Gut microbiome analysis as a tool towards targeted non-invasive biomarkers for early hepatocellular carcinoma

Atypical immunometabolism and metabolic reprogramming in liver cancer: Deciphering the role of gut microbiome

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related mortality worldwide. Much recent research has delved into understanding the underlying molecular mechanisms of HCC pathogenesis, which has revealed to be heterogenous and complex. Two major hallmarks of HCC include: (i) a hijacked immunometabolism and (ii) a reprogramming in metabolic processes. We posit that the gut microbiota is a third component in an entanglement triangle contributing to HCC progression. Besides metagenomic studies highlighting the diagnostic potential in the gut microbiota profile, recent research is pinpointing the gut microbiota as an instigator, not just a mere bystander, in HCC. In this chapter, we discuss mechanistic insights on atypical immunometabolism and metabolic reprogramming in HCC, including the examination of tumor-associated macrophages and neutrophils, tumor-infiltrating lymphocytes (e.g., T-cell exhaustion, regulatory T-cells, natural killer T-cells), the Warburg effect, rewiring of the tricarboxylic acid cycle, and glutamine addiction. We further discuss the potential involvement of the gut microbiota in these characteristics of hepatocarcinogenesis. An immediate highlight is that microbiota metabolites (e.g., short chain fatty acids, secondary bile acids) can impair anti-tumor responses, which aggravates HCC. Lastly, we describe the rising 'new era' of immunotherapies (e.g., immune checkpoint inhibitors, adoptive T-cell transfer) and discuss for the potential incorporation of gut microbiota targeted therapeutics (e.g., probiotics, fecal microbiota transplantation) to alleviate HCC. Altogether, this chapter invigorates for continuous research to decipher the role of gut microbiome in HCC from its influence on immunometabolism and metabolic reprogramming.

The microbiome, genetics, and gastrointestinal neoplasms: the evolving field of molecular pathological epidemiology to analyze the tumor-immune-microbiome interaction

Metagenomic studies using next-generation sequencing technologies have revealed rich human intestinal microbiome, which likely influence host immunity and health conditions including cancer. Evidence indicates a biological link between altered microbiome and cancers in the digestive system. Escherichia coli and Bacteroides fragilis have been found to be enriched in colorectal mucosal tissues from patients with familial adenomatous polyposis that is caused by germline APC mutations. In addition, recent studies have found enrichment of certain oral bacteria, viruses, and fungi in tumor tissue and fecal specimens from patients with gastrointestinal cancer. An integrative approach is required to elucidate the role of microorganisms in the pathogenic process of gastrointestinal cancers, which develop through the accumulation of somatic genetic and epigenetic alterations in neoplastic cells, influenced by host genetic variations, immunity, microbiome, and environmental exposures. The transdisciplinary field of molecular pathological epidemiology (MPE) offers research frameworks to link germline genetics and environmental factors (including diet, lifestyle, and pharmacological factors) to pathologic phenotypes. The integration of microbiology into the MPE model (microbiology-MPE) can contribute to better understanding of the interactive role of environment, tumor cells, immune cells, and microbiome in various diseases. We review major clinical and experimental studies on the microbiome, and describe emerging evidence from the microbiology-MPE research in gastrointestinal cancers. Together with basic experimental research, this new research paradigm can help us to develop new prevention and treatment strategies for gastrointestinal cancers through targeting of the microbiome.

Altered gut bacterial and metabolic signatures and their interaction in gestational diabetes mellitus

Emerging evidence indicates that the gut microbiome can modulate metabolic homeostasis, and thus may influence the development of gestational diabetes mellitus (GDM). However, whether and how the gut microbiome and its correlated metabolites change in GDM is uncertain. Herein we compare the gut microbial compositions, and fecal and urine metabolomes, of 59 patients with GDM versus 48 pregnant healthy controls (HCs). We showed that the microbial and metabolic signatures of GDM patients were significantly different from those of HCs. Compared to HCs, the GDM subjects were characterized by enriched bacterial operational taxonomic units (OTUs) of the family Lachnospiraceae, and depleted OTUs of the families Enterobacteriaceae and Ruminococcaceae. Some altered gut microbes were significantly correlated with glucose values and fetal ultrasonography indexes. Moreover, we identified four fecal and 15 urine metabolites that discriminate GDM from HC. These differential metabolites are mainly involved in carbohydrate and amino acid metabolism. Significantly, co-occurrence network analysis revealed that Lachnospiraceae and Enterobacteriaceae bacterial OTUs formed strong co-occurring relationships with metabolites involved in carbohydrate and amino acid metabolism, suggesting that disturbed gut microbiome may mediate GDM. Furthermore, we identified a novel combinatorial marker panel that could distinguish GDM from HC subjects with high accuracy. Together our findings demonstrate that altered microbial composition and metabolic function may be relevant to the pathogenesis and pathophysiology of GDM.

From correlation to causality: the case of Subdoligranulum

Gut microbes are considered as major factors contributing to human health. Nowadays, the vast majority of the data available in the literature are mostly exhibiting negative or positive correlations between specific bacteria and metabolic parameters. From these observations, putative detrimental or beneficial effects are then inferred. Akkermansia muciniphila is one of the unique examples for which the correlations with health benefits have been causally validated in vivo in rodents and humans. In this study, based on available metagenomic data in overweight/obese population and clinical variables that we obtained from two cohorts of individuals (n = 108) we identified several metagenomic species (MGS) strongly associated with A. muciniphila with one standing out: Subdoligranulum. By analyzing both qPCR and shotgun metagenomic data, we discovered that the abundance of Subdoligranulum was correlated positively with microbial richness and HDL-cholesterol levels and negatively correlated with fat mass, adipocyte diameter, insulin resistance, levels of leptin, insulin, CRP, and IL6 in humans. Therefore, to further explore whether these strong correlations could be translated into causation, we investigated the effects of the unique cultivated strain of Subdoligranulum (Subdoligranulum variabile DSM 15176 ^T) in obese and diabetic mice as a proof-of-concept. Strikingly, there were no significant difference in any of the hallmarks of obesity and diabetes measured (e.g., body weight gain, fat mass gain, glucose tolerance, liver weight, plasma lipids) at the end of the 8 weeks of treatment. Therefore, the absence of effect following the supplementation with S. variabile indicates that increasing the intestinal abundance of this bacterium is not translated into beneficial effects in mice. In conclusion, we demonstrated that despite the fact that numerous strong correlations exist between a given bacteria and health, proof-of-concept experiments are required to be further validated or not in vivo. Hence, an urgent need for causality studies is warranted to move from human observations to preclinical validations.

The Microbiome and Cancer: Creating Friendly Neighborhoods and Removing the Foes Within

The human body is colonized by the microbial cells that are estimated to be as abundant as human cells, yet their genome is roughly 100 times the human genome, providing significantly more genetic diversity. The past decade has observed an explosion of interest in examining the existence of microbiota in the human body and understanding its role in various diseases including inflammatory bowel disease, neurologic diseases, cardiovascular disorders, and cancer. Many studies have demonstrated differential community composition between normal tissue and cancerous tissue, paving the way for investigations focused on deciphering the cause-and-effect relationships between specific microbes and initiation and progression of various cancers. Also, evolving are the strategies to alter tumor-associated dysbiosis and move it toward eubiosis with holistic approaches to change the entire neighborhood or to neutralize pathogenic strains. In this review, we discuss important pathogenic bacteria and the underlying mechanisms by which they affect cancer progression. We summarize key microbiota alterations observed in multiple tumor niches, their association with clinical stages, and their potential use in cancer diagnosis and management. Finally, we discuss microbiota-based therapeutic approaches.

Gut fungal dysbiosis and altered bacterial-fungal interaction in patients with diarrhea-predominant irritable bowel syndrome: An explorative study

BACKGROUND

Little is known about intestinal fungi in IBS patients whose gut bacteria have been investigated a lot. In order to explore causal relationship between IBS and gut mycobiome, and use gut fungi to diagnose or even treat IBS, further characterization of it in IBS is required.

METHODS

Fifty-five diarrhea-predominant IBS (D-IBS) patients fulfilling Rome III criteria, and 16 healthy controls (HC) were recruited. Fresh fecal samples were collected and used for 16s rRNA and ITS2 high-throughput sequencing. Diversity and composition of gut bacteria and fungi, as well as bacterial-fungal interactions in D-IBS patients, were characterized. Specific fungal taxa differentiating D-IBS from HC were recognized by LEfSe and RandomForest methods, and their association with clinical symptoms was assessed by Spearman's correlation.

RESULTS

Diarrhea-predominant irritable bowel syndrome patients showed abnormal (IBS-dysbiosis) or normal (HC-like IBS) fecal bacterial structure and diversity compared with healthy controls. However, fecal fungal signatures differed absolutely between D-IBS and HC, which indicated a more susceptible alteration of gut fungi than bacteria in D-IBS. Fecal fungi showed significant correlations with IBS symptoms, especially Mycosphaerella, Aspergillus, Sporidiobolus, and Pandora which were identified to potentially differentiate D-IBS from HC. Moreover, compared with HC there were markedly declined bacterial-fungal interactions in D-IBS, in which Candida changed from negative to positive correlations with bacteria, and Eurotium changed from positive correlations to irrelevance, while Debaryomyces gained negative correlations with bacteria.

CONCLUSIONS

Gut fungal dysbiosis and altered bacterial-fungal interactions were present in patients with D-IBS, and gut fungi could be used to diagnose D-IBS.

The gut microbiome in differential diagnosis of diabetic kidney disease and membranous nephropathy

Background

Diabetic kidney disease (DKD) and membranous nephropathy (MN) are the two major causes of end-stage renal disease (ESRD). Increasing evidence has shown that intestinal dysbiosis is associated with many diseases. The aim of this study was to explore the composition of the gut microbiome in DKD and MN patients.

Methods

16S rRNA gene sequencing was performed on 271 fecal samples (DKD = 129 and MN = 142), and taxonomic annotation of microbial composition and function was completed.

Results

We observed distinct microbial communities between the two groups, with MN samples exhibiting more severe dysbiosis than DKD samples. Relative increases in genera producing short-chain fatty acids (SCFAs) in DKD and a higher proportion of potential pathogens in MN were the main contributors to the microbiome alterations in the two groups. Five-fold cross-validation was performed on a random forest model, and four operational taxonomic unit (OTU)-based microbial markers were selected to distinguish DKD from MN. The results showed 92.42% accuracy in the training set and 94.52% accuracy in the testing set, indicating high potential for these microbiome-based markers in separating MN from DKD. Overexpression of several amino acid metabolic pathways, carbohydrate metabolism and lipid metabolism was found in DKD, while interconversion of pentose/glucoronate and membrane transport in relation to ABC transporters and the phosphotransferase system were increased in MN.

Conclusion

The composition of the gut microbiome appears to differ considerably between patients with DKD and those with MN. Thus, microbiome-based markers could be used as an alternative tool to distinguish DKD and MN.

Gut Microbiota, Peroxisome Proliferator-Activated Receptors, and Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. HCC incidence rate is sixth and mortality is fourth worldwide. However, HCC pathogenesis and molecular mechanisms remain unclear. The incidence of HCC is associated with genetic, environmental, and metabolic factors. The role of gut microbiota in the pathogenesis of HCC has attracted researchers' attention because of anatomical and functional interactions between liver and intestine. Studies have demonstrated the involvement of gut microbiota in the development of HCC and chronic liver diseases, such as alcoholic liver disease (ALD), nonalcoholic fatty liver disease (NAFLD), and liver cirrhosis. Peroxisome proliferator-activated receptors (PPARs) are a group of receptors with diverse biological functions. Natural and synthetic PPAR agonists show potential for treatment of NAFLD, liver fibrosis, and HCC. Recent studies have demonstrated that PPARs take part in gut microbiota inhabitation and adaptation. This manuscript reviews the role of gut microbiota in the development of HCC and precancerous diseases, the role of PPARs in modulation of gut microbiota and HCC, and potential of gut microbiota for HCC diagnosis and treatment.

Potential role of intestinal microflora in disease progression among patients with different stages of Hepatitis B

BACKGROUND

Increasing evidence demonstrate that the gut microbiota is involved in the pathogenesis of liver diseases, and faecal microbiota transplantation is considered to be a promising new treatment option. However, there are no reports on the intestinal flora of asymptomatic HBV carriers using next-generation sequencing. This study intends to investigate the potential role of the intestinal microflora in predicting the progression of Hepatitis B patients in different non-cancerous stages.

RESULTS

A total of 266 patients with different stages of Hepatitis B and 31 healthy controls were included in this study. Some of the subjects (217 cases) underwent 16S rRNA gene sequencing. Compared with the control group (CK), the α diversity of patients in Group A (HBV carrier) slightly increased, while that of patients in the other three groups decreased. Each group of patients, especially those in Group C (cirrhosis) and Group D (acute-on-chronic liver failure), could be separated from the CK using weighted UniFrac PCoA and ANOSIM. LEfSe revealed that 40 taxa belonging to three phyla had an LDA larger than 4. In addition to the comparison between Group B (chronic Hepatitis B) and Group C, the specific flora and potential taxonomic function were also identified. Different microbial communities were found to be highly correlated with clinical indicators and the Child-Pugh scores. Changes in the microbial community were highly related to the alternations of host metabolism, which in turn, was related to the development of Hepatitis B. Our analysis identified a total of 47 strains with potential biomarker functions at all levels except for the phylum level.

CONCLUSIONS

Faecal microbiota transplantation of some potential beneficial bacteria can change with the occurrence of disease, and HBV carriers might be the most suitable donors.

A Comparative Study of the Gut Microbiota Associated With Immunoglobulin a Nephropathy and Membranous Nephropathy

The pathogenesis of immunoglobulin A nephropathy (IgAN) and membranous nephropathy (MN) is characterized by immune dysregulation, which is related to gut dysbiosis. The aim of the study was to compare the gut microbiota of patients with IgAN and MN vs. healthy controls. We used 16S rDNA amplicon sequencing to investigate the bacterial communities of 44 patients with kidney biopsy-proven IgAN, 40 patients with kidney biopsy-proven MN, and 30 matched healthy controls (HC). The abundance of Escherichia-Shigella and Defluviitaleaceae_incertae_sedis were significantly higher in IgAN than in HC, whereas lower abundances were observed for Roseburia, Lachnospiraceae_unclassified, Clostridium_sensu_stricto_1, and Fusobacterium. Furthermore, the abundance of Escherichia-Shigella, Peptostreptococcaceae_incertae_sedis, Streptococcus, and Enterobacteriaceae_unclassified increased, while that of Lachnospira, Lachnospiraceae_unclassified, Clostridium_sensu_stricto_1, and Veillonella decreased in MN. The abundance of Megasphaera and Bilophila was higher, whereas that of Megamonas, Veillonella, Klebsiella, and Streptococcus was lower in patients with IgAN than in those with MN. Analysis of the correlations showed that in the IgAN group, Prevotella was positively correlated, while Klebsiella, Citrobacter, and Fusobacterium were negatively correlated with the level of serum albumin. Positive correlation also existed between Bilophila and Crescents in the Oxford classification of IgAN. In the MN group, negative correlation was observed between Escherichia-Shigella and proteinuria, Bacteroides and Klebsiella showed positive correlation with the MN stage. Patients with IgAN and MN exhibited gut microbial signatures distinct from healthy controls. Our study suggests the potential of gut microbiota as specific biomarker and contributor in the pathogenesis of IgAN and MN.

Gut dysbiosis is associated with primary hypothyroidism with interaction on gut-thyroid axis

Background Previous studies have shown that the gut microbiome is associated with thyroid diseases, including Graves' disease, Hashimoto's disease, thyroid nodules, and thyroid cancer. However, the association between intestinal flora and primary hypothyroidism remains elusive. We aimed to characterize gut microbiome in primary hypothyroidism patients. Methods Fifty-two primary hypothyroidism patients and 40 healthy controls were recruited. The differences in gut microbiota between the two groups were analyzed by 16S rRNA sequencing technology. Fecal microbiota transplantation (FMT) was performed in mice using flora from both groups; changes in thyroid function were then assessed in the mice. Results There were significant differences in α and β diversities of gut microbiota between primary hypothyroidism patients and healthy individuals. The random forest analysis indicated that four intestinal bacteria (Veillonella, Paraprevotella, Neisseria, and Rheinheimera) could distinguish untreated primary hypothyroidism patients from healthy individuals with the highest accuracy; this was confirmed by receiver operator characteristic curve analysis. The short chain fatty acid producing ability of the primary hypothyroidism patients' gut was significantly decreased, which resulted in the increased serum lipopolysaccharide (LPS) levels. The FMT showed that mice receiving the transplant from primary hypothyroidism patients displayed decreased total thyroxine levels. Conclusions Our study suggests that primary hypothyroidism causes changes in gut microbiome. In turn, an altered flora can affect thyroid function in mice. These findings could help understand the development of primary hypothyroidism and might be further used to develop potential probiotics to facilitate the adjuvant treatment of this disease.

Dissimilarity of microbial diversity of pond water, shrimp intestine and sediment in Aquamimicry system

The Pacific white shrimp, with the largest production in shrimp industry, has suffered from multiple severe viral and bacterial diseases, which calls for a more reliable and environmentally friendly system to promote shrimp culture. The "Aquamimicry system", mimicking the nature of aquatic ecosystems for the well-being of aquatic animals, has effectively increased shrimp production and been adapted in many countries. However, the microbial communities in the shrimp intestine and surrounding environment that act as an essential component in Aquamimicry remain largely unknown. In this study, the microbial composition and diversity alteration in shrimp intestine, surrounding water and sediment at different culture stages were investigated by high throughput sequencing of 16S rRNA gene, obtaining 13,562 operational taxonomic units (OTUs). Results showed that the microbial communities in shrimp intestine and surrounding environment were significantly distinct from each other, and 23 distinguished taxa for each habitat were further characterized. The microbial communities differed significantly at different culture stages, confirmed by a great number of OTUs dramatically altered during the culture period. A small part of these altered OTUs were shared between shrimp intestine and surrounding environment, suggesting that the microbial alteration of intestine was not consistent with that of water and sediment. Regarding the high production of Aquamimicry farm used as a case in this study, the dissimilarity between intestinal and surrounding microbiota might be considered as a potential indicator for healthy status of shrimp farming, which provided hints on the appropriate culture practices to improve shrimp production.

Gut microbiome, big data and machine learning to promote precision medicine for cancer

The gut microbiome has been implicated in cancer in several ways, as specific microbial signatures are known to promote cancer development and influence safety, tolerability and efficacy of therapies. The 'omics' technologies used for microbiome analysis continuously evolve and, although much of the research is still at an early stage, large-scale datasets of ever increasing size and complexity are being produced. However, there are varying levels of difficulty in realizing the full potential of these new tools, which limit our ability to critically analyse much of the available data. In this Perspective, we provide a brief overview on the role of gut microbiome in cancer and focus on the need, role and limitations of a machine learning-driven approach to analyse large amounts of complex health-care information in the era of big data. We also discuss the potential application of microbiome-based big data aimed at promoting precision medicine in cancer.

The Microbiome and Hepatocellular Carcinoma

The human microbiome is a vast and complex system encompassing all of the microbes and their genes that occupy the environmentally exposed surfaces of the human body. The gut microbiota and its associated microbiome play an integral role in mammalian metabolism and immune tolerance as well as in immunocompetence. Disruptions in the human gut microbiome are associated with a cycle of hepatocyte injury and regeneration characteristic of chronic liver disease. The persistence of this inflammation has been shown to induce the accumulation of genetic and epigenetic changes leading to hepatocellular carcinoma (HCC). Therefore, the importance and prognostic influence of the gut microbiome on hepatocarcinogenesis has been increasingly studied in recent years. This review discusses the mechanisms by which imbalances in the gut microbiome disturb the gut-liver axis to impact hepatocarcinogenesis, including disruption of the intestinal barrier, changes in bile acid metabolism, and reduction in tumor-suppressing microRNA. Furthermore, this review summarizes recent advances in potential microbiome-based therapeutic opportunities in HCC.

Alterations of the Human Gut Microbiome in Chronic Kidney Disease

Gut microbiota make up the largest microecosystem in the human body and are closely related to chronic metabolic diseases. Herein, 520 fecal samples are collected from different regions of China, the gut microbiome in chronic kidney disease (CKD) is characterized, and CKD classifiers based on microbial markers are constructed. Compared with healthy controls (HC, n = 210), gut microbial diversity is significantly decreased in CKD (n = 110), and the microbial community is remarkably distinguished from HC. Genera Klebsiella and Enterobacteriaceae are enriched, while Blautia and Roseburia are reduced in CKD. Fifty predicted microbial functions including tryptophan and phenylalanine metabolisms increase, while 36 functions including arginine and proline metabolisms decrease in CKD. Notably, five optimal microbial markers are identified using the random forest model. The area under the curve (AUC) reaches 0.9887 in the discovery cohort and 0.9512 in the validation cohort (49 CKD vs 63 HC). Importantly, the AUC reaches 0.8986 in the extra diagnosis cohort from Hangzhou. Moreover, Thalassospira and Akkermansia are increased with CKD progression. Thirteen operational taxonomy units are correlated with six clinical indicators of CKD. In conclusion, this study comprehensively characterizes gut microbiome in non-dialysis CKD and demonstrates the potential of microbial markers as non-invasive diagnostic tools for CKD in different regions of China.

Granulocyte-macrophage colony-stimulating factor protects mice against hepatocellular carcinoma by ameliorating intestinal dysbiosis and attenuating inflammation

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide. The gut microbiota can help maintain healthy metabolism and immunity. Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a critical factor in promoting health and homeostasis; it promotes intestinal immunity, stimulates bone marrow precursors to generate macrophage colonies, and enhances the antibacterial and antitumor activity of circulating monocytes. As such, GM-CSF may protect against HCC development by regulating immunity as well as intestinal microecology.

AIM

To investigate the impact of GM-CSF on the gut microbiome and metabolic characteristics of HCC.

METHODS

Thirty-six male BALB/c nude mice were divided into three groups: Control (n = 10), HCC (n = 13), and HCC + GM-CSF (GM-CSF overexpression, n = 13). We utilized HCC cells to establish orthotopic transplantation tumor models of HCC with normal and over-expressing GM-CSF. Liver injury, immune inflammatory function and intestinal barrier function were evaluated. The fecal microbiome and metabolome were studied using 16S rRNA absolute quantification sequencing and gas chromatography-mass spectrometry.

RESULTS

GM-CSF overexpression significantly affected the gut microbiome of mice with HCC and resulted in a high abundance of organisms of the genera Roseburia, Blautia and Butyricimonass, along with a significant reduction in Prevotella, Parabacteroides, Anaerotruncus, Streptococcus, Clostridium, and Mucispirillum. Likewise, GM-CSF overexpression resulted in a substantial increase in fecal biotin and oleic acid levels, along with a prominent decrease in the fecal succinic acid, adenosine, fumaric acid, lipoic acid, and maleic acid levels. Correlation analysis revealed that the intestinal microbiota and fecal metabolites induced by GM-CSF were primarily involved in pathways related to reducing the inflammatory response, biotin metabolism, and intestinal barrier dysfunction.

CONCLUSION

GM-CSF can protect against HCC development by regulating immunity and modulating the abundance of specific intestinal microorganisms and their metabolites. This study provides new insights into the therapeutic approaches for HCC.

A Holistic View of Berberine Inhibiting Intestinal Carcinogenesis in Conventional Mice Based on Microbiome-Metabolomics Analysis

Berberine (BBR) has been reported that it has effects on inhibiting colorectal cancer (CRC). However, the mechanism of BBR on CRC also remains largely unknown. Herein, we investigated the therapeutic effects of BBR on CRC from the perspective of gut microbiota and metabolic alterations, which can provide a holistic view to understand the effects of BBR on CRC. First, azoxymethane (AOM)/dextran sodium sulfate (DSS) mouse was used as CRC animal model, then the degree of colorectal carcinogenesis in AOM/DSS mice with or without BBR administration was measured. The composition and abundance of gut microbiota was investigated by using 16S rRNA. Meanwhile, feces samples were analyzed with ¹H NMR spectroscopy to investigate the metabolic alterations. As a result, BBR significantly reduced intestinal tumor development with lower macroscopic polyps and ki-67 expression of intestinal tissue, and better colonic morphology in mice. Moreover, BBR altered the composition of gut microbiota in AOM/DSS mice obviously, which were characterized by a decrease of Actinobacteria and Verrucomicrobia significantly at the phylum level. At the genus level, it was able to suppress pathogenic species, such as f_Erysipelotrichaceae, Alistipes, and elevate some short-chain fatty acids (SCFA)-producing bacteria, including Alloprevotella, Flavonifractor, and Oscillibacter. Metabolic data further revealed that BBR induced metabolic changes in feces focus on regulating glycometabolism, SCFA metabolism and amino acid metabolism, which also provides evidence for alteration of the microbiota because these feces metabolites are the products of interactions between the host and the microbial community. This study showed that BBR induced alterations in microbiota and metabolic in AOM/DSS mice, which might providing new insight into the inhibition effects of BBR on CRC.

Human oral microbiome dysbiosis as a novel non-invasive biomarker in detection of colorectal cancer

Background: The oral microbiome may play an important role in colorectal carcinogenesis. However, few studies have investigated the association between oral microbiome and the development of colorectal cancer (CRC). We aimed to investigate whether oral health-colorectal tumor association has an underlying microbial basis, in the quest for novel non-invasive biomarkers for CRC.

Methods: We collected oral swab samples from 161 patients with CRC, 34 patients with colorectal adenoma (CRA), and 58 healthy volunteers. The oral microbiota was assessed using 16S rRNA sequencing. We characterized oral microbiome, identified microbial markers, constructed and validated colorectal tumor (CRA and CRC) classifier.

Results: Oral microbial composition and diversity were significantly different among the three groups, and the CRA group had the highest diversity. Analysis of the functional potential of oral microbiota demonstrated that the pathway involving cell motility was overrepresented in the CRA and CRC groups relative to that in the healthy controls. Moreover, a random forest model was constructed based on oral microbial markers, which could distinguish the colorectal tumor groups from the healthy controls and achieve a powerful classification potential in the discovery and validation cohorts.

Conclusion: This study suggests a potential association between oral microbiome dysbiosis and colorectal cancer. Oral microbiota-based biomarkers may be helpful in predicting the risks for the development of CRA and CRC.

Secondary Sclerosing Cholangitis in Critically Ill Patients Alters the Gut-Liver Axis: A Case Control Study

Secondary sclerosing cholangitis in critically ill patients (SC-CIP) occurs after long-term intensive care treatment. This study aimed to assess the gut-liver axis in SC-CIP. Stool microbiome composition, gut permeability, bacterial translocation and serum bile acid profiles of 18 SC-CIP patients compared to 11 patients after critical illness without liver disease (CIP controls), 21 patients with cirrhosis and 21 healthy controls were studied. 16S rDNA was isolated from stool and sequenced using the Illumina technique. Diamine oxidase, zonulin, soluble CD14 (sCD14) and lipopolysaccharide binding protein were measured in serum and calprotectin in stool. Serum bile acids were analyzed by high-performance liquid chromatography-mass spectrometry (HPLC-MS). Reduced microbiome alpha diversity and altered beta diversity were seen in SC-CIP, CIP controls and cirrhosis compared to healthy controls. SC-CIP patients showed a shift towards pathogenic taxa and an oralization. SC-CIP, CIP controls and cirrhotic patients presented with impaired gut permeability, and biomarkers of bacterial translocation were increased in SC-CIP and cirrhosis. Total serum bile acids were elevated in SC-CIP and cirrhosis and the bile acid profile was altered in SC-CIP, CIP controls and cirrhosis. In conclusions, observed alterations of the gut-liver axis in SC-CIP cannot solely be attributed to liver disease, but may also be secondary to long-term intensive care treatment.

Role of Microbiota in Pathogenesis and Management of Viral Hepatitis

Hepatitis is a condition that can be self-limiting or can progress to fibrosis (scarring), cirrhosis, or liver cancer. These days, gut microbiota becomes an important part of our immune system, which is important for disease progression or recovery. Translocation of gut microbial and metabolic products causes intestinal inflammation by modulating immune cells leading to impairment of the primary barrier. But there are limited studies discussing pathogenesis and management of hepatitis with gut microbiota. In this review, we have discussed the role of gut microbiota in pathogenesis and management of various hepatitis, especially hepatitis B and C. We have discussed the role of bacterial products, LPS-TLR4 pathway, and unmethylated CpG DNA, which ultimately affects downstream NF-kB signaling in hepatitis. Finally, we have discussed the role of fecal microbiota transplantation in the management of hepatitis.

Fecal Microbiomes Distinguish Patients With Autoimmune Hepatitis From Healthy Individuals

Objective: The intestinal microbiome is associated with various autoimmune diseases. Regional difference is the main influencing factor of intestinal microbial difference. This study aimed to identify the differences in fecal microbiome between autoimmune hepatitis (AIH) patients and healthy controls (HCs) in Central China, and to validate the efficacy of fecal microbiome as a diagnostic tool for AIH. Design: We collected 115 fecal samples from AIH patients (N = 37) and HCs (N = 78) in Central China and performed gene sequencing. Fecal microbiomes were characterized and microbial markers for AIH were identified. Results: Fecal microbial diversity showed a downward trend in AIH compared with HCs. Fecal microbial communities significantly differed between both groups. At the phylum level, Verrucomicrobia abundance was significantly increased, while Lentisphaerae and Synergistetes were significantly decreased in the AIH patients vs. the HCs. Compared to the HCs, 15 genera, including Veillonella, Faecalibacterium, and Akkermansia, were enriched, while 19 genera, such as Pseudobutyrivibrio, Lachnospira, and Ruminococcaceae, were decreased in the AIH patients. Ten genera, including Veillonella, Faecalibacterium, and Akkermansia, predominated in the AIH patients. Five microbial biomarkers were deemed optimal diagnostic tools for AIH. The probability of disease was significantly increased in AIH group vs. HCs, achieving 83.25% value of area under the curve. Conclusion: We present the characteristics of AIH patients in Central China for the first time. Five microbial biomarkers, including Lachnospiraceae, Veillonella, Bacteroides, Roseburia, and Ruminococcaceae, achieved a high potential distinguishing AIH patients from HCs.

Microbiome: Emerging Concepts in Patients with Chronic Liver Disease

The gut microbiome is an exciting new area of research in chronic liver disease. It has shown promise in expanding our understanding of these complicated disease processes and has opened up new treatment modalities. The aim of this review is to increase understanding of the microbiome and explain the collection and analysis process in the context of liver disease. It also looks at our current understanding of the role of the microbiome in the wide spectrum of chronic liver diseases and how it is being used in current therapies and treatments.

Advances in the Involvement of Gut Microbiota in Pathophysiology of NAFLD

Non-alcoholic fatty liver disease (NAFLD) is characterized by hepatic steatosis and progresses to non-steatohepatitis (NASH) when the liver displays overt inflammatory damage. Increasing evidence has implicated critical roles for dysbiosis and microbiota-host interactions in NAFLD pathophysiology. In particular, microbiota alter intestine absorption of nutrients and intestine permeability, whose dysregulation enhances the delivery of nutrients, endotoxin, and microbiota metabolites to the liver and exacerbates hepatic fat deposition and inflammation. While how altered composition of gut microbiota attributes to NAFLD remains to be elucidated, microbiota metabolites are shown to be involved in the regulation of hepatocyte fat metabolism and liver inflammatory responses. In addition, intestinal microbes and circadian coordinately adjust metabolic regulation in different stages of life. During aging, altered composition of gut microbiota, along with circadian clock dysregulation, appears to contribute to increased incidence and/or severity of NAFLD.

Liver Cirrhosis and Sarcopenia from the Viewpoint of Dysbiosis

Sarcopenia in patients with liver cirrhosis (LC) has been attracting much attention these days because of the close linkage to adverse outcomes. LC can be related to secondary sarcopenia due to protein metabolic disorders and energy metabolic disorders. LC is associated with profound alterations in gut microbiota and injuries at the different levels of defensive mechanisms of the intestinal barrier. Dysbiosis refers to a state in which the diversity of gut microbiota is decreased by decreasing the bacterial species and the number of bacteria that compose the gut microbiota. The severe disturbance of intestinal barrier in LC can result in dysbiosis, several bacterial infections, LC-related complications, and sarcopenia. Here in this review, we will summarize the current knowledge of the relationship between sarcopenia and dysbiosis in patients with LC.

Liquid Chromatography-Mass Spectrometry-Based Nontargeted Metabolomics Predicts Prognosis of Hepatocellular Carcinoma after Curative Resection

Assessment and prediction of prognostic risk in patients with hepatocellular carcinoma (HCC) would greatly benefit the optimal treatment selection. Here, we aimed to identify the critical metabolites associated with the outcomes and develop a risk score to assess the prognosis of HCC patients after curative resection. A total of 78 serum samples of HCC patients were analyzed by liquid chromatography-mass spectrometry to characterize the metabolic profiling. A novel network-based feature selection method (NFSM) was developed to define the critical metabolites with the most discriminant capacity to outcomes. The metabolites defined by NFSM was further reduced by Cox regression analysis to generate a prognostic metabolite panel-phenylalanine and choline. Furthermore, univariate and multivariate Cox regression analyses were applied to combine the metabolite panel with the presence of satellite nodes to generate a global prognostic index (GPI) score for overall survival assessment. Compared with the current clinical classification systems, including the Barcelona-clinic liver cancer stage, tumor-node-metastasis stage, and albumin-bilirubin grade, the GPI score presented comparable performance, according to the time-dependent receiver operating characteristic curves and was validated in an independent cohort, which suggested that metabolomics could serve as a helpful tool to stratify the HCC prognostic risk after operation.

Screening and verification of long noncoding RNA promoter methylation sites in hepatocellular carcinoma

Background

Long noncoding ribonucleic acid (lncRNA) promoter methylation is closely related to the occurrence and development of hepatocellular carcinoma (HCC). Thus, we aim to screen and verify the lncRNA promoter methylation sites associated with overall survival (OS), vascular invasion, pathological grade, and clinical stage in HCC.

Methods

Methylation-related data including clinical characteristic, transcriptome, methylation, and messenger RNA (mRNA) expression were taken from the Cancer Genome Atlas (TCGA) database. The OS, vascular invasion, pathological grade, and clinical stage-related lncRNA promoter methylation models were developed by the least absolute shrinkage and selection operator (LASSO) algorithm based on the lncRNA promoter methylation sites screened via R software. The Kaplan-Meier analysis, the area under the receiver operating characteristic (ROC) curve (AUC), the calibration curve (C-index) were performed to evaluate the performance of these models. Finally, the methylation-specific polymerase chain reaction (MS-PCR) was performed to verify the accuracy of these models based on 146 HCC tissues from our hospital.

Results

A total of 10 methylation sites were included in the OS-related lncRNA promoter methylation model that could effectively divide HCC patients into high-risk and low-risk groups (P < 0.0001) via survival analysis. COX univariable and multivariable regression analysis found that the OS-related model (P < 0.001, 95% CI 1.378-2.942) and T stage (P < 0.001, 95% CI 1.490-3.418) were independent risk factors affecting OS in HCC patients. The vascular invasion-related model contained 8 methylation sites with its AUC value of 0.657; the pathological grade-related model contained 22 methylation sites with its AUC value of 0.797; the clinical stage-related model contained 13 methylation sites with its AUC of 0.724. Target genes corresponded to vascular invasion-related lncRNA promoter methylation sites were involved in many kinds of biological processes in HCC such as PI3K-Akt signaling pathway. The accuracy of the vascular invasion-related model was consistent with our bioinformatics conclusion after being verified via MS-PCR.

Conclusion

The lncRNA promoter methylation sites are closely correlated with the process of HCC and can be utilized to improve the therapy and prognosis of HCC.

Specific gut microbiome signature predicts the early-stage lung cancer

Alterations of gut microbiota have been implicated in multiple diseases including cancer. However, the gut microbiota spectrum in lung cancer remains largely unknown. Here we profiled the gut microbiota composition in a discovery cohort containing 42 early-stage lung cancer patients and 65 healthy individuals through the 16S ribosomal RNA (rRNA) gene sequencing analysis. We found that lung cancer patients displayed a significant shift of microbiota composition in contrast to the healthy populations. To identify the optimal microbiota signature for noninvasive diagnosis purpose, we took advantage of Support-Vector Machine (SVM) and found that the predictive model with 13 operational taxonomic unit (OTU)-based biomarkers achieved a high accuracy in lung cancer prediction (area under curve, AUC = 97.6%). This signature performed reasonably well in the validation cohort (AUC = 76.4%), which contained 34 lung cancer patients and 40 healthy individuals. To facilitate potential clinical practice, we further constructed a 'patient discrimination index' (PDI), which largely retained the prediction efficiency in both the discovery cohort (AUC = 92.4%) and the validation cohort (AUC = 67.7%). Together, our study uncovered the microbiota spectrum of lung cancer patients and established the specific gut microbial signature for the potential prediction of the early-stage lung cancer.

Omics-derived hepatocellular carcinoma risk biomarkers for precision care of chronic liver diseases

Precise hepatocellular carcinoma (HCC) risk prediction will play increasingly important roles with the contemporary HCC etiologies, that is, non-alcoholic fatty liver disease and resolved hepatitis C virus infection. Because the HCC incidence rate in this emerging patient population is relatively low (~1% per year), identification of a subset of patients at the highest risk is critical to concentrate the effort and resources of regular HCC screening to those who most need it. Omics profiling has been derived using several candidate HCC risk biomarkers, which could refine HCC screening by enabling individual risk-based personalized or risk-stratified patient management. Various types of biomolecules have been explored as sources of information to predict HCC risk at various time horizons. Germline DNA polymorphisms likely reflect race/ethnicity- and/or etiology-specific susceptibility to HCC development or chronic liver disease progression toward carcinogenesis. Transcriptomic dysregulations in the diseased liver capture functional molecular status supporting oncogenesis such as inflammatory pathway and myofibroblast activation. Circulating nucleic acids, proteins, and metabolites could serve as less-invasive measures of molecular HCC risk. Characterization of gut microbiota could also inform HCC risk estimation. Each biomarker could have its niche of clinical application depending on logistics of use, performance, and costs with a goal to eventually improve patient prognosis as a part of the whole algorithm of chronic liver disease management.

A novel predicted model for hypertension based on a large cross-sectional study

Hypertension is a global public health issue and leading risk for death and disability. It is urgent to search novel methods predicting hypertension. Herein, we chose 73158 samples of physical examiners in central China from June 2008 to June 2018. After strict exclusion processes, 33570 participants with hypertension and 35410 healthy controls were included. We randomly chose 70% samples as the train set and the remaining 30% as the test set. Clinical parameters including age, gender, height, weight, body mass index, triglyceride, total cholesterol, low-density lipoprotein, blood urea nitrogen, uric acid, and creatinine were significantly increased, while high-density lipoprotein was decreased in the hypertension group versus controls. Nine optimal markers were identified by a logistic regression model, and achieved AUC value of 76.52% in the train set and 75.81% in the test set for hypertension. In conclusions, this study is the first to establish predicted models for hypertension using the logistic regression model in Central China, which provide risk factors and novel prediction method to predict and prevent hypertension.

Comparison of Bioinformatics Pipelines and Operating Systems for the Analyses of 16S rRNA Gene Amplicon Sequences in Human Fecal Samples

Amplicon high-throughput sequencing of 16S ribosomal RNA (rRNA) gene is currently the most widely used technique to investigate complex gut microbial communities. Microbial identification might be influenced by several factors, including the choice of bioinformatic pipelines, making comparisons across studies difficult. Here, we compared four commonly used pipelines (QIIME2, Bioconductor, UPARSE and mothur) run on two operating systems (OS) (Linux and Mac), to evaluate the impact of bioinformatic pipeline and OS on the taxonomic classification of 40 human stool samples. We applied the SILVA 132 reference database for all the pipelines. We compared phyla and genera identification and relative abundances across the four pipelines using the Friedman rank sum test. QIIME2 and Bioconductor provided identical outputs on Linux and Mac OS, while UPARSE and mothur reported only minimal differences between OS. Taxa assignments were consistent at both phylum and genus level across all the pipelines. However, a difference in terms of relative abundance was identified for all phyla (p < 0.013) and for the majority of the most abundant genera (p < 0.028), such as Bacteroides (QIIME2: 24.5%, Bioconductor: 24.6%, UPARSE-linux: 23.6%, UPARSE-mac: 20.6%, mothur-linux: 22.2%, mothur-mac: 21.6%, p < 0.001). The use of different bioinformatic pipelines affects the estimation of the relative abundance of gut microbial community, indicating that studies using different pipelines cannot be directly compared. A harmonization procedure is needed to move the field forward.

Alterations in the Gut Microbiome in the Progression of Cirrhosis to Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. While cirrhosis is the main risk factor for HCC, the factors influencing progression from cirrhosis to HCC remain largely unknown. Gut microbiota plays a key role in liver diseases; however, its association with HCC remains elusive. This study aimed to elucidate microbial differences between patients with HCC-associated cirrhosis (HCC-cirrhosis) and cirrhotic patients without HCC and healthy volunteers and to explore the associations between diet, lifestyle, and the microbiome of these patients. Fecal samples and food frequency questionnaires were collected from 95 individuals (30 HCC-cirrhosis patients, 38 cirrhotic patients without HCC, and 27 age- and body mass index [BMI]-matched healthy volunteers). 16S rRNA gene sequencing was performed. Bacterial richness in cirrhosis and HCC-cirrhosis patients was significantly lower than in healthy controls. The HCC-cirrhosis group was successfully classified with an area under the curve (AUC) value of 0.9 based on the dysbiotic fecal microbial signature. The HCC-cirrhosis group had a significant overrepresentation of Clostridium and CF231 and reduced Alphaproteobacteria abundance compared to cirrhotic patients without HCC. Patients with HCC-cirrhosis who were overweight displayed significantly decreased bacterial richness and altered microbiota composition compared to their normal-weight counterparts. There was a significant correlation in the HCC-cirrhosis group between intake of artificial sweeteners and the presence of Akkermansia muciniphila A unique microbial signature was observed in patients with HCC-cirrhosis, irrespective of cirrhosis stage, diet, or treatment. BMI, dietary sugar, and artificial sweeteners were significantly associated with alterations in the microbiome of HCC-cirrhosis patients. However, the increased abundance of Clostridium and CF231 observed in HCC-cirrhosis patients was not influenced by environmental factors, implying that this change was due to development of HCC.IMPORTANCE Development of hepatocellular carcinoma in patients with cirrhosis is associated with alterations in intestinal microbiota, including an escalation of dysbiosis and reduced bacterial richness. This study demonstrates that reduced bacterial richness and dysbiosis escalate with the progression of cirrhosis from compensated to decompensated cirrhosis and to HCC-associated cirrhosis (HCC-cirrhosis). Moreover, we report for the first time the effect of environmental factors on HCC-cirrhosis. Excess weight was associated with increased dysbiosis in patients with HCC compared to their normal-weight counterparts. Moreover, fatty liver, consumption of artificial sweeteners, and high-sugar foods were associated with altered microbial composition, including altered levels of Akkermansia muciniphila in HCC-cirrhosis. We have successfully determined that levels of Alphaproteobacteria and the two genera CF231 and Clostridium are significantly altered in cirrhotic patients who develop hepatocellular carcinoma, independently of cirrhosis severity and dietary habits.

Polysaccharides isolated from Cordyceps Sinensis contribute to the progression of NASH by modifying the gut microbiota in mice fed a high-fat diet

Various dietary fibers are considered to prevent obesity by modulating the gut microbiota. Cordyceps sinensis polysaccharide (CSP) is a soluble dietary fiber known to have protective effects against obesity and related diseases, but whether these effects induce any side effects remains unknown. The function and safety of CSP were tested in high-fat diet (HFD)-feding C57BL/6J mice. The results revealed that even though CSP supplementation could prevent an increase in body weight, it aggravated liver fibrosis and steatosis as evidenced by increased inflammation, lipid metabolism markers, insulin resistance (IR) and alanine aminotransferase (ALT) in HFD-induced obesity. 16S rDNA gene sequencing was used to analyze the gut microbiota composition, and the relative abundance of the Actinobacteria phylum, including the Olsenella genus, was significantly higher in CSP-treated mice than in HFD-fed mice. CSP supplementation may increase the proportion of Actinobacteria, which can degrade CSP. The high level of Actinobacteria aggravated the disorder of the intestinal flora and contributed to the progression from obesity to nonalcoholic steatohepatitis (NASH) and related diseases.

The promise and challenge of cancer microbiome research

Many microbial agents have been implicated as contributors to cancer genesis and development, and the search to identify and characterize new cancer-related organisms is ongoing. Modern developments in methodologies, especially culture-independent approaches, have accelerated and driven this research. Recent work has shed light on the multifaceted role that the community of organisms in and on the human body plays in cancer onset, development, detection, treatment, and outcome. Much remains to be discovered, however, as methodological variation and functional testing of statistical correlations need to be addressed for the field to advance.

Characterization of the lung microbiome and exploration of potential bacterial biomarkers for lung cancer

Background

Emerging evidence has suggested that dysbiosis of the lung microbiota may be associated with the development of lung diseases. However, the interplay between the lung microbiome and lung cancer remains unclear. The aim of the present study was to evaluate and compare differences in taxonomic and derived functional profiles in the lung microbiota between lung cancer and benign pulmonary diseases.

Methods

Bronchoalveolar lavage fluid (BALF) samples were collected from 32 patients with lung cancer and 22 patients with benign pulmonary diseases, and further analyzed by 16S rRNA amplicon sequencing. The obtained sequence data were deeply analyzed by bioinformatics methods.

Results

A significant differentiation trend was observed between the lung cancer and control groups based on principal coordinate analysis (PCoA), while richness and evenness in the lung microbiome of lung cancer patients generally resembled those of patients with benign pulmonary diseases. Phylum TM7 and six genera (c:TM7-3, Capnocytophaga, Sediminibacterium, Gemmiger, Blautia and Oscillospira) were enriched in the lung cancer group compared with the control group (adjust P<0.05). The area under the curve (AUC) combining the microbiome with clinical tumor markers to predict lung cancer was 84.52% (95% CI: 74.06–94.97%). In addition, predicted KEGG pathways showed that the functional differences in metabolic pathways of microbiome varied with groups.

Conclusions

The results indicated that differences existed in the lung microbiome of patients with lung cancer and those with benign pulmonary diseases, and some certain bacteria may have potential to predict lung cancer, though future larger-sample studies are required to validate this supposition.

Biomarkers in Hepatocellular Carcinoma: Diagnosis, Prognosis and Treatment Response Assessment

Hepatocellular carcinoma (HCC) is one of the main cancer-related causes of death worldwide. Thus, there is a constant search for improvement in screening, diagnosis, and treatment strategies to improve the prognosis of this malignancy. The identification of useful biomarkers for surveillance and early HCC diagnosis is still deficient, with available serum biomarkers showing low sensitivity and heterogeneous specificity despite different cut-off points, even when assessed longitudinally, or with a combination of serum biomarkers. In contrast, HCC biomarkers used for prognostic (when associated with clinical outcomes) or predictive purposes (when associated with treatment response) may have an increased clinical role in the near future. Furthermore, some serum biomarkers are already implicated as a treatment selection tool, whether to provide access to certain therapies or to assess clinical benefit after treatment. In the present review we will discuss the clinical utility and foreseen future of HCC biomarkers implicated in surveillance, diagnosis, prognosis, and post-treatment assessment.

Alterations of gut microbiome accelerate multiple myeloma progression by increasing the relative abundances of nitrogen-recycling bacteria

BACKGROUND

Gut microbiome alterations are closely related to human health and linked to a variety of diseases. Although great efforts have been made to understand the risk factors for multiple myeloma (MM), little is known about the role of the gut microbiome and alterations of its metabolic functions in the development of MM.

RESULTS

Here, in a cohort of newly diagnosed patients with MM and healthy controls (HCs), significant differences in metagenomic composition were discovered, for the first time, with higher bacterial diversity in MM. Specifically, nitrogen-recycling bacteria such as Klebsiella and Streptococcus were significantly enriched in MM. Also, the bacteria enriched in MM were significantly correlated with the host metabolome, suggesting strong metabolic interactions between microbes and the host. In addition, the MM-enriched bacteria likely result from the regulation of urea nitrogen accumulated during MM progression. Furthermore, by performing fecal microbiota transplantation (FMT) into 5TGM1 mice, we proposed a mechanistic explanation for the interaction between MM-enriched bacteria and MM progression via recycling urea nitrogen. Further experiments validated that Klebsiella pneumoniae promoted MM progression via de novo synthesis of glutamine in mice and that the mice fed with glutamine-deficient diet exhibited slower MM progression.

CONCLUSIONS

Overall, our findings unveil a novel function of the altered gut microbiome in accelerating the malignant progression of MM and open new avenues for novel treatment strategies via manipulation of the intestinal microbiota of MM patients. Video abstract.

Dietary Protein, Fiber and Coffee Are Associated with Small Intestine Microbiome Composition and Diversity in Patients with Liver Cirrhosis

: The gut microbiome is a key factor in chronic liver disease progression. In prior research, we found that the duodenal microbiome was associated with sex, ethnicity, and cirrhosis complications. Here, we examined the association between diet and the duodenal microbiome in patients with liver cirrhosis. This study included 51 participants who completed a detailed food frequency questionnaire and donated duodenal biopsies for microbiome characterization by 16S ribosomal RNA gene sequencing. Data were analyzed for alpha diversity, beta diversity, and association of taxa abundance with diet quality and components using QIIME 2 pipelines. Diet quality was assessed through calculation of the Healthy Eating Index 2010. Participants with higher adherence to protein recommendations exhibited increased microbial richness and evenness (p = 0.03) and a different microbial profile compared to those with lower adherence (p = 0.03). Prevotella-9 and Agathobacter were increased in association with increased protein adherence. Fiber consumption was also associated with the duodenal microbial profile (p = 0.01), with several taxa exhibiting significantly decreased or increased abundance in association with fiber intake. Coffee drinking was associated with microbial richness and evenness (p = 0.001), and there was a dose-response association between coffee drinking and relative abundance of Veillonella (p = 0.01). We conclude that protein, fiber, and coffee are associated with diversity and composition of the duodenal microbiome in liver cirrhosis.

High Protein Intake Is Associated With Histological Disease Activity in Patients With NAFLD

Overconsumption of carbohydrates and lipids are well known to cause nonalcoholic fatty liver disease (NAFLD), while the role of nutritional protein intake is less clear. In Western diet, meat and other animal products are the main protein source, with varying concentrations of specific amino acids. Whether the amount or composition of protein intake is associated with a higher risk for disease severity has not yet been examined. In this study, we investigated associations of dietary components with histological disease activity by analyzing detailed 14-day food records in a cohort of 61 patients with biopsy-proven NAFLD. Furthermore, we used 16S ribosomal RNA gene sequencing to detect associations with different abundances of the gut microbiota with dietary patterns. Patients with definite nonalcoholic steatohepatitis (NAFLD activity score of 5-8 on liver biopsy) had a significantly higher daily relative intake of protein compared with patients with a NAFLD activity score of 0-4 (18.0% vs. 15.8% of daily protein-based calories, P = 0.018). After adjustment for several potentially confounding factors, a higher protein intake (≥17.3% of daily protein-based calories) remained associated with definite nonalcoholic steatohepatitis, with an odds ratio of 5.09 (95% confidence interval 1.22-21.25, P = 0.026). This association was driven primarily by serine, glycine, arginine, proline, phenylalanine, and methionine. A higher protein intake correlated with a lower Bacteroides abundance and an altered abundance of several other bacterial taxa. Conclusion: A high protein intake was independently associated with more active and severe histological disease activity in patients with NAFLD. Further studies are needed to investigate the potential harmful role of dietary amino acids on NAFLD, with special attention to meat as their major source.

Toxicomicrobiomics: The Human Microbiome vs. Pharmaceutical, Dietary, and Environmental Xenobiotics

The harmful impact of xenobiotics on the environment and human health is being more widely recognized; yet, inter- and intraindividual genetic variations among humans modulate the extent of harm, mostly through modulating the outcome of xenobiotic metabolism and detoxification. As the Human Genome Project revealed that host genetic, epigenetic, and regulatory variations could not sufficiently explain the complexity of interindividual variability in xenobiotics metabolism, its sequel, the Human Microbiome Project, is investigating how this variability may be influenced by human-associated microbial communities. Xenobiotic-microbiome relationships are mutual and dynamic. Not only does the human microbiome have a direct metabolizing potential on xenobiotics, but it can also influence the expression of the host metabolizing genes and the activity of host enzymes. On the other hand, xenobiotics may alter the microbiome composition, leading to a state of dysbiosis, which is linked to multiple diseases and adverse health outcomes, including increased toxicity of some xenobiotics. Toxicomicrobiomics studies these mutual influences between the ever-changing microbiome cloud and xenobiotics of various origins, with emphasis on their fate and toxicity, as well the various classes of microbial xenobiotic-modifying enzymes. This review article discusses classic and recent findings in toxicomicrobiomics, with examples of interactions between gut, skin, urogenital, and oral microbiomes with pharmaceutical, food-derived, and environmental xenobiotics. The current state and future prospects of toxicomicrobiomic research are discussed, and the tools and strategies for performing such studies are thoroughly and critically compared.

The intestinal microbiota and hepatocellular carcinoma

The intestinal microbiota seems to play a key role in many gastrointestinal, pancreatic and liver disorders. Dysbiosis, a substantial alteration in the intestinal microbiome, is associated with chronic liver disease (CLD) compared to healthy individuals. These findings were shown in several preclinical and clinical studies and were most distinct in the stage of cirrhosis. The pathogenesis of hepatocellular carcinoma (HCC) and its underlying diseases is still not completely understood: Bacteria and related metabolites and pro-inflammatory signals may be involved. Several animal and human studies have focused on the role of intestinal microbiota in HCC. Here a key role of the intestinal microbiota in the pathogenesis could be addressed, whereby the abundance of pro-inflammatory intestinal species is increased. Additionally, some studies could demonstrate a decrease of butyrate-producing species and other species known for their anti-inflammatory potential. Furthermore, multiple preclinical studies could demonstrate that the intestinal microbiota is a key player in hepatocarcinogenesis. The intestinal microbiota seems to interact with the central pathways of hepatocarcinogenesis.

Liver cirrhosis contributes to the disorder of gut microbiota in patients with hepatocellular carcinoma

Background

Gut microbiota (GM) of patients with liver cancer is disordered, and syet no study reported the GM distribution of liver cirrhosis‐induced HCC (LC‐HCC) and nonliver cirrhosis‐induced HCC (NLC‐HCC). In this study, we aimed to characterize gut dysbiosis of LC‐HCC and NLC‐HCC to elucidate the role of GM in the pathogenesis of HCC.

Methods

A consecutive series of fecal samples of patients with hepatitis (24 patients), liver cirrhosis (24 patients), HCC (75 patients: 35 infected by HBV, 25 infected by HCV, and 15 with alcoholic liver disease), and healthy controls (20 patients) were obtained and sequenced on the Illumina Hiseq platform. The HCC group contains 52 LC‐HCC and 23 NLC‐HCC. Bioinformatic analysis of the intestinal microbiota was performed with QIIME and MicrobiomeAnalyst.

Results

Alpha‐diversity analysis showed that fecal microbial diversity was significantly decreased in the LC group, and there were significant differences in 3 phyla and 27 genera in the LC group vs the other groups (the healthy, hepatitis, and HCC groups). Beta‐diversity analysis showed that there were large differences between LC and the others. Gut microbial diversity was significantly increased from LC to HCC. Characterizing the fecal microbiota of LC‐HCC and NLC‐HCC, we found that microbial diversity was increased from LC to LC‐HCC rather than NLC‐HCC. Thirteen genera were discovered to be associated with the tumor size of HCC. Three biomarkers (Enterococcus, Limnobacter, and Phyllobacterium) could be used for precision diagnosis. We also found that HBV infection, HCV infection, or ALD (alcoholic liver disease) was not associated with intestinal microbial dysbiosis in HCC.

Conclusion

Our results suggest that GM disorders are more common in patients with LC‐HCC. The butyrate‐producing genera were decreased, while genera producing‐lipopolysaccharide (LPS) were increased in LC‐HCC patients. Further studies of GM disorders may achieve early diagnosis and new therapeutic approaches for HCC patients.

The effect of acupuncture on tumor growth and gut microbiota in mice inoculated with osteosarcoma cells

BACKGROUND

Cancer is a complex systemic disease. As a key component of traditional Chinese medicine, acupuncture is a clinically proven medical treatment for many diseases, and it also has preventative effects as it balances the body, allowing it to self-regulate. For cancer patients, acupuncture is widely used as complementary therapy to boost the immune system and reduce the side effects of radiotherapy and chemotherapy. However, few studies have determined how acupuncture against cancer, especially in regulating the intestinal flora of the tumor-burdened mice.

METHODS

We treated osteosarcoma tumor-burdened mice by using needling on different acupoints and acupoints combination, thereafter determined the effects of acupuncture on tumor growth by using imaging technology in vitro. In addition, intestinal bacteria were analyzed for further understanding the holistic and systemic treatment effects of acupuncture in osteosarcoma tumor-burdened mice.

RESULTS

Acupuncture treatment can delay tumor growth and changes of intestinal bacteria in osteosarcoma tumor-burdened mice. In detail, the loss of body weight and the development of tumor volume of mice have been postposed by needling specific acupoints. In addition, acupuncture treatment has delayed the changes of the relative abundance of Bacteroidetes, Firmicutes and Candidatus Saccharibacteria at the phylum level. Moreover, the relative abundance of many bacteria (e.g., Catabacter, Acetatifactor and Aestuariispira) has been regulated by using acupuncture treatment, and the trend of structural changes of these bacteria at the genus level has also been postposed compared to that of the tumor-burdened mice model group.

CONCLUSION

Our results suggest that acupuncture may provide a systemic treatment for cancer. Our findings encourage new and extensive research into the effects of acupuncture on changes of the intestinal microbiome associated with the development of cancer.

Characterizing the gut microbiota in patients with chronic kidney disease

Objectives: Emerging evidence suggests that gut microbiota dysbiosis plays a critical role in chronic kidney disease (CKD). However, the relationship between altered gut microbiome profiles and disease severity remains unclear. In this study, we sought to characterize the gut microbiota in CKD patients compared to healthy controls, and to explore potential relationships between gut microbiota composition and disease severity. Methods: Fecal samples were collected from 95 patients at different stages of CKD (non-dialysis patients from stage 1 to 5) and 20 healthy controls. Bacterial DNA was extracted for 16S ribosomal DNA sequencing targeting the V3-V4 region. The diversity and relative abundance of gut microbiota were analyzed as outcome indicators. Results: Differences were observed in the microbial composition and diversity of fecal samples from CKD patients and healthy controls. Specifically, disease severity was found to alter gut microbiota composition. Compared to that in healthy controls, CKD patients showed an increased abundance of Proteobacteria and decreased Synergistetes, most notably in disease stage 5. Lower levels of butyrate-producing bacteria and higher levels of potential pathogens were also detected in CKD patients. Further, Pyramidobacter and Prevotellaceae_UCG-001 were significantly decreased in the CKD1 group compared with healthy controls. Notably, nine microbial genera, including Escherichia-Shigella, Parabacteroides, Roseburia, rectale_group, Ruminococcaceae_NK4A214_group, Prevotellaceae_UCG.001, Hungatella, Intestinimonas, and Pyramidobacter, identified using a random forest model, distinguished between patients with CKD and healthy controls with high accuracy. Functional analysis also revealed that fatty acid and inositol phosphate metabolism were enriched in the CKD group, while aminoacyl-tRNA biosynthesis, oxidative phosphorylation, phenylalanine, tyrosine, and tryptophan biosynthesis, thiamine metabolism, pantothenate, and CoA biosynthesis, as well as valine, leucine, and isoleucine biosynthesis were enriched in healthy controls. Conclusion: Gut microbiota composition and function are associated with CKD severity. And, specific gut microbes are potentially helpful for CKD early diagnosis and prognosis monitoring.

Human microbiome is a diagnostic biomarker in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the third leading cause of cancer mortality worldwide. Increasing evidence indicates a close relationship between HCC and the human microbiota. Herein, we reviewed the important potential of the human microbiota as a diagnostic biomarker of HCC.

DATA SOURCES

Several innovative studies have investigated the characteristics of the gut and oral microbiomes in patients with HCC and proposed that the human microbiome has the potential to be a diagnostic biomarker of HCC. Literature from February 1999 to February 2019 was searched in the PubMed database using the keywords "microbiota" or "microbiome" or "microbe" and "liver cancer" or "hepatocellular carcinoma", and the results of clinical and experimental studies were analyzed.

RESULTS

Specific changes occur in the human microbiome of patients with HCC. Moreover, the gut microbiome and oral microbiome can be used as non-invasive diagnostic biomarkers for HCC. Furthermore, they also have certain diagnostic potential for precancerous diseases of HCC. The diagnostic potential of the blood microbiota and ascites microbiota in HCC will be gradually discovered in the future.

CONCLUSIONS

The human microbiome is valuable to the diagnosis of HCC and provides a novel strategy for targeted therapy of HCC. The human microbiome may be widely used in the diagnosis, treatment and prognosis for multiple system diseases or cancers in the future.

Probiotic Mixture of Lactobacillus plantarum Strains Improves Lipid Metabolism and Gut Microbiota Structure in High Fat Diet-Fed Mice

The global prevalence of obesity is rising year by year, which has become a public health problem worldwide. In recent years, animal studies and clinical studies have shown that some lactic acid bacteria possess an anti-obesity effect. In our previous study, mixed lactobacilli (Lactobacillus plantarum KLDS1.0344 and Lactobacillus plantarum KLDS1.0386) exhibited anti-obesity effects in vivo by significantly reducing body weight gain, Lee's index and body fat rate; however, its underlying mechanisms of action remain unclear. Therefore, the present study aims to explore the possible mechanisms for the inhibitory effect of mixed lactobacilli on obesity. C57BL/6J mice were randomly divided into three groups including control group (Control), high fat diet group (HFD) and mixed lactobacilli group (MX), and fed daily for eight consecutive weeks. The results showed that mixed lactobacilli supplementation significantly improved blood lipid levels and liver function, and alleviated liver oxidative stress. Moreover, the mixed lactobacilli supplementation significantly inhibited lipid accumulation in the liver and regulated lipid metabolism in epididymal fat pads. Notably, the mixed lactobacilli treatment modulated the gut microbiota, resulting in a significant increase in acetic acid and butyric acid. Additionally, Spearman's correlation analysis found that several specific genera were significantly correlated with obesity-related indicators. These results indicated that the mixed lactobacilli supplementation could manipulate the gut microbiota and its metabolites (acetic acid and butyric acid), resulting in reduced liver lipid accumulation and improved lipid metabolism of adipose tissue, which inhibited obesity.

Featured Gut Microbiomes Associated With the Progression of Chronic Hepatitis B Disease

Dysbiosis of gut microbiota during the progression of HBV-related liver disease is not well understood, as there are very few reports that discuss the featured bacterial taxa in different stages. The aim of this study was to reveal the featured bacterial species whose abundances are directly associated with HBV disease progression, that is, progression from healthy subjects to, chronic HBV infection, chronic hepatitis B to liver cirrhosis. Approximately 400 fecal samples were collected, and 97 samples were subjected to 16S rRNA gene sequencing after age and BMI matching. Compared with the healthy individuals, significant gut microbiota alterations were associated with the progression of liver disease. LEfSe results showed that the HBV infected patients had higher Fusobacteria, Veillonella, and Haemophilus abundance while the healthy individuals had higher levels of Prevotella and Phascolarctobacterium. Indicator analysis revealed that 57 OTUs changed as the disease progressed, and their combination produced an AUC value of 90% (95% CI: 86-94%) between the LC and non-LC groups. In addition, the abundances of OTU51 (Dialister succinatiphilus) and OTU50 (Alistipes onderdonkii) decreased as the disease progressed, and these results were further verified by qPCR. The LC patients had the higher bacterial network complexity, which was accompanied with a lower abundance of potential beneficial bacterial taxa, such as Dialister and Alistipes, while they had a higher abundance of pathogenic species within Actinobacteria. The compositional and network changes in the gut microbiota in varied CHB stages, suggest the potential contributions of gut microbiota in CHB disease progression.

Gut Microbiome-Based Diagnostic Model to Predict Coronary Artery Disease

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

Microecological Koch's postulates reveal that intestinal microbiota dysbiosis contributes to shrimp white feces syndrome

BACKGROUND

Recently, increasing evidence supports that some complex diseases are not attributed to a given pathogen, but dysbiosis in the host intestinal microbiota (IM). The full intestinal ecosystem alterations, rather than a single pathogen, are associated with white feces syndrome (WFS), a globally severe non-infectious shrimp disease, while no experimental evidence to explore the causality. Herein, we conducted comprehensive metagenomic and metabolomic analysis, and intestinal microbiota transplantation (IMT) to investigate the causal relationship between IM dysbiosis and WFS.

RESULTS

Compared to the Control shrimp, we found dramatically decreased microbial richness and diversity in WFS shrimp. Ten genera, such as Vibrio, Candidatus Bacilloplasma, Photobacterium, and Aeromonas, were overrepresented in WFS, whereas 11 genera, including Shewanella, Chitinibacter, and Rhodobacter were enriched in control. The divergent changes in these populations might contribute the observation that a decline of pathways conferring lipoic acid metabolism and mineral absorption in WFS. Meanwhile, some sorts of metabolites, especially lipids and organic acids, were found to be related to the IM alteration in WFS. Integrated with multiomics and IMT, we demonstrated that significant alterations in the community composition, functional potentials, and metabolites of IM were closely linked to shrimp WFS. The distinguished metabolites which were attributed to the IM dysbiosis were validated by feed-supplementary challenge. Both homogenous selection and heterogeneous selection process were less pronounced in WFS microbial community assembly. Notably, IMT shrimp from WFS donors eventually developed WFS clinical signs, while the dysbiotic IM can be recharacterized in recipient shrimp.

CONCLUSIONS

Collectively, our findings offer solid evidence of the causality between IM dysbiosis and shrimp WFS, which exemplify the 'microecological Koch's postulates' (an intestinal microbiota dysbiosis, a disease) in disease etiology, and inspire our cogitation on etiology from an ecological perspective. Video abstract.