New Results

The gut microbiome regulates memory function

Emily E Noble, Elizabeth Davis, Linda Tsan, Yen-Wei Chen, Christine A. Olson, Ruth Schade, Clarissa Liu, Andrea Suarez, Roshonda B Jones, Michael I Goran, Claire de La Serre, Xia Yang, Elaine Y. Hsiao, Scott E Kanoski
doi: https://doi.org/10.1101/2020.06.16.153809

Abstract

The mammalian gastrointestinal tract contains a diverse ecosystem of microbial species collectively making up the gut microbiota. Emerging evidence highlights a critical relationship between gut microbiota and neurocognitive development. Consumption of unhealthy yet palatable dietary factors associated with obesity and metabolic dysfunction (e.g., saturated fat, added sugar) alters the gut microbiota and negatively impacts neurocognitive function, particularly when consumed during early life developmental periods. Here we explore whether excessive early life consumption of added sugars negatively impacts neurocognitive development via the gut microbiome. Using a rodent model of habitual sugar-sweetened beverage (SSB) consumption during the adolescent stage of development, we first show that excessive early life sugar intake impairs hippocampal-dependent memory function when tested during adulthood while preserving other neurocognitive domains. 16S rRNA gene sequencing of the fecal and cecal microbiota reveals that early life SSB consumption alters the relative abundance of various bacterial taxa. In particular, SSB elevates fecal operational taxonomic units within the genus Parabacteroides, which negatively correlate with memory task performance. Additional results reveal that transferred enrichment of Parabacteroides species P. distasonis and P. johnsonii in adolescent rats impairs memory function during adulthood. Hippocampus transcriptome analyses identify gene expression alterations in neurotransmitter synaptic signaling, intracellular kinase signaling, metabolic function, neurodegenerative disease, and dopaminergic synaptic signaling-associated pathways as potential mechanisms linking bacterial alterations with memory impairment. Collectively these results identify a role for microbiota “dysbiosis” in mediating the negative effects of early life unhealthy dietary factors on neurocognitive outcomes.

Introduction

The gut microbiome is increasingly implicated in modulating neurocognitive development and consequent functioning 1,2. Early life developmental periods represent critical windows for the impact of indigenous gut microbes on the brain, as evidenced by the reversal of behavioral and neurochemical abnormalities in germ free rodents when inoculated with conventional microbiota during early life, but not during adulthood 3–5. Dietary factors are a critical determinant of gut microbiota diversity and can alter gut bacterial communities, as evident from the microbial plasticity observed in response to pre- and probiotic treatment, as well as the “dysbiosis” resulting from consuming unhealthy, yet palatable foods that are associated with obesity and metabolic disorders (e.g., “Western diet”; foods high in saturated fatty acids and added sugar) 6. In addition to altering the gut microbiota, consumption of these dietary factors yields long-lasting memory impairments, and these effects are more pronounced when consumed during early life developmental periods vs. during adulthood 7–9. Whether diet-induced changes in specific bacterial populations are functionally related to altered early life neurocognitive outcomes, however, is poorly understood.

The hippocampus, which is well known for its role in spatial and episodic memory and more recently for regulating learned and social aspects of food intake control 10–15, is particularly vulnerable to the deleterious effects of Western dietary factors 16–18. During the juvenile and adolescent stages of development, a time when the brain is rapidly developing, consumption of diets high in saturated fat and sugar 19–21 or sugar alone 22–25 impairs hippocampal function while in some cases preserving memory processes that do not rely on the hippocampus. While several putative underlying mechanisms have been investigated, the precise biological pathways linking dietary factors to neurocognitive dysfunction remain largely undetermined 9. Here we aimed to determine whether sugar-induced alterations in gut microbiota during early life are causally related to hippocampal-dependent memory impairments observed during adulthood.

Early-life sugar consumption impairs hippocampal-dependent memory function without affecting other neurocognitive domains

Results from the Novel Object in Context (NOIC) task, which measures hippocampal-dependent episodic contextual memory function 26, reveal that while there were no differences in total exploration time of the combined objects on days 1 or 3 of the task (Fig. 1A,B), animals fed sugar solutions in early life beginning at PN 28 had a reduced capacity to discriminate an object that was novel to a specific context when animals were tested during adulthood (PN 60), indicating impaired hippocampal function (Fig. 1C, D). Conversely, when tested in the novel object recognition task (NOR), which tests object recognition memory independent of context and is primarily dependent on the perirhinal cortex 26–28, animals fed sugar solutions in early life performed similarly to those in the control group (Fig. 1E).

Figure 1:
Figure 1: Early-life sugar consumption negatively impacts hippocampal-dependent memory function.

(A,B) Early life sugar consumption had no effect on total exploration time in the Novel Object in Context (NOIC) task. (C,D) discrimination index and discrimination shift from baseline were significantly reduced by early life sugar consumption, indicating impaired hippocampal function (P<.05, n=10,11; two-tailed, type 2 Student’s T-test). (E) There were no differences in exploration index in the Novel Object Recognition (NOR task) (n=6; two-tailed, type 2 Student’s T-test). (F, G) There were no differences in time spent in the open arm or the number of entries into the open arm in the Zero Maze task for anxiety-like behavior (n=10,11; two-tailed, type 2 Student’s t-test). (H, I) There were no differences in distance travelled or time spent in the center arena in the Open Field task (n=10,11; two-tailed, type 2 Student’s T-test). (J-K) Body weights and did not differ between the groups and there was no effect of treatment on total kcal intake while animals had access to early life sugar (n=10,11; two-way repeated measures ANOVA). (L) There were no differences in body composition between rats fed early life sugar and controls (n=10,11; two-tailed, type 2 Student’s T-test). CTL=control, SUG= sugar, PN= post-natal day; data shown as mean + SEM.

Elevated anxiety and altered general activity levels may influence novelty exploration independent of memory effects and may therefore confound the interpretation of behavioral results. Thus, we next tested whether early life sugar consumption affects anxiety-like behavior using two different tasks designed to measure anxiety in the rat: the elevated zero maze and the open field task, that latter of which also assesses levels of general activity 29. Early life sugar had no effect on time spent in the open area or in the number of open area entries in the zero maze (Fig. 1F, G). Similarly, early life sugar had no effect on distance travelled or time spent in the center zone in the open field task (Fig. 1H, I). Together these data suggest that habitual early life sugar consumption did not increase anxiety-like behavior or general activity levels in the rats.

Early life sugar consumption impairs glucose tolerance without affecting total caloric intake, body weight, or adiposity

Given that excessive sugar consumption is associated with weight gain and metabolic deficits 30, we tested whether access to a sugar solution during the adolescent phase of development would affect food intake, body weight gain, adiposity, and glucose tolerance in the rat. Early life sugar consumption had no effect on body weight or total kcal intake (Fig. 1J, K), which is in agreement with previous findings 22,31,32. Animals steadily increased their intake of the 11% sugar solution throughout the study but compensated for the calories consumed in the sugar solutions by reducing their intake of dietary chow (Supplemental Fig. 1A, B). There were no differences in body fat percentage during adulthood (Fig. 1L) or in total grams of body fat or lean mass. However, animals that were fed sugar solutions during early life showed impaired peripheral glucose metabolism in an intraperitoneal glucose tolerance test (IP GTT) (Fig. 1L, Supplemental Fig 1C-E).

Gut microbiota are impacted by early life sugar consumption

Principal component analyses of 16s rRNA gene sequencing data of fecal samples revealed a separation between the fecal microbiota of rats fed early life sugar and controls (Fig. 2A). Results from LEfSe analysis identified differentially abundant bacterial taxa in fecal samples that were elevated by sugar consumption. These include the family Clostridiaceae and the genus 02d06 within Clostridiaceae, the family Mogibacteriaceae, the family Enterobacteriaceae, the order Enterobacteriales, the class of Gammaproteobacteria, and the genus Parabacteroides within the family Porphyromonadaceae (Fig. 2B,C). In addition to an elevated % relative abundance of the genus Parabacteroides in animals fed early life sugar (Fig 2D), log transformed counts of the Parabacteroides negatively correlated with performance scores in the NOIC memory task (R2=.64, P<.0001; Fig. 2E). Within Parabacteroides, levels of three operational taxonomic units (OTUs) that were elevated by sugar significantly correlated negatively with performance in the NOIC task, two of which were identified as taxonomically related to P. johnsonii and P. distasonis (Fig. 2F, G). The significant negative correlation between NOIC performance and each of these OTUs was also present within the sugar groups alone (not shown). Abundance of other bacterial populations that were affected by sugar consumption were not significantly related to memory task performance.

Figure 2:
Figure 2: Effect of adolescent sugar consumption on the gut microbiome in rats

(A) Principal component analysis showing separation between fecal microbiota of rats fed early life sugar or controls (n=11, 10; dark triangles= sugar, open circles= control). (B) Results from LEfSe analysis showing Linear Discriminate Analysis (LDA) scores for microbiome analysis of fecal samples of rats fed early life sugar or controls. (C) A cladogram representing the results from the LEfSe analysis with class as the outer most taxonomic level and species at the inner most level. Taxa in red are elevated in the sugar group. (D) Relative % abundance of fecal Parabacteroides were significantly elevated in rats fed early life sugar (P<.05; n=11, 10, two-tailed, type 2 Student’s T-test). (E) Linear regression of log normalized fecal Parabacteroides counts against shift from baseline performance scores in the novel object in context task (NOIC) across all groups tested (n=21). (E,F) Linear regression of the most abundant fecal Parabacteroides OTUs against shift from baseline performance scores in NOIC across all groups tested (n=21). *P<0.05; data shown as mean + SEM.

There was a similar separation between groups in bacteria analyzed from cecal samples (Supplemental Fig. 2A). LEfSe results from cecal samples show elevated Bacilli, Actinobacteria, Erysipelotrichia, and Gammaproteobacteria in rats fed early life sugar, and elevated Clostridia in the controls (Supplemental Fig. 2B). Abundances at the different taxonomic levels in fecal and cecal samples are shown in (Supplemental Fig. 3, 4). Regression analyses did not identify these altered cecal bacterial populations as being significantly correlated to NOIC memory performance.

Early life Parabacteroides enrichment impairs memory function

To determine whether neurocognitive outcomes due to early life sugar consumption could be attributable to elevated levels of Parabacteroides in the gut, we experimentally enriched the gut microbiota of naïve juvenile rats with two Parabacteroides species that exhibited high 16S rRNA sequencing alignment with OTUs that were increased by sugar consumption and were negatively correlated with behavioral outcomes in rats fed early life sugar. P. johnsonii and P. distasoni species were cultured individually under anaerobic conditions and transferred to a group of antibiotic-treated young rats in a 1:1 ratio via oral gavage using the experimental design described in Methods and outlined in Supplemental Fig. 5A, and from 33. All rats treated with antibiotics showed a reduction in food intake and body weight during the initial stages of antibiotic treatment, however, there were no differences in body weight between the two groups of antibiotic treated animals by PN50, at the time of testing (Supplemental Fig. 5B, C).

Results from the hippocampal-dependent NOIC memory task showed that while there were no differences in total exploration time of the combined objects on days 1 or 3 of the task, indicating similar exploratory behavior, animals treated with Parabacteroides showed a significantly reduced discrimination index in the NOIC task (Fig 3A-D), indicating impaired performance in hippocampal-dependent memory function. When tested in the perirhinal cortex-dependent NOR task 26, animals treated with Parabacteroides showed impaired object recognition memory as indicated by a reduced novel object exploration index, with no differences in total exploration time (Fig 3E). These findings show that unlike sugar-fed animals, Parabacteroides enrichment impaired perirhinal cortex-dependent memory processes in addition to hippocampal-dependent memory.

Figure 3:
Figure 3: Early-life enrichment with Parabacteroides negatively impacts neurocognitive function

(A, B) Early-life enrichment with a 1:1 ratio of P. johnsonii and P. distasonis had no effect on total exploration time in the Novel Object in Context (NOIC) task. (C, D) Discrimination index was significantly reduced and discrimination shift from baseline tended to be reduced by enrichment with P. johnsonii and P. distasonis, indicating impaired hippocampal function (P<.05, n=14,8; two-tailed, type 2 Student’s T-test). (E) There was a significant reduction in the exploration index in the Novel Object Recognition (NOR task), indicating impaired perirhinal cortex function (P<.05, n=14, 8; two-tailed, type 2 Student’s T-test). (F, G) There were no differences in time spent in the open arm but there was a trend toward a reduced number of entries into the open arm by animals with P. johnsonii and P. distasonis enrichment in the Zero Maze task for anxiety-like behavior (P=.052, n=14, 8; two-tailed, type 2 Student’s T-test). (H, I) There were no differences in distance travelled or time spent in the center arena in the Open Field task (n=14, 8; two-tailed, type 2 Student’s T-test). (J-L) Body weights and lean mass were significantly reduced in animals enriched with P. johnsonii and P. distasonis, but body fat did not differ between the groups (P<.05, n=14, 8; two-tailed, type 2 Student’s T-test). CTL=control, ABX-PARA= P. johnsonii and P. distasonis enriched, PN= post-natal day; data shown as mean + SEM.

Results from the zero maze showed a non-significant trend toward reduced time spent in the open arms and a reduced number of open arm entries for the Parabacteroides treated rats (Fig 3F, G), which is indicative of increased anxiety-like behavior. However, there were no differences in distance travelled or time spent in the center arena in the open field test, which is a measure of both anxiety-like behavior and general activity in rodents (Fig. 3H, I). Together these data suggest that Parabacteroides treatment negatively impacted both hippocampal-dependent perirhinal cortex-dependent memory function without significantly affecting general activity or anxiety-like behavior.

Similar to a recent report 34, Parabacteroides enrichment in the present study impacted body weight. Animals who received P. johnsonii and P. distasonis treatment showed reduced body weight 40 days after the transfer, with significantly lower lean mass and a trend toward reduced fat mass (Fig 3J-L). There were no differences in percent body fat between groups, nor were there significant group differences in glucose metabolism in the IPGTT (Supplemental Fig. 5D, E).

Early life sugar consumption and Parabacteroides enrichment alter hippocampal gene expression profiles

To further investigate how sugar and Parabacteroides affect cognitive behaviors, we conducted transcriptome analysis of the hippocampus samples. Supplemental Fig 6A shows the results of principal component analysis revealing moderate separation based on RNA sequencing data from the dorsal hippocampus of rats fed sugar in early life compared with controls. Gene pathway enrichment analyses from RNA sequencing data revealed multiple pathways significantly affected by early life sugar consumption, including four pathways involved in neurotransmitter synaptic signaling: dopaminergic, glutamatergic, cholinergic, and serotonergic signaling pathways. Additionally, several gene pathways that also varied by sugar were those involved in kinase-mediated intracellular signaling: cGMP-PKG, RAS, cAMP, and MAPK signaling pathways (Fig. 4A, Supplemental Table 1).

Figure 4:
Figure 4: Effect of early life sugar or targeted Parabacteroides enrichment on hippocampal gene expression

(A) Pathway analyses for differentially expressed genes (DEGs) at a p-value < 0.01 in hippocampal tissue punches from rats fed early life sugar compared with controls. Upregulation by sugar is shown in red and downregulation by sugar in blue. (B) A heatmap depicting DEGs that survived the Benjamini-Hochberg corrected FDR of P< 0.05 in rats fed early life sugar compared with controls. Warmer colors (red) signify an increase in gene expression and cool colors (blue) a reduction in gene expression by treatment (CTL=control, SUG= early life sugar; n=7/group). (C) A heatmap depicting DEGs that survived the Benjamini-Hochberg corrected FDR of P< 0.05 in rats with early life Parabacteroides enrichment compared with controls. Warmer colors (red) signify an increase in gene expression and cool colors (blue) a reduction in gene expression by treatment (n=7, 14). (D) Pathway analyses for differentially expressed genes (DEGs) at a P-value < 0.01 in rats enriched with Parabacteroides compared with controls. Upregulation by Parabacteroides transfer is shown in red and downregulation in blue. Dotted line indicates ±0.25 log2 fold change.

Analyses of individual genes across the entire transcriptome using a stringent false-discovery rate criterion further identified 21 genes that were differentially expressed in rats fed early life sugar compared with controls, with 11 genes elevated and 10 genes decreased in rats fed sugar compared to controls (Fig 4B). Among the genes impacted, several genes that regulate cell survival, migration, differentiation, and DNA repair were elevated by early life sugar access, including Faap100, which encodes an FA core complex member of the DNA damage response pathway 35, and Eepd1, which transcribes an endonuclease involved in repairing stalled DNA replication forks, stressed from DNA damage 36. Other genes associated with ER stress and synaptogenesis were also significantly increased by sugar consumption, including Klf9, Dgkh, Neurod2, Ppl, and Kirrel1 37,38,39,40.

Several genes were reduced by dietary sugar, including Tns2, which encodes tensin 2, important for cell migration 41, RelA, which encodes a NF/kB complex protein that regulates activity dependent neuronal function and synaptic plasticity 42, and Grm8, the gene for the metabotropic glutamate receptor 8 (mGluR8). Notably, reduced expression of mGluR8 receptor may contribute to the impaired neurocognitive functioning in animals fed sugar, as mGluR8 knockout mice show impaired hippocampal-dependent learning and memory 43.

Supplemental Fig 6B shows the results of principal component analysis of dorsal hippocampus RNA sequencing data indicating moderate separation between rats enriched with Parabacteroides and controls. Gene pathway analyses revealed that early life Parabacteroides treatment, similar to effects associated with sugar consumption, significantly altered the genetic signature of dopaminergic synaptic signaling pathways, though differentially expressed genes were commonly affected in opposite directions between the two experimental conditions (Supplemental Fig 7). Parabacteroides treatment also impacted gene pathways associated with metabolic signaling. Specifically, pathways regulating fatty acid oxidation, rRNA metabolic processes, mitochondrial inner membrane, and valine, leucine, and isoleucine degradation were significantly affected by Parabacteroides enrichment. Other pathways that were influenced were those involved in neurodegenerative disorders, including Alzheimer’s disease and Parkinson’s disease, though most of the genes affected in these pathways were mitochondrial genes (Fig. 4D, Supplemental Table 2).

At the level of individual genes, dorsal hippocampal RNA sequencing data revealed that 15 genes were differentially expressed in rats enriched with Parabacteroides compared with controls, with 13 genes elevated and two genes decreased in the Parabacteroides group compared with controls (Fig 4C). Consistent with results from gene pathway analyses, several individual genes involved in metabolic processes were elevated by Parabacteroides enrichment, such as Hmgcs2, which is a mitochondrial regulator of ketogenesis and provides energy to the brain under metabolically taxing conditions or when glucose availability is low 44, and Cox6b1, a mitochondrial regulator of energy metabolism that improves hippocampal cellular viability following ischemia/reperfusion injury 45. Parabacteroides enrichment was also associated with incased expression of Slc27A1 and Mfrp, which are each critical for the transport of fatty acids into the brain across capillary endothelial cells 46,47.

Discussion

Dietary factors are a key source of gut microbiome diversity 31,33,48–50 and emerging evidence indicates that diet-induced alterations in the gut microbiota may be linked with altered neurocognitive development 33,50–52. Our results identify species within the genus Parabacteroides that are elevated by habitual early life consumption of dietary sugar and are negatively associated with hippocampal-dependent memory performance. Further, targeted microbiota enrichment of Parabacteroides perturbed both hippocampal- and perirhinal cortex-dependent memory performance. These findings are consistent with previous literature in showing that early life consumption of Western dietary factors impair neurocognitive outcomes 8,9, and further suggest that altered gut bacteria due to excessive early life sugar consumption may functionally link dietary patterns with cognitive impairment.

Our previous data show that rats are not susceptible to habitual sugar consumption-induced learning and memory impairments when 11% sugar solutions are consumed ad libitum during adulthood, in contrast to effects observed in the present and previous study in which the sugar is consumed during early life development 22. It is possible that habitual sugar consumption differentially affects the gut microbiome when consumed during adolescence vs. adulthood. However, a recent report showed that adult consumption of a high fructose diet (35% kcal from fructose) promotes gut microbial “dysbiosis” and neuroinflammation and cell death in the hippocampus, yet without impacting cognitive function 53, suggesting that perhaps neurocognitive function is more susceptible to gut microbiota influences during early life than during adulthood. Indeed, several reports have identified early life critical periods for microbiota influences on behavioral and neurochemical endpoints in germ free mice 3,5,4. However, the age-specific profile of sugar-associated microbiome dysbiosis and neurocognitive impairments remains to be determined.

While our study reveals a strong negative correlation between levels of fecal Parabacteroides and performance in the hippocampal-dependent contextual episodic memory NOIC task, as well as impaired NOIC performance in rats given access to a sugar solution during adolescence, sugar intake did not produce impairments in the perirhinal cortex-dependent NOR memory task. That early life sugar consumption negatively impacts hippocampal-dependent spatial 22 and contextual-based learning without influencing NOR performance is consistent with previous reports using a cafeteria diet high in both fat content and sugar 54. On the other hand, enrichment of P. johnsonii and P. distasonis in the present study impaired memory performance in both tasks, suggesting a broader impact on neurocognitive functioning with this targeted bacterial enrichment approach.

Gene pathway enrichment analyses from dorsal hippocampus RNA sequencing identified multiple neurobiological pathways that may functionally connect gut dysbiosis with memory impairment. Early life sugar consumption was associated with alterations in several neurotransmitter synaptic signaling pathways (e.g., glutamatergic, cholinergic) and intracellular signaling targets (e.g., cAMP, MAPK). A different profile was observed in Parabacteroides-enriched animals, where gene pathways involved with metabolic function (e.g., fatty acid oxidation, branched chain amino acid degradation) and neurodegenerative disease (e.g., Alzheimer’s disease) were altered relative to controls. Given that sugar has effects on bacterial populations in addition to Parabacteroides, and that sugar consumption and Parabacteroides treatment differentially influenced peripheral glucose metabolism and body weight, these transcriptome differences in the hippocampus are not surprising. However, gene clusters involved with dopaminergic synaptic signaling were significantly influenced by both early life sugar consumption and Parabacteroides treatment, thus identifying a common pathway through which both diet-induced and gut bacterial infusion-based elevations in Parabacteroides may influence neurocognitive development. Though differentially expressed genes were commonly affected in opposite directions in Parabacteroides enriched animals compared with early life sugar treated animals, it is possible that perturbations to the dopamine system play a role in the observed cognitive dysfunction. For example, while dopamine signaling in the hippocampus has not traditionally been investigated for mediating memory processes, several recent reports have identified a role for dopamine inputs from the locus coeruleus in regulating hippocampal-dependent memory and neuronal activity 55,56. Interestingly, endogenous dopamine signaling in the hippocampus has recently been linked with regulating food intake and food-associated contextual learning 57, suggesting that dietary effects on gut microbiota may also impact feeding behavior and energy balance-relevant cognitive processes.

Many of the genes that were differentially upregulated in the hippocampus by Parabacteroides enrichment were involved in fat metabolism and transport. Thus, it is possible that Parabacteroides conferred an adaptation in the brain, shifting fuel preference away from carbohydrate toward lipid-derived ketones. Consistent with this framework, Parabacteroides was previously shown to be upregulated by a ketogenic diet in which carbohydrate consumption is drastically depleted and fat is used as a primary fuel source due. Furthermore, enrichment of Parabacteroides merdae together with Akkermansia muciniphila was protective against seizures in mice 33. It is possible that P. distasonis reduces glucose uptake from the gut, enhances glucose clearing from the blood, and/ or alter nutrient utilization in general, an idea further supported by recent finding that P. distasonis is associated with reduced diet- and genetic-induced obesity and hyperglycemia in mice 34.

Collective results provide mechanistic insight into the neurobiological mechanisms that link early life unhealthy dietary patters with altered gut microbiota changes and neurocognitive impairments. Currently probiotics, live microorganisms intended to confer health benefits, are not regulated with the same rigor as pharmaceuticals but instead are sold as dietary supplements. Our findings suggest that gut enrichment with certain species of Parabacteroides is potentially harmful for neurocognitive mnemonic development. These results highlight the importance of conducting rigorous basic science analyses on the relationship between diet, microorganisms, brain, and behavior prior to widespread recommendations of bacterial microbiome interventions for humans.

Author Contributions

E.E.N. and S.E.K. designed the experiments. E.E.N. performed the majority of the behavioral experiments and analyzed the data. E.D. helped with the behavioral experiments and performed the RNA sequencing preparation with Y.C. and X.Y. for analyses of the RNA sequencing data. C.A.O. and E.Y.H. contributed to the design and implementation of the bacterial enrichment procedure. R.J., M.G., R. S. and C.D.L.S., performed the gut microbiome analyses. L.T., C.L., and A.S., helped with behavioral experiments. The paper was written by E.E.N and S.E.K. with additional editorial input from the other authors.

Competing interests

The authors declare no competing interests

Methods and Materials

Experimental Subjects

Juvenile male Sprague Dawley rats (Envigo; arrival post natal day (PN) 26-28; 50-70g) were housed individually in standard conditions with a 12:12 light/dark cycle. All rats had ad libitum access to water and Lab Diet 5001 (PMI Nutrition International, Brentwood, MO; 29.8 % kcal from protein, 13.4% kcal from fat, 56.7% kcal from carbohydrate), with modifications where noted. All experiments were performed in accordance with the approval of the Animal Care and Use Committee at the University of Southern California.

Experiment 1

Twenty one juvenile male rats (PN 26-28) were divided into two groups with equal body weight and given ad libitum access to: 1) 11% weight-by-volume (w/v) solution containing monosaccharide ratio of 65% fructose and 35% glucose in reverse osmosis-filtered water (SUG; n=11) or 2) or an extra bottle of reverse osmosis-filtered water (CTL; n=10). This solution was chosen to model commonly consumed sugar-sweetened beverages in humans in terms of both caloric content and monosaccharide ratio1. Additionally, all rats were given ad libitum access to water and standard rat chow. Food intake, solution intake and body weights were monitored thrice weekly except where prohibited due to behavioral testing. At PN 60, rats underwent Novel Object in Context (NOIC) testing, to measure hippocampal-dependent episodic contextual memory. At PN 67 rats underwent anxiety testing in the Zero Maze, followed by body composition testing at PN 70 and an intraperitoneal glucose tolerance test (IP GTT) at PN 84. Fecal and cecal samples were collected prior to sacrifice at PN 104 (for details on all procedures, see supplemental materials).

In a separate cohort of juvenile male rats (n=8/group) animals were treated as above, but on PD day 60 rats were tested in the Novel Object Recognition (NOR) and Open Field (OF) tasks, with two days in between tasks. Animals were sacrificed and tissue punches were collected from the dorsal hippocampus on PN day 65. Tissue punches were flash frozen in isopentane packed in dry ice and stored at −80°C until further analyses.

Experiment 2

Twenty-three juvenile male rats (PN 26-28) were divided into two groups and received a gavage twice daily (12 hours apart) for 7 days (only one treatment was given on day 7) of either (1) saline (SAL; n=8), or (2) a cocktail of antibiotics consisting of Vancomycin (50 mg/kg), Neomycin (100 mg/kg), and Metronidazole (100 mg/kg) along with 1 mg/mL of ampicillin in their drinking water (ABX; n=15), which is a protocol modified from 2. Animals were housed in fresh, sterile cages on Day 3 of the antibiotic or saline treatment, and again switched to fresh sterile cages on Day 7 after the final gavage. All animals were maintained on sterile, autoclaved water and chow for the remainder of the experiment. Rats in the ABX group were given water instead of ampicillin solution on Day 7. Animals in the ABX group were further subdivided to receive either gavage of a 1:1 ratio of Parabacteroides distasonis and Parabacteroides johnsonii (PARA; n=8) or saline (SAL; n=7) thirty six hours after the last ABX treatment. To minimize potential contamination, rats were handled minimally for 14 days. Cage changes occurred once weekly at which time animals and food were weighed. Experimenters wore fresh, sterile PPE and weigh boxes were cleaned with sterilizing solution in between each cage change. On PN 50 rats were tested in NOIC, on PN 60 rats were tested in NOR, on PN 62 rats were tested in the Zero Maze, followed by Open Field on PN 64. On PN 73 rats were given an IP GTT, and on PN 76 body composition was tested. Rats were sacrificed at PN 83 and dorsal hippocampus tissue punches were collected on PN day 65. Tissue punches were flash frozen in isopentane packed in dry ice and stored at −80°C until further analyses.

IP glucose tolerance test (IP GTT)

Animals were food restricted 24 hours prior to IP GTT. Immediately prior to the test, baseline blood glucose readings were obtained from tail tip and recorded by a blood glucose meter (One touch Ultra2, LifeScan Inc., Milpitas, CA). Each animal was then intraperitoneally (IP) injected with dextrose solution (0.923g/ml by body weight) and tail tip blood glucose readings were obtained at 30, 60, 90, and 120 min after IP injections, as previously described3.

Zero Maze

The Zero Maze is an elevated circular track (63.5 cm fall height, 116.8cm outside diameter), divided into four equal length sections. Two sections were open with 3 cm high curbs, whereas the 2 other closed sections contained 17.5 cm high walls. Animals are placed in the maze facing the open section of the track in a room with ambient lighting for 5 min while the experimenter watches the animal from a monitor outside of the room. The experimenter records the total time spent in the open sections (defined as the head and front two paws in open arms), and the number of crosses into the open sections from the closed sections.

Novel object in context task (NOIC)

NOIC measures episodic contextual memory based on the capacity for an animal to identify which of two familiar objects it has never seen before in a specific context. Procedures were adapted from prior reports 4, 5. Briefly, rats are habituated to two distinct contexts on subsequent days (with the habituation order counterbalanced by group) for 5-min sessions: Context 1 is a semi-transparent box (15in W x 24in L x 12in H) with orange stripes and Context 2 is a grey opaque box (17in W x 17in L x 16in H) (Context identify assignments counterbalanced by group). Day 1 of NOIC begins with each animal being placed in Context 1 containing two distinct objects placed in opposite corners: a 500ml jar filled with blue water (Object A) and a square glass container (Object B) (Object assignments counterbalanced by group). On day 2 of NOIC, animals are placed in Context 2 with duplicates of one of the objects. On NOIC day 3, rats are placed in Context 2 with Objects A and Object B. One of these objects is not novel to the rat, but its placement in Context 2 is novel. All sessions are 5 minutes long and are video recorded. The time spent investigating each object is recorded from the video recordings by an experimenter who is blinded to the treatment groups. Exploration is defined as sniffing or touching the object with the nose or forepaws. The task is scored by calculating the time spent exploring the Novel Object to the context divided by the time spent exploring both Objects A and B combined, which is the novelty or “discrimination index”. Rats with an intact hippocampus will preferentially investigate the object that is novel to Context 2, given that this object is a familiar object yet is now presented in a novel context, whereas hippocampal inactivation impairs the preferential investigation of the object novel to Context 2 4.

Novel Object Recognition

The apparatus used for NOR is a grey opaque box (17in W x 17in L x 16in H). Procedures are adapted from 6. Rats are habituated to the empty arena and conditions for 10 minutes on the day prior to testing. The test begins with a 5 minute familiarization phase, where rats are placed in the center of the arena with two identical copies of the same object to explore. The objects were either two identical cans or two identical bottles, counterbalanced by treatment group. Animals are then removed from the arena and placed in the home cage for 5 minutes. The arena and objects are cleaned with 10% ethanol solution, and one of the objects in the arena is replaced with a different one (either the can or bottle, whichever the animal has not previously seen, i.e., the “novel object”). Animals are again placed in the center of the arena and allowed to explore for 3 minutes. Time spent exploring the objects is recorded via video recording and analyzed using Any-maze activity tracking software (Stoelting Co., Wood Dale, IL).

Open Field

Open field measures general activity level and also anxiety in the rat. A large gray bin, 60 cm (L) X 56 CM (W) is placed under diffuse even lighting (30 lux). A center zone is identified and marked in the bin (19 cm L X 17.5 cm W). A video camera is placed directly overhead and animals are tracked using AnyMaze Software (Stoelting Co., Wood Dale, IL). Animals are placed in the center of the box facing the back wall and allowed to explore the arena for 10 min while the experimenter watches from a monitor in an adjacent room. The apparatus is cleaned with 10% ethanol after each rat is tested.

Body Composition

Body composition (body fat, lean mass) was measured using LF90 time domain nuclear magnetic resonance (Bruker NMR minispec LF 90II, Bruker Daltonics, Inc.).

Bacterial transfer

Parabacteroides distasonis (ATCC 8503) was cultured under anaerobic conditions at 37C in Reinforced Clostridial Medium (RCM, BD Biosciences). Parabacteroides johnsonii (DSM 18315) was grown in anaerobic conditions in PYG medium (modified, DSM medium 104). Cultures were authenticated by full-length 16S rRNA gene sequencing. For bacterial enrichment, 109 colony-forming units of both P. distasonis and P. johnsonii were suspended in 500 uL pre-reduced PBS and orally gavaged into antibiotic-treated rats. When co-administered, a ratio of 1:1 was used for P. distasonis and P. johnsonii.

Gut microbiota DNA extraction and 16s rRNA gene sequencing

All samples were extracted and sequenced according to the guidelines and procedures established by the Earth Microbiome Project 7. DNA was extracted from fecal and cecal samples using the MO BIO PowerSoil DNA extraction kit. PCR targeting the V4 region of the 16S rRNA bacterial gene was performed with the 515F/806R primers, utilizing the protocol described in Caporaso et al.8. Amplicons were barcoded and pooled in equal concentrations for sequencing. The amplicon pool was purified with the MO BIO UltraClean PCR Clean-up kit and sequenced by the 2 x 150bp MiSeq platform at the Institute for Genomic Medicine at UCSD. All sequences were deposited in Qiita Study 11255 as raw FASTQ files. Sequences were demultiplexed using Qiime-1 based “split libraries” with the forward reads only dropping. Demultiplexed sequences were then trimmed evenly to 100 bp and 150 bp to enable comparison to other studies for metaanalysis. Trimmed sequences were matched to known OTUs at 97% identity.

Hippocampal RNA extraction and sequencing

Hippocampi from rats treated with or without sugar or Parabacteroides were subject to RNA-seq analysis. Total RNA was extracted according to manufacturer’s instructions using RNeasy Lipid Tissue Mini Kit (Qiagen, Hilden, Germany). Total RNA was checked for degradation in a Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA). Quality was very high for all samples, and libraries were prepared from 1 ug of total RNA using a NuGen Universal Plus mRNA-seq Library Prep Kit (Tecan Genomics Inc. Redwood City, CA). Final library products were quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc., Waltham, MA, USA), and the fragment size distribution was determined with the Bioanalyzer 2100. The libraries were then pooled equimolarly, and the final pool was quantified via qPCR using the Kapa Biosystems Library Quantification Kit, according to manufacturer’s instructions. The pool was sequenced in an Illumina NextSeq 550 platform (Illumina, San Diego, CA, USA), in Single-Read 75 cycles format, obtaining about 25 million reads per sample. The preparation of the libraries and the sequencing was performed at the USC Genome Core (http://uscgenomecore.usc.edu/)

RNA-seq quality control

Data quality checks were performed using the FastQC tool (http://www.bioinformatics.babraham.ac.uk/projects/fastqc) and low quality reads were trimmed with Trim_Galore (http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/). RNA-seq reads passing quality control were mapped to Rattus novegicus transcriptome (Rnor6) and quantified with Salmon 9. Salmon directly mapped RNA-seq reads to Rat transcriptome and quantified transcript counts. Txiimport 10 were used to convert transcript counts into gene counts. Potential sample outliers were detected by principle component analysis (PCA) and one control and one treatment sample from the Parabacteroides experiment were deemed outliers (Supplementary Figure 6A, B) and removed.

Identification of differentially expressed genes (DEGs)

DESeq211 were used to conduct differential gene expression analysis between sugar treatment and the corresponding controls, or between Parabacteroides treatment and the corresponding controls. Low-abundance genes were filtered out and only those having a mean raw count > 1 in more than 50% of the samples were included. Differentially expressed genes were detected by DESeq2 with default settings. Significant DEGs were defined as Benjamini-Hochberg (BH) adjusted false discovery rate (FDR) < 0.05. For heatmap visualization, genes were normalized with variance stabilization transformation implemented in DESeq2, followed by calculating a z-score for each gene.

Pathway analyses of DEGs

For the pathway analyses, DEGs at p-value < 0.01 was used. Pathway enrichment analysis were conducted using enrichr12 by intersecting each signature with pathways or gene sets from KEGG13, gene ontology biological pathways (GOBP), Cellular Component (GOCP), Molecular Function (GOMF)14 and Wikipathways15. Pathways at FDR < 0.05 were considered significant. Unless otherwise specified, R 3.5.2 was used for the analysis mentioned in the RNA sequencing section.

Additional Statistical methods

Data are presented as means ± SEM. For analytic comparisons of body weight, total food intake, and chow intake, groups were compared using repeated measures ANOVA in Prism software (GraphPad Inc., version 8.0). When significant differences were detected, Sidak post-hoc test for multiple comparisons was used. Area under the curve (AUC) for the IP GTT testing was also calculated using Prism. All other statistical analyses were performed using Student’s two-tailed unpaired t tests in excel software (Microsoft Inc., version 15.26). For all analyses, statistical significance was set at P<0.05.

Extended Data

Extended Data Fig. 1
Extended Data Fig. 1 Effect of early life sugar consumption on food intake and metabolic measures

(A) kcals from sugar over the feeding period beginning at post-natal day (PN) 28 with the first measurement taken on PN 30 (n=11). (B) Kcals from chow intake were lower throughout the feeding period in animals fed early life sugar (n=10,11). (C, D) there were no differences in fat mass or lean mass (n=10,11; two-tailed, type 2 Student’s T-test). (E, F) Results from the intraperitoneal glucose tolerance test show an elevated area under the curve (AUC) in rodents fed sugar solutions during early life (n=10,11; two-tailed, type 2 Student’s T-test; P<.05). CTL=control, SUG= sugar, PN= post-natal day; data shown as mean + SEM.

Extended Data Fig. 2
Extended Data Fig. 2 Effect of early life sugar consumption on the rat cecal microbiota

(A) Principal component analysis (PCA) was run using all phylogenic levels (112 normalized taxa abundances) and shows different clustering patterns based on overall cecal microbial profiles. (B) Linear discriminant analysis (LDA) Effect Size (LEfSe), run using the GALAXY platform, identified characteristic features of the cecal microbiota of rats fed a control diet or early life sugar. Relative differences among groups were used to rank the features with the LDA score set at 2. (C) Identified taxa are displayed by scores and on a phylogenic cladogram. CTL=control, SUG= sugar.

Extended Data Fig. 3
Extended Data Fig. 3 Effect of early life sugar consumption on the rat fecal microbiota.

Filtered bacterial abundances by taxonomic levels phylum, class, order, family, genus in fecal samples from rats fed a control diets or early life sugar. Differences in abundances were assessed by Mann-Whitney non-parametric test. * p<0.05, *** p<0.001. CTL=control, SUG=sugar.

Extended Data Fig. 4
Extended Data Fig. 4 Effect of early life sugar consumption on the rat cecal microbiota:

Filtered bacterial abundances by taxonomic levels phylum, class, order, family, genus in cecal samples from rats fed a control diets or early life sugar. Differences in abundances were assessed by Mann-Whitney non-parametric test. * p<0.05, *** p<0.001. CTL=control, SUG= sugar.

Phylogenic taxonomy legend:

Extended Data Fig. 5.
Extended Data Fig. 5. Experimental design, food intake, and metabolic measures for gut Parabacteroides enrichment

(A) Schematic showing the timeline for the experimental design of the Parabacteroides transfer experiment. (B) Effect of antibiotic treatment on food intake (C) and body weight. (D) Effect of gut Parabacteroides enrichment on body composition 30 days post treatment (n=15, 8, n.s.). (E) Effect of gut Parabacteroides enrichment blood glucose levels during an interaperitoneal glucose tolerance test (IP GTT) (n=15, 8, n.s.) CTL=control, ABX-PARA= Parabacteroides enriched, PN= post-natal day; data shown as mean + SEM.

Extended Data Fig. 6.
Extended Data Fig. 6. Principal component analyses (PCA) of hippocampal gene expression data to identify outliers

(A) PCA identified one control sample (red arrow) as an outlier when all samples from both sugar and Parabacteroides enrichment experiments were considered. (B) PCA identified one treatment sample (red arrow) from the Parabacteroides experiment as an outlier. After removing the outliers, PCA for the remaining samples from the sugar treatment experiment (C) and those from the Parabacteroides enrichment experiments (D).

Extended Data Fig. 7.
Extended Data Fig. 7. Comparison of hippocampal gene expression pathways altered by sugar and Parabacteriodes

The dopaminergic synapse pathway overlaps in the sugar and Parabacteroidas transfer experiments. Red= upregulated by sugar, dark blue= downregulated by sugar, orange= upregulated by Parabacteroides, light blue= downregulated by Parabacteroides. * P < 0.05 and ** P < 0.01. Dotted line indicated ± 0.25 log2 fold change.

Acknowledgements

We thank Alyssa Cortella for contributing the rodent artwork. We thank Caroline Szjewski, Lekha Chirala, Vaibhav Konanur, Sarah Terrill, and Ted Hsu for their critical contributions to the research. The research was supported by DK104897, DK118402, and institutional funds to S.E.K., DK111158 to E.E.N., DK116558 to A.N.S., DK 118944 to C.M.L. C.A.O. was supported by an F31 AG064844. E.Y.H. was supported by ARO MURI award W911NF-17-1-0402. DK104363 to X.Y., Eureka Scholarship and BWF-CHIP Fellowship to Y.C.

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The gut microbiome regulates memory function
Emily E Noble, Elizabeth Davis, Linda Tsan, Yen-Wei Chen, Christine A. Olson, Ruth Schade, Clarissa Liu, Andrea Suarez, Roshonda B Jones, Michael I Goran, Claire de La Serre, Xia Yang, Elaine Y. Hsiao, Scott E Kanoski
bioRxiv 2020.06.16.153809; doi: https://doi.org/10.1101/2020.06.16.153809
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