Somnotate: An accurate, robust, and flexible sleep stage classifier for the experimentalist Manual sleep stage annotation is a time-consuming but often essential step in the analysis of sleep data. To address this bottleneck we need automated approaches that exhibit high levels of performance, are robust under different experimental conditions, are accessible, and meet the specific needs of sleep scientists. Here we develop an unbiased framework for assessing automated performance against a consensus derived from multiple experienced researchers. We then construct a new sleep stage classifier that combines automated feature extraction using linear discriminant analysis, with inference based on vigilance state-dependent contextual information using a hidden Markov model. This produces annotation accuracies that exceed expert performance on rodent electrophysiological data. We demonstrate that the classifier is robust to errors in the training data, compatible with different recording configurations, and maintains high performance during experimental interventions including sleep deprivation and optogenetic manipulations. Finally, the classifier quantifies and reports its certainty, which can be leveraged to identify ambiguous epochs for further examination. Ambiguous epochs are shown to include unsuccessful transitions between vigilance states, which may offer new insight into the mechanisms underlying sleep-wake dynamics. We call our classifier  Somnotate and make an implementation available to the neuroscience community.
Spontaneous emergence of music detectors in a deep neural network Music exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. These characteristics suggest an innateness of the sense of music in our brain, but it is unclear how this innateness emerges and what functions it has. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. By simulating the responses of network units to 35,487 natural sounds in 527 categories, we found that various subclasses of music are strongly clustered in the embedding space, and that this clustering arises from the music-selective response of the network units. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. We confirmed that the process of generalization is critical for the emergence of music-selectivity and that music-selectivity can work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that our sense of music can be innate, universally shaped by evolutionary adaptation to process natural sound.

One-sentence summaryMusic-selectivity can arise spontaneously in deep neural networks trained for natural sound detection without learning music.
Pathways of savannization in a mesic African savanna-forest mosaic O_LIFires in savannas limit tree cover, thereby promoting flammable grass accumulation and fuelling further frequent fires. Meanwhile, forests and thickets form dense canopies that reduce C4-grass fuel loads and creating a humid microclimate, thereby excluding fires under typical climatic conditions.
C_LIO_LIHowever, extreme fires occasionally burn into these closed-canopy systems. Although these rare fires cause substantial tree mortality and can make repeat fires more likely, the long-term consequences of an extreme fire for closed canopy vegetation structure and potential to convert to savanna (hereafter "savannization") remain largely unknown.
C_LIO_LIHere, we analysed whether an extreme fire could, alone, alter species composition, vegetation structure, and fire regimes of closed-canopy ecosystems in an intact savanna-forest-thicket mosaic, or whether successive fires after an initial extreme fire were necessary to trigger a biome transition between from forest to savanna.
C_LIO_LIWe found that forests that only burned once recovered, whereas those that burned again following an initial extreme fire transitioned from closed-canopy forests towards open, grassy savannas.
C_LIO_LIWhile thickets had less tree mortality in fires than forests, repeat fires nonetheless precipitated a transition towards savannas.
C_LIO_LIColonization of the savanna tree community lagged behind the grass community, but also began to transition.
C_LI

SynthesisOur results suggest that rare extreme fires, followed by repeated burning can indeed result in savannization in places where savanna and forest represent alternative stable states. Pattern Recognition Receptor for Bacterial Lipopolysaccharide in the Cytosol of Human Macrophages Endotoxin, a component of bacterial lipopolysaccharide (LPS), is a driver of the lethal infection sepsis through activation of innate immune responses. When delivered to the cytosol of macrophages, LPS (cLPS) induces the assembly of an inflammasome that contains caspases-4/5 in humans or caspase-11 in mice. Whereas activation of all other inflammasomes is triggered by sensing of pathogen products by a specific host cytosolic pattern recognition receptor protein, whether pattern recognition receptors for cLPS exist has been doubted by many investigators, as caspases-4, -5, and -11 bind and activate LPS directly in vitro. Here we show that the primate-specific protein NLRP11 is a pattern recognition receptor for cLPS required for efficient activation of the caspase-4 inflammasome in human macrophages. NLRP11 is present in humans and other primates, but absent in mice, likely explaining why it has been missed in screens looking for innate immune signaling molecules, most of which have been carried out in mice. NLRP11 is a previously missing link and a component of the human caspase-4 inflammasome activation pathway.

One Sentence SummaryDiscovery that human macrophages contain a cytosolic sensor for endotoxin-containing bacterial lipopolysaccharide. HYBRID REACTION-DIFFUSION AND CLOCK-AND-WAVEFRONT MODEL FOR THE ARREST OF OSCILLATIONS IN THE SOMITOGENESIS SEGMENTATION CLOCK AO_SCPLOWBSTRACTC_SCPLOWThe clock and wavefront paradigm is arguably the most widely accepted model for explaining the embryonic process of somitogenesis. According to this model, somitogenesis is based upon the interaction between a genetic oscillator, known as segmentation clock, and a differentiation wavefront, which provides the positional information indicating where each pair of somites is formed. Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation. Cotterell et al. called it a progressive oscillatory reaction-diffusion (PORD) model. In the Meinhardt-PORD model, somitogenesis is driven by short-range interactions and the posterior movement of the front is a local, emergent phenomenon, which is not controlled by global positional information. With this model, it is possible to explain some experimental observations that are incompatible with the clock and wavefront model. However the Meinhardt-PORD model has some important disadvantages of its own. Namely, it is quite sensitive to fluctuations and depends on very specific initial conditions (which are not biologically realistic). In this work, we propose an equivalent Meinhardt-PORD model, and then amend it to couple it with a wavefront consisting of a receding morphogen gradient. By doing so, we get a hybrid model between the Meinhardt-PORD and the clock-and-wavefront ones, which overcomes most of the deficiencies of the two originating models.

Somitogenesis, the process by which somites are formed, is an essential developmental stage in many vertebrates. This process occurs with a strikingly regular periodicity, that is preserved among embryos of a single species. The clock and wavefront paradigm is arguably the most widely accepted model for explaining somitogenesis. However, it is incapable of explaining some experimental facts, like the appearance of somites in the absence of an external wavefront (i.e. a receding morphogen gradient). Shortly after the clock and wavefront paradigm was introduced, Meinhardt presented a conceptually different mathematical model for morphogenesis in general, and somitogenesis in particular. Recently, Cotterell et al. rediscovered an equivalent model by systematically enumerating and studying small networks performing segmentation, and called it a progressive oscillatory reaction-diffusion (PORD) model. The Meinhardt-PORD model tackles some of the deficiencies of the clock and wave-front models, but it has some serious issues of its own. In the present work, we introduce an equivalent Meinhardt-PORD model, and then amend it to couple it with a receding morphogen gradient. By doing so, we get a hybrid model that incorporates characteristics of the Meinhardt-PORD and clock-and-wavefront models. We show that this hybrid model under-goes a bifurcation, from a stable to an unstable limit cycle, as the value of the parameter accounting for a background regulatory input (associated to the receding morphogen gradient) decreases. This bifurcation allows the model to explain why somites can form in the absence of an external wavefront, reassesses the role of the receding morphogen gradient as a conductor for somitogenesis, and makes the model behavior robust to random fluctuations, as well as independent from specific initial conditions (the latter, are two of the weak points of the Meinhardt-PORD model). We argue that this findings provide convincing evidence that reaction-diffusion and positional information (receding morphogen gradient) mechanisms could work together in somitogenesis. The "dark matter" of protein variants carries a distinct DNA signature and predicts damaging variant effects AO_SCPLOWBSTRACTC_SCPLOWSignatures of DNA motifs associated with distinct mutagenic exposures have been defined for somatic variants, but little is known about the consequences different mutational processes pose to the cell, especially how mutagens exert damage on specific proteins and their three-dimensional structures. Here we identify a DNA mutational signature which corresponds to damaging protein variants. We show that this mutational signature is under-sampled in sequencing data from tumour cohorts, constituting the "dark matter" of the mutational landscape which could only be accessed using deep mutational scanning (DMS) data. By training a set of gradient boosting classifiers, we illustrate that DMS data from only a handful ({approx} 10) of experiments can accurately predict variant impact, and that DNA mutational signatures embed information about the protein-level impact of variants. We bridge the gap between DNA sequence variations and protein-level consequences, discuss the significance of this signature in informing protein design and molecular principles of protein stability, and clarify the relationship between disease association and the true impact mutations bring to protein function. Glucose regulates expression of pro-inflammatory genes IL-1β and IL-12 through a mechanism involving hexosamine biosynthesis pathway dependent regulation of α-E catenin in the RAW 264.7 macrophage cell line High glucose levels are associated with changes in macrophage polarization and evidence indicates that the sustained or even short-term high glucose levels modulate inflammatory responses in macrophages. However, the mechanism by which macrophages can sense the changes in glucose levels are not clearly understood. We find that high glucose levels rapidly increase the -E catenin protein level in RAW264.7 macrophages. We also find an attenuation of glucose induced increase of -E catenin when hexosamine biosynthesis pathway is inhibited either with glutamine depletion or with the drugs azaserine and tunicamycin. This indicates the involvement of hexosamine biosynthesis pathway in this process. Then, we investigated the potential role of -E catenin in glucose induced macrophage polarization. We find that the reduction of -E catenin level using siRNA attenuates the glucose induced change of IL-1{beta} mRNA level under LPS stimulated condition. Further, we identified that the depletion of -E catenin also decreases the IL-12 gene expression in basal glucose conditions leading to a reduction of glucose induced changes in IL-12. Together this indicates that -E catenin can sense the changes in glucose levels in macrophages via hexosamine biosynthesis pathway and also can modulate the glucose induced gene expression of inflammatory markers such as IL-1-{beta} and IL-12. This identifies a new part of the mechanism by which macrophages are able to respond to changes in glucose levels. Naming Human Diseases: Ethical Principles of Curating Exclusive Substitute for Inopportune Nosology BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin BackgroundEvolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation at many enhancers, distal regulatory elements that control spatio-temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific, code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

ResultsWe present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that is able to predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Then, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity and liver enhancers associated with liver regeneration have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

ConclusionThe framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements. Conserved organ-specific microbial assemblages in different populations of a terrestrial crab Brachyuran crabs originated in the oceans and evolved specific morphological and physiological adaptations to live in freshwater, intertidal and even terrestrial habitats but the role of a selection mechanism involving symbiotic microorganisms long these colonization processes are not known. In this work we investigated the associated microbiota of three populations of a terrestrial brachyuran crab, Chiromantes haematocheir, to find evidence of a conserved crab-specific microbiome unrelated to the population of origin and dissimilar from environmental microbial assemblages. Bacterial 16S rRNA gene and fungal ITS sequences were obtained from selected crab organs and environmental matrices to profile microbial communities. In spite of the presence of truly marine larval stages and no gregarious behaviour, favouring microbiota exchanges, we found common, organ-specific microbiota, associated to the gut and the gills of the crabs (with more than 15% of the genera detected specifically enriched only in one organ). Our results suggest an early establishment of a new common, stable microbiota in the transition from water to land. Decellularized Normal and Tumor Extracellular Matrix as Scaffold for Cancer Organoid Cultures of Colorectal Peritoneal Metastases Peritoneal metastases (PM) from colorectal cancer (CRC) are associated with poor survival. The extracellular matrix (ECM) plays a fundamental role in modulating the homing of CRC metastases to the peritoneum. The mechanisms underlying the interactions between metastatic cells and the ECM, however, remain poorly understood and the number of in vitro models available for the study of the peritoneal metastatic process is limited. Here, we show that decellularized ECM of the peritoneal cavity allows the growth of organoids obtained from PM, favoring the development of three-dimensional nodules that maintain the characteristics of in vivo PM. Organoids preferentially grow on scaffolds obtained from neoplastic peritoneum, which are characterized by greater stiffness than normal scaffolds. A gene expression analysis of organoids grown on different substrates reflected faithfully the clinical and biological characteristics of the organoids. An impact of the ECM on the response to standard chemotherapy treatment for PM was also observed.

SignificanceEvidence of the value of ex vivo 3D models obtained by combining patient-derived extracellular matrices depleted of cellular components and organoids to mimic the metastatic niche, to be used as a tool to develop new therapeutic strategies in a biologically relevant context, to personalize treatments and increase their efficacy. Selective Ablation of 3' RNA ends and Processive RTs Facilitate Direct cDNA Sequencing of Full-length Host Cell and Viral Transcripts Alternative splicing (AS) is necessary for viral proliferation in host cells and a critical regulatory component of viral gene expression. Conventional RNA-seq approaches provide incomplete coverage of AS due to their short read-lengths and are susceptible to biases and artifacts introduced in prevailing library preparation methodologies. Moreover, viral splicing studies are often conducted separately from host cell transcriptome analysis, precluding an assessment of the viral manipulation of host splicing machinery. To address current limitations, we developed a quantitative full-length direct cDNA sequencing strategy to simultaneously profile viral and host cell transcripts. This nanopore-based approach couples processive reverse transcriptases with a novel one-step chemical ablation of 3 RNA ends (termed CASPR) which decreases ribosomal RNA reads and enriches for poly-adenylated coding sequences. We extensively validate our approach using synthetic reference transcripts and show CASPR doubles the breadth of coverage per transcript and increases detection of long transcripts (>4kb), while being functionally equivalent to PolyA+ selection for transcript quantification. We used our approach to interrogate host cell and HIV-1 transcript dynamics during viral reactivation and identified novel putative HIV-1 host factors containing exon skipping or novel intron retentions and delineated the HIV-1 transcriptional state associated with these differentially regulated host factors. Somewhere I belong: phylogeny and morphological evolution in a species-rich lineage of ectoparasitic flatworms infecting cichlid fishes AO_SCPLOWBSTRACTC_SCPLOWA substantial portion of biodiversity evolved through adaptive radiation. However, the effects of explosive speciation on species interactions remain poorly understood. Metazoan parasites infecting radiating host lineages could improve our knowledge because of their intimate host relationships. Yet limited molecular, phenotypic, and ecological data discourage multivariate analyses of evolutionary patterns and encourage the use of discrete characters. Here, we assemble new molecular, morphological, and host range data widely inferred from a species-rich lineage of parasites (Cichlidogyrus, Platyhelminthes: Monogenea) infecting cichlid fishes to address data scarcity. We infer a multi-marker (28S/18S rDNA, ITS1, COI mtDNA) phylogeny of 58/137 species and characterise major lineages through synapomorphies inferred from mapping morphological characters. We predict the phylogenetic position of species without DNA data through shared character states, a combined molecular-morphological phylogenetic analysis, and a classification analysis with support vector machines. Based on these predictions and a cluster analysis, we assess the systematic informativeness of continuous characters, search for continuous equivalents for discrete characters, and suggest new characters for morphological traits not analysed to date. We also model the attachment/reproductive organ and host range evolution using the data of 136/137 described species and multivariate phylogenetic comparative methods (PCMs). We show that discrete characters can mask phylogenetic signals but can be key for characterising species groups. Regarding the attachment organ morphology, a divergent evolutionary regime for at least one lineage was detected and a limited morphological variation indicates host and environmental parameters affecting its evolution. However, moderate success in predicting phylogenetic positions, and a low systematic informativeness and high multicollinearity of morphological characters call for a revaluation of characters included in species characterisations. Polycystins are upregulated in fibrotic kidneys and promote renal fibrosis Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. Foraging with friends, moving with anyone: effects of the social environment on movement-integrated habitat selection O_LIMovement links the distribution of habitats with the social environment of animals using those habitats; yet integrating movement, habitat selection, and socioecology remains an opportunity for further study.
C_LIO_LIHere, our objective was to disentangle the roles of habitat selection and social association as drivers of collective movement in a gregarious ungulate. To accomplish this objective, we (1) assessed whether socially familiar individuals form discrete social communities and whether social communities have high spatial, but not necessarily temporal, overlap; and (2) we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection analysis.
C_LIO_LIWe used social network analysis to assign individuals to social communities and determine short and long-term social preference among individuals. Using integrated step selection functions (iSSF), we then modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.
C_LIO_LIBased on assignment of individuals to social communities and home range overlap analyses, individuals assorted into discrete social communities, and these communities had high spatial overlap. By unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals foraged with more familiar individuals, but moved collectively with any between foraging patches.
C_LIO_LIOur study demonstrates that social behaviour and space use are inter-related based on spatial overlap of social communities and movement-dependent habitat selection. Movement, habitat selection, and social behaviour are linked in theory. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.
C_LI Thermal preconditioning in a reef-building coral alleviates oxidative damage through a BI-1 mediated antioxidant response Global coral reef decline is largely driven by the breakdown of the coral-algal symbiosis during temperature stress. Corals can acclimatize to higher temperatures, but the cellular processes underlying this ability are poorly understood. We show that preconditioning-based improvements in thermal tolerance in Pocillopora acuta are accompanied by increases in host glutathione reductase (GR) activity and expression, which prevents DNA damage. A strong correlation between GR and BI-1 expression in heat-stressed preconditioned corals and the presence of an antioxidant response element (ARE) in the GR promoter suggest BI-1 could regulate GR expression through Nrf2/ARE pathway. To fortify this link, we developed an siRNA- mediated gene knockdown protocol and targeted the coral BI-1 gene. BI-1 knock-down specifically decreased GR expression and activity and increased oxidative DNA damage in heat- stressed preconditioned corals, showing that BI-1-mediated enhanced antioxidant response during acute heat stress is a key mechanism that prevents oxidative DNA damage after preconditioning.

TeaserPreconditioning improves redox homeostasis and prevents oxidative stress in a thermally stressed reef-building coral Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC array A variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enabling directional sensitivity and scalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting. Tracking the stochastic growth of bacterial populations in microfluidic droplets Bacterial growth in microfluidic droplets is relevant in biotechnology, in microbial ecology, and in understanding stochastic population dynamics in small populations. However, it has proved challenging to automate measurement of absolute bacterial numbers within droplets, forcing the use of proxy measures for population size. Here we present a microfluidic device and imaging protocol that allows high-resolution imaging of thousands of droplets, such that individual bacteria stay in the focal plane and can be counted automatically. Using this approach, we track the stochastic growth of hundreds of replicate Escherichia coli populations within droplets. We find that, for early times, the statistics of the growth trajectories obey the predictions of the Bellman-Harris model, in which there is no inheritance of division time. Our approach should allow further testing of models for stochastic growth dynamics, as well as contributing to broader applications of droplet-based bacterial culture. Correlational networking guides the discovery of cryptic natural product biosynthetic enzymes Bacterial natural product biosynthetic genes, canonically clustered, have been increasingly found to rely on cryptic enzymes encoded elsewhere in the genome for completion of biosynthesis. The study and application of lanthipeptides are frequently hindered by cryptic proteases required for final maturation. Here, we establish a global correlation network bridging the gap between lanthipeptide precursors and cryptic proteases. Applying our analysis to 161,954 bacterial genomes, we establish 5,209 correlations between precursors and cryptic proteases, with 91 prioritized. We use network predictions and co-expression analysis to reveal a previously missing protease for the maturation of class I lanthipeptide paenilan. We further discover widely distributed bacterial M16B metallopeptidases of previously unclear biological function as a new family of lanthipeptide proteases. We show the involvement of a pair of bifunctional M16B proteases in the production of novel class III lanthipeptides with high substrate specificity. Together, these results demonstrate the strength of our correlational networking approach to the discovery of cryptic lanthipeptide proteases and potentially other missing enzymes for natural products biosynthesis.

Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Immediate and sustained effects of cobalt and zinc-containing pigments on macrophages Pigments are among the oldest nanoparticulate products known to mankind, and their use in tattoos is also very old. Nowadays, 25% American people aged 18 to 50 are tattooed, which poses the question of the delayed effects of tattoos. In this article, we investigated three cobalt (Pigment Violet 14 (purple color)) or cobalt alloy pigments (Pigment Blue 28 (blue color), Pigment Green 14 (green color)), and one zinc pigment (Pigment White 4 (white color)) which constitute a wide range of colors found in tattoos. These pigments contain microparticles and a significant proportion of nanoparticles (in either aggregate or free form). Because of the key role of macrophages in the scavenging of particulate materials, we tested the effects of cobalt- and zinc-based pigments on the J774A.1 macrophage cell line. In order to detect delayed effects, we compared two exposure schemes: acute exposure for 24 hours and an exposure for 24 hours followed by a 3-day post-exposure recovery period. The conjunction of these two schemes allowed for the investigation of the delayed or sustained effects of pigments. All pigments induced functional effects on macrophages, most of which were pigment-dependent. For example, Pigment Green 19, Pigment Blue 28, and Pigment White 4 showed a delayed alteration of the phagocytic capacity of cells. Moreover, all the pigments tested induced a slight but significant increase in TNF secretion. This effect, however, was transitory. Conversely, only Pigment Blue 28 induced a short and sustained increase in interleukin 6. Results showed that in response to bacterial stimuli (LPS), the secretion of tumor necrosis factor and interleukin 6 declined after recovery exposure with pigments. The pigments also induced persisting changes in some important macrophage membrane markers such as CD11b, an integrin contributing to cell adhesion and immunological tolerance. In conclusion, the pigments induced functional dis-orders in macrophages, which, in some cases, persist long after exposure, even at non-toxic doses. Discovery of highly potent pancoronavirus fusion inhibitors that also effectively inhibit COVID-19 variants from the UK (Alpha), South Africa (Beta), and India (Delta) We report here the discovery of several highly potent small molecules that showed low nM potency against SARS-CoV (IC50: as low as 13 nM), SARS-CoV-2 (IC50: as low as 23 nM), and MERS-CoV (IC50: as low as 76 nM) in pseudovirus based assays with excellent selectivity indices (SI: as high as > 5000) demonstrating their pancoronavirus inhibition. Some compounds also show 100% inhibition of CPE (IC100) at 1.25 {micro}M against an authentic SARS-CoV-2 (US_WA-1/2020). Furthermore, the most active inhibitors also potently inhibited variants of concerns (VOCs), such as the UK (B.1.1.7), South Africa (B.1.351), and Delta variant (B.1.617.2), originated in India. We confirmed that one of the potent inhibitors binds to the prefusion spike protein trimer of SARS-CoV-2 by SPR. Besides, we showed that they inhibit virus-mediated cell-cell fusion. The ADME data of one of the most active inhibitors, NBCoV1, show drug-like properties. In vivo PK of NBCoV1 in rats demonstrated excellent half-life (t1/2) of 11.3 h, mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect the lead inhibitors to pave the way for further development to preclinical and clinical candidates. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. The relative speed of the glucorticoid stress response varies independently of scope and is predicted by environmental variability and longevity across birds. The acute glucocorticoid response is a key mediator of the coordinated vertebrate response to unpredictable challenges. Rapid glucocorticoid increases initiate changes that allow animals to cope with stressors. The scope of the glucocorticoid response -- defined here as the absolute increase in glucocorticoids -- is associated with individual differences in performance and varies across species with environment and life history. In addition to varying in scope, responses can differ enormously in speed; however, relatively little is known about whether speed and absolute glucocorticoid levels covary, how selection shapes speed, or what aspects of speed are important. We used corticosterone samples collected at 5 time points from 1,750 individuals of 60 species of birds to ask i) how the speed and scope of the glucocorticoid response covary and ii) whether variation in absolute or relative speed is predicted by environmental context or life history. As predicted by a recent model, faster absolute glucocorticoid responses were strongly associated with a larger scope. Despite this covariation, the relative speed of the glucocorticoid response (standardized within species) varied independently of absolute scope, suggesting that selection could operate on both features independently. Species with faster relative glucocorticoid responses lived in locations with more variable temperature and had shorter lifespans. Our results suggest that rapid changes associated with the speed of the glucocorticoid response, such as those occurring through non-genomic receptors, might be an important determinant of coping ability and we emphasize the need for studies designed to measure speed independently of absolute glucocorticoid levels. Regulatory perturbations of ribosome allocation optimize the growth proteome with a trade-off in adaptation capacity Bacteria regulate their cellular resource allocation to enable fast growth-adaptation to a variety of environmental niches. We studied the ribosomal allocation, growth and expression profiles of two sets of fast-growing mutants of Escherichia coli K-12 MG1655 in glucose minimal medium. Mutants with only 3 of the seven copies of ribosomal RNA operons grew faster than the wild-type strain in minimal media and show similar phenotype to previously studied rpoB mutants. Higher growth rates due to increased ribosome content affected resource allocation. Expression profiles of fast-growing mutants shared downregulation of hedging functions and upregulated growth functions. Mutants showed longer diauxic shifts and reduced activity of gluconeogenic promoters during glucose-acetate shifts, suggesting reduced availability of the RNA Polymerase for expressing hedging proteome. These results show that the regulation of ribosomal allocation underlies the growth/hedging phenotypes obtained from laboratory evolution experiments. We show how two different regulatory perturbations (rRNA promoters or rpoB mutations) reshape the proteome for growth with a concomitant fitness cost

HighlightsMutants with only 3 ribosomal operons grow faster than wild-type in minimal medium

 {Delta}4 rrn and rpoB mutants share phenotypic traits

Faster growth of mutants is achieved by increased ribosome content

Fast-growing mutants display reduced hedging expression and adaptation trade-offs

Despite similar ribosomal content in rich medium the mutants present growth defects Precise exogenous insertion and sequence replacements in poplar by simultaneous HDR overexpression and NHEJ suppression using CRISPR-Cas9 CRISPR-mediated genome editing has become a powerful tool for genetic modification of biological traits. However, developing an efficient, site-specific, gene knock-in system based on homology-directed DNA repair (HDR) remains a significant challenge in plants, especially in woody species like poplar. Here, we show that simultaneous inhibition of non-homologous end joining (NHEJ) recombination cofactor XRCC4 and overexpression of HDR enhancer factors CtIP and MRE11 can improve the HDR efficiency for gene knock-in. Using this approach, the BleoR gene was integrated onto the 3' end of the MKK2 MAP Kinase gene to generate a BleoR-MKK2 fusion protein. Based on exogenous BleoR expression, the HDR-mediated knock-in efficiency was up to [~]40-fold greater when using a XRCC4 silencing incorporated with a combination of CtIP and MRE11 overexpression compared to no HDR enhancement or NHEJ silencing. Furthermore, this corporation of HDR enhancer overexpression and NHEJ repression also resulted in 7-fold fewer CRISPR-induced Insertions and Deletions (InDels), resulting in no functional effects on MKK2-based salt stress responses in poplar. Therefore, this approach may be useful not only in poplar and plants or crops but also in mammalians for improving CRISPR-mediated gene knock-in efficiency.