Gut Microbiome Metagenomic Sequencing And Metabonomic Analysis Of Choledocholithiasis Concurrent With Cholangitis

Background and objectiveCholedocholithiasis concurrent with cholangitis（CC）,known as the sudden onset of obstruction and inflammation in the common bile duct owing to extrahepatic bile duct stones,is characterized by severe abdominal pain,obstructive jaundice and acute bacterial infection in the bile duct.Currently,CC occurs in people with cholelithiasis or is caused by gallstones originating in the gallbladder and spontaneously migrating into the common bile duct.In the United States,10%to 20%of patients with symptomatic cholelithiasis have been documented to have concomitant choledocholithiasis,which also leads to the admission of 275,000 acute biliary pancreatitis cases annually.Furthermore,cholangitis caused by bile duct obstruction has been considered a potentially severe complication of choledocholithiasis,leading up to 10%mortality rates.At present,there are still some deficiencies in the diagnosis,treatment and prevention of choledocholithiasisIn recent years,with the continuous maturity of 16S RNA sequencing and metagenomic sequencing technologies,plenty of studies indicated that there is a close relationship between gut microbiome and human health.To date,gut microbiome has been reported to act as a key environmental factor to promote metabolism and synthesis of nutritional factors in the gut,as well as maintain renewal and integrity of the intestinal mucosa,simultaneously maintaining the effective immune defensive ability of the gut More importantly,accumulated evidence has demonstrated that the gut microbiome could have a potential influence on many disease processes,especially on the development of hepatobiliary disorders through the enterohepatic bile acid recycling process,which maintains continuous contact between the biliary system and complex bacterial communitiesIn the past,a small number of studies have explored the characteristic gut dysbiosis of patients with cholelithiasis and its possible influence on the occurrence and development of cholelithiasis.However,these studies have a small sample size,do not strictly control factors such as antibiotics and prebiotics that clearly affect the composition of the intestinal microbiota.Most importantly,there is no study on the characteristic gut dysbiosis,metabolite profiles and the possible roles in patients with CC.Methods1.Sample collection and baseline information analysisFrom February 2016 to October 2020,fecal samples of patients with CC were collected through the established liver and gallbladder disease sample bank.The patients with CC were diagnosed according to the clinical typical symptoms,blood sample tests,bile culture,B ultrasound,computed tomography（CT）or magnetic resonance cholangiography（MRCP）,which were subsequently confirmed by ERCP.Demographics of participants and clinical data were retrieved from hospital medical records.Inclusion criteria included the following:（1）20-75 years old,and（2）a validated diagnosis of CC with bile culture bacteria being positive and without a previous medical history of tumor or uncontrolled chronic diseases involving the heart,lung,kidney and liver.The exclusion criteria were as follows:（1）pregnancy or breastfeeding,（2）treatment with antibiotics during the previous 2 months,（3）long-term use of prebiotics or probiotics,（3）history of intestinal surgery or chronic intestinal disease such as IBD,and（4）chronic hepatitis or liver disease with functional damage.Stool samples were collected from a total of 254 patients newly diagnosed CC.After rigorous screening and low-quality sample removal,29 patients with CC and 29 age-,sex-and BMI-matched healthy individuals were enrolled for final gut microbiome analysis.SPSS was applied for clinical statistical analyses.2.Metagenomic sequencing and bioinformatic analysisIllumina HiSeq4000 platform was employed for metagenome sequencing in ac cordance with the standardized process.Subsequently,the relative abundance of do minant bacteria in CCs and HCs were counted,and α diversity and β diversity w ere analyzed to further describe the differences of gut microbiome profile between CCs and HCs.LEfSE was performed to determine the differences in relative abu ndance and the effect size of the microbial features between CCs and HCs.The characteristic bacteria of CC were screened by LDA,and the changes of the relat ed KEGG metabolic pathways were predicted.The correlation between clinical par ameters and characteristic bacteria of CC was evaluated using partial Spearman’s r ank-based correlation test.3.Non-targeted metabolomics analysisLiquid chromatography/mass spectrometry（LC/MS）analysis was performed to quantify the metabolites in samples according to the standardized process.VIP value of the PLS-DA model（threshold value>1）was combined with the P-value of the t-test（P<0.05）to identify the features of different metabolites.Markedly changed metabolites（VIP>1.0 and P<0.05）were identified and further analyzed to validate aberrant metabolic patterns between CCs and HCs.According to the metabolite classification information in the HMDB 4.0（www.hmdb.ca）database,markedly changed metabolites are clustered To explore the potential metabolic pathways of the dominant different metabolites,Scipy（Python）（Version 1.0.0）was applied to annotate significantly different KEGG pathways of the metabolites.Results1.Abnormal serum inflammation indexes and liver function indexes,and bile culture in patients with CCBased on the demographics analysis,CCs and HCs were well balanced in age,sex and BMI,while significant abnormalities of white blood cell（WBC）,c-reaction protein（CRP）and hepatic function were observed as a result of obstruction and inflammation of the bile duct in CCs.Bile culture of patients with CC dete cted a variety of pathogenic bacteria,including Escherichia_coli and Klebsiella_oxytoca.2.Change of the overall gut microbial community in CCs.We counted the top 50 genera in the two groups and found that the abundance of multiple dominant genera was different between CCs and HCs.The most different genera were listed to visualize the variations in the gut microbiome composition of the fecal samples in CCs and HCs,including Prevotella（CCs:4.09%vs HCs:7.37%）,Escherichia（CCs:7.32%vs HCs:2.78%）,unclassified_fEnterobacteriaceae（CCs:7.08%vs HCs:1.59%）,Blautia（CCs:3.63%vs HCs:4.31%）,Faecalibacterium（CCs:2.78%vs HCs:4.44%）,Roseburia（CCs:2.49%vs HCs:4.14%）,and Clostridium（CCs:1.84%vs HCs:4.54%）.Analysis of gut microbiome diversity found that the Shannon diversity index significantly reduced in CCs compared with HCs β=0.043).Meanwhile,PCoA of weighted UniFrac analysis of β-diversity showed that compared with HCs,the overall fecal microbiota community structure was significantly different in CCs（the total diversity captured by the top three principal coordinates was 46.13%）（PERMANOVA:pseudo-F statistic:3.6,P=0.002;ANOSIM:R=0.13,P=0.008）.Venn diagram indicated that the clustering of species of CCs is less than HCs3.Different bacterial abundances and functional profile of gut microbiome between CCs and HCsThe dominant 12 species were identified（LDA score>3.0,P<0.05）,including a significant enrichment of unclassified_fEnterobacteriaceae,Escherichia_coli,Klebsiella_oxytoca,Clostridium_bolteae,Enterococcus_casseliflavus and Enterococcus_casseliflavus in CCs and decreased abundance in bacteria including Roseburia_faecis,Clostridium_sp_CAG₁27,Eubacterium_rectale,Eubacterium_sp_CAG₂02,Eubacterium_sp_CAG₁80 and Dorea_longicatena.The KEGG pathways related to characteristic bacteria were also different between CCs and HCs.Among them,the a bundance of bio film formation-Escherichia coli,lipopoly saccharide biosynthesis,propanoate metabolism,and glutathione metabolism,lysine degradation,tryptophan metabolism increased in CCs and the abundance of biosynthesis of amino acids,purine metabolism and lysine biosynthesis,alanine aspartate and glutamate metabolism decreased in CCs4.Metabolite identification and analysis of metabolite profiles between CCs and HCs49 markedly changed metabolites（VIP>1.0 and p<0.05）were identified and further analyzed in individual samples to validate aberrant metabolic patterns between CCs and HCs.Remarkably,in CCs,high concentrations of N-palmitoylsphingosine and low levels of kynurenic acid（KYNA）,5-methoxyretryptamine and 2-formaminobenzoylacetate implicated that metabolism of tryptophan and ceramides might play an important role in changed metabolite profiles and aberrant metabolic patterns between CCs and HCs.Scipy（Python）（Version 1.0.0）was applied to annotate significantly different KEGG pathways of the metabolites,and 8 predominant metabolic pathways of the important different metabolites were identified.The different abundant KEGG pathways involving tryptophan metabolism and the sphingolipid signaling pathway were in line with the alterations in the predominant fecal metabolites closely related to gut microbiota dysbiosis and inflammation in CCConclusions1.The inflammatory indexes and liver function parameters of patients with CC were obviously abnormal,and some characteristic bacteria from the bile culture of patients with CC were detected,such as Escherichia_coli,Klebsiella_oxytoca.2.The overall gut microbial community of CCs changed,and the diversity and richness of gut microbioma reduced in CCs.3.The alterant of abundances of characteristic species of CC,such as unclassified f Enterobacteriaceae、Escherichia_coli,Klebsiella_oxytoca,was confirmed.These characteristic species and associated KEGG pathways,including biofilm formation-Escherichia coli and lipopolysaccharide biosynthesis,might promote the progressing of CC.4.The changed metabolite profiles,and different concentration of characteristic metabolites,such as N-palmitoylsphingosine and KYNA were validated.The changed KYNA and its involved tryptophan metabolic pathway as well as N-palmitoylsphingosterol and its associated neuramide and sphingolipid signaling pathway may play a important role in the progressive of CC.