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At least 415 records · Page 23

Using a Genetic Algorithm to Optimize Configurations in a Data-Driven Application

Users of highly-configurable software systems often want to optimize a particular objective such as improving a functional outcome or increasing system performance. One approach is to use an evolutionary algorithm. However, many applications today are data-driven, meaning they depend on inputs or data which can be complex and varied. Hence, a search needs to be run (and re-run) for all inputs, making optimization a heavy-weight and potentially impractical process. In this paper, we explore this issue on a data-driven highly-configurable scientific application. We build an exhaustive database containing 3,000 configurations and 10,000 inputs, leading to almost 100 million records as our oracle, and then run a genetic algorithm individually on each of the 10,000 inputs. We ask if (1) a genetic algorithm can find configurations to improve functional objectives; (2) whether patterns of best configurations over all input data emerge; and (3) if we can we use sampling to approximate the results. We find that the original (default) configuration is best only 34% of the time, while clear patterns emerge of other best configurations. Out of 3,000 possible configurations, only 112 distinct configurations achieve the optimal result at least once across all 10,000 inputs, suggesting the potential for lighter weight optimization approaches. We show that sampling of the input data finds similar patterns at a lower cost.

Sinha, Urjoshi↗

The origin and evolution of viruses inferred from fold family structure

The canonical frameworks of viral evolution describe viruses as cellular predecessors, reduced forms of cells, or entities that escaped cellular control. The discovery of giant viruses has changed these standard paradigms. Their genetic, proteomic and structural complexities resemble those of cells, prompting a redefinition and reclassification of viruses. In a previous genome-wide analysis of the evolution of structural domains in proteomes, with domains defined at the fold superfamily level, we found the origins of viruses intertwined with those of ancient cells. In this review, we extend these data-driven analyses to the study of fold families confirming the co-evolution of viruses and ancient cells and the genetic ability of viruses to foster molecular innovation. The results support our suggestion that viruses arose by genomic reduction from ancient cells and validate a co-evolutionary ‘symbiogenic’ model of viral origins.

59 BASIC BIOLOGICAL SCIENCES↗

Changes to virus taxonomy, the international code of virus classification and nomenclature, and the ICTV statutes ratified by the International Committee on Taxonomy of Viruses (2025)

Abstract The 56th meeting of the Executive Committee (EC) of the International Committee on Taxonomy of Viruses (ICTV) was held in Bari, Italy, in July/August, 2024, and 115 submitted taxonomy proposals were reviewed. A total of 112 were subsequently ratified by the ICTV membership. An additional 9 error correction proposals were also approved in August 2025. This article lists the taxonomy proposals that have now been incorporated into release 40 version v2 of the Master Species List ( https://ictv.global/msl ), the Virus Metadata Resource ( https://ictv.global/vmr ), and associated ICTV databases. In addition to the assignments of 1,563 new virus species, 243genera, 55 families, 11 orders, and 8 classes, there were substantial additions to higher taxonomic ranks. These include the creation of a new realm ( Singelaviria ), which is based on the recognition of a separate evolutionary origin for the hallmark capsid genes of members of the kingdom Helvetiavirae. These express capsid proteins forming a single jelly-roll fold that is structurally and evolutionarily distinct from those of members of the family Bamfordvirae , assigned to the realm Varidnaviria . Furthermore, the realm Varidnaviria underwent a major reorganization, including the addition of a new kingdom, Abadenavirae . Another notable change was the classification of the vertebrate-infecting single-stranded DNA anellovirids into a new phylum Commensaviricota (kingdom Shotokuvirae , realm Monodnaviria ). Archaeal viruses infecting the hyperthermophilic Archaeoglobi were assigned to a new phylum Calorviricota , in the kingdom Trapavirae (realm Monodnaviria ), whereas RNA viruses infecting hyperthermophilic bacteria were classified into a new phylum Artimaviricota (realm Riboviria ). In recognition of his extensive and valuable contributions to virus taxonomic developments in Study Groups and over the period of his EC membership, Stuart Siddell was honoured as a new life member of the ICTV. The ICTV has created a new strategy for disseminating information on taxonomy advances through annual open-access publication of citeable taxonomy proposal summaries from each ICTV Subcommittee. A collective total of 354 co-authors of the seven summaries were drawn from members of each Subcommittee, the EC, and a very large number of contributors from the wider virology community.

Simmonds, Peter (ORCID:0000000279644700)↗

Quantifying microbial control of soil organic matter dynamics at macrosystem scales

Soil organic matter (SOM) stocks, decomposition and persistence are largely the product of controls that act locally. Yet the controls are shaped and interact at multiple spatiotemporal scales, from which macrosystem patterns in SOM emerge. Theory on SOM turnover recognizes the resulting spatial and temporal conditionality in the effect sizes of controls that play out across macrosystems, and couples them through evolutionary and community assembly processes. For example, climate history shapes plant functional traits, which in turn interact with contemporary climate to influence SOM dynamics. Selection and assembly also shape the functional traits of soil decomposer communities, but it is less clear how in turn these traits influence temporal macrosystem patterns in SOM turnover. Here, we review evidence that establishes the expectation that selection and assembly should generate decomposer communities across macrosystems that have distinct functional effects on SOM dynamics. Representation of this knowledge in soil biogeochemical models affects the magnitude and direction of projected SOM responses under global change. Yet there is high uncertainty and low confidence in these projections. To address these issues, we make the case that a coordinated set of empirical practices are required which necessitate (1) greater use of statistical approaches in biogeochemistry that are suited to causative inference; (2) long-term, macrosystem-scale, observational and experimental networks to reveal conditionality in effect sizes, and embedded correlation, in controls on SOM turnover; and (3) use of multiple measurement grains to capture local- and macroscale variation in controls and outcomes, to avoid obscuring causative understanding through data aggregation. Here, when employed together, along with process-based models to synthesize knowledge and guide further empirical work, we believe these practices will rapidly advance understanding of microbial controls on SOM and improve carbon cycle projections that guide policies on climate adaptation and mitigation.

59 BASIC BIOLOGICAL SCIENCES↗

Differential DNA methylation and metabolite profiling of Atlantic killifish (Fundulus heteroclitus) from the New Bedford Harbor Superfund site

Atlantic killifish (Fundulus heteroclitus) is a valuable model in evolutionary toxicology to study how the interactions between genetic and environmental factors serve the adaptive ability of organisms to resist chemical pollution. Killifish populations inhabiting environmental toxicant-contaminated New Bedford Harbor (NBH) show phenotypes tolerant to polychlorinated biphenyls (PCBs) and differences at the transcriptional and genomic levels. However, limited research has explored epigenetic alterations and metabolic effects in NBH killifish. To identify the involvement of epigenetic and metabolic regulation in the adaptive response of killifish, we investigated tissue- and sex-specific differences in global DNA methylation and metabolomic profiles of NBH killifish populations, compared to sensitive populations from a non-polluted site, Scorton Creek (SC). The results revealed that liver-specific global DNA hypomethylation and differential metabolites were evident in fish from NBH compared with those from SC. The sex-specific differences were not greater than the tissue-specific differences. We demonstrated liver-specific enriched metabolic pathways (e.g., amino acid metabolic pathways converged into the urea cycle and glutathione metabolism), suggesting possible crosstalk between differential metabolites and DNA hypomethylation in the livers of NBH killifish. Additional investigation of methylated gene regions is necessary to understand the functional role of DNA hypomethylation in the regulation of enzyme-encoding genes associated with metabolic processes and physiological changes in NBH populations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The PshX subunit of the photochemical reaction center from Heliobacterium modesticaldum acts as a low-energy antenna

The anoxygenic phototrophic bacterium Heliobacterium modesticaldum contains a photochemical reaction center protein complex (called the HbRC) consisting of a homodimer of the PshA polypeptide and two copies of a newly discovered polypeptide called PshX, which is a single transmembrane helix that binds two bacteriochlorophyll g molecules. Here, to assess the function of PshX, we produced a ΔpshX strain of Hbt. modesticaldum by leveraging the endogenous Hbt. modesticaldum Type I-A CRISPR-Cas system to aid in mutant selection. We optimized this system by separating the homologous recombination and CRISPR-based selection steps into two plasmid transformations, allowing for markerless gene replacement. Fluorescence and low-temperature absorbance of the purified HbRC from the wild-type and ΔpshX strains showed that the bacteriochlorophylls bound by PshX have the lowest site energies in the entire HbRC. This indicates that PshX acts as a low-energy antenna subunit, participating in entropy-assisted uphill energy transfer towards the P 800 special bacteriochlorophyll g pair. We further discuss the role that PshX may play in stability of the HbRC, its conservation in other heliobacterial species, and the evolutionary pressure to produce and maintain single-TMH subunits in similar locations in other reaction centers.

59 BASIC BIOLOGICAL SCIENCES↗

Preface: special issues on photosystem II

Here, the appearance of oxygenic photosynthesis 3–4 billion years ago is arguably one of the most important evolutionary developments which radically transformed both the biotic and abiotic landscapes of Earth. The presence of molecular oxygen enabled the evolution of complex lifeforms requiring large amounts of chemical energy which could only be produced by aerobic respiration. Additionally, molecular oxygen remodeled the geochemistry of the planet during its transition from a reducing to an oxidizing atmosphere during the Great Oxidation Event. Central to these processes is Photosystem II (PS II), the light energy-driven, water-plastoquinone oxidoreductase which initially evolved in cyanobacteria and subsequently was incorporated, along with Photosystem I (PS I), the cytochrome b 6 f complex and the Ndh complex, into all algae and higher plants by the process of endosymbiosis. This membrane protein complex releases molecular oxygen and protons as the byproducts of water splitting and produces plastoquinol, which provides reducing equivalents that are used sequentially by the cytochrome b 6 /f complex, PS I, and ultimately, as NADPH + H + , by the Calvin–Benson–Bassham cycle. Additionally, the protons released by PS II (and those pumped by the cytochrome b 6 /f complex and the NDH complex (during cyclic electron transfer)) form the proton motive force that drives ATP synthesis via the ATP Synthase, thus providing the chemical energy source for carbon fixation.

59 BASIC BIOLOGICAL SCIENCES↗

A Review of Coccidioides Research, Outstanding Questions in the Field, and Contributions by Women Scientists

Abstract Purpose of Review Coccidioidomycosis is an infectious disease that gained clinical significance in the early 20th century. Many of the foundational contributions to coccidioidomycosis research, including the discovery of the fungal disease agent, Coccidioides spp., were made by women. We review recent progress in Coccidioides research and big questions remaining in the field, while highlighting some of the contributions from women. Recent Findings New molecular-based techniques provide a promising method for detecting Coccidioides, which can help determine the dominate reservoir host and ideal environmental conditions for growth. Genetic and genomic analyses have allowed an understanding of population structure, species level diversity, and evolutionary histories. We present a current, comprehensive genome list, where women contributed many of these entries. Several efforts to develop a coccidioidomycosis vaccine are underway. Summary Women continue to pioneer research on Coccidioides, including the relationships between the fungi and the environment, genetics, and clinical observations. Significant questions remain in the field of Coccidioides, including the main host reservoir, the relationships between genotypic and phenotypic variation, and the underlying cause for chronic clinical coccidioidomycosis cases.

59 BASIC BIOLOGICAL SCIENCES↗

Chlorophylls as primary electron acceptors in reaction centers

Photosynthetic Reaction Centers (RCs) can be considered blueprints for highly efficient energy transfer. Embedded with an array of cofactors, including (bacterio)chlorophyll ((B)Chl) and (B)pheophytin ((B)Pheo) molecules, RCs function with a high quantum yield that spans a wide spectral range. Understanding the principles that underlie their function can influence the design of the next generation of artificial photosynthetic devices. We are particularly interested in the factors that influence the early stages of light-driven charge separation in RCs. With the recent publication of several highly anticipated RC structures and advanced computational methods available, it is possible to probe both the geometric and electronic structures of an array of RCs. In this chapter, we review the electronic and geometric structures of the (B)Chl and (B)Pheo primary electron acceptors from fiveRCs, comprising both Type I and Type II RCs and representing both heterodimeric and homodimeric systems. We showcase the dimeric A0•- state of Type I RCs, whereby the unpaired electron is delocalized, to various extents, over two (B)Chl molecules (B)Chl2 and (B)Chl3. This delocalization is controlled by several factors, including the structure of the (B)Chls, interactions with the surrounding protein matrix, and the orientation and distances of the cofactors themselves. In contrast, the primary acceptors of Type II RCs are entirely monomeric, with electron density residing solely on the (B)Pheo. We compare the natural design of the primary acceptors of the Type I and Type II RCs from both an evolutionary and application based perspective.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SIF-based GPP modeling for evergreen forests considering the seasonal variation in maximum photochemical efficiency

Solar-induced chlorophyll fluorescence (SIF) has shown great potential in estimating gross primary production (GPP). However, their quantitative relationship is not invariant, which undermines the reliability of empirical SIF-based GPP estimation at fine spatiotemporal scales, especially under extreme conditions. In this study, we developed a parsimonious mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) by employing the Mechanistic Light Response framework and Eco-Evolutionary theory to describe the light and dark reactions during photosynthesis, respectively. Specifically, we found that considering the seasonal variation in a key parameter of the MLR framework, the maximum photochemical efficiency of photosystem II (Φ PSIImax ), can avoid the GPP overestimation in winter and early spring due to the relatively low environmental sensitivity of SIF. Compared to the estimates from other benchmark models, our GPP estimates were closer to the 1: 1 line and had higher accuracy (average R 2 = 0.86, RMSE=1.99 μmol m -2 s -1 ) across sites. Furthermore, the changes in the relationship between SIF and J (refers to the electron transport rate) contribute a lot to the dynamic SIF–GPP relationship in this study, while the J–GPP relationship is less variant when the temperature drops. Further, the seasonal variation in the SIF–J relationship, especially the reduction in its slope at low temperatures, is found largely explained by the Φ PSIImax . These results indicate the importance of the uncertainty caused by the variation in the SIF–J relationship for SIF-based GPP estimation, and the consideration of changes in Φ PSIImax under extreme conditions (such as severe winter in this study) is crucial for the improvement of GPP estimation via SIF.

59 BASIC BIOLOGICAL SCIENCES↗

The state of algal genome quality and diversity

The genomic era of biology has created unprecedented opportunity to study how life works, including understanding evolutionary principles, bioprospecting for novel antibiotics, and genetic manipulation of bioeconomically-relevant species. While genome sequencing and genomic analysis was previously restricted to large-scale projects and consortia, sequencing has become democratized. However, as genomics has become commonplace, the cataloging of sequenced organisms has become challenging, and standardized practices for sequencing, assembly, and annotation have not been adopted. This is equally true in research fields such as algal biology, despite the growing importance of algae in a bio-based economy. Here, in this study, we provide a comprehensive review of the state of eukaryotic algal genomics, explore the quality of algal genome assemblies, and identify the biases and gaps in the current species distribution to inform the development of future genome projects. Overall, we find a trend of declining quality of genomic resources, including a reduction in assembly quality, gene annotation quality, and genome completeness. Potential solutions to improve genome quality include widespread utilization of long read and scaffolding technologies, implementation of standards for assembly quality, evidence-based gene annotation and requisite publication, and support of continued development of gene prediction and genome assessment software.

59 BASIC BIOLOGICAL SCIENCES↗

Selection-enriched genomic loci (SEGL) reveals genetic loci for environmental adaptation and photosynthetic productivity in Chlamydomonas reinhardtii

This work demonstrates an approach to produce and select hybrid algal strains exhibiting increased photosynthetic productivity under multiple environmental conditions. This simultaneously addresses two major impediments to improving algal bioenergy production: 1) generating new genetic variants with improved performance; and 2) disentangling complex interactions between genetic and physiological factors contributing to these improvements. We pooled progeny generated from mating two environmental isolates of the green alga Chlamydomonas reinhardtii and cultured the pools under multiple environmental conditions. Strains from the outcompeting populations showed substantial (in some cases over 3 fold) increases in productivity over the parental lines under certain environments related to biomass production, including laboratory conditions as well as hyperoxia, fluctuating light, high salinity and high temperature. The results indicate that C. reinhardtii has remarkable, untapped, directed evolution capacity that may be harnessed using breeding and competition approaches. The populations were deep sequenced at multiple time points to identify “Selection-Enriched Genomic Loci” (SEGL) that accumulated in the populations, and thus likely confer increased fitness under the respective environmental conditions. With improved resolution, SEGL mapping can identify allelic combinations used for targeted breeding approaches, generating elite algal lines with multiple desirable traits, as well as to further understand the genetic and mechanistic bases of photosynthetic productivity. Increasing the photosynthetic efficiency of algae during biomass production is perhaps the most critical hurdle for economically sustainable algal based biofuels. This presents unique challenges because modifications designed to increase photosynthesis often result in decreased fitness, due to production of toxic reactive oxygen species when photosynthesis is not adequately regulated. These problems are exacerbated under natural and outdoor production environments because of the complex nature of photosynthesis and the multifaceted interactions between genetic, environmental and physiological factors. Here, we demonstrate a high throughput biotechnological screening approach that simultaneously produces algal strains with highly increased autotrophic productivity and identifies genomic loci contributing to these improvements. Our results demonstrate that Chlamydomonas reinhardtii exhibits high directed evolutionary capacity readily accessed through breeding and selection.

59 BASIC BIOLOGICAL SCIENCES↗

Multi-objective optimization of sustainable aviation fuel production pathways in the U.S. Corn Belt

As a potential source of low-carbon transportation energy, biofuels offer certain advantages over vehicle electrification (e.g., lower societal vulnerability to grid failures, and improved range of sustainable aviation), but also several challenges, including cost, carbon intensity, and land usage. There are also well-founded concerns that biofuel supply chains could be disrupted if extreme weather events impact feedstock yields. In this paper, we explore the use of multi-objective optimization to identify biofuel production pathways that balance cost, greenhouse gas emissions, and supply vulnerability to extreme weather. We compare the use of three different many-objective evolutionary algorithms and linear programming in optimizing biomass cultivation decisions in the U.S. Corn Belt under weather uncertainty using historical, modeled, and synthetic yield data. We consider four feedstock choices (corn, soy, switchgrass, and algae) with two land types (agricultural and marginal lands) and evaluate decisions using three alternative spatial resolutions (ranging from the USDA agricultural district level to the state level). Results show that feedstock choice is the primary driver of objective performance (i.e., the position and shape of 3D, approximate Pareto frontiers). Spatial diversification is a less effective tool in reducing exposure to weather-caused drops in crop yield.

09 BIOMASS FUELS↗

Recent developments in pretreatment technologies on lignocellulosic biomass: Effect of key parameters, technological improvements, and challenges

Lignocellulosic biomass is an inexpensive renewable source that can be used to produce biofuels and bioproducts. The recalcitrance nature of biomass hampers polysaccharide accessibility for enzymes and microbes. Several pretreatment methods have been developed for the conversion of lignocellulosic biomass into value-added products. Yet, these pretreatment methods also produce a wide range of secondary compounds, which are inhibitory to enzymes and microorganisms. The selection of an effective and efficient pretreatment method discussed in the review and its process optimization can significantly reduce the production of inhibitory compounds and may lead to enhanced production of fermentable sugars and biochemicals. Furthermore, evolutionary and genetic engineering approaches are being used for the improvement of microbial tolerance towards inhibitors. Advancements in pretreatment and detoxification technologies may help to increase the productivity of lignocellulose-based biorefinery. Here, we discuss the recent advancements in lignocellulosic biomass pretreatment technologies and strategies for the removal of inhibitors.

09 BIOMASS FUELS↗

Generative $β$-hairpin design using a residue-based physicochemical property landscape

De novo peptide design is a new frontier that has broad application potential in the biological and biomedical fields. Most existing models for de novo peptide design are largely based on sequence homology that can be restricted based on evolutionarily derived protein sequences and lack the physicochemical context essential in protein folding. Generative machine learning for de novo peptide design is a promising way to synthesize theoretical data that are based on, but unique from, the observable universe. In this study, we created and tested a custom peptide generative adversarial network intended to design peptide sequences that can fold into the -hairpin secondary structure. This deep neural network model is designed to establish a preliminary foundation of the generative approach based on physicochemical and conformational properties of 20 canonical amino acids, for example, hydrophobicity and residue volume, using extant structure-specific sequence data from the PDB. The beta generative adversarial network model robustly distinguishes secondary structures of hairpin from α helix and intrinsically disordered peptides with an accuracy of up to 96% and generates artificial -hairpin peptide sequences with minimum sequence identities around 31% and 50% when compared against the current NCBI PDB and nonredundant databases, respectively. These results highlight the potential of generative models specifically anchored by physicochemical and conformational property features of amino acids to expand the sequence-to-structure landscape of proteins beyond evolutionary limits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microbial community diversity changes during voltage reversal repair in a 12-unit microbial fuel cell

Microbial fuel cell stacks (MFC-Stack) are often confronted with voltage reversals, likely due to an interplay between microbial community dynamics and insufficient electric circuit balancing. Herein, we provide new insight into voltage reversals by examining the microbiomes of twelve MFC units of a 12-liter Pilot-MFC-Stack during repair. Different biofilm repair methods (self-healing, electrostimulation, and re-acclimatization upon cross-inoculation) were used to evaluate the microbial community response. In addition, MFC-Stack simulation was performed based on Kirchhoff’s Second Law to predict values for source potentials and post-evaluate internal resistances. Analysis of the 16S rRNA amplicon sequencing data suggests that the biofilm repair methods could slowly heal damaged biofilms. Notably, severely voltage reversed MFC units had low electrogen relative abundances (18%) and positive anode potentials, while strong bioanodes and contained more than 50% electrogens and had negative anode potentials. Between-community analyses (beta diversity ordination and multinomial regression) of the voltage reversed MFC units revealed differences among biofilms in contrast to healthy/strong MFC units. Permutational multivariate analysis of variance (PERMANOVA) confirmed that reversed biofilms were, indeed, significantly (p < 0.05) different from stronger ones. Overall, these analyses demonstrated the utility of combining electrotechnical and microbial community analyses, especially beta diversity ordination and multinomial regression, to understand problematic MFC units and the potential success of a biofilm repair method. Finally, thicker biofilms were usually healthier and stronger, although thickness was no guarantee for proper structure and power function as all factors were interdependent. There was an evolutionary trend that strong anodes became stronger/healthier and others weaker. This spontaneous trend has to be considered to avoid irreversible voltage reversals and to repair electrogenic biofilms in an MFC-Stack.

59 BASIC BIOLOGICAL SCIENCES↗

Disrupting autorepression circuitry generates “open-loop lethality” to yield escape-resistant antiviral agents

Across biological scales, gene-regulatory networks employ autorepression (negative feedback) to maintain homeostasis and minimize failure from aberrant expression. In this study, we present a proof of concept that disrupting transcriptional negative feedback dysregulates viral gene expression to therapeutically inhibit replication and confers a high evolutionary barrier to resistance. We find that nucleic-acid decoys mimicking cis-regulatory sites act as “feedback disruptors,” break homeostasis, and increase viral transcription factors to cytotoxic levels (termed “open-loop lethality”). Feedback disruptors against herpesviruses reduced viral replication >2-logs without activating innate immunity, showed sub-nM IC 50 , synergized with standard-of-care antivirals, and inhibited virus replication in mice. In contrast to approved antivirals where resistance rapidly emerged, no feedback-disruptor escape mutants evolved in long-term cultures. For SARS-CoV-2, disruption of a putative feedback circuit also generated open-loop lethality, reducing viral titers by >1-log. These results demonstrate that generating open-loop lethality, via negative-feedback disruption, may yield a class of antimicrobials with a high genetic barrier to resistance.

59 BASIC BIOLOGICAL SCIENCES↗

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes can rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but few have been shown to hydrolyze synthetic polyamides. Here, in this work, we synthesized and characterized a panel of 95 enzymes from the N-terminal nucleophile hydrolase superfamily with 30%–50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, but there was no relationship between phylogeny and activity, nor any evidence of prior evolutionary selection for nylon hydrolysis. Several newly identified hydrolases showed substrate selectivity, generating up to 20-fold higher product titers with nylon-6,6 versus nylon-6. However, the yield was still less than 1%, necessitating further optimization before potential applications. Finally, we determined the crystal structure and oligomerization state of a nylon-6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases.

nylon↗