University of Southern California Dissertations and Theses

Effects of western dietary factors during early life on glucose metabolism, the gut microbiome, and neurocognition

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Effects of western dietary factors during early life on glucose metabolism, the gut microbiome, and neurocognition

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Content EFFECTS OF WESTERN DIETARY FACTORS DURING EARLY LIFE ON GLUCOSE
METABOLISM, THE GUT MICROBIOME, AND NEUROCOGNITION
by
LINDA TSAN
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(NEUROSCIENCE)
May 2022
Copyright 2022 Linda Tsan

ii

Dedication

For my sisters WENDY TSAN and HANG TSAN
who contributed the most to my early life development

and my dog LUCKY TSAN
who has been walking with me for all 10 years of my adulthood

iii
Acknowledgements

I couldn’t have done this without my faculty advisor, Scott E. Kanoski, PhD. His
mentorship taught me that it’s good to be dubious. He set up a training environment
where questions are encouraged. With that in mind, I learned how to critique my own
data and build upon each study, in a process he calls “planting a seed,” where he
suggests an idea and provides the necessary support to nourish the growth of the study.
I also deeply value his penchant to collaborate both internally and externally, which
showed me how much stronger research can become when different opinions and
viewpoints are present throughout the duration of a project.

I am also extremely grateful to my dissertation committee members: Lindsey A.
Schier, PhD, Katie A. Page, MD, and Michael I. Goran, PhD, who have shaped
many of the projects discussed here with their unique expertise in studying dietary
influences on development and through their annual organization of USC’s Diabetes and
Obesity Symposium, where I held my first graduate oral presentation and learned how
this work fits into the greater context of the field.

I would also like to thank key members of the lab that have helped me throughout
graduate school: our lab managers, Alyssa Cortella, MPH, and Kirsten Donahue, former
and current postdoctoral scholars, Emily E. Noble, PhD, Elizabeth A. Davis, PhD, Sarah
J. Terrill, PhD, Léa Décarie-Spain, PhD, and Anna M.R. Hayes, PhD, prior and present
graduate students, Andrea N. Suarez, PhD, Clarissa M. Liu, PhD, Keshav Subramanian,
Jessica (Jesse) J. Rea, and Molly Klug, lab technicians, Lekha S. Chirala and Logan
Tierno-Lauer, and undergraduate students Lana Bridi, Rae Lan, Victor Lee, Ryan
Fatemi, Jamie Clarke, Anish Reddy, Alicia Kao, Iris Deng, Kara McBurnett, Grace
Schwartz, and Isabella Gianatiempo. Their enthusiasm and teamwork helped fuel these
experiments.

I would also like to acknowledge researchers whose mentorship inspired me to pursue a
Ph.D. in neuroscience, including: Nigel T. Maidment, PhD, Niall P. Murphy, PhD, Hoa
Lam, MS, Alisa R. Kosheleff, PhD, Ian A. Mendez, PhD, Zhan Shu, PhD, Jingwen Araki,
Linda M. Liau, MD, PhD, MBA, Sylvia Odesa, Horacio Soto, Emma Billingslea-Yoon,
NP, Joseph Antonios, MD, PhD, Stephen Miloro, PhD, Joey Orpilla, and Tama Hasson,
PhD. Their teaching, advice and encouragement prepared me for graduate school.

Being the first of a first-generation family to pursue a graduate degree, I would also like
to express deep gratitude to my family for their support of my higher education. Lastly,
I’d like to thank my partner, William J. Matloff, for helping me throughout my graduate
studies from neuroscience discussions on the intercampus shuttle after core class to
presentation practice before conferences and symposiums despite being just as busy
pursuing his MD/PhD at USC.

iv

Table of Contents

Dedication……………………………………………………………………………………….…………………ii

Acknowledgements……………………………………………………………………………….………….iii

List of Figures…………………………………………………………………………………………………….v

Abstract……………………………………………………………………………………………………………..vi

CHAPTER 1: GENERAL INTRODUCTION……………………………..………………..1

CHAPTER 2: EARLY LIFE WESTERN-DIET INDUCED MEMORY
IMPAIRMENTS AND GUT MICROBIOME CHANGES IN FEMALE RATS ARE
LONG-LASTING DESPITE HEALTHY DIETARY INTERVENTION……………17
Abstract................................................................................................................................17
Introduction…………………………………………………………………………………………………………18
Materials and Methods…………………………………………………………………………………………20
Results…………………………………………………………………………………………………………………29
Discussion……………………………………………………………………………………………………………40

CHAPTER 3: EARLY LIFE LOW-CALORIE SWEETENER CONSUMPTION
DISRUPTS GLUCOSE REGULATION, SUGAR-MOTIVATED BEHAVIOR,
pAND MEMORY FUNCTION IN
RATS………………………………………………………………………………………………..49
Abstract...............................................................................................................................49
Introduction…………………………………………………………………………………………………………50
Materials and Methods………………………………………………………………………………………….51
Results…………………………………………………………………………………………………………………69
Discussion……………………………………………………………………………………………………………81

CHAPTER 4: GENERAL CONCLUSIONS………………………………………………85

REFERENCES……………………………………………………………………………………91

v
List of Figures

Figure 2.1: Timeline of cafeteria diet and sugar experiments. Pg. 24
Figure 2.2: Energy balance and metabolic outcomes following adolescent
cafeteria diet consumption.
Pg. 30
Figure 2.3: Energy balance and metabolic outcomes following adolescent sugar
diet consumption.
Pg. 32
Figure 2.4: Hippocampal-dependent memory following adolescent cafeteria diet
consumption.
Pg. 33
Figure 2.5: Hippocampal-dependent memory following adolescent sugar diet
consumption.
Pg. 35
Figure 2.6: Gut microbiome following adolescent cafeteria diet consumption. Pg. 37
Figure 2.7: Gut microbiome following adolescent sugar diet consumption. Pg. 39
Figure 3.1: Timeline of LCS experiments. Pg. 68
Figure 3.2: Early life LCS consumption impairs peripheral glucose metabolism
without influencing total caloric intake, body weight, or adiposity
Pg. 69
Figure 3.3: Early life LCS consumption impairs hippocampal-dependent
memory during adulthood
Pg. 71
Figure 3.4: Early life LCS exposure alters sugar consumption and reduces
lingual sweet taste receptor expression
Pg. 74
Figure 3.5: Early life LCS consumption reduces effort-based responding for
sucrose while increasing long term free-access sucrose intake
Pg. 76
Figure 3.6: Early life LCS consumption differentially impacts gene expression
patterns in the HPC and ACB
Pg. 78

vi
Abstract

Consumption of high fat, high sugar Western diets (WD) during adolescence
results in neurocognitive impairments and gut microbiome dysbiosis. Whether these
adverse outcomes are reversible in adulthood following intervention with a healthy diet
is unknown. Furthermore, while consumption of low-calorie sweeteners (LCS) during
early life is increasing due to its widespread presence in the food environment and
efforts to mitigate obesity through sugar replacement, mechanistic studies on the long-
term impact of early-life LCS consumption on cognitive, sensory-reward, and
physiological function are lacking. In Chapter 1, we review the current state of the
literature surrounding the short-term and long-term effects of Western diet exposure in
mechanistic studies involving adolescent rodents. In Chapters 2-3, data is presented
from two mechanistic studies involving WD consumption in adolescent rodents that aim
to address 1) the endurance of WD-induced metabolic, memory, and gut microbiome
impairments following healthy dietary intervention and 2) the metabolic and
neurocognitive effects of LCS use. In Chapter 4, we discuss the implications and future
directions of the data collected in this dissertation. Together, these chapters fill a
substantial gap in the literature regarding the effectiveness of healthy dietary
intervention and the use of LCS in avoiding the effects of early life WD exposure in rats.
Overall, the data suggests that the effects of healthy dietary intervention depends largely
on the diet composition consumed during early life and that LCS use during early life
has negative implications on metabolism and neurocognition in adulthood in rats.

1
Chapter 1: General Introduction
Adapted from Tsan L., Décarie-Spain L., Noble E.E., Kanoski S.E. Western Diet
Consumption During Development: Setting the Stage for Neurocognitive Dysfunction,
Front Neurosci., 2021

Children in the U.S. are exposed to a dietary environment where there is an
overabundance of highly palatable foods that are easily affordable and readily
accessible. Observations from earlier National Health and Nutrition Examination
Surveys (2003-2004, 2005-2006) report that the highest sources of energy for 2- to 18-
year-olds were grain desserts, pizza, and soda, which are low in beneficial nutrients, but
high in solid fats and/or added sugars (1). More recent data indicates that consumption
of saturated fat and sugar in children continues to exceed the recommended limit of
fewer than 10% of total calories for anyone 2-years-old or older, as boys and girls (age 1-
18) obtain a range of about 11-12% of their total calories on average from saturated fat
and a range of about 11-17% of their total calories on average from added sugar (2). This
type of dietary environment, along with a shift towards larger food portions, has
undoubtedly contributed to the alarming increased prevalence of childhood obesity,
which is now approximately 18% in children aged 2-19 years (3). In addition, the
majority of children with obesity remain obese, both as adolescents and as adults (4).
Emerging evidence reveals that both childhood and adult obesity are associated with
impaired performance in various cognitive tasks (5–7). However, given that obesity is
strongly associated with consumption of a Western Diet (WD; specified in more detail
below), a standing question arises as to whether the WD per se may impart
neurocognitive dysfunction independent of obesity and/or its associated metabolic

2
impairments. Indeed, evidence from both humans and preclinical rodent models
indicates that habitual consumption of a WD during early life developmental periods
can lead to long-lasting neurocognitive dysfunction even independent of obesity and
severe metabolic dysfunction (8, 9). Thus, in order to better inform policies relating to
dietary recommendations, it is imperative to understand the dietary and neurobiological
mechanisms linking perinatal and childhood WD consumption with impaired cognitive
abilities throughout the lifespan.
To study the link between WD patterns during early life periods and
neurocognitive development, rodent models are often used to target discrete periods of
development during which dietary components can be administered with rigorous
control and with objective quantification of the amount of calories consumed. Although
the exact timing varies slightly by strain, in rats postnatal day (PN) 22-27 is considered
the approximate juvenile stage of development, PN 28–42 equivalent to the early-mid
adolescent period (~12–17 years in humans), and PN 43–55 comparable to the late
adolescence/emerging adulthood period in humans (~18–25 years) (Spear, 2016). The
juvenile and adolescent phases of development are critical periods through which
complex cognitive abilities such as working memory, sociability, and inhibitory control
develop (13).
In laboratory rodents, several different dietary manipulations have been used to
model aspects of the WD. A rodent “high fat diet” (HFD) model typically involves
increasing the amount of fat (as a % of total kcal, e.g., 45% or 60% kcal from fat) while
reducing the amount of carbohydrates compared to low fat and high carbohydrate
standard rodent control diets. However, the carbohydrate content of a common rodent
HFD is predominantly comprised of simple sugars, vs. the complex polysaccharide-

3
based carbohydrate content of a typical rodent control diet (with the exception of some
low-fat control diets that are high in sucrose). Another common rodent WD model is a
cafeteria diet, which is a free-choice diet with combination of highly palatable, energy
dense foods (e.g., high saturated fat, high sugar) that are commonly consumed by
humans. Modeling the obesogenic environment omnipresent in modern Westernized
cultures, these diets are provided in the home cages and are therefore easily accessible
to the animals. Relative to a control group on a healthy diet, rodents exposed to these
WD models may, but do not always, display one or more of the following outcomes
associated with metabolic syndrome and obesity: increased caloric intake, body weight
gain, increased adiposity, hyperinsulinemia, hyperglycemia, glucose intolerance, and
inflammation contributing to hepatosteatosis (14).
Cafeteria diets are often obesogenic when consumed by rodents during
adulthood, however, whether or not adolescent consumption of cafeteria diets in
rodents promotes cognitive impairment is still controversial. For example, adolescent
male rats on a cafeteria diet consisting of a variety of high fat and high sugar palatable
food options, standard chow, and a 15% (w/v) sucrose solution weighed more and had
greater adiposity compared with rats maintained on chow and water alone. The cafeteria
diet-fed rats also exhibited impairments in hippocampal-dependent spatial learning and
memory in the Morris Water Maze (MWM), but not object novelty detection or fear
acquisition, during adulthood (15). In contrast, a similar study, using very similar
dietary parameters of highly palatable human foods along with standard chow and a
12% w/v sucrose solution, found no effect of adolescent consumption of a cafeteria diet
on spatial memory in adulthood using the Barnes Maze (16). Despite intact spatial
learning, the cafeteria diet rats displayed an obesogenic phenotype as indicated by

4
increased body weights, visceral adiposity, hyperinsulinemia, glucose intolerance, and
dyslipidemia with elevated serum triglyceride levels and reduced HDL cholesterol, and
greater hippocampal neuroinflammation in adulthood. Moreover, replacing the
cafeteria diet with a standard rodent diet appeared to reverse all of the metabolic deficits
mentioned before as well as the neuroinflammation (16). These studies reveal that the
effects of an adolescent cafeteria diet on memory are variable and highlight that more
work is needed to identify critical mediating variables, such as the percentage of fat to
sugar. However, given that in some cases obesogenic effects have been observed in the
absence of memory impairments (and vice versa), these findings further highlight a
framework in which the effects of early life WD consumption on cognition and
metabolism are dissociable.

1.1 Acute exposure to an early life WD on learning and memory
Evidence from multiple studies suggests that adolescent consumption of a WD
containing a high % kcal from fat impairs hippocampal-dependent learning and memory
in rodents, and that these effects even occur following acute exposure. For example,
short-term feeding (1 week, from PN 21-28) of a WD containing 60% kcals from fat in
male mice impaired spatial memory in the Y-maze alteration task and object recognition
memory impairment in the Novel Object Recognition (NOR) task during adolescence
(17). Similarly, impaired object location memory and impaired hippocampal long-term
potentiation was reported in adolescent male rats with a similar dietary exposure (18).
Finally, impaired extinction of cued fear conditioning is observed in male rats after only
1 week of exposure (PN 31-38) to a 41% kcals saturated fat diet in male rats (19).

5
Together, these reports suggest that short-term exposure to high-fat WDs post-weaning
impairs spatial and episodic memory during adolescence.
While the aforementioned short-term WD exposure studies suggest that the diet
significantly impacted memory, these impairments were likely independent of metabolic
effects, as the short duration on the diet was insufficient to promote weight gain (17–19)
or aberrant glucose metabolism (17, 19). Kaczmarczyk and colleagues reported impaired
performance in the NOR task in adolescent mice after both 1 and 3 weeks of exposure to
a 60% kcals fat WD, which could be improved by switching animals to a healthy low-fat
diet for 1 week. On the other hand, spatial memory deficits in the Y-maze task were
present after 1 week, but this effect could no longer be observed after 3 weeks of WD
exposure. The 3 weeks of WD timepoint coincides with elevated activity of monoamine
oxidase A and B, the enzymes that metabolize dopamine, in the hippocampus (HPC)
and hypothalamus. In combination with decreased levels of hypothalamic dopamine
and increased levels of its metabolic homovanilic acid in the HPC at the 1 week
timepoint only, these results suggest spatial memory deficits may be consequent to
reduced dopamine signaling after 1 week of WD exposure, whereas dopamine levels are
restored after 3 weeks with increased activity of dopamine metabolizing enzymes (17).
Another possible mechanism for memory impairment following short-term WD feeding
involves glucocorticoid receptors. Khazen and colleagues found that intraperitoneal
treatment with a glucocorticoid receptor antagonist was able to reverse impaired long-
term potentiation and memory deficits, suggesting that glucocorticoid signaling may
mediate the effects of WD on hippocampal dysfunction. Similarly, Vega-Torres and
colleagues reported dampened neuronal activity in the amygdala following foot shock
delivery, as well as increased gene expression for the corticotropin release hormone

6
receptor-1 within the medial prefrontal cortex (mPFC). In sum, short-term exposure to a
WD post-weaning can impair memory independent of the obesogenic effects of the diet,
and these memory deficits are associated with changes in dopamine, glucocorticoid
signaling, and long-term potentiation in the HPC and mPFC.

1.2 Chronic exposure to an early life WD on learning and memory
Given that short-term feeding of WD impacts memory function, it is not
surprising that long-term WD feeding also impairs memory. For example, while binging
on a WD (45% kcals from fat) for 2 hrs daily throughout adolescence did not result in
spatial memory deficits (20), ad libitum access (for 1+ month) to this diet after weaning
promotes deficits in spatial learning in the MWM task (21), the Novel Object Location
(NOL) task (22), the radial arm maze task (23), and the Hebb Williams Maze (20) in
adult male rodents. Impairments are also seen in reversal learning in the MWM (21) and
enhanced aversive and auditory fear memory (24), as assessed by Conditioned Odor
Avoidance (COA) and auditory fear conditioning, respectively. Although 2hrs daily
access to high fat and high sugar pellets for 28 days during adolescence did not affect
odor recognition, rats under this diet regimen failed to demonstrate novelty preference
in the NOR task (25). Adolescent (PN 28-56) consumption of a 63% kcal fat diet in male
mice impaired discrimination in the Y-maze, reversal learning in the MWM, and cued
fear extinction (26). Alterations in fear extinction were also reported in male rats fed a
41% kcal fat diet for 82 days (PN 28-110) (27). Interestingly, adolescent exposure to a
lard-enriched WD for 13 weeks (well into adulthood) showed memory deficits in the
radial arm maze and the NOL task, despite animals undergoing a 70% caloric restriction
over the last 5 weeks of the diet period (28, 29). Importantly, in some cases switching

7
from a 45% fat diet to a standard rodent diet for 2 weeks can reverse the spatial memory
deficits (20). Similarly, chronic consumption of a WD initiated during adolescence and
consisting of powdered chow, lard, and dextrose (with 41.7% of the calories were derived
from fat) is also associated with episodic memory impairments in adulthood (30).
Switching the rats to a control diet for 5 months after an initial 3 months of exposure to
a lard-enriched 45% fat WD initiated at weaning, normalized memory impairments in
the MWM and COA task (31). These data suggest that male rats develop impairments in
spatial memory, reversal learning, and aversive and auditory fear memory in adulthood
in response to long-term high-fat, high-sugar consumption starting during adolescence,
and moreover, that these effects may be reversible in some cases with dietary
intervention. Importantly, learning and memory deficits in male rodents were not
observed when WD consumption for a similar duration was confined to adulthood,
despite similar diet-induced elevations in body weight and metabolic disruption (21, 23,
24, 26, 29). These findings corroborate that adolescence is a developmental period of
particular vulnerability for WD effects on learning and memory function.
In addition to memory impairment, long-term feeding of a WD also leads to
significant disruptions in metabolism and neurobiological systems associated with
memory control. While short-term feeding of a WD during adolescence does not
promote weight gain, long-term feeding from adolescence to adulthood typically
promotes weight gain in male rodents (20, 21, 23, 24, 26–30). Additionally, prolonged
intake (3+ months) of a WD started during adolescence and maintained well into
adulthood in male rodents imparts metabolic alterations in adulthood such as increased
circulating leptin (23, 28, 29), corticosterone, cholesterol, and insulin (23) as well as
hyperglycemia (29, 32) and insulin resistance (30, 32). Memory deficits following

8
adolescent WD exposure are also found in the absence of significant weight gain, such as
impaired NOR in male rats with intermittent access (2 hrs daily) to high fat and high
sugar pellets (25). Long-term consumption of a WD, initiated during adolescence,
resulted in molecular alterations in the HPC, amygdala and mPFC that accompanied
memory impairments at adulthood. For example, reduced neurogenesis (23, 31, 32),
increased microglial activation (32) and diminished gene expression of monoamine
oxidase A (25) can be observed in the HPC of rodents fed a WD since adolescence and
displaying spatial memory deficits. Alterations in aversive and auditory fear memory in
adult male rats fed a WD since adolescence are attenuated by glucocorticoid receptor
antagonism in the amygdala (24). Rodents with impaired extinction and reversal
learning, but also spatial memory and NOR, due to WD exposure during adolescence,
presented with downregulation of the synaptic modulator reelin and altered long term
depression (26) and reduced BDNF and monoamine oxidase A gene expression (25) in
the mPFC. Altogether, these results demonstrate weight gain and metabolic
impairments often accompany but are not conditional for WD initiated during
adolescence to induce learning and memory deficits. These data further suggest
neurogenesis, microglial activation, glucocorticoid signaling, as well as synaptic
transmission and neural plasticity in the HPC, amygdala and mPFC as potential
mechanisms.

1.3 Adolescent consumption of sugars on learning and memory
Given that rodent WDs high in fat are often also high in sugar, it is important to
investigate the contribution of dietary sugars to the effects on learning and memory.
Common obesity-promoting diet compositions from Research Diets consist of the 45%

9
kcal HFD, which contains 17.5% of kcal from sucrose, the 58% kcal HFD, which contains
about 13% of kcal from sucrose, and the 60% kcal HFD, which contains about 7.5% of
kcal from sucrose. Interestingly, the effects of sugar alone have been shown to impact
learning and memory independent of weight gain when given during the adolescent
period (33–38). Furthermore, the effects of adolescent dietary sugar on learning and
memory function persist into adulthood. For example, male rats given free access to an
11% w/v high fructose corn syrup drink for at least 30 days during adolescence had
episodic and spatial memory impairments, assessed by the Novel Object in Context
(NOIC), Barnes Maze, and MWM tasks (33, 36, 38). Furthermore, NOIC memory
impairments persisted even when animals were tested after several months without
access to sugar solutions (Noble et al., 2019). Notably, adult rats fed sugar solutions for
a similar length of time did not show memory deficits (Hsu et al., 2015). Rats consuming
a high in sugar, but low in fat diet (26.7% sucrose/lactose, 6.5% fat) starting at weaning
impaired episodic and spatial memory in the object recognition and Y-Maze tasks and
impaired learning in the contextual fear conditioning task in adulthood (39). Overall,
these studies suggest that WDs high in sugar (independent of elevated fat content vs. a
control diet) have adverse effects on learning and memory that last into adulthood and
are not easily reversible by removal of the diet.
While the studies described above typically involve ad libitum access to the
experimental diet, some studies have examined the effects of intermittent access to a
sugar solution during adolescence on learning and memory function. Results of these
studies suggest that intermittent sugar access similarly conferred lasting impairments in
learning and memory function later in life (34, 35, 37, 38). For example, male rats given
intermittent access (2 hrs daily) to a 10% w/v sucrose drink during adolescence were

10
impaired in both the place recognition (35) and object-in-place recognition tasks (34,
35) and were unable to use contextual information to discriminate between the context-
appropriate and context-inappropriate levers in a context devaluation task, which
requires communication between the mPFC and HPC (34). Similarly, male rats with
intermittent access to a 10% sucrose solution for 28 days (PN 28-55) presented
impairments in both learning and memory in the MWM task at adulthood (40). Despite
conferring impairments in learning and memory, male rats that had free access to an
11% w/v sugar solution have normal body weights throughout the dietary exposure
period (33, 38), with one study finding that consumption of a high fructose corn syrup
solution actually led to a decrease in body weight despite the rats showing glucose
intolerance and increased adiposity (36). Intermittent access to an 10-11% w/v sugar
solution also did not promote weight gain during the 30 days of access in either males
(35, 38, 40) or females (35), yet one study has found that significant weight gain
occurred in male rats after the intermittent access period to a 10% sucrose solution (34).
Collectively, these studies show that intermittent access to a sugar solution during
adolescence can impart long-lasting memory deficits, and that these effects can occur
independent of body weight gain.
With regard to underlying neurobiological mechanisms for how high sugar diets
during adolescence impact memory function, memory deficits induced by free access to
the 11% w/v sugar solution in adolescence are associated with increased plasma insulin
and pro-inflammatory cytokines such as interleukin 6 and interleukin 1β in the dorsal
HPC (33). Moreover, another study found systemic inflammation after adolescent
consumption of a 11% w/v sugar solution. Using in-vivo electrophysiology, the authors
revealed that concurrent with systemic inflammation, high fructose corn syrup

11
consumption induced hyperexcitability in hippocampal CA3-CA1 synapses (36).
Furthermore, the effect of a diet high in sugar on plasticity depended on the
developmental stage, such that during adolescence, 1 week of consumption reduced
synaptophysin, BDNF, protein kinase B (AKT), and phosphorylated AKT in the HPC.
However, when access to the simple sugar-enriched WD is maintained into adulthood,
there is increased synaptophysin, spinophilin/neurabin-II, and decreased BDNF and
neuronal nitric oxide synthase, suggesting that plasticity markers change depending on
stage of development (41). As opposed to free access to sugar, the memory deficits
associated with intermittent access to sugar in adolescent males were accompanied by
deficits in parvalbumin-immunoreactive cell density in the HPC and mPFC in adulthood
(34). Altogether, these findings suggest that the HPC is a region that is particularly
sensitive to perturbations by adolescent dietary sugar consumption, with plasticity and
inflammatory signaling pathways implicated as putative mechanistic links between diet
and memory dysfunction.

1.4 Low-calorie sweeteners (LCS) as an alternative to sugar
Given that sugar consumption can lead to weight gain, metabolic impairment,
and cognitive dysfunction (42–44), sugar is often substituted with LCS in food products
to maintain sweet taste while reducing caloric intake and mitigating the negative health
effects of sugar. Despite having little to no calories, the evidence for LCS’s use in weight
management has been conflicting in observational studies (45, 46) with many studies
indicating that there are potential risks to consuming LCS, particularly due to its
consumption activating brain regions associated with sweet taste (47–51). The brain is
capable of distinguishing LCS from sugar (52–54) and studies have shown that

12
consuming LCS may affect the way the body recognizes and processes sweet foods over
time due to the mismatch of uncoupling sweet taste from calories (55–57). With the
widespread use of LCS during early life (58, 59), it is imperative to understand the
health implications of consuming LCS during development. Studies thus far have also
pointed to uncertainty as to whether LCSs benefit or worsen weight and metabolic
health in children, with observational studies finding that LCS consumption is positively
associated with weight gain whereas interventional studies reporting that LCS
consumption may help with weight management in children (58). There are also limited
rodent studies that found adverse metabolic effects due to LCS consumption during
early life (60–62) or adulthood (63–65). Furthermore, some rodent studies suggest that
LCS consumption can impair memory when consumed in adulthood (64, 66) and that
effects on cognition due to LCS consumption can be transgenerational (62, 67).
However, these studies often use doses that are above the acceptable daily intake (ADI)
as recommended by the U.S. Food and Drug Administration (FDA) by providing ad
libitum access to the LCS in question. Therefore, more mechanistic studies evaluating
LCS use at the ADI during development are needed.

1.5 Adolescent WD exposure on the gut microbiome
Given that WD consumption during early life can impact metabolism (68–70),
one potential mechanism for this is via the gut microbiome. Microbes in the gut
microbiome can alter metabolism through the production of short chain fatty acids such
as acetate, propionate and butyrate (71). Specifically, butyrate and proprionate assist
gluconeogenesis (72) whereas acetate is involved in cholesterol metabolism and
lipogenesis (71). Although there is a certain degree of stability in the gut microbiome

13
that is established during infancy (73–75), it has been shown that WD consumption can
significantly alter the composition of the gut microbiome throughout life (76–79). For
example, high fat diet (42% kJ from fat) consumption in male mice during the juvenile
and adolescent period had a significant lasting impact on alpha diversity, which
measured the species richness and diversity within a single sample, and beta diversity,
which measured differences in microbial communities between WD mice and CTL mice,
in the gut microbiome in adulthood (80). In another study, consumption of the LCS
aspartame or stevia in combination with a high fat, high sucrose diet during pregnancy
and lactation in obese rat dams led to increased body fat and disrupted the gut
microbiota in male and female offspring despite being weaned onto a control diet (62).
In light of the gut microbiome’s potential role in metabolism following WD
consumption, which is known to affect cognitive performance in cases of metabolic
syndrome (81, 82), more studies have elucidated a role of the gut microbiome following
WD consumption in cognitive performance (83–86). For example, Noble et al. (83)
discovered two species in the genus Parabacteroides (P. distasonis and P. johnsonii)
that were elevated in abundance and negatively correlated with HPC-dependent
memory in male rats following adolescent sugar consumption (ad libitum access to an
11% w/v solution of 65% fructose and 35% glucose in water). Altogether, these studies
highlight a significant role of the gut microbiome in metabolism and neurocognition,
which may be more sensitive to WD exposure during early life.
1.6 Sex differences on memory following adolescent WD exposure
The influence of sex with regards to adolescent WD exposure effects on memory
function is poorly understood. Males, but not females, on a chronic 45% kcals fat WD

14
have reduced freezing behavior compared with chow fed controls in a contextual fear
conditioning task in adulthood (87). However, given that WD consumption can be
anxiolytic, it is difficult to determine whether the reduced freezing behavior was due to
improved memory function per se, or was a function of reduced anxiety. Moreover,
Buyukata et al. found that both male and female rats on an intermittent sucrose access
schedule showed impaired NOR memory during adolescence when the objects shared
multiple similar features. However, when the objects were arranged with either small or
large spatial separations (spontaneous location recognition task), males that consumed
sugar performed worse in tasks with small spatial separations, whereas females
performed worse in tasks with large spatial separations (37). In another study, both
male and female rats previously on a chronic 58% kcals fat WD during adolescence
displayed impaired memory in a spatial object recognition task in adulthood (88). In
addition, female mice fed for 12 weeks of a 60% kcals fat WD showed altered reversal
but not initial learning in the MWM task (89). While these studies suggest that the
effects of adolescent WD exposure are sexually dimorphic depending on the task and
type of memory being tested, further research is clearly needed in this area.
Estrogen may be a critical factor mediating sex differences in vulnerability to
adolescent WD-induced memory impairments. For example, in female rats intermittent
dietary sucrose access during adolescence (10% w/v sucrose solution, 2 hrs daily) did
not impact Novel Place Recognition (NPR) performance, however the rats were only
able to perform place recognition correctly during the proestrus phase of the estrous
cycle, a stage that contains higher levels of circulating estrogens (35). Taken together,
similar to males, female rats given intermittent sugar access display impairments in

15
episodic memory. However, the episodic memory deficits may be determined by the
stage of the estrous cycle.
Metabolically, female mice exhibit similar deficits to males in response to a 45%
kcal from fat WD from adolescence to adulthood, having significant weight gain relative
to controls despite comparable caloric intake (87). However, WD-fed males are
distinguished from females by having higher glucose levels relative to controls fed a
healthy low fat diet (87). Unlike male rats, female rats did not gain significant weight or
display glucose intolerance after chronic WD exposure (58% kcal fat), suggesting that
female rats may develop a less severe metabolic phenotype under these conditions
compared to males (88). However, female mice fed a 60% kcal fat WD for 12 weeks did
develop hyperphagia and greater body weight gain relative to animals receiving the
control diet, and alterations in reversal learning in the MWM task were prevented by
wheel running (89). As for a potential mechanism as to how male and female rodents
differ in regard to contextual fear conditioning, Hwang et al (87) found that WD-fed
males, but not females, had reduced long term potentiation but were also lacking a
normal long term depression response. Together, these studies suggest that chronic
exposure to WD starting in adolescence may alter learning and memory processes in
female rodents, although the specific types of memory involved may be sex-dependent,
and like males, memory function is dissociable from metabolic impairments.

1.7 Summary and Overview of Chapters
Herein we discuss insights from male and female rodent studies that inform on
the impact of WD (cafeteria diet, sugar, and LCS) consumed during early life
developmental stages on various cognitive domains, including anxiety-like behavior and

16
reward-motivated behavior, but largely learning and memory function. A second
overarching goal of this dissertation is to describe potential underlying central and
peripheral mechanisms, such as through the involvement of the gut microbiome, linking
dietary models with cognitive outcomes. We also describe neurocognitive results with
regards to whether or not these outcomes were accompanied by obesogenic outcomes,
thus leading to a concluding framework on the effects of early life WD on cognition and
metabolism.
Importantly, the subsequent research discussed in the following chapters
contribute to several key gaps in the literature regarding WD exposure during early life
periods of development. For example, while the effects of early life WD exposure (sugar,
saturated fat, LCS) on metabolism and brain responses has been studied in rodents and
children (33, 38, 47, 62, 90, 91), these data offer more mechanistic evidence on the
involvement of the gut microbiome and the effects of these diets on neurocognition
using carefully controlled rodent experiments that model daily human consumption
during adolescence. Importantly, we include experiments that study the neurocognitive
effects of early life WD exposure in female rodents, which has been largely
understudied. Finally, we also address whether or not these early life WD-induced
metabolic and neurocognitive effects endure by assessing these outcomes in adulthood
well after the diets were removed.

17
Chapter 2: Early life Western diet-induced memory impairments and gut
microbiome changes in female rats are long-lasting despite healthy dietary
intervention
Tsan L., Sun S., Hayes A.M.R., Bridi L., Chirala L.S., Noble E.E., Fodor A.A., Kanoski
S.E. Nutr Neurosci., 2021
Abstract:
Consumption of a Western diet during adolescence results in hippocampus
(HPC)-dependent memory impairments and gut microbiome dysbiosis. Whether these
adverse outcomes persist in adulthood following intervention with a healthy diet is
unknown. Here we assessed the short- and long-term effects of adolescent consumption
of a Western diet enriched with either sugar alone, or sugar and fat on metabolic
outcomes, HPC-dependent memory, and gut microbiota. Adolescent female rats (PN 26)
were fed a healthy standard chow diet (CHOW), a chow diet with access to 11% sugar
solution (SUG), or a junk food cafeteria-style diet (CAF) containing a variety of foods
high in fat and/or sugar. During adulthood (PN 65+), metabolic outcomes, HPC-
dependent memory, and gut microbial populations were evaluated. In a subsequent
experiment, the same outcomes were evaluated following a 5-week dietary intervention
(PN 100+) where the CAF and SUG groups were maintained on water and standard
chow. When examined after the adolescent diet treatments, both CAF and SUG groups
demonstrated impaired HPC-dependent memory, increased adiposity, and altered gut
microbial populations relative to the CHOW group. However, impaired peripheral
glucose regulation was only observed in the SUG group. In another experiment, when
examined following dietary intervention, metabolic dysfunction was not observed in
either the CAF or SUG groups, whereas HPC-dependent memory impairments were

18
observed in the CAF group but not the SUG group. The composition of the gut
microbiota was distinct from chow-fed rats in both groups after the healthy dietary
intervention. While the metabolic impairments associated with adolescent cafeteria diet
consumption are not present in adulthood following dietary intervention, the HPC-
dependent memory impairments and the gut microbiome dysbiosis persist.

Introduction
Globalization has brought technological advances in food processing, shelf-life,
marketing, and distribution practices have increased the availability of low-cost
palatable foods that have a high percentage of calories derived from saturated fat and
sugar. The increased prevalence and accessibility of high fat, high sugar foods, herein
referred to as a Western diet (WD), has directly impacted the diet quality of U.S.
citizens, particularly children, as U.S. children on average exceed the recommended
guidelines for consumption of sugars and fats before they reach school age (92).
Furthermore, in U.S. children aged 2 to 19 years, ultra-processed foods rich in lipids and
added sugars contribute to ~65% of total energy intake (93). Indeed, the declining
quality in the WD is likely contributing to the increasing rates of childhood obesity as
consumption of ultra-processed foods in children is positively associated with body fat
(94–96) and increased risk for metabolic syndrome (97, 98).
In addition to adverse metabolic outcomes, WD exposure during early life
periods of development adversely impacts neurocognitive development (8, 9, 99, 100).
For example, habitual added sugar consumption in children is associated with altered
hippocampus (HPC) volume and HPC-cortical connectivity (101), whereas habitual
saturated fatty acid intake is negatively associated with HPC-dependent relational

19
memory (91). Rodent studies also reveal impaired HPC-dependent learning and
memory associated with early life consumption of either a WD or excessive sugar
consumption without elevated fat intake, even in cases where the WD (or sugar)
consumption is not accompanied by metabolic dysfunction and/or obesity (15, 38, 102,
103). The overwhelming majority of these rodent model studies tested memory
performance during adulthood while the animals were still being maintained on the WD
or the high sugar diet. While memory impairments associated with WD consumption in
male rats can be reversed with intervention, such as exercise (104), very little is
understood about whether these early life WD-induced memory impairments can be
remediated with healthy dietary intervention during adulthood, with one study finding
that removing access to a sugar-sweetened beverage solution for 4 months in adulthood
after prolonged access in adolescence with an otherwise standard rodent diet did not
reverse sugar-sweetened beverage-induced HPC-dependent memory impairment in
male rats (38). Additionally, few studies have specifically investigated the effects of
healthy dietary intervention on diet-induced cognitive dysfunction in females.
Emerging evidence suggests that the gut microbiome influences cognitive
function (105–109) and that this relationship may be
dependent on early life nutrition (110). For example, excessive early life sugar
consumption in male rats yields HPC-dependent memory impairments (103), an
outcome that was recently connected functionally to robust changes in the microbiome
relative to chow-fed controls (106). In another study, transplanting the microbiota of
male mice that received an early life high fat diet to chow-fed mice conferred HPC-
dependent learning and memory deficits, suggesting a possible functional connection
between microbiota composition and HPC-dependent learning and memory (86).

20
However, as is the case with WD-associated memory impairments, it is poorly
understood whether microbiome outcomes linked to early life WD consumption can be
reversed with healthy dietary intervention. In humans, after the first 3 years of life an
estimated 60-70% of the microbiota composition remains relatively stable, yet ~30-40%
may be more susceptible to changes induced by diet or other factors (111). The extent to
which microbiome changes induced by dietary factors during early life developmental
periods are long-lasting vs. reversible when the habitual diet changes during adulthood
is unknown.
In the present study, we evaluate, neurocognitive (HPC-dependent memory,
anxiety-like behavior), metabolic (glucose tolerance, body weight, adiposity ratio, caloric
intake), and gut microbiome outcomes in female rats maintained on either a standard
chow diet (CHOW; free access to water and a healthy standard low-fat rat chow) or one
of two different WD models during the entire adolescent period of development: 1) a
junk food cafeteria-style diet (CAF) group, with free choice access to water, a rodent
high-fat diet, an 11% carbohydrate weight-by-volume (w/v) high fructose corn syrup
(HFCS) solution, potato chips, and chocolate peanut butter cups, or 2) a group with
access to water, standard low-fat rat chow, and the 11% w/v HFCS solution (SUG). In
order to explore possible links between gut microbiota and memory outcomes, linear
regression analyses were conducted to determine the relationship between bacterial taxa
abundancies and HPC-dependent memory performance.

Methods and Materials
Subjects and Diets: Adolescent (postnatal day [PN] 26) female Sprague Dawley rats
(n=101, Envigo; 50-70g) were housed individually in a climate-controlled (22–24 °C)

21
environment with a 12:12 reverse light/dark cycle and maintained on standard chow
(Lab Diet 5001; PMI Nutrition International, Brentwood, MO, USA; 29.8 % kcal from
protein, 13.4% kcal from fat, 56.7% kcal from carbohydrate) and water unless otherwise
stated. All experiments were approved by the Animal Care and Use Committee at the
University of Southern California and performed in accordance with the National
Research Council Guide for the Care and Use of Laboratory Animals.

Experiment 1 Design (Junk Food-Style Cafeteria Diet): At PN 26, rats were
randomized to one of two groups (matched for body weight) and received ad libitum
access to either [1] standard chow and water (chow-fed [CHOW] group, n=10), or [2] a
cafeteria (CAF) diet, with free access to potato chips (Ruffles), peanut butter cups
(Reese’s minis), 45% kcal high fat/sucrose chow (Research Diets D12451, New
Brunswick, NJ, USA), a bottle of 11% weight/volume (w/v) high fructose corn syrup
(HFCS)-55 solution (Best Flavors, Orange, CA, USA), and water (CAF group, n=10). The
concentration of sugar (11% w/v) was selected to model the amount of sugar present in
sugar-sweetened beverages commonly consumed by humans, and is also based on our
prior studies in male rats (38, 103). Three food hoppers were used in each cage for
precise measure of individual solid food types (in CAF group) or for consistency across
experimental groups (in CHOW group, all hoppers filled with standard chow). Papers
were placed underneath the cages to enable the collection and recording of food spillage.
Body weights and food intake were measured 3x/week throughout the study.

Experiment 1A: At PN 61 (young adulthood), testing began for the Novel Object
in Context (NOIC) task, which measures hippocampal-dependent episodic/contextual

22
memory (112). Anxiety-like behavior was assessed using a Zero Maze at PN 67. Fecal
samples for analyses of gut microbiota were collected at PN 70 (Timepoint A,
n=10/group). Body composition was measured using nuclear magnetic resonance
(NMR) spectroscopy at PN 74 and an intraperitoneal glucose tolerance test (IPGTT) was
conducted at PN 78. At PN 79, animals in CAF were switched to a standard chow diet
with water access for the remainder of the study as a dietary intervention. Body
composition was reevaluated at PN 115.

Experiment 1B: A second cohort of female rats (n=31, 50-70g) was treated as
described above in order to collect behavioral data following the dietary intervention.
These rats were tested on NOIC after 5 weeks of dietary intervention (chow and water
only) at PN 101 and Zero Maze at PN 108 (Fig. 1B), with the interventional timeframe
being similarly adapted from other studies that evaluated the metabolic and
neurocognitive effects of WD consumption after dietary intervention (113, 114). Fecal
samples for microbiota analyses were collected after the dietary intervention at PN 106
(n=15 CHOW group, n=16 CAF group). Caloric intake and body weight were recorded
3x/week and IPGTT conducted while still on the diet (PN 66).

Experiment 2 Design (Sugar-Sweetened Beverage): At PN 26, rats were
randomized to two groups matched for body weight and were given ad libitum access to
standard chow and either: [1] 11% weight-by-volume (w/v) sugar-sweetened beverage
solution (high fructose corn syrup type 55; Best Flavors, Orange, CA, USA) diluted in
water (SUG; n=16) or [2] a second bottle of water (CHOW; n=16).

23
Experiment 2A: Episodic memory was tested during young adulthood at PN 65
using the hippocampal-dependent NOIC task. At PN 67, rats were then tested for
anxiety-like behavior using the Zero Maze. Fecal samples for microbiota analyses
following sugar-sweetened beverage exposure (n=16/group) were collected at PN 70. At
PN 73, body composition using NMR was assessed. At PN 74, rodents underwent an
IPGTT, and the dietary intervention where sugar solutions were removed was initiated.
Post-dietary intervention body composition was measured at PN 132 and IPGTT was
conducted at PN 134 (n=8/group; Fig. 1C).

Experiment 2B: A second cohort of juvenile (PN 25) female Sprague Dawley rats
(n=18, 50-70g) were treated as described above for post dietary intervention behavioral
testing. These rats were tested on NOIC after dietary intervention after 5 weeks of chow
maintenance at PN 101 and Zero Maze at PN 107 (Fig. 1D). Fecal samples for
microbiome analysis were collected after dietary intervention at PN 105 (n=9/group).
Caloric intakes and body weights were recorded in this group as described above.

24

Figure 1. Timeline of experiments. During the adolescent period of development, rats
were exposed to either a junk food-style cafeteria diet (top) or an otherwise healthy diet
with access to a sugar-sweetened beverage (bottom). Metabolic, cognitive, and gut
microbiome outcomes were evaluated either before (Experiments 1A and 2A) or after
(Experiments 1B and 2B) a healthy dietary intervention (access to standard chow and
water only) during early adulthood. PN: postnatal day; CAF: cafeteria diet; SUG: sugar
diet; NOIC: novel object in context; NMR: nuclear magnetic resonance imaging
spectroscopy; IPGTT: intraperitoneal glucose tolerance test.

Novel Object in Context: The Novel Object in Context (NOIC) task, which measures
contextual episodic memory, was adapted from previous reports (112, 115). Rats are
habituated on consecutive days to both Context 1, a semi-transparent box (15in W ×
24in L × 12in H) with yellow stripes, and Context 2, a grey opaque box (17in W × 17in L
× 16in H) with the order counterbalanced between groups. Following the two
habituation days, on the next day (Day 1 of NOIC), each animal is placed in Context 1
and allowed to explore two different objects (Object A and Object B) placed on diagonal,
equidistant markings with ample space for the rat to circle the objects. The markings on
which each object is placed are counterbalanced within each group. Objects used were
Context 1 Context 2 Context 2
Novel object in context paradigm
Novel object in context:
Memory probe
CON KD
0
20
40
60
80
100
120
Time in open zones (s)
Open zone time
A B C
Zero maze:
Open zone time
D E
Zero maze paradigm
CON KD
0
5
10
15
20
Open zone entries
Entries to open zones
Zero maze:
Open zone entries
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin BDNF levels in dDG/CA1
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin
BDNF levels in dCA3
*
CON KD CON KD CON KD CON KD
dCA3 BDNF dCA1+dDG BDNF G H I dCA1+dDG DCX
CON KD CON KD
F
dCA3 dCA1+
dDG
BDNF BDNF DCX
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-tubulin
DCX levels in dDG
β-tub β-act β-act
CON KD
-0.10
-0.05
0.00
0.05
0.10
Novel object investigation:
shift from baseline
Novel Object in Context
*
Context 1 Context 2 Context 2
Novel object in context paradigm
Novel object in context:
Memory probe
CON KD
0
20
40
60
80
100
120
Time in open zones (s)
Open zone time
A B C
Zero maze:
Open zone time
D E
Zero maze paradigm
CON KD
0
5
10
15
20
Open zone entries
Entries to open zones
Zero maze:
Open zone entries
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin BDNF levels in dDG/CA1
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin
BDNF levels in dCA3
*
CON KD CON KD CON KD CON KD
dCA3 BDNF dCA1+dDG BDNF G H I dCA1+dDG DCX
CON KD CON KD
F
dCA3 dCA1+
dDG
BDNF BDNF DCX
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-tubulin
DCX levels in dDG
β-tub β-act β-act
CON KD
-0.10
-0.05
0.00
0.05
0.10
Novel object investigation:
shift from baseline
Novel Object in Context
*
Context 1 Context 2 Context 2
Novel object in context paradigm
Novel object in context:
Memory probe
CON KD
0
20
40
60
80
100
120
Time in open zones (s)
Open zone time
A B C
Zero maze:
Open zone time
D E
Zero maze paradigm
CON KD
0
5
10
15
20
Open zone entries
Entries to open zones
Zero maze:
Open zone entries
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin BDNF levels in dDG/CA1
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin
BDNF levels in dCA3
*
CON KD CON KD CON KD CON KD
dCA3 BDNF dCA1+dDG BDNF G H I dCA1+dDG DCX
CON KD CON KD
F
dCA3 dCA1+
dDG
BDNF BDNF DCX
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-tubulin
DCX levels in dDG
β-tub β-act β-act
CON KD
-0.10
-0.05
0.00
0.05
0.10
Novel object investigation:
shift from baseline
Novel Object in Context
*
Context 1 Context 2 Context 2
Novel object in context paradigm
Novel object in context:
Memory probe
CON KD
0
20
40
60
80
100
120
Time in open zones (s)
Open zone time
A B C
Zero maze:
Open zone time
D E
Zero maze paradigm
CON KD
0
5
10
15
20
Open zone entries
Entries to open zones
Zero maze:
Open zone entries
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin BDNF levels in dDG/CA1
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-actin
BDNF levels in dCA3
*
CON KD CON KD CON KD CON KD
dCA3 BDNF dCA1+dDG BDNF G H I dCA1+dDG DCX
CON KD CON KD
F
dCA3 dCA1+
dDG
BDNF BDNF DCX
CON KD
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Relative BDNF / β-tubulin
DCX levels in dDG
β-tub β-act β-act
CON KD
-0.10
-0.05
0.00
0.05
0.10
Novel object investigation:
shift from baseline
Novel Object in Context
*
SUG Experiments (2A & 2B)
• Cohort 1
• Cohort 2
CAF Experiments (1A & 1B)
• Cohort 1
• Cohort 2
PN 26 Sugar
sweetened beverage
(SUG) ad libitum
access (2A & 2B) +
CHOW or CHOW only
PN 65
NOIC (2A)
PN 67 Zero
maze (2A)
PN 73
NMR (2A)
PN 74 SUG removal (2B)
and IPGTT (2A)
PN 132 NMR (2B) PN 137
IPGTT
(2B)
Juvenile/Adolescence Adulthood
PN 26 cafeteria diet
(CAF) or standard chow
(CHOW) ad libitum
access (1A & 1B)
PN 61
NOIC (1A)
PN 67 Zero
maze (1A)
PN 74
NMR (1A)
(A)
PN 78
IPGTT
(1A)
PN 115
NMR (1B)
PN 79 CAF diet
removal (1B)
PN 101 NOIC (1B)
PN 66 IPGTT (1A) and CAF diet
replaced with standard chow (1B)
Juvenile/Adolescence Adulthood
PN 108
Zero
Maze (1B)
PN 70
Gut
microbiome
Sequencing
(2A)
PN 105
Gut microbiome
Sequencing (2B)
PN 106
Gut microbiome
sequencing (1B)
PN 70
Gut
microbiome
sequencing
(1A)
PN 107
Zero maze (2B)
PN 65 SUG removal (2B)
PN 101 NOIC (2B)
or
or
+

25
either: a magic eight ball paired with a pyramid-shaped Lego object or a 12 oz. soda can
(Coca-Cola®) paired with an upside-down stemless transparent wine glass. On the
following day (NOIC day 2), rats are placed in Context 2 with Object A and a duplicate of
Object A, one on each marking. On the subsequent day (test day; NOIC day 3), rats are
placed again in Context 2 with Object A and Object B (which is not a novel object per se,
but its presence in Context 2 is novel). Sessions are 5 minutes long and conducted under
diffuse lighting conditions and are video recorded using an overhead camera (Digital
USB 2.0 CMOS Camera with Vari-focal, 2.8-12mm lens; Stöelting) connected to a
computer licensed with Any-Maze software (Stöelting, Wood Dale, IL, USA), which
objectively tracks the time spent investigating each object based on a programmed
template. The discrimination index for the novel object is calculated as follows: (Time
spent exploring Object B/ [Time spent exploring Object A + Time spent exploring Object
B]). The shift from baseline exploration of Object B is then calculated by subtracting the
discrimination indices of NOIC day 1 (baseline) from NOIC day 3 (test day) and then
multiplying by 100 to calculate percent shift from baseline. Intact rats typically
preferentially explore Object B on NOIC day 3 due to its novelty in that particular
context, an effect that is disrupted with hippocampal inactivation (112), or by early life
sugar consumption in male rats (38).

Zero Maze: The Zero Maze test was utilized to measure anxiety-like behavior (116).
The maze consists of an elevated circular platform (63.5 cm height, 116.8 cm external
diameter) with two closed zones and two open zones, all of which are equal in length.
The closed zones are enclosed with 17.5 cm high walls whereas the open zones have only
3 cm high curbs. Animals are placed in the maze for a single 5-min session, and the

26
apparatus is cleaned with 10% ethanol in between animals. Any-Maze software scripts
(Stoelting Co., Wood Dale, IL, USA) are used to record videos and analyze the following
parameters: time spent in the open zones and number of entries into the open zones.

Body Composition using NMR: Rats are food restricted for one hour prior to being
weighed and scanned for body composition as previously described (117) using the
Bruker NMR Minispec LF 90II (Bruker Daltonics, Inc., Billerica, MA, USA), which is
based on Time Domain NMR signals from all protons and has the benefit of being non-
invasive and requiring no anesthesia. Percent body fat is calculated as [fat mass
(g)/body weight (g)] x 100.

Intraperitoneal Glucose Tolerance Test: An intraperitoneal glucose tolerance test
(IPGTT) was administered to estimate peripheral insulin sensitivity. Rats are food
restricted for 22 hours prior to IPGTT. Baseline blood glucose readings are collected
from blood sampled from the tip of the tail and measured using a glucometer (One
touch Ultra2, LifeScan Inc., Milpitas, CA, USA). Each rat receives an intraperitoneal
injection of a 50% dextrose solution (0.5g/kg body weight) and blood glucose readings
are obtained from the tail snip at the 0 (immediately before injection), 30, 60, 90, and
120 min timepoints following injection.

Fecal Sample Collection and 16s Ribosomal RNA (rRNA) Gene Sequencing:
Rats were placed in a sterile cage with no bedding and were mildly restrained until
defecation occurred. Two fecal samples were collected per animal. Samples were
weighed under sterile conditions and then placed into a DNA/RNA free 2 mL cryogenic

27
vial embedded in dry ice. Samples were then stored in a -80°C freezer until processing.
The cages and all materials used to collect samples were cleaned with 70% ethanol in
between rats. Bacterial genomic DNA was extracted from rat fecal samples using
Laragen's validated in-house fecal DNA extraction protocol. Quantification of 16S rRNA
gene loads was performed by qPCR using the SYBR Green master mix (Roche, Basel,
Switzerland), universal 16S rRNA gene primers55 and the QuantStudio 5 thermocycler
(cycling parameters: 2 min at 50 °C, 10 min at 95 °C, 40 cycles of 10 s at 95 °C, and 45 s
at 62 °C). Sequencing libraries were generated using methods previously described
(118). The V4 regions of the 16S rRNA gene were PCR amplified using individually
barcoded universal primers and 3 ng of the extracted genomic DNA. The PCR reaction
was set up in a single reaction, and the PCR product was purified using Laragen's
validated in-house bead-based purification. Two hundred and fifty nanograms of
purified PCR product from each sample was pooled and sequenced by Laragen, Inc.
using the Illumina MiSeq platform and 2 × 150 bp reagent kit for paired-end
sequencing.

Taxonomic Classification of 16S rRNA Gene Sequences: The sequencing reads
were analyzed with QIIME2 and DADA2 following the developers’ instructions for
quality control, de-noising and chimera removal (119, 120). The forward sequencing
reads were truncated to 110 bp and denoised to 2067 amplicon sequence variants
(ASVs) using DADA2. The chimeras were identified and removed using the DADA2
‘consensus’ method. The ASVs were classified using the QIIME2 feature classifier
classify-sklearn based on the SILVA database (release 132). The taxonomic abundance

28
tables were normalized to correct for the different sequencing depth as previously
described (121).

Statistics: Data, presented as means ± SEM, were analyzed and graphed using Prism
software (GraphPad Inc., version 8.4.2), with significance set as p < 0.05. Body weights,
caloric intake, and the IPGTT were analyzed using a Two-way mixed ANOVA with time
as a within-subjects factor and diet as a between-subjects factor. Data were corrected for
multiple comparisons using Sidak’s multiple comparison test. For the IPGTT, area
under the curve (AUC) was measured using Prism software. NOIC and Zero maze
results were analyzed by two-tailed t-test. The statistical analyses and visualization for
microbiome outcomes were primarily performed using R statistical software (Version
3.6.3). The principal coordinates analysis (PCoA) of the rat gut microbiomes were
calculated based on the Bray-Curtis dissimilarity at the genus level and visualized with
functions in the R package ‘vegan’. The associations between gut microbiome and
treatment were analyzed with the PERMANOVA test with 999 permutations using
function ‘adonis’ in R package ‘vegan’. Shannon index was used for analyzing the alpha-
diversity of gut microbiomes. The associations of individual taxa and treatment were
analyzed with Wilcoxon test. The P-values were adjusted with the Benjamini-Hochberg
method for multiple hypotheses testing. The correlations between each taxa and NOIC
performance, defined by the rat’s % shift from baseline investigation of the object novel
to the context, calculated from time (s) spent investigating the objects in each context
(see NOIC methods for more details), were analyzed separately for each experiment
with Spearman’s correlations and the P-values were adjusted with the Benjamini-
Hochberg method.

29
Results
The increased adiposity associated with early life CAF diet consumption is
not observed after healthy dietary intervention. In Experiment 1A, free access to
the CAF diet throughout the juvenile and adolescence period did not result in significant
differences in body weight (F(1, 18) = 0.2917; P = 0.5958) or total caloric intake (F(1, 18) =
2.065; P = 0.1679) (Fig. 2A-B). A significant time x diet interaction, however, was
observed for total calories consumed (F(33, 589) = 4.229; P < 0.0001). Surprisingly, this
interaction was driven by reduced caloric consumption in the CAF group vs. chow-fed
group following a healthy dietary intervention, as confirmed by a significant group main
effect when analyzed separately over the post-intervention period (F(1, 18) = 12.68; P =
0.0022) and the lack of significant group differences when analyzed separately over the
CAF diet maintenance period before the intervention (F(1, 18) = 0.1916; P = 0.6668).
However, in Experiment 1A NMR-based body composition analyses revealed that CAF
rats had elevated fat mass relative to chow-fed rats at PN 74 after consuming a CAF
during the juvenile and adolescence period (P = 0.0059). Results from an IPGTT
conducted before the CAF group was switched to chow maintenance (Experiment 1A)
revealed no significant group differences in area under the curve (AUC) (P = 0.3711) (Fig
2D), suggesting that glucose tolerance was not affected by CAF consumption. IPGTT
results were comparable in the 2
nd
cohort. Importantly, the elevated adiposity in CAF vs.
chow-fed groups was not present at PN 115 after 41 days of standard chow maintenance
(Experiment 1B; Fig. 2E).

Rats in the CAF group derived approximately 45.6% of their total calories from the high-
fat-diet chow, 21.1% from potato chips, 26.0% from peanut butter cups, and 6.6% from

30
the sugar beverage (Fig. 2F). The percentage of total kcals consumed from each
macronutrient, calculated from the nutritional information and kcals consumed from
each dietary component, was 12% from protein, 46% from fat, and 42% from
carbohydrates.

Figure 2. Energy balance and metabolic outcomes following adolescent cafeteria diet
consumption. There were no overall significant group differences in body weight (A),
total caloric intake (B), or glucose tolerance in the IPGTT test (C and D). Rats in the CAF
group consumed significantly fewer calories following the healthy dietary intervention
(B). CAF-exposed rats had significantly greater adiposity than CHOW rats (E). Percent
total calories from each food item in the CAF diet as well as % macronutrient
composition of total calories consumed in Cohort 1 are depicted in (F). Data are
means ± SEM; n = 10/group, **P < 0.01. CHOW: chow-fed; CAF: cafeteria diet; kcal:
kilocalories; IPGTT: intraperitoneal glucose tolerance test.

The impaired peripheral glucose regulation induced by excessive early life
sugar consumption is not observed after healthy dietary intervention. In
Experiment 2, body weights and total caloric intake were comparable in the SUG and
chow-fed groups throughout the experiment from PN 26-137 despite ad libitum access
to a sugar beverage from PN 26-74 in the SUG group (Fig. 3A and 3B). However, there
was a significant interaction (time x diet) for calories consumed from standard chow
40 60 80 100 120
0
30
60
90
120
150
180
210
240
270
300
Postnatal day
CTL
CAF
grams
Body weights
IPGTT
40 60 80 100 120
0
10
20
30
40
50
60
70
80
90
100
Postnatal day
CTL
CAF
kcal/24 hr
kcal consumed
switched to healthy diet
0 30 60 90 120
0
50
100
150
200
250
min
Blood glucose
(mg/dL)
IPGTT
PN 78
CTL
CAF
CTL CAF
0
5000
10000
15000
20000
25000
mg/dL
IPGTT Area under curve
PN 78
PN 74 PN 115
0
5
10
15
% body fat
Body Composition
✱✱
CTL
CAF
Cafeteria Diet
% total kcals consumed
45.6% from
High Fat Diet
Chow
21.1% from Potato Chips
26.0%
from
Peanut
Butter
Cups
6.6% from Sugar Beverage
A) B) C) D)
E) F)
Body weight kcal consumed
Body composition
Cafeteria Diet
% total macronutrients consumed
12% Protein
46% Fat
42% Carbohydrate
CHOW
CHOW
CAF switched to healthy diet
CHOW
CHOW
CHOW

31
(F(39, 850) = 17.58; P < 0.0001) with a main effect of time (F(7.808, 170.2) = 41.55; P < 0.0001)
and diet (F(1, 30) = 94.52; P < 0.0001). Post hoc analyses showed that from PN 28-73,
SUG rats consumed fewer calories from chow (Fig. 3C), suggesting that the female SUG
rats were reducing their chow intake to compensate for the kcals consumed from the
sugar solution (Fig. 3D). Rats in the SUG group derived approximately 36.0% of their
total calories from the sugar beverage (data not shown). Caloric intake and body weights
within and between groups were comparable in the 2
nd
cohort, who also derived around
33.6% of their total calories from the sugar beverage (data not shown). Similarly, in
Experiment 2A adiposity measured by body composition using NMR was higher in the
SUG group before removal of the sugar at PN 73 (P = 0.0021), but not at PN 132 after a
dietary intervention (Experiment 2B; Fig. 3H).

In Experiment 2A, analyses of IPGTT results at PN 74 for the SUG and chow-fed rats
revealed a significant interaction (time x diet) for blood glucose levels (F(4, 120) = 3.196, P
= 0.0156) with a main effect of both time (F(1.681, 50.42) = 231.8, P < 0.0001) and diet (F(1,
30) = 7.642, P = 0.0097). Post hoc analyses revealed that the SUG group had higher
glucose levels at the 120-minute timepoint after glucose administration (Fig. 3E). The
IPGTT AUC analyses revealed that the SUG rats had significantly higher glucose levels
than CHOW rats (P = 0.0106), further supporting that the SUG animals had impaired
glucose tolerance at PN 74 (Fig. 3G). However, when tested at PN 137 after having
removed the sugar for ~1.5 months as a healthy dietary intervention (Experiment 2B),
SUG rats did not exhibit significantly impaired glucose tolerance relative to chow-fed
rats (Fig. 3F).

32

Figure 3. Energy balance and metabolic outcomes following adolescent sugar diet
consumption. There were no overall significant group differences in body weight (A) or
total caloric intake (B), although rats in the SUG group consumed less calories from
chow (C) when consuming the sugar solution (D). The SUG group had significantly
higher blood glucose levels (E and G) and adiposity (H) relative to CHOW rats, which
normalized after healthy dietary intervention (F, G and H). Data are means ± SEM;
n=16/group before sugar removal (PN 74), n=8/group after sugar removal (PN 75+)
*P < 0.05, **P < 0.01. CHOW: chow-fed; SUG: sugar; kcal: kilocalories; IPGTT:
intraperitoneal glucose tolerance test

Hippocampal-dependent memory impairments associated with early life
junk food diet consumption are observed despite healthy dietary
intervention. In Experiment 1A, results from the NOIC task revealed that CAF rats
40 60 80 100 120
0
10
20
30
40
50
60
70
80
Postnatal day
CTL
SUG
kcals/24 hr
kcals from chow
Sugar removed
40 60 80 100 120
0
30
60
90
120
150
180
210
240
270
300
Postnatal day
CTL SUG
grams
Body Weight
Sugar removed
40 60 80 100 120
0
10
20
30
40
50
60
70
80
Postnatal day
CTL
SUG
kcals/24 hr
Total kcals consumed
Sugar removed
40 60 80 100 120 140
0
5
10
15
20
25
30
35
Postnatal day
kcals/24 hr
kcals from sugar solution
SUG
0 30 60 90 120
0
50
100
150
200
250
min
Blood glucose
(mg/dl)
CTL
SUG
*
IPGTT PN 74
PN 74 PN 137
0
5000
10000
15000
20000
mg/dL
IPGTT Area under curve
CTL
SUG
✱
PN 73 PN 132
0
5
10
15
20
Body composition
% body fat
CTL
SUG
✱✱
0 30 60 90 120
0
50
100
150
200
250
min
CTL
SUG
IPGTT PN 137
Blood glucose
(mg/dl)
A) B)
C)
D)
E) F)
G) H)
Total kcal consumed Body weight
kcal from chow kcal from sugar solution
CHOW
CHOW
CHOW
CHOW
CHOW
CHOW CHOW

33
had deficits in hippocampal-dependent episodic contextual memory relative to chow-fed
rats, which was supported by a lower shift from baseline discrimination index for the
novel object (P = 0.008; Fig. 4A). After switching the CAF animals to standard chow as a
healthy dietary intervention (Experiment 1B), rats that had been exposed to the CAF
diet during early life displayed a significantly reduced shift from baseline discrimination
of the novel object (P = 0.02; Fig. 4B). This suggests that the memory impairment
associated with ~1.5 months of CAF diet exposure during adolescence may persist even
after 5 weeks of healthy dietary intervention. There were no differences in anxiety-like
behavior in the Zero Maze test before switching to a low-fat diet at PN 67 (Experiment
1A) or after the dietary intervention at PN 108 (Experiment 1B; Fig. 4C-D).

Figure 4. Hippocampal-dependent memory following adolescent cafeteria diet
consumption. CAF-exposed rats were impaired in the NOIC memory task (calculated as
shift from baseline discrimination index on test day) when tested either before (A) or
after (B) a healthy dietary intervention. There were no significant group differences in
CTL CAF
-40
-30
-20
-10
0
10
20
30
✱✱
% Shift from Baseline
NOIC
PN 61
CTL CAF
-40
-30
-20
-10
0
10
20
30
✱
% Shift from Baseline
NOIC
PN 101
CTL CAF
0
50
100
150
200
Time spent
in open (s)
Zero maze
PN 67
CTL CAF
0
50
100
150
200
Time spent
in open (s)
Zero maze
PN 108
A) B)
C) D)
CHOW CHOW
CHOW CHOW

34
anxiety-like behavior in the Zero Maze when tested either before (C) or after (D) a
dietary intervention. Data are means ± SEM; A/C: n = 10/group, B/D: n = 15/CHOW
group, n = 16/CAF group, *P < 0.05, **P < 0.01. CHOW: chow-fed; CAF: cafeteria diet;
NOIC = novel object in context

In Experiment 2A, SUG rats were impaired in the hippocampal-dependent NOIC task
relative to chow-fed rats when tested at PN 65, supported by a significantly lower shift
from baseline discrimination index for the novel object relative to chow-fed rats (P =
0.0309; Fig. 5A). After removing the SUG beverages as a dietary intervention in
Experiment 2B, rats that had been previously exposed to the SUG diet during
adolescence had a similar shift from baseline discrimination of the novel object as the
CHOW group (Fig. 5B). This suggests that the memory impairments associated with
early life SUG consumption in female rats may benefit from healthy dietary
intervention. There were no differences in anxiety-like behavior in the Zero Maze test
either when tested at PN 67 (Experiment 2A) or PN 107 following a dietary intervention
(Experiment 2B; Fig. 5C).

35

Figure 5. Hippocampal-dependent memory following adolescent sugar diet
consumption. SUG-exposed rats were impaired in the NOIC memory task (calculated as
shift from baseline discrimination index on test day) when tested before (A), but not
after (B) a healthy dietary intervention. There were no significant group differences in
anxiety-like behavior in the Zero Maze when tested either before (C) or after (D) the
dietary intervention. Data are means ± SEM; A/C: n=16/group, B/D: n=9/group
*P < 0.05. CHOW: chow-fed; SUG: sugar; NOIC: novel object in context

Gut microbiome changes associated with early life Western diet
consumption (junk food diet or excessive sugar consumption) are observed
despite healthy dietary intervention. We characterized the rat gut microbiome to
estimate the impact of early life Western diet consumption. The CAF and CHOW groups’
gut microbiomes are separated in the PCoA plots for Experiment 1A (PN 70, 44 days
after the start of the WD diet) and for Experiment 1B (27 days after healthy dietary
intervention), but the separation for Experiment 1B is more distinct (Fig. 6A and B). The
CTL SUG
0
20
40
60
80
% Time in Open
Zero Maze
PN 107
CTL SUG
0
20
40
60
80
% Time in Open
Zero Maze
PN 67
CTL SUG
-40
-20
0
20
40
% Shift from
Baseline
✱
NOIC
PN 65
CTL SUG
-40
-20
0
20
40
% Shift from
Baseline
NOIC
PN 101
A) B)
C)
D)
CHOW SUG
CHOW SUG
CHOW SUG CHOW SUG

36
alpha diversity of CAF rats for Experiment 1B was significantly reduced compared to
other groups (Fig. 6C).
In order to generate a more detailed picture of changes to the microbiome, we
next analyzed the differential abundance of individual taxa between CAF and CHOW
rats for both experiments. Consistent with the view given by the PCoA plots, there are
more taxa with significant group differences for Experiment 1B compared to Experiment
1A (148 vs 22 taxa at phylum to species level, Wilcoxon test, FDR<0.1; Fig. S3). The
differential taxa for Experiment 1 are broadly distributed across various taxonomic
groups, as depicted in the cladograms (Fig. 6D and E).
Similar to Experiment 1, Experiment 2 PCoA plots also showed clear separation
of the SUG and CHOW rats’ gut microbiomes in both Experiments 2A (27 days after
healthy dietary intervention) and 2B (27 days after healthy dietary intervention), with a
stronger separation observed in Experiment 2B (Fig. 7A and B). Unlike the CAF data,
however, the alpha diversity of SUG and CHOW rats was not significantly different for
either Experiment 2A or 2B (Fig. 7C). Statistical tests of individual taxa at phylum to
species level revealed 69 and 60 significant taxa between SUG and CHOW rats for
Experiments 2A and 2B, respectively (Wilcoxon test, FDR<0.1) (Fig. S5). The
differential taxa for Experiment 2 are broadly distributed across various taxonomic
groups, as depicted in the cladograms (Fig. 7D and E).

37

Figure 6. Gut microbiome following adolescent cafeteria diet consumption. (A and B)
PCoA plots of CAF-exposed rats gut microbiomes when analyzed either in Experiment
1A (no healthy dietary intervention) or in Experiment 1B (after healthy dietary
intervention). Ellipses indicate 95% confidence limits. R
2
and P are from PERMANOVA
tests. (C) Shannon index of CAF-exposed rats gut microbiomes either before or after
healthy dietary intervention. The differences were tested with Wilcoxon tests. (D and E)
Significant differential taxa between treatment and chow-fed rats at phylum to species
level (Wilcoxon test, FDR<0.1) are highlighted on the phylogenetic trees of all taxa
identified in this study. An FDR cutoff of 0.1 was used here for visualization. (F) The
correlation plots of Deferribacteraceae in Experiment 1A, Proteobacteria, Actinobacteria
(phylum), Cyanobacteria and Ruminiclostridium in Experiment 1B with NOIC
performance (% shift from baseline discrimination index on test day) across CAF and
CHOW samples. Spearman’s correlation was used for the analysis and P-values were
corrected for multiple hypotheses testing with the Benjamini-Hochberg method.
A) B)
E) Experiment 1B
D) Experiment 1A
G)
2.0
2.4
2.8
3.2
CTL 1A CAF 1A CTL 1B CAF 1B
Treatment_Experiment
Shannon Index
Treatment_Experiment
CTL 1A
CAF 1A
CTL 1B
CAF 1B
Experiment 1A P = 0.01893
Experiment 1B P = 0.00186
2.50
2.75
3.00
3.25
SUG 2A CTL 2A CTL 2B SUG 2B
Treatment_Experiment
Shannon Index
Treatment_Experiment
CTL 2A
SUG 2A
CTL 2B
SUG 2B
Experiment 1A P = 0.77012
Experiment 1B P = 0.48943
C)
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.0794 P= 0.03
PCoA1 (26.33%)
PCoA2 (16.64%)
CTL 1A
CTL 1B
CTL 1A
CTL 1B
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5 2.0
R2 = 0.06844 P= 0.024
PCoA1 (21.45%)
PCoA2 (18.93%)
CTL 1A
CAF 1A
CTL 1A
CAF 1A
−1.5 −1.0 −0.5 0.0 0.5 1.0
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.54708 P= 0.001
PCoA1 (59.78%)
PCoA2 (9.37%)
CTL 1B
CAF 1B
CTL 1B
CAF 1B
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.466 P= 0.001
PCoA1 (50.24%)
PCoA2 (11.91%)
CAF 1A CAF 1B
CAF 1A
CAF 1B
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.0794 P= 0.03
PCoA1 (26.33%)
PCoA2 (16.64%)
CTL 1A
CTL 1B
CTL 1A
CTL 1B
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5 2.0
R2 = 0.06844 P= 0.024
PCoA1 (21.45%)
PCoA2 (18.93%)
CTL 1A
CAF 1A
CTL 1A
CAF 1A
−1.5 −1.0 −0.5 0.0 0.5 1.0
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.54708 P= 0.001
PCoA1 (59.78%)
PCoA2 (9.37%)
CTL 1B
CAF 1B
CTL 1B
CAF 1B
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
−1.5 −1.0 −0.5 0.0 0.5 1.0
R2 = 0.466 P= 0.001
PCoA1 (50.24%)
PCoA2 (11.91%)
CAF 1A CAF 1B
CAF 1A
CAF 1B
Deferribacteraceae
rho = 0.513
FDR = 0.085
−10
0
10
20
30
0.0 0.5 1.0 1.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1A CTL 1A
Actinobacteria
rho = 0.513
FDR = 0.085
−20
0
20
2.0 2.5 3.0 3.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Proteobacteria
rho = 0.513
FDR = 0.085
−20
0
20
2.0 2.4 2.8
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Cyanobacteria
rho = 0.513
FDR = 0.085
−20
0
20
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Deferribacteraceae
rho = 0.513
FDR = 0.085
−10
0
10
20
30
0.0 0.5 1.0 1.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1A CTL 1A
Actinobacteria
rho = 0.513
FDR = 0.085
−20
0
20
2.0 2.5 3.0 3.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Proteobacteria
rho = 0.513
FDR = 0.085
−20
0
20
2.0 2.4 2.8
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Cyanobacteria
rho = 0.513
FDR = 0.085
−20
0
20
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
F)
Deferribacteraceae
rho = 0.513
FDR = 0.085
−10
0
10
20
30
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1A CTL 1A
Actinobacteria
rho = −0.544
FDR = 0.092
−20
0
20
1.5 2.0 2.5 3.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Proteobacteria
rho = −0.484
FDR = 0.092
−20
0
20
2.25 2.50 2.75 3.00 3.25 3.50
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Cyanobacteria
rho = −0.474
FDR = 0.092
−20
0
20
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Deferribacteraceae
rho = 0.513
FDR = 0.085
−10
0
10
20
30
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1A CTL 1A
Actinobacteria
rho = −0.544
FDR = 0.092
−20
0
20
1.5 2.0 2.5 3.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Proteobacteria
rho = −0.484
FDR = 0.092
−20
0
20
2.25 2.50 2.75 3.00 3.25 3.50
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Cyanobacteria
rho = −0.474
FDR = 0.092
−20
0
20
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Deferribacteraceae
rho = 0.513
FDR = 0.085
−10
0
10
20
30
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1A CTL 1A
Actinobacteria
rho = −0.544
FDR = 0.092
−20
0
20
1.5 2.0 2.5 3.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Proteobacteria
rho = −0.484
FDR = 0.092
−20
0
20
2.25 2.50 2.75 3.00 3.25 3.50
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Cyanobacteria
rho = −0.474
FDR = 0.092
−20
0
20
0.0 0.5 1.0 1.5 2.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Ruminiclostridium.6
rho = 0.674
FDR = 0.082
−20
0
20
0 1 2 3
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Alistipes obesi
rho = −0.6
FDR = 0.06
0
10
20
30
40
0.0 0.5 1.0 1.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CTL 2B SUG 2B
CHOW 1A
CHOW 1B

38
CHOW: chow-fed; CAF: cafeteria diet; PCoA: Principal Coordinate Analysis; FDR: false
discovery rate; rho: Spearman’s ρ

Microbiome changes are associated with changes in NOIC. We next analyzed
the correlations between individual taxa and NOIC to explore the potential microbiome
signature associated with memory performance. In the CAF diet study (Experiment 1),
we found several taxa significantly correlated with NOIC (Spearman’s correlation,
FDR<0.1). This included a significant positive correlation with memory performance for
Deferribacteraceae (family) for Experiment 1A (Fig. 6F), and significant negative
correlations for Actinobacteria (phylum), Proteobacteria (phylum), and Cyanobacteria
(phylum), and a significant positive correlation for Ruminiclostridium 6 (genus) for
Experiment 1B (Fig. 6G). In the SUG experiment (Experiment 2), only Alistipes obesi
(species) was significantly (negatively) associated with NOIC memory performance in
Experiment 2A (Fig. 7F).

39

Figure 7. Gut microbiome following adolescent sugar diet consumption. (A and B)
PCoA plots of SUG-exposed rats gut microbiomes when analyzed either before (A) or
after (B) a healthy dietary intervention. Ellipses indicate 95% confidence limits. R
2
and
P are from PERMANOVA tests. (C) Shannon index of SUG-exposed rats gut
microbiomes when analyzed either before or after a healthy dietary intervention. The
differences were tested with Wilcoxon tests. (D and E) Significant differential taxa
between treatment and CHOW at phylum to species level (Wilcoxon test, FDR<0.1) are
highlighted on the phylogenetic trees of all taxa identified in this study. An FDR cutoff of
0.1 was used here for visualization. (F) The correlations plots of Alistipes obesi with
NOIC performance (% shift from baseline discrimination index on test day) in
Experiment 2B. Spearman’s correlation was used for the analysis and P-values were
D) Experiment 2A E) Experiment 2B
F)
A) B)
2.0
2.4
2.8
3.2
CTL 1A CAF 1A CTL 1B CAF 1B
Treatment_Experiment
Shannon Index
Treatment_Experiment
CTL 1A
CAF 1A
CTL 1B
CAF 1B
Experiment 1A P = 0.01893
Experiment 1B P = 0.00186
2.50
2.75
3.00
3.25
SUG 2A CTL 2A CTL 2B SUG 2B
Treatment_Experiment
Shannon Index
Treatment_Experiment
CTL 2A
SUG 2A
CTL 2B
SUG 2B
Experiment 1A P = 0.77012
Experiment 1B P = 0.48943
C)
−1 0 1 2
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
Treatment R2 = 0.12211 P= 0.001
Timepoint R2 = 0.13998 P= 0.001
Interaction R2 = 0.15835 P= 0.001
PCoA1 (37.59%)
PCoA2 (10.92%)
CAF 1A
CAF 1B
CTL 1A
CTL 1B
CAF 1A
CAF 1B
CTL 1A
CTL 1B
−2 −1 0 1
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.12679 P= 0.001
PCoA1 (27.87%)
PCoA2 (15.78%)
CTL 2A
CTL 2B
CTL 2A
CTL 2B
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.10386 P= 0.003
PCoA1 (27.16%)
PCoA2 (14.58%)
CTL 2A
SUG 2A
CTL 2A
SUG 2A
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.24669 P= 0.001
PCoA1 (33.85%)
PCoA2 (22.21%)
CTL 2B
SUG 2B
CTL 2B
SUG 2B
−1 0 1 2
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
Treatment R2 = 0.12211 P= 0.001
Timepoint R2 = 0.13998 P= 0.001
Interaction R2 = 0.15835 P= 0.001
PCoA1 (37.59%)
PCoA2 (10.92%)
CAF 1A
CAF 1B
CTL 1A
CTL 1B
CAF 1A
CAF 1B
CTL 1A
CTL 1B
−2 −1 0 1
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.12679 P= 0.001
PCoA1 (27.87%)
PCoA2 (15.78%)
CTL 2A
CTL 2B
CTL 2A
CTL 2B
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.10386 P= 0.003
PCoA1 (27.16%)
PCoA2 (14.58%)
CTL 2A
SUG 2A
CTL 2A
SUG 2A
−2 −1 0 1
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
R2 = 0.24669 P= 0.001
PCoA1 (33.85%)
PCoA2 (22.21%)
CTL 2B
SUG 2B
CTL 2B
SUG 2B
Ruminiclostridium.6
rho = 0.513
FDR = 0.085
−20
0
20
1.0 1.5 2.0 2.5 3.0
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Alistipes obesi
rho = 0.513
FDR = 0.085
0
10
20
30
40
0.0 0.5 1.0 1.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CTL 2B SUG 2B
Ruminiclostridium.6
rho = 0.674
FDR = 0.082
−20
0
20
0 1 2 3
log10 (normalized Abundance)
Novel Object in Context Score
Group CAF 1B CTL 1B
Alistipes obesi
rho = −0.6
FDR = 0.06
0
10
20
30
40
0.0 0.5 1.0 1.5
log10 (normalized Abundance)
Novel Object in Context Score
Group CTL 2B SUG 2B
CHOW 2B SUG 2B

40
corrected for multiple hypotheses testing with the Benjamini-Hochberg method.
CHOW: chow-fed; SUG: sugar; PCoA: Principal Coordinate Analysis; FDR: false
discovery rate; rho: Spearman’s ρ

Discussion:
Our results reveal that female rats who were maintained on a CAF diet
throughout adolescence demonstrate impaired HPC-dependent episodic memory,
altered abundances of gut microbiome bacterial taxa, and increased adiposity relative to
chow-fed rats maintained on a healthy standard rodent diet. The CAF diet had no effect,
however, on total caloric intake, body weight, or glucose tolerance relative to standard
chow-fed rats. Similar to previous results in male rats (38, 103), our results further
reveal that adolescent access to healthy chow, water, and an 11% carbohydrate w/v sugar
solution (SUG) in female rats impaired HPC-dependent episodic memory, altered the
gut microbiome, increased adiposity, and impaired glucose tolerance without affecting
body weight or total caloric intake relative to chow-fed rats. Additional results revealed
that some, but not all of these early life WD-associated outcomes may benefit from a 5-
week healthy diet intervention in which all animals were maintained on a standard chow
rodent diet beginning at early adulthood. CAF rats that received a dietary intervention
also had episodic memory deficits and significant separation in gut microbial taxa,
whereas the increased adiposity relative to chow-fed rats normalized. For SUG rats that
received a dietary intervention, impaired metabolic and cognitive outcomes were not
observed. However, similar to the CAF rats, the gut microbiome from SUG rats was
distinct from chow-fed rats despite a 5-week dietary intervention. Together, these
results show that some, but not all, negative outcomes associated with early life Western
diet (WD) consumption in female rats may be remediated by switching to a healthy diet.

41
Consistent with the present results, previous studies conducted in male rodents
revealed that dietary intervention ameliorates metabolic deficits associated with WD
consumption (high fat or high fat, high sugar diets) (38, 122–126). However, some of the
present results from female rats differ from studies conducted in male rodents. For
instance, unlike the female CAF rats in the present study, switching to a low fat diet
following adolescent high fat diet exposure in male rats resulted in marginal
improvements in HPC-dependent memory (31) and cognitive flexibility (127). In
another study, male rats that received an adolescent CAF diet were not impaired in a
spatial memory task despite showing symptoms of metabolic syndrome, which were
reversible by switching to standard chow (113). Moreover, studies using a diet
manipulation similar to our SUG model revealed that a high sugar diet during
adolescence led to impairments in both HPC-dependent episodic (38) and spatial
memory (128) in male rats that were not reversible by dietary intervention (i.e.,
removing the sugar access). Compared to these findings in males, the present findings
suggest that female rats may benefit more from dietary intervention for neurocognitive
impairments associated with early life excessive sugar consumption, despite consuming
more of their total calories from the sugar beverage than males (here, the females
consumed around ~33-36% of their daily energy intake from the sugar beverage
whereas Noble et al. found that males on the same diet consumed on average ~24% of
their daily energy intake from the sugar beverage) (38). There is also evidence to suggest
that even metabolic and place-recognition memory impairments due to excessive sugar
consumption in adult female rats can be reversed with dietary intervention (switching to
saccharin or water) (129). However, female rats may be more susceptible to sustained
detrimental effects on memory when the diet is high in both sugar and fat (e.g., the CAF

42
diet). Given that estradiol levels can affect food intake, body weight, and learning and
memory function in female rodents (130, 131), and estrogen and sex hormones have
been shown to influence gut bacteria as well (132–134), one limitation of the present
study is that we did not evaluate the estrous stage at the time of behavioral testing or
tissue harvest. Future studies that evaluate both sexes directly and carefully track
estrous in females are needed to disentangle the role of sex and sex hormones on the
enduring neurocognitive outcomes associated with early life WD consumption.
Given that increased anxiety-like behavior may develop following early life WD
exposure in rodents (100), we tested the rats in the Zero Maze test but found no effects
of CAF exposure on anxiety-like behavior either before or after the dietary intervention.
Similar to our CAF rats, an anxiety-like phenotype was not seen in the SUG cohorts,
which is consistent with our previous findings in male rats using the Zero Maze test
(103). However, other studies have reported an anxiety-like phenotype in the open field
test in male rodents after switching to standard chow for 1 week following an adolescent
CAF diet (135) and after adolescent SUG exposure even after removing the sugar access
for 25 days in young adulthood (114). Thus, it is possible that the detection of anxiety-
like behavior after WD exposure may be more or less sensitive depending on the type of
behavioral test used.
Our data show that gut microbial richness, as measured with the Shannon Index,
is significantly reduced following early life CAF, but not SUG, diet, and that this effect
was actually greater in animals that underwent the healthy dietary intervention
compared to those that did not. This outcome is consistent with other studies in which
microbial richness was reduced after the removal of high-fat, high-sugar diets (136, 137)
or reduced adiposity following lifestyle modifications (eating breakfast, avoiding sugar-

43
sweetened beverages, decreasing processed foods rich in animal fat or lengthening meal
duration, and implementing more exercise) (138). Composition of the gut microbiota
was significantly distinct from chow-fed rats immediately after either the adolescent
CAF or SUG exposure period analyzed with PERMANOVA tests. Surprisingly, microbial
separation between CAF and chow-fed rats and between SUG and chow-fed rats was
greater after a 5-week healthy dietary intervention, suggesting that diet-induced shifts in
the gut microbiome that occur during early life periods of development may be long-
lasting independent of dietary patterns during adulthood. One possible explanation for
the increased microbial divergence from chow-fed rats in the experimental groups that
underwent dietary intervention is that both of these groups (CAF and SUG) were
switched to a higher fiber diet (all kcal from standard chow) for the intervention.
Further, cellulose contained within the high fat chow is the main dietary fiber of the CAF
diet, whereas the standard chow diet contains a diverse set of dietary fibers from the
ground corn, beet pulp, ground oats, alfalfa meal, and wheat middlings ingredients of
this diet (e.g., arabinoxylan [corn, wheat], beta glucan [oat], cellulose [corn, alfalfa,
wheat, beet], hemicellulose [corn, alfalfa, wheat, beet], pectin [beet]) (139–142). These
different dietary fibers have been shown to serve as nutrient sources for a variety of gut
microbial taxa, including the genus Bifidobacterium (cellulose, pectin, oat,
arabinoxylan) (143–147), the genus Parasutterella (pectin) (147), the phylum
Actinobacteria (pectin) (147), and the genera Bacteroides-Prevotella (oat, arabinoxylan)
(143), among others. The present study was not designed to pinpoint the effects of
specific dietary fibers (or lack thereof) on cognitive function or the microbiome, but this
is an important area of future work. Another factor to consider with regards to observed
group differences in gut microbial richness is that our procedures for handling animals

44
and food were not conducted in a completely sterile environment, and thus microbial
cross-contamination between experimental groups was not completely prevented. Thus,
it is likely that the dietary treatments may have led to even greater differences in the
Shannon Index compared to chow-fed rats had all procedures been conducted under
pure sterility.
In some cases, the same bacterial taxa were altered by both CAF and SUG
treatment, but in opposite directions, and differential by experimental design. For
example, for Experiments 1A and 2A (analyses conducted before dietary intervention),
the CAF and SUG group shared changes in the class Gammaproteobacteria, the order
Betaproteobacteriales, the family Tannerellaceae, and the genera Parabacteroides and
ASF356, yet all of these followed the same trend and differed by dietary treatment: the
abundances of these taxa were lower in CAF rats vs. chow-fed rats and higher in SUG
rats vs. chow-fed rats. For Experiments 1B and 2B (analyses conducted after dietary
intervention), abundances in the class Gammaproteobacteria, which is more abundant
in obese mice (148) and increased after consumption of high-fructose syrup in
honeybees (149), and the order Betaproteobacteriales were still significantly different in
the CAF, but not SUG, group relative to their respective CHOW groups. However, the
direction changed such that the values of these taxa were lower than chow-fed rats in
the CAF group when analyzed without a dietary intervention, yet higher than chow-fed
rats when analyzed after a dietary intervention. For Experiments 1B and 2B, the class
Mollicutes and the order Mollicutes RF39 were the only taxa that were significantly
different in both CAF and SUG treated groups, lower in the CAF group, but higher in the
SUG group compared to respective chow-fed rats. Overall, it is clear that CAF and SUG
diets both significantly altered the gut microbiomes, but the changes in microbiota were

45
often divergent, which may be related to differences in dietary fiber composition or
content in the diets. These dietary treatments had significant and distinct influences on
the microbiomes that can persist even after the healthy dietary intervention.
There is evidence to suggest that gut dysbiosis occurs before metabolic and
spatial memory impairment in rodents (150) and that certain bacteria can improve
memory performance (151, 152) or have detrimental effects on HPC neurons (153) and
cognitive ability (Magnusson et al., 2015). Further, we recently showed that elevated
levels of Parabacteroides in male rats given the SUG dietary treatment during
adolescence were functionally connected to HPC-dependent memory impairments
(106). This conclusion was based on findings that levels of Parabacteroides were
negatively associated with memory performance, and targeted enrichment of
Parabacteroides in rats that had never consumed sugar replicated the memory deficits.
Similar to these findings, here we show in female rats that Parabacteroides levels were
increased in the SUG group relative to chow-fed rats, and interestingly, that this
elevation was not observed following the dietary intervention. Given that the HPC-
dependent memory impairments were also not observed following dietary intervention
in this group, this suggests that levels of Parabacteroides may be functionally connected
to SUG-associated memory impairments in females as well. However, correlation
analyses revealed that Parabacteroides abundance was not significantly correlated with
memory performance in females after adjusting for multiple hypotheses testing,
suggesting the associations between Parabacteroides and SUG-associated memory
impairments may vary by the sex of rats. It is also possible that this association in
female rats may require a larger sample size than male rats for adequate statistical
power.

46
Our data identify multiple taxa that were significantly correlated with NOIC
performance. Diet-induced changes in the abundance of some of these microbiome
populations may be related to the impaired memory performance in CAF-fed animals
that were tested after the dietary intervention. For example, in Experiment 1B the phyla
Actinobacteria and Proteobacteria were both negatively correlated with NOIC
performance and were significantly higher in abundance in CAF rats that received a
dietary intervention relative to chow-fed rats. On the other hand, the genus
Ruminiclostridium 6 was positively correlated with NOIC performance and was
significantly lower in abundance in CAF rats that received dietary intervention relative
to chow-fed rats. Although little is known about the association between
Ruminiclostridium 6 and memory performance, Actinobacteria has been associated
with memory performance in dogs, albeit in an opposing direction compared with the
present study as reduced abundance in that study was associated with better
performance in a memory task (154). Consistent with the present results, however,
greater abundance of Proteobacteria has been correlated with memory dysfunction in
adult mice whose mothers were fed a high fat diet before and during pregnancy (155).
Collectively, these data highlight various bacterial populations that may be associated
with the poor memory performance associated with early life CAF exposure. However,
one limitation of the present study is that correlations were analyzed with experimental
and standard chow groups combined, as sample sizes were not sufficient to evaluate
correlations within each diet group separately. Further, functional conclusions cannot
be made from correlation alone, and thus future studies that directly target these
bacterial populations will be required to determine the possible causal relationships
between these bacteria and hippocampal-dependent memory.

47
In contrast to our results, some studies have reported that dietary interventions
involving a switch to healthier diets following WD can alleviate gut dysbiosis in rodents
(156–158) and in humans (159, 160). Our results, however, show an even greater
divergence in the microbiome relative to chow-fed rats after switching from either a
SUG or a CAF diet to a healthy standard chow diet for ~5 weeks, especially in the CAF
animals. These discrepancies could be due to the timing of when WD was introduced
(we exposed animals to the WD during a critical developmental period, whereas the
studies cited above evaluated WD consumption in adulthood). Thus, the present results
reinforce that diet composition during early life is critical to the composition of the gut
microbiome in adulthood. Although further research needs to be conducted, this
divergence despite healthy dietary intervention may be related to altered competition
within the gut microbial community due to the long-term effects of an early life WD.
Understanding the influence of early life diets on the competitive landscape of the gut
microbiome will be key in helping to reverse WD-induced gut dysbiosis and its effect on
cognitive ability. One possible therapy to explore further is the use of probiotics,
especially since there is evidence to suggest that probiotics can help improve memory
function after WD exposure in male rodents (86, 161, 162) and help improve WD-
induced gut dysbiosis in female mice (163).
In conclusion, we found that consumption of either a high sugar diet or a
cafeteria-style junk food diet during adolescence can lead to metabolic dysfunction,
HPC-dependent episodic memory deficits, and gut microbiome dysbiosis in female rats.
These negative metabolic outcomes were not observed following a 5-week healthy
dietary intervention (maintained on chow and water only). On the other hand, HPC-
dependent memory deficits associated with adolescent cafeteria-style junk food diet

48
consumption were observed despite healthy dietary intervention, whereas memory
deficits associated with early life sugar consumption were not observed after the
intervention. The changes in the gut microbiome relative to chow-fed rats, however, are
present either with or without dietary intervention, suggesting that dietary effects on gut
bacterial populations during early life periods may have long-lasting implications for the
microbiome during adulthood. However, more studies need to be conducted to evaluate
Western diet-associated changes in the microbiome across time given that one
limitation of the present study is that it was not longitudinal, but rather, compared
experimental dietary groups to a standard chow-fed group under different conditions
(either immediately following early life dietary treatment, or 5 weeks after a healthy
dietary intervention). Cross study comparisons of present results with the literature
identify the need to consider sex as a key variable in studying connections between WD,
the microbiome, and neurocognitive outcomes.

Acknowledgments
This work was supported by grant numbers DK123423 (Awarded to SK and AF)
from the National Institute of Diabetes and Digestive and Kidney Diseases and also by
the National Science Foundation Graduate Research Fellowship DGE-1842487
(Awarded to LT). The authors have nothing to disclose.

49
Chapter 3: Early life low-calorie sweetener consumption disrupts glucose
regulation, sugar-motivated behavior, and memory function in rats
Tsan L., Chometton S., Zuo Y., Sun S., Hayes A.M.R., Bridi L., Lan R., Fodor A.A.,
Noble E.E., Yang X., Kanoski S.E., Schier L.A.S., under review
Abstract:
Low-calorie sweetener (LCS) consumption in children has increased dramatically
due to widespread presence in the food environment and efforts to mitigate obesity
through sugar replacement. However, mechanistic studies on the long-term impact of
early-life LCS consumption on cognitive function and physiological processes are
lacking. Here, we developed a rodent model to evaluate the effects of daily LCS
consumption (acesulfame potassium, saccharin, or stevia) during adolescence on adult
metabolic, behavioral, gut microbiome, and neural outcomes. Results reveal that
habitual early-life LCS consumption disrupts post-oral glucose tolerance and impairs
hippocampal-dependent memory in the absence of weight gain. Furthermore,
adolescent LCS consumption yielded long-term reductions in lingual sweet taste
receptor expression and alterations in sugar-motivated appetitive and consummatory
responses. While early life LCS consumption did not produce robust changes in the gut
microbiome, brain region-specific RNA sequencing analyses reveal LCS-induced
changes in collagen- and synaptic signaling-related gene pathways in the hippocampus
and nucleus accumbens, respectively, in a sex-dependent manner. Collectively, these
results reveal that habitual early-life LCS consumption yields long-lasting impairments
in glucoregulation, sugar-motivated behavior, and hippocampal-dependent memory in
rats, which may be based in part on changes in sweet taste receptor expression and
neuronal gene pathways.

50
Introduction:
Children are the highest sugar consumers of any age group with approximately
16% of total calories coming from added sugar, nearly 40% of which comes from sugar-
sweetened beverages (SSBs) (164). Studies in humans and rodent models reveal that
excessive early life sugar consumption negatively impacts glucose metabolism (165,
166), sensory/reward processing (167, 168), the gut microbiome (83, 169), and
neurocognitive abilities (44, 170–172). To combat these adverse effects, children, like
adults, are consuming more foods and beverages that contain low calorie sweeteners
(LCS) in lieu of sugar (173, 174). Indeed, LCS consumption in children increased by
nearly 200% between 1999 and 2012 (173). Even though substitution of sugar-laden
foods and fluids with those containing LCS is perceived to be beneficial for body weight
management, the evidence for this in youth is mixed (175–181). Mechanistic rodent
model studies may offer some insight into the long-term effects of habitual early life LCS
consumption on caloric intake and metabolic function.
Although LCS bind to the same taste receptors as caloric sugars (182), they are
less effective at eliciting biological signals that influence food intake and metabolism.
For example, carbohydrates and other nutrients trigger the release of hormones from
intestinal enteroendocrine cells that influence satiation and glucose metabolism,
including glucagon-like-peptide 1 (GLP-1) and glucose-dependent insulinotropic
polypeptide (GIP) (183). LCS consumption, however, fails to stimulate GLP-1 secretion
in rats (57) and can lead to over-secretion of GIP in humans (184). Some have suggested
that extended LCS consumption results in the uncoupling of sweet taste from the
physiological and neural events normally produced by sugars, which, over time,
degrades the ability of sweet taste cues to effectively guide food choice, satiety, and

51
metabolic processes (185). Consistent with this view, a history of LCS consumption in
rodent models attenuates cephalic phase physiological signaling (56, 186).
In addition to physiological metabolic outcomes, emerging evidence indicates
that LCS consumption may be linked with neurocognitive function. For example,
habitual LCS consumption based on food-frequency questionnaires is associated with
increased prospective risk for all-cause dementia(187). To mechanistically address
whether early-life LCS consumption impacts memory function, here we developed a
model in which juvenile rats (postnatal [PN] day 26) are given daily access to LCS
(saccharin, stevia, or acesulfame potassium [ACE-K]) under conditions where oral
consumption is voluntary, the daily dose is fixed based on body weight and is within the
U.S. FDA-recommended ADI. Our goal was to investigate the impact of voluntary daily
LCS consumption throughout the juvenile and adolescent stages of development in rats
(PN 26-60) on ingestive and cognitive behavioral outcomes during adulthood, and
whether early life LCS consumption leads to changes in glucoregulatory function, the
gut microbiome, and neuronal gene expression patterns in adulthood.

Materials and Methods:
Animal Monitoring: Male and female Sprague Dawley rats (Envigo, Indianapolis, IN,
USA; postnatal day (PN) 25; 50-70g) were housed individually in a climate controlled
(22–24 °C) environment with a 12:12 light/dark cycle (lights off at 6pm). Rats were
maintained on standard chow (Lab Diet 5001; PMI Nutrition International, Brentwood,
MO, USA; 29.8% kcal from protein, 13.4% kcal from fat, 56.7% kcal from carbohydrate)
and water. All experiments were performed during the light cycle. At PN 26, rats were
randomized into groups of comparable weights and provided with their experimental

52
diets. Body weights were measured daily whereas water consumption and chow intake
were measured 3 times per week. All experiments were approved by the Animal Care
and Use Committee at the University of Southern California and performed in
accordance with the National Research Council Guide for the Care and Use of
Laboratory Animals.

Experiment 1: Juvenile male and female rats (n=10 per sex/sweetener) were provided
with the maximum acceptable daily intake (ADI) in mg/kg body weight, as
recommended by the U.S. FDA, for acesulfame potassium (ACE-K; catalog # A2815,
Spectrum Chemical, Gardena, CA, USA; 0.1% weight/volume (w/v) in reverse osmosis
(RO) water; ~15 mg/kg), saccharin (catalog # 81-07-2, Sigma, St. Louis, MO, USA; 0.1%
w/v in RO water; ~15 mg/kg), or stevia (JG Group, Ontario, Canada; 0.033% w/v in RO
water; ~4 mg/kg) from PN 26-77 (approximately 7 weeks of access to the assigned
sweetener). The volume required for delivery of each solution was calculated based on
body weight daily and injected into empty rodent sipper tubes, fastened at the end with
vinyl caps (6mm inner diameter, Jocon SF9000) to prevent leakage, and placed on the
wire rack of the home cage adjacent to the rat’s ad libitum standard chow and water
bottle. Voluntary consumption of the entire sweetener ration was verified daily by
inspecting the tube for all animals. Rats in the control group (CTL; n=10 per sex) were
provided a sipper tube filled with RO water at an equivalent volume/body weight as the
ACE-K and saccharin groups. The concentration of each sweetener was selected based
on in-house two bottle preference tests (concentrations preferred to water) as well as
concentrations used in published studies (188, 189). Sweetener access ceased at PN 77
(experiment depicted in Fig. 1a).

53

Behavioral Experiments:
Novel Object in Context. Contextual episodic memory was assessed in rats
beginning at PN 63 (following 30 days of LCS consumption) using the hippocampal-
dependent Novel Object in Context (NOIC) task, a timeframe and behavioral procedure
adapted from (190). The NOIC procedure took place over 5-days, each day consisting of
a 5-min session per animal. The apparatus and objects were cleaned with 10% ethanol
(EtOH) between each animal. On days 1 and 2, rats were placed in Context 1, a semi-
transparent box (38.1 cm W × 61 cm L × 30.5 cm H) with yellow stripes, or Context 2, a
grey opaque box (43.2 cm W × 43.2 cm L × 40.6 cm H) (one context/day in
counterbalanced order). Following this habituation phase, each animal was placed in
Context 1 containing Object A and Object B placed on diagonal, equidistant markings
with ample space for the rat to circle the objects (NOIC, Day 1). Object A and Object B
were an unopened 12 oz. coke can and a stemless wine glass, counterbalanced among
animals. Importantly, the side Object A was located on was counterbalanced by group.
The following day (NOIC day 2), rats were placed in Context 2 with identical copies of
Object A. On the test day (NOIC day 3), rats were placed again in Context 2, except this
time with Object A and Object B (which was not a novel object per se, but its placement
in Context 2 was novel to the rat). On NOIC days 1 and 3, exploration (defined as
sniffing or touching the object with the nose or forepaws) was hand-scored by an
experimenter blinded to the experimental group assignments who was viewing a live
camera recording displayed on a computer monitor. The discrimination index for Object
B [Time spent exploring Object B/ (Time spent exploring Object A + Time spent

54
exploring Object B)] was calculated for days 1 and 3. Data were represented as % shift
from baseline, where baseline is the discrimination index on day 1.
Barnes Maze. To test for hippocampal-dependent spatial memory, we employed
a Barnes Maze task as previously described (33, 191). In this task, rats were placed on a
Barnes Maze (Med Associates; St Albans, VT, USA), a circular elevated platform
(Diameter: 122 cm, Height: 140 cm) containing 18 identical holes spaced twenty degrees
apart along the edge. Four sets of visuospatial cues (e.g., black and white stripes, a white
circle, a stuffed unicorn, and an assortment of irregular shapes) were displayed on the
room walls surrounding the maze, approximately 1 meter from the edges of the maze.
The rats were habituated to the maze for 1 day as previously described (33), then trained
for two days with two trials per day (as described below). The probe test, which assesses
spatial memory retention, was conducted at PN 77.
During each training trial, the rat was placed in a start box for 30 seconds, then the box
was lifted and the animal was given 3 minutes to find the hidden escape box within one
of the holes. Each rat was assigned a specific escape hole in relation to the spatial cues,
with the location counterbalanced across groups. To motivate the rats to search for the
escape box, mildly aversive stimuli (120 W bright overhead light and 75 db white noise)
were used, with the white noise being shut off when the rodent entered the escape box
(191). After each trial, the rat was left undisturbed in the escape box for 1 minute before
being returned to its home cage. Between each rat and trial, all surfaces were cleaned
with 10% EtOH and the maze was rotated 180 degrees (to eliminate olfactory strategies).
In the case that the rat failed to find the escape hole within the 3-minute trial, the
experimenter placed the rat inside the escape hole for 1 minute. Latency (defined as the
time to reach the escape hole), and the number of incorrect hole investigations was

55
recorded by the experimenter. The procedure for the probe test was similar to training,
except that the test was a single 2-minute trial with no escape box. Data were presented
as the percent correct investigations on the first 10 investigated holes.
Zero Maze. All rats were tested for anxiety-like behavior in the Zero Maze on PN
110 or 111. The Zero Maze was an elevated circular platform (63.5 cm height, 116.8 cm
external diameter) with two closed zones and two open zones, all of which were equal in
length. The closed zones were enclosed with 17.5 cm high walls whereas the open zones
had only 3 cm high curbs. Animals were started in the same closed arm of the maze and
allowed to roam the maze for a single 5-minute session. After each session, the
apparatus was cleaned with 10% EtOH. An experimenter scored the total time the rat
spent in the open zones. A rat was considered in an open zone if its head and two front
paws were in the open zone, as previously described (33). Data were reported as percent
time spent in the open zones over the 5-minute test.
Progressive ratio operant responding for sucrose or high-fat diet. Operant
response training for sucrose was conducted as previously described (192). Rats were
habituated to 20 sucrose pellets in the home cage on PN 134. Starting at PN 135, the rats
received a 1-h training session each day over 6 days in standard conditioning boxes
(Med Associates, Fairfax, VT, USA) that contain an ‘active’ lever and an ‘inactive’ lever,
whereby pressing the active lever, which was the same for each animal, results in the
release of a 45 mg sucrose pellet into a food cup (F0023, Bio-Serv, Frenchtown, NJ,
USA). The first two days, the rats were trained to press the active lever on a fixed ratio-1
(FR1) schedule with an autoshaping component. On these sessions, each active lever
press results in sucrose reinforcement. In the case that 10 minutes lapse without an
active lever press, a pellet is automatically dispensed. The next four days of training

56
consisted of FR1 followed by FR3 (3 active lever presses were required to obtain 1 pellet)
training without autoshaping for 2 days each. Subsequently, from PN 151-152, the rats
were tested using a progressive ratio (PR) reinforcement schedule. As previously
described, the number of lever presses for a sucrose pellet increased progressively using
the following formula:

F(i)=5e^0.2i–5

where F(i) is the number of lever presses required for the next pellet at i=pellet number
(192, 193). The test session terminates when the rat did not achieve a ratio within 20
minutes, and the total number of pellets earned was recorded. Beginning on PN 153,
rats were retrained with two FR1 sessions and one FR3 session (one session / day) with
high-fat pellets (35% kcal fat enriched with sucrose, F05989, Bio-Serv, Frenchtown, NJ,
USA). Then, the rats were retested from PN 159-160 on a PR schedule, as above, except
that high-fat pellets were used in place of sucrose pellets.
Free access sucrose consumption in the home cage. From PN 165-193, all rats
were provided ad libitum access to an 11% w/v sucrose solution (C&H Pure Granulated
White Cane Sugar, Crockett, CA, USA; dissolved in RO water) in addition to standard
chow and a water bottle in the home cage. The concentration of sucrose was selected to
match the one found in common sugar-sweetened beverages consumed by humans
(194) and our prior studies (33). Sugar intake was measured and fresh sugar solutions
were provided every three days. After 4 weeks of access, the average sucrose consumed
per day (in kcals) in sweetener groups was compared to intake of sucrose in CTL groups.

57
Ingestive behaviorial experiments:
Solutions. Corn oil emulsions were made by mixing 4.5% oil (Mazola, ACH Foods
Inc., Oakbrook Terrace, IL, USA) and 0.6% of an emulsifier (Emplex®) in deionized
water (dH 2O) in an emulsifying blender before the training sessions. Emulsions were
blended again if oil droplets started to appear in the solution. Reagent-grade glucose
(0.56 M), fructose (0.56 M), 10% w/v MALTRIN (Maltrin580), quinine HCl (0.15 mM,
0.3 mM, and 1mM; QHCl), and lithium chloride (0.12 M LiCl) were prepared fresh with
dH 2O before each lickometer session. While the concentration of LiCl produces
aversion, consumption of LiCl was capped to prevent over-ingestion, based on (195).
Lickometer training and tests. Animals were given 30-minute sessions (with the
exception of the LiCl test, which was 20 minutes, see below) in identical operant
chambers equipped with optical lickometers (Habitest, Coulbourn Instruments,
Allentown, PA, USA). The optical lickometer registered licks from a sipper spout via
breaks in a photobeam positioned just in front of the spout orifice. The sipper spout was
in the recessed magazine in the center of one end wall, ∼2 cm above a grid floor. Access
to the sipper spout was computer-controlled via a motorized guillotine door. Licks were
timestamped and recorded via Coulbourn Instruments’ Graphic State software (Ver
4.0). Starting at PN 82, overnight water deprived rats were trained to lick in the
lickometer for 30-minute sessions on two consecutive days (one session / day). On each
day, rats were offered a bottle of dH 2O in the lickometer. The second day, any rat that
did not take at least 800 licks in 30 minutes was given an additional 30-minute session
with dH 2O later the same day. After the second training day, rats were provided home
cage water to replete. Then, starting on PN 85, rats were provided rations every day to
maintain their body weight to 85% of their ad libitum feeding body weight. At PN 88,

58
rats were trained to lick for 4.5% corn oil emulsion for one 30-minute session so they
would associate the spout with calorie intake. Rats were retrained as necessary the same
day, under the same criterion as water training (at least 800 licks at the end of the
session). Testing started at PN 89 and occurred over two days. Testing order was
counterbalanced such that half the animals were given 0.56 M glucose to consume for
30 minutes on the first test day and 0.56 M fructose on the second test day; the other
half received the reverse order. After one day of rest, rats were then tested with 10% w/v
MALTRIN for 30 minutes and were returned to ad libitum chow 30 minutes after
testing. From PN 95-105, the rats were water restricted (bottles pulled the day before
water retraining, which occurred over 1 day, and returned 30 minutes after the test) to
test for 30-minute quinine intake (starting with the lowest concentration on PN 96 and
ending with the highest concentration on PN 105, with 2-4 days on ad libitum water
between concentrations to allow for sufficient rehydration). At PN 130, overnight water
deprived rats were retrained with 30-minute access to water, and then water deprived
again. The next day, rats were tested with the 0.12 M LiCl solution. Microstructural
analyses of licking patterns on each test were performed with the time stamped lick
records using an open-source Python program
(https://github.com/pungaliy/Microstructural_Lick_Analysis). Bursts were defined as
runs of licks, separated by a ≥ 1 second pause in licking (196). In addition to the total
number of licks taken per session, total licks in the first minute, first burst size, number
of bursts, and mean burst sizes were computed.

Body Composition: At PN 194, rats were food restricted for one hour prior to being
weighed and scanned for body composition as previously described (169) using the

59
Bruker NMR Minispec LF 90II (Bruker Daltonics, Inc., Billerica, MA, USA). The
apparatus was based on Time Domain Nuclear Magnetic Resonance (NMR) signals from
all protons and has the benefit of being non-invasive and requiring no anesthesia.
Percent body fat was calculated as [fat mass (g)/body weight (g)] x 100.

Microbiome:
Fecal collection. Immediately after Barnes Maze testing (PN 77), animals were
individually placed in a sterile cage with no bedding and were mildly restrained until
defecation occurred. Fecal samples were weighed under sterile conditions and then
placed into a DNAse/RNAse free 2 mL cryogenic vial embedded in dry ice. Samples
were then stored in a -80°C freezer. All materials used to collect samples were cleaned
with 70% EtOH in between rats.
16s rRNA Sequencing. Frozen fecal samples were shipped on dry ice to UC Davis
MMPC and Host Microbe Systems Biology Core. Total DNA was extracted using Mo-Bio
(now Qiagen) PowerFecal kit. Sample libraries were prepared and analyzed by barcoded
amplicon sequencing. In brief, the purified DNA was amplified on the V4 region of the
16S rRNA genes via PCR using the following primers: F319 (5’-
ACTCCTACGGGAGGCAGCAGT-3’) and R806 (5’-GGACTACNVGGGTWTCTAAT-3’).
High-throughput sequencing was performed with Illumina MiSeq paired end 250-bp
run.
Sequence processing and data analysis. Sequencing reads were analyzed with
DADA2 and QIIME2 following the developers’ instructions (197). The forward reads
were truncated to 200bp and denoised to amplicon sequence variants (ASVs), and the
chimera sequences were detected with the DADA2 ‘consensus’ method and removed.

60
The ASV sequences were classified using the QIIME2 sklearn classifier with the SILVA
database (release 132) (198). The taxonomic abundance tables were normalized as
previously described to correct for the varied sequencing depth across samples (199).
The statistical analysis was performed with R. The PCoA ordinations of the microbiomes
were calculated based on the Bray-Curtis dissimilarity and visualized using the R
function ‘capscale’ in the package ‘vegan’. The PERMANOVA test of the associations
between microbiome and groups (CTL vs LCS, and CTL vs ACE-K) was performed with
the function ‘adonis’ in the same package. Shannon diversity index was calculated with
the function ‘diversity’ and used to characterize the alpha diversity of the microbiomes.
The associations of individual taxa and groups (CTL vs LCS, and CTL vs ACE-K) were
analyzed with a linear regression model with Group and Sex of the rat as the main
effects and Group x Sex as the interaction. Rare taxa (prevalence <25% samples) were
not included in order to avoid over adjustment for false discovery rate. The Wilcoxon
test (FDR<0.1) was used to identify significant differential taxa between treatment and
CTL. The P-values were adjusted for multiple hypotheses testing with the Benjamini-
Hochberg method.

Experiment 2: To examine the effects of early life sugar and LCS consumption on
glucose tolerance in adulthood, a cohort of juvenile male rats (n=15) was divided into
the following two groups at PN 26: 1) control diet, with standard chow and water, and a
sipper tube injected daily with water as in Experiment 1 (CON; n=8), 2) ACE-K diet,
which received the U.S. FDA-recommended ADI amount of ACE-K (0.1% w/v;
~15mg/kg) daily via a sipper tube, with standard chow and water as described above
(ACE-K; n=7). Rats were on the experimental diets until PN 74, to approximately match

61
the ACE-K exposure in Experiment 1 (7 weeks of access), and then subsequently
outfitted with gastric catheters from PN 79-81 to compare glucose tolerance following
either oral or gastric dextrose administration (experiment depicted in Fig. 1b).
Gastric catheter surgeries. Gastric catheter surgeries were conducted as
described in Schier et al. previously (200). Briefly, following an overnight fast, rats were
laparotomized while under the anesthetic isoflurane (~5% induction rate; ~1.5–3%
maintenance rate). A gastric catheter made of silastic tubing (inside diameter = 0.64
mm, outside diameter = 1.19 mm; Dow Corning, Midland, MI, USA) was inserted ~1 cm
into the stomach through a puncture wound in the greater curvature of the forestomach.
The catheter was tethered to the stomach wall with a single stay suture, silastic cuff, and
piece of Marlex mesh (Davol, Cranston, RI, USA). A purse string suture and concentric
serosal tunnel were used to close the wound in the stomach. The other end of the
catheter was then tunneled subcutaneously to an interscapular exit site, where it was
attached using a single stay suture and a larger square piece of Marlex mesh. The tube
was then connected to a Luer lock adapter, as part of a backpack harness worn by the rat
(Quick Connect Harness, Strategic Applications, Lake Villa, IL, USA). Rats were treated
postoperatively with gentamicin (8 mg/kg, subcutaneous injection) and ketoprofen (1
mg/kg, subcutaneous injection). Rats were given increasing increments of chow (1-3
pellets) after surgery and then ad libitum access to chow. The gastric catheter was
routinely flushed with 0.5 ml of isotonic saline beginning 48 h after surgery to maintain
its patency. Harness bands were adjusted daily to accommodate changes in body mass.
Intragastic and Oral Glucose Tolerance Test. The method for comparing the
effects of oral versus intragastric (IG) glucose tolerance tests in rats was newly
established and modified from prior procedures (186, 201). Following recovery from

62
surgery, all rats were trained to lick at the lickometer for water and habituated to passive
IG infusions in the Coulbourn chambers. After an overnight water deprivation, rats were
given 30-minute free access to a bottle and sipper containing water, and then returned
to the home cage (without water). Approximately 3-4 hours later, rats were returned to
the chambers. The IG catheter was connected to an infusion line, which consists of
polyethylene tubing encased in a spring tether and routed through a single channel
swivel allowing the rats to move freely about the chamber. The other end of the infusion
line was connected to syringe in a computer-controlled infusion pump. Rats were
infused with 4 ml of water at a rate of 0.75 ml/minute. Rats were returned to the home
cage at the end of the IG infusion; no home cage water was provided. On the following
day, rats received the same IG habituation session in the morning. 3-4 hours later, rats
received a second lickometer training session. In this session, rats had access to water
for 5 minutes through a sipper spout that was connected to an infusion pump. In this
system, licking the spout activated the infusion pump for 1 seconds at a rate of 0.75
ml/minute and during this activation time licks did not re-activate the pump. Rats were
returned to a home cage with water after this session. Then, to train the rats to associate
the spout with nutritive value, a third training session was conducted with 4.5% w/v
corn oil emulsion in place of water, for 30 minutes, in the morning following a 20 hour
fast. Animals were given additional 30-minute training sessions if they did not take at
least 800 licks. Approximately 3-4 hours later, rats were placed back in the chamber and
received a 4 ml IG infusion of corn oil over 5 minutes. Chow was returned after the IG
infusion. All rats underwent oral and IG glucose tolerance testing in counterbalanced
order on PN 98 and PN 101. Chow was removed from the home cage 20 hours prior to
test. Water was removed from the home cage approximately 14-20 hours prior to testing

63
to encourage licking during the test. Then, five minutes prior to the start of each test,
baseline blood glucose readings were collected from the tip of the tail and measured
using a glucometer (One touch Ultra2, LifeScan Inc., Milpitas, CA, USA). At minute 0,
rats received 3 ml of a 20% w/v dextrose solution dissolved in sterile saline via a pump-
infused licking session (OGTT) or IG infusion (IGTT) over 5 minutes. Blood glucose
readings were obtained at 5, 10, 30, 60, and 120 minutes after time 0. Rats were kept in
the behavioral chambers until after the 30-minute blood glucose measurements and
were promptly returned to their home cages for the remaining measurements.

Experiment 3: Male and female rats (n=16 per sex/treatment) were given daily ACE-K
(0.1% w/v; ~15mg/kg) through a sipper tube, chow, and water (ACE-K group); or chow,
water, and a sipper tube with water (CTL group) until PN 80. Our goal was to match the
design of Experiment 1 (~7 weeks access to ACE-K), in order to generate tissues for
analyses. At PN 80, chow and ACE-K sippers were removed 4 hours into the light cycle
and all rats were anesthetized with a Ketamine:Xylazine:Acepromazine mixture
(90mg/kg: 2.8mg/kg: 0.72mg/kg, intramuscular injection) before being rapidly
decapitated for collection of circumvallate tissue in RNAlater (ThermoFisher Scientific,
Waltham, MA) and flash frozen brain tissue (experiment depicted in Fig. 1c).

qPCR:
Circumvallate tissue harvest. Given that sugar-sensing genes can display a
diurnal rhythm (202) and gene expression within the circumvallate (CV) has a circadian
rhythm (203), CV samples analyzed were collected within a two-hour timeframe six
hours after fasting. The whole tongue was removed and pinned into a Sylgard® dish

64
filled with a Tyrode’s solution (140 mM NaCl, 5 mM KCl, 2 mM CaCl 2, 1 mM MgCl 2, 10
mM HEPES and 10 mM glucose). Under a dissecting microscope, 3 ml of an enzyme
cocktail [1 mg/ml collagenase A (#11088793001, Sigma-Aldrich, St. Louis, MO, USA)
and 0.1 mg/ml elastase (Sigma-Aldrich, St. Louis, MO, USA) in phosphate-buffered
saline (PBS)] was injected under the tongue epithelium, and the tongue was incubated
at 37°C for approximately 20 minutes. Then, the epithelium was carefully peeled from
the underlying connective tissue under the dissecting microscope, and the CV was
separated from the rest of the epithelium. The CVs were stored overnight at 4°C in
RNAlater (ThermoFisher Scientific, Waltham, MA), then transferred in an empty tube
and stored at -80°C.
Reverse Transcriptase-quantitative Polymerase Chain Reaction (RT-qPCR). To
quantify the relative Tas1r2 and Tas1r3 mRNA expression between the control (n= 8, 4
females and 4 males) and ACE-K (n= 8, 4 females and 4 males) rats in the CV part of the
tongue epithelium, reverse transcriptase quantitative polymerase chain reaction (RT-
qPCR) was performed as previously described (204). Total RNA was extracted from
each sample using the RNeasy Lipid Tissue Mini Kit (Cat No. 74804, Qiagen) following
the manufacturer’s instructions. The total RNA concentration per sample was measured
with a NanoDrop Spectrophotometer (ND-ONE-W, ThermoFisher Scientific). cDNA
was synthesized using the QuantiTect Reverse Transcription Kit (Cat No. 205311,
Qiagen) following the manufacturer’s instructions, and amplified using the TaqMan
PreAmp Master Mix (Cat No. 4391128, ThermoFisher Scientific). Real-time PCR was
performed using TaqMan Gene Expression Assay for rat β-actin (Actb,
Rn00667869_m1, Applied Biosystems), rat Taste receptor type 1 member 3 (Tas1r3,
Rn00590759_g1, Applied Biosystems) and rat Taste receptor, type 1, member 2 (Tas1r2,

65
Rn01515494_m1, Applied Biosystems), and TaqMan Fast Advanced Master Mix (Cat No
4444557, Applied Biosystems), in the Applied Biosystems QuantStudio 5 Real-Time
PCR System (ThermoFisher Scientific). All reactions were run in triplicate, and controls
wells without cDNA template were included to verify the absence of genomic DNA
contamination. The triplicate Ct values for each sample were averaged and normalized
to β-actin expression. The comparative 2-ΔΔCt method was used to quantify the relative
expression levels of our genes of interest between groups.

RNA-seq:
Brain tissue collection (dHPC and ACB). Whole brains were removed, flash
frozen in isopentane surrounded by dry ice and stored at −80°C until use. Tissue
punches of dorsal hippocampus (dHPC) and nucleus accumbens (ACB) (2.0 mm
circumference, 1-2 mm depth) were collected from brains mounted on a stage in a Leica
CM 1860 cryostat (Wetzlar, Germany). Anatomical landmarks based on the Swanson
brain atlas [dHPC containing dorsal cornu ammonis area 1 and dorsal dentate gyrus at
atlas levels 28-30, and ACB at atlas levels 10-12)] (205).
Sample preparation and sequencing. Total RNA was extracted according to the
manufacturer’s instructions using an AllPrep DNA/RNA Mini Kit (Qiagen, Hilden,
Germany) and checked for purity using the NanoDrop One (Thermo Fisher Scientific,
Waltham, MA, USA). All samples were found to have high purity and were sent to the
USC Genome Core for library preparation and RNA sequencing. There, the total RNA
was checked for degradation using a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA)
to verify the quality for all samples. Libraries were prepared from 1 ug of total RNA
using a NuGen Universal Plus mRNA-seq Library Prep Kit (Tecan Genomics Inc.

66
Redwood City, CA, USA). Final library products were quantified using the Qubit 2.0
Fluorometer (Thermo Fisher Scientific Inc., Waltham, MA, USA), and the fragment size
distribution was determined with the Bioanalyzer 2100. The libraries were pooled
equimolarly, and the final pool was quantified via qPCR using the Kapa Biosystems
Library Quantification Kit, according to manufacturer’s instructions. The pool was
sequenced using an Illumina NextSeq 550 platform (Illumina, San Diego, CA, USA), in
Single-Read 75 cycles format, obtaining about 25 million reads per sample.
RNA-sequencing quality control. RNA-seq quality control was performed using
FastQC (206). Low-quality reads were trimmed by Trimmomatic (207). Reads were
then aligned to Rattus norvegicus genome Rnor6.0 using STAR (208). Gene counts were
quantified using HTSeq (209). Principal component analysis (PCA) was used to detect
potential sample outliers, and one ACB sample from the ACE-K treatment group was
removed. RNA-seq quality control was performed using FastQC (206). Low-quality
reads were trimmed by Trimmomatic (207). Reads were then aligned to Rattus
norvegicus genome Rnor6.0 using STAR (208). Gene counts were quantified using
HTSeq (209). PCA was used to detect potential sample outliers (one ACB sample from
the ACE-K treatment group was removed).
Identification of differentially expressed genes (DEGs). Genes detected in less
than three samples or with a normalized count lower than five were filtered out. DEseq2
was then used to perform differential gene expression analysis between control and
ACE-K treatment groups across both sexes to identify DEGs affected by ACE-K
Treatment, Sex, and Treatment x Sex interactions, or within males and females
separately to identify DEGs affected by treatment within each sex (210). P-values were
adjusted for multiple testing corrections using Benjamini-Hochberg correction. At false

67
discovery rate (FDR) < 0.05, no significant DEGs were identified for the treatment effect
in both across and within sexes analyses. Suggestive DEGs were defined as DEGs with
an unadjusted P-value < 0.05 and the absolute value of log fold change >= 0.4. For
heatmap visualization, raw counts were normalized using regularized log
transformation implemented in DESeq2. Z-scores for each gene were then calculated
and visualized.
Pathway analyses of DEGs. Suggestive DEGs were selected for pathway analyses.
Pathway analysis was conducted using EnrichR by checking the DEG enrichment in
curated pathways from KEGG, BioCarta, Reactome (https://reactome.org/), and gene
ontology (GO) biological pathways (211–213). Pathways with an FDR < 0.05 were
considered significant.

Statistics: All data except for gene and microbiome sequencing results are presented as
mean ± SEM and analyzed and graphed using Prism software (GraphPad Inc., Version
9.1.2 (225)) or Statistica (Version 7; Statsoft), with significance set as p < 0.05. Body
weights, water and caloric intake were analyzed using a multi-factor mixed ANOVA with
Time as a within-subjects factor and Group (Experiments 1-3), Sex (Experiments 1,3)
and Sweetener (Experiment 1) as between-subjects factors. Glucose tolerance results
were analyzed via 2-way mixed ANOVA with Time as a within-subjects variable and
Group as a between-subjects variable. Body composition, NOIC, Barnes Maze, Zero
Maze, licking/ingestive tests, progressive ratio, sucrose consumption in the home cage,
and Tas1r2 and Tas1r3 mRNA expression were analyzed using a multi-factor ANOVA
with Sex, Group, and Sweetener as the independent between-subjects variables (except
for Tas1r2 and Tas1r3 mRNA analyses which did not include Sweetener as a variable).

68
Data were corrected for multiple comparisons using Sidak’s multiple comparison test.
Given that there was not a significant interaction or main effect of Sex or Sweetener in
the majority of analyses from Experiment 1 (exceptions being Barnes Maze and the
glucose vs. fructose test), all of the data from Experiment 1 are also presented with sexes
and sweeteners combined as the “LCS” group, as well as separated.

Figure 1. Timeline of Experiments. In experiment 1, rats were maintained on a
standard rodent diet of chow and water throughout the experiment. LCS solutions
(acesulfame-K, saccharin, stevia) were given daily based on mg/kg body weight doses
via a sipper tube from PN 26-77. Behavioral experiments were conducted from PN 63-
193 followed by body composition analysis at PN 194 (a). Timeline for the LCS access
A Experiment 1
B Experiment 2
C Experiment 3

69
(acesulfame-K) and glucose tolerance tests in experiment 2 is shown in (b). Timeline for
the LCS access (acesulfame-K) and tissue collection in Experiment 3 is shown in (c).
LCS: low-calorie sweeteners; NOIC: novel object in context; PN: postnatal day

Results:
Early life LCS consumption impairs post-oral glucose tolerance without
influencing body weight, caloric intake, water intake, or adiposity. Early life
LCS consumption did not yield differences in body weight (Fig. 2a), caloric intake (Fig.
2b), water intake (Fig. 2c), or body composition (data not shown) relative to controls.
Despite the lack of group differences in these energy balance parameters, early life LCS-
fed (ACE-K, specifically) rats showed impaired post-oral glucose tolerance, as evident
from higher blood glucose levels at 30 minutes after intragastric administration of a
glucose load that bypasses the oral cavity (Fig. 2d) (P = 0.0244 for Group). On the other
hand, LCS-exposure was not associated with differences in blood glucose clearance
when the same glucose load was consumed orally (Fig. 2e).

0 20 30 40 50 60 70 80 90 100 110
0
20
40
60
80
100
120
postnatal day
kcals
Total kcal intake
CTL
LCS
0 20 30 40 50 60 70 80 90 100 110
0
100
200
300
400
500
600
postnatal day
grams
Body weights
CTL
LCS
0 10 20 30 40 50 60 70 80 90 100110120
0
100
120
140
160
180
200
minutes
Blood glucose (mg/dl)
Intragastric GTT
CTL
LCS
*
0 10 20 30 40 50 60 70 80 90 100110120
0
100
120
140
160
180
200
minutes
Blood glucose (mg/dl)
Oral GTT
CTL
LCS
A B C
D E
0 20 30 40 50 60 70 80 90 100 110
0
10
20
30
40
50
postnatal day
grams
Water intake
CTL
LCS

70
Figure 2. Early life LCS consumption impairs peripheral glucose metabolism without
influencing total caloric intake, body weight, or adiposity. Daily LCS consumption
(acesulfame-K, saccharin, stevia) during development did not affect body weight (a),
total caloric intake (b), or water intake (c). Glucose intolerance in LCS-exposed rats was
observed following intragastric administration of glucose (d), but not following oral
glucose consumption when cephalic phase and orosensory responses to glucose were
intact (e). Data are means ± SEM; *P < 0.05, CTL: control; GTT: glucose tolerance test;
kcals: kilocalories; LCS: low-calorie sweeteners

Early life LCS consumption impairs hippocampal-dependent memory in
adulthood. In the NOIC task (depicted in Fig. 3a), rats normally spend more time
exploring the object that is novel to the test context; this phenomenon is disrupted by
hippocampal loss of function (112). Present results show that daily LCS consumption
during the juvenile and adolescent period yielded contextual episodic memory
impairments in the hippocampal-dependent NOIC task (timeline of experiment
depicted in Fig. 1a), exhibited by a lower shift from baseline discrimination index for
investigation of the novel object in the test context for combined male and female LCS
groups relative to controls. This outcome did not differ by sex or sweetener (sexes and
sweeteners combined analysis in Fig. 3b [P = 0.0341 for Group], separated by sex in Fig.
3c).

Spatial memory deficits associated with early life LCS consumption were also
observed in the hippocampal-dependent Barnes Maze task (depicted in Fig. 2d), albeit
only in the males, as demonstrated by significantly fewer correct (or adjacent to correct)
hole investigations during the memory probe. This outcome did not differ by sweetener
and was observed in males only (sexes and sweeteners combined in Fig. 3e, separated by
sex in Fig. 3f [P = 0.0166 for Group in males]). For females, neither control nor LCS
animals utilized a spatial strategy to solve the Barnes maze as indicated by memory

71
performance that was not above the probability due to chance (chance performance
represented by the dashed line in Fig. 3f; 1-sample t tests vs. chance performance
[0.167%] not significant for either group).

Early life LCS was not associated with significant group differences in anxiety-
like behavior in the Zero Maze test (procedure depicted in Fig. 3g; percentages of time in
the open arm area data are depicted in Fig. 3h [sexes and sweeteners combined], and
Fig. 3i [separated by sex].

CTL LCS
-40
-20
0
20
40
60
Novel Object in Context
% Shift from Baseline
✱
Males Females
-40
-20
0
20
40
60
Novel Object in Context
% Shift from Baseline
CTL
LCS
ns ns
Day 1
Baseline
Day 2 Day 3
Test
CTL LCS
0
20
40
60
80
Barnes Maze
% correct + adjacent holes
first 10 investigations
ns
Males Females
0
20
40
60
80
Barnes Maze
% correct + adjacent holes
first 10 investigations
CTL
LCS
✱ ns
Males Females
0
10
20
30
40
50
Zero Maze
% time in open arm
CTL
LCS
ns ns
CTL LCS
0
10
20
30
40
50
Zero Maze
% time in open arm
ns
B
D
C
A
E F
G H I
Contextual Episodic Memory
(Novel Object in Context)
Spatial Memory (Barnes Maze)
Anxiety-like behavior (Zero Maze)
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns

72
Figure 3. Early life LCS consumption impairs hippocampal-dependent memory during
adulthood. LCS consumption (acesulfame-K, saccharin, stevia) during the juvenile and
adolescent developmental stages impaired contextual episodic memory in the NOIC
procedure (a) regardless of sex (b, c). LCS-associated spatial memory deficits in the
Barnes Maze procedure (d) were observed in males, whereas neither female CTL nor
LCS-exposed rats utilized a spatial strategy (e, f). There were no group or sex differences
in anxiety-like behavior in the Zero Maze procedure (g-i). Data are means ± SEM; ns =
nonsignificant, *P < 0.05, CTL: control; LCS: low-calorie sweeteners; NOIC: novel
object in context

Early life LCS consumption alters ingestive responses to sugar and reduces
lingual sweet taste receptor expression (Tas1r2 and Tas1r3) without
affecting ingestion of bitter, salty, or non-sweet carbohydrate substances.
Rats that consumed LCS daily during the juvenile and adolescent period demonstrated
altered short-term sugar intake in adulthood (procedure depicted in Fig 4a). This was
due, in part, to differential early taste-guided licking responses to the two sugars in the
first minute of the test, when consummatory behaviors are primarily driven by taste and
other cephalic cues. No such differences in early licking responses were observed in the
controls. Post-hoc analyses revealed that, independent of sex and sweetener, LCS rats
consumed more fructose during the first minute of consumption relative to equimolar
glucose (sexes and sweeteners combined in Fig. 4b [P = 0.0002 for Sugar], separated by
sex in Fig. 4c-d [P = 0.0238 for Sugar in males, P = 0.0083 for Sugar in females]).
Across the entire session, however, control rats licked more for glucose than fructose.
This is consistent with previous studies showing that glucose stimulates ingestion from a
post-oral site of action more so than fructose (214). By contrast, LCS rats consumed
comparable amounts of the two sugars in the 30-minute test (Fig. 4e; P = 0.3654), an
outcome primarily driven by males with a significant Group x Sugar interaction (F(1, 32) =
6.6981, P = 0.01440) and a significant main effect of Sugar (P < 0.001), but not Group.

73
Post-hoc analyses revealed that there was a significant difference between glucose and
fructose consumption in the control males (P < 0.001 Fig. 4f) but not in LCS males. In
females, no significant interactions or main effects were observed (Fig. 4g). Although
several LCSs have bitter and/or metallic taste qualities, LCS-exposed rats did not
display differences in consumption of the prototypical bitterant, quinine, at various
concentrations (0.15, 0.3, and 1 mM) during the first minute (Fig. 4h) or entire session
(Fig. 4i).
The altered ingestive responses to monosaccharides observed in rats given early
life daily access to LCSs may be based on altered sweet taste receptor expression, as
gene expression analyses for the two sweet receptors revealed reduced relative sweet
taste receptor mRNA levels in the circumvallate papillae of LCS-exposed (ACE-K,
specifically) rats compared to controls [Tas1r2: P = 0.0015; Fig. 4j, separated by sex in
Fig. 4k, P = 0.0252 for males, P = 0.0311 for females) and Tas1r3: P = 0.0027; Fig. 4l,
separated by sex in Fig. 4m, P = 0.0234 for females).

74

Figure 4. Early life LCS exposure alters sugar consumption and reduces lingual sweet
taste receptor expression. Schematic displaying the use of the lickometer for analyses of
ingestive responses to equimolar glucose and fructose solutions is depicted in (a).
Whereas CTL showed equivalent short-term (first minute) ingestive responses for a
glucose versus an equimolar fructose solution, rats previously given daily LCS treatment
(acesulfame-K, saccharin, stevia) show heightened initial licking responses for the
fructose solution relative to glucose regardless of sex (b-d). Longer-term (30 min)
ingestive appetitive responses were higher for the glucose relative to the fructose
solution in CTL, but not in LCS-exposed rats (e-g). Ingestive responding for the bitter
tastant quinine, as measured by licks during the first minute of exposure (h), or whole-
session consumption (i), was comparable between CTL and LCS-exposed animals. LCS-
exposed rats (acesulfame-K) also had reduced gene expression levels of the sweet taste
0.15mM 0.3mM 1mM
0
500
1000
1500
2000
2500
Quinine [ ]
Total licks
CTL
LCS
Sexes combined
ns ns ns
0.15mM 0.3mM 1mM
0
100
200
300
400
500
Quinine [ ]
Licks in min1
CTL
LCS
Sexes combined
ns ns ns
CTL LCS
0.0
0.5
1.0
1.5
2.0
Relative Tas1r2
mRNA expression
✱✱
Sexes combined
CTL LCS
0
100
200
300
400
500
Sexes combined
Licks in min1
Glucose
Fructose
ns ✱✱✱
CTL LCS
0
100
200
300
400
500
Licks in min1
Males
Glucose
Fructose
ns ✱
CTL LCS
0
100
200
300
400
500
Females
Licks in min1
Glucose
Fructose
ns ✱✱
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Males
Total licks
Glucose
Fructose
✱✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Total licks
Females
Glucose
Fructose ns ns
A B C
D E F
G H I
Males Females
0.0
0.5
1.0
1.5
2.0
Relative Tas1r2
mRNA expression
CTL
LCS
✱ ✱
CTL LCS
0.0
0.5
1.0
1.5
2.0
Relative Tas1r3
mRNA expression
✱✱
Sexes combined
Males Females
0.0
0.5
1.0
1.5
2.0
Relative Tas1r3
mRNA expression
CTL
LCS
ns ✱
J K L M

75
receptors, Tas1r2 (j,k) and Tas1r3 (l,m) in the CV regardless of sex. Data are
means ± SEM; ns = not significant, *P < 0.05, **P < 0.01, ***P < 0.001. CTL: control;
CV: circumvallate papillae of the tongue; LCS: low-calorie sweeteners

Early life LCS consumption reduces effort-based responses for sucrose yet
increases free access sucrose consumption. Daily LCS consumption during the
juvenile and adolescent period was associated with reduced motivation to lever press for
sucrose, but not high fat, reinforcement in the operant progressive ratio task (depicted
in Fig. 5a) when tested during adulthood (Group main effect for sucrose P = 0.0308;
Fig. 5b), an effect primarily driven by the females (P = 0.0248 for females; Fig. 5c). In
comparison, LCS-exposed rats earned similar amounts of HFD pellets during the
progressive ratio test as controls (Fig. 5d, separated by sex in Fig. 5e).

In contrast, LCS-exposed rats showed increased free access consumption of
sucrose (10% w/v) relative to controls when consumption was measured in the home
cage over a 4-week period (Fig. 5f-g, P = 0.0011), an outcome that did not differ by sex
(Fig. 5h, P = 0.0380 for males, P = 0.0443 for females). During these 4 weeks with
sucrose access in the home cage, there were no long-term effects of early life LCS
consumption on body weight (Fig. 5i, separated by sex in Fig. 5j), total calories
consumed from chow and sucrose combined (Fig. 5k; separated by sex in Fig. 5l),
calories consumed from chow (Fig. 5m; separated by sex in Fig. 5n), or water intake
(Fig. 5o; separated by sex in Fig. 5p). Neither the progressive ratio nor the home cage
free access sucrose consumption results were significantly affected by sweetener.

76

Figure 5. Early life LCS consumption reduces effort-based responding for sucrose
while increasing long term free-access sucrose intake. In the progressive ratio schedule
operant task which measures effort-based responding for food reinforcement (a), LCS
rats (acesulfame-K, saccharin, stevia) earned fewer sucrose pellets collapsed across sex,
though this effect was more pronounced in LCS females (b, c). No group differences
were observed in motivated operant responding for high fat diet pellets (d, e). However,
when provided with free access to a sucrose solution in the home cage (f), LCS rats
consumed more of the sucrose solution relative to controls regardless of sex (g, h). There
were no significant group differences in body weight (i, j), total (sucrose plus chow)
caloric intake (k, l), caloric intake from chow (m, n), or water intake (o, p) . Data are
means ± SEM; ns = not significant, *P < 0.05, **P < 0.01. CTL: control; HFD: high fat
diet; kcals: kilocalories; LCS: low-calorie sweeteners
Males Females
0
20
40
60
80
100
Total kcals
CTL
LCS
ns ns
CTL LCS
0
200
400
600
Body weight (g)
ns
Males Females
0
200
400
600
Body weight (g)
CTL
LCS
ns ns
Males Females
0
20
40
60
80
100
Chow (kcals)
CTL
LCS
ns ns
CTL LCS
0
5
10
15
20
Progressive Ratio
Sucrose pellets earned
✱
Males Females
0
5
10
15
20
Progressive Ratio
Sucrose pellets earned
CTL
LCS
ns ✱
CTL LCS
0
5
10
15
20
Progressive Ratio
HFD pellets earned
ns
Males Females
0
5
10
15
20
Progressive Ratio
HFD pellets earned
CTL
LCS
ns ns
Males Females
0
20
40
60
80
100
11% w/v sucrose/day (kcals)
Sucrose in Home Cage
CTL
LCS
✱ ✱
CTL LCS
0
20
40
60
80
100
11% w/v sucrose/day (kcals)
11% Sucrose_collapsed
✱✱
B C A D
E F H
Progressive Ratio
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
I J K L
CTL LCS
0
20
40
60
80
100
Chow (kcals)
ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
CTL LCS
0
1000
2000
3000
4000
5000
Sexes combined
Total licks
Glucose
Fructose
✱✱ ns
M N O P
CTL LCS
0
2
4
6
8
Water intake (g)
ns
Males Females
0
2
4
6
8
Water intake (g)
CTL
LCS
ns ns
CTL LCS
0
20
40
60
80
100
Total kcals
ns
G

77
Collagen-related gene pathways in the hippocampus are altered by early life
LCS consumption in a sex-specific manner. To explore potential mechanisms
related to the effects of LCS consumption (ACE-K, specifically) on neurocognitive
outcomes, brains from animals that received early life ACE-K were collected in
adulthood for bulk RNA sequencing and gene pathway enrichment analyses
(experimental timeline depicted in Fig. 1c). Analysis of bulk rRNA sequencing of HPCd
tissue punches (targeted region depicted in Fig. 6a) identified 132 differentially
expressed genes (DEGs) for males and 138 DEGs for females (data not shown). Despite
the animals not having a clear group separation in the PCA, LCS consumption
significantly altered gene pathways related to collagen formation and synthesis.
Interestingly, various collagen-related pathways were all upregulated in LCS males
relative to controls but were downregulated in LCS females relative to controls (Fig. 6b-
d). Specifically, the DEGs were related to gene pathways involved in protein digestion
and absorption (FDR = 0.0075, P = 3.74E-05 for males; FDR = 0.0075, P = 8.25E-05
for females), assembly of collagen fibrils and other multimeric structures (FDR =
0.0075, P = 3.51E-05 for males; FDR = 0.0006, P = 4.33E-06 for females), collagen
biosynthesis and modifying enzymes (FDR = 0.01, P = 7.41E-05 for males; FDR =
0.0002, P = 6.69E-07 for females), and collagen formation (FDR = 0.0309, P = 0.0003
for males; FDR = 0.0006, P = 5.16E-06 for females).

78

Figure 6. Early life LCS consumption differentially impacts gene expression patterns in
the HPC and ACB. Target region for dorsal HPC tissue harvest (a). PCA of male and
female LCS (acesulfame-K) and CTL rats (b). Gene pathway enrichment analyses
identified 4 common gene signaling pathways that were significantly altered by LCS
consumption in both males and females, as illustrated in the Venn diagram (c). All 4 of
these pathways were related to collagen, and each pathway was significantly upregulated
in male LCS rats, but downregulated in female LCS rats relative to controls (d). Target
region for ACB shell tissue harvest (e). PCA of male and female LCS and CTL rats (f).
Pathway enrichment analyses identified 5 common gene signaling pathways that were
significantly altered by LCS consumption in both males and females, as illustrated in the
Venn diagram (g). These pathways were related to synaptic plasticity, and each pathway
was significantly downregulated in male LCS rats, but upregulated in female LCS rats.
Data are means ± SEM; ns = not significant, *P < 0.05, **P < 0.01. Significant gene
ec SI
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scc
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EPd
CP IG
IG
CLA
4 3
2 1
5
MOp
SSp
GU AId rhs
PIR
1
2
3
6a
6b
crp
crp
ACAd ACAv
VLa
3
5
SEZ
MOs
lcf
lotp
es
SH
OT IIn
2 1
isl
isl
isl
isl
isl
1 2
3
ACB aco
islm
TTd2
ILA
n
ul
AIv
ccr
LSr
LSc.d.r
r.m.d
r.vl.d.m
r.vl.d.l
Atlas Level 12
PC2: 17% variance
TUsv
ec
ec
amc
pofh vlt optt opth SI
mttt
int
st
fi
alv
ccb
ccb
crp
df
scc alv
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VMH LHA
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PCN
MD
RE
ARH
PVi
SOr
V3h
ME tis lem
GPm
TUi
MEApv
ste IA
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CEA BLAp
LA
EPd
EPv
SMT
RH
sme
MH LH
CL
PVT
LD
RT
GPl
CP
VLb
m l
CA3
CA2
CA1d
IG
4
3
2 1
5
RSPv lcf RSPd MOs MOp
SSp
PIR
1
2
3 BMAa
6a
6b
PR
DG
DG
suph
COAa COApl
ex in
FC
MEApd
vl
m
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l
chpl
c
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CM
c
c
dm
DMHa
BLAa
BMAp
da
VPMpr
VPLpr
em
hs
IMD
so sp sr
mo sg po sg mo
slm
slu
1 2a b 3 5 6 ENTl
PERI AIp
VISC
SSs
tr
bfd
4
PAA
CLA
rhs
c m
cp cd
2
2
2
1
1
1
3
c
b a LHAma
LHApc TUl
sfa LHAjvv LHAsfp
LHAjvd
LHAjd
LHAs LHAd
I
I
che3
V3i
Atlas Level 28
A
PCA
E
Dorsal HPC
target tissue
Male
LCS up
Male LCS
down
Female LCS up
Female LCS down
Female LCS
down
Male LCS
down
PCA
B C
D
F G
PC1: 21% variance
H
-20 -15 -10 -5 0
0
-3
-6
3
6
Male
LCS up
Male LCS
down
Female LCS up
Female LCS down
ACB target tissue
PC1: 53% variance
PC2: 13% variance
-10 0
0
-4
4
CTL
LCS
CTL
LCS

79
pathways were identified using the following parameters: p<0.05, |logFC|>=0.4 and
FDR cutoff was < 0.05. CTL: control; LCS: low-calorie sweetener; HPC: hippocampus;
ACB: nucleus accumbens; PCA: principal component analysis; DEG: differentially
expressed gene; FDR: false discovery rate.

Glutamatergic plasticity-related pathways in the nucleus accumbens are
altered by early life LCS consumption in a sex-specific manner. RNA
sequencing analyses in ACB tissue punches (targeted region in Fig. 6e) revealed 135
DEGs for males and 227 DEGs for females overall (data not shown). A few of these
DEGs were part of gene pathways that were altered in both males and females that
consumed LCS during early life, despite the animals not having a clear separation in
PCA (Fig. 6f). Gene pathway enrichment analyses revealed that several gene pathways
related to glutamatergic signaling and synaptic plasticity were downregulated in LCS
males but upregulated in LCS females (Fig. 6g-h). These pathways include those
involved in transmission across chemical synapses (FDR = 0.0024, P = 3.24E-05 for
males; FDR = 0.0011, P = 1.73E-06 for females), trafficking of AMPA receptors (FDR =
0.0009, P = 8.76E-06 for males; FDR = 0.0038, P = 5.42E-05 for females), glutamate
binding, activation of AMPA receptors and synaptic plasticity (FDR = 0.0009, P =
8.76E-06 for males; FDR = 0.0038, P = 5.42E-05 for females), and neurotransmitter
receptor binding and downstream transmission in the postsynaptic cell (FDR = 0.0204,
P = 0.0003 for males; FDR = 0.0014, P = 5.49E-06 for females).

Gut microbial diversity was not affected by early life LCS consumption. We
first analyzed the associations between groups (CTL/LCS) and the microbiome from
phylum to ASV levels. CTL and LCS microbiomes were not separated at PCoA1 and
PCoA2 for all 7 levels (Fig. 7a-g). In addition, PERMANOVA tests indicated that the

80
microbiomes were not significantly associated with group for all 7 phylogenetic levels (P
> 0.05). The Shannon diversity was also not significantly different between CTL and
LCS groups (Fig. 7h-n). We used a linear regression model to analyze the associations
between individual taxa and groups, with Group and Sex as the main effects and Group
x Sex as the interaction effect. The genus Corynebacterium.1 was the only taxa
significantly more abundant in control than LCS group after adjusting for multiple
testing (FDR = 0.068)) (Fig. 7o).

CTL LCS
3.5
4.0
4.5
5.0
ASV P = 0.92
Group
Shannon
CTL LCS
2.2
2.4
2.6
2.8
3.0
3.2
species P = 0.62
Group
Shannon
CTL LCS
2.2
2.4
2.6
2.8
3.0
genus P = 0.6
Group
Shannon
CTL LCS
1.7
1.8
1.9
2.0
2.1
2.2
family P = 0.85
Group
Shannon
CTL LCS
0.9
1.0
1.1
1.2
1.3
1.4
order P = 0.73
Group
Shannon
CTL LCS
0.9
1.0
1.1
1.2
1.3
1.4
class P = 0.73
Group
Shannon
CTL LCS
0.4
0.5
0.6
0.7
0.8
phylum P = 0.18
Group
Shannon
−2 −1 0 1 2
−2 −1 0 1 2
ASV
P = 0.988
PCoA1 (8.69%)
PCoA2 (7.27%)
CTL LCS
CTL
LCS
−2 −1 0 1
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
species
P = 0.724
PCoA1 (14.05%)
PCoA2 (10.7%)
CTL LCS
CTL
LCS
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
genus
P = 0.807
PCoA1 (14.92%)
PCoA2 (10.88%)
CTL LCS
CTL
LCS
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
family
P = 0.598
PCoA1 (13.58%)
PCoA2 (8.73%)
CTL LCS
CTL
LCS
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
−1.0 −0.5 0.0 0.5 1.0 1.5
order
P = 0.431
PCoA1 (17.91%)
PCoA2 (11.33%)
CTL LCS
CTL
LCS
−1.5 −1.0 −0.5 0.0 0.5 1.0
−1.5 −1.0 −0.5 0.0 0.5 1.0 1.5
class
P = 0.158
PCoA1 (17.54%)
PCoA2 (14.23%)
CTL LCS
CTL
LCS
−2.0 −1.5 −1.0 −0.5 0.0 0.5 1.0
−1.0 −0.5 0.0 0.5 1.0 1.5
phylum
P = 0.37
PCoA1 (19.95%)
PCoA2 (17.04%)
CTL LCS
CTL
LCS
A
Control LCS
0.0
0.5
1.0
p__Actinobacteria;c__Actinobacteria;o__Corynebacteriales
f__Corynebacteriaceae;g__Corynebacterium.1
NA;g__Corynebacterium.1
FDR = 0.068
Group
normalized abundance
Control LCS
0.0
0.5
1.0
p__Actinobacteria;c__Actinobacteria;o__Corynebacteriales
f__Corynebacteriaceae;g__Corynebacterium.1
__
FDR = 0.068
Group
normalized abundance
p__Actinobacteria;c__Actinobacteria;o__Corynebacteriale
s
f__Corynebacteriaceae;g__Corynebacterium.1
FDR = 0.068
B
L K J I H
G
F
E
C D
O
M N
CTL

81
Figure 7. Gut microbiome analyses of CTL and LCS groups following 7 weeks of early
life LCS exposure. PCoA ordinations of the microbiome of CTL and LCS groups
(acesulfame-K, saccharin, stevia) at phylum to ASV levels (a-g). Ellipses indicate 95%
confidence limits. P-values are from PERMANOVA tests (999 permutations). Shannon
diversity of the microbiome at phylum to ASV levels (h-n). The normalized abundance
(log10) of genus Corynebacterium.1 was significantly higher in CTL (o). ASV = all
species variation; CTL: control; LCS: low-calorie sweeteners; PCoA: principal coordinate
analyses

Discussion:
Sugar substitution with LCS is one strategy for minimizing the detrimental effects
of excess sugar intake on metabolic and neurobehavioral systems. Our findings,
however, shed new light on the widespread and lasting consequences of regular LCS
consumption across a sensitive developmental period spanning the juvenile and
adolescence phases. Results reveal that early life LCS consumption, kept within the
FDA-recommended ADI limits and consumed under voluntary conditions, significantly
impairs key aspects of glucoregulation, ingestive control of caloric sugars, and memory
function later in adulthood.
Even though LCS added to foods or beverages yields insignificant added calories,
these compounds exert influence on nutrient intake and assimilation at various sites of
action along the gut-brain axis. Here, we demonstrated that a history of daily LCS
consumption during the formative stages of life leads to impaired post-oral glucose
tolerance in rats, as well as specific perturbations in ingestive control for actual/caloric
sugars later on during adulthood. Close inspection of consummatory patterns during a
short-term intake test revealed that LCS-exposed rats were hyperresponsive to variances
in the orosensory properties of two common dietary sugars, glucose and fructose, early
in the ingestive episode. Furthermore, parallel analyses revealed reduced “sweet” taste
receptor expression levels in the taste bud cells of LCS-exposed rats. LCS-exposed rats

82
also displayed abnormal relative absolute levels of sugar intake in this acute intake test.
That is, while rats typically consume greater amounts of glucose than fructose within a
meal due to the net positive post-ingestive effects of glucose (215), LCS-exposed rats
showed no such appetition for glucose. LCS-exposed rats were also less motivated to
work for sugar in a progressive ratio task. Altogether, these data provide novel evidence
that LCS consumption during critical periods of postnatal development reprograms
physiological and behavioral responses to signals generated by sugars in the early
phases of nutrient assimilation.
A history of habitual LCS intake early in life also affected long-term control of
sugar consumption. Our results show that when LCS-exposed rats were later provided
ad libitum access to a sucrose solution in their home-cage environment, they consumed
more of the sugar than their LCS naïve counterparts. Our data further show that early
life LCS consumption alters glutamatergic synaptic plasticity genetic pathways in the
nucleus accumbens, a brain region critically involved in both appetitive and
consummatory aspects of sugar reward. Further, these glutamatergic pathways were
significantly affected in opposite directions by sex, with significant increases relative to
controls in females and significant decreases relative to controls in males despite the
fact that LCS had similar effects on behavior between sexes. Future studies will need to
delineate the basis of these opposing sex-dependent effects on ACB glutamate signaling,
as well as whether these motivational and ingestive perturbations stem from the
heightened responsivity to the rewarding taste of sugar and/or a diminished expectation
for calories conditioned by regular LCS exposure during early life.
The consequences of early life LCS consumption are not limited to ingestive
control, but also include negative impacts on memory function. Previous work revealed

83
that excessive long-term ACE-K consumption in mice led to impaired hippocampal-
dependent memory function (64, 66). However, these studies are limited by the fact that
only one sweetener (ACE-K) and sex (males) were employed. Further, these studies
were conducted in adults and involved ACE-K consumption from the only source of
drinking water, which is thus involuntary and likely exceeds the FDA recommended ADI
levels of daily consumption. Our study shows in adolescent animals that more limited,
and voluntary exposure to LCS at the ADI level leads to hippocampal-dependent
memory deficits in adulthood, as both males and females had impaired episodic
memory in the NOIC task, and LCS-exposed male rats were also deficient in spatial
working memory in the Barnes Maze task. Gene transcriptome pathway analyses
revealed significant alterations in collagen synthesis pathways in the hippocampus
following early life LCS consumption. Interestingly, despite the fact that LCS
consumption was associated with HPC-dependent memory impairments in both sexes,
these collagen-related gene pathway changes were sex-dependent with significant
increases relative to controls in males and the opposite observed in females. Collagen
plays a vital role in neural development, including in axonal guidance, synaptogenesis
and glial cell differentiation (216), and thus the present data highlight the need for more
research aimed at unveiling mechanistic links between early LCS consumption, brain
collagen signaling, and neurocognitive performance.

Acknowledgments
Funding was provided by DK123423 (Awarded to S.K. and A.F.) from the National
Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and institutional
start-up funds (L.A.S.). L.T. was supported by a National Science Foundation Graduate

84
Research Fellowship (DGE-1842487). XY was supported by DK104363 from the
NIDDK. The authors have nothing to disclose.

85
Chapter 4: General Conclusions

Overview
Processed foods that often compromise nutritional value with high amounts of
salt, sugar, fat, and flavor additives have become ubiquitous in the WD (217). A growing
concern is that the highly palatable aspect of these foods is contributing to a low-quality
diet in U.S. children (92) and in turn, increased rates of childhood obesity, which often
carries over into adulthood (4). Here, we present data surrounding the metabolic and
neurocognitive effects of consuming WD dietary factors (sugary beverage, high fat and
sugar content, and LCS) during adolescence. Importantly, we show that the effects due
to consumption of these WD dietary factors can endure in adulthood long after
removing access to the diet following adolescence, supporting a need for more research
on potential interventional strategies for the long-term effects of consuming an
adolescent WD.
In Chapter 2, we investigated the persistence of adolescent WD-induced memory
deficits and gut dysbiosis following a 5-week healthy dietary intervention in female rats.
Previous studies in adolescent male rodents have found that sugar-induced memory
impairments were not reversible with healthy dietary intervention in adulthood (38).
Furthermore, few studies have investigated the persistence of gut dysbiosis due to either
adult or adolescent WD but both studies found that switching from a WD to a CTL diet
during adolescence significantly alters adult microbiota composition in males (80, 218).
We expanded on this work by exploring these effects in female rodents following an
adolescent diet enriched with either sugar alone or sugar and fat. We demonstrated that
adolescent females with ad libitum access to a sugary beverage could recover from most

86
of the effects of the diet, including increased body fat %, impaired glucose tolerance, and
episodic memory deficits, in adulthood when access to that sugary beverage was
removed for 5 weeks. However, sugar-induced gut dysbiosis remained even after the
interventional period. In contrast, adolescent females with ad libitum access to a
cafeteria diet high in fat and sugar did not display impaired glucose tolerance but did
show increased body fat % and episodic memory deficits, both of which were not
treatable by replacing the diet high in fat and sugar with a standard rodent diet. These
enduring effects on body fat composition and memory in the cafeteria treated animals
may have been exacerbated by the gut microbiome becoming even more divergent
following the healthy dietary intervention. Overall, these data show that females differ
in response to healthy dietary intervention depending on the type of WD consumed
during adolescence and suggests that an adolescent diet enriched with both sugar and
fat, but not sugar alone, produces enduring effects on body fat composition and episodic
memory.
In Chapter 3, we studied the long-term effects of another common WD
ingredient, LCS, when consumed habitually throughout adolescence in male and female
rats, which has been largely understudied. Chronic consumption of the LCS saccharin in
adult male mice can lead to gut dysbiosis that contributes to impaired glucose tolerance
(63). While we did not find any differences in the gut microbiome in LCS rats, our data
show that consumption of LCS, particularly ACE-K, during adolescence results in
impaired glucose tolerance following an intragastric load of glucose as opposed to oral
consumption of glucose, suggesting that the post-oral response to glucose is impaired.
In addition, habitual ACE-K consumption during adolescence in our LCS rats reduced
sweet taste receptor expression on the circumvallate papillae when assessed in

87
adulthood. Together, these changes may in part explain the differences in adult ingestive
behavior seen in LCS rats that consumed either ACE-K, saccharin, or stevia during
adolescence, including display of increased palatability for fructose, impaired post-
ingestive response to glucose over isocaloric fructose, and reduced effort-based
responding for sucrose despite having increased long term free-access sucrose intake.
Other behavioral outcomes found in our LCS rats in adulthood include impaired
episodic and spatial memory. Collection of HPC and ACB-enriched tissue in adulthood
following ACE-K consumption during adolescence resulted in the discovery of altered
gene pathways related to collagen synthesis in dHPC-enriched brain tissue and
glutamatergic plasticity in ACB-enriched brain tissue. In particular, our data showed sex
differences such that pathways related to collagen synthesis in dHPC-enriched tissue
were upregulated in males yet downregulated in females. Moreover, pathways related to
glutamatergic plasticity in ACB-enriched tissue were downregulated in males but
upregulated in females. These changes in collagen and glutamatergic plasticity pathways
may be another mechanism by which LCS impacts neurocognitive and ingestive
behavior. Importantly, all of these effects occurred without any differences in body
weight, total caloric intake, or body fat % following adolescent LCS consumption and
despite the sex differences seen in gene pathways in the brain, many of these behaviors
were seen across sexes. Overall, these results suggest that habitual LCS consumption
during early life in rats disrupts glucoregulation, sugar-motivated behavior, and
hippocampal-dependent memory, which may be partially mediated by reduced sweet
taste receptor expression and altered neuronal gene pathways.
Altogether, the data collected from experiments in this dissertation highlight the
endurance of adolescent WD-induced effects on metabolism and neurocognition in

88
adulthood in rats. Specifically, excessive consumption of sugar and fat, but not sugar
alone, during adolescence led to increased body fat % and memory impairments that
were not remediated by a 5-week healthy dietary intervention in adulthood in female
rats. Additionally, both diets (SUG and CAF) led to even more divergence in the gut
microbiome relative to CTLs in adulthood following the healthy dietary intervention.
Furthermore, although LCS are often used to reduce sugar consumption, our data reflect
that regular consumption of LCS in both male and female rats during adolescence can
cause impaired memory, glucose dysregulation, and altered ingestive behavior for
sugars in adulthood. These effects may be based in part on changes in sweet taste
receptor expression and neuronal gene pathways, as seen in ACE-K animals. Further
studies will be needed to elucidate how these metabolic and neurocognitive outcomes
due to early life WD exposure can be potentially treated.

Implications and Future Directions
Advances in food production and distribution have led to an abundance of low-
cost, highly palatable foods in the modern food environment (217, 219). Studies have
shown that even short-term consumption of these highly palatable foods in adults can
result in impaired hippocampal-dependent learning and memory (220–222) and affect
appetitive decision-making (223). This begs the question how increased accessibility to
high fat, high sugar foods in the WD have impacted brain development in children,
especially given that adolescence is a critical period for neurocognitive development.
This is also an important question to address for LCS use during development, as the
brain is capable of distinguishing between energy-yielding sugars and LCS (53, 54, 224,
225), which may in turn impact neuronal plasticity during adolescence and lead to

89
changes in appetite and neurocognitive behavior in adulthood following long-term LCS
use. Lastly, as healthy dietary intervention is often recommended to reverse WD-
induced effects on metabolism, an empirical question is whether or not healthy dietary
intervention can also alleviate diet-induced cognitive dysfunction.
In this dissertation, we contributed data that suggests that adolescent WD-
induced effects can vary by 1) sex, particularly with our data showing that adolescent
females may be less susceptible to the long-term effects of sugar (190) than previously
shown in males (38) and 2) diet, with the combination of fat and sugar consumption
being more metabolically and cognitively detrimental than consumption of sugar alone.
Furthermore, our data also suggests that regardless of the type of WD, the composition
of the gut microbiota in females does not become similar to CTLs even if the rats were
put on a CTL diet following their WD exposure, suggesting that disruptions in the gut
microbiota may require a more potent intervention that targets the growth of healthy
gut microbiota. Similarly, we showed that adolescent LCS consumption within the ADI
can lead to glucose intolerance, reduced sweet taste receptor expression, and
neurocognitive consequences related to memory and appetitive behavior for sugar in
adulthood. Therefore, although LCS are often used to substitute the sweet taste of sugar
in foods, our data suggests practicing caution on habitually consuming LCS during
adolescence until more studies are done to evaluate these long-term effects of LCS use in
children.
Still, many questions regarding the lasting effects of early life WD consumption
remain. Following up on this data, future studies in the lab aim to investigate how the
combination of fat and sugar affects adolescent male rats. Importantly, we aim to
narrow the critical window in which the negative neurocognitive and metabolic effects of

90
WD exposure begin during adolescence. Moreover, we plan to investigate alternate
interventional strategies, targeting the microbiome, to alleviate the lasting impairments
seen with diets enriched with both fat and sugar. Another question that remains
regarding these data is how reduced sweet taste receptor expression on the tongue due
to early life LCS consumption affects food choices in adulthood. Given that the data
shown in the prior chapters of this dissertation support that adolescent WD
consumption of either sugar and fat, LCS, or sugar alone can lead to neurocognitive
deficits, another future research goal of the lab is to hone in on these effects at the
synaptic level for a better understanding of how brain regions, such as the HPC and
ACB, are impacted by adolescent WD consumption. In conclusion, the research
presented here show that various dietary components of processed food consumed
during the critical period of adolescence can have metabolic, neurocognitive and
appetitive consequences in adulthood, warranting further research on the long-term
effects of these dietary components in children.

91
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Creator Tsan, Linda (author)

Core Title Effects of western dietary factors during early life on glucose metabolism, the gut microbiome, and neurocognition

School College of Letters, Arts and Sciences

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Degree Program Neuroscience

Degree Conferral Date 2022-05

Publication Date 04/11/2022

Defense Date 02/28/2022

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Tag acesulfame potassium,adolescence,appetitive responses,collagen,diet,glucose,high-fat diet,hippocampus,low-calorie sweeteners,microbiota,OAI-PMH Harvest,object recognition,saccharin,stevia,sugars,sweet taste receptor

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