Cell-wide analysis of protein thermal unfolding reveals determinants of thermostability

Hidden information on protein function in censuses of proteome foldedness

Methods that assay protein foldedness with proteomics have generated censuses of apparent protein folding stabilities in biological milieu. However, different censuses poorly correlate with each other. Here, we show that the reason for this is that methods targeting foldedness through monitoring amino acid sidechain reactivity also detect changes in conformation and ligand binding, which can be a substantial fraction of the data. We show that the reactivity of only one quarter of cysteine or methionine sidechains in proteins in a urea denaturation curve of mammalian cell lysate can be confidently explained by a two-state unfolding isotherm. Contrary to that expected from unfolding, up to one third of the cysteines decreased reactivity. These cysteines were enriched in proteins with functions relating to unfolded protein stress. One protein, chaperone HSPA8, displayed changes arising from ligand and cofactor binding. Unmasking this hidden information using the approaches outlined here should improve efforts to understand both folding and the remodeling of protein function directly in complex biological settings.

Proteomics can define features of proteome foldedness by assessing the reactivity of surface exposed amino acids. Here, the authors show that such exposure patterns yield insight to structural changes in chaperones as they bind to unfolded proteins in urea-denatured mammalian cell lysate.

In-Cell Structural Biology by NMR: The Benefits of the Atomic Scale

In-cell structural biology aims at extracting structural information about proteins or nucleic acids in their native, cellular environment. This emerging field holds great promise and is already providing new facts and outlooks of interest at both fundamental and applied levels. NMR spectroscopy has important contributions on this stage: It brings information on a broad variety of nuclei at the atomic scale, which ensures its great versatility and uniqueness. Here, we detail the methods, the fundamental knowledge, and the applications in biomedical engineering related to in-cell structural biology by NMR. We finally propose a brief overview of the main other techniques in the field (EPR, smFRET, cryo-ET, etc.) to draw some advisable developments for in-cell NMR. In the era of large-scale screenings and deep learning, both accurate and qualitative experimental evidence are as essential as ever to understand the interior life of cells. In-cell structural biology by NMR spectroscopy can generate such a knowledge, and it does so at the atomic scale. This review is meant to deliver comprehensive but accessible information, with advanced technical details and reflections on the methods, the nature of the results, and the future of the field.

The emerging role of mass spectrometry-based proteomics in drug discovery

Proteins are the main targets of most drugs; however, system-wide methods to monitor protein activity and function are still underused in drug discovery. Novel biochemical approaches, in combination with recent developments in mass spectrometry-based proteomics instrumentation and data analysis pipelines, have now enabled the dissection of disease phenotypes and their modulation by bioactive molecules at unprecedented resolution and dimensionality. In this Review, we describe proteomics and chemoproteomics approaches for target identification and validation, as well as for identification of safety hazards. We discuss innovative strategies in early-stage drug discovery in which proteomics approaches generate unique insights, such as targeted protein degradation and the use of reactive fragments, and provide guidance for experimental strategies crucial for success.

Protein folding stabilities are a major determinant of oxidation rates for buried methionine residues

The oxidation of protein-bound methionines to form methionine sulfoxides has a broad range of biological ramifications, making it important to delineate factors that influence methionine oxidation rates within a given protein. This is especially important for biopharmaceuticals, where oxidation can lead to deactivation and degradation. Previously, neighboring residue effects and solvent accessibility have been shown to impact the susceptibility of methionine residues to oxidation. In this study, we provide proteome-wide evidence that oxidation rates of buried methionine residues are also strongly influenced by the thermodynamic folding stability of proteins. We surveyed the Escherichia coli proteome using several proteomic methodologies and globally measured oxidation rates of methionine residues in the presence and absence of tertiary structure, as well as the folding stabilities of methionine-containing domains. These data indicated that buried methionines have a wide range of protection factors against oxidation that correlate strongly with folding stabilities. Consistent with this, we show that in comparison to E. coli, the proteome of the thermophile Thermus thermophilus is significantly more stable and thus more resistant to methionine oxidation. To demonstrate the utility of this correlation, we used native methionine oxidation rates to survey the folding stabilities of E. coli and T. thermophilus proteomes at various temperatures and propose a model that relates the temperature dependence of the folding stabilities of these two species to their optimal growth temperatures. Overall, these results indicate that oxidation rates of buried methionines from the native state of proteins can be used as a metric of folding stability.

Protein degradation on the global scale

Protein degradation occurs through proteasomal, endosomal, and lysosomal pathways. Technological advancements have allowed for the determination of protein copy numbers and turnover rates on a global scale, which has provided an overview of trends and rules governing protein degradation. Sharper chemical and gene-editing tools have enabled the specific perturbation of each degradation pathway, whose effects on protein dynamics can now be comprehensively analyzed. We review major studies and innovation in this field and discuss the interdependence between the major pathways of protein degradation.

Novel mutation in hexokinase 2 confers resistance to 2-deoxyglucose by altering protein dynamics

Glucose is central to many biological processes, serving as an energy source and a building block for biosynthesis. After glucose enters the cell, hexokinases convert it to glucose-6-phosphate (Glc-6P) for use in anaerobic fermentation, aerobic oxidative phosphorylation, and the pentose-phosphate pathway. We here describe a genetic screen in Saccharomyces cerevisiae that generated a novel spontaneous mutation in hexokinase-2, hxk2^G238V, that confers resistance to the toxic glucose analog 2-deoxyglucose (2DG). Wild-type hexokinases convert 2DG to 2-deoxyglucose-6-phosphate (2DG-6P), but 2DG-6P cannot support downstream glycolysis, resulting in a cellular starvation-like response. Curiously, though the hxk2^G238V mutation encodes a loss-of-function allele, the affected amino acid does not interact directly with bound glucose, 2DG, or ATP. Molecular dynamics simulations suggest that Hxk2^G238V impedes sugar binding by altering the protein dynamics of the glucose-binding cleft, as well as the large-scale domain-closure motions required for catalysis. These findings shed new light on Hxk2 dynamics and highlight how allosteric changes can influence catalysis, providing new structural insights into this critical regulator of carbohydrate metabolism. Given that hexokinases are upregulated in some cancers and that 2DG and its derivatives have been studied in anti-cancer trials, the present work also provides insights that may apply to cancer biology and drug resistance.

Glucose fuels many of the energy-production processes required for normal cell growth. Before glucose can participate in these processes, it must first be chemically modified by proteins called hexokinases. To better understand how hexokinases modify glucose—and how mutations in hexokinase genes might confer drug resistance—we evolved resistance in yeast to a toxic hexokinase-binding molecule called 2DG. We discovered a mutation in the hexokinase gene that confers 2DG resistance and reduces the protein’s ability to modify glucose. Biochemical analyses and computer simulations of the hexokinase protein suggest that the mutation diminishes glucose binding by altering enzyme flexibility. This work shows how cells can evolve resistance to toxins via only modest changes to protein structures. Furthermore, because cancer-cell hexokinases are particularly active, 2DG has been studied as cancer chemotherapy. Thus, the insights this work provides might also apply to cancer biology.

Preparation and Use of Cellular Reagents: A Low-resource Molecular Biology Reagent Platform

Protein reagents are indispensable for most molecular and synthetic biology procedures. Most conventional protocols rely on highly purified protein reagents that require considerable expertise, time, and infrastructure to produce. In consequence, most proteins are acquired from commercial sources, reagent expense is often high, and accessibility may be hampered by shipping delays, customs barriers, geopolitical constraints, and the need for a constant cold chain. Such limitations to the widespread availability of protein reagents, in turn, limit the expansion and adoption of molecular biology methods in research, education, and technology development and application. Here, we describe protocols for producing a low-resource and locally sustainable reagent delivery system, termed "cellular reagents," in which bacteria engineered to overexpress proteins of interest are dried and can then be used directly as reagent packets in numerous molecular biology reactions, without the need for protein purification or a constant cold chain. As an example of their application, we describe the execution of polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP) using cellular reagents, detailing how to replace pure protein reagents with optimal amounts of rehydrated cellular reagents. We additionally describe a do-it-yourself fluorescence visualization device for using these cellular reagents in common molecular biology applications. The methods presented in this article can be used for low-cost, on-site production of commonly used molecular biology reagents (including DNA and RNA polymerases, reverse transcriptases, and ligases) with minimal instrumentation and expertise, and without the need for protein purification. Consequently, these methods should generally make molecular biology reagents more affordable and accessible. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Preparation of cellular reagents Alternate Protocol 1: Preparation of lyophilized cellular reagents Alternate Protocol 2: Evaluation of bacterial culture growth via comparison to McFarland turbidity standards Support Protocol 1: SDS-PAGE for protein expression analysis of cellular reagents Basic Protocol 2: Using Taq DNA polymerase cellular reagents for PCR Basic Protocol 3: Using Br512 DNA polymerase cellular reagents for loop-mediated isothermal amplification (LAMP) Support Protocol 2: Building a fluorescence visualization device.

The Influence of Codon Usage, Protein Abundance, and Protein Stability on Protein Evolution Vary by Evolutionary Distance and the Type of Protein

In general, the evolutionary rate of proteins is not primarily related to protein and amino acid functions, and factors such as protein abundance, codon usage, and the protein's T_M are more important. To better understand the factors that affect protein evolution, E. coli MG1655 orthologs were compared to those in closely related bacteria and to more distantly related prokaryotes, eukaryotes, and archaea. Also, the evolution of different types of proteins was studied. The analyses indicate that the amino acid conservation of enzymes that do not use macromolecules (e.g. DNA, RNA, and proteins) as substrates and that carry out metabolic processes involving small molecules (i.e. small molecule enzymes) is different than other enzymes. For example, the small molecule enzymes have a lower percent identity than other enzymes when sequences from closely related bacteria are compared. Analyses indicate the lower percent identity is not a result of the amino acid or codon usage of the small molecule enzymes. The small molecule enzymes also don't have a significantly lower protein abundance indicating that is also not likely an important factor driving differences in amino acid conservation. Analyses indicate different methods to measure the T_M of proteins have different relationships between amino acid conservation over different evolutionary distances. In totality, the results demonstrate that the relationship between the factors thought to affect protein evolution (protein abundance, codon usage, and proteins T_Ms) and protein evolution are complex and depend on the factor, the organisms, and the type of proteins being analyzed.

Barcoded reciprocal hemizygosity analysis via sequencing illuminates the complex genetic basis of yeast thermotolerance

Decades of successes in statistical genetics have revealed the molecular underpinnings of traits as they vary across individuals of a given species. But standard methods in the field cannot be applied to divergences between reproductively isolated taxa. Genome-wide reciprocal hemizygosity mapping (RH-seq), a mutagenesis screen in an interspecies hybrid background, holds promise as a method to accelerate the progress of interspecies genetics research. Here, we describe an improvement to RH-seq in which mutants harbor barcodes for cheap and straightforward sequencing after selection in a condition of interest. As a proof of concept for the new tool, we carried out genetic dissection of the difference in thermotolerance between two reproductively isolated budding yeast species. Experimental screening identified dozens of candidate loci at which variation between the species contributed to the thermotolerance trait. Hits were enriched for mitosis genes and other housekeeping factors, and among them were multiple loci with robust sequence signatures of positive selection. Together, these results shed new light on the mechanisms by which evolution solved the problems of cell survival and division at high temperature in the yeast clade, and they illustrate the power of the barcoded RH-seq approach.

Hsp40 Affinity to Identify Proteins Destabilized by Cellular Toxicant Exposure

Environmental toxins and toxicants can damage proteins and threaten cellular proteostasis. Most current methodologies to identify misfolded proteins in cells survey the entire proteome for sites of changed reactivity. We describe and apply a quantitative proteomics methodology to identify destabilized proteins based on their binding to the human Hsp40 chaperone DNAJB8. These protein targets are validated by an orthogonal limited proteolysis assay using parallel reaction monitoring. We find that a brief exposure of HEK293T cells to meta-arsenite increases the affinity of two dozen proteins to DNAJB8, including known arsenite-sensitive proteins. In particular, arsenite treatment destabilizes both the pyruvate dehydrogenase complex E1 subunit and several RNA-binding proteins. This platform can be used to explore how environmental toxins impact cellular proteostasis and to identify the susceptible proteome.

Biochemical and structural studies of two tetrameric nucleoside 2'-deoxyribosyltransferases from psychrophilic and mesophilic bacteria: Insights into cold-adaptation

Nucleoside 2'-deoxyribosyltransferases (NDTs) catalyze the cleavage of glycosidic bonds of 2'-deoxynucleosides and the following transfer of the 2'-deoxyribose moiety to acceptor nucleobases. Here, we report the crystal structures and biochemical properties of the first tetrameric NDTs: the type I NDT from the mesophilic bacterium Enterococcus faecalis V583 (EfPDT) and the type II NDT from the bacterium Desulfotalea psychrophila (DpNDT), the first psychrophilic NDT. This novel structural and biochemical data permitted an exhaustive comparative analysis aimed to shed light into the basis of the high global stability of the psychrophilic DpNDT, which has a higher melting temperature than EfPDT (58.5 °C versus 54.4 °C) or other mesophilic NDTs. DpNDT possesses a combination of unusual structural motifs not present neither in EfPDT nor any other NDT that most probably contribute to its global stability, in particular, a large aliphatic isoleucine-leucine-valine (ILV) bundle accompanied by a vicinal disulfide bridge and also an intersubunit disulfide bridge, the first described for an NDT. The functional and structural features of DpNDT do not fit the standard features of psychrophilic enzymes, which lead us to consider the implication of (sub)cellular levels together with the protein level in the adaptation of enzymatic activity to low temperatures.

Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit

While transcriptome- and proteome-wide technologies to assess processes in protein biogenesis are now widely available, we still lack global approaches to assay post-ribosomal biogenesis events, in particular those occurring in the eukaryotic secretory system. We here develop a method, SECRiFY, to simultaneously assess the secretability of >10⁵ protein fragments by two yeast species, S. cerevisiae and P. pastoris, using custom fragment libraries, surface display and a sequencing-based readout. Screening human proteome fragments with a median size of 50-100 amino acids, we generate datasets that enable datamining into protein features underlying secretability, revealing a striking role for intrinsic disorder and chain flexibility. The SECRiFY methodology generates sufficient amounts of annotated data for advanced machine learning methods to deduce secretability patterns. The finding that secretability is indeed a learnable feature of protein sequences provides a solid base for application-focused studies.

Dynamics and Conformational Changes in Human NEIL2 DNA Glycosylase Analyzed by Hydrogen/Deuterium Exchange Mass Spectrometry

Base excision DNA repair (BER) is necessary for removal of damaged nucleobases from the genome and their replacement with normal nucleobases. BER is initiated by DNA glycosylases, the enzymes that cleave the N-glycosidic bonds of damaged deoxynucleotides. Human endonuclease VIII-like protein 2 (hNEIL2), belonging to the helix-two-turn-helix structural superfamily of DNA glycosylases, is an enzyme uniquely specific for oxidized pyrimidines in non-canonical DNA substrates such as bubbles and loops. The structure of hNEIL2 has not been solved; its closest homologs with known structures are NEIL2 from opossum and from giant mimivirus. Here we analyze the conformational dynamics of free hNEIL2 using a combination of hydrogen/deuterium exchange mass spectrometry, homology modeling and molecular dynamics simulations. We show that a prominent feature of vertebrate NEIL2 - a large insert in its N-terminal domain absent from other DNA glycosylases - is unstructured in solution. It was suggested that helix-two-turn-helix DNA glycosylases undergo open-close transition upon DNA binding, with the large movement of their N- and C-terminal domains, but the open conformation has been elusive to capture. Our data point to the open conformation as favorable for free hNEIL2 in solution. Overall, our results are consistent with the view of hNEIL2 as a conformationally flexible protein, which may be due to its participation in the repair of non-canonical DNA structures and/or to the involvement in functional and regulatory protein-protein interactions.

Phase transitions in biology: from bird flocks to population dynamics

Phase transitions are an important and extensively studied concept in physics. The insights derived from understanding phase transitions in physics have recently and successfully been applied to a number of different phenomena in biological systems. Here, we provide a brief review of phase transitions and their role in explaining biological processes ranging from collective behaviour in animal flocks to neuronal firing. We also highlight a new and exciting area where phase transition theory is particularly applicable: population collapse and extinction. We discuss how phase transition theory can give insight into a range of extinction events such as population decline due to climate change or microbial responses to stressors such as antibiotic treatment.

The low-complexity domain of the FUS RNA binding protein self-assembles via the mutually exclusive use of two distinct cross-β cores

Single amino acid changes causative of neurologic disease often map to the cross-β forming regions of low-complexity (LC) domains. All such mutations studied to date lead to enhanced avidity of cross-β interactions. The LC domain of the fused in sarcoma (FUS) RNA binding protein contains three different regions that are capable of forming labile cross-β interactions. Here we describe the perplexing effect of amyotrophic lateral sclerosis (ALS)-causing mutations localized to the LC domain of FUS to substantially weaken its ability to form one of its three cross-β interactions. An understanding of how these mutations abet uncontrolled polymerization of the FUS LC domain may represent an important clue as to how LC domains achieve their proper biological function.

The low-complexity (LC) domain of the fused in sarcoma (FUS) RNA binding protein self-associates in a manner causing phase separation from an aqueous environment. Incubation of the FUS LC domain under physiologically normal conditions of salt and pH leads to rapid formation of liquid-like droplets that mature into a gel-like state. Both examples of phase separation have enabled reductionist biochemical assays allowing discovery of an N-terminal region of 57 residues that assembles into a labile, cross-β structure. Here we provide evidence of a nonoverlapping, C-terminal region of the FUS LC domain that also forms specific cross-β interactions. We propose that biologic function of the FUS LC domain may operate via the mutually exclusive use of these N- and C-terminal cross-β cores. Neurodegenerative disease–causing mutations in the FUS LC domain are shown to imbalance the two cross-β cores, offering an unanticipated concept of LC domain function and dysfunction.

Oncogenic HSP90 Facilitates Metabolic Alterations in Aggressive B-cell Lymphomas

HSP90 is critical for maintenance of the cellular proteostasis. In cancer cells, HSP90 also becomes a nucleating site for the stabilization of multiprotein complexes including signaling pathways and transcription complexes. Here we described the role of this HSP90 form, referred to as oncogenic HSP90, in the regulation of cytosolic metabolic pathways in proliferating B-cell lymphoma cells. Oncogenic HSP90 assisted in the organization of metabolic enzymes into non-membrane-bound functional compartments. Under experimental conditions that conserved cellular proteostasis, oncogenic HSP90 coordinated and sustained multiple metabolic pathways required for energy production and maintenance of cellular biomass as well as for secretion of extracellular metabolites. Conversely, inhibition of oncogenic HSP90, in absence of apparent client protein degradation, decreased the efficiency of MYC-driven metabolic reprogramming. This study reveals that oncogenic HSP90 supports metabolism in B-cell lymphoma cells and patients with diffuse large B-cell lymphoma, providing a novel mechanism of activity for HSP90 inhibitors. SIGNIFICANCE: The oncogenic form of HSP90 organizes and maintains functional multienzymatic metabolic hubs in cancer cells, suggesting the potential of repurposing oncogenic HSP90 selective inhibitors to disrupt metabolism in lymphoma cells.

Members of the GADD45 Protein Family Show Distinct Propensities to form Toxic Amyloid-Like Aggregates in Physiological Conditions

The three members (GADD45α, GADD45β, and GADD45γ) of the growth arrest and DNA damage-inducible 45 (GADD45) protein family are involved in a myriad of diversified cellular functions. With the aim of unravelling analogies and differences, we performed comparative biochemical and biophysical analyses on the three proteins. The characterization and quantification of their binding to the MKK7 kinase, a validated functional partner of GADD45β, indicate that GADD45α and GADD45γ are strong interactors of the kinase. Despite their remarkable sequence similarity, the three proteins present rather distinct biophysical properties. Indeed, while GADD45β and GADD45γ are marginally stable at physiological temperatures, GADD45α presents the Tm value expected for a protein isolated from a mesophilic organism. Surprisingly, GADD45α and GADD45β, when heated, form high-molecular weight species that exhibit features (ThT binding and intrinsic label-free UV/visible fluorescence) proper of amyloid-like aggregates. Cell viability studies demonstrate that they are endowed with a remarkable toxicity against SHSY-5Y and HepG2 cells. The very uncommon property of GADD45β to form cytotoxic species in near-physiological conditions represents a puzzling finding with potential functional implications. Finally, the low stability and/or the propensity to form toxic species of GADD45 proteins constitute important features that should be considered in interpreting their many functions.

Fenton-Chemistry-Based Oxidative Modification of Proteins Reflects Their Conformation

In order to understand protein structure to a sufficient extent for, e.g., drug discovery, no single technique can provide satisfactory information on both the lowest-energy conformation and on dynamic changes over time (the ‘four-dimensional’ protein structure). Instead, a combination of complementary techniques is required. Mass spectrometry methods have shown promise in addressing protein dynamics, but often rely on the use of high-end commercial or custom instruments. Here, we apply well-established chemistry to conformation-sensitive oxidative protein labelling on a timescale of a few seconds, followed by analysis through a routine protein analysis workflow. For a set of model proteins, we show that site selectivity of labelling can indeed be rationalised in terms of known structural information, and that conformational changes induced by ligand binding are reflected in the modification pattern. In addition to conventional bottom-up analysis, further insights are obtained from intact mass measurement and native mass spectrometry. We believe that this method will provide a valuable and robust addition to the ‘toolbox’ of mass spectrometry researchers studying higher-order protein structure.

"Structuromics": another step toward a holistic view of the cell

Large-scale mapping of protein structures and their different states is crucial for gaining a mechanistic understanding of proteome function and regulation. In this issue of Cell, Cappelletti et al. achieve such a feat and identify hundreds of protein structural changes in response to outside stressors, providing a rich "structuromics" resource characterizing cellular adaptation.

The Proteome Folding Problem and Cellular Proteostasis

Stunning advances have been achieved in addressing the protein folding problem, providing deeper understanding of the mechanisms by which proteins navigate energy landscapes to reach their native states and enabling powerful algorithms to connect sequence to structure. However, the realities of the in vivo protein folding problem remain a challenge to reckon with. Here, we discuss the concept of the "proteome folding problem"-the problem of how organisms build and maintain a functional proteome-by admitting that folding energy landscapes are characterized by many misfolded states and that cells must deploy a network of chaperones and degradation enzymes to minimize deleterious impacts of these off-pathway species. The resulting proteostasis network is an inextricable part of in vivo protein folding and must be understood in detail if we are to solve the proteome folding problem. We discuss how the development of computational models for the proteostasis network's actions and the relationship to the biophysical properties of the proteome has begun to offer new insights and capabilities.

Fuzzy protein theory for disordered proteins

Why proteins are fuzzy? Constant adaptation to the cellular environment requires a wide range of changes in protein structure and interactions. Conformational ensembles of disordered proteins in particular exhibit large shifts to activate or inhibit alternative pathways. Fuzziness is critical for liquid–liquid phase separation and conversion of biomolecular condensates into fibrils. Interpretation of these phenomena presents a challenge for the classical structure-function paradigm. Here I discuss a multi-valued formalism, based on fuzzy logic, which can be applied to describe complex cellular behavior of proteins.

Unexpectedly high thermostability of an NADP-dependent malic enzyme from a psychrophilic bacterium, Shewanella livingstonensis Ac10

Psychrophilic enzymes are generally active at low temperatures, and their functions have attracted much interest in food processing, biochemical research, and chemical industry. However, their activities are usually lost above their growth temperature because of their flexible and unstable structure. Here, we unexpectedly found that a homodimeric NADP-dependent malic enzyme from a psychrophilic bacterium, Shewanella livingstonensis Ac10 (SL-ME) showed sufficient activity with 60°C treatment, similar to its counterpart from mesophilic Escherichia coli (MaeB). Consistently, SL-ME and MaeB irreversibly denatured at 71.9°C and 64.5°C, respectively. Therefore, SL-ME shows robust catalytic activity, which appears to be advantageous for its application in the bioconversion of NADP to NADPH, an essential ingredient for membrane phospholipid synthesis.

Characterization of the Heat-Stable Proteome during Seed Germination in Arabidopsis with Special Focus on LEA Proteins

During seed germination, desiccation tolerance is lost in the radicle with progressing radicle protrusion and seedling establishment. This process is accompanied by comprehensive changes in the metabolome and proteome. Germination of Arabidopsis seeds was investigated over 72 h with special focus on the heat-stable proteome including late embryogenesis abundant (LEA) proteins together with changes in primary metabolites. Six metabolites in dry seeds known to be important for seed longevity decreased during germination and seedling establishment, while all other metabolites increased simultaneously with activation of growth and development. Thermo-stable proteins were associated with a multitude of biological processes. In the heat-stable proteome, a relatively similar proportion of fully ordered and fully intrinsically disordered proteins (IDP) was discovered. Highly disordered proteins were found to be associated with functional categories development, protein, RNA and stress. As expected, the majority of LEA proteins decreased during germination and seedling establishment. However, four germination-specific dehydrins were identified, not present in dry seeds. A network analysis of proteins, metabolites and amino acids generated during the course of germination revealed a highly connected LEA protein network.

Heat Stress Tolerance Gene FpHsp104 Affects Conidiation and Pathogenicity of Fusarium pseudograminearum

Heat shock protein Hsp104, a homolog of the bacterial chaperone ClpB and plant Hsp100, plays an essential part in the response to heat and various chemical agents in Saccharomyces cerevisiae. However, their functions remain largely unknown in plant fungal pathogens. Here, we report the identification and functional characterization of a plausible ortholog of yeast Hsp104 in Fusarium pseudograminearum, which we termed FpHsp104. Deletion mutant of FpHsp104 displayed severe defects in the resistance of heat shock during F. pseudograminearum mycelia and conidia when exposed to extreme heat. We also found that the protein showed dynamic localization to small particles under high temperature. However, no significant differences were detected in osmotic, oxidative, or cell wall stress responses between the wild-type and Δfphsp104 strains. Quantitative real-time PCR analysis showed that FpHsp104 was upregulated in the conidia, and disruption of FpHsp104 gene resulted in defects in conidia production, morphology, and germination. The transcript levels of conidiation-related genes of FpFluG, FpVosA, FpWetA, and FpAbaA were reduced in the Δfphsp104 mutant vs. the wild-type strain, but heat-shocked mRNA splicing repair was not affected in Δfphsp104. Moreover, Δfphsp104 mutant also showed attenuated virulence, but its DON synthesis was normal. These data from the first study of Hsp104 in F. pseudograminearum strongly suggest that FpHsp104 gene is an important element in the heat tolerance, development, and pathogenicity processes of F. pseudograminearum.

Nonrefoldability is Pervasive Across the E. coli Proteome

Decades of research on protein folding have primarily focused on a subset of small proteins that can reversibly refold from a denatured state. However, these studies have generally not been representative of the complexity of natural proteomes, which consist of many proteins with complex architectures and domain organizations. Here, we introduce an experimental approach to probe protein refolding kinetics for whole proteomes using mass spectrometry-based proteomics. Our study covers the majority of the soluble E. coli proteome expressed during log-phase growth, and among this group, we find that one-third of the E. coli proteome is not intrinsically refoldable on physiological time scales, a cohort that is enriched with certain fold-types, domain organizations, and other biophysical features. We also identify several properties and fold-types that are correlated with slow refolding on the minute time scale. Hence, these results illuminate when exogenous factors and processes, such as chaperones or cotranslational folding, might be required for efficient protein folding.

Temperature-resistant and solvent-tolerant lipases as industrial biocatalysts: Biotechnological approaches and applications

The development of new biocatalytic systems to replace the chemical catalysts, with suitable characteristics in terms of efficiency, stability under high temperature reactions and in the presence of organic solvents, reusability, and eco-friendliness is considered a very important step to move towards the green processes. From this basis, the use of lipase as a catalyst is highly desired for many industrial applications because it offers the reactions in which could be used, stability in harsh conditions, reusability and a greener process. Therefore, the introduction of temperature-resistant and solvent-tolerant lipases have become essential and ideal for industrial applications. Temperature-resistant and solvent-tolerant lipases have been involved in many large-scale applications including biodiesel, detergent, food, pharmaceutical, organic synthesis, biosensing, pulp and paper, textile, animal feed, cosmetics, and leather industry. So, the present review provides a comprehensive overview of the industrial use of lipase. Moreover, special interest in biotechnological and biochemical techniques for enhancing temperature-resistance and solvent-tolerance of lipases to be suitable for the industrial uses.

Characterization of a Stable Form of Carboxypeptidase G2 (Glucarpidase), a Potential Biobetter Variant, From Acinetobacter sp. 263903-1

Carboxypeptidase G2 (CPG2) is a bacterial enzyme widely used to detoxify methotrexate (MTX) and in enzyme/prodrug therapy for cancer treatment. However, several drawbacks, such as instability, have limited its efficiency. Herein, we have evaluated the properties of a putative CPG2 from Acinetobacter sp. 263903-1 (AcCPG2). AcCPG2 is compared with a CPG2 derived from Pseudomonas sp. strain RS-16 (PsCPG2), available as an FDA-approved medication called glucarpidase. After modeling AcCPG2 using the I-TASSER program, the refined model was validated by PROCHECK, VERIFY 3D and according to the Z score of the model. Using computational analyses, AcCPG2 displayed higher thermodynamic stability and a lower aggregation propensity than PsCPG2. AcCPG2 showed an optimum pH of 7.5 against MTX and was stable over a pH range of 5-10. AcCPG2 exhibited optimum activity at 50 °C and higher thermal stability at a temperature range of 20-70 °C compared to PsCPG2. The K_m value of the purified AcCPG2 toward folate and MTX was 31.36 µM and 44.99 µM, respectively. The V_max value of AcCPG2 for folate and MTX was 125.80 µmol/min/mg and 48.90  µmol/min/mg, respectively. Accordingly, thermostability and pH versatility makes AcCPG2 a potential biobetter variant for therapeutic applications.

Identification and interaction mechanism of protein corona on silver nanoparticles with different sizes and the cellular responses

With the potential biomedical applications of nanomaterials such as silver nanoparticles (SNPs), nanotoxicity concerns are growing, and the importance of NP and protein interactions is far from being addressed enough. Here, we identified the major binding protein on SNPs in blood as human serum albumin (HSA) using polyacrylamide gel electrophoresis and liquid chromatography-mass spectrometry/mass spectrometry. By comparing with the previous methods, we emphasized surface area concentration as a new dose metric to address the importance of NP curvature. SNPs interacted with cysteine and cystine, disrupting the secondary structure and conformation of HSA, and this tendency became stronger on small SNPs than large ones. The protein corona significantly alleviated the toxicity and decreased SNPs' internalization in a particle size-dependent manner, where more significant inhibition effects occurred on larger particles at the same area concentration. These findings may shed light on nanotoxicity and also the design of safe nanomaterials by a comprehensive preconsideration of the metrological method.

Population and comparative genetics of thermotolerance divergence between yeast species

Many familiar traits in the natural world-from lions' manes to the longevity of bristlecone pine trees-arose in the distant past, and have long since fixed in their respective species. A key challenge in evolutionary genetics is to figure out how and why species-defining traits have come to be. We used the thermotolerance growth advantage of the yeast Saccharomyces cerevisiae over its sister species Saccharomyces paradoxus as a model for addressing these questions. Analyzing loci at which the S. cerevisiae allele promotes thermotolerance, we detected robust evidence for positive selection, including amino acid divergence between the species and conservation within S. cerevisiae populations. Because such signatures were particularly strong at the chromosome segregation gene ESP1, we used this locus as a case study for focused mechanistic follow-up. Experiments revealed that, in culture at high temperature, the S. paradoxus ESP1 allele conferred a qualitative defect in biomass accumulation and cell division relative to the S. cerevisiae allele. Only genetic divergence in the ESP1 coding region mattered phenotypically, with no functional impact detectable from the promoter. Our data support a model in which an ancient ancestor of S. cerevisiae, under selection to boost viability at high temperature, acquired amino acid variants at ESP1 and many other loci, which have been constrained since then. Complex adaptations of this type hold promise as a paradigm for interspecies genetics, especially in deeply diverged traits that may have taken millions of years to evolve.

An Overexpression Experiment Does Not Support the Hypothesis That Avoidance of Toxicity Determines the Rate of Protein Evolution

The misfolding avoidance hypothesis postulates that sequence mutations render proteins cytotoxic and therefore the higher the gene expression, the stronger the operation of selection against substitutions. This translates into prediction that relative toxicity of extant proteins is higher for those evolving faster. In the present experiment, we selected pairs of yeast genes which were paralogous but evolving at different rates. We expressed them artificially to high levels. We expected that toxicity would be higher for ones bearing more mutations, especially that overcrowding should rather exacerbate than reverse the already existing differences in misfolding rates. We did find that the applied mode of overexpression caused a considerable decrease in fitness and that the decrease was proportional to the amount of excessive protein. However, it was not higher for proteins which are normally expressed at lower levels (and have less conserved sequence). This result was obtained consistently, regardless whether the rate of growth or ability to compete in common cultures was used as a proxy for fitness. In additional experiments, we applied factors that reduce accuracy of translation or enhance structural instability of proteins. It did not change a consistent pattern of independence between the fitness cost caused by overexpression of a protein and the rate of its sequence evolution.

Proteome plasticity in response to persistent environmental change

Temperature is a variable component of the environment, and all organisms must deal with or adapt to temperature change. Acute temperature change activates cellular stress responses, resulting in refolding or removal of damaged proteins. However, how organisms adapt to long-term temperature change remains largely unexplored. Here we report that budding yeast responds to long-term high temperature challenge by switching from chaperone induction to reduction of temperature-sensitive proteins and re-localizing a portion of its proteome. Surprisingly, we also find that many proteins adopt an alternative conformation. Using Fet3p as an example, we find that the temperature-dependent conformational difference is accompanied by distinct thermostability, subcellular localization, and, importantly, cellular functions. We postulate that, in addition to the known mechanisms of adaptation, conformational plasticity allows some polypeptides to acquire new biophysical properties and functions when environmental change endures.

Direct visualization and profiling of protein misfolding and aggregation in live cells

Over the past few years, research tools have been developed to monitor the multistep protein aggregation process in live cells, a process that has been associated with a growing number of human diseases. Herein, we describe recent advances in methods that can either survey the distribution of aggregation at the level of the cellular proteome using mass spectroscopy or discern the multistep aggregation process of specific proteins of interest via fluorescence signals. Future development and application of such technologies are expected to provide insights on mechanisms, diagnosis, and treatment of diseases rooted in protein aggregation.

The rise of proteome-wide biophysics

While informative, protein amounts and physical protein associations do not provide a full picture of protein function. This Commentary highlights the potential of structural and stability proteomic technologies to derive new insights in biology and medicine.

A Bayesian semi-parametric model for thermal proteome profiling

The thermal stability of proteins can be altered when they interact with small molecules, other biomolecules or are subject to post-translation modifications. Thus monitoring the thermal stability of proteins under various cellular perturbations can provide insights into protein function, as well as potentially determine drug targets and off-targets. Thermal proteome profiling is a highly multiplexed mass-spectrommetry method for monitoring the melting behaviour of thousands of proteins in a single experiment. In essence, thermal proteome profiling assumes that proteins denature upon heating and hence become insoluble. Thus, by tracking the relative solubility of proteins at sequentially increasing temperatures, one can report on the thermal stability of a protein. Standard thermodynamics predicts a sigmoidal relationship between temperature and relative solubility and this is the basis of current robust statistical procedures. However, current methods do not model deviations from this behaviour and they do not quantify uncertainty in the melting profiles. To overcome these challenges, we propose the application of Bayesian functional data analysis tools which allow complex temperature-solubility behaviours. Our methods have improved sensitivity over the state-of-the art, identify new drug-protein associations and have less restrictive assumptions than current approaches. Our methods allows for comprehensive analysis of proteins that deviate from the predicted sigmoid behaviour and we uncover potentially biphasic phenomena with a series of published datasets.

Performance of Regression Models as a Function of Experiment Noise

Background:

A challenge in developing machine learning regression models is that it is difficult to know whether maximal performance has been reached on the test dataset, or whether further model improvement is possible. In biology, this problem is particularly pronounced as sample labels (response variables) are typically obtained through experiments and therefore have experiment noise associated with them. Such label noise puts a fundamental limit to the metrics of performance attainable by regression models on the test dataset.

Results:

We address this challenge by deriving an expected upper bound for the coefficient of determination (R²) for regression models when tested on the holdout dataset. This upper bound depends only on the noise associated with the response variable in a dataset as well as its variance. The upper bound estimate was validated via Monte Carlo simulations and then used as a tool to bootstrap performance of regression models trained on biological datasets, including protein sequence data, transcriptomic data, and genomic data.

Conclusions:

The new method for estimating upper bounds for model performance on test data should aid researchers in developing ML regression models that reach their maximum potential. Although we study biological datasets in this work, the new upper bound estimates will hold true for regression models from any research field or application area where response variables have associated noise.

Ubiquitination is essential for recovery of cellular activities after heat shock

Eukaryotic cells respond to stress through adaptive programs that include reversible shutdown of key cellular processes, the formation of stress granules, and a global increase in ubiquitination. The primary function of this ubiquitination is thought to be for tagging damaged or misfolded proteins for degradation. Here, working in mammalian cultured cells, we found that different stresses elicited distinct ubiquitination patterns. For heat stress, ubiquitination targeted specific proteins associated with cellular activities that are down-regulated during stress, including nucleocytoplasmic transport and translation, as well as stress granule constituents. Ubiquitination was not required for the shutdown of these processes or for stress granule formation but was essential for the resumption of cellular activities and for stress granule disassembly. Thus, stress-induced ubiquitination primes the cell for recovery after heat stress.

Thermal Analysis of a Mixture of Ribosomal Proteins by vT-ESI-MS: Toward a Parallel Approach for Characterizing the Stabilitome

The thermal stabilities of endogenous, intact proteins and protein assemblies in complex mixtures were characterized in parallel by means of variable-temperature electrospray ionization coupled to mass spectrometry (vT-ESI-MS). The method is demonstrated by directly measuring the melting transitions of seven proteins from a mixture of proteins derived from ribosomes. A proof-of-concept measurement of a fraction of an Escherichia coli lysate is provided to extend this approach to characterize the thermal stability of a proteome. As the solution temperature is increased, proteins and protein complexes undergo structural and organizational transitions; for each species, the folded ↔ unfolded and assembled ↔ disassembled populations are monitored based on changes in vT-ESI-MS charge state distributions and masses. The robustness of the approach illustrates a step toward the proteome-wide characterization of thermal stabilities and structural transitions-the stabilitome.

Interaction of mercury ion (Hg2+) with blood and cytotoxicity attenuation by serum albumin binding

Blood mercury reflects the amount available from tissues, which is an indication of the exposure level. Here we confirm that Hg²⁺ caused hemolytic effects at high concentrations; while at light concentrations, most of the ions were bound to human serum albumin (HSA). The binding mechanism of Hg²⁺ to HSA has been investigated, which indicated that the presence of Hg²⁺ significantly perturbed the structure of HSA and quenched the fluorescence of protein in a hybrid dynamic and static mode. Hg²⁺ was preferably bound to cysteine and cystine, where the R‒S‒S‒R structure is responsible for maintaining the protein's structure by stabilizing the α-helical bundles. The metal-protein interaction mitigated the cellular toxicity as concealed by A498 cell lines. The fundamental and comprehensive data in this work is beneficial to elucidating and understanding the identification and binding mechanisms of heavy metals with proteins, as well as possible risks on human beings and the environment.

Solar Water Disinfection to Produce Safe Drinking Water: A Review of Parameters, Enhancements, and Modelling Approaches to Make SODIS Faster and Safer

Solar water disinfection (SODIS) is one the cheapest and most suitable treatments to produce safe drinking water at the household level in resource-poor settings. This review introduces the main parameters that influence the SODIS process and how new enhancements and modelling approaches can overcome some of the current drawbacks that limit its widespread adoption. Increasing the container volume can decrease the recontamination risk caused by handling several 2 L bottles. Using container materials other than polyethylene terephthalate (PET) significantly increases the efficiency of inactivation of viruses and protozoa. In addition, an overestimation of the solar exposure time is usually recommended since the process success is often influenced by many factors beyond the control of the SODIS-user. The development of accurate kinetic models is crucial for ensuring the production of safe drinking water. This work attempts to review the relevant knowledge about the impact of the SODIS variables and the techniques used to develop kinetic models described in the literature. In addition to the type and concentration of pathogens in the untreated water, an ideal kinetic model should consider all critical factors affecting the efficiency of the process, such as intensity, spectral distribution of the solar radiation, container-wall transmission spectra, ageing of the SODIS reactor material, and chemical composition of the water, since the substances in the water can play a critical role as radiation attenuators and/or sensitisers triggering the inactivation process.

Fundamentals to function: Quantitative and scalable approaches for measuring protein stability

Folding a linear chain of amino acids into a three-dimensional protein is a complex physical process that ultimately confers an impressive range of diverse functions. Although recent advances have driven significant progress in predicting three-dimensional protein structures from sequence, proteins are not static molecules. Rather, they exist as complex conformational ensembles defined by energy landscapes spanning the space of sequence and conditions. Quantitatively mapping the physical parameters that dictate these landscapes and protein stability is therefore critical to develop models that are capable of predicting how mutations alter function of proteins in disease and informing the design of proteins with desired functions. Here, we review the approaches that are used to quantify protein stability at a variety of scales, from returning multiple thermodynamic and kinetic measurements for a single protein sequence to yielding indirect insights into folding across a vast sequence space. The physical parameters derived from these approaches will provide a foundation for models that extend beyond the structural prediction to capture the complexity of conformational ensembles and, ultimately, their function.

Discovery of a cooperative mode of inhibiting RIPK1 kinase

RIPK1, a death domain-containing kinase, has been recognized as an important therapeutic target for inhibiting apoptosis, necroptosis, and inflammation under pathological conditions. RIPK1 kinase inhibitors have been advanced into clinical studies for the treatment of various human diseases. One of the current bottlenecks in developing RIPK1 inhibitors is to discover new approaches to inhibit this kinase as only limited chemotypes have been developed. Here we describe Necrostatin-34 (Nec-34), a small molecule that inhibits RIPK1 kinase with a mechanism distinct from known RIPK1 inhibitors such as Nec-1s. Mechanistic studies suggest that Nec-34 stabilizes RIPK1 kinase in an inactive conformation by occupying a distinct binding pocket in the kinase domain. Furthermore, we show that Nec-34 series of compounds can synergize with Nec-1s to inhibit RIPK1 in vitro and in vivo. Thus, Nec-34 defines a new strategy to target RIPK1 kinase and provides a potential option of combinatorial therapy for RIPK1-mediated diseases.

A molecular dynamics study on using of naturally occurring polymers for structural stabilization of erythropoietin at high temperature

Today the nano drug delivery systems are among the hot topics in drug design and pharmacy studies. Extensive researches are conducted worldwide for obtaining more effective therapeutics and screen the best drug carrier in-vivo and in-vitro. Considering the high cost of such experiments and the ethical issues linked with in-vivo studies, the in-silico analysis provides the time and cost-effective opportunity to evaluation of physiochemical properties and the interactions between drugs and their carriers. In this study using molecular dynamics (MD) simulation, five commonly used biodegradable biopolymers in pharmaceutical formulations including Chitosan, Alginate, Cyclodextrin, Hyaluronic Acid, and Pectin were investigated as proper carriers for the erythropoietin (EPO) in heat stress. The EPO was simulated in different temperatures of 298 and 343 K and the ability of polymers for temperature stabilization of the protein was evaluated comparatively. Overall, the results obtained in this study suggest that the pectin polysaccharide is the preferable carrier than others in term of protein stability in high temperatures and using for the delivery of erythropoietin.Communicated by Ramaswamy H. Sarma.

Effect of manganese doping on the hyperthermic profile of ferrite nanoparticles using response surface methodology

Magnetic hyperthermia-based cancer therapy mediated by magnetic nanomaterials is a promising antitumoral nanotherapy, owning to its power to generate heat under the application of an alternating magnetic field. However, although the ultimate targets of these treatments, the heating potential and its relation with the magnetic behavior of the employed magnetic nanomaterials are rarely studied. Here we provide a bridge between the heating potential and magnetic properties such as anisotropy energy constant and saturation magnetization of the nano-magnets by simultaneous investigation of both hyperthermia and magnetism under a controlled set of variables given by response surface methodology. In the study, we have simultaneously investigated the effect of various synthesis parameters like cation ratio, reaction temperature and time on the magnetic response and heat generation of manganese-doped ferrite nanomaterials synthesized by a simple hydrothermal route. The optimum generation of heat and magnetization is obtained at a cationic ratio of approximately 42 at a temperature of 100 °C for a time period of 4 h. The optimized nanomaterial was then evaluated for in vitro magnetic hyperthermia application for cancer therapy against glioblastoma in terms of cell viability, effect on cellular cytoskeleton and morphological alterations. Furthermore, the correlation between the magnetic properties of the synthesized nanomaterial with its hyperthermia output was also established using K.V.M s variable where K, V and M s are the anisotropy energy constant, volume, and saturation magnetization of the nanomaterial respectively. It was found that the intensity of heat generation decreases with an increase in K.V.M s value, beyond 950 J emu g-1.

General method to stabilize mesophilic proteins in hyperthermal water

The stability of protein structures and biological functions at normal temperature is closely linked with the universal aqueous environment of organisms. Preserving bioactivities of proteins in hyperthermia water would expand their functional capabilities beyond those in native environments. However, only a limited number of proteins derived from hyperthermophiles are thermostable at elevated temperatures. Triggered by this, here we describe a general method to stabilize mesophilic proteins in hyperthermia water. The mesophilic proteins, protected by amphiphilic polymers with multiple binding sites, maintain their secondary and tertiary structures after incubation even in boiling water. This approach, outside the conventional environment for bioactivities of mesophilic proteins, provides a general strategy to dramatically increase the T_m (melting temperature) of mesophilic proteins without any changes to amino sequences of the native proteins. Current work offers a new insight with protein stability engineering for potential application, including vaccine storage and enzyme engineering.

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Preserving bioactivities of proteins in hyperthermia water is promising.

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Amphiphilic polymers could protect mesophilic proteins even in boiling water.

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Mesophilic proteins protected by amphiphilic polymers show dramatically increased T_m.

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The method offers application prospect for vaccine storage and enzyme engineering.

Pathogenic missense protein variants affect different functional pathways and proteomic features than healthy population variants

Missense variants are present amongst the healthy population, but some of them are causative of human diseases. A classification of variants associated with “healthy” or “diseased” states is therefore not always straightforward. A deeper understanding of the nature of missense variants in health and disease, the cellular processes they may affect, and the general molecular principles which underlie these differences is essential to offer mechanistic explanations of the true impact of pathogenic variants. Here, we have formalised a statistical framework which enables robust probabilistic quantification of variant enrichment across full-length proteins, their domains, and 3D structure-defined regions. Using this framework, we validate and extend previously reported trends of variant enrichment in different protein structural regions (surface/core/interface). By examining the association of variant enrichment with available functional pathways and transcriptomic and proteomic (protein half-life, thermal stability, abundance) data, we have mined a rich set of molecular features which distinguish between pathogenic and population variants: Pathogenic variants mainly affect proteins involved in cell proliferation and nucleotide processing and are enriched in more abundant proteins. Additionally, rare population variants display features closer to common than pathogenic variants. We validate the association between these molecular features and variant pathogenicity by comparing against existing in silico variant impact annotations. This study provides molecular details into how different proteins exhibit resilience and/or sensitivity towards missense variants and provides the rationale to prioritise variant-enriched proteins and protein domains for therapeutic targeting and development. The ZoomVar database, which we created for this study, is available at fraternalilab.kcl.ac.uk/ZoomVar. It allows users to programmatically annotate missense variants with protein structural information and to calculate variant enrichment in different protein structural regions.

How do can one improve the classification of genetic variants as harmful or harmless? This study uses a robust statistical analysis to exploit the interplay between protein structure, proteomic measurements and functional pathways to enable better discrimination between missense variants in health and disease.

Mechano-Induced Assembly of a Nanocomposite for "Press-N-Go" Coatings with Highly Efficient Surface Disinfection

Using antimicrobial coatings to control the spread of pathogenic microbes is appreciated in public and healthcare settings, but the performance of most antimicrobial coatings could not fulfill the increasing requirements, particularly the ease of preparation, high durability, rapid response, and high killing efficiency. Herein, we develop a new type of mechano-induced assembly of nanocomposite coating by simple "Press-N-Go" procedures on various substrates such as glassware, gloves, and fabrics, in which the coating shows strong adhesion, high shear stability, and high stiffness, making it durable in daily use to withstand common mechanical deformation and scratches. The coating also shows remarkable disinfection effectiveness over 99.9% to clinically significant multiple drug-resistant bacterial pathogens upon only 6 s near-infrared irradiation, which can be further improved to over 99.9999% upon another 6 s treatment. We envision that the coating can provide convenience and values to control pathogen spread for easily contaminated substrates in high-risk areas.