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At least 829 records · Page 46

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DOE OSTI2020

RNA-guided transcriptional regulation

Methods of modulating expression of a target nucleic acid in a cell are provided including introducing into the cell a first foreign nucleic acid encoding one or more RNAs complementary to DNA, wherein the DNA includes the target nucleic acid, introducing into the cell a second foreign nucleic acid encoding a nuclease-null Cas9 protein that binds to the DNA and is guided by the one or more RNAs, introducing into the cell a third foreign nucleic acid encoding a transcriptional regulator protein or domain, wherein the one or more RNAs, the nuclease-null Cas9 protein, and the transcriptional regulator protein or domain are expressed, wherein the one or more RNAs, the nuclease-null Cas9 protein and the transcriptional regulator protein or domain co-localize to the DNA and wherein the transcriptional regulator protein or domain regulates expression of the target nucleic acid.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Non-coding RNAs linked to immortality and associated methods and compositions

Aspects of the present disclosure include RNAs that confer a mortal phenotype and nucleic acids encoding same. Liposomes, recombinant cells, and pharmaceutical compositions that include the RNAs or nucleic acids encoding same are also provided. Further provided are methods involving quantifying MORT RNAs and/or determining the methylation status of the MORT promoter, as well as methods that employ the RNAs or nucleic acids encoding same.

Stampfer, Martha R.↗

DOE OSTI2021

Adaptive neural network management system

A method and computer system for managing a neural network. Data is sent into an input layer in a portion of layers of nodes in the neural network. The data moves on an encode path through the portion such that an output layer in the portion outputs encoded data. The encoded data is sent into the output layer on a decode path through the portion back to the input layer to obtain a reconstruction of the data by the input layer. A determination is made as to whether an undesired amount of error has occurred in the output layer based on the data sent into the input layer and the reconstruction of the data. A number of new nodes is added to the output layer when a determination is present that the undesired amount of the error occurred, enabling reducing the error using the number of the new nodes.

Draelos, Timothy J.↗

DOE OSTI2021

Production of organic acids from Aspergillus cis-aconitic acid decarboxylase (cadA) deletion strains

This application provides recombinant Aspergillus fungi having an endogenous cis-aconitic acid decarboxylase (cadA) gene genetically inactivated, which allows aconitic acid production by the recombinant fungi. Such recombinant fungi can further include an exogenous nucleic acid molecule encoding aspartate decarboxylase (panD), an exogenous nucleic acid molecule encoding β-alanine-pyruvate aminotransferase (BAPAT), and an exogenous nucleic acid molecule encoding 3-hydroxypropionate dehydrogenase (HPDH). Kits including these fungi, and methods of using these fungi to produce aconitic acid and 3-hydroxypropionic acid (3-HP) are also provided.

Deng, Shuang↗

DOE OSTI2020

A 20 Gbps Data Transmitting ASIC with PAM4 for Particle Physics Experiments

We present the design principle and test results of a data transmitting ASIC, GBS20, for particle physics experiments. The goal of GBS20 will be an ASIC that employs two serializers each from the 10.24 Gbps lpGBT SerDes, sharing the PLL also from lpGBT. A PAM4 encoder plus a VCSEL driver will be implemented in the same die to use the same clock system, eliminating the need of CDRs in the PAM4 encoder. This way the transmitter module, GBT20, developed using the GBS20 ASIC, will have the exact lpGBT data interface and transmission protocol, with an output up to 20.48 Gbps over one fiber. With PAM4 embedded FPGAs at the receiving end, GBT20 will halve the fibers needed in a system and better use the input bandwidth of the FPGA. A prototype, GBS20v0 is fabricated using a commercial 65 nm CMOS technology. This prototype has two serializers and a PAM4 encoder sharing the lpGBT PLL, but no user data input. An internal PRBS generator provides data to the serializers. GBS20v0 is tested barely up to 20.48 Gbps. With lessons learned from this prototype, we are designing the second prototype, GBS20v1, that will have 16 user data input channels each at 1.28 Gbps. We present the design concept of the GBS20 ASIC and the GBT20 module, the preliminary test results, and lessons learned from GBS20v0 and the design of GBS20v1 which will be not only a test chip but also a user chip with 16 input data channels.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Methods for making polypeptides including d-amino acids

A method of making a polypeptide including one or more D-amino acids is provided. The method includes combining a ribosome with protein translation factors including (1) a template encoding the polypeptide, wherein the template encoding the polypeptide includes one or more codons which have been recoded to accept a tRNA attached to a D-amino acid, (2) a plurality of L-amino acids and a plurality of corresponding tRNAs, (3) a plurality of D-amino acids and their corresponding aminoacyl tRNA synthetase or a plurality of tRNAs ligated with a D-amino acid, and (4) elongation factor P in a concentration of 2 to 20 micromolar, wherein translation of the template encoding the polypeptide occurs to produce the polypeptide including one or more D-amino acids.

Church, George M.↗

DOE OSTI2025

Fast Sideband Control of a Weakly Coupled Multimode Bosonic Memory

Circuit quantum electrodynamics (cQED) with superconducting cavities coupled to nonlinear circuits like transmons offers a promising platform for hardware-efficient quantum information processing. We address critical challenges in realizing this architecture by weakening the dispersive coupling while also demonstrating fast, high-fidelity multimode control by dynamically amplifying gate speeds through transmon-mediated sideband interactions. This approach enables transmon-cavity SWAP gates, for which we achieve speeds up to 30 times larger than the bare dispersive coupling. Combined with transmon rotations, this allows for efficient, universal state preparation in a single cavity mode, though achieving unitary gates and extending control to multiple modes remains a challenge. In this work, we overcome this by introducing two sideband control strategies: (1) a shelving technique that prevents unwanted transitions by temporarily storing populations in sideband-transparent transmon states and (2) a method that exploits the dispersive shift to synchronize sideband transition rates across chosen photon-number pairs to implement transmon-cavity SWAP gates that are selective on photon number. We leverage these protocols to prepare Fock and binomial code states across any of ten modes of a multimode cavity with millisecond cavity coherence times. We demonstrate the encoding of a qubit from a transmon into arbitrary vacuum and Fock state superpositions, as well as entangled NOON states of cavity mode pairs— a scheme extendable to arbitrary multimode Fock encodings. Furthermore, we implement a new binomial encoding gate that converts arbitrary transmon superpositions into binomial code states in $\qty{4}{\micro\second}$ (less than $1/\chi$), achieving an average post-selected final state fidelity of $\qty{96.3}{\percent}$ across different fiducial input states.

Huang, Jordan [Rutgers U., Piscataway]↗

DOE OSTI2024

Advancing spatiotemporal forecasts of CO 2 plume migration using deep learning networks with transfer learning and interpretation analysis

Accurate and timely forecasts of CO 2 plume distribution throughout the injection and post-injection phases are crucial for detecting plume migration, assessing leakage risks, and supporting operational decisions in geologic carbon storage (GCS). Current convolutional neural network-based approaches primarily focus on spatial information and overlook temporal dependencies in plume distributions, thus limiting their ability to capture dynamic movement effects and provide accurate predictions of plume migration. In this work, we propose two deep learning models, Auto-Encoder (AE)-LSTM and Encoder-Decoder (ED)-ConvLSTM, each uniquely designed to capture both spatial and temporal features. We apply the proposed methods to forecast the dynamic distribution of CO 2 plumes based on 108 reservoir simulations over a 30-year injection and a 30-year post-injection period. The results indicate that the ED-ConvLSTM model outperforms the AE-LSTM model in accurately predicting the spatiotemporal dynamics of CO 2 plume migration, achieving R 2 values above 0.99. To provide a deeper understanding of these model predictions, we employ a gradient-based explanation method on the trained models. This approach provides insights into the influence of input variables on plume migration forecasts and uncovers the underlying prediction mechanisms of the proposed models. Furthermore, we introduce a transfer learning technique, enabling fast and accurate plume migration forecasting in the post-injection phase by leveraging the trained model during the injection phase. This reduces the necessity for extensive data collection or re-training. In conclusion, the methods proposed in our work enhances the performance and interpretability of CO 2 plume migration forecasts, thereby facilitating informed decision-making throughout the entire lifecycle of GCS applications.

58 GEOSCIENCES↗

DOE OSTI2025

Characterization of the thermophilic xylanase Fsa02490Xyn from the hyperthermophile Fervidibacter sacchari belonging to glycoside hydrolase family 10

Fervidibacter sacchari is an aerobic hyperthermophile belonging to the phylum Armatimonadota that degrades a variety of polysaccharides. Its genome encodes 117 enzymes with one or more annotated glycoside hydrolase (GH) domain, but the roles of these putative GHs in polysaccharide catabolism are poorly defined. Here, we describe one F. sacchari enzyme encoding a GH10 domain, Fsa02490Xyn, that was previously shown to be active on Miscanthus, oat β-glucan, and beech-wood xylan, with optimal activity at 90-100 °C. We show that Fsa02490Xyn is also active on birch-wood xylan and gellan gum. The pH range on beech-wood xylan was 4.5 to 9.5 (pHopt 7.0-8.0). Fsa024940Xyn had a Km of 2.375 mm, Vmax of 1250 μm·min-1, and kcat/Km of 1.259 × 104 s-1·m-1 when using a para-nitrophenyl-?-xylobioside assay. A phylogenetic analysis of GH10 family enzymes revealed a large clade of enzymes from diverse members of the class Fervidibacteria, including Fsa02490Xyn and a second enzyme from F. sacchari, with apparent horizontal gene transfer within Fervidibacteria and between Fervidibacteria and thermophilic Bacillota. This study establishes Fsa02490Xyn as a hyperthermophilic GH10 enzyme with endo-β-1,4-xylanase activity and identifies a large clade of homologous GH10 enzymes within the class Fervidibacteria. Impact statement The depolymerization of xylan at high temperatures is important because this process limits the degradation of polysaccharides in nature and the synthesis of biofuels from plant wastes. Our study is also important because F. sacchari is one of only a few cultivated members of the Armatimonadota, which are polysaccharide-degradation specialists.

Armatimonadota↗

DOE OSTI2023

Universal Polarization Transformations: Spatial Programming of Polarization Scattering Matrices Using a Deep Learning‐Designed Diffractive Polarization Transformer

Abstract Controlled synthesis of optical fields having nonuniform polarization distributions presents a challenging task. Here, a universal polarization transformer is demonstrated that can synthesize a large set of arbitrarily‐selected, complex‐valued polarization scattering matrices between the polarization states at different positions within its input and output field‐of‐views (FOVs). This framework comprises 2D arrays of linear polarizers positioned between isotropic diffractive layers, each containing tens of thousands of diffractive features with optimizable transmission coefficients. After its deep learning‐based training, this diffractive polarization transformer can successfully implement N i N o = 10 000 different spatially‐encoded polarization scattering matrices with negligible error, where N i and N o represent the number of pixels in the input and output FOVs, respectively. This universal polarization transformation framework is experimentally validated in the terahertz spectrum by fabricating wire‐grid polarizers and integrating them with 3D‐printed diffractive layers to form a physical polarization transformer. Through this set‐up, an all‐optical polarization permutation operation of spatially‐varying polarization fields is demonstrated, and distinct spatially‐encoded polarization scattering matrices are simultaneously implemented between the input and output FOVs of a compact diffractive processor. This framework opens up new avenues for developing novel devices for universal polarization control and may find applications in, e.g., remote sensing, medical imaging, security, material inspection, and machine vision.

Optical neural networks↗

DOE OSTI2024

Development of inducible promoters for regulating gene expression in Clostridium tyrobutyricum for biobutanol production

Abstract Clostridium tyrobutyricumis an anaerobe known for its ability to produce short‐chain fatty acids, alcohols, and esters. We aimed to develop inducible promoters for fine‐tuning gene expression inC. tyrobutyricum. Synthetic inducible promoters were created by employing anEscherichia coli lacoperator to regulate the thiolase promoter (PCathl) fromClostridium acetobutylicum, with the best one (LacI‐Pto4s) showing a 5.86‐fold dynamic range with isopropyl β‐d‐thiogalactoside (IPTG) induction. A LT‐Pt7 system with a dynamic range of 11.6‐fold was then created by combining LacI‐Pto4s with a T7 expression system composing of RNA polymerase (T7RNAP) and Pt7lacpromoter. Furthermore, two inducible expression systems BgaR‐PbgaLA and BgaR‐PbgaLB with a dynamic range of ~40‐fold were developed by optimizing a lactose‐inducible expression system fromClostridium perfringenswith modified 5′ untranslated region (5′ UTR) and ribosome‐binding site (RBS). BgaR‐PbgaLB was then used to regulate the expressions of a bifunctional aldehyde/alcohol dehydrogenase encoded byadhE2 and butyryl‐CoA/acetate Co‐A transferase encoded bycat1 inC. tyrobutyricumwild type and Δcat1::adhE2, respectively, demonstrating its efficient inducible gene regulation. The regulatedcat1 expression also confirmed that the Cat1‐catalyzed reaction was responsible for acetate assimilation inC. tyrobutyricum. The inducible promoters offer new tools for tuning gene expression inC. tyrobutyricumfor industrial applications.

Biotechnology & Applied Microbiology↗

DOE OSTI2022

Newly developed sugarbeet lines with altered postharvest respiration rates differ in transcription factor and glycolytic enzyme expression

Respiration is the principal cause for postharvest sucrose loss in sugarbeet (Beta vulgaris L.) roots. Although reductions in respiration rate could mitigate these losses, developing sugarbeet cultivars and storage procedures that reduce respiration are hindered by a lack of knowledge of the genetic and metabolic factors that control storage respiration rate. Research was conducted to identify genes and gene products that affect storage respiration rate by creating two sugarbeet lines that differ in respiration rate and characterizing gene expression differences between these lines. Sugarbeet lines F1056 and F1057, which differ by up to 42% in respiration rate, were created by divergent selection of a sugarbeet population using root respiration rate after 30 d in storage as the principal selection criterion. RNA sequencing identified 287 differentially expressed genes (DEGs) between these lines on the day of harvest and after 28-d storage. Of these DEGs, nine encoded transcription factors and five encoded enzymes involved in the respiratory pathway. Other DEGs contributed to a variety of biological and molecular functions based on gene ontology classifications. Of respiratory pathway DEGS, genes for NAD+- and NADP+-dependent forms of glyceraldehyde-3-phosphate dehydrogenase were of note due to their high upregulation in the high respiring line and for their established role in glycolysis, a pathway identified as a likely bottleneck in respiratory substrate production. Overall, lines F1056 and F1057 provide new tools for investigating genetic and physiological differences in storage respiration rate, and their DEGs identify candidates for genes affecting sugarbeet root respiration rate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Structural and functional analysis of the human cone‐rod homeobox transcription factor

Abstract The cone‐rod homeobox (CRX) protein is a critical K50 homeodomain transcription factor responsible for the differentiation and maintenance of photoreceptor neurons in the vertebrate retina. Mutant alleles in the human gene encoding CRX result in a variety of distinct blinding retinopathies, including retinitis pigmentosa, cone‐rod dystrophy, and Leber congenital amaurosis. Despite the success of using in vitro biochemistry, animal models, and genomics approaches to study this clinically relevant transcription factor over the past 25 years since its initial characterization, there are no high‐resolution structures in the published literature for the CRX protein. In this study, we use bioinformatic approaches and small‐angle X‐ray scattering (SAXS) structural analysis to further understand the biochemical complexity of the human CRX homeodomain (CRX‐HD). We find that the CRX‐HD is a compact, globular monomer in solution that can specifically bind functional cis‐regulatory elements encoded upstream of retina‐specific genes. This study presents the first structural analysis of CRX, paving the way for a new approach to studying the biochemistry of this protein and its disease‐causing mutant protein variants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Unusual modifications of protein biomarkers expressed by plasmid, prophage, and bacterial host of pathogenic Escherichia coli identified using top‐down proteomic analysis

Rationale Pathogenic bacteria often carry prophage (bacterial viruses) and plasmids (small circular pieces of DNA) that may harbor toxin, antibacterial, and antibiotic resistance genes. Proteomic characterization of pathogenic bacteria should include the identification of host proteins and proteins produced by prophage and plasmid genomes. Methods Protein biomarkers of two strains of Shiga toxin–producingEscherichia coli(STEC) were identified using antibiotic induction, matrix‐assisted laser desorption/ionization tandem time‐of‐flight (MALDI‐TOF‐TOF) tandem mass spectrometry (MS/MS) with post‐source decay (PSD), top‐down proteomic (TDP) analysis, and plasmid sequencing. Alphafold2 was also used to compare predicted in silico structures of the identified proteins to prominent fragment ions generated using MS/MS‐PSD. Strain samples were also analyzed with and without chemical reduction treatment to detect the attachment of pendant groups bound by thioester or disulfide bonds. Results Shiga toxin was detected and/or identified in both STEC strains. For the first time, we also identified the osmotically inducible protein (OsmY) whose sequence unexpectedly had two forms: a full and a truncated sequence. The truncated OsmY terminates in the middle of an α‐helix as determined by Alphafold2. A plasmid‐encoded colicin immunity protein was also identified with and without attachment of an unidentified cysteine‐bound pendant group (~307 Da). Plasmid sequencing confirmed top‐down analysis and the identification of a promoter upstream of the immunity gene that is activated by antibiotic induction, that is, SOS box. Conclusions TDP analysis, coupled with other techniques (e.g., antibiotic induction, chemical reduction, plasmid sequencing, and in silico protein modeling), is a powerful tool to identify proteins (and their modifications), including prophage‐ and plasmid‐encoded proteins, produced by pathogenic microorganisms.

Biochemistry & Molecular Biology↗

DOE OSTI2023

Learning and Predicting Photonic Responses of Plasmonic Nanoparticle Assemblies via Dual Variational Autoencoders

In this work, the application of machine learning is demonstrated for rapid and accurate extraction of plasmonic particles cluster geometries from hyperspectral image data via a dual variational autoencoder (dual-VAE). In this approach, the information is shared between the latent spaces of two VAEs acting on the particle shape data and spectral data, respectively, but enforcing a common encoding on the shape-spectra pairs. It is shown that this approach can establish the relationship between the geometric characteristics of nanoparticles and their far-field photonic responses, demonstrating that hyperspectral darkfield microscopy can be used to accurately predict the geometry (number of particles, arrangement) of a multiparticle assemblies below the diffraction limit in an automated fashion with high fidelity (for monomers (0.96), dimers (0.86), and trimers (0.58). This approach of building structure-property relationships via shared encoding is universal and should have applications to a broader range of materials science and physics problems in imaging of both molecular and nanomaterial systems.

variational autoencoder↗

DOE OSTI2025

Semi-supervised permutation invariant particle-level anomaly detection

The development of analysis methods to distinguish potential beyond the Standard Model phenomena in a model-agnostic way can significantly enhance the discovery reach in collider experiments. However, the typical machine learning (ML) algorithms employed for this task require fixed length and ordered inputs that break the natural permutation invariance in collision events. To address this, a semi-supervised anomaly detection tool is presented that takes a variable number of particle-level inputs and leverages a signal model to encode this information into a permutation invariant, event-level representation via supervised training with a Particle Flow Network (PFN). Data events are then encoded into this representation and given as input to an autoencoder for unsupervised ANomaly deTEction on particLe flOw latent sPacE (ANTELOPE), classifying anomalous events based on a low-level and permutation invariant input modeling. Performance of the ANTELOPE architecture is evaluated on simulated samples of hadronic processes in a high energy collider experiment, showing good capability to distinguish disparate models of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Quantum error correction in the black hole interior

We study the quantum error correction properties of the black hole interior in a toy model for an evaporating black hole: Jackiw-Teitelboim gravity entangled with a non-gravitational bath. After the Page time, the black hole interior degrees of freedom in this system are encoded in the bath Hilbert space. We use the gravitational path integral to show that the interior density matrix is correctable against the action of quantum operations on the bath which (i) do not have prior access to details of the black hole microstates, and (ii) do not have a large, negative coherent information with respect to the maximally mixed state on the bath, with the lower bound controlled by the black hole entropy and code subspace dimension. Thus, the encoding of the black hole interior in the radiation is robust against generic, low-rank quantum operations. For erasure errors, gravity comes within an O (1) distance of saturating the Singleton bound on the tolerance of error correcting codes. For typical errors in the bath to corrupt the interior, they must have a rank that is a large multiple of the bath Hilbert space dimension, with the precise coefficient set by the black hole entropy and code subspace dimension.

2D gravity↗

DOE OSTI2024

Massive twistor worldline in electromagnetic fields

We study the (ambi-)twistor model for spinning particles interacting via electromagnetic field, as a toy model for studying classical dynamics of gravitating bodies including effects of both spins to all orders. We compute the momentum kick and spin kick up to one-loop order and show precisely how they are encoded in the classical eikonal. The all-orders-in-spin effects are encoded as a dynamical implementation of the Newman-Janis shift, and we find that the expansion in both spins can be resummed to simple expressions in special kinematic configurations, at least up to one-loop order. We confirm that the classical eikonal can be understood as the generator of canonical transformations that map the in-states of a scattering process to the out-states. We also remark that cut contributions for converting worldline propagators from time-symmetric to retarded amount to the iterated action of the leading eikonal at one-loop order.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗