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DOE OSTI2021

A consensus-based ensemble approach to improve transcriptome assembly

Systems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. In this study, we first provide a pipeline to generate a set of the simulated benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. Without using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Biophysical characterization and a roadmap towards the NMR solution structure of G0S2, a key enzyme in non-alcoholic fatty liver disease

In the United States non-alcoholic fatty liver disease (NAFLD) is the most common form of chronic liver disease, affecting an estimated 80 to 100 million people. It occurs in every age group, but predominantly in people with risk factors such as obesity and type 2 diabetes. NAFLD is marked by fat accumulation in the liver leading to liver inflammation, which may lead to scarring and irreversible damage progressing to cirrhosis and liver failure. In animal models, genetic ablation of the protein G0S2 leads to alleviation of liver damage and insulin resistance in high fat diets. The research presented in this paper aims to aid in rational based drug design for the treatment of NAFLD by providing a pathway for a solution state NMR structure of G0S2. Here we describe the expression of G0S2 in an E. coli system from two different constructs, both of which are confirmed to be functionally active based on the ability to inhibit the activity of Adipose Triglyceride Lipase. In one of the constructs, preliminary NMR spectroscopy measurements show dominant alpha-helical characteristics as well as resonance assignments on the N-terminus of G0S2, allowing for further NMR work with this protein. Additionally, the characterization of G0S2 oligomers are outlined for both constructs, suggesting that G0S2 may defensively exist in a multimeric state to protect and potentially stabilize the small 104 amino acid protein within the cell. This information presented on the structure of G0S2 will further guide future development in the therapy for NAFLD.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗

DOE OSTI2021

A gene-editing/complementation strategy for tissue-specific lignin reduction while preserving biomass yield

Lignification of secondary cell walls is a major factor conferring recalcitrance of lignocellulosic biomass to deconstruction for fuels and chemicals. Genetic modification can reduce lignin content and enhance saccharification efficiency, but usually at the cost of moderate-to-severe growth penalties. We have developed a method, using a single DNA construct that uses CRISPR–Cas9 gene editing to knock-out expression of an endogenous gene of lignin monomer biosynthesis while at the same time expressing a modified version of the gene’s open reading frame that escapes cutting by the Cas9 system and complements the introduced mutation in a tissue-specific manner. Expressing the complementing open reading frame in vessels allows for the regeneration of Arabidopsis plants with reduced lignin, wild-type biomass yield, and up to fourfold enhancement of cell wall sugar yield per plant. The above phenotypes are seen in both homozygous and bi-allelic heterozygous T1 lines, and are stable over at least four generations. The method provides a rapid approach for generating reduced lignin trees or crops with one single transformation event, and, paired with a range of tissue-specific promoters, provides a general strategy for optimizing loss-of-function traits that are associated with growth penalties. This method should be applicable to any plant species in which transformation and gene editing are feasible and validated vessel-specific promoters are available.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

A Landing Pad System for Multicopy Gene Integration in Issatchenkia orientalis

The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. This study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.

Fatma, Zia↗

DOE OSTI2023

A landing pad system for multicopy gene integration in Issatchenkia orientalis

The robust nature of the non-conventional yeast Issatchenkia orientalis allows it to grow under highly acidic conditions and therefore, has gained increasing interest in producing organic acids using a variety of carbon sources. Recently, the development of a genetic toolbox for I. orientalis, including an episomal plasmid, characterization of multiple promoters and terminators, and CRISPR-Cas9 tools, has eased the metabolic engineering efforts in I. orientalis. However, multiplex engineering is still hampered by the lack of efficient multicopy integration tools. To facilitate the construction of large, complex metabolic pathways by multiplex CRISPR-Cas9-mediated genome editing, we developed a bioinformatics pipeline to identify and prioritize genome-wide intergenic loci and characterized 47 gRNAs located in 21 intergenic regions. These loci are screened for guide RNA cutting efficiency, integration efficiency of a gene cassette, the resulting cellular fitness, and GFP expression level. We further developed a landing pad system using components from these well-characterized loci, which can aid in the integration of multiple genes using single guide RNA and multiple repair templates of the user’s choice. We have demonstrated the use of the landing pad for simultaneous integrations of 2, 3, 4, or 5 genes to the target loci with efficiencies greater than 80%. As a proof of concept, we showed how the production of 5-aminolevulinic acid can be improved by integrating five copies of genes at multiple sites in one step. We have further demonstrated the efficiency of this tool by constructing a metabolic pathway for succinic acid production by integrating five gene expression cassettes using a single guide RNA along with five different repair templates, leading to the production of 9 g/L of succinic acid in batch fermentations. Furthermore, this study demonstrates the effectiveness of a single gRNA-mediated CRISPR platform to build complex metabolic pathways in a non-conventional yeast. This landing pad system will be a valuable tool for the metabolic engineering of I. orientalis.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

H ∞ Control for Energy Dispatch in Autonomous Nanogrid With Communication Delays

This paper proposes an optimal controller and estimator for energy dispatch to balance the power supply and demand considering communication delays. The proposed algorithm involves modeling an autonomous nanogrid (ANG) consisting of distributed energy resources, energy storage systems, loads, an $H$ ∞ controller with a reference power modulation technique, and a state estimator. The ANG was developed to express the dynamic supply-demand energy balance of a nanogird system. Reference power modulation was designed to generate the desired ESS power based on the imbalanced energy. Random communication delays were modeled using a stochastic variable satisfying the Bernoulli random binary distribution. The optimal $H$ ∞ controller and estimator were developed using a linear matrix inequality approach to exponentially stabilize the closed-loop system. Simulations were performed using real daily demand forecasts obtained from the Korea Meteorological Administration to demonstrate the effectiveness of the proposed real-time optimization algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

High-throughput cell-free screening of eukaryotic membrane protein expression in lipidic mimetics

Membrane proteins play essential roles in cellular function and metabolism. Nonetheless, biophysical and structural studies of membrane proteins are impeded by the difficulty of their expression in and purification from heterologous cell-based systems. As an alternative to these cell-based systems, cell-free protein synthesis has proven to be an exquisite method for screening membrane protein targets in a variety of lipidic mimetics. Here we report a high-throughput screening workflow and applied it to screen 61eukaryotic membrane protein targets. For each target, we tested its expression in lipidic mimetics: two detergents, two liposomes, and two nanodiscs. We show that 35 membrane proteins (57%) can be expressed in a soluble fraction in at least one of the mimetics with the two detergents performing significantly better than nanodiscs and liposomes, in that order. Using the established cell-free workflow, we studied the production and biophysical assays for mitochondrial pyruvate carrier (MPC) complexes. Our studies show that the complexes produced in cell-free are functional competent in complex formation and substrate binding. Our results highlight the utility of using cell-free systems for screening and production of eukaryotic membrane proteins.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

A bipartite bacterial virulence factor targets the complement system and neutrophil activation

Abstract The complement system and neutrophils constitute the two main pillars of the host innate immune defense against infection by bacterial pathogens. Here, we identify T-Mac, a novel virulence factor of the periodontal pathogen Treponema denticola that allows bacteria to evade both defense systems. We show that T-Mac is expressed as a pre-protein that is cleaved into two functional units. The N-terminal fragment has two immunoglobulin-like domains and binds with high affinity to the major neutrophil chemokine receptors FPR1 and CXCR1, blocking N -formyl-Met-Leu-Phe- and IL-8-induced neutrophil chemotaxis and activation. The C-terminal fragment functions as a cysteine protease with a unique proteolytic activity and structure, which degrades several components of the complement system, such as C3 and C3b. Murine infection studies further reveal a critical T-Mac role in tissue damage and inflammation caused by bacterial infection. Collectively, these results disclose a novel innate immunity-evasion strategy, and open avenues for investigating the role of cysteine proteases and immunoglobulin-like domains of gram-positive and -negative bacterial pathogens.

Kurniyati, Kurni↗

DOE OSTI2021

Electrical Submersible Pumps: A System Modeling Approach for Power Quality Analysis With Variable Frequency Drives

This article proposes a high-level engineering guide to develop an integrated system model for power quality analysis in electrical submersible pump (ESP) applications with variable frequency drives (VFDs). Such analyses are troublesome in the industry due to the complexity of these systems. In this article, simple steps to perform system integration analyses of such arrangements, including torsional analysis, are developed. A simplified VFD-ESP model suitable for coupled electrical and mechanical analysis in steady state is proposed in all their configurations of practical interest. Such a model can be easily implemented in common simulation software, significantly reducing engineering efforts for implementation and analysis. The focus of the proposed model is the prediction of ESP failures that might result from a poor power quality caused by VFDs. Analytical expressions of different types of harmonics in these systems, as well as their accurate locations in the frequency domain, including their interharmonics and common-mode harmonics, are derived for this purpose. Further, the effectiveness of the proposed model is verified through offline and real-time hybrid simulation results. Finally, a comparison between simulation results obtained using the proposed model and measurements collected on a down-scale laboratory prototype is carried out to demonstrate the accuracy of the suggested modeling approach.

42 ENGINEERING↗

DOE OSTI2022

Biosensor and optogenetics for systems biology of yeast branched-chain alcohol production and tolerance

In this project we combined synthetic biology, systems biology, protein engineering and metabolic engineering to study, control, and improve the production of branched chain alcohols (BCAs), a class of advanced biofuels preferred by the DOE, in the yeast Saccharomyces cerevisiae. This involved the development and application of optogenetic systems as a new modality of dynamic control of native and engineered metabolic pathways, using light as inducible or repressible agent. The optogenetic systems include gene circuits for light control of gene expression, as well as light-assembled synthetic organelles and photo-switchable protein binders to control metabolic and protein function with light at the protein level. In addition, we developed the first genetically encoded biosensor for BCA production in yeast, which we used to design high throughput assays to identify highly productive strains, pathways, and enzymes. We also showed that this biosensor can be functionally co-expressed with optogenetic circuits in the same strain, raising the possibility of establishing, for the first time, computer-interfaced closed-loop controls of engineered metabolic pathways. The yeast gene deletion library was also utilized to conduct the first systems-level study on BCA toxicity in yeast, which uncovered key fundamental principles of yeast sensitivity and tolerance to these alcohols, allowing us to design highly tolerant strains with increased BCA production. This project, thus comprises the development of several new technologies, which we integrated to make new discoveries on the dynamics of BCA production and their mechanisms of cellular toxicity and tolerance, as well as to establish new paradigms to engineer and control metabolic pathways and microbial fermentations with light, for the production of BCAs and other products of interest to the DOE.

2-metyl-1-butanol↗

DOE OSTI2021

Escalation in the host-pathogen arms race: A host resistance response corresponds to a heightened bacterial virulence response

The zig-zag model of host-pathogen interaction describes the relative strength of defense response across a spectrum of pathogen-induced plant phenotypes. A stronger defense response results in increased resistance. Here, we investigate the strength of pathogen virulence during disease and place these findings in the context of the zig-zag model. Xanthomonas vasicola pv. holcicola ( Xvh ) causes sorghum bacterial leaf streak. Despite being widespread, this disease has not been described in detail at the molecular level. We divided diverse sorghum genotypes into three groups based on disease symptoms: water-soaked lesions, red lesions, and resistance. Bacterial growth assays confirmed that these three phenotypes represent a range of resistance and susceptibility. To simultaneously reveal defense and virulence responses across the spectrum of disease phenotypes, we performed dual RNA-seq on Xvh -infected sorghum. Consistent with the zig-zag model, the expression of plant defense-related genes was strongest in the resistance interaction. Surprisingly, bacterial virulence genes related to the type III secretion system (T3SS) and type III effectors (T3Es) were also most highly expressed in the resistance interaction. This expression pattern was observed at multiple time points within the sorghum- Xvh pathosystem. Further, a similar expression pattern was observed in Arabidopsis infected with Pseudomonas syringae for effector-triggered immunity via AvrRps4 but not AvrRpt2. Specific metabolites were able to repress the Xvh virulence response in vitro and in planta suggesting a possible signaling mechanism. Taken together, these findings reveal multiple permutations of the continually evolving host-pathogen arms race from the perspective of host defense and pathogen virulence responses.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Domain Aware Deep-learning Algorithms Integrated with Scientific-computing Technologies (DADAIST)

This technical report summarized the contribution of the DADAIST project funded by the Data Model Convergence Initiative via the Laboratory Directed Research and Development (LDRD) investments at Pacific Northwest National Laboratory (PNNL). Specifically, we report the development of the NeuroMANCER (Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularizations), a new open-source Scientific Machine Learning library for formulating and solving parametric constrained optimization problems, physics-informed system identification, and parametric optimal control problems. NeuroMANCER is using differentiable programming to combine modern data-driven models and optimization modeling language into a coherent algorithmic and software framework. NeuroMANCER is a Pytorch-based framework and adopts much of its philosophy focused on research and development, rapid prototyping, and streamlined deployment. Strong emphasis is given to extensibility, interoperability with the PyTorch ecosystem, and quick adaptability to custom domain problems. Neuromancer repository contains a comprehensive library of differentiable modules, including custom activation functions, matrix factorizations, deep learning architectures, neural differential equations, differential equation solvers, implicit layers such as iterative solvers, high-level API for symbolic expressions, API for modeling and control of dynamical systems, and extensive set of tutorial code examples in the form of python scripts and jupyter notebooks.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Statistical mechanics and pressure of composite multimoded weakly nonlinear optical systems

Statistical mechanics can provide a versatile theoretical framework for investigating the collective dynamics of weakly nonlinear-wave settings that can be utterly complex to describe otherwise. In optics, composite systems arise due to interactions between different frequencies and polarizations. The purpose of this work is to develop a thermodynamic theory that takes into account the synergistic action of multiple components. We find that the type of the nonlinearity involved can have important implications in the thermalization process and, hence, can lead to different thermal equilibrium conditions. Importantly, we derive closed-form expressions for the actual optomechanical pressure that is exerted on the system. In particular, the total optomechanical pressure is the sum of the partial pressures due to each component. Our results can be applied to a variety of weakly nonlinear optical settings such as multimode fibers, bulk waveguides, photonic lattices, and coupled microresonators. We present two specific examples, where two colors interact in a one-waveguide array with either a cubic or quadratic nonlinearity.

Efremidis, Nikolaos K. (ORCID:0000000298300268)↗

DOE OSTI2023

A Suite of Constitutive Promoters for Tuning Gene Expression in Plants

The need for convenient tools to express transgenes over a large dynamic range is pervasive throughout plant synthetic biology; however, current efforts are largely limited by the heavy reliance on a small set of strong promoters, precluding more nuanced and refined engineering endeavors in planta . To address this technical gap, we characterize a suite of constitutive promoters that span a wide range of transcriptional levels and develop a GoldenGate-based plasmid toolkit named PCONS, optimized for versatile cloning and rapid testing of transgene expression at varying strengths. We demonstrate how easy access to a stepwise gradient of expression levels can be used for optimizing synthetic transcriptional systems and the production of small molecules in planta . We also systematically investigate the potential of using PCONS as an internal standard in plant biology experimental design, establishing the best practices for signal normalization in experiments. Although our library has primarily been developed for optimizing expression in N. benthamiana , we demonstrate the translatability of our promoters across distantly related species using a multiplexed reporter assay with barcoded transcripts. In conclusion, our findings showcase the advantages of the PCONS library as an invaluable toolkit for plant synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Intrinsic Anomalous Hall Conductivity in a Nonuniform Electric Field

We study how the intrinsic anomalous Hall conductivity is modified in two-dimensional crystals with broken time-reversal symmetry due to weak inhomogeneity of the applied electric field. Focusing on a clean noninteracting two-band system without band crossings, we derive the general expression for the Hall conductivity at small finite wave vector q to order q 2 , which governs the Hall response to the second gradient of the electric field. Using the Kubo formula, we show that the answer can be expressed through the Berry curvature, Fubini-Study quantum metric, and the rank-3 symmetric tensor which is related to the quantum geometric connection and physically corresponds to the gauge-invariant part of the third cumulant of the position operator. We further compare our results with the predictions made within the semiclassical approach. By deriving the semiclassical equations of motion, we reproduce the result obtained from the Kubo formula in some limits. We also find, however, that the conventional semiclassical description in terms of the definite position and momentum of the electron is not fully consistent because of singular terms originating from the Heisenberg uncertainty principle. We thus present a clear example of a case when the semiclassical approach inherently suffers from the uncertainty principle, implying that it should be applied to systems in nonuniform fields with extra care.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

Data for "Discovery, Characterization, and Application of Chromosomal Integration Sites in the Hyperthermophilic Archaeon Sulfolobus islandicus"

Sulfolobus islandicus , an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

AI/ML↗

DOE OSTI2020

Glycosylation of hyperthermostable designer cellulosome components yields enhanced stability and cellulose hydrolysis

Biomass deconstruction remains integral for enabling second-generation biofuel production at scale. However, several steps necessary to achieve significant solubilization of biomass, notably harsh pretreatment conditions, impose economic barriers to commercialization. By employing hyperthermostable cellulase machinery, biomass deconstruction can be made more efficient, leading to milder pretreatment conditions and ultimately lower production costs. The hyperthermophilic bacterium Caldicellulosiruptor bescii produces extremely active hyperthermostable cellulases, including the hyperactive multifunctional cellulase CbCel9A/Cel48A. Recombinant CbCel9A/Cel48A components have been previously produced in Escherichia coli and integrated into synthetic hyperthermophilic designer cellulosome complexes. Since then, glycosylation has been shown to be vital for the high activity and stability of CbCel9A/Cel48A. Here, we studied the impact of glycosylation on a hyperthermostable designer cellulosome system in which two of the cellulosomal components, the scaffoldin and the GH9 domain of CbCel9A/Cel48A, were glycosylated as a consequence of employing Ca. bescii as an expression host. Inclusion of the glycosylated components yielded an active cellulosome system that exhibited long-term stability at 75 degrees C. The resulting glycosylated designer cellulosomes showed significantly greater synergistic activity compared to the enzymatic components alone, as well as higher thermostability than the analogous nonglycosylated designer cellulosomes. These results indicate that glycosylation can be used as an essential engineering tool to improve the properties of designer cellulosomes. Additionally, Ca. bescii was shown to be an attractive candidate for production of glycosylated designer cellulosome components, which may further promote the viability of this bacterium both as a cellulase expression host and as a potential consolidated bioprocessing platform organism.

09 BIOMASS FUELS↗