The gut microbiota profile of schizophrenic patients

We carried out shotgun sequencing on fecal samples from 90 medication-free patients and 81 healthy controls (for demographic and clinical characteristics see Supplementary Data 1–3) and obtained an average of 11.46 gigabases (Gb) sequence data per sample and mapped the high-quality reads onto a comprehensive reference gene catalog of 11.4 million genes21 (Supplementary Data 4).

The gut microbiota in schizophrenic patients showed greater α diversity at the genus level (P = 0.027, Wilcoxon rank-sum test), higher β diversity at the genus level (P < 0.001, Wilcoxon rank-sum test) and microbial gene level (P < 0.001, Wilcoxon rank-sum test) and comprised more genes compared with healthy controls (Supplementary Fig. 1). Out of a total of 360 metagenomic operational taxonomic units (mOTUs)22, 83 mOTUs showed significant differences in relative abundance between patients and controls (P < 0.05 and false discovery rate (FDR) = 0.136, Wilcoxon rank sum test and Storey’s FDR method; Supplementary Data 5a). After adjusting for BMI, age, sex, and diet, these 83 mOTUs were still significant (Supplementary Data 5a). The gut microbiota in schizophrenic patients harbored many facultative anaerobes such as Lactobacillus fermentum, Enterococcus faecium, Alkaliphilus oremlandii, and Cronobacter sakazakii/turicensis, which are rare in a healthy gut. Additionally, bacteria that are often present in the oral cavity, such as Veillonella atypica, Veillonella dispar, Bifidobacterium dentium, Dialister invisus, Lactobacillus oris, and Streptococcus salivarius were more abundant in patients with schizophrenia than in healthy controls, indicating a close association between the oral and the gut microbiota in schizophrenia.

We then constructed a mOTU network to depict the co-occurrence correlation between the schizophrenia-associated gut bacteria (Fig. 1). Schizophrenia-enriched mOTUs were more interconnected than control-enriched mOTUs (Spearman’s correlation coefficient <−0.3 or >0.3, P < 0.05). The mOTU species from the genera Streptococcus and Veillonella showed positive cross-correlations. Moreover, the majority of the species in these two clusters of correlated mOTUs originated from the oral cavity, again pointing to the relation between oral resident bacteria and gut bacteria, suggesting that oral resident bacteria in a synergistic manner may colonize the gut in schizophrenic patients (Fig. 1 and Supplementary Data 5a).

Fig. 1: Network of mOTUs differentially enriched in healthy controls and schizophrenic patients. Node sizes reflect the mean abundance of significant mOTUs. mOTUs annotated to species are colored according to family (Red edges, Spearman’s rank correlation coefficient > 0.3, P < 0.05; blue edges, Spearman’s rank correlation coefficient <−0.3, P < 0.05;). See detailed statistical data in supplementary Source Data file. Full size image

Functional modules and pathways enriched in the gut microbiota of patients relative to controls were analyzed using the KEGG database (Supplementary Data 6). The relative enrichment of 579 KEGG modules and 323 KEGG pathways varied significantly between the two groups. Schizophrenia-depleted microbial functional modules included pectin degradation, lipopolysaccharide biosynthesis, autoinducer-2 (AI-2) transport system, glutamate/aspartate transport system, beta-carotene biosynthesis, whereas schizophrenia-enriched functional modules included methanogenesis, the gamma-aminobutyrate (GABA) shunt, and transport system of manganese, zinc, and iron (Supplementary Data 6).

Neuroactive potential of schizophrenia-related bacteria

We next compared the altered microbial neuroactive potential of the gut microbiota of schizophrenic patients with the controls at the species level using the method reported by Valles-Colomer et al.20. We mapped the metagenomic data of the 171 samples to a genome database including the 42 microbial species that were detected based on the 83 schizophrenia-associated mOTUs using PanPhlan23 and calculated the prevalence of species-level microbes. We then determined whether the abundance of 56 previously reported gut-brain modules (GBMs)20, present in each microbial species, varied significantly between schizophrenic patients and controls. The GBM set of each microbial species was obtained by cross-checking GBM-related genes and the species gene repertoires (Supplementary Data 7a). The frequency of the occurrence of each GBM within each species was compared between patients and controls using a Chi-squared test (Supplementary Data 7b). Schizophrenia-associated GBMs included short-chain fatty acid synthesis (acetate, propionate, butyrate, and isovaleric acid), tryptophan metabolism, and the synthesis of several neurotransmitters, such as glutamate, GABA, and nitric oxide (Fig. 2).

Fig. 2: The gut-brain modules present in schizophrenia-associated bacterial species. A green dot indicates a statistically significant association between a gut-brain modules present in schizophrenia-associated bacterial species and a metabolite. No dot represents a non-significant association or a non-existent association. The difference in relation to presence between schizophrenic patients and heathy controls was calculated (Chi-square test, P < 0.05). The bar plot shows the frequency of each bacterial species present in schizophrenic patients (SCZ, blue bar) and healthy controls (HC, red bar), respectively. See detailed statistical data in supplementary Source Data file. Full size image

We chose to validate the presence of the GBM associated with tryptophan metabolism in schizophrenia, as tryptophan metabolism is modulated by the gut microbiota and implicated in schizophrenia pathogenesis24,25. Hence, serum tryptophan metabolites were measured in patients and controls and correlated with the presence of tryptophan modules in the gut microbiota. In agreement with the higher abundance of tryptophan metabolisms related GBMs, we observed lower serum tryptophan levels and higher kynurenic acid (KYNA) levels in schizophrenic patients(Supplementary Fig. 2a, c). Moreover, serum tryptophan levels were negatively correlated with the abundances of 38 bacterial species enriched in schizophrenic patients and positively correlated with 6 bacterial species enriched in controls (Supplementary Fig. 2d). Similarly, serum KYNA levels were positively correlated with 10 schizophrenia-enriched bacterial species and negatively correlated with 3 control-enriched bacterial species (Supplementary Fig. 2d). Thus, an altered gut microbiota may be associated with changes in serum levels of tryptophan and KYNA in schizophrenia.

Gut microbial species characteristic of schizophrenia

To identify novel gut bacterial species associated with schizophrenia and evaluate their diagnostic values, we first constructed a set of random forest disease classifiers based on gut mOTUs. We performed a five-fold cross-validation procedure ten times on 90 patients and 81 controls. Twenty six gut mOTUs reached the lowest classifier error in the random forest cross validation, and the area under the receiver operating characteristic curve (AUC) of the model was 0.896 (Fig. 3a, b). This microbial based classifier was not significant influenced by age, gender, BMI, and diet style. (Supplementary Data 8). This discriminatory model was validated on an additional validation cohort consisting 45 patients taking antipsychotics and 45 controls (Supplementary Data 9). The model still distinguished patients from controls with an AUC of 0.765. Among the 26 mOTUs included in the classifier, 11 bacterial species with taxonomic identity were significantly enriched in schizophrenia, namely Akkermansia muciniphila, Bacteroides plebeius, Veillonella parvula, Clostridium symbiosum, Eubacterium siraeum, Cronobacter sakazakii/turicensis, S. vestibularis, Alkaliphilus oremlandii, Enterococcus faecium, Bifidobacterium longum, and Bifidobacterium adolescentis. Some of these microbial species were significantly associated with symptom severity, cognitive performance, and diagnosis (Fig. 3c).

We next performed metagenomic analysis on the fecal samples from 38 of the 90 patients after 3-months of treatment (27 with risperidone and 11 with other antipsychotics, shown in Supplementary Data 1). The psychotic symptoms and cognitive impairment improved greatly along with treatment (Supplementary Fig. 3). However, only approximately half of mOTUs that distinguished SCZ patients from controls returned to the levels in controls after treatment (Fig. 3d). As the sample size of the follow-up patients was smaller, the statistical significance threshold was increased from 0.05 to 0.1. Of the 26 identified microbial species, 20 species remained significantly changed between 81 controls and 38 baseline patients (P < 0.1, FDR = 0.44, Benjamini and Hochberg method, Fig. 3d). After 3-months of treatment, the abundances of 12 of these 26 mOTUs remained significantly changed compared with the 81 controls (P < 0.1, FDR = 0.33, Benjamini and Hochberg method, Supplementary Data 10). Pair-wise comparison of all gut mOTUs for treatment effect in the follow-up patients revealed 48 differentially abundant bacterial species (P < 0.05 and FDR = 0.420, Paired Wilcoxon rank sum test; Benjamini and Hochberg method, Supplementary Data 11). However, only 5 of the 48 differentially abundant species were included in the 26 mOTUs schizophrenia classifiers. This result suggests that antipsychotic treatment influences the gut microbiota, but does not completely restore the altered microbiota associated with schizophrenia.

Fig. 3: Gut microbiome-based discrimination between schizophrenic patients and healthy controls. a Receiver operating characteristic curve (ROC) according to 171 samples of the discovery set (green line) and 90 independent validation samples (pink line) calculated by cross-validated random forest models. Area under ROC (AUC) and the 95% confidence intervals are also shown. b The 26 mOTUs with most weight to discriminate schizophrenic (SCZ) patients and healthy controls (HC) were selected by the cross-validated random forest models. The length of line indicates the contribution of the mOTU to the discriminative model. The color of each mOTU indicates its enrichment in schizophrenic patients (blue) or healthy controls (red) or no significant direction (black), respectively. c Spearman’s correlation of 26 mOTUs classifiers with three types of neurotransmitter in serum (green), seven types of cognitive function evaluated using the MATRICS Consensus Cognitive Battery (purple), and with the positive score and the negative score of the Positive and Negative Syndrome Scale (light green). Only significant associations are displayed with correlation coefficient (P-value < 0.05). d The relative abundance (log 10 ) of 26 mOTUs classifiers in 90 HCs and 38 SCZ patients at baseline and on a follow-up (3 months later). The dot represents one value from individual participants and boxes represent the median and interquartile ranges (IQRs) between the first and third quartiles; whiskers represent the lowest or highest values within 1.5 times IQR from the first or third quartiles. Outliers are not shown. GABA: 4-aminobutyric acid; TMT: Trail Making Test; BACS: Brief Assessment of Cognition in Schizophrenia; Fluency: Category Fluency in Animal Naming; WMS-III: Wechsler Memory Scale-Third Edition for working memory; HVLT-R: Hopkins Verbal Learning Test-Revised for visual learning; NAB: Neuropsychological Assessment Battery for reasoning and problem solving; MSCEIT: Mayer-Salovey-Caruso Emotional Intelligence Test for social cognition. See detailed statistical data in supplementary Source Data file. Full size image

S. vestibularis induced schizophrenia-like behaviors in mice

S. vestibularis contributed to discriminate patients from controls and was associated with serum GABA, tryptophan, KYNA, and the Brief Assessment of Cognition in Schizophrenia (BACS) scores in MATRICS Consensus Cognitive Battery (MCCB) test (Fig. 3 and Supplementary Fig. 2). Moreover, S. vestibularis, present in the gut of a number of schizophrenic patients, was predicted to have GBMs related to glutamate synthesis, GABA degradation, and isovaleric acid synthesis (Fig. 2). As some pathogenic species of Streptococcus are known to enter the brain26, and have been implicated in pediatric acute-onset neuropsychiatric syndrome27,28, we asked if S. vestibularis might play a role in the pathophysiology of schizophrenia. Hence, we transplanted S. vestibularis ATCC 49124, using oral gavage and drinking water, into C57BL/6 mice after antibiotics-based microbiota depletion (Supplementary Fig. 4). Another strain of Streptococcus, S. thermophilus ST12, which is widely present in the human gut, was used as a bacterial control. Behavioral tests were performed to evaluate the effect of S. vestibularis transplantation (Fig. 4a). Quantitative polymerase chain reaction (q-PCR) used to quantify the 16S rRNA gene of S. vestibularis and S. thermophilus, revealed that their concentration increased by 4,164- and 6,183-fold immediately after transplantation and remained at a 31.2- and 58.1-fold increase after the behavioral tests as compared to the control mice (Supplementary Fig. 5). Compared to control mice gavaged with saline or with S. thermophilus, the S. vestibularis-treated mice exhibited an increase in the total traveled distance and times of rearing during a 30-minute open-field test (Fig. 4b, d). They continued their hyperlocomotion after the 10-minute habituation period and showed no obvious decline in locomotion activity after a period of 30-minutes (Fig. 4c). In the three-chamber social test, the S. vestibularis mice displayed obvious deficits in sociability and social novelty, as they were much less sociable and avoided social novelty (Fig. 4e–g). However, in Barnes maze, elevated plus maze, and tail suspension test, the mice transplanted with S. vestibularis displayed spatial memory function, depressive state, and anxiety levels similar to either saline or S. thermophilus-treated mice (Supplementary Fig. 6). There were no significant changes in body weight, systemic pro-inflammatory cytokines, and endotoxin, and HPA axis hormones between S. vestibularis-treated, S. thermophilus-treated, and control mice (Supplementary Fig. 7 a–i).

Fig. 4: Streptococcus vestibularis induces hyperkinetic behavior and impaired social interaction in mice. a Schematic diagram of bacterial transplantation and behavioral tests. b The cumulative distance (meters) in different zones in 30-min Open field test (OFT) in the three groups of mice with oral gavage of Streptococcus vestibularis, S. thermophilus, and saline, respectively. c the cumulative distance (meters) in every 10-minutes time interval of OFT traveled and d the number of rearing by S. vestibularis-gavaged mice compared to mice gavaged with S. thermophilus and control mice. e–g three-chamber social test (TCST) comparing sociability of S. vestibularis-gavaged mice to that of S. thermophilus-gavaged mice and control mice. The results show that S. thermophilus-gavaged mice and saline-gavaged mice display obvious sociability, i.e., demonstrate an increase in the number of times probing a mouse (e, P < 0.0001) and spending longer time interacting with a mouse (f, P = 0.002) compared to an empty cage, and obvious social novelty, i.e., spending longer time interacting with an unacquainted mouse (new mouse; g, P = 0.005) in comparison with an acquainted mouse. However, these types of social behaviors were not observed in S. vestibularis-gavaged mice (for sociability: e, P = 0.881; f, P = 0.282; for social novelty, g, P = 0.923). The data are representative of two independent experiments and are presented as means ± SEM (n = 16 S. vestibularis-gavaged mice or S. thermophiles-gavaged mice, 17 saline-gavaged mice per independent experiment in OFT; n = 16 mice/group/independent experiment in TCST). The circle represents one value from individual mice (b, d, e–g). P-values were determined by one-way analysis of variance (ANOVA) (b), repeated measure two-way ANOVA followed by Sidak’s multiple comparisons test (c; Blue P: S. vestibularis-gavaged versus saline-gavaged mice; green P: S. thermophilus-gavaged versus saline-gavaged mice), two-sided Kruskal-Wallis test followed by Dunn’s multiple comparisons test (d), or two-way (ANOVA) followed by Sidak’s multiple comparisons test (e–g). See detailed statistical data in supplementary Source Data file. Full size image

We then compared the transcriptome and neurotransmitter levels between S. vestibularis-treated and saline-treated mice in peripheral tissues and brain. S. vestibularis-treated mice had significantly lower levels of dopamine in serum, intestinal contents, and colonic tissue, as well as decreased GABA levels in the intestinal contents immediately after the transplantation, but these effects disappeared 10 days post-transplantation (Supplementary Fig. 8b, e, h, f). Intestinal contents of S. vestibularis-treated mice showed increased levels of 5-HT throughout the behavioral tests (Supplementary Fig. 8d). S. vestibularis transplantation did not induce obvious inflammatory cell infiltration (Supplementary Fig. 7j), but induced changes in the expression of numerous immune/inflammation-related genes in the intestine when compared with mice receiving saline gavage (Supplementary Data 12a, b). By gene enrichment analysis, we found that these genes were enriched in cytokine-cytokine receptor interaction, chemokine signaling pathways, leukocyte trans-endothelial migration, complement and coagulation cascades, antigen processing and presentation, intestinal immune network for IgA production, and inflammatory bowel disease (Supplementary Fig. 9a, b). These results suggested that S. vestibularis may influence gut immune homeostasis. In the brain, the levels of neurotransmitters were not affected by transplantation with S. vestibularis and only tryptophan decreased in the prefrontal cortex of S. vestibularis-treated mice (Supplementary Data 13). However, we observed 354, 540, and 470 significantly differentially expressed gene in the PFC, striatum, and hippocampus, respectively, between S. vestibularis-treated and saline-treated mice (Supplementary Data 12c–e). The pathways influenced by these differentially expressed genes include defense responses and immune-regulating pathways, similar to the observed differentially expressed genes in the intestine, as well as peroxisome proliferator-activated receptor signaling pathway, steroid biosynthesis, tyrosine, and tryptophan metabolism (Supplementary Fig. 9c–e).