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At least 163 records · Page 9

Promising approaches for the assembly of the catalytically active, recombinant Desulfomicrobium baculatum hydrogenase with substitutions at the active site

Background: Hydrogenases (H2ases) are metalloenzymes capable of the reversible conversion of protons and electrons to molecular hydrogen. Exploiting the unique enzymatic activity of H2ases can lead to advancements in the process of biohydrogen evolution and green energy production. Results: Here we created of a functional, optimized operon for rapid and robust production of recombinant [NiFe] Desulfomicrobium baculatum hydrogenase (Dmb H2ase). The conversion of the [NiFeSe] Dmb H2ase to [NiFe] type was performed on genetic level by site-directed mutagenesis. The native dmb operon includes two structural H2ase genes, coding for large and small subunits, and an additional gene, encoding a specific maturase (protease) that is essential for the proper maturation of the enzyme. Dmb, like all H2ases, needs intricate bio-production machinery to incorporate its crucial inorganic ligands and cofactors. Strictly anaerobic, sulfate reducer D. baculatum bacteria are distinct, in terms of their biology, from E. coli. Thus, we introduced a series of alterations within the native dmb genes. As a result, more than 100 elements, further compiled into 32 operon variants, were constructed. The initial requirement for a specific maturase was omitted by the artificial truncation of the large Dmb subunit. The assembly of the produced H2ase subunit variants was investigated both, in vitro and in vivo. This approach resulted in 4 recombinant [NiFe] Dmb enzyme variants, capable of H 2 evolution. The aim of this study was to overcome the gene expression, protein biosynthesis, maturation and ligand loading bottlenecks for the easy, fast, and cost-effective delivery of recombinant [NiFe] H2ase, using a commonly available E. coli strains. Conclusion: The optimized genetic constructs together with the developed growth and purification procedures appear to be a promising platform for further studies toward fully-active and O 2 tolerant, recombinant [NiFeSe] Dmb H2ase, resembling the native Dmb enzyme. It could likely be achieved by selective cysteine to selenocysteine substitution within the active site of the [NiFe] Dmb variant.

59 BASIC BIOLOGICAL SCIENCES↗

Environmental impacts of dam reservoir filling in the East Amazon

Mitigating the environmental impacts caused by hydroelectric dams is a worldwide challenge. The aquatic ecosystem is the most impacted during the reservoir filling phase, yet biogeochemical dynamics at this stage are not well-studied. Here we evaluate water quality and hydraulic parameters in the Araguari River (Amapá/Brazil) during the filling of the Ferreira Gomes Hydroelectric Power Plant reservoir (UHEFG). Five field campaigns were performed from July 2014 to August 2015 across nine sample sites within the reservoir (P1, P2, …P9) and only one downstream (P10). The following key variables were monitored: Trophic State Index (TSI), Total Coliforms (TC), E. coli (EC) and Chlorophyll-a (Chl-a), along with physical and chemical variables (Temperature, Suspended Solids, Total Dissolved Solids, Electrical Conductivity, Turbidity, Color, pH, DO, Al3+, NH4+, Cl-, Mg1+, Ca2+, total Phosphorous, NH3, NO3-, and SO42). Besides that, hydraulic-operational variables were also investigated: inflows (Qa), outflows (Qd), and variation in reservoir volume (Vol%). Multiple Regression Analyses showed that the key parameters were both significantly influenced by physio-chemical and hydraulic variables (0.46=R2adj=0.99, p<0.05). The DO showed significant spatial variation, being influenced by the turbulence from the Coaracy Nunes dam (UHECN) upstream and the UHEFG dam downstream. The Vol% influenced the TSI, which ranged from oligotrophic to hypertrophic and eventually stabilized at mesotrophic. The levels of TSI, TC, and Chl-a decreased and the level of E. coli increased (p<0.05) as a function of Vol%. A Cluster Analysis showed the formation of three spatial groups - two inside the reservoir and one downstream (P10). This suggests that in the rainy season or transition season, the hydraulic residence time in the reservoir is very low (16 = thr = 36 h) when hydrodynamic processes are dominant. In the dry season (thr ˜ 1 month), biogeochemical and hydrodynamic processes occur at similar time scales to the nutrient and microbial abundance. These results confirm the hypothesis that the filling phase has significant impacts on the key parameters of the water quality (p<0.05). We conclude that the filling phase of the UHEFG reservoir generated significant environmental impacts, which have repercussions even retrospectively.

Amazon, biogeochemistry, ecosystem, extreme event,↗

Synthesis, antibiotic structure–activity relationships, and cellulose dissolution studies of new room-temperature ionic liquids derived from lignin

Ionic liquids (ILs) are promising pretreatment solvents for lignocellulosic biomass, but are largely prepared from petroleum precursors. Benzaldehydes from depolymerized lignin, such as vanillin, syringaldehyde, and 4-methoxy benzaldehyde, represent renewable feedstocks for the synthesis of ionic liquids. We herein report syntheses of novel lignin-derived ionic liquids, with extended N -alkyl chains, and examine their melting points, cellulose dissolution capacities, and toxicity profiles against Daphnia magna and E. coli strain 1A1. The latter organism has been engineered to produce isoprenol, a drop-in biofuel and precursor for commodity chemicals. The new N,N -diethyl and N,N -dipropyl methyl benzylammonium ILs were liquids at room temperature, showing 75–100 °C decreased melting points as compared to their N,N,N -trimethyl benzylammonium analog. Extension of N -alkyl chains also increased antibacterial activity threefold, while ionic liquids prepared from vanillin showed 2- to 4-fold lower toxicity as compared to those prepared from syringaldehyde and 4-methoxybenzaldehyde. The trend of antibacterial activity for anions of lignin-derived ILs was found to be methanesulfonate < acetate < hydroxide. Microcrystalline cellulose dissolution, from 2 to 4 wt% after 20 min at 100 °C, was observed in all new ILs using light microscopy and IR spectroscopy. Ionic liquids prepared from H-, S- and G-lignin oxidation products provided differential cytotoxic activity against E. coli and D. magna , suggesting these compounds could be tailored for application specificity within a biorefinery.

09 BIOMASS FUELS↗

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↗

Data for Expression of a Bacterial Trehalose 6-Phosphate Synthase Gene otsA in Camelina sativa Seeds Promotes the Channelling of Carbon Towards Oil Accumulation

Improving seed oil yield is essential for developing Camelina sativa as a sustainable biofuel crop. Fatty acid synthesis depends on the production of acetyl-CoA from photosynthetically derived sugars. Trehalose 6-phosphate (T6P), a proxy for sucrose availability, can link sugar status to plant growth and development. Synthesised by trehalose 6-phosphate synthase (TPS) from UDP-glucose and glucose-6-phosphate, T6P plays a regulatory role in metabolism. Our previous studies on Arabidopsis transgenic lines constitutively expressing the E. coli otsA (encoding TPS) showed increased T6P levels and seed triacylglycerol, along with stunted growth. In the present study we express otsA in camelina under the control of a seed-specific Phaseolin promoter. Seeds of the resulting transgenic lines accumulated high levels of T6P, and a 15%–20% increase in total fatty acids and triacylglycerol compared to wild-type. Molecular analysis showed the transgenic seeds had reduced SnRK1 activity, elevated WRI1 protein levels, and increased the levels of WRI1 and its target genes, along with enhanced rates of fatty acid synthesis that increased seed weights relative to wild type. Notably, the increase in oil did not affect seed protein levels but did reduce the soluble metabolite fraction. Crucially, seed-specific expression of otsA mitigated the growth defects associated with constitutive otsA expression, and the transgenic lines showed normal seed development and germination. These findings demonstrate that targeted T6P modulation via seed-specific otsA expression is an effective metabolic engineering strategy to boost oil production in camelina and potentially in other oilseed crops and bioenergy crops such as energycane, sorghum and miscanthus.

Lipids↗

Probing the limits of genetic recoding using multi-omics-guided evolution

Engineering the genetic code—by reassigning multiple of the 64 natural codons—enables making organisms resistant to all viruses, preventing genetic information exchange, and allowing the biosynthesis of genetically encoded unnatural polymers. However, synonymous codon replacement—recoding—is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using genome synthesis, directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple synthetic Escherichia coli genomes. We construct six partially recoded E. coli strains bearing up to 45.8% of a synthetic genome with a deleterious 57-codon genetic code. As our analyses revealed widespread defects—including unassigned codons in Syn61 and Syn57—we apply multi-omics to revise our genome design and mitigate defects. Using multi-omics, we show that recoding induces transcriptional and translational changes leading to fitness defects under hundreds of conditions. Finally, we develop a multi-omics-guided evolution strategy that rapidly restores fitness, enabling genome synthesis with radical changes.

Nyerges, Akos [Harvard Medical School, Boston, MA ↗

Engineering of increased L-Threonine production in bacteria by combinatorial cloning and machine learning

The goal of this study is to develop a general strategy for bacterial engineering using an integrated synthetic biology and machine learning (ML) approach. This strategy was developed in the context of increasing L-threonine production in Escherichia coli ATCC 21277. A set of 16 genes was initially selected based on metabolic pathway relevance to threonine biosynthesis and used for combinatorial cloning to construct a set of 385 strains to generate training data (i.e., a range of L-threonine titers linked to each of the specific gene combinations). Hybrid (regression/classification) deep learning (DL) models were developed and used to predict additional gene combinations in subsequent rounds of combinatorial cloning for increased L-threonine production based on the training data. As a result, E. coli strains built after just three rounds of iterative combinatorial cloning and model prediction generated higher L-threonine titers (from 2.7 g/L to 8.4 g/L) than those of patented L-threonine strains being used as controls (4-5 g/L). Interesting combinations of genes in L-threonine production included deletions of the tdh, metL, dapA, and dhaM genes as well as overexpression of the pntAB, ppc, and aspC genes. Mechanistic analysis of the metabolic system constraints for the best performing constructs offers ways to improve the models by adjusting weights for specific gene combinations. Graph theory analysis of pairwise gene modifications and corresponding levels of L-threonine production also suggests additional rules that can be incorporated into future ML models.

60 APPLIED LIFE SCIENCES↗

Scalable production of recombinant three-finger proteins: from inclusion bodies to high quality molecular probes

The three-finger proteins are a collection of disulfide bond rich proteins of great biomedical interests. Scalable recombinant expression and purification of bioactive three-finger proteins is quite difficult. We introduce a working pipeline for expression, purification and validation of disulfide-bond rich three-finger proteins using E. coli as the expression host. With this pipeline, we have successfully obtained highly purified and bioactive recombinant α-Βungarotoxin, k-Bungarotoxin, Hannalgesin, Mambalgin-1, α-Cobratoxin, MTα, Slurp1, Pate B etc. Milligrams to hundreds of milligrams of recombinant three finger proteins were obtained within weeks in the lab. The recombinant proteins showed specificity in binding assay and six of them were crystallized and structurally validated using X-ray diffraction protein crystallography. Our pipeline allows refolding and purifying recombinant three finger proteins under optimized conditions and can be scaled up for massive production of three finger proteins. As many three finger proteins have attractive therapeutic or research interests and due to the extremely high quality of the recombinant three finger proteins we obtained, our method provides a competitive alternative to either their native counterparts or chemically synthetic ones and should facilitate related research and applications.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing microbial systems and process configurations for improved ethanol production from sugary stovers by integrating soluble sugars and holocellulose

Here, this study evaluated microbial systems and technological approaches to configure the whole slurry co-fermentation process for ethanol biosynthesis from a novel stover system rich in sugars. Two approaches, namely separate and simultaneous hydrolysis and co-fermentation (SHCF and SSCF, respectively), were investigated using Escherichia coli monoculture and E. coli-yeast coculture. The SSCF with E. coli monoculture produced 32.75 g/L ethanol, representing only 44.87% yield, which left 65.13 g/L of total sugars unconverted and exhibited limited xylose consumption. Subsequently, a coculture-based SHCF significantly enhanced sugar consumption, leading to increase in ethanol yield and concentration to 66.94% and 48.86 g/L, respectively. Nevertheless, xylose utilization remained minimal due to the preference for glucose and the inhibitory effects of certain compounds. Thereafter, modification of the medium composition by supplementing betaine and sodium metabisulfite improved ethanol production to 53.18 g/L by reducing the toxic effects of inhibitors. Finally, a dual-phase SSCF (DP-SSCF) was explored by allowing the consumption of sugars from the pretreated slurry in the first phase, followed by concurrent cellulose hydrolysis and utilization of the resulting glucose in the second phase. This strategy increased ethanol titer to 63.14 g/L, with 84.3% yield and 0.88 g/L/h productivity.

09 BIOMASS FUELS↗

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Abstract Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli . Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus , RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

59 BASIC BIOLOGICAL SCIENCES↗

ATP biosensor reveals microbial energetic dynamics and facilitates bioproduction

Adenosine-5’-triphosphate (ATP), the primary energy currency in cellular processes, drives metabolic activities and biosynthesis. Despite its importance, understanding intracellular ATP dynamics’ impact on bioproduction and exploiting it for enhanced bioproduction remains largely unexplored. Here, we harness an ATP biosensor to dissect ATP dynamics across different growth phases and carbon sources in multiple microbial strains. We find transient ATP accumulations during the transition from exponential to stationary growth phases in various conditions, coinciding with fatty acid (FA) and polyhydroxyalkanoate (PHA) production in Escherichia coli and Pseudomonas putida, respectively. We identify carbon sources (acetate for E. coli, oleate for P. putida) that elevate steady-state ATP levels and boost FA and PHA production. Moreover, we employ ATP dynamics as a diagnostic tool to assess metabolic burden, revealing bottlenecks that limit limonene bioproduction. Our results not only elucidate the relationship between ATP dynamics and bioproduction but also showcase its value in enhancing bioproduction in various microbial species.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para -aminophenylalanine

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging, as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para -aminophenylalanine (pAF) in Escherichia coli . First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism and computationally identified metabolic interventions in the host’s native metabolism to improve pAF production. Next, we explored different approaches of imposing these flux interventions experimentally and found that the upregulation of flux in the chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers (~20-fold) while maintaining a reasonable pAF production-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

59 BASIC BIOLOGICAL SCIENCES↗

Computational design and analysis of modular cells for large libraries of exchangeable product synthesis modules

Microbial metabolism can be harnessed to produce a large library of useful chemicals from renewable resources such as plant biomass. However, it is laborious and expensive to create microbial biocatalysts to produce each new product. To tackle this challenge, we have recently developed modular cell (ModCell) design principles that enable rapid generation of production strains by assembling a modular (chassis) cell with exchangeable production modules to achieve overproduction of target molecules. Previous computational ModCell design methods are limited to analyze small libraries of around 20 products. In this study, we developed a new computational method, named ModCell-HPC, that can design modular cells for large libraries with hundreds of products with a highly-parallel and multi-objective evolutionary algorithm and enable us to elucidate modular design properties. We demonstrated ModCell-HPC to design Escherichia coli modular cells towards a library of 161 endogenous production modules. From these simulations, we identified E. coli modular cells with few genetic manipulations that can produce dozens of molecules in a growth-coupled manner with different types of fermentable sugars. These designs revealed key genetic manipulations at the chassis and module levels to accomplish versatile modular cells, involving not only in the removal of major by-products but also modification of branch points in the central metabolism. We further found that the effect of various sugar degradation on redox metabolism results in lower compatibility between a modular cell and production modules for growth on pentoses than hexoses. To better characterize the degree of compatibility, we developed a method to calculate the minimal set cover, identifying that only three modular cells are all needed to couple with up 85 compatible production modules. By determining the unknown compatibility contribution metric, we further elucidated the design features that allow an existing modular cell to be re-purposed towards production of new molecules. Altogether, ModCell-HPC is a useful tool for understanding modularity of biological systems and guiding more efficient and generalizable design of modular cells that help reduce research and development cost in biocatalysis.

59 BASIC BIOLOGICAL SCIENCES↗

Functional reconstitution of a bacterial CO2 concentrating mechanism in Escherichia coli

Many photosynthetic organisms employ a CO 2 concentrating mechanism (CCM) to increase the rate of CO 2 fixation via the Calvin cycle. CCMs catalyze ≈50% of global photosynthesis, yet it remains unclear which genes and proteins are required to produce this complex adaptation. We describe the construction of a functional CCM in a non-native host, achieved by expressing genes from an autotrophic bacterium in an Escherichia coli strain engineered to depend on rubisco carboxylation for growth. Expression of 20 CCM genes enabled E. coli to grow by fixing CO 2 from ambient air into biomass, with growth in ambient air depending on the components of the CCM. Bacterial CCMs are therefore genetically compact and readily transplanted, rationalizing their presence in diverse bacteria. Reconstitution enabled genetic experiments refining our understanding of the CCM, thereby laying the groundwork for deeper study and engineering of the cell biology supporting CO 2 assimilation in diverse organisms.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Rethinking Suicide Thi4 Thiazole Synthases: Comparative Genomic Insights and Pilot Functional Evidence

Suicide thiazole synthases (Thi4) are mononuclear metal enzymes that form the thiazole moiety of thiamin from NAD + , glycine, and a sulfur atom that is stripped from an active-site cysteine residue, causing enzyme inactivation. Comparative genomic analysis shows that prokaryotic Thi4 genes often cluster on the chromosomal regions encoding ThiS, ThiF, and other proteins that can produce, relay, or use persulfide or thiocarboxylate sulfur. These recurring genomic associations raise the possibility that, in some microorganisms, suicide Thi4s may interact with sulfur-relay systems, i.e., they can possibly operate in a nonsuicide mode. This proof-of-concept study explores this possibility via complementation assays using Escherichia coli as a heterologous platform. A representative bacterial Thi4 that clustered with thiS and thiF complemented an E. coli ΔthiG (thiazole auxotroph) single mutant better than a ΔthiG ΔthiF ΔthiS triple mutant. Although (in)direct sulfur transfer could not be assessed in the scope of our investigation, the initial results suggest a dependence on host sulfur relay components, consistent with predicted interactions with the host sulfide transfer chain. Collectively, this new perspective provides a useful guide for future biochemical studies on alternative modes of action for “suicide Thi4s” and accessory proteins.

Bacteria↗

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↗