Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two <Emphasis Type="Italic">Blattabacterium cuenoti</Emphasis> strains,primary endosymbionts of cockroaches

BACKGROUND: Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. RESULTS: We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. CONCLUSIONS: The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the reconstructed networks from the two bacteria helps to refine the functional analysis of the genomes enabling us to postulate how slightly different host metabolic contexts drove their parallel evolution.     

Evolutionary Convergence and Nitrogen Metabolism in Blattabacterium strain Bge,Primary Endosymbiont of the Cockroach Blattella germanica

Bacterial endosymbionts of insects play a central role in upgrading the diet of their hosts. In certain cases, such as aphids and tsetse flies, endosymbionts complement the metabolic capacity of hosts living on nutrient-deficient diets, while the bacteria harbored by omnivorous carpenter ants are involved in nitrogen recycling. In this study, we describe the genome sequence and inferred metabolism of Blattabacterium strain Bge, the primary Flavobacteria endosymbiont of the omnivorous German cockroach Blattella germanica. Through comparative genomics with other insect endosymbionts and free-living Flavobacteria we reveal that Blattabacterium strain Bge shares the same distribution of functional gene categories only with Blochmannia strains, the primary Gamma-Proteobacteria endosymbiont of carpenter ants. This is a remarkable example of evolutionary convergence during the symbiotic process, involving very distant phylogenetic bacterial taxa within hosts feeding on similar diets. Despite this similarity, different nitrogen economy strategies have emerged in each case. Both bacterial endosymbionts code for urease but display different metabolic functions: Blochmannia strains produce ammonia from dietary urea and then use it as a source of nitrogen, whereas Blattabacterium strain Bge codes for the complete urea cycle that, in combination with urease, produces ammonia as an end product. Not only does the cockroach endosymbiont play an essential role in nutrient supply to the host, but also in the catabolic use of amino acids and nitrogen excretion, as strongly suggested by the stoichiometric analysis of the inferred metabolic network. Here, we explain the metabolic reasons underlying the enigmatic return of cockroaches to the ancestral ammonotelic state.     

Plant growth enhancement is not a conserved feature in the Caulobacter genus

Aims

Species within the Caulobacter genus have been termed ‘hub species’ in the plant microbiome. To understand these interactions, we assessed the interactions between several Caulobacter strains and a common host plant.

Methods

We identified a set of 11 Caulobacter strains that range in genetic diversity and tested them for their ability to increase the growth of Arabidopsis thaliana. In addition, biochemical assays were employed to determine if these Caulobacter strains produce common plant growth promoting (PGP) biosynthates. To identify potential PGP-related genes, genomic analyses were performed to compare the genomes of PGP Caulobacter strains to those of non-PGP Caulobacter strains.

Results

For the PGP Caulobacter strains, we observed that common PGP biosynthates did not contribute to the observed Caulobacter-mediated plant growth stimulation. Genomic analyses suggested that the genomes of PGP strains maintain similar metabolic pathways compared to those of non-PGP strains, and that common genes related to PGP factors do not explain the PGP mechanisms for the Caulobacter strains we analyzed.

Conclusions

Plant growth enhancement is not a conserved feature in the Caulobacter genus, and some Caulobacter strains even inhibit plant growth. Moreover, common PGP factors do not fully explain Caulobacter-mediated plant growth enhancement.

     

Comparison of closely related,uncultivated Coxiella tick endosymbiont population genomes reveals clues about the mechanisms of symbiosis

Understanding the symbiotic interaction between Coxiella‐like endosymbionts (CLE) and their tick hosts is challenging due to lack of isolates and difficulties in tick functional assays. Here we sequenced the metagenome of a CLE population from wild Rhipicephalus sanguineus ticks (CRs) and compared it to the previously published genome of its close relative, CLE of R. turanicus (CRt). The tick hosts are closely related sympatric species, and their two endosymbiont genomes are highly similar with only minor differences in gene content. Both genomes encode numerous pseudogenes, consistent with an ongoing genome reduction process. In silico flux balance metabolic analysis (FBA) revealed the excess production of L‐proline for both genomes, indicating a possible proline transport from Coxiella to the tick. Additionally, both CR genomes encode multiple copies of the proline/betaine transporter, proP gene. Modelling additional Coxiellaceae members including other tick CLE, did not identify proline as an excreted metabolite. Although both CRs and CRt genomes encode intact B vitamin synthesis pathway genes, which are presumed to underlay the mechanism of CLE‐tick symbiosis, the FBA analysis indicated no changes for their products. Therefore, this study provides new testable hypotheses for the symbiosis mechanism and a better understanding of CLE genome evolution and diversity.     

Enhanced Mutation Rate,Relaxed Selection,and the “Domino Effect” are associated with Gene Loss in Blattabacterium,A Cockroach Endosymbiont

Intracellular endosymbionts have reduced genomes that progressively lose genes at a timescale of tens of million years. We previously reported that gene loss rate is linked to mutation rate in Blattabacterium, however, the mechanisms causing gene loss are not yet fully understood. Here, we carried out comparative genomic analyses on the complete genome sequences of a representative set of 67 Blattabacterium strains, with sizes ranging between 511 and 645 kb. We found that 200 of the 566 analyzed protein-coding genes were lost in at least one lineage of Blattabacterium, with the most extreme case being one gene that was lost independently in 24 lineages. We found evidence for three mechanisms influencing gene loss in Blattabacterium. First, gene loss rates were found to increase exponentially with the accumulation of substitutions. Second, genes involved in vitamin and amino acid metabolism experienced relaxed selection in Cryptocercus and Mastotermes, possibly triggered by their vertically inherited gut symbionts. Third, we found evidence of epistatic interactions among genes leading to a “domino effect” of gene loss within pathways. Our results highlight the complexity of the process of genome erosion in an endosymbiont.     

A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011

The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000. It has been updated and periodically released since then based on new and curated genomic and biochemical knowledge. An update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites. iJO1366 was (1) updated in part using a new experimental screen of 1075 gene knockout strains, illuminating cases where alternative pathways and isozymes are yet to be discovered, (2) compared with its predecessor and to experimental data sets to confirm that it continues to make accurate phenotypic predictions of growth on different substrates and for gene knockout strains, and (3) mapped to the genomes of all available sequenced E. coli strains, including pathogens, leading to the identification of hundreds of unannotated genes in these organisms. Like its predecessors, the iJO1366 reconstruction is expected to be widely deployed for studying the systems biology of E. coli and for metabolic engineering applications.     

Improving the accuracy of flux balance analysis through the implementation of carbon availability constraints for intracellular reactions

Constraint-based modeling methods, such as Flux Balance Analysis (FBA), have been extensively used to decipher complex, information rich -omics datasets to elicit system-wide behavioral patterns of cellular metabolism. FBA has been successfully used to gain insight in a wide range of applications, such as range of substrate utilization, product yields and to design metabolic engineering strategies to improve bioprocess performance. A well-known challenge associated with large genome-scale metabolic networks is that they result in underdetermined problem formulations. Consequently, rather than unique solutions, FBA and related methods examine ranges of reaction flux values that are consistent with the studied physiological conditions. The wider the reported flux ranges, the higher the uncertainty in the determination of basic reaction properties, limiting interpretability of and confidence in the results. Herein, we propose a new, computationally efficient approach that refines flux range predictions by constraining reaction fluxes on the basis of the elemental balance of carbon. We compared carbon constraint FBA (ccFBA) against experimentally-measured intracellular fluxes using the latest CHO GEM (iCHO1766) and were able to substantially improve the accuracy of predicted flux values compared with FBA. ccFBA can be used as a stand-alone method but is also compatible with and complimentary to other constraint-based approaches.     

Assessment of bacterial endosymbiont diversity in Otiorhynchusspp. (Coleoptera: Curculionidae) larvae using a multitag 454 pyrosequencing approach

Background

Weevils of the genus Otiorhynchus are regarded as devastating pests in a wide variety of horticultural crops worldwide. So far, little is known on the presence of endosymbionts in Otiorhynchus spp.. Investigation of endosymbiosis in this genus may help to understand the evolution of different reproductive strategies in these weevils (parthenogenesis or sexual reproduction), host-symbiont interactions, and may provide a future basis for novel pest management strategy development. Here, we used a multitag 454 pyrosequencing approach to assess the bacterial endosymbiont diversity in larvae of four economically important Otiorhynchus species.

Results

High-throughput tag-encoded FLX amplicon pyrosequencing of a bacterial 16S rDNA fragment was used to characterise bacterial communities associated with different Otiorhynchus spp. larvae. By sequencing a total of ~48,000 PCR amplicons, we identified 49 different operational taxonomic units (OTUs) as bacterial endosymbionts in the four studied Otiorhynchus species. More than 90% of all sequence reads belonged either to the genus Rickettsia or showed homology to the phylogenetic group of “Candidatus Blochmannia” and to endosymbionts of the lice Pedicinus obtusus and P. badii. By using specific primers for the genera Rickettsia and “Candidatus Blochmannia”, we identified a new phylogenetic clade of Rickettsia as well as “Candidatus Nardonella” endosymbionts in Otiorhynchus spp. which are closely related to “Candidatus Blochmannia” bacteria.

Conclusions

Here, we used multitag 454 pyrosequencing for assessment of insect endosymbiotic communities in weevils. As 454 pyrosequencing generates only quite short sequences, results of such studies can be regarded as a first step towards identifying respective endosymbiotic species in insects. In the second step of our study, we analysed sequences of specific gene regions for a more detailed phylogeny of selected endosymbiont genera. As a result we identified the presence of Rickettsia and “Candidatus Nardonella” endosymbionts in Otiorhynchus spp.. This knowledge is an important step in exploring bacteria-insect associations for potential use in insect pest control.

     

Estimation of the number of extreme pathways for metabolic networks

Background  

The set of extreme pathways (ExPa), {p _i }, defines the convex basis vectors used for the mathematical characterization of the null space of the stoichiometric matrix for biochemical reaction networks. ExPa analysis has been used for a number of studies to determine properties of metabolic networks as well as to obtain insight into their physiological and functional states in silico. However, the number of ExPas, p = |{p _i }|, grows with the size and complexity of the network being studied, and this poses a computational challenge. For this study, we investigated the relationship between the number of extreme pathways and simple network properties.     

Metabolic flux balance analysis and the in silicoanalysis of Escherichia coliK-12 gene deletions

Background

Genome sequencing and bioinformatics are producing detailed lists of the molecular components contained in many prokaryotic organisms. From this 'parts catalogue' of a microbial cell, in silicorepresentations of integrated metabolic functions can be constructed and analyzed using flux balance analysis (FBA). FBA is particularly well-suited to study metabolic networks based on genomic, biochemical, and strain specific information.

Results

Herein, we have utilized FBA to interpret and analyze the metabolic capabilities of Escherichia coli. We have computationally mapped the metabolic capabilities of E. coliusing FBA and examined the optimal utilization of the E. colimetabolic pathways as a function of environmental variables. We have used an in silicoanalysis to identify seven gene products of central metabolism (glycolysis, pentose phosphate pathway, TCA cycle, electron transport system) essential for aerobic growth of E. colion glucose minimal media, and 15 gene products essential for anaerobic growth on glucose minimal media. The in silico tpi ^-, zwf, and pta ^-mutant strains were examined in more detail by mapping the capabilities of these in silicoisogenic strains.

Conclusions

We found that computational models of E. colimetabolism based on physicochemical constraints can be used to interpret mutant behavior. These in silicaresults lead to a further understanding of the complex genotype-phenotype relation. Supplementary information: 10.1186/1471-2105-1-1     

Genome-scale reconstruction of the metabolic network in Staphylococcus aureus N315: an initial draft to the two-dimensional annotation

Background  

Several strains of bacteria have sequenced and annotated genomes, which have been used in conjunction with biochemical and physiological data to reconstruct genome-scale metabolic networks. Such reconstruction amounts to a two-dimensional annotation of the genome. These networks have been analyzed with a constraint-based formalism and a variety of biologically meaningful results have emerged. Staphylococcus aureus is a pathogenic bacterium that has evolved resistance to many antibiotics, representing a significant health care concern. We present the first manually curated elementally and charge balanced genome-scale reconstruction and model of S. aureus' metabolic networks and compute some of its properties.     

Escher-FBA: a web application for interactive flux balance analysis

Background

Flux balance analysis (FBA) is a widely-used method for analyzing metabolic networks. However, most existing tools that implement FBA require downloading software and writing code. Furthermore, FBA generates predictions for metabolic networks with thousands of components, so meaningful changes in FBA solutions can be difficult to identify. These challenges make it difficult for beginners to learn how FBA works.

Results

To meet this need, we present Escher-FBA, a web application for interactive FBA simulations within a pathway visualization. Escher-FBA allows users to set flux bounds, knock out reactions, change objective functions, upload metabolic models, and generate high-quality figures without downloading software or writing code. We provide detailed instructions on how to use Escher-FBA to replicate several FBA simulations that generate real scientific hypotheses.

Conclusions

We designed Escher-FBA to be as intuitive as possible so that users can quickly and easily understand the core concepts of FBA. The web application can be accessed at https://sbrg.github.io/escher-fba.

     

Microbial community of predatory bugs of the genus Macrolophus(Hemiptera: Miridae)

Background

The predatory mirids of the genus Macrolophus are key natural enemies of various economically important agricultural pests. Both M. caliginosus and M. pygmaeus are commercially available for the augmentative biological control of arthropod pests in European greenhouses. The latter species is known to be infected with Wolbachia -inducing cytoplasmic incompatibility in its host- but the presence of other endosymbionts has not been demonstrated. In the present study, the microbial diversity was examined in various populations of M. caliginosus and M. pygmaeus by 16S rRNA sequencing and denaturing gradient gel electrophoresis.

Results

Besides Wolbachia, a co-infection of 2 Rickettsia species was detected in all M. pygmaeus populations. Based on a concatenated alignment of the 16S rRNA gene, the gltA gene and the coxA gene, the first is phylogenetically related to Rickettsia bellii, whereas the other is closely related to Rickettsia limoniae. All M. caliginosus populations were infected with the same Wolbachia and limoniae-like Rickettsia strain as M. pygmaeus, but did not harbour the bellii-like Rickettsia strain. Interestingly, individuals with a single infection were not found. A PCR assay on the ovaries of M. pygmaeus and M. caliginosus indicated that all endosymbionts are vertically transmitted. The presence of Wolbachia and Rickettsia in oocytes was confirmed by a fluorescence in situ hybridisation. A bio-assay comparing an infected and an uninfected M. pygmaeus population suggested that the endosymbionts had minor effects on nymphal development of their insect host and did not influence its fecundity.

Conclusion

Two species of the palaearctic mirid genus Macrolophus are infected with multiple endosymbionts, including Wolbachia and Rickettsia. Independent of the origin, all tested populations of both M. pygmaeus and M. caliginosus were infected with three and two endosymbionts, respectively. There was no indication that infection with endosymbiotic bacteria had a fitness cost in terms of development and fecundity of the predators.

     

Using Topology of the Metabolic Network to Predict Viability of Mutant Strains

Background  

Understanding the relationships between the structure (topology) and function of biological networks is a central question of systems biology. The idea that topology is a major determinant of systems function has become an attractive and highly-disputed hypothesis. While the structural analysis of interaction networks demonstrates a correlation between the topological properties of a node (protein, gene) in the network and its functional essentiality, the analysis of metabolic networks fails to find such correlations. In contrast, approaches utilizing both the topology and biochemical parameters of metabolic networks, e.g. flux balance analysis (FBA), are more successful in predicting phenotypes of knock-out strains.     

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and ¹³C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.     

How will bioinformatics influence metabolic engineering?

Ten microbial genomes have been fully sequenced to date, and the sequencing of many more genomes is expected to be completed before the end of the century. The assignment of function to open reading frames (ORFs) is progressing, and for some genomes over 70% of functional assignments have been made. The majority of the assigned ORFs relate to metabolic functions. Thus, the complete genetic and biochemical functions of a number of microbial cells may be soon available. From a metabolic engineering standpoint, these developments open a new realm of possibilities. Metabolic analysis and engineering strategies can now be built on a sound genomic basis. An important question that now arises; how should these tasks be approached? Flux-balance analysis (FBA) has the potential to play an important role. It is based on the fundamental principle of mass conservation. It requires only the stoichiometric matrix, the metabolic demands, and some strain specific parameters. Importantly, no enzymatic kinetic data is required. In this article, we show how the genomically defined microbial metabolic genotypes can be analyzed by FBA. Fundamental concepts of metabolic genotype, metabolic phenotype, metabolic redundancy and robustness are defined and examples of their use given. We discuss the advantage of this approach, and how FBA is expected to find uses in the near future. FBA is likely to become an important analysis tool for genomically based approaches to metabolic engineering, strain design, and development.     

Generation,analysis and functional annotation of expressed sequence tags from the sheepshead minnow (Cyprinodon variegatus)

Background

Genomic islands (GIs) are clusters of alien genes in some bacterial genomes, but not be seen in the genomes of other strains within the same genus. The detection of GIs is extremely important to the medical and environmental communities. Despite the discovery of the GI associated features, accurate detection of GIs is still far from satisfactory.

Results

In this paper, we combined multiple GI-associated features, and applied and compared various machine learning approaches to evaluate the classification accuracy of GIs datasets on three genera: Salmonella, Staphylococcus, Streptococcus, and their mixed dataset of all three genera. The experimental results have shown that, in general, the decision tree approach outperformed better than other machine learning methods according to five performance evaluation metrics. Using J48 decision trees as base classifiers, we further applied four ensemble algorithms, including adaBoost, bagging, multiboost and random forest, on the same datasets. We found that, overall, these ensemble classifiers could improve classification accuracy.

Conclusions

We conclude that decision trees based ensemble algorithms could accurately classify GIs and non-GIs, and recommend the use of these methods for the future GI data analysis. The software package for detecting GIs can be accessed at http://www.esu.edu/cpsc/che_lab/software/GIDetector/.

     

Development and experimental verification of a genome-scale metabolic model for Corynebacterium glutamicum

Background  

In silico genome-scale metabolic models enable the analysis of the characteristics of metabolic systems of organisms. In this study, we reconstructed a genome-scale metabolic model of Corynebacterium glutamicum on the basis of genome sequence annotation and physiological data. The metabolic characteristics were analyzed using flux balance analysis (FBA), and the results of FBA were validated using data from culture experiments performed at different oxygen uptake rates.     

Intradialytic neuromuscular electrical stimulation reduces DNA damage in chronic kidney failure patients: a randomized controlled trial

Background: Chronic kidney failure (CKF) patients on renal replacement therapies exhibit elevated levels of DNA lesions and this is directly related to high mortality.

Objective: This study aimed to evaluate the effect of neuromuscular electrical stimulation (NMES) on genomic damage in CKF patients on conventional haemodialysis (HD).

Methods: Twenty-one patients with CKF on HD were randomized into control (CG =10) or neuromuscular electrical stimulation (NMESG?=?11) groups. NMES was applied on the quadriceps muscle during the HD session, three times a week, for 8 weeks in NMESG. DNA damage in blood was evaluated by the alkaline comet assay prior to follow-up, after 4 and 8 weeks of intervention.

Results: Intradialytic NMES in CKF patients induced a significant decrease in DNA damage after four [49.9 (3.68) vs 101.5 (6.53); p?=?0.000] than eight [19.9 (2.07) vs 101.5 (6.53); p?=?0.000] weeks compared to baseline. Genomic damage was also significantly less after four [NMESG: 49.9 (3.68) vs CG: 92.9 (12.61); p?=?0.001] than after eight [NMESG: 19.9 (2.07) vs CG: 76.4 (11.15); p?=?0.000] weeks compared to CG.

Conclusions: This study demonstrates for the first time that intradialytic NMES is able to reduce DNA damage in blood of CKF patients.