Adaptive laboratory evolution and genetic engineering improved terephthalate utilization in Pseudomonas putida KT2440.

Poly(ethylene terephthalate) (PET) is one of the most ubiquitous plastics and can be depolymerized through biological and chemo-catalytic routes to its constituent monomers, terephthalic acid (TPA) and ethylene glycol (EG). TPA and EG can be re-synthesized into PET for closed-loop recycling or microbially converted into higher-value products for open-loop recycling. Here, we expand on our previous efforts engineering and applying Pseudomonas putida KT2440 for PET conversion by employing adaptive laboratory evolution (ALE) to improve TPA catabolism.

Diversity of Transcriptional Regulatory Adaptation in E. coli.

The transcriptional regulatory network (TRN) in bacteria is thought to rapidly evolve in response to selection pressures, modulating transcription factor (TF) activities and interactions. In order to probe the limits and mechanisms surrounding the short-term adaptability of the TRN, we generated, evolved, and characterized knockout (KO) strains in Escherichia coli for 11 regulators selected based on measured growth impact on glucose minimal media. All but one knockout strain (Δlrp) were able to recover growth and did so requiring few convergent mutations.

Diagnosis and mitigation of the systemic impact of genome reduction in DGF-298.

Unlabelled: Microorganisms with simplified genomes represent interesting cell chassis for systems and synthetic biology. However, genome reduction can lead to undesired traits, such as decreased growth rate and metabolic imbalances. To investigate the impact of genome reduction on strain DGF-298, a strain in which ~ 36% of the genome has been removed, we reconstructed a strain-specific metabolic model (AC1061), investigated the regulation of gene expression using iModulon-based transcriptome analysis, and performed adaptive laboratory evolution to let the strain correct potential imbalances that arose during its simplification.

Genetic heterogeneity of engineered Escherichia coli Nissle 1917 strains during scale-up simulation.

Advanced microbiome therapeutics have emerged as a powerful approach for the treatment of numerous diseases. While the genetic instability of genetically engineered microorganisms is a well-known challenge in the scale-up of biomanufacturing processes, it has not yet been investigated for advanced microbiome therapeutics. Here, the evolution of engineered Escherichia coli Nissle 1917 strains producing Interleukin 2 and Aldafermin were investigated in two strain backgrounds with and without the three error-prone DNA polymerases polB, dinB, and umuDC, which contribute to the mutation rate of the host strain.

Evolution and engineering of pathways for aromatic O-demethylation in Pseudomonas putida KT2440.

Biological conversion of lignin from biomass offers a promising strategy for sustainable production of fuels and chemicals. However, aromatic compounds derived from lignin commonly contain methoxy groups, and O-demethylation of these substrates is often a rate-limiting reaction that influences catabolic efficiency. Several enzyme families catalyze aromatic O-demethylation, but they are rarely compared in vivo to determine an optimal biocatalytic strategy.

Biocomposite thermoplastic polyurethanes containing evolved bacterial spores as living fillers to facilitate polymer disintegration.

The field of hybrid engineered living materials seeks to pair living organisms with synthetic materials to generate biocomposite materials with augmented function since living systems can provide highly-programmable and complex behavior. Engineered living materials have typically been fabricated using techniques in benign aqueous environments, limiting their application. In this work, biocomposite fabrication is demonstrated in which spores from polymer-degrading bacteria are incorporated into a thermoplastic polyurethane using high-temperature melt extrusion.

Advancing the scale of synthetic biology via cross-species transfer of cellular functions enabled by iModulon engraftment.

Machine learning applied to large compendia of transcriptomic data has enabled the decomposition of bacterial transcriptomes to identify independently modulated sets of genes, such iModulons represent specific cellular functions. The identification of iModulons enables accurate identification of genes necessary and sufficient for cross-species transfer of cellular functions. We demonstrate cross-species transfer of: 1) the biotransformation of vanillate to protocatechuate, 2) a malonate catabolic pathway, 3) a catabolic pathway for 2,3-butanediol, and 4) an antimicrobial resistance to ampicillin found in multiple Pseudomonas species to Escherichia coli.

Laboratory evolution, transcriptomics, and modeling reveal mechanisms of paraquat tolerance.

Relationships between the genome, transcriptome, and metabolome underlie all evolved phenotypes. However, it has proved difficult to elucidate these relationships because of the high number of variables measured. A recently developed data analytic method for characterizing the transcriptome can simplify interpretation by grouping genes into independently modulated sets (iModulons).

Adaptive evolution of a minimal organism with a synthetic genome.

The bacterial strain JCVI-syn3.0 stands as the first example of a living organism with a minimized synthetic genome, derived from the genome and chemically synthesized . Here, we report the experimental evolution of a syn3.

Have you tried turning it off and on again? Oscillating selection to enhance fitness-landscape traversal in adaptive laboratory evolution experiments.

Adaptive Laboratory Evolution (ALE) is a powerful tool for engineering and understanding microbial physiology. ALE relies on the selection and enrichment of mutations that enable survival or faster growth under a selective condition imposed by the experimental setup. Phenotypic fitness landscapes are often underpinned by complex genotypes involving multiple genes, with combinatorial positive and negative effects on fitness.

Laboratory evolution reveals general and specific tolerance mechanisms for commodity chemicals.

Although strain tolerance to high product concentrations is a barrier to the economically viable biomanufacturing of industrial chemicals, chemical tolerance mechanisms are often unknown. To reveal tolerance mechanisms, an automated platform was utilized to evolve Escherichia coli to grow optimally in the presence of 11 industrial chemicals (1,2-propanediol, 2,3-butanediol, glutarate, adipate, putrescine, hexamethylenediamine, butanol, isobutyrate, coumarate, octanoate, hexanoate), reaching tolerance at concentrations 60%-400% higher than initial toxic levels. Sequencing genomes of 223 isolates from 89 populations, reverse engineering, and cross-compound tolerance profiling were employed to uncover tolerance mechanisms.

Understanding Functional Redundancy and Promiscuity of Multidrug Transporters in under Lipophilic Cation Stress.

Multidrug transporters (MDTs) are major contributors to microbial drug resistance and are further utilized for improving host phenotypes in biotechnological applications. Therefore, the identification of these MDTs and the understanding of their mechanisms of action in vivo are of great importance. However, their promiscuity and functional redundancy represent a major challenge towards their identification.

Revealing oxidative pentose metabolism in new Pseudomonas putida isolates.

The Pseudomonas putida group in the Gammaproteobacteria has been intensively studied for bioremediation and plant growth promotion. Members of this group have recently emerged as promising hosts to convert intermediates derived from plant biomass to biofuels and biochemicals. However, most strains of P.

Experimental Evolution Reveals Unifying Systems-Level Adaptations but Diversity in Driving Genotypes.

Genotype-fitness maps of evolution have been well characterized for biological components, such as RNA and proteins, but remain less clear for systems-level properties, such as those of metabolic and transcriptional regulatory networks. Here, we take multi-omics measurements of 6 different E. coli strains throughout adaptive laboratory evolution (ALE) to maximal growth fitness.

Laboratory evolution of synthetic electron transport system variants reveals a larger metabolic respiratory system and its plasticity.

The bacterial respiratory electron transport system (ETS) is branched to allow condition-specific modulation of energy metabolism. There is a detailed understanding of the structural and biochemical features of respiratory enzymes; however, a holistic examination of the system and its plasticity is lacking. Here we generate four strains of Escherichia coli harboring unbranched ETS that pump 1, 2, 3, or 4 proton(s) per electron and characterized them using a combination of synergistic methods (adaptive laboratory evolution, multi-omic analyses, and computation of proteome allocation).

Membrane transporter identification and modulation via adaptive laboratory evolution.

Membrane transport proteins are potential targets for medical and biotechnological applications. However, more than 30% of reported membrane transporter families are either poorly characterized or lack adequate functional annotation. Here, adaptive laboratory evolution was leveraged to identify membrane transporters for a set of four amino acids as well as specific mutations that modulate the activities of these transporters.

Engineering Pseudomonas putida for improved utilization of syringyl aromatics.

Lignin is a largely untapped source for the bioproduction of value-added chemicals. Pseudomonas putida KT2440 has emerged as a strong candidate for bioprocessing of lignin feedstocks due to its resistance to several industrial solvents, broad metabolic capabilities, and genetic amenability. Here we demonstrate the engineering of P.

Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network.

Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction.

Selection for Cell Yield Does Not Reduce Overflow Metabolism in Escherichia coli.

Overflow metabolism is ubiquitous in nature, and it is often considered inefficient because it leads to a relatively low biomass yield per consumed carbon. This metabolic strategy has been described as advantageous because it supports high growth rates during nutrient competition. Here, we experimentally evolved bacteria without nutrient competition by repeatedly growing and mixing millions of parallel batch cultures of Escherichia coli.

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr.

Environmental conditions dictate differential evolution of vancomycin resistance in Staphylococcus aureus.

While microbiological resistance to vancomycin in Staphylococcus aureus is rare, clinical vancomycin treatment failures are common, and methicillin-resistant S. aureus (MRSA) strains isolated from patients after prolonged vancomycin treatment failure remain susceptible. Adaptive laboratory evolution was utilized to uncover mutational mechanisms associated with MRSA vancomycin resistance in a physiological medium as well as a bacteriological medium used in clinical susceptibility testing.