Within-host evolutionary dynamics of seasonal and pandemic human influenza A viruses in young children The evolution of influenza viruses is fundamentally shaped by within-host processes. However, the within-host evolutionary dynamics of influenza viruses remain incompletely understood, in part because most studies have focused on within-host virus diversity of infections in otherwise healthy adults based on single timepoint data. Here, we analysed the within-host evolution of 82 longitudinally-sampled individuals, mostly young children, infected with A/H3N2 or A/H1N1pdm09 viruses between 2007 and 2009. For A/H1N1pdm09 infections during the 2009 pandemic, nonsynonymous changes were common early in infection but decreased or remained constant throughout infection. For A/H3N2 viruses, early infection was dominated by purifying selection. However, as infections progressed, nonsynonymous variants increased in frequencies even though within-host virus titres decreased, leading to the maintenance of virus diversity via mutation-selection balance. Our findings suggest that this maintenance of genetic diversity in these children combined with their longer duration of infection may provide important opportunities for within-host virus evolution.
Phylogenetic and population structure analyses uncover pervasive misclassification and help assessing the biosafety of Pseudomonas alloputida for biotechnological applications The Pseudomonas putida group comprises strains with biotechnological and clinical relevance. P. alloputida was proposed as a new species and highlighted the misclassification of P. putida. Nevertheless, the population structure of P. alloputida remained unexplored. We retrieved 11,025 Pseudomonas genomes and used P. alloputida Kh7T to delineate the species. The P. alloputida population structure comprises at least 7 clonal complexes (CCs). Clinical isolates are mainly found in CC4 and acquired resistance genes are present at low frequency in plasmids. Virulence profiles support the potential of CC7 members to outcompete other plant or human pathogens through a type VI secretion system. Finally, we found that horizontal gene transfer had an important role in shaping the ability of P. alloputida to bioremediate aromatic compounds such as toluene. Our results provide the grounds to understand P. alloputida genetic diversity and safety for environmental applications.
A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice Selective Src-Family B Kinase Inhibition Promotes Pulmonary Artery Endothelial Cell Dysfunction. Protein tyrosine kinases (PTKs) are essential for eukaryotic signaling. By targeting select PTKs, the group of drugs known as Tyrosine kinase inhibitors (TKIs) have proven to be effective for treating multiple diseases ranging from cancer to pulmonary fibrosis. However, some TKIs also paradoxically lead to the development of adverse conditions such as pulmonary arterial hypertension (PAH) by promoting endothelial cell dysfunction (ECD). We hypothesize that (1) subsets of PTKs may disproportionately modulate signaling pathways critical for endothelial homeostasis, such as BMPR2 signaling, and (2) inhibiting those pro-endothelial PTKs can promote the development of ECD. Herein we use an agnostic high-throughput siRNA screen to investigate how PTKs affect the canonical BMPR2 signaling pathway. Our major finding is that within the Src-family of non-receptor PTKs, the Src-B family promotes canonical BMPR2 signaling while the Src-A family suppresses it. We focus on two representative members of each family, Lck (for Src-B) and Fyn (for Src-A) that are the strongest activators or inhibitors of BMPR2 signaling in the screen. We confirm that Lck is expressed in the endothelium of pulmonary arteries and show that Lck knockout (termed si-Lck) in pulmonary artery endothelial cells (PAECs) suppresses canonical BMPR2 signaling while Fyn knockout (termed si-Fyn) promotes canonical BMPR2 signaling. Furthermore, Lck and Fyn are responsible for opposing functional behaviors in PAECs: si-Lck promotes apoptosis and interferes with tube formation while si-Fyn suppresses apoptosis and promotes tube formation. After analyzing the whole-transcriptome signature of si-Lck and si-Fyn PAECs we find that in addition to BMPR2 signaling suppression, si-Lck (and not si-Fyn) increases a broad number of ECD markers and increases canonical NF-{kappa}{beta} signaling. In summary, for the first time we show that Src-A and B Family of PTKs exert differential control over key endothelial cell signaling pathways resulting in direct phenotypic consequences. This knowledge may help to guide the design of more precise TKIs which avoid adverse drug reactions brought about through endothelial cell dysfunction. Virtual screening for small molecule pathway regulators by image profile matching Identifying chemical regulators of biological pathways is a time-consuming bottleneck in developing therapeutics and research compounds. Typically, thousands to millions of candidate small molecules are tested in target-based biochemical screens or phenotypic cell-based screens, both expensive experiments customized to each disease. Here, our uncustomized, virtual profile-based screening approach instead matches compounds to pathways based on phenotypic information in public cell image data, created using the Cell Painting assay. Our simple correlation-based computational strategy efficiently uncovered the expected small molecule regulators for 32% of positive control gene queries. In discovery mode, we identified compounds related to three of seven tested query genes, validated in subsequent gene-relevant assays. This image profile-based approach could replace many customized labor- and resource-intensive screens and accelerate the discovery of biologically and therapeutically useful compounds.

One sentence summaryIf a genetic perturbation impacts cell morphology, a computational query can reveal compounds whose morphology "matches". Force profile of the two-handed hardstyle kettlebell swing in novice older adults: an exploratory profile BackgroundUnderstanding the force profile of an exercise increases clinical confidence when assessing the benefits and potential risks of a prescribed exercise. This exploratory study presents the force profile of the hardstyle kettlebell swing in novice older adults and compares peak force with kettlebell deadlifts. These data will help inform healthcare providers and coaches who are considering prescribing kettlebell exercises for older adults.

MethodsThirty-five community-dwelling males and females (59-79 years) were recruited, from applicants to participate in the BELL trial. Two-handed hardstyle swings were performed with 8-16 kg. Deadlifts were performed with 8-24 kg and 8-32 kg for females and males, respectively. Ground reaction force was obtained from a floor-mounted force platform. Pairwise comparisons of peak force, forward force, rate of force development, swing cadence, sex, and kettlebell mass, were investigated for the kettlebell swing, with representative force-time curves described. Pairwise comparisons of peak force, sex and kettlebell mass were investigated for the deadlift, with comparisons of peak force, kettlebell mass, and sex, between swings and deadlifts.

ResultsFor kettlebells up to 16 kg, paired samples T-tests show a large exercise effect ({delta} > 1.4) with peak force higher for swings than deadlifts. Data shows: (i) higher peak force during swings than deadlifts ({delta} = 1.77), reaching 4.5 (1.0) N.kg-1, (ii) peak force during an 8 kg swing was greater than a 32kg deadlift, (iii) negligible difference in normalised peak force between males and females performing kettlebell swings, but a moderately large effect size during deadlifts (males > females, {delta} = 0.69), (iv) mean rate of force development of 19.9 (4.7) N.s-1.kg-1 with a very weak, positive correlation with kettlebell mass (y = 14.4 + 0.32x), and trivial effect of sex, (v) mean forward force equal to 5.5% of vertical force during swings, increasing from 3.8 (1.6) % with 8 kg to 7.1 (2.6) % with 16 kg.

ConclusionDuring kettlebell swings, there is negligible difference in normalised net peak force between novice males and females using the same absolute loads. Where ground reaction force is a therapeutic target, kettlebell swings with an 8 kg kettlebell could have similar effects to much heavier deadlifts (>24 kg). Kettlebell swings performed with lighter loads, could provider similar therapeutic value to much heavier deadlifts, and may be a more appealing, affordable, and convenient option for older adults. Micro topographical instruction of bacterial attachment, biofilm formation and in vivo host response Bio-instructive materials that prevent bacterial biofilm formation and drive an appropriate host immune response have the potential to significantly reduce the burden of medical device-associated infections. As bacterial surface attachment is sensitive to surface topography, we experimentally surveyed 2,176 combinatorially generated shapes using an unbiased high-throughput micro topographical polystyrene polymer chip screen. This identified topographies that reduced colonization in vitro by up to 15-fold compared with a flat surface for both motile and non-motile bacterial pathogens. Equivalent reductions were achieved on polyurethane, a polymer commonly used in medical devices. Using machine learning methods, a set of design rules based on generalisable topo-descriptors was established for predicting bacteria-resistant micro topographies. In a murine foreign body infection model, anti-attachment topographies were shown to be refractory to P. aeruginosa colonization and serendipitously, the fibrotic response to the implant was reduced, offering control of foreign body response using simple topographical patterning of non-eluting implants. 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. TFAP2 paralogs facilitate chromatin access for MITF at pigmentation genes but inhibit expression of cell-cell adhesion genes independently of MITF In developing melanocytes and in melanoma cells, multiple paralogs of the Activating-enhancer-binding Protein 2 family of transcription factors (TFAP2) contribute to expression of genes encoding pigmentation regulators, but their interaction with Microphthalmia transcription factor (MITF), a master regulator of these cells, is unclear. Supporting the model that Tfap2 facilitates MITFs ability to activate expression of pigmentation genes, single-cell seq analysis of zebrafish embryos revealed that pigmentation genes are only expressed in the subset of mitfa- expressing cells that also express Tfap2 paralogs. To test this model in SK-MEL-28 melanoma cells we deleted the two TFAP2 paralogs with highest expression, TFAP2A and TFAP2C, creating TFAP2 knockout (TFAP2-KO) cells. We then assessed gene expression, chromatin accessibility, binding of TFAP2A and of MITF, and the chromatin marks H3K27Ac and H3K27Me3 which are characteristic of active enhancers and silenced chromatin, respectively. Integrated analyses of these datasets indicate TFAP2 paralogs directly activate enhancers near genes enriched for roles in pigmentation and proliferation, and directly repress enhancers near genes enriched for roles in cell adhesion. Consistently, compared to WT cells, TFAP2-KO cells proliferate less and adhere to one another more. TFAP2 paralogs and MITF co-operatively activate a subset of enhancers, with the latter necessary for MITF binding and chromatin accessibility. By contrast, TFAP2 paralogs and MITF do not appear to co-operatively inhibit enhancers. These studies reveal a mechanism by which TFAP2 profoundly influences the set of genes activated by MITF, and thereby the phenotype of pigment cells and melanoma cells. Mitochondrial pyruvate supports lymphoma proliferation by fueling a non-canonical glutamine metabolism pathway The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner.

HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas.
C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated  -ketoglutarate production.
C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas.
C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment.
C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts.
C_LI Trade-offs in biosensor optimization for dynamic pathway engineering Recent progress in synthetic biology allows the construction of dynamic control circuits for metabolic engineering. This technology promises to overcome many challenges encountered in traditional pathway engineering, thanks to their ability to self-regulate gene expression in response to bioreactor perturbations. The central components in these control circuits are metabolite biosensors that read out pathway signals and actuate enzyme expression. However, the construction of metabolite biosensors is a major bottleneck for strain design, and a key challenge is to understand the relation between biosensor dose-response curves and pathway performance. Here we employ multiobjective optimization to quantify performance trade-offs that arise in the design and calibration of metabolite biosensors. Our approach reveals strategies for tuning dose-response curves along an optimal trade-off between production flux and the cost of an increased expression burden on the host. We explore properties of control architectures built in the literature, and identify their advantages and caveats in terms of performance and robustness to growth conditions and leaky promoters. We demonstrate the optimality of a control circuit for glucaric acid production in Escherichia coli, which has been shown to increase titer by 2.5-fold as compared to static designs. Our results lay the groundwork for the automated design of control circuits for pathway engineering, with applications in the food, energy and pharmaceutical sectors. Neuroinvasion and neurotropism by SARS-CoV-2 variants in the K18-hACE2 mouse Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) not only affects the respiratory tract but also causes neurological symptoms such as loss of smell and taste, headache, fatigue or severe cerebrovascular complications. Using transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) we investigated the spatiotemporal distribution and pathomorphological features in the CNS following intranasal infection with SARS-CoV-2 variants, also after prior influenza A virus infection. Apart from Omicron, we found all variants to frequently spread to and within the CNS. Infection was restricted to neurons and appeared to spread from the olfactory bulb mainly in basally orientated regions in the brain and into the spinal cord, independent of ACE2 expression and without evidence of neuronal cell death, axonal damage or demyelination. However, microglial activation, microgliosis and a mild macrophage and T cell dominated inflammatory response was consistently observed, accompanied by apoptotic death of endothelial, microglial and immune cells, without their apparent infection. Microgliosis and immune cell apoptosis indicate a potential role of microglia for pathogenesis and viral effect in COVID-19 and possible impairment of neurological functions, especially in long COVID. These data may also be informative for the selection of therapeutic candidates, and broadly support investigation of agents with adequate penetration into relevant regions of the CNS. Thirteen independent genetic loci associated with preserved processing speed in a study of cognitive resilience in 330,097 individuals in the UK Biobank Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. UK Biobank (UKB) does not have direct measurements of the same cognitive phenotype at distal timepoints. Therefore, we used number of education years (EY) as a proxy phenotype for past cognitive performance. Current cognitive performance was determined based on processing speed. This approach captured an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a GWAS-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience. Subtracting one from the other generated a GWAS of Resilience. Replication of this approach was shown using independent discovery and replication samples within UKB and the full UKB GWAS results show significant genetic correlation with a GWAS of cognitive change in the independent Health and Retirement Study (N=9,526; P=1.5x10-3). We found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and involvement of specific cell types, including GABAergic neurons (P=6.59x10-8) and glutamatergic neurons (P=6.98x10-6) in the cortex. Gene-set analyses implicated the biological process "neuron differentiation" (P=9.7x10-7) and the cellular component "synaptic part" (P=2.14x10-6). Mendelian randomization analysis showed a causative effect of white matter volume on cognitive resilience. These results enhance neurobiological understanding of resilience. A General Biphasic-Bodyweight Model for Scaling Basal Metabolic Rate, Glomerular Filtration Rate and Drug Clearance from Birth to Adulthood Understanding the maturation process of human physiology and metabolism has broad medical and pharmaceutical implications. Age and bodyweight are frequently considered as separate variables in modeling the dynamical changes of human organ functions and of drug clearance from birth to adulthood. The objective of this study is to propose a unified, continuous and bodyweight-only equation to quantify the changes of human basal metabolic rate (BMR), glomerular filtration rate (GFR) and drug clearance (CL) from infancy to adulthood. The BMR datasets were retrieved from a comprehensive historical database of male and female subjects (0.02 to 64 years). The CL datasets for 17 drugs and the GFR dataset were generated from age-incorporated maturation-and-growth models with reported parameter values. The model used in the simulation is independent of the proposed model. A statistical approach was used to simulate the model generated CL and GFR data for a hypothetical population with 26 age groups (ranging from 0 to 20 years). Besides, individual CL data for one drug, and sparse PBPK-modeled CL values for two drugs were also included for analysis. A 4-parameter, mixed-allometry equation with two power-law functions of bodyweight was proposed and evaluated as a general model using nonlinear regression and dimensionless analysis. All datasets universally reveal biphasic curves with two distinct linear segments on log-log plots. Compared with simple allometry, the biphasic model fits satisfactorily to all datasets (based on Akaikes Information Criterion and residual plots). The biphasic equation consists of two reciprocal allometric terms that asymptotically determine the overall curvature. The fitting results show a superlinear scaling phase (slope >1; ca. 1.5 - 3.5) below the characteristic bodyweight at the phase transition; and above which, a sublinear scaling phase (slope <1; ca. 0.5 - 0.7) is evident. The phase-transition bodyweight is ranging from 5 to 20 kg (corresponding to 0.5 - 9 years) and the mean value is around 10 kg ([~]2 years) for all data sets. The dimensionless analysis generalizes, and offers quantitative realization of, the maturation and growth process. In conclusion, the proposed mixed-allometry equation is a generic model that quantitatively describes the phase transition occurring in the human maturation process of BMR, GFR and drug CL. Antithrombin glycoforms are selectively physiosorbed on plasma extracellular vesicles Antithrombin (AT) is a glycoprotein produced by the liver and a principal antagonist of active clotting proteases. A deficit in AT function leads to AT qualitative deficiency, challenging to diagnose. Here we report that active AT may travel physiosorbed on the surface of plasma extracellular vesicles (EVs), contributing to form the "EV-protein corona". The corona is enriched in specific AT glycoforms, thus suggesting glycosylation to play a key role in AT partitioning between EVs and plasma. Differences in AT glycoform composition of the corona of EVs separated from plasma of healthy and AT qualitative deficiency-affected subjects were also noticed. This suggests deconstructing the plasma into its nanostructured components, as extracellular vesicles, could help to unravel pathophysiological mechanisms otherwise undiscovered. Deep inference of seabird dives from GPS-only records: performance and generalization properties AO_SCPLOWBSTRACTC_SCPLOWAt-sea behaviour of seabirds have received significant attention in ecology over the last decades as it is a key process in the ecology and fate of these populations. It is also, through the position of top predator that these species often occupy, a relevant and integrative indicator of the dynamics of the marine ecosystems they rely on. Seabird trajectories are recorded through the deployment of GPS, and a variety of statistical approaches have been tested to infer probable behaviours from these location data. Recently, deep learning tools have shown promising results for the segmentation and classification of animal behaviour from trajectory data. Yet, these approaches have not been widely used and investigation is still needed to identify optimal network architecture and to demonstrate their generalization properties. From a database of about 300 foraging trajectories derived from GPS data deployed simultaneously with pressure sensors for the identification of dives, this work has benchmarked deep neural network architectures trained in a supervised manner for the prediction of dives from trajectory data. It first confirms that deep learning allows better dive prediction than usual methods such as Hidden Markov Models. It also demonstrates the generalization properties of the trained networks for inferring dives distribution for seabirds from other colonies and ecosystems. In particular, convolutional networks trained on Peruvian boobies from a specific colony show great ability to predict dives of boobies from other colonies and from distinct ecosystems. We further investigate accross-species generalization using a transfer learning strategy known as  fine-tuning. Starting from a convolutional network pre-trained on Guanay cormorant data reduced by two the size of the dataset needed to accurately predict dives in a tropical booby from Brazil. We believe that the networks trained in this study will provide relevant starting point for future fine-tuning works for seabird trajectory segmentation. To make easier such applications, we share online the different models we trained on the considered datasets (https://github.com/AmedeeRoy/BirdDL/models).

Author SummaryOver the last decades, the use of miniaturized electronic devices enabled the tracking of many wide-ranging animal species. The deployment of GPS has notably informed on migratory, habitat and foraging strategies of numerous seabird species. A key challenge in movement ecology is to identify specific behavioural patterns (e.g. travelling, resting, foraging) through the observed movement data. In this work, we address the inference of seabird diving behaviour from GPS data using deep learning methods. We demonstrate the performance of deep networks to accurately identify movement patterns from GPS data over state-of-the-art tools, and we illustrate their great accross-species generalization properties (i.e. the ability to generalize prediction from one seabird species to aother). Our results further supports the relevance of deep learning schemes as  ready-to-use tools which could be used by ecologists to segmentate animal trajectories on new (small) datasets, including when these datasets do not include groundtruthed labelled data for a supervised training. Thermodynamics and kinetics of aggregation of flexible peripheral membrane proteins Biomembrane remodeling is essential for cellular trafficking, with membrane-binding peripheral proteins playing a key role in it. Significant membrane remodeling as in endo- and exocytosis is often due to aggregates of many proteins with direct or membrane-mediated interactions. Understanding this process via computer simulations is extremely challenging: protein-membrane systems involve time- and lengthscales that make atomistic simulations impractical, while most coarse-grained models fall short in resolving dynamics and physical effects of protein and membrane flexibility. Here, we develop a coarse-grained model of the bilayer membrane bestrewed with rotationally-symmetric flexible proteins, parametrized to reflect local curvatures and lateral dynamics of proteins. We investigate the kinetics, equilibrium distributions, and the free energy landscape governing the formation and break-up of protein clusters on the surface of the membrane. We demonstrate how the flexibility of the proteins as well as their surface concentration play deciding roles in highly selective macroscopic aggregation behavior. Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. Artificial seawater based long-term culture of colonial ascidians Tunicates are highly diverse marine invertebrate filter-feeders that are vertebrates closest relatives. These organisms, despite a drastically different body plan during their adulthood, have a tissue complexity related to that of vertebrates. Ascidians, which compose most of the Tunicata, are benthic sessile hermaphrodites that reproduce sexually through a motile tadpole larval stage. Over half of the known ascidians species are able to reproduce asexually by budding, typically leading to the formation of colonies where animals, called zooids, are interconnected through an external vascular system. In addition, colonial ascidians are established models for important biological processes including allorecognition, immunobiology, aging, angiogenesis and whole-body regeneration. However, the current paucity in breeding infrastructures limits the study of these animals to coastal regions.

To promote a wider scientific spreading and popularity of colonial ascidians, we have developed a flexible recirculating husbandry setup for their long-term in-lab culture. Our system is inspired both by the flow-through aquariums used by coastal ascidian labs, as well as by the recirculating in-lab systems used for zebrafish research. Our hybrid system thus combines colony breeding, water filtering and food culturing in a semi-automated system where specimens develop on hanging microscopy glass slides. Temperature, light/dark cycles, flow speed and feeding rates can be controlled independently in four different breeding environments to provide room for species-specific optimization as well as for running experiments. This setup is complemented with a quarantine for the acclimatization of wild isolates.

Herein we present our success in breeding Botrylloides diegensis, a species of colonial ascidians, for more than 3 years in recirculating artificial seawater over 600 km away from their natural habitat. We show that colonies adapt well to in-lab culturing provided that a suitable marine microbiome is present, and that a specific strain can be isolated, propagated and efficiently used for research over prolonged periods of time. The flexible and modular structure of our system can be scaled and adapted to the needs of specific species, such as Botryllus schlosseri, as well as of particular laboratory spaces. Overall, we show that Botrylloides diegensis can be proficiently bred in-land and suggest that our results can be extended to other species of colonial ascidians to promote research on these fascinating animals.

HighlightsO_LIFirst artificial seawater based recirculating aquaculture for colonial ascidians
C_LIO_LIOver 3 years of continuous breeding
C_LIO_LISemi-automated setup with minimized maintenance
C_LIO_LIGood biomass production for strain propagation
C_LIO_LI4 different culture conditions for optimized breeding for species of interest
C_LI The transmission of African Animal Trypanosomiasis (Nagana) in two districts in the forest zone of Ghana The African Animal Trypanosomiasis (nagana) is caused by several species of trypanosome species which results in significant clinical diseases. This consequently leads to huge economic losses. We carried out a cross-sectional survey to investigate the composition of vectors, parasite diversity and intensities in two districts in the Eastern region of Ghana. Cytochrome c oxidase subunit 1 (COI) and internal transcribed spacer (ITS1) dependent PCR assays identified tsetse fly species and trypanosome parasites circulating in the area. A total of 229 tsetse flies, 65 pigs and 20 were sampled. Female and male flies 155 (51.8%), 74 (32.3%) respectively were collected with biconical traps. The overall vector density of 4.3 flies/trap/day was observed. Typanosome prevalence of 58.9% (95% CI: 52.5-65.1), 46.2% (95% CI: 34.6-58.1) and 0.0% (95% CI: 0.0-16.1) in tsetse flies, pigs and cattle respectively were detected. Trypanosoma congolense was the predominant species with a prevalence of 80.7% (95% CI: 73.3-86.5) in flies and 60.0% (95% CI: 42.3-75.4). There was evidence of multiple trypanosome infection with T. congolense/T. simiae occurring highest with prevalence of 38.0% (95% CI: 30.7-46.9). The parasite prevalence in pigs across the communities was high with significant differences associated between locations (Chi2 = 28.06, 95% CI: 0.05-0.81, P=0.0009). Blood meal with flies revealed feeding on both domestic Sus scrofa domesticus (pig) and Phacochoerus africanus (warthog). Tsetse flies in this area remain highly infected with trypanosomes and continue to transmit the parasites to livestock and human populations in the communities. Juvenile Gouldian Finches (Erythrura gouldiae) form sibling sub-groups during social integration The formation of social relationships in complex groups is critical in shaping patterns of social organization and behavioral development. In many birds, young individuals remain dependent on their parents for extended periods but must abruptly transition to navigating interactions in the wider group after independence. While lack of social relationships during this period is detrimental in the development of later social skills, little is known about the social relationships juveniles form after independence in many bird species. In this study we describe patterns of social interactions in juvenile Gouldian Finches (Erythrura gouldiae) during transitions from family groups into flocks of unfamiliar individuals. A group of 20 juveniles from 4 families were introduced into two flocks. After introductions juveniles showed a gradient of approach rates with most approaches directed towards siblings, followed by juvenile peers, adult females, and lastly adult males. Significant preferences for siblings resulted in the emergence of sibling subgroups within the larger social network. This active self-assortment of siblings suggests that sibling sub-groups are an important bridge linking social connections within the family and the wider group. Such findings suggests that sibling relationships have a critical role in the socialization after independence, as well as structuring the social organization of Gouldian finch flocks. 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. A novel Fiji/ImageJ plugin for the rapid analysis of blebbing cells When confined, cells have recently been shown to undergo a phenotypic switch to what has been termed, fast amoeboid (leader bleb-based) migration. However, as this is a nascent area of research, few tools are available for the rapid analysis of cell behavior. Here, we demonstrate that a novel Fiji/ImageJ-based plugin, Analyze_Blebs, can be used to quickly obtain cell migration parameters and morphometrics from time lapse images. As validation, we show that Analyze_Blebs can detect significant differences in cell migration and morphometrics, such as the largest bleb size, upon introducing different live markers of F-actin, including F-tractin and LifeAct tagged with green and red fluorescent proteins. We also demonstrate, using flow cytometry, that live markers increase total levels of F-actin. Furthermore, that F-tractin increases cell stiffness, which was found to correlate with a decrease in migration, thus reaffirming the importance of cell mechanics as a determinant of Leader Bleb-Based Migration (LBBM).

Highlight summaryA new plugin, Analyze_Blebs, enables the rapid analysis of cell migration and morphometrics of fast amoeboid cells. Morphometrics combined with cell stiffness are found to be predictive of confined, fast amoeboid (leader bleb-based), migration. Quantifying the Morphology and Mechanisms of Cancer Progression in 3D in-vitro environments: Integrating Experiments and Multiscale Models Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale, spatiotemporal models of cancer growth using state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns. Its implementation enabled us to pursue two goals; first, the quantitative description of the morphology of cancer progression in 3D cultures, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration. We applied this framework to the study of the spatiotemporal progression of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and accumulation, as well as random motion during the examined time period of development. To our knowledge, this is the first time that a multiscale model is used to quantify the relationship between the spatial patterns and the underlying mechanisms of cancer growth in 3D environments. 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. Methylome dynamic upon proteasome inhibition by the Pseudomonas syringae virulence factor Syringolin A DNA methylation is an important epigenetic mark required for proper gene expression and silencing of transposable elements. DNA methylation patterns can be modified by environmental factors such as pathogen infection, where modification of DNA methylation can be associated with plant resistance. To counter the plant defense pathways, pathogens produce effectors molecule, several of which act as proteasome inhibitors. Here we investigated the effect of proteasome inhibition by the bacterial virulence factor Syringolin A on genome-wide DNA methylation. We show that Syringolin A treatment results in an increase of DNA methylation at centromeric and pericentromeric regions of Arabidopsis chromosomes. We identify several CHH DMRs that are enriched in the proximity of transcriptional start sites. Syringolin A treatment does not result in significant changes in small RNA composition. However, significant changes in genome transcriptional activity can be observed, including a strong upregulation of resistance genes that are located on chromosomal arms. We hypothesize that DNA methylation changes could be linked to the upregulation of some atypical members of the de novo DNA methylation pathway: AGO3, AGO9 and DRM1. Our data suggests that modification of genome-wide DNA methylation resulting from an inhibition of the proteasome by bacterial effectors could be part of a epi-genomic arms race against pathogens.