ABSTRACT The emerging infectious agent Elizabethkingia meningoseptica is associated with life-threatening infections in immunocompromised individuals. However, there are limited data on its geographic distribution, phylogenetic evolution, pathogenesis, and transmission. In this study, we comprehensively analyze and compare the genomic features, evolutionary history, emergence date, and transmission networks of global E. meningoseptica. Geographical distribution reveals the presence of the emerging bacteria in Asia, Europe, and North America, three continents with similar latitudes. Phylogenetic analyses show no relationship between the strain’s evolutionary history and its location, origin, or source, despite the presence of genetic diversity. Analysis of the emergence timeline suggests that America is the most likely source of E. meningoseptica with the common ancestor of this pathogen dating back 90 years. Putative transmission networks indicate that E. meningoseptica bacteria can spread within the same hospital and even across borders. Minor variations in resistance genotypes and virulence genes are observed, supporting existing evidence of inherent resistance and pathogenicity in E. meningoseptica. Additionally, minocycline and doxycycline demonstrate potent antimicrobial activity against this pathogen, making them promising candidates for treating E. meningoseptica infections. Our research highlights the potential for severe nosocomial outbreaks caused by E. meningoseptica with horizontal transmission occurring between countries worldwide. To prevent future outbreak infections, increased genomic surveillance of global E. meningoseptica populations is necessary. IMPORTANCE Elizabethkingia meningoseptica is an emerging infectious agent associated with life-threatening infections in immunocompromised individuals. However, there are limited data available on the genomic features of E. meningoseptica. This study aims to characterize the geographical distribution, phylogenetic evolution, pathogenesis, and transmission of this bacterium. A systematic analysis of the E. meningoseptica genome revealed that a common ancestor of this bacterium existed 90 years ago. The evolutionary history showed no significant relationship with the sample source, origin, or region, despite the presence of genetic diversity. Whole genome sequencing data also demonstrated that E. meningoseptica bacteria possess inherent resistance and pathogenicity, enabling them to spread within the same hospital and even across borders. This study highlights the potential for E. meningoseptica to cause severe nosocomial outbreaks and horizontal transmission between countries worldwide. The available evidence is crucial for the development of evidence-based public health policies to prevent global outbreaks caused by emerging pathogens.

Bacterial genome sequencing is a powerful technique for studying the genetic diversity and evolution of microbial populations. However, the detection of genomic variants from sequencing data is challenging due to the presence of contamination, sequencing errors and multiple strains within the same species. Several bioinformatics tools have been developed to address these issues, but their performance and accuracy have not been systematically evaluated. In this study, we compared 10 variant detection pipelines using 18 simulated and 17 real datasets of high-throughput sequences from a bundle of representative bacteria. We assessed the sensitivity of each pipeline under different conditions of coverage, simulation and strain diversity. We also demonstrated the application of these tools to identify consistent mutations in a 30-time repeated sequencing dataset of Staphylococcus hominis . We found that HaplotypeCaller, but not Mutect2, from the GATK tool set showed the best performance in terms of accuracy and robustness. CFSAN and Snippy performed not as well in several simulated and real sequencing datasets. Our results provided a comprehensive benchmark and guidance for choosing the optimal variant detection pipeline for high-throughput bacterial genome sequencing data.

Purpose: This study was designed to analyze the liver tissue changes among the CHB patients who received treatment for at least 6 months and follow-up for at least 1 year, together with the correlation between the different disease condition and serum markers. Methods: One-hundred and eighty-five CHB patients underwent antiviral therapy for at least 6 months were enrolled. In the 12-month follow-up, ultrasonography-guided biopsy was performed. The patients were grouped based on the serum markers and pathological changes in liver tissues. Then we determined the serum markers, virological tests and Tim-3 expression among these groups. Results: Antiviral therapy significantly reduced liver inflammation indicators and serum Tim-3 level. However, the fibrosis process of liver tissue was not changed, and there are still disputes on the serum marker and hepatic lesion outcomes. Under normal liver function or negative hepatitis B e antigen (HBeAg) of CHB patients, there might be consensus between Tim-3 change and liver pathological outcome. According to the liver tissue inflammation and fibrosis conditions, Tim-3 was positively correlated with liver function indices. Besides, it was also related to fibrosis stage and inflammation grade. Conclusion: There were inconsistent changes between serum markers and liver tissue conditions after anti-viral therapy. Tim-3 expression was more suitable to indicate the changes of liver inflammatory and fibrosis response to some extent than ALT and AST. It may serve as a certain indicator to predict the CHB prognosis, which could be used as one of the monitoring indicators in liver pathological changes of chronic HBV infection, especially in monitoring liver tissue inflammation.

Background Hepatocellular 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. Methods The 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. Results In 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. Conclusion These 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.

Objective To analyze the genomic characteristics of a community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) HZW450 isolated from a patient with impetigo herpetifomis.Methods The whole genome was sequenced using PacBio sequencing techniques.The assembling,annotation,gene prediction,cluster of orthologous group,virulence and antibiotic resistance genes analysis were performed with different software respectively.The relevant genes of virulence factors and antibiotic resistance were analyzed and compared among the same sequencing-type (ST) isolates in China.Results The genome of HZW450 was consisted of a single circular DNA chromosome of 2,831,958 bp with 32.9％ GC.The sequence was submitted to GenBank,and the accession number was CP020741.The HZW450 strain was found to belong to ST59 and has numerous virulence factors and antibiotic resistance genes including aph (3')-Ⅲ,ant (6) Ia,mecA,norA,erm (B) and cat (pC233).Compared to the other strains with the same sequencing type,HZW450 had different virulence factors and antibiotic resistance.Antimicrobial susceptibility test and antibiotic resistance analysis showed that there were differences between its genotypes and phenotypes.Conclusion This study reported the whole genome of CA-MRSA HZW450,which contains a large number of virulence genes including LukS-PV,lukF-PV,eta,nbA,fnbB,sspB and sspC,etc.The encoding virulence factors of these genes were related with toxin,adhesion and immune escape,inducing its higher virulence and pathogenicity.

Hepatocellular 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.The 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.In 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.These 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.

Between March and June, 2013, forty H7N9 patients were hospitalized in our hospital. Next-generation sequencing technologies have been used to sequence the fecal DNA samples of the patient, the within sample diversity analysis, enterotyping, functional gene and metagenomic species analysis have been carried on both the patients and healthy controls. The influence of associated treatment in H7N9 infected patients is dramatic and was firstly revealed in species level due to deep sequencing technology. We found that most of the MetaGenomic Species (MGS) enriched in the control samples were Roseburia inulinivorans DSM 16841, butyrate producing bacterium SS3/4 and most of MGS enriched in the H7N9 patients were Clostridium sp. 7 2 43FAA and Enterococcus faecium. It was concluded that H7N9 viral infection and antibiotic administration have a significant effect on the microbiota community with decreased diversity and overgrowth of the bacteria such as Escherichia coli and Enterococcus faecium. Enterotype analysis showed that the communities were unstable. Treatment including antivirals, probiotics and antibiotics helps to improve the microbiota diversity and the abundance of beneficial bacteria in the gut.

Liver cirrhosis occurs as a consequence of many chronic liver diseases that are prevalent worldwide. Here we characterize the gut microbiome in liver cirrhosis by comparing 98 patients and 83 healthy control individuals. We build a reference gene set for the cohort containing 2.69 million genes, 36.1% of which are novel. Quantitative metagenomics reveals 75,245 genes that differ in abundance between the patients and healthy individuals (false discovery rate < 0.0001) and can be grouped into 66 clusters representing cognate bacterial species; 28 are enriched in patients and 38 in control individuals. Most (54%) of the patient-enriched, taxonomically assigned species are of buccal origin, suggesting an invasion of the gut from the mouth in liver cirrhosis. Biomarkers specific to liver cirrhosis at gene and function levels are revealed by a comparison with those for type 2 diabetes and inflammatory bowel disease. On the basis of only 15 biomarkers, a highly accurate patient discrimination index is created and validated on an independent cohort. Thus microbiota-targeted biomarkers may be a powerful tool for diagnosis of different diseases.