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. 2023 Feb;137(1):15-28.
doi: 10.1037/bne0000532. Epub 2022 Jul 28.

Acute gut microbiome changes after traumatic brain injury are associated with chronic deficits in decision-making and impulsivity in male rats

Michelle A Frankot  1 , Christopher M O'Hearn  1 , Alyssa M Blancke  1 , Bryan Rodriguez  1 , Kristen M Pechacek  1 , Jasleen Gandhi  2 , Gangqing Hu  2 , Kris M Martens  1 , Cole Vonder Haar  1
Affiliations

Acute gut microbiome changes after traumatic brain injury are associated with chronic deficits in decision-making and impulsivity in male rats

Michelle A Frankot et al. Behav Neurosci. 2023 Feb.

Abstract

The mechanisms underlying chronic psychiatric-like impairments after traumatic brain injury (TBI) are currently unknown. The goal of the present study was to assess the role of diet and the gut microbiome in psychiatric symptoms after TBI. Rats were randomly assigned to receive a high-fat diet (HFD) or calorie-matched low-fat diet (LFD). After 2 weeks of free access, rats began training on the rodent gambling task (RGT), a measure of risky decision-making and motor impulsivity. After training, rats received a bilateral frontal TBI or a sham procedure and continued postinjury testing for 10 weeks. Fecal samples were collected before injury and 3-, 30-, and 60 days postinjury to evaluate the gut microbiome. HFD altered the microbiome, but ultimately had low-magnitude effects on behavior and did not modify functional outcomes after TBI. Injury-induced functional deficits were far more robust; TBI substantially decreased optimal choice and increased suboptimal choice and motor impulsivity on the RGT. TBI also affected the microbiome, and a model comparison approach revealed that bacterial diversity measured 3 days postinjury was predictive of chronic psychiatric-like deficits on the RGT. A functional metagenomic analysis identified changes to dopamine and serotonin synthesis pathways as a potential candidate mechanism. Thus, the gut may be a potential acute treatment target for psychiatric symptoms after TBI, as well as a biomarker for injury and deficit severity. However, further research will be needed to confirm and extend these findings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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Figures

Figure 1.
Figure 1.
The experimental timeline is depicted in Panel A. Negative week numbers represent weeks prior to injury; positive numbers represent weeks after injury. Rats were free fed a high-fat (HFD) or low-fat diet (LFD). Then, they were trained on an operant gambling task. When behavior was stable, bilateral frontal injuries were induced, and testing continued for 10 weeks. Fecal samples were collected 1 day prior to injury and 3-, 30-, and 60-days post injury (arrows). Rats were euthanized during post-injury Week 11, and brain tissue was collected. A schematic of the Rodent Gambling Task (RGT) is depicted in Panel B. After initiating a trial, rats were able to choose from any of the four options. Each hole was associated with a different probability and magnitude of reinforcement (sugar pellets) and punishment (time outs from earning sugar pellets). Body weight data is depicted in Panel C. TBI decreased the progression of weight gain over time after injuries (p < 0.001) but did not interact with the HFD (p = 0.85). There were no differences in body weight due to diet (p = 0.21).
Figure 2.
Figure 2.
The effects of diet and injury on choice of the P1, P2, P3, and P4 options (panels A-D) of the Rodent Gambling Task. Data shown are mean (points) + SEM (error bars). TBI drastically increased suboptimal P1 choice (Main effect of injury: F(1,30.97) = 37.32, p < 0.001) and decreased optimal P2 choice (Main effect of injury: F(1,31) = 13.83, p < 0.001). Injury by week interactions suggest recover over time for TBI rats by increasing P2 choice (F(1, 1456.19) = 15.89, p < 0.001) and decreasing P3 (F(1, 1456.29) = 22.41, p <0.001) and P4 choice (F(1, 1456.46) = 10.47, p = 0.001). There no main effect of diet on P2 choice (F(1, 31.00) = 0.14, p = 0.707), but there was a diet by week interaction (F(1, 1456.19) = 14.82, p < 0.001), such that HFD rats decreased P2 choice over time.
Figure 3.
Figure 3.
The effects of diet and injury on other Rodent Gambling Task variables: premature responses (A), omissions (B), total reinforcers earned (C), latency to respond (D) and latency to collect reinforcers (E). Data shown are mean (points) + SEM (error bars). TBI led to significant impairments across all variables (F(1,30.97) = 6.91, p = 0.012, F(1,31.04) = 7.71, p =0.009, F(1,31.01) = 37.84, p < 0.001, F(1,31.04) = 14.61, p < 0.001, F(1,31) = 113.64, p < 0.001, respectively for the main effect of Injury). Some of these deficits, including omissions (Injury x Week: F(1,1457.47) = 7.99, p < 0.001), reinforcers earned (Injury x Week: F(1,1494.04) = 262.42, p < 0.001), choice latency (Injury x Week: F(1,2370.04) = 172.99, p < 0.001), and collection latency (Injury x Week: F(1,2368) = 595.33, p < 0.001) attenuated over time. HFD interacted with injury to exacerbate effects on premature responses (Diet x Injury x Week: F(1,1460.8) = 4.79, p = 0.029) and omissions (Diet x Injury x Week: F(1,1457.49) = 7.99, p = 0.005).
Figure 4.
Figure 4.
Effects of diet and injury on remaining frontal brain volume and lesion size (panels A, B). An exemplar sham and TBI brain are depicted (panel A), showing positions for lesion analysis. TBI decreased remaining frontal brain volume (F(1,32) = 17.24, p < 0.001) and increased lesion size (F(1,32) = 27.2, p < 0.001) but did not interact with diet (F(1,32) = 2.55, p = 0.45, F(1,32) = 0.160, p = 0.693). Data shown in Panel B are mean (bars) + SEM (error bars).
Figure 5.
Figure 5.
The effects of diet, injury, and fecal collection timepoint on alpha diversity (Panel A) and beta diversity (Panel B). There was no effect of TBI on alpha diversity (F(1,59) = 1.67, p = 0.202) , but TBI did increase beta diversity (R2 = 0.05, p = 0.034). There was also a significant effect of time (R2 = 0.08, p = 0.019) such that beta diversity on Day 3 was greater than Day 30 (Z = 4.43, p < 0.001) and Day 60 (Z = 2.37, p = 0.027). Data shown in Panel A are individual subject values (points) and the group mean (lines). Panel B contains individual subject values (points) and data ellipses surrounding them.
Figure 6.
Figure 6.
The effects of diet, injury, and fecal collection timepoint on abundance of three phyla: Firmicutes, Bacteroidetes, and Proteobacteria (Panels A-C), abundance of classes from phyla with significant effects (Panels D-E), and abundance of orders from classes with significant effects (Panels F-G). At the phyla level, TBI decreased Firmicutes (p = 0.040), but had no effect on Bacteroidetes (p = 0.159) or Proteobacteria (p = 0.470); Diet increased Firmicutes (p = 0.003), decreased Bacteroidetes (p < 0.001), and had no effect on Proteobacteria (p = 0.527). Within Firmicutes, TBI caused an acute decrease in class Clostridia (p = 0.008) and order Clostridiales (p = 0.018). Within Bacteroidetes, HFD increased abundance of class Bacteroidia (p = 0.001) and order Bacteroidales (p = 0.007). Data shown in all panels are mean (points) + SEM (error bars).
Figure 7.
Figure 7.
Results of the ALDEx2 comparisons between TBI and Sham rats on pathways generated by picrust2 at Day 3 (Panel A), 30 (Panel B), and 60 (Panel C) post injury. The magnitude of difference between TBI and Sham is on the x-axis, and the p-value for that difference is on the y-axis. Each point represents a different functional metagenomic pathway. Significant p-values (<0.05) are signified by points that appear below the dashed horizontal line. At 3 days post injury, there were significant differences for a multitude of pathways, including prominent changes to the pathways involved in precursors to serotonin and dopamine (i.e., tyrosine, tryptophan, phenylalanine, chorismate synthesis and metabolism). Pathways involved in tyrosine synthesis are highlighted in blue, tryptophan synthesis in red, and the common precursor chorismate in purple.
Figure 8.
Figure 8.
Spiderplot visualization of model comparison testing. Different metrics of model strength (Akaike information criterion [AIC], Bayesian information criterion [BIC], R2 marginal, R2 conditional, and residual mean square error [RMSE]) are provided for 4 combinations of independent variables (TBI, Diversity, TBI+Diversity, TBI*Diversity*HFD) used to predict behavior on the Rodent Gambling Task. At 3 days post injury, the addition of bacterial diversity reduced the AIC for predictions of both optimal choice and impulsivity. At other timepoints, the addition of bacterial diversity and diet into the model improved the R2 and RMSE of the model but not the AIC or BIC.
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