Observing the Dynamics of an Electrochemically Driven Active Material with Liquid Electron Microscopy.

Electrochemical liquid electron microscopy has revolutionized our understanding of nanomaterial dynamics by allowing for direct observation of their electrochemical production. This technique, primarily applied to inorganic materials, is now being used to explore the self-assembly dynamics of active molecular materials. Our study examines these dynamics across various scales, from the nanoscale behavior of individual fibers to the micrometer-scale hierarchical evolution of fiber clusters. To isolate the influences of the electron beam and electrical potential on material behavior, we conducted thorough beam-sample interaction analyses. Our findings reveal that the dynamics of these active materials at the nanoscale are shaped by their proximity to the electrode and the applied electrical current. By integrating electron microscopy observations with reaction-diffusion simulations, we uncover that local structures and their formation history play a crucial role in determining assembly rates. This suggests that the emergence of nonequilibrium structures can locally accelerate further structural development, offering insights into the behavior of active materials under electrochemical conditions.

Correlating electrochemical stimulus to structural change in liquid electron microscopy videos using the structural dissimilarity metric.

In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.

Decoding the metabolic response of Escherichia coli for sensing trace heavy metals in water.

Heavy metal contamination due to industrial and agricultural waste represents a growing threat to water supplies. Frequent and widespread monitoring for toxic metals in drinking and agricultural water sources is necessary to prevent their accumulation in humans, plants, and animals, which results in disease and environmental damage. Here, the metabolic stress response of bacteria is used to report the presence of heavy metal ions in water by transducing ions into chemical signals that can be fingerprinted using machine learning analysis of vibrational spectra. Surface-enhanced Raman scattering surfaces amplify chemical signals from bacterial lysate and rapidly generate large, reproducible datasets needed for machine learning algorithms to decode the complex spectral data. Classification and regression algorithms achieve limits of detection of 0.5 pM for As3+ and 6.8 pM for Cr6+, 100,000 times lower than the World Health Organization recommended limits, and accurately quantify concentrations of analytes across six orders of magnitude, enabling early warning of rising contaminant levels. Trained algorithms are generalizable across water samples with different impurities; water quality of tap water and wastewater was evaluated with 92% accuracy.

Structure of Geobacter OmcZ filaments suggests extracellular cytochrome polymers evolved independently multiple times.

While early genetic and low-resolution structural observations suggested that extracellular conductive filaments on metal-reducing organisms such as Geobacter were composed of type IV pili, it has now been established that bacterial c-type cytochromes can polymerize to form extracellular filaments capable of long-range electron transport. Atomic structures exist for two such cytochrome filaments, formed from the hexaheme cytochrome OmcS and the tetraheme cytochrome OmcE. Due to the highly conserved heme packing within the central OmcS and OmcE cores, and shared pattern of heme coordination between subunits, it has been suggested that these polymers have a common origin. We have now used cryo-electron microscopy (cryo-EM) to determine the structure of a third extracellular filament, formed from the Geobacter sulfurreducens octaheme cytochrome, OmcZ. In contrast to the linear heme chains in OmcS and OmcE from the same organism, the packing of hemes, heme:heme angles, and between-subunit heme coordination is quite different in OmcZ. A branched heme arrangement within OmcZ leads to a highly surface exposed heme in every subunit, which may account for the formation of conductive biofilm networks, and explain the higher measured conductivity of OmcZ filaments. This new structural evidence suggests that conductive cytochrome polymers arose independently on more than one occasion from different ancestral multiheme proteins.

Cryo-EM structure of an extracellular Geobacter OmcE cytochrome filament reveals tetrahaem packing.

Electrically conductive appendages from the anaerobic bacterium Geobacter sulfurreducens were first observed two decades ago, with genetic and biochemical data suggesting that conductive fibres were type IV pili. Recently, an extracellular conductive filament of G. sulfurreducens was found to contain polymerized c-type cytochrome OmcS subunits, not pilin subunits. Here we report that G. sulfurreducens also produces a second, thinner appendage comprised of cytochrome OmcE subunits and solve its structure using cryo-electron microscopy at ~4.3 Å resolution. Although OmcE and OmcS subunits have no overall sequence or structural similarities, upon polymerization both form filaments that share a conserved haem packing arrangement in which haems are coordinated by histidines in adjacent subunits. Unlike OmcS filaments, OmcE filaments are highly glycosylated. In extracellular fractions from G. sulfurreducens, we detected type IV pili comprising PilA-N and -C chains, along with abundant B-DNA. OmcE is the second cytochrome filament to be characterized using structural and biophysical methods. We propose that there is a broad class of conductive bacterial appendages with conserved haem packing (rather than sequence homology) that enable long-distance electron transport to chemicals or other microbial cells.

Electrically Fueled Active Supramolecular Materials.

Fuel-driven dissipative self-assemblies play essential roles in living systems, contributing both to their complex, dynamic structures and emergent functions. Several dissipative supramolecular materials have been created using chemicals or light as fuel. However, electrical energy, one of the most common energy sources, has remained unexplored for such purposes. Here, we demonstrate a new platform for creating active supramolecular materials using electrically fueled dissipative self-assembly. Through an electrochemical redox reaction network, a transient and highly active supramolecular assembly is achieved with rapid kinetics, directionality, and precise spatiotemporal control. As electronic signals are the default information carriers in modern technology, the described approach offers a potential opportunity to integrate active materials into electronic devices for bioelectronic applications.

Roadmap on emerging concepts in the physical biology of bacterial biofilms: from surface sensing to community formation.

Bacterial biofilms are communities of bacteria that exist as aggregates that can adhere to surfaces or be free-standing. This complex, social mode of cellular organization is fundamental to the physiology of microbes and often exhibits surprising behavior. Bacterial biofilms are more than the sum of their parts: single-cell behavior has a complex relation to collective community behavior, in a manner perhaps cognate to the complex relation between atomic physics and condensed matter physics. Biofilm microbiology is a relatively young field by biology standards, but it has already attracted intense attention from physicists. Sometimes, this attention takes the form of seeing biofilms as inspiration for new physics. In this roadmap, we highlight the work of those who have taken the opposite strategy: we highlight the work of physicists and physical scientists who use physics to engage fundamental concepts in bacterial biofilm microbiology, including adhesion, sensing, motility, signaling, memory, energy flow, community formation and cooperativity. These contributions are juxtaposed with microbiologists who have made recent important discoveries on bacterial biofilms using state-of-the-art physical methods. The contributions to this roadmap exemplify how well physics and biology can be combined to achieve a new synthesis, rather than just a division of labor.

Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing.

Rapid antimicrobial susceptibility testing (AST) is an integral tool to mitigate the unnecessary use of powerful and broad-spectrum antibiotics that leads to the proliferation of multi-drug-resistant bacteria. Using a sensor platform composed of surface-enhanced Raman scattering (SERS) sensors with control of nanogap chemistry and machine learning algorithms for analysis of complex spectral data, bacteria metabolic profiles post antibiotic exposure are correlated with susceptibility. Deep neural network models are able to discriminate the responses of Escherichia coli and Pseudomonas aeruginosa to antibiotics from untreated cells in SERS data in 10 min after antibiotic exposure with greater than 99% accuracy. Deep learning analysis is also able to differentiate responses from untreated cells with antibiotic dosages up to 10-fold lower than the minimum inhibitory concentration observed in conventional growth assays. In addition, analysis of SERS data using a generative model, a variational autoencoder, identifies spectral features in the P. aeruginosa lysate data associated with antibiotic efficacy. From this insight, a combinatorial dataset of metabolites is selected to extend the latent space of the variational autoencoder. This culture-free dataset dramatically improves classification accuracy to select effective antibiotic treatment in 30 min. Unsupervised Bayesian Gaussian mixture analysis achieves 99.3% accuracy in discriminating between susceptible versus resistant to antibiotic cultures in SERS using the extended latent space. Discriminative and generative models rapidly provide high classification accuracy with small sets of labeled data, which enormously reduces the amount of time needed to validate phenotypic AST with conventional growth assays. Thus, this work outlines a promising approach toward practical rapid AST.

Structural Determination of a Filamentous Chaperone to Fabricate Electronically Conductive Metalloprotein Nanowires.

The transfer of electrons through protein complexes is central to cellular respiration. Exploiting proteins for charge transfer in a controllable fashion has the potential to revolutionize the integration of biological systems and electronic devices. Here we characterize the structure of an ultrastable protein filament and engineer the filament subunits to create electronically conductive nanowires under aqueous conditions. Cryoelectron microscopy was used to resolve the helical structure of gamma-prefoldin, a filamentous protein from a hyperthermophilic archaeon. Conjugation of tetra-heme c3-type cytochromes along the longitudinal axis of the filament created nanowires capable of long-range electron transfer. Electrochemical transport measurements indicated networks of the nanowires capable of conducting current between electrodes at the redox potential of the cytochromes. Functionalization of these highly engineerable nanowires with other molecules, such as redox enzymes, may be useful for bioelectronic applications.

Surface-Enhanced Raman Scattering-Based Odor Compass: Locating Multiple Chemical Sources and Pathogens.

Olfaction is important for identifying and avoiding toxic substances in living systems. Many efforts have been made to realize artificial olfaction systems that reflect the capacity of biological systems. A sophisticated example of an artificial olfaction device is the odor compass which uses chemical sensor data to identify odor source direction. Successful odor compass designs often rely on plume-based detection and mobile robots, where active, mechanical motion of the sensor platform is employed. Passive, diffusion-based odor compasses remain elusive as detection of low analyte concentrations and quantification of small concentration gradients from within the sensor platform are necessary. Further, simultaneously identifying multiple odor sources using an odor compass remains an ongoing challenge, especially for similar analytes. Here, we show that surface-enhanced Raman scattering (SERS) sensors overcome these challenges, and we present the first SERS odor compass. Using a grid array of SERS sensors, machine learning analysis enables reliable identification of multiple odor sources arising from diffusion of analytes from one or two localized sources. Specifically, convolutional neural network and support vector machine classifier models achieve over 90% accuracy for a multiple odor source problem. This system is then used to identify the location of an Escherichia coli biofilm via its complex signature of volatile organic compounds. Thus, the fabricated SERS chemical sensors have the needed limit of detection and quantification for diffusion-based odor compasses. Solving the multiple odor source problem with a passive platform opens a path toward an Internet of things approach to monitor toxic gases and indoor pathogens.

Structure of Microbial Nanowires Reveals Stacked Hemes that Transport Electrons over Micrometers.

Long-range (>10 µm) transport of electrons along networks of Geobacter sulfurreducens protein filaments, known as microbial nanowires, has been invoked to explain a wide range of globally important redox phenomena. These nanowires were previously thought to be type IV pili composed of PilA protein. Here, we report a 3.7 Å resolution cryoelectron microscopy structure, which surprisingly reveals that, rather than PilA, G. sulfurreducens nanowires are assembled by micrometer-long polymerization of the hexaheme cytochrome OmcS, with hemes packed within ∼3.5-6 Å of each other. The inter-subunit interfaces show unique structural elements such as inter-subunit parallel-stacked hemes and axial coordination of heme by histidines from neighboring subunits. Wild-type OmcS filaments show 100-fold greater conductivity than other filaments from a ΔomcS strain, highlighting the importance of OmcS to conductivity in these nanowires. This structure explains the remarkable capacity of soil bacteria to transport electrons to remote electron acceptors for respiration and energy sharing.

Electrical Conductivity, Selective Adhesion, and Biocompatibility in Bacteria-Inspired Peptide-Metal Self-Supporting Nanocomposites.

Bacterial type IV pili (T4P) are polymeric protein nanofibers that have diverse biological roles. Their unique physicochemical properties mark them as a candidate biomaterial for various applications, yet difficulties in producing native T4P hinder their utilization. Recent effort to mimic the T4P of the metal-reducing Geobacter sulfurreducens bacterium led to the design of synthetic peptide building blocks, which self-assemble into T4P-like nanofibers. Here, it is reported that the T4P-like peptide nanofibers efficiently bind metal oxide particles and reduce Au ions analogously to their native counterparts, and thus give rise to versatile and multifunctional peptide-metal nanocomposites. Focusing on the interaction with Au ions, a combination of experimental and computational methods provides mechanistic insight into the formation of an exceptionally dense Au nanoparticle (AuNP) decoration of the nanofibers. Characterization of the thus-formed peptide-AuNPs nanocomposite reveals enhanced thermal stability, electrical conductivity from the single-fiber level up, and substrate-selective adhesion. Exploring its potential applications, it is demonstrated that the peptide-AuNPs nanocomposite can act as a reusable catalytic coating or form self-supporting immersible films of desired shapes. The films scaffold the assembly of cardiac cells into synchronized patches, and present static charge detection capabilities at the macroscale. The study presents a novel T4P-inspired biometallic material.

Going the Distance: Long-Range Conductivity in Protein and Peptide Bioelectronic Materials.

Bioelectronic materials interface biomolecules, cells, organs, or organisms with electronic devices, and they represent an active and growing field of materials research. Protein and peptide nanostructures are ideal bioelectronic materials. They possess many of the properties required for biocompatibility across scales from enzymatic to organismal interfaces, and recent examples of supramolecular protein and peptide nanostructures exhibit impressive electronic properties. The ability of such natural and synthetic protein and peptide materials to conduct electricity over micrometer to centimeter length scales, however, is not readily understood from a conventional view of their amino acid building blocks. Distinct in structure and properties from solid-state inorganic and synthetic organic metals and semiconductors, supramolecular conductive proteins and peptides require careful theoretical treatment and experimental characterization methods to understand their electronic structure. In this review, we discuss theory and experimental evidence from recent literature describing the long-range conduction of electronic charge in protein and peptide materials. Electron transfer across proteins has been studied extensively, but application of models for such short-range charge transport to longer distances relevant to bioelectronic materials are less well-understood. Implementation of electronic band structure and electron transfer formulations in extended biomolecular systems will be covered in the context of recent materials discoveries and efforts at characterization of electronic transport mechanisms.

Amino-acid-encoded biocatalytic self-assembly enables the formation of transient conducting nanostructures.

Aqueous compatible supramolecular materials hold promise for applications in environmental remediation, energy harvesting and biomedicine. One remaining challenge is to actively select a target structure from a multitude of possible options, in response to chemical signals, while maintaining constant, physiological conditions. Here, we demonstrate the use of amino acids to actively decorate a self-assembling core molecule in situ, thereby controlling its amphiphilicity and consequent mode of assembly. The core molecule is the organic semiconductor naphthalene diimide, functionalized with D- and L- tyrosine methyl esters as competing reactive sites. In the presence of α-chymotrypsin and a selected encoding amino acid, kinetic competition between ester hydrolysis and amidation results in covalent or non-covalent amino acid incorporation, and variable supramolecular self-assembly pathways. Taking advantage of the semiconducting nature of the naphthalene diimide core, electronic wires could be formed and subsequently degraded, giving rise to temporally regulated electro-conductivity.

Conformations of peptoids in nanosheets result from the interplay of backbone energetics and intermolecular interactions.

The conformations adopted by the molecular constituents of a supramolecular assembly influence its large-scale order. At the same time, the interactions made in assemblies by molecules can influence their conformations. Here we study this interplay in extended flat nanosheets made from nonnatural sequence-specific peptoid polymers. Nanosheets exist because individual polymers can be linear and untwisted, by virtue of polymer backbone elements adopting alternating rotational states whose twists oppose and cancel. Using molecular dynamics and quantum mechanical simulations, together with experimental data, we explore the design space of flat nanostructures built from peptoids. We show that several sets of peptoid backbone conformations are consistent with their being linear, but the specific combination observed in experiment is determined by a combination of backbone energetics and the interactions made within the nanosheet. Our results provide a molecular model of the peptoid nanosheet consistent with all available experimental data and show that its structure results from a combination of intra- and intermolecular interactions.

Electronic Conductivity in Biomimetic α-Helical Peptide Nanofibers and Gels.

Examples of long-range electronic conductivity are rare in biological systems. The observation of micrometer-scale electronic transport through protein wires produced by bacteria is therefore notable, providing an opportunity to study fundamental aspects of conduction through protein-based materials and natural inspiration for bioelectronics materials. Borrowing sequence and structural motifs from these conductive protein fibers, we designed self-assembling peptides that form electronically conductive nanofibers under aqueous conditions. Conductivity in these nanofibers is distinct for two reasons: first, they support electron transport over distances orders of magnitude greater than expected for proteins, and second, the conductivity is mediated entirely by amino acids lacking extended conjugation, π-stacking, or redox centers typical of existing organic and biohybrid semiconductors. Electrochemical transport measurements show that the fibers support ohmic electronic transport and a metallic-like temperature dependence of conductance in aqueous buffer. At higher solution concentrations, the peptide monomers form hydrogels, and comparisons of the structure and electronic properties of the nanofibers and gels highlight the critical roles of α-helical secondary structure and supramolecular ordering in supporting electronic conductivity in these materials. These findings suggest a structural basis for long-range electronic conduction mechanisms in peptide and protein biomaterials.

Longitudinal Monitoring of Biofilm Formation via Robust Surface-Enhanced Raman Scattering Quantification of Pseudomonas aeruginosa-Produced Metabolites.

Detection of bacterial metabolites at low concentrations in fluids with complex background allows for applications ranging from detecting biomarkers of respiratory infections to identifying contaminated medical instruments. Surface-enhanced Raman scattering (SERS) spectroscopy, when utilizing plasmonic nanogaps, has the relatively unique capacity to reach trace molecular detection limits in a label-free format, yet large-area device fabrication incorporating nanogaps with this level of performance has proven difficult. Here, we demonstrate the advantages of using chemical assembly to fabricate SERS surfaces with controlled nanometer gap spacings between plasmonic nanospheres. Control of nanogap spacings via the length of the chemical crosslinker provides uniform SERS signals, exhibiting detection of pyocyanin, a secondary metabolite of Pseudomonas aeruginosa, in aqueous media at concentration of 100 pg·mL-1. When using machine learning algorithms to analyze the SERS data of the conditioned medium from a bacterial culture, having a more complex background, we achieve 1 ng·mL-1 limit of detection of pyocyanin and robust quantification of concentration spanning 5 orders of magnitude. Nanogaps are also incorporated in an in-line microfluidic device, enabling longitudinal monitoring of P. aeruginosa biofilm formation via rapid pyocyanin detection in a medium effluent as early as 3 h after inoculation and quantification in under 9 h. Surface-attached bacteria exposed to a bactericidal antibiotic were differentially less susceptible after 10 h of growth, indicating that these devices may be useful for early intervention of bacterial infections.

Correction: Geobacter sulfurreducens pili support ohmic electronic conduction in aqueous solution.

Correction for 'Geobacter sulfurreducens pili support ohmic electronic conduction in aqueous solution' by Nicole L. Ing et al., Phys. Chem. Chem. Phys., 2017, 19, 21791-21799.

Driving Chemical Reactions in Plasmonic Nanogaps with Electrohydrodynamic Flow.

Nanoparticles from colloidal solution-with controlled composition, size, and shape-serve as excellent building blocks for plasmonic devices and metasurfaces. However, understanding hierarchical driving forces affecting the geometry of oligomers and interparticle gap spacings is still needed to fabricate high-density architectures over large areas. Here, electrohydrodynamic (EHD) flow is used as a long-range driving force to enable carbodiimide cross-linking between nanospheres and produces oligomers exhibiting sub-nanometer gap spacing over mm2 areas. Anhydride linkers between nanospheres are observed via surface-enhanced Raman scattering (SERS) spectroscopy. The anhydride linkers are cleavable via nucleophilic substitution and enable placement of nucleophilic molecules in electromagnetic hotspots. Atomistic simulations elucidate that the transient attractive force provided by EHD flow is needed to provide a sufficient residence time for anhydride cross-linking to overcome slow reaction kinetics. This synergistic analysis shows assembly involves an interplay between long-range driving forces increasing nanoparticle-nanoparticle interactions and probability that ligands are in proximity to overcome activation energy barriers associated with short-range chemical reactions. Absorption spectroscopy and electromagnetic full-wave simulations show that variations in nanogap spacing have a greater influence on optical response than variations in close-packed oligomer geometry. The EHD flow-anhydride cross-linking assembly method enables close-packed oligomers with uniform gap spacings that produce uniform SERS enhancement factors. These results demonstrate the efficacy of colloidal driving forces to selectively enable chemical reactions leading to future assembly platforms for large-area nanodevices.

The Phe-Ile Zipper: A Specific Interaction Motif Drives Antiparallel Coiled-Coil Hexamer Formation.

Coiled coils are a robust motif for exploring amino acid interactions, generating unique supramolecular structures, and expanding the functional properties of biological materials. A recently discovered antiparallel coiled-coil hexamer (ACC-Hex, peptide 1) exhibits a unique interaction in which Phe and Ile residues from adjacent α-helices interact to form a Phe-Ile zipper within the hydrophobic core. Analysis of the X-ray crystallographic structure of ACC-Hex suggests that the stability of the six-helix bundle relies on specific interactions between the Phe and Ile residues. The Phe-Ile zipper is unprecedented and represents a powerful tool for utilizing the Phe-Ile interactions to direct supramolecular assembly. To further probe and understand the limits of the Phe-Ile zipper, we designed peptide sequences with natural and unnatural amino acids placed at the Phe and Ile residue positions. Using size exclusion chromatography and small-angle X-ray scattering, we found that the proper assembly of ACC-Hex from monomers is sensitive to subtle changes in side chain steric bulk and hydrophobicity introduced by mutations at the Phe and Ile residue positions. Of the sequence variants that formed ACC-Hex, mutations in the hydrophobic core significantly affected the stability of the hexamer, from a ΔGuw of 2-8 kcal mol-1. Additional sequences were designed to further probe and enhance the stability of the ACC-Hex system by maximizing salt bridging between the solvent-exposed residues. Finally, we expanded on the generality of the Phe-Ile zipper, creating a unique sequence that forms an antiparallel hexamer that is topologically similar to ACC-Hex but atomistically unique.