Bone repairs represent a major focus in orthopedic medicine with biomaterials as a critical aspect of the regenerative process. However, only a limited set of biomaterials are utilized today and few studies relate biomaterial scaffold design to degradation rate and new bone formation. Matching biomaterial remodeling rate towards new bone formation is important in terms of the overall rate and quality of bone regeneration outcomes. We report on the osteogenesis and metabolism of human bone marrow derived mesenchymal stem cells (hMSCs) in 3D silk scaffolds. The scaffolds were prepared with two different degradation rates in order to study relationships between matrix degradation, cell metabolism and bone tissue formation in vitro. SEM, histology, chemical assays, real-time PCR and metabolic analyses were assessed to investigate these relationships. More extensively mineralized ECM formed in the scaffolds designed to degrade more rapidly, based on SEM, von Kossa and type I collagen staining and calcium content. Measures of osteogenic ECM were significantly higher in the more rapidly degrading scaffolds than in the more slowly degrading scaffolds over 56 days of study in vitro. Metabolic analysis, including glucose and lactate levels, confirmed the degradation rate differences with the two types of scaffolds, with the more rapidly degrading scaffolds supporting higher levels of glucose consumption and lactate synthesis by the hMSCs upon osteogenesis, in comparison to the more slowly degrading scaffolds. The results demonstrate that scaffold degradation rates directly impact the metabolism of hMSCs, and in turn the rate of osteogenesis. An understanding of the interplay between cellular metabolism and scaffold degradability should aid in the more rational design of scaffolds for bone regeneration needs both in vitro and in vivo.

Despite excellent biocompatibility and mechanical properties, the poor in vitro and in vivo degradability of cellulose has limited its biomedical and biomass conversion applications. To address this issue, we report a metabolic engineering-based approach to the rational redesign of cellular metabolites to introduce N-acetylglucosamine (GlcNAc) residues into cellulosic biopolymers during de novo synthesis from Gluconacetobacter xylinus. The cellulose produced from these engineered cells (modified bacterial cellulose [MBC]) was evaluated and compared with cellulose produced from normal cells (bacterial cellulose [BC]). High GlcNAc content and lower crystallinity in MBC compared to BC make this a multifunctional bioengineered polymer susceptible to lysozyme, an enzyme widespread in the human body, and to rapid hydrolysis by cellulase, an enzyme commonly used in biomass conversion. Degradability in vivo was demonstrated in subcutaneous implants in mice, where modified cellulose was completely degraded within 20 days. We provide a new route toward the production of a family of tailorable modified cellulosic biopolymers that overcome the longstanding limitation associated with the poor degradability of cellulose for a wide range of potential applications.

BackgroundIncreasing energy expenditure at the cellular level offers an attractive option to limit adiposity and improve whole body energy balance. In vivo and in vitro observations have correlated mitochondrial uncoupling protein-1 (UCP1) expression with reduced white adipose tissue triglyceride (TG) content. The metabolic basis for this correlation remains unclear.Methodology/Principal FindingsThis study tested the hypothesis that mitochondrial uncoupling requires the cell to compensate for the decreased oxidation phosphorylation efficiency by up-regulating lactate production, thus redirecting carbon flux away from TG synthesis. Metabolic flux analysis was used to characterize the effects of non-lethal, long-term mitochondrial uncoupling (up to 18 days) on the pathways of intermediary metabolism in differentiating 3T3-L1 adipocytes. Uncoupling was induced by forced expression of UCP1 and chemical (FCCP) treatment. Chemical uncoupling significantly decreased TG content by ca. 35%. A reduction in the ATP level suggested diminished oxidative phosphorylation efficiency in the uncoupled adipocytes. Flux analysis estimated significant up-regulation of glycolysis and down-regulation of fatty acid synthesis, with chemical uncoupling exerting quantitatively larger effects.Conclusions/SignificanceThe results of this study support our hypothesis regarding uncoupling-induced redirection of carbon flux into glycolysis and lactate production, and suggest mitochondrial proton translocation as a potential target for controlling adipocyte lipid metabolism.

Metabolic pathways for amino sugars (N-acetylglucosamine; GlcNAc and glucosamine; Gln) are essential and remain largely conserved in all three kingdoms of life, i.e., microbes, plants and animals. Upon uptake, in the cytoplasm these amino sugars undergo phosphorylation by phosphokinases and subsequently deacetylation by the enzyme N-acetylglucosamine 6-phosphate deacetylase (nagA) to yield glucosamine-6-phosphate and acetate, the first committed step for both GlcNAc assimilation and amino-sugar-nucleotides biosynthesis. Here we report the cloning of a DNA fragment encoding a partial nagA gene and its implications with regard to amino sugar metabolism in the cellulose producing bacterium Glucoacetobacter xylinus (formally known as Acetobacter xylinum). For this purpose, nagA was disrupted by inserting tetracycline resistant gene (nagA::tetr; named as ΔnagA) via homologous recombination. When compared to glucose fed conditions, the UDP-GlcNAc synthesis and bacterial growth (due to lack of GlcNAc utilization) was completely inhibited in nagA mutants. Interestingly, that inhibition occured without compromising cellulose production efficiency and its molecular composition under GlcNAc fed conditions. We conclude that nagA plays an essential role for GlcNAc assimilation by G. xylinus thus is required for the growth and survival for the bacterium in presence of GlcNAc as carbon source. Additionally, G. xylinus appears to possess the same molecular machinery for UDP-GlcNAc biosynthesis from GlcNAc precursors as other related bacterial species.

BackgroundMicrobial hosts offer a number of unique advantages when used as production systems for both native and heterologous small-molecules. These advantages include high selectivity and benign environmental impact; however, a principal drawback is low yield and/or productivity, which limits economic viability. Therefore a major challenge in developing a microbial production system is to maximize formation of a specific product while sustaining cell growth. Tools to rationally reconfigure microbial metabolism for these potentially conflicting objectives remain limited. Exhaustively exploring combinations of genetic modifications is both experimentally and computationally inefficient, and can become intractable when multiple gene deletions or insertions need to be considered. Alternatively, the search for desirable gene modifications may be solved heuristically as an evolutionary optimization problem. In this study, we combine a genetic algorithm and elementary mode analysis to develop an optimization framework for evolving metabolic networks with energetically favorable pathways for production of both biomass and a compound of interest.ResultsUtilization of thermodynamically-weighted elementary modes for flux reconstruction of E. coli central metabolism revealed two clusters of EMs with respect to their ΔGp°. For proof of principle testing, the algorithm was applied to ethanol and lycopene production in E. coli. The algorithm was used to optimize product formation, biomass formation, and product and biomass formation simultaneously. Predicted knockouts often matched those that have previously been implemented experimentally for improved product formation. The performance of a multi-objective genetic algorithm showed that it is better to couple the two objectives in a single objective genetic algorithm.ConclusionA computationally tractable framework is presented for the redesign of metabolic networks for maximal product formation combining elementary mode analysis (a form of convex analysis), pathway thermodynamics, and a genetic algorithm to optimize the production of two industrially-relevant products, ethanol and lycopene, from E. coli. The designed algorithm can be applied to any small-scale model of cellular metabolism theoretically utilizing any substrate and applied towards the production of any product.