Location and function of Plasmodium kinesins: key roles in parasite proliferation, polarity, and transmission Kinesins are microtubule-based motors important in cell division, motility, polarity, and intracellular transport in many eukaryotes. However, they are poorly studied in the divergent eukaryotic pathogens-Plasmodium spp., the causative agents of malaria, which manifest atypical aspects of cell division and plasticity of morphology throughout the lifecycle in both mammalian and mosquito hosts. Here we describe a genome-wide screen of Plasmodium kinesins, revealing diverse subcellular locations and functions in spindle assembly, axoneme formation and cell morphology. Surprisingly, only kinesin-13 is essential for growth in the mammalian host while the other eight kinesins are required during the proliferative and invasive stages of parasite transmission through the mosquito vector. In-depth analyses of kinesin-13 and kinesin-20 revealed functions in microtubule dynamics during apical cell polarity formation, spindle assembly, and axoneme biogenesis. These findings help us to understand the importance of microtubule motors and may be exploited to discover new therapeutic interventions against malaria.
WIN 55,212-2 shows anti-inflammatory and survival properties in human iPSC-derived cardiomyocytes infected with SARS-CoV-2 Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which can infect several organs, especially impacting respiratory capacity. Among the extrapulmonary manifestations of COVID-19 is myocardial injury, which is associated with a high risk of mortality. Myocardial injury, caused directly or indirectly by SARS-CoV-2 infection, can be triggered by inflammatory processes that cause damage to the heart tissue. Since one of the hallmarks of severe COVID-19 is the "cytokine storm", strategies to control inflammation caused by SARS-CoV-2 infection have been considered. Cannabinoids are known to have anti-inflammatory properties by negatively modulating the release of pro-inflammatory cytokines. Herein, we investigated the effects of the cannabinoid agonist WIN 55,212-2 (WIN) in human iPSC-derived cardiomyocytes (hiPSC-CMs) infected with SARS-CoV-2. WIN did not modify angiotensin-converting enzyme II protein levels, nor reduced viral infection and replication in hiPSC-CMs. On the other hand, WIN reduced the levels of interleukins 6, 8, 18 and tumor necrosis factor-alpha (TNF-) released by infected cells, and attenuated cytotoxic damage measured by the release of lactate dehydrogenase (LDH). Our findings suggest that cannabinoids should be further explored as a complementary therapeutic tool for reducing inflammation in COVID-19 patients.
Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Omicron BA.2 specifically evades broad sarbecovirus neutralizing antibodies Omicron sub-lineage BA.2 has rapidly surged globally, accounting for over 60% of recent SARS-CoV-2 infections. Newly acquired RBD mutations and high transmission advantage over BA.1 urge the investigation of BA.2s immune evasion capability. Here, we show that BA.2 causes strong neutralization resistance, comparable to BA.1, in vaccinated individuals plasma. However, BA.2 displays more severe antibody evasion in BA.1 convalescents, and most prominently, in vaccinated SARS convalescents plasma, suggesting a substantial antigenicity difference between BA.2 and BA.1. To specify, we determined the escaping mutation profiles1,2 of 714 SARS-CoV-2 RBD neutralizing antibodies, including 241 broad sarbecovirus neutralizing antibodies isolated from SARS convalescents, and measured their neutralization efficacy against BA.1, BA.1.1, BA.2. Importantly, BA.2 specifically induces large-scale escape of BA.1/BA.1.1-effective broad sarbecovirus neutralizing antibodies via novel mutations T376A, D405N, and R408S. These sites were highly conserved across sarbecoviruses, suggesting that Omicron BA.2 arose from immune pressure selection instead of zoonotic spillover. Moreover, BA.2 reduces the efficacy of S309 (Sotrovimab)3,4 and broad sarbecovirus neutralizing antibodies targeting the similar epitope region, including BD55-5840. Structural comparisons of BD55-5840 in complexes with BA.1 and BA.2 spike suggest that BA.2 could hinder antibody binding through S371F-induced N343-glycan displacement. Intriguingly, the absence of G446S mutation in BA.2 enabled a proportion of 440-449 linear epitope targeting antibodies to retain neutralizing efficacy, including COV2-2130 (Cilgavimab)5. Together, we showed that BA.2 exhibits distinct antigenicity compared to BA.1 and provided a comprehensive profile of SARS-CoV-2 antibody escaping mutations. Our study offers critical insights into the humoral immune evading mechanism of current and future variants. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. Gene structure-based homology search identifies highly divergent putative effector gene family Homology of highly divergent genes often cannot be determined from sequence similarity alone. For example, we recently identified in Hormaphis cornu a family of rapidly evolving bicycle genes, which encode novel proteins implicated as plant gall effectors. Sequence similarity search methods yielded few putative bicycle homologs in other species. Coding sequence-independent features of genes, such as intron-exon boundaries, often evolve more slowly than coding sequences, however, and can provide complementary evidence for homology. We found that a linear logistic regression classifier using only structural features of bicycle genes identified many putative bicycle homologs in other species. Independent evidence from sequence features and intron locations supported homology assignments. To test the potential roles of bicycle genes in other aphids, we sequenced the genome of a second gall- forming aphid, Tetraneura ulmi, and found that many bicycle genes are strongly expressed in the salivary glands of the gall forming foundress. In addition, bicycle genes are strongly overexpressed in the salivary glands of a non-gall forming aphid, Acyrthosiphon pisum, and in the non-gall forming generations of Hormaphis cornu. These observations suggest that Bicycle proteins may be used by multiple aphid species to manipulate plants in diverse ways. Incorporation of gene structural features into sequence search algorithms may aid identification of deeply divergent homologs, especially of rapidly evolving genes involved in host-parasite interactions. Elucidating Microscopic Events Driven by GTP Hydrolysis Reaction in Ras-GAP System with Semi-reactive Molecular Dynamics Simulation: Alternative Role of Phosphate Binding Loop as Mechanical Energy Storage ATPase and GTPase have been widely found as chemical energy-mechanical work transducers, whereas the physicochemical mechanisms are not satisfactorily understood. We addressed the problem by examining John Ross conjecture that repulsive Coulomb interaction between ADP/GDP and inorganic phosphate (Pi) does the mechanical work upon the system. We effectively simulated the consequence of GTP hydrolysis reaction in a complex system of Rat sarcoma (Ras) and GTPase activation protein (GAP) in the framework of classical molecular dynamics by switching force field parameters between the reactant and product systems. We then observed ca. 5 kcal/mol raise of potential energy about the phosphate-binding loop (P-loop) in Ras protein, indicating that the mechanical work generated via the GTP hydrolysis is converted into the local interaction energy and stored in the P-loop. Interestingly, this local energy storage in the P-loop depends on neither impulsive nor consecutive collisions of GDP and Pi with P-loop. Instead, GTP-GDP conversion itself does work on the Ras system, elevating the potential energy. These observations encourage us to challenge a conjecture previously given by Ross. We assert that triphosphate nucleotide hydrolyses do mechanical work by producing emergent steric interaction accompanied with relaxation, namely, a shift of biomolecular system to non-equilibrium state on the reshaped potential energy landscape. Recalling the universality of the P-loop motif among GTPases and ATPases, the observations that we obtained through this study would progress physicochemical understanding for the operating principles of GTP/ATP hydrolysis-driven biological nano-machines. Non-Newtonian Blood Rheology Impacts Left Atrial Stasis in Patient-Specific Simulations The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects can be subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered in calculating patient-specific blood stasis indices by computational fluid dynamics. Spatially explicit ecological modeling improves empirical characterization of dispersal Dispersal is a key ecological process, but remains difficult to measure. By recording numbers of dispersed individuals at different distances from the source one can acquire a dispersal gradient. Although dispersal gradients contain information on dispersal, they are influenced by the spatial extent of the source. How can we separate the two contributions to extract knowledge on dispersal?

One could use a small, point-like source for which a dispersal gradient represents a dispersal kernel, which quantifies the probability of an individual dispersal event from a source to a destination point. However, the validity of this approximation cannot be established before conducting measurements.

We formulated a theory that incorporates the spatial extent of sources to estimate dispersal kernels from dispersal gradients. We re-analyzed published dispersal gradients for three major plant pathogens. We also demonstrated using simulations that this approach provides more accurate estimates of dispersal kernels across biologically plausible scenarios. We concluded that the three plant pathogens disperse over substantially shorter distances compared to conventional estimates. Using this method, a significant proportion of published dispersal gradients can be re-analyzed to improve our knowledge about spatial scales of dispersal. Thus, our results can boost progress in characterization of dispersal across taxa. The first multi-tissue diel genome-scale metabolic model of a woody plant highlights the suberin biosynthesis pathways in Quercus suber In the last decade, genome-scale metabolic models have been increasingly used to study plant metabolic behavior at the tissue and multi-tissue level under different environmental conditions. Quercus suber, also known as the cork oak tree, is one of the most important forest communities of the Mediterranean/Iberian region. In this work, we present the genome-scale metabolic model of the Q. suber (iEC7871), the first of a woody plant. The metabolic model comprises 7871 genes, 6231 reactions, and 6481 metabolites across eight compartments. Transcriptomics data was integrated into the model to obtain tissue-specific models for the leaf, inner bark, and phellogen, with specific biomass compositions. The tissue-specific models were merged into a diel multi-tissue metabolic model to predict interactions among the three tissues at the light and dark phases. The metabolic models were also used to analyze the pathways associated with the synthesis of suberin monomers. Nevertheless, the models developed in this work can provide insights into other aspects of the metabolism of Q. suber, such as its secondary metabolism and cork formation. Small extracellular vesicles from young mice prevent frailty, improve healthspan and decrease epigenetic age in old mice. Aging is associated with an increased risk of frailty, disability, comorbidities, institutionalization, falls, fractures, hospitalization, and mortality. Searching for strategies to delay the degenerative changes associated with aging and frailty is interesting. We treated old animals intravenously with small extracellular vesicles (sEVs) derived from adipose mesenchymal stem cells (ADSCs) of young animals, and we found an improvement of several functional parameters usually altered with aging, such as motor coordination, grip strength, fatigue resistance, fur regeneration, and renal function. Frailty index analysis showed that 40% of old control mice were frail, whereas none of the old ADSCs-sEVs treated mice were. Molecular and structural benefits in muscle and kidney accompanied this functional improvement. ADSCs-sEVs induced pro-regenerative effects and a decrease in oxidative stress, inflammation, and senescence markers. Moreover, predicted epigenetic age was lower in tissues of old mice treated with ADSCs-sEVs and their metabolome changed to a youth-like pattern. Finally, we gained some insight into the miRNAs contained in sEVs that might be, at least in part, responsible for the effects observed. We propose that young sEVs treatment can be beneficial against frailty and therefore can promote healthy aging. Dosage sensitivity in Pumilio1-associated diseases involves two distinct mechanisms Mutations in the RNA-binding protein (RBP) Pumilio1 (PUM1) can cause dramatically different phenotypes. Mild mutations that reduce PUM1 levels by 25% lead to a mild, adult-onset ataxia, whereas more severe mutations that reduce PUM1 levels 40-60% produce an infantile syndrome involving multiple developmental delays and seizures. Why this difference in expression should cause such different phenotypes has been unclear; known PUM1 targets are de-repressed to equal degrees in both diseases. We therefore sought to identify PUM1s protein partners in the murine brain. We identified a number of putative interactors involved in different aspects of RNA metabolism such as silencing, alternative splicing, and polyadenylation. We find that PUM1 haploinsufficiency alters the stability of several interactors and disrupts the regulation of targets of those interactors, whereas mild PUM1 loss only de-represses PUM1-specific targets. We validated these phenomena in patient-derived cell lines and show that normalizing PUM1 levels rescues the levels of interactors and their targets. We therefore propose that dosage sensitivity does not necessarily reflect a linear change in levels but can involve distinct mechanisms. Studying the interactors of RBPs in vivo will be necessary to understand their functions in neurological diseases. Marburg and Ebola virus infections elicit a complex, muted inflammatory state in bats The Marburg and Ebola filoviruses cause a severe, often fatal, disease in humans and nonhuman primates but have only subclinical effects in bats, including Egyptian rousettes, which are a natural reservoir of Marburg virus. A fundamental question is why these viruses are highly pathogenic in humans but fail to cause disease in bats. To understand how bats resist the disease caused by filoviruses, we infected one cohort of Egyptian rousette bats with Marburg virus and another cohort with Ebola virus and harvested multiple tissues for mRNA expression analysis. While virus transcripts were found primarily in the liver, Principal component analysis (PCA) revealed coordinated changes across multiple tissues. Gene signatures in kidney and liver pointed at induction of vasodilation, reduction of coagulation and changes in the regulation of iron metabolism. Signatures of immune response detected in spleen and liver indicated a robust anti-inflammatory state signified by macrophages in the M2 state and an active T cell response. Many of the responsive genes were found to be evolutionarily divergent, providing a framework for understanding the differences in outcomes of filovirus infections between bats and humans. In this study, we outline multiple interconnected pathways that respond to infection by MARV and EBOV, providing insights into the complexity of the mechanisms that enable bats to resist the disease caused by filoviral infections. The results have the potential to aid in the development of new strategies to effectively mitigate and treat the disease caused by these viruses in humans. Induction of exaggerated cytokine production in human peripheral blood mononuclear cells by a recombinant SARS-CoV-2 spike glycoprotein S1 and its inhibition by dexamethasone An understanding of the pathological inflammatory mechanisms involved in SARS-CoV-2 virus infection is necessary in order to discover new molecular pharmacological targets for SARS-CoV-2 cytokine storm. In this study, the effects of a recombinant SARS-CoV-2 spike glycoprotein S1 was investigated in human peripheral blood mononuclear cells (PBMCs). Stimulation of PBMCs with spike glycoprotein S1 (100 ng/mL) resulted in significant elevation in the production of TNF, IL-6, IL-1{beta} and IL-8. However, pre-treatment with dexamethasone (100 nM) caused significant reduction in the release of these cytokines. Further experiments revealed that S1 stimulation of PBMCs increased phosphorylation of NF-{kappa}B p65 and I{kappa}B, and I{kappa}B degradation. DNA binding of NF-{kappa}B p65 was also significantly increased following stimulation with spike glycoprotein S1. Treatment of PBMCs with dexamethasone (100 nM) or BAY11-7082 (1 {micro}M) resulted in inhibition of spike glycoprotein S1-induced NF-{kappa}B activation. Activation of p38 MAPK by S1 was blocked in the presence of dexamethasone and SKF 86002. CRID3, but not dexamethasone pre-treatment produced significant inhibition of S1-induced activation of NLRP3/caspase-1. Further experiments revealed that S1-induced increase in the production of TNF, IL-6, IL-1{beta} and IL-8 was reduced in the presence of BAY11-7082 and SKF 86002, while CRID3 pre-treatment resulted in the reduction of IL-1{beta} production. These results suggest that SARS-CoV-2 spike glycoprotein S1 stimulated PBMCs to release pro-inflammatory cytokines through mechanisms involving activation of NF-{kappa}B, p38 MAPK and NLRP3 inflammasome. It is proposed that the clinical benefits of dexamethasone in COVID-19 is possibly due to its anti-inflammatory activity in reducing SARS-CoV-2 cytokine storm. 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. "Adopt a Microorganism" methodology enhances the discourse richness of high school students in both hybrid learning and remote education 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. Chromatin-contact atlas reveals disorder-mediated protein interactions and moonlighting chromatin-associated RBPs RNA-binding proteins (RBPs) play diverse roles in regulating co-transcriptional RNA-processing and chromatin functions, but our knowledge of the repertoire of chromatin-associated RBPs (caRBPs) and their interactions with chromatin remains limited. Here, we developed SPACE (Silica Particle Assisted Chromatin Enrichment) to isolate global and regional chromatin components with high specificity and sensitivity, and SPACEmap to identify the chromatin-contact regions in proteins. Applied to mouse embryonic stem cells, SPACE identified 1,459 chromatin-associated proteins, [~]48% of which are annotated as RBPs, indicating their dual roles in chromatin and RNA-binding. Additionally, SPACEmap stringently verified chromatin-binding of 404 RBPs and identified their chromatin-contact regions. Notably, SPACEmap showed that about half of the caRBPs bind to chromatin by intrinsically disordered regions (IDRs). Studying SPACE and total proteome dynamics from mES cells grown in 2iL and serum medium indicates significant correlation (R = 0.62). One of the most dynamic caRBPs is Dazl, which we find co-localized with PRC2 at transcription start sites of genes that are distinct from Dazl mRNA binding. Dazl and other PRC2-colocalised caRBPs are rich in intrinsically disordered regions (IDRs), which could contribute to the formation and regulation of phase-separated PRC condensates. Together, our approach provides an unprecedented insight into IDR-mediated interactions and caRBPs with moonlighting functions in native chromatin. Directed functional and structural connectivity in a large-scale model for the mouse cortex AO_SCPLOWBSTRACTC_SCPLOWInferring the structural connectivity from electrophysiological measurements is a fundamental challenge in systems neuroscience. Directed functional connectivity measures, such as the Generalized Partial Directed Coherence (GPDC), provide estimates of the causal influence between areas. However, the relation between causality estimates and structural connectivity is still not clear. We analyzed this problem by evaluating the effectiveness of GPDC to estimate the connectivity of a ground-truth, data-constrained computational model of a large-scale network model of the mouse cortex. The model contains 19 cortical areas comprised of spiking neurons, with areas connected by long-range projections with weights obtained from a tract-tracing cortical connectome. We show that GPDC values provide a reasonable estimate of structural connectivity, with an average Pearson correlation over simulations of 0.74. Moreover, even in a typical electrophysiological recording scenario containing five areas, the mean correlation was above 0.6. These results suggest that it may be possible to empirically estimate structural connectivity from functional connectivity even when detailed whole-brain recordings are not achievable. Feed efficiency of lactating Holstein cows was not as repeatable across diets as within diet over subsequent lactation stages BackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet-low fibre (diet S+F-), then switched over to a low starch diet-high fibre (diet S-F+). To know if diet affect feed efficiency, we compared the ability of feed efficiency to be maintained within a diet over subsequent lactation stages, known as repeatability of feed efficiency, with its ability to be maintained across diets, known as reproducibility of feed efficiency. To do so we used two indicators: the estimation of the error of repeatability/reproducibility, which is commonly used in metrology, and the coefficient of correlation of concordance (CCC), which is used in biology. The effect of diet change could also lead to a change in cows sorting behaviour which could potentially affect feed efficiency if for example the most efficient cows select more concentrate than the least efficient. We therefore analysed the relationship between the differences in individual feed refusals composition and the differences in feed efficiency. To do so, the composition of each feed refusal was described with its near infra-red (NIR) spectroscopy and was performed on each individual feed ingredient, diet and refusals and used as composition variable. The variability of the NIR spectra of the refusals was described with its principal components thanks to a principal component analysis (PCA). The Pearson correlation was estimated to check the relationship between feed efficiency and refusals composition, i.e. sorting behaviour.

ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet, which were 2.01 MJ/d within diet S-F+ and 2.40 MJ/d within diet S+F-. The CCC was 0.64 between feed efficiency estimated within diet S+F- and feed efficiency estimated within diet S-F+. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet S+F- and 0.85 within diet S-F+). Feed efficiency was poorly correlated to the first two principal components, which explained 90% of the total variability of the NIR spectra of the individual refusals. This suggests that feed sorting behaviour did not explain differences in feed efficiency.

ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cows ranking for feed efficiency was not significantly affected by diet change. This loss in repeatability across diets could be due to a more pronounced feed sorting subsequent to the change in diet composition. However, the differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the S+F- diet nor with the S-F+ diet. Those results have to be confirmed on diets having different forage to concentrate ratios to ensure that the least and most efficient cows will not change. Combinatorial drug-microenvironment interaction mapping reveals cell-extrinsic drug resistance mechanisms and clinically relevant patient subgroups in CLL The tumour microenvironment and genetic alterations collectively influence drug efficacy in cancer, but current evidence is limited to small scale studies and systematic analyses are lacking. We chose Chronic Lymphocytic Leukaemia (CLL), the most common leukaemia in adults, as a model disease to study this complex interplay systematically. We performed a combinatorial assay using 12 drugs individually co-applied with each of 17 microenvironmental stimuli in 192 primary CLL samples, generating a comprehensive map of drug-microenvironment interactions in CLL. This data was combined with whole-exome sequencing, DNA-methylation, RNA-sequencing and copy number variant annotation. Our assay identified four distinct CLL subgroups that differed in their responses to the panel of microenvironmental stimuli. These subgroups were characterized by distinct clinical outcomes independently of known prognostic markers. We investigated the effect of CLL- specific recurrent genetic alterations on microenvironmental responses and identified trisomy 12 as an amplifier of multiple microenvironmental stimuli. We further quantified the impact of microenvironmental stimuli on drug response, confirmed known interactions such as Interleukin (IL) 4 mediated resistance to B cell receptor (BCR) inhibitors, and identified new interactions such as Interferon-{gamma} induced resistance to BCR inhibitors. Finally, we identified interactions which were limited to genetic subgroups. Resistance to chemotherapeutics, such as Fludarabine, induced by Toll-Like Receptor (TLR) agonists could be observed in IGHV unmutated patient samples and IGHV mutated samples with trisomy 12. In-vivo relevance was investigated in CLL-infiltrated lymph nodes, which showed increased IL4 and TLR signalling activity compared to healthy samples (p<0.001). High IL4 activity in lymph nodes correlated with faster disease progression (p=0.038).

We provide a publicly available resource (www.dietrichlab.de/CLL_Microenvironment/) which uncovers tumour cell extrinsic influences on drug response and disease progression in CLL, and how these interactions are modulated by cell intrinsic molecular features. Extending Bayesian Elo-rating to quantify the steepness of dominance hierarchies The steepness of dominance hierarchies provides information about the degree of competition within animal social groups and is thus an important concept in socioecology. The currently most widely-used metrics to quantify steepness are based on Davids scores (DS) derived from dominance interaction networks. One serious drawback of these DS-based metrics is that they are biased, i.e., network density systematically decreases steepness values. Here, we provide a novel approach to estimate steepness based on Elo-ratings, implemented in a Bayesian framework (STEER: Steepness estimation with Elo-rating). Our new metric has two key advantages. First, STEER is unbiased, precise and more robust to data density than DS-based steepness. Second, it provides explicit probability distributions of the estimated steepness coefficient, which allows uncertainty assessment. In addition, it relies on the same underlying concept and is on the same scale as the original measure, and thus allows comparison to existing published results. We evaluate and validate performance of STEER by means of experimentation on empirical and artificial data sets and compare its performance to that of several other steepness estimators. Our results suggest that STEER provides a considerable improvement over existing methods to estimate dominance hierarchy steepness. We provide an R package EloSteepness to calculate the new steepness measure, and also show an example of using steepness in a comparative analysis. A revised view on the evolution of glutamine synthetase isoenzymes in plants Glutamine synthetase (GS) is a key enzyme responsible for the incorporation of inorganic nitrogen in the form of ammonium into the amino acid glutamine. The genes encoding GS are among the oldest existing genes in living organisms. In plants, two groups of functional GS enzymes are found: eubacterial GSIIb (GLN2) and eukaryotic GSIIe (GLN1/GS). Phylogenetic analyses have shown that the GLN2 group originated from bacteria following horizontal gene transfer. Only GLN1/GS genes are found in vascular plants, which suggests that they are involved in the final adaptation of plants to terrestrial life. The present phylogenetic study reclassifies the different GS of seed plants into three clusters: GS1a, GS1b and GS2. The presence of genes encoding GS2 has been expanded to Cycadopsida gymnosperms, which suggests the origin of this gene in a common ancestor of Cycadopsida, Ginkgoopsida and angiosperms. GS1a genes have been identified in all gymnosperms, basal angiosperms and some Magnoliidae species. Previous studies in conifers and the gene expression profiles obtained in ginkgo and magnolia in the present work could explain the absence of GS1a in more recent angiosperm species (e.g., monocots and eudicots) due to the redundant roles of GS1a and GS2 in photosynthetic cells. Altogether, the results provide a better understanding of the evolution of plant GS isoenzymes and their physiological roles, which is valuable for improving crop nitrogen use efficiency and productivity. Morphological aspects of opossum (Didelphis aurita) pancreas during intramarsupial development Functionalized nanostructured systems can be used for imaging and drug delivery for anti-tumor therapy, including breast tumors. This is a more efficient approach that offers reduced systemic side effects compared to conventional diagnostic and chemotherapy methods. Multifunctional nanoparticles are potential tools in the diagnosis, location tracing and kill tumor cells through a less invasive manner. Functionalized phosphate-based nanoparticles are capable of encapsulating, or may be associated, with fluorescent probes. In this study, we synthesize a nanoparticle phosphate-based composite (NPC) and functionalize it with poly-ethylene glycol (PEG), hyaluronic acid (HA), the fluorescent probe rhodamin 6G (R6G) and the antimitotic doxorubicin (DOX). We focused on targeting human breast cancer cells reporting the biological effects of functionalized NPC on them. NPC and NPC formulations containing PEG, HA, and R6G did not cause cell viability reduction on MCF-7 and MDA-MB-231 cell lines. The cellular internalization of NPC was quantified by real-time in vitro observation, and confirmed by electron microscopy techniques. Intracellular NPC distribution is detected in the cytoplasm and nucleus of tumor cells by confocal fluorescent images. The percent association of doxorubicin to NPC matrix was approximately 18% and NPC formulations associated with doxorubicin led to a significant reduction in cell viability in MDA-MB-231 and MCF-7 cells. This data suggest the potential use of NPC as a non-cytotoxic platform for association with functional ligands to selective targeting breast cancer cells. NPC use can be also explored in drug delivery to cancer cells. Development of a novel PROTAC using the nucleic acid aptamer as a targeting ligand for tumor-selective degradation of nucleolin PROteolysis TArgeting Chimeras (PROTACs) induce targeted protein degradation by hijacking the intracellular ubiquitin proteasome system, thus emerging as a new strategy for drug development. However, most PROTACs generated lack cell-type selectivity and have poorly soluble in water. To address this drawback, we developed a novel PROTAC ZL216 using aptamer AS1411 as a targeting ligand of nucleolin to conjugate with a small molecule ligand of E3 ligase VHL, which shows high aqueous solubility and serum stability. Based on the differential expression of nucleolin on the cell surface, ZL216 could bind to and internalize into breast cancer cells, but not normal breast cells. Furthermore, we revealed that ZL216 promoted the formation of a nucleolin-ZL216-VHL ternary complex in breast cancer cells and potently induced nucleolin degradation in vitro and in vivo. As a result, ZL216 inhibited the proliferation and migration of breast cancer cells. These studies demonstrate that in addition to peptides and small molecule compounds, nuclei acid aptamers can also be used to generate PROTACs, which broadens the toolbox constructing PROTACs and provides a promising strategy for development of tumor-selective PROTACs. Construction of a new chromosome-scale, long-read reference genome assembly for the Syrian hamster, Mesocricetus auratus BackgroundThe Syrian hamster (Mesocricetus auratus) has been suggested as a useful mammalian model for a variety of diseases and infections, including infection with respiratory viruses such as SARS-CoV-2. The MesAur1.0 genome assembly was generated in 2013 using whole-genome shotgun sequencing with short-read sequence data. Current more advanced sequencing technologies and assembly methods now permit the generation of near-complete genome assemblies with higher quality and greater continuity.

FindingsHere, we report an improved assembly of the M. auratus genome (BCM_Maur_2.0) using Oxford Nanopore Technologies long-read sequencing to produce a chromosome-scale assembly. The total length of the new assembly is 2.46 Gbp, similar to the 2.50 Gbp length of a previous assembly of this genome, MesAur1.0. BCM_Maur_2.0 exhibits significantly improved continuity with a scaffold N50 that is 6.7 times greater than MesAur1.0. Furthermore, 21,616 protein coding genes and 10,459 noncoding genes are annotated in BCM_Maur_2.0 compared to 20,495 protein coding genes and 4,168 noncoding genes in MesAur1.0. This new assembly also improves the unresolved regions as measured by nucleotide ambiguities, where approximately 17.11% of bases in MesAur1.0 were unresolved compared to BCM_Maur_2.0 in which the number of unresolved bases is reduced to 3.00%.

ConclusionsAccess to a more complete reference genome with improved accuracy and continuity will facilitate more detailed, comprehensive, and meaningful research results for a wide variety of future studies using Syrian hamsters as models. Bayesian Additive Regression Trees for Genotype by Environment Interaction Models We propose a new class of models for the estimation of genotype by environment (GxE) interactions in plant-based genetics. Our approach, named AMBARTI, uses semi-parametric Bayesian additive regression trees to accurately capture marginal genotypic and environment effects along with their interaction in a fully Bayesian model. We demonstrate that our approach is competitive or superior to similar models widely used in the literature via both simulation and a real world data set. Furthermore, we introduce new types of visualisation to properly assess both the marginal and interactive predictions from the model. An R package that implements our approach is available at https://github.com/ebprado/ambarti.