Transposon-based approaches to identify essential bacterial genes

Transposons are a powerful tool for identifying genes essential for bacterial viability. The availability of many bacterial genome sequences and the large number of genes of unknown function therein have inspired the generation of a variety of different approaches. These methods are described and their advantages and disadvantages are discussed.     

基因组分析方法在微生物分类学中的应用

细菌分类学始于19世纪后半叶,当时主要是以表型标记和生理生化特性为基础的简单分类,之后DNA-DNA分子杂交、16S rRNA基因序列分析方法的出现给微生物分类带来了极大的便利。尽管如此,这些分类学方法仍然存在一些局限性,而基因组时代的到来,为微生物分类带来了新思路。本文主要介绍了5种基于全基因组数据的微生物分类方法,包括平均核苷酸同源性分析、核心基因组分析、最大唯一匹配指数分析、K串组分矢量法和基因流动性分析,并论述了这些方法在微生物分类学中的应用。     

Complementary DNA libraries

The generation of complete and full-length cDNA libraries for potential functional assays of specific gene sequences is essential for most molecules in biotechnology and biomedical research. The field of cDNA library generation has changed rapidly in the past 10 yr. This review presents an overview of the method available for the basic information of generating cDNA libraries, including the definition of the cDNA library, different kinds of cDNA libraries, difference between methods for cDNA library generation using conventional approaches and a novel strategy, and the quality of cDNA libraries. It is anticipated that the high-quality cDNA libraries so generated would facilitate studies involving genechips and the microarray, differential display, subtractive hybridization, gene cloning, and peptide library generation.     

Construction of libraries of structural genes (cDNA) and "jumping" gene libraries in lambda vectors

Main approaches and methods used for constructing "jamping" and cDNA libraries, including novel ones, that omit the employment of methylases and linkers, are presented. The advantages and drawbacks of the well-known and new lambda vectors, suitable for the purposes mentioned, are discussed. Special attention is paid to diphasmids lambda ZAP, lambda SK12, lambda SK15, that combine features of lambda and M13 phages and of plasmids. The convenience and difficulties of "jumping" libraries for physical mapping of chromosomes are briefly considered.     

Molecular epidemiology of group B streptococcal infections

Streptococcus agalactiae (GBS) is a causative agent of sepsis and meningitis in newborns and diseases in pregnant women and nonpregnant adults. Various approaches, including both nongenetic and genetic techniques, are currently used for the study of epidemiology of GBS infections. In the present paper the different methods of molecular epidemiology of GBS infections are reviewed, and several novel approaches are introduced. The advantages and disadvantages of molecular methods are discussed and compared with traditional serotyping technique. The possible use of the molecular approaches for identification of different genetic lineages in GBS as well as for identification and control of the epidemiologically actual clones is discussed.     

High-throughput methods for detection of genetic variation

Understanding human genetic variation is currently believed to reveal the cause of individual susceptibility to disease and the large variation observed in response to treatment. In this review, we will focus on different approaches to identify and visualize genetic alterations. The various approaches for allele discrimination are formally systematically divided into (i) enzymatic approaches, in which the properties of different enzymes to discriminate between nucleotides are used (restriction enzymes type II, Cleavase and Resolvase, DNA polymerase, and ligase); (ii) electrophoretic methods, in which the allele discrimination is based on the difference in mobility in polymeric gels or capillaries (single- and double-stranded conformation assays, heteroduplex analysis, and DNA sequencing); (iii) solid-phase determination of allelic variants, including high-density oligonucleotide arrays for hybridization analysis, minisequencing primer extension analysis, and fiberoptic DNA sensor array; (iv) chromatographic methods such as denaturing high-performance liquid chromatography (DHPLC); (v) other physical methods of discrimination of allelic variants such as mass spectrometry (mass and charge) or fluorescence exchange-based techniques; and (vi) in silico methods such as high-throughput analysis of expressed sequence tag data. The most frequently used techniques and instrumental settings applied in different combinations are described, and other methods that are less broadly used but have interesting potentials are discussed.     

Evaluation of methods for the extraction and purification of DNA from the human microbiome

Background

DNA extraction is an essential step in all cultivation-independent approaches to characterize microbial diversity, including that associated with the human body. A fundamental challenge in using these approaches has been to isolate DNA that is representative of the microbial community sampled.

Methodology/Principal Findings

In this study, we statistically evaluated six commonly used DNA extraction procedures using eleven human-associated bacterial species and a mock community that contained equal numbers of those eleven species. These methods were compared on the basis of DNA yield, DNA shearing, reproducibility, and most importantly representation of microbial diversity. The analysis of 16S rRNA gene sequences from a mock community showed that the observed species abundances were significantly different from the expected species abundances for all six DNA extraction methods used.

Conclusions/Significance

Protocols that included bead beating and/or mutanolysin produced significantly better bacterial community structure representation than methods without both of them. The reproducibility of all six methods was similar, and results from different experimenters and different times were in good agreement. Based on the evaluations done it appears that DNA extraction procedures for bacterial community analysis of human associated samples should include bead beating and/or mutanolysin to effectively lyse cells.     

Strategies for microarray analysis of limiting amounts of RNA.

One of the critical limitations of current microarray technologies for use in expression analyses is the relatively large amount of input RNA required to generate labelled cDNA populations for array analysis. In situations where RNA is limiting, the options for expression profiling are to increase cDNA labelling and hybridisation efficiency, or to use an amplification strategy to generate enough RNA/cDNA for use with a standard labelling method. Sample amplification approaches must preserve the representation of the relative abundances of the different RNAs within the starting population and must also be highly reproducible. This review evaluates current signal and sample amplification technologies, including those that can be used to generate labelled cDNA populations for array analysis from as little as a single cell.     

Mining the genomes of plant pathogenic bacteria: how not to drown in gigabases of sequence

Hundreds of bacterial genomes including the genomes of dozens of plant pathogenic bacteria have been sequenced. These genomes represent an invaluable resource for molecular plant pathologists. In this review, we describe different approaches that can be used for mining bacterial genome sequences and examples of how some of these approaches have been used to analyse plant pathogen genomes so far. We review how genomes can be mined one by one and how comparative genomics of closely related genomes releases the true power of genomics. Databases and tools useful for genome mining that are publicly accessible on the Internet are also described. Finally, the need for new databases and tools to efficiently mine today's plant pathogen genomes and hundreds more in the near future is discussed.     

cDNA Labeling Strategies for Microarrays Using Fluorescent Dyes

Microarray analysis has become a key experimental tool in the study of genome‐wide patterns of gene expression. The labeling step of target molecules such as cDNA or cRNA plays a key role in a microarray experiment because the amount of mRNA is measured indirectly by the labeled molecules. In this paper, the most widely used cDNA labeling strategies in microarray experiments are reviewed in detail, including direct labeling and indirect labeling methods along with a discussion of the merits and disadvantages of these methods. Furthermore, various RNA amplification approaches were surveyed to obtain a target nucleic acid sufficient for microarray experiments from minute amounts of mRNA. Finally, the labeling strategies of commonly used microarray platforms (e.g., Affymetrix GeneChip®, CodeLink? Bioarray, Agilent and spotted microarrays) were compared.     

Irrigation scheduling: advantages and pitfalls of plant-based methods

This paper reviews the various methods available for irrigation scheduling, contrasting traditional water-balance and soil moisture-based approaches with those based on sensing of the plant response to water deficits. The main plant-based methods for irrigation scheduling, including those based on direct or indirect measurement of plant water status and those based on plant physiological responses to drought, are outlined and evaluated. Specific plant-based methods include the use of dendrometry, fruit gauges, and other tissue water content sensors, while measurements of growth, sap flow, and stomatal conductance are also outlined. Recent advances, especially in the use of infrared thermometry and thermography for the study of stomatal conductance changes, are highlighted. The relative suitabilities of different approaches for specific crop and climatic situations are discussed, with the aim of indicating the strengths and weaknesses of different approaches, and highlighting their suitability over different spatial and temporal scales. The potential of soil- and plant-based systems for automated irrigation control using various scheduling techniques is also discussed.     

Measurement of bacterial gene expression in vivo

The complexities of bacterial gene expression during mammalian infection cannot be addressed by in vitro experiments. We know that the infected host represents a complex and dynamic environment, which is modified during the infection process, presenting a variety of stimuli to which the pathogen must respond if it is to be successful. This response involves hundreds of ivi (in vivo-induced) genes which have recently been identified in animal and cell culture models using a variety of technologies including in vivo expression technology, differential fluorescence induction, subtractive hybridization and differential display. Proteomic analysis is beginning to be used to identify IVI proteins, and has benefited from the availability of genome sequences for increasing numbers of bacterial pathogens. The patterns of bacterial gene expression during infection remain to be investigated. Are ivi genes expressed in an organ-specific or cell-type-specific fashion? New approaches are required to answer these questions. The uses of the immunologically based in vivo antigen technology system, in situ PCR and DNA microarray analysis are considered. This review considers existing methods for examining bacterial gene expression in vivo, and describes emerging approaches that should further our understanding in the future.     

Bacterial genomics

Abstract: During the last decade, great advances have been made in the study of bacterial genomes which is perhaps better described by the term bacterial genomics. The application of powerful techniques, such as pulsed-field gel electrophoresis of macro-restriction fragments of genomic DNA, has freed the characterisation of the chromosomes of many bacteria from the constraints imposed by classical genetic analysis. It is now possible to analyse the genome of virtually every microorganism by direct molecular methods and to construct detailed physical and gene maps. In this review, the various practical approaches are compared and contrasted, and some of the emerging themes of bacterial genomics, such as the size, shape, number and organisation of chromosomes are discussed.     

Culture-dependent and culture-independent diversity surveys target different bacteria: a case study in a freshwater sample

Compared with culture-independent approaches, traditionally used culture-dependent methods have a limited capacity to characterize water microbiota. Nevertheless, for almost a century the latter have been optimized to detect and quantify relevant bacteria. A pertinent question is if culture-independent diversity surveys give merely an extended perspective of the bacterial diversity or if, even with a higher coverage, focus on a different set of organisms. We compared the diversity and phylogeny of bacteria in a freshwater sample recovered by currently used culture-dependent and culture-independent methods (DGGE and 454 pyrosequencing). The culture-dependent diversity survey presented lower coverage than the other methods. However, it allowed bacterial identifications to the species level, in contrast with the other procedures that rarely produced identifications below the order. Although the predominant bacterial phyla detected by both approaches were the same (Proteobacteria, Actinobacteria, Bacteroidetes), sequence similarity analysis showed that, in general, different operational taxonomical units were targeted by each method. The observation that culture-dependent and independent approaches target different organisms has implications for the use of the latter for studies in which taxonomic identification has a predictive value. In comparison to DGGE, 454 pyrosequencing method had a higher capacity to explore the bacterial richness and to detect cultured organisms, being also less laborious.     

Feature selection for the prediction of translation initiation sites

Translation initiation sites （TISs） are important signals in cDNA sequences. In many previous attempts to predict TISs in cDNA sequences, three major factors affect the prediction performance： the nature of the cDNA sequence sets, the relevant features selected. and the classification methods used. In this paper, we examine different approaches to select and integrate relevant features for TIS prediction. The top selected significant features include the features from the position weight matrix and the propensity matrix, the number of nucleotide C in the sequence downstream ATG, the number of downstream stop codons. the number of upstream ATGs, and the number of some amino acids, such as amino acids A and D. With the numerical data generated from these features, different classification methods, including decision tree. naive Bayes, and support vector machine, were applied to three independent sequence sets. The identified significant features were found to be biologically meaningful. while the experiments showed promising results.     

Microbial fuel cell (MFC) power performance improvement through enhanced microbial electrogenicity

Within the past 5?years, tremendous advances have been made to maximize the performance of microbial fuel cells (MFCs) for both “clean” bioenergy production and bioremediation. Most research efforts have focused on parameters including (i) optimizing reactor configuration, (ii) electrode construction, (iii) addition of redox-active, electron donating mediators, (iv) biofilm acclimation and feed nutrient adjustment, as well as (v) other parameters that contribute to enhanced MFC performance. To date, tremendous advances have been made, but further improvements are needed for MFCs to be economically practical. In this review, the diversity of electrogenic microorganisms and microbial community changes in mixed cultures are discussed. More importantly, different approaches including chemical/genetic modifications and gene regulation of exoelectrogens, synthetic biology approaches and bacterial community cooperation are reviewed. Advances in recent years in metagenomics and microbiomes have allowed researchers to improve bacterial electrogenicity of robust biofilms in MFCs using novel, unconventional approaches. Taken together, this review provides some important and timely information to researchers who are examining additional means to enhance power production of MFCs.     

Mass spectrometry-based proteomics strategies for protease cleavage site identification

Protease-catalyzed hydrolysis of peptide bonds is one of the most pivotal post-translational modifications fulfilling manifold functions in the regulation of cellular processes. Therefore, dysregulation of proteolytic reactions plays a central role in many pathophysiological events. For this reason, understanding the molecular mechanisms in proteolytic reactions, in particular the knowledge of proteases involved in complex processes, expression levels and activity of protease and knowledge of the targeted substrates are an indispensable prerequisite for targeted drug development. The present review focuses on mass spectrometry-based proteomic methods for the analysis of protease cleavage sites, including the identification of the hydrolyzed bonds as well as of the surrounding sequence. Peptide- and protein-centric approaches and bioinformatic tools for experimental data interpretation will be presented and the major advantages and drawbacks of the different approaches will be addressed. The recent applications of these approaches for the analysis of biological function of different protease classes and potential future directions will be discussed.