Neural representations of others' traits predict social decisions To guide social interaction, people often rely on expectations about the traits of other people based on markers of social group membership, i.e., stereotypes. Although the influence of stereotypes on social behavior is widespread, key questions remain about how traits inferred from social group membership are instantiated in the brain and incorporated into neural computations that guide social behavior. Here, we show that the human lateral orbitofrontal cortex (OFC) represents the content of stereotypes about members of different social groups in the service of social decision-making. During fMRI scanning, participants decided how to distribute resources across themselves and members of a variety of social groups in a modified Dictator Game. Behaviorally, we replicated our recent finding that perceptions of others traits, captured by a two-dimensional framework of stereotype content (warmth and competence), biased participants monetary allocation choices in a context-dependent manner: recipients warmth increased advantageous inequity aversion and their competence increased disadvantageous inequity aversion. Neurally, representational similarity analysis (RSA) revealed that perceptions of others traits in the two-dimensional space were represented in the temporoparietal junction and superior temporal sulcus, two regions associated with mentalizing, and in the lateral OFC, known to represent latent environmental features during goal-directed outcome inference outside the social domain. Critically, only the latter predicted individual choices, suggesting that the effect of stereotypes on behavior is mediated by inference-based, domain-general decision-making processes in the OFC.
Rapid encoding of task regularities in the human hippocampus guides sensorimotor timing The brain encodes the statistical regularities of the environment in a task-specific yet flexible and generalizable format. Here, we seek to understand this process by converging two parallel lines of research, one centered on sensorimotor timing, and the other on cognitive mapping in the hippocampal system. By combining functional magnetic resonance imaging (fMRI) with a fastpaced time-to-contact (TTC) estimation task, we found that the hippocampus signaled behavioral feedback received in each trial as well as performance improvements across trials along with reward-processing regions. Critically, it signaled performance improvements independent from the tested intervals, and its activity accounted for the trial-wise regression-to-the-mean biases in TTC estimation. This suggests that the hippocampus supports the rapid encoding of temporal context even on short time scales in a behavior-dependent manner. Our results emphasize the central role of the hippocampus in statistical learning and position it at the core of a brain-wide network updating sensorimotor representations in real time for flexible behavior.
A biochemically-realisable relational model of the self-manufacturing cell As shown by Hofmeyr, the processes in the living cell can be divided into three classes of efficient causes that produce each other, so making the cell closed to efficient causation, the hallmark of an organism. They are the enzyme catalysts of covalent metabolic chemistry, the intracellular milieu that drives the supramolecular processes of chaperone-assisted folding and self-assembly of polypeptides and nucleic acids into functional catalysts and transporters, and the membrane transporters that maintain the intracellular milieu, in particular its electrolyte composition. Each class of efficient cause can be modelled as a relational diagram in the form of a mapping in graph-theoretic form, and a minimal model of a self-manufacturing system that is closed to efficient causation can be constructed from these three mappings using the formalism of relational biology. This Fabrication-Assembly or (F,A)-system serves as an alternative to Robert Rosens replicative Metabolism-Repair or (M,R)-system, which has been notoriously problematic to realise in terms of real biochemical processes. A key feature of the model is the explicit incorporation of formal cause, which arrests the infinite regress that plagues all relational models of the cell. The (F,A)-system is extended into a detailed relational model of the self-manufacturing cell that has a clear biochemical realisation. This (F,A) cell model allows the interpretation and visualisation of concepts such as the metabolism and repair components of Rosens (M,R)-system, John von Neumanns universal constructor, Howard Pattees symbol-function split via the symbol-folding transformation, Marcello Barbieris genotype-ribotype-phenotype ontology, and Tibor Gantis chemoton. An Evolutionary Process Without Variation and Selection Natural selection successfully explains how organisms accumulate adaptive change despite that traits acquired over a lifetime are eliminated at the end of each generation. However, in some domains that exhibit cumulative, adaptive change--e.g., cultural evolution, and earliest life--acquired traits are retained; these domains do not face the problem that Darwins theory was designed to solve. Lack of transmission of acquired traits occurs when germ cells are protected from environmental change, due to a self-assembly code used in two distinct ways: (i) actively interpreted during development to generate a soma, and (ii) passively copied without interpretation during reproduction to generate germ cells. Early life and cultural evolution appear not to involve a self-assembly code used in these two ways. We suggest that cumulative, adaptive change in these domains is due to a lower-fidelity evolutionary process, and model it using Reflexively Autocatalytic and Foodset-generated networks. We refer to this more primitive evolutionary process as Self-Other Reorganisation (SOR) because it involves internal self-organising and self-maintaining processes within entities, as well as interaction between entities. SOR encompasses learning but in general operates across groups. We discuss the relationship between SOR and Lamarckism, and illustrate a special case of SOR without variation. Elucidation of fibril helix structure responsible for swimming in Spiroplasma using electron microscopy Spiroplasma, known pathogens and commensals of arthropods and plants, are helical-shaped bacteria lacking the peptidoglycan layer. They swim by alternating between left- and right-handed cell helicity, which is driven by an internal structure called the ribbon. This system is unrelated to flagellar motility that is widespread in bacteria. The ribbon comprises the bacterial actin homolog MreB and fibril, the protein specific to Spiroplasma. Here, we isolated the ribbon and its core, the fibril filament, and using electron microscopy, found that the helicity of the ribbon and the cell is linked to the helicity of the fibril. Single particle analysis using the negative-staining method revealed that the three-dimensional structures of the fibril filament comprise a repeated ring structure twisting along the filament axis. The handedness of these structures were verified by the structures reconstituted through tomogram from quick-freeze deep-etch replica electron microscopy. Based on these observations, we propose a scheme for the helicity-switching mechanism in which the twists caused by the conformational changes in the fibril filament are accumulated, transmitted to the ribbon, and then propel the cells by rotating the cell body like a screw.

Significance StatementSpiroplasma are commensal and pathogenic bacteria widespread globally in animals and plants. A few species are also recognized as male-killing bacteria of insects. Their special swimming mechanism is caused by helicity switching, which could be the simplest swimming mechanism, because helicity shift can be caused by contraction and extension of paired filaments. This mechanism has attracted research attention for many years because of the possible application in the field of nano actuators; however, the details of this mechanism remain to be clarified. Here, we propose a model for the swimming mechanism based on the structure of the core of the Spiroplasma ribbon. Protein-protein interactions on membrane surfaces analysed using pull-downs with supported bilayers on silica beads Discovery-based proteomics workflows that identify novel interactors rely on immunoprecipitations or pull-downs with genetically-tagged bait proteins immobilized on appropriate matrices. But strategies to analyse protein interactions on a diffusible membrane surface combined with the practical ease of pull-downs remain unavailable. Such strategies are important to analyse protein complexes that mature in composition and stability because of diffusion-based encounter between participant proteins. Here, we describe a generic pull-down strategy to analyse such complexes using chelating lipid-containing supported bilayers formed on silica beads. These templates can display desired His-tagged bait proteins on a diffusible membrane surface. Using clathrin-mediated endocytosis as a paradigm, we find that the clathrin-binding adaptor protein epsin1 displayed as bait on these templates pulls down significantly higher amounts of clathrin from brain lysates than when immobilized on conventional matrices. Together, our results establish the potential of such templates as superior matrices for analysing protein-protein interactions and resultant complexes formed on membrane surfaces. Dimerization of kringle 1 domain from hepatocyte growth factor/scatter factor provides a potent minimal MET receptor agonist. Hepatocyte Growth Factor/Scatter Factor (HGF/SF) and its cognate receptor MET play several essential roles in embryogenesis and regeneration in post-natal life of epithelial organs such as liver, kidney, lung, and pancreas, prompting a strong interest in harnessing HGF/SF-MET signalling for regeneration of epithelial organs after acute or chronic damage. The limited stability and tissue diffusion of native HGF/SF, however, which reflect the tightly controlled, local mechanism of action of the morphogen, have led to a major search for HGF/SF mimics for therapy. In this work, we describe the rational design, production and characterisation of K1K1, a novel minimal MET agonist consisting of two copies of the kringle 1 domain of HGF/SF placed in tandem. K1K1 is highly stable and displays biological activities equivalent or superior to native HGF/SF in a variety of in vitro assay systems and in a mouse model of liver disease. These data suggest that this engineered ligand may find wide applications in acute and chronic diseases of the liver and other epithelial organs dependent on MET activation. SIX1 Reprograms Myogenic Transcription Factors to Maintain the Rhabdomyosarcoma undifferentiated state Rhabdomyosarcoma (RMS) is a pediatric skeletal muscle sarcoma characterized by the expression of the myogenic-lineage transcription factors (TF) MYOD1 and MYOG. Despite high expression of these TFs, RMS cells fail to terminally differentiate, suggesting the presence of factors that alter their function. Here, we demonstrate that the developmental TF, SIX1, is highly expressed in RMS and is critical to maintain a muscle progenitor-like state. SIX1 loss induces terminal differentiation of RMS cells into myotube-like cells and dramatically impedes tumor growth in vivo. We show that SIX1 maintains the RMS undifferentiated state by controlling enhancer activity and MYOD1 occupancy at loci more permissive to tumor growth over terminal muscle differentiation. Finally, we demonstrate that a gene signature derived from SIX1 loss correlates with differentiation status in RMS and predicts RMS progression in human disease. Our findings demonstrate a master regulatory role for SIX1 in the repression of RMS differentiation via genome-wide alterations in MYOD1-mediated transcription.

HighlightsO_LISIX1 prevents differentiation in RMS while it promotes differentiation during normal development
C_LIO_LIFN-RMS are highly dependent on SIX1 for growth in both zebrafish and mouse xenograft models
C_LIO_LILoss of SIX1 alters the transcriptional landscape of RMS cells, inducing a growth to differentiation switch
C_LIO_LISIX1 knockdown in FN-RMS causes reduced super enhancer-based activity at stem-related genes and enhanced MYOD1 binding to differentiation loci, resulting in the activation of a myogenic differentiation program
C_LIO_LIA gene signature derived from SIX1 loss strongly correlates with myogenic differentiation status and is predictive of advanced RMS.
C_LI Chromatin-contact atlas reveals disorder-mediated protein interactions RNA-binding proteins (RBPs) play diverse roles in regulating co-transcriptional RNA-processing and chromatin functions, but our knowledge of the repertoire of chromatin-associated RBPs (caRBPs) and their interactions with chromatin remains limited. Here, we developed SPACE (Silica Particle Assisted Chromatin Enrichment) to isolate global and regional chromatin components with high specificity and sensitivity, and SPACEmap to identify the chromatin-contact regions in proteins. Applied to mouse embryonic stem cells, SPACE identified 1,459 chromatin-associated proteins, [~]48% of which are annotated as RBPs, indicating their dual roles in chromatin and RNA-binding. Additionally, SPACEmap stringently verified chromatin-binding of 404 RBPs and identified their chromatin-contact regions. Notably, SPACEmap showed that about half of the caRBPs bind to chromatin by intrinsically disordered regions (IDRs). Studying SPACE and total proteome dynamics from mES cells grown in 2iL and serum medium indicates significant correlation (R = 0.62). One of the most dynamic caRBPs is Dazl, which we find co-localized with PRC2 at transcription start sites of genes that are distinct from Dazl mRNA binding. Dazl and other PRC2-colocalised caRBPs are rich in intrinsically disordered regions (IDRs), which could contribute to the formation and regulation of phase-separated PRC condensates. Together, our approach provides an unprecedented insight into IDR-mediated interactions and caRBPs with moonlighting functions in native chromatin. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. G protein-coupled estrogen receptor activation by Bisphenol-A disrupts protection from apoptosis conferred by estrogen receptors ERα and ERβ in pancreatic beta cells 17{beta}-estradiol protects pancreatic {beta}-cells from apoptosis via the estrogen receptors ER, ER{beta} and GPER. Conversely, the endocrine disruptor Bisphenol-A (BPA), which exerts multiple effects in this cell type via the same estrogen receptors, increased basal apoptosis. The molecular initiated events that trigger these opposite actions have yet to be identified. We demonstrated that combined genetic downregulation and pharmacological blockade of each estrogen receptor increased apoptosis to a different extent. The increase in apoptosis induced by BPA was diminished by the pharmacological blockade or the genetic silencing of GPER, and it was partially reproduced by the GPER agonist G1. BPA and G1-induced apoptosis were abolished upon pharmacological inhibition, silencing of ER and ER{beta}, or in dispersed islet cells from ER{beta} knockout (BERKO) mice. Yet, the ER and ER{beta} agonists, PPT and DPN, respectively, had no effect on beta cell viability. To exert their biological actions, ER and ER{beta} form homodimers and heterodimers. Molecular dynamic simulations together with proximity ligand assay and coimmunoprecipitation experiments indicated that the interaction of BPA with ER and ER{beta} as well as the GPER activation by G1 decreased ER{beta} heterodimers. We propose that ER{beta} heterodimers play an antiapoptotic role in beta cells and that BPA- and G1-induced decrease in ER{beta} heterodimers leads to beta cell apoptosis. Unveiling how different estrogenic chemicals affect the crosstalk among estrogen receptors should help to identify diabetogenic endocrine disruptors.

HighlightsO_LIPharmacological blockade and gene silencing of estrogen receptors ER, ER{beta} and GPER indicate that they are antiapoptotic in basal conditions.
C_LIO_LIGPER activation by G1 and BPA triggered apoptosis via a crosstalk with ER and ER{beta}.
C_LIO_LIBPA interaction with ER and ER{beta} as well as GPER activation decreased ER{beta} heterodimers, which was associated to increased apoptosis.
C_LIO_LIThis pathway represents a novel molecular initiating event underlying the pro-apoptotic effect of BPA
C_LIO_LIThe EndoC-{beta}H1 cell line may be a valid model of human {beta}-cells for identifying diabetogenic pollutants.
C_LI Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals due to various confounding challenges. Here, we demonstrate that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales--from genes to genomic regions and pathways--have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits, as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts. Fatal COVID-19 ARDS associated with incomplete AEC1 differentiation from the transitional state without senescence or fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. PrISM: precision for integrative structural models SummaryA single precision value is currently reported for an integrative model. However, precision may vary for different regions of an integrative model owing to varying amounts of input information. We develop PrISM (Precision for Integrative Structural Models), to efficiently identify high and low-precision regions for integrative models.

Availability and ImplementationPrISM is available at https://github.com/isblab/prism; benchmark data used in this paper is available at doi:10.5281/zenodo.6241200

Contactshruthiv@ncbs.res.in

Supplementary informationThis article contains Supplementary data online. Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding. Diverse wMel variants of Wolbachia pipientis differentially rescue fertility and cytological defects of the bag of marbles partial loss of function mutation in Drosophila melanogaster In Drosophila melanogaster, the maternally inherited endosymbiont Wolbachia pipientis interacts with germline stem cell genes during oogenesis. One such gene, bag of marbles (bam) is the key switch for differentiation and also shows signals of adaptive evolution for protein diversification. These observations have led us to hypothesize that W. pipientis could be driving the adaptive evolution of bam for control of oogenesis. To test this hypothesis, we must understand the specificity of the genetic interaction between bam and W. pipientis. Previously, we documented that the W. pipientis variant, wMel, rescued the fertility of the bamBW hypomorphic mutant as a transheterozygote over a bam null. However, bamBW was generated more than 20 years ago in an uncontrolled genetic background and maintained over a balancer chromosome. Consequently, the chromosome carrying bamBW accumulated mutations that have prevented controlled experiments to further assess the interaction. Here, we used CRISPR/Cas9 to engineer the same single amino acid bam hypomorphic mutation (bamL255F) and a new bam null disruption mutation into the w1118 isogenic background. We assess the fertility of wildtype bam, bamL255F/bamnull hypomorphic, and bamL255F/ bamL255F mutant females, each infected individually with ten W. pipientis wMel variants representing three phylogenetic clades. Overall, we find that all of the W. pipientis variants tested here rescue bam hypomorphic fertility defects with wMelCS-like variants exhibiting the strongest rescue effects. Additionally, these variants did not increase wildtype bam female fertility. Therefore, both bam and W. pipientis interact in genotype-specific ways to modulate female fertility, a critical fitness phenotype. MTG16 (CBFA2T3) regulates colonic epithelial differentiation, colitis, and tumorigenesis by repressing E protein transcription factors Aberrant epithelial differentiation and regeneration contribute to colon pathologies including inflammatory bowel disease (IBD) and colitis-associated cancer (CAC). MTG16 (CBFA2T3) is a transcriptional corepressor expressed in the colonic epithelium. MTG16 deficiency in mice exacerbates colitis and increases tumor burden in CAC, though the underlying mechanisms remain unclear. Here, we identified MTG16 as a central mediator of epithelial differentiation, promoting goblet and restraining enteroendocrine cell development in homeostasis and enabling regeneration following dextran sulfate sodium (DSS)-induced colitis. Transcriptomic analyses implicated increased E box-binding transcription factor (E protein) activity in MTG16-deficient colon crypts. Using a novel mouse model with a point mutation that disrupts MTG16:E protein complex formation (Mtg16P209T), we established that MTG16 exerts control over colonic epithelial differentiation and regeneration by repressing E protein-mediated transcription. Mimicking murine colitis, MTG16 expression was increased in biopsies from patients with active IBD compared to unaffected controls. Finally, uncoupling MTG16:E protein interactions only partially phenocopied the enhanced tumorigenicity of Mtg16-/- colon in the azoxymethane(AOM)/DSS-induced model of CAC, indicating that MTG16 protects from tumorigenesis through additional mechanisms. Collectively, our results demonstrate that MTG16, via its repression of E protein targets, is a key regulator of cell fate decisions during colon homeostasis, colitis, and cancer.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/467178v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@21948borg.highwire.dtl.DTLVardef@9f60eeorg.highwire.dtl.DTLVardef@194b9fdorg.highwire.dtl.DTLVardef@13eb1a7_HPS_FORMAT_FIGEXP  M_FIG C_FIG PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microcopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized.

HighlightsO_LIWe present PySTACHIO, a refined version of our spot tracking algorithm
C_LIO_LIWe demonstrate highly improved performance over previous MATLAB versions
C_LIO_LIPySTACHIO can accurately estimate stoichiometries and 2D diffusion coefficients
C_LIO_LIPerformance is comparable to state-of-the-art packages on challenge data
C_LIO_LIPySTACHIO has both GUI and command line interfaces and can be hosted as a web app
C_LI

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=77 SRC="FIGDIR/small/435952v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@17cc45dorg.highwire.dtl.DTLVardef@3fb66eorg.highwire.dtl.DTLVardef@e20360org.highwire.dtl.DTLVardef@4ba47d_HPS_FORMAT_FIGEXP  M_FIG C_FIG Transmembrane helices are an overlooked and evolutionarily conserved source of major histocompatibility complex class I and II epitopes Cytolytic T cell responses are predicted to be biased towards membrane proteins. The peptide-binding grooves of most haplotypes of histocompatibility complex class I (MHC-I) are relatively hydrophobic, therefore peptide fragments derived from human transmembrane helices (TMHs) are predicted to be presented more often as would be expected based on their abundance in the proteome. However, the physiological reason of why membrane proteins might be over-presented is unclear. In this study, we show that the over-presentation of TMH-derived peptides is general, as it is predicted for bacteria and viruses and for both MHCI and MHC-II. Moreover, we show that TMHs are evolutionarily more conserved, because single nucleotide polymorphisms (SNPs) are present relatively less frequently in TMH-coding chromosomal regions compared to regions coding for extracellular and cytoplasmic protein regions. Thus, our findings suggest that both cytolytic and helper T cells respond more to membrane proteins, because these are evolutionary more conserved. We speculate that TMHs therefore are less prone to escape mutations that enable pathogens to evade T cell responses. Social behavioral profiling by unsupervised deep learning reveals a stimulative effect of dopamine D3 agonists on zebrafish sociality It has been a major challenge to systematically evaluate and compare how pharmacological perturbations influence social behavioral outcomes. Although some pharmacological agents are known to alter social behavior, precise description and quantification of such effects have proven difficult. The complexity of brain functions regulating sociality makes it challenging to predict drug effects on social behavior without testing in live animals, and most existing behavioral assays are low-throughput and provide only unidimensional readouts of social function. To achieve richer characterization of drug effects on sociality, we developed a scalable social behavioral assay for zebrafish named ZeChat based on unsupervised deep learning. High-dimensional and dynamic social behavioral phenotypes are automatically classified using this method. By screening a neuroactive compound library, we found that different classes of chemicals evoke distinct patterns of social behavioral fingerprints. By examining these patterns, we discovered that dopamine D3 agonists possess a social stimulative effect on zebrafish. The D3 agonists pramipexole, piribedil, and 7-hydroxy-DPAT-HBr rescued social deficits in a valproic acid-induced zebrafish autism model. The ZeChat platform provides a promising approach for dissecting the pharmacology of social behavior and discovering novel social-modulatory compounds. Embracing imperfection: machine-assisted invertebrate classification in difficult datasets O_LIDespite growing concerns over the health of global invertebrate diversity, terrestrial invertebrate monitoring efforts remain poorly geographically distributed. Machine-assisted classification has been proposed as a potential solution to quickly gather large amounts of data; however, previous studies have often used unrealistic or idealized datasets to train their models.
C_LIO_LIIn this study, we describe a practical methodology for including machine learning in ecological data acquisition pipelines. Here we train and test machine learning algorithms to classify over 56,000 bulk terrestrial invertebrate specimens from morphometric data and contextual metadata. All vouchered specimens were collected in pitfall traps by the National Ecological Observatory Network (NEON) at 27 locations across the United States in 2016. Specimens were photographed, and morphometric data was extracted as feature vectors using ImageJ. Issues stemming from inconsistent taxonomic label specificity were resolved by making classifications at the lowest identified taxonomic level (LITL). Taxa with too few specimens to be included in the training dataset were classified by the model using zero-shot classification.
C_LIO_LIWhen classifying specimens that were known and seen by our models, we reached an accuracy of 72.7% using extreme gradient boosting (XGBoost) at the LITL. Models that were trained without contextual metadata underperformed models with contextual metadata by an average of 7.2%. We also classified invertebrate taxa that were unknown to the model using zero-shot classification, with an accuracy of 39.4%, resulting in an overall accuracy of 71.5% across the entire NEON dataset.
C_LIO_LIThe general methodology outlined here represents a realistic application of machine learning as a tool for ecological studies. Hierarchical and LITL classifications allow for flexible taxonomic specificity at the input and output layers. These methods also help address the  long tail problem of underrepresented taxa missed by machine learning models. Finally, we encourage researchers to consider more than just morphometric data when training their models, as we have shown that the inclusion of contextual metadata can provide significant improvements to accuracy.
C_LI Inhibitors of ERp44, PDIA1, and AGR2 induce disulfide-mediated oligomerization of Death Receptors 4 and 5 and cancer cell death Breast cancer mortality remains unacceptably high, indicating a need for safer and more effective therapeutic agents. Disulfide bond Disrupting Agents (DDAs) were previously identified as a novel class of anticancer compounds that selectively kill cancers that overexpress the Epidermal Growth Factor Receptor (EGFR) or its family member HER2. DDAs kill EGFR+ and HER2+ cancer cells via the parallel downregulation of EGFR, HER2, and HER3 and activation/oligomerization of Death Receptors 4 and 5 (DR4/5). However, the mechanisms by which DDAs mediate these effects are unknown. Affinity purification analyses employing biotinylated-DDAs reveal that the Protein Disulfide Isomerase (PDI) family members AGR2, PDIA1, and ERp44 are DDA target proteins. Further analyses demonstrate that shRNA-mediated knockdown of AGR2 and ERp44, or expression of ERp44 mutants, enhance basal and DDA-induced DR5 oligomerization. DDA treatment of breast cancer cells disrupts PDIA1 and ERp44 mixed disulfide bonds with their client proteins. Together, the results herein reveal DDAs as the first small molecule, active site inhibitors of AGR2 and ERp44, and demonstrate roles for AGR2 and ERp44 in regulating the activity, stability, and localization of DR4 and DR5, and activation of Caspase 8. 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. Sperm Histone H3 Lysine 4 tri-methylation serves as a metabolic sensor of paternal obesity and is associated with the inheritance of metabolic dysfunction ObjectiveParental environmental exposures can strongly influence descendant risks for adult disease. How paternal obesity changes the sperm chromatin leading to the acquisition of metabolic disease in offspring remains controversial and ill-defined. The objective of this study was to assess: (1) whether obesity induced by a high-fat diet alters sperm histone methylation; (2) whether paternal obesity can induce metabolic disturbances across generations; (3) whether there could be cumulative damage to the sperm epigenome leading to enhanced metabolic dysfunction in descendants; and (4) whether obesity-sensitive regions associate with embryonic epigenetic and transcriptomic profiles. Using a genetic mouse model of epigenetic inheritance, we investigated the role of histone H3 lysine 4 methylation (H3K4me3) in the paternal transmission of metabolic dysfunction. This transgenic mouse overexpresses the histone demethylase enzyme KDM1A in the developing germline and has an altered sperm epigenome at the level of histone H3K4 methylation. We hypothesized that challenging transgenic sires with a high-fat diet would further erode the sperm epigenome and lead to enhanced metabolic disturbances in the next generations.

MethodsTo assess whether paternal obesity can have inter- or transgenerational impacts, and if so, to identify potential mechanisms of this non-genetic inheritance, we used wildtype C57BL/6NCrl and transgenic males with a pre-existing altered sperm epigenome. To induce obesity, sires were fed either a control or high-fat diet (10% or 60% kcal fat, respectively) for 10-12 weeks, then bred to wildtype C57BL/6NCrl female fed a regular diet. F1 and F2 descendants were characterized for metabolic phenotypes by examining the effects of paternal obesity by sex, on body weight, fat mass distribution, the liver transcriptome, intraperitoneal glucose and insulin tolerance tests. To determine whether obesity altered the F0 sperm chromatin, native chromatin immunoprecipitation-sequencing targeting H3K4me3 was performed. To gain insight into mechanisms of paternal transmission, we compared our sperm H3K4me3 profiles with embryonic and placental chromatin states, histone modification and gene expression profiles.

ResultsObesity-induced alterations in H3K4me3 occurred at genes implicated in metabolic, inflammatory, and developmental processes. These processes were associated with offspring metabolic dysfunction and corresponded to genes enriched for H3K4me3 in embryos, and overlapped embryonic and placenta gene expression profiles. Transgenerational susceptibility to metabolic disease was only observed when obese F0 had a pre-existing modified sperm epigenome. This coincided with increased H3K4me3 alterations in sperm and more severe phenotypes affecting their offspring.

ConclusionsOur data suggest sperm H3K4me3 might serve as a metabolic sensor that connects paternal diet with offspring phenotypes via the placenta. This non-DNA based knowledge of inheritance has the potential to improve our understanding of how environment shapes heritability and may lead to novel routes for the prevention of disease. This study highlights the need to further study the connection between the sperm epigenome, placental development and childrens health. Genetic variation associated with plastic and homeostatic growth responses to drought in Arabidopsis O_LINatural genetic variation influences plant responses to environmental stressors. However, the extent to which such variation underlies plastic versus homeostatic response phenotypes has been little studied.
C_LIO_LIWe quantified the extent of drought-induced changes in leaf area in a set of Iberian Arabidopsis accessions and then performed association studies correlating variation in this phenotype with genomic and transcriptomic variation.
C_LIO_LIDrought-induced plastic reductions in relative leaf area typified accessions originating from productive environments. In contrast, homeostasis in relative leaf area typified accessions originating from unproductive environments. Genome-Wide Association Studies (GWAS), Transcriptome Wide Association Studies (TWAS), and expression GWAS (eGWAS) highlighted the importance of auxin-related processes and, in particular, the potential role of the SMALL AUXIN UP RNA 26 (SAUR26) gene in conferring leaf area plasticity. Homeostatic responses in relative leaf area were associated with a diverse gene set and positively associated with a higher intrinsic water use efficiency (WUEi) as confirmed in a TWAS metanalysis of previously published {delta}13C measurements.
C_LIO_LIWe have identified not only candidate "plasticity genes" but also candidate "homeostasis genes" controlling leaf area. Our results demonstrate the value of a combined GWAS, TWAS, and eGWAS approach to identify mechanisms underlying phenotypic responses to stress.
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One-sentence summaryInformation on phenotype, genotype, and transcript abundance is integrated to identify both plasticity and homeostasis genes and processes associated with local adaptation to drought stress in Arabidopsis accessions of the Iberian Peninsula. Robust retrieval of data stored in DNA by de Bruijn graph-based de novo strand assembly DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted.