multiple modes of action. Much of the role of BAs and their receptors in energy homeostasis has been discerned from studies on genetic and/or pharmacologic manipulations. Additionally, changes in BA metabolism and transport have been reported in settings of insulin resistance, obesity, and liver dysfunction. Thus, BA-based interventions have been proposed for treatment of metabolic diseases. However, the heterogeneity of endogenous BAs lends to different affinities for and potencies in activating the various BA receptors, and the effects of altering BA composition per se are incompletely understood. In this dissertation, we aimed to characterize the effects of altering

BA composition by stimulating intestinal organoids with distinct BA pools modeled after those in humans and mice. Unexpectedly, we found that BA composition regulated expression of the manganese transporter encoded by Slc30a10 and manganese efflux from cells, suggesting a role for BAs in metal homeostasis. We also identified genes that were similarly and differentially regulated by the distinct mouse and human BA pools. Overall, our studies reveal a pathway by which BAs could modulate micronutrient metabolism, which might also mediate known effects of BAs on macronutrient metabolism.

Table of Contents

List of Figures ……………………………………………………………………………………... iii

Acknowledgements ………………………………………………………………………………… v

Chapter 1: Introduction ………...………………………………………………………………… 1

Bile acids in glucose metabolism and insulin signalling—mechanisms and research needs ……. 2

Introduction ……………………………………………………………………………………. 4

Nonreceptor-mediated mechanisms …………………………………………………………... 6

Receptor-mediated mechanisms ………………………………………………………………. 8

Conditions and pathologies that affect BAs …………………………………………………... 12

Future research needs …………………………………………………………………………. 20

Tables ………………………………………………………………………………………….. 22

Figure legends …………………………………………………………………………………. 24

Box 1 …………………………………………………………………………………………… 26

Figures …………………………………………………………………………………………. 28

Manganese…………………………………………………………………………………………. 31

Roles of Mn in biology ………………………………………………………………………… 31

Mn toxicity …………………………………………………………………………………….. 34

Regulators of Mn homeostasis ………………………………………………………………... 36

Figures …………………………………………………………………………………………. 41

Chapter 2: Validation of Gut Organoids for Bile Acid Signaling Studies …………………….. 43

Introduction ………………………………………………………………………………….... 43

i Results …………………………………………………………………………………...... 45

Discussion …………………………………………………………………………………...... 49

Materials and Methods ………………………………………………………………………... 50

Figures …………………………………………………………………………………...... 56

Chapter 3: Bile Acid Regulation of Intestinal Manganese Transport ……...………………….. 62

Introduction ……………………………………………………………….…………………... 62

Results …………………………………………………………………………………………. 64

Discussion ……………………………………………………………………………………... 71

Materials and Methods ………………………………………………………………………... 76

Figures …………………………………………………………………………………………. 81

Table …………………………………………………………………………………………… 91

Chapter 4: Conclusions and Future Directions …………………………………………………. 93

4.1 BA regulation of Mn homeostasis ………………………………………………………… 93

4.2 Coordinate regulation of Mn transporters by low 12HBA pools ………………………... 94

4.3 Potential reciprocal regulation: Mn effects on BAs ……………………………………….. 96

4.4 BA-dependent induction of intestinal gene expression through VDR and FXR ………… 98

4.5 BA-dependent suppression of intestinal gene expression ……………………………….. 100

4.6 Final remarks: BAs and Mn in health and diseases ………………………………………. 101

Figures ………………………………………………………………………………………... 102

References ………………………………………………………………………………………... 109

ii List of Figures

Chapter 1

Part 1

Figure 1. Bile acid synthesis, modification, and physicochemical properties.

Figure 2. Bile acid composition.

Figure 3. Effects of bile acids on metabolic processes throughout the body.

Figure 4. Physiologic and pathologic conditions and therapies that influence bile acids.

Part 2

Figure 1. Mn in active sites of human proteins.

Figure 2. Mn-dependent detoxification of superoxide (O2•–) carried out by SOD2.

Figure 3. An overview of key organs and transporters in Mn homeostasis.

Chapter 2

Figure 2.1. hiPSC-derived gut organoids express intestine epithelial cell markers and BA

receptors.

Figure 2.2 BA pool composition.

Figure 2.3. TGR5 signaling in hiPSC-derived gut organoids increase GLP-1 secretion.

Figure 2.4. BA pool induces FGF19 expression in hiPSC-derived gut organoids.

Figure 2.5. Composition of high (80%) 12HBA and low (20%) 12HBA pools.

Figure 2.6. High 12HBA pool blunts induction of FXR targets.

Figure 2.7. Functional TGR5 and FXR signaling in mouse primary gut organoids.

iii Figure 2.8 Effects of changing BA composition on FXR transcriptional targets in mouse

primary gut organoids.

Figure 2.9. Effects of altering BA/micelle composition on transcription of FXR target

genes.

Chapter 3

Figure 1. RNA sequencing reveals differential regulation of gene expression by BA pool

composition.

Figure 2. Validation of differential expression of FXR and VDR target genes.

Figure 3. Low 12HBA pools regulate Mn efflux from gut organoids and Caco-2 cells.

Figure 4. Slc30a10 is transcriptionally regulated by LCA–VDR signaling.

Figure 5. VDR activation increases Slc30a10 transcription in vivo.

Chapter 4

Figure 4.1. Model of Mn transport regulation by BA pool composition.

Figure 4.2. Transcriptional effects of low 12HBAs and LCA–VDR signaling on other Mn

transporters.

Figure 4.3. Potential reciprocal regulation of BAs by Mn.

Figure 4.5. Suppression of intestinal gene expression by BAs.

iv Acknowledgements

I would like to thank my mentor, Dr. Rebecca Haeusler, for her guidance, patience, and generosity over the years of my graduate studies. I would like to thank my committee members

Dr. Dieter Egli, Dr. Ira Tabas, and Dr. Anthony Ferrante for their suggestions and thoughtful discussions. I am especially grateful to Dr. Alison Kohan, my external defense committee member, for teaching me how to isolate primary intestinal crypts. I would also like to thank every

Haeusler Lab member, past and present, for their everyday support. I am indebted to Dr. Enrico

Bertaggia and Dr. Sei Higuchi for their help with mouse experiments, as well as their wisdom and resourceful tricks to make bench work easier. I was lucky to work with Allison Hung, an incredible undergraduate researcher, who helped with organoids maintenance and experiments.

I am also grateful to Nicole Muse and Niroshan Shanmugarajah, who helped acquire in vivo data in the late stages of my studies. Although our studies rarely overlapped, I am also thankful to everyone on the HDL cholesterol part of the lab for being amazing labmates: Dr. Conchi

Izquierdo, Dr. Sam Lee, Dr. Clarence Manuel, and Kendra Zhong. I also want to thank everyone in the Pajvani, Egli, and Accili Labs for all their help sharing reagents and equipment, and advice.

I am also thankful to our collaborators, Dr. Somshuvra Mukhopadhyay and Dr. Diane Re for sharing samples and reagents. Lastly, this PhD work would not have been possible without friends and family who gave me many hugs and went on climbing, dancing, and food adventures with me. Thank you all so very much.

v Chapter 1

Introduction

The overarching goal of this dissertation was to better understand the role of bile acids (BAs), particularly as signaling molecules, in the small intestine. In addition to absorbing nutrients, the small intestine produces hormones that signal to itself and other organs, including liver, pancreas, gallbladder, and brain. These hormones regulate cholesterol conversion to BAs

(Fgf15/FGF19), insulin secretion (GLP-1), gallbladder contraction (CCK), gut motility

(serotonin, GLP-2), and satiety (PYY), making the small intestine a significant player in energy homeostasis. Changes in the BA pool have been reported to affect intestinal lipid absorption and hormone secretion, and might affect additional functions of the small intestine. The first part of this chapter is a review of BAs and the diverse mechanisms by which they affect glycemia. This review has been accepted by Nature Reviews Endocrinology and is awaiting final editorial proof.

In our studies, we found that BA composition transcriptionally regulates the manganese efflux transporter SLC30A10. Thus, the second part of this Introduction provides an overview of manganese. As most of the work I share here was done using primary mouse ileal organoids and designer BA pools, we show our validation of the intestinal organoid system in Chapter 2. In

Chapter 3, we dissect the determinants of differential regulation of Slc30a10 by BA composition; this work is being prepared for publication. Finally, we discuss the implications of our findings and suggest future research directions in Chapter 4.

1 Part 1

Bile acids in glucose metabolism and insulin signalling — mechanisms and research needs

Tiara R. Ahmad1 and Rebecca A. Haeusler1*

1Naomi Berrie Diabetes Center and Department of Pathology and Cell Biology, Columbia University Medical Center New York, NY, USA

*email: Rebecca A. Haeusler [email protected]

2 Abstract

Of all the novel glucoregulatory molecules discovered in the past twenty years, bile acids are notable for the fact that they were hiding in plain sight. Bile acids (BAs) had been well-known for their requirement in dietary lipid absorption and biliary cholesterol secretion, due to their micelle-forming properties. However, it wasn’t until 1999 that BAs were discovered to be endogenous ligands for the nuclear receptor FXR. Since that time, BAs have been shown to act through multiple receptors (PXR, VDR, TGR5, S1PR2), as well as receptor-independent mechanisms (membrane dynamics, allosteric modulation of NAPE-PLD). We now also have an appreciation for the range of physiologic, pathophysiologic, and therapeutic conditions in which endogenous BAs are altered, raising the possibility that BAs contribute to the effects of those conditions on glycaemia. In this Review, we highlight the mechanisms by which BAs regulate glucose homeostasis, the settings in which endogenous BAs are altered, and provide suggestions for future research.

Key points

• Pathways in multiple tissues have been reported to link bile acids with glycaemia

• Normal and disease settings, and several medications, influence bile acid levels and

composition

• When interpreting studies with genetic and pharmacologic modulations of BA receptors,

one should take into consideration that these modulations affect BA concentration,

distribution, and composition.

3 • Rodent models with humanized BA composition will enhance the relevance of basic

research findings to human health

• Human cells and organoid models should be used to address the interspecies differences

in BA receptor structure

Introduction

Over the last 15 years, bile acids (BAs) have emerged as unexpected players in glucose homeostasis. In addition to their well-established role in promoting lipid absorption, BAs are also implicated in glucose metabolism and the secretion of glucoregulatory hormones. In this

Review we highlight the mechanisms by which BAs influence glucose metabolism and suggest directions for future research.

BAs are cholesterol catabolites that are generated in hepatocytes (Figure 1a). Following synthesis, BAs are conjugated to an amino acid and secreted into the bile. BAs are actively reabsorbed by enterocytes in the terminal ileum and travel via the portal vein to hepatocytes, where they are taken up and recycled . A portion of BAs, however, escape ileal uptake, become modified by intestinal microbes, and are subsequently absorbed via passive diffusion in the colon3. Thus, BAs are found at high levels in liver, bile and intestine (Table 1). Due to incomplete reuptake by hepatocytes, BAs are detected at low levels in plasma. The presence of BAs in the systemic circulation raises the possibility that BAs directly affect tissues throughout the body.

High-affinity BA uptake transporters, however, are thought to be expressed predominantly in liver and ileum 2–5. Thus, it is unclear what concentration of BAs could penetrate parenchymal

4 cells or interstitial fluid in most tissues. The enterohepatic circulation of BAs has been reviewed extensively in REF2.

Numerous BA species are detectable in humans (Figure 1b). They differ primarily in their hydroxylation sites and the presence or absence of a conjugated amino acid, predominantly glycine in humans (of note, in rodents BAs are predominantly conjugated with taurine). In both humans and mice, a minor portion of BAs also undergo sulfation6,7. BA modifications alter their physicochemical properties, including the so-called ‘hydrophobicity’ of a BA molecule8,9. It is worth noting that this descriptor is derived from the chromatographic separation method, whereby BAs are designated more hydrophobic if they are retained longer on a nonpolar chromatography column during elution with a polar solvent 9,10. BAs are more accurately described as amphipathic, meaning they have a hydrophobic surface and a hydrophilic surface, and the number and position of hydroxyl groups on a BA molecule determine its amphipathic nature (Figure 1c)10. In addition to these physical descriptors, BAs can also be categorized as primary (synthesized in the liver) versus secondary (generated by microbial modification of primary BAs in the gut)11. The composition of the BA pool is remodeled during numerous pathophysiologic and experimental conditions12–16, and this could influence BA function.

Examples of BA pool remodeling will be discussed in the second half of this review.

A unique feature of BAs is that they can act via multiple completely distinct molecular mechanisms, for example, by emulsifying lipids, by affecting cellular membranes, through allosteric effects and via receptor-mediated pathways. Some of the mechanisms that BAs act upon are known to have effects on glycaemia, and a number of other mechanisms have the potential to effect glycaemia. In the first part of this Review we describe these mechanisms, many of which were revealed by studies in preclinical models. In the second section, we discuss

5 conditions that affect BAs and which might, in turn, affect glycaemia. Such conditions include changes in insulin sensitivity, microbiome and liver diseases. We will also examine interventions and therapeutics that alter BA-dependent pathways, deliberately or unexpectedly. Finally, we highlight gaps in our knowledge and questions for future consideration.

Nonreceptor-mediated mechanisms

The canonical physicochemical effect of BAs is to support the emulsification of water-insoluble lipids. It is possible that this and other nonreceptor-mediated BA effects could affect glycaemia, directly or indirectly.

Lipid emulsification. By their amphipathic nature, BAs, in combination with polar phospholipids, incorporate dietary lipids into mixed micellar solutions. This micellization process increases the surface area of luminal lipids and improves the accessibility of intestinal lipases and efficiency of fat hydrolysis17. This property of BAs is essential to lipid absorption and total-body energy balance.

Different BA species are differentially able to promote lipid absorption18,19. This ability to promote lipid absorption could be influenced by a BA’s micelle-forming properties8 and its permeability in the unstirred water layer lining the intestinal epithelium20. There is also evidence that enterocyte intracellular cholesterol esterification is regulated by BAs, though the mechanism of this is unknown21.

Effects on cell membranes. BAs can insert into cell membranes, including the plasma membrane, and impact membrane dynamics22,23. A 2014 study showed that this is the mechanism by which

6 BAs activate the BA-sensitive ion channel (BASIC) whose physiologic function remains elusive24.

At supraphysiologic doses, BAs can disrupt cell membranes and cause cell lysis25–27. Deoxycholic acid (DCA), a secondary BA produced by dehydroxylation of CA, is particularly potent, and taking advantage of this attribute is an injectable synthetic form of DCA, which was approved by the FDA for reduction of fat under the chin in 201628.

BAs might affect intracellular membranes as well. DCA reportedly colocalizes with the mitochondrial outer membrane and perturbs its structure29. Tauroursodeoxycholic acid

(TUDCA) is reported to protect against endoplasmic reticulum (ER) stress, and treating leptin- deficient ob/ob mice with TUDCA improved glycemia30,31. The molecular mechanisms by which

TUDCA functions are not clear, but could involve effects on the ER membrane itself.

Allosteric functions. BAs can directly bind and modulate the activities of certain proteins.

N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD) is an enzyme found in brain and intestine that converts membrane lipids into specialized bioactive lipids32. Products of

NAPE-PLD include arachidonoylethanolamide (anandamide) and oleoylethanolamide (OEA), the latter of which promotes GLP-1 secretion and both of which are involved in food intake regulation33. While solving the crystal structure of NAPE-PLD, researchers unexpectedly found

DCA within the hydrophobic substrate binding pocket34. DCA was found to bind and stabilize the enzyme, and enhance its enzymatic activity. Further studies showed that LCA, CDCA, and

35 DCA bind NAPE-PLD (KD ~ 20, 25, and 43 µM, respectively) . At sufficiently high concentrations, LCA inhibits NAPE-PLD, whereas CDCA and DCA activate it, but the

7 physiologic relevance of this, and any downstream effects on metabolism have not yet been investigated.

Receptor-mediated mechanisms

BAs activate several nuclear receptors and G protein-coupled receptors, with differing potencies

(Table 2). Much of our understanding of the roles of BA receptors in glycaemia comes from experiments using mouse knockouts, agonists and antagonists. An important consideration for interpreting such studies is that BAs regulate their own synthesis through a series of negative feedback loops that converge on the key enzymes CYP7A1 and CYP8B12,36,37. Therefore, experimentally manipulating BA receptors frequently alters BA levels and composition (Figure

2), which in turn influences other BA-sensitive pathways. In this section we will review the reported involvement of BA receptors in glucose homeostasis; published mechanisms are summarized in Figure 3. Of note, the reliance on preclinical models for these studies is a limitation. Mechanistic data in humans might be facilitated by identifying and studying individuals carrying genetic variants and by additional studies using receptor agonists.

FXR. The first BA-responsive receptor discovered38–40, FXR is highly expressed in liver, intestine and kidney. Its role in glucose homeostasis has been investigated in multiple studies 15,41–44. Some mouse studies observed beneficial effects of FXR activation41,42 , while others reported beneficial effects of deleting or inhibiting FXR43,45. Contradictions between studies could be due to differential effects in liver versus intestine, pharmacokinetics of agonists and/or antagonists, sex, age, diet and genetic background. It is also worth noting that nuclear receptor deletion,

8 antagonism, or absence of ligand are not necessarily equivalent, as endogenous nuclear receptors can have effects in the basal, unliganded state46.

The evidence that FXR activity is beneficial for glycaemia arises from studies on mice with FXR deficiency, as well as mice that were given FXR agonists. On chow diet, FXR–/– mice showed worse intraperitoneal (IP) glucose tolerance and lower glucose disposal during hyperinsulinemic-euglycemic clamp compared with wild–type mice42,47,48. Consistently, treating ob/ob and db/db mice with the FXR agonist GW4064 lowered glucose excursions during IP glucose and insulin tolerance tests42,47. The gut-restricted FXR agonist fexaramine improved glycemia and reduced diet-induced weight gain in mice15,41. The proposed mechanisms for FXR’s beneficial effects on glucose metabolism include: suppression of gluconeogenic genes, due to

FXR activation of the transcriptional repressor SHP48; protection from skeletal muscle lipotoxicity, via FXR-dependent liver lipid metabolism48; reduced weight gain due to adipose tissue browning, downstream of FXR-dependent alterations in BA composition41; increased

GLP-1 and insulin secretion, due to shifts in gut bacteria composition, which increase the TGR5 agonist TLCA15; and increased secretion of FGF15 and/or FGF19, described in detail below.

Conversely, other studies have reported that FXR inhibition improves glycaemia. Whole body FXR knockout mice and mice that lack FXR only in the intestinal epithelium had improved oral glucose tolerance, and this was frequently associated with reduced body weight43,45,49–51.

Compared to vehicle-treated animals, when challenged with high-fat diet, GW4064-treated mice displayed exacerbated weight gain, increased fasting glucose and insulin, and worsened glucose and insulin tolerance 44. Furthermore, antagonizing FXR activity by treating mice with glycine-β-

9 MCA resulted in improved insulin tolerance and oral glucose tolerance, and reduced fasting insulin, compared to vehicle-treated control mice43.

The proposed mechanisms for the beneficial effects of FXR inhibition include: decreased hepatic gluconeogenesis due to decreased pyruvate carboxylase activity; this is proposed to be downstream of lower FXR-dependent intestinal production of hepatotoxic serum ceramides50; reduced weight gain due to increased thermogenesis, also downstream of FXR-dependent production of serum ceramides43; release of FXR-dependent suppression of Proglucagon, the

GLP-1 precursor, and consequent increases in glucose-stimulated GLP-1 release51; delayed intestinal glucose absorption, due to increased glucose phosphorylation in enterocytes49; and release of FXR-dependent suppression of hepatic glycolytic genes52.

FGF15 and/or FGF19. By activating FXR, BAs induce robust transcription of the peptide hormone Fibroblast growth factor 15 (Fgf15) and its human ortholog FGF19. FGF15 and/or FGF

19, which are highly expressed in ileal enterocytes, have a key endocrine role in suppressing hepatic BA synthesis, which occurs through the FGFR4–b-Klotho receptor complex53. FGF15 and/or FGF 19 are also important for maintaining normoglycemia, as evidenced by the impaired glucose tolerance in FGF15–/– mice and glycaemic improvements after transgenic expression or injection of FGF1954–57. The beneficial effects of FGF15 and/or FGF 19 are potentially due to: reduced hepatic gluconeogenesis, downstream of FGF15 and/or FGF 19-dependent dephosphorylation of the gluconeogenic transcription factor CREB56; increased hepatic glycogen synthesis, due to FGF15/19-dependent activation of an ERK-GSK3a/b phosphorylation cascade57; reduced body weight and adiposity54,58, due to increased metabolic rate by increasing b-

10 Klotho-dependent sympathetic nerve activity in brown adipose tissue58; and increased insulin- independent peripheral glucose disposal59, downstream of FGF15/19 induction of ERK signaling in hypothalamic neurons58,60,61. Plasma FGF19 is reportedly reduced in patients with obesity and/or type 2 diabetes mellitus 62–64, and negatively correlated with BMI65. However, the endogenous functions of FGF19 have been called into question66,67.

The therapeutic prospects of FGF19 are potentially limited by the association of high levels of FGF15 and/or 19 with increased hepatocellular carcinoma in mice and humans68,69 .

However, nontumorigenic variants of FGF19 have been generated, and are now in development for liver diseases. Variants M70 and M52 have been shown to protect against fibrosis, steatohepatitis, and cholestasis in mice, effects that are expected to be secondary to suppression of BA synthesis70–72. M70 is also capable of suppressing BA synthesis in humans70, and in a phase

2 clinical trial, it markedly improved markers of liver damage, cholestasis, and inflammation in patients with primary biliary cholangitis73. A phase-2 trial for M70 in patients with nonalcoholic steatohepatitis is underway74.

VDR. Some BAs, namely LCA and 3-keto-LCA, can activate the nuclear vitamin D receptor

(VDR), although these BAs are poorly taken up into cells. Although micromolar levels of LCA can activate VDR (comparable to FXR activation by CDCA)75, the active form of vitamin D,

1a,25-dihydroxyvitamin D3 activates VDR at nanomolar concentrations, making LCA about

1000 times less potent than vitamin D. 76,77. Therefore, high doses of LCA are required to activate

VDR in vivo, and it occurs more strongly under conditions of vitamin D deficiency78. VDR has been reported to have a role in maintaining glycaemia, and this could be carried out via effects in

11 islets79, macrophages80 or endothelial cells81. However, few studies have specifically investigated the effects of LCA-to-VDR signalling on glucose homeostasis. In vitro studies suggest that the

LCA derivative LCA propionate protects b cells against dedifferentiation82. Another LCA derivative, tauro-LCA-3 sulfate, induces insulin resistance in cultured hepatocytes, though this was not specifically linked to VDR83. Whether physiological or pharmacological levels of LCA and its derivatives regulate glucose metabolism in vivo remains to be determined.

TGR5. The most extensively studied G protein-coupled receptor for BAs, TGR5 (also known as

GPBAR1) is expressed in a wide range of tissues84,85. Preclinical studies suggest that TGR5 has a protective role in glucose homeostasis. The most widely-reported mechanism by which this occurs is by TGR5-mediated increases in GLP-1 secretion, accompanied by increased insulin secretion86–90. Alternative mechanisms by which TGR5 may influence metabolism include

C/EBPb-dependent suppression of macrophage infiltration into white adipose tissue91 and increased energy expenditure92,93.

Conditions & treatments that affect BAs

Endogenous BAs are altered in multiple physiologic, pathophysiologic and therapeutic conditions, and it is possible that these alterations contribute to BA-driven glycaemic regulation12,13,15,94,95 (Figure 4). Investigating the effects of human conditions on BA pool size and composition is inherently challenging. Stable isotope kinetic studies are a gold-standard method for assessing the synthesis and turnover of BAs in vivo, but require specialized expertise and are typically limited to small sample sizes. For studying larger populations, accessible specimens

12 include plasma and faeces, and neither is a perfect representation of the concentrations and compositions of BA pools present in liver, gallbladder, or small intestine, the primary residences of BAs in the body. Nonetheless, in this section we Review the published literature, keeping these caveats in mind.

Impaired insulin signaling. Data from rodent models were the first to indicate that insulin signaling regulates BA production and composition. Compared to healthy control animals, rodent models of insulinopaenia and hyperglycaemia have increases in total BA pool size and a larger percentage of the BA pool consists of 12a-hydroxylated BAs96–98. The same is true in mice lacking hepatic insulin receptors99. The effects of hepatic insulin signaling on BA synthesis and composition are thought to be transcriptionally determined100. Evidence suggests that the transcription factor FOXO1, which is inactivated by insulin signaling, mediates insulin’s effects on BA composition101. See Box 1.

Several studies have analyzed plasma BAs and markers of BA synthesis and how they relate to insulin sensitivity in humans. Insulin resistance has been reported to be positively correlated with plasma BAs, especially primary BAs and/or 12a-hydroxylated BAs16,94,102. Obesity is associated with increased BA synthesis103–105, 12a-hydroxylation103 and alterations in BA transport12,103. Patients with type 2 diabetes mellitus have been reported to have increased taurine-conjugated BA species106. In addition, kinetic studies show increased synthesis of BAs, particularly CA, in patients with type 2 diabetes mellitus 107. Thus, preclinical and human studies support the consensus that hepatic insulin resistance increases BA synthesis, and may also cause other alterations in BA composition, such as increased 12a-hydroxylation. The dual concepts (i)

13 that insulin resistance, obesity or diabetes mellitus influence BA concentration and composition and (ii) that BA concentration and composition can influence energy metabolism, suggests the possibility of adaptive or maladaptive feed-forward signals contributing to metabolic disease.

Bariatric surgery. Since 2009, numerous papers have reported that BA concentration in systemic circulation are increased after Roux-en-Y gastric bypass, biliopancreatic diversion, and possibly vertical sleeve gastrectomy, but not adjustable gastric banding108. These findings are recapitulated in animal models, including mice, rats and minipigs108–111. The mechanisms by which bariatric surgeries cause increased circulating BAs are not yet known, and could be different between surgical procedures. Increased synthesis alone is not the explanation. BA synthesis is increased in patients after biliointestinal bypass and biliopancreatic diversion 112,113, potentially because these surgeries limit BA signalling in ileum, which would decrease FGF19-dependent suppression of

BA synthesis. Patients who have undergone Roux-en-Y gastric bypass or sleeve gastrectomy, BA synthesis is decreased in the short-term and later returns to the normal range 113–115. In sum, following metabolic surgery there are probably alterations in BA transport that cause increased circulating BAs. Preclinical models have suggested that BA uptake transporters in the ileum are increased109, or that BA uptake transporters in liver are decreased after surgery110,111. The effect of bariatric surgeries on BA composition have not come to consensus, potentially because of differences in surgical procedures, animals versus humans and environmental factors.

Whether or not alterations in BAs are the cause of improved glycaemia after bariatric surgery is also still up for debate. Proposed mechanisms include BA-driven increases in the secretion of GLP-1, insulin or FGF19108. Some human studies support correlations between these hormones and plasma BAs116, though BAs present in plasma are not necessarily representative of

14 BAs present in the relevant tissues. Evidence supporting a role for BAs in metabolic improvements following bariatric surgery has come from mice deficient in BA receptors. Mice lacking FXR117,118, the FXR target SHP119 or TGR5120,121 have all been reported to resist metabolic benefits of bariatric surgery. However, potential caveats arise due to differences between these knockouts and their wild-type controls before the surgery. Moreover, some have argued that the timing of elevated BAs does not coincide with improved glycemia after surgery115. Future mechanistic studies are required.

Liver diseases. It has been known for over sixty years that liver diseases differentially affect BA concentration, distribution and composition122. One area that has been extensively examined is intrahepatic cholestasis of pregnancy (ICP). ICP is characterized by impaired bile flow, as a consequence of genetic variation in hepatic BA transporters and high concentrations of pregnancy hormone metabolites, which competitively bind and reduce the activity of BA transporters and FXR123. Reduced activities of FXR and hepatic BA transporters cause elevations in maternal circulating plasma BAs and altered BA composition, with CA becoming a much larger portion of the pool124,125. Fetal plasma BAs, which are generated by the fetal liver, are also altered in ICP — concentrations are higher and CA predominates125. ICP increases risk of adverse fetal outcomes123.

ICP is also associated with metabolic dysfunction. Compared to healthy pregnant women, women with ICP are more likely to have impaired glucose tolerance and gestational diabetes 95,126.

Babies born to mothers with the condition are more likely to be large for gestational age compared to babies born to mothers with healthy pregnancies 95,127. In adolescent offspring of women who were affected by ICP, males show higher body mass index and fasting insulin levels

15 and females show higher hip and waist girth, compared to offspring of non-affected mothers128.

Whether or not BAs are responsible for these effects is unclear. In mice, feeding pregnant dams a

CA-rich diet results in offspring that are more susceptible to weight gain and glucose intolerance on a western diet128. These findings suggest the possibility of in utero metabolic programming in response to BAs.

The development of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) is strongly linked to insulin resistance and dysbiosis129. It has also been reported that in patients with NASH, liver tissue concentrations of BA are higher and composition is altered compared to disease-free control livers 130,131. Plasma BAs are also higher, with altered composition in NASH patients compared to healthy controls 132–137. These BA changes are reported to occur in patients with NASH with and without type 2 diabetes mellitus, compared with controls136. Because patients with NAFLD and NASH are typically more obese and more insulin resistant than control participants, Vanessa Legry and colleagues compared patients with NASH to control participants who were matched for body mass index and insulin resistance16. This analysis revealed that alterations in BA metabolism are associated with insulin resistance, rather than liver necroinflammation itself. These findings highlight the complex interactions between insulin resistance, BAs and NAFLD and NASH. Nonetheless, BA- dependent pathways are under vigorous pursuit as treatment for NASH, and these have been reviewed extensively elsewhere129,138.

Gut microbiome. The metabolism of BAs by gut microbes is an important determinant of BA composition. A common modification is the removal of the amino acid moiety of conjugated primary BAs, such as GCA and GCDCA, to create unconjugated or free BAs, such as CA and

16 CDCA (Fig. 1). This activity is carried out by bile salt hydrolases, which are expressed in a wide range of bacteria and archaea139. Unconjugated BAs can undergo dehydroxylation at the 7 position to form secondary BAs; for example, CA is converted to DCA and CDCA is converted to LCA. Other possible modifications include epimerization and oxidation140. Although these conversions occur primarily in the microbe-abundant colon where there are no active BA uptake transporters, unconjugated and secondary BAs can be passively absorbed2. Once returned to hepatocytes, unconjugated primary and secondary BAs can be re-conjugated2,141. However, the human liver is not efficient at re-hydroxylating secondary BA species; this is evidenced by the substantial portion (~30%) of the human BA pool made up of DCA and its conjugated forms

(Fig. 2) 142–144.

Agents that manipulate the microbiome can modify BA pool composition. Individuals treated for 7-days with the Gram-positive bacteria-directed antibiotic vancomycin showed significant reductions in secondary BAs in plasma and feces145. This effect occurred in response to vancomycin, which markedly altered the faecal microbiota composition, but not in response to amoxicillin. Indeed, different antibiotics have distinct effects on BA pool composition146.

Although it is outside the scope of this Review, it is worth noting that BAs can also influence the microbiome. A particularly intriguing example of this is presented by Clostridioides difficile: certain BAs (12a-hydroxylated species) promote the germination of C. difficile spores, while some BAs (secondary species) suppress vegetative growth147.

The consequences of microbiome-derived BAs on host metabolism are currently under investigation148 and new methodological advances hold the promise of new ways to investigate this. In 2018, Lina Yao and colleagues colonized gnotobiotic mice with isogenic bacterial strains

17 with or without bile salt hydrolase and found that eliminating BA deconjugation capacity was sufficient to attenuate high fat diet-induced weight gain149. Such approaches are likely to further refine the effect of the microbiome–BA–energy metabolism axis.

Therapeutics. Interventions that target BAs or BA signalling pathways are currently in use or being developed for metabolic indications150,151. BA sequestrants block intestinal BA reabsorption, consequently increasing BA fecal excretion and causing compensatory increases in

BA synthesis, which lowers plasma cholesterol152,153. BA sequestrants are now also known to improve glycaemia in patients with type 2 diabetes mellitus. A meta-analysis of 17 randomized controlled trials reported that BA sequestrants reduced HbA1C by 0.55%154. The mechanisms by which BA sequestrants improve glycaemia remain under debate. One possibility is that these resins increase BA concentration in colon thus activating BA-dependent secretion of GLP-1155, but this has not been confirmed in other studies156–158. One study provides evidence that BA sequestrant actually reduces BA-induced GLP-1 secretion159. Mechanistic studies suggest that

TGR5 is localized on the basolateral membrane of enteroendocrine cells and thus BAs must be absorbed in order to activate it160,161, and this would preclude TGR5 activation by sequestrant- bound BAs. Another possibility is that sequestrants increase splanchnic glucose uptake and utilization156, potentially due to lower FXR signaling in intestine49.

Another mechanism to block BA reabsorption from intestine is to inhibit the apical sodium-bile acid transporter (ASBT), and ASBT inhibitors were developed to lower LDL- cholesterol150,162,163. Studies in rodent models of type 2 diabetes mellitus suggested that, like BA sequestrants, ASBT inhibitors could also improve glycaemia164–166. Consistent with this, inhibiting

ASBT in patients with type 2 diabetes mellitus improves glycaemia167,168. In nondiabetic

18 participants, ASBT inhibitors might increase GLP-1, but do not affect plasma levels of glucose

169,170.

Obeticholic acid (OCA, INT-747) is an FXR agonist that is a leading candidate in clinical trials for NASH. In a small study that included patients with type 2 diabetes mellitus, OCA improved insulin sensitivity in hyperinsulinemic-euglycaemic clamps171. However, in a larger study OCA increased fasting insulin and thus worsened insulin resistance, as calculated by the homeostasis model of assessment (HOMA)172. Further studies are required to determine the effects of OCA on glycaemia in humans. We note that in addition to its direct effects on FXR- dependent energy metabolism pathways, OCA (and any other agonist or antagonist of FXR) will also have major consequences on BA concentrations and composition, because of the potent,

FXR-mediated negative feedback loops on CYP7A1 and CYP8B1, thus potentially influencing other BA-dependent pathways.

The BA TUDCA has long been used in the treatment of liver diseases, due to its ability to increase bile flow. Rodent studies suggested TUDCA might also improve glycaemia, potentially through its effects on ER stress in metabolic tissues and/or b cells31,173. Indeed, treating individuals who are obese for four weeks with TUDCA (1750 mg per day) resulted improved hepatic and muscle insulin sensitivity174. However, this treatment did not affect ER stress markers, and another study with the related unconjugated molecule UDCA (20 mg per kg per day) actually induced some ER stress markers in liver175. Thus the mechanisms of TUDCA and

UDCA continue to be elusive.

Metformin is the most widely used anti-diabetes drug and numerous mechanisms of action have been proposed, including several implicating BAs. One possibility is that metformin

19 impairs intestinal BA uptake176,177, potentially increasing GLP-1 secretion. Another human study reported that metformin enhanced BA-induced GLP-1 secretion178. Metformin is known to activate AMPK, and it has been suggested that AMPK directly phosphorylates and inhibits FXR activity179. Other evidence indicates that metformin’s effect to alter the gut microbiome changes

BA levels and/or composition, resulting in lower intestinal FXR activity180,181.

Future research needs

To fill in the gaps in our understanding of the mechanisms linking BAs with glycaemia, especially those of clinical relevance, several laboratory approaches can be undertaken. First, many of rodent models of BA receptor activation and/or inhibition are associated with alterations in BA composition (Figure 2). Therefore, it is not possible to separate the direct effects of the receptor on glucose metabolism pathways per se from its indirect effects (via altered BA composition) on

TGR5, or other receptor-mediated or nonreceptor-mediated BA effects. One way to approach this concern is to use mice with controlled BA pools, such as those lacking the Cyp2c family of enzymes, which generate the 6-hydroxylated MCAs182; those lacking Cyp8b1, which generates

12a-hydroxylated BAs, and which is known to effect glycaemia via its effects on BA composition13,183,184; and those with designer microbiota reconstitution149.

Second, lack of BA receptors or BA synthesis enzymes might engender long-term and compensatory phenotypes that make data interpretation challenging. Exemplifying this are the studies of bariatric surgery in BA receptor knockout mice, which have phenotypic differences from wild-type mice at baseline. Temporal control of genetic knockouts, using inducible systems, could temper these caveats.

20 Third, there are differences in BA composition between humans and mice (Figure 2).

Humans have predominantly glycine-conjugated BAs (compared to taurine), abundance of DCA and conjugated forms (compared to rodents, which efficiently re-hydroxylate DCA into CA), and very low levels of MCAs (compared to high levels in mice and rats). One potential approach could be to use human liver chimeric mice, although these are known to retain a substantial portion of murine hepatocytes. At a minimum, researchers should keep these differences in mind and consider comparing humanized versus murine BA pools where possible, such as in vitro experiments.

Fourth, there are differences in the primary structure of FXR between species that influence sensitivity to certain BA subtypes185. These differences call for using human cells when possible, and stem cell-derived organoid methods might provide novel experimental platforms.

Finally, systems biology approaches might help resolve the complexity of the BA functionality network (Figure 4). Ultimately, clinical and translational studies in human subjects will have the most impact in determining the mechanisms linking BAs with glucose metabolism.

Conclusions

BAs are unique in their ability to act as structural molecules, allosteric modulators and signalling molecules. It is through a combination of these mechanisms that BAs affect key aspects of metabolic homeostasis. Whether or not these are druggable targets for patients with type 2 diabetes mellitus is not yet clear. New opportunities and experimental tools will allow basic, translational and clinical researchers to answer this question.

21 Table 1. Concentration of bile acids found in human tissues and compartments

Tissue Concentration Reference Systemic plasma/serum 0.2-22.0 µM 104,186,187 Portal venous plasma/serum 9-43 µM 186,188,189 Gallbladder bile 31-234 mM 143,144 Common bile duct 42-204 mM 142,190 Duodenum contents–fasting 0.3-9.6 mM 191,192 Duodenum contents–postprandial 8.3-11.9 mM 192 Jejunum contents–fasting 0.8-5.5 mM 191 Jejunum contents–postprandial 5-8 mM 193 Upper ileum contents–postprandial 10 mM 193 Lower ileum contents–postprandial 2 mM 193 Cecum contents 0.2-1 mM 194 Feces ~4.5 µmol/g 195 Liver ~60 nmol/g 130,196 (note: liver biopsies contain bile canaliculi and ducts in addition to hepatocytes) Subcutaneous white adipose tissue ~0.2 nmol/g 187

Different studies quantified BA levels using different extraction methods, processing of blood specimens (plasma vs. serum), and using different chromatography and mass spectrometry techniques. Please see individual references for details.

22 Table 2. Individual effects of bile acids on bile acid receptors

FXR EC50/IC50 TGR5 EC50 VDR PXR EC50 EC50 CA 100 - 200 µM 197 7.72 µM 85 no effect 198 no effect 198 > 10 µM 84 13.6 µM DCA 50 µM 40 1.01–1.25 µM 85,199 no effect 198 50.2 µM 198 50 - 75 µM 197 CDCA 1-2 µM 197 4 - 4.43 µM 84,85 no effect 198 (T) 104 µM 198 4.5 µM 38 (T) 1.92 µM 199 5.2 µM 185 (G) 3.88 µM 199 7 µM 75 10 µM 39,197 (T, G) 10 µM 38 10 - 30 µM 200 20 µM 39,197 25 - 50 µM 197 50 µM 40 LCA 50 µM 40 35 nM 84 8 µM 39 10.2 µM 198 (T) 0.33 µM 85 12.1 µM 201 0.53 µM 85 21.6 µM 198 3 µM 84 3-keto-LCA 3 µM 75 8.3 µM 198 6.8 µM 201 UDCA no effect 38 36.4 µM 199 no effect 75 no effect 85 202 198 198 a-MCA IC50 (T) 28 µM 101.7 µM 56 µM 202 198 198 b-MCA IC50 (T) 40 µM no effect no effect HDCA 31.6 µM 199

Abbreviations: cholic acid (CA), deoxycholic acid (DCA), chenodeoxycholic acid (CDCA), lithocholic acid (LCA), ursodeoxycholic acid (UDCA), muricholic acid (MCA), hyodeoxycholic acid (HDCA). (T) and (G) refer to values specifically for taurine and glycine conjugates.

We note that different studies use different systems (cell lysates, different cell lines) and methods (competitive binding assays, cAMP levels, cAMP-responsive luciferase reporter, etc.) to determine EC50 and IC50 values. Please see individual references for details.

23 Figure 1. Bile acid synthesis, modification, and physicochemical properties. (a) Bile acid synthesis occurs only in the liver. In the classic pathway of bile acid synthesis, cholesterol is hydroxylated in the 7a position by the enzyme CYP7A1. Alternatively, cholesterol is first converted to an oxysterol prior to being 7a-hydroxylated by the enzymes CYP7B1 or CYP39A1.

These oxysterols can arise in the liver, through the enzyme CYP27A1, or they can arise in other cells—such as macrophages via CYP27A1, or brain via CYP46A1—then travel to the liver. After the initial step, which is considered rate-limiting, over a dozen enzymatic reactions proceed to generate the primary bile acid molecule chenodeoxycholic acid (CDCA). An intermediate of bile acid synthesis, 7a-hydroxy-4-cholesten-3-one, can undergo 12a-hydroxylation by the enzyme

CYP8B1, and subsequently proceed through the additional steps. This results in the generation of the second primary bile acid found in humans, cholic acid (CA). Bile acids are conjugated to an amino acid such as glycine (G), and secreted into the bile. Bile acids enter the duodenum directly or are stored in the gallbladder until postprandial gallbladder contraction. Most bile acids are reabsorbed from the terminal ileum by the active transporter apical sodium-bile acid transporter

(ASBT). A minor portion travel into the colon where they can be deconjugated and dehydroxylated by gut microbes, producing bile acids that can be passively absorbed. From the portal vein, bile acids are efficiently taken up into hepatocytes and recycled. A small fraction enters the systemic circulation. (b) The major bile acid species found in humans and mice. (c)

Schematic demonstrating the amphipathic nature of bile acids.

Figure 2. Bile acid composition. (a) Average bile acid composition in human biliary bile and in enterohepatic tissues (including bile) of wild-type mice. Human biliary bile data are averages from 142–144. Mouse bile acid pool data is averaged from 58 wild-type mice across multiple of our

24 own published and unpublished studies. TMCA represents the sum of taurine-conjugated ⍺-, β-,

ω-muricholic acids. (b) Effects of genetic knockouts36,182,203–206 and pharmacological treatments41,44,202,207 on murine bile acid composition. Data for each BA species are the sum of conjugated and unconjugated, and are calculated based on [% in experimental pool / % in control pool]. PX20606 and GW4064 are FXR agonists. Fexaramine is a gut-restricted FXR agonist. *In germ-free mice, no unconjugated BAs are detected.

Figure 3. Effects of bile acids on metabolic processes throughout the body. The primary sites of bile acid function are liver and intestine, which are enriched in bile acids and bile acid receptors. Through their ability to promote secretion of hormones such as GLP-1, FGF19, and others, bile acids can indirectly impact other tissues, including the brain. Furthermore, low levels of bile acids are found in systemic circulation, allowing for potential direct effects of bile acids in tissues throughout the body. (R) indicates supporting data is mostly from rodents; (H) indicates supporting data in humans, human cells, or purified human proteins.

Effects in CNS: peripheral glucose disposal59 (r), energy expenditure58 (r), food intake208 (r); in islets: ER stress31,173 (r), insulin secretion209 (r); in liver: gluconeogenic gene expression48,56 (r), glycogen synthesis57 (r), hepatic triglyceride metabolism210 (r), hepatic lipotoxicity48 (r), lipoprotein turnover152,211 (r, h), in adipose tissue: immune cell infiltration91 (r), thermogenesis58; in gut: lipid absorption13,183,184 (r), vitamin absorption212 (r, h), glucose absorption49 (r), ceramide production50,213 (r), NAPE-PLD activity34,35 (purified human protein), GLP-1 secretion86–90,214 (r, h), PYY secretion90,214 (r, h), FGF19 secretion214 (r, h); in skeletal muscle: lipotoxicity48 (r).

Figure 4. Physiologic and pathologic conditions and therapies that influence bile acids. An individual’s total levels of bile acids, levels in selective tissues like gut or plasma, and the composition of those bile acid species can each influence bile acid functions. This includes functions mediated by receptors such as FXR and TGR5, as well as receptor-independent effects, such as nutrient absorption. Abbreviations: apical sodium-dependent bile acid transporter

(ASBT); bile acid (BA) sequestrants; tauroursodeoxycholic acid (TUDCA).

Box 1 Hepatic insulin signalling regulates BA pool composition in mice and humans

• The insulin-repressible FoxO transcription factors promote mRNA expression of the

sterol 12α hydroxylase, Cyp8b1, in murine liver. Hepatic FoxO1 ablation in mice reduces

12α-hydroxylated bile acids in enterohepatic tissues101. Triple hepatic ablation of FoxO1,

FoxO3, and FoxO4 exacerbates this phenotype [RA Haeusler, unpublished],

demonstrating redundant functions of FoxOs on Cyp8b1.

• Mouse and rat models of hyperglycaemia and insulinopaenia are surmised to have higher

FoxO activity, and they show increased 12α-hydroxylated bile acids. These include

rodents treated with β-cell toxins streptozotocin and alloxan, and NOD mice96–98,215. Mice

lacking hepatic insulin receptors also show increased 12α-hydroxylated bile acids101.

• Stable isotope kinetic studies in patients with type 2 diabetes, compared to controls

matched for body mass index, show increased synthesis of cholic acid, the primary 12α-

hydroxylated bile acid107.

26 • In nonobese human subjects, insulin resistance (as assessed by gold-standard

hyperinsulinemic-euglycemic clamp studies) is associated with increased plasma levels of

12α-hydroxylated bile acids94.

• Obese, insulin resistant individuals have higher Cyp8b1 activity compared to nonobese

controls, as determine by plasma levels of Cyp8b1’s product, 7a, 12α-dihydroxy-4-

cholesten-3-one103.

Summary: these studies demonstrate the identification of a molecular pathway directly linking insulin signalling with BA pool composition in mice, which translates to human pathophysiology. Investigation into the functional consequences of this pathway is being pursued by multiple research groups.

27 FIGURES

29 Glucose

30 Part 2

Manganese

In chapter 3, we uncovered the role of BAs in intestinal manganese (Mn) transport, which occurs via transcriptional regulation of the Mn efflux transporter Slc30a10. In mammals, the majority of

Mn is obtained from food and enters through intestinal absorption, and excess Mn is disposed of via biliary and intestinal excretion216,217. Here, we review (1) roles of Mn in cellular processes, (2) causes and effects of Mn toxicity, and (3) key players in Mn homeostasis.

Roles of Mn in biology

Mn is an essential micronutrient for all forms of life, from bacteria to mammals218. As a divalent metal ion, Mn2+ serves as a cofactor for many enzymes, described below. In addition, because it is a transition metal with several possible oxidation states, Mn can accept or donate electrons in redox reactions. Evidence for the necessity of Mn in multiple cellular and physiologic processes come from studying effects of Mn depletion in vitro219,220, experimentally inducing Mn deficiency in lab animals220–222 and recent identification of patients with missense mutations in the gene encoding the Mn importer SLC39A8223–225.

One of the most consequential roles of Mn is in protein glycosylation. The majority of secreted proteins and cell surface proteins undergo glycosylation, as do many intracellular proteins226,227.

Glycosyltransferases comprise families of enzymes that catalyze the attachment of sugar moieties

(glycans) to lipids, complex carbohydrates, and specific protein residues226. Many glycosyltransferases require metal ions (usually Mn2+ or Mg2+) for proper function226. However,

31 some glycosyltransferases exclusively use Mn2+, such as β-1,4-galactosyltransferase, which is necessary for galactosylation of glycoproteins228.

Glycosylation affects protein structure, function, solubility, and stability226. Not surprisingly, complete abrogation of either N- or O-glycosylation is embryonic lethal in mice226,229,230.

Moreover, when enzymes involved in glycan synthesis, transfer, or subsequent processing are defective, they result in congenital disorders of glycosylation (CDG)226. Notably, Mn depletion in

Chinese hamster ovary cells resulted in reduced N- and O-glycosylation231, and biallelic mutations in the Mn importer SLC39A8, which cause Mn deficiency, also lead to CDG

(designated CDG-IIn)223,224.

Mn is also a component of the antioxidant enzyme Mn-dependent superoxide dismutase

(MnSOD, also called SOD2). Rats on a Mn-deficient diet showed heart SOD2 activities lower than those of rats on Mn-adequate diet232,233. In vitro, mammalian cells depleted of Mn show reduced SOD2 activity and mitochondria function, making them susceptible to oxidative stress- induced apoptosis220,234. The mitochondrial dysfunction could be partly explained by the incorporation of iron into SOD2 under low Mn and/or excess iron conditions, resulting in a prooxidant enzyme220.

Mn can affect carbohydrate metabolism through its role as cofactor for the gluconeogenic enzymes pyruvate carboxylase (PC) and phosphoenolpyruvate carboxylase (PEPCK)221.

Compared to the control group, rats born to Mn-deficient dams and maintained on Mn-deficient diet had lower fasting PC and PEPCK activities, accompanied by lower insulin-to-glucagon ratios

32 and higher liver glycogen content, though there was no difference in plasma glucose levels221.

Another study reported that Mn-deficient rats had impaired oral glucose tolerance and lower glucose-stimulated insulin secretion (GSIS), suggesting Mn may impact islet function235. In a case report, a patient with diabetes had hypoglycemic episodes following administration of MnCl2

(either orally or intravenously)236.

Another Mn-dependent enzyme of interest is arginase. Arginase catalyzes the conversion of l- arginine into ornithine and urea, important for polyamine and proline synthesis as well as protection against ammonia237. Mammals have two isoforms of arginase: the cytosolic A1 isoform is predominantly expressed in the liver, while the mitochondrial A2 isoform is highly expressed in the kidney237. Endothelial cells of the vasculature express both isoforms237. In endothelial cells and macrophages, arginase competes with nitric oxide synthase (NOS) for l- arginine. Feeding rats Mn-deficient diets results in reduced liver238 and kidney arginase activity, along with increased plasma arginine239,240. The reduced arginase activity was accompanied by aorta vasodilation and improved renal function239,240. On the other hand, reduced Mn availability in striatal neurons leading to decreased arginase activity has been proposed to explain the accumulation of urea cycle intermediates in a mouse model of Huntington disease241. The interplay between Mn and l-arginine availability, arginase and NOS isoforms, and various cell types are research topics of interest for many pathologies237,242–245.

Because of the widespread involvement of Mn in biological processes, Mn deficiency has severe consequences. Feeding pregnant rats a Mn-deficient diet (1 µg/g) resulted in 90% pup mortality within the first 7 days, highlighting the necessity of Mn during development221. At a slightly

33 higher level of Mn (3 µg/g), pups survived past the 1-week mark but exhibited congenital ataxia221. In Mn-deficient mice, ataxia was due to abnormal development of the inner ear, as well as skeletal abnormalities, resulting from defective synthesis of glycosaminoglycans (which involve glycosyltransferases and Mn)222. Patients with CDG due to SLC39A8 mutations present with variable symptoms involving multiple organ systems, such as hypotonia, developmental delay, abnormal blood clotting, seizures, liver disease, and heart problems223–225. Because of Mn’s role in SOD2, some of these patients also exhibit mitochondrial dysfunction, as determined by activities of electron transport chain enzymes, similar to Leigh syndrome219,246. Furthermore, MRI reveals atrophy of the cerebrum and/or cerebellum in most SLC39A8-deficient patients225.

Currently patients with CDG-IIn are treated with oral Mn sulfate, with or without galactose supplementation, resulting in improved coordination and hearing abilities, as well as normalization of mitochondrial enzyme functions225.

Mn toxicity

Mn is needed only in small amounts; excess Mn is toxic. The recognition that chronic overexposure to Mn could result in neurological problems dates back to 1837247. Individuals with manganism typically develop bradykinesia, stiffness and behavior disturbances—symptoms also common in Parkinson disease216,248–250. Most cases of Mn overload in humans are caused by occupational and environmental exposures216. Several industries where Mn is an occupational hazard include those involving mining, welding, and production of steel, dry-cell batteries, glass, and fireworks248,249. In a 2015 study of over 700 welders and non-welders at the same worksite,

Andruska and Racette observed that parkinsonism was more prevalent (15.6%) in Mn-exposed

34 welders248. Mn toxicity also afflict people with mutations in Mn transporters encoded by

SLC30A10 and SLC39A14225,251; these mutations will be discussed in detail below.

Several mechanisms by which excess Mn causes cellular toxicity have been proposed. The redox potential of Mn is a double-edged sword—though Mn is critical for SOD2 function, excess Mn promotes cellular oxidative stress252,253. It is also possible that high intracellular Mn2+ would interfere with metalloproteins that might prefer other divalent metals, such as magnesium

(Mg2+), iron (Fe2+), or zinc (Zn2+). For example, most polymerases prefer Mg2+, while many transcription factors contain zinc finger domains254,255. Excess copper has been shown to reduce

DNA binding of nuclear receptors in liver biopsies of patients with Wilson’s disease256, however, this mechanism has not been reported in cells with Mn overload. In bacteria, Mn stress leads to iron depletion, negatively affecting biogenesis and maturation of iron–sulfur cluster and heme proteins257. This mechanism might be relevant in human cells, as depletion of iron stores has been reported in patients with hypermanganesemia due to mutations in SLC30A10225.

In addition to manganese-induced parkinsonism, higher levels of Mn have also been reported in other neurodegenerative diseases258. Thus, many studies on Mn toxicity have focused on the central nervous system (CNS). Regardless of the cause of manganism (environmental or genetic), the brain accumulates Mn in several preferred regions, include the globus pallidus, substantia nigra, and striatum216,249. Mn toxicity is implicated in dysregulation of the glutamine/glutamate γ- aminobutiric acid cycle (GCC) between astrocytes and neurons, which might lead to disruption of neurotransmission and excitotoxic neuronal death258,259. Additional modes of Mn-induced

35 neuronal injury include increased oxidative stress and subsequent release of pro-inflammatory cytokines from activated glial cells258,260.

The liver plays a critical role in removing excess circulating Mn, but it is also a target of Mn toxicity. Two major transporters mediate systemic Mn excretion by hepatocytes: SLC39A14, which takes up Mn from the basolateral side, and SLC30A10, which pumps Mn out of hepatocytes and into the bile canaliculi251. Patients with hypermangansemia due to SLC30A10 mutations accumulate Mn in their livers and suffer from chronic liver disease225,251,261,262. Notably, patients with hypermanganesemia due to SLC39A14 mutations do not accumulate Mn in their liver, and do not develop cirrhosis225,263. In combination with bilirubin, high doses of Mn have been used to induce intrahepatic cholestasis in rats264,265. High dose Mn has also been shown to affect hepatocyte ultrastructure and induce hepatocellular necrosis266. Conversely, toxic systemic

Mn levels might be a result of liver dysfunction. MRI scans indicative of Mn deposition in basal ganglia was reported in 11 of 51 patients with hepatic encephalopathy resulting from cirrhosis267.

Furthermore, of the patients whose samples were available, blood Mn was elevated up to 7-fold, and cerebrospinal fluid (CSF) Mn was elevated 3-fold compared to normal ranges267.

Current treatment for patients suffering from Mn toxicity, regardless of cause, is chelation therapy, which increases Mn excretion through the urinary tract225,249,268. Patients with mutations in SLC30A10 are also supplemented with iron, as their iron stores are depleted225.

Regulators of Mn homeostasis

36 Because Mn is essential yet toxic, its cellular and systemic levels must be tightly regulated. Most

Mn uptake from dietary sources occur in the proximal small intestine. In certain environments,

Mn can also be inhaled and enter the bloodstream through the lungs216,249. Once absorbed, Mn is distributed to various tissues. About 60% of Mn in blood is carried by erythrocytes216,269,270. In the body, Mn is stored in the liver, brain, pancreas, and bone216. Mn in bone has the longest half-life, about 140 days in rats, or 8.5 years in humans216. Mn is primarily excreted in the feces, with evidence for hepatocytes exporting into the bile and enterocyte efflux into the intestinal lumen217,271–273. Thus, while Mn is distributed systemically, a significant portion of Mn remains in the enterohepatic circulation274,275. At present, three key transporters have been identified to be critical in whole-body Mn homeostasis in humans and mice: SLC39A8, SLC39A14, and

SLC30A10225,276–278. The first two mediate Mn uptake into cells and the latter mediates Mn efflux from cells. The organs expressing these transporters and the directionality of Mn flux are illustrated in Fig. I.2.3. Notably, additional transporters exist and are involved in distribution of

Mn, as well as other metals, in various cellular compartments—these are discussed in a recent review by Chen and Aschner216.

SLC39A8 is a transporter capable of importing Mn2+ and other similarly charged metals, notably iron, zinc, and cadmium279–282. The physiological role of SLC39A8 in Mn uptake is evident from

(i) patients with SLC39A8 mutations, whose blood Mn levels are undetectable, but iron and zinc levels are not always affected223,224,246, and (ii) inducible whole-body Slc39a8 knockout mice, as well as hepatocyte-specific Slc39a8 knockout mice, whose blood Mn levels decreased by more than 50%276. SLC39A8 is expressed on hepatocyte canicular membranes and imports Mn from bile, thereby modulating liver and systemic Mn levels, as well as Mn-dependent enzymatic

37 activities276. In HeLa cells, fluorescent-tagged disease-causing SLC39A8 mutant proteins seem to be retained in the ER instead of properly localizing to the plasma membrane219. Furthermore, shRNA knockdown of SLC39A8 results in decreased mitochondrial Mn content and SOD2 activity219. Interestingly, variants in SLC39A8 have been identified in several genome-wide association studies (GWAS) to be linked to not just blood Mn levels, but also HDL-cholesterol,

LDL-cholesterol, and total cholesterol levels, body fat percentage, body mass index, and blood pressure283–285.

SLC39A14 is another Mn uptake transporter, though notably its role is in the Mn excretion pathway. Mutations in SLC39A14 cause hypermanganesemia and childhood-onset parkinsonism225,251,263. The accumulation of Mn and significant neuronal loss in parts of the brain of patients with SLC39A14251,263 indicate Mn uptake into the brain is likely to be mediated by other transporters. This also supports the notion that SLC39A14 serves to take up Mn into cells that subsequently transfer Mn for excretion. Interestingly, while Mn does not accumulate in livers of patients with SLC39A14 mutations225,251,263, highlighting the importance of Mn uptake into the liver for clearance, mice lacking SLC39A14 only in hepatocytes do not develop hypermanganesemia277. Recently, Scheiber and colleagues reported the localization of SLC39A14 to the basolateral side of differentiated Caco-2 cells273. Furthermore, mice lacking SLC39A14 in enterocytes show Mn accumulation in liver and brain273, though not to the same degree as the whole-body knockout, and whether this resulted in neurological defects was not reported277.

SLC30A10 facilitates Mn efflux from the cytosol to the extracellular environment286,287. SLC30A10 mutations result in hypermanganesemia and dystonia, as seen in cases of SLC39A14

38 mutations251,288, though with a few differences. First, patients with SLC30A10 mutations accumulate Mn in their livers and develop liver dysfunction261,262,289. Second, patients with

SLC30A10 mutations show depleted iron stores and polycythemia225,261,262,289. These confirm liver as a primary target of Mn toxicity and highlight a link between hepatic Mn and iron regulation251.

As seen in liver-specific SLC39A14 knockout mice, liver-specific SLC30A10 knockout mice did not phenocopy the corresponding whole-body knockout mice272. However, when SLC30A10 is deleted from the liver and gastrointestinal tract, mice develop hypermanganesemia and accumulate brain Mn272. Evidence from pan-neuronal/glial SLC30A10 knockout mice suggest that brain SLC30A10 primarily protects against Mn accumulation and neurotoxicity when liver and gastrointestinal tracts are bypassed, e.g. when Mn is delivered by subcutaneous injections over the course of 4 weeks272. Interestingly, SLC30A10 works by exchanging Mn export with calcium import290. The use of calcium, instead of protons, as an exchanger might be due to the steep Mn concentration gradient that SLC30A10 must work against290, as Mn levels are considerably higher in bile and intestinal lumen compared to hepatocytes and enterocytes.

The severe consequences of loss of either SLC39A8, SLC39A14, or SLC30A10 in the liver and/or gastrointestinal tract demonstrate the importance of these transporters in Mn homeostasis. The reduction of liver and systemic Mn in patients with SLC39A8 mutations and liver-specific

SLC39A8 KO mice suggests that Mn excretion might be a constitutively active process, and

SLC39A8 functions to prevent excessive loss of Mn. Additionally, the iron deficiency seen in patients with SLC30A10 mutations show a link between Mn and iron regulation. It has been known that expression and degradation of iron transporters in various tissues are regulated by

39 hepcidin291. The regulation of the Mn transporters, however, are incompletely understood and are of interest for further investigations.

40 FIGURES

Figure 1. Mn in active sites of human proteins. (A) SOD2 in tetramer configuration, each monomer containing Mn (purple) and potassium (light purple) and adjacent phosphate (red)292.

(B) PEPCK bound to Mn (pink) and phosphoenolpyruvate (yellow)293 (C) Arginase in a homotrimer configuration, each monomer binding to two Mn (pink) molecules294. Adapted from crystal structures 5VF9, 1KHG, 2ZAV available on RCSB Protein Data Bank.

•– Figure 2. Mn-dependent detoxification of superoxide (O2 ) carried out by SOD2.

Figure 3. An overview of key organs and transporters in Mn homeostasis.

41 Figure 1

A B C

Figure 2

Figure 3 Brain (major target of Mn toxicity)

Lung epithelia Uptake by (inhalation of Mn-containing dust) SLC39A8, SLC39A14

Hepatocyte Bile canalicular membrane

SLC30A10 SLC39A14 (Mn uptake SLC39A8 from blood)

Enterocyte Lumenal membrane SLC39A14 SLC30A10 SLC39A8 (?) DMT1 FPN (?) SLC39A8 (?)

42 Chapter 2

Validation of Gut Organoids for Bile Acid Signaling Studies

INTRODUCTION

The small intestine, particularly the terminal ileum, is a key site for bile acid (BA) signaling due to multiple factors. First, high levels of BAs (millimolar range) cycle through the small intestine

4–12 times daily and enterocytes actively reabsorb BAs from the intestinal lumen1. Second, ileal enterocytes highly express FXR1,2, a major nuclear receptor for BAs38–40. Third, the BA-responsive membrane receptor TGR5 is expressed in ileal L cells, and its activation induces secretion of hormones GLP-1 and PYY86,90,295,296. Modulation of intestinal FXR and TGR5 affects whole-body glucose and lipid metabolism in rodents and humans87,171,172,297,298 . Studies on the effects of deleting, overexpressing, or pharmacologically activating BA receptors in cells and animals have been instrumental in furthering our understanding of BA signaling299,300. However, the BA pool comprises diverse BA species, each with differential ability to activate the different BA receptors38–40,75,84,85, and the effects of shifting BA pool composition on downstream cellular signaling events have not been fully investigated.

Changes in BA synthesis, transport, and excretion, leading to changes in BA pool size and composition, have been associated with metabolic health outcomes103,153,154. Hepatic CYP8B1 catalyzes 12α-hydroxylation of an intermediate in the BA synthesis pathway, resulting in cholic acid (CA) as the end product36,301. Interestingly, CYP8B1 expression is regulated by insulin101,302, and increased CYP8B1 activity has been reported in settings of insulin resistance. Furthermore, when CYP8B1 is deleted or suppressed, mice are protected against weight gain, atherosclerosis,

43 and NASH, as well as show improved glucose tolerance13,14,183,184,303,304. Importantly, although the

BA pool size does not significantly change in these mice, the BA pool composition does.

Inhibition of CYP8B1 results in lack of CA, its bacterial metabolite deoxycholic acid (DCA), and their conjugates (collectively termed 12α-hydroxylated BAs, 12HBAs), as well as increased synthesis of non-12HBAs, especially α- and β-muricholic acids36,184. Although changes in the physicochemical properties of the BA pool have been shown to mediate the effects of CYP8B1 deletion/inhibition, i.e. reduced lipid absorption14,183,184, we hypothesized that BA signaling would also be altered due to the shift in BA pool composition.

We proposed to use gut organoids, together with custom BA pools, to investigate the effects of intestinal BA signaling, while being able to address the heterogeneity of BA species as well as intestine epithelial cell types. Gut organoids are three-dimensional structures made of intestine epithelial cells organized in crypts and villi surrounding hollow lumens, resembling human and mouse small intestine architecture1,2 (Fig 2.1). Gut organoids contain intestine epithelial stem cells that, provided the appropriate growth factors, self-renew and give rise to all other cell types of the intestine epithelium305,306, thus providing several advantages over typical cell culture and animal studies. First, because a single source (e.g. one stem cell line or one mouse) generates numerous gut organoids, we can minimize interindividual baseline variations (i.e. a portion of each batch of organoids serve as an internal (paired) control group), which is not possible when performing experiments using live animals. Additionally, the in vitro setting of gut organoids allows for precise control over BA pool concentration and composition. This is difficult to achieve in vivo due to gallbladder contraction and its consequent surge of BAs in the small intestine upon feeding and/or oral gavage. Furthermore, metabolic pathways in organoids might

44 be more physiologically relevant than immortalized cell lines because they consist of normal, non-transformed cells. Cancer cells often have metabolic needs that are different from normal cells, and thus often rewire their nutrient acquisition and utilization networks. Thus, gut organoids provide continuous supply of normal intestine epithelial cells for molecular and cellular studies.

Gut organoids have proven useful in studies on intestinal development307–310, response to injury311 and infection312, cystic fibrosis313, lipid absorption314, hormone production and secretion315–320, and cancers321–324, to name a few. However, only a limited number of studies have reported using this model system to elucidate the role of BA receptors or the effects of BAs per se321. In this chapter, we validated the use of human iPSC-derived and mouse primary gut organoids to study intestinal BA signaling.

RESULTS

BA signaling pathways are functional in hiPSC-derived gut organoids

In a proof-of-concept experiment, we differentiated hiPSCs into gut organoids. We quantified mRNA expression of intestine epithelial cell markers and BA receptors at different timepoints by qPCR (Fig 2.1). As the organoids matured, we observed increased mRNA levels of the enterocyte brush border marker VIL1 and the enteroendocrine marker CGA (Fig 2.1). Similarly, FXR expression was highly and consistently induced after 138 days of differentiation (Fig 2.1). In contrast, TGR5 was expressed at low levels (Ct values ~30) and did not change over time (Fig

2.1).

45 A well-known effect of TGR5 activation is GLP-1 secretion from enteroendocrine L-cells. To test whether our hiPSC-derived gut organoids had functional TGR5 signaling, we treated them with

(i) a mixture of BAs, (ii) the potent endogenous TGR5 ligand taurolithocholic acid (TLCA), or

(iii) the synthetic TGR5 agonist 3-(2-chlorophenyl)-N-(4-chlorophenyl)-N, 5-dimethylisoxazole-

4-carboxamide (CCDC), and measured GLP-1 secretion. We modeled the BA mix after the average human plasma BA composition, consisting of equal parts 12HBAs and non-12HBAs, as well as a mix of unconjugated and taurine-conjugated BAs (Fig 2.2). Gut organoids increased

GLP-1 secretion in response to TLCA (2.58-fold, p < 0.05) and CCDC (2.38-fold, p < 0.01), while vehicle-treated organoids showed no significant difference in GLP-1 secretion (Fig 2.3). At lower concentrations, the BA mix did not affect GLP-1 secretion (Fig 2.3). Although there was a notable increase in GLP-1 release from gut organoids given 100 µM BAs (3.2-fold, p = 0.07) (Fig

2.3). In another experiment, a higher dose of the BA mix (500 µM) was able to induce GLP-1 secretion (Fig 2.3). Importantly, the synthetic FXR-specific agonist GW4064 did not induce GLP-

1 secretion (Fig 2.3).

Next, we assessed FXR signaling by exposing gut organoids to the same mixture of BAs and analyzing expression of FXR target genes. At 250 µM, BAs significantly induced expression of the canonical FXR target FGF19 (Fig 2.4). Likewise, the FXR synthetic agonist GW4064 also induced expression of FGF19 (Fig 2.4). Altogether, these data indicate our hiPSC-derived gut organoids express functional BA receptors and downstream signaling components, making them suitable for studying intestinal BA signaling.

BA pool composition affects transcription of FXR targets in hiPSC-derived gut organoids

46 Because of the link between insulin resistance and increased 12HBAs, we next asked whether varying the BA pool composition would affect transcription of FXR targets in hiPSC-derived gut organoids. We designed two BA pools: low (20%) 12HBA and high (80%) 12HBA (Fig 2.5) based on extreme BA pool compositions reported in the most insulin sensitive and most insulin resistant groups94. Considering CDCA is the strongest activator of FXR38,39 and it makes up the majority of the low 12HBA pool, we hypothesized the low 12HBA pool would induce FXR targets more strongly than the high 12HBA pool. Indeed, FGF19 and IBABP mRNA levels were robustly increased in gut organoids treated with the low 12HBA pool, and this induction was blunted in high 12HBA-treated gut organoids (Fig 2.6).

BA signaling pathways are functional in mouse primary gut organoids

We also sought to optimize our methods for studying BA signaling in mouse primary gut organoids. Isolating crypts from mouse ilea allowed us to bypass multiple differentiation steps and obtain mature organoids in 7-10 days, making them attractive alternatives to hiPSC-derived gut organoids. We found that FXR and TGR5 signaling pathways remain intact in the mouse primary gut organoids, as evidenced by increased expression of Fgf15 and Ibabp in response to

BAs and GW4064 (Fig 2.7), as well as increased GLP-1 secretion upon exposure to BAs (Fig 2.7).

We next tested whether altering BA pool composition affected expression of FXR targets in these mouse primary gut organoids. Because mouse BA pools contain an abundance of muricholic acids (MCAs) and extremely low CDCA36,182,325, we included a third BA pool, where the non-

12HBAs in the low 12HBA pool were replaced with unconjugated and taurine-conjugated β-

MCAs (denoted low 12HBA +MCAs) (Fig. 2.8). Both low 12HBA and high 12HBA pools

47 robustly induced Ibabp and Ostb in mouse gut organoids (Fig. 2.8). On the other hand, low

12HBA +MCAs-treated organoids had blunted induction of these targets (Fig. 2.8), consistent with their previously reported effects as FXR antagonists43,45.

Delivery of BAs in mixed micelles affects gene expression

Upon entry into the small intestine, BAs form mixed micelles with dietary lipids and additional lipophilic components from bile. However, many in vitro studies, including ours thus far, use dimethyl sulfoxide (DMSO) to dissolve BAs before adding them cell culture media. We reasoned that treating gut organoids with BAs in mixed micelles would better mimic conditions in the intestinal lumen. In lipid absorption studies, taurocholic acid (TCA) has been the BA of choice to prepare mixed micelles314. To determine whether the presence of lipophilic micelle components and/or differences in BAs present in mixed micelles could affect FXR activation, we exposed mouse primary gut organoids to micelle components without BAs (vehicle), TCA, TCA in micelles, and a 1:1 mix of TCA and TCDCA in micelles.

We observed differential effects of micelle composition on induction of FXR target genes (Fig

2.9). The presence of micelles enhanced TCA-induced expression of Fgf15, Osta, and Ostb, but did not influence Ibabp (Fig 2.9). Organoids exposed to TCA-TCDCA-micelles did not induce

Osta (p < 0.001) and Ostb (p < 0.001) as strongly as organoids given TCA-micelles, though notably induction of Fgf15 (p = 0.3) and Ibabp (p = 0.05) were not different (Fig 2.9).

Additionally, Asbt, a target of FXR repression, was also influenced by BA/micelle composition.

While all groups receiving BAs had lower Asbt expression compared to the vehicle group, organoids given TCA-TCDCA-micelles showed the most repression (~70% less expression than

48 vehicle) (Fig 2.9). Overall, our data support the use of primary gut organoids, mixed micelles, and varying BA composition to investigate nuances in intestinal BA signaling.

DISCUSSION

In these studies, we confirm that FXR and TGR5 signaling pathways are functional in hiPSC- derived gut organoids as well as mouse primary gut organoids. Both signaling pathways were induced by BA pools and synthetic receptor agonists. Our data also indicate that while keeping total BA concentration constant, altering the BA pool composition could affect gene expression of FXR targets. Further, we found that delivery of BA pools in mixed micelles could also modulate FXR signaling.

The FXR targets FGF19 and IBABP were preferentially induced in hiPSC-derived gut organoids treated with the low 12HBA pool. This is consistent with CDCA being the strongest endogenous

BA to activate human FXR38–40. Additionally, human FXR contains specific residues in its ligand- binding domain that renders it especially sensitive to CDCA185. The preferential induction of

FXR by low 12HBA might be relevant in vivo, as lower circulating FGF19 and increased BA synthesis has been observed in individuals with obesity63,103. Interestingly, both low- and high-

12HBA pools robustly induced FXR targets in mouse primary gut organoids. Considering that

CDCA is efficiently converted to MCAs in mouse liver182 and thus exist in low abundance in the natural mouse BA pools, Replacement of non-12HBAs with β-MCA and its taurine conjugate resulted in marked reduction of Ibabp and Ostb in mouse primary gut organoids. This is consistent with the role of MCAs as inhibitors of FXR202,213. Several studies have suggested inhibiting intestinal FXR signaling as an approach to treat diabetes and obesity43,45,213. Notably,

49 MCAs are not present in adult humans1,182,194, and the effects of MCAs on human FXR signaling have not been extensively evaluated. The combination of hiPSC-derived, or human primary crypt-derived, gut organoids and designer BA pools containing MCAs may provide further insight.

Because of the time required for hiPSCs to differentiate and mature, generating organoids from primary crypts is a practical alternative. Preliminary studies in mouse organoids treated with BAs in mixed micelles suggest that the presence of lipids could affect BA action. This could be due to improved BA absorption, or the lipid components activating other nuclear receptors, such as

PPARα and PPARγ326,327. In sum, we have validated intestinal organoids as a viable system to study BA signaling. In Chapter 3, we used mouse primary ileal organoids to investigate the effects of varying composition of BA pools delivered in mixed micelles, which revealed a surprising role of BAs in micronutrient homeostasis.

MATERIALS AND METHODS

Reagents

Unconjugated and taurine-conjugated β-MCAs were obtained from Steraloids. All other BAs, oleic acid, 2-palmitoyl glycerol, phosphatidylcholine, and cholesterol were purchased from

Sigma-Aldrich. Human and mouse growth factors (FGF4, Wnt3A, R-spondin 1, Noggin, EGF) were purchased from R&D Systems. Growth factor-reduced Matrigel and hESC-qualified

Matrigel were from Corning. Cell culture media and supplements were from Gibco, unless noted otherwise.

50 Human iPSC (hiPSC) culture and differentiation

Human iPSCs were gifted by Dr. Dieter Egli. hiPSCs were maintained on a feeder layer of irradiated mouse embryonic fibroblasts (MEFs) (MTI-GlobalStem) and given human embryonic stem cell medium (KO DMEM supplemented with 15% KnockOut Serum Replacement, 2.13 mM GlutaMAX, 106 µM MEM non-essential amino acids, 106 U/ml penicillin, 106 µg/ml streptomycin, and 58.6 µM 2-mercaptoethanol), according to the New York Stem Cell

Foundation Protocol Book. Cells were fed daily and passaged every 3-4 days. To prepare hiPSCs for differentiation, cells were grown on Matrigel-coated plates, fed mTeSR1 (STEMCELL

Technologies) daily, and passaged twice. We followed methods developed by Jason Spence and colleagues to differentiate hiPSCs into hindgut organoids306,328, with minor modifications1. First, we used the STEMdiff Definitive Endoderm Kit (STEMCELL technologies) to differentiate iPSCs to definitive endoderm following manufacturer’s instruction for 4 days. On day 5, we washed cells with PBS and switched to gut differentiation medium (RPMI supplemented with 2% FBS, 2 mM GlutaMAX, 100 U/ml penicillin, 100 µg/ml streptomycin, 500 ng/ml FGF4, and 500 ng/ml

Wnt3A). We replaced gut differentiation medium daily until day 9. We harvested spheroids that emerged between days 7 and 9, transferred them to Matrigel domes on Nunclon Delta surface 4- well dishes and, after the Matrigel had set, fed them intestine growth medium (Advanced

DMEM/F-12, 1X GlutaMAX, 10 mM HEPES, 100 U/ml penicillin, 100 µg/ml streptomycin, 500 ng/ml human R-Spondin 1, 100 ng/ml human Noggin, 100 ng/ml human EGF, 1X B-27, and 1X

N2) every 4 days. We passaged gut organoids every 2 weeks by manually cutting organoids using sterile sharp forceps under a dissecting microscope, transferring the segments into new mounds of Matrigel.

51 Intestinal crypt isolation and primary gut organoid culture

We isolated crypts from mouse ileum following methods established by the Clevers Lab305, with minor modifications. We euthanized 6- to 12-week-old C57BL/6 mice by CO2 inhalation followed by cervical dislocation and dissected the small intestines. We divided each small intestine into 3 parts of equal length (~10 cm). We collected the ileum (distal) portion, cut it longitudinally, and minced it into 2-5 mm fragments. We washed ileal fragments 4-6 times in ice-cold PBS, until the supernatant was clear. We incubated fragments in ice-cold PBS containing

2 mM EDTA with gentle shaking for 1 hour. After removing EDTA-PBS solution, we harvested crypts by vigorously pipetting the fragments in ice-cold PBS containing 10% FBS, allowing fragments to settle, and collecting the supernatant. To pellet the crypts, we centrifuged the supernatant at 900 rpm for 5 minutes at 4ºC. We resuspended the pellet in ice-cold base medium

(Advanced DMEM/F-12 containing 1X GlutaMAX and 10 mM HEPES), centrifuged this mixture at 720 rpm for 5 minutes at 4ºC, and discarded the supernatant. We resuspended the pellet in base medium, passed this mixture through a 70 µm cell strainer, and centrifuged again at

900 rpm for 5 minutes at 4ºC. We finally mixed the crypt pellet with Matrigel and seeded 20-40

µl domes on pre-warmed Nunclon Delta surface 24-well plates. We incubated the plates in a

37ºC, 5% CO2 chamber to allow the Matrigel to solidify (15-20 minutes). We added organoid growth medium (Advanced DMEM/F-12 containing 1X GlutaMAX, 10 mM HEPES, 100 U/ml penicillin, 100 µg/ml streptomycin, 1 µg/ml R-spondin 1, 100 ng/ml Noggin, 100 ng/ml EGF, 1X

B-27, and 1X N-2) and replaced it twice weekly.

We passaged the organoids every 7-10 days. Briefly, we aspirated organoid growth medium and replaced it with ice-cold PBS. We used a P1000 pipet to disrupt the Matrigel dome. We passed

52 the mixture through a 27 ½ gauge needle and collected them in a 50 ml tube. We centrifuged the mixture at 150g for 10 minutes at 4ºC, removed the supernatant, washed the pellet with ice-cold

PBS, and repeated the centrifugation step. We then resuspend the pellet in ice-cold Matrigel and distribute into new pre-warmed 24-well plates, incubated the plates at 37ºC until the Matrigel solidified, and added fresh organoid growth medium.

Preparation of micelles

We prepared micelles as previously described314 with minor modifications. We prepared individual stock solutions of oleic acid (OA), 2-palmitoyl glycerol (2-PG), phosphatidylcholine

(PC), and cholesterol in chloroform. We prepared individual stock solutions of TCA and

TCDCA at 20 mM in PBS. We mixed lipophilic components (those in chloroform stocks) in a glass vial and allowed them to dry under N2 stream. After the lipophilic components dried, we added warm PBS, TCDA, or a mixture of TCA-TCDCA and vortexed. We further diluted the mixture with DMEM containing 0.2% BSA, yielding final concentrations of 0.6 mM OA, 0.2 mM

2-PG, 0.2 mM PC, 0.05 mM cholesterol, and 0 (for PBS vehicle) or 1.5 mM total BAs.

BA-stimulated gene expression

We exposed organoids’ lumens by cutting hiPSC-derived gut organoids with sharp forceps or passing mouse primary gut organoids through a P200 tip to allow BAs access to enterocytes’ apical surfaces. We washed organoids with PBS, centrifuged at 150g for 10 min, and removed the supernatant. We used DMEM containing 0.2% BSA as base medium and added BA mixtures previously dissolved in DMSO or prepared in micelles at concentrations indicated in the

53 different experiments and incubated at 37ºC, 5% CO2 for 24 hours. We collected organoid pellets after centrifugation at 150g for 10 min and proceeded with RNA extraction.

RNA extraction, cDNA synthesis, and qPCR analyses

We extracted RNA from organoids using the RNeasy Mini Kit (QIAGEN) and used 200 ng RNA for cDNA synthesis. For cDNA synthesis, we used the High-Capacity cDNA Reverse

Transcription Kit (Thermo Fisher). For qPCR analyses, we used iTaq Universal SYBR Green

Supermix (Bio-Rad) and the CFX96 Real-Time PCR detection system (Bio-Rad). For hiPSC- derived gut organoids samples, we used RPLP0 (QIAGEN) as reference to calculate relative gene expression. For mouse gut organoids samples, we used 36b4 or B2m as references. Primer sequences are listed in Appendix.

GLP-1 secretion assay

To assess GLP-1 secretion from gut organoids, we followed methods previously described by

Petersen and colleagues315 with minor modifications. We mechanically disrupted the spherical structure of the organoids to expose their lumens, collected them into 1.5 ml tubes and washed them in Hank’s Balanced Salt Solution (HBSS) containing 0.1% BSA and 10 mM HEPES at 37ºC for 2 hours. We centrifuged organoids at 150g for 10 min and removed the wash solution. To measure baseline GLP-1 secretion, we incubated gut organoids with baseline solution (wash solution containing 50 µl/ml Aprotinin (Fisher) and 20 µl/ml DPP-4 inhibitor (Millipore)) at

37ºC for 1 hour, centrifuged organoid/incubation medium mix, and collected the supernatant.

To measure stimulated GLP-1 secretion, we incubated gut organoids with test reagents added to

54 the baseline solution at 37ºC for 1 hour, centrifuged organoid/incubation medium mix, and collected the supernatant. We lysed cells by vigorous pipetting in RIPA buffer to extract intracellular proteins. Supernatants and cell extracts were stored at -80ºC until analysis. GLP-1 in all samples were quantified using Total GLP-1 (ver. 2) Kit (Meso Scale Discovery) following manufacturer’s instructions.

Statistical analyses

We used one-way ANOVA followed by pairwise comparisons with the Benjamini-Hochberg correction. Adjusted p values < 0.05 were considered significant.

55 FIGURES

Figure 2.1. hiPSC-derived gut organoids express intestine epithelial cell markers and BA receptors. An organoid at 158 d post-differentiation. Expression levels at 57- and 158-days post- differentiation. Numbers above the green bars indicate qPCR Ct values. Mature enterocyte marker: Villin-1 (VIL1). Enteroendocrine marker: Chromogranin A (CGA). L-cell marker:

Proglucagon (GCG). BA receptors: FXR, TGR5.

Figure 2.2 BA pool composition. Pool consists of 50% 12HBAs and 50% non-12HBAs based on average human pool. CA, cholic acid; DCA, deoxycholic acid; CDCA, chenodeoxycholic acid;

UDCA, ursodeoxycholic acid; LCA, lithocholic acid. “T-” marks conjugated species.

Figure 2.3. TGR5 signaling in hiPSC-derived gut organoids increase GLP-1 secretion.

Figure 2.4. BA pool induces FGF19 expression in hiPSC-derived gut organoids. Organoids were treated with DMSO (vehicle), BA pool at indicated concentrations, or 10 µM GW4604 for

24 h. n=9-15 organoids/group, **p < 0.01 vs. vehicle treated.

Figure 2.5. Composition of high (80%) 12HBA and low (20%) 12HBA pools. BA pools were modeled after extreme compositions in healthy subjects stratified by insulin sensitivity94.

Figure 2.6. High 12HBA pool blunts induction of FXR targets. Human iPSC-derived gut organoids were treated with DMSO (vehicle), high 12HBA, or low 12HBA pool for 24 h. n = 2-

3/group. ANOVA followed by pairwise comparisons, *p < 0.05

Figure 2.7. Functional TGR5 and FXR signaling in mouse primary gut organoids. GLP-1 release after stimulation with 250 µM BA pool consisting of 50% 12HBAs or 10 µM forskolin +

10µM IBMX (positive control for GLP-1 secretion). Expression of FXR targets in mouse primary gut organoids following exposure to DMSO, 250 µM BA pool containing 50% 12HBAs, or the synthetic agonist GW4604 for 24 h.

Figure 2.8 Effects of changing BA composition on FXR transcriptional targets in mouse primary gut organoids. Mouse primary gut organoids were exposed to DMSO or 250 µM BA pools with varying compositions for 24 h. **p < 0.01 vs. DMSO.

Figure 2.9. Effects of altering BA/micelle composition on transcription of FXR target genes.

Mouse primary gut organoids were incubated in DMEM, 0.2% BSA containing (1) micelle components without BAs, (2) 1.5 mM TCA in PBS, (3) 1.5 mM TCA in micelles, or (4) 0.75 mM

TCA + 0.75 mM TCDCA in micelles for 24 h. n = 4 wells/group. ANOVA followed by pairwise comparisons with Benjamini-Hochberg correction, *p < 0.05, **p < 0.01, ***p < 0.001.

57 Figure 2.1. Expression of intestine epithelial cell markers and BA receptors in hiPSC-derived gut organoids.

1000 22.2 8 24.3 1000 27.0 1000 26.8 2.0 31.2

100 6 100 1.5 57d 10 4 10 10 1.0 158d 1 2 1 0.5 158d 0.0 hiPSC-derived Relative levelsmRNA 0.1 0 0 0.1 organoid VIL1 CGA GCG FXR TGR5

Figure 2.2. Composition of BA pool consisting of 50% 12HBAs and 50% non-12HBAs

CDCA T-CDCA LCA T-LCA UDCA CA T-CA DCA T-DCA

Figure 2.3. GLP-1 secretion from hiPSC-derived gut organoids

1.5 p=0.07 2.0 ***

1.5 1.0 *** ***

cell content) 1.0 Pre secretion Pre 1 - 0.5 Post 0.5 Post GLP relative to relative DMSO) ( 1 release (%

- 0.0 0.0 GLP DMSO CCDC TLCA BA CCDC DMSO blend BA mix GW4604 25µM 20µM 100µM 500µM 10µM 10µM

58 Figure 2.4. BA pool induces FGF19 expression in hiPSC-derived gut organoids.

** 15 DMSO 10 BA 50µM

5 BA 100µM 3 ** DMSO 2 BA 50µM BA 100µM 1 Relative levelsmRNA BA 250µM 0 GW FGF19

Figure 2.5. Composition of humanized high- and low- 12HBA pools

High 12HBA Low 12HBA

Figure 2.6. High 12HBA pool blunts induction of FXR targets

FXR TGR5 2.0 2.0

1.5 1.5

1.0 1.0

0.5 0.5 Relative mRNA

0.0 0.0 DMSO High Low DMSO High Low 12HBA 12HBA 12HBA 12HBA

FGF19 IBABP *** 40 800 *** * 30 600 * 20 400

10 200 Relative mRNA 0 0 DMSO High Low DMSO High Low 12HBA 12HBA 12HBA 12HBA

59 Figure 2.7. TGR5 and FXR signaling pathways are functional in mouse primary gut organoids

Figure 2.8. Effects of altering BA pool composition on transcription of FXR target genes in mouse primary gut organoids Low 12HBA High 12HBA Low 12HBA + MCAs

12HBAs CA, DCA CA, DCA CA, DCA

non- CDCA, LCA, CDCA, LCA, β-MCA 12HBAs UDCA UDCA

Ibabp Ostb

80 12 *** ** *** ** 60 8 * 40 ** 4 20

Relative levelsmRNA 0 0 DMSO High 12a Low 12a Low 12a DMSO High Low Low DMSODMSO HighHigh LowLow LowLow 12HBA 12HBA +12HBA MCA 12HBA12a 12HBA12a 12a12HBA + +MCAs +MCAsMCA

60 Figure 2.9. Effects of altering BA/micelle composition on transcription of FXR target genes

Fgf15 Fabp6* 40 600 *** p = 0.05 Micelle components, no BAs 30 TCA in PBS 400 Fgf15 Fabp6 20 *** TCA in micelles 200 10 TCA + TCDCA in micelles Relative Relative 0 0 Micelles : + – + + Micelles : + – + + TCA : – + + + TCA : – + + + TCDCA : – – – + TCDCA : – – – +

*** Slc51a** Slc51b Slc10a2 10 12 1.5 *** *** *** 8 *** *** 8 1.0 ** Slc51a Slc51b

6 Slc10a2 p=0.07 4 4 0.5 2 Relative Relative Relative 0 0 0.0 Micelles : + – + + Micelles : + – + + Micelles : + – + + TCA : – + + + TCA : – + + + TCA : – + + + TCDCA : – – – + TCDCA : – – – + TCDCA : – – – +

61 Chapter 3

Bile Acid Regulation of Intestinal Manganese Transport

INTRODUCTION

Bile acids (BAs) are cholesterol catabolites that regulate many biological functions, including multiple aspects of macronutrient metabolism. One of the mechanisms by which they do so is by promoting lipid emulsification and absorption299. A second mechanism is by acting as receptor ligands, and BA receptors also regulate lipid and glucose metabolism299. It is underappreciated that there is structural diversity among BAs that results in variable capacities to activate BA receptors38–40,75,84,85. BAs differ primarily in: (1) the number and position of hydroxyl groups and

(2) the conjugation of the molecule to glycine, taurine, or neither8,329. Thus the composition of the BA pool may affect the activity of BA receptors. However, the biological consequences of altered BA pool composition are not fully known.

One key determinant of BA composition is the hepatic enzyme sterol 12α-hydroxylase (encoded by CYP8B1). By adding a 12α-hydroxylation to an intermediate of the BA synthesis pathway,

CYP8B1 determines the hepatic synthesis of cholic acid (CA) instead of chenodeoxycholic acid

(CDCA) (Fig. 1A)36,329. In settings of insulin resistance, there is increased proportion of CA, its bacterial metabolite deoxycholic acid (DCA), and their conjugates—collectively termed 12α- hydroxylated BAs (12HBAs)94,103. Moreover, even in healthy subjects, increases in 12HBAs are correlated to the characteristic metabolic abnormalities of insulin resistance94. On the other hand,

Cyp8b1–/– mice, which lack 12HBAs, absorb less cholesterol and are protected from western-type diet-induced weight gain and atherosclerosis compared to wild-type mice14. Cyp8b1–/– mice also

62 show improved glucose tolerance, which has been proposed to be due to increased secretion of glucagon-like peptide-1 (GLP-1)13. Furthermore, siRNA against Cyp8b1 improved non-alcoholic steatohepatitis in mice304. Thus, CYP8B1 inhibition is a potential therapeutic target for metabolic diseases. However, the biological processes that are regulated by 12HBAs are incompletely understood. In this work, we investigate the effects of lowering 12HBAs (to mimic CYP8B1 inhibition) in the intestine, which is a major site of BA signaling and which encounters high BA concentrations, approximately 2-12 mM after a meal192,193.

There are at least three intestinal BA receptors. The transcription factor FXR regulates BA transport and feedback suppression of hepatic BA synthesis, and also modulates lipid and glucose metabolism299. The membrane receptor TGR5 regulates glucose homeostasis and colonic motility by promoting the secretion of GLP-1 and serotonin87,330,331. Another intestinal receptor responsive to certain BAs is the vitamin D receptor (VDR), whose canonical role is to promote calcium and phosphate absorption332. For each of these receptors, the best reported endogenous

BA agonists are non-12HBAs. For FXR it is CDCA38–40, for TGR5 and VDR it is lithocholic acid

(LCA)75,84,85. LCA is formed by 7α-dehydroxylation of CDCA by bacterial enzymes in the gut.

Investigating the effects of BA composition on intestinal BA signaling in vivo is challenging, because of the continued presence of endogenous BAs. This is particularly important for experiments in mice, as mice contain a class of BAs–muricholic acids (MCAs), which are non-

12HBAs–that are not found in adult humans. Traditional in vitro systems comprise transformed cells, such as cell lines derived from colorectal tumors, and thus may differ from normal tissue.

To fill the gap, we investigated the effects of suppressing 12HBAs using primary murine

63 intestinal organoids, also called enteroids. These organoids are generated from stem cells of the intestinal crypts, and contain all known cell types of the intestinal epithelium305. Furthermore, we addressed the interspecies differences in BAs by using designer BA pools that mimic the effects of

CYP8B1 inhibition in humans and mice.

In these studies, we elucidated an unexpected finding from our analyses of genes differentially regulated by BA pool composition. We found that varying 12HBA proportions modulates expression of Slc30a10, a manganese (Mn) efflux transporter critical for whole-body Mn excretion. Cellular Mn levels are tightly regulated, as it is essential for numerous cellular processes, yet its excess is toxic216. Our data demonstrate a previously unknown role of BAs in intestinal control of metal homeostasis.

RESULTS

Distinct BA pool compositions differentially induce transcription of FXR and VDR targets

To test the effects of a low 12HBA pool on intestinal gene expression, we designed four distinct

BA pools with which to stimulate primary mouse ileal organoids. The differences between the pools were due to two key features: (i) The BA pool of the species we model, either human or mouse. In the human pools, BAs were glycine-conjugated, and in the mouse pools, BAs were taurine-conjugated, to mimic the natural abundance in those species. Additionally, mouse BA pools contained MCAs, whereas these were not included in the human pools. (ii) The proportion of 12HBAs, either 10% (low) or 90% (high) (Fig. 1B). Thus the four BA pools are labeled human low 12HBA (hL), human high 12HBA (hH), mouse low 12HBA (mL), and mouse high 12HBA

(mH). Many prior in vitro studies of BA signaling have used DMSO or ethanol as vehicles for BA

64 solubilization. To better mimic conditions of the intestinal lumen, we prepared BAs in mixed micelles containing oleic acid, 2-palmitoyl glycerol, phosphatidylcholine, and free cholesterol.

We used the four lipid-emulsified BA pools–versus a vehicle control, containing all micelle components except BAs–to treat primary murine ileal organoids. After 24-hours of treatment, we collected RNA and performed sequencing.

First, we focused on the effects of the low 12HBA pools, as this would mimic the effects of

CYP8B1 inhibition. We examined all genes that could be significantly induced compared to vehicle, as BAs are known to induce gene expression via receptor-mediated signaling. We set a threshold of log2FC>1.0 and padj<0.05 for differential expression. The low 12HBA pools collectively induced 1361 genes compared to vehicle. Of these, 516 reached those thresholds for both hL and mL pools. 95 reached those thresholds for hL only, and 750 for mL only. Pathway analysis indicates enrichment of genes involved in lipid metabolism, consistent with known effects of BAs (Table 1).

Next, we focused on the subset of these genes that are differentially regulated by low- versus high-12HBA pools, with a particular focus on those for which the effects were shared between human and mouse pools. We used a threshold of log2FC>1.0 and Padj<0.05 for differential expression. The majority of genes did not reach this threshold, indicating that they are similarly regulated by both low- and high-12HBA pools, or are differentially regulated by low- versus high- 12HBAs in human pools only or in mouse pools only (Table 2). These genes included canonical FXR targets such as Fabp6 (encoding the ileal bile acid binding protein, Ibabp), Slc51b

65 (encoding the basolateral BA efflux transporter Ostb), and Fgf15, which we validated by qPCR

(Fig. 1D).

There were 44 genes that were preferentially induced by hL and mL compared to hH and mH, respectively (Table 2, Fig. 1C). Among these, we noted that several are known transcriptional targets of VDR. This included Cyp24a1, S100g, and Cyp3a11, and we validated these by qPCR

(Fig. 1E). This is consistent with the concepts that (i) certain BAs, especially the non-12HBA lithocholic acid (LCA) and its conjugates, can activate VDR at the µM range75, and (ii) the low

12HBA pools contain more LCA (9 µM vs. 1 µM in the high 12HBA pools).

Validation of RNA-seq findings

We validated the findings of our RNA-seq using qPCR from organoids in several independent experiments. To compare organoids derived from different mice, we calculated the ratios of expression induced by low 12HBAs to high 12HBAs for human and mouse pools, respectively.

Ratios larger than 1 indicate expression is higher in low 12HBA pool, while ratios smaller than 1 indicate expression is lower in low 12HBA pool. Both hL and mL pools induced Cyp24a1 by at least one order of magnitude higher than hH and mH pools (Fig. 2A). Similarly, S100g transcript levels were 4 to 12 times higher in hL and mL pools compared to hH and mH pools (Fig. 2A).

These results are consistent with our RNA-seq data, and suggest low 12HBA pools are better activators of VDR than high 12HBA pools.

66 We also validated the FXR targets Fgf15 and Fabp6. All BA pools induced Fgf15 and Fabp6 (Fig.

2B). Fgf15 expression was more strongly induced by hL than hH, but we did not observe differential expression between mL and mH groups (Fig. 2B). In contrast, there was no preference for either low or high 12HBA pools in induction of Fabp6 (Fig. 2B). These results are consistent with the RNA-seq data. This indicates that 12HBAs differentially impact some, but not all, FXR targets, and the effects are different for mouse and human BA pools.

In the prior experiments, the BA pools were prepared in mixed micelles. To test whether the differing BA pool compositions per se were sufficient to induce differential expression of VDR and FXR target genes, we treated organoids with BA pools without the other micelle components. As expected, BAs alone were able to activate expression of the VDR targets Cyp24a1 and S100g, and hL induced these genes more strongly than hH (Fig. 2C). BAs also increased transcripts of FXR targets Fgf15, Fabp6/Ibabp, and Slc51b/Ostb (Fig. 2D). These data demonstrate that the variable induction of target genes by low versus high 12HBA pools is attributable to the BAs per se, and did not require the presence of micelles.

To validate whether these differential responses to varying BA pool composition also occur in human cells, we performed experiments in Caco-2 cells. Consistent with data from murine organoids, CYP24A1 and S100G transcript levels were increased by treatment with hL, but not hH, pool (Fig. 2E). The hL pool also induced FXR targets FGF19, FABP6/IBABP, and

SLC51B/OSTb better than the hH pool (Fig. 2F). We conclude that, consistent with the RNA-seq data, BA pools low in 12HBAs are robust inducers of VDR targets in intestinal epithelial cells.

BA composition regulates Slc30a10 transcription and cellular Mn efflux

Among the genes differentially induced in response to low 12HBAs, one of the most robust was

Slc30a10 (Fig. 1C, Table 2). This gene encodes a Mn efflux transporter critical for whole-body

Mn excretion. Humans with mutations in SLC30A10 gene develop hypermanganesemia, accompanied by parkinsonism and cirrhosis225,261,262,289,333.

In gut organoids, low 12HBA pools were superior to high 12HBA pools in inducing Slc30a10

(Fig. 3A, 3B). This preferential induction of Slc30a10 by low 12HBA pools was consistent across multiple independent batches of organoids (Fig. 3C). This differential expression of Slc30a10 was also observed when BA pools were delivered without micelles (Fig. 3D), indicating a direct effect of BAs. Finally, we validated the preferential induction of SLC30A10 by low 12HBAs in human

Caco-2 cells (Fig. 3E).

Next we sought to determine whether BA-induced changes in Slc30a10 transcript levels yield functional (cellular) consequences. We predicted that the induction of Slc30a10 expression by low 12HBA pools would increase Mn efflux from organoids. To test this, we carried out Mn efflux assays, where we preloaded cells with Mn, then treated the cells with vehicle or BA pools, and measured Mn levels in cells and media. Organoids treated with hL had higher Mn in their efflux media compared to organoids treated with vehicle or hH. Additionally, while Mn exposure greatly increased intracellular Mn content, organoids treated with hL had a reduction in intracellular Mn levels (Fig. 3F). Consistently, Caco-2 cells receiving hL also showed higher Mn

68 efflux compared to vehicle- and hH-treated cells (Fig. 3G). Altogether, these data suggest that the induction of Slc30a10 by low 12HBA pools promotes Mn efflux.

Slc30a10 transcription is driven by LCA-to-VDR signaling

Recently, SLC3010 was found to be induced by the VDR agonist 1α,25-dihydroxyvitamin D3 in

334 Caco-2 cells . LCA is a potent VDR ligand, with an EC50 comparable to CDCA’s EC50 for human

FXR75. Although LCA made up less than 1% of the BA pools in our studies, we investigated whether the differential Slc30a10 induction by low 12HBAs was due to LCA-to-VDR signaling.

To test whether LCA is the differentiating factor between hL and hH in their induction of

Slc30a10, we treated ileal organoids with hL and hH pools lacking LCA. In pools lacking LCA, we compensated its removal by increasing other non-12HBAs such that the total BA pool concentrations matched. Without LCA, hL induction of Slc30a10 was significantly blunted, and was not different from hH. (Fig. 4A). This pattern was similar to that of VDR targets Cyp24a1 and S100g (Fig. 4B). On the other hand, presence or absence of LCA had no effect on FXR targets

Fgf15 and Fabp6/Ibabp, consistent with the observation that LCA is not a potent FXR agonist

(Fig. 4C).

In contrast, removing CDCA from the BA pools did not affect Slc30a10 induction. CDCA and its conjugates are potent agonists of FXR38–40, and this BA makes up a large proportion of the low

12HBA pools. We treated gut organoids with mouse BA pools containing or lacking T-CDCA. In pools lacking T-CDCA, we compensated its removal by increasing other non-12HBAs such that the total BA pool concentrations matched. Removing T-CDCA had no significant effect on

69 Slc30a10 mRNA levels (Fig. 4D), suggesting T-CDCA is dispensable for Slc30a10 induction.

Similarly, there was no effect of removing T-CDCA on Cyp24a1 or S100g expression (Fig. 4E).

However, as expected for an FXR target, removing T-CDCA from mL and mH pools resulted in blunted Fgf15 and Ibabp induction (Fig. 4F). Together, these findings indicate that LCA, but not

CDCA, is the BA responsible for the differential expression of Slc30a10 between low- versus high- 12HBA pools.

To directly test the requirement of VDR for BA-induced Slc30a10 transcription, we carried out experiments on gut organoids derived from VDR+/+, VDR+/–, and VDR–/– littermate mice.

Strikingly, VDR–/– gut organoids showed substantially blunted Slc30a10 transcription in response to hL pool (Fig. 4G). Furthermore, VDR+/– gut organoids increased Slc30a10 transcription to intermediate levels between that in VDR+/+ and VDR–/– organoids, suggesting a gene dosage effect. As expected, ablating VDR diminished the induction of Cyp24a1 and S100g (Fig. 4H), but had little effect on Fgf15 and Fabp6/Ibabp (Fig. 4I). We noted that VDR–/– gut organoids still showed a small but significant increase in Slc30a10 upon hL treatment, suggesting possible residual activation by another transcription factor. Thus, we conclude that low 12HBA-induced

Slc30a10 is largely mediated by VDR.

LCA and vitamin D induce Slc30a10 expression in mouse ileum

The data presented thus far have been generated from cells of the distal intestine–ileal organoids and the Caco-2 colorectal cancer cell line. To determine the distribution of Slc30a10 in vivo, we quantified its expression in murine enterohepatic tissues. We found that all segments of the small intestine expressed Slc30a10 mRNA at levels higher than the liver (Fig. 5A). This is of interest

70 because the liver’s role in eliminating excess Mn has long been known335–337, and recent evidence suggest the gastrointestinal tract also plays a role in whole-body Mn homeostasis272,273.

Next, we tested whether LCA and VDR signaling could also affect expression of Mn transporters in vivo. We administered LCA, calcitriol, or CA to C57BL/6 mice by oral gavage and analyzed mRNA expression in ileal epithelia. Mice receiving LCA and calcitriol showed on average 4- to 6- fold increases in Slc30a10 expression in ileum (Fig. 5B). The increase in Slc30a10 expression was accompanied by increased Cyp24a1 and S100g (Fig. 5C), consistent with activation of VDR.

Notably, CA did not induce Slc30a10, Cyp24a1, or S100g (Fig. 5B, 5C). In liver tissues, Slc30a10 mRNA levels were not affected by any of the treatments (Fig. 5D). These data show that in vivo,

LCA and VDR carry out transcriptional regulation of Slc30a10 in ileum, but not liver.

DISCUSSION

Our analyses reveal that BA composition regulates the expression of Slc30a10, a Mn efflux transporter. SLC30A10 is one of three transporters identified thus far to be critical for whole- body Mn homeostasis in humans and mice224,251,261,262,277,278,338. We found that BA pools low in

12HBAs, which have increased abundance of the non-12HBA LCA, act via VDR to promote

Slc30a10 expression. We also found that ileal Slc30a10 was inducible by LCA and the VDR agonist calcitriol, indicating that LCA and VDR signaling modulate intestinal Mn transport.

Mn is a cofactor for numerous metalloproteins involved in many cellular processes216,222. Yet, like other metals in biology, Mn in excess amounts is toxic. Mn poisoning results in neurological symptoms similar to Parkinson disease216,248. Most cases of Mn toxicity are due to occupational

71 and environmental exposures216,248. Mn toxicity has also been reported in cases of severe liver diseases and in patients receiving total parenteral nutrition339–342. Current treatment for Mn toxicity is with chelation therapy, which increases urinary Mn excretion225, but is nonspecific.

Since the identification of disease-causing mutations of SLC30A10, there has been considerable progress in understanding how the transporter works and where it is localized in cells290,343.

However, how the transporter is regulated is incompletely understood.

We identified BA composition, especially LCA, as a modulator of Slc30a10 expression in vitro, ex vivo, and in mouse ileum. We also showed that VDR is the mediator of this signaling pathway.

This is consistent with a previous report showing VDR activation inducing SLC30A10 transcription in Caco-2 cells, and that this requires the VDRE in SLC30A10’s promoter region334.

Other proposed contributors to SLC30A10 regulation include the ER stress response factor ATF4 and the zinc-sensitive transcription factor ZNF658344,345. The identification of this new BA- sensitive pathway may shed light on a known phenomenon: Mn poisoning has been reported in patients on total parenteral nutrition340–342, suggesting that the lack of intestinal BA signaling leads to reduced SLC30A10 and impaired efflux of Mn from enterocytes into the intestinal lumen, consequently reducing Mn excretion.

Our data show that Slc30a10 transcription could be induced by LCA and calcitriol in mouse ileum. Claro da Silva and colleagues previously reported increased SLC30A10 mRNA levels in half of duodenal biopsies from volunteers administered oral calcitriol (0.5 µg for 10 days)334.

However, ileal biopsies were not reported. Our data also demonstrate that Slc30a10 induction was not completely abrogated upon removal of LCA from BA pools or deletion of VDR. Thus,

72 other BAs and nuclear receptors might also contribute to BA-dependent induction of Slc30a10. A published ChIP-seq dataset identified two potential FXR binding sites within 1 kb of the first exon of mouse Slc3010, and another potential site within 5 kb346. However, these binding peaks were approximately an order of magnitude smaller than those seen for classical intestinal FXR targets Fgf15 and Slc51a/Osta346, potentially indicating a smaller contribution of FXR compared to VDR at this gene. Though our data indicate CDCA was not the cause for the differential expression of Slc30a10 by the BA pools, we cannot rule out a role for FXR, and experiments in

FXR–/– gut organoids are of future interest.

Similar to BAs, a significant portion of Mn undergoes enterohepatic cycling274,275. Thus, enterocytes are exposed to luminal Mn from two sources: bile and diet. In adult humans, only about 3-5% of ingested Mn is absorbed216, indicating robust regulation of intestinal Mn absorption. Obstructing the bile duct resulted in reduced excretion rates of intravenously administered 54Mn in rats271, highlighting the importance of Mn clearance by the liver and final excretion in the feces. But the intestine appears to play an important role in Mn homeostasis as well, especially when liver excretion has been saturated217. While deletion of Slc30a10 only in hepatocytes is insufficient to cause hypermanganesemia, combined deletion in liver and gastrointestinal tract causes severe hypermanganesemia and neurotoxicity272, mimicking the whole-body Slc30a10 knockout mice278. These findings support the notion that intestine and hepatobiliary excretion systems both participate in Mn homeostasis.

Does BA-dependent regulation of Mn homeostasis have any impact on cardiometabolic disease?

Mn is a required or preferred cofactor for many enzymes, including arginase,

73 phosphoenolpyruvate carboxykinase (PEPCK), and pyruvate carboxylase (PC)216,347. Arginase competes with endothelial nitric oxide synthase (eNOS) for their substrate, l-arginine348.

Increased arginase activity has been implicated in endothelial dysfunction in diabetic and atherosclerotic settings, and arginase inhibition has been proposed to improve microvascular complications such as diabetic nephropathy and retinopathy242,243. Importantly, arginase activity can be fine-tuned by Mn levels. This was demonstrated in liver extracts from mice rendered Mn- deficient by knockout of the Mn uptake transporter Slc39a8. In these livers, arginase activity was significantly lower than in liver extracts from control Slc39a8flox/flox mice276. Conversely, adding

276 MnCl2 to the reaction buffer or overexpressing SLC39A8 led to increased arginase activity .

Interestingly, mice and rats rendered diabetic by streptozotocin injections showed increased liver arginase activity and increased hepatic Mn content349, suggesting insulin signaling might regulate liver Mn levels and Mn-dependent enzymes. The liver enzymes PEPCK and PC catalyze critical steps for gluconeogenesis. Additionally, oxaloacetate production by PC can also enter other pathways, one of which is the TCA cycle, and reduced PC activity leads to build up of lactate350,351.

Although Mn deficiency has been reported to reduce activities of these enzymes in adult rats221,235, the effects of excess Mn on these enzymes have not been reported. Whether (a) BA regulation of

SLC30A10 affects the activities of these Mn-dependent enzymes in vivo and (b) these Mn- sensitive enzymes partially mediate the relationship between BA composition and metabolic health are of interest for future investigations.

Whether Mn levels per se are associated with risk for metabolic disease is less clear. Some have reported that patients with type-2 diabetes have plasma or serum Mn at levels higher than controls, while others have reported the opposite352–355. Because Mn levels must be maintained

74 within a small range216,225, it makes sense that both too little and too much Mn would lead to negative consequences. Accordingly, a recent report showed a U-shaped relationship between plasma Mn and the odds ratio for type-2 diabetes356. When interpreting the previous findings, it should be noted that the most accurate circulating Mn levels are obtained from whole blood, not plasma, since over 60% of blood Mn is found in erythrocytes269. In an unusual case of diabetes, a patient showed severe hypoglycemia in response to oral MnCl2, which was abolished upon a partial pancreatectomy236. Interestingly, intravenous glucose tolerance tests in individuals with chronic manganism revealed reactionary hypoglycemia, which was proposed to be due to dysregulation of the hypothalamus-pituitary-adrenal axis357. Moreover, genetic variants in the

Mn uptake transporter SLC39A8, which recovers Mn from bile276, are linked to blood Mn levels as well as body mass index, total cholesterol, and HDL-cholesterol358–361. Though severe Mn deficiency and toxicity lead to overt neurological disorders, the role of Mn in metabolic diseases might be more nuanced.

Quantitative and qualitative changes in BA pools are associated with health outcomes in laboratory animals as well as humans. Yet, the diversity of BAs, BA receptors, and epithelial cell types present in the intestine pose challenges when dissecting effects of modulating the BA pool.

While it has been well-established that BAs–and BA pool composition–regulate macronutrient metabolism, this work reveals that BAs and BA pool compositions also regulate micronutrient homeostasis, which may be relevant for health and disease.

75 MATERIALS AND METHODS

Reagents

Taurine-conjugated α- and β-MCAs were purchased from Cayman Chemical. All other BAs, corn oil, and MnCl2 were obtained from Sigma. Calcitriol was obtained from Selleck Chemicals.

Unless noted otherwise, all cell culture media and supplements were purchased from Gibco.

Crypt isolation and gut organoid culture

Mouse ileal crypts were isolated following methods developed by the Clevers Lab305, with minor modifications. We euthanized adult (6-12 weeks old) mice using CO2 inhalation followed by cervical dislocation. With the exception of the growth medium, all solutions and Matrigel were kept ice-cold during handling of crypts and organoids. We divided the small intestine into 3 parts of equal length and collected the last segment, adjacent to the cecum. We cut open the ileum longitudinally and rinsed it in PBS. We minced the tissue and washed the pieces by vigorously pipetting in PBS, allowing the pieces to settle, and removing the cloudy supernatant.

We repeated this wash step until the supernatant was clear, 4-6 times. We then transferred the pieces into PBS containing 2 mM EDTA and incubated the mixture at 4ºC for 30-60 min with gentle shaking. Next, we removed the EDTA-PBS and replaced it with PBS containing 10% fetal bovine serum (FBS). We harvested crypts by vigorously pipetting, allowing the segments to settle, and collected the supernatant in a new tube. We repeated this harvesting procedure with additional FBS-PBS mixture, 3-4 times, pooling the supernatant from the same mouse. We then pelleted the crypts by centrifuging the crypts-FBS-PBS mixture at 900 rpm, 4ºC for 5 min. We discarded the supernatant, resuspended the crypts in base medium (Advanced DMEM/F-12 supplemented with 1X GlutaMax, 1X penicillin-streptomycin, and 10 mM HEPES), and pelleted

76 the crypts by centrifuging at 720 rpm, 4ºC, 5 min. We discarded the supernatant, resuspended the crypts in base medium, passed the crypts-medium mixture through a 70-µm cell strainer, and centrifuged the crypts-medium mixture at 900 rpm, 4ºC, 5 min. Finally, we resuspend the crypts in Matrigel and seeded them on pre-warmed 24-well Nunclon Delta surface-treated plates. After

15-20 min incubation at 37ºC, we added IntestiCult Mouse Organoid Growth Medium

(STEMCELL Technologies) to the wells. Medium was replaced twice weekly. Mature organoids were passaged every 7-10 days by dissolving the Matrigel dome with vigorous pipetting in PBS, passing the organoids-Matrigel-PBS mixture through a 27 ½-gauge needle, centrifuging to pellet the organoid pieces, resuspending them in new Matrigel, and distributing the organoid-Matrigel mixture into new pre-warmed multiwell plates.

Caco-2 cell culture

Cells were cultured in DMEM containing GlutaMAX and high glucose, supplemented with 10%

FBS and 1X penicillin-streptomycin and incubated in a 37ºC, 5% CO2 chamber. Medium was replenished 3 times per week and cells were passaged by trypsinization every 5-7 days.

Preparation of micelles

We prepared micelles as previously described314 with minor modifications. Individual stock solutions of oleic acid (OA), 2-palmitoyl glycerol (2-PG), phosphatidylcholine (PC), cholesterol,

GUDCA, and LCA were prepared in chloroform. Individual stock solutions of all other BAs were prepared in PBS. We mixed lipophilic components (those in chloroform stocks) in a glass vial and allowed them to dry under N2 stream. We mixed BAs to prepare four distinct BA pools: human low (10%) 12HBA (hL), human high (90%) 12HBA (hH), mouse low (10%) 12HBA (mL),

77 and mouse high (90%) 12HBA (mH). After the lipophilic components dried, we added BA pools to the vials and vortexed the mixture. We further diluted the mixture with DMEM containing

0.2% BSA (base medium), yielding final concentrations of 0.6 mM OA, 0.2 mM 2-PG, 0.2 mM

PC, 0.05 mM cholesterol, and 1 mM total BAs. Composition of BA pools are detailed in Table 1 and illustrated in Fig. 1A.

BA treatments

We removed gut organoids from Matrigel and exposed the lumens by pipetting in ice-cold PBS followed by centrifugation at 150g, 4ºC for 10 min. Following a second PBS wash, we placed exposed gut organoids to micelle components without BAs (vehicle), or 1 mM BA pool (hL, hH, mL, or mH) in base medium (DMEM, 0.2% BSA) for 24 hours. For BA treatments in the absence of micelles, BA pools were prepared in PBS and diluted in base medium for a final concentration of 1 mM. For Caco-2 cells, we seeded 200,000 cells/well into 12-well plates and allowed cells to reach confluency. We replaced the growth medium, washed cells with PBS, added test media to the cells as indicated in the experiments.

RNA sequencing

We extracted RNA using the RNeasy Mini Kit (Qiagen). RNA concentration and quality were determined by Qubit Bioanalyzer. RNA from 3 samples per treatment group were submitted to the JP Sulzberger Columbia Genome Center for library preparation (standard poly-A pull-down for mRNA enrichment), RNA sequencing (30M depth, single read), and processing of raw data.

Differential expression analysis on counts data was done using the DESeq2 package in R.

78 Mn efflux assays

Mn efflux assays were done as previously described343. We collected organoids by dissolving the

Matrigel dome with ice-cold PBS, pipetting, and centrifuging at 150 g for 10 min. Organoids were first incubated in ‘exposure media’ (DMEM supplemented with 0.2% BSA containing 0 or 500

µM MnCl2) for 16h at 37ºC, 5% CO2. Following exposure, organoids were washed with PBS, given media containing micelle components (vehicle), 1 mM hL, or 1 mM hH, and incubated for another 20h. Organoids were pelleted by centrifugation and efflux media were collected in metal- free tubes. For each treatment group, organoids were pooled together, washed with PBS, and collected in metal-free tubes. For Mn efflux assay in Caco-2 cells, we followed the same procedure, with the exception of 100 µM MnCl2 for exposure and cell pellets were not pooled.

Mn was measured by inductively coupled plasma mass spectrometry (ICP-MS).

Mouse experiments

Male C57BL/6 mice (Taconic) were given AIN-93G with vitamin D adjusted at 50 IU/kg for 3 days before the experiment. Mice had free access to food at all times. Ethanol (vehicle), LCA, and calcitriol were dissolved in corn oil. Oral gavages were done at 14 h and 2 h prior to sacrifice.

Doses and time points were based on previous studies by Ishizawa and colleagues362. We collected ileum epithelia by cutting open the segment longitudinally and scraping the mucosa layer away from the muscle wall. Tissues were stored at –80ºC until processed for RNA extraction.

RNA extraction, cDNA synthesis, and qPCR

We extracted RNA from gut organoids using the RNeasy Mini Kit (QIAGEN) and used 200 ng for cDNA synthesis. We extracted RNA from Caco-2 cells and ileum epithelium scrapings using

79 TRIzol (Thermo Fisher) and used 1 µg for cDNA synthesis. cDNA synthesis was done using the

High Capacity cDNA Reverse Transcription Kit (Thermo Fisher). Quantitative real-time PCRs were carried out using iTaq Universal SYBR Green Supermix (Bio-Rad) and the CFX96 Real-

Time PCR detection system (Bio-Rad). Mouse 36b4 or B2m were used as for reference genes for samples from mouse gut organoids and tissues. Human RPLP0 (primers from QIAGEN) was used as reference gene for cDNA from Caco-2 samples. Primer sequences are listed in Appendix.

80 FIGURES

Figure 1. RNA sequencing reveals differential regulation of gene expression by BA pool composition. Gut organoids were treated with micelle components without BAs (vehicle) or 1 mM of human low 12HBA (hL), human high 12HBA (hH), mouse low 12HBA (mL), or mouse high 12HBA (mH). (A) Simplified BA synthesis pathway. CYP8B1 activity determines the production of CA instead of CDCA, as well as abundance of CA conjugated and derivatives in the BA pool. CDCA dehydroxylation by gut bacteria yields LCA. (B) Composition of BA pools used in this study. With the exception of LCA, glycine-conjugated BAs were used in human pools, while taurine-conjugated BAs were used in mouse pools. (C) Genes preferentially induced by hL and mL compared to hH and mH identified by RNA sequencing (log2 fold-change > 1 and padj < 0.05). (D) Expression of FXR target genes, (E) expression of VDR target genes measured by qPCR.

Figure 2. Validation of differential expression of FXR and VDR target genes. (A, B) Ratio of gene expression induced by low 12HBA to high 12HBA. Each point represents (mRNA levels in low 12HBA-treated organoids)/(mRNA levels in high 12HBA-treated organoids) for the gene of interest from one batch of gut organoids derived from one mouse. Ratios >1 signify higher expression in low 12HBA-treated group, ratios <1 signify higher expression in high 12HBA- treated group, ratios = 1 signify no difference between low- versus high- 12HBA-treated groups.

The gray dotted line marks ratio = 1. H denotes hL/hH, M denotes mL/mH. (A) VDR targets, (B)

FXR targets. (C, D) Gene expression in gut organoids treated with 1 mM BA pools in the absence or presence of micelles. (C) Cyp24a1, (D) Fgf15. (E, F) Gene expression in Caco-2 cells treated with 1 mM BA pools. (E) VDR targets, (F) FXR targets.

Figure 3. Low 12HBA pools regulate Mn efflux from gut organoids and Caco-2 cells.

(A) Slc30a10 mRNA levels in a representative batch of gut organoids treated with micelle components (vehicle), 1 mM human low 12HBA pool, or 1 mM human high 12HBA pool. (B)

Slc30a10 mRNA levels in a representative batch of gut organoids treated with vehicle, 1 mM mouse low 12HBA pool, or 1 mM mouse high 12HBA pool. (C) Fold-change difference in

Slc30a10 induction across different batches of organoids. Each point represents (average

Slc30a10 level induced by low 12HBA)/(average Slc30a10 level induced by high 12HBA) from one batch of gut organoids derived from one mouse. (D) SLC30A10 mRNA levels in Caco-2 cells after treatment with vehicle, 1 mM human low 12HBA pool, or 1 mM human high 12HBA pool.

(E) Schematic of Mn efflux assay. (F) Mn in efflux medium and (G) intracellular Mn after gut organoids were treated with 0 or 500 µM MnCl2 for 16h followed by vehicle, 1 mM human low

12HBA pool, or 1 mM human high 12HBA pool for 20h. (H) Mn in efflux medium and (G) intracellular Mn after Caco-2 cells were treated with 0 or 100 µM MnCl2 for 16h followed by vehicle or human BA pools for 20h.

Figure 4. Slc30a10 is transcriptionally regulated by LCA–VDR signaling. Messenger RNA levels of Slc30a10, FXR targets, and VDR targets in (A) wild-type gut organoids after exposure to micelle components (vehicle) or mouse BA pools containing or lacking CDCA. Pools lacking

CDCA had compensatory increases in other non-12-HBAs (UDCA, α- and β-MCAs) such that the total pool concentration is unchanged (1 mM); (B) wild-type gut organoids after exposure to vehicle or human BA pools containing or lacking LCA. Pools lacking LCA had compensatory increases in other non-12-HBAs (CDCA, UDCA); (C) gut organoids derived from Vdr+/+, Vdr+/–,

82 and Vdr–/– littermates after exposure to vehicle or human BA pools. n=/group, ANOVA followed by pairwise comparisons with Benjamini-Hochberg correction, *p < 0.05, **p < 0.01

Figure 5. VDR activation increases Slc30a10 transcription in vivo. (A) Slc30a10 expression in liver and gastrointestinal tissues (n=7 mice). Liver was used as reference tissue; Relative levels of

(B) Slc30a10 and (C) VDR targets Cyp24a1 and S100g after oral gavage with corn oil supplemented with ethanol (vehicle), 0.8 mmol/kg LCA, or 50 nmol/kg calcitriol at 14 hours and

2 hours before euthanasia (n=4–5 mice/group). ANOVA followed by pairwise comparisons with

Benjamini-Hochberg correction, *p < 0.05, **p < 0.01

83 Figure 1. RNA sequencing of gut organoids reveal varying BA pool composition induce differential gene expression

B Human pools Mouse pools CA DCA CDCA UDCA LCA β -MCA Low (10%) High (90%) Low (10%) High (90%) α-MCA 12HBA 12HBA 12HBA 12HBA (hL) (hH) (mL) (mH)

84 Figure 1 (continued) * C D * * *

* * * *

E * * * *

* * * *

85 Figure 2.

** *** *** C *** ***

** ***

+ micelles + micelles

*** *** D *** *** *** *** *** *** *** ***

+ micelles + micelles

*** *** E 8 *** *** 10 *** *** F 5 6 8 4

mRNA 6 3 mRNA 4 mRNA 4 2 2 1

2 FGF19 CYP3A4 CYP24A1 0 0 0 veh hL hH veh hL hH veh hL hH

86 Figure 3. Low 12HBA pools preferentially induce Slc30a10 and increased Mn efflux

A *** B C *** *** ** **

D E Caco-2 cells 3 *** *** *** *** *** 2 ***

1 Slc30a10 Slc30a10 mRNA 0 vehA hLB hHC vehmiA miBhL miChH – micelles + micelles

F Efflux media Intracellular (pooled) ** *** *** Organoids

0 Mn + Mn 0 Mn + Mn

G Efflux media Intracellular *** *** ** 2 - Caco

0 Mn + Mn 0 Mn + Mn

87 Figure 4. Induction of Slc30a10 transcription is primarily driven by LCA and VDR

A B *** *** *** *** *** *** *** *** *** *

n.s. *** *** C ***

n.s. n.s. D E n.s. *** *** *** *** *** ***

F * *** n.s.

88 Figure 4 (continued)

+/+ +/– –/– VDR VDR VDR VDR–/– (close-up) G * *** * *** *** n.s. *** ***

H VDR+/+ VDR+/– VDR–/–

*** ***

VDR+/+ VDR+/– VDR–/–

*** *** *** ***

*** ***

I VDR+/+ VDR+/– VDR–/–

*** ***

*** *** *** ***

VDR+/+ VDR+/– VDR–/– *** *** * *** *** *** *** *** ***

89 Figure 5. Slc30a10 expression in ileum is inducible by LCA and VDR signaling

A **

B Ileum *** C *** *** *** *** ***

D Liver

90 FDR 2.70E-08 2.34E-05 6.56E-04 Fold Enrichment 3.61500961 2.78401021 6.74692845 Pop Pop Total 18082 17446 17446 81 459 604 Pop Pop Hits 425 415 415 List List Total Genes HSD17B11,ACOX1, CHKA, PTGS2,ALOXE3, CHKB, ASAH2, ABHD3, EHHADH, APOBR, INSIG2, APOB, MGLL, ETNK1, ACOT12, HSD17B4, PLCB1, PLCD1, SCD1, ACSL5, ACAA1B, CUBN, MOGAT2, SOAT2, NCEH1, LIPA, PLB1, EPHX2, LPCAT3, LPIN2, ACACB, LPCAT4,MTTP, GDPD2, PCX, CLPS, HMGCS2, LIPH, VLDLR HSD17B11,ME1, ACOX1, CYP24A1, ALDH1L1, CYP3A25, PTGS2,ALOXE3, EHHADH, ALDH3A2, ALDH1L2, OSGIN1, ADH1, FMO5, MTHFD2, GPX3, ADH4, ALDH1A3, HSD17B4, SMOX, ALDH1A7, NOS2, QSOX1, CYP3A44, SUOX, SCD1, ADH6A, CYP3A13, CYP3A11, DHRS9, CYP4A10, AKR1B8, POR, RDH10, AKR1B7, DHRS1, HSDL2,TPH1, BCO2, RETSAT NCEH1, ACOT2, ABHD3, ACOT4, ACOT5, ACOT1, CES2A, ACOT12, ACOT3, CES1G, MGLL, LIPH, CES2B 1.60E-11 1.57E-08 4.39E-07 PValue % 7.88 8.08 2.63 39 40 13 Count Description lipid metabolic process metabolic lipid activity oxidoreductase hydrolase ester carboxylic activity GO term GO Table 1. Pathway analysis of 516 genes induced by both human low 12HBA and mouse low 12HBA pools low mouse 12HBA and low human both by induced genes analysis 516 of Pathway 1. Table GO:0006629 GO:0016491 GO:0052689

91 FDR 0.00281558 0.00950826 0.01207519 0.03207602 0.04137758 Fold 2.7549538 Enrichment 2.39163244 19.4024096 4.09095023 15.9547059 Pop Pop Total 18082 17446 17446 18082 18082 13 16 676 412 156 Pop Pop Hits 425 415 415 425 425 List List Total Genes HSD17B11,ME1, ACOX1, CYP24A1, ALDH1L1, CYP3A25, PTGS2,ALOXE3, EHHADH, MTHFD2, ALDH3A2, ALDH1L2, ALDH1A3, ADH1, FMO5, ALDH1A7, GPX3, ADH4, NOS2, HSD17B4, SMOX, SCD1, CYP3A44, QSOX1, CYP3A11, CYP3A13, SUOX, DHRS1, AKR1B8, POR, DHRS9, CYP4A10, AKR1B7, RDH10, HSDL2,TPH1, BCO2, RETSAT ACOX1, PVR, FGF15, EHHADH, ANG, SCT, ACOT4, ACOT2, GSTK1, CCDC129, NOS2, HSD17B4,FGF3, MATK, H2- H2-Q1, ICOSL, PLAT, Q2, BTNL2, EPHX2, CD160, PLAUR, LAMA3,GM8909, LAMA5, H2- BL, VEGFA ACOT1, ACOT2, ACOT12, ACOT3 ACOT4, ACOT5, PTGS2, LIPA, ACOX1, SCD1, ACACB, EHHADH, ALOXE3, LPIN2,CYP4A10, ACOT12, HSD17B4, FABP2, MGLL, ACSL5 ACAA1B, HSD17B4, ACOT2, ACOX1, ACOT3 ACOT4, ACOT5, 1.66E-06 6.36E-06 8.08E-06 1.89E-05 2.44E-05 PValue % 7.68 5.45 1.21 3.03 1.21 6 6 38 27 15 Count Description oxidation-reduction oxidation-reduction process binding receptor acyl-CoAhydrolase activity fattyacid metabolic process acidlong-chain fatty very process metabolic GO term GO Table 1 (continued) Table GO:0055114 GO:0005102 GO:0047617 GO:0006631 GO:0000038

92 Chapter 4

Conclusions and Future Directions

In this PhD thesis work, we examined the consequences of shifting BA pool composition on gene expression. These studies revealed a previously unknown role of BAs in Mn homeostasis. Here we discuss current conclusions, ongoing studies, and suggest avenues for future research.

4.1 BA regulation of Mn homeostasis

In chapter 3, we uncovered a pathway by which BAs regulate cellular Mn homeostasis. Mn transporters essential for systemic Mn homeostasis have only been identified within the last 10-

15 years, and the regulation of these transporters remains poorly defined. We showed that (i) low

12HBA pools containing LCA increased expression of Slc30a10 and induced Mn efflux from cells, (ii) the transcriptional control was largely mediated by VDR, and (iii) this pathway is active in ileal enterocytes, but not liver. This pathway is summarized in Fig 4.1. Although VDR activation has been previously shown to activate SLC30A10 in Caco-2 cells, there was insufficient evidence for its relevance in vivo334. Our work confirmed that this transcriptional regulation also occurs in mouse ileum. It would be interesting to determine whether this transcriptional regulation affects Mn levels in intestine or in the whole body, or whether it affects the activities of

Mn-dependent enzymes. In ongoing experiments, we are measuring tissue Mn levels in LCA- treated mice.

Another avenue of interest would be to study whether Mn levels are altered in vivo in settings where BA composition, especially LCA levels, are modified. LCA is a product of CDCA

93 dehydroxylation by certain gut bacteria. Thus, interventions affecting gut bacteria could lead to changes in LCA abundance. For example, fexaramine administration leads to changes in mouse gut bacteria population and increased T-LCA in the gallbladder by ~1000 fold15. On the other hand, mice treated with the antibiotic ciprofloxacin resulted in reduced hepatic T-LCA content to about 30% of control levels363. Additionally, Cyp8b1–/– mice lack 12HBAs and have compensatory increases in non-12HBAs, including LCA and its conjugates13,36,184. Future experiments could examine the effects of these conditions on Mn homeostasis.

Considering the interconnectedness of metal homeostasis, BAs might also affect other metals.

Systemic Mn levels are especially affected by iron status216,270,364. Small intestine expresses divalent metal transporter 1 (DMT1, encoded by SLC11A2) is a major facilitator of iron absorption, but can also transport Mn216,364,365. Additionally, transferrin, the chief carrier protein for circulating iron, can also bind Mn364,366. Iron deficiency is common, affecting over 2 billion people worldwide270. Higher blood Mn levels have been reported in infants, children, and women with iron deficiency270, and 2.5-fold higher intestinal Mn absorption has been reported in patients with anemia270. Thus, people with iron deficiency are at greater risk for Mn poisoning216,270.

Conversely, patients with hypermanganesemia due to SLC30A10 mutations have depleted iron stores and, in addition to chelation therapy, are treated with iron supplementation225. Further studies could address the potential BA regulation of additional metals.

4.2 Coordinate regulation of Mn transporters by low 12HBA pools

In addition to SLC30A10 on the lumenal surface, enterocytes express other Mn transporters. As described above, DMT1 can transport Mn from the intestinal lumen into enterocytes216. Another

94 Mn uptake transporter, SLC39A14, is responsible for Mn intake from the basolateral side273.

Considering the proposed synergy of SLC30A10 and SLC39A14 in mediating whole-body Mn excretion251,367, we asked whether low 12HBAs would also increase Slc39a14 expression.

Interestingly, Slc39a14 was not among the differentially expressed genes identified by RNA-seq, and none of the BA pools induced Slc39a14 expression in gut organoids (Fig. 4.2A). Similarly,

BA pools did not affect Slc11a2 expression (Fig. 4.2B). Consistently, we did not observe induction of SLC39A14 nor SLC11A2 upon exposure to hL or hH pools in Caco-2 cells (Fig.

4.2E).

On the other hand, we observed that the transcript levels of Slc39a8 to be affected by the BA pools similar to Slc30a10. SLC39A8 is a Mn uptake transporter that is highly expressed in liver, where it is critical for Mn uptake from bile into hepatocytes276. The localization and physiological relevance of SLC39A8 in intestine has not been reported. We found that Slc39a8 is expressed in small intestine, at levels approximately 10-30% of those in liver (Fig. 4.2C). Furthermore, we found that gut organoids treated with hL and mL pools upregulated Slc39a8 transcription more strongly than hH and mL pools (Fig. 4.2D). Caco-2 cells also showed increased SLC39A8 transcription upon hL, but not hH, treatment (Fig. 4.2E). Further analyses showed that Slc39a8 transcription was blunted upon removal of LCA from BA pools, as well as in VDR KO gut organoids (Figs. 4.2F,G). These data support the possibility that both Slc30a10 and Slc39a8 are regulated by LCA-to-VDR signaling. They also suggest that Mn transport into and out of enterocytes could be coordinated by BA regulation of Slc30a10 and Slc39a8 at the transcriptional level. Future experiments using monolayers of polarized intestinal epithelial cells will determine

(i) whether Mn can be taken up from the basolateral side in an Slc39a8-dependent manner, and

95 (ii) whether BAs induce the unidirectional transport of Mn across the epithelial layer from basolateral fluid into lumenal fluid, due to coordinated induction of Slc39a8 and Slc30a10.

4.3 Potential reciprocal regulation: Mn effects on BAs

We considered the possibility that BAs and Mn reciprocally regulate each other. To begin to investigate this, we examined Slc30a10 whole-body knockout mice, which have extreme hypermanganesemia, because of impaired Mn excretion. We compared these knockouts to a group of littermate controls, comprising heterozygous and wild-type mice. We collected enterohepatic tissues (liver + gallbladder + small intestine) and measured the total BA pool by

LC-MS/MS. We found that Slc30a10–/– mice have decreased total BA pool size, and substantial differences in BA pool composition, with relative reductions in 12HBAs and in secondary BAs

(Fig. 4.3A). This suggested that Mn regulates BA homeostasis and 12α-hydroxylation.

To investigate mechanisms by which Mn affects BAs, we measured hepatic gene expression of the enzymes involved in BA synthesis. We found Slc30a10–/– mice have a remarkable 99% reduction in hepatic Cyp8b1 expression (Fig 4.3B). They also show a 50% reduction in the expression of Cyp27a1, and trends towards reductions in Cyp7a1 and Cyp7b1 (Fig 4.3B). This suggests that excess intracellular Mn impairs the expression of BA synthesis enzymes, with a particularly potent effect on Cyp8b1.

To date, no Mn-sensitive transcription factors have been identified. To investigate the mechanisms by which Slc30a10 ablation decreased Cyp8b1 expression, we examined transcription factors known to regulate it. HNF4a and FoxO1 are known to promote Cyp8b1

96 expression, but we found levels of HNF4a and FoxO1 were normal in Slc30a10–/– mice (Fig.

4.3C). Hepatic FXR suppresses the expression of Cyp8b1, by inducing the transcriptional repressor Shp. We found both FXR and Shp were significantly reduced in Slc30a10–/– mice (Fig.

4.3C). Though the mechanism of this is unknown, decreased levels of these Cyp8b1-repressors cannot explain the reduction in Cyp8b1 expression. Finally, we measured expression of the carbohydrate response element binding protein (ChREBP), which is activated by intracellular glucose metabolism, and which was recently reported to induce Cyp8b1368. We found ChREBP to be decreased by 85% in Slc30a10–/– mice (Fig. 4.3C), suggesting the possibility that ChREBP is sensitive to Mn. Future experiments will examine this in further detail.

Many transcription factors and other DNA-binding domain-containing proteins require zinc in their zinc finger domains254,369. Molecular studies demonstrate that alternative metals can replace zinc in these DNA binding domains370. However, in the case of some metals, including copper and Mn, the tertiary structure of the domain is compromised370. Elevated copper levels in livers from Wilson’s disease patients, progressive familial intrahepatic cholestasis (PFIC), and Atp7b–/– mice (an animal model of Wilson’s disease) impaired (i) binding of nuclear receptors FXR, RXR,

HNF4α, and LRH-1 to their response elements and (ii) expression of target genes256. It is possible that excess Mn disrupts nuclear receptor signaling by a similar mechanism. Consistently, preliminary experiments that we carried out in mouse hepatoma Hepa1c1c7 cells showed that adding 100 µM MnCl2 to the media significantly reduces BA induction of FXR targets (Fig.

4.3D). Further investigations will determine whether high intracellular Mn interferes with the functions of nuclear receptors involved in BA homeostasis, and whether these result in metabolic consequences.

4.4 BA-dependent induction of intestinal gene expression through VDR and FXR

Our studies in Chapters 2 and 3 revealed that BAs exert transcriptional control over thousands of genes, many of which have never previously been reported as BA targets. Furthermore, we found that shifting BA composition results in differential expression of many of these genes.

In Chapter 3, we focused on VDR. We found that VDR target genes are preferentially induced by low 12HBAs in both mouse ileal organoids, Caco-2 cells, and mouse ileum. This indicates that although most prior studies of BA-dependent transcriptional regulation have focused on FXR,

VDR signaling can also be affected by shifts in BA pool composition.

Our RNA-seq data also showed differences in expression of some FXR targets in response to low- versus high-12HBA pools. This may be partially explained by abundant CDCA, the strongest endogenous FXR agonist, in human low 12HBA (hL) pool. However, other FXR targets were not differentially regulated by 12HBA proportion. The variable induction of FXR targets by the distinct BA pools suggests functional selectivity. We initially expected mouse low 12HBA (mL) pool to blunt induction of FXR targets due to (i) the abundance of taurine-conjugated α- and β-

MCAs (collectively comprising 67.5% of mL pool, see Chapter 3, Fig. 1B) and (ii) having seen this effect when primary mouse gut organoids were given a pool consisting of 80% MCAs + 20%

12HBAs (Chapter 2, Fig. 2.9). However, mL pool did not differ in its ability to induce FXR targets compared to the mouse high 12HBA (mH) pool (see Chapter 3, Fig. 2B). Of note, we designed the mL pool based on the enterohepatic BA pool of Cyp8b1–/– mice, which also have significant increases in CDCA to compensate for lack of hepatic CA synthesis36,184. Thus, the levels of CDCA

98 (13.5%) in mL might explain the similarities between mL and mH pools’ abilities to induce expression of FXR targets. Additionally, the RNA-seq data showed 750 genes induced by mL, but not hL pool, suggesting specific signaling by MCAs to promote expression of these genes. As

FXR antagonists, MCAs might inhibit FXR-dependent suppression of gene expression or activate entirely different receptors. In the future it would be of interest to further dissect which subsets of

FXR targets are sensitive to 12HBAs, and which are not. Promoter analysis using computational methods could reveal genomic mechanisms that confer sensitivity to 12HBAs.

Another potential difference between mouse and human BA signaling is in the structure of FXR itself. In human FXR, there are two critical residues in the ligand-binding domain, Asn354 and

Ile372, that render it highly sensitive to CDCA185. Interestingly, substituting Asn and Ile into the corresponding Lys366 and Val384 positions in mouse FXR results in increased affinity and response to CDCA in vitro185. This could explain our observation that in human Caco-2 cells, there is preferential FXR activation by human low 12HBA pool (which is rich in CDCA, see Chapter 3,

Fig.1B). We observed consistent findings in hiPSC-derived gut organoids (see Chapter 2, Fig 2.6).

However, in mouse organoids, preferential induction by human low 12HBA pool was blunted and varied between FXR targets. This supports the notion that translating findings about FXR signaling from preclinical models into human cells and tissues requires caution. Because mouse primary gut organoids provide practical alternatives to the time-intensive hiPSC-derived gut organoids, or when fresh human intestinal biopsies are unavailable for crypt isolation, a more humanized model for potential future development could be to use genome editing to substitute the two critical residues in mouse FXR.

99 4.5 BA-dependent suppression of intestinal gene expression

In Chapter 3 we reported the genes that were induced by low 12HBA pools. We focused on induced genes, because that is the best-characterized mode of action for gene regulation via nuclear receptors. On the other hand, our RNA-seq experiment also identified many genes suppressed by BAs, and some of them were differentially suppressed by low- versus high- 12HBA pools (Fig. 4.5). Pathway analysis of genes whose levels were reduced by BAs showed enrichment of genes involved in cell cycle and proliferation (Table 4.5). This is consistent with a recent study that reported (i) APCmin/+ mice (a model of colon cancer) treated with T-βMCA, which antagonizes FXR, had increased expression of cancer stem cell markers and intestinal stem cell markers in their tumors compared to vehicle-treated mice; (ii) conversely, intestinal organoids derived from APCmin/+ mice treated with synthetic FXR agonists fexaramine D, GW4604, and obeticholic acid had reduced cell proliferation and WNT signaling compared to vehicle-treated organoids; and (iii) APCmin/+ mice treated with fexaramine D had increased intestinal p53 signaling and delayed tumor progression compared to vehicle-treated mice321. Although these experiments suggest a suppressive effect of BA-to-FXR signaling in intestinal and cancer stem cells, it does not fully examine the heterogeneity of the endogenous BA pool. The effects of changing BA composition—without significantly changing the total BA pool size, as well as those that may be mediated by other and/or multiple BA receptors—on intestinal stem cells and proliferation, are of interest and currently being investigated by Dr. Sei Higuchi in the Haeusler

Lab.

100 4.6 Final remarks: BAs and Mn in health and diseases

Enterohepatic tissues are key sites for BA action and regulation of Mn homeostasis. Our studies demonstrate that enterocyte Mn transport could be regulated by BA pool composition through transcriptional regulation SLC30A10, a Mn efflux transporter. Notably, Mn availability can modulate expression and activity of Mn-dependent enzymes, some of which have been implicated in cardiometabolic disease, neurodegenerative diseases, and certain cancers234,242,259.

Further research would answer whether modulating Mn levels could be a mechanism by which

BA composition influence health outcomes.

101 FIGURES

Figure 4.1. Model of Mn transport regulation by BA pool composition. Most Mn enters the body via ingestion of Mn-containing foods and absorption in the gut. Mn enters the circulation and is distributed throughout the body, and excess Mn is cleared by hepatocytes and exported to the bile. Enterocytes are exposed to luminal Mn from diet and bile. In settings where LCA is relatively abundant, LCA activates VDR, consequently increasing Slc30a10 expression and subsequent Mn efflux.

Figure 4.2. Transcriptional effects of low 12HBAs and LCA–VDR signaling on other Mn transporters. Relative mRNA expression of several known Mn transporters in (A) gut organoids treated with 1 mM human BA pools; (B) gut organoids treated with 1 mM mouse BA pools; (C)

Caco-2 cells treated with 1 mM human BA pools. Slc39a8 expression in (D) organoids treated with 1 mM mouse BA pools with or without CDCA; (E) organoids treated with 1 mM human BA pools with or without LCA; (F) VDR+/+, VDR+/–, or VDR+/– gut organoids treated with 1 mM human BA pools.

Figure 4.3. Potential reciprocal regulation of BAs by Mn. (A) BAs in Slc30a10 KO mice; (B, C,

D, E) Hepatic gene expression in Slc30a10 KO mice; (F) Gene expression in Hepa1c1c7 cells treated with 100 µM BA pools or 500 nM calcitriol, with or without 100 µM MnCl2 for 24 h.

Figure 4.5. Suppression of intestinal gene expression by BAs. Differential expression of 51 genes that were suppressed by all BAs (log2FC < -1 vs. vehicle, padj < 0.05).

102 Figure 4.1

Low 12HBA pools

lumen Mn

SLC30A10 VDR Slc30a10

103 Figure 4.2

A B

104 Figure 4.2 (continued)

n.s. F *** *** *** ***

VDR+/+ VDR+/– VDR–/– G ** * ** **

105 Figure 4.3

A 6000 3 8000 *** *** *** 4000 6000

12HBAs 2 - * 4000 2000 1

(nmol/g tissue) (nmol/g 2000 (nmol/g tissue) (nmol/g BA BA concentration BA BA concentration 0 12HBAs/non 0 0 12HBAs non-12HBAs Control KO Control KO Control KO

B Bile Acid Synthesis Genes 1.5 p = 0.08 *** ** 1 Control 0.5 KO

Relative Expression 0 Cyp7a1 Cyp27a1 Cyp7b1 Cyp8b1

C Transcription Factors 1.5 *** ** ** 1 Control 0.5 KO

Relative Expression 0 Shp FXR HNF4α ChREBP FoxO1 D Shp Bsep 3 ** 2 ** ** 2 ** p=0.06 * * 1 1

Relative expression 0 0 veh hL hL calci veh hL hL calci

Mn: – + – + – + – + Mn: – + – + – + – +

106 Figure 4.4

107 Table 4.1 Gene enrichment analysis of 1600 genes suppressed by at least 1 BA pool BA 1 least at by suppressed genes 1600 of analysis enrichment Gene 4.1 Table

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