Multi-omic meta-analysis of transcriptomes and the bibliome uncovers novel hypoxia-inducible genes Hypoxia is a condition in which cells, tissues, or organisms are deprived of sufficient oxygen supply. Aerobic organisms have a hypoxic response system, represented by hypoxia-inducible factor 1- (HIF1A), to adapt to this condition. Due to publication bias, there has been little focus on genes other than well-known signature hypoxia-inducible genes. Therefore, in this study, we performed a meta-analysis to identify novel hypoxia-inducible genes. We searched publicly available transcriptome databases to obtain hypoxia-related experimental data, retrieved the metadata, and manually curated it. We selected the genes that are differentially expressed by hypoxic stimulation, and evaluated their relevance in hypoxia by performing enrichment analyses. Next, we performed a bibliometric analysis using gene2pubmed data to examine genes that have not been well studied in relation to hypoxia. Gene2pubmed data that provides information about the relationship between gene and publication. We calculated and evaluated the number of reports and similarity coefficients of each gene to HIF1A, which is a representative gene in hypoxia studies. In this data-driven study, we report that several genes that were not known to be associated with hypoxia, including the G protein-coupled receptor 146 gene, are upregulated by hypoxic stimulation.
Scalable parametric encoding of multiple modalities AO_SCPLOWBSTRACTC_SCPLOWA flexible model is introduced which shares ideas with the Autoencoder, Canonical Correlation Analysis, Singular Value Decomposition, and Procrustes Analysis. It is proposed to find relevant maps to transform multiple datasets of various types from one modality to another. Here, the Generative Encoder is used to transform spatial gene expression from breast tissue, to the images of histology tissue measured with Spatial Transcriptomics. The model is directly interpretable given all parameters are linked to the data space. It is scalable on Big Data, training reasonably on several thousand RGB images of 100 by 100 pixels in under an hour, which equates to 30,000 pixel features per sample image.
Mapping the subcortical connectome using in vivo diffusion MRI: feasibility and reliability Tractography combined with regions of interest (ROIs) has been used to non-invasively study the structural connectivity of the cortex as well as to assess the reliability of these connections. However, the subcortical connectome (subcortex to subcortex) has not been comprehensively examined, in part due to the difficulty of performing tractography in this complex and compact region. In this study, we performed an in vivo investigation using tractography to assess the feasibility and reliability of mapping known connections between structures of the subcortex using the test-retest dataset from the Human Connectome Project (HCP). We further validated our observations using a separate unrelated subjects dataset from the HCP. Quantitative assessment was performed by computing tract densities and spatial overlap of identified connections between subcortical ROIs. Further, known connections between structures of the basal ganglia and thalamus were identified and visually inspected, comparing tractography reconstructed trajectories with descriptions from tract-tracing studies. Our observations demonstrate both the feasibility and reliability of using a data-driven tractography-based approach to map the subcortical connectome in vivo. 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. NPEPPS regulates intracellular import and sensitivity to cisplatin by interaction with volume regulated anion channels Despite routine use of platinum-based chemotherapeutics in cancer treatment, there remains a need to improve efficacy and patient selection. Multi-omic assessment of human bladder cancer cell lines and their cisplatin resistant derivatives and whole-genome CRISPR screens identified NPEPPS, the puromycin-sensitive aminopeptidase as a novel driver of cisplatin resistance. NPEPPS depletion increased cisplatin import and sensitization of resistant cells in vitro and in vivo. Pharmacologic inhibition of NPEPPS in cells and chemoresistant, patient-derived tumor organoids improved response to cisplatin. NPEPPS was found in complex with volume regulated anion channel (VRAC) subunits LRRC8A and LRRC8D, whose loss is known to enhance resistance to cisplatin. Depletion of LRRC8A the only obligate subunit for normal VRAC function abrogated the effect of NPEPPS-mediated cisplatin import. Our findings describe the first mechanism by which VRACs can be targeted for therapeutic benefit.

HIGHLIGHTSO_LIMulti-omic screening found NPEPPS is a driver of cisplatin resistance in cancer
C_LIO_LINPEPPS is in protein complex with LRRC8A and D, volume regulated anion channel (VRAC) subunits
C_LIO_LILRRC8A and D loss increases cisplatin resistance and reduce its intracellular levels
C_LIO_LINPEPPS regulates cisplatin import and sensitivity through VRACs
C_LIO_LINPEPPS function is inhibited by small molecules offering potential for clinical translation
C_LI Re-convolving the compositional landscape of primary and recurrent glioblastoma reveals prognostic andtargetable tissue states Glioblastoma is an aggressive diffusely infiltrating neoplasm that spreads beyond surgical resection margins, where it intermingles with non-neoplastic brain cells. This complex microenvironment harbouring infiltrating glioma and non-neoplastic brain cells is the origin of tumor recurrence. Thus, understanding the cellular and molecular features of the glioma microenvironment is therapeutically and prognostically important. Here, we used single-nucleus RNA sequencing (snRNAseq) of primary and recurrent glioma to define three compositional  tissue-states rooted in cohabitation of cell-types and transcriptional states. These comprise a state featuring A) abundant normal brain microenvironment cells, B) reactive/inflamed brain microenvironment, and C) cellular/proliferative tumor. All these states exhibited variable degrees of infiltration by glioma cells. Spatial transcriptomics confirmed that the cell-types and transcriptomics states which compositionally cohabitate tissue states also colocalize in space. Tissue states are clinically significant because they correlate with radiographic, histopathologic, and prognostic features. We found that enrichment of tissue state B signature correlated with shorter survival. Importantly, we found that our compositionally defined tissue states are enriched in distinct metabolic pathways. One such pathway is fatty acid biosynthesis, which was enriched in tissue state B - a state enriched in recurrent glioblastoma and composed of astrocyte-like/mesenchymal glioma cells, reactive astrocytes resembling those seen in neurodegeneration, and monocyte-like myeloid cells. We showed that treating acute slices of GBM with a fatty acid synthesis inhibitor is sufficient to deplete the transcriptional signature of tissue state B. Our findings define a novel compositional approach to the glioma-infiltrated tissue which allows us to discover prognostic and targetable features, paving the way to new mechanistic and therapeutic discoveries. A novel Boolean network inference strategy to model early hematopoiesis aging Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. Large protein complex interfaces have evolved to promote cotranslational assembly Assembly pathways of protein complexes should be precise and efficient to minimise misfolding and unwanted interactions with other proteins in the cell. One way to achieve this efficiency is by seeding assembly pathways during translation via the cotranslational assembly of subunits. While recent evidence suggests that such cotranslational assembly is widespread, little is known about the properties of protein complexes associated with the phenomenon. Here, using a combination of proteome-specific protein complex structures and publicly available ribosome profiling data, we show that cotranslational assembly is particularly common between subunits that form large intermolecular interfaces. To test whether large interfaces have evolved to promote cotranslational assembly, as opposed to cotranslational assembly being a non-adaptive consequence of large interfaces, we compared the sizes of first and last translated interfaces of heteromers in bacterial, yeast, and human complexes. We detect a clear preference in N-terminal interfaces, which will be translated first and thus more likely to form cotranslationally, to be larger than C-terminal interfaces, suggesting that large interfaces have evolved as a means to maximise the chance of successful cotranslational subunit binding. The RAG1 Ubiquitin Ligase Domain Enhances Assembly and Selection of T Cell Receptor Genes to Restrain the Autoimmune Hazard of Generating T Cell Receptor Diversity RAG1/RAG2 (RAG) endonuclease-mediated assembly of diverse lymphocyte antigen receptor genes by V(D)J recombination is critical for the development and immune function of T and B cells. However, this process creates highly self-reactive cells that must be properly selected to suppress autoimmunity. The RAG1 protein contains a ubiquitin ligase domain that stabilizes RAG1 and stimulates RAG endonuclease activity in vitro. We report that mice with a mutation that inactivates the RAG1 ubiquitin ligase in vitro exhibit modestly reduced thymic cellularity, decreased assembly and altered repertoires of T cell receptor (TCR) {beta} and  genes in thymocytes, and impaired thymocyte developmental transitions that require the assembly of TCR{beta} or  genes and signaling by their proteins. These RAG1 mutant mice also exhibit less efficient positive selection and superantigen-mediated negative selection of conventional {beta} T cells, 2) impaired differentiation of iNKT lineage {beta} T cells, and 3) CD4+ {beta} T cells with elevated autoimmune potential. Our findings demonstrate that the RAG1 ubiquitin ligase domain functions in vivo to stimulate the assembly and selection of TCR{beta} and TCR genes, thereby establishing replete diversity of {beta} TCRs and {beta} T cell lineages while restraining the inherent autoimmune hazard of generating diverse antigen specificities. Inter-chromosomal linkage disequilibrium and linked fitness cost loci associated with selection for herbicide resistance The adaptation of weedy plants to herbicide is both a significant problem in agriculture and a model for the study of rapid adaptation under regimes of strong selection. Despite recent advances in our understanding of simple genetic changes that lead to resistance, a significant gap remains in our knowledge of resistance controlled by many loci and the evolutionary factors that influence the maintenance of resistance over time. Here, we perform a multi-level analysis involving whole genome sequencing and assembly, resequencing and gene expression analysis to both uncover putative loci involved in nontarget herbicide resistance and to examine evolutionary forces underlying the maintenance of resistance in natural populations. We found loci involved in herbicide detoxification, stress sensing, and alterations in the shikimate acid pathway to be under selection, and confirmed that detoxification is responsible for glyphosate resistance using a functional assay. Furthermore, we found interchromosomal linkage disequilibrium (ILD), most likely associated with epistatic selection, to influence NTSR loci found on separate chromosomes thus potentially mediating resistance through generations. Additionally, by combining the selection screen, differential expression and LD analysis, we identified fitness cost loci that are strongly linked to resistance alleles, indicating the role of genetic hitchhiking in maintaining the cost. Overall, our work strongly suggests that NTSR glyphosate resistance in I. purpurea is conferred by multiple genes which are maintained through generations via ILD, and that the fitness cost associated with resistance in this species is a by-product of genetic-hitchhiking. Modeling microRNA-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. Effect of a low concentration in chloride, sodium and potassium on oocyte maturation, oocyte hydration, ovulation and egg quality in rainbow trout. Water salinity is an important environmental factor known to have detrimental effects on salmonid reproduction, mostly when migrating female broodfish are held in sea water. In contrast, data obtained in freshwater are scarce and the impact of low water salinity, and more specifically of low water concentrations in sodium, chloride and potassium, during reproduction in freshwater is currently unknown. For this reason, and because ion and water fluxes are critical for the final steps of the female gamete formation, including oocyte hydration and ovulation, the aim of the present study was to investigate the impact of low salinity water on final oocyte maturation, ovulation and, ultimately, on egg quality, using rainbow trout as a physiological model and relevant aquaculture species.

Fish from the same commercial strain were raised either in a site characterized by low concentrations of Na+, K+, and Cl- ions in the water or in a closely located control site exhibiting higher concentration in these elements. Egg quality and duration of final oocyte maturation were investigated using innovative phenotyping tools such as automatic assessment of egg viability using the VisEgg system and non-invasive echograph-based monitoring of final oocyte maturation duration, respectively. Oocyte hydration during final oocyte maturation and after ovulation was also investigated. Finally, molecular phenotyping was performed using real-time PCR-based monitoring of several key players of final oocyte maturation and ovulation associated with ion and water transport, inflammation, proteolytic activity, and coagulation. Oocyte hydration and gene expression data were analyzed in the light of the duration of final oocyte maturation.

Here we show that low water salinity (i.e., low water concentration in chloride, sodium and potassium) negatively influences final oocyte maturation, ovulation and, ultimately, egg quality. Low water salinity triggered delayed ovulation and lower oocyte viability. When investigating the impact of low water salinity on final oocyte maturation duration, individuals presenting the most severe phenotypes exhibited impaired oocyte hydration and abnormally reduced gene expression levels of several key players of the ovulatory process. While the under expression of water (i.e., aquaporins) and ion (i.e., solute carriers) transporters is consistent with impaired oocyte hydration, our observations also indicate that the overall ovulatory gene expression program is disrupted. Our results raise the question of the mechanisms underlying the negative influence of low salinity water on the dynamics of the preovulatory phase, on the control of the oocyte homeostasis, including hydration, and on the overall success of the maturation-ovulation process.

HighlightsO_LILow water salinity impairs final oocyte maturation and egg quality in rainbow trout
C_LIO_LILow water salinity induces delayed ovulation and impaired oocyte hydration
C_LIO_LILow water salinity induces a dysregulation of several key ovulatory genes
C_LIO_LIMonitoring of final oocyte maturation can be performed using ultrasound staging
C_LI High Spatial Resolution MALDI Imaging Mass Spectrometry ofFresh-Frozen Bone Bone and bone marrow are vital to mammalian structure, movement, and immunity. These tissues are also commonly subjected to molecular alterations giving rise to debilitating diseases like rheumatoid arthritis, osteoporosis, osteomyelitis, and cancer. Technologies such as matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) enable the discovery of spatially resolved chemical information in biological tissue samples to help elucidate the complex molecular processes underlying pathology. Traditionally, preparation of native osseous tissue for MALDI IMS has been difficult due to the mineralized composition and heterogenous morphology of the tissue, and compensation for these challenges with decalcification and fixation protocols can remove or delocalize molecular species. Here, sample preparation methods were advanced to enable multimodal MALDI IMS of undecalcified, fresh-frozen murine femurs allowing the distribution of endogenous lipids to be linked to specific tissue structures and cell types. Adhesive-bound bone sections were mounted onto conductive glass slides with a microscopy-compatible glue and freeze-dried to minimize artificial bone marrow damage. Subliming matrix does not induce further bone marrow cracking, and recrystallizing the deposited matrix improves lipid signal. High spatial resolution (10 m) MALDI IMS was employed to characterize lipid distributions in fresh-frozen bone, and use of complementary microscopy modalities aided tissue and cell assignments. For example, various phosphatidylcholines localize to bone marrow, adipose tissue, marrow adipose tissue, and muscle. Further, sphingomyelin(42:1) was abundant in megakaryocytes, whereas sphingomyelin(42:2) was diminished in this cell type. These data reflect the vast molecular and cellular heterogeneity indicative of the bone marrow and the soft tissue surrounding the femur. Multimodal MALDI IMS has the potential to advance bone-related biomedical research by offering deep molecular coverage with spatial relevance in a preserved native bone microenvironment. Interactions and information: Exploring task allocation in ant colonies using network analysis In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individuals task - foraging, cleaning or nursing - and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.

HighlightsO_LIWe analysed the interaction networks of six Camponotus fellah colonies
C_LIO_LIWe tested how centrality and information flow were tied to task switching
C_LIO_LINode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groups
C_LIO_LIInteractions were correlated with task switching, but the strength of the correlation differed across functional groups
C_LI Inhibitors of ERp44, PDIA1, and AGR2 induce disulfide-mediated oligomerization of Death Receptors 4 and 5 and cancer cell death Breast cancer mortality remains unacceptably high, indicating a need for safer and more effective therapeutic agents. Disulfide bond Disrupting Agents (DDAs) were previously identified as a novel class of anticancer compounds that selectively kill cancers that overexpress the Epidermal Growth Factor Receptor (EGFR) or its family member HER2. DDAs kill EGFR+ and HER2+ cancer cells via the parallel downregulation of EGFR, HER2, and HER3 and activation/oligomerization of Death Receptors 4 and 5 (DR4/5). However, the mechanisms by which DDAs mediate these effects are unknown. Affinity purification analyses employing biotinylated-DDAs reveal that the Protein Disulfide Isomerase (PDI) family members AGR2, PDIA1, and ERp44 are DDA target proteins. Further analyses demonstrate that shRNA-mediated knockdown of AGR2 and ERp44, or expression of ERp44 mutants, enhance basal and DDA-induced DR5 oligomerization. DDA treatment of breast cancer cells disrupts PDIA1 and ERp44 mixed disulfide bonds with their client proteins. Together, the results herein reveal DDAs as the first small molecule, active site inhibitors of AGR2 and ERp44, and demonstrate roles for AGR2 and ERp44 in regulating the activity, stability, and localization of DR4 and DR5, and activation of Caspase 8. Growth and division mode plasticity is dependent on cell density in marine-derived black yeasts The diversity and ecological contribution of the fungus kingdom in the marine environment remain under-studied. A recent survey in the Atlantic (Woods Hole, MA, USA) brought to light the diversity and unique biological features of marine fungi. The study revealed that black yeast species undergo an unconventional cell division cycle, which has not been documented in conventional model yeast species such as Saccharomyces cerevisiae (budding yeast) and Schizosaccharomyces pombe (fission yeast). The prevalence of this unusual property is unknown. Here, I collected and identified 65 marine fungi species across 40 genera from the surface ocean water, sediment, and the surface of macroalgae (seaweeds) in the Pacific (Sugashima, Toba, Japan). The Sugashima collection largely did not overlap with the Woods Hole collection and included several unidentifiable species, further illustrating the diversity of marine fungi. Three black yeast species were isolated, two of which were commonly found in Woods Hole (Aureobasidium pullulans, Hortaea werneckii). Surprisingly, their cell division mode was dependent on cell density, and the previously reported unconventional division mode was reproduced only at a certain cell density. For all three black yeast species, cells underwent filamentous growth with septations at low cell density and immediately formed buds at high cell density. At intermediate cell density, two black yeasts (H. werneckii and an unidentifiable species) showed rod cells undergoing septation at the cell equator. In contrast, all eight budding yeast species showed a consistent division pattern regardless of cell density. This study suggests the plastic nature of the growth/division mode of marine-derived black yeast. New phylogenetic Markov models for inapplicable morphological characters This paper describes new Markov models for phylogenetic inference with inapplicable (anatomically dependent) morphological characters. It shows that the new solutions fall into two categories depending on the type of character hierarchy and require use of different Markov models. A combination of the new models and previous solutions is capable to model all general types of dependencies that may exists between morphological traits. The performance of the new models is assessed using theory and simulations. Bayesian phylogenetic inference with the new models and their construction for a hierarchy of custom complexity is demonstrated using RevBayes and the R package rphenoscate respectively. Unsupervised clustering analysis of SARS-Cov-2population structure reveals six major subtypes atearly stage across the world Identifying the population structure of the newly emerged coronavirus SARS-CoV-2 has significant potential to inform public health management and diagnosis. As SARS-CoV-2 sequencing data accrued, grouping them into clusters is important for organizing the landscape of the population structure of the virus. Due to the limited prior information on the newly emerged coronavirus, we utilized four different clustering algorithms to group 16,873 SARS-CoV-2 strains, which automatically enables the identification of spatial structure for SARS-CoV-2. A total of six distinct genomic clusters were identified using mutation profiles as input features. Comparison of the clustering results reveals that the four algorithms produced highly consistent results, but the state-of-the-art unsupervised deep learning clustering algorithm performed best and produced the smallest intra-cluster pairwise genetic distances. The varied proportions of the six clusters within different continents revealed specific geographical distributions. In particular, our analysis found that Oceania was the only continent on which the strains were dispersively distributed into six clusters. In summary, this study provides a concrete framework for the use of clustering methods to study the global population structure of SARS-CoV-2. In addition, clustering methods can be used for future studies of variant population structures in specific regions of these fast-growing viruses. Co-option of immune effectors by the hormonal signalling system triggering metamorphosis in Drosophila melanogaster Insect metamorphosis is regulated by the production, secretion and degradation of two peripheral hormones: 20-hydroxyecdysone (ecdysone) and juvenile hormone (JH). In addition to their roles in developmental regulation, increasing evidence suggests that these hormones are involved in innate immunity processes, such as phagocytosis and the induction of antimicrobial peptide (AMP) production. AMP regulation includes systemic responses as well as local responses at surface epithelia that contact with the external environment. At pupariation, Drosophila melanogaster increases dramatically the expression of three AMP genes, drosomycin (drs), drosomycin-like 2 (drsl2) and drosomycin-like 5 (drsl5). We show that the systemic action of drs at pupariation is dependent on ecdysone signalling in the fat body and operates via the ecdysone downstream target, Broad-Z4. In parallel, ecdysone also regulates local responses, specifically through the activation of drsl2 expression in the gut. Finally, we confirm the relevance of this ecdysone dependent AMP expression for the control of bacterial persistence by showing that flies lacking drs expression in the fat body have higher bacterial persistence over metamorphosis. Together, our data emphasize the importance of the association between ecdysone signalling and immunity using in vivo studies and establish a new role for ecdysone at pupariation, which impacts developmental success by regulating the immune system in a stage-dependent manner. We speculate that this co-option of immune effectors by the hormonal system may constitute a pre-emptive mechanism to control bacterial numbers in the pupa at the core of metamorphosis evolution. Cell-specific Bioorthogonal Tagging of Glycoproteins Altered glycosylation is an undisputed corollary of cancer development. Understanding these alterations is paramount but hampered by limitations underlying cellular model systems. For instance, the intricate interactions between tumour and host cannot be adequately recapitulated in monoculture of tumour-derived cell lines. More complex co-culture models usually rely on sorting procedures for proteome analyses and rarely capture the details of protein glycosylation. Here, we report a strategy termed Bio-Orthogonal Cell line-specific Tagging of Glycoproteins (BOCTAG). Cells are equipped by transfection with an artificial biosynthetic pathway that transforms bioorthogonally tagged sugars into the corresponding nucleotide-sugars. Only transfected cells incorporate bioorthogonal tags into glycoproteins in the presence of non-transfected cells. We employ BOCTAG as an imaging technique and to annotate cell-specific glycosylation sites in mass spectrometry-glycoproteomics. We demonstrate application in co-culture and mouse models, allowing for profiling of the glycoproteome as an important modulator of cellular function. Fiber orientation downsampling compromises the computation of white matter tract-related deformation Incorporating neuroimaging-revealed structural details into finite element (FE) head models opens vast new opportunities to better understand brain injury mechanisms. Recently, growing efforts have been made to integrate fiber orientation from diffusion tensor imaging (DTI) into FE models to predict white matter (WM) tract-related deformation that is biomechanically characterized by tract-related strains. Commonly used approaches often downsample the spatially enriched fiber orientation to match the FE resolution with one orientation per element (i.e., element-wise orientation implementation). However, the validity of such downsampling operation and corresponding influences on the computed tract-related strains remain elusive. To address this, the current study proposed a new approach to integrate voxel-wise fiber orientation from one DTI atlas (isotropic resolution of 1 mm3) into FE models by embedding orientations from multiple voxels within one element (i.e., voxel-wise orientation implementation). By setting the responses revealed by the newly proposed voxel-wise orientation implementation as the reference, we evaluated the reliability of two previous downsampling approaches by examining the downsampled fiber orientation and the computationally predicted tract-related strains secondary to one concussive impact. Two FE models with varying element sizes (i.e., 6.37 {+/-} 1.60 mm and 1.28 {+/-} 0.55 mm, respectively) were incorporated. The results showed that, for the model with a large voxel-mesh resolution mismatch, the downsampled element-wise fiber orientation, with respect to its voxel-wise counterpart, exhibited an absolute deviation over 30{degrees} across the WM/gray matter interface and the pons regions. Accordingly, this orientation deviation compromised the computation of tract-related strains with normalized root-mean-square errors up to 30% and underestimated the peak tract-related strains up to 10%. For the other FE model with finer meshes, the downsampling-induced effects were lower, both on the fiber orientation and tract-related strains. Taken together, the voxel-wise orientation implementation is recommended in future studies as it leverages the DTI-delineated fiber orientation to a larger extent than the element-wise orientation implementation. Thus, this study yields novel insights on integrating neuroimaging-revealed fiber orientation into FE models and may better inform the computation of WM tract-related deformation, which are crucial for advancing the etiological understanding and computational predictability of brain injury.

Graphic abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/471622v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@12ebda9org.highwire.dtl.DTLVardef@1a5d624org.highwire.dtl.DTLVardef@8e068borg.highwire.dtl.DTLVardef@4f8ff5_HPS_FORMAT_FIGEXP  M_FIG C_FIG 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. Hot and cold spots of pest-induced US urban tree death, 2020-2050 O_LIUrban trees are important nature-based solutions for future wellbeing and livability but are at high risk of mortality from insect pests. In the United States (US), 82% of the population live in urban settings and this number is growing, making urban tree mortality a matter of concern for most of its population. Until now, the magnitudes and spatial distributions of risks were unknown.
C_LIO_LIHere, we combine new models of street tree populations in [~]30,000 US communities, species-specific spread predictions for 57 invasive insect species, and estimates of tree death due to insect exposure for 48 host tree genera.
C_LIO_LIWe estimate that 1.4 million street trees will be killed by invasive insects from 2020 through 2050, costing an annualized average of US$ 30M. However, these estimates hide substantial variation: 23% of urban centers will experience 95% of all insect-induced mortality. Further, 90% of all mortality will be due to emerald ash borer (Agrilus planipennis, EAB), which is expected to kill virtually all ash trees (Fraxinus spp.) in >6000 communities.
C_LIO_LIWe define an EAB high-impact zone spanning 902,500km2, largely within the southern and central US, within which we predict the death of 98.8% of all ash trees. "Mortality hotspot cities" include Milwaukee, WI; Chicago, IL; and New York, NY.
C_LIO_LIWe identify Asian wood borers of maple and oak trees as the highest risk future invaders, where a new establishment could cost US$ 4.9B over 30 years.
C_LIO_LIPolicy implications: To plan effective mitigation, managers must know which tree species in which communities will be at the greatest risk, as well as the highest-risk insects. We provide the first country-wide, spatial forecast of urban tree mortality due to invasive insect pests. This framework identifies dominant pest insects and spatial impact hotspots, which can provide the basis for spatial prioritization of spread control efforts such as quarantines and biological control release sites. Our results highlight the need for EAB early-detection efforts as far from current infestations as Seattle, WA. Further, these findings produce a list of biotic and spatiotemporal risk factors for future high-impact US urban forest insect pests.
C_LI A Proteome-Wide Map of Chaperone-Assisted Protein Refolding in the Cytosol The journey by which proteins navigate their energy landscapes to their native structures is complex, involving (and sometimes requiring) many cellular factors and processes operating in partnership with a given polypeptide chains intrinsic energy landscape. The cytosolic environment and its complement of chaperones play critical roles in granting proteins safe passage to their native states; however, the complexity of this medium has generally precluded biophysical techniques from interrogating protein folding under cellular-like conditions for single proteins, let alone entire proteomes. Here, we develop a limited-proteolysis mass spectrometry approach paired with an isotope-labeling strategy to globally monitor the structures of refolding E. coli proteins in the cytosolic medium and with the chaperones, GroEL/ES (Hsp60) and DnaK/DnaJ/GrpE (Hsp70/40). GroEL can refold the majority (85%) of the E. coli proteins for which we have data, and is particularly important for restoring acidic proteins and proteins with three to five domains, trends that come to light because our assay measures the structural outcome of the refolding process itself, rather than indirect measures like binding or aggregation. For the most part, DnaK and GroEL refold a similar set of proteins, supporting the view that despite their vastly different structures, these two chaperones both unfold misfolded states, as one mechanism in common. Finally, we identify a cohort of proteins that are intransigent to being refolded with either chaperone. The data support a model in which chaperone-nonrefolders have evolved to fold efficiently once and only once, co-translationally, and remain kinetically trapped in their native conformations. A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. Contrasting resistance and resilience to light variation of the coupled oxic and anoxic componentsof an experimental microbial ecosystem Understanding how microbial communities of aquatic ecosystems respond to environmental change remains a critical challenge in microbial ecology. In this study, we used phototrophic oxic-anoxic micro-ecosystems to understand how the functioning and diversity of aerobic and anaerobic lake analog communities is affected by light deprivation. Continuous measurements were performed to describe oxygen dynamics (mean/min/max/amplitude) and time-series of full-length 16S rRNA sequencing were used to quantify changes in alpha- and beta-diversity. In the top oxic layer, oxygen concentration decreased significantly under light deprivation, but showed resilience in mean, minimum and maximum after light conditions were restored. Only the amplitude of diurnal fluctuations in oxygen concentrations did not recover fully, and instead tended to remain lower in treated ecosystems. Alpha-diversity of the top oxic layer communities showed a delayed increase after light conditions were restored, and was not resilient. In contrast, alpha-diversity of the anoxic bottom layer communities increased due to the stressor, but was resilient. Community composition changed significantly during light deprivation, showed resilience in the oxic layer and lack of resilience in the anoxic layer. Alpha-diversity and the amplitude of oxygen within and among treatments were strongly correlated, suggesting that higher diversity could lead to less variable oxygen concentrations, or vice versa. Our experiment showed that light deprivation induces multifaceted responses of community function and structure, hence focusing on a single stability component could potentially be misleading.