Single-nucleus RNA Sequencing and Spatial Transcriptomics Reveal the Immunological Microenvironment of Cervical Squamous Cell Carcinoma Effective treatment of advanced invasive cervical cancer remains challenging nowadays. Herein, single-nucleus RNA sequencing (snRNA-seq) and SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) technology are used to investigate the immunological microenvironment of cervical squamous cell carcinoma (CSCC), a major type of cervical cancers. The expression levels of most immune checkpoint genes in tumor and inflammation areas of CSCC were not significantly higher than those in the non-cancer samples except for LGALS9 and IDO1. Stronger signals of CD56+ NK cells and immature dendritic cells are found in the hypermetabolic tumor areas, while more eosinophils, immature B cells, and Treg cells are found in the hypometabolic tumor areas. Moreover, a cluster of cancer-associated fibroblasts (CAFs) are identified around some tumors, which highly expressed ACTA2, POSTN, ITGB4, and FAP. The CAFs might support the growth and metastasis of tumors by inhibiting lymphocyte infiltration and remodeling the tumor extracellular matrix. Furthermore, CAFs are associated with poorer survival probability in CSCC patients and might be present in a small fraction ([~]20%) of advanced cancer patients. Collectively, these findings might enhance understanding of the CSCC immunological microenvironment and shed some light on the treatment of advanced CSCC.
Decreased cell stiffness facilitates detachment and migration of breast cancer cells in 3D collagen matrices: An exploratory study BackgroundTumour-cell detachment is a critical early event in the metastatic cascade. However, the role of the cells mechanical properties in detachment and migration is not well understood. This exploratory study aimed to assess how intracellular stiffness changes these processes.

MethodsMDA-MB-231 cells were embedded as 10,000-cell spheroids in 2 and 4 mg/ml collagen matrices. Intracellular stiffness was assessed with mitochondria tracking microrheology of cells that migrated distances equivalent to four and six times the cell diameter (dC) from the spheroid and compared to cells at the spheroid surface (0dC), representing medium, high and no migration, respectively.

Results and discussionThe mitochondrial mean square displacement and intracellular stiffness decreased during detachment and migration for both collagen concentrations (i.e. rigidities). The mean square displacement of 4dC and 6dC cells was similar, whereas cell stiffness was lower for 4dC than for 6dC cells. With increasing matrix rigidity, the intracellular stiffness decreased for 0dC cells and did not change for 4dC and 6dC cells. It is proposed that decreased cell stiffness drives detachment and migration and increased matrix rigidity physically hinders migration, and cells need to become softer or remodel the environment to migrate. The independence of the stiffness of migrated cells from matrix rigidity suggests that cells remodel their environment through matrix proteins cleavage to migrate.

ConclusionsThe study revealed the collective effects of enhanced migratory conditions and increased matrix rigidity on the mechanical properties of the cells. The expression of matrix metalloproteinases and transforming growth factor {beta} and the role of cell volume on detachment and migration in matrices with varying pore sizes are proposed targets for further studies on metastatic cancer cells.
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. Using total RNA quality metrics for time since deposition estimates in degrading bloodstains Determining the time since deposition (TSD) of bloodstains would provide forensic scientists with critical information regarding the timeline of the events involving bloodshed. The physicochemical changes occurring to biomolecules as a bloodstain degrades can be used to approximate the TSD of bloodstains. Our study aims to quantify the timewise degradation trends and temperature dependence found in total RNA from bloodstains without the use of amplification, expanding the scope of the RNA TSD research which has previously targeted mRNA molecules. Whole bovine blood was stored in plastic microcentrifuge tubes at 21{degrees}C or 4{degrees}C and tested over different timepoints spanning one week. Nine RNA metrics were visually assessed and quantified using linear and mixed models; the RNA Integrity Number equivalent (RINe) and the DV200 demonstrated strong negative trends over time and statistical independence. The RINe model fit was high (R2 = 0.60), and while including the biological replicate as a random effect increased the fit for all RNA metrics, no significant differences were found between biological replicates stored at the same temperature for the RINe and DV200 metrics. Importantly, this suggests that these standardized metrics can likely be directly compared between scenarios and individuals, with DV200 having an inflection point at [~]28 hrs. This study provides a novel approach for blood TSD estimates, producing metrics that are not affected by inter-individual variation and improving our understanding of the rapid degradation occurring in bloodstains.

HIGHLIGHTSO_LIAmplification-free analysis of total RNA in degrading bloodstains.
C_LIO_LIShort-term RNA degradation assessment using high-resolution size measurements.
C_LIO_LITotal RNA quality and quantity metrics were assessed across a one-week.
C_LIO_LITotal RNA quality metrics demonstrated the strongest timewise trends.
C_LIO_LIBiological replicates produced similar results for RNA quality metrics.
C_LI A cell cycle-dependent GARP-like transcriptional repressor regulates the initiation of differentiation in Giardia lamblia Transcriptional regulation of differentiation is critical for parasitic pathogens to adapt to environmental changes and regulate transmission. In response to encystation stimuli, Giardia lamblia cells shift from G1+S phase of the cell cycle to G2+M. By 2-4 hours, cyst wall proteins are upregulated, indicating that key regulatory steps occur within the first four hours of encystation. However, all characterized transcription factors (TFs) in Giardia have only been investigated at later time points of encystation. How TFs initiate encystation and link it to the cell cycle remains enigmatic. Here, we systematically screened six putative early upregulated TFs for nuclear localization, established their dynamic expression profiles, and determined their functional role in regulating encystation. We found a critical repressor, GLP4 that increases rapidly after 30 min of encystation stimuli and downregulates encystation specific markers, including Cyst Wall Proteins (CWPs) and enzymes in the cyst N-acetyl galactosamine (GalNAc) pathway. Depletion of GLP4 increases cyst production. Importantly, we observe that G2+M cells exhibit higher levels of CWP1 resulting from the activation of MYB2, a TF previously linked to encystation in Giardia. GLP4 upregulation occurs in G1+S cells, suggesting a role in repressing MYB2 and encystation specific genes in the G1+S phase of the cell cycle. Furthermore, we demonstrate that depletion of GLP4 upregulates MYB2 and promotes encystation while overexpression of GLP4 downregulates MYB2 and represses encystation. Together, these results suggest that Giardia employs a dose-dependent transcriptional response that involves the cell cycle regulated repressor GLP4 to orchestrate MYB2 and entry into the encystation pathway.

ImportanceTransition between life cycle stages is a common feature among parasitic pathogens and its regulation must be optimized to balance persistence of infection with transmission. The early transcription factors (TFs) regulating commitment to differentiate are totally unknown in Giardia. In this work, we identified GLP4, a previously uncharacterized GARP-like TF, as an early-acting transcriptional repressor that inhibits G1+S cells from entering the encystation pathway. GLP4 is therefore a key regulator controlling the balance between proliferative growth and terminal differentiation into infective cysts. Severe COVID-19 shares a common neutrophil activation signature with other acute inflammatory states Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaky disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflamatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention. A vesicle microrheometer for high-throughput viscosity measurements of lipid and polymer membranes Viscosity is a key property of cell membranes that controls mobility of embedded proteins and membrane remodeling. Measuring it is challenging because existing approaches involve complex experimental designs and/or models, and the applicability of some is limited to specific systems and membrane compositions. As a result there is scarcity of data and the reported values for membrane viscosity vary by orders of magnitude for the same system. Here, we show how viscosity of bilayer membranes can be obtained from the transient deformation of giant unilamellar vesicles. The approach enables a non-invasive, probe-independent and high-throughput measurement of the viscosity of bilayers made of lipids or polymers with a wide range of compositions and phase state. Pure lipid and single-phase mixed bilayers are found to behave as Newtonian fluids with strain-rate independent viscosity, while phase-separated and diblock-copolymers systems exhibit shear-thinning in the explored range of strain rates 1-2000 s-1. The results also reveal that electrically polarized bilayers can be significantly more viscous than charge-neutral bilayers. These findings suggest that biomembrane viscosity is a dynamic property that can be actively modulated not only by composition but also by membrane polarization, e.g., as in action potentials. Placental uptake and metabolism of 25(OH)Vitamin D determines its activity within the fetoplacental unit Pregnancy 25-hydroxyvitamin D (25(OH)D) concentrations are associated with maternal and fetal health outcomes. Using physiological human placental perfusion and villous explants, we investigate the role of the placenta in regulating the relationships between maternal 25(OH)D and fetal physiology. We demonstrate active placental uptake of 25(OH)D3 by endocytosis, placental metabolism of 25(OH)D3 into 24,25-dihydroxyvitamin D3 and active 1,25-dihydroxyvitamin D [1,25(OH)2D3], with subsequent release of these metabolites into both the maternal and fetal circulations. Active placental transport of 25(OH)D3 and synthesis of 1,25(OH)2D3 demonstrate that fetal supply is dependent on placental function rather than simply the availability of maternal 25(OH)D3. We demonstrate that 25(OH)D3 exposure induces rapid effects on the placental transcriptome and proteome. These map to multiple pathways central to placental function and thereby fetal development, independent of vitamin D transfer. Our data suggest that the underlying epigenetic landscape helps dictate the transcriptional response to vitamin D treatment. This is the first quantitative study demonstrating vitamin D transfer and metabolism by the human placenta, with widespread effects on the placenta itself. These data demonstrate a complex interplay between vitamin D and the placenta and will inform future interventions using vitamin D to support fetal development and maternal adaptations to pregnancy. Inter-tissue convergence of gene expression during ageing suggests age-related loss of tissue and cellular identity Developmental trajectories of gene expression may reverse in their direction during ageing, a phenomenon previously linked to cellular identity loss. Our analysis of cerebral cortex, lung, liver and muscle transcriptomes of 16 mice, covering development and ageing intervals, revealed widespread but tissue-specific ageing-associated expression reversals. Cumulatively, these reversals create a unique phenomenon: mammalian tissue transcriptomes diverge from each other during postnatal development, but during ageing, they tend to converge towards similar expression levels, a process we term Divergence followed by Convergence, or DiCo. We found that DiCo was most prevalent among tissue-specific genes and associated with loss of tissue identity, which is confirmed using data from independent mouse and human datasets. Further, using publicly available single-cell transcriptome data, we showed that DiCo could be driven both by alterations in tissue cell type composition and also by cell-autonomous expression changes within particular cell types. Mitochondrial double-stranded RNAs as a pivotal mediator in the pathogenesis of Sjogrens syndrome ObjectiveSjogrens syndrome (SS) is a systemic autoimmune disease that targets the exocrine glands, resulting in impaired saliva and tear secretion. To date, type I interferons (I-IFNs) are increasingly recognized as pivotal mediators in SS, but their endogenous drivers have not been elucidated. This study investigates the role of mitochondrial double-stranded RNAs (mt-dsRNAs) in regulating I-IFN response in SS.

MethodsSaliva and tear from SS patients and controls (n=73 for saliva and n=16 for tear), the salivary glands of the SS-prone-non-obese-diabetic mouse, and primary human salivary glandular cells were screened for mt-dsRNAs by RT-qPCR. The human salivary cell line (NS-SV-AC) grown as three-dimensional spheroids were subject to dsRNA stress to measure mt-dsRNA induction and recapitulation of SS glandular inflammatory features. Acetylcholine, SS-IgG, upadacitinib (JAK1 inhibitor), or 2-C'-methyladenosine (mitochondrial transcription inhibitor) were applied to characterize the roles of mt-dsRNAs. To identify endogenous dsRNA-sensor and confirm the mitochondrial origin of cytoplasmic dsRNAs, the immunoprecipitation of dsRNAs was performed.

Resultsmt-dsRNAs were elevated in the SS specimens with salivary ND5 and tear CYTB1 being statistically associated with secretory dysfunction/inflammation and corneal/conjunctival damage, respectively. Stimulation of the spheroids with dsRNA stress of poly I:C induced mt-dsRNAs, p-PKR, and I-IFNS via the JAK1/STAT pathway whereas the inhibition of mt-RNA synthesis or JAK1 attenuated the glandular signature. The inhibitory effect of acetylcholine on mt-dsRNAs and I-IFNS induction was reversed by SS-IgG.

Conclusionmt-dsRNAs amplify the impact of dsRNA stress on SS glandular signatures in vitro, potentially propagating a pseudo-viral signal in the SS target tissue.

SummaryMitochondrial double-stranded RNA levels were elevated in the tear and saliva of SS patients, which was associated with secretory dysfunction and tissue inflammation. These RNAs amplified type I interferon signature as well as glandular phenotypes reported in SS. Inhibitors of mitochondrial RNA transcription or JAK1 in salivary gland acinar cell spheroids attenuated the mitochondrial RNA-mediated changes. Immunomodulatory Contribution of Mast Cells to the Regenerative Biomaterial Microenvironment Bioactive immunomodulatory biomaterials have shown promise for influencing the immune response to promote tissue repair and regeneration. Macrophages and T cells have been associated with this response; however, other immune cell types have been traditionally overlooked. In this study, we investigated the role of mast cells in the regulation of the immune response to decellularized biomaterial scaffolds using a subcutaneous implant model. In mast cell-deficient mice, there was dysregulation of the expected M1 to M2 macrophage transition typically induced by the biomaterial scaffold. Polarization progression deviated in a sex specific manner with an early transition to an M2 profile in female mice, while the male response was unable to properly transition past a pro-inflammatory M1 state. Both were reversed with adoptive mast cell transfer. Further investigation of the later stage immune response in male mice determined a greater sustained pro-inflammatory gene expression profile including the IL-1 cytokine family, IL-6, alarmins, and chemokines. These results highlight mast cells as another important cell type that influences the immune response to pro-regenerative biomaterials. Confronting population models with experimental microcosm data: from trajectory matching to state-space models O_LIPopulation and community ecology traditionally has a very strong theoretical foundation with well-known models, such as the logistic and its many variations, and many modification of the classical Lotka-Volterra predator-prey and interspecific competition models. More and more, these classical models are confronted to data via fitting to empirical time-series for purposes of projections or for estimating model parameters of interest. However, the interface between mathematical population or community models and data, provided by a statistical model, is far from trivial.
C_LIO_LIIn order to help empiricists, especially researchers working with experimental laboratory populations in micro- and mesocosms, make informed decisions, we here ask which error structure one should use when fitting classical deterministic ODE models to empirical data, from single species to community dynamics and trophic interactions. We use both realistically simulated data and empirical data from microcosms to answer this question in a Bayesian framework.
C_LIO_LIWe find that many model parameters can be estimated precisely with an appropriate choice of error structure using pure observation error or state-space models, if observation errors are not too high. However, Allee effect models are typically hard to identify and state-space models should be preferred with when model complexity increases.
C_LIO_LIOur work shows that, at least in the context of experimental laboratory populations, deterministic models can be used to describe stochastic population dynamics that include process variability and observation error. Also, many scenarios do not require a complex state-space model formulation and simpler trajectory matching is sufficient for accurate parameter estimates. Finally, we provide a comprehensive tutorial for fitting these models in R.
C_LI Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Genetic instability from a single S-phase after whole genome duplication Diploid and stable karyotypes are associated with health and fitness in animals. In contrast, whole genome duplications (WGDs) - doubling full chromosome content - are linked to genetic instability (GIN) and frequently found in human cancers 1-3. It has been established that WGDs fuel chromosome instability through abnormal mitosis 4-8, however, the immediate consequences of tetraploidy in the first interphase are not known. This is an essential question because single WGD events such as cytokinesis failure can promote tumorigenesis 9. Here, we found that newly born tetraploid human cells undergo high rates of DNA damage during DNA replication in the first S-phase. Using DNA combing and single cell sequencing, we show that DNA replication dynamics is perturbed, generating under- and over-replicated regions. Mechanistically, we found that these defects result from the lack of protein mass scaling up at the G1/S transition, which impairs the fidelity of DNA replication. This work shows that within a single interphase, unscheduled tetraploid cells can acquire highly abnormal karyotypes. These findings provide an explanation for the GIN landscape that favors tumorigenesis after tetraploidization. Ribosome actuator via the SpoT/ppGpp pathway to mitigate gene overexpression burden Gene overexpression causes a burden on ribosomes, which decreases the expression of other genes and growth rate. Here, we engineer a genetic ribosome actuator that increases gene expression rate and growth rate by over 150% and 80%, respectively. The actuator expresses the hydrolysis domain of the SpoT enzyme (SpoTH) in a bacterial strain with high basal levels of ppGpp, thus increasing ribosome availability. We use this actuator in a feedforward control arrangement, wherein SpoTH is co-expressed with a gene of interest (GOI). Without SpoTH co-expression, activation of the GOI decreases the expression of a constitutive gene and growth rate by over 80% and 40%, respectively. By contrast, with SpoTH co-expression, the ribosome binding site (RBS) of SpoTH can be tuned to achieve inappreciable change of either the expression of the constitutive gene or growth rate when the GOI is activated to the same level. We finally employ the actuator to keep growth rate constant while expressing dCas9 to a level that would otherwise decrease growth rate by more than 40% due to toxicity. This actuator will be relevant in applications where high cellular protein concentrations are desired without growth defects or global reduction of gene expression. Pulled Diversification Rates, Lineages-Through-Time Plots and Modern Macroevolutionary Modelling AO_SCPLOWBSTRACTC_SCPLOWEstimating time-dependent rates of speciation and extinction from dated phylogenetic trees of extant species (timetrees), and determining how and why they vary, is key to understanding how ecological and evolutionary processes shape biodiversity. Due to an increasing availability of phylogenetic trees, a growing number of process-based methods relying on the birth-death model have been developed in the last decade to address a variety of questions in macroevolution. However, this methodological progress has regularly been criticised such that one may wonder how reliable the estimations of speciation and extinction rates are. In particular, using lineages-through-time (LTT) plots, a recent study (Louca and Pennell, 2020) has shown that there are an infinite number of equally likely diversification scenarios that can generate any timetree. This has lead to questioning whether or not diversification rates should be estimated at all. Here we summarize, clarify, and highlight technical considerations on recent findings regarding the capacity of models to disentangle diversification histories. Using simulations we demonstrate the characteristics of newly-proposed "pulled rates" and their utility. We recognize that the recent findings are a step forward in understanding the behavior of macroevolutionary modelling, but they in no way suggest we should abandon diversification modelling altogether. On the contrary, the study of macroevolution using phylogenetic trees has never been more exciting and promising than today. We still face important limitations in regard to data availability and methodological shortcomings, but by acknowledging them we can better target our joint efforts as a scientific community. Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies of Serum N- and O-Glycopeptide Data Glycoproteome profiling (glycoproteomics) is a powerful yet analytically challenging research tool. The complex tandem mass spectra generated from glycopeptide mixtures require sophisticated analysis pipelines for structural determination. Diverse software aiding the process have appeared, but their relative performance remains untested. Conducted through the HUPO Human Proteome Project - Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates the performance of informatics solutions for system-wide glycopeptide analysis. Mass spectrometry-based glycoproteomics datasets from human serum were shared with all teams. The relative team performance for N- and O-glycopeptide data analysis was comprehensively established and validated through orthogonal performance tests. Excitingly, several high-performance glycoproteomics informatics solutions were identified. While the study illustrated that significant informatics challenges remain, as indicated by a high discordance between annotated glycopeptides, lists of high-confidence (consensus) glycopeptides were compiled from the standardised team reports. Deep analysis of the performance data revealed key performance-associated search variables and led to recommendations for improved "high coverage" and "high accuracy" glycoproteomics search strategies. This study concludes that diverse software for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies, and specifies key variables that may guide future software developments and assist informatics decision-making in glycoproteomics. A Eukaryotic Circuit for Secretion-coupled Cellular Autonomy Cancers represent complex autonomous robust systems, displaying interconnectivity with feedback control. Autonomous growth is fueled by a cancer cells ability to  secrete-and-sense growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giabg and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimuli-proportionate secretion. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy.

GRAPHIC ABSTRACT

O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/436048v3_ufig1.gif" ALT="Figure 1">
View larger version (51K):
org.highwire.dtl.DTLVardef@183ff5corg.highwire.dtl.DTLVardef@f21de7org.highwire.dtl.DTLVardef@1893683org.highwire.dtl.DTLVardef@159d966_HPS_FORMAT_FIGEXP  M_FIG C_FIG In BriefThis work delivers an experimentally validated dynamical systems model of the cooperativity between two distinct classes of biological switches in eukaryotic cells and reveals the basis of secretion-coupled cellular autonomy in cancer.

HIGHLIGHTSO_LIModeling and experimental approaches were used to dissect a coupled GTPase circuit
C_LIO_LICoupling enables closed loop feedback and mutual control of GTPases
C_LIO_LICoupling generates dose response alignment behavior of sensing and secretion.
C_LIO_LICoupling is critical for multiscale feedback control to achieve secretion-coupled autonomy.
C_LI 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. 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. Effects of substrate on shrimp growth, water quality and bacterial community in the biofloc system nursing Penaeus vannamei postlarvae This study aimed to investigate the effects of substrate on water quality, shrimp growth and bacterial community in the biofloc system with a salinity of 5{per thousand}. Two treatments, biofloc system with (sB) or without (nB) addition of elastic solid packing filler (nylon) as substrate, were set up. Penaeus vannamei postlarvae (PL, [~] stage 15) were stocked at a density of 4000 PL m-3 in each treatment with triplicates for a 28-days culture experiment, taking glucose as carbon source (C:N 15:1). Results showed that the survival rate (96.3{+/-}3.6%), FCR (0.76{+/-}0.06) and productivity (1.54{+/-}0.12 kg m-3) in sB treatment were significantly better than those in nB treatment (81.0{+/-}7.1%, 0.98{+/-}0.08 and 1.14{+/-}0.09 kg m-3, P<0.05). All water parameters were in the recommended ranges. Substrate showed significant effect on TAN, TSS, turbidity, biofloc volume, pH and carbonate alkalinity (P < 0.05). Actinobacteria (4.0-22.7%), Bacteroidetes (10.4-33.5%), Firmicutes (0.2-11.2%), Planctomycetes (4.0-14.9%) and Proteobacteria (29.4-59.0%) were the most dominant phyla for both treatments. However, the bacterial community in sB treatment showed to be significantly different from that in nB treatment (Jaccard distance 0.94{+/-}0.01, P=0.001). Substrate showed significant effects on Shannon, Heip, Pielou and Simpson index, as well as relative abundances of Actinobacteria, Bacteroidetes and Planctomycetes (P < 0.05). The results suggested that addition of substrate affected the shrimp growth, water quality and bacterial community in the biofloc system nursing P. vannamei PL with a 5{per thousand} salinity. A cell type-specific multiomics uncovers a guard cell-specific RAF15-SnRK2.6/OST1 kinase cascade Multicellular organisms such as plants contain different cell types with specialized functions. Analyzing the characteristics of each cell type reveals specific cell functions and enhances understanding of organization and function at the organismal level. Here we report a highly-sensitive and efficient cell type-specific multiomics pipeline, combining simplified flow cytometry-based cell sorting for fluorescent protoplasts and optimized nanoscale proteomics and metabolomics methods, which allow in-depth analysis of the proteomes and metabolomes of a particular cell type. Using this method, we quantitatively compared the proteomes and metabolomes of guard cells and mesophyll cells and revealed that the enrichment of signal transduction-related proteins enables guard cells to respond rapidly to various environmental stimuli. We uncovered a guard cell-specific kinase cascade whereby RAF15 and OST1 mediate ABA-induced stomatal closure. This pipeline can be applied to various cell types in plant or non-plant systems to learn how cells function in highly organized multicellular organisms. Conformist social learning leads to self-organised prevention against adverse bias in risky decision making Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. SARS-CoV-2 Alpha, Beta and Delta variants display enhanced Spike-mediated Syncytia Formation Severe COVID-19 is characterized by lung abnormalities, including the presence of syncytial pneumocytes. Syncytia form when SARS-CoV-2 spike protein expressed on the surface of infected cells interacts with the ACE2 receptor on neighbouring cells. The syncytia forming potential of spike variant proteins remain poorly characterized. Here, we first assessed Alpha and Beta spread and fusion in cell cultures. Alpha and Beta replicated similarly to D614G reference strain in Vero, Caco-2, Calu-3 and primary airway cells. However, Alpha and Beta formed larger and more numerous syncytia. Alpha, Beta and D614G fusion was similarly inhibited by interferon induced transmembrane proteins (IFITMs). Individual mutations present in Alpha and Beta spikes differentially modified fusogenicity, binding to ACE2 and recognition by monoclonal antibodies. We further show that Delta spike also triggers faster fusion relative to D614G. Thus, SARS-CoV-2 emerging variants display enhanced syncytia formation.

SynopsisThe Spike protein of the novel SARS-CoV-2 variants are comparative more fusogenic than the earlier strains. The mutations in the variant spike protein differential modulate syncytia formation, ACE2 binding, and antibody escape.

O_LIThe spike protein of Alpha, Beta and Delta, in the absence of other viral proteins, induce more syncytia than D614G
C_LIO_LIThe ACE2 affinity of the variant spike proteins correlates to their fusogenicity
C_LIO_LIVariant associated mutations P681H, D1118H, and D215G augment cell-cell fusion, while antibody escape mutation E484K, K417N and {Delta}242-244 hamper it.
C_LIO_LIVariant spike-mediated syncytia formation is effectively restricted by IFITMs
C_LI Accommodating site variation in neuroimaging data using normative and hierarchical Bayesian models AO_SCPLOWBSTRACTC_SCPLOWThe potential of normative modeling to make individualized predictions from neuroimaging data has enabled inferences that go beyond the case-control approach. However, site effects are often confounded with variables of interest in a complex manner and can bias estimates of normative models, which has impeded the application of normative models to large multi-site neuroimaging data sets. In this study, we suggest accommodating for these site effects by including them as random effects in a hierarchical Bayesian model. We compared the performance of a linear and a non-linear hierarchical Bayesian model in modeling the effect of age on cortical thickness. We used data of 570 healthy individuals from the ABIDE (autism brain imaging data exchange) data set in our experiments. In addition, we used data from individuals with autism to test whether our models are able to retain clinically useful information while removing site effects. We compared the proposed single stage hierarchical Bayesian method to several harmonization techniques commonly used to deal with additive and multiplicative site effects using a two stage regression, including regressing out site and harmonizing for site with ComBat, both with and without explicitly preserving variance related to age and sex as biological variation of interest. In addition, we made predictions from raw data, in which site has not been accommodated for. The proposed hierarchical Bayesian method showed the best predictive performance according to multiple metrics. Beyond that, the resulting z-scores showed little to no residual site effects, yet still retained clinically useful information. In contrast, performance was particularly poor for the regression model and the ComBat model in which age and sex were not explicitly modeled. In all two stage harmonization models, predictions were poorly scaled, suffering from a loss of more than 90 % of the original variance. Our results show the value of hierarchical Bayesian regression methods for accommodating site variation in neuroimaging data, which provides an alternative to harmonization techniques. While the approach we propose may have broad utility, our approach is particularly well suited to normative modelling where the primary interest is in accurate modelling of inter-subject variation and statistical quantification of deviations from a reference model.

1 HighlightsO_LIDevelopment and presentation of normative modeling approach based on hierarchical Bayesian modeling that can be applied to large multi-site neuroimaging data sets.
C_LIO_LIComparison of performance of Hierarchical Bayesian model including site as predictor to several common ways to harmonize for multi-site effects.
C_LIO_LIPresentation of normative modeling as site correction tool.
C_LI MorphoHub: A Platform for Petabyte-Scale Multi-Morphometry Generation Recent advances in neuroscience make the extraction of full neuronal morphology at whole brain dataset available. To produce quality morphometry at large scale, it is highly desirable but extremely challenging to efficiently handle petabyte-scale high-resolution whole brain imaging database. Here, we developed a multi-level method to produce high quality somatic, dendritic, axonal, and potential synaptic morphometry, which was made possible by utilizing necessary petabyte hardware and software platform to optimize both the data and workflow management. Our method also boosts data sharing and remote collaborative validation. We highlight a petabyte application dataset involving 62 whole mouse brains, from which we identified 50,233 somata of individual neurons, profiled the dendrites of 11,322 neurons, reconstructed the full 3-D morphology of more than one thousand neurons including their dendrites and full axons, and detected million scale putative synaptic sites derived from axonal boutons. Analysis and simulation of these data indicate the promise of this approach for modern large-scale morphology applications.