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Polarization of microglia by sodium butyrate in Alcohol Use Disorder

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Polarization of microglia by sodium butyrate in Alcohol Use Disorder

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Content POLARIZATION OF MICROGLIA BY SODIUM BUTYRATE IN ALCOHOL
USE DISORDER
By
Surabhi Vasisht
PI: Dr. Liana Asatryan
A Dissertation Presented to the
FACULTY OF THE USC ALFRED E.MANN SCHOOL OF PHARMACY
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF SCIENCE
(PHARMACEUTICAL SCIENCES)
May 2024

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ACKNOWLEDGEMENTS
I am indebted to my research principal investigator, Dr. Liana Asatryan, for her whole-hearted
support, suggestions, and invaluable advice throughout my project work and for helping in the
preparation of this thesis. I also express my gratitude to my panel members, Dr. Enrique Cadenas
and Dr. Daryl Davies, for their valuable comments and suggestions.
I would like to acknowledge Greg Havton, Alex Tai and the other undergraduate students of the
laboratory who lent their hands in animal studies and tissue processing.
I would also like to express my appreciation to my parents and friends for their continuous
support and belief in me.

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TABLE OF CONTENTS
Acknowledgements ……………………………………………………………………. ii
List of Tables …………………………………………………………………………... v
List of Figures …………………………………………………………………………. vi
Abbreviations ………………………………………………………………………….. vii
Abstract ………………………………………………………………………………... viii
Chapter 1: Background
1.1.Introduction ………………………………………………………………………….. 1
1.2.Current treatment options for AUD ………………………………………………….. 2
1.3.Gut-Brain Axis in AUD ……………………………………………………………… 3
1.4.The role of gut microbiome metabolites in AUD ……………………………………. 6
1.5.Epigenetic mechanisms in AUD ……………………………………………………... 8
1.6.Neuroimmune perspective of AUD ………………………………………………….. 8
1.7. Involvement of microglia in neuroinflammation ……………………………………. 10
1.8. AUD and its impact on microglial function …………………………………………. 11
1.9. Therapeutic potential of butyrate supplementation in AUD ………………………… 13
Chapter 2: Hypothesis - Investigating the Effects of Sodium Butyrate
Supplementation on Microglial Polarization in the Context of AUD ………………… 14
Chapter 3: Materials and Methods
3.1. Animal housing conditions ………………………………………………………….. 15
3.2. Two-bottle choice drinking model …………………………………………………... 15
3.3. Sample Collection …………………………………………………………………… 17
3.4. Blood ethanol concentration (BEC) determination ………………………………….. 18
3.5. Cell Culture of BV2 microglia and treatment ……………………………………….. 18
3.6. MTT viability assay …………………………………………………………………. 19
3.7. RT-qPCR …………………………………………………………………………….. 19
3.8. Western Blot …………………………………………………………………………. 20

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3.9. Statistical Analysis …………………………………………………………………… 21
Chapter 4: Results
4.1. Mice had a reduced preference for ethanol when treated with SB …………………… 22
4.2. Butyrate increases the metabolism of ethanol when supplemented two weeks after
ethanol exposure …………………………………………………………………………... 26
4.3. Modulation of M1 microglia in the brain by butyrate is time dependent …………….. 28
4.4. Butyrate increases M2 microglia polarization in the brain …………………………… 29
4.5. Optimization of treatment conditions for BV-2 cell cultures using MTT Assay ……... 31
4.6. Butyrate upregulates the expression of BDNF receptor in BV2 microglial cells …….. 34
4.7. Butyrate provides neuroprotection by upregulating CX3CR1 mRNA expression …… 35
Chapter 5: Discussion ……………………………………………………………………. 37
Bibliography ……………………………………………………………………………… 44

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LIST OF TABLES
Table 1. Two-bottle choice study design …………………………………………… 17
Table 2. Forward and reverse primer sequences …………………………………… 20

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LIST OF FIGURES
Figure 1. The pathways connecting the gut and the brain to form the gut-brain axis …… 5
Figure 2. Phenotypes of activated microglia …………………………………………….. 11
Figure 3. Weekly analysis of ethanol consumption and preference ………………………….. 25
Figure 4. Overall ethanol consumption and preference ………………………………….. 26
Figure 5. BEC of mice 24 hrs. after being given access to ethanol ……………………… 27
Figure 6. M1 microglial marker mRNA expression ……………………………………... 29
Figure 7. M2 microglial marker mRNA expression ……………………………………... 30
Figure 8. MTT viability assay optimizing the treatment conditions …………………….. 32
Figure 9. BDNF receptor (TrkB) expression in LPS activated BV-2 cells treated with
ethanol in the presence or absence of SB ………………………………………………… 34
Figure 10. mRNA expression of CX3CR1 is upregulated in the SB treated groups
compared to the control group ……………………………………………………………. 36

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ABBREVIATIONS
AUD Alcohol use disorder
CNS Central nervous system
GBA Gut-brain axis
SCFA Short-chain fatty acid
SB Sodium butyrate
GABA γ-aminobutyric acid
LPS Lipopolysaccharide
BBB Blood-brain barrier
HDAC Histone de-acetylases
MCP-1 Monocyte chemoattractant protein-1
TLR-4 Toll-like receptor-4
DAMP Danger associated molecular pattern
IL-6 Interleukin-6
TNFα Tumor necrosis factor alpha
IL-10 Interleukin-10
BDNF Brain-derived neurotrophic factor
HDACi HDAC inhibitor
Arg-1 Arginase-1
DID Drinking-in-the-dark
TBC Two-bottle choice

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ABSTRACT
Alcohol Use Disorder (AUD) is a complex neurological condition characterized by compulsive
alcohol consumption and adverse effects on physical and mental health. Despite its prevalence
and impact, effective treatments for AUD remain limited. One area of investigation lies in the
gut-brain axis, where disruptions in the gut microbiome due to alcohol consumption contribute to
neuroinflammation and addiction development. Notably, the imbalance of short-chain fatty
acids, such as butyrate has emerged as a key factor in this process. Butyrate, known for its antiinflammatory properties, has been proposed as a potential therapeutic agent for AUD due to its
ability to modulate microglia. Microglia play a pivotal role in neuroinflammation and have been
implicated in the pathophysiology of AUD. These cells exhibit distinct functional states,
including pro-inflammatory M1 and anti-inflammatory M2 states, which can be influenced by
neuromodulators such as alcohol. However, the specific effects of alcohol on microglia
polarization and how they may be altered by sodium butyrate (SB) supplementation remain
poorly understood. This thesis aims to elucidate the potential role of SB in shifting the
polarization of microglia and its therapeutic implications for AUD. This was achieved through a
comprehensive mRNA expression analysis in the brain tissues of mice from two-bottle choice
studies, where mice were given either ethanol only or both ethanol and SB treatment. RT-qPCR
to identify pro-inflammatory and anti-inflammatory cytokines, and M1 and M2 microglia
markers showed a mixed upregulation and downregulation of all markers, such as IL-1β, IL-6
(pro-inflammatory cytokines); BDNF, IL-10 (anti-inflammatory cytokines); MCP-1 (M1
markers); and Arg-1 (M2 marker), in both alcohol-fed groups and SB treated groups, thus
leading to a conclusion that both phenotypes M1 and M2 exist at the same time in both groups.
However, overall analysis of ethanol preference in the two-bottle choice model revealed a

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reduced preference for ethanol when SB was treated two weeks after establishing ethanol
dependence. Furthermore, this group had an increase in consumption of SB. The upregulation of
BDNF was supported by a higher expression of its receptor TrkB, which was analyzed through
western blot of LPS activated, ethanol and SB treated BV2 microglial cell lines. We also found
increased neuroprotection by CX3CR1 and BDNF upregulation in groups treated with SB after
two weeks of ethanol dependence. Finally, all these data point to a direction that suggests that SB
treatment requires the dependence of alcohol to have a greater therapeutic effect. Our current
study aims to explore microglial polarization as a target for AUD management, in particular
BDNF and CX3CR1, through the use of SB.

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Chapter 1: Background
1.1. Introduction
Alcohol Use Disorder (AUD) is a persistent recurring neurological condition marked by an
irresistible urge to consume alcohol, an inability to regulate drinking, and detrimental effects on
both physical and mental well-being. Acutely, alcohol effects manifest as mild symptoms like
dizziness and imbalance, but it eventually leads to undesirable pathological consequences
including liver damage and impaired cognitive function [1]. However, very few therapies are
currently available to treat AUD effectively due to the fact that alcohol can affect various
systems in the body, including the central nervous system (CNS), the cardiovascular system and
digestive system.
The intestinal system is highly affected by alcohol consumption. Alcohol hinders the uptake of
nutrients and boosts the passage of toxins through the intestinal wall. These impacts could
potentially lead to the onset of alcohol-induced damage to several bodily organs [2]. Scientists
have identified a strong connection between the gut microbiome and the brain, thus establishing
the gut-brain axis (GBA) [3]. The microbiome is a large community of microorganisms residing
in the gastrointestinal tract and has a multitude of functions. It is known to influence mental
health, metabolism of food components that are not digestible, absorption of vitamins and
promoting skin health [4]. Most importantly, it is instrumental in preserving gut function and
regulation of the immune system. Alcohol consumption disrupts the gut microbiome and leads to
gut dysbiosis, which has been linked to neuroinflammation and the development of alcohol
addiction [5]. Disruption of the gut microbiome also results in the imbalance of metabolites
produced by these microorganisms, including short-chain fatty acids (SCFA) such as butyrate.

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Butyrate is the most abundant SCFA and plays a role in cell proliferation and apoptosis,
suppressing inflammation, and improving gastrointestinal health [6]. It is a potent inhibitor of
histone deacetylases, enzymes involved in gene regulation. As such, it has been hypothesized
that butyrate (in the form of sodium butyrate or tributyrin) may have a therapeutic potential in
the treatment of AUD by exerting anti-inflammatory and neuroprotective effects through its
ability to modulate microglia [7].
Microglia, the resident immune cells in the brain, are key players in neuroinflammation and have
been implicated in the pathophysiology of AUD [8]. These cells have shown to be bimodal in
function, exhibiting pro-inflammatory M1 and/or anti-inflammatory M2 states in response to
neuromodulators such as alcohol [9]. However, limited data specify the effects of alcohol on
microglial polarization and how it may be influenced by sodium butyrate (SB) supplementation.
The current thesis focuses on understanding the potential role of SB in causing a shift in
polarization of microglia and to discuss its potential therapeutic implications.
1.2. Current treatment options for AUD
AUD is a complex disorder that is prevalent in almost all societies. According to the Diagnostic
and Statistical Manual of mental disorders, Fifth Edition, AUD is “A problematic pattern of
alcohol use leading to clinically significant impairment or distress” [10]. It can exhibit a range
of severity, from mild to moderate. As of 2022, 29.5 million people over the age of 12 were
diagnosed with AUD out of which 750 thousand of them were adolescents [11]. As AUD
worsens, the impact of alcohol on the brain can create significant obstacles for reducing
consumption or stopping altogether. Nevertheless, with extended periods of abstinence, some of
the changes in brain function caused by AUD may show signs of improvement and even reverse
as alternative neural pathways adjust to compensate for those affected by alcohol. Evidence-

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supported interventions can assist individuals in reaching abstinence and supporting these
neurological adjustments; however, this remains a considerable challenge [12].
One of the main focuses of AUD treatment is addressing the behavioral aspect of the disorder
through therapies such as cognitive-behavioral therapy and motivational interviewing. These
therapeutic approaches are designed to help individuals by developing coping strategies, increase
motivation for change, and modify problematic thoughts and behaviors associated with alcohol
use . Integration of Alcoholics Anonymous along with exposure therapy has also shown
promising results in reducing the consumption of alcohol and promoting long-term recovery
[12][13]. However, the search for more effective pharmacotherapeutic options continues.
The current existing pharmacotherapies that are FDA approved are limited and are its effects are
transient with high rates of relapse [14]. Naltrexone is an opioid receptor antagonist that
functions by mimicking exogenous opioids at the mu-opioid receptor, and thus helps manage
relapse of alcohol use [15]. Acamprosate is another commonly prescribed medication for AUD.
It is similar in structure to -aminobutyric acid (GABA) and is thought to affect the glutamine
and GABA pathways, and calcium ion channels in the brain (kam hunter). But their effectiveness
varies among individuals and long-term outcomes are often unsatisfactory [14], [16]. Other
medications include disulfiram which creates an unpleasant reaction when alcohol is consumed,
and topiramate, which helps reduce cravings [14].
1.3. The Gut-Brain Axis (GBA) in AUD
The CNS plays a critical role in modulating a wide range of gut functions, such as motility,
secretion, blood flow, and immune function, in response to physical and psychological stressors,
as substantiated by preclinical and clinical evidence [17]. The gut microbiota, on the other hand,

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can communicate with the brain through various pathways, including the immune system, vagus
nerve, and production of neurotransmitters and metabolites [5], [18], [19]. This bidirectional
communication forms the basis of the GBA, which has been implicated in several
neuropsychiatric disorders, including AUD.
Recent studies have suggested that alterations in the function and composition of the gut
microbiota, as well as changes in the production of microbial metabolites, may contribute to the
development of AUD and its associated behaviors [5]. This phenomenon, termed as dysbiosis
causes a disruption in the tight junction proteins and increases intestinal permeability, leading to
the leakage of microbial products and toxins into the bloodstream [20]. The main toxin that is
released into the bloodstream is bacterial lipopolysaccharide (LPS), a component of the outer
membrane of gram-negative bacteria [21]. This can circulate in the body and activate the
immune system, leading to a state of chronic inflammation, by interacting with its receptor TLR4
[22].
The vagus nerve, responsible for innervating the abdominal organs, plays a significant role in
facilitating neural communication between the CNS and the periphery. It has been observed that
the vagus nerve output mediates the induction of in-situ cytokines expression and the resulting
sickness behavior following the leaking of LPS into the peripheral bloodstream [23].
Additionally, peripheral cytokines that infiltrate the brain add to the cytokine levels within the
tissue, worsening the sickness symptoms. However, the role of the vagus nerve in AUD is being
researched and is not yet fully understood.
The maintenance of the CNS relies heavily on the blood-brain barrier (BBB), which is a vital
component in ensuring its integrity and proper function. However, it has been suggested that
chronic alcohol consumption can compromise the function of the BBB, allowing for the entry of

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harmful substances into the brain [24]. Ethanol disrupts the BBB by downregulating important
tight junction proteins at the barrier such as Occludin, Claudin-5 and ZO-1 [25]. These proteins
are essential for maintaining the structural integrity of the BBB, and its disruption can lead to
increased permeability and the infiltration of pro-inflammatory molecules and immune cells into
the brain, along with toxins such as LPS [26]. This disruption in the BBB may further contribute
to neuroinflammation and neuronal dysfunction observed in AUD.
Moreover, the role of the GBA in influencing behavior and craving associated with alcohol
consumption is also an area of active investigation. The cooperative signaling between the gut
and the brain, mediated by neurotransmitters and gut hormones, has implications for the
regulation of reward pathways and addictive behaviors [27]. Understanding these mechanisms
may open new avenues for targeted interventions to reduce alcohol cravings and support longterm recovery in individuals with AUD.
Figure 1. The pathways connecting the gut and brain to form the gut-brain axis [27]

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1.4. The role of gut microbiome metabolites in AUD
The gut microbiota is a complex ecosystem of microorganisms that reside in the gastrointestinal
tract and play a crucial role in digestion, function of the immune system, and overall health.
There are about 1.3 times more bacterial cells than host cells in the human body [28], and this
population is dominated by species such as Bacteroidetes and Firmicutes [29].
Research has shown that the alterations in the gut microbiome and its metabolites play a
significant role in the development and progression of AUD. The production of an extensive
range of neurochemicals by bacteria has been the subject of comprehensive investigation for
many years. These chemicals have been thoroughly examined in terms of their interactions with
receptors in both the intestinal tract and other areas of the body. A prime illustration of this
phenomenon is the production of GABA by probiotic bacteria, which occurs through the
identical biosynthetic pathway found in neuronal tissue [18]. The microbiota has also been found
to secrete neurotransmitters, including dopamine and serotonin [19], which are involved in the
reward and pleasure pathways associated with alcohol addiction [30].
Additionally, the gut microbiome produces SCFAs, such as butyrate, propionate, and acetate,
through the fermentation of dietary fiber [5]. These SCFAs have been shown to have various
effects on various systems of the body including the immune system, CNS and the liver in the
context of AUD [31].
The anti-lipogenic and cholesterol lowering effects of propionate have been demonstrated in
numerous studies. Moreover, it has been observed to have significant impacts on weight control
and feeding behavior. It also is known to exert an anti-proliferative effect on colon cancer cells
[32].

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Acetate operates by directly suppressing appetite through central hypothalamic mechanisms that
involve modifications in transcellular neurotransmitter cycles. It stimulates the release of insulin,
aiding in the transfer of glucose from the bloodstream to cells, while simultaneously decelerating
the release of glucagon—a hormone that typically raises blood sugar levels. The heightened
secretion of these hormones amplifies the sensation of fullness, potentially resulting in reduced
food intake. Moreover, acetate also impacts adipocytes, triggering the secretion of leptin, a
hormone that further curbs appetite. Additionally, there is some evidence indicating that the
short-chain fatty acid acetate may traverse from the gut to the brain, where it can effectively
suppress hunger [33], [34].
Butyrate is known to have a pleiotropic effect on the body. Butyrate has been documented to
enhance glucose regulation through a mechanism like that of acetate. Additionally, butyrate
exerts beneficial impacts on the secretion and metabolic functions of growth hormones,
consequently stimulating lipolysis and oxidative metabolism. On the other hand, butyrate can be
metabolized in the gut by acetyl-coA to produce lipids, cholesterol, and ketone bodies, thus
providing a basis for development of obesity. It also has been shown to induce resistance to
insulin and promotes diabetes [6]. Although butyrate primarily acts on the gastrointestinal
system, it is also known to provide cardiovascular protection [35]. Butyrate has been found to
have anti-inflammatory properties and can modulate neuroimmune responses [7]. Furthermore,
butyrate has been shown to have protective effects on the gut barrier integrity and reduce
intestinal permeability, which is often compromised in individuals with AUD [20].

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1.5. Epigenetic mechanisms in AUD
Epigenetics involves the study of heritable modifications in gene expression that do not involve
alterations to the DNA sequence itself. The occurrence of epigenetic alterations within an
organism or individual can be highly diverse, depending on factors like time and specific
tissue/organ. Environmental factors, toxic agents, and drugs have the ability to induce
modifications in DNA and histones, such as methylation and acetylation [36]. In the context of
AUD, epigenetic mechanisms have been implicated in the development and maintenance of
alcohol addiction.
Several studies emphasize the role of epigenetic modifications, particularly histone acetylation in
regulating alcohol-dependent behaviors. Acute exposure to alcohol increases the acetylation of
H3 histone at the Lys9 position due to the upregulation in the activity of histone
acetyltransferases (HAT). This accompanied by the inhibition of histone deacetylases (HDAC)
results in the unwinding of the chromatin structure and increased accessibility of genes involved
in addiction-related behaviors [37]. Following chronic ethanol exposure, these changes revert to
their baseline levels, including anxiety-like behaviors. However, during withdrawal, there is a
decline in histone acetylation caused by increased HDAC activity, leading to the development of
anxiety-like behaviors [38]. Oxidative stress caused by the prolonged exposure to alcohol is the
driving force for the HDAC activity increase, specifically HDAC2 expression [39], [40].
1.6. Neuroimmune perspective of AUD
The interaction between the immune system and the nervous system is a complex and dynamic
process that plays an important role in the pathophysiology of AUD. Emerging research suggests

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that chronic alcohol consumption triggers neuroimmune activation, leading to the dysregulation
of immune responses in the brain [22].
Recent investigations have yielded compelling evidence that supports the existence of
widespread inflammation markers, including monocyte chemoattractant protein-1 (MCP-1).
Additionally, it has been observed that individuals with AUD display an elevated level of MCP-1
expression in their brain tissue, which was detected post-mortem [41]. MCP-1, also known as
CCL2, plays an important role in recruiting monocytes and macrophages to sites of
inflammation. Within the brain, it can also attract microglia, the resident immune cells of the
CNS [42]. Another study has found highly elevated levels of a systemic inflammation marker,
high sensitivity C-reactive protein (hs-CRP), in men with AUD [43].
LPS that leak from the gut into the bloodstream during alcohol consumption are the main source
of neuroinflammation. It works through various pathways to induce an inflammatory state in the
brain. One of the earliest pathways known is the induction of systemic IL-1 [44], [45], which is a
family of cytokines that are mostly pro-inflammatory in nature [46]. This was confirmed by the
presence of IL-1 receptors in the hippocampus, dentate gyrus and choroid plexus. The other
pathway involved is the activation of toll like receptor 4 (TLR4), which recognizes and responds
to danger associated molecular patterns (DAMPs) like LPS and endogenous danger signals such
as high-mobility group box 1 (HMGB1) [47]. The activation of TLR4 initiates a cascade of
inflammatory reactions, which involve the secretion of pro-inflammatory cytokines and
chemokines.
Cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNFα) are mainly
considered to be key players in the neuroinflammatory response associated with AUD [48].
However, anti-inflammatory cytokines, such as interleukin-10 (IL-10) are being increasingly

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recognized for their role in modulating neuroinflammation, where a reduction in their levels can
contribute to an exaggerated pro-inflammatory response [49]. These findings suggest that a
balance between pro-inflammatory and anti-inflammatory cytokines is crucial for maintaining
neuroimmune homeostasis in individuals with AUD.
1.7. Involvement of microglia in neuroinflammation
Microglia are cells of the CNS that act as the primary immune cells and play a pivotal role in
neuroinflammation. In the brain, the microglia act as the first line of defense against harmful
stimuli and play a critical role in maintaining neuronal homeostasis [50]. Microglia are highly
responsive to changes in the brain environment, especially in the presence of damaged neurons
or infectious agents such as LPS. As a result of such stimulation, microglia undergo a process
called activation, which involves morphological and functional changes [51].
During activation, microglia transform into different phenotypes, known as polarization, with the
two main phenotypes being the M1 pro-inflammatory and the M2 anti-inflammatory phenotypes
[52]. However, recent evidences suggest that there is no single definitive M1 or M2 phenotype,
but rather a spectrum of microglial phenotypes with varying degrees of pro-inflammatory and
anti-inflammatory properties [53]. Microglia in their activation states can produce a wide range
of inflammatory mediators and suppressors, such as cytokines, chemokines, enzymes and growth
factors, which can have both detrimental and beneficial effects on the brain [54]. A shift in the
microglial polarization is primarily important in neurodegenerative diseases such as Alzheimer’s,
Parkinson’s, amyotrophic lateral sclerosis, and multiple sclerosis. Despite ongoing research
efforts, the precise mechanisms governing microglia polarization remain unclear. Nevertheless,
targeting transcription factors, cytokines, and ion channels may hold promise for driving
microglial transition from an M1 to an M2 phenotype [55]. Numerous studies have explored this

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phenomenon in vitro, in wild type mice, and in various diseases like ischemic stroke, spinal cord
injury, and traumatic brain injury [56], [57], [58], [59].
Figure 2. Phenotypes of activated microglia [60]
1.8. AUD and its impact on microglial function
The involvement of microglia in neuroinflammation is particularly relevant in the context of
AUD. However, chronic and acute alcohol exposure can significantly impact microglial function
and lead to dysregulation of the neuroimmune response, contributing to the development and
progression of AUD [8], [61].
Studies have shown that alcohol exposure can have a varied effect on microglia. Acute alcohol
consumption has been shown to promote autophagy in microglial BV-2 cells, suggesting a
potential protective mechanism [62], [63]. Consumption of alcohol for longer periods of time
however, has shown to result in microglial apoptosis, causing symptoms such as dizziness and
brain discomfort [8]. Additionally, chronic alcohol use has also shown to impact neural synapses
due to microglial phagocytosis [64].

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Alcohol can activate microglia, similar to other neuroinflammatory stimuli, leading to microglial
polarization into M1 phenotype. This results in the release of pro-inflammatory cytokines and
chemokines such as IL-6, TNFα, and MCP-1 [7]. MCP-1 and its receptor CCR2 play a crucial
role in alcohol drinking behavior. Mutations in MCP-1 and CCR2 increased aversion to ethanol
in female mice [65], thus elucidating the role of microglial chemokines in the modulation of
alcohol consumption.
Brain-derived neurotrophic factor (BDNF), an anti-inflammatory growth factor released by M2
microglia, has been shown to be decreased in the hippocampus of alcohol-exposed rodents,
suggesting a potential mechanism by which alcohol-induced microglia suppresses neuronal
plasticity and prevents activation of microglia to an anti-inflammatory state [66]. The
involvement of cyclic AMP-responsive element binding protein (CREB), a transcription factor,
in the signaling of BDNF via the TrkB receptor is well-established [67]. Notably, research has
shown that both alcohol dependence and alcohol withdrawal are associated with a decline in
CREB levels, suggesting a potential decrease in the expression of TrkB as well [68].
Microglia being a mononuclear phagocytotic cell express high levels of the reactive oxygen
species (ROS) producing enzyme NADPH oxidase (NOX) [69]. ROS is responsible for the
hyperactivation of the microglial NLRP3 inflammasome and the subsequent release of proinflammatory cytokines IL-1β and IL-18 in response to alcohol exposure [70]. Furthermore,
ethanol has shown to mediate microglial cell death via the NOX/ROS signaling pathway [61].
Alcohol consumption has a varied effect on microglia, depending on the concentration and
duration of exposure [8]. Alcohol has shown to activate microglia to an M1 state, however,
various studies have shown the co-existence of both M1 and M2 states with exposure to alcohol
[9], [71]. These findings elucidate the intricate relationship between alcohol and microglia

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polarization, suggesting that alcohol can induce both pro-inflammatory and potentially
beneficial, recovery-promoting phenotypes in microglia.
1.9. Therapeutic potential of butyrate supplementation in AUD
Emerging research suggests that interventions aimed at restoring the gut microbiota composition
and optimizing the production of beneficial metabolites, such as butyrate, could have a positive
impact on alcohol addiction [72]. Strategies such as probiotic supplements, dietary
modifications, and the use of prebiotics to stimulate the growth of advantageous gut bacteria
have shown promise in preclinical studies [18], [73]. Additionally, the administration of butyrate
or its analogs, such as Sodium Butyrate (SB), to modulate gut barrier integrity and reduce
inflammation may offer a novel approach to managing AUD [74].
SB protects the gut barrier from the effects of alcohol by promoting the expression of tight
junction proteins like occludin, ZO-1, and claudin-1, thus improving the integrity of the intestinal
lining and reducing the leakage of harmful substances into the bloodstream [75], [76]. In addition
to the gut wall integrity, SB also prevents the disruption of the BBB by augmenting the
expression of similar proteins at the surface of the brain [77], [78].
HDAC inhibitors (HDACi) work specifically to mitigate the epigenetic effects of alcohol. SB is
one such HDACi that has shown potential in reducing alcohol consumption and preventing the
neuroinflammatory response associated with AUD [7], [79]. In these studies, supplementation
with SB prevented the increase in mRNA levels of key brain cytokines induced by alcohol.
There was also a significant prevention of changes in microglia and astrocytes. Overall, these
findings suggested that SB holds a potential as a therapeutic for AUD.

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Chapter 2: Hypothesis - Investigating the effects of sodium butyrate
supplementation on microglial polarization in the context of AUD
Butyrate, a short-chain fatty acid produced by the gut microbiota, has been found to have
multiple beneficial effects on the body. Previous studies have demonstrated that supplementation
with SB was able to prevent increased ethanol consumption in rodent models of AUD [79].
These studies suggest that SB may be able to modulate neuroinflammatory responses and protect
against the enhanced ethanol consumption induced by antibiotic treatment in mice [7].
The ability of SB to modulate microglia, the resident immune cells in the brain, is a niche area
of research in the field of alcohol addiction studies. As mentioned earlier, microglia exhibit
bimodal functions and can adopt pro-inflammatory (M1) or anti-inflammatory (M2) states in
response to various stimuli. Understanding the influence of SB on microglial polarization in the
context of alcohol consumption is crucial for elucidating its potential therapeutic role in treating
AUD. Studies that have explored the role of SB in neuroprotection have shown the upregulation
of M2 microglial markers such as BDNF, IL-10, CD-206 and Arginase-1 (Arg-1), suggesting a
shift towards an anti-inflammatory phenotype. Evidence also suggests that SB acts by inhibiting
the NF-B pathway, eventually leading to a downregulation of pro-inflammatory markers such
IL-1β, IL-6 and other M1 microglial markers.
Therefore, we hypothesized that exposure to alcohol causes the activation of microglia to
primarily adopt a pro-inflammatory M1 phenotype. Supplementation with SB can shift the
microglial polarization towards an anti-inflammatory M2 phenotype. We think that this shift in
polarization by sodium butyrate will contribute to the prevention of neuroinflammatory
responses and ultimately reduce ethanol consumption.

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Chapter 3: Materials and Methods
3.1. Animal housing conditions
For this study, forty-five male C57BL/6J mice aged 6-8 weeks were procured from Jackson
Laboratories, USA. The mice were housed individually in standard laboratory cages to ensure
controlled conditions and minimize external influences. During the acclimatization period lasting
a minimum of one week, the mice were provided with access to mouse chow and drinking water
ad libitum. This period allowed them to adapt to their new environment and diet. Measurements
of body weight, food intake, and water consumption were taken every other day during the
acclimatization period to ensure that the mice were in good health and to establish baseline
values for comparison throughout the study. The vivarium where the mice were housed was
carefully maintained at a temperature of 21-23°C and a humidity of about 40%. Moreover, a 12-
hour light/dark cycle was maintained to mimic their natural day and night cycles, where mice
had light from 12AM to 12PM and darkness from 12PM to 12AM.
3.2. Two-bottle choice drinking model
There are two widely recognized models of alcohol use disorder, which aim at recreating
moderate and binge-drinking profiles in mice. Both models allow mice to consume alcohol
voluntarily. The first model is a "Drinking in the dark" (DID) model, where mice are given
access to alcohol for a limited period of time (typically 2-4 hours) starting at 3 hours into the
dark cycle. This model has demonstrated reliable and high levels of ethanol consumption in a
short period of time, mimicking binge-drinking behavior [80], [81].

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The model used in our study was the two-bottle choice (TBC) drinking model, which allows for
the assessment of both ethanol consumption and preference. This is an intermittent access model
where mice are given simultaneous access to two bottles: one containing water and the other
containing ethanol every other day for 24 hours. This allows for mice to experience withdrawal
for one day during weekdays and 48 hours on weekends [81], [82].
In our experiment, the mice were randomly divided into four treatment groups: control group
(n=9), water-ethanol group (Et-H2O, n=12) and two treatment groups, ethanol-(ethanol+SB) (EtS1, Et-S2, n=12). The control group had access to two bottles containing only water. The EtH2O group had access to one bottle with water and another with 20% ethanol. The treatment
groups received one bottle of 20% ethanol and one treatment bottle containing 40 mg/mL SB;
the Et-S2 group started their treatment two weeks after the experiment began while the Et-S1
group had access from the start of the experiment. The bottles had 15 mL of liquid according to
their treatment groups and they were provided on Monday, Wednesday, and Fridays for 6 weeks.
The positions of bottles were alternated each time the treatment bottles were administered to
avoid any position preference. On Tuesday and Thursday, the ethanol and treatment bottles were
switched out for bottles containing water to allow for withdrawal effects. Throughout the
duration of the experiment, the mice were provided with rodent chow ad libitum. Body weight
(g), food (g) and liquid (mL) intake were measured every other day.

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Table 1. Two-bottle choice study design
Weeks
1 2 3 4 5 6
Groups
Control Water - Water
H2O-Et Water - EtOH
Et-S2 Water - EtOH EtOH - EtOH+SB
Et-S1 EtOH - EtOH+SB
3.3. Sample collection
After the experimental period, ethical guidelines were followed to euthanize the mice. The
primary method of euthanasia used was asphyxiation in a CO2 chamber, followed by a secondary
method of cervical dislocation to ensure death. Blood samples were obtained right after
euthanasia by cardiac puncture using a 23-gauge needle and 5 mL syringe. The samples were
allowed to clot for one to two hours at room temperature before being centrifuged at 10,000 rpm
for 10 minutes at 4°C to separate the serum, which was then carefully stored in microcentrifuge
tubes at -80°C until further analysis.
Whole brain tissue from each mouse was collected; the right hemisphere underwent immediate
fixation in 10% formalin for histopathological analysis while the left hemisphere was stored at -
80°C for biochemical analysis. Livers were also collected similarly, with their weight (in grams)
recorded and their largest lobe fixed in formalin. The remaining liver tissue was flash frozen.

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3.4. Blood Ethanol Concentration (BEC) determination
Blood samples were obtained right after euthanasia by cardiac puncture using a 23-gauge needle
and 5 mL syringe. The samples were allowed to clot for one to two hours at room temperature
before being centrifuged at 10,000 rpm for 10 minutes at 4°C to separate the serum. BEC was
determined from the serum using the Ethanol Assay Kit (Sigma-Aldrich, St. Louis, MO, USA).
The serum was diluted to 50 µL (1:2, 1:5) with the ethanol buffer provided in the kit and mixed
with the master mix according to manufacturer’s instructions. The absorption was then measured
at 570 nm and the concentration was calculated by extrapolating from a standard curve.
3.5. Cell culture of BV2 microglia and treatment
During the initial days, primary microglial cultures such as N9 cell lines, derived from mouse
brains were used for in-vitro assessment of microglial signaling. However, these cell lines
yielded limited biological material. Since then, the use of immortalized murine neonatal
microglia such as BV2 cell line has become a popular choice for in vitro studies on microglia.
Research has also confirmed the suitability of BV2 cells for modeling neuroinflammation in
vitro [83].
BV2 microglial cells were grown in Dulbecco's Modified Eagle Medium (DMEM) supplemented
with 10% fetal bovine serum, 100 units/mL penicillin, and streptomycin (100 µg/mL) in T75
flasks. The cells were placed at 37°C with 5% CO2 and 95% humidity. Upon reaching
confluency, the BV2 cells were trypsinized and seeded into appropriate culture plates or dishes
for subsequent experiments.

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3.6. MTT Viability Assay
BV2 cells after trypsinization were counted using a hemocytometer and diluted to achieve a cell
density of 5x10^5 cells/well. They were then seeded into 6 well plates at the desired density
where each group was assigned 2 wells. The cells were allowed to adhere to the wells for 48
hours in complete DMEM medium. After the initial 48 hours, PBS was used to wash the cells,
and then they were treated with different concentrations of ethanol (10mM, 20mM and 50mM)
with or without LPS (100 ng/mL) and SB (0.25mM, 0.5mM, 1mM and 2mM). The cells were
then incubated for an additional 24 hours, after which the medium was removed and replaced
with 1mL of 0.5 mg/mL MTT solution. The cells were then kept for 4 hours at 37°C, allowing
the MTT to be metabolized by viable cells. After the incubation period, the MTT solution was
taken out, and the formazan crystals were dissolved in 1mL DMSO by shaking gently. The
absorbance was measured at 570 nm.
3.7. RT-qPCR
RNA extraction was performed with RNeasy Mini Kit (Qiagen, Germantown, MD, USA).
Frozen brain tissue samples were lysed using the TissueLyser II (Qiagen, Germantown, MD,
USA). Total isolated RNA was quantified using a NanoDrop spectrophotometer.
After RNA quantification, cDNA synthesis was performed with RevertAid First Strand cDNA
Synthesis Kit (Thermofisher Scientific, Waltham, MA, USA). 180 ng of RNA for the tissue was
reverse transcribed into cDNA in a final volume of 20 µL.
The cDNA was then subjected to quantitative PCR using the PowerUp SYBR Green Master Mix
(Applied Biosystems, Austin, TX, USA) and specific primer sets for target genes (please, see

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Table 2 for the forward and reverse sequences for the primers of different markers). The qPCR
was run on the QuantStudio K12 Flex Real-Time PCR system (Thermo Fisher Scientific,
Waltham, MA, USA) with the following cycling conditions: an initial denaturation step at 95°C
(10 mins), followed by 40 cycles of denaturation at 95°C (15 secs) and annealing/extension at
60°C (1 min).
Table 2. Forward and reverse primer sequences
Target Forward (5' to 3') Reverse (5' to 3')
IL- 6 ACAACCACGGCCTTCCCTACTT CACGATTTCCCAGAGAACATGTG
IL-1β TGGACCTTCCAGGATGAGGACA GTTCATCTCGGAGCCTGTAGTG
MCP-1 GCAGCAGGTGTCCCAAAGAA ATTTACGGGTCAACTTCACATTCA
CX3CR1 GAGAGATGGCTCAGTGGTTAAG CACAGGAACAGGGAGCTATTT
BDNF TGCAGGGGCATAGACAAAAGG CTTATGAATCGCCAGCCAATTCTC
Arg-1 AATGAAGAGCTGGCTGGTGT CTGGTTGTCAGGGGAGTGTT
IL-10 CCAAGACCAAGGTGTCTACAA GGAGTCCAGCAGACTCAATAC
GAPDH AGGTCGGTGTGAACGGATTTG TGTAGACCATGTAGTTGAGGTCA
3.8. Western Blot
For western blot analysis, BV2 cells were seeded in 6-well plates at a density of 5 x 10^5 cells
per well. After the designated treatment, cells were washed with ice-cold PBS and lysed in RIPA
buffer supplemented with beta-mercaptoethanol (BME). Protein concentration of the lysates was
determined using the Bicinchoninic acid Assay (BCA). BV2 cell lysates were loaded with 8μg of
protein onto a 7.5% gel for electrophoresis. Proteins were then transferred onto a PVDF

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membrane (Bio-Rad Laboratories, USA) using a semi-dry transfer system. The PVDF membrane
was blocked with 5% non-fat milk in tris-buffered saline with 0.5% Tween-20 for 1 hour at room
temperature. Then, the membrane was incubated overnight at 4°C with primary antibodies
against the target proteins (TrkB). The primary antibodies used were rabbit anti-target protein
antibody (1:500 dilution) and mouse anti-GAPDH antibody. The membranes were then
incubated with species specific secondary antibodies (1:10,000 dilution) for 1 hour at room
temperature. Finally, the proteins of interest were visualized using an enhanced
chemiluminescence (ECL) detection system and captured with the iBright FL1000 Imaging
System (Bio-Rad Laboratories, USA).
3.9. Statistical Analysis
Statistical analyses utilized Microsoft Excel and GraphPad Prism software. For the behavioral
data (TBC model), amount of ethanol consumed was calculated as grams of ethanol per grams of
body weight. Ethanol preference was calculated as the percentage of ethanol consumed(%)/mean
body weight of group (g). For RT-qPCR the expression levels of target genes were normalized to
the housekeeping gene GAPDH, and the relative gene expression was calculated using the ΔΔCt
method. Quantification of integrated band intensity for the western blot images was performed
using ImageJ software. The intensities were normalized to band intensities of GAPDH and
presented as relative protein expression levels. The behavioral data and RT-qPCR data were
analyzed using a one-way analysis of variance (ANOVA).

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Chapter 4: Results
4.1. Mice had a reduced preference for ethanol when treated with SB
TBC intermittent access alcohol drinking model was established to assess effects of SB on
ethanol intake and preference. In this model, mice are given two bottles with different liquids
whose difference in preference we are testing (in our case ethanol and sodium butyrate). They
are placed in their cages for a specific period of time, usually 24 hrs., allowing free access to
both the bottles simultaneously. After the time period the liquids levels are noted to measure the
difference in consumption between the two liquids. This model was chosen because it allows for
ad-libitum drinking and ease of assessing preference between ethanol and SB. We also
attempted to establish whether ethanol dependence is required to observe effects of SB. For that,
SB was introduced at two time points - from the beginning of the experiment, denoted as Et-S1,
and after 2 weeks of ethanol consumption, denoted as Et-S2.
After the initial acclimatization period, mice were given 10% ethanol to measure the baseline
ethanol consumption levels. Throughout the tested weeks, the baseline ethanol intake remained
relatively consistent, showing minimal fluctuations. Mice in the Et-S1 exhibited significantly
higher ethanol consumption in weeks 3 and 6 (one way ANOVA, p = 0.006, 0003 respectively),
whereas those in Et-S2 group showed significantly reduced intake in week 3 (one way ANOVA,
p = 0.041) with respect to Et-H2O group (Figure 3A). At the end of six weeks, overall, the Et-S1
group consumed a higher amount of ethanol compared to the Et-H2O group (Figure 4A). We
also see that mice in Et-S2 group drink reduced ethanol volumes compared to the Et-H2O group.
In fact, the Et-S2 group drank significantly less ethanol than the Et-S1 group as well (one way
ANOVA, p = 0.0005).

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During the whole six weeks of the TBC experiment there was no significant difference in ethanol
preference (Figure 3B) between the Et-H2O and the Et-S1 group. Interestingly, when SB was
introduced to the Et-S2 group in the third week, there was a lowering in ethanol preference in
weeks 3 and 5 with respect to the Et-H2O group (one way ANOVA, p = 0.053, 0.345
respectively). This drop in preference was non-significant statistically. However, contrary to the
weekly data, the overall ethanol preference showed highly significant differences. Both the Et-S1
group and the Et-S2 group showed significantly lower preference for ethanol compared to the EtH2O group (one way ANOVA, p = 0.013, 0.0001 respectively; Figure 4B).
An analysis of total liquid intake (Figure 3C) to determine whether overall liquid intake
influenced ethanol consumption or preference among the mice was then conducted using oneway ANOVA. In weeks 1, 3, and 6, mice in the Et-S1 group displayed significantly higher total
liquid intake relative to the Et-H2O group (one way ANOVA, p = 0.014, <0.001, 0.003
respectively). Furthermore, mice in the Et-S2 group consumed significantly more liquids in
weeks 5 and 6 (one way ANOVA, p = 0.009, 0.0001 respectively). Interestingly, the liquid
intake trend at week 3 for Et-S1 is similar to that at week 5 for Et-S2, which translates to the
average liquid intake over the entire six weeks (Figure 4C). Overall, both the Et-S1 and Et-S2
groups consumed significantly more liquids, including both ethanol and SB, compared to the EtH2O group (one way ANOVA, p = 0.0001, <0.001 respectively). As seen in the weekly data, the
average total liquid intake was similar in the groups that were given SB.
We further assessed the intake of SB-containing liquid vs water. There was increased SB
consumption in weeks 1, 3 and 6 for Et-S1 group compared to water intake in the Et-H2O group
(one way ANOVA, p = 0.012, 0.017, <0.001 respectively; Figure 3D). SB liquid consumption

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was also increased in the Et-S2 group in comparison to water intake in the Et-H2O group for
weeks 3, 5 and 6 (Figure 3D). Overall changes in liquid consumption paralleled changes in SB
liquid intake (Figure 3C and D; Figure 4C and D), suggesting that mice may have taste
preference for SB. This phenomenon was observed in studies conducted earlier in our lab [79].
Mouse body weights and food intake throughout the weeks were analyzed. This was done to rule
out any effects of body changes and health issues on ethanol consumption. The body weight of
mice in all groups increased gradually throughout the weeks (Figure 3E). This indicates a healthy
weight gain and growth. Remarkably, mice in the Et-SB1 group had smaller but significantly
lower weights compared to their counterparts in the Et-H2O group (one way ANOVA, p < 0.05).
Mice of all groups consumed similar amounts of food over the period of 6 weeks (Figure 3F).
This eliminates the effects of dietary changes on ethanol consumption.

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Figure 3. Weekly analysis of ethanol consumption and preference. (A) Ethanol consumption varied
only in weeks 3 and 6. (B) Ethanol preference was not significantly increased at any time point for both
the ethanol and SB treated groups. (C) The total liquid intake was significantly changed in all weeks
except for week 4. Total liquid intake is influenced by either ethanol intake, (D) SB intake or both. (E)
Body weight of the mice in all groups increased gradually along the six-week period, however (F) no
significant differences in food intake were observed.

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Figure 4. Overall ethanol consumption and preference. (A) Ethanol consumption was increased in EtS1 but decreased in Et-S2. (B) Ethanol preference was significantly less for both SB groups with respect
to Et-H2O group. (C) The total liquid intake was significantly increased in both groups. (D) SB intake
was significantly increased in both groups.
4.2. Butyrate increases the metabolism of ethanol when supplemented two
weeks after ethanol exposure
In the previous section we observed that when SB was supplemented to the mice from the
beginning, the overall preference for ethanol was lower than when mice were not given SB
(Figure 4B). In support of this the SB intake for this group was higher (Figure 4D), however, its
ethanol intake was also higher (Figure 4A). Therefore, we hypothesized that the higher ethanol
intake is most likely due to an increase in metabolism by SB when it was supplemented from the
beginning. To assess this, we measured the concentration of ethanol in the serum 24 hrs. after the
mice had access to ethanol. We observed that the mice in the Et-H2O group had the highest

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serum ethanol concentration. The Et-S1 and Et-S2 groups had a lower BEC than the Et-H2O
group. Interestingly mice in the Et-S1 group had a significantly lower BEC than mice in the EtS2 group (one-way ANOVA, p = 0.012; Figure 5). This suggests that supplementation with SB
from the beginning increases ethanol metabolism compared to when supplemented after ethanol
dependence by more than 50%.
Figure 5. Blood ethanol concentration of mice 24 hrs. after being given access to ethanol.
Presentation of data is in the form Mean ± SEM, n = 3 to 5 per group

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4.3. Modulation of M1 microglia in the brain by butyrate is time dependent
Microglia are an important part of the immune environment in the brain. They are known to
regulate cytokine production and promote homeostasis within the brain. When exposed to a
stimulant such as ethanol, these cells get activated into an M1 pro-inflammatory state. However,
internal mechanisms cause them to switch into an M2 anti-inflammatory state that provides
neuroprotection. In previous studies conducted in our lab, we identified SB to have a
neuroprotective effect and reduce neuroinflammation [7]. Thus we hypothesized that SB could
promote the polarization of ethanol exposed microglia from an M1 to an M2 phenotype. To
analyze the polarization of microglia in the brain, qRT-PCR analysis was conducted to examine
key microglial markers. On exposure to ethanol, the expression of IL-1β was upregulated in the
Et-H2O group, compared to the control group. However, this change was not significant (Figure
6A). On the other hand, when provided with SB after 2 weeks of ethanol exposure, a significant
increase in IL-1β expression was observed in the Et-S2 group compared to the control group
(one way ANOVA, p = 0.046). Although a slight increase in expression is observed in the Et-S1
group as well, it is lesser than that of the Et-S2 group. A similar trend is seen in the expression of
MCP-1, where the Et-S2 group has a greater expression level. The Et-S1 group, however, shows
levels of expression that are similar to that of the control group. The Et-H2O group surprisingly
has a lower expression of MCP-1. Moreover, although there was an increase in MCP-1 (Figure
6B) and IL-6 (Figure 6C) in the Et-S2 group relative to the control group, these changes did not
reach statistical significance. Typically, the highest pro-inflammatory expression would be
expected in the Et-H2O group; however, unexpectedly, the Et-S2 group showed a higher
expression than the Et-H2O group with respect to control.

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Figure 6. M1 microglial marker mRNA expression. (A) IL-1β showed increased expression in Et-S2
group. (B) MCP-1 expression and (C) IL-6 expression were also increased, however were not significant.
Presentation of data is in the form Mean ± SEM, n = 2 to 3 per group
4.4. Butyrate increases M2 microglia polarization in the brain
On the contrary to ethanol exposure, butyrate is thought to provide a protective effect on the
brain by increasing the polarization of microglia towards the M2 phenotype. Post-mortem mouse
brains of the Et-S1 group showed a highly significant increase in the expression of M2 marker
BDNF (one way ANOVA, p = 0.016) compared to the control group (Figure 7A). There was also
an increase in BDNF expression in the Et-S2 group, however it was not significant compared to
control. Arg-1, also an important M2 marker, interestingly showed quite the opposite (Figure
7B), having significant increase in expression in Et-Et group, and a decrease in expression in the
Et-S2 group (one way ANOVA, p = 0.001, 0.02 respectively). IL-10, which is thought to be a

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pleiotropic cytokine that also has anti-inflammatory properties shows an increase in mRNA
expression in the Et-S1 group, however it does not show significance (Figure 7C).
Figure 7. M2 microglial marker mRNA expression. (A) BDNF showed increased expression in Et-S1
group. (B) Arg-1 expression is decreased in Et-S2 group but increased in Et-Et group. (C) IL-10
expression is increased in the Et-S1 group but does not show statistical significance. Presentation of data
is in the form Mean ± SEM, n = 2 to 3 per group

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4.5. Optimization of treatment conditions for BV-2 cell cultures using MTT
assay
BDNF is a very important marker of microglial activation to the M2 phenotype. The action of
BDNF relies on its binding with two of its receptors, TrkB and p75NTR. Thus, we hypothesized
that the differential effects of BDNF in the presence of ethanol and SB are a result of differential
expression of its receptor TrkB. Studying TrkB expression in an isolated system seemed ideal to
see its expression without the influence of other cells. Therefore, we assessed the expression of
TrkB, by BV-2 cell culture and subsequent western blot analysis.
Prior to the western blot analysis, optimization of treatment conditions for activation of BV-2
microglial cells was conducted. First, the different concentrations of SB were added to the cells,
with or without LPS (100 ng/mL) to assess the viability post-treatment (Figure 8A). A slight
reduction in viability with LPS was observed in all groups except the 1mM SB treated group
(denoted as SB-1), which showed an increase in viability with LPS. The 0.25mM SB treated
group (denoted as SB-0.25) showed slightly higher viability compared to the group with no SB.
The group treated with 0.5mM SB (denoted as SB-0.5) had similar viability compared to the
control groups. However, the 2mM SB treated group (denoted as SB-2) was the only group that
showed a significantly lower viability with LPS than without (one-way ANOVA, p = 0.003).
Thus we decided to use 0.5mM SB in further experiments, since the viability of the cells treated
with it was similar to the cells not treated with SB.
We then treated a separate batch of cells with different ethanol concentrations and LPS, either in
the presence or absence of 0.5mM SB (from now, denoted as only SB; Figure 8B). We observed
an increase in viability of cells treated with all ethanol concentrations and LPS in the presence of

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SB, with the exception of those treated with LPS and 50mM ethanol (denoted as LPS-E50), that
showed reduced viability with SB. However, a statistically significant difference in viability with
and without SB was only seen in four treatment conditions: LPS (one-way ANOVA, p = 0.03),
10mM ethanol (denoted as E10; one-way ANOVA, p = 0.02), 20mM ethanol (denoted as E20;
one-way ANOVA, p = 0.007) and E20 with LPS (denoted as LPS-E20; one-way ANOVA, p =
0.028). Treatment groups with ethanol alone had higher viability than their counterparts with
LPS.

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Figure 8. MTT Viability assay optimizing the treatment conditions. (A) Different concentrations of
SB were used as treatments with or without LPS, and viability was analyzed. SB-0.5 was used for further
experiments. (B) Different ethanol concentration treatments with or without LPS and SB were added to
BV-2 cells and viability was assessed. LPS-E10 and LPS-E50 were carried forward to further
experiments. Data represented as Mean ± SEM, n= 6 per group
Since the lowermost concentration E10 was showing high viability, we decided to use this as one
of the concentrations for further experiments. The other concentration we chose was E50 since it
showed reduced viability with SB.

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4.6. Butyrate upregulates the expression of BDNF receptor in BV2
microglial cells
Using the decided concentrations for SB (0.5mM) and ethanol (10mM and 50mM), we
performed overnight treatment and subsequent western blot analysis. The results demonstrated a
significant increase in TrkB expression (one way ANOVA, p = 0.004) when treated with ethanol
(10mM), and a non-significant increase at a higher ethanol concentration of 50mM, in the
presence of SB (0.25mM) compared to ethanol alone (Figures 9A, 9B). However, when
microglia were further activated with LPS (100 ng/mL), the increase in TrkB expression was
significant in cells treated with 50mM ethanol in the presence of SB, while 10mM ethanol
treated cells displayed a non-significant decrease in its expression. Our results are consistent with
animal studies that show that TrkB expression is upregulated in the presence of ethanol [68],
[84].
Figure 9. BDNF receptor (TrkB) expression in LPS activated BV-2 cells treated with ethanol in the
presence or absence of SB. (A) Cells treated with 10mM ethanol show an increase in expression in the
presence of SB without LPS activation. (B) Cells treated with 50mM ethanol show an increased
expression in the presence of SB, only when it was additionally activated by LPS. Data were normalized
with GAPDH integrated density. Presentation of data is in the form Mean ± SEM, n = 6 per group

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4.7. Butyrate provides neuroprotection by upregulating CX3CR1 mRNA
expression
CX3CR1 is a chemokine receptor that is commonly found on activated microglia, macrophages,
T cells and astrocytes. Its primary known function is to promote the migration and activation of
leukocytes. CX3CR1 plays a crucial role in brain development by engaging in synaptic pruning,
a process that is essential for promoting maturation of synaptic connectivity in the brain. It is
also responsible for neurogenesis in adult brains, specifically in the hippocampal region [85].
Previously, it has been identified that CX3CR1 knockout mice have impaired cognitive growth
and insufficient connectivity in the hippocampus [86]. Ethanol reduces the microglial number,
resulting in the lack of CX3CR1 in alcohol exposed brains. This leads to cognitive impairment
and decreased neurodevelopment. Thus we hypothesized that SB, known to attenuate
neuroinflammation, also upregulates CX3CR1 expression in alcohol-exposed mouse brains.
We found that the mRNA expression of CX3CR1 is increased in the Et-H20 group compared to
the control group (Figure 10). Interestingly, the expression is further enhanced in both the Et-S1
as well as the Et-S2 group compared to the control group. Also, the levels of expression in the
two SB treated groups are identical. This suggests that SB is a major factor in the increased
expression of CX3CR1.

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Figure 10. mRNA expression of CX3CR1 is upregulated in the SB treated groups compared to the
control group. Presentation of data is in the form Mean ± SEM, n = 3 to 4 per group

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Chapter 5: Discussion
The present study focused on two different aspects of AUD and the potential of using SB as a
therapeutic to mitigate alcohol intake. In our previous experiments where we treated mice with
antibiotics (ABX) and measured drinking patterns using the DID model, we observed that the gut
microbiome plays an important role in the development and progression of AUD [72]. ABX
dramatically alters the gut environment, thus being able to directly study the role of the gut
microbiome in AUD. We identified that butyrate producing bacteria are depleted in ABX treated
mice in the case of alcohol use disorder, and thus supplementing with SB could potentially
restore the balance and alleviate some of the negative effects of alcohol on the brain, such as
neuroinflammation [7], [79].
However, in these previous experiments ethanol and SB were provided ad-libitum, thus giving
the mice a choice to consume one liquid over the other based on preference. Thus the first
objective of this study was to identify whether consumption of either ethanol or sodium butyrate
was due to a preference for either liquid when they were provided simultaneously ad-libitum. For
this purpose, a two-bottle choice paradigm was used and it was found that mice had a lowered
preference for ethanol when supplemented with SB. Weekly analysis did not have any
conclusive results, with varying effects in each week. In some weeks, mice that were given SB
drank more ethanol, while in others they drank less. However, by averaging the weekly data, we
were able to notice significant differences in ethanol preference. A potential explanation for this
could possibly be due to the increased preference for SB. It is interesting to note that the
preference for ethanol was the lowest after 2 weeks of SB supplementation. This occurred twice
in our study; during the third week when SB was supplemented in ethanol naive mice and later in

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week 5 after the start of SB treatments in mice pre-exposed to ethanol. This can be substantiated
by the reduced overall ethanol intake, and an overall increased SB intake in that group. In
addition, there was a lower ethanol preference in mice that had access to SB from the beginning,
this group had a higher overall ethanol intake. We think that the mice developed a tolerance to
the effects of ethanol and SB, thus mitigating its effects and increasing ethanol intake. This
explains why there is a lower preference for ethanol, even with higher consumptions of SB. In
support of this, one particular study demonstrated ethanol tolerance after multiple exposures to
the same concentration. However, a higher concentration in subsequent exposures produced
ethanol mediated anxiolytic effects [87]. Another study showed that SB can induce tolerance to
itself by HDAC inhibition and subsequent acetylation of histones [88]. Concentration of ethanol
in the serum was drastically low in the group that had access to SB from the beginning,
suggesting the SB supplementation for a longer period of time increases ethanol metabolism,
leading to more ethanol intake over time.
These differences in consumption patterns highlight the complex nature of alcohol intake and
suggest that preference may not be the sole driving force behind addiction. Rather, factors such
as physiological effects, neurochemical changes, and the interplay between the gut and the CNS
may contribute to alcohol abuse.
As mentioned previously, chronic ethanol consumption has been shown to increase
neuroinflammation in various regions of the brain. Microglial activation and polarization are an
important mechanism that contributes to this neuroinflammation. Two phenotypes of microglia
have been observed when activated, the M1 pro-inflammatory phenotype and the M2 antiinflammatory phenotype. Inflammatory triggers such as ethanol can cause microglia to polarize

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to an M1 state. This increase in inflammatory microglia then shifts the polarization towards an
M2 state by internal mechanisms, thus activating anti-inflammatory pathways. We hypothesized
that SB could help switch the polarization from an M1 state to an M2 state. Therefore, we
investigated the mRNA expression of key pro inflammatory and anti-inflammatory cytokines,
and M1 and M2 microglia markers to analyze the upregulation and downregulation of these
genes. To accept our hypothesis we thought that in mice that are exposed to alcohol there would
be a greater expression of M1 markers and in those treated with SB, upregulation of M2 markers
would be observed.
Various studies have shown that ethanol exposure leads to a pro-inflammatory M1 microglial
phenotype, characterized by the release of pro-inflammatory cytokines and neurotoxicity, and the
suppression of anti-inflammatory markers. Similarly, our study demonstrated that post-mortem
brains of alcohol exposed mice exhibited increased mRNA expression of pro-inflammatory
cytokines IL-1β and IL-6 in mice that had access to ethanol only. We also saw a downregulation
in anti-inflammatory cytokine IL-10 and BDNF in this group. However MCP-1, an M1
microglial marker expression was downregulated and Arg-1, and M2 microglial marker was
upregulated. Mice that were treated with SB showed a shift in microglial polarization towards
the anti-inflammatory M2 phenotype. This was evident by the upregulation of BDNF and IL-10
and downregulation of IL-6. IL-1B and MCP-1 expression was reduced only in mice that were
given SB from the beginning. Surprisingly, Arg-1 was also downregulated in mice treated with
SB. This can be explained by evidence in scientific literature demonstrating that butyrate alone is
not sufficient to polarize macrophages to the M2 phenotype. In a study that explored the
potential of SB in activation of macrophages, it was shown that the presence of IL-4 is required
for the upregulation of the expression of Arg-1 in macrophages [89], [90]. Going on the

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assumption that microglia, that also function like macrophages act in the same way, one can
conclude that IL-4 needs to be present in the brain to see appropriate arg-1 expression. A
limitation of our study was that IL-4 expression was not analyzed. The anti-inflammatory effects
of BDNF can be attributed to the presence of its receptor TrkB, whose presence we confirmed in
the BV2 microglial cell line treated with SB.
Several reports have demonstrated polarization of microglia by alcohol and SB, however mixed
evidence exists regarding the specific phenotypes in each kind of treatment. Studies suggest that
there is no single phenotype associated with alcohol exposure and SB supplementation, as both
pro-inflammatory and anti-inflammatory states can be observed [9], [71]. Our findings of
differentially expressed pro and anti-inflammatory cytokines, and M1 and M2 markers validate
this statement and add to the notion on the complexity of microglial polarization in the brain.
This is also true, considering that our behavioral data suggests that SB given after 2 weeks of
alcohol exposure reduces drinking behavior; however on measuring the neuroinflammatory
response, we observed better attenuation of neuroinflammation by upregulated M2 microglia
when SB was given from the beginning. It is important to keep in mind that in our previous
studies with ABX, drinking-in-the-dark (DID) model was used to measure the effects of SB on
ethanol intake. However, our current model is a two-bottle choice, which represents a social
drinking behavior rather than a binge drinking model. A TBC model is a milder drinking model,
and does not drastically change the gut microbiome, like the DID model. This can explain the
inconsistent findings on microglial polarization in our study.
CX3CR1 and BDNF are two important aspects in our study. CX3CR1, the fractalkine receptor,
is commonly found on microglia. They are known to be responsible for various important

41 | P a g e
functions of the microglia. One study demonstrated that CX3CR1 knockout mice had reduced
neurogenesis in the hippocampal region of the brain. It also mentioned that a lack of CX3CR1
can lead to dysfunctional synaptic pruning as well as suppression of inflammatory responses
[85], [91]. Similarly, another study that performed selective genetic ablation of BDNF from
microglia found that this genetic ablation affected the self-renewal and proliferation capacity of
microglia, thus reducing its density. Furthermore, it also suppressed neurogenesis in the
hippocampal region, similar to what CX3CR1 knockout did [92]. These results can be connected
to another study that suggested that microglial depletion by BDNF is associated with impaired
synaptic plasticity related to learning abilities [86]. In support of all these findings, our studies
also show that SB plays a role in cognitive growth and neurodevelopment, shown by the increase
in CX3CR1 expression in both mice that were given SB from the beginning and after 2 weeks,
along with a reduced expression in mice that were given only alcohol. We also found a
downregulation of BDNF in alcohol exposed mice, and an upregulation with SB treatment.
Looking at our data as a whole, we concluded that SB given 2 weeks after ethanol exposure
provides more neuroprotection than when it is given from the beginning. This means that sodium
butyrate, rather than being a preventative measure, acts better as a therapeutic once increased
alcohol consumption has been established. Furthermore, all these findings are evidence that
although the polarization of microglia is an important mechanism of protective response in
alcohol use disorder, targeting this might not be ideal due the biphasic nature of microglia. It will
be interesting, however, to further explore a connection between CX3CR1 and BDNF in the
context of AUD and SB supplementation. Future therapies could focus on targeting these
neuroprotective elements to reduce alcohol dependence.

42 | P a g e
One of the characteristics of using an animal model to study microglia rather than using in-vitro
models is that we can also see the effects of other cells of the brain and peripheral cells on the
microglial function, activation, and polarization. AUD can lead to both neuroinflammation and
peripheral inflammation [93], and it is important to understand that these processes can interact
across the BBB and influence each other. With respect to that, a limitation in our study was that
prior to flash freezing the brain tissue during necropsy, the brain was not drained of its peripheral
blood, so it is possible that some of the cytokine mRNA expression observed could be influenced
by the presence of peripheral cytokines and/or the contribution form perivascular macrophages
and not just by the activation and polarization of the microglia, making it hard to delineate the
specific contribution of microglia in the observed effects. To counter the effects of peripheral
cytokines and cells, different isolation techniques could be used. Primarily, performing assays on
isolated microglia from the brains, instead of on whole brains can be a viable option to study the
effects of SB treatment on microglia alone. Furthermore, techniques like flow cytometry and
differential staining with multiple markers in immunohistochemical analysis can help us identify
microglia, macrophages and activated vs non-activated microglia, allowing us to make
inferences on specific cell types alone. Another limitation in our study is the limited sample size
with only about 10 mice per group. Having more mice for each treatment will allow us to
eliminate individual differences between mice. Our current approach of two-bottle choice is one
of the best ways to assess preference for ethanol. Our study design ensures that both the bottles
that are being given to the SB supplemented groups have SB in them, ensuring a guaranteed
administration of SB to the mice. However, different mice within a group can consume different
amounts adding to individual differences within a group. To avoid this, SB can be given through
oral gavage or intraperitoneal injection, thus ensuring that all mice get the same amount of SB.

43 | P a g e
This will eliminate the individual differences in SB consumption and lets us focus on preference
for ethanol alone. Moreover, it is important to establish a leakage control, where bottles with
liquids are placed in a cage without mice to measure how much liquid has leaked from the
sippers.
Targeting microglial polarization as well as BDNF and CX3CR1 using SB has a huge potential
in managing AUD. SB not only affects the neuroinflammatory pathways but also works by
modulating pathways in different organ systems, thus establishing it as a holistic drug in the case
of AUD. Further research must be pursued with a focus on individual organ systems as well as
analyzing how all these systems work together to help manage AUD with SB.
We hypothesized that mice that have been treated with SB have a lower preference for ethanol.
This was examined using a two-bottle choice paradigm, and in support of our hypothesis, those
mice did have a lower preference for ethanol, especially when it was treated 2 weeks after
ethanol exposure. Our next hypothesis was that mice that are treated with SB has a polarization
of microglia to an M2 phenotype. Using qRT-PCR and western blot we found that mice that
were not treated with SB had a mixed expression of M1 and M2 markers such as IL-1β, MCP-1,
IL-6, BDNF, Arg-1 and IL-10. where some were upregulated and some were downregulated,
which was also seen in SB treated mice. Neuroprotective markers BDNF and CX3CR1 were
particularly upregulated in mice that were treated with SB after 2 weeks of ethanol exposure. We
thus were able to conclude that although SB may not cause a shift of microglial polarization into
a specific phenotype, SB treatment provided after ethanol dependence provides neuroprotection
using microglial polarization as one of its mechanisms.

44 | P a g e
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Abstract (if available)

Abstract Alcohol Use Disorder (AUD) is a complex neurological condition characterized by compulsive alcohol consumption and adverse effects on physical and mental health. Despite its prevalence and impact, effective treatments for AUD remain limited. One area of investigation lies in the gut-brain axis, where disruptions in the gut microbiome due to alcohol consumption contribute to neuroinflammation and addiction development. Notably, the imbalance of short-chain fatty acids, such as butyrate has emerged as a key factor in this process. Butyrate, known for its anti inflammatory properties, has been proposed as a potential therapeutic agent for AUD due to its ability to modulate microglia. Microglia play a pivotal role in neuroinflammation and have been implicated in the pathophysiology of AUD. These cells exhibit distinct functional states, including pro-inflammatory M1 and anti-inflammatory M2 states, which can be influenced by neuromodulators such as alcohol. However, the specific effects of alcohol on microglia polarization and how they may be altered by sodium butyrate (SB) supplementation remain poorly understood. This thesis aims to elucidate the potential role of SB in shifting the polarization of microglia and explores microglial polarization as a target for AUD management through treatment of SB

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Creator Vasisht, Surabhi (author)

Core Title Polarization of microglia by sodium butyrate in Alcohol Use Disorder

School School of Pharmacy

Degree Master of Science

Degree Program Pharmaceutical Sciences

Degree Conferral Date 2024-05

Publication Date 05/21/2024

Defense Date 05/10/2024

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

Tag alcohol use disorder,cytokines,gut-brain axis,microglia,neuroinflammation,OAI-PMH Harvest,polarization,short-chain fatty acid,sodium butyrate,two-bottle choice

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