Trophic resources of the edaphic microarthropods: a worldwide review of the empirical evidence Ecosystem sustainable use requires reliable information about its biotic and abiotic structure and functioning. Accurate knowledge of trophic relations is central for the understanding of ecosystem dynamics, which in turn, is essential for food web stability analyzes and the development of sustainable practices. There is a rapid growth in the knowledge on how belowground biodiversity regulates the structure and functioning of terrestrial ecosystems. Although, the available information about trophic relationships is hard to find and fragmented. This gathering the information available worldwide about the food resources of soil mesofauna. From the 3105 hits of the initial search on food resources of soil microarthropods, only a total of 196 published works related particular species, genera, and families to particular trophic resources, the majority of them dealing with soils of the Palearctic region. From the 196 publications we extracted 3009 records relating specific taxonomic groups to their trophic resources, 20% mention saprophytic fungi as a food resource, 16% cite microfauna, 11% mention bacteria, 10% litter and 5% cite Mycorrhizal fungi. The available information was highly skewed, the 73.71% comes from Acari, and within these, 50.62% correspond just to Sarcoptiformes. For Collembola, the literature is scarce, the majority coming from Arthropleona. This review highlights the general lack of information relating species, genera, and families of the soil mesofauna to specific trophic resources. It also highlights that available research mostly comes from European sites, with the use of trophic resources by the mesofauna of the majority of the soils in other parts of the world still largely unknown.
Worldwide analysis of reef surveys sorts coral taxa by (adaptive) response to heat stress Coral reefs around the world are under threat due to widespread decline of hard corals caused by anomalous heat waves. Different coral taxa are known to have different sensitivities to heat. However, little is known about how long-term effects of heat exposure differ between coral taxa, nor in particular how such effects might drive adaptive processes. Here, we combined worldwide reef survey data with remotely sensed thermal anomalies to evaluate how local rates of taxa-specific coral cover were associated with heat stress. We found a negative association between coral cover and heat stress: weaker for massive and encrusting Poritidae, for meandroid Favidae and Mussidae; and stronger for branching, tabular and corymbose Acroporidae. Additionally, we found that coral cover decline driven by recent heat stress (measured as the year before a survey) was mitigated by long-term past heat (measured since 1985) in branching, tabular and corymbose Acroporidae and Pocilloporidae, but not in Poritidae, Favidae and Mussidae. This mitigation of coral decline was not observed under the effect of short-term past heat (measured during the two previous years), suggesting that these presumptive adaptive processes are the result of evolutionary adaptation, rather than of physiological acclimatization. We finally queried the Coral Trait Database to characterize morphological, physiological and reproductive traits of different taxa showing similar heat-responses. Further genomics studies should confirm the evolutionary origin of such divergent adaptive responses to heat stress.
SyMBac: Synthetic Micrographs for Training Deep Neural Networks for Accurate Segmentation of Bacterial Cells We present a novel method of bacterial image segmentation using machine learning based on Synthetic Micrographs of Bacteria (SyMBac). SyMBac allows for rapid, automatic creation of arbitrary amounts of training data that combines detailed models of cell growth, physical interactions, and microscope optics to create synthetic images which closely resemble real micrographs, with access to the ground truth positions of cells. This approach provides the following major advantages: (1) Synthetic training data can be generated virtually instantly, and on demand; (2) it is accompanied by perfect ground truth information, which also means large sets of training data can be generated without the need for curation; (3) Biological ground truth and imaging effects can be tuned independently, enabling easy adaptation to different biological conditions, imaging platforms, and imaging modalities. Machine-learning models trained on SyMBac data generate more accurate and precise cell masks than those trained on human annotated data. This enables precise analysis of cell size regulation along changing conditions in a growing bacterial cell culture, revealing novel insights about the physiological dynamics of individual bacterial cells during entry and exit from dormancy.

Author SummaryMicroscopy is integral to microbiology, but accurate processing of microscopy data has been a major obstacle towards quantitative analysis of microbial physiology. The small size of bacterial cells and the comparable size of the microscopes point-spread function has made it virtually impossible to accurately determine the size, shape, and intensity of individual cells from their images. The difficulties of accurately identifying the boundaries of a cell from their image using computational thresholding or human annotators also limits the performance of recently developed machine-learning based image segmentation approaches, since these toolsets rely on the quality and quantity of the ground truth in the training data. In response to all these problems, we have developed SyMBac: Synthetic Micrographs of Bacteria. SyMBac is a tool which rapidly generates arbitrary amounts of synthetic training data of bacteria growing in microfluidic devices. Synthetic images generated by SyMBAc are accompanied by perfect ground truth information, which means large sets of training data can be generated without the need for curation. Our benchmarking results show that deep-learning algorithms trained with SyMBac are far superior, in terms of accuracy and precision of segmentation, compared to the same models trained on human annotated or computationally segmented data. This will significantly advance the field of quantitative microbiology. Host Chitinase 3-like-1 is a Universal Therapeutic Target for SARS-CoV-2 Viral Variants in COVID 19 COVID 19 is the disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2; SC2) which has caused a world-wide pandemic with striking morbidity and mortality. Evaluation of SC2 strains demonstrated impressive genetic variability and many of these viral variants are now defined as variants of concern (VOC) that cause enhanced transmissibility, decreased susceptibility to antibody neutralization or therapeutics and or the ability to induce severe disease. Currently, the delta ({delta}) and omicron (o) variants are particularly problematic based on their impressive and unprecedented transmissibility and ability to cause break through infections. The delta variant also accumulates at high concentrations in host tissues and has caused waves of lethal disease. Because studies from our laboratory have demonstrated that chitinase 3-like-1 (CHI3L1) stimulates ACE2 and Spike (S) priming proteases that mediate SC2 infection, studies were undertaken to determine if interventions that target CHI3L1 are effective inhibitors of SC2 viral variant infection. Here we demonstrate that CHI3L1 augments epithelial cell infection by pseudoviruses that express the alpha, beta, gamma, delta or omicron S proteins and that the CHI3L1 inhibitors anti-CHI3L1 and kasugamycin inhibit epithelial cell infection by these VOC pseudovirus moieties. Thus, CHI3L1 is a universal, VOC-independent therapeutic target in COVID 19. Robust and annotation-free analysis of alternative splicing using short-read scRNA-seq data Although alternative splicing is a fundamental and pervasive aspect of gene expression in higher eukaryotes, it is often omitted from single-cell studies due to quantification challenges inherent to commonly used short-read sequencing technologies. Here, we undertake the analysis of alternative splicing across numerous diverse murine cell types from two large-scale single-cell datasets--the Tabula Muris and BRAIN Initiative Cell Census Network--while accounting for understudied technical artifacts and unannotated isoforms. We find strong and general cell-type-specific alternative splicing, complementary to total gene expression but of similar discriminatory value, and identify a large volume of novel isoforms. We specifically highlight splicing variation across different cell types in primary motor cortex neurons, bone marrow B cells, and various epithelial cells; and show that the implicated transcripts include many genes which do not display total expression differences. To elucidate the regulation of alternative splicing, we build a custom predictive model based on splicing factor activity, recovering several known interactions while generating new hypotheses, including potential regulatory roles for novel alternative splicing events in critical genes including Khdrbs3 and Rbfox1. We make our results available using public interactive browsers to spur further exploration by the community. Genetic coupling of life-history and aerobic performance in Atlantic salmon indicates potential constrains on life-history evolution A better understanding of the genetic and phenotypic architecture underlying life-history variation is a longstanding aim in biology. Theories suggest energy metabolism determines life-history variation by modulating resource acquisition and allocation trade-offs, but the genetic underpinnings of the relationship and its dependence on ecological conditions have rarely been demonstrated. The strong genetic determination of age-at-maturity by two unlinked genomic regions (vgll3 and six6) makes Atlantic salmon (Salmo salar) an ideal model to address these questions. Using more than 250 juveniles in common garden conditions, we quantified the covariation between metabolic phenotypes -standard and maximum metabolic rates (SMR and MMR), and aerobic scope (AS) - and the life-history genomic regions and tested if food availability modulates the relationships. We found that the early maturation genotype in vgll3 was associated with higher MMR and consequently AS. Additionally, MMR exhibited physiological epistasis; it was decreased when late maturation genotypes co-occurred in both genomic regions. Contrary to our expectation, the life-history genotypes had no effects on SMR. Further, food availability had no effect on the genetic covariation, suggesting a lack of genotype-by-environment interactions. Our results provide insights on the key organismal processes that link energy use at the juvenile-stage to age-at-maturity, indicating potential mechanisms by which metabolism and life-history can coevolve. The N terminus of adhesion G protein-coupled receptor GPR126/ADGRG6 as allosteric force integrator The adhesion G protein-coupled receptor (aGPCR) GPR126/ADGRG6 plays an important role in several physiological functions, such as myelination or peripheral nerve repair. This renders the receptor an attractive pharmacological target. GPR126 is a mechano-sensor that translates binding of extracellular matrix (ECM) molecules to its N terminus into a metabotropic intracellular signal. To date, the structural requirements and the character of the forces needed for this ECM-mediated receptor activation are largely unknown.

In this study we provide this information by combining classic second messenger detection with single cell atomic force microscopy. We establish a monoclonal antibody targeting the N terminus to stimulate GPR126 and compare it to the activation through its known ECM ligands collagen IV and laminin 211. As each ligand uses a distinct mode of action, the N terminus can be viewed as an allosteric module that can fine-tune receptor activation in a context-specific manner. Embedded 3D printing in self-healing annealable composites for precise patterning of functionally mature human neural constructs Human in vitro models of neural tissue with controllable cellular identity, tunable microenvironment, and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing in jammed microgel supports (i.e., granular gels) holds great promise as it allows precise and programmable patterning of extremely soft and compliant tissue constructs. However, in contrast to the vast material landscape available for bulk hydrogels, granular printing support formulations are restricted to a handful of materials without the ability for facile adjustment of biofunctional properties of the cellular microenvironment. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, we present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise freeform patterning of human stem cells and consequent generation and long-term maintenance of mature subtype-specific neurons that extend projections within the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular channels. Due to its modularity, SHAPE biomanufacturing toolbox not only offers a solution for functional modeling of mechanically sensitive neural constructs, but also has potential to be applied to a wide range of biomaterials with different crosslinking mechanisms to model tissues and diseases where recapitulation of complex architectural features and topological cues is essential. Comparison of hybrid learning and remote education in the implementation of the 'Adopt a Microorganism' methodology The Internet has changed the way teachers and students access information and build knowledge. The recent COVID-19 pandemic has created challenges for both teachers and students and a demand for new methodologies of remote learning. In the life sciences, mixing online content with practical activities represents an even greater challenge. In microbiology, the implementation of an active teaching methodology, the #Adopt project, based on the social network Facebook(R), represents an excellent option for connecting remote education with classroom activities. In 2020, the version applied in high school, "Adopt a Microorganism", was adapted to meet the demands of emergency remote education owing to the suppression of face-to-face activities caused by the pandemic. In the present study, we assessed how the change in methodology impacted the discourse richness of students from high school integrated with technical education in the Business Administration program of the Federal Institute of Sao Paulo, Sorocaba Campus. Three questionnaires related to the groups of microorganisms (Archaea, Bacteria, Virus, Fungi, and Protozoan) were applied. The students responses in the 2019 and 2020 classes were compared concerning content richness and multiplicity of concepts through the application of the Shannon diversity index, an approach that is generally used to assess biodiversity in different environments. The observed results suggest that remote learning provided students with a conceptual basis and richness of content equivalent to that achieved by students subjected to the hybrid teaching model. In conclusion, this study suggests that the #Adopt project methodology increases students discourse richness in microbiology even without face-to-face traditional classes. 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. The neurogenic fate of the hindbrain boundaries relies on Notch-dependent asymmetric cell divisions The generation of cell diversity in the central nervous system occurs during embryogenesis and requires a precise balance between cell proliferation, commitment to specific fates, and further neuronal differentiation. The cellular and molecular mechanisms regulating this balance in the embryonic brain are still poorly understood. Here we study how the neurogenic capacity in the embryonic hindbrain is spatiotemporally allocated, and how the fate and the growth of the hindbrain boundary cells are regulated. By generating a CRISPR-based knock-in zebrafish transgenic line to specifically label the hindbrain boundaries, we unveiled that boundary cells undergo a functional transition to become neurogenic during hindbrain segmentation concurrently as they maintain the progenitor cell pool. Boundary cells engaged in neurogenesis coinciding with the onset of Notch signaling, which triggered their asymmetrical cell division. Our findings reveal that distinct neurogenic phases take place during hindbrain growth and suggest that boundary cells contribute to refine the final number, identity, and proportion of neurons in the brain.

SUMMARYHindbrain boundary cells undergo a functional transition to become neurogenic concurrently as they are maintained as a progenitor cell pool. This involves a behavioral switch from symmetrically dividing progenitor cells to asymmetrically dividing progenitors, which depends on Notch-activity. METHYLOME DYNAMICS UPON PROTEASOME INHIBITION BY THE PSEUDOMONAS 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. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. A distinctive neural nexus predicts Braille reading proficiency in blind individuals Natural Braille reading, a demanding cognitive skill, poses a huge challenge for the brain network of the blind. Here, with behavioral measurement and functional MRI imaging data, we pinpointed the neural pathway and investigated the neural mechanisms of individual differences in Braille reading in late blindness. Using resting state fMRI, we identified a distinct neural link between the higher-tier  visual cortex--the lateral occipital cortex (LOC), and the inferior frontal cortex (IFC) in the late blind brain, which is significantly stronger than sighted controls. Individual Braille reading proficiency positively correlated with the left-lateralized LOC-IFC functional connectivity. In a natural Braille reading task, we found an enhanced bidirectional information flow with a stronger top-down modulation of the IFC-to-LOC effective connectivity. Greater top-down modulation contributed to higher Braille reading proficiency via a broader area of task-engaged LOC. Together, we established a model to predict Braille reading proficiency, considering both functional and effective connectivity of the LOC-IFC pathway. This  two-tale model suggests that developing the underpinning neural circuit and the top-down cognitive strategy contributes uniquely to superior Braille reading performance.

SIGNIFICANCE STATEMENTFor late blind humans, one of the most challenging cognitive skills is natural Braille reading. However, little is known about the neural mechanisms of significant differences in individual Braille reading performance. Using functional imaging data, we identified a distinct neural link between the left lateral occipital cortex (LOC) and the left inferior frontal cortex (IFC) for natural Braille reading in the late blind brain. To better predict individual Braille reading proficiency, we proposed a linear model with two variables of the LOC-IFC link: the resting-state functional connectivity and the task-engaged top-down effective connectivity. These findings suggest that developing the underpinning neural pathway and the top-down cognitive strategy contributes uniquely to superior Braille reading performance. Discovery of highly potent pancoronavirus fusion inhibitors that also effectively inhibit COVID-19 variants from the UK (Alpha), South Africa (Beta), and India (Delta) We report here the discovery of several highly potent small molecules that showed low nM potency against SARS-CoV (IC50: as low as 13 nM), SARS-CoV-2 (IC50: as low as 23 nM), and MERS-CoV (IC50: as low as 76 nM) in pseudovirus based assays with excellent selectivity indices (SI: as high as > 5000) demonstrating their pancoronavirus inhibition. Some compounds also show 100% inhibition of CPE (IC100) at 1.25 {micro}M against an authentic SARS-CoV-2 (US_WA-1/2020). Furthermore, the most active inhibitors also potently inhibited variants of concerns (VOCs), such as the UK (B.1.1.7), South Africa (B.1.351), and Delta variant (B.1.617.2), originated in India. We confirmed that one of the potent inhibitors binds to the prefusion spike protein trimer of SARS-CoV-2 by SPR. Besides, we showed that they inhibit virus-mediated cell-cell fusion. The ADME data of one of the most active inhibitors, NBCoV1, show drug-like properties. In vivo PK of NBCoV1 in rats demonstrated excellent half-life (t1/2) of 11.3 h, mean resident time (MRT) of 14.2 h, and oral bioavailability. We expect the lead inhibitors to pave the way for further development to preclinical and clinical candidates. Force profile of the two-handed hardstyle kettlebell swing performed by an RKC-certified Instructor BackgroundThe effects of hardstyle kettlebell training are increasingly cited in strength and conditioning research, yet reference data from a proficient swing is scarce. The aim of this exploratory study was to investigate the force profile of a two-handed hardstyle swing performed by a Russian Kettlebell Challenge (RKC) instructor.

MethodsThe subject is a 44-year-old male, body mass 75.6 kg, height 173.5 cm, with six years of regular hardstyle training experience. Two-handed hardstyle swings were performed with a series of incremental mass kettlebells (8-68 kg). Ground reaction force (GRFs) was obtained from a floor-mounted force platform. Force-time curves (FTCs), peak force, forward force, rate of force development (RFD) and swing cadence were investigated.

ResultsData revealed the FTC of a proficient swing is highly consistent and dominated by a single force peak (mean SD = 47 N), with a profile that remained largely unchanged to 24 kg. Pearson correlation analysis revealed a very strong positive correlation in peak force with kettlebell mass (r = 0.95), which increased disproportionately from the lightest to heaviest kettlebells; net peak force increased from 8.36 {+/-} 0.75 N.kg-1 (0.85 x BW) to 12.82 {+/-} 0.39 N.kg-1 (1.3x BW). There was a strong negative correlation between RFD and kettlebell mass (r = 0.82) that decreased from 39.2 N.s-1.kg-1 to 21.5 N.s-1.kg-1. There was a very strong positive correlation in forward ground reaction force with kettlebell mass (r = 0.99), expressed as a ratio of vertical ground reaction, that increased from 0.092 (9.2%) to 0.205 (20.5%). Swing cadence exceeded 40 swings per minute (SPM) with all kettlebells.

ConclusionOur findings challenge some of the popular beliefs of the hardstyle kettlebell swing. Consistent with hardstyle practice, and previous kinematic analysis of expert and novice, force-time curves show a characteristic single large force peak, differentiating passive from active shoulder flexion. Ground reaction force did not increase proportionate to kettlebell mass, with a magnitude of forward force smaller than described in practice. These results could be useful for coaches and trainers wanting to improve athletic performance, and healthcare providers using the kettlebell swing for therapeutic purposes. Findings from this study were used to inform the BELL Trial, a pragmatic controlled trial of kettlebell training with older adults. www.anzctr.org.au ACTRN12619001177145. Positive supercoiling favors transcription elongation through lac repressor-mediated DNA loops Some proteins, like the lac repressor (LacI), mediate long-range loops that alter DNA topology and create torsional barriers. During transcription, RNA polymerase generates supercoiling that may facilitate passage through such barriers. We monitored E. coli RNA polymerase progress along templates in conditions that prevented, or favored, LacI-mediated DNA looping. Tethered particle motion measurements revealed that RNA polymerase paused longer at unlooped LacI obstacles or those barring entry to a loop than those barring exit from the loop. Enhanced dissociation of a LacI roadblock by the positive supercoiling generated ahead of a transcribing RNA polymerase within a torsion-constrained DNA loop may be responsible. In support of this, RNA polymerase transcribed a looped segment more slowly than an unlooped segment and paused more briefly at LacI obstacles on positively supercoiled templates, especially under increased tension (torque). Positive supercoiling propagating ahead of polymerase appears to facilitate elongation along topologically-complex, protein-coated templates. Development and Characterization of PAR-Trackers: New Tools for Detecting Poly(ADP-ribose) In Vitro and In Vivo AO_SCPLOWBSTRACTC_SCPLOWADP-ribosylation (ADPRylation) is a reversible post-translation modification resulting in the covalent attachment of ADP-ribose (ADPR) moieties on substrate proteins. Naturally-occurring protein motifs and domains, including WWEs, PBZs, and macrodomains, act as "readers" for protein-linked ADPR. Although recombinant, antibody-like ADPR detection reagents containing these readers have facilitated the detection of ADPR, they are limited in their ability to capture the dynamic nature of ADPRylation. Herein, we describe and characterize a set of poly(ADP-ribose) (PAR) Trackers (PAR-Ts) - optimized dimerization-dependent or split-protein reassembly PAR sensors in which a naturally occurring PAR binding domain, WWE, was fused to both halves of dimerization-dependent GFP (ddGFP) or split Nano Luciferase (NanoLuc), respectively. We demonstrate that these new tools allow the detection and quantification of PAR levels in extracts, living cells, and living tissues with greater sensitivity, as well as temporal and spatial precision. Importantly, these sensors detect changes in cellular ADPR levels in response to physiological cues (e.g., hormone-dependent induction of adipogenesis without DNA damage), as well as xenograft tumor tissues in living mice. Our results indicate that PAR Trackers have broad utility for detecting ADPR in many different experimental and biological systems. Predicting microbiome compositions from species assemblages through deep learning. Microbes can form complex communities that perform critical functions in maintaining the integrity of their environment or their hosts well-being. Rationally managing these microbial communities requires improving our ability to predict how different species assemblages affect the final species composition of the community. However, making such a prediction remains challenging because of our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. To overcome this challenge, here we present a deep learning framework that automatically learns the map between species assemblages and community compositions from training data only, without knowledge of any of the above processes. First, we systematically validate our framework using synthetic data generated by classical population dynamics models. Then, we apply it to experimental data of both in vitro and in vivo communities, including ocean and soil microbial communities, Drosophila melanogaster gut microbiota, and human gut and oral microbiota. In particular, we show how our framework learns to perform accurate out-of-sample predictions of complex community compositions from a small number of training samples. Our results demonstrate how deep learning can enable us to understand better and potentially manage complex microbial communities. TAK1 blockade as a therapy for retinal neovascularization Retinal neovascularization, or pathological angiogenesis in the retina, is a leading cause of blindness in developed countries. Transforming growth factor-{beta}-activated kinase 1 (TAK1) is a mitogen-activated protein kinase kinase kinase (MAPKKK) activated by TGF-{beta}1 and other pro-inflammatory cytokines. TAK1 is also a key mediator of inflammation, innate immune responses, apoptosis and tissue homeostasis and plays an important role in physiological angiogenesis. Its role in pathological angiogenesis, particularly in retinal neovascularization, remains unclear. We investigated the regulatory role of TAK1 in pathological angiogenesis in the retina. Transcriptome analysis of human retina featuring retinal neovascularization revealed enrichment of known TAK1-mediated signaling pathways. Selective inhibition of TAK1 activation by 5Z-7-oxozeaenol attenuated aberrant retinal angiogenesis in rats following oxygen-induced retinopathy. Transcriptome profiling revealed that TAK1 activation in human microvascular endothelial cells under TNF stimulation led to increase the gene expression related to cytokines and leukocyte-endothelial interaction, mainly through nuclear factor kappa B (NF{kappa}B) signaling pathways. These results reveal that inhibition of TAK1 signaling may have therapeutic value for the treatment of pathological angiogenesis in the retina. MT-MAG: Accurate and interpretable machine learning for complete or partial taxonomic assignments of metagenome-assembled genomes We propose MT-MAG, a novel machine learning-based software tool for the complete or partial hierarchically-structured taxonomic classification of metagenome-assembled genomes (MAGs). MT-MAG is capable of classifying large and diverse metagenomic datasets: a total of 245.68 Gbp in the training sets, and 9.6 Gbp in the test sets analyzed in this study. MT-MAG is, to the best of our knowledge, the first machine learning method for taxonomic assignment of metagenomic data that offers a "partial classification" option. MT-MAG outputs complete or partial classification paths, and interpretable numerical classification confidences of its classifications, at all taxonomic ranks. To assess the performance of MT-MAG, we define a "weighted classification accuracy," with a weighting scheme reflecting the fact that partial classifications at different ranks are not equally informative. For the two benchmarking datasets analyzed (genomes from human gut microbiome species, and bacterial and archaeal genomes assembled from cow rumen metagenomic sequences), MT-MAG achieves an average of 80.13% in weighted classification accuracy. At the Species level, MT-MAG outperforms DeepMicrobes, the only other comparable software tool, by an average of 35.75% in weighted classification accuracy. In addition, MT-MAG is able to completely classify an average of 67.7% of the sequences at the Species level, compared with DeepMicrobes which only classifies 47.45%. Moreover, MT-MAG provides additional information for sequences that are not completely classified at the Species level, resulting in the partial or complete classification of 95.15%, of the genomes in the datasets analyzed. In particular, MT-MAG classifies, on average, 88.84% of the test sequences to the Phylum level, 88.39% to the Class level, 86.81% to the Order level, 81.17% to the Family level, and 71.13% to the Genus level. Embracing curiosity eliminates the exploration-exploitation dilemma Balancing exploration with exploitation is seen as a mathematically intractable dilemma that all animals face. In this paper, we provide an alternative view of this classic problem that does not depend on exploring to optimize for reward. We argue that the goal of exploration should be pure curiosity, or learning for learnings sake. Through theory and simulations we prove that explore-exploit problems based on this can be solved by a simple rule that yields optimal solutions: when information is more valuable than rewards, be curious, otherwise seek rewards. We show that this rule performs well and robustly under naturalistic constraints. We suggest three criteria can be used to distinguish our approach from other theories. Quantitative analysis of gene expression on the inactive human X chromosome The human X chromosome exists in active (Xa) and inactive (Xi) states. To quantify Xi gene expression and explore its implications, we conducted RNA sequencing in two cell types from individuals with one Xa and zero to three Xis. Linear models fit the data well, indicating equal contributions from each Xi and quantifying significant Xi-driven expression changes for 124 of 406 expressed X-chromosome genes. As revealed by allele-specific expression analyses, these Xi-driven changes reflect both i) Xi transcription and ii) Xi modulation - both positive and negative - of Xa transcript levels. Incorporating population and evolutionary measures of constraint on expression levels, we identified 13 X-chromosome genes most likely to drive the phenotypic consequences of natural variation in Xi copy number. These analytics and the underlying datasets offer a foundation for understanding Turner, Klinefelter, and other sex chromosome aneuploidy syndromes, and sex-chromosome effects on health and disease in euploid males and females. Neuroinvasion and neurotropism by SARS-CoV-2 variants in the K18-hACE2 mouse Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) not only affects the respiratory tract but also causes neurological symptoms such as loss of smell and taste, headache, fatigue or severe cerebrovascular complications. Using transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) we investigated the spatiotemporal distribution and pathomorphological features in the CNS following intranasal infection with SARS-CoV-2 variants, also after prior influenza A virus infection. Apart from Omicron, we found all variants to frequently spread to and within the CNS. Infection was restricted to neurons and appeared to spread from the olfactory bulb mainly in basally orientated regions in the brain and into the spinal cord, independent of ACE2 expression and without evidence of neuronal cell death, axonal damage or demyelination. However, microglial activation, microgliosis and a mild macrophage and T cell dominated inflammatory response was consistently observed, accompanied by apoptotic death of endothelial, microglial and immune cells, without their apparent infection. Microgliosis and immune cell apoptosis indicate a potential role of microglia for pathogenesis and viral effect in COVID-19 and possible impairment of neurological functions, especially in long COVID. These data may also be informative for the selection of therapeutic candidates, and broadly support investigation of agents with adequate penetration into relevant regions of the CNS. Chromosome breaks in breast cancers occur near herpes tumor virus sequences and explain why cancer drugs stop working One explanation for why breast cancer has a relentless tendency to come back after treatment is that breast cancer phenomes are fluid, so it is difficult for therapy to target new phenotypes that arise. In breast cancer, viral interactions cause chromosome breakage and fusion, producing anaphase bridges containing two centromeres. Cell division then leads to more chromosome breaks, more mutations, and new cancer phenotypes. Analyses of public data from about 2100 breast cancers implicate Epstein-Barr virus (EBV or Human Herpes Virus 4) in the cycles that break chromosomes and produce anaphase bridges. EBV generates breakage cycles with highly fragmented chromosomes (chromothripsis) as an inherent feature. These episodes continually produce new cancer driver mutations. DNA at chromothripsis boundaries in breast cancers consistently matches EBV tumor variants. Breakpoints are often near known EBV binding sites, and breast cancer shares an EBV methylation signature with other known EBV cancers. Breast cancer breakpoints on all chromosomes cluster around the same positions as in cancers definitively associated with EBV infection (nasopharyngeal cancer and Burkitts lymphoma). The status of EBV in the microbiome and the presence of anaphase bridges are phenotypic markers of breast cancer that are not explicitly targeted by chemotherapy. The breast cancer phenome continually supplies new cancer driver genes that foster breast cancer recurrence.

SummaryBreaks in breast cancer chromosomes and in fragments of anaphase bridges occur mainly near regions that resemble Epstein-Barr virus (EBV) tumor variants

Extensive breaks are an inherent outcome of anaphase bridges and the reassembly of highly fragmented chromosomes continually generates new cancer driver mutations and new cancer phenotypes.

Treatment does not explicitly target the underlying breakage and reassembly cycles so breast cancer often comes back.

The breast cancer phenome is not fixed and can continuously generate new phenotypes

Graphical Abstract

O_FIG O_LINKSMALLFIG WIDTH=154 HEIGHT=200 SRC="FIGDIR/small/467751v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@6537cforg.highwire.dtl.DTLVardef@132fa50org.highwire.dtl.DTLVardef@1cfcb04org.highwire.dtl.DTLVardef@11979aa_HPS_FORMAT_FIGEXP  M_FIG C_FIG A unified view of low complexity regions (LCRs) across species Low-complexity regions (LCRs) in proteins are important for higher-order assemblies of organisms, yet we lack a unified view of their sequences, features, relationships, and functions. Here, we use dotplots and dimensionality reduction to systematically define LCR type/copy relationships and create a map of LCR sequence space capable of integrating LCR features and functions. By defining LCR relationships across the proteome, we provide insight into how LCR type and copy number contribute to higher-order assemblies, such as the importance of K-rich LCR copy number for assembly of the nucleolar protein RPA43 in vivo and in vitro. With LCR maps, we reveal the underlying structure of LCR sequence space, and relate differential occupancy in this space to the conservation and emergence of higher-order assemblies, including the metazoan extracellular matrix and plant cell wall. Together, LCR relationships and maps uncovered the distribution and prevalence of E-rich LCRs in the nucleolus, and revealed previously undescribed regions of LCR sequence space with properties of higher order assemblies, including a teleost-specific T/H-rich sequence space. Thus, this unified view of LCRs enables discovery of how LCRs encode higher-order assemblies of organisms.