Japheth E. Gado

Bio: Japheth E. Gado is an academic researcher from National Renewable Energy Laboratory. The author has contributed to research in topics: Enzyme & Carbohydrate-binding module. The author has an hindex of 3, co-authored 6 publications receiving 88 citations. Previous affiliations of Japheth E. Gado include University of Kentucky.

Characterization and engineering of a two-enzyme system for plastics depolymerization.

Abstract: Plastics pollution represents a global environmental crisis. In response, microbes are evolving the capacity to utilize synthetic polymers as carbon and energy sources. Recently, Ideonella sakaiensis was reported to secrete a two-enzyme system to deconstruct polyethylene terephthalate (PET) to its constituent monomers. Specifically, the I. sakaiensis PETase depolymerizes PET, liberating soluble products, including mono(2-hydroxyethyl) terephthalate (MHET), which is cleaved to terephthalic acid and ethylene glycol by MHETase. Here, we report a 1.6 A resolution MHETase structure, illustrating that the MHETase core domain is similar to PETase, capped by a lid domain. Simulations of the catalytic itinerary predict that MHETase follows the canonical two-step serine hydrolase mechanism. Bioinformatics analysis suggests that MHETase evolved from ferulic acid esterases, and two homologous enzymes are shown to exhibit MHET turnover. Analysis of the two homologous enzymes and the MHETase S131G mutant demonstrates the importance of this residue for accommodation of MHET in the active site. We also demonstrate that the MHETase lid is crucial for hydrolysis of MHET and, furthermore, that MHETase does not turnover mono(2-hydroxyethyl)-furanoate or mono(2-hydroxyethyl)-isophthalate. A highly synergistic relationship between PETase and MHETase was observed for the conversion of amorphous PET film to monomers across all nonzero MHETase concentrations tested. Finally, we compare the performance of MHETase:PETase chimeric proteins of varying linker lengths, which all exhibit improved PET and MHET turnover relative to the free enzymes. Together, these results offer insights into the two-enzyme PET depolymerization system and will inform future efforts in the biological deconstruction and upcycling of mixed plastics.

Enabling microbial syringol conversion through structure-guided protein engineering

Abstract: Microbial conversion of aromatic compounds is an emerging and promising strategy for valorization of the plant biopolymer lignin. A critical and often rate-limiting reaction in aromatic catabolism is O-aryl-demethylation of the abundant aromatic methoxy groups in lignin to form diols, which enables subsequent oxidative aromatic ring-opening. Recently, a cytochrome P450 system, GcoAB, was discovered to demethylate guaiacol (2-methoxyphenol), which can be produced from coniferyl alcohol-derived lignin, to form catechol. However, native GcoAB has minimal ability to demethylate syringol (2,6-dimethoxyphenol), the analogous compound that can be produced from sinapyl alcohol-derived lignin. Despite the abundance of sinapyl alcohol-based lignin in plants, no pathway for syringol catabolism has been reported to date. Here we used structure-guided protein engineering to enable microbial syringol utilization with GcoAB. Specifically, a phenylalanine residue (GcoA-F169) interferes with the binding of syringol in the active site, and on mutation to smaller amino acids, efficient syringol O-demethylation is achieved. Crystallography indicates that syringol adopts a productive binding pose in the variant, which molecular dynamics simulations trace to the elimination of steric clash between the highly flexible side chain of GcoA-F169 and the additional methoxy group of syringol. Finally, we demonstrate in vivo syringol turnover in Pseudomonas putida KT2440 with the GcoA-F169A variant. Taken together, our findings highlight the significant potential and plasticity of cytochrome P450 aromatic O-demethylases in the biological conversion of lignin-derived aromatic compounds.

Improving Enzyme Optimum Temperature Prediction with Resampling Strategies and Ensemble Learning.

Abstract: Accurate prediction of the optimal catalytic temperature (Topt) of enzymes is vital in biotechnology, as enzymes with high Topt values are desired for enhanced reaction rates. Recently, a machine l...

Sourcing thermotolerant poly(ethylene terephthalate) hydrolase scaffolds from natural diversity

Abstract: Enzymatic deconstruction of poly(ethylene terephthalate) (PET) is under intense investigation, given the ability of hydrolase enzymes to depolymerize PET to its constituent monomers near the polymer glass transition temperature. To date, reported PET hydrolases have been sourced from a relatively narrow sequence space. Here, we identify additional PET-active biocatalysts from natural diversity by using bioinformatics and machine learning to mine 74 putative thermotolerant PET hydrolases. We successfully express, purify, and assay 51 enzymes from seven distinct phylogenetic groups; observing PET hydrolysis activity on amorphous PET film from 37 enzymes in reactions spanning pH from 4.5-9.0 and temperatures from 30-70 °C. We conduct PET hydrolysis time-course reactions with the best-performing enzymes, where we observe differences in substrate selectivity as function of PET morphology. We employed X-ray crystallography and AlphaFold to examine the enzyme architectures of all 74 candidates, revealing protein folds and accessory domains not previously associated with PET deconstruction. Overall, this study expands the number and diversity of thermotolerant scaffolds for enzymatic PET deconstruction.

AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models.

Abstract: The AlphaFold Protein Structure Database (AlphaFold DB, https://alphafold.ebi.ac.uk) is an openly accessible, extensive database of high-accuracy protein-structure predictions. Powered by AlphaFold v2.0 of DeepMind, it has enabled an unprecedented expansion of the structural coverage of the known protein-sequence space. AlphaFold DB provides programmatic access to and interactive visualization of predicted atomic coordinates, per-residue and pairwise model-confidence estimates and predicted aligned errors. The initial release of AlphaFold DB contains over 360,000 predicted structures across 21 model-organism proteomes, which will soon be expanded to cover most of the (over 100 million) representative sequences from the UniRef90 data set.

Chemical and biological catalysis for plastics recycling and upcycling

Abstract: Plastics pollution is causing an environmental crisis, prompting the development of new approaches for recycling, and upcycling. Here, we review challenges and opportunities in chemical and biological catalysis for plastics deconstruction, recycling, and upcycling. We stress the need for rigorous characterization and use of widely available substrates, such that catalyst performance can be compared across studies. Where appropriate, we draw parallels between catalysis on biomass and plastics, as both substrates are low-value, solid, recalcitrant polymers. Innovations in catalyst design and reaction engineering are needed to overcome kinetic and thermodynamic limitations of plastics deconstruction. Either chemical and biological catalysts will need to act interfacially, where catalysts function at a solid surface, or polymers will need to be solubilized or processed to smaller intermediates to facilitate improved catalyst–substrate interaction. Overall, developing catalyst-driven technologies for plastics deconstruction and upcycling is critical to incentivize improved plastics reclamation and reduce the severe global burden of plastic waste. Plastics are invaluable materials for modern society, although they result in the generation of large amounts of litter at the end of their life cycle. This Review explores the challenges and opportunities associated with the catalytic transformation of waste plastics, looking at both chemical and biological approaches to transforming such spent materials into a resource.

A promiscuous cytochrome P450 aromatic O-demethylase for lignin bioconversion.

Abstract: Microbial aromatic catabolism offers a promising approach to convert lignin, a vast source of renewable carbon, into useful products. Aryl-O-demethylation is an essential biochemical reaction to ultimately catabolize coniferyl and sinapyl lignin-derived aromatic compounds, and is often a key bottleneck for both native and engineered bioconversion pathways. Here, we report the comprehensive characterization of a promiscuous P450 aryl-O-demethylase, consisting of a cytochrome P450 protein from the family CYP255A (GcoA) and a three-domain reductase (GcoB) that together represent a new two-component P450 class. Though originally described as converting guaiacol to catechol, we show that this system efficiently demethylates both guaiacol and an unexpectedly wide variety of lignin-relevant monomers. Structural, biochemical, and computational studies of this novel two-component system elucidate the mechanism of its broad substrate specificity, presenting it as a new tool for a critical step in biological lignin conversion.