Deep inference of seabird dives from GPS-only records: performance and generalization properties AO_SCPLOWBSTRACTC_SCPLOWAt-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as  fine-tuning. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation. To make easier such applications, we share online the different models we trained on the considered datasets (https://github.com/AmedeeRoy/BirdDL/models).

Author SummaryOver the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as  ready-to-use tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training.
The elevational ascent and spread of exotic annual grass dominance in the Great Basin, USA AimIn the western US, sagebrush (Artemisia spp.) and salt desert shrublands are rapidly transitioning to communities dominated by exotic annual grasses, a novel and often self-reinforcing state that threatens the economic sustainability and conservation value of rangelands. Climate change is predicted to directly and indirectly favor annual grasses, potentially pushing transitions to annual grass dominance into higher elevations and north-facing aspects. We sought to quantify the expansion of annual grass-dominated vegetation communities along topographic gradients over the past several decades.

LocationOur analysis focused on rangelands among three ecoregions in the Great Basin of the western US, where several species of exotic annual grasses are widespread among shrub and perennial grass-dominated vegetation communities.

MethodsWe used recently developed remote sensing-based rangeland vegetation data to produce yearly maps of annual grass-dominated vegetation communities spanning the period 1990-2020. With these maps, we quantified the rate of spread and characterized changes in the topographic distribution (i.e., elevation and aspect) of areas transitioning to annual grass dominance.

ResultsWe documented more than an eight-fold increase in annual grass-dominated area (to >77,000 km2) occurring at an average rate of >2,300 km2 yr-1. In 2020, annual grasses dominated one fifth (19.8%) of Great Basin rangelands. This rapid expansion is associated with a broadening of the topographic niche, with widespread movement into higher elevations and north-facing aspects.

Main conclusionsAccelerated, strategic intervention is critically needed to conserve the fragile band of rangelands being compressed between annual grassland transitions at lower elevations and woodland expansion at higher elevations.
Failure to account for behavioral variability significantly compromises accuracy in indirect population monitoring Indirect wildlife population surveying largely depends upon counts of artefacts of behavior (e.g., nests or dung). Likelihood to encounter these artefacts is derived from both artefact production and decay, and variability in artefact production behavior is considered to contribute minimally to inaccuracy in wildlife estimation. Here we demonstrate how ignoring behavioral variability contributes to significant population misestimation, using an example of an endangered ape, the bonobo (Pan paniscus). Until now, a single estimate of (i.e., nest construction) has been used to extrapolate bonobo densities, assumed to be broadly representative of bonobo sign production behavior. We estimated nest construction rate across seasons and social groups at the Kokolopori Bonobo Reserve, DRC and find that nest construction rates in bonobos to be highly variable across populations as well as seasonal. Failure to account for this variability led to potentially severe degradation in accuracy of bonobo population estimates of abundance, accounting for a likely overestimation of bonobo numbers by 34%, and at worst as high as 80%. With this example, we demonstrate that failure to account for inter- and intra-population behavioral variation compromises the ability to estimate both relative and absolute wildlife abundances. We argue that variation in sign production is but one of several potential ways that behavioral variability can affect conservation monitoring, should be measured across contexts whenever possible, and must be considered in population estimation confidence intervals. With increasing attention to behavioral variability as a potential tool for conservation, conservationists must also account for the impact that behavioral variability can play upon wildlife population estimation. Our results underline the importance of observational research to wildlife monitoring schemes as a critical but overlooked component of conservation management. We extensively discuss the various avenues through which behavioral variability is likely to impact wildlife monitoring accuracy and precision and propose potential avenues for accounting for behavioral variability in wildlife monitoring. Kinetochore-mediated microtubule assembly and Augmin-dependent amplification drive k-fiber maturation in mammals Chromosome segregation in mammals relies on the maturation of a thick bundle of kinetochore-attached microtubules known as k-fibers. How k-fibers mature from initial kinetochore-microtubule attachments remains a fundamental question. By combining functional perturbations in Indian muntjac, a placental mammal with the lowest known chromosome number (n=3) and distinctively large kinetochores, with fixed- and subsecond live-cell super-resolution CH-STED nanoscopy, we uncovered the mechanism by which Augmin mediates k-fiber maturation. Augmin promoted kinetochore microtubule turnover by sustaining microtubule formation from kinetochores and poleward flux, regardless of pioneer centrosomal microtubules. Tracking of microtubule growth events within individual k-fibers revealed a wide angular dispersion, consistent with Augmin-mediated branched microtubule nucleation. Augmin depletion reduced the frequency of microtubule growth events within k-fibers and hampered normal repair after acute k-fiber injury by laser microsurgery. Our work underscores the contribution of microtubule formation from kinetochores and Augmin-mediated microtubule amplification for k-fiber maturation and spindle assembly in mammals. Expression of the ACE2 virus entry protein in the nervus terminalis reveals the potential for an alternative route to brain infection in COVID-19 Previous studies suggested that the SARS-CoV-2 virus may gain access to the brain by using a route along the olfactory nerve. However, there is a general consensus that the obligatory virus entry receptor, angiotensin converting enzyme 2 (ACE2), is not expressed in olfactory receptor neurons, and the timing of arrival of the virus in brain targets is inconsistent with a neuronal transfer along olfactory projections. We determined whether nervus terminalis neurons and their peripheral and central projections should be considered as a potential alternative route from the nose to the brain. Nervus terminalis neurons in postnatal mice were double-labeled with antibodies against ACE2 and two nervus terminalis markers, gonadotropin-releasing hormone (GnRH) and choline acetyltransferase (CHAT). We show that a small fraction of CHAT-labeled nervus terminalis neurons, and the large majority of GnRH-labeled nervus terminalis neurons with cell bodies in the region between the olfactory epithelium and the olfactory bulb express ACE2 and cathepsins B and L. Nervus terminalis neurons therefore may provide a direct route for the virus from the nasal epithelium, possibly via innervation of Bowmans glands, to brain targets, including the telencephalon and diencephalon. This possibility needs to be examined in suitable animal models and in human tissues. Venomics and antivenomics of Indian spectacled cobra (Naja naja) from the Western Ghats Venom proteome profiling of Naja naja from the Western Ghats region in Kerala was achieved through SDS-PAGE and RP-HPLC followed by Q-TOF LC-MS/MS analysis, incorporating PEAKS and Novor assisted de novo sequencing methodologies. A total of 115 proteins distributed across 17 different enzymatic and non-enzymatic venom protein families were identified through conventional and 39 peptides through homology-driven proteomics approaches. Fourteen peptides derived through de novo complements the Mascot data indicating the importance of homology-driven approaches in improving protein sequence information. Among the protein families identified, glutathione peroxidase and endonuclease were reported for the first time in the Indian cobra venom. Immunological cross-reactivity assessed using Indian polyvalent antivenoms suggested that VINS showed better EC50 (2.48 g/mL) value than that of PSAV (6.04 g/mL) and Virchow (6.03 g/mL) antivenoms. Western blotting experiments indicated that all the antivenoms elicited poor binding specificities, especially towards low molecular mass proteins. Second-generation antivenomics studies revealed that VINS antivenom was less efficient to detect many low molecular mass proteins such as three-finger toxins and Kunitz-type serine protease Inhibitors. Taken together, the present study enabled a large-scale characterization of the venom proteome of Naja naja from the Western Ghats and emphasized the need for developing more efficient antivenoms.

HighlightsO_LIProteomics of cobra venom resulted in the identification of 115 proteins representing 17 snake venom protein families.
C_LIO_LIDe novo approaches exclusively yielded 39 peptides harbouring multiple amino acid mutations.
C_LIO_LIGlutathione peroxidase and endonuclease were identified for the first time in Indian cobra venom.
C_LIO_LIIndian polyvalent antivenoms showed varying cross-reactivity towards cobra venom.
C_LIO_LIVINS antivenom was less efficient to detect many low molecular mass proteins (< 20 kDa).
C_LI INPP4B drives lysosome biogenesis to restrict leukemic stem cell differentiation and promote leukemogenesis Signaling pathways that control vital features of leukemic stem cells including multipotency, self-renewal, clonal expansion and quiescence remain unclear. Emerging studies illustrate critical roles for lysosomes in hematopoietic and leukemic stem cell fate. By investigating consequences of INPP4B alterations in AML, we have discovered its role in driving leukemic  stemness. We observed that INPP4B is highly expressed leukemic stem cell populations and Inpp4b-deficeint leukemias demonstrate increased disease latency, reduced leukemia initiating potential which is associated with a differentiated leukemic phenotype. Molecular analyses show that Inpp4b-deficient leukemias have compromised lysosomal gene expression, lysosomal content, and lysosomal activity. Our discovery of a novel pathway linking INPP4B, lysosomal biogenesis and leukemic stemness, provides a mechanism to explain the association of high INPP4B expression with poor AML prognosis, and highlights novel patient stratification strategies and LSC-specific leukemic therapies.

Key PointsOur findings highlight a novel pathway linking INPP4B, lysosomal function and leukemic stemness that explains the prognostic role of INPP4B in AML.
Our data reveal the utility of INPP4B as a biomarker of aggressive AML and provide a rationale to explore INPP4B and its associated function in lysosome biology as novel strategies to target LSC and AML Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep learning-based approach that couples remarkably precise nuclear segmentation with quantitation of fluorescent labeling intensity within segmented nuclei, and then apply it to the analysis of cell cycle dependent protein concentration in mouse tissues using 2D fluorescent still images. First, several existing deep learning-based methods were evaluated to accurately segment nuclei using different imaging modalities with a small training dataset. Next, we developed a deep learning-based approach to identify and measure fluorescent labels within segmented nuclei, and created an ImageJ plugin to allow for efficient manual correction of nuclear segmentation and label identification. Lastly, using fluorescence intensity as a readout for protein concentration, a three-step global estimation method was applied to the characterization of the cell cycle dependent expression of E2F proteins in the developing mouse intestine. 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. 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. Versatile mixotrophs employ CO2 fixation as fill-up function to dominate in modern groundwater The current understanding of organic carbon inputs into ecosystems lacking photosynthetic primary production is predicated on data and inferences derived almost entirely from metagenomic analyses. The elevated abundances of putative chemolithoautotrophs in groundwaters suggest that dark CO2 fixation is an integral component of subsurface trophic webs. To understand the impact of autotrophically-fixed carbon, the flux of CO2-derived carbon through various subpopulations of subsurface microbiota must first be resolved, both quantitatively and temporally. Here, we implement novel stable isotope cluster analysis to render a time-resolved and quantitative evaluation of 13CO-derived carbon flow through a groundwater microbiome stimulated with reduced sulfur compounds. We demonstrate that mixotrophs, not obligate chemolithoautotrophs, were the most abundant active organisms in groundwater microcosms. Species of Hydrogenophaga, Polaromonas, Dechloromonas, and other metabolically versatile mixotrophs drove the recycling of organic carbon and, when chance afforded, supplemented their carbon requirements via chemolithoautotrophy and uptake of available organic compounds. Mixotrophic activity facilitated the replacement of 43 and 80% of total microbial carbon stores with 13C in just 21 and 70 days, respectively. This opportunistic "utilize whatever pathways net the greatest advantage in fitness" strategy may explain the great abundances of mixotrophs in other oligotrophic habitats, like the upper ocean and boreal lakes. Micro topographical instruction of bacterial attachment, biofilm formation and in vivo host response Bio-instructive materials that prevent bacterial biofilm formation and drive an appropriate host immune response have the potential to significantly reduce the burden of medical device-associated infections. As bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2,176 combinatorially generated shapes using an unbiased high-throughput micro topographical polystyrene polymer chip screen. This identified topographies that reduced colonization in vitro by up to 15-fold compared with a flat surface for both motile and non-motile bacterial pathogens. Equivalent reductions were achieved on polyurethane, a polymer commonly used in medical devices. Using machine learning methods, a set of design rules based on generalisable topo-descriptors was established for predicting bacteria-resistant micro topographies. In a murine foreign body infection model, anti-attachment topographies were shown to be refractory to P. aeruginosa colonization and serendipitously, the fibrotic response to the implant was reduced, offering control of foreign body response using simple topographical patterning of non-eluting implants. Prostaglandin EP3 Receptor signaling is required to prevent insulin hypersecretion and metabolic dysfunction in a non-obese mouse model of insulin resistance When homozygous for the LeptinOb mutation (Ob), Black-and-Tan Brachyury (BTBR) mice become morbidly obese and severely insulin resistant, and by 10 weeks of age, frankly diabetic. Previous work has shown Prostaglandin EP3 Receptor (EP3) expression and activity is up-regulated in islets from BTBR-Ob mice as compared to lean controls, actively contributing to their beta-cell dysfunction. In this work, we aimed to test the impact of beta-cell-specific EP3 loss on the BTBR-Ob phenotype by crossing Ptger3 floxed mice with the Rat insulin promoter (RIP)-CreHerr driver strain. Instead, germline recombination of the floxed allele in the founder mouse - an event whose prevalence we identified as directly associated with underlying insulin resistance of the background strain - generated a full-body knockout. Full-body EP3 loss provided no diabetes protection to BTBR-Ob mice, but, unexpectedly, significantly worsened BTBR-lean insulin resistance and glucose tolerance. This in vivo phenotype was not associated with changes in beta-cell fractional area or markers of beta-cell replication ex vivo. Instead, EP3-null BTBR-lean islets had essentially uncontrolled insulin hypersecretion. The selective up-regulation of constitutively-active EP3 splice variants in islets from young, lean BTBR mice as compared to C57BL/6J, where no phenotype of EP3 loss has been observed, provides a potential explanation for the hypersecretion phenotype. In support of this, high islet EP3 expression in Balb/c females vs. Balb/c males was fully consistent with their sexually-dimorphic metabolic phenotype after loss of EP3-coupled Gz protein. Taken together, our findings provide a new dimension to the understanding of EP3 as a critical brake on insulin secretion.

New and NoteworthyIslet Prostaglandin EP3 receptor (EP3) signaling is well-known as up-regulated in the pathophysiological conditions of type 2 diabetes, contributing to beta-cell dysfunction. Unexpected findings in mouse models of non-obese insulin sensitivity and resistance provide a new dimension to our understanding of EP3 as a key modulator of insulin secretion. A previously-unknown relationship between mouse insulin resistance and the penetrance of Rat insulin promoter-driven germline floxed allele recombination is critical to consider when creating beta-cell-specific knockouts.

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org.highwire.dtl.DTLVardef@15cf1d5org.highwire.dtl.DTLVardef@108f565org.highwire.dtl.DTLVardef@126e479org.highwire.dtl.DTLVardef@61fdf8_HPS_FORMAT_FIGEXP  M_FIG C_FIG Dosage sensitivity in Pumilio1-associated diseases involves two distinct mechanisms Mutations in the RNA-binding protein (RBP) Pumilio1 (PUM1) can cause dramatically different phenotypes. Mild mutations that reduce PUM1 levels by 25% lead to a mild, adult-onset ataxia, whereas more severe mutations that reduce PUM1 levels 40-60% produce an infantile syndrome involving multiple developmental delays and seizures. Why this difference in expression should cause such different phenotypes has been unclear; known PUM1 targets are de-repressed to equal degrees in both diseases. We therefore sought to identify PUM1s protein partners in the murine brain. We identified a number of putative interactors involved in different aspects of RNA metabolism such as silencing, alternative splicing, and polyadenylation. We find that PUM1 haploinsufficiency alters the stability of several interactors and disrupts the regulation of targets of those interactors, whereas mild PUM1 loss only de-represses PUM1-specific targets. We validated these phenomena in patient-derived cell lines and show that normalizing PUM1 levels rescues the levels of interactors and their targets. We therefore propose that dosage sensitivity does not necessarily reflect a linear change in levels but can involve distinct mechanisms. Studying the interactors of RBPs in vivo will be necessary to understand their functions in neurological diseases. Volatile social environments can favour investments in quality over quantity of social relationships Cooperation does not occur in a vacuum: interactions develop over time in social groups that undergo demographic changes. Intuition suggests that stable social environments favour developing few but strong reciprocal relationships (a  focused strategy), while volatile social environments favour the opposite: more but weaker social relationships (a  diversifying strategy). We model reciprocal investments under a quality-quantity tradeoff for social relationships. We find that volatility, counterintuitively, can favour a focused strategy. This result becomes explicable through applying the theory of antagonistic pleiotropy, originally developed for senescence, to social life. Diversifying strategies show superior performance later in life, but with costs paid at young ages while the social network is slowly being built. Under volatile environments, many individuals die before reaching sufficiently old ages to reap the benefits. Social strategies that do well early in life are then favoured: a focused strategy leads individuals to form their first few social bonds quickly and to make strong use of existing bonds. Our model highlights the importance of pleiotropy and population age structure for the evolution of cooperative strategies and other social traits, and shows that it is not sufficient to reflect on the fate of survivors only, when evaluating the benefits of social strategies. Identification and characterization of the WYL BrxR protein and its gene asseparable regulatory elements of a BREX phage restriction system Bacteriophage exclusion ( BREX) phage restriction systems are found in a wide range of bacteria. Various BREX systems encode unique combinations of proteins that usually include a site-specific methyltransferase; none appear to contain a nuclease. Here we describe the identification and characterization of a Type I BREX system from Acinetobacter and the effect of deleting each BREX ORF on growth, methylation, and restriction. We identified a previously uncharacterized gene in the BREX operon that is dispensable for methylation but involved in restriction. Biochemical and crystallographic analyses of this factor, which we term BrxR ( BREX Regulator), demonstrate that it forms a homodimer and specifically binds a DNA target site upstream of its transcription start site. Deletion of the BrxR gene causes cell toxicity, reduces restriction, and significantly increases the expression of BrxC. In contrast, the introduction of a premature stop codon into the BrxR gene, or a point mutation blocking its DNA binding ability, has little effect on restriction, implying that the BrxR coding sequence and BrxR protein play independent functional roles. We speculate that the BrxR coding sequence is involved in cis regulation of anti-phage activity, while the BrxR protein plays an additional regulatory role, perhaps during horizontal transfer. 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. Bioinformatic and mechanistic analysis of the palmerolide PKS-NRPS biosynthetic pathway from the microbiome of an Antarctic ascidian Complex interactions exist between microbiomes and their hosts. Increasingly, defensive metabolites that have been attributed to host biosynthetic capability are now being recognized as products of host-associated microbes. These unique metabolites often have bioactivity targets in human disease and can be purposed as pharmaceuticals. Polyketides are a complex family of natural products that often serve as defensive metabolites for competitive or pro-survival purposes for the producing organism, while demonstrating bioactivity in human diseases as cholesterol lowering agents, anti-infectives, and anti-tumor agents. Marine invertebrates and microbes are a rich source of polyketides. Palmerolide A, a polyketide isolated from the Antarctic ascidian Synoicum adareanum, is a vacuolar-ATPase inhibitor with potent bioactivity against melanoma cell lines. The biosynthetic gene clusters (BGCs) responsible for production of secondary metabolites are encoded in the genomes of the producers as discrete genomic elements. A candidate palmerolide BGC was identified from a S. adareanum microbiome-metagenome based on a high degree of congruence with a chemical structure-based retrobiosynthetic prediction. Protein family homology analysis, conserved domain searches, active site and motif identification were used to identify and propose the function of the [~]75 kb trans-acyltransferase (AT) polyketide synthase-non-ribosomal synthase (PKS-NRPS) domains responsible for the stepwise synthesis of palmerolide A. Though PKS systems often act in a predictable co-linear sequence, this BGC includes multiple trans-acting enzymatic domains, a non-canonical condensation termination domain, a bacterial luciferase-like monooxygenase (LLM), and is found in multiple copies within the metagenome-assembled genome (MAG). Detailed inspection of the five highly similar pal BGC copies suggests the potential for biosynthesis of other members of the palmerolide chemical family. This is the first delineation of a biosynthetic gene cluster from an Antarctic microbial species, recently proposed as Candidatus Synoicohabitans palmerolidicus. These findings have relevance for fundamental knowledge of PKS combinatorial biosynthesis and could enhance drug development efforts of palmerolide A through heterologous gene expression. Single-dose AAV-based vaccine induces a high level of neutralizing antibodies against SARS-CoV-2 in rhesus macaques Coronavirus disease 2019 (COVID-19), which is triggered by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, continues to threaten global public health. Developing a vaccine that only requires single immunization but provides long-term protection for the prevention and control of COVID-19 is important. Here, we developed an adeno-associated virus (AAV)-based vaccine expressing a stable receptor-binding domain (SRBD) protein. The vaccine requires only a single shot but provides effective neutralizing antibodies (NAbs) over 598 days in rhesus macaques (Macaca mulatta). Importantly, our results showed that the NAbs were kept in high level and long lasting against authentic wild-type SARS-CoV-2, Beta, Delta and Omicron variants using plaque reduction neutralization test. Of note, although we detected pre-existing AAV2/9 antibodies before immunization, the vaccine still induced high and effective NAbs against COVID-19 in rhesus macaques. AAV-SRBD immune serum also efficiently inhibited the binding of ACE2 with RBD in the SARS-CoV-2 B.1.1.7 (Alpha), B.1.351 (Beta), P.1/P.2 (Gamma), B.1.617.2 (Delta), B.1.617.1/3(Kappa), and C.37 (Lambda) variants. Thus, these data suggest that the vaccine has great potential to prevent the spread of SARS-CoV-2. "Neighbourhood watch" model: embryonic epiblast cells assess positional information in relation to their neighbours In many developing and regenerating systems, tissue pattern is established through gradients of informative morphogens, but we know little about how cells interpret these. Using experimental manipulation of early chick embryos including misexpression of an inducer (VG1 or ACTIVIN) and an inhibitor (BMP4), we test two alternative models for their ability to explain how the site of primitive streak formation is positioned relative to the rest of the embryo. In one model, cells read morphogen concentrations cell-autonomously. In the other, cells sense changes in morphogen status relative to their neighbourhood. We find that only the latter model can account for the experimental results, including some counter-intuitive predictions. This mechanism (which we name "neighbourhood watch" model) illuminates the classic "French Flag Problem" and how positional information is interpreted by a sheet of cells in a large developing system.

Summary statementIn a large developing system, the chick embryo before gastrulation, cells interpret gradients of positional signals relative to their neighbours to position the primitive streak, establishing bilateral symmetry. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. Multiple brace root phenotypes promote anchorage and limit root lodging in maize Plant mechanical failure (lodging) causes global yield losses of 7-66% in cereal crops. We have previously shown that the above-ground nodal roots (brace roots) in maize are critical for anchorage. However, it is unknown how brace root phenotypes vary across genotypes and the functional consequence of this variation. This study quantifies the contribution of brace roots to anchorage, brace root traits, plant height, and root lodging susceptibility in 52 maize inbred lines. We show that the contribution of brace roots to anchorage and root lodging susceptibility varies among genotypes and this contribution can be explained by plant architectural variation. Additionally, supervised machine learning models were developed and show that multiple plant architectural phenotypes can predict the contribution of brace roots to anchorage and root lodging susceptibility. Together these data define the plant architectures that are important in lodging resistance and show that the contribution of brace roots to anchorage is a good proxy for root lodging susceptibility. "Adopt a Microorganism" methodology enhances the discourse richness of high school students in both hybrid learning and remote education The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Allopurinol Blocks The Formation And Progression Of Aortic Aneurysm In A Mouse Model Of Marfan Syndrome BackgroundThe pathogenesis and progression of aortic aneurysm in Marfan syndrome (MFS) involves dysregulated TGF-{beta} and nitric oxide signaling, altered hemodynamics, and biomechanical forces. Increasing evidence indicates that redox stress participates in MFS aortopathy, though its contribution is not well established. We reported elevated reactive oxygen species (ROS) formation and NADPH oxidase NOX4 upregulation in MFS patients and mice aortic samples. Here we address the contribution of xanthine oxidoreductase (XOR), which is transcribed as dehydrogenase (XDH) and then post-translationally modified to oxidase (XO), catabolizing mainly purines into uric acid and ROS.

Methods and ResultsWe report that in MFS patients, XOR protein levels increased in aortic samples. In MFS mice (Fbn1C1041G/+), XOR mRNA transcripts augmented in the aorta of young but not older MFS mice. Moreover, the enzymatic activity of XO form increased with respect to XDH. The administration of the XOR inhibitor allopurinol (ALO) blocked the progression of aortic root aneurysm in MFS mice. ALO was also protective when administrated before the appearance of aneurysm. MFS-induced elastic fiber fragmentation, fibrotic remodeling, nuclear translocation of pNRF2, and increased 3-nitrotyrosine levels in the aortic tunica media as well as endothelial dysfunction were all prevented by allopurinol. The large overproduction of H2O2 in MFS aorta did not occur in allopurinol-treated mice whose uric acid plasma levels remained unaltered.

ConclusionsThis study strengthens the concept that redox stress is an important determinant of aortic aneurysm formation and progression in MFS and supports a clinical trial for ALO in the pharmacological treatment of MFS aortopathy.

GRAPHICAL ABSTRACT

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org.highwire.dtl.DTLVardef@eab02aorg.highwire.dtl.DTLVardef@1d3b39eorg.highwire.dtl.DTLVardef@1b54d0forg.highwire.dtl.DTLVardef@1d61ad0_HPS_FORMAT_FIGEXP  M_FIG C_FIG Magnetic wire active microrheology of human respiratory mucus Mucus is a viscoelastic gel secreted by the pulmonary epithelium in the tracheobronchial region of the lungs. The coordinated beating of cilia in contact with the gel layer moves mucus upwards towards pharynx, removing inhaled pathogens and particles from the airways. The efficacy of this clearance mechanism depends primarily on the rheological properties of mucus. Here we use a magnetic wire based microrheology technique to study the viscoelastic properties of human mucus collected from human bronchus tubes. The response of wires between 5 and 80 {micro}m in length to a magnetic rotating field is monitored by optical time-lapse microscopy and analyzed using constitutive equation models of rheology, including Maxwell and Kelvin-Voigt. The static shear viscosity and elastic modulus can be inferred from low frequency (10-3 - 10 rad s-1) measurements, leading to the evaluation of the mucin network relaxation time. This relaxation time is found to be widely distributed, from one to several hundred seconds. Mucus is identified as a viscoelastic liquid with an elastic modulus of 2.5 {+/-} 0.5 Pa and a static viscosity of 100 {+/-} 40 Pa s. Our work shows that beyond the established spatial variations in rheological properties due to microcavities, mucus exhibits secondary inhomogeneities associated with the relaxation time of the mucin network that may be important for its flow properties. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors.