Phenotypic diversity as a tool to guide and optimize random strain improvement approaches

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2009.Includes bibliographical references (leaves 258-298).A sustainable economy will depend, if only partly, on efficient renewable-feedstock conversion to chemicals and fuels, and advances in that direction have relied and will continue to rely on strain engineering. Traditional methods comprising directed genetic modifications (i.e. targeting specific genes) have been quite successful in improving several phenotypes of industrial interest. Evolutionary approaches have also contributed much to these efforts and are gaining attention in particular for addressing complex phenotypes. Most commonly, mutagenesis and selection has been the method of choice, but many other random search-based approaches for phenotypic alteration have been developed in recent years. One such method, transcriptional engineering, relies on transcriptome-wide modifications that can be exploited to better complex traits. The initial aim of this work was to build upon the idea of transcriptional engineering in bacteria, which had been tried in our laboratory through mutagenesis of the principal sigma factor, sigma D. Initially, we explored new targets for transcriptional engineering. Using error-prone PCR, we constructed libraries of several stress-related sigma factors in Escherichia coli (sigma S, sigma E, and sigma H) and screened them for phenotypes of interest. We also considered the alpha subunit of the RNA polymerase as a tool for phenotypic alteration, and fruitfully used it to improve butanol and solvent tolerance, accumulation of hyaluronic acid, and L-tyrosine production.(cont.) Carefull assessment of the sigma and alpha libraries for a few phenotypes revealed that not all the targets were equally useful, and that succeeding at improving one trait does not imply that the same target could be used to improve a different one. We also extended the use of the already-proven target, sigma D, to a new species, Lactobacillus plantarum. We constructed random mutagenesis libraries of this gene and produced a cell library that was selected in conditions relevant to the production of lactic acid. This chemical has attracted attention for its use as a food and pharmaceutical additive, and in the production of specialty chemicals and biodegradable plastics. We isolated two mutants with significantly higher growth rates in media acidified with both lactic and hydrochloric acid, one of which is also better at fermenting lactic acid at low pH. The mixed results obtained during our target search forced us to re-frame the question of what constitutes a useful library for phenotypic alteration. We hypothesized that the phenotypic diversity of a library could be quantified and used to evaluate the potential of different populations for strain improvement. After developing the conceptual framework to support it, we proposed a metric to estimate phenotypic diversity and showed that it correlates with the usefulness of a library with regard to finding an improved mutant. The metric, termed divergence, can be used to assess the potential of different targets, to prioritize and economize screening experiments, and, as we later proved, to optimize the construction of libraries.(cont.) The usefulness of evolutionary methods is often times muddled by the element of chance, and more so because failing to isolate an improved mutant does not suggest a modification to the experimental approach. With this in mind, we tested whether the divergence metric could be used to systematize the construction of new libraries when screening or selection of a previous library fails to deliver mutants improved for a trait of interest. We used the metric for successively modifying the alpha subunit library design until a mutant of interest was isolated. We showed that this effort increases the likelihood of finding desired clones, in our case, a butyrate-tolerant mutant that grows significantly faster in the presence of the toxic chemical compared to the wild-type. An optimized library, in which surface amino acids of the C-terminal domain of alpha were targeted for mutagenesis, was constructed by gathering the information about how modifications to the library design affected the resulting divergence. We repeated the approach with the sigma D libraries, and considerably enhanced the diversity by targeting regions 4.1 and 4.2 of this protein for mutagenesis. We used the novel sigma factor libraries to improve tolerance to the simultaneous stresses of overlimed bagasse hydrolysate and high concentrations of ethanol. Lastly, we explored the use of our divergence metric to study key determinants of regulatory proteins (residues, regions, structures, or functionalities) that have a high potential for altering phenotype.(cont.) We modified our divergence quantification protocol to test whether individual amino acids in the alpha subunit could be experimentally considered as determinants for diversity. We showed that not only can single residues be probed individually, but also that, by testing the phenotypic diversity produced by saturation mutagenesis at different positions, we could find regions and functionalities that are promising for further studies. We proposed this as a novel way for reducing the search space in a particular target for the purpose of increasing the quality of a library. What started as an effort to improve upon transcriptional engineering, soon evolved into a general approach to optimize random search-based methods for isolating traits of interest. We demonstrated the use of this approach for guiding the construction of transcriptional engineering libraries, and in addition outlined the conceptual framework for extending this work to any genetic library. As such, the work of this thesis served both theoretical and practical goals, and furthered the understanding of how evolution can be exploited in the laboratoryby Daniel Klein-Marcuschamer.Ph.D

Computational identification of adaptive mutants using the VERT system

<p/> <p>Background</p> <p>Evolutionary dynamics of microbial organisms can now be visualized using the Visualizing Evolution in Real Time (VERT) system, in which several isogenic strains expressing different fluorescent proteins compete during adaptive evolution and are tracked using fluorescent cell sorting to construct a population history over time. Mutations conferring enhanced growth rates can be detected by observing changes in the fluorescent population proportions.</p> <p>Results</p> <p>Using data obtained from several VERT experiments, we construct a hidden Markov-derived model to detect these adaptive events in VERT experiments without external intervention beyond initial training. Analysis of annotated data revealed that the model achieves consensus with human annotation for 85-93% of the data points when detecting adaptive events. A method to determine the optimal time point to isolate adaptive mutants is also introduced.</p> <p>Conclusions</p> <p>The developed model offers a new way to monitor adaptive evolution experiments without the need for external intervention, thereby simplifying adaptive evolution efforts relying on population tracking. Future efforts to construct a fully automated system to isolate adaptive mutants may find the algorithm a useful tool.</p

Simultaneous saccharification and fermentation of steam exploded duckweed: Improvement of the ethanol yield by increasing yeast titre

This study investigated the conversion of Lemna minor biomass to bioethanol. The biomass was pre-treated by steam explosion (SE, 210 °C, 10 min) and then subjected to simultaneous saccharification and fermentation (SSF) using CellicÒ CTec 2 (20 U or 0.87 FPU gﰂ1 substrate) cellulase plus b-glucosidase (2 U gﰂ1 substrate) and a yeast inoculum of 10% (v/v or 8.0 ﰀ 107 cells mLﰂ1). At a substrate concentration of 1% (w/v) an ethanol yield of 80% (w/w, theoretical) was achieved. However at a substrate concentration of 20% (w/v), the ethanol yield was lowered to 18.8% (w/w, theoretical). Yields were considerably improved by increasing the yeast titre in the inoculum or preconditioning the yeast on steam exploded liquor. These approaches enhanced the ethanol yield up to 70% (w/w, theoretical) at a substrate concen- tration of 20% (w/v) by metabolising fermentation inhibitors

Design of low-cost ionic liquids for lignocellulosic biomass pretreatment

The cost of ionic liquids (ILs) is one of the main impediments to IL utilization in the cellulosic biorefinery, especially in the pretreatment step. In this study, a number of ionic liquids were synthesized with the goal of optimizing solvent cost and stability whilst demonstrating promising processing potential. To achieve this, inexpensive feedstocks such as sulfuric acid and simple amines were combined into a range of protic ionic liquids containing the hydrogen sulfate [HSO] anion. The performance of these ionic liquids was compared to a benchmark system containing the IL 1-ethyl-3-methylimidazolium acetate [CCim][OAc]. The highest saccharification yields were observed for the triethylammonium hydrogen sulfate IL, which was 75% as effective as the benchmark system. Techno-economic modeling revealed that this promising and yet to be optimized yield was achieved at a fraction of the processing cost. This study demonstrates that some ILs can compete with the cheapest pretreatment chemicals, such as ammonia, in terms of effectiveness and process cost, removing IL cost as a barrier to the economic viability of IL-based biorefineries

Development of an estimation model for the evaluation of the energy requirement of dilute acid pretreatments of biomass

This study aims to develop a mathematical model to evaluate the energy required by pretreatment processes used in the production of second generation ethanol. A dilute acid pretreatment process reported by National Renewable Energy Laboratory (NREL) was selected as an example for the model's development. The energy demand of the pretreatment process was evaluated by considering the change of internal energy of the substances, the reaction energy, the heat lost and the work done to/by the system based on a number of simplifying assumptions. Sensitivity analyses were performed on the solid loading rate, temperature, acid concentration and water evaporation rate. The results from the sensitivity analyses established that the solids loading rate had the most significant impact on the energy demand. The model was then verified with data from the NREL benchmark process. Application of this model on other dilute acid pretreatment processes reported in the literature illustrated that although similar sugar yields were reported by several studies, the energy required by the different pretreatments varied significantly

Isoprenoid Pathway Optimization for Taxol Precursor Overproduction in Escherichia coli

Author Manuscript February 6, 2011Taxol (paclitaxel) is a potent anticancer drug first isolated from the Taxus brevifolia Pacific yew tree. Currently, cost-efficient production of Taxol and its analogs remains limited. Here, we report a multivariate-modular approach to metabolic-pathway engineering that succeeded in increasing titers of taxadiene—the first committed Taxol intermediate—approximately 1 gram per liter (~15,000-fold) in an engineered Escherichia coli strain. Our approach partitioned the taxadiene metabolic pathway into two modules: a native upstream methylerythritol-phosphate (MEP) pathway forming isopentenyl pyrophosphate and a heterologous downstream terpenoid–forming pathway. Systematic multivariate search identified conditions that optimally balance the two pathway modules so as to maximize the taxadiene production with minimal accumulation of indole, which is an inhibitory compound found here. We also engineered the next step in Taxol biosynthesis, a P450-mediated 5α-oxidation of taxadiene to taxadien-5α-ol. More broadly, the modular pathway engineering approach helped to unlock the potential of the MEP pathway for the engineered production of terpenoid natural products

Recent advances in production of lignocellulolytic enzymes by solid-state fermentation of agro-industrial wastes

Agricultural, forestry, and food industries produce large amounts of lignocellulosic wastes every year. Land disposal of these residues without proper treatment leads to environmental pollution and negative health effects. The recent advances in valorization of agro-industrial wastes by the production of lignocellulolytic enzymes under solid-state fermentation (SSF) are reviewed. SSF is a promising technology to produce lignocellulolytic enzymes. However, the large-scale feasibility is the main challenge of SSF being the control of operational parameters and adequate reactor design the first locks. The current and future trends of SSF bioreactors for lignocellulolytic enzyme production are summarized. SSF allows the production of lignocellulolytic enzymes with high stability at different temperatures and pH, improving their applicability in different industrial settings.This work was supported by the project ‘Development of innovative sustainable protein and omega-3 rich feedstuffs for aquafeeds, from local agroindustrial by-products,’ reference POCI-01-0145-FEDER-030377, funded by European Regional Development Fund (ERDF). JMS was supported by contract from this project. This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. PL was supported by the PhD grant (SFRH/BD/114777/2016) funded by FCT. DS was supported by the doctoral programme ‘Agricultural Production Chains e from fork to farm’ (PD/ 00122/2012). HF was supported by the PhD grant SFRH/BD/131219/2017, and MF was funded by SFRH/BD/143614/2019, both funded by FCT. MG and DF were supported by project InovFeed (ref. MAR-02.01.01-FEAMP0111; Mar2020).info:eu-repo/semantics/publishedVersio