A cell cycle-dependent GARP-like transcriptional repressor regulates the initiation of differentiation in Giardia lamblia Transcriptional regulation of differentiation is critical for parasitic pathogens to adapt to environmental changes and regulate transmission. In response to encystation stimuli, Giardia lamblia cells shift from G1+S phase of the cell cycle to G2+M. By 2-4 hours, cyst wall proteins are upregulated, indicating that key regulatory steps occur within the first four hours of encystation. However, all characterized transcription factors (TFs) in Giardia have only been investigated at later time points of encystation. How TFs initiate encystation and link it to the cell cycle remains enigmatic. Here, we systematically screened six putative early upregulated TFs for nuclear localization, established their dynamic expression profiles, and determined their functional role in regulating encystation. We found a critical repressor, GLP4 that increases rapidly after 30 min of encystation stimuli and downregulates encystation specific markers, including Cyst Wall Proteins (CWPs) and enzymes in the cyst N-acetyl galactosamine (GalNAc) pathway. Depletion of GLP4 increases cyst production. Importantly, we observe that G2+M cells exhibit higher levels of CWP1 resulting from the activation of MYB2, a TF previously linked to encystation in Giardia. GLP4 upregulation occurs in G1+S cells, suggesting a role in repressing MYB2 and encystation specific genes in the G1+S phase of the cell cycle. Furthermore, we demonstrate that depletion of GLP4 upregulates MYB2 and promotes encystation while overexpression of GLP4 downregulates MYB2 and represses encystation. Together, these results suggest that Giardia employs a dose-dependent transcriptional response that involves the cell cycle regulated repressor GLP4 to orchestrate MYB2 and entry into the encystation pathway.

ImportanceTransition between life cycle stages is a common feature among parasitic pathogens and its regulation must be optimized to balance persistence of infection with transmission. The early transcription factors (TFs) regulating commitment to differentiate are totally unknown in Giardia. In this work, we identified GLP4, a previously uncharacterized GARP-like TF, as an early-acting transcriptional repressor that inhibits G1+S cells from entering the encystation pathway. GLP4 is therefore a key regulator controlling the balance between proliferative growth and terminal differentiation into infective cysts.
Mouse CHD4-NURD is required for spermatogonia survival and normal meiotic progression Testis development and sustained germ cell production in adults rely on the establishment and maintenance of spermatogonia stem cells and their proper differentiation into spermatocytes. Chromatin remodeling complexes regulate critical processes during gamete development by restricting or promoting accessibility of DNA repair and gene expression machineries to the chromatin. Here, we investigated the role of CHD4 and CHD3 catalytic subunits of the NURD complex during spermatogenesis. Germ cell-specific deletion of Chd4 early in gametogenesis, but not Chd3, resulted in arrested early gamete development due to failed cell survival of neonate undifferentiated spermatogonia stem cell population. Candidate assessment revealed that CHD4 controls expression of Dmrt1 and its downstream target Plzf, both described as prominent regulators of spermatogonia stem cell maintenance. Our results show the requirement of CHD4 in mammalian gametogenesis pointing to functions in gene expression early in the process.
Macroscopic control of synchronous electrical signaling with chemically-excited gene expression Excitable cells can convert electrical signals into chemical outputs to facilitate the active transport of information across larger distances. This electrical-to-chemical conversion requires a tightly regulated expression of ion channels. Alterations of ion channel expression provide landmarks of numerous pathological diseases, such as cardiac arrhythmia, epilepsy, or cancer. Although the activity of ion channels can be locally regulated by external light or chemical stimulus, it remains challenging to coordinate the expression of ion channels on extended spatial-temporal scales in a non-invasive manner. Here, we have engineered yeast S. cerevisiae to read and convert local chemical concentrations into a dynamic electrical field distributed across cell populations. The core mechanism encodes a chemically-excitable dual-feedback gene circuit that precisely tunes the expression domain of potassium channels, globally coordinating cyclic firing of the plasma membrane potential (PMP). We demonstrate that this mechanism leverages an engineered constitutively open bacterial potassium channel KcsA to directly couple chemical stimuli with ion flux through gene expression and it can interface with the host ion channels through the pulsatile production of toxins. Our study provides a robust synthetic transcriptional toolbox underlying the conversion of local chemical environments into spatiotemporally organized electrical impulses for various cellular engineering, synthetic biology, and potential therapeutic applications. The impact of obesity; key features of raised intracranial pressure and clinical sequalae in rodents Elevated intracranial pressure (ICP) is observed in many brain disorders. Obesity has been linked to ICP pathogenesis in disorders such as idiopathic intracranial pressure (IIH). We investigated the effect of diet induced obesity (DIO) on ICP and clinically relevant sequelae.

Rats were fed either a control or high fat diet. Following weight gain long term ICP, headache behavior, body composition and retinal outcome were examined. Post-hoc analysis of retinal histology and molecular analysis of choroid plexus and trigeminal ganglion (TG) were performed.

DIO rats demonstrated raised ICP by 55% which correlated with the abdominal fat percentage and increased non-respiratory slow waves, suggestive of altered cerebral compliance. Concurrently, DIO rats demonstrated a specific cephalic cutaneous allodynia which negatively correlated with the abdominal fat percentage. This sensitivity was associated with increased expression of headache markers in TG. Additionally, DIO rats had an in vivo increased retinal nerve fiber layer thickness associated with raised ICP with a subsequent post-hoc demonstration of neuroretinal degeneration.

This study demonstrates for the first time that DIO leads to raised ICP and subsequent clinically relevant symptom development. This novel model of non-traumatic raised ICP could expand the knowledge regarding disorders with elevated ICP such as IIH. Honeybee cognition as a tool for scientific engagement In addition to the crowdsourcing of experimental data, citizen science, and scientific engagement more broadly, serve as a bridge between researchers and the wider community. This serves to foster a greater understanding of the scientific method and science-based solutions generally. Apis mellifera (honeybees) are a well-established model for the study of learning and cognition and can serve as an engaging outreach system for this wider community. Here, we developed and implemented a protocol using well established honeybee conditioning protocols to safely study the effects of caffeine and dopamine on learning performance. Using this protocol, a group of high-school aged students as part of the Ryukyu Girls program demonstrated that caffeine, but not dopamine, significantly reduced the number of trials required for a successful conditioning response. This allowed these students to explore the scientific method in a relatable and engaging way.

Simple SummaryGlobal scientific literacy can be improved through widespread and effective community engagement by researchers. We propose Apis mellifera (honeybee) as an public engagement tool due to widespread awareness of colony collapse and the bees importance in food production. Moreover, their cognitive abilities make for engaging experiments. Their relative ease of cultivation means that studies can be performed cost-effectively, especially when partnering with local aperists. Using a proxy for honeybee learning, a group of non-specialist high-school-aged participants obtained data suggesting that caffeine, but not dopamine, improved learning. This hands-on experience facilitated student understanding of the scientific method, factors that shape learning and the importance of learning for hive health. DetecDiv, a generalist deep-learning platform for automated cell division tracking and survival analysis Automating the extraction of meaningful temporal information from sequences of microscopy images represents a major challenge to characterize dynamical biological processes. So far, strong limitations in the ability to quantitatively analyze single-cell trajectories have prevented large-scale investigations to assess the dynamics of entry into replicative senescence in yeast. Here, we have developed DetecDiv, a microfluidic-based image acquisition platform combined with deep learning-based software for high-throughput single-cell division tracking. We show that DetecDiv can automatically reconstruct cellular replicative lifespans with high accuracy and performs similarly with various imaging platforms and geometries of microfluidic traps. In addition, this methodology provides comprehensive temporal cellular metrics using time-series classification and image semantic segmentation. Last, we show that this method can be further applied to automatically quantify the dynamics of cellular adaptation and the real-time cell survival upon exposure to environmental stress. Hence, this methodology provides an all-in-one toolbox for high-throughput phenotyping for cell cycle, stress response, and replicative lifespan assays. 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. Inhibition of microbial deconjugation of micellar bile acids protects against intestinal permeability and liver injury Altered host-microbe interactions and increased intestinal permeability have been implicated in the pathogenesis of a range of diseases. However, the mechanisms by which gut microbes affect epithelial barrier integrity remain unclear. Few host-produced metabolites that protect against epithelial damage have been identified, and whether microbial metabolism of host factors alters intestinal barrier function is unknown. Here, we investigate the effects of bacterial metabolism of host-produced bile acid (BA) metabolites on epithelial barrier integrity. We observe that rats fed a choline-deficient, high-fat diet (CDAHFD) exhibit reduced abundance of host-produced conjugated BAs in the intestine at early timepoints coinciding with increased permeability. We show that in vitro, conjugated BAs protect gut epithelial monolayers from damage caused by bacterially produced unconjugated BAs through micelle formation. We then demonstrate that inhibition of BA deconjugation using a small molecule inhibitor of gut bacterial bile salt hydrolase (BSH) enzymes prevents development of pathologic intestinal permeability and hepatic inflammation in CDAHFD-fed rats. Finally, we show that the predominant conjugated BAs in humans protect against epithelial barrier disruption in vitro. Our study identifies a protective role for conjugated BAs in intestinal epithelial barrier function and suggests that rational manipulation of microbial BA metabolism could be leveraged to regulate gut barrier integrity. wnt16 exerts pleiotropic effects on bone and lean mass in zebrafish Osteoporosis, a disease of bone fragility, and sarcopenia, a condition of reduced muscle mass and strength, commonly occur in the same individual--a condition termed osteosarcopenia. Genetic variants at the CPED1-WNT16 locus have pleiotropic effects on human bone mineral density (BMD) and lean tissue mass. However, our current understanding of Wnt16 and its influence on bone fails to explain effects on lean mass at this locus. In this study, we sought to better understand the biological mechanism underlying pleiotropy at the CPED1-WNT16 locus on BMD and lean mass. Using single cell analysis, microCT imaging, and genetic approaches in zebrafish, we show that wnt16 exerts dual influence on muscle and bone, and provide evidence that this occurs through a function in somite development, a period in which precursors for both of these tissues are specified. We show that mutations in wnt16 alter vertebral size and lean mass during axial skeletogenesis. We show that wnt16+ cells transcriptionally resemble cells within the amniote dermomyotome, and provide evidence they function as myogenic precursors during embryonic development. We also provide evidence that WNT16 is a gene of major effect on lean mass at the CPED-WNT16 locus. Our studies support the potential for wnt16 to exert pleiotropic effects on bone and lean mass through a function in myogenic precursors. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. Crystal structures of alphavirus nonstructural protein 4 (nsP4) reveal an intrinsically dynamic RNA-dependent RNA polymerase fold. Alphaviruses such as Ross River virus (RRV), chikungunya virus, Sindbis virus (SINV), and Venezuelan equine encephalitis virus are mosquito-borne pathogens that can cause arthritis or encephalitis diseases. Nonstructural protein 4 (nsP4) of alphaviruses possesses RNA-dependent RNA polymerase (RdRp) activity essential for viral RNA replication. No 3D structure has been available for nsP4 of any alphaviruses despite its importance for understanding alphaviral RNA replication and for the design of antiviral drugs. Here, we report crystal structures of the RdRp domain of nsP4 from both RRV and SINV determined at resolutions of 2.6 and 1.9 [A]. The structure of the alphavirus RdRp domain appears most closely related to RdRps from pestiviruses, noroviruses, and picornaviruses. Hydrogendeuterium exchange mass spectrometry (HDX-MS) and nuclear magnetic resonance (NMR) methods, showed that in solution, nsP4 is highly dynamic with an intrinsically disordered N-terminal domain. Both full-length nsP4 and the RdRp domain were capable to catalyze RNA polymerization. Structure-guided mutagenesis using a trans-replicase system identified nsP4 regions critical for viral RNA replication.

Key PointsO_LICrystal structures of alphavirus nsP4 RNA polymerase domain from RRV and SINV.
C_LIO_LInsP4 protein is highly dynamic with an intrinsically disordered N-terminal domain.
C_LIO_LIOptimized RNA elongation activity assay to facilitate antiviral discovery.
C_LI 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. Cell type-specific inference of differential expression in spatial transcriptomics Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed (DE) within specific cell types across tissue context. We show that current approaches cannot learn cell type-specific DE due to changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type. Here, we introduce a statistical method, Cell type-Specific Inference of Differential Expression (C-SIDE), that identifies cell type-specific patterns of differential gene expression while accounting for localization of other cell types. We model spatial transcriptomics gene expression as an additive mixture across cell types of general log-linear cell type-specific expression functions. This approach provides a unified framework for defining and identifying gene expression changes in a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MER-FISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimers mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our C-SIDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr. Transcriptional condensates formed by phase-separated ALOG family proteins control shoot meristem maturation for flowering Plants have evolved remarkable diversity in inflorescence architecture. At the center of this diversity lies a meristem maturation program featured by transition of stem cell populations from a vegetative state into a reproductive growth, determining when, where, and how many flowers are produced on inflorescences. Here we identified a new meristem maturation regulator TMF FAMILY MEMBER3 (TFAM3) that encodes an ALOG family transcription factor. Loss of TFAM3 results in early flowering and simplified inflorescences with fewer flowers. Genetic analysis by creating high-order mutants of TFAM3 with three key regulators of tomato shoot meristem maturation, TERMINATING FLOWER (TMF), TMF FAMILY MEMBER1 (TFAM1) and TMF FAMILY MEMBER2 (TFAM2), suggested that they synergistically control flowering transition and inflorescence architecture. The four paralogous ALOG proteins share the prion-like properties and undergo liquid-liquid phase separation in vitro. Strikingly, TMF can recognize cognate TFAM proteins and selectively recruit them into phase separated condensates. Supporting this, they interact with themselves and each other to form biomolecular condensates in the nucleus. Their interaction induces formation of transcriptional condensates that directly repress expression of floral identity gene ANANTHA. Our study revealed a selective-recruitment phase separation mechanism for transcriptional condensation by which plants achieve optimal coordination of functional overlapped paralogs within a protein family to enable precise control of shoot meristem maturation for flowering and production of compound inflorescences. SyMBac: Synthetic Micrographs for Training Deep Neural Networks for Accurate Segmentation of Bacterial Cells We present a novel method of bacterial image segmentation using machine learning based on Synthetic Micrographs of Bacteria (SyMBac). SyMBac allows for rapid, automatic creation of arbitrary amounts of training data that combines detailed models of cell growth, physical interactions, and microscope optics to create synthetic images which closely resemble real micrographs, with access to the ground truth positions of cells. This approach provides the following major advantages: (1) Synthetic training data can be generated virtually instantly, and on demand; (2) it is accompanied by perfect ground truth information, which also means large sets of training data can be generated without the need for curation; (3) Biological ground truth and imaging effects can be tuned independently, enabling easy adaptation to different biological conditions, imaging platforms, and imaging modalities. Machine-learning models trained on SyMBac data generate more accurate and precise cell masks than those trained on human annotated data. This enables precise analysis of cell size regulation along changing conditions in a growing bacterial cell culture, revealing novel insights about the physiological dynamics of individual bacterial cells during entry and exit from dormancy.

Author SummaryMicroscopy is integral to microbiology, but accurate processing of microscopy data has been a major obstacle towards quantitative analysis of microbial physiology. The small size of bacterial cells and the comparable size of the microscopes point-spread function has made it virtually impossible to accurately determine the size, shape, and intensity of individual cells from their images. The difficulties of accurately identifying the boundaries of a cell from their image using computational thresholding or human annotators also limits the performance of recently developed machine-learning based image segmentation approaches, since these toolsets rely on the quality and quantity of the ground truth in the training data. In response to all these problems, we have developed SyMBac: Synthetic Micrographs of Bacteria. SyMBac is a tool which rapidly generates arbitrary amounts of synthetic training data of bacteria growing in microfluidic devices. Synthetic images generated by SyMBAc are accompanied by perfect ground truth information, which means large sets of training data can be generated without the need for curation. Our benchmarking results show that deep-learning algorithms trained with SyMBac are far superior, in terms of accuracy and precision of segmentation, compared to the same models trained on human annotated or computationally segmented data. This will significantly advance the field of quantitative microbiology. Probing effects of the SARS-CoV-2 E protein on membrane curvature and intracellular calcium SARS-CoV-2 contains four structural proteins in its genome. These proteins aid in the assembly and budding of new virions at the ER-Golgi intermediate compartment (ERGIC). Current fundamental research efforts largely focus on one of these proteins - the spike (S) protein. Since successful antiviral therapies are likely to target multiple viral components, there is considerable interest in understanding the biophysical role of its other structural proteins, in particular structural membrane proteins. Here, we have focused our efforts on the characterization of the full-length envelope (E) protein from SARS-CoV-2, combining experimental and computational approaches. Recombinant expression of the full-length E protein from SARS-CoV-2 reveals that this membrane protein is capable of independent multimerization, possibly as a tetrameric or smaller species. Fluorescence microscopy shows that the protein localizes intracellularly, and coarse-grained MD simulations indicate it causes bending of the surrounding lipid bilayer, corroborating a potential role for the E protein in viral budding. Although we did not find robust electrophysiological evidence of ion-channel activity, cells transfected with the E protein exhibited reduced intracellular Ca2+, which may further promote viral replication. However, our atomistic MD simulations revealed that previous NMR structures are relatively unstable, and result in models incapable of ion conduction. Our study highlights the importance of using high-resolution structural data obtained from a full-length protein to gain detailed molecular insights, and eventually permitting virtual drug screening. IRGM/Irgm1 Aggravates Progression of Atherosclerosis by Inducing Macrophage Apoptosis through the MAPK Signaling Pathway AimsAtherosclerosis underlies most cardiovascular diseases, among which acute coronary syndrome (ACS) caused by plaque rupture (PR) often leads to death. Immune-related GTPases (IRGM/Irgm1) have been extensively studied in inflammatory diseases, but their role in atherosclerosis is unclear. Determining how IRGM/Irgm1 promotes atherosclerotic plaque vulnerability will provide information for new biomarkers and/or therapeutic targets.

Methods and resultsWe identified ruptured and unruptured plaques by optical coherence tomography, and found that serum IRGM was highly expressed in patients with ST-segment elevation myocardial infarction in PR. We used ApoE-/-Irgm1+/+, ApoE-/-Irgm1+/- mice and chimeric mice to establish a model of advanced atherosclerosis. The results of pathological experiments showed that Irgm1 caused plaque necrosis. The ratio of neutral lipids and cholesterol crystals increases, while the content of collagen fibers decreases, aggravating the destabilization of atherosclerotic plaques. In vitro, we used multiple approaches to confirm that Irgm1 promotes macrophage apoptosis by promoting the production of reactive oxygen species and activating the MAPK signaling pathway.

ConclusionsIRGM may be a potential risk factor for PR. Mechanistic studies have shown that IRGM/Irgm1 contributes to the formation and rupture of fragile plaques. This is partly mediated by the induction of macrophage apoptosis via the MAPK signaling pathway. IRGM may offer new strategies for early treatment of ACS.

Translation viewOur findings indicate that IRGM/Irgm1 contributes to formation and rupture of vulnerable plaques. It suggests that IRGM may provide a new target for the early treatment of ACS. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. Spontaneous Chiral Symmetry Breaking in a Random Driven Chemical System Living systems have evolved to efficiently consume available energy sources using an elaborate circuitry of chemical reactions which, puzzlingly, bear a strict restriction to asymmetric chiral configurations. While autocatalysis is known to promote such chiral symmetry breaking, whether a similar phenomenon may also be induced in a more general class of configurable chemical systems--via energy exploitation--is a sensible yet underappreciated possibility. This work examines this question within a model of randomly generated complex chemical networks. We show that chiral symmetry breaking may occur spontaneously and generically by harnessing energy sources from external environmental drives. Key to this transition are intrinsic fluctuations of achiral-to-chiral reactions and tight matching of system configurations to the environmental drives, which together amplify and sustain diverged enantiomer distributions. These asymmetric states emerge through steep energetic transitions from the corresponding symmetric states and sharply cluster as highly-dissipating states. The results thus demonstrate a generic mechanism in which energetic drives may give rise to homochirality in an otherwise totally symmetrical environment, and from an early-life perspective, might emerge as a competitive, energy-harvesting advantage. Drug-Target Binding Affinity Prediction Using Transformers Drug discovery is generally difficult, expensive, and low success rate. One of the essential steps in the early stages of drug discovery and drug repurposing is identifying drug-target interactions. Binding affinity indicates the strength of drug-target pair interactions. In this regard, several computational methods have been developed to predict the drug-target binding affinity, and the input representation of these models has been shown to be very effective in improving accuracy. Although the recent models predict binding affinity more accurate than the first ones, they need the structure of target proteins. Despite the strong interest in protein structure, there is a massive gap between known sequences and experimentally determined structures. Therefore, finding an appropriate presentation for drug and protein sequences is vital for drug-target binding affinity prediction. In this paper, our primary goal is to assess the drug and protein sequence representation for improving drug-target binding affinity prediction. Substrate specialization in microbes is driven by biochemical constraints of dynamic flux sensing Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic re-organization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa and Pseudomonas putida. We combined growth dynamics and dynamic changes of intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis and growth and uncovered fundamental limitations of the regulatory network: after nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Graphical synopsis O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

Standfirst textMicrobes face a series of fundamental trade-offs that limit their ability to optimize simultaneously for both glycolytic and gluconeogenic growth.

Bullet pointsO_LILag times between glycolysis and gluconeogenesis show asymmetry in many microbes: A long lag in one direction, but a short lag in the other.
C_LIO_LILong lag times are caused by an inability to sense fluxes after nutrient shifts.
C_LIO_LIWith existing regulation, lag time asymmetry can only be overcome by reducing either growth rate or increasing futile cycling in metabolism.
C_LI Temporally robust occupancy frequency distributions in riverine ecosystems explained by local biodiversity regulation The distribution of species site occupancy--the occupancy frequency distribution (OFD)--is a fundamental pattern in spatial ecology. Despite decades of research, the mechanisms responsible for the shape of the distribution remain incompletely understood. Here, we simultaneously examine both spatial and temporal patterns of site occupancy in communities of macroinverterbrates, macrophytes and diatoms. We find that the shape of the OFD at the catchment scale is typically time invariant despite substantial turnover in composition and species proportional occupancy over the 30 year time series. This can been seen as evidence in favour of an ecological mechanism for the shape of the OFD driven by local regulation of species richness and other biodiversity properties. We show that a simple, locally saturated patch occupancy model explains both the shape of the OFD and the temporal turnover rate in English rivers. This model is mathematically analogous to Hubbells neutral theory however concerns patches occupied by a given species rather its population size. Our analysis supports the view that metacommunities exist in a dynamic steady state arising from local ecological constraints and that this intrinsic regulation can drives the emergence of a wide variety of macroecological patterns. We also show that interspecific differences are unlikely to play a dominant role in driving large scale ecosystem structure. A phylogenetic and proteomic reconstruction of eukaryotic chromatin evolution Histones and associated chromatin proteins have essential functions in eukaryotic genome organization and regulation. Despite this fundamental role in eukaryotic cell biology, we lack a phylogenetically-comprehensive understanding of chromatin evolution. Here, we combine comparative proteomics and genomics analysis of chromatin in eukaryotes and archaea. Proteomics uncovers the existence of histone post-translational modifications in Archaea. However, archaeal histone modifications are scarce, in contrast with the highly conserved and abundant marks we identify across eukaryotes. Phylogenetic analysis reveals that chromatin-associated catalytic functions (e.g., methyltransferases) have pre-eukaryotic origins, whereas histone mark readers and chaperones are eukaryotic innovations. We show that further chromatin evolution is characterized by expansion of readers, including capture by transposable elements and viruses. Overall, our study infers detailed evolutionary history of eukaryotic chromatin: from its archaeal roots, through the emergence of nucleosome-based regulation in the eukaryotic ancestor, to the diversification of chromatin regulators and their hijacking by genomic parasites. Use of lignocellulosic residue from 2G ethanol production to enhance methane production through co-digestion This is a pioneer study evaluating the methane (CH4) production potential from residues of integrated 1st (vinasse and filter cake) and 2nd (deacetylation pretreatment liquor from straw) generation (1G2G) sugarcane biorefinery, providing a fully chemical characterization of them and their relation with the anaerobic digestion (AD) process. Small-scale assays provided fundamentals for basing the co-digestion optimization by assessing the optimal co-substrates synergistic conditions. Biochemical Methane Potential (BMP) tests showed co-digestion enhanced CH4 yield of isolated substrates, reaching up to 605 NmLCH4 gVS-1. The association of vinasse and deacetylation liquor as co-substrates increased the BMP by ~38% mostly by nutritionally benefiting the methanogenic activity. The kinetic analysis confirmed that the deacetylation liquor was the co-substrate responsible for improving the CH4 production in the co-digestion systems due to the highest CH4 conversion rate. The alkaline characteristic of the liquor (pH~12) also prevented alkalizing from being added to the co-digestion, an input that normally makes the process economically unfeasible to implement on an industrial scale due to the large quantities required for buffering the reactor. The filter cake had the lowest BMP (262 NmLCH4 gVS-1) and digestibility ([&le;] 40%), further limited by the required stirring to improve the mass transfer of biochemical reactions. The present study drives towards more sustainable use of vinasse, the most voluminous waste from the sugarcane industry, and lignin-rich residues derived from pre-treatment alkaline methods, aiming at an energy-efficient utilization, by at least 16% when compared to the traditional vinasse AD. The experimental and modeling elements from this work indicated the lignin-rich liquor is the main responsible for putting the co-digestion as a disruptive technological arrangement within the 1G2G sugarcane biorefineries, reinforcing the biogas production as the hub of the bioeconomy in the agroindustrial sector. Molecular switch between mammalian MLL complexes dictates response to Menin-MLL inhibition The chromatin adaptor Menin interacts with oncogenic fusion proteins encoded by MLL1-rearrangements (MLL1-r), and small molecules that disrupt these associations are currently in clinical trials for the treatment of leukemia. By integrating chromatin-focused and genome-wide CRISPR screens with genetic, pharmacological, and biochemical approaches in mouse and human systems, we discovered a molecular switch between the MLL1-Menin and MLL3/4-UTX chromatin modifying complexes that dictates response to Menin-MLL inhibitors. We show that MLL1-Menin safeguards leukemia survival by impeding binding of the MLL3/4-UTX complex at a subset of target gene promoters. Disrupting the interaction between Menin and MLL1 leads to UTX-dependent transcriptional activation of a tumor suppressor gene-program that is crucial for a therapeutic response in murine and human leukemia. We establish the therapeutic relevance of this mechanism by showing that CDK4/6 inhibitors allow re-activation of this tumor-suppressor program in Menin-inhibitor insensitive leukemia cells, mitigating treatment resistance. The discovery of a molecular switch between MLL1-Menin and MLL3/4-UTX complexes on chromatin sheds light on novel functions of these evolutionary conserved epigenetic mediators and is particularly relevant to understand and target molecular pathways determining response and resistance in ongoing phase 1/2 clinical trials. 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.