Alterations of the human gut microbiome in liver cirrhosis

Variability and bias in microbiome metagenomic sequencing: an interlaboratory study comparing experimental protocols

Several studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5 × human stool samples and 2 × mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. A total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. This study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

Nonalcoholic Fatty Liver Disease: Changes in Gut Microbiota and Blood Lipids

Background and Aims

The global prevalence of nonalcoholic fatty liver disease (NAFLD) is 25%. This study aimed to explore differences in the gut microbial community and blood lipids between normal livers and those affected by NAFLD using 16S ribosomal deoxyribonucleic acid sequencing.

Methods

Gut microbiome profiles of 40 NAFLD and 20 non-NAFLD controls were analyzed. Information about four blood lipids and 13 other clinical features was collected. Patients were divided into three groups by ultrasound and FibroScan, those with a normal liver, mild FL (FL1), and moderate-to-severe FL (FL2). FL1 and FL2 patients were divided into two groups, those with either hyperlipidemia or non-hyperlipidemia based on their blood lipids. Potential keystone species within the groups were identified using univariate analysis and a specificity-occupancy plot. Significant difference in biochemical parameters ion NAFLD patients and healthy individuals were identified by detrended correspondence analysis and canonical correspondence analysis.

Results

Decreased gut bacterial diversity was found in patients with NAFLD. Firmicutes/Bacteroidetes decreased as NAFLD progressed. Faecalibacterium and Ruminococcus 2 were the most representative fatty-related bacteria. Glutamate pyruvic transaminase, aspartate aminotransferase, and white blood cell count were selected as the most significant biochemical indexes. Calculation of areas under the curve identified two microbiomes combined with the three biochemical indexes that identified normal liver and FL2 very well but performed poorly in diagnosing FL1.

Conclusions

Faecalibacterium and Ruminococcus 2, combined with glutamate pyruvic transaminase, aspartate aminotransferase, and white blood cell count distinguished NAFLD. We speculate that regulating the health of gut microbiota may release NAFLD, in addition to providing new targets for clinicians to treat NAFLD.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Metagenomic data of microbiota in mangrove soil from Lukut River, Malaysia

The mangrove ecosystem contains sediment microorganisms that play a crucial part in the decomposition of organic matter and the cycling of water and nutrients in the mangrove. Here we present the metagenomics whole genome shotgun (mWGS) sequence data analysis from three soil samples that were collected at the freshwater riverine mangrove at Lukut River, Negeri Sembilan, Malaysia. Data analysis shows different distributions of bacteria of the genera Bradyrhizobium, Methyloceanibacter and Desulfobacteaceae were detected in soil samples collected at freshwater riverine mangrove. In the data analysis, we report the existence of a large number of Carbohydrate-Active genes in metagenomes collected from mangrove soil. An in-depth exploration of functional annotation analysis based on the KEGG database also showed that the most abundant genes found in these three soils are those that function in carbon fixation pathways, followed by methane, nitrogen, sulfur metabolisms, atrazine and dioxin degradations.

Gut-Liver Axis Dysregulation in Portal Hypertension: Emerging Frontiers

Portal hypertension (PH) is a complex clinical challenge with severe complications, including variceal bleeding, ascites, hepatic encephalopathy, and hepatorenal syndrome. The gut microbiota (GM) and its interconnectedness with human health have emerged as a captivating field of research. This review explores the intricate connections between the gut and the liver, aiming to elucidate how alterations in GM, intestinal barrier function, and gut-derived molecules impact the development and progression of PH. A systematic literature search, following PRISMA guidelines, identified 12 original articles that suggest a relationship between GM, the gut-liver axis, and PH. Mechanisms such as dysbiosis, bacterial translocation, altered microbial structure, and inflammation appear to orchestrate this relationship. One notable study highlights the pivotal role of the farnesoid X receptor axis in regulating the interplay between the gut and liver and proposes it as a promising therapeutic target. Fecal transplantation experiments further emphasize the pathogenic significance of the GM in modulating liver maladies, including PH. Recent advancements in metagenomics and metabolomics have expanded our understanding of the GM's role in human ailments. The review suggests that addressing the unmet need of identifying gut-liver axis-related metabolic and molecular pathways holds potential for elucidating pathogenesis and directing novel therapeutic interventions.

Dynamic changes of Bacterial Microbiomes in Oropharynx during Infection and Recovery of COVID-19 Omicron Variant

Oropharyngeal microbiomes play a significant role in the susceptibility and severity of COVID-19, yet the role of these microbiomes play for the development of COVID-19 Omicron variant have not been reported. A total of 791 pharyngeal swab samples were prospectively included in this study, including 297 confirmed cases of Omicron variant (CCO), 222 confirmed case of Omicron who recovered (CCOR), 73 confirmed cases of original strain (CCOS) and 199 healthy controls (HC). All samples completed MiSeq sequencing. The results showed that compared with HC, conditional pathogens increased in CCO, while acid-producing bacteria decreased. Based on six optimal oropharyngeal operational taxonomy units (OTUs), we constructed a marker microbial classifier to distinguish between patients with Omicron variant and healthy people, and achieved high diagnostic efficiency in both the discovery queue and the verification queue. At same time, we introduced a group of cross-age infection verification cohort and Omicron variant subtype XBB.1.5 branch, which can be accurately distinguished by this diagnostic model. We also analyzed the characteristics of oropharyngeal microbiomes in two subgroups of Omicron disease group-severity of infection and vaccination times, and found that the change of oropharyngeal microbiomes may affect the severity of the disease and the efficacy of the vaccine. In addition, we found that some genera with significant differences gradually increased or decreased with the recovery of Omicron variant infection. The results of Spearman analysis showed that 27 oropharyngeal OTUs were closely related to 6 clinical indexes in CCO and HC. Finally, we found that the Omicron variant had different characterization of oropharyngeal microbiomes from the original strain. Our research characterizes oropharyngeal microbiomes of Omicron variant cases and rehabilitation cases, successfully constructed and verified the non-invasive diagnostic model of Omicron variant, described the correlation between microbial OTUs and clinical indexes. It was found that the infection of Omicron variant and the infection of original strain have different characteristics of oropharyngeal microbiomes.

Deep learning methods in metagenomics: a review

The ever-decreasing cost of sequencing and the growing potential applications of metagenomics have led to an unprecedented surge in data generation. One of the most prevalent applications of metagenomics is the study of microbial environments, such as the human gut. The gut microbiome plays a crucial role in human health, providing vital information for patient diagnosis and prognosis. However, analysing metagenomic data remains challenging due to several factors, including reference catalogues, sparsity and compositionality. Deep learning (DL) enables novel and promising approaches that complement state-of-the-art microbiome pipelines. DL-based methods can address almost all aspects of microbiome analysis, including novel pathogen detection, sequence classification, patient stratification and disease prediction. Beyond generating predictive models, a key aspect of these methods is also their interpretability. This article reviews DL approaches in metagenomics, including convolutional networks, autoencoders and attention-based models. These methods aggregate contextualized data and pave the way for improved patient care and a better understanding of the microbiome's key role in our health.

Rifaximin treatment shapes a unique metagenome-metabolism network in patients with decompensated cirrhosis

BACKGROUND

Patients with decompensated cirrhosis face poor prognosis and increased mortality risk. Rifaximin, a non-absorbable antibiotic, has been shown to have beneficial effects in preventing complications and improving survival in these patients. However, the underlying mechanisms of rifaximin's effects remain unclear.

METHODS

We obtained fecal samples from decompensated cirrhotic patients undergoing rifaximin treatment and controls, both at baseline and after 6 months of treatment. Shotgun metagenome sequencing profiled the gut microbiome, and untargeted metabolomics analyzed fecal metabolites. Linear discriminant and partial least squares discrimination analyses were used to identify differing species and metabolites between rifaximin-treated patients and controls.

RESULTS

Forty-two patients were enrolled and divided into two groups (26 patients in the rifaximin group and 16 patients in the control group). The gut microbiome's beta diversity changed in the rifaximin group but remained unaffected in the control group. We observed 44 species with reduced abundance in the rifaximin group, including Streptococcus_salivarius, Streptococcus_vestibularis, Haemophilus_parainfluenzae, etc. compared to only four in the control group. Additionally, six species were enriched in the rifaximin group, including Eubacterium_sp._CAG:248, Prevotella_sp._CAG:604, etc., and 14 in the control group. Furthermore, rifaximin modulated different microbial functions compared to the control. Seventeen microbiome-related metabolites were altered due to rifaximin, while six were altered in the control group.

CONCLUSION

Our study revealed distinct microbiome-metabolite networks regulated by rifaximin intervention in patients with decompensated cirrhosis. These findings suggest that targeting these specific metabolites or related bacteria might be a potential therapeutic strategy for decompensated cirrhosis.

Comprehensive bibliometric and visualized analysis of research on gut-liver axis published from 1998 to 2022

Background

The concept of the gut-liver axis was proposed by Marshall in 1998, and since then, this hypothesis has been gradually accepted by the academic community. Many publications have been published on the gut-liver axis, making it important to assess the scientific implications of these studies and the trends in this field.

Methods

Publications were retrieved from the Web of Science Core Collection. Microsoft Excel, CiteSpace, VOSviewer, and Scimago Graphica software were used for bibliometric analysis.

Results

A total of 776 publications from the Web of Science core database were included in this study. In the past 25 years, the number of publications on the gut-liver axis has shown an upward trend, particularly in the past 3 years (2020-2022). China had the highest number of publications (267 articles, 34.4%). However, the United States was at the top regarding influence and international cooperation in this field. The University of California San Diego had contributed the most publications. Suk, Ki Tae and Schnabl, Bernd were tied for the first rank in most publications. Thematic hotspots and frontiers were focused on gut microbiota, microbial metabolite, intestinal permeability, bacterial translocation, bile acid, non-alcoholic steatohepatitis, and alcoholic liver disease.

Conclusion

Our study is the first bibliometric analysis of literature using visualization software to present the current research status of the gut-liver axis over the past 25 years. The damage and repair of intestinal barrier function, as well as the disruption of gut microbiota and host metabolism, should be a focus of attention. This study can provide a reference for later researchers to understand the global research trends, hotspots, and frontiers in this field.

phylaGAN: data augmentation through conditional GANs and autoencoders for improving disease prediction accuracy using microbiome data

MOTIVATION

Research is improving our understanding of how the microbiome interacts with the human body and its impact on human health. Existing machine learning methods have shown great potential in discriminating healthy from diseased microbiome states. However, Machine Learning based prediction using microbiome data has challenges such as, small sample size, imbalance between cases and controls and high cost of collecting large number of samples. To address these challenges, we propose a deep learning framework phylaGAN to augment the existing datasets with generated microbiome data using a combination of conditional generative adversarial network (C-GAN) and autoencoder. Conditional generative adversarial networks train two models against each other to compute larger simulated datasets that are representative of the original dataset. Autoencoder maps the original and the generated samples onto a common subspace to make the prediction more accurate.

RESULTS

Extensive evaluation and predictive analysis was conducted on two datasets, T2D study and Cirrhosis study showing an improvement in mean AUC using data augmentation by 11% and 5% respectively. External validation on a cohort classifying between obese and lean subjects, with a smaller sample size provided an improvement in mean AUC close to 32% when augmented through phylaGAN as compared to using the original cohort. Our findings not only indicate that the generative adversarial networks can create samples that mimic the original data across various diversity metrics, but also highlight the potential of enhancing disease prediction through machine learning models trained on synthetic data.

AVAILABILITY AND IMPLEMENTATION

https://github.com/divya031090/phylaGAN.

Approaching the Sarcopenic Patient with Nonalcoholic Steatohepatitis-related Cirrhosis

Sarcopenia is a well-known complication of chronic liver disease (CLD), and it is almost always observed in patients with cirrhosis, at least in those with decompensated disease. Since nonalcoholic fatty liver disease (NAFLD), recently renamed metabolic dysfunction-associated steatotic liver disease (MASLD), is becoming the leading cause of end-stage liver disease, a new scenario characterized by the frequent coexistence of NAFLD, obesity, and sarcopenia is emerging. Although it is not yet resolved whether the bidirectional relationship between sarcopenia and NAFLD subtends causal determinants, it is clear that the interaction of these two conditions is associated with an increased risk of poor outcomes. Notably, during the course of CLD, deregulation of the liver-muscle-adipose tissue axis has been described. Unfortunately, owing to the lack of properly designed studies, specific therapeutic guidelines for patients with sarcopenia in the context of NAFLD-related CLD have not yet been defined. Strategies aimed to induce the loss of fat mass together with the maintenance of lean body mass seem most appropriate. This can be achieved by properly designed diets integrated with specific nutritional supplementations and accompanied by adequate physical exercise. Future studies aiming to add to the knowledge of the correct assessment and approach to sarcopenia in the context of NAFLD-related CLD are eagerly awaited.

Metagenomic insight into the pathogenic-related characteristics and resistome profiles within microbiome residing on the Angkor sandstone monuments in Cambodia

To reveal the characteristics of indigenous microbiome including the pathogenic-related ones on Angkor monuments in Cambodia and the distribution pattern of resistome at different locations, several sites, namely Angkor Wat, Bayon of Angkor Thom, and Prasat Preah Vihear with different exposure levels to tourists were selected to conduct the metagenomic analysis in this study. The general characteristics of the microbiome on these monuments were revealed, and the association between the environmental geo-ecological feature and the indigenous microbiome was delineated. The most common microbial groups included 6 phyla, namely Acidobacteria, Actinobacteria, Gemmatimonadetes, Nitrospirae, Proteobacteria and Verrucomicrobia on the monuments, but Firmicutes and Chlamydiae were the most dominant phyla found in bats droppings. The taxonomic family of Chitinophagaceae could serve as a signature microbial group for Preah Vihear, the less visited site. More importantly, the pathogenic-related characteristics of the microbiome residing on Angkor monuments were uncovered. A set of specific antibiotic resistance genes (ARGs) with cross-niches dispersal capacity (between the environmental microbiome and the microbiome within warm blood fauna) was identified to be high by the source tracking analysis based on ARGs profile varies in this study. Among the 10 ARG-types detected in this study, 6 of them are confined to resistance mechanism of antibiotic efflux-pump. The findings of this study provide new a new direction on public health management and implication globally at archaeological sites for tourism.

Piperine promotes PI3K/AKT/mTOR-mediated gut-brain autophagy to degrade α-Synuclein in Parkinson's disease rats

ETHNOPHARMACOLOGICAL RELEVANCE

Piper longum L., a medicinal and food homologous herb, has a traditional history of use in treating gastrointestinal and neurological disorders. Piperine (PIP) the main alkaloid of P. longum, exists neuroprotective effects on various animal models of Parkinson's disease (PD). Nevertheless, the underlying mechanism, particularly the role of PIP in promoting gut-brain autophagy for α-Synuclein (α-Syn) degradation in PD, remains incompletely understood.

AIM OF THE STUDY

To explore the role of PIP in regulating the gut-brain autophagy signaling pathway to reduce α-Syn levels in both the colon and substantia nigra (SN) of PD model rats.

MATERIALS AND METHODS

Behavioral experiments were conducted to assess the impact of PIP on 6-hydroxydopamine (6-OHDA)-induced PD rats. The intestinal microbiome composition and intestinal metabolites were analyzed by metagenomics and GC-MS/MS. The auto-phagosomes were visualized by transmission electron microscopy. Immunohistochemistry, immunofluorescence, and western blotting were performed to assess the levels of tyrosine hydroxylase (TH), α-Syn, LC3II/LC3I, p62, and the PI3K/AKT/mTOR pathway in both the SN and colon of the rats. The pathway-related inhibitor and agonist were used to verify the autophagy mechanism in the SH-SY5Y cells overexpressing A53T mutant α-Syn (A53T-α-Syn).

RESULTS

PIP improved autonomic movement and gastrointestinal dysfunctions, reduced α-Syn aggregation and attenuated the loss of dopaminergic neurons in 6-OHDA-induced PD rats. After oral administration of PIP, the radio of LC3II/LC3I increased and the expression of p62 was degraded, as well as the phosphorylation levels of PI3K, AKT and mTOR decreased in the SN and colon of rats. The effect of PIP on reducing A53T-α-Syn through the activation of the PI3K/AKT/mTOR-mediated autophagy pathway was further confirmed in A53T-α-Syn transgenic SH-SY5Y cells. This effect could be inhibited by the autophagy inhibitor bafilomycin A1 and the PI3K agonist 740 Y-P.

CONCLUSIONS

Our findings suggested that PIP could protect neurons by activating autophagy to degrade α-Syn in the SN and colon, which were related to the suppression of PIP on the activation of PI3K/AKT/mTOR signaling pathway.

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.

Effects of Lactobacillus paracasei N1115 on gut microbial imbalance and liver function in patients with hepatitis B-related cirrhosis

BACKGROUND

Hepatitis B cirrhosis (HBC) is a chronic disease characterized by irreversible diffuse liver damage and aggravated by intestinal microbial imbalance and metabolic dysfunction. Although the relationship between certain single probiotics and HBC has been explored, the impact of the complex ready-to-eat Lactobacillus paracasei N1115 (LP N1115) supplement on patients with HBC has not been determined.

AIM

To compare the changes in the microbiota, inflammatory factor levels, and liver function before and after probiotic treatment in HBC patients.

METHODS

This study included 160 HBC patients diagnosed at the General Hospital of Ningxia Medical University between October 2018 and December 2020. Patients were randomly divided into an intervention group that received LP N1115 supplementation and routine treatment and a control group that received routine treatment only. Fecal samples were collected at the onset and conclusion of the 12-wk intervention period. The structure of the intestinal microbiota and the levels of serological indicators, such as liver function and inflammatory factors, were assessed.

RESULTS

Following LP N1115 intervention, the intestinal microbial diversity significantly increased in the intervention group (P < 0.05), and the structure of the intestinal microbiota was characterized by an increase in the proportions of probiotic microbes and a reduction in harmful bacteria. Additionally, the intervention group demonstrated notable improvements in liver function indices and significantly lower levels of inflammatory factors (P < 0.05).

CONCLUSION

LP N1115 is a promising treatment for ameliorating intestinal microbial imbalance in HBC patients by modulating the structure of the intestinal microbiota, improving liver function, and reducing inflammatory factor levels.

The gut microbiome of Baka forager-horticulturalists from Cameroon is optimized for wild plant foods

The human gut microbiome is losing biodiversity, due to the "microbiome modernization process" that occurs with urbanization. To keep track of it, here we applied shotgun metagenomics to the gut microbiome of the Baka, a group of forager-horticulturalists from Cameroon, who combine hunting and gathering with growing a few crops and working for neighboring Bantu-speaking farmers. We analyzed the gut microbiome of individuals with different access to and use of wild plant and processed foods, to explore the variation of their gut microbiome along the cline from hunter-gatherer to agricultural subsistence patterns. We found that 26 species-level genome bins from our cohort were pivotal for the degradation of the wild plant food substrates. These microbes include Old Friend species and are encoded for genes that are no longer present in industrialized gut microbiome. Our results highlight the potential relevance of these genes to human biology and health, in relation to lifestyle.

Multi-omics reveals the mechanism of rumen microbiome and its metabolome together with host metabolome participating in the regulation of milk production traits in dairy buffaloes

Recently, it has been discovered that certain dairy buffaloes can produce higher milk yield and milk fat yield under the same feeding management conditions, which is a potential new trait. It is unknown to what extent, the rumen microbiome and its metabolites, as well as the host metabolism, contribute to milk yield and milk fat yield. Therefore, we will analyze the rumen microbiome and host-level potential regulatory mechanisms on milk yield and milk fat yield through rumen metagenomics, rumen metabolomics, and serum metabolomics experiments. Microbial metagenomics analysis revealed a significantly higher abundance of several species in the rumen of high-yield dairy buffaloes, which mainly belonged to genera, such as Prevotella, Butyrivibrio, Barnesiella, Lachnospiraceae, Ruminococcus, and Bacteroides. These species contribute to the degradation of diets and improve functions related to fatty acid biosynthesis and lipid metabolism. Furthermore, the rumen of high-yield dairy buffaloes exhibited a lower abundance of methanogenic bacteria and functions, which may produce less methane. Rumen metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, including lipids, carbohydrates, and organic acids, as well as volatile fatty acids (VFAs), such as acetic acid and butyric acid. Meanwhile, several Prevotella, Butyrivibrio, Barnesiella, and Bacteroides species were significantly positively correlated with these metabolites. Serum metabolome analysis showed that high-yield dairy buffaloes had significantly higher concentrations of metabolites, mainly lipids and organic acids. Meanwhile, several Prevotella, Bacteroides, Barnesiella, Ruminococcus, and Butyrivibrio species were significantly positively correlated with these metabolites. The combined analysis showed that several species were present, including Prevotella.sp.CAG1031, Prevotella.sp.HUN102, Prevotella.sp.KHD1, Prevotella.phocaeensis, Butyrivibrio.sp.AE3009, Barnesiella.sp.An22, Bacteroides.sp.CAG927, and Bacteroidales.bacterium.52-46, which may play a crucial role in rumen and host lipid metabolism, contributing to milk yield and milk fat yield. The "omics-explainability" analysis revealed that the rumen microbial composition, functions, metabolites, and serum metabolites contributed 34.04, 47.13, 39.09, and 50.14%, respectively, to milk yield and milk fat yield. These findings demonstrate how the rumen microbiota and host jointly affect milk production traits in dairy buffaloes. This information is essential for developing targeted feeding management strategies to improve the quality and yield of buffalo milk.

Pseudomonas-associated bacteria play a key role in obtaining nutrition from bamboo for the giant panda (Ailuropoda melanoleuca)

Gut microbiota plays a vital role in obtaining nutrition from bamboo for giant pandas. However, low cellulase activity has been observed in the panda's gut. Besides, no specific pathway has been implicated in lignin digestion by gut microbiota of pandas. Therefore, the mechanism by which they obtain nutrients is still controversial. It is necessary to elucidate the precise pathways employed by gut microbiota of pandas to degrade lignin. Here, the metabolic pathways for lignin degradation in pandas were explored by comparing 209 metagenomic sequencing data from wild species with different feeding habits. Lignin degradation central pathways, including beta-ketoadipate and homogentisate pathway, were enriched in the gut of wild bamboo-eating pandas. The gut microbiome of wild bamboo-eating specialists was enriched with genes from pathways implicated in degrading ferulate and p-coumarate into acetyl-CoA and succinyl-CoA, which can potentially provide the raw materials for metabolism in pandas. Specifically, Pseudomonas, as the most dominant gut bacteria genus, was found to be the main bacteria to provide genes involved in lignin or lignin derivative degradation. Herein, three Pseudomonas-associated strains isolated from the feces of wild pandas showed the laccase, lignin peroxidase, and manganese peroxidase activity and extracellular lignin degradation ability in vitro. A potential mechanism for pandas to obtain nutrition from bamboo was proposed based on the results. This study provides novel insights into the adaptive evolution of pandas from the perspective of lignin metabolism.

IMPORTANCE

Although giant pandas only feed on bamboo, the mechanism of lignin digestion in pandas is unclear. Here, the metabolic pathways for lignin degradation in wild pandas were explored by comparing gut metagenomic from species with different feeding habits. Results showed that lignin degradation central pathways, including beta-ketoadipate and homogentisate pathway, were enriched in the gut of wild bamboo-eating pandas. Genes from pathways involved in degrading ferulate and p-coumarate via beta-ketoadipate pathway were also enriched in bamboo-eating pandas. The final products of the above process, such as acetyl-CoA, can potentially provide the raw materials for metabolism in pandas. Specifically, Pseudomonas, as the most dominant gut bacteria genus, mainly provides genes involved in lignin degradation. Herein, Pseudomonas-associated strains isolated from the feces of pandas could degrade extracellular lignin. These findings suggest that gut microbiome of pandas is crucial in obtaining nutrition from lignin via Pseudomonas, as the main lignin-degrading bacteria.

The role of microbiota in gastric cancer: A comprehensive review

BACKGROUND

Gastric cancer (GC) continues to pose a significant global threat in terms of cancer-related fatalities. Despite notable advancements in medical research and therapies, further investigation is warranted to elucidate its underlying etiology and risk factors. Recent times have witnessed an escalated emphasis on comprehending the role of the microbiota in cancer development.

METHODS

This review briefly delves into recent developments in microbiome-related research pertaining to gastric cancer.

RESULTS

According to studies, the microbiota can influence GC growth by inciting inflammation, disrupting immunological processes, and generating harmful microbial metabolites. Furthermore, there is ongoing research into how the microbiome can impact a patient's response to chemotherapy and immunotherapy.

CONCLUSION

The utilization of the microbiome for detecting, preventing, and managing stomach cancer remains an active area of exploration.

Porphyromonas gingivalis as a promotor in the development of the alcoholic liver disease via ferroptosis

Alcoholic liver disease (ALD) is a liver disease caused by heavy drinking. Porphyromonas gingivalis (P.g), a major cause of periodontitis, whose antibodies are elevated in severe ALD patients in the plasma. The purpose of this study is to further study the role and the molecular mechanism of P.g in the progress of ALD. In this study, saliva of patients with ALD was collected. Then, an animal model of ALD with oral P.g administration was established, pathology of liver and spleen, intestinal microorganisms and metabolites were analyzed. The molecular mechanism of P.g on ALD was analyzed in vitro. ALD and intestinal microflora and metabolite changes were observed more serious in the alcohol and P.g groups than the alcohol group. Moreover, ferroptosis was aggravated by P.g in the liver. Meanwhile, P.g promoted ferroptosis accomplication with alcohol in vitro, which can be reversed by ferroptosis inhibitors. In conclusion, P.g aggravates ALD through exacerbation gut microbial metabolic disorder in mice with alcohol, which maybe depend on ferroptosis activation in hepatocytes. The study provides a new strategy for prevention and treatment of ALD by improving the oral micro-environment.

Liver cirrhosis and antibiotic therapy but not TIPS application leads to a shift of the intestinal bacterial communities: A controlled, prospective study

OBJECTIVES

The gut-liver axis is discussed to play an important role in hepatic cirrhosis. Decompensated liver cirrhosis is associated with portal hypertension, which can lead to a variety of complications. Transjugular intrahepatic portosystemic shunt (TIPS) is an established treatment option for the complications of portal hypertension. In this study we focused on the effect of TIPS on intestinal microbial composition in cirrhotic patients.

METHODS

Thirty patients with liver cirrhosis were compared to 18 healthy adults. Seventeen patients with cirrhosis and portal hypertension received a TIPS. Clinical characteristics, including age, sex, and liver function measured with a Child-Pugh score and model for end-stage liver disease score, were obtained. Intestinal microbial composition was assessed via 16S rRNA gene amplicon sequencing from stool probes before and after TIPS.

RESULTS

TIPS led to a reduction of hepatic venous pressure gradient. However, TIPS did not cause a shift in the intestinal bacterial communities. Independent from the application of TIPS, antibiotic therapy was associated with a significant difference in the intestinal bacterial microbiota and also a reduced α-diversity. In addition, a significant difference was observed in the intestinal bacterial composition between patients with liver cirrhosis and healthy controls.

CONCLUSION

The presence of liver cirrhosis and the use of antibiotic therapy, but not the application of TIPS, were associated with a significant shift of the intestinal bacterial communities, showing a high impact on the microbiota of patients with liver cirrhosis.

Effects of 1-kestose on microbiome changes caused by vonoprazan: a randomized, double-blind, placebo-controlled pilot study

BACKGROUND AND AIM

Potassium-competitive acid blockers more strongly suppress the gastric acid barrier than proton pump inhibitors and cause dysbiosis. However, preventive measures in this regard have not been established. We aimed to evaluate whether 1-kestose, a known prebiotic, was effective at alleviating dysbiosis caused by potassium-competitive acid blockers.

METHODS

Patients scheduled to undergo endoscopic resection for superficial gastroduodenal tumors were enrolled and randomized 1:1 to receive either 1-kestose or placebo. All patients were started on potassium-competitive acid blocker (vonoprazan 20 mg/day) and took 1-kestose 10 g/day or placebo (maltose) 5 g/day for 8 weeks. The primary outcome was the effect of 1-kestose on potassium-competitive acid blocker-induced alterations in the microbiome. The fecal microbiome was analyzed before and after potassium-competitive acid blocker treatment via MiSeq (16S rRNA gene V3-V4 region).

RESULTS

Forty patients were enrolled, and 16 in each group were analyzed. In the placebo group, the Simpson index, an alpha diversity, was significantly decreased and relative abundance of Streptococcus was significantly increased by 1.9-fold. In the kestose group, the Simpson index did not change significantly and relative abundance of Streptococcus increased 1.3-fold, but this was not a significant change. In both groups, no adverse events occurred, ulcers were well healed, and pretreatment and posttreatment short-chain fatty acid levels did not differ.

CONCLUSIONS

The potassium-competitive acid blocker caused dysbiosis in the placebo group; this effect was prevented by 1-kestose. Thus, 1-kestose may be useful in dysbiosis treatment.

Microbiota modulation by dietary oat beta-glucan prevents steatotic liver disease progression

Background & Aims

Changes in gut microbiota in metabolic dysfunction-associated steatotic liver disease (MASLD) are important drivers of disease progression towards fibrosis. Therefore, reversing microbial alterations could ameliorate MASLD progression. Oat beta-glucan, a non-digestible polysaccharide, has shown promising therapeutic effects on hyperlipidemia associated with MASLD, but its impact on gut microbiota and most importantly MASLD-related fibrosis remains unknown.

Methods

We performed detailed metabolic phenotyping, including assessments of body composition, glucose tolerance, and lipid metabolism, as well as comprehensive characterization of the gut-liver axis in a western-style diet (WSD)-induced model of MASLD and assessed the effect of a beta-glucan intervention on early and advanced liver disease. Gut microbiota were modulated using broad-spectrum antibiotic treatment.

Results

Oat beta-glucan supplementation did not affect WSD-induced body weight gain or glucose intolerance and the metabolic phenotype remained largely unaffected. Interestingly, oat beta-glucan dampened MASLD-related inflammation, which was associated with significantly reduced monocyte-derived macrophage infiltration and fibroinflammatory gene expression, as well as strongly reduced fibrosis development. Mechanistically, this protective effect was not mediated by changes in bile acid composition or signaling, but was dependent on gut microbiota and was lost upon broad-spectrum antibiotic treatment. Specifically, oat beta-glucan partially reversed unfavorable changes in gut microbiota, resulting in an expansion of protective taxa, including Ruminococcus, and Lactobacillus followed by reduced translocation of Toll-like receptor ligands.

Conclusions

Our findings identify oat beta-glucan as a highly efficacious food supplement that dampens inflammation and fibrosis development in diet-induced MASLD. These results, along with its favorable dietary profile, suggest that it may be a cost-effective and well-tolerated approach to preventing MASLD progression and should be assessed in clinical studies.

Impact and Implications

Herein, we investigated the effect of oat beta-glucan on the gut-liver axis and fibrosis development in a mouse model of metabolic dysfunction-associated steatotic liver disease (MASLD). Beta-glucan significantly reduced inflammation and fibrosis in the liver, which was associated with favorable shifts in gut microbiota that protected against bacterial translocation and activation of fibroinflammatory pathways. Together, oat beta-glucan may be a cost-effective and well-tolerated approach to prevent MASLD progression and should be assessed in clinical studies.

Double Trouble: How Microbiome Dysbiosis and Mitochondrial Dysfunction Drive Non-Alcoholic Fatty Liver Disease and Non-Alcoholic Steatohepatitis

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are closely related liver conditions that have become more prevalent globally. This review examines the intricate interplay between microbiome dysbiosis and mitochondrial dysfunction in the development of NAFLD and NASH. The combination of these two factors creates a synergistic situation referred to as "double trouble", which promotes the accumulation of lipids in the liver and the subsequent progression from simple steatosis (NAFLD) to inflammation (NASH). Microbiome dysbiosis, characterized by changes in the composition of gut microbes and increased intestinal permeability, contributes to the movement of bacterial products into the liver. It triggers metabolic disturbances and has anti-inflammatory effects. Understanding the complex relationship between microbiome dysbiosis and mitochondrial dysfunction in the development of NAFLD and NASH is crucial for advancing innovative therapeutic approaches that target these underlying mechanisms.

Lignite-steel slag constructed wetland with multi-functionality and effluent reuse

Constructed wetlands (CWs) are widely used to treat wastewater, while innovative studies are needed to support resource conservation, enhance multi-functionality, and improve the effectiveness of effluent usage. This study assessed the potential of CW's multiple functions by combining low-rank coal (lignite) and industrial waste (steel slag) in different configurations as CW substrates. The results of scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and metagenomic sequencing showed that the experimental treatment with lignite and steel slag mixtures had the highest multi-functionality, including efficient nutrient removal and carbon sequestration, as well as hydroponic crop production. Lignite and steel slag were mixed to form lignite-steel slag particle clusters, where Ca2+ dissolved on the surface of steel slag was combined with PO43- in wastewater to form Ca3(PO4)2 precipitation for phosphorus removal. A biofilm grew on the surface of lignite in this cluster, and OH- released from steel slag promoted lignite to release fulvic acid, which provided a carbon source for heterotrophic microorganisms and promoted denitrification. Moreover, fulvic acid enhanced carbon sequestration in CWs by increasing the biomass of Phragmites australis. The effluent from lignite-steel slag CW increased cherry tomato yield and quality while saving N and P applications. These results provide new ideas for the "green" and economic development of CW technology.

Integrated meta-omics reveals the regulatory landscape involved in lipid metabolism between pig breeds

BACKGROUND

Domesticated pigs serve as an ideal animal model for biomedical research and also provide the majority of meat for human consumption in China. Porcine intramuscular fat content associates with human health and diseases and is essential in pork quality. The molecular mechanisms controlling lipid metabolism and intramuscular fat accretion across tissues in pigs, and how these changes in response to pig breeds, remain largely unknown.

RESULTS

We surveyed the tissue-resident cell types of the porcine jejunum, colon, liver, and longissimus dorsi muscle between Lantang and Landrace breeds by single-cell RNA sequencing. Combining lipidomics and metagenomics approaches, we also characterized gene signatures and determined key discriminating markers of lipid digestibility, absorption, conversion, and deposition across tissues in two pig breeds. In Landrace, lean-meat swine mainly exhibited breed-specific advantages in lipid absorption and oxidation for energy supply in small and large intestinal epitheliums, nascent high-density lipoprotein synthesis for reverse cholesterol transport in enterocytes and hepatocytes, bile acid formation, and secretion for fat emulsification in hepatocytes, as well as intestinal-microbiota gene expression involved in lipid accumulation product. In Lantang, obese-meat swine showed a higher synthesis capacity of chylomicrons responsible for high serum triacylglycerol levels in small intestinal epitheliums, the predominant characteristics of lipid absorption in muscle tissue, and greater intramuscular adipcytogenesis potentials from muscular fibro-adipogenic progenitor subpopulation.

CONCLUSIONS

The findings enhanced our understanding of the cellular biology of lipid metabolism and opened new avenues to improve animal production and human diseases. Video Abstract.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Study Highlights

The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

The oral microbiome: diversity, biogeography and human health

The human oral microbiota is highly diverse and has a complex ecology, comprising bacteria, microeukaryotes, archaea and viruses. These communities have elaborate and highly structured biogeography that shapes metabolic exchange on a local scale and results from the diverse microenvironments present in the oral cavity. The oral microbiota also interfaces with the immune system of the human host and has an important role in not only the health of the oral cavity but also systemic health. In this Review, we highlight recent advances including novel insights into the biogeography of several oral niches at the species level, as well as the ecological role of candidate phyla radiation bacteria and non-bacterial members of the oral microbiome. In addition, we summarize the relationship between the oral microbiota and the pathology of oral diseases and systemic diseases. Together, these advances move the field towards a more holistic understanding of the oral microbiota and its role in health, which in turn opens the door to the study of novel preventive and therapeutic strategies.

A metagenomics study reveals the gut microbiome as a sex-specific modulator of healthy aging in Hainan centenarians

BACKGROUND

Sex differences in health status and life expectancy are widely accepted to exist. The mechanisms underlying it are still poorly understood. In this study, we aimed to clarify the influences and contributions of sex on the gut microbiome in healthy centenarians and to explore the different roles played by the gut microbiome in healthy aging between the sexes.

RESULTS

Taking covariates of different dimensions into account (social demographics, anthropometry, the activities of daily living, dietary structure, mental state, blood tests, lifestyle and disease history), our data showed that sex was one of the most significant covariates affecting the gut microbiome of healthy centenarians at both the species and Kyoto Encyclopedia of Genes and Genomes Orthology (KO) levels. The beta diversity between the sexes were significantly different (Adonis test: p = 0.011, R2 = 0.031), and the male centenarians had a greater alpha diversity than the females (Simpson and Shannon test: P<0.05). At the species level, we identified 31 species enriched in males and 7 species enriched in females. The composition and function patterns of the microbiome varied between the sexes. Further functional analysis showed that males' gut microbiome exhibited greater resistance to oxidative stress compared to females. In contrast to men, the species associated with healthy aging dominated among healthy female centenarians, while the species associated with unhealthy aging were relatively rare.

CONCLUSIONS

The present study reveals that the gut microbiome structure and resistance to oxidative stress in healthy centenarians differ between the sexes and provides new insights into the possible sex-specific role of the gut microbiome in healthy aging.

The role of microbiomes in gastrointestinal cancers: new insights

Gastrointestinal (GI) cancers constitute more than 33% of new cancer cases worldwide and pose a considerable burden on public health. There exists a growing body of evidence that has systematically recorded an upward trajectory in GI malignancies within the last 5 to 10 years, thus presenting a formidable menace to the health of the human population. The perturbations in GI microbiota may have a noteworthy influence on the advancement of GI cancers; however, the precise mechanisms behind this association are still not comprehensively understood. Some bacteria have been observed to support cancer development, while others seem to provide a safeguard against it. Recent studies have indicated that alterations in the composition and abundance of microbiomes could be associated with the progression of various GI cancers, such as colorectal, gastric, hepatic, and esophageal cancers. Within this comprehensive analysis, we examine the significance of microbiomes, particularly those located in the intestines, in GI cancers. Furthermore, we explore the impact of microbiomes on various treatment modalities for GI cancer, including chemotherapy, immunotherapy, and radiotherapy. Additionally, we delve into the intricate mechanisms through which intestinal microbes influence the efficacy of GI cancer treatments.

PM-CNN: microbiome status recognition and disease detection model based on phylogeny and multi-path neural network

Motivation

The human microbiome, found throughout various body parts, plays a crucial role in health dynamics and disease development. Recent research has highlighted microbiome disparities between patients with different diseases and healthy individuals, suggesting the microbiome's potential in recognizing health states. Traditionally, microbiome-based status classification relies on pre-trained machine learning (ML) models. However, most ML methods overlook microbial relationships, limiting model performance.

Results

To address this gap, we propose PM-CNN (Phylogenetic Multi-path Convolutional Neural Network), a novel phylogeny-based neural network model for multi-status classification and disease detection using microbiome data. PM-CNN organizes microbes based on their phylogenetic relationships and extracts features using a multi-path convolutional neural network. An ensemble learning method then fuses these features to make accurate classification decisions. We applied PM-CNN to human microbiome data for status and disease detection, demonstrating its significant superiority over existing ML models. These results provide a robust foundation for microbiome-based state recognition and disease prediction in future research and applications.

Availability and implementation

PM-CNN software is available at https://github.com/qdu-bioinfo/PM_CNN.

Microbiota-gut-liver-brain axis and hepatic encephalopathy

Hepatic encephalopathy (HE) is a clinical manifestation of neurological and psychiatric abnormalities that are caused by complications of liver dysfunction including hyperammonemia, hyperuricemia, and portal hypertension. Accumulating evidence suggests that HE could be reversed through therapeutic modifications of gut microbiota. Multiple preclinical and clinical studies have indicated that gut microbiome affects the physiological function of the liver, such as the regulation of metabolism, secretion, and immunity, through the gut-liver crosstalk. In addition, gut microbiota also influences the brain through the gut-brain crosstalk, altering its physiological functions including the regulation of the immune, neuroendocrine, and vagal pathways. Thus, key molecules that are involved in the microbiota-gut-liver-brain axis might be able to serve as clinical biomarkers for early diagnosis of HE, and could be effective therapeutic targets for clinical interventions. In this review, we summarize the pathophysiology of HE and further propose approaches modulating the microbiota-gut-liver-brain axis in order to provide a comprehensive understanding of the prevention and potential clinical treatment for HE with a microbiota-targeted therapy.

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.

metaProbiotics: a tool for mining probiotic from metagenomic binning data based on a language model

Beneficial bacteria remain largely unexplored. Lacking systematic methods, understanding probiotic community traits becomes challenging, leading to various conclusions about their probiotic effects among different publications. We developed language model-based metaProbiotics to rapidly detect probiotic bins from metagenomes, demonstrating superior performance in simulated benchmark datasets. Testing on gut metagenomes from probiotic-treated individuals, it revealed the probioticity of intervention strains-derived bins and other probiotic-associated bins beyond the training data, such as a plasmid-like bin. Analyses of these bins revealed various probiotic mechanisms and bai operon as probiotic Ruminococcaceae's potential marker. In different health-disease cohorts, these bins were more common in healthy individuals, signifying their probiotic role, but relevant health predictions based on the abundance profiles of these bins faced cross-disease challenges. To better understand the heterogeneous nature of probiotics, we used metaProbiotics to construct a comprehensive probiotic genome set from global gut metagenomic data. Module analysis of this set shows that diseased individuals often lack certain probiotic gene modules, with significant variation of the missing modules across different diseases. Additionally, different gene modules on the same probiotic have heterogeneous effects on various diseases. We thus believe that gene function integrity of the probiotic community is more crucial in maintaining gut homeostasis than merely increasing specific gene abundance, and adding probiotics indiscriminately might not boost health. We expect that the innovative language model-based metaProbiotics tool will promote novel probiotic discovery using large-scale metagenomic data and facilitate systematic research on bacterial probiotic effects. The metaProbiotics program can be freely downloaded at https://github.com/zhenchengfang/metaProbiotics.

Liver cirrhosis and complications from the perspective of dysbiosis

The gut-liver axis refers to the intimate relationship and rigorous interaction between the gut and the liver. The intestinal barrier's integrity is critical for maintaining liver homeostasis. The liver operates as a second firewall in this interaction, limiting the movement of potentially dangerous compounds from the gut and, as a result, contributing in barrier management. An increasing amount of evidence shows that increased intestinal permeability and subsequent bacterial translocation play a role in liver damage development. The major pathogenic causes in cirrhotic individuals include poor intestinal permeability, nutrition, and intestinal flora dysbiosis. Portal hypertension promotes intestinal permeability and bacterial translocation in advanced liver disease, increasing liver damage. Bacterial dysbiosis is closely related to the development of cirrhosis and its related complications. This article describes the potential mechanisms of dysbiosis in liver cirrhosis and related complications, such as spontaneous bacterial peritonitis, hepatorenal syndrome, portal vein thrombosis, hepatic encephalopathy, and hepatocellular carcinoma, using dysbiosis of the intestinal flora as an entry point.

Contributing roles of mitochondrial dysfunction and hepatocyte apoptosis in liver diseases through oxidative stress, post-translational modifications, inflammation, and intestinal barrier dysfunction

This review provides an update on recent findings from basic, translational, and clinical studies on the molecular mechanisms of mitochondrial dysfunction and apoptosis of hepatocytes in multiple liver diseases, including but not limited to alcohol-associated liver disease (ALD), metabolic dysfunction-associated steatotic liver disease (MASLD), and drug-induced liver injury (DILI). While the ethanol-inducible cytochrome P450-2E1 (CYP2E1) is mainly responsible for oxidizing binge alcohol via the microsomal ethanol oxidizing system, it is also responsible for metabolizing many xenobiotics, including pollutants, chemicals, drugs, and specific diets abundant in n-6 fatty acids, into toxic metabolites in many organs, including the liver, causing pathological insults through organelles such as mitochondria and endoplasmic reticula. Oxidative imbalances (oxidative stress) in mitochondria promote the covalent modifications of lipids, proteins, and nucleic acids through enzymatic and non-enzymatic mechanisms. Excessive changes stimulate various post-translational modifications (PTMs) of mitochondrial proteins, transcription factors, and histones. Increased PTMs of mitochondrial proteins inactivate many enzymes involved in the reduction of oxidative species, fatty acid metabolism, and mitophagy pathways, leading to mitochondrial dysfunction, energy depletion, and apoptosis. Unique from other organelles, mitochondria control many signaling cascades involved in bioenergetics (fat metabolism), inflammation, and apoptosis/necrosis of hepatocytes. When mitochondrial homeostasis is shifted, these pathways become altered or shut down, likely contributing to the death of hepatocytes with activation of inflammation and hepatic stellate cells, causing liver fibrosis and cirrhosis. This review will encapsulate how mitochondrial dysfunction contributes to hepatocyte apoptosis in several types of liver diseases in order to provide recommendations for targeted therapeutics.

Body Composition in Chronic Liver Disease

Body composition has recently been attracting people's attention, not only from a cosmetic standpoint but also from the perspective of health and longevity. The body is classified into three components: fat, bone, and lean soft tissue, and it is common to see an increase in body fat and a decrease in total body muscle mass with aging. Aging-related loss of muscle mass and muscle function is referred to as primary sarcopenia, while sarcopenia caused by disease-specific conditions is referred to as secondary sarcopenia. On the other hand, the liver-muscle axis has been attracting attention in recent years, and it has become clear that the liver and the skeletal muscles interact with each other. In particular, patients with cirrhosis are prone to secondary sarcopenia due to protein-energy malnutrition, which is a characteristic pathophysiology of the disease, suggesting the importance of the organ-organ network. In this review, we would like to outline the latest findings in this field, with a focus on body composition in liver diseases such as liver cirrhosis, fatty liver disease, alcoholic liver disease, and hepatocellular carcinoma.

Bifidobacterium longum promotes postoperative liver function recovery in patients with hepatocellular carcinoma

Timely liver function recovery (LFR) is crucial for postoperative hepatocellular carcinoma (HCC) patients. Here, we established the significance of LFR on patient long-term survival through retrospective and prospective cohorts and identified a key gut microbe, Bifidobacterium longum, depleted in patients with delayed recovery. Fecal microbiota transfer from HCC patients with delayed recovery to mice similarly impacted recovery time post hepatectomy. However, oral gavage of B. longum improved liver function and repair in these mice. In a clinical trial of HCC patients, orally administering a probiotic bacteria cocktail containing B. longum reduced the rates of delayed recovery, shortened hospital stays, and improved overall 1-year survival. These benefits, attributed to diminished liver inflammation, reduced liver fibrosis, and hepatocyte proliferation, were associated with changes in key metabolic pathways, including 5-hydroxytryptamine, secondary bile acids, and short-chain fatty acids. Our findings propose that gut microbiota modulation can enhance LFR, thereby improving postoperative outcomes for HCC patients.

Viral Liver Disease and Intestinal Gut–Liver Axis

The intestinal microbiota is closely related to liver diseases via the intestinal barrier and bile secretion to the gut. Impairment of the barrier can translocate microbes or their components to the liver where they can contribute to liver damage and fibrosis. The components of the barrier are discussed in this review along with the other elements of the so-called gut–liver axis. This bidirectional relation has been widely studied in alcoholic and non-alcoholic liver disease. However, the involvement of microbiota in the pathogenesis and treatment of viral liver diseases have not been extensively studied, and controversial data have been published. Therefore, we reviewed data regarding the integrity and function of the intestinal barrier and the changes of the intestinal microbioma that contribute to progression of Hepatitis B (HBV) and Hepatitis C (HCV) infection. Their consequences, such as cirrhosis and hepatic encephalopathy, were also discussed in connection with therapeutic interventions such as the effects of antiviral eradication and the use of probiotics that may influence the outcome of liver disease. Profound alterations of the microbioma with significant reduction in microbial diversity and changes in the abundance of both beneficial and pathogenic bacteria were found.

Multi-kingdom microbial signatures in excess body weight colorectal cancer based on global metagenomic analysis

Excess body weight (EBW) increases the risk of colorectal cancer (CRC) and is linked to lower colonoscopy compliance. Here, we extensively analyzed 981 metagenome samples from multiple cohorts to pinpoint the specific microbial signatures and their potential capability distinguishing EBW patients with CRC. The gut microbiome displayed considerable variations between EBW and lean CRC. We identify 44 and 37 distinct multi-kingdom microbial species differentiating CRC and controls in EBW and lean populations, respectively. Unique bacterial-fungal associations are also observed between EBW-CRC and lean-CRC. Our analysis revealed specific microbial functions in EBW-CRC, including D-Arginine and D-ornithine metabolism, and lipopolysaccharide biosynthesis. The best-performing classifier for EBW-CRC, comprising 12 bacterial and three fungal species, achieved an AUROC of 0.90, which was robustly validated across three independent cohorts (AUROC = 0.96, 0.94, and 0.80). Pathogenic microbial species, Anaerobutyricum hallii, Clostridioides difficile and Fusobacterium nucleatum, are EBW-CRC specific signatures. This work unearths the specific multi-kingdom microbial signatures for EBW-CRC and lean CRC, which may contribute to precision diagnosis and treatment of CRC.

Analyzing lung cancer risks in patients with impaired pulmonary function through characterization of gut microbiome and metabolites

BACKGROUND

Lung cancer (LC) is one of the most devastating diseases worldwide, there is growing studies confirm the role of impaired lung function in LC susceptibility. Moreover, gut microbiota dysbiosis is associated with LC severity. Whether alterations in gut microbiota and metabolites are associated with long-term lung dysfunction in LC patients remain unclear. Our study aimed to analyze the risk factors in LC patients with impaired pulmonary function based on the characteristics of the gut microbiome and metabolites.

METHODS

Fecal samples from 55 LC patients and 28 benign pulmonary nodules patients were collected. Pulmonary ventilation function was graded according to the American Thoracic Society/ European Respiratory Society (ATS/ERS) method. LC patients were divided into 3 groups, including 20 patients with normal lung ventilation, 23 patients with mild pulmonary ventilation dysfunction and 12 patients with moderate or above pulmonary ventilation dysfunction. The fecal samples were analyzed using 16 S rRNA gene amplicon sequencing and metabolomics.

RESULTS

The gut microbiome composition between LC patients and benign pulmonary nodules patients presented clearly differences based on Partial Least Squares Discriminant Analysis (PLS-DA). Pulmonary ventilation function was positively correlated with LC tumor stage, the richness and diversity of the gut microbiota in LC patients with moderate or above pulmonary ventilation dysfunction increased significantly, characterized by increased abundance of Subdoligranulum and Romboutsia. The metabolomics analysis revealed 69 differential metabolites, which were mainly enriched in beta-Alanine metabolism, styrene degradation and pyrimidine metabolism pathway. The area under the curve (AUC) combining the gut microbiome and metabolites was 90% (95% CI: 79-100%), indicating that the two species and four metabolites might regarded as biomarkers to assess the prediction of LC patients with impaired pulmonary function.

CONCLUSIONS

Our results showed that microbiome and metabolomics analyses provide important candidate to be used as clinically diagnostic biomarkers and therapeutic targets related to lung cancer with impaired pulmonary function.

Gut microbiota depletion delays somatic peripheral nerve development and impairs neuromuscular junction maturation

Gut microbiota is responsible for essential functions in human health. Several communication axes between gut microbiota and other organs via neural, endocrine, and immune pathways have been described, and perturbation of gut microbiota composition has been implicated in the onset and progression of an emerging number of diseases. Here, we analyzed peripheral nerves, dorsal root ganglia (DRG), and skeletal muscles of neonatal and young adult mice with the following gut microbiota status: a) germ-free (GF), b) gnotobiotic, selectively colonized with 12 specific gut bacterial strains (Oligo-Mouse-Microbiota, OMM12), or c) natural complex gut microbiota (CGM). Stereological and morphometric analyses revealed that the absence of gut microbiota impairs the development of somatic median nerves, resulting in smaller diameter and hypermyelinated axons, as well as in smaller unmyelinated fibers. Accordingly, DRG and sciatic nerve transcriptomic analyses highlighted a panel of differentially expressed developmental and myelination genes. Interestingly, the type III isoform of Neuregulin1 (NRG1), known to be a neuronal signal essential for Schwann cell myelination, was overexpressed in young adult GF mice, with consequent overexpression of the transcription factor Early Growth Response 2 (Egr2), a fundamental gene expressed by Schwann cells at the onset of myelination. Finally, GF status resulted in histologically atrophic skeletal muscles, impaired formation of neuromuscular junctions, and deregulated expression of related genes. In conclusion, we demonstrate for the first time a gut microbiota regulatory impact on proper development of the somatic peripheral nervous system and its functional connection to skeletal muscles, thus suggesting the existence of a novel 'Gut Microbiota-Peripheral Nervous System-axis.'

Theranostic Diagnostics

Diagnosing and then treating disease defines theranostics. The approach holds promise by facilitating targeted disease outcomes. The simultaneous analysis of finding the presence of disease pathophysiology while providing a parallel in treatment is a novel and effective strategy for seeking improved medical care. We discuss how theranostics improves disease outcomes is discussed. The chapter reviews the delivery of targeted therapies. Bioimaging techniques are highlighted as early detection and tracking systems for microbial infections, degenerative diseases, and cancers.

Disease- and stage-specific alterations of the oral and fecal microbiota in Alzheimer's disease

Microbial communities in the intestinal tract are suggested to impact the ethiopathogenesis of Alzheimer's disease (AD). The human microbiome might modulate neuroinflammatory processes and contribute to neurodegeneration in AD. However, the microbial compositions in patients with AD at different stages of the disease are still not fully characterized. We used 16S rRNA analyses to investigate the oral and fecal microbiota in patients with AD and mild cognitive impairment (MCI; n = 84), at-risk individuals (APOE4 carriers; n = 17), and healthy controls (n = 50) and investigated the relationship of microbial communities and disease-specific markers via multivariate- and network-based approaches. We found a slightly decreased diversity in the fecal microbiota of patients with AD (average Chao1 diversity for AD = 212 [SD = 66]; for controls = 215 [SD = 55]) and identified differences in bacterial abundances including Bacteroidetes, Ruminococcus, Sutterella, and Porphyromonadaceae. The diversity in the oral microbiota was increased in patients with AD and at-risk individuals (average Chao1 diversity for AD = 174 [SD = 60], for at-risk group = 195 [SD = 49]). Gram-negative proinflammatory bacteria including Haemophilus, Neisseria, Actinobacillus, and Porphyromonas were dominant oral bacteria in patients with AD and MCI and the abundance correlated with the cerebrospinal fluid biomarker. Taken together, we observed a strong shift in the fecal and the oral communities of patients with AD already prominent in prodromal and, in case of the oral microbiota, in at-risk stages. This indicates stage-dependent alterations in oral and fecal microbiota in AD which may contribute to the pathogenesis via a facilitated intestinal and systemic inflammation leading to neuroinflammation and neurodegeneration.

Alterations in microbiome of COVID-19 patients and its impact on forensic investigations

The human microbiome is vital for maintaining human health and has garnered substantial attention in recent years, particularly in the context of the coronavirus disease 2019 (COVID-19) outbreak. Studies have underscored significant alterations in the microbiome of COVID-19 patients across various body niches, including the gut, respiratory tract, oral cavity, skin, and vagina. These changes manifest as shifts in microbiota composition, characterized by an increase in opportunistic pathogens and a decrease in beneficial commensal bacteria. Such microbiome transformations may play a pivotal role in influencing the course and severity of COVID-19, potentially contributing to the inflammatory response. This ongoing relationship between COVID-19 and the human microbiome serves as a compelling subject of research, underscoring the necessity for further investigations into the underlying mechanisms and their implications for patient health. Additionally, these alterations in the microbiome may have significant ramifications for forensic investigations, given the microbiome's potential in establishing individual characteristics. Consequently, changes in the microbiome could introduce a level of complexity into forensic determinations. As research progresses, a more profound understanding of the human microbiome within the context of COVID-19 may offer valuable insights into disease prevention, treatment strategies, and its potential applications in forensic science. Consequently, this paper aims to provide an overarching review of microbiome alterations due to COVID-19 and the associated impact on forensic applications, bridging the gap between the altered microbiome of COVID-19 patients and the challenges forensic investigations may encounter when analyzing this microbiome as a forensic biomarker.

The association between periodontitis and hepatitis virus infection: a cross-sectional study utilizing data from the NHANES database (2003-2018)

OBJECTIVES

Periodontitis and hepatitis virus infection significantly impact individuals' well-being and are prevalent public health concerns globally. Given the current scarcity of large-scale cross-sectional epidemiological studies, this study seeks to enrich the evidence base by examining the link between these two conditions.

STUDY DESIGN AND METHODS

A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2003-2018. A multivariate logistic regression analysis was performed to assess the association between periodontitis and hepatitis virus infection, adjusting for the potential confounding factors. Subsequently, a stratified analysis was conducted to explore the relationship between periodontitis and hepatitis virus infection based on age, gender, race, marital status, alcohol consumption, smoking status, and the presence of chronic diseases.

RESULTS

In this study, which included 5755 participants, there was a positive association between hepatitis virus infection and periodontitis (odds ratio [OR]: 2.609 [95% confidence interval (CI): 1.513, 4.499]). Furthermore, a significant association was observed between moderate periodontitis and hepatitis virus infection (OR: 2.136 [95% CI: 1.194, 3.822]), and this association was even stronger for severe periodontitis (OR: 3.583 [95% CI: 1.779, 7.217]). Importantly, this positive association between hepatitis virus infection and periodontitis was consistent across different subgroups.

CONCLUSIONS

This study presents evidence of a significant association between periodontitis and hepatitis virus infection. These findings highlight the crucial importance of integrating periodontal health and liver health considerations into public health interventions. Further research is necessary to elucidate the underlying mechanisms and develop targeted interventions for effectively managing periodontitis and hepatitis virus infection.

Incorporating metabolic activity, taxonomy and community structure to improve microbiome-based predictive models for host phenotype prediction

We developed MicroKPNN, a prior-knowledge guided interpretable neural network for microbiome-based human host phenotype prediction. The prior knowledge used in MicroKPNN includes the metabolic activities of different bacterial species, phylogenetic relationships, and bacterial community structure, all in a shallow neural network. Application of MicroKPNN to seven gut microbiome datasets (involving five different human diseases including inflammatory bowel disease, type 2 diabetes, liver cirrhosis, colorectal cancer, and obesity) shows that incorporation of the prior knowledge helped improve the microbiome-based host phenotype prediction. MicroKPNN outperformed fully connected neural network-based approaches in all seven cases, with the most improvement of accuracy in the prediction of type 2 diabetes. MicroKPNN outperformed a recently developed deep-learning based approach DeepMicro, which selects the best combination of autoencoder and machine learning approach to make predictions, in all of the seven cases. Importantly, we showed that MicroKPNN provides a way for interpretation of the predictive models. Using importance scores estimated for the hidden nodes, MicroKPNN could provide explanations for prior research findings by highlighting the roles of specific microbiome components in phenotype predictions. In addition, it may suggest potential future research directions for studying the impacts of microbiome on host health and diseases. MicroKPNN is publicly available at https://github.com/mgtools/MicroKPNN.

Impacts of gut microbiota alteration on age-related chronic liver diseases

The gut microbiome and its metabolites are involved in developing and progressing liver disease. Various liver illnesses, such as non-alcoholic fatty liver disease, alcoholic liver disease, hepatitis C, and hepatocellular carcinoma, are made worse and have worse prognoses with aging. Dysbiosis, which occurs when the symbiosis between the microbiota and the host is disrupted, can significantly negatively impact health. Liver disease is linked to qualitative changes, such as an increase in hazardous bacteria and a decrease in good bacteria, as well as quantitative changes in the overall amount of bacteria (overgrowth). Intestinal gut microbiota and their metabolites may lead to chronic liver disease development through various mechanisms, such as increasing gut permeability, persistent systemic inflammation, production of SCFA, bile acids, and alteration in metabolism. Age-related gut dysbiosis can disrupt the communication between gut microbiota and the host, impacting the host's health and lifespan. With aging, a gradual loss of the ability to maintain homeostasis because of structural alteration and gut dysbiosis leads to the disease progression in end-stage liver disease. Recently chronic liver disease has been identified as a global problem. A large number of patients are receiving liver transplants yearly. Thereby gut microbiome ecology is changing in the patients of the gut due to the changes in pathophysiology during the preoperative stage. The present review summarises the age-associated dysbiosis of gut microbial composition and its contribution to chronic liver disease. This review also provides information about the impact of liver transplant on the gut microbiome and possible disadvantageous effects of alteration in gut microbiota.