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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.

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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Combination of Human Broadly Neutralizing Antibodies against Hepatitis B Virus HBsAg with Distinct Epitopes Suppresses Escape Mutations

Although there is no effective cure for chronic hepatitis B virus (HBV) infection, antibodies are protective and correlate with recovery from infection. To examine the human antibody response to HBV, we screened 124 vaccinated and 20 infected, spontaneously recovered individuals. The selected individuals produced shared clones of broadly neutralizing antibodies (bNAbs) that targeted 3 non-overlapping epitopes on the HBV S antigen (HBsAg). Single bNAbs protected humanized mice against infection but selected for resistance mutations in mice with prior established infection. In contrast, infection was controlled by a combination of bNAbs targeting non-overlapping epitopes with complementary sensitivity to mutations that commonly emerge during human infection. The co-crystal structure of one of the bNAbs with an HBsAg peptide epitope revealed a stabilized hairpin loop. This structure, which contains residues frequently mutated in clinical immune escape variants, provides a molecular explanation for why immunotherapy for HBV infection may require combinations of complementary bNAbs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

CarcSeq Measurement of Rat Mammary Cancer Driver Mutations and Relation to Spontaneous Mammary Neoplasia

Abstract The ability to deduce carcinogenic potential from subchronic, repeat dose rodent studies would constitute a major advance in chemical safety assessment and drug development. This study investigated an error-corrected NGS method (CarcSeq) for quantifying cancer driver mutations (CDMs) and deriving a metric of clonal expansion predictive of future neoplastic potential. CarcSeq was designed to interrogate subsets of amplicons encompassing hotspot CDMs applicable to a variety of cancers. Previously, normal human breast DNA was analyzed by CarcSeq and metrics based on mammary-specific CDMs were correlated with tissue donor age, a surrogate of breast cancer risk. Here we report development of parallel methodologies for rat. The utility of the rat CarcSeq method for predicting neoplastic potential was investigated by analyzing mammary tissue of 16-week-old untreated rats with known differences in spontaneous mammary neoplasia (Fischer 344, Wistar Han, and Sprague Dawley). Hundreds of mutants with mutant fractions ≥ 10−4 were quantified in each strain, most were recurrent mutations, and 42.5% of the nonsynonymous mutations have human homologs. Mutants in the mammary-specific target of the most tumor-sensitive strain (Sprague Dawley) showed the greatest nonsynonymous/synonymous mutation ratio, indicative of positive selection consistent with clonal expansion. For the mammary-specific target (Hras, Pik3ca, and Tp53 amplicons), median absolute deviation correlated with percentages of rats that develop spontaneous mammary neoplasia at 104 weeks (Pearson r = 1.0000, 1-tailed p = .0010). Therefore, this study produced evidence CarcSeq analysis of spontaneously occurring CDMs can be used to derive an early metric of clonal expansion relatable to long-term neoplastic outcome.

McKim, Karen L.↗
DOE OSTI2023

Fully synthetic platform to rapidly generate tetravalent bispecific nanobody–based immunoglobulins

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human V H 3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor–binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the V H and V L domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Engineering regulatory networks for complex phenotypes in E. coli

Regulatory networks describe the hierarchical relationship between transcription factors, associated proteins, and their target genes. Regulatory networks respond to environmental and genetic perturbations by reprogramming cellular metabolism. Here we design, construct, and map a comprehensive regulatory network library containing 110,120 specific mutations in 82 regulators expected to perturb metabolism. We screen the library for different targeted phenotypes, and identify mutants that confer strong resistance to various inhibitors, and/or enhanced production of target compounds. These improvements are identified in a single round of selection, showing that the regulatory network library is universally applicable and is convenient and effective for engineering targeted phenotypes. The facile construction and mapping of the regulatory network library provides a path for developing a more detailed understanding of global regulation in E. coli , with potential for adaptation and use in less-understood organisms, expanding toolkits for future strain engineering, synthetic biology, and broader efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optimized purification methods for metallic contaminant removal from directly recycled Li-ion battery cathodes

Metallic contaminants pose a significant challenge to the viability of directly recycling Li-ion batteries. To date, few strategies exist to selectively remove metallic impurities from mixtures of shredded end-of-life material (black mass; BM) without concurrently damaging the structure and electrochemical performance of the target active material. We herein present tailored methods to selectively ionize two major contaminants—Al and Cu—while retaining a representative cathode (LiNi 0.33 Mn 0.33 Co 0.33 O 2 ; NMC-111) intact. This BM purification process is conducted at moderate temperatures in a KOH-based solution matrix. We rationally evaluate approaches to increase both the kinetic corrosion rate and the thermodynamic solubility of Al 0 and Cu 0 , and evaluate the impact of these treatment conditions on the structure, chemistry, and electrochemical performance of NMC. Specifically, we explore the impacts of chloride-based salts, a strong chelating agent, elevated temperature, and sonication on the rate and extent of contaminant corrosion, while concurrently evaluating the effects on NMC. The reported BM purification process is then demonstrated on samples of “simulated BM” containing a practically relevant 1 wt% concentration of Al or Cu. Increasing the kinetic energy of the purifying solution matrix through elevated temperature and sonication accelerates the corrosion of metallic Al and Cu, such that ∼100% corrosion of 75 μm Al and Cu particles is achieved within 2.5 hr. Further, we determine that effective mass transport of ionized species critically impacts the efficacy of Cu corrosion, and that saturated Cl – hinders rather than accelerates Cu corrosion by increasing solution viscosity and introducing competitive pathways for Cu surface passivation. The purification conditions do not induce bulk structural damage to NMC, and electrochemical capacity is maintained in half-cell format. Testing in full cells suggests that a limited quantity of residual surface species are present after treatment, which initially disrupt electrochemical behavior at the graphite anode but are subsequently consumed. Process demonstration on simulated BM suggests that contaminated samples—which prior to treatment show catastrophic electrochemical performance—can be recovered to pristine electrochemical capacity. The reported BM purification method offers a compelling and commercially viable solution to address contamination, particularly in the “fine” fraction of BM where contaminant sizes are on the same order of magnitude as NMC and where traditional separation approaches are unfeasible. Thus, this optimized BM purification technique offers a pathway towards viable direct recycling of BM feedstocks that would otherwise be unusable.

25 ENERGY STORAGE↗
DOE OSTI2024

System and method for vehicle coast control

A method for controlling vehicle propulsion includes identifying at least one route characteristic of a portion of a route being traversed by a vehicle. The method further includes determining a profile for a target vehicle speed based on the at least one route characteristic and a vehicle energy consumption profile. The method further includes selectively adjusting a vehicle speed control input based on the target vehicle speed profile. The method further includes communicating the vehicle speed control input to a vehicle propulsion controller to achieve the target vehicle speed profile.

Aggoune, Karim↗
DOE OSTI2020

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗
DOE OSTI2025

Mechanistic studies of small molecule ligands selective to RNA single G bulges

Abstract Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated molecular dynamics simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity relationship studies and transverse relaxation measurements by nuclear magnetic resonance spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Our work deepened the understanding of RNA-small molecule interactions and integrated a new framework for the rational design of selective small-molecule RNA binders.

Biochemistry & Molecular Biology↗
DOE OSTI2023

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release (DR18) of the Sloan Digital Sky Survey (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs or “Mappers”: the Milky Way Mapper (MWM), the Black Hole Mapper (BHM), and the Local Volume Mapper. This data release contains extensive targeting information for the two multiobject spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration and scientifically focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Engineering well-expressed, V2-immunofocusing HIV-1 envelope glycoprotein membrane trimers for use in heterologous prime-boost vaccine regimens

HIV-1 vaccine immunofocusing strategies may be able to induce broadly-reactive neutralizing antibodies (NAbs). Here, we engineered a panel of diverse, membrane-resident native HIV-1 trimers vulnerable to two broad targets—the V2 apex and fusion peptide (FP). Selection criteria included i) high expression and ii) infectious function, so that trimer neutralization sensitivity can be profiled in pseudovirus (PV) assays. Initially, we boosted the expression of 17 candidate trimers by truncating gp41 and introducing a gp120-gp41 SOS disulfide to prevent gp120 shedding. "Repairs" were made to fill glycan holes and eliminate other strain-specific aberrations. A new neutralization assay allowed PV infection when our standard assay was insufficient. Trimers with exposed V3 loops, a target of non-NAbs, were discarded. To try to increase V2-sensitivity, we removed clashing glycans and modified the C-strand. Notably, a D167N mutation improved V2-sensitivity in several cases. Glycopeptide analysis of JR-FL trimers revealed near complete sequon occupation and that filling the N197 glycan hole was well-tolerated. In contrast, sequon optimization and inserting/removing glycans at other positions frequently had global "ripple" effects on glycan maturation and sequon occupation throughout the gp120 outer domain and gp41. V2 MAb CH01 selectively bound to trimers with small high mannose glycans near the base of the V1 loop, thereby avoiding clashes. Knocking in a rare N49 glycan was found to perturb gp41 glycans, increasing FP NAb sensitivity—and sometimes improving expression. Finally, a biophysical analysis of VLPs revealed that i) ~25% of particles bear Env spikes, ii) spontaneous particle budding is high and only increases 4-fold upon Gag transfection, and iii) Env+ particles express ~30–40 spikes. Taken together, we identified 7 diverse trimers with a range of sensitivities to two targets to allow rigorous testing of immunofocusing vaccine concepts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Energy-Efficient and Water-Saving Sorbent Regeneration at Near Room Temperature for Direct Air Capture

Here this study reports energy-efficient and water-saving microwave-accelerated regeneration of sorbent (MARS) for dilute carbon capture from the ambient air. The experimental studies indicated that the CO 2 desorption rate from the chemisorbents increased with microwave output under near-isothermal conditions at near room temperature. The reduced activation energy of MARS, i.e., 20–28 kJ/mol, indicated enhanced CO 2 desorption kinetics by microwave-induced rotational–vibrational (rovibrational) coupling transitions, primarily due to the highly polarized feature of the carbamate (CO 2 -PEI). The instant and selective delivery of microwave energy to the targeted polarized C–N bonds at room temperature is particularly advantageous for energy-efficient direct air capture. The experimental results also demonstrated a good working capacity of 0.6–1.4 mmol of CO 2 /g and a promising rapid MARS-DAC process with microwave swing. As it does not require steam regeneration and heat exchanger, a simple MARS process is attractive for CO 2 capture in water-stressed regions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Database-wide hazard modelling of the onset of DIII-D tearing modes with field features

The rate of onset (hazard) of tearing modes is modelled probabilistically using statistical learning algorithms. Axisymmetric energy-density equilibrium fields are taken as raw high-dimensional input features which are reduced with principal component analysis. Signal processing of non-axisymmetric magnetics fluctuation array data provides the target information from which to learn. Model selection, visualization and calibration assessment procedures are detailed. Here, the analysis is deployed at large scale across the DIII-D tokamak database. Standard model selection criteria suggest that the energy-density post-processed feature is a better choice for modelling the onset rate compared to the non-processed equilibrium reconstruction solution. Two example applications of the learned rate function are demonstrated: (i) proximity-to-onset discharge monitoring and (ii) database analysis showing an (expected) observational global trend that the general hazard increases as a plasma performance metric increases. An important connection between the hazard function and its use as a conditional probability generator is reviewed in the Appendix.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-Peptide

Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here, in this study, we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: (i) quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteoforms typically introduced when using a single antibody; (ii) Lys-C digestion producing unique signature peptides for each proteoform, and (iii) trapping-nano-LC coupled with FAIMS/dCV-MS for an ultrasensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing S/N. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive (n = 20) and new-onset type 1 diabetes (T1D, n = 19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the β-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.

Shen, Qingqing [University at Buffalo, NY (United ↗
DOE OSTI2026

Superstructure Optimization of Waste Plastic Pyrolysis, Integrating Thermal, Catalytic, and Plasma Technologies with Machine Learning

Global plastic waste generation exceeds 430 million tonnes per year, yet fewer than 9% are recycled in the United States. Pyrolysis offers a chemical recycling route at scale, but existing techno-economic and life cycle assessments fix product yields to single pure polymers, producing economic and environmental outputs that break down when the feed composition changes. Here, we present a superstructure optimization framework that addresses this by embedding a composition-aware random forest yield predictor, trained on 566 pyrolysis experiments, within a full-scale process simulation. Product distributions update automatically as feed allocation shifts across four reactor chemistries: conventional thermal, catalytic (HZSM-5), thermal oxo-degradation, and nonequilibrium CO2 plasma. The optimal superstructure achieves minimum selling prices of −0.56 to −0.76/kg feed and global warming potentials of −0.276 to −0.322 kg CO2-eq/kg feed across four commodity price scenarios, confirming profitable, carbon-negative operation without tipping fees. Carbon abatement costs of $\$$0.46 to $\$$1.25/kg CO2-eq are competitive with direct air capture. Sensitivity analysis shows that the catalytic-plasma split fraction is the single largest driver of both economic and climate performance, while hydrocracking allocation in the wax upgrading stage is emission-neutral across the full variable range. Mixed plastic waste streams, evaluated as composition-variable feedstocks rather than pure resins, are profitable and carbon-negative across realistic market conditions. These results give a quantitative basis for reactor selection, circular economy investment, and policy design targeting chemical recycling on a large scale.

Life cycle assessment↗
DOE OSTI2025

Numerical Investigation of Susceptor-Catalyst Design for Ethylene Generation in Radio Frequency Based Reactors

Ethylene is the most widely produced petrochemical component in the world. Whether reactors are heated directly or indirectly via steam, manufacturers use economies of scale to overcome inherent thermodynamic inefficiencies when burning fossil fuels. While allowing large-scale operations to use alternative sources of energy and raw materials, new methods of supplying energy to chemical reactor systems can reduce the energy waste produced by conventional processes. One viable method for effectively supplying energy to reactor systems is electromagnetic (EM) induction heating. Using the properties of radio frequency (RF) waves, heterogeneous catalysts can be precisely targeted for heating inside reactors. Site-selective heating can greatly lower the energy requirements of the process by supplying heat to reaction sites while reducing needless heat transfer elsewhere. In this study, a microscale model was used to help create guidelines for susceptors and catalysts to improve ethylene production. The oxidative dehydrogenation of ethane is investigated by utilizing several catalysts and potential catalyst/susceptor combinations, with heat provided by an EM susceptor. Having the susceptors and catalyst function separately results in higher gradients in both heat and mass transfer, which drives transport through the catalyst region, while still providing adequate heating for endothermic reactions. However, using a susceptive core with a catalyst covering produces the maximum ethylene concentration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

In vivo human T cell engineering with enveloped delivery vehicles

Viruses and virally derived particles have the intrinsic capacity to deliver molecules to cells, but the difficulty of readily altering cell-type selectivity has hindered their use for therapeutic delivery. Here, we show that cell surface marker recognition by antibody fragments displayed on membrane-derived particles encapsulating CRISPR–Cas9 protein and guide RNA can deliver genome editing tools to specific cells. Compared to conventional vectors like adeno-associated virus that rely on evolved capsid tropisms to deliver virally encoded cargo, these Cas9-packaging enveloped delivery vehicles (Cas9-EDVs) leverage predictable antibody–antigen interactions to transiently deliver genome editing machinery selectively to cells of interest. Antibody-targeted Cas9-EDVs preferentially confer genome editing in cognate target cells over bystander cells in mixed populations, both ex vivo and in vivo. By using multiplexed targeting molecules to direct delivery to human T cells, Cas9-EDVs enable the generation of genome-edited chimeric antigen receptor T cells in humanized mice, establishing a programmable delivery modality with the potential for widespread therapeutic utility.

42 ENGINEERING↗
DOE OSTI2020

Crystallographic characterization of a tri-Asp metal-binding site at the three-fold symmetry axis of LarE

Detailed crystallographic characterization of a tri-aspartate metal-binding site previously identified on the three-fold symmetry axis of a hexameric enzyme, LarE from Lactobacillus plantarum, was conducted. By screening an array of monovalent, divalent, and trivalent metal ions, we demonstrated that this metal binding site stoichiometrically binds Ca 2+ , Mn 2+ , Fe 2+ /Fe 3+ , Co 2+ , Ni 2+ , Cu 2+ , Zn 2+ , and Cd 2+ , but not monovalent metal ions, Cr 3+ , Mg 2+ , Y 3+ , Sr 2+ or Ba 2+ . Extensive database searches resulted in only 13 similar metal binding sites in other proteins, indicative of the rareness of tri-aspartate architectures, which allows for engineering such a selective multivalent metal ion binding site into target macromolecules for structural and biophysical characterization.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Global analysis of SBP gene family in Brachypodium distachyon reveals its association with spike development

SQUAMOSA-promoter binding like proteins (SBPs/SPLs) are plant specific transcription factors targeted by miR156 and involved in various biological pathways, playing multi-faceted developmental roles. This gene family is not well characterized in Brachypodium. We identified a total of 18 SBP genes in B. distachyon genome. Phylogenetic analysis revealed that SBP gene family in Brachypodium expanded through large scale duplication. A total of 10 BdSBP genes were identified as targets of miR156. Transcript cleavage analysis of selected BdSBPs by miR156 confirmed their antagonistic connection. Alternative splicing was observed playing an important role in BdSBPs and miR156 interaction. Characterization of T-DNA Bdsbp9 mutant showed reduced plant growth and spike length, reflecting its involvement in the spike development. Expression of a majority of BdSBPs elevated during spikelet initiation. Specifically, BdSBP1 and BdSBP3 differentially expressed in response to vernalization. Differential transcript abundance of BdSBP1, BdSBP3, BdSBP8, BdSBP9, BdSBP14, BdSBP18 and BdSBP23 genes was observed during the spike development under high temperature. Co-expression network, protein–protein interaction and biological pathway analysis indicate that BdSBP genes mainly regulate transcription, hormone, RNA and transport pathways. Our work reveals the multi-layered control of SBP genes and demonstrates their association with spike development and temperature sensitivity in Brachypodium.

59 BASIC BIOLOGICAL SCIENCES↗