Activity subspaces in medial prefrontal cortex distinguish states of the world Medial prefrontal cortex (mPfC) activity represents information about the state of the world, including present behaviour, such as decisions, and the immediate past, such as short-term memory. Unknown is whether information about different states of the world are represented in the same mPfC neural population and, if so, how they are kept distinct. To address this, we analyse here mPfC population activity of rats learning rules in a Y-maze, with self-initiated choice trials to an arm-end followed by a self-paced return during the inter-trial interval (ITI). We find that trial and ITI population activity from the same population fall into different low-dimensional subspaces. These subspaces encode different states of the world: multiple features of the task can be decoded from both trial and ITI activity, but the decoding axes for the same feature are roughly orthogonal between the two task phases, and the decodings are predominantly of features of the present during the trial but features of the preceding trial during the ITI. These subspace distinctions are carried forward into sleep, where population activity is preferentially reactivated in post-training sleep, but differently for activity from the trial and ITI subspaces. Our results suggest that the problem of interference when representing different states of the world is solved in mPfC by population activity occupying different subspaces for the world states, which can be independently decoded by downstream targets and independently addressed by upstream inputs.

Significance statementActivity in the medial prefrontal cortex plays a roles in representing the current and past states of the world. We show that during a maze task the activity of a single population in medial prefrontal cortex represents at least two different states of the world. These representations were sequential and sufficiently distinct that a downstream population could separately read out either state from that activity. Moreover, the activity representing different states is differently reactivated in sleep. Different world states can thus be represented in the same medial prefrontal cortex population, but in such a way that prevents potentially catastrophic interference between them.
Naturalistic viewing conditions can increase task engagement and aesthetic preference but have only minimal impact on EEG quality AO_SCPLOWBSTRACTC_SCPLOWFree gaze and moving images are typically avoided in EEG experiments due to the expected generation of artifacts and noise. Yet for a growing number of research questions, loosening these rigorous restrictions would be beneficial. Among these is research on visual aesthetic experiences, which often involve open-ended exploration of highly variable stimuli. Here we systematically compare the effect of conservative vs. more liberal experimental settings on various measures of behavior, brain activity and physiology in an aesthetic rating task. Our primary aim was to assess EEG signal quality. 43 participants either maintained fixation or were allowed to gaze freely, and viewed either static images or dynamic (video) stimuli consisting of dance performances or nature scenes. A passive auditory background task (auditory steady-state response; ASSR) was added as a proxy measure for overall EEG recording quality. We recorded EEG, ECG and eyetracking data, and participants rated their aesthetic preference and state of boredom on each trial. Whereas both behavioral ratings and gaze behavior were affected by task and stimulus manipulations, EEG SNR was barely affected and generally robust across all conditions, despite only minimal preprocessing and no trial rejection. In particular, we show that using video stimuli does not necessarily result in lower EEG quality and can, on the contrary, significantly reduce eye movements while increasing both the participants aesthetic response and general task engagement. We see these as encouraging results indicating that - at least in the lab - more liberal experimental conditions can be adopted without significant loss of signal quality.

HighlightsO_LIWe assess trade-offs between EEG quality and behavior for common task constraints
C_LIO_LIInvestigated constraints: fixation task vs. free gaze, and video vs. static stimuli
C_LIO_LIMeasures: EEG quality, aesthetic preference, task engagement, gaze and heart rate
C_LIO_LIVideo stimuli reduce eye movements, increase engagement and do not affect EEG SNR
C_LIO_LIFixation task only slightly increases SNR and does not influence ratings
C_LI
Second Heart Field-derived Cells Contribute to Angiotensin II-mediated Ascending Aortopathies BackgroundThe ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies.

MethodsAscending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry assisted proteomics, and molecular features of SHF-derived cells were determined by single cell transcriptomic analyses. Genetic deletion of either low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-{beta} receptor 2 (Tgfbr2) in SHF- derived cells was conducted to examine the impact of SHF-derived cells on vascular integrity.

ResultsPathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas following AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion, prior to overt pathology, evoked downregulation of SMC proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single cell transcriptomics results identified plasminogen activator inhibitor 1 (PAI1) as the most increased protein in SHF-derived SMCs and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies.

ConclusionSHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and TGF-{beta} signaling associated with increases of aortic PAI1.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/930917v6_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@185e3d9org.highwire.dtl.DTLVardef@131d702org.highwire.dtl.DTLVardef@11afa42org.highwire.dtl.DTLVardef@242786_HPS_FORMAT_FIGEXP  M_FIG C_FIG Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABS- SHF-derived SMCs and fibroblasts associate with AngII-induced aortic pathologies.
- AngII induces a distinct fibroblast sub-cluster that is less abundant for mRNAs related to major extracellular components and TGF{beta} ligands and receptors, but more abundant for proliferative genes.
- TGFBR2 deletion in SHF-derived cells are embryonic lethal with significant dilatation of the outflow tract in mice.
- SHF-specific deletion of LRP1 leads to aortic pathologies in mice, supporting the importance of SHF-derived cells in maintaining ascending aortic wall integrity.


What are the clinical implications?- Heterogeneity of the embryonic origins of SMCs and fibroblasts contributes to complex mechanisms of vasculopathy formation, which should be considered when investigating the pathogenesis of thoracic aortopathies. Unifying Transcriptome Regulation and Cellular Operational Efficiency: Application of the Locality and Caching Principles via a Cell-to-Computer Analogy Gene expression is time-consuming, and the delay from transcription activation to produced proteins is sequentially longer from bacteria to yeast and to humans. How human cells overcome the delay and attain operational efficiency, i.e., quick proteomic response to signals, is not well understood. The computer has endured the same system latency issue due to much slower information retrieval (hard drive (HD) to memory and to central processing unit (CPU)) than CPU execution, and mitigated it via efficient memory management, namely, the spatiotemporal locality principles that control specialized user programs and the permanent caching of core system functions - the operating system (OS) kernel. In this study, we unified gene expression and HD-memory-CPU information flow as instances of the Shannon information theory, that support the respective system operations and both consist of three components: information storage, the execution/decoding step, and the channel for the dynamic storage-to-execution information flow; the gene expression machinery and their regulators, and the OS kernel, were deemed as the respective channels. This abstraction prompted a multi-omic comparative analysis, leading to three observations. First, the temporal locality principle explains the mRNA stabilization-by-translation regulatory mechanism and controls specialized cellular functions. Second, the caching principle explains cytoplasmic mRNA sequestration and the defiance of the locality principle by highly sequestered mRNAs. Third, strikingly, in both systems, the caching principle controls the information channels; similar to permanent caching of OS kernel, basic gene expression machinery and their regulators are the top most sequestered mRNAs. In short, the locality and the caching principles act in the cells to control specialized and core cellular functions, respectively. The results close the knowledge gap between, and thus unify, transcriptome regulation and cellular operational latency mitigation. SARS-CoV-2 Can Infect Human Embryos The spread of SARS-CoV-2 has led to a devastating pandemic, with infections resulting in a range of symptoms collectively known as COVID-19. The full repertoire of human tissues and organs susceptible to infection is an area of active investigation, and some studies have implicated the reproductive system. The effects of COVID-19 on human reproduction remain poorly understood, and particularly the impact on early embryogenesis and establishment of a pregnancy are not known. In this work, we explore the susceptibility of early human embryos to SARS-CoV-2 infection. We note that ACE2 and TMPRSS2, two canonical cell entry factors for SARS-CoV-2, are co-expressed in cells of the trophectoderm in blastocyst-stage preimplantation embryos. Using fluorescent reporter virions pseudotyped with Spike (S) glycoprotein from SARS-CoV-2, we observe robust infection of trophectoderm cells, and this permissiveness could be attenuated with blocking antibodies targeting S or ACE2. When exposing human blastocysts to the live, fully infectious SARS-CoV-2, we detected cases of infection that compromised embryo health. Therefore, we identify a new human target tissue for SARS-CoV-2 with potential medical implications for reproductive health during the COVID-19 pandemic and its aftermath. Deep learning tools and modeling to estimate the temporal expression of cell cycle proteins from 2D still images Automatic characterization of fluorescent labeling in intact mammalian tissues remains a challenge due to the lack of quantifying techniques capable of segregating densely packed nuclei and intricate tissue patterns. Here, we describe a powerful deep learning-based approach that couples remarkably precise nuclear segmentation with quantitation of fluorescent labeling intensity within segmented nuclei, and then apply it to the analysis of cell cycle dependent protein concentration in mouse tissues using 2D fluorescent still images. First, several existing deep learning-based methods were evaluated to accurately segment nuclei using different imaging modalities with a small training dataset. Next, we developed a deep learning-based approach to identify and measure fluorescent labels within segmented nuclei, and created an ImageJ plugin to allow for efficient manual correction of nuclear segmentation and label identification. Lastly, using fluorescence intensity as a readout for protein concentration, a three-step global estimation method was applied to the characterization of the cell cycle dependent expression of E2F proteins in the developing mouse intestine. Quantifying the potential for red blood cell β-adrenergic sodium-proton exchangers to protect oxygen transport in hypoxic and hypercapnic white seabass White seabass (Atractoscion nobilis) are increasingly experiencing periods of low oxygen (O2; hypoxia) and high carbon dioxide (CO2, hypercapnia) due to climate change and eutrophication of the coastal waters of California. Hemoglobin (Hb) is the principal O2 carrier in the blood and in many teleost fishes Hb-O2 binding is compromised at low pH; however, the red blood cells (RBC) of some species regulate intracellular pH with adrenergically-stimulated sodium-proton-exchangers ({beta}-NHE). We hypothesized that RBC {beta}-NHEs in white seabass are an important mechanism that can protect the blood O2-carrying capacity during hypoxia and hypercapnia. We determined the O2-binding characteristics of white seabass blood, the response of RBCs to adrenergic stimulation, and quantified the protective effect of {beta}-NHE activity on Hb-O2 saturation. White seabass had typical teleost Hb characteristics, with a moderate O2 affinity (PO2 at half-saturation; P50 2.9 kPa) that was highly pH-sensitive (Bohr coefficient -0.92; Root effect 52%). The presence of RBC {beta}-NHEs was confirmed by functional, molecular and bioinformatic data and super-resolution imaging revealed, for the first time, the subcellular location of {beta}-NHE protein in vesicle-like structures and on the RBC membrane, and its translocation after adrenergic stimulation. The activation of RBC {beta}-NHEs increased Hb-O2 saturation by [~]8% in normoxia at 1 kPa PCO2, and by up to 20% in hypoxia. Our results confirm that RBC {beta}-NHE activity in white seabass has great potential to protect arterial O2 transport in environmentally relevant conditions of hypoxia and hypercapnia, but also reveal a potential vulnerability of fish to combinations of these stressors. 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. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Discoidin Domain Receptor 2 regulates AT1R expression in Angiotensin II-stimulated cardiac fibroblasts via fibronectin-dependent Integrin-β1 signaling Recent reports on the cardioprotective effects of fibronectin inhibition following myocardial injury suggest a largely unexplored role for the extracellular matrix (ECM) glycoprotein in cardiac fibroblast function. We probed the molecular regulation and functional implications of fibronectin gene expression in cardiac fibroblasts exposed to Angiotensin II, a major pro-fibrotic factor in the myocardium. Using gene knockdown and over-expression approaches, western blotting and promoter pull-down assay, we show that collagen type I-activated Discoidin Domain Receptor 2 (DDR2) mediates Angiotensin II-stimulated transcriptional up-regulation of fibronectin by Yes-activated Protein in cardiac fibroblasts. Further, siRNA-mediated fibronectin knockdown attenuated Angiotensin II-stimulated expression of collagen type I and anti-apoptotic cIAP2, and enhanced susceptibility to apoptosis. Importantly, an obligate role for fibronectin was observed in Angiotensin II-stimulated expression of AT1R, the Angiotensin II receptor, which would link ECM signaling and Angiotensin II signaling in cardiac fibroblasts. Moreover, conditioned medium from DDR2- or fibronectin-silenced cardiac fibroblasts reduced AT1R expression in H9c2 cardiomyoblasts. The regulatory role of fibronectin in Angiotensin II-stimulated cIAP2, collagen type I and AT1R expression was mediated by Integrin-{beta}1-integrin-linked kinase signaling. In vivo, we observed modestly reduced basal levels of AT1R in DDR2-null mouse myocardium, associated with the previously reported reduction in myocardial Integrin-{beta}1 levels. The role of fibronectin, downstream of DDR2, could be a critical determinant of cardiac fibroblast-mediated wound healing following myocardial injury. In summary, our findings suggest a complex mechanism of regulation of cardiac fibroblast function involving two major extracellular matrix proteins, collagen type I and fibronectin, and their receptors, DDR2 and Integrin-{beta}1. Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing The Oxford Nanopore (ONT) platform provides portable and rapid genome sequencing, and its ability to natively profile DNA methylation without complex sample processing is attractive for clinical sequencing. We recently demonstrated ONT shallow whole-genome sequencing to detect copy number alterations (CNA) from the circulating tumor DNA (ctDNA) of cancer patients. Here, we show that cell-type and cancer-specific methylation changes can also be detected, as well as cancer-associated fragmentation signatures. This feasibility study suggests that ONT shallow WGS could be a powerful tool for liquid biopsy, especially real-time medical applications. A potent human monoclonal antibody with pan-neutralizing activities directly dislocates S trimer of SARS-CoV-2 through binding both up and down forms of RBD The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). The neutralizing monoclonal antibodies (mAbs) targeting the receptor binding domain (RBD) of SARS-CoV-2 are among the most promising strategies to prevent and treat COVID-19. However, SARS-CoV-2 variants of concern (VOCs) profoundly reduced the efficacies of most of mAbs and vaccines approved for clinical use. Herein, we demonstrated mAb 35B5 efficiently neutralizes both wild-type (WT) SARS-CoV-2 and VOCs, including B.1.617.2 (delta) variant, in vitro and in vivo. Cryo-electron microscopy (cryo-EM) revealed that 35B5 neutralizes SARS-CoV-2 by targeting a unique epitope that avoids the prevailing mutation sites on RBD identified in circulating VOCs, providing the molecular basis for its pan-neutralizing efficacy. The 35B5-binding epitope could also be exploited for the rational design of a universal SARS-CoV-2 vaccine. Swine H1N1 influenza virus variants with enhanced polymerase activity and HA stability promote airborne transmission in ferrets Understanding how animal influenza A viruses (IAVs) acquire airborne transmissibility in humans and ferrets is needed to prepare for and respond to pandemics. Here, we investigated in ferrets the replication and transmission of swine H1N1 isolates P4 and G15, whose majority population had decreased polymerase activity and poor HA stability, respectively. For both isolates, a minor variant was selected and transmitted in ferrets. Polymerase-enhancing variant PA-S321 airborne-transmitted and propagated in one ferret. HA-stabilizing variant HA1-S210 was selected in all G15-inoculated ferrets and was transmitted by contact and airborne routes. With an efficient polymerase and a stable HA, the purified minor variant G15-HA1-S210 had earlier and higher peak titers in inoculated ferrets and was recovered at a higher frequency after airborne transmission than P4 and G15. Overall, HA stabilization played a more prominent role than polymerase enhancement in the replication and transmission of these viruses in ferrets. The results suggest pandemic risk-assessment studies may benefit from deep sequencing to identify minor variants with human-adapted traits.

IMPORTANCEDiverse IAVs circulate in animals, yet few acquire the viral traits needed to start a human pandemic. A stabilized HA and mammalian-adapted polymerase have been shown to promote the adaptation of IAVs to humans and ferrets (the gold-standard model for IAV replication, pathogenicity, and transmissibility). Here, we used swine IAV isolates of the gamma lineage a model to investigate the importance of HA stability and polymerase activity in promoting replication and transmission in ferrets. These are emerging viruses that bind to both -2,6- and -2,3-linked receptors. Using isolates containing mixed populations, a stabilized HA was selected within days in inoculated ferrets. An enhanced polymerase was also selected and propagated after airborne transmission to a ferret. Thus, HA stabilization was a stricter requirement, yet both traits promoted transmissibility. Knowing the viral traits needed for pandemic potential, and the relative importance of each, will help identify emerging viruses of greatest concern. Dynamic Phosphorylation of RGS Provides Spatial Regulation of MAP Kinase And Promotes Completion of Cytokinesis during the Yeast Pheromone Response Yeast use a G-protein coupled receptor (GPCR) signaling pathway to detect mating pheromone, arrest in G1, and direct polarized growth towards the potential mating partner. The primary negative regulator of this pathway is the regulator of G-protein signaling (RGS), Sst2, which induces G GTPase activity and subsequent inactivation of all downstream signaling including a MAPK cascade. The MAPK Fus3 phosphorylates the RGS in response to pheromone, but the role of this modification is unknown. We set out to examine the role of RGS phosphorylation during the pheromone response. We found that RGS phosphorylation peaks early in the pheromone response and diminishes RGS localization to the polarity site and focuses MAPK complexes there. At later time points, RGS is predominantly unphosphorylated, which promotes RGS localization to the polar cap and broadens the distribution of MAPK complexes relative to the Cdc42 polarity machinery. Surprisingly, we found that phosphorylation of the RGS is required for the completion of cytokinesis prior to pheromone induced growth. The completion of cytokinesis in the presence of pheromone is promoted by the formin Bnr1 and the kelch-repeat protein, Kel1, both proteins previously found to interact with the RGS. Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Force correction analysis method for derivation of multidimensional free energy landscapes from adaptively-biased replica simulations A methodology is proposed for the calculation of multidimensional free-energy landscapes of molecular systems, based on analysis of multiple Molecular Dynamics trajectories wherein adaptive biases have been applied to enhance the sampling of different collective variables. In this approach, which we refer to as Force Correction Analysis Method (FCAM), local averages of the total and biasing forces are evaluated post-hoc, and the latter are subtracted from the former to obtain unbiased estimates of the mean force across collective-variable space. Multidimensional free-energy surfaces and minimum free-energy pathways are then derived from integration of the mean force landscape through kinetic Monte Carlo algorithm. To evaluate the proposed method, a series of numerical tests and comparisons with existing approaches were carried out for small molecules, peptides, and proteins, based on all-atom trajectories generated with standard, concurrent and replica-exchange Metadynamics in collective-variable spaces ranging from one- to six-dimensional. The tests confirm the correctness of the FCAM formulation and demonstrate that calculated mean forces and free energies converge rapidly and accurately, outperforming other methods used to unbias this kind of simulation data.



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C_FIG A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found allelic imbalances in the expression of PIK3CA in normal breast tissue and mapped a germline candidate regulatory variant. An imbalance was also frequently observed in the expression of the missense mutant and wild-type PIK3CA alleles in breast tumors from METABRIC and TCGA projects. Moreover, although 60% of tumors preferentially expressed the mutant allele, 10% did preferentially express the wild-type allele. Mechanistically, we show that these imbalances are more frequently due to regulatory variants in cis than altered copy-number and predict that somatic variants have a more significant role than germline ones. We further found that imbalanced allelic expression between mutant and wild-type alleles due to cis-regulatory variants associated with poor prognosis (p=0.0081).

Interestingly, ER+, PR+, and Her2- tumors expressing very low levels of the mutant allele had the poorest prognosis (DSS <7.5yrs for ER+ and PR+ tumors and <5yrs for Her2- tumors). Hence, our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying this cohort of low mutant allele expressing patients of poorer prognosis, who will unlikely benefit from PI3K inhibitors. Furthermore, our work establishes a new model of differential regulation of critical cancer-promoting genes. Genome-wide association study of musical beat synchronization demonstrates high polygenicity Moving in synchrony to the beat is a fundamental component of musicality. Here, we conducted a genome-wide association study (GWAS) to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with sixty-nine loci reaching genome-wide significance (p<5x10-8) and SNP-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues, and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central nervous system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through internet-based experiments) and of the GWAS (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed, and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations. Circadian-period variation underlies the local adaptation of photoperiodism in the short-day plant Lemna aequinoctialis. Phenotypic variation is the basis for trait adaptation via evolutionary selection.1, 2, 3 However, the driving forces behind the quantitative trait variations remain unclear owing to their complexity at the molecular level.4, 5, 6 This study focused on the natural variation of the free-running period (FRP) of the circadian clock because FRP is a determining factor of the internal clock phase (chronotype), which is responsible for physiological timing during a day.7 Although natural variations in FRP have been widely reported,8, 10, 11 few studies have shown the association between FRP and adaptive temporal traits. As a clock-dependent physiological process, photoperiodism is a typical target of local adaptation.12, 13 Lemna aequinoctialis in Japan is a paddy-field duckweed exhibiting a latitudinal cline of critical day-lengths (CDLs) for short-day flowering.14 To investigate the relationship between FRP and CDL, we collected 72 strains of L. aequinoctialis within a latitudinal range between 31.5{degrees}N to 43.8{degrees}N. We found a significant correlation (P = 7.5E-8) between FRPs and locally adaptive CDLs, confirming that the variation in FRP-dependent chronotypes underlies geographically differentiated photoperiodism. Diel transcriptome analysis revealed that the induction timing of a florigen gene is key for connecting chronotypes to photoperiodism at the molecular level. Based on these results, we propose a fundamental rule concerning the "chronotype effect" in evolution: the variation of FRP functions as a resource for the variation of temporal traits. This study highlights the adaptive significance of FRP variation and provides a reason for the maintenance of FRP variation in natural populations. Superinfection exclusion: a viral strategy with short-term benefits and long-term drawbacks Viral superinfection occurs when multiple viral particles subsequently infect the same host. In nature, several viral species are found to have evolved diverse mechanisms to prevent superinfection (superinfection exclusion) but how this strategic choice impacts the fate of mutations in the viral population remains unclear. Using stochastic simulations, we find that genetic drift is suppressed when superinfection occurs, thus facilitating the fixation of beneficial mutations and the removal of deleterious ones. Interestingly, we also find that the competitive (dis)advantage associated with variations in life history parameters is not necessarily captured by the viral growth rate for either infection strategy. Putting these together, we then show that a mutant with superinfection exclusion will easily overtake a superinfecting population even if the latter has a much higher growth rate. Our findings suggest that while superinfection exclusion can negatively impact the long-term adaptation of a viral population, in the short-term it is ultimately a winning strategy.

Author summaryViral social behaviour has recently been receiving increasing attention in the context of ecological and evolutionary dynamics of viral populations. One fascinating and still relatively poorly understood example is superinfection or co-infection, which occur when multiple viruses infect the same host. Among bacteriophages, a wide range of mechanisms have been discovered that enable phage to prevent superinfection (superinfection exclusion) even at the cost of using precious resources for this purpose. What is the evolutionary impact of this strategic choice and why do so many phages exhibit this behaviour? Here, we conduct an extensive simulation study of a phage population to address this question. In particular, we investigate the fate of viral mutations arising in an environment with a constant supply of bacterial hosts designed to mimic a "turbidostat," as these are increasingly being used in laboratory evolution experiments. Our results show that allowing superinfection in the long-term yields a population which is more capable of adapting to changes in the environment. However, when in direct competition, mutants capable of preventing superinfection experience a very large advantage over their superinfecting counterparts, even if this ability comes at a significant cost to their growth rate. This indicates that while preventing superinfection can negatively impact the long-term prospects of a viral population, in the short-term it is ultimately a winning strategy. Protective host-dependent antagonism among 	Pseudomonas in the Arabidopsis phyllosphere The plant microbiome is a rich biotic environment, comprising numerous taxa. The community structure of these colonizers is constrained by multiple factors, including host-microbe and microbe-microbe interactions, as well as the interplay between the two. While much can be learned from pairwise relationships between individual hosts and microbes, or individual microbes with themselves, the ensemble of interrelations between the host and microbial consortia may lead to different outcomes that are not easily predicted from the individual interactions. Their study can thus provide new insights into the complex relationship between plants and microbes. Of particular importance is how strain-specific such plant-microbe-microbe interactions are, and how they eventually affect plant health. Here, we test strain-level interactions in the phyllosphere between groups of co-existing commensal and pathogenic Pseudomonas among each other and with A. thaliana, by employing synthetic communities of genome-barcoded isolates. We found that commensal Pseudomonas prompted a host response leading to a selective inhibition of a specific pathogenic lineage, resulting in plant protection. The extent of plant protection, however, was dependent on plant genotype, indicating that these effects are host-mediated. There were similar genotype-specific effects on the microbe side, as we could pinpoint an individual Pseudomonas isolate as the predominant cause for this differential interaction. Collectively, our work highlights how within-species genetic differences on both the host and microbe side can have profound effects on host-microbe-microbe dynamics. The paradigm that we have established provides a platform for the study of host-dependent microbe-microbe competition and cooperation in the A. thaliana-Pseudomonas system. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Environment dependent benefits of inter-individual variation in honey bee recruitment Inter-individual differences in behaviour within the members of a social group can affect the groups productivity. In eusocial insects, individual differences amongst workers in a colony play a central role division of labour and task allocation. Extensive empirical and theoretical work has highlighted variation in response thresholds as a proximate mechanism underlying individual behavioural differences and hence division of labour. However, other response parameters, like response probability and intensity, can affect these differences. In this study, we first extended a previously published agent-based model on honey bee foraging to understand the relative importance of response (dance) probability and response (dance) intensity in the task of recruitment. Comparing variation obtained from the simulations with previously published empirical data, we found that response intensity plays a more important role than probability in producing consistent inter-individual differences in recruitment behaviour. We then explored the benefits provided by this individual variation in recruitment behaviour to the colonys collective foraging effort under different environmental conditions. Our results revealed that individual variation leads to a greater energetic yield per forager, but only when food is abundant. Our study highlights the need to consider all response parameters while studying division of labour and adds to the growing body of evidence linking individual variation in behavioural responses to the success of social groups. Universal protein misfolding intermediates can bypass the proteostasis network and remain soluble and less-functional Misfolded protein conformations with decreased functionality can bypass the proteostasis machinery and remain soluble in vivo. This is an unexpected phenomenon as several cellular quality control mechanisms have evolved to rid cells of misfolded proteins. Three questions, then, are: how is it structurally possible for long-lived, soluble, misfolded proteins to bypass the proteostasis machinery and processes? How widespread are these soluble, misfolded states across the proteome? And how long do they persist for? Here, we address these questions using coarse-grain molecular dynamics simulations of the synthesis, termination, and post-translational dynamics of a representative set of cytosolic E. coli proteins. We predict that half of all proteins exhibit subpopulations of misfolded conformations that are likely to bypass molecular chaperones, avoid aggregation, and not be rapidly degraded. These misfolded states may persist for months or longer for some proteins. Structurally characterizing these misfolded states, we observe they have a large amount of native structure, but also contain localized misfolded regions from non-native changes in entanglement, in which a protein segment threads through a loop formed by another portion of the protein that is not found in the native state. The surface properties of these misfolded states are native like, suggesting they may bypass the proteostasis machinery and its regulatory processes to remain soluble, while their entanglements make these states long-lived kinetic traps, as disentanglement requires unfolding of already folded portions of the protein. In terms of function, we predict that one-third of proteins have subpopulations that misfold into less-functional states that have structurally perturbed functional sites yet remain soluble. Data from limited-proteolysis mass spectrometry experiments, which interrogate the misfolded conformations populated by proteins upon unfolding and refolding, are consistent with the structural changes seen in the entangled states of glycerol-3-phosphate dehydrogenase upon misfolding. These results provide an explanation for how proteins can misfold into soluble conformations with reduced functionality that can bypass cellular quality controls, and indicate, unexpectedly, this may be a wide-spread phenomenon in proteomes. Such entanglements are observed in many native structures, suggesting the non-native entanglements we observe are plausible. More broadly, these near-native entangled structures suggest a hypothesis for how synonymous mutations can modulate downstream protein structure and function, with these mutations partitioning nascent proteins between these kinetically trapped states.