Fecal Coprococcus, Hidden behind Abdominal Symptoms in Patients with Small Intestinal Bacterial Overgrowth

Fecal Coprococcus, Hidden behind Abdominal Symptoms in Patients with Small Intestinal Bacterial Overgrowth | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Fecal Coprococcus, Hidden behind Abdominal Symptoms in Patients with Small Intestinal Bacterial Overgrowth Huaizhu Guo, Yuzhu Chen, Wenxin Dong, Siqi Lu, Yanlin Du, Liping Duan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3823305/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: Small intestinal bacterial overgrowth (SIBO) is the presence of an abnormally excessive amount of bacterial colonization in the small bowel. Hydrogen and methane breath test has been widely applied as a non-invasive method for SIBO. However, the positive breath test representative of bacterial overgrowth could also be detected in asymptomatic individuals. Methods: To explore the relationship between clinical symptoms and gut dysbiosis, and find potential fecal biomarkers for SIBO, we compared the microbial profiles between SIBO subjects with positive breath test but without abdominal symptoms (PBT) and healthy controls (HC). Results: Fecal samples were collected from 63 SIBO who complained of diarrhea, distension, constipation or abdominal pain, 36 PBT and 55 HC. Increased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. At the genus level, significantly decreased Bacteroides and increased Coprococcus_2 were observed, and unique Butyrivibrio could ferment multiple carbohydrates producing hydrogen and hydrogen sulfide. There was a significant correlation between Coprococcus_2 and the severity of abdominal symptoms. Differently, The unique Veillonella , Escherichia-Shigella , Barnesiella and Tyzzerella_3 in PBT group were related to amino acid fermentation. Interestingly, the co-occurrence network density of PBT is the largest indicating a complicated interaction of genera. The Euclidean distance between paired networks using either the betweenness centrality or the degree distribution showed that PBT is closer to SIBO. Conclusions: Increased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. Butyrivibrio and Coprococcus_2 abundance along with lower Bacteroides contributed to more noticeable discomfort of SIBO patients. The enriched Coprococcus may be one of the potential biomarkers of SIBO. Represented by Veillonella , asymptomatic PBT objects exhibited a different microbiome spectrum associated with the fermentation of amino acids and peptides rather than carbohydrates. The network of PBT was more stable which may play a protective role, but it deserved further attention in view of the shared essential “bridged” genera with SIBO. small intestinal bacterial overgrowth hydrogen and methane breath test gut microbiome network analysis saccharolytic bacteria Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Small intestinal bacterial overgrowth (SIBO) is a sparsely recognized clinical syndrome as the presence of an abnormally excessive amount of bacterial colonization in the small bowel with abdominal complaints [1; 2] . SIBO is closely associated with many gastrointestinal (GI) diseases, such as irritable bowel syndrome (IBS) [ 3 ] , inflammatory bowel disease (IBD) [ 4 ] , pancreatitis [ 5 ] , nonalcoholic liver disease [ 6 ] , colorectal cancer and abdominal surgery. It is believed that symptoms linked to SIBO consist of bloating, diarrhea and abdominal pain/discomfort. In addition to main complaints, steatorrhea, vitamin B 12 deficiency and malnutrition can be seen in more severe cases [ 1 ] . Primary or secondary motility abnormalities destroy the ability of the small intestine to prevent colon bacterial translocation [ 7 ] . Meanwhile, ileocaecal valve dysfunction leads to colonic bacterial regurgitation [ 8 ] . Long-term medication of proton pump inhibitors (PPIs) is associated with an increased risk of SIBO. The intragastric defence barrier damage by acid suppression therapy makes it easier for upstream opportunistic pathogens to enter the small intestine [ 9 – 11 ] . Congenital or postoperative intestinal anatomical malformations increase local food residues and bacterial accumulation, like intestinal diverticulum, Roux-en-Y anastomosis or small bowel resection [12; 13] . Multiple pathophysiological mechanisms contribute to abdominal discomforts including carbohydrate fermentation and improper metabolites, GI chronic inflammation, mucosal immune deficiency, increased gut permeability, food intolerance and antigenemia [14; 15] . The gold standard for diagnosis of SIBO is quantitative culture of small intestine aspirates. AGA recommended a new threshold at > 10 3 colony-forming units per milliliter (CFU/ml) on fresh aspirate culture instead of > 10 5 CFU/ml based on a large scale study [ 16 ] , derived from subjects with altered intestinal anatomy because bacterial level in normal subjects rarely exceed 10 2 CFU/ml [ 17 ] . Based on the above diagnostic standard, SIBO subjects from the REIMAGINE study had a higher relative abundance of Proteobacteria and lower Firmicutes than non-SIBO subjects [18; 19] . Barblow et al. found that absolute loads of taxa in duodenal aspirates including Klebsiella , Escherichia , Enterococcus , and Clostridium enriched in individuals with SIBO were associated with more severe upper GI symptoms, but they lacked healthy controls [ 20 ] . Another cohort study found that duodenal aspirate microbiome were altered in symptomatic patients, while the absolute counting of anaerobes in the small intestine fluid wasn’t parallel with the severity of symptoms [ 21 ] . An alternative method is the measurement of exhaled hydrogen and methane gas during the breath test (BT), which is considered as a non-invasive, safe, useful and cost-efficient method for SIBO. The North American Consensus recommended that a rise in hydrogen of ≥ 20 part per million (ppm) or methane levels ≥ 10 ppm by 90 min during glucose or lactulose breath test was considered positive [ 22 ] . However, the positive lactulose or glucose breath test representative of bacterial overgrowth could also be detected in asymptomatic subjects with the prevalence varied from 3–30% [ 23 – 27 ] . At present, we are still not clear about the possible mechanisms which lead to GI complaints and carbohydrate malabsorption in part of the positive BT population. Indeed, the small bowel microbiome analysis limited its’ application. This study aimed to illustrate the gut microbiome profiles of SIBO patients compared with asymptomatic positive breath test (PBT) subjects and health control (HC), and identify potential fecal biomarkers for abdominal discomfort in SIBO. Patients and Methods Patient recruitment The study was performed from April 2019 to May 2021. SIBO patients who reported non-specific abdominal symptoms and fulfilled the diagnostic criteria of lactulose hydrogen and methane breath test were recruited from the Department of Gastroenterology, Peking University Third Hospital. The inclusion criteria were as follows: a) aged ≥ 18 and ≤ 65 years old; b) GI discomfort, mainly abdominal pain, distension, constipation, diarrhoea for over 6 months; c) positive lactulose hydrogen methane breath test (LBT); d) voluntarily joined the study and completed the case report form, hydrogen-methane breath test and stool collection. Patients were excluded if they fulfilled one or more of the following exclusion criteria: a) GI organic diseases detected by endoscopy or digestive tract surgery history; b) with severe heart, liver, lung, kidney, blood, endocrine and nervous system diseases or severe respiratory tract, digestive tract, urinary tract infections or mental disorders; c) taking antibiotics and acid suppression drugs for more than 3 days during the past month or probiotics, laxatives, antidiarrheal or prokinetic agents within 2 weeks; d) pregnant or lactating women. Asymptomatic subjects were recruited in the same clinical center. According to their LBT results, they were divided into positive breath test (PBT) group and negative health control (HC). Clinical evaluation and sampling Demographic data including age, gender, height, weight and body mass index (BMI) were recorded for each participant. Daily bowel habit and frequency were recorded based on the Bristol stool form (BSF) scale [ 28 ] . GI symptom severity was evaluated by gastrointestinal symptom rating scale (GSRS) [ 29 ] . The symptom score was the sum of abdominal pain, distension, constipation, diarrhoea scores. Self-reporting anxiety scale (SAS) and self-reporting depression scale (SDS) were used to evaluate the mental health conditions [30; 31] . 7 day food frequency questionnaire (FFQ) was used to estimate their dietary pattern [ 32 ] . Written informed consent was obtained from each participant prior to sample collection. All included participants were required to stop using antibiotics, probiotics, prebiotics, and other microbiota-related supplements at least two weeks before stool sampling. Stool specimen were stored by stool nucleic acid collection and servation tubes (Norgen Biotek Corp., Toronto, Ontario, Canada), then transported to the laboratory using dry ice and were frozen at − 80°C. Gut microbiota analysis Microbial community genomic DNA was extracted from 154 samples and purified amplicons were pooled in equimolar and paired-end sequences on an Illumina MiSeq PE300 platform (Illumina, San Diego, U.S.) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). All microbiome samples were processed and analyzed by Parallel-Meta Suite with SILVA database on the operational taxonomy units (OTU) similarity level of 97% [33; 34] . The functional profiles were predicted with PICRUSt2 and annotated with Kyoto Encyclopedia of Genes and Genome (KEGG) Orthology (KO) [ 35 ] . For alpha diversity, Shannon indexes of each samples were calculated and illustrated into boxplots with permutational multivariate analysis of variance (PERMANOVA) test. For beta diversity, principal co-ordinates analysis (PcoA) using meta storms distance algorithm [ 36 ] and partial least squares discriminant analysis (PLS-DA) was analyzed in R (version 4.2.1). Cytoscape was used in the co-occurrence network analysis with p <0.05 and |r|≥0.5 [ 37 ] . Additional information on sequencing and analysis is available in Supplemental Materials. Clinical feature statistical analysis Analysis will be conducted through SPSS V.26.0. The quantitative and qualitative variables were reported as mean ± standard error (SE), median ± interquartile range (IQR), and number (frequency). Univariate analysis of variance (ANOVA) will examine differences between groups for variables with continuous data. χ2 tests will examine differences between groups for categorical variables. Linear correlations will be analyzed through Pearson’s correlation analysis. Non-parametric correlations will be analyzed through Spearman's correlation analysis. A p < 0.05 was considered statistical significance for above tests. Results The clinical manifestation of SIBO patients In total, 154 subjects were enrolled, including 63 SIBO patients, 36 PBT and 55 HC (Fig. 1 a). There were no statistically significant differences among the three groups in terms of gender, age, body mass index (BMI), carbohydrate, protein, fat consumption and energy proportion (Table 1 ). Patients with SIBO had significantly higher anxiety scores (39.42 ± 8.70) than PBT (36.53 ± 6.49, p < 0.01) and HC (34.68 ± 7.68, p < 0.01), respectively. The depression scores of SIBO group (42.84 ± 8.31) were higher than that of HC group (38.72 ± 8.41, p < 0.05) (Table 1 and Fig. 1 b). Table 1 Comparison of clinical manifestation among SIBO, PBT and HC group Legend: * a significant difference compared with HC; # a significant difference compared with PBT HC PBT SIBO P value Number 55 36 63 Sex (female, n/%) 32/58.18% 29/80.55% 45/71.42% 0.065 Age(year) 21.49 ± 2.08 22.08 ± 2.67 21.44 ± 2.72 0.431 BMI(kg/m 2 ) 21.30 ± 2.79 21.44 ± 2.91 20.96 ± 2.38 0.635 Carbohydrate (g/d) 307.79 ± 43.13 223.57 ± 21.56 301.30 ± 58.21 0.494 Protein (g/d) 66.98 ± 6.01 59.35 ± 6.35 70.64 ± 7.22 0.847 Fat (g/d) 72.01 ± 7.36 67.89 ± 4.54 67.69 ± 3.80 0.541 Energy proportion of carbohydrate (%) 58.70 ± 1.83 53.77 ± 2.09 55.46 ± 1.48 0.160 Energy proportion of protein (%) 13.87 ± 0.51 14.09 ± 0.64 14.62 ± 0.54 0.523 Energy proportion of fat (%) 34.32 ± 2.44 36.90 ± 2.18 33.55 ± 1.32 0.590 Anxiety 34.68 ± 7.68 35.63 ± 6.49 39.42 ± 8.70 * # < 0.01 Depression 38.72 ± 8.41 39.86 ± 8.91 42.84 ± 8.31 * < 0.05 According to GSRS scores, the dominant symptoms in SIBO patients were distension (63.49%), constipation (49.21%), loose stool (47.62%), hunger pain (46.03%), urgent stool (41.27%), hyperactive sound (41.27%) and abdominal pain (38.10%) (Fig. 1 c). Overall fecal microbiota composition and diversity No significant difference was found in community diversity of the gut microbiome on genus level ( p = 0.229, Fig. 2 a). Notably the Shannon index of SIBO significantly decreased compared with HC group on KEGG BRITE level3 pathway ( p < 0.05, Fig. 2 b). Butyrivibrio only occurred in SIBO, Veillonella, Barnesiella, Escherichia-Shigella and Tyzzerella_3 in PBT group, and Holdemanella in HC group, respectively. Alloprevotella and Ruminiclostridium_6 were detected in both SIBO and PBT groups (Fig. 2 c and Table 2 ). Each group was dominated by Bacteroides , followed by Prevotella_9, Faecalibacterium, Blautia and Roseburia at the genus level (Fig. 2 d and Table S1 ). The taxonomic compositions at the phylum level were shown in Figure S1 . Even though no significant effect was found at the OTU level in the beta-diversity analysis among three groups (Fig. 2 e), PLS-DA indicated a compositional distinction of microbiota (Fig. 2 f). Table 2 The unique bacterial genera and their metabolic characteristics Genus Phylum Family Product Gas PBT Veillonella Firmicutes Veillonellaceae Polyamines Yes Acetate, propionate Barnesiella Bacteroidota Barnesiellaceae Acetate Succinate NR Escherichia-Shigella Proteobacteria Enterobacteriaceae NR Yes Tyzzerella_3 Firmicutes Lachnospiraceae NR NR PBT&SIBO Alloprevotella Bacteroidota Prevotellaceae Acetate Succinate Yes Ruminiclostridium_6 Firmicutes Oscillospiraceae Acetate Propionate butyrate Yes SIBO Butyrivibrio Firmicutes Lachnospiraceae Butyrate Yes HC Holdemanella Firmicutes Erysipelotrichaceae Acetate Propionate Butyrate Lactic acid NR Legend: PBT: positive breath test; SIBO: small intestinal bacterial overgrowth; HC: health control; NR no related evidence. Fecal microbiota taxonomic changes for screening potential biomarkers The significant lower abundance of Bacteroides and higher abundance of Coprococcus_2 were observed in SIBO compared with HC at the genus level (Fig. 3 a, b). It should be noted that more kinds of microbiota differences were discovered in the PBT group. The relative abundance of Bilophila , Oscillibacter and Ruminococcus_torques were significantly decreased, and the Butyricicoccus , Sutterella , Lachnospiraceae_UCG004 and Dialister were enriched in PBT (Fig. 3 c-i). Furthermore, we assessed the Spearman’s correlations of these microbiota which suggested the synergistic and competitive effects (Fig. 3 j). The relative abundance of Bacteroides was negatively associated with that of Coprococcus_2 ( r =-0.563, p < 0.001). We also detected the negative correlation between Ruminococcus_torques and Sutterella ( r =-0.304, p < 0.001), as well as between Bilophila and Lachnospiraceae_UCG004 ( r =-0.210, p < 0.01). The significantly positive correlations between each pair of the three decreasing genera in PBT group suggested the similar trend. The relative abundance of Coprococcus_2 was positively associated with that of Oscillibacter ( r = 0.218, p < 0.01) and Ruminococcus_torques ( r = 0.310, p < 0.001). The correlation heatmap revealed significant positive correlations between the relative abundance of Coprococcus_2 and the severity of all symptoms (Fig. 3 k). Bacteroides was negatively related to constipation and distension. No significant relation was found between the differential genera and the mental scores. Diminishing metabolic functions associated with abdominal symptoms in SIBO To explore the functional changes associated with differences in microbial composition, gut microbiome function was imputed using PICRUSt2 and pathway analysis based on the KEGG database. Different predicted pathways were determined (Fig. 4 a-d and Figure S2 ). Interestingly, pathways associated with amino acid metabolism were enriched in healthy individuals, including arginine and proline metabolism, valine, leucine and isoleucine degradation, and phenylalanine metabolism, mostly essential amino acids involved. The pathway reflective of one carbon pool by folate were significantly dropped in SIBO. Furthermore, the significant negative correlation between the gas production rate at 90 minutes and the functional changes were stable (Fig. 4 e-h). To determine the association of microbiota functional changes and disease, the relative abundance of the functions and host parameters were considered for the correlation analyses. Overall, the above functional changes were negatively associated with symptom scale, constipation, abdominal distension and pain (Fig. 4 i). The functional changes also had a significantly positive correlation with Bacteroides and a negative correlation with Coprococcus_2 , supporting the synergism with the taxonomic relative abundance (Figure S3 ). Microbial co-occurrence network analysis The co-occurrence network including 62 common genera was obtained cross-correlating all the relative abundance against one another in three groups, respectively. The absolute value of relative coefficient greater than 0.5 were coded in the line color. The node names were presented in Table S2 . The local properties of the networks were analyzed including degree (Fig. 5 a and Table S3 ) and betweenness centrality (Fig. 5 b and Table S4 ). Figure 5 a showed the largest network density in PBT group (ρ = 0.089), which represented a more complex microbiota interaction compared to the similar degree distributions in HC (ρ = 0.061) and SIBO (ρ = 0.060). The larger nodes indicated a higher degree which reflected the complicated interaction in the whole network. Figure 5 b, the size of each node was proportional to the betweeness centrality, suggesting that the larger one could be necessary for network functionality. Nodes 42, 30 and 21, which represent the genus Eubacterium_oxidoreducens , Dorea and Ruminococcaceae_NK4A214 , showed a high betweeness centrality in HC group. Nodes 11, 42 and 18, which represent the genus Ruminococcus_1 , Eubacterium_oxidoreducens and Coprococcus_2 , showed a high betweeness centrality in SIBO group. Nodes 18, 43 and 42, which represent the genus Coprococcus_2 , Eubacterium_ruminantium and Eubacterium_oxidoreducens , showed a high betweeness centrality in PBT group. The Euclidean distance of 62-dimensional betweeness centralities between PBT and SIBO is 512.78, the distance between PBT and HC is 539.76, while the distance between HC and SIBO is 557.60, reflecting that the necessary microbiota in the whole network were more similar in the PBT and SIBO. Discussion In this study, we present the microbial composition from the positive hydrogen and methane breath test population with and without abdominal discomfort and with an otherwise healthy gut for the first time. We observed that symptomatic patients showed higher alpha diversity of the fecal microbiota. Significantly decreased Bacteroides and increased Coprococcus_2 were observed, and unique Butyrivibrio richness was responsible for gas production with carbohydrates as fermentation substrates. The alpha diversity at the KEGG functional level was significantly reduced. Both the composition and function alterations of the microbiota were correlated with GI symptoms in SIBO. Anxiety and depression might be related to reporting more abdominal symptoms in SIBO patients. On the other hand, individuals with solely positive breath test possessed a more stable network reflecting the complicated interactions of the fecal microbiota. Gas production represented by Veillonella in PBT was associated with the microbial fermentation of amino acids and peptides (Fig. 6 ). Mostly, SIBO patients complain of non-specific GI symptoms by the presence of the excessive colonization of aerobic or anaerobic bacteria in the small bowel [ 38 ] . The symptoms are closely related to fermentation of non-absorbed carbohydrates like nausea, bloating, flatulence, distension, abdominal pain, diarrhoea, and/or constipation [ 39 ] . A significant proportion of patients deny effective treatment as misdiagnosed as IBS due to the unclear symptom spectrum [2; 40; 41] . In our study, we found that the most frequently reported symptom was abdominal distension, followed by changes of defecation habits (constipation). Abdominal pain for the essential diagnosis of IBS in Rome IV consensus was not highlighted for SIBO patients. Gas-producing related symptoms such as bloating, gassiness, cramping and distension were more obvious [ 42 ] . Primary or secondary motility abnormalities destroy the ability of the small intestine to prevent colon bacterial translocation [ 7 ] , thus slow intestinal transit leads to excessive gas retention and constipation [ 43 ] . The small intestine represents the first region where food components and the intestinal bacteria encounter each other for primary carbohydrate metabolism. Over the past few decades, the lack of knowledge for SIBO was confined to the collection, storage and culture of small bowel fluids. Almost samples were obtained near the duodenal or jejunum rather than the bacterial colonization by upper gastrointestinal endoscopy at the risk of contamination. Inevitably gas injection during the endoscopic operation may disturb anaerobic culture of SIBO [44; 45] .The fecal microbiota composition alteration may help for the explanation of the metabolism features and progression of SIBO. SIBO can be defined as the inappropriate fermentation of many kinds of carbohydrate and simultaneously multiple nutrient malabsorption by the culture of proximal intestinal aspirates or measurement of exhaled hydrogen and methane. The Butyrivibrio spp. from Lachnospriaceae detected only in SIBO patients could encode a more impressive repertoire of carbohydrate-active enzymes than most Firmicutes [ 46 ] , capable of growing on a range of carbohydrates, from mono-or oligosaccharides to complex plant polysaccharides, such as pectins, mannans, starch, and hemicelluloses [47; 48] . The end-products were butyrate and many kinds of gas including hydrogen (H 2 ), carbon dioxide (CO 2 ) and hydrogen sulfide (H 2 S). Butyrivibrio was significantly abundant in subjects that reported traveler’s diarrhea [ 49 ] , while also significantly higher in the constipation dominant IBS patients from mucosal samples [ 50 ] . Our findings supported a negative correlation of the relative abundance of Bacteroides and GI symptoms, concurred with lower amount of Bacteroides in SIBO patients. Several species of Bacteroides which we considered as beneficial bacteria could access their desired nutrients from long chain polysaccharides and oligosaccharides that are not readily absorbed by the epithelial cells of the colon in healthy status base on the polysaccharide utilization loci (PULs) [ 51 ] , producing useful short-chain fatty acids. It is recognized that Bacteroides spp. have been widely implicated in mental disorders and could modulate depression-like behavior [ 52 – 54 ] . Bamba et al. (2023) have found that the relative abundance of Bacteroides in duodenal aspirates of SIBO patients was significantly lower than that of non-SIBO patients. Therefore, we inferred that the decline of Bacteroides in accordance to the duodenal aspirates reflected the overuse of carbohydrates or inner competition by proliferating bacteria in the small intestine. Conversely, the genus Coprococcus_2 was positively correlated with the symptom score and all symptoms concurred with a higher abundance in SIBO. Coprococcus spp. within the family Lachnospiraceae of Firmicutes are deemed the core genera for the maintenance of microbial homeostasis and healthy status [56; 57] , as they contribute to the production of the health-promoting metabolite butyrate. Nevertheless, Coprococcus_2 was associated with a higher risk of IBD [ 58 ] , obesity and polycystic ovary syndrome (PCOS) [ 59 ] . There are significant differences in the utilization of carbohydrates among Coprococcus subgroups. Multiple carbon source substrates could be utilized by C.eutactus , mainly contained in Coprococcus_2 [ 60 ] . As a short-chain fatty acid-producing bacterium, C. eutactus mainly generates acetic acid [ 61 ] . An randomized clinical trial of berberine and rifaximine effects for SIBO is underway in our clinical center [ 62 ] . We further found that lower relative abundance of Coprococcus inhibited by berberine was observed in patients with negative hydrogen methane breath tests after medication compared with baseline (0.18 ± 0.13% vs. 1.09 ± 0.20%, p < 0.001). On the contrary, there was no significant change in the relative abundance of Coprococcus before and after medication in those who failed to respond to berberine (0.32 ± 0.17% vs. 0.27 ± 0.11%, p = 0.775). The baseline relative abundance of Coprococcus could also indicate drug response (Figure S4 ). The increased Coprococcus abundance may be one of the potential biomarkers of SIBO. Further studies should be performed to determine the disruptors in the small intestine. PICRUSt analysis found that the metabolic function alterations matched with the microbiota abundance changes. Amino acid metabolism pathways, mostly essential amino acids involved, were downregulated in SIBO patients reflecting the result of competition of the nutrient metabolism in the small bowel. Studies have shown that an excess of bacteria in the small intestine altered the tryptophan metabolism which may increase in a variety of infections and inflammations [ 63 ] . Our study further revealed that these bacteria predominantly ferment carbohydrates with a consequence of the down regulation of amino acid metabolism, which may interfere the amino acid absorption. In addition, biosynthesis and cycle of tetrahydrofolate were down regulated according to the decreased one carbon pool by folate in SIBO, which provided the potential explanation for megaloblastic anemia in more severe patients. The metabolic pathway functions were also negatively correlate with the symptom spectrum and hydrogen levels, which illustrated the harmful effects of SIBO on the microbiota metabolism function. A number of taxonomic groups we identified in PBT reflected the diverse nutrient metabolic features as the highlight of this study. Veillonella within the family Veillonellaceae of Firmicutes, existed in 28 of 36 PBT objects, were also commonly found in duodenal aspirate sequencing [ 20 ] . Veillonella is the predominant components in the small intestine of healthy subjects [ 64 ] . It is characterized in that glucose or any other carbohydrate is not fermented, but relies on organic acids, amino acids and peptides as carbon sources which may explain the exhaled gas production like H 2 and H 2 S [65; 66] . Fermentation of amino acids and proteins were also observed on Barnesiella , another unique genus occurred in most PBT individuals [ 67 ] . Dialister , asaccharolytic, had close phylogenetic distance and similar physiological characteristics with Veillonella and overrepresented in cirrhosis duodenum [68; 69] . The great abundance of above taxa also suggested higher transport and survival of oral microorganisms and promoted growth of the upper-gastrointestinal tract species in the distal bowel related to weight loss after gastric surgery in the previous study [70; 71] . However, in our study, they were observed in asymptomatic PBT individuals. It indicated that the existence of these taxa was impossibly responsible for inducing abdominal discomfort. More stable network we observed in PBT population provided a possible protective effect. The strong positive correlations between each pair of genera reveal that they grow and proliferate synchronously. In contrast, the negative correlations of the genus abundance indicate that they may compete with survival resources to inhibit each other. The more bacterial interactions in the intestinal microenvironment, it was more complicated to help maintain the gut homeostasis and less susceptible to be disturbed by external environmental factors. The genera with the high degree simply centralized in the Firmicutes in SIBO group in contrast that Bacteroides from Bacteroidota participated in maintaining the stability of the network in PBT. The betweeness centrality distribution indicated that the essential “bridges” were distinct in each network. However, the similarity could be found in PBT and SIBO due to the smaller Euclidean distance which demonstrated potential pathogens like Coprococcus_2 might be shared in two groups. In brief, we need pay more attention to the healthy conditions of PBT people even though none abdominal discomfort is reported so far. We also pay attention to the mental health of SIBO patients. Gut-brain-microbiota axis plays a core role in many functional gastrointestinal diseases (FGID) and provides a potential treatment target of mental disorders [ 72 ] . Numerous evidence indicates that psychological distress influences the gut immunity, leading to a potentiation of sensory nerves and visceral pain perception [73; 74] . Increased intestinal permeability is associated with the pathophysiology of neuroimmune disorders [ 75 ] . However, there was sparse knowledge about the mental status of SIBO patients. In our study, anxiety and depression scores in SIBO group using self-reporting scales were worse compared with healthy individuals. Interestingly, the anxiety scores of symptomatic patients also significantly higher compared with PBT, under the positive breath test background which represented the similar intestinal microbial loads. Neither anxiety ( r =-0.079, p = 0.331) nor depression ( r =-0.145, p = 0.074) were significantly related to Bacteroides . We supposed that mental status may be involved in abdominal complaints. In this study, asymptomatic individuals with abnormal breath tests were recruited for the first time. The bacterial composition and functional characteristics compared by 16S rRNA sequencing revealed possible microorganisms for GI symptoms in hydrogen/methane-producing populations. The saccharolytic bacteria associated with the development of SIBO and functional abnormalities were found. There was a significant correlation between Coprococcus and the severity of symptoms, which may be one of the biomarkers of SIBO. We also adopted novel bioinformatics methods and innovatively applied statistical parameters to establish objective indicators of network analysis. This may provide a basis for targeted treatment of pathogenic bacteria of SIBO in the future. However, it has some limitations which should not be neglected. First, we lack direct small intestine samples. Although the convenient and non-invasive fecal samples reflected the disturbed luminal contents influenced by the upstream bacterial overgrowth in our study, we need to take it into account that the microbiota transmission from the small intestine to the colon could not behave consistently [ 76 ] . The small intestine fluid and mucosal biopsies might be more representative to reflect the local pathogenic microbiota and host interactions even though there is still debate about the sampling position and contamination [1; 76; 77] . Additionally, we failed to follow up the symptoms of PBT individuals so that long-term impact of differential microbes in the small intestine is unknown. It deserved further concern about their future health status and whether they will develop GI symptoms with persistent intestinal dysbiosis. Conclusion This study provided the fecal composition and metabolic function changes in SIBO patients to explain their abdominal complaints. Increased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. Butyrivibrio and Coprococcus_2 abundance along with lower Bacteroides contributed to more noticeable discomfort of SIBO patients. The enriched Coprococcus may be one of the potential biomarkers of SIBO. Represented by Veillonella , asymptomatic PBT objects exhibited a different microbiome spectrum associated with the fermentation of amino acids and peptides rather than carbohydrates. The network of PBT was more stable which may play a protective role, but it deserved further attention in view of the shared essential “bridged” genera with SIBO. Abbreviations ANOVA univariate analysis of variance BMI body mass index BSF Bristol stool form BT breath test CFU colony-forming units CO2 carbon dioxide FFQ food frequency questionnaire FGID functional gastrointestinal diseases GI gastrointestinal GSRS gastrointestinal symptom rating scale H2S hydrogen sulfide HC healthy controls IBD inflammatory bowel disease IBS irritable bowel syndrome IQR interquartile range KEGG Kyoto Encyclopedia of Genes and Genome KO Kyoto Encyclopedia of Genes and Genome Orthology LBT lactulose hydrogen methane breath test OTU operational taxonomy units PBT positive breath test PcoA principal co-ordinates analysis PCOS obesity and polycystic ovary syndrome PERMANOVA permutational multivariate analysis of variance test PLS-DA partial least squares discriminant analysis PPIs proton pump inhibitors ppm part per million PULs polysaccharide utilization loci SAS self-reporting anaxiety scale SDS self-reporting depression scale SE standard error SIBO small intestinal bacterial overgrowth Declarations Ethical approval and consent to participate The study was conducted in accordance with the Declaration of Helsinki and was approved by the Medical Science Research Ethics Commission of Peking University Third Hospital (2019-293-02). Informed written consent was obtained from all patients prior to their enrolment in this study. Consent for publication Not applicable. Data availability The data that support the findings of this study are openly available in the National Center for Biotechnology Information Sequence Read Archive (SRA) repository at the reference number PRJNA907418. Competing interests The authors declare that they have no competing interests. Funding The study is supported by the International Institute of Population Health of Peking University Health Science Center (JKCJ202101). This funding source had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results. Authors’ contributions HZ G and LP D designed the study; HZ G, WX D, SQ L and YL D collected the samples; HZ G analysed the clinical symptom data; YZ C performed the bioinformatic and statistical analysis. HZ G, YZ C and LP D wrote the paper. LP D supervised the whole study. All authors commented on drafts of the paper and approved the final manuscript. Acknowledgements Not applicable. References Quigley EMM, Murray JA, Pimentel M. AGA Clinical Practice Update on Small Intestinal Bacterial Overgrowth: Expert Review [J]. Gastroenterology. 2020;159(4):1526–32. Bushyhead D, Quigley EMM. Small Intestinal Bacterial Overgrowth-Pathophysiology and Its Implications for Definition and Management [J]. Gastroenterology. 2022;163(3):593–607. Ghoshal UC, Nehra A, Mathur A, et al. A meta-analysis on small intestinal bacterial overgrowth in patients with different subtypes of irritable bowel syndrome [J]. J Gastroenterol Hepatol. 2020;35(6):922–31. Shah A, Morrison M, Burger D, et al. Systematic review with meta-analysis: the prevalence of small intestinal bacterial overgrowth in inflammatory bowel disease [J]. Aliment Pharmacol Ther. 2019;49(6):624–35. El Kurdi B, Babar S, Iskandarani E. 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Supplementary Files SupplementaryFigure.docx SupplementaryMethods.docx SupplementaryTableS1.xlsx SupplementaryTableS2.xlsx SupplementaryTableS3.xlsx SupplementaryTableS4.xlsx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 01 Jan, 2024 Reviewers invited by journal 01 Jan, 2024 Editor assigned by journal 30 Dec, 2023 First submitted to journal 29 Dec, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3823305","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":264605747,"identity":"c85b9ee5-75bb-4f21-b0cb-3f3a98daf535","order_by":0,"name":"Huaizhu Guo","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huaizhu","middleName":"","lastName":"Guo","suffix":""},{"id":264605748,"identity":"32617027-4270-41a7-a3ec-80dd7af88419","order_by":1,"name":"Yuzhu Chen","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuzhu","middleName":"","lastName":"Chen","suffix":""},{"id":264605749,"identity":"4f8adbdb-7e9d-4b9e-b80d-ff8e37c14c5e","order_by":2,"name":"Wenxin Dong","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenxin","middleName":"","lastName":"Dong","suffix":""},{"id":264605750,"identity":"1f0cdc41-0ed8-4c8a-9151-715cae179d5c","order_by":3,"name":"Siqi Lu","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Siqi","middleName":"","lastName":"Lu","suffix":""},{"id":264605751,"identity":"8f0d4242-02b5-4bab-83c7-1efa23a976a0","order_by":4,"name":"Yanlin Du","email":"","orcid":"","institution":"Peking University Third Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanlin","middleName":"","lastName":"Du","suffix":""},{"id":264605752,"identity":"7a2578a9-5bb8-423a-a501-1c9b07ec9b9f","order_by":5,"name":"Liping Duan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYDCCA0D8gMEmgbEBxGMjVksCQxrpWg4nQHjEaOG7kfzsQeKO83nM084YMHwoO8zAP7sBvxbJG2nmBolnbhczzs4xYJxx7jCDxJ0D+LUY3Egwk0hsu53YCNTCzNt2mMFAIoGQlvRvQC3nIFr+EqclB2TLAYgWRmK0SJ55UyaReCYZ6Je0goM959J5JG4Q0MJ3PH2bxMcddnmGs5M3PvhRZi3HP4OAFjAARaNhAySOeIhQD9UiT5zSUTAKRsEoGIkAAN0TSZgaabh0AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-6886-6888","institution":"Peking University Third Hospital","correspondingAuthor":true,"prefix":"","firstName":"Liping","middleName":"","lastName":"Duan","suffix":""}],"badges":[],"createdAt":"2023-12-30 06:27:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3823305/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3823305/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49129706,"identity":"a3bb43c0-a0d8-4fe8-be20-313f4375e63c","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":97963,"visible":true,"origin":"","legend":"\u003cp\u003eThe flow diagram and clinical manifestations. (a) Flow diagram of the participants in this study. (b) Comparison of anxiety and depression scores. (c) The severity and proportion of gastrointestinal symptom rating scale (GSRS) distribution in SIBO patients. HC: health control;PBT: positive breath test; SIBO: small intestinal bacterial overgrowth; IBS-SSS: irritable bowel syndrome symptom severity scale; BSF: Bristol stool form. * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/b3b708e8c3304a40683756ac.png"},{"id":49130064,"identity":"6f5843ff-f1bb-40cd-9e6b-5b12a6aef495","added_by":"auto","created_at":"2024-01-03 15:25:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":92963,"visible":true,"origin":"","legend":"\u003cp\u003eOverall microbiota composition and diversity. (a) Shannon index at the genus level in the alpha diversity. (b) Shannon index at the KEGG level3 pathway. (c) Venn analysis. (d) The relative abundance distribution at the genus level. (e) PCOA at the OTU level in the beta-diversity analysis. (f)PLS-DA analysis at the OTU level. KEGG: Kyoto encyclopedia of genes and genome; PCOA: principal co-ordinates analysis; OTU: operational taxonomic unit; PLS-DA: partial least squares discriminant analysis. * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/6061f3a5fb1ee02e3fcd08a3.png"},{"id":49129707,"identity":"791680e3-7a96-4b31-bc81-a4a6f0d9dbe4","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":88440,"visible":true,"origin":"","legend":"\u003cp\u003eDifferent microbiota profiles and inner correlation. (a-i) The relative abundance of different genera. (j) The inner correlation heatmap at the genus level. (k) The correlation heatmap between microbiota and host factors. * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; *** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/2a0aa5f69cfa27458d84bfde.png"},{"id":49129709,"identity":"b3293ce6-83fb-4da1-86e1-ba87c69d3e32","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":91270,"visible":true,"origin":"","legend":"\u003cp\u003eThe microbiota function changes in SIBO patients. (a-d) The relative abundance at the KEGG pathways. (e-h) The scatter plot of the gas production and the function relative abundance. Axis Y presented the hydrogen elevation rate at 90 minutes compared to the baseline level. (i) The correlation heatmap between functional changes and host factors. * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05; ** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; *** \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/f61225513a14df6a0b8462ba.png"},{"id":49130061,"identity":"00c67fe2-62bc-423e-912e-23f6b4f05112","added_by":"auto","created_at":"2024-01-03 15:25:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":312248,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation network of sixty-two genera common in three groups. The absolute value of relative coefficient greater than 0.5 were coded in the line color according to statistical significance (\u003cem\u003ep\u0026lt;\u003c/em\u003e0.05). The color of each node referred to the phylum. The genus names corresponding to each node were shown in Supplementary table 1. (a) Degree calculated in the network. The largest five nodes indicated a highest degree in the network. (b) Betweeness centrality calculated in the network. The size of each node was proportional to the betweeness centrality.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/4415d7ca59277e8e087308dd.png"},{"id":49129708,"identity":"7dd36587-a3f3-4688-8d6e-27f528cf2e29","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":312619,"visible":true,"origin":"","legend":"\u003cp\u003eThe probable explanation of the microbiota effect for SIBO and PBT group and potential treatment strategies. PBT: positive breath test; SIBO: small intestinal bacterial overgrowth\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/e501854ccbfb3176ee0e783a.png"},{"id":49131291,"identity":"c76cb0cf-eb5a-4b45-b51c-9fb74dc6ee0b","added_by":"auto","created_at":"2024-01-03 15:41:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2433565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/a9941a02-f6d2-4144-9c72-0be83dab3f46.pdf"},{"id":49129716,"identity":"7bd26991-a73f-4972-b30d-142e7f5fa58c","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":740806,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/44c92f044e21e36bfdf81bed.docx"},{"id":49130063,"identity":"53f57446-6695-4993-a0eb-ee0e885746b0","added_by":"auto","created_at":"2024-01-03 15:25:51","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":33836,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMethods.docx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/7f74e07bb047a17e7a83c927.docx"},{"id":49129714,"identity":"89ec1af8-390a-427f-aeb8-066ad446410b","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"xlsx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":41240,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/f0b2c8f3a0c64da3054241eb.xlsx"},{"id":49129713,"identity":"d3d93c7c-aa85-4682-9917-c684878ece60","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"xlsx","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":11345,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/539a783e8a9e470768f8c71a.xlsx"},{"id":49130695,"identity":"e5d2a416-f24d-41bf-9a47-4d7836384c93","added_by":"auto","created_at":"2024-01-03 15:33:51","extension":"xlsx","order_by":14,"title":"","display":"","copyAsset":false,"role":"supplement","size":11202,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/5030d4da5aff2043b2dcb779.xlsx"},{"id":49129717,"identity":"1288bee6-225a-48a5-9300-f21af8ce2e91","added_by":"auto","created_at":"2024-01-03 15:17:51","extension":"xlsx","order_by":15,"title":"","display":"","copyAsset":false,"role":"supplement","size":11387,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3823305/v1/dfd1df7bd5d0aa7c32c369ec.xlsx"}],"financialInterests":"","formattedTitle":"Fecal Coprococcus, Hidden behind Abdominal Symptoms in Patients with Small Intestinal Bacterial Overgrowth","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSmall intestinal bacterial overgrowth (SIBO) is a sparsely recognized clinical syndrome as the presence of an abnormally excessive amount of bacterial colonization in the small bowel with abdominal complaints \u003csup\u003e[1; 2]\u003c/sup\u003e. SIBO is closely associated with many gastrointestinal (GI) diseases, such as irritable bowel syndrome (IBS) \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e, inflammatory bowel disease (IBD) \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, pancreatitis \u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e, nonalcoholic liver disease \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, colorectal cancer and abdominal surgery. It is believed that symptoms linked to SIBO consist of bloating, diarrhea and abdominal pain/discomfort. In addition to main complaints, steatorrhea, vitamin B\u003csub\u003e12\u003c/sub\u003e deficiency and malnutrition can be seen in more severe cases \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Primary or secondary motility abnormalities destroy the ability of the small intestine to prevent colon bacterial translocation \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. Meanwhile, ileocaecal valve dysfunction leads to colonic bacterial regurgitation \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Long-term medication of proton pump inhibitors (PPIs) is associated with an increased risk of SIBO. The intragastric defence barrier damage by acid suppression therapy makes it easier for upstream opportunistic pathogens to enter the small intestine \u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Congenital or postoperative intestinal anatomical malformations increase local food residues and bacterial accumulation, like intestinal diverticulum, Roux-en-Y anastomosis or small bowel resection \u003csup\u003e[12; 13]\u003c/sup\u003e. Multiple pathophysiological mechanisms contribute to abdominal discomforts including carbohydrate fermentation and improper metabolites, GI chronic inflammation, mucosal immune deficiency, increased gut permeability, food intolerance and antigenemia \u003csup\u003e[14; 15]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe gold standard for diagnosis of SIBO is quantitative culture of small intestine aspirates. AGA recommended a new threshold at \u0026gt;\u0026thinsp;10\u003csup\u003e3\u003c/sup\u003e colony-forming units per milliliter (CFU/ml) on fresh aspirate culture instead of \u0026gt;\u0026thinsp;10\u003csup\u003e5\u003c/sup\u003e CFU/ml based on a large scale study \u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e, derived from subjects with altered intestinal anatomy because bacterial level in normal subjects rarely exceed 10\u003csup\u003e2\u003c/sup\u003e CFU/ml \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Based on the above diagnostic standard, SIBO subjects from the REIMAGINE study had a higher relative abundance of Proteobacteria and lower Firmicutes than non-SIBO subjects \u003csup\u003e[18; 19]\u003c/sup\u003e. Barblow et al. found that absolute loads of taxa in duodenal aspirates including \u003cem\u003eKlebsiella\u003c/em\u003e, \u003cem\u003eEscherichia\u003c/em\u003e, \u003cem\u003eEnterococcus\u003c/em\u003e, and \u003cem\u003eClostridium\u003c/em\u003e enriched in individuals with SIBO were associated with more severe upper GI symptoms, but they lacked healthy controls \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Another cohort study found that duodenal aspirate microbiome were altered in symptomatic patients, while the absolute counting of anaerobes in the small intestine fluid wasn\u0026rsquo;t parallel with the severity of symptoms \u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAn alternative method is the measurement of exhaled hydrogen and methane gas during the breath test (BT), which is considered as a non-invasive, safe, useful and cost-efficient method for SIBO. The North American Consensus recommended that a rise in hydrogen of \u0026ge;\u0026thinsp;20 part per million (ppm) or methane levels\u0026thinsp;\u0026ge;\u0026thinsp;10 ppm by 90 min during glucose or lactulose breath test was considered positive \u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. However, the positive lactulose or glucose breath test representative of bacterial overgrowth could also be detected in asymptomatic subjects with the prevalence varied from 3\u0026ndash;30% \u003csup\u003e[\u003cspan additionalcitationids=\"CR24 CR25 CR26\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. At present, we are still not clear about the possible mechanisms which lead to GI complaints and carbohydrate malabsorption in part of the positive BT population. Indeed, the small bowel microbiome analysis limited its\u0026rsquo; application. This study aimed to illustrate the gut microbiome profiles of SIBO patients compared with asymptomatic positive breath test (PBT) subjects and health control (HC), and identify potential fecal biomarkers for abdominal discomfort in SIBO.\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatient recruitment\u003c/h2\u003e \u003cp\u003eThe study was performed from April 2019 to May 2021. SIBO patients who reported non-specific abdominal symptoms and fulfilled the diagnostic criteria of lactulose hydrogen and methane breath test were recruited from the Department of Gastroenterology, Peking University Third Hospital. The inclusion criteria were as follows: a) aged\u0026thinsp;\u0026ge;\u0026thinsp;18 and \u0026le;\u0026thinsp;65 years old; b) GI discomfort, mainly abdominal pain, distension, constipation, diarrhoea for over 6 months; c) positive lactulose hydrogen methane breath test (LBT); d) voluntarily joined the study and completed the case report form, hydrogen-methane breath test and stool collection. Patients were excluded if they fulfilled one or more of the following exclusion criteria: a) GI organic diseases detected by endoscopy or digestive tract surgery history; b) with severe heart, liver, lung, kidney, blood, endocrine and nervous system diseases or severe respiratory tract, digestive tract, urinary tract infections or mental disorders; c) taking antibiotics and acid suppression drugs for more than 3 days during the past month or probiotics, laxatives, antidiarrheal or prokinetic agents within 2 weeks; d) pregnant or lactating women. Asymptomatic subjects were recruited in the same clinical center. According to their LBT results, they were divided into positive breath test (PBT) group and negative health control (HC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eClinical evaluation and sampling\u003c/h2\u003e \u003cp\u003eDemographic data including age, gender, height, weight and body mass index (BMI) were recorded for each participant. Daily bowel habit and frequency were recorded based on the Bristol stool form (BSF) scale \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. GI symptom severity was evaluated by gastrointestinal symptom rating scale (GSRS) \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. The symptom score was the sum of abdominal pain, distension, constipation, diarrhoea scores. Self-reporting anxiety scale (SAS) and self-reporting depression scale (SDS) were used to evaluate the mental health conditions \u003csup\u003e[30; 31]\u003c/sup\u003e. 7 day food frequency questionnaire (FFQ) was used to estimate their dietary pattern \u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e. Written informed consent was obtained from each participant prior to sample collection.\u003c/p\u003e \u003cp\u003eAll included participants were required to stop using antibiotics, probiotics, prebiotics, and other microbiota-related supplements at least two weeks before stool sampling. Stool specimen were stored by stool nucleic acid collection and servation tubes (Norgen Biotek Corp., Toronto, Ontario, Canada), then transported to the laboratory using dry ice and were frozen at \u0026minus;\u0026thinsp;80\u0026deg;C.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGut microbiota analysis\u003c/h2\u003e \u003cp\u003eMicrobial community genomic DNA was extracted from 154 samples and purified amplicons were pooled in equimolar and paired-end sequences on an Illumina MiSeq PE300 platform (Illumina, San Diego, U.S.) according to the standard protocols by Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China).\u003c/p\u003e \u003cp\u003eAll microbiome samples were processed and analyzed by Parallel-Meta Suite with SILVA database on the operational taxonomy units (OTU) similarity level of 97% \u003csup\u003e[33; 34]\u003c/sup\u003e. The functional profiles were predicted with PICRUSt2 and annotated with Kyoto Encyclopedia of Genes and Genome (KEGG) Orthology (KO) \u003csup\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. For alpha diversity, Shannon indexes of each samples were calculated and illustrated into boxplots with permutational multivariate analysis of variance (PERMANOVA) test. For beta diversity, principal co-ordinates analysis (PcoA) using meta storms distance algorithm \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e and partial least squares discriminant analysis (PLS-DA) was analyzed in R (version 4.2.1). Cytoscape was used in the co-occurrence network analysis with \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05 and |r|\u0026ge;0.5 \u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Additional information on sequencing and analysis is available in Supplemental Materials.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eClinical feature statistical analysis\u003c/h2\u003e \u003cp\u003eAnalysis will be conducted through SPSS V.26.0. The quantitative and qualitative variables were reported as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard error (SE), median\u0026thinsp;\u0026plusmn;\u0026thinsp;interquartile range (IQR), and number (frequency). Univariate analysis of variance (ANOVA) will examine differences between groups for variables with continuous data. χ2 tests will examine differences between groups for categorical variables. Linear correlations will be analyzed through Pearson\u0026rsquo;s correlation analysis. Non-parametric correlations will be analyzed through Spearman's correlation analysis. A \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistical significance for above tests.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eThe clinical manifestation of SIBO patients\u003c/h2\u003e \u003cp\u003eIn total, 154 subjects were enrolled, including 63 SIBO patients, 36 PBT and 55 HC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). There were no statistically significant differences among the three groups in terms of gender, age, body mass index (BMI), carbohydrate, protein, fat consumption and energy proportion (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Patients with SIBO had significantly higher anxiety scores (39.42\u0026thinsp;\u0026plusmn;\u0026thinsp;8.70) than PBT (36.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.49, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and HC (34.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.68, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), respectively. The depression scores of SIBO group (42.84\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31) were higher than that of HC group (38.72\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical manifestation among SIBO, PBT and HC group Legend: \u003csup\u003e*\u003c/sup\u003ea significant difference compared with HC; \u003csup\u003e#\u003c/sup\u003e a significant difference compared with PBT\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePBT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSIBO\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (female, n/%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32/58.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29/80.55%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45/71.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.49\u0026thinsp;\u0026plusmn;\u0026thinsp;2.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.08\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.30\u0026thinsp;\u0026plusmn;\u0026thinsp;2.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.44\u0026thinsp;\u0026plusmn;\u0026thinsp;2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.96\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate (g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e307.79\u0026thinsp;\u0026plusmn;\u0026thinsp;43.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223.57\u0026thinsp;\u0026plusmn;\u0026thinsp;21.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e301.30\u0026thinsp;\u0026plusmn;\u0026thinsp;58.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.494\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein (g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.98\u0026thinsp;\u0026plusmn;\u0026thinsp;6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.35\u0026thinsp;\u0026plusmn;\u0026thinsp;6.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.847\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat (g/d)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.01\u0026thinsp;\u0026plusmn;\u0026thinsp;7.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.89\u0026thinsp;\u0026plusmn;\u0026thinsp;4.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.69\u0026thinsp;\u0026plusmn;\u0026thinsp;3.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy proportion of carbohydrate (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.46\u0026thinsp;\u0026plusmn;\u0026thinsp;1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy proportion of protein (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy proportion of fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.32\u0026thinsp;\u0026plusmn;\u0026thinsp;2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.90\u0026thinsp;\u0026plusmn;\u0026thinsp;2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.55\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.68\u0026thinsp;\u0026plusmn;\u0026thinsp;7.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.42\u0026thinsp;\u0026plusmn;\u0026thinsp;8.70\u003csup\u003e* #\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.72\u0026thinsp;\u0026plusmn;\u0026thinsp;8.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.86\u0026thinsp;\u0026plusmn;\u0026thinsp;8.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.84\u0026thinsp;\u0026plusmn;\u0026thinsp;8.31\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to GSRS scores, the dominant symptoms in SIBO patients were distension (63.49%), constipation (49.21%), loose stool (47.62%), hunger pain (46.03%), urgent stool (41.27%), hyperactive sound (41.27%) and abdominal pain (38.10%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eOverall fecal microbiota composition and diversity\u003c/h2\u003e \u003cp\u003eNo significant difference was found in community diversity of the gut microbiome on genus level (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.229, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Notably the Shannon index of SIBO significantly decreased compared with HC group on KEGG BRITE level3 pathway (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). \u003cem\u003eButyrivibrio\u003c/em\u003e only occurred in SIBO, \u003cem\u003eVeillonella, Barnesiella, Escherichia-Shigella\u003c/em\u003e and \u003cem\u003eTyzzerella_3\u003c/em\u003e in PBT group, and \u003cem\u003eHoldemanella\u003c/em\u003e in HC group, respectively. \u003cem\u003eAlloprevotella\u003c/em\u003e and \u003cem\u003eRuminiclostridium_6\u003c/em\u003e were detected in both SIBO and PBT groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Each group was dominated by \u003cem\u003eBacteroides\u003c/em\u003e, followed by \u003cem\u003ePrevotella_9, Faecalibacterium, Blautia and Roseburia\u003c/em\u003e at the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed and Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The taxonomic compositions at the phylum level were shown in Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Even though no significant effect was found at the OTU level in the beta-diversity analysis among three groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), PLS-DA indicated a compositional distinction of microbiota (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe unique bacterial genera and their metabolic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePhylum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProduct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGas\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePBT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eVeillonella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFirmicutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVeillonellaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePolyamines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetate, propionate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eBarnesiella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBacteroidota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBarnesiellaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetate Succinate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEscherichia-Shigella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProteobacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEnterobacteriaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTyzzerella_3\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirmicutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLachnospiraceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePBT\u0026amp;SIBO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAlloprevotella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBacteroidota\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrevotellaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetate Succinate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRuminiclostridium_6\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirmicutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOscillospiraceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetate Propionate butyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSIBO\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eButyrivibrio\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirmicutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLachnospiraceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eButyrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHoldemanella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirmicutes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eErysipelotrichaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAcetate Propionate Butyrate Lactic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNR\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eLegend: PBT: positive breath test; SIBO: small intestinal bacterial overgrowth; HC: health control; NR no related evidence.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eFecal microbiota taxonomic changes for screening potential biomarkers\u003c/h2\u003e \u003cp\u003eThe significant lower abundance of \u003cem\u003eBacteroides\u003c/em\u003e and higher abundance of \u003cem\u003eCoprococcus_2\u003c/em\u003e were observed in SIBO compared with HC at the genus level (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, b). It should be noted that more kinds of microbiota differences were discovered in the PBT group. The relative abundance of \u003cem\u003eBilophila\u003c/em\u003e, \u003cem\u003eOscillibacter\u003c/em\u003e and \u003cem\u003eRuminococcus_torques\u003c/em\u003e were significantly decreased, and the \u003cem\u003eButyricicoccus\u003c/em\u003e, \u003cem\u003eSutterella\u003c/em\u003e, \u003cem\u003eLachnospiraceae_UCG004\u003c/em\u003e and \u003cem\u003eDialister\u003c/em\u003e were enriched in PBT (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec-i).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFurthermore, we assessed the Spearman\u0026rsquo;s correlations of these microbiota which suggested the synergistic and competitive effects (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ej). The relative abundance of \u003cem\u003eBacteroides\u003c/em\u003e was negatively associated with that of \u003cem\u003eCoprococcus_2\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e=-0.563, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). We also detected the negative correlation between \u003cem\u003eRuminococcus_torques\u003c/em\u003e and \u003cem\u003eSutterella\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e=-0.304, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as between \u003cem\u003eBilophila\u003c/em\u003e and \u003cem\u003eLachnospiraceae_UCG004\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e=-0.210, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01). The significantly positive correlations between each pair of the three decreasing genera in PBT group suggested the similar trend. The relative abundance of \u003cem\u003eCoprococcus_2\u003c/em\u003e was positively associated with that of \u003cem\u003eOscillibacter\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.218, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and \u003cem\u003eRuminococcus_torques\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.310, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eThe correlation heatmap revealed significant positive correlations between the relative abundance of \u003cem\u003eCoprococcus_2\u003c/em\u003e and the severity of all symptoms (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ek). \u003cem\u003eBacteroides\u003c/em\u003e was negatively related to constipation and distension. No significant relation was found between the differential genera and the mental scores.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDiminishing metabolic functions associated with abdominal symptoms in SIBO\u003c/h2\u003e \u003cp\u003eTo explore the functional changes associated with differences in microbial composition, gut microbiome function was imputed using PICRUSt2 and pathway analysis based on the KEGG database. Different predicted pathways were determined (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea-d and Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Interestingly, pathways associated with amino acid metabolism were enriched in healthy individuals, including arginine and proline metabolism, valine, leucine and isoleucine degradation, and phenylalanine metabolism, mostly essential amino acids involved. The pathway reflective of one carbon pool by folate were significantly dropped in SIBO. Furthermore, the significant negative correlation between the gas production rate at 90 minutes and the functional changes were stable (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ee-h). To determine the association of microbiota functional changes and disease, the relative abundance of the functions and host parameters were considered for the correlation analyses. Overall, the above functional changes were negatively associated with symptom scale, constipation, abdominal distension and pain (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ei). The functional changes also had a significantly positive correlation with \u003cem\u003eBacteroides\u003c/em\u003e and a negative correlation with \u003cem\u003eCoprococcus_2\u003c/em\u003e, supporting the synergism with the taxonomic relative abundance (Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMicrobial co-occurrence network analysis\u003c/h2\u003e \u003cp\u003eThe co-occurrence network including 62 common genera was obtained cross-correlating all the relative abundance against one another in three groups, respectively. The absolute value of relative coefficient greater than 0.5 were coded in the line color. The node names were presented in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. The local properties of the networks were analyzed including degree (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea and Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e) and betweenness centrality (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb and Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003ea showed the largest network density in PBT group (ρ\u0026thinsp;=\u0026thinsp;0.089), which represented a more complex microbiota interaction compared to the similar degree distributions in HC (ρ\u0026thinsp;=\u0026thinsp;0.061) and SIBO (ρ\u0026thinsp;=\u0026thinsp;0.060). The larger nodes indicated a higher degree which reflected the complicated interaction in the whole network. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eb, the size of each node was proportional to the betweeness centrality, suggesting that the larger one could be necessary for network functionality. Nodes 42, 30 and 21, which represent the genus \u003cem\u003eEubacterium_oxidoreducens\u003c/em\u003e, \u003cem\u003eDorea\u003c/em\u003e and \u003cem\u003eRuminococcaceae_NK4A214\u003c/em\u003e, showed a high betweeness centrality in HC group. Nodes 11, 42 and 18, which represent the genus \u003cem\u003eRuminococcus_1\u003c/em\u003e, \u003cem\u003eEubacterium_oxidoreducens\u003c/em\u003e and \u003cem\u003eCoprococcus_2\u003c/em\u003e, showed a high betweeness centrality in SIBO group. Nodes 18, 43 and 42, which represent the genus \u003cem\u003eCoprococcus_2\u003c/em\u003e, \u003cem\u003eEubacterium_ruminantium\u003c/em\u003e and \u003cem\u003eEubacterium_oxidoreducens\u003c/em\u003e, showed a high betweeness centrality in PBT group. The Euclidean distance of 62-dimensional betweeness centralities between PBT and SIBO is 512.78, the distance between PBT and HC is 539.76, while the distance between HC and SIBO is 557.60, reflecting that the necessary microbiota in the whole network were more similar in the PBT and SIBO.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we present the microbial composition from the positive hydrogen and methane breath test population with and without abdominal discomfort and with an otherwise healthy gut for the first time. We observed that symptomatic patients showed higher alpha diversity of the fecal microbiota. Significantly decreased \u003cem\u003eBacteroides\u003c/em\u003e and increased \u003cem\u003eCoprococcus_2\u003c/em\u003e were observed, and unique \u003cem\u003eButyrivibrio\u003c/em\u003e richness was responsible for gas production with carbohydrates as fermentation substrates. The alpha diversity at the KEGG functional level was significantly reduced. Both the composition and function alterations of the microbiota were correlated with GI symptoms in SIBO. Anxiety and depression might be related to reporting more abdominal symptoms in SIBO patients. On the other hand, individuals with solely positive breath test possessed a more stable network reflecting the complicated interactions of the fecal microbiota. Gas production represented by \u003cem\u003eVeillonella\u003c/em\u003e in PBT was associated with the microbial fermentation of amino acids and peptides (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMostly, SIBO patients complain of non-specific GI symptoms by the presence of the excessive colonization of aerobic or anaerobic bacteria in the small bowel \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e. The symptoms are closely related to fermentation of non-absorbed carbohydrates like nausea, bloating, flatulence, distension, abdominal pain, diarrhoea, and/or constipation \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. A significant proportion of patients deny effective treatment as misdiagnosed as IBS due to the unclear symptom spectrum \u003csup\u003e[2; 40; 41]\u003c/sup\u003e. In our study, we found that the most frequently reported symptom was abdominal distension, followed by changes of defecation habits (constipation). Abdominal pain for the essential diagnosis of IBS in Rome IV consensus was not highlighted for SIBO patients. Gas-producing related symptoms such as bloating, gassiness, cramping and distension were more obvious \u003csup\u003e[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. Primary or secondary motility abnormalities destroy the ability of the small intestine to prevent colon bacterial translocation \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e, thus slow intestinal transit leads to excessive gas retention and constipation \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe small intestine represents the first region where food components and the intestinal bacteria encounter each other for primary carbohydrate metabolism. Over the past few decades, the lack of knowledge for SIBO was confined to the collection, storage and culture of small bowel fluids. Almost samples were obtained near the duodenal or jejunum rather than the bacterial colonization by upper gastrointestinal endoscopy at the risk of contamination. Inevitably gas injection during the endoscopic operation may disturb anaerobic culture of SIBO \u003csup\u003e[44; 45]\u003c/sup\u003e.The fecal microbiota composition alteration may help for the explanation of the metabolism features and progression of SIBO. SIBO can be defined as the inappropriate fermentation of many kinds of carbohydrate and simultaneously multiple nutrient malabsorption by the culture of proximal intestinal aspirates or measurement of exhaled hydrogen and methane. The \u003cem\u003eButyrivibrio spp.\u003c/em\u003e from Lachnospriaceae detected only in SIBO patients could encode a more impressive repertoire of carbohydrate-active enzymes than most Firmicutes \u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e, capable of growing on a range of carbohydrates, from mono-or oligosaccharides to complex plant polysaccharides, such as pectins, mannans, starch, and hemicelluloses \u003csup\u003e[47; 48]\u003c/sup\u003e. The end-products were butyrate and many kinds of gas including hydrogen (H\u003csub\u003e2\u003c/sub\u003e), carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) and hydrogen sulfide (H\u003csub\u003e2\u003c/sub\u003eS). \u003cem\u003eButyrivibrio\u003c/em\u003e was significantly abundant in subjects that reported traveler\u0026rsquo;s diarrhea \u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e, while also significantly higher in the constipation dominant IBS patients from mucosal samples \u003csup\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur findings supported a negative correlation of the relative abundance of \u003cem\u003eBacteroides\u003c/em\u003e and GI symptoms, concurred with lower amount of \u003cem\u003eBacteroides\u003c/em\u003e in SIBO patients. Several species of \u003cem\u003eBacteroides\u003c/em\u003e which we considered as beneficial bacteria could access their desired nutrients from long chain polysaccharides and oligosaccharides that are not readily absorbed by the epithelial cells of the colon in healthy status base on the polysaccharide utilization loci (PULs) \u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e, producing useful short-chain fatty acids. It is recognized that \u003cem\u003eBacteroides spp.\u003c/em\u003e have been widely implicated in mental disorders and could modulate depression-like behavior\u003csup\u003e[\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e. Bamba et al. (2023) have found that the relative abundance of \u003cem\u003eBacteroides\u003c/em\u003e in duodenal aspirates of SIBO patients was significantly lower than that of non-SIBO patients. Therefore, we inferred that the decline of \u003cem\u003eBacteroides\u003c/em\u003e in accordance to the duodenal aspirates reflected the overuse of carbohydrates or inner competition by proliferating bacteria in the small intestine. Conversely, the genus \u003cem\u003eCoprococcus_2\u003c/em\u003e was positively correlated with the symptom score and all symptoms concurred with a higher abundance in SIBO. \u003cem\u003eCoprococcus spp.\u003c/em\u003e within the family Lachnospiraceae of Firmicutes are deemed the core genera for the maintenance of microbial homeostasis and healthy status \u003csup\u003e[56; 57]\u003c/sup\u003e, as they contribute to the production of the health-promoting metabolite butyrate. Nevertheless, \u003cem\u003eCoprococcus_2\u003c/em\u003e was associated with a higher risk of IBD \u003csup\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e, obesity and polycystic ovary syndrome (PCOS) \u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. There are significant differences in the utilization of carbohydrates among \u003cem\u003eCoprococcus\u003c/em\u003e subgroups. Multiple carbon source substrates could be utilized by \u003cem\u003eC.eutactus\u003c/em\u003e, mainly contained in \u003cem\u003eCoprococcus_2\u003c/em\u003e\u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e. As a short-chain fatty acid-producing bacterium, \u003cem\u003eC. eutactus\u003c/em\u003e mainly generates acetic acid\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/sup\u003e. An randomized clinical trial of berberine and rifaximine effects for SIBO is underway in our clinical center\u003csup\u003e[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/sup\u003e. We further found that lower relative abundance of \u003cem\u003eCoprococcus\u003c/em\u003e inhibited by berberine was observed in patients with negative hydrogen methane breath tests after medication compared with baseline (0.18\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13% vs. 1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). On the contrary, there was no significant change in the relative abundance of \u003cem\u003eCoprococcus\u003c/em\u003e before and after medication in those who failed to respond to berberine (0.32\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17% vs. 0.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.775). The baseline relative abundance of \u003cem\u003eCoprococcus\u003c/em\u003e could also indicate drug response (Figure \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e). The increased \u003cem\u003eCoprococcus\u003c/em\u003e abundance may be one of the potential biomarkers of SIBO. Further studies should be performed to determine the disruptors in the small intestine.\u003c/p\u003e \u003cp\u003ePICRUSt analysis found that the metabolic function alterations matched with the microbiota abundance changes. Amino acid metabolism pathways, mostly essential amino acids involved, were downregulated in SIBO patients reflecting the result of competition of the nutrient metabolism in the small bowel. Studies have shown that an excess of bacteria in the small intestine altered the tryptophan metabolism which may increase in a variety of infections and inflammations \u003csup\u003e[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e. Our study further revealed that these bacteria predominantly ferment carbohydrates with a consequence of the down regulation of amino acid metabolism, which may interfere the amino acid absorption. In addition, biosynthesis and cycle of tetrahydrofolate were down regulated according to the decreased one carbon pool by folate in SIBO, which provided the potential explanation for megaloblastic anemia in more severe patients. The metabolic pathway functions were also negatively correlate with the symptom spectrum and hydrogen levels, which illustrated the harmful effects of SIBO on the microbiota metabolism function.\u003c/p\u003e \u003cp\u003eA number of taxonomic groups we identified in PBT reflected the diverse nutrient metabolic features as the highlight of this study. \u003cem\u003eVeillonella\u003c/em\u003e within the family Veillonellaceae of Firmicutes, existed in 28 of 36 PBT objects, were also commonly found in duodenal aspirate sequencing \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eVeillonella\u003c/em\u003e is the predominant components in the small intestine of healthy subjects \u003csup\u003e[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/sup\u003e. It is characterized in that glucose or any other carbohydrate is not fermented, but relies on organic acids, amino acids and peptides as carbon sources which may explain the exhaled gas production like H\u003csub\u003e2\u003c/sub\u003e and H\u003csub\u003e2\u003c/sub\u003eS \u003csup\u003e[65; 66]\u003c/sup\u003e. Fermentation of amino acids and proteins were also observed on \u003cem\u003eBarnesiella\u003c/em\u003e, another unique genus occurred in most PBT individuals \u003csup\u003e[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/sup\u003e. \u003cem\u003eDialister\u003c/em\u003e, asaccharolytic, had close phylogenetic distance and similar physiological characteristics with \u003cem\u003eVeillonella\u003c/em\u003e and overrepresented in cirrhosis duodenum \u003csup\u003e[68; 69]\u003c/sup\u003e. The great abundance of above taxa also suggested higher transport and survival of oral microorganisms and promoted growth of the upper-gastrointestinal tract species in the distal bowel related to weight loss after gastric surgery in the previous study \u003csup\u003e[70; 71]\u003c/sup\u003e. However, in our study, they were observed in asymptomatic PBT individuals. It indicated that the existence of these taxa was impossibly responsible for inducing abdominal discomfort. More stable network we observed in PBT population provided a possible protective effect. The strong positive correlations between each pair of genera reveal that they grow and proliferate synchronously. In contrast, the negative correlations of the genus abundance indicate that they may compete with survival resources to inhibit each other. The more bacterial interactions in the intestinal microenvironment, it was more complicated to help maintain the gut homeostasis and less susceptible to be disturbed by external environmental factors. The genera with the high degree simply centralized in the Firmicutes in SIBO group in contrast that \u003cem\u003eBacteroides\u003c/em\u003e from Bacteroidota participated in maintaining the stability of the network in PBT. The betweeness centrality distribution indicated that the essential \u0026ldquo;bridges\u0026rdquo; were distinct in each network. However, the similarity could be found in PBT and SIBO due to the smaller Euclidean distance which demonstrated potential pathogens like \u003cem\u003eCoprococcus_2\u003c/em\u003e might be shared in two groups. In brief, we need pay more attention to the healthy conditions of PBT people even though none abdominal discomfort is reported so far.\u003c/p\u003e \u003cp\u003eWe also pay attention to the mental health of SIBO patients. Gut-brain-microbiota axis plays a core role in many functional gastrointestinal diseases (FGID) and provides a potential treatment target of mental disorders \u003csup\u003e[\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]\u003c/sup\u003e. Numerous evidence indicates that psychological distress influences the gut immunity, leading to a potentiation of sensory nerves and visceral pain perception \u003csup\u003e[73; 74]\u003c/sup\u003e. Increased intestinal permeability is associated with the pathophysiology of neuroimmune disorders \u003csup\u003e[\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e]\u003c/sup\u003e. However, there was sparse knowledge about the mental status of SIBO patients. In our study, anxiety and depression scores in SIBO group using self-reporting scales were worse compared with healthy individuals. Interestingly, the anxiety scores of symptomatic patients also significantly higher compared with PBT, under the positive breath test background which represented the similar intestinal microbial loads. Neither anxiety (\u003cem\u003er\u003c/em\u003e=-0.079, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.331) nor depression (\u003cem\u003er\u003c/em\u003e=-0.145, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.074) were significantly related to \u003cem\u003eBacteroides\u003c/em\u003e. We supposed that mental status may be involved in abdominal complaints.\u003c/p\u003e \u003cp\u003eIn this study, asymptomatic individuals with abnormal breath tests were recruited for the first time. The bacterial composition and functional characteristics compared by 16S rRNA sequencing revealed possible microorganisms for GI symptoms in hydrogen/methane-producing populations. The saccharolytic bacteria associated with the development of SIBO and functional abnormalities were found. There was a significant correlation between \u003cem\u003eCoprococcus\u003c/em\u003e and the severity of symptoms, which may be one of the biomarkers of SIBO. We also adopted novel bioinformatics methods and innovatively applied statistical parameters to establish objective indicators of network analysis. This may provide a basis for targeted treatment of pathogenic bacteria of SIBO in the future.\u003c/p\u003e \u003cp\u003eHowever, it has some limitations which should not be neglected. First, we lack direct small intestine samples. Although the convenient and non-invasive fecal samples reflected the disturbed luminal contents influenced by the upstream bacterial overgrowth in our study, we need to take it into account that the microbiota transmission from the small intestine to the colon could not behave consistently \u003csup\u003e[\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e]\u003c/sup\u003e. The small intestine fluid and mucosal biopsies might be more representative to reflect the local pathogenic microbiota and host interactions even though there is still debate about the sampling position and contamination \u003csup\u003e[1; 76; 77]\u003c/sup\u003e. Additionally, we failed to follow up the symptoms of PBT individuals so that long-term impact of differential microbes in the small intestine is unknown. It deserved further concern about their future health status and whether they will develop GI symptoms with persistent intestinal dysbiosis.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provided the fecal composition and metabolic function changes in SIBO patients to explain their abdominal complaints. Increased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. \u003cem\u003eButyrivibrio\u003c/em\u003e and \u003cem\u003eCoprococcus_2\u003c/em\u003e abundance along with lower \u003cem\u003eBacteroides\u003c/em\u003e contributed to more noticeable discomfort of SIBO patients. The enriched \u003cem\u003eCoprococcus\u003c/em\u003e may be one of the potential biomarkers of SIBO. Represented by \u003cem\u003eVeillonella\u003c/em\u003e, asymptomatic PBT objects exhibited a different microbiome spectrum associated with the fermentation of amino acids and peptides rather than carbohydrates. The network of PBT was more stable which may play a protective role, but it deserved further attention in view of the shared essential \u0026ldquo;bridged\u0026rdquo; genera with SIBO.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eunivariate analysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBSF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBristol stool form\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ebreath test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecolony-forming units\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCO2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecarbon dioxide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFFQ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efood frequency questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFGID\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efunctional gastrointestinal diseases\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egastrointestinal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGSRS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egastrointestinal symptom rating scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eH2S\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehydrogen sulfide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehealthy controls\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einflammatory bowel disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eirritable bowel syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genome Orthology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elactulose hydrogen methane breath test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOTU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eoperational taxonomy units\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePBT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epositive breath test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePcoA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprincipal co-ordinates analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eobesity and polycystic ovary syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePERMANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epermutational multivariate analysis of variance test\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLS-DA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epartial least squares discriminant analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPIs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eproton pump inhibitors\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eppm\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epart per million\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePULs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epolysaccharide utilization loci\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eself-reporting anaxiety scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eself-reporting depression scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard error\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSIBO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esmall intestinal bacterial overgrowth\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki and was approved by the Medical Science Research Ethics Commission of Peking University Third Hospital (2019-293-02). Informed written consent was obtained from all patients prior to their enrolment in this study.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe data that support the findings of this study are openly available in the National Center for Biotechnology Information Sequence Read Archive (SRA) repository at the reference number PRJNA907418.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThe study is supported by the International Institute of Population Health of Peking University Health Science Center (JKCJ202101). This funding source had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eHZ G and LP D designed the study; HZ G, WX D, SQ L and YL D collected the samples; HZ G analysed the clinical symptom data; YZ C performed the bioinformatic and statistical analysis. HZ G, YZ C and LP D wrote the paper. LP D supervised the whole study. All authors commented on drafts of the paper and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuigley EMM, Murray JA, Pimentel M. AGA Clinical Practice Update on Small Intestinal Bacterial Overgrowth: Expert Review [J]. Gastroenterology. 2020;159(4):1526\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBushyhead D, Quigley EMM. Small Intestinal Bacterial Overgrowth-Pathophysiology and Its Implications for Definition and Management [J]. Gastroenterology. 2022;163(3):593\u0026ndash;607.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhoshal UC, Nehra A, Mathur A, et al. A meta-analysis on small intestinal bacterial overgrowth in patients with different subtypes of irritable bowel syndrome [J]. J Gastroenterol Hepatol. 2020;35(6):922\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah A, Morrison M, Burger D, et al. Systematic review with meta-analysis: the prevalence of small intestinal bacterial overgrowth in inflammatory bowel disease [J]. Aliment Pharmacol Ther. 2019;49(6):624\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Kurdi B, Babar S, Iskandarani E. 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World J Gastroenterol. 2012;18(46):6801\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLo WK, Chan WW. Proton pump inhibitor use and the risk of small intestinal bacterial overgrowth: a meta-analysis [J]. Clin Gastroenterol Hepatol. 2013;11(5):483\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen B, Kim JJ, Zhang Y, et al. Prevalence and predictors of small intestinal bacterial overgrowth in irritable bowel syndrome: a systematic review and meta-analysis [J]. J Gastroenterol. 2018;53(7):807\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu T, Lai S, Lee A, et al. Meta-analysis: proton pump inhibitors moderately increase the risk of small intestinal bacterial overgrowth [J]. J Gastroenterol. 2018;53(1):27\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGrath KH, Pitt J, Bines JE. Small intestinal bacterial overgrowth in children with intestinal failure on home parenteral nutrition [J]. JGH Open. 2019;3(5):394\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDolan RD, Baker J, Harer K, et al. Small Intestinal Bacterial Overgrowth: Clinical Presentation in Patients with Roux-en-Y Gastric Bypass [J]. Obes Surg. 2021;31(2):564\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAvelar Rodriguez D, Ryan PM, Monjaraz T. Small Intestinal Bacterial Overgrowth in Children: A State-Of-The-Art Review [J]. Front Pediatr. 2019;7:363.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiazga A, Osiński M, Cichy W, et al. Current views on the etiopathogenesis, clinical manifestation, diagnostics, treatment and correlation with other nosological entities of SIBO [J]. Adv Med Sci. 2015;60(1):118\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeite G, Villanueva-Millan MJ, Celly S et al. First Large Scale Study Defining the Characteristic Microbiome Signatures of Small Intestinal Bacterial Overgrowth (SIBO): Detailed Analysis from the Reimagine Study [J]. Gastroenterology. 2019, 156(6): S-1-S-2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePimentel M, Saad RJ, Long MD, et al. ACG Clinical Guideline: Small Intestinal Bacterial Overgrowth [J]. Am J Gastroenterol. 2020;115(2):165\u0026ndash;78.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeite G, Morales W, Weitsman S, et al. The duodenal microbiome is altered in small intestinal bacterial overgrowth [J]. PLoS ONE. 2020;15(7):e0234906.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeite GGS, Morales W, Weitsman S, et al. Optimizing microbiome sequencing for small intestinal aspirates: validation of novel techniques through the REIMAGINE study [J]. BMC Microbiol. 2019;19(1):239.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarlow JT, Leite G, Romano AE, et al. Quantitative sequencing clarifies the role of disruptor taxa, oral microbiota, and strict anaerobes in the human small-intestine microbiome [J]. Microbiome. 2021;9(1):214.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaffouri GB, Shields-Cutler RR, Chen J et al. Small intestinal microbial dysbiosis underlies symptoms associated with functional gastrointestinal disorders [J]. Nat Commun. 2019, 10(1): 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRezaie A, Buresi M, Lembo A, et al. Hydrogen and Methane-Based Breath Testing in Gastrointestinal Disorders: The North American Consensus [J]. Am J Gastroenterol. 2017;112(5):775\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah A, Shanahan E, Macdonald GA, et al. 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The Spectrum of Small Intestinal Bacterial Overgrowth (SIBO) [J]. Curr Gastroenterol Rep. 2019;21(1):3.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"small intestinal bacterial overgrowth, hydrogen and methane breath test, gut microbiome, network analysis, saccharolytic bacteria","lastPublishedDoi":"10.21203/rs.3.rs-3823305/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3823305/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Small intestinal bacterial overgrowth (SIBO) is the presence of an abnormally excessive amount of bacterial colonization in the small bowel. Hydrogen and methane breath test has been widely applied as a non-invasive method for SIBO. However, the positive breath test representative of bacterial overgrowth could also be detected in asymptomatic individuals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e To explore the relationship between clinical symptoms and gut dysbiosis, and find potential fecal biomarkers for SIBO, we compared the microbial profiles between SIBO subjects with positive breath test but without abdominal symptoms (PBT) and healthy controls (HC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eFecal samples were collected from 63 SIBO who complained of diarrhea, distension, constipation or abdominal pain, 36 PBT and 55 HC. Increased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. At the genus level, significantly decreased \u003cem\u003eBacteroides\u003c/em\u003eand increased \u003cem\u003eCoprococcus_2\u003c/em\u003e were observed, and unique \u003cem\u003eButyrivibrio \u003c/em\u003ecould ferment multiple carbohydrates producing hydrogen and hydrogen sulfide. There was a significant correlation between \u003cem\u003eCoprococcus_2 \u003c/em\u003eand the severity of abdominal symptoms. Differently, The unique \u003cem\u003eVeillonella\u003c/em\u003e, \u003cem\u003eEscherichia-Shigella\u003c/em\u003e, \u003cem\u003eBarnesiella\u003c/em\u003e and \u003cem\u003eTyzzerella_3\u003c/em\u003e in PBT group were related to amino acid fermentation. Interestingly, the co-occurrence network density of PBT is the largest indicating a complicated interaction of genera. The Euclidean distance between paired networks using either the betweenness centrality or the degree distribution showed that PBT is closer to SIBO.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eIncreased taxonomic diversity and decreased functional diversity were consistent with the progression of SIBO. \u003cem\u003eButyrivibrio\u003c/em\u003e and \u003cem\u003eCoprococcus_2\u003c/em\u003e abundance along with lower \u003cem\u003eBacteroides\u003c/em\u003e contributed to more noticeable discomfort of SIBO patients. The enriched \u003cem\u003eCoprococcus\u003c/em\u003e may be one of the potential biomarkers of SIBO. Represented by \u003cem\u003eVeillonella\u003c/em\u003e, asymptomatic PBT objects exhibited a different microbiome spectrum associated with the fermentation of amino acids and peptides rather than carbohydrates. The network of PBT was more stable which may play a protective role, but it deserved further attention in view of the shared essential “bridged” genera with SIBO.\u003c/p\u003e","manuscriptTitle":"Fecal Coprococcus, Hidden behind Abdominal Symptoms in Patients with Small Intestinal Bacterial Overgrowth","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 15:17:46","doi":"10.21203/rs.3.rs-3823305/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2024-01-01T23:02:32+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-01T09:53:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-12-31T03:30:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2023-12-30T01:27:07+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67114ddc-8d5f-4f32-91fa-7e20034ce58d","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-05-21T10:09:15+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-03 15:17:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3823305","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3823305","identity":"rs-3823305","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}