Zachary A. King

An economic and technical evaluation of microalgal biofuels

In her News Feature “Biotech’s green gold”, Emily Waltz details the ‘hype’ being propagated around emerging microalgal biofuel technologies, which often exceeds the physical and thermodynamic constraints that ultimately define their economic viability. Our calculations counter such excessive claims and demonstrate that 22 MJ m−2 d−1 solar radiation supports practical yield maxima of ∼60 to 100 kl oil ha−1 y−1 (∼6,600 to 10,800 gal ac−1 y−1) and an absolute theoretical ceiling of ∼94 to 155 kl oil ha−1 y−1, assuming a maximum photosynthetic conversion efficiency of 10%. To evaluate claims and provide an accurate analysis of the potential of microalgal biofuel systems, we have conducted industrial feasibility studies and sensitivity analyses based on peer-reviewed data and industrial expertise. Given that microalgal biofuel research is still young and its development still in flux, we anticipate that the stringent assessment of the technologys economic potential presented below will assist R&D investment and policy development in the area going forward.

Constraint-based models predict metabolic and associated cellular functions

The prediction of cellular function from a genotype is a fundamental goal in biology. For metabolism, constraint-based modelling methods systematize biochemical, genetic and genomic knowledge into a mathematical framework that enables a mechanistic description of metabolic physiology. The use of constraint-based approaches has evolved over ~30 years, and an increasing number of studies have recently combined models with high-throughput data sets for prospective experimentation. These studies have led to validation of increasingly important and relevant biological predictions. As reviewed here, these recent successes have tangible implications in the fields of microbial evolution, interaction networks, genetic engineering and drug discovery.

In Vitro and In Vivo Evaluation of PEDOT Microelectrodes for Neural Stimulation and Recording

Cortical neural prostheses require chronically implanted small-area microelectrode arrays that simultaneously record and stimulate neural activity. It is necessary to develop new materials with low interface impedance and large charge transfer capacity for this application and we explore the use of conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) for the same. We subjected PEDOT coated electrodes to voltage cycling between -0.6 and 0.8 V, 24 h continuous biphasic stimulation at 3 mC/cm2 and accelerated aging for four weeks. Characterization was performed using cyclic voltammetry, electrochemical impedance spectroscopy, and voltage transient measurements. We found that PEDOT coated electrodes showed a charge injection limit 15 times higher than Platinum Iridium (Ptlr) electrodes and electroplated Iridium Oxide (IrOx) electrodes when using constant current stimulation at zero voltage bias. In vivo chronic testing of microelectrode arrays implanted in rat cortex revealed that PEDOT coated electrodes show higher signal-to-noise recordings and superior charge injection compared to Ptlr electrodes.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repositories of high-quality models must be established, models must adhere to established standards and model components must be linked to relevant databases. Tools for model visualization further enhance their utility. To meet these needs, we present BiGG Models (http://bigg.ucsd.edu), a completely redesigned Biochemical, Genetic and Genomic knowledge base. BiGG Models contains more than 75 high-quality, manually-curated genome-scale metabolic models. On the website, users can browse, search and visualize models. BiGG Models connects genome-scale models to genome annotations and external databases. Reaction and metabolite identifiers have been standardized across models to conform to community standards and enable rapid comparison across models. Furthermore, BiGG Models provides a comprehensive application programming interface for accessing BiGG Models with modeling and analysis tools. As a resource for highly curated, standardized and accessible models of metabolism, BiGG Models will facilitate diverse systems biology studies and support knowledge-based analysis of diverse experimental data.

The Morphology of Poly(3,4-Ethylenedioxythiophene)

Poly(3,4-ethylene dioxythiophene) (PEDOT) is a chemically stable, conjugated polymer that is of considerable interest for a variety of applications including coatings for interfacing electronic biomedical devices with living tissue. Here, we describe recent work from our laboratory and elsewhere to investigate the morphology of PEDOT in the solid state. We discuss the importance of oxidative chemical and electrochemical polymerization, as well as the critical role of the counterion used during synthesis and film deposition. We have obtained information about the morphology of PEDOT from a number of different complimentary techniques including X-ray diffraction, optical microscopy, scanning electron microscopy, transmission high-resolution electron microscopy, and low-voltage electron microscopy. We also discuss results from ultraviolet-visible light spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). PEDOT is a relatively rigid polymer that packs in the solid state at a characteristic face-to-face distance (010) of ∼0.34 nm, similar to graphite. These sheets of oriented PEDOT molecules are separated from one another by ∼1.4 nm laterally, with the (100) distance between layers quite sensitive to the choice of counterion used during sample preparation. The order in the films is typically modest, although this also depends on the counterion used and the method of film deposition. The films can be organized into useful structures with a variety of nanoscale dissolvable templates (including fibers, particles, and lyotropic mesophases). When PEDOT is electrochemically deposited in the presence of bromine counterions, highly ordered crystalline phases are observed. It is also possible to deposit PEDOT around living cells, both in vitro and in vivo.

Next-generation genome-scale models for metabolic engineering.

Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict optimal genetic modifications that improve the rate and yield of chemical production. A new generation of COBRA models and methods is now being developed--encompassing many biological processes and simulation strategies-and next-generation models enable new types of predictions. Here, three key examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering.

Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways

Escher is a web application for visualizing data on biological pathways. Three key features make Escher a uniquely effective tool for pathway visualization. First, users can rapidly design new pathway maps. Escher provides pathway suggestions based on user data and genome-scale models, so users can draw pathways in a semi-automated way. Second, users can visualize data related to genes or proteins on the associated reactions and pathways, using rules that define which enzymes catalyze each reaction. Thus, users can identify trends in common genomic data types (e.g. RNA-Seq, proteomics, ChIP)—in conjunction with metabolite- and reaction-oriented data types (e.g. metabolomics, fluxomics). Third, Escher harnesses the strengths of web technologies (SVG, D3, developer tools) so that visualizations can be rapidly adapted, extended, shared, and embedded. This paper provides examples of each of these features and explains how the development approach used for Escher can be used to guide the development of future visualization tools.

Sexual dimorphism and steroid responsiveness of the posterodorsal medial amygdala in adult mice

The posterodorsal aspect of the medial amygdala (MePD) is sexually dimorphic in regional volume, rostrocaudal extent, and neuronal soma size in rats. These dimorphisms are maintained by circulating gonadal hormones, as castration of adult male rats reduces MePD measures, while testosterone treatment of females increases them. We now report that the MePD is also sexually dimorphic in volume, rostrocaudal extent, and somal area in BALB/c mice. Four weeks after castration of adult male mice, MePD regional volume and soma size are reduced, but rostrocaudal extent is not, compared to sham-castrated males. Treatment of adult ovariectomized females with an aromatized metabolite of testosterone, estradiol, for 8 weeks increased MePD volume and soma size, but not rostrocaudal extent. To probe the possible role of afferents in the steroid-induced plasticity of the MePD, we examined the effect of removing the olfactory bulbs in gonadally intact males and in estrogen-treated females. Bulbectomy had no effect on MePD morphology with one exception: among gonadally intact males, neuronal soma size was slightly smaller in the right MePD of bulbectomized males compared to males with intact bulbs. These results indicate that the sexual dimorphism and hormone responsiveness of the MePD that has been extensively studied in rats is also present in mice, which offers genetic tools for future research. We detected little or no evidence that olfactory bulb afferents play a role in maintaining MePD morphology in adult mice.

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

A model‐driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K‐12 MG1655 that is biochemically and thermodynamically consistent

The advent of model‐enabled workflows in systems biology allows for the integration of experimental data types with genome‐scale models to discover new features of biology. This work demonstrates such a workflow, aimed at establishing a metabolomics platform applied to study the differences in metabolomes between anaerobic and aerobic growth of Escherichia coli. Constraint‐based modeling was utilized to deduce a target list of compounds for downstream method development. An analytical and experimental methodology was developed and tailored to the compound chemistry and growth conditions of interest. This included the construction of a rapid sampling apparatus for use with anaerobic cultures. The resulting genome‐scale data sets for anaerobic and aerobic growth were validated by comparison to previous small‐scale studies comparing growth of E. coli under the same conditions. The metabolomics data were then integrated with the E. coli genome‐scale metabolic model (GEM) via a sensitivity analysis that utilized reaction thermodynamics to reconcile simulated growth rates and reaction directionalities. This analysis highlighted several optimal network usage inconsistencies, including the incorrect use of the beta‐oxidation pathway for synthesis of fatty acids. This analysis also identified enzyme promiscuity for the pykA gene, that is critical for anaerobic growth, and which has not been previously incorporated into metabolic models of E coli. Biotechnol. Bioeng. 2014;111: 803–815.