Changes to the mtDNA copy number during yeast culture growth We show that the mtDNA copy number in growing cultures of the yeast Saccharomyces cerevisiae increases by a factor of up to 4, being lowest ([~]10 per haploid genome) and stable during rapid fermentative growth, and highest at the end of the respiratory phase. When yeast are grown on glucose, the onset of the mtDNA copy number increase coincides with the early stages of the diauxic shift, and the increase continues through respiration. A lesser yet still substantial copy number increase occurs when yeast are grown on a nonfermentable carbon source, i.e. when there is no diauxic shift. The mtDNA copy number increase during and for some time after the diauxic shift is not driven by an increase in cell size. The copy number increase occurs in both haploid and diploid strains, but is markedly attenuated in a diploid wild isolate that is a ready sporulator. Strain-to-strain differences in mtDNA copy number are least apparent in fermentation and most apparent in late respiration or stationary phase. While changes in mitochondrial morphology and function were previously known to accompany changes in physiological state, it had not been previously shown that the mtDNA copy number changes substantially over time in a clonal growing culture. The mtDNA copy number in yeast is therefore a highly dynamic phenotype.
Non-invasive imaging of gene expression and protein secretion dynamics in living mice: identification of ectopic prothrombin expression as driver of thrombosis in cancer The topology of gene expression and protein localization is a crucial characteristic of life, where the spatiotemporal dynamic of secretory proteins instruct higher order organization, including the orchestration of developmental and adaptive programs. However tools to non-invasively interrogate the fate of secretory proteins in vivo are scarce. Here we introduce a genetic tagging strategy for in vivo imaging of the secretion and expression dynamics of secretory proteins in living animals. Applying this to a prototypical liver-derived secretory protein, we demonstrate that this approach, combined with optical in-vivo imaging, uncovers extrahepatic prothrombin expression in multiple novel anatomical sites (including testes, placenta, brain, kidney, heart and lymphatic system) and in emerging tumors, resulting in significant amounts of tumor-derived prothrombin in the blood with procoagulant properties. Syngeneic cell lines from this mouse model enable unravelling regulatory mechanisms in high resolution, and in a scalable format ex vivo. Beyond discovering new functions of proteins in a targeted manner, this model allows identifying rheostats in the cross-talk between gene expression and availability of a secretory protein. It is also a valuable resource for uncovering novel (tissue-specific) therapeutic vulnerabilities.
Loss of Acta2 in cardiac fibroblasts does not prevent myofibroblast differentiation or affect cardiac repair after myocardial infarction In response to myocardial infarction (MI), quiescent cardiac fibroblasts differentiate into myofibroblasts mediating tissue repair in the infarcted area. One of the most widely accepted markers of myofibroblast differentiation is the expression of Acta2 which encodes smooth muscle alpha-actin (SMA) that is assembled into stress fibers. However, the requirement of Acta2 in the myofibroblast differentiation of cardiac fibroblasts and its role in post-MI cardiac repair were still not known. To answer these questions, we generated a tamoxifen-inducible cardiac fibroblast-specific Acta2 knockout mouse line. Surprisingly, mice that lacked Acta2 in cardiac fibroblasts had a normal survival rate after MI. Moreover, Acta2 deletion did not affect the function or overall histology of infarcted hearts. No difference was detected in the proliferation, migration, or contractility between WT cardiac fibroblasts and Acta2-null cardiac myofibroblasts. Additional analysis identified that Acta2-null cardiac myofibroblasts had a normal total filamentous actin level and total actin level. Acta2 deletion caused a unique compensatory increase in the transcription level of Actg2 and a possible increase in the protein abundance of cytoplasmic actin isoforms. In conclusion, the deletion of Acta2 does not prevent the myofibroblast differentiation of cardiac fibroblasts or affect the post-MI cardiac repair, and the increase in the expression of non-SMA actin isoforms and the functional redundancy between actin isoforms are likely able to compensate for the loss of Acta2 in cardiac myofibroblasts. 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. Slowing down an analyte in a nanopore An unresolved problem in nanopore sensing is the high translocation speed ([~]10-100 monomers/s) of an analyte (nucleotide, DNA, amino acid (AA), peptide) through the pore. Here a method based on reversing the pore voltage and changing the solution pH is described. A simplified Fokker-Planck model shows mean translocation times of 1-10 ms in a nanopore of length 10 nm. Simulations show that a positive-negative voltage profile can trap an analyte for [~]1 ms. This method can be used for free nucleotides, single AAs, oligonucleotides, and oligopeptides. Its applicability to existing nanopore sensing and sequencing techniques and implementation issues are discussed. The isoforms of pyruvate kinase act as nutrient sensors for the β-cell KATP channel Insulin release from pancreatic {beta}-cells is triggered by the metabolism-dependent closure of ATP-sensitive K+ (KATP) channels. Here, we used isoform-specific deletion of pyruvate kinase (PK) to identify the unique roles of PKm1 and PKm2 in the {beta}-cell nutrient response. In the absence of PK activity, cytosolic ATP/ADP was insufficient to close KATP channels. Both PK isoforms were found on the plasma membrane, where they endow KATP channels with nutrient sensitivity and specificity. Although PKm1 accounts for >90% of cellular activity, PKm2 controls glucosedependent KATP closure. Amino acids, which generate mitochondrial phosphoenolpyruvate (PEP) without allosterically activating PKm2, depend on PKm1 to raise ATP/ADP and close KATP channels. Shifting the {beta}-cell from PKm2 to PKm1 correspondingly increased amino acid sensitivity and boosted secretory output. In addition to these membrane depolarizing "on-switches," {beta}-cell deletion of PCK2 exposed a mitochondrial PEP-dependent "off-switch" that facilitates Ca2+ extrusion. Restricting PCK2 prolonged Ca2+ influx and increased insulin secretion. In summary, it is not the KATP channel alone, but the PK-KATP microcompartment that confers nutrient sensitivity to the {beta}-cell plasma membrane. The differential response of the PK isoforms to the glycolytic and mitochondrial sources of PEP influences {beta}-cell nutrient preference, and controls the oscillatory cycle regulating insulin secretion. Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for sparse genomic measures Deep learning has the ability to extract meaningful features from data given enough training examples. Large scale genomic data are well suited for this class of machine learning algorithms; however, for many of these data the labels are at the level of the sample instead of at the level of the individual genomic measures and features. To leverage the power of deep learning for these types of data we turn to a multiple instance learning framework, and present an easily extensible tool built with TensorFlow and Keras. We show how this tool can be applied to somatic variants (featurizing genomic position, sequence context, and read counts) on a range of artificial tasks (classification, regression, Cox regression). In addition, we confirm the model can achieve high performance on real-world problems, accurately classifying samples according to whether they contain a specific variant (hotspot or tumor suppressor), groups of variants (tumor clonality), or a type of variant (microsatellite instability). Our results suggest this framework will lead to improvements on sample-level tasks that require aggregation of a set of genomic measures. A MALDI-TOF assay identifies nilotinib as an inhibitor of inflammation in acute myeloid leukaemia Inflammatory responses are important in cancer, particularly in the context of monocyte-rich aggressive myeloid neoplasm. We developed a label-free cellular phenotypic drug discovery assay to identify anti-inflammatory drugs in human monocytes derived from acute myeloid leukaemia (AML), by tracking several biological features ionizing from only 2,500 cells using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry. A proof-of-concept screen showed that the BCR-ABL inhibitor nilotinib, but not the structurally similar imatinib, blocks inflammatory responses. In order to identify the cellular (off-)targets of nilotinib, we performed thermal proteome profiling (TPP). Unlike imatinib, nilotinib and other later generation BCR-ABL inhibitors inhibit the p38-MK2/3 signalling axis which suppressed the expression of inflammatory cytokines, cell adhesion and innate immunity markers in activated human monocytes derived from AML. Thus, our study provides a tool for the discovery of new anti-inflammatory drugs, which could contribute to the treatment of inflammation in myeloid neoplasms and other diseases.

Key PointsLabel-free cell-based assay identifies new anti-inflammatory drugs using MALDI-TOF MS. Nilotinib reduces inflammation by inhibition of MAPK14-MK2/3 signalling axis in AML. 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. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Structure-Functional-Selectivity Relationship Studies on A-86929 Analogs and Small biaryl Fragments toward Discovery of biased D1 agonists Dopamine regulates normal functions such as movement, reinforcement learning, and cognition, and its dysfunction has been implicated in multiple psychiatric and neurological disorders. Dopamine acts through the D1- (D1R and D5R) and D2-class (D2R, D3R and D4R) of seven transmembrane receptors, and activates both G-protein- and {beta}-arrestin-dependent signaling pathways, to mediate its physiological effects. Current dopamine receptor-based therapies are used to ameliorate motor deficits in Parkinsons disease, or as antipsychotic medications for schizophrenia. These drugs show efficacy for ameliorating only some symptoms caused by dopamine dysfunction and are plagued by debilitating side-effects. Studies in primates and rodents have shown that shifting the balance of dopamine receptor signaling towards the arrestin pathway can be beneficial for inducing normal movement, while reducing motor side-effects such as dyskinesias, and can be efficacious at enhancing cognitive function compared to balanced agonists. Several structure-activity-relationship (SAR) studies have embarked on discovering {beta}-arrestin-biased dopamine agonists, focused on D2 partial agonists, non-catechol D1 agonists, and mixed D1/D2R dopamine receptor agonists. Here, we describe an SAR study to identify novel D1R {beta}-arrestin biased ligands using A-86929, a high-affinity D1R catechol agonist, as a core scaffold. Previously described and novel analogs of A-86929 were synthesized and screened in vitro for structure-functional-selectivity relationships (SFSR) studies to identify chemical motifs responsible for {beta}-arrestin biased activity at both D1 and D2Rs. Most of the A-86929 analogs screened were G protein biased but none of them were exclusively arrestin-biased. Additionally, various catechol aryl fragments were designed and synthesized. Other compounds surveyed included hydroxyl and chloro analogs of dopamine to test for hydrogen bonding and ionic interactions. Some of these small molecular probes displayed weak bias towards the {beta}-arrestin pathway. Continued in-depth SFSR studies informed by structure determination, molecular modeling, and mutagenesis studies will facilitate discovery of potent and efficacious arrestin-biased dopamine receptor ligands. Omicron BA.1 and BA.2 Variants Increase the Interactions of SARS-CoV-2 Spike Glycoprotein with ACE2 SARS-CoV-2 infection is initiated by binding of the receptor-binding domain (RBD) of its spike glycoprotein to the peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptors in host cells. Recently detected Omicron variant of SARS-CoV-2 (B.1.1.529) is heavily mutated on RBD. Currently, the most common Omicron variants are the original BA.1 Omicron strain and the BA.2 variant, which became more prevalent since it first appeared. To investigate how these mutations affect RBD-PD interactions, we performed all-atom molecular dynamics simulations of the BA.1 and BA.2 RBD-PD in the presence of full-length glycans, explicit water and ions. Simulations revealed that RBDs of BA.1 and BA.2 variants exhibit a more dispersed interaction network and make an increased number of salt bridges and hydrophobic interactions with PD compared to wild-type RBD. Although BA.1 and BA.2 differ in two residues at the RBD-ACE2 interface, no major difference in RBD-PD interactions and binding strengths were observed between these variants. Using the conformations sampled in each trajectory, the Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA) method estimated ~34% and ~51% stronger binding free energies for BA.1 and BA.2 RBD, respectively, than wild-type RBD, which may result in higher binding efficiency of the Omicron variant to infect host cells. Development of antibiotic resistance reveals diverse evolutionary pathways to face the complex and dynamic environment of a long-term treated patient Antibiotic resistance development has been studied using approaches that range from laboratory experimental evolution, surveillance and epidemiology, to clinical isolate sequencing. However, evolutionary trajectories depend on the environment in which selection takes place, compelling to address evolutionary analyses in antibiotic-treated patients, to embrace the whole inherent environmental complexities as well as their dynamics over time. Herein, we address the complexity of the bacterial adaptive response to changing antibiotic selective pressures by studying the long-term in-patient evolution of a broad diversity of {beta}-lactam resistant Pseudomonas aeruginosa clones. By using mutational and ultra-deep amplicon sequencing, we analyzed multiple generations of a P. aeruginosa hypermutator strain persisting for more than 26 years of chronic infection in the airways of a cystic fibrosis (CF) patient. We identified the accumulation of multiple alterations targeting the chromosomally encoded class C {beta}-lactamase (blaPDC), providing structural and functional protein changes that resulted in a continuous enhancement of its catalytic efficiency and high level of cephalosporin resistance. This evolution was linked to the persistent treatment with ceftazidime, which we demonstrate selected for variants with robust catalytic activity against this expanded-spectrum cephalosporin. Surprisingly, "a gain of function" of collateral resistance towards ceftolozane, a more recently introduced cephalosporin that was not prescribed to this patient, was also observed and the biochemical basis of this cross-resistance phenomenon was elucidated. This work unveils the diversity of evolutionary trajectories driven by bacteria in the natural CF environmental setting, towards a multidrug resistant phenotype after years of antibiotic treatment against a formidable pathogen. Microsecond simulations and CD spectroscopy reveals the intrinsically disordered nature of SARS-CoV-2 Spike-C-terminal cytoplasmic tail (residues 1242-1273) in isolation All available SARS-CoV-2 spike protein crystal and cryo-EM structures have shown missing electron densities for cytosolic C-terminal regions. Generally, the missing electron densities point towards the intrinsically disordered nature of the protein region. This curiosity has led us to investigate the C terminal cytosolic region of the spike glycoprotein of SARS-CoV-2 in isolation. The cytosolic regions is supposed to be from 1235-1273 residues or 1242-1273 residues depending on what prediction tool we use. Therefore, we have demonstrated the structural conformation of cytosolic region and its dynamics through computer simulations up to microsecond timescale using OPLS and CHARMM forcefields. The simulations have revealed the unstructured conformation of cytosolic region. Also, in temperature dependent replica-exchange molecular dynamics simulations it has shown its conformational dynamics. Further, we have validated our computational observations with circular dichroism (CD) spectroscopy-based experiments and found its signature spectra at 198 nm which is also adding the analysis as its intrinsically disordered nature. We believe that our findings will surely help us understand the structure-function relationship of the spike proteins cytosolic region.

Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY The limits of evolutionary convergence in sympatry: reproductive interference and historical constraints leading to local diversity in warning traits Mutualistic interactions between defended species represent a striking case of evolutionary convergence in sympatry, driven by the increased protection against predators brought by mimicry in warning traits. However, such convergence is often limited: sympatric defended species frequently display different or imperfectly similar warning traits. The phylogenetic distance between sympatric species may indeed prevent evolution towards the exact same signal. Moreover, warning traits are also involved in mate recognition, so that trait convergence might result in heterospecific courtship and mating. Here, we develop a mathematical model to investigate the strength and direction of evolution of warning trait in defended species with different ancestral traits. Specifically, we determine the effect of phenotypic distances between ancestral trait states of sympatric defended species and of costs of heterospecific sexual interactions on imperfect mimicry and trait divergence. Our analytical results confirm that reproductive interference and historical constraints limit the convergence of warning traits, leading to either complete divergence, or imperfect mimicry. Our model reveals that imperfect mimicry evolves only when ancestral trait values differ between species, due to historical constraints and highlights the importance of female and predator discriminations in the evolution of such imperfect mimicry. Our study thus provides new predictions on how reproductive interference interacts with historical constraints and may promote the emergence of novel warning traits, enhancing mimetic diversity. Arabidopsis AtPME2 has a pH-dependent processivity and control cell wall mechanical properties Pectin methylesterases (PMEs) modify homogalacturonans (HG) chemistry and play a key role in regulating primary cell wall mechanical properties. How PME activity can fine-tune pectin structure in the growing plant has remained elusive. Here we report on the Arabidopsis AtPME2, which we found to be highly expressed during lateral root emergence and dark-grown hypocotyl elongation. We produced the mature active enzyme using heterologous expression in Pichia pastoris and characterized it through the use of a generic plant PME antiserum suitable for detecting recombinant and native enzyme independent of species source. At neutral pH AtPME2 is preferentially active on pectins with a degree of 55-70% methylesterification and can be inhibited by PME inhibitor protein (PMEI). We show that the mode of action for AtPME2 can switch from full processivity (at pH 8), creating large blocks of unmethylated galacturonic acid, to low processivity (at pH 5) and relate these observations to the differences in electrostatic potential of the protein at acidic and alkaline pH. To assess the role of AtPME2 in development, we characterized two knock-out lines. We show that in the context of acidified apoplast, low-processive demethylesterification by AtPME2 can loosen the cell wall, with consequent increase in cell elongation and etiolated hypocotyl length. Our study brings insights into how the pH-dependent regulation by PME activity could affect pectin structure and associated cell wall mechanical properties in expansion.

One sentence summaryThe processivity of AtPME2, a pectin methylesterase that fine-tunes cell wall pectins is modulated by pH in vitro and impacts the mechanical properties of the wall, affecting development in planta. Intestine-enriched apolipoprotein b orthologs are required for stem cell differentiation and regeneration in planarians Lipid metabolism plays an instructive role in regulating stem cell state and differentiation. However, the roles of lipid mobilization and utilization in stem cell-driven regeneration are unclear. Planarian flatworms readily restore missing tissue due to injury-induced activation of pluripotent somatic stem cells called neoblasts. Here, we identify two intestine-enriched orthologs of apolipoprotein b, apob-1 and apob-2, which mediate transport of neutral lipid stores from the intestine to target tissues including neoblasts, and are required for tissue homeostasis and regeneration. Inhibition of apob function by RNAi causes head regression and lysis in uninjured animals, and delays body axis re-establishment and regeneration of multiple organs in amputated fragments. Furthermore, apob RNAi causes expansion of the population of differentiating neoblast progeny and dysregulates expression of genes enriched in differentiating and mature cells in eight major cell type lineages. We conclude that intestine-derived lipids serve as a source of metabolites required for neoblast differentiation. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Cell type-specific inference of differential expression in spatial transcriptomics Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed (DE) within specific cell types across tissue context. We show that current approaches cannot learn cell type-specific DE due to changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type. Here, we introduce a statistical method, Cell type-Specific Inference of Differential Expression (C-SIDE), that identifies cell type-specific patterns of differential gene expression while accounting for localization of other cell types. We model spatial transcriptomics gene expression as an additive mixture across cell types of general log-linear cell type-specific expression functions. This approach provides a unified framework for defining and identifying gene expression changes in a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MER-FISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimers mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our C-SIDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr. Mouse lemur, a new animal model to investigate cardiac pacemaker activity in primates. 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. Sex-specific effects of an IgE polymorphism on immunity, susceptibility to infection and reproduction in a wild rodent The genotype of an individual is an important predictor of their immune function, and subsequently, their ability to control or avoid infection and ultimately contribute offspring to the next generation. However, the same genotype, subjected to different environments, can also result in different outcomes. The sexes represent two such different environments. Sexual dimorphism is widespread across the animal kingdom. Despite this, very little is known about the importance of sex for the expression of genotype in the context of health and disease, particularly in natural populations. We identified a synonymous polymorphism in the high-affinity Immunoglobulin E (IgE) receptor (GC and non-GC haplotypes) that has sex-specific effects on immune gene expression, susceptibility to infection and reproductive success of individuals in a natural population of field voles (Microtus agrestis). We found that the effect of the GC haplotype on the expression of genes affecting inflammation displayed a significant interaction with sex. While males with the GC haplotype had upregulated pro-inflammatory genes, in particular the pro-inflammatory cytokine Il33, females had upregulated anti-inflammatory genes, in particular the anti-inflammatory cytokine inhibitor Socs3. Furthermore we found that the effect of the GC haplotype on the probability of infection with a common microparasite, Babesia microti, displayed a significant interaction with sex. While males with the GC haplotype did not differ significantly in their susceptibility to infection, females with the GC haplotype were more likely to be infected. Finally, we found that the effect of the GC haplotype on reproductive success also displayed a significant interaction with sex. While males with the GC haplotype had a lower reproductive success, females with the GC haplotype did not differ in the number of offspring they produced. To our knowledge, this is the first time that a polymorphism with sex-specific effects across all three levels (immune gene expression, susceptibility to infection and reproductive success) has been documented in a natural population. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. Improved AlphaFold modeling with implicit experimental information Machine learning prediction algorithms such as AlphaFold1 and RoseTTAFold2 can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy3-6. We hypothesized that by implicitly including experimental information, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt based on experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We find that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for crystallographic and electron cryo-microscopy map interpretation. Identifying control ensembles for information processing within the cortico-basal ganglia-thalamic circuit In situations featuring uncertainty about action-reward contingencies, mammals exhibit a high degree of flexibility in adopting strategies for decision-making that are tuned in response to the conditions that they encounter. Although the cortico-basal ganglia thalamic (CBGT) network is implicated in information processing during decisions, it features a complex synaptic architecture, comprised of multiple feed-forward, reciprocal, and feedback pathways, that complicate efforts to elucidate the roles of specific CBGT populations in the process of evidence accumulation. In this paper we apply a strategic sampling approach, based on Latin hypercube sampling, to explore how variations in CBGT network properties, including subpopulation firing rates and synaptic weights, map to variability of parameters in a normative drift diffusion model (DDM), representing algorithmic aspects of information processing during decision-making. Through the application of canonical correlation analysis, we find that this relationship can be characterized in terms of three low-dimensional control ensembles within the CBGT network that impact specific qualities of the emergent decision policy: responsiveness (associated with overall activity in corticothalamic and direct pathways), pliancy (associated largely with overall activity in components of the indirect pathway of the basal ganglia), and choice (associated with differences in direct and indirect pathways across action channels). These analyses provide key mechanistic predictions about the roles of specific CBGT network elements in tuning information processing dynamics during decisions.

Author summaryMammals are continuously subjected to uncertain situations in which they have to choose among behavioral options. The cortico-basal ganglia-thalamic (CBGT) circuit is a complicated collection of interconnected nuclei believed to strongly influence the ability to adapt to environmental changes. The roles of specific CBGT components in controlling information during decisions remains unclear. At a more phenomenological, algorithmic level, drift-diffusion models have been shown to be able to reproduce behavioral data (action selection probabilities and the time needed to make a decision) obtained experimentally from mammals and to provide an abstract representation of a decision policy. In this work, we use simulated decision-making to establish a mapping from neural activity in the CBGT circuit to behavioral outcomes. This mapping illuminates the importance of three core sets of CBGT subnetworks in the action selection process and how they are involved in adapting decision policies across exploitative and exploratory situations. 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. Integrative small and long RNA-omics analysis of human healing and non-healing wounds discovers cooperating microRNAs as therapeutic targets MicroRNAs (miR) are important posttranscriptional regulators and exhibit a high potential to be utilized in diagnosis and therapy. However, our insufficient knowledge of the miR-mediated gene regulation in human skin wound healing severely hinders the identification of clinically relevant miRs. Here, we performed paired small RNA and long RNA sequencing in human tissue samples, including matched skin and acute wounds collected at each healing stage and chronic non-healing venous ulcers (VU). With integrative small and long RNA-omics analysis, we developed a compendium (https://www.xulandenlab.com/humanwounds-mirna-mrna), which will be an open, comprehensive resource to broadly aid wound healing research. With this first clinical, wound-centric resource of miRs and mRNAs, we identified 17 pathologically relevant miRs that exhibited abnormal VU expression and displayed their targets enriched explicitly in the VU gene signature. Intermeshing regulatory networks controlled by these miRs revealed their high cooperativity in contributing to chronic wound pathology characterized by persistent inflammation and proliferative phase initiation failure. Furthermore, we demonstrated that miR-34a, miR-424, and miR-516, upregulated in VU, cooperatively suppressed keratinocyte growth while promoting inflammatory response. Collectively, our study opens the possibility of developing innovative wound treatment that targets pathologically relevant cooperating miRs to attain higher therapeutic efficacy and specificity.