Longitudinal Multi-omics Reveals Subset-Specific Mechanisms Underlying Irritable Bowel Syndrome

Modulation of gut microbiota and metabolites by Flammulina velutipes polysaccharides during in vitro human fecal fermentation: Unveiling Bacteroides as a potential primary degrader

Flammulina velutipes, a widely cultivated species of edible fungus, exhibits diverse functional activities attributed to its polysaccharides. In this study, we employed an in vitro model to investigate the impact of F. velutipes polysaccharides (FVP) fermentation on gut microbiota, with a particular focus on Bacteroides. FVP fermentation resulted in the proliferation of microbiota associated with short-chain fatty acid (SCFA) metabolism and suppression of Escherichia-Shigella. Bacteroides emerged as potential primary degraders of FVP, with species-level analysis identifying the preference of B. thetaiotaomicron and B. intestinalis in FVP degradation. Metabolomics analysis revealed significant increases in hypoxanthine and 7-methyladenine contents, with histidine metabolism emerging as the most enriched pathway. B. nordii and B. xylanisolvens exhibited the most influence on amino acid and SCFA metabolism. Understanding the mechanisms by which gut microbiota metabolize FVP can provide valuable insights into the potential of FVP to promote intestinal health and disease prevention.

Comparison of the effects of Amomum tsaoko and its adulterants on functional dyspepsia rats based on metabolomics analysis

Amomum tsaoko (AT) is commonly used in clinical practice to treat abdominal distension and pain. It is also a seasoning for cooking, with the functions of appetizing, invigorating the spleen, and being digestive-promoting. Amomum tsaoko (AT) has three adulterants, Amomum paratsaoko (AP), Amomum koenigii (AK), and Alpinia katsumadai Hayata, because of the confusion in historical classics regarding recorded sources as well as the near geographic distribution and fruit morphological similarities. In this study, we established a functional dyspepsia (FD) rat model and then treated it with the corresponding medicinal solutions AT, AP, AK, and AKH. The gastric emptying rate, intestinal propulsion rate, serum biochemical indicators, histopathological changes, and fecal metabolism were measured. The efficacy and mechanism of AT, AP, AK, and AKH in the treatment of FD were compared. Fecal metabolomics revealed that 20 potential biomarkers were involved in seven significant metabolic pathways in FD rats. These pathways include ubiquinone and other terpenoid-quinone biosynthesis, glycerophospholipid metabolism, tyrosine metabolism, primary bile acid biosynthesis, purine metabolism, folate biosynthesis, and amino sugar and nucleotide sugar metabolism. AP regulates 6 metabolic pathways, 5 metabolic pathways affected by AT, 4 metabolic pathways affected by AK, and 2 metabolic pathways affected by AKH.The above results suggest that the different effects of AT, AP, AK, and AKH on FD rats may be due to their different regulatory effects on the metabolome.

Longitudinal analysis of the enteric virome in paediatric subjects from the Free State Province, South Africa, reveals early gut colonisation and temporal dynamics

The gut of healthy neonates is devoid of viruses at birth, but rapidly becomes colonised by normal viral commensals that aid in important physiological functions like metabolism but can, in some instances, result in gastrointestinal illnesses. However, little is known about how this colonisation begins, its variability and factors shaping the gut virome composition. Thus, understanding the development, assembly, and progression of enteric viral communities over time is key. To explore early-life virome development, metagenomic sequencing was employed in faecal samples collected longitudinally from a cohort of 17 infants during their first six months of life. The gut virome analysis revealed a diverse and dynamic viral community, formed by a richness of different viruses infecting humans, non-human mammals, bacteria, and plants. Eukaryotic viruses were detected as early as one week of life, increasing in abundance and diversity over time. Most of the viruses detected are commonly associated with gastroenteritis and include members of the Caliciviridae, Picornaviridae, Astroviridae, Adenoviridae, and Sedoreoviridae families. The most common co-occurrences involved asymptomatic norovirus-parechovirus, norovirus-sapovirus, sapovirus-parechovirus, observed in at least 40 % of the samples. Majority of the plant-derived viruses detected in the infants' gut were from the Virgaviridae family. This study demonstrates the first longitudinal characterisation of the gastrointestinal virome in infants, from birth up to 6 months of age, in sub-Saharan Africa. Overall, the findings from this study delineate the composition and variability of the healthy infants' gut virome over time, which is a significant step towards understanding the dynamics and biogeography of viral communities in the infant gut.

[Microbial metaproteomics--From sample processing to data acquisition and analysis]

Microorganisms are closely associated with human diseases and health. Understanding the composition and function of microbial communities requires extensive research. Metaproteomics has recently become an important method for throughout and in-depth study of microorganisms. However, major challenges in terms of sample processing, mass spectrometric data acquisition, and data analysis limit the development of metaproteomics owing to the complexity and high heterogeneity of microbial community samples. In metaproteomic analysis, optimizing the preprocessing method for different types of samples and adopting different microbial isolation, enrichment, extraction, and lysis schemes are often necessary. Similar to those for single-species proteomics, the mass spectrometric data acquisition modes for metaproteomics include data-dependent acquisition (DDA) and data-independent acquisition (DIA). DIA can collect comprehensive peptide information from a sample and holds great potential for future development. However, data analysis for DIA is challenged by the complexity of metaproteome samples, which hinders the deeper coverage of metaproteomes. The most important step in data analysis is the construction of a protein sequence database. The size and completeness of the database strongly influence not only the number of identifications, but also analyses at the species and functional levels. The current gold standard for metaproteome database construction is the metagenomic sequencing-based protein sequence database. A public database-filtering method based on an iterative database search has been proven to have strong practical value. The peptide-centric DIA data analysis method is a mainstream data analysis strategy. The development of deep learning and artificial intelligence will greatly promote the accuracy, coverage, and speed of metaproteomic analysis. In terms of downstream bioinformatics analysis, a series of annotation tools that can perform species annotation at the protein, peptide, and gene levels has been developed in recent years to determine the composition of microbial communities. The functional analysis of microbial communities is a unique feature of metaproteomics compared with other omics approaches. Metaproteomics has become an important component of the multi-omics analysis of microbial communities, and has great development potential in terms of depth of coverage, sensitivity of detection, and completeness of data analysis.

Deciphering the therapeutic potential of SheXiangXinTongNing: Interplay between gut microbiota and brain metabolomics in a CUMS mice model, with a focus on tryptophan metabolism

Depression, a prevalent and multifaceted mental disorder, has emerged as a significant public health concern due to its escalating prevalence and heightened risk of severe suicidality. Given its profound impact, the imperative for preventing and intervening in depression is paramount. Substantial evidence underscores intricate connections between depression and cardiovascular health. SheXiangXinTongNing (XTN), a recognized traditional Chinese medicine for treating Coronary Heart Disease (CHD), prompted our exploration into its antidepressant effects and underlying mechanisms. In this investigation, we assessed XTN's antidepressant potential using the chronic unpredictable mild stress (CUMS) mice model and behavioral tests. Employing network pharmacology, we delved into the intricate mechanisms at play. We characterized the microbial composition and function in CUMS mice, both with and without XTN treatment, utilizing 16S rRNA sequencing and metabolomics analysis. The joint analysis of these results via Cytoscape identified pivotal metabolic pathways. In the realm of network pharmacology, XTN administration exhibited antidepressant effects by modulating pathways such as IL-17, neuroactive ligand-receptor interaction, PI3K-Akt, cAMP, calcium, and dopamine synapse signaling pathways. Our findings revealed that XTN significantly mitigated depression-like symptoms and cognitive deficits in CUMS mice by inhibiting neuroinflammation and pyroptosis. Furthermore, 16S rRNA sequencing unveiled that XTN increased the alpha-diversity and beta-diversity of the gut microbiome in CUMS mice. Metabolomics analysis identified brain metabolites crucial for distinguishing between the CUMS and CUMS+XTN groups, with a focus on pathways like Tryptophan metabolism and Linoleic acid metabolism. Notably, specific bacterial families, including Alloprevotella, Helicobacter, Allobaculum, and Clostridia, exhibited robust co-occurring relationships with brain tryptophan metabolomics, hinting at the potential mediating role of gut microbiome alterations and metabolites in the efficacy of XTN treatment. In conclusion, our study unveils modifications in microbial compositions and metabolic functions may be pivotal in understanding the response to XTN treatment, offering novel insights into the mechanisms underpinning the efficacy of antidepressants.

Fecal bacteria and short-chain fatty acids in irritable bowel syndrome: Relations to subtype

BACKGROUND

The relationship between gut microbiota and irritable bowel syndrome (IBS) subtype is unclear. We aimed to explore whether differences in fecal bacteria composition and short-chain fatty acid (SCFA) levels were associated with subtypes and symptoms of IBS.

METHODS

All participants delivered fecal samples and self-reports on IBS Symptom Severity Score (IBS-SSS), Bristol Stool Scale (BSS), and Gastrointestinal Symptom Rating Scale (GSRS). Fecal bacteria composition was assessed by the GA-map® Dysbiosis Test based on 16S rRNA sequences of bacterial species/groups. SCFAs were analyzed by vacuum distillation followed by gas chromatography.

KEY RESULTS

Sixty patients with IBS were included (mean age 38 years, 46 [77%] females): Twenty-one patients were classified as IBS-D (diarrhea), 31 IBS-M (mixed diarrhea and constipation), and eight IBS-C (constipation). Forty-two healthy controls (HCs) (mean age 35 years, 27 [64%] females) were included. Patients had a significantly higher relative frequency of dysbiosis, lower levels of Actinobacteria, and higher levels of Bacilli than HCs. Eight bacterial markers were significantly different across IBS subgroups and HCs, and 13 bacterial markers were weakly correlated with IBS symptoms. Clostridia and Veillonella spp. had a weak negative correlation with constipation scores (GSRS) and a weak positive correlation with loose stools (BSS). Diarrhea scores (GSRS) and looser stool (BSS) were weakly correlated with levels of total SCFAs, acetic and butyric acid. Levels of total SCFAs and acetic acid were weakly correlated with symptom severity (IBS-SSS).

CONCLUSIONS & INFERENCES

Patients with IBS had a different fecal bacteria composition compared to HCs, and alterations of SCFAs may contribute to the subtype.

Mechanisms of gastrointestinal toxicity in neuromyelitis optica spectrum disorder patients treated with mycophenolate mofetil: insights from a mouse model and human study

Mycophenolate mofetil (MMF) is commonly utilized for the treatment of neuromyelitis optica spectrum disorders (NMOSD). However, a subset of patients experience significant gastrointestinal (GI) adverse effects following MMF administration. The present study aims to elucidate the underlying mechanisms of MMF-induced GI toxicity in NMOSD. Utilizing a vancomycin-treated mouse model, we compiled a comprehensive data set to investigate the microbiome and metabolome in the GI tract to elucidate the mechanisms of MMF GI toxicity. Furthermore, we enrolled 17 female NMOSD patients receiving MMF, who were stratified into non-diarrhea NMOSD and diarrhea NMOSD (DNM) groups, in addition to 12 healthy controls. The gut microbiota of stool samples was analyzed using 16S rRNA gene sequencing. Vancomycin administration prevented weight loss and tissue injury caused by MMF, affecting colon metabolomes and microbiomes. Bacterial β-glucuronidase from Bacteroidetes and Firmicutes was linked to intestinal tissue damage. The DNM group showed higher alpha diversity and increased levels of Firmicutes and Proteobacteria. The β-glucuronidase produced by Firmicutes may be important in causing gastrointestinal side effects from MMF in NMOSD treatment, providing useful information for future research on MMF.

IMPORTANCE

Neuromyelitis optica spectrum disorder (NMOSD) patients frequently endure severe consequences like paralysis and blindness. Mycophenolate mofetil (MMF) effectively addresses these issues, but its usage is hindered by gastrointestinal (GI) complications. Through uncovering the intricate interplay among MMF, gut microbiota, and metabolic pathways, this study identifies specific gut bacteria responsible for metabolizing MMF into a potentially harmful form, thus contributing to GI side effects. These findings not only deepen our comprehension of MMF toxicity but also propose potential strategies, such as inhibiting these bacteria, to mitigate these adverse effects. This insight holds broader implications for minimizing complications in NMOSD patients undergoing MMF therapy.

The role of the gut microbiome in disorders of gut-brain interaction

Disorders of Gut-Brain Interaction (DGBI) are widely prevalent and commonly encountered in gastroenterology practice. While several peripheral and central mechanisms have been implicated in the pathogenesis of DGBI, a recent body of work suggests an important role for the gut microbiome. In this review, we highlight how gut microbiota and their metabolites affect physiologic changes underlying symptoms in DGBI, with a particular focus on their mechanistic influence on GI transit, visceral sensitivity, intestinal barrier function and secretion, and CNS processing. This review emphasizes the complexity of local and distant effects of microbial metabolites on physiological function, influenced by factors such as metabolite concentration, duration of metabolite exposure, receptor location, host genetics, and underlying disease state. Large-scale in vitro work has elucidated interactions between host receptors and the microbial metabolome but there is a need for future research to integrate such preclinical findings with clinical studies. The development of novel, targeted therapeutic strategies for DGBI hinges on a deeper understanding of these metabolite-host interactions, offering exciting possibilities for the future of treatment of DGBI.

Statistical and computational methods for integrating microbiome, host genomics, and metabolomics data

Large-scale microbiome studies are progressively utilizing multiomics designs, which include the collection of microbiome samples together with host genomics and metabolomics data. Despite the increasing number of data sources, there remains a bottleneck in understanding the relationships between different data modalities due to the limited number of statistical and computational methods for analyzing such data. Furthermore, little is known about the portability of general methods to the metagenomic setting and few specialized techniques have been developed. In this review, we summarize and implement some of the commonly used methods. We apply these methods to real data sets where shotgun metagenomic sequencing and metabolomics data are available for microbiome multiomics data integration analysis. We compare results across methods, highlight strengths and limitations of each, and discuss areas where statistical and computational innovation is needed.

Colorectal Disease and the Gut Microbiome: What a Surgeon Needs to Know

The gut microbiome is defined as the microorganisms that reside within the gastrointestinal tract and produce a variety of metabolites that impact human health. These microbes play an intricate role in human health, and an imbalance in the gut microbiome, termed gut dysbiosis, has been implicated in the development of varying diseases. The purpose of this review is to highlight what is known about the microbiome and its impact on colorectal cancer, inflammatory bowel disease, constipation, Clostridioides difficile infection, the impact of bowel prep, and anastomotic leaks.

Unveiling the dynamics of gut microbial interactions: a review of dietary impact and precision nutrition in gastrointestinal health

The human microbiome, a dynamic ecosystem within the gastrointestinal tract, plays a pivotal role in shaping overall health. This review delves into six interconnected sections, unraveling the intricate relationship between diet, gut microbiota, and their profound impact on human health. The dance of nutrients in the gut orchestrates a complex symphony, influencing digestive processes and susceptibility to gastrointestinal disorders. Emphasizing the bidirectional communication between the gut and the brain, the Brain-Gut Axis section highlights the crucial role of dietary choices in physical, mental, and emotional well-being. Autoimmune diseases, particularly those manifesting in the gastrointestinal tract, reveal the delicate balance disrupted by gut microbiome imbalances. Strategies for reconciling gut microbes through diets, precision nutrition, and clinical indications showcase promising avenues for managing gastrointestinal distress and revolutionizing healthcare. From the Low-FODMAP diet to neuro-gut interventions, these strategies provide a holistic understanding of the gut's dynamic world. Precision nutrition, as a groundbreaking discipline, holds transformative potential by tailoring dietary recommendations to individual gut microbiota compositions, reshaping the landscape of gastrointestinal health. Recent advancements in clinical indications, including exact probiotics, fecal microbiota transplantation, and neuro-gut interventions, signify a new era where the gut microbiome actively participates in therapeutic strategies. As the microbiome takes center stage in healthcare, a paradigm shift toward personalized and effective treatments for gastrointestinal disorders emerges, reflecting the symbiotic relationship between the human body and its microbial companions.

mi-Mic: a novel multi-layer statistical test for microbiota-disease associations

mi-Mic, a novel approach for microbiome differential abundance analysis, tackles the key challenges of such statistical tests: a large number of tests, sparsity, varying abundance scales, and taxonomic relationships. mi-Mic first converts microbial counts to a cladogram of means. It then applies a priori tests on the upper levels of the cladogram to detect overall relationships. Finally, it performs a Mann-Whitney test on paths that are consistently significant along the cladogram or on the leaves. mi-Mic has much higher true to false positives ratios than existing tests, as measured by a new real-to-shuffle positive score.

The Microbiome and Irritable Bowel Syndrome: An Emerging Hope for Treatment

Irritable bowel syndrome is a gastrointestinal disorder that affects 15%-20% of the US population. Its symptoms can have negative effects on a person's quality of life, and its treatment can be associated with high medical costs. An emerging area of irritable bowel syndrome research concerns the relationship between this condition and the gut microbiome. The purpose of this article is not only to review irritable bowel syndrome, and the role that the microbiome can play in its symptoms, but also to examine new emerging pathways that could blaze the trail for more individualized treatments. If equipped with this knowledge, gastrointestinal nurses and providers of care can be better prepared to help patients with irritable bowel syndrome in order to manage symptoms and improve their quality of life.

HMOs Impact the Gut Microbiome of Children and Adults Starting from Low Predicted Daily Doses

Recent studies suggest that the dietary intake of human milk oligosaccharides (HMOs) provides health benefits from infancy up to adulthood. Thus far, beneficial changes in the adult gut microbiome have been observed at oral doses of 5-20 g/day of HMOs. Efficacy of lower doses has rarely been tested. We assessed four HMO molecular species-2'Fucosyllactose (2'FL), Lacto-N-neotetraose (LNnT), 3'Sialyllactose (3'SL), and 6'Sialyllactose (6'SL)-at predicted doses from 0.3 to 5 g/day for 6-year-old children and adults (n = 6 each), using ex vivo SIFR® technology (Cryptobiotix, Ghent, Belgium). This technology employing bioreactor fermentation on fecal samples enables us to investigate microbial fermentation products that are intractable in vivo given their rapid absorption/consumption in the human gut. We found that HMOs significantly increased short-chain fatty acids (SCFAs), acetate, propionate (in children/adults), and butyrate (in adults) from predicted doses of 0.3-0.5 g/day onwards, with stronger effects as dosing increased. The fermentation of 6'SL had the greatest effect on propionate, LNnT most strongly increased butyrate, and 2'FL and 3'SL most strongly increased acetate. An untargeted metabolomic analysis revealed that HMOs enhanced immune-related metabolites beyond SCFAs, such as aromatic lactic acids (indole-3-lactic acid/3-phenyllactic acid) and 2-hydroxyisocaproic acid, as well as gut-brain-axis-related metabolites (γ-aminobutyric acid/3-hydroxybutyric acid/acetylcholine) and vitamins. The effects of low doses of HMOs potentially originate from the highly specific stimulation of keystone species belonging to, for example, the Bifidobacteriaceae family, which had already significantly increased at doses of only 0.5 g/day LNnT (adults) and 1 g/day 2'FL (children/adults).

Susceptibility to febrile malaria is associated with an inflammatory gut microbiome

Malaria is a major public health problem, but many of the factors underlying the pathogenesis of this disease are not well understood. Here, we demonstrate in Malian children that susceptibility to febrile malaria following infection with Plasmodium falciparum is associated with the composition of the gut microbiome prior to the malaria season. Gnotobiotic mice colonized with the fecal samples of malaria-susceptible children had a significantly higher parasite burden following Plasmodium infection compared to gnotobiotic mice colonized with the fecal samples of malaria-resistant children. The fecal microbiome of the susceptible children was enriched for bacteria associated with inflammation, mucin degradation, gut permeability and inflammatory bowel disorders (e.g., Ruminococcus gauvreauii, Ruminococcus torques, Dorea formicigenerans, Dorea longicatena, Lachnoclostridium phocaeense and Lachnoclostridium sp. YL32). However, the susceptible children also had a greater abundance of bacteria known to produce anti-inflammatory short-chain fatty acids and those associated with favorable prognosis and remission following dysbiotic intestinal events (e.g., Anaerobutyricum hallii, Blautia producta and Sellimonas intestinalis). Metabolomics analysis of the human fecal samples corroborated the existence of inflammatory and recovery-associated features within the gut microbiome of the susceptible children. There was an enrichment of nitric oxide-derived DNA adducts (deoxyinosine and deoxyuridine) and long-chain fatty acids, the absorption of which has been shown to be inhibited by inflamed intestinal epithelial cells, and a decrease in the abundance of mucus phospholipids. Nevertheless, there were also increased levels of pseudouridine and hypoxanthine, which have been shown to be regulated in response to cellular stress and to promote recovery following injury or hypoxia. Overall, these results indicate that the gut microbiome may contribute malaria pathogenesis and suggest that therapies targeting intestinal inflammation could decrease malaria susceptibility.

Multi-omic integration of microbiome data for identifying disease-associated modules

Multi-omic studies of the human gut microbiome are crucial for understanding its role in disease across multiple functional layers. Nevertheless, integrating and analyzing such complex datasets poses significant challenges. Most notably, current analysis methods often yield extensive lists of disease-associated features (e.g., species, pathways, or metabolites), without capturing the multi-layered structure of the data. Here, we address this challenge by introducing "MintTea", an intermediate integration-based approach combining canonical correlation analysis extensions, consensus analysis, and an evaluation protocol. MintTea identifies "disease-associated multi-omic modules", comprising features from multiple omics that shift in concord and that collectively associate with the disease. Applied to diverse cohorts, MintTea captures modules with high predictive power, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome study, MintTea identifies a module with serum glutamate- and TCA cycle-related metabolites, along with bacterial species linked to insulin resistance. In another dataset, MintTea identifies a module associated with late-stage colorectal cancer, including Peptostreptococcus and Gemella species and fecal amino acids, in line with these species' metabolic activity and their coordinated gradual increase with cancer development. This work demonstrates the potential of advanced integration methods in generating systems-level, multifaceted hypotheses underlying microbiome-disease interactions.

Antibiotic alters host's gut microbiota, fertility, and antimicrobial peptide gene expression vis-à-vis ampicillin treatment on model organism Drosophila melanogaster

Antibiotics are commonly used to treat infectious diseases; however, persistence is often expressed by the pathogenic bacteria and their long-term relative effect on the host have been neglected. The present study investigated the impact of antibiotics in gut microbiota (GM) and metabolism of host. The effect of ampicillin antibiotics on GM of Drosophila melanogaster was analyzed through deep sequencing of 16S rRNA amplicon gene. The dominant phyla consisted of Proteobacteria, Bacteroidetes, Firmicutes, Actinobacteria, Planctomycetes, Chloroflexi, Euryarchaeota, Acedobacteria, Verrucomicrobia, and Cyanobacteria. It was found that the composition of GM was significantly altered on administration of antibiotics. On antibiotic treatments, there were decline in relative abundance of Proteobacteria and Firmicutes, while there were increase in relative abundance of Chlorophyta and Bacteroidota. High abundance of 14 genera, viz., Wolbachia, Lactobacillus, Bacillus, Pseudomonas, Thiolamprovum, Pseudoalteromonas, Vibrio, Romboutsia, Staphylococcus, Alteromonas, Clostridium, Lysinibacillus, Litoricola, and Cellulophaga were significant (p ≤ 0.05) upon antibiotic treatment. Particularly, the abundance of Acetobacter was significantly (p ≤ 0.05) declined but increased for Wolbachia. Further, a significant (p ≤ 0.05) increase in Wolbachia endosymbiont of D. melanogaster, Wolbachia endosymbiont of Curculio okumai, and Wolbachia pipientis and a decrease in the Acinetobacter sp. were observed. We observed an increase in functional capacity for biosynthesis of certain nucleotides and the enzyme activities. Further, the decrease in antimicrobial peptide production in the treated group and potential effects on the host's defense mechanisms were observed. This study helps shed light on an often-overlooked dimension, namely the persistence of antibiotics' effects on the host.

Temporal stability of fecal metabolomic profiles in irritable bowel syndrome

BACKGROUND

The potential of the fecal metabolome to serve as a biomarker for irritable bowel syndrome (IBS) depends on its stability over time. Therefore, this study aimed to determine the temporal dynamics of the fecal metabolome, and the potential relationship with stool consistency, in patients with IBS and healthy subjects.

METHODS

Fecal samples were collected in two cohorts comprising patients with IBS and healthy subjects. For Cohort A, fecal samples collected during 5 consecutive days were analyzed by gas chromatography-tandem mass spectrometry (GC-MS/MS). For Cohort B, liquid chromatography-MS (LC-MS) was used to analyze fecal samples collected at week 0 (healthy and IBS) and at week 4 (patients only). Stool consistency was determined by the Bristol Stool Form scale.

KEY RESULTS

Fecal samples were collected from Cohort A (seven healthy subjects and eight IBS patients), and Cohort B (seven healthy subjects and 11 IBS patients). The fecal metabolome of IBS patients was stable short-term (Cohort A, 5 days and within the same day) and long-term (Cohort B, 4 weeks). A similar trend was observed over 5 days in the healthy subjects of Cohort A. The metabolome dissimilarity was larger between than within participants over time in both healthy subjects and IBS patients. Further analyses showed that patients had greater range of stool forms (types) than healthy subjects, with no apparent influence on metabolomic dynamics.

CONCLUSION & INFERENCES

The fecal metabolome is stable over time within IBS patients as well as healthy subjects. This supports the concept of a stable fecal metabolome in IBS despite fluctuations in stool consistency, and the use of single timepoint sampling to further explore how the fecal metabolome is related to IBS pathogenesis.

Amino acids in piglet diarrhea: Effects, mechanisms and insights

Piglet diarrhea is among one of the most serious health problems faced by the pig industry, resulting in significant economic losses. Diarrheal disease in piglets has a multifactorial etiology that is affected by physiology, environment, and management strategy. Diarrhea is the most apparent symptom of intestinal dysfunction. As a key class of essential nutrients in the piglet diet, amino acids confer a variety of beneficial effects on piglets in addition to being used as a substrate for protein synthesis, including maintaining appropriate intestinal integrity, permeability and epithelial renewal, and alleviating morphological damage and inflammatory and oxidative stress. Thus, provision of appropriate levels of amino acids could alleviate piglet diarrhea. Most amino acid effects are mediated by metabolites, gut microbes, and related signaling pathways. In this review, we summarize the current understanding of dietary amino acid effects on gut health and diarrhea incidence in piglets, and reveal the mechanisms involved. We also provide ideas for using amino acid blends and emphasize the importance of amino acid balance in the diet to prevent diarrhea in piglets.

Multi-omics reveal mechanisms of high enteral starch diet mediated colonic dysbiosis via microbiome-host interactions in young ruminant

BACKGROUND

Although rumen development is crucial, hindgut undertakes a significant role in young ruminants' physiological development. High-starch diet is usually used to accelerate rumen development for young ruminants, but always leading to the enteral starch overload and hindgut dysbiosis. However, the mechanism behind remains unclear. The combination of colonic transcriptome, colonic luminal metabolome, and metagenome together with histological analysis was conducted using a goat model, with the aim to identify the potential molecular mechanisms behind the disrupted hindgut homeostasis by overload starch in young ruminants.

RESULT

Compared with low enteral starch diet (LES), high enteral starch diet (HES)-fed goats had significantly higher colonic pathology scores, and serum diamine oxidase activity, and meanwhile significantly decreased colonic mucosal Mucin-2 (MUC2) protein expression and fecal scores, evidencing the HES-triggered colonic systemic inflammation. The bacterial taxa Prevotella sp. P4-67, Prevotella sp. PINT, and Bacteroides sp. CAG:927, together with fungal taxa Fusarium vanettenii, Neocallimastix californiae, Fusarium sp. AF-8, Hypoxylon sp. EC38, and Fusarium pseudograminearum, and the involved microbial immune pathways including the "T cell receptor signaling pathway" were higher in the colon of HES goats. The integrated metagenome and host transcriptome analysis revealed that these taxa were associated with enhanced pathogenic ability, antigen processing and presentation, and stimulated T helper 2 cell (TH2)-mediated cytokine secretion functions in the colon of HES goats. Further luminal metabolomics analysis showed increased relative content of chenodeoxycholic acid (CDCA) and deoxycholic acid (DCA), and decreased the relative content of hypoxanthine in colonic digesta of HES goats. These altered metabolites contributed to enhancing the expression of TH2-mediated inflammatory-related cytokine secretion including GATA Binding Protein 3 (GATA3), IL-5, and IL-13. Using the linear mixed effect model, the variation of MUC2 biosynthesis explained by the colonic bacteria, bacterial functions, fungi, fungal functions, and metabolites were 21.92, 20.76, 19.43, 12.08, and 44.22%, respectively. The variation of pathology scores explained by the colonic bacterial functions, fungal functions, and metabolites were 15.35, 17.61, and 57.06%.

CONCLUSIONS

Our findings revealed that enteral starch overload can trigger interrupted hindgut host-microbiome homeostasis that led to impaired mucosal, destroyed colonic water absorption, and TH2-mediated inflammatory process. Except for the colonic metabolites mostly contribute to the impaired mucosa, the nonnegligible contribution from fungi deserves more future studies focused on the fungal functions in hindgut dysbiosis of young ruminants. Video Abstract.

Gut microbiome-metabolome interactions predict host condition

BACKGROUND

The effect of microbes on their human host is often mediated through changes in metabolite concentrations. As such, multiple tools have been proposed to predict metabolite concentrations from microbial taxa frequencies. Such tools typically fail to capture the dependence of the microbiome-metabolite relation on the environment.

RESULTS

We propose to treat the microbiome-metabolome relation as the equilibrium of a complex interaction and to relate the host condition to a latent representation of the interaction between the log concentration of the metabolome and the log frequencies of the microbiome. We develop LOCATE (Latent variables Of miCrobiome And meTabolites rElations), a machine learning tool to predict the metabolite concentration from the microbiome composition and produce a latent representation of the interaction. This representation is then used to predict the host condition. LOCATE's accuracy in predicting the metabolome is higher than all current predictors. The metabolite concentration prediction accuracy significantly decreases cross datasets, and cross conditions, especially in 16S data. LOCATE's latent representation predicts the host condition better than either the microbiome or the metabolome. This representation is strongly correlated with host demographics. A significant improvement in accuracy (0.793 vs. 0.724 average accuracy) is obtained even with a small number of metabolite samples ([Formula: see text]).

CONCLUSION

These results suggest that a latent representation of the microbiome-metabolome interaction leads to a better association with the host condition than any of the two separated or the simple combination of the two. Video Abstract.

Dynamics of the Gut Microbiota and Faecal and Serum Metabolomes during Pregnancy-A Longitudinal Study

Normal pregnancy involves numerous physiological changes, including changes in hormone levels, immune responses, and metabolism. Although several studies have shown that the gut microbiota may have an important role in the progression of pregnancy, these findings have been inconsistent, and the relationship between the gut microbiota and metabolites that change dynamically during and after pregnancy remains to be clarified. In this longitudinal study, we comprehensively profiled the temporal dynamics of the gut microbiota, Bifidobacterium communities, and serum and faecal metabolomes of 31 women during their pregnancies and postpartum periods. The microbial composition changed as gestation progressed, with the pregnancy and postpartum periods exhibiting distinct bacterial community characteristics, including significant alterations in the genera of the Lachnospiraceae or Ruminococcaceae families, especially the Lachnospiraceae FCS020 group and Ruminococcaceae UCG-003. Metabolic dynamics, characterised by changes in nutrients important for fetal growth (e.g., docosatrienoic acid), anti-inflammatory metabolites (e.g., trans-3-indoleacrylic acid), and steroid hormones (e.g., progesterone), were observed in both serum and faecal samples during pregnancy. Moreover, a complex correlation was identified between the pregnancy-related microbiota and metabolites, with Ruminococcus1 and Ruminococcaceae UCG-013 making important contributions to changes in faecal and serum metabolites, respectively. Overall, a highly coordinated microbiota-metabolite regulatory network may underlie the pregnancy process. These findings provide a foundation for enhancing our understanding of the molecular processes occurring during the progression of pregnancy, thereby contributing to nutrition and health management during this period.

Multi-omic integration of microbiome data for identifying disease-associated modules

The human gut microbiome is a complex ecosystem with profound implications for health and disease. This recognition has led to a surge in multi-omic microbiome studies, employing various molecular assays to elucidate the microbiome's role in diseases across multiple functional layers. However, despite the clear value of these multi-omic datasets, rigorous integrative analysis of such data poses significant challenges, hindering a comprehensive understanding of microbiome-disease interactions. Perhaps most notably, multiple approaches, including univariate and multivariate analyses, as well as machine learning, have been applied to such data to identify disease-associated markers, namely, specific features (e.g., species, pathways, metabolites) that are significantly altered in disease state. These methods, however, often yield extensive lists of features associated with the disease without effectively capturing the multi-layered structure of multi-omic data or offering clear, interpretable hypotheses about underlying microbiome-disease mechanisms. Here, we address this challenge by introducing MintTea - an intermediate integration-based method for analyzing multi-omic microbiome data. MintTea combines a canonical correlation analysis (CCA) extension, consensus analysis, and an evaluation protocol to robustly identify disease-associated multi-omic modules. Each such module consists of a set of features from the various omics that both shift in concord, and collectively associate with the disease. Applying MintTea to diverse case-control cohorts with multi-omic data, we show that this framework is able to capture modules with high predictive power for disease, significant cross-omic correlations, and alignment with known microbiome-disease associations. For example, analyzing samples from a metabolic syndrome (MS) study, we found a MS-associated module comprising of a highly correlated cluster of serum glutamate- and TCA cycle-related metabolites, as well as bacterial species previously implicated in insulin resistance. In another cohort, we identified a module associated with late-stage colorectal cancer, featuring Peptostreptococcus and Gemella species and several fecal amino acids, in agreement with these species' reported role in the metabolism of these amino acids and their coordinated increase in abundance during disease development. Finally, comparing modules identified in different datasets, we detected multiple significant overlaps, suggesting common interactions between microbiome features. Combined, this work serves as a proof of concept for the potential benefits of advanced integration methods in generating integrated multi-omic hypotheses underlying microbiome-disease interactions and a promising avenue for researchers seeking systems-level insights into coherent mechanisms governing microbiome-related diseases.

High-Abundance Protein-Guided Hybrid Spectral Library for Data-Independent Acquisition Metaproteomics

Metaproteomics offers a direct avenue to identify microbial proteins in microbiota, enabling the compositional and functional characterization of microbiota. Due to the complexity and heterogeneity of microbial communities, in-depth and accurate metaproteomics faces tremendous limitations. One challenge in metaproteomics is the construction of a suitable protein sequence database to interpret the highly complex metaproteomic data, especially in the absence of metagenomic sequencing data. Herein, we present a high-abundance protein-guided hybrid spectral library strategy for in-depth data independent acquisition (DIA) metaproteomic analysis (HAPs-hyblibDIA). A dedicated high-abundance protein database of gut microbial species is constructed and used to mine the taxonomic information on microbiota samples. Then, a sample-specific protein sequence database is built based on the taxonomic information using Uniprot protein sequence for subsequent analysis of the DIA data using hybrid spectral library-based DIA analysis. We evaluated the accuracy and sensitivity of the method using synthetic microbial community samples and human gut microbiome samples. It was demonstrated that the strategy can successfully identify taxonomic compositions of microbiota samples and that the peptides identified by HAPs-hyblibDIA overlapped greatly with the peptides identified using a metagenomic sequencing-derived database. At the peptide and species level, our results can serve as a complement to the results obtained using a metagenomic sequencing-derived database. Furthermore, we validated the applicability of the HAPs-hyblibDIA strategy in a cohort of human gut microbiota samples of colorectal cancer patients and controls, highlighting its usability in biomedical research.

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important factor in precision medicine. High-throughput sequencing technologies have revolutionized -omics data generation, facilitating the characterization of the human gut microbiome with exceptional resolution. The analysis of various -omics data, including metatranscriptomics, metagenomics, glycomics, and metabolomics, holds potential for personalized therapies by revealing information about functional genes, microbial composition, glycans, and metabolites. This multi-omics approach has not only provided insights into the role of the gut microbiome in various diseases but has also facilitated the identification of microbial biomarkers for diagnosis, prognosis, and treatment. Machine learning algorithms have emerged as powerful tools for extracting meaningful insights from complex datasets, and more recently have been applied to metagenomics data via efficiently identifying microbial signatures, predicting disease states, and determining potential therapeutic targets. Despite these rapid advancements, several challenges remain, such as key knowledge gaps, algorithm selection, and bioinformatics software parametrization. In this mini-review, our primary focus is metagenomics, while recognizing that other -omics can enhance our understanding of the functional diversity of organisms and how they interact with the host. We aim to explore the current intersection of multi-omics, precision medicine, and machine learning in advancing our understanding of the gut microbiome. A multidisciplinary approach holds promise for improving patient outcomes in the era of precision medicine, as we unravel the intricate interactions between the microbiome and human health.

Gut virome in inflammatory bowel disease and beyond

OBJECTIVE

The gut virome is a dense community of viruses inhabiting the gastrointestinal tract and an integral part of the microbiota. The virome coexists with the other components of the microbiota and with the host in a dynamic equilibrium, serving as a key contributor to the maintenance of intestinal homeostasis and functions. However, this equilibrium can be interrupted in certain pathological states, including inflammatory bowel disease, causing dysbiosis that may participate in disease pathogenesis. Nevertheless, whether virome dysbiosis is a causal or bystander event requires further clarification.

DESIGN

This review seeks to summarise the latest advancements in the study of the gut virome, highlighting its cross-talk with the mucosal microenvironment. It explores how cutting-edge technologies may build upon current knowledge to advance research in this field. An overview of virome transplantation in diseased gastrointestinal tracts is provided along with insights into the development of innovative virome-based therapeutics to improve clinical management.

RESULTS

Gut virome dysbiosis, primarily driven by the expansion of Caudovirales, has been shown to impact intestinal immunity and barrier functions, influencing overall intestinal homeostasis. Although emerging innovative technologies still need further implementation, they display the unprecedented potential to better characterise virome composition and delineate its role in intestinal diseases.

CONCLUSIONS

The field of gut virome is progressively expanding, thanks to the advancements of sequencing technologies and bioinformatic pipelines. These have contributed to a better understanding of how virome dysbiosis is linked to intestinal disease pathogenesis and how the modulation of virome composition may help the clinical intervention to ameliorate gut disease management.

The gut microbiome in disorders of gut-brain interaction

Functional gastrointestinal disorders (FGIDs), chronic disorders characterized by either abdominal pain, altered intestinal motility, or their combination, have a worldwide prevalence of more than 40% and impose a high socioeconomic burden with a significant decline in quality of life. Recently, FGIDs have been reclassified as disorders of gut-brain interaction (DGBI), reflecting the key role of the gut-brain bidirectional communication in these disorders and their impact on psychological comorbidities. Although, during the past decades, the field of DGBIs has advanced significantly, the molecular mechanisms underlying DGBIs pathogenesis and pathophysiology, and the role of the gut microbiome in these processes are not fully understood. This review aims to discuss the latest body of literature on the complex microbiota-gut-brain interactions and their implications in the pathogenesis of DGBIs. A better understanding of the existing communication pathways between the gut microbiome and the brain holds promise in developing effective therapeutic interventions for DGBIs.

Multi-omic approaches for host-microbiome data integration

The gut microbiome interacts with the host through complex networks that affect physiology and health outcomes. It is becoming clear that these interactions can be measured across many different omics layers, including the genome, transcriptome, epigenome, metabolome, and proteome, among others. Multi-omic studies of the microbiome can provide insight into the mechanisms underlying host-microbe interactions. As more omics layers are considered, increasingly sophisticated statistical methods are required to integrate them. In this review, we provide an overview of approaches currently used to characterize multi-omic interactions between host and microbiome data. While a large number of studies have generated a deeper understanding of host-microbiome interactions, there is still a need for standardization across approaches. Furthermore, microbiome studies would also benefit from the collection and curation of large, publicly available multi-omics datasets.

The protective role of commensal gut microbes and their metabolites against bacterial pathogens

Multidrug-resistant microorganisms have become a major public health concern around the world. The gut microbiome is a gold mine for bioactive compounds that protect the human body from pathogens. We used a multi-omics approach that integrated whole-genome sequencing (WGS) of 74 commensal gut microbiome isolates with metabolome analysis to discover their metabolic interaction with Salmonella and other antibiotic-resistant pathogens. We evaluated differences in the functional potential of these selected isolates based on WGS annotation profiles. Furthermore, the top altered metabolites in co-culture supernatants of selected commensal gut microbiome isolates were identified including a series of dipeptides and examined for their ability to prevent the growth of various antibiotic-resistant bacteria. Our results provide compelling evidence that the gut microbiome produces metabolites, including the compound class of dipeptides that can potentially be applied for anti-infection medication, especially against antibiotic-resistant pathogens. Our established pipeline for the discovery and validation of bioactive metabolites from the gut microbiome as novel candidates for multidrug-resistant infections represents a new avenue for the discovery of antimicrobial lead structures.

Host genetic regulation of human gut microbial structural variation

Although the impact of host genetics on gut microbial diversity and the abundance of specific taxa is well established1-6, little is known about how host genetics regulates the genetic diversity of gut microorganisms. Here we conducted a meta-analysis of associations between human genetic variation and gut microbial structural variation in 9,015 individuals from four Dutch cohorts. Strikingly, the presence rate of a structural variation segment in Faecalibacterium prausnitzii that harbours an N-acetylgalactosamine (GalNAc) utilization gene cluster is higher in individuals who secrete the type A oligosaccharide antigen terminating in GalNAc, a feature that is jointly determined by human ABO and FUT2 genotypes, and we could replicate this association in a Tanzanian cohort. In vitro experiments demonstrated that GalNAc can be used as the sole carbohydrate source for F. prausnitzii strains that carry the GalNAc-metabolizing pathway. Further in silico and in vitro studies demonstrated that other ABO-associated species can also utilize GalNAc, particularly Collinsella aerofaciens. The GalNAc utilization genes are also associated with the host's cardiometabolic health, particularly in individuals with mucosal A-antigen. Together, the findings of our study demonstrate that genetic associations across the human genome and bacterial metagenome can provide functional insights into the reciprocal host-microbiome relationship.

A key genetic factor governing arabinan utilization in the gut microbiome alleviates constipation

Impaired gastrointestinal motility is associated with gut dysbiosis. Probiotics, such as Bifidobacteria, can improve this bowel disorder; however, efficacy is strain-dependent. We determine that a genetic factor, the abfA cluster governing arabinan utilization, in Bifidobacterium longum impacts treatment efficacy against functional constipation (FC). In mice with FC, B. longum, but not an abfA mutant, improved gastrointestinal transit time, an affect that was dependent upon dietary arabinan. abfA genes were identified in other commensal bacteria, whose effects in ameliorating murine FC were similarly abfA-dependent. In a double-blind, randomized, placebo-controlled clinical trial, supplementation with abfA-cluster-carrying B. longum, but not an abfA-deficient strain, enriched arabinan-utilization residents, increased beneficial metabolites, and improved FC symptoms. Across human cohorts, abfA-cluster abundance can predict FC, and transplantation of abfA cluster-enriched human microbiota to FC-induced germ-free mice improved gut motility. Collectively, these findings demonstrate a role for microbial abfA cluster in ameliorating FC, establishing principles for genomics-directed probiotic therapies.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Microbiota-derived butyrate dampens linaclotide stimulation of the guanylate cyclase C pathway in patient-derived colonoids

BACKGROUND & AIMS

Disorders of gut-brain interaction (DGBI) are complex conditions that result in decreased quality of life and a significant cost burden. Linaclotide, a guanylin cyclase C (GCC) receptor agonist, is approved as a DGBI treatment. However, its efficacy has been limited and variable across DGBI patients. Microbiota and metabolomic alterations are noted in DGBI patients, provoking the hypothesis that the microbiota may impact the GCC response to current therapeutics.

METHODS

Human-derived intestinal organoids were grown from pediatric DGBI, non-IBD colon biopsies (colonoids). Colonoids were treated with 250 nM linaclotide and assayed for cGMP to develop a model of GCC activity. Butyrate was administered to human colonoids overnight at a concentration of 1 mM. Colonoid lysates were analyzed for cGMP levels by ELISA. For the swelling assay, colonoids were photographed pre- and post-treatment and volume was measured using ImageJ. Principal coordinate analyses (PCoA) were performed on the Bray-Curtis dissimilarity and Jaccard distance to assess differences in the community composition of short-chain fatty acid (SCFA) producing microbial species in the intestinal microbiota from pediatric patients with IBS and healthy control samples.

KEY RESULTS

Linaclotide treatment induced a significant increase in [cGMP] and swelling of patient-derived colonoids, demonstrating a human in vitro model of linaclotide-induced GCC activation. Shotgun sequencing analysis of pediatric IBS patients and healthy controls showed differences in the composition of commensal SCFA-producing bacteria. Butyrate exposure significantly dampened linaclotide-induced cGMP levels and swelling in patient-derived colonoids.

CONCLUSIONS & INFERENCES

Patient-derived colonoids demonstrate that microbiota-derived butyrate can dampen human colonic responses to linaclotide. This study supports incorporation of microbiota and metabolomic assessment to improve precision medicine for DGBI patients.

Diet and gut microbial associations in irritable bowel syndrome according to disease subtype

The role of diet and the gut microbiome in the etiopathogenesis of irritable bowel syndrome (IBS) is not fully understood. Therefore, we investigated the interplay between dietary risk factors and gut microbiota in IBS subtypes using a food frequency questionnaire and stool metagenome data from 969 participants aged 18-65 years in the ZOE PREDICT 1 study, an intervention study designed to predict postprandial metabolic responses. We identified individuals with IBS subtype according to the Rome III criteria based on predominant bowel habits during symptom onset: diarrhea (i.e. looser), constipation (i.e. harder), and mixed. Participants with IBS-D (n = 59) consumed more healthy plant-based foods (e.g. whole grains, leafy vegetables) and fiber, while those with IBS-C (n = 49) tended to consume more unhealthy plant-based foods (e.g. refined grains, fruit juice) than participants without IBS (n = 797). Microbial diversity was nominally lower in patients with IBS-D than in participants without IBS or with IBS-C. Using multivariable-adjusted linear regression, we identified specific microbiota variations in IBS subtypes, including slight increases in pro-inflammatory taxa in IBS-C (e.g. Escherichia coli) and loss of strict anaerobes in IBS-D (e.g. Faecalibacterium prausnitzii). Our analysis also revealed intriguing evidence of interactions between diet and Faecalibacterium prausnitzii. The positive associations between fiber and iron intake and IBS-diarrhea were stronger among individuals with a higher relative abundance of Faecalibacterium prausnitzii, potentially driven by carbohydrate metabolic pathways, including the superpathway of β-D-glucuronide and D-glucuronate degradation. In conclusion, our findings suggest subtype-specific variations in dietary habits, gut microbial composition and function, and diet-microbiota interactions in IBS, providing insights into potential microbiome-informed dietary interventions.

Probiotics in Postoperative Pain Management

Postoperative pain is the unpleasant sensory and emotional experience after surgery, its origin being both the inflammatory reaction induced by the surgical trauma on the abdominal wall and the splanchnic pain induced by the activation of nociceptors of the viscera, which are highly sensitive to distension, ischemia, and inflammation. Nowadays, it is well recognized that there is a close relationship between the gut microbiome and pain perception, and that microbiome is highly affected by both anesthesia and surgical manipulation. Thus, efforts to restore the disturbed microbiome via supplementation with beneficial bacteria, namely probiotics, seem to be effective. In this article, the knowledge gained mainly from experimental research on this topic is analyzed, the concluding message being that each probiotic strain works in its own way towards pain relief.

Does the Human Gut Virome Contribute to Host Health or Disease?

The human gastrointestinal (GI) tract harbors eukaryotic and prokaryotic viruses and their genomes, metabolites, and proteins, collectively known as the "gut virome". This complex community of viruses colonizing the enteric mucosa is pivotal in regulating host immunity. The mechanisms involved in cross communication between mucosal immunity and the gut virome, as well as their relationship in health and disease, remain largely unknown. Herein, we review the literature on the human gut virome's composition and evolution and the interplay between the gut virome and enteric mucosal immunity and their molecular mechanisms. Our review suggests that future research efforts should focus on unraveling the mechanisms of gut viruses in human homeostasis and pathophysiology and on developing virus-prompted precision therapies.

Microbial-Related Metabolites May Be Involved in Eight Major Biological Processes and Represent Potential Diagnostic Markers in Gastric Cancer

Metabolites associated with microbes regulate human immunity, inhibit bacterial colonization, and promote pathogenicity. Integrating microbe and metabolome research in GC provides a direction for understanding the microbe-associated pathophysiological process of metabolic changes and disease occurrence. The present study included 30 GC patients with 30 cancerous tissues and paired non-cancerous tissues (NCs) as controls. LC-MS/MS metabolomics and 16S rRNA sequencing were performed to obtain the metabolic and microbial characteristics. Integrated analysis of the microbes and metabolomes was conducted to explore the coexistence relationship between the microbial and metabolic characteristics of GC and to identify microbial-related metabolite diagnostic markers. The metabolic analysis showed that the overall metabolite distribution differed between the GC tissues and the NC tissues: 25 metabolites were enriched in the NC tissues and 42 metabolites were enriched in the GC tissues. The α and β microbial diversities were higher in the GC tissues than in the NC tissues, with 11 differential phyla and 52 differential genera. In the correlation and coexistence integrated analysis, 66 differential metabolites were correlated and coexisted, with specific differential microbes. The microbes in the GC tissue likely regulated eight metabolic pathways. In the efficacy evaluation of the microbial-related differential metabolites in the diagnosis of GC, 12 differential metabolites (area under the curve [AUC] >0.9) exerted relatively high diagnostic efficiency, and the combined diagnostic efficacy of 5 to 6 microbial-related differential metabolites was higher than the diagnostic efficacy of a single feature. Therefore, microbial diversity and metabolite distribution differed between the GC tissues and the NC tissues. Microbial-related metabolites may be involved in eight major metabolism-based biological processes in GC and represent potential diagnostic markers.

Editorial: Faecal microbiota transplantation in IBS-Moving closer or away from success?

This article is linked to Yau et al papers. To view these articles, visit https://doi.org/10.1111/apt.17703 and https://doi.org/10.1111/apt.17729

Application of metabolomics in irritable bowel syndrome in recent 5 years

Irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorders worldwide, characterized by chronic abdominal pain or discomfort and altered bowel habits. To date, the exact pathogenesis of IBS remains elusive, but is clearly multifactorial, including environmental and host factors. However, the management of patients with IBS is challenging and the current diagnostic and therapeutic modalities have unsatisfactory outcomes. Therefore, it is important to develop more effective methods to diagnose IBS early. Metabolomics studies the metabolites most closely related to patient characteristics, which can provide useful clinical biomarkers that can be applied to IBS and may open up new diagnostic approaches. Traditional Chinese medicine (TCM) can play a role in improving symptoms and protecting target organs, but its mechanism needs to be studied in depth. In this review, based on PubMed/MEDLINE and other databases, we searched metabolomics studies related to IBS in the past 5 years, including those related to clinical studies and animal studies, as well as literatures on TCM interventions in IBS, to provide an updated overview of the application of metabolomics to the diagnosis and treatment of IBS and the improvement of IBS by TCM.

"Sentinel or accomplice": gut microbiota and microglia crosstalk in disorders of gut-brain interaction

Abnormal brain-gut interaction is considered the core pathological mechanism behind the disorders of gut-brain interaction (DGBI), in which the intestinal microbiota plays an important role. Microglia are the "sentinels" of the central nervous system (CNS), which participate in tissue damage caused by traumatic brain injury, resist central infection and participate in neurogenesis, and are involved in the occurrence of various neurological diseases. With in-depth research on DGBI, we could find an interaction between the intestinal microbiota and microglia and that they are jointly involved in the occurrence of DGBI, especially in individuals with comorbidities of mental disorders, such as irritable bowel syndrome (IBS). This bidirectional regulation of microbiota and microglia provides a new direction for the treatment of DGBI. In this review, we focus on the role and underlying mechanism of the interaction between gut microbiota and microglia in DGBI, especially IBS, and the corresponding clinical application prospects and highlight its potential to treat DGBI in individuals with psychiatric comorbidities.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

Randomised clinical trial: Faecal microbiota transplantation for irritable bowel syndrome with diarrhoea

BACKGROUND

Faecal microbiota transplantation (FMT) has been shown to improve symptoms in a proportion of patients with irritable bowel syndrome (IBS).

AIM

We performed a randomised trial to assess the efficacy of FMT in patients with IBS.

METHODS

We randomised 56 patients with diarrhoea-predominant IBS 1:1 to FMT or placebo via the duodenal route at baseline and week 4. The primary outcome was > 50 points decrease in IBS severity scoring system (IBS-SSS) score at week 12. Secondary outcomes were improvement in bloating and change in gut microbiota at week 12. After 12-week follow-up, those in the placebo group were assigned to receive open-label FMT.

RESULTS

At week 12, 57.1% in the FMT group and 46.4% in the placebo group achieved the primary endpoint (p = 0.42). More patients receiving FMT than placebo had improvement in bloating (72% vs 30%; p = 0.005). In an open-label extension, 65.2% and 82.4% of patients achieved, respectively, the primary endpoint and improvement in bloating. Faecal microbiome of patients in the FMT group showed a reduction in bacteria like Ruminococcus gnavus and enrichment of bacteria such as Lawsonibacter at week 12, while no change in the placebo group. Functional analyses showed that the hydrogen sulphide-producing pathway decreased in patients who had FMT (p < 0.05) accompanied by a reduction in contributing bacteria. There were no serious adverse events related to FMT.

CONCLUSION

FMT performed twice at an interval of four weeks did not significantly reduce IBS-SSS score. However, more patients had improvement in abdominal bloating, which was associated with a reduction in hydrogen sulphide-producing bacteria. (ClinicalTrials.gov NCT03125564).

16S full-length gene sequencing analysis of intestinal flora in breast cancer patients in Hainan Province

Breast cancer has become the number one cancer in the world, and intestinal flora may be closely linked to it. Geographic location also has an important impact on human intestinal flora. We conducted the first study on the intestinal flora of breast cancer patients and non-breast cancer patients in a tropical region - Hainan Province in China. At the same time, Pacbio platform based on third-generation sequencing was used for the first time to conduct 16S full-length sequencing of fecal microorganism DNA. We completed the species diversity analysis and differential species analysis of the intestinal flora between the two groups, inferred their functional genetic composition and performed functional difference analysis. There were statistically significant differences in alpha diversity between the two groups in Hainan Province. By species composition difference analysis, at the phylum level, Bacteroidales (P = 0.006) and Firmicutes (P = 0.002) was differed between the two groups, and at the genus level, 17 breast cancer-related differential species such as Bacteroides were screened. According to the five grouping methods including ER level, PR level, HER2 status, Ki67 index and histological grade of breast cancer patients, 4, 1, 9, 6, 5 differential microbiota were screened out respectively, which were in total 25 (P < 0.05 for all subgroups) . The functional prediction and difference analysis revealed two functional metabolisms with significant differences between the two groups of microbes (P < 0.05). These results suggest that breast cancer is associated with changes in the composition and function of intestinal flora. These microflora and functional differences may become biomarkers or new targets for diagnosis and treatment of breast cancer.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Gut Dysbiosis in Irritable Bowel Syndrome: A Narrative Review on Correlation with Disease Subtypes and Novel Therapeutic Implications

Irritable bowel syndrome (IBS) is a prevalent functional gastrointestinal disorder characterized by chronic abdominal pain and altered bowel habits. It can be subclassified in different subtypes according to the main clinical manifestation: constipation, diarrhea, mixed, and unclassified. Over the past decade, the role of gut microbiota in IBS has garnered significant attention in the scientific community. Emerging research spotlights the intricate involvement of microbiota dysbiosis in IBS pathogenesis. Studies have demonstrated reduced microbial diversity and stability and specific microbial alterations for each disease subgroup. Microbiota-targeted treatments, such as antibiotics, probiotics, prebiotics, synbiotics, fecal microbiota transplantation, and even diet, offer exciting prospects for managing IBS. However, definitive conclusions are hindered by the heterogeneity of these studies. Further research should focus on elucidating the mechanisms, developing microbiome-based diagnostics, and enabling personalized therapies tailored to an individual's microbiome profile. This review takes a deep dive into the microscopic world inhabiting our guts, and its implications for IBS. Our aim is to elucidate the complex interplay between gut microbiota and each IBS subtype, exploring novel microbiota-targeted treatments and providing a comprehensive overview of the current state of knowledge.

Role of Diet-Microbiome Interaction in Gastrointestinal Disorders and Strategies to Modulate Them with Microbiome-Targeted Therapies

Diet is an important determinant of health and consequently is often implicated in the development of disease, particularly gastrointestinal (GI) diseases, given the high prevalence of meal-related symptoms. The mechanisms underlying diet-driven pathophysiology are not well understood, but recent studies suggest that gut microbiota may mediate the effect of diet on GI physiology. In this review, we focus primarily on two distinct GI diseases where the role of diet has been best studied: irritable bowel syndrome and inflammatory bowel disease. We discuss how the concurrent and sequential utilization of dietary nutrients by the host and gut microbiota determines the eventual bioactive metabolite profiles in the gut and the biological effect of these metabolites on GI physiology. We highlight several concepts that can be gleaned from these findings, such as how distinct effects of an individual metabolite can influence diverse GI diseases, the effect of similar dietary interventions on multiple disease states, and the need for extensive phenotyping and data collection to help make personalized diet recommendations.

Gut microbiota-derived tryptamine and phenethylamine impair insulin sensitivity in metabolic syndrome and irritable bowel syndrome

The incidence of metabolic syndrome is significantly higher in patients with irritable bowel syndrome (IBS), but the mechanisms involved remain unclear. Gut microbiota is causatively linked with the development of both metabolic dysfunctions and gastrointestinal disorders, thus gut dysbiosis in IBS may contribute to the development of metabolic syndrome. Here, we show that human gut bacterium Ruminococcus gnavus-derived tryptamine and phenethylamine play a pathogenic role in gut dysbiosis-induced insulin resistance in type 2 diabetes (T2D) and IBS. We show levels of R. gnavus, tryptamine, and phenethylamine are positively associated with insulin resistance in T2D patients and IBS patients. Monoassociation of R. gnavus impairs insulin sensitivity and glucose control in germ-free mice. Mechanistically, treatment of R. gnavus-derived metabolites tryptamine and phenethylamine directly impair insulin signaling in major metabolic tissues of healthy mice and monkeys and this effect is mediated by the trace amine-associated receptor 1 (TAAR1)-extracellular signal-regulated kinase (ERK) signaling axis. Our findings suggest a causal role for tryptamine/phenethylamine-producers in the development of insulin resistance, provide molecular mechanisms for the increased prevalence of metabolic syndrome in IBS, and highlight the TAAR1 signaling axis as a potential therapeutic target for the management of metabolic syndrome induced by gut dysbiosis.

Glucocorticoid receptor-mediated Nr1d1 chromatin circadian misalignment in stress-induced irritable bowel syndrome

Stress-elevated glucocorticoids cause circadian disturbances and gut-brain axis (GBA) disorders, including irritable bowel syndrome (IBS). We hypothesized that the glucocorticoid receptor (GR/NR3C1) might cause chromatin circadian misalignment in the colon epithelium. We observed significantly decreased core circadian gene Nr1d1 in water avoidance stressed (WAS) BALB/c colon epithelium, like in IBS patients. WAS decreased GR binding at the Nr1d1 promoter E-box (enhancer box), and GR could suppress Nr1d1 via this site. Stress also altered GR binding at the E-box sites along the Ikzf3-Nr1d1 chromatin and remodeled circadian chromatin 3D structures, including Ikzf3-Nr1d1 super-enhancer, Dbp, and Npas2. Intestinal deletion of Nr3c1 specifically abolished these stress-induced transcriptional alternations relevant to IBS phenotypes in BALB/c mice. GR mediated Ikzf3-Nr1d1 chromatin disease related circadian misalignment in stress-induced IBS animal model. This animal model dataset suggests that regulatory SNPs of human IKZF3-NR1D1 transcription through conserved chromatin looping have translational potential based on the GR-mediated circadian-stress crosstalk.

A protease activity-based machine-learning approach as a complementary tool for conventional diagnosis of diarrhea-predominant irritable bowel syndrome

Irritable bowel syndrome (IBS) has no clinically accepted biomarkers even though it affects a large number of individuals worldwide. To address this lack of understanding, we evaluated peptidase activity in fecal samples from 35 patients with diarrheal IBS without symptom exacerbation (IBS-n) and 35 healthy subjects using a library of 384 fluorescent enzymatic substrate probes. IBS-n patients had high trypsin-like peptidase activity for cleavage of C-terminal lysine and arginine residues and low elastase-like activity for cleavage of C-terminal serine and glycine residues. These fluorescent probe library data, together with diagnostic machine-learning techniques, were able to accurately predict IBS-n. This approach can be used to diagnose diseases where no clinically accepted biomarkers exist, in which fecal enzyme activity is altered and also suggests that the development of new therapies targeting enzyme activities is possible.