Novel Feline Papillomavirus Isolate P20 Assembled from Metagenomic Data Isolated from the Human Skin of a House Cat Owner A feline papillomavirus was assembled from metagenomic sequencing data collected from the human skin of a house cat owner. This circular papillomavirus strain P20 is 8069 bp in length, has a GC content of 54.38%, and displays genome organization typical of feline papillomaviruses with six annotated protein coding regions. The genome exhibits approximately 75% sequence similarity to other feline papillomavirus genomes.
Host factors drive the within-host competition between highly and low pathogenic H5N8 avian influenza viruses Highly pathogenic avian influenza viruses (HPAIV) emerge from low pathogenic avian influenza viruses (LPAIV) through the introduction of basic amino acids at the hemagglutinin (HA) cleavage site. Following viral evolution, the newly formed HPAIV likely represents a minority variant within the index host, predominantly infected with the LPAIV precursor. Using reverse-genetics engineered H5N8 viruses differing solely at the HA cleavage, we tested the hypothesis that the interaction between the minority HPAIV and the majority LPAIV could modulate the risk of HPAIV emergence and that the nature of the interaction could depend on the host species. In chickens, we observed that the H5N8LP increased H5N8HP replication and pathogenesis. By contrast, the H5N8LP antagonized H5N8HP replication and pathogenesis in ducks. Ducks mounted a more potent antiviral innate immune response than chickens against the H5N8LP, which correlated with H5N8HP inhibition. These data provide experimental evidence that HPAIV may be more likely to emerge in chickens than in ducks and underscore the importance of within-host viral variants interactions in viral evolution.
Live imaging YAP signaling in mouse embryo development YAP protein is a critical regulator of mammalian embryonic development. By generating a near-infrared fusion YAP reporter mouse line, we have achieved high-resolution live imaging of YAP localization during mouse embryonic development. We have validated the reporter by demonstrating its predicted responses to blocking LATs kinase activity or blocking cell polarity. By time lapse imaging preimplantation embryos, we revealed a mitotic reset behavior of YAP nuclear localization. We also demonstrated deep tissue live imaging in post-implantation embryos and revealed an intriguing nuclear YAP pattern in migrating cells. The YAP fusion reporter mice and imaging methods will open new opportunities for understanding dynamic YAP signaling in vivo in many different situations. Structure-Functional-Selectivity Relationship Studies on A-86929 Analogs and Small biaryl Fragments toward Discovery of biased D1 agonists Dopamine regulates normal functions such as movement, reinforcement learning, and cognition, and its dysfunction has been implicated in multiple psychiatric and neurological disorders. Dopamine acts through the D1- (D1R and D5R) and D2-class (D2R, D3R and D4R) of seven transmembrane receptors, and activates both G-protein- and {beta}-arrestin-dependent signaling pathways, to mediate its physiological effects. Current dopamine receptor-based therapies are used to ameliorate motor deficits in Parkinsons disease, or as antipsychotic medications for schizophrenia. These drugs show efficacy for ameliorating only some symptoms caused by dopamine dysfunction and are plagued by debilitating side-effects. Studies in primates and rodents have shown that shifting the balance of dopamine receptor signaling towards the arrestin pathway can be beneficial for inducing normal movement, while reducing motor side-effects such as dyskinesias, and can be efficacious at enhancing cognitive function compared to balanced agonists. Several structure-activity-relationship (SAR) studies have embarked on discovering {beta}-arrestin-biased dopamine agonists, focused on D2 partial agonists, non-catechol D1 agonists, and mixed D1/D2R dopamine receptor agonists. Here, we describe an SAR study to identify novel D1R {beta}-arrestin biased ligands using A-86929, a high-affinity D1R catechol agonist, as a core scaffold. Previously described and novel analogs of A-86929 were synthesized and screened in vitro for structure-functional-selectivity relationships (SFSR) studies to identify chemical motifs responsible for {beta}-arrestin biased activity at both D1 and D2Rs. Most of the A-86929 analogs screened were G protein biased but none of them were exclusively arrestin-biased. Additionally, various catechol aryl fragments were designed and synthesized. Other compounds surveyed included hydroxyl and chloro analogs of dopamine to test for hydrogen bonding and ionic interactions. Some of these small molecular probes displayed weak bias towards the {beta}-arrestin pathway. Continued in-depth SFSR studies informed by structure determination, molecular modeling, and mutagenesis studies will facilitate discovery of potent and efficacious arrestin-biased dopamine receptor ligands. Hybridization alters the shape of the genotypic fitness landscape, increasing access to novel fitness peaks during adaptive radiation Estimating the complex relationship between fitness and genotype or phenotype (i.e. the adaptive landscape) is one of the central goals of evolutionary biology. However, adaptive walks connecting genotypes to organismal fitness, speciation, and novel ecological niches are still poorly understood and processes for surmounting fitness valleys remain controversial. One outstanding system for addressing these connections is a recent adaptive radiation of ecologically and morphologically novel pupfishes (a generalist, molluscivore, and scale-eater) endemic to San Salvador Island, Bahamas. We leveraged whole-genome sequencing of 139 hybrids from two independent field fitness experiments to identify the genomic basis of fitness, estimate genotypic fitness networks, and measure the accessibility of adaptive walks on the fitness landscape. We identified 132 SNPs that were significantly associated with fitness in field enclosures. Six out of the 13 regions most strongly associated with fitness contained differentially expressed genes and fixed SNPs between trophic specialists; one gene (mettl21e) was also misexpressed in lab-reared hybrids, suggesting a potential intrinsic genetic incompatibility. We then constructed genotypic fitness networks from adaptive alleles and show that scale-eating specialists are the most isolated of the three species on these networks. Intriguingly, introgressed and de novo variants reduced fitness landscape ruggedness as compared to standing variation, increasing the accessibility of genotypic fitness paths from generalist to specialists. Our results suggest that adaptive introgression and de novo mutations alter the shape of the fitness landscape, providing key connections in adaptive walks circumventing fitness valleys and triggering the evolution of novelty during adaptive radiation. Preprints in motion: tracking changes between preprint posting and journal publication during a pandemic Amidst the COVID-19 pandemic, preprints in the biomedical sciences are being posted and accessed at unprecedented rates, drawing widespread attention from the general public, press and policymakers for the first time. This phenomenon has sharpened longstanding questions about the reliability of information shared prior to journal peer review. Does the information shared in preprints typically withstand the scrutiny of peer review, or are conclusions likely to change in the version of record? We assessed preprints from bioRxiv and medRxiv that had been posted and subsequently published in a journal through 30th April 2020, representing the initial phase of the pandemic response. We utilised a combination of automatic and manual annotations to quantify how an article changed between the preprinted and published version. We found that the total number of figure panels and tables changed little between preprint and published articles. Moreover, the conclusions of 7.2% of non-COVID-19-related and 17.2% of COVID-19-related abstracts undergo a discrete change by the time of publication, but the majority of these changes do not qualitatively change the conclusions of the paper. An environmentally responsive transcriptional state modulates cell identities during root development Roots are fundamental organs for plant development and response to their environment: they anchor the plant to its growth substrate, uptake nutrients and water vital to plant growth, and can sense and respond to a variety of biotic and abiotic stresses. The architecture of root systems and their growth are known to be strongly affected by the environmental conditions found in the soil. However, the acquisition of cell identities at the root meristem is still mainly viewed as ontogenetically driven, where a small number of stem cells generate all the cell types through stereotyped divisions followed by differentiation, along a simple developmental trajectory. The extent to which environmental cues precisely shape and affect these developmental trajectories remains an open question. We used single-cell RNA-seq, combined with spatial mapping, to deeply explore the trajectories of cell states at the tip of Arabidopsis roots, known to contain multiple developing lineages. Surprisingly, we found that most lineage trajectories exhibit a stereotyped bifid topology with two developmental trajectories rather than one. The formation of one of the trajectories is driven by a strong and specific activation of genes involved in the responses to various environmental stimuli, that affects only of a subset of the cells in multiple cell types simultaneously, revealing another layer of patterning of cell identities in the root that is independent of cell ontogeny. We demonstrate the robustness of this environmentally responsive transcriptional state by showing that it is present in a mutant where cell type identities are greatly perturbed, as well as in different Arabidopsis ecotypes. We also show that the root can adapt the proportion of cells that acquire this particular state in response to environmental signals such as nutrient availability. The discovery of this cell state reveals new layers of cell identity that may underpin the adaptive potential of plant development. Temporally robust occupancy frequency distributions in riverine ecosystems explained by local biodiversity regulation The distribution of species site occupancy--the occupancy frequency distribution (OFD)--is a fundamental pattern in spatial ecology. Despite decades of research, the mechanisms responsible for the shape of the distribution remain incompletely understood. Here, we simultaneously examine both spatial and temporal patterns of site occupancy in communities of macroinverterbrates, macrophytes and diatoms. We find that the shape of the OFD at the catchment scale is typically time invariant despite substantial turnover in composition and species proportional occupancy over the 30 year time series. This can been seen as evidence in favour of an ecological mechanism for the shape of the OFD driven by local regulation of species richness and other biodiversity properties. We show that a simple, locally saturated patch occupancy model explains both the shape of the OFD and the temporal turnover rate in English rivers. This model is mathematically analogous to Hubbells neutral theory however concerns patches occupied by a given species rather its population size. Our analysis supports the view that metacommunities exist in a dynamic steady state arising from local ecological constraints and that this intrinsic regulation can drives the emergence of a wide variety of macroecological patterns. We also show that interspecific differences are unlikely to play a dominant role in driving large scale ecosystem structure. Circulating immune complexes drive immunopathology in COVID-19 A dysregulated immune response with high levels of SARS-CoV-2 specific IgG antibodies characterizes patients with severe or critical COVID-19. Although a robust IgG response is traditionally considered to be protective, excessive triggering of activating Fc-gamma-receptors (Fc{gamma}Rs) could be detrimental and cause immunopathology. Here, we document that patients who develop soluble circulating IgG immune complexes (sICs) during infection are subject to enhanced immunopathology driven by Fc{gamma}R activation. Utilizing cell-based reporter systems we provide evidence that sICs are predominantly formed prior to a specific humoral response against SARS-CoV-2. sIC formation, together with increased afucosylation of SARS-CoV-2 specific IgG eventually leads to an enhanced CD16 (Fc{gamma}RIII) activation of immune cells reaching activation levels comparable active systemic lupus erythematosus (SLE) disease. Our data suggest a vicious cycle of escalating immunopathology driven by an early formation of sICs in predisposed patients. These findings reconcile the seemingly paradoxical findings of high antiviral IgG responses and systemic immune dysregulation in severe COVID-19.

Clinical implicationsThe identification of sICs as drivers of an escalating immunopathology in predisposed patients opens new avenues regarding intervention strategies to alleviate critical COVID-19 progression.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/449893v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@b4616corg.highwire.dtl.DTLVardef@682d1aorg.highwire.dtl.DTLVardef@16946cborg.highwire.dtl.DTLVardef@a6ef7d_HPS_FORMAT_FIGEXP  M_FIG C_FIG A vicious cycle of immunopathology in COVID-19 patients is driven by soluble multimeric immune complexes (sICs). SARS-CoV-2 infection triggers sIC formation in prone individuals. Activation of Fc{gamma}RIII/CD16 expressing immune cells by sICs precedes a humoral response to SARS-CoV2 infection. sICs and infection add to IgG afucosylation, further enhancing Fc{gamma}RIII/CD16 activation by opsonized targets. High inflammation induces further sIC mediated immune cell activation ultimately leading to an escalating immunopathology. Flexibility of Short-chain dehydrogenase is interconnected to its promiscuity for the reduction of multiple ketone intermediates Short-chain dehydrogenases/reductases (SDRs) are a convenient class of enzymes used to synthesize enantiopure alcohols. Several studies describe native or engineered SDRs for converting substrates of interest using cost and time-intensive high-throughput approaches. The classification of SDRs is based on chain length and cofactor binding site. Of these, the shorter  Classical and the longer  Extended enzymes participate in ketoreduction. However, comparative analysis of various modelled SDRs reveals a length independent conserved N-terminal Rossmann fold and a variable C-terminus region for both types. The general hypothesis is that the latter domain influences the enzymes flexibility that may affect the observed promiscuity of the enzyme. We have used a machine learning algorithm on this flexible domain to build a rationale to screen promiscuous candidates. We have built a data set consisting of physicochemical properties derived from the amino-acid composition of enzymes to select closely associated promiscuous mesophilic enzymes. The resulting in vitro studies on pro-pharmaceutical substrates illustrate a direct correlation between the C-terminal lid-loop structure, enzyme melting temperature and the turnover number. We present a walkthrough for exploring promiscuous SDRs for catalyzing enantiopure alcohols of industrial importance. Intron-mediated induction of phenotypic heterogeneity Introns are universally present in the nuclear genomes of eukaryotes1. The budding yeast, an otherwise intron-poor species, preserves two sets of ribosomal protein (RP) genes differing primarily in their introns2-4. Despite recent findings on the role of RP introns under stress and starvation5-7, understanding the contribution of introns to ribosome regulation remains challenging. Here, combining isogrowth profiling8 with single-cell protein measurements9, we found that introns can mediate inducible phenotypic heterogeneity conferring a clear fitness advantage. Osmotic stress leads to bimodal expression of the small ribosomal subunit protein Rps22B, mediated by an intron in the 5 untranslated region of its transcript. The two resulting yeast subpopulations differ in their ability to cope with starvation. Low Rps22B protein levels resulted in prolonged survival under sustained starvation, while high Rps22B levels enabled cells to grow faster after transient starvation. Further, yeast growing at high sugar concentrations - similar to those in ripe grapes - exhibit bimodal Rps22B expression when approaching stationary phase. Differential intron-mediated regulation of RP genes thus provides a way to diversify the population when starvation looms in natural environments. Our findings reveal a new role for introns in inducing phenotypic heterogeneity in changing environments and suggest that duplicated RP genes in yeast contribute to resolving the evolutionary conflict between precise expression control and environmental responsiveness10. 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. Identification of the three zinc-binding sites on Tau protein Tau protein has been extensively studied due to its key roles in microtubular cytoskeleton regulation and in the formation of aggregates found in some neurodegenerative diseases. Recently it has been shown that zinc is able to induce tau aggregation by interacting with several binding sites. However, the precise location of these sites and the molecular mechanism of zinc-induced aggregation remain unknown. Here we used Nuclear Magnetic Resonance (NMR) to identify zinc binding sites on hTau40 isoform. These experiments revealed three distinct zinc binding sites on tau, located in the N-terminal part (H14, H32, H94, and H121), the repeat region (H299, C322, H329 and H330) and the C-terminal part (H362, H374, H388 and H407). Further analysis enabled us to show that the C-terminal and the N-terminal sites are independent of each other. Using molecular simulations, we modeled the structure of each site in a complex with zinc. Given the clinical importance of zinc in tau aggregation, our findings pave the way for designing potential therapies for tauopathies.

HighlightsO_LIZinc is known to induce tau aggregation in neurodegenerative diseases
C_LIO_LIZinc binding locations and mechanism are not yet clear
C_LIO_LIUsing NMR we localized 3 zinc binding site on tau
C_LIO_LIBy molecular simulations, we proposed a modeled structure of each site
C_LIO_LIOur findings pave the way for designing potential therapies for tauopathies
C_LI Engineered bacteria detect tumor DNA Advances in bacterial engineering have catalysed the development of living cell diagnostics and therapeutics1-3, including microbes that respond to diseases such as gut inflammation4, intestinal bleeding5, pathogens6 and hypoxic tumors7. Bacteria can easily access the entire gastrointestinal tract via oral administration8, and they can produce outputs that can be noninvasively measured in stool4 or urine7. Cellular memory, such as bistable switches4,9,10 or genomic rearrangement11, has been used to allow bacteria to store information over time. However, living biosensors have not yet been engineered to detect specific DNA sequences or mutations from outside the cell. Here, we engineer naturally competent Acinetobacter baylyi to detect donor DNA from the genomes of colorectal cancer (CRC) cells and organoids. We characterize the functionality of the biosensors in vitro with co-culture assays and then validate in vivo with sensor bacteria delivered orally or rectally into mice injected with orthotopic donor CRC organoids. We observe horizontal gene transfer from the tumor to the sensor bacteria in vivo, allowing their detection in stool. The sensor bacteria achieved 100% discrimination between mice with and without CRC using both delivery methods. Our findings establish a framework for biosensing applications that require the detection of mutations or organisms within environments that are difficult to sample. In addition, the platform can be readily expanded to include in situ production and delivery of therapeutic payloads at the detection site. Rational Exploration of Fold Atlas for Human Solute Carrier Proteins Solute carrier (SLC) superfamily is the largest group responsible for transmembrane transport of substances in human cells. It includes more than 400 members which are organized into 65 families according to their physiological function and sequence similarity. Different families of solute transporters can adopt the same or different folds that determine the working mechanism and reflect the evolutionary relationship between SLC members. Analysis of structural data in literatures shows that there are 13 different folds in the solute carrier superfamily covering 40 families and 343 members. To further study their working mechanism, we systematically explored the SLC superfamily to look for more folds. Based on our results, at least three new folds were found for SLC superfamily, and one was experimentally verified in the SLC44 family. Our work has laid a foundation and provided important insights for the systematic and comprehensive study on the structure and function of solute carriers. Simultaneous Brain, Brainstem and Spinal Cord pharmacological-fMRI reveals endogenous opioid network interactions mediating attentional analgesia Pain perception is decreased by shifting attentional focus away from a threatening event. This attentional analgesia engages parallel descending control pathways from anterior cingulate (ACC) to locus coeruleus, and ACC to periaqueductal grey (PAG) - rostral ventromedial medulla (RVM), indicating possible roles for noradrenergic or opioidergic neuromodulators. To determine which pathway modulates nociceptive activity in humans we used simultaneous whole brain-spinal cord pharmacological-fMRI (N=39) across three sessions. Noxious thermal forearm stimulation generated somatotopic-activation of dorsal horn (DH, C6 segment) whose activity mirrored attentional pain modulation. Activity in an adjacent cluster reported the interaction between task and noxious stimulus. Effective connectivity analysis revealed that ACC recruits PAG and RVM to modulate spinal cord activity. Blocking endogenous opioids with Naltrexone impairs attentional analgesia and disrupts RVM-DH and ACC-PAG connectivity. Noradrenergic augmentation with Reboxetine did not alter attentional analgesia. Cognitive pain modulation is mediated by opioidergic ACC-PAG-RVM descending control which supresses spinal nociceptive activity. Clonal evolution in serially passaged Cryptococcus neoformans x deneoformans hybrids reveals a heterogenous landscape of genomic change Cryptococcus neoformans x deneoformans hybrids (also known as serotype AD hybrids) are basidiomycete yeasts that are common in a clinical setting. Like many hybrids, the AD hybrids are largely locked at the F1 stage and are mostly unable to undergo normal meiotic reproduction. However, these F1 hybrids, which display a high ([~]10%) sequence divergence are known to genetically diversify through mitotic recombination and aneuploidy, and this diversification may be adaptive. In this study, we evolved a single AD hybrid genotype in six diverse environments by serial passaging and then used genome resequencing of evolved clones to determine evolutionary mechanisms of adaptation. The evolved clones generally increased fitness after passaging, accompanied by an average of 3.3 point mutations, 2.9 loss of heterozygosity (LOH) events, and 0.7 trisomic chromosomes per clone. LOH occurred through nondisjunction of chromosomes, crossing over consistent with break-induced replication, and gene conversion, in that order of prevalence. The breakpoints of these recombination events were significantly associated with regions of the genome with lower sequence divergence between the parents and clustered in subtelomeric regions, notably in regions that had undergone introgression between the two parental species. Parallel evolution was observed, particularly through repeated homozygosity via nondisjunction, yet there was little evidence of environment-specific parallel change for either LOH, aneuploidy, or mutations. These data show that AD hybrids have both a remarkable genomic plasticity and yet are challenged in the ability to recombine through sequence divergence and chromosomal rearrangements, a scenario likely limiting the precision of adaptive evolution to novel environments. Platelet transcriptome yields progressive markers in chronic myeloproliferative neoplasms and identifies putative targets of therapy Predicting disease progression remains a particularly challenging endeavor in chronic degenerative disorders and cancer, thus limiting early detection, risk stratification, and preventive interventions. Here, profiling the spectrum of chronic myeloproliferative neoplasms (MPNs) as a model, we identify the blood platelet transcriptome as a proxy for highly sensitive progression biomarkers that also enables prediction of advanced disease via machine learning algorithms. Using RNA sequencing (RNA-seq), we derive disease-relevant gene expression in purified platelets from 120 peripheral blood samples constituting two time-separated cohorts of patients diagnosed with one of three MPN subtypes at sample acquisition - essential thrombocythemia, ET (n=24), polycythemia vera, PV (n=33), and primary or post ET/PV secondary myelofibrosis, MF (n=42), and healthy donors (n=21). The MPN platelet transcriptome reveals an incremental molecular reprogramming that is independent of patient driver mutation status or therapy and discriminates each clinical phenotype. Leveraging this dataset that shows a characteristic progressive expression gradient across MPN, we develop a machine learning model (Lasso-penalized regression) and predict advanced subtype MF at high accuracy and under two conditions of external validation: i) temporal: our two Stanford cohorts, AUC-ROC of 0.96; and ii) geographical: independently published data of an additional n=25 MF and n=46 healthy donors, AUC-ROC of 0.97). Lasso-derived signatures offer a robust core set of < 5 MPN transcriptome markers that are progressive in expression. Mechanistic insights from our data highlight impaired protein homeostasis as a prominent driver of MPN evolution, with persistent integrated stress response. We also identify JAK inhibitor-specific signatures and other interferon, proliferation, and proteostasis-associated markers as putative targets for MPN-directed therapy. Our platelet transcriptome snapshot of chronic MPNs demonstrates a proof of principle for disease risk stratification and progression beyond genetic data alone, with potential utility in other progressive disorders.

HighlightsLeveraging two independent and mutually validating MPN patient cohorts, we identify progressive transcriptomic markers that also enable externally validated prediction in MPNs.

Our platelet RNA-Seq data identifies impaired protein homeostasis as prominent in MPN progression and offers putative targets of therapy.

VISUAL ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=135 HEIGHT=200 SRC="FIGDIR/small/435190v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@72dc16org.highwire.dtl.DTLVardef@cf5096org.highwire.dtl.DTLVardef@b3d460org.highwire.dtl.DTLVardef@3c0ddc_HPS_FORMAT_FIGEXP  M_FIG C_FIG RadGenNets: Deep Learning-Based Radiogenomics Model For Gene Mutation Prediction In Lung Cancer AO_SCPLOWBSTRACTC_SCPLOWIn this paper, we present our methodology that can be used for predicting gene mutation in patients with non-small cell lung cancer (NSCLC). There are three major types of gene mutations that a NSCLC patients gene structure can change to: epidermal growth factor receptor (EGFR), Kirsten rat sarcoma virus (KRAS), and Anaplastic lymphoma kinase (ALK). We worked with the clinical and genomics data for each patient as well CT scans. We preprocessed all of the data and then built a novel pipeline to integrate both the image and tabular data. We built a novel pipeline that used a fusion of Convolutional Neural Networks and Dense Neural Networks. Also, using a search approach, we pick an ensemble of deep learning models to classify the separate gene mutations. These models include EfficientNets, SENet, and ResNeXt WSL, among others. Our model achieved a high area under curve (AUC) score of 94% in detecting gene mutation. Microbial colonization of tannin-rich tropical plants: interplay between degradability, methane production and tannin disappearance in the rumen AO_SCPLOWBSTRACTC_SCPLOWCondensed tannins in plants are found free and attached to protein and fibre but it is not known whether these fractions influence rumen degradation and microbial colonization. This study explored the rumen degradation of tropical tannins-rich plants and the relationship between condensed tannins fractions disappearance and microbial communities colonising plant particles. Leaves from Calliandra calothyrsus, Gliricidia sepium, and Leucaena leucocephala, pods from Acacia nilotica and the leaves of two agricultural by-products: Manihot esculenta and Musa spp. were incubated in situ in the rumen of dairy cows. An in vitro approach was also used to assess the effects of these plants on rumen fermentation parameters. All plants contained more than 100 g/kg of condensed tannins with a large proportion (32 to 61%) bound to proteins. Calliandra calothyrsus had the highest concentration of condensed tannins at 361 g/kg, whereas Acacia nilotica was particularly rich in hydrolysable tannins (350 g/kg). Hydrolysable and free condensed tannins from all plants completely disappeared after 24 h incubation in the rumen. Disappearance of protein-bound condensed tannins was variable with values ranging from 93% for Gliricidia sepium to 21% for Acacia nilotica. In contrast, fibre-bound condensed tannins disappearance averaged ~82% and did not vary between plants. Disappearance of bound fractions of condensed tannins was not associated with degradability of plant fractions. The presence of tannins interfered with the microbial colonisation of plants. Each plant had distinct bacterial and archaeal communities after 3 and 12 h of incubation in the rumen and distinct protozoal communities at 3 h. Adherent communities in tannin-rich plants had a lower relative abundance of fibrolytic microbes, notably Fibrobacter spp. Whereas, archaea diversity was reduced in high tannin-containing Calliandra calothyrsus and Acacia nilotica at 12 h of incubation. Concurrently, in vitro methane production was lower for Calliandra calothyrsus, Acacia nilotica and Leucaena leucocephala although for the latter total volatile fatty acids production was not affected and was similar to control. Here we show that the total amount of hydrolysable and condensed tannins contained in a plant govern the interaction with rumen microbes affecting degradability and fermentation. The effect of protein- and fibre-bound condensed tannins on degradability is less important. Sensing their plasma membrane curvature allows migrating cells to circumvent obstacles Cell migration is a hallmark out-of-equilibrium process in biology. In addition to persistent self-propelled motion, many cells display remarkable adaptive behaviors when they navigate complex environments within the body. Combining theory and experiments, we identify a curvature-sensing mechanism underlying obstacle avoidance in immune-like cells. The genetic perturbation of this machinery leads to a reduced capacity to evade obstructions combined with faster and more persistent cell migration in obstacle-free environments. We propose that the active polymerization of the actin cytoskeleton at the advancing edge of migrating cells is locally inhibited by the curvature-sensitive BAR protein Snx33 in regions with inward plasma membrane curvature. This coupling between actin and membrane dynamics leads to a mechanochemical instability that generates complex protrusive patterns at the cellular front. Adaptive motility thus arises from two simultaneous curvature-dependent effects, i) the specific reduction of propulsion in regions where external objects deform the plasma membrane and ii) the intrinsic patterning capacity due to the membrane-actin coupling that promotes spontaneous changes in the cells protrusions. Our results show how cells utilize actin- and plasma membrane biophysics to sense their environment, allowing them to adaptively decide if they should move ahead or turn away. On the basis of our findings, we propose that the natural diversity of BAR proteins may allow cells to tune their curvature sensing machinery to match the shape characteristics in their environment. Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments and Multiscale Models Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale, spatiotemporal models of cancer growth using state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns. Its implementation enabled us to pursue two goals; first, the quantitative description of the morphology of cancer progression in 3D cultures, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration. We applied this framework to the study of the spatiotemporal progression of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and accumulation, as well as random motion during the examined time period of development. To our knowledge, this is the first time that a multiscale model is used to quantify the relationship between the spatial patterns and the underlying mechanisms of cancer growth in 3D environments. Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning A hallmark of human intelligence, but challenging for reinforcement learning (RL) agents, is the ability to compositionally generalise, that is, to recompose familiar knowledge components in novel ways to solve new problems. For instance, when navigating in a city, one needs to know the location of the destination and how to operate a vehicle to get there, whether it be pedalling a bike or operating a car. In RL, these correspond to the reward function and transition function, respectively. To compositionally generalize, these two components need to be transferable independently of each other: multiple modes of transport can reach the same goal, and any given mode can be used to reach multiple destinations. Yet there are also instances where it can be helpful to learn and transfer entire structures, jointly representing goals and transitions, particularly whenever these recur in natural tasks (e.g., given a suggestion to get ice cream, one might prefer to bike, even in new towns). Prior theoretical work has explored how, in model-based RL, agents can learn and generalize task components (transition and reward functions). But a satisfactory account for how a single agent can simultaneously satisfy the two competing demands is still lacking. Here, we propose a hierarchical RL agent that learns and transfers individual task components as well as entire structures (particular compositions of components) by inferring both through a non-parametric Bayesian model of the task. It maintains a factorised representation of task components through a hierarchical Dirichlet process, but it also represents different possible covariances between these components through a standard Dirichlet process. We validate our approach on a variety of navigation tasks covering a wide range of statistical correlations between task components and show that it can also improve generalisation and transfer in more complex, hierarchical tasks with goal/subgoal structures. Finally, we end with a discussion of our work including how this clustering algorithm could conceivably be implemented by cortico-striatal gating circuits in the brain. Large Scale Discovery of Microbial Fibrillar Adhesins and Identification of Novel Members of Adhesive Domain Families Fibrillar adhesins are bacterial cell surface proteins that mediate interactions with the environment including host cells during colonisation or other bacteria during biofilm formation. These proteins are characterised by a stalk that projects the adhesive domain closer to the binding target. Fibrillar adhesins evolve quickly and thus can be difficult to computationally identify, yet they represent an important component for understanding bacterial host interactions.

To detect novel fibrillar adhesins we developed a random forest prediction approach based on common characteristics we identified for this protein class. We applied this approach to Firmicute and Actinobacterial proteomes, yielding over 6,500 confidently predicted fibrillar adhesins. To verify the approach we investigated predicted fibrillar adhesins that lacked a known adhesive domain. Based on these proteins, we identified 24 sequence clusters representing potential novel members of adhesive domain families. We used AlphaFold to verify that 15 clusters showed structural similarity to known adhesive domains such as the TED domain.

Overall our study has made a significant contribution to the number of known fibrillar adhesins and has enabled us to identify novel members of adhesive domain families involved in the bacterial pathogenesis.

ImportanceFibrillar adhesins are a class of bacterial cell surface proteins that enable bacteria to interact with their environment. We developed a Machine Learning approach to identify fibrillar adhesins and applied this classification approach on the Firmicutes and Actinobacteria Reference Proteomes. This method allowed us to detect a high number of novel fibrillar adhesins, and also novel members of adhesive domain families. To confirm our predictions of these potential adhesin protein domains, we predicted their structure using the AlphaFold tool. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. Discovery and functional assessment of a novel adipocyte population driven by intracellular Wnt/β-catenin signaling in mammals Wnt/{beta}-catenin signaling has been well established as a potent inhibitor of adipogenesis. Here, we identified a population of adipocytes that exhibit persistent activity of Wnt/{beta}-catenin signaling, as revealed by the Tcf/Lef-Gfp reporter allele, in embryonic and adult mouse fat depots, named as Wnt+ adipocytes. We showed that the {beta}-catenin-mediated signaling activation in these cells is Wnt ligand- and receptor-independent but relies on AKT/mTOR pathway and is essential for cell survival. Such adipocytes are distinct from classical ones in transcriptomic and genomic signatures and can be induced from various sources of mesenchymal stromal cells including human cells. Genetic lineage-tracing and targeted cell ablation studies revealed that these adipocytes convert into beige adipocytes directly and are also required for beige fat recruitment under thermal challenge, demonstrating both cell autonomous and non-cell autonomous roles in adaptive thermogenesis. Furthermore, mice bearing targeted ablation of these adipocytes exhibited glucose intolerance, while mice receiving exogenously supplied such cells manifested enhanced glucose utilization. Our studies uncover a unique adipocyte population in regulating beiging in adipose tissues and systemic glucose homeostasis.