Loss of histone methyltransferase SETD1B in oogenesis results in the redistribution of genomic histone 3 lysine 4 trimethylation Histone 3 lysine 4 trimethylation (H3K4me3) is an epigenetic mark found at gene promoters and CpG islands. H3K4me3 is essential for mammalian development, yet mechanisms underlying its genomic targeting are poorly understood. H3K4me3 methyltransferases SETD1B and MLL2 are essential for oogenesis. We investigated changes in H3K4me3 in Setd1b conditional knockout (cKO) oocytes using ultra-low input ChIP-seq, with comparisons to DNA methylation and gene expression analyses. H3K4me3 was redistributed in Setd1b cKO oocytes showing losses at active gene promoters associated with downregulated gene expression. Remarkably, many regions also gained H3K4me3, in particular those that were DNA hypomethylated, transcriptionally inactive and CpG-rich, which are hallmarks of MLL2 targets. Consequently, loss of SETD1B disrupts the balance between MLL2 and de novo DNA methyltransferases in determining the epigenetic landscape during oogenesis. Our work reveals two distinct, complementary mechanisms of genomic targeting of H3K4me3 in oogenesis, with SETD1B linked to gene expression and MLL2 to CpG content.

Graphical AbstractIn oogenesis, SETD1B and CXXC1 target H3K4me3 to actively transcribed gene promoters, while MLL2 targets transcriptionally inactive regions based on underlying CpG composition (upper panel). When SETD1B is ablated, H3K4me3 is lost at a subset of active promoters, resulting in downregulation of transcription (lower panel). Loss of SETD1B alters the activity of MLL2, permitting MLL2 to deposit H3K4me3 at CpG-rich regions, many of which should otherwise be DNA methylated. Thus, it is evident that MLL2 and de novo DNMTs compete for genomic occupancy late in oogenesis, and loss of SETD1B disrupts the balance of these mechanisms.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY
Simultaneous suppression of ribosome biogenesis and Tor activation by TRIM-NHL proteins promotes terminal differentiation Proper tissue development and homeostasis depends on the balance between growth and terminal differentiation, but the mechanisms coordinating these processes remain elusive. Accumulating evidence indicates that ribosome biogenesis (RiBi) and protein synthesis, two of the most energy-consuming cellular processes sustaining growth, are tightly regulated and yet can be uncoupled during stem cell fate transitions. Here, using the Drosophila adult female germline stem cell (GSC) and larval neuroblast (NB) systems, we show that Mei-P26 and Brat, two Drosophila TRIM-NHL paralogs of the mammalian TRIM32 protein family, are responsible for uncoupling RiBi and protein synthesis during GSC and NB differentiation, respectively. Mei-P26 and Brat modify the metabolism of differentiating cells by activating the Target of rapamycin (Tor) kinase to promote translation, while concomitantly repressing RiBi. Depletion of Mei-P26 or Brat results in excessive cellular growth and defective terminal differentiation, which can be rescued by ectopic activation of Tor together with suppression of RiBi. Our results indicate that the anabolic reprogramming established by TRIM-NHL activity by uncoupling RiBi and translation activities creates the conditions required for terminal differentiation.
Hierarchical clustering optimizes the tradeoff between compositionality and expressivity of task structures for flexible reinforcement learning A hallmark of human intelligence, but challenging for reinforcement learning (RL) agents, is the ability to compositionally generalise, that is, to recompose familiar knowledge components in novel ways to solve new problems. For instance, when navigating in a city, one needs to know the location of the destination and how to operate a vehicle to get there, whether it be pedalling a bike or operating a car. In RL, these correspond to the reward function and transition function, respectively. To compositionally generalize, these two components need to be transferable independently of each other: multiple modes of transport can reach the same goal, and any given mode can be used to reach multiple destinations. Yet there are also instances where it can be helpful to learn and transfer entire structures, jointly representing goals and transitions, particularly whenever these recur in natural tasks (e.g., given a suggestion to get ice cream, one might prefer to bike, even in new towns). Prior theoretical work has explored how, in model-based RL, agents can learn and generalize task components (transition and reward functions). But a satisfactory account for how a single agent can simultaneously satisfy the two competing demands is still lacking. Here, we propose a hierarchical RL agent that learns and transfers individual task components as well as entire structures (particular compositions of components) by inferring both through a non-parametric Bayesian model of the task. It maintains a factorised representation of task components through a hierarchical Dirichlet process, but it also represents different possible covariances between these components through a standard Dirichlet process. We validate our approach on a variety of navigation tasks covering a wide range of statistical correlations between task components and show that it can also improve generalisation and transfer in more complex, hierarchical tasks with goal/subgoal structures. Finally, we end with a discussion of our work including how this clustering algorithm could conceivably be implemented by cortico-striatal gating circuits in the brain. Analysis of Drosophila cardiac hypertrophy by micro-computerized tomography for genetic dissection of heart growth mechanisms Heart failure is often preceded by pathological cardiac hypertrophy, a thickening of the heart musculature driven by complex gene regulatory and signaling processes. The Drosophila heart has great potential as a genetic model for deciphering the underlying mechanisms of cardiac hypertrophy. However, current methods for evaluating hypertrophy of the Drosophila heart are laborious and difficult to carry out reproducibly. Here we demonstrate that micro-computerized tomography (microCT) is an accessible, highly reproducible method for non-destructive, quantitative analysis of Drosophila heart morphology and size. To validate our microCT approach for analyzing Drosophila cardiac hypertrophy, we show that expression of constitutively active Ras (Ras85DV12), previously shown to cause hypertrophy of the fly heart, results in significant thickening of both adult and larval heart walls when measured from microCT images. We then show using microCT analysis that genetic upregulation of store-operated Ca2+ entry (SOCE) driven by expression of constitutively active Stim (StimCA) or Orai (OraiCA) proteins also results in significant hypertrophy of the Drosophila heart, through a process that specifically depends on Orai Ca2+ influx channels. Intravital imaging of heart contractility revealed significantly reduced end diastolic dimensions in StimCA and OraiCA expressing hearts, consistent with the hypertrophic phenotype. These results demonstrate that increased SOCE activity is an important driver of hypertrophic cardiomyocyte growth, and demonstrate how microCT analysis combined with tractable genetic tools in Drosophila can be used to delineate molecular signaling processes that underlie cardiac hypertrophy and heart failure.

NEW AND NOTEWORTHYGenetic analysis of cardiac hypertrophy in Drosophila holds immense potential for the discovery of new therapeutic targets to prevent and treat heart failure. However, this potential has been hindered by a lack of rapid and effective methods for analysis of heart size in flies. Here we demonstrate that analysis of the Drosophila heart with micro-computerized tomography yields accurate and highly reproducible heart size measurements that can be used to efficiently analyze heart growth and cardiac hypertrophy in Drosophila. Migrators Within Migrators: Exploring Transposable Element Landscapes, Activity, and Host Gene Associations in the Monarch Butterfly, Danaus plexippus BackgroundLepidoptera (butterflies and moths) are an important model system in ecology and evolution. A high-quality chromosomal genome assembly is available for the monarch butterfly (Danaus plexippus), but it lacks an in-depth transposable element (TE) annotation, presenting an opportunity to explore monarch TE dynamics and the impact of TEs on shaping the monarch genome.

ResultsWe find 6.21% of the monarch genome is comprised of TEs, a reduction of 6.85% compared to the original TE annotation performed on the draft genome assembly. Monarch TE content is low compared to two closely related species with available genomes, Danaus chrysippus (33.97% TE) and Danaus melanippus (11.87% TE). The biggest TE contributions to genome size in the monarch are LINEs and Penelope-like elements, and three newly identified families, r2-hero_dPle (LINE), penelope-1_dPle (Penelope-like), and hase2-1_dPle (SINE), collectively contribute 34.92% of total TE content. We find evidence of recent TE activity, with two novel Tc1 families rapidly expanding over recent timescales (tc1-1_dPle, tc1- 2_dPle). LINE fragments show signatures of genomic deletions indicating a high rate of TE turnover. We investigate associations between TEs and wing colouration and immune genes and identify a three-fold increase in TE content around immune genes compared to other host genes.

ConclusionsWe provide a detailed TE annotation and analysis for the monarch genome, revealing a considerably smaller TE contribution to genome content compared to two closely related Danaus species with available genome assemblies. We identify highly successful novel DNA TE families rapidly expanding over recent timescales, and ongoing signatures of both TE expansion and removal highlight the dynamic nature of repeat content in the monarch genome. Our findings also suggest that insect immune genes are promising candidates for future interrogation of TE-mediated host adaptation. An End-to-End Deep Learning Speech Coding and Denoising Strategy for Cochlear Implants Cochlear implant (CI) users struggle to understand speech in noisy conditions. To address this problem, we propose a deep learning speech denoising sound coding strategy that estimates the CI electric stimulation patterns out of the raw audio data captured by the micro-phone, performing end-to-end CI processing. To estimate the relative denoising performance differences between various approaches, we compared this technique to a classic Wiener filter and to a convTasNet. Speech enhancement performance was assessed by means of signal-to-noise-ratio improvement and the short-time objective speech intelligibility measure. Additionally, 5 CI users were evaluated for speech intelligibility in noise to assess the potential benefits of each algorithm. Our results show that the proposed method is capable of replacing a CI sound coding strategy while preserving its general use for every listener and performing speech enhancement in noisy environments, without sacrificing algorithmic latency. Polycystin promotes renal fibrosis through EZH2 Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. Citation needed? Wikipedia and the COVID-19 pandemic BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. Predicting the re-distribution of antibiotic molecules caused byinter-species interactions in microbial communities Microbes associate in nature forming complex communities, but they are often studied in purified form. Here I show that differences in antibiotic sensitivity between co-existing bacterial species can modify the diffusion of antibiotic molecules, and alter the drug efficacy measured in conventional in vitro assays. I developed a model, validated experimentally using an artificial two-species community, showing antibiotic molecules re-distribute evenly across all species if they have similar drug sensitivity. The result is lower drug efficacy with respect to conventional in vitro assays. However, when species have different sensitivities, the re-distribution of antibiotic is uneven and most sensitive species accumulate more drug. The result is increased drug efficacy against these species. Despite this discrepancy with conventional laboratory assays, my data suggests the changes in drug efficacy are predictable and provides insight into how communities can affect the diffusion of other molecules in the environment. A quartz crystal microbalance method to quantify the size of hyaluronan and other glycosaminoglycans on surfaces Hyaluronan (HA) is a major component of peri- and extra-cellular matrices and plays important roles in many biological processes such as cell adhesion, proliferation and migration. The abundance, size distribution and presentation of HA dictate its biological effects and are also useful indicators of pathologies and disease progression. Methods to assess the molecular mass of free-floating HA and other glycosaminoglycans (GAGs) are well established. In many biological and technological settings, however, GAGs are displayed on surfaces, and methods to obtain the size of surface-attached GAGs are lacking. Here, we present a method to size HA that is end-attached to surfaces. The method is based on the quartz crystal microbalance with dissipation monitoring (QCM-D) and exploits that the softness and thickness of films of grafted HA increase with HA size. These two quantities are sensitively reflected by the ratio of the dissipation shift ({Delta}D) and the negative frequency shift (-{Delta}f) measured by QCM-D upon the formation of HA films. Using a series of size-defined HA preparations, ranging in size from [~]2 kDa tetrasaccharides to [~]1 MDa polysaccharides, we establish a monotonic yet non-linear standard curve of the {Delta}D/-{Delta}f ratio as a function of HA size, which reflects the distinct conformations adopted by grafted HA chains depending on their size and surface coverage. We demonstrate that the standard curve can be used to determine the mean size of HA, as well as other GAGs, such as chondroitin sulfate and heparan sulfate, of preparations of previously unknown size in the range from 1 to 500 kDa, with a resolution of better than 10%. For polydisperse samples, our analysis shows that the process of surface-grafting preferentially selects smaller GAG chains, and thus reduces the average size of GAGs that are immobilised on surfaces comparative to the original solution sample. Our results establish a quantitative method to size HA and other GAGs grafted on surfaces, and also highlight the importance of sizing GAGs directly on surfaces. The method should be useful for the development and quality control of GAG-based surface coatings in a wide range of research areas, from molecular interaction analysis to biomaterials coatings. Define protein variant functions with high-complexity mutagenesis libraries and enhanced mutation detection software ASMv1.0 Open reading frame (ORF) variant libraries have advanced our ability to query the functions of a large number of variants of a protein simultaneously in a single experiment. Variant libraries targeting full-length ORFs typically consists of all possible single-amino-acid substitutions and a stop codon at each amino-acid position. Because a variant differs from the template ORF by a single codon variation, variant quantification presents the most profound challenge to this technology. Efforts such as dividing a library into sub-libraries for direct sequencing, or tag-directed subassembly are practical only for small ORFs. Our approach, however, features an enhanced variant-calling tool that processes massive shotgun sequencing data, allowing one to screen a single variant library for ORFs sized up to [~]3600 bases. The variant-calling tool detects variants reliably, and also presents variant annotations in datafiles enabling analyses that have reshaped our strategies governing library design, screen deconvolution, sequencing and sequencing data analysis. ConVarT: a search engine for orthologous variants and functional inference of human genetic variants The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely "matching variants" (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and C. elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease. Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. The RAG1 Ubiquitin Ligase Domain Enhances Assembly and Selection of T Cell Receptor Genes to Restrain the Autoimmune Hazard of Generating T Cell Receptor Diversity RAG1/RAG2 (RAG) endonuclease-mediated assembly of diverse lymphocyte antigen receptor genes by V(D)J recombination is critical for the development and immune function of T and B cells. However, this process creates highly self-reactive cells that must be properly selected to suppress autoimmunity. The RAG1 protein contains a ubiquitin ligase domain that stabilizes RAG1 and stimulates RAG endonuclease activity in vitro. We report that mice with a mutation that inactivates the RAG1 ubiquitin ligase in vitro exhibit modestly reduced thymic cellularity, decreased assembly and altered repertoires of T cell receptor (TCR) {beta} and  genes in thymocytes, and impaired thymocyte developmental transitions that require the assembly of TCR{beta} or  genes and signaling by their proteins. These RAG1 mutant mice also exhibit less efficient positive selection and superantigen-mediated negative selection of conventional {beta} T cells, 2) impaired differentiation of iNKT lineage {beta} T cells, and 3) CD4+ {beta} T cells with elevated autoimmune potential. Our findings demonstrate that the RAG1 ubiquitin ligase domain functions in vivo to stimulate the assembly and selection of TCR{beta} and TCR genes, thereby establishing replete diversity of {beta} TCRs and {beta} T cell lineages while restraining the inherent autoimmune hazard of generating diverse antigen specificities. Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harbouring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define three compositional  tissue-states rooted in cohabitation of cell-types and transcriptional states. These comprise a state featuring A) abundant normal brain microenvironment cells, B) reactive/inflamed brain microenvironment, and C) cellular/proliferative tumor. All these states exhibited variable degrees of infiltration by glioma cells. Spatial transcriptomics confirmed that the cell-types and transcriptomics states which compositionally cohabitate tissue states also colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. We found that enrichment of tissue state B signature correlated with shorter survival. Importantly, we found that our compositionally defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes resembling those seen in neurodegeneration, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to the glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries. Comprehensive analysis of pyroptosis-associated in molecular classification, immunity and prognostic of glioma Integrative analysis was performed in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas to describe the pyroptosis-associated molecular classification and prognostic signature in glioma. Pyroptosis-related genes were used for consensus clustering and to develop a prognostic signature. The immune statuses, molecular alterations and clinical features of differentially expressed genes were analyzed among different subclasses and risk groups. A lncRNA-miRNA-mRNA network was built, and drug sensitivity analysis was used to identify small molecular drugs for the identified genes. Glioma can be divided into two subclasses using 30 pyroptosis-related genes. Cluster 1 displayed high immune signatures and poor prognosis as well as high immune-related function scores. A prognostic signature based on 15 pyroptosis-related genes of the CGGA cohort can predict the overall survival of glioma and was well validated in the TCGA cohort. Cluster 1 had higher risk scores. The high-risk group had high immune cell and function scores and low DNA methylation of pyroptosis-related genes. The differences in pyroptosis-related gene mutations and somatic copy numbers were significant between the high-risk and low-risk groups. The ceRNA regulatory network uncovered the regulatory patterns of different risk groups in glioma. Nine pairs of target genes and drugs were identified. In vitro, CASP8 promotes the progression of glioma cells. Pyroptosis-related genes can reflect the molecular biological and clinical features of glioma subclasses. The established prognostic signature can predict prognosis and distinguish molecular alterations in glioma patients. Our comprehensive analyses provide valuable guidelines for improving glioma patient management and individualized therapy. Beyond tracking climate: niche shifts during native range expansion and their implications for novel invasions AimAlthough ecological niche models have been instrumental in understanding the widespread species distribution shifts under global change, rapid niche shifts limit model transferability to novel locations or time periods. Niche shifts during range expansion have been studied extensively in invasive species, but may also occur in native populations tracking climate change. We compared niche shifts during both types of range expansion in a Mediterranean annual plant to ask (i) whether the species native range expansion tracked climate change, (ii) whether further range expansion was promoted by niche expansion, and (iii) how these results changed forecasts of two ongoing invasions in Australia and California.

LocationEurasian Holarctic, California and Australia

TaxonDittrichia graveolens (L.) Greuter (Asteraceae)

MethodsNiche shifts were quantified in both environmental and geographic space, using the framework of niche centroid shift, overlap, unfilling, and expansion (COUE) as well as Maximum Entropy modelling. We used the historic native distribution and climate data (1901-1930) to project the expected distribution in the present climate (1990-2019), and compared it to the observed current distribution of D. graveolens. Finally, we compared invasion forecasts based on the historic and present native niches.

ResultsWe found that D. graveolens expanded its native range well beyond what would be sufficient to track climate change, associated with a 5.5% niche expansion towards more temperate climates. In contrast, both invasions showed niche conservatism, and were (still) constrained to climatic areas matching the historic native niche.

Main conclusionsour results show that contrary to hypotheses in the literature, niche shifts are not necessarily more rapid in invasions than in native range expansions. We conclude that niche expansion during the process of climate tracking may cause further range expansion than expected based on climate change alone. 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. 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. Stability of the genetic structure of a wild wheat population across microhabitats over 36 years Long-term genetic studies of wild populations are very scarce but are essential for connecting ecological and population genetics models, and are also necessary for understanding how climate change can affect biodiversity. We present a study of the wild ancestor of modern wheat, carried out over a 36-year period during which atmospheric CO2 increased by 70 ppm and temperature by 1.5{degrees}C. We genotyped 832 individuals that had been collected along the same transects during the course of the experiment. To our surprise, very little changed. Genotypes were clustered into ecological microhabitats over scales of tens of metres, and this clustering was stable over the 36 generations of the study. Simulations indicate that neutral processes alone are unlikely to fully explain this stability, suggesting a role for fine-scale local adaptation. Our results provide a rare insight into the dynamics of a wild population at the scale of individuals. Spike-dependent dynamic partitioning of the Locus coeruleus network through noradrenergic volume release in a simulation of nucleus core The Locus coeruleus (LC) modulates various neuronal circuits throughout the brain. Its unique architectural organization encompasses a net of axonal innervation that spans the entire brain; while its somatic core is highly compact. Recent research revealed an unexpected cellular input specificity within the nucleus that can give rise to various network states that either broadcast norepinephrine signals throughout the brain or pointedly modulate specific brain areas. Such adaptive input-output functions likely surpass our existing network models that build upon a given synaptic wiring configuration between neurons. As the distances between noradrenergic neurons in the core of the LC are unusually small, neighboring neurons could theoretically impact each other via volume transmission of NE. We therefore set out to investigate if such interaction could be mediated through noradrenergic alpha2-receptors in a spiking neuron model of the LC. We validate our model of LC neurons through comparison with experimental patch-clamp data and identify key variables that impact alpha2-mediated inhibition of neighboring LC neurons. Our simulation confirms a reliable autoinhibition of LC neurons after episodes of high neuronal activity that continue even after neuronal activity subsided. Also, dendro-somatic synapses inhibit spontaneous spiking in the somatic compartment of connected neurons in our model. We determined the exact position of hundreds of LC neurons in the mouse brain stem via a tissue clearing approach and, based on this, further determined that 25 percent of noradrenergic neurons have a neighboring LC neuron within less than a 25-micrometer radius. By modeling NE diffusion, we estimate that more than 15 percent of alpha2-adrenergic receptors fraction can bind NE within such diffusion radius. Our spiking neuron model of LC neurons predicts that repeated or long-lasting episodes of high neuronal activity induce partitioning of the gross LC network, and reduces the spike rate in neighboring neurons at distances smaller than 25 micrometers.

As these volume-mediate neighboring effects are challenging to test with the current methodology, our findings can guide future experimental approaches to test this phenomenon and its physiological consequences. Using Hierarchical Similarity To Examine The Genetics of Behcet's disease Behcets disease (BD) is a multisystem inflammatory disease that affects patients along the historic silk road. Thus far, the pathogenesis of the disease has proved elusive due to the complex genetic interactions and unknown environmental or viral triggering factors of the disease. In this paper, we seek to clarify the genetic factors of the disease while also uncovering other diseases of interest that present with a similar genotype as BD. To do this, we employ a convergent functional genomics approach by leveraging the hierarchical similarity tool available in Geneweaver. Through our analysis, we were able to ascertain 7 BD consensus genes and 16 autoimmune diseases with genetic overlap with BD. The results of our study will inform further research into the pathogenesis of Behcets Disease. F1F0 ATP Hydrolysis is a Determinant of Metabolic Rate, a Correlate of Lifespan, and a Weakness of Cancer Dramatic rectal temperature decrease, in mice administered with a drug that specifically inhibits F1F0 ATP hydrolysis, suggests that F1F0 ATP hydrolysis is a major determinant of metabolic rate in vivo. Across twelve investigated species, less F1F0 ATP hydrolysis correlates with greater maximal lifespan. Specific drug inhibition of F1F0 ATP hydrolysis exerts potent anti-cancer activity in vitro. Autophagosomes fuse to phagosomes and facilitate the degradation of apoptotic cells in Caenorhabditis elegans Autophagosomes are double-membrane intracellular vesicles that degrade protein aggregates, intracellular organelles, and other cellular components. During the development of the nematode Caenorhabditis elegans, many somatic and germ cells undergo apoptosis. These cells are engulfed and degraded by their neighboring cells. We discovered a novel role of autophagosomes in facilitating the degradation of apoptotic cells using a real-time imaging technique. Specifically, the double-membrane autophagosomes in engulfing cells are recruited to the surfaces of phagosomes containing apoptotic cells and subsequently fuse to phagosomes, allowing the inner vesicle to enter the phagosomal lumen. Mutants defective in the production of autophagosomes display significant defects in the degradation of apoptotic cells, demonstrating the importance of autophagosomes to this process. The signaling pathway led by the phagocytic receptor CED-1, the adaptor protein CED-6, and the large GTPase dynamin (DYN-1) promotes the recruitment of autophagosomes to phagosomes. Moreover, the subsequent fusion of autophagosomes with phagosomes requires the functions of the small GTPase RAB-7 and the HOPS complex components. Further observations suggest that autophagosomes provide apoptotic cell-degradation activities in addition to and in parallel of lysosomes. Our findings reveal that, unlike the single-membrane, LC3-associated phagocytosis (LAP) vesicles reported for mammalian phagocytes, the canonical double-membrane autophagosomes facilitate the clearance of C. elegans apoptotic cells. These findings add autophagosomes to the collection of intracellular organelles that contribute to phagosome maturation, identify novel crosstalk between the autophagy and phagosome maturation pathways, and discover the upstream signaling molecules that initiate this crosstalk. Membrane insertion mechanism of the caveolae coat protein Cavin1 Caveolae are small plasma membrane invaginations, important for control of membrane tension, signaling cascades and lipid sorting. The caveolae coat protein Cavin1 is essential for shaping such high curvature membrane structures. Yet, a mechanistic understanding of how Cavin1 assembles at the membrane interface is lacking. Here, we used model membranes combined with biophysical dissection and computational modelling to show that Cavin1 inserts into membranes. We establish that initial PI(4,5)P2-dependent membrane adsorption of the trimeric helical region 1 (HR1) of Cavin1 mediates the subsequent partial separation and membrane insertion of the individual helices. Insertion kinetics of the HR1 is further enhanced by the presence of flanking negatively charged disordered regions, which was found important for the co-assembly of Cavin1 with Caveolin1 in living cells. We propose that this intricate mechanism potentiates membrane curvature generation and facilitates dynamic rounds of assembly and disassembly of Cavin1 at the membrane.

Significance statementCaveolae are cholesterol enriched membrane invaginations coupled to severe muscle and lipid disorders. Their formation is dependent on assembly of the protein Cavin1 at the lipid membrane interface driving membrane curvature. In this work, we dissect the mechanism for how Cavin1 binds and inserts into membranes using a combination of biochemical and biophysical characterization as well as computational modelling. The proposed model for membrane assembly potentiates dynamic switching between shielded and exposed hydrophobic helices used for membrane insertion and clarifies how Cavin1 can drive membrane curvature and the formation of caveolae. 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.