Identifying control ensembles for information processing within the cortico-basal ganglia-thalamic circuit In situations featuring uncertainty about action-reward contingencies, mammals exhibit a high degree of flexibility in adopting strategies for decision-making that are tuned in response to the conditions that they encounter. Although the cortico-basal ganglia thalamic (CBGT) network is implicated in information processing during decisions, it features a complex synaptic architecture, comprised of multiple feed-forward, reciprocal, and feedback pathways, that complicate efforts to elucidate the roles of specific CBGT populations in the process of evidence accumulation. In this paper we apply a strategic sampling approach, based on Latin hypercube sampling, to explore how variations in CBGT network properties, including subpopulation firing rates and synaptic weights, map to variability of parameters in a normative drift diffusion model (DDM), representing algorithmic aspects of information processing during decision-making. Through the application of canonical correlation analysis, we find that this relationship can be characterized in terms of three low-dimensional control ensembles within the CBGT network that impact specific qualities of the emergent decision policy: responsiveness (associated with overall activity in corticothalamic and direct pathways), pliancy (associated largely with overall activity in components of the indirect pathway of the basal ganglia), and choice (associated with differences in direct and indirect pathways across action channels). These analyses provide key mechanistic predictions about the roles of specific CBGT network elements in tuning information processing dynamics during decisions.

Author summaryMammals are continuously subjected to uncertain situations in which they have to choose among behavioral options. The cortico-basal ganglia-thalamic (CBGT) circuit is a complicated collection of interconnected nuclei believed to strongly influence the ability to adapt to environmental changes. The roles of specific CBGT components in controlling information during decisions remains unclear. At a more phenomenological, algorithmic level, drift-diffusion models have been shown to be able to reproduce behavioral data (action selection probabilities and the time needed to make a decision) obtained experimentally from mammals and to provide an abstract representation of a decision policy. In this work, we use simulated decision-making to establish a mapping from neural activity in the CBGT circuit to behavioral outcomes. This mapping illuminates the importance of three core sets of CBGT subnetworks in the action selection process and how they are involved in adapting decision policies across exploitative and exploratory situations.
A Parsimonious Description of Global Functional Brain Organization in Three Spatiotemporal Patterns Resting-state functional MRI has yielded many, seemingly disparate insights into large-scale organization of the human brain. Representations of the brains large-scale organization can be divided into two broad categories - zero-lag representations of functional connectivity structure and time-lag representations of traveling wave or propagation structure. Here we sought to unify multiple observed phenomena in these two categories by applying concepts from the study of standing (zero-lag) and traveling (time-lag) waves. Using simulated data, we first described the behavior of zero-lag and time-lag analyses applied to spatiotemporal patterns with varying degrees of standing and traveling wave patterns. We then identified three low-frequency spatiotemporal patterns in empirical resting-state fMRI signals, composed of a mixture of standing and traveling wave dynamics, that describe both the zero-lag and time-lag structure of these signals. We showed that a wide range of previously observed empirical phenomena, including functional connectivity gradients, the task-positive/task-negative pattern, the global signal, time-lag propagation patterns, the quasiperiodic pattern, and the functional connectome network structure are manifestations of these three spatiotemporal patterns. These patterns account for much of the global spatial structure that underlies functional connectivity analyses, and therefore impact how we interpret everything derived from resting-state fMRI data from functional networks to graphs.
A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. The Point Mutations in SARS-CoV-2 Variants Induce Long-Range Dynamical Perturbations in Neutralizing Antibodies Monoclonal antibodies are emerging as a viable treatment for the coronavirus disease 19 (COVID-19). However, newly evolved variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reduce the efficacy of currently available antibodies and can diminish vaccine-induced immunity. Here, we demonstrate that the microscopic dynamics of neutralizing monoclonal antibodies can be profoundly modified by the mutations present in the spike proteins of the SARS-COV-2 variants currently circulating in the world population. The dynamical perturbations within the antibody structure, which alter the thermodynamics of antigen recognition, are diverse and can depend both on the nature of the antibody and on the spatial location of the spike mutation. The correlation between the motion of the antibody and that of the spike receptor binding domain (RBD) can also be changed, modulating binding affinity. Using protein-graph-connectivity networks, we delineated the mutant-induced modifications in the information-flow along allosteric pathway throughout the antibody. Changes in the collective dynamics were spatially distributed both locally and across long-range distances within the antibody. On the receptor side, we identified an anchor-like structural element that prevents the detachment of the antibodies; individual mutations there can significantly affect the antibody binding propensity. Our study provides insight into how virus neutralization by monoclonal antibodies can be impacted by local mutations in the epitope via a change in dynamics. This realization adds a new layer of sophistication to the efforts for rational design of monoclonal antibodies against new variants of SARS-CoV2, taking the allostery in the antibody into consideration. Effect of Adolescent Stress on Adult Morphine-Induced Behavioral Sensitization is Dependent Upon Genetic Background 1Deaths related to opioid use have skyrocketed in the United States, leading to a public health epidemic. Research has shown that both biological (genes) and environmental (stress) precursors are linked to opioid use. In particular, stress during adolescence - a critical period of frontal lobe development - influences the likelihood of abusing drugs. However, little is known about the biological mechanisms through which adolescent stress leads to long-term risk of opioid use, or whether genetic background moderates this response. Male and female C57BL/6J and BALB/cJ mice were exposed to chronic variable social stress (CVSS) or control conditions throughout adolescence and then tested for morphine locomotor sensitization or morphine consumption in adulthood. To examine possible mechanisms that underlie stress-induced changes in morphine behaviors, we assessed physiological changes in response to acute stress exposure and prefrontal cortex miRNA gene expression. Adolescent stress did not influence morphine sensitization or consumption in BALB/cJ animals, and there was limited evidence of stress effects in female C57BL/6J mice. In contrast, male C57BL/6J mice exposed to adolescent CVSS had blunted morphine sensitization compared to control animals; no differences were observed in the acute locomotor response to morphine administration or morphine consumption. Physiologically, C57BL/6J mice exposed to CVSS had an attenuated corticosterone recovery following an acute stressor and downregulation of twelve miRNA in the prefrontal cortex compared to control mice. The specificity of the effects for C57BL/6J versus BALB/cJ mice provides evidence of a gene by environmental interaction influencing opioid behaviors. Long-term differences in stress reactivity or miRNA expression suggests two possible biological mechanisms to evaluate in future research. Hierarchical autoencoder-based integration improves performance in multi-omics cancer survival models through soft modality selection With decreasing costs of high-throughput sequencing, more and more datasets providing omics profiles of cancer patients become available. Thus, novel survival analysis approaches integrating these differently sized and heterogeneous molecular and clinical groups of variables start being developed. Due to the difficulty of the task of multi-omics data integration, the Cox Proportional-Hazards (PH) model using clinical data has remained one of the best-performing techniques, barely outperformed by models using molecular data modalities. There is therefore a need for methods that can successfully perform multi-omics integration in survival analysis and outperform the clinical Cox PH model. Moreover, while certain deep learning methods have been shown to provide state-of-the-art accuracy of cancer survival prediction, most of them show no benefit or even decay in performance when integrating a larger number of modalities, further motivating a need to investigate how modality-specific representations should be integrated when using neural networks for multi-omics integration. We benchmarked multiple integration techniques for a neural network architecture, revealing that hierarchical autoencoder-based integration of modality-specific representations outperformed other methods such as max-pooling and was comparable with state-of-the-art statistical approaches for multi-omics integration. Further, we showed that the hierarchical autoencoder-based integration of modality-specific representations achieved increased performance through a soft modality selection mechanism, focusing on the most informative modalities for each cancer. We thus framed multiomics integration as a partial group-wise feature selection problem, highlighting that only those models performed well that could adequately weight important modalities in the presence of the high noise imposed by less important modalities. Soil inoculum identity and rate jointly steer microbiomes and plant communities in the field The importance of soil inoculation to engineer soil microbiomes and ultimately entire ecosystems is becoming widely acknowledged. Inoculation with soil from different ecosystems can induce directional changes in soil and plant communities and promote the restoration of degraded ecosystems. However, it is unknown how such inoculations influence the soil microbiome, how much inoculum is needed, and whether inocula collected from similar ecosystems will steer the microbiome in different directions. We conducted a three-year soil inoculation field experiment at a degraded grassland and used two different soil inocula both from grasslands with three inoculation rates. Our results show that inoculation with soil that originates from different donor grasslands steers the soil microbiome as well as the plant communities at the inoculated site which was a degraded grassland into different directions and that these effects were stronger with increasing amount of soil used to inoculate. Inoculation with upland meadow soil introduced more keystone genera and resulted in more complex biotic networks in the soil than inoculation with meadow steppe soil. Our experiment highlights that soil inoculation can steer soil microbiomes in the field and that the direction and speed of development depend on the origin and the amount of soil inoculum used. Network Inference from Perturbation Time Course Data Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible. Map7D2 and Map7D1 facilitate microtubule stabilization through distinct mechanisms in neuronal cells Microtubule (MT) dynamics are modulated through the coordinated action of various MT-associated proteins (MAPs). However, the regulatory mechanisms underlying MT dynamics remain unclear. We show that the MAP7 family protein Map7D2 stabilizes MTs to control cell motility and neurite outgrowth. Map7D2 directly bound to MTs through its N-terminal half and stabilized MTs in vitro. Map7D2 localized prominently to the centrosome and partially on MTs in mouse N1-E115 neuronal cells, which expresses two of the four MAP7 family members, Map7D2 and Map7D1. Map7D2 loss decreased the resistance to the MT-destabilizing agent, nocodazole without affecting acetylated/detyrosinated stable MTs, suggesting that Map7D2 stabilizes MTs via direct binding. In addition, Map7D2 loss increased the rate of random cell migration and neurite outgrowth, presumably by disturbing the balance between MT stabilization and destabilization. Map7D1 exhibited similar subcellular localization and gene knock-down phenotypes to Map7D2. However, in contrast to Map7D2, Map7D1 was required for the maintenance of acetylated stable MTs. Taken together, our data suggest that Map7D2 and Map7D1 facilitate MT stabilization through distinct mechanisms in cell motility and neurite outgrowth. 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. Oncogenic protein condensates suppress growth factor perception and modulate drug tolerance Drug resistance remains a central challenge towards durable cancer therapy, including for cancers driven by the EML4-ALK oncogene. EML4-ALK and related fusion oncogenes form cytoplasmic protein condensates that transmit oncogenic signals through the Ras/Erk pathway. However, whether such condensates play a role in drug response is unclear. Here, we used optogenetics to find that condensates suppress signaling through endogenous RTKs including EGFR. Notably, ALK inhibition hypersensitized RTK signals, which are known to drive resistance. Suppression of RTKs occurred because condensates sequestered downstream adapter proteins that are required for RTK signal transmission. Strikingly, EGFR hypersensitization resulted in rapid and pulsatile Erk signal reactivation, which originated from neighboring apoptotic cells. Paracrine signals promoted survival during ALK inhibition, and blockade of paracrine signals suppressed drug tolerance. Our results uncover a regulatory role for RTK fusion condensates in cancer drug response and demonstrate the potential of optogenetics for uncovering functional biomarkers of cancer cells. Modeling miRNA-driven post-transcriptional regulation by using exon-intron split analysis (EISA) in pigs The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses. NOMA: a high-throughput microchip for robust, sequential measurements of secretions from the same single-cells Despite recent advances in single-cell analysis technologies, lacking simple methods to keep the live single-cells traceable for longitudinal detection reliably poses a significant obstacle in single-cell secretion analysis. Here we reported the high-density NOMA (narrow-opening microwell array) microchip that realized the retention of[&ge;] 97% of trapped single cells in dedicated spatial locations during repetitive detection procedures, verified with both adherent and suspension cells by two researchers independently. We applied it in monitoring single-cell protein secretions sequentially from the same single cells, and we found the digital protein secretion patterns dominate the protein secretion. We also demonstrated the microchip for longitudinally tracking IL-8 and the CD81+EV secretions from the same single-cells over days, which revealed the presence of "super secretors" within the cell population be more persistent to secrete protein or extracellular vesicle for an extended period. The NOMA platform reported here is simple, robust, and easy to operate for tracking sequential measurements from the same single cells, representing a novel and informative tool to inspire new observations in biomedical research.

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org.highwire.dtl.DTLVardef@aa69c7org.highwire.dtl.DTLVardef@6bc79org.highwire.dtl.DTLVardef@3fcbbforg.highwire.dtl.DTLVardef@597f4b_HPS_FORMAT_FIGEXP  M_FIG C_FIG Arg-tRNA synthetase links inflammatory metabolism to RNA splicing and nuclear trafficking via SRRM2 Cells respond to perturbations like inflammation by sensing changes in metabolite levels. Especially prominent is arginine, which has known connections to the inflammatory response. Here, we found that depletion of arginine during inflammation decreased levels of a nuclear form of arginyl-tRNA synthetase (ArgRS). Surprisingly, we found that nuclear ArgRS interacts with serine/arginine repetitive matrix protein 2 (SRRM2), a spliceosomal protein and nuclear speckle component and that arginine depletion impacted both condensate-like nuclear trafficking of SRRM2 and splice-site usage in certain genes. These splice-site usage changes cumulated in synthesis of different protein isoforms that altered cellular metabolism and peptide presentation to immune cells. Our findings uncover a novel mechanism whereby a tRNA synthetase cognate to a key amino acid that is metabolically controlled during inflammation modulates the splicing machinery. PKR-mediated Stress Response Enhances Dengue and Zika Virus Replication The mechanisms by which Flaviviruses use non-canonical translation to support their replication in host cells are largely unknown. Here we investigated how the integrated stress response (ISR), which promotes translational arrest by eIF2 phosphorylation (p-eIF2), regulates Flavivirus replication. During Dengue virus (DENV) and Zika virus (ZIKV) infection, eIF2 activation peaked at 24 hours post infection and was dependent on PKR but not type I interferon. The ISR is activated downstream of p-eIF2 during infection with either virus, but translation arrest only occurred following DENV infection. Despite this difference, both DENV and ZIKV replication was impaired in cells lacking PKR, independent of IFN-I/NF-kB signaling or cell viability. By using a ZIKV 5UTR reporter system as a model, we found that this region of the genome is sufficient to promote an enhancement of viral mRNA translation in the presence of an active ISR. Together we provide evidence that Flaviviruses escape ISR translational arrest and co-opt this response to increase viral replication. Effects of substrate on shrimp growth, water quality and bacterial community in the biofloc system nursing Penaeus vannamei postlarvae This study aimed to investigate the effects of substrate on water quality, shrimp growth and bacterial community in the biofloc system with a salinity of 5{per thousand}. Two treatments, biofloc system with (sB) or without (nB) addition of elastic solid packing filler (nylon) as substrate, were set up. Penaeus vannamei postlarvae (PL, [~] stage 15) were stocked at a density of 4000 PL m-3 in each treatment with triplicates for a 28-days culture experiment, taking glucose as carbon source (C:N 15:1). Results showed that the survival rate (96.3{+/-}3.6%), FCR (0.76{+/-}0.06) and productivity (1.54{+/-}0.12 kg m-3) in sB treatment were significantly better than those in nB treatment (81.0{+/-}7.1%, 0.98{+/-}0.08 and 1.14{+/-}0.09 kg m-3, P<0.05). All water parameters were in the recommended ranges. Substrate showed significant effect on TAN, TSS, turbidity, biofloc volume, pH and carbonate alkalinity (P < 0.05). Actinobacteria (4.0-22.7%), Bacteroidetes (10.4-33.5%), Firmicutes (0.2-11.2%), Planctomycetes (4.0-14.9%) and Proteobacteria (29.4-59.0%) were the most dominant phyla for both treatments. However, the bacterial community in sB treatment showed to be significantly different from that in nB treatment (Jaccard distance 0.94{+/-}0.01, P=0.001). Substrate showed significant effects on Shannon, Heip, Pielou and Simpson index, as well as relative abundances of Actinobacteria, Bacteroidetes and Planctomycetes (P < 0.05). The results suggested that addition of substrate affected the shrimp growth, water quality and bacterial community in the biofloc system nursing P. vannamei PL with a 5{per thousand} salinity. Clonal evolution in serially passaged Cryptococcus neoformans x deneoformans hybrids reveals a heterogenous landscape of genomic change Cryptococcus neoformans x deneoformans hybrids (also known as serotype AD hybrids) are basidiomycete yeasts that are common in a clinical setting. Like many hybrids, the AD hybrids are largely locked at the F1 stage and are mostly unable to undergo normal meiotic reproduction. However, these F1 hybrids, which display a high ([~]10%) sequence divergence are known to genetically diversify through mitotic recombination and aneuploidy, and this diversification may be adaptive. In this study, we evolved a single AD hybrid genotype in six diverse environments by serial passaging and then used genome resequencing of evolved clones to determine evolutionary mechanisms of adaptation. The evolved clones generally increased fitness after passaging, accompanied by an average of 3.3 point mutations, 2.9 loss of heterozygosity (LOH) events, and 0.7 trisomic chromosomes per clone. LOH occurred through nondisjunction of chromosomes, crossing over consistent with break-induced replication, and gene conversion, in that order of prevalence. The breakpoints of these recombination events were significantly associated with regions of the genome with lower sequence divergence between the parents and clustered in subtelomeric regions, notably in regions that had undergone introgression between the two parental species. Parallel evolution was observed, particularly through repeated homozygosity via nondisjunction, yet there was little evidence of environment-specific parallel change for either LOH, aneuploidy, or mutations. These data show that AD hybrids have both a remarkable genomic plasticity and yet are challenged in the ability to recombine through sequence divergence and chromosomal rearrangements, a scenario likely limiting the precision of adaptive evolution to novel environments. Experimental evolution reveals post-transcriptional regulation as a novel driver of Leishmania fitness gain The protozoan parasite Leishmania donovani causes fatal human visceral leishmaniasis in absence of treatment. Genome instability has been recognized as a driver in Leishmania fitness gain in response to environmental change or chemotherapy. How genome instability generates beneficial phenotypes despite potential deleterious gene dosage effects is unknown. Here we address this important open question applying experimental evolution and integrative systems approaches on parasites adapting to in vitro culture. Phenotypic analyses of parasites from early and late stages of culture adaptation revealed an important fitness tradeoff, with selection for accelerated growth in promastigote culture (fitness gain) impairing infectivity (fitness costs). Comparative genomics, transcriptomics and proteomics analyses revealed a complex regulatory network driving parasite fitness, with genome instability causing highly reproducible, gene dosage-dependent changes in protein abundance linked to post-transcriptional regulation. These in turn were associated with a gene dosage-independent reduction in abundance of flagellar transcripts and a coordinated increase in abundance of coding and non-coding RNAs implicated in ribosomal biogenesis and protein translation. We correlated differential expression of small nucleolar RNAs (snoRNAs) with changes in rRNA modification, providing first evidence that Leishmania fitness gain in culture may be controlled by post-transcriptional and epitranscriptomic regulation. Our findings propose a novel model for Leishmania fitness gain in culture, where differential regulation of mRNA stability and the generation of fitness-adapted ribosomes may potentially filter deleterious from beneficial gene dosage effects and provide proteomic robustness to genetically heterogenous, adapting parasite populations. This model challenges the current, genome-centric approach to Leishmania epidemiology and identifies the Leishmania transcriptome and non-coding small RNome as potential novel sources for the discovery of biomarkers that may be associated with parasite phenotypic adaptation in clinical settings. Bulk-assembly of monodisperse coacervates and giant unilamellar vesicles with programmable hierarchical complexity Compartmentalization is an essential step for the emergence of protocellular life on the early earth and the endeavor to bottom-up construct synthetic cells in the lab. Among manifold natural strategies for compartmentalization, assembly of lipid vesicles or coacervate droplets with resemblance to cell envelope or cytoplasm have emerged as two dominant paradigms. However, the spontaneous assembly of lipid vesicles or coacervates generally results in polydisperse microcompartments and lacks the ability to efficiently integrate functional building blocks towards defined complexity, which give rise to the difficulty to achieve the order and complexity towards the scope of that of life via spontaneous assembly. Herein, we show that the interplay of coacervates and colloidal particles provides a bulk-assembly approach to form monodisperse coacervates and giant unilamellar vesicles (GUVs) with programmable hierarchical complexity. The hierarchical complexity of the synthetic cell microcompartments can be delicately engineered from the control of the spatial or temporal organization of components in entity unit to manifold forms of interconnected synthetic cell consortia, achieving a compartment hierarchy analogous to the organelle-cell-tissue structure. The increase in complexity gives rise to emergent properties, for instance, collective morphology evolution of coacervate assemblages, gated permeability of GUVs without sophisticated protein machinery, and remarkable structural and functional stability of GUVs at extreme conditions. This work paves an unprecedented step to form monodisperse, hierarchical coacervates and GUVs via bulk-assembly, which provides a prebiotically plausible approach for the proper integration of inanimate matter towards the order and complexity of life and monodisperse, hierarchical microdroplets for follow-up scientific and technological applications. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis 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. Mutation rate dynamics reflect ecological change in an emerging zoonotic pathogen While mutation is often deleterious, it can also be adaptive. Mutation rates vary both within and between bacterial species, and understanding what drives this variation is essential for understanding the evolutionary dynamics of bacterial populations. In this study we investigate two factors that are predicted to influence the trade-off between the costs and benefits of mutation: ecology and genome size. To investigate the relationship between these factors and mutation rate we conducted mutation accumulation experiments on eight strains of the emerging zoonotic pathogen Streptococcus suis. Natural variation within this species allows us to compare tonsil carriage and invasive disease isolates, from both more and less pathogenic populations, with a wide range of genome sizes. We find that invasive disease isolates have repeatedly evolved mutation rates that are higher than those of closely related carriage isolates, regardless of variation in genome size. Independent of this variation in overall rate, we also observe a stronger bias towards G/C to A/T mutations in isolates from more pathogenic populations, whose genomes tend to be smaller and more AT-rich. Our results suggest that ecology is a stronger correlate of mutation rate than genome size over these timescales, and that transitions to invasive disease are consistently accompanied by rapid increases in mutation rate. These results shed light on the impact ecology can have on the adaptive potential of bacterial pathogens. A chemical screen based on an interruption of zebrafish gastrulation identifies the HTR2C inhibitor Pizotifen as a suppressor of EMT-mediated metastasis Metastasis is responsible for approximately 90% of cancer-associated mortality but few models exist that allow for rapid and effective screening of anti-metastasis drugs. Current mouse models of metastasis are too expensive and time consuming to use for rapid and high-throughput screening. Therefore, we created a unique screening concept utilizing conserved mechanisms between zebrafish gastrulation and cancer metastasis for identification of potential anti-metastatic drugs. We hypothesized that small chemicals that interrupt zebrafish gastrulation might also suppress metastatic progression of cancer cells and developed a phenotype-based chemical screen to test the hypothesis. The screen used epiboly, the first morphogenetic movement in gastrulation, as a marker and enabled 100 chemicals to be tested in five hours. The screen tested 1280 FDA-approved drugs and identified Pizotifen, an antagonist for serotonin receptor 2C (HTR2C) as an epiboly-interrupting drug. Pharmacologic and genetic inhibition of HTR2C suppressed metastatic progression in a mouse model. Blocking HTR2C with Pizotifen restored epithelial properties to metastatic cells through inhibition of Wnt-signaling. In contrast, HTR2C induced epithelial to mesenchymal transition (EMT) through activation of Wnt-signaling and promoted metastatic dissemination of human cancer cells in a zebrafish xenotransplantation model. Taken together, our concept offers a novel platform for discovery of anti-metastasis drugs. Positive Selection and Heat-Response Transcriptomes Reveal Adaptive Features of the Brassicaceae Desert Model, Anastatica hierochuntica O_LIPlant adaptation to a desert environment and its endemic heat stress is poorly understood at the molecular level. The naturally heat-tolerant Brassicaceae species Anastatica hierochuntica is an ideal extremophyte model to identify genetic adaptations that have evolved to allow plants to tolerate heat stress and thrive in deserts.
C_LIO_LIWe generated an A. hierochuntica reference transcriptome and pinpointed extremophyte adaptations by comparing Arabidopsis thaliana and A. hierochuntica transcriptome responses to heat and identifying positively selected genes in A. hierochuntica.
C_LIO_LIThe two species exhibit similar transcriptome adjustment in response to heat and the A. hierochuntica transcriptome does not exist in a constitutive heat "stress-ready" state. Furthermore, the A. hierochuntica global transcriptome as well as heat-responsive orthologs, display a lower basal and higher heat-induced expression than in A. thaliana. Genes positively selected in multiple extremophytes are associated with stomatal opening, nutrient acquisition, and UV-B induced DNA repair while those unique to A. hierochuntica are consistent with its photoperiod-insensitive, early-flowering phenotype.
C_LIO_LIWe suggest that evolution of a flexible transcriptome confers the ability to quickly react to extreme diurnal temperature fluctuations characteristic of a desert environment while positive selection of genes involved in stress tolerance and early flowering could facilitate an opportunistic desert lifestyle.
C_LI 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. 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. Novel MOG analogues to explore the MCT2 pharmacophore, α-ketoglutarate biology and cellular effects of N-oxalylglycine -ketoglutarate (KG) is a central metabolic node with a broad influence on cellular physiology. The KG analogue N-oxalylglycine (NOG) and its membrane-permeable pro-drug derivative dimethyl-oxalylglycine (DMOG) have been extensively used as tools to study prolyl hydroxylases (PHDs) and other KG-dependent processes. In cell culture media, DMOG is rapidly converted to MOG, which enters cells through monocarboxylate transporter MCT2, leading to intracellular NOG concentrations that are sufficiently high to inhibit glutaminolysis enzymes and cause cytotoxicity. Therefore, the degree of (D)MOG instability together with MCT2 expression levels determine the intracellular targets NOG engages with and, ultimately, its effects on cell viability. Here we designed and characterised a series of MOG analogues with the aims of improving stability and exploring the functional requirements for interaction with MCT2, a relatively understudied member of the SLC16 family. We report MOG analogues that maintain ability to enter cells via MCT2, and identify compounds that do not inhibit glutaminolysis or cause cytotoxicity but can still inhibit PHDs. We use these analogues to show that glutaminolysis-induced activation of mTORC1 can be uncoupled from PHD activity. Therefore, these new compounds can help deconvolute cellular effects that result from the polypharmacological action of NOG.