Improving localization precision via restricting biomolecule confined stochastic motion in SMLM Single-molecule localization microscopy (SMLM) boosts its applications when combined with the studies of cells, in which nanometer-sized biomolecules are irresolvable due to diffraction limit unless being subjected to SMLM. Although being well immobilized, given the nanometer sizes of biological molecules, they are still capable of movement stochastically around their immobilized sites. The influence of such motion on image quality and possible improvements have not yet been systematically investigated. Here, we accessed the biomolecule stochastic motion in SMLM by calculating the displacements between different localizations from the same molecule in single-molecule samples of Alexa Fluor-647-conjugated oligonucleotides. We found that, for most molecules, localization displacements at random frame intervals are remarkably larger than those between temporally neighbouring frames despite of drift correction, showing that biomolecule stochastic motion is involved in SMLM. Furthermore, the localization displacements were observed to increase with frame intervals and then saturate, suggesting biomolecule stochastic motion is confined within a finite area. Moreover, we showed that the localization precision is deteriorated by enlarging molecule sizes and improved by sample post-fixation. This study reveals confined stochastic motion of biomolecules increase localization uncertainty in SMLM, and improved localization precision can be achieved via restricting biomolecule stochastic motion.
Cryptic pathogen-sugar interactions revealed by universal saturation transfer analysis Many host pathogen interactions such as human viruses (including non-SARS-coronaviruses) rely on attachment to host cell-surface glycans. There are conflicting reports about whether the Spike protein of SARS-CoV-2 binds to sialic acid commonly found on host cell-surface N-linked glycans. In the absence of a biochemical assay, the ability to analyze the binding of glycans to heavily- modified proteins and resolve this issue is limited. Classical Saturation Transfer Difference (STD) NMR can be confounded by overlapping sugar resonances that compound with known experimental constraints. Here we present  universal saturation transfer analysis (uSTA), an NMR method that builds on existing approaches to provide a general and automated workflow for studying protein-ligand interactions. uSTA reveals that B-origin-lineage-SARS-CoV-2 spike trimer binds sialoside sugars in an  end on manner and modelling guided by uSTA localises binding to the spike N-terminal domain (NTD). The sialylated-polylactosamine motif is found on tetraantennary human N-linked-glycoproteins in deeper lung and may have played a role in zoonosis. Provocatively, sialic acid binding is abolished by mutations in some subsequent SARS- CoV-2 variants-of-concern. A very high resolution cryo-EM structure confirms the NTD location and  end on mode; it rationalises the effect of NTD mutations and the structure-activity relationship of sialic acid analogues. uSTA is demonstrated to be a robust, rapid and quantitative tool for analysis of binding, even in the most demanding systems.

Extended AbstractThe surface proteins found on both pathogens and host cells mediate entry (and exit) and influence disease progression and transmission. Both types can bear host-generated post- translational modifications such as glycosylation that are essential for function but can confound biophysical methods used for dissecting key interactions. Several human viruses (including non- SARS-coronaviruses) attach to host cell-surface N-linked glycans that include forms of sialic acid (sialosides). There remains, however, conflicting evidence as to if or how SARS-associated coronaviruses might use such a mechanism. Here, we demonstrate quantitative extension of  saturation transfer protein NMR methods to a complete mathematical model of the magnetization transfer caused by interactions between protein and ligand. The method couples objective resonance-identification via a deconvolution algorithm with Bloch-McConnell analysis to enable a structural, kinetic and thermodynamic analysis of ligand binding beyond previously-perceived limits of exchange rates, concentration or system. Using an automated and openly available workflow this  universal saturation transfer analysis (uSTA) can be readily-applied in a range of even heavily-modified systems in a general manner to now obtain quantitative binding interaction parameters (KD, kEx). uSTA proved critical in mapping direct interactions between natural sialoside sugar ligands and relevant virus-surface attachment glycoproteins - SARS-CoV-2-spike and influenza-H1N1-haemagglutinin variants - by quantitating ligand signal in spectral regions otherwise occluded by resonances from mobile protein glycans (that also include sialosides). In B- origin-lineage-SARS-CoV-2 spike trimer  end on-binding to sialoside sugars was revealed contrasting with  extended surface-binding for heparin sugar ligands; uSTA-derived constraints used in structural modelling suggested sialoside-glycan binding sites in a beta-sheet-rich region of spike N-terminal domain (NTD). Consistent with this, uSTA-glycan binding was minimally- perturbed by antibodies that neutralize the ACE2-binding domain (RBD) but strongly disrupted in spike from the B1.1.7/alpha and B1.351/beta variants-of-concern, which possess hotspot mutations in the NTD. Sialoside binding in B-origin-lineage-NTD was unequivocally pinpointed by cryo-EM to a site that is created from residues that are notably deleted in variants (e.g. H69,V70,Y145 in alpha). An analysis of beneficial genetic variances in cohorts of patients from early 2020 suggests a model in which this site in the NTD of B-origin-lineage-SARS-CoV-2 (but not in alpha/beta-variants) may have exploited a specific sialylated-polylactosamine motif found on tetraantennary human N-linked-glycoproteins in deeper lung. Together these confirm a novel binding mode mediated by the unusual NTD of SARS-CoV-2 and suggest how it may drive virulence and/or zoonosis via modulation of glycan attachment. Since cell-surface glycans are widely relevant to biology and pathology, uSTA can now provide ready, quantitative, widespread analysis of complex, host-derived and post-translationally modified proteins with putative ligands relevant to disease even in previously confounding complex systems.
Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression level with cell volume While most genes expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiaes mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model. Robust and Remote Measurement of Heart Rate Based on A Surveillance Camera Arrhythmia is a marked symptom of many cardiovascular diseases (CVDs). The accurate and timely detection of heart rate can greatly reduce the harm of arrhythmia to people. However, it is still a challenge to robustly and remotely measure heart rate in daily life due to the changing environmental conditions during measurement, such as the varying light intensity, the movement of people, and the uncertain distance between the sensor to people. In this study, we propose a method to accurately measure human heart rate within a distance of 4.5 meters under different light intensities by simply using a surveillance camera. After a 20-second color video of a persons hand is captured by the camera, a method based on the Fast Fourier Transform (FFT) algorithm is designed to extract the blood volume pulse wave to calculate the heart rate. According to the comparison between the real heart rate and results measured by electrocardiography (ECG), the proposed method achieves an accuracy of 95.8% when the measurement is performed within a distance of 4.5 meters and 90% when within 5.0 meters. Our experiments show that when the illuminance varies between 100-1000 lux (lighting level indoor), we still get the correct results. Our experiments also demonstrate that the proposed method accurately obtain heart rate even when the light intensity is below 32 lux (300-500 lux in a workplace environment). The methods strong adaptability to changing environmental conditions makes it applicable to many scenarios, such as homes of the elderly, classrooms, and other public spaces. High performance single-cell gene regulatory network inference at scale: The Inferelator 3.0 MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.

ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.

AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/). Pathological LSD1 mutations repress enhancer-mediated gene regulatory networks in early differentiation Lysine-specific demethylase 1 (LSD1/KDM1A) demethylates both histone and non-histone substrates, recruits repressive chromatin complexes, and is increased in cancers. De novo LSD1 mutations impairing protein function lead to a rare developmental disorder, but the molecular details of the pathology remains unclear. Using patient-derived fibroblasts, reprogrammed pluripotent stem cells, and differentiated cells, we found over 4000 differentially expressed genes and 68 transcription factors (TFs) whose motif accessibilities changed upon LSD1 mutation. An enhancer-mediated gene regulatory network approach identified transcriptional repressors with impaired activity in fibroblast and stem cells, leading to erroneous activation of their target genes. We also revealed overall decreases in TF target gene expression during early lineage differentiation of LSD1 mutant stem cells, likely caused by increased activity of repressive histone deacetylases (HDACs), co-factors of LSD1. Indeed, an HDACs inhibitor restored changes in gene expression including downregulation phenotype. Our findings characterize the molecular pathogenesis of LSD1 mutations and suggest potential therapeutic strategies for the developmental disorder and cancers caused by LSD1 dysregulations. Drug development of an affinity enhanced, broadly neutralizing heavy chain-only antibody that restricts SARS-CoV-2 in rodents We have identified camelid single-domain antibodies (VHHs) that cross-neutralize SARS-CoV-1 and -2, such as VHH72, which binds to a unique highly conserved epitope in the viral receptor-binding domain (RBD) that is difficult to access for human antibodies. Here, we establish a protein engineering path for how a stable, long-acting drug candidate can be generated out of such a VHH building block. When fused to human IgG1-Fc, the prototype VHH72 molecule prophylactically protects hamsters from SARS-CoV-2. In addition, we demonstrate that both systemic and intranasal application protects hACE-2-transgenic mice from SARS-CoV-2 induced lethal disease progression. To boost potency of the lead, we used structure-guided molecular modeling combined with rapid yeast-based Fc-fusion prototyping, resulting in the affinity-matured VHH72_S56A-Fc, with subnanomolar SARS-CoV-1 and -2 neutralizing potency. Upon humanization, VHH72_S56A was fused to a human IgG1 Fc with optimized manufacturing homogeneity and silenced effector functions for enhanced safety, and its stability as well as lack of off-target binding was extensively characterized. Therapeutic systemic administration of a low dose of VHH72_S56A-Fc antibodies strongly restricted replication of both original and D614G mutant variants of SARS-CoV-2 virus in hamsters, and minimized the development of lung damage. This work led to the selection of XVR011 for clinical development, a highly stable anti-COVID-19 biologic with excellent manufacturability. Additionally, we show that XVR011 is unaffected in its neutralizing capacity of currently rapidly spreading SARS-CoV-2 variants, and demonstrate its unique, wide scope of binding across the Sarbecovirus clades. R7 photoreceptor axon targeting depends on the relative levels of lost and found expression in R7 and its synaptic partners As neural circuits form, growing processes select the correct synaptic partners through interactions between cell surface proteins. The presence of such proteins on two neuronal processes may lead to either adhesion or repulsion; however, the consequences of mismatched expression have rarely been explored. Here we show that the Drosophila CUB-LDL protein Lost and found (Loaf) is required in the UV-sensitive R7 photoreceptor for normal axon targeting only when Loaf is also present in its synaptic partners. Although targeting occurs normally in loaf mutant animals, removing loaf from photoreceptors or expressing it in their postsynaptic neurons Tm5a/b or Dm9 in a loaf mutant causes mistargeting of R7 axons. Loaf localizes primarily to intracellular vesicles including endosomes. We propose that Loaf regulates the trafficking or function of one or more cell surface proteins, and an excess of these proteins on the synaptic partners of R7 prevents the formation of stable connections. Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. Mutualism-enhancing mutations dominate early adaptation in a microbial community Species interactions drive species evolution while evolution shapes these interactions. The resulting eco-evolutionary dynamics, their outcomes and their repeatability depend on how adaptive mutations available to community members affect fitness and ecologically relevant traits. However, the diversity of adaptive mutations available to community members is not well characterized, and we do not know how this diversity is affected by the ecological milieu. Here we use barcode lineage tracking to address this gap in a competitive mutualism between the yeast Saccharomyces cerevisiae and the alga Chlamydomonas reinhardtii. We find that yeast has access to many adaptive mutations with diverse ecological consequences, in particular, those that increase and reduce the yields of both species. The presence of alga does not change which mutations are adaptive in yeast (i.e., there is no fitness trade-off for yeast between growing alone or with alga), but rather shifts selection to favor yeast mutants that increase the yields of both species and make the mutualism stronger. Thus, in the presence of alga, we find that yeast repeatably evolves to become more cooperative, even though cooperativity is not directly favored by natural selection in our system. Our results demonstrate that ecological interactions not only alter the trajectory of evolution but also dictate its repeatability; in particular, weak mutualisms can repeatably evolve to become stronger. Experimental evolution reveals post-transcriptional regulation as a novel driver of Leishmania fitness gain The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings. Characterization of DNA extrusion scenarios underlying aggregate Hi-C patterns by a new computational framework 1Aggregate Hi-C maps centered on several genetic elements show significant DNA extrusion features. However, these features are missing from the component Hi-C images. To resolve this discrepancy, we present a new computational framework that reconstructs DNA extrusion scenarios (DESs) and explains the enhancement of DNA extrusion features by aggregation. We showed that the reconstructed DES is essential to understand the site interactions of the relevant genetic elements. For example, CCCTC-binding factor (CTCF) binding elements (CBE) with a specific motif direction are only affected by DNA extrusion activities initiated from one side, manifested as a directional bias. About half of promoters search for enhancers in a specific direction, as indicated by the corresponding DES. Moreover, since DNA extrusion does not pause at promoter or enhancer elements, direct promoter-enhancer contacts are not long-lasting; rather, promoters and enhancers are brought in proximity by continuous, dynamic DNA extrusion. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. The impact of housing conditions on mesenchymal stromal/stem cell populations differ between adipose tissue and skeletal muscle BackgroundIn pigs, the ratio between lean mass and fat mass in the carcass determines production efficiency and is strongly influenced by the number and size of cells in tissues. During growth, the increase in the number of cells results from the recruitment of different populations of multipotent mesenchymal stromal/stem cells (MSCs) residing in the tissues. We hypothesized that the impact of hygiene of housing conditions during growth on the proportions of MSCs in adipose tissue and skeletal muscle may differ between pigs with different residual feed intake (RFI), a measure of feed efficiency.

MethodsAt the age of 12 weeks, Large White pigs from two lines divergently selected for low and high RFI were housed in two contrasting hygiene conditions (good vs poor). After six weeks, pigs were slaughtered (n = 30; 5-9/group). Samples of subcutaneous adipose tissue and longissimus skeletal muscle were collected, and cells from the stromal vascular fraction (SVF), which includes mesenchymal stromal/stem cell populations, were isolated from each tissue. Adipose and muscle cell populations from the SVF were phenotyped by flow cytometry using antibodies that targeted different cell surface markers (CD45 to separate hematopoietic cells from MSCs; CD34, CD38, CD56 and CD140a to identify MSC populations with adipogenic and/or myogenic potential).

ResultsAdipose tissue and muscle shared some common MSC populations although MSC diversity was higher in muscle than in adipose tissue. In muscle, the CD45-CD56+CD34-CD140a+ and CD45-CD56+CD34+CD140a+ cell populations were abundant. Of these two cell populations, only the proportions of CD45-CD56+CD34+CD140a+ cells increased (P < 0.05) in pigs housed in poor hygiene as compared with pigs in good hygiene conditions. For the CD45-CD56-CD34- cell population, present in low proportion, there was an interaction between hygiene condition and genetic line (P < 0.05) with a decrease in low RFI pigs housed in poor hygiene conditions. In adipose tissue, the two abundant MSC populations were CD45-CD56-CD34- and CD45-CD56+CD34-. The proportion of CD45-CD56-CD34- cells increased (P < 0.05) whereas the proportion of CD45-CD56+CD34- tended to decrease (P < 0.1) in pigs housed in poor conditions. This study shows that the proportions of some MSC populations were affected by hygiene of housing conditions in a tissue-dependent manner in pigs of both RFI lines. It suggests that MSCs may play a significant role in adipose tissue and skeletal muscle homeostasis and may influence later growth and body composition in growing animals. 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. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns It has been stated that in human migratory behavior, the step length series may have temporal correlation and that there is some relationship between this time dependency and the fact that the frequency distribution of step length follows a power-law distribution. Furthermore, the frequency of occurrence of the step length in some large marine organisms has been found to switch between power-law and exponential distributions, depending on the difficulty of prey acquisition. However, to date it has not been clarified how the aforementioned three phenomena arise: the positive correlation created in the step length series, the relation between the positive correlation of the step length series and the form of an individuals step length distribution, and the switching between power-law and exponential distributions depending on the abundance of prey. This study simulated foraging behavior using the Bayesian decision-making agent simultaneously performing both knowledge learning and knowledge-based inference to analyze how the aforementioned three phenomena arise. In the agent with learning and inference, past experiences were stored as hypotheses (knowledge) and they were used in current foraging behavior; at the same time, the hypothesis continued to be updated based on new experiences. The simulation results show that the agent with both learning and inference has a mechanism that simultaneously causes all the phenomena. Statistics of antibody binding to the spike protein explain the dependence of COVID 19 infection risk on antibody concentration and affinity The increase of COVID-19 breakthrough infection risk with time since vaccination has a clear relationship to the decrease of antibody concentration with time. The empirically-observed dependence on blood IgG anti-receptor binding domain antibody concentration of SARS-CoV-2 vaccine efficacy against infection has a rational explanation in the statistics of binding of antibody to spike proteins on the virus surface, leading to blocking of binding to the receptor: namely that the probability of infection is the probability that a critical number of the spike proteins protruding from the virus are unblocked. The model is consistent with the observed antibody concentrations required to induce immunity and with the observed dependence of vaccine efficacy on antibody concentration and thus is a useful tool in the development of models to relate, for an individual person, risk of infection given measured antibody concentration. It can be used to relate population breakthrough infection risk to the distribution across the population of antibody concentration, and its variation with time. A thermodynamic model for water activity and redox potential in evolution and development Reactions involving water and oxygen are basic features of geological and biological processes. To understand how life interacts with its environment requires monitoring interactions with H2O and O2 at timescales relevant to not only organismal growth but also billions of years of geobiological evolution. Here, chemical transformations intrinsic to evolution and development were characterized by analyzing data from recent phylostratigraphic and proteomic studies. This two-stage analysis involves obtaining chemical metrics (carbon oxidation state and stoichiometric hydration state) from the elemental compositions of proteins followed by modeling the relative stabilities of target proteins against a proteomic background to infer thermodynamic parameters (oxygen fugacity, water activity, and virtual redox potential (Eh)). The main results of this study are a rise in carbon oxidation state of proteins spanning the time of the Great Oxidation Event, a rise in virtual redox potential that coincides with the likely emergence of aerobic metabolism, a rise in carbon oxidation state of proteins inferred from the transcriptome in late stages of Bacillus subtilis biofilm growth, and a drop in stoichiometric hydration state of the fruit fly developmental proteome at the same time as a drop in organismal water content. Stoichiometric hydration state also decreases for proteins with more recent gene ages and through stages of biofilm development, leading to predictions of higher hydration potentials at earlier time points. By building chemical representations of protein evolution and developmental proteomes, exciting new types of geobiochemical proxies can be developed. Phenotypic heterogeneity driven by plasticity of the intermediate EMT state governs disease progression and metastasis in breast cancer The Epithelial-to-Mesenchymal Transition (EMT) is a developmental cellular program frequently coopted by cancer cells1 and is a key contributor to both heterogeneity in solid tumors2-4 and later stage chemo-resistance and metastasis5,6. Rather than being a switch from an epithelial to a mesenchymal state, increasing evidence points to the existence of intermediate EMT states, wherein cells co-express both epithelial and mesenchymal traits7-13. Multiple stable intermediate EMT states possessing unique characteristics exist across the EMT spectrum7,8,14,15, contributing to the complex heterogeneity of tumors to promote metastasis16. While much work has been carried out identifying and characterizing EMT-inducing transcription factors17-20, the transcriptional and epigenetic networks responsible for the stability and maintenance of the midpoints along the EMT spectrum are poorly defined. In addition, there are currently no approaches to identifying and quantifying intermediate EMT subpopulations within patient tumors to evaluate their prognostic significance. Using clonally isolated derivatives of the SUM149PT breast cancer cell line, we systematically interrogate how each EMT state independently contributes to heterogeneity and influences metastatic progression, uncovering the role of RUNX2 in stabilizing certain intermediate states. Using SUM149PT-derived tumors as a training set, we develop an entropy-based model to quantify phenotypic heterogeneity and EMT status. Remarkably, the majority of cell states captured in the SUM149PT model are represented in a selection of patient tumors, laying the foundation for quantification of epithelial-mesenchymal heterogeneity and understanding the role of the intermediate EMT state in tumor progression. Hippocampal sharp wave-ripples and the associated sequence replay emerge from structured synaptic interactions in a network model of area CA3 Hippocampal place cells are activated sequentially as an animal explores its environment. These activity sequences are internally recreated ("replayed"), either in the same or reversed order, during bursts of activity (sharp wave-ripples; SWRs) that occur in sleep and awake rest. SWR-associated replay is thought to be critical for the creation and maintenance of long-term memory. In order to identify the cellular and network mechanisms of SWRs and replay, we constructed and simulated a data-driven model of area CA3 of the hippocampus. Our results show that the chain-like structure of recurrent excitatory interactions established during learning not only determines the content of replay, but is essential for the generation of the SWRs as well. We find that bidirectional replay requires the interplay of the experimentally confirmed, temporally symmetric plasticity rule, and cellular adaptation. Our model provides a unifying framework for diverse phenomena involving hippocampal plasticity, representations, and dynamics, and suggests that the structured neural codes induced by learning may have greater influence over cortical network states than previously appreciated. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. A revised view on the evolution of glutamine synthetase isoenzymes in plants Glutamine synthetase (GS) is a key enzyme responsible for the incorporation of inorganic nitrogen in the form of ammonium into the amino acid glutamine. The genes encoding GS are among the oldest existing genes in living organisms. In plants, two groups of functional GS enzymes are found: eubacterial GSIIb (GLN2) and eukaryotic GSIIe (GLN1/GS). Phylogenetic analyses have shown that the GLN2 group originated from bacteria following horizontal gene transfer. Only GLN1/GS genes are found in vascular plants, which suggests that they are involved in the final adaptation of plants to terrestrial life. The present phylogenetic study reclassifies the different GS of seed plants into three clusters: GS1a, GS1b and GS2. The presence of genes encoding GS2 has been expanded to Cycadopsida gymnosperms, which suggests the origin of this gene in a common ancestor of Cycadopsida, Ginkgoopsida and angiosperms. GS1a genes have been identified in all gymnosperms, basal angiosperms and some Magnoliidae species. Previous studies in conifers and the gene expression profiles obtained in ginkgo and magnolia in the present work could explain the absence of GS1a in more recent angiosperm species (e.g., monocots and eudicots) due to the redundant roles of GS1a and GS2 in photosynthetic cells. Altogether, the results provide a better understanding of the evolution of plant GS isoenzymes and their physiological roles, which is valuable for improving crop nitrogen use efficiency and productivity. How grower decision-making is modelled impacts the effect of plant disease control. While the spread of plant disease depends strongly on biological factors driving transmission, it also has a human dimension. Disease control depends on decisions made by individual growers, who are in turn influenced by a broad range of factors. Despite this, human behaviour has rarely been included in plant epidemic models. Considering Cassava Brown Streak Disease, we model how the perceived increase in profit due to disease management influences participation in clean seed systems (CSS). Our models are rooted in game theory, with growers making strategic decisions based on the expected profitability of different control strategies. We find that both the information used by growers to assess profitability and the perception of economic and epidemiological parameters influence long-term participation in the CSS. Over-estimation of infection risk leads to lower participation in the CSS, as growers perceive that paying for the CSS will be futile. Additionally, even though good disease management can be achieved through the implementation of CSS, and a scenario where all controllers use the CSS is achievable when growers base their decision on the average of their entire strategy, CBSD is rarely eliminated from the system. These results are robust to stochastic and spatial effects. Our work highlights the importance of including human behaviour in plant disease models, but also the significance of how that behaviour is included. Apolipoprotein M attenuates anthracycline cardiotoxicity and lysosomal injury ObjectivesDetermine the role of apolipoprotein M (ApoM) in anthracycline (Dox) cardiotoxicity.

BackgroundApoM binds the cardioprotective sphingolipid sphingosine-1-phosphate (S1P). Circulating ApoM is inversely associated with mortality in human heart failure (HF).

MethodsIn the Penn HF Study (PHFS), we tested the relationship between ApoM and mortality in a subset with anthracycline-induced cardiomyopathy. We measured ApoM in humans and mice treated with Dox and utilized hepatic ApoM transgenic (ApomTG), ApoM knockout (ApomKO), ApoM knock-in mice with impaired S1P binding, and S1P receptor 3 (S1PR3) knockout mice in Dox cardiotoxicity. We assayed autophagy in left ventricular tissue from anthracycline-induced HF patients versus donor controls.

ResultsApoM was inversely associated with mortality in PHFS, and Dox reduced circulating ApoM in mice and breast cancer patients. ApomTG mice were protected from Dox-induced cardiac dysfunction and loss of left ventricular mass. ApomTG attenuated Dox-induced impairment in autophagic flux in vivo and accumulation of insoluble p62, which was also observed in the myocardium of patients with anthracycline-induced HF. In vehicle-treated mice, ApoM negatively regulated transcription factor EB (TFEB), a master regulator of autophagy and lysosomal biogenesis. The effect of ApoM on TFEB required both S1P binding and S1PR3. In the presence of Dox, ApoM preserved TFEB and cardiomyocyte lysosomal abundance assessed as lysosomal associated membrane protein 1 positive structures in vivo, while S1P mimetic pretreatment of cardiomyocytes prevented Dox-induced changes in lysosomal pH.

ConclusionsApoM attenuates Dox cardiotoxicity via the autophagy-lysosome pathway. The association between ApoM and reduced mortality may be explained by its role in sustaining autophagy.

HighlightsO_LICirculating ApoM is inversely associated with survival in human anthracycline-induced cardiomyopathy
C_LIO_LIAnthracycline treatment reduces circulating ApoM in humans and mice
C_LIO_LIIncreasing ApoM attenuates doxorubicin cardiotoxicity, lysosomal injury and preserves myocardial autophagic flux, but does not impact doxorubicin anti-neoplastic efficacy
C_LIO_LIAutophagic impairment is characteristic of human anthracycline cardiomyopathy
C_LI Microvesicles Transfer Mitochondria and Increase Mitochondrial Function in Brain Endothelial Cells We have demonstrated, for the first time that microvesicles, a sub-type of extracellular vesicles (EVs) derived from hCMEC/D3: a human brain endothelial cell (BEC) line transfer polarized mitochondria to recipient BECs in culture and to neurons in mice acute brain cortical and hippocampal slices. This mitochondrial transfer increased ATP levels by 100 to 200-fold (relative to untreated cells) in the recipient BECs exposed to oxygen-glucose deprivation, an in vitro model of cerebral ischemia. We have also demonstrated that transfer of microvesicles, the larger EV fraction, but not exosomes resulted in increased mitochondrial function in hypoxic endothelial cultures. Gene ontology and pathway enrichment analysis of EVs revealed a very high association to glycolysis-related processes. In comparison to heterotypic macrophage- derived EVs, BEC-derived EVs demonstrated a greater selectivity to transfer mitochondria and increase endothelial cell survival under ischemic conditions.

HighlightsO_LIMicrovesicles transfer mitochondria to endothelial cells and brain slice neurons
C_LIO_LIMitochondrial transfer increased ATP in ischemic brain endothelial cells (BECs)
C_LIO_LITransfer of microvesicles increased mitochondrial function in hypoxic BECs
C_LIO_LITransfer of exosomes did not affect mitochondrial function in hypoxic BECs
C_LIO_LIHomotypic BEC-derived EVs result in greater ATP levels in the recipient BECs
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