Microbial biomass, composition, and functions are responsible for the differential removal of trace organic chemicals in biofiltration systems Biofiltration processes help to remove trace organic chemicals (TOrCs) both in wastewater and drinking water treatment systems. However, the detailed TOrCs biotransformation mechanisms as well as the underlying drivers behind the variability of site specific transformation processes remain elusive. In this study, we used laboratory batch incubations to investigate the biotransformation of 51 TOrCs in eight bioactive filter materials of different origins treating a range of waters, from wastewater effluents to drinking water. Microscopy, 16S rRNA amplicon and whole metagenome sequencing for assessing associations between the biotransformation rate constants, microbial composition and genetic potential complemented chemical analysis. We observed strong differences in the mean global removal of TOrCs between the individual sand filters (-1.4% to 58%), which were mirrored in overall biomass, microbial community composition, and enzyme encoding genes. From the six investigated biomass markers, ATP turned out to be a major predictor of the mean global biotransformation rate, while compound specific biotransformations were correlated with the microbial community composition. High biomass ecosystems were indicated in our systems by a dominance of Nitrospirae, but individual TOrC biotransformation was statistically connected to rare taxa (< 2%) such as Hydrogenophaga, or indiviudal functions such as the enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase encoding genes. In general, this study provides new insights into so far rarely addressed variability of TOrCs biotransformation. We propose novel biological indicators for the removal performance of TOrCs in biofiltration systems, highlighting the role of living biomass in predicting and normalizing the global transformation, and the role of the microbial community for the individual transformation of TOrCs in engineered and natural systems.

Contribution to the Field StatementTrace organic chemicals (TOrCs) are an emerging problem in the aquatic environment that has attracted global attention over the last decade. Recent research efforts on this topic have increased our knowledge on the transformation of TOrCs and various technologies have been developed to improve their removal. In this study, we investigated a wide range of biotransformation of TOrCs by eight sand filter materials from wastewater and water treatment plants. Biotransformation rate constants were calculated using first-order kinetics to evaluate TOrC removal performance. We reevaluated the role of biomass and could thus explain a greater part of the global TOrC removal performance. The remaining variation in removal rates of individual compounds correlated with the microbiome of the biofilter. Rare biosphere lineages and specific enzyme categories genes were correlated with the removal of certain compounds. In summary, our research identified future indicators for successful biotransformation of TOrCs in biofilter systems.
Diversification of B. subtilis during experimental evolution on A. thaliana and the complementarity in root colonization of evolved subpopulations The soil bacterium Bacillus subtilis is known to suppress pathogens as well as promote plant growth. However, in order to fully exploit the potential as natural fertilizer, we need a better understanding of the interactions between B. subtilis and plants. Here, B. subtilis was examined for root colonization through experimental evolution on Arabidopsis thaliana. The populations evolved rapidly, improved in root colonization and diversified into three distinct morphotypes. In order to better understand the adaptation that had taken place, single evolved isolates from the final transfer were randomly selected for further characterization, revealing changes in growth and pellicle formation in medium supplemented with plant polysaccharides. Intriguingly, certain evolved isolates showed improved root colonization only on the plant species they evolved on, but not on another plant species, namely tomato, suggesting A. thaliana specific adaption paths. Finally, the mix performed better than the sum of its constituents in monoculture, which was demonstrated to be caused by complementarity effects. Our results suggest, that genetic diversification occurs in an ecological relevant setting on plant roots and proves to be a stable strategy for root colonization.

Significance StatementUnderstanding how plant-growth-promoting rhizobacteria (PGPR) colonize plant roots is crucial to fully utilize their potential for agricultural applications. Here, we employ experimental evolution of the PGPR Bacillus subtilis on Arabidopsis thaliana to study root colonization. We revealed that evolving populations rapidly improve in root colonization and diversify into distinct morphotypes. Notably, improved root colonization by evolved isolates was observed on A. thaliana, not on tomato. Moreover, isolates of distinct morphotypes interacted during root colonization and the mixture of morphotypes showed higher productivity than predicted. These findings suggest that genetic diversification might be a stable strategy to maximize root colonization.
Improving GWAS discovery and genomic prediction accuracy in Biobank data Genetically informed and deep-phenotyped biobanks are an important research resource. The cost of phenotyping far outstrips that of genotyping, and therefore it is imperative that the most powerful, versatile and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. On average, GMRM accuracies were 15% (SE 7%) greater than prediction models run in the LDAK software with SNP annotation marker groups, 18% (SE 3%) greater than a baseline BayesR model without SNP markers grouped into MAF-LD-annotation categories, and 106% (SE 9%) greater than polygenic risk scores calculated from mixed-linear model association (MLMA) estimates. For height, the prediction accuracy R2 was 47% in a UK Biobank hold-out sample, which was 76% of the estimated [Formula]. We then extend our GMRM prediction model to provide MLMA SNP marker estimates for GWAS discovery, which increased the independent loci detected to 7,910 in unrelated UK Biobank individuals, as compared to 5,521 from BoltLMM and 5,727 from Regenie, a 43% and 38% increase respectively. The average{chi} 2 value of the leading markers was 34% (SE 5.11) higher for GMRM as compared to Regenie, and increased by 17% for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modelling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and for discovery in large-scale individual-level biobank-scale studies. 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. Evidence for spatiotemporal shift in demersal fisheries management priority areas in the western Mediterranean Marine Protected Areas (MPAs) are a promising management tool for the conservation and recovery of marine ecosystems, as well as fisheries management. MPAs are generally established as permanent closures but marine systems are dynamic, which has generated debate in favour of more dynamic designs. As a consequence, the identification of priority areas should assess their persistence in space and time. Here, we develop a step-by-step approach to assess the spatiotemporal dynamics of fisheries management priority areas using standard fishery-independent survey data. To do so, we fit Bayesian hierarchical spatiotemporal SDM models to different commercially important demersal species and use the resulting maps to fit different spatial prioritisation configurations. We use these results to assess the spatiotemporal dynamics of fisheries priority areas. The proposed method is illustrated through a western Mediterranean case study using fishery-independent trawl survey data on six commercially important species collected over 17 years. We identified two fisheries priority area patterns in the study area, each predominant during a different time-period of the study, asserting the importance of regularly re-assessing MPA designs. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. MODEL PREDICTIVE CONTROL OF CANCER CELLULAR DYNAMICS: A NEW STRATEGY FOR THERAPY DESIGN Recent advancements in Cybergenetics have led to the development of new computational and experimental platforms that enable to robustly steer cellular dynamics by applying external feedback control. Such technologies have never been applied to regulate intracellular dynamics of cancer cells. Here, we show in silico that adaptive model predictive control (MPC) can effectively be used to steer signalling dynamics in Non-Small Cell Lung Cancer (NSCLC) cells to resemble those of wild-type cells, and to support the design of combination therapies. Our optimisation-based control algorithm enables tailoring the cost function to force the controller to alternate different drugs and/or reduce drug exposure, minimising both drug-induced toxicity and resistance to treatment. Our results pave the way for new cybergenetics experiments in cancer cells for drug combination therapy design. B1 SINE-binding ZFP266 impedes reprogramming through suppression of chromatin opening mediated by pioneering factors Induced pluripotent stem cell reprogramming is inherently inefficient and understanding the molecular mechanisms underlying this inefficiency holds the key to successfully control cellular identity. Here, we report 16 novel reprogramming roadblock genes identified by CRISPR/Cas9-mediated genome-wide knockout (KO) screening. Of these, depletion of the predicted KRAB zinc finger protein (KRAB-ZFP) Zfp266 strongly and consistently enhanced iPSC generation in several iPSC reprogramming settings, emerging as the most robust roadblock. Further analyses revealed that ZFP266 binds Short Interspersed Nuclear Elements (SINEs) adjacent to binding sites of pioneering factors, OCT4 (POU5F1), SOX2 and KLF4, and impedes chromatin opening. Replacing the KRAB co-suppressor with a co-activator domain converted ZFP266 from a reprogramming inhibitor to a potent reprogramming facilitator. This work proposes SINE-KRAB-ZFP interaction to be a critical regulator of chromatin accessibility at enhancers for efficient cellular identity changes and also serves as a resource to further illuminate molecular mechanisms hindering reprogramming. A vascularized tumoroid model for human glioblastoma angiogenesis Glioblastoma (GBM) angiogenesis is critical for tumor growth and recurrence, making it a compelling therapeutic target. Here, a disease-relevant, vascularized tumoroid in vitro model with stem-like features and stromal surrounds is reported. The model is used to recapitulate how individual components of the GBMs complex brain microenvironment such as hypoxia, vasculature-related stro-mal cells and growth factors support GBM angiogenesis. It is scalable, tractable, cost-effective and can be used with biologically-derived or biomimetic matrices. Patient-derived primary GBM cells are found to closely participate in blood vessel formation in contrast to a GBM cell line containing differentiated cells. Exogenous growth factors amplify this effect under normoxia but not at hypoxia suggesting that a significant amount of growth factors is already being produced under hypoxic conditions. Under hypoxia, primary GBM cells and umbilical vein endothelial cells are found to strongly co-localize in a mosaic pattern to form sprouting vascular networks, with GBM cells acquiring an endothelial-like behaviour, which has been reported to occur in vivo. These findings demonstrate that our 3D tumoroid in vitro model exhibits biomimetic attributes that may permit its use as a preclinical model in studying microenvironment cues of tumor angiogenesis. Deep learning-based real-time detection of novel pathogens during sequencing Novel pathogens evolve quickly and may emerge rapidly, causing dangerous outbreaks or even global pandemics. Next-generation sequencing is the state-of-the-art in open-view pathogen detection, and one of the few methods available at the earliest stages of an epidemic, even when the biological threat is unknown. Analyzing the samples as the sequencer is running can greatly reduce the turnaround time, but existing tools rely on close matches to lists of known pathogens and perform poorly on novel species. Machine learning approaches can predict if single reads originate from more distant, unknown pathogens, but require relatively long input sequences and processed data from a finished sequencing run. Incomplete sequences contain less information, leading to a trade-off between sequencing time and detection accuracy. Using a workflow for real-time pathogenic potential prediction, we investigate which subsequences already allow accurate inference. We train deep neural networks to classify Illumina and Nanopore reads and integrate the models with HiLive2, a real-time Illumina mapper. This approach outperforms alternatives based on machine learning and sequence alignment on simulated and real data, including SARS-CoV-2 sequencing runs. After just 50 Illumina cycles, we observe an 80-fold sensitivity increase compared to real-time mapping. The first 250bp of Nanopore reads, corresponding to 0.5s of sequencing time, are enough to yield predictions more accurate than mapping the finished long reads. The approach could also be used for screening synthetic sequences against biosecurity threats. Dynamical interactions reconfigure the gradient of cortical timescales A hierarchy of local timescales with a back (sensory)-to-front (prefrontal) gradient reflects brain region specialization. However, cognitive processes emerge from the coordinated activity across regions, and the corresponding timescales should refer to the interactions rather than to regional activity. Using edgewise connectivity on magnetoencephalography signals, we demonstrate a reverse front-to-back gradient when non-local interactions are prominent. Thus, the timescales are dynamic and reconfigure between back-to-front and front-to-back patterns. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Hidden dynamics of human proteasome autoregulation during protein degradation The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation. Microbial colonization of tannin-rich tropical plants: interplay between degradability, methane production and tannin disappearance in the rumen AO_SCPLOWBSTRACTC_SCPLOWCondensed tannins in plants are found free and attached to protein and fibre but it is not known whether these fractions influence rumen degradation and microbial colonization. This study explored the rumen degradation of tropical tannins-rich plants and the relationship between condensed tannins fractions disappearance and microbial communities colonising plant particles. Leaves from Calliandra calothyrsus, Gliricidia sepium, and Leucaena leucocephala, pods from Acacia nilotica and the leaves of two agricultural by-products: Manihot esculenta and Musa spp. were incubated in situ in the rumen of dairy cows. An in vitro approach was also used to assess the effects of these plants on rumen fermentation parameters. All plants contained more than 100 g/kg of condensed tannins with a large proportion (32 to 61%) bound to proteins. Calliandra calothyrsus had the highest concentration of condensed tannins at 361 g/kg, whereas Acacia nilotica was particularly rich in hydrolysable tannins (350 g/kg). Hydrolysable and free condensed tannins from all plants completely disappeared after 24 h incubation in the rumen. Disappearance of protein-bound condensed tannins was variable with values ranging from 93% for Gliricidia sepium to 21% for Acacia nilotica. In contrast, fibre-bound condensed tannins disappearance averaged ~82% and did not vary between plants. Disappearance of bound fractions of condensed tannins was not associated with degradability of plant fractions. The presence of tannins interfered with the microbial colonisation of plants. Each plant had distinct bacterial and archaeal communities after 3 and 12 h of incubation in the rumen and distinct protozoal communities at 3 h. Adherent communities in tannin-rich plants had a lower relative abundance of fibrolytic microbes, notably Fibrobacter spp. Whereas, archaea diversity was reduced in high tannin-containing Calliandra calothyrsus and Acacia nilotica at 12 h of incubation. Concurrently, in vitro methane production was lower for Calliandra calothyrsus, Acacia nilotica and Leucaena leucocephala although for the latter total volatile fatty acids production was not affected and was similar to control. Here we show that the total amount of hydrolysable and condensed tannins contained in a plant govern the interaction with rumen microbes affecting degradability and fermentation. The effect of protein- and fibre-bound condensed tannins on degradability is less important. CellKb Immune: a manually curated database of hematopoietic marker gene sets from 7 species for rapid cell type identification Using single-cell RNA sequencing, it is now possible to get the detailed gene expression pattern in each cell for millions of cells in a single experiment under varying conditions. Annotating cells by assigning a type or state to them is important for correct interpretation of results. In spite of current advances in technology, assigning cell types in single-cell datasets remains a bottleneck due to the lack of a comprehensive reference database and an accurate search method in a single tool. CellKb Immune is a knowledgebase of manually collected, curated and annotated marker gene sets representing cell types in the immune response in mouse. It allows users to find matching cell types in literature given a list of genes. We evaluated the contents and search methodology of CellKb Immune using a leave-one-out approach. We further used CellKb Immune to annotate previously defined marker gene sets from a bulk RNA-seq dataset to confirm its accuracy and coverage. CellKb Immune provides an easy-to-use online tool with a reliable method to find matching cell types and annotate cells in single-cell experiments. It is available at https://www.cellkb.com/immune. Creatine transporter deficient rat model show motor dysfunction, cerebellar alterations and muscle creatine deficiency without muscle atrophy Creatine (Cr) is a nitrogenous organic acid and plays roles as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy and motor dysfunction. Among CCDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8Y389C knock-in (KI) rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunction, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. Structure-Functional-Selectivity Relationship Studies on A-86929 Analogs and Small biaryl Fragments toward Discovery of biased D1 agonists Dopamine regulates normal functions such as movement, reinforcement learning, and cognition, and its dysfunction has been implicated in multiple psychiatric and neurological disorders. Dopamine acts through the D1- (D1R and D5R) and D2-class (D2R, D3R and D4R) of seven transmembrane receptors, and activates both G-protein- and {beta}-arrestin-dependent signaling pathways, to mediate its physiological effects. Current dopamine receptor-based therapies are used to ameliorate motor deficits in Parkinsons disease, or as antipsychotic medications for schizophrenia. These drugs show efficacy for ameliorating only some symptoms caused by dopamine dysfunction and are plagued by debilitating side-effects. Studies in primates and rodents have shown that shifting the balance of dopamine receptor signaling towards the arrestin pathway can be beneficial for inducing normal movement, while reducing motor side-effects such as dyskinesias, and can be efficacious at enhancing cognitive function compared to balanced agonists. Several structure-activity-relationship (SAR) studies have embarked on discovering {beta}-arrestin-biased dopamine agonists, focused on D2 partial agonists, non-catechol D1 agonists, and mixed D1/D2R dopamine receptor agonists. Here, we describe an SAR study to identify novel D1R {beta}-arrestin biased ligands using A-86929, a high-affinity D1R catechol agonist, as a core scaffold. Previously described and novel analogs of A-86929 were synthesized and screened in vitro for structure-functional-selectivity relationships (SFSR) studies to identify chemical motifs responsible for {beta}-arrestin biased activity at both D1 and D2Rs. Most of the A-86929 analogs screened were G protein biased but none of them were exclusively arrestin-biased. Additionally, various catechol aryl fragments were designed and synthesized. Other compounds surveyed included hydroxyl and chloro analogs of dopamine to test for hydrogen bonding and ionic interactions. Some of these small molecular probes displayed weak bias towards the {beta}-arrestin pathway. Continued in-depth SFSR studies informed by structure determination, molecular modeling, and mutagenesis studies will facilitate discovery of potent and efficacious arrestin-biased dopamine receptor ligands. Wnt target enhancer regulation by a CDX/TCF transcription factor collective and a novel DNA motif Transcriptional regulation by Wnt signalling is primarily thought to be accomplished by a complex of {beta}-catenin and TCF family transcription factors (TFs). Although numerous studies have suggested that additional TFs play roles in regulating Wnt target genes, their mechanisms of action have not been investigated in detail. We characterised a Wnt-responsive element (WRE) downstream of the Wnt target gene Axin2 and found that TCFs and Caudal-related homeodomain (CDX) proteins were required for its activation. Using a new separation-of-function TCF mutant, we found that WRE activity requires the formation of a TCF/CDX complex. Our systematic mutagenesis of this enhancer identified other sequences essential for activation by Wnt signalling, including several copies of a novel CAG DNA motif. Computational and experimental evidence indicates that the TCF/CDX/CAG mode of regulation is prevalent in multiple WREs. Put together, our results demonstrate the complex nature of cis- and trans- interactions required for signal-dependent enhancer activity. 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. Loss of histone methyltransferase SETD1B in oogenesis results in the redistribution of genomic histone 3 lysine 4 trimethylation Histone 3 lysine 4 trimethylation (H3K4me3) is an epigenetic mark found at gene promoters and CpG islands. H3K4me3 is essential for mammalian development, yet mechanisms underlying its genomic targeting are poorly understood. H3K4me3 methyltransferases SETD1B and MLL2 are essential for oogenesis. We investigated changes in H3K4me3 in Setd1b conditional knockout (cKO) oocytes using ultra-low input ChIP-seq, with comparisons to DNA methylation and gene expression analyses. H3K4me3 was redistributed in Setd1b cKO oocytes showing losses at active gene promoters associated with downregulated gene expression. Remarkably, many regions also gained H3K4me3, in particular those that were DNA hypomethylated, transcriptionally inactive and CpG-rich, which are hallmarks of MLL2 targets. Consequently, loss of SETD1B disrupts the balance between MLL2 and de novo DNA methyltransferases in determining the epigenetic landscape during oogenesis. Our work reveals two distinct, complementary mechanisms of genomic targeting of H3K4me3 in oogenesis, with SETD1B linked to gene expression and MLL2 to CpG content.

Graphical AbstractIn oogenesis, SETD1B and CXXC1 target H3K4me3 to actively transcribed gene promoters, while MLL2 targets transcriptionally inactive regions based on underlying CpG composition (upper panel). When SETD1B is ablated, H3K4me3 is lost at a subset of active promoters, resulting in downregulation of transcription (lower panel). Loss of SETD1B alters the activity of MLL2, permitting MLL2 to deposit H3K4me3 at CpG-rich regions, many of which should otherwise be DNA methylated. Thus, it is evident that MLL2 and de novo DNMTs compete for genomic occupancy late in oogenesis, and loss of SETD1B disrupts the balance of these mechanisms.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Visualizing cancer-originated acetate uptake through MCT1 in reactive astrocytes demarcates tumor border and extends survival in glioblastoma patients Glioblastoma multiforme (GBM) is a devastating brain tumor with dismal prognosis of only 15-month survival regardless of surgical resection. Here, we report an advanced neuroimaging technique combining 11C-acetate PET and MRI (AcePET), visualizing the boundary beyond the MRI-defined tumor. Targeted biopsy of the regions with increased 11C-acetate uptake revealed the presence of reactive astrocytes with enhanced acetate-transporter MCT1, along with cancer stem cells. Reactive astrogliosis and MCT1-dependent 11C-acetate-uptake were recapitulated in U87MG-orthotopic models. Mechanistically, glycolytic tumor cells release excessive acetate causing reactive astrogliosis, leading to the release of aberrant astrocytic GABA and H2O2, which further down-regulate the neuronal glucose uptake through GLUT3. Clincally, AcePET-guided surgery allows complete tumor resection of infiltrating cancer stem cells and extends the overall survival of patients by 5.25 months compared to conventional MRI-guided surgery. We established a new concept of the metabolic interactions between GBM cells and neighboring neurons through reactive astrocytes and developed AcePET-guided surgery to fight against GBM. Pulsatile contractions and pattern formation in excitable actomyosin cortex The actin cortex is an active adaptive material, embedded with complex regulatory networks that can sense, generate, and transmit mechanical forces. The cortex exhibits a wide range of dynamic behaviours, from generating pulsatory contractions and travelling waves to forming organised structures. Despite the progress in characterising the biochemical and mechanical components of the actin cortex, the emergent dynamics of this mechanochemical system is poorly understood. Here we develop a reaction-diffusion model for the RhoA signalling network, the upstream regulator for actomyosin assembly and contractility, coupled to an active actomyosin gel, to investigate how the interplay between chemical signalling and mechanical forces regulate stresses and patterns in the cortex. We demonstrate that mechanochemical feedback in the cortex acts to destabilise homogeneous states and robustly generate pulsatile contractions. By tuning active stress in the system, we show that the cortex can generate propagating contraction pulses, form network structures, or exhibit topological turbulence. Diurnal activity budget and conservation implication of Hippopotamus amphibius at Bui National Park, Ghana Animals apportion time for their daily behavioral activities. We studied the activity budget of Hippopotamus amphibius at the Black Volta River in the Bui National Park, Ghana. We performed instantaneous scan sample using ground count survey between August 2020 to July 2021. We observed that H. amphibius spent most of their day time resting (54.75 %), followed by feeding (22.93 %), walking (19.2 %) and touching (3.12 %). We found significant difference in the time spent between the daily activities (H = 41.67; p < 0.0001). Except activities involving touching, we found no significant seasonal differences in feeding, resting and walking activities by H. amphibius. Understanding the behavioral activities of H. amphibius will enhance management and conservation of the animals. The mutation effect reaction norm (Mu-RN) highlights environmentally dependent mutation effects and genetic interactions Since the modern synthesis, the fitness effects of mutations and epistasis have been central yet provocative concepts in evolutionary and population genetics. Studies of how the interactions between parcels of genetic information can change as a function of environmental context have added a layer of complexity to these discussions. Here I introduce the "mutation effect reaction norm" (Mu-RN), a new instrument through which one can analyze the phenotypic consequences of mutations and interactions across environmental contexts. It embodies the fusion of measurements of genetic interactions with the reaction norm, a classic depiction of the performance of genotypes across environments. I demonstrate the utility of the Mu-RN through the signature of a "compensatory ratchet" mutation that undermines reverse evolution of antimicrobial resistance. More broadly, I argue that the mutation effect reaction norm may help us resolve the dynamism and unpredictability of evolution, with implications for theoretical biology, genetic modification technology, and public health. Epitope-tagging of the endogenous murine BiP/GRP78/Hspa5 locus allows direct analysis of the BiP interactome and protein misfolding in vivo BiP/GRP78, encoded by the Hspa5 gene, is the major HSP70 family member in the endoplasmic reticulum (ER) lumen, and controls ER protein folding. The essential functions of BiP in facilitating proper protein folding are mainly mediated through its dynamic interaction with unfolded or misfolded client proteins, and by serving as a negative regulator of the Unfolded Protein Response. A mechanistic understanding of the dynamics of BiP interaction with its protein partners is essential to understand ER biology, and therefore, we have sought to develop a tractable model to study misfolded protein interaction with BiP. For this purpose, we have used homologous recombination to insert a 3xFLAG epitope tag into the endogenous murine Hspa5 gene, just upstream from the essential KDEL signal necessary for ER localization of BiP. Tagging BiP in this way did not alter Hspa5 expression under basal or ER-stress induced conditions in hepatocytes ex vivo or in fibroblasts. Furthermore, the tag did not alter the cellular localization of BiP or its functionality. All of these findings in primary tissue culture were also confirmed in vivo in livers of heterozygous mice harboring one WT and one FLAG-tagged Hspa5 allele. Hepatocyte-specific BiP-FLAG modification did not alter liver function or UPR signaling. Importantly, immunoprecipitation with anti-FLAG antibody completely pulled down FLAG-tagged BiP from lysates of BiP-FLAG expressing livers. Affinity purification-mass spectrometry (AP-MS) of BiP-FLAG protein complexes isolated from the BiP-FLAG-expressing livers of tunicamycin (TM)- and vehicle-treated mice revealed a marked increase in interaction of glycoproteins with BiP-FLAG in response to inhibition of N-glycosylation due to TM-treatment, validating utility of our BiP-Flag mice as a tool to identify ER misfolded proteins in vivo. Significantly, our AP-MS analysis also provided in vivo evidence demonstrating that BiP-FLAG binds to UPR transducers IRE1 and PERK under basal conditions but is released upon TM-treatment to activate UPR. We have also employed this mouse model to demonstrate that proinsulin in pancreatic {beta} cells misfolds and interacts with BiP-FLAG in healthy mice. In summary, we generated a novel model that can be used to investigate the BiP interactome in vivo under physiological and pathophysiological conditions in a cell type-specific manner. This tool provides, for the first time, an unbiased approach to identify unfolded and misfolded BiP-client proteins, and a new approach to study ER protein misfolding in a cell-type and temporal manner to uncover the role of BiP in many essential ER processes.