B1 SINE-binding ZFP266 impedes reprogramming through suppression of chromatin opening mediated by pioneering factors Induced pluripotent stem cell reprogramming is inherently inefficient and understanding the molecular mechanisms underlying this inefficiency holds the key to successfully control cellular identity. Here, we report 16 novel reprogramming roadblock genes identified by CRISPR/Cas9-mediated genome-wide knockout (KO) screening. Of these, depletion of the predicted KRAB zinc finger protein (KRAB-ZFP) Zfp266 strongly and consistently enhanced iPSC generation in several iPSC reprogramming settings, emerging as the most robust roadblock. Further analyses revealed that ZFP266 binds Short Interspersed Nuclear Elements (SINEs) adjacent to binding sites of pioneering factors, OCT4 (POU5F1), SOX2 and KLF4, and impedes chromatin opening. Replacing the KRAB co-suppressor with a co-activator domain converted ZFP266 from a reprogramming inhibitor to a potent reprogramming facilitator. This work proposes SINE-KRAB-ZFP interaction to be a critical regulator of chromatin accessibility at enhancers for efficient cellular identity changes and also serves as a resource to further illuminate molecular mechanisms hindering reprogramming.
Ex vivo anticoagulants affect human blood platelet biomechanics with implications for high-throughput functional mechanophenotyping. Inherited platelet disorders affecting the human platelet cytoskeleton result in increased bleeding risk. However, deciphering their impact on cytoskeleton-dependent intrinsic biomechanics of platelets remains challenging and represents an unmet need from a diagnostic and prognostic perspective. It is currently unclear whether ex vivo anticoagulants used for the collection of peripheral blood impact the mechanophenotype of cellular components of blood. Using unbiased, high-throughput functional mechanophenotyping of single human platelets by deformability cytometry, we found that ex vivo anticoagulants are a critical pre-analytical variable that differentially influences platelet deformation, their size and functional response to agonists by altering the cytoskeleton. We applied our findings to characterize the functional mechanophenotype of platelets from a patient with Myosin Heavy Chain 9 (MYH9) related macrothrombocytopenia. Our data suggest that platelets from MYH9 p.E1841K mutation in humans affecting platelet non-muscle myosin heavy chain IIa (NMMHC-IIA) are biomechanically less deformable in comparison to platelets from healthy individuals.
Bulk-assembly of monodisperse coacervates and giant unilamellar vesicles with programmable hierarchical complexity Compartmentalization is an essential step for the emergence of protocellular life on the early earth and the endeavor to bottom-up construct synthetic cells in the lab. Among manifold natural strategies for compartmentalization, assembly of lipid vesicles or coacervate droplets with resemblance to cell envelope or cytoplasm have emerged as two dominant paradigms. However, the spontaneous assembly of lipid vesicles or coacervates generally results in polydisperse microcompartments and lacks the ability to efficiently integrate functional building blocks towards defined complexity, which give rise to the difficulty to achieve the order and complexity towards the scope of that of life via spontaneous assembly. Herein, we show that the interplay of coacervates and colloidal particles provides a bulk-assembly approach to form monodisperse coacervates and giant unilamellar vesicles (GUVs) with programmable hierarchical complexity. The hierarchical complexity of the synthetic cell microcompartments can be delicately engineered from the control of the spatial or temporal organization of components in entity unit to manifold forms of interconnected synthetic cell consortia, achieving a compartment hierarchy analogous to the organelle-cell-tissue structure. The increase in complexity gives rise to emergent properties, for instance, collective morphology evolution of coacervate assemblages, gated permeability of GUVs without sophisticated protein machinery, and remarkable structural and functional stability of GUVs at extreme conditions. This work paves an unprecedented step to form monodisperse, hierarchical coacervates and GUVs via bulk-assembly, which provides a prebiotically plausible approach for the proper integration of inanimate matter towards the order and complexity of life and monodisperse, hierarchical microdroplets for follow-up scientific and technological applications. A General Biphasic-Bodyweight Model for Scaling Basal Metabolic Rate, Glomerular Filtration Rate and Drug Clearance from Birth to Adulthood Understanding the maturation process of human physiology and metabolism has broad medical and pharmaceutical implications. Age and bodyweight are frequently considered as separate variables in modeling the dynamical changes of human organ functions and of drug clearance from birth to adulthood. The objective of this study is to propose a unified, continuous and bodyweight-only equation to quantify the changes of human basal metabolic rate (BMR), glomerular filtration rate (GFR) and drug clearance (CL) from infancy to adulthood. The BMR datasets were retrieved from a comprehensive historical database of male and female subjects (0.02 to 64 years). The CL datasets for 17 drugs and the GFR dataset were generated from age-incorporated maturation-and-growth models with reported parameter values. The model used in the simulation is independent of the proposed model. A statistical approach was used to simulate the model generated CL and GFR data for a hypothetical population with 26 age groups (ranging from 0 to 20 years). Besides, individual CL data for one drug, and sparse PBPK-modeled CL values for two drugs were also included for analysis. A 4-parameter, mixed-allometry equation with two power-law functions of bodyweight was proposed and evaluated as a general model using nonlinear regression and dimensionless analysis. All datasets universally reveal biphasic curves with two distinct linear segments on log-log plots. Compared with simple allometry, the biphasic model fits satisfactorily to all datasets (based on Akaikes Information Criterion and residual plots). The biphasic equation consists of two reciprocal allometric terms that asymptotically determine the overall curvature. The fitting results show a superlinear scaling phase (slope >1; ca. 1.5 - 3.5) below the characteristic bodyweight at the phase transition; and above which, a sublinear scaling phase (slope <1; ca. 0.5 - 0.7) is evident. The phase-transition bodyweight is ranging from 5 to 20 kg (corresponding to 0.5 - 9 years) and the mean value is around 10 kg ([~]2 years) for all data sets. The dimensionless analysis generalizes, and offers quantitative realization of, the maturation and growth process. In conclusion, the proposed mixed-allometry equation is a generic model that quantitatively describes the phase transition occurring in the human maturation process of BMR, GFR and drug CL. Sarcoplasmic reticulum calcium handling in young DBA/2J vs C57BL/10 mdx models of Duchenne muscular dystrophy The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Decoding nonspecific interactions between human nuclear transport proteins: A computational study The nuclear protein transport between the nucleus and cytosol can be considered a core process of cell regulation. Specially designed proteins in nature such as importins, exportins, and some other transporters facilitate this transport in the cell and control the cellular processes. Transient and weak protein-protein interactions are basis of these various biomolecular processes. Prior to cargo transports, the transport proteins recognize the Nuclear localization signals (NLSs) and Nuclear export signals (NESs) of cargo proteins and, bind to the RanGTP. Also, these proteins bind with other similar protein subunits along with RanGTP to transport cargos. Cell is enormously crowded place where DNA, RNA, proteins, lipids and small molecules cooperatively facilitate numerous cellular processes. In such environment, existence of nonspecific interactions between proteins is quite obvious. Considering this hypothesis, in this study, protein-protein docking approach was applied to determine the binding affinities of 12 human nuclear transport proteins. Results showed that KPNA1, TNPO1 and TNPO3 have greater affinity to bind with other transport proteins. Also, among 78 complexes (12 homodimers and 66 heterodimers), KPNA1-KPNB1, KPNA1-TNPO1 and KPNA1-TNPO3 complexes have the highest stability.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/436462v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@d81d48org.highwire.dtl.DTLVardef@6a929dorg.highwire.dtl.DTLVardef@bfa16eorg.highwire.dtl.DTLVardef@ff610b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Initially, 12 human nuclear transport proteins PDB structures were retrieved from the 1. Protein data bank (PDB). These proteins had some missing terminals and residues thus, we used 2. SWISS-MODEL and 3. MODELLER v.10.1 to model those regions in these proteins. Next, we used widely popular web server, 4. ClusPro v.2.0 for protein-protein docking analysis among 12 proteins. Then, we employed 5. PRODIGY web server to calculate the binding affinities of 78 complexes (12 homodimers & 66 heterodimers). Finally, we utilised three web tools, 6. Arpeggio, 7. PIMA and 8. PDBePISA to analyse top-three complexes (KPNA1-KPNB1, KPNA1-TNPO1 & TNPO3) for in-depth interactions and energetics. A causal test of affect processing bias in response to affect regulation In this study we merged methods from machine learning and human neuroimaging to causally test the role of self-induced affect processing states in biasing the affect processing of subsequent image stimuli. To test this causal relationship we developed a novel paradigm in which (n=40) healthy adult participants observed affective neural decodings of their real-time functional magnetic resonance image (rtfMRI) responses as feedback to guide explicit regulation of their brain (and corollary affect processing) state towards a positive valence goal state. By this method individual differences in affect regulation ability were controlled. Attaining this brain-affect goal state triggered the presentation of pseudo-randomly selected affectively congruent (positive valence) or incongruent (negative valence) image stimuli drawn from the International Affective Picture Set. Separately, subjects passively viewed randomly triggered positively and negatively valent image stimuli during fMRI acquisition. Multivariate neural decodings of the affect processing induced by these stimuli were modeled using the task trial type (state- versus randomly-triggered) as the fixed-effect of a general linear mixed-effects model. Random effects were modeled subject-wise. We found that self-induction of a positive valence brain state significantly positively biased valence processing of subsequent stimuli. As a manipulation check, we validated affect processing state induction achieved by the image stimuli using independent psychophysiological response measures of hedonic valence and autonomic arousal. We also validated the predictive fidelity of the trained neural decoding models using brain states induced by an out-of-sample set of image stimuli. Beyond its contribution to our understanding of the neural mechanisms that bias affect processing this work demonstrated the viability of novel experimental paradigms triggered by pre-defined cognitive states. This line of individual differences research potentially provides neuroimaging scientists with a valuable tool for causal exploration of the roles and identities of intrinsic cognitive processing mechanisms that shape our perceptual processing of sensory stimuli. Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning A hallmark of human intelligence, but challenging for reinforcement learning (RL) agents, is the ability to compositionally generalise, that is, to recompose familiar knowledge components in novel ways to solve new problems. For instance, when navigating in a city, one needs to know the location of the destination and how to operate a vehicle to get there, whether it be pedalling a bike or operating a car. In RL, these correspond to the reward function and transition function, respectively. To compositionally generalize, these two components need to be transferable independently of each other: multiple modes of transport can reach the same goal, and any given mode can be used to reach multiple destinations. Yet there are also instances where it can be helpful to learn and transfer entire structures, jointly representing goals and transitions, particularly whenever these recur in natural tasks (e.g., given a suggestion to get ice cream, one might prefer to bike, even in new towns). Prior theoretical work has explored how, in model-based RL, agents can learn and generalize task components (transition and reward functions). But a satisfactory account for how a single agent can simultaneously satisfy the two competing demands is still lacking. Here, we propose a hierarchical RL agent that learns and transfers individual task components as well as entire structures (particular compositions of components) by inferring both through a non-parametric Bayesian model of the task. It maintains a factorised representation of task components through a hierarchical Dirichlet process, but it also represents different possible covariances between these components through a standard Dirichlet process. We validate our approach on a variety of navigation tasks covering a wide range of statistical correlations between task components and show that it can also improve generalisation and transfer in more complex, hierarchical tasks with goal/subgoal structures. Finally, we end with a discussion of our work including how this clustering algorithm could conceivably be implemented by cortico-striatal gating circuits in the brain. Designing single-cell experiments to harvest fluctuation information while rejecting measurement noise Measurement error is a complicating factor that reduces or distorts the information contained in any experiment. This problem becomes even more serious in the context of experiments that are specifically designed to quantify single-cell gene expression heterogeneity, where important RNA and protein copy numbers are themselves subject to the inherently random fluctuations of biochemical reactions. It is not clear how measurement noise should be managed, in addition to other experiment design variables such as sampling size and frequency, to ensure that collected data will provide useful insights on gene expression mechanisms of interest. To address these fundamental single-cell experiment design challenges, we propose a computational framework that makes explicit use of measurement error modeling and Fisher Information Matrix-based criteria to decide between experimental methods. This unified approach not only quantifies how different noise characteristics affect uncertainty in parameter estimation, but also enables a systematic approach to design hybrid experiments that combine different measurement modalities. Population differences in the length and early-life dynamics of telomeres among European pied flycatchers Telomere length and shortening rate are increasingly used as biomarkers for long-term costs in ecological and evolutionary studies because of their relationships with survival and fitness. Both early-life conditions and growth, and later-life stressors can create variation in telomere shortening rate. Studies on between- population telomere length and dynamics are scarce, despite the expectation that populations exposed to varying environmental constraints would present divergent telomere length patterns. The pied flycatcher (Ficedula hypoleuca) is a passerine bird breeding across Eurasia (from Spain to western Siberia) and migrating through the Iberian Peninsula to spend the non-breeding period in sub-Saharan Africa. Thus, different populations show marked differences in migration distance. We studied the large-scale variation of telomere length and early-life dynamics in the pied flycatcher by comparing six European populations across a north- south gradient (Finland, Estonia, England, and Spain) predicting negative effect of migration distance on adult telomere length, and of nestling growth on nestling telomere dynamics. There were clear population differences in telomere length, with English birds from mid-latitudes having the longest telomeres. Telomere length did not thus show consistent latitudinal variation and was not linearly linked to differences in migration distance. Early-life telomere shortening rate tended to vary between populations. Fast growth was associated with shorter telomeres in the early life, but faster nestling growth affected telomeres more negatively in northern than southern populations. While the sources of between-population differences in telomere-related biology remain to be more intensively studied, our study illustrates the need to expand telomere studies at the between-population level. An End-to-End Deep Learning Speech Coding and Denoising Strategy for Cochlear Implants Cochlear implant (CI) users struggle to understand speech in noisy conditions. To address this problem, we propose a deep learning speech denoising sound coding strategy that estimates the CI electric stimulation patterns out of the raw audio data captured by the micro-phone, performing end-to-end CI processing. To estimate the relative denoising performance differences between various approaches, we compared this technique to a classic Wiener filter and to a convTasNet. Speech enhancement performance was assessed by means of signal-to-noise-ratio improvement and the short-time objective speech intelligibility measure. Additionally, 5 CI users were evaluated for speech intelligibility in noise to assess the potential benefits of each algorithm. Our results show that the proposed method is capable of replacing a CI sound coding strategy while preserving its general use for every listener and performing speech enhancement in noisy environments, without sacrificing algorithmic latency. Evaluation of methods for estimating coalescence times using ancestral recombination graphs The ancestral recombination graph (ARG) is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress towards scalably estimating whole-genome genealogies. In addition to inferring the ARG, some of these methods can also provide ARGs sampled from a defined posterior distribution. Obtaining good samples of ARGs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from three popular ARG inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare 1) the true coalescence times to the inferred times at each locus; 2) the distribution of coalescence times across all loci to the expected exponential distribution; 3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all three methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relates, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices. Cold stress upregulates the expression of heat shock and Frost genes, but the evolution of cold stress resistance is apparently not mediated through either heat shock or Frost genes in the cold stress selected populations of Drosophila melanogaster The ability to thermal adaptation can alter insects reproductive traits and physiologic response. A number of studies in Drosophila documented the higher expression levels of heat shock proteins (Hsps) and Frost (Fst) genes during the recovery phase of cold shock treatment and suggested that higher expression levels of these genes and lipids can protect from cold stress. However, these genes expression and cold adaptation have not been well studied. Therefore, understanding the molecular and biochemical basis of cold adaptation, we examined the levels of lipid and expression patterns of Hsp22, Hsp23, Hsp40, Hsp68, Hsp70, Hsp 83, and Fst genes under the cold stress or benign condition in the populations of Drosophila melanogaster selected for increased resistance to cold shock.

We observed the significant up-regulation of Hsp22, Hsp23, Hsp40, Hsp68, and Fst genes in the FSB and FCB populations during the recovery phase post cold shock compared to the no shock condition. However, there was not a significant change in the transcript levels of these genes between FSB and FCB under both the cold stress or no shock condition. Additionally, we noticed higher total lipid levels in the females from cold shock treatment than those from no shock treatment. This finding suggests that cold selected populations have different mechanisms to sustain cold stress. CryoEM of endogenous mammalian V-ATPase interacting with the TLDc protein mEAK-7 V-ATPases are rotary proton pumps that serve as signaling hubs with numerous proposed binding partners in cells. We used cryoEM combined with exhaustive focused classification to detect endogenous proteins that associate with V-ATPase from porcine kidney. A super-stoichiometric copy of subunit C was found in ~3% of complexes, while an additional ~1.6% of complexes bound mEAK-7, a protein with proposed roles in dauer formation in nematodes and mTOR signaling in mammals. High-resolution cryoEM of porcine kidney V-ATPase with recombinant mEAK-7 shows that mEAK-7s TLDc domain interacts with V-ATPases stator while its C-terminal  helix binds V-ATPases rotor. This crosslink would be expected to inhibit rotary catalysis. However, unlike inhibition of yeast V-ATPase by the TLDc protein Oxr1p, exogenous mEAK-7 does not inhibit V-ATPase and mEAK-7 overexpression in cells does not alter lysosomal or phagosomal pH. Instead, cryoEM suggests that interaction of mEAK-7 with V-ATPase is disrupted by ATP-induced rotation of the rotor. Comparison of Oxr1p and mEAK-7 binding explains this difference. Together, these results show that differences in V-ATPase binding by TLDc domain-containing proteins can lead to effects ranging from strong inhibition to formation of labile interactions that are sensitive to the enzymes activity. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Destructive fishing - A ubiquitously used but vague term? Usage and impacts across academic research, media and policy The term "destructive fishing" appears in multiple international policy instruments intended to improve outcomes for marine biodiversity, coastal communities and sustainable fisheries. However, the meaning of "destructive fishing" is often vague, limiting effectiveness in policy. Therefore, in this study we systematically reviewed the use of "destructive fishing" in three record types: academic literature, media articles, and policy documents between 1976-2020. A more detailed analysis was performed on sub-sets of these records, considering the extent to which the term is characterised, geographic distribution of use, and specific impacts and practices associated with the term. We found that use of "destructive fishing" relative to the generic term  fisheries has increased since the 1990s. Records focused predominantly on fishing practices in South-eastern Asia, followed by Southern Asia and Europe. The term was characterised in detail in only 15% of records. Habitat damage and blast/poison fishing were the most associated ecological impacts and gear/practices, respectively. Bottom trawling and unspecified net fishing were regularly linked to destructive fishing. Importantly, the three record types use the term differently. Academic literature tends to specifically articulate the negative impacts, while media articles focus generally on associated gears/practices. Significant regional variation also exists in how the term is used and what phenomena it is applied to. This study provides evidence and recommendations to inform stakeholders in any future pursuit of a unified definition of "destructive fishing" to support more meaningful implementation of global sustainability goals. Nrg1/ErbB Signaling-Mediated Regulation of Fibrosis After Myocardial Infarction RATIONALEAppropriate fibrotic tissue formation after myocardial infarction (MI) is crucial to maintenance of the hearts structure. Reparative or M2-like macrophages play a vital role in post-MI fibrosis by activating cardiac fibroblasts. However, the mechanism by which post-MI cardiac fibrosis is regulated is not fully understood.

OBJECTIVEWe investigated the cellular and molecular mechanisms of post-MI fibrotic tissue formation, especially those related to regulation of cellular senescence and apoptosis.

METHODS AND RESULTSIn vivo and in vitro experiments were used to investigate the molecular and cellular mechanisms through which post-MI fibrosis occurs, with a focus on the role of M2-like macrophages. Microarray analysis revealed that CD206+F4/80+CD11b+ M2-like macrophages collected from mouse hearts on post-MI day 7 showed increased expression of neuregulin 1 (Nrg1). Nrg1 receptor epidermal growth factor receptor ErbB was expressed on cardiac fibroblasts in the infarct area. In cardiac fibroblasts in which hydrogen peroxide-induced senescence, M2-like macrophage-derived Nrg1 suppressed both senescence and apoptosis of the fibroblasts, whereas blockade of ErbB function significantly accelerated. M2-like macrophage-derived Nrg1/ErbB/PI3K/Akt signaling, which was shown to be related to anti-senescence, was activated in damaged cardiac fibroblasts. Interestingly, systemic blockade of ErbB function in MI model mice enhanced senescence and apoptosis of cardiac fibroblasts and exacerbated inflammation. Further, increased accumulation of M2-like macrophages resulted in excessive progression of fibrosis in post-MI murine hearts. The molecular mechanism underlying regulation of fibrotic tissue formation in the infarcted myocardium was shown in part to be attenuation of apoptosis and senescence of cardiac fibroblasts by activation of Nrg1/ErbB/PI3K/Akt signaling.

CONCLUSIONSM2-like macrophage-mediated regulation of Nrg1/ErbB signaling, have a substantial effect on fibrotic tissue formation in the infarcted adult mouse heart, is critical for suppressing the progression of senescence and apoptosis of cardiac fibroblasts. Possible Cross Reactivity of Feline and White-tailed Deer Antibodies Against the SARS-CoV-2 Receptor Binding Domain In late 2019, a novel coronavirus began circulating within humans in central China. It was designated SARS-CoV-2 because of its genetic similarities to the 2003 SARS coronavirus (SARS-CoV). Now that SARS-CoV-2 has spread worldwide, there is a risk of it establishing new animal reservoirs and recombination with native circulating coronaviruses. To screen local animal populations in the United States for exposure to SARS-like coronaviruses, we developed a serological assay using the receptor binding domain (RBD) from SARS-CoV-2. SARS-CoV-2s RBD is antigenically distinct from common human and animal coronaviruses allowing us to identify animals previously infected with SARS-CoV or SARS-CoV-2. Using an indirect ELISA for SARS-CoV-2s RBD, we screened serum from wild and domestic animals for the presence of antibodies against SARS-CoV-2s RBD. Surprisingly pre-pandemic feline serum samples submitted to the University of Tennessee Veterinary Hospital were [~]50% positive for anti-SARS RBD antibodies. Some of these samples were serologically negative for feline coronavirus (FCoV), raising the question of the etiological agent generating anti-SARS-CoV-2 RBD cross-reactivity. We also identified several white-tailed deer from South Carolina with anti-SARS-CoV-2 antibodies. These results are intriguing as cross-reactive antibodies towards SARS-CoV-2 RBD have not been reported to date. The etiological agent responsible for seropositivity was not readily apparent, but finding seropositive cats prior to the current SARS-CoV-2 pandemic highlights our lack of information about circulating coronaviruses in other species.

ImportanceWe report cross-reactive antibodies from pre-pandemic cats and post-pandemic South Carolina white-tailed deer that are specific for that SARS-CoV RBD. There are several potential explanations for this cross-reactivity, each with important implications to coronavirus disease surveillance. Perhaps the most intriguing possibility is the existence and transmission of an etiological agent (such as another coronavirus) with similarity to SARS-CoV-2s RBD region. However, we lack conclusive evidence of pre-pandemic transmission of a SARS-like virus. Our findings provide impetus for the adoption of a One Health Initiative focusing on infectious disease surveillance of multiple animal species to predict the next zoonotic transmission to humans and future pandemics. RNA degradation of blood reveals a time diagnostic window in a controlled environment 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 Decoding the porcine developing spatial processing system and production of human entorhinal stellate cell-like cells by a direct programming approach. Classic studies investigating how and when the entorhinal cortex (component of the memory processing system of the brain) develops have been based on traditional thymidine autoradiography and histological techniques. In this study, we take advantage of modern technologies to trace at a high resolution, the cellular complexity of the developing porcine medial entorhinal cortex by using single-cell profiling. The postnatal medial entorhinal cortex comprises 4 interneuron, 3 pyramidal neuron and 2 stellate cell populations which emerge from intermediate progenitor and immature neuron populations. We discover four MGE-derived interneurons and one CGE-derived interneuron population as well as several IN progenitors. We also identify two oligodendrocyte progenitor populations and three populations of oligodendrocytes. We perform a proof-of-concept experiment demonstrating that porcine scRNA-seq data can be used to develop novel protocols for producing human entorhinal cells in-vitro. We identified six transcription factors (RUNX1A1, SOX5, FOXP1, MEF2C, TCF4, EYA2) important in neurodevelopment and differentiation from one RELN+ stellate cell population. Using a lentiviral vector approach, we reprogrammed human induced pluripotent stem cells into stellate cell-like cells which expressed RELN, SATB2, LEF1 and BCL11B. Our findings contribute to the understanding of the formation of the brains cognitive memory and spatial processing system and provides proof-of-concept for the production of entorhinal cells from human pluripotent stem cells in-vitro. 2,3-cAMP treatment mimics stress molecular response in Arabidopsis thaliana The role of the RNA degradation product 2,3-cyclic adenosine monophosphate (2,3-cAMP) is poorly understood. Recent studies have identified 2,3-cAMP in plant material and determined its role in stress signaling. The level of 2,3-cAMP increases upon wounding, dark, and heat, and 2,3-cAMP by binding to an RNA-binding protein, Rbp47b, promotes stress granule (SG) assembly. To gain further mechanistic insight into 2,3-cAMP function, we used a multi-omics approach combining transcriptomics, metabolomics, and proteomics to dissect Arabidopsis response to 2,3-cAMP treatment. We demonstrated that 2,3-cAMP is metabolized into adenosine, suggesting that the well-known cyclic nucleotide-adenosine pathway from human cells might also exist in plants. Transcriptomic analysis revealed only minor overlap between 2,3-cAMP-and adenosine-treated plants, suggesting that these molecules act through independent mechanisms. Treatment with 2,3-cAMP changed the levels of hundreds of transcripts, proteins, and metabolites, many previously associated with plant stress responses including protein and RNA degradation products, glucosinolates, chaperones and SG components. Finally, we demonstrated that 2,3-cAMP treatment influences the movement of processing bodies, supporting the role of 2,3-cAMP in the formation and motility of membraneless organelles. Tetrazoles as PPARγ ligands: A Structural and Computational Investigation. Diabetes is an important chronic disease affecting about 10% of the adult population in the US and over 420 million people worldwide, resulting in 1.6 million deaths every year, according to the World Health Organization. The most common type of the disease, type 2 diabetes, can be pharmacologically managed using oral hypoglycemic agents or thiazolidinediones (TZDs), such as pioglitazone, which act by activating the Peroxisome Proliferated-Activated Receptor {gamma}. Despite their beneficial effects in diabetes treatment, TZDs like rosiglitazone and troglitazone were withdrawn due to safety reasons, creating a void in the pharmacological options for the treatment of this important disease. Here, we explored a structure-based approach in the screening for new chemical probes for a deeper investigation of the effects of PPAR{gamma} activation. A class of tetrazole compounds was identified and the compounds named T1, T2 and T3 were purchased and evaluated for their ability to interact with the PPAR{gamma} ligand binding domain (LBD). The compounds were binders with micromolar range affinity, as determined by their IC50 values. A Monte Carlo simulation of the compound T2 revealed that the tetrazole ring makes favorable interaction with the polar arm of the receptor binding pocket. Finally, the crystal structure of the PPAR{gamma}-LBD-T2 complex was solved at 2.3 [A], confirming the binding mode for this compound. The structure also revealed that, when the helix H12 is mispositioned, an alternative binding conformation is observed for the ligand suggesting an H12-dependent binding conformation for the tetrazole compound. Evaluation of SARS-CoV-2 Entry, Inflammation and New Therapeutics in Human Lung Tissue Cells The development of physiological models that reproduce SARS-CoV-2 infection in primary human cells will be instrumental to identify host-pathogen interactions and potential therapeutics. Here, using cell suspensions directly from primary human lung tissues (HLT), we have developed a rapid platform for the identification of viral targets and the expression of viral entry factors, as well as for the screening of viral entry inhibitors and anti-inflammatory compounds. The direct use of HLT cells, without long-term cell culture and in vitro differentiation approaches, preserves main immune and structural cell populations, including the most susceptible cell targets for SARS-CoV-2; alveolar type II (AT-II) cells, while maintaining the expression of proteins involved in viral infection, such as ACE2, TMPRSS2, CD147 and AXL. Further, antiviral testing of 39 drug candidates reveals a highly reproducible method, suitable for different SARS-CoV-2 variants, and provides the identification of new compounds missed by conventional systems, such as VeroE6. Using this method, we also show that interferons do not modulate ACE2 expression, and that stimulation of local inflammatory responses can be modulated by different compounds with antiviral activity. Overall, we present a relevant and rapid method for the study of SARS-CoV-2.

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/440731v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@96abf6org.highwire.dtl.DTLVardef@1f3cfe3org.highwire.dtl.DTLVardef@1d55fdborg.highwire.dtl.DTLVardef@1884cd6_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsEx vivo physiological systems for the study of SARS-CoV-2-host interactions are scarce. Here, we establish a method using primary human lung tissue (HLT) cells for the rapid analysis of cell tropism and identification of therapeutics.

O_LIHLT cells preserve main cell subpopulations, including alveolar type-2 cells, and expression of SARS-CoV-2 entry factors ACE2, CD147, TMPRSS2 and AXL.
C_LIO_LIHLT cells are readily susceptible to SARS-CoV-2 infection without the need of cell isolation or further cell differentiation.
C_LIO_LIAntiviral testing in HLT cells allows the rapid identification of new drug candidates against SARS-CoV-2 variants, missed by conventional systems.
C_LIO_LILocal inflammation is supported in HLT cells and offers the identification of relevant anti-inflammatory compounds for SARS-CoV-2 infection.
C_LI STING activation promotes robust immune response and NK cell-mediated tumor regression in glioblastoma models Immunotherapy has had a tremendous impact on cancer treatment in the past decade, with hitherto unseen responses at advanced and metastatic stages of the disease. However, the aggressive brain tumor glioblastoma (GBM) is highly immunosuppressive and remains largely refractory to current immunotherapeutic approaches. The cGAS-STING cytoplasmic double stranded DNA (dsDNA) sensing pathway has emerged as a next-generation immunotherapy target with potent local immune stimulatory properties.

Here, we investigated the status of the STING pathway in GBM and the modulation of the brain tumor microenvironment (TME) with the STING agonist ADU-S100. Our data reveal the presence of STING in human GBM specimens, where it stains strongly in the tumor vasculature. We show that human GBM explants can respond to STING agonist treatment by secretion of inflammatory cytokines. In murine GBM models, we show a profound shift in the tumor immune landscape after STING agonist treatment, with massive infiltration of the tumor-bearing hemisphere with innate immune cells including inflammatory macrophages, neutrophils and NK populations. Treatment of established murine intracranial GL261 and CT-2A tumors by biodegradable ADU-S100-loaded intracranial implants demonstrated a significant increase in survival in both models and long-term survival with immune memory in GL261. Responses to treatment were abolished by NK cell depletion. This study reveals therapeutic potential and deep remodeling of the TME by STING activation in GBM and warrants the further examination of STING agonists alone or in combination with other immunotherapies such as cancer vaccines, CAR T cells, NK therapies or immune checkpoint blockade.

Significance statementModulation of the immune microenvironment is critical for immunosuppressive and therapy refractory tumors like glioblastoma. Activation of the STING pathway deeply remodels the brain tumor environment and attracts innate immune cells and natural killer cell populations, producing a robust antitumor effect with long-term immune memory. We further show that human glioblastoma tissue can respond to the therapy and lay the foundations for combined intracranial immunotherapies by using crosslinked biodegradable brain implants. 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. 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.