Selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes.
Pathways of savannization in a mesic African savanna-forest mosaic following an extreme fire O_LIFires in savannas limit tree cover, thereby promoting flammable grass accumulation and fuelling further frequent fires. Meanwhile, forests and thickets form dense canopies that reduce C4-grass fuel loads and creating a humid microclimate, thereby excluding fires under typical climatic conditions.
C_LIO_LIHowever, extreme fires occasionally burn into these closed-canopy systems. Although these rare fires cause substantial tree mortality and can make repeat fires more likely, the long-term consequences of an extreme fire for closed canopy vegetation structure and potential to convert to savanna (hereafter "savannization") remain largely unknown.
C_LIO_LIHere, we analysed whether an extreme fire could, alone, alter species composition, vegetation structure, and fire regimes of closed-canopy ecosystems in an intact savanna-forest-thicket mosaic, or whether successive fires after an initial extreme fire were necessary to trigger a biome transition between from forest to savanna.
C_LIO_LIWe found that forests that only burned once recovered, whereas those that burned again following an initial extreme fire transitioned from closed-canopy forests towards open, grassy savannas.
C_LIO_LIWhile thickets had less tree mortality in fires than forests, repeat fires nonetheless precipitated a transition towards savannas.
C_LIO_LIColonization of the savanna tree community lagged behind the grass community, but also began to transition.
C_LI

SynthesisOur results suggest that rare extreme fires, followed by repeated burning can indeed result in savannization in places where savanna and forest represent alternative stable states.
A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. The maize gene maternal derepression of r1 (mdr1) encodes a DNA glycosylase with maternal and paternal fertility functions Demethylation of transposons can activate expression of nearby genes and cause imprinted gene expression in endosperm, and it is hypothesized to lead to expression of transposon siRNAs that reinforce silencing in the next generation through transfer either into egg or embryo. Here we describe maternal derepression of r1 (mdr1), which encodes a DNA glycosylase with homology to Arabidopsis DEMETER and which is partially responsible for demethylation of thousands of regions in endosperm. Instead of promoting siRNA expression in endosperm, MDR1 activity inhibits it. Methylation of most repetitive DNA elements in endosperm is not significantly affected by MDR1, with an exception of Helitrons. While maternally-expressed imprinted genes preferentially overlap with MDR1 demethylated regions, the majority of genes that overlap demethylated regions are not imprinted. Double mutant megagametophytes lacking both MDR1 and its close homolog DNG102 result in early seed failure, and double mutant microgametophytes fail pre-fertilization. These data establish DNA demethylation by glycosylases as essential in maize endosperm and pollen and suggest that neither transposon repression nor genomic imprinting are its main function in endosperm. Decreased cell stiffness facilitates detachment and migration of breast cancer cells in 3D collagen matrices: An exploratory study BackgroundTumour-cell detachment is a critical early event in the metastatic cascade. However, the role of the cells mechanical properties in detachment and migration is not well understood. This exploratory study aimed to assess how intracellular stiffness changes these processes.

MethodsMDA-MB-231 cells were embedded as 10,000-cell spheroids in 2 and 4 mg/ml collagen matrices. Intracellular stiffness was assessed with mitochondria tracking microrheology of cells that migrated distances equivalent to four and six times the cell diameter (dC) from the spheroid and compared to cells at the spheroid surface (0dC), representing medium, high and no migration, respectively.

Results and discussionThe mitochondrial mean square displacement and intracellular stiffness decreased during detachment and migration for both collagen concentrations (i.e. rigidities). The mean square displacement of 4dC and 6dC cells was similar, whereas cell stiffness was lower for 4dC than for 6dC cells. With increasing matrix rigidity, the intracellular stiffness decreased for 0dC cells and did not change for 4dC and 6dC cells. It is proposed that decreased cell stiffness drives detachment and migration and increased matrix rigidity physically hinders migration, and cells need to become softer or remodel the environment to migrate. The independence of the stiffness of migrated cells from matrix rigidity suggests that cells remodel their environment through matrix proteins cleavage to migrate.

ConclusionsThe study revealed the collective effects of enhanced migratory conditions and increased matrix rigidity on the mechanical properties of the cells. The expression of matrix metalloproteinases and transforming growth factor {beta} and the role of cell volume on detachment and migration in matrices with varying pore sizes are proposed targets for further studies on metastatic cancer cells. HaloTag9: an engineered protein tag to improve fluorophore performance HaloTag9 is an engineered variant of HaloTag7 with up to 40% higher brightness and increased fluorescence lifetime when labeled with fluorogenic rhodamines. Moreover, combining HaloTag9 with HaloTag7 and other fluorescent probes enabled live-cell multiplexing using a single fluorophore and the generation of a fluorescence lifetime-based biosensor. The increased brightness of HaloTag9 and its use in fluorescence lifetime multiplexing makes it a powerful tool for live-cell imaging. Embedded 3D printing in self-healing annealable composites for precise patterning of functionally mature human neural constructs Human in vitro models of neural tissue with controllable cellular identity, tunable microenvironment, and defined spatial arrangement are needed to facilitate studies of brain development and disease. Towards this end, embedded printing in jammed microgel supports (i.e., granular gels) holds great promise as it allows precise and programmable patterning of extremely soft and compliant tissue constructs. However, in contrast to the vast material landscape available for bulk hydrogels, granular printing support formulations are restricted to a handful of materials without the ability for facile adjustment of biofunctional properties of the cellular microenvironment. Therefore, there has been a need for novel materials that take advantage of versatile biomimicry of bulk hydrogels while providing high-fidelity support for embedded printing akin to granular gels. To address this need, we present a modular platform for bioengineering of neuronal networks via direct embedded 3D printing of human stem cells inside Self-Healing Annealable Particle-Extracellular matrix (SHAPE) composites. SHAPE composites consist of soft microgels immersed in viscous extracellular-matrix solution to enable precise freeform patterning of human stem cells and consequent generation and long-term maintenance of mature subtype-specific neurons that extend projections within the volume of the annealed support. The developed approach further allows multi-ink deposition, live spatial and temporal monitoring of oxygen levels, as well as creation of vascular channels. Due to its modularity, SHAPE biomanufacturing toolbox not only offers a solution for functional modeling of mechanically sensitive neural constructs, but also has potential to be applied to a wide range of biomaterials with different crosslinking mechanisms to model tissues and diseases where recapitulation of complex architectural features and topological cues is essential. Simulation of foraging behavior using a decision-making agent with Bayesian and inverse Bayesian inference: Temporal correlations and power laws in displacement patterns It has been stated that in human migratory behavior, the step length series may have temporal correlation and that there is some relationship between this time dependency and the fact that the frequency distribution of step length follows a power-law distribution. Furthermore, the frequency of occurrence of the step length in some large marine organisms has been found to switch between power-law and exponential distributions, depending on the difficulty of prey acquisition. However, to date it has not been clarified how the aforementioned three phenomena arise: the positive correlation created in the step length series, the relation between the positive correlation of the step length series and the form of an individuals step length distribution, and the switching between power-law and exponential distributions depending on the abundance of prey. This study simulated foraging behavior using the Bayesian decision-making agent simultaneously performing both knowledge learning and knowledge-based inference to analyze how the aforementioned three phenomena arise. In the agent with learning and inference, past experiences were stored as hypotheses (knowledge) and they were used in current foraging behavior; at the same time, the hypothesis continued to be updated based on new experiences. The simulation results show that the agent with both learning and inference has a mechanism that simultaneously causes all the phenomena. Synthetic Cooling Agents in US-marketed E-cigarette Refill Liquids and Popular Disposable E-cigarettes: Chemical Analysis and Risk Assessment. BackgroundMenthol, through its cooling and pleasant sensory effects, facilitates smoking and tobacco product initiation, resulting in the high popularity of mint/menthol-flavored E-cigarettes. More recently, E-cigarette vendors started marketing synthetic cooling agents as additives that impart a cooling effect but lack a characteristic minty odor. Knowledge about content of synthetic coolants in US-marketed E-cigarette products and associated health risks is limited.

MethodsE-liquid vendor sites were searched with the terms "koolada", "kool/cool", "ice", or WS-3/WS-23, denoting individual cooling agents, and relevant refill E-liquids were purchased. "Ice" flavor varieties of Puffbar, the most popular disposable E-cigarette brand, were compared with non-"Ice" varieties. E-liquids were characterized, and synthetic coolants quantified using GC/MS. Margin of exposure (MOE), a risk assessment parameter, was calculated to assess the risk associated with synthetic coolant exposure from E-cigarette use.

ResultsWS-3 was detected in 24/25 refill E-liquids analyzed. All Puffbar flavor varieties contained either WS-23 (13/14) or WS-3 (5/14), in both "Ice"- and non-"Ice" flavors. Modeling consumption of WS-3 from vaped E-liquids, resulted in MOEs below the safe margin of 100 for most daily use scenarios. MOEs for WS-23 were <100 for 10/13 Puffbar flavors in all use scenarios. Puffbar power specifications are identical to Juul devices.

ConclusionsSynthetic cooling agents (WS-3/WS-23) were present in US-marketed E-cigarettes, at levels that may result in consumer exposures exceeding safety thresholds set by regulatory agencies. Synthetic coolants are not only found in mint-or menthol-flavored products, but also in fruit- and candy-flavored products, including popular disposable E-cigarette products such as Puffbar.

ImplicationsSynthetic cooling agents are widely used in "kool/cool"- and "ice"-flavored E-liquids and in E-liquids without these labels, both as a potential replacement for menthol or to add cooling  notes to non-menthol flavors. These agents may be used to bypass current and future regulatory limits on menthol content in tobacco products, and not just E-cigarettes. Since synthetic cooling agents are odorless, they may not fall under the category of "characterizing flavor", potentially circumventing regulatory measures based on this concept. Regulators need to consider the additional health risks associated with exposure to synthetic cooling agents. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. Antibody Resistance of SARS-CoV-2 Variants B.1.351 and B.1.1.7 The COVID-19 pandemic has ravaged the globe, and its causative agent, SARS-CoV-2, continues to rage. Prospects of ending this pandemic rest on the development of effective interventions. Single and combination monoclonal antibody (mAb) therapeutics have received emergency use authorization1-3, with more in the pipeline4-7. Furthermore, multiple vaccine constructs have shown promise8, including two with ~95% protective efficacy against COVID-199,10. However, these interventions were directed toward the initial SARS-CoV-2 that emerged in 2019. The recent emergence of new SARS-CoV-2 variants B.1.1.7 in the UK11 and B.1.351 in South Africa12 is of concern because of their purported ease of transmission and extensive mutations in the spike protein. We now report that B.1.1.7 is refractory to neutralization by most mAbs to the N-terminal domain (NTD) of spike and relatively resistant to a few mAbs to the receptor-binding domain (RBD). It is not more resistant to convalescent plasma or vaccinee sera. Findings on B.1.351 are more worrisome in that this variant is not only refractory to neutralization by most NTD mAbs but also by multiple individual mAbs to the receptor-binding motif on RBD, largely due to an E484K mutation. Moreover, B.1.351 is markedly more resistant to neutralization by convalescent plasma (9.4 fold) and vaccinee sera (10.3-12.4 fold). B.1.351 and emergent variants13,14 with similar spike mutations present new challenges for mAb therapy and threaten the protective efficacy of current vaccines. SENIES: DNA Shape Enhanced Two-layer Deep Learning Predictor for the Identification of Enhancers and Their Strength The identification of enhancers has always been an important task in bioinformatics owing to their major role in regulating gene expression. For this reason, many computational algorithms devoted to enhancer identification have been put forward over the years. To boost the performance of their methods, more features are extracted from the single DNA sequences and integrated to develop an ensemble classifier. Nevertheless, the sequence-derived features used in previous studies can hardly provide the 3D structure information of DNA sequences, which is regarded as an important factor affecting the binding preferences of transcription factors to regulatory elements like enhancers. Given that, we here propose SENIES, a DNA shape enhanced deep learning predictor, for the identification of enhancers and their strength. The predictor consists of two layers where the first layer is for enhancer and non-enhancer identification, and the second layer is for predicting the strength of enhancers. Besides utilizing two common sequence-derived features (i.e. one-hot and k-mer) as input, it introduces DNA shape for describing the 3D structures of DNA sequences. Performance comparison with state-of-the-art methods conducted on the same datasets demonstrates the effectiveness and robustness of our method. The code implementation of our predictor is publicly available at https://github.com/hlju-liye/SENIES. SufB intein splicing in Mycobacterium tuberculosis is influenced by two remote conserved N-extein Histidines Inteins are auto-processing domains that implement a multi-step biochemical reaction termed protein splicing, marked by cleavage and formation of peptide bonds. They excise from a precursor protein, generating a functional protein via covalent bonding of flanking exteins. We report the kinetic study of splicing and cleavage reaction in [Fe-S] cluster assembly protein SufB from Mycobacterium tuberculosis. Although it follows a canonical intein splicing pathway, distinct features are added by extein residues present in the active site. Sequence analysis identified two conserved histidines in the N-extein region; His-5 and His-38. Kinetic analyses of His-5Ala and His-38Ala SufB mutants exhibited significant reductions in splicing and cleavage rates relative to the SufB wild-type precursor protein. Structural analysis and molecular dynamics simulations suggested that Mtu SufB displays a unique mechanism where two remote histidines work concurrently to facilitate N-terminal cleavage reaction. His-38 is stabilized by the solvent-exposed His-5, and can impact N-S acyl shift by direct interaction with the catalytic Cys1. Development of inteins as biotechnological tools or as pathogen specific novel antimicrobial targets requires a more complete understanding of such unexpected roles of conserved extein residues in protein splicing. 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. Can fMRI reveal the representation of syntactic structure in the brain? While studying semantics in the brain, neuroscientists use two approaches. One is to identify areas that are correlated with semantic processing load. Another is to find areas that are predicted by the semantic representation of the stimulus words. However, in the domain of syntax, most studies have focused only on identifying areas correlated with syntactic processing load. One possible reason for this discrepancy is that representing syntactic structure in an embedding space such that it can be used to model brain activity is a non-trivial computational problem. Another possible reason is that it is unclear if the low signal-to-noise ratio of neuroimaging tools such as functional Magnetic Resonance Imaging (fMRI) can allow us to reveal correlates of complex (and perhaps subtle) syntactic representations. In this study, we propose novel multi-dimensional features that encode information about the syntactic structure of sentences. Using these features and fMRI recordings of participants reading a natural text, we model the brain representation of syntax. First, we find that our syntactic structure-based features explain additional variance in the brain activity of various parts of the language system, even after controlling for complexity metrics that capture processing load. At the same time, we see that regions well-predicted by syntactic features are distributed in the language system and are not distinguishable from those processing semantics. A novel Fiji/ImageJ plugin for the rapid analysis of blebbing cells When confined, cells have recently been shown to undergo a phenotypic switch to what has been termed, fast amoeboid (leader bleb-based) migration. However, as this is a nascent area of research, few tools are available for the rapid analysis of cell behavior. Here, we demonstrate that a novel Fiji/ImageJ-based plugin, Analyze_Blebs, can be used to quickly obtain cell migration parameters and morphometrics from time lapse images. As validation, we show that Analyze_Blebs can detect significant differences in cell migration and morphometrics, such as the largest bleb size, upon introducing different live markers of F-actin, including F-tractin and LifeAct tagged with green and red fluorescent proteins. We also demonstrate, using flow cytometry, that live markers increase total levels of F-actin. Furthermore, that F-tractin increases cell stiffness, which was found to correlate with a decrease in migration, thus reaffirming the importance of cell mechanics as a determinant of Leader Bleb-Based Migration (LBBM).

Highlight summaryA new plugin, Analyze_Blebs, enables the rapid analysis of cell migration and morphometrics of fast amoeboid cells. Morphometrics combined with cell stiffness are found to be predictive of confined, fast amoeboid (leader bleb-based), migration. Enrichment analyses identify shared associations for 25 quantitative traits in over 600,000 individuals from seven diverse ancestries Since 2005, genome-wide association (GWA) datasets have been largely biased toward sampling European ancestry individuals, and recent studies have shown that GWA results estimated from self-identified European individuals are not transferable to non-European individuals due to various confounding challenges. Here, we demonstrate that enrichment analyses which aggregate SNP-level association statistics at multiple genomic scales--from genes to genomic regions and pathways--have been underutilized in the GWA era and can generate biologically interpretable hypotheses regarding the genetic basis of complex trait architecture. We illustrate examples of the robust associations generated by enrichment analyses while studying 25 continuous traits assayed in 566,786 individuals from seven diverse self-identified human ancestries in the UK Biobank and the Biobank Japan, as well as 44,348 admixed individuals from the PAGE consortium including cohorts of African-American, Hispanic and Latin American, Native Hawaiian, and American Indian/Alaska Native individuals. We identify 1,000 gene-level associations that are genome-wide significant in at least two ancestry cohorts across these 25 traits, as well as highly conserved pathway associations with triglyceride levels in European, East Asian, and Native Hawaiian cohorts. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Phenotypic Heterogeneity Facilitates Survival While Hindering the Evolution of Drug Resistance Due to Intraspecific Competition Rising rates of resistance to antimicrobial drugs threatens the effective treatment of infections across the globe. Drug resistance has been established to emerge from non-genetic mechanisms, such as "persistence" in quiescent microbes and fluctuations in gene expression in actively replicating cells, as well as from genetic mutations. However, it is still unclear how non-genetic drug resistance affects the evolution of genetic drug resistance. We develop deterministic and stochastic population models that incorporate resource competition to quantitatively investigate the transition from non-genetic to genetic resistance during the exposure to static and cidal drugs. We find that non-genetic resistance facilitates the survival of cell populations during drug treatment, but that it hinders the development of genetic resistance due to the competition between the non-genetically and genetically resistant subpopulations. Non-genetic drug resistance in the presence of subpopulation competition is found to increase the first-appearance and fixation times of drug resistance mutations, while increasing the probability of mutation before population extinction during cidal drug treatment. Intense intraspecific competition during drug treatment leads to extinction of the susceptible and non-genetically resistant subpopulations. These findings advance our fundamental understanding of the evolution of drug resistance and may guide novel treatment strategies for patients with drug-resistant infections.

SIGNIFICANCEDrug resistance is predicted to kill as many as 10 million people per year and cost over 100 trillion USD in cumulative lost production globally by 2050. To mitigate these socio-economic costs, we need to fundamentally understand the drug resistance process. We investigate the effect that different forms of resistance have on the evolution of drug resistance using mathematical modeling and computer simulations. We find that the presence of non-genetically drug-resistant cells (whose resistance is temporary and not encoded in a genetic mutation) allows the population to survive drug treatment, while competition between these subpopoulations simultaneously slows down the evolution of permanent genetic drug resistance and in some cases drives them extinct. These findings have important implications for advancing evolutionary theory and for developing effective "resistance-proof" treatments. Preprints in motion: tracking changes between preprint posting and journal publication during a pandemic Amidst the COVID-19 pandemic, preprints in the biomedical sciences are being posted and accessed at unprecedented rates, drawing widespread attention from the general public, press and policymakers for the first time. This phenomenon has sharpened longstanding questions about the reliability of information shared prior to journal peer review. Does the information shared in preprints typically withstand the scrutiny of peer review, or are conclusions likely to change in the version of record? We assessed preprints from bioRxiv and medRxiv that had been posted and subsequently published in a journal through 30th April 2020, representing the initial phase of the pandemic response. We utilised a combination of automatic and manual annotations to quantify how an article changed between the preprinted and published version. We found that the total number of figure panels and tables changed little between preprint and published articles. Moreover, the conclusions of 7.2% of non-COVID-19-related and 17.2% of COVID-19-related abstracts undergo a discrete change by the time of publication, but the majority of these changes do not qualitatively change the conclusions of the paper. New insights into tomato CLE peptide repertoire and perception mechanisms Precision in sensing the environmental cues and adjusting the growth and the physiology of the root system are necessary for plant robustness. Plants achieve their phenotypic plasticity by tightly controlling and buffering developmental decisions. In addition to the classical plant hormones that mediate plant development and stress responses, the CLE peptides constitute an additional crucial level of regulation. While the CLV3-CLV1 module appears to be highly conserved to control the proliferation of the shoot apical meristem stem cells, we do not yet fully understand the function of the additional CLE genes and whether they act in a similar way across the plant species, including tomato. Due to the small gene size and high sequence variability, it is extremely difficult to precisely annotate CLE genes in plant genomes. Here we present our analysis of the CLE family in tomato, based on a combination of iterative tBLASTn and Hidden-Markov-Model (HMM), which allowed us to identify thirty-seven new SlCLEs in addition to the fifteen reported previously. We could confirm the biological activities of selected SlCLEs in suppressing root meristematic cell divisions. We show that root response is mediated by SlCLAVATA2, indicating the conservation of CLE perception mechanism.

One-sentence summaryUsing a combination of iterative tBLASTn and Hidden-Markov-Model approaches, we uncovered 37 new tomato CLE genes predominantly expressed in roots, and we showed a conserved effect on root meristem arrest, that was SlCLAVATA2-dependent.

HighlightsO_LIWe applied a combined approach of iterative tBLASTn and Hidden-Markov-Model to identify fifty-two tomato SlCLE genes, including thirty-seven new genes
C_LIO_LIAll identified genes encode for pre-propeptides with a single CLE-domain containing conserved residues similar to Arabidopsis
C_LIO_LIAnalyzing the publicly available RNAseq datasets, we could confirm the expression of SlCLE genes that was often associated specifically with root or shoot, a certain developmental stage of the fruit, or with drought stress conditions
C_LIO_LIRemarkably, the majority of SlCLE genes are predominantly expressed in the root tissues
C_LIO_LIWe showed the conserved inhibitory effect on the root meristem and columella cells division for the selected SlCLE peptides that were SlCLAVATA2-dependent.
C_LI Network Inference from Perturbation Time Course Data Networks underlie much of biology from subcellular to ecological scales. Yet, understanding what experimental data are needed and how to use them for unambiguously identifying the structure of even small networks remains a broad challenge. Here, we integrate a dynamic least squares framework into established modular response analysis (DL-MRA), that specifies sufficient experimental perturbation time course data to robustly infer arbitrary two and three node networks. DL-MRA considers important network properties that current methods often struggle to capture: (i) edge sign and directionality; (ii) cycles with feedback or feedforward loops including self-regulation; (iii) dynamic network behavior; (iv) edges external to the network; and (v) robust performance with experimental noise. We evaluate the performance of and the extent to which the approach applies to cell state transition networks, intracellular signaling networks, and gene regulatory networks. Although signaling networks are often an application of network reconstruction methods, the results suggest that only under quite restricted conditions can they be robustly inferred. For gene regulatory networks, the results suggest that incomplete knockdown is often more informative than full knockout perturbation, which may change experimental strategies for gene regulatory network reconstruction. Overall, the results give a rational basis to experimental data requirements for network reconstruction and can be applied to any such problem where perturbation time course experiments are possible. Analysis of diverse eukaryotes suggests the existence of an ancestral 1 mitochondrial apparatus derived from the bacterial type II secretion system The type 2 secretion system (T2SS) is present in some Gram-negative eubacteria and used to secrete proteins across the outer membrane. Here we report that certain representative heteroloboseans, jakobids, malawimonads and hemimastigotes unexpectedly possess homologues of core T2SS components. We show that at least some of them are present in mitochondria, and their behaviour in biochemical assays is consistent with the presence of a mitochondrial T2SS-derived system (miT2SS). We additionally identified 23 protein families co-occurring with miT2SS in eukaryotes. Seven of these proteins could be directly linked to the core miT2SS by functional data and/or sequence features, whereas others may represent different parts of a broader functional pathway, possibly also involving the peroxisome. Its distribution in eukaryotes and phylogenetic evidence together indicate that the miT2SS-centred pathway is an ancestral eukaryotic trait. Our findings thus have direct implications for the functional properties of the early mitochondrion. N-glycan chitobiose core biosynthesis by Agl24 strengthens the hypothesis of an archaeal origin of the eukaryal N-glycosylation Protein N-glycosylation is the most common posttranslational modifications found in all three domains of life. The crenarchaeal N-glycosylation begins with the synthesis of a lipid-linked chitobiose core structure, identical to that in eukaryotes. Here, we report the identification of a thermostable archaeal beta-1,4-N-acetylglucosaminyltransferase, named archaeal glycosylation enzyme 24 (Agl24), responsible for the synthesis of the N-glycan chitobiose core. Biochemical characterization confirmed the function as an inverting {beta}-D-GlcNAc-(1[-&gt;]4)--D-GlcNAc-diphosphodolichol glycosyltransferase. Substitution of a conserved histidine residue, found also in the eukaryotic and bacterial homologs, demonstrated its functional importance for Agl24. Furthermore, bioinformatics and structural modeling revealed strong similarities between Agl24 and both the eukaryotic Alg14/13 and a distant relation to the bacterial MurG, which catalyze the identical or a similar process, respectively. Our data, complemented by phylogenetic analysis of Alg13 and Alg14, revealed similar sequences in Asgardarchaeota, further supporting the hypothesis that the Alg13/14 homologs in eukaryotes have been acquired during eukaryogenesis.

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/427365v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@13d1ffdorg.highwire.dtl.DTLVardef@1ff48d0org.highwire.dtl.DTLVardef@1056e75org.highwire.dtl.DTLVardef@196ff58_HPS_FORMAT_FIGEXP  M_FIG C_FIG HighlightsO_LIFirst identification and characterization of a thermostable {beta}-D-GlcNAc-(1[-&gt;]4)--D-GlcNAc-diphosphodolichol glycosyltransferase (GT family 28) in Archaea.
C_LIO_LIA highly conserved histidine, within a GGH motif in Agl24, Alg14, and MurG, is essential for function of Agl24.
C_LIO_LIAgl24-like homologs are broadly distributed among Archaea.
C_LIO_LIThe eukaryotic Alg13 and Alg14 are closely related to the Asgard homologs, suggesting their acquisition during eukaryogenesis.
C_LI Quantifying the potential for red blood cell β-adrenergic sodium-proton exchangers to protect oxygen transport in hypoxic and hypercapnic white seabass White seabass (Atractoscion nobilis) are increasingly experiencing periods of low oxygen (O2; hypoxia) and high carbon dioxide (CO2, hypercapnia) due to climate change and eutrophication of the coastal waters of California. Hemoglobin (Hb) is the principal O2 carrier in the blood and in many teleost fishes Hb-O2 binding is compromised at low pH; however, the red blood cells (RBC) of some species regulate intracellular pH with adrenergically-stimulated sodium-proton-exchangers ({beta}-NHE). We hypothesized that RBC {beta}-NHEs in white seabass are an important mechanism that can protect the blood O2-carrying capacity during hypoxia and hypercapnia. We determined the O2-binding characteristics of white seabass blood, the response of RBCs to adrenergic stimulation, and quantified the protective effect of {beta}-NHE activity on Hb-O2 saturation. White seabass had typical teleost Hb characteristics, with a moderate O2 affinity (PO2 at half-saturation; P50 2.9 kPa) that was highly pH-sensitive (Bohr coefficient -0.92; Root effect 52%). The presence of RBC {beta}-NHEs was confirmed by functional, molecular and bioinformatic data and super-resolution imaging revealed, for the first time, the subcellular location of {beta}-NHE protein in vesicle-like structures and on the RBC membrane, and its translocation after adrenergic stimulation. The activation of RBC {beta}-NHEs increased Hb-O2 saturation by [~]8% in normoxia at 1 kPa PCO2, and by up to 20% in hypoxia. Our results confirm that RBC {beta}-NHE activity in white seabass has great potential to protect arterial O2 transport in environmentally relevant conditions of hypoxia and hypercapnia, but also reveal a potential vulnerability of fish to combinations of these stressors. Feedforward regulatory logic underlies robustness of the specification-to-differentiation transition and fidelity of terminal cell fate during C. elegans endoderm development Development is driven by gene regulatory networks (GRNs) that progressively dictate specification and differentiation of cell fates. The architecture of GRNs directly determines the specificity and accuracy of developmental outcomes. We report here that the core regulatory circuitry for endoderm development in C. elegans is comprised of a recursive series of interlocked feedforward modules linking a cascade of six sequentially expressed GATA-type transcription factors. This structure results in a reiterated sequential redundancy, in which removal of a single factor or alternate factors in the cascade results in no, or a mild, effect on endoderm development and gut differentiation, while elimination of any two factors that are sequentially deployed in the cascade invariably results in a strong phenotype. The strength of the observed phenotypes is successfully predicted by a computational model based on the timing and levels of transcriptional states. The feedforward regulatory logic in the GRN appears to ensure timely onset of terminal differentiation genes and allows rapid and robust lockdown of cell fate during early embryogenesis. We further found that specification-to-differentiation transition is linked through a common regulator, the END-1 GATA factor that straddles the two processes. Finally, we revealed roles for key GATA factors in establishing spatial regulatory state domains by acting as transcriptional repressors that appear to define the boundaries of the digestive tract. Our findings support a comprehensive model of the core gene network that describes how robust endoderm development is achieved during C. elegans embryogenesis.

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