Evidence for Deleterious Antigenic Imprinting in SARS-CoV-2 Immune Response A previous report demonstrated the strong association between the presence of antibodies binding to an epitope region from SARS-CoV-2 nucleocapsid, termed Ep9, and COVID-19 disease severity. Patients with anti-Ep9 antibodies (Abs) had hallmarks of antigenic imprinting (AIM), including early IgG upregulation and cytokine-associated injury. Thus, the immunological memory of a previous infection was hypothesized to drive formation of suboptimal anti-Ep9 Abs in severe COVID-19 infections. This study identifies a putative primary antigen capable of stimulating production of cross-reactive, anti-Ep9 Abs. Binding assays with patient blood samples directly show cross-reactivity between Abs binding to Ep9 and only one bioinformatics-derived, homologous potential antigen, a sequence derived from the neuraminidase protein of H3N2 Influenza A virus. This cross-reactive binding is highly influenza strain specific and sensitive to even single amino acid changes in epitope sequence. The neuraminidase protein is not present in the influenza vaccine, and the anti-Ep9 Abs likely resulted from the widespread influenza infection in 2014. Therefore, AIM from a previous infection could underlie some cases of COVID-19 disease severity.

ImportanceInfections with SARS-COV-2 result in diverse disease outcomes, ranging from asymptomatic to fatal. The mechanisms underlying different disease outcomes remain largely unexplained. Previously, our laboratory identified a strong association between the presence of an antibody and increased disease severity in a subset of COVID-19 patients. Here, we report that this severity-associated antibody cross-reacts with viral proteins from an influenza A viral strain from 2014. Therefore, we speculate that antibodies generated against previous infections, like the 2014 influenza A, play a significant role in directing some peoples immune responses against SARS-COV-2. Such understanding of the sources and drivers of COVID-19 disease severity can help early identification and pre-emptive treatment.
High temporal resolution systems profiling reveals distinct patterns of interferon response after Covid-19 mRNA vaccination and SARS-CoV2 infection Knowledge of the mechanisms underpinning the development of protective immunity conferred by mRNA vaccines is fragmentary. Here we investigated responses to COVID-19 mRNA vaccination via ultra-low-volume sampling and high-temporal-resolution transcriptome profiling (23 subjects across 22 timepoints, and with 117 COVID-19 patients used as comparators). There were marked differences in the timing and amplitude of the responses to the priming and booster doses. Notably, we identified two distinct interferon signatures. The first signature (A28/S1) was robustly induced both post-prime and post-boost and in both cases correlated with the subsequent development of antibody responses. In contrast, the second interferon signature (A28/S2) was robustly induced only post-boost, where it coincided with a transient inflammation peak. In COVID19 patients, a distinct phenotype dominated by A28/S2 was associated with longer duration of intensive care. In summary, high-temporal-resolution transcriptomic permitted the identification of post- vaccination phenotypes that are determinants of the course of COVID-19 disease.
Chromosomal rearrangements with stable repertoires of genes and transposable elements in an invasive forest-pathogenic fungus AO_SCPLOWBSTRACTC_SCPLOWChromosomal rearrangements have been largely described among eukaryotes, and may have important consequences on evolution of species. High genome plasticity has been often reported in Fungi, which may explain their apparent ability to quickly adapt to new environments. Cryphonectria parasitica, causing the Chestnut blight disease, is an invasive fungal pathogen species associated with several recent host shifts during its successive introductions from Asia to North America and Europe. Previous cytological karyotyping and genomic studies suggested several chromosomal rearrangements which remains to be described in detail for this species. A serious limitation for valid genome comparisons is the access to robust genome assemblies that usually contain genomic regions of low complexity. We present a new de novo whole-genome assembly obtained from a new method of DNA extraction and long-reads sequencing Nanopore technology obtained from a Japanese isolate sampled in the native area of the species. The comparison with a recently published reference genome revealed stable gene and transposable elements (TEs) repertoires. We also showed that the C. parasitica genome is lowly compartmentalized, with a poor association between TEs and genes, such as those potentially involved in host interactions (i.e., genes coding for small secreted proteins or for secondary metabolites). This genome comparison, however, detected several large chromosomal rearrangements that may have important consequences in gene regulations and sexual mating in this invasive species. This study opens the way for more comparisons of high-quality assembled genomes, and questions the role of structural variations in the invasive success of this fungal pathogen species. 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. Misoprostol Treatment Prevents Hypoxia-Induced Cardiac Dysfunction Through a 14-3-3 and PKA regulatory motif on Bnip3 Systemic hypoxia is a common element in most perinatal emergencies and is a known driver of Bnip3 expression in the neonatal heart. Bnip3 plays a prominent role in the evolution of necrotic cell death, disrupting ER calcium homeostasis and initiating mitochondrial permeability transition (MPT). Emerging evidence suggests a cardioprotective role for the prostaglandin E1 analogue misoprostol during periods of hypoxia, but the mechanisms for this protection are not completely understood. Using a combination of mouse and cell models, we tested if misoprostol is cardioprotective during neonatal hypoxic injury by altering Bnip3 function. Here we report that hypoxia elicits mitochondrial-fragmentation, MPT, reduced ejection fraction, and evidence of necroinflammation, which were abrogated with misoprostol treatment or Bnip3 knockout. Through molecular studies we show that misoprostol leads to PKA-dependent Bnip3 phosphorylation at threonine-181, and subsequent redistribution of Bnip3 from mitochondrial Opa1 and the ER through an interaction with 14-3-3 proteins. Taken together, our results demonstrate a role for Bnip3 phosphorylation in the regulation of cardiomyocyte contractile/metabolic dysfunction, and necroinflammation. Furthermore, we identify a potential pharmacological mechanism to prevent neonatal hypoxic injury. A revised view on the evolution of glutamine synthetase isoenzymes in plants Glutamine synthetase (GS) is a key enzyme responsible for the incorporation of inorganic nitrogen in the form of ammonium into the amino acid glutamine. The genes encoding GS are among the oldest existing genes in living organisms. In plants, two groups of functional GS enzymes are found: eubacterial GSIIb (GLN2) and eukaryotic GSIIe (GLN1/GS). Phylogenetic analyses have shown that the GLN2 group originated from bacteria following horizontal gene transfer. Only GLN1/GS genes are found in vascular plants, which suggests that they are involved in the final adaptation of plants to terrestrial life. The present phylogenetic study reclassifies the different GS of seed plants into three clusters: GS1a, GS1b and GS2. The presence of genes encoding GS2 has been expanded to Cycadopsida gymnosperms, which suggests the origin of this gene in a common ancestor of Cycadopsida, Ginkgoopsida and angiosperms. GS1a genes have been identified in all gymnosperms, basal angiosperms and some Magnoliidae species. Previous studies in conifers and the gene expression profiles obtained in ginkgo and magnolia in the present work could explain the absence of GS1a in more recent angiosperm species (e.g., monocots and eudicots) due to the redundant roles of GS1a and GS2 in photosynthetic cells. Altogether, the results provide a better understanding of the evolution of plant GS isoenzymes and their physiological roles, which is valuable for improving crop nitrogen use efficiency and productivity. Loss of the DYRK1A protein kinase results in reduction of ribosomal protein genes expression, ribosome mass and translation defects Ribosomal proteins (RPs) are evolutionary conserved proteins that are essential for protein translation. RP expression must be tightly regulated to ensure the appropriate assembly of ribosomes and to respond to the growth demands of cells. The elements regulating the transcription of RP genes (RPGs) have been characterized in yeast and Drosophila, yet how cells regulate the production of RPs in mammals is less well understood. Here, we show that a subset of RPG promoters is characterized by the presence of the palindromic TCTCGCGAGA motif and marked by the recruitment of the protein kinase DYRK1A. The presence of DYRK1A at these promoters is associated with enhanced binding of the TATA-binding protein, TBP, and it is negatively correlated with the binding of the GABP transcription factor, establishing at least two clusters of RPGs that could be coordinately regulated. However, DYRK1A silencing leads to a global reduction of RPGs, mRNA pointing at DYRK1A activities beyond those dependent on its chromatin association. Significantly, cells in which DYRK1A is depleted have reduced RP levels, fewer ribosomes, reduced global protein synthesis and smaller size. We therefore propose a novel role for DYRK1A in coordinating the expression of genes encoding RPs, thereby controlling cell growth in mammals. The Temporal Statistics of Musical Rhythm across Western Genres: An Amplitude Modulation Phase Hierarchy Model Statistical learning by the human brain plays a core role in the development of cognitive systems like language and music. Both music and speech have structured inherent rhythms, however the acoustic sources of these rhythms are debated. Theoretically, rhythm structures in both systems may be related to a novel set of acoustic statistics embedded in the amplitude envelope, statistics originally revealed by modelling childrens nursery rhymes. Here we apply similar modelling to explore whether the amplitude modulation (AM) timescales underlying rhythm in music match those in child-directed speech (CDS). Utilising AM-driven phase hierarchy modelling previously applied to infant-directed speech (IDS), adult-directed speech (ADS) and CDS, we test whether the physical stimulus characteristics that yield speech rhythm in IDS and CDS describe rhythm in music. Two models were applied. One utilized a low-dimensional representation of the auditory signal adjusted for known mechanisms of the human cochlear, and the second utilized probabilistic amplitude demodulation, estimating the modulator (envelope) and carriers using Bayesian inference. Both models revealed a similar hierarchically-nested temporal modulation structure across Western musical genres and instruments. Core bands of AM and spectral patterning matched prior analyses of IDS and CDS, and music showed strong phase dependence between slower bands of AMs, again matching IDS and CDS. This phase dependence is critical to the perception of rhythm. Control analyses modelling other natural sounds (wind, rain, storms, rivers) did not show similar temporal modulation structures and phase dependencies. We conclude that acoustic rhythm in language and music has a shared statistical basis. Predicting microbiome compositions from species assemblages through deep learning. Microbes can form complex communities that perform critical functions in maintaining the integrity of their environment or their hosts well-being. Rationally managing these microbial communities requires improving our ability to predict how different species assemblages affect the final species composition of the community. However, making such a prediction remains challenging because of our limited knowledge of the diverse physical, biochemical, and ecological processes governing microbial dynamics. To overcome this challenge, here we present a deep learning framework that automatically learns the map between species assemblages and community compositions from training data only, without knowledge of any of the above processes. First, we systematically validate our framework using synthetic data generated by classical population dynamics models. Then, we apply it to experimental data of both in vitro and in vivo communities, including ocean and soil microbial communities, Drosophila melanogaster gut microbiota, and human gut and oral microbiota. In particular, we show how our framework learns to perform accurate out-of-sample predictions of complex community compositions from a small number of training samples. Our results demonstrate how deep learning can enable us to understand better and potentially manage complex microbial communities. Elucidation of SARS-CoV-2 budding mechanisms through molecular dynamics simulations of M and E protein complexes SARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratorys refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. 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. The coiled coil of FtsLB is a structurally detuned element critical for modulating activation in bacterial cell division The FtsLB complex is a key regulator of bacterial cell division, existing in either an off or on state which supports the activation of septal peptidoglycan synthesis. In Escherichia coli, residues known to be critical for this activation are located in a region near the C-terminal end of the periplasmic coiled-coil domain of FtsLB, raising questions about the precise role of this conserved domain in the activation mechanism. Here, we investigate an unusual cluster of polar amino acids found within the core of the FtsLB coiled coil. We hypothesized that these amino acids likely reduce the structural stability of the domain and thus may be important for governing conformational changes. We found that mutating these positions to hydrophobic residues increased the thermal stability of FtsLB but caused cell division defects, suggesting that the coiled-coil domain is a "detuned" structural element. In addition, we identified suppressor mutations within the polar cluster, indicating that the precise identity of the polar amino acids is important for fine-tuning the structural balance between the off and on states. We propose a revised structural model of the tetrameric FtsLB (named the "Y-model") in which the periplasmic domain splits into a pair of coiled-coil branches. In this configuration, the hydrophilic terminal moieties of the polar amino acids remain more favorably exposed to water than in the original four-helix bundle model ("I-model"). We propose that a shift in this architecture, dependent on its marginal stability, is involved in activating the FtsLB complex and triggering septal cell wall reconstruction. Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. Comprehensive-immunopeptidomics analysis reveals presentation of potential neoantigens carrying cancer driver mutations Understanding the properties of human leukocyte antigen (HLA) peptides (HLAp) is essential for cancer precision medicine, while the direct identification of HLAp from a tiny piece of clinical tissues by mass spectrometry (MS) is still confronted with technical challenges. Here, to overcome that hindrances, high-field asymmetric waveform ion mobility spectrometry (FAIMS) is introduced to conduct differential ion mobility (DIM)-MS by seamless gas-phase fractionation optimal for scarce samples. The global-immunopeptidomics analysis enables in-depth identification of 44,785 HLAp, including 2 neoantigens with KRAS-G12V and CPPED1-R228Q from stage IV colorectal cancer (CRC) tissues obtained from 17 subjects. Comparison of tissue-based personal immunopeptidome disclosed cancer-specific processing of HLAp. Since the direct identification of neoantigens from CRC tissues suggests more potential neoantigens have yet to been identified, the targeted-immunopeptidomics by screening-oriented parallel reaction monitoring (PRM) has been established and identified two more neoantigens with oncogenic KRAS. The targeted-immunopeptidomics analysis clarifies the presentation of aimed neoantigens, including neoantigens that are unpredictable by computational algorithms. The comprehensive-immunopeptidomics approach combining the FAIMS-assisted DIM-MS and the screening-oriented PRM contributes the direct and effective identification of HLAp and emerging neoantigens from clinical tissue samples, as an advanced strategy to identify the authentic and recurrent neoantigens for cancer immunotherapy. Alien chromatin other than the GST-encoding Fhb7 candidate confers Fusarium head blight resistance in wheat breeding The lack of resistance resources is a major bottleneck for wheat Fusarium head blight (FHB) resistance breeding. Three wheat-Th. elongatum FHB resistant translocation lines have been developed and used for wheat breeding without yield penalty. Transcriptomic analysis identified a derivative glutathione S-transferase transcript T26102, which was homologous to Fhb7 and induced dramatically by Fusarium graminearum. Unlike other studies, Fhb7 homologs were detected not only in Thinopyrum but also in Elymus, Leymus, Pseudoroegeria and Roegeria. We also found that several wheat-Th. ponticum derivatives carrying Fhb7 and its homologs were highly susceptible to FHB. Moreover, the transgenic plants expressing Fhb7 and its homolog on different backgrounds did not improve the FHB resistance.

One Sentence SummaryThe GST-encoding Fhb7 candidate cannot improve Fusarium head blight resistance in wheat breeding. Task-independent metrics of computational hardness predict human cognitive performance The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of cognitive tasks using a set of task-independent metrics related to the computational resource requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that they predict both time spent on a task as well as accuracy in three canonical cognitive tasks. Our findings demonstrate that performance in cognitive tasks can be predicted based on generic metrics of their inherent computational hardness.

TeaserThe ability of humans to solve cognitive tasks is affected by generic mathematical properties of problems related to their computational complexity. Design of a radial multi-offset detection pattern for in vivo phase contrast imaging of the retinal ganglion cells in humans Previous work has shown that multi-offset detection in adaptive optics scanning laser ophthalmoscopy (AOSLO) can be used to image retinal ganglion cells (RGCs) in monkeys and humans. However, though images of RGCs in anesthetized monkeys with high light levels produced high contrast images of RGCs, images from humans failed to reach the same contrast due to several drawbacks in the previous dual-wavelength multi-offset approach. Our aim here was to design and build a multi-offset detection pattern for humans at safe light levels that could reveal the retinal ganglion cell layer neurons with a contrast, robustness and acquisition time approaching results only previously obtained in monkeys. Here, we present a new imaging system using only one light source, compared to the previous dual-wavelength used on monkeys. Our single-wavelength solution allows for increased light power and eliminates problematic chromatic aberrations. Then, we demonstrate that a radial multi-offset detection pattern with an offset distance of 8-10 Airy Disk Diameter (ADD) is optimal to detect photons multiply scattered in all directions from RGCs thereby enhancing their contrast. This new setup and image processing pipeline led to improved imaging of retinal ganglion cells using multi-offset imaging in AOSLO. 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. A tool for assessing alignment of biomedical data repositories with open, FAIR, citation and trustworthy principles Increasing attention is being paid to the operation of biomedical data repositories in light of efforts to improve how scientific data is handled and made available for the long term. Multiple groups have produced recommendations for functions that biomedical repositories should support, with many using requirements of the FAIR data principles as guidelines. However, FAIR is but one set of principles that has arisen out of the open science community. They are joined by principles governing open science, data citation and trustworthiness, all of which are important aspects for biomedical data repositories to support. Together, these define a framework for data repositories that we call OFCT: Open, FAIR, Citable and Trustworthy. Here we developed an instrument using the open source PolicyModels toolkit that attempts to operationalize key aspects of OFCT principles and piloted the instrument by evaluating eight biomedical community repositories listed by the NIDDK Information Network (dkNET.org). Repositories included both specialist repositories that focused on a particular data type or domain, in this case diabetes and metabolomics, and generalist repositories that accept all data types and domains. The goal of this work was both to obtain a sense of how much the design of current biomedical data repositories align with these principles and to augment the dkNET listing with additional information that may be important to investigators trying to choose a repository, e.g., does the repository fully support data citation? The evaluation was performed from March to November 2020 through inspection of documentation and interaction with the sites by the authors. Overall, although there was little explicit acknowledgement of any of the OFCT principles in our sample, the majority of repositories provided at least some support for their tenets. AFFORDABLE, REPLICABLE ROBOTIC MINIRHIZOTRON SAMPLING FOR ROOT DYNAMICS STUDIES O_LIMinirhizotrons (paired camera systems and buried observatories) are the best current method to make repeatable measurements of fine root dynamics in the field. Automating data collection is the only way to assess fine-scale temporal changes in fine roots in natural systems. When paired with above-ground proximal remote sensing, automatic minirhizotron data could reveal coordination between above and below ground phenology, supporting both plant allocation and carbon exchange understanding. However, there are many challenges to automating minirhizotrons for field experiments. First, instruments must be cheap enough to replicate given shallow field of view and variable natural environments. Second, automated analysis must be robust to changeable soil and root conditions because image properties extracted must have biological meaning.
C_LIO_LIHere, we demonstrate an automatic minirhizotron scheme, built with off-the-shelf parts and capable to sample at sub-daily resolution paired with a neural network-based image analysis method. As a proof of concept, we tested the instruments and the methodology in a mesocosm study and in two short real-world field trials alongside datasets from other instruments (e.g. proximal remote sensed leaf dynamics).
C_LIO_LIWe show that the method produces robust daily time-series of root dynamics in the mesocosm and the field. We applied the same model across multiple instruments, demonstrating good reproducibility of measurements. Temporal variations of root cover were a strong driver of soil CO2 efflux in mesocosm, and vegetation dynamics from above ground proximal remote sensing and minirhizotron data differed both in mesocosm and field. We found sensitivity of root cover extracted to soil moisture and sometimes time of day (potentially relating to soil moisture), which may only affect high frequency imagery and not commonly reported as encountered when training neural networks on traditional, time-distinct minirhizotron studies.
C_LIO_LIWe discuss avenues for dealing with such issues in future field applications of minirhizotrons. If such issues are dealt with to a satisfactory manner in the field, timeseries of root biomass and traits from replicated instruments can add a new dimension to phenology studies at the ecosystem level by understanding the dynamics of root properties and traits.
C_LI Patterns of connectome variability in autism across five functional activation tasks. Findings from the LEAP project BackgroundAutism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioural, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterise heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

MethodsAll analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism and typically developing controls (TD) between 6 and 30 years of age. We employed a novel task-potency approach which combines the unique aspects of both resting-state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioural data.

ResultsDeviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p<0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p<0.002). The CCA identified significant and robust brainbehavior covariation between functional connectivity atypicality and autism-related behavioral features.

ConclusionsIndividuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show, moving forward, sophisticated modeling methods such as task-potency and normative modeling will prove key to unravelling complex heterogeneous conditions like autism. Leaf Aqueous Extract of Manilkara hexandra influenced Glucose Metabolism in fish: An observation with Labeo rohita Fingerlings as model organism Manilkara hexandra (Roxb.) Dubard (common name Khirni, family: Sapotaceae) is an evergreen traditionally used medicinal plant. The present study aimed to see the effects of leaf aqueous extract of M. hexandra (LAEMH) on digestive and glucose metabolic enzyme action and serum glucose level in rohu, Labeo rohita, fingerlings. Experimental fish were fed a basal diet (Group I), and diets supplemented with LAEMH at 300 mg (Group II) and 600 mg (Group III) kg-1body weight. A significant reduction in serum glucose was noticed in the treated groups when compared with the control group. The reduced amylase activity was noticed in the treated fingerlings in a dose-dependent manner. However, lipase and protease activities didnt differ significantly among the experimental groups. Reduced serum glucose level might be correlated with the decline in the activity of digestive amylase in fish. Group II (3.35{+/-}0.19 U) and Group III (3.49{+/-}0.13 U) were recorded with reduced glucose-6-phosphatase activities than the control group (4.4{+/-}0.39 U). Moreover, the study revealed a decline in fructose-1,6-phosphatase activities in the treated groups in comparison to the control group. The decline in the activities of the metabolic enzymes might be associated with the non-availability of glucose owing to reduced activity of the digestive amylase in the treated groups. In conclusion, the present study established the hypoglycaemic effect of the leaf aqueous extract of M. hexandra in a fish model. Cluster-specific gene markers enhance Shigella and Enteroinvasive Escherichia coli in silico serotyping Shigella and enteroinvasive Escherichia coli (EIEC) cause human bacillary dysentery with similar invasion mechanisms and share similar physiological, biochemical and genetic characteristics. The ability to differentiate Shigella and EIEC from each other is important for clinical diagnostic and epidemiologic investigations. The existing genetic signatures may not discriminate between Shigella and EIEC. However, phylogenetically, Shigella and EIEC strains are composed of multiple clusters and are different forms of E. coli. In this study, we identified 10 Shigella clusters, 7 EIEC clusters and 53 sporadic types of EIEC by examining over 17,000 publicly available Shigella/EIEC genomes. We compared Shigella and EIEC accessory genomes to identify the cluster-specific gene markers or marker sets for the 17 clusters and 53 sporadic types. The gene markers showed 99.63% accuracy and more than 97.02% specificity. In addition, we developed a freely available in silico serotyping pipeline named Shigella EIEC Cluster Enhanced Serotype Finder (ShigEiFinder) by incorporating the cluster-specific gene markers and established Shigella/EIEC serotype specific O antigen genes and modification genes into typing. ShigEiFinder can process either paired end Illumina sequencing reads or assembled genomes and almost perfectly differentiated Shigella from EIEC with 99.70% and 99.81% cluster assignment accuracy for the assembled genomes and mapped reads respectively. ShigEiFinder was able to serotype over 59 Shigella serotypes and 22 EIEC serotypes and provided a high specificity with 99.40% for assembled genomes and 99.38% for mapped reads for serotyping. The cluster markers and our new serotyping tool, ShigEiFinder (https://github.com/LanLab/ShigEiFinder), will be useful for epidemiologic and diagnostic investigations.

Impact statementThe differentiation of Shigella strains from enteroinvasive E. coli (EIEC) is important for clinical diagnosis and public health epidemiologic investigations. The similarities between Shigella and EIEC strains make this differentiation very difficult as both share common ancestries within E. coli. However, Shigella and EIEC are phylogenetically separated into multiple clusters, making high resolution separation using cluster specific genomic markers possible. In this study, we identified 17 Shigella or EIEC clusters including five that were newly identified through examination of over 17,000 publicly available Shigella and EIEC genomes. We further identified an individual or a set of cluster-specific gene markers for each cluster using comparative genomic analysis. These markers can then be used to classify isolates into clusters and were used to develop an in silico pipeline, ShigEiFinder (https://github.com/LanLab/ShigEiFinder) for accurate differentiation, cluster typing and serotyping of Shigella and EIEC from Illumina sequencing reads or assembled genomes. This study will have broad application from understanding the evolution of Shigella/EIEC to diagnosis and epidemiology.

Data summarySequencing data have been deposited at the National Center for Biotechnology Information under BioProject number PRJNA692536.

RepositoriesRaw sequence data are available from NCBI under the BioProject number PRJNA692536. 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. Late-life fitness gains explain the absence of a selection shadow in ants A key hypothesis for the occurrence of senescence is a decrease in the selection strength because of low late-life fitness - the so-called selection shadow. However, in social insects, aging is considered a plastic trait and senescence seems to be absent. By life-long tracking of 102 ant colonies, we find that queens increase the production of sexuals in late life regardless of their absolute lifespan or worker investment. This indicates a genetically accommodated adaptive shift towards increasingly queen-biased caste ratios over the course of a queens life. Furthermore, mortality decreased with age, supporting the hypothesis that aging is adaptive. We argue that selection for late life reproduction diminishes the selection shadow of old age and leads to the apparent absence of senescence in ants, in contrast to most iteroparous species.

Significance StatementSocial insects are extraordinary with regard to the absolute age of queens of some species as well as the age differences between queens and short-lived workers. Yet, ultimate causes explaining these aging patterns remain poorly understood. By manipulating the investment ratio into queens and workers we studied the effect on lifespan and temporal reproductive investment of queens. We show that queens shift to the production of sexuals late in life, independent of social context (colony size) or individual quality (reproductive output and lifespan). Such late fitness gains result in maintenance in the selection strength with age, and thus explains the absence of senescence in queens.