Mapping regulatory networks in microbial cells

Hierarchy of transcription factor network in Escherichia coli K-12: H-NS-mediated silencing and Anti-silencing by global regulators

Transcriptional regulation for genome expression determines growth and adaptation of single-cell bacteria that are directly exposed to environment. The transcriptional apparatus in Escherichia coli K-12 is composed of RNA polymerase core enzyme and two groups of its regulatory proteins, seven species of promoter-recognition subunit sigma and about 300 species of transcription factors. The identification of regulatory targets for all these regulatory proteins is critical toward understanding the genome regulation as a whole. For this purpose, we performed a systematic search in vitro of the whole set of binding sites for each factor by gSELEX system. This review summarizes the accumulated knowledge of regulatory targets for more than 150 TFs from E. coli K-12. Overall TFs could be classified into four families: nucleoid-associated bifunctional TFs; global regulators; local regulators; and single-target regulators, in which the regulatory functions remain uncharacterized for the nucleoid-associated TFs. Here we overview the regulatory targets of two nucleoid-associated TFs, H-NS and its paralog StpA, both together playing the silencing role of a set of non-essential genes. Participation of LeuO and other global regulators have been indicated for the anti-silencing. Finally, we propose the hierarchy of TF network as a key framework of the bacterial genome regulation.

Comparative gene expression analysis of Porphyromonas gingivalis ATCC 33277 in planktonic and biofilms states

Background and objective

Porphyromonas gingivalis is a keystone pathogen in the onset and progression of periodontitis. Its pathogenicity has been related to its presence and survival within the subgingival biofilm. The aim of the present study was to compare the genome-wide transcription activities of P. gingivalis in biofilm and in planktonic growth, using microarray technology.

Material and methods

P. gingivalis ATCC 33277 was incubated in multi-well culture plates at 37°C for 96 hours under anaerobic conditions using an in vitro static model to develop both the planktonic and biofilm states (the latter over sterile ceramic calcium hydroxyapatite discs). The biofilm development was monitored by Confocal Laser Scanning Microscopy (CLSM) and Scanning Electron Microscopy (SEM). After incubation, the bacterial cells were harvested and total RNA was extracted and purified. Three biological replicates for each cell state were independently hybridized for transcriptomic comparisons. A linear model was used for determining differentially expressed genes and reverse transcription quantitative polymerase chain reaction (RT-qPCR) was used to confirm differential expression. The filtering criteria of ≥ ±2 change in gene expression and significance p-values of <0.05 were selected.

Results

A total of 92 out of 1,909 genes (4.8%) were differentially expressed by P. gingivalis growing in biofilm compared to planktonic. The 54 up-regulated genes in biofilm growth were mainly related to cell envelope, transport, and binding or outer membranes proteins. Thirty-eight showed decreased expression, mainly genes related to transposases or oxidative stress.

Conclusion

The adaptive response of P. gingivalis in biofilm growth demonstrated a differential gene expression.

After genomics, what proteomics tools could help us understand the antimicrobial resistance of Escherichia coli?

Proteomic approaches have been considerably improved during the past decade and have been used to investigate the differences in protein expression profiles of cells grown under a broad spectrum of growth conditions and with different stress factors including antibiotics. In Europe, the most significant disease threat remains the presence of microorganisms that have become resistant to antimicrobials and so it is important that different scientific tools are combined to achieve the largest amount of knowledge in this area of expertise. The emergence and spread of the antibiotic-resistant Gram-negative pathogens, such as Escherichia coli, can lead to serious problem public health in humans. E. coli, a very well described prokaryote, has served as a model organism for several biological and biotechnological studies increasingly so since the completion of the E. coli genome-sequencing project. The purpose of this review is to present an overview of the different proteomic approaches to antimicrobial-resistant E. coli that will be helpful to obtain a better knowledge of the antibiotic-resistant mechanism(s). This can also aid to understand the molecular determinants involved with pathogenesis, which is essential for the development of effective strategies to combat infection and to reveal new therapeutic targets. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Design principles of the bacterial quorum sensing gene networks

Bacterial quorum sensing (QS) has attracted much interest as the manifestation of collective behavior in prokaryotic organisms once considered strictly solitary. Significant amount of genetic, biochemical, and structural data which, has been accumulated in studies on QS in many species allows us to map properties of specific molecules and their interactions on the observed population-wide bacterial behavior. The present review attempts to give a systems biology perspective on the structure of genetic regulatory networks that control QS and considers functional implications of a variety of design principles that recur in the organization of these networks across species.

Mycoplasma pneumoniae Community Acquired Respiratory Distress Syndrome toxin expression reveals growth phase and infection-dependent regulation

Mycoplasma pneumoniae causes acute and chronic respiratory infections, including tracheobronchitis and community acquired pneumonia, and is linked to asthma and an array of extra-pulmonary disorders. Recently, we identified an ADP-ribosylating and vacuolating toxin of M. pneumoniae, designated Community Acquired Respiratory Distress Syndrome (CARDS) toxin. In this study we analysed CARDS toxin gene (annotated mpn372) transcription and identified its promoter. We also compared CARDS toxin mRNA and protein profiles in M. pneumoniae during distinct in vitro growth phases. CARDS toxin mRNA expression was maximal, but at low levels, during early exponential growth and declined sharply during mid-to-late log growth phases, which was in direct contrast to other mycoplasma genes examined. Between 7% and 10% of CARDS toxin was localized to the mycoplasma membrane at mid-exponential growth, which was reinforced by immunogold electron microscopy. No CARDS toxin was released into the medium. Upon M. pneumoniae infection of mammalian cells, increased expression of CARDS toxin mRNA was observed when compared with SP-4 broth-grown cultures. Further, confocal immunofluorescence microscopy revealed that M. pneumoniae readily expressed CARDS toxin during infection of differentiated normal human bronchial epithelial cells. Analysis of M. pneumoniae-infected mouse lung tissue revealed high expression of CARDS toxin per mycoplasma cell when compared with M. pneumoniae cells grown in SP-4 medium alone. Taken together, these studies indicate that CARDS toxin expression is carefully controlled by environmental cues that influence its transcription and translation. Further, the acceleration of CARDS toxin synthesis and accumulation in vivo is consistent with its role as a bona fide virulence determinant.

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference

Background

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality.

Results

Microarray experiments were performed in a γ-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses.

Conclusion

These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

Limited functional conservation of a global regulator among related bacterial genera: Lrp in Escherichia, Proteus and Vibrio

Background

Bacterial genome sequences are being determined rapidly, but few species are physiologically well characterized. Predicting regulation from genome sequences usually involves extrapolation from better-studied bacteria, using the hypothesis that a conserved regulator, conserved target gene, and predicted regulator-binding site in the target promoter imply conserved regulation between the two species. However many compared organisms are ecologically and physiologically diverse, and the limits of extrapolation have not been well tested. In E. coli K-12 the leucine-responsive regulatory protein (Lrp) affects expression of ~400 genes. Proteus mirabilis and Vibrio cholerae have highly-conserved lrp orthologs (98% and 92% identity to E. coli lrp). The functional equivalence of Lrp from these related species was assessed.

Results

Heterologous Lrp regulated gltB, livK and lrp transcriptional fusions in an E. coli background in the same general way as the native Lrp, though with significant differences in extent. Microarray analysis of these strains revealed that the heterologous Lrp proteins significantly influence only about half of the genes affected by native Lrp. In P. mirabilis, heterologous Lrp restored swarming, though with some pattern differences. P. mirabilis produced substantially more Lrp than E. coli or V. cholerae under some conditions. Lrp regulation of target gene orthologs differed among the three native hosts. Strikingly, while Lrp negatively regulates its own gene in E. coli, and was shown to do so even more strongly in P. mirabilis, Lrp appears to activate its own gene in V. cholerae.

Conclusion

The overall similarity of regulatory effects of the Lrp orthologs supports the use of extrapolation between related strains for general purposes. However this study also revealed intrinsic differences even between orthologous regulators sharing >90% overall identity, and 100% identity for the DNA-binding helix-turn-helix motif, as well as differences in the amounts of those regulators. These results suggest that predicting regulation of specific target genes based on genome sequence comparisons alone should be done on a conservative basis.

Porphyromonas gingivalis genes involved in community development with Streptococcus gordonii

Porphyromonas gingivalis, one of the causative agents of adult periodontitis, develops biofilm microcolonies on substrata of Streptococcus gordonii but not on Streptococcus mutans. P. gingivalis genome microarrays were used to identify genes differentially regulated during accretion of P. gingivalis in heterotypic biofilms with S. gordonii. Thirty-three genes showed up- or downregulation by array analysis, and differential expression was confirmed by quantitative reverse transcription-PCR. The functions of the regulated genes were predominantly related to metabolism and energy production. In addition, many of the genes have no current known function. The roles of two upregulated genes, ftsH (PG0047) encoding an ATP-dependent zinc metallopeptidase and ptpA (PG1641) encoding a putative tyrosine phosphatase, were investigated further by mutational analysis. Strains with mutations in these genes developed more abundant biofilms with S. gordonii than the parental strain developed. ftsH and ptpA may thus participate in a regulatory network that constrains P. gingivalis accumulation in heterotypic biofilms. This study provided a global analysis of P. gingivalis transcriptional responses in an oral microbial community and also provided insight into the regulation of heterotypic biofilm development.

Proteomics

Proteomics is the measurement of one or more protein populations or proteomes, preferably in a quantitative manner. A protein population may be the set of proteins found in an organism, in a tissue or biofluid, in a cell, or in a subcellular compartment. A population also may be the set of proteins with a common characteristic, for example, those that interact with each other in molecular complexes, those involved in the same process such as signal transduction or cell cycle control, or those that share a common posttranslational modification such as phosphorylation or glycosylation. Proteomics experiments that involve mass spectrometry are divided into five categories: (1) protein identification, (2) protein quantitation or differential analysis, (3) protein-protein interactions, (4) post-translational modifications, and (5) structural proteomics. Each of these proteomics categories is reviewed. Examples are given for quantitative experiments involving two-dimensional gel electrophoresis, and for gel-free analysis using isotope-coded affinity tags. The impact of proteomics on biological research and on drug development is discussed. Challenges for further development in proteomics are presented, including sample preparation, sensitivity, dynamic range, and automation.

A nonlinear discrete dynamical model for transcriptional regulation: construction and properties

Transcriptional regulation is a fundamental mechanism of living cells, which allows them to determine their actions and properties, by selectively choosing which proteins to express and by dynamically controlling the amounts of those proteins. In this article, we revisit the problem of mathematically modeling transcriptional regulation. First, we adopt a biologically motivated continuous model for gene transcription and mRNA translation, based on first-order rate equations, coupled with a set of nonlinear equations that model cis-regulation. Then, we view the processes of transcription and translation as being discrete, which, together with the need to use computational techniques for large-scale analysis and simulation, motivates us to model transcriptional regulation by means of a nonlinear discrete dynamical system. Classical arguments from chemical kinetics allow us to specify the nonlinearities underlying cis-regulation and to include both activators and repressors as well as the notion of regulatory modules in our formulation. We show that the steady-state behavior of the proposed discrete dynamical system is identical to that of the continuous model. We discuss several aspects of our model, related to homeostatic and epigenetic regulation as well as to Boolean networks, and elaborate on their significance. Simulations of transcriptional regulation of a hypothetical metabolic pathway illustrate several properties of our model, and demonstrate that a nonlinear discrete dynamical system may be effectively used to model transcriptional regulation in a biologically relevant way.

Reliability of gene expression ratios for cDNA microarrays in multiconditional experiments with a reference design

In a typical gene expression profiling experiment with multiple conditions, a common reference sample is used for co-hybridization with the samples to yield expression ratios. Differential expression for any other sample pair can then be calculated by assembling the ratios from their hybridizations with the reference. In this study we test the validity of this approach. Differential expression of a sample pair (i, j) was obtained in two ways: directly, by hybridizations of sample i versus j, and indirectly, by multiplying the expression ratios for hybridizations of sample i versus pool and pool versus sample j. We performed gene expression profiling using amphibian embryos (Xenopus laevis). Every sample combination of four different stages and a pool was profiled. Direct and indirect values were compared and used as the quality criterion for the data. Based on this criterion, 82% of all ratios were found to be sufficiently accurate. To increase the reliability of the signals, several widely used filtering techniques were tested. Filtering by differences of repeated hybridizations was found to be the optimal filter. Finally, we compared microarray-based gene expression profiles with the corresponding expression patterns obtained by whole-mount in situ hybridizations, resulting in a 90% correspondence.

Proteomics of bacterial pathogens

The rapid growth of proteomics that has been built upon the available bacterial genome sequences has opened provided new approaches to the analysis of bacterial functional genomics. In the study of pathogenic bacteria the combined technologies of genomics, proteomics and bioinformatics has provided valuable tools for the study of complex phenomena determined by the action of multiple gene sets. The review considers some of the recent developments in the establishment of proteomic databases as well as attempts to define pathogenic determinants at the level of the proteome for some of the major human pathogens. Proteomics can also provide practical applications through the identification of immunogenic proteins that may be potential vaccine targets as well as in extending our understanding of antibiotic action. There is little doubt that proteomics has provided us with new and valuable information on bacterial pathogens and will continue to be an important source of information in the coming years.

Proteomics based on high-efficiency capillary separations

Identifying and quantifying in a high throughput manner the proteins expressed by cells, tissues or an organism provides the basis for understanding the functions of its constituents at a "systems" level. As a result, proteome analysis has increasingly become the focus of significant interest and research over the past decade. This is especially true following the recent stunning achievements in genomics analyses. However, unlike the static genome, the complexities and dynamism of the proteome present significant analytical challenges and demand highly efficient separations and detection technologies. A number of recent technological advancements have been in direct response to these challenges. Currently, strategically mated combinations of sophisticated separations techniques and advanced mass spectrometric detection represent the best approach to addressing the intricacies of the proteome. Liquid-phase separations, often within capillaries, are increasingly recognized as the best separations technique for this approach. In combination on-line with mass spectrometry, liquid-phase separations provide the improved analytical sensitivity, sample throughput, and quantitation capabilities necessitated by the multifaceted problems within proteomics analyses. This review focuses primarily on current high-efficiency capillary separations techniques, including both capillary liquid chromatography and capillary electrophoresis, applied to the analysis of complex proteomic samples. We emphasize developments at our laboratory and illustrate technical advances that attempt to review the role of separations within the broader context of a state-of-the-art integrated proteomics effort.

The Leopoldina international symposium on parasitism, commensalism and symbiosis--common themes, different outcome

The development of new methods, including genomics, which can even be applied to unculturable microorganisms, has significantly increased our knowledge about bacterial pathogenesis and symbiosis and, in consequence, is profoundly modifying our views on the evolution and the genetic and physiological basis of bacteria-host interactions. The presentations at this symposium revealed conceptual links between bacterial pathogenesis and symbiosis. The close co-operation of experts in both fields will result in significant synergy and new insights into basic mechanisms of bacteria-host interactions and their evolution. The meeting provided fascinating news about the genetic and metabolic consequences that the change in their lifestyle had for bacteria that developed from free-living to permanent host-associated organisms exemplified by intracellular pathogens or symbionts. In addition, surprising similarities but also striking differences between the strategies involved in the establishment of a symbiotic versus a parasitic lifestyle can be noted. In the long run, the characterization of such differences might lead to lifestyle prediction or to an evaluation of the pathogenic potential of newly isolated bacteria via the definition of genetic and/or metabolic signatures characteristic for pathogenic or symbiotic organisms. Moreover, it is expected that these investigations will lead to new strategies for the treatment or prevention of bacterial infections, or the avoidance of pathogen transmission.

Mice, microbes and models of infection

We urgently need animal models to study infectious disease. Mice are susceptible to a similar range of microbial infections as humans. Marked differences between inbred strains of mice in their response to pathogen infection can be exploited to analyse the genetic basis of infections. In addition, the genetic tools that are available in the laboratory mouse, and new techniques to monitor the expression of bacterial genes in vivo, make it the principal experimental animal model for studying mechanisms of infection and immunity.

Biotechnological manufacture of lysine

L-Lysine has been manufactured using Corynebacterium glutamicum for more than 40 years. Nowadays production exceeds 600,000 tons per year. Based on conventionally bred strains, further improvement of lysine productivity has been achieved by genetic engineering. Pyruvate carboxylase, aspartate kinase, dihydrodipicolinate synthase, homoserine dehydrogenase and the specific lysine exporter were shown to be key enzymes for lysine production and were characterized in detail. Their combined engineering led to a striking increase in lysine formation. Pathway modeling with data emerging from 13C-isotope experiments revealed a coordinated flux through pentose phosphate cycle and tricarboxylic acid cycle and intensive futile cycling between C3 compounds of glycolysis and C4 compounds of tricarboxylic acid cycle. Process economics have been optimized by developing repeated fed-batch techniques and technical continuous fermentations. In addition, on-line metabolic pathway analysis or flow cytometry may help to improve the fermentation performance. Finally, the availability of the Corynebacterium glutamicum genome sequence has a major impact on the improvement of the biotechnological manufacture of lysine. In this context, all genes of the carbon flow from sugar uptake to lysine secretion have been identified and are accessible to manipulation. The whole sequence information gives access to post genome technologies such as transcriptome analysis, investigation of the proteome and the active metabolic network. These multi-parallel working technologies will accelerate the generation of knowledge. For the first time there is a chance of understanding the overall picture of the physiological state of lysine overproduction in a technical environment.

Proteome analysis of Escherichia coli K-12 by two-dimensional native-state chromatography and MALDI-MS

To identify proteins expressed in Escherichia coli K-12 MG1655 during exponential growth in defined medium, we separated soluble proteins of E. coli over two dimensions of native-state high-performance liquid chromatography, and examined the components of the protein mixtures in each of 380 fractions by peptide mass fingerprinting. To date, we have identified the products of 310 genes covering a wide range of cellular functions. Validation of protein assignments was made by comparing the assignments of proteins to specific first-dimension fractions to proteins visualized by two-dimensional gel electrophoresis. Co-fractionation of proteins suggests the possible identities of components of multiprotein complexes. This approach yields high-throughput gel-independent identification of proteins. It can also be used to assign identities to spots visualized by two-dimensional gels, and should be useful to evaluate differences in expressed proteome content and protein complexes among strains or between different physiological states.

RNA expression analysis using an antisense Bacillus subtilis genome array

We have developed an antisense oligonucleotide microarray for the study of gene expression and regulation in Bacillus subtilis by using Affymetrix technology. Quality control tests of the B. subtilis GeneChip were performed to ascertain the quality of the array. These tests included optimization of the labeling and hybridization conditions, determination of the linear dynamic range of gene expression levels, and assessment of differential gene expression patterns of known vitamin biosynthetic genes. In minimal medium, we detected transcripts for approximately 70% of the known open reading frames (ORFs). In addition, we were able to monitor the transcript level of known biosynthetic genes regulated by riboflavin, biotin, or thiamine. Moreover, novel transcripts were also detected within intergenic regions and on the opposite coding strand of known ORFs. Several of these novel transcripts were subsequently correlated to new coding regions.

Global transcriptional response of Bacillus subtilis to heat shock

In response to heat stress, Bacillus subtilis activates the transcription of well over 100 different genes. Many of these genes are members of a general stress response regulon controlled by the secondary sigma factor, sigma(B), while others are under control of the HrcA or CtsR heat shock regulators. We have used DNA microarrays to monitor the global transcriptional response to heat shock. We find strong induction of known sigma(B)-dependent genes with a characteristic rapid induction followed by a return to near prestimulus levels. The HrcA and CtsR regulons are also induced, but with somewhat slower kinetics. Analysis of DNA sequences proximal to newly identified heat-induced genes leads us to propose ~70 additional members of the sigma(B) regulon. We have also identified numerous heat-induced genes that are not members of known heat shock regulons. Notably, we observe very strong induction of arginine biosynthesis and transport operons. Induction of several genes was confirmed by quantitative reverse transcriptase PCR. In addition, the transcriptional responses measured by microarray hybridization compare favorably with the numerous previous studies of heat shock in this organism. Since many different conditions elicit both specific and general stress responses, knowledge of the heat-induced general stress response reported here will be helpful for interpreting future microarray studies of other stress responses.

Packed capillary reversed-phase liquid chromatography with high-performance electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry for proteomics

In this study, high-efficiency packed capillary reversed-phase liquid chromatography (RPLC) coupled on-line with high-performance Fourier transform ion cyclotron resonance (FTICR) mass spectrometry has been investigated for the characterization of complex cellular proteolytic digests. Long capillary columns (80-cm) packed with small (3-micron) C18 bonded particles provided a total peak capacity of approximately 1000 for cellular proteolytic polypeptides when interfaced with an ESI-FTICR mass spectrometer under composition gradient conditions at a pressure of 10,000 psi. Large quantities of cellular proteolytic digests (e.g., 500 micrograms) could be loaded onto packed capillaries of 150-micron inner diameter without a significant loss of separation efficiency. Precolumns with suitable inner diameters were found useful for improving the elution reproducibility without a significant loss of separation quality. Porous particle packed capillaries were found to provide better results than those containing nonporous particles because of their higher sample capacity. Two-dimensional analyses from the combination of packed capillary RPLC with high-resolution FTICR yield a combined capacity for separations of > 1 million polypeptide components and simultaneously provided information for the identification of the separated components based upon the accurate mass tag concept previously described.

Proteomic analysis of the bacterial cell cycle

A global approach was used to analyze protein synthesis and stability during the cell cycle of the bacterium Caulobacter crescentus. Approximately one-fourth (979) of the estimated C. crescentus gene products were detected by two-dimensional gel electrophoresis, 144 of which showed differential cell cycle expression patterns. Eighty-one of these proteins were identified by mass spectrometry and were assigned to a wide variety of functional groups. Pattern analysis revealed that coexpression groups were functionally clustered. A total of 48 proteins were rapidly degraded in the course of one cell cycle. More than half of these unstable proteins were also found to be synthesized in a cell cycle-dependent manner, establishing a strong correlation between rapid protein turnover and the periodicity of the bacterial cell cycle. This is, to our knowledge, the first evidence for a global role of proteolysis in bacterial cell cycle control.

Neural network model of gene expression

Many natural processes consist of networks of interacting elements that, over time, affect each other's state. Their dynamics depend on the pattern of connections and the updating rules for each element. Genomic regulatory networks are networks of this sort. In this paper we use artificial neural networks as a model of the dynamics of gene expression. The significance of the regulatory effect of one gene product on the expression of other genes of the system is defined by a weight matrix. The model considers multigenic regulation including positive and/or negative feedback. The process of gene expression is described by a single network and by two linked networks where transcription and translation are modeled independently. Each of these processes is described by different network controlled by different weight matrices. Methods for computing the parameters of the model from experimental data are discussed. Results computed by means of the model are compared with experimental observations. Generalization to a 'black box' concept, where the molecular processes occurring in the cell are considered as signal processing units forming a global regulatory network, is discussed.-Vohradský, J. Neural network model of gene expression.

Complementing genomics with proteomics: the membrane subproteome of Pseudomonas aeruginosa PAO1

With the completion of many genome projects, a shift is now occurring from the acquisition of gene sequence to understanding the role and context of gene products within the genome. The opportunistic pathogen Pseudomonas aeruginosa is one organism for which a genome sequence is now available, including the annotation of open reading frames (ORFs). However, approximately one third of the ORFs are as yet undefined in function. Proteomics can complement genomics, by characterising gene products and their response to a variety of biological and environmental influences. In this study we have established the first two-dimensional gel electrophoresis reference map of proteins from the membrane fraction of P. aeruginosa strain PA01. A total of 189 proteins have been identified and correlated with 104 genes from the P. aeruginosa genome. Annotated membrane proteins could be grouped into three distinct categories: (i) those with functions previously characterised in P. aeruginosa (38%); (ii) those with significant sequence similarity to proteins with assigned function or hypothetical proteins in other organisms (46%); and (iii) those with unknown function (16%). Transmembrane prediction algorithms showed that each identified protein sequence contained at least one membrane-spanning region. Furthermore, the current methodology used to isolate the membrane fraction was shown to be highly specific since no contaminating cytosolic proteins were characterised. Preliminary analysis showed that at least 15 gel spots may be glycosylated in vivo, including three proteins that have not previously been functionally characterised. The reference map of membrane proteins from this organism is now the basis for determining surface molecules associated with antibiotic resistance and efflux, cell-cell signalling and pathogen-host interactions in a variety of P. aeruginosa strains.

Relationship of codon bias to mRNA concentration and protein length in Saccharomyces cerevisiae

In 1982, Ikemura reported a strikingly unequal usage of different synonymous codons, in five Saccharomyces cerevisiae nuclear genes having high protein levels. To study this trend in detail, we examined data from three independent studies that used oligonucleotide arrays or SAGE to estimate mRNA concentrations for nearly all genes in the genome. Correlation coefficients were calculated for the relationship of mRNA concentration to four commonly used measures of synonymous codon usage bias: the codon adaptation index (CAI), the codon bias index (CBI), the frequency of optimal codons (F(op)), and the effective number of codons (N(c)). mRNA concentration was best approximated as an exponential function of each of these four measures. Of the four, the CAI was the most strongly correlated with mRNA concentration (r(s)=0.62+/-0.01, n=2525, p<10(-17)). When we controlled for CAI, mRNA concentration and protein length were negatively correlated (partial r(s)=-0.23+/-0.01, n=4765, p<10(-17)). This may result from selection to reduce the size of abundant proteins to minimize transcriptional and translational costs. When we controlled for mRNA concentration, protein length and CAI were positively correlated (partial r(s)=0.16+/-0.01, n=4765, p<10(-17)). This may reflect more effective selection in longer genes against missense errors during translation. The correlation coefficients between the mRNA levels of individual genes, as measured by different investigators and methods, were low, in the range r(s)=0.39-0.68.

Recent developments and future directions in computational genomics

Computational genomics is a subfield of computational biology that deals with the analysis of entire genome sequences. Transcending the boundaries of classical sequence analysis, computational genomics exploits the inherent properties of entire genomes by modelling them as systems. We review recent developments in the field, discuss in some detail a number of novel approaches that take into account the genomic context and argue that progress will be made by novel knowledge representation and simulation technologies.

Proteomics: applications in basic and applied biology

The rapid evolution of proteomics has continued during the past year, with a series of innovations in the core technologies of two-dimensional electrophoresis and mass spectrometry, and a diversity of productive research programmes. Well-annotated proteomics databases are now emerging in a number of fields to provide a platform for systematic research, with particularly promising progress in clinical applications such as cardiology and oncology. Large-scale quantitative research, comparable in power and sensitivity to that achieved for gene expression, is thus becoming a reality at the protein level.

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.