Genotype networks,innovation, and robustness in sulfur metabolism

Background  

A metabolism is a complex network of chemical reactions. This network synthesizes multiple small precursor molecules of biomass from chemicals that occur in the environment. The metabolic network of any one organism is encoded by a metabolic genotype, defined as the set of enzyme-coding genes whose products catalyze the network's reactions. Each metabolic genotype has a metabolic phenotype. We define this metabolic phenotype as the spectrum of different sources of a chemical element that a metabolism can use to synthesize biomass. We here focus on the element sulfur. We study properties of the space of all possible metabolic genotypes in sulfur metabolism by analyzing random metabolic genotypes that are viable on different numbers of sulfur sources.     

Products, requirements and efficiency of biosynthesis: a quantitative approach

The question of how many grams of an organism can grow heterotrophically from only 1·0 g of glucose and adequate minerals has been put forward many times. Only a few attempts have been made to answer this question theoretically and these attempts were rather rough. In this paper, it is demonstrated that the yield of a growth process may be accurately computed by considering the relevant biochemistry of conversion reactions and the cytological implications of biosynthesis and growth. Oxygen consumption and carbon dioxide production by these processes are also computed. The weight of the biomass synthesized from 1·0 g of substrate and the quantities of gases exchanged are independent of temperature.These results are obtained by adding the individual equations describing the formation of each compound synthesized by the organism from the substrate supplied. The sum represents an equation which accounts for all substrate molecules required for biosynthesis of the carbon skeletons of an end-product, whose chemical composition is given. It is then calculated how much energy is required for the non-synthetic processes which form a part of biosynthesis, such as intra- and intercellular transport of molecules and maintenance of RNA and enzymes. The additional amount of substrate required to provide this energy by combustion is easily calculated. Adding this substrate to the amount used for skeleton synthesis gives an overall equation which quantifies the substrate and oxygen demand as well as carbon dioxide evolution during biosynthesis of 1·0 g biomass. For example, it requires 1·34 g of glucose with adequate ammonia and minerals to synthesize 1·0 g maize plant biomass in darkness; during this process 0·14 g oxygen are consumed and 0·24 g carbon dioxide are produced. It has been described elsewhere that similar results were obtained experimentally with growing plants.Such results depend considerably upon the chemical composition of the biomass being synthesized and upon the state (oxidized or reduced) of the nitrogen source. Other parameters, such as the number of ATP molecules required for protein synthesis, the possibility for utilization of alternative pathways for synthesis or energy production, the presence or absence of compartmentation of synthetic processes and variations in the P/O ratio between two and three, under many conditions affect results of the computation less than 10%.Since maintenance of cellular structures is not considered, the approach concerns the gross yield of biosynthesis. It predicts therefore the dry matter yield of heterotrophic cells from a given quantity of substrate at high relative growth rates.     

Optimizing metabolic pathways by screening for feasible synthetic reactions

Background

Reconstruction of genome-scale metabolic networks has resulted in models capable of reproducing experimentally observed biomass yield/growth rates and predicting the effect of alterations in metabolism for biotechnological applications. The existing studies rely on modifying the metabolic network of an investigated organism by removing or inserting reactions taken either from evolutionary similar organisms or from databases of biochemical reactions (e.g., KEGG). A potential disadvantage of these knowledge-driven approaches is that the result is biased towards known reactions, as such approaches do not account for the possibility of including novel enzymes, together with the reactions they catalyze.

Results

Here, we explore the alternative of increasing biomass yield in three model organisms, namely Bacillus subtilis, Escherichia coli, and Hordeum vulgare, by applying small, chemically feasible network modifications. We use the predicted and experimentally confirmed growth rates of the wild-type networks as reference values and determine the effect of inserting mass-balanced, thermodynamically feasible reactions on predictions of growth rate by using flux balance analysis.

Conclusions

While many replacements of existing reactions naturally lead to a decrease or complete loss of biomass production ability, in all three investigated organisms we find feasible modifications which facilitate a significant increase in this biological function. We focus on modifications with feasible chemical properties and a significant increase in biomass yield. The results demonstrate that small modifications are sufficient to substantially alter biomass yield in the three organisms. The method can be used to predict the effect of targeted modifications on the yield of any set of metabolites (e.g., ethanol), thus providing a computational framework for synthetic metabolic engineering.     

Compositional complementarity and prebiotic ecology in the origin of life

We hypothesize that life began not with the first self-reproducing molecule or metabolic network, but as a prebiotic ecology of co-evolving populations of macromolecular aggregates (composomes). Each composome species had a particular molecular composition resulting from molecular complementarity among environmentally available prebiotic compounds. Natural selection acted on composomal species that varied in properties and functions such as stability, catalysis, fission, fusion and selective accumulation of molecules from solution. Fission permitted molecular replication based on composition rather than linear structure, while fusion created composomal variability. Catalytic functions provided additional chemical novelty resulting eventually in autocatalytic and mutually catalytic networks within composomal species. Composomal autocatalysis and interdependence allowed the Darwinian co-evolution of content and control (metabolism). The existence of chemical interfaces within complex composomes created linear templates upon which self-reproducing molecules (such as RNA) could be synthesized, permitting the evolution of informational replication by molecular templating. Mathematical and experimental tests are proposed.     

Constraint-Based Model of Shewanella oneidensis MR-1 Metabolism: A Tool for Data Analysis and Hypothesis Generation

Shewanellae are gram-negative facultatively anaerobic metal-reducing bacteria commonly found in chemically (i.e., redox) stratified environments. Occupying such niches requires the ability to rapidly acclimate to changes in electron donor/acceptor type and availability; hence, the ability to compete and thrive in such environments must ultimately be reflected in the organization and utilization of electron transfer networks, as well as central and peripheral carbon metabolism. To understand how Shewanella oneidensis MR-1 utilizes its resources, the metabolic network was reconstructed. The resulting network consists of 774 reactions, 783 genes, and 634 unique metabolites and contains biosynthesis pathways for all cell constituents. Using constraint-based modeling, we investigated aerobic growth of S. oneidensis MR-1 on numerous carbon sources. To achieve this, we (i) used experimental data to formulate a biomass equation and estimate cellular ATP requirements, (ii) developed an approach to identify cycles (such as futile cycles and circulations), (iii) classified how reaction usage affects cellular growth, (iv) predicted cellular biomass yields on different carbon sources and compared model predictions to experimental measurements, and (v) used experimental results to refine metabolic fluxes for growth on lactate. The results revealed that aerobic lactate-grown cells of S. oneidensis MR-1 used less efficient enzymes to couple electron transport to proton motive force generation, and possibly operated at least one futile cycle involving malic enzymes. Several examples are provided whereby model predictions were validated by experimental data, in particular the role of serine hydroxymethyltransferase and glycine cleavage system in the metabolism of one-carbon units, and growth on different sources of carbon and energy. This work illustrates how integration of computational and experimental efforts facilitates the understanding of microbial metabolism at a systems level.     

Evaluating enzymatic synthesis of small molecule drugs

There have been many achievements in applying biochemical synthetic routes to the synthesis of commodity chemicals. However, most of these endeavors have focused on optimizing and increasing the yields of naturally existing pathways. We sought to evaluate the potential for biosynthesis beyond the limits of known biochemistry towards the production of small molecule drugs that do not exist in nature. Because of the potential for improved yields compared to total synthesis, and therefore lower manufacturing costs, we focused on drugs for diseases endemic to many resource poor regions, like tuberculosis and HIV. Using generalized biochemical reaction rules, we were able to design biochemical pathways for the production of eight small molecule drugs or drug precursors and identify potential enzyme-substrate pairs for nearly every predicted reaction. All pathways begin from native metabolites, abrogating the need for specialized precursors. The simulated pathways showed several trends with the sequential ordering of reactions as well as the types of chemistries used. For some compounds, the main obstacles to finding feasible biochemical pathways were the lack of appropriate, natural starting compounds and a low diversity of biochemical coupling reactions necessary to synthesize molecules with larger molecular size.     

Improved synthesis of unique estradiol-linked platinum(II) complexes showing potent cytocidal activity and affinity for the estrogen receptor alpha and beta

We have recently reported the synthesis of a platinum(II) complex, made of estradiol, the female sex hormone, and a cisplatin analog, an anticancer drug, linked together by an eleven carbon atoms chain. The novel estradiol-Pt(II) hybrid molecule was synthesized in nine chemical steps with 10% overall yield. This new compound has been tested in vitro on estrogen-dependent (MCF-7) and -independent (MDA-MD-231) (ER(+) and ER(-)) cell lines. Interestingly, the biological activity was quite significant, more potent than that of cisplatin, the compound currently used in chemotherapy. The estrogen receptor binding affinity (ERBA) of this compound was very similar to that of 17beta-estradiol (E(2)) on both estrogen receptors (ERs), alpha and beta. In order to further study this type of molecule, we have decided to synthesize several analogs with the same estrogenic scaffold but with various chain lengths separating the estradiol from the toxic part of the molecule. This was planned in order to study the effect of the length of the linking chain on the biological activity of the hybrids. Four E(2)-Pt(II) hybrid molecules having 6-14 carbon atoms linking chain have been synthesized using a new synthetic methodology. They are synthesized in only eight chemical steps with 21% overall yield. The 17beta-estradiol-linked platinum(II) complexes have been tested for their receptor binding affinity as well as for their cytocidal activity on several breast cancer cell lines. The synthesis and biological results are reported herein.     

RNA as a catalyst: Natural and designed ribozymes

RNA can catalyse chemical reactions through its ability to fold into complex three-dimensional structures and to specifically bind small molecules and divalent metal ions. The 2′-hydroxyl groups of the ribose moieties contribute to this exceptional reactivity of RNA, compared to DNA. RNA is not only able to catalyse phosphate ester transfer reactions in ribonucleic acids, but can also show aminoacyl esterase activity, and is probably able to promote peptide bond formation. Bearing its potential for functioning both as a genome and as a gene product, RNA is suitable for in vitro evolution experiments enabling the selection of molecules with new properties. The growing repertoire of RNA catalysed reactions will establish RNA as a primordial molecule in the evolution of life.     

Engineering microbes to produce biofuels

The current biofuels landscape is chaotic. It is controlled by the rules imposed by economic forces and driven by the necessity of finding new sources of energy, particularly motor fuels. The need is bringing forth great creativity in uncovering new candidate fuel molecules that can be made via metabolic engineering. These next generation fuels include long-chain alcohols, terpenoid hydrocarbons, and diesel-length alkanes. Renewable fuels contain carbon derived from carbon dioxide. The carbon dioxide is derived directly by a photosynthetic fuel-producing organism(s) or via intermediary biomass polymers that were previously derived from carbon dioxide. To use the latter economically, biomass depolymerization processes must improve and this is a very active area of research. There are competitive approaches with some groups using enzyme based methods and others using chemical catalysts. With the former, feedstock and end-product toxicity loom as major problems. Advances chiefly rest on the ability to manipulate biological systems. Computational and modular construction approaches are key. For example, novel metabolic networks have been constructed to make long-chain alcohols and hydrocarbons that have superior fuel properties over ethanol. A particularly exciting approach is to implement a direct utilization of solar energy to make a usable fuel. A number of approaches use the components of current biological systems, but re-engineer them for more direct, efficient production of fuels.     

Design of Array-Type Compound Libraries that Combine Information from Natural Products and Synthetic Molecules

A new approach to the design of compound libraries, named MetaFocus (Metabolite-Focused library), is presented that exploits information encoded in natural molecules and combines naturally occurring and synthetic compounds. An important goal of the MF approach is the identification of synthetic compounds that mimic properties of natural molecules that are difficult to obtain in sufficient quantities or to synthesize. Compounds in MetaFocus (MF) arrays are focused on natural molecules with attractive therapeutic effects. Similarity search and diversity design techniques are employed to generate compound arrays that start from a selected natural molecule, add similar molecules, either from natural or synthetic sources, and diversify scaffolds derived from these molecules. Since the identification of similar molecules from natural and synthetic sources plays a significant role in our library design efforts, the performance of fingerprint-type search tools was systematically assessed in a newly assembled test database consisting of 16 biological activity classes. MF arrays are organized as an easily expandable and searchable data structure and serve as a knowledge base for drug discovery applications. Here we introduce the design principles and organization of MF arrays and present example applications.     

A Strategy to Calculate the Patterns of Nutrient Consumption by Microorganisms Applying a Two-Level Optimisation Principle to Reconstructed Metabolic Networks

Bacterial responses to environmental changes rely on a complex network of biochemical reactions. The properties of the metabolic network determining these responses can be divided into two groups: the stoichiometric properties, given by the stoichiometry matrix, and the kinetic/thermodynamic properties, given by the rate equations of the reaction steps. The stoichiometry matrix represents the maximal metabolic capabilities of the organism, and the regulatory mechanisms based on the rate laws could be considered as being responsible for the administration of these capabilities. Post-genomic reconstruction of metabolic networks provides us with the stoichiometry matrix of particular strains of microorganisms, but the kinetic aspects of in vivo rate laws are still largely unknown. Therefore, the validity of predictions of cellular responses requiring detailed knowledge of the rate equations is difficult to assert. In this paper, we show that by applying optimisation criteria to the core stoichiometric network of the metabolism of Escherichia coli, and including information about reversibility/irreversibility only of the reaction steps, it is possible to calculate bacterial responses to growth media with different amounts of glucose and galactose. The target was the minimisation of the number of active reactions (subject to attaining a growth rate higher than a lower limit) and subsequent maximisation of the growth rate (subject to the number of active reactions being equal to the minimum previously calculated). Using this two-level target, we were able to obtain by calculation four fundamental behaviours found experimentally: inhibition of respiration at high glucose concentrations in aerobic conditions, turning on of respiration when glucose decreases, induction of galactose utilisation when the system is depleted of glucose and simultaneous use of glucose and galactose as carbon sources when both sugars are present in low concentrations. Preliminary results of the coarse pattern of sugar utilisation were also obtained with a genome-scale E. coli reconstructed network, yielding similar qualitative results.     

Perspective on the use of humic acids from biomass as natural surfactants for industrial applications

In the context of renewable vs. non-renewable sources of chemical compounds, the development of natural surfactants as a substitute for synthetic surfactants in technological applications is an important issue. In addition, as synthetic surfactants can persist in the environment causing toxic effects, the use of natural products presents a possibility to minimize impact on the environment. Nowadays, a promising new approach in surfactant-based technologies, consists of the use of humic acids (HAs) extracted directly from biomass that exhibit amphiphilic properties, and can be conveniently used as environmentally friendly surfactants. The raw material from which HAs are extracted and their macromolecular composition affect surfactant properties. Therefore fundamental data from more strictly qualitative aspects, needs to be investigated. This review highlights surfactant ability and chemical properties of HA substances coming from renewable sources in comparison to synthetic surfactants, and points out the capacity for HAs to be used effectively in this field of application.     

Chemically reactive derivatives of gramicidin A for developing ion channel-based nanoprobes

Ion channel-forming peptides and proteins offer tremendous opportunities for fundamental and applied studies of function on individual molecules. An ongoing challenge in ion channel research is the lack of simple and accessible synthetic methods to engineer pores with tailored chemical and physical properties. This paper describes a practical synthetic route to rapidly generate C-terminally modified derivatives of gramicidin A (gA), an ion channel-forming peptide, through the use of two chemically reactive gA-based building blocks. These amine- and azide-containing building blocks can react readily with typical substrates for amidation and 1,3-dipolar cycloaddition ("click") reactions to present molecules with desired structure and functionality near the opening of a gA pore. These derivatives of gA are stable under typical aqueous conditions for ion channel recordings and retain characteristic single ion channel conductance properties in planar lipid bilayers. Additionally, the synthetic methods described here afford useful quantities of these gA derivatives in good purity and yield with minimal purification. We demonstrate that derivatives of gA can be used for studying, in situ, a change in conductance through a channel upon performing a "click" reaction on an azide moiety attached to the gA pore. We also demonstrate that these gA-based building blocks can be used to construct sensors for the recognition of specific protein-ligand binding interactions in solution. This widely accessible, enabling synthetic methodology represents a powerful new tool to study relationships between chemical structure and function on the single molecule level.     

Clustering under the line graph transformation: application to reaction network

Background  

Many real networks can be understood as two complementary networks with two kind of nodes. This is the case of metabolic networks where the first network has chemical compounds as nodes and the second one has nodes as reactions. In general, the second network may be related to the first one by a technique called line graph transformation (i.e., edges in an initial network are transformed into nodes). Recently, the main topological properties of the metabolic networks have been properly described by means of a hierarchical model. While the chemical compound network has been classified as hierarchical network, a detailed study of the chemical reaction network had not been carried out.     

The central role of the host cell in symbiotic nitrogen metabolism

Symbiotic nitrogen recycling enables animals to thrive on nitrogen-poor diets and environments. It traditionally refers to the utilization of animal waste nitrogen by symbiotic micro-organisms to synthesize essential amino acids (EAAs), which are translocated back to the animal host. We applied metabolic modelling and complementary metabolite profiling to investigate nitrogen recycling in the symbiosis between the pea aphid and the intracellular bacterium Buchnera, which synthesizes EAAs. The results differ from traditional notions of nitrogen recycling in two important respects. First, aphid waste ammonia is recycled predominantly by the host cell (bacteriocyte) and not Buchnera. Host cell recycling is mediated by shared biosynthetic pathways for four EAAs, in which aphid transaminases incorporate ammonia-derived nitrogen into carbon skeletons synthesized by Buchnera to generate EAAs. Second, the ammonia substrate for nitrogen recycling is derived from bacteriocyte metabolism, such that the symbiosis is not a sink for nitrogenous waste from other aphid organs. Host cell-mediated nitrogen recycling may be general among insect symbioses with shared EAA biosynthetic pathways generated by the loss of symbiont genes mediating terminal reactions in EAA synthesis.     

From large networks to small molecules

Large-scale analysis of genetic and physical interaction networks has begun to reveal the global organization of the cell. Cellular phenotypes observed at the macroscopic level depend on the collective characteristics of protein and genetic interaction networks, which exhibit scale-free properties and are highly resistant to perturbation of a single node. The nascent field of chemical genetics promises a host of small-molecule probes to explore these emerging networks. Although the robust nature of cellular networks usually resists the action of single agents, they may be susceptible to rationally designed combinations of small molecules able to collectively shift network behavior.     

Effect of various aqueous extracting agents on fluorescence properties of waste tea residue derived carbon dots (WTR-CDs): Comparative spectroscopic analysis

Fluorescent carbon dots (CDs) are one of the important carbonaceous nanomaterials in the area of nanoscience and nanotechnology because of their interesting physical as well as chemical properties. Herein we studied the effect of various aqueous extracting agents on fluorescence properties of waste tea residue-based carbon dots (WTR-CDs). WTR-CDs are firstly synthesized by utilizing kitchen waste-based carbonaceous biomass. To check the role of various aqueous media during the course of WTR-CDs synthesis from carbonized carbon powder, extraction of WTR-CDs was carried out in various kinds of aqueous media viz., only aqueous (100% water, WT), aqueous-alcoholic (10% ethanol, ET), aqueous-acidic (10% acetic acid, AA), and aqueous-basic (10% ammonia, AM). The consequences of extracting agents on the photophysical properties of final WTR-CDs-WT, WTR-CDs-ET, WTR-CDs-AA and WTR-CDs-AM were also discussed in detail. We have observed interesting blue shift fluorescence spectra in acidic medium for WTR-CDs-AA and polar protic solvents compared to polar aprotic medium. The solvatochromic behaviour of WTR-CDs-WT in model polar and non-polar solvent was also studied. The effect of cationic, anionic and non-anionic surfactants on the fluorescence of WTR-CDs-WT was also evaluated. The proposed findings may help researchers in the near future to obtain fast, easy and direct synthesize CDs from a variety of biomass-based precursors under different aqueous conditions.     

The use of solid waste of a nylon-6 plant as a nutrient for bacterial decolourisation of dyes

Three caprolactam-degrading bacterial isolates grew in liquid synthetic medium containing solubilised solid waste of a nylon-6 production plant as the sole source of carbon and nitrogen. Typically, the caprolactam content of solid waste was decreased by 95% in 72 h by Alcaligenes faecalis. A. faecalis was the most potent caprolactam-degrading bacterium out of the three isolates. The biomass of the bacteria obtained by growth in the solubilised solid waste medium had the ability to decolourise some synthetic azo and triphenylmethane dyes. Decolourisation of dyes was obtained in static condition, in synthetic medium which contained only the components of the solid waste as the sole sources of carbon and nitrogen and also in nutritionally rich medium. The supplementation of yeast extract to solid waste medium did not increase the efficiency of decolourisation in case of two of the bacterial cultures. Depending on the dye, medium and bacteria used, decolourisation in the range of 35–94% was achieved in 48–96 h. The decolourisation was not due to the adsorption of the dyes by the bacterial biomass except in case of Procion Blue MR and Black B. Based on these observations, the simultaneous biological treatment of the solid waste of nylon-6 plant and the decolourisation of synthetic dyes present in wastewater or solid waste is envisaged.     

Biased and unbiased strategies to identify biologically active small molecules

Small molecules are central players in chemical biology studies. They promote the perturbation of cellular processes underlying diseases and enable the identification of biological targets that can be validated for therapeutic intervention. Small molecules have been shown to accurately tune a single function of pluripotent proteins in a reversible manner with exceptional temporal resolution. The identification of molecular probes and drugs remains a worthy challenge that can be addressed by the use of biased and unbiased strategies. Hypothesis-driven methodologies employs a known biological target to synthesize complementary hits while discovery-driven strategies offer the additional means of identifying previously unanticipated biological targets. This review article provides a general overview of recent synthetic frameworks that gave rise to an impressive arsenal of biologically active small molecules with unprecedented cellular mechanisms.