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DOE OSTI2014

Comparisons of Shewanella strains based on genome annotations, modeling and experiments

Shewanella is a genus of facultatively anaerobic, Gram-negative bacteria that have highly adaptable metabolism which allows them to thrive in diverse environments. This quality makes them attractive target bacteria for research in bioremediation and microbial fuel cell applications. Constraint-based modeling is a useful tool for helping researchers gain insights into the metabolic capabilities of these bacteria. However, Shewanella oneidensis MR-1 is the only strain with a genome-scale metabolic model constructed out of the 22 sequenced Shewanella strains.

BINDING ENERGY↗

DOE OSTI2023

Fuel Injection Dynamics and Composition Effects on RDE Performance

Rotating detonation engines (RDEs) provide a promising route to substantially increasing cycle efficiency in stationary gas turbines. Much of this increase relies on the ability to achieve consistent pressure gain within the combustor. In particular, the design of injectors that feed fuel and air into the detonation channel plays a crucial role. Such injectors have to ensure proper mixing of fuel and oxidizer, while minimizing backflow of detonation products into the feed plenums, and reduce susceptibility to the complex wave structures that exist within the combustor. From a practical perspective, such RDEs also need to operate with variable fuel composition. When fuel mixtures with components that possess vastly different oxidation pathways and time-scales are used, there could be additional losses through deflagrative burning instead of detonation-driven heat release. Such sensitivity to the complete flow path is akin to the physics of thermoacoustic instabilities in conventional gas turbines. In this sense, RDEs pose a unique research challenge: the performance of the device relies on the small-scale heat release process, which is highly dependent on the flow interactions within the full-scale system. As a result, canonical flow configurations, instrumented with detailed diagnostics or modeled using high-fidelity tools, but only focus on the small-scale processes will not contain the key system-level interactions. At the same time, macroscopic measurements and models that only capture system-level performance will not provide insight into the key sources of pressure losses. These couplings and sensitivities provide a formidable challenge to both experimental and simulation studies of the effects Thus, a joint experimental/computational program designed specifically to address these challenges was undertaken in this program. The focus of this program was on two key topics: a) the interaction between injector flow and the overall wave dynamics within the combustor, and b) the deflagration/detonation structure in multi-component fuels that are of practical interest. Both topics involve interaction of small-scale heat release processes with the geometry-dependent wave structure. Studies focused on the study of full-scale RDE systems, based on a 6-inch conventional annular geometry. Experimentally RDEs were studied using a combination of diagnostics. A combination of optical diagnostics and aero-thermo-acoustic analysis based on a combination of spectral and mode decomposition analysis was used to identify the dynamics of the detonation wave and other secondary waves that exist in the system. These studies have helped the identification and investigation of injector and detonation dynamics arising from coupling, and how they affect RDE mixing, detonation structure, operability and performance. Performance of RDEs was investigated through thrust stand measurements, which was used to evaluate the effective pressure gain generated by the system through the concept of equivalent available pressure. Optical diagnostics were developed and implemented to investigate the distribution of heat release, across the detonation wave. Novel optical diagnostics of NIR imaging was also developed and applied to investigate the high temperature / high pressure distribution across the detonation wave. In order to complement the experiments, the computational tools were geared to simulate the full experimental setup. GPU-based acceleration of the models and computations were developed to enable rapid simulation of the full system. In addition, the use of adaptive mesh refinement, and unstructured grid formulation, enabled the investigation of realistic geometries studied in the laboratory. The simulations produced a wealth of detail on the structure of the detonation wave under different operating conditions. Emphasis was placed on quantifying mixture pre-burning and the impact on wave propagation and structure.

03 NATURAL GAS↗

DOE OSTI2026

Integrating Data Centers and Grid Technologies at Scale

This presentation focuses on the challenge of integrating AI-driven data centers with the power grid at scale. It examines the AI data center capacity challenge and the role of new Medium Voltage Direct Current (MVDC) and other grid-enhancing technologies in enabling efficient and reliable power delivery. The session will highlight the National Laboratory of the Rockies' ARIES capabilities and planning tools, along with collaborative examples involving Verrus, Compass, and Schneider through the Agora test bed for grid-friendly data center evaluations, and ON. Energy for UPS evaluation. It will showcase the NLR Stable Grid Platform for studying oscillations caused by large-scale data centers, along with planning tools to assess grid security and reliability. Additionally, the presentation covers reconductoring strategies to increase grid capacity and explores innovative data center architectures, including the Advanced DC Architectures with Power-electronic Transformers (ADAPT) platform, which enables testing of complete DC architectures for data centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2000

STS-92 Crew Activity Report/Flight Day 7 Highlights

On this seventh day of the STS-92 mission, the flight crew, Commander Brian Duffy, Pilot Pamela A. Melroy, and Mission Specialists Koichi Wakata, Leroy Chiao, Peter J.K. Wisoff, Michael E. Lopez-Alegria, and William S. McArthur continue work on the Z1 truss and the third pressurized mating adapter (PMA-3) on the International Space Station (ISS). Footage is seen of Chiao's and McArthur's spacewalk while they install two DC-to-DC converter units and attach a second tool storage box on the Z1 truss.

Source record↗

NASA NTRS1996

Monitoring the Photosynthetic Apparatus During Space Flight: Interspecific Variation in Chlorophyll Fluorescence Signatures Induced by Different Root Zone Stresses

Chlorophyll fluorescence has been used extensively as a tool to indicate stress to the photosynthetic apparatus in green plants. A rise in fluorescence has been attributed to the blockage of photosystem II photochemistry, and patterns of fluorescence decay (quenching) from dark adapted leaves can be related to specific photochemical and non-photochemical deexcitation pathways of light trapped by the photosynthetic apparatus and thus result in characteristically different fluorescence signatures. Four distantly related plant species, Hypocharis radicata (Asteraceae), Brassica rapa (Brassicaceae), Spinacea oleracea (Chenopodiaceae) and Triticum aestivum (Poaceae), were grown hydroponically for three weeks before the initiation of three different root zone stresses (10 mM Cu, 100 mM NaCl and nitrogen deficient nutrition). After 10 days, characteristic fluorescence signatures for each stress could be noted although the degree varied between species. Fast kinetics analysis showed a reduction in plastoquinone pool size for copper and nitrogen stress for all species but a more species specific result with NaCl stress. Photochemical quenching kinetics varied between species and stress treatments from no quenching in S. oleracea in copper treatments to increased photochemical quenching in NaCl treatments. Non-photochemical quenching kinetics demonstrated a distinct pattern between stresses for all species. Copper treatments characteristically exhibited a shallow, flat non-photochemical quenching profile suggesting a general blockage of electron transport whereas NaCl treatments exhibited a slow rising profile that suggested damage to thylakoid acidification kinetics and nitrogen deficiency exhibited a fast rising and declining profile that suggested an altered state 1-state 2 transition regulated by the phosphorylation of LHCII. These results demonstrate characteristic fluorescence signatures for specific plant stresses that may be applied to different, unrelated plant species. In addition, the potential use of chlorophyll fluorescence for both basic research and diagnostic physiology in space biology is presented.

Bubenheim, David L.↗

NASA NTRS2006

NASA Tech Briefs, October 2006

Topics covered include: Protein Sensors Based on Optical Ring Resonators; Phase Sensor for Aligning a Segmented Telescope Mirror; Control Software for Advanced Video Guidance Sensor; Generating Control Commands From Gestures Sensed by EMG; Multiple-Flat-Panel System Displays Multidimensional Data; 3D X-Ray Luggage-Screening System; Probe Station and Near-Field Scanner for Testing Antennas; Photodetector Arrays for Multicolor Visible/Infrared Imaging; Semiconductor Bolometers Give Background-Limited Performance; Multichannel X-Band Dielectric-Resonator Oscillator; Automatic Alignment of Displacement-Measuring Interferometer; Earth Observing System Data Gateway; Power User Interface; Mercury Shopping Cart Interface; Cassini Archive Tracking System; Architecture Adaptive Computing Environment; Computing Fault Displacements from Surface Deformations; Oxygen-Permeable, Hydrophobic Membranes of Silanized alpha-Al2O3; SiC Composite Turbine Vanes; Retaining Device for the Interior Structure of a Spacecraft Payload; Tool for Torquing Circular Electrical-Connector Collars; System for Continuous Deaeration of Hydraulic Oil; Solar-Powered Cooler and Heater for an Automobile Interior; Improved Oxygen-Beam Texturing of Glucose-Monitoring Optics; Tool for Two Types of Friction Stir Welding; Stationary Apparatus Would Apply Forces of Walking to Feet; Instrument Would Detect and Collect Biological Aerosols; Boundary Condition for Modeling Semiconductor Nanostructures; Miniature Distillation Column for Producing LOX From Air; Even Illumination from Fiber-Optic-Coupled Laser Diodes; Optically Driven Deformable Mirrors; Algorithm for Automated Detection of Edges of Clouds; Exploiting Quantum Resonance to Solve Combinatorial Problems; Hybrid Terrain Database; On Release of Microbe-Laden Particles from Mars Landers; A Concept for Run-Time Support of the Chapel Language; Thermoelectric Inhomogeneities in (Ag(sub 1-y)SbTe2)(sub x)(PbTe)(sub 1-x); and Spacecraft Escape Capsule.

Source record↗

NASA NTRS2014

FUN3D Manual: 12.4

This manual describes the installation and execution of FUN3D version 12.4, including optional dependent packages. FUN3D is a suite of computational fluid dynamics simulation and design tools that uses mixedelement unstructured grids in a large number of formats, including structured multiblock and overset grid systems. A discretely-exact adjoint solver enables efficient gradient-based design and grid adaptation to reduce estimated discretization error. FUN3D is available with and without a reacting, real-gas capability. This generic gas option is available only for those persons that qualify for its beta release status.

Biedron, Robert T.↗

DOE OSTI2014

Mathematical Modeling of Microbial Community Dynamics: A Methodological Review

Microorganisms in nature form diverse communities that dynamically change in structure and function in response to environmental variations. As a complex adaptive system, microbial communities show higher-order properties that are not present in individual microbes, but arise from their interactions. Predictive mathematical models not only help to understand the underlying principles of the dynamics and emergent properties of natural and synthetic microbial communities, but also provide key knowledge required for engineering them. In this article, we provide an overview of mathematical tools that include not only current mainstream approaches, but also less traditional approaches that, in our opinion, can be potentially useful. We discuss a broad range of methods ranging from low-resolution supra-organismal to high-resolution individual-based modeling. Particularly, we highlight the integrative approaches that synergistically combine disparate methods. In conclusion, we provide our outlook for the key aspects that should be further developed to move microbial community modeling towards greater predictive power.

Song, Hyun-Seob↗

NASA NTRS2003

The evolution of concepts of vestibular peripheral information processing: toward the dynamic, adaptive, parallel processing macular model

In a letter to Robert Hooke, written on 5 February, 1675, Isaac Newton wrote "If I have seen further than certain other men it is by standing upon the shoulders of giants." In his context, Newton was referring to the work of Galileo and Kepler, who preceded him. However, every field has its own giants, those men and women who went before us and, often with few tools at their disposal, uncovered the facts that enabled later researchers to advance knowledge in a particular area. This review traces the history of the evolution of views from early giants in the field of vestibular research to modern concepts of vestibular organ organization and function. Emphasis will be placed on the mammalian maculae as peripheral processors of linear accelerations acting on the head. This review shows that early, correct findings were sometimes unfortunately disregarded, impeding later investigations into the structure and function of the vestibular organs. The central themes are that the macular organs are highly complex, dynamic, adaptive, distributed parallel processors of information, and that historical references can help us to understand our own place in advancing knowledge about their complicated structure and functions.

Review, Tutorial↗

NASA NTRS2021

Verifying Mars 2020 Sampling and Caching Robotic Functions with Position Budgeting Process and Tool

The Mars 2020 Perseverance Rover was launched on July 30th, 2020 with one of the most complex robotic systems ever implemented on an interplanetary mission. Much of this robotic complexity resides in the Rover Sampling and Caching Subsystem (SCS) to enable collection of Martian samples for eventual return to earth and preparation of surfaces for close-up surface science observations. Two robotic arms are used by SCS: the large Robotic Arm (RA) positions the coring drill and science instruments mounted to the Turret for surface interactions, and the smaller Sample Handling Assembly (SHA) manipulates Sample Tube Assemblies (STA) within the Adaptive Caching Assembly (ACA) to prepare them for sample collection, processing, and hermetic sealing. The robotic arms interact with the Martian surface and other SCS components in many ways and in a variety of configurations, with positioning accuracy requirements ranging from tens of millimeters for some surface interactions down to sub-millimeter accuracy for some ACA interactions.This paper describes the process and tool used to calculate the SCS robotic interaction positioning budgets and verify the as-built hardware when delivered. To ensure that these robotic systems are able to perform their tasks, each robotic interaction with another element was broken down into its composite functions. To calculate a positioning budget margin for each function, an allowable was defined and then compared to the list of error sources that contribute to misalignment. Across the subsystem, over 250 functions were identified to be assessed, with almost 500 error sources feeding into their budget calculations. In addition to using as-built values in the budgets for SCS Verification and Validation (V&V) after the hardware was complete, these budgets were populated with design data during the design phase to identify areas of concern and guide hardware design to ensure positive position budget margins.Because of the size of the SCS team that had inputs to the positioning budgets and the sheer number of items in the budgets that needed to be created, updated, and verified, having a tool that would allow for simultaneous access and robust data integrity and processing was imperative. To accomplish this, a web-based MySQL database was created that allowed users to create function position budgets, link individual errors and allowables to them, and view function position budget margin reports. Each error and allowable records data for lateral, normal, angular, and clocking errors, with the ability to add as-built data for up to four different hardware builds. Margin reports can be generated for either design values alone or replacing design data with as-built data when available. These as-built reports are used for final verification of the SCS positioning requirements. Ultimately, the SCS positioning budget process and database tool led to successful interactions during test and an SCS robotic system that is ready to perform sample acquisition and caching on the surface of Mars.

Williams, Jeffrey↗

DOE OSTI2022

Prediction of Power Measurements Using Adaptive Filters

With the advent of smart grid concept, Internet of Things (IoT) and the deployment of smart meters, the cyberattack threats on power networks have increased due to the use of communication systems that can be accessed by adversaries. Attackers will have the ability to manipulate the outcomes of smart meters which in turn influence the core application of Energy Management System 9EMS): State Estimation (SE). Bad data analytic tools may fail to detect some attacks into measurements. Meanwhile, Machine Learning (ML) solutions have been proposed for detecting False Data Injection (FDI) attacks. However, there is a lack of ML time-series solutions presented in the state-of-the-art that is yet to be complex. In signal processing, time-series solutions do not only consider the signal, but also the statistics of the signal over time. Therefore, in this paper, a machine learning for time-series solutions is presented as an application to model the measurements of the power grid that are used in SE. The presented model takes into account adaptive linear and non-linear filters: Finite Impulse Response (FIR), and Infinite Impulse Response (IIR). The presented models are implemented and performed on the IEEE-118 bus system. The results indicate the advantage of applying those filters over the state-of-the-art machine learning solutions.

Hamad, Khaled↗

DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗

DOE OSTI2026

pyFLANK, a graph neural network based null distribution inference model for F ST outlier detection

Detecting genomic regions under selection is essential for understanding how populations adapt to different environments, yet it remains challenging due to the confounding effects of demographic history and linkage disequilibrium (LD). Fixation index (F ST ) is a widely used statistic to identify genomic regions under adaptation. However, identifying genes under selection by defining F ST outliers often remains challenging, owing to confounding effects of underlying demographic history. Traditional methods assume independence among loci and rely on simple demographic models, while newer models perform much better but are computationally expensive and not easily scalable. Here, we present pyFLANK, an open-source and automated Python implementation which detects F ST outliers using a null distribution inferred from quasi-independent loci. Our tool integrates three approaches to identify loci obeying a null distribution: graph neural network (GNN) inference, linkage disequilibrium (LD)-based inference, and user-defined input. Because pyFLANK uses GNN-based inference of quasi-independent loci, it yields a more accurate null model with less need for user parameter input. In simulation experiments, pyFLANK achieved lower false positive rates than current methods while maintaining comparable detection power, indicating that its refined null model better distinguishes true adaptive loci from background variation. The GNN-based model, in particular, detected additional loci associated with phenotypic variance that were not identified by existing methods. Assessments of simulation and real data from different species demonstrate that pyFLANK achieves lower false positive rates compared with other commonly used F ST outlier detectors, while maintaining comparable detection power and excellent computational performance, providing a robust and user-friendly tool for identifying loci under divergent selection. It extends existing F ST outlier frameworks by incorporating explicit LD-aware strategies for null model calibration. The method is intended as a practical and scalable complement to existing genome scan approaches.

FST↗

DOE OSTI2019

An Interdisciplinary Approach to Assessing Vulnerability of US Midwest to Drought and Heat Waves

More severe summer heat waves and droughts in the US Midwest and other regions due to climate change, along with changes in population distribution, pose risks for electricity shortages. Options are available for reducing these vulnerabilities. Costs and benefits of these options can be determined using a coupling of disparate analytical tools such as those that determine population allocation and climate variables to electricity service areas; tools that establish ranges of electricity demand and supply limitations and their modification in response to technological advances; and those that link water variables with power plant outages. A coupled system of this nature was used to examine the combined effects of heat wave and drought in the Midwest. Additionally, three adaptation scenarios based on changes in supply and demand for the greater Chicago, Illinois area were explored. We find that due to projected population changes in the region, the total number of metered customers approximately doubles by 2054, and that total electricity use increases 72% due to the population increase along with increases in maximum summer temperatures and frequency of heat waves in the region. Concomitantly, low availability of water during drought conditions, and high temperature effluent discharges during heat waves and higher overall temperatures, threaten operations for 30% of current power plant capacity reducing the supply at times of peak demand. As exhibited in one of the three adaptation scenarios, these conditions lead to an electricity supply deficit by 2054 and rapidly declining capacity margins during prior decades. However, technology additions, and changes in utility peak-period rates are available to modify customer demand substantially after 2024. Additionally, many water-cooled power plants near the end of their operational lives are projected to be replaced by more water-efficient generation.

Dumas, Melissa↗

DOE OSTI2021

Exascale models of stellar explosions: Quintessential multi-physics simulation

The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1991

An analytical and experimental study to investigate flutter suppression via piezoelectric actuation

The objective was to analytically and experimentally study the capabilities of adaptive material plate actuators for suppressing flutter. The validity of analytical modeling techniques for piezoelectric materials was also investigated. Piezoelectrics are materials which are characterized by their ability to produce voltage when subjected to a mechanical strain. The converse piezoelectric effect can be utilized to actuate a structure by applying a voltage. For this investigation, a two degree of freedom wind tunnel model was designed, analyzed, and tested. The model consisted of a rigid airfoil and a flexible mount system which permitted a translational and a rotational degree of freedom. It was designed such that flutter was encounted within the testing envelope of the wind tunnel. Actuators, made of piezoelectric material were affixed to leaf springs of the mount system. Each degree of freedom was controlled by a separate leaf spring. Command signals, applied to the piezoelectric actuators, exerted control over the damping and stiffness properties. A mathematical aeroservoelastic model was constructed using finite element methods, laminated plate theory, and aeroelastic analysis tools. Plant characteristics were determined from this model and verified by open loop experimental tests. A flutter suppression control law was designed and implemented on a digital control computer. Closed loop flutter testing was conducted. The experimental results represent the first time that adaptive materials have been used to actively suppress flutter. It demonstrates that small, carefully placed actuating plates can be used effectively to control aeroelastic response.

Heeg, Jennifer↗

DOE OSTI2024

Automatic fitting of multiple-field solid-state NMR spectra

The NMR lineshapes produced by half-integer quadrupolar nuclei are sensitive to 11 distinct fit parameters per inequivalent site. To date, automatic fitting routines have failed to replace manual parameter insertion and evaluation due to the importance of local minima and the need for fitting multiple-field magic-angle spinning (MAS) and static spectra simultaneously. Herein we introduce a new tool, AMES-Fit (Automatic Multiple Experiment Simulation and Fitting), to automatically find the global best-fit simulation parameters for a series of multiple-field NMR lineshapes. AMES-Fit uses an adaptive step size random search algorithm to dynamically probe parameter space and requires minimal human input. Importantly, the best fits are obtained in a few minutes of computation time that would otherwise have required several person-hours of work. The program is freely available and open-source.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Solution Hybrid Selection Capture for the Recovery of Functional Full-Length Eukaryotic cDNAs From Complex Environmental Samples

Eukaryotic microbial communities play key functional roles in soil biology and potentially represent a rich source of natural products including biocatalysts. Culture-independent molecular methods are powerful tools to isolate functional genes from uncultured microorganisms. However, none of the methods used in environmental genomics allow for a rapid isolation of numerous functional genes from eukaryotic microbial communities. We developed an original adaptation of the solution hybrid selection (SHS) for an efficient recovery of functional complementary DNAs (cDNAs) synthesized from soil-extracted polyadenylated mRNAs. This protocol was tested on the Glycoside Hydrolase 11 gene family encoding endo-xylanases for which we designed 35 explorative 31-mers capture probes. SHS was implemented on four soil eukaryotic cDNA pools. After two successive rounds of capture, >90% of the resulting cDNAs were GH11 sequences, of which 70% (38 among 53 sequenced genes) were full length. Between 1.5 and 25% of the cloned captured sequences were expressed in Saccharomyces cerevisiae . Sequencing of polymerase chain reaction-amplified GH11 gene fragments from the captured sequences highlighted hundreds of phylogenetically diverse sequences that were not yet described, in public databases. This protocol offers the possibility of performing exhaustive exploration of eukaryotic gene families within microbial communities thriving in any type of environment.

54 ENVIRONMENTAL SCIENCES↗