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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Solution‐Like Water Transport Across Molecular to Macroscopic Length Scales in Crosslinked Poly(Ethylene Glycol Diacrylate) Networks With Tailored Sidechains

Poly(ethylene glycol) (PEG)‐based materials, like PEG‐diacrylate (PEGDA), are prized for their hydrophilic, inert properties, and leveraged in hydrogels and as membrane mimics. While network chemistry is often tuned for selective transport and antifouling, fundamental understanding of water dynamics at the network surface and the impact on bulk transport is limited. We utilize Overhauser dynamic nuclear polarization (ODNP) to measure nanoscale water diffusivity near a tethered spin label at the water‐polymer surface and compare it to bulk water diffusivity from pulsed field gradient (PFG) NMR. Via active ester chemistry, spin labels and varied sidechain chemistries are introduced, modulating network hydrophilicity. Tuning network hydration through crosslinker content and functional groups further impacts water diffusivity. Results show rapid nanoscale water transport at the polymer surface, reflecting network volumetric water content, with further modulation by sidechain functionality. These findings demonstrate PEGDA's utility as a membrane mimic and the critical impact of network chemistry on water transport.

hydrogels↗
DOE OSTI2019

Isotope Effects on the Crystallization Kinetics of Selectively Deuterated Poly(ε-Caprolactone)

Deuterium labeling of semi-crystalline polymers can dramatically affect their crystallization behaviors. However, the influence of different labeled positions in a partially deuterated polymer on its crystallization is still far from understood. Here, we synthesized a series of selectively deuterated poly(ε-caprolactones) (PCLs) through ring-opening polymerization of ε-caprolactone with controlled deuteration sites, including fully protiated (D0), fully deuterated (D10), tetra deuteration at the 3- and 7- caprolactone ring positions (D4) and hexa deuteration at the 4-, 5-, and 6- caprolactone ring positions (D6). All the PCLs showed a similar lamellar structure and parameters. Differential scanning calorimetry (DSC) analysis revealed that the equilibrium melting temperature $T^{0}_{m}$, melting temperature T m , crystallization temperature T c , and crystallization kinetics changed systemically with the deuterium content except for D4, which indicates that the presence of—CD 2 —moieties on either side of ester group in the polymer chain combined with isotopic inhomogeneity could influence the chain packing. The nonmonotonic trend of T m as a function of deuterium content could be attributed to the difference in a hydrogen-bond like intermolecular interaction between different PCLs. Partially deuterated PCLs (D4 and D6) showed an Avrami index near 2. After analyzing the parameters at the same supercooling temperature Δ T c , the existence of two crystallization regimes of PCLs were detected.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Vibrational Spectra of HNIW and its Isotopologues: A Combined Experimental and Computational Study

Incorporating isotopically labelled materials in degradation experiments could help unravel the mechanism(s) of decomposition through use of the kinetic isotope effect. Characterizing synthesized isotopologues however requires an understanding of what observable signals are affected by the isotopic substitution. As vibrational spectroscopy can distinguish between isotopologues, it is an ideal characterization technique to evaluate isotopic variants. To this end, the vibrational spectra of HNIW and its deuterated ( 2 H), 13 C, 15 N (all), 15 N (nitro), and 18 O isotopologues have been computationally predicted in the gas phase using density functional theory. These results are compared to experimentally measured FTIR/ATR and Raman spectra of both unsubstituted HNIW and 15 N-labeled HNIW in which the six nitro groups were synthetically tagged with 15 N atoms ( 15 N nitro -HNIW). The experimental isotopic frequency shift for the -NO 2 asymmetric stretching frequencies agrees with that theoretically calculated (~35.7 cm-1 vs. 36.5cm-1, respectively). Furthermore, analysis of the theoretically predicted frequency shifts for all isotopologues suggest the -NO 2 bending modes are lower in frequency than previously reported. This assignment is supported by the experimentally measured isotopic shift of ~10.1 cm -1 for these features (consistent with the predicted shift of ~13.1 cm -1 ). This work expands our current understanding of the vibrational modes in HNIW as well as provides a method for future work on similar systems.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Cytosolic expression, solution structures, and molecular dynamics simulation of genetically encodable disulfide‐rich de novo designed peptides

Abstract Disulfide‐rich peptides represent an important protein family with broad pharmacological potential. Recent advances in computational methods have made it possible to design new peptides which adopt a stable conformation de novo. Here, we describe a system to produce disulfide‐rich de novo peptides using Escherichia coli as the expression host. The advantage of this system is that it enables production of uniformly 13 C‐ and 15 N‐labeled peptides for solution nuclear magnetic resonance (NMR) studies. This expression system was used to isotopically label two previously reported de novo designed peptides, and to determine their solution structures using NMR. The ensemble of NMR structures calculated for both peptides agreed well with the design models, further confirming the accuracy of the design protocol. Collection of NMR data on the peptides under reducing conditions revealed a dependency on disulfide bonds to maintain stability. Furthermore, we performed long‐time molecular dynamics (MD) simulations with tempering to assess the stability of two families of de novo designed peptides. Initial designs which exhibited a stable structure during simulations were more likely to adopt a stable structure in vitro , but attempts to utilize this method to redesign unstable peptides to fold into a stable state were unsuccessful. Further work is therefore needed to assess the utility of MD simulation techniques for de novo protein design.

Buchko, Garry W.↗
DOE OSTI2023

Structural characterization of an intrinsically disordered protein complex using integrated small-angle neutron scattering and computing

Characterizing structural ensembles of intrinsically disordered proteins (IDPs) and intrinsically disordered regions (IDRs) of proteins is essential for studying structure–function relationships. Due to the different neutron scattering lengths of hydrogen and deuterium, selective labeling and contrast matching in small-angle neutron scattering (SANS) becomes an effective tool to study dynamic structures of disordered systems. However, experimental timescales typically capture measurements averaged over multiple conformations, leaving complex SANS data for disentanglement. We hereby demonstrate an integrated method to elucidate the structural ensemble of a complex formed by two IDRs. We use data from both full contrast and contrast matching with residue-specific deuterium labeling SANS experiments, microsecond all-atom molecular dynamics (MD) simulations with four molecular mechanics force fields, and an autoencoder-based deep learning (DL) algorithm. From our combined approach, we show that selective deuteration provides additional information that helps characterize structural ensembles. We find that among the four force fields, a99SB-disp and CHARMM36m show the strongest agreement with SANS and NMR experiments. In addition, our DL algorithm not only complements conventional structural analysis methods but also successfully differentiates NMR and MD structures which are indistinguishable on the free energy surface. Finally, we present an ensemble that describes experimental SANS and NMR data better than MD ensembles generated by one single force field and reveal three clusters of distinct conformations. Our results demonstrate a new integrated approach for characterizing structural ensembles of IDPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Chapter 14: Dynamic Flux Analysis: An Experimental Approach of Fluxomics

Metabolic flux analysis represents an essential perspective to understand cellular physiology and offers quantitative information to guide pathway engineering. A valuable approach for experimental elucidation of metabolic flux is dynamic flux analysis, which estimates the relative or absolute flow rates through a series of metabolic intermediates in a given pathway. It is based on kinetic isotope labeling experiments, liquid chromatography-mass spectrometry (LC-MS), and computational analysis that relate kinetic isotope trajectories of metabolites to pathway activity. Herein, we illustrate the mathematic principles underlying the dynamic flux analysis and mainly focus on describing the experimental procedures for data generation. This protocol is exemplified using cyanobacterial metabolism as an example, for which reliable labeling data for central carbon metabolites can be acquired quantitatively. This protocol is applicable to other microbial systems as well and can be readily adapted to address different metabolic processes.

BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Genome-Scale 13 C Fluxomics Modeling for Metabolic Engineering of Saccharomyces cerevisiae .

Synthetic biology is a rapidly developing field that pursues the application of engineering principles and development approaches to biological engineering. Synthetic biology is poised to change the way biology is practiced, and has important practical applications: for example, building genetically engineered organisms to produce biofuels, medicines, and other chemicals. Traditionally, synthetic biology has focused on manipulating a few genes (e.g., in a single pathway or genetic circuit), but its combination with systems biology holds the promise of creating new cellular architectures and constructing complex biological systems from the ground up. Enabling this merge of synthetic and systems biology will require greater predictive capability for modeling the behavior of cellular systems, and more comprehensive data sets for building and calibrating these models. The so-called "-omics" data sets can now be generated via high throughput techniques in the form of genomic, proteomic, transcriptomic, and metabolomic information on the engineered biological system. Of particular interest with respect to the engineering of microbes capable of producing biofuels and other chemicals economically and at scale are metabolomic datasets, and their insights into intracellular metabolic fluxes. Metabolic fluxes provide a rapid and easy to understand picture of how carbon and energy flow throughout the cell. Furthermore, we present a detailed guide to performing metabolic flux analysis and modeling using the open source JBEI Quantitative Metabolic Modeling (jQMM) library. This library allows the user to transform metabolomics data in the form of isotope labeling data from a 13 C labeling experiment into a determination of cellular fluxes that can be used to develop genetic engineering strategies for metabolic engineering.The jQMM library presents a complete toolbox for performing a range of different tasks of interest in metabolic engineering. Various different types of flux analysis and modeling can be performed such as flux balance analysis, 13 C metabolic flux analysis, and two-scale 13 C metabolic flux analysis (2S- 13 C MFA). 2S- 13 C MFA is a novel method that determines genome-scale fluxes without the need of every single carbon transition in the metabolic network. In addition to several other capabilities, the jQMM library can make model based predictions for how various genetic engineering strategies can be incorporated toward bioengineering goals: it can predict the effects of reaction knockouts on metabolism using both the MoMA and ROOM methodologies. In this chapter, we will illustrate the use of the jQMM library through a step-by-step demonstration of flux determination and knockout prediction in a complex eukaryotic model organism: Saccharomyces cerevisiae ( S. cerevisiae ). Included with this chapter is a digital Jupyter Notebook file that provides a computable appendix showing a self-contained example of jQMM usage, which can be changed to fit the user's specific needs. As an open source software project, users can modify and extend the code base to make improvements at will, allowing them to share their development work and contribute back to the jQMM modeling community.

-Omics data↗
DOE OSTI2021

Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM

We present a multiple instance learning class activation map (MIL-CAM) approach for pixel-level minirhizotron image segmentation given weak image-level labels. Minirhizotrons are used to image plant roots in situ. Minirhizotron imagery is often composed of soil containing a few long and thin root objects of small diameter. The roots prove to be challenging for existing semantic image segmentation methods to discriminate. In addition to learning from weak labels, our proposed MILCAM approach re-weights the root versus soil pixels during analysis for improved performance due to the heavy imbalance between soil and root pixels. Furthermore, the proposed approach outperforms other attention map and multiple instance learning methods for localization of root objects in minirhizotron imagery.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

High-dimensional anomaly detection with radiative return in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions

Experiments at a future $\mathcal{e}$⁺$\mathcal{e}$⁻ collider will be able to search for new particles with masses below the nominal centre-of-mass energy by analyzing collisions with initial-state radiation (radiative return). We show that machine learning methods that use imperfect or missing training labels can achieve sensitivity to generic new particle production in radiative return events. In addition to presenting an application of the classification without labels (CWoLa) search method in $\mathcal{e}$⁺$\mathcal{e}$⁻ collisions, our study combines weak supervision with variable-dimensional information by deploying a deep sets neural network architecture. We have also investigated some of the experimental aspects of anomaly detection in radiative return events and discuss these in the context of future detector design.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Quantum vacua of 2d maximally supersymmetric Yang-Mills theory

Here, we analyze the classical and quantum vacua of 2d N = (8,8) supersymmetric Yang-Mills theory with SU( N ) and U( N ) gauge group, describing the worldvolume interactions of N parallel D1-branes with flat transverse directions R 8 . We claim that the IR limit of the SU( N ) theory in the superselection sector labeled M (mod N ) — identified with the internal dynamics of ( M , N )-string bound states of the Type IIB string theory — is described by the symmetric orbifold N = (8,8) sigma model into (R 8 )D–1/SD when D = gcd( M , N ) > 1, and by a single massive vacuum when D = 1, generalizing the conjectures of E. Witten and others. The full world volume theory of the D1-branes is the U( N ) theory with an additional U(1) 2-form gauge field B coming from the string theory Kalb-Ramond field. This U( N ) + B theory has generalized field configurations, labeled by the Z-valued generalized electric flux and an independent Z N -valued ’t Hooft flux. We argue that in the quantum mechanical theory, the ( M , N )-string sector with M units of electric flux has a Z N -valued discrete θ angle specified by M (mod N ) dual to the ’t Hooft flux. Adding the brane center-of-mass degrees of freedom to the SU( N ) theory, we claim that the IR limit of the U( N ) + B theory in the sector with M bound F-strings is described by the N = (8,8) sigma model into Sym D (R 8 ). We provide strong evidence for these claims by computing an N = (8,8) analog of the elliptic genus of the UV gauge theories and of their conjectured IR limit sigma models, and showing they agree. Agreement is established by noting that the elliptic genera are modular-invariant Abelian (multi-periodic and meromorphic) functions, which turns out to be very restrictive.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Effects of 31 FDA approved small-molecule kinase inhibitors on isolated rat liver mitochondria

The FDA has approved 31 small-molecule kinase inhibitors (KIs) for human use as of November 2016, with six having black box warnings for hepatotoxicity (BBW-H) in product labeling. The precise mechanisms and risk factors for KI-induced hepatotoxicity are poorly understood. Here, the 31 KIs were tested in isolated rat liver mitochondria, an in vitro system recently proposed to be a useful tool to predict drug-induced hepatotoxicity in humans. The KIs were incubated with mitochondria or submitochondrial particles at concentrations ranging from therapeutic maximal blood concentrations (Cmax) levels to 100-fold Cmax levels. Ten endpoints were measured, including oxygen consumption rate, inner membrane potential, cytochrome c release, swelling, reactive oxygen species, and individual respiratory chain complex (I–V) activities. Of the 31 KIs examined only three including sorafenib, regorafenib and pazopanib, all of which are hepatotoxic, caused significant mitochondrial toxicity at concentrations equal to the Cmax, indicating that mitochondrial toxicity likely contributes to the pathogenesis of hepatotoxicity associated with these KIs. At concentrations equal to 100-fold Cmax, 18 KIs were found to be toxic to mitochondria, and among six KIs with BBW-H, mitochondrial injury was induced by regorafenib, lapatinib, idelalisib, and pazopanib, but not ponatinib, or sunitinib. Mitochondrial liability at 100-fold Cmax had a positive predictive power (PPV) of 72% and negative predictive power (NPV) of 33% in predicting human KI hepatotoxicity as defined by product labeling, with the sensitivity and specificity being 62% and 44%, respectively. Similar predictive power was obtained using the criterion of Cmax ≥1.1 µM or daily dose ≥100 mg. Mitochondrial liability at 1–2.5-fold Cmax showed a 100% PPV and specificity, though the NPV and sensitivity were 32% and 14%, respectively. These data provide novel mechanistic insights into KI hepatotoxicity and indicate that mitochondrial toxicity at therapeutic levels can help identify hepatotoxic KIs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A Highly Ordered Nitroxide Side Chain for Distance Mapping and Monitoring Slow Structural Fluctuations in Proteins

Abstract Site-directed spin labeling electron paramagnetic resonance (SDSL-EPR) is an established tool for exploring protein structure and dynamics. Although nitroxide side chains attached to a single cysteine via a disulfide linkage are commonly employed in SDSL-EPR, their internal flexibility complicates applications to monitor slow internal motions in proteins and to structure determination by distance mapping. Moreover, the labile disulfide linkage prohibits the use of reducing agents often needed for protein stability. To enable the application of SDSL-EPR to the measurement of slow internal dynamics, new spin labels with hindered internal motion are desired. Here, we introduce a highly ordered nitroxide side chain, designated R9, attached at a single cysteine residue via a non-reducible thioether linkage. The reaction to introduce R9 is highly selective for solvent-exposed cysteine residues. Structures of R9 at two helical sites in T4 Lysozyme were determined by X-ray crystallography and the mobility in helical sequences was characterized by EPR spectral lineshape analysis, Saturation Transfer EPR, and Saturation Recovery EPR. In addition, interspin distance measurements between pairs of R9 residues are reported. Collectively, all data indicate that R9 will be useful for monitoring slow internal structural fluctuations, and applications to distance mapping via dipolar spectroscopy and relaxation enhancement methods are anticipated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Temperature-Dependent Electron Paramagnetic Resonance Studies of Docosahexaenoic Acid and Gamma Linolenic Acid Effects on Phospholipid Membranes With and Without Cholesterol

Free docosahexaenoic acid (DHAn-3) and gamma linolenic acid (GLAn-6) effects on dimyristoyl phosphatidylcholine (DMPC) membranes were studied as a function of temperature by electron paramagnetic resonance (EPR) spectroscopy. 5- and 16-doxyl stearic acid (5-, 16-DS) spin labels were utilized to obtain information from the interfacial and alkyl chain region, respectively. In the studied temperature range, the presence of DHAn-3 or GLAn-6 caused decreases in maximum hyperfi ne splitting values and correlation times of DMPC membranes. Both in the interfacial region and depths of membrane, changes were more pronounced for DHAn-3 in pure DMPC. In the presence of cholesterol (CH), DHAn-3 and GLAn-6 effects were similar and more pronounced in the depths of the membrane. The changes in the structure and dynamics of samples were obtained from simulations of spectra, which indicated some changes in the number of spectral components by incorporation of DHAn-3 and GLAn-6. In the interfacial region and below the main phase transition temperature of DMPC, there was an increase in heterogeneity. For temperatures above the phase transition, a more homogeneous environment for spin label was obtained in the presence of fatty acids.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Early Stage Detection of Stress Due to Copper on Maize (Zea mays L.) by Laser-Induced Fluorescence and Infrared Spectroscopy

Laser-induced fluorescence (LIF) and attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy has been applied for the nondestructive, label free, and rapid analyses of the impact of copper (25, 50, and 75 μM) on maize seedlings at an early stage before the changes appear visually on the plant. The LIF measurement has been used to detect the signs of stress in the photosynthetic pigment. The integrated areal intensity and increasing fluorescence intensity ratios indicate decrease in the photosynthetic pigments in the leaves of maize plants stressed with copper. The ATR-FTIR technique has been utilized to estimate the changes arising in the cell wall polysaccharides, amino acid, secondary structure of protein and lipid content of the leaves of control and copper-treated maize seedlings. The second derivative and curve fitting analyses have been applied for the enhancement of the spectral variations and quantitative estimation of the changes arising in the biochemical profile. The result shows an increase in the pectin, lignin, amino acid, and protein content and reduction in the amount of cellulose and lipid in the leaves of maize seedlings due to the treatment of copper. This study indicates the toxic response of copper by hampering the growth and reduction in the photosynthetic pigments and biochemical content of the maize seedlings. This study also demonstrates the feasibility of the spectroscopic techniques (LIF and ATRFTIR) as a rapid, label free, and nondestructive probe for the assessment of stress and monitoring of crops.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Fluorescence Correlation Spectroscopy with Photobleaching Correction in Slowly Diffusing Systems

Fluorescence correlation spectroscopy (FCS) is a powerful tool to quantitatively study the diffusion of fluorescently labeled molecules. It allows in principle important questions of macromolecular transport and supramolecular aggregation in living cells to be addressed. However, the crowded environment inside the cells slows diffusion and limits the reservoir of labeled molecules, causing artifacts that arise especially from photobleaching and limit the utility of FCS in these applications. We present a method to compute the time correlation function from weighted photon arrival times, which compensates computationally during the data analysis for the effect of photobleaching. We demonstrate the performance of this method using numerical simulations and experimental data from model solutions. Using this technique, we obtain correlation functions in which the effect of photobleaching has been removed and in turn recover quantitatively accurate mean-square displacements of the fluorophores, especially when deviations from an ideal Gaussian excitation volume are accounted for by using a reference calibration correlation function. This allows quantitative FCS studies of transport processes in challenging environments with substantial photobleaching like in living cells in the future.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2018

Discovery of the canonical Calvin–Benson cycle

It has been 65 years since the Calvin-Benson cycle was first formulated. In this paper the development of the concepts that are critical to the cycle are traced and the contributions of Calvin, Benson, and Bassham are discussed. Some simplified views often found in text books such as ascending paper chromatography and the use of the “lollipop” for short labeling are discussed and further details given. Key discoveries that underpinned elucidation of the cycle such as the importance of sedoheptulose phosphate and ribulose 1,5-bisphosphate are described. The interchange of ideas between other researchers working on what is now called the pentose phosphate pathway and the development of the ideas of Calvin and Benson are explored while the gluconeogenic aspects of the cycle are emphasized. Concerns raised about anomalies of label distribution in glucose are considered. Here, other carbon metabolism pathways associated with the Calvin-Benson cycle are also described. Finally, there is a section describing the rift between Calvin and Benson.

rubisco↗
DOE OSTI2020

Proximity-based proteomics reveals the thylakoid lumen proteome in the cyanobacterium Synechococcus sp. PCC 7002

Abstract Cyanobacteria possess unique intracellular organization. Many proteomic studies have examined different features of cyanobacteria to learn about the intracellular structures and their respective functions. While these studies have made great progress in understanding cyanobacterial physiology, the conventional fractionation methods used to purify cellular structures have limitations; specifically, certain regions of cells cannot be purified with existing fractionation methods. Proximity-based proteomics techniques were developed to overcome the limitations of biochemical fractionation for proteomics. Proximity-based proteomics relies on spatiotemporal protein labeling followed by mass spectrometry of the labeled proteins to determine the proteome of the region of interest. We performed proximity-based proteomics in the cyanobacterium Synechococcus sp. PCC 7002 with the APEX2 enzyme, an engineered ascorbate peroxidase. We determined the proteome of the thylakoid lumen, a region of the cell that has remained challenging to study with existing methods, using a translational fusion between APEX2 and PsbU, a lumenal subunit of photosystem II. Our results demonstrate the power of APEX2 as a tool to study the cell biology of intracellular features and processes, including photosystem II assembly in cyanobacteria, with enhanced spatiotemporal resolution.

59 BASIC BIOLOGICAL SCIENCES↗