How much does it take to be old? Modelling the time since the last harvesting to infer the distribution of overmature forests in France AimThe distribution of overmature forests in metropolitan France is poorly known, with only a few well-studied prominent sites, and has never been evaluated countrywide. Here, we modelled French forest reserves time since the last harvesting operation - a proxy for forest maturity - then inferred the current statistical distribution of overmature forests (i.e. forests over 50 years without harvesting) in France.

LocationMetropolitan France

MethodsWe used inventories from forest reserves and managed forests to calibrate a generalised linear mixed model explaining the time since the last harvesting with selected structural attributes and environmental variables. We then projected this model on the independent National Forest Inventory dataset. We thus obtained an updated estimation of the proportion and a rough distribution of overmature forest stands in metropolitan France.

ResultsWe found that high basal area of very large trees, high volumes of standing and downed deadwood, high diversity of tree-related microhabitats and more marginally diversity of decay stages best characterized the time since the last harvesting. Volumes of stumps and high density of coppices translating legacy of past forest management also distinguished more overmature plots. Our projection yielded an estimated 3% of French forests over 50 years without harvesting mostly located in more inaccessible areas (i.e. mountainous areas) and a promising proportion of future overmature forests if left unharvested.

Main conclusionsOur study showed that the time since the last harvesting is a good proxy for a combination of stand structure attributes key in characterising overmature temperate forests. It gives the first robust statistical estimate of the proportion of overmature forests and may serve to report on their status in metropolitan France. Our method could be implemented at a larger spatial scale, notably in countries with accessible National Forest Inventory and calibration data, to produce indicators at international level.
Specific sequence of arrival promotes coexistence via spatial niche preemption by the weak competitor Historical contingency, such as the order of species arrival, can modify competitive outcomes via niche modification or preemption. However, how these mechanisms ultimately modify stabilising niche and average fitness differences remains largely unknown. By experimentally assembling two congeneric spider mite species feeding on tomato plants during two generations, we show that order of arrival affects species competitive ability and changes the outcome of competition. Contrary to expectations, order of arrival did not cause positive frequency dependent priority effects. Instead, coexistence was predicted when the inferior competitor (Tetranychus urticae) arrived first. In that case, T. urticae colonised the preferred feeding stratum (leaves) of T. evansi leading to spatial niche preemption, which equalised fitness and reduced niche differences, driving community assembly to a close-to-neutrality scenario. Our study demonstrates how the order of species arrival and the spatial context of competitive interactions can jointly determine whether species can coexist.
Data-Driven Network Models for Genetic Circuits From Time-Series Data with Incomplete Measurements Synthetic gene networks are frequently conceptualized and visualized as static graphs. This view of biological programming stands in stark contrast to the transient nature of biomolecular interaction, which is frequently enacted by labile molecules that are often unmeasured. Thus, the network topology and dynamics of synthetic gene networks can be difficult to verify in vivo or in vitro, due to the presence of unmeasured biological states. Here we introduce the dynamical structure function as a new mesoscopic, data-driven class of models to describe gene networks with incomplete measurements. We introduce a network reconstruction algorithm and a code base for reconstructing the dynamical structure function from data, to enable discovery and visualization of graphical relationships in a genetic circuit diagram as time-dependent functions rather than static, unknown weights. We prove a theorem, showing that dynamical structure functions can provide a data-driven estimate of the size of crosstalk fluctuations from an idealized model. We illustrate this idea with numerical examples. Finally, we show how data-driven estimation of dynamical structure functions can explain failure modes in two experimentally implemented genetic circuits, a historical genetic circuit and a new E. coli based transcriptional event detector. Affordable Caenorhabditis elegans tracking system for classroom use For decades the nematode C. elegans has served as an outstanding research organism owing to its unsurpassed experimental amenability. This advantage has also made this tiny worm an attractive vehicle for science instruction across higher learning institutions. However, the prohibitive cost associated with the automated behavioral assessment of these animals remains an obstacle preventing their full adoption in undergraduate and high school settings. To improve this situation, we developed an inexpensive worm tracking system for use by high school interns and undergraduate students. Over the past two years this tracker has been successfully used by undergraduate students in our introductory Cell and Molecular lab (BSC220) at Illinois State University. Here we describe and demonstrate the use of our inexpensive worm tracking system. PLB-985 neutrophil-like cells as a model to study Aspergillus fumigatus pathogenesis Fungal infections remain a major global concern. Emerging fungal pathogens and increasing rates of resistance mean that additional research efforts and resources must be allocated to advancing our understanding of fungal pathogenesis and developing new therapeutic interventions. Neutrophilic granulocytes are a major cell type involved in protection against the important fungal pathogen Aspergillus fumigatus, where they employ numerous defense mechanisms, including production of antimicrobial extracellular vesicles. A major draw-back to work with neutrophils is the lack of a suitable cell line system for the study of fungal pathogenesis. To address this problem, we assessed the feasibility of using differentiated PLB-985 neutrophil-like cells as an in vitro model to study A. fumigatus infection. We find that dimethylformamide-differentiated PLB-985 cells provide a useful recapitulation of many aspects of A. fumigatus interactions with primary human polymorphonuclear leukocytes. We show that differentiated PLB-985 cells phagocytose fungal conidia and acidify conidia-containing phagolysosomes similar to primary neutrophils, release neutrophil extracellular traps, and also produce antifungal extracellular vesicles in response to infection. In addition, we provide an improved method for the isolation of extracellular vesicles produced during infection by employing a size-exclusion chromatography-based approach. Advanced LC-MS/MS proteomics revealed an enrichment of extracellular vesicle marker proteins and a decrease of cytoplasmic proteins in extracellular vesicles isolated using this improved method. Ultimately, we find that differentiated PLB-985 cells can serve as a genetically tractable model to study many aspects of A. fumigatus pathogenesis.

IMPORTANCEPolymorphonuclear leukocytes are an important defense against human fungal pathogens, yet our model systems to study this group of cells remains very limited in scope. In this study, we established that differentiated PLB-985 cells can serve as a model to recapitulate several important aspects of human polymorphonuclear leukocyte interactions with the important human fungal pathogen Aspergillus fumigatus. The proposed addition of a cultured neutrophil-like cell line to the experimental toolbox to study fungal pathogenesis will allow for a more mechanistic description of neutrophil antifungal biology. In addition, the easier handling of the cell line compared to primary human neutrophils allowed us to use PLB-985 cells to provide an improved method for isolation of neutrophil-derived extracellular vesicles using size-exclusion chromatography. Together, these results provide significant tools and a baseline knowledge for the future study of neutrophil-derived extracellular vesicles in the laboratory. Glycolysis/gluconeogenesis specialization in microbes is driven by biochemical constraints of flux sensing Central carbon metabolism is highly conserved across microbial species, but can catalyze very different pathways depending on the organism and their ecological niche. Here, we study the dynamic re-organization of central metabolism after switches between the two major opposing pathway configurations of central carbon metabolism, glycolysis and gluconeogenesis in Escherichia coli, Pseudomonas aeruginosa and Pseudomonas putida. We combined growth dynamics and dynamic changes of intracellular metabolite levels with a coarse-grained model that integrates fluxes, regulation, protein synthesis and growth and uncovered fundamental limitations of the regulatory network: after nutrient shifts, metabolite concentrations collapse to their equilibrium, rendering the cell unable to sense which direction the flux is supposed to flow through the metabolic network. The cell can partially alleviate this by picking a preferred direction of regulation at the expense of increasing lag times in the opposite direction. Moreover, decreasing both lag times simultaneously comes at the cost of reduced growth rate or higher futile cycling between metabolic enzymes. These three trade-offs can explain why microorganisms specialize for either glycolytic or gluconeogenic substrates and can help elucidate the complex growth patterns exhibited by different microbial species.

Graphical synopsis O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

Standfirst textMicrobes face a series of fundamental trade-offs that limit their ability to optimize simultaneously for both glycolytic and gluconeogenic growth.

Bullet pointsO_LILag times between glycolysis and gluconeogenesis show asymmetry in many microbes: A long lag in one direction, but a short lag in the other.
C_LIO_LILong lag times are caused by an inability to sense fluxes after nutrient shifts.
C_LIO_LIWith existing regulation, lag time asymmetry can only be overcome by reducing either growth rate or increasing futile cycling in metabolism.
C_LI Characterization of methylation profiles in spontaneous preterm birth placental villous tissue Preterm birth is a global public health crisis which results in significant neonatal and maternal mortality. Yet little is known regarding the molecular mechanisms of idiopathic spontaneous preterm birth, and we have few diagnostic markers for adequate assessment of placental development and function. Previous studies of placental pathology and our transcriptomics studies suggest a role for placental maturity in idiopathic spontaneous preterm birth. It is known that placental DNA methylation changes over gestation. We hypothesized that if placental hypermaturity is present in our samples, we would observe a unique idiopathic spontaneous preterm birth DNA methylation profile potentially driving the gene expression differences we previously identified in our placental samples. Our results indicate the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern suggesting hypermaturity. Only seven significant differentially methylated regions fitting the idiopathic spontaneous preterm birth specific (relative to the controls) profile were identified, indicating unusually high similarity in DNA methylation between idiopathic spontaneous preterm birth and term birth samples. We identified an additional 1,718 significantly methylated regions in our gestational age matched controls were the idiopathic spontaneous preterm birth DNA methylation pattern mimics the term birth methylation pattern, again indicating a striking level of similarity between the idiopathic spontaneous preterm birth and term birth samples. Pathway analysis of these regions revealed differences in genes within the WNT and Cadherin signaling pathways, both of which are essential in placental development and maturation. Taken together, these data demonstrate that the idiopathic spontaneous preterm birth samples are molecularly more mature than expected given their respective gestational age which likely impacts birth timing. Hidden dynamics of human proteasome autoregulation during protein degradation The cellular functions are executed by macromolecular complexes in nonequilibrium dynamic processes, which exhibit a vast diversity of conformational states. Solving conformational continuum of important complexes at atomic level remains a key challenge in the methodology of computational biophysics. Here we introduce a deep-learning framework, named AlphaCryo4D, which enables atomic-level cryogenic electron microscopy reconstructions of nonequilibrium conformational continuum. AlphaCryo4D integrates 3D deep residual learning with manifold embedding of energy landscapes, which simultaneously improves 3D classification accuracy and reconstruction resolution via an energy-based particle-voting algorithm. Applications of this methodology to six experimental datasets demonstrated its generality in breaking resolution barrier of visualizing dynamic components of functional complexes, in choreographing continuous inter-subunit motions and in exploring their  hidden conformational space. Importantly, AlphaCryo4D identified 64 conformers of the substrate-bound human 26S proteasome and reconstituted single-nucleotide-exchange dynamics of proteasomal AAA-ATPase motor during translocation initiation, which together illuminates a grand hierarchical allostery for proteasome autoregulation. Resolving when (and where) the Thylacine went extinct Like the Dodo and Passenger Pigeon before it, the predatory marsupial Thylacine (Thylacinus cynocephalus), or  Tasmanian tiger, has become an iconic symbol of human-caused extinction. The last captive animal died in 1936, but even today reports of the Thylacines possible ongoing survival in remote regions of Tasmania are newsworthy and capture the publics imagination. Extirpated from mainland Australia in the mid-Holocene, the large island of Tasmania became the species final stronghold. Following European settlement in the 1800s, the Thylacine was heavily persecuted and pushed to the margins of its range, although many sightings were reported thereafter--even well beyond the 1930s. To gain a new depth of insight into the extinction of the Thylacine, we assembled an exhaustive database of 1,237 observational records from Tasmania (from 1910 onwards), quantified their uncertainty, and charted the patterns these revealed. We also developed a new method to visualize the species 20th-century spatio-temporal dynamics, to map potential post-bounty refugia and pinpoint the most-likely location of the final persisting subpopulation. A direct reading of the high-quality records (confirmed kills and captures, in combination with sightings by past Thylacine hunters and trappers, wildlife professionals and experienced bushmen) implies a most-likely extinction date within four decades following the last capture (i.e., 1940s to 1970s). However, uncertainty modelling of the entire sighting record, where each observation is assigned a probability and the whole dataset is then subject to a sensitivity analysis, suggests that extinction might have been as recent as the late 1980s to early 2000s, with a small chance of persistence in the remote south-western wilderness areas. Beyond the intrinsically fascinating problem of reconstructing the final fate of the Thylacine, the new spatio-temporal mapping of extirpation developed herein would also be useful for conservation prioritization and search efforts for other rare taxa of uncertain status. Identification of the three zinc-binding sites on Tau protein Tau protein has been extensively studied due to its key roles in microtubular cytoskeleton regulation and in the formation of aggregates found in some neurodegenerative diseases. Recently it has been shown that zinc is able to induce tau aggregation by interacting with several binding sites. However, the precise location of these sites and the molecular mechanism of zinc-induced aggregation remain unknown. Here we used Nuclear Magnetic Resonance (NMR) to identify zinc binding sites on hTau40 isoform. These experiments revealed three distinct zinc binding sites on tau, located in the N-terminal part (H14, H32, H94, and H121), the repeat region (H299, C322, H329 and H330) and the C-terminal part (H362, H374, H388 and H407). Further analysis enabled us to show that the C-terminal and the N-terminal sites are independent of each other. Using molecular simulations, we modeled the structure of each site in a complex with zinc. Given the clinical importance of zinc in tau aggregation, our findings pave the way for designing potential therapies for tauopathies.

HighlightsO_LIZinc is known to induce tau aggregation in neurodegenerative diseases
C_LIO_LIZinc binding locations and mechanism are not yet clear
C_LIO_LIUsing NMR we localized 3 zinc binding site on tau
C_LIO_LIBy molecular simulations, we proposed a modeled structure of each site
C_LIO_LIOur findings pave the way for designing potential therapies for tauopathies
C_LI Hnf1b-CreER causes efficient recombination of a Rosa26-RFP reporter in duct and islet δ cells The Hnf1b-CreERT2 BAC transgenic (Tg(Hnf1b-cre/ERT2)1Jfer) has been used extensively to trace the progeny of pancreatic ducts in developmental, regeneration, or cancer models. Hnf1b-CreERT2 transgenics have been used to show that cells from that form a duct-like plexus in the embryonic pancreas are bipotent duct-endocrine progenitors, whereas adult mouse duct cells are not a common source of {beta} cells in various regenerative settings. The interpretation of such genetic lineage tracing studies is critically dependent on a correct understanding of the cell type specificity of recombinase activity with each reporter system. We have re-examined the performance of Hnf1b-CreERT2 with a Rosa26-RFP reporter transgene. This showed inducible recombination of up to 96% adult duct cells, a much higher efficiency than previously used reporter transgenes. Despite this high duct-cell excision, recombination in  and {beta} cells remained very low, similar to previously used reporters. However, nearly half of somatostatin-expressing {delta} cells showed reporter activation, which was due to Cre expression in {delta} cells rather than to duct to {delta} cell conversions. The high recombination efficiency in duct cells indicates that the Hnf1b-CreERT2 model can be useful for both ductal fate mapping and genetic inactivation studies. The recombination in {delta} cells does not modify the interpretation of studies that failed to show duct conversions to other cell types, but needs to be considered if this model is used in studies that aim to modify the plasticity of pancreatic duct cells. Environment dependent benefits of inter-individual variation in honey bee recruitment Inter-individual differences in behaviour within the members of a social group can affect the groups productivity. In eusocial insects, individual differences amongst workers in a colony play a central role division of labour and task allocation. Extensive empirical and theoretical work has highlighted variation in response thresholds as a proximate mechanism underlying individual behavioural differences and hence division of labour. However, other response parameters, like response probability and intensity, can affect these differences. In this study, we first extended a previously published agent-based model on honey bee foraging to understand the relative importance of response (dance) probability and response (dance) intensity in the task of recruitment. Comparing variation obtained from the simulations with previously published empirical data, we found that response intensity plays a more important role than probability in producing consistent inter-individual differences in recruitment behaviour. We then explored the benefits provided by this individual variation in recruitment behaviour to the colonys collective foraging effort under different environmental conditions. Our results revealed that individual variation leads to a greater energetic yield per forager, but only when food is abundant. Our study highlights the need to consider all response parameters while studying division of labour and adds to the growing body of evidence linking individual variation in behavioural responses to the success of social groups. Stress alters the activity of Leydig cells dependently on the diurnal time BackgroundThe increasing amount of data points to the circadian timing system as an essential part of processes regulating androgen homeostasis. However, the relationship between stress response, timekeeping-, and steroidogenesis-related systems is unexplored.

ObjectiveThe purpose of the study was to analyze the stress-response of the testosterone-producing Leydig cells depending on the stressful events time.

Materials and methodsThe study was designed to follow the effects of 3-hour immobilization (IMO) applied at different periods during the day. The IMO performed once (1xIMO) or repeated in 10 consecutive days (10xIMO). Principal-component-analysis (PCA) followed the expression study of the clock and steroidogenic-related genes in Leydig cells.

ResultsBoth types of IMO in all investigated periods increased corticosterone and decreased testosterone blood level. Transcriptional analysis revealed different sensitivity to IMO events depending on the circadian time. The majority of steroidogenesis-related genes (Lhcgr, Cyp11a1, Cyp17a1, Hsd3b1/2) were down-regulated in the inactive but unchanged or even up-regulated in the active phase of the day. Both types of IMO potentiated the expression of clock elements Bmal1/BMAL1, Per1/PER1 regardless of the days stage and reduced Reverba in the inactive phase. The PCA confirmed a major shift, for both IMO-types, in the transcription of steroidogenesis and clock genes across the inactive/active phase. Further, the diurnal pattern of the glucocorticoid receptor (Nr3c1/GR) expression in Leydig cells was increased in the inactive phase due to 10xIMO. The observed time-dependent IMO-response of the Leydig cells correlated with different GR engagements.

DiscussionStress- and the circadian-system coordinatively shape Leydig cells physiology, assuming diverse GR engagement as a possible factor in mediating the diurnal effect of stress.

ConclusionThe Leydig cells stress-response depends on the time of the stressful situation, emphasizing the importance of circadian activity in supporting androgen homeostasis and male fertility. Large-scale analysis of SARS-CoV-2 synonymous mutations reveals the adaptation to the human codon usage during the virus evolution Many large national and transnational studies have been dedicated to the analysis of SARS-CoV-2 genome, most of which focused on missense and nonsense mutations. However, approximately 30% of the SARS-CoV-2 variants are synonymous, therefore changing the target codon without affecting the corresponding protein sequence.

By performing a large-scale analysis of sequencing data generated from almost 400,000 SARS-CoV-2 samples, we show that silent mutations increasing the similarity of viral codons to the human ones tend to fixate in the viral genome over-time. This indicates that SARS-CoV-2 codon usage is adapting to the human host, likely improving its effectiveness in using the human aminoacyl-tRNA set through the accumulation of deceitfully neutral silent mutations.

One-Sentence SummarySynonymous SARS-CoV-2 mutations related to the activity of different mutational processes may positively impact viral evolution by increasing its adaptation to human codon usage. An integrative process-based model for biomass and yield estimation of hardneck garlic (Allium sativum) We introduce an integrative process-driven crop model for garlic (Allium sativum). Building on our previous model that simulated key phenological, morphological, and physiological features of a garlic plant, the new garlic model provides comprehensive and integrative estimations of biomass accumulation and yield formation under diverse environmental conditions. This model also showcases an application of Cropbox to develop a comprehensive crop model. Cropbox is a crop modeling framework featuring declarative modeling language and unified simulation interface for building and improving crop models. Using Cropbox, we first evaluated the model performance against three datasets with an emphasis on biomass and yield measured under different environmental conditions and growing seasons. We then applied the model to simulate optimal planting dates under future climate conditions for assessing climate adaptation strategies between two contrasting locations in South Korea: the current growing region (Gosan) and an unfavorable cold winter region (Chuncheon, Gangwon-do). The model simulated the growth and development of a southern-type cultivar (Namdo, Jeju-do) reasonably well. Under RCP (Representative Concentration Pathway) scenarios, an overall delay in optimal planting date from a week to a month and a slight increase in potential yield were expected in Gosan. Expansion of growing region to northern area including Chuncheon was expected due to mild winter temperatures in the future and may allow Namdo cultivar production in more regions. The predicted optimal planting date in the new region was similar to the current growing region that favors early fall planting. Our new integrative garlic model provides mechanistic, process-driven crop responses to environmental cues and can be useful for assessing climate impacts and identifying crop specific climate adaptation strategies for the future. Analysis of the leaf metabolome in Arabidopsis thaliana mutation accumulation lines reveals association of pleiotropy and fitness consequences Understanding the mechanisms by which mutations affect fitness and the distribution of mutational effects are central goals in evolutionary biology. Mutation accumulation (MA) lines have long been an important tool for understanding the effect of new mutations on fitness, phenotypic variation, and mutational parameters. However, there is a clear gap in predicting the effect of specific new mutations to their effects on fitness. Here, we complete gene ontology analysis and metabolomics experiments on Arabidopsis thaliana MA lines to determine how spontaneous mutations directly affect global metabolic output in lines that have measured fitness consequences. For these analyses, we compared three lines with relative fitness consistently higher than the unmutated progenitor and three lines with lower relative fitness as measured in four different field trials. In a gene ontology analysis, we find that the high fitness lines were significantly enriched in mutations in or near genes with transcription regulator activity. We also find that although they do not have an average difference in the number of mutations, low fitness lines have significantly more metabolic subpathways disrupted than high fitness lines. Taken together, these results suggest that the effect of a new mutation on fitness depends less on the specific metabolic pathways disrupted and more on the pleiotropic effects of those mutations, and that organisms can explore a considerable amount of physiological space with only a few mutations.

Significance StatementAs the source of all genetic variation, new mutations are crucial for understanding how organisms adapt to their environment. However, the ways in which new mutations affect the range of metabolic reactions that occur in the cell is unknown. With a combination of gene functional analyses and measurement of the small molecules that drive cellular function and physiology, we find that mutations associated with high fitness are disproportionately found in or near proteins-coding genes that regulate the specific timing and location of gene expression and are less disruptive of cellular physiology. SERCA function is impaired in skeletal and cardiac muscles from young DBA/2J mdx mice The DBA/2J (D2) mdx mouse has emerged as a more severe model of Duchenne muscular dystrophy when compared to the traditional C57BL/10 (C57) mdx mouse. Here, we questioned whether sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) function would differ in muscles from young D2 and C57 mdx mice. In gastrocnemius muscles, both D2- and C57 mdx mice exhibited signs of impaired Ca2+ uptake, however, this was more severe in D2 mdx mice. Maximal SERCA activity was lowered only in D2 mdx gastrocnemius muscles and not C57 mdx muscles. Furthermore, in the left ventricle and diaphragm, Ca2+ uptake was impaired in C57 mdx muscles with lowered rates of Ca2+ uptake compared with C57 WT mice, whereas in muscles from D2 mdx mice, rates of Ca2+ uptake were unattainable due to the severe impairments in their ability to transport Ca2+. Overall, our study demonstrates that SERCA function is drastically impaired in young D2 mdx mice. Time- and cell-dependent atypia and cell death are caused by progressive deficiency in DNA replication Pleiotropy caused by single-gene mutations is common and poorly understood. A zebrafish null mutant of DNA polymerase  subunit B, huli hutu (hht), evolves a complex pleiotropy associated with DNA damage and S phase arrest across multiple organ systems over 5-7 days, including nuclear atypia, a common cellular feature in human cancers and pre-cancers, in gastrointestinal organs, and nuclear fragmentation in the eye and brain. The pleiotropic pattern of hht phenotypes is explained by progressive loss of wild-type maternal pola2 function in homozygous mutant embryos whose pola2 mRNA becomes undetectable by 24 hours post-fertilization (hpf). Inhibition of DNA synthesis by aphidicolin or hydroxyurea in wild-type embryos from 24 hpf phenocopied the pleiotropic pattern of hht. These results are consistent with a model in which time-sensitive, reduced capacity for DNA synthesis results in cell death in fast-replicating cells, and nuclear atypia in tissues with fewer and larger cells. Autotaxin is a Potential Link between Genetic Risk Factors and Pathogenesis of Systematic Lupus Erythematosus in Plasmacytoid Dendritic Cells BackgroundThe importance of autotaxin, an enzyme that catalyzes lysophospholipid production, has recently been recognized in various diseases, including cancer and autoimmune diseases. Herein, we examined the role of autotaxin in systemic lupus erythematosus (SLE), utilizing data from ImmuNexUT, a comprehensive database consisting of transcriptome data and expression quantitative trait locus (eQTL) data of immune cells from patients with immune-mediated disorders.

MethodsSerum autotaxin concentrations in patients with SLE and healthy controls (HCs) were compared. The transcriptome data of patients with SLE and age-and sex-matched HCs were obtained from ImmuNexUT. The expression of ENPP2, the gene encoding autotaxin, was examined in peripheral blood immune cells. Next, weighted gene correlation network analysis (WGCNA) was performed to identify genes with expression patterns similar to ENPP2. The ImmuNexUT eQTL database and public epigenomic databases were used to infer the relationship between autotaxin and pathogenesis of SLE.

ResultsAutotaxin levels were elevated in the serum of patients with SLE compared to HCs. Furthermore, the expression of ENPP2 was higher in plasmacytoid dendritic cells (pDCs) than in other immune cell subsets, and its expression was elevated in pDCs of patients with SLE compared to HCs. In WGCNA, ENPP2 belonged to a module that correlated with disease activity. This module was enriched in interferon-associated genes and included genes whose expression was influenced by single-nucleotide polymorphisms associated with SLE, suggesting that it is a key module connecting genetic risk factors of SLE with disease pathogenesis. Analysis utilizing the ImmuNexUT eQTL database and public epigenomic databases suggested that the increased expression of ENPP2 in pDCs from patients with SLE may be caused by increased expression of interferon-associated genes and increased binding of STAT3 complexes to the regulatory region of ENPP2.

ConclusionsAutotaxin may play a critical role in connecting genetic risk factors of SLE to disease pathogenesis in pDCs. Microbial Communities Performing Hydrogen Solventogenic Metabolism of Volatile Fatty Acids 1This work evaluates four different physicochemical pretreatments (acidic, thermal, acidic-thermal and thermal-acidic) on an anaerobic inoculum used for alcohol production from acetate and butyrate. All experiments were conducted in single batches using acetate and butyrate as substrates at 30 {degrees}C and with a pressurized headspace of pure H2 at 2.15 atm (218.2 MPa). Thermal and acidic-thermal pretreatments lead to higher production of both ethanol and butanol. Mathematical modelling shows that the highest attainable concentrations of ethanol and butanol produced were 122 mg L-1 and 97 mg L-1 for the thermal pretreatment (after 17.5 days) and 87 mg L-1 and 143 mg L-1 for the acidic-thermal pretreatment (after 18.9 days). Acetate was produced in all assays. Thermodynamic data indicated that a high H2 partial pressure favoured solventogenic metabolic pathways. Finally, sequencing data showed that both thermal and acidic-thermal pretreatments selected mainly the bacterial genera Pseudomonas, Brevundimonas and Clostridium. The acidic-thermal pretreatment selected a bacterial community more adapted to the conversion of acetate and butyrate into ethanol and butanol, respectively. Thermal-acidic pretreatment was unstable, showing significant variability between replicates. Acidic pretreatment showed the lowest alcohol production. P2X2 receptor subunit interfaces are missense variant hotspots where mutations tend to increase apparent ATP affinity Background and PurposeP2X receptors (P2XRs) are trimeric ligand-gated ion channels (LGICs) that open a cation-selective pore in response to ATP binding to their large extracellular domain (ECD). The seven known P2XR subtypes can assemble as homo- or heterotrimeric complexes and contribute to numerous physiological functions, including nociception, inflammation and hearing. The overall structure of P2XRs is well established, but little is known about the spectrum and prevalence of human genetic variations and the functional implications in specific domains.

Experimental ApproachHere we examine the impact of P2X2 receptor (P2X2R) inter-subunit interface missense variants identified in the human population or through structural predictions. We test both single and double mutants through electrophysiological and biochemical approaches.

Key resultsWe demonstrate that predicted ECD inter-subunit interfaces display a higher-than-expected density of missense variations and that the majority of mutations that disrupt putative inter-subunit interactions result in channels with higher apparent ATP affinity. Lastly, we show that double mutants at the subunit interface show significant energetic coupling, especially if located in close proximity.

Conclusions and ImplicationsWe provide the first structural mapping of the mutational burden across the human population in a LGIC and show that the density of missense mutations is constrained between protein domains, indicating evolutionary selection at the domain level. Our data may indicate that, unlike other LGICs, P2X2Rs have evolved an intrinsically high threshold for activation, possibly to allow for additional modulation or as a cellular protection mechanism against overstimulation.

Bullet point summary What is already known: O_LIP2X2 receptors are ATP-activated ion channels implicated in hearing and nociceptice pathways
C_LI
 What this study adds: O_LIA structural mapping of missense variants observed in the human population
C_LIO_LIWe identify the intersubunit-interface as a variant hotspot and decipher functional impact of mutations
C_LI
 Clinical significance: O_LIThe development of both inhibitors and activators of P2X2 receptor function may be required
C_LI Construction of a new chromosome-scale, long-read reference genome assembly for the Syrian hamster, Mesocricetus auratus BackgroundThe Syrian hamster (Mesocricetus auratus) has been suggested as a useful mammalian model for a variety of diseases and infections, including infection with respiratory viruses such as SARS-CoV-2. The MesAur1.0 genome assembly was generated in 2013 using whole-genome shotgun sequencing with short-read sequence data. Current more advanced sequencing technologies and assembly methods now permit the generation of near-complete genome assemblies with higher quality and greater continuity.

FindingsHere, we report an improved assembly of the M. auratus genome (BCM_Maur_2.0) using Oxford Nanopore Technologies long-read sequencing to produce a chromosome-scale assembly. The total length of the new assembly is 2.46 Gbp, similar to the 2.50 Gbp length of a previous assembly of this genome, MesAur1.0. BCM_Maur_2.0 exhibits significantly improved continuity with a scaffold N50 that is 6.7 times greater than MesAur1.0. Furthermore, 21,616 protein coding genes and 10,459 noncoding genes are annotated in BCM_Maur_2.0 compared to 20,495 protein coding genes and 4,168 noncoding genes in MesAur1.0. This new assembly also improves the unresolved regions as measured by nucleotide ambiguities, where approximately 17.11% of bases in MesAur1.0 were unresolved compared to BCM_Maur_2.0 in which the number of unresolved bases is reduced to 3.00%.

ConclusionsAccess to a more complete reference genome with improved accuracy and continuity will facilitate more detailed, comprehensive, and meaningful research results for a wide variety of future studies using Syrian hamsters as models. Glucose dynamics during ozone exposure measured using radiotelemetry: Stress drivers BackgroundStress-related neurobehavioral and metabolic disorders are associated with altered circulating adrenal-derived hormones and hyperglycemia. Temporal assessment of glucose and these hormones is critical for insights on an individuals health.

ObjectivesHere we used implantable-telemetry in rats to assess real-time changes in circulating glucose during and after exposure to the air pollutant ozone, and link responses to circulating neuroendocrine stress and metabolic hormones. We also compared rodent glucose and corticosterone (cortisol in humans) responses to humans exposed to ozone.

MethodsFirst, using a cross-over design, we monitored glucose levels during single or repeated ozone exposures (0.0, 0.2, 0.4 and 0.8-ppm) and non-exposure periods in male Wistar-Kyoto-rats implanted with glucose-telemeters. A second cohort of un-implanted rats was exposed to ozone (0.0, 0.4 or 0.8-ppm) for 30-min, 1-hour, 2-hour, or 4-hour with hormones measured immediately after exposure. Then we assessed glucose metabolism in sham and adrenalectomized rats with or without pharmacological interventions of adrenergic and glucocorticoid receptors. Finally, we assessed glucose and cortisol in serum samples from a clinical study involving exposure of human volunteers to air or 0.3 ppm ozone.

ResultsOzone (0.8-ppm) caused hyperglycemia and hypothermia beginning 90-min into exposure, with reversal of effects 4-6 hours post-exposure. Glucose monitoring during four daily 4-hour ozone exposures revealed duration of hyperglycemia, adaptation, and diurnal variations. Ozone-induced hyperglycemia was preceded by increased adrenocorticotropic hormone, corticosterone, and epinephrine, but depletion of thyroid-stimulating, prolactin, and luteinizing hormones. Hyperglycemia was inhibited in rats that were adrenalectomized and/or treated with glucocorticoid inhibitor. The depletion of cortisol was dampened in humans exposed to ozone during intermittent exercise.

DiscussionWe demonstrate for the first time the temporality of neuroendocrine-stress-mediated biological sequalae responsible for ozone-induced metabolic dysfunction as exposure occurs. Real-time glucose monitoring with stress hormones assessment may be useful in identifying interactions among pollutants and stress-related illnesses. Feature-reweighted representational similarity analysis: A method for improving the fit between computational models, brains, and behavior Representational Similarity Analysis (RSA) has emerged as a popular method for relating representational spaces from human brain activity, behavioral data, and computational models. RSA is based on the comparison of representational (dis-)similarity matrices (RDM or RSM), which characterize the pairwise (dis-)similarities of all conditions across all features (e.g. fMRI voxels or units of a model). However, classical RSA treats each feature as equally important. This  equal weights assumption contrasts with the flexibility of multivariate decoding, which reweights individual features for predicting a target variable. As a consequence, classical RSA may lead researchers to underestimate the correspondence between a model and a brain region and, in case of model comparison, may lead them to select an inferior model. The aim of this work is twofold: First, we sought to broadly test feature-reweighted RSA (FR-RSA) applied to computational models and reveal the extent to which reweighting model features improves RSM correspondence and affects model selection. Previous work suggested that reweighting can improve model selection in RSA but it has remained unclear to what extent these results generalize across datasets and data modalities. To draw more general conclusions, we utilized a range of publicly available datasets and three popular deep neural networks (DNNs). Second, we propose voxel-reweighted RSA, a novel use case of FR-RSA that reweights fMRI voxels, mirroring the rationale of multivariate decoding of optimally combining voxel activity patterns. We found that reweighting individual model units markedly improved the fit between model RSMs and target RSMs derived from several fMRI and behavioral datasets and affected model selection, highlighting the importance of considering FR-RSA. For voxel-reweighted RSA, improvements in RSM correspondence were even more pronounced, demonstrating the utility of this novel approach. We additionally show that classical noise ceilings can be exceeded when FR-RSA is applied and propose an updated approach for their computation. Taken together, our results broadly validate the use of FR-RSA for improving the fit between computational models, brain, and behavioral data, possibly allowing us to better adjudicate between competing computational models. Further, our results suggest that FR-RSA applied to brain measurement channels could become an important new method to assess the correspondence between representational spaces. 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. Mitochondria preserve an autarkic one-carbon cycle to confer growth-independent cancer cell migration and metastasis Progression of primary cancer to metastatic disease is the most common cause of death in cancer patients with minimal treatment options available. Canonical drugs target mainly the proliferative capacity of cancer cells, which often leaves slow-proliferating, persistent cancer cells unaffected. Metabolic determinants that contribute to growth-independent functions supporting resistance and metastatic dissemination are still poorly understood.

In the present study, we revealed that antifolate treatment results in an uncoupled and autarkic mitochondrial one-carbon (1C) metabolism allowing sustained serine catabolism and formate overflow when cytosolic 1C metabolism is impaired. Interestingly, antifolate dependent growth-arrest did not correlate with decreased migration capacity. Therefore, using the antifolate Methotrexate as a tool compound allowed us to disentangle proliferation and migration to profile the metabolic phenotype of migrating (growth-arrested) cells. Supported by an increased NAD/NADH ratio, we observed increased serine de novo synthesis and increased serine catabolism to formate.

Consequently, inhibition of serine de novo synthesis using the competitive PHGDH-inhibitor BI-4916 or direct inhibition of mitochondrial 1C metabolism reduced cancer cell migration. Using an orthotopic breast cancer model, we show that sole inhibition of mitochondrial serine catabolism does not affect primary tumor growth but strongly inhibits pulmonary metastasis.

We conclude that mitochondrial 1C metabolism, despite being dispensable for proliferative capacities, confers an advantage to cancer cells by supporting their motility potential.

Our results improve our understanding of 1C metabolism and of metabolic determinants that support the process of cancer cell migration and metastasis.