Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Expression systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

River Plume Liftoff Dynamics and Surface Expressions

The water surface expression of liftoff and its dependence on discharge are examined using numerical simulations with the Regional Ocean Modeling System (ROMS). Liftoff is the process by which buoyant river water separates from the bed and flows over denser saltwater. During low-discharge conditions liftoff occurs in the river and is accompanied by a change in the surface slope. During high-discharge conditions liftoff occurs outside the mouth and generates a ridge on the water surface. The location and height of the ridge can be described by analytical equations in terms of discharge, shelf slope, and river mouth aspect ratio. The offshore distance and height of the ridge are proportional to the river discharge and vary inversely with river mouth aspect ratio. For steep shelf slopes liftoff occurs close to the river mouth and generates a large ridge. The ridge is modified, but not eliminated, by the presence of tides. The water surface slope change at the ridge peak is large enough to be detected by the upcoming Surface Water and Ocean Topography (SWOT) altimeter and can be used to identify the liftoff location during high discharge. However, during low discharge the water surface slope change at the liftoff location is too small to be detected by SWOT. These results indicate that remote measurements of the presence or absence of the ridge may be useful to distinguish between low and high flows, and remote measurements of the ridge location or height could be used to estimate freshwater discharge.

42 ENGINEERING↗
DOE OSTI2023

The exceptional form and function of the giant bacterium Ca. Epulopiscium viviparus revolves around its sodium motive force

Epulopiscium spp. are the largest known heterotrophic bacteria; a large cigar-shaped individual is a million times the volume of Escherichia coli. To better understand the metabolic potential and relationship of Epulopiscium sp. type B with its host Naso tonganus, we generated a high-quality draft genome from a population of cells taken from a single fish. We propose the name Candidatus Epulopiscium viviparus to describe populations of this best-characterized Epulopiscium species. Metabolic reconstruction reveals more than 5% of the genome codes for carbohydrate active enzymes, which likely degrade recalcitrant host-diet algal polysaccharides into substrates that may be fermented to acetate, the most abundant short-chain fatty acid in the intestinal tract. Moreover, transcriptome analyses and the concentration of sodium ions in the host intestinal tract suggest that the use of a sodium motive force (SMF) to drive ATP synthesis and flagellar rotation is integral to symbiont metabolism and cellular biology. In natural populations, genes encoding both F-type and V-type ATPases and SMF generation via oxaloacetate decarboxylation are among the most highly expressed, suggesting that ATPases synthesize ATP and balance ion concentrations across the cell membrane. High expression of these and other integral membrane proteins may allow for the growth of its extensive intracellular membrane system. Further, complementary metabolism between microbe and host is implied with the potential provision of nitrogen and B vitamins to reinforce this nutritional symbiosis. The few features shared by all bacterial behemoths include extreme polyploidy, polyphosphate synthesis, and thus far, they have all resisted cultivation in the lab.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

ATAC-Seq Reveals an Isl1 Enhancer That Regulates Sinoatrial Node Development and Function

Cardiac pacemaker cells (PCs) in the sinoatrial node (SAN) have a distinct gene expression program that allows them to fire automatically and initiate the heartbeat. Although critical SAN transcription factors, including Isl1 (Islet-1), Tbx3 (T-box transcription factor 3), and Shox2 (short-stature homeobox protein 2), have been identified, the cis-regulatory architecture that governs PC-specific gene expression is not understood, and discrete enhancers required for gene regulation in the SAN have not been identified. Here, to define the epigenetic profile of PCs using comparative ATAC-seq (assay for transposase-accessible chromatin with sequencing) and to identify novel enhancers involved in SAN gene regulation, development, and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

In silico evaluation of a targeted metaproteomics strategy for broad screening of cellulolytic enzyme capacities in anaerobic microbiome bioreactors

Microbial-driven solubilization of lignocellulosic material is a natural mechanism that is exploited in anaerobic digesters (ADs) to produce biogas and other valuable bioproducts. Glycoside hydrolases (GHs) are the main enzymes that bacterial and archaeal populations use to break down complex polysaccharides in these reactors. Methodologies for rapidly screening the physical presence and types of GHs can provide information about their functional activities as well as the taxonomical diversity within AD systems but are largely unavailable. Targeted proteomic methods could potentially be used to provide snapshots of the GHs expressed by microbial consortia in ADs, giving valuable insights into the functional lignocellulolytic degradation diversity of a community. Such observations would be essential to evaluate the hydrolytic performance of a reactor or potential issues with it.

09 BIOMASS FUELS↗
DOE OSTI2025

Yes, No, Maybe So: Human Factors Considerations for Fostering Calibrated Trust in Foundation Models Under Uncertainty

High-stakes analytical environments require analysts to evaluate evidence and generate conclusions to inform critical decisions often under conditions of uncertainty. Probabilistic decision-making based on incomplete or inaccurate information can reduce productivity, compromise national interests, and endanger public safety. Researchers are developing expert systems built on foundation models (FMs) to support analysts’ decision-making processes by enabling human-artificial intelligence (AI) teaming, in part through the quantification and expression of uncertainty information. As FMs continue to mature, it is imperative to correspondingly consider analysts’ needs for appropriately interpreting and using uncertainty information. However, prior research indicates that it remains unclear how analysts engage with FM-generated uncertainty information and the extent to which these interactions influence trust in, and reliance on, expert systems. We plan to review the state of the science and conduct an exploratory, qualitative study to (a) understand how properly communicated uncertainty can foster calibrated trust and appropriate reliance and (b) identify approaches for effectively conveying FM-generated uncertainty information during analytical workflows. We will administer semi-structured interviews with analysts from a specific high-stakes analytical environment to collect their current experiences with job-related uncertainty and their impressions when viewing FM-generated uncertainty information. During the interview protocol, participants will be presented with several different FM outputs and invited to discuss their thoughts and beliefs about the uncertainty information displayed. Participants may provide insights into how trust and reliance may be influenced by uncertainty. The results of this study will help us to better understand how analysts currently interpret and use uncertainty information. Our findings may inform human factors recommendations for effectively conveying uncertainty information to foster calibrated trust in, and appropriate reliance on, expert systems. Interaction designers and FM developers can use this knowledge to enhance human-AI teaming and ensure the responsible deployment of FM-based expert systems in analytical workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Ammonia-Oxidizing Bacteria Maintain Abundance but Lower amoA -Gene Expression during Cold Temperature Nitrification Failure in a Full-Scale Municipal Wastewater Treatment Plant

The diverse microbial community of activated sludge used in biological treatment systems exhibits dynamic seasonal shifts in community composition and activity. Many wastewater treatment plants in temperate/continental climates experience seasonal cold temperature nitrification failure. “Seasonal nitrification failure” is the discharge of elevated concentrations of ammonia (greater than 4 mg/liter) with treated wastewater during the winter (influent wastewater temperatures below 13°C).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Hypergraph Models of Biological Networks to Identify Genes Critical to Pathogenic Viral Response

Motivation: Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationships present among genes and proteins in biological systems such as protein complexes, metabolic reactions, and signal transduction pathways. Hypergraphs are generalizations of graphs that naturally model multi-way interactions in data, and we therefore seek to understand how they can more faithfully identify, and potentially predict, complex relationships in genomic expression data sets. Results: We compiled a novel data set of transcriptional host response to pathogenic viral infections and formulated relationships between genes as a hypergraph where hyperedges are differentially expressed genes and vertices represent conditions. We find that hypergraph betweenness centrality is a superior method for identification of genes important to viral response when compared with graph centrality. Our results demonstrate the utility of using hypergraphs to represent complex biological systems, and highlight potentially interesting biological results about host response to highly pathogenic viruses.

systems biology, hypergraph, viral infection, biol↗
DOE OSTI2023

Ghrelin Modulates Differential Expression of Genes Relevant to Immune Activities and Antimicrobial Peptides in Primary Head Kidney Cells of Rainbow Trout ( Oncorhynchus mykiss )

Ghrelin is a peptide hormone/cytokine that regulates metabolic processes and plays essential roles in the immune system. To evaluate the immunomodulatory actions of ghrelin isoforms in rainbow trout (RT), an in vitro model was utilized with primary cells isolated from fish head kidney (HKD). These RT-HKD cells were treated with synthetic rainbow trout ghrelin and its truncated isoform, desVRQ-ghrelin, over time (0, 2, 4, and 24 h). Reverse transcriptase-coupled qPCR was used to measure the differential expression patterns of genes relevant to various immune processes and genes of antimicrobial peptides. Ghrelin isoform treatments resulted in functional perturbations that displayed overlapping and divergent patterns of gene expression. The differing actions between the two ghrelin isoforms on various assessed genes, and at differing time points, suggested that the two analogs may activate unique pathways, thereby eliciting distinct responses in fish immunity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Identification of ancestral gnathostome Gli3 enhancers with activity in mammals

Abnormal expression of the transcriptional regulator and hedgehog (Hh) signaling pathway effector Gli3 is known to trigger congenital disease, most frequently affecting the central nervous system (CNS) and the limbs. Accurate delineation of the genomic cis-regulatory landscape controlling Gli3 transcription during embryonic development is critical for the interpretation of noncoding variants associated with congenital defects. Here, we employed a comparative genomic analysis on fish species with a slow rate of molecular evolution to identify seven previously unknown conserved noncoding elements (CNEs) in Gli3 intronic intervals (CNE15–21). Transgenic assays in zebrafish revealed that most of these elements drive activities in Gli3 expressing tissues, predominantly the fins, CNS, and the heart. Intersection of these CNEs with human disease associated SNPs identified CNE15 as a putative mammalian craniofacial enhancer, with conserved activity in vertebrates and potentially affected by mutation associated with human craniofacial morphology. Finally, comparative functional dissection of an appendage-specific CNE conserved in slowly evolving fish (elephant shark), but not in teleost (CNE14/hs1586) indicates co-option of limb specificity from other tissues prior to the divergence of amniotes and lobe-finned fish. In conclusion, these results uncover a novel subset of intronic Gli3 enhancers that arose in the common ancestor of gnathostomes and whose sequence components were likely gradually modified in other species during the process of evolutionary diversification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Permutation invariant polynomial neural network based diabatic ansatz for the ( E + A ) × ( e + a ) Jahn–Teller and Pseudo-Jahn–Teller systems

In this work, the permutation invariant polynomial neural network (PIP-NN) approach is employed to construct a quasi-diabatic Hamiltonian for system with non-Abelian symmetries. It provides a flexible and compact NN-based diabatic ansatz from the related approach of Williams, Eisfeld, and co-workers. The example of $H^3_+$ is studied, which is an (E + A) × (e + a) Jahn–Teller and Pseudo-Jahn–Teller system. The PIP-NN diabatic ansatz is based on the symmetric polynomial expansion of Viel and Eisfeld, the coefficients of which are expressed with neural network functions that take permutation-invariant polynomials as input. This PIP-NN-based diabatic ansatz not only preserves the correct symmetry but also provides functional flexibility to accurately reproduce ab initio electronic structure data, thus resulting in excellent fits. Further, the adiabatic energies, energy gradients, and derivative couplings are well reproduced. A good description of the local topology of the conical intersection seam is also achieved. Therefore, this diabatic ansatz completes the PIP-NN based representation of DPEM with correct symmetries and will enable us to diabatize even more complicated systems with complex symmetries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Engineering the cellulolytic extreme thermophile Caldicellulosiruptor bescii to reduce carboxylic acids to alcohols using plant biomass as the energy source

Abstract Caldicellulosiruptor bescii is the most thermophilic cellulolytic organism yet identified (Topt 78 °C). It grows on untreated plant biomass and has an established genetic system thereby making it a promising microbial platform for lignocellulose conversion to bio-products. Here, we investigated the ability of engineered C. bescii to generate alcohols from carboxylic acids. Expression of aldehyde ferredoxin oxidoreductase (aor from Pyrococcus furiosus) and alcohol dehydrogenase (adhA from Thermoanaerobacter sp. X514) enabled C. bescii to generate ethanol from crystalline cellulose and from biomass by reducing the acetate produced by fermentation. Deletion of lactate dehydrogenase in a strain expressing the AOR–Adh pathway increased ethanol production. Engineered strains also converted exogenously supplied organic acids (isobutyrate and n-caproate) to the corresponding alcohol (isobutanol and hexanol) using both crystalline cellulose and switchgrass as sources of reductant for alcohol production. This is the first instance of an acid to alcohol conversion pathway in a cellulolytic microbe.

Biotechnology & Applied Microbiology↗
DOE OSTI2025

Differential Expression of Core Metabolic Functions in Candidatus Altiarchaeum Inhabiting Distinct Subsurface Ecosystems

Candidatus Altiarchaea are widespread across aquatic subsurface ecosystems and possess a highly conserved core genome, yet adaptations of this core genome to different biotic and abiotic factors based on gene expression remain unknown. Here, we investigated the metatranscriptome of two Ca. Altiarchaeum populations that thrive in two substantially different subsurface ecosystems. In Crystal Geyser, a high-CO2 groundwater system in the USA, Ca. Altiarchaeum crystalense co-occurs with the symbiont Ca. Huberiarchaeum crystalense, while in the Muehlbacher sulfidic spring in Germany, an artesian spring high in sulfide concentration, Ca. A. hamiconexum is heavily infected with viruses. We here mapped metatranscriptome reads against their genomes to analyse the in situ expression profile of their core genomes. Out of 537 shared gene clusters, 331 were functionally annotated and 130 differed significantly in expression between the two sites. Main differences were related to genes involved in cell defence like CRISPR-Cas, virus defence, replication, transcription and energy and carbon metabolism. Our results demonstrate that altiarchaeal populations in the subsurface are likely adapted to their environment while influenced by other biological entities that tamper with their core metabolism. We consequently posit that viruses and symbiotic interactions can be major energy sinks for organisms in the deep biosphere.

archaea↗
DOE OSTI2021

Designer membraneless organelles sequester native factors for control of cell behavior

Subcellular compartmentalization of macromolecules increases flux and prevents inhibitory interactions to control biochemical reactions. Inspired by this functionality, we sought to build designer compartments that function as hubs to regulate the flow of information through cellular control systems. Here we report a synthetic membraneless organelle platform to control endogenous cellular activities through sequestration and insulation of native proteins. We engineer and express a disordered protein scaffold to assemble micron size condensates and recruit endogenous clients via genomic tagging with high-affinity dimerization motifs. By relocalizing up to ninety percent of a targeted enzymes to synthetic condensates, we efficiently control cellular behaviors, including proliferation, division, and cytoskeletal organization. Further, we demonstrate multiple strategies for controlled cargo release from condensates to switch cells between functional states. These synthetic organelles offer a powerful and generalizable approach to modularly control cell decision-making in a variety of model systems with broad applications for cellular engineering.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Inference-Based Quantum Sensing

In a standard quantum sensing (QS) task one aims at estimating an unknown parameter θ, encoded into an n-qubit probe state, via measurements of the system. The success of this task hinges on the ability to correlate changes in the parameter to changes in the system response $\mathscr{R}$⁡(θ) (i.e., changes in the measurement outcomes). For simple cases the form of $\mathscr{R}$⁡(θ) is known, but the same cannot be said for realistic scenarios, as no general closed-form expression exists. Here, in this Letter, we present an inference-based scheme for QS. We show that, for a general class of unitary families of encoding, $\mathscr{R}$⁡(θ) can be fully characterized by only measuring the system response at 2⁢n+1 parameters. This allows us to infer the value of an unknown parameter given the measured response, as well as to determine the sensitivity of the scheme, which characterizes its overall performance. We show that inference error is, with high probability, smaller than δ, if one measures the system response with a number of shots that scales only as Ω⁢(log 3 ⁡(n)/δ 2 ). Furthermore, the framework presented can be broadly applied as it remains valid for arbitrary probe states and measurement schemes, and, even holds in the presence of quantum noise. We also discuss how to extend our results beyond unitary families. Finally, to showcase our method we implement it for a QS task on real quantum hardware, and in numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Improved motional Stark effect signal processing using fast Fourier transform spectral analysis

A Fast Fourier Transform (FFT) based method has been developed, which improves the frequency response of the Motional Stark Effect (MSE) system by about a factor of 10 over the conventional analog lock-in method. The method uses fits to rigorously derived analytic expressions for the FFT spectral components of the MSE signal to accurately obtain the amplitudes and phases of the 2f1 and 2f2 photo-elastic modulator (PEM) frequencies that encode the polarization angle. Since no frequency filtering is used in the FFT method, the frequency response is limited by fundamental measurement properties: the frequency response of the detector, photon statistics, sample rate, and the ability to resolve the spectral components. In contrast, the frequency response of the analog lock-in is limited by a low pass filter with a cutoff of around 500 Hz. In the case of the DIII-D MSE system, the output of the photo-multiplier tube detector was sampled at 500 kHz and FFTs with as few as 100 points were used to obtain the amplitudes of the 2f1 and 2f2 PEM frequency components. This corresponds to a frequency response of 5 kHz, about ten times faster than the analog lock-in amplifier system. Details of the FFT method will be presented and compared to those of the analog lock-in system.

Makowski, M. A.↗
DOE OSTI2024

Targeted protein degradation systems to enhance Wnt signaling

Molecules that facilitate targeted protein degradation (TPD) offer great promise as novel therapeutics. The human hepatic lectin asialoglycoprotein receptor (ASGR) is selectively expressed on hepatocytes. We have previously engineered an anti-ASGR1 antibody-mutant RSPO2 (RSPO2RA) fusion protein (called SWEETS) to drive tissue-specific degradation of ZNRF3/RNF43 E3 ubiquitin ligases, which achieved hepatocyte-specific enhanced Wnt signaling, proliferation, and restored liver function in mouse models, and an antibody–RSPO2RA fusion molecule is currently in human clinical trials. In the current study, we identified two new ASGR1- and ASGR1/2-specific antibodies, 8M24 and 8G8. High-resolution crystal structures of ASGR1:8M24 and ASGR2:8G8 complexes revealed that these antibodies bind to distinct epitopes on opposing sides of ASGR, away from the substrate-binding site. Both antibodies enhanced Wnt activity when assembled as SWEETS molecules with RSPO2RA through specific effects sequestering E3 ligases. In addition, 8M24-RSPO2RA and 8G8-RSPO2RA efficiently downregulate ASGR1 through TPD mechanisms. These results demonstrate the possibility of combining different therapeutic effects and degradation mechanisms in a single molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Semi-Analytical Hierarchical Bayesian Inference of Nonlinear Model Structure in Stochastic Dynamics: Applied to Compartmental Models of Infectious Diseases

A Bayesian computational framework for parsimonious inference in stochastic nonlinear dynamical systems is presented. This framework enables the concurrent estimation of system states, time-varying parameters, time-invariant parameters, and the optimal sparsity structure of the model parameters. Because differential equation-based models are often simplified mechanistic or phenomenological representations, robust inference from noisy measurement data requires explicit treatment of model error and uncertainty. Model error and time-varying parameters can be represented as random processes, enabling inference while making minimal assumptions about the underlying sources of discrepancy and variability. Adopting stochastic differential equation representations affords the model significant flexibility, but can also render it susceptible to overfitting during statistical inversion, where the inferred model may track noise rather than the underlying signal. To alleviate the effects of overfitting and to enable the discovery of the optimal sparse representation of the time-invariant parameters, a Bayesian sparse learning algorithm is embedded within the framework. This sparse learning framework adopts an approximate hierarchical Bayesian setting defined by a series of semi-analytical expressions. The model structure inference framework is validated using a stochastic compartmental model for tracking and forecasting active cases of an infectious disease. Compartmental models describe population-level infectious disease dynamics through interactions among population fractions grouped by disease state. Mathematically, such models consist of a system of coupled ordinary differential equations. This example adopts an expressive compartmental model that includes multiple possible interactions between disease states, motivated by early uncertainty surrounding COVID-19 reinfection dynamics and their implications for long-term epidemic forecasting. The sparse learning exercise permits the inference of a priori unknown epidemiological dynamics from simulated public health data, discovering the nested compartmental model that optimizes the trade-off between average data-fit and model complexity. It is shown that inducing sparsity among the model parameters eliminates redundant interactions between compartments, equivalently revealing the optimal coupling structure between differential equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Immunophenotypic characterization and therapeutics effects of human bone marrow- and umbilical cord-derived mesenchymal stromal cells in an experimental model of sepsis

Highlights: • Mesenchymal stromal cells (MSCs) may be a therapeutic option for sepsis. • Bone marrow (BM) vs. umbilical cord (UC) -MSCs induce different M1/M2 gene profiles. • In a CLP model of sepsis, only BM-MSCs improved survival and bacterial clearance. Sepsis is a complicated multi-system disorder characterized by a dysregulated host response to infection. Despite substantial progress in the understanding of mechanisms of sepsis, translation of these advances into clinically effective therapies remains challenging. Mesenchymal Stromal Cells (MSCs) possess immunomodulatory properties that have shown therapeutic promise in preclinical models of sepsis. The therapeutic effects of MSCs may vary depending on the source and type of these cells. In this comparative study, the gene expression pattern and surface markers of bone marrow-derived MSCs (BM-MSCs) and umbilical cord-derived MSCs (UC-MSCs) as well as their therapeutic effects in a clinically relevant mouse model of polymicrobial sepsis, cecal ligation and puncture (CLP), were investigated. The results showed remarkable differences in gene expression profile, surface markers and therapeutic potency in terms of enhancing survival and pro/anti-inflammatory responses between the two MSC types. BM-MSCs improved survival concomitant with an enhanced systemic bacterial clearance and improved inflammatory profile post CLP surgery. Despite some improvement in the inflammatory profile of the septic animals, treatment with UC-MSCs did not enhance survival or bacterial clearance. Overall, the beneficial therapeutic effects of BM-MSCs over UC-MSCs may likely be attributed to their pro-inflammatory function, and to some extent anti-inflammatory features, reflected in their gene expression pattern enhancing macrophage polarization to M1/M2 phenotypes resulting in a balanced pro- and anti-inflammatory response against polymicrobial sepsis.

60 APPLIED LIFE SCIENCES↗