An Essential Role of UBXN3B in B Lymphopoiesis Hematopoiesis is finely regulated to enable timely production of the right numbers and types of mature immune cells to maintain tissue homeostasis. Dysregulated hematopoiesis may compromise antiviral immunity and/or exacerbate immunopathogenesis. Herein, we report an essential role of UBXN3B in maintenance of hematopoietic homeostasis and restriction of immunopathogenesis during respiratory viral infection. Ubxn3b deficient (Ubxn3b-/-) mice are highly vulnerable to SARS-CoV-2 and influenza A infection, characterized by more severe lung immunopathology, lower virus-specific IgG, significantly fewer B cells, but more myeloid cells than Ubxn3b+/+ littermates. This aberrant immune compartmentalization is recapitulated in uninfected Ubxn3b-/- mice. Mechanistically, UBXN3B controls precursor B-I (pre-BI) transition to pre-BII and subsequent proliferation in a cell-intrinsic manner, by maintaining BLNK protein stability and pre-BCR signaling. These results reveal an essential role of UBXN3B for the early stage of B cell development.
Immune complex solubility and size govern Fc-gamma receptor responses: A scalable cell-based reporter system Fc-gamma receptor (Fc{gamma}R) activation by soluble IgG immune complexes (sICs) represents a major mechanism of inflammation in certain autoimmune diseases such as systemic lupus erythematosus (SLE). A robust and scalable test system allowing for the detection and quantification of sIC bioactivity is missing. Previously described Fc{gamma}R interaction assays are limited to certain Fc{gamma}Rs, lack scalability and flexibility, are not indicative of receptor activation or lack sensitivity towards sIC size. We developed a comprehensive reporter cell panel detecting individual activation of Fc{gamma}Rs from humans and the mouse. The reporter cell lines were integrated into an assay format that provides flexible read-outs enabling the quantification of sIC reactivity via ELISA or a fast detection using flow cytometry. This identified Fc{gamma}RIIA(H) and Fc{gamma}RIIIA as the most sIC-sensitive Fc{gamma}Rs in our test system. Applying the assay we demonstrate that sICs versus immobilized ICs are fundamentally different Fc{gamma}R-ligands with regard to Fc{gamma}R preference and signal strength. Reaching a detection limit in the very low nanomolar range, the assay proved also to be sensitive to sIC stoichiometry and size enabling for the first time a complete reproduction of the Heidelberger-Kendall precipitation curve in terms of immune receptor activation. Analyzing sera from SLE patients and mouse models of lupus and arthritis proved that sIC-dependent Fc{gamma}R activation has predictive capabilities regarding severity of SLE disease. The new methodology provides a sensitive, scalable and comprehensive tool to evaluate the size, amount and bioactivity of sICs in all settings.

One Sentence SummaryIn this study we established a comprehensive Fc{gamma}R reporter cell assay enabling the detection and quantification of soluble immune complexes generated in experimental and clinical settings.
Interferon alpha-based combinations suppress SARS-CoV-2 infection in vitro and in vivo There is an urgent need for new antivirals with powerful therapeutic potential and tolerable side effects. In the present study, we found that recombinant human interferon-alpha (IFNa) triggers intrinsic and extrinsic cellular antiviral responses, as well as reduces replication of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro. Although IFNa alone was insufficient to completely abolish SARS-CoV-2 replication, combinations of IFNa with remdesivir or other antiviral agents (EIDD-2801, camostat, cycloheximide, or convalescent serum) showed strong synergy and effectively inhibited SARS-CoV-2 infection in human lung epithelial Calu-3 cells. Furthermore, we showed that the IFNa-remdesivir combination suppressed virus replication in human lung organoids, and that its single prophylactic dose attenuated SARS-CoV-2 infection in lungs of Syrian hamsters. Transcriptome and metabolomic analyses showed that the combination of IFNa-remdesivir suppressed virus-mediated changes in infected cells, although it affected the homeostasis of uninfected cells. We also demonstrated synergistic antiviral activity of IFNa2a-based combinations against other virus infections in vitro. Altogether, our results indicate that IFNa2a-based combination therapies can achieve higher efficacy while requiring lower dosage compared to monotherapies, making them attractive targets for further pre-clinical and clinical development. Region-specific microRNA alterations in marmosets carrying SLC6A4 polymorphisms are associated to anxiety-like behavior. Psychiatric diseases such as depression and anxiety are multifactorial conditions, highly prevalent in western societies. Human studies have identified a number of high-risk genetic variants for these diseases. Among them, polymorphisms in the promoter region of the serotonin transporter gene (SLC6A4) have attracted much attention. However, due to the paucity of experimental models, molecular alterations induced by these genetic variants and how they correlate to behavioral deficits have not been examined. Marmosets have emerged as a powerful model in translational neuroscience to investigate molecular underpinnings of complex behaviors. Here, we took advantage of naturally occurring genetic polymorphisms in marmoset SLC6A4 gene that have been linked to anxiety-like behaviors. Using FACS-sorted cells from different brain regions, we revealed that marmosets bearing different SLC6A4 variants exhibit distinct microRNAs signatures in a region of the prefrontal cortex whose activity has been consistently altered in patients with depression/anxiety. We also identified DCC, a gene previously linked to these diseases, as a downstream target of the dysregulated microRNAs. Significantly, we showed that levels of both microRNAs and DCC in this region were highly correlated to anxiety-like behaviors as well as to the response to citalopram, a selective serotonin re-uptake inhibitor and widely prescribed anti-depressant. Our findings establish links between genetic variants, molecular modifications in specific cortical regions and complex behavioral/pharmacological responses, providing new insights into gene-behavior relationships underlying human psychopathology. An hidden Markov model to estimate homozygous-by-descent probabilities associated with nested layers of ancestors Inbreeding results from the mating of related individuals and has negative consequences because it brings together deleterious variants in one individual. Genomic estimates of the inbreeding coefficients are preferred to pedigree-based estimators as they measure the realized inbreeding levels and they are more robust to pedigree errors. Several methods identifying homozygous-by-descent (HBD) segments with hidden Markov models (HMM) have been recently developed and are particularly valuable when the information is degraded or heterogeneous (e.g., low-fold sequencing, low marker density, heterogeneous genotype quality or variable marker spacing). We previously developed a multiple HBD class HMM where HBD segments are classified in different groups based on their length (e.g., recent versus old HBD segments) but we recently observed that for high inbreeding levels with many HBD segments, the estimated contributions might be biased towards more recent classes (i.e., associated with large HBD segments) although the overall estimated level of inbreeding remained unbiased. We herein propose a new model in which the HBD classification is modeled in successive nested levels with decreasing expected HBD segment lengths, the underlying exponential rates being directly related to the number of generations to the common ancestor. The non-HBD classes are now modeled as a mixture of HBD segments from later generations and shorter non-HBD segments (i.e., both with higher rates). The new model has improved statistical properties and performs better on simulated data compared to our previous version. We also show that the parameters of the model are easier to interpret and that the model is more robust to the choice of the number of classes. Overall, the new model results in an improved partitioning of inbreeding in different HBD classes and should be preferred. An automated workflow for multiplexed single-cell proteomics sample preparation at unprecedented sensitivity. The analysis of single-cell proteomes has recently become a viable complement to transcriptomics and genomics studies. Proteins are the primary driver of cellular functionality and mRNA levels are often an unreliable proxy of such. Therefore, the global analysis of the proteome is essential to study cellular identities. Multiplexed and label-free mass spectrometry-based approaches with single-cell resolution have lately attributed surprising heterogeneity to presumed homogenous cell populations. Even though specialized experimental designs and instrumentation have demonstrated remarkable advances, the efficient sample preparation of single cells still lag. Here, we introduce the proteoCHIP, a universal option for single-cell proteomics sample preparation at surprising sensitivity and throughput. The automated processing using a commercial system combining single-cell isolation and picoliter dispensing, the cellenONE(R), reduces final sample volumes to low nanoliters submerged in a hexadecane layer simultaneously eliminating error-prone manual sample handling and overcoming evaporation. The specialized proteoCHIP design allows direct injection of single cells via a standard autosampler resulting in around 1,500 protein groups per analytical run at remarkable reporter ion signal to noise while reducing or eliminating the carrier proteome. We identified close to 2,600 proteins across 170 multiplexed single cells from two highly similar human cell types. This dedicated loss-less workflow allows distinguishing in vitro co-differentiated cell types of self-organizing cardiac organoids based on indicative markers across 150 single cells. In-depth characterization revealed enhanced cellular motility of cardiac endothelial cells and sarcomere organization in cardiomyocytes. Our versatile and automated sample preparation has not only proven to be easily adaptable but is also sufficiently sensitive to drive biological applications of single-cell proteomics. 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. 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 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. Host phenology can drive the evolution of intermediate virulence strategies in some parasites AO_SCPLOWBSTRACTC_SCPLOWThe traditional mechanistic trade-offs resulting in a negative correlation between transmission and virulence are the foundation of nearly all current theory on the evolution of parasite virulence. Several ecological factors have been shown to modulate the optimal virulence strategies predicted from mechanistic trade-off models, but these ecological factors have not yet been shown to be sufficient to explain the intermediate virulence strategies observed in any natural system. The timing of seasonal activity, or phenology, is a common factor that influences the types and impact of many ecological interactions but is difficult to incorporate into virulence evolution studies. We develop a mathematical model of a disease system with seasonal host activity to study the evolutionary consequences of host phenology on the virulence of obligate-killer parasite. Results from this model demonstrated that seasonal host activity is sufficient to drive the evolution of intermediate parasite virulence in some types of natural disease systems, even when a traditional mechanistic trade-off between transmission and virulence is not assumed in the modeling framework. The optimal virulence strategy in these systems can be determined by both the duration of the host activity period as well as the variation in the host emergence timing. Parasites with low virulence strategies are favored in environments with long host activity periods and in environments in which hosts emerge synchronously. The results demonstrate that host phenology can be sufficient to select for intermediate optimal virulence strategies, providing an alternative mechanism to account for virulence evolution in some natural systems. Regulation of the PKD2 channel function by TACAN Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in membrane receptor PKD1 or cation channel PKD2. TACAN (also named TMEM120A), recently reported as an ion channel in neuron cells for mechano and pain sensing, is also distributed in diverse non-neuronal tissues such as kidney, heart and intestine, suggesting its involvement in other functions. In this study, we found that TACAN is in complex with PKD2 in native renal cell lines. Using the two-electrode voltage clamp in Xenopus oocytes we found that TACAN inhibited the channel activity of PKD2 gain-of-function mutant F604P. The first and last transmembrane domains of TACAN were found to interact with the PKD2 C-and N-terminal portions, respectively. We showed that the TACAN N-terminus acted as a blocking peptide and that TACAN inhibits the PKD2 function through the PKD2/TACAN binding. By patch clamping in mammalian cells, we found that TACAN inhibits both the single channel conductance and open probability of PKD2 and mutant F604P. PKD2 co-expressed with TACAN, but not PKD2 alone, exhibited pressure sensitivity. Furthermore, we also found that TACAN aggravates PKD2-dependent tail curvature and pronephric cysts in larval zebrafish, in support of the in vitro inhibitory effects of TACAN. In summary, this study revealed that TACAN acts as a PKD2 inhibitor and mediates mechano sensitivity of the PKD2/TACAN channel complex. Liver ductal organoids reconstruct intrahepatic biliary trees in decellularized liver grafts Three-dimensional scaffolds decellularized from native organs are a promising technique to establish engineered liver grafts and overcome the current shortage of donor organs. However, limited sources of bile duct cells and inappropriate cell distribution in bioengineered liver grafts have hindered their practical application. Organoid technology is anticipated to be an excellent tool for the advancement of regenerative medicine. In the present study, we reconstructed intrahepatic bile ducts in a rat decellularized liver graft by recellularization with liver ductal organoids. Using an ex vivo perfusion culture system, we demonstrated the biliary characteristics of repopulated mouse liver organoids, which maintained bile duct markers and reconstructed biliary tree-like networks with luminal structures. We also established a method for the co-recellularization with engineered bile ducts and primary hepatocytes, revealing the appropriate cell distribution to mimic the native liver. We then utilized this model in human organoids to demonstrate the reconstructed bile ducts. Our results show that liver ductal organoids are a potential cell source for bile ducts from bioengineered liver grafts using three-dimensional scaffolds. The neurogenic fate of the hindbrain boundaries relies on Notch-dependent asymmetric cell divisions The generation of cell diversity in the central nervous system occurs during embryogenesis and requires a precise balance between cell proliferation, commitment to specific fates, and further neuronal differentiation. The cellular and molecular mechanisms regulating this balance in the embryonic brain are still poorly understood. Here we study how the neurogenic capacity in the embryonic hindbrain is spatiotemporally allocated, and how the fate and the growth of the hindbrain boundary cells are regulated. By generating a CRISPR-based knock-in zebrafish transgenic line to specifically label the hindbrain boundaries, we unveiled that boundary cells undergo a functional transition to become neurogenic during hindbrain segmentation concurrently as they maintain the progenitor cell pool. Boundary cells engaged in neurogenesis coinciding with the onset of Notch signaling, which triggered their asymmetrical cell division. Our findings reveal that distinct neurogenic phases take place during hindbrain growth and suggest that boundary cells contribute to refine the final number, identity, and proportion of neurons in the brain.

SUMMARYHindbrain boundary cells undergo a functional transition to become neurogenic concurrently as they are maintained as a progenitor cell pool. This involves a behavioral switch from symmetrically dividing progenitor cells to asymmetrically dividing progenitors, which depends on Notch-activity. Tackling polypharmacology of kinase inhibitors and selecting chemical kinase probes by transcription factor activity profiling. Protein kinase inhibitors (PKI) evolved as promising drugs for multiple diseases. However, PKIs promiscuity causes polypharmacological effects challenging therapeutic development. We show that the polypharmacology of PKIs can be inferred from their impact on transcription factors (TF) lying at the apexes of signaling pathways. Using a high-content reporter assay, we evaluated TF activity profiles (TFAP) in cells treated with Akt, CDK, Aurora, Raf, MEK, and ERK inhibitors. For each kinase family, we found kinase-specific consensus TFAP signatures signifying the on-target PKI activity. Remarkably, proximal kinases had the highest similarity of their PKIs consensus signatures. Furthermore, we show that individual PKIs exhibited the consensus, "on-target signatures" within certain "specificity windows" and distinct "off-target signatures" at other concentrations. We also show that the TFAP signatures permit pinpointing the off-target PKI activity at irrelevant kinases and non-kinase effectors. Therefore, the TFAP approach provides clear-cut quantitative metrics for assessing PKI activity and concentration ranges where the on-target activity dominates cell response. By illuminating PKI biology invisible to target-based techniques, this effect-based approach streamlines the selection of kinase chemical probes and PKI drug prioritization. AutoGGN: A Gene Graph Network AutoML Tool for Multi-Omics Research Omics data identifies biological characteristics from genetic to phenotypic levels during the life span. Molecular interaction networks have a fundamental impact on life activities. Integrating omics data and molecular interaction networks will help researchers delve into comprehensive information underlying the data. Here, we proposed a new multimodal method called AutoGGN to aggregate multi-omics data and molecular interaction networks based on graph convolutional neural networks. We evaluated AutoGGN using two different tasks: cancer type classification and single-cell stage classification. On both tasks, AutoGGN showed better performance compared to other methods, the trend is relevant to the ability of utilizing much more information from biological data. The phenomenon indicated AutoGGN has the potential to incorporate valuable information from molecular interaction networks and multi-omics data effectively. Furthermore, in order to provide a better understanding of the mechanism of prediction results, we assessed the explanation using SHAP module and identified the key genes contributing to the prediction of classification, which will provide insights for the downstream design of biological experiments. Adapting to extremes: reconstructing evolution in response to changing climate over time and space in the diverse Australian plant genus Acacia AimMacroevolutionary analysis is increasingly being used to study biodiversity responses to climate change, for example by using phylogenetic node ages to infer periods of diversification, or phylogenetic reconstruction of traits to infer adaptation to particular stresses. Here we apply a recently developed macroevolutionary method to investigate the responses of a diverse plant genus, Acacia, to increasing aridity and salinity in Australia from the Miocene to the present. We ask whether increase in tolerance of aridity and salinity coincided with periods of aridification, and if it allowed the radiation of Acacia into a wide range of niches.

TaxonAcacia

LocationAustralia

MethodsWe applied the Niche Evolution Model (NEMo), which combines Environmental (or Ecological) Niche Modelling (ENM) with phylogenetic comparative methods (PCM) in a single statistical framework, to a large database of Acacia presence-only records and presence-absence survey sites in order to infer current environmental tolerances of Australia Acacia species and reconstruct the evolution of environmental tolerance to increasing aridity and salinity.

ResultsWe find that patterns in evolution of Acacia, over time and across different habitat types, are consistent with the aridification history of Australia and suggests substantial ability to adapt to high aridity and salinity.

Main conclusionsOur results suggest that many Acacia lineages have been able to exploit new environments created during the aridification of Australia through evolution of environmental tolerance, resulting in their current dominance of many habitats across the continent. This study demonstrates that phylogenetic studies of the evolution of responses to changing environment can move beyond application of simple trait-based models, allowing the underlying processes of speciation, adaptation and dispersal to be explicitly modelled in a macroecological and macroevolutionary context.

Statement of significanceAcacia species are found throughout Australia, from rainforests to deserts, and are striking in their environmental adaptability, so they are a perfect case study for understanding evolution of tolerance to environmental extremes in a changing climate. We use the largest database of spatial distribution records yet assembled, using both surveys and atlas data, and a new analytical method that combines the strengths of environmental niche modelling with phylogenetic comparative methods, to demonstrate rapid evolution in aridity and salinity tolerance in response to aridification of the Australian continent during the Neogene and Quaternary. 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 A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information. Foraging with friends, moving with anyone: effects of the social environment on movement-integrated habitat selection O_LIMovement links the distribution of habitats with the social environment of animals using those habitats; yet integrating movement, habitat selection, and socioecology remains an opportunity for further study.
C_LIO_LIHere, our objective was to disentangle the roles of habitat selection and social association as drivers of collective movement in a gregarious ungulate. To accomplish this objective, we (1) assessed whether socially familiar individuals form discrete social communities and whether social communities have high spatial, but not necessarily temporal, overlap; and (2) we modelled the relationship between collective movement and selection of foraging habitats using socially informed integrated step selection analysis.
C_LIO_LIWe used social network analysis to assign individuals to social communities and determine short and long-term social preference among individuals. Using integrated step selection functions (iSSF), we then modelled the effect of social processes, i.e., nearest neighbour distance and social preference, and movement behaviour on patterns of habitat selection.
C_LIO_LIBased on assignment of individuals to social communities and home range overlap analyses, individuals assorted into discrete social communities, and these communities had high spatial overlap. By unifying social network analysis with iSSF, we identified movement-dependent social association, where individuals foraged with more familiar individuals, but moved collectively with any between foraging patches.
C_LIO_LIOur study demonstrates that social behaviour and space use are inter-related based on spatial overlap of social communities and movement-dependent habitat selection. Movement, habitat selection, and social behaviour are linked in theory. Here, we put these concepts into practice to demonstrate that movement is the glue connecting individual habitat selection to the social environment.
C_LI Beyond tracking climate: niche shifts during native range expansion and their implications for novel invasions AimAlthough ecological niche models have been instrumental in understanding the widespread species distribution shifts under global change, rapid niche shifts limit model transferability to novel locations or time periods. Niche shifts during range expansion have been studied extensively in invasive species, but may also occur in native populations tracking climate change. We compared niche shifts during both types of range expansion in a Mediterranean annual plant to ask (i) whether the species native range expansion tracked climate change, (ii) whether further range expansion was promoted by niche expansion, and (iii) how these results changed forecasts of two ongoing invasions in Australia and California.

LocationEurasian Holarctic, California and Australia

TaxonDittrichia graveolens (L.) Greuter (Asteraceae)

MethodsNiche shifts were quantified in both environmental and geographic space, using the framework of niche centroid shift, overlap, unfilling, and expansion (COUE) as well as Maximum Entropy modelling. We used the historic native distribution and climate data (1901-1930) to project the expected distribution in the present climate (1990-2019), and compared it to the observed current distribution of D. graveolens. Finally, we compared invasion forecasts based on the historic and present native niches.

ResultsWe found that D. graveolens expanded its native range well beyond what would be sufficient to track climate change, associated with a 5.5% niche expansion towards more temperate climates. In contrast, both invasions showed niche conservatism, and were (still) constrained to climatic areas matching the historic native niche.

Main conclusionsour results show that contrary to hypotheses in the literature, niche shifts are not necessarily more rapid in invasions than in native range expansions. We conclude that niche expansion during the process of climate tracking may cause further range expansion than expected based on climate change alone. Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity: a case study of Th1/Th2/Th17 cell differentiation Naive helper (CD4+) T-cells can differentiate into distinct functional subsets including Th1, Th2, and Th17 phenotypes. Each of these phenotypes has a  master regulator - T-bet (Th1), GATA3 (Th2) and ROR{gamma}T (Th17) - that inhibits the other two master regulators. Such mutual repression among them at a transcriptional level can enable multistability, giving rise to six experimentally observed phenotypes - Th1, Th2, Th17, hybrid Th/Th2, hybrid Th2/Th17 and hybrid Th1/Th17. However, the dynamics of switching among these phenotypes, particularly in the case of epigenetic influence, remains unclear. Here, through mathematical modeling, we investigated the coupled transcription-epigenetic dynamics in a three-node mutually repressing network to elucidate how epigenetic changes mediated by any  master regulator can influence the transition rates among different cellular phenotypes. We show that the degree of plasticity exhibited by one phenotype depends on relative strength and duration of mutual epigenetic repression mediated among the master regulators in a three-node network. Further, our model predictions can offer putative mechanisms underlying relatively higher plasticity of Th17 phenotype as observed in vitro and in vivo. Together, our modeling framework characterizes phenotypic plasticity and heterogeneity as an outcome of emergent dynamics of a three-node regulatory network, such as the one mediated by T-bet/GATA3/ROR{gamma}T. Nuclear alpha-synuclein is present in the human brain and is modified in dementia with Lewy bodies Dementia with Lewy bodies is pathologically defined by the cytoplasmic accumulation of alpha-synuclein within neuronal cells in the brain. Alpha-synuclein is predominately pre-synaptic, but has been reported present in various subcellular compartments in cell and animal models. In particular, nuclear alpha-synuclein is evident in-vitro and in disease models and has been associated with altered DNA integrity, gene transcription, nuclear homeostasis. However, owing to various factors, the presence of alpha-synuclein in the nuclei of human brain cells remains controversial, as does its role in synucleinopathies.

Here, we close this gap and provide a unique demonstration confirming the presence of nuclear alpha-synuclein in post-mortem brain tissue obtained from cases of dementia with Lewy bodies as well as from controls via immunohistochemistry, immunoblot, and label-free mass-spectrometry.

Discrete intra-nuclear alpha-synuclein puncta reactive against phosphorylated serine 129-alpha-synuclein and pan-alpha-synuclein antibodies were observed in cortical neurons and non-neuronal cells in fixed brain sections and in isolated nuclear preparations from Dementia with Lewy bodies cases and matched controls. Subsequent biochemical analysis of subcellular fractionated tissue confirmed alpha-synuclein as present in a nuclear fraction at levels ~ 10-fold lower than in the cytoplasm. Critically, however, an increase in monomeric nuclear alpha-synuclein phosphorylated as serine 129 was observed in cases of dementia with Lewy bodies alongside higher molecular weight pan- and phosphorylation reactive alpha-synuclein species, consistent with the formation of intranuclear phosphorylated alpha-synuclein oligomers. Furthermore, the presence of nuclear alpha-synuclein was confirmed via label free mass spectrometry, as 6 unique alpha-synuclein derived peptide sequences were identified in nuclear fractions (71.4% sequence coverage).

Collectively, our data confirm the presence of nuclear alpha-synuclein in human brain tissue and describe nuclear pathology associated with dementia with Lewy bodies. These findings address a major controversy in the synucleinopathy field by confirming the presence of nuclear alpha-synuclein in autoptic human brain tissue and, for the first time, identify that alpha-synuclein is aggregated into novel and potentially pathological assemblies in the nucleus as part of the disease process associated with dementia with Lewy bodies and thus may contribute to the disease phenotype. Can single-component protein condensates form multiphase architectures? Phase-separated biomolecular condensates that contain multiple coexisting phases are widespread in vitro and in cells. Multiphase condensates emerge readily within multi-component mixtures of biomolecules (e.g. proteins and nucleic acids) when the different components present sufficient physicochemical diversity (e.g. in inter-molecular forces, structure, and chemical composition) to sustain separate coexisting phases. Because such diversity is highly coupled to the solution conditions (e.g. temperature, pH, salt, composition), it can manifest itself immediately from the nucleation and growth stages of condensate formation, develop spontaneously due to external stimuli, or progressively as the condensates age. Here, we investigate thermodynamic factors that can explain the intrinsic transformation of single-component condensates into multiphase architectures during the nonequilibrium process of ageing. We develop a multiscale model that integrates atomistic simulations of proteins, sequence-dependent coarse-grained simulations of condensates, and a minimal model of dynamically ageing condensates with non-conservative inter-molecular forces. Our nonequilibrium simulations of condensate ageing predict that single-component condensates that are initially homogeneous and liquid-like can transform into gel-core/liquid-shell or liquid-core/gel-shell multiphase condensates as they age, due to gradual and irreversible enhancement of inter-protein interactions. The type of multiphase architecture is determined by the ageing mechanism, the molecular organization of the gel and liquid phases, and the chemical make up of the protein. Notably, we predict that inter-protein disorder-to-order transitions within the prion-like domains of intracellular proteins could lead to the required non-conservative enhancement of inter-molecular interactions. Our study, therefore, predicts a potential mechanism

Significance StatementBiomolecular condensates are highly diverse systems spanning not only homogeneous liquid droplets, but also gels, glasses, and even multiphase architectures that contain various coexisting liquid-like and/or gel-like inner phases. Multiphase architectures form when the different biomolecular components in a multi-component condensate establish sufficiently imbalanced inter-molecular forces to sustain different coexisting phases. While such a requirement seems, at first glance, impossible to fulfil for a condensate formed exclusively of chemically-identical proteins (i.e., single-component), our simulations predict conditions under which this may be possible. During condensate ageing, a sufficiently large imbalance in inter-molecular interactions can emerge intrinsically from the accumulation of protein structural transitions--driving even single-component condensates into nonequilibrium liquid-core/gel-shell or gel-core/liquid-shell multiphase architectures. Targeted biallelic integration of an inducible Caspase 9 suicide gene for safer cellular therapies prevents development of drug-resistant escapees in human iPSCs Drug-inducible suicide systems may help to minimize risks of cellular therapies due to the tumor forming potential of human induced pluripotent stem cells (hiPSCs). Recent research challenged the usefulness of such systems since rare drug-resistant subclones were observed that showed elimination or silencing of the transgene.

We have introduced a drug-inducible Caspase9 suicide system (iCASP9) into the AAVS1 safe harbor locus of hiPSCs. In these cells, apoptosis could be efficiently induced in vitro. In mice, drug treatment generally led to rapid elimination of teratomas, but individual animals subsequently formed tumor tissue from monoallelic iCASP9 hiPSCs. Very rare drug-resistant subclones of monoallelic iCASP9 hiPSCs appeared in vitro with frequencies of ~ 3x10-8. Transgene elimination, presumably via Loss of Heterozygosity (LoH), or methylation of the CAG promoter but not methylation of the O_SCPLOWPPPC_SCPLOWO_SCPCAP1C_SCPCAPO_SCPLOWRC_SCPLOWO_SCPCAP12C_SCPCAPO_SCPLOWCC_SCPLOW locus were identified as underlying mechanisms. In contrast, we never observed any escapees from biallelic iCASP9 hiPSCs, even after treatment of up to 0.8 billion hiPSCs.

In conclusion, biallelic integration of an iCASP9 system in the AAVS1 locus may substantially contribute to the safety level of iPSC-based therapies, which should be calculated by relating clonal escapee frequencies to the cell number in tumors of a size that is readily detectable during routine screening procedures. Age of the bone marrow dictates clonality of smooth muscle-derived cells in the atherosclerotic plaque Aging is the predominant risk factor for atherosclerosis, the leading cause of death. Rare smooth muscle cell (SMC) progenitors clonally expand giving rise to up to [~]70% of atherosclerotic plaque cells; however, the effect of age on SMC clonality is not known. Our results indicate that aged bone marrow (BM)-derived cells non-cell autonomously induce SMC polyclonality and worsen atherosclerosis. Indeed, in myeloid cells from aged mice and humans, TET2 levels are reduced which epigenetically silences integrin {beta}3 resulting in increased tumor necrosis factor [TNF]- signaling. In turn, TNF signals through TNF receptor 1 on SMCs to promote proliferation and induces recruitment and expansion of multiple SMC progenitors into the atherosclerotic plaque. Notably, integrin {beta}3 overexpression in aged BM preserves dominance of the lineage of a single SMC progenitor and attenuates plaque burden. Our results demonstrate a molecular mechanism of aged macrophage-induced SMC polyclonality and atherogenesis and suggest novel therapeutic strategies.

Graphical abstractAge of BM-derived monocytes/macrophages determines clonality of SMC lineage in the atherosclerotic plaque. Atherogenesis is depicted in a young (a) or aged (b) host. Aged monocytes/macrophages have decreased levels of the epigenetic regulator TET2, leading to reduction of the 5-hydroxymethylcytosine (5hmC) mark on the Itgb3 promoter. The resulting low integrin {beta}3 levels in aged monocytes/macrophages induces high TNF- levels, facilitating recruitment and expansion of multiple SMC progenitors (polyclonality) in the atherosclerotic plaque and worse disease burden. In contrast, the young control is characterized by mono/oligoclonal SMC expansion in a smaller plaque.



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org.highwire.dtl.DTLVardef@12f7090org.highwire.dtl.DTLVardef@186ff92org.highwire.dtl.DTLVardef@1f4da69org.highwire.dtl.DTLVardef@2f509c_HPS_FORMAT_FIGEXP  M_FIG C_FIG Evaluation of methods for estimating coalescence times using ancestral recombination graphs The ancestral recombination graph (ARG) is a structure that describes the joint genealogies of sampled DNA sequences along the genome. Recent computational methods have made impressive progress towards scalably estimating whole-genome genealogies. In addition to inferring the ARG, some of these methods can also provide ARGs sampled from a defined posterior distribution. Obtaining good samples of ARGs is crucial for quantifying statistical uncertainty and for estimating population genetic parameters such as effective population size, mutation rate, and allele age. Here, we use standard neutral coalescent simulations to benchmark the estimates of pairwise coalescence times from three popular ARG inference programs: ARGweaver, Relate, and tsinfer+tsdate. We compare 1) the true coalescence times to the inferred times at each locus; 2) the distribution of coalescence times across all loci to the expected exponential distribution; 3) whether the sampled coalescence times have the properties expected of a valid posterior distribution. We find that inferred coalescence times at each locus are most accurate in ARGweaver, and often more accurate in Relate than in tsinfer+tsdate. However, all three methods tend to overestimate small coalescence times and underestimate large ones. Lastly, the posterior distribution of ARGweaver is closer to the expected posterior distribution than Relates, but this higher accuracy comes at a substantial trade-off in scalability. The best choice of method will depend on the number and length of input sequences and on the goal of downstream analyses, and we provide guidelines for the best practices.