酒酒球菌的快速特异性PCR鉴定

以Oenococcus oeni苹果酸-乳酸酶基因(mleA)为目标基因,设计了1对特异性引物PmleaL/PmleaR进行酒酒球菌的快速鉴定研究。结果表明,直接以O.oeni的菌落为模板,通过引物对PmleaL/PmleaR的PCR扩增,可得到mleA基因的特异性条带;用此特异性引物进行供试乳酸菌的PCR鉴定,所有O.oeni菌系均得到特异性条带,而供试的其它种类乳酸菌未扩增出目标带。PmleaL/PmleaR可用于O.oeni的快速PCR鉴定。     

细菌鉴定方法

细菌的分类鉴定与细菌的研究和应用有着同等重要的地位。准确地鉴定细菌类别,根据其菌种种类不同,分别针对肠杆菌、阳性球菌、非发酵菌等菌种设计不同药敏板条的抗生素组合,可以指导临床应用用药。目前,细菌分类鉴定方法主要包括表型鉴定法和分子遗传学鉴定法两大类,针对这两大类鉴定方法,汇总其生理生化分类特征,简述各方法采用的关键技术,针对各技术讨论其优缺点。同时详细研究了表型鉴定法下数值分类法中自动化鉴定涉及的算法,结合目前细菌鉴定方法,对细菌分类鉴定的发展趋势进行了总结和展望。     

GOToolBox: functional analysis of gene datasets based on Gene Ontology

We have developed methods and tools based on the Gene Ontology (GO) resource allowing the identification of statistically over- or under-represented terms in a gene dataset; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology. The source codes are available upon request, and distributed under the GPL license.     

Molecular tools in marine ecology

Molecular tools have diverse applications in marine ecology. In microbial systems, DNA sequences of rRNA and other genes have identified a variety of novel lineages of bacteria inhabiting marine environments that have resisted traditional culture methods. However, relatively few natural populations have been characterized due to the rather labor-intensive methodologies employed. Recent technological developments such as in situ PCR and flow cytometry promise to greatly enhance the speed at which microbial taxa can be identified and enumerated in field collected water and substrate samples; such advances will allow future work to employ the spatial and temporal field sampling required to monitor the impact of natural and anthropogenic changes in the environment. This approach also holds promise for examining physiological status of field collected cells, garnering information on such elusive parameters as growth rates and the extent of nutrient limitation under natural conditions. Studies of macrobiota have similarly benefited from the use of molecular approaches to species identification. This has been particularly true with regard to distinguishing among larval forms of closely related taxa which are nearly identical morphologically. Genetic variation within species assayed by molecular tools has been useful in examining the stability of populations through time and in assessing patterns of recruitment to geographically separated populations. Enhanced understanding of these ecological problems will also require intensive spatial and temporal monitoring of both larval and adult populations. Often, the newer techniques based on DNA sequence variation have practical advantages over allozyme techniques: e.g., PCR allows assay of minute quantities of DNA that may come from ethanol preserved samples. However, when ample allozyme variation exists to address a given issue, these older techniques may be favored on a variety of criteria, including speed and cost. Hence, choice of methodology should be based on the expected efficiency of a given approach to a specific problem rather than the apparent sophistication of the method itself.     

Approaches to prokaryotic biodiversity: a population genetics perspective

The study of prokaryotic diversity has blossomed during the last 10-15 years as a result of the introduction of molecular identification, mostly based on direct 16S rRNA gene polymerase chain reaction (PCR) amplification and sequencing from natural samples. A large amount of information exists about the diversity of this specific gene. However, data from the field of bacterial population genetics and genomics make questionable the value of information regarding just one gene. Even if we accept 16S rRNA genes as useful for species identification, intraspecific variation in bacteria is so high that species catalogues are often of little value. The gene pools represented by an operational species are yet impossible to predict. On the other hand, adaptive features in prokaryotes are often coded in gene clusters (genomic islands) that can be cloned directly from the environment, sequenced and even expressed in a surrogate host. Thus, the study of the environmental genome or metagenome appears as an alternative that could eventually lead to a more realistic understanding of prokaryotic biodiversity, provide biotechnology with new tools and maybe even contribute to develop a model of prokaryotic evolution.     

Identification and characterization of bacterial isolates from the Mir space station

Twenty bacterial isolates (supplied by NASA) from the Mir space station water system were identified using Vitek GNI+ test card, API 20NE, and 16S rRNA gene sequencing. The identification of only one isolate agreed among the three techniques. The utility of the API 20NE and Vitek GNI+ test card approaches for identifying these isolates was Limited. Although 16S rRNA gene sequencing effectively identified many of the bacteria to the genus level, 74% of the isolates could not be identified to the species level. Isolates were also characterized based on motility and hydrophobicity. About 40% of the isolates were motile and four isolates were hydrophobic, suggesting that many of the bacteria have the potential to colonize surfaces and form biofilms. These findings demonstrate the difficulties in identifying bacteria from some environments to the species level and have implications for determining the risks of contamination in water systems of space shuttles and stations.     

GPA: A Microbial Genetic Polymorphisms Assignments Tool in Metagenomic Analysis by Bayesian Estimation

Identifying antimicrobial resistant(AMR) bacteria in metagenomics samples is essential for public health and food safety. Next-generation sequencing(NGS) technology has provided a powerful tool in identifying the genetic variation and constructing the correlations between genotype and phenotype in humans and other species. However, for complex bacterial samples, there lacks a powerful bioinformatic tool to identify genetic polymorphisms or copy number variations(CNVs) for given genes. Here we provide a Bayesian framework for genotype estimation for mixtures of multiple bacteria, named as Genetic Polymorphisms Assignments(GPA). Simulation results showed that GPA has reduced the false discovery rate(FDR) and mean absolute error(MAE) in CNV and single nucleotide variant(SNV) identification. This framework was validated by whole-genome sequencing and Pool-seq data from Klebsiella pneumoniae with multiple bacteria mixture models, and showed the high accuracy in the allele fraction detections of CNVs and SNVs in AMR genes between two populations. The quantitative study on the changes of AMR genes fraction between two samples showed a good consistency with the AMR pattern observed in the individual strains. Also, the framework together with the genome annotation and population comparison tools has been integrated into an application, which could provide a complete solution for AMR gene identification and quantification in unculturable clinical samples. The GPA package is available at https://github.com/IID-DTH/GPA-package.     

Fast identification of ten clinically important micro-organisms using an electronic nose

AIMS: To evaluate the electronic nose (EN) as method for the identification of ten clinically important micro-organisms. METHODS AND RESULTS: A commercial EN system with a series of ten metal oxide sensors was used to characterize the headspace of the cultured organisms. The measurement procedure was optimized to obtain reproducible results. Artificial neural networks (ANNs) and a k-nearest neighbour (k-NN) algorithm in combination with a feature selection technique were used as pattern recognition tools. Hundred percent correct identification can be achieved by EN technology, provided that sufficient attention is paid to data handling. CONCLUSIONS: Even for a set containing a number of closely related species in addition to four unrelated organisms, an EN is capable of 100% correct identification. SIGNIFICANCE AND IMPACT OF THE STUDY: The time between isolation and identification of the sample can be dramatically reduced to 17 h.     

Rapid identification of acetic acid bacteria using MALDI-TOF mass spectrometry fingerprinting

Acetic acid bacteria (AAB) are widespread microorganisms characterized by their ability to transform alcohols and sugar-alcohols into their corresponding organic acids. The suitability of matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS) for the identification of cultured AAB involved in the industrial production of vinegar was evaluated on 64 reference strains from the genera Acetobacter, Gluconacetobacter and Gluconobacter. Analysis of MS spectra obtained from single colonies of these strains confirmed their basic classification based on comparative 16S rRNA gene sequence analysis. MALDI-TOF analyses of isolates from vinegar cross-checked by comparative sequence analysis of 16S rRNA gene fragments allowed AAB to be identified, and it was possible to differentiate them from mixed cultures and non-AAB. The results showed that MALDI-TOF MS analysis was a rapid and reliable method for the clustering and identification of AAB species.     

细菌脂多糖及其寡糖链结构分析技术研究进展

脂多糖是大多数革兰氏阴性细菌细胞壁的主要成分,能诱发宿主细胞固有免疫反应,在细菌的识别、黏附、转移、致病等过程中发挥非常重要的作用.其结构组成与细菌的血清型和致病能力息息相关,因而对其结构进行精准分析,有助于研究其结构与生物效应间的关系,便于鉴别菌种和研发相关的抗生素及疫苗.由于脂多糖具有两亲性、多电荷且结构复杂等特点,为研究分析带来很多难题.本文全面归纳了细菌脂多糖分析技术的相关研究成果,阐述脂多糖及其寡糖链的提取、分离纯化及鉴定方法.     

Whole-cell matrix-assisted laser desorption/ionization time-of-flight mass spectrometry for rapid identification of bacteria cultured in liquid media

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been used for many years to rapidly identify whole bacteria. However, no consistent methodology exists for the rapid identification of bacteria cultured in liquid media. Thus, in this study we explored the use of MALDI-TOF MS analysis for rapid identification of cells cultured in liquid media. We determined that 2,5-dihydroxybenzoic acid (50 mg mL^?1, 50% acetonitrile, 0.1% trifluoroacetic acid) was the best matrix solution for MALDI-TOF MS for this type of study. Moreover, the tested strains were successfully differentiated by principal component analysis, and the main characteristics of the mass peaks for each species were found in mixed culture samples. In addition, we found that the minimum number of cells for detection was 1.8×10³. In conclusion, our findings suggest that MS-based techniques can be developed as an auxiliary method for rapidly and accurately identifying bacteria cultured in liquid media.     

Insights into the taxonomy, genetics and physiology of bifidobacteria

Despite the generally accepted importance of bifidobacteria as probiotic components of the human intestinal microflora and their use in health promoting foods, there is only limited information about their phylogenetic position, physiology and underlying genetics. In the last few years numerous molecular approaches have emerged for the identification and characterization of bifidobacterial strains. Their use, in conjunction with traditional culturing methods, has led to a polyphasic taxonomy which has significantly enhanced our knowledge of the role played by these bacteria in the human intestinal ecosystem. The recent adaptation of culture-independent molecular tools to the fingerprinting of intestinal and food communities offers an exciting opportunity for revealing a more detailed picture of the true complexity of these environments. Furthermore, the availability of bifidobacterial genome sequences has advanced knowledge on the genetics of bifidobacteria and the effects of their metabolic activities on the intestinal ecosystem. The release of a complete Bifidobacterium longum genome sequence and the recent initiative to sequence additional strains are expected to open up a new era of comparative genomics in bifidobacterial biology. Moreover, the use of genomotyping allows a global comparative analysis of gene content between different bifidobacterial isolates of a given species without the necessity of sequencing many strains. Genomotyping provides useful information about the degree of relatedness among various strains of Bifidobacterium species and consequently can be used in a polyphasic identification approach. This review will deal mainly with the molecular tools described for bifidobacterial identification and the first insights into the underlying genetics involved in bifidobacterial physiology as well as genome variability.     

A Universal Method for the Identification of Bacteria Based on General PCR Primers

The Universal Method (UM) described here will allow the detection of any bacterial rDNA leading to the identification of that bacterium. The method should allow prompt and accurate identification of bacteria. The principle of the method is simple; when a pure PCR product of the 16S gene is obtained, sequenced, and aligned against bacterial DNA data base, then the bacterium can be identified. Confirmation of identity may follow. In this work, several general 16S primers were designed, mixed and applied successfully against 101 different bacterial isolates. One mixture, the Golden mixture7 (G7) detected all tested isolates (67/67). Other golden mixtures; G11, G10, G12, and G5 were useful as well. The overall sensitivity of the UM was 100% since all 101 isolates were detected yielding intended PCR amplicons. A selected PCR band from each of 40 isolates was sequenced and the bacterium identified to species or genus level using BLAST. The results of the UM were consistent with bacterial identities as validated with other identification methods; cultural, API 20E, API 20NE, or genera and species specific PCR primers. Bacteria identified in the study, covered 34 species distributed among 24 genera. The UM should allow the identification of species, genus, novel species or genera, variations within species, and detection of bacterial DNA in otherwise sterile samples such as blood, cerebrospinal fluid, manufactured products, medical supplies, cosmetics, and other samples. Applicability of the method to identifying members of bacterial communities is discussed. The approach itself can be applied to other taxa such as protists and nematodes.     

Automatic identification of large collections of protein-coding or rRNA sequences

The number of available genomic sequences is growing very fast, due to the development of massive sequencing techniques. Sequence identification is needed and contributes to the assessment of gene and species evolutionary relationships. Automated bioinformatics tools are thus necessary to carry out these identification operations in an accurate and fast way. We developed HoSeqI (Homologous Sequence Identification), a software environment allowing this kind of automated sequence identification using homologous gene family databases. HoSeqI is accessible through a Web interface (http://pbil.univ-lyon1.fr/software/HoSeqI/) allowing to identify one or several sequences and to visualize resulting alignments and phylogenetic trees. We also implemented another application, MultiHoSeqI, to quickly add a large set of sequences to a family database in order to identify them, to update the database, or to help automatic genome annotation. Lately, we developed an application, ChiSeqI (Chimeric Sequence Identification), to automate the processes of identification of bacterial 16S ribosomal RNA sequences and of detection of chimeric sequences.     

Candidate gene prioritization

Candidate gene identification is typically labour intensive, involving laboratory experiments required to corroborate or disprove any hypothesis for a nominated candidate gene being considered the causative gene. The traditional approach to reduce the number of candidate genes entails fine-mapping studies using markers and pedigrees. Gene prioritization establishes the ranking of candidate genes based on their relevance to the biological process of interest, from which the most promising genes can be selected for further analysis. To date, many computational methods have focused on the prediction of candidate genes by analysis of their inherent sequence characteristics and similarity with respect to known disease genes, as well as their functional annotation. In the last decade, several computational tools for prioritizing candidate genes have been proposed. A large number of them are web-based tools, while others are standalone applications that install and run locally. This review attempts to take a close look at gene prioritization criteria, as well as candidate gene prioritization algorithms, and thus provide a comprehensive synopsis of the subject matter.     

Species identification of Tanzanian antelopes using DNA barcoding

Efficient tools for consistent species identification are important in wildlife conservation as it can provide information on the levels of species exploitation and assist in solving forensic-related problems. In this study, we evaluated the effectiveness of the mitochondrial cytochrome c oxidase subunit I (COI) barcode in species identification of Tanzanian antelope species. A 470 base-pair region of the COI gene was examined in 95 specimens representing 20 species of antelopes, buffalo and domestic Bovidae. All the Tanzanian species showed unique clades, and sequence divergence within species was <1%, whereas divergence between species ranged from 6.3% to 22%. Lowest interspecific divergence was noted within the Tragelaphus genus. Neighbour-joining phylogenetic analyses demonstrated that the examined COI region provided correct and highly supported species clustering using short fragments down to 100 base-pair lengths. This study demonstrates that even short COI fragments can efficiently identify antelope species, thus demonstrating its high potential for use in wildlife conservation activities.     

Methods for the bioinformatic identification of bacterial lipoproteins encoded in the genomes of Gram-positive bacteria

Bacterial lipoproteins are a diverse and functionally important group of proteins that are amenable to bioinformatic analyses because of their unique signal peptide features. Here we have used a dataset of sequences of experimentally verified lipoproteins of Gram-positive bacteria to refine our previously described lipoprotein recognition pattern (G+LPP). Sequenced bacterial genomes can be screened for putative lipoproteins using the G+LPP pattern. The sequences identified can then be validated using online tools for lipoprotein sequence identification. We have used our protein sequence datasets to evaluate six online tools for efficacy of lipoprotein sequence identification. Our analyses demonstrate that LipoP () performs best individually but that a consensus approach, incorporating outputs from predictors of general signal peptide properties, is most informative. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.