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At least 19 records

Down-selection of biomolecules to assemble “reverse micelle” with perovskites

Abstract Biological molecule-semiconductor interfacing has triggered numerous opportunities in applied physics such as bio-assisted data storage and computation, brain-computer interface, and advanced distributed bio-sensing. The introduction of electronics into biological embodiment is being quickly developed as it has great potential in providing adaptivity and improving functionality. Reciprocally, introducing biomaterials into semiconductors to manifest bio-mimetic functionality is impactful in triggering new enhanced mechanisms. In this study, we utilize the vulnerable perovskite semiconductors as a platform to understand if certain types of biomolecules can regulate the lattice and endow a unique mechanism for stabilizing the metastable perovskite lattice. Three tiers of biomolecules have been systematically tested and the results reveal a fundamental mechanism for the formation of a “reverse-micelle” structure. Systematic exploration of a large set of biomolecules led to the discovery of guiding principle for down-selection of biomolecules which extends the classic emulsion theory to this hybrid systems. Results demonstrate that by introducing biomaterials into semiconductors, natural phenomena typically observed in biological systems can also be incorporated into semiconducting crystals, providing a new perspective to engineer existing synthetic materials.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanical Properties of a Solvated Biomolecule: RGD (1FUV) Peptide

The mechanical properties of proteins/peptides play an essential role in their functionalities and implications, as well as their structure and dynamic properties. Understanding mechanical properties is pivotal to our knowledge of protein folding and the molecular basis of diverse cellular processes. Herein, we present a computational approach using ab initio quantum mechanical calculations to determine the mechanical properties—such as bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio—of a solvated Arg-Gly-Asp (RGD) peptide model. Since this peptide serves as the RGD-directed integrin recognition site and may participate in cellular adhesion, it is considered a promising small peptide for medicinal applications. This successful approach paves the way for investigating larger and more complex biomolecules.

Biochemistry & Molecular Biology↗

Using Vertically Aligned Carbon Nanofiber Arrays on Rigid or Flexible Substrates for Delivery of Biomolecules and Dyes to Plants

The delivery of biomolecules and impermeable dyes to intact plants is a major challenge. Nanomaterials are up-and-coming tools for the delivery of DNA to plants. As exciting as these new tools are, they have yet to be widely applied. Nanomaterials fabricated on rigid substrate (backing) are particularly difficult to successfully apply to curved plant structures. This study describes the process for microfabricating vertically aligned carbon nanofiber arrays and transferring them from a rigid to a flexible substrate. We detail and demonstrate how these fibers (on either rigid or flexible substrates) can be used for transient transformation or dye (e.g., fluorescein) delivery to plants. We show how VACNFs can be transferred from rigid silicon substrate to a flexible SU-8 epoxy substrate to form flexible VACNF arrays. Further, to overcome the hydrophobic nature of SU-8, fibers in the flexible film were coated with a thin silicon oxide layer (2-3 nm). To use these fibers for delivery to curved plant organs, we deposit a 1 µL droplet of dye or DNA solution on the fiber side of VACNF films, wait 10 min, place the films on the plant organ and employ a swab with a rolling motion to drive fibers into plant cells. With this method, we have achieved dye and DNA delivery in plant organs with curved surfaces.

59 BASIC BIOLOGICAL SCIENCES↗

DancePartner: Python Package to Mine Multiomics Relationship Networks from Literature and Databases

A goal of multi-omics experiments is to understand how mechanistic molecular biology is altered between conditions, typically a control group and experimental groups. Oftentimes this involves studying changes in biomolecule relationships (e.g. interactions, metabolic relationships) of several types of biomolecules (e.g. proteins, lipids, metabolites). Though several databases contain relationships between biomolecules, understudied species may have little to no relationship information in databases and thus must be mined from literature. There are several challenges to literature mining, including automated full-text extraction, duplicate biomolecule term collapsing, and implementing complex machine learning tools. To make relationship extraction more accessible to the community, a python package called DancePartner was developed to allow for the extraction of relationships from literature and databases, with functions to map biomolecule synonyms to standardized identifiers and visualize and characterize the resulting multi-omics network. Here, in this study, an example dataset involving Caenorhabditis elegans is presented, where relationships are mined from 1443 publications using DancePartner. These relationships are combined with relationships from KEGG, WikiPathways, UniProt, and LipidMaps, and visualized.

BERT↗

Spatially confined protein assembly in hierarchical mesoporous metal-organic framework

Immobilization of biomolecules into porous materials could lead to significantly enhanced performance in terms of stability towards harsh reaction conditions and easier separation for their reuse. Metal-Organic Frameworks (MOFs), offering unique structural features, have emerged as a promising platform for immobilizing large biomolecules. Although many indirect methods have been used to investigate the immobilized biomolecules for diverse applications, understanding their spatial arrangement in the pores of MOFs is still preliminary due to the difficulties in directly monitoring their conformations. To gain insights into the spatial arrangement of biomolecules within the nanopores. We used in situ small-angle neutron scattering (SANS) to probe deuterated green fluorescent protein (d-GFP) entrapped in a mesoporous MOF. Our work revealed that GFP molecules are spatially arranged in adjacent nanosized cavities of MOF-919 to form “assembly” through adsorbate-adsorbate interactions across pore apertures. Our findings, therefore, lay a crucial foundation for the identification of proteins structural basics under confinement environment of MOFs.

59 BASIC BIOLOGICAL SCIENCES↗

Primary biomolecular adsorption energetics of core–shell nanocomplexes: Implications for biological interactions

Molecular organization at the nano-bio interface governing the colloidal stability, reactivity, immune recognition, and drug delivery performance of nanoparticles remains difficult to predict. Quantifying the primary hydration energetics of biomolecule-coated nanomaterials can determine those interactions and provide a basis for engineered nanocarriers with tailored behavior in biological systems. Here, we measured the thermodynamics of water adsorption on patchy dry magnetite (Fe 3 O 4 ) nanoparticles coated with three model biomolecules, bovine serum albumin, potato starch, and lauric acid and compared these properties to the hydration energetics of the corresponding free dry biomolecules. The results demonstrate how the surface functionalization alters the hydrophilicity, the accessible hydrophilic surface, and the interaction potential of the nanocomplex surface with biological media. The protein coating increases the interaction potential of the surface of the nanocomplex. The weaker interaction potential of the polysaccharide coating and the relatively large hydrophilic surface area allow dynamic and reversible binding, while the fatty acid rearranges into a partial bilayer with very strong hydrophilicity. The findings establish the hydration enthalpy as a quantitative basis to determine and interpret nanoparticle interactions with proteins, membranes, and biological fluids, and provide a thermodynamic foundation for designing nanocarriers with predictable biological reactivity.

59 BASIC BIOLOGICAL SCIENCES↗

High throughput single cell multiomics platform [Abstract]

In this collaborative project, PNNL and Scienion will co-develop an integrated microfluidic technology to co-measure the transcriptome and proteome in single cells. The technology will enable us to efficiently separate proteins from mRNA transcripts between two microchips, barcode the molecules, and measure them separately with next-generation sequencing and mass spectrometry, respectively. Multicellular organisms contain diverse cell types and tremendous cell-to-cell heterogeneity that dictates a multitude of biological functions in both physiological and pathological environments. Even in the case of microbes, these genetically identical organisms can randomly differentiate into many subpopulations that assume different roles for the survival of the community. Bulk-scale measurements are insufficient to resolve such complexities. The development and applications of high throughput single-cell omics technologies have transformed our understanding of cellular heterogeneities and their differential responses to internal signaling events or external stimulations. Despite these advances, most current single-cell omic technologies provide information on only one type of biomolecule. Perse, such measurements provide incomplete information because the cell phenotype is determined by multiple layers of biomolecules and the interplay between genome, epigenome, transcriptome, and proteome. For example, mRNA abundance in one cell can not be precisely referred to the corresponding DNA and protein in other cells because of the potential subtle difference in genotype (e.g., somatic mutation or copy number variation) or phenotype (external microenvironment and cell-cell interactions). As such, parallel measurement of multiple biomolecules in the same single cells can offer unique advantages compared with measuring them separately in different single cells. Scienion is a world-leading biotech company focusing on precision liquid handling and its application in single-cell whole-genome sequencing and RNA sequencing. PNNL is the leading institution in ultrasensitive mass spectrometry, microfluidics, and untargeted single-cell proteomics (scProteomics). This collaboration will facilitate a unique fusion between scTranscriptomics capability at Scienion and scProteomics capabilities at PNNL to, for the first time, perform both untargeted transcriptomics and proteomics from the same single cells.

59 BASIC BIOLOGICAL SCIENCES↗

BioPhotovoltaics: New paradigm towards high-efficiency and high-stability cells

In this project, we demonstrated significant progress in the development of Bio-Photovoltaic (BioPV) technology, with a particular focus on the transition from the initial success with Artemisinin (ART) to the development of the E1 compound. This journey began with the exploration of less conformationally restricted analogs of ART, leading to the discovery of E1. The initial success in the first quarter with ART set a precedent for the project, guiding our approach in molecular selection and design. Our computational studies provided a solid rationale for selecting specific biomolecules, with density functional theory calculations revealing the potential of certain molecules to form beneficial interactions with perovskite. This was a crucial step in narrowing down the candidate molecules from a broader selection. Subsequently, our approach involved simplifying these molecules to refine their properties and enhance their performance in bioPV applications. The ART-MAPbI3 films, for example, showcased not only high carrier mobility and hydrophobicity but also a significant increase in PCE. The evolution from ART to E1 was marked by a thorough understanding of molecular interactions and their impact on the material’s performance. This progression, from the complexity of lead candidates to the modeling and testing of simplified compounds, has culminated in the development of next-generation biomolecules with vastly improved properties. The link between E1 and ART, through this enhanced understanding, has been compelling and instrumental in achieving the milestones set forth in our project. The success in material and device performance underscores the importance of fundamental molecular design parameters, pointing towards future potential in the field of bioPV technology.

14 SOLAR ENERGY↗

Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study

The easiest and often most useful way to work with experimentally determined or computationally predicted structures of biomolecules is by viewing their three-dimensional (3D) shapes using a molecular visualization tool. Mol* was collaboratively developed by RCSB Protein Data Bank (RCSB PDB, RCSB.org) and Protein Data Bank in Europe (PDBe, PDBe.org) as an open-source, web-based, 3D visualization software suite for examination and analyses of biostructures. It is capable of displaying atomic coordinates and related experimental data of biomolecular structures together with a variety of annotations, facilitating basic and applied research, training, education, and information dissemination. Across RCSB.org, the RCSB PDB research-focused web portal, Mol* has been implemented to support single-mouse-click atomic-level visualization of biomolecules (e.g., proteins, nucleic acids, carbohydrates) with bound cofactors, small-molecule ligands, ions, water molecules, or other macromolecules. RCSB.org Mol* can seamlessly display 3D structures from various sources, allowing structure interrogation, superimposition, and comparison. Using influenza A H5N1 virus as a topical case study of an important pathogen, we exemplify how Mol* has been embedded within various RCSB.org tools—allowing users to view polymer sequence and structure-based annotations integrated from trusted bioinformatics data resources, assess patterns and trends in groups of structures, and view structures of any size and compositional complexity. In addition to being linked to every experimentally determined biostructure and Computed Structure Model made available at RCSB.org, Standalone Mol* is freely available for visualizing any atomic-level or multi-scale biostructure at rcsb.org/3d-view.

3D biostructure↗

Advances in mass spectrometry-enabled multiomics at single-cell resolution

We report biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

47 OTHER INSTRUMENTATION↗

Enhanced rare earth element recovery with cross-linked glutaraldehyde-lanthanide binding peptides in foam-based separations

Lanthanide Binding Tag (LBT) peptides that coordinate selectively with lanthanide ions can be used to replace the energy intensive processes used for the separation of rare earth elements (REEs). These surface-active biomolecules, once selectively complexed with the trivalent REE cations, can adsorb to air/aqueous interfaces of bubbles for foam-based REEs recovery. Glutaraldehyde, an organic compound that is a homobifunctional crosslinker for proteins and peptides, can be used to enhance the adsorption and interfacial stabilization of lanthanide-bound peptides films. The stability of the interfacial cross-linked films was tested by measuring their dilational and shear surface rheological properties. Surface activity of the adsorbed species was analyzed using pendant drop tensiometry, while surface density and molecular arrangement were determined using x-ray reflectivity and x-ray fluorescence near total reflection. Glutaraldehyde cross-linked REE-peptide complexes enhance the adsorption of lanthanides to air-water interfaces, resulting in thicker interfacial structures. Subsequently, these thicker layers enhance the dilational and shear interfacial rheological properties. The interfacial film stabilization and REEs extraction promoted by the cross-linker presented in this work provides an approach to integrate glutaraldehyde as a substitute of common foam stabilizers such as polymers, surfactants, and particles to optimize the recovery of REEs when using biomolecules as extractants.

36 MATERIALS SCIENCE↗

Radiocarbon analysis of soil microbial biomass via direct chloroform extraction

Microbial processing of soil organic matter is a significant driver of C cycling, yet we lack an understanding of what shapes the turnover of this large terrestrial pool. In part, this is due to limited options for accurately identifying the source of C assimilated by microbial communities. Laboratory incubations are the most common method for this; however, they can introduce artifacts due to sample disruption and processing and can take months to produce sufficient CO 2 for analysis. We present a biomass extraction method which allows for the direct 14 C analysis of microbial biomolecules and compare the results to laboratory incubations. In the upper 50 cm soil depths, the Δ 14 C from incubations was indistinguishable from that of extracted microbial biomass. Below 50 cm, the Δ 14 C of the biomass was more depleted than that of the incubations, either due to the stimulation of labile C decomposition in the incubations, the inclusion of biomolecules from non-living cells in the biomass extractions, or differences in C used for assimilation versus respiration. Our results suggest that measurement of Δ 14 C of microbial biomass extracts can be a useful alternative to soil incubations.

54 ENVIRONMENTAL SCIENCES↗

Computationally efficient Bayesian estimation of graphical networks for omics data

Graphical networks are useful, widely-used modeling approaches to represent complex biological processes with biological measurements generated by platforms such as mass spectrometry. Bayesian analyses of graphical networks for omics data have several advantages over their frequentist counterparts, such as the inclusion of prior knowledge in the estimation of models. However, Bayesian approaches to date have only been feasible for data with a couple hundred biomolecules due to prohibitive computational time, but omics data often contains tens of thousands of biomolecules. Here, we present and illustrate a more computationally efficient approach named BPlane (Bayesian PseudoLikelihood-based Algorithm for Network Estimation) to extend Bayesian modeling capabilities for larger-sized datasets, such as most untargeted proteomics data. Via simulation, we demonstrate that BPlane produces substantial computational savings over a current state-of-the-art Bayesian algorithm while maintaining competitive edge detection accuracy. On a SARS-CoV2 proteomics data with 7000 proteins, the competing algorithm takes three times as long to complete the first iteration as BPlane takes to converge after over 100 iterations.

EM algorithm↗

Substrate-Directed Dimensional and Phase Control of Peptide Assemblies on Two-Dimensional van der Waals Materials

Understanding and controlling biomolecular self-assembly on van der Waals (vdW) materials has the potential to advance hybrid bioelectronic devices by enabling precise tuning of the interface and modulation of the resulting electronic properties of the biomolecule-vdW heterostructure. However, how surface properties of vdW materials direct biomolecule assembly remains poorly understood. To fill this knowledge gap, we investigated the assembly of a peptide known to assemble into two-dimensional (2D) crystalline films on MoS 2 on three representative vdW surfaces: WS 2 , MoS 2 , and highly oriented pyrolytic graphite (HOPG). Using in situ atomic force microscopy (AFM), we find that assembly is substrate-dependent, resulting in multilayers on WS 2 , monolayers on MoS 2 , and multiple coexisting phases on HOPG. WS 2 exhibits a higher negative charge, strong long-range electrostatic interactions, and extensive hydration layering that may promote multilayer stacking. In contrast, MoS 2 has stronger short-range interactions with the peptides but much weaker long-range interactions and hydration structure, which may favor monolayer formation. Molecular dynamics simulations predict a corresponding switch from monolayer to multilayer aggregates of the adsorbed monomers, reflected in their relative mobilities. On hydrophobic HOPG, the peptides bind most strongly and remain as monomers with high surface mobility. The peptide dimers comprising the basic unit of the crystals are more compact on HOPG, which has a smaller lattice constant than WS 2 or MoS 2 , suggesting strain contributes to stabilizing multiple phases. Our results provide mechanistic insights into how surface charge and hydration structure, and the lattice structure of the substrates governs peptide assembly on vdW materials, offering a framework to rationally control the 2D peptide-vdW heterostructures.

Molecular dynamics simulations↗

Unimodal Imaging of Monovalent Metal-Chelator Complexes and Lipids by MALDI Imaging Mass Spectrometry

Careful regulation of monovalent metal ions (M + ) is necessary to maintain a functional cellular system. Of these ions, appropriate sodium (Na + ) and potassium (K + ) concentrations are particularly integral for electrochemical signaling, as well as the secondary transport of nutrients and waste. Dysregulation of M + homeostasis can disrupt these mechanisms, potentially influencing the metabolism of downstream biomolecules such as lipids. Thus, the relationship between M + abundances and related biomolecular distributions must be elucidated to better understand the physiology of healthy and disordered tissues. Traditional techniques for imaging biological metal distributions include SIMS, LA-ICP-MS, and XRF; however, these capabilities are limited to elemental analysis or the analysis of molecular fragments and must be paired with other modalities to visualize distributions of more complex biomolecules within the same or similar samples. Conversely, matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool often used for mapping such biomolecular distributions, but current methods are unable to detect metals within tissue. This study illustrates a novel methodology that adds metal detection to the MALDI IMS repertoire through which the simultaneous detection of M + metals and lipids is achievable. Using a robotic sprayer for homogeneous application, on-tissue deposition of the chelator deferiprone (DEF) enables subsequent detection of the ionizable metal-chelator complex by MALDI without hindering lipid detection. Our work provides proof-of-concept data for the simultaneous detection of K + , Na + , and intact lipids using MALDI IMS.

59 BASIC BIOLOGICAL SCIENCES↗

Scalable 3D reconstruction for X-ray single particle imaging with online machine learning

X-ray free-electron lasers offer unique capabilities for measuring the structure and dynamics of biomolecules, helping us understand the basic building blocks of life. Notably, high-repetition-rate free-electron lasers enable single particle imaging, where individual, weakly scattering biomolecules are imaged under near-physiological conditions with the opportunity to access fleeting states that cannot be captured in cryogenic or crystallized conditions. Existing X-ray single particle reconstruction algorithms, which estimate the particle orientation for each image independently, are slow and memory-intensive when handling the massive datasets generated by emerging free-electron lasers. Here, we introduce X-RAI (X-Ray single particle imaging with Amortized Inference), an online reconstruction framework that estimates the structure of 3D macromolecules from large X-ray single particle datasets. X-RAI consists of a convolutional encoder, which amortizes pose estimation over large datasets, as well as a physics-based decoder, which employs an implicit neural representation to enable high-quality 3D reconstruction in an end-to-end, self-supervised manner. We demonstrate that X-RAI achieves state-of-the-art performance for small-scale datasets in simulation and challenging experimental settings and demonstrate its unprecedented ability to process large datasets containing millions of diffraction images in an online fashion. These abilities signify a paradigm shift in X-ray single particle imaging towards real-time reconstruction.

Computer science↗

Complex water networks visualized by cryogenic electron microscopy of RNA

The stability and function of biomolecules are directly influenced by their myriad interactions with water. Here we investigated water through cryogenic electron microscopy (cryo-EM) on a highly solvated molecule: the Tetrahymena ribozyme. By using segmentation-guided water and ion modelling (SWIM), an approach combining resolvability and chemical parameters, we automatically modelled and cross-validated water molecules and Mg 2+ ions in the ribozyme core, revealing the extensive involvement of water in mediating RNA non-canonical interactions. Unexpectedly, in regions where SWIM does not model ordered water, we observed highly similar densities in both cryo-EM maps. In many of these regions, the cryo-EM densities superimpose with complex water networks predicted by molecular dynamics, supporting their assignment as water and suggesting a biophysical explanation for their elusiveness to conventional atomic coordinate modelling. Our study demonstrates an approach to unveil both rigid and flexible waters that surround biomolecules through cryo-EM map densities, statistical and chemical metrics, and molecular dynamics simulations.

59 BASIC BIOLOGICAL SCIENCES↗