James Winkler

Performance assessment of topologically diverse power systems subjected to hurricane events

Large tropical cyclones cause severe damage to major cities along the United States Gulf Coast annually. A diverse collection of engineering and statistical models are currently used to estimate the geographical distribution of power outage probabilities stemming from these hurricanes to aid in storm preparedness and recovery efforts. Graph theoretic studies of power networks have separately attempted to link abstract network topology to transmission and distribution system reliability. However, few works have employed both techniques to unravel the intimate connection between network damage arising from storms, topology, and system reliability. This investigation presents a new methodology combining hurricane damage predictions and topological assessment to characterize the impact of hurricanes upon power system reliability. Component fragility models are applied to predict failure probability for individual transmission and distribution power network elements simultaneously. The damage model is calibrated using power network component failure data for Harris County, TX, USA caused by Hurricane Ike in September of 2008, resulting in a mean outage prediction error of 15.59% and low standard deviation. Simulated hurricane events are then applied to measure the hurricane reliability of three topologically distinct transmission networks. The rate of system performance decline is shown to depend on their topological structure. Reliability is found to correlate directly with topological features, such as network meshedness, centrality, and clustering, and the compact irregular ring mesh topology is identified as particularly favorable, which can influence regional lifeline policy for retrofit and hardening activities to withstand hurricane events.

Visualizing evolution in real time to determine the molecular mechanisms of n-butanol tolerance in Escherichia coli ☆

Toxicity of products or feedstock components poses a challenge in the biocatalyst-based production of fuels and chemicals. The genetic determinants that are involved in increased resistance to an inhibitor form the adaptive landscape for the phenotype; so in order to engineer more robust biocatalysts, a better understanding of the adaptive landscape is required. Here, we used an adaptive laboratory evolution method called visualizing evolution in real time (VERT) to help map out part of the adaptive landscape of Escherichia coli tolerance to the biofuel n-butanol. VERT enables identification of adaptive events (population expansions triggered by adaptive mutants) via visualization of the relative proportions of different fluorescently-labeled cells. Knowledge of the occurrence of adaptive events allows for a more systematic isolation of adaptive mutants while simultaneously reducing the number of missed adaptive mutants (and the underlying adaptive mechanisms) that result from clonal interference during the course of in vitro evolution. Based on the evolutionary dynamics observed, clonal interference was found to play a significant role in shaping the population structure of E. coli during exposure to n-butanol, and VERT helped to facilitate the isolation of adaptive mutants from the population. We further combined adaptive laboratory evolution with genome shuffling to significantly enhance the desired n-butanol tolerance phenotype. Subsequent transcriptome analysis of the isolated adaptive mutants revealed different mechanisms of n-butanol resistance in different lineages. In one fluorescently-marked subpopulation, members of the Fur regulon were upregulated; which was not observed in the other subpopulation. In addition, genome sequencing of several adaptive mutants revealed the genetic basis for some of the observed transcriptome profiles. We further elucidated the potential role of the iron-related gene in n-butanol tolerance via overexpression and deletion studies and hypothesized that the upregulation of the iron-related genes indirectly led to modifications in the outer membrane, which contributed to enhanced n-butanol tolerance.

Transcriptional analysis of Lactobacillus brevis to N-butanol and ferulic acid stress responses.

Background The presence of anti-microbial phenolic compounds, such as the model compound ferulic acid, in biomass hydrolysates pose significant challenges to the widespread use of biomass in conjunction with whole cell biocatalysis or fermentation. Currently, these inhibitory compounds must be removed through additional downstream processing or sufficiently diluted to create environments suitable for most industrially important microbial strains. Simultaneously, product toxicity must also be overcome to allow for efficient production of next generation biofuels such as n-butanol, isopropanol, and others from these low cost feedstocks. Methodology and Principal Findings This study explores the high ferulic acid and n-butanol tolerance in Lactobacillus brevis, a lactic acid bacterium often found in fermentation processes, by global transcriptional response analysis. The transcriptional profile of L. brevis reveals that the presence of ferulic acid triggers the expression of currently uncharacterized membrane proteins, possibly in an effort to counteract ferulic acid induced changes in membrane fluidity and ion leakage. In contrast to the ferulic acid stress response, n-butanol challenges to growing cultures primarily induce genes within the fatty acid synthesis pathway and reduced the proportion of 19∶1 cyclopropane fatty acid within the L. brevis membrane. Both inhibitors also triggered generalized stress responses. Separate attempts to alter flux through the Escherichia coli fatty acid synthesis by overexpressing acetyl-CoA carboxylase subunits and deleting cyclopropane fatty acid synthase (cfa) both failed to improve n-butanol tolerance in E. coli, indicating that additional components of the stress response are required to confer n-butanol resistance. Conclusions Several promising routes for understanding both ferulic acid and n-butanol tolerance have been identified from L. brevis gene expression data. These insights may be used to guide further engineering of model industrial organisms to better tolerate both classes of inhibitors to enable facile production of biofuels from lignocellulosic biomass.

Recent advances in the evolutionary engineering of industrial biocatalysts.

Evolutionary engineering has been used to improve key industrial strain traits, such as carbon source utilization, tolerance to adverse environmental conditions, and resistance to chemical inhibitors, for many decades due to its technical simplicity and effectiveness. The lack of need for prior genetic knowledge underlying the phenotypes of interest makes this a powerful approach for strain development for even species with minimal genotypic information. While the basic experimental procedure for laboratory adaptive evolution has remained broadly similar for many years, a range of recent advances show promise for improving the experimental workflows for evolutionary engineering by accelerating the pace of evolution, simplifying the analysis of evolved mutants, and providing new ways of linking desirable phenotypes to selectable characteristics. This review aims to highlight some of these recent advances and discuss how they may be used to improve industrially relevant microbial phenotypes.

Evolved osmotolerant Escherichia coli mutants frequently exhibit defective N-acetylglucosamine catabolism and point mutations in cell shape-regulating protein MreB.

ABSTRACT Biocatalyst robustness toward stresses imposed during fermentation is important for efficient bio-based production. Osmotic stress, imposed by high osmolyte concentrations or dense populations, can significantly impact growth and productivity. In order to better understand the osmotic stress tolerance phenotype, we evolved sexual (capable of in situ DNA exchange) and asexual Escherichia coli strains under sodium chloride (NaCl) stress. All isolates had significantly improved growth under selection and could grow in up to 0.80 M (47 g/liter) NaCl, a concentration that completely inhibits the growth of the unevolved parental strains. Whole genome resequencing revealed frequent mutations in genes controlling N-acetylglucosamine catabolism (nagC, nagA), cell shape (mrdA, mreB), osmoprotectant uptake (proV), and motility (fimA). Possible epistatic interactions between nagC, nagA, fimA, and proV deletions were also detected when reconstructed as defined mutations. Biofilm formation under osmotic stress was found to be decreased in most mutant isolates, coupled with perturbations in indole secretion. Transcriptional analysis also revealed significant changes in ompACGL porin expression and increased transcription of sulfonate uptake systems in the evolved mutants. These findings expand our current knowledge of the osmotic stress phenotype and will be useful for the rational engineering of osmotic tolerance into industrial strains in the future.

Interface Network Models for Complex Urban Infrastructure Systems

The reliability assessment of infrastructure systems providing power, natural gas, and potable water is an integral part of societal preparedness to unforeseen hazards. The topological properties of interface networks connecting electric substations to water pumping stations and natural gas compressors have received little attention, despite the key role these connections play in operation and failure propagation. This work introduces a performance assessment methodology for coupled infrastructures that links physical fragility modeling with the topology of realistic and ideal connecting interfaces. Distinct interfaces based on features such as betweenness, clustering, vertex degree, and Euclidean distance are assessed regarding their role in connecting utility systems and propagating failures from random and hurricane events in Harris County, Texas. The interface minimizing the Euclidean distance between electric substations and other utility nodes exhibits a slow performance decline as random failures increase, and retains the greatest functionality under hurricane events compared to alternative interfaces, although it suffers from limited efficiency and controllability during normal operation. A convenient hybrid interface using both betweenness and distance features shows adequate performance during normal operation while exhibiting tolerance to random failures and sufficient performance at increasing hurricane event levels. These findings provide utility owners and operators with new simple yet adequate strategies focused on the interface across complex systems to enhance routine operation and reduce the probability of widespread interdependent failures following disruptive events.

Novel Escherichia coli hybrids with enhanced butanol tolerance

Hybrids between Escherichia coli and Lactobacillus brevis were generated via protoplast fusion. Growth kinetics of five hybrid strains and E. coli were used to evaluate the butanol tolerance of the novel strains under different conditions. The hybrid strains tolerated up to 2% (v/v) butanol compared to the 1% (v/v) maximum for E. coli. The growth inhibitory effects of butanol were also significantly less in several of the hybrids compared to E. coli. These results demonstrate the potential use of protoplast fusion to generate butanol-tolerant strains.

Harnessing recombination to speed adaptive evolution in Escherichia coli

Evolutionary engineering typically involves asexual propagation of a strain to improve a desired phenotype. However, asexual populations suffer from extensive clonal interference, a phenomenon where distinct lineages of beneficial clones compete and are often lost from the population given sufficient time. Improved adaptive mutants can likely be generated by genetic exchange between lineages, thereby reducing clonal interference. We present a system that allows continuous in situ recombination by using an Esherichia coli F-based conjugation system lacking surface exclusion. Evolution experiments revealed that Hfr-mediated recombination significantly speeds adaptation in certain circumstances. These results show that our system is stable, effective, and suitable for use in evolutionary engineering applications.

Adaptive Laboratory Evolution for Strain Engineering

Complex phenotypes, such as tolerance to growth inhibitors, are difficult to rationally engineer into industrial model organisms due our poor understanding of their underlying molecular mechanisms. Adaptive evolution circumvents this issue by exploiting the linkage between growth rate and inhibitor resistance to select for mutants with enhanced tolerance. In order to aid experimentalists in the design and execution of adaptive laboratory evolution, we present detailed protocols for batch, continuous, and visualizing evolution in real-time (VERT) approaches to this technique.

Visualizing evolution in real-time method for strain engineering.

The adaptive landscape for an industrially relevant phenotype is determined by the effects of the genetic determinants on the fitness of the microbial system. Identifying the underlying adaptive landscape for a particular phenotype of interest will greatly enhance our abilities to engineer more robust microbial strains. Visualizing evolution in real-time (VERT) is a recently developed method based on in vitro adaptive evolution that facilitates the identification of fitter mutants throughout the course of evolution. Combined with high-throughput genomic tools, VERT can greatly enhance the mapping of adaptive landscapes of industrially relevant phenotypes in microbial systems, thereby expanding our knowledge on the parameters that can be used for strain engineering.