BackgroundPseudomonas putida KT2442 is a natural producer of polyhydroxyalkanoates (PHAs), which can substitute petroleum-based non-renewable plastics and form the basis for the production of tailor-made biopolymers. However, despite the substantial body of work on PHA production by P. putida strains, it is not yet clear how the bacterium re-arranges its whole metabolism when it senses the limitation of nitrogen and the excess of fatty acids as carbon source, to result in a large accumulation of PHAs within the cell. In the present study we investigated the metabolic response of KT2442 using a systems biology approach to highlight the differences between single- and multiple-nutrient-limited growth in chemostat cultures.ResultsWe found that 26, 62, and 81% of the cell dry weight consist of PHA under conditions of carbon, dual, and nitrogen limitation, respectively. Under nitrogen limitation a specific PHA production rate of 0.43 (g·(g·h)-1) was obtained. The residual biomass was not constant for dual- and strict nitrogen-limiting growth, showing a different feature in comparison to other P. putida strains. Dual limitation resulted in patterns of gene expression, protein level, and metabolite concentrations that substantially differ from those observed under exclusive carbon or nitrogen limitation. The most pronounced differences were found in the energy metabolism, fatty acid metabolism, as well as stress proteins and enzymes belonging to the transport system.ConclusionThis is the first study where the interrelationship between nutrient limitations and PHA synthesis has been investigated under well-controlled conditions using a system level approach. The knowledge generated will be of great assistance for the development of bioprocesses and further metabolic engineering work in this versatile organism to both enhance and diversify the industrial production of PHAs.

One of the major challenges in metabolic engineering for enhanced synthesis of value-added chemicals is to design and develop new strains that can be translated into well-controlled fermentation processes using bioreactors. The aim of this study was to assess the influence of various fed-batch strategies in the performance of metabolically engineered Pseudomonas putida strains, Δgcd and Δgcd-pgl, for improving production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs) using glucose as the only carbon source. First we developed a fed-batch process that comprised an initial phase of biomass accumulation based on an exponential feeding carbon-limited strategy. For the mcl-PHA accumulation stage, three induction techniques were tested under nitrogen limitation. The substrate-pulse feeding was more efficient than the constant-feeding approach to promote the accumulation of the desirable product. Nonetheless, the most efficient approach for maximum PHA synthesis was the application of a dissolved-oxygen-stat feeding strategy (DO-stat), where P. putida Δgcd mutant strain showed a final PHA content and specific PHA productivity of 67% and 0.83 g·l(-1)·h(-1), respectively. To our knowledge, this mcl-PHA titer is the highest value that has been ever reported using glucose as the sole carbon and energy source. Our results also highlighted the effect of different fed-batch strategies upon the extent of realization of the intended metabolic modification of the mutant strains.

Many species of microalgae produce hydrocarbons, polysaccharides, and other valuable products in significant amounts. However, large-scale production of algal products is not yet competitive against non-renewable alternatives from fossil fuel. Metabolic engineering approaches will help to improve productivity, but the exact metabolic pathways and the identities of the majority of the genes involved remain unknown. Recent advances in bioinformatics and systems-biology modeling coupled with increasing numbers of algal genome-sequencing projects are providing the means to address this. A multidisciplinary integration of methods will provide synergy for a systems-level understanding of microalgae, and thereby accelerate the improvement of industrially valuable strains. In this review we highlight recent advances and challenges to microalgal research and discuss future potential.

BackgroundBurkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF) or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets.ResultsWe reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets.ConclusionsAs the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.