Metabolic engineering of Escherichia coli for the enhanced production of l-tyrosine.

Despite wide applications of l-tyrosine in the market, microbial overproduction of l-tyrosine has been a great challenge due to the complex gene regulations involved in its biosynthetic pathway. To this end, effects of knocking out tyrR on the l-tyrosine production were further explored during the strain development. Also, blocking cellular uptake of l-tyrosine by knocking out tyrosine transporters was examined with respect to l-tyrosine production. Using feedback-resistant aroG and tyrA genes (aroGfbr and tyrAfbr hereafter) as initial overexpression targets, which encode 3-deoxy-7-phosphoheptulonate synthase and chorismate mutase or prephenate dehydrogenase, respectively, various combinations of genes were subsequently overexpressed in the Escherichia coli wild-type and tyrR knockout strain, and their effects on the l-tyrosine production were examined. Co-overexpression of aroGfbr , aroL and tyrC, a gene from Zymomonas mobilis functionally similar to tyrAfbr , but insensitive to l-tyrosine, led to the greatest l-tyrosine production regardless of the strains and plasmid constructs examined in this study. The strain BTY2.13 overexpressing the abovementioned three genes together with the removal of the l-tyrosine-specific transporter (tyrP) produced 43.14 g/L of l-tyrosine by fed-batch fermentation using the exponential feeding followed by DO-stat feeding method. This outcome suggested that the tyrR gene knockout was not mandatory for the l-tyrosine overproduction, but the production performance of strains having tyrR appeared to be highly affected by vector systems and feeding methods. With an optimal vector system and a feeding method, tyrP knockout appeared to be more effective in enhancing the l-tyrosine than tyrR knockout.

Applications of genome-scale metabolic network model in metabolic engineering.

Genome-scale metabolic network model (GEM) is a fundamental framework in systems metabolic engineering. GEM is built upon extensive experimental data and literature information on gene annotation and function, metabolites and enzymes so that it contains all known metabolic reactions within an organism. Constraint-based analysis of GEM enables the identification of phenotypic properties of an organism and hypothesis-driven engineering of cellular functions to achieve objectives. Along with the advances in omics, high-throughput technology and computational algorithms, the scope and applications of GEM have substantially expanded. In particular, various computational algorithms have been developed to predict beneficial gene deletion and amplification targets and used to guide the strain development process for the efficient production of industrially important chemicals. Furthermore, an Escherichia coli GEM was integrated with a pathway prediction algorithm and used to evaluate all possible routes for the production of a list of commodity chemicals in E. coli. Combined with the wealth of experimental data produced by high-throughput techniques, much effort has been exerted to add more biological contexts into GEM through the integration of omics data and regulatory network information for the mechanistic understanding and improved prediction capabilities. In this paper, we review the recent developments and applications of GEM focusing on the GEM-based computational algorithms available for microbial metabolic engineering.

Combinatorial design of a highly efficient xylose-utilizing pathway in Saccharomyces cerevisiae for the production of cellulosic biofuels.

Balancing the flux of a heterologous metabolic pathway by tuning the expression and properties of the pathway enzymes is difficult, but it is critical to realizing the full potential of microbial biotechnology. One prominent example is the metabolic engineering of a Saccharomyces cerevisiae strain harboring a heterologous xylose-utilizing pathway for cellulosic-biofuel production, which remains a challenge even after decades of research. Here, we developed a combinatorial pathway-engineering approach to rapidly create a highly efficient xylose-utilizing pathway for ethanol production by exploring various combinations of enzyme homologues with different properties. A library of more than 8,000 xylose utilization pathways was generated using DNA assembler, followed by multitiered screening, which led to the identification of a number of strain-specific combinations of the enzymes for efficient conversion of xylose to ethanol. The balancing of metabolic flux through the xylose utilization pathway was demonstrated by a complete reversal of the major product from xylitol to ethanol with a similar yield and total by-product formation as low as 0.06 g/g xylose without compromising cell growth. The results also suggested that an optimal enzyme combination depends on not only the genotype/phenotype of the host strain, but also the sugar composition of the fermentation medium. This combinatorial approach should be applicable to any heterologous pathway and will be instrumental in the optimization of industrial production of value-added products.

Bio-based production of C2-C6 platform chemicals.

Platform chemicals composed of 2-6 carbons derived from fossil resources are used as important precursors for making a variety of chemicals and materials, including solvents, fuels, polymers, pharmaceuticals, perfumes, and foods. Due to concerns regarding our environment and the limited nature of fossil resources, however, increasing interest has focused on the development of sustainable technologies for producing these platform chemicals from renewable resources. The techniques and strategies for developing microbial strains for chemicals production have advanced rapidly, and it is becoming feasible to develop microbes for producing additional types of chemicals, including non-natural molecules. In this study, we review the current status of the bio-based production of major C2-C6 platform chemicals, focusing on the microbial production of platform chemicals that have been used for the production of chemical intermediates, building block compounds, and polymers.

Cloning, characterization, and engineering of fungal L-arabinitol dehydrogenases.

L-Arabinitol 4-dehydrogenase (LAD) catalyzes the conversion of L-arabinitol to L-xylulose with concomitant NAD(+) reduction in fungal L-arabinose catabolism. It is an important enzyme in the development of recombinant organisms that convert L: -arabinose to fuels and chemicals. Here, we report the cloning, characterization, and engineering of four fungal LADs from Penicillium chrysogenum, Pichia guilliermondii, Aspergillus niger, and Trichoderma longibrachiatum, respectively. The LAD from P. guilliermondii was inactive, while the other three LADs were NAD(+)-dependent and showed high catalytic activities, with P. chrysogenum LAD being the most active. T. longibrachiatum LAD was the most thermally stable and showed the maximum activity in the temperature range of 55-65 degrees C with the other LADs showed the maximum activity in the temperature range of 40-50 degrees C. These LADs were active from pH 7 to 11 with an optimal pH of 9.4. Site-directed mutagenesis was used to alter the cofactor specificity of these LADs. In a T. longibrachiatum LAD mutant, the cofactor preference toward NADP(+) was increased by 2.5 x 10(4)-fold, whereas the cofactor preference toward NADP(+) of the P. chrysogenum and A. niger LAD mutants was also drastically improved, albeit at the expense of significantly reduced catalytic efficiencies. The wild-type LADs and their mutants with altered cofactor specificity could be used to investigate the functionality of the fungal L-arabinose pathways in the development of recombinant organisms for efficient microbial L-arabinose utilization.

Single-cell analysis demonstrates how nutrient deprivation creates apoptotic and quiescent cell populations in tumor cylindroids.

Understanding how quiescent and apoptotic populations form in tumors is necessary because these cell types can considerably diminish therapeutic efficacy. Most cancer therapeutics are ineffective against quiescent cells because they target rapidly proliferating cells. Distinguishing apoptosis is important because apoptotic cells are committed to death and do not require treatment. Regrowth of quiescent cell can lead to tumor re-occurrence and metastasis, which are the leading causes of cancer mortality. We hypothesized that cylindroid cultures and acridine orange staining could be used to determine how nutrient diffusion creates apoptotic and quiescent regions in tumors. To test this hypothesis we developed a microscopy technique to measure cellular DNA and RNA content in single cells using thin cylindroids and acridine orange staining. Cell classification was compared to flow cytometry of cells grown in defined monolayer cultures. The presence of apoptosis was confirmed by morphological nuclear analysis. The effect of diffusion was determined by varying incubation time, cylindroid size, and exposing cylindroids to nutrient-deficient media. Four overlapping regions were identified as a function of cylindroid radius: an outer viable/quiescent region; a second quiescent/apoptotic region; a third late-stage apoptotic region; and an inner dead region. In monolayer cultures the absence of glutamine and growth factors induced apoptosis and hypoxia induced quiescence. Treating with nutrient-deficient media suggested that cells became quiescent near the periphery because of glucose and oxygen limitations, and became apoptotic and died further from the edge because of glutamine and growth factor limitations. These results show that cellular microenvironments can be identified in cylindroids using simple acridine orange staining and that single cell fluorescence can be measured in three-dimensional culture. The developed techniques will be useful for developing cancer therapies and determining how cell death and apoptosis are induced in three-dimensional tumor tissue.

The Role of Lunate Morphology on Scapholunate Instability and Fracture Location in Patients Treated for Scaphoid Nonunion.

BACKGROUND: To determine the association between lunate morphology and the scapholunate instability using radiographic images, and investigate the association between lunate morphology and scaphoid fracture location. METHODS: Between January 2003 and December 2011, we retrospectively evaluated the plain radiographs and computed tomography (CT) images of 70 patients who underwent surgical intervention for a scaphoid nonunion, in order to determine the association between lunate type (I or II) and scapholunate instability or scaphoid fracture location. We determined the scaphoid fracture location using the fragment ratio and measured the radiolunate angle and capitate-triquetrum (C-T) distance. RESULTS: A type II lunate was present in 68.6% (48 of 70 cases). Mean fragment ratio of fracture location was 50.6% in the type II lunate group and 56.2% in the type I lunate group (p = 0.032). Sixteen of the 70 patients had dorsal intercalated segmental instability (DISI) deformities. Nine of 22 cases showed DISI deformity in type I lunate and 7 of 48 cases showed DISI deformity in type II lunate (p = 0.029). However, there were no significant differences between the presence of DISI deformity and fracture location (p = 0.15). Morphologic comparisons by both plain radiography and CT indicated a mean C-T distance in the type I lunate group (22 cases) of 2.3 mm and 5.0 mm in the type II lunate group (48 cases). The C-T distances were significantly correlated with lunate morphology (p = 0.001). CONCLUSIONS: A type II lunate was associated with low incidence of DISI deformity and proximal location of fracture in patients presenting with a scaphoid nonunion.

Reuse of imputed data in microarray analysis increases imputation efficiency.

BACKGROUND: The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. RESULTS: We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. CONCLUSIONS: Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data.

Metabolic engineering of Escherichia coli for the production of phenol from glucose.

Phenol is an industrially versatile commodity chemical and is currently produced from fossil resources. Phenol's biological production from renewable resources has been limited due to its toxicity to microorganisms. Here, we simultaneously engineered 18 Escherichia coli strains for the production of phenol using synthetic regulatory small RNA (sRNA) technology. sRNA-based knock-down of the two regulators and overexpression of the genes involved in the tyrosine biosynthetic pathway together with tyrosine phenol-lyase (TPL) in E. coli strains resulted in the production of phenol from glucose. The 18 engineered E. coli strains showed significant differences in the production of tyrosine (i.e. the immediate precursor for phenol), TPL activity, and tolerance to phenol. Among the engineered E. coli strains, the BL21 strain produced phenol most efficiently: 419 mg/L by flask culture and 1.69 g/L by fed-batch culture. The final titer and productivity were further improved through biphasic fed-batch fermentation using glycerol tributyrate as an extractant of phenol. The concentration of phenol in the glycerol tributyrate phase and fermentation broth reached 9.84 and 0.3 g/L, respectively, in 21 hours, which translates into the final phenol titer and productivity of 3.79 g/L and 0.18 g/L/h, respectively. This is the highest titer achieved by microbial fermentation. Although further engineering is required to be competitive with the current petro-based process, the strategies used for the development of the engineered strain and fermentation process will provide a valuable framework for the microbial production of toxic chemicals.

Micrometer-scale oxygen delivery rearranges cells and prevents necrosis in tumor tissue in vitro.

Oxygen availability plays a critical role in cancer progression and is correlated with poor prognosis. Despite this connection, the independent effects of oxygen gradients on tumor tissues have not been measured. To address this, we developed an oxygen delivery device that uses microelectrodes to generate oxygen directly underneath three-dimensional tumor cylindroids composed of colon carcinoma cells. The extent of cell death was measured using fluorescence staining. Supplying oxygen for 60 h eliminated the necrotic region typically found in the center of cylindroids despite the continued presence of other nutrient gradients. A mathematical model of cylindroid growth showed that the rate of cell death was more sensitive to oxygen than the growth rate. After oxygenation, a ring of dead cells was observed at the outside edge of cylindroids, and dead cells were observed moving outward from cylindroid centers. This movement suggests that dead cells were pushed by viable cells migrating in response to oxygen gradients, a mechanism that may connect transient oxygen gradients to metastasis formation. These measurements show that oxygen gradients are a primary factor governing cell viability and rearrange cells in tumors.

Tuning payload delivery in tumour cylindroids using gold nanoparticles.

Nanoparticles have great potential as controllable drug delivery vehicles because of their size and modular functionality. Timing and location are important parameters when optimizing nanoparticles for delivery of chemotherapeutics. Here, we show that gold nanoparticles carrying either fluorescein or doxorubicin molecules move and localize differently in an in vitro three-dimensional model of tumour tissue, depending on whether the nanoparticles are positively or negatively charged. Fluorescence microscopy and mathematical modelling show that uptake, not diffusion, is the dominant mechanism in particle delivery. Our results indicate that positive particles may be more effective for drug delivery because they are taken up to a greater extent by proliferating cells. Negative particles, which diffuse more quickly, may perform better when delivering drugs deep into tissues. An understanding of how surface charge can control tissue penetration and drug release may overcome some of the current limitations in drug delivery.

Flux analysis shows that hypoxia-inducible-factor-1-alpha minimally affects intracellular metabolism in tumor spheroids.

Heterogeneous metabolic microenvironments in tumors affect local cell growth, survival, and overall therapeutic efficacy. Hypoxia-inducible-factor-1alpha (HIF-1alpha) is a transcription factor that responds to low-oxygen environments by upregulating genes for cell survival and metabolism. To date, the metabolic effects of HIF-1alpha in three-dimensional tissue have not been investigated. Preliminary experiments have shown that the effects of HIF-1alpha are dependent on glucose availability. Based on this observation, we hypothesized that HIF-1alpha would not affect cell survival and metabolism in the center of spheroids, where the concentrations of oxygen and glucose are low, similar to hypoxic regions found in tumors. To test this hypothesis we used fluorescence microscopy and the tumor cylindroid model to quantify cellular viability in three-dimensional tissue. Isotope labeling and metabolic flux analysis were also used to quantity the intracellular metabolism of wild-type and HIF-1alpha-null spheroids. As hypothesized, cell survival and intracellular metabolism were not different between wild-type and HIF-1alpha-null tissues. In addition, small spheroids, which contain less quiescent cells and are less nutritionally limited, were found to have increased carbon flux through the biosynthetic pentose phosphate and pyruvate carboxylase pathways. These results show how nutrient gradients affect cell growth and metabolism in spheroids and suggest that metabolic microenvironment should be taken into account when developing HIF-1alpha-based therapies.

Glutathione-mediated delivery and release using monolayer protected nanoparticle carriers.

We demonstrate here the effective delivery of a dye payload into cells using 2-nm core gold nanoparticles, with release occurring via place exchange of glutathione onto the particle surface. In vitro experiments demonstrate effective release of drug analogues upon addition of glutathione. Cell culture experiments show rapid uptake of nanoparticle and effective release of payload. The role of glutathione in the release process was demonstrated through improved payload release upon transient increase in glutathione levels achieved via introduction of glutathione ethyl ester into the cell.