Heteologous saRNA-Prime, DNA Dual-Antigen-Boost SARS-CoV-2 Vaccination Elicits Robust Cellular Immunogenicity and Cross-Variant Neutralizing Antibodies We assessed if immune responses are enhanced in CD-1 mice by heterologous vaccination with two different nucleic acid-based COVID-19 vaccines: a next-generation human adenovirus serotype 5 (hAd5)-vectored dual-antigen spike (S) and nucleocapsid (N) vaccine (AdS+N) and a self-amplifying and -adjuvanted S RNA vaccine (SASA S) delivered by a nano-lipid carrier. The AdS+N vaccine encodes S modified with a fusion motif to increase cell-surface expression. The N antigen is modified with an Enhanced T-cell Stimulation Domain (N-ETSD) to direct N to the endosomal/lysosomal compartment and increase MHC class I and II stimulation potential. The S sequence in the SASA S vaccine comprises the D614G mutation, two prolines to stabilize S in the prefusion conformation, and 3 glutamines in the furin cleavage region to increase cross-reactivity across variants. CD-1 mice received vaccination by homologous and heterologous prime > boost combinations. Humoral responses to S were the highest with any regimen including the SASA S vaccine, and IgG bound to wild type and Delta (B.1.617.2) variant S1 at similar levels. An AdS+N boost of an SASA S prime particularly enhanced both CD4+ and CD8+ T-cell responses to both wild type and Delta S peptides relative to all other vaccine regimens. Sera from mice receiving SASA S homologous or heterologous vaccination were found to be highly neutralizing of all pseudovirus strains tested: Wuhan, Beta, Delta, and Omicron strain. The findings here support the clinical testing of heterologous vaccination by an SASA S > AdS+N regimen to provide increased protection against emerging SARS-CoV-2 variants.
Creation of a single cell RNA seq meta-atlas to define human liver immune homeostasis The liver is unique in both its ability to maintain immune homeostasis and in its potential for immune tolerance following solid organ transplantation. Single-cell RNA sequencing (scRNA seq) is a powerful approach to generate highly dimensional transcriptome data to understand cellular phenotypes. However, when scRNA data is produced by different groups, with different data models, different standards, and samples processed in different ways, it can be challenging to draw meaningful conclusions from the aggregated data. The goal of this study was to establish a method to combine  human liver scRNA seq datasets by 1) characterizing the heterogeneity between studies and 2) using the meta-atlas to define the dominant phenotypes across immune cell subpopulations in healthy human liver. Publicly available scRNA seq data generated from liver samples obtained from a combined total of 17 patients and [~]32,000 cells were analyzed. Liver-specific immune cells (CD45+) were extracted from each dataset, and immune cell subpopulations (myeloid cells, NK and T cells, plasma cells, and B cells) were examined using dimensionality reduction (UMAP), differential gene expression, and ingenuity pathway analysis. All datasets co-clustered, but cell proportions differed between studies. Gene expression correlation demonstrated similarity across all studies, and canonical pathways that differed between datasets were related to cell stress and oxidative phosphorylation rather than immune-related function. Next, a meta-atlas was generated via data integration and compared against PBMC data to define gene signatures for each hepatic immune subpopulation. This analysis defined key features of hepatic immune homeostasis, with decreased expression across immunologic pathways and enhancement of pathways involved with cell death. This method for meta-analysis of scRNA seq data provides a novel approach to broadly define the features of human liver immune homeostasis. Specific pathways and cellular phenotypes described in this human liver immune meta-atlas provide a critical reference point for further study of immune mediated disease processes within the liver.
Quantifying ERK-activity in response to inhibition of the BRAFV600E-MEK-ERK cascade using mathematical modelling BackgroundSimultaneous inhibition of multiple components of the BRAF-MEK-ERK cascade (vertical inhibition) has become a standard of care for treating BRAF-mutant melanoma. However, the molecular mechanism of how vertical inhibition synergistically suppresses intracellular ERK-activity, and consequently cell proliferation, are yet to be fully elucidated.

MethodsWe develop a mechanistic mathematical model that describes how the mutant BRAF-inhibitor, dabrafenib, and the MEK-inhibitor, trametinib, affect BRAFV600E-MEK-ERK signalling. The model is based upon a system of chemical reactions that describes cascade signalling dynamics. Using mass action kinetics, the chemical reactions are re-expressed as ordinary differential equations which are parameterised by in vitro data and solved numerically to obtain the temporal evolution of cascade component concentrations.

ResultsThe model provides a quantitative method to compute how dabrafenib and trametinib can be used in combination to synergistically inhibit ERK-activity in BRAFV600E-mutant melanoma cells. The model elucidates molecular mechanisms of vertical inhibition of the BRAFV600E-MEK-ERK cascade and delineates how elevated BRAF concentrations generate drug resistance to dabrafenib and trametinib. The computational simulations further suggest that elevated ATP levels could be a factor in drug resistance to dabrafenib.

ConclusionsThe model can be used to systematically motivate which dabrafenib-trametinib dose-combinations, for treating BRAFV600E-mutated melanoma, warrant experimental investigation. Where there's smoke, there's fuel: dynamic vegetation data improve predictions of wildfire hazard in the Great Basin Wildfires are a growing management concern in western US rangelands, where invasive annual grasses have altered fire regimes and contributed to an increased incidence of catastrophic large wildfires. Fire activity in arid, non-forested ecosystems is thought to be largely controlled by interannual variation in fuel amount, which in turn is controlled by antecedent weather. Thus, long-range forecasting of fire activity in rangelands should be feasible given annual estimates of fuel quantity. Using a 32 yr time series of spatial data, we employed machine learning algorithms to predict the relative probability of large (>405 ha) wildfire in the Great Basin based on fine-scale annual and 16-day estimates of cover and production of vegetation functional groups, weather, and multitemporal scale drought indices. We evaluated the predictive utility of these models with a leave-one-year-out cross-validation, building spatial hindcasts of fire probability for each year that we compared against actual footprints of large wildfires. Herbaceous aboveground biomass production, bare ground cover, and long-term drought indices were the most important predictors of burning. Across 32 fire seasons, 88% of the area burned in large wildfires coincided with the upper 3 deciles of predicted fire probabilities. At the scale of the Great Basin, several metrics of fire activity were moderately to strongly correlated with average fire probability, including total area burned in large wildfires, number of large wildfires, and maximum fire size. Our findings show that recent years of exceptional fire activity in the Great Basin were predictable based on antecedent weather-driven growth of fine fuels and reveal a significant increasing trend in fire probability over the last three decades driven by widespread changes in fine fuel characteristics. Navigating the amino acid sequence space between functional proteins using a deep learning framework MotivationShedding light on the relationships between protein se-quences and functions is a challenging task with many implications in protein evolution, diseases understanding, and protein design. Protein sequence / function space is however hard to comprehend due to its com-plexity. Generative models help to decipher complex systems thanks to their abilities to learn and recreate data specificity. Applied to protein sequences, they can point out relationships between protein positions and functions capture the sequence patterns associated with functions or navigate through uncharted area of molecular evolution.

ResultsIn this study, an unsupervised generative approach based on adversarial auto-encoder (AAE) is proposed to generate and explore new sequences with respect to their functions thanks to the prior distribution allowing a continuous exploration of the latent space. AAEs are tested on three protein families known for their multiple functions. Clustering re-sults on the encoded sequences from the latent space computed by AAEs display high level of homogeneity regarding the protein sequence func-tions. The study also reports and analyzes for the first time two sampling strategies based on latent space interpolation and latent space arithmetic to generate intermediate protein sequences sharing sequential and functional properties of original sequences issued from different families and functions. Generated sequences by interpolation between latent space data points demonstrate the ability of the AAE to generalize and to pro-duce meaningful biological sequences from an evolutionary uncharted area of the biological sequence space. Finally, 3D structure models generated by comparative modelling between different combinations of structures of different sub-families and of generated sequences from latent space or sub-family sequences point out to the ability of the latent space arithmetic to successfully transfer functional properties between sub-families. All in all this study confirms the ability of deep learning frameworks to model biological complexity and bring new tools to explore amino acid sequence and functional spaces.

AvailabilityCode and data used for this study are freely available at https://github.com/T-B-F/aae4seq.

Contacttristan@bitardfeildel.fr

Supplementary informationSupplementary data are available at online. Mutation rate dynamics reflect ecological change in an emerging zoonotic pathogen While mutation is often deleterious, it can also be adaptive. Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study we investigate two factors that are predicted to influence the trade-off between the costs and benefits of mutation: ecology and genome size. To investigate the relationship between these factors and mutation rate we conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact ecology can have on the adaptive potential of bacterial pathogens. Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. SARS-CoV-2 infection induces soluble platelet activation markers and PAI-1 in the early moderate stage of COVID-19 IntroductionCoagulation dysfunction and thromboembolism emerge as strong comorbidity factors in severe COVID-19. However, it is unclear when particularly platelet activation markers and coagulation factors dysregulated during the pathogenesis of COVID-19. Here, we sought to assess the levels of coagulation and platelet activation markers at moderate and severe stages of COVID-19 to understand the pathogenesis.

MethodsTo understand this, hospitalized COVID-19 patients with (severe cases that required intensive care) or without pneumonia (moderate cases) were recruited. Phenotypic and molecular characterizations were performed employing basic coagulation tests including PT, APTT, D-Dimer and TFPI. The flow cytometry-based multiplex assays were performed to assess FXI, anti-thrombin, prothrombin, fibrinogen, FXIII, P-selectin, sCD40L, plasminogen, tissue-plasminogen activator (tPA), plasminogen activator inhibitor-1 (PAI-1) and D-Dimer.

ResultsThe investigations revealed induction of plasma P-selectin and CD40 ligand (sCD40L) in moderate COVID-19 cases which were significantly abolished with the progression of COVID-19 severity. Moreover, a profound reduction in plasma tissue factor pathway inhibitor (TFPI) and FXIII were identified particularly in the severe COVID-19. Further analysis revealed fibrinogen induction in both moderate and severe patients. Interestingly, an elevated PAI-1 more prominently in moderate, and tPA particularly in severe COVID-19 cases were observed. Particularly, the levels of fibrinogen and tPA directly correlated with the severity of the disease.

ConclusionsIn summary, induction of soluble P-selectin, sCD40L, fibrinogen and PAI-1 in moderate COVID-19 cases suggests the activation of platelets and coagulation system before patients require intensive care. These findings would help in designing better thromboprophylaxis to limit the COVID-19 severity. Sgs1BLM independent role of Dna2DNA2 nuclease at DNA double strand break is inhibited by Nej1XLF The two major pathways of DNA double strand break (DSB) repair, non-homologous end-joining (NHEJ) and homologous recombination (HR), are highly conserved from yeast to mammals. The regulation of 5 DNA resection controls repair pathway choice and influences repair outcomes. Nej1 was first identified as a canonical NHEJ factor involved in stimulating the ligation of broken DNA ends and more recently, it was shown to be important for DNA end-bridging and inhibiting 5 resection mediated by Dna2-Sgs1. Nej1 interacts with Sae2 and this impacts DSB repair in three ways. First, Nej1 inhibits MRX-Sae2 interactions and Sae2 localization to a DSB. Second, Nej1 inhibits Sae2-dependent recruitment of Dna2 in the absence of Sgs1. Third, NEJ1 and SAE2 showed an epistatic relationship for DNA end-bridging, an event that restrains the broken ends and reduces the frequency of genomic deletions from developing at the DSB. Deletion of NEJ1 suppressed the synthetic lethality of sae2{Delta} sgs1{Delta} and was dependent on the nuclease activity of Dna2. These Nej1 functions promote end-joining DSB repair, but could also be relevant for controlling resection initiation during HR repair.

HighlightsO_LINej1 physically interacts with Sae2 and inhibits end-resection at a DSB.
C_LIO_LINej1 inhibits Sae2 interactions with the MRX complex.
C_LIO_LINej1 inhibits Sae2-dependent recruitment of Dna2 to a DSB.
C_LIO_LINEJ1 and SAE2 are epistatic for DNA end-bridging.
C_LIO_LIDeletion of NEJ1 suppresses the synthetic lethality of sae2{Delta} sgs1{Delta}, which is dependent on Dna2 nuclease activity.
C_LI SMC protein RecN drives RecA filament translocation and remodelling for in vivo homology search While the molecular repertoire of the homologous recombination pathway is well-studied, the search mechanism that enables recombination between distant homologous regions is poorly understood. Earlier work suggests that the recombinase RecA, an essential component for homology search, forms an elongated filament, nucleating at the break site. How this RecA structure carries out long distance search remains unclear. Here, we follow the dynamics of RecA after induction of a single double-strand break on the Caulobacter chromosome. We find that the RecA-nucleoprotein filament, once formed, rapidly translocates in a directional manner in the cell, undergoing several pole-to-pole traversals, until homology search is complete. Concomitant with translocation, we observe dynamic remodelling of the filament. Importantly in vivo, the RecA filament alone is incapable of such long distance movement; both translocation and dynamic remodelling are contingent on action of SMC-like protein RecN, via its ATPase cycle. We provide a stochastic description of RecN-regulated changes in filament length during translocation via modulation of RecA assembly-disassembly. In summary, we have uncovered the three key elements of homology search driven by RecN: mobility of a finite segment of RecA, filament remodelling and ability to conduct multiple pole-to-pole traversals, which together point to a novel optimal search strategy. Isotopically Nonstationary 13C Metabolic Flux Analysis in Resting and Activated Human Platelets Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary 13C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies. First detection of herpesvirus and prevalence of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity. Strain and rupture of HIV-1 capsids during uncoating Viral replication in HIV-1 relies on a fullerene-shaped capsid to transport genetic material deep into the nucleus of an infected cell. Capsid stability is linked to the presence of cofactors, including inositol hexakisphosphate (IP6) that bind to pores found in the capsid. Using extensive all-atom molecular dynamics simulations of HIV-1 cores imaged from cryo-electron tomography (cryo-ET) in intact virions, which contain IP6 and a ribonucleoprotein complex, we find markedly striated patterns of strain on capsid lattices. The presence of these cofactors also increases rigidity of the capsid. Conformational analysis of capsid (CA) proteins show CA accommodates strain by locally flexing away from structures resolved using x-ray crystallography and cryo-electron microscopy. Then, cryo-ET of HIV-1 cores undergoing endogenous reverse transcription demonstrate that lattice strain increases in the capsid prior to mechanical failure and that the capsid ruptures by crack propagation along regions of high strain. These results uncover HIV-1 capsid properties involved in their critical disassembly process.

Significance statementThe mature capsids of HIV-1 are transiently stable complexes that self-assemble around the viral genome during maturation, and uncoat to release preintegration complexes that archive a double-stranded DNA copy of the virus in the host cell genome. However, a detailed view of how HIV cores rupture remains lacking. Here, we elucidate the physical properties involved in capsid rupture using a combination of large-scale all-atom molecular dynamics simulations and cryo-electron tomography. We find that intrinsic strain on the capsid forms highly correlated patterns along the capsid surface, along which cracks propagate. Capsid rigidity also increases with high strain. Our findings provide fundamental insight into viral capsid uncoating. Cellular feedback to organotelluranes displays modulation of antioxidant proteins gene expression Organotelluranes RT3 and RT4 are thiol reagents that induce mitochondrial transition pore (MTP) opening in a sensitive and insensitive manner to cyclosporin A. Although RT3 and RT4 promote glutathione depletion, paradoxically, they are also an efficient antioxidant for membrane lipids. These compounds antagonistic effects elicited the challenging question of how the gene expression of antioxidant enzymes would respond to treatment with these compounds. The influence of RT3 and RT4 on antioxidant enzyme expression was investigated in cultured aortic smooth muscle cells (ASMC). RT3 and RT4 promoted disruption of ionic calcium homeostasis, mitochondrial transmembrane potential ({Delta}{Psi}), and cell death in a dose-dependent manner. The cell death mechanisms responded qualitatively to the increase of the organotellurane concentration and changed from apoptosis to necrosis. RT3 and RT4 increased the expression of thioredoxin significantly. RT3 also increased the expression of glutaredoxin and glutathione peroxidase, slightly the catalase expression without significant effects on SOD expression. The results are consistent with GSH and protein thiol depletion and discussed based on the cell toxicity mechanism exhibited by these compounds.



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org.highwire.dtl.DTLVardef@52bb82org.highwire.dtl.DTLVardef@19476d9org.highwire.dtl.DTLVardef@6aa99org.highwire.dtl.DTLVardef@1aa605e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Evaluating the Anti-aging Effects of Chinese Herbal Medicine Rhodiola rosea L. in Cultured Keratinocytes Among the many health benefits Chinese herbal medicine (CHM) presents, anti-aging is of special interest (Shen, Jiang, Yang, Wang, & Zhu, 2017; Zhao & Luo, 2017). Reported to possess anti-aging effects, the CHM Rhodiola rosea L., known colloquially as the "golden root", has been widely incorporated in various drinks, daily supplements, and even cosmetics. This study investigates the effects of commercial R. rosea extracts and natural R. rosea roots on preventing UV-induced photoaging of the skin and correlates such effects with the composition of active ingredients in the extracts. To simulate the photoaging process, drug treated HaCaT cells were exposed to UVA and UVB radiation. The pharmacological anti-aging effects of R. rosea extracts were evaluated qualitatively and quantitatively through confocal immunofluorescence images with {gamma}-H2A.X marker and telomerase activity assay (Telo TAGGG Telomerase PCR-ELISA). Preparatory thin layer chromatography and high-performance liquid chromatography were performed to isolate and quantify active ingredients. Cultured HaCaT cells showed morphological change after exposure to both UVA (>15.0 J) and UVB (>2000 mJ). The photoaging of keratinocytes was rescued by pretreating cells with R. rosea extracts as well as salidroside and rosavin active ingredients (P < 0.05). R. rosea-treated cells were characterized by increased telomerase activity and fewer {gamma}-H2A.X foci compared to that of the control. Extracts with better preventative effects contained higher salidroside and rosavin content. The findings in this study reaffirm R. roseas efficacy as an anti-aging remedy and provide a basis for CHMs integration into the mainstream of global healthcare. Single molecule studies reveal branched pathways for activator-dependent assembly of RNA polymerase II pre-initiation complexes RNA polymerase II (Pol II) transcription reconstituted from purified factors suggests pre-initiation complexes (PICs) can assemble by sequential incorporation of factors at the TATA box. However, these basal transcription reactions are generally independent of activators and co-activators. To study PIC assembly under more realistic conditions, we used single-molecule microscopy to visualize factor dynamics during activator-dependent reactions in nuclear extracts. Surprisingly, Pol II, TFIIF, and TFIIE can pre-assemble on enhancer-bound activators before loading into PICs, and multiple Pol II complexes can bind simultaneously to create a localized cluster. Unlike TFIIF and TFIIE, TFIIH binding is singular and dependent on the basal promoter. Activator-tethered factors exhibit dwell times on the order of seconds. In contrast, PICs can persist on the order of minutes in the absence of nucleotide triphosphates, although TFIIE remains unexpectedly dynamic even after TFIIH incorporation. Our kinetic measurements lead to a new branched model for activator-dependent PIC assembly.

HIGHLIGHTSSingle molecule microscopy reveals unexpected dynamics of RNA Pol II and GTFs

Multiple Pol IIs cluster on UAS/enhancer-bound activators before binding the core promoter

Pol II, TFIIF, and TFIIE, but not TFIIH, can pre-assemble at the UAS/enhancer

Activators increase the rates of Pol II and GTF association with DNA

eTOC BlurbSingle-molecule microscopy experiments by Baek et al. show that RNA polymerase II and basal transcription factors TFIIF and TFIIE preassemble on UAS/enhancer-bound activators, poised for loading into initiation complexes with TFIIH at the core promoter. Transcription activators kinetically enhance factor recruitment, creating a localized cluster of polymerases at the UAS/enhancer. Mouse lemur, a new primate model to investigate cardiac pacemaker activity. BackgroundGray mouse lemurs (Microcebus murinus) are one of the smallest and most ancestral primates known. Their size falls in between that of mice and rats, and their genetic proximity to humans makes them an emerging model to study age-related neurodegeneration. Since Microcebus murinus replicates similar senescence processes of humans, it constitutes a useful model also for studying cardiovascular dysfunctions. However, its cardiac physiology is unknown. Thus, we investigated sinoatrial node (SAN) pacemaker activity of mouse lemurs, presenting the first characterization of heart automaticity in nonhuman primates.

Methods and ResultsWe recorded the heart automaticity in freely moving mouse lemurs and in their SAN tissues and pacemaker myocytes. Mouse lemurs have a heart rate (HR) in between those of mice and rats and a similar generation of electrical impulses in the SAN tissue. Conversely, their ventricular depolarization is more similar to large mammals. Mouse lemur SAN myocytes express the main pacemaker currents at densities similar to mice: the hyperpolarization-activated current (If) and the L-type (ICa,L) and T-type (ICa,T) calcium currents. Moreover, mouse lemur SAN myocytes display spontaneous ryanodine receptor (RyR)-dependent Ca2+ transients. Using muscle-derived stem cells (MDSCs) from the Microcebus murinus skeletal muscle, we also differentiated pacemaker-like (PML) cells showing spontaneous automaticity and expressing markers of native SAN myocytes (HCN4 and connexin-45).

ConclusionsIn conclusion, our characterization of heart automaticity in Microcebus murinus provides new opportunities for comparative cardio-physiology studies in primates and with humans, and for pharmacologic testing of molecules that could assist in modulating age-related dysfunctions of automaticity. Placental structure, function and mitochondrial phenotype relate to fetal size and sex in mice Fetal growth depends on placental function, which requires energy from mitochondria. Here we investigated whether mitochondrial function in the placenta relates to growth of the lightest and heaviest fetuses of each sex within the litter of mice. Placentas from the lightest and heaviest fetuses were taken to evaluate placenta morphology (stereology), mitochondrial energetics (high-resolution respirometry), and mitochondrial regulators, nutrient transporters, hormone handling and signalling pathways (qPCR and western blotting). We found that mitochondrial complex I and II oxygen consumption rate was greater for placentas supporting the lightest female fetuses, although placental complex I abundance of the lightest females and complexes III and V of the lightest males were decreased compared to their heaviest counterparts. Expression of mitochondrial biogenesis (Nrf1) and fission (Drp1 and Fis1) genes was lower in the placenta from the lightest females, whilst biogenesis-related gene Tfam was greater in the placenta of the lightest male fetuses. Additionally, placental morphology and steroidogenic gene (Cyp17a1 and Cyp11a1) expression was aberrant for the lightest females, but glucose transporter (Glut1) expression was lower in only the lightest males versus their heaviest counterparts. Differences in intra-litter placental phenotype were related to sex-dependent changes in the expression of hormone responsive (androgen receptor) and metabolic signalling (AMPK, AKT, PPAR{gamma}) pathways. Thus, in normal mouse pregnancy, placental structure, function and mitochondrial phenotype are differentially responsive to growth of the female and the male fetus. This study may inform the design of sex- specific therapies for placental insufficiency and fetal growth abnormalities with life-long benefits for the offspring. Endogenous retroviruses co-opted as divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells Transposable elements are an abundant source of transcription factor binding sites and favorable genomic integration may lead to their recruitment by the host genome for gene regulatory functions. However, it is unclear how frequent co-option of transposable elements as regulatory elements is, to which regulatory programs they contribute and how they compare to regulatory elements devoid of transposable elements. Here, we report a transcription initiation-centric, in-depth characterization of the transposon-derived regulatory landscape of mouse embryonic stem cells. We demonstrate that a substantial number of transposable elements, in particular endogenous retroviral elements, carry open chromatin regions that are divergently transcribed into unstable RNAs in a cell-type specific manner, and that these elements contribute to a sizable proportion of active enhancers and gene promoters. We further show that transposon subfamilies contribute differently and distinctly to the pluripotency regulatory program through their repertoires of transcription factor binding sites, shedding light on the formation of regulatory programs and the origins of regulatory elements. Re-distribution of antibiotic within a community is behind the unpredictable change in efficacy observed in classic laboratory assays Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that differences in antibiotic sensitivity between co-existing bacterial species can modify the diffusion of antibiotic molecules, and alter the drug efficacy measured in conventional in vitro assays. I developed a model, validated experimentally using an artificial two-species community, showing antibiotic molecules re-distribute evenly across all species if they have similar drug sensitivity. The result is lower drug efficacy with respect to conventional in vitro assays. However, when species have different sensitivities, the re-distribution of antibiotic is uneven and most sensitive species accumulate more drug. The result is increased drug efficacy against these species. Despite this discrepancy with conventional laboratory assays, my data suggests the changes in drug efficacy are predictable and provides insight into how communities can affect the diffusion of other molecules in the environment. Reducing Movement Synchronization to Increase Interest Improves Interpersonal Liking Synchronization has been identified as a key aspect of achieving mutual goals and enhancing social bonding. While synchronization could be maximized by increasing the predictability of an interaction, such predictability is in tension with individuals level of interest, which is tied to the interactions complexity and novelty. In this study, we tested the interplay between synchronization and interest. We asked 104 female dyads to play the Mirror Game, in which they were instructed to move their hands as coordinately as possible, and then report how much they liked each other. Utilizing information theory and video processing tools, we found that a combination of movement synchronization and complexity explained liking almost two times better than movement synchronization alone. Moreover, we found that people initiated novel and challenging interactions, even though they paid a price - being less synchronized. Examining the interactions dynamics, we found that people who liked each other moved in a more synchronized, complex, and novel manner during most of the interaction. This suggests that in addition to synchronization, maintaining interest may be critical for positive social bonding. Thus, we propose a new framework in which balancing synchronization and interest, rather than merely maximizing synchronization, optimizes the interaction quality. The desert green algae Chlorella ohadii thrives at excessively high light intensities by exceptionally enhancing the mechanisms that protect photosynthesis from photoinhibition Although light is the driving force of photosynthesis, excessive light can be harmful. One of the main processes that limits photosynthesis is photoinhibition, the process of light-induced photodamage. When the absorbed light exceeds the amount that is dissipated by photosynthetic electron flow and other processes, damaging radicals are formed that mostly inactivate photosystem II (PSII). Damaged PSII must be replaced by a newly repaired complex in order to preserve full photosynthetic activity. Chlorella ohadii is a green micro-alga, isolated from biological desert soil crusts, that thrives under extreme high light and is highly resistant to photoinhibition. Therefore, C. ohadii is an ideal model for studying the molecular mechanisms underlying protection against photoinhibition. Comparison of the thylakoids of C. ohadii cells that were grown under low light versus extreme high light intensities, found that the alga employs all three known photoinhibition protection mechanisms: i) massive reduction of the PSII antenna size; ii) accumulation of protective carotenoids; and iii) very rapid repair of photo-damaged reaction center proteins. This work elucidated the molecular mechanisms of photoinhibition resistance in one of the most light-tolerant photosynthetic organisms and shows how photoinhibition protection mechanisms evolved to marginal conditions, enabling photosynthesis-dependent life in severe habitats.

One Sentence HighlightAnalysis of the photosynthetic properties of a desert algae that thrives at extreme high light intensities revealed protection from photoinhibition driven by the remarkable enhancement of three protection mechanisms. Game of theories: an agent-based model of how variation in contest cost-benefits determines the evolution of contest resolution rules Game-theory based models are used to understand rules that animals use to settle contests over indivisible resources. However, the empirical literature of contests indicates controversial support to models, with some species supporting different models and other species showing no support to any model. Since strategies used to resolve contests may have different associated costs, it is possible that different conditions have determined the evolution of distinct assessment strategies used by animals. We used an agent-based model to explore the importance of the following conditions: resource availability, probability of reproduction with resource, and damage costs on evolution of assessment strategies. We used self- and mutual-assessment models as a heurist framework to build agents with different assessment strategies. In our model, agents competed for resources in scenarios with different combinations of resource availability, probability of reproduction with resource, and damage costs. We found that agents following the self-assessment with damage strategy were prevalent in scenarios with no probability of reproduction without the resource, independently of other variables. We also found that agents following the non-aggressive strategy occurred in all scenarios. However, agents using the non-aggressive strategy were prevalent only in scenarios with probability of reproduction with the resource. Finally, we observed that agents using mutual-assessment occurred only in a scenario with high risk of damage, low availability of resources, and with probability of reproduction without the resource. These results indicate that agents following the self-assessment with damage and non-aggressive strategies may be able to stay at most scenarios. 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. TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. Spatio-temporal, optogenetic control of gene expression in organoids Organoids derived from stem cells become increasingly important to study human development and to model disease. However, methods are needed to control and study spatio-temporal patterns of gene expression in organoids. To this aim, we combined optogenetics and gene perturbation technologies to activate or knock-down RNA of target genes, at single-cell resolution and in programmable spatio-temporal patterns. To illustrate the usefulness of our approach, we locally activated Sonic Hedgehog (SHH) signaling in an organoid model for human neurodevelopment. High-resolution spatial transcriptomic and single-cell analyses showed that this local induction was sufficient to generate stereotypically patterned organoids in three dimensions and revealed new insights into SHHs contribution to gene regulation in neurodevelopment.

With this study, we propose optogenetic perturbations in combination with spatial transcriptomics as a powerful technology to reprogram and study cell fates and tissue patterning in organoids.