Potential Microbial Markers Research Articles

Metagenomics reveals unique gut mycobiome biomarkers in psoriasis.

In present, the diagnosis of psoriasis is mainly based on the patient's typical clinical manifestations, dermoscopy and skin biopsy, and unlike other immune diseases, psoriasis lacks specific indicators in the blood. Therefore, we are required to search novel biomarkers for the diagnosis of psoriasis. In this study, we analyzed the composition and the differences of intestinal fungal communities composition between psoriasis patients and healthy individuals in order to find the intestinal fungal communities associated with the diagnosis of psoriasis. We built a machine learning model and identified potential microbial markers for the diagnosis of psoriasis. The results of AUROC (area under ROC) showed that Aspergillus puulaauensis (AUROC=0.779), Kazachstania africana (AUROC=0.750) and Torulaspora delbrueckii (AUROC=0.745) had high predictive ability (AUROC>0.7) for predicting psoriasis, While Fusarium keratoplasticum (AUROC=0.670) was relatively lower (AUROC<0.7). The strategy based on the prediction of intestinal fungal communities provides a new idea for the diagnosis of psoriasis and is expected to become an auxiliary diagnostic method for psoriasis.

Molecular surveillance of influenza A virus in Saudi Arabia: whole-genome sequencing and metagenomic approaches.

Outbreaks of influenza A viruses are generally seasonal and cause annual epidemics worldwide. Due to their frequent reassortment and evolution, annual surveillance is of paramount importance to guide vaccine strategies. The aim of this study was to explore the molecular epidemiology of influenza A virus and nasopharyngeal microbiota composition in infected patients in Saudi Arabia. A total of 103 nasopharyngeal samples from 2015 and 12 samples from 2022 were collected from patients positive for influenza A. Sequencing of influenza A as well as metatranscriptomic analysis of the nasopharyngeal microbiota was conducted using Oxford Nanopore sequencing. Phylogenetic analysis of hemagglutinin, neuraminidase segments, and concatenated influenza A genomes was performed using MEGA7. Whole-genome sequencing analysis revealed changing clades of influenza A virus: from 6B.1 in 2015 to 5a.2a in 2022. One sample containing the antiviral resistance-mediating mutation S247N toward oseltamivir and zanamivir was found. Phylogenetic analysis showed the clustering of influenza A strains with the corresponding vaccine strains in each period, thus suggesting vaccine effectiveness. Principal component analysis and alpha diversity revealed the absence of a relationship between hospital admission status, age, or gender of infected patients and the nasopharyngeal microbial composition, except for the infecting clade 5a.2a. The opportunistic pathogens Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis were the most common species detected. The molecular epidemiology appears to be changing in Saudi Arabia after the COVID-19 pandemic. Antiviral resistance should be carefully monitored in future studies. In addition, the disease severity of patients as well as the composition of the nasopharyngeal microbiota in patients infected with different clades should also be assessed.IMPORTANCEIn this work, we have found that the clade of influenza A virus circulating in Riyadh, KSA, has changed over the last few years from 6B.1 to 5a.2a. Influenza strains clustered with the corresponding vaccine strains in our population, thus emphasizing vaccine effectiveness. Metatranscriptomic analysis showed no correlation between the nasopharyngeal microbiome and the clinical and/or demographic characteristics of infected patients. This is except for the 5a.2a strains isolated post-COVID-19 pandemic. The influenza virus is among the continuously evolving viruses that can cause severe respiratory infections. Continuous surveillance of its molecular diversity and the monitoring of anti-viral-resistant strains are thus of vital importance. Furthermore, exploring potential microbial markers and/or dysbiosis of the nasopharyngeal microbiota during infection could assist in the better management of patients in severe cases.

Microbial profile in bile from pancreatic and extra-pancreatic biliary tract cancer.

Dysbiotic biliary bacterial profile is reported in cancer patients and is associated with survival and comorbidities, raising the question of its effect on the influence of anticancer drugs and, recently, the suggestion of perichemotherapy antibiotics in pancreatic cancer patients colonized by the Escherichia coli and Klebsiella pneumoniae. In this study, we investigated the microbial communities that colonize tumours and which bacteria could aid in diagnosing pancreatic and biliary cancer and managing bile-colonized patients. A retrospective study on positive bile cultures of 145 Italian patients who underwent cholangiopancreatography with PC and EPC cancer hospitalized from January 2006 to December 2020 in a QA-certified academic surgical unit were investigated for aerobic/facultative-anaerobic bacteria and fungal organisms. We found that among Gram-negative bacteria, Escherichia coli and Pseudomonas spp were the most frequent in the EPC group, while Escherichia coli, Klebsiella spp, and Pseudomonas spp were the most frequent in the PC group. Enterococcus spp was the most frequent Gram-positive bacteria in both groups. Comparing the EPC and PC, we found a significant presence of patients with greater age in the PC compared to the EPC group. Regarding Candida spp, we found no significant but greater rate in the PC group compared to the EPC group (11.7% vs 1.96%). We found that Alcaligenes faecalis was the most frequent bacteria in EPC than the PC group, among Gram-negative bacterial species. Age differences in gut microbiota composition may affect biliary habitats in our cancer population, especially in patients with pancreatic cancer. Alcaligenes faecalis isolated in the culture of bile samples could represent potential microbial markers for a restricted follow-up to early diagnosis of extra-pancreatic cancer. Finally, the prevalence of Candida spp in pancreatic cancer seems to trigger new aspects about debate about the role of fungal microbiota into their relationship with pancreatic cancer.

Gut microbiota and its metabolites in non-small cell lung cancer and brain metastasis: from alteration to potential microbial markers and drug targets.

The elevated mortality rate associated with non-small-cell lung cancer (NSCLC) is a well-established global concern. Considerable attention has been directed toward exploring the association between gut microbiota and various malignant tumors. We herein investigated the associations between the intestinal microbiome and its metabolites, particularly short-chain fatty acids (SCFAs), in patients with NSCLC at different stages, including early and brain metastasis (BM) stages. The findings aim to offer a fresh perspective on the diagnosis and management of NSCLC. Fecal samples were collected from 115 participants, comprising healthy controls (n = 35) and patients with treatment-naive NSCLC at the early stage (ELC, n = 40) and the BM stage (n = 40). Characterization of the intestinal microbiome and fecal SCFA levels was performed using 16S rRNA gene sequencing and gas chromatography. The microbial diversity in patients with NSCLC was found to be less abundant and uniform, particularly in the BM stage. Significant alterations in the community structure of the gut microbiota were observed in patients with NSCLC, with an increase in pathogens in Fusobacteria and Proteobacteria and a decrease in SCFA-producing bacteria in Firmicutes and Actinobacteria, particularly in the BM stage. Meanwhile, microbial communities displayed intricate associations in patients with NSCLC. A biomarker panel (Faecalibacterium, Bifidobacterium, Butyricicoccus, Klebsiella, Streptococcus, and Blautia) successfully distinguished patients in the ELC and BM stages from healthy controls (area under the curve: 0.884). The overall concentration of fecal SCFAs was significantly lower in patients with BM compared to patients with ELC and healthy controls. Subgroup analysis of acetate and butyrate yielded similar results. Moreover, multiple disrupted pathways in the NSCLC group were identified using the Kyoto Encyclopedia of Genes and Genomes annotation, including lipid metabolism and genetic information processing, specifically in the BM stage. Compared with healthy controls, distinct host-microbe interactions were evident in different phases of patients with NSCLC. Furthermore, specific forms of the gut microbiome and SCFAs may serve as valuable biomarkers and therapeutic targets in the diagnosis and treatment of NSCLC.

Alterations in urinary microbiota composition in urolithiasis patients: insights from 16S rRNA gene sequencing.

To investigate the urinary microbiota composition in urolithiasis patients compared to healthy controls and to identify potential microbial markers and their association with clinical parameters. A total of 66 samples, comprising 45 from urolithiasis patients and 21 from healthy controls, were analyzed. 16S rRNA gene sequencing was employed to determine the microbiota composition. Various statistical and bioinformatics tools, including ANOVA, PCoA, and LEfSe, were utilized to analyze the sequencing data and identify significant differences in microbial abundance. No significant demographic differences were observed between the two groups. Post-quality control, clean tags ranged from 60,979 to 68,736. Significant differences in α-diversity were observed between the two groups. β-diversity analysis revealed distinct clustering of the urinary microbiota in urolithiasis patients and controls. Notably, Ruminococcaceae was predominant in urolithiasis samples, while Proteobacteria was more prevalent in healthy samples. Lactobacillus was significantly overrepresented in samples from healthy females. The urinary microbiota composition in urolithiasis patients is distinct from that of healthy controls. Specific microbial taxa, such as Ruminococcaceae and Proteobacteria, could serve as potential biomarkers for urolithiasis. The findings pave the way for further exploration of the role of microbiota in urolithiasis and the development of microbiome-based therapeutic strategies.

Metataxonomic analysis of milk microbiota in the bovine subclinical mastitis.

Subclinical mastitis is one of the most widespread diseases affecting dairy herds with detrimental effects on animal health, milk productivity, and quality. Despite its multifactorial nature, the presence of pathogenic bacteria is regarded one of the main drivers of subclinical mastitis, causing a disruption of the homeostasis of the bovine milk microbial community. However, bovine milk microbiota alterations associated with subclinical mastitis still represents a largely unexplored research area. Therefore, the species-level milk microbiota of a total of 75 milk samples, collected from both healthy and subclinical mastitis-affected cows from two different stables, was deeply profiled through an ITS, rather than a traditional, and less informative, 16S rRNA gene microbial profiling. Surprisingly, the present pilot study not only revealed that subclinical mastitis is characterized by a reduced biodiversity of the bovine milk microbiota, but also that this disease does not induce standard alterations of the milk microbial community across stables. In addition, a flow cytometry-based total bacterial cell enumeration highlighted that subclinical mastitis is accompanied by a significant increment in the number of milk microbial cells. Furthermore, the combination of the metagenomic and flow cytometry approaches allowed to identify different potential microbial marker strictly correlated with subclinical mastitis across stables.

Multi-omics revealed the long-term effect of ruminal keystone bacteria and the microbial metabolome on lactation performance in adult dairy goats

BackgroundThe increased growth rate of young animals can lead to higher lactation performance in adult goats; however, the effects of the ruminal microbiome on the growth of young goats, and the contribution of the early-life rumen microbiome to lifelong growth and lactation performance in goats has not yet been well defined. Hence, this study assessed the rumen microbiome in young goats with different average daily gains (ADG) and evaluated its contribution to growth and lactation performance during the first lactation period.ResultsBased on monitoring of a cohort of 99 goats from youth to first lactation, the 15 highest ADG (HADG) goats and 15 lowest ADG (LADG) goats were subjected to rumen fluid microbiome and metabolome profiling. The comparison of the rumen metagenome of HADG and LADG goats revealed that ruminal carbohydrate metabolism and amino acid metabolism function were enhanced in HADG goats, suggesting that the rumen fluid microbiome of HADG goats has higher feed fermentation ability. Co-occurrence network and correlation analysis revealed that Streptococcus, Candidatus Saccharimonans, and Succinivibrionaceae UCG-001 were significantly positively correlated with young goats’ growth rates and some HADG-enriched carbohydrate and protein metabolites, such as propionate, butyrate, maltoriose, and amino acids, while several genera and species of Prevotella and Methanogens exhibited a negative relationship with young goats’ growth rates and correlated with LADG-enriched metabolites, such as rumen acetate as well as methane. Additionally, some functional keystone bacterial taxa, such as Prevotella, in the rumen of young goats were significantly correlated with the same taxa in the rumen of adult lactation goats. Prevotella also enriched the rumen of LADG lactating goats and had a negative effect on rumen fermentation efficiency in lactating goats. Additional analysis using random forest machine learning showed that rumen fluid microbiota and their metabolites of young goats, such as Prevotellaceae UCG-003, acetate to propionate ratio could be potential microbial markers that can potentially classify high or low ADG goats with an accuracy of prediction of > 81.3%. Similarly, the abundance of Streptococcus in the rumen of young goats could be predictive of milk yield in adult goats with high accuracy (area under the curve 91.7%).ConclusionsThis study identified the keystone bacterial taxa that influence carbohydrate and amino acid metabolic functions and shape the rumen fluid microbiota in the rumen of adult animals. Keystone bacteria and their effects on rumen fluid microbiota and metabolome composition during early life can lead to higher lactation performance in adult ruminants. These findings suggest that the rumen microbiome together with their metabolites in young ruminants have long-term effect on feed efficiency and animal performance. The fundamental knowledge may allow us to develop advanced methods to manipulate the rumen microbiome and improve production efficiency of ruminants.CFkFrpUn9s69m82LGb2Mf6Video

Identification of colorectal cancer progression-associated intestinal microbiome and predictive signature construction

ObjectiveThe relationship between intestinal microbiome and colorectal cancer (CRC) progression is unclear. This study aims to identify the intestinal microbiome associated with CRC progression and construct predictive labels to support the accurate assessment and treatment of CRC.MethodThe 192 patients included in the study were divided into stage I-II and stage III-IV CRC patients according to the pathological stages, and preoperative stools were collected from both groups for 16S rDNA sequencing of the intestinal microbiota. Pearson correlation and Spearman correlation coefficient analysis were used to analyze the differential intestinal microbiome and the correlation with tumor microenvironment and to predict the functional pathway. XGBoost model (XGB) and Random Forest model (RF) were used to construct the microbiome-based signature. The total RNA extraction from 17 CRC tumor simples was used for transcriptome sequencing.ResultThe Simpson index of intestinal microbiome in stage III-IV CRC were significantly lower than those in stage I-II CRC. Proteus, Parabacteroides, Alistipes and Ruminococcus etc. are significantly enriched genus in feces of CRC patients with stage III-IV. ko00514: Other types of O − glycan biosynthesis pathway is relevant with CRC progression. Alistipes indistinctus was positively correlated with mast cells, immune activators IL-6 and IL6R, and GOBP_PROTEIN_FOLDING_IN_ENDOPLASMIC_RETICULUM dominantly. The Random Forest (RF) model and eXtreme Gradient Boosting (XGBoost) model constructed with 42 CRC progression-associated differential bacteria were effective in distinguishing CRC patients between stage I-II and stage III-IV.ConclusionsThe abundance and diversity of intestinal microbiome may increase gradually with the occurrence and progression of CRC. Elevated fetal abundance of Proteus, Parabacteroides, Alistipes and Ruminococcus may contribute to CRC progression. Enhanced synthesis of O − glycans may result in CRC progression. Alistipes indistinctus may play a facilitated role in mast cell maturation by boosting IL-6 production. Alistipes indistinctus may work in the correct folding of endoplasmic reticulum proteins in CRC, reducing ER stress and prompting the survival and deterioration of CRC, which may owe to the enhanced PERK expression and activation of downstream UPR by Alistipes indistinctus. The CRC progression-associated differential intestinal microbiome identified in our study can be served as potential microbial markers for CRC staging prediction.

Alterations of the gut microbiota associated with the occurrence and progression of viral hepatitis.

Gut microbiota is the largest population of microorganisms and is closely related to health. Many studies have explored changes in gut microbiota in viral hepatitis. However, the correlation between gut microbiota and the occurrence and progression of viral hepatitis has not been fully clarified. PubMed and BioProject databases were searched for studies about viral hepatitis disease and 16S rRNA gene sequencing of gut microbiota up to January 2023. With bioinformatics analyses, we explored changes in microbial diversity of viral hepatitis, screened out crucial bacteria and microbial functions related to viral hepatitis, and identified the potential microbial markers for predicting risks for the occurrence and progression of viral hepatitis based on ROC analysis. Of the 1389 records identified, 13 studies met the inclusion criteria, with 950 individuals including 656 patient samples (HBV, n = 546; HCV, n = 86; HEV, n = 24) and 294 healthy controls. Gut microbial diversity is significantly decreased as the infection and progression of viral hepatitis. Alpha diversity and microbiota including Butyricimonas, Escherichia-Shigella, Lactobacillus, and Veillonella were identified as the potential microbial markers for predicting the risk of development of viral hepatitis (AUC>0.7). Microbial functions including tryptophan metabolism, fatty acid biosynthesis, lipopolysaccharide biosynthesis, and lipid metabolism related to the microbial community increased significantly as the development of viral hepatitis. This study demonstrated comprehensively the gut microbiota characteristics in viral hepatitis, screened out crucial microbial functions related to viral hepatitis, and identified the potential microbial markers for predicting the risk of viral hepatitis.

Alterations of commensal microbiota are associated with pancreatic cancer.

Dysbiosis commonly occurs in pancreatic cancer, but its specific characteristics and interactions with pancreatic cancer remain obscure. The 16S rRNA sequencing method was used to analyze multisite (oral and gut) microbiota characteristics of pancreatic cancer, chronic pancreatitis, and healthy controls. Differential analysis was used to identify the pancreatic cancer-associated genera and pathways. A random forest algorithm was adopted to establish the diagnostic models for pancreatic cancer. The chronic pancreatitis group exhibited the lowest microbial diversity, while no significant difference was found between the pancreatic cancer group and healthy controls group. Diagnostic models based on the characteristics of the oral (area under the curve (AUC) 0.916, 95% confidence interval (CI) 0.832-1) or gut (AUC 0.856; 95% CI 0.74, 0.972) microbiota effectively discriminate the pancreatic cancer samples in this study, suggesting saliva as a superior sample type in terms of detection efficiency and clinical compliance. Oral pathogenic genera (Granulicatella, Peptostreptococcus, Alloprevotella, Veillonella, etc.) and gut opportunistic genera (Prevotella, Bifidobacterium, Escherichia/Shigella, Peptostreptococcus, Actinomyces, etc.), were significantly enriched in pancreatic cancer. The 16S function prediction analysis revealed that inflammation, immune suppression, and barrier damage pathways were involved in the course of pancreatic cancer. This study comprehensively described the microbiota characteristics of pancreatic cancer and suggested potential microbial markers as non-invasive tools for pancreatic cancer diagnosis.

A new iron supplement: The chelate of pig skin collagen peptide and Fe2+ can treat iron-deficiency anemia by modulating intestinal flora.

Iron deficiency anemia (IDA) is one of the most common nutritional diseases encountered all over the world. Nowadays, oral iron supplementation is still the mainstay of IDA treatment. In this study, a new iron nutritional supplement named pig skin collagen peptides ferrous chelates (PSCP-Fe) was prepared, and its structure was characterized by the scanning electron microscopy, sykam amino acid analyzer and Fourier transform infrared spectroscopy (FTIR). The anti-IDA activity of PSCP-Fe was evaluated in low-Fe2+ diet-induced IDA in rats. 16S amplicon sequencing technology was then used to reveal the mechanism of PSCP-Fe against IDA. The results of amino acid analysis and FTIR showed that aspartic acid (Asp), arginine (Arg), histidine (His), glutamic acid (Glu), cystine (Cys), and lysine (Lys) residued in PSCP chelated readily with Fe2+ through their functional groups. PSCP-Fe treated reversed the hematology-related indexes, such as red blood cells (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentrate (MCHC), serum ferritin (SF), serum hepcidin (HEPC) and serum transferrin receptor (TFR). And its regulatory action was better than that of FeSO4. Moreover, PSCP-Fe alleviated the hepatocyte apoptosis and necrosis, Fe2+ loss, and injury in IDA rats. In addition, PSCP-Fe could significantly retrace the disturbed profile of gut microbiota in IDA rats (p < 0.05) and significantly up-regulated the relative abundances of nine bacterial genus, including Lactobacillus, Alloprevotella, unclassified_of_Oscillospiraceae, and NK4A214_group (p < 0.05). It could also downgrade the relative abundances of Subdoligranulum and Coriobacteriaceae_UCG-002 (p < 0.05). The results of Spearman's correlation analysis and distance-based redundancy analysis (db-RDA) revealed that Subdoligranulum and Christensenellaceae_R-7_group may be potential microbial markers for effective PSCP-Fe action in the treatment of IDA. Overall, our results elucidate the interactions between gut bacteria and related cytokines and reveal the mechanisms underlying the anti-IDA effect of PSCP-Fe. They will thus provide a theoretical foundation for PSCP-Fe as a new iron nutritional supplement.

Screening of potential microbial markers for lung cancer using metagenomic sequencing.

Lung cancer is the most prevalent cancer with high mortality in China, and it is associated with the dysbiosis of the lung microbiome. This study attempted to screen for specific microorganisms as potential biomarkers for distinguishing benign lung disease from lung cancer. Bronchoalveolar lavage fluid (BALF) sample was selected in the study instead of saliva to avoid contamination with oral microorganisms, and microbial taxonomic and functional differences in BALF samples from patients with lung cancer and those with those from patients with benign lung diseases were performed based on metagenomic next-generation sequencing, for the first time, so that microorganisms other than bacteria could be included. The results showed that the intrasample diversity of malignant samples was different from benign samples, and the microbial differences among malignant samples were smaller, with lower microbial diversity, significantly changed microbial abundance and metabolic functions. Metabolic function analysis revealed amino acid-related metabolism was more prevalent in benign samples, whereas carbohydrate-related metabolism was more prevalent in malignant samples. By LEfSe, Metastat and Random Forest analysis, we identified a series of important differential microorganisms. Importantly, the model combining five key genera plus one tumor marker (neuron-specific enolase) as indicators presented the optimal disease typing performance. Thus results suggest the value of these differential microorganisms enriched in tumors in mechanism research and may be potential new targets for lung cancer therapy. More importantly, the biomarkers identified in this study can be conducive to improve the clinical diagnosis of lung cancer and have good application prospects.

Multi-omics reveals diet-induced metabolic disorders and liver inflammation via microbiota-gut-liver axis

The gut microbiota medicated gut-liver axis is vital for liver function and health. We aimed to explore the underlying molecular mechanism of diet-induced metabolic liver disorders via microbiota-gut-liver axis using multi-omics. Metataxonomics, metaproteomics, transcriptomics, and metabolomics were conducted on liver tissue and biofluids (gastrointestinal contents and blood) to elucidate the microbial mechanism related to metabolic disorders and liver injury. The hepatic inflammation occurred based on histomorphology after feeding a long-term grain-based high-energy diet, and the serum biochemical parameters and proinflammatory cytokines were significantly activated. Metaproteomics analysis indicated that the high-energy diet reduced anti-infection, immunity, anti-oxidant functions, and increased cell death and damage of rumen microbiome. Ruminal Ruminococcus_2, Solobacterium, and Syntrophococcu and jejunal Pirellula were potential microbial markers of liver disorders. The high-energy diet promoted hepatic inflammatory response and cytokine/chemokine-mediated signaling pathways located in the core of the functional genomic network. The high-energy diet increased indoxyl sulfate and p-cresol sulfate and decreased triterpenoids in the liver that were the potential biomarkers associated with metabolic liver disorders. Integrated multi-omics analyses showed interactions among the rumen and jejunum microbiota, circulating metabolites, and liver gene expression, suggesting a systemic immune response and liver disorder that signals through the microbiota-gut-liver axis.

A role of gut–microbiota–brain axis via subdiaphragmatic vagus nerve in depression-like phenotypes in Chrna7 knock-out mice

The α7 subtype of the nicotinic acetylcholine receptor (α7 nAChR: coded by Chrna7) is known to regulate the cholinergic ascending anti-inflammatory pathway. We previously reported that Chrna7 knock-out (KO) mice show depression-like behaviors through abnormal composition of gut microbiota and systemic inflammation. Given the role of subdiaphragmatic vagus nerve in gut–microbiota–brain axis, we investigated whether subdiaphragmatic vagotomy (SDV) could affect depression-like behaviors, abnormal composition of gut microbiota, and microbes-derived metabolites in Chrna7 KO mice. SDV blocked depression-like behaviors and reduced expression of synaptic proteins in the medial prefrontal cortex (mPFC) of Chrna7 KO mice. LEfSe (linear discriminant analysis effect size) analysis revealed that the species Lactobacillus sp. BL302, the species Lactobacillus hominis, and the species Lactobacillus reuteri, were identified as potential microbial markers in the KO + SDV group. There were several genus and species altered among the three groups [wild-type (WT) + sham group, KO + sham group, KO + SDV group]. Furthermore, there were several plasma metabolites altered among the three groups. Moreover, there were correlations between relative abundance of several microbiome and behavioral data (or synaptic proteins). Network analysis showed correlations between relative abundance of several microbiome and plasma metabolites (or behavioral data). These data suggest that Chrna7 KO mice produce depression-like behaviors and reduced expression of synaptic proteins in the mPFC through gut–microbiota–brain axis via subdiaphragmatic vagus nerve.

Antibiotic-induced microbiome depletion improves LPS-induced acute lung injury via gut-lung axis

AimsAcute lung injury (ALI) is an acute inflammatory disorder. However, the precise mechanisms underlying the pathology of ALI remain elusive. An increasing evidence suggests the role of the gut-microbiota axis in the pathology of lung injury. This study aimed to investigate whether antibiotic-induced microbiome depletion could affect ALI in mice after lipopolysaccharide (LPS) administration. Main methodsThe effects of antibiotic cocktail (ABX) on ALI in the mice after intratracheally administration of LPS (5 mg/kg) were examined. Furthermore, 16s rRNA analysis and measurement of short-chain fatty acids in feces samples and metabolomics analysis of blood samples were performed. Key findingsLPS significantly increased the interleukin-6 (IL-6) levels in the bronchoalveolar lavage fluid (BALF) of water-treated mice. Interestingly, an ABX significantly attenuated the LPS-induced increase in IL-6 in BALF and lung injury scores. Furthermore, ABX and/or LPS treatment markedly altered the α- and β-diversity of the gut microbiota. There were significant differences in the α- and β-diversity of the water + LPS group and ABX + LPS group. LEfSe analysis identified Enterococusfaecalis, Clostriumtertium, and Bacteroidescaecimyris as potential microbial markers for ABX + LPS group. Untargeted metabolomics analysis identified several plasma metabolites responsible for discriminating water + LPS group from ABX + LPS group. There were correlations between the relative abundance of the microbiome and plasma metabolites. Integrative network analysis showed correlations between IL-6 levels in BALF and several gut microbes (or plasma metabolites). SignificanceThese data suggest that ABX-induced microbiome depletion could protect against LPS-induced ALI via the gut-microbiota-lung axis.

Association of the Microbiota and Pancreatic Cancer: Opportunities and Limitations.

The human body is thoroughly colonized by a wide variety of microorganisms, termed microbiota. Pancreatic cancer, one of the most aggressive forms of cancer, is no exception. The microbiota of pancreatic cancer largely influences and even dominates the occurrence, development and outcome of pancreatic cancer in many ways. Studies have shown that microbiota could change the malignant phenotype and prognosis of pancreatic cancer by stimulating persistent inflammation, regulating the antitumor immune system, changing the tumor microenvironment and affecting cellular metabolism. This is why the association of the microbiota with pancreatic cancer is an emerging area of research that warrants further exploration. Herein, we investigated the potential microbial markers of pancreatic cancer, related research models, the mechanism of action of microbiota in pancreatic cancer, and pancreatic cancer-microbiota-related treatment.

Metagenome-wide association study of gut microbiome revealed potential microbial marker set for diagnosis of pediatric myasthenia gravis

BackgroundMyasthenia gravis (MG) is an acquired immune-mediated disorder of the neuromuscular junction that causes fluctuating skeletal muscle weakness and fatigue. Pediatric MG and adult MG have many different characteristics, and current MG diagnostic methods for children are not quite fit. Previous studies indicate that alterations in the gut microbiota may be associated with adult MG. However, it has not been determined whether the gut microbiota are altered in pediatric MG patients.MethodsOur study recruited 53 pediatric MG patients and 46 age- and gender-matched healthy controls (HC). We sequenced the fecal samples of recruited individuals using whole-genome shotgun sequencing and analyzed the data with in-house bioinformatics pipeline.ResultsWe built an MG disease classifier based on the abundance of five species, Fusobacterium mortiferum, Prevotella stercorea, Prevotella copri, Megamonas funiformis, and Megamonas hypermegale. The classifier obtained 94% area under the curve (AUC) in cross-validation and 84% AUC in the independent validation cohort. Gut microbiome analysis revealed the presence of human adenovirus F/D in 10 MG patients. Significantly different pathways and gene families between MG patients and HC belonged to P. copri, Clostridium bartlettii, and Bacteroides massiliensis. Based on functional annotation, we found that the gut microbiome affects the production of short-chain fatty acids (SCFAs), and we confirmed the decrease in SCFA levels in pediatric MG patients via serum tests.ConclusionsThe study indicated that altered fecal microbiota might play vital roles in pediatric MG’s pathogenesis by reducing SCFAs. The microbial markers might serve as novel diagnostic methods for pediatric MG.

Abnormalities in the composition of the gut microbiota in mice after repeated administration of DREADD ligands

Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) are known as genetically modified G-protein-coupled receptors (GPCRs), which can be activated by synthetic ligands such as clozapine N-oxide (CNO) and DREADD agonist 21 (compound 21: C21). The brain-gut-microbiota axis has a crucial role in bidirectional interactions between the brain and the gastrointestinal microbiota. In this study, we investigated whether repeated administration of CNO or C21 could influence the gut microbiota and short-chain fatty acids (SCFAs) in feces of adult mice. Repeated administration of CNO or C21 as drinking water did not alter the α- and β-diversity of gut microbiota in mice compared with control mice. However, we found significant changes in relative abundance for several bacteria in the CNO (or C21) group at the taxonomic level compared to the control group. The linear discriminant analysis effect size (LEfSe) algorithm distinguished the family Prevotellaceae, the genus Anaerocolumna, the genus Prevotella, and the genus Frisingicoccus, these four specific microbial markers for the CNO group relative to the control group. In addition, the LEfSe algorithm identified the family Clostridiaceae, the genus Faecalicatena and the genus Marinisporobacter, these three bacteria of different taxonomic as potential microbial markers for the C21 group relative to the control group. In contrast, repeated administration of CNO (or C21) did not alter SCFAs in feces samples of adult mice. The data suggest that repeated administration of CNO or C21 contributes to an unusual organization of the gut microbiota in adult mice. Therefore, abnormalities in the composition of gut microbiota by repeated dosing of DREADD ligands should be taken into consideration for behavioral and biological functions in rodents treated with DREADD ligands.

Pulmonary Micro-Ecological Changes and Potential Microbial Markers in Lung Cancer Patients.

The relationship between the microbiome and disease has been investigated for many years. As a highly malignant tumor, biomarkers for lung cancer are diverse. However, precision of these biomarkers has not yet been achieved. It has been confirmed that lung microecology changes in lung cancer patients compared with healthy individuals. Furthermore, the abundance of some bacterial species shows obvious changes, suggesting their potential use as a microbial marker for the detection of lung cancer. In addition, recent studies have confirmed that inflammation, immune response, virulence factors, and metabolism may be potential mechanisms linking the microbiome with carcinogenesis. In this review, microbiome studies of lung cancer, potential mechanisms, potential microbial markers, and the influence of the microbiome on the diagnosis and treatment of lung cancer are summarized, providing theoretical strategies for the diagnosis and treatment of lung cancer.

Characterization of Bacterial Communities Associated with Rhynchophorus ferrugineus Olivier (Coleoptera: Curculionidae) and its Host Phoenix sylvestris.

This study measured the changes of microorganisms in the midgut and habitat niche of Rhynchophorus ferrugineus Olivier, an invasive quarantine pest, by Illumina sequencing. The bacterial diversity in the R. ferrugineus larvae midgut and their habitat niche was compared to the uninfected P. sylvestris. The Proteobacteria and Firmicutes occupied a dominant position in the R. ferrugineus midgut and infected P. sylvestris, while in the uninfected P. sylvestris the predominant bacterial phylum was the Cyanobacteria. Enterobacter, Dysgonomonas, and Entomoplasma were the dominant bacterial genera in R. ferrugineus midgut and also within the infected trees and uninfected trees with low relative abundance. These bacteria could be exploited as the biopesticide vector to control R. ferrugineus population. Besides, Sphingobacterium, Shinella, and Rhodobacter genera had the same distribution pattern in the infected and uninfected P. sylvestris, and these bacteria were not found in the midgut of R. ferrugineus. Interestingly, Paludibacter and Parabacteroides were only distributed in the wood fiber of the infected P. sylvestris, which could be used as potential microbial markers to detect if the palm plants are damaged by the R. ferrugineus. The results of this study will be beneficial to the development of control strategies for R. ferrugineus.