Human electroencephalography recordings for 1,854 concepts presented in rapid serial visual presentation streams The neural basis of object recognition and semantic knowledge has been extensively studied but the high dimensionality of object space makes it challenging to develop overarching theories on how the brain organises object knowledge. To help understand how the brain allows us to recognise, categorise, and represent objects and object categories, there is a growing interest in using large-scale image databases for neuroimaging experiments. In the current paper, we present THINGS-EEG, a dataset containing human electroencephalography responses from 50 subjects to 1,854 object concepts and 22,248 images in the THINGS stimulus set, a manually curated and high-quality image database that was specifically designed for studying human vision. The THINGS-EEG dataset provides neuroimaging recordings to a systematic collection of objects and concepts and can therefore support a wide array of research to understand visual object processing in the human brain.
Finding structure in time: Humans, machines, and language The emergence of artificial neural networks (ANNs) that seem capable of emulating the remarkable human capacity for language has raised fundamental questions about complex cognition in humans and machines. This debate has taken place, however, in the context of limited empirical evidence about how the internal operations of ANNs relate to dynamic processes in the human brain as listeners understand language. Using Representational Similarity Analysis, we conducted a set of in-depth comparisons between these two types of systems, focusing on a core aspect of human language - the building of a structured and meaningful interpretation as each word in a sentence is heard in sequence. We extracted incremental structural measures of unfolding sentences from a deep language ANN and tested these against the spatiotemporally resolved brain activity recorded by electro/magnetoencephalography when human participants were listening to the same sentences. These uniquely neurocomputationally specific comparisons revealed strong behavioral and neural alignments between humans and ANNs in the use of multi-dimensional probabilistic constraints to build word-by-word structural interpretations, suggesting important commonalities in basic computational strategies for finding structure in time.
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. Intramolecular 13C signals inform about carbon allocation in plants Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at treering glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesising leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference of leaf-cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

HighlightIntramolecular 13C/12C analysis resolves information about carbon uptake and allocation (and associated environmental controls) enabling more comprehensive assessments of carbon metabolism, plant-environment interactions, and environmental variability than whole-molecule 13C/12C analysis. CellKb Immune: a manually curated database of mammalian hematopoietic marker gene sets for rapid cell type identification Using single-cell RNA sequencing, it is now possible to get the detailed gene expression pattern in each cell for millions of cells in a single experiment under varying conditions. Annotating cells by assigning a type or state to them is important for correct interpretation of results. In spite of current advances in technology, assigning cell types in single-cell datasets remains a bottleneck due to the lack of a comprehensive reference database and an accurate search method in a single tool. CellKb Immune is a knowledgebase of manually collected, curated and annotated marker gene sets representing cell types in the immune response in mouse. It allows users to find matching cell types in literature given a list of genes. We evaluated the contents and search methodology of CellKb Immune using a leave-one-out approach. We further used CellKb Immune to annotate previously defined marker gene sets from a bulk RNA-seq dataset to confirm its accuracy and coverage. CellKb Immune provides an easy-to-use online tool with a reliable method to find matching cell types and annotate cells in single-cell experiments. It is available at https://www.cellkb.com/immune. Engineering of a fluorescent chemogenetic reporter with tunable color for advanced live-cell imaging Biocompatible fluorescent reporters with spectral properties spanning the entire visible spectrum are indispensable tools for imaging the biochemistry of living cells and organisms in real time. Here, we present the engineering of a fluorescent chemogenetic reporter with tunable optical and spectral properties. A collection of live-cell compatible fluorogenic chromophores with various electronic properties enables to generate bimolecular fluorescent assemblies that cover the visible spectrum from blue to red using a single protein tag engineered and optimized by directed evolution and rational design. We showed that the ability to tune the fluorescence color and properties through simple molecular modulation provides an unprecedent experimental versatility for imaging proteins in live cells, including delicate cultured hippocampal neurons, and in multicellular organisms. The ability to tune the spectral properties and fluorescence performance enables to match the spectral specifications and requirements of the most advanced imaging techniques, and allowed us to achieve efficient stimulated emission depletion (STED) nanoscopy of fusion proteins in live cells and live primary cultured neurons. Shorter effective lifespan in laboratory populations of D. melanogaster can reduce sexual selection. The role of sexual selection in mediating levels of sexual conflict has been demonstrated in many experimental evolution studies on Drosophila spp. where competition among males for mating was the target of selection. Sexual selection has also been shown to affect the evolution of life-histories. However, the influence of divergent life-histories on reproductive strategies and, therefore, sexual selection and possibly sexual conflict, has been less well studied. We examined D. melanogaster populations selected for a short development time and early age at reproduction for changes in reproductive behaviour and traits that are proxies of sexual selection. We report a large reduction in reproductive competition experienced by the males of these populations, compared to ancestral populations that are not consciously selected for rapid development or early reproduction, potentially leading to reduced sexual selection. We show that rapidly developing and early reproducing populations have very low levels of mating in their lifetime (females are more or less monandrous), low courtship levels, shorter copulation duration, and longer time from eclosion to first mating, compared to the controls. These results are discussed in the context of the previously demonstrated reduction of inter-locus sexual conflict in these populations. We show that life-history strategies might have a large and significant impact on sexual selection, with each influencing the other and contributing to the complexities of adaptation.

Significance statementSexual conflict, often manifested as an arms-race between males and females trying to enhance their own reproductive success at some cost to the other, is of great evolutionary interest because it can maintain genetic variation in populations, prevent the independent optimization of male and female traits, and also promote speciation. Sexual selection, or variation in mating success, is well known to affect levels of sexual conflict. However, it is not so clear whether, and how, the regular evolution of life-histories also affects sexual selection. Here, we show that life-history evolution in fruit fly populations selected for traits not directly related to sexual conflict might, nevertheless, mediate the possible evolution of altered sexual conflict levels through effects on sexual selection. Populations that evolved to develop to adulthood fast, and reproduce relatively early in life, are shown to potentially experience less sexual selection, which can explain the low sexual conflict levels earlier observed in them. BRD2 inhibition blocks SARS-CoV-2 infection by reducing transcription of the host cell receptor ACE2 SARS-CoV-2 infection of human cells is initiated by the binding of the viral Spike protein to its cell-surface receptor ACE2. We conducted a targeted CRISPRi screen to uncover druggable pathways controlling Spike protein binding to human cells. We found that the protein BRD2 is required for ACE2 transcription in human lung epithelial cells and cardiomyocytes, and BRD2 inhibitors currently evaluated in clinical trials potently block endogenous ACE2 expression and SARS-CoV-2 infection of human cells, including those of human nasal epithelia. Moreover, pharmacological BRD2 inhibition with the drug ABBV-744 inhibited SARS-CoV-2 replication in Syrian hamsters. We also found that BRD2 controls transcription of several other genes induced upon SARS-CoV-2 infection, including the interferon response, which in turn regulates the antiviral response. Together, our results pinpoint BRD2 as a potent and essential regulator of the host response to SARS-CoV-2 infection and highlight the potential of BRD2 as a novel therapeutic target for COVID-19. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. The longevity response to warm temperature is neurally controlled via the regulation of collagen genes Studies in diverse species have associated higher temperatures with shorter lifespan and lower temperatures with longer lifespan. However, the mechanisms behind these inverse effects of temperature on longevity are not well understood. Here, we demonstrate that in Caenorhabditis elegans, functional loss of NPR-8, a G protein-coupled receptor related to mammalian neuropeptide Y receptors, increases worm lifespan at 25{degrees}C but not at 20{degrees}C or 15{degrees}C, and that the lifespan increase at 25{degrees}C is regulated by the NPR-8-expressing AWB and AWC chemosensory neurons as well as AFD thermosensory neurons. RNA sequencing revealed that both warm temperature and old age profoundly alter gene expression. Further investigation uncovered that the NPR-8-dependent longevity response to warm temperature is achieved by regulating the expression of a subset of collagen genes. As elevated collagen expression is a common feature of many lifespan-extending interventions and enhanced stress resistance, collagen expression could be critical for healthy aging. Genomically Mined Acoustic Reporter Genes Enable In Vivo Monitoring of Tumors and Tumor-Homing Bacteria A major outstanding challenge in the fields of biological research, synthetic biology and cell-based medicine is the difficulty of visualizing the function of natural and engineered cells noninvasively inside opaque organisms. Ultrasound imaging has the potential to address this challenge as a widely available technique with a tissue penetration of several centimeters and spatial resolution below 100 {micro}m. Recently, the first genetically encoded acoustic reporters were developed based on bacterial gas vesicles to link ultrasound signals to molecular and cellular function. However, the properties of these first-generation acoustic reporter genes (ARGs) resulted in limited sensitivity and specificity for imaging in the in vivo context. Here, we describe second-generation ARGs with greatly improved acoustic properties and expression characteristics, identified through a phylogenetic screen of candidate gene clusters from diverse bacteria and archaea. The resulting constructs offer major qualitative and quantitative improvements, including much stronger ultrasound contrast, the ability to produce nonlinear signals distinguishable from background tissue, and stable long-term expression. We demonstrate the utility of these next-generation ARGs by imaging in situ gene expression in mouse models of breast cancer and tumor-homing probiotic bacteria, revealing the unique spatial distributions of tumor growth and colonization by therapeutic cells noninvasively in living subjects. Are microbes growing on flowers evil? Effects of old flower microbes on fruit set in a wild ginger with one-day flowers, Alpinia japonica (Zingiberaceae) Flowers are colonized and inhabited by diverse microbes. Plants rapidly replace flowers with short lifespan, and old flowers senesce. This may contribute to avoiding adverse effects of the microbes. In this study, we investigate if the flower microbial community on old flowers impedes fruit and seed production in a wild ginger with one-day flowers. We inoculated newly opened flowers with old flower microbes, and monitored the effects on fruit and seed set. We also assessed prokaryotic communities on the flowers using amplicon sequencing. We found six bacterial amplicon sequence variants (ASVs) whose proportions were increased on the inoculated flowers. These ASVs were also found on flower buds and flowers that were bagged by net or paper during anthesis, suggesting that they had been present in small numbers prior to flowering. Fruit set was negatively associated with the proportions of these ASVs, while seed set was not. The results suggest that old flowers harbor microbial communities different from those at anthesis, and that the microbes abundant on old flowers negatively affect plant reproduction. Though the short lifespan of flowers has gotten little attention, it might be an essential defense mechanism to cope with antagonistic microbes that rapidly proliferate on the flowers. 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. The Inflammatory Role of Milk Fat Globule Epidermal Growth Factor VIII in Angiotensin II Induced Arterial Remodeling BackgroundAngiotensin II (Ang II) and milk fat globule-epidermal growth factor VIII (MFG-E8) are involved in age-associated arterial remodeling; however, the inflammatory role of MFG-E8 in Ang II associated arterial remodeling with aging remains unknown.

Methods and ResultsIn this study, 30-week-old MFG-E8 knock out (KO) and age-matched wild-type (WT) mice were infused with Ang II or saline. After infusion the with Ang II, the aortic molecular, cellular, and structural remodeling were observed in mice and compared to those infused with saline, but these effects were dependent on the expression of MFG-E8: (1) In the WT mice, Ang II infusion substantially increased intimal-medial thickness, elastic lamina degradation, collagen deposition, and the proliferation of VSMCs; in contrast, in the KO mice, these effects were significantly reduced; (2) In the WT mice, Ang II treatment significantly increased the activation and expression of MMP2, TGF-{beta}1, and its downstream signaling molecule p-SMAD2, and collagen type I production, however, in the KO mice, these molecular effects were significantly reduced; (3) In the WT mice, Ang II treatment increased inflammatory p-NF-{kappa}B p65, MCP1, TNF-, ICAM1, and VCAM1 molecular expression, while conversely, in the KO mice, no significant inflammatory changes were found; (4) Importantly, compared to untreated control mice with a wide range of age from 4-96 weeks, Ang II infused "younger" mice produced an "older" arterial inflammatory phenotype, which was alleviated by MFG-E8 deficiency.

ConclusionsMFG-E8 mediates Ang II associated arterial inflammatory remodeling. Targeting MFG-E8 is a novel molecular approach to curb adverse arterial remodeling during aging and hypertension.

CLINICAL PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABS* Both Ang II and MFG-E8 increases are involved in proinflammatory arterial remodeling mediating the molecular, cellular and tissue events in aging and hypertension.
* MFG-E8 is essential for Ang II induced and age-associated adverse arterial remodeling via the increase of proinflammation, intimal medial thickening, elastin fragmentation, collagen deposition, and VSMC proliferation.


What Are the Clinical Implications?Since MFG-E8 mediates Ang II induced proinflammation in arterial wall remodeling in aging and hypertension, targeting MFG-E8 is a potential molecular approach to curb inflammatory arterial remodeling, maintaining the health of the vascular system during aging and hypertension. Python-Microscope: A new open source Python library for the control of microscopes Custom built microscopes often require control of multiple hardware devices and precise hardware coordination. It is also desirable to have a solution that is scalable to complex systems and translatable between components from different manufacturers. Here we report Python-Microscope, a free and open source Python library for high performance control of arbitrarily complex and scalable custom microscope systems. Python-Microscope offers simple to use Python-based tools, abstracting differences between physical devices by providing a defined interface for different device types. Concrete implementations are provided for a range of specific hardware and a framework exists for further expansion. Python-Microscope supports the distribution of devices over multiple computers while maintaining synchronisation via highly precise hardware triggers. We discuss the architecture choices of Python-Microscope that overcome the performance problems often raised against Python and demonstrate the different use cases that drove its design: its integration in user facing projects, namely in the Microscope-Cockpit project; in controlling complex microscopes at high speed while using the Python programming language; and as a microscope simulation tool for software development. The transposable element-rich genome of the cereal pest Sitophilus oryzae BackgroundThe rice weevil Sitophilus oryzae is one of the most important agricultural pests, causing extensive damage to cereal in fields and to stored grains. S. oryzae has an intracellular symbiotic relationship (endosymbiosis) with the Gram-negative bacterium Sodalis pierantonius and is a valuable model to decipher host-symbiont molecular interactions.

ResultsWe sequenced the Sitophilus oryzae genome using a combination of short and long reads to produce the best assembly for a Curculionidae species to date. We show that S. oryzae has undergone successive bursts of transposable element (TE) amplification, representing 72% of the genome. In addition, we show that many TE families are transcriptionally active, and changes in their expression are associated with insect endosymbiotic state. S. oryzae has undergone a high gene expansion rate, when compared to other beetles. Reconstruction of host-symbiont metabolic networks revealed that, despite its recent association with cereal weevils (30 Kyear), S. pierantonius relies on the host for several amino acids and nucleotides to survive and to produce vitamins and essential amino-acids required for insect development and cuticle biosynthesis.

ConclusionsHere we present the genome of an agricultural pest beetle, which may act as a foundation for pest control. In addition, S. oryzae may be a useful model for endosymbiosis, and studying TE evolution and regulation, along with the impact of TEs on eukaryotic genomes. A multivariate view of cognitive performance reveals positive correlation in the Trinidadian Guppy (Poecilia reticulata) Cognitive variation is common among-individuals and can be consistent across time and context. From an evolutionary perspective, among-individual variation is important as a pre-requisite for natural selection and adaptive evolution. Selection is widely hypothesized to favor high cognitive performance but directional selection should erode variation over time, how then is cognitive variation maintained? As selection does not act on traits in isolation, covariance among specific cognitive traits and/or other aspects of phenotype (e.g. personality) could result in fitness trade-offs that are important in shaping evolutionary dynamics. Here we test this using Trinidadian guppies (Poecilia reticulata), using a multivariate approach by characterising the correlation structure among task-specific cognitive performance measures and a personality trait. We estimate the among-individual correlation matrix (ID) in performance across three cognitive tasks; colour association learning task; motor learning task; reversal learning task, and the personality trait  boldness measured as emergence time from a shelter. We found no support for trade-offs among performance in these tasks. Nor do we find evidence of hypothesised speed-accuracy trade-offs within the association learning task. Rather we find strong positive correlation structure in ID, with 57% of variation explained by the leading eigen vector. While noting that non-cognitive factors and assay composition may affect the structure of ID, we suggest our findings are consistent with the g-model of cognitive performance variation, in which a dominant axis of variation loads positively on all performance measures. Thus, we add to a growing body of support for general variation among individuals in animal cognitive ability. SARS-CoV-2 Variants Reveal Features Critical for Replication in Primary Human Cells Since entering the human population, SARS-CoV-2 (the causative agent of COVID-19) has spread worldwide, causing >100 million infections and >2 million deaths. While large-scale sequencing efforts have identified numerous genetic variants in SARS-CoV-2 during its circulation, it remains largely unclear whether many of these changes impact adaptation, replication or transmission of the virus. Here, we characterized 14 different low-passage replication-competent human SARS-CoV-2 isolates representing all major European clades observed during the first pandemic wave in early 2020. By integrating viral sequencing data from patient material, virus stocks, and passaging experiments, together with kinetic virus replication data from non-human Vero-CCL81 cells and primary differentiated human bronchial epithelial cells (BEpCs), we observed several SARS-CoV-2 features that associate with distinct phenotypes. Notably, naturally-occurring variants in Orf3a (Q57H) and nsp2 (T85I) were associated with poor replication in Vero-CCL81 cells but not in BEpCs, while SARS-CoV-2 isolates expressing the Spike D614G variant generally exhibited enhanced replication abilities in BEpCs. Strikingly, low-passage Vero-derived stock preparation of 3 SARS-CoV-2 isolates selected for substitutions at positions 5/6 of E, and were highly attenuated in BEpCs, revealing a key cell-specific function to this region. Rare isolate-specific deletions were also observed in the Spike furin-cleavage site during Vero-CCL81 passage, but these were rapidly selected against in BEpCs, underscoring the importance of this site for SARS-CoV-2 replication in primary human cells. Overall, our study uncovers sequence features in SARS-CoV-2 variants that determine cell-specific virus replication, and highlights the need to monitor SARS-CoV-2 stocks carefully when phenotyping newly emerging variants or potential variants-of-concern. Human 14-3-3 proteins site-selectively bind the mutational hotspot region of SARS-CoV-2 nucleoprotein modulating its phosphoregulation Phosphorylated within its Ser/Arg-rich region, the SARS-CoV-2 nucleoprotein (N) recruits the phosphopeptide-binding human 14-3-3 proteins that play a well-recognized role in replication of many viruses. Here we use genetic code expansion to demonstrate that phosphorylation of SARS-CoV-2 N at either of two pseudo-repeats centered at Ser197 and Thr205 is sufficient for 14-3-3 binding. According to fluorescence anisotropy, the pT205-motif, present in SARS-CoV-2 but not in SARS-CoV, is preferred over the pS197-motif by all seven human 14-3-3 isoforms, which display unforeseen pT205/pS197 binding selectivity hierarchy. Crystal structures demonstrate that pS197 and pT205 are mutually exclusive 14-3-3-binding sites, whereas SAXS and biochemical data indicate 14-3-3 binding occludes the Ser/Arg-rich region, inhibiting its dephosphorylation. This Ser/Arg-rich region of N is highly prone to mutations, as exemplified by the Omicron and Delta variants, with our data suggesting how the strength of its 14-3-3 binding can be linked with the replicative fitness of the virus. Mechanisms Underlying WNT-mediated Priming of Human Embryonic Stem Cells Embryogenesis is guided by a limited set of signaling pathways dynamically expressed in different places. How a context dependent signaling response is generated has been a central question of developmental biology, which can now be addressed with in vitro models of human embryos that are derived from embryonic stem cells (hESCs) called gastruloids. Our previous work demonstrated that during early self-organization of gastruloids, cells chronicle signaling hierarchy. Only cells that have been exposed (primed) by WNT signaling can respond to subsequent Activin exposure and differentiate to mesendodermal (ME) fates. Here, we show that WNT priming does not alter SMAD2 binding nor its chromatin opening, but rather, acts by inducing the expression of the SMAD2 co-factor, EOMES. Expression of EOMES is sufficient to replace WNT upstream of Activin-mediated ME differentiation, thus unveiling the mechanistic basis for priming and cellular memory in early development. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Chromosome breaks in breast cancers occur near herpes tumor virus sequences and explain why cancer drugs stop working One explanation for why breast cancer has a relentless tendency to come back after treatment is that breast cancer phenomes are fluid, so it is difficult for therapy to target new phenotypes that arise. In breast cancer, viral interactions cause chromosome breakage and fusion, producing anaphase bridges containing two centromeres. Cell division then leads to more chromosome breaks, more mutations, and new cancer phenotypes. Analyses of public data from about 2100 breast cancers implicate Epstein-Barr virus (EBV or Human Herpes Virus 4) in the cycles that break chromosomes and produce anaphase bridges. EBV generates breakage cycles with highly fragmented chromosomes (chromothripsis) as an inherent feature. These episodes continually produce new cancer driver mutations. DNA at chromothripsis boundaries in breast cancers consistently matches EBV tumor variants. Breakpoints are often near known EBV binding sites, and breast cancer shares an EBV methylation signature with other known EBV cancers. Breast cancer breakpoints on all chromosomes cluster around the same positions as in cancers definitively associated with EBV infection (nasopharyngeal cancer and Burkitts lymphoma). The status of EBV in the microbiome and the presence of anaphase bridges are phenotypic markers of breast cancer that are not explicitly targeted by chemotherapy. The breast cancer phenome continually supplies new cancer driver genes that foster breast cancer recurrence.

SummaryBreaks in breast cancer chromosomes and in fragments of anaphase bridges occur mainly near regions that resemble Epstein-Barr virus (EBV) tumor variants

Extensive breaks are an inherent outcome of anaphase bridges and the reassembly of highly fragmented chromosomes continually generates new cancer driver mutations and new cancer phenotypes.

Treatment does not explicitly target the underlying breakage and reassembly cycles so breast cancer often comes back.

The breast cancer phenome is not fixed and can continuously generate new phenotypes

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC="FIGDIR/small/467751v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@6537cforg.highwire.dtl.DTLVardef@132fa50org.highwire.dtl.DTLVardef@1cfcb04org.highwire.dtl.DTLVardef@11979aa_HPS_FORMAT_FIGEXP  M_FIG C_FIG Compression for population genetic data through finite-state entropy We improve the efficiency of population genetic file formats and GWAS computation by leveraging the distribution of sample ordering in population-level genetic data. We identify conditional exchangeability of these data, recommending finite state entropy algorithms as an arithmetic code naturally suited to population genetic data. We show between 10% and 40% speed and size improvements over dictionary compression methods for population genetic data such as Zstd and Zlib in computation and and decompression tasks. We provide a prototype for genome-wide association study with finite state entropy compression demonstrating significant space saving and speed comparable to the state-of-the-art. An integrative approach leads to the discovery of a novel anti-leukemic peptide from human milk Chemotherapy in childhood leukemia is associated with late morbidity in leukemic survivors, while certain patient subsets are relatively resistant to standard chemotherapy. It is therefore important to identify new agents with sensitivity and selectivity towards leukemic cells, while having less systemic toxicity. Peptide-based therapeutics has gained much attention during the last few years. Here, we used an integrative workflow combining mass spectrometric peptide library construction, in silico anticancer peptide screening, and in vitro leukemic cell studies to discover a novel anti-leukemic peptide having 3+charges and alpha-helical structure, namely HMP-S7, from human breast milk. HMP-S7 showed cytotoxic activity against four distinct leukemic cell lines in a dose-dependent manner but had no effect on solid malignancies or representative normal cells. HMP-S7 induced leukemic cell death by penetrating the plasma membrane to enter the cytoplasm and cause leakage of lactate dehydrogenase, thus acting in a membranolytic manner. Importantly, HMP-S7 exhibited anti-leukemic effect against patient-derived leukemic cells ex vivo. In conclusion, HMP-S7 is a selective anti-leukemic peptide with promise which requires further validation in preclinical and clinical studies.

TeaserIn silico screening of naturally occurring human milk peptides discovers a new anticancer peptide that kills leukemic cells in vitro and ex vivo. Revisiting regulatory decoherence: Accounting for temporal bias in a co-expression analysis reveals novel candidates controlling environmental response Environment can alter the degree of phenotypic variation and covariation, potentially influencing evolutionary trajectories. However, environment-driven changes in phenotypic variation remain understudied. In an effort to exploit the abundance of RNASequencing data now available, an increasing number of ecological studies rely on population-level correlation to characterize the plastic response of the entire transcriptome and to identify environmentally responsive molecular pathways. These studies are fundamentally interested in identifying groups of genes that respond in concert to environmental shifts. We show that population-level differential co-expression exhibits biases when capturing changes of regulatory activity and strength in rice plants responding to elevated temperature. One possible cause of this bias is regulatory saturation, the observation that detectable co-variance between a regulator and its target may be low as their transcript abundances are induced. This phenomenon appears to be particularly acute for rapid-onset environmental stressors. However, our results suggest that temporal correlations may be a reliable means to detect transient regulatory activity following rapid onset environmental perturbations such as temperature stress. Such temporal bias is likely to confound the studies of phenotypic integration, where high-order organismal traits are hypothesized to be more integrated with strong correlation under stressful conditions, while recent transcriptome studies exhibited weaker coexpression between genes under stressful conditions. Collectively, our results point to the need to account for the nuances of molecular interactions and the possibly confounding effects that these can introduce into conventional approaches to study transcriptome datasets. 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.