Peter B. Otoupal

Harnessing Yarrowia lipolytica lipogenesis to create a platform for lipid and biofuel production

Economic feasibility of biosynthetic fuel and chemical production hinges upon harnessing metabolism to achieve high titre and yield. Here we report a thorough genotypic and phenotypic optimization of an oleaginous organism to create a strain with significant lipogenesis capability. Specifically, we rewire Yarrowia lipolyticas native metabolism for superior de novo lipogenesis by coupling combinatorial multiplexing of lipogenesis targets with phenotypic induction. We further complete direct conversion of lipid content into biodiesel. Tri-level metabolic control results in saturated cells containing upwards of 90% lipid content and titres exceeding 25 g l(-1) lipids, which represents a 60-fold improvement over parental strain and conditions. Through this rewiring effort, we advance fundamental understanding of lipogenesis, demonstrate non-canonical environmental and intracellular stimuli and uncouple lipogenesis from nitrogen starvation. The high titres and carbon-source independent nature of this lipogenesis in Y. lipolytica highlight the potential of this organism as a platform for efficient oleochemical production.

Surveying the lipogenesis landscape in Yarrowia lipolytica through understanding the function of a Mga2p regulatory protein mutant

Lipogenic organisms represent great starting points for metabolic engineering of oleochemical production. While previous engineering efforts were able to significantly improve lipid production in Yarrowia lipolytica, the lipogenesis landscape, especially with respect to regulatory elements, has not been fully explored. Through a comparative genomics and transcriptomics approach, we identified and validated a mutant mga2 protein that serves as a regulator of desaturase gene expression and potent lipogenesis factor. The resulting strain is enriched in unsaturated fatty acids. Comparing the underlying mechanism of this mutant to other previously engineered strains suggests that creating an imbalance between glycolysis and the TCA cycle can serve as a driving force for lipogenesis when combined with fatty acid catabolism overexpressions. Further comparative transcriptomics analysis revealed both distinct and convergent rewiring associated with these different genotypes. Finally, by combining metabolic engineering targets, it is possible to further engineer a strain containing the mutant mga2 gene to a lipid production titer of 25g/L.

CRISPR Perturbation of Gene Expression Alters Bacterial Fitness under Stress and Reveals Underlying Epistatic Constraints

The evolution of antibiotic resistance has engendered an impending global health crisis that necessitates a greater understanding of how resistance emerges. The impact of nongenetic factors and how they influence the evolution of resistance is a largely unexplored area of research. Here we present a novel application of CRISPR-Cas9 technology for investigating how gene expression governs the adaptive pathways available to bacteria during the evolution of resistance. We examine the impact of gene expression changes on bacterial adaptation by constructing a library of deactivated CRISPR-Cas9 synthetic devices to tune the expression of a set of stress-response genes in Escherichia coli. We show that artificially inducing perturbations in gene expression imparts significant synthetic control over fitness and growth during stress exposure. We present evidence that these impacts are reversible; strains with synthetically perturbed gene expression regained wild-type growth phenotypes upon stress removal, while maintaining divergent growth characteristics under stress. Furthermore, we demonstrate a prevailing trend toward negative epistatic interactions when multiple gene perturbations are combined simultaneously, thereby posing an intrinsic constraint on gene expression underlying adaptive trajectories. Together, these results emphasize how CRISPR-Cas9 can be employed to engineer gene expression changes that shape bacterial adaptation, and present a novel approach to synthetically control the evolution of antimicrobial resistance.

Gene Expression Variability Underlies Adaptive Resistance in Phenotypically Heterogeneous Bacterial Populations

The root cause of the antibiotic resistance crisis is the ability of bacteria to evolve resistance to a multitude of antibiotics and other environmental toxins. The regulation of adaptation is difficult to pinpoint due to extensive phenotypic heterogeneity arising during evolution. Here, we investigate the mechanisms underlying general bacterial adaptation by evolving wild-type Escherichia coli populations to dissimilar chemical toxins. We demonstrate the presence of extensive inter- and intrapopulation phenotypic heterogeneity across adapted populations in multiple traits, including minimum inhibitory concentration, growth rate, and lag time. To search for a common response across the heterogeneous adapted populations, we measured gene expression in three stress-response networks: the mar regulon, the general stress response, and the SOS response. While few genes were differentially expressed, clustering revealed that interpopulation gene expression variability in adapted populations was distinct from that of unadapted populations. Notably, we observed both increases and decreases in gene expression variability upon adaptation. Sequencing select genes revealed that the observed gene expression trends are not necessarily attributable to genetic changes. To further explore the connection between gene expression variability and adaptation, we propagated single-gene knockout and CRISPR (clustered regularly interspaced short palindromic repeats) interference strains and quantified impact on adaptation to antibiotics. We identified significant correlations that suggest genes with low expression variability have greater impact on adaptation. This study provides evidence that gene expression variability can be used as an indicator of bacterial adaptive resistance, even in the face of the pervasive phenotypic heterogeneity underlying adaptation.

Transcriptome-Level Signatures in Gene Expression and Gene Expression Variability during Bacterial Adaptive Evolution

Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress response processes known as adaptive resistance. Adaptive resistance fosters transient tolerance increases and the emergence of mutations conferring heritable drug resistance. In order to extend the applicable lifetime of new antibiotics, we must seek to hinder the occurrence of bacterial adaptive resistance; however, the regulation of adaptation is difficult to identify due to immense heterogeneity emerging during evolution. This study specifically seeks to generate heterogeneity by adapting bacteria to different stresses and then examines gene expression trends across the disparate populations in order to pinpoint key genes and pathways associated with adaptive resistance. The targets identified here may eventually inform strategies for impeding adaptive resistance and prolonging the effectiveness of antibiotic treatment. ABSTRACT Antibiotic-resistant bacteria are an increasingly serious public health concern, as strains emerge that demonstrate resistance to almost all available treatments. One factor that contributes to the crisis is the adaptive ability of bacteria, which exhibit remarkable phenotypic and gene expression heterogeneity in order to gain a survival advantage in damaging environments. This high degree of variability in gene expression across biological populations makes it a challenging task to identify key regulators of bacterial adaptation. Here, we research the regulation of adaptive resistance by investigating transcriptome profiles of Escherichia coli upon adaptation to disparate toxins, including antibiotics and biofuels. We locate potential target genes via conventional gene expression analysis as well as using a new analysis technique examining differential gene expression variability. By investigating trends across the diverse adaptation conditions, we identify a focused set of genes with conserved behavior, including those involved in cell motility, metabolism, membrane structure, and transport, and several genes of unknown function. To validate the biological relevance of the observed changes, we synthetically perturb gene expression using clustered regularly interspaced short palindromic repeat (CRISPR)-dCas9. Manipulation of select genes in combination with antibiotic treatment promotes adaptive resistance as demonstrated by an increased degree of antibiotic tolerance and heterogeneity in MICs. We study the mechanisms by which identified genes influence adaptation and find that select differentially variable genes have the potential to impact metabolic rates, mutation rates, and motility. Overall, this work provides evidence for a complex nongenetic response, encompassing shifts in gene expression and gene expression variability, which underlies adaptive resistance. IMPORTANCE Even initially sensitive bacteria can rapidly thwart antibiotic treatment through stress response processes known as adaptive resistance. Adaptive resistance fosters transient tolerance increases and the emergence of mutations conferring heritable drug resistance. In order to extend the applicable lifetime of new antibiotics, we must seek to hinder the occurrence of bacterial adaptive resistance; however, the regulation of adaptation is difficult to identify due to immense heterogeneity emerging during evolution. This study specifically seeks to generate heterogeneity by adapting bacteria to different stresses and then examines gene expression trends across the disparate populations in order to pinpoint key genes and pathways associated with adaptive resistance. The targets identified here may eventually inform strategies for impeding adaptive resistance and prolonging the effectiveness of antibiotic treatment.

Decaffeination and measurement of caffeine content by addicted escherichia coli with a refactored N-demethylation operon from pseudomonas putida CBB5

The widespread use of caffeine (1,3,7-trimethylxanthine) and other methylxanthines in beverages and pharmaceuticals has led to significant environmental pollution. We have developed a portable caffeine degradation operon by refactoring the alkylxanthine degradation (Alx) gene cluster from Pseudomonas putida CBB5 to function in Escherichia coli. In the process, we discovered that adding a glutathione S-transferase from Janthinobacterium sp. Marseille was necessary to achieve N 7 -demethylation activity. E. coli cells with the synthetic operon degrade caffeine to the guanine precursor, xanthine. Cells deficient in de novo guanine biosynthesis that contain the refactored operon are ″addicted″ to caffeine: their growth density is limited by the availability of caffeine or other xanthines. We show that the addicted strain can be used as a biosensor to measure the caffeine content of common beverages. The synthetic N-demethylation operon could be useful for reclaiming nutrient-rich byproducts of coffee bean processing and for the cost-effective bioproduction of methylxanthine drugs.

Multiplexed deactivated CRISPR-Cas9 gene expression perturbations deter bacterial adaptation by inducing negative epistasis

The ever-increasing threat of multi-drug resistant bacteria, a shrinking antibiotic pipeline, and the innate ability of microorganisms to adapt necessitates long-term strategies to slow the evolution of antibiotic resistance. Here we develop an approach, dubbed Controlled Hindrance of Adaptation of OrganismS or CHAOS, involving induction of epistasis between gene perturbations to deter adaption. We construct a combinatorial library of multiplexed, deactivated CRISPR-Cas9 devices to systematically perturb gene expression in Escherichia coli. While individual perturbations improved fitness during antibiotic exposure, multiplexed perturbations caused large fitness loss in a significant epistatic fashion. Strains exhibiting epistasis adapted significantly more slowly over three to fourteen days, and loss in adaptive potential was shown to be sustainable. Finally, we show that multiplexed peptide nucleic acids increase the antibiotic susceptibility of clinically isolated Carbapenem-resistant E. coli in an epistatic fashion. Together, these results suggest a new therapeutic strategy for restricting the evolution of antibiotic resistance.Peter Otoupal et al. present CHAOS, an approach for preventing the development of antibiotic resistance in E. coli through CRISPR-Cas9-based perturbation of gene expression. They show that multiplexed perturbations decrease fitness of clinically-isolated Carbapenem-resistant E. coli upon antibiotic exposure.

Design of a de novo aggregating antimicrobial peptide and bacterial conjugation delivery system

Traditional antibiotics are reaching obsolescence as a consequence of antibiotic resistance; therefore novel antibiotic approaches are needed. A recent non-traditional approach involves formation of protein aggregates as antimicrobials to disrupt bacterial homeostasis. Previous work on protein aggregates has focused on genome mining for aggregation-prone sequences in bacterial genomes rather than on rational design of aggregating antimicrobial peptides. Here, we use a synthetic biology approach to design an artificial gene encoding the first de novo aggregating antimicrobial peptide. This artificial gene, opaL (overexpressed protein aggregator Lipophilic), disrupts bacterial homeostasis by expressing extremely hydrophobic peptides. When this hydrophobic sequence is disrupted by acidic residues, consequent aggregation and antimicrobial effect decreases. Further, to deliver this artificial gene, we developed a probiotic approach using RK2, a broad host range conjugative plasmid, to transfer opaL from donor to recipient bacteria. We utilize RK2 to mobilize a shuttle plasmid carrying the opaL gene by adding the RK2 origin of transfer. We show that opaL is non-toxic to the donor, allowing for maintenance and transfer since its expression is under control of a promoter with a recipient-specific T7 RNA polymerase. Upon mating of donor and recipient Escherichia coli, we observe selective growth repression in T7 polymerase expressing recipients. This technique could be used to target desired pathogens by selecting pathogen-specific promoters to control opaL expression. This system provides a basis for the design and delivery of novel antimicrobial peptides. Importance The growing threat of antibiotic resistance necessitates new treatment options for bacterial infections that are recalcitrant to traditional antimicrobials. Existing methods usually involve small-molecule compounds which interfere with essential processes in bacterial cells. By contrast, protein aggregates operate by causing widespread disruption of bacterial homeostasis and may provide a new method for combating infections. We used rational design to create and test an aggregating de novo antimicrobial peptide, OpaL. In addition, we employed bacterial conjugation to deliver the opaL gene from donor bacteria to recipient bacteria while using a strain-specific promoter to ensure that OpaL was only expressed in targeted recipients. To the best of our knowledge, this represents the first design for a de novo peptide with aggregation-mediated antimicrobial activity. We envision that OpaL’s design parameters could be used in developing a new class of antimicrobial peptides to help treat antibiotic resistant infections.

CRISPR Gene Perturbations Provide Insights for Improving Bacterial Biofuel Tolerance

Economically-viable biofuel production is often limited by low levels of microbial tolerance to high biofuel concentrations. Here we demonstrate the first application of deactivated CRISPR perturbations of gene expression to improve Escherichia coli biofuel tolerance. We construct a library of 31 unique CRISPR inhibitions and activations of gene expression in E. coli and explore their impacts on growth during 10 days of exposure to n-butanol and n-hexane. We show that perturbation of metabolism and membrane-related genes induces the greatest impacts on growth in n-butanol, as does perturbation of redox-related genes in n-hexanes. We identify uncharacterized genes yjjZ and yehS with strong potential for improving tolerance to both biofuels. Perturbations demonstrated significant temporal dependencies, suggesting that rationally designing time-sensitive gene circuits can optimize tolerance. We also introduce a sgRNA-specific hyper-mutator phenotype (~2,600-fold increase) into our perturbation strains using error-prone Pol1. We show that despite this change, strains exhibited similar growth phenotypes in n-butanol as before, demonstrating the robustness of CRISPR perturbations during prolonged use. Collectively, these results demonstrate the potential of CRISPR manipulation of gene expression for improving biofuel tolerance and provide constructive starting points for optimization of biofuel producing microorganisms.