Microbiota profile in new-onset pediatric Crohn's disease: data from a non-Western population

Persistent dysbiosis of duodenal microbiota in patients with controlled pediatric Crohn's disease after resolution of inflammation

Crohn's disease is an inflammatory condition of the intestine characterized by largely unknown etiology and a relapse remission cycle of disease control. While possible triggers have been identified, research is inconsistent on the precise cause of these relapses, especially in the under-researched pediatric population. We hypothesized that patients in remission would have persistent microbial and inflammatory changes in small intestinal tissue that might trigger relapse. To this end, we analyzed intestinal biopsy samples from six patients with pediatric Crohn's disease in remission and a control group of 16 pediatric patients with no evident pathogenic abnormality. We identified compositional microbiota differences, including decreases in the genera Streptococcus and Actinobacillus as well as increases in Oribacterium and Prevotella in patients with controlled Crohn's disease compared to controls. Further, a histologic analysis found that patients with controlled Crohn's disease had increased epithelial integrity, and decreased intraepithelial lymphocytes compared with controls. Additionally, we observed increased peripheral CD4+ T cells in patients with pediatric Crohn's disease. These results indicate that markers of intestinal inflammation are responsive to Crohn's disease treatment, however the interventions may not resolve the underlying dysbiosis. These findings suggest that persistent dysbiosis may increase vulnerability to relapse of pediatric Crohn's disease. This study used a nested cohort of patients from the Bangladesh Environmental Enteric Dysfunction (BEED) study (ClinicalTrials.gov ID: NCT02812615 Date of first registration: 24/06/2016).

Bacterial dysbiosis in newly diagnosed treatment naïve pediatric ulcerative colitis in Saudi Arabia

BACKGROUND

The role of microbiota in the pathogenesis of ulcerative colitis (UC) has been increasingly recognized. However, most of the reports are from Western populations. In Middle Eastern countries, including Saudi Arabia, little is known about the role of microbiota. Therefore, our aim was to describe the bacterial microbiota profile and signature in pediatric UC in Saudi Arabia.

METHODS

Twenty children with UC and 20 healthy controls enrolled in the study gave stool samples. Twenty rectal mucosal samples were taken from UC and 20 from non-UC controls. Inclusion criteria included newly diagnosed and untreated children and lack of antibiotic exposure for at least 6 months before stool collection was required for children with UC and controls. Bacterial deoxyribonucleic acid was extracted and sequenced using shotgun metagenomic analysis. Statistical analysis included Shannon alpha diversity metrics, Bray-Curtis dissimilarity, DESeq2, and biomarker discovery.

RESULTS

The demographic characteristics were similar in children with UC and controls. There was a significant reduction in alpha diversity (P = 0.037) and beta diversity in samples from children with UC (P = 0.001). Many taxa were identified with log2 abundance analysis, revealing 110 and 102 species significantly depleted and enriched in UC, respectively. Eleven bacterial species' signatures were identified.

CONCLUSIONS

In Saudi Arabian children with UC, we demonstrate a dysbiosis similar to reports from Western populations, possibly related to changes of lifestyle. Microbial signature discovery in this report is an important contribution to research, leading to the development of adjunctive non-invasive diagnostic options in unusual cases of UC.

Gut microbiota predicts the diagnosis of ulcerative colitis in Saudi children

BACKGROUND

Ulcerative colitis (UC) is an immune-mediated chronic inflammatory condition with a worldwide distribution. Although the etiology of this disease is still unknown, the understanding of the role of the microbiota is becoming increasingly strong.

AIM

To investigate the predictive power of the gut microbiota for the diagnosis of UC in a cohort of newly diagnosed treatment-naïve Saudi children with UC.

METHODS

The study population included 20 children with a confirmed diagnosis of UC and 20 healthy controls. Microbial DNA was extracted and sequenced, and shotgun metagenomic analysis was performed for bacteria and bacteriophages. Biostatistics and bioinformatics demonstrated significant dysbiosis in the form of reduced alpha diversity, beta diversity, and significant difference of abundance of taxa between children with UC and control groups. The receiver operating characteristic curve, a probability curve, was used to determine the difference between the UC and control groups. The area under the curve (AUC) represents the degree of separability between the UC group and the control group. The AUC was calculated for all identified bacterial species and for bacterial species identified by the random forest classification algorithm as important potential biomarkers of UC. A similar method of AUC calculation for all bacteriophages and important species was used.

RESULTS

The median age and range were 14 (0.5-21) and 12.9 (6.8-16.3) years for children with UC and controls, respectively, and 40% and 35% were male for children with UC and controls, respectively. The AUC for all identified bacterial species was 89.5%. However, when using the bacterial species identified as important by random forest classification algorithm analysis, the accuracy increased to 97.6%. Similarly, the AUC for all the identified bacteriophages was 87.4%, but this value increased to 94.5% when the important bacteriophage biomarkers were used.

CONCLUSION

The very high to excellent AUCs of fecal bacterial and viral species suggest the potential use of noninvasive microbiota-based tests for the diagnosis of unusual cases of UC in children. In addition, the identification of important bacteria and bacteriophages whose abundance is reduced in children with UC suggests the potential of preventive and adjuvant microbial therapy for UC.

ExpLOring the role of the intestinal MiCrobiome in InflammATory bowel disease-AssocIated SpONdylarthritis (LOCATION-IBD)

Background

Inflammatory Bowel Disease (IBD)-associated arthritis is a frequent and potentially debilitating complication of IBD, that can affect those with or without active intestinal disease, and is often difficult to treat. The microbiome is known to play a role in IBD development and has been shown to be associated with inflammatory arthritis without concomitant IBD, but its role in IBD-associated arthritis is still unexplored. Further, disease localization is associated with development of IBD-associated arthritis, and stool compositional profiles are predictive of disease localization, yet mucosal location-specific microbiomes have not been well characterized. To address this gap in understanding, we designed a study (LOCATION-IBD) to characterize the mucosa-associated intestinal microbiome and metabolome in IBD-associated arthritis.

Methods

Adults with an established diagnosis of IBD undergoing clinical colonoscopy between May of 2021 and February of 2023 were invited to participate in this study; those interested in participation who met inclusion criteria were enrolled. Prior to enrollment, participants were stratified into those with or without IBD-associated arthritis. All participants were interviewed and had clinical and demographic data collected, and 97.8% completed clinical colonoscopy with biopsy collection.

Results and conclusion

A total of 182 participants, 53 with confirmed IBD-associated arthritis, were enrolled in this study, resulting in 1151 biopsies obtained for microbiome and metabolome analysis (median 6, mean 6.3 per participant). Clinical and demographic data obtained from the study population will be analyzed with microbiome and metabolome data obtained from biopsies, with the goal of better understanding the mechanisms underpinning the host-microbiome relationship associated the development of IBD-associated arthritis.

Intravenous ferric carboxymaltose and ferric derisomaltose alter the intestinal microbiome in female iron-deficient anemic mice

Iron deficiency anemia (IDA) is a leading global health concern affecting approximately 30% of the population. Treatment for IDA consists of replenishment of iron stores, either by oral or intravenous (IV) supplementation. There is a complex bidirectional interplay between the gut microbiota, the host's iron status, and dietary iron availability. Dietary iron deficiency and supplementation can influence the gut microbiome; however, the effect of IV iron on the gut microbiome is unknown. We studied how commonly used IV iron preparations, ferric carboxymaltose (FCM) and ferric derisomaltose (FDI), affected the gut microbiome in female iron-deficient anemic mice. At the phylum level, vehicle-treated mice showed an expansion in Verrucomicrobia, mostly because of the increased abundance of Akkermansia muciniphila, along with contraction in Firmicutes, resulting in a lower Firmicutes/Bacteroidetes ratio (indicator of dysbiosis). Treatment with either FCM or FDI restored the microbiome such that Firmicutes and Bacteroidetes were the dominant phyla. Interestingly, the phyla Proteobacteria and several members of Bacteroidetes (e.g., Alistipes) were expanded in mice treated with FCM compared with those treated with FDI. In contrast, several Clostridia class members were expanded in mice treated with FDI compared with FCM (e.g., Dorea spp., Eubacterium). Our data demonstrate that IV iron increases gut microbiome diversity independently of the iron preparation used; however, differences exist between FCM and FDI treatments. In conclusion, replenishing iron stores with IV iron preparations in clinical conditions, such as inflammatory bowel disease or chronic kidney disease, could affect gut microbiome composition and consequently contribute to an altered disease outcome.

Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network

Background

Microbes have dense linkages with human diseases. Balanced microorganisms protect human body against physiological disorders while unbalanced ones may cause diseases. Thus, identification of potential associations between microbes and diseases can contribute to the diagnosis and therapy of various complex diseases. Biological experiments for microbe-disease association (MDA) prediction are expensive, time-consuming, and labor-intensive.

Methods

We developed a computational MDA prediction method called GPUDMDA by combining graph attention autoencoder, positive-unlabeled learning, and deep neural network. First, GPUDMDA computes disease similarity and microbe similarity matrices by integrating their functional similarity and Gaussian association profile kernel similarity, respectively. Next, it learns the feature representation of each microbe-disease pair using graph attention autoencoder based on the obtained disease similarity and microbe similarity matrices. Third, it selects a few reliable negative MDAs based on positive-unlabeled learning. Finally, it takes the learned MDA features and the selected negative MDAs as inputs and designed a deep neural network to predict potential MDAs.

Results

GPUDMDA was compared with four state-of-the-art MDA identification models (i.e., MNNMDA, GATMDA, LRLSHMDA, and NTSHMDA) on the HMDAD and Disbiome databases under five-fold cross validations on microbes, diseases, and microbe-disease pairs. Under the three five-fold cross validations, GPUDMDA computed the best AUCs of 0.7121, 0.9454, and 0.9501 on the HMDAD database and 0.8372, 0.8908, and 0.8948 on the Disbiome database, respectively, outperforming the other four MDA prediction methods. Asthma is the most common chronic respiratory condition and affects ~339 million people worldwide. Inflammatory bowel disease is a class of globally chronic intestinal disease widely existed in the gut and gastrointestinal tract and extraintestinal organs of patients. Particularly, inflammatory bowel disease severely affects the growth and development of children. We used the proposed GPUDMDA method and found that Enterobacter hormaechei had potential associations with both asthma and inflammatory bowel disease and need further biological experimental validation.

Conclusion

The proposed GPUDMDA demonstrated the powerful MDA prediction ability. We anticipate that GPUDMDA helps screen the therapeutic clues for microbe-related diseases.

Integration of taxa abundance and occurrence frequency to identify key gut bacteria correlated to clinics in Crohn's disease

Bacteria abundance alternation in the feces or mucosa of Crohn's disease (CD) patients has long been applied to identify potential biomarkers for this disease, while the taxa occurrence frequency and their correlations with clinical traits were understudied. A total of 97 samples from the feces and gut mucosa were collected from CD patients and healthy controls (HCs), 16S rRNA-based analyses were performed to determine the changes in taxa abundance and occurrence frequency along CD and to correlate them with clinical traits. The results showed that bacteria communities were divergent between feces and mucosa, while the taxa abundance and occurrence frequency in both partitions showed similar exponential correlations. The decrease of specific fecal bacteria was much more effective in classifying the CD and HCs than that of the mucosal bacteria. Among them, Christensenellaceae_R-7_group and Ruminococcus were predicted as biomarkers by using random forest algorithm, which were persistently presented (> 71.40% in frequency) in the feces of the HCs with high abundance, whereas transiently presented in the feces (< 5.5% in frequency) and mucosa (< 18.18% in frequency) of CD patients with low abundance. Co-occurrence network analysis then identified them as hub taxa that drive the alternations of other bacteria and were positively correlated to the circuiting monocytes. The loss of specific bacteria in the healthy gut may cause great disturbance of gut microbiota, causing gut bacteria dysbiosis and correlated to immune disorders along CD, which might not only be developed as effective noninvasive biomarkers but also as therapy targets.

Milk protein digestion and the gut microbiome influence gastrointestinal discomfort after cow milk consumption in healthy subjects

Many healthy people suffer from milk-related gastrointestinal discomfort (GID) despite not being lactose intolerant; the mechanisms underpinning such condition are unknown. This study aimed to explore milk protein digestion and related physiological responses (primary outcome), gut microbiome and gut permeability in 19 lactose-tolerant healthy nonhabitual milk consumers [NHMCs] reporting GID after consuming cow milk compared to 20 habitual milk consumers [HMCs] without GID. NHMCs and HMCs participated in a milk-load (250 mL) test, underwent blood sample collection at 6 time points over 6 h after milk consumption and collected urine samples and GID self-reports over 24 h. We measured the concentrations of 31 milk-derived bioactive peptides (BAPs), 20 amino acids, 4 hormones, 5 endocannabinoid system mediators, glucose and the dipeptidyl peptidase-IV (DPPIV) activity in blood and indoxyl sulfate in urine samples. Subjects also participated in a gut permeability test and delivered feces sample for gut microbiome analysis. Results showed that, compared to HMCs, milk consumption in NHMCs, along with GID, elicited a slower and lower increase in circulating BAPs, lower responses of ghrelin, insulin, and anandamide, a higher glucose response and serum DPPIV activity. The gut permeability of the two groups was similar, while the habitual diet, which was lower in dairy products and higher in the dietary-fibre-to-protein ratio in NHMCs, possibly shaped the gut microbiome; NHMCs exhibited lower abundance of Bifidobacteria, higher abundance of Prevotella and lower abundance of protease-coding genes, which may have reduced protein digestion, as evidenced by lower urinary excretion of indoxyl sulfate. In conclusion, the findings showed that a less efficient digestion of milk proteins, supported by a lower proteolytic capability of the gut microbiome, may explain GID in healthy people after milk consumption.

Identifying Microbiome Dynamics in Pediatric IBD: More than a Family Matter

BACKGROUND

Pediatric inflammatory bowel disease (IBD) is a chronic inflammatory intestinal disease that affects both children and adolescents. Symptoms can significantly affect a child's growth, development, and quality of life, making early diagnosis and effective management crucial. This study focuses on treatment-naïve pediatric IBD patients and their immediate families to identify the role of the microbiome in disease onset.

METHODS

Nine families with pediatric IBD were recruited, comprising seven drug-naïve Crohn's disease (CD) patients and two drug-naïve ulcerative colitis (UC) patients, as well as twenty-four healthy siblings/parents. Fecal samples were collected for 16S ribosomal RNA gene sequencing and bioinformatics analysis.

RESULTS

We identified patterns of dysbiosis and hallmark microbial taxa among patients who shared ethnic, habitual, and dietary traits with themselves and their families. In addition, we examined the impact of the disease on specific microbial taxa and how these could serve as potential biomarkers for early detection.

CONCLUSIONS

Our results suggest a potential role of maternal factors in the establishment and modulation of the early life microbiome, consistent with the current literature, which may have implications for understanding the etiology and progression of IBD.

SAELGMDA: Identifying human microbe-disease associations based on sparse autoencoder and LightGBM

Introduction

Identification of complex associations between diseases and microbes is important to understand the pathogenesis of diseases and design therapeutic strategies. Biomedical experiment-based Microbe-Disease Association (MDA) detection methods are expensive, time-consuming, and laborious.

Methods

Here, we developed a computational method called SAELGMDA for potential MDA prediction. First, microbe similarity and disease similarity are computed by integrating their functional similarity and Gaussian interaction profile kernel similarity. Second, one microbe-disease pair is presented as a feature vector by combining the microbe and disease similarity matrices. Next, the obtained feature vectors are mapped to a low-dimensional space based on a Sparse AutoEncoder. Finally, unknown microbe-disease pairs are classified based on Light Gradient boosting machine.

Results

The proposed SAELGMDA method was compared with four state-of-the-art MDA methods (MNNMDA, GATMDA, NTSHMDA, and LRLSHMDA) under five-fold cross validations on diseases, microbes, and microbe-disease pairs on the HMDAD and Disbiome databases. The results show that SAELGMDA computed the best accuracy, Matthews correlation coefficient, AUC, and AUPR under the majority of conditions, outperforming the other four MDA prediction models. In particular, SAELGMDA obtained the best AUCs of 0.8358 and 0.9301 under cross validation on diseases, 0.9838 and 0.9293 under cross validation on microbes, and 0.9857 and 0.9358 under cross validation on microbe-disease pairs on the HMDAD and Disbiome databases. Colorectal cancer, inflammatory bowel disease, and lung cancer are diseases that severely threat human health. We used the proposed SAELGMDA method to find possible microbes for the three diseases. The results demonstrate that there are potential associations between Clostridium coccoides and colorectal cancer and one between Sphingomonadaceae and inflammatory bowel disease. In addition, Veillonella may associate with autism. The inferred MDAs need further validation.

Conclusion

We anticipate that the proposed SAELGMDA method contributes to the identification of new MDAs.

KGNMDA: A Knowledge Graph Neural Network Method for Predicting Microbe-Disease Associations

Accumulated studies discovered that various microbes in human bodies were closely related to complex human diseases and could provide new insight into drug development. Multiple computational methods were constructed to predict microbes that were potentially associated with diseases. However, most previous methods were based on single characteristics of microbes or diseases, that lacked important biological information related to microorganisms or diseases. Therefore, we constructed a knowledge graph centered on microorganisms and diseases from several existed databases to provide knowledgeable information for microbes and diseases. Then, we adopted a graph neural network method to learn representations of microbes and diseases from the constructed knowledge graph. After that, we introduced the Gaussian kernel similarity features of microbes and diseases to generate final representations of microbes and diseases. At last, we proposed a score function on final representations of microbes and diseases to predict scores of microbe-disease associations. Comprehensive experiments on the Human Microbe-Disease Association Database (HMDAD) dataset had demonstrated that our approach outperformed baseline methods. Furthermore, we implemented case studies on two important diseases (asthma and inflammatory bowel disease), the result demonstrated that our proposed model was effective in revealing the relationship between diseases and microbes. The source code of our model and the data were available on https://github.com/ChangzhiJiang/KGNMDA_master.

The Therapeutic Role of Short-Chain Fatty Acids Mediated Very Low-Calorie Ketogenic Diet-Gut Microbiota Relationships in Paediatric Inflammatory Bowel Diseases

The very low-calorie ketogenic diet (VLCKD) has been recognized as a promising dietary regimen for the treatment of several diseases. Short-chain fatty acids (SCFAs) produced by anaerobic bacterial fermentation of indigestible dietary fibre in the gut have potential value for their underlying epigenetic role in the treatment of obesity and asthma-related inflammation through mediating the relationships between VLCKD and the infant gut microbiota. However, it is still unclear how VLCKD might influence gut microbiota composition in children, and how SCFAs could play a role in the treatment of inflammatory bowel disease (IBD). To overcome this knowledge gap, this review aims to investigate the role of SCFAs as key epigenetic metabolites that mediate VLCKD-gut microbiota relationships in children, and their therapeutic potential in IBD.

Targeted Analysis of the Gut Microbiome for Diagnosis, Prognosis and Treatment Individualization in Pediatric Inflammatory Bowel Disease

We explored the fecal microbiota in pediatric patients <18 years of age with treatment-naïve IBD (80 Crohn’s disease (CD), 27 ulcerative colitis (UC)), in 50 non-IBD patients with gastrointestinal symptoms without inflammation and in 75 healthy children. Using a targeted qPCR approach, the quantities of more than 100 different bacterial species were measured. Results: The bacterial abundance was statistically significantly reduced in the IBD and non-IBD patients compared to the healthy children for several beneficial species. The CD patients had a lower abundance of Bifidobacterium species compared to the UC patients, and the IBD patients in need of biologic therapy had a lower abundance of butyrate producing bacteria. Based on the abundance of bacterial species at diagnosis, we constructed Diagnostic, Phenotype and Prognostic Indexes. Patients with a high Diagnostic Index had 2.5 times higher odds for having IBD than those with a lower index. The CD patients had a higher Phenotype Index than the UC patients. Patients with a high Prognostic Index had 2.1 higher odds for needing biologic therapy compared to those with a lower index. Conclusions: The fecal abundance of bacterial species can aid in diagnosing IBD, in distinguishing CD from UC and in identifying children with IBD in need of biologic therapy.

Gut microbiota in mucosa and feces of newly diagnosed, treatment-naïve adult inflammatory bowel disease and irritable bowel syndrome patients

The knowledge on how gut microbes contribute to the inflammatory bowel disease (IBD) at the onset of disease is still scarce. We compared gut microbiota in newly diagnosed, treatment-naïve adult IBD (Crohn's disease (CD) and ulcerative colitis (UC)) to irritable bowel syndrome (IBS) patients and healthy group. Mucosal and fecal microbiota of 49 patients (13 UC, 10 CD, and 26 IBS) before treatment initiation, and fecal microbiota of 12 healthy subjects was characterized by 16S rRNA gene sequencing. Mucosa was sampled at six positions, from terminal ileum to rectum. We demonstrate that mucosal microbiota is spatially homogeneous, cannot be differentiated based on the local inflammation status and yet provides bacterial footprints superior to fecal in discriminating disease phenotypes. IBD groups showed decreased bacterial diversity in mucosa at all taxonomic levels compared to IBS. In CD and UC, Dialister was significantly increased, and expansion of Haemophilus and Propionibacterium characterized UC. Compared to healthy individuals, fecal microbiota of IBD and IBS patients had increased abundance of Proteobacteria, Enterobacteriaceae, in particular. Shift toward reduction of Adlercreutzia and butyrate-producing taxa was found in feces of IBD patients. Microbiota alterations detected in newly diagnosed treatment-naïve adult patients indicate that the microbiota changes are set and detectable at the disease onset and likely have a discerning role in IBD pathophysiology. Our results justify further investigation of the taxa discriminating between disease groups, such as H. parainfluenzae, R. gnavus, Turicibacteriaceae, Dialister, and Adlercreutzia as potential biomarkers of the disease.

Multiomic Analysis of the Gut Microbiome in Psoriasis Reveals Distinct Host‒Microbe Associations

Psoriasis is a chronic, inflammatory skin disease that affects 2‒3% of the global population. Besides skin manifestations, patients with psoriasis have increased susceptibility to a number of comorbidities, including psoriatic arthritis, cardiovascular disease, and inflammatory bowel disease. To understand the systemic component of psoriasis pathogenesis, we performed a pilot study to examine the fecal metagenome, host colonic transcriptome, and host peripheral blood immune profiles of patients with psoriasis and healthy controls. Our study showed increased functional diversity in the gut microbiome of patients with psoriasis. In addition, we identified microbial species that preferentially associate with patients with psoriasis and which have been previously found to associate with other autoimmune diseases. Intriguingly, our data revealed three psoriasis subgroups that have distinct microbial and host features. Integrating these features revealed host‒microbe associations that are specific to psoriasis or particular psoriasis subgroups. Our findings provide insight into the factors that may affect the development of comorbidities in patients with psoriasis and may hold diagnostic potential for early identification of patients with psoriasis at risk for these comorbidities.

Lactiplantibacillus plantarum Reduced Renal Calcium Oxalate Stones by Regulating Arginine Metabolism in Gut Microbiota

Renal calcium oxalate (CaOx) stones are a common kidney disease. There are few methods for reducing the formation of these stones. However, the potential of probiotics for reducing renal stones has received increasing interest. We previously isolated a strain of Lactiplantibacillus plantarum N-1 from traditional cheese in China. This study aimed to investigate the effects of N-1 on renal CaOx crystal deposition. Thirty rats were randomly allocated to three groups: control group (ddH2O by gavage), model group [ddH2O by gavage and 1% ethylene glycol (EG) in drinking water], and Lactiplantibacillus group (N-1 by gavage and 1% EG in drinking water). After 4 weeks, compared with the model group, the group treated with N-1 exhibited significantly reduced renal crystals (P < 0.05). In the ileum and caecum, the relative abundances of Lactobacillus and Eubacterium ventriosum were higher in the control group, and those of Ruminococcaceae UCG 007 and Rikenellaceae RC9 were higher in the N-1-supplemented group. In contrast, the relative abundances of Staphylococcus, Corynebacterium 1, Jeotgalicoccus, Psychrobacter, and Aerococcus were higher in the model group. We also predicted that the arginase level would be higher in the ileal microbiota of the model group than in the N-1-supplemented group with PICRUSt2. The arginase activity was higher, while the level of arginine was lower in the ileal contents of the model group than in the N-1-supplemented group. The arginine level in the blood was also higher in the N-1-supplemented group than in the model group. In vitro studies showed that exposure to arginine could reduce CaOx crystal adhesion to renal epithelial HK-2 cells. Our findings highlighted the important role of N-1 in reducing renal CaOx crystals by regulating arginine metabolism in the gut microbiota. Probiotics containing L. plantarum N-1 may be potential therapies for preventing renal CaOx stones.

HLA Class II Polymorphisms Modulate Gut Microbiota and Experimental Autoimmune Encephalomyelitis Phenotype

Multiple sclerosis (MS) is an autoimmune disease of the CNS in which the interaction between genetic and environmental factors plays an important role in disease pathogenesis. Although environmental factors account for 70% of disease risk, the exact environmental factors associated with MS are unknown. Recently, gut microbiota has emerged as a potential missing environmental factor linked with the pathobiology of MS. Yet, how genetic factors, such as HLA class II gene(s), interact with gut microbiota and influence MS is unclear. In the current study, we investigated whether HLA class II genes that regulate experimental autoimmune encephalomyelitis (EAE) and MS susceptibility also influence gut microbiota. Previously, we have shown that HLA-DR3 transgenic mice lacking endogenous mouse class II genes (AE-KO) were susceptible to myelin proteolipid protein (91-110)-induced EAE, an animal model of MS, whereas AE-KO.HLA-DQ8 transgenic mice were resistant. Surprisingly, HLA-DR3.DQ8 double transgenic mice showed higher disease prevalence and severity compared with HLA-DR3 mice. Gut microbiota analysis showed that HLA-DR3, HLA-DQ8, and HLA-DR3.DQ8 double transgenic mice microbiota are compositionally different from AE-KO mice. Within HLA class II transgenic mice, the microbiota of HLA-DQ8 mice were more similar to HLA-DR3.DQ8 than HLA-DR3. As the presence of DQ8 on an HLA-DR3 background increases disease severity, our data suggests that HLA-DQ8-specific microbiota may contribute to disease severity in HLA-DR3.DQ8 mice. Altogether, our study provides evidence that the HLA-DR and -DQ genes linked to specific gut microbiota contribute to EAE susceptibility or resistance in a transgenic animal model of MS.

Rank normalization empowers a t-test for microbiome differential abundance analysis while controlling for false discoveries

A major task in the analysis of microbiome data is to identify microbes associated with differing biological conditions. Before conducting analysis, raw data must first be adjusted so that counts from different samples are comparable. A typical approach is to estimate normalization factors by which all counts in a sample are multiplied or divided. However, the inherent variation associated with estimation of normalization factors are often not accounted for in subsequent analysis, leading to a loss of precision. Rank normalization is a nonparametric alternative to the estimation of normalization factors in which each count for a microbial feature is replaced by its intrasample rank. Although rank normalization has been successfully applied to microarray analysis in the past, it has yet to be explored for microbiome data, which is characterized by high frequencies of 0s, strongly correlated features and compositionality. We propose to use rank normalization as an alternative to the estimation of normalization factors and examine its performance when paired with a two-sample t-test. On a rigorous 3rd-party benchmarking simulation, it is shown to offer strong control over the false discovery rate, and at sample sizes greater than 50 per treatment group, to offer an improvement in performance over commonly used normalization factors paired with t-tests, Wilcoxon rank-sum tests and methodologies implemented by R packages. On two real datasets, it yielded valid and reproducible results that were strongly in agreement with the original findings and the existing literature, further demonstrating its robustness and future potential. Availability: The data underlying this article are available online along with R code and supplementary materials at https://github.com/matthewlouisdavisBioStat/Rank-Normalization-Empowers-a-T-Test.

Short communication: Comparison of the fecal bacterial communities in diarrheic and nondiarrheic dairy calves from multiple farms in southeastern Pennsylvania

Diarrhea is a major cause of illness and death in preweaned calves and causes significant economic losses to producers. A better understanding of the fecal microbiota in diarrheic and nondiarrheic calves could lead to improved treatment and prevention strategies. The purpose of this study was to compare the fecal microbiota of diarrheic and nondiarrheic calves to improve our understanding of what constitutes a healthy fecal microbiota in preweaned calves. At each of 7 farms, fecal samples were obtained from 1 to 3 diarrheic Holstein dairy calves (2 to 17 d old at sampling time) and age-matched (within 5 d) nondiarrheic controls for a total of 20 samples. Calves were fed either acidified bulk milk, pasteurized or unpasteurized waste milk, or milk replacer depending on farm. Fecal samples were extracted for genomic DNA, PCR-amplified for the V1-V2 region of the 16S rRNA bacterial gene, sequenced on the Illumina MiSeq (Illumina Inc., San Diego, CA) platform, and analyzed using QIIME2. Firmicutes and Bacteroidetes were the most abundant phyla in both groups; Fusobacteria was numerically more abundant in the diarrheic group, whereas Proteobacteria and Actinobacteria were numerically more abundant in the nondiarrheic group. At the genus level, Bacteroides was the most abundant genus in both groups and was numerically more abundant in the nondiarrheic group. Results from the mixed-effects regression model showed that Faecalibacterium and Butyricimonas were more abundant in the nondiarrheic calves, whereas Clostridium and Peptostreptococcus were more abundant in the diarrheic calves. Our results indicate that commensal bacteria acquired in the neonatal period may have been replaced with potential pathogens in diarrheic calves, which may have contributed to the incidence of diarrhea either directly or indirectly.

Dysbiosis in Metabolic Genes of the Gut Microbiomes of Patients with an Ileo-anal Pouch Resembles That Observed in Crohn's Disease

Crohn's disease (CD), ulcerative colitis (UC), and pouchitis are multifactorial and chronic inflammatory bowel diseases (IBD). Pouchitis develops in former UC patients after proctocolectomy and ileal-pouch-anal anastomosis and is characterized by inflammation of the previously normal small intestine comprising the pouch. The extent to which microbial functional alteration (dysbiosis) in pouchitis resembles that of CD or UC has not been investigated, and the pathogenesis of pouchitis remains unknown. We collected 208 fecal metagenomes from 69 patients with a pouch (normal pouch and pouchitis) and compared them to publicly available metagenomes of patients with CD (n = 88), patients with UC (n = 76), and healthy controls (n = 56). Patients with pouchitis presented the highest alterations in species, metabolic pathways, and enzymes, which was correlated with intestinal inflammation. Ruminococcus gnavus strains encoding mucin-degrading glycoside hydrolases were highly enriched in pouchitis. Butyrate and secondary bile acid biosynthesis pathways were decreased in IBD phenotypes and were especially low in pouchitis. Pathways such as amino acid biosynthesis and degradation of aromatic compounds and sugars, encoded by members of the Enterobacteriaceae, were enriched in pouch and CD but not in UC. We developed microbial feature-based classifiers that can distinguish between patients with a normal pouch and pouchitis and identified species and genes that were predictive of pouchitis. We propose that the noninflamed pouch is already dysbiotic and microbially is similar to CD. Our study reveals microbial functions that outline the pathogenesis of pouchitis and suggests bacterial groups and functions that could be targeted for intervention to attenuate small intestinal inflammation present in pouchitis and CD.

IMPORTANCE Crohn's disease (CD), ulcerative colitis (UC), and pouchitis are chronic inflammatory conditions of the bowel. Pouchitis develops in former UC patients after proctocolectomy and ileal-pouch-anal anastomosis and is characterized by inflammation of the previously normal small intestine comprising the pouch. The extent to which microbial dysbiosis in patients with pouchitis resembles that of CD or UC and the pathogenesis of pouchitis remains unclear. We investigated the functions in the gut microbiomes of these patients using metagenomics. We found that the noninflamed pouch is already dysbiotic and microbially is similar to CD. Our study reveals microbial functions with a potential role in pouchitis pathogenesis such as depletion in butyrate and secondary bile acid synthesis and enrichment of amino acid synthesis and degradation of aromatic compounds, encoded by members of the Enterobacteriaceae. We developed microbial feature-based classifiers that can distinguish between patients with a normal pouch and pouchitis and identified species and genes that were predictive of pouchitis. We suggest species and functions that could be targeted for intervention to attenuate small intestinal inflammation present in pouchitis and CD.

Bacterial dysbiosis predicts the diagnosis of Crohn's disease in Saudi children

BACKGROUND

Studies have reached different conclusions regarding the accuracy of dysbiosis in predicting the diagnosis of Crohn's disease (CD). The aim of this report is to assess the utility of mucosal and fecal microbial dysbiosis as predictors in the diagnosis of this condition in Saudi children.

METHODS

Tissue and fecal samples were collected prospectively from children with final diagnosis of CD and from controls. Bacterial DNA was extracted and sequenced using Illumina MiSeq chemistry. The abundance and diversity of bacteria in tissue and fecal samples were determined in relation to controls. Sparse logistic regression was calculated to predict the diagnosis of CD based on subject's microbiota profile.

RESULTS

There were 17 children with CD and 18 controls. All children were Saudis. The median age was 13.9 and 16.3 years for children with CD and controls respectively. Sex distribution showed that 11/17 (65%) of the CD and 12/18 (67%) of the control subjects were boys. The mean area under the curve (AUC) was significantly higher in stool (AUC = 0.97 ± 0.029) than in tissue samples (AUC = 0.83 ±0.055) (P < 0.001).

CONCLUSIONS

We found high AUC in mucosal and fecal samples. The higher AUC for fecal samples suggests higher accuracy in predicting the diagnosis of CD.

Prevention and Alleviation of Dextran Sulfate Sodium Salt-Induced Inflammatory Bowel Disease in Mice With Bacillus subtilis-Fermented Milk via Inhibition of the Inflammatory Responses and Regulation of the Intestinal Flora

The pathogenesis of inflammatory bowel disease (IBD) might be related to the local inflammatory damage and the dysbacteriosis of intestinal flora. Probiotics can regulate the intestinal flora and ameliorate IBD. The probiotic Bacillus subtilis strain B. subtilis JNFE0126 was used as the starter of fermented milk. However, the therapeutic effects of B. subtilis-fermented milk on IBD remain to be explored. In this research, the therapeutic effect of B. subtilis-fermented milk on dextran sulfate sodium salt (DSS)-induced IBD mouse model was evaluated. Besides, the expression of pro-inflammatory/anti-inflammatory cytokines, the proliferation of the intestinal stem cells, and the reconstruction of the mucosa barrier were investigated. Finally, alteration of the gut microbiota was investigated by taxonomic analysis. As shown by the results, the disease activity index (DAI) of IBD was significantly decreased through oral administration of B. subtilis (JNFE0126)-fermented milk, and intestinal mucosa injury was attenuated. Moreover, B. subtilis could reduce the inflammatory response of the intestinal mucosa, induce proliferation of the intestinal stem cell, and promote reconstruction of the mucosal barrier. Furthermore, B. subtilis could rebalance the intestinal flora, increasing the abundance of Bacillus, Alistipes, and Lactobacillus while decreasing the abundance of Escherichia and Bacteroides. In conclusion, oral administration of the B. subtilis-fermented milk could alleviate DSS-induced IBD via inhibition of inflammatory response, promotion of the mucosal barrier reconstruction, and regulation of the intestinal flora.

Gut Microbiota Profile in Pediatric Patients With Inflammatory Bowel Disease: A Systematic Review

Background and Aim: Accumulating evidence have implicated gut microbiota alterations in pediatric and adult patients with inflammatory bowel disease (IBD); however, the results of different studies are often inconsistent and even contradictory. It is believed that early changes in new-onset and treatment-naïve pediatric patients are more informative. We performed a systematic review to investigate the gut microbiota profiles in pediatric IBD and identify specific microbiota biomarkers associated with this disorder. Methods: Electronic databases were searched from inception to 31 July 2020 for studies that observed gut microbiota alterations in pediatric patients with IBD. Study quality was assessed using the Newcastle-Ottawa scale. Results: A total of 41 original studies investigating gut microbiota profiles in pediatric patients with IBD were included in this review. Several studies have reported a decrease in α-diversity and an overall difference in β-diversity. Although no specific gut microbiota alterations were consistently reported, a gain in Enterococcus and a significant decrease in Anaerostipes, Blautia, Coprococcus, Faecalibacterium, Roseburia, Ruminococcus, and Lachnospira were found in the majority of the included articles. Moreover, there is insufficient data to show specific microbiota bacteria associated with disease activity, location, and behavior in pediatric IBD. Conclusions: This systematic review identified evidence for differences in the abundance of some bacteria in pediatric patients with IBD when compared to patients without IBD; however, no clear overall conclusion could be drawn from the included studies due to inconsistent results and heterogeneous methodologies. Further studies with large samples that follow more rigorous and standardized methodologies are needed.

Bacterial Mucosa-associated Microbiome in Inflamed and Proximal Noninflamed Ileum of Patients With Crohn's Disease

BACKGROUND

Microbiota is most likely essential in the pathogenesis of Crohn's disease (CD). Fecal diversion after ileocecal resection (ICR) protects against CD recurrence, whereas infusion of fecal content triggers inflammation. After ICR, the majority of patients experience endoscopic recurrence in the neoterminal ileum, and the ileal microbiome is of particular interest. We have assessed the mucosa-associated microbiome in the inflamed and noninflamed ileum in patients with CD.

METHODS

Mucosa-associated microbiome was assessed by 16S rRNA sequencing of biopsies sampled 5 and 15 cm orally of the ileocecal valve or ileocolic anastomosis.

RESULTS

Fifty-one CD patients and forty healthy controls (HCs) were included in the study. Twenty CD patients had terminal ileitis, with endoscopic inflammation at 5 cm, normal mucosa at 15 cm, and no history of upper CD involvement. Crohn's disease patients (n = 51) had lower alpha diversity and separated clearly from HC on beta diversity plots. Twenty-three bacterial taxa were differentially represented in CD patients vs HC; among these, Tyzzerella 4 was profoundly overrepresented in CD. The microbiome in the inflamed and proximal noninflamed ileal mucosa did not differ according to alpha diversity or beta diversity. Additionally, no bacterial taxa were differentially represented.

CONCLUSIONS

The microbiome is similar in the inflamed and proximal noninflamed ileal mucosa within the same patients. Our results support the concept of CD-specific microbiota alterations and demonstrate that neither ileal sublocation nor endoscopic inflammation influence the mucosa-associated microbiome.

Gut microbes from the phylogenetically diverse genus Eubacterium and their various contributions to gut health

Over the last two decades our understanding of the gut microbiota and its contribution to health and disease has been transformed. Among a new 'generation' of potentially beneficial microbes to have been recognized are members of the genus Eubacterium, who form a part of the core human gut microbiome. The genus consists of phylogenetically, and quite frequently phenotypically, diverse species, making Eubacterium a taxonomically unique and challenging genus. Several members of the genus produce butyrate, which plays a critical role in energy homeostasis, colonic motility, immunomodulation and suppression of inflammation in the gut. Eubacterium spp. also carry out bile acid and cholesterol transformations in the gut, thereby contributing to their homeostasis. Gut dysbiosis and a consequently modified representation of Eubacterium spp. in the gut, have been linked with various human disease states. This review provides an overview of Eubacterium species from a phylogenetic perspective, describes how they alter with diet and age and summarizes its association with the human gut and various health conditions.

Bacterial Taxa and Functions Are Predictive of Sustained Remission Following Exclusive Enteral Nutrition in Pediatric Crohn's Disease

BACKGROUND

The gut microbiome is extensively involved in induction of remission in pediatric Crohn's disease (CD) patients by exclusive enteral nutrition (EEN). In this follow-up study of pediatric CD patients undergoing treatment with EEN, we employ machine learning models trained on baseline gut microbiome data to distinguish patients who achieved and sustained remission (SR) from those who did not achieve remission nor relapse (non-SR) by 24 weeks.

METHODS

A total of 139 fecal samples were obtained from 22 patients (8-15 years of age) for up to 96 weeks. Gut microbiome taxonomy was assessed by 16S rRNA gene sequencing, and functional capacity was assessed by metagenomic sequencing. We used standard metrics of diversity and taxonomy to quantify differences between SR and non-SR patients and to associate gut microbial shifts with fecal calprotectin (FCP), and disease severity as defined by weighted Pediatric Crohn's Disease Activity Index. We used microbial data sets in addition to clinical metadata in random forests (RFs) models to classify treatment response and predict FCP levels.

RESULTS

Microbial diversity did not change after EEN, but species richness was lower in low-FCP samples (<250 µg/g). An RF model using microbial abundances, species richness, and Paris disease classification was the best at classifying treatment response (area under the curve [AUC] = 0.9). KEGG Pathways also significantly classified treatment response with the addition of the same clinical data (AUC = 0.8). Top features of the RF model are consistent with previously identified IBD taxa, such as Ruminococcaceae and Ruminococcus gnavus.

CONCLUSIONS

Our machine learning approach is able to distinguish SR and non-SR samples using baseline microbiome and clinical data.

History of Inflammatory Bowel Disease and Self-Reported Oral Health: Women's Health Initiative Observational Study

Background and Objective: Both periodontal disease and inflammatory bowel disease (IBD), are chronic inflammatory conditions, which are mediated by a complex interplay among a dysbiotic microbiota, dysregulated host immune-inflammatory responses, and lifestyle factors. Despite substantial differences in physical and chemical environments, rather strong correlations have been detected between microbial compositions of the oral cavity and stool. In this study, we tested the hypothesis that oral health conditions are affected by the presence of IBD. Materials and Methods: We analyzed the data from 73,621 women who were enrolled in the Women's Health Initiative observational cohort study and completed a follow-up questionnaire that surveyed oral health status specifically at year 5. Among these, 880 reported IBD at the baseline, including 47% who were symptomatic cases and 27% who were on immunosuppressive treatment. We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association of IBD and medication status for self-reported oral health outcomes, using logistic regression models, adjusted for selected covariates. Results: IBD was not associated with periodontal disease history itself in a multivariable model; however, poorer self-rated oral health was modestly associated with the presence of IBD (OR = 1.15, 95% CI: 1.01-1.30). Likewise, more frequent eating limitations due to teeth were associated with the presence of IBD history (OR = 1.22, 95% CI: 1.07-1.39). When IBD cases were limited to those who were symptomatic, the associations with these two self-rated oral health outcomes were more pronounced with ORs of 1.28 (95% CI: 1.07-1.54) and 1.36 (95% CI: 1.07-1.54), respectively. Immunosuppressive treatment had little effect on these risk estimates. Conclusions: Among this nation-wide cohort of women 50-79 years of age, history of IBD was associated with poorer perceived oral health status.

Gut Microbiome-Based Diagnostic Model to Predict Coronary Artery Disease

In the present study, we aimed to characterize gut microbiome and develop a gut microbiome-based diagnostic model in patients with coronary artery disease (CAD). Prospectively, we collected 309 fecal samples from Central China and Northwest China and carried out the sequencing of the V3-V4 regions of the 16S rRNA gene. The gut microbiome was characterized, and microbial biomarkers were identified in 152 CAD patients and 105 healthy controls (Xinjiang cohort, n = 257). Using the biomarkers, we constructed a diagnostic model and validated it externally in 34 CAD patients and 18 healthy controls (Zhengzhou cohort, n = 52). Fecal microbial diversity was increased in CAD patients compared to that in healthy controls (P = 0.021). Phylum Bacteroidetes was increased in CAD patients versus healthy controls (P = 0.001). Correspondingly, 48 microbial markers were identified through a 10-fold cross-validation on a random forest model, and an area under the curve (AUC) of 87.7% (95% CI: 0.832 to 0.916, P < 0.001) was achieved in the Xinjiang cohort (development cohort, n = 257). Notably, an AUC of 90.4% (95% CI: 0.848 to 0.928, P < 0.001) was achieved using combined analysis of gut microbial markers and clinical variables. This model provided a robust tool for the prediction of CAD. It could be widely employed to complement the clinical assessment and prevention of CAD.

The influence of blood on the human gut microbiome

BACKGROUND

Colorectal cancer (CRC) is one of the prevailing causes of cancer mortality in the world. A common screening test for CRC is based on the human hemoglobin immunochemical based fecal occult blood test (iFOBT), which consists in the detection of blood in the patient's stool. In addition to iFOBT, recent studies support the use of the gut microbiome as a biomarker for CRC prediction. However, these studies did not take into account the effect of blood itself on the microbiome composition, independently of CRC. Therefore, we investigated the microbiome of patients undergoing the iFOBT screening in order to determine the effect of blood alone. Our cohort consisted of patients who had no blood in their stools (n = 265) or did have blood but no underlying precancerous or cancerous lesions (n = 235). We also identified bacterial taxa specifically associated with the presence of blood in stools.

RESULTS

We observed significant differences in the intestinal bacterial composition that could be solely caused by the presence of blood in stools. More precisely, we identified 12 bacterial species showing significant differences in abundance between both our study groups. These species, Bacteroides uniformis, Collinsella aerofaciens, Eggerthella lenta and Clostridium symbiosum demonstrated increased abundance in the presence of blood. In contrast, the species Prevotella copri, Coprococcus eutactus and catus, Faecalibacterium prausnitzii, Roseburia faecis, Blautia obeum, Gemmiger formicilis and Clostridium celatum showed decreased abundance in patients with blood in their stools. Notably, we found multiple taxa that were reported in previous studies linking microbiome composition and diseases.

CONCLUSIONS

We show that, in the absence of disease, blood in the stools has a major influence on the composition of the microbiome. Our data suggest that blood itself should be taken into consideration when investigating the microbiome signatures of intestinal diseases.

Some Gammaproteobacteria are enriched within CD14+ macrophages from intestinal lamina propria of Crohn's disease patients versus mucus

Crohn's disease causes chronic inflammation in the gastrointestinal tract and its pathogenesis remains unclear. In the intestine of Crohn's disease patients, CD14⁺CD11⁺CD163^low macrophages contribute to inflammation through the induction of Th17 cells and production of inflammatory cytokines; the CD14⁺CD11c⁺163^high fraction is anti-inflammatory through the production of IL-10 in normal cases. In this report, the 16S rRNA gene amplicon sequencing method was used to identify bacteria that are specifically present in intestinal CD14⁺CD11c⁺ macrophages of Crohn's disease patients. Bacteria present in intestinal CD14⁺CD11c⁺ macrophages and mucus of Crohn's disease patients were separated into different clusters in principal coordinates analysis. There was a statistically significant increase in the relative composition of CD14⁺CD11c⁺ macrophages from mucus in two phyla (Proteobacteria [p = 0.01] and Actinobacteria [p = 0.02]) and two families (Moraxellaceae [p < 0.001] and Pseudomonadaceae [p = 0.01]). In addition, OTU-1: Acinetobacter and OTU-8: Pseudomonadaceae tended to concentrate in the CD14⁺CD11c⁺CD163^low subset, whereas OTU-10: Proteus, OTU-15: Collinsella tended to concentrate more in the CD14⁺CD11c⁺CD163^high subset than the other subset and mucus.

Development of an Index Score for Intestinal Inflammation-Associated Dysbiosis Using Real-World Stool Test Results

BACKGROUND

Gut microbiota play an important role in human health. However, the application of gut microbiome in regular clinical practice is limited by interindividual variations and complexity of test results.

HYPOTHESIS

It is possible to address interindividual variation by using large data-based exploratory-pattern analysis.

METHODS

The current study was conducted using a large data set (n = 173,221) of nonselective incoming patients' test results from a stool test. The data set included assays for the detection of 24 selected commensal microorganisms and multiple biomarkers in feces. Patients were grouped based on their levels of inflammation biomarkers such as calprotectin, eosinophil protein X, and IgA. Group mean values of biomarkers and commensal microbes were used in an exploratory-pattern analysis for association from which an index score for intestinal inflammation-associated dysbiosis (IAD) was developed. The IAD score was evaluated in one questionnaire-based study (n = 7263) and one prospective case series study (n = 122) with patients of inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), and celiac disease.

RESULTS

We identified a microbial profile strongly associated with fecal inflammation biomarkers. Developed on the pattern of the microbial profile, the IAD score demonstrated a strong association with fecal inflammation biomarkers and was significantly different between patients with IBD and those with IBS or celiac disease.

CONCLUSION

Using real-world data, we have developed a method to predict gut dysbiosis associated with different GI disease conditions. It may help clinicians simplify the process of interpreting gut microbial status and provide gut health assessment and treatment evaluation.

Synthetic Methane-Consuming Communities from a Natural Lake Sediment

The metabolism of methane is an important part of the global carbon cycle. While deciphering the community function and the potential role of the different functional guilds is very difficult when considering native complex communities, synthetic communities, built of species originating from a study site in question, present a simplified model and allow specific questions to be addressed as to carbon, nitrogen, and other nutrient transfer among species in a controlled system. This study applies an ecophysiological approach, as a proof of principle, to an already well-studied model system, contributing to a better understanding of microbial community function and microbial ecosystem processes.

The factors and processes that influence the behavior and functionality of ecosystems inhabited by complex microbiomes are still far from being clearly understood. Synthetic microbial communities provide reduced-complexity models that allow an examination of ecological theories under defined and controlled conditions. In this study, we applied a multiphasic approach to study synthetic methane-oxidizing communities and species interactions as proxies to the natural communities. Our results confirm that, under selective pressures, natural-sediment communities of high complexity simplify rapidly, selecting for several major functional guilds, the major partners in methane oxidation being the Methylococcaceae methanotrophs and the Methylophilaceae methylotrophs, along with minor but persistent partners, members of Burkholderiales and Flavobacteriales. As a proof of concept, we established minimalist synthetic communities that were representative of the four functional guilds to demonstrate the dependency of the non-methane-utilizing species on the methanotrophs as the primary carbon-providing species. We observed that in communities consisting of multiple representatives of the key guilds, members of the same guild appeared to compete for resources. For example, when two methanotrophs of the same family were present, the two expressed similar key methanotrophy pathways and responded similarly to changing environmental conditions, suggesting that they perform a similar keystone function in situ. Similar observations were made for the Methylophilaceae. However, differences were noted in the expression of auxiliary and unique genes among strains of the same functional guild, reflecting differential adaptation and suggesting mechanisms for competition. At the same time, differences were also noted in the performances of partners with specific metabolic schemes. For example, a mutant of Methylotenera mobilis impaired in nitrate utilization behaved as a more efficient cooperator in methane consumption, suggesting that the loss of function may lead to changes in communal behavior. Overall, we demonstrate the robust nature of synthetic communities built of native lake sediment strains and their utility in addressing important ecological questions while using a simplified model.