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A one month high fat diet disrupts the gut microbiome and integrity of the colon
inducing adiposity and behavioral despair in male Sprague Dawley rats
Gladys Chompre, Lubriel Sambolin, Myrella L. Cruz, Rafael Sanchez, Yarelis
Rodriguez, Ronald E. Rodríguez-Santiago, Yasuhiro Yamamura, Caroline B.
Appleyard
PII: S2405-8440(22)02482-3
DOI: https://doi.org/10.1016/j.heliyon.2022.e11194
Reference: HLY 11194
To appear in: HELIYON
Received Date: 12 January 2022
Revised Date: 17 June 2022
Accepted Date: 17 October 2022
Please cite this article as: Chompre, G., Sambolin, L., Cruz, M.L, Sanchez, R., Rodriguez, Y.,
Rodríguez-Santiago, R.E, Yamamura, Y., Appleyard, C.B, A one month high fat diet disrupts the gut
microbiome and integrity of the colon inducing adiposity and behavioral despair in male Sprague Dawley
rats, HELIYON, https://doi.org/10.1016/j.heliyon.2022.e11194.
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A One Month High Fat Diet Disrupts the Gut Microbiome and Integrity of the Colon Inducing
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Adiposity and Behavioral Despair in Male Sprague Dawley Rats
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Gladys Chomprea,b*, Lubriel Sambolinc, Myrella L Cruzb, Rafael Sanchezd, Yarelis Rodriguezb, Ronald E
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Rodríguez-Santiagod, Yasuhiro Yamamurad, and Caroline B Appleyardb
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aBiology and Biotechnology Department, Pontifical Catholic University of Puerto Rico, Ponce, Puerto
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Rico, bBasic Sciences Department, Division of Physiology, Ponce Health Sciences University/Ponce
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Research Institute, Ponce, Puerto Rico, Rico, cBasic Sciences Department, Division of Pharmacology,
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Ponce Health Sciences University/Ponce Research Institute, Ponce, Puerto, dAIDS Research Infrastructure
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Program, Ponce Health Sciences University/Ponce Research Institute, Ponce, Puerto Rico.
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Correspondence:
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gladys_chompre@pucpr.edu
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SUMMARY
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High-fat diet (HFD) is associated with gut microbiome dysfunction and mental disorders.
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However, the time-dependence as to when this occurs is unclear. We hypothesized that a
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short-term HFD causes colonic tissue integrity changes resulting in behavioral changes.
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Rats were fed HFD or low-fat diet (LFD) for a month and gut microbiome, colon, and
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behavior were evaluated. Behavioral despair was found in the HFD group. Although obesity
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was absent, the HFD group showed increased percent weight gain, epididymal fat tissue,
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and leptin expression. Moreover, the HFD group had increased colonic damage, decreased
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expression of the tight junction proteins, and higher lipopolysaccharides (LPS) in serum.
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Metagenomic analysis revealed that the HFD group had more Bacteroides and less S24-7
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which correlated with the decreased claudin-5. Finally, HFD group showed an increase of
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microglia percent area, increased astrocytic projections, and decreased phospho-mTOR. In
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conclusion, HFD consumption in a short period is still sufficient to disrupt gut integrity
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resulting in LPS infiltration, alterations in the brain, and behavioral despair even in the
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absence of obesity.
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INTRODUCTION
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The prevalence of obesity has increased over the last few decades in all age groups worldwide (Faith et
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al., 2011; Ng et al., 2014). Recent statistics from the Center for Diseases Control and Prevention show
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that around seventy percent of adults of twenty years old and over are overweight (Fryar et al., 2020). A
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high fat diet (HFD) is related to increased body mass index and associated with obesity; however, body
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weight does not necessarily correlate with the amount of adiposity in the body or metabolic disorders
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(Malik et al., 2013; Oliveros et al., 2014). Regardless, a HFD has been associated with comorbidities such
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as hypertension, atherosclerosis, diabetes, metabolic syndrome, and depression (Laborde et al., 2013;
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Goodpaster et al., 2005; Ford et al., 2004; Stunkard et al., 2003). Importantly, more than 10 million
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American adults suffer from mood disorders including major depressive disorder, dysthymic disorder, and
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bipolar disorder according to the U.S. Census Bureau Population Estimates by Demographic
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Characteristics (Kessler et al., 2005; Baxter et al., 2014). Although several studies in both obese humans
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and animals have found depressive-like behavior (Stunkard et al., 2003; Baxter et al., 2014; Reeves et al.,
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2008; Willner et al., 1992; Gotlib and Joormann., 2010), and lately there is increased awareness of the
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importance of gut-brain interactions on behavior, it is still not clear how alterations in the gut microbiome
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due to dietary habits might be associated with behavioral changes.
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Prior studies reported that the human gut microbiome has approximately one trillion bacteria including
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one thousand species, but recent studies using culturomics used to understand the bacterial diversity to
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species reveal that the gut microbiome genome has higher than the human genome (Methé et al., 2012;
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Lagier et al. 2018; Almedia et al., 2019). Next generation sequencing methods have helped to ascertain
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the bacterial composition of different fluids, including the feces, using 16S ribosomal RNA (Qin et al.,
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2010). According to the Human Microbiome Project Consortium, healthy gut human samples are
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dominated by two phyla: Firmicutes and Bacteroidetes, and it is known that the microbiome changes with
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various diseases including obesity (Huttenhower and Human Microbiome Project Consortium., 2012;
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Gregor and Hotamisligil., 2011; Clemente et al., 2012). It has been demonstrated that gut microbiome
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from obese rodents transplanted into lean rodents changes several characteristics of the recipient animals
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including fat accumulation, gut inflammation, and behavior, to resemble that of the donor obese rodent
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(Baxter et al., 2014; Considine et al., 1996; Bäckhed et al., 2007; Bruce-Keller et al., 2015). Increased
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levels of Bacteroidetes, Actinobacteria, and Proteobacteria are present in patients with depression (Jiang
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et al., 2015), which also correlates strongly with Alistepes and Oscillibacter (Naseribafrouei et al., 2014),
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and these can be associated with inflammatory pathways that may be linked to gut permeability.
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Importantly, permeability in the gut is normally tightly controlled to ensure that the appropriate defense
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mechanisms occur, while at the same time allowing absorption of the necessary nutrients. An imbalanced
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diet, such as that containing high levels of fat, has been associated with decreased gut motility, decreased
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tight junctions, and increased gut permeability (Kim et al., 2012; Cani et al., 2008). Consumption of a
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high fat, low carbohydrate diet in mice for 4 weeks decreased tight junctions allowing the translocation of
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bacterial products such as lipopolysaccharide (LPS) from the gut to the blood, activating the immune
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system to increase inflammation (Cani et al., 2008).
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Prior studies have found that consumption of an HFD for more than 10 weeks induces obesity and insulin
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resistance, and is related to behavioral changes such as impaired cognition, anxiety, and depressive-like
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behavior (Bose et al., 2008; Cordner and Tamashiro, 2015; Calligaris et al., 2013; Privitera et al., 2011).
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Additional studies found that long-term consumption of HFD also causes neuroinflammation (Miller and
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Spencer., 2014; Almeida-Suhett et al., 2017). Interestingly, long-term but not short-term exposure to the
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microbiome from HFD-fed mice is associated with insulin resistance (Foley et al., 2018). The impact of a
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shorter length HFD is unclear: in one study Sprague-Dawley rats 7 days on an HFD appeared to have
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anti-depressive like effects with decreased immobility in a forced swim test (Sumaya et al., 2016), while
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mice on an HFD of 8 weeks developed depressive-like behavior only when concomitant administration of
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low levels of corticosterone occurred (Liu et al., 2014). In short, the link between an HFD over a short-
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term period, the gut microbiome, LPS, and changes in behavior is still not well understood. We
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hypothesized that a short-term HFD can cause changes in the microbiome, and in the integrity of the
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colonic tissue, resulting in behavioral changes. The specific research objectives of this study were to
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evaluate whether an HFD given over a short period of time can alter the gut microbiome and the structural
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integrity of the colonic tissue; and then to assess if these changes resulted in translocation of bacterial
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products and systemic inflammation, which would correlate with behavioral changes.
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RESULTS
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Thirty days of HFD feeding results in higher percent weight gain and epididymal fat tissue than
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LFD
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Before switching to either the HFD or the LFD, the absolute weight of the LFD group (349.4±9.02 g) and
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the HFD group (349.4±9.18 g) were similar (Figure 1A, n=14/group). After the 30-day dietary
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intervention animals were weighed and again no significant differences were found between the LFD
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(452.8±9.37g) and the HFD (467.9±9.35g) with both groups gaining weight (Figure 1A, n=14/group),
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nor in the absolute weight per day during the month (Figure 1B, n=14/group). We also checked to see if
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animals were gaining weight taking into consideration their weight at day zero. Animals in the HFD
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group showed a larger increase in percent weight gained on several days during the protocol (days
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2,3,4,5,6,7,8,9,10,11,14,16,17,20,28,29) compared with the LFD group (p<0.05; Figure 1C, n=14/group).
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As expected, animals fed with HFD consumed more kilocalories per animal per week than LFD during
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week 1 (781.5±10.85kcal/rat/week vs 670.4±24.32kcal/rat/week), week 2 (617.4±17.88kcal/rat/week vs.
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560.3±18.76kcal/rat/week), and week 4 (649.5±12.30kcal/rat/week vs. 594.7±15.30kcal/rat/week; p<0.05;
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(Figure 1D, n=6/group). Moreover, there was no difference between the groups in feeding efficiency
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during week 1 (5.1±0.42 % vs. 6.0±0.32%), week 2 (9.5±0.56% vs. 10.3±0.42%), week 3 (13.2±0.63%
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vs. 14.4±0.99%), or week 4 (16.4±0.70% vs. 18.0±1.02%); p>0.05 (Figure 1E, n=6/group). Additionally,
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the relative epididymal fat pad percent was found to be significantly higher in the HFD group
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(1.0±0.06%) compared to LFD (0.8±0.04%; p<0.01; Figure 1F, n=14/group).
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Animals on HFD show behavioral despair in the forced swim test
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After a month on either the HFD or the LFD, the behavior of the rats was assessed in the forced swim
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test. An increase in immobility time, or a decrease in swimming or struggling in the forced swim test can
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indicate despair behavior in rodents. Our analysis found no statistically significant differences in
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struggling (Figure 2A, n=14/group, LFD, 62.11 ± 13.90 sec; HFD, 105.4 ± 19.0 sec, p>0.05) or diving
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(Figure 2B, n=14/group, LFD, 0.4 ± 0.23 sec; HFD, 0.45 ± 0.32 sec, p>0.05). No significant differences
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were found in fecal pellet count either (Figure 2C, n=14/group, LFD, 4.1± 0.64 FPC vs HFD, 4.6±.067
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FPC). However, the HFD group were more immobile (Figure 2D, n=14/group, LFD, 192.4 ± 29.48 sec;
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HFD, 317.4 ± 32.75 sec, p<0.01), spent less time swimming (Figure 2E, n=14/group, LFD, 339.2 ± 25.45
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sec; HFD, 153.3 ± 32.67 sec, p<0.001), and covered less distance, than the LFD group (Figure 2F,
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n=14/group, LFD, 42.55 ± 5.22 cm; HFD, 33.6 ± 4.65 cm, p>0.05) suggesting behavioral despair.
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Thirty days of HFD does not alter anxiety-like behavior
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The open field test measures anxiety-like behavior using a set of parameters including: time spent in
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center of the arena, distance, and velocity. Anxious animals tend to spend less time in the center. No
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differences were found between the LFD and HFD in fecal pellet counts (an indirect indicator of anxiety-
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like behavior) on day 30 in the open field (Figure 3A, n=14/group). Consistent with the lack of
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difference in the fecal pellet counts, animals from both groups spent a similar amount of time in the center
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of the arena (Figure 3B, n=14/group, LFD: 49.4 ± 8.51 secs vs HFD 42.5 ± 7.10 secs, p>0.05) and in the
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periphery (Figure 3B, n=14/group, LFD: 544.40 ± 8.81 secs vs HFD 548.00 ± 8.97 secs, p>0.05)
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suggesting that the HFD did not alter anxiety-like behavior. To check for the presence of locomotor
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differences, distance and velocity were also assessed. No differences were found in either distance
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traveled (Figure 3C, n=14/group, LFD, 5727 ± 353.50cm v HFD, 5256 ± 154.1cm, p>0.05) or velocity
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(Figure 3D, n=14/group, LFD, 8.5 ± 0.60 cm/s vs HFD, 8.3 ± 0.37 cm/s, p>0.05) suggesting that both
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groups showed similar locomotion.
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Rodents fed with HFD have greater colonic damage
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After behavioral analysis, both groups were sacrificed and their colons were evaluated. We found that
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rodents in the HFD group had significantly greater macroscopic damage in the colon (Figure 4A,
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n=11/group, LFD, 1.4 ± 0.25, HFD 1.9 ±0.22, p<0.01). Although there was a trend towards increased
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microscopic damage with more loss of crypt architecture, this did not reach significance (Figure 4B,
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LFD(n=9), 4.1 ± 0.53, HFD(n=11) 5.3 ±0.85, p>0.05). Interestingly, we observed that the average colonic
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crypt length of the HFD group was longer (Figure 4C, LFD (n=14), 203.9 ± 3.44, HFD(n=12), 220.8 ±
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5.75, p<0.05) than that found in the LFD group which suggests a possible hyperplasia and inflammation
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represented in photos from both groups (Figure 4D).
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HFD rats have increased Bacteroides and decreased expression of tight junction proteins in the
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distal colon
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After sacrifice, the fecal gut microbiome was analyzed for differences in alpha diversity, beta diversity,
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and taxonomy at phylum, family, and genus level (n=6 in LFD group and n=6 in HFD group). Alpha
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diversity showed no significant difference between the phylogenetic diversity whole tree (Figure 5A,
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n=6/group; LFD, 31.41 ± 6.04, HFD 30.81±7.15, p>0.05), Chao1 Box Plots (Figure 5B, n=6/group;
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LFD, 1263± 384.47, HFD1222.7±459.59, p>0.05), Shannon Index (Figure 5C, n=6/group; LFD, 7.80±
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0.19, HFD7.64±0.17, p>0.05), and Pielou Index (Figure 5C, n=6/group; LFD, 0.76± 0.02,
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HFD0.74±0.02, p>0.05). The ANOSIM test showed however that the diet significantly contributed to the
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variability between the groups (p<0.05, Figure 5D), thus contributing to the differences between the
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microbiomes of the HFD and LFD groups. At the phylum level, Firmicutes, Bacteroidetes and
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Proteobacteria were predominantly found with no significant differences between the two groups
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(Firmicutes-LFD, 71.98%±4.10; HFD, 74.13%±2.29,p>0.05; Bacteroidetes-LFD, 25.35%±3.86, HFD,
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23.30%±1.80, p>0.05; Proteobacteria- LFD, 0.48%±0.14; HFD, 1.96%±1.15, p>0.05(not shown); Figure
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5E; n=6 in LFD group and n=6 in HFD group). At the family level, Porphyromonadaceae LFD,
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0.80%±0.25; HFD, 0.88%±0.28, p>0.05;(not shown); n=6 in LFD group and n=6 in HFD group),
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Prevotellaceae (LFD, 1.13%±0.37; HFD, 0.38%±0.11, p>0.05;(not shown); n=6 in LFD group and n=6 in
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HFD group), Lactobacillaceae (LFD, 4.27%±2.67; HFD, 4.07%±3.32, p>0.05;Figure 5G; n=6 in LFD
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group and n=6 in HFD group), Clostridiales (LFD, 24.62%±3.20; HFD 29.12%±4.44, p>0.05;Figure 5G;
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n=6 in LFD group and n=6 in HFD group), Clostridiaceae (LFD, 1.37%±0.57; HFD 2.48%±0.72,
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p>0.05;Figure 5G; n=6 in LFD group and n=6 in HFD group), Lachnospiraceae (LFD, 7.133%±1.00;
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HFD,9.03%±0.76, p>0.05;Figure 5G; n=6 in LFD group and n=6 in HFD group), and
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Ruminococcaceae(LFD, 30.23%±4.83; HFD, 23.32%±2.02, p>0.05;Figure 5G; n=6 in LFD group and
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n=6 in HFD group) were found with no differences in composition between the groups; however,
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Bacteroidaceae were increased in HFD group compared with LFD group (Figure 5G; n=6/group, LFD,
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5.2% ± 1.01, HFD 12.6%±1.67, p<0.01). Interestingly, we observed that the average whereas S24-7 were
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decreased in the HFD compared to LFD (n=6/group, LFD, 4.27% ± 2.66, HFD 4.1% ± 3.32, p<0.05) and
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Streptococcacea (LFD, 1.20%±0.43; HFD 0.08%±0.047, p<0.05;not shown; n=6 in LFD group and n=6
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in HFD group) in a low percent of abundance. At the genus level, for Lactobacillus (LFD, 4.27%±2.66;
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HFD, 4.072%±3.32, p>0.05;Figure 5H; n=6 in LFD group and n=6 in HFD group), genus of
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Clostridiales (LFD, 424.62%±3.21; HFD, 291.12%±4.43, p>0.05;Figure 5H; n=6 in LFD group and n=6
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in HFD group), genus of Clostridiaceae (LFD, 0.97%±0.45; HFD, 2.03%±0.62, p>0.05;Figure 5H; n=6
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in LFD group and n=6 in HFD group), genus of Ruminococcaceae (LFD, 9.73%±1.74; HFD,
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9.11%±0.87, p>0.05;Figure 5H; n=6 in LFD group and n=6 in HFD group); Oscillospira(LFD,
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012.65%±3.11; HFD, 10.12%±1.04, p>0.05;Figure 5H; n=6 in LFD group and n=6 in HFD group), and
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Ruminococcus(LFD, 7.8%±1.61; HFD, 4.05%±1.33, p>0.05;Figure 5H; n=6 in LFD group and n=6 in
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HFD group) no differences were found in bacteria composition between the diets (Figure 5H; n=6 in
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LFD group and n=6 in HFD group; p>0.5) nor in the F/B Ratio between the groups (Figure 5F
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n=6/group, LFD, 3.6 ± 1.11, 3.3 ± 0.34, p>0.05). However, the HFD group showed a significant increase
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in percent of Bacteroides (Figure 5H, n=6/group, LFD, 5.2% ± 1.05, HFD 12.63% ± 1.67, p<0.01) and in
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Lachnospiraceae (LFD, 3.65%±0.53; HFD, 5.57%±0.61, p<0.05;Figure 5H; n=6 in LFD group and n=6
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in HFD group). Interestingly, we observed that the average S24-7 bacteria decreases in HFD compared
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with in LFD group (Figure 5H n=6/group, LFD, 17.2% ± 3.46, HFD 8.75% ± 1.38, p<0.05). LPS levels
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in the blood were higher in HFD compared to LFD group (Figure 5I, n=10 LFD 1.1pg/mL ± 3.46; n=11,
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HFD 2.5pg/mL ± 0.58, p<0.05). We also examined the expression of the tight junction proteins claudin-5
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and occludin in colonic tissue. We found reduced expression of claudin-5 (Figure 5J, n=11 LFD 1.0 ± 0;
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n=13, HFD.3592 ± 0.08 p<0.0001) and occludin (Figure 5J, n=9 LFD,1.0 ± 0; n=13, HFD 0.4 ± 0.07
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p<0.0001) in the colon of animals in the HFD group (Figure 5J), which may suggest a leaky gut. To
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determine if the changes in microbiome were related to the reduced expression of tight junction genes,
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Spearman correlations were performed between Bacteroides and S24-7 abundance and tight junction
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expression. Bacteroides abundance was negatively correlated with claudin-5 expression (-0.87, p<0.001,
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Figure 5K; n=5-6 per group), while S24-7 abundance positively correlated with claudin-5 expression
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(0.71, p<0.05).
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HFD rats exhibit alterations in astrocyte morphology with increased microglia percent area &
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intensity in the CA1, and decreased Phospho-mTOR in the Cingulate Cortex
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Brain sections were removed to assess the alterations of the astrocytes and the microglia in the CA1. Glial
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Fibrillary Acid Protein (GFAP), primary astrocytic projection length, showed no differences between the
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groups (Figure 6A, LFD (n=5), 11.5m ± 1.88, HFD (n=5), 9.2m ±1.32, p>0.05), however, differences
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in primary astrocytic projection number between the groups was increased (LFD (n=5), 3.9 ± 0.21, HFD
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(n=5), 5.9 ±0.24, p<0.01). HFD and LFD groups showed no difference in secondary astrocytic projections
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length (LFD (n=5), 6.9m ± 0.61, HFD (n=5), 6.72m ± 0.69, p>0.05), but HFD showed higher
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secondary astrocytic projections number compared with the LFD group (LFD (n=5), 3.49 ± 0.29, HFD
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(n=5), 8.9 ± 0.65, p<0.01). HFD group exhibits higher tertiary astrocytic projections length (LFD (n=5),
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0.23m ± 0.17, HFD (n=5), 4.88m ±1.15, p<0.01) and tertiary astrocytic projections number (LFD
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(n=5), 0.11 ± 0.06, HFD (n=5), 5.072 ±1.15, p<0.01). In addition, the microglia marker (IBA-1) (Figure
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6B) showed higher percent area (LFD (n=6), 0.86 ± 0.16, HFD (n=7), 2.10 ± 0.16, p<0.01) in the HFD
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rats compared with the control, on the contrary correlations between IBA-1 vs. immobility (p>0.05,
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n=13), and IBA-1 vs LPS concentration in the blood (p>0.05, n=13) did not reach significance. Finally,
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(Figure 6C) HFD showed decreased cingulum cortex area stained against Phospho-mTOR (LFD (n=6),
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98501μm2 ± 5936, HFD(n=5), 73742 μm2 ±7523, p<0.05), Phospho-mTOR percent area (LFD (n=6),
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31.2% ± 5.42, HFD(n=5), 14.76%±4.12, p=0.05), and Phospho-mTOR intensity (LFD (n=6), 72.8 ±
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12.21, HFD (n=5), 32.0% ± 7.98, p<0.05) compared with the LFD group. Scale bars show 100 m for
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GFAP, IBA-1, and Phospho-mTOR representative photos.
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Leptin levels were significantly higher in rodents with HFD
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Markers of inflammation such as interleukin-1 beta (IL-1β), tumor necrosis alpha (TNF-α), monocyte
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chemoattractant protein-1 (MCP-1 or CCl-2), and interleukin 6 (IL-6), and markers related to obesity such
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as leptin and insulin were measured systemically in the blood. As shown in Table 2, no differences were
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found in inflammatory cytokines; however, there were significantly higher levels of leptin in the HFD
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group compared with the LFD group. Additionally, HFD animals had significantly higher LPS levels
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(p<0.05; Figure 5I).
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DISCUSSION
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In this study, we used an animal model to better understand the early changes between the gut and the
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peripheral system even before obesity is apparent. Our results show that Sprague Dawley rats fed an HFD
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for only one month demonstrated behavioral despair even without excessive weight gain. Further,
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consumption of the HFD for this short time period altered beta diversity and bacterial abundance in the
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lower taxonomic levels, increasing Bacteroides abundance, which correlated with decreased expression of
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tight junction proteins and LPS in the blood suggesting a leaky gut. Even more, the metabolites present in
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the blood such as leptin, free fatty acid, and LPS produce alterations in the brain that may be associated to
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behavior despair.
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The gut microflora helps to maintain the physiology and histology of the colon (Belkaid and Hand.,
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2014), and can be affected by many factors including dietary components (David et al., 2014; Wu et al.,
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1998). In the present study we found significant differences in the beta diversity of the fecal microflora
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between an HFD and LFD even without obesity, however we did not see differences in alpha diversity. In
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addition, we observed the taxonomy at family and genus level and found that the percentage of
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Bacteroide and Bacteroides was significantly higher in the animals fed with HFD, which echoes other
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reports of HFD impact (Wu et al., 1998; Schnorr et al., 2014). In addition, the S24-7 family was
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significantly lower in rats fed with HFD. This bacterium is not well characterized (Salzman et al., 2002;
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Ormerod et al., 2016), but appears to be related to gut composition in rodents fed with low fat diet
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undergoing exercise (Evans et al., 2014) and was observed during remission in a colitis mouse model
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(Rooks et al., 2014). Bacteroides is an obligate anaerobic bacterium that provides beneficial properties to
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the gut including survival under different environments and can digest plant and host polysaccharides
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(Almeida-Suhett et al., 2017; Belkaid and Hand, 2014; Gecici et al., 2005; Methé et al., 2012). Different
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species of Bacteroides have been studied for their polysaccharide utilization loci (PUL) since the bacteria
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have the capacity to recognize, translocate, hydrolyze, and regulate polysaccharide genes (Methé et al.,
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2012; Hooper et al., 2001; Dutheil et al., 2016; Hsiao et al., 2013). However, in diets with low fiber, such
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as a high fat diet, Bacteroides can digest the glycans present in the gut (Sonnenburg et al., 2005). This can
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be detrimental since O-glycans are a major component of mucin 2, secreted by goblet cells, which
275
normally comprise a mucus barrier separating the gut microflora from the epithelium of the host. A
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decreased mucus barrier is associated with epithelial cell damage and diets lower in fiber (Johansson et
277
al., 2008). Such diets have been associated with inflammatory bowel diseases (IBD) or cancer (Cameron
278
and Sperandio, 2015), while those high in fiber may reduce the risk of developing IBD (Owczarek et al.,
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2016). In the present study the HFD contained no starch and this perhaps might be associated with a
280
decreased layer of mucus, contributing to the inflammation observed although this was not specifically
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measured.
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We found that a short-term HFD significantly increased macroscopic damage in the colon and altered
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crypt length, suggesting presence of inflammation (Erben et al., 2014). Indeed, the expression of the tight
285
junction proteins, Claudin-5 and Occludin, were significantly decreased in the colon. Such a decreased
286
expression has previously been associated with a leaky gut, and linked to an HFD in humans and rodent
287
models (Barmeyer et al., 2017; Alhasson et al., 2017; Camilleri et al., 2012; Jakobsson et al., 2015; Rose
288
et al., 2012; Sánchez-Villegas et al., 2012; Rahner et al., 2001). Interestingly, the increased presence of
289
Bacteroides species, as found in our study, has also been associated with changes in intestinal
290
permeability with an HFD (Cani et al., 2008; Hooper et al., 2001; David et al., 2014). We observed a
291
positive correlation between Claudin-5 and S24-7, whereas a negative correlation was found with
292
Bacteroides. In line with our results, various colonic conditions such as acute colitis and Crohn’s disease
293
have also found decreased expression of claudin-5 associated with increased Bacteroides abundance
294
(Mennigen et al., 2009; Rosen et al., 2011). In general, Bacteroides has been shown to negatively impact
295
patients with ulcerative colitis and influence symptoms found in patients with inflammatory bowel
296
diseases (Kuwahara et al., 2004; Setoyama et al., 2003; Matsuda et al., 2000; Hansen et al., 2012;
297
Hudcovic et al., 2009). Bacteroides can produce a toxin called fragilysin, which may disrupt the epithelial
298
paracellular barrier (Obiso et al., 1997) through proteolytic degradation of the extracellular domain on E-
299
cadherin on intestinal cells, resulting in junction disassembly (Wu et al., 2011; Wu et al., 1998). The
300
lower expression of tight junctions we observed might therefore contribute to translocation of bacterial
301
products, such as LPS, and increased gut permeability. As gut permeability increases, LPS can enter
302
through the tight junctions and then be transported inside chylomicrons to reach the circulation to produce
303
low-grade inflammation. In humans an HFD was shown to increase this transport (Ghoshal et al., 2009).
304
LPS can then activate toll like receptors, specifically toll like receptor 4, which are present in the colonic
305
epithelium and immune cells (Abreu et al., 2010, Yiu et al., 2015, Medzhitov et al., 2007) and
306
consequently stimulate the NFKB pathway increasing inflammatory cytokines (Cook et al., 2004; Billack,
307
2006). Interestingly, Bacteriodes also has the ability to change the polysaccharide surface mediated by an
308
invertase gene called mpi, which has the capacity of immune evasion (Coyne et al., 2003). In addition,
309
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LPS also increases white adipose tissue and inflammatory markers affecting the brain behavior (André et
310
al., 2014; Zhao et al., 2019).
311
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We observed that although our HFD group showed no significant increase in absolute weight during the
313
intervention, the animals had increased epididymal fat pads, and increased leptin in the blood suggesting
314
metabolic changes. A significant increase in percent weight gain was observed compared to those animals
315
fed LFD but the difference did not reach the commonly accepted definition of obesity (Hariri and
316
Thibault, 2020). The presence of increased epididymal fat pads following a short-term (2 week) HFD in
317
rats has previously been observed (Li et al., 2002), and it is known that high levels of LPS in the blood
318
may produce blood brain barrier (BBB) permeability resulting in increased leptin and inflammatory
319
cytokines, such as interleukin 1β (IL-1β) and interleukin 6 (IL-6) (Lago et al., 2007; Banks et al., 2015;
320
Nishioku et al., 2009). This BBB permeability may permit entry of products producing activation of toll
321
like receptors in the brain in different cell types such as microglia (Liu et al., 2014; Chakravarty and
322
Herkenham, 2005), causing brain inflammation that then leads to changes in behavior. It has been shown
323
that LPS, IL-1β, and IL-6 injected peripherally can produce depressive-like behavior (Anforth et al.,
324
1998; Walker et al., 2013; Wang et al., 2011), and free fatty acids (FFA) can activate the microglia in
325
vitro in a TLR-4 dependent manner (Wang et al., 2012; Lee et al., 2011; Lee et al., 2001). Interestingly,
326
decreased adiposity and inflammation have been shown in TLR-4 knockout mice (Saberi et al., 2009;
327
Tsumuko et al., 2007) and behavioral despair has been observed when TLR-4 is inhibited or knocked out
328
(Zhang et al., 2020).
329
330
In this study, we used an HFD which contained lard as the major source of fat. This diet had roughly
331
equivalent levels of saturated fat (SFA;32%), monounsaturated fat (MUFA;36%), and polyunsaturated fat
332
(PUFA;32%). Several studies show the importance of MUFA and PUFA on the brain and behavior
333
(Levant, 2013; Hryhorczuk et al., 2016) where an imbalance (higher ratio of omega-6: omega-3) is
334
associated with depressive-like behavior (du Bois et al., 2006; Tang et al., 2016). Our diet is high in SFA,
335
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specifically palmitic acid, that has been associated with immobility in the forced swim test (Sharma and
336
Fulton, 2013; Kaczmarczyk et al., 2013). Further, in humans, an association has been found between
337
systemic palmitic acid levels and symptoms of depression (Tsuboi et al., 2013). Our data is thus
338
comparable with other studies showing that consumption of a diet high in saturated fat increases FFA
339
resulting in adiposity even over a short time period (Lee et al., 2011; Lee et al., 2001; Horton et al., 1995;
340
Phillips et al., 2012; Nguyen et al., 2007). In our short timeframe, the HFD group had significantly
341
increased immobility with decreased swimming time and less distance traveled in the forced swim test,
342
supporting the hypothesis that an HFD can lead to behavioral despair. These data correlate with other
343
studies, which found depressive-like behavior in rodents consuming an HFD over a longer time frame of
344
10 weeks (Abilgaard et al., 2011; Sharma and Fulton, 2013). In our study we found no anxiety-like
345
behavior in the HFD group as measured by the open field test. These findings corroborate those found
346
previously in rodents fed with HFD for 6 weeks, indicating that the depressive-like syndrome is not due
347
to sickness behavior nor anxiety (Gainey et al., 2016). On the contrary, when the rats were fed with HFD
348
for a longer time period, more than 15-17 weeks (Dutheil et al., 2016), it is notable that these authors did
349
see an increase of anxiety-like behavior in the open field test, again pointing to temporal effects of the
350
diet on behavior. It is possible then that the data discrepancies can be due to differences in rat strains, diet
351
and performed tests. However, it is important to recall the importance of neuroinflammation and immune
352
cells in the brain.
353
354
Immune cells can be found in the brain especially in the hippocampus. In our research, we demonstrated
355
that HFD caused a reactive state in astrocytes by increasing the number of primary, secondary, and
356
tertiary projections per cell, suggesting hyperactivity and increased microglia levels in the hippocampus,
357
CA-1. We also found decreased phospho-mTOR in the cingulate cortex. The hippocampus has been
358
studied for its role in memory formation and depressive like syndrome, and under normal conditions
359
sends information to the subiculum and to the entorhinal cortex (van Groen et al. 2014). However, under
360
neuro inflammation conditions, the mTOR signaling is inhibited (Dutheil et al., 2016, Huang et al., 2001,
361
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Li et al., 2010, Sengupta et al., 2014) resulting in a decrease of the derived neurotropic factor (BDNF)
362
levels affecting synaptogenesis. In addition, short- and long-term HFD exposure in animal models has
363
been associated with increased dysregulation of astrocytes and microglia (Soforniew & Vinters, 2010;
364
Calvo-Ochoa et al., 2014; Rorato et al., 2022). The TLR4 receptor in the brain is known to express pro-
365
inflammatory cytokines (Hanke el at, 2011) and inflammation can decrease phospho-mTOR, which is
366
important for the synthesis of BDNF (Dutheil et al., 2016). In response to LPS microglial cell staining
367
showed increased percent area for Iba-1 positive cells, denoting the possibility of a neuroinflammatory
368
process in the CA-1, which is a key structure related to an enhanced response to antidepressant treatments
369
(Rolls et al., 2018; Taylor et al., 2014), and further resolution of depressive symptoms. As well, mTOR
370
signaling has been confirmed as an important modulator of protein synthesis including synaptic protein
371
synthesis, which is deregulated in behaviors such as major depressive disorder or depression (Ignácio et
372
al., 2016; Abelaria et al., 2014). We demonstrate here that short-term HFD exposure reduces the cingulum
373
cortex area stained against Phospho-mTOR, which agrees with what has already been published, where
374
exposure to HFD reduces mTOR staining and mTOR mRNA expression in brain tissue (Oh et al., 2013;
375
Dasuri et al., 2015; Arnold et al., 2014). In addition, we found a decrease in cingulum area which may be
376
associated to human studies where depressed patients have lower fractional anisotropy (Won E et al.,
377
2016). Interesting, lesions in the cingulum are associated to depression (Taylor et al., 2014). In sum, these
378
data suggest that the presence of immune cells such as astrocytes and microglia may affect the
379
hippocampal connectivity by affecting the BDNF expression inhibiting mTOR signaling.
380
Based on our findings and the literature, we accept our hypothesis but acknowledge limitations (see the
381
limitations section) and propose a conceptual model for the impact of a short-term high-fat diet on
382
behavior taking into consideration our findings and the literature (Figure 7): consumption of a high fat
383
diet over even a short period of time will be associated with increased abundance of Bacteroides and
384
increased circulating FFA in the blood (van Dijk et al., 2009; Rosqvist et al., 2014). In the colon, this low
385
fiber diet promotes digestion of the mucin in the host (Benjdia et al., 2011; Martens et al., 2009; Turroni
386
et al., 2010) resulting in decreased expression of tight junction proteins such as occludin and claudin-5
387
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and entrance of bacterial products such as LPS into the circulation. Circulating LPS and FFA may
388
activate TLR-4 pathways in adipose tissue resulting in increased leptin levels. In addition, circulating LPS
389
and FFA may activate immune cells in the brain such as microglia (Krinos et al., 2001; Chatzidaki-livanis
390
et al., 2010). This results in increased brain inflammation and promotes behavioral despair (Millett et al.,
391
2019; O’Connor et al., 2009).
392
393
Limitations of the study
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Our study has several limitations that may restrict some of the conclusions that we are able to draw since
395
some of the data is correlative. We only analyzed the microbiome on day 30 at sacrifice, whereas
396
collection of fecal pellets for analysis at day 0 and Day 15 would have helped us to better understand the
397
microbiome shifts during the intervention. Only one behavioral test (forced swim) was used to measure
398
‘despair’ and the results of this test could be interpreted not only as the animals giving up trying to escape
399
from the situation, but also as a failure to cope. Ideally, in follow up experiments to define the behavioral
400
changes as being equivalent to a depressive-like behavior, additional tests such as social defeat (social
401
aversion), the sucrose preference test (anhedonia) and nest building (apathy) could be used (Planchez et
402
al., 2019). Finally, we did not assess the expression of the possible responsible receptors, such as TLR4,
403
in the colon, feces or the brain, nor performed inhibition of TLR4 and inflammatory cell in the colon.
404
Follow up investigations might directly measure gut permeability, TLR4, mp1 or endotoxin to identify
405
which parameter LPS uses to enter to the blood stream, and examine in more depth the role of the S24-7
406
genus. In future studies such further investigations may shed additional light on the various mechanistic
407
pathways that may be involved in generating the behavioral changes.
408
409
ACKNOWLEDGMENTS
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The authors acknowledge Maria Colon, Anixa Hernandez, Lisette Maldonado and Dr. Siomara
411
Hernández for technical assistance. They also recognize the involvement of undergraduate and graduate
412
students Suheil Cruz, Roberto Torres-Aguiar, Evelyn Cora, Madeline Nazario, and Sugeily Ramos. The
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authors would like to thank Pablo Lopez for support in the bead array, microbiome procedures, and
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BioProject PRJNA870914 submission. Drs. James Porter, Annelyn Torres-Reveron, and Dinah Ramos for
415
advice with neuro behavior analysis. Special thanks to Dr. Julyann Perez Mayoral for additional editing
416
and input. The content is solely the responsibility of the authors and does not necessarily represent the
417
official views of the National Institutes of Health.
418
419
AUTHOR CONTRIBUTIONS
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Gladys Chompre: Conceived and designed the experiments; Performed the experiments; Analyzed and
421
interpreted the data; Contributed reagents, materials; analysis tools or data; Wrote the paper
422
Lubriel Sambolin: Performed the experiments; Analyzed and interpreted the data, analysis tools or data;
423
Wrote the paper
424
Myrella L Cruz: Performed the experiments; Analyzed and interpreted the data, analysis tools or data;
425
Wrote the paper
426
Rafael Sanchez: Performed the experiments; Analyzed and interpreted the data analysis tools or data;
427
Contributed reagents, materials, analysis tools or data; Wrote the paper
428
Yarelis Rodriguez: Performed the experiments; Analyzed and interpreted the data, analysis tools or data;
429
Wrote the paper
430
Ronald E Rodriguez-Santiago: Analyzed and interpreted the data; Contributed reagents, materials,
431
analysis tools or data; Wrote the paper
432
Yasuhiro Yamamura: Conceived and designed the experiments; Analyzed and interpreted the data;
433
Contributed reagents, materials, analysis tools or data; Wrote the paper
434
Caroline B Appleyard: Conceived and designed the experiments; Analyzed and interpreted the data;
435
Contributed reagents, materials, analysis tools or data; Wrote the paper
436
437
DECLARATION OF INTERESTS
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Finally, the authors declare that this work was not carried out in the presence of any personal,
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professional or financial relationships that could be construed as a conflict of interest.
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Component
Ingredient
Low-Fat diet
(D12450J)
(g/kg of diet)a
High-Fat diet
(D12492)
(g/kg of diet)a
Protein
Casein, Lactic, 30 Mesh
189.50 g
258.25 g
Cystine, L
2.84 g
3.88 g
Starch, Corn
479.79 g
0 g
Carbohydrate
Lodex
118.48 g
161.53 g
Sucrose, Fine Granulated
69.00 g
94.08g
Solka Floc, FCC200
47.39 g
64.61 g
Fat
Soybean Oil, USP
23.70 g
32.31 g
Lard
18.96g
316.60 g
Mineral Mix
S10026B
47.39 g
64.61 g
Vitamin
Choline Bitartrate
1.90 g
2.58 g
V10001C (Vitamin mix)
0.95g
1.29 g
Dye
Dye, Yellow FD&C #5,
Alum. Lake 35-42%
0.04 g
0 g
Dye, Blue FD&C #1,
Alum. 35-42%
0.01 g
0.06 g
Total
1000 g
1000g
Caloric Information
Protein
20 % Kcal
20 % Kcal
Fat
10 % Kcal
60 % Kcal
Carbohydrate
70 % Kcal
20 % Kcal
Energy Density
3.82 Kcal/g
5.21 Kcal/g
932
Table 1. Formulation of the Low-Fat Diet and High-Fat Diet given to male Sprague-Dawley rats for
933
30 daysa Ingredients calculated to 1000g of diet based on the Information from Research Diets, Inc.
934
(https://www.researchdiets.com)
935
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936
937
938
939
940
941
Blood Marker
LFD (pg/mL)
HFD (pg/mL)
p value
IL-1β
0.91±0.35
0.57±0.01
>0.05
IL-6
Below detection
Below Detection
>0.05
TNF-α
0.15±0.09
0.09±0.01
>0.05
CCL-2
76.59±10.49
86.77±11.94
>0.05
Insulin
1998±448.10
2025±784.00
>0.05
Leptin
1408±193.00
2078±174.00
<0.05
942
Table 2: Protein Array of inflammatory cytokines and insulin in the serum. Two-month-old male
943
Sprague Dawley on LFD or HFD show no significant differences in inflammatory cytokine levels (IL-1β,
944
IL-6, TNFα, CCL2, Insulin). Higher levels of leptin were found in the rats fed with HFD compared with
945
those on LFD. Data represented as mean ± standard error of the mean. N= 6/group. Statistics used student
946
t-test. *p<0.05.
947
948
949
950
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951
952
Figure 1: Thirty days of HFD feeding results in higher percent weight gain and epididymal fat
953
tissue than LFD. Before switching to either the HFD or the LFD, the absolute weight (A) of the LFD
954
group and the HFD group were similar (day 1). No significant differences were observed during the
955
dietary intervention, or at time of sacrifice (day 30) between animals on the LFD and HFD (B). However,
956
(C) animals in the HFD group showed a larger increase in percent weight gained at several time points
957
during the intervention. (D) Animals fed with HFD consumed more kilocalories than LFD during week 1,
958
week 2 and week 4 (n=6/group). (E) Both groups showed no significant differences in feeding efficiency
959
percent during the four weeks (n=6/group). (F) Additionally, the epididymal fat pads were found to be
960
significantly heavier in the HFD group compared to LFD. Data represented as mean ± standard error of
961
the mean; n=14/group except where indicated otherwise. *p<0.05, **p<0.01, ***p<0.001.
962
963
964
965
LFD HFD LFD HFD
0
100
200
300
400
500
600
700
800
Weight(grams)
0 1 2 3 4
400
600
800
1000
Week
Food intake (kcal/ rat / week)
** **
0 5 10 15 20 25 30
300
350
400
450
500
Days
Absolute Weight (grams)
0 1 2 3 4
0
5
10
15
20
25
Week
Feeding Efficiency Percent
( % of gram/kcalories)
0 5 10 15 20 25 30
90
100
110
120
130
140
Days
Percent Weight Gain(%)
***
***
**
******
***
***
***
******
**
LFD HFD
0
1
2
3
4
Relative Fat Pad weight
(% body weight)
**
A B C
D E F
Day0 Day30
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966
Figure 2: Animals on HFD show behavioral despair in the forced swim test. Two-month-old male
967
Sprague Dawley rats fed with LFD or HFD showed no significant differences in (A) time spent
968
struggling, or (B) time spent diving during the Forced Swim Test, and no significant differences in (C)
969
fecal pellet output. However, rats receiving the HFD spent (D) more time immobile, (E) less time
970
swimming, and (F) covered less distance. Data represented as mean ± standard error of the mean. n=14 in
971
LFD group and n=14 in HFD group. *p<0.05, **p<0.01.
972
973
974
ABC
DEF
LFD HFD
0
50
100
150
200
Time Struggling(sec)
LFD HFD
0
1
2
3
4
5
Time Diving (sec)
LFD HFD
0
200
400
600
Time immobile(sec)
**
LFD HFD
0
200
400
600
Time Swimming (sec)
***
LFD HFD
0
20
40
60
80
Distance (cm)
LFD HFD
0
2
4
6
8
10
Amount of Fecal Pellet
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975
976
Figure 3: Thirty days of HFD does not alter anxiety-like behavior. After 30 days on HFD or LFD no
977
differences were observed in anxiety-like behavior or motor capabilities in the open field test as assessed
978
by (A) fecal pellet count, (B) time spent in the center and periphery of the area, (C) distance travelled, and
979
(D) velocity. Data represented as mean ± standard error of the mean; n=14/group.
980
981
982
983
984
985
986
987
LFD HFD
0
1
2
3
4
5
Amount of Fecal Pellet
LFD HFD
0
2000
4000
6000
8000
Distance (cm)
LFD HFD LFD HFD
0
200
400
600
800
Spending Time (sec)
LFD HFD
0
5
10
Velocity (cm/sec)
A B
C D
Center Periphery
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988
Figure 4: Rodents fed with HFD have greater colonic damage. Distal colon from HFD animals had
989
(A) increased macroscopic damage (n=11/group), (B) a trend towards increased microscopic damage
990
(LFD, n=9; HFD, n=11), and (C) longer crypt length (LFD, n=14; HFD, n=12). (D) Representative colon
991
tissue sections from animals fed with LFD or HFD. Data are shown as mean ± standard error of the mean.
992
*p<0.05, **p<0.01. Scale bar = 100μm
993
994
995
996
997
998
999
LFD HFD
0
2
4
6
8
10
Macroscopic Score
*
A B C
LFD HFD
100
120
140
160
180
200
220
240
260
280
300
Crypt Length (
m
m)
*
D
LFD HFD
0
2
4
6
8
10
Microscopic Score
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1000
LFD HFD
0.0
0.5
1.0
1.5
2.0
Claudin-5 Fold Change
****
LFD HFD
0.0
0.5
1.0
1.5
2.0
Occludin Fold Change
****
PD Whole Tree
Sequences per Sample
Rarefraction Measure: PD Whole Tree
A B C
LFD
HFD
LFD HFD
0
2
4
6
8
10
LPS Concentration
(pg/mL)
*
PC1(14.28% )
PC3(12.04% )
PC2(12.41% )
Low Fat Diet High Fat Diet
LFDHFD
D E F
0
2
4
6
8
10
Firmicutes/ Bacteriodetes ratio
LFD HFD
G
0 5 10 15 20
0
2
4
6
Bacteroides Percent (%)
mRNA Claudin-5 Levels
012345
0
2
4
6
SF24-7 family Percent (%)
mRNA Claudin-5 Levels
*
***
LFD HFD
0.4
0.6
0.8
1.0
Pielou Index
LFD HFD
6
7
8
9
10
Shannon Index
I J K
0
20
40
60
80
100
Abundance
(%)
** *
Bacteroidaceae S24-7 Lactobacillaceae o_Clostridiales_f Clostridiaceae Lachnospiraceae Ruminococcaceae
Phylum Family Genus
LFDHFDLFDHFDLFDHFD
Phylum Family Genus
LFDHFDLFDHFDLFDHFD
0
20
40
60
80
100
Abundance(%)
Firmicutes Bacteroides
Phylum Family Genus
LFDHFDLFDHFDLFDHFD
H
0
20
40
60
80
100
Abundance
(%)
Bacteroides
f_S24-7;g Clostridiales;g clostridiaceae;g lachnospiraceae;g
Ruminococcaceae;g
Oscillospira Ruminococcus Lactobacillus
**
*
**
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Figure 5: HFD rats have increased Bacteroides and decreased expression of tight junction proteins
1001
in the distal colon. Alpha diversity shows no difference between HFD and LFD group (A) in PD Whole
1002
Tree, (B) Chao1 box plot, (C) Shannon index & Pielou index (p>0.05;n=6/group). (D) However,
1003
differences in beta diversity were found between the LFD and HFD animals (p<0.05; n=6/group). (G&
1004
H) Bacterial abundance was significantly different at both family and genus level, however (E&F)
1005
Firmicutes/Bacteroidetes abundance and ratio is similar in both groups (n=6/group). (G & H) Bacteroides
1006
was significantly increased in HFD whereas S24-7 family and genus levels were significantly decreased.
1007
(I) LPS levels in the blood were higher in the HFD group compared with the LFD group (LFD, n=10;
1008
HFD, n=11). (J) Analysis of tight junction proteins revealed lower mRNA expression of claudin-5 (LFD,
1009
n=11; HFD, n=13) and occludin in the HFD compared with LFD (LFD, n=10; HFD, n=11). (K)
1010
Significant correlations were found between % Bacteroides vs Claudin-5 mRNA, and % S24-7 vs
1011
Claudin-5 mRNA. Data are represented as mean ± standard error of the mean (n=11/group). P values
1012
*p<0.05, **p<0.01, and ***p<0.001.
1013
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1014
Figure 6: HFD rats exhibit higher astrocytic branching in projections, higher percent area of
1015
microglia and lower expression of Phospho-mTOR in the brain. (A) HFD group show increased
1016
hippocampal astrocytic projection length in the secondary and the tertiary projections respectively.
1017
However, HFD show a higher number of projections from the primary to the tertiary projections
1018
compared with the LFD n=5/group. (B) Hippocampal IBA-1 staining, show higher increase in percent
1019
area and intensity in the HFD group (n=7) compared with the LFD group (n=6). On the contrary,
1020
association of the immobile parameter and IBA-1 percent of area and LPS concentration vs Phospho-
1021
mTOR show a trend but did not reach significance. (C) The area and intensity of phospho-mTOR levels
1022
were decreased in the HFD (n=5) group compared with the LFD group (n=6). In addition, the area of the
1023
cingulum in the dorsal hippocampus showed a significant decrease in HFD group compared with the
1024
control. Data are represented as mean ± standard error of the mean. *p<0.05, **p<0.01, and ***p<0.001.
1025
LFD HFD
0
50
100
150
200
Phospho mTOR Intensity
(AU)
*
LFD HFD
0
20
40
60
80
100
Phospho mTOR Levels
(% Area)
p=0.05
LFD HFD
50000
100000
150000
200000
Cingulum Area(
m
m2)
*
Phospho-mTOR
Microglia
Astrocytes
LFD HFD
0
5
10
15
20
Average Projection
Number per cell
**
LFD HFD
0
5
10
15
20
Average Length
per cell (
m
m)
**
Tertiary Projections
LFD HFD
0
5
10
15
20
Average Projection
Number per cell
**
LFD HFD
0
5
10
15
20
Average Length
per cell (
m
m)
Secondary Projections Primary Projections
LFD HFD
0
5
10
15
20
Average Projection
Number per cell
**
LFD HFD
0
5
10
15
20
Average Length
per cell (
m
m)
0
1
2
3
4
5
IBA-1 (Percent of area %)
***
LFD HFD
HighFatDiet
HighFatDiet
LowFatDietLowFatDiet
A B C
0 2 4 6
0
1
2
3
4
5
LPS Levels(pg/mL)
IBA-1 (Percent of area %)
0.2074
0.4965
p=
r=
LowFatDiet
HighFatDiet
HighFatDiet
HighFatDiet HighFatDiet
LowFatDietLowFatDiet
0200 400 600
0
1
2
3
4
5
Behavioral Immobility parameter
IBA-1 (Percent of area %)
0.3838
0.1954
p=
r=
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1026
Figure 7: HFD conceptual model. (1a) An HFD (unsaturated fat) produces an increase in Bacteroides
1027
abundance and also the gut increasing Free Fatty Acids (FFA) in the blood absorbs (1b). (2) Bacteroides
1028
digest the mucins in the host when low levels of starch are present (as found in the HFD). (3) Toxins from
1029
the Bacteroides decrease tight junction mRNA levels promoting the entry of LPS (represented by black
1030
dots) to the peripheral system. (4) Circulating LPS and FFA increases adiposity and leptin levels, and
1031
possibly activates microglia in a TLR4 dependent manner. (5) TLR4 pathway produces inflammation in
1032
the brain by cytokines. (6) Brain inflammation produces behavioral despair.
1033
1034
1035
1036
1037
1038
HighFatDiet
1a
2
3
4
TightJunc ons
Blood(circula on)
FFA
LPS
Adiposity
Lep n
1b
FFA
FFA
FFA
FFA
FFA FFA
FFA
FFA FFA
FFA
Adipocytes
Inflamma on 5
DespairBehavior 6
Microglia
ac va on
EpitheliaLayer
MucosalLayer
Bacteriodes
Gutmicrobiome
FFA FFA
FFA
FFA
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STAR METHODS
1039
KEY RESOURCES TABLE
1040
REAGENT or
RESOURCE
SOURCE
IDENTIFIER
Diet
Low-fat diet
Research Diet
Cat. No. D12450J
High-fat diet
Research Diet
Cat. No. D12492
Experimental model
Sprague Dawley rats
Animal House Facilities
N/A
Behavioral equipment
Open Field Test
BRAIN Core Facilities
N/A
Forced Swim Test
BRAIN Core Facilities
N/A
qPCR primers
Beta actin
Qiagen Co.
PPR06570C
Claudin-5
Qiagen Co.
PPR46476A
Occludin
Qiagen Co.
PPR48441A
Commercial Assays
AllPrep
DNA/RNA/Protein
Minikit
Qiagen Co.
Cat. No. 80004
iScript cDNA synthesis
kit
Biorad Co.
Cat. No. 1708891
iQ SYBR Green
Supermix
Biorad Co.
Cat. No. 1708882
QIAamp DNA stool
Minikit
Qiagen Co.
Cat. No. 51504
Kinetic QCL
Chromogenic Assay
Millipore Co.
Cat. No. NC9597521
MILLIPLEX MAP
Human Bone Magnetic
Bead Panel
Millipore Co.
Cat. No. HBNMAG-51K
Antibodies
GFAP
BioLegend
644702
IBA-1
FUJIFILM Wako Pure
Chemical Corporation
019-19741
Phospho-mTOR
Cell Signaling
c2976
Softwares
Image J
Image J
https://imagej.nih.gov/ij/download.html
ANY-maze software
Stoelting Co.
https://www.any-maze.com/
Epidat 3.1
Epidat
https://www.sergas.es/Saude-publica/Epidat-3-1-
descargar-Epidat-3-1-(espanol)
GraphPad 7.0
GraphPad Prism
https://www.graphpad.com/
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Equipment
Nanodrop 2000
Thermoforma Co.
https://www.fishersci.es/shop/products/nanodrop-
2000-2000c-spectrophotometers/p-4532022
Qubit 3.0
Life Sciences
https://www.fishersci.es/shop/products/qubit-3-0-
fluorometer/15387293
Qiime 1.9
QIIME development
team
http://qiime.org/
1041
EXPERIMENTAL MODEL AND SUBJECT DETAILS
1042
Two-month-old male Sprague Dawley rats were purchased from the Ponce Health Sciences University
1043
Animal House having a diet of Prolab® Rat/Mouse/Hamster 3000. This age represents young adults
1044
equivalent to approximately eighteen human years which were subjected to a diet intervation of 30 days
1045
which represents around 2 human years (Senguta et al.2012 &2013, Quinn et al.,2005). For the dietary
1046
intervention they were fed either a Low-Fat Diet (LFD; 10% fat, 20% protein and 70% carbohydrate,
1047
Research Diet, New Brunswick NJ Cat. No. D12450J, n=14) or High-Fat Diet (HFD; 60% fat, 20%
1048
protein and 20% carbohydrate, Research Diet, New Brunswick NJ Cat. No. D12492, n=14) for a period of
1049
one month (Table 1, and supplemental data). These diets were selected based on studies by Novak et al.
1050
who demonstrated that a similar HFD increased weight and changed spontaneous physical behavior
1051
(Novak et al., 2006), and Dutheil et al., 2016 who showed behavioral changes between a LFD and HFD
1052
using a longer 60 day time period. Animals were kept in a bio-bubble on a twelve-hour light/dark
1053
schedule being individually housed with sterile bedding. Food and water were provided ad libitum and
1054
animal weights recorded every day during handling. Obesity in animal models can be defined based on
1055
animal weight and/or increased body fat content, with an increase of 10-25% body weight over normal
1056
chow fed age-matched rats commonly reported as moderate obesity, and >40% as being severe (Hariri
1057
and Thibault, 2020). Every week, the cages were cleaned with alcohol and sterile bedding was replaced.
1058
Thirty days after commencing the diet, animals underwent behavioral testing using open field and forced
1059
swim tests. All procedures were approved by Ponce Health Sciences University Institutional Animal Care
1060
and Use Committee protocol #199 and carried out in accordance with the National Institutes of Health
1061
guide for the care and use of laboratory animals.
1062
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METHOD DETAILS
1063
Open Field Test
1064
An open field test was performed as previously described (Ramos-Ortolaza et al., 2017). The open field
1065
arena consisted of a square wood box covered with black Formica (W 36 x L 36 x H 18 inches), located
1066
in a small isolated room (7.5 x 7.5 feet) with dim red light. For the test, animals were placed in the center
1067
of the arena and allowed to roam for 10 minutes. A video camera was placed above the arena to record
1068
the animals during the test. The ANY-maze software (Stoelting Co., IL.) was used to track time spent at
1069
the central and peripheral zones of the arena, total distance traveled and velocity, as measures of anxiety-
1070
like behavior (Prutt et al., 2003;Gould et al., 2009). White noise contained in the ANY-maze software
1071
were used to reduce variations in environmental sounds. Fecal pellets were also counted as an indirect
1072
measure of anxiety-like behavior (Malliots et al., 2000, Cuevas et al., 2012). The arena was cleaned with
1073
100% ethanol between animals to remove scent cues that could potentially affect their behavior.
1074
1075
Forced Swim Test
1076
Immediately after the open field test, a Forced Swim Test (FST) was performed to measure behavioral
1077
despair as previously described (Ramos-Ortolaza et al., 2017). Briefly, animals were placed in a glass
1078
cylinder (40cm in height and 30cm in diameter) filled with water (30± 1°C) to a height of 20cm with
1079
15cm above the head of the rat. This level was high enough to avoid the animals touching the bottom with
1080
their tails, but far enough below the top edge of the cylinder to prevent them from being able to escape.
1081
The trial was recorded for 10 minutes. ANY-maze software was used to manually track immobility,
1082
swimming, struggling and diving. In addition, white noise was used to avoid the impact of the
1083
environmental sound variation. Immobility was measured when the rats were floating or slightly moving
1084
their forepaws to keep their nose above the water; swimming was measured when the rats were moving
1085
horizontally while keeping the nose above the water; struggling was measured when the rats were moving
1086
their forepaws rapidly and breaking the surface of the water; and diving was measured when the rats
1087
completely submerged to the bottom of the cylinder. Escaping, touching the bottom of the cylinder with
1088
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the tail, or giving up and sinking was used as criteria to exclude animals from the analysis. Two animals
1089
from the LFD and one from the HFD group were removed under these exclusion criteria. At the end of
1090
the FST, animals were removed from the cylinder and dried under warm light for 10 minutes. Only one
1091
FST session was performed, with no acclimation period, to prevent confounding effects of learning
1092
(Wulsin et al., 2010; De Pablo et al., 1991).
1093
1094
Euthanasia and Sample Collection
1095
Twenty-four hours after behavioral testing, rats were deeply anesthetized with pentobarbital (45 mg/kg
1096
i.p.). A cardiac puncture was used to obtain blood after verifying non-responsiveness. A laparotomy was
1097
performed and epididymal fat pads were removed carefully, weighed and snap frozen on dry ice. The
1098
distal colon was removed and opened longitudinally to allow the collection of feces and macroscopic
1099
examination. Feces were transferred to labeled tubes and snap frozen on dry ice. One half of the colon
1100
was formalin fixed and processed for H&E staining and the other was removed and snap frozen on dry ice
1101
for molecular analysis. The brain was removed and mid brain sections were formalin fixed for staining
1102
(see sections below).
1103
1104
Colonic damage and crypt length
1105
The colon specimens were analyzed in a blinded fashion for the presence of diarrhea, ulceration,
1106
thickness (mm), and adhesions to give a total macroscopic damage score (Appleyard and Wallace, 1995).
1107
Using previously described procedures H&E stained sections were examined for histological changes by
1108
two different observers using the following criteria: loss of mucosal architecture (from 0 to 3: absent,
1109
to severe), muscle thickness (from 0 to 3: zero meaning 1/2mucosal thickness, one meaning ½ to ¾
1110
mucusal thickness, two meaning equal to mucosal thickness, and three meaning all muscles) , cell
1111
inflitration (zero non infiltration, one in the muscularis mucosae, two in lamina propria/villi , and
1112
three in serosa), crypt abscess formation (present (1) or absent (0)), and goblet cell depletion
1113
(present(1) or absent (0)), were evaluated (Appleyard and Wallace, 1995, Hernandez et al., 2003).
1114
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Photos were taken under the 40x objective. Separately, images were examined and the crypt length
1115
measured using Image J computer software from the National Institutes of Health. Images were examined
1116
using three similar fields and three measurements of crypt length (from the bottom to top of the crypt)
1117
were obtained and averaged.
1118
1119
Claudin-5 and Occludin mRNA expression
1120
Thirty milligrams of snap frozen colonic tissue were transferred to mRNAse free microcentrifuge tubes
1121
filled with beads and homogenizing solution from the AllPrep DNA/RNA/Protein Minikit from Qiagen
1122
Co. (Cat. No. 80004). Tubes were transferred to the Bullet blender from Advance Co and homogenized
1123
for five minutes before extracting RNA following the Qiagen manufacturer’s procedure measuring the
1124
concentration and quality of the RNA using nanodrop 2000 (Thermoforma Co). One microgram of
1125
mRNA was changed to complementary DNA using iScript cDNA synthesis kit from Biorad Co.
1126
(1708891). Realtime Polymerase reaction was performed using iQ SYBR Green Supermix (1708882)
1127
from Biorad Co. and primers from Qiagen Co (Claudin-5 PPR46476A; Occludin PPR48441A, with beta
1128
actin PPR06570C as internal control). Data was reported as a fold change using the equation 2-CT and
1129
normalized by the control (LFD).
1130
1131
Fecal Metagenomics
1132
DNA purified from rat feces pellets was used as template for PCR targeting the V1-V3 region of the
1133
bacterial 16s rDNA gene for the microbiome analysis. Amplification was verified by gel electrophoresis
1134
and successfully amplified samples were then quantified using the Qubit 2.0 (Life Technologies). MiSeq
1135
libraries were prepared using the Nextera XT DNA kit (Illumina LLC), according to manufacturer
1136
protocol. The final libraries were loaded in a MiSeq instrument with a 500 cycles kit.
1137
MiSeq data was extracted, decompressed, and analyzed using the QIIME software (v.1.9.0) in a Linux
1138
platform (Ubuntu). Forward and reverse reads (FASTQ file) of each sample were joined using the
1139
join_paired_ends.py script with QIIME default parameters. The resulting reads were split libraries and
1140
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then filtered by quality and length, reads shorter than 12 bp and with a quality less than Q30 were
1141
discarded. A closed OTUs was picked using the greengenes 13_8-release database with a 97-similarity
1142
threshold. The generated OTU table was rarefied to an equal number of OTUs per sample using the
1143
single_rarefication.py QIIME command ad used for downstream analyses and other statistical data. Raw
1144
data is available at National Center for Biotechnology information (NCBI) with accession number:
1145
PRJNA870914 .
1146
1147
Immunofluorescence Assay
1148
IBA-1 and GFAP immunofluorescence staining was performed in previously preserved tissue embedded
1149
in paraffin. After sacrifice, brain was extracted and fixed in 10% paraformaldehyde. Tissue sections were
1150
embedded in paraffin and coronal sections of dorsal were cut at 8 μm using a microtome and placed on a
1151
positively charged slide. Slides were deparaffinized in xylene followed by hydration in descending grade
1152
of ethanol (100% two times, 95%, 80%, and 70%, CDA-19), for 3 minutes each. Tissues were washed for
1153
1 minute with distilled water and placed in PBS solution for 5 minutes prior to the antigen retrieval
1154
incubation made with 0.01 M Citrate-EDTA buffer (pH = 6.2) at 90–95 °C for 40 min. Tissues were
1155
washed two times for 2 minutes with distilled water and were placed in PBS for 5 minutes. Then, protein
1156
block (Cat No. 50062Z, Life Technologies, Frederick, MD) step was performed for 15 minutes to avoid
1157
non-specific bindings on the tissue. Tissues were incubated with Anti-Iba-1 rabbit polyclonal primary
1158
antibody (Cat no. 019-19741, FUJIFILM Wako Pure Chemical Corporation) or Anti-GFAP mouse
1159
monoclonal primary antibody (Cat no. 644702, BioLegend) overnight in a humidified chamber at 4 °C.
1160
The day after, slides were washed twice with PBS for 5 minutes and incubated during 5 minutes with
1161
Goat Anti-Rabbit IgG Secondary Antibody conjugated with Alexa Fluor 555 (Cat no. A21429, Invitrogen
1162
by Thermo Fisher Scientific) for the Anti-Iba-1 stained slices and Goat Anti-Mouse IgG Highly Cross-
1163
Adsorbed Secondary Antibody, Alexa Fluor 488 (Cat no. A11029, Invitrogen by Thermo Fisher
1164
Scientific) for Anti-GFAP stained slices during 30 min at room temperature. Then, slices were washed
1165
two times by PBS for 5 minutes each, followed by incubation with DAPI during 5 minutes for cell nuclei
1166
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labeling. Tissues were washed twice with PBS for 5 minutes and coverslip were mounted on the slides
1167
with ProLong Gold antifade (Cat No. P36934, Invitrogen by Thermo Fisher Scientific). Samples were
1168
taken using an Olympus System Microscope Model BX60 (Olympus Life Sciences Solution). ImageJ
1169
software was used to measure intensity, percent of area for microglia and length for GFAP stainig(for
1170
each field, lenght and number of projection were measure) . The values are reported as mean ± SEM.
1171
1172
Phospho m-TOR Immunohistochemistry
1173
Brain sections were cut at 4µm thickness with a microtome (Microm HM340, Microm International) and
1174
mounted on glass slides. Tissue sections were deparaffinized with xylene, 2 changes, 15 minutes each,
1175
and hydrated in descending grades of ethanol to distilled water. This was followed by a 3% Hydrogen
1176
peroxide (Sigma-Aldrich) incubation for 15 minutes to block endogenous peroxidase and a fine minute
1177
PBS wash. After antigen retrieval (0.01M Citrate-EDTA buffer, pH 6.0, 95-99°C for 40 minutes), slides
1178
were left for 20 minutes at room temperature, rinsed with 2 changes of distilled water for 2 minutes and
1179
placed in PBS for 5 minutes. Slides were blocked with normal goat serum (BioGenex, cat#HK112-9KE)
1180
for 15minutes and followed by an overnight incubation with primary antibody (Phospho- mTOR
1181
antibody, cat# 2976, Cell signaling; 1/10 dil.). A negative control with PBS instead of primary antibody
1182
was run in each slide. On the second day, slides were washed with PBS for 5 minutes. A Multi Link was
1183
used as the secondary antibody for 20 minutes, followed by PBS wash for 5 minutes. The slides were
1184
placed in the Streptavidin Peroxidase for 20 minutes (Super Sensitive Link-Label IHC Detection System,
1185
cat#LP000-UCLE, BioGenex, San Ramon, CA, USA). For development, one drop of 3,3’
1186
Diaminobencidine (DAB) (cat# HK153-5KE, BioGenex, San Ramon, CA, USA) was used on each tissue
1187
and the exposure was monitored for 45 seconds under a light microscope. Then, the slides were washed
1188
with running water for 5 minutes, dehydrated through graded alcohol, cleared with xylene and mounted
1189
with Cytoseal XYL (cat# 8312-4, Richard Allan Scientific, Kalamazoo, MI, USA). After representative
1190
areas were photographed at high power field for each slide, the intensity and percent of area was
1191
determined.
1192
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1193
Cytokine Bead Array and Lipopolysaccharide
1194
After removing the red blood cells by centrifugation, the serum was transferred to a sterile tube and stored
1195
at -20°C. Serum was analyzed using bead array following the manufacturer’s procedure (Millipore,
1196
Billerica, MA; Cat. No HBNMAG-51K) and Kinetic QCL Chromogenic Assay (Millipore, Billerica, MA;
1197
Cat. No NC9597521) to measure LPS.
1198
1199
QUANTIFICATION AND STATISTICAL ANALYSIS
1200
Statistical Analyses
1201
Prior to carrying out the study a power analysis was performed by the epidemiology department at Ponce
1202
Health Sciences University using Epidat software version 3.1 as required by the IACUC. Animals were
1203
assigned a number then distributed randomly with blinded analysis to avoid bias in scoring. Data were
1204
reported as the average and standard error of the means. A student t-test was used for absolute weight or
1205
percent weight change, absolute weight per day with repeated student t-test measures analysis. A
1206
student’s T-test was used to analyze significance for the overall data, Mann-Whitney test was used for
1207
microbial data such bacterial abundance, and Spearman correlation was used. All were reported as
1208
p<0.05(*), p<0.01(**), and p<0.001(***). For metagenomics: for the alpha-diversity, measurements were
1209
calculated and analyzed by a non-parametric student t-test and using 999 Monte Carlo permutation, Beta-
1210
diversity using ANOSIM test, Bacterial abundance was analyzed through non-parametric student t-test
1211
with bonferroni post hoc. All analyses were done on GraphPad version 7.0. ANOSIM test was done with
1212
Qiime 1.9.1(41).
1213
1214
1215
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