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At least 127 records · Page 7

Mimicking Natural Photosynthesis: Designing Ultrafast Photosensitized Electron Transfer into Multiheme Cytochrome Protein Nanowires

Efficient nanomaterials for artificial photosynthesis require fast and robust unidirectional electron transfer (ET) from photosensitizers through charge-separation and accumulation units to redox-active catalytic sites. We explored the ultrafast time-scale limits of photo-induced charge transfer between a Ru(II)tris(bipyridine) derivative photosensitizer and PpcA, a 3-heme c-type cytochrome serving as a nanoscale biological wire. Four covalent attachment sites (K28C, K29C, K52C, and G53C) were engineered in PpcA enabling site-specific covalent labeling with expected donor-acceptor (DA) distances of 4–8 Å. X-ray scattering results demonstrated that mutations and chemical labeling did not disrupt the structure of the proteins. Time-resolved spectroscopy revealed three orders of magnitude difference in charge transfer rates for the systems with otherwise similar DA distances and the same number of covalent bonds separating donors and acceptors. All-atom molecular dynamics simulations provided additional insight into the structure-function requirements for ultrafast charge transfer and the requirement of van der Waals contact between aromatic atoms of photosensitizers and hemes in order to observe sub-nanosecond ET. This work demonstrates opportunities to utilize multi-heme c-cytochromes as frameworks for designing ultrafast light-driven ET into charge-accumulating biohybrid model systems, and ultimately for mimicking the photosynthetic paradigm of efficiently coupling ultrafast, light-driven electron transfer chemistry to multi-step catalysis within small, experimentally versatile photosynthetic biohybrid assemblies.

36 MATERIALS SCIENCE↗

Diffraction-quality, ultraflexible protein single crystals engineered with DNA

DNA-functionalized colloidal nanoparticles assemble through flexible, nanoscale DNA hybridization interactions that limit atomic-level structural order. Here, we report a valence-centric strategy that enables DNA-bonded, protein single crystals with unconventional mechanical properties. An octameric enzyme, glutarate L-2-hydroxylase, was site- and number-selectively conjugated with eight self-complementary single-stranded DNA, yielding octavalent molecular bonds. The resulting conjugate assembled into the designed body-centered tetragonal crystals that diffracted to 1.42- to 2.61-angstrom resolution, with contacts mediated by B-form DNA helices spanning 17 to 25 angstroms. Increasing oligonucleotide length induces anisotropic lattice expansion while preserving atomic periodicity, even with partial DNA occupancy. Mechanistic studies suggest that the dynamic motion of unhybridized DNA facilitates crystallization, analogous to fluctuating electron clouds in atomic bonding. Compared with native protein crystals, DNA-hybridized crystals are 23-fold softer. These results challenge the assumption that flexibility is incompatible with structural order and establish a programmable framework for biomolecular crystallization and nanomaterials engineering with atomic precision.

Han, Zhenyu [Department of Chemistry, Northwestern↗

Signal sequences target enzymes and structural proteins to bacterial microcompartments and are critical for microcompartment formation

ABSTRACT Spatial organization of pathway enzymes has emerged as a promising tool to address several challenges in metabolic engineering, such as flux imbalances and off-target product formation. Bacterial microcompartments (MCPs) are a spatial organization strategy used natively by many bacteria to encapsulate metabolic pathways that produce toxic, volatile intermediates. Several recent studies have focused on engineering MCPs to encapsulate heterologous pathways of interest, but how this engineering affects MCP assembly and function is poorly understood. In this study, we investigated the role of signal sequences, short domains that target proteins to the MCP core, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterized two novel Pdu signal sequences on the structural proteins PduM and PduB, which constitute the first report of metabolosome signal sequences on structural proteins rather than enzymes. We then explored the role of enzymatic and structural Pdu signal sequences on MCP assembly by deleting their encoding sequences from the genome alone and in combination. Deleting enzymatic signal sequences decreased the MCP formation, but this defect could be recovered in some cases by overexpressing genes encoding the knocked-out signal sequence fused to a heterologous protein. By contrast, deleting structural signal sequences caused similar defects to knocking out the genes encoding the full-length PduM and PduB proteins. Our results contribute to a growing understanding of how MCPs form and function in bacteria and provide strategies to mitigate assembly disruption when encapsulating heterologous pathways in MCPs. IMPORTANCE Spatially organizing biosynthetic pathway enzymes is a promising strategy to increase pathway throughput and yield. Bacterial microcompartments (MCPs) are proteinaceous organelles that many bacteria natively use as a spatial organization strategy to encapsulate niche metabolic pathways, providing significant metabolic benefits. Encapsulating heterologous pathways of interest in MCPs could confer these benefits to industrially relevant pathways. Here, we investigate the role of signal sequences, short domains that target proteins for encapsulation in MCPs, in the assembly of 1,2-propanediol utilization (Pdu) MCPs. We characterize two novel signal sequences on structural proteins, constituting the first Pdu signal sequences found on structural proteins rather than enzymes, and perform knockout studies to compare the impacts of enzymatic and structural signal sequences on MCP assembly. Our results demonstrate that enzymatic and structural signal sequences play critical but distinct roles in Pdu MCP assembly and provide design rules for engineering MCPs while minimizing disruption to MCP assembly.

Johnson, Elizabeth R. (ORCID:0000000179236881)↗

Experimental and Computational Insights into the Structural Dynamics of the Fc Fragment of IgG1 Subtype from Biosimilar VEGF‐Trap

The constant fragment (Fc) of the immunoglobulin G1 (IgG1) subtype is increasingly recognized as a crucial scaffold in the development of advanced therapeutics due to its enhanced specificity, efficacy, and extended half‐life. A prime example is VEGF‐Trap (Aflibercept), a recombinant fusion protein that merges the Fc region of the IgG1 subtype with the binding domains of vascular endothelial growth factor receptors (VEGFR)‐1 and VEGFR‐2. The Fc region's role in N‐glycosylation is particularly important, as it significantly influences protein stability. Herein, the first near‐physiological temperature structures of the N‐glycan‐bound Fc fragment of IgG1 subtype from a biosimilar VEGF‐Trap are presented, determined using the SPring‐8 Angstrom Compact free electron LAser (SACLA) and the Turkish Light Source (Turkish DeLight). Comparative analysis with cryogenic structures, including existing data, reveals alternate conformations within the glycan‐binding pocket. Furthermore, molecular dynamics simulations indicate the presence of a high degree of structural plasticity, explaining how the protein adapts its structure through conformational changes. The observed structural fluctuations/conformational changes demonstrate the effect of N‐glycans on protein stability. These findings offer new insights into the molecular basis of Fc‐mediated functions and provide valuable information for the design of next‐generation therapeutics.

60 APPLIED LIFE SCIENCES↗

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors↗

Mesoporous peptide frameworks engineered from crystallizable collagen-mimetic peptide amphiphiles

The rational design of porous frameworks with tunable pore dimensions and chemical functionalities is a critical step toward their implementation in diverse applications. While traditional porous materials are typically constructed from abiotic components, there is increasing interest in employing biologically derived building blocks (e.g., peptides and proteins) that offer unmatched structural and functional diversity. Here, we report the construction of crystalline mesoporous frameworks that are self-assembled from amphiphilic collagen-mimetic peptides. Comprehensive structural characterization via microscopy, spectroscopy, and computational techniques provides insights into the assembly packing model, in which hexagonally packed channels are interconnected by antiparallel-aligned collagen triple helices via hydrophobic and electrostatic interactions. Lastly, we demonstrate the functional potential of aCMP frameworks through the encapsulation of various molecular guests, including doxorubicin, an anti-cancer drug. Overall, this work establishes a class of mesoporous frameworks, derived from synthetically engineerable peptide conjugates, marking a significant step forward in broadening the architectural scope and application potential of peptide-based materials.

Perez, Anthony R↗

High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

59 BASIC BIOLOGICAL SCIENCES↗

Recombinant expression of computationally designed peptide-bundlemers in Escherichia coli

Computational design of fully artificial peptides is extensively researched by material scientists and engineers for the construction of novel nanostructures and biomaterials. Such design has yielded a peptide-based building block or bundlemer, a coiled coil peptide assembly that undergoes further physical-covalent interactions to form 1D, 2D and, potentially, 3D hierarchical assemblies and displays targeted and biomimetic material properties. Recombinant expression is a convenient, flexible tool to synthesize such artificial and modified peptides in large quantities while also enabling economical synthesis of isotopically labeled peptides and longer protein-like artificial peptides. This report describes the protocol for recombinant expression of a 31-amino acid, computationally designed bundlemer-forming peptide in Escherichia coli. Peptide yields of 10 mgs per liter of media were achieved which highlights complementary advantages of recombinant expression technique relative to conventional laboratory-scale synthesis, such as solid-phase peptide synthesis.

36 MATERIALS SCIENCE↗

Biofoundries: Principles, Tools, and Applications

This chapter aims to provide a broad overview of biofoundries and introduces the principles, concepts, and case studies. We first outline the underlying principles of the Design-Build-Test-Learn (DBTL) framework and the role of automation, digital integration, and standardization. The chapter then explores core biofoundry technologies including robotic liquid handlers, high-throughput analytical instruments, and digital infrastructure for data management and workflow scheduling. Case studies spanning DNA assembly, protein engineering, metabolic engineering, and mammalian cell culture demonstrate the practical applications of the biofoundries. Economic and societal impacts are assessed alongside current limitations. We discuss the emerging trends including artificial intelligence integration and cloud-based distributed facilities to highlight its potential for biotechnology and the bioeconomy.

Singh, Nilmani↗

Nanoparticle-Mediated Assembly of Peptoid Nanosheets Functionalized with Solid-Binding Proteins: Designing Heterostructures for Hierarchy

The fabrication of ordered architectures that intimately integrate polymer, protein and inorganic components remains difficult. Two promising building blocks to tackle this challenge are peptoids, peptide mimics capable of self-assembly into well-defined structures, and solid-binding peptides, which offer a biological path to controlled inorganic assembly. Here, we report on the synthesis of 3.3 nm-thick, thiol-reactive peptoid nanosheets from equimolar mixtures of unmodified and maleimide-derivatized versions of the Nbpe 6 Nce 6 oligomer, optimize the location of engineered cysteine residues in silica-binding derivatives of superfolder green fluorescent protein for maleimide conjugation, and react the two components to form proteinpeptoid hybrids exhibiting partial or uniform protein coverage on both of their sides. Using 10 nm silica nanoparticles, we trigger the stacking of these 2D structures into a multi-layer material comprised of alternating peptoid, protein and organic layers. This simple and modular approach to hierarchical hybrid synthesis should prove useful in bioimaging and photocatalysis applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Crystallography Reveals Metal‐Triggered Restructuring of β‐Hairpins

Abstract Metal binding to β‐sheets occurs in many metalloproteins and is also implicated in the pathology of Alzheimer's disease. De novo designed metallo‐β‐sheets have been pursued as models and mimics of these proteins. However, no crystal structures of canonical β‐sheet metallopeptides have yet been obtained, in stark contrast to many examples for ɑ‐helical metallopeptides, leading to a poor understanding for their chemistry. To address this, we have engineered tryptophan zippers, stable 12‐residue β‐sheet peptides, to bind Cu(II) ions and obtained crystal structures through single crystal X‐ray diffraction (SC‐XRD). We find that metal binding triggers several unexpected supramolecular assemblies that demonstrate the range of higher‐order structures available to metallo‐β‐sheets. Overall, these findings underscore the importance of crystallography in elucidating the rich structural landscape of metallo‐β‐sheet peptides.

Thuc Dang, Viet↗

Predicting the viability of beta-lactamase: How folding and binding free energies correlate with beta-lactamase fitness

One of the long-standing holy grails of molecular evolution has been the ability to predict an organism’s fitness directly from its genotype. With such predictive abilities in hand, researchers would be able to more accurately forecast how organisms will evolve and how proteins with novel functions could be engineered, leading to revolutionary advances in medicine and biotechnology. In this work, we assemble the largest reported set of experimental TEM-1 β-lactamase folding free energies and use this data in conjunction with previously acquired fitness data and computational free energy predictions to determine how much of the fitness of β-lactamase can be directly predicted by thermodynamic folding and binding free energies. We focus upon β-lactamase because of its long history as a model enzyme and its central role in antibiotic resistance. Based upon a set of 21 β-lactamase single and double mutants expressly designed to influence protein folding, we first demonstrate that modeling software designed to compute folding free energies such as FoldX and PyRosetta can meaningfully, although not perfectly, predict the experimental folding free energies of single mutants. Interestingly, while these techniques also yield sensible double mutant free energies, we show that they do so for the wrong physical reasons. We then go on to assess how well both experimental and computational folding free energies explain single mutant fitness. We find that folding free energies account for, at most, 24% of the variance in β-lactamase fitness values according to linear models and, somewhat surprisingly, complementing folding free energies with computationally-predicted binding free energies of residues near the active site only increases the folding-only figure by a few percent. This strongly suggests that the majority of β-lactamase’s fitness is controlled by factors other than free energies. Overall, our results shed a bright light on to what extent the community is justified in using thermodynamic measures to infer protein fitness as well as how applicable modern computational techniques for predicting free energies will be to the large data sets of multiply-mutated proteins forthcoming.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Biochemical Process Modeling and Simulation (BPMS)

The Biochemical Process Modeling and Simulation project aims to reduce the cost and time of research by applying theory, modeling, and simulation to the most relevant bottlenecks in the biochemical process. We use molecular modeling, quantum mechanics, metabolic modeling, fluid dynamics, and reaction-diffusion methods in close collaboration with pretreatment, hydrolysis, upgrading, and TEA. The project's outcomes are increased yields and efficiency of the biochemical process, added value to products, and reduced price of fuels by specifically targeting catalytic efficiency, reactor design, enzyme efficiency, and microbial design. We work closely with experimental projects to identify problems and iterate with experiments to find and refine solutions. By working with experimentalists, we decide on problems that can be solved with simulation that could otherwise not be solved or would take too long with experiment alone to reach BETO's targets. Over the years, we have produced solutions that have resulted in determining the most likely fatty-acid derivative for passive transport out of bacteria that upgrade biomass, and we have also designed enzyme mutations for enhanced lignin upgrading. Metabolic models have been developed to tune the activity of 2,3 butanediol production for the 2030 target. A computational method to deliver understanding of how complex omics data can be interpreted in the metabolic pathways of organisms used in the Agile Biofoundry. We have found methods to overcome specific barriers and continue to develop those methods. Our reactor studies have guided the design of both the microbes and reactors for aerobic and micro-aerobic production at all scales and have been instrumental in improving the accuracy of techno-economic analysis models. This project is essential in the process of selecting the final processes for 2030 SAF production targets. More specifically, recently, we have: 1) Predicted the strength of the basic structural interactions in commodity plastics to provide guidance for plastics upcycling strategies. 2) Developed computational tool to improve the characterization of lignin-derived compounds 3) Developed new methodologies to enable Machine Learning-based Directed Evolution for protein engineering. 4) Developed Machine Learning methods to predict protein promiscuity and mutations to further improve microbial and enzymatic driven processes and demonstrated the utility of ML approaches to engineering proteins from sparse experimental datasets. 5) Developed new methods to enable high-fidelity simulation of aerobic fermentation at industrial scale and resolving mismatch of time scales through subcycling/operator splitting 7) Identified the difficulty in preventing local high-oxygen conditions in industrial bubble columns, which leads to less-desirable acetoin production, suggesting future research directions in alternative reactor configurations (e.g loop reactors, shallow-channel reactors).

BIOMASS FUELS↗

Structure-Based Design and Antigenic Validation of Respiratory Syncytial Virus G Immunogens

Respiratory syncytial virus (RSV) is a leading cause of severe lower respiratory tract disease of children, the elderly, and immunocompromised individuals. Currently, there are no FDA-approved RSV vaccines. The RSV G glycoprotein is used for viral attachment to host cells and impairment of host immunity by interacting with the human chemokine receptor CX3CR1. Antibodies that disrupt this interaction are protective against infection and disease. Nevertheless, development of an RSV G vaccine antigen has been hindered by its low immunogenicity and safety concerns. A previous study described three engineered RSV G proteins containing single-point mutations that induce higher levels of IgG antibodies and have improved safety profiles compared to wild-type RSV G. However, it is unclear if the mutations affect RSV G protein folding and display of its conformational epitopes. In this study, we show that the RSV G S177Q protein retains high-affinity binding to protective human and mouse monoclonal antibodies and has equal reactivity as wild-type RSV G protein to human reference immunoglobulin to RSV. Additionally, we determined the high-resolution crystal structure of RSV G S177Q protein in complex with the anti-RSV G antibody 3G12, further validating its antigenic structure. These studies show for the first time that an engineered RSV G protein with increased immunogenicity and safety retains conformational epitopes to high-affinity protective antibodies, supporting its further development as an RSV vaccine immunogen. Respiratory syncytial virus (RSV) causes severe lower respiratory diseases of children, the elderly, and immunocompromised populations. There currently are no FDA-approved RSV vaccines. Most vaccine development efforts have focused on the RSV F protein, and the field has generally overlooked the receptor-binding antigen RSV G due to its poor immunogenicity and safety concerns. However, single-point mutant RSV G proteins have been previously identified that have increased immunogenicity and safety. In this study, we investigate the antibody reactivities of three known RSV G mutant proteins. We show that one mutant RSV G protein retains high-affinity binding to protective monoclonal antibodies, is equally recognized by anti-RSV antibodies in human sera, and forms the same three-dimensional structure as the wild-type RSV G protein. Our study validates the structure-guided design of the RSV G protein as an RSV vaccine antigen.

59 BASIC BIOLOGICAL SCIENCES↗

Three-dimensional structure-guided evolution of a ribosome with tethered subunits

We report RNA-based macromolecular machines, such as the ribosome, have functional parts reliant on structural interactions spanning sequence-distant regions. These features limit evolutionary exploration of mutant libraries and confound three-dimensional structure-guided design. To address these challenges, we describe Evolink (evolution and linkage), a method that enables high-throughput evolution of sequence-distant regions in large macromolecular machines, and library design guided by computational RNA modeling to enable exploration of structurally stable designs. Using Evolink, we evolved a tethered ribosome with a 58% increased activity in orthogonal protein translation and a 97% improvement in doubling times in SQ171 cells compared to a previously developed tethered ribosome, and reveal new permissible sequences in a pair of ribosomal helices with previously explored biological function. The Evolink approach may enable enhanced engineering of macromolecular machines for new and improved functions for synthetic biology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Expanding the synthetic biology toolbox of Cupriavidus necator for establishing fatty acid production

Abstract The Gram-negative betaproteobacterium Cupriavidus necator is a chemolithotroph that can convert carbon dioxide into biomass. Cupriavidus necator has been engineered to produce a variety of high-value chemicals in the past. However, there is still a lack of a well-characterized toolbox for gene expression and genome engineering. Development and optimization of biosynthetic pathways in metabolically engineered microorganisms necessitates control of gene expression via functional genetic elements such as promoters, ribosome binding sites (RBSs), and codon optimization. In this work, a set of inducible and constitutive promoters were validated and characterized in C. necator, and a library of RBSs was designed and tested to show a 50-fold range of expression for green fluorescent protein (gfp). The effect of codon optimization on gene expression in C. necator was studied by expressing gfp and mCherry genes with varied codon-adaptation indices and was validated by expressing codon-optimized variants of a C12-specific fatty acid thioesterase to produce dodecanoic acid. We discuss further hurdles that will need to be overcome for C. necator to be widely used for biosynthetic processes.

59 BASIC BIOLOGICAL SCIENCES↗

The potential of bacterial microcompartment architectures for phytonanotechnology

The application of nanotechnology to plants, termed phytonanotechnology, has the potential to revolutionize plant research and agricultural production. Advancements in phytonanotechnology will allow for the time-controlled and target-specific release of bioactive compounds and agrochemicals to alter and optimize conventional plant production systems. A diverse range of engineered nanoparticles with unique physiochemical properties is currently being investigated to determine their suitability for plants. Improvements in crop yield, disease resistance and nutrient and pesticide management are all possible using designed nanocarriers. However, despite these prospective benefits, research to thoroughly understand the precise activity, localization and potential phytotoxicity of these nanoparticles within plant systems is required. Protein-based bacterial microcompartment shell proteins that self-assemble into spherical shells, nanotubes and sheets could be of immense value for phytonanotechnology due to their ease of manipulation, multifunctionality, rapid and efficient producibility and biodegradability. Here in this review, we explore bacterial microcompartment-based architectures within the scope of phytonanotechnology.

59 BASIC BIOLOGICAL SCIENCES↗