Chronic gut inflammation differentially modulates mitochondrial and antioxidant transcriptional programs in limbic brain structures

Chronic gut inflammation differentially modulates mitochondrial and antioxidant transcriptional programs in limbic brain structures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Chronic gut inflammation differentially modulates mitochondrial and antioxidant transcriptional programs in limbic brain structures Chelsea E MATISZ, Valerie LAPOINTE, Kaylen BEEKMAN, Travis HAIGHT, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4486754/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Chronic inflammatory diseases are frequently comorbid with depression and anxiety, often persisting during periods of inflammatory remission. This suggests functional changes to neural circuits involved in the contextual regulation of motivation and threat processing. Here, we test how chronic gut inflammation evoked by dextran sodium sulfate (DSS) affects gene expression in several limbic brain structures associated with these functions. We assessed post-mortem expression of mRNA transcripts in the anterior cingulate cortex (ACC), CA1 hippocampus, nucleus accumbens (NAc), and primary motor cortex (M1) as a non-limbic control. The levels of mRNA associated with mitochondrial function, inflammation, and synaptic connectivity were altered in DSS-treated animals, but the specific pattern of changes was heterogeneous among brain structures. Chronic gut inflammation affected transcript expression in the CA1 and NAc more so than in the ACC and M1. These differences involved genes related to antioxidant systems and mitochondrial function. For example, expression of the cytochrome oxidase 1 gene mt-co1, which is necessary for oxidative phosphorylation, was reduced in ACC and NAc of DSS animals, suggesting reduced capacity for ATP production in these regions. Markers of gut inflammation correlated with expression of several transcripts in the ACC, including markers of synapses and GABA synthesis. The NAc showed strong correlations of mitochondrial function and measures of mitochondrial fission, inflammation, synaptic connectivity, and GABA synthesis. In sum, these data indicate neuroinflammatory processes in the brain evoked by chronic relapsing gut inflammation are heterogeneous among brain structures, and possess complex relationships between mitochondrial function, antioxidants, neurotransmission and gut inflammation. neuroinflammation hippocampus nucleus accumbens anterior cingulate cortex mt-co1 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 1 Introduction Inflammation appears to promote anxiety and depression, likely by altering neurophysiological processes. This may contribute to the high comorbidity of anxiety and depression in chronic inflammatory diseases such as diabetes (Castellano-Guerrero, Guerrero, and Relimpio 2018 ), rheumatoid arthritis (Isik et al. 2007 ), and cardiovascular diseases (Celano et al. 2016 ). Such comorbidity is particularly high in people with inflammatory bowel disease (IBD). Approximately 57% of people with active IBD experience anxiety, and 39% have symptoms of depression (Barberio et al. 2021 ). Importantly, these mood disorders persist even during periods of disease remission (Barberio et al. 2021 ). This suggests that chronic somatic inflammation can produce changes in the brain that persist after peripheral inflammation subsides. Neuroinflammation is a likely intermediary. Even transient inflammation in the gut produces a neuroinflammatory response in the brain, leading to changes in behaviour (Emge et al. 2016 ; Jain et al. 2015 ; Chelsea E. Matisz et al. 2020 ) and an array of changes in neural physiology (Chelsea E. Matisz et al. 2022 ; Riazi et al. 2015 ; Zonis et al. 2015 ). Several of these physiological changes are associated with anxiety and depression, including oxidative stress, mitochondrial dysfunction, changes in neural structure, altered neural activity, and neurotransmitter levels(Salim 2014 ; Y. Liu, Zhao, and Guo 2018; Guo et al. 2023 ; Allen et al. 2018 ; Rezin et al. 2009 ) The diversity and complexity of neuroinflammatory-evoked changes in neural physiology complicates a straightforward theory for the cellular etiology of anxiety and depression. We and others have proposed that bioenergetics and its regulation by reactive oxygen species in a key brain circuit called the limbic system are a core feature that may account for many phenomena (C. E. Matisz and Gruber 2022 ; Picard and McEwen 2018). The brain’s high energy demand is predominantly met by mitochondria, the largest cellular source of ATP. Mitochondria activity influence a variety of processes related to neural structure, function, and circuity, including dendritic and axonal branching (Courchet et al. 2013 ; Gebara et al. 2021 ) and neurotransmitter synthesis (Kwon et al. 2018 ; Sun et al. 2013 ). The metabolic needs of the brain are both spatially and temporally variable, as evidenced by functional and molecular evidence (Castrillon et al. 2023 ). For example, the energetic costs of stress and inflammation can deplete metabolic resources in the brain if they reach sufficient magnitude and duration (Lacourt et al. 2018 ; Straub 2017 ). It has been proposed that prolonged downregulation of energy production in the brain can promote alterations in neuronal architecture and plasticity that promote anxiety and depression (Morava and Kozicz 2013; Picard et al. 2018 ). Specific regions of the brain appear to be more liable to this process. For example, clinical and preclinical studies indicate that certain structures within the limbic system, such as the hippocampus (Bagot et al. 2015 ; Haj-Mirzaian et al. 2017 ), anterior cingulate cortex (C. E. Matisz and Gruber 2022 ; J. Wang et al. 2017 ), and nucleus accumbens (Gebara et al. 2021 ; Strasser et al. 2019 ) are associated with changes in brain metabolism that appear to promote anxiety and depressive behaviours (Duman et al. 2016 ). Moreover, the phenotype of mitochondria varies among brain structures, as does the mitochondrial sensitivity to stressors and endocrines; notably, stress induced changes to identified ‘mitochondrial networks’, which correlated with anxiety-like behaviours in mice (Rosenberg et al. 2023 ). Whereas structure-specific effects of chronic stress on mitochondrial function have been reported, the consequences of gut inflammation on brain mitochondria have received less attention. We and others hypothesize that chronic neuroinflammation may have a similar effect on mitochondrial function as stress (Zhao et al. 2019 ; Culmsee et al. 2018 ). Much of the previous work on gut inflammation-induced neuroinflammation has employed relatively brief inflammatory treatments. Our previous research has demonstrated that the duration of gut inflammation influences its behavioural effects. Short-term gut inflammation (1 week) produced deficits in learning and memory, and increased motoric response in a forced swim task. These behavioural changes, however, were not observed in mice with chronic gut inflammation (5 weeks) (Chelsea E. Matisz et al. 2020 ). In other words, it appears that the mnemonic and motoric alterations were transient effects triggered by the onset of inflammation. Conversely, increased contextual fear only emerged in chronic gut inflammation (C. E. Matisz et al. 2022 ). These data suggest that the neural circuits that encode some behaviours (e.g. contextual fear memory) are only affected by prolonged inflammation, possibly by the accumulated effects of neuroinflammation over many weeks. Here, we test the hypothesis that the accumulated effects of gut inflammation involve decreased mitochondrial function in limbic brain structures more so than in non-limbic structures , and that reduced metabolic function will be associated with changes in cellular physiology and metabolics, such as the management of oxidative stress. 2 Materials and Methods Animals The study used 16 male C57Bl/6 mice (8 weeks old, Jackson Laboratories, Bar Harbor, ME, USA). Mice were housed in groups of four in standard clear plastic cages in a vivarium with a 12-h light/dark cycle, with free access to standard mouse chow and drinking water. Animals were acclimatized to the facility for 2 weeks prior to the start of experimentation. All experiments were carried out in accordance with the guidelines of the Canadian Council of Animal Care, and were approved by the University of Lethbridge Animal Care Committee (Protocol #2018). Colitis For the induction of chronic DSS colitis, mice were exposed to three cycles (3% wt/v) of DSS (MW 40kD; Fischer Scientific, CAT 9011-18-1) each lasting five days, with 9 days of recovery (access to regular drinking water) between cycles. Control mice received regular drinking water for the duration of the experiment (Fig. 1 ). Forced Swim Task The forced swim task was conducted on day 42. Mice were placed in a clear glass cylinder (30cm tall, 15 cm diameter) filled 14cm deep with water (28C) and video recorded for 6 minutes. Mice were monitored continuously. Any animal unable to keep its head above water was immediately removed from the cylinder. After completing the task, mice were removed, dried with a paper towel, and placed in a cage with a heating pad before being returned to the home cage. Immobility time was defined by minimal movements to keep its head above water, recorded by an observer blind to the experimental treatment. Each mouse was euthanized 30 minutes after its completion of the FST, and the brain was quickly snap frozen. The timing of testing, euthanasia, and brain freezing was kept as constant as possible among animals in order to normalize any effects of stress and/or motoring output (swimming) on gene expression. Colitis Assessment : Disease activity was assessed on the third cycle of DSS and scored as previously described (Matisz et al. 2020 ). Briefly, percentage of body weight lost from the start of the cycle on day 28 scored on a 1–4 range based on the percentage of body weight lost (0 = 0%, 1 = 5 to ≤ 10%, 3 = > 10 to ≤ 15%, 4 = > 15%); stool consistency (solid fecal pellets = 0, soft, sticky stools = 2, loose, water stools = 4); and the presence of fecal blood (no blood = 0, fecal blood = 4). The total disease score was computed as a weighted average of each of these three measures. After euthanasia, the length of the colon was measured from anus to ileocecal junction. Tissue Collection Mice were euthanized 30 minutes post forced swim task on day 42 by induction into an isoflurane chamber and subsequent injection with ~ 1.6mL/kg euthanyl (Bimeda MTC 00141704). Brains were immediately removed and snap-frozen via immersion into pre-chilled isopentane for 60–120 seconds and subsequently stored at -80°C until downstream processing. Tissue punches were obtained following protocols outlined by Wager-Miller et al.. (Wager-Miller et al. 2020 ). All tools and surfaces were cleaned using RNaseZap™ RNase Decontamination Solution and UltraPure™ DNase/RNase-Free Distilled Water (Thermofisher scientific). ELISA Fecal lipocalin-2 is a biomarker for intestinal inflammation in both humans and rodents. Samples were prepared following previously published protocols (C. E. Matisz et al. 2022 ). Briefly, frozen fecal samples were reconstituted in PBS with 1% Tween 20 (10mg/100uL), and vortexed for 20 minutes. Samples were centrifuged for 10 minutes at 12,000 rpm, and supernatants were collected and stored at -20◦C until analysis. At baseline, all processed fecal samples were diluted at 1:1 in reagent diluent. Moving forward, all fecal samples from mice exposed to DSS were diluted at 1:1250 in reagent diluent to ensure optical density was within limits of detection of the standard curve. Lipocalin-2 levels were quantified in the supernatants using the DuoSet murine Lcn-2 ELISA Kit (R&D Systems, Minneapolis, MN), following the manufacturer’s instructions. RNA isolation and RT-PCR RNA was extracted using the standard Trizol reagent protocol (Cat # 1596026, Invitrogen) and reverse transcribed using Superscript IV (CAT 18090010, Invitrogen) by the following method: 100ng of total RNA was mixed with 100ng Random Primer Mix (S1330S, NEB), and 1 uL of 10mM dNTP mix (CAT N0447S, NEB). The mixture was incubated for 5 min at 65°C and placed immediately on ice for a minimum of 1 minute. The mixture was then incubated with 4uL of 5X Superscript IV buffer, 1uL of 0.1M DTT, and 1uL of Superscript IV (200U/uL) for 10 min at 25°C, 10 min at 55°C and 10 min at 80°C. The produced cDNA was analyzed by qPCR using 2uL of 1:10 diluted cDNA, 0.5uL of each gene-specific primer diluted to 10uM, 5uL of Luna Universal qPCR master Mix (M3003E, NEB), and 2uL of H2O. qPCR was performed using the Bio-Rad CFX384 Real-time detection system, with the following thermocycler conditions: 3 min at 95°C (15 s at 95°C, 30 s at 54°C, 30 s at 66°C) × 40 cycles. Fluorometer readings were taken during the extension phase, while standard curves were prepared for relative expression. The analysis of PCR efficiency was achieved by pooling 2uL of each cDNA sample and the subsequent preparation of standard dilutions SD1: 1:2; SD2: 1:4; SD3: 1:8; SD4: 1:16; SD5: 1:32. All samples were run in triplicate. Quantitative measurements of target gene expression relative to controls followed the 2 −ΔΔCt method. Group differences were expressed as fold changes, normalized to the housekeeping gene hypoxanthine phosphoribosyltransferase (Hprt). Gene-specific primers were ordered from IDT (USA, CO) as custom DNA oligos. The sequences of primers used are shown in Table 1 . Table 1 List of RNA primers used in study. Gene Forward primer (5’-3’) Reverse primer (5’-3’) DRP1 ATG CCA GCA AGT CCA CAG AA TGT TCT CGG GCA GAC AGT TT MFN2 TGC ACC GCC ATA TAG AGG AAG TCT GCA GTG AAC TGG CAA TG MtCO1 ACC CAA TCA AAC GCC TAG CA GGA CTG GAA TGC TGG TTG G GPX1 CCT CAA GTA CGT CCG ACC TG CAA TGT CGT TGC GGC ACA CC NRF2 TAG ATG ACC ATG AGT CGC TTG C GCC AAA CTT GCT CCA TGT CC GAD1 TCC TGG TTG ACT GTA GAG ACA C CAT ATT GGT ATT GGC AGT CGA T CFOS TTT TGC GCA GAT CTG TCC GT GTG GGG AGT CCG TAA GGA TG SNAP25 GTG CAC TTA GGG TGC GGT AT ATC TCC TCC AGC TCA TTG CG PSD95 TCT GTG CGA GAG GTA GCA GA AAG CAC TCC GTG AAC TCC TG Statistical analysis Data are presented as mean ± SEM. Statistical significance was set at p < 0.05. Body weight was analyzed by a two-way repeated measures ANOVA with Sidak post-test, and Lcn-2 expression analyzed by mixed effects analysis with a Tukey’s comparison post-test. Disease activity index was analyzed by One Sample Wilcoxon Signed ranked Test. Comparisons of the mean between groups was analyzed via Student’s t-test or One-Way ANOVA with Tukey’s post-test. Principal component analyses (PCA) were used to generate plots to visualize clustering between treatment groups. Primary and secondary principal components were compared via Mann-Whitney between DSS and control groups. Significant differences between the first or second principal component are reported. Statistical analyses were conducted with GraphPad Prism 10.0.0 (GraphPad Software, La Jolla, CA). Figures created with BioRender.com and Adobe Photoshop. 3 RESULTS Exposure to DSS produces signs of gut inflammation and disease Dextran Sodium Sulfate is widely used to model gut inflammation in rodents, with excellent face validity (Chassaing et al. 2014 ). In our study, exposure to DSS in the drinking water led to expected signs of disease. Mice exposed to DSS for 3 cycles exhibited significant weight loss relative to controls (Two-way Rm ANOVA F 1,14 = 41.48, p < 0.0001; Fig. 2 A). Further, expression of the pro-inflammatory mediator lipocalin-2 (Lcn2) was significantly elevated in the feces among DSS-treated mice throughout the study (Mixed-effects model F 1,14 =19.70, p = 0.0006; Fig. 2 B). The disease activity index was increased after final cycle of DSS in DSS-treated animals compared to controls (One way Wilcoxon Signed Rank Test, W = 36, p = 0.0078; Fig. 2 C). Colon length was reduced, but not significantly, among mice exposed to DSS (Students t-test, t = 1.064; Fig. 2 D). Overall, mice chronically exposed to DSS exhibited increased weight loss, disease activity, and increased fecal lipocalin-2 expression relative to controls, indicating that DSS treatment evoked the expected inflammation in the gastrointestinal tract. Transcript Selection The objective of the study was to determine if DSS-colitis more strongly affects neurons in brain regions associated with anxiety and depression (e.g. limbic structures) as compared to other structures. Four brain regions were selected, based on their well-recognized role in goal-directed and threat-coping behaviors that are altered in anxiety and depression; the CA1 of the hippocampus, the ACC, and the NAc. The motor cortex (M1) was selected as a control region (Supplementary Fig. 1). A panel of 9 different primers were selected to assess several transcriptional programs in neurons that may be modulated by gut inflammation (Table 2 ). Three transcripts were selected to assess how gut inflammation may affect mitochondrial function in the brain. Inflammation has been shown to affect mitochondrial network dynamics and mitochondrial function. Mitochondria form dynamic networks that undergo fusion and fission to maintain cellular energetic requirements. These structural changes are mediated by several fusion and fission proteins, including Mfn2, and Drp1, respectively. Mt-Co1 encodes for a subunit of complex IV in the electron transport chain in mitochondria, by which the process of oxidative phosphorylation generates cellular energy in the form of ATP. Thus, its expression regulates energy production in mitochondria. Inflammation can promote oxidative stress. Therefore, we selected two transcripts to assess how gut inflammation affects oxidative stress responses in the brain. Nuclear factor erythroid 2 related factor 2 (Nrf2) regulates antioxidant response elements, while Gpx1 encodes for glutathione peroxidase 1, an enzyme that works with glutathione as a key neuronal antioxidant. Our previous research has revealed that acute DSS alters spine density in CA1, as well as the fraction of neurons activated by the forced swim task (Chelsea E. Matisz et al. 2022 ). Therefore, to assess how chronic DSS may affect pre- and post-synaptic elements and neuronal activation, we assessed transcript expression of Snap25, Psd95, and cFos. Animals were subjected to a 6-minute forced swim task (FST) prior to euthanization in order to (i) test for changes in active threat coping or depressive endophenotypes, and (ii) provide a stressor to activate neurons in the limbic system and motor cortex. Mice previously given DSS exhibited similar mobility time during the FST relative to controls (t = 0.43; Fig. 2 E), in alignment with previous reports (Chelsea E. Matisz et al. 2020 ). Finally, because GABAergic transmission has been implicated in anxiety and depression, we assessed Gad1 expression. Gad1 mRNA encodes for the rate-limiting enzyme glutamate decarboxylase 67, which is responsible for over 90% of basal GABA synthesis (Asada et al. 1997 ). Table 2 List of selected genes examined in the present study and their function Gene name (transcript) Function Mfn2 Mitofusin2; Regulates mitochondrial fusion Drp1 Dynamin-related protein; Regulates mitochondrial fission Mt-Co1 Cytochrome C oxidase subunit I; Mitochondria-encoded gene important for oxidative phosphorylation and ATP production CFos Early immediate gene, expressed by recently activated cells, inducing neurons Gad1 Precursor to GABA, inhibitory neurotransmitter Nrf2 Nuclear factor erythroid 2-related factor 2; Regulates cellular defense against oxidative stress Gpx1 Glutathione peroxidase; antioxidant enzyme Psd95 Postsynaptic density 95kda; regulates retention of glutamate receptors Snap25 Synaptosome associated protein 25kda; participates in synaptic vesicle exocytosis of neurotransmitters Regional differences in basal transcript expression We first examined how expression of the selected transcripts varied among brain structures in control animals (Supplementary Fig. 2; Supplementary Table 1). The NAc exhibited an expression profile that most differed from the other structures. The expression of Gad1 (F 3,20 ) = 29.56, p < 0.001) was significantly highest in the NAc relative to all other structures (Tukey’s test for ACC and Ca1, NAc, and M1 are all p < 0.001). This is not surprising, as GABAergic medium spiny neurons are the dominant neuronal cell in the striatum (Yager et al. 2015 ). Interestingly, the NAc also possessed highest expression of Gpx1 (F 3,20 ) = 76.18, p < 0.001) relative to all other structures (p < 0.0001). The NAc expressed significantly higher expression of Mt-Co1 (F 3,20 ) = 7.554, p = 0.0014) and Psd95 (F 3,20 ) = 8.062, p = 0.0010) compared to the ACC (Mt-co1, p = 0.0060; Psd95, p = 0.0013) and M1 ( Mt-co1, p = x ; Psd95, p = 0.0033, and significantly lower expression of Snap25 relative to CA1 and M1. The CA1 and NAc displayed lowest expression of cFos relative to the ACC and MA (F 3,20 =12.21, p < 0.0001; CA1 vs. ACC p = 0.0004; CA1 vs. M1, p = 0.0026; NAc vs. ACC p = 0.002, NAc vs. M1 p = 0.014), and highest expression of Nrf2, relative to the ACC and M1 (F 3,20 =20.30, p < 0.0001; CA1 vs. ACC p < 0.0001; CA1 vs. M1 p < 0.0001; NAc vs ACC p = 0.002; NAc vs. M1 p = 0.0053). No differences in the expression of Mfn2 (F 3,20 =0.6606, p = 0.59) and Drp1 (F 3,20 =1.070, p = 0.38) were observed among neural structures in control animals. Gut inflammation alters expression of selected gene transcripts in regional manner We next compared the structure-specific expression of transcripts between treatment groups. Exposure to DSS altered the expression of several transcripts, in a region-specific manner (Table 3 ). The CA1 of the HPC was most affected by exposure to DSS; expression of 6 of the 9 transcripts were different (Fig. 3 B,C). Specifically, cFos (t = 2.94, p = 0.015), Drp1 (t = 2.64, p = 0.025), Gad1 (t = 2.27, p = 0.046) and Snap25 (t = 2.29, p = 0.045) expression was significantly elevated in the CA1 among DSS-treated mice relative to controls. Conversely, Nrf2 (t = 3.91, p = 0.0029) and Gpx1 (t = 6.707 p = 0.000053) were significantly reduced in the CA1 of DSS-treated mice. Mt-Co1 approached significance (t = 2.092, p = 0.063). The expression of Mt-Co1 was significantly reduced in the NAc (t = 5.19, p = 0.00041) and ACC (t = 2.722, p = 0.021), and Gpx (t = 1 3.29, p = 0.0082) was significantly reduced in the NAc of mice with DSS relative to controls (Fig. 3 B,C). Treatment did not significantly affect the expression of any selected transcripts in the M1. These data indicate that chronic gut inflammation promotes heterogenous responses of different transcripts that vary among brain regions. Table 3 T-test and p-value for comparisons between control and DSS exposed animals in different regions N = 6 male mice per treatment group. Data shown in Fig. 3 . Gene Region T ratio P value Drp1 ACC 1.04 0.32 CA1 2.64 0.02 NAc 1.08 0.30 M1 0.13 0.90 Mfn2 ACC 0.31 0.76 CA1 1.62 0.14 NAc 0.29 0.78 M1 0.26 0.80 Mt-Co1 ACC 2.72 0.02 CA1 2.09 0.06 NAc 5.19 0.00 M1 1.90 0.09 C-fos ACC 0.31 0.77 CA1 2.94 0.01 NAc 0.53 0.60 M1 0.12 0.90 Gad1 ACC 0.73 0.35 CA1 0.05 2.27 NAc 0.97 0.04 M1 0.22 1.31 Gpx1 ACC 1.02 0.33 CA1 6.71 0.00 NAc 3.29 0.01 M1 1.93 0.08 Nrf2 ACC 0.77 0.46 CA1 3.91 0.00 NAc 1.60 0.14 M1 1.22 0.25 Psd95 ACC 0.26 0.80 CA1 1.83 0.10 NAc 0.39 0.71 M1 0.94 0.37 Snap 25 ACC 0.18 0.86 CA1 2.29 0.05 NAc 0.07 0.94 M1 0.44 0.67 Gut inflammation drives regional changes in transcriptional programs in the brain To better understand how transcriptional programs were differentially affected by gut inflammation, we conducted principal component analysis (PCA). When all gene transcripts were loaded (Fig. 4 A), and transcript expression from all brain regions are included in the PCA, clear clustering among mice with DSS colitis vs control emerged (p = 0.0022). Further, when PCA loadings were restricted to transcript expression within specific brain regions, there were significant differences between control and DSS animals in the CA1 (p = 0.0022) and NAc (p = 0.015). When only transcripts related to mitochondrial function (Drp1, Mfn2, Mt-Co1) were loaded into the PCA analysis, there was a significant difference in PC1 between control and DSS mice among all brain regions; and upon separation of structure in the analysis, there were significant differences between principal components of control and DSS mice in the CA1 (P = 0.015), and PC2 NAc (p = 0.0043) (Fig. 4 B). Similarly, PCA of transcripts related to inflammation regulation (Gpx1, Nrf2) revealed significant differences between the PC1 of controls and DSS among all brain regions (p = 0.0022; Fig. 4 C). This significance persisted when the PCA only included transcript expression from the CA1 (p = 0.0022) and the NAc (p = 0.026). The expression of transcripts related to pre- and post-synaptic density proteins did not reveal any significant clustering of principal components (Fig. 4 D). All genes include Mfn2, Drp1, Mtco1, CFos, Gad1, Gpx1, Nrf2, Snap25, and Psd95. Genes related to mitochondrial function include Drp1, Mfn2, Mt-Co1. Genes related to antioxidant regulation include Nrf2 and Gpx1. Pre and post-related synapse genes include post-synpatic (Psd95) and pre-synaptic (Snap25) mechanisms. The percentage of variation explained by the principal component is indicated on the axis. N = 6 male mice per treatment group. Ellipses indicate significant differences between the first or second principal component (*p < 0.05) between treatment groups. Correlations between transcript expression within brain regions among healthy and gut-inflamed animals We next tested if gut inflammation affects the relationships (i.e. correlations) between expression among transcripts within each brain structure. DSS treatment did have structure-dependent effects on the correlation among transcript levels (Fig. 5 ). Pearson correlation analysis of transcript expression within a given brain region, in mice with gut inflammation and healthy controls. N = 6 per treatment group. *p < 0.05. Animals with gut inflammation displayed significantly different relationships between several transcripts in the NAc relative to healthy controls (Table 4 ). Interestingly, the expression of MtCo-1 was a common denominator for all these relationships. We observed a significant positive correlation with Mt-Co1 and Drp1 (p = 0.048, r2 = 0.67; Fig. 6 A), Mfn2 (p = 0.015, r2 = 0.81; Fig. 6 B) and Gad1 (p = 0.030, r2 = 0.73, Fig. 6 C), with a similar trend observed with Psd95 (p = 0.067; Fig. 6 D). A negative relationship between Mt-co1 and Drp1, Mfn2, Gad1, and Psd95 was observed among controls, with the latter reaching statistical significance (p = 0.016, r2 = 0.80; Fig. 6 ). Table 4 Correlation between Mt-Co1 and Drp1, Mfn2, Gad1, and Psd95 among different treatment groups, within the NAc Pearson correlation and linear regression; n = 6 per treatment group. Data shown in Fig. 6 . Comparison within NAc Treatment Pearson r Linear Regression r 2 P value Mt-co1 vs. Drp1 Among controls -0.58 0.33 0.23 Mt-co1 vs. Drp1 Among DSS * 0.67 0.67 0.048 Mt-co1 vs. Mfn2 Among controls -0.41 0.17 0.42 Mt-co1 vs. Mfn2 Among DSS * 0.90 0.81 0.015 Mt-co1 vs. Gad1 Among controls -0.12 0.61 0.065 Mt-co1 vs. Gad1 Among DSS * 0.88 0.73 0.030 Mt-co1 vs. Psd95 Among controls* -0.90 0.80 0.016 Mt-co1 vs. Psd95 Among DSS 0.78 0.61 0.066 Within the CA1, expression of Psd95 was positively correlated with Nrf2 among controls (p = 0.012, r = 0.91), but not DSS animals (p = 0.64, r=-0.24; Fig. 7 ). No significant relationship between Psd95 and Nrf2 was observed for any other regions, among control of DSS mice. We observed a significant correlation between the expression of Psd95 and Gad1 among control and DSS animals in the M1 and the NAc, among DSS animals in the ACC, and among controls in the CA1 (Supplementary Table 2). However in the CA1, among animals with DSS, the positive relationship between these genes was lost, and trended towards a negative correlation, although this did not reach statistical significance. The expression of Drp and Gad1 were positively correlated with each other among controls, in all limbic regions, but not M1 (Supplementary Table 3). This positive correlation was maintained in mice with DSS in the ACC, with similar trends in the NAc and the M1. Conversely, exposure to DSS was associated with a negative correlation between Drp and Gad1 in CA1 (Supplementary Table 3). Expression of Psd95 as a function of Nrf2 among control and DSS animals in the CA1 N = 6 animals per group. Transcript expression normalized to expression of Hprt. Pearson R and p values for all comparisons can be found in Supplementary Table 4. In the motor cortex and the NAc, DSS animals exhibited a significant positive correlation between MtCo1 and Gad (p = 0.030 r = 0.85); this relationship did not exist among controls, trending towards a negative correlation in the NAc (p = 0.065, r=-0.78) (Table 4 ). No such relationships between transcript expression in the ACC were affected by gut inflammation. Correlations of transcript expression between brain structures, among control and DSS animals To examine the possibility that gut inflammation affects the way the expression of a given transcript between two structures are related, we analyzed the relationship between transcript expression among different brain structures. Correlations of the same gene transcript between different regions are listed in Supplementary Table 5. Treatment status affected the correlation of transcripts related to GABA synthesis, mitochondrial function, and synapse function between brain structures. For example, correlations between the expression of Drp1, Gad1, and Psd95 in the ACC and the NAc were only present in healthy controls (Supplementary Table 5). CFos expression in the CA1 and NAc was negatively correlated only among DSS-treated animals. Further, Psd95 expression in the CA1 and ACC were correlated only among mice exposed to DSS. Interestingly, many correlations between gene expression were observed between the M1 and ACC, and the M1 and the Ca1 (Supplementary Table 5). Correlations between fecal Lcn-2 and transcript expression within DSS animals To determine if there was a relationship between the severity of disease among mice with DSS and mRNA transcript expression, we produced a correlation matrix between transcript expression and levels of Lcn-2 from fecal samples of DSS exposed mice that were collected the same day as euthanasia. Pearson correlation coefficients relating levels of fecal Lcn-2 with expression of transcripts in different brain regions reveals that ACC transcript expression was most strongly correlated with fecal Lcn-2 levels, with a positive correlation between 4 transcripts (Fig. 8 ). Specifically, the expression of Drp1 (p = 0.033, r = 0.0849), Gad1 (p = 0.029, r = 0.858), Psd95 (p = 0.049, r = 0.813), and Snap25 (p = 0.003, r = 0.957) in the ACC were all positively correlated with fecal Lcn-2. Ca1 expression of Psd95 (p = 0.018, and M1 expression of Snap25 (p = 0.019, r = 0.0886) were also positively correlation with fecal Lcn-2. No significant relationships between transcripts in the NAc and fecal Lcn-2 were observed, although Gad1 and Psd95 approached significance (p = 0.062 and p = 0.064, respectively). Pearson correlation of transcript expression in different brain structures and fecal Lcn-2 levels among mice with gut inflammation. N = 6, *p < 0.05. Discussion In this study we investigated the effects of chronic gut inflammation on transcript expression in four neural structures, using the DSS-colitis model of IBD in mice. We report here that chronic gut inflammation is associated with changes in the expression of several transcripts related to mitochondrial function and antioxidant responses. The CA1 of the hippocampus, and secondarily the nucleus accumbens were most affected. Several interesting relationships between transcript expression emerged in mice with chronic gut inflammation that suggest impaired mitochondrial metabolism in the CA1 and NAc. Reduced transcript expression of Mt-co1, indicative of diminished mitochondrial output, was also observed in the ACC. In contrast to these limbic structures, the expression of transcripts in the primary motor cortex (M1) were not affected by DSS. Combined, these results suggest ( i ) effects of chronic gut inflammation are heterogeneous among brain structures, and ( ii ) that limbic structures may be more susceptible to such inflammation. Chronic gut inflammation is associated with regional changes in mitochondrial transcripts Mitochondria play a key role in brain health, and their impairment is hypothesized as a key feature of psychiatric diseases including anxiety, depression, and cognitive dysfunction (Giménez-Palomo et al. 2021; L. Liu et al. 2023; Picard and McEwen 2014; Khacho et al. 2017). Inflammation can produce mitochondrial dysfunction through several mechanisms. For example, pro-inflammatory mediators can promote oxidative damage to mitochondrial components, leading to impaired energy production (Brown and Borutaite 2004; Al-Mehdi et al. 2012). Further, inflammation can generate alterations in calcium homeostasis, in turn disrupting mitochondrial dynamics and promoting fragmentation, which can exacerbate inflammation, and reduce energy capacity (Boyapati et al. 2018; Irazoki et al. 2023). Considering the high basal metabolic rate of the brain, neuroinflammation may generate exacerbated metabolic consequences, particularly in neural structures with high metabolic activity. The bulk of ATP production in the brain is accomplished by mitochondrial oxidative phosphorylation, by which electrons are transported through a series of protein complexes to generate ATP. The final complex of the electron transport chain is cytochrome oxidase c, which is comprised of several subunits, including mt-co1. Thus, Mt-co1 gene expression plays a role in regulating energy production, and can be used as an indicator for ATP production (Nagai et al. 2019). Indeed, previous studies have reported a relationship between low Mt-co1 gene expression and mitochondrial dysfunction and oxidative stress (Holvoet et al. 2017). Our results suggest that chronic gut inflammation is associated with reduced mitochondrial respiration in the NAc and ACC, based on the significant reduction in Mt-Co1 expression relative to control animals. The reduced Mt-Co1 expression was most pronounced in the NAc, with a 30% reduction relative to healthy controls; comparatively, the ACC exhibited a 21% reduction in Mt-Co1 expression. Within the Ca1, there was a trend towards reduced Mt-co1 expression relative to controls, and significantly increased expression of Drp1, which suggests increased mitochondrial fission. Enhanced fission can lead to increased levels of mitochondrial damage associated molecular patterns (DAMPS; e.g. ROS, mtDNA) in the cytoplasm, inducing the production of the proinflammatory cytokine IL-1b via inflammasome activation (Park et al. 2015). Increased expression of IL-1b has been reported in the HPC following gut inflammation (Gadotti et al. 2019). We speculate that the emergence of DAMPS within the brain as a consequence of chronic gut inflammation may be a mechanism by which neuroinflammation persists during periods of disease remission, mirroring the role of systemic mitochondrial DAMPS in promoting inflammation in IBD (Boyapati et al. 2018). Chronic gut inflammation also transformed the relationship between Mt-Co1 and other transcripts in the NAc. Among control mice, we observed a negative relationship between expression of Mt-Co1 and Drp1, Mfn2, Gad1, and Psd95. These relationships were consistently shifted to the left and inverted to positive correlations among mice with chronic gut inflammation. The physiological significance of this finding is unclear; however, the fact that this transformation was only observed in the NAc, and all correlated with expression with Mt-Co1, suggests chronic gut inflammation may promote changes in mitochondrial function that impact neurotransmitter signaling and neuronal spine structure in this region. In our study, the NAc had significantly highest expression of Mt-Co1 relative to other regions among control animals. This may reflect a higher basal metabolic requirement in the NAc, which could render this region especially vulnerable to the metabolic demands of neuroinflammation. Research indicates that there are regional differences in mitochondrial bioenergetics within the brain (Rosenberg et al. 2023; Andersen et al. 2019) and evidence suggests mitochondria within the striatum may be particularly active. For example, mitochondria from striatal neurons exhibited highest rates of oxygen consumption and ATP production in the presence of some respiratory substrates, relative to mitochondria from cerebral cortex and hippocampal neurons (Andersen et al. 2019). Indeed, striatal mitochondria are more susceptible to calcium-induced activation of the permeability transition pore (leading to cell damage or death) than cortical mitochondria (Brustovetsky et al. 2003), and evidence suggests the striatal mitochondria are particularly sensitive to defects in oxidative phosphorylation relative to mitochondria in the cortex and hippocampus (Pickrell et al. 2011). Combined, these data suggest that chronic gut inflammation impairs the energy transformation capacity of mitochondria in a regionally dependent manner. The effect of colitis-induced neuroinflammation on aspects of mitochondrial metabolism in the brain, and how this influences neural physiology requires further investigation. The CA1 displays increased sensitivity to chronic gut inflammation Our study revealed that out of the structures examined, the CA1 of the hippocampus appeared to be the most sensitive to gut inflammation; the expression of 6 out of 9 of the selected transcripts were significantly altered. As well, our PCA revealed that the principal components that included the expression for all transcripts, antioxidant-related transcripts, and mitochondria function related transcripts in the CA1 was consistently different between treatment groups. The apparent sensitivity of the HPC to gut inflammation is supported by the literature, where the reported effects of gut-inflammation in the brain are dominated by the HPC (C. E. Matisz and Gruber 2022). For example, mice administered chemically-induced models of colitis demonstrated increased expression of proinflammatory cytokines (e.g. IL-6, IL-1β, TNF-α) and a variety of markers of oxidative stress in the HPC (Gadotti et al. 2019; Hilel et al. 2018; Haj-Mirzaian et al. 2017). Our previous research has revealed that acute exposure to DSS is associated with increased proportion of immature spines in the apical dendrites of CA1 pyramidal neurons, and reduced neural activation in the CA1, based on reduced immunostaining of cFos (Chelsea E. Matisz et al. 2022). It is tempting to speculate that sensitivity of the CA1 HPC to gut inflammation is associated with activated learning mechanisms, possibly to aid in identification of environmental factors that may be contributing to negative affective states associated with gut inflammation. this may explain the increased Snap25 in the Ca1 of mice with chronic DSS exposure. However, additional testing is needed to substantiate such speculation. In the present study we also observed that chronic gut inflammation is associated with elevated cFos mRNA expression in the CA1. This contrasts the effects of acute DSS exposure, which is associated with reduced immunostaining of cFos in the CA1 of mice (Chelsea E. Matisz et al. 2022). Interestingly, CA1 hypoactivity was correlated with increased swimming time in the FST in mice exposed to a single 5-day exposure of DSS; here we report increased cFos expression in mice with three cycles of 5-day exposures to DSS, which was accompanied by swimming in the FST equivalent to controls. This suggests neural activity in the CA1 may contribute to mobility in this task. Taken together, the results from these studies suggest that the duration of inflammation differentially modulates neural activity in the CA1 hippocampus. Chronic Gut Inflammation is associated with reduced expression of antioxidant-related genes Reactive oxygen species (ROS) play an essential role in normal physiological processes, including cell signaling, immune responses, and mitochondrial function. However, the accumulation of ROS can lead to cellular damage, a pathological state termed oxidative stress. Antioxidant responses play an important role in maintaining the balance between ROS production and its elimination. The brain is a huge consumer of oxygen; estimates suggest 20% of the body’s oxygen supply is consumed by this organ to support the ATP intensive activities of neurons, despite only accounting for 2% of the body weight (Rolfe and Brown 1997). As such, neurons are especially vulnerable to oxidative damage due to their high oxygen demand, combined with their relatively weak antioxidant defense system (Cobley, Fiorello, and Bailey 2018). Inflammation is energy-intensive; it is estimated that chronic inflammatory diseases can increase energy costs by 10-15% (Straub 2017; Lacourt et al. 2018). Inflammation drives a metabolic switch in astrocytes and microglia towards glycolysis, increasing the production of ATP and the consumption of glucose (L. Wang et al. 2019). Further, inflammation can lead to impairments in glutamate clearance, leading to neuronal excitotoxicity and metabolic dysfunction (Haroon, Miller, and Sanacora 2017).Thus, neuroinflammation places an additional metabolic demand on an already highly metabolic organ, leading to increased risk of oxidative stress, both of which are hypothesized to play a role in the pathophysiology of anxiety, depression, and co­­­­gnitive dysfunction (Black et al. 2015; Bhatt, Nagappa, and Patil 2020; Hovatta, Juhila, and Donner 2010; Guo et al. 2023). Chronic gut inflammation was associated with reduced mRNA expression for Gpx1, the enzyme that contributes to the potent antioxidant activity of glutathione, in the CA1 and the NAc. Reduced expression of the transcription factor Nrf2, which regulates antioxidant expression, was also observed in the CA1. These findings suggest impaired antioxidant responses in the CA1 and NAc of mice with chronic gut inflammation. Mice with acute DSS colitis has increased levels of reactive oxidant-induced protein and lipid modifications in the HPC and striatum, respectively (Hilel et al. 2018). The effects of chronic gut inflammation on antioxidant systems in the brain has not been reported. However, chronic unpredictable stress, which can produce neuroinflammation and similar behavioural phenotypes as chronic inflammation in animal models, was found to reduce activity of glutathione peroxidase in the brain of rats (Che et al. 2015). Interestingly, we observed a positive correlation between Nrf2 and Psd95 among control mice; chronic gut inflammation decoupled this relationship. This aligns with previous studies which suggest that depletion of antioxidant systems can impair synaptic function and plasticity, as observed in rodent models of traumatic brain injury (Ansari, Roberts, and Scheff 2008). Further, Both Nrf2 and Psd95 were reduced in a mouse model of chronic stress, and treatment with the Nrf2 activator oltipraz restored Psd95 expression in the hippocampus(Zeng et al. 2023). Research suggests the brain possesses regional vulnerability to oxidative stress. For example, the literature paints the CA1 as a region that is highly vulnerable to insult. Within the hippocampus, the CA1 and CA3 subfields lie adjacent to each other, and both possess a high density of pyramidal neurons. However, despite these similarities, studies conducted in a diversity of mammalian species (rats, gerbils, primates, humans) using a variety of different methods to generate oxidative stress in the brain demonstrate that CA1 neurons are much more sensitive to oxidative stress relative to their CA3 neuronal counterparts (Bartsch et al. 2015; Kirino 1982; Pulsinelli, Brierley, and Plum 1982; Tabuchi et al. 1992). Molecular mechanisms that ascribe such vulnerability are not completely understood; it has been suggested that high baseline levels of ROS-generating activities (e.g. cellular respiration) within neuronal populations render those neurons more vulnerable to insults, such as neuroinflammation (X. Wang and Michaelis 2010). Extending from this, regions with greater basal levels of oxidative stress should also possess higher basal expression of genes involved in antioxidant responses, such as Nrf2. Indeed, Wang et al . report higher basal expression of Nrf2 in the CA1 than that of the CA3 (X. Wang et al. 2005). In the present study, basal levels of Nrf2 in control mice were significantly higher in the CA1 and NAc compared to the ACC and M1. Further, transcript expression of Gpx1 was significantly higher in the NAc relative to other regions in control mice. Combined, these data support previous assertations that the CA1 maybe especially vulnerable to neuroinflammation relative to other structures. Our results extend upon these studies and suggest the NAc may similarly possess intrinsic vulnerability to the costs of neuroinflammation. Both the Ca1 and NAc represent neural substrates involved in anxiodepressive phenotypes, which are well-established comorbidities in preclinical and clinical studies of IBD (C. E. Matisz and Gruber 2022). The relative vulnerability of neural regions involved in threat-coping and motivation behaviours in the face of chronic neuroinflammation may explain why anxiety and depression emerge in such a wide range of chronic inflammatory diseases, despite their diverse etiology. Further studies are necessary to confirm the oxidative stress vulnerability transcript responses to chronic gut inflammation in other regions known to be involved in anxiety and depression, such as the basal ganglia, prefrontal cortex, and amygdala. Chronic gut inflammation is associated with altered Gad1 expression in the CA1 Disturbed modulation of excitatory circuits by Gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the CNS, is implicated in psychological processes such as anxiety and depression (Möhler 2012; Nuss 2015). GABA synthesis is in part regulated by the rate-limiting enzyme glutamate decarboxylase isoform Gad67, which is encoded by Gad1 mRNA. We report the expression of Gad1 mRNA is significantly increased in the CA1 of mice with chronic DSS exposure. Further, chronic gut inflammation transformed the relationship between the expression of Gad1 and Psd95, and Drp1 in the CA1. The functional significance of these relationships is not clear; however, it suggests an intriguing relationship between post-synaptic density, mitochondrial dynamics, and the GABAergic system in our model. To our knowledge, the effects of gut inflammation on hippocampal GABA expression have not been previously reported. However, research suggests neuroinflammation induced by chronic stress (Lang et al. 2020) and toxin exposure (Nascimento et al. 2022) can alter GABA signaling in the hippocampus by increasing GABA receptor expression and GABA levels, respectively. In vitro studies indicate GABA contributes to neuroinflammation by stimulating the secretion of pro-inflammatory cytokines from microglia (Lang et al. 2020). Using the TNBS model of colitis in rats, Riazi et al. revealed that gut inflammation is associated with increased neuronal excitability in the HPC, and increased susceptibility to seizure that was dependent on microglial activation (Riazi et al. 2008). Specifically microglial activation was increased in the entorhinal cortex, and activation of this region has been shown to promote increased Gad1 mRNA in the CA1 (Falkenberg et al. 1997; Riazi et al. 2008). The entorhinal cortex was not investigated in the present study, but is involved in processing fear responses and anxiety, which we have shown are modulated as a consequence of chronic gut inflammation (C. E. Matisz et al. 2022). Fecal Lcn2 expression is correlated with transcript expression in the ACC, and other regions The ACC, positioned at the interface between the ‘emotional’ limbic system, and the ‘cognitive’ prefrontal cortex, is heavily involved in affective processing. Neuroinflammatory remodeling of the ACC is a key driver of anxiety and depression, and this region is among the most consistently altered neural structures in patients with gastrointestinal diseases and disorders, displaying cortical thinning and hyperactivity (C. E. Matisz and Gruber 2022). Despite evidence that suggests the ACC is heavily involved in the neuropathology comorbid with gut inflammation, the only transcriptional change observed in the ACC on mice with chronic gut inflammation was the reduced expression of Mt-co1. Interestingly, we did note that fecal Lcn2 was most frequently associated with shifts in transcript expression in the ACC; the expression of 4 of 9 transcripts positively correlated with fecal Lcn-2. Fecal Lcn-2 is a well-established biomarker for severity of gut disease in preclinical models, and patients with ulcerative colitis (Chassaing et al. 2012; Hsieh et al. 2016; Buisson et al. 2014). The correlation between fecal Lcn-2 and Drp1 may reflect a relationship between the severity of gut inflammation and increased mitochondrial fission, which aligns with reduced Mt-co1 expression in this region. GABAergic neurons regulate neuronal activity, and their activity in the ACC has been shown to attenuate anxiety in a rodent model of inflammatory pain (Shao et al. 2021); the correlation between fecal Lcn2 and Gad1 in the ACC may reflect a greater need for regulating neuronal activity in the ACC among these animals. The physiological significance of changes in pre and postsynaptic protein transcripts in the ACC, CA1 and M1 as they relate to fecal Lcn-2 levels are not clear. The correlation between fecal Lcn-2 and Psd95 mRNA may reflect visceral pain among more severely inflamed animals; DSS-induced colitis promotes visceral hyperalgesia in mice (Lapointe et al. 2015; Defaye et al. 2022; Esquerre et al. 2020), and PSD95 in the ACC has been shown to contribute to neuropathic pain (Li et al. 2022). Stress and inflammation have also been shown to alter spine morphology in both the ACC and CA1 It is important to note that the current study did not assess post transcriptional modifications or protein expression of the transcripts. Further, the phenotype of cell on which these mRNA transcripts are modified is unknown, which limits the interpretations of these findings. Conclusions Our results indicate chronic gut inflammation is associated with heterogenous changes in the brain, particularly the limbic system. Changes in transcript expression suggest prolonged colitis promotes reduced oxidative phosphorylation, and impaired antioxidant defense systems in the ACC, CA1, and NAc. Our data suggest chronic gut inflammation may alter mitochondrial function and dynamics in regions of the brain that are known to be affected in patients with symptoms of anxiety and depression. This lends support to the literature that proposes a role of altered bioenergetics and mitochondrial dysfunction in the brain of patients with chronic inflammatory diseases, which may play a role in mood disorders that are comorbid in these illnesses. Declarations Acknowledgements We are grateful for Natural Sciences and Engineering Research Council (CEM; PDF, AJG and RJS, discovery grant) and Canada Research Chairs program and Genome Canada BioNet grant (AZ) for financial support of this work. Funding AJS and RJS received an NSERC Discovery Grant from the National Science and Engineering Research Council. AZ is a recipient of the Canada Research Chairs program and Genome Canada BioNet grant. CEM was supported by an NSERC PDF. Competing Interests The authors have no financial or non-financial interests to disclose. Author Contributions CEM and AJG conceptualized the study; CEM, VL, KB, and TH collected, curated and analyzed data; CEM and AJG drafted the manuscript; all authors critically revised and approved the final manuscript for submission. AJG, AZ, and RJS obtained funding and provided oversight and supervision of the study. Ethics Approval All experiments were carried out in accordance with the guidelines of the Canadian Council of Animal Care and were approved by the University of Lethbridge Animal Care Committee (Protocol #2018). Data Availability The datasets generated and analyzed for the current study are included in the supplementary materials. References Allen, Josh, Raquel Romay-Tallon, Kyle J. Brymer, Hector J. Caruncho, and Lisa E. 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Supplementary Files CM26112022DRP1analysis.xlsx CM26112022MFN2analysis.xlsx CM26112022MitConanalysis.xlsx CM27112022Gadanalysis.xlsx CM27112022Gshpanalysis.xlsx CM27112022NRF2analysis.xlsx SupplementaryFigsandTables.pdf CM27112022SNAP25analysis.xlsx CM27112022Psd95analysis.xlsx CM27112022cFosanalysis.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4486754","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":329536932,"identity":"6342bb1b-6e8a-416e-9c4d-89d8bcbc9d68","order_by":0,"name":"Chelsea E MATISZ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3Pv0sDMRTA8XcEesuzXQP1x18gBIRMcn9HxzsCnQquQg9aENKxa/+chEC6lN564GI5cK5bhCLmhIIOiY4O+ULgPciHEIBU6h822kCmzosf7mEIMIgS2n7d7CP9MPX3SZywyTfiM38g4yel3WMBt6tGa3dqKpmv7QvURZhc2tLgTgD3xyA+VxJNzsCKMKEzZjJJgCtPgHpCxYBmSxIhD0f9/rEA3nSgHdtX8qbrySLy/Rmoi6UB3gpQWCr/CumJCRLaTplBu0Xedn5Q4k6i4LS02yAZbcTh4Or5NW+q7s2diqt1rl/psZ4HyTn8uZa/glQqlUrF+gSUoFW8ZvJgIwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Lethbridge","correspondingAuthor":true,"prefix":"","firstName":"Chelsea","middleName":"E","lastName":"MATISZ","suffix":""},{"id":329536933,"identity":"bc83c372-4828-48b0-aadf-7a60fb8caa1f","order_by":1,"name":"Valerie LAPOINTE","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Valerie","middleName":"","lastName":"LAPOINTE","suffix":""},{"id":329536934,"identity":"44adea50-b383-4b6c-9d17-355c908b6d7a","order_by":2,"name":"Kaylen BEEKMAN","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Kaylen","middleName":"","lastName":"BEEKMAN","suffix":""},{"id":329536935,"identity":"3ed34e47-e889-47c6-96e1-38a0c306a565","order_by":3,"name":"Travis HAIGHT","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Travis","middleName":"","lastName":"HAIGHT","suffix":""},{"id":329536936,"identity":"55dc4393-62b3-4b69-8aa3-3cc4a93f8ee6","order_by":4,"name":"Robert J SUTHERLAND","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"J","lastName":"SUTHERLAND","suffix":""},{"id":329536937,"identity":"6dee1095-69b5-4cb0-8cc5-d6ee25e35d60","order_by":5,"name":"Athanasios ZOVOILIS","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Athanasios","middleName":"","lastName":"ZOVOILIS","suffix":""},{"id":329536938,"identity":"2a7786e1-1364-4439-9e4b-65ac2fa05f9e","order_by":6,"name":"Aaron J GRUBER","email":"","orcid":"","institution":"University of Lethbridge","correspondingAuthor":false,"prefix":"","firstName":"Aaron","middleName":"J","lastName":"GRUBER","suffix":""}],"badges":[],"createdAt":"2024-05-27 19:08:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4486754/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4486754/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":61866790,"identity":"34508ab1-321c-40c4-a733-5c08a7a969b7","added_by":"auto","created_at":"2024-08-06 12:19:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":74961,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExperimental Timeline\u003c/strong\u003e Male mice were exposed to three cycles of 3% DSS in their drinking water for 5 days, followed by regular drinking water. Fecal samples were collected on days 1, 7, 14, 28, 35, and 42. On day 42 mice were subjected to forced swim task, humanely euthanized, and brains extracted for PCR analysis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/eb27dfb638bfa9741bc5fffe.png"},{"id":61866223,"identity":"b7d066c4-e73f-427b-ba49-83f40b2da08d","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102794,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExposure to DSS produces typical signs of gut inflammation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Change in weight throughout the duration of the experiment. (B) Disease activity score at peak disease (day 34) on third cycle of DSS exposure. (C) Fecal Lcn-2 expression throughout the study. (D) Colon length at time of necropsy (day 42). (E) Time spent swimming in a forced swim task. Data are mean ± SEM; n=8 male mice per treatment group. P\u0026lt;0.05\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/61139bb7c47a16d3d8a79b76.png"},{"id":61866221,"identity":"0bd3fe96-9974-44b4-b104-e1a3c4993338","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":134576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of mRNA transcripts in four brain structures in control and mice with chronic DSS colitis\u003c/strong\u003e (A) The approximate location of tissue punches in coronal mouse brain sections used for downstream PCR analysis. (B) Mean expression of mRNA transcripts, using Hprt as a reference gene, in the ACC, CA1, NAc, and M1. (C) Average change in mean gene expression relative to controls in mice with chronic DSS-induced colitis. Data represent mean ± SEM. *p\u0026lt;0.05, n=6 per treatment group. Treatment comparisons analyzed by t-test. T stat and p values can be found in Table 3.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/99b2967a0f42525209ea14b7.png"},{"id":61867657,"identity":"d6ddaafe-e9db-40e5-9830-372e6da8e15d","added_by":"auto","created_at":"2024-08-06 12:27:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":177739,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrincipal component analysis (PCA) of mRNA transcript expression (row labels) from brain samples (column labels)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/6a33b15040193199138ae4a3.png"},{"id":61866228,"identity":"e57cee6f-9087-49b8-94a6-3ebeeda7e398","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":155098,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePearson correlation coefficients of mRNA transcript expression in brain structures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePearson correlation analysis of transcript expression within a given brain region, in mice with gut inflammation and healthy controls. N=6 per treatment group. *p\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/61c3a17fd86f309fe43b97c6.png"},{"id":61866786,"identity":"aa38e73e-10af-4f75-8d05-974194669fcb","added_by":"auto","created_at":"2024-08-06 12:19:28","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":73142,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGut inflammation is associated with an inverse in the relationships between multiple transcripts in the NAc, relative to controls \u003c/strong\u003eExpression of (A) Drp1, (B) Mfn2, (C) Gad1, and (D) Psd95 as a function of Mt-Co1 in the NAc among mice with gut inflammation and healthy controls. Transcript expression normalized to expression of Hprt. N=6 mice/group. Linear regression and Pearson R coefficients are outlined in Table 4.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/792645ef57c6e8bb16e7b36e.png"},{"id":61868172,"identity":"24e1f73c-609c-47e7-a682-76b26f7b189d","added_by":"auto","created_at":"2024-08-06 12:35:28","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":19353,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation between Nrf2 and Psd95 expression among control and DSS animals, in the CA1 \u003c/strong\u003e​\u003c/p\u003e\n\u003cp\u003eExpression of Psd95 as a function of Nrf2 among control and DSS animals in the CA1 N=6 animals per group. Transcript expression normalized to expression of Hprt. Pearson R and p values for all comparisons can be found in Supplementary Table 4.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/5b6ae9dd82c7b3592a1d1f2f.png"},{"id":61866230,"identity":"f4526a06-14a4-4b56-8714-d7d8c754bced","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":61953,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation coefficient between mRNA transcript expression in different regions of the brain and fecal Lcn-2 among mice with DSS-induced colitis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePearson correlation of transcript expression in different brain structures and fecal Lcn-2 levels among mice with gut inflammation. N=6, *p\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/bc43ef2ee590ae680f892c21.png"},{"id":78856181,"identity":"5a7a2340-7765-4e48-ab31-a0319778efce","added_by":"auto","created_at":"2025-03-19 22:46:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2148903,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/4c66f99b-abf5-4e2f-bb71-5bf2159cbff4.pdf"},{"id":61868961,"identity":"a6efca9b-e939-4c54-a9d7-a1c34c9f3230","added_by":"auto","created_at":"2024-08-06 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12:19:28","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":230983,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigsandTables.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/8fda0fd052874e2815f4e632.pdf"},{"id":61866242,"identity":"3f7c09b8-4c22-4e77-be66-bcab7b10396b","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":104537,"visible":true,"origin":"","legend":"","description":"","filename":"CM27112022SNAP25analysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/e51a199c2afb6bd207bc63ca.xlsx"},{"id":61868960,"identity":"c2d2ad5a-78d6-448f-b0a4-cc040e6cfc9f","added_by":"auto","created_at":"2024-08-06 12:43:28","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":98860,"visible":true,"origin":"","legend":"","description":"","filename":"CM27112022Psd95analysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/abb51e9c7d04b42bac892191.xlsx"},{"id":61866237,"identity":"f0d89d0c-f743-4cf6-aa0a-05078714d6c8","added_by":"auto","created_at":"2024-08-06 12:11:28","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":104938,"visible":true,"origin":"","legend":"","description":"","filename":"CM27112022cFosanalysis.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4486754/v1/36a9c8cfdef794bb3813dca8.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Chronic gut inflammation differentially modulates mitochondrial and antioxidant transcriptional programs in limbic brain structures","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eInflammation appears to promote anxiety and depression, likely by altering neurophysiological processes. This may contribute to the high comorbidity of anxiety and depression in chronic inflammatory diseases such as diabetes (Castellano-Guerrero, Guerrero, and Relimpio \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), rheumatoid arthritis (Isik et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), and cardiovascular diseases (Celano et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Such comorbidity is particularly high in people with inflammatory bowel disease (IBD). Approximately 57% of people with active IBD experience anxiety, and 39% have symptoms of depression (Barberio et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Importantly, these mood disorders persist even during periods of disease remission (Barberio et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This suggests that chronic somatic inflammation can produce changes in the brain that persist after peripheral inflammation subsides. Neuroinflammation is a likely intermediary. Even transient inflammation in the gut produces a neuroinflammatory response in the brain, leading to changes in behaviour (Emge et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Jain et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Chelsea E. Matisz et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and an array of changes in neural physiology (Chelsea E. Matisz et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Riazi et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Zonis et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Several of these physiological changes are associated with anxiety and depression, including oxidative stress, mitochondrial dysfunction, changes in neural structure, altered neural activity, and neurotransmitter levels(Salim \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Y. Liu, Zhao, and Guo 2018; Guo et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Allen et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rezin et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) The diversity and complexity of neuroinflammatory-evoked changes in neural physiology complicates a straightforward theory for the cellular etiology of anxiety and depression. We and others have proposed that bioenergetics and its regulation by reactive oxygen species in a key brain circuit called the limbic system are a core feature that may account for many phenomena (C. E. Matisz and Gruber \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Picard and McEwen 2018).\u003c/p\u003e \u003cp\u003eThe brain\u0026rsquo;s high energy demand is predominantly met by mitochondria, the largest cellular source of ATP. Mitochondria activity influence a variety of processes related to neural structure, function, and circuity, including dendritic and axonal branching (Courchet et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gebara et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and neurotransmitter synthesis (Kwon et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The metabolic needs of the brain are both spatially and temporally variable, as evidenced by functional and molecular evidence (Castrillon et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For example, the energetic costs of stress and inflammation can deplete metabolic resources in the brain if they reach sufficient magnitude and duration (Lacourt et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Straub \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). It has been proposed that prolonged downregulation of energy production in the brain can promote alterations in neuronal architecture and plasticity that promote anxiety and depression (Morava and Kozicz 2013; Picard et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Specific regions of the brain appear to be more liable to this process. For example, clinical and preclinical studies indicate that certain structures within the limbic system, such as the hippocampus (Bagot et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Haj-Mirzaian et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), anterior cingulate cortex (C. E. Matisz and Gruber \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; J. Wang et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), and nucleus accumbens (Gebara et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Strasser et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) are associated with changes in brain metabolism that appear to promote anxiety and depressive behaviours (Duman et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Moreover, the phenotype of mitochondria varies among brain structures, as does the mitochondrial sensitivity to stressors and endocrines; notably, stress induced changes to identified \u0026lsquo;mitochondrial networks\u0026rsquo;, which correlated with anxiety-like behaviours in mice (Rosenberg et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Whereas structure-specific effects of chronic stress on mitochondrial function have been reported, the consequences of gut inflammation on brain mitochondria have received less attention. We and others hypothesize that chronic neuroinflammation may have a similar effect on mitochondrial function as stress (Zhao et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Culmsee et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMuch of the previous work on gut inflammation-induced neuroinflammation has employed relatively brief inflammatory treatments. Our previous research has demonstrated that the duration of gut inflammation influences its behavioural effects. Short-term gut inflammation (1 week) produced deficits in learning and memory, and increased motoric response in a forced swim task. These behavioural changes, however, were not observed in mice with chronic gut inflammation (5 weeks) (Chelsea E. Matisz et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In other words, it appears that the mnemonic and motoric alterations were transient effects triggered by the onset of inflammation. Conversely, increased contextual fear only emerged in chronic gut inflammation (C. E. Matisz et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). These data suggest that the neural circuits that encode some behaviours (e.g. contextual fear memory) are only affected by prolonged inflammation, possibly by the accumulated effects of neuroinflammation over many weeks. Here, we test the hypothesis that the accumulated effects of gut inflammation involve decreased mitochondrial function in \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003elimbic brain structures\u003c/span\u003e more so than in \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003enon-limbic structures\u003c/span\u003e, and that reduced metabolic function will be associated with changes in cellular physiology and metabolics, such as the management of oxidative stress.\u003c/p\u003e"},{"header":"2 Materials and Methods","content":"\u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eAnimals\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe study used 16 male C57Bl/6 mice (8 weeks old, Jackson Laboratories, Bar Harbor, ME, USA). Mice were housed in groups of four in standard clear plastic cages in a vivarium with a 12-h light/dark cycle, with free access to standard mouse chow and drinking water. Animals were acclimatized to the facility for 2 weeks prior to the start of experimentation. All experiments were carried out in accordance with the guidelines of the Canadian Council of Animal Care, and were approved by the University of Lethbridge Animal Care Committee (Protocol #2018).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eColitis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFor the induction of chronic DSS colitis, mice were exposed to three cycles (3% wt/v) of DSS (MW 40kD; Fischer Scientific, CAT 9011-18-1) each lasting five days, with 9 days of recovery (access to regular drinking water) between cycles. Control mice received regular drinking water for the duration of the experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eForced Swim Task\u003c/span\u003e \u003c/p\u003e \u003cp\u003eThe forced swim task was conducted on day 42. Mice were placed in a clear glass cylinder (30cm tall, 15 cm diameter) filled 14cm deep with water (28C) and video recorded for 6 minutes. Mice were monitored continuously. Any animal unable to keep its head above water was immediately removed from the cylinder. After completing the task, mice were removed, dried with a paper towel, and placed in a cage with a heating pad before being returned to the home cage. Immobility time was defined by minimal movements to keep its head above water, recorded by an observer blind to the experimental treatment. Each mouse was euthanized 30 minutes after its completion of the FST, and the brain was quickly snap frozen. The timing of testing, euthanasia, and brain freezing was kept as constant as possible among animals in order to normalize any effects of stress and/or motoring output (swimming) on gene expression.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eColitis Assessment\u003c/span\u003e:\u003c/p\u003e \u003cp\u003eDisease activity was assessed on the third cycle of DSS and scored as previously described (Matisz et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Briefly, percentage of body weight lost from the start of the cycle on day 28 scored on a 1\u0026ndash;4 range based on the percentage of body weight lost (0\u0026thinsp;=\u0026thinsp;0%, 1\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;1 to \u0026le;\u0026thinsp;5%, 2\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;5 to \u0026le;\u0026thinsp;10%, 3\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;10 to \u0026le;\u0026thinsp;15%, 4\u0026thinsp;=\u0026thinsp;\u0026gt;\u0026thinsp;15%); stool consistency (solid fecal pellets\u0026thinsp;=\u0026thinsp;0, soft, sticky stools\u0026thinsp;=\u0026thinsp;2, loose, water stools\u0026thinsp;=\u0026thinsp;4); and the presence of fecal blood (no blood\u0026thinsp;=\u0026thinsp;0, fecal blood\u0026thinsp;=\u0026thinsp;4). The total disease score was computed as a weighted average of each of these three measures. After euthanasia, the length of the colon was measured from anus to ileocecal junction.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eTissue Collection\u003c/span\u003e \u003c/p\u003e \u003cp\u003eMice were euthanized 30 minutes post forced swim task on day 42 by induction into an isoflurane chamber and subsequent injection with ~\u0026thinsp;1.6mL/kg euthanyl (Bimeda MTC 00141704). Brains were immediately removed and snap-frozen via immersion into pre-chilled isopentane for 60\u0026ndash;120 seconds and subsequently stored at -80\u0026deg;C until downstream processing. Tissue punches were obtained following protocols outlined by Wager-Miller et al.. (Wager-Miller et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). All tools and surfaces were cleaned using RNaseZap\u0026trade; RNase Decontamination Solution and UltraPure\u0026trade; DNase/RNase-Free Distilled Water (Thermofisher scientific).\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eELISA\u003c/span\u003e \u003c/p\u003e \u003cp\u003eFecal lipocalin-2 is a biomarker for intestinal inflammation in both humans and rodents. Samples were prepared following previously published protocols (C. E. Matisz et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Briefly, frozen fecal samples were reconstituted in PBS with 1% Tween 20 (10mg/100uL), and vortexed for 20 minutes. Samples were centrifuged for 10 minutes at 12,000 rpm, and supernatants were collected and stored at -20◦C until analysis. At baseline, all processed fecal samples were diluted at 1:1 in reagent diluent. Moving forward, all fecal samples from mice exposed to DSS were diluted at 1:1250 in reagent diluent to ensure optical density was within limits of detection of the standard curve. Lipocalin-2 levels were quantified in the supernatants using the DuoSet murine Lcn-2 ELISA Kit (R\u0026amp;D Systems, Minneapolis, MN), following the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eRNA isolation and RT-PCR\u003c/span\u003e \u003c/p\u003e \u003cp\u003eRNA was extracted using the standard Trizol reagent protocol (Cat # 1596026, Invitrogen) and reverse transcribed using Superscript IV (CAT 18090010, Invitrogen) by the following method: 100ng of total RNA was mixed with 100ng Random Primer Mix (S1330S, NEB), and 1 uL of 10mM dNTP mix (CAT N0447S, NEB). The mixture was incubated for 5 min at 65\u0026deg;C and placed immediately on ice for a minimum of 1 minute. The mixture was then incubated with 4uL of 5X Superscript IV buffer, 1uL of 0.1M DTT, and 1uL of Superscript IV (200U/uL) for 10 min at 25\u0026deg;C, 10 min at 55\u0026deg;C and 10 min at 80\u0026deg;C. The produced cDNA was analyzed by qPCR using 2uL of 1:10 diluted cDNA, 0.5uL of each gene-specific primer diluted to 10uM, 5uL of Luna Universal qPCR master Mix (M3003E, NEB), and 2uL of H2O. qPCR was performed using the Bio-Rad CFX384 Real-time detection system, with the following thermocycler conditions: 3 min at 95\u0026deg;C (15 s at 95\u0026deg;C, 30 s at 54\u0026deg;C, 30 s at 66\u0026deg;C) \u0026times; 40 cycles. Fluorometer readings were taken during the extension phase, while standard curves were prepared for relative expression. The analysis of PCR efficiency was achieved by pooling 2uL of each cDNA sample and the subsequent preparation of standard dilutions SD1: 1:2; SD2: 1:4; SD3: 1:8; SD4: 1:16; SD5: 1:32. All samples were run in triplicate. Quantitative measurements of target gene expression relative to controls followed the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method. Group differences were expressed as fold changes, normalized to the housekeeping gene hypoxanthine phosphoribosyltransferase (Hprt). Gene-specific primers were ordered from IDT (USA, CO) as custom DNA oligos. The sequences of primers used are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of RNA primers used in study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGene\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eForward primer (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eReverse primer (5\u0026rsquo;-3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDRP1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eATG CCA GCA AGT CCA CAG AA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTGT TCT CGG GCA GAC AGT TT\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMFN2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTGC ACC GCC ATA TAG AGG AAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTCT GCA GTG AAC TGG CAA TG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMtCO1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACC CAA TCA AAC GCC TAG CA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGA CTG GAA TGC TGG TTG G\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGPX1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCT CAA GTA CGT CCG ACC TG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAA TGT CGT TGC GGC ACA CC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eNRF2\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTAG ATG ACC ATG AGT CGC TTG C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGCC AAA CTT GCT CCA TGT CC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGAD1\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCC TGG TTG ACT GTA GAG ACA C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCAT ATT GGT ATT GGC AGT CGA T\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCFOS\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTTT TGC GCA GAT CTG TCC GT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGTG GGG AGT CCG TAA GGA TG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSNAP25\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGTG CAC TTA GGG TGC GGT AT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eATC TCC TCC AGC TCA TTG CG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePSD95\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCT GTG CGA GAG GTA GCA GA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAAG CAC TCC GTG AAC TCC TG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eStatistical analysis\u003c/span\u003e \u003c/p\u003e \u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Body weight was analyzed by a two-way repeated measures ANOVA with Sidak post-test, and Lcn-2 expression analyzed by mixed effects analysis with a Tukey\u0026rsquo;s comparison post-test. Disease activity index was analyzed by One Sample Wilcoxon Signed ranked Test. Comparisons of the mean between groups was analyzed via Student\u0026rsquo;s t-test or One-Way ANOVA with Tukey\u0026rsquo;s post-test. Principal component analyses (PCA) were used to generate plots to visualize clustering between treatment groups. Primary and secondary principal components were compared via Mann-Whitney between DSS and control groups. Significant differences between the first or second principal component are reported. Statistical analyses were conducted with GraphPad Prism 10.0.0 (GraphPad Software, La Jolla, CA). Figures created with BioRender.com and Adobe Photoshop.\u003c/p\u003e"},{"header":"3 RESULTS","content":"\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eExposure to DSS produces signs of gut inflammation and disease\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eDextran Sodium Sulfate is widely used to model gut inflammation in rodents, with excellent face validity (Chassaing et al. \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). In our study, exposure to DSS in the drinking water led to expected signs of disease. Mice exposed to DSS for 3 cycles exhibited significant weight loss relative to controls (Two-way Rm ANOVA F\u003csub\u003e1,14\u003c/sub\u003e = 41.48, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA). Further, expression of the pro-inflammatory mediator lipocalin-2 (Lcn2) was significantly elevated in the feces among DSS-treated mice throughout the study (Mixed-effects model F\u003csub\u003e1,14\u003c/sub\u003e=19.70, p\u0026thinsp;=\u0026thinsp;0.0006; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB). The disease activity index was increased after final cycle of DSS in DSS-treated animals compared to controls (One way Wilcoxon Signed Rank Test, W\u0026thinsp;=\u0026thinsp;36, p\u0026thinsp;=\u0026thinsp;0.0078; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC). Colon length was reduced, but not significantly, among mice exposed to DSS (Students t-test, t\u0026thinsp;=\u0026thinsp;1.064; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD). Overall, mice chronically exposed to DSS exhibited increased weight loss, disease activity, and increased fecal lipocalin-2 expression relative to controls, indicating that DSS treatment evoked the expected inflammation in the gastrointestinal tract.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eTranscript Selection\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe objective of the study was to determine if DSS-colitis more strongly affects neurons in brain regions associated with anxiety and depression (e.g. limbic structures) as compared to other structures. Four brain regions were selected, based on their well-recognized role in goal-directed and threat-coping behaviors that are altered in anxiety and depression; the CA1 of the hippocampus, the ACC, and the NAc. The motor cortex (M1) was selected as a control region (Supplementary Fig. 1). A panel of 9 different primers were selected to assess several transcriptional programs in neurons that may be modulated by gut inflammation (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Three transcripts were selected to assess how gut inflammation may affect mitochondrial function in the brain. Inflammation has been shown to affect mitochondrial network dynamics and mitochondrial function. Mitochondria form dynamic networks that undergo fusion and fission to maintain cellular energetic requirements. These structural changes are mediated by several fusion and fission proteins, including Mfn2, and Drp1, respectively. Mt-Co1 encodes for a subunit of complex IV in the electron transport chain in mitochondria, by which the process of oxidative phosphorylation generates cellular energy in the form of ATP. Thus, its expression regulates energy production in mitochondria. Inflammation can promote oxidative stress. Therefore, we selected two transcripts to assess how gut inflammation affects oxidative stress responses in the brain. Nuclear factor erythroid 2 related factor 2 (Nrf2) regulates antioxidant response elements, while Gpx1 encodes for glutathione peroxidase 1, an enzyme that works with glutathione as a key neuronal antioxidant. Our previous research has revealed that acute DSS alters spine density in CA1, as well as the fraction of neurons activated by the forced swim task (Chelsea E. Matisz et al. \u003cspan class=\"CitationRef\"\u003e2022\u003c/span\u003e). Therefore, to assess how chronic DSS may affect pre- and post-synaptic elements and neuronal activation, we assessed transcript expression of Snap25, Psd95, and cFos. Animals were subjected to a 6-minute forced swim task (FST) prior to euthanization in order to (i) test for changes in active threat coping or depressive endophenotypes, and (ii) provide a stressor to activate neurons in the limbic system and motor cortex. Mice previously given DSS exhibited similar mobility time during the FST relative to controls (t\u0026thinsp;=\u0026thinsp;0.43; Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE), in alignment with previous reports (Chelsea E. Matisz et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Finally, because GABAergic transmission has been implicated in anxiety and depression, we assessed Gad1 expression. Gad1 mRNA encodes for the rate-limiting enzyme glutamate decarboxylase 67, which is responsible for over 90% of basal GABA synthesis (Asada et al.\u0026nbsp;\u003cspan class=\"CitationRef\"\u003e1997\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eList of selected genes examined in the present study and their function\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene name (transcript)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFunction\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMfn2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMitofusin2; Regulates mitochondrial fusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDrp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDynamin-related protein; Regulates mitochondrial fission\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-Co1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCytochrome C oxidase subunit I; Mitochondria-encoded gene important for oxidative phosphorylation and ATP production\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCFos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly immediate gene, expressed by recently activated cells, inducing neurons\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGad1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrecursor to GABA, inhibitory neurotransmitter\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNrf2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNuclear factor erythroid 2-related factor 2; Regulates cellular defense against oxidative stress\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGpx1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGlutathione peroxidase; antioxidant enzyme\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePsd95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostsynaptic density 95kda; regulates retention of glutamate receptors\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSnap25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSynaptosome associated protein 25kda; participates in synaptic vesicle exocytosis of neurotransmitters\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eRegional differences in basal transcript expression\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWe first examined how expression of the selected transcripts varied among brain structures in control animals (Supplementary Fig.\u0026nbsp;2; Supplementary Table\u0026nbsp;1). The NAc exhibited an expression profile that most differed from the other structures. The expression of Gad1 (F\u003csub\u003e3,20\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;29.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) was significantly highest in the NAc relative to all other structures (Tukey\u0026rsquo;s test for ACC and Ca1, NAc, and M1 are all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This is not surprising, as GABAergic medium spiny neurons are the dominant neuronal cell in the striatum (Yager et al. \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Interestingly, the NAc also possessed highest expression of Gpx1 (F\u003csub\u003e3,20\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;76.18, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) relative to all other structures (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). The NAc expressed significantly higher expression of Mt-Co1 (F\u003csub\u003e3,20\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;7.554, p\u0026thinsp;=\u0026thinsp;0.0014) and Psd95 (F\u003csub\u003e3,20\u003c/sub\u003e)\u0026thinsp;=\u0026thinsp;8.062, p\u0026thinsp;=\u0026thinsp;0.0010) compared to the ACC (Mt-co1, p\u0026thinsp;=\u0026thinsp;0.0060; Psd95, p\u0026thinsp;=\u0026thinsp;0.0013) and M1 ( Mt-co1, p\u0026thinsp;=\u0026thinsp;x ; Psd95, p\u0026thinsp;=\u0026thinsp;0.0033, and significantly lower expression of Snap25 relative to CA1 and M1. The CA1 and NAc displayed lowest expression of cFos relative to the ACC and MA (F\u003csub\u003e3,20\u003c/sub\u003e=12.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; CA1 vs. ACC p\u0026thinsp;=\u0026thinsp;0.0004; CA1 vs. M1, p\u0026thinsp;=\u0026thinsp;0.0026; NAc vs. ACC p\u0026thinsp;=\u0026thinsp;0.002, NAc vs. M1 p\u0026thinsp;=\u0026thinsp;0.014), and highest expression of Nrf2, relative to the ACC and M1 (F\u003csub\u003e3,20\u003c/sub\u003e=20.30, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; CA1 vs. ACC p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; CA1 vs. M1 p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001; NAc vs ACC p\u0026thinsp;=\u0026thinsp;0.002; NAc vs. M1 p\u0026thinsp;=\u0026thinsp;0.0053). No differences in the expression of Mfn2 (F\u003csub\u003e3,20\u003c/sub\u003e=0.6606, p\u0026thinsp;=\u0026thinsp;0.59) and Drp1 (F\u003csub\u003e3,20\u003c/sub\u003e=1.070, p\u0026thinsp;=\u0026thinsp;0.38) were observed among neural structures in control animals.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eGut inflammation alters expression of selected gene transcripts in regional manner\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWe next compared the structure-specific expression of transcripts between treatment groups. Exposure to DSS altered the expression of several transcripts, in a region-specific manner (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). The CA1 of the HPC was most affected by exposure to DSS; expression of 6 of the 9 transcripts were different (Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB,C). Specifically, cFos (t\u0026thinsp;=\u0026thinsp;2.94, p\u0026thinsp;=\u0026thinsp;0.015), Drp1 (t\u0026thinsp;=\u0026thinsp;2.64, p\u0026thinsp;=\u0026thinsp;0.025), Gad1 (t\u0026thinsp;=\u0026thinsp;2.27, p\u0026thinsp;=\u0026thinsp;0.046) and Snap25 (t\u0026thinsp;=\u0026thinsp;2.29, p\u0026thinsp;=\u0026thinsp;0.045) expression was significantly elevated in the CA1 among DSS-treated mice relative to controls. Conversely, Nrf2 (t\u0026thinsp;=\u0026thinsp;3.91, p\u0026thinsp;=\u0026thinsp;0.0029) and Gpx1 (t\u0026thinsp;=\u0026thinsp;6.707 p\u0026thinsp;=\u0026thinsp;0.000053) were significantly reduced in the CA1 of DSS-treated mice. Mt-Co1 approached significance (t\u0026thinsp;=\u0026thinsp;2.092, p\u0026thinsp;=\u0026thinsp;0.063). The expression of Mt-Co1 was significantly reduced in the NAc (t\u0026thinsp;=\u0026thinsp;5.19, p\u0026thinsp;=\u0026thinsp;0.00041) and ACC (t\u0026thinsp;=\u0026thinsp;2.722, p\u0026thinsp;=\u0026thinsp;0.021), and Gpx (t\u0026thinsp;=\u0026thinsp;1 3.29, p\u0026thinsp;=\u0026thinsp;0.0082) was significantly reduced in the NAc of mice with DSS relative to controls (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eB,C). Treatment did not significantly affect the expression of any selected transcripts in the M1. These data indicate that chronic gut inflammation promotes heterogenous responses of different transcripts that vary among brain regions.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eT-test and p-value for comparisons between control and DSS exposed animals in different regions\u003c/strong\u003e N\u0026thinsp;=\u0026thinsp;6 male mice per treatment group. Data shown in Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGene\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRegion\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eT ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eDrp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMfn2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMt-Co1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eC-fos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eGad1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eGpx1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eNrf2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003ePsd95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eSnap 25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eACC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNAc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eGut inflammation drives regional changes in transcriptional programs in the brain\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eTo better understand how transcriptional programs were differentially affected by gut inflammation, we conducted principal component analysis (PCA). When all gene transcripts were loaded (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eA), and transcript expression from all brain regions are included in the PCA, clear clustering among mice with DSS colitis vs control emerged (p\u0026thinsp;=\u0026thinsp;0.0022). Further, when PCA loadings were restricted to transcript expression within specific brain regions, there were significant differences between control and DSS animals in the CA1 (p\u0026thinsp;=\u0026thinsp;0.0022) and NAc (p\u0026thinsp;=\u0026thinsp;0.015). When only transcripts related to mitochondrial function (Drp1, Mfn2, Mt-Co1) were loaded into the PCA analysis, there was a significant difference in PC1 between control and DSS mice among all brain regions; and upon separation of structure in the analysis, there were significant differences between principal components of control and DSS mice in the CA1 (P\u0026thinsp;=\u0026thinsp;0.015), and PC2 NAc (p\u0026thinsp;=\u0026thinsp;0.0043) (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eB). Similarly, PCA of transcripts related to inflammation regulation (Gpx1, Nrf2) revealed significant differences between the PC1 of controls and DSS among all brain regions (p\u0026thinsp;=\u0026thinsp;0.0022; Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eC). This significance persisted when the PCA only included transcript expression from the CA1 (p\u0026thinsp;=\u0026thinsp;0.0022) and the NAc (p\u0026thinsp;=\u0026thinsp;0.026). The expression of transcripts related to pre- and post-synaptic density proteins did not reveal any significant clustering of principal components (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eD).\u003c/p\u003e\n\u003cp\u003eAll genes include Mfn2, Drp1, Mtco1, CFos, Gad1, Gpx1, Nrf2, Snap25, and Psd95. Genes related to mitochondrial function include Drp1, Mfn2, Mt-Co1. Genes related to antioxidant regulation include Nrf2 and Gpx1. Pre and post-related synapse genes include post-synpatic (Psd95) and pre-synaptic (Snap25) mechanisms. The percentage of variation explained by the principal component is indicated on the axis. N\u0026thinsp;=\u0026thinsp;6 male mice per treatment group. Ellipses indicate significant differences between the first or second principal component (*p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between treatment groups.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eCorrelations between transcript expression within brain regions among healthy and gut-inflamed animals\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWe next tested if gut inflammation affects the relationships (i.e. correlations) between expression among transcripts within each brain structure. DSS treatment did have structure-dependent effects on the correlation among transcript levels (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003ePearson correlation analysis of transcript expression within a given brain region, in mice with gut inflammation and healthy controls. N\u0026thinsp;=\u0026thinsp;6 per treatment group. *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\n\u003cp\u003eAnimals with gut inflammation displayed significantly different relationships between several transcripts in the NAc relative to healthy controls (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). Interestingly, the expression of MtCo-1 was a common denominator for all these relationships. We observed a significant positive correlation with Mt-Co1 and Drp1 (p\u0026thinsp;=\u0026thinsp;0.048, r2\u0026thinsp;=\u0026thinsp;0.67; Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eA), Mfn2 (p\u0026thinsp;=\u0026thinsp;0.015, r2\u0026thinsp;=\u0026thinsp;0.81; Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eB) and Gad1 (p\u0026thinsp;=\u0026thinsp;0.030, r2\u0026thinsp;=\u0026thinsp;0.73, Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eC), with a similar trend observed with Psd95 (p\u0026thinsp;=\u0026thinsp;0.067; Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003eD). A negative relationship between Mt-co1 and Drp1, Mfn2, Gad1, and Psd95 was observed among controls, with the latter reaching statistical significance (p\u0026thinsp;=\u0026thinsp;0.016, r2\u0026thinsp;=\u0026thinsp;0.80; Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation between Mt-Co1 and Drp1, Mfn2, Gad1, and Psd95 among different treatment groups, within the NAc\u003c/strong\u003e Pearson correlation and linear regression; n\u0026thinsp;=\u0026thinsp;6 per treatment group. Data shown in Fig. \u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComparison within NAc\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePearson r\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLinear Regression r\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Drp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Drp1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong DSS *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Mfn2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Mfn2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong DSS *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Gad1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Gad1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong DSS *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Psd95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong controls*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMt-co1 vs. Psd95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmong DSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWithin the CA1, expression of Psd95 was positively correlated with Nrf2 among controls (p\u0026thinsp;=\u0026thinsp;0.012, r\u0026thinsp;=\u0026thinsp;0.91), but not DSS animals (p\u0026thinsp;=\u0026thinsp;0.64, r=-0.24; Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e). No significant relationship between Psd95 and Nrf2 was observed for any other regions, among control of DSS mice. We observed a significant correlation between the expression of Psd95 and Gad1 among control and DSS animals in the M1 and the NAc, among DSS animals in the ACC, and among controls in the CA1 (Supplementary Table 2). However in the CA1, among animals with DSS, the positive relationship between these genes was lost, and trended towards a negative correlation, although this did not reach statistical significance. The expression of Drp and Gad1 were positively correlated with each other among controls, in all limbic regions, but not M1 (Supplementary Table 3). This positive correlation was maintained in mice with DSS in the ACC, with similar trends in the NAc and the M1. Conversely, exposure to DSS was associated with a negative correlation between Drp and Gad1 in CA1 (Supplementary Table 3).\u003c/p\u003e\n\u003cp\u003eExpression of Psd95 as a function of Nrf2 among control and DSS animals in the CA1 N\u0026thinsp;=\u0026thinsp;6 animals per group. Transcript expression normalized to expression of Hprt. Pearson R and p values for all comparisons can be found in Supplementary Table\u0026nbsp;4.\u003c/p\u003e\n\u003cp\u003eIn the motor cortex and the NAc, DSS animals exhibited a significant positive correlation between MtCo1 and Gad (p\u0026thinsp;=\u0026thinsp;0.030 r\u0026thinsp;=\u0026thinsp;0.85); this relationship did not exist among controls, trending towards a negative correlation in the NAc (p\u0026thinsp;=\u0026thinsp;0.065, r=-0.78) (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). No such relationships between transcript expression in the ACC were affected by gut inflammation.\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eCorrelations of transcript expression between brain structures, among control and DSS animals\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eTo examine the possibility that gut inflammation affects the way the expression of a given transcript between two structures are related, we analyzed the relationship between transcript expression among different brain structures. Correlations of the same gene transcript between different regions are listed in Supplementary Table\u0026nbsp;5. Treatment status affected the correlation of transcripts related to GABA synthesis, mitochondrial function, and synapse function between brain structures. For example, correlations between the expression of Drp1, Gad1, and Psd95 in the ACC and the NAc were only present in healthy controls (Supplementary Table\u0026nbsp;5). CFos expression in the CA1 and NAc was negatively correlated only among DSS-treated animals. Further, Psd95 expression in the CA1 and ACC were correlated only among mice exposed to DSS. Interestingly, many correlations between gene expression were observed between the M1 and ACC, and the M1 and the Ca1 (Supplementary Table\u0026nbsp;5).\u003c/p\u003e\n\u003cp\u003e\u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eCorrelations between fecal Lcn-2 and transcript expression within DSS animals\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eTo determine if there was a relationship between the severity of disease among mice with DSS and mRNA transcript expression, we produced a correlation matrix between transcript expression and levels of Lcn-2 from fecal samples of DSS exposed mice that were collected the same day as euthanasia.\u003c/p\u003e\n\u003cp\u003ePearson correlation coefficients relating levels of fecal Lcn-2 with expression of transcripts in different brain regions reveals that ACC transcript expression was most strongly correlated with fecal Lcn-2 levels, with a positive correlation between 4 transcripts (Fig. \u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e). Specifically, the expression of Drp1 (p\u0026thinsp;=\u0026thinsp;0.033, r\u0026thinsp;=\u0026thinsp;0.0849), Gad1 (p\u0026thinsp;=\u0026thinsp;0.029, r\u0026thinsp;=\u0026thinsp;0.858), Psd95 (p\u0026thinsp;=\u0026thinsp;0.049, r\u0026thinsp;=\u0026thinsp;0.813), and Snap25 (p\u0026thinsp;=\u0026thinsp;0.003, r\u0026thinsp;=\u0026thinsp;0.957) in the ACC were all positively correlated with fecal Lcn-2. Ca1 expression of Psd95 (p\u0026thinsp;=\u0026thinsp;0.018, and M1 expression of Snap25 (p\u0026thinsp;=\u0026thinsp;0.019, r\u0026thinsp;=\u0026thinsp;0.0886) were also positively correlation with fecal Lcn-2. No significant relationships between transcripts in the NAc and fecal Lcn-2 were observed, although Gad1 and Psd95 approached significance (p\u0026thinsp;=\u0026thinsp;0.062 and p\u0026thinsp;=\u0026thinsp;0.064, respectively).\u003c/p\u003e\n\u003cp\u003ePearson correlation of transcript expression in different brain structures and fecal Lcn-2 levels among mice with gut inflammation. N\u0026thinsp;=\u0026thinsp;6, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study we investigated the effects of chronic gut inflammation on transcript expression in four neural structures, using the DSS-colitis model of IBD in mice. We report here that chronic gut inflammation is associated with changes in the expression of several transcripts related to mitochondrial function and antioxidant responses. The CA1 of the hippocampus, and secondarily the nucleus accumbens were most affected. Several interesting relationships between transcript expression emerged in mice with chronic gut inflammation that suggest impaired mitochondrial metabolism in the CA1 and NAc. Reduced transcript expression of Mt-co1, indicative of diminished mitochondrial output, was also observed in the ACC. In contrast to these limbic structures, the expression of transcripts in the primary motor cortex (M1) were not affected by DSS. Combined, these results suggest (\u003cem\u003ei\u003c/em\u003e) effects of chronic gut inflammation are heterogeneous among brain structures, and (\u003cem\u003eii\u003c/em\u003e) that limbic structures may be more susceptible to such inflammation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eChronic gut inflammation is associated with regional changes in mitochondrial transcripts\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMitochondria play a key role in brain health, and their impairment is hypothesized as a key feature of psychiatric diseases including anxiety, depression, and cognitive dysfunction\u0026nbsp;(Giménez-Palomo et al. 2021; L. Liu et al. 2023; Picard and McEwen 2014; Khacho et al. 2017). Inflammation can produce mitochondrial dysfunction through several mechanisms. \u0026nbsp;For example, pro-inflammatory mediators can promote oxidative damage to mitochondrial components, leading to impaired energy production\u0026nbsp;(Brown and Borutaite 2004; Al-Mehdi et al. 2012). Further, inflammation can generate alterations in calcium homeostasis, in turn disrupting mitochondrial dynamics and promoting fragmentation, which can exacerbate inflammation, and reduce energy capacity\u0026nbsp;(Boyapati et al. 2018; Irazoki et al. 2023). Considering the high basal metabolic rate of the brain, neuroinflammation may generate exacerbated metabolic consequences, particularly in neural structures with high metabolic activity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe bulk of ATP production in the brain is accomplished by mitochondrial oxidative phosphorylation, by which electrons are transported through a series of protein complexes to generate ATP. The final complex of the electron transport chain is cytochrome oxidase c, which is comprised of several subunits, including mt-co1. Thus, Mt-co1 gene expression plays a role in regulating energy production, and can be used as an indicator for ATP production\u0026nbsp;(Nagai et al. 2019). Indeed, previous studies have reported a relationship between low Mt-co1 gene expression and mitochondrial dysfunction and oxidative stress\u0026nbsp;(Holvoet et al. 2017). Our results suggest that chronic gut inflammation is associated with reduced mitochondrial respiration in the NAc and ACC, based on the significant reduction in Mt-Co1 expression relative to control animals. The reduced Mt-Co1 expression was most pronounced in the NAc, with a 30% reduction relative to healthy controls; comparatively, the ACC exhibited a 21% reduction in Mt-Co1 expression. Within the Ca1, there was a trend towards reduced Mt-co1 expression relative to controls, and significantly increased expression of Drp1, which suggests increased mitochondrial fission. \u0026nbsp;Enhanced fission can lead to increased levels of mitochondrial damage associated molecular patterns (DAMPS; e.g. ROS, mtDNA) in the cytoplasm, inducing the production of the proinflammatory cytokine IL-1b via inflammasome activation\u0026nbsp;(Park et al. 2015). Increased expression of IL-1b has been reported in the HPC following gut inflammation\u0026nbsp;(Gadotti et al. 2019). We speculate that the emergence of DAMPS within the brain as a consequence of chronic gut inflammation may be a mechanism by which neuroinflammation persists during periods of disease remission, mirroring the role of systemic mitochondrial DAMPS in promoting inflammation in IBD\u0026nbsp;(Boyapati et al. 2018).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Chronic gut inflammation also transformed the relationship between Mt-Co1 and other transcripts in the NAc. Among control mice, we observed a negative relationship between expression of Mt-Co1 and Drp1, Mfn2, Gad1, and Psd95. These relationships were consistently shifted to the left and inverted to positive correlations among mice with chronic gut inflammation. The physiological significance of this finding is unclear; however, the fact that this transformation was only observed in the NAc, and all correlated with expression with Mt-Co1, suggests chronic gut inflammation may promote changes in mitochondrial function that impact neurotransmitter signaling and neuronal spine structure in this region. In our study, the NAc had significantly highest expression of Mt-Co1 relative to other regions among control animals. This may reflect a higher basal metabolic requirement in the NAc, which could render this region especially vulnerable to the metabolic demands of neuroinflammation. Research indicates that there are regional differences in mitochondrial bioenergetics within the brain\u0026nbsp;(Rosenberg et al. 2023; Andersen et al. 2019)\u0026nbsp;and evidence suggests mitochondria within the striatum may be particularly active. \u0026nbsp; For example, mitochondria from striatal neurons exhibited highest rates \u0026nbsp;of oxygen consumption and ATP production in the presence of some respiratory substrates, relative to mitochondria from cerebral cortex and hippocampal neurons\u0026nbsp;(Andersen et al. 2019). Indeed, striatal mitochondria are more susceptible to calcium-induced activation of the permeability transition pore (leading to cell damage or death) than cortical mitochondria\u0026nbsp;(Brustovetsky et al. 2003), \u0026nbsp; and evidence suggests the striatal mitochondria are particularly sensitive to defects in oxidative phosphorylation relative to mitochondria in the cortex and hippocampus\u0026nbsp;(Pickrell et al. 2011). Combined, these data suggest that chronic gut inflammation impairs the energy transformation capacity of mitochondria in a regionally dependent manner. The effect of colitis-induced neuroinflammation on aspects of mitochondrial metabolism in the brain, and how this influences neural physiology requires further investigation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eThe CA1 displays increased sensitivity to chronic gut inflammation\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study revealed that out of the structures examined, the CA1 of the hippocampus appeared to be the most sensitive to gut inflammation; the expression of 6 out of 9 of the selected transcripts were significantly altered. As well, our PCA revealed that the principal components that included the expression for all transcripts, antioxidant-related transcripts, and mitochondria function related transcripts in the CA1 was consistently different between treatment groups. The apparent sensitivity of the HPC to gut inflammation is supported by the literature, where the reported effects of gut-inflammation in the brain are dominated by the HPC\u0026nbsp;(C. E. Matisz and Gruber 2022). For example, mice administered chemically-induced models of colitis demonstrated increased expression of proinflammatory cytokines (e.g. IL-6, IL-1β, TNF-α) and a variety of markers of oxidative stress in the HPC\u0026nbsp;(Gadotti et al. 2019; Hilel et al. 2018; Haj-Mirzaian et al. 2017). Our previous research has revealed that acute exposure to DSS is associated with increased proportion of immature spines in the apical dendrites of CA1 pyramidal neurons, and reduced neural activation in the CA1, based on reduced immunostaining of cFos\u0026nbsp;(Chelsea E. Matisz et al. 2022). It is tempting to speculate that sensitivity of the CA1 HPC to gut inflammation is associated with activated learning mechanisms, possibly to aid in identification of environmental factors that may be contributing to negative affective states associated with gut inflammation. this may explain the increased Snap25 in the Ca1 of mice with chronic DSS exposure. However, additional testing is needed to substantiate such speculation. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the present study we also observed that chronic gut inflammation is associated with elevated cFos mRNA expression in the CA1. This contrasts the effects of acute DSS exposure, which is associated with reduced immunostaining of cFos in the CA1 of mice\u0026nbsp;(Chelsea E. Matisz et al. 2022). Interestingly, CA1 hypoactivity was correlated with increased swimming time in the FST in mice exposed to a single 5-day exposure of DSS; here we report increased cFos expression in mice with three cycles of 5-day exposures to DSS, which was accompanied by swimming in the FST equivalent to controls. This suggests neural activity in the CA1 may contribute to mobility in this task.\u0026nbsp;Taken together, the results from these studies suggest that the duration of inflammation differentially modulates neural activity in the CA1 hippocampus.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eChronic Gut Inflammation is associated with reduced expression of antioxidant-related genes\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReactive oxygen species (ROS) play an essential role in normal physiological processes, including cell signaling, immune responses, and mitochondrial function. However, the accumulation of ROS can lead to cellular damage, a pathological state termed oxidative stress. Antioxidant responses play an important role in maintaining the balance between ROS production and its elimination. The brain is a huge consumer of oxygen; estimates suggest 20% of the body’s oxygen supply is consumed by this organ to support the ATP intensive activities of neurons, despite only accounting for 2% of the body weight\u0026nbsp;(Rolfe and Brown 1997). As such, neurons are especially vulnerable to oxidative damage due to their high oxygen demand, combined with their relatively weak antioxidant defense system \u0026nbsp;(Cobley, Fiorello, and Bailey 2018). Inflammation is energy-intensive; it is estimated that chronic inflammatory diseases can increase energy costs by 10-15%\u0026nbsp;(Straub 2017; Lacourt et al. 2018). Inflammation drives a metabolic switch in astrocytes and microglia towards glycolysis, increasing the production of ATP and the consumption of glucose\u0026nbsp;(L. Wang et al. 2019). Further, inflammation can lead to impairments in glutamate clearance, leading to neuronal excitotoxicity and metabolic dysfunction\u0026nbsp;(Haroon, Miller, and Sanacora 2017).Thus, neuroinflammation places an additional metabolic demand on an already highly metabolic organ, leading to increased risk of oxidative stress, both of which are hypothesized to play a role in the pathophysiology of anxiety, depression, and co­­­­gnitive dysfunction\u0026nbsp;(Black et al. 2015; Bhatt, Nagappa, and Patil 2020; Hovatta, Juhila, and Donner 2010; Guo et al. 2023). Chronic gut inflammation was associated with reduced mRNA expression for Gpx1, the enzyme that contributes to the potent antioxidant activity of glutathione, in the CA1 and the NAc. \u0026nbsp;Reduced expression of the transcription factor Nrf2, which regulates antioxidant expression, was also observed in the CA1. These findings suggest impaired antioxidant responses in the CA1 and NAc of mice with chronic gut inflammation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMice with acute DSS colitis has increased levels of reactive oxidant-induced protein and lipid modifications in the HPC and striatum, \u0026nbsp;respectively\u0026nbsp;(Hilel et al. 2018). The effects of chronic gut inflammation on antioxidant systems in the brain has not been reported. However, chronic unpredictable stress, which can produce neuroinflammation and similar behavioural phenotypes as chronic inflammation in animal models, \u0026nbsp;was found to reduce activity of glutathione peroxidase in the brain of rats\u0026nbsp;(Che et al. 2015). Interestingly, we observed a positive correlation \u0026nbsp;between Nrf2 and Psd95 among control mice; chronic gut inflammation decoupled this relationship. This aligns with previous studies which suggest that depletion of antioxidant systems can impair synaptic function and plasticity, as observed in rodent models of traumatic brain injury\u0026nbsp;(Ansari, Roberts, and Scheff 2008). Further, Both Nrf2 and Psd95 were reduced in a mouse model of chronic stress, and treatment with the Nrf2 activator oltipraz restored Psd95 expression \u0026nbsp; in the hippocampus(Zeng et al. 2023).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResearch suggests the brain possesses regional vulnerability to oxidative stress. For example, the literature paints the CA1 as a region that is highly vulnerable to insult. Within the hippocampus, the CA1 and CA3 subfields lie adjacent to each other, and both possess a high density of pyramidal neurons. However, despite these similarities, studies conducted in a diversity of mammalian species (rats, gerbils, primates, humans) using a variety of different methods to generate oxidative stress in the brain demonstrate that CA1 neurons are much more sensitive to oxidative stress relative to their CA3 neuronal counterparts\u0026nbsp;(Bartsch et al. 2015; Kirino 1982; Pulsinelli, Brierley, and Plum 1982; Tabuchi et al. 1992). Molecular mechanisms that ascribe such vulnerability are not completely understood; it has been suggested that high baseline levels of ROS-generating activities (e.g. cellular respiration) within neuronal populations render those neurons more vulnerable to insults, such as neuroinflammation\u0026nbsp;(X. Wang and Michaelis 2010). Extending from this, regions with greater basal levels of oxidative stress should also possess higher basal expression of genes involved in antioxidant responses, such as Nrf2. Indeed, Wang \u003cem\u003eet al\u003c/em\u003e. report higher basal expression of Nrf2 in the CA1 than that of the CA3\u0026nbsp;(X. Wang et al. 2005). In the present study, basal levels of Nrf2 in control mice were significantly higher in the CA1 and NAc compared to the ACC and M1. Further, transcript expression of Gpx1 was significantly higher in the NAc relative to other regions in control mice. Combined, these data support previous assertations that the CA1 maybe especially vulnerable to neuroinflammation relative to other structures. \u0026nbsp;Our results extend upon these studies and suggest the NAc may similarly possess intrinsic vulnerability to the costs of neuroinflammation. Both the Ca1 and NAc represent neural substrates involved in anxiodepressive phenotypes, which are well-established \u0026nbsp;comorbidities in preclinical and clinical studies of IBD\u0026nbsp;(C. E. Matisz and Gruber 2022). The relative vulnerability of neural regions involved in threat-coping and motivation behaviours in the face of chronic neuroinflammation may explain why anxiety and depression emerge in such a wide range of chronic inflammatory diseases, despite their diverse etiology. Further studies are necessary to confirm the oxidative stress vulnerability transcript responses to chronic gut inflammation in other regions known to be involved in anxiety and depression, such as the basal ganglia, prefrontal cortex, and amygdala.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eChronic gut inflammation is associated with altered Gad1 expression in the CA1\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDisturbed modulation of excitatory circuits by Gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the CNS, is implicated in psychological processes such as anxiety and depression\u0026nbsp;(Möhler 2012; Nuss 2015). GABA synthesis is in part regulated by the rate-limiting enzyme glutamate decarboxylase isoform Gad67, which is encoded by Gad1 mRNA. We report the expression of Gad1 mRNA is significantly increased in the CA1 of mice with chronic DSS exposure. Further, chronic gut inflammation transformed the relationship between the expression of Gad1 and Psd95, and Drp1 in the CA1. The functional significance of these relationships is not clear; however, it suggests an intriguing relationship between post-synaptic density, mitochondrial dynamics, and the GABAergic system in our model. To our knowledge, the effects of gut inflammation on hippocampal GABA expression have not been previously reported. However, research suggests neuroinflammation induced by chronic stress\u0026nbsp;(Lang et al. 2020)\u0026nbsp;and toxin exposure\u0026nbsp;(Nascimento et al. 2022)\u0026nbsp;can alter GABA signaling in the hippocampus by increasing GABA receptor expression and GABA levels, respectively. \u003cem\u003eIn vitro\u003c/em\u003e studies indicate GABA contributes to neuroinflammation by stimulating the secretion of pro-inflammatory cytokines from microglia\u0026nbsp;(Lang et al. 2020). Using the TNBS model of colitis in rats, Riazi \u003cem\u003eet al.\u003c/em\u003e revealed that gut inflammation is associated with increased neuronal excitability in the HPC, and increased susceptibility to seizure that was dependent on microglial activation\u0026nbsp;(Riazi et al. 2008). Specifically microglial activation was increased in the entorhinal cortex, and activation of this region has been shown to promote increased Gad1 mRNA in the CA1\u0026nbsp;(Falkenberg et al. 1997; Riazi et al. 2008). The entorhinal cortex was not investigated in the present study, but is involved in processing fear responses and anxiety, which we have shown are modulated as a consequence of chronic gut inflammation\u0026nbsp;(C. E. Matisz et al. 2022).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFecal Lcn2 expression is correlated with transcript expression in the ACC, and other regions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe ACC, positioned at the interface between the ‘emotional’ limbic system, and the ‘cognitive’ prefrontal cortex, is heavily involved in affective processing. Neuroinflammatory remodeling of the ACC is a key driver of anxiety and depression, and this region is among the most consistently altered neural structures in patients with gastrointestinal diseases and disorders, displaying cortical thinning and hyperactivity (C. E. Matisz and Gruber 2022). Despite evidence that suggests the ACC is heavily involved in the neuropathology comorbid with gut inflammation, the only transcriptional change observed in the ACC on mice with chronic gut inflammation was the reduced expression of Mt-co1. Interestingly, we did note that fecal Lcn2 was most frequently associated with shifts in transcript expression in the ACC; the expression of 4 of 9 transcripts positively correlated with fecal Lcn-2. Fecal Lcn-2 is a well-established biomarker for severity of gut disease in preclinical models, and patients with ulcerative colitis (Chassaing et al. 2012; Hsieh et al. 2016; Buisson et al. 2014). The correlation between fecal Lcn-2 and Drp1 may reflect a relationship between the severity of gut inflammation and increased mitochondrial fission, which aligns with reduced Mt-co1 expression in this region. \u0026nbsp; GABAergic neurons regulate neuronal activity, and their activity in the ACC has been shown to attenuate anxiety in a rodent model of inflammatory pain (Shao et al. 2021); the correlation between fecal Lcn2 and Gad1 in the ACC may reflect a greater need for regulating neuronal activity in the ACC among these animals. The physiological significance of changes in pre and postsynaptic protein transcripts in the ACC, CA1 and M1 as they relate to fecal Lcn-2 levels are not clear. The correlation between fecal Lcn-2 and Psd95 mRNA may reflect visceral pain among more severely inflamed animals; DSS-induced colitis promotes visceral hyperalgesia in mice (Lapointe et al. 2015; Defaye et al. 2022; Esquerre et al. 2020), and \u0026nbsp;PSD95 in the ACC has been shown to contribute to neuropathic pain (Li et al. 2022). \u0026nbsp; Stress and inflammation have also been shown to alter spine morphology in both the ACC and CA1 It is important to note that the current study did not assess post transcriptional modifications or protein expression of the transcripts. Further, the phenotype of cell on which these mRNA transcripts are modified is unknown, which limits the interpretations of these findings.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur results indicate chronic gut inflammation is associated with heterogenous changes in the brain, particularly the limbic system. Changes in transcript expression suggest prolonged colitis promotes reduced oxidative phosphorylation, and impaired antioxidant defense systems in the ACC, CA1, and NAc. \u0026nbsp;Our data suggest chronic gut inflammation may alter mitochondrial function and dynamics in regions of the brain that are known to be affected in patients with symptoms of anxiety and depression. This lends support to the literature that proposes a role of altered bioenergetics and mitochondrial dysfunction in the brain of patients with chronic inflammatory diseases, which may play a role in mood disorders that are comorbid in these illnesses. \u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful for Natural Sciences and Engineering Research Council (CEM; PDF, AJG and RJS, discovery grant) and\u0026nbsp;Canada Research Chairs program and Genome Canada BioNet grant (AZ)\u0026nbsp;for financial support of this work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAJS and RJS received an NSERC Discovery Grant from the National Science and Engineering Research Council. AZ is a recipient of the Canada Research Chairs program and Genome Canada BioNet grant. CEM was supported by an NSERC PDF.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no financial or non-financial interests to disclose.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCEM and AJG conceptualized the study; CEM, VL, KB, and TH collected, curated and analyzed data; CEM and AJG drafted the manuscript; all authors critically revised and approved the final manuscript for submission. \u0026nbsp;AJG, AZ, and RJS obtained funding and provided oversight and supervision of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll experiments were carried out in accordance with the guidelines of the Canadian Council of Animal Care and were approved by the University of Lethbridge Animal Care Committee (Protocol #2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed for the current study are included in the supplementary materials.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAllen, Josh, Raquel Romay-Tallon, Kyle J. 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Magnago, et al. 2018. \u0026ldquo;Dextran Sulphate of Sodium-Induced Colitis in Mice: Antihyperalgesic Effects of Ethanolic Extract of Citrus Reticulata and Potential Damage to the Central Nervous System.\u0026rdquo; \u003cem\u003eAnais Da Academia Brasileira de Ciencias\u003c/em\u003e 90 (3): 3139\u0026ndash;45.\u003c/li\u003e\n \u003cli\u003eHolvoet, Paul, Maarten Vanhaverbeke, Benjamine Geeraert, Dieuwke De Keyzer, Maarten Hulsmans, and Stefan Janssens. 2017. \u0026ldquo;Low Cytochrome Oxidase 1 Links Mitochondrial Dysfunction to Atherosclerosis in Mice and Pigs.\u0026rdquo; \u003cem\u003ePloS One\u003c/em\u003e 12 (1): e0170307.\u003c/li\u003e\n \u003cli\u003eHovatta, Iiris, Juuso Juhila, and Jonas Donner. 2010. \u0026ldquo;Oxidative Stress in Anxiety and Comorbid Disorders.\u0026rdquo; \u003cem\u003eNeuroscience Research\u003c/em\u003e 68 (4): 261\u0026ndash;75.\u003c/li\u003e\n \u003cli\u003eHsieh, Heidi, Jeffrey Morin, Cyndi Filliettaz, Rao Varada, Shelby LaBarre, and Zaher Radi. 2016. \u0026ldquo;Fecal Lipocalin-2 as a Sensitive and Noninvasive Biomarker in the TNBS Crohn\u0026rsquo;s Inflammatory Bowel Disease Model.\u0026rdquo; \u003cem\u003eToxicologic Pathology\u003c/em\u003e 44 (8): 1084\u0026ndash;94.\u003c/li\u003e\n \u003cli\u003eIrazoki, Andrea, Isabel Gordaliza-Alaguero, Emma Frank, Nikolaos Nikiforos Giakoumakis, Jordi Seco, Manuel Palac\u0026iacute;n, Anna Gum\u0026agrave;, Lykke Sylow, David Sebasti\u0026aacute;n, and Antonio Zorzano. 2023. \u0026ldquo;Disruption of Mitochondrial Dynamics Triggers Muscle Inflammation through Interorganellar Contacts and Mitochondrial DNA Mislocation.\u0026rdquo; \u003cem\u003eNature Communications\u003c/em\u003e 14 (1): 1\u0026ndash;19.\u003c/li\u003e\n \u003cli\u003eIsik, Ahmet, Suleyman Serdar Koca, Abdullah Ozturk, and Osman Mermi. 2007. \u0026ldquo;Anxiety and Depression in Patients with Rheumatoid Arthritis.\u0026rdquo; \u003cem\u003eClinical Rheumatology\u003c/em\u003e 26 (6): 872\u0026ndash;78.\u003c/li\u003e\n \u003cli\u003eJain, Piyush, Ahmed M. 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Michelsen, and Vera Chesnokova. 2015. \u0026ldquo;Chronic Intestinal Inflammation Alters Hippocampal Neurogenesis.\u0026rdquo; \u003cem\u003eJournal of Neuroinflammation\u003c/em\u003e 12 (April): 65.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"neuroinflammation, hippocampus, nucleus accumbens, anterior cingulate cortex, mt-co1","lastPublishedDoi":"10.21203/rs.3.rs-4486754/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4486754/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChronic inflammatory diseases are frequently comorbid with depression and anxiety, often persisting during periods of inflammatory remission. This suggests functional changes to neural circuits involved in the contextual regulation of motivation and threat processing. Here, we test how chronic gut inflammation evoked by dextran sodium sulfate (DSS) affects gene expression in several limbic brain structures associated with these functions. We assessed post-mortem expression of mRNA transcripts in the anterior cingulate cortex (ACC), CA1 hippocampus, nucleus accumbens (NAc), and primary motor cortex (M1) as a non-limbic control. The levels of mRNA associated with mitochondrial function, inflammation, and synaptic connectivity were altered in DSS-treated animals, but the specific pattern of changes was heterogeneous among brain structures. Chronic gut inflammation affected transcript expression in the CA1 and NAc more so than in the ACC and M1. These differences involved genes related to antioxidant systems and mitochondrial function. For example, expression of the cytochrome oxidase 1 gene mt-co1, which is necessary for oxidative phosphorylation, was reduced in ACC and NAc of DSS animals, suggesting reduced capacity for ATP production in these regions. Markers of gut inflammation correlated with expression of several transcripts in the ACC, including markers of synapses and GABA synthesis. The NAc showed strong correlations of mitochondrial function and measures of mitochondrial fission, inflammation, synaptic connectivity, and GABA synthesis. In sum, these data indicate neuroinflammatory processes in the brain evoked by chronic relapsing gut inflammation are heterogeneous among brain structures, and possess complex relationships between mitochondrial function, antioxidants, neurotransmission and gut inflammation.\u003c/p\u003e","manuscriptTitle":"Chronic gut inflammation differentially modulates mitochondrial and antioxidant transcriptional programs in limbic brain structures","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-06 12:11:23","doi":"10.21203/rs.3.rs-4486754/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"66606f63-fb53-40f8-b6b0-9afada4c1481","owner":[],"postedDate":"August 6th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-19T22:38:11+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-06 12:11:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4486754","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4486754","identity":"rs-4486754","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}