Theory of condensin mediated loop extrusion in genomes Condensation of hundreds of mega-base-pair-long human chromosomes in a small nuclear volume is a spectacular biological phenomenon. This process is driven by the formation of chromosome loops. The ATP consuming motor, condensin, interacts with chromatin segments to actively extrude loops. Motivated by real-time imaging of loop extrusion (LE), we created an analytically solvable model, predicting the LE velocity and step size distribution as a function of external load. The theory fits the available experimental data quantitatively, and suggests that condensin must undergo a large conformational change, induced by ATP binding, bringing distant parts of the motor to proximity. Simulations using a simple model confirm that the motor transitions between an open and a closed state in order to extrude loops by a scrunching mechanism, similar to that proposed in DNA bubble formation during bacterial transcription. Changes in the orientation of the motor domains are transmitted over ~ 50 nm, connecting the motor head and the hinge, thus providing an allosteric basis for LE.
Dipeptides are minimalistic but sufficient for liquid-liquid phase separation Liquid-liquid phase separation (LLPS) of proteins mediates the assembly of biomolecular condensates involved in physiological and pathological processes. Identifying the minimalistic building blocks and the sequence determinant of protein phase separation is of urgent importance but remains challenging due to the enormous sequence space and difficulties of existing methodologies in characterizing the phase behavior of ultrashort peptides. Here we demonstrate computational tools to efficiently quantify the microscopic fluidity and density of liquid-condensates/solid-aggregates and the temperature-dependent phase diagram of peptides. Utilizing our approaches, we comprehensively predict the LLPS abilities of all 400 dipeptide combinations of coded amino acids based on 492 micro-second molecular dynamics simulations, and observe the occurrences of spontaneous LLPS. We identify 54 dipeptides that form solid-like aggregates and three categories of dipeptides with high LLPS propensity. Our predictions are validated by turbidity assays and differential interference contrast (DIC) microscopy on four representative dipeptides (WW, QW, GF, and VI). Phase coexistence diagrams are constructed to explore the temperature dependence of LLPS. Our results reveal that aromatic moieties are crucial for a dipeptide to undergo LLPS, and hydrophobic and polar components are indispensable. We demonstrate for the first time that dipeptides, minimal but complete, possess multivalent interactions sufficient for LLPS, suggesting that LLPS is a general property of peptides/proteins, independent of their sequence length. This study provides a computational and experimental approach to the prediction and characterization of the phase behavior of minimalistic peptides, and will be helpful for understanding the sequence-dependence and molecular mechanism of protein phase separation.

SignificanceProtein liquid-liquid phase separation (LLPS) is associated with human health and diseases. Identifying the minimalistic building blocks and sequence determinants of LLPS is of urgent importance but remains computationally challenging partially due to the lack of methodologies characterizing the liquid condensates. Herein we provide approaches to evaluate LLPS ability of dipeptides, and screen all 400 dipeptides by MD simulations combined with multi-bead-per-residue models which capture key interactions driving LLPS that are missing in one-bead-per-residue models. Three categories of LLPS dipeptides are identified and the experimentally-verified QW dipeptide is by far the smallest LLPS system. Our results suggest that dipeptides, minimal but complete, possess multivalent interactions sufficient for LLPS, and LLPS is a general property of peptides/proteins, independent of their length.
Phenomics data processing: Extracting dose-response curve parameters from high-resolution temperature courses and repeated field-based wheat height measurements Temperature is a main driver of plant growth and development. New phenotyping tools enable quantifying the temperature response of hundreds of genotypes. Yet, for field-derived data, temperature response modeling bears flaws and pitfalls concerning the interpretation of derived parameters. In this study, climate data from five growing seasons with differing temperature distributions served as starting point for a growth simulation of wheat stem elongation, based on a four-parametric temperature response function (Wang-Engel) including all cardinal temperatures. In a novel approach, we re-extracted dose-responses from the simulation by combining high-resolution (hours) temperature courses with low-resolution (days) height data. The collection of such data is common in field phenotyping platforms. To take advantage of the lack of supra-optimal temperatures during the stem elongation, simpler (linear and asymptotic) models to predict temperature-response parameters were investigated. The asymptotic model extracted the base temperature of growth and the maximum absolute growth rate with high precision, whereas simpler, linear models failed to do so. Additionally, the asymptotic model provided a proxy estimate for the optimum temperature. However, when including seasonally changing cardinal temperatures, the prediction accuracy of the asymptotic model was strongly reduced. In a field study with three winter wheat varieties, significant differences were found for all three asymptotic dose-response curve parameters. We conclude that the asymptotic model based on high-resolution temperature courses is suitable to extract meaningful parameters from field-based data. Distinguishing excess mutations and increased cell death based on variant allele frequencies Tumors often harbor orders of magnitude more mutations than healthy tissues. The increased number of mutations may be due to an elevated mutation rate or frequent cell death and correspondingly rapid cell turnover, or a combination of the two. It is difficult to disentangle these two mechanisms based on widely available bulk sequencing data, where sequences from individual cells are intermixed and, thus, the cell lineage tree of the tumor cannot be resolved. Here we present a method that can simultaneously estimate the cell turnover rate and the rate of mutations from bulk sequencing data. Our method works by simulating tumor growth and finding the parameters with which the observed data can be reproduced with maximum likelihood. Applying this method to a real tumor sample, we find that both the mutation rate and the frequency of death may be high.

Author SummaryTumors frequently harbor an elevated number of mutations, compared to healthy tissue. These extra mutations may be generated either by an increased mutation rate or the presence of cell death resulting in increased cellular turnover and additional cell divisions for tumor growth. Separating the effects of these two factors is a nontrivial problem. Here we present a method which can simultaneously estimate cell turnover rate and genomic mutation rate from bulk sequencing data. Our method is based on the estimation of the parameters of a generative model of tumor growth and mutations. Applying our method to a human hepatocellular carcinoma sample reveals an elevated per cell division mutation rate and high cell turnover. Translation of upstream open reading frames does not trigger nonsense-mediated decay in Arabidopsis Upstream ORFs (uORFs) are widespread cis-regulatory elements in the 5 untranslated regions of eukaryotic genes. In addition to repressing main ORF translation, uORF translation in animals also reduces mRNA stability through nonsense-mediated decay (NMD). In contrast, the roles of uORFs in plants are less understood. One limitation of most prior studies is the inclusion of both translated and untranslated uORFs for analysis. Here, we identified actively translated uORFs (TuORFs) in Arabidopsis through ribosome profiling and examined their roles in gene expression by integrating multiple genome-wide datasets. Similar to animal systems, TuORFs are associated with 38%, 14%, and 43% reductions in translation efficiency, mRNA stability, and protein levels, respectively. Surprisingly, TuORF-containing mRNAs in plants have 51% higher transcript levels, which is opposite to the observations in animals. We present multiple lines of evidence showing that uORF translation generally does not trigger NMD in Arabidopsis. First, TuORF-containing mRNAs are not upregulated in various NMD mutants. Second, TuORF- containing mRNAs and known NMD targets have distinct expression patterns, and they are translationally repressed via different mechanisms. Finally, TuORF-containing mRNAs and NMD targets are degraded through separate pathways. Together, our results highlight fundamental differences in gene regulation mediated by TuORFs in plants and animals. Hypertrophic Chondrocytes Serve as a Reservoir for Marrow Associated Skeletal Stem and Progenitor Cells, Osteoblasts, and Adipocytes During Skeletal Development Hypertrophic chondrocytes give rise to osteoblasts during skeletal development; however, the process by which these non-mitotic cells make this transition is not well understood. Prior studies have also suggested that skeletal stem and progenitor cells (SSPCs) localize to the surrounding periosteum and serve as a major source of marrow associated SSPCs, osteoblasts, osteocytes, and adipocytes during skeletal development. To further understand the cell transition process by which hypertrophic chondrocytes contribute to osteoblasts or other marrow associated cells, we utilized inducible and constitutive hypertrophic chondrocyte lineage tracing and reporter mouse models (Col10a1CreERT2; R26-tdTomatof/+ and Col10a1Cre; R26-tdTomatof/+) in combination with a PDGFRa-H2B-GFP transgenic line, single cell RNA-sequencing, bulk RNA-sequencing, immunofluorescence staining, and cell transplantation assays. Our data demonstrate that hypertrophic chondrocytes undergo a process of dedifferentiation to generate marrow associated SSPCs that serve as a primary source of osteoblasts during skeletal development. These hypertrophic chondrocyte derived SSPCs commit to a CXCL12-abundant reticular (CAR) cell phenotype during skeletal development and demonstrate unique abilities to recruit vasculature and promote bone marrow establishment, while also contributing to the adipogenic lineage. SERCA function is impaired in skeletal and cardiac muscles from young DBA/2J mdx mice The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Tackling polypharmacology of kinase inhibitors and selecting chemical kinase probes by transcription factor activity profiling. Protein kinase inhibitors (PKI) evolved as promising drugs for multiple diseases. However, PKIs promiscuity causes polypharmacological effects challenging therapeutic development. We show that the polypharmacology of PKIs can be inferred from their impact on transcription factors (TF) lying at the apexes of signaling pathways. Using a high-content reporter assay, we evaluated TF activity profiles (TFAP) in cells treated with Akt, CDK, Aurora, Raf, MEK, and ERK inhibitors. For each kinase family, we found kinase-specific consensus TFAP signatures signifying the on-target PKI activity. Remarkably, proximal kinases had the highest similarity of their PKIs consensus signatures. Furthermore, we show that individual PKIs exhibited the consensus, "on-target signatures" within certain "specificity windows" and distinct "off-target signatures" at other concentrations. We also show that the TFAP signatures permit pinpointing the off-target PKI activity at irrelevant kinases and non-kinase effectors. Therefore, the TFAP approach provides clear-cut quantitative metrics for assessing PKI activity and concentration ranges where the on-target activity dominates cell response. By illuminating PKI biology invisible to target-based techniques, this effect-based approach streamlines the selection of kinase chemical probes and PKI drug prioritization. Activation of neuronal FLT3 promotes exaggerated sensorial and emotional pain-related behaviors facilitating the transition from acute to chronic pain Acute pain events have been associated with persistent pain sensitization of nociceptive pathways increasing the risk of transition from acute to chronic pain. However, it is unclear whether injuryinduced persistent pain sensitization can promote long-term mood disorders. The receptor tyrosine kinase FLT3 is causally required for pain chronification after peripheral nerve injury, questioning its role in the development of pain-induced mood alterations. Here, we evaluated the emotional and sensorial components of pain after a single (SI) or double paw incision (DI). We then investigated the role of FLT3 either by inhibition using transgenic knock-out mice and functional antibodies or by activation with FLT3 ligand (FL) administrations.

DI mice showed significant anxiodepressive-like and spontaneous pain behaviors as opposed to SI mice. DI also promoted and extended mechanical pain hypersensitivity compared to SI. This emotional and sensorial pain exaggeration correlated with spinal changes especially by increased microglia activation after DI versus SI. Intrathecal minocycline, a microglial inhibitor, specifically reversed DI inducedmechanical hypersensitivity in males. Repeated treatment with the microglia proliferation inhibitor GW2580 not only eliminated the exaggerated pain hypersensitivity produced by DI but also prevented anxiodepressive-related behaviors in DI animals. Finally, FL injections in naive animals provoked mechanical allodynia and anxiodepressive-like disorders concomitant with a strong microglial activation while Flt3 silencing in a genetic mouse line or FLT3 blocking via functional antibodies, blunted the development of persistent pain and depression after DI. Altogether our results show that the repetition of peripheral lesions facilitate not only exaggerated nociceptive behaviors but also induced anxiodepressive disorders supported by spinal central changes. The inhibition of FLT3 could thus become a promising therapy in the management of pain sensitization and related mood alterations. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amenable to Dexamethasone Therapy SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS), death and long-term sequelae. Innate immune cells are critical for host defense but are also the primary drivers of ARDS. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial effects of dexamethasone therapy during severe COVID-19 remain speculative, but understanding the mechanistic effects could improve evidence-based therapeutic interventions. To interrogate these relationships, we developed an scRNA-Seq and plasma proteomics atlas (biernaskielab.ca/COVID_neutrophil). We discovered that compared to bacterial ARDS, COVID-19 was associated with distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. Neutrophils from bacterial ARDS had higher expression of antibacterial molecules such as PLAC8 and CD83. Dexamethasone therapy in COVID patients rapidly altered the IFNactive state, downregulated interferon responsive genes, and activated IL1R2+ve neutrophils. Dexamethasone also induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1, which were not present in healthy controls. Moreover, dexamethasone remodeled global cellular interactions by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFNactive neutrophils, a greater degree of steroid-induced immature neutrophil expansion, and increased mortality benefit compared to females in the dexamethasone era. Indeed, the highest proportion of IFNactive neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the molecular benefits of dexamethasone therapy are also defined, and the identified pathways and plasma proteins can now be targeted to develop improved therapeutics. Combinatorial drug-microenvironment interaction mapping reveals cell-extrinsic drug resistance mechanisms and clinically relevant patient subgroups in CLL The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited to small scale studies and systematic analyses are lacking. We chose Chronic Lymphocytic Leukaemia (CLL), the most common leukaemia in adults, as a model disease to study this complex interplay systematically. We performed a combinatorial assay using 12 drugs individually co-applied with each of 17 microenvironmental stimuli in 192 primary CLL samples, generating a comprehensive map of drug-microenvironment interactions in CLL. This data was combined with whole-exome sequencing, DNA-methylation, RNA-sequencing and copy number variant annotation. Our assay identified four distinct CLL subgroups that differed in their responses to the panel of microenvironmental stimuli. These subgroups were characterized by distinct clinical outcomes independently of known prognostic markers. We investigated the effect of CLL- specific recurrent genetic alterations on microenvironmental responses and identified trisomy 12 as an amplifier of multiple microenvironmental stimuli. We further quantified the impact of microenvironmental stimuli on drug response, confirmed known interactions such as Interleukin (IL) 4 mediated resistance to B cell receptor (BCR) inhibitors, and identified new interactions such as Interferon-{gamma} induced resistance to BCR inhibitors. Finally, we identified interactions which were limited to genetic subgroups. Resistance to chemotherapeutics, such as Fludarabine, induced by Toll-Like Receptor (TLR) agonists could be observed in IGHV unmutated patient samples and IGHV mutated samples with trisomy 12. In-vivo relevance was investigated in CLL-infiltrated lymph nodes, which showed increased IL4 and TLR signalling activity compared to healthy samples (p<0.001). High IL4 activity in lymph nodes correlated with faster disease progression (p=0.038).

We provide a publicly available resource (www.dietrichlab.de/CLL_Microenvironment/) which uncovers tumour cell extrinsic influences on drug response and disease progression in CLL, and how these interactions are modulated by cell intrinsic molecular features. Evolutionary association of receptor-wide amino acids with G protein coupling selectivity in aminergic GPCRs G protein-coupled receptors (GPCRs) induce signal transduction pathways through coupling to four main subtypes of G proteins (Gs, Gi, Gq, G12/13), selectively. However, G protein selective activation mechanisms and residual determinants in GPCRs have remained obscure. Herein, we performed an extensive phylogenetic analysis and identified specifically conserved residues for the receptors having similar coupling profiles in each aminergic receptor. By integrating our methodology of differential evolutionary conservation of G protein-specific amino acids with structural analyses, we identified selective activation networks for Gs, Gi1, Go, and Gq. To validate that these networks could determine coupling selectivity we further analyzed Gs specific activation network and associated it with the larger TM6 tilt which is a signature of Gs-coupled receptors. Through molecular dynamics simulations, we showed that previously uncharacterized Glycine at position 7x41 plays an important role in both receptor activation and Gs coupling selectivity by inducing a larger TM6 movement. Finally, we gathered our results into a comprehensive model of G protein selectivity called "sequential switches of activation" describing three main molecular switches controlling GPCR activation: ligand binding, G protein selective activation mechanisms and G protein contact. Global structural stability and the role of cooperation in mutualistic system Dynamical systems on graphs allow to describe multiple phenomena from different areas of Science. In particular, many complex systems in Ecology are studied by this approach. In this paper we analize the mathematical framework for the study of the structural stability of each stationary point, feasible or not, introducing a generalization for this concept, defined as Global Structural Stability. This approach would fit with the proper mathematical concept of structural stability, in which we find a full description of the complex dynamics on the phase space due to nonlinear dynamics. This fact can be analyzed as an informational field grounded in a global attractor whose structure can be completely characterized. These attractors are stable under perturbation and suppose the minimal structurally stable sets. We also study in detail, mathematically and computationally, the zones characterizing different levels of biodiversity in bipartite graphs describing mutualistic antagonistic systems of population dynamics. In particular, we investigate the dependence of the region of maximal biodiversity of a system on its connectivity matrix. On the other hand, as the network topology does not completely determine the robustness of the dynamics of a complex network, we study the correlation between structural stability and several graph measures. A systematic study on synthetic and biological graphs is presented, including 10 mutualistic networks of plants and seed-dispersal and 1000 random synthetic networks. We compare the role of centrality measures and modularity, concluding the importance of just cooperation strength among nodes when describing areas of maximal biodiversity. Indeed, we show that cooperation parameters are the central role for biodiversity while other measures act as secondary supporting functions.

Author summaryWe introduce the concept of Global Structural Stability as a proper mathematical concept to fully understand biodiversity in some ecological systems. Our concept retakes the definitions in the classical works of R. Thom [1] and Andronov-Pontryagin [2]. Moreover, there exists a close relation between the structure of a complex network, described as a graph, and its associated dynamics. Mutualistic networks introduce cooperation links between two groups of species, as plant and pollinators or seed-dispersal. The understanding of organizational aspects leading to maximizing biodiversity is one of the more important research areas in Theoretical and Applied Ecology. In this work we introduce a systematic study on different graph measures in order to identify optimal organization for maximal biodiversity (defined as structural stability). Our results conclude that, for mutualistic systems, the strength in cooperation parameters are the core fact, i.e., cooperation is the real fact optimizing biodiversity among other possible structural configurations. Receptor localization maximizes information acquisition in natural cell environments Cells in natural environments like tissue or soil sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions, sculpted by processes such as fluid flow and substrate adhesion. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. We develop an information-theoretic framework for computing the optimal spatial organization of a sensing system for a given signaling environment. We find that receptor localization maximizes information acquisition in simulated natural contexts, including tissue and soil. Receptor localization extends naturally to produce a dynamic protocol for continuously redistributing signaling receptors, which when implemented using simple feedback, boosts cell navigation efficiency by 30-fold. Broadly, our work shows how cells can maximize the fidelity of information transfer by adapting the spatial organization of signaling molecules to the spatial structure of the environment. Structural and Functional Analyses Explain Pea KAI2 Receptor Diversity and Reveal Stereoselective Catalysis During Signal Perception KAI2 are plant /{beta} hydrolase receptors, which perceive smoke-derived butenolide signals (karrikins) and putative endogenous, yet unidentified phytohormones (KAI2-ligands, KLs). The number of functional KAI2 receptors varies among plant species. It has been suggested that KAI2 gene duplication and sub-functionalization plays an adaptative role for diverse environments or ligand diversification by altering the receptor responsiveness to specific KLs. Legumes represent one of the largest families of flowering plants and contain many essential agronomic crops. Prior to legume diversification, KAI2 underwent duplication, resulting in KAI2A and KAI2B. Integrating plant genetics, ligand perception and enzymatic assays, and protein crystallography, we demonstrate that Pisum sativum KAI2A and KAI2B act as receptors and enzymes with divergent ligand stereoselectivity. KAI2B has a stronger affinity than KAI2A towards the KAI2-ligand (-)-GR24 and remarkably hydrolyses a broader range of substrates including the strigolactone-like isomer (+)-GR24. We determine the crystal structures of PsKAI2B in apo and butenolide-bound states. The biochemical and structural analyses as well as recorded mass spectra of KAI2s reveal a transient intermediate on the catalytic serine and a stable adduct on the catalytic histidine, further illuminating the role of KAI2 not only as receptors but also as bona fide enzymes. Our work uncovers the stereoselectivity of ligand perception and catalysis by evolutionarily diverged KAI2 receptors in KAR/KL signaling pathways and proposes adaptive sensitivity to KAR/KL and strigolactone phytohormones by KAI2B. Extending Bayesian Elo-rating to quantify the steepness of dominance hierarchies The steepness of dominance hierarchies provides information about the degree of competition within animal social groups and is thus an important concept in socioecology. The currently most widely-used metrics to quantify steepness are based on Davids scores (DS) derived from dominance interaction networks. One serious drawback of these DS-based metrics is that they are biased, i.e., network density systematically decreases steepness values. Here, we provide a novel approach to estimate steepness based on Elo-ratings, implemented in a Bayesian framework (STEER: Steepness estimation with Elo-rating). Our new metric has two key advantages. First, STEER is unbiased, precise and more robust to data density than DS-based steepness. Second, it provides explicit probability distributions of the estimated steepness coefficient, which allows uncertainty assessment. In addition, it relies on the same underlying concept and is on the same scale as the original measure, and thus allows comparison to existing published results. We evaluate and validate performance of STEER by means of experimentation on empirical and artificial data sets and compare its performance to that of several other steepness estimators. Our results suggest that STEER provides a considerable improvement over existing methods to estimate dominance hierarchy steepness. We provide an R package EloSteepness to calculate the new steepness measure, and also show an example of using steepness in a comparative analysis. 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. Cell-type specific circadian bioluminescence rhythms in Dbp reporter mice Circadian rhythms are endogenously generated physiological and molecular rhythms with a cycle length of about 24 h. Bioluminescent reporters have been exceptionally useful for studying circadian rhythms in numerous species. Here, we report development of a reporter mouse generated by modification of a widely expressed and highly rhythmic gene encoding D-site albumin promoter binding protein (Dbp). In this line of mice, firefly luciferase is expressed from the Dbp locus in a Cre-recombinase-dependent manner, allowing assessment of bioluminescence rhythms in specific cellular populations. A mouse line in which luciferase expression was Cre-independent was also generated. The Dbp reporter alleles do not alter Dbp gene expression rhythms in liver or circadian locomotor activity rhythms. In vivo and ex vivo studies show the utility of the reporter alleles for monitoring rhythmicity. Our studies reveal cell-type specific characteristics of rhythms among neuronal populations within the suprachiasmatic nuclei ex vivo. In vivo studies show Dbp-driven bioluminescence rhythms in the liver of Albumin-Cre;DbpKI/+ "liver reporter" mice. After a shift of the lighting schedule, locomotor activity achieved the proper phase relationship with the new lighting cycle more rapidly than hepatic bioluminescence did. As previously shown, restricting food access to the daytime altered the phase of hepatic rhythmicity. Our model allowed assessment of the rate of recovery from misalignment once animals were provided with food ad libitum. These studies confirm the previously demonstrated circadian misalignment following environmental perturbations and reveal the utility of this model for minimally invasive, longitudinal monitoring of rhythmicity from specific mouse tissues. Cell-specific Bioorthogonal Tagging of Glycoproteins Altered glycosylation is an undisputed corollary of cancer development. Understanding these alterations is paramount but hampered by limitations underlying cellular model systems. For instance, the intricate interactions between tumour and host cannot be adequately recapitulated in monoculture of tumour-derived cell lines. More complex co-culture models usually rely on sorting procedures for proteome analyses and rarely capture the details of protein glycosylation. Here, we report a strategy termed Bio-Orthogonal Cell line-specific Tagging of Glycoproteins (BOCTAG). Cells are equipped by transfection with an artificial biosynthetic pathway that transforms bioorthogonally tagged sugars into the corresponding nucleotide-sugars. Only transfected cells incorporate bioorthogonal tags into glycoproteins in the presence of non-transfected cells. We employ BOCTAG as an imaging technique and to annotate cell-specific glycosylation sites in mass spectrometry-glycoproteomics. We demonstrate application in co-culture and mouse models, allowing for profiling of the glycoproteome as an important modulator of cellular function. TCAB1 prevents nucleolar accumulation of the telomerase RNA to promote telomerase assembly Localization of a wide variety of RNAs to non-membrane bound cellular compartments such as nucleoli, Cajal bodies, and stress-granules is critical for their function and stability. The molecular mechanisms that underly the recruitment and exclusion of specific RNAs from these phase-separated organelles is poorly understood. Telomerase is a ribonucleoprotein (RNP), that is composed of the reverse transcriptase protein TERT, the telomerase RNA (TR), and several auxiliary proteins that associate with TR, including TCAB1. Here we show that, that in the absence of TCAB1, TR is sequestered in the nucleolus, while TERT localizes to the nucleoplasm and is excluded from the nucleolus, which prevents telomerase assembly. Thus, nuclear compartmentalization by the non-membrane bound nucleolus counteracts telomerase assembly and TCAB1 is required to exclude the telomerase RNA from the nucleolus. Our work provides general insight into the mechanism and functional consequences of RNA recruitment to organelles formed by phase-separation and proposes a new model explaining the critical role of TCAB1 in telomerase function. Micro topographical instruction of bacterial attachment, biofilm formation and in vivo host response Bio-instructive materials that prevent bacterial biofilm formation and drive an appropriate host immune response have the potential to significantly reduce the burden of medical device-associated infections. As bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2,176 combinatorially generated shapes using an unbiased high-throughput micro topographical polystyrene polymer chip screen. This identified topographies that reduced colonization in vitro by up to 15-fold compared with a flat surface for both motile and non-motile bacterial pathogens. Equivalent reductions were achieved on polyurethane, a polymer commonly used in medical devices. Using machine learning methods, a set of design rules based on generalisable topo-descriptors was established for predicting bacteria-resistant micro topographies. In a murine foreign body infection model, anti-attachment topographies were shown to be refractory to P. aeruginosa colonization and serendipitously, the fibrotic response to the implant was reduced, offering control of foreign body response using simple topographical patterning of non-eluting implants. 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. The giant staphylococcal protein Embp facilitates colonization of surfaces through Velcro-like attachment to fibrillated fibronectin Staphylococcus epidermidis causes some of the most hard-to-treat clinical infections by forming biofilms: Multicellular communities of bacteria encased in a protective matrix, supporting immune evasion and tolerance against antibiotics. Biofilms occur most commonly on medical implants, and a key event in implant colonization is the robust adherence to the surface, facilitated by interactions between bacterial surface proteins and host matrix components. S. epidermidis is equipped with a giant adhesive protein, Embp, which facilitates bacterial interactions with surface-deposited, but not soluble fibronectin. The structural basis behind this selective binding process has remained obscure. Using a suite of single-cell and single-molecule analysis techniques, we show that S. epidermidis is capable of such distinction because Embp binds specifically to fibrillated fibronectin on surfaces, while ignoring globular fibronectin in solution. S. epidermidis adherence is critically dependent on multi-valent interactions involving 50 fibronectin-binding repeats of Embp. This unusual, Velcro-like interaction proved critical for colonization of surfaces under high flow, making this newly identified attachment mechanism particularly relevant for colonization of intravascular devices, such as prosthetic heart valves or vascular grafts. Other biofilm-forming pathogens, such as Staphylococcus aureus, express homologs of Embp and likely deploy the same mechanism for surface colonization. Our results may open for a novel direction in efforts to combat devastating, biofilm-associated infections, as the development of implant materials that steer the conformation of adsorbed proteins is a much more manageable task than avoiding protein adsorption altogether.

Graphical abstractFibronectin exists in two different conformations in the body. It circulates in the bodily fluids in globular conformation, however, it become fibrillated once adsorbed to an implant surface. S. epidermidis possess a giant 1 MDa receptor known as Embp bind specifically to fibrillated Fn but not to the globular Fn.



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org.highwire.dtl.DTLVardef@1999895org.highwire.dtl.DTLVardef@f0717corg.highwire.dtl.DTLVardef@1aa8773org.highwire.dtl.DTLVardef@a2991b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Coordination of genome replication and anaphase entry by rDNA copy number in S. cerevisiae Eukaryotes maintain hundreds of copies of ribosomal DNA (rDNA), many more than required for ribosome biogenesis, suggesting a yet undefined role for large rDNA arrays outside of ribosomal RNA synthesis. We demonstrate that reducing the Saccharomyces cerevisiae rDNA array to 35 copies, which is sufficient for ribosome function, shifts rDNA from being the latest replicating region in the genome to one of the earliest. This change in replication timing results in delayed genome-wide replication and classic replication defects. We present evidence that the requirement for rDNA to replicate late, which is conserved among eukaryotes, also coordinates the completion of genome replication with anaphase entry through the proper sequestration of the mitotic exit regulator Cdc14p in the rDNA-containing nucleolus. Our findings suggest that, instead of being a passive repetitive element, the large late-replicating rDNA array plays an active role in genome replication and cell cycle control. Using Obviously-Related Instrumental Variables to Increase the Predictive Power of Polygenic Scores The conventional way of boosting the predictive power of polygenic scores is to increase the GWAS sample size by meta-analyzing GWAS results of multiple cohorts. In this paper, we challenge this convention. Through simulations, we show that Instrumental Variable (IV) regression using two polygenic scores constructed from independent GWAS summary statistics outperforms the typical Ordinary Least Squares (OLS) model employing a single meta-analysis based polygenic score in terms of bias, root mean squared error, and statistical power. We verify the empirical validity of the simulations by predicting educational attainment (EA) and height in a sample of siblings from the UK Biobank. We show that IV regression between-families approaches the SNP-based heritability, and improves the predictive power of polygenic scores by 12% (height) to 22% (EA). Furthermore, IV regression within-families provides the tightest lower bound for the direct genetic effect, increasing the lower bound for EA from 2.0% to 3.4%, and for height from 28.9% to 37.7%.