A tRNA processing enzyme is a central regulator of the mitochondrial unfolded protein response The mitochondrial unfolded protein response (UPRmt) has emerged as a predominant mechanism that preserves mitochondrial function. Consequently, multiple pathways likely exist to modulate UPRmt. We unexpectedly discovered that the tRNA processing enzyme, homolog of ELAC2 (HOE-1), is central to UPRmt regulation in Caenorhabditis elegans. We find that nuclear HOE-1 is necessary and sufficient to robustly activate UPRmt. We show that HOE-1 acts via transcription factors ATFS-1 and DVE-1 that are crucial for UPRmt. Mechanistically, we show that HOE-1 likely mediates its effects via tRNAs, as blocking tRNA export prevents HOE-1-induced UPRmt. Interestingly, we find that HOE-1 does not act via the integrated stress response, which can be activated by uncharged tRNAs, pointing towards its reliance on a new mechanism. Finally, we show that the subcellular localization of HOE-1 is responsive to mitochondrial stress and is subject to negative regulation via ATFS-1. Together, we have discovered a novel RNA-based cellular pathway that modulates UPRmt.
Implicit Laplacian of Enhanced Edge: An Unguided Algorithm for Accurate and Automated Quantitative Analysis of Cytoskeletal Images The eukaryotic cytoskeleton plays essential roles in cell signaling and trafficking, which is broadly associated with immunity and diseases of human and plants. To date, most analyses aiming at defining the temporal and spatial dynamics of the cytoskeleton have relied on qualitative and quantitative analysis of fluorescence images to describe cytoskeletal function. While state-of-the-art, these approaches have limitations: the diverse shape and brightness of the cytoskeleton cause considerable inaccuracy in both human-driven and automated approaches, and the widely adopted image projection process (3D to 2D) leads to bias and information loss. Here, we describe the development and application of Implicit Laplacian of Enhanced Edge (ILEE), an unguided approach that uses a 2D/3D-compatible local thresholding algorithm for the quantitative evaluation of cytoskeletal status and organization at high performance. Using ILEE, we constructed a Python library to enable automated cytoskeletal image analysis, providing numerous biologically-interpretable indices measuring the density, bundling, severing, branching, and directionality of the cytoskeleton. The data presented herein demonstrate that ILEE resolves the defects of classic cytoskeleton analysis approaches, enables the measurement of novel cytoskeletal features, and yields quantitatively descriptive data with superior accuracy, stability, and robustness. We released the ILEE algorithm as an open-source library and further developed a Google Colab interface as a community resource.
A chemical screen based on an interruption of zebrafish gastrulation identifies the HTR2C inhibitor Pizotifen as a suppressor of EMT-mediated metastasis Metastasis is responsible for approximately 90% of cancer-associated mortality but few models exist that allow for rapid and effective screening of anti-metastasis drugs. Current mouse models of metastasis are too expensive and time consuming to use for rapid and high-throughput screening. Therefore, we created a unique screening concept utilizing conserved mechanisms between zebrafish gastrulation and cancer metastasis for identification of potential anti-metastatic drugs. We hypothesized that small chemicals that interrupt zebrafish gastrulation might also suppress metastatic progression of cancer cells and developed a phenotype-based chemical screen to test the hypothesis. The screen used epiboly, the first morphogenetic movement in gastrulation, as a marker and enabled 100 chemicals to be tested in five hours. The screen tested 1280 FDA-approved drugs and identified Pizotifen, an antagonist for serotonin receptor 2C (HTR2C) as an epiboly-interrupting drug. Pharmacologic and genetic inhibition of HTR2C suppressed metastatic progression in a mouse model. Blocking HTR2C with Pizotifen restored epithelial properties to metastatic cells through inhibition of Wnt-signaling. In contrast, HTR2C induced epithelial to mesenchymal transition (EMT) through activation of Wnt-signaling and promoted metastatic dissemination of human cancer cells in a zebrafish xenotransplantation model. Taken together, our concept offers a novel platform for discovery of anti-metastasis drugs. 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. T Cell Receptor Beta Germline Variability is Revealed by Inference From Repertoire Data BackgroundT and B cell receptor (TCR, BCR) repertoires constitute the foundation of adaptive immunity. Adaptive immune receptor repertoire sequencing (AIRR-seq) is a common approach to study immune system dynamics. Understanding the genetic factors influencing the composition and dynamics of these repertoires is of major scientific and clinical importance. The chromosomal loci encoding for the variable regions of TCRs and BCRs are challenging to decipher due to repetitive elements and undocumented structural variants.

MethodsTo confront this challenge, AIRR-seq-based methods have recently been developed for B cells, enabling genotype and haplotype inference and discovery of undocumented alleles. However, this approach relies on complete coverage of the receptors variable regions, whereas most T cell studies sequence a small fraction of that region. Here, we adapted a B cell pipeline for undocumented alleles, genotype, and haplotype inference for full and partial TCR sequences. The pipeline also deals with gene assignment ambiguities, which is especially important in the analysis of data-sets of partial sequences.

ResultsWe identified 39 undocumented polymorphisms in T cell receptor Beta V (TRBV) and 31 undocumented 5 UTR sequences. A subset of these inferences was also observed using independent genomic approaches. We found that a single nucleotide polymorphism differentiating between the two documented T cell receptor Beta D2 (TRBD2) alleles is strongly associated with dramatic changes in the expressed repertoire.

ConclusionsWe reveal a rich picture of germline variability, and demonstrate how a single nucleotide polymorphism dramatically affects the composition of the whole repertoire. Our findings provide a basis for annotation of TCR repertoires for future basic and clinical studies. A combined human in silico and CRISPR/Cas9-mediated in vivo zebrafish based approach for supporting gene target validation in early drug discovery The clinical heterogeneity of heart failure has challenged our understanding of the underlying genetic mechanisms of this disease. In this respect, large-scale patient DNA sequencing studies have become an invaluable strategy for identifying potential genetic contributing factors. The complex aetiology of heart failure, however, also means that in vivo models are vital to understand the links between genetic perturbations and functional impacts. Traditional approaches (e.g. genetically-modified mice) are optimal for assessing small numbers of proposed target genes, but less practical when multiple targets are identified. The zebrafish, in contrast, offers great potential for higher throughput in vivo gene functional assessment to aid target prioritisation and support definitive studies undertaken in mice. Here we used whole-exome sequencing and bioinformatics on human patient data to identify 3 genes (API5, HSPB7, and LMO2) suggestively associated with heart failure that were also predicted to play a broader role in disease aetiology. The role of these genes in cardiovascular system development and function was then further investigated using in vivo CRISPR/Cas9-mediated gene mutation analysis in zebrafish. We observed multiple impacts in F0 knockout zebrafish embryos (crispants) following effective somatic mutation, including reductions in ventricle size, pericardial oedema, and chamber malformation. In the case of lmo2, there was also a significant impact on cardiovascular function as well as an expected reduction in erythropoiesis. The data generated from both the human in silico and zebrafish in vivo assessments undertaken supports roles for API5, HSPB7, and LMO2 in human cardiovascular disease and identifies them as potential drug targets for further investigation. The data presented also supports the use of human in silico genetic variant analysis, in combination with zebrafish crispant phenotyping, as a powerful approach for assessing gene function as part of an integrated multi-level drug target validation strategy. 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. Morphology of immatures of the thelytokous ant, Monomorium triviale Wheeler (Formicidae: Myrmicinae: Solenopsidini) with descriptions of the extraordinary last-instar queen larvae The ant genus Monomorium is one of the most species-rich but taxonomically problematic groups in the hyperdiverse subfamily Myrmicinae. An East Asian species, M. triviale Wheeler, produces both reproductive queens and sterile workers via obligate thelytokous parthenogenesis. Here, we describe the immature forms of M. triviale based on light and scanning electron microscopy observations, with a note on the striking caste dimorphism in the last larval instar. The last-instar queen larvae were easily recognized by their large size, "aphaenogastroid" body shape, and rows of doorknob-like tubercles on the lateral and dorsal body surface. This type of queen-specific structure has not been found in ants in general, let alone congeneric species found in Japan. In stark contrast to the queen larvae, worker larvae showed a "pheidoloid" body shape and a body surface similar to other ants. The worker larvae were estimated to have three instars, consistent with previously described congeners. The pupae of both castes had no cocoon, a characteristic commonly described in other Myrmicinae species. In total, the developmental period from egg to adult worker averaged 59 days under 25{degrees}C. We discuss possible functions of the tubercles of queen larvae based on previous studies. Transcriptional condensates formed by phase-separated ALOG family proteins control shoot meristem maturation for flowering Plants have evolved remarkable diversity in inflorescence architecture. At the center of this diversity lies a meristem maturation program featured by transition of stem cell populations from a vegetative state into a reproductive growth, determining when, where, and how many flowers are produced on inflorescences. Here we identified a new meristem maturation regulator TMF FAMILY MEMBER3 (TFAM3) that encodes an ALOG family transcription factor. Loss of TFAM3 results in early flowering and simplified inflorescences with fewer flowers. Genetic analysis by creating high-order mutants of TFAM3 with three key regulators of tomato shoot meristem maturation, TERMINATING FLOWER (TMF), TMF FAMILY MEMBER1 (TFAM1) and TMF FAMILY MEMBER2 (TFAM2), suggested that they synergistically control flowering transition and inflorescence architecture. The four paralogous ALOG proteins share the prion-like properties and undergo liquid-liquid phase separation in vitro. Strikingly, TMF can recognize cognate TFAM proteins and selectively recruit them into phase separated condensates. Supporting this, they interact with themselves and each other to form biomolecular condensates in the nucleus. Their interaction induces formation of transcriptional condensates that directly repress expression of floral identity gene ANANTHA. Our study revealed a selective-recruitment phase separation mechanism for transcriptional condensation by which plants achieve optimal coordination of functional overlapped paralogs within a protein family to enable precise control of shoot meristem maturation for flowering and production of compound inflorescences. Ultrahigh-Throughput Ambient MS: Direct Analysis at 22 Samples per Second by Infrared Matrix-Assisted Desorption Electrospray Ionization Mass Spectrometry Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) mass spectrometry is an ambient-direct sampling method being developed for high-throughput, label-free, biochemical screening of large-scale compound libraries. Here, we report the development of an ultrahigh-throughput continuous motion IR-MALDESI sampling approach capable of acquiring data at rates up to 22.7 samples per second in a 384-well microtiter plate. At top speed, less than 1% analyte carryover is observed from well-to-well and signal intensity relative standard deviations (RSD) of 11.5% and 20.9% for 3 M 1-hydroxymidazolam and 12 M dextrorphan, respectively, are achieved. The ability to perform parallel kinetics studies on 384 samples with ~30s time resolution using an isocitrate dehydrogenase 1 (IDH1) enzyme assay is shown. Finally, we demonstrate the repeatability and throughput of our approach by measuring 115,200 samples from 300 microtiter plate reads consecutively over 5.54 hours with RSDs under 8.14% for each freshly introduced plate. Taken together, these results demonstrate the use of IR-MALDESI at sample acquisition rates that surpass other currently reported direct sampling mass spectrometry approaches used for high throughput compound screening.

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org.highwire.dtl.DTLVardef@5f916corg.highwire.dtl.DTLVardef@4473b4org.highwire.dtl.DTLVardef@82e8forg.highwire.dtl.DTLVardef@128b57b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Improving epigenetic clock performance and interpretation with deep learning Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years, with the vast majority based on regularized linear regression. This study explores the improvement in the performance and interpretation of epigenetic clocks using deep learning. First, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a neural network framework that is a highly accurate and precise age predictor. Compared to ElasticNet, AltumAge performs better for within-data set and cross-data set age prediction, being particularly more generalizable in older ages and new tissue types. We then used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observe that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. Using chromatin annotations, we show that the CpG sites with the highest contribution to the model predictions were related to gene regulatory regions in the genome, including proximity to CTCF binding sites. We also found age-related KEGG pathways for genes containing these CpG sites. Lastly, we perform downstream analyses of AltumAge to explore its applicability and compare its age acceleration with Horvaths model. We show that our neural network approach predicts higher age acceleration for tumors and for cells that exhibit age-related changes in vitro, such as replicative senescence and mitochondrial dysfunction. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks for both performance and model interpretability. 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. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Advanced paternal age diversifies individual trajectories of vocalization patterns in neonatal mice Infant crying is an innate communicative behavior that is frequently impaired in certain neurodevelopmental disorders (NDDs). Since advanced paternal age is a reported risk factor for NDDs in offspring, we evaluated the impact of a fathers age on early vocal development in C57BL/6J mice. We recorded and applied a unique combination of computational analyses to ultrasonic vocalizations (USVs) emitted by mouse pups sired by young and aged fathers. Our data showed that advanced paternal age reduced the number and duration of USVs, and altered the syllable composition in pups. Moreover, pups born to young fathers showed convergent vocal characteristics with a rich repertoire during postnatal development, while those born to aged fathers exhibited more divergent vocal patterns with limited repertoire. Principal component analysis in conjunction with clustering analysis demonstrated that pups from aged fathers deviated from typical trajectories of vocal development, which were considered as atypical individuals. Thus, our study indicates that advanced paternal age has a significant effect on offsprings early vocal development. It is suggested that the trajectories of vocal development could be a useful marker of the NDD-like phenotype associated with the advanced paternal age. In addition, our comprehensive computational analysis described here is an effective approach to characterize the altered individual diversity relevant to neurodevelopmental disorders.

One Sentence SummaryAdvanced paternal age affects vocal development in early postnatal mice, with more pups showing atypical developmental trajectories. Designing viral diagnostics with model-based optimization Diagnostics, particularly for rapidly evolving viruses, stand to benefit from a principled, measurement-driven design that harnesses machine learning and vast genomic data--yet the capability for such design has not been previously built. Here, we develop and extensively validate an approach to designing viral diagnostics that applies a learned model within a combinatorial optimization framework. Concentrating on CRISPR-based diagnostics, we screen a library of 19,209 diagnostic-target pairs and train a deep neural network that predicts, from RNA sequence alone, diagnostic signal better than contemporary techniques. Our model then makes it possible to design assays that are maximally sensitive over the spectrum of a viruss genomic variation. We introduce ADAPT (https://adapt.guide), a system for fully-automated design, and use ADAPT to design optimal diagnostics for the 1,933 vertebrate-infecting viral species within 2 hours for most species and 24 hours for all but 3. We experimentally show ADAPTs designs are sensitive and specific down to the lineage level, including against viruses that pose challenges involving genomic variation and specificity. ADAPTs designs exhibit significantly higher fluorescence and permit lower limits of detection, across a viruss entire variation, than the outputs of standard design techniques. Our model-based optimization strategy has applications broadly to viral nucleic acid diagnostics and other sequence-based technologies, and, paired with clinical validation, could enable a critically-needed, proactive resource of assays for surveilling and responding to pathogens. Spatial proteomics reveals subcellular reorganization in human keratinocytes exposed to UVA light The effects of UV light on the skin have been extensively investigated. However, systematic information about how exposure to UVA light, the least energetic but the most abundant UV radiation reaching the Earth, shapes the subcellular organization of proteins is lacking. Using subcellular fractionation, mass spectrometry-based proteomics, machine learning algorithms, immunofluorescence, and functional assays, we mapped the subcellular reorganization of the proteome of human keratinocytes in response to UVA light. Our workflow quantified and assigned subcellular localization for over 1600 proteins, of which about 200 were found to redistribute upon UVA exposure. Reorganization of the proteome affected modulators of signaling pathways, cellular metabolism, and DNA damage response. Strikingly, mitochondria were identified as one of the main targets of UVA-induced stress. Further investigation demonstrated that UVA induces mitochondrial fragmentation, up-regulates redox-responsive proteins and attenuates respiratory rates. These observations emphasize the role of this radiation as a potent metabolic stressor in the skin. Targeting MLL methyltransferases enhance the anti-tumor effects of PI3K inhibition in hormone receptor-positive breast cancer The high frequency of aberrant PI3K pathway activation in hormone receptor-positive (HR+) breast cancer has led to the development, clinical testing, and approval of the p110-selective PI3K inhibitor alpelisib. The limited clinical efficacy of alpelisib and other PI3K inhibitors is partially attributed to the functional antagonism between PI3K and estrogen receptor (ER) signaling, which is mitigated via combined PI3K inhibition and endocrine therapy. We and others have previously demonstrated a chromatin-associated mechanism by which PI3K supports cancer development and antagonizes ER signaling through the modulation of H3K4 methylation. Here we show that inhibition of the H3K4 histone methyltransferase MLL1 in combination with PI3K inhibition impairs HR+ breast cancer clonogenicity and cell proliferation. While combined PI3K/MLL1 inhibition reduces AKT effector signaling and H3K4 methylation, MLL1 inhibition increases PI3K effector signaling and upregulates the expression of receptor tyrosine kinase signaling cascades upstream of and including AKT. These data reveal a feedback loop between MLL1 and AKT in which MLL1 inhibition reactivates AKT. We additionally show that combined PI3K and MLL1 inhibition synergizes to cause cell death in in vitro and in vivo models of HR+ breast cancer, which is enhanced by the additional genetic ablation of the H3K4 methyltransferase and AKT target MLL4. Together, our data provide evidence of a feedback mechanism connecting histone methylation with AKT and may support the preclinical development and testing of pan-MLL inhibitors.

Significance StatementPharmacological inhibition of PI3K provides limited efficacy in PIK3CA-mutated, HR+ breast cancers. Here the authors leverage PI3K/AKT-driven chromatin modification to identify MLL histone methyltransferases as a therapeutic target. Dual PI3K and MLL inhibition synergize to reduce clonogenicity and cell proliferation while enhancing apoptosis in in vitro models, and induces tumor regression in xenograft models of PI3K-activated, HR+ breast cancer. Furthermore, MLL1 inhibition reveals a feedback loop leading to AKT hyperactivation, which is relieved with combined PI3K/MLL inhibition. These findings demonstrate the utility of MLL inhibitors for the treatment of some solid cancers, as patients with HR+ breast cancer characterized by PIK3CA mutation may derive clinical benefit from combined PI3K/MLL inhibition. wnt16 exerts pleiotropic effects on bone and lean mass in zebrafish Osteoporosis, a disease of bone fragility, and sarcopenia, a condition of reduced muscle mass and strength, commonly occur in the same individual--a condition termed osteosarcopenia. Genetic variants at the CPED1-WNT16 locus have pleiotropic effects on human bone mineral density (BMD) and lean tissue mass. However, our current understanding of Wnt16 and its influence on bone fails to explain effects on lean mass at this locus. In this study, we sought to better understand the biological mechanism underlying pleiotropy at the CPED1-WNT16 locus on BMD and lean mass. Using single cell analysis, microCT imaging, and genetic approaches in zebrafish, we show that wnt16 exerts dual influence on muscle and bone, and provide evidence that this occurs through a function in somite development, a period in which precursors for both of these tissues are specified. We show that mutations in wnt16 alter vertebral size and lean mass during axial skeletogenesis. We show that wnt16+ cells transcriptionally resemble cells within the amniote dermomyotome, and provide evidence they function as myogenic precursors during embryonic development. We also provide evidence that WNT16 is a gene of major effect on lean mass at the CPED-WNT16 locus. Our studies support the potential for wnt16 to exert pleiotropic effects on bone and lean mass through a function in myogenic precursors. Flexible control of Pavlovian-instrumental transfer based on expected reward value The Pavlovian-instrumental transfer (PIT) paradigm is widely used to assay the motivational influence of reward-predictive cues, reflected by their ability to invigorate instrumental behavior. Leading theories of incentive learning assume that cues are assigned motivational properties based on the value of the rewards they predict. We outline an alternative account of PIT which recognizes that reward-predictive cues may suppress rather than motivate instrumental behavior under certain conditions. We posit that cues capable of triggering a strong reward expectancy will tend to inhibit instrumental behavior, which is exploratory by nature, in order to facilitate retrieval of the expected reward before it is lost or stolen. According to this view, the motivation to engage in instrumental behavior during a cue should be inversely related to the value of the predicted reward, since there is more to lose by failing to secure a high-value reward than a low-value reward. We tested this hypothesis in rats using a high-conflict PIT protocol which elicits competing instrumental and food-port entry responses. In Experiment 1, cues signaling different reward magnitudes (1, 3, or 9 pellets) differentially influenced these behaviors. Whereas the 1-pellet cue increased instrumental behavior, cues signaling 3 or 9 pellets suppressed instrumental behavior and elicited high levels of food-port activity. Experiment 2 found that reward-predictive cues suppressed instrumental behavior and increased food-port activity in a flexible manner that was disrupted by post-training reward devaluation. We discuss how the PIT task provides a useful tool for studying cognitive control over cue-motivated behavior in rodents. Placental uptake and metabolism of 25(OH)Vitamin D determines its activity within the fetoplacental unit Pregnancy 25-hydroxyvitamin D (25(OH)D) concentrations are associated with maternal and fetal health outcomes. Using physiological human placental perfusion and villous explants, we investigate the role of the placenta in regulating the relationships between maternal 25(OH)D and fetal physiology. We demonstrate active placental uptake of 25(OH)D3 by endocytosis, placental metabolism of 25(OH)D3 into 24,25-dihydroxyvitamin D3 and active 1,25-dihydroxyvitamin D [1,25(OH)2D3], with subsequent release of these metabolites into both the maternal and fetal circulations. Active placental transport of 25(OH)D3 and synthesis of 1,25(OH)2D3 demonstrate that fetal supply is dependent on placental function rather than simply the availability of maternal 25(OH)D3. We demonstrate that 25(OH)D3 exposure induces rapid effects on the placental transcriptome and proteome. These map to multiple pathways central to placental function and thereby fetal development, independent of vitamin D transfer. Our data suggest that the underlying epigenetic landscape helps dictate the transcriptional response to vitamin D treatment. This is the first quantitative study demonstrating vitamin D transfer and metabolism by the human placenta, with widespread effects on the placenta itself. These data demonstrate a complex interplay between vitamin D and the placenta and will inform future interventions using vitamin D to support fetal development and maternal adaptations to pregnancy. de novo gene birth as an inevitable consequence of adaptive evolution Phylostratigraphy suggests that new genes are continually born de novo from non-genic sequences, and the genes that persist found new lineages, contributing to the adaptive evolution of organisms. While recent evidence supports the view that de novo gene birth is frequent and widespread, the mechanisms underlying this process are yet to be discovered. Here we hypothesize and examine a potential general mechanism of gene birth driven by the accumulation of beneficial mutations at non-genic loci. To demonstrate this possibility, we model this mechanism within the boundaries set by current knowledge on mutation effects. Estimates from this analysis are in line with observations of recurrent and extensive gene birth in genomics studies. Thus, we propose that, rather than being inactive and silent, non-genic regions are likely to be dynamic storehouses of potential genes. Revealing the inherent susceptibility of pathogenic bacteria to magnetic hyperthermia The growing number of multiple drug resistant (MDR) bacteria and the dwindling pipeline of new antibiotics are driving us towards a  post-antibiotic era in which even common infections would become difficult to treat. To address this, an antibiotic-free strategy that can combat multiple bacteria is recommended. Most of the proposed approaches nevertheless have several limitations, including bacterial targeting. To overcome such limitations, the proposed strategy employs the bacterial machinery to self-destruct. Herein, the biosynthesis of magnetic nanoparticle (MNP) is reported for the first time in multiple pathogenic bacteria, including MDR bacteria. The intracellular MNPs composed of superparamagnetic zinc ferrites were formed in presence of iron and zinc precursors. Exposure of the treated bacteria/biofilms to an alternating magnetic field (AMF) exhibited hyperthermia (5-6{degrees}C) and a dramatic decrease in bacterial viability, suggesting the MNPs therapeutic potential. Likewise, the bacteria existing in vivo biosynthesize the MNPs by mining these elements from the host. To determine its therapeutic efficacy, the infected tissues were exposed directly to AMF. A 3-4 log reduction in bacterial burden, as compared to antibiotics treatment, confirmed the significance of using naturally existing MNPs to combat bacterial infections. The proposed broad-spectrum approach can therefore aid in overcoming the challenges facing anti-bacterial therapies. Activation of the type 3 secretion system of enteropathogenic E. coli leads to remodeling of its membrane composition The cell envelope of gram-negative bacteria is a complex structure, essential for bacterial survival and for resistance to many antibiotics. Channels that cross the bacterial envelope and the host cell membrane form secretion systems that are activated upon attachment to host, enabling bacteria to inject effector molecules into the host cell, required for bacterial-host interaction. The type III secretion system (T3SS) is critical for the virulence of several pathogenic bacteria, including enteropathogenic E. coli (EPEC). The EPEC T3SS activation is associated with repression of carbon storage regulator (CsrA), resulting in gene expression remodeling, which is known to affect EPEC central carbon metabolism and contributes to the adaptation to a cell-adherent lifestyle in a poorly understood manner. We reasoned that the changes in bacterial envelope upon attachment to host and the activation of a secretion system may involve a modification of the lipid composition of bacterial envelope. Accordingly, we performed a lipidomics analysis on mutant strains that simulate T3SS activation. We saw a shift in glycerophospholipid metabolism towards the formation of lysophospholipids, attributed to corresponding upregulation of the phospholipase pldA and the acyltransferase ygiH upon T3SS activation in EPEC. We also detected a shift from menaquinones and ubiquinones to undecaprenyl lipids, concomitant to abnormal synthesis of O-antigen. The remodeling of lipid metabolism is mediated by CsrA and associated with increased bacteria cell size and Zeta potential, and a corresponding alteration in EPEC permeability to vancomycin, increasing the sensitivity of T3SS-activated strains and of adherent wild type EPEC to the antibiotic.

ImportanceThe characterization of EPEC membrane lipid metabolism upon attachment to host is an important step towards a better understanding the shift of EPEC, a notable human pathogen, from a planktonic to adherent life style. It may also apply to other pathogenic bacteria that use this secretion system. We predict that upon attachment to host cells the lipid remodeling upon T3SS activation contributes to bacterial fitness and promotes host colonization, and show that it is associated with increased cell permeability and higher sensitivity to vancomycin.

To the best of our knowledge, this is the first demonstration of a bacterial lipid remodeling due to activation of a secretion system. 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. Between two walls: Modeling the adsorption behavior of Beta-glucosidase A on bare and SAM-functionalised gold surfaces The efficient immobilization of enzymes on surfaces remains a complex but central issue in the biomaterials field, which requires us to understand this process at the atomic level. Using a multi-scale approach combining all-atom molecular dynamics and coarse-grain Brownian dynamics simulations, we investigated the adsorption behavior of {beta}-glucosidase A ({beta}GA) on bare and SAM-functionalized gold surfaces. We monitored the enzyme position and orientation during the MD trajectories, and measured the contacts it forms with both surfaces. While the adsorption process has little impact on the protein conformation, it can nonetheless perturb its mechanical properties and catalytic activity. Our results show that compared to the SAM-functionalized surface, the adsorption of {beta}GA on bare gold is more stable, but also less specific, and more likely to disrupt the enzymes function. This observation emphasizes the fact that the structural organization of proteins at the solid interface is a keypoint when designing devices based on enzyme immobilization, as one must find an acceptable stability-activity trade-off.

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org.highwire.dtl.DTLVardef@d3d0d7org.highwire.dtl.DTLVardef@3403e4org.highwire.dtl.DTLVardef@eb804dorg.highwire.dtl.DTLVardef@13469c2_HPS_FORMAT_FIGEXP  M_FIG C_FIG Climate warming changes synchrony of plants and pollinators Climate warming changes the phenology of many species. When interacting organisms respond differently, climate change may disrupt their interactions and affect the stability of ecosystems. Here, we used GBIF occurrence records to examine phenology trends in plants and their associated insect pollinators in Germany since the 1980s. We found strong phenological advances in plants, but differences in the extent of shifts among pollinator groups. The temporal trends in plant and insect phenologies were generally associated with interannual temperature variation, and thus likely driven by climate change. When examining the synchrony of species-level plant-pollinator interactions, their temporal trends differed among pollinator groups. Overall, plant-pollinator interactions become more synchronized, mainly since the phenology of plants responded more strongly to climate change than that of the pollinators. However, if the observed trends continue, many interactions may become more asynchronous again in the future. Our study suggests that climate change affects the phenologies of both plants and insects, and that it also influences the synchrony of plant-pollinator interactions.