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At least 217 records · Page 12

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DOE OSTI2026

HtPIP: High-throughput phage isolation platform increases diversity and reduces isolation time using multiple bacteria

Bacteriophages are ubiquitous in nature, but relatively few have been isolated and characterized compared to the number of bacterial strains. Phage biotechnology applications benefit from a diverse library of isolated phages to kill or transfer genetic material to a bacterium of interest. However, scaling up phage discovery for diverse bacterial hosts can be time-consuming and costly. Here, we developed an approach to capture novel phages for multiple bacterial strains in parallel from an environmental sample using commercially available 0.2-μM filter plates. Using this High-throughput Phage Isolation Platform (HtPIP), 12 novel phages were isolated spanning 9 diverse bacterial host genera. Eleven of the isolated phages define new phage species, with nine also defining new genera. The HtPIP was used to discover both DNA and RNA phages, including a Tectiviridae infecting Pseudomonas putida mt-2 and a Leviviricetes infecting a Microbacterium isolate, which represents the first cultured RNA phage infecting a host outside of Proteobacteria. Using a metagenomic approach, we demonstrate that the HtPIP captures a higher proportion of novel phages compared to traditional low-throughput methods.

High-throughput↗

DOE OSTI2021

Case Study of High-Throughput Drug Screening and Remote Data Collection for SARS-CoV-2 Main Protease by Using Serial Femtosecond X-ray Crystallography

Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in silico drug screening studies have been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with nine drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers would ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode, also known as multiple reaction monitoring (MRM), is capable of quantitatively measuring hundreds of candidate protein biomarkers from a relevant clinical sample in a single analysis. The specificity, reproducibility and sensitivity could be as good as ELISA. Furthermore, SRM MS can also quantify protein isoforms and post-translational modifications, for which traditional antibody-based immunoassays often don’t exist.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2024

Indirect Liftoff Mechanism for High‐Throughput, Single‐Source Laser Scribing for Perovskite Solar Modules

A high‐throughput, single‐source laser scribing method exploiting a transparent conducting oxide (TCO) indirect liftoff mechanism is developed to produce serially interconnected perovskite solar modules. The TCO‐based indirect liftoff mechanism relies solely on laser absorption in the front transparent electrode material reducing thermal damage to the overlying layers and allowing for fast scribing speeds with low‐cost μs‐pulse duration fiber laser systems. Minimal resistive power losses are observed with the method compared to conventional ablative laser scribes, maintaining the power conversion efficiencies of small‐area devices (≈0.2 cm 2 ) across significantly larger deposition areas (≈1 cm 2 ). Finally, demonstrating > 3 m s −1 processing speeds, TCO‐based liftoff provides the highest throughput laser scribing method for thin‐film photovoltaic devices produced on glass/TCO substrates, capable of processing large‐area perovskite solar modules at a manufacturing scale.

14 SOLAR ENERGY↗

DOE OSTI2017

Impact of media and antifoam selection on monoclonal antibody production and quality using a high throughput micro-bioreactor system

Monoclonal antibody production in commercial scale cell culture bioprocessing requires a thorough understanding of the engineering process and components used throughout manufacturing. It is important to identify high impact components early on during the lifecycle of a biotechnology-derived product. While cell culture media selection is of obvious importance to the health and productivity of mammalian bioreactor operations, other components such as antifoam selection can also play an important role in bioreactor cell culture. Silicone polymer-based antifoams were known to have negative impacts on cell health, production, and downstream filtration and purification operations. High throughput screening in micro-scale bioreactors provides an efficient strategy to identify initial operating parameters. Here, we utilized a micro-scale parallel bioreactor system to study an IgG1 producing CHO cell line, to screen Dynamis, ProCHO5, PowerCHO2, EX-Cell Advanced, and OptiCHO media, and 204, C, EX-Cell, SE-15, and Y-30 antifoams and their impacts on IgG1 production, cell growth, aggregation, and process control. This study found ProCHO5, EX-Cell Advanced, and PowerCHO2 media supported strong cellular growth profiles, with an IVCD of 25-35 3 106 cells-d/ mL, while maintaining specific antibody production (Qp> 2 pg/cell-d) for our model cell line and a monomer percentage above 94%. Antifoams C, EX-Cell, and SE-15 were capable of providing adequate control of foaming while antifoam 204 and Y-30 noticeably stunted cellular growth. This work highlights the utility of high throughput micro bioreactors and the importance of identifying both positive and negative impacts of media and antifoam selection on a model IgG1 producing CHO cell line.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2013

High-Throughput Mapping of the Electrochemical Properties of (Ni-Fe-Co-Ce)O x Oxygen-Evolution Catalysts

Discovering improved electrocatalysts is critical for many technologically important processes and for the development of new clean-energy technologies. In this paper, high-throughput methods for measuring fundamental electrochemical properties are demonstrated through the investigation of oxygen-evolution catalysis by using 665 oxide compositions containing nickel, iron, cobalt, and cerium. The behavior of each composition is characterized in 1.0 M NaOH(aq) by using a scanning drop three-electrode cell to perform chronopotentiometry (CP) and cyclic voltammetry experiments. CP measurements at different current densities identify different composition–performance trends, owing to underlying variations in fundamental electrochemical behavior. We report systematic, coincident, composition-dependent trends in the Tafel slopes and the reversible redox potentials of the catalysts. Finally, applying high-throughput electrochemical methods provides insight into composition–property–performance relationships and motivates new directions for the study of catalyst mechanisms by using informatics and theory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

Accelerating virtual high-throughput ligand docking: current technology and case study on a petascale supercomputer

In this paper, we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel Message Passing Interface version of AutoDock4 to run a virtual high-throughput screen of one million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this Message Passing Interface version of AutoDock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

High‐throughput profiling and analysis of plant responses over time to abiotic stress

Abstract Sorghum ( Sorghum bicolor (L.) Moench) is a rapidly growing, high‐biomass crop prized for abiotic stress tolerance. However, measuring genotype‐by‐environment (G x E) interactions remains a progress bottleneck. We subjected a panel of 30 genetically diverse sorghum genotypes to a spectrum of nitrogen deprivation and measured responses using high‐throughput phenotyping technology followed by ionomic profiling. Responses were quantified using shape (16 measurable outputs), color (hue and intensity), and ionome (18 elements). We measured the speed at which specific genotypes respond to environmental conditions, in terms of both biomass and color changes, and identified individual genotypes that perform most favorably. With this analysis, we present a novel approach to quantifying color‐based stress indicators over time. Additionally, ionomic profiling was conducted as an independent, low‐cost, and high‐throughput option for characterizing G x E, identifying the elements most affected by either genotype or treatment and suggesting signaling that occurs in response to the environment. This entire dataset and associated scripts are made available through an open‐access, user‐friendly, web‐based interface. In summary, this work provides analysis tools for visualizing and quantifying plant abiotic stress responses over time. These methods can be deployed as a time‐efficient method of dissecting the genetic mechanisms used by sorghum to respond to the environment to accelerate crop improvement.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Automated High‐Throughput Fatigue Testing of Freestanding Thin Films

Abstract Mechanical testing at small length scales has traditionally been resource‐intensive due to difficulties with meticulous sample preparation, exacting load alignments, and precision measurements. Microscale fatigue testing can be particularly challenging due to the time‐intensive, tedious repetition of single fatigue experiments. To mitigate these challenges, this work presents a new methodology for the high‐throughput fatigue testing of thin films at the microscale. This methodology features a microelectromechanical systems‐based Si carrier that can support the simultaneous and independent fatigue testing of an array of samples. To demonstrate this new technique, the microscale fatigue behavior of nanocrystalline Al is efficiently characterized via this Si carrier and automated fatigue testing with in situ scanning electron microscopy. This methodology reduces the total testing time by an order of magnitude, and the high‐throughput fatigue results highlight the stochastic nature of the microscale fatigue response. This manuscript also discusses how this initial capability can be adapted to accommodate more samples, different materials, new geometries, and other loading modes.

Barrios, Alejandro↗

DOE OSTI2017

Analytical Validation of a Portable Mass Spectrometer Featuring Interchangeable, Ambient Ionization Sources for High Throughput Forensic Evidence Screening

Forensic evidentiary backlogs are indicative of the growing need for cost-effective, high-throughput instrumental methods. One such emerging technology that shows high promise in meeting this demand while also allowing on-site forensic investigation is portable mass spectrometric (MS) instrumentation, particularly that which enables the coupling to ambient ionization techniques. While the benefits of rapid, on-site screening of contraband can be anticipated, the inherent legal implications of field-collected data necessitates that the analytical performance of technology employed be commensurate with accepted techniques. To this end, comprehensive analytical validation studies are required before broad incorporation by forensic practitioners can be considered, and are the focus of this work. Pertinent performance characteristics such as throughput, selectivity, accuracy/precision, method robustness, and ruggedness have been investigated. Reliability in the form of false positive/negative response rates is also assessed, examining the effect of variables such as user training and experience level. To provide flexibility toward broad chemical evidence analysis, a suite of rapidly-interchangeable ion sources has been developed and characterized through the analysis of common illicit chemicals and emerging threats like substituted phenethylamines. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics

Determining a process–structure–property relationship is the holy grail of materials science, where both computational prediction in the forward direction and materials design in the inverse direction are essential. Problems in materials design are often considered in the context of process–property linkage by bypassing the materials structure, or in the context of structure–property linkage as in microstructure-sensitive design problems. However, there is a lack of research effort in studying materials design problems in the context of process–structure linkage, which has a great implication in reverse engineering. In this paper, given a target microstructure, we propose an active learning high-throughput microstructure calibration framework to derive a set of processing parameters, which can produce an optimal microstructure that is statistically equivalent to the target microstructure. The proposed framework is formulated as a noisy multi-objective optimization problem, where each objective function measures a deterministic or statistical difference of the same microstructure descriptor between a candidate microstructure and a target microstructure. Furthermore, to significantly reduce the physical waiting wall-time, we enable the high-throughput feature of the microstructure calibration framework by adopting an asynchronously parallel Bayesian optimization to exploit high-performance computing resources. Case studies in additive manufacturing and grain growth are used to demonstrate the applicability of the proposed framework, where kinetic Monte Carlo (kMC) simulation is used as a forward predictive model, such that for a given target microstructure, the target processing parameters that produced this microstructure are successfully recovered.

36 MATERIALS SCIENCE↗

DOE OSTI2018

High-throughput, one-step screening, cloning and expression based on the lethality of DpnI in Escherichia coli

Highlights: • The extreme toxicity of the DpnI from Streptococcus pneumoniae in bacteria containing Gm6ATC, the product of Dam methylation. • One-step screening, cloning and expression based on the lethality of DpnI in Escherichia coli. • The efficiency of using this method for cloning was approximately 100%. • Rapid one-step selection of soluble proteins. The manipulation of recombinant DNA has been an integral step in molecular biology to date. A number of strategies have been developed over the years, as traditional cloning methods are time consuming, have high backgrounds and low efficiency and are often limited by the number of suitable restriction sites available. Here, we constructed a series of new positive-selection-based cloning vectors that overcome most of the above mentioned drawbacks and can be applied in both eukaryotic and prokaryotic systems. This strategy is based on the extreme toxicity of DpnI in wild-type E. coli and the inactivation of this lethality by the introduction of target gene within multiple cloning sites. There are no rapid approaches for identifying soluble proteins for high-throughput screening. In this study, we combined this highly efficient cloning strategy with rapid identification of soluble proteins to construct vectors with multiple fusion tags, such as MBP, GST, CBD, NusA, and Sumo, to generate enzymes with potential diagnostic, industrial or therapeutic applications. Thus, this versatile positive-selection-based technology is appropriate for routine cloning, DNA library construction, and high-throughput screening for the expression of proteins of interest.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

High-throughput thermodynamic screening of carbide/refractory metal cermets for ultra-high temperature applications

Carbide/refractory metal cermets possess attractive combinations of thermal and mechanical properties for ultra-high temperature structural applications. Using a high-throughput computational thermodynamic approach, 16 carbide/refractory metal cermet systems were identified, out of 1808 possible combinations, that could be fabricated by the displacive compensation of porosity (DCP) method using molten copper alloys as infiltrators at 1300 °C. Experimental results for ZrC/W and ZrC/Mo, and other proposed systems in the literature provide a level of validation to this approach. We found that copper alloys are more suitable for DCP than aluminum alloys owing to the low melting temperature of copper alloys (e.g., Zr 2 Cu and Ti 2 Cu), and the minimal chemical reaction as well as very limited mutual solid solubility of copper with refractory metals. Our results show that high-throughput thermodynamics calculation is a robust approach for systematically and thoroughly identifying refractory metal cermets that are suitable for DCP.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Optimal high-throughput virtual screening pipeline for efficient selection of redox-active organic materials

As global interest in renewable energy continues to increase, there has been a pressing need for developing novel energy storage devices based on organic electrode materials that can overcome the shortcomings of the current lithium-ion batteries. One critical challenge for this quest is to find materials whose redox potential (RP) meets specific design targets. In this study, we propose a computational framework for addressing this challenge through the effective design and optimal operation of a high-throughput virtual screening (HTVS) pipeline that enables rapid screening of organic materials that satisfy the desired criteria. Starting from a high-fidelity model for estimating the RP of a given material, we show how a set of surrogate models with different accuracy and complexity may be designed to construct a highly accurate and efficient HTVS pipeline. We demonstrate that the proposed HTVS pipeline construction and operation strategies substantially enhance the overall screening throughput.

36 MATERIALS SCIENCE↗

DOE OSTI2012

High-throughput and in situ EDXRD investigation on the formation of two new metal aminoethylphosphonates - Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 2}) and Ca(OH)(O{sub 3}PC{sub 2}H{sub 4}NH{sub 3}){center_dot}2H{sub 2}O

The system Ca{sup 2+}/2-aminoethylphosphonic acid/H{sub 2}O/NaOH was systematically investigated using high-throughput methods. The experiments led to one new compound Ca(O{sub 3}PC{sub 2} H{sub 4}NH{sub 2}) (1) and the crystal structure was determined using in house X-ray powder diffraction data (monoclinic, P2{sub 1}/c, a=9.7753(3), b=6.4931(2), c=8.4473(2) A, {beta}=106.46(2) Degree-Sign , V=514.20(2) A{sup 3}, Z=4). The formation of 1 was investigated by in situ energy dispersive X-ray diffraction measurements (EDXRD) at beamline F3 at HASYLAB (light source DORIS III), DESY, Hamburg. An intermediate, Ca(OH)(O{sub 3}PC{sub 2}H{sub 4}NH{sub 3}){center_dot}2H{sub 2}O (2), was observed and could be isolated from the reaction mixture at ambient temperatures by quenching the reaction. The crystal structure of 2 was determined from XRPD data using synchrotron radiation (monoclinic, P2{sub 1}/m, a=11.2193(7), b=7.1488(3), c=5.0635(2) A, {beta}=100.13(4) Degree-Sign , V=399.78(3) A{sup 3}, Z=2). - Graphical abstarct: The detailed in situ energy dispersive X-ray diffraction (EDXRD) investigation on the formation of the new inorganic-organic hybrid compound Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 2}) leads to the discovery of a new crystalline intermediate phase. Both crystal structures were elucidated using X-ray powder diffraction data. Highlights: Black-Right-Pointing-Pointer High-throughput investigation led to new metal aminoethylphosphonate Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 2}). Black-Right-Pointing-Pointer The formation of Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 2}) was followed by in situ EDXRD measurements. Black-Right-Pointing-Pointer The crystalline intermediate Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 3})(OH){center_dot}2H{sub 2}O was discovered. Black-Right-Pointing-Pointer Isolation of Ca(O{sub 3}PC{sub 2}H{sub 4}NH{sub 3})(OH){center_dot}2H{sub 2}O was accomplished by quenching experiments. Black-Right-Pointing-Pointer The structures were determined using X-ray powder diffraction data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗

DOE OSTI2018

Digital pulse deconvolution with adaptive shaping for real-time high-resolution high-throughput gamma spectroscopy

A high-resolution high-throughput real-time adaptive digital pulse processing system is developed for high count rate gamma-ray spectroscopy applications. The adaptive digital pulse processing algorithms are implemented on a reconfigurable FPGA and include a pulse deconvolver, adaptive shaping filter, timing filter, baseline restorer, and pile-up rejecter. Digital pulse deconvolution is implemented to reconstruct the original detector signal from the preamplifier signal, which reduces the resolution deterioration due to pulse pile-up. The deconvoluted signal is shaped with a trapezoid filter and the shaping parameter is selected adaptively based on the time separation between successive input pulses. Experimental measurements are performed with a 137Cs source under varying count-rate conditions and using germanium detectors equipped with resistive feedback and transistor reset preamplifiers (TRP). The results herein demonstrate that when using a TRP, adaptive digital signal processing allows handling 106 counts/s. In addition, the implementation of a deconvolution approach limits resolution deterioration for throughput rates that are 4 to 10 times better than achievable in typical digital and analog gamma-ray spectroscopy systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2010

A high-throughput method for assessing chemical toxicity using a Caenorhabditis elegans reproduction assay

The National Research Council has outlined the need for non-mammalian toxicological models to test the potential health effects of a large number of chemicals while also reducing the use of traditional animal models. The nematode Caenorhabditis elegans is an attractive alternative model because of its well-characterized and evolutionarily conserved biology, low cost, and ability to be used in high-throughput screening. A high-throughput method is described for quantifying the reproductive capacity of C. elegans exposed to chemicals for 48 h from the last larval stage (L4) to adulthood using a COPAS Biosort. Initially, the effects of exposure conditions that could influence reproduction were defined. Concentrations of DMSO vehicle {<=} 1% did not affect reproduction. Previous studies indicated that C. elegans may be influenced by exposure to low pH conditions. At pHs greater than 4.5, C. elegans reproduction was not affected; however below this pH there was a significant decrease in the number of offspring. Cadmium chloride was chosen as a model toxicant to verify that automated measurements were comparable to those of traditional observational studies. EC{sub 50} values for cadmium for automated measurements (176-192 {mu}M) were comparable to those previously reported for a 72-h exposure using manual counting (151 {mu}M). The toxicity of seven test toxicants on C. elegans reproduction was highly correlative with rodent lethality suggesting that this assay may be useful in predicting the potential toxicity of chemicals in other organisms.

60 APPLIED LIFE SCIENCES↗