Impact of genome reduction on bacterial metabolism and its regulation

What mechanisms/processes underlie radiation-induced genomic instability?

Radiation-induced genomic instability is a modification of the cell genome found in the progeny of irradiated somatic and germ cells but that is not confined on the initial radiation-induced damage and may occur de novo many generations after irradiation. Genomic instability in the germ line does not follow Mendelian segregation and may have unpredictable outcomes in every succeeding generation. This phenomenon, for which there is extensive experimental data and some evidence in human populations exposed to ionising radiation, is not taken into account in health risk assessments. It poses an unknown morbidity/mortality burden. Based on experimental data derived over the last 20 years (up to January 2012) six mechanistic explanations for the phenomenon have been proposed in the peer-reviewed literature. This article compares these hypotheses with the empirical data to test their fitness to explain the phenomenon. As a conclusion, the most convincing explanation of radiation-induced genomic instability attributes it to an irreversible regulatory change in the dynamic interaction network of the cellular gene products, as a response to non-specific molecular damage, thus entailing the rejection of the machine metaphor for the cell in favour of one appropriate to a complex dissipative dynamic system, such as a whirlpool. It is concluded that in order to evaluate the likely morbidity/mortality associated with radiation-induced genomic instability, it will be necessary to study the damage to processes by radiation rather than damage to molecules.

Mycoplasma haemocanis--the canine hemoplasma and its feline counterpart in the genomic era

Mycoplasma haemocanis is a hemotrophic mycoplasma (hemoplasma), blood pathogen that may cause acute disease in immunosuppressed or splenectomized dogs. The genome of the strain Illinois, isolated from blood of a naturally infected dog, has been entirely sequenced and annotated to gain a better understanding of the biology of M. haemocanis. Its single circular chromosome has 919 992 bp and a low G + C content (35%), representing a typical mycoplasmal genome. A gene-by-gene comparison against its feline counterpart, M. haemofelis, reveals a very similar composition and architecture with most of the genes having conserved synteny extending over their entire chromosomes and differing only by a small set of unique protein coding sequences. As in M. haemofelis, M. haemocanis metabolic pathways are reduced and apparently rely heavily on the nutrients afforded by its host environment. The presence of a major percentage of its genome dedicated to paralogous genes (63.7%) suggests that this bacterium might use antigenic variation as a mechanism to evade the host’s immune system as also observed in M. haemofelis genome. Phylogenomic comparisons based on average nucleotide identity (ANI) and tetranucleotide signature suggest that these two pathogens are different species of mycoplasmas, with M. haemocanis infecting dogs and M. haemofelis infecting cats.

Exploration of the core metabolism of symbiotic bacteria

Background

A large number of genome-scale metabolic networks is now available for many organisms, mostly bacteria. Previous works on minimal gene sets, when analysing host-dependent bacteria, found small common sets of metabolic genes. When such analyses are restricted to bacteria with similar lifestyles, larger portions of metabolism are expected to be shared and their composition is worth investigating. Here we report a comparative analysis of the small molecule metabolism of symbiotic bacteria, exploring common and variable portions as well as the contribution of different lifestyle groups to the reduction of a common set of metabolic capabilities.

Results

We found no reaction shared by all the bacteria analysed. Disregarding those with the smallest genomes, we still do not find a reaction core, however we did find a core of biochemical capabilities. While obligate intracellular symbionts have no core of reactions within their group, extracellular and cell-associated symbionts do have a small core composed of disconnected fragments. In agreement with previous findings in Escherichia coli, their cores are enriched in biosynthetic processes whereas the variable metabolisms have similar ratios of biosynthetic and degradation reactions. Conversely, the variable metabolism of obligate intracellular symbionts is enriched in anabolism.

Conclusion

Even when removing the symbionts with the most reduced genomes, there is no core of reactions common to the analysed symbiotic bacteria. The main reason is the very high specialisation of obligate intracellular symbionts, however, host-dependence alone is not an explanation for such absence. The composition of the metabolism of cell-associated and extracellular bacteria shows that while they have similar needs in terms of the building blocks of their cells, they have to adapt to very distinct environments. On the other hand, in obligate intracellular bacteria, catabolism has largely disappeared, whereas synthetic routes appear to have been selected for depending on the nature of the symbiosis. As more genomes are added, we expect, based on our simulations, that the core of cell-associated and extracellular bacteria continues to diminish, converging to approximately 60 reactions.

Predicting effects of structural stress in a genome-reduced model bacterial metabolism

Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

Construction of a genome-scale kinetic model of mycobacterium tuberculosis using generic rate equations

The study of biological systems at the genome scale helps us understand fundamental biological processes that govern the activity of living organisms and regulate their interactions with the environment. Genome-scale metabolic models are usually analysed using constraint-based methods, since detailed rate equations and kinetic parameters are often missing. However, constraint-based analysis is limited in capturing the dynamics of cellular processes. In this paper, we present an approach to build a genome-scale kinetic model of Mycobacterium tuberculosis metabolism using generic rate equations. M. tuberculosis causes tuberculosis which remains one of the largest killer infectious diseases. Using a genetic algorithm, we estimated kinetic parameters for a genome-scale metabolic model of M. tuberculosis based on flux distributions derived from Flux Balance Analysis. Our results show that an excellent agreement with flux values is obtained under several growth conditions, although kinetic parameters may vary in different conditions. Parameter variability analysis indicates that a high degree of redundancy remains present in model parameters, which suggests that the integration of other types of high-throughput datasets will enable the development of better constrained models accounting for a variety of in vivo phenotypes.

A comprehensive proteome of Mycoplasma genitalium

Mycoplasma genitalium is a human pathogen associated with several sexually transmitted diseases. Proteomic technologies, along with other methods for global gene expression analysis, play a key role in understanding the mechanisms of bacterial pathogenesis and physiology. The proteome of M. genitalium, model of a minimal cell, has been extended using a combination of different proteomic approaches and technologies. The total proteome of this microorganism has been analyzed using gel-based and gel-free approaches, achieving the identification of 85.3% of the predicted ORFs. In addition, a comprehensive analysis of membrane subproteome has been performed. For this purpose, the TX-114 soluble fraction has been analyzed as well as the surface proteins, using cell-surface protein labeling with CyDye. Finally, the serological response of M. genitalium-infected patients and healthy donors has been analyzed to identify proteins that trigger immunological response. Here, we present the most extensive M. genitalium proteome analysis (85.3% of predicted ORFs), a comprehensive M. genitalium membrane analysis, and a study of the human serological response to M. genitalium.

Transcription start site associated RNAs in bacteria

A new class of small RNA (~45 bases long) is identified in gram positive and negative bacteria. These tssRNAs are associated with RNA polymerase pausing some 45 bases downstream of the transcription start site and show global changes in expression during the growth cycle.

A new class of bacterial small RNAs have been identified. They are related to eukaryotic tiRNAs in their localization (transcription start sites, TSS) but not in their biogenesis.

tssRNAs are generated at the same positions as long transcripts, as well as at independent positions, but both seem to have promoter-like characteristics (Pribnow box).

We provide compelling evidence that tssRNAs are not mRNA degradation products and neither abortive transcripts; rather, they are newly synthesized transcripts and require more factors than the basal transcription machinery (i.e., RNA polymerase subunits)

tssRNAs show dynamic behavior dependent on the growth phase.

We show that RNA polymerase is halted at tssRNAs positions, both in bona fide genes and in positions where no long transcript is produced. This indicates that tssRNAs could be generated by RNA polymerase pausing to ensure that no spurious long RNA is generated by random appearance of Pribnow sequences in the genome.

Here, we report the genome-wide identification of small RNAs associated with transcription start sites (TSSs), termed tssRNAs, in Mycoplasma pneumoniae. tssRNAs were also found to be present in a different bacterial phyla, Escherichia coli. Similar to the recently identified promoter-associated tiny RNAs (tiRNAs) in eukaryotes, tssRNAs are associated with active promoters. Evidence suggests that these tssRNAs are distinct from previously described abortive transcription RNAs. ssRNAs have an average size of 45 bases and map exactly to the beginning of cognate full-length transcripts and to cryptic TSSs. Expression of bacterial tssRNAs requires factors other than the standard RNA polymerase holoenzyme. We have found that the RNA polymerase is halted at tssRNA positions in vivo, which may indicate that a pausing mechanism exists to prevent transcription in the absence of genes. These results suggest that small RNAs associated with TSSs could be a universal feature of bacterial transcription.

Structure-based functional inference of hypothetical proteins from Mycoplasma hyopneumoniae

Enzootic pneumonia caused by Mycoplasma hyopneumoniae is a major constraint to efficient pork production throughout the world. This pathogen has a small genome with 716 coding sequences, of which 418 are homologous to proteins with known functions. However, almost 42% of the 716 coding sequences are annotated as hypothetical proteins. Alternative methodologies such as threading and comparative modeling can be used to predict structures and functions of such hypothetical proteins. Often, these alternative methods can answer questions about the properties of a model system faster than experiments. In this study, we predicted the structures of seven proteins annotated as hypothetical in M. hyopneumoniae, using the structure-based approaches mentioned above. Three proteins were predicted to be involved in metabolic processes, two proteins in transcription and two proteins where no function could be assigned. However, the modeled structures of the last two proteins suggested experimental designs to identify their functions. Our findings are important in diminishing the gap between the lack of annotation of important metabolic pathways and the great number of hypothetical proteins in the M. hyopneumoniae genome.

Proteomics characterization of cytoplasmic and lipid-associated membrane proteins of human pathogen Mycoplasma fermentans M64

Mycoplasma fermentans is a potent human pathogen which has been implicated in several diseases. Notably, its lipid-associated membrane proteins (LAMPs) play a role in immunomodulation and development of infection-associated inflammatory diseases. However, the systematic protein identification of pathogenic M. fermentans has not been reported. From our recent sequencing results of M. fermentans M64 isolated from human respiratory tract, its genome is around 1.1 Mb and encodes 1050 predicted protein-coding genes. In the present study, soluble proteome of M. fermentans was resolved and analyzed using two-dimensional gel electrophoresis. In addition, Triton X-114 extraction was carried out to enrich amphiphilic proteins including putative lipoproteins and membrane proteins. Subsequent mass spectrometric analyses of these proteins had identified a total of 181 M. fermentans ORFs. Further bioinformatics analysis of these ORFs encoding proteins with known or so far unknown orthologues among bacteria revealed that a total of 131 proteins are homologous to known proteins, 11 proteins are conserved hypothetical proteins, and the remaining 39 proteins are likely M. fermentans-specific proteins. Moreover, Triton X-114-enriched fraction was shown to activate NF-kB activity of raw264.7 macrophage and a total of 21 lipoproteins with predicted signal peptide were identified therefrom. Together, our work provides the first proteome reference map of M. fermentans as well as several putative virulence-associated proteins as diagnostic markers or vaccine candidates for further functional study of this human pathogen.

Superessential reactions in metabolic networks

The metabolic genotype of an organism can change through loss and acquisition of enzyme-coding genes, while preserving its ability to survive and synthesize biomass in specific environments. This evolutionary plasticity allows pathogens to evolve resistance to antimetabolic drugs by acquiring new metabolic pathways that bypass an enzyme blocked by a drug. We here study quantitatively the extent to which individual metabolic reactions and enzymes can be bypassed. To this end, we use a recently developed computational approach to create large metabolic network ensembles that can synthesize all biomass components in a given environment but contain an otherwise random set of known biochemical reactions. Using this approach, we identify a small connected core of 124 reactions that are absolutely superessential (that is, required in all metabolic networks). Many of these reactions have been experimentally confirmed as essential in different organisms. We also report a superessentiality index for thousands of reactions. This index indicates how easily a reaction can be bypassed. We find that it correlates with the number of sequenced genomes that encode an enzyme for the reaction. Superessentiality can help choose an enzyme as a potential drug target, especially because the index is not highly sensitive to the chemical environment that a pathogen requires. Our work also shows how analyses of large network ensembles can help understand the evolution of complex and robust metabolic networks.

Mycoplasma polysaccharide protects against complement

Although they lack a cell wall, mycoplasmas do possess a glycocalyx. The interactions between the glycocalyx, mycoplasmal surface proteins and host complement were explored using the murine pathogen Mycoplasma pulmonis as a model. It was previously shown that the length of the tandem repeat region of the surface lipoprotein Vsa is associated with susceptibility to complement-mediated killing. Cells producing a long Vsa containing about 40 repeats are resistant to complement, whereas strains that produce a short Vsa of five or fewer repeats are susceptible. We show here that the length of the Vsa protein modulates the affinity of the M. pulmonis EPS-I polysaccharide for the mycoplasma cell surface, with more EPS-I being associated with mycoplasmas producing a short Vsa protein. An examination of mutants that lack EPS-I revealed that planktonic mycoplasmas were highly susceptible to complement killing even when the Vsa protein was long, demonstrating that both EPS-I and Vsa length contribute to resistance. In contrast, the mycoplasmas were resistant to complement even in the absence of EPS-I when the cells were encased in a biofilm.

The minimal genome: a metabolic and environmental comparison

The field of Synthetic Biology seeks to apply engineering principles to biology in order to produce novel biological systems. One approach to accomplish this goal is the genome-driven cell engineering approach, which searches for functioning minimal genomes in naturally occurring microorganisms, which can then be used as a template for future systems. Currently a prototypical minimal genome has not been discovered. This review analyzes the organisms Mycoplasma pneumoniae, Pelagibacter ubique, Vesicomyosocius okutanii and Prochlorococcus marinus as models of heterotrophic symbiont, heterotrophic free-living, autotrophic symbiont and autotrophic free-living organisms respectively and compares them to the current minimal cell model in order to determine which most closely resembles a true minimal genome. M. pneumoniae possesses a genome of 816 394 base pairs (bp) with 688 open reading frames (ORF) and a severely limited metabolism. Pelagibacter ubique possesses a 1 308 000 bp genome with 1354 ORF and has a fully functional metabolism but requires a reduced form of sulphur. Vesicomyosocius okutanii possesses a 1 020 000 bp genome with 975 ORF and is deficient in the production of threonine, isoleucine and ubiquinone. Prochlorococcus marinus possesses a 1 751 080 bp genome with 1884 ORF and has a complete metabolism with no deficiencies. The current minimal cell model requires a genome to be of limited size, culturalble and having minimal media requirements as such it is the conclusion of this review that P. marinus best fits this model. Further, future research should concentrate on genome reduction experiments using P. marinus and the search for additional minimal genomes should concentrate on autotrophic free-living organisms.

Complexity of the Mycoplasma fermentans M64 genome and metabolic essentiality and diversity among mycoplasmas

Recently, the genomes of two Mycoplasma fermentans strains, namely M64 and JER, have been completely sequenced. Gross comparison indicated that the genome of M64 is significantly bigger than the other strain and the difference is mainly contributed by the repetitive sequences including seven families of simple and complex transposable elements ranging from 973 to 23,778 bps. Analysis of these repeats resulted in the identification of a new distinct family of Integrative Conjugal Elements of M. fermentans, designated as ICEF-III. Using the concept of “reaction connectivity”, the metabolic capabilities in M. fermentans manifested by the complete and partial connected biomodules were revealed. A comparison of the reported M. pulmonis, M. arthritidis, M. genitalium, B. subtilis, and E. coli essential genes and the genes predicted from the M64 genome indicated that more than 73% of the Mycoplasmas essential genes are preserved in M. fermentans. Further examination of the highly and partly connected reactions by a novel combinatorial phylogenetic tree, metabolic network, and essential gene analysis indicated that some of the pathways (e.g. purine and pyrimidine metabolisms) with partial connected reactions may be important for the conversions of intermediate metabolites. Taken together, in light of systems and network analyses, the diversity among the Mycoplasma species was manifested on the variations of their limited metabolic abilities during evolution.

Global network reorganization during dynamic adaptations of Bacillus subtilis metabolism

Adaptation of cells to environmental changes requires dynamic interactions between metabolic and regulatory networks, but studies typically address only one or a few layers of regulation. For nutritional shifts between two preferred carbon sources of Bacillus subtilis, we combined statistical and model-based data analyses of dynamic transcript, protein, and metabolite abundances and promoter activities. Adaptation to malate was rapid and primarily controlled posttranscriptionally compared with the slow, mainly transcriptionally controlled adaptation to glucose that entailed nearly half of the known transcription regulation network. Interactions across multiple levels of regulation were involved in adaptive changes that could also be achieved by controlling single genes. Our analysis suggests that global trade-offs and evolutionary constraints provide incentives to favor complex control programs.

Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium

The effect of kinase, phosphatase and N-acetyltransferase deletions on proteome phosphorylation and acetylation was investigated in Mycoplasma pneumoniae. Bi-directional cross-talk between post-transcriptional modifications suggests an underlying regulatory molecular code in prokaryotes.

Post-translational modifications (PTMs) change the chemical properties of proteins, conferring diversity beyond the amino-acid sequence. Proteins are often modified on multiple sites. A PTM code has been proposed, whereby modifications at specific positions influence further modifications. These regulatory circuits though have rarely been studied on a large-scale; conservation in prokaryotes remains elusive.

Here, we studied two important PTMs– phosphorylation and lysine acetylation in the small bacterium Mycoplasma pneumoniae. We combined genetics and quantitative mass spectrometry to measure the effect of systematic kinase, phosphatase and N-acetyltransferase deletions on proteome abundance, phosphorylation and lysine acetylation.

The data set represents a comprehensive analysis of both phosphorylation and lysine acetylation in a single prokaryote. It reveals (1) proteins often carry multiple modifications and multiple types of PTMs, reminiscent of the PTM code proposed in eukaryotes, (2) phosphorylation exerts pleiotropic effect on proteins abundances, phosphorylation, but also lysine acetylation, (3) the cross-talk between the two PTMs is bi-directional and (4) PTMs are frequently located at interaction interfaces and in multifunctional proteins, illustrating how PTMs could modulate protein functions affecting the way they interact.

The study provides an unbiased and quantitative view on cross-talk between phosphorylation and lysine acetylation. It suggests that these regulatory circuits are a fundamental principle of regulation that might have evolved before the divergence of prokaryotes and eukaryotes.

Protein post-translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post-transcriptional regulatory mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae. Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein-specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N-acetyltransferases affects protein phosphorylation, confirming cross-talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co-occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post-transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell.

The genome of th17 cell-inducing segmented filamentous bacteria reveals extensive auxotrophy and adaptations to the intestinal environment

Perturbations of the composition of the symbiotic intestinal microbiota can have profound consequences for host metabolism and immunity. In mice, segmented filamentous bacteria (SFB) direct the accumulation of potentially proinflammatory Th17 cells in the intestinal lamina propria. We present the genome sequence of SFB isolated from monocolonized mice, which classifies SFB phylogenetically as a unique member of Clostridiales with a highly reduced genome. Annotation analysis demonstrates that SFB depend on their environment for amino acids and essential nutrients and may utilize host and dietary glycans for carbon, nitrogen, and energy. Comparative analyses reveal that SFB are functionally related to members of the genus Clostridium and several pathogenic or commensal "minimal" genera, including Finegoldia, Mycoplasma, Borrelia, and Phytoplasma. However, SFB are functionally distinct from all 1200 examined genomes, indicating a gene complement representing biology relatively unique to their role as a gut commensal closely tied to host metabolism and immunity.

Insights into the gene expression profile of uncultivable hemotrophic Mycoplasma suis during acute infection, obtained using proteome analysis

Hemotrophic mycoplasmas, bacteria without cell walls whose niche is the erythrocytes of their hosts, have never been cultivated in vitro. Therefore, knowledge of their pathogenesis is fundamental. Mycoplasma suis infects pigs, causing either acute fatal hemolytic anemia or chronic low-grade anemia, growth retardation, and immune suppression. Recently, the complete genomes of two hemotrophic mycoplasma species, M. suis and M. haemofelis, were sequenced, offering new strategies for the analysis of their pathogenesis. In this study we implemented a proteomic approach to identify M. suis proteins during acute infection by using tandem mass spectrometry. Twenty-two percent of the predicted proteins encoded in M. suis strain KI_3806 were identified. These included nearly all encoded proteins of glycolysis and nucleotide metabolism. The proteins for lipid metabolism, however, were underrepresented. A high proportion of the detected proteins are involved in information storage and processing (72.6%). In addition, several proteins of different functionalities, i.e., posttranslational modification, membrane genesis, signal transduction, intracellular trafficking, inorganic ion transport, and defense mechanisms, were identified. In its reduced genome, M. suis harbors 65.3% (strain Illinois) and 65.9% (strain KI_3806) of the genes encode hypothetical proteins. Of these, only 6.3% were identified at the proteome level. All proteins identified in this study are present in both M. suis strains and are encoded in more highly conserved regions of the genome sequence. In conclusion, our proteome approach is a further step toward the elucidation of the pathogenesis and life cycle of M. suis as well as the establishment of an in vitro cultivation system.

LeishCyc: a guide to building a metabolic pathway database and visualization of metabolomic data

The complexity of the metabolic networks in even the simplest organisms has raised new challenges in organizing metabolic information. To address this, specialized computer frameworks have been developed to capture, manage, and visualize metabolic knowledge. The leading databases of metabolic information are those organized under the umbrella of the BioCyc project, which consists of the reference database MetaCyc, and a number of pathway/genome databases (PGDBs) each focussed on a specific organism. A number of PGDBs have been developed for bacterial, fungal, and protozoan pathogens, greatly facilitating dissection of the metabolic potential of these organisms and the identification of new drug targets. Leishmania are protozoan parasites belonging to the family Trypanosomatidae that cause a broad spectrum of diseases in humans. In this work we use the LeishCyc database, the BioCyc database for Leishmania major, to describe how to build a BioCyc database from genomic sequences and associated annotations. By using metabolomic data generated in our group, we show how such databases can be utilized to elucidate specific changes in parasite metabolism.

Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling

This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

Characterization of NrnA homologs from Mycobacterium tuberculosis and Mycoplasma pneumoniae

Processive RNases are unable to degrade efficiently very short oligonucleotides, and they are complemented by specific enzymes, nanoRNases, that assist in this process. We previously identified NrnA (YtqI) from Bacillus subtilis as a bifunctional protein with the ability to degrade nanoRNA (RNA oligos ≤5 nucleotides) and to dephosphorylate 3'-phosphoadenosine 5'-phosphate (pAp) to AMP. While the former activity is analogous to that of oligoribonuclease (Orn) from Escherichia coli, the latter corresponds to CysQ. NrnA homologs are widely present in bacterial and archaeal genomes. They are found preferably in genomes that lack Orn or CysQ homologs. Here, we characterize NrnA homologs from important human pathogens, Mpn140 from Mycoplasma pneumoniae, and Rv2837c from Mycobacterium tuberculosis. Like NrnA, these enzymes degrade nanoRNA and dephosphorylate pAp in vitro. However, they show dissimilar preferences for specific nanoRNA substrate lengths. Whereas NrnA prefers RNA 3-mers with a 10-fold higher specific activity compared to 5-mers, Rv2837c shows a preference for nanoRNA of a different length, namely, 2-mers. Mpn140 degrades Cy5-labeled nanoRNA substrates in vitro with activities varying within one order of magnitude as follows: 5-mer>4-mer>3-mer>2-mer. In agreement with these in vitro activities, both Rv2837c and Mpn140 can complement the lack of their functional counterparts in E. coli: CysQ and Orn. The NrnA homolog from Streptococcus mutans, SMU.1297, was previously shown to hydrolyze pAp and to complement an E. coli cysQ mutant. Here, we show that SMU.1297 can complement an E. coli orn(-) mutant, suggesting that having both pAp-phosphatase and nanoRNase activity is a common feature of NrnA homologs.

Metabolic networks and their evolution

Since the last decade of the twentieth century, systems biology has gained the ability to study the structure and function of genome-scale metabolic networks. These are systems of hundreds to thousands of chemical reactions that sustain life. Most of these reactions are catalyzed by enzymes which are encoded by genes. A metabolic network extracts chemical elements and energy from the environment, and converts them into forms that the organism can use. The function of a whole metabolic network constrains evolutionary changes in its parts. I will discuss here three classes of such changes, and how they are constrained by the function of the whole. These are the accumulation of amino acid changes in enzyme-coding genes, duplication of enzyme-coding genes, and changes in the regulation of enzymes. Conversely, evolutionary change in network parts can alter the function of the whole network. I will discuss here two such changes, namely the elimination of reactions from a metabolic network through loss of function mutations in enzyme-coding genes, and the addition of metabolic reactions, for example through mechanisms such as horizontal gene transfer. Reaction addition also provides a window into the evolution of metabolic innovations, the ability of a metabolism to sustain life on new sources of energy and of chemical elements.

Mycoplasma pneumoniae and respiratory virus infections in children with persistent cough in England: a retrospective analysis

BACKGROUND

Persistent cough following an acute respiratory tract infection is common in children, but clinicians may find it difficult to give accurate prognostic information on likely duration of cough without a microbiologic diagnosis. This study estimates the prevalence of Mycoplasma pneumoniae (Mp) and assesses the prognostic value of detecting Mp and respiratory viruses in children with persistent cough.

METHODS

We retrospectively analyzed blood samples, nasopharyngeal aspirates (NPAs), and cough duration data from 179 children with persistent cough lasting 14 days or longer. Of these children, 37% had serologically confirmed Bordetella pertussis (pertussis). We detected Mp by polymerase chain reaction of NPAs and IgM serology, and respiratory viruses (human rhinoviruses, influenza viruses, respiratory syncytial viruses, and human metapneumovirus) by polymerase chain reaction of NPAs. We used Kaplan-Meier analyses to calculate median cough durations with 95% confidence intervals (CIs).

RESULTS

We detected Mp in 22 of 170 children with sufficient blood and/or NPAs (12.9%, 95% CI: 8.7-18.8). Cough duration in children with positive Mp serology (median: 39 days, 95% CI: 24-54) was significantly shorter than in children with positive pertussis serology (median: 118 days, 95% CI: 82-154, P < 0.001). The presence of respiratory viruses did not significantly lengthen cough duration in children with pertussis (median: 154 days, 95% CI: 74-234, P = 0.810). Only 3 children had both Mp and respiratory virus infections.

CONCLUSIONS

Mp is an important infection in children with persistent cough and is associated with a significantly shorter duration of cough than pertussis. However, detecting respiratory viruses does not add prognostic value in children with pertussis.

A trigger enzyme in Mycoplasma pneumoniae: impact of the glycerophosphodiesterase GlpQ on virulence and gene expression

Mycoplasma pneumoniae is a causative agent of atypical pneumonia. The formation of hydrogen peroxide, a product of glycerol metabolism, is essential for host cell cytotoxicity. Phosphatidylcholine is the major carbon source available on lung epithelia, and its utilization requires the cleavage of deacylated phospholipids to glycerol-3-phosphate and choline. M. pneumoniae possesses two potential glycerophosphodiesterases, MPN420 (GlpQ) and MPN566. In this work, the function of these proteins was analyzed by biochemical, genetic, and physiological studies. The results indicate that only GlpQ is an active glycerophosphodiesterase. MPN566 has no enzymatic activity as glycerophosphodiesterase and the inactivation of the gene did not result in any detectable phenotype. Inactivation of the glpQ gene resulted in reduced growth in medium with glucose as the carbon source, in loss of hydrogen peroxide production when phosphatidylcholine was present, and in a complete loss of cytotoxicity towards HeLa cells. All these phenotypes were reverted upon complementation of the mutant. Moreover, the glpQ mutant strain exhibited a reduced gliding velocity. A comparison of the proteomes of the wild type strain and the glpQ mutant revealed that this enzyme is also implicated in the control of gene expression. Several proteins were present in higher or lower amounts in the mutant. This apparent regulation by GlpQ is exerted at the level of transcription as determined by mRNA slot blot analyses. All genes subject to GlpQ-dependent control have a conserved potential cis-acting element upstream of the coding region. This element overlaps the promoter in the case of the genes that are repressed in a GlpQ-dependent manner and it is located upstream of the promoter for GlpQ-activated genes. We may suggest that GlpQ acts as a trigger enzyme that measures the availability of its product glycerol-3-phosphate and uses this information to differentially control gene expression.

Mycoplasma pneumoniae serves as a model organism for bacteria with very small genomes that are nonetheless independently viable. These bacteria infect the human lung and cause an atypical pneumonia. The major virulence determinant of M. pneumoniae is hydrogen peroxide that is generated during the utilization of glycerol-3-phosphate, which might be derived from free glycerol or from the degradation of phospholipids. Indeed, lecithin is the by far most abundant carbon source on lung epithelia. In this study, we made use of the recent availability of methods to isolate mutants of M. pneumoniae and characterized the enzyme that generates glycerol-3-phosphate from deacylated lecithin (glycerophosphocholine). This enzyme, called GlpQ, is essential for the formation of hydrogen peroxide when the bacteria are incubated with glycerophosphocholine. Moreover, M. pneumoniae is unable to cause any detectable damage to the host cells in the absence of GlpQ. This underlines the important role of phospholipid metabolism for the virulence of M. pneumoniae. We observed that GlpQ in addition to its enzymatic activity is also involved in the control of expression of several genes, among them the glycerol transporter. Thus, GlpQ is central to the normal physiology and to pathogenicity of the minimal pathogen M. pneumoniae.

Genome of Mycoplasma haemofelis, unraveling its strategies for survival and persistence

Mycoplasma haemofelis is a mycoplasmal pathogen (hemoplasma) that attaches to the host's erythrocytes. Distributed worldwide, it has a significant impact on the health of cats causing acute disease and, despite treatment, establishing chronic infection. It might also have a role as a zoonotic agent, especially in immunocompromised patients. Whole genome sequencing and analyses of M. haemofelis strain Ohio2 was undertaken as a step toward understanding its survival and persistence. Metabolic pathways are reduced, relying on the host to supply many of the nutrients and metabolites needed for survival. M. haemofelis must import glucose for ATP generation and ribose derivates for RNA/DNA synthesis. Hypoxanthine, adenine, guanine, uracil and CMP are scavenged from the environment to support purine and pyrimidine synthesis. In addition, nicotinamide, amino acids and any vitamins needed for growth, must be acquired from its environment. The core proteome of M. haemofelis contains an abundance of paralogous gene families, corresponding to 70.6% of all the CDSs. This "paralog pool" is a rich source of different antigenic epitopes that can be varied to elude the host's immune system and establish chronic infection. M. haemofelis also appears to be capable of phase variation, which is particularly relevant to the cyclic bacteremia and persistence, characteristics of the infection in the cat. The data generated herein should be of great use for understanding the mechanisms of M. haemofelis infection. Further, it will provide new insights into its pathogenicity and clues needed to formulate media to support the in vitro cultivation of M. haemofelis.

The molecular origins of evolutionary innovations

The history of life is a history of evolutionary innovations, qualitatively new phenotypic traits that endow their bearers with new, often game-changing abilities. We know many individual examples of innovations and their natural history, but we know little about the fundamental principles of phenotypic variability that permit new phenotypes to arise. Most phenotypic innovations result from changes in three classes of systems: metabolic networks, regulatory circuits, and macromolecules. I here highlight two important features that these classes of systems share. The first is the ubiquity of vast genotype networks - connected sets of genotypes with the same phenotype. The second is the great phenotypic diversity of small neighborhoods around different genotypes in genotype space. I here explain that both features are essential for the phenotypic variability that can bring forth qualitatively new phenotypes. Both features emerge from a common cause, the robustness of phenotypes to perturbations, whose origins are linked to life in changing environments.

A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants

Background

The numerous diverse metabolic pathways by which plant compounds can be produced make it difficult to predict how colour pigmentation is lost for different tissues and plants. This study employs mathematical and in silico methods to identify correlated gene targets for the loss of colour pigmentation in plants from a whole cell perspective based on the full metabolic network of Arabidopsis. This involves extracting a self-contained flavonoid subnetwork from the AraCyc database and calculating feasible metabolic routes or elementary modes (EMs) for it. Those EMs leading to anthocyanin compounds are taken to constitute the anthocyanin biosynthetic pathway (ABP) and their interplay with the rest of the EMs is used to study the minimal cut sets (MCSs), which are different combinations of reactions to block for eliminating colour pigmentation. By relating the reactions to their corresponding genes, the MCSs are used to explore the phenotypic roles of the ABP genes, their relevance to the ABP and the impact their eliminations would have on other processes in the cell.

Results

Simulation and prediction results of the effect of different MCSs for eliminating colour pigmentation correspond with existing experimental observations. Two examples are: i) two MCSs which require the simultaneous suppression of genes DFR and ANS to eliminate colour pigmentation, correspond to observational results of the same genes being co-regulated for eliminating floral pigmentation in Aquilegia and; ii) the impact of another MCS requiring CHS suppression, corresponds to findings where the suppression of the early gene CHS eliminated nearly all flavonoids but did not affect the production of volatile benzenoids responsible for floral scent.

Conclusions

From the various MCSs identified for eliminating colour pigmentation, several correlate to existing experimental observations, indicating that different MCSs are suitable for different plants, different cells, and different conditions and could also be related to regulatory genes. Being able to correlate the predictions with experimental results gives credence to the use of these mathematical and in silico analyses methods in the design of experiments. The methods could be used to prioritize target enzymes for different objectives to achieve desired outcomes, especially for less understood pathways.

Expression and characterization of a Mycoplasma genitalium glycosyltransferase in membrane glycolipid biosynthesis: potential target against mycoplasma infections

Mycoplasmas contain glycoglycerolipids in their plasma membrane as key structural components involved in bilayer properties and stability. A membrane-associated glycosyltransferase (GT), GT MG517, has been identified in Mycoplasma genitalium, which sequentially produces monoglycosyl- and diglycosyldiacylglycerols. When recombinantly expressed in Escherichia coli, the enzyme was functional in vivo and yielded membrane glycolipids from which Glcβ1,6GlcβDAG was identified as the main product. A chaperone co-expression system and extraction with CHAPS detergent afforded soluble protein that was purified by affinity chromatography. GT MG517 transfers glucosyl and galactosyl residues from UDP-Glc and UDP-Gal to dioleoylglycerol (DOG) acceptor to form the corresponding β-glycosyl-DOG, which then acts as acceptor to give β-diglycosyl-DOG products. The enzyme (GT2 family) follows Michaelis-Menten kinetics. k(cat) is about 5-fold higher for UDP-Gal with either DOG or monoglucosyldioleoylglycerol acceptors, but it shows better binding for UDP-Glc than UDP-Gal, as reflected by the lower K(m), which results in similar k(cat)/K(m) values for both donors. Although sequentially adding glycosyl residues with β-1,6 connectivity, the first glycosyltransferase activity (to DOG) is about 1 order of magnitude higher than the second (to monoglucosyldioleoylglycerol). Because the ratio between the non-bilayer-forming monoglycosyldiacylglycerols and the bilayer-prone diglycosyldiacylglycerols contributes to regulate the properties of the plasma membrane, both synthase activities are probably regulated. Dioleoylphosphatidylglycerol (anionic phospholipid) activates the enzyme, k(cat) linearly increasing with dioleoylphosphatidylglycerol concentration. GT MG517 is shown to be encoded by an essential gene, and the addition of GT inhibitors results in cell growth inhibition. It is proposed that glycolipid synthases are potential targets for drug discovery against infections by mycoplasmas.

Proteins with complex architecture as potential targets for drug design: a case study of Mycobacterium tuberculosis

Lengthy co-evolution of Homo sapiens and Mycobacterium tuberculosis, the main causative agent of tuberculosis, resulted in a dramatically successful pathogen species that presents considerable challenge for modern medicine. The continuous and ever increasing appearance of multi-drug resistant mycobacteria necessitates the identification of novel drug targets and drugs with new mechanisms of action. However, further insights are needed to establish automated protocols for target selection based on the available complete genome sequences. In the present study, we perform complete proteome level comparisons between M. tuberculosis, mycobacteria, other prokaryotes and available eukaryotes based on protein domains, local sequence similarities and protein disorder. We show that the enrichment of certain domains in the genome can indicate an important function specific to M. tuberculosis. We identified two families, termed pkn and PE/PPE that stand out in this respect. The common property of these two protein families is a complex domain organization that combines species-specific regions, commonly occurring domains and disordered segments. Besides highlighting promising novel drug target candidates in M. tuberculosis, the presented analysis can also be viewed as a general protocol to identify proteins involved in species-specific functions in a given organism. We conclude that target selection protocols should be extended to include proteins with complex domain architectures instead of focusing on sequentially unique and essential proteins only.

Quantification of mRNA and protein and integration with protein turnover in a bacterium

Determination of the average cellular copy number of 400 proteins under different growth conditions and integration with protein turnover and absolute mRNA levels reveals the dynamics of protein expression in the genome-reduced bacterium Mycoplasma pneumoniae.

Our study provides a fine-grained, quantitative picture to unprecedented detail in an established model organism for systems-wide studies.

Our integrative approach reveals a novel, dynamic view on the processes, interactions and regulations underlying the central dogma pathway and the composition of protein complexes.

Simulations using our quantitative data on mRNA, protein and turnover show how an organism copes with stochastic noise in gene expression in vivo.

Our data serve as an important resource for colleagues both within our field of research and in related disciplines.

A hallmark of Systems Biology is the integration of diverse, large quantitative data sets with the aim to gain novel insights into how biological processes work. We measured individual mRNA and protein abundances as well as protein turnover in the bacterium Mycoplasma pneumoniae. This human pathogen is an ideal model organism for organism-wide studies. It can be readily cultured under laboratory conditions and it has a very small genome with only 690 protein-coding genes. This comparably low complexity allows for the exhaustive analysis of major cellular biomolecules avoiding constrains introduced by limitations of available analysis techniques.

Using a recently developed mass spectrometry-based approach, we determined the average cellular copy number for over 400 individual proteins under different growth and stress conditions. The 20 most abundant proteins, including Elongation factor Tu, cellular chaperones, and proteins involved in metabolizing glucose, the major energy source of M. pneumoniae account for nearly 44% of the total cellular protein mass. We observed abundance changes of many expected and several unexpected proteins in response to cellular stress, such as heat shock, DNA damage and osmotic stress, as well as along batch culture growth over 4 days.

Integration of the protein abundance data with quantitative mRNA measurements revealed a modest correlation between these two classes of biomolecules. However, for several classical stress-induced proteins, we observed a correlated induction of mRNA and protein in response to heat shock. A focused analysis of mRNA–protein abundance dynamics during batch culture growth suggested that the regulation of gene expression is largely decoupled from protein dynamics in M. pneumoniae, indicating extensive post-transcriptional and post-translational regulation influencing the cellular mRNA–protein ratios.

To investigate the factors influencing the cellular protein abundance, we measured individual protein turnover rates by mass spectrometry using a label-chase approach involving stable isotope-labelled amino acids. The average half-life of a protein in M. pneumoniae is 23 h. Based on the measured quantitative mRNA data, the protein abundances and their half-lives, we established an ordinary differential equations model for the estimation of individual in vivo protein degradation and translation efficiency rates. We found out that translation efficiency rather than protein turnover is the dominating factor influencing protein abundance. Using our abundance and turnover data, we additionally performed stochastic simulations of gene expression. We observed that long protein half-life and low translational efficiency buffers gene expression noise propagating from low cellular mRNA levels in vivo.

We compared the abundance ratios of proteins associating into complexes in vivo with their expected functional stoichiometries. We observed that for stable protein complexes, such as the GroEL/ES chaperonin or DNA gyrase, our measured abundance ratios reflected the expected subunit stoichiometries. More dynamic protein complexes, such as the DnaK/J/GrpE chaperone system or RNA polymerase, showed several unusual subunit ratios, pointing towards transient interaction of sub-stoichiometric subunits for function. A detailed, quantitative analysis of the ribosome, the largest cellular protein complex, revealed large abundance differences of the 51 subunits. This observation indicates a multi-functionality for several, abundant ribosomal proteins.

Finally, a comparison of the determined average cellular protein abundances with a different pathogenic bacterium, Leptospira interrogans, revealed that cellular protein abundances closely reflect their respective lifestyles.

Our study represents an organism-wide, quantitative analysis of cellular protein abundances. Integrating our proteomics data with determined mRNA levels and protein turnover rates reveals insights into the dynamic interplay and regulation of mRNA and proteins, the central biomolecules of a cell.

Biological function and cellular responses to environmental perturbations are regulated by a complex interplay of DNA, RNA, proteins and metabolites inside cells. To understand these central processes in living systems at the molecular level, we integrated experimentally determined abundance data for mRNA, proteins, as well as individual protein half-lives from the genome-reduced bacterium Mycoplasma pneumoniae. We provide a fine-grained, quantitative analysis of basic intracellular processes under various external conditions. Proteome composition changes in response to cellular perturbations reveal specific stress response strategies. The regulation of gene expression is largely decoupled from protein dynamics and translation efficiency has a higher regulatory impact on protein abundance than protein turnover. Stochastic simulations using in vivo data show how low translation efficiency and long protein half-lives effectively reduce biological noise in gene expression. Protein abundances are regulated in functional units, such as complexes or pathways, and reflect cellular lifestyles. Our study provides a detailed integrative analysis of average cellular protein abundances and the dynamic interplay of mRNA and proteins, the central biomolecules of a cell.

The ten grand challenges of synthetic life

The construction of artificial life is one of the main scientific challenges of the Synthetic Biology era. Advances in DNA synthesis and a better understanding of regulatory processes make the goal of constructing the first artificial cell a realistic possibility. This would be both a fundamental scientific milestone and a starting point of a vast range of applications, from biofuel production to drug design. However, several major issues might hamper the objective of achieving an artificial cell. From the bottom-up to the selection-based strategies, this work encompasses the ten grand challenges synthetic biologists will have to be aware of in order to cope with the task of creating life in the lab.

Network-based scoring system for genome-scale metabolic reconstructions

Background

Network reconstructions at the cell level are a major development in Systems Biology. However, we are far from fully exploiting its potentialities. Often, the incremental complexity of the pursued systems overrides experimental capabilities, or increasingly sophisticated protocols are underutilized to merely refine confidence levels of already established interactions. For metabolic networks, the currently employed confidence scoring system rates reactions discretely according to nested categories of experimental evidence or model-based likelihood.

Results

Here, we propose a complementary network-based scoring system that exploits the statistical regularities of a metabolic network as a bipartite graph. As an illustration, we apply it to the metabolism of Escherichia coli. The model is adjusted to the observations to derive connection probabilities between individual metabolite-reaction pairs and, after validation, to assess the reliability of each reaction in probabilistic terms. This network-based scoring system uncovers very specific reactions that could be functionally or evolutionary important, identifies prominent experimental targets, and enables further confirmation of modeling results.

Conclusions

We foresee a wide range of potential applications at different sub-cellular or supra-cellular levels of biological interactions given the natural bipartivity of many biological networks.

Complete genome sequence of Mycoplasma suis and insights into its biology and adaption to an erythrocyte niche

Mycoplasma suis, the causative agent of porcine infectious anemia, has never been cultured in vitro and mechanisms by which it causes disease are poorly understood. Thus, the objective herein was to use whole genome sequencing and analysis of M. suis to define pathogenicity mechanisms and biochemical pathways. M. suis was harvested from the blood of an experimentally infected pig. Following DNA extraction and construction of a paired end library, whole-genome sequencing was performed using GS-FLX (454) and Titanium chemistry. Reads on paired-end constructs were assembled using GS De Novo Assembler and gaps closed by primer walking; assembly was validated by PFGE. Glimmer and Manatee Annotation Engine were used to predict and annotate protein-coding sequences (CDS). The M. suis genome consists of a single, 742,431 bp chromosome with low G+C content of 31.1%. A total of 844 CDS, 3 single copies, unlinked rRNA genes and 32 tRNAs were identified. Gene homologies and GC skew graph show that M. suis has a typical Mollicutes oriC. The predicted metabolic pathway is concise, showing evidence of adaptation to blood environment. M. suis is a glycolytic species, obtaining energy through sugars fermentation and ATP-synthase. The pentose-phosphate pathway, metabolism of cofactors and vitamins, pyruvate dehydrogenase and NAD⁺ kinase are missing. Thus, ribose, NADH, NADPH and coenzyme A are possibly essential for its growth. M. suis can generate purines from hypoxanthine, which is secreted by RBCs, and cytidine nucleotides from uracil. Toxins orthologs were not identified. We suggest that M. suis may cause disease by scavenging and competing for host' nutrients, leading to decreased life-span of RBCs. In summary, genome analysis shows that M. suis is dependent on host cell metabolism and this characteristic is likely to be linked to its pathogenicity. The prediction of essential nutrients will aid the development of in vitro cultivation systems.

Evolutionary microbial genomics: insights into bacterial host adaptation

Host-adapted bacteria include mutualists and pathogens of animals, plants and insects. Their study is therefore important for biotechnology, biodiversity and human health. The recent rapid expansion in bacterial genome data has provided insights into the adaptive, diversifying and reductive evolutionary processes that occur during host adaptation. The results have challenged many pre-existing concepts built from studies of laboratory bacterial strains. Furthermore, recent studies have revealed genetic changes associated with transitions from parasitism to mutualism and opened new research avenues to understand the functional reshaping of bacteria as they adapt to growth in the cytoplasm of a eukaryotic host.

Exploring the spatial and temporal organization of a cell's proteome

To increase our current understanding of cellular processes, such as cell signaling and division, knowledge is needed about the spatial and temporal organization of the proteome at different organizational levels. These levels cover a wide range of length and time scales: from the atomic structures of macromolecules for inferring their molecular function, to the quantitative description of their abundance, and spatial distribution in the cell. Emerging new experimental technologies are greatly increasing the availability of such spatial information on the molecular organization in living cells. This review addresses three fields that have significantly contributed to our understanding of the proteome's spatial and temporal organization: first, methods for the structure determination of individual macromolecular assemblies, specifically the fitting of atomic structures into density maps generated from electron microscopy techniques; second, research that visualizes the spatial distributions of these complexes within the cellular context using cryo electron tomography techniques combined with computational image processing; and third, methods for the spatial modeling of the dynamic organization of the proteome, specifically those methods for simulating reaction and diffusion of proteins and complexes in crowded intracellular fluids. The long-term goal is to integrate the varied data about a proteome's organization into a spatially explicit, predictive model of cellular processes.

Metabolomics of Mycobacterium tuberculosis reveals compartmentalized co-catabolism of carbon substrates

Metabolic adaptation to the host environment is a defining feature of the pathogenicity of Mycobacterium tuberculosis (Mtb), but we lack biochemical knowledge of its metabolic networks. Many bacteria use catabolite repression as a regulatory mechanism to maximize growth by consuming individual carbon substrates in a preferred sequence and growing with diauxic kinetics. Surprisingly, untargeted metabolite profiling of Mtb growing on ¹³C-labeled carbon substrates revealed that Mtb could catabolize multiple carbon sources simultaneously to achieve enhanced monophasic growth. Moreover, when co-catabolizing multiple carbon sources, Mtb differentially catabolized each carbon source through the glycolytic, pentose phosphate, and/or tricarboxylic acid pathways to distinct metabolic fates. This unusual topologic organization of bacterial intermediary metabolism has not been previously observed and may subserve the pathogenicity of Mtb.