Flux Balance Analysis of Cyanobacterial Metabolism: The Metabolic Network of Synechocystis sp. PCC 6803

Cyanobacteria are versatile unicellular phototrophic microorganisms that are highly abundant in many environments. Owing to their capability to utilize solar energy and atmospheric carbon dioxide for growth, cyanobacteria are increasingly recognized as a prolific resource for the synthesis of valuable chemicals and various biofuels. To fully harness the metabolic capabilities of cyanobacteria necessitates an in-depth understanding of the metabolic interconversions taking place during phototrophic growth, as provided by genome-scale reconstructions of microbial organisms. Here we present an extended reconstruction and analysis of the metabolic network of the unicellular cyanobacterium Synechocystis sp. PCC 6803. Building upon several recent reconstructions of cyanobacterial metabolism, unclear reaction steps are experimentally validated and the functional consequences of unknown or dissenting pathway topologies are discussed. The updated model integrates novel results with respect to the cyanobacterial TCA cycle, an alleged glyoxylate shunt, and the role of photorespiration in cellular growth. Going beyond conventional flux-balance analysis, we extend the computational analysis to diurnal light/dark cycles of cyanobacterial metabolism.     

Energy drives the dynamic localization of cyanobacterial nitrogen regulators during diurnal cycles

Cyanobacteria, phototrophic organisms performing oxygenic photosynthesis, must adapt their metabolic processes to the challenges imposed by the succession of days and nights. Two conserved cyanobacterial proteins, PII and PipX, function as hubs of the nitrogen interaction network, forming complexes with a variety of diverse targets. While PII proteins are found in all three domains of life as integrators of signals of the nitrogen and carbon balance, PipX proteins are unique to cyanobacteria, where they provide a mechanistic link between PII signalling and the control of gene expression by the global nitrogen regulator NtcA. Here we demonstrate that PII and PipX display distinct localization patterns during diurnal cycles, co‐localizing into the same foci at the periphery and poles of the cells during dark periods, a circadian‐independent process requiring a low ATP/ADP ratio. Genetic, cellular biology and biochemical approaches used here provide new insights into the nitrogen regulatory network, calling attention to the roles of PII as energy sensors and its interactions with PipX in the context of essential signalling pathways. This study expands the contribution of the nitrogen regulators PII and PipX to integrate and transduce key environmental signals that allow cyanobacteria to thrive in our planet.     

Synthetic Biology Toolkits for Metabolic Engineering of Cyanobacteria

Cyanobacteria are of great importance to Earth's ecology. Due to their capability in photosynthesis and C1 metabolism, they are ideal microbial chassis that can be engineered for direct conversion of carbon dioxide and solar energy into biofuels and biochemicals. Facilitated by the elucidation of the basic biology of the photoautotrophic microbes and rapid advances in synthetic biology, genetic toolkits have been developed to enable implementation of nonnatural functionalities in engineered cyanobacteria. Hence, cyanobacteria are fast becoming an emerging platform in synthetic biology and metabolic engineering. Herein, the progress made in the synthetic biology toolkits for cyanobacteria and their utilization for transforming cyanobacteria into microbial cell factories for sustainable production of biofuels and biochemicals is outlined. Current techniques in heterologous gene expression, strategies in genome editing, and development of programmable regulatory parts and modules for engineering cyanobacteria towards biochemical production are discussed and prospected. As cyanobacteria synthetic biology is still in its infancy, apart from the achievements made, the difficulties and challenges in applying and developing genetic toolkits in cyanobacteria for biochemical production are also evaluated.     

Genetic control of hydrogen metabolism in cyanobacteria

The development of methods for the use of phototrophic cyanobacteria as producers of molecular hydrogen via bioconversion of solar energy is a promising filed of hydrogen energetics. Optimization of hydrogen formation and release is based on studying the genetic control of hydrogen metabolism and the use of genetic approaches for obtaining efficient producer strains. Data on genes coding for the hydrogenases that are responsible for hydrogen uptake and production in cyanobacteria are summarized. Bioinformatic methods have been used to construct the scheme of the hydrogen metabolism gene network of nitrogen-fixing heterocystous cyanobacteria. The possible approaches to constructing the cyanobacterium strains producing molecular hydrogen that would be promising for photobiotechnology by mutagenesis and genetic engineering methods are discussed in terms of this model and analysis of the data on hydrogen-producing mutants.     

Genetic control of hydrogen metabolism in cyanobacteria

The development of methods for the use of phototrophic cyanobacteria as producers of molecular hydrogen via bioconversion of solar energy is a promising filed of hydrogen energetics. Artificial optimization of hydrogen formation and release is based on studying the genetic control of hydrogen metabolism and the use of genetic approaches for obtaining efficient producer strains. Data on genes coding for the hydrogenases that are responsible for hydrogen uptake and production in cyanobacteria are summarized. Bioinformatic methods have been used to construct the scheme of the hydrogen metabolism gene network of nitrogen-fixing heterocyst cyanobacteria. The possible approaches to constructing the cyanobacterium strains producing molecular hydrogen that would be promising for photobiotechnology by mutagenesis and genetic engineering methods are discussed in terms of this model and analysis of the data on hydrogen-producing mutants.     

Cyanobacteria and microalgae: a positive prospect for biofuels

Biofuel-bioenergy production has generated intensive interest due to increased concern regarding limited petroleum-based fuel supplies and their contribution to atmospheric CO2 levels. Biofuel research is not just a matter of finding the right type of biomass and converting it to fuel, but it must also be economically sustainable on large-scale. Several aspects of cyanobacteria and microalgae such as oxygenic photosynthesis, high per-acre productivity, non-food based feedstock, growth on non-productive and non-arable land, utilization of wide variety of water sources (fresh, brackish, seawater and wastewater) and production of valuable co-products along with biofuels have combined to capture the interest of researchers and entrepreneurs. Currently, worldwide biofuels mainly in focus include biohydrogen, bioethanol, biodiesel and biogas. This review focuses on cultivation and harvesting of cyanobacteria and microalgae, possible biofuels and co-products, challenges for cyanobacterial and microalgal biofuels and the approaches of genetic engineering and modifications to increase biofuel production.     

Application of Petri net theory for modelling and validation of the sucrose breakdown pathway in the potato tuber

MOTIVATION: Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood. RESULTS: We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.     

A new easy method for determination of surface adhesion of phototrophic biofilms

Terrestrial cyanobacteria grow as phototrophic biofilms and offer a wide spectrum of interesting products. For cultivation of phototrophic biofilms different reactor concepts have been developed in the last years. One of the main influencing factors is the surface material and the adhesion strength of the chosen production strain. In this work a flow chamber was developed, in which, in combination with optical coherence tomography and computational fluid dynamics simulation, an easy analysis of adhesion forces between different biofilms and varied surface materials is possible. Hereby, differences between two cyanobacteria strains and two surface materials were shown. With longer cultivation time of biofilms adhesion increased in all experiments. Additionally, the content of extracellular polymeric substances was analyzed and its role in surface adhesion was evaluated. To test the comparability of obtained results from the flow chamber with other methods, analogous experiments were conducted with a rotational rheometer, which proved to be successful. Thus, with the presented flow chamber an easy to implement method for analysis of biofilm adhesion was developed, which can be used in future research for determination of suitable combinations of microorganisms with cultivation surfaces on lab scale in advance of larger processes.     

Comparison of metabolic states using genome-scale metabolic models

Genome-scale metabolic models (GEMs) are comprehensive knowledge bases of cellular metabolism and serve as mathematical tools for studying biological phenotypes and metabolic states or conditions in various organisms and cell types. Given the sheer size and complexity of human metabolism, selecting parameters for existing analysis methods such as metabolic objective functions and model constraints is not straightforward in human GEMs. In particular, comparing several conditions in large GEMs to identify condition- or disease-specific metabolic features is challenging. In this study, we showcase a scalable, model-driven approach for an in-depth investigation and comparison of metabolic states in large GEMs which enables identifying the underlying functional differences. Using a combination of flux space sampling and network analysis, our approach enables extraction and visualisation of metabolically distinct network modules. Importantly, it does not rely on known or assumed objective functions. We apply this novel approach to extract the biochemical differences in adipocytes arising due to unlimited vs blocked uptake of branched-chain amino acids (BCAAs, considered as biomarkers in obesity) using a human adipocyte GEM (iAdipocytes1809). The biological significance of our approach is corroborated by literature reports confirming our identified metabolic processes (TCA cycle and Fatty acid metabolism) to be functionally related to BCAA metabolism. Additionally, our analysis predicts a specific altered uptake and secretion profile indicating a compensation for the unavailability of BCAAs. Taken together, our approach facilitates determining functional differences between any metabolic conditions of interest by offering a versatile platform for analysing and comparing flux spaces of large metabolic networks.     

Silica sol-gel encapsulation of cyanobacteria: lessons for academic and applied research

Cyanobacteria inhabit nearly every ecosystem on earth, play a vital role in nutrient cycling, and are useful as model organisms for fundamental research in photosynthesis and carbon and nitrogen fixation. In addition, they are important for several established biotechnologies for producing food additives, nutritional and pharmaceutical compounds, and pigments, as well as emerging biotechnologies for biofuels and other products. Encapsulation of living cyanobacteria into a porous silica gel matrix is a recent approach that may dramatically improve the efficiency of certain production processes by retaining the biomass within the reactor and modifying cellular metabolism in helpful ways. Although encapsulation has been explored empirically in the last two decades for a variety of cell types, many challenges remain to achieving optimal encapsulation of cyanobacteria in silica gel. Recent evidence with Synechocystis sp. PCC 6803, for example, suggests that several unknown or uncharacterized proteins are dramatically upregulated as a result of encapsulation. Also, additives commonly used to ease stresses of encapsulating living cells, such as glycerol, have detrimental impacts on photosynthesis in cyanobacteria. This mini-review is intended to address the current status of research on silica sol-gel encapsulation of cyanobacteria and research areas that may further the development of this approach for biotechnology applications.     

Reconstruction and visualization of carbohydrate, N-glycosylation pathways in Pichia pastoris CBS7435 using computational and system biology approaches

Pichia pastoris is an efficient expression system for production of recombinant proteins. To understand its physiology for building novel applications it is important to understand and reconstruct its metabolic network. The metabolic reconstruction approach connects genotype with phenotype. Here, we have attempted to reconstruct carbohydrate metabolism pathways responsible for high biomass density and N-glycosylation pathways involved in the post translational modification of proteins of P. pastoris CBS7435. Both these metabolic pathways play a crucial role in heterologous protein production. We report novel, missing and unannotated enzymes involved in the target metabolic pathways. A strong possibility of cellulose and xylose metabolic processes in P. pastoris CBS7435 suggests its use in the area of biofuels. The reconstructed metabolic networks can be used for increased yields and improved product quality, for designing appropriate growth medium, for production of recombinant therapeutics and for making biofuels.     

细菌应激反应中(p)ppGpp代谢的调控

(p)ppGpp是介导细菌细胞对环境胁迫产生应激反应的重要胞内信号,通过控制一系列重要的细胞活动使细菌得以生存。通过对蓝细菌中(p)ppGpp代谢的研究,对(p)ppGpp作用机制、控制(p)ppGpp代谢的酶系统、环境胁迫信号传递、细胞中(p)ppGpp水平的调控及其多样性进行了总结。     

Decision tree modeling predicts effects of inhibiting contractility signaling on cell motility

Background

Mathematical modelling of cellular networks is an integral part of Systems Biology and requires appropriate software tools. An important class of methods in Systems Biology deals with structural or topological (parameter-free) analysis of cellular networks. So far, software tools providing such methods for both mass-flow (metabolic) as well as signal-flow (signalling and regulatory) networks are lacking.

Results

Herein we introduce CellNetAnalyzer, a toolbox for MATLAB facilitating, in an interactive and visual manner, a comprehensive structural analysis of metabolic, signalling and regulatory networks. The particular strengths of CellNetAnalyzer are methods for functional network analysis, i.e. for characterising functional states, for detecting functional dependencies, for identifying intervention strategies, or for giving qualitative predictions on the effects of perturbations. CellNetAnalyzer extends its predecessor FluxAnalyzer (originally developed for metabolic network and pathway analysis) by a new modelling framework for examining signal-flow networks. Two of the novel methods implemented in CellNetAnalyzer are discussed in more detail regarding algorithmic issues and applications: the computation and analysis (i) of shortest positive and shortest negative paths and circuits in interaction graphs and (ii) of minimal intervention sets in logical networks.

Conclusion

CellNetAnalyzer provides a single suite to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks in a user-friendly environment. It provides a large toolbox with various, partially unique, functions and algorithms for functional network analysis.CellNetAnalyzer is freely available for academic use.     

Metabolic engineering strategies toward production of biofuels

Exacerbation of climate change and air pollution around the world have emphasized the necessity of replacing fossil fuels with clean and sustainable energy. Metabolic engineering has provided strategies to engineer diverse organisms for the production of biofuels from renewable carbon sources. Although some of the processes are commercialized, there has been continued effort to produce advanced biofuels with higher efficiencies. In this article, metabolic engineering strategies recently exploited to enhance biofuel production and facilitate utilization of non-edible low-value carbon sources are reviewed. The strategies include engineering enzymes, exploiting new pathways, and systematically optimizing metabolism and fermentation processes, among others. In addition, metabolic and bioprocess engineering strategies to achieve competitiveness of current biofuel production systems compared with fossil fuels are discussed.     

Insights into chemotaxonomic composition and carbon cycling of phototrophic communities in an artesian sulfur-rich spring (Zodletone, Oklahoma, USA), a possible analog for ancient microbial mat systems

Zodletone spring in Oklahoma is a unique environment with high concentrations of dissolved-sulfide (10 mm) and short-chain gaseous alkanes, exhibiting characteristics that are reminiscent of conditions that are thought to have existed in Earth's history, in particular the late Archean and early-to-mid Proterozoic. Here, we present a process-oriented investigation of the microbial community in two distinct mat formations at the spring source, (1) the top of the sediment in the source pool and (2) the purple streamers attached to the side walls. We applied a combination of pigment and lipid biomarker analyses, while functional activities were investigated in terms of oxygen production (microsensor analysis) and carbon utilization ((13)C incorporation experiments). Pigment analysis showed cyanobacterial pigments, in addition to pigments from purple sulfur bacteria (PSB), green sulfur bacteria (GSB) and Chloroflexus-like bacteria (CLB). Analysis of intact polar lipids (IPLs) in the source sediment confirmed the presence of phototrophic organisms via diacylglycerol phospholipids and betaine lipids, whereas glyceroldialkylglyceroltetraether additionally indicated the presence of archaea. No archaeal IPLs were found in the purple streamers, which were strongly dominated by betaine lipids. (13)C-bicarbonate- and -acetate-labeling experiments indicated cyanobacteria as predominant phototrophs in the source sediment, carbon was actively fixed by PSB/CLB/GSB in purple streamers by using near infrared light. Despite the presence of cyanobacteria, no oxygen could be detected in the presence of light, suggesting anoxygenic photosynthesis as the major metabolic process at this site. Our investigations furthermore indicated photoheterotrophy as an important process in both habitats. We obtained insights into a syntrophically operating phototrophic community in an ecosystem that bears resemblance to early Earth conditions, where cyanobacteria constitute an important contributor to carbon fixation despite the presence of high sulfide concentrations.     

A genome‐scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism

Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health‐promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome‐scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome‐scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses.