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DOE OSTI2025

A map of the rubisco biochemical landscape

Rubisco is the primary CO 2 -fixing enzyme of the biosphere, yet it has slow kinetics. The roles of evolution and chemical mechanism in constraining its biochemical function remain debated. Engineering efforts aimed at adjusting the biochemical parameters of rubisco have largely failed, although recent results indicate that the functional potential of rubisco has a wider scope than previously known. Here we developed a massively parallel assay, using an engineered Escherichia coli in which enzyme activity is coupled to growth, to systematically map the sequence–function landscape of rubisco. Composite assay of more than 99% of single-amino acid mutants versus CO 2 concentration enabled inference of enzyme velocity and apparent CO 2 affinity parameters for thousands of substitutions. This approach identified many highly conserved positions that tolerate mutation and rare mutations that improve CO 2 affinity. These data indicate that non-trivial biochemical changes are readily accessible and that the functional distance between rubiscos from diverse organisms can be traversed, laying the groundwork for further enzyme engineering efforts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Major Revisions in Arthropod Phylogeny Through Improved Supermatrix, With Support for Two Possible Waves of Land Invasion by Chelicerates

Deep phylogeny involving arthropod lineages is difficult to recover because the erosion of phylogenetic signals over time leads to unreliable multiple sequence alignment (MSA) and subsequent phylogenetic reconstruction. One way to alleviate the problem is to assemble a large number of gene sequences to compensate for the weakness in each individual gene. Such an approach has led to many robustly supported but contradictory phylogenies. A close examination shows that the supermatrix approach often suffers from two shortcomings. The first is that MSA is rarely checked for reliability and, as will be illustrated, can be poor. The second is that, to alleviate the problem of homoplasy at the third codon position of protein-coding genes due to convergent evolution of nucleotide frequencies, phylogeneticists may remove or degenerate the third codon position but may do it improperly and introduce new biases. We performed extensive reanalysis of one of such “big data” sets to highlight these two problems, and demonstrated the power and benefits of correcting or alleviating these problems. Our results support a new group with Xiphosura and Arachnopulmonata (Tetrapulmonata + Scorpiones) as sister taxa. This favors a new hypothesis in which the ancestor of Xiphosura and the extinct Eurypterida (sea scorpions, of which many later forms lived in brackish or freshwater) returned to the sea after the initial chelicerate invasion of land. Our phylogeny is supported even with the original data but processed with a new “principled” codon degeneration. We also show that removing the 1673 codon sites with both AGN and UCN codons (encoding serine) in our alignment can partially reconcile discrepancies between nucleotide-based and AA-based tree, partly because two sequences, one with AGN and the other with UCN, would be identical at the amino acid level but quite different at the nucleotide level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ADEPT: a domain independent sequence alignment strategy for gpu architectures

Bioinformatic workflows frequently make use of automated genome assembly and protein clustering tools. At the core of most of these tools, a significant portion of execution time is spent in determining optimal local alignment between two sequences. This task is performed with the Smith-Waterman algorithm, which is a dynamic programming based method. With the advent of modern sequencing technologies and increasing size of both genome and protein databases, a need for faster Smith-Waterman implementations has emerged. Multiple SIMD strategies for the Smith-Waterman algorithm are available for CPUs. However, with the move of HPC facilities towards accelerator based architectures, a need for an efficient GPU accelerated strategy has emerged. Existing GPU based strategies have either been optimized for a specific type of characters (Nucleotides or Amino Acids) or for only a handful of application use-cases. In this paper, we present ADEPT, a new sequence alignment strategy for GPU architectures that is domain independent, supporting alignment of sequences from both genomes and proteins. Our proposed strategy uses GPU specific optimizations that do not rely on the nature of sequence. We demonstrate the feasibility of this strategy by implementing the Smith-Waterman algorithm and comparing it to similar CPU strategies as well as the fastest known GPU methods for each domain. ADEPT’s driver enables it to scale across multiple GPUs and allows easy integration into software pipelines which utilize large scale computational systems. We have shown that the ADEPT based Smith-Waterman algorithm demonstrates a peak performance of 360 GCUPS and 497 GCUPs for protein based and DNA based datasets respectively on a single GPU node (8 GPUs) of the Cori Supercomputer. Overall ADEPT shows 10x faster performance in a node-to-node comparison against a corresponding SIMD CPU implementation. ADEPT demonstrates a performance that is either comparable or better than existing GPU strategies. We demonstrated the efficacy of ADEPT in supporting existing bionformatics software pipelines by integrating ADEPT in MetaHipMer a high-performance denovo metagenome assembler and PASTIS a high-performance protein similarity graph construction pipeline. Our results show 10% and 30% boost of performance in MetaHipMer and PASTIS respectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Simultaneous carbon catabolite repression governs sugar and aromatic co-utilization in Pseudomonas putida M2

ABSTRACT Pseudomonas putida have emerged as promising biocatalysts for the conversion of sugars and aromatic compounds obtained from lignocellulosic biomass. Understanding the role of carbon catabolite repression (CCR) in these strains is critical to optimize biomass conversion to fuels and chemicals. The CCR functioning in P. putida M2, a strain capable of consuming both hexose and pentose sugars as well as aromatic compounds, was investigated by cultivation experiments, proteomics, and CRISPRi-based gene repression. Strain M2 co-utilized sugars and aromatic compounds simultaneously; however, during cultivation with glucose and aromatic compounds ( p- coumarate and ferulate) mixture, intermediates (4-hydroxybenzoate and vanillate) accumulated, and substrate consumption was incomplete. In contrast, xylose-aromatic consumption resulted in transient intermediate accumulation and complete aromatic consumption, while xylose was incompletely consumed. Proteomics analysis revealed that glucose exerted stronger repression than xylose on the aromatic catabolic proteins. Key glucose (Eda) and xylose (XylX) catabolic proteins were also identified at lower abundance during cultivation with aromatic compounds implying simultaneous catabolite repression by sugars and aromatic compounds. Reduction of crc expression via CRISPRi led to faster growth and glucose and p -coumarate uptake in the CRISPRi strains compared to the control, while no difference was observed on xylose+ p -coumarate. The increased abundances of Eda and amino acid biosynthesis proteins in the CRISPRi strain further supported these observations. Lastly, small RNAs (sRNAs) sequencing results showed that CrcY and CrcZ homologues levels in M2, previously identified in P. putida strains, were lower under strong CCR (glucose+ p -coumarate) condition compared to when repression was absent ( p -coumarate or glucose only). IMPORTANCE A newly isolated Pseudomonas putida strain, P. putida M2, can utilize both hexose and pentose sugars as well as aromatic compounds making it a promising host for the valorization of lignocellulosic biomass. Pseudomonads have developed a regulatory strategy, carbon catabolite repression, to control the assimilation of carbon sources in the environment. Carbon catabolite repression may impede the simultaneous and complete metabolism of sugars and aromatic compounds present in lignocellulosic biomass and hinder the development of an efficient industrial biocatalyst. This study provides insight into the cellular physiology and proteome during mixed-substrate utilization in P. putida M2. The phenotypic and proteomics results demonstrated simultaneous catabolite repression in the sugar-aromatic mixtures, while the CRISPRi and sRNA sequencing demonstrated the potential role of the crc gene and small RNAs in carbon catabolite repression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Single Amino Acid Mutations Affect Zika Virus Replication In Vitro and Virulence In Vivo

The 2014–2016 Zika virus (ZIKV) epidemic in the Americas resulted in large deposits of next-generation sequencing data from clinical samples. This resource was mined to identify emerging mutations and trends in mutations as the outbreak progressed over time. Information on transmission dynamics, prevalence, and persistence of intra-host mutants, and the position of a mutation on a protein were then used to prioritize 544 reported mutations based on their ability to impact ZIKV phenotype. Using this criteria, six mutants (representing naturally occurring mutations) were generated as synthetic infectious clones using a 2015 Puerto Rican epidemic strain PRVABC59 as the parental backbone. The phenotypes of these naturally occurring variants were examined using both cell culture and murine model systems. Mutants had distinct phenotypes, including changes in replication rate, embryo death, and decreased head size. In particular, a NS2B mutant previously detected during in vivo studies in rhesus macaques was found to cause lethal infections in adult mice, abortions in pregnant females, and increased viral genome copies in both brain tissue and blood of female mice. Additionally, mutants with changes in the region of NS3 that interfaces with NS5 during replication displayed reduced replication in the blood of adult mice. This analytical pathway, integrating both bioinformatic and wet lab experiments, provides a foundation for understanding how naturally occurring single mutations affect disease outcome and can be used to predict the of severity of future ZIKV outbreaks. To determine if naturally occurring individual mutations in the Zika virus epidemic genotype affect viral virulence or replication rate in vitro or in vivo, we generated an infectious clone representing the epidemic genotype of stain Puerto Rico, 2015. Using this clone, six mutants were created by changing nucleotides in the genome to cause one to two amino acid substitutions in the encoded proteins. The six mutants we generated represent mutations that differentiated the early epidemic genotype from genotypes that were either ancestral or that occurred later in the epidemic. We assayed each mutant for changes in growth rate, and for virulence in adult mice and pregnant mice. Three of the mutants caused catastrophic embryo effects including increased embryonic death or significant decrease in head diameter. Three other mutants that had mutations in a genome region associated with replication resulted in changes in in vitro and in vivo replication rates. These results illustrate the potential impact of individual mutations in viral phenotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Activity-based cell sorting reveals responses of uncultured archaea and bacteria to substrate amendment

Metagenomic studies have revolutionized our understanding of the metabolic potential of uncultured microorganisms in various ecosystems. However, many of these genomic predictions have yet to be experimentally tested, and the functional expression of genomic potential often remains unaddressed. In order to obtain a more thorough understanding of cell physiology, novel techniques capable of testing microbial metabolism under close to in situ conditions must be developed. Here, we provide a benchmark study to demonstrate that bioorthogonal non-canonical amino acid tagging (BONCAT) in combination with fluorescence-activated cell sorting (FACS) and 16S rRNA gene sequencing can be used to identify anabolically active members of a microbial community incubated in the presence of various growth substrates or under changing physicochemical conditions. We applied this approach to a hot spring sediment microbiome from Yellowstone National Park (Wyoming, USA) and identified several microbes that changed their activity levels in response to substrate addition, including uncultured members of the phyla Thaumarchaeota, Acidobacteria, and Fervidibacteria. Because shifts in activity in response to substrate amendment or headspace changes are indicative of microbial preferences for particular growth conditions, results from this and future BONCAT-FACS studies could inform the development of cultivation media to specifically enrich uncultured microbes. Most importantly, BONCAT-FACS is capable of providing information on the physiology of uncultured organisms at as close to in situ conditions as experimentally possible.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structural characterization of a GNAT family acetyltransferase from Elizabethkingia anophelis bound to acetyl-CoA reveals a new dimeric interface

General control non-repressible 5 (GCN5)-related N-acetyltransferases (GNATs) catalyse the acetylation of a diverse range of substrates, thereby orchestrating a variety of biological processes within prokaryotes and eukaryotes. GNAT enzymes can catalyze the transfer of an acetyl group from acetyl coenzyme A to substrates such as aminoglycoside antibiotics, amino acids, polyamines, peptides, vitamins, catecholamines, and large macromolecules including proteins. Although GNATs generally exhibit low to moderate sequence identity, they share a conserved catalytic fold and conserved structural motifs. In this current study we characterize the high-resolution X-ray crystallographic structure of a GNAT enzyme bound with acetyl-CoA from Elizabethkingia anophelis , an important multi-drug resistant bacterium. The tertiary structure is comprised of six α-helices and nine β-strands, and is similar with other GNATs. We identify a new and uncharacterized GNAT dimer interface, which is conserved in at least two other unpublished GNAT structures. This suggests that GNAT enzymes can form at least five different types of dimers, in addition to a range of other oligomers including trimer, tetramer, hexamer, and dodecamer assemblies. The high-resolution structure presented in this study is suitable for future in-silico docking and structure–activity relationship studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Amino acid substrate specificities and tissue expression profiles of the nine CYP79A encoding genes in Sorghum bicolor

Cytochrome P450s of the CYP79 family catalyze two N-hydroxylation reactions, converting a selected number of amino acids into the corresponding oximes. The sorghum genome (Sorghum bicolor) harbours nine CYP79A encoding genes, and here sequence comparisons of the CYP79As along with their substrate recognition sites (SRSs) are provided. The substrate specificity of previously uncharacterized CYP79As was investigated by transient expression in Nicotiana benthamiana and subsequent transformation of the oximes formed into the corresponding stable oxime glucosides catalyzed by endogenous UDPG-glucosyltransferases (UGTs). CYP79A61 uses phenylalanine as a substrate, whereas CYP79A91, CYP79A93, and CYP79A95 use valine and isoleucine as substrates, with CYP79A93 showing the ability also to use phenylalanine. CYP79A94 uses isoleucine as a substrate. Analysis of 249 sorghum transcriptomes from two different sorghum cultivars showed the expression levels and tissue-specific expression of the CYP79As. CYP79A1 is the committed gene in dhurrin formation and was the highest expressed gene in most tissues/organs. CYP79A61 was primarily expressed in fully developed leaf blades and leaf sheaths. CYP79A91 and CYP79A92 were expressed mainly in roots >200 cm below ground, while CYP79A93 and CYP79A94 were most highly expressed in the leaf collar and leaf sheath, respectively. Here, the possible signalling effects of the oximes and their metabolites produced in different sorghum tissues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗
DOE OSTI2021

Coxsackievirus B4 sewage-isolate induces pancreatitis after oral infection of mice

ABSTRACT Numerous serotypes which belong to the genus Enterovirus (EV) show variability in their virulence and clinical manifestations. They are also known to undergo changes caused by mutations and recombination during their circulation in the environment and the population. Various EV serotypes are prevalent in groundwater, wastewater and surface waters. Our previous studies showed that oral infection induces pancreatitis depending on specific conditions, such as gravidity, in an outbred murine model. Our aim in the present study was to further explore the pancreatic histopathology in an outbred mouse model following oral infection with clinical isolates from a patient who had aseptic meningitis and an isolate from a treated-sewage sample recovered from the residential area of the patient. The isolates were identified as coxsackievirus B4 (CVB4) in tissue culture. The CVB4 sewage-isolate induced pancreatitis after oral infection. In contrast, pancreatitis was absent following infection with the clinical isolates. Comparison of polyprotein sequences showed that the treated-sewage strains differed from the patient's isolates by 9 and 11 amino acids. We conclude that the isolates of clinical and environmental origin differed in their pathogenic properties and showed genetic variation.

Benkoova, Brigita↗
DOE OSTI2020

Properties of protein unfolded states suggest broad selection for expanded conformational ensembles

Much attention is being paid to conformational biases in the ensembles of intrinsically disordered proteins. However, it is currently unknown whether or how conformational biases within the disordered ensembles of foldable proteins affect function in vivo. Recently, we demonstrated that water can be a good solvent for unfolded polypeptide chains, even those with a hydrophobic and charged sequence composition typical of folded proteins. These results run counter to the generally accepted model that protein folding begins with hydrophobicity-driven chain collapse. Here we investigate what other features, beyond amino acid composition, govern chain collapse. We found that local clustering of hydrophobic and/or charged residues leads to significant collapse of the unfolded ensemble of pertactin, a secreted autotransporter virulence protein from Bordetella pertussis , as measured by small angle X-ray scattering (SAXS). Sequence patterns that lead to collapse also correlate with increased intermolecular polypeptide chain association and aggregation. Crucially, sequence patterns that support an expanded conformational ensemble enhance pertactin secretion to the bacterial cell surface. Similar sequence pattern features are enriched across the large and diverse family of autotransporter virulence proteins, suggesting sequence patterns that favor an expanded conformational ensemble are under selection for efficient autotransporter protein secretion, a necessary prerequisite for virulence. More broadly, we found that sequence patterns that lead to more expanded conformational ensembles are enriched across water-soluble proteins in general, suggesting protein sequences are under selection to regulate collapse and minimize protein aggregation, in addition to their roles in stabilizing folded protein structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

De novo design and Rosetta-based assessment of high-affinity antibody variable regions (Fv) against the SARS-CoV -2 spike receptor binding domain ( RBD )

The continued emergence of new SARS-CoV-2 variants has accentuated the growing need for fast and reliable methods for the design of potentially neutralizing antibodies (Abs) to counter immune evasion by the virus. Here, we report on the de novo computational design of high-affinity Ab variable regions (Fv) through the recombination of VDJ genes targeting the most solvent-exposed hACE2-binding residues of the SARS-CoV-2 spike receptor binding domain (RBD) protein using the software tool OptMAVEn-2.0. Subsequently, we carried out computational affinity maturation of the designed variable regions through amino acid substitutions for improved binding with the target epitope. Immunogenicity of designs was restricted by preferring designs that match sequences from a 9-mer library of “human Abs” based on a human string content score. We generated 106 different antibody designs and reported in detail on the top five that trade-off the greatest computational binding affinity for the RBD with human string content scores. We further describe computational evaluation of the top five designs produced by OptMAVEn-2.0 using a Rosetta-based approach. We used Rosetta SnugDock for local docking of the designs to evaluate their potential to bind the spike RBD and performed “forward folding” with DeepAb to assess their potential to fold into the designed structures. Ultimately, our results identified one designed Ab variable region, P1.D1, as a particularly promising candidate for experimental testing. This effort puts forth a computational workflow for the de novo design and evaluation of Abs that can quickly be adapted to target spike epitopes of emerging SARS-CoV-2 variants or other antigenic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ancestral archaea expanded the genetic code with pyrrolysine

The pyrrolysyl-tRNA synthetase (PylRS) facilitates the cotranslational installation of the 22nd amino acid pyrrolysine. Owing to its tolerance for diverse amino acid substrates, and its orthogonality in multiple organisms, PylRS has emerged as a major route to install noncanonical amino acids into proteins in living cells. Recently, a novel class of PylRS enzymes was identified in a subset of methanogenic archaea. Enzymes within this class (ΔPylSn) lack the N-terminal tRNA-binding domain that is widely conserved amongst PylRS enzymes, yet remain active and orthogonal in bacteria and eukaryotes. In this study, we use biochemical and in vivo UAG-readthrough assays to characterize the aminoacylation efficiency and substrate spectrum of a ΔPylSn class PylRS from the archaeon Candidatus Methanomethylophilus alvus. We show that, compared with the full-length enzyme from Methanosarcina mazei, the Ca. M. alvus PylRS displays reduced aminoacylation efficiency but an expanded amino acid substrate spectrum. To gain insight into the evolution of ΔPylSn enzymes, we performed molecular phylogeny using 156 PylRS and 105 pyrrolysine tRNA (tRNA Pyl ) sequences from diverse archaea and bacteria. This analysis suggests that the PylRS•tRNA Pyl pair diverged before the evolution of the three domains of life, placing an early limit on the evolution of the Pyl-decoding trait. Furthermore, our results document the coevolutionary history of PylRS and tRNA Pyl and reveal the emergence of tRNA Pyl sequences with unique A73 and U73 discriminator bases. The orthogonality of these tRNA Pyl species with the more common G73-containing tRNA Pyl will enable future efforts to engineer PylRS systems for further genetic code expansion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Correction for Thompson et al., “Fatty Acid and Alcohol Metabolism in Pseudomonas putida : Functional Analysis Using Random Barcode Transposon Sequencing”

Volume 86, no. 21, 2020, e01665-20, https://doi.org/10.1128/AEM.01665-20. Readers should note that when the authors created the deletion mutant of PP_2675, they deleted the entire region between the gene’s start and stop codons. However, this also deleted the DNA that codes for the first 14 amino acids of the overlapping ORF PP_2676. Additionally, the originally published URL for the JBEI public strain repository was incorrect. The correct link to all strains and plasmids in this study is https://public-registry.jbei .org/folders/641.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method which directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy-to-use, generalizable, and scalable. With accompanying software, DeCOIL can be readily implemented to generate desired informed libraries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Origins of glycan selectivity in streptococcal Siglec-like adhesins suggest mechanisms of receptor adaptation

Bacterial binding to host receptors underlies both commensalism and pathogenesis. Many streptococci adhere to protein-attached carbohydrates expressed on cell surfaces using Siglec-like binding regions (SLBRs). The precise glycan repertoire recognized may dictate whether the organism is a strict commensal versus a pathogen. However, it is currently not clear what drives receptor selectivity. Here, we use five representative SLBRs and identify regions of the receptor binding site that are hypervariable in sequence and structure. We show that these regions control the identity of the preferred carbohydrate ligand using chimeragenesis and single amino acid substitutions. We further evaluate how the identity of the preferred ligand affects the interaction with glycoprotein receptors in human saliva and plasma samples. As point mutations can change the preferred human receptor, these studies suggest how streptococci may adapt to changes in the environmental glycan repertoire.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more.1 One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and Fireprot to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more. One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and FireProt to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗