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More than twelve morphologically and physiologically distinct subtypes of primary somatosensory neuron report salient features of our internal and external environments 1 , 2 , 3 – 4 . It is unclear how specialized gene expression programs emerge during development to endow these subtypes with their unique properties. To assess the developmental progression of transcriptional maturation of each subtype of principal somatosensory neuron, we generated a transcriptomic atlas of cells traversing the primary somatosensory neuron lineage in mice. Here we show that somatosensory neurogenesis gives rise to neurons in a transcriptionally unspecialized state, characterized by co-expression of transcription factors that become restricted to select subtypes as development proceeds. Single-cell transcriptomic analyses of sensory neurons from mutant mice lacking transcription factors suggest that these broad-to-restricted transcription factors coordinate subtype-specific gene expression programs in subtypes in which their expression is maintained. We also show that neuronal targets are involved in this process; disruption of the prototypic target-derived neurotrophic factor NGF leads to aberrant subtype-restricted patterns of transcription factor expression. Our findings support a model in which cues that emanate from intermediate and final target fields promote neuronal diversification in part by transitioning cells from a transcriptionally unspecialized state to transcriptionally distinct subtypes by modulating the selection of subtype-restricted transcription factors. Neuronal targets mediate the emergence of somatosensory neuron subtypes by altering the expression of neuronal transcription factors.

Evolutionary dynamics in spatially structured populations has been studied for a long time. More recently, the focus has been to construct structures that amplify selection by fixing beneficial mutations with higher probability than the well-mixed population and lower probability of fixation for deleterious mutations. It has been shown that for a structure to substantially amplify selection, self-loops are necessary when mutants appear predominately in nodes that change often. As a result, for low mutation rates, self-looped amplifiers attain higher steady-state average fitness in the mutation-selection balance than well-mixed populations. But what happens when the mutation rate increases such that fixation probabilities alone no longer describe the dynamics? We show that self-loops effects are detrimental outside the low mutation rate regime. In the intermediate and high mutation rate regime, amplifiers of selection attain lower steady-state average fitness than the complete graph and suppressors of selection. We also provide an estimate of the mutation rate beyond which the mutation-selection dynamics on a graph deviates from the weak mutation rate approximation. It involves computing average fixation time scaling with respect to the population sizes for several graphs.

To improve lithium-ion battery technology, it is essential to probe and comprehend the microscopic dynamic processes that occur in a real-world composite electrode under operating conditions. The primary and secondary particles are the structural building blocks of battery cathode electrodes. Their dynamic inconsistency has profound but not well-understood impacts. In this research, we combine operando coherent multi-crystal diffraction and optical microscopy to examine the chemical dynamics in local domains of layered oxide cathode. Our results not only pinpoint the asynchronicity of the lithium (de)intercalation at the sub-particle level, but also reveal sophisticated diffusion kinetics and reaction patterns, involving various localized processes, e.g., chemical onset, reaction front propagation, domains equilibration, particle deformation and motion. These observations shed new lights onto the activation and degradation mechanisms of state-of-the-art battery cathode materials. The battery performance at the cell level is an integration of contributions from many active particles. Here, the authors present a direct visualization of the active cathode particles that react heterogeneously and asynchronously by using coherent multi-crystal diffraction and optical microscopy.

The transcription factor NPAS4 enables neurons to distinguish synaptic inputs received at their soma or dendrites; sensory stimulation increases NPAS4 which promotes inhibitory synapses on the soma and destabilizes inhibitory synapses on the dendrites. Activity-dependent neuronal activity Individual neurons distinguish synaptic inputs received at their soma and dendrites, but how behaviour may affect their balance has been unclear. Now Michael Greenberg and colleagues show that mouse hippocampus neurons respond to sensory enrichment with increased levels of the transcription factor NPAS4 and its target-gene product, brain derived neurotrophic factor (BDNF), which then promotes inhibitory synapses on the cell body while destabilizing those on dendrites. Thus individual neurons respond to sensory stimulation by redrawing the map of their inhibitory inputs, restricting their somatic output while promoting plasticity at their dendrites. A heterogeneous population of inhibitory neurons controls the flow of information through a neural circuit 1 , 2 , 3 . Inhibitory synapses that form on pyramidal neuron dendrites modulate the summation of excitatory synaptic potentials 4 , 5 , 6 and prevent the generation of dendritic calcium spikes 7 , 8 . Precisely timed somatic inhibition limits both the number of action potentials and the time window during which firing can occur 8 , 9 . The activity-dependent transcription factor NPAS4 regulates inhibitory synapse number and function in cell culture 10 , but how this transcription factor affects the inhibitory inputs that form on distinct domains of a neuron in vivo was unclear. Here we show that in the mouse hippocampus behaviourally driven expression of NPAS4 coordinatesthe redistribution of inhibitory synapses made onto a CA1 pyramidal neuron, simultaneously increasing inhibitory synapse number on the cell body while decreasing the number of inhibitory synapses on the apical dendrites. This rearrangement of inhibition is mediated in part by the NPAS4 target gene brain derived neurotrophic factor ( Bdnf ), which specifically regulates somatic, and not dendritic, inhibition. These findings indicate that sensory stimuli, by inducing NPAS4 and its target genes, differentially control spatial features of neuronal inhibition in a way that restricts the output of the neuron while creating a dendritic environment that is permissive for plasticity.

STING is a nodal point for cellular innate immune response to microbial infections, autoimmunity and cancer; it triggers the synthesis of the antiviral proteins, type I interferons. Many DNA viruses, including Herpes Simplex Virus 1 (HSV1), trigger STING signaling causing inhibition of virus replication. Here, we report that HSV1 evades this antiviral immune response by inducing a cellular microRNA, miR-24, which binds to the 3’ untranslated region of STING mRNA and inhibits its translation. Expression of the gene encoding miR-24 is induced by the transcription factor AP1 and activated by MAP kinases in HSV1-infected cells. Introduction of exogenous miR-24 or prior activation of MAPKs, causes further enhancement of HSV1 replication in STING-expressing cells. Conversely, transfection of antimiR-24 inhibits virus replication in those cells. HSV1 infection of mice causes neuropathy and death; using two routes of infection, we demonstrated that intracranial injection of antimiR-24 alleviates both morbidity and mortality of the infected mice. Our studies reveal a new immune evasion strategy adopted by HSV1 through the regulation of STING and demonstrates that it can be exploited to enhance STING’s antiviral action.

Birth-death models are used to understand the interplay of genetic drift and natural selection. While well-mixed populations remain unaffected by the order of birth and death and where selection acts, evolutionary outcomes in spatially structured populations are affected by these choices. We show that the choice of individual moving to vacant sites—parent or offspring—controls the initial mutant placement on a graph and hence alters its fixation probability. Moving parent individuals introduces, to our knowledge, previously unexplored update rules and fixation categories for heterogeneous graphs. We identify a class of graphs, amplifiers of fixation, where fixation probability is larger than in well-mixed populations, regardless of the mutant fitness. Under death-Birth parent moving, the star graph is an amplifier of fixation, with a non-zero fixation probability for deleterious mutants, in contrast to very large well-mixed populations. Most Erdős-Rényi graphs of size 8 are amplifiers of fixation under death-Birth parent moving, but suppressors of fixation under Birth-death offspring moving. Surprisingly, amplifiers of fixation attain lower fitness in long-term evolution, despite favouring beneficial mutants, while suppressors of fixation attain higher fitness. These counterintuitive findings are explained by the fate of deleterious mutations and highlight the crucial role of deleterious mutants for adaptive evolution. In birth-death models, the evolution of spatially structured populations is impacted by the order of birth and death events. Here, the authors demonstrate that moving the parent to a vacant site leads to new update rules where mutants have a higher probability of fixation.

Behavioural experiences activate the FOS transcription factor in sparse populations of neurons that are critical for encoding and recalling specific events 1 – 3 . However, there is limited understanding of the mechanisms by which experience drives circuit reorganization to establish a network of Fos -activated cells. It is also not known whether FOS is required in this process beyond serving as a marker of recent neural activity and, if so, which of its many gene targets underlie circuit reorganization. Here we demonstrate that when mice engage in spatial exploration of novel environments, perisomatic inhibition of Fos -activated hippocampal CA1 pyramidal neurons by parvalbumin-expressing interneurons is enhanced, whereas perisomatic inhibition by cholecystokinin-expressing interneurons is weakened. This bidirectional modulation of inhibition is abolished when the function of the FOS transcription factor complex is disrupted. Single-cell RNA-sequencing, ribosome-associated mRNA profiling and chromatin analyses, combined with electrophysiology, reveal that FOS activates the transcription of Scg2 , a gene that encodes multiple distinct neuropeptides, to coordinate these changes in inhibition. As parvalbumin- and cholecystokinin-expressing interneurons mediate distinct features of pyramidal cell activity 4 – 6 , the SCG2-dependent reorganization of inhibitory synaptic input might be predicted to affect network function in vivo. Consistent with this prediction, hippocampal gamma rhythms and pyramidal cell coupling to theta phase are significantly altered in the absence of Scg2 . These findings reveal an instructive role for FOS and SCG2 in establishing a network of Fos -activated neurons via the rewiring of local inhibition to form a selectively modulated state. The opposing plasticity mechanisms acting on distinct inhibitory pathways may support the consolidation of memories over time. Novel experiences in mice lead to opposing effects on inhibition of Fos -activated hippocampal CA1 pyramidal neurons by parvalbumin- and cholecystokinin-expressing interneurons, revealing the roles of FOS and SCG2 in neural plasticity and consolidation of memories.

A diagnosis of MND takes an average 10-16 months from symptom onset. Early diagnosis is important to access supportive measures to maximise quality of life. The COVID-19 pandemic has caused significant delays in NHS pathways; the majority of GP appointments now occur online with subsequent delays in secondary care assessment. Given the rapid progression of MND, patients may be disproportionately affected resulting in late stage new presentations. We used Monte Carlo simulation to model the pre-COVID-19 diagnostic pathway and then introduced plausible COVID-19 delays. The diagnostic pathway was modelled using gamma distributions of time taken: 1) from symptom onset to GP presentation, 2) for specialist referral, and 3) for diagnosis reached after neurology appointment. We incorporated branches to simulate delays: when patients did not attend their GP and when the GP consultation did not result in referral. An emergency presentation was triggered when diagnostic pathway time was within 30 days of projected median survival. Total time-to-diagnosis was calculated over 100,000 iterations. The pre-COVID-19 model was estimated using published data and the Improving MND Care Survey 2019. We estimated COVID-19 delays using published statistics. The pre-COVID model reproduced known features of the MND diagnostic pathway, with a median time to diagnosis of 399 days and predicting 5.2% of MND patients present as undiagnosed emergencies. COVID-19 resulted in diagnostic delays from 558 days when only primary care was 25% delayed, to 915 days when both primary and secondary care were 75%. The model predicted an increase in emergency presentations ranging from 15.4%-44.5%. The model suggests the COVID-19 pandemic will result in later-stage diagnoses and more emergency presentations of undiagnosed MND. Late-stage presentations may require rapid escalation to multidisciplinary care. Proactive recognition of acute and late-stage disease with altered service provision will optimise care for people with MND.

The human gut microbiome interacts with many diseases, with recent small studies suggesting a link with COVID-19 severity. Exploring this association at the population-level may provide novel insights and help to explain differences in COVID-19 severity between countries. We explore whether there is an association between the gut microbiome of people within different countries and the severity of COVID-19, measured as hospitalisation rate. We use data from the large (n = 3,055) open-access gut microbiome repository curatedMetagenomicData, as well as demographic and country-level metadata. Twelve countries were placed into two groups (high/low) according to COVID-19 hospitalisation rate before December 2020 (ourworldindata.com). We use an unsupervised machine learning method, Topological Data Analysis (TDA). This method analyses both the local geometry and global topology of a high-dimensional dataset, making it particularly suitable for population-level microbiome data. We report an association of distinct baseline population-level gut microbiome signatures with COVID-19 severity. This was found both with a PERMANOVA, as well as with TDA. Specifically, it suggests an association of anti-inflammatory bacteria, including Bifidobacteria species and Eubacterium rectale , with lower severity, and pro-inflammatory bacteria such as Prevotella copri with higher severity. This study also reports a significant impact of country-level confounders, specifically of the proportion of over 70-year-olds in the population, GDP, and human development index. Further interventional studies should examine whether these relationships are causal, as well as considering the contribution of other variables such as genetics, lifestyle, policy, and healthcare system. The results of this study support the value of a population-level association design in microbiome research in general and for the microbiome-COVID-19 relationship, in particular. Finally, this research underscores the potential of TDA for microbiome studies, and in identifying novel associations.