Identifying complex sequence patterns in massive omics data with a variable-convolutional layer in deep neural network Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named Variable Convolutional (vConv) layer, for effective motif identification in high-throughput omics data by learning kernel length from data adaptively. Empirical evaluations on DNA-protein binding and DNase footprinting cases well demonstrated that vConv-based networks have superior performance to their convolutional counterparts regardless of model complexity. Meanwhile, vConv could be readily integrated into multi-layer neural networks as an "in-place replacement" of canonical convolutional layer. All source codes are freely available on GitHub for academic usage.
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
Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression 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. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. Limitations of composability of cis-regulatory elements in messenger RNA Genes are commonly abstracted into a coding sequence and cis-regulatory elements (CREs), such as promoters and terminators, and short sequence motifs within these regions. Modern cloning techniques allow easy assembly of synthetic genetic constructs from discrete cis-regulatory modules. However, it is unclear how much the contributions of CREs to gene expression depend on other CREs in the host gene. Using budding yeast, we probe the extent of composability, or independent effects, of distinct CREs. We confirm that the quantitative effect of a terminator on gene expression depends on both promoter and coding sequence. We then explore whether individual cisregulatory motifs within terminator regions display similar context dependence, using transcriptomewide datasets of mRNA decay. To test the extent of composability, we construct reporter genes consisting of combinations of motifs within various terminator contexts, paired with different promoters. Our results show that the effect of a motif on RNA abundance depends both on its host terminator, and also on the associated promoter sequence. This emphasises the need for improved motif inference that includes both local and global context effects, which in turn could aid in the accurate use of CREs for the engineering of synthetic genetic constructs. Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. VIP plasma levels associate with survival in severe COVID-19 patients, correlating with protective effects in SARS-CoV-2-infected cells. Infection by SARS-CoV-2 may elicit uncontrolled and damaging inflammatory responses. Thus, it is critical to identify compounds able to inhibit virus replication and thwart the inflammatory reaction. Here, we show that the plasma levels of the immunoregulatory neuropeptide VIP are elevated in patients with severe COVID-19, correlating with reduced inflammatory mediators and with survival on those patients. In vitro, VIP and PACAP, highly similar neuropeptides, decreased the SARS-CoV-2 genome replication in human monocytes and viral production in lung epithelial cells, also reducing cell death. Both neuropeptides inhibited the production of proinflammatory mediators in lung epithelial cells and in monocytes. VIP and PACAP prevented in monocytes the SARS-CoV-2-induced activation of NF-kB and SREBP1 and SREBP2, transcriptions factors involved in proinflammatory reactions and lipid metabolism, respectively. They also promoted CREB activation, a transcription factor with antiapoptotic activity and negative regulator of NF-kB. Specific inhibition of NF-kB and SREBP1/2 reproduced the anti-inflammatory, antiviral and cell death protection effects of VIP and PACAP. Our results support further clinical investigations of these neuropeptides against COVID-19. Amoxicillin-resistant Streptococcus pneumoniae can be resensitized by targeting the mevalonate pathway as indicated by sCRilecs-seq Antibiotic resistance in the important opportunistic human pathogen Streptococcus pneumoniae is on the rise. This is particularly problematic in the case of the {beta}-lactam antibiotic amoxicillin, which is the first-line therapy. It is therefore crucial to uncover targets that would kill or resensitize amoxicillin-resistant pneumococci. To do so, we developed a genome-wide, single-cell based, gene silencing screen using CRISPR interference called sCRilecs-seq (subsets of CRISPR interference libraries extracted by fluorescence activated cell sorting coupled to next generation sequencing). Since amoxicillin affects growth and division, sCRilecs-seq was used to identify targets that are responsible for maintaining proper cell size. Our screen revealed that downregulation of the mevalonate pathway leads to extensive cell elongation. Further investigation into this phenotype indicates that it is caused by insufficient transport of cell wall precursors across the cell membrane due to a limitation in the production of undecaprenyl phosphate (Und-P), the lipid carrier responsible for this process. The data suggest that whereas peptidoglycan synthesis continues even with reduced Und-P levels, cell constriction is specifically halted. We successfully exploited this knowledge to create a combination treatment strategy where the FDA-approved drug clomiphene, an inhibitor of Und-P synthesis, is paired up with amoxicillin. Our results show that clomiphene potentiates the antimicrobial activity of amoxicillin and that combination therapy resensitizes amoxicillin-resistant S. pneumoniae. These findings could provide a starting point to develop a solution for the increasing amount of hard-to-treat amoxicillin-resistant pneumococcal infections. Ineffectual AEC1 differentiation from KRT8hi transitional state without fibrosis is associated with fatal COVID-19 ARDS ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. 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. Resetting of the 24-nt siRNA landscape in rice zygotes BackgroundThe zygote, a totipotent stem cell, constitutes a critical stage of the life cycle of sexually reproducing organisms. It is produced by the fusion of two differentiated cells -- the egg and sperm, which in plants have radically different siRNA transcriptomes from each other and from multicellular embryos. Due to technical challenges, the epigenetic changes that accompany the zygotic transition are poorly understood.

ResultsHere, we characterized the small RNA transcriptome of rice zygotes. We found widespread redistribution of 24-nt siRNAs relative to gametes, including absence of sperm signature siRNAs, reduction at egg signature siRNA loci, and upregulation at seedling signature siRNA loci. Loci with reduced siRNAs in zygote relative to egg were gene-distal and heterochromatic, while loci with increased siRNAs relative to egg had a similar genomic distribution to canonical siRNA loci. Although both egg and zygote siRNA loci had higher mCHH level in wildtype than in drm2 embryo, zygote but not egg siRNA loci were associated with hypermethylation in mature embryo. A small fraction of siRNA loci (~1%) called siren loci accounted for 60% of all siRNAs within zygote siRNA loci, that likely arose from maternal carryover as they had similarly abundant siRNAs in egg; these siren loci were not associated with embryo hypermethylation.

ConclusionsTaken together, our results indicate re-distribution of siRNAs in rice zygotes towards the canonical vegetative profile, that are consistent with the initiation of resetting of the gametic epigenome before the first embryonic division. Microvesicles Transfer Mitochondria and Increase Mitochondrial Function in Brain Endothelial Cells We have demonstrated, for the first time that microvesicles, a sub-type of extracellular vesicles (EVs) derived from hCMEC/D3: a human brain endothelial cell (BEC) line transfer polarized mitochondria to recipient BECs in culture and to neurons in mice acute brain cortical and hippocampal slices. This mitochondrial transfer increased ATP levels by 100 to 200-fold (relative to untreated cells) in the recipient BECs exposed to oxygen-glucose deprivation, an in vitro model of cerebral ischemia. We have also demonstrated that transfer of microvesicles, the larger EV fraction, but not exosomes resulted in increased mitochondrial function in hypoxic endothelial cultures. Gene ontology and pathway enrichment analysis of EVs revealed a very high association to glycolysis-related processes. In comparison to heterotypic macrophage- derived EVs, BEC-derived EVs demonstrated a greater selectivity to transfer mitochondria and increase endothelial cell survival under ischemic conditions.

HighlightsO_LIMicrovesicles transfer mitochondria to endothelial cells and brain slice neurons
C_LIO_LIMitochondrial transfer increased ATP in ischemic brain endothelial cells (BECs)
C_LIO_LITransfer of microvesicles increased mitochondrial function in hypoxic BECs
C_LIO_LITransfer of exosomes did not affect mitochondrial function in hypoxic BECs
C_LIO_LIHomotypic BEC-derived EVs result in greater ATP levels in the recipient BECs
C_LI Foraging with friends, moving with anyone: effects of the social environment on movement-integrated habitat selection O_LIMovement links the distribution of habitats with the social environment of animals using those habitats; yet integrating movement, habitat selection, and socioecology remains an opportunity for further study.
C_LIO_LIHere, our objective was to disentangle the roles of habitat selection and social association as drivers of collective movement in a gregarious ungulate. To accomplish this objective, we (1) assessed whether socially familiar individuals form discrete social communities and whether social communities have high spatial, but not necessarily temporal, overlap; and (2) we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection analysis.
C_LIO_LIWe used social network analysis to assign individuals to social communities and determine short and long-term social preference among individuals. Using integrated step selection functions (iSSF), we then modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.
C_LIO_LIBased on assignment of individuals to social communities and home range overlap analyses, individuals assorted into discrete social communities, and these communities had high spatial overlap. By unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals foraged with more familiar individuals, but moved collectively with any between foraging patches.
C_LIO_LIOur study demonstrates that social behaviour and space use are inter-related based on spatial overlap of social communities and movement-dependent habitat selection. Movement, habitat selection, and social behaviour are linked in theory. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.
C_LI α-catenin links integrin adhesions to F-actin to regulate ECM mechanosensing and rigidity-dependence Both cell-cell and cell-matrix adhesions are regulated by mechanical signals, but the mechanobiological processes that mediate the crosstalk between these structures are poorly understood. Here we show that - catenin, a mechanosensitive protein that is classically associated with cadherin-based adhesions, directly interacts with and regulates integrin adhesions. -catenin is recruited to the edges of mesenchymal cells, where it interacts with F-actin. This is followed by mutual retrograde flow of -catenin and F-actin from the cell edge, during which -catenin interacts with vinculin within integrin adhesions. This interaction affects adhesion maturation, stress-fiber assembly, and force transmission to the matrix. In epithelial cells, -catenin is present in cell-cell adhesions and absent from cell-matrix adhesions. However, when these cells undergo epithelial-to-mesenchymal transition, -catenin transitions to cell-matrix adhesions, where it facilitates proper mechanosensing. This is highlighted by the ability of -catenin-depleted cells to grow on soft matrices. These results suggest a dual role of -catenin in mechanosensing, through both cell-cell and cell-matrix adhesions. Mechanical coupling of supracellular stress amplification and tissue fluidization during exit from quiescence Cellular quiescence is a state of reversible cell cycle arrest that is associated with tissue dormancy. Timely regulated entry into and exit from quiescence is important for processes such as tissue homeostasis, tissue repair, stem cell maintenance, developmental processes and immunity. Here we show that quiescent human keratinocyte monolayers contain an actinomyosin-based system that facilitates global viscoelastic flow upon serum-stimulated exit from quiescence. Mechanistically, serum exposure causes rapid amplification of pre-existing contractile sites leading to a burst in monolayer stress that subsequently drives monolayer fluidization. The stress magnitude after quiescence exit correlates with quiescence depth, and a critical stress level must be reached to overcome the cell sheet displacement barrier. The study shows that static quiescent cell monolayers are mechanically poised for motility and identifies global stress amplification as a mechanism for tissue fluidization. Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors - Dependencies and Novel Pitfalls Personalized Oncology is a rapidly evolving area and offers cancer patients therapy options more specific than ever. Yet, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation Projection (UMAP)) on three datasets of metastases (n=682 samples) with three different data transformations (unprocessed, log10 as well as log10+1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n=616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between site of resection and cluster formation outcome could be demonstrated, neither for datasets consisting of solely metastasis nor mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results indicate only minor transcriptional differences for metastases and corresponding primary tumors. Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers By using TGIRT-seq, we identified >8,500 short full-length excised linear intron (FLEXI) RNAs in human cells. Subsets of FLEXIs accumulated in a cell-type specific manner, and [~]200 corresponded to agotrons or mirtrons or encoded snoRNAs. Analysis of CLIP-seq datasets identified potential interactions between FLEXIs and >100 different RNA-binding proteins (RBPs), 53 of which had binding sites in [&ge;]30 different FLEXIs. In addition to proteins that function in RNA splicing, these 53 RBPs included transcription factors, chromatin remodeling proteins, and cellular growth regulators that impacted FLEXI host gene alternative splicing and/or mRNA levels in knockdown datasets. We computationally identified six groups of RBPs whose binding sites were enriched in different subsets of FLEXIs: AGO1-4 and DICER associated with agotrons and mirtrons; AATF, DKC1, NOLCI, and SMNDC1 associated with snoRNA-encoding FLEXIs; two different combinations of alternative splicing factors found in stress granules; and two novel RBP-intron combinations, one including LARP4 and PABC4, which function together in the cytoplasm to regulate ribosomal protein translation. Our results suggest a model in which proteins involved in transcriptional regulation, alternative splicing, or post-splicing secondary functions bind and stabilize cell-type specific subsets of FLEXIs that perform different biological functions and have potential utility as biomarkers. Outer hair cell electro-mechanical power conversion Outer hair cells are the cellular motors in the mammalian inner ear responsible for sensitive high-frequency hearing. Motor function requires expression of the protein prestin in the OHC lateral membrane and mechano-electrical transduction in the apical hair bundle. In the present report, electrical power consumption and mechanical power output are determined using previously published voltage clamp data from isolated OHCs and membrane patches. Results reveal that power output by the prestin-motor complex peaks at a best frequency much higher than implied by the low-pass character of nonlinear capacitance, and much higher than the whole-cell resistive-capacitive corner frequency. High frequency power output is enabled by a -90{degrees} shift in the phase of prestin-dependent electrical charge displacement, manifested electrically as emergence of imaginary-valued nonlinear capacitance. 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. Many ways to stick the landing: novel righting strategies allow spotted lanternfly nymphs to land on diverse substrates Unlike large animals, insects and other very small animals are so unsusceptible to impact-related injuries that they can use falling for dispersal and predator evasion. Reorienting to land upright can mitigate lost access to resources and predation risk. Such behaviors are critical for the spotted lanternfly (SLF) (Lycorma delicatula), an invasive, destructive insect pest spreading rapidly in the US. High-speed video of SLF nymphs released under different conditions showed that these insects self-right using both active midair righting motions previously reported for other insects, and novel post-impact mechanisms that take advantage of their ability to experience near-total energy loss on impact. Unlike during terrestrial self-righting, in which an animal initially at rest on its back uses appendage motions to flip over, SLF nymphs impacted the surface at varying angles and then self-righted during the rebound using coordinated body rotations, foot-substrate adhesion, and active leg motions. These previously-unreported strategies were found to promote disproportionately upright, secure landings on both hard, flat surfaces and tilted, compliant host plant leaves. Our results highlight the importance of examining biomechanical phenomena in ecologically-relevant contexts, and show that, for small animals, the post-impact bounce period can be critical for achieving an upright landing. FACT regulates pluripotency through distal regulation of gene expression in murine embryonic stem cells The FACT complex is a conserved histone chaperone with essential roles in transcription and histone deposition. FACT is essential in pluripotent and cancer cells, but otherwise dispensable for most mammalian cell types. FACT deletion or inhibition can block induction of pluripotent stem cells, yet the mechanism through which FACT regulates cell fate decisions remains unclear. To determine this mechanism, we used inducible depletion of FACT subunit SPT16 in murine embryonic stem cells paired with genomic factor localization, nascent transcription, and chromatin accessibility analyses. Over a timecourse of SPT16 depletion, nucleosomes invade loci bound by master pluripotency factors and gene-distal DNaseI hypersensitive sites. Simultaneously, transcription of Pou5f1 (OCT4), Sox2, Nanog, and enhancer RNAs produced at the genes' associated enhancers are downregulated, suggesting that FACT regulates expression of the pluripotency factors themselves. We find that FACT maintains cellular pluripotency through a precise nucleosome-based regulatory mechanism for appropriate expression of both coding and non-coding transcripts associated with pluripotency. Comparative proteome signatures of trace samples by multiplexed Data-Independent Acquisition Single cell transcriptomics has revolutionized our understanding of basic biology and disease. Since transcript levels often do not correlate with protein expression, it is crucial to complement transcriptomics approaches with proteome analyses at single cell resolution. Despite continuous technological improvements in sensitivity, mass spectrometry-based single cell proteomics ultimately faces the challenge of reproducibly comparing the protein expression profiles of thousands of individual cells. Here, we combine two hitherto opposing analytical strategies, DIA and Tandem-Mass-Tag (TMT)-multiplexing, to generate highly reproducible, quantitative proteome signatures from ultra-low input samples. While conventional, data-dependent shotgun proteomics (DDA) of ultra-low input samples critically suffers from the accumulation of missing values with increasing sample-cohort size, data-independent acquisition (DIA) strategies do usually not take full advantage of isotope-encoded sample multiplexing. We developed a novel, identification-independent proteomics data-analysis pipeline that allows to quantitatively compare DIA-TMT proteome signatures across hundreds of samples independent of their biological origin, and to identify cell types and single protein knockouts. We validate our approach using integrative data analysis of different human cell lines and standard database searches for knockouts of defined proteins. These data establish a novel and reproducible approach to markedly expand the numbers of proteins one detects from ultra-low input samples, such as single cells. Patterns of connectome variability in autism across five functional activation tasks. Findings from the LEAP project BackgroundAutism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioural, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterise heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

MethodsAll analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism and typically developing controls (TD) between 6 and 30 years of age. We employed a novel task-potency approach which combines the unique aspects of both resting-state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioural data.

ResultsDeviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p<0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p<0.002). The CCA identified significant and robust brainbehavior covariation between functional connectivity atypicality and autism-related behavioral features.

ConclusionsIndividuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show, moving forward, sophisticated modeling methods such as task-potency and normative modeling will prove key to unravelling complex heterogeneous conditions like autism. Investigation of ongoing recombination through genealogical reconstruction for SARS-CoV-2 AO_SCPLOWBSTRACTC_SCPLOWThe evolutionary process of genetic recombination has the potential to rapidly change the properties of a viral pathogen, and its presence is a crucial factor to consider in the development of treatments and vaccines. It can also significantly affect the results of phylogenetic analyses and the inference of evolutionary rates. The detection of recombination from samples of sequencing data is a very challenging problem, and is further complicated for SARS-CoV-2 by its relatively slow accumulation of genetic diversity. The extent to which recombination is ongoing for SARS-CoV-2 is not yet resolved. To address this, we use a parsimony-based method to reconstruct possible genealogical histories for samples of SARS-CoV-2 sequences, which enables us to pinpoint specific recombination events that could have generated the data. We propose a statistical framework for disentangling the effects of recurrent mutation from recombination in the history of a sample, and hence provide a way of estimating the probability that ongoing recombination is present. We apply this to samples of sequencing data collected in England and South Africa, and find evidence of ongoing recombination. Manipulating the microbiome alters regenerative outcomes in Xenopus laevis tadpoles via lipopolysaccharide signalling Xenopus laevis tadpoles can regenerate functional tails, containing spinal cord, notochord, muscle, fin, blood vessels and nerves, except for a brief refractory period at around one week of age. At this stage, amputation of the tadpoles tail may either result in scarless wound healing, or the activation of a regeneration programme, which replaces the lost tissues. We recently demonstrated a link between bacterial lipopolysaccharides and successful tail regeneration in refractory stage tadpoles, and proposed that this could result from lipopolysaccharides binding to Toll-like receptor 4 (TLR4). Here, we have used 16S rRNA sequencing to show that the tadpole skin microbiome is highly variable between sibships and that the community can be altered by raising embryos in the antibiotic gentamicin. Six gram-negative genera, including Delftia and Chryseobacterium, were over-represented in tadpoles that underwent tail regeneration. Lipopolysaccharides purified from a commensal Chryseobacterium spp. XDS4, an exogenous Delftia spp. or Escherichia coli could significantly increase the number of antibiotic-raised tadpoles that attempted regeneration. Conversely, the quality of regeneration was impaired in native-raised tadpoles exposed to the antagonistic lipopolysaccharide of Rhodobacter sphaeroides. Editing TLR4 using CRISPR/Cas9 also reduced regeneration quality, but not quantity, at the level of the cohort. However, we found that the editing level of individual tadpoles was a poor predictor of regenerative outcome. In conclusion, our results suggest that variable regeneration in refractory stage tadpoles depends at least in part on the skin microbiome and lipopolysaccharide signalling, but that signalling via TLR4 cannot account for all of this effect.