The Landscape of Receptor-Mediated Precision Cancer Combination Therapy: A Single-Cell Perspective The availability of single-cell transcriptomics data opens new opportunities for rational design of combination cancer treatments. Mining such data, we employed combinatorial optimization techniques to explore the landscape of optimal combination therapies in solid tumors including brain, head and neck, melanoma, lung, breast and colon cancers. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. As a baseline case, we studied the killing of at least 80% of the tumor cells while sparing more than 90% of the non-tumor cells in each patient, as a putative regimen. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient. However, the number of distinct targets that one would need to assemble to treat all patients in a cohort accordingly would be around 10 in most cases. Further requiring that the target genes be also lowly expressed in healthy tissues uncovers qualitatively similar trends. However, as one asks for more stringent and selective killing beyond the baseline regimen we focused on, we find that the number of targets needed rises rapidly. Emerging individual promising receptor targets include PTPRZ1, which is frequently found in the optimal combinations for brain and head and neck cancers, and EGFR, a recurring target in multiple tumor types. In sum, this systematic single-cell based characterization of the landscape of combinatorial receptor-mediated cancer treatments establishes first of their kind estimates on the number of targets needed, identifying promising ones for future development.
DeLUCS: Deep Learning for Unsupervised Clustering of DNA Sequences We present a novel Deep Learning method for the Unsupervised Clustering of DNA Sequences (DeLUCS) that does not require sequence alignment, sequence homology, or (taxonomic) identifiers. DeLUCS uses Frequency Chaos Game Representations (FCGR) of primary DNA sequences, and generates "mimic" sequence FCGRs to self-learn data patterns (genomic signatures) through the optimization of multiple neural networks. A majority voting scheme is then used to determine the final cluster assignment for each sequence. The clusters learned by DeLUCS match true taxonomic groups for large and diverse datasets, with accuracies ranging from 77% to 100%: 2,500 complete vertebrate mitochondrial genomes, at taxonomic levels from sub-phylum to genera; 3,200 randomly selected 400 kbp-long bacterial genome segments, into clusters corresponding to bacterial families; three viral genome and gene datasets, averaging 1,300 sequences each, into clusters corresponding to virus subtypes. DeLUCS significantly outperforms two classic clustering methods (K-means++ and Gaussian Mixture Models) for unlabelled data, by as much as 47%. DeLUCS is highly effective, it is able to cluster datasets of unlabelled primary DNA sequences totalling over 1 billion bp of data, and it bypasses common limitations to classification resulting from the lack of sequence homology, variation in sequence length, and the absence or instability of sequence annotations and taxonomic identifiers. Thus, DeLUCS offers fast and accurate DNA sequence clustering for previously intractable datasets.
Spatial transcriptomic characterization of COVID-19 pneumonitis identifies immune circuits related to tissue injury Severe lung damage in COVID-19 involves complex interactions between diverse populations of immune and stromal cells. In this study, we used a spatial transcriptomics approach to delineate the cells, pathways and genes present across the spectrum of histopathological damage in COVID-19 lung tissue. We applied correlation network-based approaches to deconvolve gene expression data from areas of interest within well preserved post-mortem lung samples from three patients. Despite substantial inter-patient heterogeneity we discovered evidence for a common immune cell signaling circuit in areas of severe tissue that involves crosstalk between cytotoxic lymphocytes and pro-inflammatory macrophages. Expression of IFNG by cytotoxic lymphocytes was associated with induction of chemokines including CXCL9, CXCL10 and CXCL11 which are known to promote the recruitment of CXCR3+ immune cells. The tumour necrosis factor (TNF) superfamily members BAFF (TNFSF13B) and TRAIL (TNFSF10) were found to be consistently upregulated in the areas with severe tissue damage. We used published spatial and single cell SARS-CoV-2 datasets to confirm our findings in the lung tissue from additional cohorts of COVID-19 patients. The resulting model of severe COVID-19 immune-mediated tissue pathology may inform future therapeutic strategies.

One Sentence SummarySpatial analysis identifies IFN{gamma} response signatures as focal to severe alveolar damage in COVID-19 pneumonitis. Enhanced transcriptional heterogeneity mediated by NF-κB super-enhancers The transcription factor NF-{kappa}B, which plays an important role in cell fate determination, is involved in the activation of super-enhancers (SEs). However, the biological functions of the NF-{kappa}B SEs in gene control are not fully elucidated. We investigated the characteristics of NF-{kappa}B-mediated SE activity using fluorescence live-cell imaging of RelA, single-cell transcriptome, and chromatin accessibility analyses in anti-IgM-stimulated B cells. Cell stimulation induced nuclear foci formation of RelA and gene expression in a switch-like manner. The gained SEs induced a higher fold-change expression and enhanced cell-to-cell variability in transcriptional response. These properties were correlated with the number of gained cis-regulatory interactions, while switch-like gene induction was associated with the number of NF-{kappa}B binding sites in SE. Our study suggests that NF-{kappa}B SEs have unique roles for quantitative control of gene expression through direct binding to accessible DNA and enhanced DNA contacts. Improving GWAS discovery and genomic prediction accuracy in Biobank data Genetically informed and deep-phenotyped biobanks are an important research resource. The cost of phenotyping far outstrips that of genotyping, and therefore it is imperative that the most powerful, versatile and efficient analysis approaches are used. Here, we apply our recently developed Bayesian grouped mixture of regressions model (GMRM) in the UK and Estonian Biobanks and obtain the highest genomic prediction accuracy reported to date across 21 heritable traits. On average, GMRM accuracies were 15% (SE 7%) greater than prediction models run in the LDAK software with SNP annotation marker groups, 18% (SE 3%) greater than a baseline BayesR model without SNP markers grouped into MAF-LD-annotation categories, and 106% (SE 9%) greater than polygenic risk scores calculated from mixed-linear model association (MLMA) estimates. For height, the prediction accuracy R2 was 47% in a UK Biobank hold-out sample, which was 76% of the estimated [Formula]. We then extend our GMRM prediction model to provide MLMA SNP marker estimates for GWAS discovery, which increased the independent loci detected to 7,910 in unrelated UK Biobank individuals, as compared to 5,521 from BoltLMM and 5,727 from Regenie, a 43% and 38% increase respectively. The average{chi} 2 value of the leading markers was 34% (SE 5.11) higher for GMRM as compared to Regenie, and increased by 17% for every 1% increase in prediction accuracy gained over a baseline BayesR model across the traits. Thus, we show that modelling genetic associations accounting for MAF and LD differences among SNP markers, and incorporating prior knowledge of genomic function, is important for both genomic prediction and for discovery in large-scale individual-level biobank-scale studies. Localization of signaling receptors maximizes cellular informationacquisition in spatially-structured natural environments Cells in natural environments like tissue or soil sense and respond to extracellular ligands with intricately structured and non-monotonic spatial distributions, sculpted by processes such as fluid flow and substrate adhesion. In this work, we show that spatial sensing and navigation can be optimized by adapting the spatial organization of signaling pathways to the spatial structure of the environment. We develop an information-theoretic framework for computing the optimal spatial organization of a sensing system for a given signaling environment. We find that receptor localization maximizes information acquisition in simulated natural contexts, including tissue and soil. Receptor localization extends naturally to produce a dynamic protocol for continuously redistributing signaling receptors, which when implemented using simple feedback, boosts cell navigation efficiency by 30-fold. Broadly, our work shows how cells can maximize the fidelity of information transfer by adapting the spatial organization of signaling molecules to the spatial structure of the environment. Common Dynamic Determinants Govern Quorum Quenching Activity in N-terminal Serine Hydrolases Growing concerns about microbial antibiotic resistance have motivated extensive research into ways of overcoming antibiotic resistance. Quorum quenching (QQ) processes disrupt bacterial communication via quorum sensing, which enables bacteria to sense the surrounding bacterial cell density and markedly affects their virulence. Due to its indirect mode of action, QQ is believed to exert limited pressure on essential bacterial functions and may thus avoid inducing resistance. Although many enzymes display QQ activity against various bacterial signaling molecules, their mechanisms of action are poorly understood, limiting their potential optimization as QQ agents. Here we evaluate the capacity of three N-terminal serine hydrolases to degrade N-acyl homoserine lactones that serve as signaling compounds for Gram-negative bacteria. Using molecular dynamics simulations of the free enzymes and their complexes with two signaling molecules of different lengths, followed by quantum mechanics/molecular mechanics molecular dynamics simulations of their initial catalytic steps, we clarify the molecular processes underpinning their QQ activity. We conclude that all three enzymes degrade bacterial signaling molecules via similar reaction mechanisms. Moreover, we experimentally confirmed the activity of two penicillin G acylases from Escherichia coli (ecPGA) and Achromobacter spp. (aPGA), adding these biotechnologically well-optimized enzymes to the QQ toolbox. We also observed enzyme- and substrate-dependent differences in the catalytic actions of these enzymes, arising primarily from the distinct structures of their acyl-binding cavities and the dynamics of their molecular gates. As a consequence, the first reaction step catalyzed by ecPGA with a longer substrate had an elevated energy barrier because its shallow acyl binding site could not accommodate a productive substrate-binding configuration. Conversely, aPGA in complex with both substrates exhibited unfavorable energetics in both reaction steps due to the dynamics of the residues gating the acyl binding cavity entrance. Finally, the energy barriers of the second reaction step catalyzed by Pseudomonas aeruginosa acyl-homoserine lactone acylase with both substrates were higher than in the other two enzymes due to the unique positioning of Arg297{beta} in this enzyme. The discovery of these dynamic determinants will guide future efforts to design robust QQ agents capable of selectively controlling virulence in resistant bacterial species. RNAi screen of RING/U-box domain ubiquitin ligases identifies critical regulators of tissue regeneration in planarians Regenerative processes depend on the interpretation of signals to coordinate cell behaviors. The role of ubiquitin-mediated signaling is known to be important in many cellular and biological contexts, but its role in regeneration is not well understood. To investigate how ubiquitylation impacts tissue regeneration in vivo, we are studying planarians that are capable of regenerating after nearly any injury using a population of stem cells. Here we used RNAi to screen RING/U-box E3 ubiquitin ligases that are highly expressed in planarian stem cells and stem cell progeny. RNAi screening identified nine genes with functions in regeneration, including the spliceosomal factor prpf19 and histone modifier rnf2; based on their known roles in developmental processes, we further investigated these two genes. We found that prpf19 was required for animal survival but not for stem cell maintenance, suggesting a role in promoting cell differentiation. Because RNF2 is the catalytic subunit of the Polycomb Repressive Complex 1 (PRC1), we also examined other putative members of this complex (CBX and PHC). We observed a striking phenotype of regional tissue misspecification in cbx and phc RNAi planarians. To identify genes regulated by PRC1, we performed RNA-seq after knocking down rnf2 or phc. Although these proteins are predicted to function in the same complex, we found that the set of genes differentially expressed in rnf2 versus phc RNAi were largely non-overlapping. Using in situ hybridization, we showed that rnf2 regulates gene expression levels within a tissue type, whereas phc is necessary for the spatial restriction of gene expression, findings consistent with their respective in vivo phenotypes. This work not only uncovered roles for RING/U-box E3 ligases in stem cell regulation and regeneration, but also identified differential gene targets for two putative PRC1 factors required for maintaining cell-type-specific gene expression in planarians. In vivo profiling of site-specific human cancer cell states in zebrafish Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a significant challenge. We present a quantitative high-resolution imaging assay of cancer cell morphology in zebrafish xenografts to probe functional adaptation to variable cell extrinsic cues and molecular interventions. We focus on Ewing Sarcoma, a pediatric cancer driven by a single oncogenic fusion protein EWSR1-FLI1, and with little to no additional somatic mutations, making it a prototypical form of cancer whose adaptation to microenvironments is likely driven by acute, non-genomic mechanisms. Using computer vision analysis of 3D cell shapes, we find systematic shifts in the distribution of cell morphotypes between distinct sites in the fish embryo. We also find site-specific morphological responses to differential expression of EWSR1-FLI1. Combining these data we propose a model where Ewing Sarcoma cancer cell plasticity is sensitive both to expression fluctuation of EWSR1-FLI1 and signals from the surrounding tissue microenvironment, with either or both factors possibly contributing to the oncogenic potential of these cells. 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. Computation of the mitochondrial age distribution along the axon length We describe a compartmental model of mitochondrial transport in axons, which we apply to compute mitochondrial age at different distances from the soma. The model predicts that the average mitochondrial age at the tip of an axon with a length of 1 cm is approximately 22 hours. The mitochondria are youngest closest to the soma and their age scales approximately linearly with distance from the soma. To the best of the authors knowledge, this is the first attempt to predict the spatial distribution of mitochondrial age within an axon. A sensitivity study of the mean age of mitochondria to various model parameters is also presented. The Inflammatory Role of Milk Fat Globule Epidermal Growth Factor VIII in Angiotensin II Induced Arterial Remodeling BackgroundAngiotensin II (Ang II) and milk fat globule-epidermal growth factor VIII (MFG-E8) are involved in age-associated arterial remodeling; however, the inflammatory role of MFG-E8 in Ang II associated arterial remodeling with aging remains unknown.

Methods and ResultsIn this study, 30-week-old MFG-E8 knock out (KO) and age-matched wild-type (WT) mice were infused with Ang II or saline. After infusion the with Ang II, the aortic molecular, cellular, and structural remodeling were observed in mice and compared to those infused with saline, but these effects were dependent on the expression of MFG-E8: (1) In the WT mice, Ang II infusion substantially increased intimal-medial thickness, elastic lamina degradation, collagen deposition, and the proliferation of VSMCs; in contrast, in the KO mice, these effects were significantly reduced; (2) In the WT mice, Ang II treatment significantly increased the activation and expression of MMP2, TGF-{beta}1, and its downstream signaling molecule p-SMAD2, and collagen type I production, however, in the KO mice, these molecular effects were significantly reduced; (3) In the WT mice, Ang II treatment increased inflammatory p-NF-{kappa}B p65, MCP1, TNF-, ICAM1, and VCAM1 molecular expression, while conversely, in the KO mice, no significant inflammatory changes were found; (4) Importantly, compared to untreated control mice with a wide range of age from 4-96 weeks, Ang II infused "younger" mice produced an "older" arterial inflammatory phenotype, which was alleviated by MFG-E8 deficiency.

ConclusionsMFG-E8 mediates Ang II associated arterial inflammatory remodeling. Targeting MFG-E8 is a novel molecular approach to curb adverse arterial remodeling during aging and hypertension.

CLINICAL PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABS* Both Ang II and MFG-E8 increases are involved in proinflammatory arterial remodeling mediating the molecular, cellular and tissue events in aging and hypertension.
* MFG-E8 is essential for Ang II induced and age-associated adverse arterial remodeling via the increase of proinflammation, intimal medial thickening, elastin fragmentation, collagen deposition, and VSMC proliferation.


What Are the Clinical Implications?Since MFG-E8 mediates Ang II induced proinflammation in arterial wall remodeling in aging and hypertension, targeting MFG-E8 is a potential molecular approach to curb inflammatory arterial remodeling, maintaining the health of the vascular system during aging and hypertension. Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Conformist social learning leads to self-organised prevention against adverse bias in risky decision making Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. Harnessing changes in open chromatin determined by ATAC-seq to generate insulin-responsive reporter constructs. BackgroundGene regulation is critical for proper cellular function. Next-generation sequencing technology has revealed the presence of regulatory networks that regulate gene expression and essential cellular functions. Studies investigating the epigenome have begun to uncover the complex mechanisms regulating transcription. Assay for transposase-accessible chromatin by sequencing (ATAC-seq) is quickly becoming the assay of choice for many epigenomic investigations. However, whether intervention-mediated changes in accessible chromatin determined by ATAC-seq can be harnessed to generate intervention-inducible reporter constructs has not been systematically assayed.

ResultsWe used the insulin signaling pathway as a model to investigate chromatin regions and gene expression changes using ATAC- and RNA-seq in insulin-treated Drosophila S2 cells. We found correlations between ATAC- and RNA-seq data, especially when stratifying differentially-accessible chromatin regions by annotated feature type. In particular, our data demonstrated a strong correlation between chromatin regions annotated to distal promoters (1-2 kb from the transcription start site) and downstream gene expression. We cloned candidate distal promoter regions upstream of luciferase and demonstrate insulin-inducibility of several of these reporters.

ConclusionsInsulin-induced chromatin accessibility determined by ATAC-seq reveals enhancer regions that drive insulin-inducible reporter gene expression. Life history adaptations to fluctuating environments: Combined effects of demographic buffering and lability of demographic parameters Demographic buffering and lability have been identified as adaptive strategies to optimise fitness in a fluctuating environment. These are not mutually exclusive, however we lack efficient methods to measure their relative importance for a given life history. Here, we decompose the stochastic growth rate (fitness) into components arising from nonlinear responses and variance-covariance of demographic parameters to an environmental driver, which allows studying joint effects of buffering and lability. We apply this decomposition for 154 animal matrix population models under different scenarios, to explore how these main fitness components vary across life histories. Faster-living species appear more responsive to environmental fluctuations, either positively or negatively. They have the highest potential for strong adaptive demographic lability, while demographic buffering is a main strategy in slow-living species. Our decomposition provides a comprehensive framework to study how organisms adapt to variability through buffering and lability, and to predict species responses to climate change. Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis The aim of this study was to identify detailed changes in behavior, and in salivary serum amyloid A (SAA), associated with subclinical mastitis. This included standard sickness behaviors (which form part of an adaptive response to conserve energy, minimize heat loss and facilitate recovery following infection and inflammation) and lesser-studied behaviors, that are biologically predicted to change at low-level infection, and therefore particularly relevant for detecting subclinical mastitis (here labelled  luxury behaviors). SAA is a physiological marker of systemic inflammation, with levels in milk and serum already known to increase during subclinical mastitis. We investigated whether the same was true for SAA in cow saliva. Data were collected for n = 34 commercial barn-housed dairy cows, tested in 17 matched-pairs. Each pair comprised a cow with subclinical mastitis (SCM) and a healthy control (CTRL), identified using somatic cell count (SCC) (SCM: SCC >200 x1000 cells/ml; CTRL: SCC <100 x1000 cells/ml). SCM cows were selected for study ad-hoc, at which point they were paired with a CTRL cow, based upon parity and calving date; consequently, the full data set was accrued over several months. Data were collected for each pair over 3 days: SCC (l4:00-l5:00h) Day 1; behavior (24h from 00:00h) Day 2; salivary serum amyloid-A (SAA) Day 3. We report, for the first time, that an increase in salivary SAA occurs during subclinical mastitis; SAA was higher in SCM cows and demonstrated a positive (weak) correlation with SCC. The behavioral comparisons revealed that SCM cows had reductions in activity (behavioral transitions and distance moved), social exploration, social reactivity (here: likelihood to move away/be displaced following receipt of agonism), performance of social grooming and head butts, and the receipt of agonistic non-contact challenges. In addition, SCM cows received more head swipes, and spent a greater proportion of time lying with their head on their flank than CTRL cows. SCM cows also displayed an altered feeding pattern; they spent a greater proportion of feeding time in direct contact with two conspecifics, and a lower proportion of feeding time at self-locking feed barriers, than CTRL cows. Behavioral measures were found to correlate, albeit loosely, with serum SAA in a direction consistent with predictions for sickness behavior. These included positive correlations with both lying duration and the receipt of all agonistic behavior, and negative correlations with feeding, drinking, the performance of all social and all agonistic behavior, and social reactivity. We conclude that changes in salivary SAA, social behavior, and activity offer potential in the detection of subclinical mastitis and recommend further investigation to substantiate and refine our findings. A conserved uORF regulates APOBEC3G translation and is targeted by HIV-1 Vif protein to repress the antiviral factor The HIV-1 Vif protein is essential for viral fitness and pathogenicity. Vif decreases expression of cellular restriction factors APOBEC3G (A3G), A3F, A3D and A3H, which inhibit HIV-1 replication by inducing hypermutation during reverse transcription. Vif counteracts A3G at several levels (transcription, translation and protein degradation) that together reduce the levels of A3G in cells and prevent its incorporation into viral particles. How Vif affects A3G translation remains unclear. Here, we uncovered the importance of a short conserved uORF (upstream ORF) located within two critical stem-loop structures of the 5 untranslated region (5UTR) of A3G mRNA for this process. A3G translation occurs through a combination of leaky-scanning and translation re-initiation and the presence of an intact uORF decreases the extent of global A3G translation under normal conditions. Interestingly, the uORF is also absolutely required for Vif-mediated translation inhibition and redirection of A3G mRNA into stress granules. Overall, we discovered that A3G translation is regulated by a small uORF conserved in the human population and that Vif uses this specific feature to repress its translation. Plant biomechanics and resilience to environmental changes are controlled by specific lignin chemistries in each vascular cell type and morphotype The biopolymer lignin, deposited in the cell walls of vascular cells, is essential for long-distance water conduction and structural support of plants. Independently of the species, each different vascular cell type contains a conserved lignin chemistry with specific aromatic and aliphatic substitutions. Yet, the biological role of this conserved and specific lignin chemistry for each cell type remained unclear. Herein, we investigate the role of specific lignin chemistries for cellular function by producing single cell analyses on vascular cell morphotypes, all enabling sap conduction but differing in morphology. We found that specific lignin chemistries accumulate in each morphotype. Moreover, lignin accumulates dynamically, increasing in quantity and changing composition, to alter the cell wall biomechanics of each morphotype during their maturation. For similar aromatic substitution, residues with alcohol aliphatic functions increased stiffness whereas aldehydes increased flexibility. Modifying this specific lignin chemistry impairs the cell wall biomechanics of each morphotype and consequently reduces their capacity to optimally conduct water in normal conditions, and to recover from drought. Altogether, lignin chemistry is differently controlled for each sap conducting cell types during their maturation to dynamically adjust their biomechanics and hydraulic properties to adapt to developmental and environmental constraints. F1F0 ATP Hydrolysis is a Determinant of Metabolic Rate, a Correlate of Lifespan, and a Weakness of Cancer Dramatic rectal temperature decrease, in mice administered with a drug that specifically inhibits F1F0 ATP hydrolysis, suggests that F1F0 ATP hydrolysis is a major determinant of metabolic rate in vivo. Across twelve investigated species, less F1F0 ATP hydrolysis correlates with greater maximal lifespan. Specific drug inhibition of F1F0 ATP hydrolysis exerts potent anti-cancer activity in vitro. Betacoronavirus binding dynamics relevant to the functional evolution of the highly transmissible SARS-CoV-2 variant N501Y Comparative functional analysis of the dynamic interactions between various Betacoronavirus mutant strains and broadly utilized target proteins such as ACE2 and CD26, is crucial for a more complete understanding of zoonotic spillovers of viruses that cause diseases such as COVID-19. Here, we employ machine learning to replicated sets of nanosecond scale GPU accelerated molecular dynamics simulations to statistically compare and classify atom motions of these target proteins in both the presence and absence of different endemic and emergent strains of the viral receptor binding domain (RBD) of the S spike glycoprotein. Machine learning was used to identify functional binding dynamics that are evolutionarily conserved from bat CoV-HKU4 to human endemic/emergent strains. Conserved dynamics regions of ACE2 involve both the N-terminal helices, as well as a region of more transient dynamics encompassing K353, Q325 and a novel motif AAQPFLL 386-92 that appears to coordinate their dynamic interactions with the viral RBD at N501. We also demonstrate that the functional evolution of Betacoronavirus zoonotic spillovers involving ACE2 interaction dynamics are likely pre-adapted from two precise and stable binding sites involving the viral bat progenitor strains interaction with CD26 at SAMLI 291-5 and SS 333-334. Our analyses further indicate that the human endemic strains hCoV-HKU1 and hCoV-OC43 have evolved more stable N-terminal helix interactions through enhancement of an interfacing loop region on the viral RBD, whereas the highly transmissible SARS-CoV-2 variants (B.1.1.7, B.1.351 and P.1) have evolved more stable viral binding via more focused interactions between the viral N501 and ACE2 K353 alone. Bidirectional Control of Parathyroid Hormone and Bone Mass by Subfornical Organ Parathyroid hormone (PTH) is one of the most important hormones responsible for bone turnover and calcium homeostasis. In mammals, PTH is secreted through the parathyroid glands, unlike in fishes, which are secreted through central nervous system. Studies indicated that a variety of peripheral nerve regulates serum PTH level, however, the mechanism underlying central neural regulation of PTH in mammals remains largely unknown. With an approach including neural-specific retrograde tracing, PTH-Biotin binding assay, and cFos staining, we identified the subfornical organ (SFO) and the paraventricular nucleus (PVN) as two important brain nuclei that responded to serum PTH and calcium changes. Using chemogenetics, we found that serum PTH was suppressed by stimulation of GABAergic neurons in SFO followed by a decrease in trabecular bone mass. Conversely, stimulation of glutamatergic neurons in SFO promoted serum PTH and bone mass. Moreover, we found that the majority of neurons expressing parathyroid hormone 1 receptor (PTH1R) were GABAergic neurons and the majority of neurons expressing parathyroid hormone 2 receptor (PTH2R) were glutamatergic neurons. The paraventricular nucleus (PVN) is downstream of the SFO, and chemogenetic activation of glutamatergic neurons in PVN induced an increase in serum PTH. In summary, our study demonstrates for the first time that distinct neuronal subtypes in the SFO are responsible for bidirectional regulation of serum PTH and bone metabolism, which is mediated through the PVN and the peripheral nervous system. These findings reveal important central neural nodes and will advance our understanding of the central neural regulation of PTH at the molecular, cellular and circuit level. Wolbachia load variation in Drosophila is more likely caused by drift than by host genetic factors Symbiosis is a continuum of long-term interactions ranging from mutualism to parasitism, according to the balance between costs and benefits for the protagonists. The density of endosymbionts is, in both cases, a key factor that determines both the transmission of symbionts and the host extended phenotype, and is thus tightly regulated within hosts. However, the evolutionary and molecular mechanisms underlying bacterial density regulation are currently poorly understood. In this context, the symbiosis between the fruit fly and its intracellular bacteria Wolbachia (wMelPop strain) is particularly interesting to study. Although vertically transmitted, the symbiont is pathogenic, and a positive correlation between virulence and wMelPop density is observed. In addition, the number of repeats of a bacterial genomic region -Octomom-is positively correlated with Wolbachia density, underlying a potential genetic mechanism that controls bacterial density. Interestingly, the number of repeats varies between host individuals, but most likely also within them. Such genetic heterogeneity within the host could promote conflicts between bacteria themselves and with the host, notably by increasing within-host competition between symbiont genotypes through a process analogous to the tragedy of the commons. To characterize the determinisms at play in the regulation of bacterial density, we first introgressed wMelPop in different genetic backgrounds of D. melanogaster, and found different density levels and Octomom copy numbers in each host lineage. To determine whether such variations reflect a host genetic determinism on density regulation through Octomom copy number selection, we replicated the introgressions and performed reciprocal crosses on the two Drosophila populations with the most extreme density levels. In both experiments, we detected an absence of directionality in the patterns of infection, associated with a strong instability of these patterns across generations. Given that bacterial density was highly correlated with Octomom copy numbers in all experiments, these results rather suggest a strong influence of drift and a random increase in the frequency of certain bacterial variants. We then discuss how drift, both on the symbiont population during transmission and on the host population, could limit the efficiency of selection in such a symbiotic system, and the consequences of drift on the regulation of density and composition of bacterial populations. A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice In vivo analysis of the contribution of proprotein convertases to the processing of FGF23 Fibroblast growth factor 23 (FGF23) is a hormone secreted from fully differentiated osteoblasts and osteocytes that inhibits phosphate reabsorption by kidney proximal tubules. The full-length (i.e., intact) protein mediates FGF23 endocrine functions, while endoproteolytic cleavage at a consensus cleavage sequence for the proprotein convertases (PCs) inactivates FGF23. Two PCs, furin and PC5, were shown to cleave FGF23 in vitro at RHTR179{downarrow}, but whether they are fulfilling this function in vivo is currently unknown. To address this question we used here mice lacking either or both furin and PC5 in cell-specific manners and mice lacking the paired basic amino acid-cleaving enzyme 4 (PACE4) in all cells. Our analysis shows that furin inactivation in osteoblasts and osteocytes results in a 25% increase in circulating intact FGF23, without any significant impact on serum phosphate levels, whether mice are maintained on a normal or a low phosphate diet. Under conditions of iron deficiency, FGF23 is normally processed in control mice, but its processing is impaired in mice lacking furin in osteoblasts and osteocytes. In contrast, FGF23 is normally cleaved following erythropoietin or IL-1{beta} injections in mice lacking furin or both furin and PC5, and in PACE4-deficient mice. Altogether, these studies suggest that furin is only partially responsible for FGF23 cleavage under certain conditions in vivo. The processing of FGF23 may therefore involve the redundant action of multiple PCs or of other peptidases in osteoblasts, osteocytes and hematopoietic cells.