Only a small subset of the horizontally transferred chromosomal genes in Escherichia coli are translated into proteins

Multichannel Reverse Transcription-Polymerase Chain Reaction Microdevice for Rapid Gene Expression and Biomarker Analysis

A microdevice is developed for RNA analysis that integrates one-step reverse transcription and 30 cycles of PCR (RT-PCR) amplification with capillary electrophoresis (CE) separation and fluorescence detection of the amplicons. The four-layer glass-PDMS-glass-glass hybrid microdevice integrates microvalves, on-chip heaters and temperature sensors, nanoliter reaction chambers (380 nL), and 5-cm-long CE separation channels. The direct integration of these processes results in attomolar detection sensitivity (<11 template RNA molecules or approximately 0.1 cellular equiv) and rapid 45-min analysis, while minimizing sample waste and eliminating contamination. Size-based electrophoretic product analysis provides definitive amplicon-size verification and multiplex analysis. Multiplexed differential gene expression analysis is demonstrated on mdh and gyrB E. coli transcripts. RNA splice variant analysis of the RBBP8 gene is used to identify tumorigenic tissue. RT-PCR microdevice analysis of normal breast tissue RNA generates the expected 202-bp normal splice isoform; tumor breast tissue RNA samples generate a 151-bp amplicon signifying the presence of the tumorigenic splice variant. The ability to perform RNA transcript and splice variant biomarker analysis establishes our RT-PCR microdevice as a versatile gene expression platform.

Prevalent Structural Disorder inE.coliandS.cerevisiaeProteomes

Intrinsically unstructured proteins, which exist without a well-defined 3D structure, carry out essential functions and occur with high frequency, as predicted for genomes. The generality of this phenomenon, however, is questioned by the uncertainty of what fraction of genomes actually encodes for expressed proteins. Here, we used two independent bioinformatic predictors, PONDR VSL1, and IUPred, to demonstrate that disorder prevails in the recently characterized proteomes and essential proteins of E. coli and S. cerevisiae, at levels exceeding that estimated from the genomes. The S. cerevisiae proteome contains three times as much disorder as that of E. coli, with 50-60% of proteins containing at least one long (>30 residues) disordered segment. This evolutionary advance can be explained by the observation that disorder is much higher in Gene Ontology categories related to regulatory, as opposed to metabolic, functions, and also in categories unique to yeast. Thus, protein disorder is a widespread and functionally important phenomenon, which needs to be characterized in full detail for understanding complex organisms at the molecular level.

Ten years of bacterial genome sequencing: comparative-genomics-based discoveries

It has been more than 10 years since the first bacterial genome sequence was published. Hundreds of bacterial genome sequences are now available for comparative genomics, and searching a given protein against more than a thousand genomes will soon be possible. The subject of this review will address a relatively straightforward question: "What have we learned from this vast amount of new genomic data?" Perhaps one of the most important lessons has been that genetic diversity, at the level of large-scale variation amongst even genomes of the same species, is far greater than was thought. The classical textbook view of evolution relying on the relatively slow accumulation of mutational events at the level of individual bases scattered throughout the genome has changed. One of the most obvious conclusions from examining the sequences from several hundred bacterial genomes is the enormous amount of diversity--even in different genomes from the same bacterial species. This diversity is generated by a variety of mechanisms, including mobile genetic elements and bacteriophages. An examination of the 20 Escherichia coli genomes sequenced so far dramatically illustrates this, with the genome size ranging from 4.6 to 5.5 Mbp; much of the variation appears to be of phage origin. This review also addresses mobile genetic elements, including pathogenicity islands and the structure of transposable elements. There are at least 20 different methods available to compare bacterial genomes. Metagenomics offers the chance to study genomic sequences found in ecosystems, including genomes of species that are difficult to culture. It has become clear that a genome sequence represents more than just a collection of gene sequences for an organism and that information concerning the environment and growth conditions for the organism are important for interpretation of the genomic data. The newly proposed Minimal Information about a Genome Sequence standard has been developed to obtain this information.

The fate of laterally transferred genes: life in the fast lane to adaptation or death

Large-scale genome arrangement plays an important role in bacterial genome evolution. A substantial number of genes can be inserted into, deleted from, or rearranged within genomes during evolution. Detecting or inferring gene insertions/deletions is of interest because such information provides insights into bacterial genome evolution and speciation. However, efficient inference of genome events is difficult because genome comparisons alone do not generally supply enough information to distinguish insertions, deletions, and other rearrangements. In this study, homologous genes from the complete genomes of 13 closely related bacteria were examined. The presence or absence of genes from each genome was cataloged, and a maximum likelihood method was used to infer insertion/deletion rates according to the phylogenetic history of the taxa. It was found that whole gene insertions/deletions in genomes occur at rates comparable to or greater than the rate of nucleotide substitution and that higher insertion/deletion rates are often inferred to be present at the tips of the phylogeny with lower rates on more ancient interior branches. Recently transferred genes are under faster and relaxed evolution compared with more ancient genes. Together, this implies that many of the lineage-specific insertions are lost quickly during evolution and that perhaps a few of the genes inserted by lateral transfer are niche specific.

Escherichia coli competence gene homologs are essential for competitive fitness and the use of DNA as a nutrient

Natural genetic competence is the ability of cells to take up extracellular DNA and is an important mechanism for horizontal gene transfer. Another potential benefit of natural competence is that exogenous DNA can serve as a nutrient source for starving bacteria because the ability to "eat" DNA is necessary for competitive survival in environments containing limited nutrients. We show here that eight Escherichia coli genes, identified as homologs of com genes in Haemophilus influenzae and Neisseria gonorrhoeae, are necessary for the use of extracellular DNA as the sole source of carbon and energy. These genes also confer a competitive advantage to E. coli during long-term stationary-phase incubation. We also show that homologs of these genes are found throughout the proteobacteria, suggesting that the use of DNA as a nutrient may be a widespread phenomenon.

Proteome analysis of yeast response to various nutrient limitations

We compared the response of Saccharomyces cerevisiae to carbon (glucose) and nitrogen (ammonia) limitation in chemostat cultivation at the proteome level. Protein levels were differentially quantified using unlabeled and ¹⁵N metabolically labeled yeast cultures. A total of 928 proteins covering a wide range of isoelectric points, molecular weights and subcellular localizations were identified. Stringent statistical analysis identified 51 proteins upregulated in response to glucose limitation and 51 upregulated in response to ammonia limitation. Under glucose limitation, typical glucose-repressed genes encoding proteins involved in alternative carbon source utilization, fatty acids β-oxidation and oxidative phosphorylation displayed an increased protein level. Proteins upregulated in response to nitrogen limitation were mostly involved in scavenging of alternative nitrogen sources and protein degradation. Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulation in response to nitrogen limitation was essentially controlled at the post-transcriptional level by increased translational efficiency and/or decreased protein degradation. These observations underline the need for multilevel analysis in yeast systems biology.

The nature and dynamics of bacterial genomes

Though generally small and gene rich, bacterial genomes are constantly subjected to both mutational and population-level processes that operate to increase amounts of functionless DNA. As a result, the coding potential of bacterial genomes can be substantially lower than originally predicted. Whereas only a single pseudogene was included in the original annotation of the bacterium Escherichia coli, we estimate that this genome harbors hundreds of inactivated and otherwise functionless genes. Such regions will never yield a detectable phenotype, but their identification is vital to efforts to elucidate the biological role of all the proteins within the cell.

Shuffling bacterial metabolomes

Horizontal gene transfer (HGT) is more important than gene duplication in bacterial evolution, as has recently been illustrated by work demonstrating the role of HGT in the emergence of bacterial metabolic networks.

Horizontal gene transfer (HGT) has a far more significant role than gene duplication in bacterial evolution. This has recently been illustrated by work demonstrating the importance of HGT in the emergence of bacterial metabolic networks, with horizontally acquired genes being placed in peripheral pathways at the outer branches of the networks.

Mass Spectrometric Identification of Proteins in Complex Post-Genomic Projects

The rapidly developing proteomics technologies help to advance the global understanding of physiological and cellular processes. The lifestyle of a study organism determines the type and complexity of a given proteomic project. The complexity of this study is characterized by a broad collection of pathway-specific subproteomes, reflecting the metabolic versatility as well as the regulatory potential of the aromatic-degrading, denitrifying bacterium 'Aromatoleum' sp. strain EbN1. Differences in protein profiles were determined using a gel-based approach. Protein identification was based on a progressive application of MALDI-TOF-MS, MALDI-TOF-MS/MS and LC-ESI-MS/MS. This progression was result-driven and automated by software control. The identification rate was increased by the assembly of a project-specific list of background signals that was used for internal calibration of the MS spectra, and by the combination of two search engines using a dedicated MetaScoring algorithm. In total, intelligent bioinformatics could increase the identification yield from 53 to 70% of the analyzed 5,050 gel spots; a total of 556 different proteins were identified. MS identification was highly reproducible: most proteins were identified more than twice from parallel 2DE gels with an average sequence coverage of >50% and rather restrictive score thresholds (Mascot >or=95, ProFound >or=2.2, MetaScore >or=97). The MS technologies and bioinformatics tools that were implemented and integrated to handle this complex proteomic project are presented. In addition, we describe the basic principles and current developments of the applied technologies and provide an overview over the current state of microbial proteome research.

Adaptive evolution of bacterial metabolic networks by horizontal gene transfer

Numerous studies have considered the emergence of metabolic pathways, but the modes of recent evolution of metabolic networks are poorly understood. Here, we integrate comparative genomics with flux balance analysis to examine (i) the contribution of different genetic mechanisms to network growth in bacteria, (ii) the selective forces driving network evolution and (iii) the integration of new nodes into the network. Most changes to the metabolic network of Escherichia coli in the past 100 million years are due to horizontal gene transfer, with little contribution from gene duplicates. Networks grow by acquiring genes involved in the transport and catalysis of external nutrients, driven by adaptations to changing environments. Accordingly, horizontally transferred genes are integrated at the periphery of the network, whereas central parts remain evolutionarily stable. Genes encoding physiologically coupled reactions are often transferred together, frequently in operons. Thus, bacterial metabolic networks evolve by direct uptake of peripheral reactions in response to changed environments.

Electrochemical structure of the crowded cytoplasm

The current view of the cytoplasm as a 'bustling and well-organized metropolitan city' raises the issue of how physicochemical forces control the macromolecular interactions and transport of metabolites and energy in the cell. Motivated by studies on bacterial osmosensors, we argue that charged cytoplasmic macromolecules are stabilized electrostatically by their ionic atmospheres. The high cytoplasmic crowding (25-50% of cell volume) shapes the remaining cell volume (50-75%) into transient networks of electrolyte pathways and pools. The predicted 'semi-conductivity' of the electrolyte pathways guides the flow of biochemical ions throughout the cytoplasm. This metabolic and signaling current is powered by variable electrochemical gradients between the pools. The electrochemical gradients are brought about by cellular biochemical reactions and by extracellular stimuli. The cellular metabolism is thus vectorial not only across the membrane but also throughout the cytoplasm.

STEM: A Software Tool for Large-Scale Proteomic Data Analyses

We describe the software, STEM (STrategic Extractor for Mascot's results), which efficiently processes large-scale mass spectrometry-based proteomics data. V (View)-mode evaluates the Mascot peptide identification dataset, removes unreliable candidates and redundant assignments, and integrates the results with key information in the experiment. C (Comparison)-mode compares peptide coverage among multiple datasets and displays proteins commonly/specifically found therein, and processes data for quantitative studies that utilize conventional isotope tags or tags having a smaller mass difference. STEM significantly improves throughput of proteomics study.

Cell surface labeling and mass spectrometry reveal diversity of cell surface markers and signaling molecules expressed in undifferentiated mouse embryonic stem cells

Although interactions between cell surface proteins and extracellular ligands are key to initiating embryonic stem cell differentiation to specific cell lineages, the plasma membrane protein components of these cells are largely unknown. We describe here a group of proteins expressed on the surface of the undifferentiated mouse embryonic stem cell line D3. These proteins were identified using a combination of cell surface labeling with biotin, subcellular fractionation of plasma membranes, and mass spectrometry-based protein identification technology. From 965 unique peptides carrying biotin labels, we assigned 324 proteins including 235 proteins that have putative signal sequences and/or transmembrane segments. Receptors, transporters, and cell adhesion molecules were the major classes of proteins identified. Besides known cell surface markers of embryonic stem cells, such as alkaline phosphatase, the analysis identified 59 clusters of differentiation-related molecules and more than 80 components of multiple cell signaling pathways that are characteristic of a number of different cell lineages. We identified receptors for leukemia-inhibitory factor, interleukin 6, and bone morphogenetic protein, which play critical roles in the maintenance of undifferentiated mouse embryonic stem cells. We also identified receptors for growth factors/cytokines, such as fibroblast growth factor, platelet-derived growth factor, ephrin, Hedgehog, and Wnt, which transduce signals for cell differentiation and embryonic development. Finally we identified a variety of integrins, cell adhesion molecules, and matrix metalloproteases. These results suggest that D3 cells express diverse cell surface proteins that function to maintain pluripotency, enabling cells to respond to various external signals that initiate differentiation into a variety of cell types.

Proteome analysis of serovars Typhimurium and Pullorum of Salmonella enterica subspecies I

BACKGROUND

Salmonella enterica subspecies I includes several closely related serovars which differ in host ranges and ability to cause disease. The basis for the diversity in host range and pathogenic potential of the serovars is not well understood, and it is not known how host-restricted variants appeared and what factors were lost or acquired during adaptations to a specific environment. Differences apparent from the genomic data do not necessarily correspond to functional proteins and more importantly differential regulation of otherwise identical gene content may play a role in the diverse phenotypes of the serovars of Salmonella.

RESULTS

In this study a comparative analysis of the cytosolic proteins of serovars Typhimurium and Pullorum was performed using two-dimensional gel electrophoresis and the proteins of interest were identified using mass spectrometry. An annotated reference map was created for serovar Typhimurium containing 233 entries, which included many metabolic enzymes, ribosomal proteins, chaperones and many other proteins characteristic for the growing cell. The comparative analysis of the two serovars revealed a high degree of variation amongst isolates obtained from different sources and, in some cases, the variation was greater between isolates of the same serovar than between isolates with different sero-specificity. However, several serovar-specific proteins, including intermediates in sulphate utilisation and cysteine synthesis, were also found despite the fact that the genes encoding those proteins are present in the genomes of both serovars.

CONCLUSION

Current microbial proteomics are generally based on the use of a single reference or type strain of a species. This study has shown the importance of incorporating a large number of strains of a species, as the diversity of the proteome in the microbial population appears to be significantly greater than expected. The characterisation of a diverse selection of strains revealed parts of the proteome of S. enterica that alter their expression while others remain stable and allowed for the identification of serovar-specific factors that have so far remained undetected by other methods.

The continuing evolution of shotgun proteomics

Shotgun proteomics has emerged as a powerful approach for the analysis of complex protein mixtures, including biofluids, tissues, cells, organelles or protein complexes. Having evolved from the integration of chromatography and mass spectrometry, innovations in sample preparation, multidimensional chromatography, mass spectrometry and proteomic informatics continually facilitate, enable and challenge shotgun proteomics. As a result, shotgun proteomics continues to evolve and enable new areas of biological research, and is beginning to impact human disease diagnosis and therapeutic intervention.

Towards a comprehensive understanding ofBacillus subtiliscell physiology by physiological proteomics

Using Bacillus subtilis as a model system for functional genomics, this review will provide insights how proteomics can be used to bring the virtual life of genes to the real life of proteins. Physiological proteomics will generate a new and broad understanding of cellular physiology because the majority of proteins synthesized in the cell can be visualized. From a physiological point of view two major proteome fractions can be distinguished: proteomes of growing cells and proteomes of nongrowing cells. In the main analytical window almost 50% of the vegetative proteome expressed in growing cells of B. subtilis were identified. This proteomic view of growing cells can be employed for analyzing the regulation of entire metabolic pathways and thus opens the chance for a comprehensive understanding of metabolism and growth processes of bacteria. Proteomics, on the other hand, is also a useful tool for analyzing the adaptational network of nongrowing cells that consists of several partially overlapping regulation groups induced by stress/starvation stimuli. Furthermore, proteomic signatures for environmental stimuli can not only be applied to predict the physiological state of cells, but also offer various industrial applications from fermentation monitoring up to the analysis of the mode of action of drugs. Even if DNA array technologies currently provide a better overview of the gene expression profile than proteome approaches, the latter address biological problems in which they can not be replaced by mRNA profiling procedures. This proteomics of the second generation is a powerful tool for analyzing global control of protein stability, the protein interaction network, protein secretion or post-translational modifications of proteins on the way towards the elucidation of the mystery of life.