Slc9a6 mutation causes Purkinje cell loss and ataxia in the shaker rat BackgroundThe shaker rat carries a naturally occurring mutation leading to progressive ataxia characterized by Purkinje cell (PC) loss. We previously reported on fine-mapping the shaker locus to the long arm of the rat X chromosome. In this work, we sought to identify the mutated gene underlying the shaker phenotype and confirm its identity by functional complementation.

MethodsWe fine-mapped the candidate region and analyzed cerebellar transcriptomes to identify deleterious variants. We generated an adeno-associated virus (AAV) targeting solute carrier family 9, member A6 (Slc9a6) expression to PCs using a mouse L7-6 (L7) promoter, as well as a control green fluorescent protein (GFP)-expressing virus. We administered AAVs prior to the onset of PC degeneration through intracerebroventricular injection and evaluated the molecular, cellular, and motor phenotypes.

ResultsWe identified a XM_217630.9 (Slc9a6):c.[191_195delinsA] variant in the Slc9a6 gene that segregated with disease. This mutation is predicted to generate a truncated sodium-hydrogen exchanger 6 (NHE6) protein, p.(Ala64Glufs*23). Administration of AAV9-PHP.eB expressing rat Slc9a6 prior to symptom onset reduced the shaker motor, molecular, and cellular phenotypes.

InterpretationSlc9a6 is mutated in shaker and also in human Christianson syndrome, an epileptic encephalopathy. AAV-based gene therapy may be a viable therapeutic strategy for Christianson syndrome, and the shaker rat model may aid in therapeutic development.
From perception to action: Intracortical recordings reveal cortical gradients of human exogenous attention Exogenous attention, the process that makes external salient stimuli pop-out of a visual scene, is essential for survival. How attention-capturing events modulate processing dynamics in the human brain remains unclear. We obtained a comprehensive depiction of attentional cortical dynamics at high spatiotemporal resolution, by analyzing brain activity from 1,403 intracortical contacts implanted in 28 individuals, while they performed an exogenous attention task. The timing, location and task-relevance of attentional events defined a spatiotemporal gradient of three neural clusters, which mapped onto cortical core-periphery topography and presented a hierarchy of timescales, providing the scaffolding for attention temporal computations. Visual attributes modulated neural activity at one end of the gradient, while activity at the other end reflected the upcoming response timing, with attentional effects occurring at the intersection of visual and response signals. These findings reveal how the psychological construct of exogenous attention emerges over large-scale cortical gradients in the human brain.
TNFa-induced LDL cholesterol accumulation involve elevated LDLR cell surface levels and SR-B1 downregulation in human arterial endothelial cellsan arterial endothelial cells Excess lipid droplets are frequently observed in arterial endothelial cells at sites of advanced atherosclerotic plaques. Here, the role of tumor necrosis factor alpha (TNF) in modulating low density lipoprotein (LDL) content in confluent primary human aortic endothelial cells (pHAECs) was investigated. TNF promoted up to 2 folds increase in cellular cholesterol, which was resistant to ACAT inhibition. The cholesterol increase was associated with increased 125I-LDL surface binding. Using the non-hydrolysable label, Dil, TNF could induce a massive increase in Dil-LDL by over 200 folds. The elevated intracellular Dil-LDL was blocked with excess unlabeled LDL and PCSK9, but not oxidized LDL (oxLDL), receptor associated protein (RAP), or apolipoprotein (apoE) depletion. Moreover, TNF-induced increase of LDL-derived lipids was elevated through lysosome inhibition. Using specific LDLR antibody, the Dil-LDL accumulation was reduced by over 99%. Effects of TNF included LDLR cell surface increase by 138%, and very large increases in ICAM-1 total and surface proteins, respectively. In contrast, that of scavenger receptor B1 (SR-B1) was reduced. Additionally, LDLR antibody bound rapidly in TNF-treated cells by about 30 folds, inducing a migrating shift in the LDLR protein. The effect of TNF on Dil-LDL accumulation was inhibited by the antioxidant tetramethythiourea (TMTU) dose-dependently, but not by inhibitors against NF-{kappa}B, stress kinases, ASK1, JNK, p38, or apoptosis caspases. Grown on transwell inserts, TNF did not enhance apical to basolateral LDL cholesterol or Dil release. It is concluded that TNF promotes LDLR functions through combined increase at the cell surface and SR-B1 downregulation. Evaluation of methods for estimating coalescence times using ancestral recombination graphs The ancestral recombination graph (ARG) is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress towards scalably estimating whole-genome genealogies. In addition to inferring the ARG, some of these methods can also provide ARGs sampled from a defined posterior distribution. Obtaining good samples of ARGs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from three popular ARG inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare 1) the true coalescence times to the inferred times at each locus; 2) the distribution of coalescence times across all loci to the expected exponential distribution; 3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all three methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relates, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices. Extending Bayesian Elo-rating to quantify the steepness of dominance hierarchies The steepness of dominance hierarchies provides information about the degree of competition within animal social groups and is thus an important concept in socioecology. The currently most widely-used metrics to quantify steepness are based on Davids scores (DS) derived from dominance interaction networks. One serious drawback of these DS-based metrics is that they are biased, i.e., network density systematically decreases steepness values. Here, we provide a novel approach to estimate steepness based on Elo-ratings, implemented in a Bayesian framework (STEER: Steepness estimation with Elo-rating). Our new metric has two key advantages. First, STEER is unbiased, precise and more robust to data density than DS-based steepness. Second, it provides explicit probability distributions of the estimated steepness coefficient, which allows uncertainty assessment. In addition, it relies on the same underlying concept and is on the same scale as the original measure, and thus allows comparison to existing published results. We evaluate and validate performance of STEER by means of experimentation on empirical and artificial data sets and compare its performance to that of several other steepness estimators. Our results suggest that STEER provides a considerable improvement over existing methods to estimate dominance hierarchy steepness. We provide an R package EloSteepness to calculate the new steepness measure, and also show an example of using steepness in a comparative analysis. Shortcuts in stochastic systems and control of biophysical processes The biochemical reaction networks that regulate living systems are all stochastic to varying degrees. The resulting randomness affects biological outcomes at multiple scales, from the functional states of single proteins in a cell to the evolutionary trajectory of whole populations. Controlling how the distribution of these outcomes changes over time--via external interventions like time-varying concentrations of chemical species--is a complex challenge. In this work, we show how counterdiabatic (CD) driving, first developed to control quantum systems, provides a versatile tool for steering biological processes. We develop a practical graph-theoretic framework for CD driving in discrete-state continuous-time Markov networks. Though CD driving is limited to target trajectories that are instantaneous stationary states, we show how to generalize the approach to allow for non-stationary targets and local control--where only a subset of system states are targeted. The latter is particularly useful for biological implementations where there may be only a small number of available external control knobs, insufficient for global control. We derive simple graphical criteria for when local versus global control is possible. Finally, we illustrate the formalism with global control of a genetic regulatory switch and local control in chaperone-assisted protein folding. The derived control protocols in the chaperone system closely resemble natural control strategies seen in experimental measurements of heat shock response in yeast and E. coli. Usutu virus escapes langerin-induced restriction to productively infect human Langerhans cells, unlike West Nile virus. Usutu virus (USUV) and West Nile virus (WNV) are phylogenetically close emerging arboviruses transmitted by mosquitoes, and constitute a global public health threat. Since USUV and WNV enter the body through the skin, the first immune cells they encounter are skin-resident dendritic cells, the most peripheral outpost of immune defense. This unique network is composed of Langerhans cells (LCs) and dermal DCs, which reside in the epidermis and the dermis, respectively.

Using human skin explants, we show that while both viruses can replicate in keratinocytes, they can also infect resident DCs with distinct tropism, since WNV preferentially infects DCs in the dermis, whereas USUV has a greater propensity to infect LCs. Using both purified human epidermal LCs (eLCs) and monocyte derived LCs (MoLCs), we confirm that LCs sustain a faster and more efficient replication of USUV compared with WNV and that this correlates with a more intense innate immune response to USUV compared with WNV. Next, we show that ectopic expression of the LC-specific C-type lectin receptor (CLR), langerin, in HEK293T cells allows WNV and USUV to bind and enter, but supports the subsequent replication of USUV only. Conversely, blocking or silencing langerin in MoLCs or eLCs made them resistant to USUV infection, thus demonstrating that USUV uses langerin to enter and replicate in LCs. Altogether, our results demonstrate that LCs constitute privileged target cells for USUV in human skin, because langerin favors its entry and replication. Intriguingly, this suggests that USUV efficiently escapes the antiviral functions of langerin, which normally safeguards LCs from most viral infections. 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. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2 Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, due to the poor stability, most current mRNA delivery platforms need to be stored at -20 {degrees}C or -70 {degrees}C. Here we present lyophilized thermostable mRNA loaded lipid nanoparticles, which could be stored at room temperature with long-term stability. We demonstrate the applicability of lyophilization techniques to different mRNA sequences and lipid components. Three lyophilized vaccines targeting wild-type, Delta and Omicron SARS-CoV-2 variant were prepared and demonstrated to be able induce high-level of IgG titer and neutralization response. In the Delta challenge in vivo experiment, the lyophilized mRNA vaccine successfully protected the mice from infection and clear the virus. This lyophilization platform could significantly improve the accessibility of mRNA vaccine or therapeutics, particularly in remote regions. Unsupervised clustering analysis of SARS-Cov-2population structure reveals six major subtypes atearly stage across the world Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses. Transcription factors in the fungus Aspergillus nidulans: Markers of genetic innovation, network rewiring and conflict between genomics and transcriptomics Gene Regulatory Networks (GRNs) are shaped by the democratic/hierarchical relationships among transcription factors (TFs) and associated proteins, together with the cis-regulatory sequences (CRSs) bound by these TFs at target promoters. GRNs control all cellular processes, including metabolism, stress-response, growth and development. Due to the ability to modify morphogenetic and developmental patterns, there is the consensus view that the reorganization of GRNs is a driving force of species evolution and differentiation. Duplication of TF-coding genes, their divergent sequence evolution and gain/loss/modification of CRSs are events rewiring GRNs. Fungi (mainly Saccharomycotina) have served as a reference kingdom for the study of GRN evolution. Here, I studied the genes predicted to encode TFs in the fungus Aspergillus nidulans (Pezizomycotina). The analysis of the expansion of different families of TFs suggests that duplication of TFs impacts the species level and that the expansion in Zn2Cys6 TFs is mainly due to dispersed duplication events. Comparison of genomic annotation and transcriptomic data suggests that a significant percentage of genes should be re-annotated while many others remain silent. Finally, a new regulator of growth and development is identified and characterized. Overall, this study establishes a novel theoretical framework in synthetic biology, since overexpression of silent TF forms would provide additional tools to assess how GRNs are rewired.

Impact StatementGRNs controlling fungal sexual and asexual development, stress response, carbon/nitrogen metabolism or secondary metabolism, have been widely characterized in the fungus A. nidulans and, in several cases, were characterized for the first time in this fungus. The functional and genetic relationships among the TFs of these networks are known. By comparing the genomes/proteomes of hundreds of fungal genomes available in public repositories, researchers can track the emergence of regulators of interest, and identify groups of paralog TFs. The present work uses basic bioinformatics tools and standard RNA-seq analysis tools to compare genomic annotation and transcriptomics data, find incorrectly annotated TFs, identify paralog clusters of TFs, track the trajectories of duplication events and expansion of bHLH-type TFs, and identify TFs with a role in the control of growth and development. The study of TFs and GRNs of A. nidulans offers the opportunity to dissect and analyze sequentially the contribution of each cis and trans regulatory element to network rewiring and the modification of developmental patterns.

Data SummaryThe data underlying this article are available in supplementary tables and supplementary figures. RNA-seq, genomic and proteomic data used is this article (and previously deposited by others; see references and accession numbers in Materials and Methods) were retrieved from sources (www.ebi.ac.uk/arrayexpress/; www.ncbi.nlm.nih.gov/bioproject/; https://www.ncbi.nlm.nih.gov/geo/) and databases (https://fungidb.org/fungidb/app) in the public domain. Aspergillus nidulans strains generated in this article will be shared on reasonable request to the corresponding author.

One-sentence summaryA study of the predicted set of transcriptional regulators in the fungus Aspergillus nidulans, their conservation patterns and the correlation between gene annotations and transcriptomic data PAK1 and PAK2 in cell metabolism regulation P21-activated kinases (PAKs) regulate processes associated with cytoskeletal rearrangements, such as cell division, adhesion, and migration. The possible regulatory role of PAKs in cell metabolism has not been well explored, but increasing evidence suggests that a cell metabolic phenotype is related to cell interactions with the microenvironment. We analyzed the impact of PAK inhibition by small molecule inhibitors, small interfering RNA, or gene knockout on the rates of mitochondrial respiration and aerobic glycolysis. Pharmacological inhibition of PAK group I by IPA-3 induced a strong decrease in metabolic rates in human adherent cancer cell lines, leukemia/lymphoma cell lines, and primary leukemia cells. The immediate effect of FRAX597, which inhibits PAK kinase activity, was moderate, indicating that PAK nonkinase functions are essential for cell metabolism. Selective downregulation or deletion of PAK2 was associated with a shift toward oxidative phosphorylation. Alternatively, PAK1 knockout resulted in increased glycolysis. However, the overall metabolic capacity was not substantially reduced by PAK1 or PAK2 deletion, possibly due to partial redundancy in PAK1/PAK2 regulatory roles or to activation of other compensatory mechanisms. Reconstitution of minimal motility system based on Spiroplasma swimming by expressing two bacterial actins in synthetic minimal bacterium Motility is one of the most important features of life, but its evolutionary origin remains unknown. In this study, we focused on Spiroplasma, commensal, or parasitic bacteria. They swim by switching the helicity of a ribbon-like cytoskeleton that comprises six proteins, each of which evolved from a nucleosidase and bacterial actin called MreB. We expressed these proteins in a synthetic, non-motile minimal bacterium, JCVI-syn3.0B, whose reduced genome was computer-designed and chemically synthesized. The synthetic bacterium exhibited swimming motility with features characteristic of Spiroplasma swimming. Moreover, some combinations of the two proteins produced a helical cell shape and swimming, suggesting that the swimming originated from the differentiation and coupling of bacterial actins, and we also obtained a minimal system for motility of the synthetic bacterium.

One-Sentence SummaryThe minimal system comprised two bacterial actins that provided cell helicity and swimming to the synthetic minimal bacterium. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. Actomyosin activity-dependent apical targeting of Rab11 vesicles reinforces apical constriction During tissue morphogenesis, cell shape changes resulting from cell-generated forces often require active regulation of intracellular trafficking. How mechanical stimuli influence intracellular trafficking and how such regulation impacts tissue mechanics are not fully understood. In this study, we identify an actomyosin dependent mechanism involving Rab11- mediated trafficking in regulating apical constriction in the Drosophila embryo. During Drosophila mesoderm invagination, apical actin and Myosin II (actomyosin) contractility induces apical accumulation of Rab11-marked vesicle-like structures ("Rab11 vesicles") by promoting a directional bias in dynein mediated vesicle transport. At the apical domain, Rab11 vesicles are enriched near the adherens junctions (AJs). The apical accumulation of Rab11 vesicles is essential to prevent fragmented apical AJs, breaks in the supracellular actomyosin network and a reduction in the apical constriction rate. This Rab11 function is separate from its role in promoting apical Myosin II accumulation. These findings suggest a feedback mechanism between actomyosin activity and Rab11-mediated intracellular trafficking that regulates the force generation machinery during tissue folding. Creatine transporter deficient rat model show motor dysfunction, cerebellar alterations and muscle creatine deficiency without muscle atrophy Creatine (Cr) is a nitrogenous organic acid and plays roles as fast phosphate energy buffer to replenish ATP, osmolyte, antioxidant, neuromodulator, and as a compound with anabolic and ergogenic properties in muscle. Cr is taken from the diet or endogenously synthetized by the enzymes AGAT and GAMT, and specifically taken up by the transporter SLC6A8. Loss-of-function mutations in the genes encoding for the enzymes or the transporter cause Cerebral Creatine Deficiency Syndromes (CCDS). CCDS are characterized by brain Cr deficiency, intellectual disability with severe speech delay, behavioral troubles, epilepsy and motor dysfunction. Among CCDS, the X-linked Cr transporter deficiency (CTD) is the most prevalent with no efficient treatment so far. Different animal models of CTD show reduced brain Cr levels, cognitive deficiencies and together they cover other traits similar to those of patients. However, motor function was poorly explored in CTD models and some controversies in the phenotype exist in comparison with CTD patients. Our recently described Slc6a8Y389C knock-in (KI) rat model of CTD showed mild impaired motor function, morphological alterations in cerebellum, reduced muscular mass, Cr deficiency and increased guanidinoacetate content in muscle, although no consistent signs of muscle atrophy. Our results indicate that such motor dysfunction co-occurred with both nervous and muscle dysfunction, suggesting that muscle strength and performance as well as neuronal connectivity might be affected by this Cr deficiency in muscle and brain. Sequence-dependent model of genes with dual σ factor preference Escherichia coli uses {sigma} factors to quickly control large gene cohorts during stress conditions. While most of its genes respond to a single {sigma} factor, approximately 5% of them have dual {sigma} factor preference. The most common are those responsive to both {sigma}70, which controls housekeeping genes, and {sigma}38, which activates genes during stationary growth and stresses. Using RNA-seq and flow-cytometry measurements, we show that  {sigma}70+38 genes are nearly as upregulated in stationary growth as  {sigma}38 genes. Moreover, we find a clear quantitative relationship between their promoter sequence and their response strength to changes in {sigma}38 levels. We then propose and validate a sequence dependent model of {sigma}70+38 genes, with dual sensitivity to {sigma}38 and {sigma}70, that is applicable in the exponential and stationary growth phases, as well in the transient period in between. We further propose a general model, applicable to other stresses and {sigma} factor combinations. Given this, promoters controlling {sigma}70+38 genes (and variants) could become important building blocks of synthetic circuits with predictable, sequence-dependent sensitivity to transitions between the exponential and stationary growth phases. Non-targeted multimodal metabolomics and lipidomics data from ovine rumen fluid fractions BackgroundMetabolomics is a powerful and sensitive approach for investigating low molecular weight metabolite profiles present in rumen biofluids to identify potential roles of metabolites in rumen microbiome and understanding host-level regulatory mechanisms associated with animal production.

FindingsRumen samples from sheep grazed on a mixed ryegrass and clover pasture diet, were fractionated based on molecular weight and analysed using metabolomics and lipidomics to detect the small molecules present in ovine rumen fluid fractions.

ConclusionsUntargeted metabolomics provides a detailed snapshot of the ovine ruminal fluid metabolome that can be used as reference for future studies on ovine rumen fluid or as a comparator for other ruminant species. All data and metadata are available for download in the MetaboLights database. Spontaneous differentiation leads to emergence of hybrid cell states relate to poor prognosis in oral cancer PurposeCellular dynamics between phenotypically heterogeneous subpopulations of cancer cells within individual tumor is shown to be responsible for drug tolerance and overall poor prognosis; however, evidences were largely missing in oral cancer. Therefore, this study was undertaken to describe the dynamic phenotypic states among oral cancer cells, its influence on transcriptomic heterogeneity as well as its clinical significance.

Experimental DesignWe multiplexed phenotypic markers of putative oral-stem-like cancer cells (SLCCs) and characterized diversity among CD44-positive oral cancer cell subpopulations with respect to distinct expression of CD24 and aldehyde dehydrogenase (ALDH)-activity in multiple cell lines. Population trajectories were characterized by Markov model and cell states were defined based on the population specific RNA sequencing (RNAseq). ssGSEA based gene expression signatures were explore for prognostic significance.

ResultsOral cancer cells followed two distinct patterns of spontaneous repopulation dynamics with stochastic inter-conversions on  ALDH-axis, however a strict non-interconvertible transition on  CD24-axis. Interestingly, plastic  ALDH-axis was harnessed to enrich ALDHHigh subpopulations in response to Cisplatin treatment, to adapt a drug tolerant state. Phenotype-specific RNAseq results suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate states of stemness within the differentiating oral cancer cells. Further, survival analysis with each subpopulation-specific gene signature strongly suggested that the cell-state dynamics may act as possible mechanism to drive ITH, resulting in poor prognosis in patient.

ConclusionsOur results emphasized the prognostic power of the population dynamics in oral cancer. Importantly, we have described the phenotypic-composition of heterogeneous subpopulations critical for global tumor behaviour in oral cancer; which is a prerequisite knowledge important for precision treatment, however largely lacking for most solid tumors.

Graphical AbstractWe have characterized diversity among CD44-positive oral cancer cells lines with respect to distinct expression of CD24 and ALDH-activity. Subpopulations showed stochastic inter-conversions on ALDH-axis but a strict non-interconvertible transition of CD24Low to CD24High phenotype, even in response to chemotherapy-induced stress. RNAseq study suggested the organization of subpopulations into hierarchical structure with possible maintenance of intermediate alternate states of stemness within the differentiating oral cancer cells. The described population dynamics demonstrtaed influence tumor behaviour possibly by increasing intratumoral heterogeneity in aggressive oral tumors.



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org.highwire.dtl.DTLVardef@1dc6a7org.highwire.dtl.DTLVardef@dd0948org.highwire.dtl.DTLVardef@18c9603org.highwire.dtl.DTLVardef@cca8fb_HPS_FORMAT_FIGEXP  M_FIG C_FIG Translational relevanceIntratumoral heterogeneity (ITH) has been the clinically important factor, impacting aggressive cancer behaviour, drug tolerance and overall poor prognosis. Recent high-throughput studies have provided better cellular and molecular resolution of ITH; however, the prerequisite knowledge which defines the composition of subpopulations critical for global tumor behaviour is majorly lacking for most of the solid tumors. By combining phenotypic markers, we have defined four subpopulations of oral cancer cells. These subpopulations showed stochastic inter-conversions as well as a strict non-interconvertible transition among them to acheive heterogeneity. Importantly, transcriptional states of each subpopulations indicated a clinically relevant signatures for patient prognosis. Also, we observed interconversions of these subpopulations in response to Cisplatin to accumulate drug-tolerant cell state, as rapid and reversible strategy to respond to chemotherapy induced stress. Thus, the characteristics of described phenotypic subgroups may be translated to the clinic for estimating the extent of intratumoral heterogeneity in oral cancer patients. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. 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. PIN-FORMED1 polarity in the shoot is insensitive to the polarity of neighbouring cells In plants, epidermal cells are planar-polarized along an axis marked by the asymmetric localization patterns of several proteins including PIN-FORMED1 (PIN1), which facilitates the directional efflux of the plant hormone auxin to pattern phyllotaxis (Heisler et al., 2010; Mansfield et al., 2018; Reinhardt et al., 2003). While PIN1 polarity is known to be regulated non-cell autonomously via the MONOPTEROS (MP) transcription factor, how this occurs has not been determined (Bhatia et al., 2016). Here we use mosaic expression of the serine threonine kinase PINOID (PID) to test whether PIN1 polarizes according to the polarity of neighbouring cells. Our findings reveal that PIN1 is insensitive to the polarity of PIN1 in neighbouring cells arguing against auxin flux or extracellular auxin concentrations acting as a polarity cue, in contrast to previous model proposals (Abley et al., 2016; Stoma et al., 2008). Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. Synthetic Nanobody-Functionalized Nanoparticles for Accelerated Development of Rapid, Accessible Detection of Viral Antigens Successful control of emerging infectious diseases requires accelerated development of fast, affordable, and accessible assays to be widely implemented at a high frequency. Here we present a generalizable assay platform, nanobody-functionalized nanoparticles for rapid, electronic detection (Nano2RED), demonstrated in the detection of Ebola and COVID-19 antigens. To efficiently generate high-quality affinity reagents, synthetic nanobody co-binders and mono-binders with high affinity, specificity, and stability were selected by phage display screening of a vastly diverse, rationally randomized combinatorial library, bacterially expressed and site-specifically conjugated to gold nanoparticles (AuNPs) as multivalent in-solution sensors. Without requiring fluorescent labelling, washing, or enzymatic amplification, these AuNPs reliably transduce antigen binding signals upon mixing into physical AuNP aggregation and sedimentation processes, displaying antigen-dependent optical extinction readily detectable by spectrometry or simple electronic circuitry. With nanobodies against an Ebola virus secreted glycoprotein (sGP) and a SARS-CoV-2 spike protein receptor binding domain (RBD) as targets, Nano2RED showed a high sensitivity (limit of detection of [~]10 pg/mL for sGP and [~]40 pg/mL for RBD in diluted human serum), a high specificity, and a large dynamic range ([~]7 logs). Unlike conventional assays where slow mass transport for surface binding limits the assay time, Nano2RED features fast antigen diffusion at micrometer scale, and can be accelerated to deliver results within a few minutes. The rapid detection, low material cost (estimated < $0.01 per test), inexpensive and portable readout system (< $5 and < 100 cm3), and digital data output, make Nano2RED particularly suitable for screening of patient samples with simplified operation and accelerated data transmission. Our method is widely applicable for prototyping diagnostic assays for other antigens from new emerging viruses. 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.