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DOE OSTI2021

Airborne hyperspectral imaging of nitrogen deficiency on crop traits and yield of maize by machine learning and radiative transfer modeling

Nitrogen is an essential nutrient that directly affects plant photosynthesis, crop yield, and biomass production for bioenergy crops, but excessive application of nitrogen fertilizers can cause environmental degradation. To achieve sustainable nitrogen fertilizer management for precision agriculture, there is an urgent need for nondestructive and high spatial resolution monitoring of crop nitrogen and its allocation to photosynthetic proteins as that changes over time. Here, we used visible to shortwave infrared (400–2400 nm) airborne hyperspectral imaging with high spatial (0.5 m) and spectral (3–5 nm) resolutions to accurately estimate critical crop traits, i.e., nitrogen, chlorophyll, and photosynthetic capacity (CO 2 -saturated photosynthesis rate, V max,27 ), at leaf and canopy scales, and to assess nitrogen deficiency on crop yield. We conducted three airborne campaigns over a maize (Zea mays L.) field during the growing season of 2019. Physically based soil-canopy Radiative Transfer Modeling (RTM) and data-driven approaches i.e. Partial-Least Squares Regression (PLSR) were used to retrieve crop traits from hyperspectral reflectance, with ground truth of leaf nitrogen, chlorophyll, V max,27 , Leaf Area Index (LAI), and harvested grain yield. To improve computational efficiency of RTMs, Random Forest (RF) was used to mimic RTM simulations to generate machine learning surrogate models RTM-RF. The results show that prior knowledge of soil background and leaf angle distribution can significantly reduce the ill-posed RTM retrieval. RTM-RF achieved a high accuracy to predict leaf chlorophyll content (R 2 = 0.73) and LAI (R 2 = 0.75). Meanwhile, PLSR exhibited better accuracy to predict leaf chlorophyll content (R 2 = 0.79), nitrogen concentration (R 2 = 0.83), nitrogen content (R 2 = 0.77), and V max,27 (R 2 = 0.69) but required measured traits for model training. We also found that canopy structure signals can enhance the use of spectral data to predict nitrogen related photosynthetic traits, as combining RTM-RF LAI and PLSR leaf traits well predicted canopy-level traits (leaf traits × LAI) including canopy chlorophyll (R 2 = 0.80), nitrogen (R 2 = 0.85) and V max,27 (R 2 = 0.82). Compared to leaf traits, we further found that canopy-level photosynthetic traits, particularly canopy V max,27 , have higher correlation with maize grain yield. This study highlights the potential for synergistic use of process-based and data-driven approaches of hyperspectral imaging to quantify crop traits that facilitate precision agricultural management to secure food and bioenergy production.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Conformational and oligomeric states of SPOP from small-angle X-ray scattering and molecular dynamics simulations

Speckle-type POZ protein (SPOP) is a substrate adaptor in the ubiquitin proteasome system, and plays important roles in cell-cycle control, development, and cancer pathogenesis. SPOP forms linear higher-order oligomers following an isodesmic self-association model. Oligomerization is essential for SPOP’s multivalent interactions with substrates, which facilitate phase separation and localization to biomolecular condensates. Structural characterization of SPOP in its oligomeric state and in solution is, however, challenging due to the inherent conformational and compositional heterogeneity of the oligomeric species. Here, we develop an approach to simultaneously and self-consistently characterize the conformational ensemble and the distribution of oligomeric states of SPOP by combining small-angle X-ray scattering (SAXS) and molecular dynamics (MD) simulations. We build initial conformational ensembles of SPOP oligomers using coarse-grained molecular dynamics simulations, and use a Bayesian/maximum entropy approach to refine the ensembles, along with the distribution of oligomeric states, against a concentration series of SAXS experiments. Our results suggest that SPOP oligomers behave as rigid, helical structures in solution, and that a flexible linker region allows SPOP’s substrate-binding domains to extend away from the core of the oligomers. Additionally, our results are in good agreement with previous characterization of the isodesmic self-association of SPOP. In the future, the approach presented here can be extended to other systems to simultaneously characterize structural heterogeneity and self-assembly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Role of pore dilation in molecular transport through the nuclear pore complex: Insights from polymer scaling theory

The nuclear pore complex (NPC), a channel within the nuclear envelope filled with intrinsically disordered proteins, regulates the transport of macromolecules between the nucleus and the cytoplasm. Recent studies have highlighted the NPC’s ability to adjust its diameter in response to the membrane tension, underscoring the importance of exploring how variations in pore size influence molecular transport through the NPC. In this study, we investigated the relationship between pore size and transport rate and proposed a mathematical model describing this connection. We began by theoretically analyzing how the pore size scales with the characteristic dimensions of the mesh-like structure within the pore. By introducing key assumptions about how the meshwork structure influences molecular diffusion, we derived a mathematical expression for the transport rate based on the size of the pore and the transported molecules. To validate our model, we conducted Brownian dynamics simulations using a coarse-grained representation of the NPC. These simulations, performed across a range of pore sizes, demonstrated strong agreement with our model’s predictions, confirming its accuracy and applicability. Our model is specifically tailored for small-to-medium-sized molecules, approximately 5 nanometers in size, making it relevant to a wide range of transcription factors and signaling molecules. It also extends to molecules with weak and transient interactions with FG-Nups, such as importin-β. By presenting this model formula, our study offers a quantitative framework for analyzing the effects of pore dilation on nucleocytoplasmic transport.

Biochemistry & Molecular Biology↗

NASA NTRS2000

Pollination and embryo development in Brassica rapa L. in microgravity

Plant reproduction under spaceflight conditions has been problematic in the past. In order to determine what aspect of reproductive development is affected by microgravity, we studied pollination and embryo development in Brassica rapa L. during 16 d in microgravity on the space shuttle (STS-87). Brassica is self-incompatible and requires mechanical transfer of pollen. Short-duration access to microgravity during parabolic flights on the KC-135A aircraft was used initially to confirm that equal numbers of pollen grains could be collected and transferred in the absence of gravity. Brassica was grown in the Plant Growth Facility flight hardware as follows. Three chambers each contained six plants that were 13 d old at launch. As these plants flowered, thin colored tape was used to indicate the date of hand pollination, resulting in silique populations aged 8-15 d postpollination at the end of the 16-d mission. The remaining three chambers contained dry seeds that germinated on orbit to produce 14-d-old plants just beginning to flower at the time of landing. Pollen produced by these plants had comparable viability (93%) with that produced in the 2-d-delayed ground control. Matched-age siliques yielded embryos of equivalent developmental stage in the spaceflight and ground control treatments. Carbohydrate and protein storage reserves in the embryos, assessed by cytochemical localization, were also comparable. In the spaceflight material, growth and development by embryos rescued from siliques 15 d after pollination lagged behind the ground controls by 12 d; however, in the subsequent generation, no differences between the two treatments were found. The results demonstrate that while no stage of reproductive development in Brassica is absolutely dependent upon gravity, lower embryo quality may result following development in microgravity.

short duration↗

NASA NTRS2015

Biomaterials Out of Thin Air: in Situ, On-Demand Printing of Advanced Biocomposites

Upmass is the single most significant limitation of our current space mission capability. Although biomaterials and biocomposites have mass, strength, flexibility, and self-healing properties that could significantly reduce upmass, their use is limited by the following drawbacks: Expensive, specific production. Many biomaterials can only be produced as part of significant support ecosystem; Inaccessible functional customization. The grain of wood, the porosity of bone, and so on are an integral part of the materials' desired mechanical properties, but are not deterministic when the material is naturally grown; Limited compositions. Most biomaterials (unlike metal, plastic, etc.) cannot be easily combined or modified to produce new materials. This project builds on recent advances in: Synthetic biology. Libraries of standardized genetic parts which can be used for controlled cellular material production, delivery, and binding; 3D printing. Commercial off-the-shelf components which can be used to make of a pico- to nanoliter cell deposition system; Tissue engineering. Proven cell-compatible support hydrogels and scaffolds can be modified to bind the deposited biomaterials of interest. Objectives: Feasibility and benefit analysis. Two mission contexts span the concept's scope (see below); Proof-of-concept demonstration. A simple grid of two proteins, fluorescent for easy detection, to validate the core technology concept; Proposed implementations for follow-on work. Avenues for future work on each core component (host cell, production control, material delivery, material binding, etc.); Complementary studies exploration. A survey of other emerging areas (in situ resource utilization, protein engineering, etc.) with the potential to multiply our technology's impact. Potential Impacts: This application could dramatically expand manufacturing capabilities on Earth and in space: In situ resource utilization. A far greater range of materials and products will be available from the limited palette offered by in situ resource extraction techniques; Reduced equipment and material upmass for off-Earth habitats. Ready- to-use highly specialized construction materials (radiation hardened, compressive/tensile, light or dense) from an extremely low starting mass; Structured biomaterial production. New ready-to-use macro, micro, and molecular manufacturing techniques for traditional biomaterials such as wood, bone and shell; New and novel biocomposite creation. The ability to create completely novel material composites from any base material that cells can be engineered to produce. Suggested Mission Contexts: ISS part manufacturing. A 'minimal working example' making a finished biomaterial part aboard the International Space Station; A long-term Mars habitat. 'Cradle-to-grave' use at a hypothetical Mars habitat, covering everything from tools to construction materials. Alternate Abstract: Imagine being able to print anything from tools and composite building materials to food and human tissues. Imagine being on Mars with the ability to replace any broken part, whether it's a part of your spacesuit, your habitat, or your own body. We propose a technique that would allow just that. By printing 3D arrays of cells engineered to secrete the necessary materials, the abundant in situ resources of atmosphere and regolith become organic, inorganic, or organic-inorganic composite materials. Such materials include novel, biologically derived materials not previously possible to fabricate.

habitats↗

NASA NTRS2015

Biomaterials Out of Thin Air: in Situ, On-demand Printing of Advanced Biocomposites

habitats↗

DOE OSTI2020

The Role of Ligand–Ligand Interactions in Multimodal Ligand Conformational Equilibria and Surface Pattern Formation

Multimodal chromatography uses multiple modes of interaction such as charge, hydrophobic, or hydrogen bonding to separate proteins. Recently, we used molecular dynamics (MD) simulations to show that ligands immobilized on surfaces can interact and associate with neighboring ligands to form hydrophobic and charge patches, which may have important implications for the nature of protein–surface interactions. Here, we study interfacial systems of increasing complexity—from a single immobilized multimodal ligand to high density surfaces—to better understand how ligand behavior is affected by the presence of a surface and the presence of other ligands in the vicinity, and how this behavior scales to larger systems. Furthermore, we find that tethering a ligand to a surface restricts its conformations to a subset of those observed in free solution, yet the ligand maintains flexibility in the plane of the surface and can form contacts with neighboring ligands. We find that although the formation of a contact between two neighboring ligands is slightly unfavorable, three neighboring ligands exhibit a preference for the formation of a fully connected cluster. To explore how these trends in ligand association extend to a larger surface with high density of ligands, we performed coarse-grained Monte Carlo (MC) simulations of a 132-ligand surface using ligand interactions parametrized based on free energies obtained from the three-ligand MD simulations. Despite their simplicity, the coarse-grained simulations qualitatively capture the cluster size distribution of ligands observed in detailed MD simulations. Quantitative differences between the two suggest opportunities for improvements in the coarse-grained energy function for efficient predictions of cluster and pattern formations. Our approach presents a promising route to the engineering of multimodal patterns for future chromatographic resin design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRSDate not supplied

Organic Matter in Itokawa Particles

The first Hayabusa mission returned samples from the near-Earth S-type asteroid 25143 Itokawa to Earth in 2010[1]. Although Itokawa has a lithology related to ordinary chondrites(OCs) that typically have low organic contents, several Itokawa particles were found to contain organic matter (OM)[2-5]. However, there was not an explicit conclusion to the origin of the observed OMin these early studies. We have extended our search for OM into other Itokawa grains. Here, we report extraterrestrial OM (macromolecular carbon and amino acids) observed in six Itokawa particles(including a category1 particle: RA-QD02-0162[#62; also nicknamed “Amazon”],and five category3 carbon-rich particles:RA-QD02-0012[#12], RA-QD02-0078[#78], RB-CV-0029[#29], RB-CV-0080 [#80] and RB-QD04-0052[#52]).All allocated Itokawa samples were initially analysed by spot and point-by-point mapping Raman spectroscopic analysis at the Open University, UK. Amazon was then transferred and mounted into indium on an aluminium stub, which was studied with a NanoSIMS 50L ion microprobe for its H,C,N isotopic compositions. The rest of the samples were mounted in sterile gold foils, and the amino acid contents of their acid hydrolysed hot water extracts were obtained with a liquid chromatography with tandem fluorescence and accurate mass detection at NASA Goddard Space Flight Center, USA. Based on the observation of the Raman parameters(e.g. the peak locations and widths of the defect (D) and graphite (G) bands)[6], a significant variety of carbonaceous materials has been observed in Amazon. The carbonaceous materials include primitive and unaltered OM that shares similarity with the IOM in primitive (CI,CM,CR) carbonaceous chondrites, as well as OM that has been heavily graphitised. The organic structure of the heated material is best represented by nanocrystalline graphite, comparable to that observed for metamorphosed meteorites (e.g., L3–6 Inman, Tieschitz and New Concord,CV3 Allende, and EH4 Indarch),suggesting peak metamorphic temperatures (PMT) of >~600°C. The thermal history recorded in the graphitic OM agrees with PMT estimates for returned Itokawa regolith grains (600–800°C)[7].We have obtained the H,C,N isotopic compositions for the primitive OM in Amazon, which exhibits unambiguously extraterrestrial isotopic signatures (δD = +4868±2288‰; δ13C = −24±5‰; δ15N = +344±20‰), contrasting to the typically negative isotopic values obtained for terrestrial organic matter[8]. The δD and δ13C values of the organic material in Amazon are comparable to OCs, however, the δ15N value is higher than that typically observed for OCs (δ15N = −47 to +36‰), and is similar to that of CRs (δ15N = +153 to +309‰)[9].Our data suggest a genetic link between the primitive organic material observed in Itokawa to CRs and IDPs for they share similar D, 13C and 15N enrichments[10].The high carbon contents of the five category 3 Itokawa particles suggest potentially higher OM abundances, hence we extracted and analysed amino acids in these samples. Although terrestrial contamination was observed primarily as L-protein amino acids, several terrestrially uncommon non-protein amino acids were also observed at low abundances, such as β-aminoisobutyric acid (β-AIB),β-amino-n-butyric acid (β-ABA), and β-alanine. Itokawa amino acid content observed here was dissimilar to thermally altered OCs, but preliminarily analogous to more aqueously altered CR2s.Continued evolution of Itokawa is evident by the in fall of primitive organic material derived from CRs/IDPs, accounting for a complex interplay between the remnant Itokawa silicates with exogenous organics. The results reported here are the first evidence of extraterrestrial OM in asteroid material from a sample-return mission, showcasing a working protocol for analysing samples returned by the Hayabusa2 and OSIRIS-REx missions

Q. H. S. Chan↗

DOE OSTI2024

Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae

Microbial metabolism is a fundamental cellular process that involves many biochemical events and is distinguished by its emergent properties. While the molecular details of individual reactions have been increasingly elucidated, it is not well understood how these reactions are quantitatively orchestrated to produce collective cellular behaviors. Here we developed a coarse-grained, systems, and dynamic mathematical framework, which integrates metabolic reactions with signal transduction and gene regulation to dissect the emergent metabolic traits of Saccharomyces cerevisiae. Our framework mechanistically captures a set of characteristic cellular behaviors, including the Crabtree effect, diauxic shift, diauxic lag time, and differential growth under nutrient-altered environments. It also allows modular expansion for zooming in on specific pathways for detailed metabolic profiles. Furthermore, this study provides a systems mathematical framework for yeast metabolic behaviors, providing insights into yeast physiology and metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Multiple Wheat Genomes Reveal Novel Gli-2 Sublocus Location and Variation of Celiac Disease Epitopes in Duplicated α-Gliadin Genes

The seed protein α-gliadin is a major component of wheat flour and causes gluten-related diseases. However, due to the complexity of this multigene family with a genome structure composed of dozens of copies derived from tandem and genome duplications, little was known about the variation between accessions, and thus little effort has been made to explicitly target α-gliadin for bread wheat breeding. Here, we analyzed genomic variation in α-gliadins across 11 recently published chromosome-scale assemblies of hexaploid wheat, with validation using long-read data. We unexpectedly found that the Gli-B2 locus is not a single contiguous locus but is composed of two subloci, suggesting the possibility of recombination between the two during breeding. We confirmed that the number of immunogenic epitopes among 11 accessions varied. The D subgenome of a European spelt line also contained epitopes, in agreement with its hybridization history. Evolutionary analysis identified amino acid sites under diversifying selection, suggesting their functional importance. The analysis opens the way for improved grain quality and safety through wheat breeding.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Genomic Dissection of Anthracnose ( Colletotrichum sublineolum ) Resistance Response in Sorghum Differential Line SC112-14

Sorghum production is expanding to warmer and more humid regions where its production is being limited by multiple fungal pathogens. Anthracnose, caused by Colletotrichum sublineolum , is one of the major diseases in these regions, where it can cause yield losses of both grain and biomass. In this study, 114 recombinant inbred lines (RILs) derived from resistant sorghum line SC112-14 were evaluated at four distinct geographic locations in the United States for response to anthracnose. A genome scan using a high-density linkage map of 3,838 single nucleotide polymorphisms (SNPs) detected two loci at 5.25 and 1.18 Mb on chromosomes 5 and 6, respectively, that explain up to 59% and 44% of the observed phenotypic variation. A bin-mapping approach using a subset of 31 highly informative RILs was employed to determine the disease response to inoculation with ten anthracnose pathotypes in the greenhouse. A genome scan showed that the 5.25 Mb region on chromosome 5 is associated with a resistance response to nine pathotypes. Five SNP markers were developed and used to fine map the locus on chromosome 5 by evaluating 1,500 segregating F 2:3 progenies. Based on the genotypic and phenotypic analyses of 11 recombinants, the locus was narrowed down to a 470-kb genomic region. Following a genome-wide association study based on 574 accessions previously phenotyped and genotyped, the resistance locus was delimited to a 34-kb genomic interval with five candidate genes. All five candidate genes encode proteins associated with plant immune systems, suggesting they may act in synergy in the resistance response.

Genetics & Heredity↗

DOE OSTI2021

Metabolic Interactions between Brachypodium and Pseudomonas fluorescens under Controlled Iron-Limited Conditions

Plant iron (Fe) nutritional status has a significant impact on rhizosphere microbial communities. While this effect has been attributed to alterations in the composition of root exudates, the underlying mechanisms are not known. Here, we investigated the effect of Fe deficiency on the interactions between the grass Brachypodium distachyon and the common soil bacteria Pseudomonas fluorescens SBW25. Increased phytosiderophore production was the most significant response of Brachypodium root exudation to Fe deficiency. We observed upregulated expression of phytosiderophore biosynthesis genes but lower accumulated exudate concentrations in the presence of Pseudomonas, indicating that the bacteria degrade these phytosiderophores. Pseudomonas did not produce endogenous siderophores under the low Fe conditions. Rather, the bacterial transcriptome revealed upregulation of four genes in response to Fe deficiency that contain motifs associated with cellular uptake of small molecules. Collectively, these results suggest that rhizosphere Pseudomonas fluorescens may take up phytosiderophores produced by grasses in response to Fe deficiency, and we propose target genes that may be involved. Our findings provide insight into the molecular basis for the exchange of C, N, and Fe between plants and bacteria under Fe deficient conditions. These interactions may contribute to differences in the rhizosphere microbial community structure across soil pH regimes.

Boiteau, Rene M.↗

DOE OSTI2023

Genomic dissection of anthracnose resistance response in sorghum [Sorghum bicolor (L.) Moench]

Sorghum [Sorghum bicolor (L.) Moench] is the fifth most important grain crop behind maize, wheat, rice, and barley. Today, it is of interest as a source of fermentable sugars for the production of renewable fuels and chemicals, and as a source of biomass for co-firing. The productivity and profitability of sorghum are limited by several biotic constraints, most notably anthracnose caused by the fungal pathogen Colletotrichum sublineolum. The most cost-effective and environmentally benign strategy to control anthracnose is through the incorporation of resistance genes. Over the last three years, our research efforts have been directed to identify new sources of resistance in temperate adapted and tropical germplasm, and to delimited genomic regions associated with the observe anthracnose resistant response. Three biparental mapping populations derived from the resistant lines SC112-14, QL3 and IS18760 were evaluated for anthracnose resistance response in Texas, Georgia, Florida and Puerto Rico. In parallel, three high density recombination maps were constructed and used to identify resistant loci. Anthracnose resistant response in line SC112-14 is controlled by a major locus on chromosome 5. Segregation analysis of 1,500 progenies delimited the resistance locus on chromosome 5 to a 23-kb region harboring three candidate genes, including Sobic.005G17230 identified by GWAS of the sorghum association panel (SAP). The latter gene belongs to a family of genes encoding F-box proteins indicating that this resistance response involved in signaling cascades and transcriptional reprograming, rather than recognition of pathotype-associated molecular patterns. In contrast, anthracnose resistant response in lines QL3 and IS18760 is controlled by multiple small-effect genes. Greenhouse evaluation of a representative subset of the three mapping populations against nine pathotypes found that lines susceptible in the field could be resistant to a single pathotype in the greenhouse. Thus, the activation of a resistance response system by a single pathotype could not provide a broader resistance response against multiple pathotypes. The screening of 1,801 sweet sorghum accessions from the National Plant Germplasm System identified 654 accessions with Brix value larger than 10, which in turn was used to select a subset of 233 accessions for evaluation of anthracnose resistant response. Even though most of the accessions were not completely infected by anthracnose, 28 accessions were completely resistant against pathotypes from Texas, Georgia, Florida and Puerto Rico. Genotyping-by-sequencing analysis of this subset identified 157,843 single nucleotide polymorphisms. Population structure analysis of the subset based on a subset of 2,345 unlinked SNPs found that the genetic diversity could be divided into four populations. The genetic relatedness among accessions within populations suggests most of the resistant germplasm may contain few different resistance sources. These resistance sources present in sweet sorghum germplasm could expedite the development of new resistant sweet sorghum cultivars and hybrids by avoiding time-consuming introgression breeding approaches with non-sweet sorghums serving as donor of the resistance alleles.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

HLA-Clus: HLA class I clustering based on 3D structure

In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository (https://github.com/yshen25/HLA-Clus).

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Impacts of corn intercropping with soybean, peanut and millet through different planting patterns on population dynamics and community diversity of insects under fertilizer reduction

Corn is one of the key grain crops in China and the excessive use of chemical fertilizers and pesticides seriously damages the ecological environment in fields. To explore a more scientific and reasonable way to plant corn and simultaneously reduce the overuse of chemical fertilizers and pesticides, the impact of corn intercropping with soybean, peanut, and millet, respectively, through five planting patterns, including three intercropping patterns (2 corn rows to 2, 3 and 4 rows of soybean/peanut or 2, 4 and 6 millet rows, respectively) and two monoculture patterns of corn and soybean, peanut or millet under normal (600 kg/ha) and reduced (375 kg/ha) levels of NPK (N:P 2 O 5 :K 2 O = 15:15:15) fertilization on the population abundance and community diversity of insects, leaf nutrients, and induced plant hormones jasmonic acid (JA) and salicylic acid (SA) was studied in 2018 and 2019. The results showed that the insect community indexes of the species number ( S ), the diversity index ( H ), and the uniformity index ( E ) generally increased under intercropping and were significantly higher than those under corn monoculture. The prevalence of Asian corn borer ( Ostrinia furnacalis ) on the intercropping corn plants decreased by based on the average of seven surveys per year for each treatment 2.9 to 17 heads per 30 plants compared with that on the monoculture corn plants. The number of natural enemy insect species on corn plants under intercropping was significantly higher than that under corn monoculture. That is, intercropping may decrease the population of Asian corn borers by increasing S , H , E , and natural enemy insect species (NEI). Moreover, intercropping type and fertilizer level significantly affected corn leaf nutrient contents. Compared with the normal fertilizer level, fertilizer reduction significantly reduced the foliar contents of amino acids, soluble protein, and soluble sugar in corn plants. In addition, corn–soybean and corn–peanut intercropping significantly increased the three nutrient contents in corn leaves compared with corn monoculture. In terms of corn nutrients, intercropping could compensate for the effects of fertilizer reduction. The foliar content of JA in corn–soybean intercropping was significantly higher than in corn monoculture. Under corn–soybean and corn–peanut intercropping, SA was significantly lower than under corn monoculture. Overall, intercropping, not fertilizer reduction, can significantly increase insect community diversity while reducing the population abundances of the key insect pest species on corn plants. Intercropping reduced the SA content, increased amino acids and thus reduced the susceptibility of corn to the pest insects.

Li, Likun↗

DOE OSTI2024

How Does Escherichia coli Allocate Proteome?

Microorganisms are shown to actively partition their intracellular resources, such as pro- teins, for growth optimization. Recent experiments have begun to reveal molecular com- ponents unpinning the partition; however, it remains unclear quantitatively how individual parts orchestrate to yield precise resource allocation that is both robust and dynamic. Here we developed a coarse-grained mathematical framework that centers on guanosine pentaphosphate (ppGpp)-mediated regulation, and used it to systematically uncover the design principles of proteome allocation in Escherichia coli. Our results showed that cellular ability of resource partition lies in an ultrasensitive, negative feedback control- ling topology with the ultrasensitivity arising from zero-order amino acid kinetics and the negative feedback from ppGpp-controlled ribosome synthesis. In addition, together with the time-scale separation between slow ribosome kinetics and fast turnovers of ppGpp and amino acids, the network topology confers the organism an optimization mechanism which mimics sliding mode control, a nonlinear optimization strategy that is widely used in man-made systems. We further showed that such a controlling mechanism is robust against parameter variations and molecular fluctuations, and is also efficient for biomass production over time. Furthermore, this work elucidates the fundamental controlling mechanism of E. coli proteome allocation, thereby providing insights into quantitative microbial physiology as well as the design of synthetic gene networks.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Functional Design of Peptide Materials Based on Supramolecular Cohesion

Peptide materials offer a broad platform to design biomimetic soft matter, and filamentous networks that emulate those in extracellular matrices and the cytoskeleton are among the important targets. Given the vast sequence space, a combination of computational approaches and readily accessible experimental techniques is required to design peptide materials efficiently. Here, we report here on a strategy that utilizes this combination to predict supramolecular cohesion within filaments of peptide amphiphiles, a property recently linked to supramolecular dynamics and consequently bioactivity. Using established coarse-grained simulations on 10,000 randomly generated peptide sequences, we identified 3500 likely to self-assemble in water into nanoscale filaments. Atomistic simulations of small clusters were used to further analyze this subset of sequences and identify mathematical descriptors that are predictive of intermolecular cohesion, which was the main purpose of this work. We arbitrarily selected a small cohort of these sequences for chemical synthesis and verified their fiber morphology. With further characterization, we were able to link the latent heat associated with fiber to micelle transitions, an indicator of cohesion and potential supramolecular dynamicity within the filaments, to calculated hydrogen bond densities in the simulation clusters. Based on validation from in situ synchrotron X-ray scattering and differential scanning calorimetry, we conclude that the phase transitions can be easily observed by very simple polarized light microscopy experiments. We are encouraged by the methodology explored here as a relatively low-cost and fast way to design potential functions of peptide materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗