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Evaluating isoprenol production using the IPP-bypass pathway in the oleaginous yeast Rhodosporidium toruloides

Background To strengthen the national energy supply, there is an increasing demand for domestically generated aviation fuels. Bio-derived advanced aviation fuels offer the opportunity to meet this domestic need while presenting a unique opportunity to investigate the production of novel aviation fuels. Isoprenol, a chemical precursor to such novel fuels, has been shown to be a biologically producible compound in model organisms, but its bio-producibility needs to be further explored in organisms more compatible with industrial bioproduction. Results In this work, we evaluate isoprenol production using the promising bioproduction yeast, Rhodosporidium toruloides. First, we show successful isoprenol production using the IPP-bypass pathways most successful in laboratory strains of E. coli and S. cerevisiae. Next, we demonstrate that increased flux through the mevalonate pathway only modestly increases isoprenol titers. Using proteomics, we identified a potential bottleneck in production at the final step in the IPP-bypass pathway and explored alternative enzymes for this step. Finally, the top three strains of R. toruloides were evaluated in sorghum hydrolysates generated using cholinium lysinate. Through this work, 93.1 mg/L of isoprenol was produced in mock medium and 27.3 mg/L in sorghum hydrolysates. Conclusion Together these results lay the foundation for future work for the production of isoprenol from bioproduction crops.

Advanced aviation fuel

Alternate routes to acetate tolerance lead to varied isoprenol production from mixed carbon sources in Pseudomonas putida

ABSTRACT Lignocellulose is a renewable resource for the production of a diverse array of platform chemicals, including the biofuel isoprenol. Although this carbon stream provides a rich source of sugars, other organic compounds, such as acetate, can be used by microbial hosts. Here, we examined the growth and isoprenol production in a Pseudomonas putida strain pre-tolerized (“PT”) background where its native isoprenol catabolism pathway is deleted, using glucose and acetate as carbon sources. We found that PT displays impaired growth in minimal medium containing acetate and often fails to grow in glucose-acetate medium. Using a mutant recovery-based approach, we generated tolerized strains that overcame these limitations, achieving fast growth and isoprenol production in the mixed carbon feed. Changes in the glucose and acetate assimilation routes, including an upregulation in PP_0154 (SpcC, succinyl-CoA:acetate CoA-transferase) and differential expression of the gluconate assimilation pathways, were key for higher isoprenol titers in the tolerized strains, whereas a different set of mechanisms were likely enabling tolerance phenotypes in media containing acetate. Among these, a coproporphyrinogen-III oxidase (HemN) was upregulated across all tolerized strains and in one isolate required for acetate tolerance. Utilizing a defined glucose and acetate mixture ratio reflective of lignocellulosic feedstocks for isoprenol production in P. putida allowed us to obtain insights into the dynamics and challenges unique to dual carbon source utilization that are obscured when studied separately. Together, this enabled the development of a P. putida bioconversion chassis able to use a more complex carbon stream to produce isoprenol. IMPORTANCE Acetate is a relatively abundant component of many lignocellulosic carbon streams and has the potential to be used together with sugars, especially in microbes with versatile catabolism such as P. putida . However, the use of mixed carbon streams necessitates additional optimization. Furthermore, the use of P. putida for the production of the biofuel target, isoprenol, requires the use of engineered strains that have additional growth and production constraints when cultivated in acetate and glucose mixtures. In this study, we generate acetate-tolerant P. putida strains that overcome these challenges and examine their ability to produce isoprenol. We show that acetate tolerance and isoprenol production, although independent phenotypes, can both be optimized in a given P. putida strain. Using proteomics and whole genome sequencing, we examine the molecular basis of both phenotypes and show that tolerance to acetate can occur via alternate routes and result in different impacts on isoprenol production.

de Siqueira, Guilherme M. V. (ORCID:00000002364563

Automation and machine learning drive rapid optimization of isoprenol production in Pseudomonas putida

Advances in genome engineering have improved our ability to perturb microbial metabolic networks, yet bioproduction campaigns often struggle with parsing complex metabolic datasets to efficiently enhance product titers. We address this challenge by coupling laboratory automation with machine learning to systematically optimize the production of isoprenol, a sustainable aviation fuel precursor, in Pseudomonas putida. The simultaneous downregulation through CRISPR interference of combinations of up to four gene targets, guided by machine learning, permitted us to increase isoprenol titer 5-fold in six consecutive design-build-test-learn cycles. Moreover, machine learning enabled us to swiftly explore a vast experimental design space of 800,000 possible combinations by strategically recommending approximately 400 priority constructs. High-throughput proteomics allowed us to validate CRISPRi downregulation and identify biological mechanisms driving production increases. Our work demonstrates that ML-driven automated design-build-test-learn cycles, when combined with rigorous data validation, can rapidly enhance titers without specific biological knowledge, suggesting that it can be applied to any host, product, or pathway.

Carruthers, David N

Biosensor-driven strain engineering reveals key cellular processes for maximizing isoprenol production in Pseudomonas putida

Synthetic biology generates vast combinatorial designs, yet high-throughput analytical methods to screen them are poorly matched to interrogate this search space. We address this challenge by developing a biosensor-driven, growth-coupled selection strategy in Pseudomonas putida for isoprenol, a potential aviation fuel precursor. We found and characterized a noncanonical signaling pathway, revealing a functional and physical complex between a hybrid histidine kinase and an alcohol dehydrogenase, whose activity is tuned by heterodimerization. Leveraging this biosensor in a pooled CRISPRi library selection, we identified key host limitations. Iterative combinatorial strain engineering derived from these hits yielded a 36-fold titer increase to ~900 milligrams per liter. Integrated omics analysis revealed that metabolic rewiring toward amino acid catabolism was crucial for this improvement. This observation was found to be beneficial by technoeconomic analysis. Our modular workflow provides a powerful strategy for optimizing complex heterologous pathways and uncovering emergent host biology.

CRISPRi

Prenol production in a microbial host via the “Repass” Pathways

Prenol and isoprenol are promising advanced biofuels and serve as biosynthetic precursors for pharmaceuticals, fragrances, and other industrially relevant compounds. Despite engineering improvements that circumvent intermediate cytotoxicity and lower energy barriers, achieving high titer ‘mevalonate (MVA)-derived’ prenol has remained elusive. Difficulty in selective prenol production stems from the necessary isomerization of isopentenyl diphosphate (IPP) to dimethylallyl diphosphate (DMAPP) as well as the intrinsic toxicity of these diphosphate precursors. Here, the expression of specific isopentenyl monophosphate kinases with model-guided enzyme substitution of diphosphate isomerases and phosphatases enabled selective cycling of monophosphates and diphosphates, dramatically improving prenol titers and selectivity in Escherichia coli. Pairing this approach with the canonical MVA pathway resulted in 300 mg/L prenol at a 30:1 ratio with isoprenol. Further pairing with the “IPP-Bypass” pathway resulted in 526 mg/L prenol at a 72:1 ratio with isoprenol, the highest and purest MVA-derived prenol titer to date. Additionally, modifying this “IPP-Repass” for DMAPP production and coexpressing the prenyltransferase acPT1 yielded 48.3 mg/L of the potential therapeutic precursor drupanin from p-coumarate. These novel repass pathways establish a unique strategy for tuning diphosphate precursors to drive isoprenoid biosynthesis and prenylation reactions.

59 BASIC BIOLOGICAL SCIENCES

Predictive CRISPR-mediated gene downregulation for enhanced production of sustainable aviation fuel precursor in Pseudomonas putida

CRISPR interference (CRISPRi) has emerged as a valuable tool for redirecting metabolic flux to enhance bioproduction. However, its application is often constrained by two challenges: (i) rationally identifying effective gene targets for downregulation and (ii) efficiently constructing multiplexed CRISPRi systems. In this study, we address both challenges by integrating a computational prioritization tool with a versatile assembly method for building multiplexed CRISPRi systems. FluxRETAP (Flux-Reaction Target Prioritization) accurately identified gene targets whose knockdown led to substantial increase of isoprenol titers in Pseudomonas putida KT2440, outperforming a conventional non-computational, pathway-guided target selection. The highest isoprenol titer of nearly 1.5 g/L was achieved by knocking down PP_4118 (a gene encoding α-ketoglutarate dehydrogenase). The use of VAMMPIRE (Versatile Assembly Method for MultiPlexing CRISPRi-mediated downREgulation) enabled accurate assembly of CRISPRi constructs containing up to five sgRNA arrays, reducing context dependency and achieving uniform, position-independent gene downregulation. The integration of FluxRETAP and VAMMPIRE has the potential to advance metabolic engineering by rapidly identifying CRISPRi-mediated knockdowns and knockdown combinations that enhance bioproduction titers, with potential applicability to other microbial systems.

CRISPR interference

Off-gas capture: a promising strategy for removal and recovery of toxic bioproducts in aerobic fermentation

In many bioprocesses, maximum achievable titers are limited below economically viable levels by toxic accumulation of the primary end-product. To combat end-product inhibition, a variety of in situ product removal technologies have been developed to selectively remove or partition toxic bioproducts, thereby prolonging fermentation and improving overall process efficiency. Use of an in situ organic overlay to partition toxic hydrophobic products is a commonly employed approach, but this technique occupies valuable space in the fermentor, imposes replacement costs for unrecovered solvent, and increases downstream separation due to formation of stable emulsions. In addition, for many volatile hydrophobic products produced under aerobic conditions—including medium-chain alcohols, esters, monoterpenes, and other aviation fuel precursors—a significant fraction of the product is volatilized to the fermentor off-gas and must be recovered separately to maximize product yield. To address these challenges, we explore the viability of leveraging existing aeration energy to fully strip and recover volatile products from the fermentor off-gas. We compare two strategies of in situ product removal—liquid–liquid extraction and direct recovery from fermentation off-gas—for the production and recovery of intermediates used to generate isoprene and DMCO (1,4-dimethylcyclooctane), a high-performance jet fuel. We evaluate product toxicity, solvent toxicity, solvent partitioning, and the impact of aeration and internal overlay configurations on product volatilization rates. We then optimize product recovery from fermentor off-gas via condensation in chilled solvent, achieving 84% capture efficiency. In addition to greatly simplifying downstream processing, relying on aeration for product volatilization in the absence of an internal overlay enables continuous removal of toxic fermentation products up to maximum isoprenol titers of 20.4 g/L, the highest reported to date.

isoprene

Origin of replication discovery for environmentally isolated Pantoea strain enables expression of heterologous proteins, pathways and products

Leveraging predicted origin sequences from a previously characterized groundwater plasmidome, we constructed a barcoded plasmid library to screen for previously unknown origins. Testing this library against a panel of representative bacterial strains led to the identification of 3 previously unknown origins that replicate in gram-negative bacteria not previously associated with these origin sequences. Experimental validation confirmed that a plasmid bearing origin 6911 as the sole origin could replicate with a copy number of 9 (±2) in Pantoea sp. MT58, a fast growing and metal tolerant, environmentally important bacterium. Plasmids based on this new origin were used to express the reporter protein GFP, and non-native metabolite pathways for the natural product indigoidine and the terpenoid compound isoprenol. Functional previously unknown origins of replication in such non-model organisms can expand the toolkit for genetic manipulations of both model and less-studied bacteria.

molecular biology

Thermostable Enzyme Variants in the Lower Mevalonate Pathway Improve Isoprenoid Production by Cell-Free Biocatalysis

Cell-free biocatalysis is a rapidly evolving field with great potential for sustainably producing valuable chemicals. Some challenges in cell-free biocatalysis include reaction longevity, enzyme stability, and the cost of the biocatalysts. Here, the challenge of enzyme instability was addressed by employing thermophilic enzymes to improve the productivity of the lower mevalonate pathway, using limonene as an example isoprenoid product. The Classical mesophilic mevalonate pathway was compared to a newly assembled set of thermophilic enzymes comprising the Archaea I mevalonate pathway. The thermophilic pathway enzymes were thermostable to at least 60 °C and exhibited a 6× longer operating lifetime at 22 °C. Thus, despite lower initial activity rates at ambient temperature, the thermophilic pathway was longer-lived and resulted in a more productive cell-free reaction overall, achieving 1.7× higher yield of limonene compared to using enzymes from mesophiles. Moreover, the thermostable pathway retained activity for longer with the challenge of solvent exposure, namely, ethanol and isoprenol, which broadens the scope of accessible substrates and/or products in cell-free reactions employing this pathway. Altogether, we showed significant improvement in the stability and productivity of the lower mevalonate pathway, which will enable more efficient cell-free biosynthesis of isoprenoid products. This represents a valuable strategy to increase the robustness of cell-free systems by carefully sourcing biocatalysts from thermophilic organisms, which have proven to be resilient to challenges unique to cell-free reaction systems.

09 BIOMASS FUELS

Fast growth and high-titer bioproduction from renewable formate via metal-dependent formate dehydrogenase in Escherichia coli

Microbial bioproduction using one-carbon (C1) feedstocks has the potential to decarbonize the manufacturing of materials, fuels, and chemicals. Formate is a promising C1 feedstock, and the realization of industrial, formatotrophic platform organisms is a key goal for C1-based bioproduction. So far, a major limitation for synthetic formatotrophy has been slow energy supply due to slow formate dehydrogenase activity. Here, we implement a fast, metal-dependent formate dehydrogenase complex in a synthetic formatotrophic Escherichia coli utilizing the reductive glycine pathway. After a short-term evolution, we demonstrate formatotrophic growth of E. coli with a doubling time of less than 4.5 h, comparable to the fastest natural formatotrophs. To further explore the potential of a formate-based bioeconomy, this strain is engineered to produce mevalonate, as well as the terpenoid and aviation fuel precursor isoprenol, using formate we generate directly from the electrochemical reduction of CO2. This work demonstrates an improvement in bioproduct titer from formate, achieving the production of 3.8 g/L of mevalonate. Additionally, the abundant and recalcitrant polymer lignin is chemically decomposed into a formate-rich mixture of small organic acids and subsequently bioconverted into mevalonate. Overall, the described fast-growing, formatotrophic bioproduction strain demonstrates that a sustainable formate bioeconomy is within reach.

Cowan, Aidan E

Demonstrating a butylamine-based deconstruction method for poplar biomass and conversion by diverse microbial strains

Low-boiling alkylamines such as butylamine offer promise as effective biomass pretreatment solvents that can be readily recovered and recycled; however, their capability to support microbial conversion of nutrients present in hydrolysates represents an important area for investigation. Here we employed butylamine to pretreat poplar biomass and characterize its effects on the release of fermentable sugars after solvent removal and enzymatic hydrolysis, as well as the biocompatibility of the produced hydrolysates with three organisms commonly used as bioconversion hosts. We observed that residual butylamine and the derivative butylacetamide were present in high enough concentrations to exert toxicity to strains of Aspergillus niger, Pseudomonas putida, and Rhodosporidium toruloides that produce malic acid, isoprenol and bisabolene, respectively. Removal of the toxic compounds by charcoal filtration and nutrient supplementation resulted in a hydrolysate containing >100 g L −1 of sugars that enabled strong growth, substrate consumption and bioproduct accumulation, outperforming defined cultivation media. This is the first demonstration of a butylamine-based deconstruction process for poplar biomass at a pilot-scale to achieve conversion of high sugar concentrations to valuable bioproducts with engineered microbes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J

Flux REaction TArget Prioritization (Flux RETAP) v1

Metabolic engineering is evolving rapidly as a result of new advances in synthetic biology and automation, as well as the irruption of machine learning (ML). ML has been shown to provide the predictive power synthetic biology lacked and needed, and to be able to effectively guide the metabolic engineering process. However, current technical limitations prevent the independent application of ML approaches to metabolic engineering without the use of previous biological knowledge in the form of a prioritized list of desirable engineering targets. Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale metabolic models (GSMs) for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing metabolite production. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production in the literature accessible to us, 50% of targets that experimentally improved taxadiene production in E. coli and ~60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets which can also be utilized in ML pipelines.

Czajka, Jeffrey [Battelle Memorial Institute, Paci