Kismet/CHD7/CHD8 affects gut biomechanics, the gut microbiome, and gut-brain axis in Drosophila melanogaster

The gut-brain axis may contribute to the pathophysiology of neurodevelopmental disorders, yet it is often unclear how risk genes associated with these disorders affect gut physiology in a manner that could impact microbial colonization. We addressed this question using Drosophila melanogaster with a null mutation in kismet, the ortholog of chromodomain helicase DNA-binding protein ( CHD ) family members CHD7 and CHD8. In humans, CHD7 and CHD8 are risk genes for neurodevelopmental disorders with co-occurring gastrointestinal symptoms . We found kismet mutant flies have a significant increase in gastrointestinal transit time, indicating functional homology of kismet with CHD7/CHD8 in vertebrates. To measure gut tissue mechanics, we used a high-precision force transducer and length controller, capable of measuring forces to micro-Newton precision, which revealed significant changes in the mechanics of kismet mutant guts, in terms of elasticity, strain stiffening, and tensile strength. Using 16S rRNA metagenomic sequencing, we also found kismet mutants have reduced diversity of gut microbiota at every taxonomic level and an increase in pathogenic taxa. To investigate the connection between the gut microbiome and behavior, we depleted gut microbiota in kismet mutant and control flies and measured courtship behavior. Depletion of gut microbiota rescued courtship defects of kismet mutant flies, indicating a connection between gut microbiota and behavior. In striking contrast, depletion of gut microbiome in the control strain reduced courtship activity. This result demonstrated that antibiotic treatment can have differential impacts on behavior that may depend on the status of microbial dysbiosis in the gut prior to depletion. We propose that Kismet influences multiple gastrointestinal phenotypes that contribute to the gut-brain axis to influence behavior. Based on our results, we also suggest that gut tissue mechanics should be considered as an element in the gut-brain communication loop, both influenced by and potentially influencing the gut microbiome and neuronal development.

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Meta-analysis of the Parkinson’s disease gut microbiome suggests alterations linked to intestinal inflammation

npj Parkinson s Disease ◽

10.1038/s41531-021-00156-z ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Stefano Romano ◽

George M. Savva ◽

Janis R. Bedarf ◽

Ian G. Charles ◽

Falk Hildebrand ◽

...

Keyword(s):

Parkinson’S Disease ◽

Fatty Acids ◽

Parkinson's Disease ◽

Gut Microbiota ◽

Gut Microbiome ◽

Intestinal Inflammation ◽

Meta Analysis ◽

Gastrointestinal Symptoms ◽

Short Chain Fatty Acids ◽

Inflammatory Status

AbstractThe gut microbiota is emerging as an important modulator of neurodegenerative diseases, and accumulating evidence has linked gut microbes to Parkinson’s disease (PD) symptomatology and pathophysiology. PD is often preceded by gastrointestinal symptoms and alterations of the enteric nervous system accompany the disease. Several studies have analyzed the gut microbiome in PD, but a consensus on the features of the PD-specific microbiota is missing. Here, we conduct a meta-analysis re-analyzing the ten currently available 16S microbiome datasets to investigate whether common alterations in the gut microbiota of PD patients exist across cohorts. We found significant alterations in the PD-associated microbiome, which are robust to study-specific technical heterogeneities, although differences in microbiome structure between PD and controls are small. Enrichment of the genera Lactobacillus, Akkermansia, and Bifidobacterium and depletion of bacteria belonging to the Lachnospiraceae family and the Faecalibacterium genus, both important short-chain fatty acids producers, emerged as the most consistent PD gut microbiome alterations. This dysbiosis might result in a pro-inflammatory status which could be linked to the recurrent gastrointestinal symptoms affecting PD patients.

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Yoghurt Consumption is Associated With Transient Changes in the Composition of the Human Gut Microbiome

10.21203/rs.3.rs-99718/v1 ◽

2020 ◽

Author(s):

Caroline Ivanne Le Roy ◽

Alexander Kurilshikov ◽

Emily Leeming ◽

Alessia Visconti ◽

Ruth Bowyer ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

Visceral Fat ◽

Gut Microbiome ◽

Body Weight Gain ◽

Healthy Eating Index ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Shotgun Metagenomic Sequencing

Abstract Background: Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. Results: According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17±0.34; P = 2.72x10-10) and improved metabolic health characterised by reduced visceral fat (beta = -28.18±11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41±0.051; P = 6.14x10-12) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30±0.052; P = 1.49x10-8) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LifeLines-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed that increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation.Conclusions: Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species (i.e. S. thermophilus and B. lactis).

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An online atlas of human plasma metabolite signatures of gut microbiome composition

10.1101/2021.12.23.21268179 ◽

2021 ◽

Author(s):

Koen F. Dekkers ◽

Sergi Sayols-Baixeras ◽

Gabriel Baldanzi ◽

Christoph Nowak ◽

Ulf Hammar ◽

...

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

High Performance ◽

Alpha Diversity ◽

Plasma Metabolites ◽

Uremic Toxin ◽

Metagenomic Sequencing ◽

Microbiome Composition ◽

Plasma Metabolite

The human gut microbiota produces a variety of small compounds, some of which enter the bloodstream and impact host health. Conversely, various exogenous nutritional and pharmaceutical compounds affect the gut microbiome composition before entering circulation. Characterization of the gut microbiota—host plasma metabolite interactions is an important step towards understanding the effects of the gut microbiota on human health. However, studies involving large and deeply phenotyped cohorts that would reveal such meaningful interactions are scarce. Here, we used deep metagenomic sequencing and ultra-high-performance liquid chromatography linked to mass spectrometry for detailed characterization of the fecal microbiota and plasma metabolome, respectively, of 8,584 participants invited at age 50 to 64 of the Swedish CArdioPulmonary bioImage Study (SCAPIS). After adjusting for multiple comparisons, we identified 1,008 associations between species alpha diversity and plasma metabolites, and 318,944 associations between specific gut metagenomic species and plasma metabolites. The gut microbiota explained up to 50% of the variance of individual plasma metabolites (mean of 4.7%). We present all results as the searchable association atlas "GUTSY" as a rich resource for mining associations, and exemplify the potential of the atlas by presenting novel associations between oral medication and the gut microbiome, and microbiota species strongly associated with levels of the uremic toxin p-cresol sulfate. The association atlas can be used as the basis for targeted studies of perturbation of specific bacteria and for identification of candidate plasma biomarkers of gut flora composition.

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Machine-Learning Model for Resistance/Relapse Prediction in Immune Thrombocytopenia Using Gut Microbiota and Function Signatures

Blood ◽

10.1182/blood-2021-148987 ◽

2021 ◽

Vol 138 (Supplement 1) ◽

pp. 18-18

Author(s):

Feng-Qi Liu ◽

Qi Chen ◽

Qingyuan Qu ◽

Xueyan Sun ◽

Qiu-Sha Huang ◽

...

Keyword(s):

Machine Learning ◽

Gut Microbiota ◽

Corticosteroid Therapy ◽

Gut Microbiome ◽

Immune Thrombocytopenia ◽

Corticosteroid Treatment ◽

Metagenomic Sequencing ◽

Chronic Itp ◽

Microbial Biomarkers ◽

And Function

Abstract Introduction Growing evidence has implicated gut microbiota in the pathogenesis of immune thrombocytopenia (ITP). In a previous research study, we found dysbiosis in the phylogenetic composition and function of gut microbiome in ITP and that corticosteroid treatment may have a strong effect on gut microbiota [Sci China Life Sci, 2020]. Corticosteroids have been widely used in the initial treatment of newly diagnosed ITP patients, but most adult patients relapse upon cessation of steroid treatment. Patients on agents in subsequent therapy may improve at any time, but which patients improve and when is unpredictable. The gut microbiome has been increasingly used in the assessment and prediction of immunomodulatory therapy in autoimmune diseases and cellular immunotherapy in cancers. Here, we provide evidence that gut microbiota and function signatures can be used to predict immune thrombocytopenia patients at high risk of relapse/resistance after corticosteroid treatment and to identify patients that are more likely to benefit from TPO-RAs in subsequent therapy. Methods Seventy-five fecal samples from 60 patients with newly diagnosed ITP (60 specimens before corticosteroid therapy and 15 specimens after corticosteroid therapy) and 41 samples from persistent/chronic ITP before and after treatment with TPO-RAs, including eltrombopag and avatrombopag were collected for deep shotgun metagenomic sequencing. To identify the microbial biomarkers related to relapse/resistance after corticosteroid treatment, we constructed a random forest classifier using machine learning to determine the risk of relapse/resistance of a training cohort of 30 patients from baseline samples and validated the classifier for 30 patients. Patients with persistent/chronic ITP were divided into responders and nonresponders according to their response to TPO-RA treatment in subsequent therapy. After identifying the microbial species and functional biomarkers related to the response to TPO-RA therapy, a random forest classifier was constructed using a training set of 20 patients and validated using a validation set of 21 patients. Results We used a metagenomic sequencing technique to investigate the differences among gut microbiota associated with relapse within 3 months of corticosteroid treatment. We observed that the diversity and composition of the microbial community in ITP patients after corticosteroid therapy (Post-C) changed significantly from the baseline (Pre-C), whereas the gut microbiota of the remission group was similar to that of the HC group, which implies that a shift in the gut microbiome could represent a return to homeostasis. To identify the microbial biomarkers related to early relapse after corticosteroid treatment, the Pre-C samples were divided into a remission group and a resistant/relapse group according to the response to corticosteroid therapy within 3 months. Nine significant associations with the microbial species and function were identified between the remission and resistant/relapse groups. A risk index built from this panel of microbes and functional pathways was used to differentiate remission from resistant/relapsed patients based on the baseline characteristics. The receiver operating characteristic (ROC) curve demonstrated that the risk index was a strong predictor of treatment response, with an area under the curve (AUC) of 0.87. Furthermore, to predict the response to TPO-RAs in subsequent therapy, the baseline gut microbiomes of responders and nonresponders before TPO-RA treatment were compared. Patients who responded to treatment exhibited an increase in Ruminococcaceae, Clostridiaceae and Bacteroides compared to nonresponders, with elevated abundance of the phosphotransferase system, tyrosine metabolism and secondary bile acid biosynthesis pathways according to KEGG analysis. Our prediction model based on the gut microbiome for TPO-RA response was robust across the cohorts and showed 89.5% and 79.2% prediction accuracy for persistent/chronic ITP patients in the training and validation sets, respectively. Conclusions The gut microbiome and function signatures based on machine learning analysis are novel potential biomarkers for predicting resistance/relapse after corticosteroid treatment and response to TPO-RAs, which may have important manifestations in the clinical. Disclosures No relevant conflicts of interest to declare.

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The Nursing Home Older Adult Gut Microbiome Composition Shows Time-dependent Dysbiosis and is Influenced by Medication Exposures, Age, Environment, and Frailty

The Journals of Gerontology Series A ◽

10.1093/gerona/glab167 ◽

2021 ◽

Author(s):

John P Haran ◽

Abigail Zeamer ◽

Doyle V Ward ◽

Protiva Dutta ◽

Vanni Bucci ◽

...

Keyword(s):

Older Adults ◽

Gut Microbiota ◽

Older Adult ◽

Gut Microbiome ◽

Assessment Tool ◽

Mini Nutritional Assessment ◽

Metagenomic Sequencing ◽

Mixed Effect ◽

Stool Samples ◽

Over Time

Abstract Older adults in nursing homes (NHs) have increased frailty, medication, and antimicrobial exposures, all factors that are known to affect the composition of gut microbiota. Our objective was to define which factors have the greatest association with the NH resident gut microbiota, explore patterns of dysbiosis and compositional changes in gut microbiota over time in this environment. We collected serial stool samples from NH residents. Residents were assessed using the Mini Nutritional Assessment tool and Clinical Frailty Scale. Bacterial composition of resident stool samples was determined by metagenomic sequencing. We used mixed-effect random forest modeling to identify clinical covariates that associate with microbiota. We enrolled and followed 166 residents from 5 NHs collecting 512 stool samples and following 15 residents for > 1 year. Medications, particularly psychoactive and anti-hypertensive medications, had the greatest effect on the microbiota. Age and frailty also contributed, and were associated with increased and decreased diversity, respectively. The microbiota of residents who had lived in the NH for > 1 year were enriched in inflammatory and pathogenic species and reduced in anti-inflammatory and symbiotic species. We observed intra-individual stability of the microbiome among older adults who had lived in the NH already for >1 year followed with sample collections 1 year apart. Older adult NH gut microbiome is heavily influenced by medications, age, and frailty. This microbiome is influenced by length of NH residence with dysbiosis becoming evident at 12 months, however after this point there is demonstrated relative stability over time.

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Diet and gut microbiome interactions of relevance for symptoms in irritable bowel syndrome

Microbiome ◽

10.1186/s40168-021-01018-9 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Julien Tap ◽

Stine Störsrud ◽

Boris Le Nevé ◽

Aurélie Cotillard ◽

Nicolas Pons ◽

...

Keyword(s):

Irritable Bowel Syndrome ◽

Gut Microbiota ◽

Gut Microbiome ◽

Symptom Severity ◽

Dietary Habits ◽

Gastrointestinal Symptoms ◽

Linear Regression Models ◽

Food Diary ◽

New Associations ◽

Irritable Bowel

Abstract Background While several studies have documented associations between dietary habits and microbiota composition and function in healthy individuals, no study explored these associations in patients with irritable bowel syndrome (IBS), and especially with symptoms. Methods Here, we used a novel approach that combined data from a 4-day food diary, integrated into a food tree, together with gut microbiota (shotgun metagenomic) for individuals with IBS (N = 149) and healthy controls (N = 52). Paired microbiota and food-based trees allowed us to detect new associations between subspecies and diet. Combining co-inertia analysis and linear regression models, exhaled gas levels and symptom severity could be predicted from metagenomic and dietary data. Results We showed that individuals with severe IBS are characterized by a higher intake of poorer-quality food items during their main meals. Our analysis suggested that covariations between gut microbiota at subspecies level and diet could be explained with IBS symptom severity, exhaled gas, glycan metabolism, and meat/plant ratio. We provided evidence that IBS severity is associated with altered gut microbiota hydrogen function in correlation with microbiota enzymes involved in animal carbohydrate metabolism. Conclusions Our study provides an unprecedented resolution of diet-microbiota-symptom interactions and ultimately guides new interventional studies that aim to identify gut microbiome-based nutritional recommendations for the management of gastrointestinal symptoms. Trial registration This trial was registered on the ClinicalTrials.gov, with the registration number NCT01252550, on 3rd December 2010.

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Deep Investigating the Changes of Gut Microbiome and Its Correlation With the Shifts of Host Serum Metabolome Around Parturition in Sows

Frontiers in Microbiology ◽

10.3389/fmicb.2021.729039 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hao Fu ◽

Maozhang He ◽

Jinyuan Wu ◽

Yunyan Zhou ◽

Shanlin Ke ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

16S Rrna Gene ◽

Gut Microbiome ◽

Bacterial Species ◽

Late Pregnancy ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Functional Capacities

Parturition is a crucial event in the sow reproduction cycle, which accompanies by a series of physiological changes, including sex hormones, metabolism, and immunity. More and more studies have indicated the changes of the gut microbiota from pregnancy to parturition. However, what bacterial species and functional capacities of the gut microbiome are changed around parturition has been largely unknown, and the correlations between the changes of gut bacterial species and host metabolome were also uncovered. In this study, by combining 16S rRNA gene and shotgun metagenomic sequencing data, and the profiles of serum metabolome and fecal short-chain fatty acids (SCFAs), we investigated the changes of gut microbiome, serum metabolite features and fecal SCFAs from late pregnancy (LP) to postpartum (PO) stage. We found the significant changes of gut microbiota from LP to PO stage in both 16S rRNA gene sequencing and metagenomic sequencing analyses. The bacterial species from Lactobacillus, Streptococcus, and Clostridium were enriched at the LP stage, while the species from Bacteroides, Escherichia, and Campylobacter had higher abundances at the PO stage. Functional capacities of the gut microbiome were also significantly changed and associated with the shifts of gut bacteria. Untargeted metabolomic analyses revealed that the metabolite features related to taurine and hypotaurine metabolism, and arginine biosynthesis and metabolism were enriched at the LP stage, and positively associated with those bacterial species enriched at the LP stage, while the metabolite features associated with vitamin B6 and glycerophospholipid metabolism had higher abundances at the PO stage and were positively correlated with the bacteria enriched at the PO stage. Six kinds of SCFAs were measured in feces samples and showed higher concentrations at the LP stage. These results suggested that the changes of gut microbiome from LP to PO stage lead to the shifts of host lipid, amino acids and vitamin metabolism and SCFA production. The results from this study provided new insights for the changes of sow gut microbiome and host metabolism around parturition, and gave new knowledge for guiding the feeding and maternal care of sows from late pregnancy to lactation in the pig industry.

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Gut microbes in healthy dogs have individualized responses to synbiotic supplementation that lead to increased abundances of probiotic strains: A randomized controlled trial

10.21203/rs.3.rs-100335/v1 ◽

2020 ◽

Author(s):

Jirayu Tanprasertsuk ◽

Aashish R Jha ◽

Justin Shmalberg ◽

LeeAnn M Perry ◽

Heather Maughan ◽

...

Keyword(s):

Gut Microbiota ◽

Controlled Trial ◽

Bacterial Species ◽

Gastrointestinal Symptoms ◽

Healthy Population ◽

Significant Shift ◽

Metagenomic Sequencing ◽

Β Diversity ◽

Populations At Risk ◽

Healthy Dogs

Abstract Background: Probiotics ameliorate gastrointestinal symptoms in dogs. However, the effect of probiotics in a healthy population, as well as factors contributing individualized responses, remains largely unknown. This trial examined gut microbiota (GM) and health outcomes in household dogs after synbiotic (SN) supplementation containing probiotics and inulin. Healthy dogs were randomized to receive SN (50 mg/d inulin and 20 billion total CFU/d of L. reuteri, P. acidilactici, E. faecium, L. acidophilus, B. animalis, L. fermentum, L. rhamnosus) or placebo (PL) for 4 weeks. Owners completed a health survey and collected stool samples for GM profiling (metagenomic sequencing) at baseline and week 4 in both groups, and at week 6 in the SN group.Results: A significant shift (p<0.001) in β-diversity was observed in the SN (n=24), but not PL group (n=19), relative to baseline at week 4. Forty-five bacterial species, 43 (96%) of which were Lactobacillales, showed an increase in the abundances (≥2 fold change, adjusted p<0.05) at week 4. E. coli also decreased at week 4 in the SN group (2.8 folds, adjusted p<0.01). The altered taxa largely returned to baseline at week 6. The degree of changes in the β-diversity was associated with GM at baseline. Specifically, dogs with higher Proteobacteria and lower Lactobacillales responded more robustly to supplementation. Dogs fed SN tended to have lower diarrhea incidence (0% vs 16%, p=0.08).Conclusions: SN supplement had an impact on the change of gut microbiota in healthy household dogs as characterized with metagenomic sequencing. Findings warrant further investigation with longer duration or in populations at risk of gastrointestinal diseases. The magnitude of response to the supplement was associated with microbial profile at baseline. To our knowledge, this is the first study documenting such association that may provide a basis of personalized nutrition in companion dogs.

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Yoghurt consumption is associated with transient changes in the composition of the human gut microbiome

10.21203/rs.3.rs-38248/v1 ◽

2020 ◽

Author(s):

Caroline Ivanne Le Roy ◽

Alexander Kurilshikov ◽

Emily Leeming ◽

Alessia Visconti ◽

Ruth Bowyer ◽

...

Keyword(s):

16S Rrna ◽

Gut Microbiota ◽

Visceral Fat ◽

Gut Microbiome ◽

Body Weight Gain ◽

Healthy Eating Index ◽

Rrna Gene ◽

Metagenomic Sequencing ◽

Sequencing Data ◽

Shotgun Metagenomic Sequencing

Abstract Background: Yoghurt contains live bacteria that could contribute via modulation of the gut microbiota to its reported beneficial effects such as reduced body weight gain and lower incidence of type 2 diabetes. To date, the association between yoghurt consumption and the composition of the gut microbiota is underexplored. Here we used clinical variables, metabolomics, 16S rRNA and shotgun metagenomic sequencing data collected on over 1000 predominantly female UK twins to define the link between the gut microbiota and yoghurt-associated health benefits. Results: According to food frequency questionnaires (FFQ), 73% of subjects consumed yoghurt. Consumers presented a healthier diet pattern (healthy eating index: beta = 2.17±0.34; P = 2.72x10 -10 ) and improved metabolic health characterised by reduced visceral fat (beta = -28.18±11.71 g; P = 0.01). According to 16S rRNA gene analyses and whole shotgun metagenomic sequencing approach consistent taxonomic variations were observed with yoghurt consumption. More specifically, we identified higher abundance of species used as yoghurt starters Streptococcus thermophilus (beta = 0.41±0.051; P = 6.14x10 -12 ) and sometimes added Bifidobacterium animalis subsp. lactis (beta = 0.30±0.052; P = 1.49x10 -8 ) in the gut of yoghurt consumers. Replication in 1103 volunteers from the LL-DEEP cohort confirmed the increase of S. thermophilus among yoghurt consumers. Using food records collected the day prior to faecal sampling we showed that increase in these two yoghurt bacteria could be transient. Metabolomics analysis revealed that B. animalis subsp. lactis was associated with 13 faecal metabolites including a 3-hydroxyoctanoic acid, known to be involved in the regulation of gut inflammation. Conclusions: Yoghurt consumption is associated with reduced visceral fat mass and changes in gut microbiome including transient increase of yoghurt-contained species ( i.e. S. thermophilus and B. lactis ).

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Gut microbiome and serum metabolome alterations in isolated dystonia

10.21203/rs.3.rs-139606/v1 ◽

2021 ◽

Author(s):

Yongfeng Hu ◽

Ling yan Ma ◽

Min Cheng ◽

Bo Liu ◽

Hua Pan ◽

...

Keyword(s):

Gut Microbiota ◽

Gut Microbiome ◽

Metagenomic Sequencing ◽

Metabolome Analysis ◽

Citrate Cycle ◽

Microbial Dysbiosis ◽

Α Diversity ◽

Drug Naïve ◽

Neurological Movement Disorder ◽

The Relationship

Abstract Background Dystonia is a complex neurological movement disorder characterised by involuntary muscle contractions. The relationship between the gut microbiota and isolated dystonia remains poorly explored. Methods We collected faeces and blood samples to study the microbiome and the serum metabolome from a cohort of 57 drug-naïve isolated dystonia patients and 27 age- and environment-matched healthy individuals. We first sequenced the V4 regions of the 16S rDNA gene from all faeces samples. Further, we performed metagenomic sequencing of gut microbiome and non-targeted metabolomics profiling of serum from dystonia patients with significant dysbiosis. Results Gut microbial β-diversity was significantly different, with a more heterogeneous community structure among dystonia individuals than healthy controls, while no difference in α-diversity was found. Gut microbiota in dystonia patients was enriched with Blautia obeum, Dorea longicatena and Eubacterium hallii, but depleted with Bacteroides vulgatus and Bacteroides plebeius. Metagenomic sequencing revealed that genes related to the citrate cycle, vitamin B6 and glycan metabolism were less abundant in dystonia, while genes linked to purine and tryptophan biosynthesis were more abundant. Serum metabolome analysis revealed altered levels of tyrosine and glutamate. The integrative analysis of the gut microbiome and serum metabolomics identified dystonia-associated gut microbial species linked to changes in serum metabolites, reflecting the effect of the gut microbiome on metabolic activity in isolated dystonia. Conclusion This study is the first to reveal gut microbial dysbiosis in dystonia patients. Our findings identified previously unknown links between intestinal microbiota alterations, circulating amino acids and dystonia, providing new insight into the pathogenesis of isolated dystonia.

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