Characterization of growth and metabolism of the haloalkaliphile Natronomonas pharaonis

The effective deficiency of biochemical networks

The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a measure of its ability to support exotic dynamical behavior and/or multistationarity. The classical definition of deficiency relates to the capacity of a network to permit variations of the complex formation rate vector at steady state, irrespective of the network kinetics. However, the deficiency is by definition completely insensitive to the fine details of the directionality of reactions as well as bounds on reaction fluxes. While the classical definition of deficiency can be readily applied in the analysis of unconstrained, weakly reversible networks, it only provides an upper bound in the cases where relevant constraints on reaction fluxes are imposed. Here we propose the concept of effective deficiency, which provides a more accurate assessment of the network's capacity to permit steady state variations at the complex level for constrained networks of any reversibility patterns. The effective deficiency relies on the concept of nonstoichiometric balanced complexes, which we have already shown to be present in real-world biochemical networks operating under flux constraints. Our results demonstrate that the effective deficiency of real-world biochemical networks is smaller than the classical deficiency, indicating the effects of reaction directionality and flux bounds on the variation of the complex formation rate vector at steady state.

Diversity and Potential Multifunctionality of Archaeal CetZ Tubulin-like Cytoskeletal Proteins

Tubulin superfamily (TSF) proteins are widespread, and are known for their multifaceted roles as cytoskeletal proteins underpinning many basic cellular functions, including morphogenesis, division, and motility. In eukaryotes, tubulin assembles into microtubules, a major component of the dynamic cytoskeletal network of fibres, whereas the bacterial homolog FtsZ assembles the division ring at midcell. The functions of the lesser-known archaeal TSF proteins are beginning to be identified and show surprising diversity, including homologs of tubulin and FtsZ as well as a third archaea-specific family, CetZ, implicated in the regulation of cell shape and possibly other unknown functions. In this study, we define sequence and structural characteristics of the CetZ family and CetZ1 and CetZ2 subfamilies, identify CetZ groups and diversity amongst archaea, and identify potential functional relationships through analysis of the genomic neighbourhoods of cetZ genes. We identified at least three subfamilies of orthologous CetZ proteins in the archaeal class Halobacteria, including CetZ1 and CetZ2 as well as a novel uncharacterized subfamily. CetZ1 and CetZ2 were correlated to one another as well as to cell shape and motility phenotypes across diverse Halobacteria. Among other known CetZ clusters in orders Archaeoglobales, Methanomicrobiales, Methanosarcinales, and Thermococcales, an additional uncharacterized group from Archaeoglobales and Methanomicrobiales is affiliated strongly with Halobacteria CetZs, suggesting that they originated via horizontal transfer. Subgroups of Halobacteria CetZ2 and Thermococcales CetZ genes were found adjacent to different type IV pili regulons, suggesting potential utilization of CetZs by type IV systems. More broadly conserved cetZ gene neighbourhoods include nucleotide and cofactor biosynthesis (e.g., F₄₂₀) and predicted cell surface sugar epimerase genes. These findings imply that CetZ subfamilies are involved in multiple functions linked to the cell surface, biosynthesis, and motility.

The hidden simplicity of metabolic networks is revealed by multireaction dependencies

Understanding the complexity of metabolic networks has implications for manipulation of their functions. The complexity of metabolic networks can be characterized by identifying multireaction dependencies that are challenging to determine due to the sheer number of combinations to consider. Here, we propose the concept of concordant complexes that captures multireaction dependencies and can be efficiently determined from the algebraic structure and operational constraints of metabolic networks. The concordant complexes imply the existence of concordance modules based on which the apparent complexity of 12 metabolic networks of organisms from all kingdoms of life can be reduced by at least 78%. A comparative analysis against an ensemble of randomized metabolic networks shows that the metabolic network of Escherichia coli contains fewer concordance modules and is, therefore, more tightly coordinated than expected by chance. Together, our findings demonstrate that metabolic networks are considerably simpler than what can be perceived from their structure alone.

Comprehensive Genome Analysis of Halolamina pelagica CDK2: Insights into Abiotic Stress Tolerance Genes

Halophilic archaeon Halolamina pelagica CDK2, showcasing plant growth-promoting properties and endurance towards harsh environmental conditions (high salinity, heavy metals, high temperature and UV radiation) was sequenced earlier. Pan-genome of Halolamina genus was created and investigated for strain-specific genes of CDK2, which might confer it with features helping it to withstand high abiotic stress. Pathways and subsystems in CDK2 were compared with other Halolamina strain CGHMS and analysed using KEGG and RAST. A genome-scale metabolic model was reconstructed from the genome of H. pelagica CDK2. Results implicated strain-specific genes like thermostable carboxypeptidase and DNA repair protein MutS which might protect the proteins and DNA from high temperature and UV denaturation respectively. A bifunctional trehalose synthase gene responsible for trehalose biosynthesis was also annotated specifying the need for low salt compatible solute strategy, the probable reason behind the ability of this haloarchaea to survive in a wide range of salt concentrations. A modified shikimate and mevalonate pathways were also identified in CDK2, along with many ABC transporters for metal uptakes like zinc and cobalt through pathway analysis. Probable employment of one multifunctional ABC transporter in place of two for similar metals (Nickel/cobalt and molybdenum/tungsten) might be employed as a strategy for energy conservation. The findings of the present study could be utilized for future research relating metabolic model for flux balance analysis and the genetic repertoire imparting resistance to harsh conditions can be transferred to crops for improving their tolerance to abiotic stresses.

A structural property for reduction of biochemical networks

Large-scale biochemical models are of increasing sizes due to the consideration of interacting organisms and tissues. Model reduction approaches that preserve the flux phenotypes can simplify the analysis and predictions of steady-state metabolic phenotypes. However, existing approaches either restrict functionality of reduced models or do not lead to significant decreases in the number of modelled metabolites. Here, we introduce an approach for model reduction based on the structural property of balancing of complexes that preserves the steady-state fluxes supported by the network and can be efficiently determined at genome scale. Using two large-scale mass-action kinetic models of Escherichia coli, we show that our approach results in a substantial reduction of 99% of metabolites. Applications to genome-scale metabolic models across kingdoms of life result in up to 55% and 85% reduction in the number of metabolites when arbitrary and mass-action kinetics is assumed, respectively. We also show that predictions of the specific growth rate from the reduced models match those based on the original models. Since steady-state flux phenotypes from the original model are preserved in the reduced, the approach paves the way for analysing other metabolic phenotypes in large-scale biochemical networks.

Bacterial-like nitric oxide synthase in the haloalkaliphilic archaeon Natronomonas pharaonis

Bacterial nitric oxide (NO) synthases (bNOS) play diverse and important roles in microbial physiology, stress resistance, and virulence. Although bacterial and mammalian NOS enzymes have been well-characterized, comparatively little is known about the prevalence and function of NOS enzymes in Archaea. Analysis of archaeal genomes revealed that highly conserved bNOS homologs were restricted to members of the Halobacteria. Of these, Natronomonas pharaonis NOS (npNOS) was chosen for further characterization. NO production was confirmed in heterologously expressed His-tagged npNOS by coupling nitrite production from N-hydroxy-L-arginine in an H2O2-supported reaction. Additionally, the nos gene was successfully targeted and disrupted to create a Nmn. pharaonis nos mutant by adapting an established Natrialba magadii transformation protocol. Genome re-sequencing of this mutant revealed an additional frameshift in a putative cation-acetate symporter gene, which could contribute to altered acetate metabolism in the nos mutant. Inactivation of Nmn. pharaonis nos was also associated with several phenotypes congruent with bacterial nos mutants (altered growth, increased oxygen consumption, increased pigment, increased UV susceptibility), suggesting that NOS function may be conserved between bacteria and archaea. These studies are the first to describe genetic inactivation and characterization of a Nmn. pharaonis gene and provides enhanced tools for probing its physiology.

Microorganisms and Their Metabolic Capabilities in the Context of the Biogeochemical Nitrogen Cycle at Extreme Environments

Extreme microorganisms (extremophile) are organisms that inhabit environments characterized by inhospitable parameters for most live beings (extreme temperatures and pH values, high or low ionic strength, pressure, or scarcity of nutrients). To grow optimally under these conditions, extremophiles have evolved molecular adaptations affecting their physiology, metabolism, cell signaling, etc. Due to their peculiarities in terms of physiology and metabolism, they have become good models for (i) understanding the limits of life on Earth, (ii) exploring the possible existence of extraterrestrial life (Astrobiology), or (iii) to look for potential applications in biotechnology. Recent research has revealed that extremophilic microbes play key roles in all biogeochemical cycles on Earth. Nitrogen cycle (N-cycle) is one of the most important biogeochemical cycles in nature; thanks to it, nitrogen is converted into multiple chemical forms, which circulate among atmospheric, terrestrial and aquatic ecosystems. This review summarizes recent knowledge on the role of extreme microorganisms in the N-cycle in extremophilic ecosystems, with special emphasis on members of the Archaea domain. Potential implications of these microbes in global warming and nitrogen balance, as well as their biotechnological applications are also discussed.

A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber

A genome-scale metabolic network reconstruction of Salinibacter ruber DSM13855 is presented here. To our knowledge, this is the first metabolic model of an organism in the phylum Rhodothermaeota. This model, which will be called iMB631, was reconstructed based on genomic and biochemical data available on the strain Salinibacter ruber DSM13855. This network consists of 1459 reactions, 1363 metabolites and 631 genes. Model evaluation was performed based on existing biochemical data in the literature and also by performing laboratory experiments. For growth on different carbon sources, we show that iMB631 is able to correctly predict the growth in 91% of cases where growth has been observed experimentally and 83% of conditions in which S. ruber did not grow. The F-score was 93%, demonstrating a generally acceptable performance of the model. Based on the predicted flux distributions, we found that under certain autotrophic condition, a reductive tricarboxylic acid cycle (rTCA) has fluxes in all necessary reactions to support autotrophic growth. To include special metabolites of the bacterium, salinixanthin biosynthesis pathway was modeled based on the pathway proposed recently. For years, main glucose consumption pathway has been under debates in S. ruber. Using flux balance analysis, iMB631 predicts pentose phosphate pathway, rather than glycolysis, as the active glucose consumption method in the S. ruber.

Genome-scale metabolic model analysis indicates low energy production efficiency in marine ammonia-oxidizing archaea

Marine ammonia-oxidizing archaea (AOA) play an important role in the global nitrogen cycle by obtaining energy for biomass production from CO₂ via oxidation of ammonium. The isolation of Candidatus “Nitrosopumilus maritimus” strain SCM1, which represents the globally distributed AOA in the ocean, provided an opportunity for uncovering the contributions of those AOA to carbon and nitrogen cycles in ocean. Although several ammonia oxidation pathways have been proposed for SCM1, little is known about its ATP production efficiency. Here, based on the published genome of Nitrosopumilus maritimus SCM1, a genome-scale metabolic model named NmrFL413 was reconstructed. Based on the model NmrFL413, the estimated ATP/NH₄⁺ yield (0.149–0.276 ATP/NH₄⁺) is tenfold lower than the calculated theoretical yield of the proposed ammonia oxidation pathways in marine AOA (1.5–1.75 ATP/NH₄⁺), indicating a low energy production efficiency of SCM1. Our model also suggested the minor contribution of marine AOA to carbon cycle comparing with their significant contribution to nitrogen cycle in the ocean.

Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria.

Control of fluxes in metabolic networks

Understanding the control of large-scale metabolic networks is central to biology and medicine. However, existing approaches either require specifying a cellular objective or can only be used for small networks. We introduce new coupling types describing the relations between reaction activities, and develop an efficient computational framework, which does not require any cellular objective for systematic studies of large-scale metabolism. We identify the driver reactions facilitating control of 23 metabolic networks from all kingdoms of life. We find that unicellular organisms require a smaller degree of control than multicellular organisms. Driver reactions are under complex cellular regulation in Escherichia coli, indicating their preeminent role in facilitating cellular control. In human cancer cells, driver reactions play pivotal roles in malignancy and represent potential therapeutic targets. The developed framework helps us gain insights into regulatory principles of diseases and facilitates design of engineering strategies at the interface of gene regulation, signaling, and metabolism.

A manual curation strategy to improve genome annotation: application to a set of haloarchael genomes

Genome annotation errors are a persistent problem that impede research in the biosciences. A manual curation effort is described that attempts to produce high-quality genome annotations for a set of haloarchaeal genomes (Halobacterium salinarum and Hbt. hubeiense, Haloferax volcanii and Hfx. mediterranei, Natronomonas pharaonis and Nmn. moolapensis, Haloquadratum walsbyi strains HBSQ001 and C23, Natrialba magadii, Haloarcula marismortui and Har. hispanica, and Halohasta litchfieldiae). Genomes are checked for missing genes, start codon misassignments, and disrupted genes. Assignments of a specific function are preferably based on experimentally characterized homologs (Gold Standard Proteins). To avoid overannotation, which is a major source of database errors, we restrict annotation to only general function assignments when support for a specific substrate assignment is insufficient. This strategy results in annotations that are resistant to the plethora of errors that compromise public databases. Annotation consistency is rigorously validated for ortholog pairs from the genomes surveyed. The annotation is regularly crosschecked against the UniProt database to further improve annotations and increase the level of standardization. Enhanced genome annotations are submitted to public databases (EMBL/GenBank, UniProt), to the benefit of the scientific community. The enhanced annotations are also publically available via HaloLex.

Simple topological properties predict functional misannotations in a metabolic network

Motivation: Misannotation in sequence databases is an important obstacle for automated tools for gene function annotation, which rely extensively on comparison with sequences with known function. To improve current annotations and prevent future propagation of errors, sequence-independent tools are, therefore, needed to assist in the identification of misannotated gene products. In the case of enzymatic functions, each functional assignment implies the existence of a reaction within the organism’s metabolic network; a first approximation to a genome-scale metabolic model can be obtained directly from an automated genome annotation. Any obvious problems in the network, such as dead end or disconnected reactions, can, therefore, be strong indications of misannotation.

Results: We demonstrate that a machine-learning approach using only network topological features can successfully predict the validity of enzyme annotations. The predictions are tested at three different levels. A random forest using topological features of the metabolic network and trained on curated sets of correct and incorrect enzyme assignments was found to have an accuracy of up to 86% in 5-fold cross-validation experiments. Further cross-validation against unseen enzyme superfamilies indicates that this classifier can successfully extrapolate beyond the classes of enzyme present in the training data. The random forest model was applied to several automated genome annotations, achieving an accuracy of in most cases when validated against recent genome-scale metabolic models. We also observe that when applied to draft metabolic networks for multiple species, a clear negative correlation is observed between predicted annotation quality and phylogenetic distance to the major model organism for biochemistry (Escherichia coli for prokaryotes and Homo sapiens for eukaryotes).

Contact:j.pinney@imperial.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

The complete genome sequence of Natrinema sp. J7-2, a haloarchaeon capable of growth on synthetic media without amino acid supplements

Natrinema sp. J7-2 is an extreme haloarchaeon capable of growing on synthetic media without amino acid supplements. Here we report the complete genome sequence of Natrinema sp. J7-2 which is composed of a 3,697,626-bp chromosome and a 95,989-bp plasmid pJ7-I. This is the first complete genome sequence of a member of the genus Natrinema. We demonstrate that Natrinema sp. J7-2 can use gluconate, glycerol, or acetate as the sole carbon source and that its genome encodes complete metabolic pathways for assimilating these substrates. The biosynthetic pathways for all 20 amino acids have been reconstructed, and we discuss a possible evolutionary relationship between the haloarchaeal arginine synthetic pathway and the bacterial lysine synthetic pathway. The genome harbors the genes for assimilation of ammonium and nitrite, but not nitrate, and has a denitrification pathway to reduce nitrite to N₂O. Comparative genomic analysis suggests that most sequenced haloarchaea employ the TrkAH system, rather than the Kdp system, to actively uptake potassium. The genomic analysis also reveals that one of the three CRISPR loci in the Natrinema sp. J7-2 chromosome is located in an integrative genetic element and is probably propagated via horizontal gene transfer (HGT). Finally, our phylogenetic analysis of haloarchaeal genomes provides clues about evolutionary relationships of haloarchaea.

Condition-dependent cell volume and concentration of Escherichia coli to facilitate data conversion for systems biology modeling

Systems biology modeling typically requires quantitative experimental data such as intracellular concentrations or copy numbers per cell. In order to convert population-averaging omics measurement data to intracellular concentrations or cellular copy numbers, the total cell volume and number of cells in a sample need to be known. Unfortunately, even for the often studied model bacterium Escherichia coli this information is hardly available and furthermore, certain measures (e.g. cell volume) are also dependent on the growth condition. In this work, we have determined these basic data for E. coli cells when grown in 22 different conditions so that respective data conversions can be done correctly. First, we determine growth-rate dependent cell volumes. Second, we show that in a 1 ml E. coli sample at an optical density (600 nm) of 1 the total cell volume is around 3.6 µl for all conditions tested. Third, we demonstrate that the cell number in a sample can be determined on the basis of the sample's optical density and the cells' growth rate. The data presented will allow for conversion of E. coli measurement data normalized to optical density into volumetric cellular concentrations and copy numbers per cell--two important parameters for systems biology model development.

Whole-genome metabolic network reconstruction and constraint-based modeling

With the advent of modern high-throughput genomics, there is a significant need for genome-scale analysis techniques that can assist in complex systems analysis. Metabolic genome-scale network reconstructions (GENREs) paired with constraint-based modeling are an efficient method to integrate genomics, transcriptomics, and proteomics to conduct organism-specific analysis. This text explains key steps in the GENRE construction process and several methods of constraint-based modeling that can help elucidate basic life processes and development of disease treatment, bioenergy solutions, and industrial bioproduction applications.