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At least 289 records · Page 16

From chromatin to crop: epigenetic innovations in bioenergy systems

Energy crops encompass a diverse array of plant species cultivated primarily as a source of biomass for energy generation and biofuel production. As such, they play a pivotal role in the transition to sustainable energy systems. However, their productivity is often limited by environmental stresses, nutrient availability, and the need for optimized yield. While traditional breeding and genetic engineering have driven improvements, challenges such as narrow genetic diversity, long development cycles, trait instability, and unexpected gene interactions remain. Epigenetics offers a largely untapped opportunity to overcome these constraints by regulating gene expression through mechanisms that are dynamic, finely tuned, and responsive to environmental and developmental cues. Epigenetic modifications including DNA methylation, histone post-translational changes, and small non-coding RNAs influence nearly all aspects of plant development and physiology, including traits central to bioenergy crops. While these mechanisms are well characterized in model species such as Arabidopsis thaliana, they remain underexplored in many purpose-grown energy crops. This review summarizes the current state of knowledge of epigenetic regulation in bioenergy species, explores how these mechanisms can be leveraged to enhance crop resilience and productivity, and identifies gaps in our understanding. By characterizing epigenetic mechanisms and harnessing epigenetic variation, we can expand the toolkit for developing resilient, high-yielding bioenergy crops to meet future environmental and energy demands.

09 BIOMASS FUELS↗

Novel Microbial Routes to Synthesize Industrially Significant Precursor Compounds

Ethylene is the most widely employed organic precursor compound in industry. The potential to impact ethylene formation via recently discovered microbial processes is tenable using plentiful CO2 feedstocks. The overall long-term objective of this project was to develop an industrially compatible microbial process to synthesize ethylene in high yields. The key objective of this project was to fully define and initially characterized a recently discovered and genetically regulated anaerobic pathway to produce high levels of ethylene called the Dihydroxyacetone Phosphate - Ethylene Pathway in phototrophic bacteria. This was addressed through the following specific aims: 1. Fully probe the catalytic potential of all enzymes of the DHAP ethylene pathway and determine the regulatory mechanism of DHAP-ethylene pathway gene expression. 2. Discover effective and active ethylene enzymes encoded in cultured and uncultured organisms from anoxic environments. 3.Model the thermodynamics and kinetics of ethylene synthetic pathways to guide engineering efforts in integrating best performing DHAP-ethylene pathway enzymes into model bacteria chassis for enhance ethylene yields. Through this project we discovered the initially missing genetic and enzyme component of the DHAP-ethylene pathway that directly synthesized ethylene and other important industrial compounds like methane and ethane from specific substrates. We uncovered and partially characterized a nitrogenase-like reductase that functions in DHAP-ethylene pathway specifically and in methionine synthesis in general. This nitrogenase-like system is called the Methylthio-Alkane Reductase (MAR) for its ability to cleave volatile organic sulfur compounds into methanethiol (CH3-SH) for methionine synthesis and a hydrocarbon byproduct. Key to the DHAP-ethylene pathway, MAR is the essential enzyme that cleaves 2-methylthioethanol (CH3-S-CH2-CH2-OH) into ethylene. Coordinately, we uncovered that the MAR genes and genes associated with conversion of methanethiol (CH3-SH) to methionine are under genetic control of a LysR Type Transcriptional Regulator called SalR, whose activity is dependent upon the amount of sulfate available to the cell. When sulfate as the preferred sulfur source for cell growth drops below 200 micromolar, SalR become active for expressing the MAR and methionine biosynthesis genes to enable the cell to grow from volatile organic sulfur compounds and make ethylene. Metabolic thermos-kinetic modeling revealed that these MAR reactions for ethylene and other hydrocarbon production are highly thermodynamically favorable and are one of the largest driving forces for ethylene production by the DHAP-ethylene pathway for high ethylene yields. Modeling also indicated that a key aldolase and to a lesser extent an isomerase of the DHAP-ethylene pathway for production of the ethylene precursor, 2-methylthioethanol, also would increase ethylene yields. Through metagenomic mining and gene synthesis by the JGI DNA synthesis program, over 500 aldolase and isomerase homologs were synthesized and screened. From this, variants were uncovered with substantially higher activity that increased ethylene yields 5-fold via the aldolase reaction and 1.5-fold via the isomerase reaction. Each of these elements that increase ethylene production were integrated together via plasmid under appropriate gene promoter elements in the phototrophic bacterium, Rhodospirillum rubrum, resulting in at least 3 orders of magnitude increase in ethylene yield from carbon dioxide feedstock.

10 SYNTHETIC FUELS↗

Modeling distributed energy resource aggregations in security constrained unit commitment and economic dispatch

The Federal Energy Regulatory Commission (FERC) recently issued Order 2222, which requires all wholesale electricity markets in the US to allow distributed energy resources (DERs) to participate in the market as aggregated resources. These DER aggregations may be composed of many individual resources that are offered and dispatched by the market as a single entity. We present here a model of a distributed energy resource aggregator (DERA) that is scheduled by a market operator’s security constrained unit commitment (SCUC) and security constrained economic dispatch (SCED). The DERA model includes constraints for battery energy storage systems (BESSs), demand response resources (DRRs), and a simple distributed energy resource (DER). This paper describes a model for each resource type and presents two methods for the DERA to generate market offer curves: a profit-maximizing optimization to compute cost curves and a direct cost algorithm to determine dispatch costs for each resource and combine into cost curves. Once all participating DERAs are scheduled in SCUC/SCED, the model is then modified to dispatch individual DERs to maximize profit or minimize schedule deviation of the DERAs. A simulation of a representative day illustrates the DERA offers, the scheduled generation, and the DERA dispatch. Findings show the potential for unavoidable schedule deviations due to internal DER constraints and due to economic incentives to deviate from the SCUC/SCED schedules. This highlights the importance of DERA offer construction on market efficiency and system reliability. Novel aspects of our approach include: (1) We consider the asymmetry of price incentives impacting DERAs from the wholesale market compared to those impacting consumers from the retail market, as imposed by current regulations and laws. (2) We model aggregate consumer response through statistically parameterizable utility functions rather than a potentially impractical approach of modeling each individual consumer. (3) We show how to use the DERA operational dispatch model to create offers into the wholesale electricity market. (4) We show how DERAs may fail to meet their scheduled dispatch because the market offer format may not permit them to fully express their operational features such as intertemporal costs and constraints to the market.

aggregations↗

Balancing Doses of EL222 and Light Improves Optogenetic Induction of Protein Production in Komagataella phaffii

ABSTRACT Komagataella phaffii, also known asPichia pastoris, is a powerful host for recombinant protein production, in part due to its exceptionally strong and tightly controlled P AOX1 promoter. MostK. phaffiibioprocesses for recombinant protein production rely on P AOX1 to achieve dynamic control in two‐phase processes. Cells are first grown under conditions that repress P AOX1 (growth phase), followed by methanol‐induced recombinant protein expression (production phase). In this study, we propose a methanol‐free approach for dynamic metabolic control inK. phaffiiusing optogenetics, which can help enhance input tunability and flexibility in process optimization and control. The light‐responsive transcription factor EL222 fromErythrobacter litoralisis used to regulate protein production from the P C120 promoter inK. phaffiiwith blue light. We used two system designs to explore the advantages and disadvantages of coupling or decoupling EL222 integration with that of the gene of interest. We investigate the relationship between EL222 gene copy number and light dosage to improve production efficiency for intracellular and secreted proteins. Experiments in lab‐scale bioreactors demonstrate the feasibility of the outlined optogenetic systems as potential alternatives to conventional methanol‐inducible bioprocesses usingK. phaffii.

Biotechnology & Applied Microbiology↗

The Exoproteome and Surfaceome of Toxigenic Corynebacterium diphtheriae 1737 and Its Response to Iron Restriction and Growth on Human Hemoglobin

Toxin-producing Corynebacterium diphtheriae strains are the etiological agents of the severe upper respiratory disease, diphtheria. A global phylogenetic analysis revealed that biotype gravis is particularly lethal as it produces diphtheria toxin and a range of other virulence factors, particularly when it encounters low levels of iron at sites of infection. Here, to gain insight into how it colonizes its host, we have identified iron-dependent changes in the exoproteome and surfaceome of C. diphtheriae strain 1737 using a combination of whole-cell fractionation, intact cell surface proteolysis, and quantitative proteomics. In total, we identified 1414 of the predicted 2265 proteins (62%) encoded by its reference genome. For each protein, we quantified its degree of secretion and surface exposure, revealing that exoproteases and hydrolases predominate in the exoproteome, while the surfaceome is enriched with adhesins, particularly DIP2093. Our analysis provides insight into how components in the heme-acquisition system are positioned, showing pronounced surface exposure of the strain-specific ChtA/ChtC paralogues and high secretion of the species-conserved heme-binding HtaA protein, suggesting it functions as a hemophore. Profiling the response of the exoproteome and surfaceome after microbial exposure to human hemoglobin and iron limitation reveals potential virulence factors that may be expressed at sites of infection. Data are available via ProteomeXchange with identifier PXD051674.

cell envelope↗

Structure and in vivo psoralen DNA crosslink repair activity of mycobacterial Nei2

Mycobacterium smegmatis Nei2 is a monomeric enzyme with AP β-lyase activity on single-stranded DNA. Expression of Nei2, and its operonic neighbor Lhr (a tetrameric 3'-to-5' helicase), is induced in mycobacteria exposed to DNA damaging agents. Here, we find that nei2 deletion sensitizes M. smegmatis to killing by DNA inter-strand crosslinker trimethylpsoralen but not to crosslinkers mitomycin C and cisplatin. By contrast, deletion of lhr sensitizes to killing by all three crosslinking agents. We report a 1.45 Å crystal structure of recombinant Nei2, which is composed of N and C terminal lobes flanking a central groove suitable for DNA binding. The C lobe includes a tetracysteine zinc complex. Mutational analysis identifies the N-terminal proline residue (Pro2 of the ORF) and Lys51, but not Glu3, as essential for AP lyase activity. We find that Nei2 has 5-hydroxyuracil glycosylase activity on single-stranded DNA that is effaced by alanine mutations of Glu3 and Lys51 but not Pro2. Testing complementation of psoralen sensitivity by expression of wild-type and mutant nei2 alleles in Δnei2 cells established that AP lyase activity is neither sufficient nor essential for crosslink repair. By contrast, complementation of psoralen sensitivity of Δlhr cells by mutant lhr alleles depended on Lhr’s ATPase/helicase activities and its tetrameric quaternary structure. The lhr–nei2 operon comprises a unique bacterial system to rectify inter-strand crosslinks.

59 BASIC BIOLOGICAL SCIENCES↗

Towards a Deeper Fundamental Understanding of (Al,Sc)N Ferroelectric Nitrides

Density functional theory (DFT) calculations, within the virtual crystal alloy approximation, are performed, along with the development of a Landau-type model employing a symmetry-allowed analytical expression of the internal energy and having parameters determined from first principles, to investigate properties and energetics of Al1-xScxN ferroelectric nitrides in their hexagonal forms. These DFT computations and this model predict the existence of two different types of minima, namely, the fourfold-coordinated wurtzite (WZ) polar structure and a five-fold coordinated paraelectric hexagonal phase (denoted as H5), for any Sc composition up to 40%. The H5 minimum progressively becomes the lowest-energy state within hexagonal symmetry as the Sc concentration increases from 0 to 0.4. Furthermore, the model points to several key findings. Examples include the crucial role of the coupling between polarization and strains to create the WZ minimum, in addition to polar and elastic energies, and that the origin of the H5 state overcoming the WZ phase as the global minimum within hexagonal symmetry when increasing the Sc composition mostly lies in the compositional dependency of only two parameters-one linked to the polarization and another one being purely elastic in nature. Other examples are that forcing Al1-xScxN systems to have no or a weak change in lattice parameters when heating them allows us to reproduce their finite-temperature polar properties well and that a value of the axial ratio close to that of the ideal WZ structure implies a large polarization at low temperatures but not necessarily at high temperatures because of the ordered-disordered character of the temperature-induced formation of the WZ state. Such findings should allow for a better fundamental understanding of (Al,Sc)N ferroelectric nitrides, which may be used to design efficient devices having, e.g., low operating voltages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deciphering Reaction Mechanisms of Molecular Proton Reduction Catalysts with Cyclic Voltammetry: Kinetic vs Thermodynamic Control

The kinetics and thermodynamics of elementary reaction steps involved in the catalytic reduction of protons to hydrogen define the reaction landscape for catalysis. The mechanisms can differ in the order of the elementary proton transfer, electron transfer, and bond-forming steps and can be further differentiated by the sites at which protons and electrons localize. Access to fully elucidated mechanistic, kinetic, and thermochemical details of molecular catalysts is crucial to facilitate the development of new catalysts that operate with optimal efficiency, selectivity, and durability. The mechanism by which a catalyst operates, as well as the kinetics and thermodynamics associated with the individual steps, can often be accessed through electroanalytical studies. Here, this Account details the application of cyclic voltammetry to interrogate reaction mechanisms and quantify the kinetics and thermodynamics of elementary reaction steps for a series of molecular catalysts that mediate electrochemical proton reduction. I distinguish the limiting scenarios wherein a catalyst operates under kinetic control vs thermodynamic control, with a focus on detecting how cyclic voltammetry features shift with proton source strength and concentration, as well as scan rate. For systems that operate under kinetic control, catalytic currents are observed at, or slightly positive toward, the formal potential for the redox process that triggers catalysis. Under thermodynamic control, catalytic responses shift as a function of the proton source pKa and effective pH of the solution. After drawing this distinction, we introduce the appropriate voltammetry experiments and accompanying analytical expressions for extracting key metrics from the data. To illustrate analytical strategies to quantify elementary reaction steps of catalysts operating under kinetic control, I describe our studies of proton reduction catalysts Co(dmgBF 2 ) 2 (CH 3 CN) 2 (dmgBF 2 = difluoroboryl-dimethylglyoxime) and [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ (P 2 Ph N 2 Ph = 1,5-phenyl-3,7-phenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, peak shift analysis, foot-of-the-wave analysis, and plateau current analysis are applied to data sets wherein voltammetric response are recorded as a function of catalyst concentration, proton source concentration, proton source strength, and scan rate to quantify rate constants for elementary proton transfer and bond-forming steps in a catalytic cycle. Further, the case study of [Ni(P 2 Ph N 2 Ph ) 2 ] 2+ illustrates how complementary spectroscopic methods can bolster the mechanistic assignment. Collectively, these two studies showcase how detailed mechanistic studies inform on rate-limiting elementary steps in catalysis and other key processes underpinning catalysis. Second, I present analytical strategies to interrogate catalysts operating under thermodynamic control, centered on the case study of [Ni II (P 2 Ph N 2 Bn ) 2 ] 2+ (P 2 Ph N 2 Bn = 1,5-dibenzyl-3,7-diphenyl-1,5-diaza-3,7-diphosphacyclooctane). Here, the application of nonaqueous Pourbaix theory to extract thermodynamic information is introduced, and the construction of a coupled Pourbaix diagram is detailed. This study identifies ligand-based protonation as the key process that places catalysis under thermodynamic control and influences the reaction mechanism. Together, the work detailed in this Account showcases the utility of electroanalytical methods to disentangle complex reaction mechanisms and extract key thermochemical and kinetic parameters for elementary steps of catalysis. Through detailed presentation of the key analytical expressions that underpin these analyses, this Account seeks to facilitate the adoption of cyclic voltammetry by the community to fully extract kinetic, thermochemical, and mechanistic information on electrochemical small-molecule activation.

catalysts↗

Hybrid biophysical systems for atmospheric CO 2 capture

Negative emissions technologies will be essential for limiting anthropogenic global temperature increases to 2 °C in the later years of the 21st century. Carbonic anhydrase (CA) metalloenzymes catalyze the otherwise slow conversion of CO 2 into carbonic acid (H 2 CO 3 ), suggesting their utility in the rapid hydration and downstream capture of dissolved CO 2 in aqueous media for a variety of CO 2 capture methods, such as thermal and pH swings and mineralization. The possibility of driving the rapid capture of CO 2 by catalyzing the CO 2 hydration bottleneck carries real potential for realizing efficient direct air capture (DAC) and direct ocean capture (DOC) systems. However, scaled application of CAs will be dependent on some way of economically sourcing the enzymes at volumes relevant to scaled DAC/DOC operations. In this perspective, we consider the prospect of catalyzing CO 2 hydration using a CA that is bound to the outer membrane of a cyanobacterial host, engineered constructs we call CyCAMs. Coupling extracellular CA expression to a marine, photosynthetic cyanobacterial host results in a CO 2 hydration catalyst that is continuously refreshed during the bacterial growth cycle, without the need for enzyme purification or harvesting steps. In the case of marine cyanobacteria, sunlight and the solutes native to seawater provide the respective energy, nutrients and sources of inorganic carbon essential to maintaining the bacterial population. We consider the potential impact of CA-mediated CO 2 hydration on a variety of DAC processes, with CO 2 mineralization explored as a primary use case.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Transcriptomic and functional analyses uncover a conserved effector driving genotype-dependent virulence in the Sphaerulina musiva-Populus trichocarpa interaction

The introduction of invasive microbes compromises the structure, biodiversity, and function of naïve ecosystems. Sphaerulina musiva, a hemibiotrophic pathogen that causes leaf spot and stem cankers in Populus species, exemplifies an invasive fungal pathogen spread by human activities. However, the genetic mechanisms of pathogenicity and virulence are poorly understood, impeding mitigation strategies. We utilized RNA sequencing to identify fungal effectors linked to stem canker formation, informing the development of future strategies for effective disease management. Our analysis revealed 70 genes differentially expressed at 2 weeks and 110 genes at 3 weeks between inoculated trees and controls. Notably, the gene with the highest expression at 2 weeks and the second highest at 3 weeks was homologous to Extracellular protein 2 (Ecp2). Complementary genome-wide association studies linked sequence polymorphisms in this locus to phenotypic variation in disease severity. Infiltration of S. musiva Ecp2 into Populus trichocarpa leaves induced necrosis in susceptible genotypes. Gene disruption using a CRISPR-Cas9 RNP system resulted in a genotype-dependent reduction of stem canker and disease severity. Tracing the evolutionary history of this effector across the fungal kingdom, we uncovered clade-specific gene-family expansions and orthologs in new species. These findings raise questions about the function and adaptive significance of these gene families in fungal lifestyles. Our study provides the first tractable target for breeding resistant poplar genotypes, addressing the challenges of managing S. musiva and uncovering mechanisms that drive its virulence, and provides deeper insights into the evolutionary dynamics of a conserved small-secreted protein with a diversity of functions.

Sondreli, Kelsey L [Oregon State University]↗

QUANT-NET Control Plane Framework (QNCP) v1.0.0

The QUANT-NET Control Plane (QNCP) provides a software framework for expressing and managing quantum network resources. It may be used to orchestrate a physical quantum testbed with real device driver implementations, or it may be used as a proving ground when developing new protocols and management functions. In practice, both approaches may be useful when undertaking research and development in emerging quantum testbeds. While a number of control systems have been developed for specific quantum platform demonstrations, an openly available and general solution for operating quantum networks has not emerged. QNCP is designed to fill this gap. The framework has been designed to provide extensible, modular capabilities that include scheduling, routing, monitoring, and pluggable protocols. A number of reference implementations in each module category have been included in the installable packages; however, the intent is that each of these modules may be extended or re-implemented to meet the needs of the particular deployment or research need. The software is currently being used in the QUANT-NET testbed project, which spans resources between LBNL and UC Berkeley Physics.

Zhang, Liang [Lawrence Berkeley National Laborator↗

Benchmarking quantum trial wavefunctions for phaseless auxiliary-field quantum Monte Carlo

The phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) method is a stochastic imaginary-time projection technique for computing ground-state properties of strongly correlated quantum systems, with accuracy that depends critically on the choice of trial wavefunction. Here, we investigate ph-AFQMC with trial states prepared using parameterized quantum circuits. In this work, we present a comprehensive benchmarking study of quantum trial wavefunctions spanning unitary coupled-cluster, Hamiltonian-informed, Jastrow-inspired, and adaptively constructed ansatze. The benchmarking evaluates accuracy, expressibility, and scalability of these ansatze within the QC-AFQMC framework. We test these ansatze on linear hydrogen chains under bond stretching and find that several ansatz families produce chemically accurate ph-AFQMC energies across the dissociation curve. We have performed simulations using the CUDA-Q quantum development platform on the GPU partition of the Perlmutter supercomputer. When comparing ansatze at similar numbers of variational parameters, we find that different ansatz families yield comparable ph-AFQMC results despite exhibiting substantially different variational energies, optimization costs, and circuit depths. Our results indicate that the variational energy of an ansatz is not always a reliable indicator of its quality for ph-AFQMC and reveal instances of over-parameterization. In the strongly correlated regime, trial wavefunctions obtained from adaptive ansatze, exemplified here by ADAPT-VQE with the UCCSD operator pool, can outperform their fixed-ansatz counterparts (UCCSD) in terms of projected energies while using substantially more compact circuits, providing a flexible route to optimize quantum resources within the ph-AFQMC framework.

Rofougaran, Rod [LBNL, Berkeley; Columbia U.; PNL,↗

Automated Label‐Free Assay for Viral Detection and Inhibitor Screening via Biomembrane‐Functionalized Microelectrode Arrays

Most virus infection assays have indirect readout such as virus number following entry (e.g., PCR, cell lysis). While effective, these technologies are labor‐intensive, require specialized environments (e.g., sterile or RNA‐free), and detect later‐stage viral events like lysis or cell death, lacking sensitivity to early fusion events. To address these limitations, we present biologically relevant 2D membrane materials, host‐cell‐derived supported lipid bilayers (hcd‐SLBs), integrated with organic microelectrode arrays (OMEAs) for detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) fusion. By overexpressing angiotensin‐converting enzyme 2 (ACE2) receptors on the native membranes, the platform functions as a viral sensor capable of detecting virus pseudo particles (VPPs) through the late pathway. Additionally, hcd‐SLBs extracted from human lung epithelium expressing native ACE2 detect fusion events through the early pathway. The platform's utility as a drug‐screening tool is demonstrated by testing antibodies targeting either the ACE2 on the host membrane or the viral spike (S) proteins. To enhance the throughput, microfluidics are integrated for automation and OMEAs are incorporated within each channel, miniaturizing the testing units. This system supports high‐throughput data generation, automation, and scalability, providing an efficient platform for viral fusion detection that advances the study of pathogen‐host interactions and accelerates antiviral drug discovery.

Biology↗

Completion of lunar magma ocean solidification at 4.43 Ga

Crystallization of the lunar magma ocean yielded a chemically unique liquid residuum named KREEP. This component is expressed as a large patch on the near side of the Moon and a possible smaller patch in the northwest portion of the Moon’s South Pole-Aitken basin on the far side. Thermal models estimate that the crystallization of the lunar magma ocean (LMO) could have spanned from 10 and 200 My, while studies of radioactive decay systems have yielded inconsistent ages for the completion of LMO crystallization covering over 160 My. Here, we show that the Moon achieved >99% crystallization at 4,429 ± 76 Ma, indicating a lunar formation age of ~4,450 Ma or possibly older. Using the 176 Lu– 176 Hf decay system (t 1/2 = 37 Gy), we found that the initial 176 Hf/ 177 Hf ratios of lunar zircons with varied U–Pb ages are consistent with their crystallization from a KREEP-rich reservoir with a consistently low 176 Lu/ 177 Hf ratio of 0.0167 that emerged ~140 My after solar system formation. The previously proposed younger model age of ~4.33 Ga for the source of mare basalts (240 My after solar system formation) might reflect the timing of a large impact. Our results demonstrate that lunar magma ocean crystallization took place while the Moon was still battered by planetary embryos and planetesimals leftover from the main stage of planetary accretion. The study of Lu–Hf model ages for samples brought back from the South Pole-Aitken basin will help to assess the lateral continuity of KREEP and further understand its significance in the early history of the Moon.

Science & Technology - Other Topics↗

Single-cell and spatial omics in plants: from cellular atlases to regulatory mechanisms

Single-cell RNA sequencing (scRNA-seq) has transformed transcriptomic studies by enabling gene expression profiling at the resolution of individual cells within and across a broad range of tissue types, revealing cellular heterogeneity that is obscured in bulk tissue transcriptomes. Over the past decade, improvements in microfluidics and library preparation have drastically increased throughput, allowing tens of thousands of cells to be assayed in a single experiment. Although initially developed in animal systems, scRNA-seq has rapidly emerged as a powerful and widely adopted approach in plant biology. Beyond transcriptomics, the integration of single-cell data with chromatin accessibility, proteomics, metabolomics, and spatial omics is enabling a system-level understanding of plant gene regulation and cellular organization. Network-based analytical frameworks further support the reconstruction of gene regulatory networks and the interpretation of complex single-cell data. In this review, we summarize the current technological landscape of plant single-cell studies, discuss key experimental and analytical challenges, and review emerging strategies for validating single-cell discoveries. We also discuss future directions in applying single-cell technologies to woody perennials plants and bioenergy-relevant crops, emphasizing their potential to accelerate the discovery of cell type-specific regulatory mechanisms underlying growth, stress resilience, and biomass production.

Li, Miaomiao [ORNL] (ORCID:0000000321326168)↗

Altering translation allows E. coli to overcome G-quadruplex stabilizers

G-quadruplex (G4) structures can form in guanine-rich DNA or RNA and have been found to modulate cellular processes, including replication, transcription, and translation. Many studies on the cellular roles of G4s have focused on eukaryotic systems, with far fewer probing bacterial G4s. Using a chemical-genetic approach, we identified genes in Escherichia coli that are important for growth in G4-stabilizing conditions. Reducing levels of translation elongation factor Tu or slowing translation initiation or elongation with kasugamycin, chloramphenicol, or spectinomycin suppress the effects of G4-stabilizing compounds. In contrast, reducing the expression of specific translation termination or ribosome recycling proteins is detrimental to growth in G4-stabilizing conditions. Proteomic and transcriptomic analyses reveal decreased protein and transcript levels, respectively, for ribosome assembly factors and proteins associated with translation in the presence of G4 stabilizer. Our results support a model in which reducing the rate of translation by altering translation initiation, translation elongation, or ribosome assembly can compensate for G4-related stress in E. coli.

59 BASIC BIOLOGICAL SCIENCES↗

Performance Study of CXL Memory Topology

This paper presents a comprehensive evaluation of the performance impact of various Compute Express Link (CXL) memory topologies, with a particular emphasis on CXL switches, in the context of High- Performance Computing (HPC) and Large Language Model (LLM) inference workloads. Our study unveils significant performance variations across different topologies, demonstrating that certain configurations yield superior performance for specific workloads. These findings underscore the critical importance of tailored topol- ogy selection in optimizing system performance. Additionally, we address the inherent challenges associated with integrating CXL switches, including overhead considerations and routing complex- ities. Our research highlights the necessity for thorough evalua- tion methodologies to fully leverage CXL technology’s potential in contemporary computing environments. These insights provide valuable guidance for system architects and data center operators in designing and optimizing CXL-based infrastructures for diverse workload requirements.

CXL, memory, Artificial Intelligence (AI), HPC↗

Electron transport across the cell envelope via multiheme c -type cytochromes in Geobacter sulfurreducens

Extracellular electron transfer (EET) enables certain microorganisms to respire using soluble and insoluble extracellular electron acceptors by transporting electrons across the cell envelope. Among these, G. sulfurreducens serves as a model organism for understanding direct EET pathways, where multiheme c-type cytochromes mediate electron transport from intracellular redox carriers to extracellular acceptors such as Fe(III) oxides and electrodes. This review focuses on heme-dependent electron transfer in Geobacter sulfurreducens, detailing the roles of inner membrane cytochromes, periplasmic carriers, outer membrane conduits, and recently characterized extracellular nanowires formed by polymerized multiheme c-type cytochromes, including OmcS, OmcE, and OmcZ. We examine the state of understanding of their physiological function, their structural features, expression patterns, and essentiality under various respiratory conditions. These insights advance our understanding of microbial anaerobic respiration and have implications for biogeochemical cycling, bioenergy generation, and bioremediation. The molecular architecture, assembly mechanisms, and secretion pathways of multiheme c-type cytochrome nanowires remain active areas of investigation, offering promising directions for future research and biotechnological innovation in engineered microbial systems.

Chemistry↗