Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression level with cell volume While most genes expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiaes mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.
Unsupervised clustering analysis of SARS-Cov-2population structure reveals six major subtypes atearly stage across the world Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses.
Fine-scale adaptations to environmental variation and growth strategies drive phyllosphere Methylobacterium diversity. Methylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium was structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20 {degrees}C or 30 {degrees}C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100km; between forests) and small geographical scales (<1.2km within forests), among host tree species, and was dynamic over seasons. By measuring growth of 79 isolates at different temperature treatments, we observed contrasting growth performances, with strong lineage- and season-dependent variations in growth strategies. Finally, we documented a progressive replacement of lineages with a high-yield growth strategy typical of cooperative, structured communities, in favor of those characterized by rapid growth, resulting in convergence and homogenization of community structure at the end of the growing season. Together our results show how Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This works paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus.

ImportanceMethylobacterium is a bacterial group tied to plants. Despite its ubiquity and importance to their hosts, little is known about the processes driving Methylobacterium community dynamics. By combining traditional culture-dependent and independent (metabarcoding) approaches, we monitored Methylobacterium diversity in two temperate forests over a growing season. On the surface of tree leaves, we discovered remarkably diverse and dynamic Methylobacterium communities over short temporal (from June to October) and spatial scales (within 1.2 km). Because we cultured different subsets of Methylobacterium diversity depending on the temperature of incubation, we suspected that these dynamics partly reflected climatic adaptation. By culturing strains in lab conditions mimicking seasonal variations, we found that diversity and environmental variations were indeed good predictors of Methylobacterium growth performances. Our findings suggest that Methylobacterium community dynamics at the surface of tree leaves results from the succession of strains with contrasted growth strategies in response to environmental variations. Cytokinin oxidase/dehydrogenase family genes exhibit functional divergence and overlap in rice growth and development Cytokinins play key roles in plant growth and development; hence, cytokinin biosynthesis and degradation have been extensively studied. Cytokinin oxidase/dehydrogenases (CKXs) are a group of enzymes that regulate oxidative cleavage to maintain cytokinin homeostasis. In rice, 11 OsCKX genes have been identified to date; however, most of their functions remain unknown. Here, we comprehensively analyzed the expression patterns and functions of OsCKX genes. Using CRISPR/Cas9 technology, we constructed mutants of all OsCKX genes to determine the functions of OsCKXs in rice development. The results revealed that the single osckx and higher-order osckx4 osckx9 mutant lines showed functional overlap and subfunctionalization. Notably, the osckx1 osckx2 and osckx4 osckx9 double mutants displayed contrasting phenotypic changes in tiller number and panicle size compared to the wild type. Moreover, we identified several genes with significantly altered expression in osckx4 and osckx9 single and double mutant plants. Many differentially expressed genes were found to be associated with auxin and cytokinin pathways. Additionally, the cytokinins in osckx4 osckx9 mutants were increased compared to the wild type. Overall, our findings provide new insights into the functions of OsCKX genes in rice growth and may be used as a foundation for future studies aimed at improving rice yield. Key words: Cytokinin, expression pattern, OsCKX, panicle, phenotype, rice, tiller

HighlightThe osckx4 osckx9 double mutant had a significantly greater number of tillers, whereas the osckx1 osckx2 double mutant showed the opposite phenotypic change, compared to the wild type 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. The collapse of genetic incompatibilities in hybridizing populations Diverging species are often genetically incompatible upon hybridization. Such incompatibilities are considered important in keeping the integrity of species from the disruption of hybrids. However, recent empirical work has shown that not all incompatibilities are gene-flow-proof, and they can collapse due to continuing hybridization. Counterintuitively, many studies found that incompatible alleles are already segregating within species, whereas they should go extinct quickly in a randomly mating population. Due to the complexity of multilocus epistasis, few general principles explain behaviors of incompatibilities under gene flow both within and between species. In the current work, we argue that the redundancy of genetic mechanisms can robustly determine the dynamics of intrinsic incompatibilities under gene flow. While higher genetic redundancy decreases the stability of incompatibilities during hybridization, it also increases the tolerance of incompatibility polymorphism within each species. We treat two general classes of incompatibilities. In the redundant class, similar to the classical Dobzhansky-Muller system, the collapse is continuous and eventually approaches quasi-neutral polymorphism between broadly-sympatric species, often as a result of isolation-by-distance. In the non-redundant class, analogous to the shifting-balance process, incompatibilities collapse abruptly with spatial traveling waves. We obtained simulated and analytical results for several incompatibility models to demonstrate the differences between the two classes. As both redundant and non-redundant genetic mechanisms of incompatibilities are common, the proposed conceptual framework may help understand the abundance of incompatibilities in natural populations. A non-canonical convergence of carbohydrate and glutamine metabolism is required after metabolic rewiring in a solid environment 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 Cargo surface fluidity reduces inter-motor mechanical interference, promotes load-sharing and enhances run-lengths in an ATP dependent manner In cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of cytoskeletal filaments. How motors that typically mechanically interfere with each other, work as teams is unclear. Here we explored the possibility that purely physical mechanisms may potentially enhance teamwork, both at the single motor and cargo level. To explore these mechanisms, we developed a 3D dynamical simulation of cargo transport along microtubules by teams of canonically non-cooperative kinesin-1 motors. We accounted for cargo membrane fluidity by explicitly simulating the Brownian dynamics of motors on the cargo surface and considered both the load and ATP dependence of single motor functioning. We showed explicitly, for the first time, that surface fluidity leads to the reduction of negative mechanical interference between kinesins, enhancing load sharing thereby decreasing single motor off-rates and increasing processivity. Remarkably, we also showed that, independent of fluidity, increasing numbers of bound motors pull the cargo closer to the microtubule, increasing the on-rates of individual unbound motors, resulting in a cooperative increase in bound motor numbers that depends on 3D cargo geometry. At the cargo level, surface fluidity makes more motors available for binding, though this effect is significant only at low ATP or high motor density. Interestingly, we find that the fluidity induced reduction in mechanical interference dominates over the increased availability of motors for typical physiological and in vitro conditions, this allowing us to reconcile different experimental results in different regimes. Finally, we show that these effects can altogether result in enhanced mechanical efficiency and tunable cargo run-lengths for teams of molecular motors over physiological ranges of fluidity with implications for new experimental validation efforts, transport in vivo, artificial cargo design and multi-motor-driven mechanical processes in general.

Author summaryIn cells, multiple molecular motors work together as teams to carry cargoes such as vesicles and organelles over long distances to their destinations by stepping along a network of protein filaments. How do intrinsically non-cooperative motors function as teams within cells? In this paper, we show, using computer simulations, that the fluid surfaces of cellular cargo reduce the mechanical interference between motors allowing better load sharing and decreasing their detachment rates, thereby increasing the distance over which they can carry cargo. We additionally found that motors pull cargo closer to the filament increasing the attachment rates of other unbound motors. These effects act synergistically with an increased availability of motors due to fluidity to further increase travel distances. Our simulation model accounted for the dynamics of the motors on the cargo surface and their load and ATP dependent kinetics, allowing us to connect single motor properties to overall transport. Our work on understanding how teamwork arises in mechanically coupled motors sheds new light on cellular processes, reconciles existing observations, encourages new experimental validation efforts and can also suggest new ways of improving mechanical efficiency and transport of artificial cargo powered by motor teams. BioCAT: a novel tool to search biosynthetic gene clusters producing nonribosomal peptides with a known structure MotivationNonribosomal peptides are a class of secondary metabolites synthesized by multimodular enzymes named nonribosomal peptide synthetases and mainly produced by bacteria and fungi. It has been shown that non-ribosomal peptides have a huge structural and functional diversity including antimicrobial activity, therefore, they are of increasing interest for modern biotechnology. Methods such as NMR and LC-MS/MS allow to determine a peptide structure precisely, but it is often not a trivial task to find natural producers of them. Today, the search is usually performed manually, mostly with tools such as antiSMASH or Prism. However, there are cases when potential producers should be found among hundreds of strains, for instance, when analyzing metagenomes data. Thus, the development of automated approaches is a high-priority task for further nonribosomal peptides research.

ResultsWe developed BioCAT, a two-side approach to find biosynthetic gene clusters which may produce a given nonribosomal peptide when the structure of interesting nonribosomal peptide has already been found. Formally, BioCAT unites the antiSMASH software and the rBAN retrosynthesis tool but some improvements were added to both gene cluster and peptide chemical structure analyses. The main feature of the method is an implementation of position specific score matrix to store specificities of nonribosomal peptide synthetase modules, which has increased the alignment quality in comparison with more strict approaches developed earlier. An ensemble model was implemented to calculate the final alignment score. We tested the method on a manually curated nonribosomal peptides producers database and compared it with a competing tool called GARLIC. Finally, we showed the method applicability on several external examples.

AvailabilityBioCAT is available on the GitHub repository or via pip

Contactkonanovdmitriy@gmail.com 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. Activation of the type 3 secretion system of enteropathogenic E. coli leads to remodeling of its membrane composition The cell envelope of gram-negative bacteria is a complex structure, essential for bacterial survival and for resistance to many antibiotics. Channels that cross the bacterial envelope and the host cell membrane form secretion systems that are activated upon attachment to host, enabling bacteria to inject effector molecules into the host cell, required for bacterial-host interaction. The type III secretion system (T3SS) is critical for the virulence of several pathogenic bacteria, including enteropathogenic E. coli (EPEC). The EPEC T3SS activation is associated with repression of carbon storage regulator (CsrA), resulting in gene expression remodeling, which is known to affect EPEC central carbon metabolism and contributes to the adaptation to a cell-adherent lifestyle in a poorly understood manner. We reasoned that the changes in bacterial envelope upon attachment to host and the activation of a secretion system may involve a modification of the lipid composition of bacterial envelope. Accordingly, we performed a lipidomics analysis on mutant strains that simulate T3SS activation. We saw a shift in glycerophospholipid metabolism towards the formation of lysophospholipids, attributed to corresponding upregulation of the phospholipase pldA and the acyltransferase ygiH upon T3SS activation in EPEC. We also detected a shift from menaquinones and ubiquinones to undecaprenyl lipids, concomitant to abnormal synthesis of O-antigen. The remodeling of lipid metabolism is mediated by CsrA and associated with increased bacteria cell size and Zeta potential, and a corresponding alteration in EPEC permeability to vancomycin, increasing the sensitivity of T3SS-activated strains and of adherent wild type EPEC to the antibiotic.

ImportanceThe characterization of EPEC membrane lipid metabolism upon attachment to host is an important step towards a better understanding the shift of EPEC, a notable human pathogen, from a planktonic to adherent life style. It may also apply to other pathogenic bacteria that use this secretion system. We predict that upon attachment to host cells the lipid remodeling upon T3SS activation contributes to bacterial fitness and promotes host colonization, and show that it is associated with increased cell permeability and higher sensitivity to vancomycin.

To the best of our knowledge, this is the first demonstration of a bacterial lipid remodeling due to activation of a secretion system. If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. Regulatory T cells suppress the formation of potent KLRK1 and IL-7R expressing effector CD8 T cells by limiting IL-2 Regulatory T cells (Tregs) are indispensable for maintaining self-tolerance by suppressing conventional T cells. On the other hand, Tregs may promote tumor growth by inhibiting anti-cancer immunity. In this study, we identified that Tregs increase the quorum of self-reactive CD8+ T cells required for the induction of experimental autoimmune diabetes. Their major suppression mechanism is limiting available IL-2, an essential T-cell cytokine. Specifically, Tregs inhibit the formation of a previously uncharacterized subset of antigen-stimulated KLRK1+ IL7R+ (KILR) CD8+ effector T cells, which are distinct from conventional effector CD8+ T cells. KILR CD8+ T cells show a superior cell killing abilities in vivo. The administration of agonistic IL-2 immunocomplexes phenocopies the absence of Tregs, i.e., it induces KILR CD8+ T cells, promotes autoimmunity, and enhances anti-tumor responses. Counterparts of KILR CD8+ T cells were found in the human blood, revealing them as a potential target for immunotherapy. Multi-omics investigation of tacrolimus nephrotoxicity BackgroundTacrolimus, an immunosuppressive drug prescribed to a majority of transplanted patients is nephrotoxic, through still unclear mechanisms. This study aims to evaluate the impact of tacrolimus on a lineage of proximal tubular cells using a multi-omics approach.

MethodsLLC-PK1 cells were exposed to 5 M of tacrolimus for 24h. Intracellular proteins and metabolites, and extracellular metabolites were extracted and analysed by LC-MS/MS. The transcriptional expression of the dysregulated proteins PCK-1, FBP1 and FBP2 was measured using RT-qPCR.

ResultsIn our cell model, tacrolimus impacted different metabolic pathways including those of arginine (e.g., citrulline, ornithine) (p < 0.0001), amino acids (e.g., valine, isoleucine, aspartic acid) (p < 0.0001) and pyrimidine (p<0.01). In addition, it induced oxidative stress (p < 0.01) as shown by a decrease in total cell glutathione quantity. It impacted cell energy through an increase in Krebs cycle intermediates (e.g., citrate, aconitate, fumarate) (p < 0.01) and down-regulation of PCK-1 (p < 0.05) and FPB1 (p < 0.01), which are key enzymes in gluconeogenesis. Apart from glucose synthesis, gluconeogenesis is an important process in kidney mediated acid-base balance control.

ConclusionThe variations found using this multi-omics approach clearly point towards a dysregulation of energy production in epithelial cells of the renal tubule, and potentially of their functions, that may be implicated in tacrolimus nephrotoxicity in the clinics. 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. Target Recognition in Tandem WW Domains: Complex Structures for Parallel and Antiparallel Ligand Orientation in h-FBP21 Tandem WW Protein-protein interactions often rely on specialized recognition domains, such as WW domains, which bind to specific proline-rich sequences. The specificity of these protein-protein interactions can be increased by tandem repeats, i.e. two WW domains connected by a linker. With a flexible linker, the WW domains can move freely with respect to each other. Additionally, the tandem WW domains can bind in two different orientations to their target sequences. This makes the elucidation of complex structures of tandem WW domains extremely challenging. Here, we identify and characterize two complex structures of the tandem WW domain of human formin-binding protein 21 and a peptide sequence from its natural binding partner, the core-splicing protein SmB/B. The two structures differ in the ligand orientation, and consequently also in the relative orientation of the two WW domains. We analyze and probe the interactions in the complexes by molecular simulations and NMR experiments. The workflow to identify the complex structures uses molecular simulations, density-based clustering and peptide docking. It is designed to systematically generate possible complex structures for repeats of recognition domains. These structures will help us to understand the synergistic and multivalency effects that generate the astonishing versatility and specificity of protein-protein interactions. Selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes. Compartmentalized control of Cdk1 drives mitotic spindle assembly During cell division, dramatic microtubular rearrangements driven by cyclin B-cdk1 (Cdk1) kinase activity mark mitosis onset leading to interphase cytoskeleton dissolution and mitotic spindle assembly. Once activated by Cdc25, that reverses inhibitory phosphorylation operated by Wee1/Myt1, Cdk1 clears the cytoplasm from microtubules by inhibiting microtubule associated proteins (MAPs) with microtubule growth-promoting properties. Nevertheless, some of these MAPs are required for spindle assembly, creating quite a conundrum. We show here that a Cdk1 fraction bound to spindle structures escaped Cdc25 action and remained inhibited by phosphorylation (i-Cdk1) in mitotic human cells. Loss or restoration of i-Cdk1 inhibited or promoted spindle assembly, respectively. Furthermore, polymerizing spindle microtubules fostered i-Cdk1 by aggregating with Wee1 and excluding Cdc25. Our data reveal that spindle assembly relies on compartmentalized control of Cdk1 activity. 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. Conserved organ-specific microbial assemblages in different populations of a terrestrial crab Brachyuran crabs originated in the oceans and evolved specific morphological and physiological adaptations to live in freshwater, intertidal and even terrestrial habitats but the role of a selection mechanism involving symbiotic microorganisms long these colonization processes are not known. In this work we investigated the associated microbiota of three populations of a terrestrial brachyuran crab, Chiromantes haematocheir, to find evidence of a conserved crab-specific microbiome unrelated to the population of origin and dissimilar from environmental microbial assemblages. Bacterial 16S rRNA gene and fungal ITS sequences were obtained from selected crab organs and environmental matrices to profile microbial communities. In spite of the presence of truly marine larval stages and no gregarious behaviour, favouring microbiota exchanges, we found common, organ-specific microbiota, associated to the gut and the gills of the crabs (with more than 15% of the genera detected specifically enriched only in one organ). Our results suggest an early establishment of a new common, stable microbiota in the transition from water to land. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. A Positive Correlation between Bacterial GC Content and Growth Temperature BackgroundGC pairs are generally more stable than AT pairs; GC-rich genomes were proposed to be more adapted to high temperatures than AT-rich genomes. Previous studies consistently showed positive correlations between growth temperature and the GC contents of structural RNA genes. However, for the whole genome sequences and the silent sites of the codons in protein-coding genes, the relationship between GC content and growth temperature is in a long-lasting debate.

ResultsWith a dataset much larger than previous studies (681 bacteria and 155 archaea with completely assembled genomes), our phylogenetic comparative analyses showed positive correlations between optimal growth temperature (Topt) and GC content both in bacterial and archaeal structural RNA genes and in bacterial whole genome sequences, chromosomal sequences, plasmid sequences, core genes, and accessory genes. However, in the 155 archaea, we did not observe a significant positive correlation of Topt with whole-genome GC content (GCw) or GC content at four-fold degenerate sites. We randomly drew 155 samples from the 681 bacteria for 1000 rounds. In most cases (> 95%), the positive correlations between Topt and genomic GC contents became statistically nonsignificant (P > 0.05). This result suggested that the small sample sizes might account for the lack of positive correlations between growth temperature and genomic GC content in the 155 archaea and the bacterial samples of previous studies. Comparing the GC content among four categories (psychrophiles/psychrotrophiles, mesophiles, thermophiles, and hyperthermophiles) also revealed a positive correlation between GCw and growth temperature in bacteria. By including the GCw of incompletely assembled genomes, we expanded the sample size of archaea to 303. Positive correlations between GCw and Topt appear especially after excluding the halophilic archaea whose GC contents might be are strongly shaped by intense UV radiation.

ConclusionsThis study explains the previous contradictory observations and ends a long debate. Prokaryotes growing in high temperatures have higher GC contents. Thermal adaptation is one possible explanation for the positive association. Meanwhile, we propose that the elevated efficiency of DNA repair in response to heat mutagenesis might have the by-product of increasing GC content like that happens in intracellular symbionts and marine bacterioplankton. DeCalciOn: A hardware system for real-time decoding of in-vivo calcium imaging data Epifluorescence miniature microscopes ("miniscopes") are widely used for in vivo calcium imaging of neural population activity. Imaging data is usually collected while subjects are engaged in a task and stored for later offline analysis, but emerging techniques for online imaging offer potential for novel real-time experiments in which closed-loop interventions (such as neurostimulation or sensory feedback) are triggered at short latencies in response to neural population activity. Here we introduce DeCalciOn, a plug-and-play hardware device for online population decoding of in vivo calcium signals that can trigger closed-loop feedback at millisecond latencies, and is compatible with miniscopes that use the UCLA Data Acquisition (DAQ) interface. In performance tests, the position of rats (n=13) on a linear track was decoded in real time from hippocampal CA1 population activity by 24 linear classifiers. DeCalciOn required <2.5 ms after each end-of-frame to decode up to 1,024 calcium traces and trigger TTL control outputs. Decoding was most efficient using a  contour-free method of extracting traces from ROIs that were unaligned with neurons in the image, but  contour-based extraction from neuronal ROIs is also supported. DeCalciOn is an easy-to-use system for real-time decoding of calcium fluorescence that enables closed-loop feedback experiments in behaving animals. Second Heart Field-derived Cells Contribute to Angiotensin II-mediated Ascending Aortopathies BackgroundThe ascending aorta is a common location for aneurysm and dissection. This aortic region is populated by a mosaic of medial and adventitial cells that are embryonically derived from either the second heart field (SHF) or the cardiac neural crest. SHF-derived cells populate areas that coincide with the spatial specificity of thoracic aortopathies. The purpose of this study was to determine whether and how SHF-derived cells contribute to ascending aortopathies.

MethodsAscending aortic pathologies were examined in patients with sporadic thoracic aortopathies and angiotensin II (AngII)-infused mice. Ascending aortas without overt pathology from AngII-infused mice were subjected to mass spectrometry assisted proteomics, and molecular features of SHF-derived cells were determined by single cell transcriptomic analyses. Genetic deletion of either low-density lipoprotein receptor-related protein 1 (Lrp1) or transforming growth factor-{beta} receptor 2 (Tgfbr2) in SHF- derived cells was conducted to examine the impact of SHF-derived cells on vascular integrity.

ResultsPathologies in human ascending aortic aneurysmal tissues were predominant in outer medial layers and adventitia. This gradient was mimicked in mouse aortas following AngII infusion that was coincident with the distribution of SHF-derived cells. Proteomics indicated that brief AngII infusion, prior to overt pathology, evoked downregulation of SMC proteins and differential expression of extracellular matrix proteins, including several LRP1 ligands. LRP1 deletion in SHF-derived cells augmented AngII-induced ascending aortic aneurysm and rupture. Single cell transcriptomic analysis revealed that brief AngII infusion decreased Lrp1 and Tgfbr2 mRNA abundance in SHF-derived cells and induced a unique fibroblast population with low abundance of Tgfbr2 mRNA. SHF-specific Tgfbr2 deletion led to embryonic lethality at E12.5 with dilatation of the outflow tract and retroperitoneal hemorrhage. Integration of proteomic and single cell transcriptomics results identified plasminogen activator inhibitor 1 (PAI1) as the most increased protein in SHF-derived SMCs and fibroblasts during AngII infusion. Immunostaining revealed a transmural gradient of PAI1 in both ascending aortas of AngII-infused mice and human ascending aneurysmal aortas that mimicked the gradient of medial and adventitial pathologies.

ConclusionSHF-derived cells exert a critical role in maintaining vascular integrity through LRP1 and TGF-{beta} signaling associated with increases of aortic PAI1.



O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/930917v6_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@185e3d9org.highwire.dtl.DTLVardef@131d702org.highwire.dtl.DTLVardef@11afa42org.highwire.dtl.DTLVardef@242786_HPS_FORMAT_FIGEXP  M_FIG C_FIG Clinical PerspectiveO_ST_ABSWhat is new?C_ST_ABS- SHF-derived SMCs and fibroblasts associate with AngII-induced aortic pathologies.
- AngII induces a distinct fibroblast sub-cluster that is less abundant for mRNAs related to major extracellular components and TGF{beta} ligands and receptors, but more abundant for proliferative genes.
- TGFBR2 deletion in SHF-derived cells are embryonic lethal with significant dilatation of the outflow tract in mice.
- SHF-specific deletion of LRP1 leads to aortic pathologies in mice, supporting the importance of SHF-derived cells in maintaining ascending aortic wall integrity.


What are the clinical implications?- Heterogeneity of the embryonic origins of SMCs and fibroblasts contributes to complex mechanisms of vasculopathy formation, which should be considered when investigating the pathogenesis of thoracic aortopathies. Flexibility of Short-chain dehydrogenase is interconnected to its promiscuity for the reduction of multiple ketone intermediates Short-chain dehydrogenases/reductases (SDRs) are a convenient class of enzymes used to synthesize enantiopure alcohols. Several studies describe native or engineered SDRs for converting substrates of interest using cost and time-intensive high-throughput approaches. The classification of SDRs is based on chain length and cofactor binding site. Of these, the shorter  Classical and the longer  Extended enzymes participate in ketoreduction. However, comparative analysis of various modelled SDRs reveals a length independent conserved N-terminal Rossmann fold and a variable C-terminus region for both types. The general hypothesis is that the latter domain influences the enzymes flexibility that may affect the observed promiscuity of the enzyme. We have used a machine learning algorithm on this flexible domain to build a rationale to screen promiscuous candidates. We have built a data set consisting of physicochemical properties derived from the amino-acid composition of enzymes to select closely associated promiscuous mesophilic enzymes. The resulting in vitro studies on pro-pharmaceutical substrates illustrate a direct correlation between the C-terminal lid-loop structure, enzyme melting temperature and the turnover number. We present a walkthrough for exploring promiscuous SDRs for catalyzing enantiopure alcohols of industrial importance. 3D Echo Planar Time-resolved Imaging (3D-EPTI) for ultrafast multi-parametric quantitative MRI Multi-parametric quantitative MRI has shown great potential to improve the sensitivity and specificity of clinical diagnosis and to enhance our understanding of complex brain processes, but suffers from long scan time especially at high spatial resolution. To address this long-standing challenge, we introduce a novel approach, termed 3D Echo Planar Time-resolved Imaging (3D-EPTI), which significantly increases the acceleration capacity of MRI sampling, and provides high acquisition efficiency for multi-parametric MRI. This is achieved by exploiting the spatiotemporal correlation of MRI data at multiple timescales through new encoding strategies within and between efficient continuous readouts. Specifically, an optimized spatiotemporal CAIPI encoding within the readouts combined with a radial-block sampling strategy across the readouts enables an acceleration rate of 800 folds in the k-t space. A subspace reconstruction was employed to resolve thousands of artifact-free high-quality multi-contrast images spaced at a time interval of ~1 ms. We have demonstrated the ability of 3D-EPTI to provide robust and repeatable whole-brain simultaneous T1, T2, T2*, PD and B1+ mapping at high isotropic resolution within minutes (e.g., 1-mm isotropic resolution in 3 minutes), and to enable submillimeter multi-parametric imaging to study detailed brain structures.

HighlightsO_LIUltra-fast acquisition for 3D multi-parametric quantitative MRI.
C_LIO_LISimultaneous T1 T2 T2* PD and B1+ mapping.
C_LIO_LI3-minute scan at 1-mm isotropic resolution with whole-brain coverage.
C_LIO_LIMulti-parametric mapping at 700-m isotropic resolution in 10 minutes.
C_LIO_LIRepeatable quantification and cortical-depth analysis.
C_LI