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Familial Associations of Prevalence and Cause-Specific Mortality for Thoracic Aortic Disease and Bicuspid Aortic Valve in a Large-Population Database

Thoracic aortic disease and bicuspid aortic valve (BAV) likely have a heritable component, but large population-based studies are lacking. This study characterizes familial associations of thoracic aortic disease and BAV, as well as cardiovascular and aortic-specific mortality, among relatives of these individuals in a large-population database. In this observational case-control study of the Utah Population Database, we identified probands with a diagnosis of BAV, thoracic aortic aneurysm, or thoracic aortic dissection. Age- and sex-matched controls (10:1 ratio) were identified for each proband. First-degree relatives, second-degree relatives, and first cousins of probands and controls were identified through linked genealogical information. Cox proportional hazard models were used to quantify the familial associations for each diagnosis. We used a competing-risk model to determine the risk of cardiovascular-specific and aortic-specific mortality for relatives of probands. The study population included 3,812,588 unique individuals. Familial hazard risk of a concordant diagnosis was elevated in the following populations compared with controls: first-degree relatives of patients with BAV (hazard ratio [HR], 6.88 [95% CI, 5.62–8.43]); first-degree relatives of patients with thoracic aortic aneurysm (HR, 5.09 [95% CI, 3.80–6.82]); and first-degree relatives of patients with thoracic aortic dissection (HR, 4.15 [95% CI, 3.25–5.31]). In addition, the risk of aortic dissection was higher in first-degree relatives of patients with BAV (HR, 3.63 [95% CI, 2.68–4.91]) and in first-degree relatives of patients with thoracic aneurysm (HR, 3.89 [95% CI, 2.93–5.18]) compared with controls. Dissection risk was highest in first-degree relatives of patients who carried a diagnosis of both BAV and aneurysm (HR, 6.13 [95% CI, 2.82–13.33]). First-degree relatives of patients with BAV, thoracic aneurysm, or aortic dissection had a higher risk of aortic-specific mortality (HR, 2.83 [95% CI, 2.44–3.29]) compared with controls. Our results indicate that BAV and thoracic aortic disease carry a significant familial association for concordant disease and aortic dissection. The pattern of familiality is consistent with a genetic cause of disease. Furthermore, we observed higher risk of aortic-specific mortality in relatives of individuals with these diagnoses. In conclusion, this study provides supportive evidence for screening in relatives of patients with BAV, thoracic aneurysm, or dissection.

60 APPLIED LIFE SCIENCES↗

Understanding the Unique Reactivity of Cu for Electrochemical CO 2 Reduction with a 3-Site Model

Cu-based catalysts for the electrochemical reduction of CO 2 and CO exhibit a perplexingly unique reactivity toward multicarbon based products compared to other studied electrocatalysts. Here, in this study, we use insights gained from a recent phenomenological 3-site microkinetic model and grand-canonical density functional theory calculations to clarify the importance of an underemphasized aspect critical to Cu’s unique reactivity: a population of so-called “reservoir” sites. Using model Cu surface motifs, we discuss how these types can be represented by undercoordinated structural defects like step edges and grain boundaries which form a network of highly anisotropic migration channels. These pathways are found to be amenable for feeding *CO over time to reactive sites like Cu adatoms more active toward C–C coupling. These results highlight an often overlooked aspect of catalyst optimization: reservoir site engineering, which exploits surface mobility and presents an equally important avenue for electrocatalyst engineering oversimply maximizing active site densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

IPD3, a master regulator of arbuscular mycorrhizal symbiosis, affects genes for immunity and metabolism of non-host Arabidopsis when restored long after its evolutionary loss

Abstract Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana . To explore if elements of this apparently beneficial trait are still present and could be reactivated we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3 , a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis , and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4 . Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state, which partially mimics AMF exposure in non-inoculated plants. Our results indicate that molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

59 BASIC BIOLOGICAL SCIENCES↗

Real-Time Time-Dependent Density Functional Theory for Simulating Nonequilibrium Electron Dynamics

The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. Here, in this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.

Hamiltonians↗

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗

Nanotubes Growth by Self-Assembly of DNA Strands at Room Temperature

Artificial biomolecular nanotubes are a promising approach to building materials mimicking the capacity of the cellular cytoskeleton to grow and self-organize dynamically. Nucleic acid nanotechnology has demonstrated a variety of self-assembling nanotubes with programmable, robust features and morphological similarities to actual cytoskeleton components. However, their production typically requires thermal annealing, which not only poses a general constraint on their potential applications but is also incompatible with physiological conditions. Here, we demonstrate that DNA nanotubes can self-assemble from a simple mixture of five short DNA strands at constant room temperature, growing for extended periods of time in bulk conditions as well as under confinement. Assembly is achieved using a monovalent salt buffer, which ensures a faithful nanoscale arrangement and avoids nanotube aggregation. We observe the formation of individual nanotubes up to 20 days with a diameter of 22 ± 4 nm and length of several tens of micrometers. We finally encapsulate the strands in microsized compartments, such as water-in-oil microdroplets and giant unilamellar vesicles serving as simple cell models. Notably, nanotubes not only isothermally self-assemble directly inside the microcompartments but also self-organize into dynamic higher-order structures resembling rings and dynamic networks. Our study provides an advantageous method for in situ assembly of programmable biomolecular scaffolds and materials using synthetic DNA strands without requirements of thermal treatment.

Chemistry↗

Evaluating Material Design Principles for Calcium-Ion Mobility in Intercalation Cathodes

Multivalent-ion batteries offer an alternative to Li-based technologies, with the potential for greater sustainability, improved safety, and higher energy density, primarily due to their rechargeable system featuring a passivating metal anode. Although a system based on the Ca 2+ /Ca couple is particularly attractive given the low electrochemical plating potential of Ca 2+ , the remaining challenge for a viable rechargeable Ca battery is to identify Ca cathodes with fast ion transport. In this work, a high-throughput computational pipeline is adapted to (1) discover novel Ca cathodes in a largely unexplored space of empty intercalation hosts and (2) develop material design rules for Ca-ion mobility. One candidate from the screening, W 2 O 3 (PO 4 ) 2 , is confirmed to have a low Nudged Elastic Band (NEB) barrier of 168 meV within a one-dimensional (1D) ion percolation topology. This candidate is subsequently synthesized and electrochemically tested, achieving reversible Ca cycling with a capacity of 25 mA h/g. To further accelerate the screening for promising Ca intercalation electrodes, machine learning (ML) Random Forest (RF) and Extreme Gradient Boosting (XGB) classification models are created with local environment descriptors based on a large, structurally and chemically diverse dataset of minimum energy pathways, spanning over 5,000 density functional theory (DFT) site energy calculations. Accuracies of 92% are achieved, material design metrics are quantified, ML force-fields are leveraged in an accelerated iteration of the screening, and a total of 27 novel Ca cathode materials are highlighted for further investigation.

25 ENERGY STORAGE↗

Analysis of ionizing radiation induced DNA damage response in human adult stem cells and differentiated neurons

Findings of neurodegenerative features associated with human radiosensitive syndromes such as Ataxia telangiectasia suggest that DNA repair efficiency is crucial for maintaining the functional integrity of central nervous system. To gain a better understanding of ionizing radiation (IR) induced DNA damage response in undifferentiated and differentiated neural cell types and to evaluate the role of ATM in DNA double strand break (DSB) repair, an in vitro human neural cell differentiation model system was utilized in this study. As compared to adult stem cells, differentiated neurons displayed an attenuated DSB repair response (as judged by the persistence of 53BP1 foci) after IR exposure and the attenuation was even more pronounced in stem cells and neurons after suppression of ATM (Ataxia Telangiectasia Mutated) gene product suggesting the importance of ATM for an optimal DSB repair efficiency in human neural cell types. In corroboration with an attenuated DNA damage response, a sharp decline in the expression levels of several DSB repair genes was observed in neurons. Furthermore, our results suggest that cellular differentiation modulates the expression of several genes thereby compromising the DSB repair fidelity in post mitotic neurons. Further studies are required to verify whether or not ATM mediated exacerbation of DNA repair deficiency in differentiated neurons leads to neurodegeneration.

53 binding protein 1↗

Genetic and enzymatic characterization of Amy13E from Cellvibrio japonicus reclassifies it as a cyclodextrinase also capable of α-diglucoside degradation

ABSTRACT Cyclodextrinases are carbohydrate-active enzymes involved in the linearization of circular amylose oligosaccharides. Primarily thought to function as part of starch metabolism, there have been previous reports of bacterial cyclodextrinases also having additional enzymatic activities on linear malto-oligosaccharides. This substrate class also includes environmentally rare α-diglucosides such as kojibiose (α−1,2), nigerose (α−1,3), and isomaltose (α−1,6), all of which have valuable properties as prebiotics or low-glycemic index sweeteners. Previous genome sequencing of threeCellvibrio japonicusstrains adapted to utilize these α-diglucosides identified multiple, but uncharacterized, mutations in each strain. One of the mutations identified was in theamy13Egene, which was annotated to encode a neopullulanase. In this report, we functionally characterized this gene and determined that it in fact encodes a cyclodextrinase with additional activities on α-diglucosides. Deletion analysis ofamy13Efound that this gene was essential for kojibiose and isomaltose metabolism inC. japonicus. Interestingly, a Δamy13Emutant was not deficient for cyclodextrin or pullulan utilization inC. japonicus; however, heterologous expression of the gene inE. coliwas sufficient for cyclodextrin-dependent growth. Biochemical analyses found thatCjAmy13E cleaved multiple substrates but preferred cyclodextrins and maltose, but had no activity on pullulan. Our characterization of theCjAmy13E cyclodextrinase is useful for refining functional enzyme predictions in related bacteria and for engineering enzymes for biotechnology or biomedical applications. IMPORTANCE Understanding the bacterial metabolism of cyclodextrins and rare α-diglucosides is increasingly important, as these sugars are becoming prevalent in the foods, supplements, and medicines humans consume that subsequently feed the human gut microbiome. Our analysis of a cyclomaltodextrinase with an expanded substrate range is significant because it broadens the potential applications of the GH13 family of carbohydrate active enzymes (CAZymes) in biotechnology and biomedicine. Specifically, this study provides a workflow for the discovery and characterization of novel activities in bacteria that possess a high number of CAZymes that otherwise would be missed due to complications with functional redundancy. Furthermore, this study provides a model from which predictions can be made why certain bacteria in crowded niches are able to robustly utilize rare carbon sources, possibly to gain a competitive growth advantage.

Biotechnology & Applied Microbiology↗

Multiplexed fitness profiling by RB-TnSeq elucidates pathways for lignin-related aromatic catabolism in Sphingobium sp. SYK-6

Bioconversion of lignin-related aromatic compounds relies on robust catabolic pathways in microbes. Sphingobium sp. SYK-6 (SYK-6) is a well-characterized aromatic catabolic organism that has served as a model for microbial lignin conversion, and its utility as a biocatalyst could potentially be further improved by genome-wide metabolic analyses. To this end, we generate a randomly barcoded transposon insertion mutant (RB-TnSeq) library to study gene function in SYK-6. The library is enriched under dozens of enrichment conditions to quantify gene fitness. Several known aromatic catabolic pathways are confirmed, and RB-TnSeq affords additional detail on the genome-wide effects of each enrichment condition. Selected genes are further examined in SYK-6 or Pseudomonas putida KT2440, leading to the identification of new gene functions. The findings from this study further elucidate the metabolism of SYK-6, while also providing targets for future metabolic engineering in this organism or other hosts for the biological valorization of lignin.

09 BIOMASS FUELS↗

PTM‐Psi : A python package to facilitate the computational investigation of p ost‐ t ranslational m odification on p rotein s tructures and their i mpacts on dynamics and functions

Abstract Post‐translational modification (PTM) of a protein occurs after it has been synthesized from its genetic template, and involves chemical modifications of the protein's specific amino acid residues. Despite of the central role played by PTM in regulating molecular interactions, particularly those driven by reversible redox reactions, it remains challenging to interpret PTMs in terms of protein dynamics and function because there are numerous combinatorially enormous means for modifying amino acids in response to changes in the protein environment. In this study, we provide a workflow that allows users to interpret how perturbations caused by PTMs affect a protein's properties, dynamics, and interactions with its binding partners based on inferred or experimentally determined protein structure. This Python‐based workflow, called PTM‐Psi , integrates several established open‐source software packages, thereby enabling the user to infer protein structure from sequence, develop force fields for non‐standard amino acids using quantum mechanics, calculate free energy perturbations through molecular dynamics simulations, and score the bound complexes via docking algorithms. Using the S ‐nitrosylation of several cysteines on the GAP2 protein as an example, we demonstrated the utility of PTM‐Psi for interpreting sequence–structure–function relationships derived from thiol redox proteomics data. We demonstrate that the S ‐nitrosylated cysteine that is exposed to the solvent indirectly affects the catalytic reaction of another buried cysteine over a distance in GAP2 protein through the movement of the two ligands. Our workflow tracks the PTMs on residues that are responsive to changes in the redox environment and lays the foundation for the automation of molecular and systems biology modeling.

59 BASIC BIOLOGICAL SCIENCES↗

The catalytic domains of Streptococcus mutans glucosyltransferases: a structural analysis

Streptococcus mutans, found in the human oral cavity, is a significant contributor to the pathogenesis of dental caries. This bacterium expresses three genetically distinct types of glucosyltransferases named GtfB (GTF-I), GtfC (GTF-SI) and GtfD (GTF-S) that play critical roles in the development of dental plaque. The catalytic domains of GtfB, GtfC and GtfD contain conserved active-site residues for the overall enzymatic activity that relate to hydrolytic glycosidic cleavage of sucrose to glucose and fructose, release of fructose and generation of a glycosyl-enzyme intermediate in the reducing end. In a subsequent transglycosylation step, the glucosyl moiety is transferred to the nonreducing end of an acceptor to form a growing glucan polymer chain made up of glucose molecules. It has been proposed that both sucrose breakdown and glucan synthesis occur in the same active site of the catalytic domain, although the active site does not appear to be large enough to accommodate both functions. These three enzymes belong to glycoside hydrolase family 70 (GH70), which shows homology to glycoside hydrolase family 13 (GH13). GtfC synthesizes both soluble and insoluble glucans (α-1,3 and α-1,6 glycosidic linkages), while GtfB and GtfD synthesize only insoluble or soluble glucans, respectively. Here, crystal structures of the catalytic domains of GtfB and GtfD are reported. These structures are compared with previously determined structures of the catalytic domain of GtfC. With this work, apo structures and inhibitor-complex structures with acarbose are now available for the catalytic domains of GtfC and GtfB. The structure of GtfC with maltose allows further identification and comparison of active-site residues. A model of sucrose binding to GtfB is also included. The new structure of the catalytic domain of GtfD affords a structural comparison of the three S. mutans glycosyltransferases. Unfortunately, the catalytic domain of GtfD is not complete since crystallization resulted in the structure of a truncated protein lacking approximately 200 N-terminal residues of domain IV.

59 BASIC BIOLOGICAL SCIENCES↗

A Framework for Optimal Placement of Rooftop Photovoltaic: Maximizing Solar Production and Operational Cost Savings in Residential Communities

Optimizing the placement of photovoltaic (PV) panels on residential buildings has the potential to significantly increase energy efficiency benefits to both homeowners and communities. Strategic PV placement can lower electricity costs by reducing the electricity fed from the grid during on-peak hours, while maintaining PV panel efficiency in terms of the amount of solar radiation received. In this article, we present a framework that identifies the ideal location of PV panels on residential rooftops. Our framework combines energy and environmental simulation, parametric modeling, and optimization to inform PV placement as it relates to and affects the entire community (in terms of both energy use and financial cost), as well as individual buildings. Ensuring that our framework accounts for shading from nearby buildings, different utility rate structures, and different buildings’ energy demand profiles means that existing communities and future housing developments can be optimized for energy savings and PV efficiency. The framework comprises two workflows, each contributing to optimal PV placement with a unique target: (a) maximizing PV panel efficiency (i.e., solar generation) and (b) minimizing operational energy cost considering utility rate structures for operational energy. We apply our framework to a residential community in Fort Collins, Colorado, to demonstrate the optimal PV placement, considering the two workflow targets. Here, we present our results and illustrate the effect of PV location and orientation on solar energy production efficiency and operational energy cost.

14 SOLAR ENERGY↗

Binding profiles for 961 Drosophila and C. elegans transcription factors reveal tissue-specific regulatory relationships

A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here, we present the culmination of the efforts of the modENCODE (model organism Encyclopedia of DNA Elements) and modERN (model organism Encyclopedia of Regulatory Networks) consortia to systematically assay TF binding events in vivo in two major model organisms,Drosophila melanogaster(fly) andCaenorhabditis elegans(worm). These data sets comprise 605 TFs identifying 3.6 M sites in the fly and 356 TFs identifying 0.9 M sites in the worm, and represent the majority of the regulatory space in each genome. We demonstrate that TFs associate with chromatin in clusters termed “metapeaks,” that larger metapeaks have characteristics of high-occupancy target (HOT) regions, and that the importance of consensus sequence motifs bound by TFs depends on metapeak size and complexity. Combining ChIP-seq data with single-cell RNA-seq data in a machine-learning model identifies TFs with a prominent role in promoting target gene expression in specific cell types, even differentiating between parent–daughter cells during embryogenesis. These data are a rich resource for the community that should fuel and guide future investigations into TF function. To facilitate data accessibility and utility, all strains expressing green fluorescent protein (GFP)-tagged TFs are available at the stock centers for each organism. The chromatin immunoprecipitation sequencing data are available through the ENCODE Data Coordinating Center, GEO, and through a direct interface that provides rapid access to processed data sets and summary analyses, as well as widgets to probe the cell-type-specific TF–target relationships.

Biochemistry & Molecular Biology↗

Separate, separated, and together: the transcriptional program of the Clostridium acetobutylicum-Clostridium ljungdahlii syntrophy leading to interspecies cell fusion

ABSTRACT Syntrophic cocultures (hitherto assumed to be commensalistic) of Clostridium acetobutylicum and Clostridium ljungdahlii , whereby CO 2 and H 2 produced by the former feed the latter, result in interspecies cell fusion involving large-scale exchange of protein, RNA, and DNA between the two organisms. Although mammalian cell fusion is mechanistically dissected, the mechanism for such microbial-cell fusions is unknown. To start exploring this mechanism, we used RNA sequencing to identify genes differentially expressed in this coculture using two types of comparisons. One type compared coculture to the two monocultures, capturing the combined impact of interactions through soluble signals in the medium and through direct cell-to-cell interactions. The second type compared membrane-separated versus -unseparated cocultures, isolating the impact of interspecies physical contact. While we could not firmly identify specific genes that might drive cell fusion, consistent with our hypothesized model for this interspecies microbial cell fusion, we observed differential regulation of genes involved in C. ljungdahlii’s autotrophic Wood-Ljungdahl pathway metabolism and genes of the motility machinery. Unexpectedly, we also identified differential regulation of biosynthetic genes of several amino acids, and notably of arginine and histidine. We verified that they are produced by C. acetobutylicum and are metabolized by C. ljungdahlii to its growth advantage. These and other findings, and notably upregulation of C. acetobutylicum ribosomal-protein genes, paint a more complex syntrophic picture and suggest a mutualistic relationship, whereby beyond CO 2 and H 2 , C. acetobutylicum feeds C. ljungdahlii with growth-boosting amino acids, while benefiting from the H 2 utilization by C. ljungdahlii . IMPORTANCE The construction and study of synthetic microbial cocultures is a growing research area due to the untapped potential of defined multi-species industrial bioprocesses and the utility of defined cocultures for generating insight into complex, undefined, natural microbial consortia. Our previous work showed that coculturing C. acetobutylicum and C. ljungdahlii leads to a unique metabolic phenotype (production of isopropanol) and heterologous cell fusion events. Here, we used RNAseq to explore genes involved in and impacted by these fusions. First, we compared gene expression in coculture to each monoculture. Second, we utilized a transwell system to compare gene expression in mixed cocultures to cocultures with both species physically separated by a permeable membrane, isolating the impact of interspecies “touching” on the transcriptome. This study deepens our mechanistic understanding of the C. acetobutylicum-C. ljungdahlii coculture phenotype, laying the groundwork for reverse genetic studies of heterologous cell fusion in Clostridium cocultures.

Willis, Noah B. (ORCID:0009000689365955)↗

Creating multifunctional synthetic lichen platforms for sustainable biosynthesis of biofuel precursors

In this project, we were creating a sustainable platform for biofuel production, utilizing carbon-fixing autotrophs to supply oxygen and organic substrates to heterotrophic partners, which in turn produce carbon dioxide to feed the autotrophs. This symbiotic lichen community could lower the input cost, optimize metabolic exchanges and improve the generation of biofuel precursors through multi-omics driven genetic engineering. The cyanobacteria Synechococcus elongatus (S. elongatus) was used as the primary autotroph to provide oxygen and organic substrates, especially sucrose, to a co-culture system. The strain with overexpression of sucrose transporter cscB demonstrated a significant increase in sucrose production under salt stress as what we expected. We also implemented 13C metabolic flux analysis on the sucrose secreting strain S. elongatus cscB-NaCl. Next, transporters proteins like glutamate exporter mscCG from Corynebacterium glutamicum was overexpressed in S. elongatus to improve metabolite exchange. We provided sucrose and glutamate to filamentous fungi to enable their growth and production of biochemicals using substrates from the cyanobacterium. Two fungi ( Aspergillus nidulans and Aspergillus niger ) and two yeast strains ( Rhodotorula toruloides and Lipomyces starkeyi ) served as heterotrophs in this system. They were co-cultured with S.elongatus under different pH condition, and growth on different carbon source to understand the symbiotic system and optimize the parameters for production. The two fungi strained grew much better at pH 7, 8 and 9 with Yeast Nitrogen Base (YNB ) supplementation. Two yeast strains grew well on pH 7 and 8 with YNB supplementation. All four species achieved the highest biomass level when utilizing sucrose as the main carbon sources, which demonstrates a great pairing with S.elongatus . In addition to investigate the metabolite exchange and growth condition of the co-culture system, we incorporated an Aspergillus strain expressing three genes (PAND, BAPAT and HPDH). Expression of these three genes enabled production of 3-hydroxypropionic acid (3HP) with a titer of 3-6 g/L regardless of pH and other nutrient conditions. Moreover, we developed a computational model with different heterotrophic fungi symbiosing with S.elongatus to evaluate the exchange of hundreds of metabolites. The accuracy and sensitivity had been optimized by high-throughput phenotyping assays. This project demonstrated ways to enhance a synthetic lichen platform’s efficiency and scalability to create a robust system for sustainable bioproduct synthesis. The project has enabled us to explore the technological and commercial potential of sustainable lichen co-culture. The project has also trained the next generation of scientists to address sustainability, carbon fixation, and design solutions to contemporary global challenges. The lichen platform represented a novel approach to sustainably producing bioproducts with a reduced carbon footprint and lower costs.

09 BIOMASS FUELS↗

Streamlined spatial and environmental expression signatures characterize the minimalist duckweed Wolffia australiana

Single-cell genomics permits a new resolution in the examination of molecular and cellular dynamics, allowing global, parallel assessments of cell types and cellular behaviors through development and in response to environmental circumstances, such as interaction with water and the light–dark cycle of the Earth. Here, we leverage the smallest, and possibly most structurally reduced, plant, the semiaquaticWolffia australiana, to understand dynamics of cell expression in these contexts at the whole-plant level. We examined single-cell-resolution RNA-sequencing data and foundWolffiacells divide into four principal clusters representing the above- and below-water-situated parenchyma and epidermis. Although these tissues share transcriptomic similarity with model plants, they display distinct adaptations thatWolffiahas made for the aquatic environment. Within this broad classification, discrete subspecializations are evident, with select cells showing unique transcriptomic signatures associated with developmental maturation and specialized physiologies. Assessing this simplified biological system temporally at two key time-of-day (TOD) transitions, we identify additional TOD-responsive genes previously overlooked in whole-plant transcriptomic approaches and demonstrate that the core circadian clock machinery and its downstream responses can vary in cell-specific manners, even in this simplified system. Distinctions between cell types and their responses to submergence and/or TOD are driven by expression changes of unexpectedly few genes, characterizingWolffiaas a highly streamlined organism with the majority of genes dedicated to fundamental cellular processes.Wolffiaprovides a unique opportunity to apply reductionist biology to elucidate signaling functions at the organismal level, for which this work provides a powerful resource.

Biochemistry & Molecular Biology↗