PPIH acts as a potential predictive biomarker for patients with common solid tumors.

BACKGROUND: Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker. METHODS: We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers. RESULTS: Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis. CONCLUSION: Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

Prediction of transport proteins from sequence information with the deep learning approach.

Transport proteins (TPs) are vital to the growth and life of all living things, especially in fields of microbial pathogenesis and drug resistance of tumor cells. Accurately identifying potential TPs remains an important challenge for the advancement of functional genomics. This study aimed to develop a tool for predicting TPs using the deep learning approach. Here, we proposed DeepTP, a convolutional neural network model that uses parallel subnetworks to extract features from protein sequences and uses fully connected layers for TP classification. To train and evaluate the performance of the developed model, datasets were collected from the UniProtKB/Swiss-Prot database. The test results revealed that the proposed model could successfully identify TPs with the AUCROC, accuracy, F-value, and Matthews correlation coefficient of 0.9719, 0.9513, 0.8982, and 0.8679, respectively. By further comparison, DeepTP achieved better performance than other commonly used methods. Analysis of the gradients of prediction score concerning input suggested that DeepTP makes predictions by recognizing the functional domains of TPs. We anticipate that DeepTP will serve as a useful tool for predicting TPs in large-scale genome projects, which will facilitate the discovery of novel TPs.

Prediction of prokaryotic transposases from protein features with machine learning approaches.

Identification of prokaryotic transposases (Tnps) not only gives insight into the spread of antibiotic resistance and virulence but the process of DNA movement. This study aimed to develop a classifier for predicting Tnps in bacteria and archaea using machine learning (ML) approaches. We extracted a total of 2751 protein features from the training dataset including 14852 Tnps and 14852 controls, and selected 75 features as predictive signatures using the combined mutual information and least absolute shrinkage and selection operator algorithms. By aggregating these signatures, an ensemble classifier that integrated a collection of individual ML-based classifiers, was developed to identify Tnps. Further validation revealed that this classifier achieved good performance with an average AUC of 0.955, and met or exceeded other common methods. Based on this ensemble classifier, a stand-alone command-line tool designated TnpDiscovery was established to maximize the convenience for bioinformaticians and experimental researchers toward Tnp prediction. This study demonstrates the effectiveness of ML approaches in identifying Tnps, facilitating the discovery of novel Tnps in the future.

Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis.

Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack of easy-to-use predictive tools that can accurately diagnose sepsis in children. This study aimed to develop an optimal gene model for the diagnosis of pediatric sepsis using statistics and machine learning approaches. Combining gene expression profiles from a training cohort of 364 pediatric samples with a Least Absolute Shrinkage and Selection Operator analysis produced eighteen genes as diagnostic markers. With the implementation of a Gradient Boosting algorithm, a model designated PEDSEPS-GBM, that aggregated these markers was developed with optimal performance for the diagnosis of pediatric samples in the validation and two independent cohorts. Moreover, a web calculator with a user-friendly interface was established for PEDSEPS-GBM. This study presents a diagnostic model that holds great potential for the detection of pediatric sepsis, and demonstrates the biologic and clinical relevance of this model.

Analysis of Resistance to Florfenicol and the Related Mechanism of Dissemination in Different Animal-Derived Bacteria.

Bacterial resistance to antibiotics has become an important concern for public health. This study was aimed to investigate the characteristics and the distribution of the florfenicol-related resistance genes in bacteria isolated from four farms. A total of 106 florfenicol-resistant Gram-negative bacilli were examined for florfenicol-related resistance genes, and the positive isolates were further characterized. The antimicrobial sensitivity results showed that most of them (100, 94.33%) belonged to multidrug resistance Enterobacteriaceae. About 91.51% of the strains carried floR gene, while 4.72% carried cfr gene. According to the pulsed-field gel electrophoresis results, 34 Escherichia coli were subdivided into 22 profiles, the genetic similarity coefficient of which ranged from 80.3 to 98.0%. The multilocus sequence typing (MLST) results revealed 17 sequence types (STs), with ST10 being the most prevalent. The genome sequencing result showed that the Proteus vulgaris G32 genome consists of a 4.06-Mb chromosome, a 177,911-bp plasmid (pG32-177), and a 51,686-bp plasmid (pG32-51). A floR located in a drug-resistant region on the chromosome of P. vulgaris G32 was with IS91 family transposase, and the other floR gene on the plasmid pG32-177 was with an ISCR2 insertion sequence. The cfr gene was located on the pG32-51 flanked by IS26 element and TnpA26. This study suggested that the mobile genetic elements played an important role in the replication of resistance genes and the horizontal resistance gene transfer.

Association between furosemide administration and outcomes in critically ill patients with acute kidney injury.

BACKGROUND: Although current guidelines for AKI suggested against the use of furosemide in AKI management, the effect of furosemide on outcomes in real-world clinical settings remains uncertain. The aim of the present study was to investigate the association between furosemide administration and outcomes in critically ill patients with AKI using real-world data. METHODS: Critically ill patients with AKI were identified from the Medical Information Mart for Intensive Care (MIMIC)-III database. Propensity score (PS) matched analysis was used to match patients receiving furosemide to those without diuretics treatment. Linear regression, logistic regression model, and Cox proportional hazards model were used to assess the associations between furosemide and length of stay, recovery of renal function, and in-hospital and 90-day mortality, respectively. RESULTS: A total of 14,154 AKI patients were included in the data analysis. After PS matching, 4427 pairs of patients were matched between the patients who received furosemide and those without diuretics treatment. Furosemide was associated with reduced in-hospital mortality [hazard ratio (HR) 0.67; 95% CI 0.61-0.74; P < 0.001] and 90-day mortality [HR 0.69; 95% CI 0.64-0.75; P < 0.001], and it was also associated with the recovery of renal function [HR 1.44; 95% CI 1.31-1.57; P < 0.001] in over-all AKI patients. Nevertheless, results illustrated that furosemide was not associated with reduced in-hospital mortality in patients with AKI stage 0-1 defined by UO criteria, AKI stage 2-3 according to SCr criteria, and in those with acute-on-chronic (A-on-C) renal injury. CONCLUSIONS: Furosemide administration was associated with improved short-term survival and recovery of renal function in critically ill patients with AKI. Furosemide was especially effective in patients with AKI UO stage 2-3 degree. However, it was not effective in those with AKI SCr stage 2-3 and chronic kidney disease. The results need to be verified in randomized controlled trials.

Novel miRNA markers for the diagnosis and prognosis of endometrial cancer.

As endometrial cancer (EC) is a major threat to female health worldwide, the ability to provide an accurate diagnosis and prognosis of EC is promising to improve its treatment guidance. Since the discovery of miRNAs, it has been realized that miRNAs are associated with every cell function, including malignant transformation and metastasis. This study aimed to explore diagnostic and prognostic miRNA markers of EC. In this study, differential analysis and machine learning were performed, followed by correlation analysis of miRNA-mRNA based on the miRNA and mRNA expression data. Nine miRNAs were identified as diagnostic markers, and a diagnostic classifier was established to distinguish between EC and normal endometrium tissue with overall correct rates >95%. Five specific prognostic miRNA markers were selected to construct a prognostic model, which was confirmed more effective in identifying EC patients at high risk of mortality compared with the FIGO staging system. This study demonstrates that the expression patterns of miRNAs may hold promise for becoming diagnostic and prognostic biomarkers and novel therapeutic targets for EC.

Deubiquitinase inhibitor degrasyn suppresses metastasis by targeting USP5-WT1-E-cadherin signalling pathway in pancreatic ductal adenocarcinoma.

Wilm's tumour-1 (WT1) is overexpressed in pancreatic ductal adenocarcinoma (PDAC) and enhances metastasis. Deubiquitination stabilizes target proteins, and inhibiting deubiquitination facilitates the degradation of target proteins. However, whether inhibiting deubiquitination of WT1 facilitates its degradation and presents anti-cancer ability in PDAC is unknown. Here, we found that deubiquitinase inhibitor degrasyn rapidly induced the degradation of endogenous and exogenous WT1 through enhancing ubiquitination of WT1 followed by the up-regulation of E-cadherin. Knockdown of WT1 by short hairpin RNAs (shRNAs) inhibited metastasis and overexpression of WT1 partially prevented degrasyn-induced anti-metastasis activity, suggesting that degrasyn presents anti-metastasis activity partially through degrading WT1 protein. We further identified that USP5 deubiquitinated WT1 and stabilized its expression. The higher expressions of USP5 and WT1 are associated with tumour metastasis. More importantly, degrasyn inhibited the activity of USP5 and overexpression of USP5 partially prevented degrasyn-induced degradation of WT1 protein, suggesting that degrasyn degraded WT1 protein through inhibiting the activity of USP5. Finally, degrasyn reduced the tumorigenicity in a xenograft mouse model and reduced the metastasis in vivo. Our results indicate that degrasyn presents strong anti-cancer activity through USP5-WT1-E-cadherin signalling in PDAC. Therefore, degrasyn holds promise as cancer therapeutic agent in PDAC with high expressions of USP5 and WT1.

Prognostic Potential of Alternative Splicing Markers in Endometrial Cancer.

Alternative splicing (AS), an important post-transcriptional regulatory mechanism that regulates the translation of mRNA isoforms and generates protein diversity, has been widely demonstrated to be associated with oncogenic processes. In this study, we systematically analyzed genome-wide AS patterns to explore the prognostic implications of AS in endometrial cancer (EC). A total of 2,324 AS events were identified as being associated with the overall survival of EC patients, and eleven of these events were further selected using a random forest algorithm. With the implementation of a generalized, boosted regression model, a prognostic AS model that aggregated these eleven markers was ultimately established with high performance for risk stratification in EC patients. Functional analysis of these eleven AS markers revealed various potential signaling pathways implicated in the progression of EC. Splicing network analysis demonstrated the notable correlation between the expression of splicing factors and AS markers in EC and further determined eight candidate splicing factors that could be therapeutic targets for EC. Taken together, the results of this study present the utility of AS profiling in identifying biomarkers for the prognosis of EC and provide comprehensive insight into the molecular mechanisms involved in EC processes.

Comparative Genomic Analysis of Rhodococcus equi: An Insight into Genomic Diversity and Genome Evolution.

Rhodococcus equi, a member of the Rhodococcus genus, is a gram-positive pathogenic bacterium. Rhodococcus possesses an open pan-genome that constitutes the basis of its high genomic diversity and allows for adaptation to specific niche conditions and the changing host environments. Our analysis further showed that the core genome of R. equi contributes to the pathogenicity and niche adaptation of R. equi. Comparative genomic analysis revealed that the genomes of R. equi shared identical collinearity relationship, and heterogeneity was mainly acquired by means of genomic islands and prophages. Moreover, genomic islands in R. equi were always involved in virulence, resistance, or niche adaptation and possibly working with prophages to cause the majority of genome expansion. These findings provide an insight into the genomic diversity, evolution, and structural variation of R. equi and a valuable resource for functional genomic studies.

Characterization of a Novel blaKLUC Variant With Reduced ß-Lactam Resistance From an IncA/C Group Plasmid in a Clinical Klebsiella pneumoniae Isolate.

Similar to other CTX-M family enzymes, KLUC is a recently identified and emerging determinant of cefotaxime resistance that has been recovered from at least three Enterobacteriaceae species, including Kluyvera cryocrescens, Escherichia coli, and Enterobacter cloacae. Whether this extended-spectrum ß-lactamase (ESBL) has been disseminated among commonly isolated Enterobacteriaceae is worthy of further investigation. In this study, we screened 739 nosocomial Enterobacteriaceae isolates (240 Klebsiella pneumoniae and 499 E. coli strains) and found that one K. pneumoniae and four E. coli isolates harbored the blaKLUC gene. Three blaKLUC determinants isolated from E. coli were entirely identical to a blaKLUC-3 gene previously recovered in the same hospital. PFGE of four blaKLUC-harboring E. coli strains showed that prevalence of these determinants was most likely mediated by horizontal gene transfer but not clonal dissemination. However, the variant isolated from K. pneumoniae belonged to a novel member of the KLUC enzyme group. This newly identified enzyme (KLUC-5) has an amino acid substitution compared with previously identified KLUC-1 (G18S) and KLUC-3 (G240D). Antimicrobial susceptibility tests showed that KLUC-5 significantly reduced resistance activity to almost all the selected antimicrobials compared to previously identified KLUC-3. Site-directed mutagenesis showed that blaKLUC-5-D240G and blaKLUC-5-S18G significantly enhanced the MIC against its best substrate. Conjugation and S1-PFGE indicated that blaKLUC-5 was located on a transferable plasmid, which was further decoded by single-molecule, real-time sequencing. Comparative genome analysis showed that its backbone exhibited genetic homology to the IncA/C incompatibility group plasmids. A transposable element, ISEcp1, was detected 256-bp upstream of the blaKLUC-5 gene; this location was inconsistent with the previously identified blaKLUC-1 but congruent with the variants recovered from E. coli in the same hospital. These data provide evidence of the increasingly emerging KLUC group of ESBLs in China.

Characterisation of a class 1 integron associated with the formation of quadruple blaGES-5 cassettes from an IncP-1ß group plasmid in Pseudomonas aeruginosa.

Integrons are genetic platforms responsible for the dissemination of antimicrobial resistance genes among Gram-negative bacteria, primarily due to their association with transposable elements and conjugative plasmids. In this study, a cassette array containing four identical blaGES-5 genes embedded in a class 1 integron located on an IncP-1ß group plasmid from a clinical Pseudomonas aeruginosa strain was identified. Comparative genome analysis and conjugation assay showed that the plasmid pICP-4GES lacked the trbN, trbO and trbP genes but was conjugable. Antimicrobial susceptibility testing revealed that compared with single-copy blaGES-5 complementary strains, both the cloned and chromosome-targeted expression of four copies of blaGES-5 increased the minimum inhibitory concentration (MIC) by one to two dilutions for most of the selected antimicrobials. Quantitative real-time reverse transcription PCR (RT-qPCR) showed that the four consecutive cassettes increased blaGES-5 expression by approximately two-fold compared with the single-copy blaGES-5 strain, suggesting that the level of gene expression was not directly proportional to copy number. In addition, the gene cassette capture assay showed that the global blaGES-5 transfer frequency reached 5.38 × 10-4.

Exploration of DNA methylation markers for diagnosis and prognosis of patients with endometrial cancer.

The accurate diagnosis of endometrial cancer (EC) holds great promise for improving its treatment choice and prognosis prediction. This work aimed to identify diagnostic biomarkers for differentiating EC tumors from tumors in other tissues, as well as prognostic signatures for predicting survival in EC patients. We identified 48 tissue-specific markers using a cohort of genome-wide methylation data from three common gynecological tumors and their corresponding normal tissues. A diagnostic classifier was constructed based on these 48 CpG markers that could predict cancerous versus normal tissue with an overall correct rate of 98.3% in the entire repository. Fifteen CpG markers associated with the overall survival (OS) and development of EC were also identified based on the methylation patterns of the EC samples. A prognostic model that aggregated these prognostic CpG markers was established and shown to have a higher discriminative ability to distinguish EC patients with an elevated risk of mortality than the FIGO staging system and several other clinical prognostic variables. This study presents the utility of DNA methylation in identifying biomarkers for the diagnosis and prognosis of EC and will help improve our understanding of the underlying mechanisms involved in the development of EC.

Comparative Genomics Analysis of Plasmid pPV989-94 from a Clinical Isolate of Pantoea vagans PV989.

Pantoea vagans, a gram-negative bacterium from the genus Pantoea and family Enterobacteriaceae, is present in various natural environments and considered to be plant endophytes. We isolated the Pantoea vagans PV989 strain from the clinic and sequenced its whole genome. Besides a chromosome DNA molecule, it also harboured three large plasmids. A comparative genomics analysis was performed for the smallest plasmid, pPV989-94. It can be divided into four regions, including three conservative regions related to replication (R1), transfer conjugation (R2), and transfer leading (R3), and one variable region (R4). Further analysis showed that pPV989-94 is most similar to plasmids LA637P2 and pEA68 of Erwinia amylovora strains isolated from fruit trees. These three plasmids share three conservative regions (R1, R2, and R3). Interestingly, a fragment (R4') in R4, mediated by phage integrase and phage integrase family site-specific recombinase and encoding 9 genes related to glycometabolism, resistance, and DNA repair, was unique in pPV989-94. Homologues of R4' were found in other plasmids or chromosomes, suggesting that horizontal gene transfer (HGT) occurred among different bacteria of various species or genera. The acquired functional genes may play important roles in the adaptation of bacteria to different hosts or environmental conditions.

Establishment of a nine-gene prognostic model for predicting overall survival of patients with endometrial carcinoma.

Endometrial carcinoma (EC) is the most common malignant tumor of the female genital tract in developed countries. The prognosis of early stage EC is favorable, but a subset faces high risk of cancer progression or recurrence. EC has a poor prognosis upon progression to advanced or metastatic stages. Therefore, our goal is to build a robust prognostic model for predicting overall survival (OS) in EC patients. In this study, 1571 genes were identified as being associated with OS based on genomewide expression profiles using a training dataset. Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that these genes were involved in various cancer-related signaling pathways. Nine signature genes were further selected using stepwise selection, and their potential role in the development of EC was demonstrated by performing differential expression analysis between EC and normal uterine tissues. A prognostic model that aggregated these nine signature genes was ultimately established and effectively divided EC patients into two risk groups. OS for patients in the high-risk group was significantly poorer compared with that of the low-risk group. This nine-gene model was subsequently validated and evaluated using the TCGA dataset and shown to have a high discriminating power to distinguish EC patients with an elevated risk of mortality based on the FIGO staging system and other prognostic factors. This study provides a novel prognostic model for the identification of EC patients with elevated risk of mortality and will help to improve our understanding of the underlying mechanisms involved in prognostic EC factors.

Identification and molecular characterization of Escherichia coli blaSHV genes in a Chinese teaching hospital.

Escherichia coli (E. coli) commonly reside in human intestine and most E. coli strains are harmless, but some serotypes cause serious food poisoning. This study identified and molecularly characterized blaSHV genes from 490 E. coli strains with multi-drug resistance in a hospital population. PCR and molecular cloning and southern blot were performed to assess functions and localizations of this resistant E. coli gene and the pulsed-field gel electrophoresis (PFGE) was utilized to demonstrate the clonal relatedness of the positive E. coli strains. The data showed that 4 of these 490 E. coli strains (4/499, 0.8%) carried blaSHV genes that included EC D2485 (blaSHV-5), EC D2487 (blaSHV-5), EC D2684 (blaSHV-11) and EC D2616 (blaSHV-195, a novel blaSHV). Analysis of blaSHV open-reading frame showed that blaSHV-5 had a high hydrolysis activity to the broad-spectrum penicillin (ampicillin or piperacillin), ceftazidime, ceftriaxone, cefotaxime and aztreonam. blaSHV-195 and blaSHV-11 had similar resistant characteristics with high hydrolysis activities to ampicillin and piperacillin, but low activities to cephalosporins. Moreover, the two blaSHV-5 genes were located on a transferable plasmid (23kb), whereas the other two blaSHV variants (blaSHV-11 and blaSHV-195) seemed to be located in the chromosomal material. Both EC D2485 and EC D2487 clones isolated in 2010 had the same DNA finger printing profile and they might be the siblings of clonal dissemination. The data from the current study suggest that the novel blaSHV and clonal dissemination may be developed, although blaSHV genes were infrequently identified in this hospital population. The results of the work demonstrate the necessity for molecular surveillance in tracking blaSHV-producing strains in large teaching hospital settings and emphasize the need for epidemiological monitoring.

Whole genomic DNA sequencing and comparative genomic analysis of Arthrospira platensis: high genome plasticity and genetic diversity.

Arthrospira platensis is a multi-cellular and filamentous non-N2-fixing cyanobacterium that is capable of performing oxygenic photosynthesis. In this study, we determined the nearly complete genome sequence of A. platensis YZ. A. platensis YZ genome is a single, circular chromosome of 6.62 Mb in size. Phylogenetic and comparative genomic analyses revealed that A. platensis YZ was more closely related to A. platensis NIES-39 than Arthrospira sp. PCC 8005 and A. platensis C1. Broad gene gains were identified between A. platensis YZ and three other Arthrospira speices, some of which have been previously demonstrated that can be laterally transferred among different species, such as restriction-modification systems-coding genes. Moreover, unprecedented extensive chromosomal rearrangements among different strains were observed. The chromosomal rearrangements, particularly the chromosomal inversions, were analysed and estimated to be closely related to palindromes that involved long inverted repeat sequences and the extensively distributed type IIR restriction enzyme in the Arthrospira genome. In addition, species from genus Arthrospira unanimously contained the highest rate of repetitive sequence compared with the other species of order Oscillatoriales, suggested that sequence duplication significantly contributed to Arthrospira genome phylogeny. These results provided in-depth views into the genomic phylogeny and structural variation of A. platensis, as well as provide a valuable resource for functional genomics studies.

Molecular Epidemiology and Characterization of Genotypes of Acinetobacter baumannii Isolates from Regions of South China.

The aim of this study was to analyze the molecular epidemiologic characteristics of Acinetobacter baumannii. A total of 398 isolates were collected in 7 regions of South China from January to June of 2012. Drug sensitivity was tested toward 15 commonly used antibiotics; thus, 146 multi-drug-resistant strains (resistant to more than 7 drugs) were identified, representing 36.7% of all isolates. Pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) were used for molecular subtyping. According to the PFGE results (with a cutoff of 70% similarity for the DNA electrophoretic bands), 146 strains were subdivided into 15 clusters, with cluster A being the largest (33.6%, distributed in all districts except Jiaxing). Cluster B was also widespread and included 14.4% of all strains. In addition, MLST results revealed 11 sequence types (ST), with ST208 being the most prevalent, followed by ST191 and ST729. Furthermore, 4 novel alleles and 6 novel STs were identified. Our results showed that multi-drug-resistant A. baumannii in South China shares the origin with other widespread strains in other countries. The nosocomial infections caused by A. baumannii have been severe in South China. Continuous monitoring and judicious antibiotic use are required.

Comparative genomics analysis of pKF3-94 in Klebsiella pneumoniae reveals plasmid compatibility and horizontal gene transfer.

In order to get insights into plasmid evolution and the dissemination of multidrug resistance, we performed extensive comparative genomics analyses of the Klebsiella pneumoniae plasmid pKF3-94 and some of its related plasmids. pKF3-94 is one of three plasmids isolated from the K. pneumoniae strain KF3. Of the 144 putative genes it harbors, 69 can be functionally assigned to be involved in transfer conjugation, transfer leading, antimicrobial resistance, transposon function, and plasmid replication. Comparison of plasmid replicon sequence types revealed that pKF3-94 carries two replicons that are distinct from those carried on the two sibling K. pneumonia plasmids pKF3-70 and pKF3-140, thereby allowing pKF3-94 to coexist with these latter plasmids in the same host cell. Comparative genomics analyses further showed that pKF3-94 is more similar to plasmids pK1HV and pC15-k, which were isolated from different K. pneumonia strains, than to pKF3-70 and pKF3-140. Interestingly, pK1HV contains a unique 49 kb region rich in mobile genetic elements and drug resistance genes, while pKF3-94 and pC15-k share a 15 kb homology region partitioned into a region rich in drug resistance genes and one containing a replicon. It is conceivable, therefore, that pK1HV and pC15-k have both arisen from a common pKF3-94-like plasmid. The comparisons lend further support for the role horizontal gene transfer plays in genome evolution and in the dissemination of genetic elements including drug resistance genes.

Molecular variation and horizontal gene transfer of the homocysteine methyltransferase gene mmuM and its distribution in clinical pathogens.

The homocysteine methyltransferase encoded by mmuM is widely distributed among microbial organisms. It is the key enzyme that catalyzes the last step in methionine biosynthesis and plays an important role in the metabolism process. It also enables the microbial organisms to tolerate high concentrations of selenium in the environment. In this research, 533 mmuM gene sequences covering 70 genera of the bacteria were selected from GenBank database. The distribution frequency of mmuM is different in the investigated genera of bacteria. The mapping results of 160 mmuM reference sequences showed that the mmuM genes were found in 7 species of pathogen genomes sequenced in this work. The polymerase chain reaction products of one mmuM genotype (NC_013951 as the reference) were sequenced and the sequencing results confirmed the mapping results. Furthermore, 144 representative sequences were chosen for phylogenetic analysis and some mmuM genes from totally different genera (such as the genes between Escherichia and Klebsiella and between Enterobacter and Kosakonia) shared closer phylogenetic relationship than those from the same genus. Comparative genomic analysis of the mmuM encoding regions on plasmids and bacterial chromosomes showed that pKF3-140 and pIP1206 plasmids shared a 21 kb homology region and a 4.9 kb fragment in this region was in fact originated from the Escherichia coli chromosome. These results further suggested that mmuM gene did go through the gene horizontal transfer among different species or genera of bacteria. High-throughput sequencing combined with comparative genomics analysis would explore distribution and dissemination of the mmuM gene among bacteria and its evolution at a molecular level.