A defective viral genome strategy elicits broad protective immunity against respiratory viruses.

RNA viruses generate defective viral genomes (DVGs) that can interfere with replication of the parental wild-type virus. To examine their therapeutic potential, we created a DVG by deleting the capsid-coding region of poliovirus. Strikingly, intraperitoneal or intranasal administration of this genome, which we termed eTIP1, elicits an antiviral response, inhibits replication, and protects mice from several RNA viruses, including enteroviruses, influenza, and SARS-CoV-2. While eTIP1 replication following intranasal administration is limited to the nasal cavity, its antiviral action extends non-cell-autonomously to the lungs. eTIP1 broad-spectrum antiviral effects are mediated by both local and distal type I interferon responses. Importantly, while a single eTIP1 dose protects animals from SARS-CoV-2 infection, it also stimulates production of SARS-CoV-2 neutralizing antibodies that afford long-lasting protection from SARS-CoV-2 reinfection. Thus, eTIP1 is a safe and effective broad-spectrum antiviral generating short- and long-term protection against SARS-CoV-2 and other respiratory infections in animal models.

Harnessing the power of artificial intelligence to advance cell therapy.

Cell therapies are powerful technologies in which human cells are reprogrammed for therapeutic applications such as killing cancer cells or replacing defective cells. The technologies underlying cell therapies are increasing in effectiveness and complexity, making rational engineering of cell therapies more difficult. Creating the next generation of cell therapies will require improved experimental approaches and predictive models. Artificial intelligence (AI) and machine learning (ML) methods have revolutionized several fields in biology including genome annotation, protein structure prediction, and enzyme design. In this review, we discuss the potential of combining experimental library screens and AI to build predictive models for the development of modular cell therapy technologies. Advances in DNA synthesis and high-throughput screening techniques enable the construction and screening of libraries of modular cell therapy constructs. AI and ML models trained on this screening data can accelerate the development of cell therapies by generating predictive models, design rules, and improved designs.

AI in cellular engineering and reprogramming.

During the last decade, artificial intelligence (AI) has increasingly been applied in biophysics and related fields, including cellular engineering and reprogramming, offering novel approaches to understand, manipulate, and control cellular function. The potential of AI lies in its ability to analyze complex datasets and generate predictive models. AI algorithms can process large amounts of data from single-cell genomics and multiomic technologies, allowing researchers to gain mechanistic insights into the control of cell identity and function. By integrating and interpreting these complex datasets, AI can help identify key molecular events and regulatory pathways involved in cellular reprogramming. This knowledge can inform the design of precision engineering strategies, such as the development of new transcription factor and signaling molecule cocktails, to manipulate cell identity and drive authentic cell fate across lineage boundaries. Furthermore, when used in combination with computational methods, AI can accelerate and improve the analysis and understanding of the intricate relationships between genes, proteins, and cellular processes. In this review article, we explore the current state of AI applications in biophysics with a specific focus on cellular engineering and reprogramming. Then, we showcase a couple of recent applications where we combined machine learning with experimental and computational techniques. Finally, we briefly discuss the challenges and prospects of AI in cellular engineering and reprogramming, emphasizing the potential of these technologies to revolutionize our ability to engineer cells for a variety of applications, from disease modeling and drug discovery to regenerative medicine and biomanufacturing.

A hydrophilic microenvironment in the substrate-translocating groove of the YidC membrane insertase is essential for enzyme function.

The YidC family of proteins are membrane insertases that catalyze the translocation of the periplasmic domain of membrane proteins via a hydrophilic groove located within the inner leaflet of the membrane. All homologs have a strictly conserved, positively charged residue in the center of this groove. In Bacillus subtilis, the positively charged residue has been proposed to be essential for interacting with negatively charged residues of the substrate, supporting a hypothesis that YidC catalyzes insertion via an early-step electrostatic attraction mechanism. Here, we provide data suggesting that the positively charged residue is important not for its charge but for increasing the hydrophilicity of the groove. We found that the positively charged residue is dispensable for Escherichia coli YidC function when an adjacent residue at position 517 was hydrophilic or aromatic, but was essential when the adjacent residue was apolar. Additionally, solvent accessibility studies support the idea that the conserved positively charged residue functions to keep the top and middle of the groove sufficiently hydrated. Moreover, we demonstrate that both the E. coli and Streptococcus mutans YidC homologs are functional when the strictly conserved arginine is replaced with a negatively charged residue, provided proper stabilization from neighboring residues. These combined results show that the positively charged residue functions to maintain a hydrophilic microenvironment in the groove necessary for the insertase activity, rather than to form electrostatic interactions with the substrates.

Characterization of the Features of Water Inside the SecY Translocon.

Despite extended experimental and computational studies, the mechanism regulating membrane protein folding and stability in cell membranes is not fully understood. In this review, I will provide a personal and partial account of the scientific efforts undertaken by Dr. Stephen White to shed light on this topic. After briefly describing the role of water and the hydrophobic effect on cellular processes, I will discuss the physical chemistry of water confined inside the SecY translocon pore. I conclude with a review of recent literature that attempts to answer fundamental questions on the pathway and energetics of translocon-guided membrane protein insertion.

AI-driven prediction of SARS-CoV-2 variant binding trends from atomistic simulations.

We present a novel technique to predict binding affinity trends between two molecules from atomistic molecular dynamics simulations. The technique uses a neural network algorithm applied to a series of images encoding the distance between two molecules in time. We demonstrate that our algorithm is capable of separating with high accuracy non-hydrophobic mutations with low binding affinity from those with high binding affinity. Moreover, we show high accuracy in prediction using a small subset of the simulation, therefore requiring a much shorter simulation time. We apply our algorithm to the binding between several variants of the SARS-CoV-2 spike protein and the human receptor ACE2.

Entry from the Lipid Bilayer: A Possible Pathway for Inhibition of a Peptide G Protein-Coupled Receptor by a Lipophilic Small Molecule.

The pathways that G protein-coupled receptor (GPCR) ligands follow as they bind to or dissociate from their receptors are largely unknown. Protease-activated receptor-1 (PAR1) is a GPCR activated by intramolecular binding of a tethered agonist peptide that is exposed by thrombin cleavage. By contrast, the PAR1 antagonist vorapaxar is a lipophilic drug that binds in a pocket almost entirely occluded from the extracellular solvent. The binding and dissociation pathway of vorapaxar is unknown. Starting with the crystal structure of vorapaxar bound to PAR1, we performed temperature-accelerated molecular dynamics simulations of ligand dissociation. In the majority of simulations, vorapaxar exited the receptor laterally into the lipid bilayer through openings in the transmembrane helix (TM) bundle. Prior to full dissociation, vorapaxar paused in metastable intermediates stabilized by interactions with the receptor and lipid headgroups. Derivatives of vorapaxar with alkyl chains predicted to extend between TM6 and TM7 into the lipid bilayer inhibited PAR1 with apparent on rates similar to that of the parent compound in cell signaling assays. These data are consistent with vorapaxar binding to PAR1 via a pathway that passes between TM6 and TM7 from the lipid bilayer, in agreement with the most consistent pathway observed by molecular dynamics. While there is some evidence of entry of the ligand into rhodopsin and lipid-activated GPCRs from the cell membrane, our study provides the first such evidence for a peptide-activated GPCR and suggests that metastable intermediates along drug binding and dissociation pathways can be stabilized by specific interactions between lipids and the ligand.

Anomalous behavior of water inside the SecY translocon.

The heterotrimeric SecY translocon complex is required for the cotranslational assembly of membrane proteins in bacteria and archaea. The insertion of transmembrane (TM) segments during nascent-chain passage through the translocon is generally viewed as a simple partitioning process between the water-filled translocon and membrane lipid bilayer, suggesting that partitioning is driven by the hydrophobic effect. Indeed, the apparent free energy of partitioning of unnatural aliphatic amino acids on TM segments is proportional to accessible surface area, which is a hallmark of the hydrophobic effect [Öjemalm K, et al. (2011) Proc Natl Acad Sci USA 108(31):E359-E364]. However, the apparent partitioning solvation parameter is less than one-half the value expected for simple bulk partitioning, suggesting that the water in the translocon departs from bulk behavior. To examine the state of water in a SecY translocon complex embedded in a lipid bilayer, we carried out all-atom molecular-dynamics simulations of the Pyrococcus furiosus SecYE, which was determined to be in a "primed" open state [Egea PF, Stroud RM (2010) Proc Natl Acad Sci USA 107(40):17182-17187]. Remarkably, SecYE remained in this state throughout our 450-ns simulation. Water molecules within SecY exhibited anomalous diffusion, had highly retarded rotational dynamics, and aligned their dipoles along the SecY transmembrane axis. The translocon is therefore not a simple water-filled pore, which raises the question of how anomalous water behavior affects the mechanism of translocon function and, more generally, the partitioning of hydrophobic molecules. Because large water-filled cavities are found in many membrane proteins, our findings may have broader implications.

Interleaflet mixing and coupling in liquid-disordered phospholipid bilayers.

Organized as bilayers, phospholipids are the fundamental building blocks of cellular membranes and determine many of their biological functions. Interactions between the two leaflets of the bilayer (interleaflet coupling) have been implicated in the passage of information through membranes. However, physically, the meaning of interleaflet coupling is ill defined and lacks a structural basis. Using all-atom molecular dynamics simulations of fluid phospholipid bilayers of five different lipids with differing degrees of acyl-chain asymmetry, we have examined interleaflet mixing to gain insights into coupling. Reasoning that the transbilayer distribution of terminal methyl groups is an appropriate measure of interleaflet mixing, we calculated the transbilayer distributions of the acyl chain terminal methyl groups for five lipids: dioleoylphosphatidylcholine (DOPC), palmitoyloleoylphosphatidylcholine (POPC), stearoyloleoylphosphatidylcholine (SOPC), oleoylmyristoylphosphatidylcholine (OMPC), and dimyristoylphosphatidylcholine (DMPC). We observed in all cases very strong mixing across the bilayer midplane that diminished somewhat with increasing acyl-chain ordering defined by methylene order parameters. A hallmark of the interleaflet coupling idea is complementarity, which postulates that lipids with short alkyl chains in one leaflet will preferentially associate with lipids with long alkyl chains in the other leaflet. Our results suggest a much more complicated picture for thermally disordered bilayers that we call distributed complementarity, as measured by the difference in the peak positions of the sn-1 and sn-2 methyl distributions in the same leaflet.

A high-throughput method for quantifying Drosophila fecundity.

Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth) In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high throughput egg laying assays that require exposing flies to multiple different media conditions.

A tradeoff between enterovirus A71 particle stability and cell entry.

A central role of viral capsids is to protect the viral genome from the harsh extracellular environment while facilitating initiation of infection when the virus encounters a target cell. Viruses are thought to have evolved an optimal equilibrium between particle stability and efficiency of cell entry. In this study, we genetically perturb this equilibrium in a non-enveloped virus, enterovirus A71 to determine its structural basis. We isolate a single-point mutation variant with increased particle thermotolerance and decreased efficiency of cell entry. Using cryo-electron microscopy and molecular dynamics simulations, we determine that the thermostable native particles have acquired an expanded conformation that results in a significant increase in protein dynamics. Examining the intermediate states of the thermostable variant reveals a potential pathway for uncoating. We propose a sequential release of the lipid pocket factor, followed by internal VP4 and ultimately the viral RNA.

Component dynamics in polyvinylpyrrolidone concentrated aqueous solutions.

(2)H-nuclear magnetic resonance (NMR) and neutron scattering (NS) on isotopically labelled samples have been combined to investigate the structure and dynamics of polyvinylpyrrolidone (PVP) aqueous solutions (4 water molecules/monomeric unit). Neutron diffraction evidences the nanosegregation of polymer main-chains and water molecules leading to the presence of water clusters. NMR reveals the same characteristic times and spectral shape as those of the slower process observed by broadband dielectric spectroscopy in this system [S. Cerveny et al., J. Chem. Phys. 128, 044901 (2008)]. The temperature dependence of such relaxation time crosses over from a cooperative-like behavior at high temperatures to an Arrhenius behavior at lower temperatures. Below the crossover, NMR features the spectral shape as due to a symmetric distribution of relaxation times and the underlying motions as isotropic. NS results on the structural relaxation of both components-isolated via H/D labeling-show (i) anomalously stretched and non-Gaussian functional forms of the intermediate scattering functions and (ii) a strong dynamic asymmetry between the components that increases with decreasing temperature. Strong heterogeneities associated to the nanosegregated structure and the dynamic asymmetry are invoked to explain the observed anomalies. On the other hand, at short times the atomic displacements are strongly coupled for PVP and water, presumably due to H-bond formation and densification of the sample upon hydration.

Decoding CAR T cell phenotype using combinatorial signaling motif libraries and machine learning.

Chimeric antigen receptor (CAR) costimulatory domains derived from native immune receptors steer the phenotypic output of therapeutic T cells. We constructed a library of CARs containing ~2300 synthetic costimulatory domains, built from combinations of 13 signaling motifs. These CARs promoted diverse human T cell fates, which were sensitive to motif combinations and configurations. Neural networks trained to decode the combinatorial grammar of CAR signaling motifs allowed extraction of key design rules. For example, non-native combinations of motifs that bind tumor necrosis factor receptor-associated factors (TRAFs) and phospholipase C gamma 1 (PLCγ1) enhanced cytotoxicity and stemness associated with effective tumor killing. Thus, libraries built from minimal building blocks of signaling, combined with machine learning, can efficiently guide engineering of receptors with desired phenotypes.

Predicting Epitope Candidates for SARS-CoV-2.

Epitopes are short amino acid sequences that define the antigen signature to which an antibody or T cell receptor binds. In light of the current pandemic, epitope analysis and prediction are paramount to improving serological testing and developing vaccines. In this paper, known epitope sequences from SARS-CoV, SARS-CoV-2, and other Coronaviridae were leveraged to identify additional antigen regions in 62K SARS-CoV-2 genomes. Additionally, we present epitope distribution across SARS-CoV-2 genomes, locate the most commonly found epitopes, and discuss where epitopes are located on proteins and how epitopes can be grouped into classes. The mutation density of different protein regions is presented using a big data approach. It was observed that there are 112 B cell and 279 T cell conserved epitopes between SARS-CoV-2 and SARS-CoV, with more diverse sequences found in Nucleoprotein and Spike glycoprotein.

Examining the interplay between face mask usage, asymptomatic transmission, and social distancing on the spread of COVID-19.

COVID-19's high virus transmission rates have caused a pandemic that is exacerbated by the high rates of asymptomatic and presymptomatic infections. These factors suggest that face masks and social distance could be paramount in containing the pandemic. We examined the efficacy of each measure and the combination of both measures using an agent-based model within a closed space that approximated real-life interactions. By explicitly considering different fractions of asymptomatic individuals, as well as a realistic hypothesis of face masks protection during inhaling and exhaling, our simulations demonstrate that a synergistic use of face masks and social distancing is the most effective intervention to curb the infection spread. To control the pandemic, our models suggest that high adherence to social distance is necessary to curb the spread of the disease, and that wearing face masks provides optimal protection even if only a small portion of the population comply with social distance. Finally, the face mask effectiveness in curbing the viral spread is not reduced if a large fraction of population is asymptomatic. Our findings have important implications for policies that dictate the reopening of social gatherings.

Mapping Attenuation Determinants in Enterovirus-D68.

Enterovirus (EV)-D68 has been associated with epidemics in the United Sates in 2014, 2016 and 2018. This study aims to identify potential viral virulence determinants. We found that neonatal type I interferon receptor knockout mice are susceptible to EV-D68 infection via intraperitoneal inoculation and were able to recapitulate the paralysis process observed in human disease. Among the EV-D68 strains tested, strain US/MO-14-18949 caused no observable disease in this mouse model, whereas the other strains caused paralysis and death. Sequence analysis revealed several conserved genetic changes among these virus strains: nucleotide positions 107 and 648 in the 5'-untranslated region (UTR); amino acid position 88 in VP3; 1, 148, 282 and 283 in VP1; 22 in 2A; 47 in 3A. A series of chimeric and point-mutated infectious clones were constructed to identify viral elements responsible for the distinct virulence. A single amino acid change from isoleucine to valine at position 88 in VP3 attenuated neurovirulence by reducing virus replication in the brain and spinal cord of infected mice.

K2P channel C-type gating involves asymmetric selectivity filter order-disorder transitions.

K2P potassium channels regulate cellular excitability using their selectivity filter (C-type) gate. C-type gating mechanisms, best characterized in homotetrameric potassium channels, remain controversial and are attributed to selectivity filter pinching, dilation, or subtle structural changes. The extent to which such mechanisms control C-type gating of innately heterodimeric K2Ps is unknown. Here, combining K2P2.1 (TREK-1) x-ray crystallography in different potassium concentrations, potassium anomalous scattering, molecular dynamics, and electrophysiology, we uncover unprecedented, asymmetric, potassium-dependent conformational changes that underlie K2P C-type gating. These asymmetric order-disorder transitions, enabled by the K2P heterodimeric architecture, encompass pinching and dilation, disrupt the S1 and S2 ion binding sites, require the uniquely long K2P SF2-M4 loop and conserved "M3 glutamate network," and are suppressed by the K2P C-type gate activator ML335. These findings demonstrate that two distinct C-type gating mechanisms can operate in one channel and underscore the SF2-M4 loop as a target for K2P channel modulator development.

The free-volume structure of a polymer melt, poly(vinyl methylether) from molecular dynamics simulations and cavity analysis.

In this work we analyze and compare the free volume of a polymer system poly(vinyl methylether) (PVME) at 300 K obtained by the two direct but different approaches: Positron annihilation lifetime spectroscopy (PALS) and computer simulations. The free volume is calculated from the simulated cells of PVME by means of numerical methods based on grid scanning and probing the structure with a probe of a given radius R(P). The free-volume structure was found to be percolated for small probes at R(P)=0.53 A. As the probe radius increases, the cavity structure breaks into isolated cavities, reaching a maximum of the cavity number at R(P)=0.78 A. We further develop methods for a geometrical analysis of the free-volume cavities by considering their shape. The geometrical computations show that the cavities have elongated shape with side-to-length ratio corresponding to approximately 1:0.55 and with an average length of 6 A. Based on the overlap between the computed cavities and simplified geometrical representations, the best match of the cavity shape is obtained for the approximation to the ellipsoidal shape (overlap on 84.4%). A match with other examined shapes follows the sequence: ellipsoid>cylinder>bar>sphere>cube. Finally, the computed geometrical parameters are used as input parameters into the quantum-mechanical models for the orthopositronium (o-Ps) lifetime in various free-volume hole geometries. Comparison with the experimental data gives support for two ideas about the existence of an o-Ps particle in the polymeric matrix: (i) the positronium cannot localize in a portion of very small cavities; (ii) and in the case of the percolated cavities, several o-Ps particles occupy some subcavities in the same cavity. Additionally, radial distribution functions of the free volume indicate the existence of two kinds of free volume, a structured one, corresponding to interstitial spaces along the polymer chain, and the so-called "bulk free volume," distributed randomly in the structure. PALS measurements seem to be mainly related with this bulk free volume. The cavities represented by the idealized geometries are visualized in three-dimensional space providing a unique representation on the free-volume structures.

A multiscale model of mechanotransduction by the ankyrin chains of the NOMPC channel.

Our senses of touch and hearing are dependent on the conversion of external mechanical forces into electrical impulses by the opening of mechanosensitive channels in sensory cells. This remarkable feat involves the conversion of a macroscopic mechanical displacement into a subnanoscopic conformational change within the ion channel. The mechanosensitive channel NOMPC, responsible for hearing and touch in flies, is a homotetramer composed of four pore-forming transmembrane domains and four helical chains of 29 ankyrin repeats that extend 150 Å into the cytoplasm. Previous work has shown that the ankyrin chains behave as biological springs under extension and that tethering them to microtubules could be involved in the transmission of external forces to the NOMPC gate. Here we combine normal mode analysis (NMA), full-atom molecular dynamics simulations, and continuum mechanics to characterize the material properties of the chains under extreme compression and extension. NMA reveals that the lowest-frequency modes of motion correspond to fourfold symmetric compression/extension along the channel, and the lowest-frequency symmetric mode for the isolated channel domain involves rotations of the TRP domain, a putative gating element. Finite element modeling reveals that the ankyrin chains behave as a soft spring with a linear, effective spring constantof 22 pN/nm for deflections ≤15 Å. Force-balance analysis shows that the entire channel undergoes rigid body rotation during compression, and more importantly, each chain exerts a positive twisting moment on its respective linker helices and TRP domain. This torque is a model-independent consequence of the bundle geometry and would cause a clockwise rotation of the TRP domain when viewed from the cytoplasm. Force transmission to the channel for compressions >15 Å depends on the nature of helix-helix contact. Our work reveals that compression of the ankyrin chains imparts a rotational torque on the TRP domain, which potentially results in channel opening.

Structural Relaxation Processes and Collective Dynamics of Water in Biomolecular Environments.

In this simulation study, we investigate the influence of biomolecular confinement on dynamical processes in water. We compare water confined in a membrane protein nanopore at room temperature to pure liquid water at low temperatures with respect to structural relaxations, intermolecular vibrations, and the propagation of collective modes. We observe distinct potential energy landscapes experienced by water molecules in the two environments, which nevertheless result in comparable hydrogen bond lifetimes and sound propagation velocities. Hence, we show that a viscoelastic argument that links slow rearrangements of the water-hydrogen bond network to ice-like collective properties applies to both, the pure liquid and biologically confined water, irrespective of differences in the microscopic structure.