Ending animal agriculture would stabilize greenhouse gas levels for 30 years and offset 70 percent of CO2 emissions this century Animal agriculture contributes significantly to global warming through ongoing emissions of the potent greenhouse gases methane and nitrous oxide, and displacement of biomass carbon on the land used to support livestock. However, because estimates of the magnitude of the effect of ending animal agriculture often focus on only one factor, the full potential benefit of a more radical change remains underappreciated. Here we quantify the full "climate opportunity cost" of current global livestock production, by modeling the combined, long-term effects of emission reductions and biomass recovery that would be unlocked by a phaseout of animal agriculture. We show that, even in the absence of any other emission reductions, persistent drops in atmospheric methane and nitrous oxide levels, and slower carbon dioxide accumulation, following a phaseout of livestock production would, through the end of the century, have the same cumulative effect on the warming potential of the atmosphere as a 25 gigaton per year reduction in anthropogenic CO2 emissions, providing half of the net emission reductions necessary to limit warming to 2{degrees}C. The magnitude and rapidity of these potential effects should place the reduction or elimination of animal agriculture at the forefront of strategies for averting disastrous climate change.

Significance StatementThe use of animals to produce food has a negative impact on the climate, but the benefits of a global switch to a plant based diet are underappreciated. We show that the global warming impact, through the rest of this century, of eliminating greenhouse gas emissions from livestock and allowing native ecosystems to regrow on the land currently used to house and feed livestock, would be equivalent to a 68% reduction in carbon dioxide emissions. We hope putting clearer numbers on the "climate opportunity cost" of our continued use of animals as food technology will help policymakers and the public properly prioritize dietary change as a climate defense strategy.

Declaration of Conflict of InterestPatrick Brown is the founder and CEO of Impossible Foods, a company developing alternatives to animals in food-production. Michael Eisen is an advisor to Impossible Foods. Both are shareholders in the company and thus stand to benefit financially from reduction of animal agriculture.
Linking plankton size spectra and community composition to carbon export and its efficiency The magnitude and efficiency of particulate carbon export from the ocean surface depends not only on net primary production (NPP) but also on how carbon is consumed, respired, and repackaged by organisms. We contend that several of these processes can be captured by the size spectrum of the plankton community. However, most global models have relatively simple food-web structures that are unable to generate plankton sizespectra. Moreover, the life-cycles of multicellular zooplankton are typically not resolved, restricting the ability of models to represent time-lags that are known to impact carbon export and its efficiency (pe-ratio). Here, we use a global mechanistic size-spectrum model of the marine plankton community to investigate how particulate export and pe-ratio relate to the community size spectrum, community composition, and time-lags between predators and prey. The model generates emergent food-webs with associated size distributions for organisms and detrital particles. To resolve time-lags between phytoplankton and zooplankton, we implement the life-cycle of multicellular zooplankton (here represented by copepods). The simulation successfully captures observed patterns in biomass and energy fluxes across regions. We find that carbon export correlates best with copepod biomass and trophic level, whereas the pe-ratio correlates best with the exponent of the size spectrum and sea surface temperature (SST). Community metrics performed better than NPP or SST for both deep export and pe-ratio. Time-lags between phytoplankton and copepods did not strongly affect export or pe-ratio. We conclude by discussing how can we reconcile size-spectrum theory with field sampling.

Plain Language SummaryPlankton are tiny but extremely abundant aquatic organisms. Plankton lock CO2 away from the atmosphere as they sink to the deep ocean, where carbon can be stored for hundreds of years. However, how much carbon is locked away and for how long depends on how organisms eat, defecate, and respire. We argue that these processes are reflected in the size composition of the plankton community. The size composition shows a clear relationship between the number of organisms and their body-size. The steepness of this "size-abundance relationship" describes the balance between small vs. large organisms, and has been argued to reflect how energy is transferred from small to large organisms. Since large organisms create fast-sinking particles, the size-abundance relationship could be used to estimate how much carbon is being stored in the deep ocean. Here we use a computer simulation of the global plankton community to investigate how the removal of carbon relates to the plankton community and the steepness of the sizeabundance relationship. The model successfully captures patterns observed in nature. We found that the size-abundance relationship, together with the quantity of large zooplankton better explained carbon export than other measures typically used, such as photosynthesis and temperature.

Key PointsO_LIWe use a global mechanistic size-spectrum model to investigate the relation between particulate export and plankton community metrics.
C_LIO_LIWe find a good correlation between export efficiency and the exponent of the size spectrum.
C_LIO_LITotal carbon export correlated well with copepod biomass and trophic level of active copepods in the model.
C_LI
GUIdEStaR (G-quadruplex, uORF, IRES, Epigenetics, Small RNA, Repeats), the integrated metadatabase in conjunction with neural network methods GUIdEStaR integrates existing databases of various types of G-quadruplex, upstream Open Reading Frame (uORF), Internal Ribosome Entry Site (IRES), methylation to RNA and histone protein, small RNA, and repeats. GUIdEStaR consists of approx. 40,000 genes and 320,000 transcripts. An mRNA transcript is divided into 5 regions (5UTR, 3UTR, exon, intron, and biological region) where each region contains presence-absence data of 169 different types of elements. Recently, artificial intelligence (AI) based analysis of sequencing data has been gaining popularity in the area of bioinformatics. GUIdEStaR generates datasets that can be used as inputs to AI methods. At the GUIdEStaR homepage, users submit gene symbols by clicking a "Send" button, and shortly result files in CSV format are available for download at the result website. Users have an option to send the result files to their email addresses. Additionally, the entire database and the example Java codes are also freely available for download. Here, we demonstrate the database usage with three neural network classification studies-1) small RNA study for classifying transcription factor (TF) genes into either one of TF mediated by small RNA originated from SARS-CoV-2 or by human microRNA (miRNA), 2) cell membrane receptor study for classifying receptor genes as either with virus interaction or without one, and 3) nonsense mediated mRNA decay (NMD) study for classifying cell membrane and nuclear receptors as either NMD target or non-target. GUIdEStaR is available for access to the easy-to-use web-based database at www.guidestar.kr and for download at https://sourceforge.net/projects/guidestar. 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. Glucose inhibits haemostasis and accelerates diet-induced hyperlipidaemia in zebrafish larvae Hyperglycaemia damages the microvasculature in part through the reduced recruitment of immune cells and interference with platelet signalling, leading to poor wound healing and accelerated lipid deposition in mammals. We investigated the utility of zebrafish larvae to model the effect of glucose on neutrophil and macrophage recruitment to a tail wound, wound-induced haemostasis, and chicken egg yolk feed challenge-induced hyperlipidaemia by supplementing larvae with exogenous glucose by immersion or injection. Neither method of glucose supplementation affected the recruitment of neutrophils and macrophages following tail transection. Glucose injection reduced thrombocyte retention and fibrin plug formation while only thrombocyte retention was reduced by glucose immersion following tail transection. We observed accelerated lipid accumulation in glucose-injected larvae challenged with high fat chicken egg yolk feeding. Our study identifies conserved and divergent effects of high glucose on inflammation, haemostasis, and hyperlipidaemia in zebrafish larvae compared to mammals. 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. Stimulated oxygen transport in tissue by magnetic needle acupuncture AimTo understand physiology of magnetic needle acupuncture by investigating O2 transport in tissue during needle intervention.

MethodsO2 transport in tissue is modeled by utilizing COMSOL with magnetic needle inserted into muscle tissue in a 2D porous media. The damaged tissue has been mimicked by an extracted tissue block with 1st order O2 consumption rate. The convection-diffusion O2 transport in the damaged tissue has been further evaluated by varying magnetic flux density B0 of the needle (0-1 T), myoglobin concentration (0-1 mM), O2 tension (5-100 Torr), O2 consumption rates, tissue permeability (10-12-10-6 m2) and porosity (0.1-0.9).

Results1) Active O2 transport carried by interstitial flow is enhanced with the intervention of a magnetic needle by generating a high gradient magnetic field around the tip, which exerts a strong force (104 N/m3) on the diamagnetic interstitial fluid to accelerate the flow. 2) This interstitial flow can reach 30 m/s at B0 = 1T and strongly correlates to the needle B0 and tissue permeability. 3) The needle stirs the interstitial flow can pump O2 flux by 1-2 orders of magnitude compared to that without magnetic field. 4) The enhancement of active O2 transport by magnetic needle is site-specific to the tissue in the vicinity of the tip. This enhancement is more effective in edema condition with a high tissue permeability (>10-9 m2).

ConclusionsThe dramatic enhancement of O2 transport to restore the O2 mitochondria metabolism for dysfunctional muscle tissues is the fundamental physiological mechanism of magnetic needle acupuncture. The genome sequence of the avian vampire fly (Philornis downsi), an invasive nest parasite of Darwin's finches in Galapagos The invasive avian vampire fly (Philornis downsi) is considered one of the greatest threats to the unique and endemic avifauna of the Galapagos Islands, Ecuador. The fly parasitizes nearly every passerine species, including Darwins finches, in the Galapagos. The fly is thought to have been introduced from mainland Ecuador, although the full pathway of invasion is not yet known. The majority of research to date has focused on the effects of the fly on the fitness of avian hosts and explorations of mitigation methods. A lag in research related to the genetics of this invasion demonstrates, in part, a need to develop full-scale genomic resources with which to address further questions within this system. In this study, an adult P. downsi collected from San Cristobal Island within the Galapagos archipelago was sequenced to generate a high-quality genome assembly. We examined various features of the genome (e.g., coding regions, non-coding transposable elements) and carried out comparative genomics analysis against other dipteran genomes. We identified lists of gene families that are significantly expanding/contracting in P. downsi that are related to insecticide resistance, detoxification, and potential feeding ecology and counter defense against host immune responses. The P. downsi genome assembly provides an important foundational resource for studying the molecular basis of its successful invasion in the Galapagos and the dynamics of its population across multiple islands. The findings of significantly changing gene families associated with insecticide resistance and immune responses highlight the need for further investigations into the role of different gene families in aiding the flys successful invasion. Furthermore, this genomic resource will also better help inform future research studies and mitigation strategies aimed at minimizing the flys impact on the birds of the Galapagos. LCK Regulates Homologous Recombination DNA Repair Identifying a New Therapeutic Target for Sensitizing PARP Inhibitors in HR Proficient Ovarian Cancer Poly-ADP Ribose Polymerase (PARP) targeted therapy is clinically approved for the treatment of homologous recombination (HR) repair deficient tumors. The remarkable success in treatment of HR repair deficient cancers has not translated to HR-proficient cancer. Our studies identify the mechanism of non-receptor lymphocyte-specific protein tyrosine kinase (LCK) in HR repair in endometrioid epithelial ovarian cancer (eEOC). LCK expression is induced and activation in the nucleus in response to DNA damage insult. LCK inhibition attenuates expression of RAD51, BRCA1, and BRCA2 proteins necessary for HR-mediated DNA repair, sufficient to suppress RAD51 foci formation, and augments {gamma}H2AX foci formation. Mechanistically, DNA damage leads to direct interaction of LCK with RAD51 and BRCA1 in a kinase dependent manner. Attenuation of LCK sensitized HR-proficient eEOC cells to PARP inhibitor in cell culture and pre-clinical mouse studies. These findings identify a new mechanism for expanding utility of PARP inhibitors in HR proficient ovarian cancer.

Graphical Abstract

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org.highwire.dtl.DTLVardef@1715c60org.highwire.dtl.DTLVardef@167cb5forg.highwire.dtl.DTLVardef@158d807org.highwire.dtl.DTLVardef@1ced201_HPS_FORMAT_FIGEXP  M_FIG C_FIG All-optical recreation of naturalistic neural activity with a multifunctional transgenic reporter mouse Determining which features of the neural code drive perception and behavior requires the ability to simultaneous read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two photon (2p) calcium imaging and targeted 2p photostimulation enable the activation of specific, functionally defined groups of neurons in behaving animals. However, these techniques do not yet have the ability to reveal how the specific distribution of firing rates across a relevant neural population mediates neural computation and behavior. The key technical obstacle is the inability to transform single-cell calcium signals into accurate estimates of firing rate changes and then write in these cell-specific firing rate changes to each individual neuron in a targeted population. To overcome this challenge, we made two advances: first we introduce a new genetic line of mice for robust Cre-dependent co-expression of a high-performance calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we developed a pipeline that enables the read-out and write-in of precise population vectors of neural activity across a targeted group of neurons. The combination of the new multifunctional transgenic line and the photostimulation paradigm offer a powerful and convenient platform for investigating the neural codes of computation and behavior. It may prove particularly useful for probing causal features of the geometry of neural representations where the ability to directly control the topology of population activity is essential. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Proteasome complexes experience profound structural and functional rearrangements throughout mammalian spermatogenesis During spermatogenesis, spermatogonia undergo a series of mitotic and meiotic divisions on their path to spermatozoa. To achieve this, a succession of processes requiring high proteolytic activity are in part orchestrated by the proteasome. The spermatoproteasome (s20S) is specific to the developing gametes, in which the gamete-specific 4s subunit replaces the 4 isoform found in the constitutive proteasome (c20S). Although the s20S is conserved across species and was shown to be crucial for germ cell development, its mechanism, function and structure remain incompletely characterized. Here, we used advanced mass spectrometry (MS) methods to map the composition of proteasome complexes and their interactomes throughout spermatogenesis. We observed that the s20S becomes highly activated as germ cells enter meiosis, mainly through a particularly extensive 19S activation and, to a lesser extent, PA200 binding. Additionally, the proteasome population shifts from c20S (98%) to s20S (>82-92%) during differentiation, presumably due to the shift from 4 to 4s expression. We demonstrated that s20S, but not c20S, interacts with components of the meiotic synaptonemal complex, where it may localize via association with the PI31 adaptor protein. In vitro, s20S preferentially binds to 19S, and displays higher trypsin- and chymotrypsin-like activities, both with and without PA200 activation. Moreover, using MS methods to monitor protein dynamics, we identified significant differences in domain flexibility between 4 and 4s. We propose that these differences induced by 4s incorporation result in significant changes in the way the s20S interacts with its partners, and dictate its role in germ cell differentiation. Intragenomic rearrangements of SARS-CoV-2, other betacoronaviruses, and alphacoronaviruses Variation of the betacoronavirus SARS-CoV-2 has been the bane of COVID-19 control. Documented variation includes point mutations, deletions, insertions, and recombination among closely or distantly related coronaviruses. Here, we describe yet another aspect of genome variation by beta- and alphacoronaviruses. Specifically, we report numerous genomic insertions of 5-untranslated region sequences into coding regions of SARS-CoV-2, other betacoronaviruses, and alphacoronaviruses. To our knowledge this is the first systematic description of such insertions. In many cases, these insertions change viral protein sequences and further foster genomic flexibility and viral adaptability through insertion of transcription regulatory sequences in novel positions within the genome. Among human Embecorivus betacoronaviruses, for instance, from 65% to all of the surveyed sequences in publicly available databases contain 5-UTR-derived inserted sequences. In limited instances, there is mounting evidence that these insertions alter the fundamental biological properties of mutant viruses. Intragenomic rearrangements add to our appreciation of how variants of SARS-CoV-2 and other beta- and alphacoronaviruses may arise.

SignificanceUnderstanding mechanisms of variation in coronaviruses is vital to control of their associated diseases. Beyond point mutations, insertions, deletions and recombination, we here describe for the first time intragenomic rearrangements and their relevance to changes in transmissibility, immune escape and/or virulence documented during the SARS-CoV-2 pandemic. 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. Isoprenoid biosynthesis regulation in poplars by methylerythritol phosphate and mevalonic acid pathways The isoprenoids found in plants are extremely important to survive with various human applications, such as flavoring, fragrance, dye, pharmaceuticals, and biomass used for biofuels. Methylerythritol phosphate (MEP) and mevalonic acid (MVA) pathways are critical in plants, responsible for isoprenoid biosynthesis. 1-deoxy-D-xylulose5-phosphate synthase (DXS) and 1-deoxy-D-xylulose5-phosphate reductoisomerase (DXR) catalyze the rate-limiting steps in the MEP pathway, while 3-hydroxy-3-methylglutaryl-CoA reductase (HMGR) catalyzes the rate-limiting step in the MVA pathway. Here, we showed while PtHMGR overexpressors (OEs) exhibited different MEP- and MVA-related gene expressions compared with non-transgenic poplars (NT), the PtDXR-OEs revealed upregulated MEP-related and downregulated MVA-related gene expressions. PtDXR and PtHMGR overexpressions caused changes in MVA-derived trans-zeatin-riboside, isopentenyl adenosine, castasterone, and 6-deoxocastasterone well as MEP-derived carotenoids and gibberellins. In PtHMGR-OEs, the accumulated geranyl diphosphate synthase (GPS) and geranyl pyrophosphate synthase (GPPS) transcript levels in the MEP pathway led to an accumulation of MEP-derived isoprenoids. In contrast, upregulation of farnesyl diphosphate synthase (FPS) expression in the MVA pathway contributed to increased levels of MVA-derived isoprenoids. In addition, PtHMGR-OEs increased MEP-related GPS and GPPS transcript levels, expanded MEP-derived isoprenoid levels, changed FPS transcript levels, and affected MVA-derived isoprenoid yields. These results demonstrate the contribution of MVA and MEP pathways regulating isoprenoid biosynthesis in poplars. Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression level with cell volume While most genes expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiaes mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model. Repeated subfunctionalization of a modular antimicrobial peptide gene for neural function Antimicrobial peptides (AMPs) are host-encoded antibiotics that combat invading pathogens. These genes commonly encode multiple products as post-translationally cleaved polypeptides. Recent studies have highlighted roles for AMPs in neurological contexts suggesting functions for these defence molecules beyond infection. During our immune study characterizing the antimicrobial peptide gene Baramicin, we recovered multiple Baramicin paralogs in Drosophila melanogaster and other species, united by their N-terminal IM24 domain. Not all paralogs were immune-induced. Here, through careful dissection of the Baramicin familys evolutionary history, we find that these non-immune paralogs result from repeated events of duplication and subsequent truncation of the coding sequence from an immune-inducible ancestor. These truncations leave only the IM24 domain as the prominent gene product. Surprisingly, using mutation and targeted gene silencing we demonstrate that two such genes are adapted for function in neural contexts in D. melanogaster. We also show enrichment in the head for independent Baramicin genes in other species. The Baramicin evolutionary history reveals that the IM24 Baramicin domain is not strictly useful in an immune context. We thus provide a case study for how an AMP-encoding gene might play dual roles in both immune and non-immune processes via its multiple peptide products. We reflect on these findings to highlight a blind spot in the way researchers approach AMP research in in vivo contexts.

Significance statementAntimicrobial peptides are immune proteins recently implicated in neurological roles. To date little attention has been paid to the contributions of different gene products in this function. Here we show that an antimicrobial peptide gene encodes multiple products with either immune-specific or neurological roles. Intron-mediated induction of phenotypic heterogeneity Introns are universally present in the nuclear genomes of eukaryotes1. The budding yeast, an otherwise intron-poor species, preserves two sets of ribosomal protein (RP) genes differing primarily in their introns2-4. Despite recent findings on the role of RP introns under stress and starvation5-7, understanding the contribution of introns to ribosome regulation remains challenging. Here, combining isogrowth profiling8 with single-cell protein measurements9, we found that introns can mediate inducible phenotypic heterogeneity conferring a clear fitness advantage. Osmotic stress leads to bimodal expression of the small ribosomal subunit protein Rps22B, mediated by an intron in the 5 untranslated region of its transcript. The two resulting yeast subpopulations differ in their ability to cope with starvation. Low Rps22B protein levels resulted in prolonged survival under sustained starvation, while high Rps22B levels enabled cells to grow faster after transient starvation. Further, yeast growing at high sugar concentrations - similar to those in ripe grapes - exhibit bimodal Rps22B expression when approaching stationary phase. Differential intron-mediated regulation of RP genes thus provides a way to diversify the population when starvation looms in natural environments. Our findings reveal a new role for introns in inducing phenotypic heterogeneity in changing environments and suggest that duplicated RP genes in yeast contribute to resolving the evolutionary conflict between precise expression control and environmental responsiveness10. 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. First Report of Lactoria cornuta from Karnataka, West coast of India, Role of tropical cyclones in Range Extension India is known for its rich biodiversity and is fortunate to have several endemic species from different classes of vertebrates. India is home to 7.5% of the global fish diversity, with 91 endemic species of ray finned fishes, the actinopterygians. Some fish species have never been reported until recently, one such example is the long-horned Cowfish (Ostracidae), best known for inhabiting only certain areas of the Indo-Pacific oceans. However, this fish has been reported from Bay of Bengal, Costs of Goa and Lakshadweep. This is the first time this fish has been found on the Coasts of Karnataka, west coast of India. Given its morphology, the migration seems highly improbable since it can only endure lethargic swimming. In this article, we have explored the role of other external forces that could have contributed to its range extension in the east and west coast of India. In this paper we are exploring the role of Super Cyclones as a vital force in determining the expansion of its range. The fact of collection longhorn cowfish for the first time from the coast of Karwar coincides with the passage of Cyclone Ockhi on the west coast of India this suggests the possible role of super cyclone in its range extension. A year later, another specimen was recovered from a location very close to the first, which indicates the successful establishment of Lacturia cornuta in its new environment. Related morphometric and meristic studies of our specimens are consistent with previous studies reported in the Bay of Bengal. A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

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

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. Antibody-induced glomerulonephritis is amplified by RTEC-intrinsic IL-17 signaling and restrained by IL-17-mediated induction of the endoribonuclease Regnase-1 (Zc3h12a) Antibody-mediated glomerulonephritis (AGN) is a clinical manifestation of many autoimmune kidney diseases for which few effective treatments exist. Chronic inflammatory circuits in renal glomerular and tubular cells lead to tissue damage in AGN. These cells are targeted by the cytokine IL-17, which has recently been shown to be a central driver of the pathogenesis of AGN. However, surprisingly little is known about the regulation of pathogenic IL-17 signaling in the kidney. Here, using a well characterized mouse model of AGN, we show that IL-17 signaling in renal tubular epithelial cells (RTECs) is necessary for AGN development. We also show that Regnase-1, an RNA binding protein with endoribonuclease activity, is a negative regulator of IL-17 signaling in RTECs. Accordingly, mice with a selective Regnase-1 deficiency in RTECs exhibited exacerbated kidney dysfunction in AGN. Mechanistically, Regnase-1 inhibits IL-17-driven expression of the transcription factor I{kappa}B{xi} and consequently its downstream gene targets including Il6 and Lcn2. Moreover, deletion of Regnase-1 in human RTECs reduced inflammatory gene expression in an I{kappa}B{xi}-dependent manner. Overall, these data identify an IL-17-driven inflammatory circuit in RTECs during AGN that is constrained by Regnase-1. Deep Heterogeneous Dilation of LSTM for Transient-phase Gesture Prediction through High-density Electromyography: Towards Application in Neurorobotics Deep networks have been recently proposed to estimate motor intention using conventional bipolar surface electromyography (sEMG) signals for myoelectric control of neurorobots. In this regard, Deepnets are generally challenged by long training times (affecting practicality and calibration), complex model architectures (affecting the predictability of the outcomes), and a large number of trainable parameters (increasing the need for big data). Capitalizing on our recent work on homogeneous temporal dilation in a Recurrent Neural Network (RNN) model, this paper proposes, for the first time, heterogeneous temporal dilation in an LSTM model and applies that to high-density surface electromyography (HD-sEMG), allowing for the decoding of dynamic temporal dependencies with tunable temporal foci. In this paper, a 128-channel HD-sEMG signal space is considered due to the potential for enhancing the spatiotemporal resolution of human-robot interfaces. Accordingly, this paper addresses a challenging motor intention decoding problem of neurorobots, namely, transient intention identification. Our approach uses only the dynamic and transient phase of gesture movements when the signals are not stabilized or plateaued, which can significantly enhance the temporal resolution of human-robot interfaces. This would eventually enhance seamless real-time implementations. Additionally, this paper introduces the concept of "dilation foci" to modulate the modeling of temporal variation in transient phases. In this work a high number (e.g., 65) of gestures is included, which adds to the complexity and significance of the understudied problem. Our results show state-of-the-art performance for gesture prediction in terms of accuracy, training time, and model convergence. Self-assembly of pericentriolar material in interphase cells lacking centrioles AbstractThe major microtubule-organizing center (MTOC) in animal cells, the centrosome, comprises a pair of centrioles surrounded by pericentriolar material (PCM), which nucleates and anchors microtubules. Centrosome assembly depends on PCM binding to centrioles, PCM self-association and dynein{-}mediated PCM transport, but the self-assembly properties of PCM in interphase cells are poorly understood. Here, we used experiments and modeling to study centriole-independent features of interphase PCM assembly. We showed that when centrioles are lost due to PLK4 depletion or inhibition, dynein-based PCM transport and PCM self-clustering are sufficient to form a single compact MTOC, which generates a dense radial microtubule array. Interphase PCM self-assembly depends on {gamma}-tubulin, pericentrin, CDK5RAP2 and ninein, but not NEDD1, CEP152 or CEP192. Formation of a compact acentriolar MTOC is inhibited by AKAP450-dependent PCM recruitment to the Golgi or by randomly organized CAMSAP2-stabilized microtubules, which keep PCM mobile and prevent its coalescence. Linking of CAMSAP2 to a minus-end-directed motor leads to the formation of an MTOC, but MTOC compaction requires cooperation with pericentrin-containing self-clustering PCM. Our data reveal that interphase PCM contains a set of components that can self-assemble into a compact structure and organize microtubules, but PCM self-organization is sensitive to motor-and microtubule-based rearrangement. Loss of Resf1 reduces the efficiency of embryonic stem cell self-renewal and germline entry Retroelement silencing factor 1 (RESF1) interacts with the key regulators of mouse embryonic stem cells (ESCs) OCT4 and NANOG, and its absence results in sterility of mice. However, the function of RESF1 in ESCs and germ line specification is poorly understood. In this study, we used Resf1 knockout cell lines to determine the requirements of RESF1 for ESCs self-renewal and for in vitro specification of ESCs into primordial germ cell-like cells (PGCLCs). We found that deletion of Resf1 in ESCs cultured in serum and LIF reduces self-renewal potential whereas episomal expression of RESF1 has a modest positive effect on ESC self-renewal. In addition, RESF1 is not required for the capacity of NANOG and its downstream target ESRRB to drive self-renewal in the absence of LIF. However, Resf1 deletion reduces efficiency of PGCLC differentiation in vitro. These results identify Resf1 as a novel player in the regulation of pluripotent stem cells and germ cell specification. 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.