University of Southern California Dissertations and Theses

Transcriptional regulation of lipid metabolism and exploring the specific roles of AKT isoforms

(USC Thesis Other)

Transcriptional regulation of lipid metabolism and exploring the specific roles of AKT isoforms

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content

Transcriptional Regulation of Lipid Metabolism and Exploring the Specific Roles of AKT
Isoforms
By
Aditi Ashish Datta

A Thesis Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfilment of the
Requirements for the Degree
MASTER OF SCIENCE
(MOLECULAR PHARMACOLOGY AND TOXICOLOGY)
August 2023
ii

Table of Contents
List of tables ............................................................................................................................. iii
List of figures ............................................................................................................................ iv
Acknowledgements .................................................................................................................... v
Abstract ..................................................................................................................................... vi
Chapter I- Introduction .............................................................................................................. 1
Chapter II- Materials and Methods .......................................................................................... 17
Chapter III- Results .................................................................................................................. 26
Chapter IV- Discussion ............................................................................................................ 43
Chapter V- Troubleshooting .................................................................................................... 48
Chapter VI- Bibliography ........................................................................................................ 50

iii

List of tables
Table 1- List of primers of RT-qPCR ...................................................................................... 23
Table 3- Quantification of Plasmid DNA Concentration Post-Midiprep ................................ 28
Table 2- Quantification of Plasmid DNA Concentration Post-Miniprep ................................ 28

iv

List of figures
Figure 1- Overview of workflow of experiment to validate that ERRα transcriptionally
regulates GPAT4.. .............................................................................................................................. 25
Figure 2- Schematic representation of the GPAT4 promoter plasmid. ....................................... 27
Figure 3: Comprehensive Analysis of GPAT4 Promoter Plasmid Preparation and
Digestion….. ....................................................................................................................................... 30
Figure 4: Evaluating the Role of ERRα in transcriptionally regulating GPAT4 Activity. ....... 34
Figure 5: RT-qPCR data for showing ERRα expression in hepatocytes; ................................... 35
Figure 6 – RT-qPCR data for showing MCAD expression in hepatocytes ................................ 36
Figure 7: RT-qPCR data for showing CYC expression in hepatocytes. ..................................... 37
Figure 8: RT-qPCR data for showing FASN expression in hepatocytes. ................................... 38
Figure 9: RT-qPCR data for showing ACC expression in hepatocytes ...................................... 39
Figure 10- RT-qPCR data for showing PGC-1α expression in hepatocytes. ............................. 40
Figure 11- RT-qPCR data for showing GPAT4 and GPAM expression in hepatocytes. ......... 41
Figure 12- RT-qPCR data for showing DGAT2 & DGAT1 expression in hepatocytes. ......... 42

v

Acknowledgements
I would like to thank my advisor, Dr. Bangyan Stiles, for being a very kind and professional
mentor, giving me advice on the thesis and providing valuable feedback on all the experiments.
I also want to thank Dr. Martine Culty and Dr. Jennica Zaro for being my committee members
and providing me with their support and advice. Finally, I want to thank all my laboratory
colleagues for helping me with experiments.

vi

Abstract
The transcriptional network regulated by the estrogen-related receptor alpha (ERRα) plays a
pivotal role in governing the expression of numerous genes associated with mitochondrial
respiratory complexes and metabolic enzymes that are integral to lipid and glucose
metabolisms. This study intends to explore the transcriptional regulation of Glycerol-3-
phosphate acyltransferases 4 (GPAT4), a rate-limiting enzyme catalysing the initial step in
triglyceride (TG) biosynthesis, by ERRα. Our lab's previous research found that the
downregulation of ERRα led to a global reduction in the expression of essential enzymes for
TG biosynthesis in siERRα-treated Huh7 hepatocytes. Furthermore, GPAT4 has been
identified as a potential novel transcriptional target of ERRα. In this study, we aim to develop
tools to explore the mechanism of this regulation. Moreover, this study sought to identify the
specific AKT isoform upstream of ERRα in the PI3K/AKT pathway and to determine which
AKT isoform regulates ERRα and ERRα regulated genes involved in lipid metabolism and the
glycerolipid pathway. This endeavour provides a comprehensive understanding for how
PI3K/AKT pathway regulates lipid metabolism.
These investigations have significant implications for our understanding of metabolic
disorders. Deregulation in any of the processes examined in this study can lead to lipid
accumulation, resulting in fatty liver disease and non-alcoholic fatty liver disease (NAFLD),
which can further progress to liver cancer. Therefore, elucidating these pathways could pave
the way for novel therapeutic strategies to combat these conditions.
1

Chapter I- Introduction
INTRODUCTION TO NAFLD
Non-alcoholic fatty liver disease (NAFLD) affects nearly 30% of the adult population and in
recent years is seen to be a major cause of liver disease-related premature illness and deaths
around the world[1]. NAFLD encompasses a variety of hepatic disorders, spanning from
uncomplicated hepatic steatosis to a more severe condition known as non-alcoholic
steatohepatitis (NASH). These conditions can potentially evolve into more serious stages such
as fibrosis and cirrhosis [2]. A ‘two-hit hypothesis’ was proposed for this progression of fatty
liver disease wherein the first hit is simple steatosis and its progression to NASH with possible
advancement to fibrosis and cirrhosis may be considered as the second hit[1]. It is estimated
that a quarter of the NAFLD individuals are likely to progress to NASH complicated with
fibrosis or cirrhosis. NAFLD is believed to be the primary cause of chronic liver disease in the
United States, impacting an estimated 80 to 100 million people[3]. Additionally, it has a strong
correlation with greater prevalence of a number of cardiometabolic conditions, such as
diabetes, metabolic syndrome, and cardiovascular diseases (CVDs)[4].
In addition, it has been noted that the incidence of Hepatocellular Carcinoma (HCC) has been
increasing parallelly with the rise in NAFLD and its subsets. The incidence rate of HCC has
quadrupled between the years 1973 and 2011[3]. It is crucial to note that advanced fibrosis
consistently presents as a significant risk factor for HCC, with a 5-year cumulative incidence
rate of 8% for HCC development in patients diagnosed with advanced fibrosis[3]. Due to this
situation, it is expected that NAFLD will become the leading cause of HCC[3]. The focus of
this research is to delineate the mechanisms underpinning dysregulation of lipid metabolism,
a critical biological pathway implicated in an array of liver pathologies, ranging from
steatosis to NAFLD, NASH, and ultimately, HCC.
2

Understanding the molecular players and events that contribute to lipid dysregulation can
therefore provide critical insights into the pathophysiological progression from simple steatosis
to NAFLD, NASH, and eventually liver cancer. In the long term, such knowledge can inform
therapeutic strategies aimed at mitigating the risk of disease progression in individuals with
fatty liver disease.
LIPID METABOLISM
Despite the fact that the name "lipid" refers to a variety of substances, the breakdown and
synthesis of TG is typically referred to as "lipid metabolism." Esters of glycerol and three fatty
acids make up TGs. TGs can be produced in the liver from extra dietary glucose or they can
come from diets, be stored in adipose tissues, or both[5][6].
By means of the actions of bile salts and pancreatic lipase, dietary lipids are mostly digested in
the small intestine. Bile salts act as a detergent, breaking up big globules of fat into tiny micelles
so that lipase may more easily access them. Then, TGs are converted into monoglycerides,
glycerol, and free fatty acids by the enzyme pancreatic lipase. These substances migrate into
the intestinal epithelial cells called enterocytes, where they mix to produce TG. Then,
chylomicron, which are big lipoprotein particles, are formed by packing TG and cholesterol
together. Water-insoluble lipids can be transported in aquatic settings thanks to lipoproteins.
Chylomicron exit the enterocytes, go into the lymphatic capillaries, and ultimately exit the
bloodstream, transferring fats to the tissues. Lipoprotein lipase is an enzyme found on the blood
capillary walls[7]. In order for TG to enter tissues through capillary walls and be oxidized for
energy and re-esterified for storage, this enzyme hydrolyses them into fatty acids and
glycerol[6].
The liver processes remnants of chylomicrons, laden with cholesterol and apolipoproteins.
Concurrently, free fatty acids and these remnants are absorbed by the liver, while a fraction of
3

circulating glucose is utilized for the process of de novo lipogenesis. Lipid molecules from
varying sources are either utilized for ATP generation within the liver or packaged alongside
ApoB100, ApoC, and ApoE into very low-density lipoproteins (VLDL) within the
endoplasmic reticulum. These VLDL are subsequently released into circulation, undergoing
metabolism by targeted tissues in a process that mirrors chylomicron metabolism, where LPL
hydrolyses the TGs into fatty acids for cell import. Consequently, the leftover lipoprotein
particle undergoes further metabolism into low-density lipoprotein (LDL), which numerous
tissues can absorb through the LDL receptor. These are hydrolysed to fatty acids and glycerol
and are further oxidized in the mitochondria for energy. Tricarboxylic acid cycle (TCA cycle),
oxidative phosphorylation (OXPHOS), and fatty acid -oxidation (FAO) are the three main
enzymatic processes used by mitochondria to produce ATP. Acetyl-CoA, which is produced
from carbohydrates, lipids, and amino acids, is oxidized by the TCA cycle to produce NADH
and flavin adenine dinucleotide (FADH2), which can be utilized by the OXPHOS system to
produce ATP. This research project aims to elucidate the regulatory roles of specific signalling
molecules in the modulation of lipid metabolism components[6][7][8].
TRIGLYCERIDE SYNTHESIS PATHWAY/ GLYCEROLIPID BIOSYNTHESIS
PATHWAY
In most tissues TG is produced in the glycerolipid pathway. A multitude of enzymes are
involved in the catalytic transformation of fatty acyl CoA to TG[11]. Notably, Glycerol-3-
phosphate acyltransferase (GPAT) initiates the first stage in the creation of TG. GPAT
catalyses the acylation of glycerol-3-phosphate (G3P) with acyl-CoA to synthesize
lysophosphatidic acid (LPA). Following this LPA is converted into phosphatidic acid (PA),
and this conversion is catalysed by the 1-acyl glycerol-3-phosphate acyltransferase (AGPAT)
family of enzymes. The dephosphorylation of PA, which produces diacylglycerols (DAG), is
catalysed by the enzyme phosphatidic acid phosphatase (also known as PAP or lipin).
4

Diacylglycerol acyltransferase (DGAT) catalyses the conversion of DAG to TG. Furthermore,
in the biosynthesis pathway of glycerophospholipids, PA and DAG act as key precursors in the
synthesis of TG. These compounds are involved in the critical process of phospholipid
remodelling. Glycerophospholipids are the primary elements of biological membranes and are
crucial for cellular processes [11].
ROLE OF GLYCEROL-3-PHOSPHATE ACYLTRANSFERASE (GPAT) ENZYME
GPAT catalyses the first step towards formation of triacylglycerol, and is considered as the rate
limiting enzyme in this pathway. In mammalian cells GPAT activities have been detected in
two sites. One is present in the endoplasmic reticulum and the other is present in the
mitochondria. Mammals have two GPAT forms in their mitochondria: GPAT1 (also known as
GPAM) and GPAT2, as well as two GPAT forms in their microsomes: GPAT3 and
GPAT4[11].
GPAT1 is an enzyme localized on the outer membrane of mitochondria. It was initially
identified and cloned from mouse and rat mitochondria[12], where it exhibits resistance to N-
Ethylmaleimide (NEM), a characteristic consistent with the previously observed mitochondrial
GPAT activity. This enzyme has been linked to the process of TG synthesis.
Studies conducted using Gpat1 knockout mice have corroborated the enzyme's crucial role in
lipid metabolism. Notably, female knockout mice exhibited lower body weight, smaller
adipose tissue pads, and reduced levels of liver TG content and plasma cholesterol. These mice
also showed an increased rate of fatty acid oxidation in the liver and higher levels of plasma
ketone bodies, compared to control mice[13]. These findings held true across different dietary
conditions, suggesting that GPAT1 significantly influences hepatic TG content[13]. On a
biochemical level, GPAT1 shows an approximately two-fold preference for saturated fatty
acyl-CoA’s over their unsaturated counterparts[14]. It catalyses the selective transfer of fatty
5

acids to the sn-1 position of glycerol-3-phosphate (G3P). In particular, GPAT1's preference for
palmitoyl-CoA (C16:0-CoA) has been confirmed in mice with hepatic Gpat1 knockdown[15].
These mice exhibited a decrease in the amount of C16:0 and an increase in stearic acid (C18:0)
and oleic acid (C18:1) in liver phosphatidylcholine (PC) and phosphatidylethanolamine (PE),
the two most abundant phospholipids[16][15]. Conversely, the overexpression of Gpat1 in
mice or rats revealed an amplified incorporation of C16:0 fatty acids into the molecules of
LPA, DAG, and TG[14][17]. Furthermore, hepatocyte analysis from Gpat1 knockout mice
revealed that GPAT1 is required to integrate de novo synthesized fatty acids into TG and to
divert them away from the oxidation processes[14][18][13].
GPAT2 was initially identified as an additional mitochondrial enzyme, given the residual
mitochondrial GPAT activity noted in GPAT1 deficient mice. This isoform is the most
enigmatic among the mammalian GPATs. GPAT2 shares a strong resemblance with GPAT1
in terms of structure and molecular weight. Despite their similar mitochondrial location and
high homology, GPAT2 activity is sensitive to NEM, unlike GPAT1. The tissue distribution
of GPAT2 also diverges from that of GPAT1[19]. Mouse GPAT2 expression was found to be
50 times lower in the liver compared to the testis, and even lower in other tissues including
adipose tissue, skeletal muscle, brain, adrenal glands, kidneys, lungs, and heart [13][19].
Furthermore, fasting or re-feeding in rodents does not alter GPAT2 expression, suggesting that
this enzyme may not directly influence TG synthesis or energy storage within the liver[14].
Initially known as AGPAT8 and AGPAT6, GPAT3 and GPAT4 are isoforms located on the
ER membrane. Their catalytic activities exhibit sensitivity to NEM, aligning with the
previously characterized activity of microsomal GPAT. Both GPAT3 and GPAT4 were
initially discovered as members of the AGPAT (Acylglycerol phosphate Acyltransferases)
family, AGPAT6 and AGPAT8 respectively[14]. The proteins were later found to reside in the
endoplasmic reticulum and exhibit GPAT, instead of AGPAT activity. This led to the
6

reclassification of AGPAT6 as GPAT4 and AGPAT8 as GPAT3[14]. GPAT3 was seen to be
sensitive to NEM, and was a microsomal GPAT; and GPAT4 was another microsomal
GPAT[13][20].
In adipocytes, GPAT3 emerged as the predominant GPAT, as evidenced by a 60-fold increase
in GPAT3 mRNA during the maturation process of 3T3-L1 cells into adipocytes[21]. Further,
Gpat3 deletion led to an 80% reduction in total GPAT activity within white adipose tissue[22].
Conversely, GPAT4 exhibited a modest five-fold induction[23]. In liver, Gpat3 deletion had
no significant impact on total GPAT activity in the liver, but a 30% reduction in NEM-sensitive
GPAT activity was noted[22]. Additionally, female Gpat3-/- mice on a high-fat diet displayed
reduced weight gain and adiposity, coupled with elevated energy expenditure. However, these
mice-maintained viability and fertility with no apparent metabolic abnormalities when fed a
standard diet. Intriguingly, Gpat3-/- mice displayed lower fed glucose levels, slightly improved
glucose tolerance, and dysregulated cholesterol metabolism when subjected to a high-fat diet.
Furthermore, these mice exhibited enlarged livers, hinting at the potential metabolic
ramifications of GPAT3 deficiency[14][21].
In mice lacking GPAT4, a 65% reduction in NEM-sensitive GPAT activity was observed in
both the liver and brown adipose tissue, but not in the gonadal white adipose tissue[20]. This
indicates a significant role for GPAT4 in the liver and brown adipose tissue[11]. GPAT4
expression has also been reported to increase in the mammary gland epithelium during
lactation, and mice without GPAT4 exhibited severely compromised lactation and fewer fat
droplets in the mammary gland. This underscores the importance of GPAT4 in the synthesis of
TG in breast milk[14]. Additionally, the overexpression of GPAT4 in mouse liver cells was
linked to an imbalance in glucose homeostasis, such as impaired insulin suppression of
gluconeogenesis and inhibited insulin-stimulated glycogen synthesis[11]. This disruption in
glucose homeostasis was associated with a decrease in insulin-stimulated phosphorylation of
7

Akt-Ser473 and Akt-Thr308[14]. These findings suggest that lipids derived from GPAT4
activity could negatively impact insulin signalling in the liver, potentially contributing to
insulin resistance[14][11].
Overall, the GPAT enzymes are essential in the initial step of glycerolipid synthesis, and
understanding their transcriptional control can shed light on metabolic dysregulation in various
diseases, including obesity, diabetes, and NAFLD.
INSULIN REGULATED PI3K/AKT PATHWAY IN LIPID METABOLSIM
The PI3K/AKT signalling cascade is a central molecular pathway essential in the regulation of
glucose levels and response to insulin. It comprises two main components: phosphatidylinositol
3-kinase (PI3K) and AKT. When insulin binds to its receptor at the cell membrane of a cell, it
sets off a chain of events beginning with the stimulation of the insulin receptor substrate. This
action activates PI3K, which transforms a component of the cell membrane,
phosphatidylinositol (4,5)-bisphosphate (PIP2), into phosphatidylinositol 3,4,5-trisphosphate
(PIP3). PIP3 then binds to AKT, prompting its migration to the cell membrane from inside the
cell. This movement of AKT is fundamental to the cell's proper response to insulin and efficient
glucose regulation, as it orchestrates the movement of glucose transporters (GLUTs) to the cell
membrane, facilitating glucose uptake[24][25].
PTEN, or Phosphatase and TENsin homolog deleted on chromosome 10, is a significant
cancer-suppressing gene situated on chromosome 10q23.31. This gene encodes a protein of
403 amino acids, characterized by its dual phosphatase activities for both lipids and proteins.
PTEN's primary role lies in its ability to inhibit the PI3K/AKT pathway. It does so by
converting phosphatidylinositol (PI) 3,4,5-triphosphate into PI-4,5-bisphosphate, thereby
opposing the function of PI3K. PTEN's inactivity is a common occurrence in numerous
cancers, including liver cancer, as well as in fatty liver disease. This inactivation can result
8

from several genetic alterations, such as point mutations, significant chromosomal deletions,
or through epigenetic changes[26].
AKT exists in three slightly different isoforms: AKT1, AKT2, and AKT3, each with unique
roles and encoded by distinct genes located in different chromosomes. All three AKT versions
have similar structures with an N-terminal pleckstrin homology (PH) domain, a central kinase
domain, and a C-terminal regulatory domain. They differ in the linker region connecting the
PH to the catalytic domain. The activity of AKT is influenced by conformational changes and
phosphorylation.
AKT1 isoform is predominantly expressed and the best characterized isoform in many cancers
owing to its role in cell survival and growth[27]. It plays and integral role in cell cycle and
cellular functions and is considered as an important oncogene essential for tumour initiation
and growth[28]. AKT2 is critical for insulin's control of glucose metabolism[27] and also plays
a significant role in lipid metabolism. In mice where Pten is knocked out, Akt2 deletion resulted
in significant reduction in lipid accumulation in the liver, suggesting that AKT2 is crucial for
this process[29]. Furthermore, the lack of AKT2 led to a decrease in the expression of lipogenic
(fat-producing) genes and a decrease in the formation of new fatty acids[30]. The effects of
AKT3 is mostly limited to the brain and testes where it is found expression, whereas Akt1 is
ubiquitously expressed, while Akt2 is primarily expressed in insulin-responsive tissues[31].
Brain development is linked to AKT3[32]. A 20% reduction in brain size caused by Akt3 loss
in Drosophila leads to smaller and fewer cells[33]. Brain weight and size are significantly
decreased by roughly 25% in adult Akt3 mutant mice[34].
The PI3K/AKT signalling cascade is fundamental in instigating the intracellular responses
post-insulin receptor substrate-1 (IRS-1) phosphorylation, controlling key metabolic processes
9

including glucose and lipid metabolism. AKT's role is pivotal in augmenting glucose uptake
by activating downstream molecules like Glucose Transporters (GLUTs)[35][36].
In the context of Type 2 Diabetes (T2D), AKT overexpression or enhancement has been linked
to the improved glycaemic control[37]. Conversely, impaired AKT function is associated with
insulin resistance in metabolic tissues, leading to T2D[36]. There is an intriguing connection
between these metabolic disorders and increased cancer incidence. Hyperactive insulin
signalling, which escalates AKT activity, can result in decreased blood glucose levels and
consequently, a reduced likelihood of diabetes[36]. Since diabetes has been linked to enhancing
tumor growth, epidemiology statistics showing that diabetes is typically found in between 8
and 18% of cancer patients. A tenuous link between cancer and diabetes is proposed[36][38].
However, the role of AKT is complex and seemingly paradoxical, as enhanced AKT activity
is also implicated in tumor proliferation. The dichotomy in AKT's impacts necessitates a
nuanced understanding of its function and which isoform regulates which function[36].
Additionally, liver cancer often stems from fatty liver disease. It has been observed that
increased AKT activity can lead to an upsurge in lipid synthesis and fatty acid accumulation,
thus contributing to fatty liver disease[39]. This condition may escalate into liver cancer over
time. The association between liver cancer progression and the amplified synthesis, storage,
and uptake of lipids has been linked to the activation of oncogenic pathways like the PI3K/AKT
pathway[40]. As both AKT1 and AKT2 isoforms are present in insulin-sensitive tissues like
the liver, adipose tissue, and skeletal muscle, they likely perform crucial roles in regulating
different aspects of insulin action and lipid metabolism via the PI3K/AKT pathway. Therefore,
examining the distinct roles of these two AKT isoforms may provide a more profound
understanding of the signalling pathways leading to the development of fatty liver disease and
cancer. This understanding can then potentially elucidate how AKT can be therapeutically
targeted to treat these diseases more effectively.
10

TRANSCRIPTIONAL REGULATION IN LIPID METABOLISM
The transcriptional control of genes related to fatty acid metabolism is currently seen as a
primary regulatory mechanism that provides long-term stability to lipid balance. It is carried
out by a number of transcription factors, the most active of which are the SREBPs, C/EBPs,
ChREBP, and members of the nuclear receptor family[42][43].
a. Sterol regulatory element binding proteins (SREBP)
Acting as a transcriptional factor, SREBPs directly stimulate the expression of over 30 genes
crucial for the production and uptake of various substances including cholesterol, fatty acids,
TG, phospholipids, as well as the NADPH cofactor necessary for their synthesis. There are
three main SREBP isoforms encoded by the mammalian genome, which are designated as
SREBP-1a, SREBP-1c, and SREBP-2. In most cultured cell lines, SREBP-1a and SREBP-2
are the dominant isoforms. However, in the liver, SREBP-1c and SREBP-2 are more prevalent,
where they control the de novo lipogenesis of lipids for distribution into the plasma as
lipoproteins and into the bile as micelles. SREBP-1c stimulates fatty acid synthesis genes,
enhancing the synthesis of phospholipids and TGs. SREBP-2, on the other hand, activates the
genes that produce cholesterol. Both routes involve the enzymes malic enzyme (ME), glucose-
6-phosphate dehydrogenase (G6PDH), and 6-phosphogluconate dehydrogenase (PGDH),
which are used in reactions to produce NADPH[44][45].
b. peroxisome proliferator-activated receptor gamma co-activator (PGC-1α)
Recently, it was discovered that peroxisome proliferator-activated receptor gamma co-activator
(PGC-1α) is the master regulator of mitochondrial biogenesis. PGC-1α is the pioneer member
of a family comprising three related proteins that are pivotal to primary metabolic operations.
The PGC-1-related co-activator (PRC) is universally expressed, while PGC-1α and β are
predominantly present in mitochondria-rich tissues like the heart and skeletal muscles[46].
11

Research from overexpression studies proposes that PGC-1α and β exert unique bioenergetic
impacts, with PGC-1β primarily triggering genes associated with reactive oxygen species
elimination[46]. A lack of PGC-1β in the heart can lead to an overall defect in the gene
expression of electron transport chain components, resulting in a diminished mitochondrial
volume fraction and a weakened response to dobutamine stimulation[46]. However, it appears
that only PGC-1α responds to metabolic challenges such as exercise, fasting, or cold, implying
that PGC-1β could have a role in inherent mitochondrial biogenesis[46]. Targets of PGC-1α
include NRFs, transcription factors like PPARs, thyroid hormone, glucocorticoid, estrogen,
and estrogen-related ERRα and γ receptors[46].
c. Peroxisome proliferator-activated receptor (PPAR)
The PPAR’s are ligand-activated transcription factors belonging to the nuclear hormone
receptor superfamily[47]. They comprise of the following three subtypes: PPAR-α, PPAR-γ,
and PPAR-δ. PPAR-α activation lowers TG levels and is implicated in the regulation of energy
homeostasis[48]. It is primarily expressed in tissues such the liver, kidney, heart, and muscle
that exhibit high rates of β-oxidation. On the other hand, adipose tissue has high levels of
PPAR- γ expression[47]. TG levels are reduced and energy balance is regulated when PPAR-
α is activated[48]. While PPAR- γ activation increases the metabolism of glucose and makes
the body more sensitive to insulin, PPAR- β/δ activation increases the metabolism of fatty
acids[48].
d. CCAAT/enhancer binding proteins (C/EBP)
C/EBP proteins form a family of transcription factors that are essential in various tissues such
as liver cells, adipocytes, monocytes, macrophages, and B cells. Specifically, the C/EBPα
transcription factor modulates hepatic nitrogen, glucose, lipid, and iron metabolism[49].
Researchers have employed knock-in mutagenesis in mice to understand how C/EBPα
12

regulates gluconeogenesis and lipogenesis. The findings reveal that a particular region of
C/EBPα, the PHR domain, is pivotal in controlling the genes involved in synthesizing essential
fat molecules[49]. When this domain remains unphosphorylated by insulin at S193, it
significantly influences the regulation of these genes by working alongside another protein,
SREBP-1. Another crucial segment of C/EBPα, the CR4 domain, sheds phosphate groups on
two particular sites (T222 and T226) during fasting[49]. Mutations at these sites led to
increased liver gene expression involved in gluconeogenesis, resulting in glucose
intolerance[49]. The studies suggest that the phosphorylation status of C/EBPα might serve as
an independent mechanism to regulate gluconeogenesis, apart from PGC-1α[49].
In a related context, knockdown of C/EBPα reduced the intracellular neutral lipid levels and
the expression of genes related to the TG synthesis pathway, especially GPAM[50]. However,
an overexpression of C/EBPα demonstrated the opposite results[50]. It was also seen that lower
production of C/EBPβ led to reduced DGAT2 production, implying the control exerted by
C/EBPβ on DGAT2 production[51]. Mice lacking C/EBPβ also exhibited lower levels of
DGAT2 in their fat tissue[51]. These absence of DGAT2 significantly reduces TG levels in fat
tissue, underscoring the importance of DGAT2 in TG production[51]. However, despite a drop
in C/EBPβ levels during adipogenesis, DGAT2 levels remained elevated[51]. The researchers
found that another protein, C/EBPα, can take over for C/EBPβ at the same area in the DGAT2
gene during these later stages[51]. These insights provide valuable knowledge about the
regulation of DGAT2 production and suggests a role of the C/EBP family proteins in
establishing and maintaining the metabolic attributes of mature fat cells[51][50].
e. Carbohydrate response element-binding protein (ChREBP)
The ChREBP is crucial in managing conditions like type 2 diabetes, dyslipidemia, non-
alcoholic fatty liver disease, and tumorigenesis. It's mainly found in organs that produce fats
13

such as the liver, intestines, and adipose tissue, where it controls the conversion of glucose into
a molecule known as acetyl CoA by boosting the expression of certain genes (Pklr and
Acyl)[52]. Recent research reveals that ChREBP also contributes to turning acetate from gut
bacteria into acetyl CoA. It does this by activating a gene called Acss2 in the liver[42].
Moreover, ChREBP plays a part in fatty acid synthesis, extension, and desaturation by
encouraging the expression of genes like Acc1, Fasn, Elovl6, and Scd1[42]. ChREBP also
helps in creating very low-density lipoprotein (a type of fat-carrying protein) by boosting Mtp
expression. ChREBP plays a significant role in peripheral lipid metabolism by enhancing the
expression of Fgf21, Angptl3, and Angptl8. These genes are known to reduce the [52].
ChREBPα, influenced by specific molecular modifications, orchestrates energy pathways by
initiating glycolytic and lipogenic genes, and further stimulates the production of its perpetually
active form, ChREBPβ, in adipose tissue[42].
f. Estrogen-related receptors (ERR)
The ERR is also known as nuclear receptor 3B (NR3B), these are orphan nuclear receptors that
play important roles in metabolic homeostasis. ERR, plays a critical role in the transcriptional
regulation of genes involved in mitochondrial bioenergetics and functions. The orphan nuclear
receptor subfamily is made up of three members: ERRα, ERR β, and ERRγ[53]. ERRα is the
dominant isoform of ERR in the liver and it regulates the expression of various genes encoding
mitochondrial respiratory complexes and metabolic enzymes involved in lipid and glucose
metabolisms[54]. They are activated by the transcriptional coactivator PGC-1α, a critical
regulator of cellular energy metabolism [55][56].
It was assumed that the loss of ERRα activity would result in decreased oxidative
phosphorylation and suppress catabolism, leading to a buildup of lipids. This was because its
target genes have mitochondrial regulatory activities. However, mice lacking ERRα
14

demonstrated resistance to obesity and NAFLD brought on by a high-fat diet (HFD)[57]. This
observation therefore led to the conclusion that ERRα's physiological roles in metabolic
regulation are more complex and dependent on the metabolic state, or that ERRα's involvement
in lipid metabolism is mediated by other unrecognized target genes[57][58].
RATIONAL
NAFLD manifests prematurely in mice with Pten deletion, characterized by marked
macrovesicular lipid accumulation[59]. Furthermore, the Pten null mice spontaneously exhibit
histopathological features analogous to NASH, encompassing steatosis, Mallory-Denk bodies,
pericellular fibrosis, and inflammatory cell infiltration[59]. It was seen that Pten deletion in the
liver enhances insulin action, improves systemic glucose tolerance, and increases fatty acid
synthesis via the activation of P13K/AKT pathway leading to hepatomegaly and a fatty liver
phenotype[59]. A noteworthy observation was the elevation of ERRα in the livers of Pten-null
mice, suggesting that ERRα expression may be negatively regulated by PTEN[60]. Further it
was seen that ERRα inhibition prevents the PTEN loss-induced NAFLD development[57]. Our
investigation revealed that ERRα is positively modulated by insulin-mediated PI3K/AKT
signalling in hepatocytes[57]. Additionally, evidence from the study shows that ERRα fosters
lipogenesis and the sequestration of lipids in the form of TGs[57].
A more in-depth exploration of the metabolic alterations associated with the attenuation of liver
steatosis by targeting ERRα was undertaken through Gene Set Enrichment Analysis of RNA-
sequencing data procured from siERRα-treated Huh7 hepatocytes[57]. It was discerned that
the suppression of ERRα activity culminated in the downregulation of the expression of critical
enzymes, including not only those involved in de novo lipogenesis, fatty acid oxidation but
also GPATs, instrumental in TG biosynthesis[57]. GPATs catalyses the esterification of long-
chain fatty acids to glycerol 3-phosphate, a rate-limiting and initial committed step in TG
15

biosynthesis, resulting in the formation LPA[11]. The study identified GPAT4 as a previously
unknown transcriptional target of ERRα, while the regulation of GPAT1, DGAT1, and DGAT2
by C/EBPβ was ascertained. This study further intends to substantiate this hypothesis that
ERRα modulates GPAT4 at the transcriptional level.
In addition, a previous study from our lab showed that the hepatic lipid accumulation and liver
cancer development are both significantly lower in the double mutant mice (those lacking both
PTEN and AKT2) compared to the mice with only the Pten deletion[59]. This study suggests
that AKT, either total AKT or AKT2 alone plays a critical role in sustaining the expression of
genes implicated in hepatic lipid metabolism and liver cancer progression[29]. Therefore, my
investigation also addressed the roles of the two AKT isoforms in the regulation of ERRα and
its function. Here, I will explore the effects of deleting either Akt1 or Akt2 on ERRα, and ERRα
regulated transcriptional networks including de novo lipogenesis, fatty acid oxidation and
glycerolipid biosynthesis. The overarching objective is to unravel the intricacies of the
signalling network, with an emphasis on the interplay between ERRα and the PI3K/AKT
pathway in the context of lipid metabolism and liver pathophysiology. Our research objectives
are structured around three primary aims:
Aim 1: To develop a GPAT4 promoter construct to explore the transcriptional regulation of
GPAT4 by ERRα. This construct will allow us to ascertain whether ERRα regulates GPAT4 at
the transcriptional level.
Aim 2: To identify the specific AKT isoform functioning upstream of ERRα. This will provide
insights into the differential roles of AKT isoforms in regulating ERRα.
Aim 3: To determine the effects of deleting specific AKT isoform on transcription of ERRα
responsible genes. The genes involved in lipid metabolism will allow us to understanding how
16

individual AKT isoforms contribute to the regulation of lipid metabolism and their role in
disease progression.
Each aim is designed to dissect the intricate links between the AKT isoforms, ERRα, and the
genes involved in lipid metabolism, ultimately painting a detailed picture of the metabolic and
molecular interplay underlying the development of fatty liver disease.

17

Chapter II- Materials and Methods
1. Bacterial Transformation
A 100 µl aliquot of the transformation-competent bacteria cells was transferred into a pre-
chilled Eppendorf tube to which 1 µl of the GPAT4 Promoter plasmid was added. This mixture
of plasmid DNA and competent cells was incubated on ice for 30 minutes. Following the
incubation, the mixture was subjected to a heat shock at 42 °C for 45 seconds and immediately
returned to the ice for 2 minutes. Subsequently, a solution was prepared with ampicillin and
Luria broth (LB) in 1:1000 ratio. A aliquot of this LB and ampicillin solution was added to the
mixture containing the DNA and competent cells. The resultant mixture was agitated at 225
rpm for 1 hour. Post incubation, the cells were evenly spread on the previously prepared LB
agar plates supplemented with ampicillin. The plates were then inverted and incubated at 37
°C overnight. The transformed cells were allowed to grow and divide overnight, resulting in
visible colonies on the agar plates the following day.
2. Colony Pick-up and Culturing
Individual colonies were picked from the LB agar plates using a pipette tip. Each colony was
transferred to a culture tube containing 2 ml LB broth supplemented with 2 µl of ampicillin.
The tubes were incubated at 37 °C with shaking at 225 rpm overnight.
3. Standard alkali DNA isolation
A mini-prep was conducted to isolate plasmid DNA from the overnight cultures. 1.5 ml of each
culture was transferred to a microcentrifuge tube and centrifuged for 8 minutes at 5000 rpm.
The supernatant was discarded, and the bacterial pellet was resuspended in 200 µl of P1 buffer
(resuspension buffer). An equal volume of P2 buffer (lysis buffer) was added, followed by the
addition of 200 µl of P3 buffer (neutralization buffer). The tube was allowed to stand for 5
minutes before centrifugation for 20 minutes at maximum speed. The supernatant, containing
18

the plasmid DNA, was retained and mixed with 400 µl of isopropanol (IPA) for subsequent
plasmid purification procedures. Following the addition of isopropanol, the tubes were
centrifuged for another 20 minutes at maximum speed to pellet the plasmid DNA. The
supernatant was carefully discarded, and the tubes were inverted to air-dry the DNA pellet.
Finally, the pellet was resuspended in Tris/TE buffer for downstream applications. All steps
were conducted at room temperature unless stated otherwise, and care was taken to prevent
contamination during the procedure.
Also, a midi prep was conducted where in bacterial cells from a 25 ml overnight culture were
harvested by centrifugation at 6000 x g for 15 min at 4°C. The bacterial pellet was resuspended
in 4 ml of Buffer P1 (resuspension buffer) with RNAse. Subsequently, 4 ml of Buffer P2 (lysis
buffer) was added and mixed thoroughly by inverting the tube 4–6 times, followed by a 5 min
incubation at room temperature. Following this, 4 ml of chilled Buffer P3 (neutralization
buffer) was added and mixed thoroughly before incubating on ice for 15 min. The mixture was
then centrifuged at ≥20,000 x g for 30 min at 4°C. The supernatant was decanted and subjected
to a second round of centrifugation at ≥20,000 x g for 15 min at 4°C. The plasmid DNA was
bound to a pre-equilibrated QIAGEN-tip 100 column, washed twice with 10 ml of Buffer QC,
and eluted with 5 ml of Buffer QF according to the manufacturer's recommendations. The
eluted DNA was precipitated by adding 3.5 ml of isopropanol at room temperature, followed
by 30 minutes at 4°C centrifugation at 15,000 x g. After decanting the supernatant, the DNA
pellet was air-dried for 5-10 minutes before being resuspended in a suitable buffer.
4. Restriction Digestion
Following alkali DNA plasmid isolation, the plasmid DNA underwent restriction digestion.
The digestion experiments were divided into three categories: uncut, one cut (using AgeI
enzyme in r1.1 buffer, or alternatively AgeI HF with CutSmart Buffer), and two cuts (using
19

BamHI and EcoRI in r3.1 buffer). For a one-cut restriction digestion, the reaction mixture was
set up as follows: 5 µl of DNA (concentration depending, ideally 1 µg/µl), 2 µl of r1.1 buffer,
2 µl of AgeI, and 16 µl of sterile water. The reaction was incubated at 37 °C for 1 hour to
facilitate restriction digestion. For the two-cut restriction digestion, the reaction mixture was
set up as follows: 5 µl of DNA (concentration depending, ideally 1 µg/µl), 2 µl of r3.1 buffer,
1 µl of BamHI, 1 µl of EcoRI, and 16 µl of sterile water. The reaction was incubated at 37 °C
for 1 hour to facilitate restriction digestion.
5. Agarose Gel Electrophoresis
The restriction digestion products were analysed via agarose gel electrophoresis. An agarose
gel (0.6%) was prepared by dissolving 0.24 g of agarose in 40 ml of 1X TAE buffer and adding
ethidium bromide. For running the gel, 1X TAE with ethidium bromide was added to the buffer
chamber. The samples were prepared as follows for loading onto the gel: the molecular weight
DNA ladder was mixed with loading dye; the uncut plasmid DNA was mixed with loading
dye; the one-cut plasmid DNA was mixed with loading dye; and the two-cut plasmid DNA was
mixed with loading dye. These samples were loaded onto the gel and the electrophoresis was
conducted under suitable conditions to separate the DNA fragments based on their size. The
presence and size of the DNA fragments were visualized under UV light.
6. Cell culture
The Huh7 cell line is a well-established and widely-used in vitro model in the field of
hepatology research. It is a human hepatocellular carcinoma (HCC) cell line. The Huh7 cell
line was obtained and maintained in our laboratory. The cells were cultured in Dulbecco's
Modified Eagle's Medium (DMEM) (Gibco, USA) supplemented with 10% foetal bovine
serum (FBS) (Gibco, USA) and 1% penicillin-streptomycin.
20

For shRNA-mediated ERRα knockdown studies, Huh7 cells were transfected with shRNA
targeting ERRα (shERRα) using Lipofectamine 3000 (Invitrogen, USA) according to the
manufacturer's instructions. Following transfection, cells were selected with 2 μg/ml
puromycin (Sigma-Aldrich, USA) for 2 weeks to establish stable knockdown cell lines.
In parallel to our work with the Huh7 cell line, we also performed experiments using
hepatocytes isolated from genetically modified mice. These hepatocytes were isolated from
Akt1 and Akt2 knockout mice, generated using the Cre-loxP system, which allowed for the
targeted inactivation of the Akt1 and Akt2 genes in hepatocytes specifically. The knockout and
wild-type hepatocytes were cultured under conditions optimized for primary hepatocyte
culture, which included a collagen-coated surface and hepatocyte-specific culture medium.
Culture medium used was DMEM supplemented with 10% FBS and 1% penicillin-
streptomycin, 5ug/ml insulin and 10ng/ml Epidermal growth factor (EGF).
All cell lines were regularly tested for mycoplasma contamination and were authenticated to
ensure they retained their original characteristics and had not been cross-contaminated with
other cell lines. Cells were passaged when they reached approximately 80-90% confluence,
with media changes performed every 2-3 days. All experiments were conducted in accordance
with our institution's biosafety guidelines and standard cell culture practices to ensure the
validity and reproducibility of our results.
7. Lipofectamine 3000 Transfection
The transfection was performed employing Lipofectamine 3000 (Thermo Fisher Scientific) as
per the manufacturer's guidelines. Briefly, plasmid DNA and Lipofectamine 3000 were diluted
separately in Opti-MEM media (Gibco), with concentrations as specified in the protocol. After
an incubation period of 5 minutes, the two solutions were combined and incubated for an
additional 20 minutes to allow for the formation of DNA-lipid complexes. The resulting
21

complexes were added dropwise to cells cultured in antibiotic-free medium. Cells were
incubated at 37°C in a humidified atmosphere with 5% CO2. After 48 hours, transfection
efficiency was assessed by monitoring the expression of the gene of interest. Cells were then
harvested for further downstream analyses. The complete procedure was performed under
sterile conditions to avoid any contamination.
8. Fluorescence Microscopy
Fluorescence microscopy was performed using an inverted fluorescence microscope equipped
with a rhodamine specific filter set. Briefly, cells were visualized and images captured using a
digital CCD camera connected to the microscope.
9. RNA Isolation
Huh7 cells and shERRa Huh7 cells transfected with GPAT4 promoter plasmid, AKT1
knockout hepatocytes, AKT2 knockout hepatocytes, and wild-type hepatocytes were used to
isolate RNA. An RNA isolation procedure was used to each cell type. To eliminate any
remaining medium or dead cells, the cells were rinsed with phosphate-buffered saline (PBS).
After washing the cells, they were lysed directly in the culture dish with 1 mL of TRIzol
Reagent (Invitrogen, Carlsbad, CA, USA) per 10 cm of culture dish surface area. The cell lysate
was collected and incubated at room temperature for 5 minutes to allow complete dissociation
of nucleoprotein complexes. After incubation, 0.2 mL of chloroform was added for every 1 mL
of TRIzol Reagent used, and the mixture was rapidly agitated for 15 seconds. Following a 2–
3-minute rest at ambient temperature, the tubes were centrifuged at 12,000 x g for 15 minutes
at 4°C, yielding a three-phase mixture. The RNA-containing upper aqueous phase was
carefully transferred to a fresh tube. RNA precipitation was induced by mixing the aqueous
phase with isopropanol and incubating the solution at room temperature. Centrifugation at
12,000 x g was done to obtain the precipitated RNA. The supernatant was then removed, and
22

the RNA pellet was washed with 75% ethanol to eliminate any remaining salts and
contaminants. The pellet was air-dried and then resuspended in RNAse-free water. The
concentration and purity of the isolated RNA were determined using a spectrophotometer,
while its integrity was confirmed through agarose gel electrophoresis.
10. Real-Time Quantitative PCR (RT-qPCR)
Following RNA isolation, the RNA samples were subjected to reverse transcription
quantitative PCR (RT-qPCR). This procedure was initiated with the synthesis of cDNA, which
was conducted using the High-Capacity cDNA Reverse Transcription Kit (Applied
Biosystems, Foster City, CA, USA). In brief, 1 μg of total RNA from each sample was reverse
transcribed into cDNA according to the manufacturer's protocol. The RT-qPCR was performed
on the synthesized cDNA. The reactions were set up in a total volume of 20 μL, containing 1
μL of cDNA, 10 μL of SYBR Green PCR Master Mix (Applied Biosystems), and 200 nM of
each primer. The primer sequences used for amplification are detailed in Table 1. The RT-
qPCR was conducted on a StepOnePlus Real-Time PCR System (Applied Biosystems) with
the following cycling conditions: an initial hold at 95°C for 10 minutes to activate the Taq
polymerase, followed by 40 cycles of denaturation at 95°C for 15 seconds, annealing at 60°C
for 30 seconds, and extension at 72°C for 30 seconds. The reactions were run in triplicates to
account for technical variability. The expression levels of the genes were normalized to the
expression of the housekeeping gene GAPDH. The relative gene expression was calculated
using the comparative Ct (ΔΔCt) method, where Ct represents the cycle threshold, which is the
number of cycles required for the fluorescent signal to cross the threshold in qPCR. The
resulting data represents the fold change in gene expression in the various cell types relative to
the control.
Table 1- List of primers for RT-qPCR
23

Gene Primer Sequence
ERRα Forward 5’-CAAGAGCATCCCAGGCTT-3’
Reverse 5’-GCACTTCCATCCACACACTC-3’
ACC Forward 5’-TCACACCTGAAGACCTTAAAGCC-3’
Reverse 5’-AGCCCACACTGCTTGTACTG-3’
CYC1 Forward 5’-TCAGGCCCCTGGATACTCTT-3’
Reverse 5’-GCTATTAAGTCTGCCCTTTCTTCC-3’
FASN Forward 5’-ACAGCGGGGAATGGGTACT-3’
Reverse 5’-GACTGGTACAACGAGCGGAT-3’
MCAD Forward 5’-AGGGTTTAGTTTTGAGTTGACGG-3’
Reverse 50-CCCCGCTTTTGTCATATTCCG-3’
PGC-1α Forward 5’-AATCAGACCTGACACAACGC-3’
Reverse 5’-GCATTCCTCAATTTCACCAA-3’
GPAT4 Forward 5’-ATTTGGAGCTGCCTAGCCTC-3’
Reverse 5’-GACACTCTTCTCCCGAAGGC-3’
AGPAT1 Forward 5’-TCTTTGGGTTTGCGGAATGTT-3’
Reverse 5’-ATTTGGAGCTGCCTAGCCTC-3’
DGAT1 Forward 5’-TATTGCGGCCAATGTCTTTGC-3’
Reverse 5’-CACTGGAGTGATAGACTCAACCA-3’
DGAT2 Forward 5’-GAATGGGAGTGGCAATGCTAT-3’
Reverse 5’-CCTCGAAGATCACCTGCTTGT-3’
Tdtomato Forward 5’-CCTGTTCCTGGGGCATGG-3’
Reverse 5’-TGATGACGGCCATGTTGTTG-3’
ERRα Forward 5’-TGTGAGATCACCAAGCGGAG-3’
24

11. Flow Cytometry
To assess the transfection efficiency and evaluate the expression levels of tdTomato, a
fluorescent marker expressed from the GPAT4 promoter plasmid, flow cytometry analysis was
conducted in Huh7 and shERRα Huh7 cells post-transfection. Cells were grown in 6cm plates
until they reached approximately 80% confluency. Following transfection with the GPAT4
promoter-tdTomato plasmid, cells were incubated for an additional 24 hours to allow for
adequate expression of the fluorescent marker. The media was then removed, and the cells were
washed with Phosphate-Buffered Saline (PBS) to remove any residual media or dead cells.
Trypsin-EDTA (0.25%) was used to detach the cells, followed by neutralization with complete
media. The cell suspension was then centrifuged at 300 x g for 5 minutes, and the supernatant
was discarded. The cells were subsequently resuspended in PBS. The cells were kept on ice
until analysis to minimize changes in fluorescence levels. Flow cytometry analysis was
performed on a BD FACSVerse flow cytometer. The cells were excited using a 543 nm laser,
and the emission was detected through a 580/30 nm band-pass filter, which is the ideal setting
for detecting tdTomato fluorescence. A minimum of 30,000 events were recorded for each
sample.
Reverse 5’-AGTGCATTCACTGGGGCTG-3’
GAPDH Forward 5’-GTCGGTGTGAACGGATTTGG-3’
Reverse 5’-GACTCCACGACATACTCAGC-3’
25

Figure 1- Overview of workflow of experiment to validate that ERRα transcriptionally
regulates GPAT4. “Created with BioRender.com”[71].

26

Chapter III- Results
1. Validation and Utility of the GPAT4 Promoter Plasmid
In order to study the regulation of GPAT4 promoter by ERRα, I procured the GPAT4 promoter
plasmid. A promoter construct plasmid serves as a powerful tool in studying the transcriptional
regulation of a given gene. Here, the GPAT4 promoter construct contains a sequence encoding
the tdTomato protein, a derivative of the red fluorescent protein (RFP) from the coral
Discosoma, is engineered after the GPAT4 promoter sequence[61] (Figure 2). This protein is
recognized for its fluorescence capabilities and can serve as a detector protein in various assays.
The plasmid, when introduced to the cells allows us to understand how GPAT4 maybe
regulated transcriptional by ERRα and the signalling pathways that regulates ERRα utilizing
the fluorescence capabilities of the tdTomato protein.
The plasmid is composed of a total of 10,126 base pairs of nucleotide sequence, with the
GPAT4 promoter sequence size being 1433bp and flanked by EcoRI and BamHI restriction
enzyme sites (Figure 2). The plasmid also contains Ampicillin and Puromycin resistance genes,
serving different purposes in different culture environments (Figure 2). The ampicillin
resistance gene plays a crucial role in bacterial culture, allowing the selection of successfully
transformed bacteria. Only those bacteria that have taken up the plasmid - and thus the
resistance gene - will survive in an environment containing ampicillin. Puromycin serves as a
selectable marker for mammalian cell cultures. Cells that have successfully integrated the
plasmid will exhibit resistance to Puromycin, allowing for selection of cells that successfully
incorporated and expresses the plasmid in these cultures. Therefore, the incorporation of these
two resistance genes enhances the utility of the GPAT4 promoter plasmid for both bacterial
and mammalian cell culture systems.
27

Figure 2- Schematic representation of the GPAT4 promoter plasmid. Key features include the
GPAT4 promoter sequence (1433bp), the tdTomato fluorescent protein coding sequence,
ampicillin and puromycin resistance genes, and the EcoRI and BamHI restriction sites. The
total size of the plasmid is 10,126 base pairs.

2. From Bacterial Transformation to Restriction Enzyme Digestion and Gel
Electrophoresis Verification.
In an endeavour to acquire an augmented yield of DNA plasmid, we transformed DH5α
competent cells with the GPAT4 Promoter plasmid and plated the cells on Agar plates
containing Ampicillin. As expected for cells that uptake the plasmid construct, we obtained
many colonies on agar plates containing Ampicillin. We picked six colonies and expanded
them overnight in 2 ml Mini cultures for further validation. Plasmid DNA was extracted from
the mini-cultures using the mini-prep method, relying on an alkali lysis protocol. The mini-
prep from the 6 colonies produced yield with concentration from 1000 to 2000ng/ul in each
prep (Table 2). The extracted plasmid DNA isolated from the 6 colonies were run on an agarose
gel. Three bands were observed for each DNA preparation. One band is observed at 10kbp
which likely represents the linear strand of the plasmid DNA (10,126 bp). Linearized DNA is
observed when the DNA helix is cut in both strands at the same place. The majority of the
isolated DNA is observed at 5kbp seen by the high intensity of the band. This is the supercoiled
form of the DNA. Supercoiling occurs when extra twists are introduced into the double helix
28

strand. Supercoiled DNA migrates faster than the predicted size in an agarose gel due to its
conformation. Supercoiled DNA is the most abundant when isolating plasmid DNA. Above
10kbp, another band is visible, which is the Nicked, Relaxed, or Circular Plasmid. The
replication machinery cannot simply access supercoiled DNA. During replication, cellular
topoisomerases nick one strand of the DNA helix and relax the super helical tension, enabling
polymerases access to the DNA. This huge floppy circle is the slowest migrating form in an
agarose gel (Figure 3A).

For a more accurate identification and verification of the GPAT4 promoter sequence within the
obtained plasmid, we employed a restriction enzyme digestion method to cut the plasmid at
specific locations. AgeI was chosen as the restriction enzyme for its specificity in cleaving the
plasmid DNA only once within the GPAT4 promoter sequence, and expected to yield a linear
plasmid with the size of 10,126bp. The buffer selected for the restriction enzyme digestion
reaction was dictated by the NEBcloner tool. The tool recommended 10X NEBuffer r1.1 for
this reaction, owing to AgeI 100% activity in this buffer. Upon electrophoretic separation of
Colony Concentration (ng/ul)
1 509.39
2 1634.79
3 819.42
4 3069.29
5 1008.21
6 3548.77
Colony Concentration (ng/ul)
1 239.89
2 276.06
4 382.68
6 302.03
Table 2- Quantification of Plasmid DNA
Concentration Post-Miniprep: Represents
the concentration of plasmid DNA
extracted after the miniprep protocol
Table 3- Quantification of Plasmid DNA
Concentration Post-Midiprep: Illustrates
the concentration of plasmid DNA
following the midiprep protocol
29

the AgeI digested DNA, we observed a band migrating approximately at 10kbp, indicative of
a linear plasmid (which is 10,126bp in size) (Figure 3B).
We also employed a dual-enzyme digestion strategy using BamHI and EcoRI to segregate the
GPAT4 promoter sequence from the remaining plasmid backbone. As discussed earlier, these
enzymes were specifically chosen due to their cutting sites flanking the GPAT4 promoter
sequence and we expect this dual enzyme digestion to cut the plasmid at two locations and
yield a 1.4kb band and an 8.6kb band. To avoid star activity, 10X NEBuffer r3.1 was chosen,
where at least one enzyme (BamHI) showed 100% activity.
Post-digestion, electrophoretic analysis of the product revealed two distinct bands: one
migrating at approximately 1.4kbp, corresponding to the GPAT4 sequence, and another at
approximately 8.6kbp, signifying the residual plasmid backbone. Together, our analysis of the
extracted DNA suggests that 4 out of the 6 colonies had successfully incorporated the correct
plasmid that contain the GPAT4-tdTomato sequence as the fragment sizes obtained from the
restriction enzyme digestion analysis precisely matches with our theoretical predictions based
on the plasmid map (Figure 3C).
Following this initial analysis, we scaled up one of the bacterial cultures that contain the correct
plasmid by inoculating the remaining 2ml mini culture to a 25ml midi-culture and allowed
growth to proceed overnight. A mid-scale preparation (midi prep) kit was performed using a
Qiagen kit to extract high quantities of endotoxin-free plasmid DNA. The extracted DNA from
the midi-culture also underwent the same restriction enzyme digestion procedure used for the
mini-prep plasmids to validate the continued presence and correct orientation of the GPAT4-
tdTomato sequence. This thorough and rigorous validation process ensured the reliability of
our results and sets the stage for subsequent investigations using this carefully curated plasmid.
30

The resulting plasmid that are endotoxin free are used to introduce the GPAT4-tdTomato
construct to mammalian cells via liposome mediated transfection.
A.

B.

C.

Figure 3: Comprehensive Analysis of GPAT4 Promoter Plasmid Preparation and Digestion. A.
Agarose Gel Electrophoresis of Uncut Plasmid DNA: Depicts the electrophoretic pattern of the
uncut plasmid DNA, serving as a baseline for comparison with the cut samples; B. Agarose
Gel Electrophoresis of Single-Cut and Double-Cut Plasmid DNA: Displays the electrophoretic
patterns of the plasmid DNA after single and double digestions, respectively, highlighting the
impact of the restriction enzyme activity; C. Predicted Agarose Gel Electrophoresis Pattern
Post-Restriction Enzyme Digestion: Showcases the anticipated electrophoretic pattern of the
plasmid DNA following restriction enzyme digestion as predicted by the Snapgene software.
This serves as a reference to validate the actual gel results.

Molecular Weight
One cut 10,126 bp
Two cuts
BamHI +EcoRI
1. 8693 bp
2. 1433 bp
31

3. Evaluating the Role of ERRα in the transcriptional regulation of GPAT4
To study the effect of ERRα on GPAT4 promoter activity, we transfected the GPAT4-
tdTomato plasmid into HCC cell line, Huh7 cells with or without expression of shERRα to
knockdown the expression of ERRα. Western blot analysis shows successful knockdown of
ERRα with little to no ERRα protein expression in the shERRα expressing Huh7 cells (Figure
4A). As our GPAT4-tdTomato promoter plasmid harbours a puromycin resistance gene and,
renders the cells resistant to Puromycin, we cultured the Huh7 cells in puromycin containing
medium to eliminate the non-transfected cells, thereby enriching for the cells that have been
successfully transfected with the GPAT4 promoter plasmid. This offers us the ability to
maintain a consistent cellular environment in which the influence of ERRα on GPAT4
promoter activity can be accurately assessed.
After the GPAT4 promoter plasmid was successfully transfected in the Huh7 and shERRα
Huh7 cells, the cells were subjected to fluorescence microscopy to visualize tdTomato
expression, serving as a proxy for GPAT4 promoter activity. Consistent with our hypothesis,
Huh7 cells demonstrated a higher expression of tdTomato, indicative of greater GPAT4
promoter activity, compared to that in the shERRα Huh7 cells (Figure 4B). However, these
observations were somewhat complicated by autofluorescence, likely due to the presence of
lipofuscin, a pigment commonly found in hepatocytes, thereby highlighting the importance of
using complementary techniques to validate the findings.
We further performed flow cytometry analysis to corroborate the elevated tdTomato expression
in Huh7 cells relative to shERRα Huh7 cells. Huh7 cells display a greater tdTomato
fluorescence, suggesting that these cells have more robust tdTomato expression. Specifically,
the analysis revealed that 169 cells were tdTomato positive in the Huh7 cell population
compared to 129 cells in the shERRα Huh7 population (Figure 4C). This comparative
32

quantitative data reaffirms the initial fluorescence microscopy findings, suggesting a higher
GPAT4 promoter activity in Huh7 cells with the presence of ERRα. This data could result
from the presence of an intact ERRα its ability to regulate the GPAT4 promoter and thus
tdTomato expression. In contrast, in the shERRα Huh7 cells, wherein the ERRα pathway has
been silenced, lack of ERRα led to lower tdTomato expression.
To further quantitatively validate these observations, we adopted RT-qPCR analysis, a well-
established technique renowned for its precision and sensitivity in detecting and quantifying
mRNA expression levels. In these assays, we observed a marked elevation in ERRα mRNA
levels in the Huh7 cells as compared to their counterparts, the shERRα Huh7 cells. This
significant disparity in expression levels reaffirmed the successful knockout of ERRα in the
shERRα Huh7 cells. Additionally, to ascertain the expression of our transfected GPAT4
promoter plasmid, we designed primers targeting the tdTomato region of the plasmid. Again,
the Huh7 cells expressed higher mRNA levels for tdTomato compared to the shERRα Huh7
cells, echoing the results of our earlier experiments. More specifically, we noticed an 87%
surge in Tdtomato mRNA levels in Huh7 cells relative to the shERRα Huh7 cells (Figure 4D).
This increase was not only statistically significant, but also reinforced our hypothesis that the
presence of ERRα promotes the transcriptional regulation of GPAT4. Similarly, there was a
remarkable 86% enhancement in ERRα mRNA levels in Huh7 cells as compared to shERRα
Huh7 cells (Figure 4D). This substantial and statistically significant difference again confirmed
the successful downregulation of ERRα in shERRα Huh7 cells and validated the utility of
GPAT4 promoter construct as reporter for ERRα to study the transcriptional regulation of
GPAT4 by ERRα. Collectively, these RT-qPCR results provided robust evidence corroborating
our findings from the fluorescence microscopy and flow cytometry experiments, establishing
ERRα as a potential transcriptional regulator of GPAT4.
33

A.

B.

C.

I.
II.
III.
34

D.

Figure 4: Evaluating the Role of ERRα in transcriptionally regulating GPAT4 Activity. A.
Western blot showing expression of ERRα in Huh7 cells and shERRα Huh7 cells; B.
Comparative Analysis of GPAT4 Promoter Activity in Huh7 and shERRα Huh7 Cells. The
figure represents fluorescence microscopy images of Huh7 and shERRα Huh7 cells post-
transfection with the GPAT4 promoter plasmid. The tdTomato fluorescence signals, indicative
of GPAT4 promoter activity, are considerably more intense in Huh7 cells as opposed to
shERRα Huh7 cells, underscoring a differential promoter activity in these cells; C. I. Dot plot
representation of tdTomato expression in Huh7 and shERRα Huh7 cells. Each dot represents a
single cell, with the X-axis indicating FSC-A and the Y-axis indicating Comp PA::PA, II. Dot
Plot Comparison of tdTomato Expression in Huh7 and shERRα Huh7 Cells. This dot plot
provides a visual comparison of tdTomato expression levels between Huh7 and shERRα Huh7
cell populations. Each dot represents a single cell, with the X-axis indicating Forward Scatter
(FSC-A), a measure of cell size or granularity, and the Y-axis indicating Comp PA:PA, a
parameter indicative of tdTomato fluorescence intensities, III. Histogram Analysis of tdTomato
Expression in Huh7 and shERRα Huh7 cells. This histogram analysis showcases the
distribution of tdTomato expression within two distinct cell populations: Huh7 and shERRα
Huh7 cells. The X-axis depicts the intensity of tdTomato fluorescence (Comp PA::PA), while
the Y-axis represents the cell count at each intensity level. A noticeable shift towards higher
fluorescence intensities can be observed in the Huh7 cells as compared to the shERRα Huh7
cells, indicating a higher tdTomato expression in the former; D. Quantitative analysis of ERRα
and tdTomato expression using RT-qPCR. The expression levels of ERRα and tdTomato in
Huh7 and shERRα Huh7 cells post-transfection with the GPAT4 promoter plasmid were
measured. The Y-axis represents the relative expression levels normalized to a housekeeping
gene, while the X-axis represents the cell types. Error bars indicate the standard error of the
mean (SEM) from three independent experiments.
p=0.0003
p=0.0006
35

4. Identification of AKT2 as Potential Regulator of ERRα Expression in Hepatocytes
To investigate the AKT isoform that acts upstream of ERRα, RT-qPCR was conducted on
mouse hepatocytes isolated from mice lacking Akt1, Akt2, and compared with that isolated
from the wild-type control mice. Primers specific for ERRα were utilized in this analysis.
Interestingly, the results revealed a 25% decrease in the mRNA levels of ERRα in Akt2
knockout hepatocytes compared to wild-type, and this change was statistically significant
(p<0.05) (Figure 5A). Loss of AKT1 on the other hand led to a 31% increase in mRNA levels
of ERRα in Akt2 knockout hepatocytes compared to wild-type, with no statistically significant
(Figure 5B). These findings suggest that AKT2 might be responsible for the upregulation of
ERRα induced by AKT activation that our lab reported previously[57].

Figure 5: RT-qPCR data for showing ERRα expression in hepatocytes; A. The results
demonstrated a statistically significant reduction in ERRα expression in AKT2 knockout
hepatocytes compared to both wild-type (p= 0.0126). These findings suggest a pivotal role of
AKT2 in the regulation of ERRα expression; B. The figure portrays an elevation in ERRα
expression levels in the AKT1 knockout cell line relative to the wild-type control. However,
this observed increase, characterized by a p-value of 0.1948, does not reach the threshold of
statistical significance
5. Identification of AKT2 and not AKT1 as a Potential Regulator of genes involved in fatty
acid oxidation (MCAD) in Hepatocytes
36

We proceeded to scrutinize the expression patterns of Medium-Chain Acyl-CoA
Dehydrogenase (MCAD), a critical enzyme in the mitochondrial β-oxidation pathway of
medium-chain fatty acids[62]. The MCAD expression level in Akt1 knockout hepatocytes
increased by 24% when compared to the wild type hepatocytes, this change was not statistically
significant (Figure 6A). A similar pattern was noted in Akt2 knockout hepatocytes, which
showed an increased MCAD expression by 160% in comparison to their wild type counterparts,
however this change was statistically significant (p<0.05) (Figure 6B). This suggests an
enhanced fatty acid oxidation capacity in the absence of AKT2.

Figure 6 – RT-qPCR data for showing MCAD expression in hepatocytes A. MCAD expression
in Akt1 knockout hepatocytes as compared to wild type hepatocytes; B. MCAD expression in
AKT2 knockout hepatocytes in contrast with wild type hepatocytes showing statistically
significant increase (p=0.0274) in AKT2 knockout hepatocytes. Each expression level was
normalized to a housekeeping gene, with error bars representing the standard error of the mean
(SEM) from independent experiments.
6. Determination of the AKT Isoform Involved in the Regulation of genes involved in
Electron transport system (CYC) in Hepatocytes
We proceeded to scrutinize the expression patterns of Cytochrome C (CYC), an integral part
of the mitochondrial electron transport chain. In our analyses, it was observed that there was a
72% decrease in CYC expression levels in Akt1 knockout hepatocytes when contrasted with
37

the wild type counterparts (Figure 7A). A similar declining trend was discernible in Akt2
knockout hepatocytes, with a 74% reduction as compared to wild type hepatocytes (Figure 7B).
Though this reduction did reach a threshold of statistical significance, the magnitude of
downregulation is large, suggesting higher sample size maybe needed to validate this result.

Figure 7: RT-qPCR data for showing CYC expression in hepatocytes. A. CYC expression in
Akt1 knockout hepatocytes compared to wild type hepatocytes; B. CYC expression in AKT2
knockout hepatocytes compared to wild type hepatocytes. Each expression level was
normalized to a housekeeping gene, with error bars representing the standard error of the mean
(SEM) from independent experiments.
7. Determination of the AKT Isoform Involved in the Regulation of genes involved in
lipogenesis (ACC and FASn).
Turning to FASn, an enzyme instrumental in the synthesis of long-chain saturated fatty
acids[63], we observed a decreased expression in both the AKT1 and AKT2 knockout
hepatocytes compared to the wild-type counterparts (Figure 8A &B). The reduction of FASn
expression is 32% and 45% respectively for Akt1 and Akt2 deleted cells when compared with
the WT cells. This outcome implies a comparable impact of AKT1 and AKT2 knockouts on
FASn expression levels, suggesting a possibly shared regulatory function of the two AKT
isoforms on this key lipogenic enzyme. Although the observed reductions did not reach
38

statistical significance, the result is consistent with previous studies from our lab showing that
AKT indeed regulate the expression of FASn[63].

Figure 8: RT-qPCR data for showing FASN expression in hepatocytes. A. FASn expression in
Akt1 knockout hepatocytes compared to wild type hepatocytes; B. FASn expression in AKT2
knockout hepatocytes compared to wild type hepatocytes. Each expression level was
normalized to a housekeeping gene, with error bars representing the standard error of the mean
(SEM) from independent experiments.
ACC, a crucial enzyme catalysing the carboxylation of acetyl-CoA to malonyl-CoA[64], the
first and rate-limiting step in the biosynthesis of long-chain fatty acids, demonstrated a
relatively invariant expression pattern across all three cell lines. This uniformity in ACC
expression suggests a conserved role for this enzyme, which appears unaffected by the
knockout of Akt1 or Akt2 genes in both as compared to the wild type hepatocytes (Figure 9A&
B). The lack of changes observed for ACC expression across the experimental conditions
suggest that its regulation is possibly independent of its transcriptional regulation investigated
in this study. Indeed, ACC function is regulated by phosphorylation which is likely more
important for its function than its transcription regulation[65].
39

Figure 9: RT-qPCR data for showing ACC expression in hepatocytes A. ACC expression in
Akt1 knockout hepatocytes compared to wild type cells; B. ACC expression in AKT2 knockout
hepatocytes and wild type hepatocytes. Each expression level was normalized to a
housekeeping gene, with error bars indicating the standard error of the mean (SEM) from
independent experiments.
8. Determination of AKT Isoform Involved in the Regulation of PGC-1α
PGC-1α is a widely recognized transcriptional coactivator of ERRα and plays a pivotal role in
energy metabolism regulation[66]. The PGC-1α expression level in Akt1 knockout hepatocytes
exhibited an increase of 46% when compared to the wild type hepatocytes, however a statistical
significance was not observed (Figure 10A). Similar to the observed increased expression of
MCAD, a remarkable 360% increase of PGC-1α expression is observed in the Akt2 knockout
hepatocytes in comparison to their wild type counterparts (Figure 10B). However, a statistically
significance was not observed due to sample variations, though the statistical significance value
of P<0.09 was observed.
40

Figure 10- RT-qPCR data for showing PGC-1α expression in hepatocytes. A. PGC-1α
expression in Akt1 knockout hepatocytes as compared to wild type hepatocytes; B. PGC-1α
expression in AKT2 knockout hepatocytes in contrast with wild type hepatocytes showing
statistically significant at p=0.0867 in AKT2 knockout hepatocytes. Each expression level was
normalized to a housekeeping gene.
9. Exploring the role of AKT Isoforms in regulating expression of genes involved in
glycerolipid biosynthesis (GPAM, GPAT4 and DGAT1).
In the cellular context, GPAT4 and GPAM, also known as GPAT1, are integral mitochondrial
enzymes involved in TG synthesis. They catalyse the conversion of G3P to LPA, constituting
the initial and critical step in the biosynthetic pathway leading to TG formation. In the current
study, we employed RT-qPCR to analyse the expression of enzymes involved in the
glycerolipid biosynthesis pathway and found intriguing observations pertaining to their
relationship with AKTs. The RT-qPCR data unveiled that the mRNA levels of GPAT4
escalated in cells devoid of either Akt1 or Akt2. Specifically, GPAT4 transcript levels increased
by approximately 50% in Akt1 knockout cells and about 44% in Akt2 knockout cells compared
to their respective wild-type controls (Figure 11A &B). However, the data was not statistically
41

significant and therefore further analysis with a larger sample size should be made. Further, the
mRNA levels of GPAM were analysed in both Akt1 and Akt2 knockout cells. Contrary to the
pattern observed with GPAT4, the GPAM mRNA levels displayed a marked decrease in both
knockout models. In particular, an 84% decrease in the Akt1 knockout cells compared to the
wild-type control. A substantial reduction in GPAM expression was also noticed in Akt2
knockout cells, showing a 43% decrease relative to their respective controls (Figure 11C &D).

Figure 11- RT-qPCR data for showing GPAT4 and GPAM expression in hepatocytes. A.
GPAT4 expression in AKT1 knockout hepatocytes as compared to wild type hepatocytes; B.
GPAT4 expression in AKT2 knockout hepatocytes in contrast with wild type hepatocytes; C.
GPAM expression in Akt1 knockout hepatocytes as compared to wild type hepatocytes; B.
GPAM expression in AKT2 knockout hepatocytes in contrast with wild type hepatocytes. Each
expression level was normalized to a housekeeping gene.
The enzymes DGAT1 and DGAT2, are critical mediators in the conversion of DAG to TG, the
final step in TG synthesis. Given their pivotal role, we decided to scrutinize their mRNA
expression levels in both Akt1 and Akt2 knockout cells to further elucidate the nuanced roles
these AKT isoforms might play in lipid metabolism. Starting with DGAT2, we observed a
distinct upregulation in its expression in both Akt1 and Akt2 knockout cells. Specifically, there
was a striking 106% increase in DGAT2 mRNA levels in Akt1 knockout hepatocytes compared
to their wild-type counterparts (Figure 12A). Similarly, albeit to a lesser extent, we saw a
42

substantial 34% increase in DGAT2 expression in Akt2 knockout hepatocytes relative to the
control group (Figure 12B). On the other hand, the analysis of DGAT1 mRNA levels yielded
contrasting results. Unlike DGAT2, the expression of DGAT1 was found to decrease in both
knockout models, however the decrease was not statistically significant. In Akt1 knockout
hepatocytes, we observed a substantial 63% reduction in DGAT1 mRNA levels relative to the
wild-type control (Figure 12C). In Akt2 knockout hepatocytes, the reduction was somewhat
less pronounced, yet significant, showing a 42% decrease compared to their respective controls
(Figure 12D).

Figure 12- RT-qPCR data for showing DGAT2 & DGAT1 expression in hepatocytes. A.
DGAT2expression in AKT1 knockout hepatocytes as compared to wild type hepatocytes; B.
DGAT2 expression in AKT2 knockout hepatocytes in contrast with wild type hepatocytes; C.
DGAT1expression in Akt1 knockout hepatocytes as compared to wild type hepatocytes; B.
DGAT1 expression in AKT2 knockout hepatocytes in contrast with wild type hepatocytes.
Each expression level was normalized to a housekeeping gene.

43

Chapter IV- Discussion
The ERR family of orphan nuclear receptors are transcriptional activators for genes involved
in mitochondrial bioenergetics and metabolism[67]. Chen et al, found that inhibition of ERRα
blocked NAFLD development induced by either high-carbohydrate diet or high-fat diet
feeding. ERRα inhibition also diminished lipid accumulation and attenuated NASH
development in the Pten null mice[57]. Moreover, glycerolipid synthesis was discovered as an
additional mechanism for ERRα-regulated NAFLD/NASH development and it was
hypothesized that glycerophosphate acyltransferase 4 which is an enzyme involved in the
glycerolipid pathway could be a novel transcriptional target of ERRα[57]. It was further
suggested that in Pten deleted mice the PI3K/AKT pathway causes upregulation of ERRα[57],
therefore it would be interesting to understand which AKT isoform is upstream of ERRα and
the genes involved in lipid metabolism.
In this study, the objective was to validate whether ERRα transcriptionally regulates GPAT4
as well as investigate which AKT isoform is upstream of ERRα and the genes regulated by it.
For this purpose, we prepared a GPAT4-tdTomato promoter construct to study the regulation
of glycerolipid biosynthesis by the transcriptional activity of ERRα. The GPAT4-tdTomato
promoter plasmid was transfected in Huh7 cells and the shERRα Huh7 cells to assess the effect
of ERRα knockdown on the transcriptional activity of the GPAT4 promoter. Florescence
microscopy, RT-qPCR and flow cytometry analysis showed more expression of GPAT4
promoter in Huh7 cells as compared to shERRα Huh7 cells. This provides support that the
presence of ERRα regulates the induces the transcription of GPAT4, suggesting that an
amplified activity of the ERRα may increase the levels and activities of GPAT4. As GPAT4 is
the rate limiting enzyme of TG biosynthesis, the regulation of GPAT4 by ERRα may promote
the biosynthesis of TGs. Such a surge in TG formation would ultimately lead to lipid
accumulation, potentially contributing to lipid-associated metabolic disorders like NAFLD.
44

Insulin exerts its influence on lipid and glucose metabolism through its cell surface receptor
and intracellular signalling mediators such as PI3K and serine-threonine kinase AKT[59]. In
the liver, liver-specific Pten deletion leads to increased hepatic insulin signal, resulting in
improved systemic glucose tolerance[59]. Notably, the deletion of Pten in the liver also led to
increase fatty acid synthesis, resulting in hepatomegaly and a fatty liver phenotype[59]. This
suggests that increased insulin signalling prompts the activation of AKT, which, in turn,
facilitates glucose uptake by hepatocytes[59]. Inhibiting ERRα prevented the development of
NAFLD in these mice as well as in mice fed a high-carbohydrate or a high-fat diet, showing a
direct signalling regulation of ERRα by PTEN/AKT[57]. Here my data indicates that AKT2
but not AKT1 may be responsible for the increase in expression of ERRα. Previous studies
from our lab showed that the elevated levels of ERRα stimulate excessive fatty acid synthesis,
and maybe responsible for the lipid accumulation observed with PTEN loss[57]. Our data here
showing that ERRα may only regulate the AKT2 mediated lipogenesis signals since loss of
either AKT1 or AKT2 leads to reduced expression of FASn but only AKT2 regulates ERRα.
PGC-1α promotes gluconeogenesis and fatty acid oxidation and also serve as a coactivator for
a number of nuclear transcription factors and is proposed to be a major moderator for metabolic
signals[68]. AKT elicits the phosphorylation and inhibition of PGC-1α[68]. Phosphorylation
has been shown to prevents the recruitment of PGC-1α to the cognate promoter region of genes
involved in hepatic metabolism, impairing its ability to promote gluconeogenesis and fatty acid
oxidation[68]. Hence, it was concluded that insulin antagonizes the actions of PGC-1α by Akt-
dependent phosphorylation. Here, my data showed that AKT2 also negatively regulates the
transcription of PGC-1α, since the mRNA levels show that there is higher expression of PGC-
1α when Akt2 is knocked out. This upregulated PGC-1α is concurrent with the induced
expression of MCAD in the Akt2 knockout cells. In hepatocytes void of both PTEN and AKT2,
hepatic lipid accumulation appeared to be significantly lower compared with Pten deleted cells
45

alone[68]. Previous work has attributed this lipid reduction phenotype to the functions of AKT
on de novo lipogenesis[29]. Our observation of the concurrent induction of PGC-1α and
MCAD suggests an acceleration fatty acid oxidation in the Akt2 deleted hepatocytes. Thus, the
induction of fatty acid oxidation, resulting from AKT2 loss, may also contribute to the reduced
lipid accumulation in the double mutant mice vs. Pten deleted mice.
PGC-1α is a nuclear coactivator of ERRα that also transcriptionally regulates ERRα
expression. It was reported that both mRNA and protein levels of PGC-1α was induced in Pten-
null hepatocytes versus wild type hepatocytes[68]. Our lab reported previously that siRNA-
mediated PGC-1α knockdown led to reduced ERRα expression in the Pten-null hepatocytes,
suggesting that PGC-1α mediated induction of ERRα transcription may play a role in the
accumulation of ERRα when PTEN is lost[60]. Our experimental data, however, introduces an
intriguing hypothesis that AKT2 may independently regulate ERRα and PGC-1α. We observed
here that the expression of PGC-1α was significantly higher in Akt2 knockout than that
observed in wild-type hepatocytes even though ERRα expression is reduced. One potential
explanation is a feedback mechanism where PGC-1α might be induced to compensate for the
loss of ERRα in response to AKT2 deficiency. Furthermore, despite AKT2 being absent in the
knockout cells, ERRα expression levels did not plummet dramatically as might have been
expected. We propose that this could be due to a modulatory influence of PGC-1α which acts
as a coactivator for ERRα may partially compensate for the loss of AKT2 in maintaining ERRα
expression. How PGC-1α is induced in the absence of AKT2, though, needs further
investigation. Our observation, however, indeed suggests that PGC-1α assumes a more
prominent role in metabolism with or without the activation of ERRα when AKT2 is absent.
The nuances of this feedback loop and its overall implications on lipid metabolism certainly
warrant further investigation.
46

Further, the expression of both GPAM and DGAT1 are reduced in cells lacking AKTs,
consistent with the observed downregulation of ERRα in Akt2 deleted hepatocytes. In addition,
C/EBP is also recognized for its role in transcriptionally regulating GPAM and DGAT1. The
AKT1 regulated downregulations in these genes are likely attributed to the regulation by
C/EBP as ERRα expression was not altered as a result of AKT1 loss. Unlike GPAM and
DGAT1, an unexpected increase of GPAT4 expression is observed in hepatocytes lacking
either AKT2 orAKT1. One plausible explanation for this counterintuitive finding might lie in
the role of the coactivator PGC-1α. It is plausible that PGC-1α, which is known to activate
ERRα, might still drive the transcriptional activity of ERRα on select target genes even though
levels of ERRα is low. Thus, despite the reduced overall levels of ERRα, this activation might
still be sufficient to drive the upregulation of GPAT4. This hypothesis provides an interesting
perspective on the possible feedback mechanisms at play in the context of AKT isoform
absence. Further investigations are necessary to understand the full scope of these
interdependent relationships and their implications for lipid metabolism regulation. Notably,
an increase in DGAT2 expression was also observed, but only in Akt1 but not Akt2 knockout
hepatocytes. The specific mechanisms for these isoforms’ specific regulation of GPAT4 and
DGAT2 by AKTs needs to be further explored. The GPAT4-tdTomato promoter construct is
designed to help us further interrogate these AKT isoform specific regulation of glycerolipid
biosynthesis genes.
Collectively, our data illuminates the potential isoform-specific roles of AKT in modulating
gene expressions involved in lipid metabolism. It has been noted previously that AKT2 is
traditionally perceived to have a dominant role in managing genes associated with lipid
metabolism and AKT1 commonly associated with cell proliferation and differentiation[69].
However, a metabolic role of AKT1 is not excluded especially given the functions of AKTs
and their potential roles in tumor metabolism. Our data here begin to explore the AKT isoform
47

specific roles on lipid metabolism pathways. These unique findings, warrant further
exploration to comprehensively delineate their roles and interactions. This study endeavours to
discern the unique roles of AKT isoforms in modulating ERRα and ERRα regulated
metabolism and provide deeper insights into the signalling pathways implicated in the
development of fatty liver disease and cancer. Achieving a comprehensive understanding of
AKT's functionalities can illuminate potential therapeutic avenues for effectively treating these
diseases.

48

Chapter V- Troubleshooting
The observations with fluorescence microscopy were accompanied by a considerable degree
of autofluorescence, characterized by sporadic, irregular signals that did not correspond to
cellular structures. Autofluorescence is the natural emission of light by biological structures,
may possibly hamper fluorescence-based techniques if not properly addressed and corrected
for[70]. Several endogenous fluorophores are known to cause autofluorescence in many
tissues, including liver[71].
Prompted by this unexpected observation, we designed an experiment to identify the source of
this autofluorescence. The experiment utilized a six-well plate, where two wells hosted the two
cell lines (Huh7 and shERRa Huh7), another held Dulbecco's Modified Eagle Medium
(DMEM), one well was filled with media that had been passed through a 0.25-micron sieve,
effectively ultra-filtering it, and the last well was kept empty. Upon inspection, we observed
autofluorescence in the wells housing cell lines but not in the empty well or the well containing
only the medium. This observation pointed to the cells as the probable source of
autofluorescence. To further comprehend this phenomenon, we turned to the scientific
literature and identified lipofuscin as a potential contributor to this autofluorescence.
Lipofuscin, often termed the "wear-and-tear pigment," is an intracellular substance known to
accumulate in various cell types, including hepatocytes[72]. The fluorescent properties of this
pigment could have accounted for the significant autofluorescence we observed in our study.
Due to its broad excitation and emission spectra its presence complicates the use of techniques
employing exogenous fluorophores[71]. While most endogenous fluorophores have distinct
spectral emission profiles, the spectra of lipofuscin overlap those of all commonly used
exogenous fluorophores[71]. This makes it difficult or even impossible to distinguish between
specific labelling and autofluorescence caused by lipofuscin. The pretreatment with a
49

lipofuscin autofluorescence quencher like TrueBlack or Sudan Black would allow better results
from fluorescence microscopy[71].
The combined use of RT-qPCR and flow cytometry not only offers a more robust, multi-
layered approach to characterizing gene expression, but also supports the validity of our
hypothesis concerning the role of ERRα in regulating GPAT4 promoter activity. Our findings
serve as a testament to the benefits of employing an array of complementary techniques in
biological research, ensuring the generation of comprehensive and reliable data. Such an
approach can mitigate the potential for misinterpretation of results owing to confounding
factors like autofluorescence.

50

Chapter VI- Bibliography
[1] D. H. Fernando, J. M. Forbes, P. W. Angus, and C. B. Herath, “Development and
progression of non-alcoholic fatty liver disease: The role of advanced glycation end
products,” Int. J. Mol. Sci., vol. 20, no. 20, 2019, doi: 10.3390/ijms20205037.
[2] J. J. Pan and M. B. Fallon, “Gender and racial differences in nonalcoholic fatty liver
disease,” World J. Hepatol., vol. 6, no. 5, pp. 274–283, 2014, doi:
10.4254/wjh.v6.i5.274.
[3] B. J. Perumpail, M. A. Khan, E. R. Yoo, G. Cholankeril, D. Kim, and A. Ahmed,
“Clinical epidemiology and disease burden of nonalcoholic fatty liver disease,” World
J. Gastroenterol., vol. 23, no. 47, pp. 8263–8276, 2017, doi: 10.3748/wjg.v23.i47.8263.
[4] Q. Li, L. Wang, J. Wu, J. Wang, Y. Wang, and X. Zeng, “Role of age, gender and
ethnicity in the association between visceral adiposity index and non-alcoholic fatty
liver disease among US adults (NHANES 2003-2018): Cross-sectional study,” BMJ
Open, vol. 12, no. 3, 2022, doi: 10.1136/bmjopen-2021-058517.
[5] V. Natesan and S. J. Kim, “Lipid metabolism, disorders and therapeutic drugs –
Review,” Biomol. Ther., vol. 29, no. 6, pp. 596–604, 2021, doi:
10.4062/biomolther.2021.122.
[6] N. S. Alekos, M. C. Moorer, and R. C. Riddle, “Dual Effects of Lipid Metabolism on
Osteoblast Function,” Front. Endocrinol. (Lausanne)., vol. 11, no. September, pp. 1–15,
2020, doi: 10.3389/fendo.2020.578194.
[7] D. Gyamfi, E. O. Awuah, and S. Owusu, Lipid metabolism: An overview. Elsevier Inc.,
2018.
[8] K. R. Feingold, “Lipid and Lipoprotein Metabolism,” Endocrinol. Metab. Clin. North
Am., vol. 51, no. 3, pp. 437–458, 2022, doi: 10.1016/j.ecl.2022.02.008.
[9] A. Nsiah-Sefaa and M. McKenzie, “Combined defects in oxidative phosphorylation and
fatty acid β-oxidation in Mitochondrial disease,” Biosci. Rep., vol. 36, no. 2, 2016, doi:
10.1042/BSR20150295.
[10] P. Aggarwal, T. Singh, and N. Alkhouri, “Metabolic Targets in Nonalcoholic
Steatohepatitis: Treating the Disease at the Metabolic Root,” Curr. Hepatol. Reports,
vol. 19, no. 3, pp. 302–314, 2020, doi: 10.1007/s11901-020-00533-x.
[11] J. Yu, K. Loh, Z. Y. Song, H. Q. Yang, Y. Zhang, and S. Lin, “Update on glycerol-3-
phosphate acyltransferases: The roles in the development of insulin resistance,” Nutr.
Diabetes, vol. 8, no. 1, 2018, doi: 10.1038/s41387-018-0045-x.
[12] G. Monroy, F. H. Rola, and M. E. Pullman, “A substrate- and position-specific acylation
of sn-glycerol 3-phosphate by rat liver mitochondria.,” J. Biol. Chem., vol. 247, no. 21,
pp. 6884–6894, 1972, doi: 10.1016/s0021-9258(19)44668-1.
[13] K. Takeuchi and K. Reue, “Biochemistry, physiology, and genetics of GPAT, AGPAT,
and lipin enzymes in triglyceride synthesis,” Am. J. Physiol. - Endocrinol. Metab., vol.
51

296, no. 6, 2009, doi: 10.1152/ajpendo.90958.2008.
[14] A. Yamashita et al., “Glycerophosphate/Acylglycerophosphate acyltransferases,”
Biology (Basel)., vol. 3, no. 4, pp. 801–830, 2014, doi: 10.3390/biology3040801.
[15] H. Xu et al., “Hepatic knockdown of mitochondrial GPAT1 in ob/ob mice improves
metabolic profile,” Biochem. Biophys. Res. Commun., vol. 349, no. 1, pp. 439–448,
2006, doi: 10.1016/j.bbrc.2006.08.071.
[16] L. E. Hammond et al., “Mitochondrial Glycerol-3-Phosphate Acyltransferase-Deficient
Mice Have Reduced Weight and Liver Triacylglycerol Content and Altered Glycerolipid
Fatty Acid Composition,” Mol. Cell. Biol., vol. 22, no. 23, pp. 8204–8214, 2002, doi:
10.1128/mcb.22.23.8204-8214.2002.
[17] C. A. Nagle et al., “Hepatic overexpression of glycerol-sn-3-phosphate acyltransferase
1 in rats causes insulin resistance,” J. Biol. Chem., vol. 282, no. 20, pp. 14807–14815,
2007, doi: 10.1074/jbc.M611550200.
[18] A. A. Wendel, D. E. Cooper, O. R. Ilkayeva, D. M. Muoio, and R. A. Coleman,
“Glycerol-3-phosphate acyltransferase (GPAT)-1, but not GPAT4, incorporates newly
synthesized fatty acids into triacylglycerol and diminishes fatty acid oxidation,” J. Biol.
Chem., vol. 288, no. 38, pp. 27299–27306, 2013, doi: 10.1074/jbc.M113.485219.
[19] M. R. Gonzalez-Baró, T. M. Lewin, and R. A. Coleman, “Regulation of Triglyceride
Metabolism II. Function of mitochondrial GPAT1 in the regulation of triacylglycerol
biosynthesis and insulin action,” Am. J. Physiol. - Gastrointest. Liver Physiol., vol. 292,
no. 5, pp. 1195–1199, 2007, doi: 10.1152/ajpgi.00553.2006.
[20] Q. C. Yan et al., “AGPAT6 is a novel microsomal glycerol-3-phosphate
acyltransferase,” J. Biol. Chem., vol. 283, no. 15, pp. 10048–10057, 2008, doi:
10.1074/jbc.M708151200.
[21] J. Cao, J. A. Li, D. Li, J. F. Tobin, and R. E. Gimeno, “Molecular identification of
microsomal acyl-CoA:glycerol-3-phosphate acyltransferase, a key enzyme in de novo
triacylglycerol synthesis,” Proc. Natl. Acad. Sci. U. S. A., vol. 103, no. 52, pp. 19695–
19700, 2006, doi: 10.1073/pnas.0609140103.
[22] J. Cao et al., “Mice deleted for GPAT3 have reduced GPAT activity in white adipose
tissue and altered energy and cholesterol homeostasis in diet-induced obesity,” Am. J.
Physiol. - Endocrinol. Metab., vol. 306, no. 10, pp. 1176–1187, 2014, doi:
10.1152/ajpendo.00666.2013.
[23] D. Shan et al., “GPAT3 and GPAT4 are regulated by insulin-stimulated phosphorylation
and play distinct roles in adipogenesis,” J. Lipid Res., vol. 51, no. 7, pp. 1971–1981,
2010, doi: 10.1194/jlr.M006304.
[24] R. W. A. Mackenzie and B. T. Elliott, “Akt/PKB activation and insulin signaling: A
novel insulin signaling pathway in the treatment of type 2 diabetes,” Diabetes, Metab.
Syndr. Obes., vol. 7, pp. 55–64, 2014, doi: 10.2147/DMSO.S48260.
[25] L. Y. Tian, D. J. Smit, and M. Jücker, “The Role of PI3K/AKT/mTOR Signaling in
Hepatocellular Carcinoma Metabolism,” Int. J. Mol. Sci., vol. 24, no. 3, 2023, doi:
52

10.3390/ijms24032652.
[26] F. Molinari and M. Frattini, “Functions and regulation of the PTEN gene in colorectal
cancer,” Front. Oncol., vol. 4 JAN, no. January, pp. 1–8, 2014, doi:
10.3389/fonc.2013.00326.
[27] A. Basu and C. B. Lambring, “Akt isoforms: A family affair in breast cancer,” Cancers
(Basel)., vol. 13, no. 14, 2021, doi: 10.3390/cancers13143445.
[28] P. R. Somanath, O. V. Razorenova, J. Chen, and T. V. Byzova, “Akt1 in endothelial cell
and angiogenesis,” Cell Cycle, vol. 5, no. 5, pp. 512–518, 2006, doi:
10.4161/cc.5.5.2538.
[29] L. He et al., “The critical role of AKT2 in hepatic steatosis induced by PTEN loss,” Am.
J. Pathol., vol. 176, no. 5, pp. 2302–2308, 2010, doi: 10.2353/ajpath.2010.090931.
[30] K. F. Leavens, R. M. Easton, G. I. Shulman, S. F. Previs, and M. J. Birnbaum,
“resistance,” vol. 10, no. 5, pp. 405–418, 2010, doi: 10.1016/j.cmet.2009.10.004.Akt2.
[31] I. Hers, E. E. Vincent, and J. M. Tavaré, “Akt signalling in health and disease,” Cell.
Signal., vol. 23, no. 10, pp. 1515–1527, 2011, doi: 10.1016/j.cellsig.2011.05.004.
[32] C. L. Dai, J. Shi, Y. Chen, K. Iqbal, F. Liu, and C. X. Gong, “Inhibition of protein
synthesis alters protein degradation through activation of protein kinase B (AKT),” J.
Biol. Chem., vol. 288, no. 33, pp. 23875–23883, 2013, doi: 10.1074/jbc.M112.445148.
[33] R. M. Easton et al., “Role for Akt3/Protein Kinase Bγ in Attainment of Normal Brain
Size,” Mol. Cell. Biol., vol. 25, no. 5, pp. 1869–1878, 2005, doi:
10.1128/mcb.25.5.1869-1878.2005.
[34] O. Tschopp et al., “Essential role of protein kinase Bγ (PKBγ/Akt3) in postnatal brain
developmental but not in glucose homeostasis,” Development, vol. 132, no. 13, pp.
2943–2954, 2005, doi: 10.1242/dev.01864.
[35] Z. Zhang, H. Liu, and J. Liu, “Akt activation: A potential strategy to ameliorate insulin
resistance,” Diabetes Res. Clin. Pract., vol. 156, p. 107092, 2019, doi:
10.1016/j.diabres.2017.10.004.
[36] A. Alwhaibi, A. Verma, M. S. Adil, and P. R. Somanath, “The unconventional role of
Akt1 in the advanced cancers and in diabetes-promoted carcinogenesis,” Pharmacol.
Res., vol. 145, no. November 2018, p. 104270, 2019, doi: 10.1016/j.phrs.2019.104270.
[37] Y. Fu et al., “Lipid metabolism in cancer progression and therapeutic strategies,”
MedComm, vol. 2, no. 1, pp. 27–59, 2021, doi: 10.1002/mco2.27.
[38] T. Atsumi, “Diabetes and risk of cancer,” Diabetol. Int., vol. 6, no. 3, pp. 190–192, 2015,
doi: 10.1007/s13340-015-0227-x.
[39] A. Aggarwal et al., “Clinical & immunological erythematosus patients characteristics in
systemic lupus Maryam,” J. Dent. Educ., vol. 76, no. 11, pp. 1532–9, 2012, doi:
10.4103/ijmr.IJMR.
53

[40] S. Matsuda, M. Kobayashi, and Y. Kitagishi, “Roles for PI3K/AKT/PTEN Pathway in
Cell Signaling of Nonalcoholic Fatty Liver Disease,” ISRN Endocrinol., vol. 2013, no.
Figure 1, pp. 1–7, 2013, doi: 10.1155/2013/472432.
[41] C. Lankatillake, T. Huynh, and D. A. Dias, “Understanding glycaemic control and
current approaches for screening antidiabetic natural products from evidence-based
medicinal plants,” Plant Methods, vol. 15, no. 1, pp. 1–35, 2019, doi: 10.1186/s13007-
019-0487-8.
[42] X. Xu, J. S. So, J. G. Park, and A. H. Lee, “Transcriptional control of hepatic lipid
metabolism by SREBP and ChREBP,” Semin. Liver Dis., vol. 33, no. 4, pp. 301–311,
2013, doi: 10.1055/s-0033-1358523.
[43] Z. Fatehi-Hassanabad and C. B. Chan, “Transcriptional regulation of lipid metabolism
by fatty acids: A key determinant of pancreatic β-cell function,” Nutr. Metab., vol. 2,
pp. 1–12, 2005, doi: 10.1186/1743-7075-2-1.
[44] J. D. Horton, J. L. Goldstein, and M. S. Brown, “SREBPs: Activators of the complete
program of cholesterol and fatty acid synthesis in the liver,” J. Clin. Invest., vol. 109,
no. 9, pp. 1125–1131, 2002, doi: 10.1172/JCI0215593.
[45] D. Eberlé, B. Hegarty, P. Bossard, P. Ferré, and F. Foufelle, “SREBP transcription
factors: Master regulators of lipid homeostasis,” Biochimie, vol. 86, no. 11, pp. 839–
848, 2004, doi: 10.1016/j.biochi.2004.09.018.
[46] R. Ventura-Clapier, A. Garnier, and V. Veksler, “Transcriptional control of
mitochondrial biogenesis: The central role of PGC-1α,” Cardiovasc. Res., vol. 79, no.
2, pp. 208–217, 2008, doi: 10.1093/cvr/cvn098.
[47] B. Staels, “Regulation of lipid and lipoprotein metabolism by retinoids,” J. Am. Acad.
Dermatol., vol. 45, no. 5, pp. 3–11, 2001, doi: 10.1067/mjd.2001.113718.
[48] S. Tyagi, P. Gupta, A. Saini, C. Kaushal, and S. Sharma, “The peroxisome proliferator-
activated receptor: A family of nuclear receptors role in various diseases,” J. Adv.
Pharm. Technol. Res., vol. 2, no. 4, pp. 236–240, 2011, doi: 10.4103/2231-4040.90879.
[49] T. Å. Pedersen et al., “Distinct C/EBPα motifs regulate lipogenic and gluconeogenic
gene expression in vivo,” EMBO J., vol. 26, no. 4, pp. 1081–1093, 2007, doi:
10.1038/sj.emboj.7601563.
[50] S. Satoh et al., “Ribavirin-induced down-regulation of CCAAT/ enhancer-binding
protein α leads to suppression of lipogenesis,” Biochem. J., vol. 476, no. 1, pp. 137–149,
2019, doi: 10.1042/BCJ20180680.
[51] V. A. Payne et al., “UKPMC Funders Group Author Manuscript UKPMC Funders
Group Author Manuscript SEQUENTIAL REGULATION OF DGAT2 EXPRESSION
BY C / EBP β AND C / EBP α DURING ADIPOGENESIS,” vol. 282, no. 29, pp.
21005–21014, 2008.
[52] K. Iizuka, K. Takao, and D. Yabe, “ChREBP-Mediated Regulation of Lipid
Metabolism: Involvement of the Gut Microbiota, Liver, and Adipose Tissue,” Front.
Endocrinol. (Lausanne)., vol. 11, no. December, pp. 1–10, 2020, doi:
54

10.3389/fendo.2020.587189.
[53] A. Tremblay, Transcriptional Regulation by the Estrogen-Related Receptors, no.
November. 2009.
[54] V. Giguère, “Transcriptional control of energy homeostasis by the estrogen-related
receptors,” Endocr. Rev., vol. 29, no. 6, pp. 677–696, 2008, doi: 10.1210/er.2008-0017.
[55] L. Chaltel-Lima, F. Domínguez, L. Domínguez-Ramírez, and P. Cortes-Hernandez,
“The Role of the Estrogen-Related Receptor Alpha (ERRa) in Hypoxia and Its
Implications for Cancer Metabolism,” Int. J. Mol. Sci., vol. 24, no. 9, 2023, doi:
10.3390/ijms24097983.
[56] H. Xia, C. R. Dufour, and V. Giguère, “ERRα as a bridge between transcription and
function: Role in liver metabolism and disease,” Front. Endocrinol. (Lausanne)., vol.
10, no. APR, pp. 1–13, 2019, doi: 10.3389/fendo.2019.00206.
[57] C. yu Chen et al., “Inhibition of Estrogen-Related Receptor α Blocks Liver Steatosis and
Steatohepatitis and Attenuates Triglyceride Biosynthesis,” Am. J. Pathol., vol. 191, no.
7, pp. 1240–1254, 2021, doi: 10.1016/j.ajpath.2021.04.007.
[58] B. Hua, I. Slarve, A. A. Datta, C. Xu, C. Chen, and B. L. Stiles, “Transcriptional
Regulation by ERR and Its Role in NAFLD Pathogenesis,” in Non-alcoholic Fatty Liver
Disease, J.-S. Kang, Ed. Rijeka: IntechOpen, 2023.
[59] B. Stiles et al., “Live-specific deletion of negative regulator Pten results in fatty liver
and insulin hypersensitivity,” Proc. Natl. Acad. Sci. U. S. A., vol. 101, no. 7, pp. 2082–
2087, 2004, doi: 10.1073/pnas.0308617100.
[60] Y. Li et al., “Phosphatase and tensin homolog deleted on chromosome 10 (PTEN)
signaling regulates mitochondrial biogenesis and respiration via estrogen-related
receptor α (ERRα),” J. Biol. Chem., vol. 288, no. 35, pp. 25007–25024, 2013, doi:
10.1074/jbc.M113.450353.
[61] A. F. Fradkov, Y. Chen, L. Ding, E. V. Barsova, M. V. Matz, and S. A. Lukyanov,
“Novel fluorescent protein from Discosoma coral and its mutants possesses a unique
far-red fluorescence,” FEBS Lett., vol. 479, no. 3, pp. 127–130, 2000, doi:
10.1016/S0014-5793(00)01895-0.
[62] V. Gartner, P. J. McGuire, and P. R. Lee, “Child Neurology: Medium-chain acyl-
coenzyme A dehydrogenase deficiency,” Neurology, vol. 85, no. 4, pp. e37–e40, 2015,
doi: 10.1212/WNL.0000000000001786.
[63] C. W. Fhu and A. Ali, “Fatty Acid Synthase: An Emerging Target in Cancer,”
Molecules, vol. 25, no. 17, pp. 1–22, 2020, doi: 10.3390/molecules25173935.
[64] Y. Wang, W. Yu, S. Li, D. Guo, J. He, and Y. Wang, “Acetyl-CoA Carboxylases and
Diseases,” Front. Oncol., vol. 12, no. March, pp. 1–10, 2022, doi:
10.3389/fonc.2022.836058.
[65] J. Wei et al., “A unified molecular mechanism for the regulation of acetyl-CoA
carboxylase by phosphorylation,” Cell Discov., vol. 2, pp. 1–12, 2016, doi:
55

10.1038/celldisc.2016.44.
[66] H. Liang and W. F. Ward, “PGC-1α: A key regulator of energy metabolism,” Am. J.
Physiol. - Adv. Physiol. Educ., vol. 30, no. 4, pp. 145–151, 2006, doi:
10.1152/advan.00052.2006.
[67] J. A. Villena and A. Kralli, “ERRα: a metabolic function for the oldest orphan,” Trends
Endocrinol. Metab., vol. 19, no. 8, pp. 269–276, 2008, doi: 10.1016/j.tem.2008.07.005.
[68] X. Li, B. Monks, Q. Ge, and M. J. Birnbaum, “Akt/PKB regulates hepatic metabolism
by directly inhibiting PGC-1α transcription coactivator,” Nature, vol. 447, no. 7147, pp.
1012–1016, 2007, doi: 10.1038/nature05861.
[69] R. Miao, X. Fang, J. Wei, H. Wu, X. Wang, and J. Tian, “Akt: A Potential Drug Target
for Metabolic Syndrome,” Front. Physiol., vol. 13, no. March, 2022, doi:
10.3389/fphys.2022.822333.
[70] A. C. Croce and G. Bottiroli, “Autofluorescence spectroscopy and imaging: A tool for
biomedical research and diagnosis,” Eur. J. Histochem., vol. 58, no. 4, pp. 320–337,
2014, doi: 10.4081/ejh.2014.2461.
[71] A. K. Larsen et al., “Autofluorescence in freshly isolated adult human liver sinusoidal
cells,” Eur. J. Histochem., vol. 65, no. 4, pp. 1–6, 2021, doi: 10.4081/ejh.2021.3337.
[72] E. Marani, K. G. Usunoff, and H. K. P. Feirabend, “Lipofuscin and Lipofuscinosis,”
Encycl. Neurosci., pp. 481–486, 2009, doi: 10.1016/B978-008045046-9.00126-1.
[71] Images Created with BioRender.com

Abstract (if available)

Abstract The transcriptional network regulated by the estrogen-related receptor alpha (ERRα) plays a pivotal role in governing the expression of numerous genes associated with mitochondrial respiratory complexes and metabolic enzymes that are integral to lipid and glucose metabolisms. This study intends to explore the transcriptional regulation of Glycerol-3- phosphate acyltransferases 4 (GPAT4), a rate-limiting enzyme catalysing the initial step in triglyceride (TG) biosynthesis, by ERRα. Our lab's previous research found that the downregulation of ERRα led to a global reduction in the expression of essential enzymes for TG biosynthesis in siERRα-treated Huh7 hepatocytes. Furthermore, GPAT4 has been identified as a potential novel transcriptional target of ERRα. In this study, we aim to develop tools to explore the mechanism of this regulation. Moreover, this study sought to identify the specific AKT isoform upstream of ERRα in the PI3K/AKT pathway and to determine which AKT isoform regulates ERRα and ERRα regulated genes involved in lipid metabolism and the glycerolipid pathway. This endeavour provides a comprehensive understanding for how PI3K/AKT pathway regulates lipid metabolism.
These investigations have significant implications for our understanding of metabolic disorders. Deregulation in any of the processes examined in this study can lead to lipid accumulation, resulting in fatty liver disease and non-alcoholic fatty liver disease (NAFLD), which can further progress to liver cancer. Therefore, elucidating these pathways could pave the way for novel therapeutic strategies to combat these conditions.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

The regulation of fatty acid oxidation by estrogen related receptor alpha

PDF

AKT exhibits isoform-specific function in hepatocyte transformation and response to cellular stress

PDF

Regulation of mitochondrial bioenergetics via PTEN (phosphatase and tensin homolog deleted on chromosome 10)/estrogen-related receptor alpha (ERRα) signaling

PDF

Phosphatase and tensin homolog deleted on chromosome 10 (PTEN) signaling regulates fatty acid beta-oxidation

PDF

Downregulation of osteopontin by PTEN in liver-specific Pten-null mouse model

PDF

Neuronal and glial metabolic alterations in the liver-specific PTEN knockout mouse model

PDF

PI3K/AKT signaling and the regulation of the mitochondrial energy-redox axis

PDF

Akt1 deletion decrease proliferation in aged pancreatic beta-cells by arresting cell cycle in S phase

PDF

Protein kinase Bα (AKT1) but not protein kinase Bβ (AKT2) controls pancreatic β cell growth and survival

PDF

Role of the NF-κB-CXCL1 signaling pathway in the development of metabolic dysfunction-associated steatohepatitits

PDF

Maf1 is a novel target of the tumor suppressor PTEN and a negative regulator of lipid metabolism

PDF

Adaptive metabolic strategies of Mycobacterium tuberculosis to combat stress from antibiotics and ROS

PDF

Downregulation of METTL7A gene in liver-specific Pten-null mouse model

PDF

Role of steroidogenic acute regulatory protein (STAR) and sterol carrier protein-x (SCPx) in the transport of cholesterol and other lipids

PDF

Nuclear respiratory factor-1 regulation by PTEN signaling

PDF

The regulation of the expression of MRP2 in vivo

PDF

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

PDF

Inhibition of NR3B1 attenuates the progression of NAFLD and NASH in liver-specific Pten knockout mice

PDF

The role of estrogen-related receptor alpha (NR3B1) in nonalcoholic fatty liver diseases

PDF

Eicosanoid regulation of spermatogonial stem cell development

Asset Metadata

Creator Datta, Aditi Ashish (author)

Core Title Transcriptional regulation of lipid metabolism and exploring the specific roles of AKT isoforms

School School of Pharmacy

Degree Master of Science

Degree Program Molecular Pharmacology and Toxicology

Degree Conferral Date 2023-08

Publication Date 08/04/2023

Defense Date 08/04/2023

Publisher University of Southern California. Libraries (digital)

Tag AKT,estrogen-related receptor alpha,glycerol-3- phosphate acyltransferases 4,glycerolipid pathway,lipid metabolism,non-alcoholic fatty liver disease,OAI-PMH Harvest,triglycerides

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Stiles, Bangyan (committee chair), Culty, Martine (committee member), Zaro, Jennica (committee member)

Creator Email dattaa@usc.edu,dattaaditi2@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113296394

Unique identifier UC113296394

Identifier etd-DattaAditi-12200.pdf (filename)

Legacy Identifier etd-DattaAditi-12200

Document Type Thesis

Rights Datta, Aditi Ashish

Internet Media Type application/pdf

Type texts

Source 20230807-usctheses-batch-1079 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA

Repository Email cisadmin@lib.usc.edu