Short-term dietary changes can result in mucosal and systemic immune depression.

Omnivorous animals, including mice and humans, tend to prefer energy-dense nutrients rich in fat over plant-based diets, especially for short periods of time, but the health consequences of this short-term consumption of energy-dense nutrients are unclear. Here, we show that short-term reiterative switching to 'feast diets', mimicking our social eating behavior, breaches the potential buffering effect of the intestinal microbiota and reorganizes the immunological architecture of mucosa-associated lymphoid tissues. The first dietary switch was sufficient to induce transient mucosal immune depression and suppress systemic immunity, leading to higher susceptibility to Salmonella enterica serovar Typhimurium and Listeria monocytogenes infections. The ability to respond to antigenic challenges with a model antigen was also impaired. These observations could be explained by a reduction of CD4+ T cell metabolic fitness and cytokine production due to impaired mTOR activity in response to reduced microbial provision of fiber metabolites. Reintroducing dietary fiber rewired T cell metabolism and restored mucosal and systemic CD4+ T cell functions and immunity. Finally, dietary intervention with human volunteers confirmed the effect of short-term dietary switches on human CD4+ T cell functionality. Therefore, short-term nutritional changes cause a transient depression of mucosal and systemic immunity, creating a window of opportunity for pathogenic infection.

Mapping Systemic Inflammation and Antibody Responses in Multisystem Inflammatory Syndrome in Children (MIS-C).

Initially, children were thought to be spared from disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a month into the epidemic, a novel multisystem inflammatory syndrome in children (MIS-C) emerged. Herein, we report on the immune profiles of nine MIS-C cases. All MIS-C patients had evidence of prior SARS-CoV-2 exposure, mounting an antibody response with intact neutralization capability. Cytokine profiling identified elevated signatures of inflammation (IL-18 and IL-6), lymphocytic and myeloid chemotaxis and activation (CCL3, CCL4, and CDCP1), and mucosal immune dysregulation (IL-17A, CCL20, and CCL28). Immunophenotyping of peripheral blood revealed reductions of non-classical monocytes, and subsets of NK and T lymphocytes, suggesting extravasation to affected tissues. Finally, profiling the autoantigen reactivity of MIS-C plasma revealed both known disease-associated autoantibodies (anti-La) and novel candidates that recognize endothelial, gastrointestinal, and immune-cell antigens. All patients were treated with anti-IL-6R antibody and/or IVIG, which led to rapid disease resolution.

Cryo-EM Reveals How Human Cytoplasmic Dynein Is Auto-inhibited and Activated.

Cytoplasmic dynein-1 binds dynactin and cargo adaptor proteins to form a transport machine capable of long-distance processive movement along microtubules. However, it is unclear why dynein-1 moves poorly on its own or how it is activated by dynactin. Here, we present a cryoelectron microscopy structure of the complete 1.4-megadalton human dynein-1 complex in an inhibited state known as the phi-particle. We reveal the 3D structure of the cargo binding dynein tail and show how self-dimerization of the motor domains locks them in a conformation with low microtubule affinity. Disrupting motor dimerization with structure-based mutagenesis drives dynein-1 into an open form with higher affinity for both microtubules and dynactin. We find the open form is also inhibited for movement and that dynactin relieves this by reorienting the motor domains to interact correctly with microtubules. Our model explains how dynactin binding to the dynein-1 tail directly stimulates its motor activity.

Early-Life Gene Expression in Neurons Modulates Lasting Epigenetic States.

In mammals, the environment plays a critical role in promoting the final steps in neuronal development during the early postnatal period. While epigenetic factors are thought to contribute to this process, the underlying molecular mechanisms remain poorly understood. Here, we show that in the brain during early life, the DNA methyltransferase DNMT3A transiently binds across transcribed regions of lowly expressed genes, and its binding specifies the pattern of DNA methylation at CA sequences (mCA) within these genes. We find that DNMT3A occupancy and mCA deposition within the transcribed regions of genes is negatively regulated by gene transcription and may be modified by early-life experience. Once deposited, mCA is bound by the methyl-DNA-binding protein MECP2 and functions in a rheostat-like manner to fine-tune the cell-type-specific transcription of genes that are critical for brain function.

Unbiased Screens Show CD8+ T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein.

Developing effective strategies to prevent or treat coronavirus disease 2019 (COVID-19) requires understanding the natural immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used an unbiased, genome-wide screening technology to determine the precise peptide sequences in SARS-CoV-2 that are recognized by the memory CD8+ T cells of COVID-19 patients. In total, we identified 3-8 epitopes for each of the 6 most prevalent human leukocyte antigen (HLA) types. These epitopes were broadly shared across patients and located in regions of the virus that are not subject to mutational variation. Notably, only 3 of the 29 shared epitopes were located in the spike protein, whereas most epitopes were located in ORF1ab or the nucleocapsid protein. We also found that CD8+ T cells generally do not cross-react with epitopes in the four seasonal coronaviruses that cause the common cold. Overall, these findings can inform development of next-generation vaccines that better recapitulate natural CD8+ T cell immunity to SARS-CoV-2.

New reptile shows dinosaurs and pterosaurs evolved among diverse precursors.

Dinosaurs and pterosaurs have remarkable diversity and disparity through most of the Mesozoic Era1-3. Soon after their origins, these reptiles diversified into a number of long-lived lineages, evolved unprecedented ecologies (for example, flying, large herbivorous forms) and spread across Pangaea4,5. Recent discoveries of dinosaur and pterosaur precursors6-10 demonstrated that these animals were also speciose and widespread, but those precursors have few if any well-preserved skulls, hands and associated skeletons11,12. Here we present a well-preserved partial skeleton (Upper Triassic, Brazil) of the new lagerpetid Venetoraptor gassenae gen. et sp. nov. that offers a more comprehensive look into the skull and ecology of one of these precursors. Its skull has a sharp, raptorial-like beak, preceding that of dinosaurs by around 80 million years, and a large hand with long, trenchant claws that firmly establishes the loss of obligatory quadrupedalism in these precursor lineages. Combining anatomical information of the new species with other dinosaur and pterosaur precursors shows that morphological disparity of precursors resembles that of Triassic pterosaurs and exceeds that of Triassic dinosaurs. Thus, the 'success' of pterosaurs and dinosaurs was a result of differential survival among a broader pool of ecomorphological variation. Our results show that the morphological diversity of ornithodirans started to flourish among early-diverging lineages and not only after the origins of dinosaurs and pterosaurs.

Tropical forests are approaching critical temperature thresholds.

The critical temperature beyond which photosynthetic machinery in tropical trees begins to fail averages approximately 46.7 °C (Tcrit)1. However, it remains unclear whether leaf temperatures experienced by tropical vegetation approach this threshold or soon will under climate change. Here we found that pantropical canopy temperatures independently triangulated from individual leaf thermocouples, pyrgeometers and remote sensing (ECOSTRESS) have midday peak temperatures of approximately 34 °C during dry periods, with a long high-temperature tail that can exceed 40 °C. Leaf thermocouple data from multiple sites across the tropics suggest that even within pixels of moderate temperatures, upper canopy leaves exceed Tcrit 0.01% of the time. Furthermore, upper canopy leaf warming experiments (+2, 3 and 4 °C in Brazil, Puerto Rico and Australia, respectively) increased leaf temperatures non-linearly, with peak leaf temperatures exceeding Tcrit 1.3% of the time (11% for more than 43.5 °C, and 0.3% for more than 49.9 °C). Using an empirical model incorporating these dynamics (validated with warming experiment data), we found that tropical forests can withstand up to a 3.9 ± 0.5 °C increase in air temperatures before a potential tipping point in metabolic function, but remaining uncertainty in the plasticity and range of Tcrit in tropical trees and the effect of leaf death on tree death could drastically change this prediction. The 4.0 °C estimate is within the 'worst-case scenario' (representative concentration pathway (RCP) 8.5) of climate change predictions2 for tropical forests and therefore it is still within our power to decide (for example, by not taking the RCP 6.0 or 8.5 route) the fate of these critical realms of carbon, water and biodiversity3,4.

Deep whole-genome ctDNA chronology of treatment-resistant prostate cancer.

Circulating tumour DNA (ctDNA) in blood plasma is an emerging tool for clinical cancer genotyping and longitudinal disease monitoring1. However, owing to past emphasis on targeted and low-resolution profiling approaches, our understanding of the distinct populations that comprise bulk ctDNA is incomplete2-12. Here we perform deep whole-genome sequencing of serial plasma and synchronous metastases in patients with aggressive prostate cancer. We comprehensively assess all classes of genomic alterations and show that ctDNA contains multiple dominant populations, the evolutionary histories of which frequently indicate whole-genome doubling and shifts in mutational processes. Although tissue and ctDNA showed concordant clonally expanded cancer driver alterations, most individual metastases contributed only a minor share of total ctDNA. By comparing serial ctDNA before and after clinical progression on potent inhibitors of the androgen receptor (AR) pathway, we reveal population restructuring converging solely on AR augmentation as the dominant genomic driver of acquired treatment resistance. Finally, we leverage nucleosome footprints in ctDNA to infer mRNA expression in synchronously biopsied metastases, including treatment-induced changes in AR transcription factor signalling activity. Our results provide insights into cancer biology and show that liquid biopsy can be used as a tool for comprehensive multi-omic discovery.

Malaria protection due to sickle haemoglobin depends on parasite genotype.

Host genetic factors can confer resistance against malaria1, raising the question of whether this has led to evolutionary adaptation of parasite populations. Here we searched for association between candidate host and parasite genetic variants in 3,346 Gambian and Kenyan children with severe malaria caused by Plasmodium falciparum. We identified a strong association between sickle haemoglobin (HbS) in the host and three regions of the parasite genome, which is not explained by population structure or other covariates, and which is replicated in additional samples. The HbS-associated alleles include nonsynonymous variants in the gene for the acyl-CoA synthetase family member2-4 PfACS8 on chromosome 2, in a second region of chromosome 2, and in a region containing structural variation on chromosome 11. The alleles are in strong linkage disequilibrium and have frequencies that covary with the frequency of HbS across populations, in particular being much more common in Africa than other parts of the world. The estimated protective effect of HbS against severe malaria, as determined by comparison of cases with population controls, varies greatly according to the parasite genotype at these three loci. These findings open up a new avenue of enquiry into the biological and epidemiological significance of the HbS-associated polymorphisms in the parasite genome and the evolutionary forces that have led to their high frequency and strong linkage disequilibrium in African P. falciparum populations.

MeCP2 Represses the Rate of Transcriptional Initiation of Highly Methylated Long Genes.

Mutations in the methyl-DNA-binding repressor protein MeCP2 cause the devastating neurodevelopmental disorder Rett syndrome. It has been challenging to understand how MeCP2 regulates transcription because MeCP2 binds broadly across the genome and MeCP2 mutations are associated with widespread small-magnitude changes in neuronal gene expression. We demonstrate here that MeCP2 represses nascent RNA transcription of highly methylated long genes in the brain through its interaction with the NCoR co-repressor complex. By measuring the rates of transcriptional initiation and elongation directly in the brain, we find that MeCP2 has no measurable effect on transcriptional elongation, but instead represses the rate at which Pol II initiates transcription of highly methylated long genes. These findings suggest a new model of MeCP2 function in which MeCP2 binds broadly across highly methylated regions of DNA, but acts at transcription start sites to attenuate transcriptional initiation.

Magnetic Strategies for Nervous System Control.

Magnetic fields pass through tissue undiminished and without producing harmful effects, motivating their use as a wireless, minimally invasive means to control neural activity. Here, we review mechanisms and techniques coupling magnetic fields to changes in electrochemical potentials across neuronal membranes. Biological magnetoreception, although incompletely understood, is discussed as a potential source of inspiration. The emergence of magnetic properties in materials is reviewed to clarify the distinction between biomolecules containing transition metals and ferrite nanoparticles that exhibit significant net moments. We describe recent developments in the use of magnetic nanomaterials as transducers converting magnetic stimuli to forms readily perceived by neurons and discuss opportunities for multiplexed and bidirectional control as well as the challenges posed by delivery to the brain. The variety of magnetic field conditions and mechanisms by which they can be coupled to neuronal signaling cascades highlights the desirability of continued interchange between magnetism physics and neurobiology.

Optical coherence tomography-guided Brillouin microscopy highlights regional tissue stiffness differences during anterior neural tube closure in the Mthfd1l murine mutant.

Neurulation is a highly synchronized biomechanical process leading to the formation of the brain and spinal cord, and its failure leads to neural tube defects (NTDs). Although we are rapidly learning the genetic mechanisms underlying NTDs, the biomechanical aspects are largely unknown. To understand the correlation between NTDs and tissue stiffness during neural tube closure (NTC), we imaged an NTD murine model using optical coherence tomography (OCT), Brillouin microscopy and confocal fluorescence microscopy. Here, we associate structural information from OCT with local stiffness from the Brillouin signal of embryos undergoing neurulation. The stiffness of neuroepithelial tissues in Mthfd1l null embryos was significantly lower than that of wild-type embryos. Additionally, exogenous formate supplementation improved tissue stiffness and gross embryonic morphology in nullizygous and heterozygous embryos. Our results demonstrate the significance of proper tissue stiffness in normal NTC and pave the way for future studies on the mechanobiology of normal and abnormal embryonic development.

Molecular circadian rhythms are robust in marine annelids lacking rhythmic behavior.

The circadian clock controls behavior and metabolism in various organisms. However, the exact timing and strength of rhythmic phenotypes can vary significantly between individuals of the same species. This is highly relevant for rhythmically complex marine environments where organismal rhythmic diversity likely permits the occupation of different microenvironments. When investigating circadian locomotor behavior of Platynereis dumerilii, a model system for marine molecular chronobiology, we found strain-specific, high variability between individual worms. The individual patterns were maintained for several weeks. A diel head transcriptome comparison of behaviorally rhythmic versus arrhythmic wild-type worms showed that 24-h cycling of core circadian clock transcripts is identical between both behavioral phenotypes. While behaviorally arrhythmic worms showed a similar total number of cycling transcripts compared to their behaviorally rhythmic counterparts, the annotation categories of their transcripts, however, differed substantially. Consistent with their locomotor phenotype, behaviorally rhythmic worms exhibit an enrichment of cycling transcripts related to neuronal/behavioral processes. In contrast, behaviorally arrhythmic worms showed significantly increased diel cycling for metabolism- and physiology-related transcripts. The prominent role of the neuropeptide pigment-dispersing factor (PDF) in Drosophila circadian behavior prompted us to test for a possible functional involvement of Platynereis pdf. Differing from its role in Drosophila, loss of pdf impacts overall activity levels but shows only indirect effects on rhythmicity. Our results show that individuals arrhythmic in a given process can show increased rhythmicity in others. Across the Platynereis population, rhythmic phenotypes exist as a continuum, with no distinct "boundaries" between rhythmicity and arrhythmicity. We suggest that such diel rhythm breadth is an important biodiversity resource enabling the species to quickly adapt to heterogeneous or changing marine environments. In times of massive sequencing, our work also emphasizes the importance of time series and functional tests.

Genomic reconstruction of the SARS-CoV-2 epidemic in England.

The evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus leads to new variants that warrant timely epidemiological characterization. Here we use the dense genomic surveillance data generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of subepidemics that peaked in early autumn 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. The Alpha variant grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed the Alpha variant and eliminated nearly all other lineages in early 2021. Yet a series of variants (most of which contained the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. However, by accounting for sustained introductions, we found that the transmissibility of these variants is unlikely to have exceeded the transmissibility of the Alpha variant. Finally, B.1.617.2/Delta was repeatedly introduced in England and grew rapidly in early summer 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on 26 June 2021.

TMPRSS2-mediated SARS-CoV-2 uptake boosts innate immune activation, enhances cytopathology, and drives convergent virus evolution.

The accessory protease transmembrane protease serine 2 (TMPRSS2) enhances severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uptake into ACE2-expressing cells, although how increased entry impacts downstream viral and host processes remains unclear. To investigate this in more detail, we performed infection assays in engineered cells promoting ACE2-mediated entry with and without TMPRSS2 coexpression. Electron microscopy and inhibitor experiments indicated TMPRSS2-mediated cell entry was associated with increased virion internalization into endosomes, and partially dependent upon clathrin-mediated endocytosis. TMPRSS2 increased panvariant uptake efficiency and enhanced early rates of virus replication, transcription, and secretion, with variant-specific profiles observed. On the host side, transcriptional profiling confirmed the magnitude of infection-induced antiviral and proinflammatory responses were linked to uptake efficiency, with TMPRSS2-assisted entry boosting early antiviral responses. In addition, TMPRSS2-enhanced infections increased rates of cytopathology, apoptosis, and necrosis and modulated virus secretion kinetics in a variant-specific manner. On the virus side, convergent signatures of cell-uptake-dependent innate immune induction were recorded in viral genomes, manifesting as switches in dominant coupled Nsp3 residues whose frequencies were correlated to the magnitude of the cellular response to infection. Experimentally, we demonstrated that selected Nsp3 mutations conferred enhanced interferon antagonism. More broadly, we show that TMPRSS2 orthologues from evolutionarily diverse mammals facilitate panvariant enhancement of cell uptake. In summary, our study uncovers previously unreported associations, linking cell entry efficiency to innate immune activation kinetics, cell death rates, virus secretion dynamics, and convergent selection of viral mutations. These data expand our understanding of TMPRSS2's role in the SARS-CoV-2 life cycle and confirm its broader significance in zoonotic reservoirs and animal models.

Improved protein structure prediction using potentials from deep learning.

Protein structure prediction can be used to determine the three-dimensional shape of a protein from its amino acid sequence1. This problem is of fundamental importance as the structure of a protein largely determines its function2; however, protein structures can be difficult to determine experimentally. Considerable progress has recently been made by leveraging genetic information. It is possible to infer which amino acid residues are in contact by analysing covariation in homologous sequences, which aids in the prediction of protein structures3. Here we show that we can train a neural network to make accurate predictions of the distances between pairs of residues, which convey more information about the structure than contact predictions. Using this information, we construct a potential of mean force4 that can accurately describe the shape of a protein. We find that the resulting potential can be optimized by a simple gradient descent algorithm to generate structures without complex sampling procedures. The resulting system, named AlphaFold, achieves high accuracy, even for sequences with fewer homologous sequences. In the recent Critical Assessment of Protein Structure Prediction5 (CASP13)-a blind assessment of the state of the field-AlphaFold created high-accuracy structures (with template modelling (TM) scores6 of 0.7 or higher) for 24 out of 43 free modelling domains, whereas the next best method, which used sampling and contact information, achieved such accuracy for only 14 out of 43 domains. AlphaFold represents a considerable advance in protein-structure prediction. We expect this increased accuracy to enable insights into the function and malfunction of proteins, especially in cases for which no structures for homologous proteins have been experimentally determined7.

A dynamical model of growth and maturation in Drosophila.

The decision to stop growing and mature into an adult is a critical point in development that determines adult body size, impacting multiple aspects of an adult's biology. In many animals, growth cessation is a consequence of hormone release that appears to be tied to the attainment of a particular body size or condition. Nevertheless, the size-sensing mechanism animals use to initiate hormone synthesis is poorly understood. Here, we develop a simple mathematical model of growth cessation in Drosophila melanogaster, which is ostensibly triggered by the attainment of a critical weight (CW) early in the last instar. Attainment of CW is correlated with the synthesis of the steroid hormone ecdysone, which causes a larva to stop growing, pupate, and metamorphose into the adult form. Our model suggests that, contrary to expectation, the size-sensing mechanism that initiates metamorphosis occurs before the larva reaches CW; that is, the critical-weight phenomenon is a downstream consequence of an earlier size-dependent developmental decision, not a decision point itself. Further, this size-sensing mechanism does not require a direct assessment of body size but emerges from the interactions between body size, ecdysone, and nutritional signaling. Because many aspects of our model are evolutionarily conserved among all animals, the model may provide a general framework for understanding how animals commit to maturing from their juvenile to adult form.

Design of rigid protein-protein interaction inhibitors enables targeting of undruggable Mcl-1.

The structure-based design of small-molecule inhibitors targeting protein-protein interactions (PPIs) remains a huge challenge as the drug must bind typically wide and shallow protein sites. A PPI target of high interest for hematological cancer therapy is myeloid cell leukemia 1 (Mcl-1), a prosurvival guardian protein from the Bcl-2 family. Despite being previously considered undruggable, seven small-molecule Mcl-1 inhibitors have recently entered clinical trials. Here, we report the crystal structure of the clinical-stage inhibitor AMG-176 bound to Mcl-1 and analyze its interaction along with clinical inhibitors AZD5991 and S64315. Our X-ray data reveal high plasticity of Mcl-1 and a remarkable ligand-induced pocket deepening. Nuclear Magnetic Resonance (NMR)-based free ligand conformer analysis demonstrates that such unprecedented induced fit is uniquely achieved by designing highly rigid inhibitors, preorganized in their bioactive conformation. By elucidating key chemistry design principles, this work provides a roadmap for targeting the largely untapped PPI class more successfully.

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs.

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species, this can affect the health of humans as well as livestock. Here, we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography, and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realized.