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.
Nanoscale ligand density modulates gap junction intercellular communication of cell condensates during chondrogenesis To unveil the influence of cell-matrix adhesions in the establishment of gap junction intercellular communication (GJIC) during cell condensation in chondrogenesis.

Materials & MethodsPreviously developed nanopatterns of the cell adhesive ligand arginine-glycine-aspartic acid (RGD) were used as cell culture substrates to control cell adhesion at the nanoscale. We conducted in vitro chondrogenesis of mesenchymal stem cells on the nanopatterns. We evaluated cohesion and GJIC in cell condensates.

ResultsMechanical stability and GJIC are enhanced by a nanopattern configuration in which 90% of the surface area presents adhesion sites separated less than 70 nm, thus providing an onset for cell signaling.

ConclusionCell-matrix adhesions regulate GJIC of mesenchymal cell condensates during in vitro chondrogenesis from a threshold configuration at the nanoscale.
Limited selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes. Fatal COVID-19 ARDS associated with incomplete AEC1 differentiation from the transitional state without senescence or fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Non-invasive imaging of gene expression and protein secretion dynamics in living mice uncovers ectopic prothrombin expression as driver of thrombosis in cancer The topology of gene expression and protein localization is a crucial characteristic of life, where the spatiotemporal dynamic of secretory proteins instruct higher order organization, including the orchestration of developmental and adaptive programs. However tools to non-invasively interrogate the fate of secretory proteins in vivo are scarce. Here we introduce a genetic tagging strategy for in vivo imaging of the secretion and expression dynamics of secretory proteins in living animals. Applying this to a prototypical liver-derived secretory protein, we demonstrate that this approach, combined with optical in-vivo imaging, uncovers extrahepatic prothrombin expression in multiple novel anatomical sites (including testes, placenta, brain, kidney, heart and lymphatic system) and in emerging tumors, resulting in significant amounts of tumor-derived prothrombin in the blood with procoagulant properties. Syngeneic cell lines from this mouse model enable unravelling regulatory mechanisms in high resolution, and in a scalable format ex vivo. Beyond discovering new functions of proteins in a targeted manner, this model allows identifying rheostats in the cross-talk between gene expression and availability of a secretory protein. It is also a valuable resource for uncovering novel (tissue-specific) therapeutic vulnerabilities. Modeling predicts differences in CAR T cell signaling due to biological variability In recent decades, chimeric antigen receptors (CARs) have been successfully used to generate engineered T cells capable of recognizing and eliminating cancer cells. The structure of CARs frequently includes costimulatory domains, which enhance the T cell response upon antigen encounter. However, it is not fully known how the CAR co-stimulatory domains influence T cell activation in the presence of biological variability. In this work, we used mathematical modeling to elucidate how the inclusion of one such co-stimulatory molecule, CD28, impacts the response of a population of engineered T cells under different sources of variability. Particularly, our simulations demonstrate that CD28-bearing CARs mediate a faster and more consistent population response under both target antigen variability and kinetic rate variability. We identify kinetic parameters that have the most impact on mediating cell activation. Finally, based on our findings, we propose that enhancing the catalytic activity of lymphocyte-specific protein tyrosine kinase (LCK) can result in drastically reduced and more consistent response times among heterogeneous CAR T cell populations. Comparative Analysis of T Cell Spatial Proteomics and the Influence of HIV Expression As systems biology approaches to virology have become more tractable, highly studied viruses such as HIV can now be analyzed in new, unbiased ways, including spatial proteomics. We employed here a differential centrifugation protocol to fractionate Jurkat T cells for proteomic analysis by mass spectrometry; these cells contain inducible HIV-1 genomes, enabling us to look for changes in the spatial proteome induced by viral gene expression. Using these proteomics data, we evaluated the merits of several reported machine learning pipelines for classification of the spatial proteome and identification of protein translocations. From these analyses we found that classifier performance in this system was organelle-dependent, with Bayesian t-augmented Gaussian mixture modeling outperforming support vector machine (SVM) learning for mitochondrial and ER proteins, but underperforming on cytosolic, nuclear, and plasma membrane proteins by QSep analysis. We also observed a generally higher performance for protein translocation identification using a Bayesian model, BANDLE, on SVM-classified data. Comparative BANDLE analysis of cells induced to express the wild-type viral genome vs. cells induced to express a genome unable to express the accessory protein Nef identified known Nef-dependent interactors such as TCR signaling components and coatomer complex. Lastly, we found that SVM classification showed higher consistency and was less sensitive to HIV-dependent noise. These findings illustrate important considerations for studies of the spatial proteome following viral infection or viral gene expression and provide a reference for future studies of HIV-gene-dropout viruses. Mouse lemur, a new primate model to investigate cardiac pacemaker activity. BackgroundGray mouse lemurs (Microcebus murinus) are one of the smallest and most ancestral primates known. Their size falls in between that of mice and rats, and their genetic proximity to humans makes them an emerging model to study age-related neurodegeneration. Since Microcebus murinus replicates similar senescence processes of humans, it constitutes a useful model also for studying cardiovascular dysfunctions. However, its cardiac physiology is unknown. Thus, we investigated sinoatrial node (SAN) pacemaker activity of mouse lemurs, presenting the first characterization of heart automaticity in nonhuman primates.

Methods and ResultsWe recorded the heart automaticity in freely moving mouse lemurs and in their SAN tissues and pacemaker myocytes. Mouse lemurs have a heart rate (HR) in between those of mice and rats and a similar generation of electrical impulses in the SAN tissue. Conversely, their ventricular depolarization is more similar to large mammals. Mouse lemur SAN myocytes express the main pacemaker currents at densities similar to mice: the hyperpolarization-activated current (If) and the L-type (ICa,L) and T-type (ICa,T) calcium currents. Moreover, mouse lemur SAN myocytes display spontaneous ryanodine receptor (RyR)-dependent Ca2+ transients. Using muscle-derived stem cells (MDSCs) from the Microcebus murinus skeletal muscle, we also differentiated pacemaker-like (PML) cells showing spontaneous automaticity and expressing markers of native SAN myocytes (HCN4 and connexin-45).

ConclusionsIn conclusion, our characterization of heart automaticity in Microcebus murinus provides new opportunities for comparative cardio-physiology studies in primates and with humans, and for pharmacologic testing of molecules that could assist in modulating age-related dysfunctions of automaticity. Atrazine induced In vivo immunotoxicity in Bivalves Atrazine is ubiquitously used broad-spectrum herbicide to control the weeds in agriculture. The present study aimed to evaluate the acute toxicity and immunotoxicity of Atrazine in two ecologically and economically important bivalves. Acute toxicity of atrazine evaluated in triplicates by taking control and six experimental groups each comprising of 30 animals and treated with a range of atrazine from 2 PPM to 12 PPM for 96 hours. Mortalities were recorded for every 24 hours until 96 hours and data analyzed by one-way ANOVA and Dunnett T-test. The results indicated a significant increase in mortalities with increase in dose and time of exposure in both species. The values of LC50 were determined as 6.10 PPM and 4.90 PPM respectively for Perna viridis and Paphia malabarica. Furthermore, the immunotoxic potential of atrazine assessed by treating mussels and clams with the five sub-lethal doses of atrazine for 14 days and quantifying the viability of hemocytes by using simple yet reliable Tryphan blue exclusion assay. The results of the present study suggest atrazine-induced immunotoxicity by decreasing the number of viable hemocytes in bivalves. Hemocytes with phagocytic function are indispensable to confer innate immunity in bivalves, decreased viability of these cells leads to compromised immunity. This study is first of its kind to implicate atrazine with the immunotoxicity in bivalves. Naive human B cells engage the receptor binding domain of SARS-CoV-2, variants of concern, and related sarbecoviruses Exposure to a pathogen elicits an adaptive immune response aimed to control and eradicate. Interrogating the abundance and specificity of the naive B cell repertoire contributes to understanding how to potentially elicit protective responses. Here, we isolated naive B cells from 8 seronegative human donors targeting the SARS-CoV-2 receptor-binding domain (RBD). Single B cell analysis showed diverse gene usage with no restricted complementarity determining region lengths. We show that recombinant antibodies engage SARS-CoV-2 RBD, circulating variants, and pre-emergent coronaviruses. Representative antibodies signal in a B cell activation assay and can be affinity matured through directed evolution. Structural analysis of a naive antibody in complex with spike shows a conserved mode of recognition shared with infection-induced antibodies. Lastly, both naive and affinity-matured antibodies can neutralize SARS-CoV-2. Understanding the naive repertoire may inform potential responses recognizing variants or emerging coronaviruses enabling the development of pan-coronavirus vaccines aimed at engaging germline responses.

One Sentence SummaryIsolation of antibody germline precursors targeting the receptor binding domain of coronaviruses. 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. Once-daily feeding is associated with better health in companion dogs: Results from the Dog Aging Project A variety of diets have been studied for possible anti-aging effects. In particular, studies of intermittent fasting and time-restricted feeding in laboratory rodents have found evidence of beneficial health outcomes. Companion dogs represent a unique opportunity to study diet in a large mammal that shares human environments. The Dog Aging Project has been collecting data on thousands of companion dogs of all different ages, sizes, and breeds since 2019. We leveraged this diverse cross-sectional dataset to investigate associations between feeding frequency and cognitive function (n = 10,474) as well as nine broad categories of health conditions (n = 24,238). Controlling for sex, age, breed, and other potential confounders, we found that dogs fed once daily rather than more frequently had lower mean scores on a cognitive dysfunction scale, and lower odds of having gastrointestinal, dental, orthopedic, kidney/urinary, and liver/pancreas disorders. Therefore, we find that once-daily feeding is associated with better health in multiple domains. Future research with longitudinal data can provide stronger evidence for a possible causal effect of feeding frequency on health in companion dogs. High-quality genome assembly of Cinnamomum burmannii (chvar. Borneol) provides insights into the natural borneol biosynthesis Cinnamomum burmannii (chvar. Borneol) is a well-known medicinal and industrial plant cultivated in the Lingnan region of China. It is the key source from organism of natural borneol (D-borneol), one of the precious and widely used Chinese herbal medicines with a variety of medicinal effects. Here, we report a high-quality chromosome-scale genome assembly of C. burmannii (chvar. Borneol) using Pacbio single-molecule sequencing and Hi-C technology. The assembled genome size was 1.14 GB with a scaffold N50 of 94.30 Mb, while 98.77% of the assembled sequences were anchored on 12 pseudochromosomes including 41549 protein-coding genes. Genomic evolution analysis revealed C. burmannii and C. micranthum shared two Lauraceae unique ancestral whole-genome duplication (WGD) events. Likewise, comparative genomic analysis showed strong collinearity between these two species. Besides, the analysis for Long Terminal Repeat Retrotransposons (LTR-RTs) indicated the outbreak of LTR-RTs insertion made a great contribution to the size difference of genomes between C. burmannii and C. micranthum. Furthermore, the candidate genes in pathway associated with natural borneol synthesis were identified on the genome and their differential expressions were analyzed in various biological tissues. We considered that several of genes in Mevalonate (MVA) Methylerythritol Phosphate (MEP) pathways or in downstream pathway have the potential to be the key factors in the biosynthesis of D-borneol. We also constructed the genome database (CAMD; http://www.cinnamomumdatabase.com/) of Cinnamomum species for a better data utilization in the future. All these results will enrich the genomic data of Lauraceae plants and facilitate genetic improvement of this commercially important plant. Characterization of divalent cation interactions with AASTY native nanodiscs Amphiphilic copolymers show promise in extracting membrane proteins directly from lipid bilayers into  native nanodiscs. However, many such copolymers are polyanionic and sensitive to divalent cations, limiting their applicability. We characterize the Ca2+ and Mg2+ sensitivity of poly(acrylic acid-co-styrene) (AASTY) copolymers with analytical UV and fluorescent size exclusion chromatography, enabling us to separate signals from nanodiscs, copolymers, and soluble aggregates. We find that divalent cations promote aggregation and precipitation of both free and lipid bound copolymers. We see that excess, free copolymer acts as a  cation sink that protects nanodiscs from Ca2+ induced aggregation. Removal of the free copolymer through dialysis induces aggregation that can be mitigated by KCl. Finally, we find that the nanodisc size is dynamic and dependent on lipid concentration. Our results offer insight to nanodisc behaviour, and can help guide experimental design, aimed at mitigating the shortcomings inherent in negatively charged nanodisc forming copolymers. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. 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. Neprosin belongs to a new family of glutamic peptidase family based on in silico evidence Neprosin was first discovered in the insectivorous tropical pitcher plants of Nepenthes species as a novel protease with prolyl endopeptidase (PEP) activity. Neprosin has two uncharacterized domains of neprosin activation peptide and neprosin. A previous study has shown neprosin activity in hydrolyzing proline-rich gliadin, a gluten component that triggers celiac disease. In this study, we performed in silico structure-function analysis to investigate the catalytic mechanism of neprosin. Neprosin sequences lack the catalytic triad and motifs of PEP family S9. Protein structures of neprosins from Nepenthes x ventrata (NvNpr) and N. rafflesiana (NrNpr1) were generated by ab initio methods and comparatively assessed to obtain high-quality models. Structural alignment of models to experimental structures in the Protein Data Bank (PDB) found a high structural similarity to glutamic peptidases. Further investigations reveal other resemblances to the glutamic peptidases with low optimum pH that activates the enzyme via autoproteolysis for maturation. Two highly conserved glutamic acid residues, which are stable according to the molecular dynamics simulation, can be found at the active site of the substrate cleft. Protein docking demonstrated that mature neprosins bind well with potent antigen I-gliadin at the putative active site. Taken together, neprosins represent a new glutamic peptidase family, with a putative catalytic dyad of two glutamic acids. This study illustrates a hypothetical enzymatic mechanism of the neprosin family and demonstrates the useful application of an accurate ab initio protein structure prediction in the structure-function study of a novel protein family. Towards a mathematical understanding of colonization resistance in multispecies microbial communities Microbial community composition and dynamics are key to health and disease. Explaining the forces generating and shaping diversity in the microbial consortia making up our bodys defenses is a major aim of current research in microbiology. For this, tractable models are needed, that bridge the gap between observations of patterns and underlying mechanisms. While most microbial dynamics models are based on the Lotka-Volterra framework, we still do not have an analytic quantity for colonization resistance, by which a microbial systems fitness as a whole can be understood. Here, inspired by an epidemiological perspective, we propose a rather general modeling framework whereby colonization resistance can be clearly mathematically defined and studied. In our model, N similar species interact with each other through a co-colonization interaction network encompassing pairwise competition and cooperation, abstractly mirroring how organisms effectively modify their micro-scale environment in relation to others. This formulation relies on a generic notion of shared resources between members of a consortium, yielding explicit frequency-dependent dynamics among N species, in the form of a replicator equation, and offering a precise definition of colonization resistance. We demonstrate that colonization resistance arises and evolves naturally in a multispecies system as a collective quadratic term in a replicator equation, describing dynamic mean invasion fitness. Each pairwise invasion growth rate between two ecological partners, [Formula], is derived explicitly from species asymmetries and mean traits. This makes the systemic colonization resistance [Formula] also an emergent function of global mean-field parameters and trait variation architecture, weighted by the evolving relative abundances among species. In particular, if the underlying invasion fitness matrix {Lambda} displays species-specific  invasiveness or  invasibility structure, colonization resistance will be insensitive to mean micro-scale cooperation or competition. However, in general, colonization resistance depends on and may undergo critical transitions with changes in mean  environment, e.g. cooperation and growth level in a community. We illustrate several key links between our proposed measure of colonization resistance and invader success, including sensitivity to timing, and to the intrinsic pairwise invasion architecture of the resident community. Our simulations reveal that symmetric and invader-driven mutual invasion among resident species tend to maximize systemic colonization resistance to outsiders, when compared to resident-driven, anti-symmetric, almost anti-symmetric and random {Lambda} structures. We contend this modeling approach is a powerful new avenue to study, test and validate interaction networks and invasion topologies in diverse microbial consortia, and quantify analytically their role in colonization resistance, system function, and invasibility. Unique, shared, and dominant brain activation in Visual Word Form Area and Lateral Occipital Complex during reading and picture naming Identifying printed words and pictures concurrently is ubiquitous in daily tasks, and so it is important to consider the extent to which reading words and naming pictures may share a cognitive-neurophysiological functional architecture. Two functional magnetic resonance imaging (fMRI) experiments examined whether reading along the left ventral occipitotemporal region (vOT; often referred to as a visual word form area, VWFA) has activation that is overlapping with referent pictures (i.e., both conditions significant and shared, or with one significantly more dominant) or unique (i.e., one condition significant, the other not), and whether picture naming along the right lateral occipital complex (LOC) has overlapping or unique activation relative to referent words. Experiment 1 used familiar regular and exception words (to force lexical reading) and their corresponding pictures in separate naming blocks, and showed dominant activation for pictures in the LOC, and shared activation in the VWFA for exception words and their corresponding pictures (regular words did not elicit significant VWFA activation). Experiment 2 controlled for visual complexity by superimposing the words and pictures and instructing participants to either name the word or the picture, and showed primarily shared activation in the VWFA and LOC regions for both word reading and picture naming, with some dominant activation for pictures in the LOC. Overall, these results highlight the importance of including exception words to force lexical reading when comparing to picture naming, and the significant shared activation in VWFA and LOC serves to challenge specialized models of reading or picture naming. Transcription activation is enhanced by multivalent interactions independent of phase separation Transcription factors (TFs) consist of a DNA binding and an activation domain (AD) that are considered to be independent and exchangeable modules. However, recent studies conclude that also the physico-chemical properties of the AD can control TF assembly at chromatin by driving a phase separation into transcriptional condensates. Here, we dissected transcription activation by comparing different synthetic TFs at a reporter gene array with real-time single-cell fluorescence microscopy readouts. In these experiments, binding site occupancy, residence time and co-activator recruitment in relation to multivalent TF interactions were compared. While phase separation propensity and activation strength of the AD were correlated, the actual formation of liquid-like TF droplets had a neutral or inhibitory effect on transcription activation. Rather, we conclude that multivalent AD mediated interactions increase the transcription activation capacity of a TF by stabilizing chromatin binding and mediating the recruitment of co-activators independent of phase separation. Structural basis for cell-type specific evolution of viral fitness by SARS-CoV-2 As the global burden of SARS-CoV-2 infections escalates, so does the evolution of viral variants which is of particular concern due to their potential for increased transmissibility and pathology. In addition to this entrenched variant diversity in circulation, RNA viruses can also display genetic diversity within single infected hosts with co-existing viral variants evolving differently in distinct cell types. The BriS{Delta} variant, originally identified as a viral subpopulation by passaging SARS-CoV-2 isolate hCoV-19/England/02/2020, comprises in the spike glycoprotein an eight amino-acid deletion encompassing the furin recognition motif and S1/S2 cleavage site. Here, we elucidate the structure, function and molecular dynamics of this variant spike providing mechanistic insight into how the deletion correlates to viral cell tropism, ACE2 receptor binding and infectivity of this SARS-CoV-2 variant. Moreover, our study reveals long-range allosteric communication between functional regions within the spike that differ in wild-type and deletion variant. Our results support a view of SARS-CoV-2 probing multiple evolutionary trajectories in distinct cell types within the same infected host. Resurrected Rubisco suggests uniform carbon isotope signatures over geologic time The earliest geochemical indicators of microbes--and the enzymes that powered them--extend back almost 3.8 billion years on our planet. Paleobiologists often attempt to understand these indicators by assuming that the behaviors of modern microbes and enzymes are consistent (uniform) with those of their predecessors. A uniformitarian assumption (i.e., the idea that fundamental geobiological processes have occurred in much the same manner over Earth history) seems at odds with our understanding of the inherent variability of living systems. Here, we examine whether a uniformitarian assumption for an enzyme thought to generate carbon isotope indicators of biological activity, RuBisCO, can be corroborated by independently studying the history of changes recorded within RuBisCOs genetic sequences. Specifically, we resurrected a Precambrian-age, ancient RuBisCO by engineering its ancient DNA inside a modern cyanobacterium genome and measured the engineered organisms fitness and carbon-isotope-discrimination profile. The envelope of ancestral RuBisCO isotopic fractionation observed here indicates that uniformitarian assumptions may be warranted, but with important caveats. Our results suggest that further inquiries that link molecule-level evolutionary changes with planet-level geochemical conditions are needed to discern whether enzyme-affected isotope fractionation trends extend deeper into the early Precambrian. Experimental studies illuminating lifes early molecular innovations are crucial to explore the foundations of Precambrian uniformitarian assumptions. Inferring mammalian tissue-specific regulatory conservation by predicting tissue-specific differences in open chromatin BackgroundEvolutionary conservation is an invaluable tool for inferring functional significance in the genome, including regions that are crucial across many species and those that have undergone convergent evolution. Computational methods to test for sequence conservation are dominated by algorithms that examine the ability of one or more nucleotides to align across large evolutionary distances. While these nucleotide alignment-based approaches have proven powerful for protein-coding genes and some non-coding elements, they fail to capture conservation at many enhancers, distal regulatory elements that control spatio-temporal patterns of gene expression. The function of enhancers is governed by a complex, often tissue- and cell type-specific, code that links combinations of transcription factor binding sites and other regulation-related sequence patterns to regulatory activity. Thus, function of orthologous enhancer regions can be conserved across large evolutionary distances, even when nucleotide turnover is high.

ResultsWe present a new machine learning-based approach for evaluating enhancer conservation that leverages the combinatorial sequence code of enhancer activity rather than relying on the alignment of individual nucleotides. We first train a convolutional neural network model that is able to predict tissue-specific open chromatin, a proxy for enhancer activity, across mammals. Then, we apply that model to distinguish instances where the genome sequence would predict conserved function versus a loss regulatory activity in that tissue. We present criteria for systematically evaluating model performance for this task and use them to demonstrate that our models accurately predict tissue-specific conservation and divergence in open chromatin between primate and rodent species, vastly out-performing leading nucleotide alignment-based approaches. We then apply our models to predict open chromatin at orthologs of brain and liver open chromatin regions across hundreds of mammals and find that brain enhancers associated with neuron activity and liver enhancers associated with liver regeneration have a stronger tendency than the general population to have predicted lineage-specific open chromatin.

ConclusionThe framework presented here provides a mechanism to annotate tissue-specific regulatory function across hundreds of genomes and to study enhancer evolution using predicted regulatory differences rather than nucleotide-level conservation measurements. Preprints in motion: tracking changes between preprint posting and journal publication during a pandemic Amidst the COVID-19 pandemic, preprints in the biomedical sciences are being posted and accessed at unprecedented rates, drawing widespread attention from the general public, press and policymakers for the first time. This phenomenon has sharpened longstanding questions about the reliability of information shared prior to journal peer review. Does the information shared in preprints typically withstand the scrutiny of peer review, or are conclusions likely to change in the version of record? We assessed preprints from bioRxiv and medRxiv that had been posted and subsequently published in a journal through 30th April 2020, representing the initial phase of the pandemic response. We utilised a combination of automatic and manual annotations to quantify how an article changed between the preprinted and published version. We found that the total number of figure panels and tables changed little between preprint and published articles. Moreover, the conclusions of 7.2% of non-COVID-19-related and 17.2% of COVID-19-related abstracts undergo a discrete change by the time of publication, but the majority of these changes do not qualitatively change the conclusions of the paper. Bulk-assembly of monodisperse coacervates and giant unilamellar vesicles with programmable hierarchical complexity Compartmentalization is an essential step for the emergence of protocellular life on the early earth and the endeavor to bottom-up construct synthetic cells in the lab. Among manifold natural strategies for compartmentalization, assembly of lipid vesicles or coacervate droplets with resemblance to cell envelope or cytoplasm have emerged as two dominant paradigms. However, the spontaneous assembly of lipid vesicles or coacervates generally results in polydisperse microcompartments and lacks the ability to efficiently integrate functional building blocks towards defined complexity, which give rise to the difficulty to achieve the order and complexity towards the scope of that of life via spontaneous assembly. Herein, we show that the interplay of coacervates and colloidal particles provides a bulk-assembly approach to form monodisperse coacervates and giant unilamellar vesicles (GUVs) with programmable hierarchical complexity. The hierarchical complexity of the synthetic cell microcompartments can be delicately engineered from the control of the spatial or temporal organization of components in entity unit to manifold forms of interconnected synthetic cell consortia, achieving a compartment hierarchy analogous to the organelle-cell-tissue structure. The increase in complexity gives rise to emergent properties, for instance, collective morphology evolution of coacervate assemblages, gated permeability of GUVs without sophisticated protein machinery, and remarkable structural and functional stability of GUVs at extreme conditions. This work paves an unprecedented step to form monodisperse, hierarchical coacervates and GUVs via bulk-assembly, which provides a prebiotically plausible approach for the proper integration of inanimate matter towards the order and complexity of life and monodisperse, hierarchical microdroplets for follow-up scientific and technological applications. MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenome-assembled genomes We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is capable of classifying large and diverse metagenomic datasets: a total of 245.68 Gbp in the training sets, and 9.6 Gbp in the test sets analyzed in this study. MT-MAG is, to the best of our knowledge, the first machine learning method for taxonomic assignment of metagenomic data that offers a "partial classification" option. MT-MAG outputs complete or partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. To assess the performance of MT-MAG, we define a "weighted classification accuracy," with a weighting scheme reflecting the fact that partial classifications at different ranks are not equally informative. For the two benchmarking datasets analyzed (genomes from human gut microbiome species, and bacterial and archaeal genomes assembled from cow rumen metagenomic sequences), MT-MAG achieves an average of 80.13% in weighted classification accuracy. At the Species level, MT-MAG outperforms DeepMicrobes, the only other comparable software tool, by an average of 35.75% in weighted classification accuracy. In addition, MT-MAG is able to completely classify an average of 67.7% of the sequences at the Species level, compared with DeepMicrobes which only classifies 47.45%. Moreover, MT-MAG provides additional information for sequences that are not completely classified at the Species level, resulting in the partial or complete classification of 95.15%, of the genomes in the datasets analyzed. In particular, MT-MAG classifies, on average, 88.84% of the test sequences to the Phylum level, 88.39% to the Class level, 86.81% to the Order level, 81.17% to the Family level, and 71.13% to the Genus level.