Epigenetic memory of coronavirus infection in innate immune cells and their progenitors.

Inflammation can trigger lasting phenotypes in immune and non-immune cells. Whether and how human infections and associated inflammation can form innate immune memory in hematopoietic stem and progenitor cells (HSPC) has remained unclear. We found that circulating HSPC, enriched from peripheral blood, captured the diversity of bone marrow HSPC, enabling investigation of their epigenomic reprogramming following coronavirus disease 2019 (COVID-19). Alterations in innate immune phenotypes and epigenetic programs of HSPC persisted for months to 1 year following severe COVID-19 and were associated with distinct transcription factor (TF) activities, altered regulation of inflammatory programs, and durable increases in myelopoiesis. HSPC epigenomic alterations were conveyed, through differentiation, to progeny innate immune cells. Early activity of IL-6 contributed to these persistent phenotypes in human COVID-19 and a mouse coronavirus infection model. Epigenetic reprogramming of HSPC may underlie altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.

Activation of naïve CD4+ T cells re-tunes STAT1 signaling to deliver unique cytokine responses in memory CD4+ T cells.

The cytokine IL-6 controls the survival, proliferation and effector characteristics of lymphocytes through activation of the transcription factors STAT1 and STAT3. While STAT3 activity is an ever-present feature of IL-6 signaling in CD4+ T cells, prior activation via the T cell antigen receptor limits IL-6's control of STAT1 in effector and memory populations. Here we found that phosphorylation of STAT1 in response to IL-6 was regulated by the tyrosine phosphatases PTPN2 and PTPN22 expressed in response to the activation of naïve CD4+ T cells. Transcriptomics and chromatin immunoprecipitation-sequencing (ChIP-seq) of IL-6 responses in naïve and effector memory CD4+ T cells showed how the suppression of STAT1 activation shaped the functional identity and effector characteristics of memory CD4+ T cells. Thus, tyrosine phosphatases induced by the activation of naïve T cells determine the way activated or memory CD4+ T cells sense and interpret cytokine signals.

Peptide programming of supramolecular vinylidene fluoride ferroelectric phases.

Ferroelectric structures have spontaneous macroscopic polarization that can be inverted using external electric fields and have potential applications including information storage, energy transduction, ultralow-power nanoelectronics1,2 and biomedical devices3. These functions would benefit from nanoscale control of ferroelectric structure, the ability to switch polarization with lower applied fields (low coercive field) and biocompatibility. Soft ferroelectrics based on poly(vinylidene fluoride) (PVDF)4-6 have a thermodynamically unstable ferroelectric phase in the homopolymer, complex semi-crystalline structures, and high coercive fields. Here we report on ferroelectric materials formed by water-soluble molecules containing only six VDF repeating units covalently conjugated to a tetrapeptide, with the propensity to assemble into the ß-sheet structures that are ubiquitous in proteins. This led to the discovery of ribbon-shaped ferroelectric supramolecular assemblies that are thermodynamically stable with their long axes parallel to both the preferred hydrogen-bonding direction of ß-sheets and the bistable polar axes of VDF hexamers. Relative to a commonly used ferroelectric copolymer, the biomolecular assemblies exhibit a coercive field that is two orders of magnitude lower, as the result of supramolecular dynamics, and a similar level of remnant polarization, despite having a peptide content of 49 wt%. Furthermore, the Curie temperature of the assemblies is about 40 °C higher than that of a copolymer containing a similar amount of VDF. This supramolecular system was created using a biologically inspired strategy that is attractive in terms of sustainability and that could lead to new functions for soft ferroelectrics.

Phage anti-CRISPR control by an RNA- and DNA-binding helix-turn-helix protein.

In all organisms, regulation of gene expression must be adjusted to meet cellular requirements and frequently involves helix-turn-helix (HTH) domain proteins1. For instance, in the arms race between bacteria and bacteriophages, rapid expression of phage anti-CRISPR (acr) genes upon infection enables evasion from CRISPR-Cas defence; transcription is then repressed by an HTH-domain-containing anti-CRISPR-associated (Aca) protein, probably to reduce fitness costs from excessive expression2-5. However, how a single HTH regulator adjusts anti-CRISPR production to cope with increasing phage genome copies and accumulating acr mRNA is unknown. Here we show that the HTH domain of the regulator Aca2, in addition to repressing Acr synthesis transcriptionally through DNA binding, inhibits translation of mRNAs by binding conserved RNA stem-loops and blocking ribosome access. The cryo-electron microscopy structure of the approximately 40 kDa Aca2-RNA complex demonstrates how the versatile HTH domain specifically discriminates RNA from DNA binding sites. These combined regulatory modes are widespread in the Aca2 family and facilitate CRISPR-Cas inhibition in the face of rapid phage DNA replication without toxic acr overexpression. Given the ubiquity of HTH-domain-containing proteins, it is anticipated that many more of them elicit regulatory control by dual DNA and RNA binding.

Structural basis of K63-ubiquitin chain formation by the Gordon-Holmes syndrome RBR E3 ubiquitin ligase RNF216.

An increasing number of genetic diseases are linked to deregulation of E3 ubiquitin ligases. Loss-of-function mutations in the RING-between-RING (RBR) family E3 ligase RNF216 (TRIAD3) cause Gordon-Holmes syndrome (GHS) and related neurodegenerative diseases. Functionally, RNF216 assembles K63-linked ubiquitin chains and has been implicated in regulation of innate immunity signaling pathways and synaptic plasticity. Here, we report crystal structures of key RNF216 reaction states including RNF216 in complex with ubiquitin and its reaction product, K63 di-ubiquitin. Our data provide a molecular explanation for chain-type specificity and reveal the molecular basis for disruption of RNF216 function by pathogenic GHS mutations. Furthermore, we demonstrate how RNF216 activity and chain-type specificity are regulated by phosphorylation and that RNF216 is allosterically activated by K63-linked di-ubiquitin. These molecular insights expand our understanding of RNF216 function and its role in disease and further define the mechanistic diversity of the RBR E3 ligase family.

Type III CRISPR-Cas provides resistance against nucleus-forming jumbo phages via abortive infection.

Bacteria have diverse defenses against phages. In response, jumbo phages evade multiple DNA-targeting defenses by protecting their DNA inside a nucleus-like structure. We previously demonstrated that RNA-targeting type III CRISPR-Cas systems provide jumbo phage immunity by recognizing viral mRNA exported from the nucleus for translation. Here, we demonstrate that recognition of phage mRNA by the type III system activates a cyclic triadenylate-dependent accessory nuclease, NucC. Although unable to access phage DNA in the nucleus, NucC degrades the bacterial chromosome, triggers cell death, and disrupts phage replication and maturation. Hence, type-III-mediated jumbo phage immunity occurs via abortive infection, with suppression of the viral epidemic protecting the population. We further show that type III systems targeting jumbo phages have diverse accessory nucleases, including RNases that provide immunity. Our study demonstrates how type III CRISPR-Cas systems overcome the inaccessibility of jumbo phage DNA to provide robust immunity.

Corrigendum: IL-6 as a keystone cytokine in health and disease.

This corrects the article DOI: 10.1038/ni.3153.

Compensatory flux changes within an endocytic trafficking network maintain thermal robustness of Notch signaling.

Developmental signaling is remarkably robust to environmental variation, including temperature. For example, in ectothermic animals such as Drosophila, Notch signaling is maintained within functional limits across a wide temperature range. We combine experimental and computational approaches to show that temperature compensation of Notch signaling is achieved by an unexpected variety of endocytic-dependent routes to Notch activation which, when superimposed on ligand-induced activation, act as a robustness module. Thermal compensation arises through an altered balance of fluxes within competing trafficking routes, coupled with temperature-dependent ubiquitination of Notch. This flexible ensemble of trafficking routes supports Notch signaling at low temperature but can be switched to restrain Notch signaling at high temperature and thus compensates for the inherent temperature sensitivity of ligand-induced activation. The outcome is to extend the physiological range over which normal development can occur. Similar mechanisms may provide thermal robustness for other developmental signals.

Earth's early continental crust formed from wet and oxidizing arc magmas.

Formation of continental crust has shaped the surface and interior of our planet and generated the land and mineral resources on which we rely. However, how the early continental crust of Earth formed is still debated1-7. Modern continental crust is largely formed from wet and oxidizing arc magmas at subduction zones, in which oceanic lithosphere and water recycle into the mantle8-10. The magmatic H2O content and redox state of ancient rocks that constitute the early continental crust, however, are difficult to quantify owing to ubiquitous metamorphism. Here we combine two zircon oxybarometers11,12 to simultaneously determine magmatic oxygen fugacity (fO2) and H2O content of Archaean (4.0-2.5 billion years ago) granitoids that dominate the early continental crust. We show that most Archaean granitoid magmas were ≥1 log unit more oxidizing than Archaean ambient mantle-derived magmas13,14 and had high magmatic H2O contents (6-10 wt%) and high H2O/Ce ratios (>1,000), similar to modern arc magmas. We find that magmatic fO2, H2O contents and H2O/Ce ratios of Archaean granitoids positively correlate with depth of magma formation, requiring transport of large amounts of H2O to the lower crust and mantle. These observations can be readily explained by subduction but are difficult to reconcile with non-subduction models of crustal formation3-7. We note an increase in magmatic fO2 and H2O content between 4.0 and 3.6 billion years ago, probably indicating the onset of subduction during this period.

Activation mechanism of PINK1.

Mutations in the protein kinase PINK1 lead to defects in mitophagy and cause autosomal recessive early onset Parkinson's disease1,2. PINK1 has many unique features that enable it to phosphorylate ubiquitin and the ubiquitin-like domain of Parkin3-9. Structural analysis of PINK1 from diverse insect species10-12 with and without ubiquitin provided snapshots of distinct structural states yet did not explain how PINK1 is activated. Here we elucidate the activation mechanism of PINK1 using crystallography and cryo-electron microscopy (cryo-EM). A crystal structure of unphosphorylated Pediculus humanus corporis (Ph; human body louse) PINK1 resolves an N-terminal helix, revealing the orientation of unphosphorylated yet active PINK1 on the mitochondria. We further provide a cryo-EM structure of a symmetric PhPINK1 dimer trapped during the process of trans-autophosphorylation, as well as a cryo-EM structure of phosphorylated PhPINK1 undergoing a conformational change to an active ubiquitin kinase state. Structures and phosphorylation studies further identify a role for regulatory PINK1 oxidation. Together, our research delineates the complete activation mechanism of PINK1, illuminates how PINK1 interacts with the mitochondrial outer membrane and reveals how PINK1 activity may be modulated by mitochondrial reactive oxygen species.

An mTORC1-to-CDK1 Switch Maintains Autophagy Suppression during Mitosis.

Since nuclear envelope breakdown occurs during mitosis in metazoan cells, it has been proposed that macroautophagy must be inhibited to maintain genome integrity. However, repression of macroautophagy during mitosis remains controversial and mechanistic detail limited to the suggestion that CDK1 phosphorylates VPS34. Here, we show that initiation of macroautophagy, measured by the translocation of the ULK complex to autophagic puncta, is repressed during mitosis, even when mTORC1 is inhibited. Indeed, mTORC1 is inactive during mitosis, reflecting its failure to localize to lysosomes due to CDK1-dependent RAPTOR phosphorylation. While mTORC1 normally represses autophagy via phosphorylation of ULK1, ATG13, ATG14, and TFEB, we show that the mitotic phosphorylation of these autophagy regulators, including at known repressive sites, is dependent on CDK1 but independent of mTOR. Thus, CDK1 substitutes for inhibited mTORC1 as the master regulator of macroautophagy during mitosis, uncoupling autophagy regulation from nutrient status to ensure repression of macroautophagy during mitosis.

IL-6 as a keystone cytokine in health and disease.

Interleukin 6 (IL-6) has a broad effect on cells of the immune system and those not of the immune system and often displays hormone-like characteristics that affect homeostatic processes. IL-6 has context-dependent pro- and anti-inflammatory properties and is now regarded as a prominent target for clinical intervention. However, the signaling cassette that controls the activity of IL-6 is complicated, and distinct intervention strategies can inhibit this pathway. Clinical experience with antagonists of IL-6 has raised new questions about how and when to block this cytokine to improve disease outcome and patient wellbeing. Here we discuss the effect of IL-6 on innate and adaptive immunity and the possible advantages of various antagonists of IL-6 and consider how the immunobiology of IL-6 may inform clinical decisions.

Highly accurate protein structure prediction for the human proteome.

Protein structures can provide invaluable information, both for reasoning about biological processes and for enabling interventions such as structure-based drug development or targeted mutagenesis. After decades of effort, 17% of the total residues in human protein sequences are covered by an experimentally determined structure1. Here we markedly expand the structural coverage of the proteome by applying the state-of-the-art machine learning method, AlphaFold2, at a scale that covers almost the entire human proteome (98.5% of human proteins). The resulting dataset covers 58% of residues with a confident prediction, of which a subset (36% of all residues) have very high confidence. We introduce several metrics developed by building on the AlphaFold model and use them to interpret the dataset, identifying strong multi-domain predictions as well as regions that are likely to be disordered. Finally, we provide some case studies to illustrate how high-quality predictions could be used to generate biological hypotheses. We are making our predictions freely available to the community and anticipate that routine large-scale and high-accuracy structure prediction will become an important tool that will allow new questions to be addressed from a structural perspective.

Highly accurate protein structure prediction with AlphaFold.

Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort1-4, the structures of around 100,000 unique proteins have been determined5, but this represents a small fraction of the billions of known protein sequences6,7. Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence-the structure prediction component of the 'protein folding problem'8-has been an important open research problem for more than 50 years9. Despite recent progress10-14, existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14)15, demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm.

Brittle and ductile yielding in soft materials.

Many soft materials yield under mechanical loading, but how this transition from solid-like behavior to liquid-like behavior occurs can vary significantly. Understanding the physics of yielding is of great interest for the behavior of biological, environmental, and industrial materials, including those used as inks in additive manufacturing and muds and soils. For some materials, the yielding transition is gradual, while others yield abruptly. We refer to these behaviors as being ductile and brittle. The key rheological signatures of brittle yielding include a stress overshoot in steady-shear-startup tests and a steep increase in the loss modulus during oscillatory amplitude sweeps. In this work, we show how this spectrum of yielding behaviors may be accounted for in a continuum model for yield stress materials by introducing a parameter we call the brittility factor. Physically, an increased brittility decreases the contribution of recoverable deformation to plastic deformation, which impacts the rate at which yielding occurs. The model predictions are successfully compared to results of different rheological protocols from a number of real yield stress fluids with different microstructures, indicating the general applicability of the phenomenon of brittility. Our study shows that the brittility of soft materials plays a critical role in determining the rate of the yielding transition and provides a simple tool for understanding its effects under various loading conditions.

Unbiased construction of constitutive relations for soft materials from experiments via rheology-informed neural networks.

The ability to concisely describe the dynamical behavior of soft materials through closed-form constitutive relations holds the key to accelerated and informed design of materials and processes. The conventional approach is to construct constitutive relations through simplifying assumptions and approximating the time- and rate-dependent stress response of a complex fluid to an imposed deformation. While traditional frameworks have been foundational to our current understanding of soft materials, they often face a twofold existential limitation: i) Constructed on ideal and generalized assumptions, precise recovery of material-specific details is usually serendipitous, if possible, and ii) inherent biases that are involved by making those assumptions commonly come at the cost of new physical insight. This work introduces an approach by leveraging recent advances in scientific machine learning methodologies to discover the governing constitutive equation from experimental data for complex fluids. Our rheology-informed neural network framework is found capable of learning the hidden rheology of a complex fluid through a limited number of experiments. This is followed by construction of an unbiased material-specific constitutive relation that accurately describes a wide range of bulk dynamical behavior of the material. While extremely efficient in closed-form model discovery for a real-world complex system, the model also provides insight into the underpinning physics of the material.

Inferring COVID-19 testing and vaccination behavior from New Jersey testing data.

Characterizing the relationship between disease testing behaviors and infectious disease dynamics is of great importance for public health. Tests for both current and past infection can influence disease-related behaviors at the individual level, while population-level knowledge of an epidemic's course may feed back to affect one's likelihood of taking a test. The COVID-19 pandemic has generated testing data on an unprecedented scale for tests detecting both current infection (PCR, antigen) and past infection (serology); this opens the way to characterizing the complex relationship between testing behavior and infection dynamics. Leveraging a rich database of individualized COVID-19 testing histories in New Jersey, we analyze the behavioral relationships between PCR and serology tests, infection, and vaccination. We quantify interactions between individuals' test-taking tendencies and their past testing and infection histories, finding that PCR tests were disproportionately taken by people currently infected, and serology tests were disproportionately taken by people with past infection or vaccination. The effects of previous positive test results on testing behavior are less consistent, as individuals with past PCR positives were more likely to take subsequent PCR and serology tests at some periods of the epidemic time course and less likely at others. Lastly, we fit a model to the titer values collected from serology tests to infer vaccination trends, finding a marked decrease in vaccination rates among individuals who had previously received a positive PCR test. These results exemplify the utility of individualized testing histories in uncovering hidden behavioral variables affecting testing and vaccination.

Direct-ink-write cross-linkable bottlebrush block copolymers for on-the-fly control of structural color.

Additive manufacturing capable of controlling and dynamically modulating structures down to the nanoscopic scale remains challenging. By marrying additive manufacturing with self-assembly, we develop a UV (ultra-violet)-assisted direct ink write approach for on-the-fly modulation of structural color by programming the assembly kinetics through photo-cross-linking. We design a photo-cross-linkable bottlebrush block copolymer solution as a printing ink that exhibits vibrant structural color (i.e., photonic properties) due to the nanoscopic lamellar structures formed post extrusion. By dynamically modulating UV-light irradiance during printing, we can program the color of the printed material to access a broad spectrum of visible light with a single ink while also creating color gradients not previously possible. We unveil the mechanism of this approach using a combination of coarse-grained simulations, rheological measurements, and structural characterizations. Central to the assembly mechanism is the matching of the cross-linking timescale with the assembly timescale, which leads to kinetic trapping of the assembly process that evolves structural color from blue to red driven by solvent evaporation. This strategy of integrating cross-linking chemistry and out-of-equilibrium processing opens an avenue for spatiotemporal control of self-assembled nanostructures during additive manufacturing.

Diamond surface functionalization via visible light-driven C-H activation for nanoscale quantum sensing.

Nitrogen-vacancy (NV) centers in diamond are a promising platform for nanoscale NMR sensing. Despite significant progress toward using NV centers to detect and localize nuclear spins down to the single spin level, NV-based spectroscopy of individual, intact, arbitrary target molecules remains elusive. Such sensing requires that target molecules are immobilized within nanometers of NV centers with long spin coherence. The inert nature of diamond typically requires harsh functionalization techniques such as thermal annealing or plasma processing, limiting the scope of functional groups that can be attached to the surface. Solution-phase chemical methods can be readily generalized to install diverse functional groups, but they have not been widely explored for single-crystal diamond surfaces. Moreover, realizing shallow NV centers with long spin coherence times requires highly ordered single-crystal surfaces, and solution-phase functionalization has not yet been shown with such demanding conditions. In this work, we report a versatile strategy to directly functionalize C-H bonds on single-crystal diamond surfaces under ambient conditions using visible light, forming C-F, C-Cl, C-S, and C-N bonds at the surface. This method is compatible with NV centers within 10 nm of the surface with spin coherence times comparable to the state of the art. As a proof-of-principle demonstration, we use shallow ensembles of NV centers to detect nuclear spins from surface-bound functional groups. Our approach to surface functionalization opens the door to deploying NV centers as a tool for chemical sensing and single-molecule spectroscopy.

On-going Mechanical Damage from Mastication Drives Homeostatic Th17 Cell Responses at the Oral Barrier.

Immuno-surveillance networks operating at barrier sites are tuned by local tissue cues to ensure effective immunity. Site-specific commensal bacteria provide key signals ensuring host defense in the skin and gut. However, how the oral microbiome and tissue-specific signals balance immunity and regulation at the gingiva, a key oral barrier, remains minimally explored. In contrast to the skin and gut, we demonstrate that gingiva-resident T helper 17 (Th17) cells developed via a commensal colonization-independent mechanism. Accumulation of Th17 cells at the gingiva was driven in response to the physiological barrier damage that occurs during mastication. Physiological mechanical damage, via induction of interleukin 6 (IL-6) from epithelial cells, tailored effector T cell function, promoting increases in gingival Th17 cell numbers. These data highlight that diverse tissue-specific mechanisms govern education of Th17 cell responses and demonstrate that mechanical damage helps define the immune tone of this important oral barrier.