Collective regulation of metabolism, development and longevity through a socially exchanged fluid Socially exchanged fluids, like seminal fluid and milk, allow individuals to molecularly influence conspecifics. Many social insects have a social circulatory system, where food and endogenously produced molecules are transferred mouth-to-mouth (stomodeal trophallaxis), connecting all the individuals in the society. To understand how these endogenous molecules relate to colony life, we used quantitative proteomics to investigate the trophallactic fluid within colonies of the carpenter ant Camponotus floridanus. We show that different stages of the colony life cycle circulate different types of proteins: young colonies prioritize direct carbohydrate processing; mature colonies prioritize accumulation and transmission of stored resources. Further, colonies circulate proteins implicated in oxidative stress, ageing, and social insect caste determination, potentially acting as superorganismal hormones. Brood-caring individuals that are also closer to the queen in the social network (nurses) showed higher abundance of oxidative stress-related proteins. Thus, trophallaxis behavior provides a mechanism for distributed metabolism in social insect societies.
Stochastic effects during the establishment of β-lactam resistant E. colimutants indicate conditions for collective resistance For antibiotic resistance to arise, new resistant mutants must establish in a bacterial population before they can spread via natural selection. Comprehending the stochastic factors that influence mutant establishment is crucial for a quantitative understanding of antibiotic resistance emergence. Here, we quantify the single-cell establishment probability of four Escherichia coli strains expressing {beta}-lactamase alleles with different activity against the antibiotic cefotaxime, as a function of antibiotic concentration in both unstructured (liquid) and structured (agar) environments. We show that concentrations well below the minimum inhibitory concentration (MIC) can substantially hamper establishment, particularly for highly resistant mutants. While the pattern of establishment suppression is comparable in both tested environments, we find greater variability in establishment probability on agar. Using a simple branching model, we investigate possible sources of this stochasticity, including environment-dependent lineage variability. Lastly, we use the single-cell establishment probability to predict each strains MIC in the absence of social interactions. We observe substantially higher measured than predicted MIC values, particularly for highly resistant strains, which indicates cooperative effects among resistant cells at large cell numbers, such as in standard MIC assays.
Unsupervised clustering analysis of SARS-Cov-2population structure reveals six major subtypes atearly stage across the world Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses. An Essential Role of UBXN3B in B Lymphopoiesis Hematopoiesis is finely regulated to enable timely production of the right numbers and types of mature immune cells to maintain tissue homeostasis. Dysregulated hematopoiesis may compromise antiviral immunity and/or exacerbate immunopathogenesis. Herein, we report an essential role of UBXN3B in maintenance of hematopoietic homeostasis and restriction of immunopathogenesis during respiratory viral infection. Ubxn3b deficient (Ubxn3b-/-) mice are highly vulnerable to SARS-CoV-2 and influenza A infection, characterized by more severe lung immunopathology, lower virus-specific IgG, significantly fewer B cells, but more myeloid cells than Ubxn3b+/+ littermates. This aberrant immune compartmentalization is recapitulated in uninfected Ubxn3b-/- mice. Mechanistically, UBXN3B controls precursor B-I (pre-BI) transition to pre-BII and subsequent proliferation in a cell-intrinsic manner, by maintaining BLNK protein stability and pre-BCR signaling. These results reveal an essential role of UBXN3B for the early stage of B cell development. SARS-CoV-2 Variants Reveal Features Critical for Replication in Primary Human Cells Since entering the human population, SARS-CoV-2 (the causative agent of COVID-19) has spread worldwide, causing >100 million infections and >2 million deaths. While large-scale sequencing efforts have identified numerous genetic variants in SARS-CoV-2 during its circulation, it remains largely unclear whether many of these changes impact adaptation, replication or transmission of the virus. Here, we characterized 14 different low-passage replication-competent human SARS-CoV-2 isolates representing all major European clades observed during the first pandemic wave in early 2020. By integrating viral sequencing data from patient material, virus stocks, and passaging experiments, together with kinetic virus replication data from non-human Vero-CCL81 cells and primary differentiated human bronchial epithelial cells (BEpCs), we observed several SARS-CoV-2 features that associate with distinct phenotypes. Notably, naturally-occurring variants in Orf3a (Q57H) and nsp2 (T85I) were associated with poor replication in Vero-CCL81 cells but not in BEpCs, while SARS-CoV-2 isolates expressing the Spike D614G variant generally exhibited enhanced replication abilities in BEpCs. Strikingly, low-passage Vero-derived stock preparation of 3 SARS-CoV-2 isolates selected for substitutions at positions 5/6 of E, and were highly attenuated in BEpCs, revealing a key cell-specific function to this region. Rare isolate-specific deletions were also observed in the Spike furin-cleavage site during Vero-CCL81 passage, but these were rapidly selected against in BEpCs, underscoring the importance of this site for SARS-CoV-2 replication in primary human cells. Overall, our study uncovers sequence features in SARS-CoV-2 variants that determine cell-specific virus replication, and highlights the need to monitor SARS-CoV-2 stocks carefully when phenotyping newly emerging variants or potential variants-of-concern. Recovering Single-cell Heterogeneity through Information-based Dimensionality Reduction Dimensionality reduction is crucial to summarizing the complex transcriptomic landscape of single cell datasets for downstream analyses. However, current dimensionality reduction approaches favor large cellular populations defined by many genes, at the expense of smaller and more subtly-defined populations. Here, we present surprisal component analysis (SCA), a technique that leverages the information-theoretic notion of surprisal for dimensionality reduction, and demonstrate its ability to improve the representation of clinically important populations that are indistinguishable using existing pipelines. For example, in cytotoxic T-cell data, SCA cleanly separates the gamma-delta and MAIT cell subpopulations, which are not detectable via PCA, ICA, scVI, or a wide array of specialized rare cell recovery tools. We also show that, when used instead of PCA, SCA improves downstream imputation to more accurately restore mRNA dropouts and recover important gene-gene relationships. SCAs information-theoretic paradigm opens the door to more meaningful signal extraction, with broad applications to the study of complex biological tissues in health and disease. 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. Relationship between shear wave velocity and muscle activation is inconsistent across different muscle types There is an increasing use of shear wave ultrasound elastography to quantify mechanical properties of muscles under various conditions such as changes muscle length and levels of activation in healthy and pathological muscle. However, little is known about the variability in shear wave velocity among muscles as most studies investigate one specific muscle. The purpose of this study was to determine if the relationship between SWV and muscle activation is consistent across muscles with different architectures: biceps brachii, tibialis anterior, and medial gastrocnemius, All measures were made at matching levels of activation and approximately at the optimal length for each muscle to control for length-dependent changes in the relationship between activation and force or stiffness. We also conducted a control experiment to determine how the passive force within a muscle alters the relationship between muscle activation and shear wave velocity. The relationship between shear wave velocity-squared and activation above 10% MVC differed across muscles, with biceps brachii and medial gastrocnemius showing a lower slope than tibialis anterior. Shear wave velocity-squared also differed between muscles at the shortest length (p<0.001) and the increase in shear wave velocity-squared with muscle lengthening also differed between muscle types (p = 0.005) Muscle-specific differences could not be explained by the architectural features such as pennation angle, fiber length, and physiological cross-sectional area. Our results demonstrate that there is not a unique relationship between muscle activation and shear wave velocity, highlighting the importance of understanding the many factors contributing to shear wave propagation in muscle before elastography can be used to make quantitative comparisons across muscle types. Comparing genome-based estimates of relatedness for use in pedigree-based conservation management Researchers have long debated which estimator of relatedness best captures the degree of relationship between two individuals. In the genomics era, this debate continues, with relatedness estimates being sensitive to the methods used to generate markers, marker quality, and levels of diversity in sampled individuals. Here, we compare six commonly used genome-based relatedness estimators (kinship genetic distance (KGD), Wang Maximum Likelihood (TrioML), Queller and Goodnight (Rxy), Kinship INference for Genome-wide association studies (KING-robust), and Pairwise Relatedness (RAB), allele-sharing co-ancestry (AS)) across five species bred in captivity-including three birds and two mammals-with varying degrees of reliable pedigree data, using reduced-representation and whole genome resequencing data. Genome-based relatedness estimates varied widely across estimators, sequencing methods, and species, yet the most consistent results for known first order relationships were found using Rxy, RAB, and AS. However, AS was found to be less consistently correlated with known pedigree relatedness than either Rxy or RAB. Our combined results indicate there is not a single genome-based estimator that is ideal across different species and data types. To determine the most appropriate genome-based relatedness estimator for each new dataset, we recommend assessing the relative: (1) correlation of candidate estimators with known relationships in the pedigree and (2) precision of candidate estimators with known first-order relationships. These recommendations are broadly applicable to conservation breeding programs, particularly where genome-based estimates of relatedness can complement and complete poorly pedigreed populations. Given a growing interest in the application of wild pedigrees, our results and are also applicable to in-situ wildlife management. How grower decision-making is modelled impacts the effect of plant disease control. While the spread of plant disease depends strongly on biological factors driving transmission, it also has a human dimension. Disease control depends on decisions made by individual growers, who are in turn influenced by a broad range of factors. Despite this, human behaviour has rarely been included in plant epidemic models. Considering Cassava Brown Streak Disease, we model how the perceived increase in profit due to disease management influences participation in clean seed systems (CSS). Our models are rooted in game theory, with growers making strategic decisions based on the expected profitability of different control strategies. We find that both the information used by growers to assess profitability and the perception of economic and epidemiological parameters influence long-term participation in the CSS. Over-estimation of infection risk leads to lower participation in the CSS, as growers perceive that paying for the CSS will be futile. Additionally, even though good disease management can be achieved through the implementation of CSS, and a scenario where all controllers use the CSS is achievable when growers base their decision on the average of their entire strategy, CBSD is rarely eliminated from the system. These results are robust to stochastic and spatial effects. Our work highlights the importance of including human behaviour in plant disease models, but also the significance of how that behaviour is included. Phytoene synthase 2 in tomato fruits remains functional and contributes to abscisic acid formation In ripening tomato fruits, the leaf-specific carotenoids biosynthesis mediated by phytoene synthase 2 (PSY2) is replaced by a fruit-specific pathway by the expression of two chromoplast-specific genes: phytoene synthase 1 (PSY1) and lycopene-{beta}-cyclase (CYCB). Though both PSY1 and PSY2 genes express in tomato fruits, the functional role of PSY2 is not known. To decipher whether PSY2-mediated carotenogenesis operates in ripening fruits, we blocked the in vivo activity of lycopene-{beta}-cyclases in fruits of several carotenoids and ripening mutants by CPTA (2-(4-Chlorophenylthio)triethylamine hydrochloride), an inhibitor of lycopene-{beta}-cyclases. The CPTA-treatment induced accumulation of lycopene in leaves, immature-green and ripening fruits. Even, in psy1 mutants V7 and r that are deficient in fruit-specific carotenoid biosynthesis, CPTA triggered lycopene accumulation but lowered the abscisic acid level. Differing from fruit-specific carotenogenesis, CPTA-treated V7 and r mutant fruits accumulated lycopene but not phytoene and phytofluene. The lack of phytoene and phytofluene accumulation was reminiscent of PSY2-mediated leaf-like carotenogenesis, where phytoene and phytofluene accumulation is never seen. The lycopene accumulation was associated with the partial transformation of chloroplasts to chromoplasts bearing thread-like crystalline structures. Our study uncovers the operation of a parallel carotenogenesis pathway mediated by PSY2 that provides precursors for abscisic acid biosynthesis in ripening tomato fruits.

Significance statementIt is believed that in ripening tomato fruits phytoene synthase 2 that drives carotenoid biosynthesis in leaves is redundant. Contrary to this, we show that in phytoene synthase 1 mutant fruit that is bereft of lycopene, the chemical inhibition of lycopene {beta}-cyclases triggers lycopene accumulation. Our results uncover that phytoene synthase 2 remains functional in ripening fruits and provides precursors for abscisic acid formation in fruits. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Modeling the SARS-CoV-2 nsp1--5'-UTR complex via extended ensemble simulations Nonstructural protein 1 (nsp1) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a 180-residue protein that blocks translation of host mRNAs in SARS-CoV-2-infected cells. Although it is known that SARS-CoV-2s own RNA evades nsp1s host translation shutoff, the molecular mechanism underlying the evasion was poorly understood. We performed an extended ensemble molecular dynamics simulation to investigate the mechanism of the viral RNA evasion. Simulation results showed that the stem loop structure of the SARS-CoV-2 RNA 5-untranslated region (SL1) is recognized by both nsp1s globular region and intrinsically disordered region. The recognition presumably enables selective translation of viral RNAs. Cluster analysis of the binding mode and detailed analysis of the binding poses revealed several residues involved in the SL1 recognition mechanism. The simulation results imply that the nsp1 C-terminal helices are lifted from the 40S ribosome upon the binding of SL1 to nsp1, unblocking translation of the viral RNA. Plasmodium DDI1 is a potential dual-therapeutic target and essential chromatin-associated protein DDI1 proteins are involved in a variety of cellular processes, including proteasomal degradation of specific proteins. All DDI1 proteins contain a ubiquitin-like (UBL) domain and a retroviral aspartyl protease (RVP) domain. Some DDI1 proteins also contain a ubiquitin-associated (UBA) domain. The three domains confer distinct activities to DDI1 proteins. The presence of RVP domain makes DDI1 a potential target of HIV protease inhibitors, which also block the development of malaria parasites. Hence, we investigated the DDI1 of malaria parasites to identify its roles during parasite development and potential as a therapeutic target. DDI1 proteins of Plasmodium and other Apicomplexan parasites share the UBL-RVP domain architecture, and some also contain the UBA domain. Plasmodium DDI1 is expressed across all the major life cycle stages and is essential, as conditional depletion of DDI1 protein in the mouse malaria parasite Plasmodium berghei and the human malaria parasite Plasmodium falciparum compromised parasite development. Infection of mice with DDI1 knock-down P. berghei was self-limiting and protected the recovered mice from subsequent infection with homologous as well as heterologous parasites, indicating potential of DDI1 knock-down parasites as a whole organism vaccine. P. falciparum DDI1 (PfDDI1) is associated with chromatin and DNA-protein crosslinks. PfDDI1-depleted parasites accumulated DNA-protein crosslinks and showed enhanced susceptibility to DNA damaging chemicals, indicating a role of PfDDI1 in removal of DNA-protein crosslinks. Knock-down of PfDDI1 increased susceptibility to the retroviral protease inhibitor lopinavir and antimalarial artemisinin, which suggests that simultaneous inhibition of DDI1 could potentiate antimalarial activity of these drugs. Hence, Plasmodium DDI1 could be a dual-therapeutic target for malaria control. TCF11 Has a Potent Tumor-Repressing Effect than Its Prototypic Nrf1α by Definition of both Similar yet Different Regulatory Profiles, with a Striking Disparity from Nrf2 Nrf1 and Nrf2, as two principal CNC-bZIP transcription factors, regulate similar but different targets involved in a variety of biological functions for maintaining cell homeostasis and organ integrity. Of note, the unique topobiological behavior of Nrf1 makes its functions more complicated than Nrf2, because it is allowed for alternatively transcribing and selectively splicing to yield multiple isoforms (e.g., TCF11, Nrf1). In order to gain a better understanding of their similarities and differences in distinct regulatory profiles, all four distinct cell models for stably expressing TCF11, TCF11{Delta}N, Nrf1 or Nrf2 have been herein established by an Flp-In T-REx-293 system and then identified by transcriptomic sequencing. Further analysis revealed that Nrf1 and TCF11 have similar yet different regulatory profiles, although both contribute basically to positive regulation of their co-targets, which are disparate from those regulated by Nrf2. Such disparity in those gene regulation by Nrf1 and Nrf2 was further corroborated by scrutinizing comprehensive functional annotation of their specific and/or common target genes. Conversely, the mutant TCF11{Delta}N, resulting from a deletion of the N-terminal amino acids 2-156 from TCF11, resembles Nrf2 with the largely consistent structure and function. Interestingly, our further experimental evidence demonstrates that TCF11 acts as a potent tumor-repressor relative to Nrf1, albeit both isoforms possess a congruous capability to prevent malignant growth of tumor and upregulate those genes critical for improving the survival of patients with hepatocellular carcinoma. 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. Estrogen-related receptor alpha and Rplp1-dependent translation coordinately regulate starvation response and decrease NASH progression Although general translation declines during fasting, maintaining the translation of a subset or proteins is necessary for metabolic homeostasis and cell viability. Using unbiased proteome analysis of hepatic cells during starvation, we identified a novel pathway in which Esrra-mediated transcription of Rplp1-dependent translation of lysosomal proteins declined during early starvation and recovered after prolonged starvation to restore autophagy-lysosome function. Interestingly, hepatic Esrra-Rplp1-dependent translation rate of lysosomal proteins also was impaired in patients and mice with non-alcoholic steatohepatitis (NASH), and translational response to starvation was dysregulated in mice with NASH. Remarkably, activation of Esrra pharmacologically, genetically, or by alternate day fasting restored protein translation, increased expression of lysosomal proteins, induced autophagy, and reduced lipotoxicity, inflammation, and fibrosis in cell culture and in vivo models of NASH. Thus, hepatic Esrra is essential for ribosome-dependent translation of lysosomal proteins during starvation, and prevention of lipotoxicity and progression in NASH.

Lay summaryFasting for weight loss improves non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH); however, the mechanism is not well understood. Our study shows that a nuclear protein, estrogen related receptor alpha (Esrra), increases ribosome-mediated translation of autophagy and lysosome proteins during chronic starvation to maintain essential metabolic pathways for cell survival. Surprisingly, this translational pathway is impaired during NASH with reduced lysosome-autophagy activity accompanied by increased inflammation and fibrosis gene expression in the liver. Pharmacologic, genetic and dietary activation of Esrra decreases lipid-mediated toxicity in liver cells as well as inflammation and fibrosis in livers from mice with NASH. These findings suggest that the Esrra-ribosome-lysosome pathway is important for liver response to fasting and NASH and thus may be a good therapeutic target for the treatment of NASH. 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. 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. Substrate dynamics contribute to enzymatic specificity in human and bacterial methionine adenosyltransferases Protein conformational change can facilitate the binding of non-cognate substrates and underlie promiscuous activities. However, the contribution of substrate conformational dynamics to this process is comparatively poorly understood. Here we analyse human (hMAT2A) and Escherichia coli (eMAT) methionine adenosyltransferases that have identical active sites but different substrate specificity. In the promiscuous hMAT2A, non-cognate substrates bind in a stable conformation to allow catalysis. In contrast, non-cognate substrates rarely sample stable productive binding modes in eMAT owing to altered mobility in the enzyme active site. Different cellular concentrations of substrate likely drove the evolutionary divergence of substrate specificity in these orthologs. The observation of catalytic promiscuity in hMAT2A led to the detection of a new human metabolite, methyl thioguanosine, that is produced at elevated level in a cancer cell line. This work establishes that identical active sites can result in different substrate specificity owing to the effects of substrate and enzyme dynamics. 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. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Discovery of highly potent pancoronavirus fusion inhibitors that also effectively inhibit COVID-19 variants from the UK (Alpha), South Africa (Beta), and India (Delta) We report here the discovery of several highly potent small molecules that showed low nM potency against SARS-CoV (IC50: as low as 13 nM), SARS-CoV-2 (IC50: as low as 23 nM), and MERS-CoV (IC50: as low as 76 nM) in pseudovirus based assays with excellent selectivity indices (SI: as high as > 5000) demonstrating their pancoronavirus inhibition. Some compounds also show 100% inhibition of CPE (IC100) at 1.25 {micro}M against an authentic SARS-CoV-2 (US_WA-1/2020). Furthermore, the most active inhibitors also potently inhibited variants of concerns (VOCs), such as the UK (B.1.1.7), South Africa (B.1.351), and Delta variant (B.1.617.2), originated in India. We confirmed that one of the potent inhibitors binds to the prefusion spike protein trimer of SARS-CoV-2 by SPR. Besides, we showed that they inhibit virus-mediated cell-cell fusion. The ADME data of one of the most active inhibitors, NBCoV1, show drug-like properties. In vivo PK of NBCoV1 in rats demonstrated excellent half-life (t1/2) of 11.3 h, mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect the lead inhibitors to pave the way for further development to preclinical and clinical candidates. Mind blanking is a distinct mental state linked to a recurrent brain profile of globally positive connectivity during ongoing mentation Mind blanking (MB) is a waking state during which we do not report any mental content, challenging the view of a constantly thought-oriented brain. Here, we comprehensively characterize the MBs neurobehavioral profile with the aim to delineate its role during ongoing mentation. Using fMRI experience-sampling, we show that MB is reported less frequently, faster, and with low transitional dynamics among other mental states, pointing to its role as a transient mental relay. Regarding its neural underpinnings, we observe higher global signal amplitude during MB reports, indicating a distinct physiological substrate. Using the time-varying functional connectome MB reports get classified with high accuracy, suggesting that MB has a unique neural composition. Indeed, a pattern of globally positive-phase coherence shows the highest similarity to the connectivity patterns associated with MB reports. We observe that this patterns rigid signal architecture hinders content reportability due to the brains inability to differentiate signals in an informative way. Collectively, we show that MB has a unique neurobehavioural profile, indicating that non-reportable mental events can happen during wakefulness. Our results add to the characterization of spontaneous mentation and pave the way for more mechanistic investigations of MBs phenomenology.

Significance StatementThe human mind is generally assumed to be thought-oriented. Mind blanking (MB) challenges this stance because it appears as if we are derived of any particular mental content to report. We here show that, during spontaneous thinking, MB is a mental state that happens by default, it has a unique behavioural profile, and it is of a rigid neural architecture that does not permit the formulation of reportable contents. Our work essentially proposes that non-reportable mental events can happen during wakefulness, and challenges the view of the mind as a constant thought-oriented operator. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. Environment dependent benefits of inter-individual variation in honey bee recruitment Inter-individual differences in behaviour within the members of a social group can affect the groups productivity. In eusocial insects, individual differences amongst workers in a colony play a central role division of labour and task allocation. Extensive empirical and theoretical work has highlighted variation in response thresholds as a proximate mechanism underlying individual behavioural differences and hence division of labour. However, other response parameters, like response probability and intensity, can affect these differences. In this study, we first extended a previously published agent-based model on honey bee foraging to understand the relative importance of response (dance) probability and response (dance) intensity in the task of recruitment. Comparing variation obtained from the simulations with previously published empirical data, we found that response intensity plays a more important role than probability in producing consistent inter-individual differences in recruitment behaviour. We then explored the benefits provided by this individual variation in recruitment behaviour to the colonys collective foraging effort under different environmental conditions. Our results revealed that individual variation leads to a greater energetic yield per forager, but only when food is abundant. Our study highlights the need to consider all response parameters while studying division of labour and adds to the growing body of evidence linking individual variation in behavioural responses to the success of social groups.