Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes.

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

Whole-genome detection using multivalent DNA-coated colloids.

To minimize the incorrect use of antibiotics, there is a great need for rapid and inexpensive tests to identify the pathogens that cause an infection. The gold standard of pathogen identification is based on the recognition of DNA sequences that are unique for a given pathogen. Here, we propose and test a strategy to develop simple, fast, and highly sensitive biosensors that make use of multivalency. Our approach uses DNA-functionalized polystyrene colloids that distinguish pathogens on the basis of the frequency of selected short DNA sequences in their genome. Importantly, our method uses entire genomes and does not require nucleic acid amplification. Polystyrene colloids grafted with specially designed surface DNA probes can bind cooperatively to frequently repeated sequences along the entire genome of the target bacteria, resulting in the formation of large and easily detectable colloidal aggregates. Our detection strategy allows "mix and read" detection of the target analyte; it is robust and highly sensitive over a wide concentration range covering, in the case of our test target genome Escherichia coli bl21-de3, 10 orders of magnitude from [Formula: see text] to [Formula: see text] copies/mL. The sensitivity compares well with state-of-the-art sensing techniques and has excellent specificity against nontarget bacteria. When applied to real samples, the proposed technique shows an excellent recovery rate. Our detection strategy opens the way to developing a robust platform for pathogen detection in the fields of food safety, disease control, and environmental monitoring.

The Role of Host Cell Glycans on Virus Infectivity: The SARS-CoV-2 Case.

Glycans are ubiquitously expressed sugars, coating the cell and protein surfaces. They are found on many proteins as either short and branched chains or long chains sticking out from special membrane proteins, known as proteoglycans. This sugar cushion, the glycocalyx, modulates specific interactions and protects the cell. Here it is shown that both the expression of proteoglycans and the glycans expressed on the surface of both the host and virus proteins have a critical role in modulating viral attachment to the cell. A mathematical model using SARS-Cov-2 as an archetypical virus to study the glycan role during infection is proposed. It is shown that this occurs via a tug-of-war of forces. On one side, the multivalent molecular recognition that viral proteins have toward specific host glycans and receptors. On the other side, the glycan steric repulsion that a virus must overcome to approach such specific receptors. By balancing both interactions, viral tropism can be predicted. In other words, the authors can map out the cells susceptible to virus infection in terms of receptors and proteoglycans compositions.

Density Control over MBD2 Receptor-Coated Surfaces Provides Superselective Binding of Hypermethylated DNA.

Using the biomarker hypermethylated DNA (hmDNA) for cancer detection requires a pretreatment to isolate or concentrate hmDNA from nonmethylated DNA. Affinity chromatography using a methyl binding domain-2 (MBD2) protein can be used, but the relatively low enrichment selectivity of MBD2 limits its clinical applicability. Here, we developed a superselective, multivalent, MBD2-coated platform to improve the selectivity of hmDNA enrichment. The multivalent platform employs control over the MBD2 surface receptor density, which is shown to strongly affect the binding of DNA with varying degrees of methylation, improving both the selectivity and the affinity of DNAs with higher numbers of methylation sites. Histidine-10-tagged MBD2 was immobilized on gold surfaces with receptor density control by tuning the amount of nickel nitrilotriacetic acid (NiNTA)-functionalized thiols in a thiol-based self-assembled monolayer. The required MBD2 surface receptor densities for DNA surface binding decreases for DNA with higher degrees of methylation. Both higher degrees of superselectivity and surface coverages were observed upon DNA binding at increasing methylation levels. Adopting the findings of this study into hmDNA enrichment of clinical samples has the potential to become more selective and sensitive than current MBD2-based methods and, therefore, to improve cancer diagnostics.

Direct visualization of superselective colloid-surface binding mediated by multivalent interactions.

Reliably distinguishing between cells based on minute differences in receptor density is crucial for cell-cell or virus-cell recognition, the initiation of signal transduction, and selective targeting in directed drug delivery. Such sharp differentiation between different surfaces based on their receptor density can only be achieved by multivalent interactions. Several theoretical and experimental works have contributed to our understanding of this "superselectivity." However, a versatile, controlled experimental model system that allows quantitative measurements on the ligand-receptor level is still missing. Here, we present a multivalent model system based on colloidal particles equipped with surface-mobile DNA linkers that can superselectively target a surface functionalized with the complementary mobile DNA-linkers. Using a combined approach of light microscopy and Foerster resonance energy transfer (FRET), we can directly observe the binding and recruitment of the ligand-receptor pairs in the contact area. We find a nonlinear transition in colloid-surface binding probability with increasing ligand or receptor concentration. In addition, we observe an increased sensitivity with weaker ligand-receptor interactions, and we confirm that the timescale of binding reversibility of individual linkers has a strong influence on superselectivity. These unprecedented insights on the ligand-receptor level provide dynamic information into the multivalent interaction between two fluidic membranes mediated by both mobile receptors and ligands and will enable future work on the role of spatial-temporal ligand-receptor dynamics on colloid-surface binding.

Multivalent Affinity Profiling: Direct Visualization of the Superselective Binding of Influenza Viruses.

The influenza A virus (IAV) interacts with the glycocalyx of host cells through its surface proteins hemagglutinin (HA) and neuraminidase (NA). Quantitative biophysical measurements of these interactions may help to understand these interactions at the molecular level with the long-term aim to predict influenza infectivity and answer other biological questions. We developed a method, called multivalent affinity profiling (MAP), to measure virus binding profiles on receptor density gradients to determine the threshold receptor density, which is a quantitative measure of virus avidity toward a receptor. Here, we show that imaging of IAVs on receptor density gradients allows the direct visualization and efficient assessment of their superselective binding. We show how the multivalent binding of IAVs can be quantitatively assessed using MAP if the receptor density gradients are prepared around the threshold receptor density without crowding at the higher densities. The threshold receptor density increases strongly with increasing flow rate, showing that the superselective binding of IAV is influenced by shear force. This method of visualization and quantitative assessment of superselective binding allows not only comparative studies of IAV-receptor interactions, but also more fundamental studies of how superselectivity arises and is influenced by experimental conditions.

A quantitative view on multivalent nanomedicine targeting.

Although the concept of selective delivery has been postulated over 100 years ago, no targeted nanomedicine has been clinically approved so far. Nanoparticles modified with targeting ligands to promote the selective delivery of therapeutics towards a specific cell population have been extensively reported. However, the rational design of selective particles is still challenging. One of the main reasons for this is the lack of quantitative theoretical and experimental understanding of the interactions involved in cell targeting. In this review, we discuss new theoretical models and experimental methods that provide a quantitative view of targeting. We show the new advancements in multivalency theory enabling the rational design of super-selective nanoparticles. Furthermore, we present the innovative approaches to obtain key targeting parameters at the single-cell and single molecule level and their role in the design of targeting nanoparticles. We believe that the combination of new theoretical multivalent design and experimental methods to quantify receptors and ligands aids in the rational design and clinical translation of targeted nanomedicines.

Computational design of probes to detect bacterial genomes by multivalent binding.

Rapid methods for diagnosis of bacterial infections are urgently needed to reduce inappropriate use of antibiotics, which contributes to antimicrobial resistance. In many rapid diagnostic methods, DNA oligonucleotide probes, attached to a surface, bind to specific nucleotide sequences in the DNA of a target pathogen. Typically, each probe binds to a single target sequence; i.e., target-probe binding is monovalent. Here we show using computer simulations that the detection sensitivity and specificity can be improved by designing probes that bind multivalently to the entire length of the pathogen genomic DNA, such that a given probe binds to multiple sites along the target DNA. Our results suggest that multivalent targeting of long pieces of genomic DNA can allow highly sensitive and selective binding of the target DNA, even if competing DNA in the sample also contains binding sites for the same probe sequences. Our results are robust to mild fragmentation of the bacterial genome. Our conclusions may also be relevant for DNA detection in other fields, such as disease diagnostics more broadly, environmental management, and food safety.

Self-Assembly of Cu2O Monolayer Colloidal Particle Film Allows the Fabrication of CuO Sensor with Superselectivity for Hydrogen Sulfide.

CuO monolayer colloidal particle films with controllable thickness and homogeneous microstructure were prepared by self-assembly and subsequent calcination based on Cu2O colloidal particles. Large-scale CuO monolayer colloidal particle films have the particle size of 300-500 nm, and CuO colloidal particles are hollow. It was found that such a structure exhibits excellent room-temperature H2S-gas-sensing properties. It not only has high sensing response and excellent selectivity, but also has a low limit of detection of 100 ppb. The sensors exhibit different sensitive characteristics at low and high concentrations of H2S. At low concentration (100-500 ppb), the sensor can be recovered with the increase of gas response, although it takes a longer recovery time at room temperature. At medium concentration (1-100 ppm), although the gas response still increases, the sensor is irreversible at room temperature. When the concentration continues to increase (>100 ppm), the sensor is irreversible at room temperature, and the gas response first increases and then decreases. Two reaction mechanisms are proposed to explain the above-mentioned sensing behavior. More importantly, quasi in situ X-ray photoelectron spectra confirm the existence of CuS. The CuO sensor with room-temperature response and superselectivity will find potential applications in industry, environment, or intelligent electronics.

Modulation of toll-like receptor signaling by antimicrobial peptides.

Antimicrobial peptides (AMPs) are typically thought of as molecular hole punchers that directly kill pathogens by membrane permeation. However, recent work has shown that AMPs are pleiotropic, multifunctional molecules that can strongly modulate immune responses. In this review, we provide a historical overview of the immunomodulatory properties of natural and synthetic antimicrobial peptides, with a special focus on human cathelicidin and defensins. We also summarize the various mechanisms of AMP immune modulation and outline key structural rules underlying the recently-discovered phenomenon of AMP-mediated Toll-like receptor (TLR) signaling. In particular, we describe several complementary studies demonstrating how AMPs self-assemble with nucleic acids to form nanocrystalline complexes that amplify TLR-mediated inflammation. In a broader scope, we discuss how this new conceptual framework allows for the prediction of immunomodulatory behavior in AMPs, how the discovery of hidden antimicrobial activity in known immune signaling proteins can inform these predictions, and how these findings reshape our understanding of AMPs in normal host defense and autoimmune disease.

Designing multivalent probes for tunable superselective targeting.

Specific targeting is common in biology and is a key challenge in nanomedicine. It was recently demonstrated that multivalent probes can selectively target surfaces with a defined density of surface binding sites. Here we show, using a combination of experiments and simulations on multivalent polymers, that such "superselective" binding can be tuned through the design of the multivalent probe, to target a desired density of binding sites. We develop an analytical model that provides simple yet quantitative predictions to tune the polymer's superselective binding properties by its molecular characteristics such as size, valency, and affinity. This work opens up a route toward the rational design of multivalent probes with defined superselective targeting properties for practical applications, and provides mechanistic insight into the regulation of multivalent interactions in biology. To illustrate this, we show how the superselective targeting of the extracellular matrix polysaccharide hyaluronan to its main cell surface receptor CD44 is controlled by the affinity of individual CD44-hyaluronan interactions.