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At least 145 records · Page 8

Myocardial Imaging with CMR Parametric Mapping: Clinical Applications

Purpose of Review: Cardiovascular magnetic resonance (CMR) parametric mapping techniques enable the direct visualization and quantification of changes in myocardial T1, T2, T2* relaxation times and extracellular volume fraction. Recent updates on clinical applications of CMR parametric mapping techniques are reviewed in this article. Recent Findings: CMR parametric mapping techniques are useful in the evaluation of multiple conditions, including iron overload, amyloid infiltration, glycosphingolipid accumulation, myocardial edema, and fibrosis. An advantage of parametric mapping over conventional tissue characterization sequences is that these techniques are quantitative, allowing for standardization of measurements and assessment of longitudinal changes over time. Parametric mapping techniques are useful in clinical practice, including aiding in establishing a diagnosis, monitoring disease progression, evaluating response to therapy, and informing prognosis. Summary: This article provides a summary of the existing evidence for the clinical application of cardiac parametric mapping techniques.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Considering the Lives of Microbes in Microbial Communities

ABSTRACT Over the last decades, sequencing technologies have transformed our ability to investigate the composition and functional capacity of microbial communities. Yet, critical questions remain about these complex systems that cannot be addressed by the bulk, community-averaged data typically provided by sequencing methods. In this Perspective, I propose that future advances in microbiome research will emerge from considering “the lives of microbes”: we need to create methods to explicitly interrogate how microbes exist and interact in native-setting-like microenvironments. This approach includes developing approaches that expose the phenotypic heterogeneity of microbes; exploring the effects of coculture cues on cellular differentiation and metabolite production; and designing visualization systems that capture features of native microbial environments while permitting the nondestructive observation of microbial interactions over space and time with single-cell resolution.

59 BASIC BIOLOGICAL SCIENCES↗

The Trip Itinerary Optimization Platform: A Framework for Personalized Travel Information

The New Concepts Incubator team at the National Renewable Energy Laboratory (NREL) developed a three-stage online platform for travel diary collection, personal travel plan optimization and travel itinerary visualization. In the first stage, users provide a travel diary for the previous day through an interactive map and calendar interface and survey for travel attitudes and behaviors. One or more days later, users are invited via email to engage in a second stage where they view a personal mobility dashboard displaying recommended travel itineraries generated from a novel framework that optimizes travel outcomes over a sequence of interrelated trips. A week or more after viewing these recommended travel itineraries on the dashboard, users are emailed again to engage in a third stage where they complete a final survey about travel attitudes and behaviors. A usability study of the platform conducted online showed that, in general, users found the system valuable for informing their travel decisions. A total of 274 individuals were recruited through Amazon Mechanical Turk, an online survey platform, to participate in a transportation study using this platform. On average, the platform distilled 65 feasible travel plans per individual into two recommended itineraries, each optimal according to one or more outcomes and dependent on the fixed times and locations from the travel diary. For 45 percent of users, the trip recommendation algorithm returned only a single, typically automobile-centric, itinerary because there were no other viable alternative transportation modes available. Platform users generally agreed that the dashboard was enjoyable and easy to use, and that it would be a helpful tool in adopting new travel behaviors. Users generally agreed most that the time, cost and user preferred recommendations 'made sense' to them, and were most willing to implement these itineraries. Platform users typically expressed low willingness to try the carbon and calories optimized itineraries. Of the platform users who viewed the dashboard, 13 percent reported changing their travel behavior, most adopting the time, calories or carbon optimized itineraries. While the algorithm incorporates a wealth of travel data obtained from online APIs pertaining to a travelers route such as historic traffic condition data, public transit time-tables, and bike path routes, open-ended responses from users expressed an interest in the integration of even more fine-grained traffic data and the ability to dynamically model the effect of changes in travel times. Users also commonly expressed concerns over the safety of walking and biking recommendations. Responses indicate that more information about the amenities available to cyclists and pedestrians (sidewalks, shade from trees, access to food) and routes that avoid areas of perceived elevated danger would reduce barriers to implementing these recommendations. More accurate representations of personal vehicle trips (based on vehicle make and model, implications of parking) and the identification of routes that optimize caloric intensity (seeking out elevation changes or longer walks to public transit) are promising avenues for future research.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Transparent Object Tracking Benchmark

Visual tracking has achieved considerable progress in recent years. However, current research in the field mainly focuses on tracking of opaque objects, while little attention is paid to transparent object tracking. In this paper, we make the first attempt in exploring this problem by proposing a Transparent Object Tracking Benchmark (TOTB). Specifically, TOTB consists of 225 videos (86K frames) from 15 diverse transparent object categories. Each sequence is manually labeled with axis-aligned bounding boxes. To the best of our knowledge, TOTB is the first benchmark dedicated to transparent object tracking. In order to understand how existing trackers perform and to provide comparison for future research on TOTB, we extensively evaluate 25 state-of-the-art tracking algorithms. The evaluation results exhibit that more efforts are needed to improve transparent object tracking. Besides, we observe some nontrivial findings from the evaluation that are discrepant with some common beliefs in opaque object tracking. For example, we find that deeper features are not always good for improvements. Moreover, to encourage future research, we introduce a novel tracker, named TransATOM, which leverages transparency features for tracking and surpasses all 25 evaluated approaches by a large margin. By releasing TOTB, we expect to facilitate future research and application of transparent object tracking in both the academia and industry.

97 MATHEMATICS AND COMPUTING↗

Threat Reduction Research Networks: Fostering Sustainable Collaborations Through Trainings for Genomics for Biosurveillance

Scientific research communities can be represented as heterogeneous or multidimensional networks encompassing multiple types of entities and relationships. These networks might include researchers, institutions, meetings, and publications, connected by relationships like authorship, employment, and attendance. We describe a method for efficiently and flexibly capturing, storing, and extracting information from multidimensional scientific networks using a graph database. The database structure is based on an ontology that captures allowable types of entities and relationships. This allows us to construct a variety of projections of the underlying multidimensional graph through database queries to answer specific research questions. We demonstrate this process through a study of the U.S. Biological Threat Reduction Program (BTRP), which seeks to develop Threat Reduction Networks to build and strengthen a sustainable international community of biosecurity, biosafety, and biosurveillance experts to address shared biological threat reduction challenges. Networks like these create connectional intelligence among researchers and institutions around the world, and are central to the concept of cooperative threat reduction. Our analysis focuses on a series of seven BTRP genome sequencing training workshops, showing how they created a growing network of participants and countries over time, which is also reflected in coauthorship relationships among attendees. By capturing concept and relationship hierarchies, our ontology-based approach allows us to pose general or specific questions about networks within the same framework. This approach can be applied to other research communities or multidimensional social networks to capture, analyze, and visualize different types of interactions and how they change over time.

59 BASIC BIOLOGICAL SCIENCES↗

Comparative Biochemical and Structural Analysis of Novel Cellulose Binding Proteins ($ T\overline{a}pirins\ $) from Extremely Thermophilic Caldicellulosiruptor Species

Genomes of extremely thermophilic Caldicellulosiruptor species encode novel cellulose binding proteins, called $ t\overline{a}pirins\ $, located proximate to the type IV pilus locus. The C-terminal domain of Caldicellulosiruptor kronotskyensis $ t\overline{a}pirin\ $ 0844 (Calkro_0844) is structurally unique and has a cellulose binding affinity akin to that seen with family 3 carbohydrate binding modules (CBM3s). Here, full-length and C-terminal versions of $ t\overline{a}pirins\ $ from Caldicellulosiruptor bescii (Athe_1870), Caldicellulosiruptor hydrothermalis (Calhy_0908), Caldicellulosiruptor kristjanssonii (Calkr_0826), and Caldicellulosiruptor naganoensis (NA10_0869) were produced recombinantly in Escherichia coli and compared to Calkro_0844. All five $ t\overline{a}pirins\ $ bound to microcrystalline cellulose, switchgrass, poplar, and filter paper but not to xylan. Densitometry analysis of bound protein fractions visualized by SDS-PAGE revealed that Calhy_0908 and Calkr_0826 (from weakly cellulolytic species) associated with the cellulose substrates to a greater extent than Athe_1870, Calkro_0844, and NA10_0869 (from strongly cellulolytic species). Perhaps this relates to their specific needs to capture glucans released from lignocellulose by cellulases produced in Caldicellulosiruptor communities. Calkro_0844 and NA10_0869 share a higher degree of amino acid sequence identity (>80% identity) with each other than either does with Athe_1870 (~50%). The levels of amino acid sequence identity of Calhy_0908 and Calkr_0826 to Calkro_0844 were only 16% and 36%, respectively, although the three-dimensional structures of their C-terminal binding regions were closely related. Unlike the parent strain, C. bescii mutants lacking the $ t\overline{a}pirin\ $ genes did not bind to cellulose following short-term incubation, suggesting a role in cell association with plant biomass. Given the scarcity of carbohydrates in neutral terrestrial hot springs, $ t\overline{a}pirins\ $ likely help scavenge carbohydrates from lignocellulose to support growth and survival of Caldicellulosiruptor species.The mechanisms by which microorganisms attach to and degrade lignocellulose are important to understand if effective approaches for conversion of plant biomass into fuels and chemicals are to be developed. Caldicellulosiruptor species grow on carbohydrates from lignocellulose at elevated temperatures and have biotechnological significance for that reason. Novel cellulose binding proteins, called $ t\overline{a}pirins\ $, are involved in the way that Caldicellulosiruptor species interact with microcrystalline cellulose, and additional information about the diversity of these proteins across the genus, including binding affinity and three-dimensional structural comparisons, is provided here.

09 BIOMASS FUELS↗

The edge-on Galaxies in the Pan-STARRS survey (EGIPS)

ABSTRACT We present a catalogue of 16 551 edge-on galaxies created using the public DR2 data of the Pan-STARRS survey. The catalogue covers the three quarters of the sky above Dec. = −30°. The galaxies were selected using a convolutional neural network, trained on a sample of edge-on galaxies identified earlier in the SDSS survey. This approach allows us to dramatically improve the quality of the candidate selection and perform a thorough visual inspection in a reasonable amount of time. The catalogue provides homogeneous information on astrometry, SExtractor photometry, and non-parametric morphological statistics of the galaxies. The photometry is reliably for objects in the 13.8–17.4 r-band magnitude range. According to the HyperLeda data base, redshifts are known for about 63 per cent of the galaxies in the catalogue. Our sample is well separated into the red sequence and blue cloud galaxy populations. The edge-on galaxies of the red sequence are systematically Δ(g − i) ≈ 0.1 mag redder than galaxies oriented at an arbitrary angle to the observer. We found a variation of the galaxy thickness with the galaxy colour. The red sequence galaxies are thicker than the galaxies of the blue cloud. In the blue cloud, on average, thinner galaxies turn out to be bluer. In the future, based on this catalogue it is intended to explore the three-dimensional structure of galaxies of different morphologies, as well as to study the scaling relations for discs and bulges.

Makarov, D. (ORCID:0000000191103221)↗

Database development and exploration of process–microstructure relationships using variational autoencoders

The paper demonstrates graphical representation of a large database containing process–microstructure relationships using an unsupervised machine learning algorithm. Correlating microstructural features to processing is an essential first step to answer the difficult problem of process sequence design. Here, a large database of 346,200 orientation distribution functions resulting from a variety of process sequences is constructed, where each sequence comprises up to four stages of tension, compression and rolling along different directions in various permutations. This open-source database is constructed for collaborative development of process design algorithms. The paper demonstrates a novel application of the large database: graphical representation of texture–process relationships. A variational autoencoder is used to reduce the entire database to a two dimensional latent space where variations in processes and properties can be visualized. Using proximity analysis in this latent space, we can quickly unearth multiple process solutions to the problem of texture or property design.

36 MATERIALS SCIENCE↗

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗

Potent Antiviral Activity against HSV-1 and SARS-CoV-2 by Antimicrobial Peptoids

Viral infections, such as those caused by Herpes Simplex Virus-1 (HSV-1) and SARS-CoV-2, affect millions of people each year. However, there are few antiviral drugs that can effectively treat these infections. The standard approach in the development of antiviral drugs involves the identification of a unique viral target, followed by the design of an agent that addresses that target. Antimicrobial peptides (AMPs) represent a novel source of potential antiviral drugs. AMPs have been shown to inactivate numerous different enveloped viruses through the disruption of their viral envelopes. However, the clinical development of AMPs as antimicrobial therapeutics has been hampered by a number of factors, especially their enzymatically labile structure as peptides. We have examined the antiviral potential of peptoid mimics of AMPs (sequence-specific N-substituted glycine oligomers). These peptoids have the distinct advantage of being insensitive to proteases, and also exhibit increased bioavailability and stability. Our results demonstrate that several peptoids exhibit potent in vitro antiviral activity against both HSV-1 and SARS-CoV-2 when incubated prior to infection. In other words, they have a direct effect on the viral structure, which appears to render the viral particles non-infective. Visualization by cryo-EM shows viral envelope disruption similar to what has been observed with AMP activity against other viruses. Furthermore, we observed no cytotoxicity against primary cultures of oral epithelial cells. These results suggest a common or biomimetic mechanism, possibly due to the differences between the phospholipid head group makeup of viral envelopes and host cell membranes, thus underscoring the potential of this class of molecules as safe and effective broad-spectrum antiviral agents. We discuss how and why differing molecular features between 10 peptoid candidates may affect both antiviral activity and selectivity.

60 APPLIED LIFE SCIENCES↗

Data-driven selection and spectral classification of white dwarf stars

The next generation of spectroscopic surveys is expected to provide spectra for hundreds of thousands of white dwarf (WD) candidates in the upcoming years. Currently, spectroscopic classification of white dwarfs is mostly done by visual inspection, requiring substantial amounts of expert attention. We propose a data-driven pipeline for fast, automatic selection, and spectroscopic classification of WD candidates, trained using spectroscopically confirmed objects with available Gaia astrometry, photometry, and Sloan Digital Sky Survey (SDSS) spectra with signal-to-noise ratios ≥9. The pipeline selects WD candidates with improved accuracy and completeness over existing algorithms, classifies their primary spectroscopic type with ≥ 90 % accuracy, and spectroscopically detects main sequence companions with similar performance. We apply our pipeline to the Gaia Data Release 3 cross-matched with the SDSS Data Release 17 (DR17), identifying 424 096 high-confidence WD candidates and providing the first catalogue of automated and quantifiable classification for 36 523 WD spectra. Both the catalogue and pipeline are made available online. Such a tool will prove particularly useful for the undergoing SDSS-V survey, allowing for rapid classification of thousands of spectra at every data release.

79 ASTRONOMY AND ASTROPHYSICS↗

Correlating Enzymes to Antimicrobial Resistance in the Protein Data Bank

Antibiotic resistant bacteria are predicted to be the leading cause of death worldwide, with an expected death rate of 10 million people, annually, by 2050. It is vital that antimicrobial resistance (AMR) be understood at the molecular level. The Protein Data Bank (PDB) archive holds over 130,000 3D structures of macromolecular machines that can be analyzed using the RCSB PDB website at RCSB.org. Studying these 3D structures enables scientific research and education in a variety of fields, including drug discovery, nanotechnology, green energy, and disease. In this study, PDB enzymes related to antibiotic inhibitors were identified and further analyzed using additional bioinformatics including The Comprehensive Antibiotic Resistance Database (CARD). CARD holds up to date clinically relevant antibiotic related information. CARD identified 4,688 Genbank IDs (protein accession codes) that are related to AMR. These codes were then put into the Uniprot website which holds protein sequences. As a result, 696 macromolecules related to AMR were found in the PDB. I specifically researched Metallo Beta Lactamases (MBL) because have a large correlation to AMR and have been studied in great detail, with many examples in the PDB. Prominent enzymes in this category include the New Delhi Beta Lactamase which can cleave most if not all antibiotics. This particular “superbug” was found to cleave penicillin, cephalosporin, and carbapenem antibiotics. Using 3D visualizations of beta lactamase enzymes a correlation between zinc ions and spectrum of antibiotic resistance was found. For example, if an enzyme had two zinc ions instead of one it could inhibit broad spectrum antibiotics. In conclusion, the findings of this research presented here will be used to develop novel AMR tab at RCSB.org that will provide antimicrobial details of enzymes that were unavailable before. In the near future a phylogenetic tree of AMR related enzymes and classification details will be implemented. Support or Funding Information RCSB PDB is funded by a grant from the National Science Foundation (DBI‐1338415) , the National Institutes of Health , and the US Department of Energy . This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Salcedo, Priscilla M.↗

DFTT report for Signal Analysis (2023)

The Detection Framework Testbed and Toolkit (DFTT) is a database and associated java programs intended to facilitate the development and testing of algorithms for operating suites of correlation and subspace detectors. This framework is a generalization of the system described in Harris and Dodge (2011) and Dodge and Harris (2016). DFTT allows retrospective processing of sequences of data using various system configurations. Results are saved in a database, so it is easy to compare the results obtained using different configurations of the system. The principal software components of DFTT are the ConfigCreator, the framework_runner and the Builder program. ConfigCreator assembles the files necessary to define a particular configuration used for processing. The framework_runner operates suites of detectors and saves the results in an Oracle™ database. Builder allows visual examination of templates and detected signals and allows editing and creation of detectors. In addition, there are tools for importing continuous data into the database. DFTT is licensed under the MIT license and has LLNL release number LLNL-CODE-801881. In the current fiscal year DFTT has been used in two different projects. The first (NTL-funded) project investigates the feasibility of screening nuisance detections using correlation detectors. The second (GNEM-funded) project seeks to extend the results of Harris and Dodge (2021) to 3- D sources and multiple stations. Each of these efforts required that additional functionality be added to DFTT. In this report I will summarize the enhancements to DFTT in the context of the relevant research effort.

58 GEOSCIENCES↗

Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR

The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Center (BRC) program to assist researchers with analyzing the growing body of genome sequence and other omics-related data. In this report, we describe the merger of the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD) and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/. The combined BV-BRC leverages the functionality of the bacterial and viral resources to provide a unified data model, enhanced web-based visualization and analysis tools, bioinformatics services, and a powerful suite of command line tools that benefit the bacterial and viral research communities.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic in situ imaging of methane hydrate formation in coal media

Fast 3D X-ray imaging has proved to provide crucial insights into multi-phase dynamic processes in various geomaterials. In particular, many in situ imaging experiments have been made to study gas-hydrate formation in porous sandy samples. Such imaging is challenging for the methane gas-hydrate formation in coal samples because of the coal micro-porosity structure and lower X-ray contrast. Here we present results of the first dynamic in situ micro-computed tomography experiment of methane-hydrate formation in coal samples. Synchrotron phase-contrast tomography techniques allowed to achieve necessary contrast levels to separate all the materials of interest (gas, water, coal, and gas hydrate) in reconstructed images with high spatial and temporal resolution. The imaging results are compared to the ones from a similar tomographic experiment with sand samples. Methane-hydrate formation is accompanied by the water movements caused by cryogenic water suction that happens in sequences of short fast movements with longer equilibrium states in between. Only one type of the hydrate formation was observed in coal (growth as shells on grain boundaries) as opposed to three types in sand (shells, growth into gas pockets, and inside water volumes). In particular, this leads to a slower hydrateformation speed in coal. For the coal sample, we also observed water extraction from grains, and interpreted it as competitive sorption of methane. Lastly, we visualized the dynamic behavior of this water extraction via microchannels inside the coal grains, and performed nano-tomography imaging of these channels for a better understanding of this phenomenon.

58 GEOSCIENCES↗

In-situ 3D visualization of composite microstructure during polymer-to-ceramic conversion

One route for producing fiber-reinforced ceramic-matrix composites entails repeated impregnation and pyrolysis of a preceramic polymer in a fiber preform. The process relies crucially on the development of networks of contiguous cracks during pyrolysis, thereby allowing further impregnation to attain nearly-full densification. The present study employs in-situ x-ray computed tomography (XCT) to reveal in three dimensions the evolution of matrix structure during pyrolysis of a SiC-based preceramic polymer to 1200 °C. Observations are used to guide the development of a taxonomy of crack geometries and crack structures and to identify the temporal sequence of their formation. A quantitative analysis is employed to characterize effects of local microstructural dimensions on the conditions required to form cracks of various types. Complementary measurements of gas evolution and mass loss of the preceramic polymer during pyrolysis as well as changes in mass density and Young's modulus provide context for the physical changes revealed by XCT. Furthermore, the findings provide a foundation for future development of physics-based models to guide composite fabrication processes.

36 MATERIALS SCIENCE↗

Cross-reactive neutralizing human survivor monoclonal antibody BDBV223 targets the ebolavirus stalk

Three Ebolavirus genus viruses cause lethal disease and lack targeted therapeutics: Ebola virus, Sudan virus and Bundibugyo virus. Monoclonal antibody (mAb) cocktails against the surface glycoprotein (GP) present a potential therapeutic strategy. Here we report two crystal structures of the antibody BDBV223, alone and complexed with its GP2 stalk epitope, an interesting site for therapeutic/vaccine design due to its high sequence conservation among ebolaviruses. BDBV223, identified in a human survivor of Bundibugyo virus disease, neutralizes both Bundibugyo virus and Ebola virus, but not Sudan virus. Importantly, the structure suggests that BDBV223 binding interferes with both the trimeric bundle assembly of GP and the viral membrane by stabilizing a conformation in which the monomers are separated by GP lifting or bending. Targeted mutagenesis of BDBV223 to enhance SUDV GP recognition indicates that additional determinants of antibody binding likely lie outside the visualized interactions, and perhaps involve quaternary assembly or membrane-interacting regions.

59 BASIC BIOLOGICAL SCIENCES↗

Smart Microbial Cells Couple Catalysis and Sensing to Provide High-Throughput Selection of an Organophosphate Hydrolase

Enzyme engineering for gain of function requires navigating a large combinatorial sequence space efficiently. Typically, many mutations are needed to get significant improvements, while a single “bad” mutation can inactivate the enzyme. To establish high-throughput screening and achieve enhanced resolution between two variants, genetic libraries of the organophosphate hydrolase enzyme paraoxonase 1 (PON 1 ) were rapidly screened via an engineered positive-feedback circuit: a p-nitrophenol (PNP)-specific transcription factor (TF) regulated expression of PON 1 , which catalyzed paraoxon breakdown and PNP production. Rare active mutant colonies, picked by simple visual fluorescence of a PON 1 –green fluorescent protein (GFP) fusion, were characterized. Furthermore, in a single screening round, high (library-scale) throughput enabled the discovery of enhanced paraoxon degradation activity in PON 1 , including structurally unexpected mutations.

59 BASIC BIOLOGICAL SCIENCES↗