Enhancement of PCB degradation byBurkholderia xenovorans LB400 in biphasic systems by manipulating culture conditions

Biodegradation of PCB congeners by Paraburkholderia xenovorans LB400 in presence and absence of sediment during lab bioreactor experiments

Experiments were conducted to measure biodegradation of polychlorinated biphenyl (PCB) congeners contained in mixture Aroclor 1248 and congeners present in wastewater lagoon sediment contaminated decades earlier at Altavista, Virginia. A well-characterized strain of aerobic PCB-degrading bacteria, Paraburkholderia xenovorans LB400 was incubated in laboratory bioreactors with PCB-contaminated sediment collected at the site. The experiments evaluated strain LB400's ability to degrade PCBs in absence of sediment and in PCB-contaminated sediment slurry. In absence of sediment, LB400 transformed 76% of Aroclor 1248 within seven days, spanning all homolog groups present in the mixture. In sediment slurry, only mono- and di-chlorinated PCB congeners were transformed. These results show that LB400 is capable of rapidly biodegrading most PCB congeners when they are freely dissolved in liquid but cannot degrade PCB congeners having three or more chlorine substituents in sediment slurry. Finally, using GC/MS-MS triple quadrupole spectrometry, this work distinguishes between physical (sorption to cells) and biological removal mechanisms, illuminates the process by which microorganisms with LB400-type congener specificity can selectively transform lower-chlorinated congeners over time, and makes direct comparisons to other studies where individual congener data is reported.

Evolutionary design principles in metabolism

Microorganisms are ubiquitous and adapt to various dynamic environments to sustain growth. These adaptations accumulate, generating new traits forming the basis of evolution. Organisms adapt at various levels, such as gene regulation, signalling, protein-protein interactions and metabolism. Of these, metabolism forms the integral core of an organism for maintaining the growth and function of a cell. Therefore, studying adaptations in metabolic networks is crucial to understand the emergence of novel metabolic capabilities. Metabolic networks, composed of enzyme-catalysed reactions, exhibit certain repeating paradigms or design principles that arise out of different selection pressures. In this review, we discuss the design principles that are known to exist in metabolic networks, such as functional redundancy, modularity, flux coupling and exaptations. We elaborate on the studies that have helped gain insights highlighting the interplay of these design principles and adaptation. Further, we discuss how evolution plays a role in exploiting such paradigms to enhance the robustness of organisms. Looking forward, we predict that with the availability of ever-increasing numbers of bacterial, archaeal and eukaryotic genomic sequences, novel design principles will be identified, expanding our understanding of these paradigms shaped by varied evolutionary processes.

Constraint and Contingency Pervade the Emergence of Novel Phenotypes in Complex Metabolic Systems

An evolutionary constraint is a bias or limitation in phenotypic variation that a biological system produces. We know examples of such constraints, but we have no systematic understanding about their extent and causes for any one biological system. We here study metabolisms, genomically encoded complex networks of enzyme-catalyzed biochemical reactions, and the constraints they experience in bringing forth novel phenotypes that allow survival on novel carbon sources. Our computational approach does not limit us to analyzing constrained variation in any one organism, but allows us to quantify constraints experienced by any metabolism. Specifically, we study metabolisms that are viable on one of 50 different carbon sources, and quantify how readily alterations of their chemical reactions create the ability to survive on a novel carbon source. We find that some metabolic phenotypes are much less likely to originate than others. For example, metabolisms viable on D-glucose are 1835 times more likely to give rise to metabolisms viable on D-fructose than on acetate. Likewise, we observe that some novel metabolic phenotypes are more contingent on parental phenotypes than others. Biochemical similarities among carbon sources can help explain the causes of these constraints. In addition, we study metabolisms that can be produced by recombination among 55 metabolisms of different bacterial strains or species, and show that their novel phenotypes are also contingent on and constrained by parental genotypes. To our knowledge, our analysis is the first to systematically quantify the incidence of constrained evolution in a broad class of biological system that is central to life and its evolution.

The potential for non-adaptive origins of evolutionary innovations in central carbon metabolism

BACKGROUND

Biological systems are rife with examples of pre-adaptations or exaptations. They range from the molecular scale - lens crystallins, which originated from metabolic enzymes - to the macroscopic scale, such as feathers used in flying, which originally served thermal insulation or waterproofing. An important class of exaptations are novel and useful traits with non-adaptive origins. Whether such origins could be frequent cannot be answered with individual examples, because it is a question about a biological system's potential for exaptation. We here take a step towards answering this question by analyzing central carbon metabolism, and novel traits that allow an organism to survive on novel sources of carbon and energy. We have previously applied flux balance analysis to this system and predicted the viability of 10¹⁵ metabolic genotypes on each of ten different carbon sources.

RESULTS

We here use this exhaustive genotype-phenotype map to ask whether a central carbon metabolism that is viable on a given, focal carbon source C - the equivalent of an adaptation in our framework - is usually or rarely viable on one or more other carbon sources C _new - a potential exaptation. We show that most metabolic genotypes harbor potential exaptations, that is, they are viable on one or more carbon sources C _new . The nature and number of these carbon sources depends on the focal carbon source C itself, and on the biochemical similarity between C and C _new . Moreover, metabolisms that show a higher biomass yield on C, and that are more complex, i.e., they harbor more metabolic reactions, are viable on a greater number of carbon sources C _new .

CONCLUSIONS

A high potential for exaptation results from correlations between the phenotypes of different genotypes, and such correlations are frequent in central carbon metabolism. If they are similarly abundant in other metabolic or biological systems, innovations may frequently have non-adaptive ("exaptive") origins.

Phenotypic innovation through recombination in genome-scale metabolic networks

Recombination is an important source of metabolic innovation, especially in prokaryotes, which have evolved the ability to survive on many different sources of chemical elements and energy. Metabolic systems have a well-understood genotype-phenotype relationship, which permits a quantitative and biochemically principled understanding of how recombination creates novel phenotypes. Here, we investigate the power of recombination to create genome-scale metabolic reaction networks that enable an organism to survive in new chemical environments. To this end, we use flux balance analysis, an experimentally validated computational method that can predict metabolic phenotypes from metabolic genotypes. We show that recombination is much more likely to create novel metabolic abilities than random changes in chemical reactions of a metabolic network. We also find that phenotypic innovation is more likely when recombination occurs between parents that are genetically closely related, phenotypically highly diverse, and viable on few rather than many carbon sources. Survival on a new carbon source preferentially involves reactions that are superessential, that is, essential in many metabolic networks. We validate our observations with data from 61 reconstructed prokaryotic metabolic networks. Our systematic and quantitative analysis of metabolic systems helps understand how recombination creates innovation.

Exhaustive Analysis of a Genotype Space Comprising 10(15 )Central Carbon Metabolisms Reveals an Organization Conducive to Metabolic Innovation

All biological evolution takes place in a space of possible genotypes and their phenotypes. The structure of this space defines the evolutionary potential and limitations of an evolving system. Metabolism is one of the most ancient and fundamental evolving systems, sustaining life by extracting energy from extracellular nutrients. Here we study metabolism’s potential for innovation by analyzing an exhaustive genotype-phenotype map for a space of 10¹⁵ metabolisms that encodes all possible subsets of 51 reactions in central carbon metabolism. Using flux balance analysis, we predict the viability of these metabolisms on 10 different carbon sources which give rise to 1024 potential metabolic phenotypes. Although viable metabolisms with any one phenotype comprise a tiny fraction of genotype space, their absolute numbers exceed 10⁹ for some phenotypes. Metabolisms with any one phenotype typically form a single network of genotypes that extends far or all the way through metabolic genotype space, where any two genotypes can be reached from each other through a series of single reaction changes. The minimal distance of genotype networks associated with different phenotypes is small, such that one can reach metabolisms with novel phenotypes – viable on new carbon sources – through one or few genotypic changes. Exceptions to these principles exist for those metabolisms whose complexity (number of reactions) is close to the minimum needed for viability. Increasing metabolic complexity enhances the potential for both evolutionary conservation and evolutionary innovation.

Genotype-phenotype mapping is one of the ultimate goals of computational systems biology, and can provide new insights into the function and evolution of biological systems. We present a comprehensive genotype-phenotype map for a space of metabolic genotypes that comprises more than 10¹⁵ central carbon metabolisms. Only one in a million of these metabolisms can sustain life on any one of 10 carbon sources we consider, but these viable metabolisms form connected genotype networks that extend far through genotype space. In addition, they render multiple novel metabolic phenotypes in their immediate neighborhood accessible through small evolutionary changes that require only the alteration of single metabolic reactions. The map we construct reveals an organization of core metabolism that simultaneously facilitates evolutionary conservation of existing metabolic phenotypes, and the origination of novel metabolic traits that allow viability on novel carbon sources. Such metabolic innovation is essential, particularly for organisms that experience unexpected environmental changes, and that explore or invade new habitats.

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.

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.

Expression, purification and functional characterization of a recombinant 2,3-dihydroxybiphenyl-1,2-dioxygenase from Rhodococcus rhodochrous

A 2,3-dihydroxybiphenyl (2,3-DHBP) dioxygenase gene from a Rhodococcus sp. strain, named RrbphCI and involved in the degradation of polychlorinated biphenyls (PCBs), was synthesized. RrbphCI was expressed in Escherichia coli and its encoded enzyme was purified. SDS-PAGE analysis indicated that the size of the protein encoded by RrbphCI was about 32 kDa. The activity of the 2,3-DHBP dioxygenase was 82.8 U/mg when the substrate was 2,3-DHBP, with optimum pH 8.0 at 30°C, and optimum temperature was 40°C at pH 8.0. The RrbphCI gene was transformed into Pseudomonas putida strain EG11, to determine the ability of the enzyme to degrade 2,3-DHBP. The wild type EG11 degraded 61.86% of supplied 2,3-DHBP and the transformed EG11 (hosting the RrbphCI gene) utilized 52.68% after 2 min of treatment at 30°C. The overexpressed and purified enzyme was able to degrade 2,3-DHBP. The 2,3-DHBP dioxygenase is a key enzyme in the PCB degradation pathway. RrbphCI and its encoded 2,3-DHBP dioxygenase may have transgenic applications in bioremediation of PCBs.

Two-phase partitioning bioreactors operating with polymers applied to the removal of substituted phenols

Significant improvement in biodegradation performance has been demonstrated arising from the reduction of cytotoxicity provided by the sequestering of 4-nitrophenol (4NP) within Hytrel polymer beads added to a two-phase partitioning bioreactor (TPPB) operating in sequencing batch reactor (SBR) mode. This reduced toxicity is particularly apparent as the feed substrate concentration is increased; in fact it was shown that at a feed of 1000 mg/L 4NP, the inhibitory effect of the substrate completely prevents degradation from occurring in a single-phase system, whereas at only a 5% polymer loading, rapid and compete biodegradation is achieved. Different polymer/aqueous phase ratios were used to detoxify varying feed concentrations, and degradation rates were enhanced through the use of increased polymer loadings. As demonstrated in oxygen uptake experiments, the addition of polymers also reduces the maximum demand for oxygen, relative to single-phase operation, and smoothes the demand for oxygen throughout the degradation process. Polymer regeneration has also been further characterized by quantifying the number of methanol washes required to achieve satisfactory 4NP residuals, and the addition of a small amount of cosolvent has been shown to dramatically increase the rate of bioregeneration to produce beads ready for reuse.

Enhanced biodegradation of hydrocarbons in soil by microbial biosurfactant, sophorolipid

Effectiveness of a microbial biosurfactant, sophorolipid, was evaluated in washing and biodegradation of model hydrocarbons and crude oil in soil. Thirty percent of 2-methylnaphthalene was effectively washed and solubilized with 10 g/L of sophorolipid with similar or higher efficiency than that of commercial surfactants. Addition of sophorolipid in soil increased biodegradation of model compounds: 2-methylnaphthalene (95% degradation in 2 days), hexadecane (97%, 6 days), and pristane (85%, 6 days). Also, effective biodegradation method of crude oil in soil was observed by the addition of sophorolipid, resulting in 80% biodegradation of saturates and 72% aromatics in 8 weeks. These results showed the potentials of the microbial biosurfactant, sophorolipid, as an effective surfactant for soil washing and as an in situ biodegradation enhancer.