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Exploring the impact of elevated bile acids in metabolic dysfunction- associated steatotic liver disease in vitro

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Exploring the impact of elevated bile acids in metabolic dysfunction- associated steatotic liver disease in vitro

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Content Exploring the impact of elevated bile acids in metabolic dysfunctionassociated steatotic liver disease in vitro
By
Nrupa Dinesh Patel
A Thesis Presented to the
FACULTY OF THE USC ALFRED E. MANN SCHOOL OF
PHARMACY AND PHARMACEUTICAL SCIENCES
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCES)
August 2024

ii
Acknowledgments
I would like to express my deepest gratitude to Dr. Vassilios Papadopoulos for his incredible
support and the opportunity he has given me to join his lab. I truly appreciate his constant
encouragement and unwavering support in every aspect of my learning and growth. My sincere
thanks to Yuchang Li, whose guidance and innovative thinking inspired me to explore novel
approaches and maintain perseverance toward successful research with consistency and high
discipline. His support, especially during challenging times while conducting experiments, was
invaluable.
I am deeply grateful to Chantal for her constant assistance and cheerful demeanor, always
helping me with anything I needed in the lab. A heartfelt thank you to Garett and Christina, who
have been excellent mentors and have helped me in statistical analysis. Their guidance and the
skills I acquired from them have been instrumental in my development. Special thanks to
Mahima, from whom I learned a lot. Her support and companionship, especially during our trip
to the ENDO conference in Boston, made it a memorable and valuable educational experience.
I would also like to extend my sincere gratitude to Dr. Martine Culty for her motivating feedback
and comments during lab meetings. I am also grateful to Dr. Bangyan Stiles for her crucial
feedback and comments, which made my thesis more impactful and informative.
Finally, I want to thank my parents for their incredible support, without whom I would not be
where I am today. Their love and sacrifices have always been the foundation of my success.
Thank you to everyone in Dean's lab for their support throughout this journey.

iii
Table of Contents
Acknowledgements............................................................................................................. ii
List of Tables ..................................................................................................................... iv
List of Figures......................................................................................................................v
Abbrevations...................................................................................................................... vi
Abstract............................................................................................................................ viii
Chapter 1: Introduction .......................................................................................................1
1.1 Epidemiology ...................................................................................................2
1.2 Risk Factors .....................................................................................................3
1.3 Pathophysiology ...............................................................................................5
1.4 Bile ...................................................................................................................7
1.5 Bile acids...........................................................................................................8
1.6 BAs and MASH..............................................................................................11
Chapter 2: Methods ...........................................................................................................14
2.1 Cell Culture and Treatment ............................................................................14
2.2 Seahorse Assay ...............................................................................................15
2.3 MTT Assay .....................................................................................................16
2.4 Immunocytochemistry ....................................................................................16
2.5 Mitochondrial Membrane Potential ................................................................17
2.6 RNA Extraction and qPCR.............................................................................18
2.7 Statistical Analysis..........................................................................................20
Chapter 3: Results .............................................................................................................21
3.1 Serum Bile Acid Profiling in a MASH Rat Model.........................................21
3.2 MTT Test Validation of Bile Acid Concentrations for Further Invitro
Studies.............................................................................................................23
3.3 Gene Expression Changes Induced by Bile Acids in Huh7 Cells ..................24
3.4 Mitochondrial Stress Test Reveals Impaired Function with Bile
Acid Exposure.................................................................................................26
3.5 Mitochondrial Membrane Potential Disruption by Bile acids .......................28
3.6 Gene Expression Profiling of Bile Acid-treated LX2 Cells............................30
3.7 Visualization of Fibrogenic Responses in LX2 Cells Treated with Bile
Acids...............................................................................................................32
3.8 Investigating Bile Acid Effects on Macrophage Activation: THP-1 Cells
qPCR...............................................................................................................33
Chapter 4: Discussion ........................................................................................................35
Chapter 5: Conclusion........................................................................................................38
References..........................................................................................................................39
Appendices.........................................................................................................................43

iv
List of Tables
Table 1: Classification of Bile acids..................................................................................10
Table 2: Human Primer sequences used for q-PCR...........................................................43
Table 3: Antibodies used for immunocytochemistry.........................................................44

v
List of Figures
Figure 1: Stages of liver disease leading to HCC ...............................................................1
Figure 2: Epidemiology of MASLD in global prevalence map...........................................2
Figure 3: Risk factors associated with MASH.....................................................................4
Figure 4: Factors contributing to the progression of MASH...............................................6
Figure 5: Illustration of the bile circulatory pathway ..........................................................8
Figure 6: Bile acid synthesis pathway .................................................................................9
Figure 7: Bile acid composition measurement in serum from LFD+Veh, LFD+Atriol,
GAN+Veh, and GAN+Atriol groups..................................................................21
Figure 8: MTT assay of Huh7 cells treated with different bile acids ................................23
Figure 9: qPCR analysis of FXR, SHP, CYP27A1, CYP8B1, and NTCP after the
treatment with bile acids in Huh7 cells..............................................................26
Figure 10: Seahorse assay analysis of the oxygen consumption rate (OCR), an indicator
of basal and maximal mitochondrial respiration, and ATP production.............27
Figure 11: MMP assay to measure mitochondrial membrane potential (ΔΨm)
following GCA, GCDCA, GDCA, and TDCA treatment of Huh7 cells...........29
Figure 12: qPCR analysis of TGFβ, COL1A1, and ACTA2 after the treatment with
GCA, GCDCA, GDCA, and TDCA in LX2 cells .............................................31
Figure 13: Immunocytochemical analyses of ACTA2 in LX2 cells after treatment
with GCA, GCDCA, GDCA, and TDCA..........................................................32
Figure 14: qPCR analysis of as IL-1β, IL-18, CD68, IL1A, NLRP3, TLR4, MCP1,
TNF-α, and TNF-β after the treatment with GCA, GCDCA, GDCA,
and TDCA in THP-1 cells..............................................................................34
Figure 15: Mitochondrial disruption in hepatocytes and activation of LX2 cells upon
bile acid Upregulation........................................................................................35

vi
Abbreviations
GCA: Glycocholic Acid
GCDCA: Glycochenodeoxycholic Acid
GDCA: Glycodeoxycholic Acid
TDCA: Taurodeoxycholic Acid
MASH: Metabolic-Associated Steatohepatitis
MASLD: Metabolic-Associated Steatotic Liver Disease
HCC: Hepatocellular Carcinoma
CA: Cholic Acid
CDCA: Chenodeoxycholic Acid
HFD: High-Fat Diet
TGF-β: Transforming Growth Factor Beta
COL1A1: Collagen, Type I, Alpha 1
ACAT2: Smooth Muscle Alpha (α)-2 Actin
FXR: Farnesoid X Receptor
SHP: Small Heterodimer Partner
NTCP: Sodium Taurocholate Cotransporting Polypeptide
TNF-α: Tumor Necrosis Factor Alpha
TNF-β: Tumor Necrosis Factor Beta
MCP1: Monocyte Chemoattractant Protein-1
TLR4: Toll-Like Receptor 4
NLRP3: NLR Family Pyrin Domain Containing 3
IL1A: Interleukin 1 Alpha
IL-18: Interleukin 18
TSPO: Translocator Protein

vii
STATEMENT
Most of my thesis work was included in the poster presentation titled “Exploring the Impact of
Bile Acids in Metabolic Dysfunction-Associated Steatohepatitis” at the ENDO 2024 conference
on June 2nd, 2024, in Boston, USA, and in the article “The Mitochondrial TSPO Ligand Atriol
Mitigates Metabolic-Associated Steatohepatitis by Downregulating CXCL1,” published in the
journal Metabolism (https://doi.org/10.1016/j.metabol.2024.155942).

viii
ABSTRACT
Metabolic dysfunction-associated steatohepatitis (MASH) represents the most severe form of
metabolic dysfunction-associated steatotic liver disease (MASLD). Globally, over 115 million
adults are affected by MASH. Despite its prevalence, the causes remain unclear, and treatment
options are limited. Bile acids (BAs), synthesized in the liver, play a crucial role in lipid absorption.
In MASH patients, elevated BA levels are observed in both liver tissue and plasma, suggesting a
potential link to MASH pathogenesis. Our recent in vivo study using a high-fat diet rat model
revealed significant increases in the concentrations of specific BAs, such as glycocholic acid
(GCA), glycochenodeoxycholic acid (GCDCA), glycodeoxycholic acid (GDCA), and
taurodeoxycholic acid (TDCA) in MASH compared to controls, implicating them in disease
development. To explore the mechanistic connection between BA changes and MASH, in vitro
experiments were conducted using LX-2 human hepatic stellate (HSC) and Huh7 human
hepatocellular carcinoma cells. The selected BAs were found to be non-toxic to the cells.
Quantitative polymerase chain reaction (qPCR) analyses revealed upregulation of key fibrotic
genes (TGFβ, COL1A1, ACTA2) in LX-2 cells following exposure to individual BAs.
Immunocytochemistry studies further demonstrated HSC activation through increased expression
of COL1A1 after BA treatment, linking BA changes to fibrogenesis. Additionally, we investigated
the impact of BAs on mitochondrial function using the Seahorse XF Cell Mito Stress Test in Huh7
cells. BA treatment led to reduced oxygen consumption rate and ATP production, along with
impaired mitochondrial membrane potential. These observations suggest that elevated BA levels
disrupt mitochondrial homeostasis, contributing to MASH progression. In summary, our data
provide valuable insights into the complex effects of elevated BAs on MASH pathogenesis,

ix
highlighting connections between BA composition changes, fibrogenesis, and mitochondrial
dysfunction.

1
Chapter 1: INTRODUCTION
Excess fat has always been a concern for both the public and healthcare professionals1
. The number
of people affected by liver diseases is increasing day by day, accounting for millions of deaths
every year, primarily due to cirrhosis and hepatocellular carcinoma (HCC)2
. One of the main
causes of these conditions is fatty liver disease, which can be associated with both non-alcoholic
and alcoholic consumption1,2.
In the early 1980s, non-alcoholic fatty liver disease (NAFLD) was first described3
. This condition
begins with a transition from a normal liver to a fatty liver and can progress to non-alcoholic
steatohepatitis (NASH), a more severe form of NAFLD4
. NASH is characterized by inflammation
and hepatocyte ballooning, without alcohol consumption, and can further progress to fibrosis, this
state has the potential to progress into a more severe and irreversible condition, cirrhosis, and
eventually hepatocellular carcinoma (HCC)5
(Figure 1).
Figure 1: Stages of Liver Disease Leading to HCC (Created with Biorender.com).

2
As research went deeper into the pathophysiology and associated conditions, the terminology
evolved to more accurately reflect the underlying causes. The names were changed to metabolic
dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated
steatohepatitis (MASH) to better encompass the association with conditions like type 2 diabetes
mellitus, obesity, hypertension, metabolic dysfunction, along with hepatic steatosis6
.
1.1 Epidemiology of MASLD
Earlier, the prevalence of fatty liver disease was estimated to be around 25% according to NAFLD
criteria7
. However, recent studies that use the broader MASLD criteria—which include additional
factors—have shown that the prevalence has increased to more than 35%7
.
Figure 2: Epidemiology of MASLD in Global Prevalence Map (from Miao et al., 2024)8
.

3
More than 1.66 billion cases of MASLD were reported in 2017, with a significant upsurge over
the last few decades9
. In 1990, the prevalence of MASLD was 17.6%, which increased to 23.4%
in 2019. The graph indicates its impact: 31.2% in North America, 33.1% in Southeast Asia, 29.7%
in East Asia, 33.8% in South Asia, and 44.4% in Latin America8 (Figure 2). The rate of cases is
notably higher in Latin America and MENA (Middle East and North Africa) compared to AsiaPacific, Western Europe, and East Asia. It was observed that adults with obesity or overweight
demographics were more prone to MASLD. Globally, 50% of people with obesity and 60% of
subjects with type 2 diabetes were seen to have MASLD. Its global impact affects more than 10%
of the population9
. The lack of comprehensive data in some countries is due to insufficient
technology and diagnostic tools, highlighting the necessity for ongoing data collection to obtain a
more precise understanding of the current burden of this disease. This data is crucial for developing
effective strategies to manage and mitigate the disease's impact10.
1.2 Risk Factors
The prevalence of MASLD is significantly influenced by factors such as obesity, type 2 diabetes,
and polycystic ovary syndrome (PCOS)11. In individuals with these conditions, the prevalence of
MASLD is substantially higher, often nearly double that of the general population. Additionally,
recent data indicate that MASLD is more commonly seen in younger populations compared to
older ones and is more prevalent in males than females12. Many studies suggest that patients with
MASLD and NAFLD are not only affected by hepatic problems but also experience adverse effects
on the cardiovascular system and are at increased risk for extrahepatic cancers13.

4
Figure 3: Risk factors associated with MASH (Created with Biorender.com).
Variations in the gut microbiome can affect liver health, as its imbalance, also known as dysbiosis,
can cause increased intestinal permeability14. This, in turn, can lead to fibrosis and inflammation
and is also linked with several other diseases such as type 2 diabetes and obesity, which influence
the progression of liver disease. Lifestyle, genetics, and diet play a major role in the development
of liver disease, lack of physical activity and poor diet can lead to obesity, one of the main risk
factors15. There are several genes associated with MASH that make individuals more prone to the
disease, these genes can also interact with other factors16. This highlights that MASH is a part of
a broader multi-disease system17 (Figure 3).

5
1.3 Pathophysiology
The pathophysiology of MASLD/MASH is very complex due to its association with multiple
factors and its evolving nature, which is not yet completely understood. Regarding genetic factors,
several genes are significantly associated with MASLD18. Patatin-like Phospholipase Domaincontaining 3 (PNPLA3), an enzyme that resembles lipase and aids in the breakdown of
triglycerides in the liver, accumulates fat due to the I148M variant's disruption of the enzyme's
action. Transmembrane 6 Superfamily Member 2 (TM6SF2) is involved in the transport of lipids,
and the E167K variation enhances liver fat storage while decreasing fat release into the
bloodstream, potentially reducing the risk of cardiovascular disease (CVD). Membrane-bound Oacyltransferase Domain-containing 7 (MBOAT7) is involved in remodeling phospholipids, and its
decreased activity is associated with MASLD. GCKR (Glucokinase Regulatory Protein) controls
glucokinase, an enzyme involved in glucose metabolism, and the variant lessens its inhibition,
leading to increased fat production in the liver. These genes contribute to hepatic fat accumulation,
increased inflammation in the liver, elevated lipid levels, and fibrogenesis, all of which can lead
to an increased risk of hepatocellular carcinoma. While other genes may also be involved, their
roles are still under research18–20.
One of the main factors associated with this disease is a diet high in fats (high-fat diet; HFD),
which can cause the accumulation of fat in the liver through various mechanisms. HFD is also
associated with numerous other metabolic issues21. The main sources of these free fatty acids are
diet, circulating fats from the breakdown of body fats, and de novo lipogenesis, which converts
excessive carbohydrates into fats. Several mechanisms are involved in the disposition of fatty acids
in the liver. These fats are primarily stored as lipid droplets or converted into triglycerides through
esterification. Alternatively, they can be packaged into very low-density lipoproteins (VLDLs) for

6
transport out of the liver into the bloodstream or oxidized in the mitochondria for energy
production (beta-oxidation)22. However, when there is excessive fat in the body due to dietary
intake or increased production from insulin resistance or other metabolic reasons, the liver may
become overwhelmed. This leads to the accumulation of fat that cannot be transported out or
oxidized efficiently. This accumulation, along with disturbances in gut microbiota, can trigger
inflammation, and worsening conditions like metabolic dysfunction-associated steatohepatitis
(MASH)21–23.
Figure 4: Factors contributing to the progression of MASH (from Gao et al., 2021)23.

7
Toxic lipids accumulate as lipid droplets, disrupting cellular responses and causing harm to the
liver through oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, and other
mechanisms23,24. Also, there will be excessive reactive oxygen species (ROS) due to disruption,
which can lead to mitochondrial damage, resulting in reduced ATP production and ultimately
causing more inflammation. Additionally, increased ROS have been implicated in the activation
of hepatic stellate cells23. In conclusion, the pathophysiology involves a variety of factors and
comprises a complex interplay of various mechanisms24 (Figure 4).
1.4 BILE
The liver, one of the largest internal organs, is just below the diaphragm in the upper right area of
the abdomen. It performs many functions, but one of its main functions is the production of bile.
Bile, a yellowish-green fluid, is a digestive fluid that plays a crucial role in digestion, absorption,
and excretion and is stored in the gall bladder25. It is produced by hepatocytes, the primary liver
cells. Bile mainly consists of water (approximately 95%) along with bile acids, bile salts, bilirubin,
phospholipids, cholesterol, and electrolytes in smaller percentages26. Cholesterol is directly
secreted into bile by the liver, but some of it is also converted into bile salts, ultimately ending up
in the liver.
Bile is considered to have a high pH and is alkaline in nature, which allows it to neutralize
hydrochloric acid in the stomach. It also contains bile salts, which facilitate the emulsification
process by breaking large fat droplets into many smaller droplets27. This increases the surface area
available to enzymes, thereby enhancing the breakdown of fats and speeding up the digestion
process28.
The bile pathway is as follows: Bile flows out of the liver through the right and left hepatic ducts.
These ducts merge to form the common hepatic duct. The common hepatic duct then joins with

8
the cystic duct, which carries bile stored in the gallbladder, forming the common bile duct. The
common bile duct, which runs behind the superior part of the duodenum and the pancreas,
eventually joins the pancreatic duct. Together, they empty into the hepatopancreatic
ampulla28,29(Figure 5).
Figure 5: Illustration of the Bile Circulatory Pathway (Created with Biorender.com).
1.5 Bile acids
The breakdown of cholesterol in the liver leads to the synthesis of bile acids. Initially, bile acids
were primarily understood to aid in the digestion and absorption of fats and fats soluble vitamins,
and emulsification of fats and lipids30. However, recent studies suggest that bile acids are involved
in various other functions. This synthesis also helps remove excess cholesterol by converting it

9
into bile acids. Bile acid synthesis occurs mainly through two pathways: the classical (neutral)
pathway and the alternative (acidic) pathway. These pathways involve reactions such as
hydroxylation, saturation, and oxidative cleavage31.
Figure 6: Bile acid synthesis pathway (from Li and Chiang, 2014)32.
Bile acids are amphipathic, meaning they have both hydrophilic and hydrophobic faces, which
gives them strong detergent properties. Figure 6 depicts the pathways of BA synthesis. In the
classical pathway, which accounts for 80-90% of bile acid synthesis, CYP27A1 initiates the
process by converting cholesterol into 7 alpha-hydroxycholesterol. This step is crucial as it

10
regulates the entire pathway. The 7 alpha-hydroxycholesterol is then converted to 7α-hydroxy-4-
cholestene-3-one by the enzyme 3β-HSD. This compound, known as C4, is the main building
block for the two primary bile acids: cholic acid (CA) and chenodeoxycholic acid (CDCA)28. In
the classical pathway, the enzyme CYP8B1 adds a hydroxyl group to C4 at position twelve,
initiating a series of reactions that include CYP27A1 cleaving the steroid side chain, resulting in
the production of CA. CYP8B1 controls the ratio of CA to CDCA, while CYP7A1 regulates the
overall rate at which bile acids are generated31,32.
Less than 15% of bile acids are generated through the alternative pathway. Here, the process begins
with CYP27A1 converting cholesterol to 27-hydroxycholesterol and 3-beta-hydroxy cholestenoic
acid. CYP7B1 then forms 3β,7α-dihydroxy-5-cholestenoic acid by hydroxylating 3beta-hydroxy5-cholestenoic acid at the 7th position. Peripheral tissues produce oxysterol intermediates, which
are transported to the liver, where they are primarily converted into CDCA30,32.
Table 1: Classification of Bile acids.
Bile acids
Primary bile acids
Synthesized in liver
Secondary bile acids
Formed in intestine
Classification Free bile acids Conjugated bile acids
Primary bile
acids
Cholic acid Glycocholic acid Taurocholic acid
Chenodeoxycholic
acid
Glycochenodeoxycholic
acid
Taurochenodeoxycholic
acid
Secondary
bile acids
Deoxycholic acid Glycodeoxycholic acid Taurodeoxycholic acid
Lithocholic acid Glycolithocholic acid Taurolithocholic acid
The two primary bile acids are further processed as follows: Cholic acid can be conjugated with
the amino acids glycine and taurine to form glycocholic acid (GCA) and taurocholic acid (TCA),

11
respectively30,33. Similarly, chenodeoxycholic acid can be conjugated with glycine and taurine to
form glyco chenodeoxycholic acid (GCDCA) and Tauro chenodeoxycholic acid (TCDCA) and
this is known as conjugated bile acids (Table 1).
Moreover, bacterial 7a-dehydroxylase in the large intestine removes a hydroxyl group from C-7,
converting CDCA to LCA and CA to DCA. Bacterial 7a-dehydroxylase activity in the colon
converts CDCA and CA to DCA and LCA, respectively. Moreover, CDCA is changed into the
secondary bile acids THCA, TMDCA, THDCA, and TUDCA by CYP3A1 and epimerase32,33
(Figure 6). Following synthesis, BAs are secreted into the duodenum and released into the
gallbladder. The majority return to the liver via the terminal ileum. The remaining substances pass
into the colon, where some are eliminated, and others are reabsorbed into the liver and there are
numerous transporters involved in this enterohepatic circulation of BAs33.
1.6 BAs and MASH
There are a lot of theories associated with the understanding of BA function in MASH but not
completely understood. BAs may have a role in influencing intestinal microbiota on the onset and
advancement of MASLD34. Beyond their roles in digestion and lipid solubilization, BAs are
becoming more interesting as signaling molecules. It is currently unknown if individuals who have
MASLD have a different fecal BA composition than healthy individuals because the issue of BA
metabolism in the context of MASLD has not been well-researched34.
To prevent and/or treat MASLD, BAs have become a promising therapeutic target. In both rodents
and humans with MASLD/MASH, changes have been observed in total BA levels and
composition. It was shown that glycine-conjugated BAs were more prevalent in the livers of rats
fed a HFD than taurine-conjugated BAs35.

12
Since rodents often have larger levels of taurine-conjugated BAs, this shows that the
pathophysiology of NAFLD involves a change in BA conjugation. In humans, a shift in the
composition of BA is also noted36. When human liver samples from MAFLD, MASH, and healthy
livers were compared, CYP8B1 mRNA levels were found to be lower whereas CYP7B1 mRNA
levels were higher in MASH livers. This finding suggests that as patients advance toward MASH,
there may be a shift toward the alternative pathway36.
Theoretically, there is a correlation between abnormal BA production and secretion and the extent
of liver tissue damage. BAs will accumulate if the flow is decreased, and its altered composition
may result in liver damage37.
BAs have been implicated in the progression of illness in several studies. In a MASH rat model
fed a high fat and high cholesterol (HFC) diet, treatment with cholic acid (CA) dose-dependently
exacerbated hepatic steatosis, inflammation, and fibrosis. The CA diet group consistently showed
significantly higher mRNA levels of genes related to fibrogenesis and inflammatory responses
compared to the control group38.
BAs also act as potent inflammagens at pathological concentrations, triggering the release of
proinflammatory cytokines and chemokines from hepatocytes, thereby facilitating the transition
from simple steatosis to MASH38,39. Elevated BA concentrations may contribute to the
pathophysiology of MASH. Normalizing BA metabolism to levels observed in healthy controls is
crucial for therapy39.
A meta-analysis involving 15 BAs found that 9 were elevated in MASLD patients. Among the top
5 elevated BAs—UDCA, TCA, CDCA, TCDCA, and GCA—these were identified as potential
biomarkers significantly increased in MASLD patients compared to healthy individuals35.

13
Another study highlighted hepatic 7α-rehydroxylation of secondary BAs in mice with MASH,
challenging the notion that gut bacteria solely determine the balance between primary and
secondary bile acids40.
Undoubtedly, the development of MASLD and MASH is significantly influenced by BAs. The
exact functions they perform, however, are still unknown despite the research that has been done
so far41. Thus, further research is needed to elucidate how bile acids influence MASH progression,
offering insights crucial for developing effective treatments42.
Several projects in our lab have identified a link between bile acids and the MASH model while
investigating the role of the Translocator protein (TSPO), an outer mitochondrial membrane
protein, also known for its high affinity for cholesterol binding and its involvement in cholesterol
transport and steroidogenesis, as well as the role of 3,17,19-androsten-5-triol (Atriol), a TSPO
ligand known to disrupt cholesterol binding. In a healthy human liver, TSPO expression is
typically low, but it is elevated in condition such as MASLD. So, these studies indicated that Atriol
inhibits TSPO expression, leading to decreased bile acid synthesis through reduced CYP27A1
expression. Additionally, findings show that four bile acids (GCA, GCDCA, GDCA, TDCA) had
elevated concentrations in the GAN diet + Veh group, which significantly decreased after Atriol
administration.
Based on an extensive literature review, this study aims to investigate the specific effects of
elevated bile acids on the progression of Metabolic Dysfunction-Associated Steatohepatitis
(MASH). Our objective is to elucidate how these bile acids contribute to key pathological
processes, including fibrogenesis, mitochondrial dysfunction, and inflammatory responses in liver
cells.

14
Chapter 2: METHODS
2.1 Cell culture and treatment
The Huh-7 cells (hepatocytes) were obtained from the JCRB Cell Bank. The culture media used
for the cells was Dulbecco's modified Eagle medium (DMEM, #11995-075), which was enhanced
with 1% penicillin-streptomycin (#15140-122, Gibco) and 10% heat-inactivated fetal bovine
serum (HI-FBS) (#12306C, Millipore Sigma). The cells were maintained at 37 °C in a 5% CO2
humidified incubator.
Huh7 cells were treated with 200µM glycocholic acid (GCA, #20276, Cayman), 200µM
glycochenodeoxycholic acid (GCDCA, #16942, Cayman), 50µM glycodeoxycholic acid (GDCA,
#20274), and 10µM taurodeoxycholic acid (TDCA, #15935, Cayman) for 24 hours and the control
vehicle was the DMSO treatment.
The human HSC line known as Human LX-2 cells were cultured in DMEM (#11995-064, Gibco)
supplemented with 1% penicillin-streptomycin (#15140-122, Gibco) and 2% FBS (#12306C,
Millipore Sigma) under standard laboratory conditions at 37 °C in a 5% CO2 humidified incubator.
LX-2 cells were starved for 24 hours before being treated with 200µM GCA, 200µM GCDCA,
50µM GDCA, and 10µM TDCA for 24 hours each. The control vehicle was the DMSO treatment.
LX-2 cells were treated to 1 ng/ml TGF-β (#T7039, Millipore Sigma) for immunocytochemistry
to induce fibrosis as a positive control.
Pro-monocytic human THP-1 cells were grown in RPMI 1640 (Roswell Park Memorial
Institute) supplemented with 1% penicillin-streptomycin and 10% FBS. The THP-1 cells were
grown in an incubator with 5% CO2 and humidity at 37°C. For three days, THP-1 cells were

15
incubated with 50 ng/ml of phorbol 12-myristate 13-acetate (PMA) (#5005820001, Millipore
Sigma) to induce macrophage differentiation.
2.2 Seahorse Assay
The Seahorse assay was performed using the Seahorse XF Cell Mito Stress Test Kit from Agilent
(#103015-100, Agilent) in combination with the Seahorse XFe96 Analyzer to quantify the oxygen
consumption rate (OCR). HuH7 cells were firstly seeded at a density of 10,000 cells per well in
Seahorse XF Cell Culture Microplates (#101085-004, Agilent) overnight, followed by a 24-hour
treatment period with bile acids (GDCA 50 μM, TDCA 10 μM, GCA 200 μM, GCDCA 200 μM)
along with the vehicle.
The Seahorse XFe96 Analyzer needs to be warmed up one night before use. Additionally, one of
the important components, the XF sensor cartridge, needs to be kept hydrated with molecular grade
water overnight in a non-CO2, 37°C incubator, along with 10-15 ml of Seahorse XF calibrant. On
the next day, the molecular grade water was replaced with 200 μl of calibrant in the cartridge, and
the cell media was replaced with Seahorse XF DMEM medium (#103575-100, Agilent)
supplemented with 1 mM Pyruvate (#103578-100, Agilent), 2 mM glutamine (#103579-100,
Agilent), and 10 mM glucose (#103577-100, Agilent), and incubated for approximately 1 hour in
a 37°C non-CO2 incubator. Then, a hydrated sensor cartridge was loaded with a prepared working
solution of Oligomycin (2.5 μM) (#103015-100, Agilent), FCCP (2 μM) (#103015-100, Agilent),
and Rotenone (Rot/Antimycin) (0.5 μM) (#103015-100, Agilent).
The Seahorse assay was then performed on the Seahorse XFe96 Analyzer using the experimental
template designed in Wave 2.6.1 connected with Cytation5 for cell counting. The Bradford assay
(#E530, VWR) was used to determine OCR data for normalization with the protein amount per
well by using Bradford reagent (E530-1L), 0.5 mg/ml BSA, NaOH, 0.15 M NaCl followed by

16
measuring absorbance at 595 nm, and finally, the acquired results were analyzed using GraphPad
Prism 5.9.1 software.
2.3 MTT Assay
HuH7 cells were seeded in 96-well plates at a density of 10,000 cells per well and incubated
overnight until reaching approximately 85-90% confluence. Subsequently, cells were treated
with different concentrations of each bile acid to assess cell viability using the MTT (3-(4,5-
dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) (Roche, #11465007001) colorimetric
assay. Specifically, cells were treated with TDCA at concentrations of 10, 25, 50, and 75 μM;
GDCA at concentrations of 25, 50, 75, and 100 μM; GCA at concentrations of 50, 100, 150, 200,
and 250 μM; and GCDCA at concentrations of 50, 100, 150, 200, and 250 μM for 24 hours.
Following treatment, 10 μl of MTT reagent (0.5 mg/ml) was added to each well and incubated for
4 hours at 37°C. Subsequently, a solubilization buffer was added to dissolve the resulting formazan
crystals, and the plate was kept overnight in a 7% CO2 incubator at 37°C. Absorbance was
measured at 595 nm using a multimode plate reader (PerkinElmer VICTOR X5) and final data was
analyzed using Microsoft Excel and GraphPad Prism 5.9.1 software.
2.4 Immunocytochemistry
LX2 cells were seeded at a density of 0.1 million cells per milliliter in sterilized 12-well cell culture
plates on sterile glass coverslips and incubated overnight until reaching 80% confluency.
Subsequently, the cells were starved for the next 24 hours. On day 3, the cells were treated with
four different bile acids (GDCA 50 μM, TDCA 10 μM, GCA 200 μM, and GCDCA 200 μM),
while one well served as a vehicle control and TGF-beta was used as a positive control.

17
On day 4, the old media was aspirated, and the cells were washed once with PBS before fixation
with 4%v/v paraformaldehyde for 10 minutes at room temperature. Following fixation, the cells
were washed three times with PBS for 1 minute each. Subsequently, the cells were permeabilized
with 0.1% Triton X-100 diluted in PBS for 15 minutes at room temperature, followed by another
three washes with PBS. Blocking was then performed using a solution containing 5% donkey
serum (2 ml donkey serum, Sigma, #D9663, 0.1 g BSA, Equitech-Bio, #BAH65, and 17.9 ml
PBS). After additional PBS washing, the cells were incubated overnight at 4°C with a primary
antibody Collagen, type I, alpha I COL1A1 (Cell Signaling, E8F4L, Rabbit mAb #72026, 1:400
dilution in donkey serum).
The following day, the cells were washed three times with PBS and then incubated with a
secondary antibody, Alexa Fluor™ 568 donkey anti-rabbit IgG (H+L) (Thermo Fisher Scientific,
#A10042, 1:400 dilution in donkey serum), for 30 minutes at room temperature in the dark area.
After the final three washes with PBS, a drop of DAPI (4′,6-diamidino-2-phenylindole) (Vector
Laboratories, #H-1800) was added to the slides. Each coverslip was then picked up with forceps,
and the cells were placed facing down onto the DAPI. The slides were stored at -20°C before
visualization of the LX2 cells using a 63x magnification with an Olympus microscope.
2.5 Mitochondrial Membrane Potential
To assess any changes in mitochondrial membrane potential in response to treatment, we
conducted assays using the JC-10 Mitochondrial Membrane Potential Assay Kit (#ab112134,
Abcam). HuH7 cells were cultured in a sterilized 96-well cell culture plate at a density of 10,000
cells per well to ensure proper growth overnight.
The following day, the old media was aspirated and replaced with fresh media containing bile acid
treatments (GDCA 50 μM, TDCA 10 μM, GCA 200 μM, and GCDCA 200 μM), with one row

18
designated as a vehicle control. Subsequently, the cells were incubated for an additional 24 hours
to allow for optimal treatment effects.
On day 3, all kit components were thawed completely at room temperature. A mixture of lipophilic
100 X JC-10 dye in DMSO (#1050568) and Assay Buffer A (#1050568-1) was prepared.
Subsequently, 50 μL of this mixture was added per well, and the cells were incubated for
approximately 1 hour to facilitate dye uptake into the mitochondria of cells.
Following the incubation period, Assay Buffer B (#1050568-1) was added 50ul to each well and
kept at room temperature for 5 minutes, and then fluorescence intensity was monitored using a
BioTek Synergy H1 Multimode Reader (Agilent), with consideration of the red-green ratio.
Finally, images were captured using an Olympus microscope.
2.6 RNA Extraction and qPCR
Initially, cells were seeded at specific densities according to the respective cell types (Huh7, LX2,
THP-1) and incubated for 24 hours until reaching 80% confluence. On day 2, LX2 cells were
subjected to a 24-hour starvation period, while THP-1 cells underwent differentiation using PMA
(phorbol 12-myristate 13-acetate) (#5005820001, Millipore Sigma) for 24 hours or longer if
necessary, depending on their condition. In contrast, Huh7 cells did not undergo any specific
treatment. Subsequently, the cells were treated with different bile acid concentrations (GDCA 50
μM, TDCA 10 μM, GCA 200 μM, and GCDCA 200 μM), including a vehicle control, and
incubated overnight to optimize the treatment effects. Total RNA extraction was performed using
the RNAqueous-Micro Kit (Invitrogen by Thermo Fisher Scientific, #AM1931).
Lysates have been prepared by adding 100-150 μl of lysis buffer to each well, followed by the
addition of 50-75 μl of 90-100% ethanol by thoroughly mixing it through pipetting. The

19
lysate/ethanol mixture (up to 150 μl) was transferred onto a Microfilter Cartridge Assembly and
centrifuged at 15,000 rpm for 10 seconds to 1 minute until all the mixture passed through the filter.
The flow-through was discarded, and the collection tube was reused until last step. Ethanol was
added to Wash Solution 1 and Wash Solution 2/3 to prepare working solutions, and 180 μl of the
prepared working solution of Wash Solution 1 was added to the filters, followed by centrifugation
for 10-15 seconds at maximum rpm to pass the solution through. Afterward, 180 μl of Wash
Solution 2/3 was added to the filter, followed by centrifugation for 10-15 seconds at maximum
rpm. This step was repeated to ensure thorough washing, with the flow-through being discarded
both between steps and at the end for optimal cleanliness. The cartridge assembly was then
centrifuged for 1 minute without the addition of any solution to remove traces of previously used
solutions.
The filter cartridge was transferred to a new collection tube, and 20 μl of RNase-free dH2O
(#SD2192, Takara) preheated to 70-75°C was applied exactly at the center of the column, followed
by centrifugation for 1 minute at maximum speed. Finally, RNA concentration was measured using
the Nanodrop One equipment (Thermo Fisher Scientific) with RNase-free dH2O as a blank.
Reverse transcription was done with the PrimeScript RT reagent kit (#RR037A, Takara, USA).
Using 100 nM forward and reverse primers from Integrated DNA Technologies, 384-well plates
were used for qPCR amplification using SYBR Green Real-Time PCR Master Mixes (#A25742,
Thermo Fisher Scientific, USA). Primers were generated using the NCBI Primer Blast program,
with primer pairs that must span exon-exon junctions given preference. A Bio-Rad CFX384 Touch
Real-Time PCR Detection System was used to test the plates.

20
2.7 Statistical Analysis
The data was analyzed using GraphPad Prism 9.5.1 software. Analysis was done with a student's
t-test between two comparisons or one-way ANOVA for multiple comparisons. A p-value less
than 0.05 was considered statistically significant.

21
Chapter 3: RESULTS
3.1 Serum BA Profiling in a MASH Rat Model
Our laboratory performed an in vivo test to develop the MASH phenotype in male WT SD rats.
The rats were fed a Gubra-Amylin MASH (GAN) diet for 43 weeks, with a low-fat diet serving as
the control. In the last two weeks of the trial, the rats received daily intraperitoneal injections of
either a DMSO-PBS solution as the vehicle control (Veh) or Atriol (20 mg/kg) in DMSO-PBS.
This protocol produced four groups (n=10): LFD+Veh, LFD+Atriol, GAN+Veh, and
GAN+Atriol. From that study, the composition of serum bile acids was analyzed using LCMS/MS. Rat serum was collected with BD Vacutainer tubes and sent to Creative Proteomics for
quantification of bile acid levels. The results showed that the GAN+Veh group had higher-thanaverage concentrations of taurodeoxycholic acid (TDCA), glycocholic acid (GCA),
glycochenodeoxycholic acid (GCDCA), and glycodeoxycholic acid (GDCA), all of which were
dramatically reduced after receiving Atriol treatment (Figure 7).

22
Figure 7: BA composition measurement in serum from LFD+Veh, LFD+Atriol, GAN+Veh, and
GAN+Atriol groups. GCA, glycocholic acid; GCDCA, glycochenodeoxycholic acid; GDCA,
glycodeoxycholic acid; TDCA, Tauro deoxycholic acid. Data are expressed as mean ± SEM,
*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 by Student’s t-test.
This experiment sparked our interest in delving deeper into the role of these bile acids.
Additionally, several studies have shown a correlation between these bile acids and fibrosis, as
GCA and GCDCA, which are highly abundant glycoconjugate primary bile acids, have the highest
correlation with fibrosis. In animal models, the administration of TDCA and GDCA directly
activated hepatic stellate cells (HSCs) and enhanced liver fibrogenesis.
3.2 MTT Cell Viability Test Validation of BA Concentrations for Further In Vitro Studies
After reviewing the literature, the ideal doses for GCA, GCDCA, GDCA, and TDCA were
determined to be 200µM, 200 µM, 50 µM, and 10 µM, respectively. We used the 3-(4,5-
dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) test to examine cell viability
to make sure these concentrations were safe and appropriate for use in later studies along with few
other concentrations as well. This assay is a common technique for assessing cytotoxicity by
monitoring cell metabolism. The concept is that mitochondrial dehydrogenases in living cells
convert the yellow tetrazole MTT to formazan, which gives the substance a purple color. Our
goal was to verify that the selected concentrations had no harmful effects on the cells, approving
their usage in additional experiments. Other than glycochenodeoxycholic acid (GCDCA), our data
showed no significant differences in cell viability between the BA-treated groups and the negative
control. The observation that the other BAs did not show toxicity can be explained by the various
biochemical characteristics and cellular interactions of BAs. Compared to other BAs, GCDCA has

23
been recognized for having a higher hydrophobicity, which can cause more membrane disruption
and cellular stress and could potentially cause toxicity in Huh7 cells.
Figure 8: MTT assay of Huh7 cells treated with different bile acids GCA (200µM), GCDCA
(200µM), GDCA (50µM), and TDCA (10µM) for 24 hours as indicated to assess the viability.
Data are expressed as mean ± SEM, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001 by
Student’s t-test.

24
However, there is insufficient variation in cell viability—less than 10%—to cause significant
alarm. This shows that, in some cases, a proliferative response may occur in a subgroup of cells,
compensating any toxic effects. Other BAs such taurodeoxycholic acid (TDCA), glycocholic
acid (GCA), and glycodeoxycholic acid (GDCA) showed no or little effects (Figure 8). As such,
all of them continue to be interesting research objectives. Under the given concentrations, the
MTT assay results allow for the continuation of study with these bile acids as long as the toxicity
stays within acceptable limits.
3.3 Gene Expression Changes Induced by BAs in Huh7 Cells
We performed qPCR analysis on Huh7 cells to examine the expression of important genes,
including FXR, SHP, CYP27A1, CYP8B1, and NTCP, after monitoring the impact of BAs on cell
survival (Figure 9). The goal of this experiment is to better understand the molecular mechanisms
that explain the BA toxicity.
The nuclear hormone receptor superfamily includes the bile acid receptor farnesoid X receptor
(FXR, NR1H4), which is abundantly expressed in the intestines and liver. According to recent
research, FXR regulates inflammation, lipid and glucose metabolism, and bile acid equilibrium
enterohepatically. As a result, FXR has been identified as a promising therapeutic target for
conditions such as type 2 diabetes mellitus, liver fibrosis, and primary biliary cholangitis. In our
results, we observed a significant decrease in FXR in all bile acids except GDCA compared to
vehicle. This decrease in activity can lead to disturbances in bile acid metabolism and synthesis.
A small heterodimer partner (SHP) is an orphan nuclear receptor that controls a variety of liver
functions, including lipid homeostasis, immunological responses, BA, and glucose. It is directly
influenced by FXR. While FXR showed decreased, SHP expression increased in response to

25
elevated BA levels. This could be an attempt by the liver cells to counteract the excessive BAs,
which may indicate a disturbed environment in MASH.
CYP8B1 is a crucial enzyme for the synthesis of cholic acid (CA), while CYP27A1 is essential as
it initiates the alternative pathway for BA production. A significant decrease in the expression of
both of these genes indicates a disturbance in the system, as the liver will not be able to metabolize
cholesterol effectively. This can lead to lipid accumulation and overall liver dysfunction.
The multipass transmembrane protein known as sodium+/taurocholate cotransporting polypeptide
(NTCP) is expressed mostly on the sinusoidal membranes of hepatocytes. About 90% of the
absorption of BA is attributed to NTCP. Hepatocytes absorb BAs by means of the NTCP. Our
results show there is no significant change in the transcript of this transporter, which suggests the
BA disturbance may not be related to NTCP-regulated uptake by hepatocytes. Additional
measurement of NTCP protein levels in Huh7 cells could strengthen this conclusion.
In the metabolism of bile acids, the genes FRX, SHP, CYP8B1, CYP27A1, and NTCP are
essential. The production and homeostasis of bile acids are largely regulated by FRX and SHP.
Bile acids are made from cholesterol by enzymatic mechanisms that involve CYP8B1 and
CYP27A1 and NTCP promotes the transport of bile acids into liver cells. The qPCR data show no
significant change in NTCP, but a rise in SHP expression and a decrease in FRX, CYP27A1, and
CYP8B1 expression. This indicates a shift in bile acid metabolism, with decreased production and
altered regulatory feedback, but bile acid transport remains unaffected.

26
Figure 9: qPCR analysis of FXR, SHP, CYP27A1, CYP8B1, NTCP after the treatment with
GCA, GCDCA, GDCA, and TDCA in Huh7 cells. Data are expressed as mean ± SEM, *p<0.05,
**p<0.01, ***p<0.001, ****p<0.0001 by Student’s t-test.
3.4 Mitochondrial Stress Test Reveals Impaired Function with Bile Acid Exposure
To further understand the impact of these bile acids on cellular function, more specifically
mitochondrial function, we conducted the Seahorse XF Cell Mito Stress Test to evaluate the
oxygen consumption rate of cells, the technique that uses live cells on plates and monitors OCR.
This test measures key parameters of mitochondrial function, including basal respiration (oxygen
consumption to meet ATP needs), ATP production (energy used by mitochondria to produce ATP),
and maximal respiration (the cell's respiratory chain working at maximum capacity). These

27
measurements involve the addition of Oligomycin, Carbonyl cyanide-4 (trifluoromethoxy)
phenylhydrazone (FCCP), Rotenone, and Antimycin. Our Seahorse XF Cell Mito Stress Test
results clearly showed that bile acid treatment significantly impacts mitochondrial function (Figure
10).
Figure 10. The top panel shows Seahorse assay analysis of the oxygen consumption rate (OCR),
while the bottom panel shows an indicator of basal and maximal mitochondrial respiration, and
ATP production. Data are expressed as mean ± SEM, *p<0.05, **p<0.01 by Student’s t-test.
All measured parameters—basal respiration, ATP production, and maximal respiration—were
significantly decreased in cells treated with bile acids GDCA, GCA, TDCA, and GCDCA
compared to the vehicle control. This indicates a reduction in mitochondrial activity under basal
conditions, compromised energy production ability, and a decreased capacity for enhanced
respiration. Overall, these results suggest that mitochondrial function is negatively impacted,
potentially affecting overall cellular energy metabolism.

28
To further understand these results, we performed a mitochondrial membrane potential (MMP)
assay to assess mitochondrial health more comprehensively.
3.5 Mitochondrial Membrane Potential Disruption by Bile acids
A crucial parameter for assessing mitochondrial function is the mitochondrial membrane potential
(MMP), which is generated by an electrochemical gradient that can also enhance ATP production.
Following Seahorse assay data collection, we conducted a mitochondrial membrane potential
assay to specifically investigate mitochondrial health in liver cells. We performed this assay using
JC-10 dye as it is more suitable because of its better water solubility and treated Huh7 cells with
4 BAs TDCA, GDCA, GCA, and GCDCA respectively. JC-10, a lipophilic dye, readily enters
mitochondria, undergoing a color change from green to greenish orange based on membrane
potential. Normally, in healthy cells, this dye forms orange aggregates in the mitochondrial matrix,
indicating high polarization. In contrast, in damaged or disrupted cells, JC-10 leaks from
mitochondria, converting to a monomeric form and resulting in green fluorescence, indicative of
depolarization. Our results demonstrate that cells treated with BAs exhibit reduced polarization
compared to the vehicle control. We observed a significant decrease in membrane potential,
confirmed by monitoring fluorescent intensities and calculating red/green ratios from the data
(Figure 11). Additionally, fluorescence microscopy revealed higher red fluorescence in vehicles,
suggesting a healthy, high MMP. Conversely, BA-treated cells showed diminished red signals,
indicating MMP loss and compromised mitochondrial function.

29
Figure 11. The top panel shows mitochondrial membrane potential (ΔΨm) following GCA
(200µM), GCDCA (200µM), GDCA (50µM), and TDCA (10µM) treatment of Huh7 cells
detected by fluorescence. Orange fluorescence represents the mitochondrial aggregate JC10, and
green fluorescence indicates the monomeric JC10, while the bottom panel shows quantitative
analysis through red/green ratio. Data are expressed as mean ± SEM, **p<0.01, ***p<0.001,
****p<0.0001 by Student’s t-test.

30
3.6 Gene Expression Profiling of BA-treated LX2 Cells
After initially focusing on HuH7 cells, we shifted our attention to LX2 cells, the human hepatic
stellate cells that can be activated in response to liver damage to a smooth muscle-like cell type
producing extracellular matrix proteins contributing to fibrosis formation. By including LX2 cells
in our study, we aimed to gain a more detailed view of how BAs affect the liver system. We began
by performing qPCR on LX2 cells to examine the expression of key genes, including TGF-β,
COL1A1, and ACTA2 (Figure 12). We tested these genes with individual BAs, specifically GDCA,
TDCA, GCDCA, and GCA.
We focused on these genes because they are known to play a crucial role in the progression of
MAFLD. Our results showed considerable upregulation of TGF-β (Transforming Growth Factor
Beta), known as a significant inflammation marker, in response to all tested BAs, indicating an
increased fibrogenetic response and activation of hepatic stellate cells (HSCs). COL1A1 (Collagen
Type I Alpha 1), a gene encoding a major component of the extracellular matrix and closely
associated with fibrosis was significantly upregulated in response to all Bas, suggesting increased
collagen production, which is directly linked to the fibrotic process. ACTA2 (Smooth Muscle
Alpha (α)-2 Actin) is responsible for the contractility of HSCs and is expressed when they are
activated. The upregulation of ACTA2 in all BA treatments indicate HSC activation and fiber
elongation.
Overall, our findings highlight the significant impact of BAs on the activation of HSCs and the
progression of fibrosis in the liver, leading to MASH.

31
Figure 12: qPCR analysis of TGFβ, COL1A1, and ACTA2 after the treatment with GCA,
GCDCA, GDCA, and TDCA in LX2 cells. Data are expressed as mean ± SEM, *p<0.05,
**p<0.01, ***p<0.001, ****p<0.0001 by Student’s t-test.

32
3.7 Visualization of Fibrogenic Responses in LX2 Cells Treated with BAs
To visually confirm the activation of HSCs, we performed immunocytochemistry on LX2 cells
using TGF-β as a positive control, along with four BAs: TDCA, GDCA, GCA, and GCDCA. TGFβ was chosen as it is a well-known inducer of fibrosis to provide a baseline for comparison with
negative controls and treatments, ensuring that the assay is working efficiently. The blue stained
nuclei are because of DAPI staining which binds to DNA and allows visualization of the nuclei
(Figure 13).
Our positive control results validated the functionality of the assay kit and confirmed collagen
production, visualized by distinct red fluorescence indicating fiber formation. Similarly, BAs
exhibited increased expression of COL1A1, as evidenced by intense red staining indicative of
fibrogenetic response and alterations in the extracellular matrix compared to controls.
Figure 13: Immunocytochemical analyses of ACTA2 in LX2 cells after treatment with GCA,
GCDCA, GDCA, and TDCA. TGF-β is a positive control. Red color indicates ACTA2 positive
signal. Scale bar:10µm.

33
3.8 Investigating BA Effects on Macrophage Activation: THP-1 Cells qPCR
After using hepatocytes and stellate cells, we tested the effects of BAs on THP-1 cells, a monocytic
human leukemia cell line that, when stimulated, differentiates into macrophage-like cells. We used
THP-1 cells as a model for Kupffer cells, the hepatic macrophages, to determine if BAs affect
macrophages, potentially influencing the inflammatory response. These changes were evaluated
by treating post-differentiation cells, using qPCR.
We began by performing qPCR on THP-1 cells to examine the expression of key genes, including
pro-inflammatory and anti-inflammatory markers such as IL-1β, IL-18, CD68, IL1A, NLRP3,
TLR4, MCP1, TNF-α, and TNF-β. An inflammatory reaction is characterized by an inflammatory
response mediated by these markers. CD68 and MCP1 are involved in macrophage infiltration,
NLRP3 is essential for inflammasome activation, TLR4 responds to gut-derived endotoxins, and
TNF-α, TNF-β, IL-1β, IL-18, and IL1A are pro-inflammatory cytokines that mediate inflammation
and immune response. Therefore, we tested these genes with individual BAs, specifically GDCA,
TDCA, GCDCA, and GCA (Figure 14). However, the data showed no statistically significant
variation in the expression of these genes. The absence of significant data could be due to several
factors. It is possible that macrophage activation and the associated pathways do not correlate with
the effects of the specific BAs used, meaning the BAs were not sufficient to activate these
pathways. Additionally, there could be any other possible mechanism that cannot be captured
through the help of qPCR. These particular BAs may not influence these inflammatory markers in
THP-1 cells, or their effects might require different conditions or complementary assays to be
observed.

34
Figure 14: qPCR analysis of as IL-1β, IL-18, CD68, IL1A, NLRP3, TLR4, MCP1, TNF-α, and
TNF-β after the treatment with GCA, GCDCA, GDCA, and TDCA in THP-1 cells. Data are
expressed as mean ± SEM, *p<0.05, **p<0.01 by Student’s t-test.

35
Chapter 4: DISCUSSION
Figure 15: Mitochondrial Disruption in Hepatocytes and Activation of LX2 Cells upon Bile Acid
Upregulation (Created with Biorender.com)
The current studies are the continuation of in vivo studies which demonstrated elevated levels of
four BAs GDCA, GCDCA, TDCA and GCA in HFD animal models. Recent studies have
highlighted the significant role of conjugated secondary bile acids, particularly TDCA and GDCA,
in liver fibrogenesis, particularly through TGR5-mediated pathways43. Also, among various bile
acids, the glyco-conjugated forms of cholic acid (CA) and chenodeoxycholic acid (CDCA) were
found to have the strongest association with liver fibrosis44. After recognizing the potential impacts
of these findings, we reviewed few existing literatures and finalized specific bile acid
concentrations for our further studies. Our study aimed to investigate the effects of these BAs on
numerous cellular activities, as well as their possible significance in the evolution of MASH.

36
Focusing on Huh7 cells, we used an MTT assay to make sure the BA concentrations we had chosen
were safe. The results verified that the chosen concentrations were non-toxic, allowing us to move
further with the tests. We then performed qPCR analysis to look at the expression of genes
associated in MASH progression. The qPCR results revealed significant alterations in the
expression of crucial genes such as FXR, SHP, CYP27A1, CYP8B1 and NTCP, suggesting that
bile acids (BAs) play a role in the development of the disease. This finding aligns with literature
indicating that mice with MASH exhibit a significant decrease in total BAs in portal blood, which
leads to reduced activation of FXR. Additionally, CYP8B1 expression was downregulated in mice
with less pronounced insulin resistance, further supporting our results41.
To better understand the effect of BAs on mitochondrial function and health, we used the Seahorse
XF Cell Mito Stress Test. Important aspects of mitochondrial function, including maximal
respiration, ATP synthesis, and basal respiration, are measured by this test and reductions in all
measured parameters as compared to vehicle controls demonstrated our finding that BA
administration does impact mitochondrial activity. Mitochondrial membrane potential (MMP)
studies further supported this disruption, as hepatocytes treated with BAs exhibited a shift in
fluorescence from red to green due to JC-10 staining, indicating mitochondrial depolarization and
disturbed mitochondrial health. These findings are also consistent with studies showing that
hydrophobic BA accumulation can harm mitochondria, disrupt the cell membranes, and enhance
the formation of reactive oxygen species (ROS) in hepatocytes45.
We then focused on LX2 cells, a hepatic stellate cell line, as they get activated in response to liver
injury and are essential for the progression to hepatic fibrosis. We used qPCR to measure the
expression of fibrogenic markers in LX2 cells, including TGF-β, COL1A1, and ACTA2. According
to our results, BAs significantly increased the expression of these markers, suggesting that BAs

37
stimulate fibrogenesis and HSC activation. These results were further supported by
immunocytochemistry, which showed that cells treated with BA had increased COL1A1 compared
to vehicle control.
We used THP-1 cells, a monocytic human leukemia cell line that can develop into macrophagelike cells under stimulation, to investigate the possible interaction between BAs and macrophages.
Using qPCR, we investigated the expression of pro- and anti-inflammatory markers. However, the
results did not reveal statistically significant differences in gene expression in response to bile acid
treatment. This suggests that macrophages may not be as directly affected by bile acids as
hepatocytes and stellate cells are.
In summary, our results provide a comprehensive understanding of how BAs can influence the
development or progression of MASH. This research contributes to the broader biological context
by highlighting the role of bile acids in fibrosis and mitochondrial dysfunction and suggests
possible directions for therapeutic strategies in metabolic liver diseases.

38
Chapter 5: CONCLUSION
In conclusion, our study shows that elevated BA levels activate hepatic stellate cells (HSCs), as
evidenced by qPCR and immunocytochemistry. Additionally, hepatocytes treated with high levels
of BAs exhibit disrupted mitochondrial function and altered mitochondrial membrane potential, as
evidenced by Seahorse and MMP assays. These findings highlight the significant impact of BA
accumulation on fibrogenesis and mitochondrial dysfunction in HSCs and hepatocytes.
These findings underscore the significance of maintaining BA homeostasis and suggest that
investigating BA pathways could provide valuable insights into understanding and treating
conditions like MASH and other liver-related disorders marked by BA dysregulation. Future
research should delve into the molecular mechanisms behind BA-induced cellular dysfunctions
and explore novel therapies aimed at mitigating these effects, thereby enhancing prevention and
treatment strategies for liver diseases.

39
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43
Table 2: Human Primer sequences used for q-PCR.
GENE FORWARD REVERSE
FXR TGTGAGGGGTGTAAAGGTTTCT GCCAACATTCCCATCTCTTTGC
SHP CCTCTTCAACCCCGATGTGC GCTGGTCGGAATGGACTTGA
CYP27A1 GGCAACGGAGCTTAGAGGAG TGGCCTTGTAAAGCACCTGT
CYP8B1 CCACTACCCCATGTTGACCC CTGTAGGATGCAGGCGGTAG
NTCP GCGCTATGTCATCAAGGGAG GGCAGAGAGAACTGTGACGG
IL1A GCGTTTGAGTCAGCAAAGAAGT CATGGAGTGGGCCATAGCTT
MCP1 CTCGCTCAGCCAGATGCAAT TTGGGTTTGCTTGTCCAGGT
TNF-β TTCTCTCCTAGGCCTCAGCC GTCATGGGGAGAACCTGCTG
TGF-β TTCCCTCGAGGCCCTCCTA GCCGCAGCTTGGACAGGATC
COL1A1 GCTCGTGGAAATGATGGTGC ACCCTGGGGACCTTCAGAG
ACTA2 TATCCCCGGGACTAAGACGG CACCATCACCCCCTGATGTC
IL1β CCAAACCTCTTCGAGGCACA GCTGCTTCAGACACTTGAGC
IL18 TGCAGTCTACACAGCTTCGG GCAGCCATCTTTATTCCTGCG
NLRP3 CTGGCATCTGGGGAAACCT AGCCCTTCTGGGGAGGATAG
CD68 TAGCTGGACTTTGGGTGAGG CCAGTGCTCTCTGCCAGT
TLR4 CCGTTTTATCACGGAGGTGG GAGAGGTGGCTTAGGCTCTG
TNF-α CCCAGGCAGTCAGATCAT TCAGCTCCACGCCATT

44
Table 3: Antibodies used for immunocytochemistry.
Antibody Supplier Reference Dilution
Primary
COL1A1
Cell Signaling #72026, AB_2904565 1:400
Secondary
Anti-Rabbit IgG (H+L)
Alexa Fluor™ 568
ThermoFisher #A10042 1:400

Abstract (if available)

Abstract Metabolic dysfunction-associated steatohepatitis (MASH) represents the most severe form of metabolic dysfunction-associated steatotic liver disease (MASLD). Globally, over 115 million adults are affected by MASH. Despite its prevalence, the causes remain unclear, and treatment options are limited. Bile acids (BAs), synthesized in the liver, play a crucial role in lipid absorption. In MASH patients, elevated BA levels are observed in both liver tissue and plasma, suggesting a potential link to MASH pathogenesis. Our recent in vivo study using a high-fat diet rat model revealed significant increases in the concentrations of specific BAs, such as glycocholic acid (GCA), glycochenodeoxycholic acid (GCDCA), glycodeoxycholic acid (GDCA), and taurodeoxycholic acid (TDCA) in MASH compared to controls, implicating them in disease development. To explore the mechanistic connection between BA changes and MASH, in vitro experiments were conducted using LX-2 human hepatic stellate (HSC) and Huh7 human hepatocellular carcinoma cells. The selected BAs were found to be non-toxic to the cells. Quantitative polymerase chain reaction (qPCR) analyses revealed upregulation of key fibrotic genes (TGFβ, COL1A1, ACTA2) in LX-2 cells following exposure to individual BAs. Immunocytochemistry studies further demonstrated HSC activation through increased expression of COL1A1 after BA treatment, linking BA changes to fibrogenesis. Additionally, we investigated the impact of BAs on mitochondrial function using the Seahorse XF Cell Mito Stress Test in Huh7 cells. BA treatment led to reduced oxygen consumption rate and ATP production, along with impaired mitochondrial membrane potential. These observations suggest that elevated BA levels disrupt mitochondrial homeostasis, contributing to MASH progression. In summary, our data provide valuable insights into the complex effects of elevated BAs on MASH pathogenesis, highlighting connections between BA composition changes, fibrogenesis, and mitochondrial dysfunction.

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Asset Metadata

Creator Patel, Nrupa Dinesh (author)

Core Title Exploring the impact of elevated bile acids in metabolic dysfunction- associated steatotic liver disease in vitro

School School of Pharmacy

Degree Master of Science

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2024-08

Publication Date 07/31/2024

Defense Date 07/30/2024

Publisher Los Angeles, California (original), University of Southern California (original), University of Southern California. Libraries (digital)

Tag bile acid signaling,bile acids,liver fibrosis,liver metabolism,MASH (metabolic dysfunction-associated steatohepatitis),metabolic dysfunction,OAI-PMH Harvest,steatotic liver disease

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Language English

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Advisor Papadopoulos, Vassilios (committee chair), Culty, Martine (committee member), Stiles, Bangyan (committee member)

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