Spontaneous differentiation leads to emergence of hybrid cell states relate to poor prognosis in oral cancer PurposeCellular dynamics between phenotypically heterogeneous subpopulations of cancer cells within individual tumor is shown to be responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Therefore, this study was undertaken to describe the dynamic phenotypic states among oral cancer cells, its influence on transcriptomic heterogeneity as well as its clinical significance.

Experimental DesignWe multiplexed phenotypic markers of putative oral-stem-like cancer cells (SLCCs) and characterized diversity among CD44-positive oral cancer cell subpopulations with respect to distinct expression of CD24 and aldehyde dehydrogenase (ALDH)-activity in multiple cell lines. Population trajectories were characterized by Markov model and cell states were defined based on the population specific RNA sequencing (RNAseq). ssGSEA based gene expression signatures were explore for prognostic significance.

ResultsOral cancer cells followed two distinct patterns of spontaneous repopulation dynamics with stochastic inter-conversions on  ALDH-axis, however a strict non-interconvertible transition on  CD24-axis. Interestingly, plastic  ALDH-axis was harnessed to enrich ALDHHigh subpopulations in response to Cisplatin treatment, to adapt a drug tolerant state. Phenotype-specific RNAseq results suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate states of stemness within the differentiating oral cancer cells. Further, survival analysis with each subpopulation-specific gene signature strongly suggested that the cell-state dynamics may act as possible mechanism to drive ITH, resulting in poor prognosis in patient.

ConclusionsOur results emphasized the prognostic power of the population dynamics in oral cancer. Importantly, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behaviour in oral cancer; which is a prerequisite knowledge important for precision treatment, however largely lacking for most solid tumors.

Graphical AbstractWe have characterized diversity among CD44-positive oral cancer cells lines with respect to distinct expression of CD24 and ALDH-activity. Subpopulations showed stochastic inter-conversions on ALDH-axis but a strict non-interconvertible transition of CD24Low to CD24High phenotype, even in response to chemotherapy-induced stress. RNAseq study suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate alternate states of stemness within the differentiating oral cancer cells. The described population dynamics demonstrtaed influence tumor behaviour possibly by increasing intratumoral heterogeneity in aggressive oral tumors.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/457509v3_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@1dc6a7org.highwire.dtl.DTLVardef@dd0948org.highwire.dtl.DTLVardef@18c9603org.highwire.dtl.DTLVardef@cca8fb_HPS_FORMAT_FIGEXP  M_FIG C_FIG Translational relevanceIntratumoral heterogeneity (ITH) has been the clinically important factor, impacting aggressive cancer behaviour, drug tolerance and overall poor prognosis. Recent high-throughput studies have provided better cellular and molecular resolution of ITH; however, the prerequisite knowledge which defines the composition of subpopulations critical for global tumor behaviour is majorly lacking for most of the solid tumors. By combining phenotypic markers, we have defined four subpopulations of oral cancer cells. These subpopulations showed stochastic inter-conversions as well as a strict non-interconvertible transition among them to acheive heterogeneity. Importantly, transcriptional states of each subpopulations indicated a clinically relevant signatures for patient prognosis. Also, we observed interconversions of these subpopulations in response to Cisplatin to accumulate drug-tolerant cell state, as rapid and reversible strategy to respond to chemotherapy induced stress. Thus, the characteristics of described phenotypic subgroups may be translated to the clinic for estimating the extent of intratumoral heterogeneity in oral cancer patients.
A cell-based screen identifies HDAC inhibitors as activators of RIG-I signaling Enhancing the immune microenvironment in cancer by targeting the nucleic acid sensors is becoming a potent therapeutic strategy. Among the nucleic acid sensors, activation of the RNA sensor Retinoic Acid-inducible Gene (RIG-I) using small hairpin RNAs has been shown to elicit powerful innate and adaptive immune responses. Given the challenges inherent in pharmacokinetics and delivery of RNA based agonists, we set out to discover small molecule agonists of RIG-I using a cell-based assay. To this end, we established and validated a robust high throughput screening assay based on a commercially available HEK293 reporter cell line with a luciferase reporter downstream of tandem interferon stimulated gene 54 (ISG54) promoter elements. We first confirmed that the luminescence in this cell line is dependent on RIG-I and the interferon receptor using a hairpin RNA RIG-I agonist. We established a 96-well and a 384-well format HTS based on this cell line and performed a proof-of-concept screen using an FDA approved drug library of 1200 compounds. Surprisingly, we found two HDAC inhibitors Entinostat, Mocetinostat and the PLK1 inhibitor Volasertib significantly enhanced ISG-luciferase activity. This luminescence was substantially diminished in the null reporter cell line indicating the increase in signaling was dependent on RIG-I expression. Combination treatment of tumor cell lines with Entinostat increased RIG-I induced cell death in a mammary carcinoma cell line that is resistant to either Entinostat or RIG-I agonist alone. Taken together, our data indicates an unexpected role for HDAC1,-3 inhibitors in enhancing RIG-I signaling and highlight potential opportunities for therapeutic combinations.
Antibody Resistance of SARS-CoV-2 Variants B.1.351 and B.1.1.7 The COVID-19 pandemic has ravaged the globe, and its causative agent, SARS-CoV-2, continues to rage. Prospects of ending this pandemic rest on the development of effective interventions. Single and combination monoclonal antibody (mAb) therapeutics have received emergency use authorization1-3, with more in the pipeline4-7. Furthermore, multiple vaccine constructs have shown promise8, including two with ~95% protective efficacy against COVID-199,10. However, these interventions were directed toward the initial SARS-CoV-2 that emerged in 2019. The recent emergence of new SARS-CoV-2 variants B.1.1.7 in the UK11 and B.1.351 in South Africa12 is of concern because of their purported ease of transmission and extensive mutations in the spike protein. We now report that B.1.1.7 is refractory to neutralization by most mAbs to the N-terminal domain (NTD) of spike and relatively resistant to a few mAbs to the receptor-binding domain (RBD). It is not more resistant to convalescent plasma or vaccinee sera. Findings on B.1.351 are more worrisome in that this variant is not only refractory to neutralization by most NTD mAbs but also by multiple individual mAbs to the receptor-binding motif on RBD, largely due to an E484K mutation. Moreover, B.1.351 is markedly more resistant to neutralization by convalescent plasma (9.4 fold) and vaccinee sera (10.3-12.4 fold). B.1.351 and emergent variants13,14 with similar spike mutations present new challenges for mAb therapy and threaten the protective efficacy of current vaccines. Recommendations for improving statistical inference in population genomics The field of population genomics has grown rapidly in response to the recent advent of affordable, large-scale sequencing technologies. As opposed to the situation during the majority of the 20th century, in which the development of theoretical and statistical population-genetic insights out-paced the generation of data to which they could be applied, genomic data are now being produced at a far greater rate than they can be meaningfully analyzed and interpreted. With this wealth of data has come a tendency to focus on fitting specific (and often rather idiosyncratic) models to data, at the expense of a careful exploration of the range of possible underlying evolutionary processes. For example, the approach of directly investigating models of adaptive evolution in each newly sequenced population or species often neglects the fact that a thorough characterization of ubiquitous non-adaptive processes is a prerequisite for accurate inference. We here describe the perils of these tendencies, present our consensus views on current best practices in population genomic data analysis, and highlight areas of statistical inference and theory that are in need of further attention. Thereby, we argue for the importance of defining a biologically relevant baseline model tuned to the details of each new analysis, of skepticism and scrutiny in interpreting model-fitting results, and of carefully defining addressable hypotheses and underlying uncertainties. Molecular mechanisms of stress-induced reactivation in mumps virus condensates Many viruses can establish long-term persistent infections in the human host and cause chronic diseases. Here we combine cell biology, whole-cell proteomics and cryo-electron tomography to uncover how cellular stress disrupts the host-virus equilibrium in persistent infection and induces viral replication, using a model of negative-stranded RNA viruses, the mumps virus. We show that phosphorylation of the largely disordered viral phosphoprotein coincides with increased partitioning of viral polymerase into pre-formed liquid-like condensates and the formation of a stable replication machinery. By obtaining the first atomic models for the authentic mumps virus nucleocapsid, we elucidate a concomitant conformational change that exposes the viral genome to its replication machinery. These events that occur within viral condensates upon stress, together with concerted down-regulation of the host antiviral defense, provide an environment that supports up-regulation of viral replication and constitute a stress-mediated switch that disrupts the host-virus equilibrium in persistent infection.

In BriefA multi-scale approach uncovers molecular and structural basis of how cellular stress provokes activation of persistent viral infection mediated by biomolecular condensates. 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. 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 new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. Cellular feedback to organotelluranes displays modulation of antioxidant proteins gene expression Organotelluranes RT3 and RT4 are thiol reagents that induce mitochondrial transition pore (MTP) opening in a sensitive and insensitive manner to cyclosporin A. Although RT3 and RT4 promote glutathione depletion, paradoxically, they are also an efficient antioxidant for membrane lipids. These compounds antagonistic effects elicited the challenging question of how the gene expression of antioxidant enzymes would respond to treatment with these compounds. The influence of RT3 and RT4 on antioxidant enzyme expression was investigated in cultured aortic smooth muscle cells (ASMC). RT3 and RT4 promoted disruption of ionic calcium homeostasis, mitochondrial transmembrane potential ({Delta}{Psi}), and cell death in a dose-dependent manner. The cell death mechanisms responded qualitatively to the increase of the organotellurane concentration and changed from apoptosis to necrosis. RT3 and RT4 increased the expression of thioredoxin significantly. RT3 also increased the expression of glutaredoxin and glutathione peroxidase, slightly the catalase expression without significant effects on SOD expression. The results are consistent with GSH and protein thiol depletion and discussed based on the cell toxicity mechanism exhibited by these compounds.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/425411v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@52bb82org.highwire.dtl.DTLVardef@19476d9org.highwire.dtl.DTLVardef@6aa99org.highwire.dtl.DTLVardef@1aa605e_HPS_FORMAT_FIGEXP  M_FIG C_FIG 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. Catheterized bladder environment induces Candida albicans hyphal formation and promotes colonization and persistence through Als1. When Candida is found in the urine, physicians face the dilemma to treat or not, since its presence could represent commensalism or infection, resulting in inappropriate management. Candida spp., specifically Candida albicans, are the second most common cause of catheter-associated urinary tract infections (CAUTIs). Yet, the cellular and molecular details of C. albicans CAUTI are poorly understood. With the steady increase in catheter usage, combined with fungal infection mismanagement and treatment challenges, this question is of utmost public health importance. Here, for the first time, we characterized fungal mechanisms during CAUTI, finding that the catheterized bladder environment triggers Candida virulent programing, inducing Efg1-dependent hyphal morphogenesis, required for CAUTI establishment. Moreover, Als1, an Efg1-downstream effector, is necessary for in vitro and in vivo fibrinogen-biofilm formation and Als1 expression levels were crucial for fungal persistence during CAUTI. These findings unveil the mechanisms for fungal CAUTIs and identify potential treatment targets. Different contribution of the monkey prefrontal and premotor dorsal cortex in decision making during a transitive inference task Several studies have reported similar neural modulations between brain areas of the frontal cortex, such as the dorsolateral prefrontal (DLPFC) and the premotor dorsal (PMd) cortex, in tasks requiring encoding of the abstract rules for selecting the proper action. Here we compared the neuronal modulation of the DLPFC and PMd of monkeys trained to choose the higher rank from a pair of abstract images (target item), selected from an arbitrarily rank-ordered set (A>B>C>D>E>F) in the context of a transitive inference task. Once acquired by trial-and-error, the ordinal relationship between pairs of adjacent images (i.e., A>B; B>C; C>D; D>E; E>F), monkeys were tested in indicating the ordinal relation between items of the list not paired during learning. During these decisions, we observed that the choice accuracy increased and the reaction time decreased as the rank difference between the compared items enhanced. This result is in line with the hypothesis that after learning, the monkeys built an abstract mental representation of the ranked items, where rank comparisons correspond to the items position comparison on this representation. In both brain areas, we observed higher neuronal activity when the target item appeared in a specific location on the screen with respect to the opposite position and that this difference was particularly enhanced at lower degrees of difficulty. By comparing the time evolution of the activity of the two areas, we observed that the neural encoding of target item spatial position occurred earlier in the DLPFC than in the PMd. Effect of a low concentration in chloride, sodium and potassium on oocyte maturation, oocyte hydration, ovulation and egg quality in rainbow trout. Water salinity is an important environmental factor known to have detrimental effects on salmonid reproduction, mostly when migrating female broodfish are held in sea water. In contrast, data obtained in freshwater are scarce and the impact of low water salinity, and more specifically of low water concentrations in sodium, chloride and potassium, during reproduction in freshwater is currently unknown. For this reason, and because ion and water fluxes are critical for the final steps of the female gamete formation, including oocyte hydration and ovulation, the aim of the present study was to investigate the impact of low salinity water on final oocyte maturation, ovulation and, ultimately, on egg quality, using rainbow trout as a physiological model and relevant aquaculture species.

Fish from the same commercial strain were raised either in a site characterized by low concentrations of Na+, K+, and Cl- ions in the water or in a closely located control site exhibiting higher concentration in these elements. Egg quality and duration of final oocyte maturation were investigated using innovative phenotyping tools such as automatic assessment of egg viability using the VisEgg system and non-invasive echograph-based monitoring of final oocyte maturation duration, respectively. Oocyte hydration during final oocyte maturation and after ovulation was also investigated. Finally, molecular phenotyping was performed using real-time PCR-based monitoring of several key players of final oocyte maturation and ovulation associated with ion and water transport, inflammation, proteolytic activity, and coagulation. Oocyte hydration and gene expression data were analyzed in the light of the duration of final oocyte maturation.

Here we show that low water salinity (i.e., low water concentration in chloride, sodium and potassium) negatively influences final oocyte maturation, ovulation and, ultimately, egg quality. Low water salinity triggered delayed ovulation and lower oocyte viability. When investigating the impact of low water salinity on final oocyte maturation duration, individuals presenting the most severe phenotypes exhibited impaired oocyte hydration and abnormally reduced gene expression levels of several key players of the ovulatory process. While the under expression of water (i.e., aquaporins) and ion (i.e., solute carriers) transporters is consistent with impaired oocyte hydration, our observations also indicate that the overall ovulatory gene expression program is disrupted. Our results raise the question of the mechanisms underlying the negative influence of low salinity water on the dynamics of the preovulatory phase, on the control of the oocyte homeostasis, including hydration, and on the overall success of the maturation-ovulation process.

HighlightsO_LILow water salinity impairs final oocyte maturation and egg quality in rainbow trout
C_LIO_LILow water salinity induces delayed ovulation and impaired oocyte hydration
C_LIO_LILow water salinity induces a dysregulation of several key ovulatory genes
C_LIO_LIMonitoring of final oocyte maturation can be performed using ultrasound staging
C_LI Genetic diversity loss in the Anthropocene More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is key to maintaining adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging theories of biodiversity and population genetics, we introduce a mathematical framework to understand the loss of naturally occurring DNA mutations within decreasing habitat within a species. Analysing genome-wide variation data of 10,095 geo-referenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a power law with geographic area (the mutations-area relationship), which can predict genetic diversity loss in spatial computer simulations of local population extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may already be lost, surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly accelerate with advancing climate change and habitat destruction, highlighting the need for forecasting tools that facilitate implementation of policies to protect genetic resources globally. A high throughput lipidomics method using scheduled multiple reaction monitoring Lipid compositions of cells, tissues and bio-fluids are complex, with varying concentrations and structural diversity, which makes their identification challenging. Newer methods for comprehensive analysis of lipids are thus necessary. Herein, we propose a targeted-mass spectrometry based method for large-scale lipidomics using a combination of variable retention time window and relative dwell time weightage. Using this, we detected more than 1000 lipid species, including structural isomers. The limit of detection varied from femtomolar to nanomolar range and the coefficient of variance <30% for 849 lipid species. We used this method to identify lipids altered due to Vitamin B12 deficiency and found that the levels of lipids with {omega}-3 fatty acid chains decreased while those with {omega}-6 increased. This method enables identification of by far the largest number of lipid species with structural isomers in a single experiment and would significantly advance our understanding of the role of lipids in biological processes. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Alpha activity neuromodulation induced by individual alpha-based neurofeedback learning in ecological context: A double-blind randomized study The neuromodulation induced by neurofeedback training (NFT) remains a matter of debate. Investigating the modulation of brain activity specifically associated with NF requires controlling for multiple factors, such as reward, performance, congruency between task and targeted brain activity. This can be achieved using sham feedback (FB) control condition, equating all aspects of the experiment but the link between brain activity and FB. We aimed at investigating the modulation of individual alpha EEG activity induced by NFT in a double-blind, randomized, sham-controlled study. Forty-eight healthy participants were assigned to either NF (n=25) or control (n=23) group and performed alpha upregulation training (over 12 weeks) with a wearable EEG device. Participants of the NF group received FB based on their individual alpha activity. The control group received the auditory FB of participants of the NF group. An increase of alpha activity across training sessions was observed in the NF group only (p<0.001). This neuromodulation was selective in that it was not observed for theta (4-8Hz) and low beta (13-18Hz) activities. While alpha upregulation was found in the NF group only, psychological outcome variables showed increased feeling of control, decreased anxiety level and increased relaxation feeling in both the NF and control groups, without any significant difference between groups. This is interpreted in terms of learning context and placebo effects. Our results pave the way to self-learnt, NF-based neuromodulation with light-weighted, wearable EEG systems. A Bayesian model selection approach to mediation analysis Mediation analysis is a powerful tool for discovery of causal relationships. We describe a Bayesian model selection approach to mediation analysis that is implemented in our bmediatR software. Using simulations, we show that bmediatR performs as well or better than established methods including the Sobel test, while allowing greater flexibility in both model specification and in the types of inference that are possible. We applied bmediatR to genetic data from mice and human cell lines to demonstrate its ability to derive biologically meaningful findings. The Bayesian model selection framework is extensible to support a wide variety of mediation models. The chromatin factor ROW cooperates with BEAF-32 in regulating long-range inducible genes Insulator proteins located at the boundaries of topological associated domains (TAD) are involved in regulating chromatin loops. Yet, how chromatin loops contribute to transcription regulation is still not clear. Here we show that Relative-of-WOC (ROW) is essential for the long-range transcription regulation mediated by the Boundary Element-Associated Factor of 32kD (BEAF-32). We found that ROW physically interacts with heterochromatin proteins (HP1b and HP1c) and the insulator protein BEAF-32. The co-localization happens at TAD boundaries where ROW, through its AT-hooks motifs, binds AT-rich sequences flanked by BEAF-32 binding sites and motifs. Knockdown of row resulted in downregulation of genes that are long-range targets of BEAF-32 and bound indirectly by ROW (without binding motif). Analysis of high- throughput chromosome conformation capture (Hi-C) data revealed long-range interactions between promoters of housekeeping genes bound directly by ROW and promoters of developmental genes bound indirectly by ROW. Thus, our results show cooperation between BEAF-32 and the ROW complex, which includes HP1 proteins, to regulate the transcription of developmental and inducible genes by chromatin loops. Action at a distance: Defects in division plane positioning in the root meristematic zone affect cell organization in the differentiation zone Cell division plane orientation is critical for plant and animal development and growth. TANGLED1 (TAN1) and AUXIN-INDUCED-IN-ROOT-CULTURES9 (AIR9) are division-site localized microtubule-binding proteins required for division plane positioning. tan1 and air9 Arabidopsis thaliana single mutants have minor or no noticeable phenotypes but the tan1 air9 double mutant has synthetic phenotypes including stunted growth, misoriented divisions, and aberrant cell-file rotation in the root differentiation zone. These data suggest that TAN1 plays a role in nondividing cells. To determine whether TAN1 is required in elongating and differentiating cells in the tan1 air9 double mutant, we limited its expression to actively dividing cells using the G2/M-specific promoter of the syntaxin KNOLLE (pKN:TAN1-YFP). Unexpectedly, in addition to rescuing division plane defects, pKN:TAN1-YFP rescued root growth and the root differentiation zone cell file rotation defects in the tan1 air9 double mutant. This suggests that defects that occur in the meristematic zone later affect the organization of elongating and differentiating cells.

Summary StatementExpression of TAN1 in the root meristematic zone rescues cell file rotation defects in tan1 air9 mutants, suggesting defects that occur in mitosis may influence organization of nondividing cells. Mathematical Modeling and Analysis of Mitochondrial Retrograde Signaling Dynamics Mitochondria, semi-autonomous eukaryotic organelles, participate in energy production and metabolism, making mitochondrial quality control crucial. As most mitochondrial proteins are encoded by nuclear genes, quality control depends on proper mitochondria-nucleus communication, designated mitochondrial retrograde signaling. Early studies focused on retrograde signaling participants and specific gene knockouts. However, mitochondrial signal modulation remains elusive. Using yeast, we simulated signal propagation following mitochondrial damage and proposed a mathematical model based ordinary differential equations. Mitochondrial retrograde signaling decisions were described using a Boolean model. Dynamics were analyzed through an ordinary differential equation-based model and extended to evaluate the model response to noisy damage signals. Simulation revealed localized protein concentration dynamics, including waveforms, frequency response, and robustness under noise. Retrograde signaling is bistable with three localized steady states, and increased damage compromises robustness. We elucidated mitochondrial retrograde signaling, thus providing a basis for drug design against yeast and fungi.

Author SummaryThe yeast RTG pathway regulates mitochondrial metabolism and mitochondrial quality through passing mitochondrial signal to the nucleus to modulate gene expressions. Using microscopic data of RTG proteins translocation from cytosol to nucleus, the parameters were found by fitting 16 knockout conditions simulated from the proposed differential equation-based model. Further, through dose response, ultrasensitivity, frequency response and noise interference, we demonstrated a switch-like property of RTG pathway activation, a capacity charging property of RTG protein translocation, a low pass filter property of signals in different frequencies, and noise amplification due to mitochondrial signal. The proposed mathematical model enables us to understand the dynamics and mechanisms in mitochondrial retrograde signaling in yeast and provides potential antifungal treatment strategies. Modulation of RNA polymerase processivity affects double-strand break repair in the presence of a DNA end-binding protein Homologous recombination is the predominant double-strand DNA break repair pathway in Escherichia coli. A recent report of non-homologous end joining involving the Ku-like Gam protein of bacteriophage Mu (MuGam) has sparked interest in understanding the functions of DNA end-binding proteins in bacteria. MuGam binds to DNA ends, but how it interferes with DNA repair or transcription in live bacteria remains elusive. In E. coli, RNA polymerase secondary channel interactors, such as the Gre factors, play a role in coordinating transcription with DNA replication and break repair. Here we show that MuGam inhibits break repair by slowing down DNA resection and impeding recombination in living cells. Loss of GreA restores break repair in the presence of MuGam by allowing for increased DNA resection due to a potential release of MuGam from the DNA. Using MuGam as a DNA break sensor, we found that breaks are generated when translation is inhibited, more so in the presence of GreA, supporting the model where transcription-translation uncoupling increases transcription/replication collisions. Significantly, this work reveals that modulation of RNA polymerase can impact DNA break repair in presence of a Ku-like protein. A chemical screen based on an interruption of zebrafish gastrulation identifies the HTR2C inhibitor Pizotifen as a suppressor of EMT-mediated metastasis Metastasis is responsible for approximately 90% of cancer-associated mortality but few models exist that allow for rapid and effective screening of anti-metastasis drugs. Current mouse models of metastasis are too expensive and time consuming to use for rapid and high-throughput screening. Therefore, we created a unique screening concept utilizing conserved mechanisms between zebrafish gastrulation and cancer metastasis for identification of potential anti-metastatic drugs. We hypothesized that small chemicals that interrupt zebrafish gastrulation might also suppress metastatic progression of cancer cells and developed a phenotype-based chemical screen to test the hypothesis. The screen used epiboly, the first morphogenetic movement in gastrulation, as a marker and enabled 100 chemicals to be tested in five hours. The screen tested 1280 FDA-approved drugs and identified Pizotifen, an antagonist for serotonin receptor 2C (HTR2C) as an epiboly-interrupting drug. Pharmacologic and genetic inhibition of HTR2C suppressed metastatic progression in a mouse model. Blocking HTR2C with Pizotifen restored epithelial properties to metastatic cells through inhibition of Wnt-signaling. In contrast, HTR2C induced epithelial to mesenchymal transition (EMT) through activation of Wnt-signaling and promoted metastatic dissemination of human cancer cells in a zebrafish xenotransplantation model. Taken together, our concept offers a novel platform for discovery of anti-metastasis drugs. LinearTurboFold: Linear-Time Global Prediction of Conserved Structures for RNA Homologs with Applications to SARS-CoV-2 The constant emergence of COVID-19 variants reduces the effectiveness of existing vaccines and test kits. Therefore, it is critical to identify conserved structures in SARS-CoV-2 genomes as potential targets for variant-proof diagnostics and therapeutics. However, the algorithms to predict these conserved structures, which simultaneously fold and align multiple RNA homologs, scale at best cubically with sequence length, and are thus infeasible for coronaviruses, which possess the longest genomes ([~]30,000 nt) among RNA viruses. As a result, existing efforts on modeling SARS-CoV-2 structures resort to single sequence folding as well as local folding methods with short window sizes, which inevitably neglect long-range interactions that are crucial in RNA functions. Here we present LinearTurboFold, an efficient algorithm for folding RNA homologs that scales linearly with sequence length, enabling unprecedented global structural analysis on SARS-CoV-2. Surprisingly, on a group of SARS-CoV-2 and SARS-related genomes, LinearTurbo-Folds purely in silico prediction not only is close to experimentally-guided models for local structures, but also goes far beyond them by capturing the end-to-end pairs between 5 and 3 UTRs ([~]29,800 nt apart) that match perfectly with a purely experimental work. Furthermore, LinearTurboFold identifies novel conserved structures and conserved accessible regions as potential targets for designing efficient and mutation-insensitive small-molecule drugs, antisense oligonucleotides, siRNAs, CRISPR-Cas13 guide RNAs and RT-PCR primers. LinearTurboFold is a general technique that can also be applied to other RNA viruses and full-length genome studies, and will be a useful tool in fighting the current and future pandemics.

Significance StatementConserved RNA structures are critical for designing diagnostic and therapeutic tools for many diseases including COVID-19. However, existing algorithms are much too slow to model the global structures of full-length RNA viral genomes. We present LinearTurboFold, a linear-time algorithm that is orders of magnitude faster, making it the first method to simultaneously fold and align whole genomes of SARS-CoV-2 variants, the longest known RNA virus ([~]30 kilobases). Our work enables unprecedented global structural analysis and captures long-range interactions that are out of reach for existing algorithms but crucial for RNA functions. LinearTurboFold is a general technique for full-length genome studies and can help fight the current and future pandemics. Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. The glycocalyx affects the mechanotransductive perception of the topographical microenvironment The cell/microenvironment interface is the starting point of integrin-mediated mechanotransduction, but many details of mechanotransductive signal integration remain elusive due to the complexity of the involved (extra)cellular structures, such as the glycocalyx.

We used nano-bio-interfaces reproducing the complex nanotopographical features of the extracellular matrix to analyse the glycocalyx impact on PC12 cell mechanosensing at the nanoscale (e.g., by force spectroscopy with functionalised probes). Our data demonstrates that the glycocalyx configuration affects spatio-temporal nanotopography-sensitive mechanotransductive events at the cell/microenvironment interface. Opposing effects of glycocalyx removal were observed, when comparing flat and specific nanotopographical conditions. The excessive retrograde actin flow speed and force loading are strongly reduced on certain nanotopographies upon removal of the native glycocalyx, while on the flat substrate we observe the opposite trend.

Our results highlight the importance of the glycocalyx configuration in a molecular clutch force loading-dependent cellular mechanism for mechanosensing of microenvironmental nanotopographical features.