Getting more out of FLAG-Tag co-immunoprecipitation mass spectrometry experiments using FAIMS. Co-immunoprecipitation of proteins coupled to mass spectrometry is critical for the understanding of protein interaction networks. In instances where a suitable antibody is not available, it is common to graft synthetic tags onto target protein sequences and allowing the use of commercially available antibodies for affinity purification. A common approach is through FLAG-Tag co-immunoprecipitation. To allow the selective elution of protein complexes, competitive displacement using a large molar excess of the tag peptides is often carried out. Yet, this creates downstream challenges for the mass spectrometry analysis due to the presence of large quantities of these peptides. Here, we demonstrate that Field Asymmetric Ion Mobility Spectrometry (FAIMS), a gas phase ion separation device prior to mass spectrometry analysis can be applied to FLAG-Tag co-immunoprecipitation experiment to increase the depth of protein coverage. By excluding these abundant tag peptides, we were able to observe deeper coverage of interacting proteins and as a result, deeper biological insights, without the need for additional sample handling or altering sample preparation protocols.
Development of a Novel PROTAC using the Nucleic Acid Aptamer as a Targeting Ligand for Tumor Selective Degradation of Nucleolin PROteolysis TArgeting Chimeras (PROTACs) induce targeted protein degradation by hijacking the intracellular ubiquitin proteasome system, thus emerging as a new strategy for drug development. However, most PROTACs generated lack cell-type selectivity and have poorly soluble in water. To address this drawback, we developed a novel PROTAC ZL216 using aptamer AS1411 as a targeting ligand of nucleolin to conjugate with a small molecule ligand of E3 ligase VHL, which shows high aqueous solubility and serum stability. Based on the differential expression of nucleolin on the cell surface, ZL216 could bind to and internalize into breast cancer cells, but not normal breast cells. Furthermore, we revealed that ZL216 promoted the formation of a nucleolin-ZL216-VHL ternary complex in breast cancer cells and potently induced nucleolin degradation in vitro and in vivo. As a result, ZL216 inhibited the proliferation and migration of breast cancer cells. These studies demonstrate that in addition to peptides and small molecule compounds, nuclei acid aptamers can also be used to generate PROTACs, which broadens the toolbox constructing PROTACs and provides a promising strategy for development of tumor-selective PROTACs.
G Protein-Coupled Receptor-Ligand Dissociation Rates and Mechanisms from {tau}RAMD Simulations There is a growing appreciation of the importance of drug-target binding kinetics for lead optimization. For G protein-coupled receptors (GPCRs), which mediate signaling over a wide range of timescales, the drug dissociation rate is often a better predictor of in vivo efficacy than binding affinity, although it is more challenging to compute. Here, we assess the ability of the {tau}-Random Acceleration Molecular Dynamics ({tau}RAMD) approach to reproduce relative residence times and reveal dissociation mechanisms and the effects of allosteric modulation for two important membrane-embedded drug targets: the {beta}2-adrenergic receptor and the muscarinic acetylcholine receptor M2. The dissociation mechanisms observed in the relatively short RAMD simulations (in which molecular dynamics (MD) simulations are performed using an additional force with an adaptively assigned random orientation applied to the ligand) are in general agreement with much more computationally intensive conventional MD and metadynamics simulations. Remarkably, although decreasing the magnitude of the random force generally reduces the number of egress routes observed, the ranking of ligands by dissociation rate is hardly affected and agrees well with experiment. The simulations also reproduce changes in residence time due to allosteric modulation and reveal associated changes in ligand dissociation pathways.

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org.highwire.dtl.DTLVardef@743dcdorg.highwire.dtl.DTLVardef@1857381org.highwire.dtl.DTLVardef@62359aorg.highwire.dtl.DTLVardef@1ad38a3_HPS_FORMAT_FIGEXP  M_FIG C_FIG Extracellular matrix and spores impart structural hierarchy and compositional heterogeneity in Bacillus subtilis biofilms Biofilms are multicellular microbial communities that encase themselves in an extracellular matrix (ECM) of secreted biopolymers and attach to surfaces and interfaces. Bacterial biofilms are detrimental in hospital and industrial settings, but they can be beneficial in agricultural contexts. An essential property of biofilms that grants them with increased survival relative to planktonic cells is phenotypic heterogeneity; the division of the biofilm population into functionally distinct subgroups of cells. Phenotypic heterogeneity in biofilms can be traced to the cellular level, however, the molecular structures and elemental distribution across whole biofilms as well as possible linkages between them remain unexplored. Mapping X-ray diffraction (XRD) across intact biofilms in time and space, we revealed the dominant structural features in Bacillus subtilis biofilms, stemming from matrix components, spores and water. By simultaneously following the X-ray fluorescence (XRF) signal of biofilms and isolated matrix components, we discovered that the ECM preferentially binds calcium ions over other metal ions, specifically, zinc, manganese and iron. These ions, remaining free to flow below macroscopic wrinkles that act as water channels, eventually accumulate and lead to sporulation. The possible link between ECM properties, regulation of metal ion distribution and sporulation across whole intact biofilms unravels the importance of molecular-level heterogeneity in shaping biofilm physiology and development.

Significance StatementBiofilms are multicellular soft microbial communities that are able to colonize synthetic surfaces as well as living organisms. To survive sudden environmental changes and efficiently share their common resources, cells in a biofilm divide into subgroups with distinct functions, leading to phenotypic heterogeneity. Here, by studying intact biofilms by synchrotron X-ray diffraction and fluorescence, we revealed correlations between biofilm macroscopic architectural heterogeneity and the spatio-temporal distribution of extracellular matrix, spores, water and metal ions. Our findings demonstrate that biofilm heterogeneity is not only affected by local genetic expression and cellular differentiation, but also by passive effects resulting from the physicochemical properties of the molecules secreted by the cells, leading to differential distribution of nutrients that propagates through macroscopic length scales. Tracheal tube fusion in Drosophila involves release of exosomes from multivesicular bodies Extracellular vesicles (EVs) comprise diverse types of cell-released membranous structures that are thought to play important roles in intercellular communication. Despite extensive work on the formation and functions of EVs in cultured cells, studies of EVs in vivo have remained scarce. We report here that EVs are present in the developing lumen of tracheal tubes in Drosophila embryos. We defined two distinct EV subpopulations, one of which contains the Munc13-4 homologue Staccato (Stac) and is spatially and temporally associated with tracheal tube fusion events. The formation of Stac-positive luminal EVs depends on the tip-cell-specific GTPase Arl3, which is also required for the formation of Stac-positive multivesicular bodies, suggesting that Stac-EVs derive from fusion of Stac-MVBs with the luminal membrane in tip cells during anastomosis formation. The GTPases Rab27 and Rab35 cooperate downstream of Arl3 to promote Stac-MVB formation and tube fusion. We propose that Stac-MVBs act as membrane reservoirs that facilitate tracheal lumen fusion in a process regulated by Arl3, Rab27, Rab35, and Stac/Munc13-4. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. HSP90 modulates T2R bitter taste receptor nitric oxide production and innate immune responses in human airway epithelial cells and macrophages Bitter taste receptors (T2Rs) are G protein-coupled receptors (GPCRs) expressed in various cell types including ciliated airway epithelial cells and macrophages. T2Rs in these two airway innate immune cell types are activated by bitter products, including some secreted by Pseudomonas aeruginosa, leading to Ca2+-dependent activation of endothelial nitric oxide (NO) synthase (eNOS). NO enhances mucociliary clearance and has direct antibacterial effects in ciliated epithelial cells and increases phagocytosis by macrophages. Using biochemistry and live cell imaging, we explored the role of heat shock protein 90 (HSP90) in regulating T2R-dependent NO pathways in primary sinonasal epithelial cells, primary monocyte-derived macrophages, and a human bronchiolar cell line (H441). We used immunofluorescence to show that H441 cells express eNOS and certain T2Rs and that the bitterant denatonium benzoate activates NO production in an HSP90-dependent manner in cells grown either as submerged cultures and at air liquid interface. In primary sinonasal epithelial cells, we determined that HSP-90 inhibition reduces T2R-stimulated NO production and ciliary beating which are crucial for pathogen clearance. In primary monocyte-derived macrophages, we found that HSP-90 is integral to T2R-stimulated NO production and phagocytosis of FITC-labeled Escherichia coli and pHrodo-Staphylococcus aureus. Our study demonstrates that HSP90 serves an innate immune role by regulating NO production downstream of T2R signaling by augmenting eNOS activation without impairing upstream calcium signaling. These findings suggest that HSP90 plays an important role in airway antibacterial innate immunity and may be an important target in airway diseases like chronic rhinosinusitis, asthma, or cystic fibrosis. Intramolecular carbon isotope signals reflect metabolite allocation in plants Stable isotopes at natural abundance are key tools to study physiological processes occurring outside the temporal scope of manipulation and monitoring experiments. Whole-molecule carbon isotope ratios (13C/12C) enable assessments of plant carbon uptake yet conceal information about carbon allocation. Here, we identify an intramolecular 13C/12C signal at treering glucose C-5 and C-6 and develop experimentally testable theories on its origin. More specifically, we assess the potential of processes within C3 metabolism for signal introduction based (inter alia) on constraints on signal propagation posed by metabolic networks. We propose that the intramolecular signal reports carbon allocation into major metabolic pathways in actively photosynthesising leaf cells including the anaplerotic, shikimate, and non-mevalonate pathway. We support our theoretical framework by linking it to previously reported whole-molecule 13C/12C increases in cellulose of ozone-treated Betula pendula and a highly significant relationship between the intramolecular signal and tropospheric ozone concentration. Our theory postulates a pronounced preference of leaf-cytosolic triose-phosphate isomerase to catalyse the forward reaction in vivo (dihydroxyacetone phosphate to glyceraldehyde 3-phosphate). In conclusion, intramolecular 13C/12C analysis resolves information about carbon uptake and allocation enabling more comprehensive assessments of carbon metabolism than whole-molecule 13C/12C analysis.

HighlightIntramolecular 13C/12C analysis resolves information about carbon uptake and allocation (and associated environmental controls) enabling more comprehensive assessments of carbon metabolism, plant-environment interactions, and environmental variability than whole-molecule 13C/12C analysis. Drug screening at single-organoid resolution via bioprinting and interferometry High-throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms for high-throughput screening use two-dimensional cultures of immortalized cell lines which do not accurately reflect the biology of human tumors. More clinically relevant model systems, such as three-dimensional tumor organoids, can be difficult to screen and scale. For example, manually seeded organoids coupled to destructive endpoint assays allow for the characterization of response to treatment, but do not capture the transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We therefore developed a pipeline to generate bioprinted tumor organoids linked to label-free, real-time imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D organoid structures that preserve tumor histology and gene expression. HSLCI imaging in tandem with machine learning-based image segmentation and organoid classification tools enables accurate, label-free parallel mass measurements for thousands of bioprinted organoids. We demonstrate that our method quantitatively identifies individual organoids as insensitive, transiently sensitive, or persistently sensitive to specific treatments. This opens new avenues for rapid, actionable therapeutic selection using automated tumor organoid screening. Speciation dynamics and extent of parallel evolution along a lake-stream environmental contrast in African cichlid fishes Understanding the drivers and dynamics of diversification is a central topic in evolutionary biology. Here, we investigated the dynamics of diversification in the cichlid fish Astatotilapia burtoni that diverged along a lake-stream environmental gradient. Whole-genome and morphometric analyses revealed that divergent selection was essential at the early stages of diversification, but that periods in allopatry were likely involved towards the completion of speciation. While morphological differentiation was continuous, genomic differentiation was not, as shown by two clearly separated categories of genomic differentiation. Reproductive isolation increased along a continuum of genomic divergence, with a "grey zone" of speciation at [~]0.1% net nucleotide divergence. The quantification of the extent of (non-)parallelism in nine lake-stream population pairs from four cichlid species by means of multivariate analyses revealed one parallel axis of genomic and morphological differentiation among seven lake-stream systems. Finally, we found that parallelism was higher when ancestral lake populations were more similar. Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals due to various confounding challenges. Here, we demonstrate that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales--from genes to genomic regions and pathways--have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits, as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts. Analysis of science journalism reveals gender and regional disparities in coverage Science journalism is a critical way in which the public can remain informed and benefit from new scientific findings. Such journalism also shapes the publics view of the current state of scientific findings and legitimizes experts. Those covering science can only cite and quote a limited number of sources. Sources may be identified by the journalists research or by recommendations by other scientists. In both cases, biases may influence who is identified and ultimately included as an expert. To analyze possible biases in science journalism, we analyzed 22,001 non-research articles published by Nature. We chose to analyze Nature non-research articles since its research articles provide a natural comparator. Our analysis considered two possible sources of disparity: gender and name origin. To explore these sources of disparity, we extracted cited authors names as well as extracted names of quoted speakers. While citations and quotations within a piece do not reflect the entire information-gathering process, they can provide insight into the demographics of visible sources. We then used the extracted names to predict gender and name origin of the cited authors and speakers.

In order to appropriately quantify the level of difference, we must identify a suitable reference set for comparison. We chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. In our analysis, we found a skew towards male quotation in Nature science journalism-related articles. However, quotation is trending toward equal representation at a faster rate than first and last authorship in academic publishing. Interestingly, we found that the gender disparity in Nature quotes was column-dependent, with the "Career Features" column reaching gender parity. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin. This finding was observed both in extracted quotes and journal citations, but dampened in citations. Circadian-period variation underlies the local adaptation of photoperiodism in the short-day plant Lemna aequinoctialis. Phenotypic variation is the basis for trait adaptation via evolutionary selection.1, 2, 3 However, the driving forces behind the quantitative trait variations remain unclear owing to their complexity at the molecular level.4, 5, 6 This study focused on the natural variation of the free-running period (FRP) of the circadian clock because FRP is a determining factor of the internal clock phase (chronotype), which is responsible for physiological timing during a day.7 Although natural variations in FRP have been widely reported,8, 10, 11 few studies have shown the association between FRP and adaptive temporal traits. As a clock-dependent physiological process, photoperiodism is a typical target of local adaptation.12, 13 Lemna aequinoctialis in Japan is a paddy-field duckweed exhibiting a latitudinal cline of critical day-lengths (CDLs) for short-day flowering.14 To investigate the relationship between FRP and CDL, we collected 72 strains of L. aequinoctialis within a latitudinal range between 31.5{degrees}N to 43.8{degrees}N. We found a significant correlation (P = 7.5E-8) between FRPs and locally adaptive CDLs, confirming that the variation in FRP-dependent chronotypes underlies geographically differentiated photoperiodism. Diel transcriptome analysis revealed that the induction timing of a florigen gene is key for connecting chronotypes to photoperiodism at the molecular level. Based on these results, we propose a fundamental rule concerning the "chronotype effect" in evolution: the variation of FRP functions as a resource for the variation of temporal traits. This study highlights the adaptive significance of FRP variation and provides a reason for the maintenance of FRP variation in natural populations. A Physiometric Investigation of Inflammatory Composites: Comparison of A Priori Aggregates, Empirically-identified Factors, and Individual Proteins Most research testing the association between inflammation and health outcomes (e.g., heart disease, diabetes, depression) has focused on individual proteins; however, some studies have used summed composites of inflammatory markers without first investigating dimensionality. Using two different samples (MIDUS-2: N = 1,255 adults, MIDUS-R: N = 863 adults), this study investigates the dimensionality of eight inflammatory proteins (C-reactive protein (CRP), interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor- (TNF-), fibrinogen, E-selectin, and intercellular adhesion molecule (ICAM)-1) and compared the resulting factor structure to a) an "a priori"/tau-equivalent factor structure in which all inflammatory proteins equally load onto a single dimension (comparable to the summed composites) and b) proteins modeled individually (i.e., no latent variable) in terms of model fit, replicability, reliability, and their associations with health outcomes. An exploratory factor analysis indicated a two-factor structure (Factor 1: CRP and fibrinogen; Factor 2: IL-8 and IL-10) in MIDUS-2 and was replicated in MIDUS-R. Results did not clearly indicate whether the empirically-identified factor structure or the individual proteins modeled without a latent variable had superior model fit, but both strongly outperformed the "a priori"/tau-equivalent structure (which did not achieve acceptable model fit in any models). Modeling the empirically-identified factors and individual proteins (without a latent factor) as outcomes of medical diagnoses resulted in comparable conclusions. However, modeling individual proteins resulted in findings more robust to correction for multiple comparisons despite more conservative adjustments. Further, reliability for all latent variables was poor. These results indicate that modeling inflammation as a unidimensional construct equally associated with all available proteins does not fit the data well. Instead, individual inflammatory proteins or, potentially (if empirically supported and biologically-plausible) empirically-identified inflammatory factors should be used in accordance with theory. The compound of baicalein, wogonin, and oroxylin-A inhibiting EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. The response network of HSP70 defines vulnerabilities in cancer cells with the inhibited proteasome Human neoplasias are often addicted to the proteasome machinery. However, cancers have evolved efficient response mechanisms to overcome proteasome inhibition with bortezomib and carfilzomib - drugs approved for multiple myeloma treatment. To understand these responses we investigated proteome changes upon the proteasome inhibition with carfilzomib - in multiple myeloma, normal fibroblasts, and cancers of lung, colon, and pancreas. A pathway-oriented siRNA screen based on the proteomics results showed that molecular chaperones, autophagy- and endocytosis-related proteins are cancer-specific vulnerabilities combined with carfilzomib. Targeting of HSPA1A/B (HSP70 family chaperones) most specifically sensitized cancer cells and patient-derived organoids to the proteasome inhibition. A high level of HSPA1A/B mRNA correlated with a low proteasome activity in cancer patient tissues and is a risk factor in cancer patients with a low proteasome expression. Mechanistically, HSPA1A/B governed autophagy, unfolded protein response, endocytic trafficking, and chaperoned the proteasome machinery, suppressing the effect of the proteasome inhibition, but did not control the NRF1/2-driven proteasome subunit transcriptional bounce-back. Consequently, downregulation of NRF1 most specifically decreased the viability of cancer cells with the inhibited proteasome and HSP70. State-dependent network interactions differentially gate sensory input at the motor and command neuron level in Caenorhabditis elegans Neural responses are influenced by both external stimuli and internal network states. While network states have been linked to behavioral and stimulus states, little is known about how sensory inputs are filtered by whole-brain activity to affect motor and command neurons. Here, we recorded whole-brain activity of Caenorhabditis elegans experiencing bacterial food stimuli, and modeled how sensory inputs affect motor and command neurons in a network state-dependent manner. First, we classified active neurons into six functional clusters: two sensory neuron clusters (ON, OFF), and four motor/command neuron clusters (AVA, RME, SMDD, SMDV). Using encoding models, we found that ON and OFF sensory neurons that respond to onset and removal of bacteria, respectively, employ different adaptation strategies. Next, we used decoding models to show that bacterial onset and removal differentially drive AVA and RME cluster activity. To explore state-dependent effects on AVA and RME clusters, we developed a model that identified network states and fitted submodels for each state to predict how each of the six functional clusters drive AVA and RME cluster activity. We also identified network states in which AVA and RME clusters were either largely unperturbed by or receptive to bacterial sensory input. Furthermore, this model allowed us to disentangle the state-dependent contributions of stimulus timescales and bacterial content to neural activity. Collectively, we present an interpretable approach for modeling network dynamics that goes beyond implication of neurons in particular states, and moves toward explicitly dissecting how neural populations work together to produce state dependence.

Significance StatementA major function of the brain is to transform sensory information into behavior. As the first receiver of sensory input, sensory neuron activity is often most correlated with stimulus features. However, this high-fidelity representation of sensory input becomes diluted as it travels to downstream neurons, where sensory information is integrated with network activity. By the time sensory information reaches motor neurons, it is often difficult to dissociate the influence of sensory input from the influence of network activity. Here, we describe a method that is fully interpretable such that we can show how neural populations on a whole-brain scale interact to produce network states. From there, we can attribute motor neuron activity to network history and sensory input. metapredict: a fast, accurate, and easy-to-use predictor of consensus disorder and structure Intrinsically disordered proteins and protein regions make up a substantial fraction of many proteomes where they play a wide variety of essential roles. A critical first step in understanding the role of disordered protein regions in biological function is to identify those disordered regions correctly. Computational methods for disorder prediction have emerged as a core set of tools to guide experiments, interpret results, and develop hypotheses. Given the multiple different predictors available, consensus scores have emerged as a popular approach to mitigate biases or limitations of any single method. Consensus scores integrate the outcome of multiple independent disorder predictors and provide a per-residue value that reflects the number of tools that predict a residue to be disordered. Although consensus scores help mitigate the inherent problems of using any single disorder predictor, they are computationally expensive to generate. They also necessitate the installation of multiple different software tools, which can be prohibitively difficult. To address this challenge, we developed a deep-learning-based predictor of consensus disorder scores. Our predictor, metapredict, utilizes a bidirectional recurrent neural network trained on the consensus disorder scores from 12 proteomes. By benchmarking metapredict using two orthogonal approaches, we found that metapredict is among the most accurate disorder predictors currently available. Metapredict is also remarkably fast, enabling proteome-scale disorder prediction in minutes. Importantly, metapredict is fully open source and is distributed as a Python package, a collection of command-line tools, and a web server, maximizing the potential practical utility of the predictor. We believe metapredict offers a convenient, accessible, accurate, and high-performance predictor for single-proteins and proteomes alike.

Statement of SignificanceIntrinsically disordered regions are found across all kingdoms of life where they play a variety of essential roles. Being able to accurately and quickly identify disordered regions in proteins using just the amino acid sequence is critical for the appropriate design and interpretation of experiments. Despite this, performing large-scale disorder prediction on thousands of sequences is challenging using extant disorder predictors due to various difficulties including general installation and computational requirements. We have developed an accurate, high-performance and easy-to-use predictor of protein disorder and structure. Our predictor, metapredict, was designed for both proteome-scale analysis and individual sequence predictions alike. Metapredict is implemented as a collection of local tools and an online web server, and is appropriate for both seasoned computational biologists and novices alike. Localization of signaling receptors maximizes cellular informationacquisition in spatially-structured natural environments Cells in natural environments like tissue or soil sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions, sculpted by processes such as fluid flow and substrate adhesion. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. We develop an information-theoretic framework for computing the optimal spatial organization of a sensing system for a given signaling environment. We find that receptor localization maximizes information acquisition in simulated natural contexts, including tissue and soil. Receptor localization extends naturally to produce a dynamic protocol for continuously redistributing signaling receptors, which when implemented using simple feedback, boosts cell navigation efficiency by 30-fold. Broadly, our work shows how cells can maximize the fidelity of information transfer by adapting the spatial organization of signaling molecules to the spatial structure of the environment. 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. Learning and motor inhibitory control in crows and domestic chickens Cognitive abilities allow animals to navigate through complex, fluctuating environments. In the present study, we tested the performance of a captive group of eight crows, Corvus corone, and ten domestic chickens, Gallus gallus domesticus, in the cylinder task, as a test of motor inhibitory control, and reversal learning as a measure of learning ability and behavioural flexibility. Four crows and nine chickens completed the cylinder task, eight crows and six chickens completed the reversal learning experiment. Crows performed better in the cylinder task compared to chickens. In the reversal learning experiment, species did not significantly differ in the number of trials until learning criterion was reached. Performance in the reversal learning experiment did not correlate with performance in the cylinder task in chickens. Our results suggest crows to possess better motor inhibitory control compared to chickens. In contrast, learning performance in a reversal learning task did not differ between the species, indicating similar levels of behavioural flexibility. Interestingly, we describe notable individual differences in performance. We stress the importance not only to compare cognitive performance between species but also between individuals of the same species when investigating the evolution of cognitive skills. RNF213 loss of function reshapes vascular transcriptome and spliceosome leading to disrupted angiogenesis and aggravated vascular inflammatory responses. RationaleMoyamoya disease (MMD) is a rare cerebrovascular occlusive disease that affects Asian population more often. The pathogenesis of MMD is related to mutation in RNF213 gene. However, why, and how RNF213 mutation leads to MMD is still not fully understood.

ObjectiveAnalyze the impact of RNF213 loss of function on vascular cells and the observed changes correlate with MMD.

Methods and resultsRNF213 KD was conducted in HUVEC and vascular smooth muscle cells (vSMCs). First, HUVEC cells showed alteration of angiogenesis, migration under LPS stimulation, Leukocyte endothelial transmigration, and endothelial-to-vSMCs communication.

Transcriptome analysis revealed downregulation of genes regulating cell division and mitosis. Interestingly, Alternative splicing (AS) analysis revealed hundreds of AS events to occur after RNF213 KD in various types of AS. The alternatively spliced genes showed minimal overlap with transcriptome profiling. Pathway analysis revealed many processes and pathways to be regulated by AS events observed. Transcriptome profiling was also performed after LPS treatment and revealed the basis for increased sensitivity to LPS observed in our analysis. AS changes were also observed after LPS treatment in RNF213 KD HUVEC. Different types of AS showed different patterns of convergence or divergence in terms of the regulated pathways after LPS treatment. Finally, transcriptome and AS analysis was performed in vSMCs and showed various processes that impact vSMCs function and phenotype in RNF213 loss of function.

ConclusionOur data provide a wealth of information on RNF213 gene function in vascular tissues and shed important light on different processes that contribute to MMD pathogenesis. Our results signify an immune-driven and hemodynamically linked process of MMD initiation and progression. Using total RNA quality metrics for time since deposition estimates in degrading bloodstains Determining the time since deposition (TSD) of bloodstains would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. The physicochemical changes occurring to biomolecules as a bloodstain degrades can be used to approximate the TSD of bloodstains. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has previously targeted mRNA molecules. Whole bovine blood was stored in plastic microcentrifuge tubes at 21{degrees}C or 4{degrees}C and tested over different timepoints spanning one week. Nine RNA metrics were visually assessed and quantified using linear and mixed models; the RNA Integrity Number equivalent (RINe) and the DV200 demonstrated strong negative trends over time and statistical independence. The RINe model fit was high (R2 = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200 metrics. Importantly, this suggests that these standardized metrics can likely be directly compared between scenarios and individuals, with DV200 having an inflection point at [~]28 hrs. This study provides a novel approach for blood TSD estimates, producing metrics that are not affected by inter-individual variation and improving our understanding of the rapid degradation occurring in bloodstains.

HIGHLIGHTSO_LIAmplification-free analysis of total RNA in degrading bloodstains.
C_LIO_LIShort-term RNA degradation assessment using high-resolution size measurements.
C_LIO_LITotal RNA quality and quantity metrics were assessed across a one-week.
C_LIO_LITotal RNA quality metrics demonstrated the strongest timewise trends.
C_LIO_LIBiological replicates produced similar results for RNA quality metrics.
C_LI Nuclear alpha-synuclein is present in the human brain and is modified in dementia with Lewy bodies Dementia with Lewy bodies is pathologically defined by the cytoplasmic accumulation of alpha-synuclein within neuronal cells in the brain. Alpha-synuclein is predominately pre-synaptic, but has been reported present in various subcellular compartments in cell and animal models. In particular, nuclear alpha-synuclein is evident in-vitro and in disease models and has been associated with altered DNA integrity, gene transcription, nuclear homeostasis. However, owing to various factors, the presence of alpha-synuclein in the nuclei of human brain cells remains controversial, as does its role in synucleinopathies.

Here, we close this gap and provide a unique demonstration confirming the presence of nuclear alpha-synuclein in post-mortem brain tissue obtained from cases of dementia with Lewy bodies as well as from controls via immunohistochemistry, immunoblot, and label-free mass-spectrometry.

Discrete intra-nuclear alpha-synuclein puncta reactive against phosphorylated serine 129-alpha-synuclein and pan-alpha-synuclein antibodies were observed in cortical neurons and non-neuronal cells in fixed brain sections and in isolated nuclear preparations from Dementia with Lewy bodies cases and matched controls. Subsequent biochemical analysis of subcellular fractionated tissue confirmed alpha-synuclein as present in a nuclear fraction at levels ~ 10-fold lower than in the cytoplasm. Critically, however, an increase in monomeric nuclear alpha-synuclein phosphorylated as serine 129 was observed in cases of dementia with Lewy bodies alongside higher molecular weight pan- and phosphorylation reactive alpha-synuclein species, consistent with the formation of intranuclear phosphorylated alpha-synuclein oligomers. Furthermore, the presence of nuclear alpha-synuclein was confirmed via label free mass spectrometry, as 6 unique alpha-synuclein derived peptide sequences were identified in nuclear fractions (71.4% sequence coverage).

Collectively, our data confirm the presence of nuclear alpha-synuclein in human brain tissue and describe nuclear pathology associated with dementia with Lewy bodies. These findings address a major controversy in the synucleinopathy field by confirming the presence of nuclear alpha-synuclein in autoptic human brain tissue and, for the first time, identify that alpha-synuclein is aggregated into novel and potentially pathological assemblies in the nucleus as part of the disease process associated with dementia with Lewy bodies and thus may contribute to the disease phenotype. Vitronectin acts as a key regulator of adhesion and migration in human umbilical cord-derived MSCs under different stress conditions Mesenchymal stem cell (MSC)-based therapy gets compromised as adverse microenvironmental conditions like nutrient deprivation, ischemia, hypoxia at the target site affect migration, engraftment and viability, of MSCs post transplantation. To improve the treatment efficacy, it is critical to identify factors involved in regulating migration and adhesion of MSCs under such microenvironmental stress conditions. In our study, we observed that human Whartons jelly-derived MSCs (WJ-MSCs) exhibited increase in cell spread area and adhesion, with reduction in cellular migration under serum starvation stress. The changes in adhesion and migration characteristics were accompanied by formation of large number of super mature focal adhesions along with extensive stress fibres and altered ECM gene expression with notable induction in vitronectin (VTN) expression. NF-{kappa}{beta} was found to be a positive regulator of VTN expression while ERK pathway regulated it negatively. Molecular and phenotypic comparison studies with inhibition of these signalling pathways or knocking down of VTN under serum starvation established the correlation between increase in VTN expression and increased cellular adhesion with corresponding reduction in cell migration. VTN knockdown also resulted in reduction of super mature focal adhesions and extensive stress fibres, which were formed under serum starvation. Additionally, VTN induction was not detected in hypoxia-treated WJ-MSCs, and the MSCs showed no significant change in the adhesion or migration properties under hypoxia. However, when VTN expression was induced under hypoxia by ERK pathway inhibition, similar increase in cell spread area and adhesion were observed. Our study thus highlights VTN as a key player which is induced under serum starvation stress and possibly regulates the adhesion and migration properties of WJ-MSCs via focal adhesion signalling. A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information.