Cognitive processing of a common stimulus synchronizes brains, hearts, and eyes Neural, physiological and behavioral signals synchronize between human subjects in a variety of settings. Multiple hypotheses have been proposed to explain this interpersonal synchrony, but there is no clarity under which conditions it arises, for which signals, or whether there is a common underlying mechanism. We hypothesized that similar cognitive processing of a shared stimulus is the source of synchrony between subjects, measured here as inter-subject correlation. To test this we presented informative videos to participants in an attentive and distracted condition and subsequently measured information recall. Inter-subject correlation was observed for electro-encephalography, gaze position, pupil size and heart rate, but not respiration and head movements. The strength of correlation was co-modulated in the different signals, changed with attentional state, and predicted subsequent recall of information presented in the videos. There was robust within-subject coupling between brain, heart and eyes, but not respiration or head movements. The results suggest that inter-subject correlation is the result of similar cognitive processing and thus emerges only for those signals that exhibit a robust brain-body connection. While physiological and behavioral fluctuations may be driven by multiple features of the stimulus, correlation with other individuals is co-modulated by the level of attentional engagement with the stimulus.
Differences In The Effects On Human Focus Of Music Playlists And Personalized Soundscapes, As Measured By Brain Signals. The goal of this study was to investigate the effect of sounds on human focus and to identify the properties that contribute most to increasing and decreasing focus in people within their natural, everyday environment. Participants (N=62, 18-65y) performed various tasks on a tablet computer while listening to either no background sounds (silence), popular music playlists designed to increase focus (pre-recorded songs in a particular sequence), or engineered soundscapes that were personalized to individual listeners (digital audio composed in real-time based on input parameters such as heart rate, time of day, location, etc.). Sounds were delivered to participants through headphones while simultaneously their brain signals were recorded by a portable electroencephalography headband. Participants completed four one-hour long sessions at home during which different sound content played continuously. Using brain decoding technology, we obtained individual participant focus levels over time and used this data to analyze the effects of various properties of sound. We found that while participants were working, personalized soundscapes increased their focus significantly above silence (p=0.008), while music playlists did not have a significant effect. For the young adult demographic (18-36y), all sound content tested was significantly better than silence at producing focus (p=0.001-0.009). Personalized soundscapes increased focus the most relative to silence, but playlists of pre-recorded songs also increased focus significantly during specific time intervals. Ultimately we found that it is possible to accurately predict human focus levels that will be experienced in response to sounds a priori based on the sounds physical properties. We then applied this finding to compare between music genres and revealed that classical music, engineered soundscapes, and natural sounds were the best genres for increasing focus, while pop and hip-hop were the worst. These insights can enable human and artificial intelligence composers to produce increases or decreases in listener focus with high temporal (millisecond) precision. Future research will include real-time adaptation of sound libraries for other functional objectives beyond affecting focus, such as affecting listener enjoyment, stress, and memory.
Non-Newtonian Blood Rheology Impacts Left Atrial Stasis in Patient-Specific Simulations The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects can be subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered in calculating patient-specific blood stasis indices by computational fluid dynamics. Sequence Determines the Switch in the Fibril Forming Regions in the Low-Complexity FUS Protein and Its Variants Residues spanning distinct regions of the low-complexity domain of the RNA-binding protein, Fused in Sarcoma (FUS-LC), form fibril structures with different core morphologies. NMR experiments show that the 214 residue FUS-LC forms a fibril with an S-bend (core-1, residues 39-95), while the rest of the protein is disordered. In contrast, the fibrils of the C-terminal variant (FUS-LC-C; residues 111-214) has a U-bend topology (core-2, residues 112-150). Absence of the U-bend in FUS-LC implies that the two fibril cores do not coexist. Computer simulations show that these perplexing findings could be understood in terms of the population of sparsely-populated fibril-like excited states in the monomer. The propensity to form core-1 is higher compared to core-2. We predict that core-2 forms only in truncated variants that do not contain the core-1 sequence. At the monomer level, sequence-dependent enthalpic effects determine the relative stabilities of the core-1 and core-2 topologies.

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org.highwire.dtl.DTLVardef@f81959org.highwire.dtl.DTLVardef@4859f3org.highwire.dtl.DTLVardef@96aecorg.highwire.dtl.DTLVardef@4ab94e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. Honeybee cognition as a tool for scientific engagement In addition to the crowdsourcing of experimental data, citizen science, and scientific engagement more broadly, serve as a bridge between researchers and the wider community. This serves to foster a greater understanding of the scientific method and science-based solutions generally. Apis mellifera (honeybees) are a well-established model for the study of learning and cognition and can serve as an engaging outreach system for this wider community. Here, we developed and implemented a protocol using well established honeybee conditioning protocols to safely study the effects of caffeine and dopamine on learning performance. Using this protocol, a group of high-school aged students as part of the Ryukyu Girls program demonstrated that caffeine, but not dopamine, significantly reduced the number of trials required for a successful conditioning response. This allowed these students to explore the scientific method in a relatable and engaging way.

Simple SummaryGlobal scientific literacy can be improved through widespread and effective community engagement by researchers. We propose Apis mellifera (honeybee) as an public engagement tool due to widespread awareness of colony collapse and the bees importance in food production. Moreover, their cognitive abilities make for engaging experiments. Their relative ease of cultivation means that studies can be performed cost-effectively, especially when partnering with local aperists. Using a proxy for honeybee learning, a group of non-specialist high-school-aged participants obtained data suggesting that caffeine, but not dopamine, improved learning. This hands-on experience facilitated student understanding of the scientific method, factors that shape learning and the importance of learning for hive health. Where there's smoke, there's fuel: dynamic vegetation data improve predictions of wildfire hazard in the Great Basin Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (>405 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-one-year-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without 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. 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. The cell growth cycle in budding yeast: testing hypotheses. Metabolic oscillation percolate throughout cellular physiology. The transcriptome oscillates between gene cohorts encoding for biosynthesis and growth, and for catabolism and stress response. However, long protein half-lives dampen effects on protein abundance, and the function of periodic transcription remains elusive. To test three prevailing hypotheses, we performed RNA-seq analysis during a dynamic state of the system, just preceding a bifurcation of system dynamics to a longer period. A few enzymes with short protein half-live and high transcript abundance amplitude could play a direct role in metabolic dynamics (hypothesis H1), e.g., carbonic anhydrase, sulfate uptake and the glyoxylate cycle. Substantial changes in the relative duration of expression of the antagonistic cohorts precede the bifurcation, supporting the idea of a function in cellular resource allocation (H2). The pulse-width modulation model, a mathematical formulation of this idea, explains the dependence of the cycle period on the culture growth rate. This pulse-like model of cell growth provides a first theoretical framework, where the phenomenon is understood as a mechanism of cellular resource allocation and protein homeostasis. The universal temporal program of transcription encodes the spatial structure of the cell, and we further suggest a function in pattern formation of the growing cell (H3). 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. Analysis of science journalism reveals gender and regional disparities in coverage Science journalism is a critical way in which the public can remain informed and benefit from new scientific findings. Such journalism also shapes the publics view of the current state of scientific findings and legitimizes experts. Those covering science can only cite and quote a limited number of sources. Sources may be identified by the journalists research or by recommendations by other scientists. In both cases, biases may influence who is identified and ultimately included as an expert. To analyze possible biases in science journalism, we analyzed 22,001 non-research articles published by Nature. We chose to analyze Nature non-research articles since its research articles provide a natural comparator. Our analysis considered two possible sources of disparity: gender and name origin. To explore these sources of disparity, we extracted cited authors names as well as extracted names of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then used the extracted names to predict gender and name origin of the cited authors and speakers.

In order to appropriately quantify the level of difference, we must identify a suitable reference set for comparison. We chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. In our analysis, we found a skew towards male quotation in Nature science journalism-related articles. However, quotation is trending toward equal representation at a faster rate than first and last authorship in academic publishing. Interestingly, we found that the gender disparity in Nature quotes was column-dependent, with the "Career Features" column reaching gender parity. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin. This finding was observed both in extracted quotes and journal citations, but dampened in citations. A Substrate-triggered μ-Peroxodiiron(III) Intermediate in the 4-Chloro-L-Lysine-Fragmenting Heme-Oxygenase-like Diiron Oxidase (HDO) BesC: Substrate Dissociation from, and C4 Targeting by, the Intermediate The enzyme BesC from the {beta}-ethynyl-L-serine biosynthetic pathway in Streptomyces cattleya fragments 4-chloro-L-lysine (produced from L-Lysine by BesD) to ammonia, formaldehyde, and 4-chloro-L-allylglycine and can analogously fragment L-Lys itself. BesC belongs to the emerging family of O2-activating non-heme-diiron enzymes with the "heme-oxygenase-like" protein fold (HDOs). Here we show that binding of L-Lys or an analog triggers capture of O2 by the proteins diiron(II) cofactor to form a blue {micro}-peroxodiiron(III) intermediate analogous to those previously characterized in two other HDOs, the olefin-installing fatty acid decarboxylase, UndA, and the guanidino-N-oxygenase domain of SznF. The [~] 5- and [~] 30-fold faster decay of the intermediate in reactions with 4-thia-L-Lys and (4RS)-chloro-DL-lysine than in the reaction with L-Lys itself, and the primary deuterium kinetic isotope effects (D-KIEs) on decay of the intermediate and production of L-allylglycine in the reaction with 4,4,5,5-[2H]-L-Lys, imply that the peroxide intermediate or a successor complex with which it reversibly interconverts initiates the oxidative fragmentation by abstracting hydrogen from C4. Surprisingly, the sluggish substrate L-Lys can dissociate after triggering the intermediate to form, thereby allowing one of the better substrates to bind and react. Observed linkage between Fe(II) and substrate binding suggests that the triggering event involves a previously documented (in SznF) ordering of the dynamic HDO architecture that contributes one of the iron sites, a hypothesis consistent with the observation that the diiron(III) product cluster produced upon decay of the intermediate spontaneously degrades, as it has been shown to do in all other HDOs studied to date. 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. A chromosome-level genome assembly of a maize elite breeding line Dan340 The maize cultivar Dan340 is an excellent backbone inbred line of Luda Red Cob Group with several desirable characters, such as disease resistance, lodging resistance, high combining ability, wide adaptability and so on. In this study, we constructed a high-quality chromosome-level reference genome for Dan340 by combining PacBio long HiFi sequencing, Illumina short reads and chromosomal conformational capture (Hi-C) sequencing reads. The final assembly of Dan340 genome was 2,348.72 Mb, including 2,738 contigs and 2,315 scaffolds with a N50 of 41.49 Mb and 215.35 Mb, respectively. The percent of high quality Illumina reads mapped to the reference genome was up to 97.48%. The assembly of this genome will not only facilitate our understanding about intraspecific genome diversity in maize, but also provides a novel resource for maize breeding.

Key findingsO_LIThe final assembly of Dan340 genome was 2,348.72 Mb, including 2,738 contigs and 2,315 scaffolds with a N50 of 41.49 Mb and 215.35 Mb, respectively.
C_LIO_LIThe percent of reads mapped to the reference genome was up to 97.48%.
C_LIO_LIThe results showed that 96.84% of the plant single-copy orthologues were complete. Complete single-copy and multi copy genes accounted for 87.36% and 9.48% of the genes, respectively. Taken together, these results indicated that our Dan340 genome assembly presented high quality and coverage.
C_LI The integrity and assay performance of tissue mitochondrial DNA is considerably affected by choice of isolation method The integrity of mitochondrial DNA (mtDNA) isolated from solid tissues is critical for analyses such as long-range PCR, but is typically assessed under conditions that fail to provide information on the individual mtDNA strands. Using denaturing gel electrophoresis, we show that commonly-used isolation procedures generate mtDNA containing several single-strand breaks per strand. Through systematic comparison of DNA isolation methods, we identify a procedure yielding the highest integrity of mtDNA that we demonstrate displays improved performance in downstream assays. Our results highlight the importance of isolation method choice, and serve as a resource to researchers requiring high-quality mtDNA from solid tissues. Contrasting resistance and resilience to light variation of the coupled oxic and anoxic componentsof an experimental microbial ecosystem Understanding how microbial communities of aquatic ecosystems respond to environmental change remains a critical challenge in microbial ecology. In this study, we used phototrophic oxic-anoxic micro-ecosystems to understand how the functioning and diversity of aerobic and anaerobic lake analog communities is affected by light deprivation. Continuous measurements were performed to describe oxygen dynamics (mean/min/max/amplitude) and time-series of full-length 16S rRNA sequencing were used to quantify changes in alpha- and beta-diversity. In the top oxic layer, oxygen concentration decreased significantly under light deprivation, but showed resilience in mean, minimum and maximum after light conditions were restored. Only the amplitude of diurnal fluctuations in oxygen concentrations did not recover fully, and instead tended to remain lower in treated ecosystems. Alpha-diversity of the top oxic layer communities showed a delayed increase after light conditions were restored, and was not resilient. In contrast, alpha-diversity of the anoxic bottom layer communities increased due to the stressor, but was resilient. Community composition changed significantly during light deprivation, showed resilience in the oxic layer and lack of resilience in the anoxic layer. Alpha-diversity and the amplitude of oxygen within and among treatments were strongly correlated, suggesting that higher diversity could lead to less variable oxygen concentrations, or vice versa. Our experiment showed that light deprivation induces multifaceted responses of community function and structure, hence focusing on a single stability component could potentially be misleading. Adaptive Wild Introgression Mediate Temporal Wheat Root Water Influxes under Drought Stress through Plant-Atmospheric Interrelations Drought intensity as experienced by plants depends upon soil moisture status and atmospheric variables such as temperature, radiation, and air vapour pressure deficit (VPD). Although the role of shoot architecture with these edaphic and atmospheric factors is well-characterized, the extent to which shoot and root dynamic interactions as a continuum are controlled by genotypic variation is less known. Here, we targeted these interactions using a wild emmer introgression line (IL20) with a distinct drought-induced shift in the shoot-to-root ratio and its drought-sensitive recurrent parent Svevo. Using a gravimetric platform, we show that IL20 maintained higher root water influx and gas exchange under drought stress, which supported a greater growth. Interestingly, the advantage of IL20 in root water influx and transpiration was expressed earlier during the daily diurnal cycle under lower VPD and therefore supported higher transpiration efficiency. Application of structural equation model indicates that under drought, VPD and radiation are antagonistic to transpiration rate, whereas the root water influx operates as feedback for the higher atmospheric responsiveness of leaves. Collectively, our results suggest that a drought-induced shift in root-to-shoot ratio can improve plant water uptake potential in a short preferable time window determined by both water and atmospheric parameters. SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets Combinatorial therapies have been recently proposed to improve the efficacy of anticancer treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug combination datasets. Here, we report the major updates to the SynergyFinder R package for improved interpretation and annotation of drug combination screening results. Unlike the existing implementations, the updated SynergyFinder R package includes five main innovations. (1) We extend the mathematical models to higher-order drug combination data analysis and implement dimension reduction techniques for visualizing the synergy landscape. (2) We provide a statistical analysis of drug combination synergy and sensitivity with confidence intervals and P values. (3) We incorporate a synergy barometer to harmonize multiple synergy scoring methods to provide a consensus metric for synergy. (4) We evaluate drug combination synergy and sensitivity to provide an unbiased interpretation of the clinical potential. (5) We enable fast annotation of drugs and cell lines, including their chemical and target information. These annotations will improve the interpretation of the mechanisms of action of drug combinations. To facilitate the use of the R package within the drug discovery community, we also provide a web server at www.synergyfinderplus.org as a user-friendly interface to enable a more flexible and versatile analysis of drug combination data. Loss of Nuclear DNA Ligase III Reverts PARP Inhibitor Resistance in BRCA1/53BP1 Double-deficient Cells by Exposing ssDNA Gaps Inhibitors of poly(ADP-ribose) (PAR) polymerase (PARPi) have entered the clinic for the treatment of homologous recombination (HR)-deficient cancers. Despite the success of this approach, preclinical and clinical research with PARPi has revealed multiple resistance mechanisms, highlighting the need for identification of novel functional biomarkers and combination treatment strategies. Functional genetic screens performed in cells and organoids that acquired resistance to PARPi by loss of 53BP1 identified loss of LIG3 as an enhancer of PARPi toxicity in BRCA1-deficient cells. Enhancement of PARPi toxicity by LIG3 depletion is dependent on BRCA1 deficiency but independent of the loss of 53BP1 pathway. Mechanistically, we show that LIG3 loss promotes formation of MRE11-mediated post-replicative ssDNA gaps in BRCA1-deficient and BRCA1/53BP1 double-deficient cells exposed to PARPi, leading to an accumulation of chromosomal abnormalities. LIG3 depletion also enhances efficacy of PARPi against BRCA1-deficient mammary tumors in mice, suggesting LIG3 as a potential therapeutic target. Variation in Ubiquitin System Genes Creates Substrate-Specific Effects on Proteasomal Protein Degradation Ubiquitin-proteasome system (UPS) protein degradation regulates protein abundance and eliminates mis-folded and damaged proteins from eukaryotic cells. Variation in UPS activity influences numerous cellular and organismal phenotypes. However, to what extent such variation results from individual genetic differences is almost entirely unknown. Here, we developed a statistically powerful mapping approach to characterize the genetic basis of variation in UPS activity. Using the yeast Saccharomyces cerevisiae, we systematically mapped genetic influences on the N-end rule, a UPS pathway that recognizes N-degrons, degradation-promoting signals in protein N-termini. We identified 149 genomic loci that influence UPS activity across the complete set of N-degrons. Resolving four loci to individual causal nucleotides identified regulatory and missense variants in ubiquitin system genes whose products process (NTA1), recognize (UBR1 and DOA10), and ubiquitinate (UBC6) cellular proteins. Each of these genes contained multiple causal variants and several individual variants had substrate-specific effects on UPS activity. A cis-acting promoter variant that modulates UPS activity by altering UBR1 expression also alters the abundance of 36 proteins without affecting levels of the corresponding mRNAs. Our results demonstrate that natural genetic variation shapes the full sequence of molecular events in protein ubiquitination and implicate genetic influences on the UPS as a prominent source of post-translational variation in gene expression. Nuclear Progestin Receptor Mediated Linkage of Blood Coagulation and Ovulation Ovulation is a dramatic remodeling process that includes rupture of blood capillaries and clotting, but coagulation is not thought to directly regulate this process. Herein, we report remarkable increases of coagulation factors V (f5, [~]3145-fold) and tissue factor (f3a, [~]120-fold) in zebrafish ovarian follicle cells during ovulation. This increase was mediated through the nuclear progestin receptor (Pgr), which is essential for ovulation in zebrafish, and was totally abolished in ovarian follicular cells from pgr-/- mutants. In addition, promoter activities of f5 and f3a were significantly enhanced by progestin (DHP) via Pgr. Similar regulation of human F5 promoter activity was induced via human PGRB, suggesting a conserved mechanism. Site-directed mutagenesis of the zebrafish f5 promoter further demonstrated a direct regulation of coagulation factors via progestin response elements. Moreover, a stark increase of erythrocytes occurred in capillaries meshed in wildtype preovulatory follicles but was absent in pgr-/- mutants. Interestingly, anticoagulants significantly inhibited ovulation both in vitro and in vivo, respectively. Furthermore, reduced fecundity was observed in f5+/- female zebrafish. Taken together, our study provides plausible evidence for steroid regulation of coagulation factors, and a new hypothesis for blood clotting triggered ovulation in vertebrates. Stochastic effects during the establishment of β-lactam resistant E. colimutants indicate conditions for collective resistance For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing {beta}-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability. Lastly, we use the single-cell establishment probability to predict each strains MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays. 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. Optogenetic dissection of actomyosin-dependent mechanics underlying tissue fluidity Rapid epithelial tissue flows are essential to building and shaping developing embryos. However, it is not well understood how the mechanical properties of tissues and the forces driving them to flow are jointly regulated to accommodate rapid tissue remodeling. To dissect the roles of actomyosin in the mechanics of epithelial tissue flows, here we use two optogenetic tools, optoGEF and optoGAP, to manipulate Rho/Rho-kinase signaling and actomyosin contractility in the germband epithelium, which flows via convergent extension movements during Drosophila body axis elongation. The ability to perturb actomyosin in the tissue allows us to analyze the effects of actomyosin on cell rearrangements, tissue tensions, and tissue mechanical properties. We find that either optogenetic activation or deactivation of Rho1 signaling and actomyosin contractility at the apical surface of the germband disrupts cell rearrangements and tissue-level flows. Rho1 activation leads to poorly oriented rearrangements that are associated with a redistribution of myosin II from the junctional to the medial-apical domain, whereas Rho1 deactivation leads to fewer, slower cell rearrangements that are associated with decreased junctional and medial myosin. By probing mechanical tensions in the tissue using laser ablation and inferring tissue mechanical properties from cell packings, we find that actomyosin influences both the anisotropic forces that drive tissue flow and the mechanical properties of the tissue that resist flow, leading to complex relationships between actomyosin activity and tissue fluidity. Moreover, our results link the subcellular distribution of myosin II to tissue tension and cell packings, revealing how junctional and medial myosin have differential roles in promoting and orienting cell rearrangements during tissue flow. Implicating Gene and Cell Networks Responsible for Differential COVID-19 Host Responses via an Interactive Single Cell Web Portal Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/ COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.