16S rRNA and metagenomic shotgun sequencing data revealed consistent patterns of gut microbiome signature in pediatric ulcerative colitis

Diagnostic values of CD27, CD20 and MPO in pediatric ulcerative colitis

Inflammatory bowel disease (IBD), including ulcerative colitis (UC), is a chronic inflammatory disorder with a rising incidence in pediatric populations. Immune factors play important roles in the pathogenesis of UC. This study aimed to explore the relationships of intestinal immune molecules CD27, CD20 and myeloperoxidase (MPO) with pediatric UC and their diagnostic values. In this study, gene expression data of 206 new-onset UC children and 20 non-IBD controls obtained from the NCBI Gene Expression Omnibus public database and immunohistochemistry analysis were used to evaluate CD27, CD20 and MPO expression in diseased intestinal tissues of UC children. And the diagnostic potentials of them for UC were analyzed using receiver operating characteristic curve and area under the curve (AUC). We found that CD27, CD20 and MPO mRNA and protein expressions were increased in the diseased intestinal tissues of UC children. CD27, CD20 and MPO showed good diagnostic potential for UC in children, with an AUC of 0.95 for CD27, 0.79 for CD20 and 0.92 for MPO, and combination of them had better diagnostic performance with an AUC of 0.98. Besides, they were associated with immune-related biological processes and pathways, and correlated with genes related to immune factors, intestinal epithelial barrier function, and intestinal fibrosis. In conclusion, our findings demonstrated that CD27, CD20 and MPO were increased in diseased intestinal tissues of UC children, and had good diagnostic performance for UC in children.

Multimodal metagenomic analysis reveals microbial InDels as superior biomarkers for pediatric Crohn's disease

BACKGROUND AND AIMS

The gut microbiome is closely associated with pediatric Crohn's disease (CD), while the multidimensional microbial signature and their capabilities for distinguishing pediatric CD are underexplored. This study aims to characterize the microbial alterations in pediatric CD and develop a robust classification model.

METHODS

A total of 1175 fecal metagenomic sequencing samples, predominantly from 3 cohorts of pediatric CD patients, were re-analyzed from raw sequencing data using uniform process pipelines to obtain multidimensional microbial alterations in pediatric CD, including taxonomic profiles, functional profiles, and multi-type genetic variants. Random forest algorithms were used to construct classification models after comparing multiple machine learning algorithms.

RESULTS

We found pediatric CD samples exhibited reduced microbial diversity and unique microbial characteristics. Pronounced abundance differences in 45 species and 1357 KEGG orthology genes. Particularly, Enterocloster bolteae emerged as a pivotal pediatric CD-associated species. Additionally, we identified a vast amount of microbial genetic variants linked to pediatric CD, including 192 structural variants, 1256 insertions/deletions (InDels), and 3567 single nucleotide variants, with a considerable portion of these variants located in non-genic regions. The InDel-based model outperformed other predictive models against multidimensional microbial signatures, achieving an area under the ROC curve (AUC) of 0.982. The robustness and disease specificity were further confirmed in an independent CD cohort (AUC = 0.996) and 5 other microbiome-associated pediatric cohorts.

CONCLUSIONS

Our study provided a comprehensive landscape of microbial alterations in pediatric CD and introduced a highly effective diagnostic model rooted in microbial InDels, which contributes to the development of noninvasive diagnostic tools and targeted therapies.

Culture-based characterization of gut microbiota in inflammatory bowel disease

Inflammatory bowel disease (IBD) is characterized by disruptions in the gut microbiome. While most studies on gut dysbiosis in IBD rely on sequencing-based methods, we employed a streamlined culturomics approach to obtain a more comprehensive understanding of gut microbiota imbalance in patients with IBD that may not be captured by sequencing alone. A total of 367 bacteria were identified at the species level, including 211 species from ulcerative colitis patients, 164 species from Crohn's disease (CD) patients, and 263 species from healthy individuals. Consistent with our 16S rRNA gene amplicon sequencing results, a significant decrease in microbial diversity and a severe imbalance, especially in CD patients, were also observed in the culture-based analysis. Our culturomics approach provided additional insights, highlighting dysbiosis in unique anaerobic and Gram-negative species in CD patients. Moreover, species-level findings for Bifidobacterium and Enterobacterales emphasized specific species expansions in IBD patients. Notably, Mediterraneibacter gnavus, Thomasclavelia ramosa, Parabacteroides merdae, and Collinsella aerofaciens are of particular clinical interest due to their correlation with inflammatory biomarkers. This comprehensive analysis underscores the value of integrating a culture-based approach with a genome-based approach to provide complementary insights and therapeutic targets in IBD.

Dextran sodium sulfate-induced colitis alters the proportion and composition of replicating gut bacteria

The bacteria living in the human gut are essential for host health. Though the composition and metabolism of these bacteria are well described in both healthy hosts and those with intestinal disease, less is known about the metabolic activity of the gut bacteria prior to, and during, disease development-especially regarding gut bacterial replication. Here, we use a recently developed single-cell technique alongside existing metagenomics-based tools to identify, track, and quantify replicating gut bacteria both ex vivo and in situ in the dextran sodium sulfate (DSS) mouse model of colitis. We show that the proportion of replicating gut bacteria decreases when mice have the highest levels of inflammation and returns to baseline levels as mice begin recovering. In addition, we report significant alterations in the composition of the replicating gut bacterial community ex vivo during colitis development. On the taxa level, we observe significant changes in the abundance of taxa such as the mucus-degrading Akkermansia and the poorly described Erysipelatoclostridium genus. We further demonstrate that many taxa exhibit variable replication rates in situ during colitis, including Akkermansia muciniphila. Lastly, we show that colitis development is positively correlated with increases in the presence and abundance of bacteria in situ which are predicted to be fast replicators. This could suggest that taxa with the potential to replicate quickly may have an advantage during intestinal inflammation. These data support the need for additional research using activity-based approaches to further characterize the gut bacterial response to intestinal inflammation and its consequences for both the host and the gut microbial community.IMPORTANCEIt is well known that the bacteria living inside the gut are important for human health. Indeed, the type of bacteria that are present and their metabolism are different in healthy people versus those with intestinal disease. However, less is known about how these gut bacteria are replicating, especially as someone begins to develop intestinal disease. This is particularly important as it is thought that metabolically active gut bacteria may be more relevant to health. Here, we begin to address this gap using several complementary approaches to characterize the replicating gut bacteria in a mouse model of intestinal inflammation. We reveal which gut bacteria are replicating, and how quickly, as mice develop and recover from inflammation. This work can serve as a model for future research to identify how actively growing gut bacteria may be impacting health, or why these particular bacteria tend to thrive during intestinal inflammation.

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-based ensemble model predicts prognosis of pediatric inflammatory bowel disease

Developing microbiome-based markers for pediatric inflammatory bowel disease (PIBD) is challenging. Here, we evaluated the diagnostic and prognostic potential of the gut microbiome in PIBD through a case-control study and cross-cohort analyses. In a Korean PIBD cohort (24 patients with PIBD, 43 controls), we observed that microbial diversity and composition shifted in patients with active PIBD versus controls and recovered at remission. We employed a differential abundance meta-analysis approach to identify microbial markers consistently associated with active inflammation and remission across seven PIBD cohorts from six countries (n = 1,670) including our dataset. Finally, we trained and tested various machine learning models for their ability to predict a patient's future remission based on baseline bacterial composition. An ensemble model trained with the amplicon sequence variants effectively predicted future remission of PIBD. This research highlights the gut microbiome's potential to guide precision therapy for PIBD.

The emerging role of the gut microbiota and its application in inflammatory bowel disease

Inflammatory bowel disease (IBD), including Crohn's disease and ulcerative colitis, is a complex disorder with an unknown cause. However, the dysbiosis of the gut microbiome has been found to play a role in IBD etiology, including exacerbated immune responses and defective intestinal barrier integrity. The gut microbiome can also be a potential biomarker for several diseases, including IBD. Currently, conventional treatments targeting pro-inflammatory cytokines and pathways in IBD-associated dysbiosis do not yield effective results. Other therapies that directly target the dysbiotic microbiome for effective outcomes are emerging. We review the role of the gut microbiome in health and IBD and its potential as a diagnostic, prognostic, and therapeutic target for IBD. This review also explores emerging therapeutic advancements that target gut microbiome-associated alterations in IBD, such as nanoparticle or encapsulation delivery, fecal microbiota transplantation, nutritional therapies, microbiome/probiotic engineering, phage therapy, mesenchymal stem cells (MSCs), gut proteins, and herbal formulas.

Comparison between 16S rRNA and shotgun sequencing in colorectal cancer, advanced colorectal lesions, and healthy human gut microbiota

BACKGROUND

Gut dysbiosis has been associated with colorectal cancer (CRC), the third most prevalent cancer in the world. This study compares microbiota taxonomic and abundance results obtained by 16S rRNA gene sequencing (16S) and whole shotgun metagenomic sequencing to investigate their reliability for bacteria profiling. The experimental design included 156 human stool samples from healthy controls, advanced (high-risk) colorectal lesion patients (HRL), and CRC cases, with each sample sequenced using both 16S and shotgun methods. We thoroughly compared both sequencing technologies at the species, genus, and family annotation levels, the abundance differences in these taxa, sparsity, alpha and beta diversities, ability to train prediction models, and the similarity of the microbial signature derived from these models.

RESULTS

As expected, the results showed that 16S detects only part of the gut microbiota community revealed by shotgun, although some genera were only profiled by 16S. The 16S abundance data was sparser and exhibited lower alpha diversity. In lower taxonomic ranks, shotgun and 16S highly differed, partially due to a disagreement in reference databases. When considering only shared taxa, the abundance was positively correlated between the two strategies. We also found a moderate correlation between the shotgun and 16S alpha-diversity measures, as well as their PCoAs. Regarding the machine learning models, only some of the shotgun models showed some degree of predictive power in an independent test set, but we could not demonstrate a clear superiority of one technology over the other. Microbial signatures from both sequencing techniques revealed taxa previously associated with CRC development, e.g., Parvimonas micra.

CONCLUSIONS

Shotgun and 16S sequencing provide two different lenses to examine microbial communities. While we have demonstrated that they can unravel common patterns (including microbial signatures), shotgun often gives a more detailed snapshot than 16S, both in depth and breadth. Instead, 16S will tend to show only part of the picture, giving greater weight to dominant bacteria in a sample. Therefore, we recommend choosing one or another sequencing technique before launching a study. Specifically, shotgun sequencing is preferred for stool microbiome samples and in-depth analyses, while 16S is more suitable for tissue samples and studies with targeted aims.

An integrative multi-omic analysis defines gut microbiota, mycobiota, and metabolic fingerprints in ulcerative colitis patients

Background

Ulcerative colitis (UC) is a multifactorial chronic inflammatory bowel disease (IBD) that affects the large intestine with superficial mucosal inflammation. A dysbiotic gut microbial profile has been associated with UC. Our study aimed to characterize the UC gut bacterial, fungal, and metabolic fingerprints by omic approaches.

Methods

The 16S rRNA- and ITS2-based metataxonomics and gas chromatography-mass spectrometry/solid phase microextraction (GC-MS/SPME) metabolomic analysis were performed on stool samples of 53 UC patients and 37 healthy subjects (CTRL). Univariate and multivariate approaches were applied to separated and integrated omic data, to define microbiota, mycobiota, and metabolic signatures in UC. The interaction between gut bacteria and fungi was investigated by network analysis.

Results

In the UC cohort, we reported the increase of Streptococcus, Bifidobacterium, Enterobacteriaceae, TM7-3, Granulicatella, Peptostreptococcus, Lactobacillus, Veillonella, Enterococcus, Peptoniphilus, Gemellaceae, and phenylethyl alcohol; and we also reported the decrease of Akkermansia; Ruminococcaceae; Ruminococcus; Gemmiger; Methanobrevibacter; Oscillospira; Coprococus; Christensenellaceae; Clavispora; Vishniacozyma; Quambalaria; hexadecane; cyclopentadecane; 5-hepten-2-ol, 6 methyl; 3-carene; caryophyllene; p-Cresol; 2-butenal; indole, 3-methyl-; 6-methyl-3,5-heptadiene-2-one; 5-octadecene; and 5-hepten-2-one, 6 methyl. The integration of the multi-omic data confirmed the presence of a distinctive bacterial, fungal, and metabolic fingerprint in UC gut microbiota. Moreover, the network analysis highlighted bacterial and fungal synergistic and/or divergent interkingdom interactions.

Conclusion

In this study, we identified intestinal bacterial, fungal, and metabolic UC-associated biomarkers. Furthermore, evidence on the relationships between bacterial and fungal ecosystems provides a comprehensive perspective on intestinal dysbiosis and ecological interactions between microorganisms in the framework of UC.

Comparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach

The human gut microbiome establishes and matures during infancy, and dysregulation at this stage may lead to pathologies later in life. We conducted a multi-omics study comprising three generations of family members to investigate the early development of the gut microbiota. Fecal samples from 200 individuals, including infants (0-12 months old; 55% females, 45% males) and their respective mothers and grandmothers, were analyzed using two independent metabolomics platforms and metagenomics. For metabolomics, gas chromatography and capillary electrophoresis coupled to mass spectrometry were applied. For metagenomics, both 16S rRNA gene and shotgun sequencing were performed. Here we show that infants greatly vary from their elders in fecal microbiota populations, function, and metabolome. Infants have a less diverse microbiota than adults and present differences in several metabolite classes, such as short- and branched-chain fatty acids, which are associated with shifts in bacterial populations. These findings provide innovative biochemical insights into the shaping of the gut microbiome within the same generational line that could be beneficial in improving childhood health outcomes.

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.

Alterations in colorectal cancer virome and its persistence after surgery

Viruses are a key component of the colon microbiome, but the relationship between virome and colorectal cancer (CRC) remains poorly understood. We seek to identify alterations in the viral community that is characteristic of CRC and examine if they persist after surgery. Forty-nine fecal samples from 25 non-cancer (NC) individuals and 12 CRC patients, before and 6-months after surgery, were collected for metagenomic analysis. The fecal virome of CRC patients demonstrated an increased network connectivity as compared to NC individuals. Co-exclusion of influential viruses to bacterial species associated with healthy gut status was observed in CRC, suggesting an altered virome induced a change in the healthy gut bacteriome. Network analysis revealed lower connectivity within the virome and trans-kingdom interactions in NC. After surgery, the number of strong correlations decreased for trans-kingdom and within the bacteria and virome networks, indicating lower connectivity within the microbiome. Some co-occurrence patterns between dominant viruses and bacteria were also lost after surgery, suggesting a possible return to the healthy state of gut microbiome. Microbial signatures characteristic of CRC include an altered virome besides an altered bacterial composition. Elevated viral correlations and network connectivity were observed in CRC patients relative to healthy individuals, alongside distinct changes in the cross-kingdom correlation network unique to CRC patients. Some patterns of dysbiosis persist after surgery. Future studies should seek to verify if dysbiosis truly persists after surgery in a larger sample size with microbiome data collected at various time points after surgery to explore if there is field-change in the remaining colon, as well as to examine if persistent dysbiosis correlates with patient outcomes.

Evaluation of gut microbiota predictive potential associated with phenotypic characteristics to identify multifactorial diseases

Gut microbiota has been implicated in various clinical conditions, yet the substantial heterogeneity in gut microbiota research results necessitates a more sophisticated approach than merely identifying statistically different microbial taxa between healthy and unhealthy individuals. Our study seeks to not only select microbial taxa but also explore their synergy with phenotypic host variables to develop novel predictive models for specific clinical conditions.

DESIGN

We assessed 50 healthy and 152 unhealthy individuals for phenotypic variables (PV) and gut microbiota (GM) composition by 16S rRNA gene sequencing. The entire modeling process was conducted in the R environment using the Random Forest algorithm. Model performance was assessed through ROC curve construction.

RESULTS

We evaluated 52 bacterial taxa and pre-selected PV (p < 0.05) for their contribution to the final models. Across all diseases, the models achieved their best performance when GM and PV data were integrated. Notably, the integrated predictive models demonstrated exceptional performance for rheumatoid arthritis (AUC = 88.03%), type 2 diabetes (AUC = 96.96%), systemic lupus erythematosus (AUC = 98.4%), and type 1 diabetes (AUC = 86.19%).

CONCLUSION

Our findings underscore that the selection of bacterial taxa based solely on differences in relative abundance between groups is insufficient to serve as clinical markers. Machine learning techniques are essential for mitigating the considerable variability observed within gut microbiota. In our study, the use of microbial taxa alone exhibited limited predictive power for health outcomes, while the integration of phenotypic variables into predictive models substantially enhanced their predictive capabilities.

Carbohydrate quality, fecal microbiota and cardiometabolic health in older adults: a cohort study

The impact of carbohydrate quality, measured by the carbohydrate quality index (CQI), on gut microbiota and health has been scarcely investigated. The aim of this study was to cross-sectionally and longitudinally explore the relationships between CQI, fecal microbiota, and cardiometabolic risk factors in an elderly Mediterranean population at high cardiovascular risk. At baseline and 1-year, CQI was assessed from food frequency questionnaires data, cardiometabolic risk factors were measured, and fecal microbiota profiled from 16S sequencing. Multivariable-adjusted linear regression models were fitted to assess the associations between tertiles of baseline CQI, fecal microbiota, and cardiometabolic risk factors at baseline, and between tertiles of 1-year change in CQI, 1-year change in fecal microbiota and cardiometabolic risk factors. Cross-sectionally, higher CQI was positively associated with Shannon alpha diversity index, and abundance of genera Faecalibacterium and Christensenellaceae R7 group, and negatively associated with the abundance of Odoribacter, and uncultured Rhodospirillales genera. Some of these genera were associated with higher glycated hemoglobin and lower body mass index. In addition, we observed a positive association between CQI, and some pathways related with the metabolism of butyrate precursors and plants-origin molecules. Longitudinally, 1-year improvement in CQI was associated with a concurrent increase in the abundance of genera Butyrivibrio. Increased abundance of this genera was associated with 1-year improvement in insulin status. These observations suggest that a better quality of carbohydrate intake is associated with improved metabolic health, and this improvement could be modulated by greater alpha diversity and abundance of specific genera linked to beneficial metabolic outcomes.

Hydrogen gas and the gut microbiota are potential biomarkers for the development of experimental colitis in mice

Inflammatory bowel disease (IBD) is a chronic disease characterised by repeated relapses and remissions and a high recurrence rate even after symptom resolution. The primary method for IBD diagnosis is endoscopy; however, this method is expensive, invasive, and cumbersome to use serially. Therefore, more convenient and non-invasive methods for IBD diagnosis are needed. In this study, we aimed to identify biological gas markers for the development of gut inflammation. Using dextran sulphate sodium (DSS)-induced colitis mouse models, five biological gases were analysed to identify predictive markers for the development of gut inflammation. Additionally, the correlation between the changes in gas composition, gut microbiota, and inflammatory markers was assessed. The hydrogen (H2) level was found to be negatively correlated with the level of lipocalin-2 (LCN2), a gut inflammation biomarker, and weight loss due to DSS-induced colitis. Furthermore, gut microbes belonging to the Rikenellaceae and Akkermansiaceae families were positively correlated with LCN2 levels and weight loss, whereas Tannerellaceae abundance was negatively correlated with LCN2 level and weight loss and positively correlated with H2 levels. This study provides new insights for IBD diagnosis; the H2 levels in biological gases are a potential biomarker for intestinal inflammation, and specific gut microbes are associated with H2 level changes.

Integrative analysis of microbial 16S gene and shotgun metagenomic sequencing data improves statistical efficiency

Background

The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Interestingly, many microbiome studies have performed both sequencing experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, highlighting the potential for an integrative analysis to improve power of testing these signatures. However, differential experimental biases, partially overlapping samples, and differential library sizes pose tremendous challenges when combining the two datasets. Currently, researchers either discard one dataset entirely or use different datasets for different objectives.

Methods

In this article, we introduce the first method of this kind, named Com-2seq, that combines the two sequencing datasets for testing differential abundance at the genus and community levels while overcoming these difficulties. The new method is based on our LOCOM model (Hu et al., 2022), which employs logistic regression for testing taxon differential abundance while remaining robust to experimental bias. To benchmark the performance of Com-2seq, we introduce two ad hoc approaches: applying LOCOM to pooled taxa count data and combining LOCOM p-values from analyzing each dataset separately.

Results

Our simulation studies indicate that Com-2seq substantially improves statistical efficiency over analysis of either dataset alone and works better than the two ad hoc approaches. An application of Com-2seq to two real microbiome studies uncovered scientifically plausible findings that would have been missed by analyzing individual datasets.

Conclusions

Com-2seq performs integrative analysis of 16S and metagenomic sequencing data, which improves statistical efficiency and has the potential to accelerate the search of microbial communities and taxa that are involved in human health and diseases.

From-Toilet-to-Freezer: A Review on Requirements for an Automatic Protocol to Collect and Store Human Fecal Samples for Research Purposes

The composition, viability and metabolic functionality of intestinal microbiota play an important role in human health and disease. Studies on intestinal microbiota are often based on fecal samples, because these can be sampled in a non-invasive way, although procedures for sampling, processing and storage vary. This review presents factors to consider when developing an automated protocol for sampling, processing and storing fecal samples: donor inclusion criteria, urine-feces separation in smart toilets, homogenization, aliquoting, usage or type of buffer to dissolve and store fecal material, temperature and time for processing and storage and quality control. The lack of standardization and low-throughput of state-of-the-art fecal collection procedures promote a more automated protocol. Based on this review, an automated protocol is proposed. Fecal samples should be collected and immediately processed under anaerobic conditions at either room temperature (RT) for a maximum of 4 h or at 4 °C for no more than 24 h. Upon homogenization, preferably in the absence of added solvent to allow addition of a buffer of choice at a later stage, aliquots obtained should be stored at either -20 °C for up to a few months or -80 °C for a longer period-up to 2 years. Protocols for quality control should characterize microbial composition and viability as well as metabolic functionality.

Effects of marine sediment as agricultural substrate on soil microbial diversity: an amplicon sequencing study

BACKGROUND

The soil microbiota has a direct impact on plant development and other metabolic systems, such as the degradation of organic matter and the availability of microelements and metabolites. In the context of agricultural soils, microbial activity is crucial for maintaining soil health and productivity. Thus, the present study aimed to identify, characterize, and quantify the microbial communities of four types of substrates with varying proportions of marine port sediment used for cultivating lemons. By investigating microbial diversity and relative abundance, the work aimed to highlight the importance of soil microbial communities in agriculture when alternative culture media was used.

RESULTS

The composition and structure of the sampled microbial communities were assessed through the amplification and sequencing of the V3-V4 variable regions of the 16 S rRNA gene The results revealed a diverse microbial community composition in all substrate samples, with a total of 41 phyla, 113 classes, 266 orders, 405 families, 715 genera, and 1513 species identified. Among these, Proteobacteria, Bacteroidota, Planctomycetota, Patescibacteria, Chloroflexi, Actinobacteriota, Acidobacteriota, Verrucomicrobiota, and Gemmatimonadota accounted for over 90% of the bacterial reads, indicating their dominance in the substrates.

CONCLUSIONS

The impact of the substrate origin on the diversity and relative abundace of the microbiota was confirmed. The higher content of beneficial bacterial communities for plant development identified in peat could explain why is considered an ideal agricultural substrate. Development of "beneficial for plants" bacterial communities in alternative agricultural substrates, regardless of the edaphic characteristics, opens the possibility of studying the forced and specific inoculation of these culture media aiming to be agriculturally ideals.

Integrative analysis of microbial 16S gene and shotgun metagenomic sequencing data improves statistical efficiency

The most widely used technologies for profiling microbial communities are 16S marker-gene sequencing and shotgun metagenomic sequencing. Interestingly, many microbiome studies have performed both sequencing experiments on the same cohort of samples. The two sequencing datasets often reveal consistent patterns of microbial signatures, highlighting the potential for an integrative analysis to improve power of testing these signatures. However, differential experimental biases, partially overlapping samples, and differential library sizes pose tremendous challenges when combining the two datasets. Currently, researchers either discard one dataset entirely or use different datasets for different objectives. In this article, we introduce the first method of this kind, named Com-2seq, that combines the two sequencing datasets for the objective of testing differential abundance at the genus and community levels while overcoming these difficulties. We demonstrate that Com-2seq substantially improves statistical efficiency over analysis of either dataset alone and works better than two ad hoc approaches.

Potential Oral Microbial Markers for Differential Diagnosis of Crohn's Disease and Ulcerative Colitis Using Machine Learning Models

Although gut microbiome dysbiosis has been associated with inflammatory bowel disease (IBD), the relationship between the oral microbiota and IBD remains poorly understood. This study aimed to identify unique microbiome patterns in saliva from IBD patients and explore potential oral microbial markers for differentiating Crohn's disease (CD) and ulcerative colitis (UC). A prospective cohort study recruited IBD patients (UC: n = 175, CD: n = 127) and healthy controls (HC: n = 100) to analyze their oral microbiota using 16S rRNA gene sequencing. Machine learning models (sparse partial least squares discriminant analysis (sPLS-DA)) were trained with the sequencing data to classify CD and UC. Taxonomic classification resulted in 4041 phylotypes using Kraken2 and the SILVA reference database. After quality filtering, 398 samples (UC: n = 175, CD: n = 124, HC: n = 99) and 2711 phylotypes were included. Alpha diversity analysis revealed significantly reduced richness in the microbiome of IBD patients compared to healthy controls. The sPLS-DA model achieved high accuracy (mean accuracy: 0.908, and AUC: 0.966) in distinguishing IBD vs. HC, as well as good accuracy (0.846) and AUC (0.923) in differentiating CD vs. UC. These findings highlight distinct oral microbiome patterns in IBD and provide insights into potential diagnostic markers.

Gut Dysbiosis and Blood-Brain Barrier Alteration in Hepatic Encephalopathy: From Gut to Brain

A common neuropsychiatric complication of advanced liver disease, hepatic encephalopathy (HE), impacts the quality of life and length of hospital stays. There is new evidence that gut microbiota plays a significant role in brain development and cerebral homeostasis. Microbiota metabolites are providing a new avenue of therapeutic options for several neurological-related disorders. For instance, the gut microbiota composition and blood-brain barrier (BBB) integrity are altered in HE in a variety of clinical and experimental studies. Furthermore, probiotics, prebiotics, antibiotics, and fecal microbiota transplantation have been shown to positively affect BBB integrity in disease models that are potentially extendable to HE by targeting gut microbiota. However, the mechanisms that underlie microbiota dysbiosis and its effects on the BBB are still unclear in HE. To this end, the aim of this review was to summarize the clinical and experimental evidence of gut dysbiosis and BBB disruption in HE and a possible mechanism.

Gut microbiota mediates the anti-colitis effects of polysaccharides derived from Rhopilema esculentum Kishinouye in mice

Ulcerative colitis (UC) is closely associated with the disturbance of gut microbiota. Crude polysaccharide-rich extract from Rhopilema esculentum Kishinouye has been proven to alleviate dextran sulfate sodium (DSS)-triggered colitis. However, it remains unclear whether the polysaccharides from Rhopilema esculentum (REP) in the extract play a predominant role in ameliorating colitis and whether gut microbiota mediates the beneficial effect of REP. Herein, we aimed to investigate the anti-colitis effects of REP and its mechanisms and to explore the role of REP-modulated gut microbiota in alleviating colitis in mice. Oral REP supplementation ameliorated the symptoms, inflammatory responses, colonic damage and gut microbial dysbiosis in colitic mice. REP significantly enriched SCFA-producing bacteria such as Roseburia and probiotics such as Bifidobacterium and restored the level of SCFAs especially butyric acid and propionic acid. Next, we found that transplantation of microbiota from REP-treated mice alleviated DSS-induced acute colitis, evidenced by improved gut barrier integrity and lower inflammation compared with mice receiving microbiota from control mice. Notably, dramatically enriched Bifidobacterium, Faecalibaculum and SCFA-producing bacteria including Butyricicoccus and Roseburia were found in mice receiving microbiota from the REP-treated donor mice. Lastly, the protective effect of REP supplementation on colitis was abolished in the antibiotic-treated mice. Overall, our findings suggest that REP could alleviate DSS-induced colitis in mice by regulating the imbalance of the microbiome. The polysaccharides of Rhopilema esculentum Kishinouye have the potential to be developed into promising prebiotic agents for rectifying dysbiosis of gut microbiota and preventing UC.

The diagnostic and prognostic potential of gut bacteria in inflammatory bowel disease

The gut microbiome serves as a signaling hub that integrates environmental inputs with genetic and immune signals to influence the host's metabolism and immunity. Gut bacteria are intricately connected with human health and disease state, with specific bacteria species driving the characteristic dysbiosis found in gastrointestinal conditions such as inflammatory bowel disease (IBD); thus, gut bacteria changes could be harnessed to improve IBD diagnosis, prognosis, and treatment. The advancement in next-generation sequencing techniques such as 16S rRNA and whole-genome shotgun sequencing has allowed the exploration of the complexity of the gut microbial ecosystem with high resolution. Current microbiome data is promising and appears to perform better in some studies than the currently used fecal inflammation biomarker, calprotectin, in predicting IBD from healthy controls and irritable bowel syndrome (IBS). This study reviews current data on the differential potential of gut bacteria within IBD cohorts, and between IBD and other gastrointestinal diseases.

Berberine Depresses Inflammation and Adjusts Smooth Muscle to Ameliorate Ulcerative Colitis of Cats by Regulating Gut Microbiota

Intestinal microbiota dysbiosis is a well established characteristic of ulcerative colitis (UC). Regulating the gut microbiota is an effective UC treatment strategy. Berberine (BBR), an alkaloid extracted from several Chinese herbs, is a common traditional Chinese medicine. To establish the efficacy and mechanism of action of BBR, we constructed a UC model using healthy adult shorthair cats to conduct a systematic study of colonic tissue pathology, inflammatory factor expression, and gut microbiota structure. We investigated the therapeutic capacity of BBR for regulating the gut microbiota and thus work against UC in cats using 16S rRNA genes amplicon sequencing technology. Our results revealed that dextran sulfate sodium (DSS)-induced cat models of UC showed weight loss, diarrhea accompanied by mucous and blood, histological abnormalities, and shortening of the colon, all of which were significantly alleviated by supplementation with BBR. A 16S rRNA gene-based microbiota analysis demonstrated that BBR could significantly benefit gut microbiota. Western blot, quantitative PCR, and enzyme-linked immunosorbent assays (ELISAs) showed that in DSS-induced cat models, the expression of the inflammatory factors was increased, activating the JAK2/STAT3 signaling pathway, and treatment with BBR reversed this effect. The myosin light chain (MLC) phosphorylation in the smooth muscle of the intestines is associated with motility of inflammation-related diarrhea in cats. This study used gut flora analyses to demonstrate the anti-UC effects of BBR and its potential therapeutic mechanisms and offers novel insights into the prevention of inflammatory diseases using natural products. IMPORTANCE Ulcerative colitis (UC) is common in clinics. Intestinal microbiota disorder is correlated with ulcerative colitis. Although there are many studies on ulcerative colitis in rats, there are few studies on colitis in cats. Therefore, this study explored the possibility of the use of BBR as a safe and efficient treatment for colitis in cats. The results demonstrated the therapeutic effects of BBR on UC based on the state of the intestinal flora. The study found BBR supplementation to be effective against dextran sulfate sodium (DSS)-induced colitis, smooth muscle damage, and gut microbiota dysbiosis.

Homeostasis and Dysbiosis of the Intestinal Microbiota: Comparing Hallmarks of a Healthy State with Changes in Inflammatory Bowel Disease

The gut microbiota, which represent a community of different microorganisms in the human intestinal tract, are crucial to preserving human health by participating in various physiological functions and acting as a metabolic organ. In physiological conditions, microbiota-host partnership exerts homeostatic stability; however, changes in intestinal microbiota composition (dysbiosis) are an important factor in the pathogenesis of inflammatory bowel disease and its two main disease entities: ulcerative colitis and Crohn's disease. The incidence and prevalence of these inflammatory conditions have increased rapidly in the last decade, becoming a significant problem for the healthcare system and a true challenge in finding novel therapeutic solutions. The issue is that, despite numerous studies, the etiopathogenesis of inflammatory bowel disease is not completely clear. Based on current knowledge, chronic intestinal inflammation occurs due to altered intestinal microbiota and environmental factors, as well as a complex interplay between the genetic predisposition of the host and an inappropriate innate and acquired immune response. It is important to note that the development of biological and immunomodulatory therapy has led to significant progress in treating inflammatory bowel disease. Certain lifestyle changes and novel approaches-including fecal microbiota transplantation and nutritional supplementation with probiotics, prebiotics, and synbiotics-have offered solutions for dysbiosis management and paved the way towards restoring a healthy microbiome, with only minimal long-term unfavorable effects.

Metagenomic Analyses of Multiple Gut Datasets Revealed the Association of Phage Signatures in Colorectal Cancer

The association of colorectal cancer (CRC) and the human gut microbiome dysbiosis has been the focus of several studies in the past. Many bacterial taxa have been shown to have differential abundance among CRC patients compared to healthy controls. However, the relationship between CRC and non-bacterial gut microbiome such as the gut virome is under-studied and not well understood. In this study we conducted a comprehensive analysis of the association of viral abundances with CRC using metagenomic shotgun sequencing data of 462 CRC subjects and 449 healthy controls from 7 studies performed in 8 different countries. Despite the high heterogeneity, our results showed that the virome alpha diversity was consistently higher in CRC patients than in healthy controls (p-value &lt;0.001). This finding is in sharp contrast to previous reports of low alpha diversity of prokaryotes in CRC compared to healthy controls. In addition to the previously known association of Podoviridae, Siphoviridae and Myoviridae with CRC, we further demonstrate that Herelleviridae, a newly constructed viral family, is significantly depleted in CRC subjects. Our interkingdom association analysis reveals a less intertwined correlation between the gut virome and bacteriome in CRC compared to healthy controls. Furthermore, we show that the viral abundance profiles can be used to accurately predict CRC disease status (AUROC &gt;0.8) in both within-study and cross-study settings. The combination of training sets resulted in rather generalized and accurate prediction models. Our study clearly shows that subjects with colorectal cancer harbor a distinct human gut virome profile which may have an important role in this disease.