Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline.

As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purification using small-scale expression in E. coli and an affordable liquid-handling robot. This low-cost platform enables the purification of 96 proteins in parallel with minimal waste and is scalable for processing hundreds of proteins weekly per user. We demonstrate the performance of this method with the expression and purification of the leading poly(ethylene terephthalate) hydrolases reported in the literature. Replicate experiments demonstrated reproducibility and enzyme purity and yields (up to 400 µg) sufficient for comprehensive analyses of both thermostability and activity, generating a standardized benchmark dataset for comparing these plastic-degrading enzymes. The cost-effectiveness and ease of implementation of this platform render it broadly applicable to diverse protein characterization challenges in the biological sciences.

Integration of pH Control into Chi.Bio Reactors and Demonstration with Small-Scale Enzymatic Poly(ethylene terephthalate) Hydrolysis.

Small-scale bioreactors that are affordable and accessible would be of major benefit to the research community. In previous work, an open-source, automated bioreactor system was designed to operate up to the 30 mL scale with online optical monitoring, stirring, and temperature control, and this system, dubbed Chi.Bio, is now commercially available at a cost that is typically 1-2 orders of magnitude less than commercial bioreactors. In this work, we further expand the capabilities of the Chi.Bio system by enabling continuous pH monitoring and control through hardware and software modifications. For hardware modifications, we sourced low-cost, commercial pH circuits and made straightforward modifications to the Chi.Bio head plate to enable continuous pH monitoring. For software integration, we introduced closed-loop feedback control of the pH measured inside the Chi.Bio reactors and integrated a pH-control module into the existing Chi.Bio user interface. We demonstrated the utility of pH control through the small-scale depolymerization of the synthetic polyester, poly(ethylene terephthalate) (PET), using a benchmark cutinase enzyme, and compared this to 250 mL bioreactor hydrolysis reactions. The results in terms of PET conversion and rate, measured both by base addition and product release profiles, are statistically equivalent, with the Chi.Bio system allowing for a 20-fold reduction of purified enzyme required relative to the 250 mL bioreactor setup. Through inexpensive modifications, the ability to conduct pH control in Chi.Bio reactors widens the potential slate of biochemical reactions and biological cultivations for study in this system, and may also be adapted for use in other bioreactor platforms.

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. Here, two pathways for aromatic O-demethylation were compared in Pseudomonas putida KT2440. The native Rieske non-heme iron monooxygenase (VanAB) and, separately, a heterologous tetrahydrofolate-dependent demethylase (LigM) were constitutively expressed in P. putida, and the strains were optimized via adaptive laboratory evolution (ALE) with vanillate as a model substrate. All evolved strains displayed improved growth phenotypes, with the evolved strains harboring the native VanAB pathway exhibiting growth rates ∼1.8x faster than those harboring the heterologous LigM pathway. Enzyme kinetics and transcriptomics studies investigated the contribution of selected mutations toward enhanced utilization of vanillate. The VanAB-overexpressing strains contained the most impactful mutations, including those in VanB, the reductase for vanillate O-demethylase, PP_3494, a global regulator of vanillate catabolism, and fghA, involved in formaldehyde detoxification. These three mutations were combined into a single strain, which exhibited approximately 5x faster vanillate consumption than the wild-type strain in the first 8 h of cultivation. Overall, this study illuminates the details of vanillate catabolism in the context of two distinct enzymatic mechanisms, yielding a platform strain for efficient O-demethylation of lignin-related aromatic compounds to value-added products.

Design and Validation of a High-Throughput Reductive Catalytic Fractionation Method.

Reductive catalytic fractionation (RCF) is a promising method to extract and depolymerize lignin from biomass, and bench-scale studies have enabled considerable progress in the past decade. RCF experiments are typically conducted in pressurized batch reactors with volumes ranging between 50 and 1000 mL, limiting the throughput of these experiments to one to six reactions per day for an individual researcher. Here, we report a high-throughput RCF (HTP-RCF) method in which batch RCF reactions are conducted in 1 mL wells machined directly into Hastelloy reactor plates. The plate reactors can seal high pressures produced by organic solvents by vertically stacking multiple reactor plates, leading to a compact and modular system capable of performing 240 reactions per experiment. Using this setup, we screened solvent mixtures and catalyst loadings for hydrogen-free RCF using 50 mg poplar and 0.5 mL reaction solvent. The system of 1:1 isopropanol/methanol showed optimal monomer yields and selectivity to 4-propyl substituted monomers, and validation reactions using 75 mL batch reactors produced identical monomer yields. To accommodate the low material loadings, we then developed a workup procedure for parallel filtration, washing, and drying of samples and a 1H nuclear magnetic resonance spectroscopy method to measure the RCF oil yield without performing liquid-liquid extraction. As a demonstration of this experimental pipeline, 50 unique switchgrass samples were screened in RCF reactions in the HTP-RCF system, revealing a wide range of monomer yields (21-36%), S/G ratios (0.41-0.93), and oil yields (40-75%). These results were successfully validated by repeating RCF reactions in 75 mL batch reactors for a subset of samples. We anticipate that this approach can be used to rapidly screen substrates, catalysts, and reaction conditions in high-pressure batch reactions with higher throughput than standard batch reactors.

Retraction of "Hydrogenolysis of Polyethylene and Polypropylene into Propane over Cobalt-Based Catalysts".

[This retracts the article DOI: 10.1021/jacsau.2c00402.].

Topology-Accelerated and Selective Cascade Depolymerization of Architecturally Complex Polyesters.

Despite considerable recent advances already made in developing chemically circular polymers (CPs), the current framework predominantly focuses on CPs with linear-chain structures of different monomer types. As polymer properties are determined by not only composition but also topology, manipulating the topology of the single-monomer-based CP systems from linear-chain structures to architecturally complex polymers could potentially modulate the resulting polymer properties without changing the chemical composition, thereby advancing the concept of monomaterial product design. To that end, here, we introduce a chemically circular hyperbranched polyester (HBPE), synthesized by a mixed chain-growth and step-growth polymerization of a rationally designed bicyclic lactone with a pendent hydroxyl group (BiLOH). This HBPE exhibits full chemical recyclability despite its architectural complexity, showing quantitative selectivity for regeneration of BiLOH, via a unique cascade depolymerization mechanism. Moreover, distinct differences in materials properties and performance arising from topological variations between HBPE, hb-PBiLOH, and its linear analogue, l-PBiLOH, have been revealed where generally the branched structure led to more favorable interchain interactions, and topology-amplified optical activity has also been observed for chiral (1S, 4S, 5S)-hb-PBiLOH. More intriguingly, depolymerization of l-PBiLOH proceeds through an unexpected, initial topological transformation to the HBPE polymer, followed by the faster cascade depolymerization pathway adopted by hb-PBiLOH. Overall, these results demonstrate that CP design can go beyond typical linear polymers, and rationally redesigned, architecturally complex polymers for their unique properties may synergistically impart advantages in topology-augmented depolymerization acceleration and selectivity for exclusive monomer regeneration.

The reaction mechanism of the Ideonella sakaiensis PETase enzyme.

Polyethylene terephthalate (PET), the most abundantly produced polyester plastic, can be depolymerized by the Ideonella sakaiensis PETase enzyme. Based on multiple PETase crystal structures, the reaction has been proposed to proceed via a two-step serine hydrolase mechanism mediated by a serine-histidine-aspartate catalytic triad. To elucidate the multi-step PETase catalytic mechanism, we use transition path sampling and likelihood maximization to identify optimal reaction coordinates for the PETase enzyme. We predict that deacylation is likely rate-limiting, and the reaction coordinates for both steps include elements describing nucleophilic attack, ester bond cleavage, and the "moving-histidine" mechanism. We find that the flexibility of Trp185 promotes the reaction, providing an explanation for decreased activity observed in mutations that restrict Trp185 motion. Overall, this study uses unbiased computational approaches to reveal the detailed reaction mechanism necessary for further engineering of an important class of enzymes for plastics bioconversion.

Natural diversity screening, assay development, and characterization of nylon-6 enzymatic depolymerization.

Successes in biocatalytic polyester recycling have raised the possibility of deconstructing alternative polymers enzymatically, with polyamide (PA) being a logical target due to the array of amide-cleaving enzymes present in nature. Here, we screen 40 potential natural and engineered nylon-hydrolyzing enzymes (nylonases), using mass spectrometry to quantify eight compounds resulting from enzymatic nylon-6 (PA6) hydrolysis. Comparative time-course reactions incubated at 40-70 °C showcase enzyme-dependent variations in product distributions and extent of PA6 film depolymerization, with significant nylon deconstruction activity appearing rare. The most active nylonase, a NylCK variant we rationally thermostabilized (an N-terminal nucleophile (Ntn) hydrolase, NylCK-TS, Tm = 87.4 °C, 16.4 °C higher than the wild-type), hydrolyzes 0.67 wt% of a PA6 film. Reactions fail to restart after fresh enzyme addition, indicating that substrate-based limitations, such as restricted enzyme access to hydrolysable bonds, prohibit more extensive deconstruction. Overall, this study expands our understanding of nylonase activity distribution, indicates that Ntn hydrolases may have the greatest potential for further development, and identifies key targets for progressing PA6 enzymatic depolymerization, including improving enzyme activity, product selectivity, and enhancing polymer accessibility.

Engineering of glycoside hydrolase family 7 cellobiohydrolases directed by natural diversity screening.

Protein engineering and screening of processive fungal cellobiohydrolases (CBHs) remain challenging due to limited expression hosts, synergy-dependency, and recalcitrant substrates. In particular, glycoside hydrolase family 7 (GH7) CBHs are critically important for the bioeconomy and typically difficult to engineer. Here, we target the discovery of highly active natural GH7 CBHs and engineering of variants with improved activity. Using experimentally assayed activities of genome mined CBHs, we applied sequence and structural alignments to top performers to identify key point mutations linked to improved activity. From ∼1500 known GH7 sequences, an evolutionarily diverse subset of 57 GH7 CBH genes was expressed in Trichoderma reesei and screened using a multiplexed activity screening assay. Ten catalytically enhanced natural variants were identified, produced, purified, and tested for efficacy using industrially relevant conditions and substrates. Three key amino acids in CBHs with performance comparable or superior to Penicillium funiculosum Cel7A were identified and combinatorially engineered into P. funiculosum cel7a, expressed in T. reesei, and assayed on lignocellulosic biomass. The top performer generated using this combined approach of natural diversity genome mining, experimental assays, and computational modeling produced a 41% increase in conversion extent over native P. funiculosum Cel7A, a 55% increase over the current industrial standard T. reesei Cel7A, and 10% improvement over Aspergillus oryzae Cel7C, the best natural GH7 CBH previously identified in our laboratory.

The catabolism of lignin-derived p-methoxylated aromatic compounds by Rhodococcus jostii RHA1.

Emergent strategies to valorize lignin, an abundant but underutilized aromatic biopolymer, include tandem processes that integrate chemical depolymerization and biological catalysis. To date, aromatic monomers from C-O bond cleavage of lignin have been converted to bioproducts, but the presence of recalcitrant C-C bonds in lignin limits the product yield. A promising chemocatalytic strategy that overcomes this limitation involves phenol methyl protection and autoxidation. Incorporating this into a tandem process requires microbial cell factories able to transform the p-methoxylated products in the resulting methylated lignin stream. In this study, we assessed the ability of Rhodococcus jostii RHA1 to catabolize the major aromatic products in a methylated lignin stream and elucidated the pathways responsible for this catabolism. RHA1 grew on a methylated pine lignin stream, catabolizing the major aromatic monomers: p-methoxybenzoate (p-MBA), veratrate, and veratraldehyde. Bioinformatic analyses suggested that a cytochrome P450, PbdA, and its cognate reductase, PbdB, are involved in p-MBA catabolism. Gene deletion studies established that both pbdA and pbdB are essential for growth on p-MBA and several derivatives. Furthermore, a deletion mutant of a candidate p-hydroxybenzoate (p-HBA) hydroxylase, ΔpobA, did not grow on p-HBA. Veratraldehyde and veratrate catabolism required both vanillin dehydrogenase (Vdh) and vanillate O-demethylase (VanAB), revealing previously unknown roles of these enzymes. Finally, a ΔpcaL strain grew on neither p-MBA nor veratrate, indicating they are catabolized through the ß-ketoadipate pathway. This study expands our understanding of the bacterial catabolism of aromatic compounds and facilitates the development of biocatalysts for lignin valorization.IMPORTANCELignin, an abundant aromatic polymer found in plant biomass, is a promising renewable replacement for fossil fuels as a feedstock for the chemical industry. Strategies for upgrading lignin include processes that couple the catalytic fractionation of biomass and biocatalytic transformation of the resulting aromatic compounds with a microbial cell factory. Engineering microbial cell factories for this biocatalysis requires characterization of bacterial pathways involved in catabolizing lignin-derived aromatic compounds. This study identifies new pathways for lignin-derived aromatic degradation in Rhodococcus, a genus of bacteria well suited for biocatalysis. Additionally, we describe previously unknown activities of characterized enzymes on lignin-derived compounds, expanding their utility. This work advances the development of strategies to replace fossil fuel-based feedstocks with sustainable alternatives.

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440.

There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules ("functional modules"), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida. Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE: This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

Catalytic carbon-carbon bond cleavage in lignin via manganese-zirconium-mediated autoxidation.

Efforts to produce aromatic monomers through catalytic lignin depolymerization have historically focused on aryl-ether bond cleavage. A large fraction of aromatic monomers in lignin, however, are linked by various carbon-carbon (C-C) bonds that are more challenging to cleave and limit the yields of aromatic monomers from lignin depolymerization. Here, we report a catalytic autoxidation method to cleave C-C bonds in lignin-derived dimers and oligomers from pine and poplar. The method uses manganese and zirconium salts as catalysts in acetic acid and produces aromatic carboxylic acids as primary products. The mixtures of the oxygenated monomers are efficiently converted to cis,cis-muconic acid in an engineered strain of Pseudomonas putida KT2440 that conducts aromatic O-demethylation reactions at the 4-position. This work demonstrates that autoxidation of lignin with Mn and Zr offers a catalytic strategy to increase the yield of valuable aromatic monomers from lignin.

Comparison of wild-type KT2440 and genome-reduced EM42 Pseudomonas putida strains for muconate production from aromatic compounds and glucose.

Pseudomonas putida KT2440 is a robust, aromatic catabolic bacterium that has been widely engineered to convert bio-based and waste-based feedstocks to target products. Towards industrial domestication of P. putida KT2440, rational genome reduction has been previously conducted, resulting in P. putida strain EM42, which exhibited characteristics that could be advantageous for production strains. Here, we compared P. putida KT2440- and EM42-derived strains for cis,cis-muconic acid production from an aromatic compound, p-coumarate, and in separate strains, from glucose. To our surprise, the EM42-derived strains did not outperform the KT2440-derived strains in muconate production from either substrate. In bioreactor cultivations, KT2440- and EM42-derived strains produced muconate from p-coumarate at titers of 45 g/L and 37 g/L, respectively, and from glucose at 20 g/L and 13 g/L, respectively. To provide additional insights about the differences in the parent strains, we analyzed growth profiles of KT2440 and EM42 on aromatic compounds as the sole carbon and energy sources. In general, the EM42 strain exhibited reduced growth rates but shorter growth lags than KT2440. We also observed that EM42-derived strains resulted in higher growth rates on glucose compared to KT2440-derived strains, but only at the lowest glucose concentrations tested. Transcriptomics revealed that genome reduction in EM42 had global effects on transcript levels and showed that the EM42-derived strains that produce muconate from glucose exhibit reduced modulation of gene expression in response to changes in glucose concentrations. Overall, our results highlight that additional studies are warranted to understand the effects of genome reduction on microbial metabolism and physiology, especially when intended for use in production strains.

Base-Mediated Depolymerization of Amine-Cured Epoxy Resins.

Carbon fiber-reinforced epoxy composites are used in multiple industries, including aerospace, automotive, and wind energy applications, due to their excellent strength-to-weight ratios and tunable material properties. Fortunately, recycling strategies for carbon fiber-based composites are emerging, with the primary focus on the recovery of fibers due to the cost and energy intensity in their production. In addition to fiber recovery, there is an opportunity to recycle the epoxy components such that ideal recycling strategies would yield both fibers and epoxy monomers for reuse. To that end, here we examine potassium tert-butoxide-mediated cleavage of C-O and C-N bonds in amine-cured epoxy resins. We accomplish this via developing model compounds that reflect both C-O and C-N linkages in amine-cured epoxy composites before expanding to both model linear thermoplastics and thermosets. We obtain excellent yields of both phenol (up to 97% molar yield) and amine products (up to 99 mol %) from aromatic and/or aliphatic amine-based model compounds. This system enables up to a quantitative yield of bisphenol A and up to 58% molar yield of aniline from model thermoplastic epoxy amines and 71% molar yield of BPA from a reaction with a thermoset substrate. These data correspond to a 15% mass recovery of BPA from a commercial epoxy thermoset.

Elastomeric vitrimers from designer polyhydroxyalkanoates with recyclability and biodegradability.

Cross-linked elastomers are stretchable materials that typically are not recyclable or biodegradable. Medium-chain-length polyhydroxyalkanoates (mcl-PHAs) are soft and ductile, making these bio-based polymers good candidates for biodegradable elastomers. Elasticity is commonly imparted by a cross-linked network structure, and covalent adaptable networks have emerged as a solution to prepare recyclable thermosets via triggered rearrangement of dynamic covalent bonds. Here, we develop biodegradable and recyclable elastomers by chemically installing the covalent adaptable network within biologically produced mcl-PHAs. Specifically, an engineered strain of Pseudomonas putida was used to produce mcl-PHAs containing pendent terminal alkenes as chemical handles for postfunctionalization. Thiol-ene chemistry was used to incorporate boronic ester (BE) cross-links, resulting in PHA-based vitrimers. mcl-PHAs cross-linked with BE at low density (<6 mole %) affords a soft, elastomeric material that demonstrates thermal reprocessability, biodegradability, and denetworking at end of life. The mechanical properties show potential for applications including adhesives and soft, biodegradable robotics and electronics.

PolyID: Artificial Intelligence for Discovering Performance-Advantaged and Sustainable Polymers.

A necessary transformation for a sustainable economy is the transition from fossil-derived plastics to polymers derived from biomass and waste resources. While renewable feedstocks can enhance material performance through unique chemical moieties, probing the vast material design space by experiment alone is not practically feasible. Here, we develop a machine-learning-based tool, PolyID, to reduce the design space of renewable feedstocks to enable efficient discovery of performance-advantaged, biobased polymers. PolyID is a multioutput, graph neural network specifically designed to increase accuracy and to enable quantitative structure-property relationship (QSPR) analysis for polymers. It includes a novel domain-of-validity method that was developed and applied to demonstrate how gaps in training data can be filled to improve accuracy. The model was benchmarked with both a 20% held-out subset of the original training data and 22 experimentally synthesized polymers. A mean absolute error for the glass transition temperatures of 19.8 and 26.4 °C was achieved for the test and experimental data sets, respectively. Predictions were made on polymers composed of monomers from four databases that contain biologically accessible small molecules: MetaCyc, MINEs, KEGG, and BiGG. From 1.4 × 106 accessible biobased polymers, we identified five poly(ethylene terephthalate) (PET) analogues with predicted improvements to thermal and transport performance. Experimental validation for one of the PET analogues demonstrated a glass transition temperature between 85 and 112 °C, which is higher than PET and within the predicted range of the PolyID tool. In addition to accurate predictions, we show how the model's predictions are explainable through analysis of individual bond importance for a biobased nylon. Overall, PolyID can aid the biobased polymer practitioner to navigate the vast number of renewable polymers to discover sustainable materials with enhanced performance.

Lignin conversion to ß-ketoadipic acid by Pseudomonas putida via metabolic engineering and bioprocess development.

Bioconversion of a heterogeneous mixture of lignin-related aromatic compounds (LRCs) to a single product via microbial biocatalysts is a promising approach to valorize lignin. Here, Pseudomonas putida KT2440 was engineered to convert mixed p-coumaroyl- and coniferyl-type LRCs to ß-ketoadipic acid, a precursor for performance-advantaged polymers. Expression of enzymes mediating aromatic O-demethylation, hydroxylation, and ring-opening steps was tuned, and a global regulator was deleted. ß-ketoadipate titers of 44.5 and 25 grams per liter and productivities of 1.15 and 0.66 grams per liter per hour were achieved from model LRCs and corn stover-derived LRCs, respectively, the latter representing an overall yield of 0.10 grams per gram corn stover-derived lignin. Technoeconomic analysis of the bioprocess and downstream processing predicted a ß-ketoadipate minimum selling price of $2.01 per kilogram, which is cost competitive with fossil carbon-derived adipic acid ($1.10 to 1.80 per kilogram). Overall, this work achieved bioproduction metrics with economic relevance for conversion of lignin-derived streams into a performance-advantaged bioproduct.

Multiplexed fitness profiling by RB-TnSeq elucidates pathways for lignin-related aromatic catabolism in Sphingobium sp. SYK-6.

Bioconversion of lignin-related aromatic compounds relies on robust catabolic pathways in microbes. Sphingobium sp. SYK-6 (SYK-6) is a well-characterized aromatic catabolic organism that has served as a model for microbial lignin conversion, and its utility as a biocatalyst could potentially be further improved by genome-wide metabolic analyses. To this end, we generate a randomly barcoded transposon insertion mutant (RB-TnSeq) library to study gene function in SYK-6. The library is enriched under dozens of enrichment conditions to quantify gene fitness. Several known aromatic catabolic pathways are confirmed, and RB-TnSeq affords additional detail on the genome-wide effects of each enrichment condition. Selected genes are further examined in SYK-6 or Pseudomonas putida KT2440, leading to the identification of new gene functions. The findings from this study further elucidate the metabolism of SYK-6, while also providing targets for future metabolic engineering in this organism or other hosts for the biological valorization of lignin.

Stereoinversion via Alcohol Dehydrogenases Enables Complete Catabolism of ß-1-Type Lignin-Derived Aromatic Isomers.

Sphingobium sp. strain SYK-6 is an efficient aromatic catabolic bacterium that can consume all four stereoisomers of 1,2-diguaiacylpropane-1,3-diol (DGPD), which is a ring-opened ß-1-type dimer. Recently, LdpA-mediated catabolism of erythro-DGPD was reported in SYK-6, but the catabolic pathway for threo-DGPD was as yet unknown. Here, we elucidated the catabolism of threo-DGPD, which proceeds through conversion to erythro-DGPD. When threo-DGPD was incubated with SYK-6, the Cα hydroxy groups of threo-DGPD (DGPD I and II) were initially oxidized to produce the Cα carbonyl form (DGPD-keto I and II). This initial oxidation step is catalyzed by Cα-dehydrogenases, which belong to the short-chain dehydrogenase/reductase (SDR) family and are involved in the catabolism of ß-O-4-type dimers. Analysis of seven candidate genes revealed that NAD+-dependent LigD and LigL are mainly involved in the conversion of DGPD I and II, respectively. Next, we found that DGPD-keto I and II were reduced to erythro-DGPD (DGPD III and IV) in the presence of NADPH. Genes involved in this reduction were sought from Cα-dehydrogenase and ldpA-neighboring SDR genes. The gene products of SLG_12690 (ldpC) and SLG_12640 (ldpB) catalyzed the NADPH-dependent conversion of DGPD-keto I to DGPD III and DGPD-keto II to DGPD IV, respectively. Mutational analysis further indicated that ldpC and ldpB are predominantly involved in the reduction of DGPD-keto. Together, these results demonstrate that SYK-6 harbors a comprehensive catabolic enzyme system to utilize all four ß-1-type stereoisomers through successive oxidation and reduction reactions of the Cα hydroxy group of threo-DGPD with a net stereoinversion using multiple dehydrogenases. IMPORTANCE In many catalytic depolymerization processes of lignin polymers, aryl-ether bonds are selectively cleaved, leaving carbon-carbon bonds between aromatic units intact, including dimers and oligomers with ß-1 linkages. Therefore, elucidating the catabolic system of ß-1-type lignin-derived compounds will aid in the establishment of biological funneling of heterologous lignin-derived aromatic compounds to value-added products. Here, we found that threo-DGPD was converted by successive stereoselective oxidation and reduction at the Cα position by multiple alcohol dehydrogenases to erythro-DGPD, which is further catabolized. This system is very similar to that developed to obtain enantiopure alcohols from racemic alcohols by artificially combining two enantiocomplementary alcohol dehydrogenases. The results presented here demonstrate that SYK-6 has evolved to catabolize all four stereoisomers of DGPD by incorporating this stereoinversion system into its native ß-1-type dimer catabolic system.

RB-TnSeq identifies genetic targets for improved tolerance of Pseudomonas putida towards compounds relevant to lignin conversion.

Lignin-derived mixtures intended for bioconversion commonly contain high concentrations of aromatic acids, aliphatic acids, and salts. The inherent toxicity of these chemicals places a significant bottleneck upon the effective use of microbial systems for the valorization of these mixtures. Pseudomonas putida KT2440 can tolerate stressful quantities of several lignin-related compounds, making this bacterium a promising host for converting these chemicals to valuable bioproducts. Nonetheless, further increasing P. putida tolerance to chemicals in lignin-rich substrates has the potential to improve bioprocess performance. Accordingly, we employed random barcoded transposon insertion sequencing (RB-TnSeq) to reveal genetic determinants in P. putida KT2440 that influence stress outcomes during exposure to representative constituents found in lignin-rich process streams. The fitness information obtained from the RB-TnSeq experiments informed engineering of strains via deletion or constitutive expression of several genes. Namely, ΔgacAS, ΔfleQ, ΔlapAB, ΔttgR::Ptac:ttgABC, Ptac:PP_1150:PP_1152, ΔrelA, and ΔPP_1430 mutants showed growth improvement in the presence of single compounds, and some also exhibited greater tolerance when grown using a complex chemical mixture representative of a lignin-rich chemical stream. Overall, this work demonstrates the successful implementation of a genome-scale screening tool for the identification of genes influencing stress tolerance against notable compounds within lignin-enriched chemical streams, and the genetic targets identified herein offer promising engineering targets for improving feedstock tolerance in lignin valorization strains of P. putida KT2440.