RNA localization in bacteria

Bacteria localize proteins and DNA regions to specific subcellular sites, and several recent publications show that RNAs are localized within the cell as well. Localization of tmRNA and some mRNAs indicates that RNAs can be sequestered at specific sites by RNA binding proteins, or can be trapped at the location where they are transcribed. Although the functions of RNA localization are not yet completely understood, it appears that one function of RNA localization is to regulate RNA abundance by controlling access to nucleases. New techniques for visualizing RNAs will likely lead to increased examination of spatial control of RNAs and the role this control plays in the regulation of gene expression and bacterial physiology.     

RNA helicases in bacteria

1. Download : Download high-res image (115KB)
2. Download : Download full-size image

     

ELISA techniques for the determination of methanogenic bacteria

Summary Easy-to-handle enzyme-linked immunosorbent assay (ELISA) techniques have been developed suitable for quantitative species-specific determination of very low numbers of methanogens in complex bacterial populations. The amount and the distribution of different species of methanogens in anaerobic digestors is a reflection of the functional status of the degradation process; this can be recognized with these tests and hence may be used for process control.Offprint requests to: W. Trösch     

细菌非编码RNA及其分子伴侣Hfq

细菌在生存过程中要面对复杂多样的环境,在长期进化过程中,细菌逐渐形成不同的应答机制来感应环境信号的变化,并通过精确的基因表达来调控生理生化反应。基因表达调控可分为转录水平和转录后水平两个方面,对于细菌来说,非编码RNA在转录后调控上发挥着重要的作用,而大多数非编码RNA与靶标m RNA的相互作用过程又离不开Hfq蛋白的辅助。本文综述了非编码RNA的分类、调控特点,伴侣蛋白Hfq的结构、功能以及两者相互作用的机制,以期深入了解非编码RNA及其伴侣蛋白Hfq在转录后调控中发挥的作用。     

Dual-function RNA regulators in bacteria

The importance of small RNA (sRNA) regulators has been recognized across all domains of life. In bacteria, sRNAs typically control the expression of virulence and stress response genes via antisense base pairing with mRNA targets. Originally dubbed “non-coding RNAs,” a number of bacterial antisense sRNAs have been found to encode functional proteins. Although very few of these dual-function sRNAs have been characterized, they have been found in both gram-negative and gram-positive organisms. Among the few known examples, the functions and mechanisms of regulation by dual-function sRNAs are variable. Some dual-function sRNAs depend on the RNA chaperone Hfq for base pairing-dependent regulation (riboregulation); this feature appears so far exclusive to gram-negative bacterial sRNAs. Other variations can be found in the spatial organization of the coding region with respect to the riboregulation determinants. How the functions of encoded proteins relate to riboregulation is for the most part not understood. However, in one case it appears that there is physiological redundancy between protein and riboregulation functions. This mini-review focuses on the two best-studied bacterial dual-function sRNAs: RNAIII from Staphylococcus aureus and SgrS from Escherichia coli and includes a discussion of what is known about the structure, function and physiological roles of these sRNAs as well as what questions remain outstanding.     

Comparison of two direct-count techniques for enumerating aquatic bacteria.

Planktonic bacteria from an estuary were concentrated on membrane filters and counted with both a scanning electron microscope and an epi-illuminated fluorescent microscope. Counts on 0.2 micron Nuclepore filters (polycarbonate) were significantly higher (P less than 0.001) than counts on 0.2-micron Sartorius filters (cellulose). In contrast, there was not a statistically significant difference between the two techniques when Nuclepore filters were used (0.5 less than P less than 0.9). The average cell volume from this study area was 0.047 micron3. The estimated number of bacteria ranged from 10(6) to 10(7) bacteria per ml, representing from 4 to 40 mg of C per m3.     

Comparison of two direct-count techniques for enumerating aquatic bacteria.

Planktonic bacteria from an estuary were concentrated on membrane filters and counted with both a scanning electron microscope and an epi-illuminated fluorescent microscope. Counts on 0.2 micron Nuclepore filters (polycarbonate) were significantly higher (P less than 0.001) than counts on 0.2-micron Sartorius filters (cellulose). In contrast, there was not a statistically significant difference between the two techniques when Nuclepore filters were used (0.5 less than P less than 0.9). The average cell volume from this study area was 0.047 micron3. The estimated number of bacteria ranged from 10(6) to 10(7) bacteria per ml, representing from 4 to 40 mg of C per m3.     

RNA研究相关技术及其应用

RNA技术可以分为RNA基础研究相关的技术、RNA应用相关的技术和RNA的生物信息学技术。RNA基础研究相关技术包括RNA分离纯化和鉴定技术、RNA与其他生物大分子相互作用技术、RNA高级结构的研究技术和其他相关RNA技术;RNA应用相关技术则包括用于生产其他产品的RNA技术和直接用于药物开发的RNA技术;RNA的生物信息学技术则有各种数据库、非编码RNA的预测、RNA二级结构预测和各种设计软件。本文简略介绍了上述各类RNA技术的原理及其国内外研究进展,从而有助于对RNA领域有关技术方面有一较全面的了解。     

Maturation and degradation of RNA in bacteria

RNA decay plays an important role, not only in recycling nucleotides but also in determining the rapidity with which cells can react to changing growth conditions. The degradation process can be regulated, thus providing an often-underestimated means of controlling gene expression. Recent developments in the field of RNA maturation and decay in two key model organisms, Escherichia coli and Bacillus subtilis, include the resolution of the structures of many of the participants in these processes in E. coli and the identification of an enzyme in B. subtilis that appears to fit the bill as a major player in RNA decay in this organism.     

Degradation of RNA in bacteria: comparison of mRNA and stable RNA

Degradation of RNA plays a central role in RNA metabolism. In recent years, our knowledge of the mechanisms of RNA degradation has increased considerably with discovery of the participating RNases and analysis of mutants affected in the various degradative pathways. Among these processes, mRNA decay and stable RNA degradation generally have been considered distinct, and also separate from RNA maturation. In this review, each of these processes is described, as it is currently understood in bacteria. The picture that emerges is that decay of mRNA and degradation of stable RNA share many common features, and that their initial steps also overlap with those of RNA maturation. Thus, bacterial cells do not contain dedicated machinery for degradation of different classes of RNA or for different processes. Rather, only the specificity of the RNase and the accessibility of the substrate determine whether or not a particular RNA will be acted upon.     

Biomarker techniques to screen for bacteria that produce polyunsaturated fatty acids.

The production of polyunsaturated fatty acids (PUFA) by bacteria has been firmly established for over two decades although it is still commonly ignored. Investigations of Antarctic sea ice have revealed a high diversity of novel bacterial taxa with the ability to produce PUFA. The majority are psychrophilic (requiring low temperatures for growth) and halophilic (requiring the presence of salts for growth), in contrast to the bacterial community present in the underlying water column. Specific fatty acids may be used as indicators of PUFA-producing bacteria in environmental samples. Structural studies of bacterial phospholipids have been particularly revealing in suggesting biomarkers specific for prokaryotic PUFA input. The use of negative ion fast atom bombardment tandem mass spectrometry for the analysis of bacterial phospholipids has identified species specific for certain groups of bacterial PUFA producers. The phylogeny of PUFA production in the gamma-Proteobacteria also suggests the future use of PUFA genes for the assessment of marine bacterial biodiversity.     

Comparison of pattern recognition techniques for the identification of lactic acid bacteria

AIMS: The goal of this study was to evaluate three pattern recognition methods for use in the identification of lactic acid bacteria. METHODS AND RESULTS: Lactic acid bacteria (21 unknown isolates and 30 well-characterized strains), including the Lactobacillus, Lactococcus, Streptococcus, Pediococcus and Oenococcus genera, were tested for 49 phenotypic responses (acid production on carbon sources). The results were scored in several ways. Three procedures, k-nearest neighbour analysis (KNN), k-means clustering and fuzzy c-means clustering (FCM), were applied to the data. CONCLUSION: k-Nearest neighbour analysis performed better with five-point-scaled than with binary data, indicating that intermediate values are helpful to classification. k-Means clustering performed slightly better than KNN and was best with fuzzified data. The best overall results were obtained with FCM. Genus level classification was best with FCM using an exponent of 1.25. SIGNIFICANCE AND IMPACT OF THE STUDY: The three pattern recognition methods offer some advantages over other approaches to organism classification.     

Assessing computational tools for the discovery of small RNA genes in bacteria

Over the past decade, a number of biocomputational tools have been developed to predict small RNA (sRNA) genes in bacterial genomes. In this study, several of the leading biocomputational tools, which use different methodologies, were investigated. The performance of the tools, both individually and in combination, was evaluated on ten sets of benchmark data, including data from a novel RNA-seq experiment conducted in this study. The results of this study offer insight into the utility as well as the limitations of the leading biocomputational tools for sRNA identification and provide practical guidance for users of the tools.