Genetic diversity loss in the Anthropocene More species than ever before are at risk of extinction due to anthropogenic habitat loss and climate change. But even species that are not threatened have seen reductions in their populations and geographic ranges, likely impacting their genetic diversity. Although preserving genetic diversity is key to maintaining adaptability of species, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. By bridging theories of biodiversity and population genetics, we introduce a mathematical framework to understand the loss of naturally occurring DNA mutations within decreasing habitat within a species. Analysing genome-wide variation data of 10,095 geo-referenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a power law with geographic area (the mutations-area relationship), which can predict genetic diversity loss in spatial computer simulations of local population extinctions. Given pre-21st century values of ecosystem transformations, we estimate that over 10% of genetic diversity may already be lost, surpassing the United Nations targets for genetic preservation. These estimated losses could rapidly accelerate with advancing climate change and habitat destruction, highlighting the need for forecasting tools that facilitate implementation of policies to protect genetic resources globally.
Fitness-related traits are maximized in recently introduced, slow-growing populations of a global invasive clam Many species are shifting their ranges being forced to rapidly respond to novel stressful environmental conditions. Colonizing individuals experience strong selective forces that favor the expression of life history traits notably affecting dispersal and reproductive rates in newly invaded habitats. Limited information is currently available on trait variation within the invasive range despite being critical for understanding ecological and evolutionary factors that drive the process of range expansion of invasive species. Here we evaluated life history shifts of the widely introduced Asian clam Corbicula, within its invaded range. Through an exhaustive literature search, we obtained data for 17 invasive Corbicula populations from different ecosystems worldwide. We tested the relationship between population and individual parameters relevant to the process of range expansion. Our main results are that recently introduced Corbicula populations were characterized by (i) low density and low rate of population increase, (ii) clams reproduced earlier in slow-growing populations, and (iii) density had no effect on population increase. All Corbicula populations analyzed in this study, which are fixed for one genotype (lineage Form A/R), experienced different selective environments in the introduced range. These findings support the perspective that adaptive phenotypic plasticity favored the expression of traits that maximize fitness in recently established populations, which faced stronger r-selective forces relative to long-established ones. We discuss the role of plasticity in facilitating rapid adaptation and increasing the likelihood of populations to overcome difficulties associated with low densities and low population increase in newly invaded areas.
An alignment free approach confirms semantic properties of species proteomes Alignment-based methods dominate molecular biology. However, by primarily allowing one-to-one comparisons, these methods are focused on a gene-centered viewpoint and lack the broad context essential to analyze how complex biological systems function and evolve. In actuality, a gene is part of genome where more than one sequence contributes to the functional network and evolutionary trajectory of the cell. The need for conservation of established interactions, is arguably more important to the evolutionary success of species than conservation of individual function. To test whether such contextual information exists, a distributional semantics method - Latent Semantic Analysis (LSA), was applied to thousands of species proteomes. Using natural language processing, Latent Taxonomic Signatures (LTSs) were identified that outperformed existing alignment-based BLAST methods when random protein sequences were being mapped to annotated taxonomy according to GenBank. LTSs are a novel proteome distributed feature, suggesting the existence of evolutionary constraints imposed on individual proteins by their proteome context. Even orphan proteins are exhibiting LTSs, which makes their uniqueness linked to a specific taxonomic level questionable. Unlike more simple bias, LTSs represent a self-similarity pattern, where random sets of species proteins show the same statistical properties of a complete proteome at many scales. Natural language processing and machine learning provide insights not easily discernable using alignment based methods suggestive there is more to species related differences than just translational optimization. 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. Genome-wide analysis of the non-coding RNA synthetic genetic network reveals extensive plasticity and unique phenotypes in yeast Recent studies identified non-coding RNAs (ncRNAs) with unknown function that are responsible for major fitness changes in yeast. To understand ncRNA interplay and aid their functional assignment, the synthetic genetic array (SGA) methodology was employed to create >15,000 double mutants and to score their epistasis in different environments. Unlike the protein network, ncRNAs mostly displayed positive epistasis in rich medium. Interestingly, the negative interactions significantly increased under stressors, showing environmental-dependent functions for ncRNAs. No correlation was found between the network of ncRNAs and that of their neighbouring genes, suggesting functional independence. The U3 paralogs, SNR17A and SNR17B, share the majority of genetic interactions in rich medium as expected. For example, SUT480 interacted with both paralogs and its function was linked to 18S rRNA processing. However, under stressors, a large number of unique epistatic interactions were observed, supporting the notion that SNR17A and SNR17B have diverged and sub-functionalised after genome duplication. Missing the sweet spot: one of the two N-glycans on human Gb3/CD77 synthase is expendable N-glycosylation is a ubiquitous posttranslational modification that may influence folding, subcellular localization, secretion, solubility and oligomerization of proteins. In this study, we examined the effects of N-glycans on the activity of human Gb3/CD77 synthase, which catalyzes the synthesis of glycosphingolipids with terminal Gal1[-&gt;]4Gal (Gb3 and the P1 antigen) and Gal1[-&gt;]4GalNAc disaccharides (the NOR antigen). The human Gb3/CD77 synthase contains two occupied N-glycosylation sites at positions N121 and N203. Intriguingly, we found that while the N-glycan at N203 is essential for activity and correct subcellular localization, the N-glycan at N121 is dispensable and its absence did not reduce, but, surprisingly, even increased the activity of the enzyme. The fully N-glycosylated human Gb3/CD77 synthase and its glycoform missing the N121 glycan correctly localized in the Golgi, whereas a glycoform without the N203 site partially mislocalized in the endoplasmic reticulum. A double mutein missing both N-glycans was inactive and accumulated in the endoplasmic reticulum. Our results suggest that the decreased specific activity of human Gb3/CD77 synthase glycovariants results from their improper subcellular localization and, to a smaller degree, a decrease in enzyme solubility. Taken together, our findings show that the two N-glycans of human Gb3/CD77 synthase have opposing effects on its properties, revealing a dual nature of N-glycosylation and potentially a novel regulatory mechanism controlling the biological activity of proteins. The Ensemble of Gene Regulatory Networks at Mutation-Selection Balance The evolution of diverse phenotypes both involves and is constrained by molecular interaction networks. When these networks influence patterns of expression, we refer to them as gene regulatory networks (GRNs). Here, we develop a quasi-species model of GRN evolution. With this model, we prove that-across a broad spectrum of viability and mutation functions-the dynamics converge to a stationary distribution over GRNs. Next, we show from first principles how the frequency of GRNs at equilibrium will be proportional to each GRNs eigenvector centrality in the genotype network. Finally, we determine the structural characteristics of GRNs that are favored in response to a range of selective environments and mutational constraints. Our work connects GRN evolution to quasi-species models, and thus can provide a mechanistic explanation for the topology of GRNs experiencing various evolutionary forces. Engineered disulfide reveals structural dynamics of locked SARS-CoV-2 spike The spike (S) protein of SARS-CoV-2 has been observed in three distinct pre-fusion conformations: locked, closed and open. Of these, the function of the locked conformation remains poorly understood. Here we engineered a SARS-CoV-2 S protein construct "S-R/x3" to arrest SARS-CoV-2 spikes in the locked conformation by a disulfide bond. Using this construct we determined high-resolution structures confirming that the x3 disulfide bond has the ability to stabilize the otherwise transient locked conformations. Structural analyses reveal that wild-type SARS-CoV-2 spike can adopt two distinct locked-1 and locked-2 conformations. For the D614G spike, based on which all variants of concern were evolved, only the locked-2 conformation was observed. Analysis of the structures suggests that rigidified domain D in the locked conformations interacts with the hinge to domain C and thereby restrains RBD movement. Structural change in domain D correlates with spike conformational change. We propose that the locked-1 and locked-2 conformations of S are present in the acidic high-lipid cellular compartments during virus assembly and egress. In this model, release of the virion into the neutral pH extracellular space would favour transition to the closed or open conformations. The dynamics of this transition can be altered by mutations that modulate domain D structure, as is the case for the D614G mutation, leading to changes in viral fitness. The S-R/x3 construct provides a tool for the further structural and functional characterization of the locked conformations of S, as well as how sequence changes might alter S assembly and regulation of receptor binding domain dynamics. Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. Geometric machine learning informed by ground truth: Recovery of conformational continuum from single-particle cryo-EM data of biomolecules This work is based on the manifold-embedding approach to study biological molecules exhibiting continuous conformational changes. Previous work established a method capable of reconstructing 3D movies and accompanying energetics of atomic-level structures from single-particle cryo-EM images of macromolecules displaying multiple conformational degrees of freedom. Here, we introduce an unsupervised geometric machine learning approach that is informed by detailed heuristic analysis of manifolds formed by simulated heterogeneous cryo-EM datasets generated from an atomic structure. These simulated data were generated with increasing complexity to account for multiple conformational motions, state occupancies and typical microscope parameters in a wide range of signal-to-noise ratios. Using these datasets as ground-truth, we provide detailed exposition of our findings using several conformational motions while exploring the available parameter space. Guided by these insights, we build a framework to leverage the high-dimensional geometric information obtained towards reconstituting a quasi-continuum of conformational states in the form of a free-energy landscape and respective 3D density maps for all states therein. As shown by a direct comparison of results, this framework offers substantial improvements relative to the previous work. Human centromere formation activates transcription and opens chromatin fibre structure Human centromeres appear as constrictions on mitotic chromosomes and form a platform for kinetochore assembly in mitosis. Biophysical experiments led to a suggestion that repetitive DNA at centromeric regions form a compact scaffold necessary for function, but this was revised when neocentromeres were discovered on non-repetitive DNA. To test whether centromeres have a special chromatin structure we have analysed the architecture of a neocentromere. Centromere formation is accompanied by RNA pol II recruitment and active transcription to form a decompacted, negatively supercoiled domain enriched in  open chromatin fibres. In contrast, centromerisation causes a spreading of repressive epigenetic marks to surrounding regions, delimited by H3K27me3 polycomb boundaries and divergent genes. This flanking domain is transcriptionally silent and partially remodelled to form  compact chromatin, similar to satellite-containing DNA sequences, and exhibits genomic instability. We suggest transcription disrupts chromatin to provide a foundation for kine-tochore formation whilst compact pericentromeric heterochromatin generates mechanical rigidity. 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. Diversified physiological sensory input connectivity questions the existence of distinct classes of spinal interneurons The spinal cord is engaged in all forms of motor performance but its functions are far from understood. Because network connectivity defines function, we explored the connectivity for muscular, tendon and tactile sensory inputs among a wide population of spinal interneurons in the lower cervical segments. Using low noise intracellular whole cell recordings in the decerebrated, nonanesthetized cat in vivo, we could define mono-, di-, trisynaptic inputs as well as the weights of each input. Whereas each neuron had a highly specific input, and each indirect input could moreover be explained by inputs in other recorded neurons, we unexpectedly also found the input connectivity of the spinal interneuron population to form a continuum. Our data hence contrasts with the currently widespread notion of distinct classes of interneurons. We argue that this suggested diversified physiological connectivity, which likely requires a major component of circuitry learning, implies a more flexible functionality.

1. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

2. HighlightsO_LIIn vivo whole cell, intracellular recording of spinal interneurons.
C_LIO_LIPatterns of input from Ia, Ib and cutaneous afferents is highly diversified.
C_LIO_LILearning appears to be a defining factor of spinal interneuron connectivity.
C_LI The H4K20 demethylase DPY-21 regulates thedynamics of condensin DC binding Condensin is a multi-subunit SMC complex that binds to and compacts chromosomes. Here we addressed the regulation of condensin binding dynamics using C. elegans condensin DC, which represses X chromosomes in hermaphrodites for dosage compensation. We established fluorescence recovery after photobleaching (FRAP) using the SMC4 homolog DPY-27 and showed that a well-characterized ATPase mutation abolishes its binding. Next, we performed FRAP in the background of several chromatin modifier mutants that cause varying degrees of X-chromosome derepression. The greatest effect was in a null mutant of the H4K20me2 demethylase DPY-21, where the mobile fraction of condensin DC reduced from [~]30% to 10%. In contrast, a catalytic mutant of dpy-21 did not regulate condensin DC mobility. Hi-C data in the dpy-21 null mutant showed little change compared to wild type, uncoupling Hi-C measured long-range DNA contacts from transcriptional repression of the X chromosomes. Together, our results indicate that DPY-21 has a non-catalytic role in regulating the dynamics of condensin DC binding, which is important for transcription repression. The evolution of stomatal traits along the trajectory towards C4 photosynthesis C4 photosynthesis optimizes plants carbon and water relations, allowing high photosynthetic rate with low stomatal conductance. Stomata have long been believed as a part of C4 syndrome. However, it remains unclear how stomata traits evolved along the path from C3 to C4. Stomatal patterning was examined in Flaveria genus, a model for studying C4 evolution. Comparative, transgenic and semi-in-vitro experiments were used to study molecular basis that underlies stomatal traits along C4 evolution. Novel results: the evolution from C3 to C4 species through intermediate species is accompanied by a stepwise rather than an abrupt change in the stomatal traits. The initial change occurs near Type II and dramatic change occurs at the C4-like species. On the road to C4, stomata become less in number but bigger in size and changes in stomatal density dominates changes in maximum stomatal conductance (gsmax). The reduction of FSTOMAGEN expression underlies altered gsmax between Flaveria species with different photosynthetic pathways and likely occurs in other C4 lineages. Our study provides insight into the pattern, mechanism and role of stomatal evolution along the road towards C4. This work highlights the stomatal traits in the current C4 evolutionary model and the co-evolution of photosynthetic pathway and stomata. Robust retrieval of data stored in DNA by de Bruijn graph-based de novo strand assembly DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted. Co-infection of Candidatus Piscichlamydia trichopodus (order Chlamydiales) and Henneguya sp (Myxosporea, Myxobolidae) in snakeskin gourami Trichopodus pectoralis (Regan 1910) The present study describes a simultaneous infection of a novel Chlamydia-like organism (CLO) with a Myxozoa parasite, Henneguya sp. in snakeskin gourami Trichopodus pectoralis in Thailand. A new CLO is proposed "Candidatus Piscichlamydia trichopodus" (CPT) based on 16S rRNA phylogenetic analysis. Systemic intracellular CPT infection was confirmed by histological examination, in situ hybridization, PCR assay, and sequencing of 16S rRNA. This novel pathogen belongs to the order Chlamydiales but differs in certain aspects from other species. The histopathological changes associated with CPT infection were different from the typical pathological lesions of epitheliocystis caused by previously known CLO. Unlike other CLO, CPT localized in the connective tissue rather than in the epithelial cells and formed smaller clumps of intracellular bacteria that stained dark blue with hematoxylin. On the other hand, typical myxospores of the genus Henneguya with tails were observed in the gill sections. Infection with Henneguya sp. resulted in extensive destruction of the gill filaments, most likely leading to respiratory distress. Due to the frequency of co-infections and the unavailability of culture methods for CLO and Henneguya sp, it was difficult to determine which pathogens were directly responsible for the associated mortality. However, co-infections may increase the negative impact on the host and the severity of the disease. Given the commercial importance of the snakeskin gourami and its significant aquaculture potential, the findings of this study are important for further studies on disease prevention. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease BackgroundStudies on DNA methylation (DNAm) in Alzheimers disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression.

MethodsHere, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n=337).

ResultsWe identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braaks tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in AD patients vs. controls.

ConclusionIn summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression. ksrates: positioning whole-genome duplications relative to speciation events in KS distributions SummaryWe present ksrates, a user-friendly command-line tool to position ancient whole-genome duplication (WGD) events with respect to speciation events in a phylogeny by comparing paralog and ortholog KS distributions derived from genomic or transcriptomic sequences, while adjusting for substitution rate differences among the lineages involved.

Availability and implementationksrates is implemented in Python 3 and as a Nextflow pipeline. The source code, Singularity and Docker containers, documentation and tutorial are available via https://github.com/VIB-PSB/ksrates.

Contactsteven.maere@ugent.vib.be, rolf.lohaus@ugent.vib.be Plucking a string or playing a G? Choice type impacts human reinforcement learning In reinforcement learning (RL) experiments, participants learn to make rewarding choices in response to different stimuli; RL models use outcomes to estimate stimulus-response values which change incrementally. RL models consider any response type indiscriminately, ranging from more concretely defined motor choices (e.g. pressing a key with the index finger), to more general choices that can be executed in a number of ways (e.g. getting dinner at the restaurant). But does the learning process vary as a function of the choice type? In Experiment 1, we show that it does: participants were slower and less accurate in learning correct choices of a general format compared to learning more concrete, motor actions. Using computational modeling, we show that two mechanisms contribute to this. First, there was evidence of irrelevant credit assignment: the values of motor actions interfered with the values of other choice dimensions, resulting in more incorrect choices when the correct response is not defined by a single motor action; second, information integration for relevant general choices was slower. In Experiment 2, we replicated and further extended the findings from Experiment 1, by showing that slowed learning was attributable to weaker working memory use, rather than slowed RL learning. In both experiments we ruled out the explanation that the difference in performance between two condition types was driven by difficulty/different levels of complexity. We conclude that defining a more abstract choice space used by multiple learning systems for credit assignment recruits executive resources, limiting how much such processes then contribute to fast learning. First evidence of in vitro cytotoxic effects of marine microlitter on Merluccius merluccius and Mullus barbatus, two Mediterranean commercial fish species Marine litter is composed mainly of plastics and is recognized as a serious threats to marine ecosystems. Ecotoxicological approaches have started elucidating the potential severity of microplastics (MPs) in controlled laboratory studies with pristine materials but no information exist on marine environmental microlitter as a whole. Here, we characterized the litter in the coastal Northern Tyrrhenian sea and in the stomach of two fish species of socio-economic importance, and exposed primary cell cultures of mucosal and lymphoid organs to marine microlitter for evaluating possible cytotoxic effects. An average of 0.30 {+/-} 0.02 microlitter items m-3 was found in water samples. FT-IR analysis revealed that plastic particles, namely HDPE, polyamide and polypropylene were present in 100% and 83.3% of Merluccius merluccius and Mullus barbatus analyzed, which overall ingested 14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual, respectively. Moreover, microlitter was confirmed as a vector of microorganisms. Lastly, the apical end-point of viability was found to be significantly reduced in splenic cells exposed in vitro to two microlitter conditions. Considering the role of the spleen in the mounting of adaptive immune responses, our results warrant more in-depth investigations for clarifying the actual susceptibility of these two species to anthropogenic microlitter.

HighlightsO_LI0.30 {+/-} 0.02 microlitter items m-3 were found at the surface of coastal Northern Tyrrhenian sea
C_LIO_LI14.67 {+/-} 4.10 and 5.50 {+/-} 1.97 items/individual were retrieved from the stomach of hakes and mullets
C_LIO_LIThe ingested microlitter contained plastic items
C_LIO_LIMicrolitter was validated as a carrier of bacteria, fungi and flagellates
C_LIO_LISplenic cells exposed to two microlitter conditions for 72 hours suffered cytotoxicity
C_LI HuR-dependent SOD2 protein synthesis is an early adaptation to anchorage independence During metastasis, cancer cells must adapt to survive a loss of anchorage and evade anoikis. An important pro-survival adaptation is the ability of metastatic tumor cells to increase their antioxidant capacity and restore cellular redox balance. Although much is known about the transcriptional regulation of antioxidant enzymes in response to stress, how cells rapidly adapt to alter antioxidant enzyme levels is less well understood. Using ovarian cancer cells as a model, we demonstrate that an increase in protein expression of the mitochondrial superoxide dismutase SOD2 is a very early event initiated in response to cellular detachment. SOD2 protein synthesis is rapidly induced within 0.5-2 hours of matrix detachment, and polyribosome profiling demonstrates an increase in the number of ribosomes bound to SOD2 mRNA, indicating an increase in SOD2 translation in response to anchorage-independence. Mechanistically, we find that anchorage-independence specifically induces cytosolic accumulation of the RNA binding protein HuR/ELAVL1 and leads to increased HuR binding to SOD2 mRNA. Using HuR siRNA-mediated knock-down, we show that the presence of HuR is necessary for the increase in SOD2 mRNA association with the heavy polyribosome fraction and SOD2 protein synthesis observed in anchorage-independence. Cellular detachment activates the stress-response protein kinase p38 MAPK, which is necessary for HuR-SOD2 mRNA binding and optimal increases in SOD2 protein expression. These findings illustrate a novel post-transcriptional regulatory mechanisms of SOD2, enabling cells to rapidly increase their mitochondrial antioxidant capacity as an acute response to anchorage-independence. 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. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. Tracheal tube fusion in Drosophila involves release of exosomes from multivesicular bodies Extracellular vesicles (EVs) comprise diverse types of cell-released membranous structures that are thought to play important roles in intercellular communication. Despite extensive work on the formation and functions of EVs in cultured cells, studies of EVs in vivo have remained scarce. We report here that EVs are present in the developing lumen of tracheal tubes in Drosophila embryos. We defined two distinct EV subpopulations, one of which contains the Munc13-4 homologue Staccato (Stac) and is spatially and temporally associated with tracheal tube fusion events. The formation of Stac-positive luminal EVs depends on the tip-cell-specific GTPase Arl3, which is also required for the formation of Stac-positive multivesicular bodies, suggesting that Stac-EVs derive from fusion of Stac-MVBs with the luminal membrane in tip cells during anastomosis formation. The GTPases Rab27 and Rab35 cooperate downstream of Arl3 to promote Stac-MVB formation and tube fusion. We propose that Stac-MVBs act as membrane reservoirs that facilitate tracheal lumen fusion in a process regulated by Arl3, Rab27, Rab35, and Stac/Munc13-4.