Li Shao

Alterations and correlations of the gut microbiome, metabolism and immunity in patients with primary biliary cirrhosis.

We selected 42 early-stage primary biliary cirrhosis (PBC) patients and 30 healthy controls (HC). Metagenomic sequencing of the 16S rRNA gene was used to characterize the fecal microbiome. UPLC-MS/MS assaying of small molecules was used to characterize the metabolomes of the serum, urine and feces. Liquid chip assaying of serum cytokines was used to characterize the immune profiles. The gut of PBC patients were depleted of some potentially beneficial bacteria, such as Acidobacteria, Lachnobacterium sp., Bacteroides eggerthii and Ruminococcus bromii, but were enriched in some bacterial taxa containing opportunistic pathogens, such as γ-Proteobacteria, Enterobacteriaceae, Neisseriaceae, Spirochaetaceae, Veillonella, Streptococcus, Klebsiella, Actinobacillus pleuropneumoniae, Anaeroglobus geminatus, Enterobacter asburiae, Haemophilus parainfluenzae, Megasphaera micronuciformis and Paraprevotella clara. Several altered gut bacterial taxa exhibited potential interactions with PBC through their associations with altered metabolism, immunity and liver function indicators, such as those of Klebsiella with IL-2A and Neisseriaceae with urinary indoleacrylate. Many gut bacteria, such as some members of Bacteroides, were altered in their associations with the immunity and metabolism of PBC patients, although their relative abundances were unchanged. Consequently, the gut microbiome is altered and may be critical for the onset or development of PBC by interacting with metabolism and immunity.

The Serum Profile of Hypercytokinemia Factors Identified in H7N9-Infected Patients can Predict Fatal Outcomes

The novel avian origin influenza A (H7N9) virus has caused severe diseases in humans in eastern China since the spring of 2013. Fatal outcomes of H7N9 infections are often attributed to the severe pneumonia and acute respiratory distress syndrome (ARDS). There is urgent need to discover biomarkers predicting the progression of disease and fatal outcome of potentially lethal flu infections, based on sound statistical analysis. We discovered that 34 of the 48 cytokines and chemokines examined in this study were significantly elevated in the plasma samples from patients infected with H7N9. We report for the first time that the levels of MIF, SCF, MCP-1, HGF, and SCGF-β are highly positively linked to disease severity and the profile of mediators MIF, SCF, MCP-1, HGF, SCGF-β, IP-10, IL-18, and IFN-γ is an independent outcome predictor.

Development of diagnostic criteria and a prognostic score for hepatitis B virus-related acute-on-chronic liver failure

Objective The definition of acute-on-chronic liver failure (ACLF) based on cirrhosis, irrespective of aetiology, remains controversial. This study aimed to clarify the clinicopathological characteristics of patients with hepatitis B virus-related ACLF (HBV-ACLF) in a prospective study and develop new diagnostic criteria and a prognostic score for such patients. Design The clinical data from 1322 hospitalised patients with acute decompensation of cirrhosis or severe liver injury due to chronic hepatitis B (CHB) at 13 liver centres in China were used to develop new diagnostic and prognostic criteria. Results Of the patients assessed using the Chronic Liver Failure Consortium criteria with the exception of cirrhosis, 391 patients with ACLF were identified: 92 with non-cirrhotic HBV-ACLF, 271 with cirrhotic HBV-ACLF and 28 with ACLF with cirrhosis caused by non-HBV aetiologies (non-HBV-ACLF). The short-term (28/90 days) mortality of the patients with HBV-ACLF were significantly higher than those of the patients with non-HBV-ACLF. Total bilirubin (TB) ≥12 mg/dL and an international normalised ratio (INR) ≥1.5 was proposed as an additional diagnostic indicator of HBV-ACLF, and 19.3% of patients with an HBV aetiology were additionally diagnosed with ACLF. The new prognostic score (0.741×INR+0.523×HBV-SOFA+0.026×age+0.003×TB) for short-term mortality was superior to five other scores based on both discovery and external validation studies. Conclusions Regardless of the presence of cirrhosis, patients with CHB, TB ≥12 mg/dL and INR ≥1.5 should be diagnosed with ACLF. The new criteria diagnosed nearly 20% more patients with an HBV aetiology with ACLF, thus increasing their opportunity to receive timely intensive management.

Efficacy of Fluidized Bed Bioartificial Liver in Treating Fulminant Hepatic Failure in Pigs: A Metabolomics Study.

Bioartificial livers may act as a promising therapy for fulminant hepatic failure (FHF) with better accessibility and less injury compared to orthotopic liver transplantation. This study aims to evaluate the efficacy and safety of a fluidized bed bioartificial liver (FBBAL) and to explore its therapeutic mechanisms based on metabolomics. FHF was induced by D-galactosamine. Eighteen hours later, pigs were treated with an FBBAL containing encapsulated primary porcine hepatocytes (B group), with a sham FBBAL (containing cell-free capsules, S group) or with only intensive care (C group) for 6 h. Serum samples were assayed using ultra-performance liquid chromatography-mass spectrometry. The difference in survival time (51.6 ± 7.9 h vs. 49.3 ± 6.6 h) and serum metabolome was negligible between the S and C groups, whereas FBBAL treatment significantly prolonged survival time (70.4 ± 11.5h, P < 0.01) and perturbed the serum metabolome, resulting in a marked decrease in phosphatidylcholines, lysophosphatidylcholines, sphingomyelinase, and fatty acids and an increase in conjugated bile acids. The FBBAL exhibits some liver functions and may exert its therapeutic effect by altering the serum metabolome of FHF pigs. Moreover, alginate–chitosan capsules have less influence on serum metabolites. Nevertheless, the alterations were not universally beneficial, revealing that much should be done to improve the FBBAL.

Dynamic Patterns of serum metabolites in fulminant hepatic failure pigs

Fulminant hepatic failure (FHF) is still an intractable disease associated with serious metabolic disorder. Investigating the dynamic changes of serum metabolites during the development of FHF would facilitate revealing the pathogenesis and also promote its treatment. Therefore, this study characterized the dynamic metabonome of serum from FHF Pigs using ultra performance liquid chromatography–mass spectrometry. Based on multiple statistical analysis of the resulting dataset, three types of up-regulated and one type of down-regulated patterns were delineated. Each pattern demonstrated distinct trends at different stages during the whole process of FHF, implying the differential clinical significance of them. Specifically, aromatic amino acids (Pattern 1) and lysophosphatidylcholines (LPCs) (Pattern 4) might be good markers for evaluating the severity of FHF, while some conjugated bile acids, long chain acylcarnitines (Pattern 2) and Glycocholic acid (Pattern 3) could indicate liver injury in the early stage. Inspired from the PCA plot that the pathogenetic condition of FHF aggravated with sampling time, a linear discriminant analysis (LDA) model based on phenylalanine and LPC 18:1 were further constructed for evaluating the severity of FHF. The leave-one-out cross-validation accuracy of 91.67% for the training set and the prediction accuracy of 92.31% for the external validation set confirmed its excellent performance. In conclusion, findings obtained from the present study, including four types of Dynamic Patterns of serum metabolites during FHF development and an LDA model for evaluating the severity of FHF, will be of great help to the research and management of FHF in the future.

Profiling, clinicopathological correlation and functional validation of specific long non-coding RNAs for hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is one of the most prevalent and aggressive malignancies worldwide. Studies seeking to advance the overall understanding of lncRNA profiling in HCC remain rare.MethodsThe transcriptomic profiling of 12 HCC tissues and paired adjacent normal tissues was determined using high-throughput RNA sequencing. Fifty differentially expressed mRNAs (DEGs) and lncRNAs (DELs) were validated in 21 paired HCC tissues via quantitative real-time PCR. The correlation between the expression of DELs and various clinicopathological characteristics was analyzed using Student’s t-test or linear regression. Co-expression networks between DEGs and DELs were constructed through Pearson correlation co-efficient and enrichment analysis. Validation of DELs’ functions including proliferation and migration was performed via loss-of-function RNAi assays.ResultsIn this study, we identified 439 DEGs and 214 DELs, respectively, in HCC. Furthermore, we revealed that multiple DELs, including NONHSAT003823, NONHSAT056213, NONHSAT015386 and especially NONHSAT122051, were remarkably correlated with tumor cell differentiation, portal vein tumor thrombosis, and serum or tissue alpha fetoprotein levels. In addition, the co-expression network analysis between DEGs and DELs showed that DELs were involved with metabolic, cell cycle, chemical carcinogenesis, and complement and coagulation cascade-related pathways. The silencing of the endogenous level of NONHSAT122051 or NONHSAT003826 could significantly attenuate the mobility of both SK-HEP-1 and SMMC-7721 HCC cells.ConclusionThese findings not only add knowledge to the understanding of genome-wide transcriptional evaluation of HCC but also provide promising targets for the future diagnosis and treatment of HCC.

Erratum: Corrigendum: The Serum Profile of Hypercytokinemia Factors Identified in H7N9-Infected Patients can Predict Fatal Outcomes

Scientific Reports 5: Article number: 10942; published online: 01 June 2015; updated: 23 February 2016 This Article contains typographical errors in Table 2 where ‘Week 2 (N = 32)’ was incorrectly given as ‘Week (N = 2)’.

Diagnosis of Clostridium difficile infection using an UPLC–MS based metabolomics method

IntroductionThe fecal metabolome of Clostridium difficile (CD) infection is far from being understood, particularly its non-volatile organic compounds. The drawbacks of current tests used to diagnose CD infection hinder their application.ObjectiveThe aims of this study were to find new characteristic fecal metabolites of CD infection and develop a metabolomics model for the diagnosis of CD infection.MethodsUltra-performance liquid chromatography-mass spectrometry (UPLC–MS) was used to characterize the fecal metabolome of CD positive and negative diarrhea and healthy control stool samples.ResultsDiarrhea and healthy control samples showed distinct clusters in the principal components analysis score plot, and CD positive group and CD negative group demonstrated clearer separation in a partial least squares discriminate analysis model. The relative abundance of sphingosine, chenodeoxycholic acid, phenylalanine, lysophosphatidylcholine (C16:0), and propylene glycol stearate was higher, and the relative abundance of fatty amide, glycochenodeoxycholic acid, tyrosine, linoleyl carnitine, and sphingomyelin was lower in CD positive diarrhea groups, than in the CD negative group. A linear discriminant analysis model based on capsiamide, dihydrosphingosine, and glycochenodeoxycholic acid was further constructed to identify CD infection in diarrhea. The leave-one-out cross-validation accuracy and area under receiver operating characteristic curve for the training set/external validation set were 90.00/78.57%, and 0.900/0.7917 respectively.ConclusionsCompared with other hospital-onset diarrhea, CD diarrhea has distinct fecal metabolome characteristics. Our UPLC–MS metabolomics model might be useful tool for diagnosing CD diarrhea.

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

Objective To characterise gut microbiome in patients with hepatocellular carcinoma (HCC) and evaluate the potential of microbiome as non-invasive biomarkers for HCC. Design We collected 486 faecal samples from East China, Central China and Northwest China prospectively and finally 419 samples completed Miseq sequencing. We characterised gut microbiome, identified microbial markers and constructed HCC classifier in 75 early HCC, 40 cirrhosis and 75 healthy controls. We validated the results in 56 controls, 30 early HCC and 45 advanced HCC. We further verified diagnosis potential in 18 HCC from Xinjiang and 80 HCC from Zhengzhou. Results Faecal microbial diversity was increased from cirrhosis to early HCC with cirrhosis. Phylum Actinobacteria was increased in early HCC versus cirrhosis. Correspondingly, 13 genera including Gemmiger and Parabacteroides were enriched in early HCC versus cirrhosis. Butyrate-producing genera were decreased, while genera producing-lipopolysaccharide were increased in early HCC versus controls. The optimal 30 microbial markers were identified through a fivefold cross-validation on a random forest model and achieved an area under the curve of 80.64% between 75 early HCC and 105 non-HCC samples. Notably, gut microbial markers validated strong diagnosis potential for early HCC and even advanced HCC. Importantly, microbial markers successfully achieved a cross-region validation of HCC from Northwest China and Central China. Conclusions This study is the first to characterise gut microbiome in patients with HCC and to report the successful diagnosis model establishment and cross-region validation of microbial markers for HCC. Gut microbiota-targeted biomarkers represent potential non-invasive tools for early diagnosis of HCC.

Transcriptome Analysis of Porcine PBMCs Reveals the Immune Cascade Response and Gene Ontology Terms Related to Cell Death and Fibrosis in the Progression of Liver Failure

Background The key gene sets involved in the progression of acute liver failure (ALF), which has a high mortality rate, remain unclear. This study aims to gain a deeper understanding of the transcriptional response of peripheral blood mononuclear cells (PBMCs) following ALF. Methods ALF was induced by D-galactosamine (D-gal) in a porcine model. PBMCs were separated at time zero (baseline group), 36 h (failure group), and 60 h (dying group) after D-gal injection. Transcriptional profiling was performed using RNA sequencing and analysed using DAVID bioinformatics resources. Results Compared with the baseline group, 816 and 1,845 differentially expressed genes (DEGs) were identified in the failure and dying groups, respectively. A total of five and two gene ontology (GO) term clusters were enriched in 107 GO terms in the failure group and 154 GO terms in the dying group. These GO clusters were primarily immune-related, including genes regulating the inflammasome complex and toll-like receptor signalling pathways. Specifically, GO terms related to cell death, including apoptosis, pyroptosis, and autophagy, and those related to fibrosis, coagulation dysfunction, and hepatic encephalopathy were enriched. Seven Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, cytokine-cytokine receptor interaction, hematopoietic cell lineage, lysosome, rheumatoid arthritis, malaria, and phagosome and pertussis pathways were mapped for DEGs in the failure group. All of these seven KEGG pathways were involved in the 19 KEGG pathways mapped in the dying group. Conclusion We found that the dramatic PBMC transcriptome changes triggered by ALF progression was predominantly related to immune responses. The enriched GO terms related to cell death, fibrosis, and so on, as indicated by PBMC transcriptome analysis, seem to be useful in elucidating potential key gene sets in the progression of ALF. A better understanding of these gene sets might be of preventive or therapeutic interest.