A Synthetic Gene Library Yields a Previously Unknown Glycoside Phosphorylase That Degrades and Assembles Poly-β-1,3-GlcNAc, Completing the Suite of β-Linked GlcNAc Polysaccharides
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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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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A Cell-Permeant Nanobody-Based Degrader That Induces Fetal Hemoglobin
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59 BASIC BIOLOGICAL SCIENCES↗
Real-Time Multistep Asymmetrical Disassembly of Nucleosomes and Chromatosomes Visualized by High-Speed Atomic Force Microscopy
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59 BASIC BIOLOGICAL SCIENCES↗
Experimental and Computational Evaluation of Nicotinamide Cofactor Biomimetics
Oxidoreductase enzymes are widely used biocatalysts due to their high enantioselectivity and broad substrate compatibility in useful transformations. Many oxidoreductases require nicotinamide cofactors (i.e., NAD(P)H). To replace this costly natural cofactor, synthetic nicotinamide cofactor biomimetics (NCBs) offer different shapes, binding affinities, and reducing potentials that exceed the capabilities of wild-type NAD(P)H. However, the ill-defined structure–activity relationships (SARs) of various NCBs slow rationally guided innovation, such as customized reducing potentials. Here, we dissect two essential elements of NCB design, holding the nicotinamide invariant. First, the linker length between the nicotinamide and an unconjugated aromatic ring uncovered unexpected benefits to redox activity for two or three carbon linkers. Second, substitution on this unconjugated aryl group (Ring 2) might not be expected to affect activity. However, SAR trends demonstrate substantial benefits to reductive potential conferred by electron-donating functionalities on Ring 2. Furthermore, catalysis by two enzymes demonstrates enzyme-dependent tolerance or sensitivity to the NCB structures. Density functional theory (DFT) and computational modeling provide a theoretical framework to understand and build upon these observations. Ring 2 reaches up to the nicotinamide to stabilize its positive charge after oxidation through π–π stacking and charge transfer. Thus, the systematic examination of NCB’s stability, electrochemical redox potentials, and kinetics uncovers trends for the improved design of NCBs.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cyanobacterial Biofertilizer Production by Guanidine-Producing Enzymes
Cyanobacterial production of a biofertilizer shows promise as an environmentally benign alternative to conventional nitrogen fertilizers, reducing environmental and energy burdens through light-driven nitrogen and carbon fixation. One route to realizing the potential for a nitrogen-rich, slow-releasing biofertilizer involves the genetic engineering of cyanobacteria to produce guanidine. Recent advances have demonstrated enzymatic guanidine production in cyanobacteria, but an understanding of cyanobacterial guanidine metabolism is still limited. This Perspective highlights strategies and opportunities for cyanobacterial guanidine production in a Design−Build−Test−Learn cycle. Exploring new guanidine-producing enzymes via phylogenetics could expand candidate enzymes, while understanding the metabolism of substrates can identify constraints and opportunities in substrate utilization. Additionally, guanidine sensing and export are crucial areas of study to enable continuous fertilizer production and stable nitrogen flux. These strategies will guide the development of advanced nitrogen biofertilizer strategies for the agricultural sector.
09 BIOMASS FUELS↗
Targeted Growth Medium Dropouts Promote Aromatic Compound Synthesis in Crude E. coli Cell-Free Systems
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37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structure of the Wnt–Frizzled–LRP6 initiation complex reveals the basis for coreceptor discrimination
Wnt morphogens are critical for embryonic development and tissue regeneration. Canonical Wnts form ternary receptor complexes composed of tissue-specific Frizzled (Fzd) receptors together with the shared LRP5/6 coreceptors to initiate β-catenin signaling. The cryo-EM structure of a ternary initiation complex of an affinity-matured XWnt8–Frizzled8–LRP6 complex elucidates the basis of coreceptor discrimination by canonical Wnts by means of their N termini and linker domains that engage the LRP6 E1E2 domain funnels. Chimeric Wnts bearing modular linker “grafts” were able to transfer LRP6 domain specificity between different Wnts and enable non-canonical Wnt5a to signal through the canonical pathway. Synthetic peptides comprising the linker domain serve as Wnt-specific antagonists. The structure of the ternary complex provides a topological blueprint for the orientation and proximity of Frizzled and LRP6 within the Wnt cell surface signalosome.
59 BASIC BIOLOGICAL SCIENCES↗
Development of 2nd generation aminomethyl spectinomycins that overcome native efflux in Mycobacterium abscessus
Mycobacterium abscessus (Mab), a nontuberculous mycobacterial (NTM) species, is an emerging pathogen with high intrinsic drug resistance. Current standard-of-care therapy results in poor outcomes, demonstrating the urgent need to develop effective antimycobacterial regimens. Through synthetic modification of spectinomycin (SPC), we have identified a distinct structural subclass of N-ethylene linked aminomethyl SPCs (eAmSPCs) that are up to 64-fold more potent against Mab over the parent SPC. Mechanism of action and crystallography studies demonstrate that the eAmSPCs display a mode of ribosomal inhibition consistent with SPC. However, they exert their increased antimicrobial activity through enhanced accumulation, largely by circumventing efflux mechanisms. The N-ethylene linkage within this series plays a critical role in avoiding TetV-mediated efflux, as lead eAmSPC 2593 displays a mere fourfold susceptibility improvement against Mab ΔtetV, in contrast to the 64-fold increase for SPC. Even a minor shortening of the linkage by a single carbon, akin to 1st generation AmSPC 1950, results in a substantial increase in MICs and a 16-fold rise in susceptibility against Mab ΔtetV. These shifts suggest that longer linkages might modify the kinetics of drug expulsion by TetV, ultimately shifting the equilibrium towards heightened intracellular concentrations and enhanced antimicrobial efficacy. Furthermore, lead eAmSPCs were also shown to synergize with various classes of anti-Mab antibiotics and retain activity against clinical isolates and other mycobacterial strains. Encouraging pharmacokinetic profiles coupled with robust efficacy in Mab murine infection models suggest that eAmSPCs hold the potential to be developed into treatments for Mab and other NTM infections.
59 BASIC BIOLOGICAL SCIENCES↗
Novel symmetry-preserving neural network model for phylogenetic inference
Abstract Motivation Scientists world-wide are putting together massive efforts to understand how the biodiversity that we see on Earth evolved from single-cell organisms at the origin of life and this diversification process is represented through the Tree of Life. Low sampling rates and high heterogeneity in the rate of evolution across sites and lineages produce a phenomenon denoted “long branch attraction” (LBA) in which long nonsister lineages are estimated to be sisters regardless of their true evolutionary relationship. LBA has been a pervasive problem in phylogenetic inference affecting different types of methodologies from distance-based to likelihood-based. Results Here, we present a novel neural network model that outperforms standard phylogenetic methods and other neural network implementations under LBA settings. Furthermore, unlike existing neural network models in phylogenetics, our model naturally accounts for the tree isomorphisms via permutation invariant functions which ultimately result in lower memory and allows the seamless extension to larger trees. Availability and implementation We implement our novel theory on an open-source publicly available GitHub repository: https://github.com/crsl4/nn-phylogenetics.
59 BASIC BIOLOGICAL SCIENCES↗
kb_DRAM: annotation and metabolic profiling of genomes with DRAM in KBase
Microbial genome annotation is the process of identifying structural and functional elements in DNA sequences and subsequently attaching biological information to those elements. DRAM is a tool developed to annotate bacterial, archaeal, and viral genomes derived from pure cultures or metagenomes. DRAM goes beyond traditional annotation tools by distilling multiple gene annotations to genome level summaries of functional potential. Despite these benefits, a downside of DRAM is the requirement of large computational resources, which limits its accessibility. Further, it did not integrate with downstream metabolic modeling tools that require genome annotation. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated with the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point-and-click interface, as well as generate genome-scale metabolic models from DRAM annotations.
59 BASIC BIOLOGICAL SCIENCES↗
Thermodynamic Control of Activity Patterns in Cytoskeletal Networks
Biological materials, such as the actin cytoskeleton, exhibit remarkable structural adaptability to various external stimuli by consuming different amounts of energy. In this Letter, we use methods from large deviation theory to identify a thermodynamic control principle for structural transitions in a model cytoskeletal network. Specifically, we demonstrate that biasing the dynamics with respect to the work done by nonequilibrium components effectively renormalizes the interaction strength between such components, which can eventually result in a morphological transition. Further, our work demonstrates how a thermodynamic quantity can be used to renormalize effective interactions, which in turn can tune structure in a predictable manner, suggesting a thermodynamic principle for the control of cytoskeletal structure and dynamics.
59 BASIC BIOLOGICAL SCIENCES↗
HLA-Clus: HLA class I clustering based on 3D structure
In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository (https://github.com/yshen25/HLA-Clus).
59 BASIC BIOLOGICAL SCIENCES↗
Photosynthetic Antenna Research Center (PARC) (Final Report)
The Photosynthetic Antenna Research Center (PARC) was funded for five years (2009-2014) with the initial group of Energy Frontier Research Centers (EFRCs) by the U.S. Department of Energy. The PARC grant was then renewed for four more years (2014-2018). PARC was focused on basic scientific research aimed at elucidating the fundamental principles that underlie light harvesting and energy funneling in natural photosynthetic antennas and translating those principles into construction of biohybrid and bioinspired architectures to form the basis for next-generation systems for solar-energy conversion. PARC carried out high quality fundamental science on the path towards ambitious, visionary goals. The resources, infrastructure, and melding of scientific subdisciplines, techniques, and experiences made possible in PARC resulted in high risk but high reward and high impact research, enabling conceptual breakthroughs in light harvesting. PARC’s broad global vision was addressed through specific research and educational activities, and the legacy of intellectual and technical capacity that it built.
14 SOLAR ENERGY↗
Therapeutic targeting of membrane-associated proteins in central nervous system tumors
The activity of the most complex system, the central nervous system (CNS) is profoundly regulated by a huge number of membrane-associated proteins (MAP). A minor change stimulates immense chemical changes and the elicited response is organized by MAP, which acts as a receptor of that chemical or channel enabling the flow of ions. Slight changes in the activity or expression of these MAPs lead to severe consequences such as cognitive disorders, memory loss, or cancer. CNS tumors are heterogeneous in nature and hard-to-treat due to random mutations in MAPs; like as overexpression of EGFRvIII/TGFβR/VEGFR, change in adhesion molecules α5β3 integrin/SEMA3A, imbalance in ion channel proteins, etc. Extensive research is under process for developing new therapeutic approaches using these proteins such as targeted cytotoxic radiotherapy, drug-delivery, and prodrug activation, blocking of receptors like GluA1, developing viral vector against cell surface receptor. The combinatorial approach of these strategies along with the conventional one might be more potential. Henceforth, our review focuses on in-depth analysis regarding MAPs aiming for a better understanding for developing an efficient therapeutic approach for targeting CNS tumors.
60 APPLIED LIFE SCIENCES↗
Enzyme Complexes of Ptr4CL and PtrHCT Modulate Co-enzyme A Ligation of Hydroxycinnamic Acids for Monolignol Biosynthesis in Populus trichocarpa
Co-enzyme A (CoA) ligation of hydroxycinnamic acids by 4-coumaric acid:CoA ligase (4CL) is a critical step in the biosynthesis of monolignols. Perturbation of 4CL activity significantly impacts the lignin content of diverse plant species. In Populus trichocarpa, two well-studied xylem-specific Ptr4CLs (Ptr4CL3 and Ptr4CL5) catalyze the CoA ligation of 4-coumaric acid to 4-coumaroyl-CoA and caffeic acid to caffeoyl-CoA. Subsequently, two 4-hydroxycinnamoyl-CoA:shikimic acid hydroxycinnamoyl transferases (PtrHCT1 and PtrHCT6) mediate the conversion of 4-coumaroyl-CoA to caffeoyl-CoA. Here, we show that the CoA ligation of 4-coumaric and caffeic acids is modulated by Ptr4CL/PtrHCT protein complexes. Downregulation of PtrHCTs reduced Ptr4CL activities in the stem-differentiating xylem (SDX) of transgenic P. trichocarpa. The Ptr4CL/PtrHCT interactions were then validated in vivo using biomolecular fluorescence complementation (BiFC) and protein pull-down assays in P. trichocarpa SDX extracts. Enzyme activity assays using recombinant proteins of Ptr4CL and PtrHCT showed elevated CoA ligation activity for Ptr4CL when supplemented with PtrHCT. Numerical analyses based on an evolutionary computation of the CoA ligation activity estimated the stoichiometry of the protein complex to consist of one Ptr4CL and two PtrHCTs, which was experimentally confirmed by chemical cross-linking using SDX plant protein extracts and recombinant proteins. Based on these results, we propose that Ptr4CL/PtrHCT complexes modulate the metabolic flux of CoA ligation for monolignol biosynthesis during wood formation in P. trichocarpa.
59 BASIC BIOLOGICAL SCIENCES↗
Multi-Omics integration can be used to rescue metabolic information for some of the dark region of the Pseudomonas putida proteome
In every omics experiment, genes or their products are identified for which even state of the art tools are unable to assign a function. In the biotechnology chassis organism Pseudomonas putida, these proteins of unknown function make up 14% of the proteome. This missing information can bias analyses since these proteins can carry out functions which impact the engineering of organisms. As a consequence of predicting protein function across all organisms, function prediction tools generally fail to use all of the types of data available for any specific organism, including protein and transcript expression information. Additionally, the release of Alphafold predictions for all Uniprot proteins provides a novel opportunity for leveraging structural information. We constructed a bespoke machine learning model to predict the function of recalcitrant proteins of unknown function in Pseudomonas putida based on these sources of data, which annotated 1079 terms to 213 proteins. Among the predicted functions supplied by the model, we found evidence for a significant overrepresentation of nitrogen metabolism and macromolecule processing proteins. These findings were corroborated by manual analyses of selected proteins which identified, among others, a functionally unannotated operon that likely encodes a branch of the shikimate pathway.
60 APPLIED LIFE SCIENCES↗
Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma
Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.
60 APPLIED LIFE SCIENCES↗